Articles | Volume 15, issue 3
https://doi.org/10.5194/essd-15-1441-2023
© 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-15-1441-2023
© 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
| 
31 Mar 2023
Data description paper |
| 31 Mar 2023
| 31 Mar 2023
EURADCLIM: the European climatological high-resolution gauge-adjusted radar precipitation dataset
R&D Observations and Data Technology, Royal Netherlands Meteorological Institute, Utrechtseweg 297, 3731 GA De Bilt, the Netherlands
Else van den Besselaar
R&D Observations and Data Technology, Royal Netherlands Meteorological Institute, Utrechtseweg 297, 3731 GA De Bilt, the Netherlands
Gerard van der Schrier
R&D Observations and Data Technology, Royal Netherlands Meteorological Institute, Utrechtseweg 297, 3731 GA De Bilt, the Netherlands
Jan Fokke Meirink
R&D Satellite Observations, Royal Netherlands Meteorological Institute, Utrechtseweg 297, 3731 GA De Bilt, the Netherlands
Emiel van der Plas
R&D Satellite Observations, Royal Netherlands Meteorological Institute, Utrechtseweg 297, 3731 GA De Bilt, the Netherlands
Hidde Leijnse
R&D Observations and Data Technology, Royal Netherlands Meteorological Institute, Utrechtseweg 297, 3731 GA De Bilt, the Netherlands
Related authors
Abbas El Hachem, Jochen Seidel, Tess O'Hara, Roberto Villalobos Herrera, Aart Overeem, Remko Uijlenhoet, András Bárdossy, and Lotte de Vos
Hydrol. Earth Syst. Sci., 28, 4715–4731, https://doi.org/10.5194/hess-28-4715-2024, https://doi.org/10.5194/hess-28-4715-2024, 2024
Short summary
Short summary
This study presents an overview of open-source quality control (QC) algorithms for rainfall data from personal weather stations (PWSs). The methodology and usability along technical and operational guidelines for using every QC algorithm are presented. All three QC algorithms are available for users to explore in the OpenSense sandbox. They were applied in a case study using PWS data from the Amsterdam region in the Netherlands. The results highlight the necessity for data quality control.
Luuk D. van der Valk, Miriam Coenders-Gerrits, Rolf W. Hut, Aart Overeem, Bas Walraven, and Remko Uijlenhoet
Atmos. Meas. Tech., 17, 2811–2832, https://doi.org/10.5194/amt-17-2811-2024, https://doi.org/10.5194/amt-17-2811-2024, 2024
Short summary
Short summary
Microwave links, often part of mobile phone networks, can be used to measure rainfall along the link path by determining the signal loss caused by rainfall. We use high-frequency data of multiple microwave links to recreate commonly used sampling strategies. For time intervals up to 1 min, the influence of sampling strategies on estimated rainfall intensities is relatively little, while for intervals longer than 5–15 min, the sampling strategy can have significant influences on the estimates.
Aart Overeem, Hidde Leijnse, Gerard van der Schrier, Else van den Besselaar, Irene Garcia-Marti, and Lotte Wilhelmina de Vos
Hydrol. Earth Syst. Sci., 28, 649–668, https://doi.org/10.5194/hess-28-649-2024, https://doi.org/10.5194/hess-28-649-2024, 2024
Short summary
Short summary
Ground-based radar precipitation products typically need adjustment with rain gauge accumulations to achieve a reasonable accuracy. Crowdsourced rain gauge networks have a much higher density than conventional ones. Here, a 1-year personal weather station (PWS) gauge dataset is obtained. After quality control, the 1 h PWS gauge accumulations are merged with pan-European radar accumulations. The potential of crowdsourcing to improve radar precipitation products in (near) real time is confirmed.
Linda Bogerd, Hidde Leijnse, Aart Overeem, and Remko Uijlenhoet
Atmos. Meas. Tech., 17, 247–259, https://doi.org/10.5194/amt-17-247-2024, https://doi.org/10.5194/amt-17-247-2024, 2024
Short summary
Short summary
Algorithms merge satellite radiometer data from various frequency channels, each tied to a different footprint size. We studied the uncertainty associated with sampling (over the Netherlands using 4 years of data) as precipitation is highly variable in space and time by simulating ground-based data as satellite footprints. Though sampling affects precipitation estimates, it doesn’t explain all discrepancies. Overall, uncertainties in the algorithm seem more influential than how data is sampled.
