Articles | Volume 15, issue 11
https://doi.org/10.5194/essd-15-4901-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-4901-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
02 Nov 2023
Data description paper |
| 02 Nov 2023
| 02 Nov 2023
CLARA-A3: The third edition of the AVHRR-based CM SAF climate data record on clouds, radiation and surface albedo covering the period 1979 to 2023
Karl-Göran Karlsson
CORRESPONDING AUTHOR
Meteorological Research Unit, Research and Development Department, The Swedish Meteorological and Hydrological Institute (SMHI), Folkborgsvägen 17, 602 10 Norrköping, Sweden
Martin Stengel
Satellite-Based Climate Monitoring, Deutscher Wetterdienst, Frankfurter Str. 135, 63067 Offenbach am Main, Germany
Jan Fokke Meirink
R&D Satellite Observations, Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3731 GA De Bilt, the Netherlands
Aku Riihelä
Meteorological Research, Finnish Meteorological Institute, Helsinki, 00101, Finland
Jörg Trentmann
Satellite-Based Climate Monitoring, Deutscher Wetterdienst, Frankfurter Str. 135, 63067 Offenbach am Main, Germany
Tom Akkermans
Remote Sensing from Space, Royal Meteorological Institute of Belgium, 1180 Brussels, Belgium
Diana Stein
Satellite-Based Climate Monitoring, Deutscher Wetterdienst, Frankfurter Str. 135, 63067 Offenbach am Main, Germany
Abhay Devasthale
Meteorological Research Unit, Research and Development Department, The Swedish Meteorological and Hydrological Institute (SMHI), Folkborgsvägen 17, 602 10 Norrköping, Sweden
Salomon Eliasson
Meteorological Research Unit, Research and Development Department, The Swedish Meteorological and Hydrological Institute (SMHI), Folkborgsvägen 17, 602 10 Norrköping, Sweden
Erik Johansson
Meteorological Research Unit, Research and Development Department, The Swedish Meteorological and Hydrological Institute (SMHI), Folkborgsvägen 17, 602 10 Norrköping, Sweden
Nina Håkansson
Meteorological Research Unit, Research and Development Department, The Swedish Meteorological and Hydrological Institute (SMHI), Folkborgsvägen 17, 602 10 Norrköping, Sweden
Irina Solodovnik
Satellite-Based Climate Monitoring, Deutscher Wetterdienst, Frankfurter Str. 135, 63067 Offenbach am Main, Germany
Nikos Benas
R&D Satellite Observations, Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3731 GA De Bilt, the Netherlands
Nicolas Clerbaux
Remote Sensing from Space, Royal Meteorological Institute of Belgium, 1180 Brussels, Belgium
Nathalie Selbach
Satellite-Based Climate Monitoring, Deutscher Wetterdienst, Frankfurter Str. 135, 63067 Offenbach am Main, Germany
Marc Schröder
Satellite-Based Climate Monitoring, Deutscher Wetterdienst, Frankfurter Str. 135, 63067 Offenbach am Main, Germany
Rainer Hollmann
Satellite-Based Climate Monitoring, Deutscher Wetterdienst, Frankfurter Str. 135, 63067 Offenbach am Main, Germany
Related authors
Nikos Benas, Irina Solodovnik, Martin Stengel, Imke Hüser, Karl-Göran Karlsson, Nina Håkansson, Erik Johansson, Salomon Eliasson, Marc Schröder, Rainer Hollmann, and Jan Fokke Meirink
Earth Syst. Sci. Data, 15, 5153–5170, https://doi.org/10.5194/essd-15-5153-2023, https://doi.org/10.5194/essd-15-5153-2023, 2023
Short summary
Short summary
This paper describes CLAAS-3, the third edition of the Cloud property dAtAset using SEVIRI, which was created based on observations from geostationary Meteosat satellites. CLAAS-3 cloud properties are evaluated using a variety of reference datasets, with very good overall results. The demonstrated quality of CLAAS-3 ensures its usefulness in a wide range of applications, including studies of local- to continental-scale cloud processes and evaluation of climate models.
Terhikki Manninen, Emmihenna Jääskeläinen, Niilo Siljamo, Aku Riihelä, and Karl-Göran Karlsson
Atmos. Meas. Tech., 15, 879–893, https://doi.org/10.5194/amt-15-879-2022, https://doi.org/10.5194/amt-15-879-2022, 2022
Short summary
Short summary
A new method for cloud-correcting observations of surface albedo is presented for AVHRR data. Instead of a binary cloud mask, it applies cloud probability values smaller than 20% of the A3 edition of the CLARA (CM SAF cLoud, Albedo and surface Radiation dataset from AVHRR data) record provided by the Satellite Application Facility on Climate Monitoring (CM SAF) project of EUMETSAT. According to simulations, the 90% quantile was 1.1% for the absolute albedo error and 2.2% for the relative error.
Salomon Eliasson, Karl-Göran Karlsson, and Ulrika Willén
Geosci. Model Dev., 13, 297–314, https://doi.org/10.5194/gmd-13-297-2020, https://doi.org/10.5194/gmd-13-297-2020, 2020
Short summary
Short summary
This paper describes a new satellite simulator. Its purpose is to simulate the CLARA-A2 climate data record from a climate model atmosphere. We explain how the simulator takes into account the regionally variable cloud detection skill of the observations. The simulator makes use of the long/lat-gridded validation between CLARA-A2 and the CALIOP satellite-borne lidar dataset. Using the EC-Earth climate model, we show a sizable impact on climate model validation, especially at high latitudes.
Nikos Benas, Jan Fokke Meirink, Karl-Göran Karlsson, Martin Stengel, and Piet Stammes
Atmos. Chem. Phys., 20, 457–474, https://doi.org/10.5194/acp-20-457-2020, https://doi.org/10.5194/acp-20-457-2020, 2020
Short summary
Short summary
In this study we analyse aerosol and cloud changes over southern China from 2006 to 2015 and investigate their possible interaction mechanisms. Results show decreasing aerosol loads and increasing liquid cloud cover in late autumn. Further analysis based on various satellite data sets shows consistency with the aerosol semi-direct effect, whereby less absorbing aerosols in the cloud layer would lead to an overall decrease in the evaporation of cloud droplets, thus increasing cloud amount.
Salomon Eliasson, Karl Göran Karlsson, Erik van Meijgaard, Jan Fokke Meirink, Martin Stengel, and Ulrika Willén
Geosci. Model Dev., 12, 829–847, https://doi.org/10.5194/gmd-12-829-2019, https://doi.org/10.5194/gmd-12-829-2019, 2019
Short summary
Short summary
To enable fair comparisons of clouds between climate models and the
ESA Cloud_cci climate data record (CDR), we present a tool called the
Cloud_cci simulator. The tool takes into account the geometry and
cloud detection capabilities of the Cloud_cci CDR to allow fair
comparisons. We demonstrate the simulator on two climate models. We
find the impact of time sampling has a large effect on simulated cloud
water amount and that the simulator reduces the cloud cover by about
10 % globally.
Nikos Benas, Jan Fokke Meirink, Karl-Göran Karlsson, Martin Stengel, and Piet Stammes
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-554, https://doi.org/10.5194/acp-2018-554, 2018
Preprint withdrawn
Short summary
Short summary
In this study we analyse aerosol and cloud changes over South China and investigate their possible interactions. The results show decreasing aerosol loads and increasing liquid clouds. Further analysis of these changes based on various satellite data sets show consistency with the aerosol semi-direct effect, whereby less absorbing aerosols in the cloud layer would lead to an overall decrease in evaporation of cloud droplets, thus increasing cloud amount and cover.
Karl-Göran Karlsson and Nina Håkansson
Atmos. Meas. Tech., 11, 633–649, https://doi.org/10.5194/amt-11-633-2018, https://doi.org/10.5194/amt-11-633-2018, 2018
Short summary
Short summary
Data from the high-sensitivity CALIOP cloud lidar onboard the CALIPSO satellite have been used to evaluate cloud amounts estimated from satellite imagery and, specifically, from the climate data record CLARA-A2. The main purpose has been to study the limit of how thin clouds that can be detected efficiently (i.e., detected at the 50 % level) in CLARA-A2 data and how this limit varies globally. The study revealed very large geographical differences in the cloud detection efficiency.
Martin Stengel, Stefan Stapelberg, Oliver Sus, Cornelia Schlundt, Caroline Poulsen, Gareth Thomas, Matthew Christensen, Cintia Carbajal Henken, Rene Preusker, Jürgen Fischer, Abhay Devasthale, Ulrika Willén, Karl-Göran Karlsson, Gregory R. McGarragh, Simon Proud, Adam C. Povey, Roy G. Grainger, Jan Fokke Meirink, Artem Feofilov, Ralf Bennartz, Jedrzej S. Bojanowski, and Rainer Hollmann
Earth Syst. Sci. Data, 9, 881–904, https://doi.org/10.5194/essd-9-881-2017, https://doi.org/10.5194/essd-9-881-2017, 2017
Short summary
Short summary
We present new cloud property datasets based on measurements from the passive imaging satellite sensors AVHRR, MODIS, ATSR2, AATSR and MERIS. Retrieval systems were developed that include cloud detection and cloud typing followed by optimal estimation retrievals of cloud properties (e.g. cloud-top pressure, effective radius, optical thickness, water path). Special features of all datasets are spectral consistency and rigorous uncertainty propagation from pixel-level data to monthly properties.
Karl-Göran Karlsson, Kati Anttila, Jörg Trentmann, Martin Stengel, Jan Fokke Meirink, Abhay Devasthale, Timo Hanschmann, Steffen Kothe, Emmihenna Jääskeläinen, Joseph Sedlar, Nikos Benas, Gerd-Jan van Zadelhoff, Cornelia Schlundt, Diana Stein, Stefan Finkensieper, Nina Håkansson, and Rainer Hollmann
Atmos. Chem. Phys., 17, 5809–5828, https://doi.org/10.5194/acp-17-5809-2017, https://doi.org/10.5194/acp-17-5809-2017, 2017
Short summary
Short summary
The paper presents the second version of a global climate data record based on satellite measurements from polar orbiting weather satellites. It describes the global evolution of cloudiness, surface albedo and surface radiation during the time period 1982–2015. The main improvements of algorithms are described together with some validation results. In addition, some early analysis is presented of some particularly interesting climate features (Arctic albedo and cloudiness + global cloudiness).
T. Koenigk, A. Devasthale, and K.-G. Karlsson
Atmos. Chem. Phys., 14, 1987–1998, https://doi.org/10.5194/acp-14-1987-2014, https://doi.org/10.5194/acp-14-1987-2014, 2014
K.-G. Karlsson, A. Riihelä, R. Müller, J. F. Meirink, J. Sedlar, M. Stengel, M. Lockhoff, J. Trentmann, F. Kaspar, R. Hollmann, and E. Wolters
Atmos. Chem. Phys., 13, 5351–5367, https://doi.org/10.5194/acp-13-5351-2013, https://doi.org/10.5194/acp-13-5351-2013, 2013
K.-G. Karlsson and E. Johansson
Atmos. Meas. Tech., 6, 1271–1286, https://doi.org/10.5194/amt-6-1271-2013, https://doi.org/10.5194/amt-6-1271-2013, 2013
William K. Jones, Martin Stengel, and Philip Stier
Atmos. Chem. Phys., 24, 5165–5180, https://doi.org/10.5194/acp-24-5165-2024, https://doi.org/10.5194/acp-24-5165-2024, 2024
Short summary
Short summary
Storm clouds cover large areas of the tropics. These clouds both reflect incoming sunlight and trap heat from the atmosphere below, regulating the temperature of the tropics. Over land, storm clouds occur in the late afternoon and evening and so exist both during the daytime and at night. Changes in this timing could upset the balance of the respective cooling and heating effects of these clouds. We find that isolated storms have a larger effect on this balance than their small size suggests.
Nicole Docter, Anja Hünerbein, David P. Donovan, Rene Preusker, Jürgen Fischer, Jan Fokke Meirink, Piet Stammes, and Michael Eisinger
Atmos. Meas. Tech., 17, 2507–2519, https://doi.org/10.5194/amt-17-2507-2024, https://doi.org/10.5194/amt-17-2507-2024, 2024
Short summary
Short summary
MSI is the imaging spectrometer on board EarthCARE and will provide across-track information on clouds and aerosol properties. The MSI solar channels exhibit a spectral misalignment effect (SMILE) in the measurements. This paper describes and evaluates how the SMILE will affect the cloud and aerosol retrievals that do not account for it.
Alejandro Baró Pérez, Michael S. Diamond, Frida A.-M. Bender, Abhay Devasthale, Matthias Schwarz, Julien Savre, Juha Tonttila, Harri Kokkola, Hyunho Lee, David Painemal, and Annica M. L. Ekman
Atmos. Chem. Phys., 24, 4591–4610, https://doi.org/10.5194/acp-24-4591-2024, https://doi.org/10.5194/acp-24-4591-2024, 2024
Short summary
Short summary
We use a numerical model to study interactions between humid light-absorbing aerosol plumes, clouds, and radiation over the southeast Atlantic. We find that the warming produced by the aerosols reduces cloud cover, especially in highly polluted situations. Aerosol impacts on drizzle play a minor role. However, aerosol effects on cloud reflectivity and moisture-induced changes in cloud cover dominate the climatic response and lead to an overall cooling by the biomass burning plumes.
Uwe Pfeifroth, Jaqueline Drücke, Steffen Kothe, Jörg Trentmann, Marc Schröder, and Rainer Hollmann
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-91, https://doi.org/10.5194/essd-2024-91, 2024
Preprint under review for ESSD
Short summary
Short summary
The energy reaching the Earth’s surface from the sun is a quantity of high importance for the climate system and for many applications. SARAH-3 is a satellite-based climate data record of surface solar radiation parameters. It is generated and distributed by the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF). SARAH-3 covers more than 4 decades, provides a high spatial and temporal resolution and its validation shows a good accuracy and stability.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
EGUsphere, https://doi.org/10.5194/egusphere-2024-248, https://doi.org/10.5194/egusphere-2024-248, 2024
Short summary
Short summary
Aerosol-cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem model, this study aims to understand the extent to which Twomey effect manifests itself at larger scales. We report a reduction in the warm bias over the Southern Ocean due to model improvements. While we do see footprints of Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Aku Riihelä, Emmihenna Jääskeläinen, and Viivi Kallio-Myers
Earth Syst. Sci. Data, 16, 1007–1028, https://doi.org/10.5194/essd-16-1007-2024, https://doi.org/10.5194/essd-16-1007-2024, 2024
Short summary
Short summary
We describe a new climate data record describing the surface albedo, or reflectivitity, of Earth's surface (called CLARA-A3 SAL). The climate data record spans over 4 decades of satellite observations, beginning in 1979. We conduct a quality assessment of the generated data, comparing them against other satellite data and albedo observations made on the ground. We find that the new data record in general matches surface observations well and is stable through time.
Emmihenna Jääskeläinen, Kerttu Kouki, and Aku Riihelä
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-278, https://doi.org/10.5194/hess-2023-278, 2024
Revised manuscript under review for HESS
Short summary
Short summary
Snow cover is an important variable when studying the effect of climate change in the Arctic. Therefore, the correct detection of snowfall is important. In this study, we present methods for limited area to detect snowfalls accurately using satellite observations. The snowfall event detection results of our limited area are encouraging. We find that further development could enable application over the whole Arctic, providing needed information on precipitation occurrence over remote areas.
Anja Hünerbein, Sebastian Bley, Hartwig Deneke, Jan Fokke Meirink, Gerd-Jan van Zadelhoff, and Andi Walther
Atmos. Meas. Tech., 17, 261–276, https://doi.org/10.5194/amt-17-261-2024, https://doi.org/10.5194/amt-17-261-2024, 2024
Short summary
Short summary
The ESA cloud, aerosol and radiation mission EarthCARE will provide active profiling and passive imaging measurements from a single satellite platform. The passive multi-spectral imager (MSI) will add information in the across-track direction. We present the cloud optical and physical properties algorithm, which combines the visible to infrared MSI channels to determine the cloud top pressure, optical thickness, particle size and water path.
Kerttu Kouki, Kari Luojus, and Aku Riihelä
The Cryosphere, 17, 5007–5026, https://doi.org/10.5194/tc-17-5007-2023, https://doi.org/10.5194/tc-17-5007-2023, 2023
Short summary
Short summary
We evaluated snow cover properties in state-of-the-art reanalyses (ERA5 and ERA5-Land) with satellite-based datasets. Both ERA5 and ERA5-Land overestimate snow mass, whereas albedo estimates are more consistent between the datasets. Snow cover extent (SCE) is accurately described in ERA5-Land, while ERA5 shows larger SCE than the satellite-based datasets. The trends in snow mass, SCE, and albedo are mostly negative in 1982–2018, and the negative trends become more apparent when spring advances.
Tim Trent, Marc Schroeder, Shu-Peng Ho, Steffen Beirle, Ralf Bennartz, Eva Borbas, Christian Borger, Helene Brogniez, Xavier Calbet, Elisa Castelli, Gilbert P. Compo, Wesley Ebisuzaki, Ulrike Falk, Frank Fell, John Forsythe, Hans Hersbach, Misako Kachi, Shinya Kobayashi, Robert E. Kursinsk, Diego Loyola, Zhengzao Luo, Johannes K. Nielsen, Enzo Papandrea, Laurence Picon, Rene Preusker, Anthony Reale, Lei Shi, Laura Slivinski, Joao Teixeira, Tom Vonder Haar, and Thomas Wagner
EGUsphere, https://doi.org/10.5194/egusphere-2023-2808, https://doi.org/10.5194/egusphere-2023-2808, 2023
Short summary
Short summary
In a warmer future, water vapour will spend more time in the atmosphere changing global rainfall patterns. In this study, we analysed the performance of 28 water vapour records between 1988 & 2014. We find sensitivity to surface warming generally outside expected ranges, attributed to breakpoints in individual record trends & differing representations of climate variability. The implication is that longer records are required for high confidence in assessing climate trends
Nikos Benas, Irina Solodovnik, Martin Stengel, Imke Hüser, Karl-Göran Karlsson, Nina Håkansson, Erik Johansson, Salomon Eliasson, Marc Schröder, Rainer Hollmann, and Jan Fokke Meirink
Earth Syst. Sci. Data, 15, 5153–5170, https://doi.org/10.5194/essd-15-5153-2023, https://doi.org/10.5194/essd-15-5153-2023, 2023
Short summary
Short summary
This paper describes CLAAS-3, the third edition of the Cloud property dAtAset using SEVIRI, which was created based on observations from geostationary Meteosat satellites. CLAAS-3 cloud properties are evaluated using a variety of reference datasets, with very good overall results. The demonstrated quality of CLAAS-3 ensures its usefulness in a wide range of applications, including studies of local- to continental-scale cloud processes and evaluation of climate models.
Cunbo Han, Corinna Hoose, Martin Stengel, Quentin Coopman, and Andrew Barrett
Atmos. Chem. Phys., 23, 14077–14095, https://doi.org/10.5194/acp-23-14077-2023, https://doi.org/10.5194/acp-23-14077-2023, 2023
Short summary
Short summary
Cloud phase has been found to significantly impact cloud thermodynamics and Earth’s radiation budget, and various factors influence it. This study investigates the sensitivity of the cloud-phase distribution to the ice-nucleating particle concentration and thermodynamics. Multiple simulation experiments were performed using the ICON model at the convection-permitting resolution of 1.2 km. Simulation results were compared to two different retrieval products based on SEVIRI measurements.
Arndt Kaps, Axel Lauer, Rémi Kazeroni, Martin Stengel, and Veronika Eyring
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-424, https://doi.org/10.5194/essd-2023-424, 2023
Revised manuscript accepted for ESSD
Short summary
Short summary
CCClim displays observations of clouds in terms of cloud classes that have been in use for a long time. CCClim is a machine-learning-powered product based on multiple existing observational products from different satellites. We show that the cloud classes in CCClim are physically meaningful and can be used to study cloud characteristics in more detail. The goal of this is to make real-world clouds more easily understandable to eventually improve the simulation of clouds in climate models.
Almudena Velázquez Blázquez, Edward Baudrez, Nicolas Clerbaux, and Carlos Domenech
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-170, https://doi.org/10.5194/amt-2023-170, 2023
Revised manuscript accepted for AMT
Short summary
Short summary
The BBR measures shortwave and totalwave radiances filtered by the spectral response of the instrument. To obtain unfiltered solar and thermal radiances, it is needed to correct for the effect of the spectral response. This is done within the BM-RAD processor. Errors in the unfiltering are propagated into the fluxes, thus, an accurate unfiltering is required for a proper estimation of the fluxes (within BMA-FLX). Unfiltering errors are estimated to be <0.5 % for the SW and <0.1 % for the LW.
Kameswara S. Vinjamuri, Marco Vountas, Luca Lelli, Martin Stengel, Matthew D. Shupe, Kerstin Ebell, and John P. Burrows
Atmos. Meas. Tech., 16, 2903–2918, https://doi.org/10.5194/amt-16-2903-2023, https://doi.org/10.5194/amt-16-2903-2023, 2023
Short summary
Short summary
Clouds play an important role in Arctic amplification. Cloud data from ground-based sites are valuable but cannot represent the whole Arctic. Therefore the use of satellite products is a measure to cover the entire Arctic. However, the quality of such cloud measurements from space is not well known. The paper discusses the differences and commonalities between satellite and ground-based measurements. We conclude that the satellite dataset, with a few exceptions, can be used in the Arctic.
Aart Overeem, Else van den Besselaar, Gerard van der Schrier, Jan Fokke Meirink, Emiel van der Plas, and Hidde Leijnse
Earth Syst. Sci. Data, 15, 1441–1464, https://doi.org/10.5194/essd-15-1441-2023, https://doi.org/10.5194/essd-15-1441-2023, 2023
Short summary
Short summary
EURADCLIM is a new precipitation dataset covering a large part of Europe. It is based on weather radar data to provide local precipitation information every hour and combined with rain gauge data to obtain good precipitation estimates. EURADCLIM provides a much better reference for validation of weather model output and satellite precipitation datasets. It also allows for climate monitoring and better evaluation of extreme precipitation events and their impact (landslides, flooding).
Tim Trent, Richard Siddans, Brian Kerridge, Marc Schröder, Noëlle A. Scott, and John Remedios
Atmos. Meas. Tech., 16, 1503–1526, https://doi.org/10.5194/amt-16-1503-2023, https://doi.org/10.5194/amt-16-1503-2023, 2023
Short summary
Short summary
Modern weather satellites provide essential information on our lower atmosphere's moisture content and temperature structure. This measurement record will span over 40 years, making it a valuable resource for climate studies. This study characterizes atmospheric temperature and humidity profiles from a European Space Agency climate project. Using weather balloon measurements, we demonstrated the performance of this dataset was within the tolerances required for future climate studies.
Cheng You, Michael Tjernström, and Abhay Devasthale
Atmos. Chem. Phys., 22, 8037–8057, https://doi.org/10.5194/acp-22-8037-2022, https://doi.org/10.5194/acp-22-8037-2022, 2022
Short summary
Short summary
In winter when solar radiation is absent in the Arctic, the poleward transport of heat and moisture into the high Arctic becomes the main contribution of Arctic warming. Over completely frozen ocean sectors, total surface energy budget is dominated by net long-wave heat, while over the Barents Sea, with an open ocean to the south, total net surface energy budget is dominated by the surface turbulent heat.
Kerttu Kouki, Petri Räisänen, Kari Luojus, Anna Luomaranta, and Aku Riihelä
The Cryosphere, 16, 1007–1030, https://doi.org/10.5194/tc-16-1007-2022, https://doi.org/10.5194/tc-16-1007-2022, 2022
Short summary
Short summary
We analyze state-of-the-art climate models’ ability to describe snow mass and whether biases in modeled temperature or precipitation can explain the discrepancies in snow mass. In winter, biases in precipitation are the main factor affecting snow mass, while in spring, biases in temperature becomes more important, which is an expected result. However, temperature or precipitation cannot explain all snow mass discrepancies. Other factors, such as models’ structural errors, are also significant.
Terhikki Manninen, Emmihenna Jääskeläinen, Niilo Siljamo, Aku Riihelä, and Karl-Göran Karlsson
Atmos. Meas. Tech., 15, 879–893, https://doi.org/10.5194/amt-15-879-2022, https://doi.org/10.5194/amt-15-879-2022, 2022
Short summary
Short summary
A new method for cloud-correcting observations of surface albedo is presented for AVHRR data. Instead of a binary cloud mask, it applies cloud probability values smaller than 20% of the A3 edition of the CLARA (CM SAF cLoud, Albedo and surface Radiation dataset from AVHRR data) record provided by the Satellite Application Facility on Climate Monitoring (CM SAF) project of EUMETSAT. According to simulations, the 90% quantile was 1.1% for the absolute albedo error and 2.2% for the relative error.
Wim C. de Rooy, Pier Siebesma, Peter Baas, Geert Lenderink, Stephan R. de Roode, Hylke de Vries, Erik van Meijgaard, Jan Fokke Meirink, Sander Tijm, and Bram van 't Veen
Geosci. Model Dev., 15, 1513–1543, https://doi.org/10.5194/gmd-15-1513-2022, https://doi.org/10.5194/gmd-15-1513-2022, 2022
Short summary
Short summary
This paper describes a comprehensive model update to the boundary layer schemes. Because the involved parameterisations are all built on widely applied frameworks, the here-described modifications are applicable to many NWP and climate models. The model update contains substantial modifications to the cloud, turbulence, and convection schemes and leads to a substantial improvement of several aspects of the model, especially low cloud forecasts.
Manu Anna Thomas, Abhay Devasthale, and Michael Kahnert
Atmos. Chem. Phys., 22, 119–137, https://doi.org/10.5194/acp-22-119-2022, https://doi.org/10.5194/acp-22-119-2022, 2022
Short summary
Short summary
The Southern Ocean (SO) covers a large area of our planet and its boundary layer is dominated by sea salt aerosols during winter. These aerosols have large implications for the regional climate through their direct and indirect effects. Using satellite and reanalysis data, we document if and how the aerosol properties over the SO are dependent on different local meteorological parameters. Such an observational assessment is necessary to improve the understanding of atmospheric aerosol processes.
Sandra Vázquez-Martín, Thomas Kuhn, and Salomon Eliasson
Atmos. Chem. Phys., 21, 18669–18688, https://doi.org/10.5194/acp-21-18669-2021, https://doi.org/10.5194/acp-21-18669-2021, 2021
Short summary
Short summary
High-resolution top- and side-view images of snow ice particles taken by the D-ICI instrument are used to determine the shape; size; cross-sectional area; fall speed; and, based upon these properties, the mass of the individual snow particles. The study analyses the relationships between these fundamental properties as a function of particle shape and highlights that the choice of size parameter, maximum dimension or another characteristic length, is crucial when relating fall speed to mass.
Manu Anna Thomas, Abhay Devasthale, and Tiina Nygård
Atmos. Chem. Phys., 21, 16593–16608, https://doi.org/10.5194/acp-21-16593-2021, https://doi.org/10.5194/acp-21-16593-2021, 2021
Short summary
Short summary
The impact of transported pollutants and their spatial distribution in the Arctic are governed by the local atmospheric circulation or weather states. Therefore, we investigated eight different atmospheric circulation types observed during the spring season in the Arctic. Using satellite and reanalysis datasets, this study provides a comprehensive assessment of the typical circulation patterns that can lead to enhanced or reduced pollution concentrations in the different sectors of the Arctic.
Hartwig Deneke, Carola Barrientos-Velasco, Sebastian Bley, Anja Hünerbein, Stephan Lenk, Andreas Macke, Jan Fokke Meirink, Marion Schroedter-Homscheidt, Fabian Senf, Ping Wang, Frank Werner, and Jonas Witthuhn
Atmos. Meas. Tech., 14, 5107–5126, https://doi.org/10.5194/amt-14-5107-2021, https://doi.org/10.5194/amt-14-5107-2021, 2021
Short summary
Short summary
The SEVIRI instrument flown on the European geostationary Meteosat satellites acquires multi-spectral images at a relatively coarse pixel resolution of 3 × 3 km2, but it also has a broadband high-resolution visible channel with 1 × 1 km2 spatial resolution. In this study, the modification of an existing cloud property and solar irradiance retrieval to use this channel to improve the spatial resolution of its output products as well as the resulting benefits for applications are described.
Susanne Crewell, Kerstin Ebell, Patrick Konjari, Mario Mech, Tatiana Nomokonova, Ana Radovan, David Strack, Arantxa M. Triana-Gómez, Stefan Noël, Raul Scarlat, Gunnar Spreen, Marion Maturilli, Annette Rinke, Irina Gorodetskaya, Carolina Viceto, Thomas August, and Marc Schröder
Atmos. Meas. Tech., 14, 4829–4856, https://doi.org/10.5194/amt-14-4829-2021, https://doi.org/10.5194/amt-14-4829-2021, 2021
Short summary
Short summary
Water vapor (WV) is an important variable in the climate system. Satellite measurements are thus crucial to characterize the spatial and temporal variability in WV and how it changed over time. In particular with respect to the observed strong Arctic warming, the role of WV still needs to be better understood. However, as shown in this paper, a detailed understanding is still hampered by large uncertainties in the various satellite WV products, showing the need for improved methods to derive WV.
Erik Johansson, Abhay Devasthale, Michael Tjernström, Annica M. L. Ekman, Klaus Wyser, and Tristan L'Ecuyer
Geosci. Model Dev., 14, 4087–4101, https://doi.org/10.5194/gmd-14-4087-2021, https://doi.org/10.5194/gmd-14-4087-2021, 2021
Short summary
Short summary
Understanding the coupling of clouds to large-scale circulation is a grand challenge for the climate community. Cloud radiative heating (CRH) is a key parameter in this coupling and is therefore essential to model realistically. We, therefore, evaluate a climate model against satellite observations. Our findings indicate good agreement in the seasonal pattern of CRH even if the magnitude differs. We also find that increasing the horizontal resolution in the model has little effect on the CRH.
Sandra Vázquez-Martín, Thomas Kuhn, and Salomon Eliasson
Atmos. Chem. Phys., 21, 7545–7565, https://doi.org/10.5194/acp-21-7545-2021, https://doi.org/10.5194/acp-21-7545-2021, 2021
Short summary
Short summary
In this work, we present new fall speed measurements of natural snow particles and ice crystals. We study the particle fall speed relationships and how they depend on particle shape. We analyze these relationships as a function of particle size, cross-sectional area, and area ratio for different particle shape groups. We also investigate the dependence of the particle fall speed on the orientation, as it has a large impact on the cross-sectional area.
Alejandro Baró Pérez, Abhay Devasthale, Frida A.-M. Bender, and Annica M. L. Ekman
Atmos. Chem. Phys., 21, 6053–6077, https://doi.org/10.5194/acp-21-6053-2021, https://doi.org/10.5194/acp-21-6053-2021, 2021
Short summary
Short summary
We study the impacts of above-cloud biomass burning plumes on radiation and clouds over the southeast Atlantic using data derived from satellite observations and data-constrained model simulations. A substantial amount of the aerosol within the plumes is not classified as smoke by the satellite. The atmosphere warms more with increasing smoke aerosol loading. No clear influence of aerosol type, loading, or moisture within the overlying aerosol plumes is detected on the cloud top cooling rates.
Terhikki Manninen, Kati Anttila, Emmihenna Jääskeläinen, Aku Riihelä, Jouni Peltoniemi, Petri Räisänen, Panu Lahtinen, Niilo Siljamo, Laura Thölix, Outi Meinander, Anna Kontu, Hanne Suokanerva, Roberta Pirazzini, Juha Suomalainen, Teemu Hakala, Sanna Kaasalainen, Harri Kaartinen, Antero Kukko, Olivier Hautecoeur, and Jean-Louis Roujean
The Cryosphere, 15, 793–820, https://doi.org/10.5194/tc-15-793-2021, https://doi.org/10.5194/tc-15-793-2021, 2021
Short summary
Short summary
The primary goal of this paper is to present a model of snow surface albedo (brightness) accounting for small-scale surface roughness effects. It can be combined with any volume scattering model. The results indicate that surface roughness may decrease the albedo by about 1–3 % in midwinter and even more than 10 % during the late melting season. The effect is largest for low solar zenith angle values and lower bulk snow albedo values.
Marloes Gutenstein, Karsten Fennig, Marc Schröder, Tim Trent, Stephan Bakan, J. Brent Roberts, and Franklin R. Robertson
Hydrol. Earth Syst. Sci., 25, 121–146, https://doi.org/10.5194/hess-25-121-2021, https://doi.org/10.5194/hess-25-121-2021, 2021
Short summary
Short summary
The net exchange of water between the surface and atmosphere is mainly determined by the freshwater flux: the difference between evaporation (E) and precipitation (P), or E−P. Although there is consensus among modelers that with a warming climate E−P will increase, evidence from satellite data is still not conclusive, mainly due to sensor calibration issues. We here investigate the degree of correspondence among six recent
satellite-based climate data records and ERA5 reanalysis E−P data.
Ina Neher, Susanne Crewell, Stefanie Meilinger, Uwe Pfeifroth, and Jörg Trentmann
Atmos. Chem. Phys., 20, 12871–12888, https://doi.org/10.5194/acp-20-12871-2020, https://doi.org/10.5194/acp-20-12871-2020, 2020
Short summary
Short summary
Photovoltaic power is one current option to meet the rising energy demand with low environmental impact. Global horizontal irradiance (GHI) is the fuel for photovoltaic power installations and needs to be evaluated to plan and dimension power plants. In this study, 35 years of satellite-based GHI data are analyzed over West Africa to determine their impact on photovoltaic power generation. The major challenges for the development of a solar-based power system in West Africa are then outlined.
Caroline A. Poulsen, Gregory R. McGarragh, Gareth E. Thomas, Martin Stengel, Matthew W. Christensen, Adam C. Povey, Simon R. Proud, Elisa Carboni, Rainer Hollmann, and Roy G. Grainger
Earth Syst. Sci. Data, 12, 2121–2135, https://doi.org/10.5194/essd-12-2121-2020, https://doi.org/10.5194/essd-12-2121-2020, 2020
Short summary
Short summary
We have created a satellite cloud and radiation climatology from the ATSR-2 and AATSR on board ERS-2 and Envisat, respectively, which spans the period 1995–2012. The data set was created using a combination of optimal estimation and neural net techniques. The data set was created as part of the ESA Climate Change Initiative program. The data set has been compared with active CALIOP lidar measurements and compared with MAC-LWP AND CERES-EBAF measurements and is shown to have good performance.
Karsten Fennig, Marc Schröder, Axel Andersson, and Rainer Hollmann
Earth Syst. Sci. Data, 12, 647–681, https://doi.org/10.5194/essd-12-647-2020, https://doi.org/10.5194/essd-12-647-2020, 2020
Short summary
Short summary
A Fundamental Climate Data Record (FCDR) from satellite-borne microwave radiometers has been created, covering the time period from October 1978 to December 2015. This article describes how the observations are processed, calibrated, corrected, inter-calibrated, and evaluated in order to provide a homogeneous data record of brightness temperatures across 10 different instruments aboard three different satellite platforms.
Salomon Eliasson, Karl-Göran Karlsson, and Ulrika Willén
Geosci. Model Dev., 13, 297–314, https://doi.org/10.5194/gmd-13-297-2020, https://doi.org/10.5194/gmd-13-297-2020, 2020
Short summary
Short summary
This paper describes a new satellite simulator. Its purpose is to simulate the CLARA-A2 climate data record from a climate model atmosphere. We explain how the simulator takes into account the regionally variable cloud detection skill of the observations. The simulator makes use of the long/lat-gridded validation between CLARA-A2 and the CALIOP satellite-borne lidar dataset. Using the EC-Earth climate model, we show a sizable impact on climate model validation, especially at high latitudes.
Nikos Benas, Jan Fokke Meirink, Karl-Göran Karlsson, Martin Stengel, and Piet Stammes
Atmos. Chem. Phys., 20, 457–474, https://doi.org/10.5194/acp-20-457-2020, https://doi.org/10.5194/acp-20-457-2020, 2020
Short summary
Short summary
In this study we analyse aerosol and cloud changes over southern China from 2006 to 2015 and investigate their possible interaction mechanisms. Results show decreasing aerosol loads and increasing liquid cloud cover in late autumn. Further analysis based on various satellite data sets shows consistency with the aerosol semi-direct effect, whereby less absorbing aerosols in the cloud layer would lead to an overall decrease in the evaporation of cloud droplets, thus increasing cloud amount.
Martin Stengel, Stefan Stapelberg, Oliver Sus, Stephan Finkensieper, Benjamin Würzler, Daniel Philipp, Rainer Hollmann, Caroline Poulsen, Matthew Christensen, and Gregory McGarragh
Earth Syst. Sci. Data, 12, 41–60, https://doi.org/10.5194/essd-12-41-2020, https://doi.org/10.5194/essd-12-41-2020, 2020
Short summary
Short summary
The Cloud_cci AVHRR-PMv3 dataset contains global, cloud and radiative flux properties covering the period of 1982 to 2016. The properties were retrieved from AVHRR measurements recorded by afternoon satellites of the NOAA POES missions. Validation against CALIOP, BSRN and CERES demonstrates the high quality of the data. The Cloud_cci AVHRR-PMv3 dataset allows for a large variety of climate applications that build on cloud properties, radiative flux properties and/or the link between them.
Vladimir S. Kostsov, Anke Kniffka, Martin Stengel, and Dmitry V. Ionov
Atmos. Meas. Tech., 12, 5927–5946, https://doi.org/10.5194/amt-12-5927-2019, https://doi.org/10.5194/amt-12-5927-2019, 2019
Short summary
Short summary
Cloud liquid water path (LWP) is one of the target atmospheric parameters retrieved remotely from ground-based and space-borne platforms. The LWP data delivered by the satellite instruments SEVIRI and AVHRR together with the data provided by the ground-based radiometer RPG-HATPRO near St. Petersburg, Russia, have been compared. Our study revealed considerable differences between LWP data from SEVIRI and AVHRR in winter over ice-covered relatively small water bodies in this region.
Aku Riihelä, Michalea D. King, and Kati Anttila
The Cryosphere, 13, 2597–2614, https://doi.org/10.5194/tc-13-2597-2019, https://doi.org/10.5194/tc-13-2597-2019, 2019
Short summary
Short summary
We used a 1982–2015 time series of satellite observations to examine changes in surface reflectivity (albedo) of the Greenland Ice Sheet. We found notable decreases in albedo over most of the ice sheet margins in July and August, particularly over the west coast and between 2000 and 2015. The results indicate that significant melt now occurs in areas 50 to 100 m higher up the ice sheet relative to the early 1980s. The albedo decrease is consistent and covarying with modelled ice sheet mass loss.
Manu Anna Thomas, Abhay Devasthale, Tristan L'Ecuyer, Shiyu Wang, Torben Koenigk, and Klaus Wyser
Geosci. Model Dev., 12, 3759–3772, https://doi.org/10.5194/gmd-12-3759-2019, https://doi.org/10.5194/gmd-12-3759-2019, 2019
Short summary
Short summary
Snow cover significantly influences the surface albedo and radiation budget. Therefore, a realistic representation of snowfall in climate models is important. Here, using decade-long estimates of snowfall derived from the satellite sensor, four climate models are evaluated to assess how well they simulate snowfall in the Arctic. It is found that light and median snowfall is overestimated by the models in comparison to the satellite observations, and extreme snowfall is underestimated.
Frank Kaspar, Michael Borsche, Uwe Pfeifroth, Jörg Trentmann, Jaqueline Drücke, and Paul Becker
Adv. Sci. Res., 16, 119–128, https://doi.org/10.5194/asr-16-119-2019, https://doi.org/10.5194/asr-16-119-2019, 2019
Short summary
Short summary
In this study, we assess balancing effects between photovoltaics and wind energy. On average, the seasonal cycles complement each other in Germany as well as in Europe. The frequency of events with a risk of low electricity generation is analyzed. The results illustrate that the number of such events is reduced when offshore regions are included, or when a combined system of PV and wind energy is considered. A European-wide analysis also leads to a distinct reduction of such events.
Nikos Benas, Jan Fokke Meirink, Martin Stengel, and Piet Stammes
Atmos. Meas. Tech., 12, 2863–2879, https://doi.org/10.5194/amt-12-2863-2019, https://doi.org/10.5194/amt-12-2863-2019, 2019
Short summary
Short summary
Cloud glory and bow phenomena cause irregularities in satellite-based retrievals of cloud optical and microphysical properties. Here we combine two geostationary satellites over the same areas to analyze retrievals under those conditions. Results show a high sensitivity of retrievals to the assumed width of the cloud droplet size distribution and provide insights into possible improvements in satellite retrievals by appropriately adjusting this assumed parameter.
Manu Anna Thomas, Abhay Devasthale, Torben Koenigk, Klaus Wyser, Malcolm Roberts, Christopher Roberts, and Katja Lohmann
Geosci. Model Dev., 12, 1679–1702, https://doi.org/10.5194/gmd-12-1679-2019, https://doi.org/10.5194/gmd-12-1679-2019, 2019
Short summary
Short summary
Cloud processes occur at scales ranging from few micrometres to hundreds of kilometres. Their representation in global climate models and their fidelity are thus sensitive to the choice of spatial resolution. Here, cloud radiative effects simulated by models are evaluated using a satellite dataset, with a focus on investigating the sensitivity to spatial resolution. The evaluations are carried out using two approaches: the traditional statistical comparisons and the process-oriented evaluation.
Marc Mallet, Pierre Nabat, Paquita Zuidema, Jens Redemann, Andrew Mark Sayer, Martin Stengel, Sebastian Schmidt, Sabrina Cochrane, Sharon Burton, Richard Ferrare, Kerry Meyer, Pablo Saide, Hiren Jethva, Omar Torres, Robert Wood, David Saint Martin, Romain Roehrig, Christina Hsu, and Paola Formenti
Atmos. Chem. Phys., 19, 4963–4990, https://doi.org/10.5194/acp-19-4963-2019, https://doi.org/10.5194/acp-19-4963-2019, 2019
Short summary
Short summary
The model is able to represent LWP but not the LCF. AOD is consistent over the continent but also over ocean (ACAOD). Differences are observed in SSA due to the absence of internal mixing in ALADIN-Climate. A significant regional gradient of the forcing at TOA is observed. An intense positive forcing is simulated over Gabon. Results highlight the significant effect of enhanced moisture on BBA extinction. The surface dimming modifies the energy budget.
Hendrik Andersen, Jan Cermak, Irina Solodovnik, Luca Lelli, and Roland Vogt
Atmos. Chem. Phys., 19, 4383–4392, https://doi.org/10.5194/acp-19-4383-2019, https://doi.org/10.5194/acp-19-4383-2019, 2019
Short summary
Short summary
Fog and low clouds (FLCs) are an essential but poorly understood component of Namib-region climate. This study uses observations from multiple satellite platforms and ground-based measurements to coherently characterize Namib-region FLC patterns. Findings concerning the seasonal cycle of the vertical structure and the diurnal cycle of FLCs lead to a new conceptual model of the spatiotemporal dynamics of FLCs in the Namib and help to improve the understanding of underlying processes.
Salomon Eliasson, Karl Göran Karlsson, Erik van Meijgaard, Jan Fokke Meirink, Martin Stengel, and Ulrika Willén
Geosci. Model Dev., 12, 829–847, https://doi.org/10.5194/gmd-12-829-2019, https://doi.org/10.5194/gmd-12-829-2019, 2019
Short summary
Short summary
To enable fair comparisons of clouds between climate models and the
ESA Cloud_cci climate data record (CDR), we present a tool called the
Cloud_cci simulator. The tool takes into account the geometry and
cloud detection capabilities of the Cloud_cci CDR to allow fair
comparisons. We demonstrate the simulator on two climate models. We
find the impact of time sampling has a large effect on simulated cloud
water amount and that the simulator reduces the cloud cover by about
10 % globally.
Soheila Jafariserajehlou, Linlu Mei, Marco Vountas, Vladimir Rozanov, John P. Burrows, and Rainer Hollmann
Atmos. Meas. Tech., 12, 1059–1076, https://doi.org/10.5194/amt-12-1059-2019, https://doi.org/10.5194/amt-12-1059-2019, 2019
Short summary
Short summary
We developed a new algorithm for cloud identification over the Arctic. This algorithm called ASCIA, utilizes time-series measurements of Advanced Along-Track Scanning Radiometer (AATSR) on Envisat and Sea and Land Surface Temperature Radiometer (SLSTR) on Sentinel-3A and -3B.
The data product of ASCIA is compared with three satellite products: ASCIA shows an improved performance compared to them. We validated ASCIA by ground-based measurements and a promising agreement is achieved.
Martin Stengel, Cornelia Schlundt, Stefan Stapelberg, Oliver Sus, Salomon Eliasson, Ulrika Willén, and Jan Fokke Meirink
Atmos. Chem. Phys., 18, 17601–17614, https://doi.org/10.5194/acp-18-17601-2018, https://doi.org/10.5194/acp-18-17601-2018, 2018
Short summary
Short summary
We present a new approach to evaluate ERA-Interim reanalysis clouds using satellite observations. A simplified satellite simulator was developed that uses reanalysis fields to emulate clouds as they would have been seen by those satellite sensors which were used to compose Cloud_cci observational cloud datasets. Our study facilitates an adequate evaluation of modelled ERA-Interim clouds using observational datasets, also taking into account systematic uncertainties in the observations.
Rocío Baró, Pedro Jiménez-Guerrero, Martin Stengel, Dominik Brunner, Gabriele Curci, Renate Forkel, Lucy Neal, Laura Palacios-Peña, Nicholas Savage, Martijn Schaap, Paolo Tuccella, Hugo Denier van der Gon, and Stefano Galmarini
Atmos. Chem. Phys., 18, 15183–15199, https://doi.org/10.5194/acp-18-15183-2018, https://doi.org/10.5194/acp-18-15183-2018, 2018
Short summary
Short summary
Particles in the atmosphere, such as pollution, desert dust, and volcanic ash, have an impact on meteorology. They interact with incoming radiation resulting in a cooling effect of the atmosphere. Today, the use of meteorology and chemistry models help us to understand these processes, but there are a lot of uncertainties. The goal of this work is to evaluate how these interactions are represented in the models by comparing them to satellite data to see how close they are to reality.
Rita Glowienka-Hense, Andreas Hense, Thomas Spangehl, and Marc Schröder
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-141, https://doi.org/10.5194/gmd-2018-141, 2018
Revised manuscript not accepted
Short summary
Short summary
Ensemble forecast verification treats the issues of forecast errors and uncertainty estimated from ensemble spread. We suggest measures based on relative entropy. For continuous variables correlation and the mean ratio of the ensemble spread to climate variance (analysis of variance (anova)) are related to these entropies. For categorical data corresponding scores are deduced that allow the comparison with continuous data.
Chellappan Seethala, Jan Fokke Meirink, Ákos Horváth, Ralf Bennartz, and Rob Roebeling
Atmos. Chem. Phys., 18, 13283–13304, https://doi.org/10.5194/acp-18-13283-2018, https://doi.org/10.5194/acp-18-13283-2018, 2018
Short summary
Short summary
We compared the microphysical properties of South Atlantic stratocumulus (Sc) from three different satellite instruments (SEVIRI, TMI, MODIS). The liquid water path (LWP) and its diurnal cycle from the three datasets agreed very well in overcast, smoke-free scenes. LWP showed a decrease from an early morning peak to a late afternoon minimum, after which it increased until morning. The presence of smoke aloft Sc, however, negatively biased the LWP retrieved by the visible/near-infrared technique.
Mélodie Trolliet, Jakub P. Walawender, Bernard Bourlès, Alexandre Boilley, Jörg Trentmann, Philippe Blanc, Mireille Lefèvre, and Lucien Wald
Ocean Sci., 14, 1021–1056, https://doi.org/10.5194/os-14-1021-2018, https://doi.org/10.5194/os-14-1021-2018, 2018
Simon Pfreundschuh, Patrick Eriksson, David Duncan, Bengt Rydberg, Nina Håkansson, and Anke Thoss
Atmos. Meas. Tech., 11, 4627–4643, https://doi.org/10.5194/amt-11-4627-2018, https://doi.org/10.5194/amt-11-4627-2018, 2018
Short summary
Short summary
A novel neural-network-based retrieval method is proposed that combines the flexibility and computational efficiency of machine learning retrievals with the consistent treatment of uncertainties of Bayesian methods. Numerical experiments are presented that show the consistency of the proposed method with the Bayesian formulation as well as its ability to represent non-Gaussian retrieval errors. With this, the proposed method overcomes important limitations of traditional methods.
Nikos Benas, Jan Fokke Meirink, Karl-Göran Karlsson, Martin Stengel, and Piet Stammes
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-554, https://doi.org/10.5194/acp-2018-554, 2018
Preprint withdrawn
Short summary
Short summary
In this study we analyse aerosol and cloud changes over South China and investigate their possible interactions. The results show decreasing aerosol loads and increasing liquid clouds. Further analysis of these changes based on various satellite data sets show consistency with the aerosol semi-direct effect, whereby less absorbing aerosols in the cloud layer would lead to an overall decrease in evaporation of cloud droplets, thus increasing cloud amount and cover.
Marc Schröder, Maarit Lockhoff, Frank Fell, John Forsythe, Tim Trent, Ralf Bennartz, Eva Borbas, Michael G. Bosilovich, Elisa Castelli, Hans Hersbach, Misako Kachi, Shinya Kobayashi, E. Robert Kursinski, Diego Loyola, Carl Mears, Rene Preusker, William B. Rossow, and Suranjana Saha
Earth Syst. Sci. Data, 10, 1093–1117, https://doi.org/10.5194/essd-10-1093-2018, https://doi.org/10.5194/essd-10-1093-2018, 2018
Short summary
Short summary
This publication presents results achieved within the GEWEX Water Vapor Assessment (G-VAP). An overview of available water vapour data records based on satellite observations and reanalysis is given. If a minimum temporal coverage of 10 years is applied, 22 data records remain. These form the G-VAP data archive, which contains total column water vapour, specific humidity profiles and temperature profiles. The G-VAP data archive is designed to ease intercomparison and climate model evaluation.
Gregory R. McGarragh, Caroline A. Poulsen, Gareth E. Thomas, Adam C. Povey, Oliver Sus, Stefan Stapelberg, Cornelia Schlundt, Simon Proud, Matthew W. Christensen, Martin Stengel, Rainer Hollmann, and Roy G. Grainger
Atmos. Meas. Tech., 11, 3397–3431, https://doi.org/10.5194/amt-11-3397-2018, https://doi.org/10.5194/amt-11-3397-2018, 2018
Short summary
Short summary
Satellites are vital for measuring cloud properties necessary for climate prediction studies. We present a method to retrieve cloud properties from satellite based radiometric measurements. The methodology employed is known as optimal estimation and belongs in the class of statistical inversion methods based on Bayes' theorem. We show, through theoretical retrieval simulations, that the solution is stable and accurate to within 10–20% depending on cloud thickness.
Oliver Sus, Martin Stengel, Stefan Stapelberg, Gregory McGarragh, Caroline Poulsen, Adam C. Povey, Cornelia Schlundt, Gareth Thomas, Matthew Christensen, Simon Proud, Matthias Jerg, Roy Grainger, and Rainer Hollmann
Atmos. Meas. Tech., 11, 3373–3396, https://doi.org/10.5194/amt-11-3373-2018, https://doi.org/10.5194/amt-11-3373-2018, 2018
Short summary
Short summary
This paper presents a new cloud detection and classification framework, CC4CL. It applies a sophisticated optimal estimation method to derive cloud variables from satellite data of various polar-orbiting platforms and sensors (AVHRR, MODIS, AATSR). CC4CL provides explicit uncertainty quantification and long-term consistency for decadal timeseries at various spatial resolutions. We analysed 5 case studies to show that cloud height estimates are very realistic unless optically thin clouds overlap.
Quentin Bourgeois, Annica M. L. Ekman, Jean-Baptiste Renard, Radovan Krejci, Abhay Devasthale, Frida A.-M. Bender, Ilona Riipinen, Gwenaël Berthet, and Jason L. Tackett
Atmos. Chem. Phys., 18, 7709–7720, https://doi.org/10.5194/acp-18-7709-2018, https://doi.org/10.5194/acp-18-7709-2018, 2018
Short summary
Short summary
The altitude of aerosols is crucial as they can impact cloud formation and radiation. In this study, satellite observations have been used to characterize the global aerosol optical depth (AOD) in the boundary layer and the free troposphere. The free troposphere contributes 39 % to the global AOD during daytime. Overall, the results have implications for the description of budgets, sources, sinks and transport of aerosol particles as presently described in the atmospheric model.
Nina Håkansson, Claudia Adok, Anke Thoss, Ronald Scheirer, and Sara Hörnquist
Atmos. Meas. Tech., 11, 3177–3196, https://doi.org/10.5194/amt-11-3177-2018, https://doi.org/10.5194/amt-11-3177-2018, 2018
Short summary
Short summary
In this paper a new algorithm for cloud top height retrieval from imager instruments like MODIS is presented. It uses artificial neural networks and reduces the mean absolute error by 32 % compared to two other operational cloud height algorithms. This means that improved cloud height retrieval for nowcasting, as input to models and in cloud climatologies is possible.
Michael Keller, Nico Kröner, Oliver Fuhrer, Daniel Lüthi, Juerg Schmidli, Martin Stengel, Reto Stöckli, and Christoph Schär
Atmos. Chem. Phys., 18, 5253–5264, https://doi.org/10.5194/acp-18-5253-2018, https://doi.org/10.5194/acp-18-5253-2018, 2018
Short summary
Short summary
Deep convection is often associated with thunderstorms and heavy rain events. In this study, the sensitivity of Alpine deep convective events to environmental parameters and climate warming is investigated. To this end, simulations are conducted at resolutions of 12 and 2 km. The results show that the climate change signal strongly depends upon the horizontal resolution. In particular, significant differences are found in terms of the radiative feedbacks.
Uwe Pfeifroth, Jedrzej S. Bojanowski, Nicolas Clerbaux, Veronica Manara, Arturo Sanchez-Lorenzo, Jörg Trentmann, Jakub P. Walawender, and Rainer Hollmann
Adv. Sci. Res., 15, 31–37, https://doi.org/10.5194/asr-15-31-2018, https://doi.org/10.5194/asr-15-31-2018, 2018
Short summary
Short summary
Measuring solar radiation and analysing its interaction with clouds are essential for the understanding of the climate system. Trends in EUMETSAT CM SAF satellite-based climate data records of solar radiation and clouds are analysed during 1992–2015 in Europe. More surface solar radiation and less top-of-atmosphere reflected radiation and cloud cover is found. This study indicates that one of the main reasons for the positive trend in surface solar radiation is a decrease in cloud cover.
Julian Liman, Marc Schröder, Karsten Fennig, Axel Andersson, and Rainer Hollmann
Atmos. Meas. Tech., 11, 1793–1815, https://doi.org/10.5194/amt-11-1793-2018, https://doi.org/10.5194/amt-11-1793-2018, 2018
Short summary
Short summary
Latent heat fluxes (LHF) play a major role in the climate system. Over open ocean, they are increasingly observed by satellite instruments. To access their quality, this research focuses on thorough uncertainty analysis of all LHF-related variables of the HOAPS satellite climatology, in parts making use of novel analysis approaches. Results indicate climatological LHF uncertainies up to 50 W m−2, whereby underlying specific humidities tend to be more uncertain than contributing wind speeds.
Steffen Beirle, Johannes Lampel, Yang Wang, Kornelia Mies, Steffen Dörner, Margherita Grossi, Diego Loyola, Angelika Dehn, Anja Danielczok, Marc Schröder, and Thomas Wagner
Earth Syst. Sci. Data, 10, 449–468, https://doi.org/10.5194/essd-10-449-2018, https://doi.org/10.5194/essd-10-449-2018, 2018
Short summary
Short summary
We present time series of the global distribution of water vapor over more than 2 decades based on satellite measurements from different sensors. A particular focus is the consistency amongst the different sensors to avoid jumps from one instrument to another. This is reached by applying robust and simple retrieval settings consistently. The resulting
Climateproduct allows the study of the temporal evolution of water vapor over the last 20 years on a global scale.
Karl-Göran Karlsson and Nina Håkansson
Atmos. Meas. Tech., 11, 633–649, https://doi.org/10.5194/amt-11-633-2018, https://doi.org/10.5194/amt-11-633-2018, 2018
Short summary
Short summary
Data from the high-sensitivity CALIOP cloud lidar onboard the CALIPSO satellite have been used to evaluate cloud amounts estimated from satellite imagery and, specifically, from the climate data record CLARA-A2. The main purpose has been to study the limit of how thin clouds that can be detected efficiently (i.e., detected at the 50 % level) in CLARA-A2 data and how this limit varies globally. The study revealed very large geographical differences in the cloud detection efficiency.
Martin Stengel, Stefan Stapelberg, Oliver Sus, Cornelia Schlundt, Caroline Poulsen, Gareth Thomas, Matthew Christensen, Cintia Carbajal Henken, Rene Preusker, Jürgen Fischer, Abhay Devasthale, Ulrika Willén, Karl-Göran Karlsson, Gregory R. McGarragh, Simon Proud, Adam C. Povey, Roy G. Grainger, Jan Fokke Meirink, Artem Feofilov, Ralf Bennartz, Jedrzej S. Bojanowski, and Rainer Hollmann
Earth Syst. Sci. Data, 9, 881–904, https://doi.org/10.5194/essd-9-881-2017, https://doi.org/10.5194/essd-9-881-2017, 2017
Short summary
Short summary
We present new cloud property datasets based on measurements from the passive imaging satellite sensors AVHRR, MODIS, ATSR2, AATSR and MERIS. Retrieval systems were developed that include cloud detection and cloud typing followed by optimal estimation retrievals of cloud properties (e.g. cloud-top pressure, effective radius, optical thickness, water path). Special features of all datasets are spectral consistency and rigorous uncertainty propagation from pixel-level data to monthly properties.
Manu Anna Thomas and Abhay Devasthale
Atmos. Chem. Phys., 17, 12071–12080, https://doi.org/10.5194/acp-17-12071-2017, https://doi.org/10.5194/acp-17-12071-2017, 2017
Short summary
Short summary
Episodes of extreme pollution events of nitrogen dioxide (NO2) can seriously hamper air quality. But under which meteorological conditions do such extreme pollution events occur over Scandinavia? Using observational and reanalysis data it is shown that south-westerly winds (sustained for at least a few days) dominate during extreme events and cause an increase in humidity and clouds. South-easterly winds have the second largest contribution and the pollution transport is rapid when they prevail.
Lars Norin, Abhay Devasthale, and Tristan S. L'Ecuyer
Atmos. Meas. Tech., 10, 3249–3263, https://doi.org/10.5194/amt-10-3249-2017, https://doi.org/10.5194/amt-10-3249-2017, 2017
Short summary
Short summary
For a high-latitude country like Sweden snowfall is an important contributor to the regional water cycle. For Sweden, large-scale atmospheric circulation patterns, or weather states, are important for precipitation variability. In this work we investigate the sensitivity of snowfall to weather states over Sweden to eight selected weather states. The analysis is based on measurements from ground-based radar, satellite observations, spatially interpolated in situ observations, and reanalysis data.
Christopher J. Merchant, Frank Paul, Thomas Popp, Michael Ablain, Sophie Bontemps, Pierre Defourny, Rainer Hollmann, Thomas Lavergne, Alexandra Laeng, Gerrit de Leeuw, Jonathan Mittaz, Caroline Poulsen, Adam C. Povey, Max Reuter, Shubha Sathyendranath, Stein Sandven, Viktoria F. Sofieva, and Wolfgang Wagner
Earth Syst. Sci. Data, 9, 511–527, https://doi.org/10.5194/essd-9-511-2017, https://doi.org/10.5194/essd-9-511-2017, 2017
Short summary
Short summary
Climate data records (CDRs) contain data describing Earth's climate and should address uncertainty in the data to communicate what is known about climate variability or change and what range of doubt exists. This paper discusses good practice for including uncertainty information in CDRs for the essential climate variables (ECVs) derived from satellite data. Recommendations emerge from the shared experience of diverse ECV projects within the European Space Agency Climate Change Initiative.
Nikos Benas, Stephan Finkensieper, Martin Stengel, Gerd-Jan van Zadelhoff, Timo Hanschmann, Rainer Hollmann, and Jan Fokke Meirink
Earth Syst. Sci. Data, 9, 415–434, https://doi.org/10.5194/essd-9-415-2017, https://doi.org/10.5194/essd-9-415-2017, 2017
Short summary
Short summary
This study focuses on an evaluation of CLAAS-2 (Cloud property dAtAset using SEVIRI, Edition 2), which was created based on observations from geostationary Meteosat satellites. Using a variety of reference datasets, very good overall agreement is found. This suggests the usefulness of CLAAS-2 in applications ranging from high spatial and temporal resolution cloud process studies to the evaluation of regional climate models.
Stefano Federico, Rosa Claudia Torcasio, Paolo Sanò, Daniele Casella, Monica Campanelli, Jan Fokke Meirink, Ping Wang, Stefania Vergari, Henri Diémoz, and Stefano Dietrich
Atmos. Meas. Tech., 10, 2337–2352, https://doi.org/10.5194/amt-10-2337-2017, https://doi.org/10.5194/amt-10-2337-2017, 2017
Short summary
Short summary
In this paper we evaluate the performance of two estimates of the global horizontal irradiance (GHI), one derived from the Meteosat Second Generation and one from a meteorological model (Regional Atmospheric Modeling System) forecast. The focus area is Italy, and the performance is evaluated for 12 pyranometers spanning a range of climate conditions, from Mediterranean maritime to Alpine.
Sarah Taylor, Philip Stier, Bethan White, Stephan Finkensieper, and Martin Stengel
Atmos. Chem. Phys., 17, 7035–7053, https://doi.org/10.5194/acp-17-7035-2017, https://doi.org/10.5194/acp-17-7035-2017, 2017
Short summary
Short summary
Variability of convective cloud spans a wide range of temporal and spatial scales and is important for global weather and climate. This study uses satellite data from SEVIRI to quantify the diurnal cycle of cloud top temperatures over a large area. Results indicate that in some regions the diurnal cycle apparent in the observations may be significantly impacted by diurnal variability in the accuracy of the retrieval. These results may interest both the observation and modelling communities.
Karl-Göran Karlsson, Kati Anttila, Jörg Trentmann, Martin Stengel, Jan Fokke Meirink, Abhay Devasthale, Timo Hanschmann, Steffen Kothe, Emmihenna Jääskeläinen, Joseph Sedlar, Nikos Benas, Gerd-Jan van Zadelhoff, Cornelia Schlundt, Diana Stein, Stefan Finkensieper, Nina Håkansson, and Rainer Hollmann
Atmos. Chem. Phys., 17, 5809–5828, https://doi.org/10.5194/acp-17-5809-2017, https://doi.org/10.5194/acp-17-5809-2017, 2017
Short summary
Short summary
The paper presents the second version of a global climate data record based on satellite measurements from polar orbiting weather satellites. It describes the global evolution of cloudiness, surface albedo and surface radiation during the time period 1982–2015. The main improvements of algorithms are described together with some validation results. In addition, some early analysis is presented of some particularly interesting climate features (Arctic albedo and cloudiness + global cloudiness).
Ralf Bennartz, Heidrun Höschen, Bruno Picard, Marc Schröder, Martin Stengel, Oliver Sus, Bojan Bojkov, Stefano Casadio, Hannes Diedrich, Salomon Eliasson, Frank Fell, Jürgen Fischer, Rainer Hollmann, Rene Preusker, and Ulrika Willén
Atmos. Meas. Tech., 10, 1387–1402, https://doi.org/10.5194/amt-10-1387-2017, https://doi.org/10.5194/amt-10-1387-2017, 2017
Short summary
Short summary
The microwave radiometers (MWR) on board ERS-1, ERS-2, and Envisat provide a continuous time series of brightness temperature observations between 1991 and 2012. Here we report on a new total column water vapour (TCWV) and wet tropospheric correction (WTC) dataset that builds on this time series. The dataset is publicly available under doi:10.5676/DWD_EMIR/V001.
Adrianus de Laat, Eric Defer, Julien Delanoë, Fabien Dezitter, Amanda Gounou, Alice Grandin, Anthony Guignard, Jan Fokke Meirink, Jean-Marc Moisselin, and Frédéric Parol
Atmos. Meas. Tech., 10, 1359–1371, https://doi.org/10.5194/amt-10-1359-2017, https://doi.org/10.5194/amt-10-1359-2017, 2017
Short summary
Short summary
In-flight icing is an important aviation hazard which is still poorly understood, but consensus is that the presence of high ice water content is a necessary condition. For the European High Altitude Ice Crystals project a geostationary satellite remote-sensing mask has been developed for detection of atmospheric cloud environments where high ice water content is likely to occur. The mask performs satisfactory when compared against independent satellite ice water content measurements.
Moa K. Sporre, Ewan J. O'Connor, Nina Håkansson, Anke Thoss, Erik Swietlicki, and Tuukka Petäjä
Atmos. Meas. Tech., 9, 3193–3203, https://doi.org/10.5194/amt-9-3193-2016, https://doi.org/10.5194/amt-9-3193-2016, 2016
Short summary
Short summary
Satellite measurements of cloud top height and liquid water path are compared to ground-based remote sensing to evaluate the satellite retrievals. The overall performance of the satellite retrievals of cloud top height are good, but they become more problematic when several layers of clouds are present. The liquid water path retrievals also agree well, and the average differences are within the estimated measurement uncertainties.
Karl Bumke, Gert König-Langlo, Julian Kinzel, and Marc Schröder
Atmos. Meas. Tech., 9, 2409–2423, https://doi.org/10.5194/amt-9-2409-2016, https://doi.org/10.5194/amt-9-2409-2016, 2016
Short summary
Short summary
Satellite-derived HOAPS and ERA-Interim reanalysis data were validated against shipboard precipitation measurements. Results show that HOAPS detects the frequency of precipitation well, while ERA-Interim strongly overestimates it, especially at low latitudes. However, HOAPS underestimates precipitation rates, while ERA-Interim's Atlantic-wide precipitation rate is close to measurements. ERA-Interim strongly overestimates it in the intertropical convergence zone and southern subtropics.
N. Courcoux and M. Schröder
Earth Syst. Sci. Data, 7, 397–414, https://doi.org/10.5194/essd-7-397-2015, https://doi.org/10.5194/essd-7-397-2015, 2015
Short summary
Short summary
Despite its great importance for the climate, the behaviour and content of water vapour in the troposphere is insufficiently known. The ATOVS instruments onboard polar-orbiting satellites allow the retrieval of water vapour at different altitudes and on global scale. Here a consistent reprocessing of water vapour products derived from the ATOVS instrument from 1999 to 2011 is presented and compared to time series derived from other instruments. The data are freely available at www.cmsaf.eu/wui.
L. Norin, A. Devasthale, T. S. L'Ecuyer, N. B. Wood, and M. Smalley
Atmos. Meas. Tech., 8, 5009–5021, https://doi.org/10.5194/amt-8-5009-2015, https://doi.org/10.5194/amt-8-5009-2015, 2015
Short summary
Short summary
The ability to estimate snowfall accurately is important for both weather and climate applications. In this work we have intercompared snowfall estimates from two observing systems: the space-based Cloud Profiling Radar on board NASA's CloudSat satellite and Swerad, the ground-based Swedish national weather radar network. The intercomparison shows encouraging agreement between these two observing systems despite their different sensitivities and user applications.
E. Andersson, M. Kahnert, and A. Devasthale
Geosci. Model Dev., 8, 3747–3763, https://doi.org/10.5194/gmd-8-3747-2015, https://doi.org/10.5194/gmd-8-3747-2015, 2015
Short summary
Short summary
This study investigate the representation of hemispheric transport in a regional chemical transport model (CTM) in terms of lateral boundary conditions (LBCs). We evaluate the LBCs both directly with satellite retrievals and indirectly by forcing a regional CTM with LBCs and compare to in-domain observations. We believe that our work makes an important contribution to the methodology of validating LBCs for regional modelling.
E. Johansson, A. Devasthale, T. L'Ecuyer, A. M. L. Ekman, and M. Tjernström
Atmos. Chem. Phys., 15, 11557–11570, https://doi.org/10.5194/acp-15-11557-2015, https://doi.org/10.5194/acp-15-11557-2015, 2015
Short summary
Short summary
Both radiative and latent heat components of total diabatic heating influence Indian monsoon dynamics. This study investigates radiative component in detail, focusing on various cloud types that have largest radiative impact during summer monsoon over the Indian subcontinent. The vertical structure of radiative heating and its intra-seasonal variability is investigated with particular emphasis on the upper troposphere and lower stratosphere (UTLS) region.
D. Chang, Y. Cheng, P. Reutter, J. Trentmann, S. M. Burrows, P. Spichtinger, S. Nordmann, M. O. Andreae, U. Pöschl, and H. Su
Atmos. Chem. Phys., 15, 10325–10348, https://doi.org/10.5194/acp-15-10325-2015, https://doi.org/10.5194/acp-15-10325-2015, 2015
M. A. Thomas, M. Kahnert, C. Andersson, H. Kokkola, U. Hansson, C. Jones, J. Langner, and A. Devasthale
Geosci. Model Dev., 8, 1885–1898, https://doi.org/10.5194/gmd-8-1885-2015, https://doi.org/10.5194/gmd-8-1885-2015, 2015
Short summary
Short summary
We have showed that a coupled modelling system is beneficial in the sense that more complex processes can be included to better represent the aerosol processes starting from their formation, their interactions with clouds and provide better estimate of radiative forcing. Using this model set up, we estimated an annual mean 'indirect' radiative forcing of -0.64W/m2. This means that aerosols, solely by their capability of altering the microphysical properties of clouds can cool the Earth system.
M. Hummel, C. Hoose, M. Gallagher, D. A. Healy, J. A. Huffman, D. O'Connor, U. Pöschl, C. Pöhlker, N. H. Robinson, M. Schnaiter, J. R. Sodeau, M. Stengel, E. Toprak, and H. Vogel
Atmos. Chem. Phys., 15, 6127–6146, https://doi.org/10.5194/acp-15-6127-2015, https://doi.org/10.5194/acp-15-6127-2015, 2015
P. Räisänen, A. Luomaranta, H. Järvinen, M. Takala, K. Jylhä, O. N. Bulygina, K. Luojus, A. Riihelä, A. Laaksonen, J. Koskinen, and J. Pulliainen
Geosci. Model Dev., 7, 3037–3057, https://doi.org/10.5194/gmd-7-3037-2014, https://doi.org/10.5194/gmd-7-3037-2014, 2014
Short summary
Short summary
Snowmelt influences greatly the climatic conditions in spring. This study evaluates the timing of springtime end of snowmelt in the ECHAM5 model. A key finding is that, in much of northern Eurasia, snow disappears too early in ECHAM5, in spite of a slight cold bias in spring. This points to the need for a more comprehensive treatment of the surface energy budget. In particular, the surface temperature for the snow-covered and snow-free parts of a climate model grid cell should be separated.
M. A. Thomas and A. Devasthale
Atmos. Chem. Phys., 14, 11545–11555, https://doi.org/10.5194/acp-14-11545-2014, https://doi.org/10.5194/acp-14-11545-2014, 2014
M. Schröder, R. Roca, L. Picon, A. Kniffka, and H. Brogniez
Atmos. Chem. Phys., 14, 11129–11148, https://doi.org/10.5194/acp-14-11129-2014, https://doi.org/10.5194/acp-14-11129-2014, 2014
P. Reutter, J. Trentmann, A. Seifert, P. Neis, H. Su, D. Chang, M. Herzog, H. Wernli, M. O. Andreae, and U. Pöschl
Atmos. Chem. Phys., 14, 7573–7583, https://doi.org/10.5194/acp-14-7573-2014, https://doi.org/10.5194/acp-14-7573-2014, 2014
R. Lindstrot, M. Stengel, M. Schröder, J. Fischer, R. Preusker, N. Schneider, T. Steenbergen, and B. R. Bojkov
Earth Syst. Sci. Data, 6, 221–233, https://doi.org/10.5194/essd-6-221-2014, https://doi.org/10.5194/essd-6-221-2014, 2014
A. Devasthale and L. Norin
Atmos. Meas. Tech., 7, 1605–1617, https://doi.org/10.5194/amt-7-1605-2014, https://doi.org/10.5194/amt-7-1605-2014, 2014
M. Stengel, A. Kniffka, J. F. Meirink, M. Lockhoff, J. Tan, and R. Hollmann
Atmos. Chem. Phys., 14, 4297–4311, https://doi.org/10.5194/acp-14-4297-2014, https://doi.org/10.5194/acp-14-4297-2014, 2014
A. Kniffka, M. Stengel, M. Lockhoff, R. Bennartz, and R. Hollmann
Atmos. Meas. Tech., 7, 887–905, https://doi.org/10.5194/amt-7-887-2014, https://doi.org/10.5194/amt-7-887-2014, 2014
T. Koenigk, A. Devasthale, and K.-G. Karlsson
Atmos. Chem. Phys., 14, 1987–1998, https://doi.org/10.5194/acp-14-1987-2014, https://doi.org/10.5194/acp-14-1987-2014, 2014
K. Schamm, M. Ziese, A. Becker, P. Finger, A. Meyer-Christoffer, U. Schneider, M. Schröder, and P. Stender
Earth Syst. Sci. Data, 6, 49–60, https://doi.org/10.5194/essd-6-49-2014, https://doi.org/10.5194/essd-6-49-2014, 2014
J. F. Meirink, R. A. Roebeling, and P. Stammes
Atmos. Meas. Tech., 6, 2495–2508, https://doi.org/10.5194/amt-6-2495-2013, https://doi.org/10.5194/amt-6-2495-2013, 2013
B. Dürr, M. Schröder, R. Stöckli, and R. Posselt
Atmos. Meas. Tech., 6, 1883–1901, https://doi.org/10.5194/amt-6-1883-2013, https://doi.org/10.5194/amt-6-1883-2013, 2013
A. Devasthale, J. Sedlar, T. Koenigk, and E. J. Fetzer
Atmos. Chem. Phys., 13, 7441–7450, https://doi.org/10.5194/acp-13-7441-2013, https://doi.org/10.5194/acp-13-7441-2013, 2013
H. Brenot, J. Neméghaire, L. Delobbe, N. Clerbaux, P. De Meutter, A. Deckmyn, A. Delcloo, L. Frappez, and M. Van Roozendael
Atmos. Chem. Phys., 13, 5425–5449, https://doi.org/10.5194/acp-13-5425-2013, https://doi.org/10.5194/acp-13-5425-2013, 2013
K.-G. Karlsson, A. Riihelä, R. Müller, J. F. Meirink, J. Sedlar, M. Stengel, M. Lockhoff, J. Trentmann, F. Kaspar, R. Hollmann, and E. Wolters
Atmos. Chem. Phys., 13, 5351–5367, https://doi.org/10.5194/acp-13-5351-2013, https://doi.org/10.5194/acp-13-5351-2013, 2013
K.-G. Karlsson and E. Johansson
Atmos. Meas. Tech., 6, 1271–1286, https://doi.org/10.5194/amt-6-1271-2013, https://doi.org/10.5194/amt-6-1271-2013, 2013
A. Riihelä, T. Manninen, V. Laine, K. Andersson, and F. Kaspar
Atmos. Chem. Phys., 13, 3743–3762, https://doi.org/10.5194/acp-13-3743-2013, https://doi.org/10.5194/acp-13-3743-2013, 2013
M. Schröder, M. Jonas, R. Lindau, J. Schulz, and K. Fennig
Atmos. Meas. Tech., 6, 765–775, https://doi.org/10.5194/amt-6-765-2013, https://doi.org/10.5194/amt-6-765-2013, 2013
Related subject area
Domain: ESSD – Atmosphere | Subject: Meteorology
Reanalysis of multi-year high-resolution X-band weather radar observations in Hamburg
The 2023 National Offshore Wind data set (NOW-23)
Dataset of stable isotopes of precipitation in the Eurasian continent
A 7-year record of vertical profiles of radar measurements and precipitation estimates at Dumont d'Urville, Adélie Land, East Antarctica
Long-term monthly 0.05° terrestrial evapotranspiration dataset (1982–2018) for the Tibetan Plateau
High-resolution (1 km) all-sky net radiation over Europe enabled by the merging of land surface temperature retrievals from geostationary and polar-orbiting satellites
Multifrequency radar observations of marine clouds during the EPCAPE campaign
LGHAP v2: A global gap-free aerosol optical depth and PM2.5 concentration dataset since 2000 derived via big earth data analytics
Atmospheric and surface observations during the Saint John River Experiment on Cold Season Storms (SAJESS)
Year-long buoy-based observations of the air–sea transition zone off the US west coast
The historical Greenland Climate Network (GC-Net) curated and augmented level-1 dataset
Low-level mixed-phase clouds at the high Arctic site of Ny-Ålesund: a comprehensive long-term dataset of remote sensing observations
CHESS-SCAPE: high-resolution future projections of multiple climate scenarios for the United Kingdom derived from downscaled United Kingdom Climate Projections 2018 regional climate model output
Quality-controlled meteorological datasets from SIGMA automatic weather stations in northwest Greenland, 2012–2020
A dataset of energy, water vapor, and carbon exchange observations in oasis–desert areas from 2012 to 2021 in a typical endorheic basin
Derivation and compilation of lower-atmospheric properties relating to temperature, wind, stability, moisture, and surface radiation budget over the central Arctic sea ice during MOSAiC
An integrated and homogenized global surface solar radiation dataset and its reconstruction based on a convolutional neural network approach
IWIN: the Isfjorden Weather Information Network
Data collected using small uncrewed aircraft system during the TRacking Aerosol Convection Interactions ExpeRiment (TRACER)
A new daily gridded precipitation dataset for the Chinese mainland based on gauge observations
A 16-year global climate data record of total column water vapour generated from OMI observations in the visible blue spectral range
The EUPPBench postprocessing benchmark dataset v1.0
CHELSA-W5E5: daily 1 km meteorological forcing data for climate impact studies
Database of the Italian disdrometer network
East Asia Reanalysis System (EARS)
Data rescue of historical wind observations in Sweden since the 1920s
LegacyClimate 1.0: a dataset of pollen-based climate reconstructions from 2594 Northern Hemisphere sites covering the last 30 kyr and beyond
EURADCLIM: the European climatological high-resolution gauge-adjusted radar precipitation dataset
Radar and ground-level measurements of clouds and precipitation collected during the POPE 2020 campaign at Princess Elisabeth Antarctica
Combined wind lidar and cloud radar for high-resolution wind profiling
An enhanced integrated water vapour dataset from more than 10 000 global ground-based GPS stations in 2020
TPHiPr: a long-term (1979–2020) high-accuracy precipitation dataset (1∕30°, daily) for the Third Pole region based on high-resolution atmospheric modeling and dense observations
The AntAWS dataset: a compilation of Antarctic automatic weather station observations
HiTIC-Monthly: a monthly high spatial resolution (1 km) human thermal index collection over China during 2003–2020
A long-term 1 km monthly near-surface air temperature dataset over the Tibetan glaciers by fusion of station and satellite observations
A global dataset of daily maximum and minimum near-surface air temperature at 1 km resolution over land (2003–2020)
Tropospheric water vapor: a comprehensive high-resolution data collection for the transnational Upper Rhine Graben region
The hourly wind-bias-adjusted precipitation data set from the Environment and Climate Change Canada automated surface observation network (2001–2019)
Enhanced automated meteorological observations at the Canadian Arctic Weather Science (CAWS) supersites
Quality control and correction method for air temperature data from a citizen science weather station network in Leuven, Belgium
Combined high-resolution rainfall and wind data collected for 3 months on a wind farm 110 km southeast of Paris (France)
Sub-mesoscale observations of convective cold pools with a dense station network in Hamburg, Germany
Observational data from uncrewed systems over Southern Great Plains
A global dataset of spatiotemporally seamless daily mean land surface temperatures: generation, validation, and analysis
Finn Burgemeister, Marco Clemens, and Felix Ament
Earth Syst. Sci. Data, 16, 2317–2332, https://doi.org/10.5194/essd-16-2317-2024, https://doi.org/10.5194/essd-16-2317-2024, 2024
Short summary
Short summary
Knowledge of small-scale rainfall variability is needed for hydro-meteorological applications in urban areas. Therefore, we present an open-access data set covering reanalyzed radar reflectivities and rainfall estimates measured by a weather radar at high spatio-temporal resolution in the urban environment of Hamburg between 2013 and 2021. We describe the data reanalysis, outline the measurement’s performance for long time periods, and discuss open issues and limitations of the data set.
Nicola Bodini, Mike Optis, Stephanie Redfern, David Rosencrans, Alex Rybchuk, Julie K. Lundquist, Vincent Pronk, Simon Castagneri, Avi Purkayastha, Caroline Draxl, Raghavendra Krishnamurthy, Ethan Young, Billy Roberts, Evan Rosenlieb, and Walter Musial
Earth Syst. Sci. Data, 16, 1965–2006, https://doi.org/10.5194/essd-16-1965-2024, https://doi.org/10.5194/essd-16-1965-2024, 2024
Short summary
Short summary
This article presents the 2023 National Offshore Wind data set (NOW-23), an updated resource for offshore wind information in the US. It replaces the Wind Integration National Dataset (WIND) Toolkit, offering improved accuracy through advanced weather prediction models. The data underwent regional tuning and validation and can be accessed at no cost.
Longhu Chen, Qinqin Wang, Guofeng Zhu, Xinrui Lin, Dongdong Qiu, Yinying Jiao, Siyu Lu, Rui Li, Gaojia Meng, and Yuhao Wang
Earth Syst. Sci. Data, 16, 1543–1557, https://doi.org/10.5194/essd-16-1543-2024, https://doi.org/10.5194/essd-16-1543-2024, 2024
Short summary
Short summary
We have compiled data regarding stable precipitation isotopes from 842 sampling points throughout the Eurasian continent since 1961, accumulating a total of 51 753 data records. The collected data have undergone pre-processing and statistical analysis. We also analysed the spatiotemporal distribution of stable precipitation isotopes across the Eurasian continent and their interrelationships with meteorological elements.
Valentin Wiener, Marie-Laure Roussel, Christophe Genthon, Étienne Vignon, Jacopo Grazioli, and Alexis Berne
Earth Syst. Sci. Data, 16, 821–836, https://doi.org/10.5194/essd-16-821-2024, https://doi.org/10.5194/essd-16-821-2024, 2024
Short summary
Short summary
This paper presents 7 years of data from a precipitation radar deployed at the Dumont d'Urville station in East Antarctica. The main characteristics of the dataset are outlined in a short statistical study. Interannual and seasonal variability are also investigated. Then, we extensively describe the processing method to retrieve snowfall profiles from the radar data. Lastly, a brief comparison is made with two climate models as an application example of the dataset.
Ling Yuan, Xuelong Chen, Yaoming Ma, Cunbo Han, Binbin Wang, and Weiqiang Ma
Earth Syst. Sci. Data, 16, 775–801, https://doi.org/10.5194/essd-16-775-2024, https://doi.org/10.5194/essd-16-775-2024, 2024
Short summary
Short summary
Accurately monitoring and understanding the spatial–temporal variability of evapotranspiration (ET) components over the Tibetan Plateau (TP) remains difficult. Here, 37 years (1982–2018) of monthly ET component data for the TP was produced, and the data are consistent with measurements. The annual average ET for the TP was about 0.93 (± 0.037) × 103 Gt yr−1. The rate of increase of the ET was around 0.96 mm yr−1. The increase in the ET can be explained by warming and wetting of the climate.
Dominik Rains, Isabel Trigo, Emanuel Dutra, Sofia Ermida, Darren Ghent, Petra Hulsman, Jose Gómez-Dans, and Diego G. Miralles
Earth Syst. Sci. Data, 16, 567–593, https://doi.org/10.5194/essd-16-567-2024, https://doi.org/10.5194/essd-16-567-2024, 2024
Short summary
Short summary
Land surface temperature and surface net radiation are vital inputs for many land surface and hydrological models. However, current remote sensing datasets of these variables come mostly at coarse resolutions, and the few high-resolution datasets available have large gaps due to cloud cover. Here, we present a continuous daily product for both variables across Europe for 2018–2019 obtained by combining observations from geostationary as well as polar-orbiting satellites.
Juan M. Socuellamos, Raquel Rodriguez Monje, Matthew D. Lebsock, Ken B. Cooper, Robert M. Beauchamp, and Arturo Umeyama
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-454, https://doi.org/10.5194/essd-2023-454, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
This paper describes multifrequency radar observations of clouds and precipitation during the EPCAPE campaign. The data sets were obtained from CloudCube, a Ka, W and G-band atmospheric profiling radar, to demonstrate synergies between multifrequency retrievals. This data collection provides a unique opportunity to study hydrometeors with diameters in the millimeter and submillimeter size range, that can be used to better understand the drop size and distribution within clouds and precipitation.
Kaixu Bai, Ke Li, Liuqing Shao, Xinran Li, Chaoshun Liu, Zhengqiang Li, Mingliang Ma, Di Han, Yibing Sun, Zhe Zheng, Ruijie Li, Ni-Bin Chang, and Jianping Guo
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-519, https://doi.org/10.5194/essd-2023-519, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
A global long-term gap-free high-resolution air pollutants dataset (LGHAP v2) was generated to provide spatially contiguous AOD and PM2.5 concentration maps with daily 1-km resolution from 2000 to 2021. The LGHAP v2 dataset has good data accuracies compared against ground AOD and PM2.5 observations, which is an invaluable data base to advance aerosol-related studies and trigger multidisciplinary applications for environmental management, health risk assessment, and climate change analysis.
Hadleigh D. Thompson, Julie M. Thériault, Stephen J. Déry, Ronald E. Stewart, Dominique Boisvert, Lisa Rickard, Nicolas R. Leroux, Matteo Colli, and Vincent Vionnet
Earth Syst. Sci. Data, 15, 5785–5806, https://doi.org/10.5194/essd-15-5785-2023, https://doi.org/10.5194/essd-15-5785-2023, 2023
Short summary
Short summary
The Saint John River experiment on Cold Season Storms was conducted in northwest New Brunswick, Canada, to investigate the types of precipitation that can lead to ice jams and flooding along the river. We deployed meteorological instruments, took precipitation measurements and photographs of snowflakes, and launched weather balloons. These data will help us to better understand the atmospheric conditions that can affect local communities and townships downstream during the spring melt season.
Raghavendra Krishnamurthy, Gabriel García Medina, Brian Gaudet, William I. Gustafson Jr., Evgueni I. Kassianov, Jinliang Liu, Rob K. Newsom, Lindsay M. Sheridan, and Alicia M. Mahon
Earth Syst. Sci. Data, 15, 5667–5699, https://doi.org/10.5194/essd-15-5667-2023, https://doi.org/10.5194/essd-15-5667-2023, 2023
Short summary
Short summary
Our understanding and ability to observe and model air–sea processes has been identified as a principal limitation to our ability to predict future weather. Few observations exist offshore along the coast of California. To improve our understanding of the air–sea transition zone and support the wind energy industry, two buoys with state-of-the-art equipment were deployed for 1 year. In this article, we present details of the post-processing, algorithms, and analyses.
Baptiste Vandecrux, Jason E. Box, Andreas P. Ahlstrøm, Signe B. Andersen, Nicolas Bayou, William T. Colgan, Nicolas J. Cullen, Robert S. Fausto, Dominik Haas-Artho, Achim Heilig, Derek A. Houtz, Penelope How, Ionut Iosifescu Enescu, Nanna B. Karlsson, Rebecca Kurup Buchholz, Kenneth D. Mankoff, Daniel McGrath, Noah P. Molotch, Bianca Perren, Maiken K. Revheim, Anja Rutishauser, Kevin Sampson, Martin Schneebeli, Sandy Starkweather, Simon Steffen, Jeff Weber, Patrick J. Wright, Henry Jay Zwally, and Konrad Steffen
Earth Syst. Sci. Data, 15, 5467–5489, https://doi.org/10.5194/essd-15-5467-2023, https://doi.org/10.5194/essd-15-5467-2023, 2023
Short summary
Short summary
The Greenland Climate Network (GC-Net) comprises stations that have been monitoring the weather on the Greenland Ice Sheet for over 30 years. These stations are being replaced by newer ones maintained by the Geological Survey of Denmark and Greenland (GEUS). The historical data were reprocessed to improve their quality, and key information about the weather stations has been compiled. This augmented dataset is available at https://doi.org/10.22008/FK2/VVXGUT (Steffen et al., 2022).
Giovanni Chellini, Rosa Gierens, Kerstin Ebell, Theresa Kiszler, Pavel Krobot, Alexander Myagkov, Vera Schemann, and Stefan Kneifel
Earth Syst. Sci. Data, 15, 5427–5448, https://doi.org/10.5194/essd-15-5427-2023, https://doi.org/10.5194/essd-15-5427-2023, 2023
Short summary
Short summary
We present a comprehensive quality-controlled dataset of remote sensing observations of low-level mixed-phase clouds (LLMPCs) taken at the high Arctic site of Ny-Ålesund, Svalbard, Norway. LLMPCs occur frequently in the Arctic region, and substantially warm the surface. However, our understanding of microphysical processes in these clouds is incomplete. This dataset includes a comprehensive set of variables which allow for extensive investigation of such processes in LLMPCs at the site.
Emma L. Robinson, Chris Huntingford, Valyaveetil Shamsudheen Semeena, and James M. Bullock
Earth Syst. Sci. Data, 15, 5371–5401, https://doi.org/10.5194/essd-15-5371-2023, https://doi.org/10.5194/essd-15-5371-2023, 2023
Short summary
Short summary
CHESS-SCAPE is a suite of high-resolution climate projections for the UK to 2080, derived from United Kingdom Climate Projections 2018 (UKCP18), designed to support climate impact modelling. It contains four realisations of four scenarios of future greenhouse gas levels (RCP2.6, 4.5, 6.0 and 8.5), with and without bias correction to historical data. The variables are available at 1 km resolution and a daily time step, with monthly, seasonal and annual means and 20-year mean-monthly time slices.
Motoshi Nishimura, Teruo Aoki, Masashi Niwano, Sumito Matoba, Tomonori Tanikawa, Tetsuhide Yamasaki, Satoru Yamaguchi, and Koji Fujita
Earth Syst. Sci. Data, 15, 5207–5226, https://doi.org/10.5194/essd-15-5207-2023, https://doi.org/10.5194/essd-15-5207-2023, 2023
Short summary
Short summary
We presented the method of data quality checks and the dataset for two ground weather observations in northwest Greenland. We found that the warm and clear weather conditions in the 2015, 2019, and 2020 summers caused the snowmelt and the decline in surface reflectance of solar radiation at a low-elevated site (SIGMA-B; 944 m), but those were not seen at the high-elevated site (SIGMA-A; 1490 m). We hope that our data management method and findings will help climate scientists.
Shaomin Liu, Ziwei Xu, Tao Che, Xin Li, Tongren Xu, Zhiguo Ren, Yang Zhang, Junlei Tan, Lisheng Song, Ji Zhou, Zhongli Zhu, Xiaofan Yang, Rui Liu, and Yanfei Ma
Earth Syst. Sci. Data, 15, 4959–4981, https://doi.org/10.5194/essd-15-4959-2023, https://doi.org/10.5194/essd-15-4959-2023, 2023
Short summary
Short summary
We present a suite of observational datasets from artificial and natural oases–desert systems that consist of long-term turbulent flux and auxiliary data, including hydrometeorological, vegetation, and soil parameters, from 2012 to 2021. We confirm that the 10-year, long-term dataset presented in this study is of high quality with few missing data, and we believe that the data will support ecological security and sustainable development in oasis–desert areas.
Gina C. Jozef, Robert Klingel, John J. Cassano, Björn Maronga, Gijs de Boer, Sandro Dahlke, and Christopher J. Cox
Earth Syst. Sci. Data, 15, 4983–4995, https://doi.org/10.5194/essd-15-4983-2023, https://doi.org/10.5194/essd-15-4983-2023, 2023
Short summary
Short summary
Observations from the MOSAiC expedition relating to lower-atmospheric temperature, wind, stability, moisture, and surface radiation budget from radiosondes, a meteorological tower, radiation station, and ceilometer were compiled to create a dataset which describes the thermodynamic and kinematic state of the central Arctic lower atmosphere between October 2019 and September 2020. This paper describes the methods used to develop this lower-atmospheric properties dataset.
Boyang Jiao, Yucheng Su, Qingxiang Li, Veronica Manara, and Martin Wild
Earth Syst. Sci. Data, 15, 4519–4535, https://doi.org/10.5194/essd-15-4519-2023, https://doi.org/10.5194/essd-15-4519-2023, 2023
Short summary
Short summary
This paper develops an observational integrated and homogenized global-terrestrial (except for Antarctica) SSRIH station. This is interpolated into a 5° × 5° SSRIH grid and reconstructed into a long-term (1955–2018) global land (except for Antarctica) 5° × 2.5° SSR anomaly dataset (SSRIH20CR) by an improved partial convolutional neural network deep-learning method. SSRIH20CR yields trends of −1.276 W m−2 per decade over the dimming period and 0.697 W m−2 per decade over the brightening period.
Lukas Frank, Marius Opsanger Jonassen, Teresa Remes, Florina Roana Schalamon, and Agnes Stenlund
Earth Syst. Sci. Data, 15, 4219–4234, https://doi.org/10.5194/essd-15-4219-2023, https://doi.org/10.5194/essd-15-4219-2023, 2023
Short summary
Short summary
The Isfjorden Weather Information Network (IWIN) provides continuous meteorological near-surface observations from Isfjorden in Svalbard. The network combines permanent automatic weather stations on lighthouses along the coast line with mobile stations on board small tourist cruise ships regularly trafficking the fjord during spring to autumn. All data are available online in near-real time. Besides their scientific value, IWIN data crucially enhance the safety of field activities in the region.
Francesca Lappin, Gijs de Boer, Petra Klein, Jonathan Hamilton, Michelle Spencer, Radiance Calmer, Antonio R. Segales, Michael Rhodes, Tyler M. Bell, Justin Buchli, Kelsey Britt, Elizabeth Asher, Isaac Medina, Brian Butterworth, Leia Otterstatter, Madison Ritsch, Bryony Puxley, Angelina Miller, Arianna Jordan, Ceu Gomez-Faulk, Elizabeth Smith, Steve Borenstein, Troy Thornberry, Brian Argrow, and Elizabeth Pillar-Little
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-371, https://doi.org/10.5194/essd-2023-371, 2023
Revised manuscript accepted for ESSD
Short summary
Short summary
This article provides an overview of the lower atmospheric dataset collected by two uncrewed aerial systems near the Gulf of Mexico coastline south of Houston, TX, USA, as a part of the TRACER campaign. The data were collected through boundary layer transitions, sea breeze circulations, and in the pre- and near-storm environment to understand how these processes influence the coastal environment.
Jingya Han, Chiyuan Miao, Jiaojiao Gou, Haiyan Zheng, Qi Zhang, and Xiaoying Guo
Earth Syst. Sci. Data, 15, 3147–3161, https://doi.org/10.5194/essd-15-3147-2023, https://doi.org/10.5194/essd-15-3147-2023, 2023
Short summary
Short summary
Constructing a high-quality, long-term daily precipitation dataset is essential to current hydrometeorology research. This study aims to construct a long-term daily precipitation dataset with different spatial resolutions based on 2839 gauge observations. The constructed precipitation dataset shows reliable quality compared with the other available precipitation products and is expected to facilitate the advancement of drought monitoring, flood forecasting, and hydrological modeling.
Christian Borger, Steffen Beirle, and Thomas Wagner
Earth Syst. Sci. Data, 15, 3023–3049, https://doi.org/10.5194/essd-15-3023-2023, https://doi.org/10.5194/essd-15-3023-2023, 2023
Short summary
Short summary
This study presents a long-term data set of monthly mean total column water vapour (TCWV) based on measurements of the Ozone Monitoring Instrument (OMI) covering the time range from January 2005 to December 2020. We describe how the TCWV values are retrieved from UV–Vis satellite spectra and demonstrate that the OMI TCWV data set is in good agreement with various different reference data sets. Moreover, we also show that it fulfills typical stability requirements for climate data records.
Jonathan Demaeyer, Jonas Bhend, Sebastian Lerch, Cristina Primo, Bert Van Schaeybroeck, Aitor Atencia, Zied Ben Bouallègue, Jieyu Chen, Markus Dabernig, Gavin Evans, Jana Faganeli Pucer, Ben Hooper, Nina Horat, David Jobst, Janko Merše, Peter Mlakar, Annette Möller, Olivier Mestre, Maxime Taillardat, and Stéphane Vannitsem
Earth Syst. Sci. Data, 15, 2635–2653, https://doi.org/10.5194/essd-15-2635-2023, https://doi.org/10.5194/essd-15-2635-2023, 2023
Short summary
Short summary
A benchmark dataset is proposed to compare different statistical postprocessing methods used in forecasting centers to properly calibrate ensemble weather forecasts. This dataset is based on ensemble forecasts covering a portion of central Europe and includes the corresponding observations. Examples on how to download and use the data are provided, a set of evaluation methods is proposed, and a first benchmark of several methods for the correction of 2 m temperature forecasts is performed.
Dirk Nikolaus Karger, Stefan Lange, Chantal Hari, Christopher P. O. Reyer, Olaf Conrad, Niklaus E. Zimmermann, and Katja Frieler
Earth Syst. Sci. Data, 15, 2445–2464, https://doi.org/10.5194/essd-15-2445-2023, https://doi.org/10.5194/essd-15-2445-2023, 2023
Short summary
Short summary
We present the first 1 km, daily, global climate dataset for climate impact studies. We show that the high-resolution data have a decreased bias and higher correlation with measurements from meteorological stations than coarser data. The dataset will be of value for a wide range of climate change impact studies both at global and regional level that benefit from using a consistent global dataset.
Elisa Adirosi, Federico Porcù, Mario Montopoli, Luca Baldini, Alessandro Bracci, Vincenzo Capozzi, Clizia Annella, Giorgio Budillon, Edoardo Bucchignani, Alessandra Lucia Zollo, Orietta Cazzuli, Giulio Camisani, Renzo Bechini, Roberto Cremonini, Andrea Antonini, Alberto Ortolani, Samantha Melani, Paolo Valisa, and Simone Scapin
Earth Syst. Sci. Data, 15, 2417–2429, https://doi.org/10.5194/essd-15-2417-2023, https://doi.org/10.5194/essd-15-2417-2023, 2023
Short summary
Short summary
The paper describes the database of 1 min drop size distribution (DSD) of atmospheric precipitation collected by the Italian disdrometer network over the last 10 years. These data are useful for several applications that range from climatological, meteorological and hydrological uses to telecommunications, agriculture and conservation of cultural heritage exposed to precipitation. Descriptions of the processing and of the database organization, along with some examples, are provided.
Jinfang Yin, Xudong Liang, Yanxin Xie, Feng Li, Kaixi Hu, Lijuan Cao, Feng Chen, Haibo Zou, Feng Zhu, Xin Sun, Jianjun Xu, Geli Wang, Ying Zhao, and Juanjuan Liu
Earth Syst. Sci. Data, 15, 2329–2346, https://doi.org/10.5194/essd-15-2329-2023, https://doi.org/10.5194/essd-15-2329-2023, 2023
Short summary
Short summary
A collection of regional reanalysis datasets has been produced. However, little attention has been paid to East Asia, and there are no long-term, physically consistent regional reanalysis data available. The East Asia Reanalysis System was developed using the WRF model and GSI data assimilation system. A 39-year (1980–2018) reanalysis dataset is available for the East Asia region, at a high temporal (of 3 h) and spatial resolution (of 12 km), for mesoscale weather and regional climate studies.
John Erik Engström, Lennart Wern, Sverker Hellström, Erik Kjellström, Chunlüe Zhou, Deliang Chen, and Cesar Azorin-Molina
Earth Syst. Sci. Data, 15, 2259–2277, https://doi.org/10.5194/essd-15-2259-2023, https://doi.org/10.5194/essd-15-2259-2023, 2023
Short summary
Short summary
Newly digitized wind speed observations provide data from the time period from around 1920 to the present, enveloping one full century of wind measurements. The results of this work enable the investigation of the historical variability and trends in surface wind speed in Sweden for
the last century.
Ulrike Herzschuh, Thomas Böhmer, Chenzhi Li, Manuel Chevalier, Raphaël Hébert, Anne Dallmeyer, Xianyong Cao, Nancy H. Bigelow, Larisa Nazarova, Elena Y. Novenko, Jungjae Park, Odile Peyron, Natalia A. Rudaya, Frank Schlütz, Lyudmila S. Shumilovskikh, Pavel E. Tarasov, Yongbo Wang, Ruilin Wen, Qinghai Xu, and Zhuo Zheng
Earth Syst. Sci. Data, 15, 2235–2258, https://doi.org/10.5194/essd-15-2235-2023, https://doi.org/10.5194/essd-15-2235-2023, 2023
Short summary
Short summary
Climate reconstruction from proxy data can help evaluate climate models. We present pollen-based reconstructions of mean July temperature, mean annual temperature, and annual precipitation from 2594 pollen records from the Northern Hemisphere, using three reconstruction methods (WA-PLS, WA-PLS_tailored, and MAT). Since no global or hemispheric synthesis of quantitative precipitation changes are available for the Holocene so far, this dataset will be of great value to the geoscientific community.
Aart Overeem, Else van den Besselaar, Gerard van der Schrier, Jan Fokke Meirink, Emiel van der Plas, and Hidde Leijnse
Earth Syst. Sci. Data, 15, 1441–1464, https://doi.org/10.5194/essd-15-1441-2023, https://doi.org/10.5194/essd-15-1441-2023, 2023
Short summary
Short summary
EURADCLIM is a new precipitation dataset covering a large part of Europe. It is based on weather radar data to provide local precipitation information every hour and combined with rain gauge data to obtain good precipitation estimates. EURADCLIM provides a much better reference for validation of weather model output and satellite precipitation datasets. It also allows for climate monitoring and better evaluation of extreme precipitation events and their impact (landslides, flooding).
Alfonso Ferrone and Alexis Berne
Earth Syst. Sci. Data, 15, 1115–1132, https://doi.org/10.5194/essd-15-1115-2023, https://doi.org/10.5194/essd-15-1115-2023, 2023
Short summary
Short summary
This article presents the datasets collected between November 2019 and February 2020 in the vicinity of the Belgian research base Princess Elisabeth Antarctica. Five meteorological radars, a multi-angle snowflake camera, three weather stations, and two radiometers have been deployed at five sites, up to a maximum distance of 30 km from the base. Their varied locations allow the study of spatial variability in snowfall and its interaction with the complex terrain in the region.
José Dias Neto, Louise Nuijens, Christine Unal, and Steven Knoop
Earth Syst. Sci. Data, 15, 769–789, https://doi.org/10.5194/essd-15-769-2023, https://doi.org/10.5194/essd-15-769-2023, 2023
Short summary
Short summary
This paper describes a dataset from a novel experimental setup to retrieve wind speed and direction profiles, combining cloud radars and wind lidar. This setup allows retrieving profiles from near the surface to the top of clouds. The field campaign occurred in Cabauw, the Netherlands, between September 13th and October 3rd 2021. This paper also provides examples of applications of this dataset (e.g. studying atmospheric turbulence, validating numerical atmospheric models).
Peng Yuan, Geoffrey Blewitt, Corné Kreemer, William C. Hammond, Donald Argus, Xungang Yin, Roeland Van Malderen, Michael Mayer, Weiping Jiang, Joseph Awange, and Hansjörg Kutterer
Earth Syst. Sci. Data, 15, 723–743, https://doi.org/10.5194/essd-15-723-2023, https://doi.org/10.5194/essd-15-723-2023, 2023
Short summary
Short summary
We developed a 5 min global integrated water vapour (IWV) product from 12 552 ground-based GPS stations in 2020. It contains more than 1 billion IWV estimates. The dataset is an enhanced version of the existing operational GPS IWV dataset from the Nevada Geodetic Laboratory. The enhancement is reached by using accurate meteorological information from ERA5 for the GPS IWV retrieval with a significantly higher spatiotemporal resolution. The dataset is recommended for high-accuracy applications.
Yaozhi Jiang, Kun Yang, Youcun Qi, Xu Zhou, Jie He, Hui Lu, Xin Li, Yingying Chen, Xiaodong Li, Bingrong Zhou, Ali Mamtimin, Changkun Shao, Xiaogang Ma, Jiaxin Tian, and Jianhong Zhou
Earth Syst. Sci. Data, 15, 621–638, https://doi.org/10.5194/essd-15-621-2023, https://doi.org/10.5194/essd-15-621-2023, 2023
Short summary
Short summary
Our work produces a long-term (1979–2020) high-resolution (1/30°, daily) precipitation dataset for the Third Pole (TP) region by merging an advanced atmospheric simulation with high-density rain gauge (more than 9000) observations. Validation shows that the produced dataset performs better than the currently widely used precipitation datasets in the TP. This dataset can be used for hydrological, meteorological and ecological studies in the TP.
Yetang Wang, Xueying Zhang, Wentao Ning, Matthew A. Lazzara, Minghu Ding, Carleen H. Reijmer, Paul C. J. P. Smeets, Paolo Grigioni, Petra Heil, Elizabeth R. Thomas, David Mikolajczyk, Lee J. Welhouse, Linda M. Keller, Zhaosheng Zhai, Yuqi Sun, and Shugui Hou
Earth Syst. Sci. Data, 15, 411–429, https://doi.org/10.5194/essd-15-411-2023, https://doi.org/10.5194/essd-15-411-2023, 2023
Short summary
Short summary
Here we construct a new database of Antarctic automatic weather station (AWS) meteorological records, which is quality-controlled by restrictive criteria. This dataset compiled all available Antarctic AWS observations, and its resolutions are 3-hourly, daily and monthly, which is very useful for quantifying spatiotemporal variability in weather conditions. Furthermore, this compilation will be used to estimate the performance of the regional climate models or meteorological reanalysis products.
Hui Zhang, Ming Luo, Yongquan Zhao, Lijie Lin, Erjia Ge, Yuanjian Yang, Guicai Ning, Jing Cong, Zhaoliang Zeng, Ke Gui, Jing Li, Ting On Chan, Xiang Li, Sijia Wu, Peng Wang, and Xiaoyu Wang
Earth Syst. Sci. Data, 15, 359–381, https://doi.org/10.5194/essd-15-359-2023, https://doi.org/10.5194/essd-15-359-2023, 2023
Short summary
Short summary
We generate the first monthly high-resolution (1 km) human thermal index collection (HiTIC-Monthly) in China over 2003–2020, in which 12 human-perceived temperature indices are generated by LightGBM. The HiTIC-Monthly dataset has a high accuracy (R2 = 0.996, RMSE = 0.693 °C, MAE = 0.512 °C) and describes explicit spatial variations for fine-scale studies. It is freely available at https://zenodo.org/record/6895533 and https://data.tpdc.ac.cn/disallow/036e67b7-7a3a-4229-956f-40b8cd11871d.
Jun Qin, Weihao Pan, Min He, Ning Lu, Ling Yao, Hou Jiang, and Chenghu Zhou
Earth Syst. Sci. Data, 15, 331–344, https://doi.org/10.5194/essd-15-331-2023, https://doi.org/10.5194/essd-15-331-2023, 2023
Short summary
Short summary
To enrich a glacial surface air temperature (SAT) product of a long time series, an ensemble learning model is constructed to estimate monthly SATs from satellite land surface temperatures at a spatial resolution of 1 km, and long-term glacial SATs from 1961 to 2020 are reconstructed using a Bayesian linear regression. This product reveals the overall warming trend and the spatial heterogeneity of warming on TP glaciers and helps to monitor glacier warming, analyze glacier evolution, etc.
Tao Zhang, Yuyu Zhou, Kaiguang Zhao, Zhengyuan Zhu, Gang Chen, Jia Hu, and Li Wang
Earth Syst. Sci. Data, 14, 5637–5649, https://doi.org/10.5194/essd-14-5637-2022, https://doi.org/10.5194/essd-14-5637-2022, 2022
Short summary
Short summary
We generated a global 1 km daily maximum and minimum near-surface air temperature (Tmax and Tmin) dataset (2003–2020) using a novel statistical model. The average root mean square errors ranged from 1.20 to 2.44 °C for Tmax and 1.69 to 2.39 °C for Tmin. The gridded global air temperature dataset is of great use in a variety of studies such as the urban heat island phenomenon, hydrological modeling, and epidemic forecasting.
Benjamin Fersch, Andreas Wagner, Bettina Kamm, Endrit Shehaj, Andreas Schenk, Peng Yuan, Alain Geiger, Gregor Moeller, Bernhard Heck, Stefan Hinz, Hansjörg Kutterer, and Harald Kunstmann
Earth Syst. Sci. Data, 14, 5287–5307, https://doi.org/10.5194/essd-14-5287-2022, https://doi.org/10.5194/essd-14-5287-2022, 2022
Short summary
Short summary
In this study, a comprehensive multi-disciplinary dataset for tropospheric water vapor was developed. Geodetic, photogrammetric, and atmospheric modeling and data fusion techniques were used to obtain maps of water vapor in a high spatial and temporal resolution. It could be shown that regional weather simulations for different seasons benefit from assimilating these maps and that the combination of the different observation techniques led to positive synergies.
Craig D. Smith, Eva Mekis, Megan Hartwell, and Amber Ross
Earth Syst. Sci. Data, 14, 5253–5265, https://doi.org/10.5194/essd-14-5253-2022, https://doi.org/10.5194/essd-14-5253-2022, 2022
Short summary
Short summary
It is well understood that precipitation gauges underestimate the measurement of solid precipitation (snow) as a result of systematic bias caused by wind. Relationships between the wind speed and gauge catch efficiency of solid precipitation have been previously established and are applied to the hourly precipitation measurements made between 2001 and 2019 in the automated Environment and Climate Change Canada observation network. The adjusted data are available for download and use.
Zen Mariani, Laura Huang, Robert Crawford, Jean-Pierre Blanchet, Shannon Hicks-Jalali, Eva Mekis, Ludovick Pelletier, Peter Rodriguez, and Kevin Strawbridge
Earth Syst. Sci. Data, 14, 4995–5017, https://doi.org/10.5194/essd-14-4995-2022, https://doi.org/10.5194/essd-14-4995-2022, 2022
Short summary
Short summary
Environment and Climate Change Canada (ECCC) commissioned two supersites in Iqaluit (64°N, 69°W) and Whitehorse (61°N, 135°W) to provide new and enhanced automated and continuous altitude-resolved meteorological observations as part of the Canadian Arctic Weather Science (CAWS) project. These observations are being used to test new technologies, provide recommendations to the optimal Arctic observing system, and evaluate and improve the performance of numerical weather forecast systems.
Eva Beele, Maarten Reyniers, Raf Aerts, and Ben Somers
Earth Syst. Sci. Data, 14, 4681–4717, https://doi.org/10.5194/essd-14-4681-2022, https://doi.org/10.5194/essd-14-4681-2022, 2022
Short summary
Short summary
This paper presents crowdsourced data from the Leuven.cool network, a citizen science network of around 100 low-cost weather stations distributed across Leuven, Belgium. The temperature data have undergone a quality control (QC) and correction procedure. The procedure consists of three levels that remove implausible measurements while also correcting for between-station and station-specific temperature biases.
Auguste Gires, Jerry Jose, Ioulia Tchiguirinskaia, and Daniel Schertzer
Earth Syst. Sci. Data, 14, 3807–3819, https://doi.org/10.5194/essd-14-3807-2022, https://doi.org/10.5194/essd-14-3807-2022, 2022
Short summary
Short summary
The Hydrology Meteorology and Complexity laboratory of École des Ponts ParisTech (https://hmco.enpc.fr) has made a data set of high-resolution atmospheric measurements (rainfall, wind, temperature, pressure, and humidity) available. It comes from a campaign carried out on a meteorological mast located on a wind farm in the framework of the Rainfall Wind Turbine or Turbulence project (RW-Turb; supported by the French National Research Agency – ANR-19-CE05-0022).
Bastian Kirsch, Cathy Hohenegger, Daniel Klocke, Rainer Senke, Michael Offermann, and Felix Ament
Earth Syst. Sci. Data, 14, 3531–3548, https://doi.org/10.5194/essd-14-3531-2022, https://doi.org/10.5194/essd-14-3531-2022, 2022
Short summary
Short summary
Conventional observation networks are too coarse to resolve the horizontal structure of kilometer-scale atmospheric processes. We present the FESST@HH field experiment that took place in Hamburg (Germany) during summer 2020 and featured a dense network of 103 custom-built, low-cost weather stations. The data set is capable of providing new insights into the structure of convective cold pools and the nocturnal urban heat island and variations of local temperature fluctuations.
Fan Mei, Mikhail S. Pekour, Darielle Dexheimer, Gijs de Boer, RaeAnn Cook, Jason Tomlinson, Beat Schmid, Lexie A. Goldberger, Rob Newsom, and Jerome D. Fast
Earth Syst. Sci. Data, 14, 3423–3438, https://doi.org/10.5194/essd-14-3423-2022, https://doi.org/10.5194/essd-14-3423-2022, 2022
Short summary
Short summary
This work focuses on an expanding number of data sets observed using ARM TBS (133 flights) and UAS (seven flights) platforms by the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility. These data streams provide new perspectives on spatial variability of atmospheric and surface parameters, helping to address critical science questions in Earth system science research, such as the aerosol–cloud interaction in the boundary layer.
Falu Hong, Wenfeng Zhan, Frank-M. Göttsche, Zihan Liu, Pan Dong, Huyan Fu, Fan Huang, and Xiaodong Zhang
Earth Syst. Sci. Data, 14, 3091–3113, https://doi.org/10.5194/essd-14-3091-2022, https://doi.org/10.5194/essd-14-3091-2022, 2022
Short summary
Short summary
Daily mean land surface temperature (LST) acquired from satellite thermal sensors is crucial for various applications such as global and regional climate change analysis. This study proposed a framework to generate global spatiotemporally seamless daily mean LST products (2003–2019). Validations show that the products outperform the traditional method with satisfying accuracy. Our further analysis reveals that the LST-based global land surface warming rate is 0.029 K yr−1 from 2003 to 2019.
Cited articles
Akkermans, T. and Clerbaux, N.: Narrowband-to-broadband conversions for top-of-atmosphere reflectance from the Advanced Very High Resolution Radiometer (AVHRR), Remote Sens., 12, 305, https://doi.org/10.3390/rs12020305 , 2020.
Akkermans, T. and Clerbaux, N.: Retrieval of Daily Mean Top-of-Atmosphere Reflected Solar Flux Using the Advanced Very High Resolution Radiometer (AVHRR) Instruments, Remote Sens., 13, 3695, https://doi.org/10.3390/rs13183695, 2021.
Baum, B. A., Yang, P., Heymsfield, A. J., Schmitt, C. G., Xie, Y., Bansemer, A., Hu, Y.-X., and Zhang, Z.: Improvements in shortwave bulk scattering and absorption models for the remote sensing of ice clouds, J. Appl. Meteorol. Clim., 50, 1037–1056, https://doi.org/10.1175/2010JAMC2608.1, 2011.
Bodas-Salcedo, A., Webb, M. J., Bony, S., Chepfer, H., Dufresne, J.-L., Klein, S. A., Zhang, Y., Marchand, R., Haynes, J. M., Pincus, R., and John, V. O.: COSP: satellite simulation software for model assessment, B. Am. Meteorol. Soc., 92, 1023–1043, https://doi.org/10.1175/2011BAMS2856.1, 2011.
Brown, C. F., Brumby, S. P., Guzder-Williams, B., Birch, T., Hyde, S. B., Mazzariello, J., Czerwinski, W., Pasquarella, V. J., Haertel, R., Ilyushchenko, S., Schwehr, K., Weisse, M., Stolle, F., Hanson, C., Guinan, O., Moore, R. and Tait, A. M.: Dynamic World, Near real-time global 10 m land use land cover mapping, Sci. Data, 9, 1–17, 2022.
CALIPSO Science Team: CALIPSO/CALIOP Level 2, Lidar 5 km Cloud Layer Product, version 4.20, Hampton, VA, USA: NASA Atmospheric Science Data Center (ASDC), https://doi.org/10.5067/CALIOP/CALIPSO/LID_L2_05KMCLAY-STANDARD-V4-20 (last access: 27 December 2022), 2021.
Canty, T., Mascioli, N. R., Smarte, M. D., and Salawitch, R. J.: An empirical model of global climate – Part 1: A critical evaluation of volcanic cooling, Atmos. Chem. Phys., 13, 3997–4031, https://doi.org/10.5194/acp-13-3997-2013, 2013.
Cao, Y., Liang, S., Chen, X., and He, T.: Assessment of sea ice albedo radiative forcing and feedback over the Northern Hemisphere from 1982 to 2009 using satellite and reanalysis data, J. Climate, 28, 1248–1259, 2015.
Clerbaux, N., Russell, J. E., Dewitte, S., Bertrand, C., Caprion, D., De Paepe, B., Sotelino, L. G., Ipe, A., Bantges, R., and Brindley, H. E.: Comparison of GERB instantaneous radiance and flux products with CERES Edition-2 data, Remote Sens. Environ., 113, 102–114, 2009.
Clerbaux, N., Akkermans, T., Baudrez, E., Velazquez Blazquez, A., Moutier, W., Moreels, J., and Aebi, C.: The climate monitoring SAF outgoing longwave radiation from AVHRR, Remote Sens., 12, 929, https://doi.org/10.3390/rs12060929 , 2020.
Cracknell, A. P.: The Advanced Very High Resolution Radiometer (AVHRR), Taylor & Francis Ltd, 556 pp., ISBN 9780748402090, 1997.
De Haan, J. F., Bosma, P., and Hovenier, J. W.: The adding method for multiple scattering calculations of polarized light, Astron. Astrophys., 183, 371–391, 1987.
Devasthale, A. and Karlsson, K.-G.: Decadal Stability and Trends in the Global Cloud Amount and Cloud Top Temperature in the Satellite-Based Climate Data Records, Remote Sens., 15, 3819, https://doi.org/10.3390/rs15153819, 2023.
Diekmann, F. J., Happ, S., Rieland, M., Benesch, W., Czeplack, G., and Kasten, F.: An operational estimate of global solar irradiance at ground level from METEOSAT data: results from 1985 to 1987, Meteorol. Rdsch., 41, 65–79, 1988.
Doelling, D. R., Loeb, N. G., Keyes, D. F., Nordeen, M. L., Morstad, D., Nguyen, C., Wielicki, B., Young, D. F., and Sun, M.: Geostationary enhanced temporal interpolation for CERES flux products, J. Atmos. Ocean. Tech., 30, 1072–1090, 2013.
Driemel, A., Augustine, J., Behrens, K., Colle, S., Cox, C., Cuevas-Agulló, E., Denn, F. M., Duprat, T., Fukuda, M., Grobe, H., Haeffelin, M., Hodges, G., Hyett, N., Ijima, O., Kallis, A., Knap, W., Kustov, V., Long, C. N., Longenecker, D., Lupi, A., Maturilli, M., Mimouni, M., Ntsangwane, L., Ogihara, H., Olano, X., Olefs, M., Omori, M., Passamani, L., Pereira, E. B., Schmithüsen, H., Schumacher, S., Sieger, R., Tamlyn, J., Vogt, R., Vuilleumier, L., Xia, X., Ohmura, A., and König-Langlo, G.: Baseline Surface Radiation Network (BSRN): structure and data description (1992–2017), Earth Syst. Sci. Data, 10, 1491–1501, https://doi.org/10.5194/essd-10-1491-2018, 2018.
Dybbroe, A., Karlsson, K.-G., and Thoss, A.: NWCSAF AVHRR Cloud Detection and Analysis Using Dynamic Thresholds and Radiative Transfer Modelling. Part I: Algorithm Description, J. Appl. Meteor., 44, 39–54, https://doi.org/10.1175/JAM-2188.1, 2005.
Eliasson, S., Karlsson, K.-G., and Willén, U.: A simulator for the CLARA-A2 cloud climate data record and its application to assess EC-Earth polar cloudiness, Geosci. Model Dev., 13, 297–314, https://doi.org/10.5194/gmd-13-297-2020, 2020.
Ellingson, R. G.: Surface Longwave Fluxes from satellite observations: A critical review, Remore Sens. Environ., 51, 89–97, 1995.
EUMETSAT: AVHRR Fundamental Data Record – Release 1 – Multimission, European Organisation for the Exploitation of Meteorological Satellites [data set], https://doi.org/10.15770/EUM_SEC_CLM_0060, 2023a.
EUMETSAT: PyGAC AVHRR FDR Release 1 Validation Report, EUM/OPS/DOC/22/1282616, version v1F, 2023b.
Fausto, R. S., van As, D., Mankoff, K. D., Vandecrux, B., Citterio, M., Ahlstrøm, A. P., Andersen, S. B., Colgan, W., Karlsson, N. B., Kjeldsen, K. K., Korsgaard, N. J., Larsen, S. H., Nielsen, S., Pedersen, A. Ø., Shields, C. L., Solgaard, A. M., and Box, J. E.: Programme for Monitoring of the Greenland Ice Sheet (PROMICE) automatic weather station data, Earth Syst. Sci. Data, 13, 3819–3845, https://doi.org/10.5194/essd-13-3819-2021, 2021.
Fiedler, S., Kinne, S., Huang, W. T. K., Räisänen, P., O'Donnell, D., Bellouin, N., Stier, P., Merikanto, J., van Noije, T., Makkonen, R., and Lohmann, U.: Anthropogenic aerosol forcing – insights from multiple estimates from aerosol-climate models with reduced complexity, Atmos. Chem. Phys., 19, 6821–6841, https://doi.org/10.5194/acp-19-6821-2019, 2019a.
Fiedler, S., Stevens, B., Gidden, M., Smith, S. J., Riahi, K., and van Vuuren, D.: First forcing estimates from the future CMIP6 scenarios of anthropogenic aerosol optical properties and an associated Twomey effect, Geosci. Model Dev., 12, 989–1007, https://doi.org/10.5194/gmd-12-989-2019, 2019b.
Foster, M. J., Phillips, C., Heidinger, A. K., Borbas, E. E., Li, Y., Menzel, W. P., Walther, A., and Weisz, E.: PATMOS-x Version 6.0: 40 Years of Merged AVHRR and HIRS Global Cloud Data, J. Climate, 36, 1143–1160, https://doi.org/10.1175/JCLI-D-22-0147.1, 2023.
Håkansson, N., Adok, C., Thoss, A., Scheirer, R., and Hörnquist, S.: Neural network cloud top pressure and height for MODIS, Atmos. Meas. Tech., 11, 3177–3196, https://doi.org/10.5194/amt-11-3177-2018, 2018.
Heidinger, A. K.: Climate Algorithm Theoretical Basis Document (C-ATBD): Fundamental Climate Data Record (CDR) of Reflectance from AVHRR Bands 1, 2 and 3a, CDR Program Document Number CDRP-ATBD-0184, Revision 2, 2018.
Heidinger, A. K., Straka, W. C., Molling, C. C., Sullivan, J. T., and Wu, X. Q.: Deriving an inter-sensor consistent calibration for the AVHRR solar reflectance data record, Int. J. Rem. Sens., 31, 6493–6517, 2010.
Heidinger, A. K., Foster, J. M., Walther, A., and Zhao, X.: The Pathfinder Atmospheres – Extended AVHRR Climate Dataset, B. Am. Meteorol. Soc., 95, 909–922, https://doi.org/10.1175/BAMS-D-12-00246.1, 2014.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz‐Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Holm, E., Janiskova, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J. N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, 2020.
Hobbs, P. V. and Rangno, A. L.: Ice Particle Concentrations in Clouds, J. Atmos. Sci., 42, 2523–2549, 1985.
Hofmann, M. and Seckmeyer, G.: A new model for estimating the diffuse fraction of solar irradiance for photovoltaic system simulations, Energies, 10, 248, https://doi.org/10.3390/en10020248 , 2017.
Jääskeläinen, E., Manninen, T., Tamminen, J., and Laine, M.: The Aerosol Index and Land Cover Class Based Atmospheric Correction Aerosol Optical Depth Time Series 1982–2014 for the SMAC Algorithm, Remote Sens., 9, 1095, https://doi.org/10.3390/rs9111095 , 2017.
Karlsson, J. and Svensson, G.: Consequences of poor representation of Arctic sea-ice albedo and cloud-radiation interactions in the CMIP5 model ensemble, Geophys. Res. Lett., 40, 4374–4379, 2013.
Karlsson, K.-G. and Devasthale, A.: Inter-Comparison and Evaluation of the Four Longest Satellite-Derived Cloud Climate Data Records: CLARA-A2, ESA Cloud CCI V3, ISCCP-HGM, and PATMOS-x, Remote Sens., 10, 1567–1593, https://doi.org/10.3390/rs10101567, 2018.
Karlsson, K.-G. and Håkansson, N.: Characterization of AVHRR global cloud detection sensitivity based on CALIPSO-CALIOP cloud optical thickness information: demonstration of results based on the CM SAF CLARA-A2 climate data record, Atmos. Meas. Tech., 11, 633–649, https://doi.org/10.5194/amt-11-633-2018, 2018.
Karlsson, K.-G., Riihelä, A., Müller, R., Meirink, J. F., Sedlar, J., Stengel, M., Lockhoff, M., Trentmann, J., Kaspar, F., Hollmann, R., and Wolters, E.: CLARA-A1: a cloud, albedo, and radiation dataset from 28 yr of global AVHRR data, Atmos. Chem. Phys., 13, 5351–5367, https://doi.org/10.5194/acp-13-5351-2013, 2013.
Karlsson, K.-G., Anttila, K., Trentmann, J., Stengel, M., Fokke Meirink, J., Devasthale, A., Hanschmann, T., Kothe, S., Jääskeläinen, E., Sedlar, J., Benas, N., van Zadelhoff, G.-J., Schlundt, C., Stein, D., Finkensieper, S., Håkansson, N., and Hollmann, R.: CLARA-A2: the second edition of the CM SAF cloud and radiation data record from 34 years of global AVHRR data, Atmos. Chem. Phys., 17, 5809–5828, https://doi.org/10.5194/acp-17-5809-2017, 2017a.
Karlsson, K.-G., Håkansson, N., Mittaz, J. P. D., Hanschmann, T., and Devasthale, A.: Impact of AVHRR Channel 3b Noise on Climate Data Records: Filtering Method Applied to the CM SAF CLARA-A2 Data Record, Remote Sens., 9, 568–581, https://doi.org/10.3390/rs9060568, 2017b.
Karlsson, K.-G., Anttila, K., Trentmann, J., Stengel, M., Solodovnik, I., Meirink, J. F., Devasthale, A., Kothe, S., Jääskeläinen, E., Sedlar, J., Benas, N., van Zadelhoff, G.-J., Stein, D., Finkensieper, S., Håkansson, N., Hollmann, R., Kaiser, J., and Werscheck, M.: CLARA-A2.1: CM SAF cLoud, Albedo and surface RAdiation dataset from AVHRR data – Edition 2.1, Satellite Application Facility on Climate Monitoring [data set], https://doi.org/10.5676/EUM_SAF_CM/CLARA_AVHRR/V002 _01, 2020a.
Karlsson, K.-G., Johansson, E., Håkansson, N., Sedlar, J. and Eliasson, S.: Probabilistic Cloud Masking for the Generation of CM SAF Cloud Climate Data Records from AVHRR and SEVIRI Sensors, Remote Sens., 12, 713, https://doi.org/10.3390/rs12040713, 2020b.
Karlsson, K.-G., Devasthale, A., and Eliasson, S.: Global Cloudiness and Cloud Top Information from AVHRR in the 42-Year CLARA-A3 Climate Data Record Covering the Period 1979–2020, Remote Sens., 15, 3044, https://doi.org/10.3390/rs15123044, 2023a.
Karlsson, K.-G., Stengel, M., Meirink, J. F., Riihelä, A., Trentmann, J., Akkermans, T., Stein, D., Devasthale, A., Eliasson, S., Johansson, E., Håkansson, N., Solodovnik, I., Benas, N., Clerbaux, N., Selbach, N., Schröder, M., and Hollmann, R.: CLARA-A3: CM SAF cLoud, Albedo and surface RAdiation dataset from AVHRR data – Edition 3, Satellite Application Facility on Climate Monitoring [data set], https://doi.org/10.5676/EUM_SAF_CM/CLARA_AVHRR/V003, 2023b.
Kidwell, K. B.: NOAA Polar Orbiter Data Users Guide, edited by: Kidwell, K. B. and National Climatic Data Center (U.S.), National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, National Climatic Data Center, Satellite Data Services Division, 1995.
Kleipool, Q., Rozemeijer, N., van Hoek, M., Leloux, J., Loots, E., Ludewig, A., van der Plas, E., Adrichem, D., Harel, R., Spronk, S., ter Linden, M., Jaross, G., Haffner, D., Veefkind, P., and Levelt, P. F.: Ozone Monitoring Instrument (OMI) collection 4: establishing a 17-year-long series of detrended level-1b data, Atmos. Meas. Tech., 15, 3527–3553, https://doi.org/10.5194/amt-15-3527-2022, 2022.
Lee, H. T., Gruber, A., Ellingson, R. G., and Laszlo, I.: Development of the HIRS outgoing longwave radiation climate dataset, J. Atmos. Ocean. Tech., 24, 2029–2047, 2007.
Lee, H. T., Schreck, C. J., and Knapp, K. R.: Generation of the daily OLR climate data record, in: 2014 EUMETSAT meteorological satellite conference, 22–26 September 2014, Geneva, Switzerland, 22–26, 2014.
Loeb, N. G., Manalo-Smith, N., Kato, S., Miller, W. F., Gupta, S. K., Minnis, P., and Wielicki, B. A.: Angular distribution models for top-of-atmosphere radiative flux estimation from the Clouds and the Earth's Radiant Energy System instrument on the Tropical Rainfall Measuring Mission satellite. Part I: Methodology, J. Appl. Meteorol., 42, 240–265, 2003.
Loeb, N. G., Kato, S., Loukachine, K., and Manalo-Smith, N.: Angular distribution models for top-of-atmosphere radiative flux estimation from the Clouds and the Earth's Radiant Energy System instrument on the Terra satellite. Part I: Methodology, J. Atmos. Ocean. Tech., 22, 338–351, 2005.
Loeb, N. G., Doelling, D. R., Wang, H., Su, W., Nguyen, C., Corbett, J. G., Liang, L., Mitrescu, C., Rose, F. G., and Kato, S.: Clouds and the Earth's Radiant Energy System (CERES) energy balanced and filled (EBAF) top-of-atmosphere (TOA) Edition 4.0 data product, J. Climate, 31, 895–918, https://doi.org/10.1175/JCLI-D-17-0208.1, 2018.
Manninen, T., Andersson, K., and Riihelä, A.: Topography correction of the CM-SAF surface albedo product SAL, in: EUMETSAT Meteorological Satellite Conference Proceedings, 5–9 September 2011, Oslo, Norway, 2011.
Manninen, T., Jääskeläinen, E., and Riihelä, A.: Black and white-sky albedo values of snow: In situ relationships for AVHRR-based estimation using CLARA-A2 SAL, Can. J. Remote Sens., 45, 350–367, 2019.
Manninen, T., Jääskeläinen, E., Siljamo, N., Riihelä, A., and Karlsson, K.-G.: Cloud-probability-based estimation of black-sky surface albedo from AVHRR data, Atmos. Meas. Tech., 15, 879–893, https://doi.org/10.5194/amt-15-879-2022, 2022.
Mueller, R., Matsoukas, C., Gratzki, A., Behr, H., and Hollmann, R.: The CM-SAF operational scheme for the satellite based retrieval of solar surface irradiance – A LUT based eigenvector hybrid approach, Remote Sens. Environ., 113, 1012–1024, https://doi.org/10.1016/j.rse.2009.01.012, 2009.
Mueller, R. W., Dagestad, K.-F., Ineichen, P., Schroedter-Homsscheidt, M., Cros, S, Dumortier, D., Kuhlemann, R., Olseth, J. A., Izquierdo, G. P., Reise, C., Wald, L., and Heinemann, D.: Rethinking satellite-based solar irradiance modelling – The SOLIS clear-sky module, Remote Sens. Environ., 91, 160–174, https://doi.org/10.1016/j.rse.2004.02.009, 2004.
Nakajima, T. and King, M. D.: Determination of the optical thick-ness and effective particle radius of clouds from reflected solar radiation measurements, part 1: Theory, J. Atmos. Sci., 47, 1878–1893, https://doi.org/10.1175/1520-0469(1990)047<1878:DOTOTA>2.0.CO;2, 1990.
Nakajima, T. Y., Ishida, H., Nagao, T. M., Hori, M., Letu, H., Higuchi, R., Tamaru, N., Imoto, N., and Yamazaki, A.: Theoretical basis of the algorithms and early phase results of the GCOM-C (Shikisai) SGLI cloud products, Prog. Earth Planet. Sci., 6, 1–25, 2019.
NWC SAF: Algorithm Theoretical Basis Document for Cloud Micro Physics of the NWC/PPS, EUMETSAT Satellite Application Facility on Nowcasting and Very Short Range Forecasting, NWC/CDOP3/PPS/SMHI/SCI/ATBD/CMIC, Issue 3.0, 12 October 2021.
Ohmura, A.: Physical Basis for the Temperature-Based Melt-Index Method, J. Appl. Meteor., 40, 753–761, 2001.
Oleson, K. W., Bonan, G. B., Schaaf, C., Gao, F., Jin, Y., and Strahler, A.: Assessment of global climate model land surface albedo using MODIS data, Geophys. Res. Lett., 30, https://doi.org/10.1029/2002GL016749, 2003.
OSI SAF: Global Sea Ice Concentration Climate Data Record v2.0 – Multimission, EUMETSAT SAF on Ocean and Sea Ice [data set], https://doi.org/10.15770/EUM_SAF_OSI_0008, 2017a.
OSI SAF: Global Sea Ice Concentration (netCDF) – DMSP, EUMETSAT SAF on Ocean and Sea Ice, https://doi.org/10.15770/EUM_SAF_OSI_NRT_2004, 2017b.
OSI SAF: Global Sea Ice Concentration Interim Climate Data Record Release 2 – DMSP, EUMETSAT SAF on Ocean and Sea Ice [data set], https://doi.org/10.15770/EUM_SAF_OSI_NRT_2008, 2020.
Pavolonis, M. J., Heidinger, A. K., and Uttal, T.: Daytime Global Cloud Typing from AVHRR and VIIRS: Algorithm Description, Validation, and Comparisons, J. Appl. Meteor., 44, 804–826, https://doi.org/10.1175/JAM2236.1, 2005.
Perovich, D. K., Grenfell, T. C., Light, B., and Hobbs, P. V.: Seasonal evolution of the albedo of multiyear Arctic sea ice, J. Geophys. Res., 107, 8044, https://doi.org/10.1029/2000JC000438, 2002.
Pfreundschuh, S., Eriksson, P., Duncan, D., Rydberg, B., Håkansson, N., and Thoss, A.: A neural network approach to estimating a posteriori distributions of Bayesian retrieval problems, Atmos. Meas. Tech., 11, 4627–4643, https://doi.org/10.5194/amt-11-4627-2018, 2018.
Pinty, B., Lattanzio, A., Martonchik, J. V., Verstraete, M. M., Gobron, N., Taberner, M., Widlowski, J.-L., Dickinson, R. E., and Goverts, Y.: Coupling diffuse sky radiation and surface albedo, J. Atmos. Sci., 62, 2580–2591, 2005.
Platnick, S., Hubanks, P., Meyer, K., and King, M. D.: MODIS Atmosphere L3 Monthly Product (08_L3). NASA MODIS Adaptive Processing System, Goddard Space Flight Center, https://doi.org/10.5067/MODIS/MYD08_M3.006, 2015a.
Platnick, S., King, M. D., Meyer, K. G., Wind, G., Amarasinghe, N., Marchant, B., Arnold, G. T., Zhang, Z., Hubanks, P. A., Ridgway, B., and Riédi, J.: MODIS Cloud Optical Properties: User Guide for the Collection 6 Level-2 MOD06/MYD06 Product and Associated Level-3 Datasets, Version 1.0, https://modis-images.gsfc.nasa.gov/_docs/C6MOD06OPUserGuide.pdf (last access: 7 July 2023), 2015b.
Platnick, S., Meyer, K. G., King. M. D., Wind, G., Amarasinghe, N., Marchant, B., Arnold, G. T., Zhang, Z., Hubanks, P. A., Holz, R. E., Yang, P., Ridgway, W. L., and Riedi, J.: The MODIS Cloud Optical and Microphysical Products: Collection 6 Updates and Examples From Terra and Aqua, IEEE T. Geosci. Remote, 55, 502–525, https://doi.org/10.1109/TGRS.2016.2610522, 2017.
Platnick, S., Meyer, K., Wind, G., Holz, R. E., Amarasinghe, N., Hubanks, P. A., Marchant, B., Dutcher, S., and Veglio, P.: The NASA MODIS-VIIRS Continuity Cloud Optical Properties Products, Remote Sens., 13, 2, https://doi.org/10.3390/rs13010002, 2021.
Rahman, H. and G. Dedieu, G.: SMAC: a simplified method for the atmospheric correction of satellite measurements in the solar spectrum, Int. J. Remote Sens., 15, 123–143, https://doi.org/10.1080/01431169408954055, 1994.
Ri, X., Tana, G., Shi, C., Nakajima, T. Y., Shi, J., Zhao, J., Xu, J., and Letu, H.: Cloud, Atmospheric Radiation and Renewal Energy Application (CARE) Version 1.0 Cloud Top Property Product From Himawari-8/AHI: Algorithm Development and Preliminary Validation, IEEE T. Geosci. Remote, 60, 1–11, 2022.
Riihelä, A., Manninen, T., Laine, V., Andersson, K., and Kaspar, F.: CLARA-SAL: a global 28 yr timeseries of Earth's black-sky surface albedo, Atmos. Chem. Phys., 13, 3743–3762, https://doi.org/10.5194/acp-13-3743-2013, 2013.
Roman, M. O., Schaaf, C. B., Lewis P., Gao, F., Anderson G. P., Privette, J. L., Strahler, A. H., Woodcock, C. E., and Barnsley, M.: Assessing the coupling between surface albedo derived from MODIS and the fraction of diffuse skylight over spatially-characterized landscapes Remote Sens. Environ., 114, 738–60, https://doi.org/10.1016/j.rse.2009.11.014, 2010.
Rossow, W. B. and Schiffer, R. A.: ISCCP Cloud Data Products, B. Am. Meteorol. Soc., 71, 2–20, 1991.
Rutan, D. A., Kato, S., Doelling, D. R., Rose, F. G., Nguyen, L. T., Caldwell, T. E., and Loeb, N. G.: CERES Synoptic Product: Methodology and Validation of Surface Radiant Flux, J. Atmos. Ocean. Tech., 32, 1121–1143, 2015.
Schiffer, R. A. and Rossow, W. B.: The International Satellite Cloud Climatology Project (ISCCP): The First Project of the World Climate Research Programme, B. Am. Meteorol. Soc., 64, 779–784, 1983.
Schulz, J., Albert, P., Behr, H.-D., Caprion, D., Deneke, H., Dewitte, S., Dürr, B., Fuchs, P., Gratzki, A., Hechler, P., Hollmann, R., Johnston, S., Karlsson, K.-G., Manninen, T., Müller, R., Reuter, M., Riihelä, A., Roebeling, R., Selbach, N., Tetzlaff, A., Thomas, W., Werscheck, M., Wolters, E., and Zelenka, A.: Operational climate monitoring from space: the EUMETSAT Satellite Application Facility on Climate Monitoring (CM-SAF), Atmos. Chem. Phys., 9, 1687–1709, https://doi.org/10.5194/acp-9-1687-2009, 2009.
Song, Z., Liang, S., Wang, D., Zhou, Y., and Jia, A.: Long-term record of top-of-atmosphere albedo over land generated from AVHRR data, Remote Sens. Environ., 211, 71–88, 2018.
Stammes, P.: Spectral radiance modelling in the UV-Visible range, in: IRS 2000: Current problems in Atmospheric Radiation, edited by: Smith, W. L. and Timofeyev, Y. M. A., Deepak, Hampton, VA, 385–388, 2001.
Stengel, M., Stapelberg, S., Sus, O., Schlundt, C., Poulsen, C., Thomas, G., Christensen, M., Carbajal Henken, C., Preusker, R., Fischer, J., Devasthale, A., Willén, U., Karlsson, K.-G., McGarragh, G. R., Proud, S., Povey, A. C., Grainger, R. G., Meirink, J. F., Feofilov, A., Bennartz, R., Bojanowski, J. S., and Hollmann, R.: Cloud property datasets retrieved from AVHRR, MODIS, AATSR and MERIS in the framework of the Cloud_cci project, Earth Syst. Sci. Data, 9, 881–904, https://doi.org/10.5194/essd-9-881-2017, 2017.
Stengel, M., Stapelberg, S., Sus, O., Finkensieper, S., Würzler, B., Philipp, D., Hollmann, R., Poulsen, C., Christensen, M., and McGarragh, G.: Cloud_cci Advanced Very High Resolution Radiometer post meridiem (AVHRR-PM) dataset version 3: 35-year climatology of global cloud and radiation properties, Earth Syst. Sci. Data, 12, 41–60, https://doi.org/10.5194/essd-12-41-2020, 2020.
Stephens, G. L.: Radiation profiles in extended water clouds: II. Parameterization schemes, J. Atmos. Sci., 35, 2123–2132, https://doi.org/10.1175/1520-0469(1978)035<2123:RPIEWC>2.0.CO;2, 1978.
Stubenrauch, C. J., Rossow, W. B., Kinne, S., Ackerman, S., Cesana, G., Chepfer, H., Di Girolamo, L., Getzewich, B., Guignard, A., Heidinger, A., Maddux, B., Menzel, W. P., Minnis, P., Pearl, C., Platnick, S., Poulsen, C., Riedi, J., Sun-Mack, S., Walther, A., Winker, D., Zeng, S., and Zhao, G.: Assessment of global cloud datasets from satellites: Project and Database initiated by the GEWEX Radiation Panel, B. Am. Meteorol. Soc., 23, 1031–1049, https://doi.org/10.1175/BAMS-D-12-00117.1, 2013.
Tabazadeh, A., Djikaev, Y. S., and Reiss, H.: Surface crystallization of supercooled water in clouds, P. Natl. Acad. Sci. USA, 99, 15873–15878, 2003.
Thackeray, C. W. and Hall, A.: An emergent constraint on future Arctic sea-ice albedo feedback, Nat. Clim. Change, 9, 972–978, 2019.
Vihma, T., Jaagus, J., Jakobson, E., and Palo, T.: Meteorological conditions in the Arctic Ocean in spring and summer 2007 as recorded on the drifting ice station Tara, Geophys. Res. Lett., 35, https://doi.org/10.1029/2008GL034681, 2008.
Walton, C. C., Sullivan, J. T., Rao, C. R. N., and Weinreb, M. P.: Corrections for detector nonlinearities and calibration inconsistencies of the infrared channels of the Advanced Very High Resolution Radiometer, J. Geoph. Res.-Oceans, 103, 3323–3337, https://doi.org/10.1029/97JC02018, 1998.
Wang, D. and Liang, S.: Estimating high-resolution top of atmosphere albedo from Moderate Resolution Imaging Spectroradiometer data, Remote Sens. Environ., 178, 93–103, 2016.
Wielicki, B. A., Barkstrom, B. R., Harrison, E. F., Lee III, R. B., Smith, G. L., and Cooper, J. E.: Clouds and the Earth's Radiant Energy System (CERES): An earth observing system experiment, B. Am. Meteorol. Soc., 77, 853–868, 1996.
Wielicki, B. A., Barkstrom, B. R., Baum, B. A., Charlock, T. P., Green, R. N., Kratz, D. P., Lee, R. B., Minnis, P., Smith, G. L., Wong, T., Young, D. F., Cess, R. D., Coakley, J. A., Crommelynck, D. A. H., Donner, L., Kandel, R., King, M. D., Miller, A. J., Ramanathan, V., Randall, D. A., Stowe, L., and Welch, R. M.: Clouds and the Earth's Radiant Energy System (CERES): algorithm overview, IEEE T. Geosci. Remote, 36, 1127–1141, 1998.
Winker, D.: CALIPSO LID L2 5km Standard HDF File – Version 4.10, NASA Langley Research Center Atmospheric Science Data Center DAAC [data set], https://doi.org/10.5067/CALIOP/CALIPSO/LID_L2_05kmCLay-Standard-V4-20, 2016.
Xiong, X., Stamnes, K., and Lubin, D.: Surface Albedo over the Arctic Ocean Derived from AVHRR and Its Validation with SHEBA Data, J. Appl. Meteorol., 41, 413–425, 2002.
Yang, F., Mitchell, K., Hou, Y.-T., Dai, Y., Zeng, X., Wang, Z., and Liang, X.-Z.: Dependence of Land Surface Albedo on Solar Zenith Angle: Observations and Model Parametrization, J. Appl. Meteorol. Clim., 47, 2963–2982, 2008.
Yang, P., Bi, L., Baum, B. A., Liou, K.-N., Kattawar, G. W., Mishchenko, M. I., and Cole, B.: Spectrally consistent scattering, absorption, and polarization properties of atmospheric ice crystals at wavelengths from 0.2 to 100 µm, J. Atmos. Sci., 70, 330–347, https://doi.org/10.1175/JAS-D-12-039.1, 2013.
Young, A. H., Knapp, K. R., Inamdar, A., Hankins, W., and Rossow, W. B.: The International Satellite Cloud Climatology Project H-Series climate data record product, Earth Syst. Sci. Data, 10, 583–593, https://doi.org/10.5194/essd-10-583-2018, 2018.
Young, D. F., Minnis, P., Doelling, D. R., Gibson, G. G., and Wong, T.: Temporal interpolation methods for the Clouds and the Earth's Radiant Energy System (CERES) experiment, J. Appl. Meteorol., 37, 572–590, 1998.
Short summary
This paper presents a global climate data record on cloud parameters, radiation at the surface and at the top of atmosphere, and surface albedo. The temporal coverage is 1979–2020 (42 years) and the data record is also continuously updated until present time. Thus, more than four decades of climate parameters are provided. Based on CLARA-A3, studies on distribution of clouds and radiation parameters can be made and, especially, investigations of climate trends and evaluation of climate models.
This paper presents a global climate data record on cloud parameters, radiation at the surface...
Altmetrics
Final-revised paper
Preprint