Wagner Wolff, Aart Overeem, Hidde Leijnse, and Remko Uijlenhoet
Atmos. Meas. Tech., 15, 485–502, https://doi.org/10.5194/amt-15-485-2022, https://doi.org/10.5194/amt-15-485-2022, 2022
Short summary
Short summary
The existing infrastructure for cellular communication is promising for ground-based rainfall remote sensing. Rain-induced signal attenuation is used in dedicated algorithms for retrieving rainfall depth along commercial microwave links (CMLs) between cell phone towers. This processing is a source of many uncertainties about input data, algorithm structures, parameters, CML network, and local climate. Application of a stochastic optimization method leads to improved CML rainfall estimates.
Ruben Imhoff, Claudia Brauer, Klaas-Jan van Heeringen, Hidde Leijnse, Aart Overeem, Albrecht Weerts, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 25, 4061–4080, https://doi.org/10.5194/hess-25-4061-2021, https://doi.org/10.5194/hess-25-4061-2021, 2021
Short summary
Short summary
Significant biases in real-time radar rainfall products limit the use for hydrometeorological forecasting. We introduce CARROTS (Climatology-based Adjustments for Radar Rainfall in an OperaTional Setting), a set of fixed bias reduction factors to correct radar rainfall products and to benchmark other correction algorithms. When tested for 12 Dutch basins, estimated rainfall and simulated discharges with CARROTS generally outperform those using the operational mean field bias adjustments.
Thomas C. van Leth, Hidde Leijnse, Aart Overeem, and Remko Uijlenhoet
Atmos. Meas. Tech., 13, 1797–1815, https://doi.org/10.5194/amt-13-1797-2020, https://doi.org/10.5194/amt-13-1797-2020, 2020
Short summary
Short summary
We present a method of using collocated microwave link instruments to estimate the average size distribution of raindrops along a path of several kilometers. Our method is validated using simulated fields as well as five laser disdrometers installed along a path. We also present preliminary results from an experimental setup measuring at 26 and 38 GHz along a 2.2 km path. We show that a retrieval on the basis of microwave links can be highly accurate, provided the base power level is stable.
Thomas C. van Leth, Aart Overeem, Hidde Leijnse, and Remko Uijlenhoet
Atmos. Meas. Tech., 11, 4645–4669, https://doi.org/10.5194/amt-11-4645-2018, https://doi.org/10.5194/amt-11-4645-2018, 2018
Short summary
Short summary
We present a campaign to address several error sources associated with rainfall estimates from microwave links in cellular communication networks. The set-up consists of three co-located links, complemented with reference instruments. We investigate events covering different attenuating phenomena: Rainfall, solid precipitation, temperature, fog, antenna wetting due to rain or dew, and clutter.
Manuel F. Rios Gaona, Aart Overeem, Timothy H. Raupach, Hidde Leijnse, and Remko Uijlenhoet
Atmos. Meas. Tech., 11, 4465–4476, https://doi.org/10.5194/amt-11-4465-2018, https://doi.org/10.5194/amt-11-4465-2018, 2018
Short summary
Short summary
Rainfall estimates from commercial microwave links were obtained for the city of Sao Paulo (Brazil). The results show the potential of such networks as complementary rainfall measurements for more robust networks (e.g. radars, gauges, satellites).
Lotte de Vos, Hidde Leijnse, Aart Overeem, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 21, 765–777, https://doi.org/10.5194/hess-21-765-2017, https://doi.org/10.5194/hess-21-765-2017, 2017
Short summary
Short summary
Recent developments have made it possible to easily crowdsource meteorological measurements from automatic personal weather stations worldwide. This has offered free access to rainfall ground measurements at spatial and temporal resolutions far exceeding those of national operational sensor networks, especially in cities. This paper is the first step to make optimal use of this promising source of rainfall measurements and identify challenges for future implementation for urban applications.
Aart Overeem, Hidde Leijnse, and Remko Uijlenhoet
Atmos. Meas. Tech., 9, 2425–2444, https://doi.org/10.5194/amt-9-2425-2016, https://doi.org/10.5194/amt-9-2425-2016, 2016
Short summary
Short summary
Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide rainfall maps can be derived from the signal attenuations of microwave links in such a network. Here we give a detailed description of the employed rainfall retrieval algorithm and the corresponding code, which is freely provided at GitHub.
M. F. Rios Gaona, A. Overeem, H. Leijnse, and R. Uijlenhoet
Hydrol. Earth Syst. Sci., 19, 3571–3584, https://doi.org/10.5194/hess-19-3571-2015, https://doi.org/10.5194/hess-19-3571-2015, 2015
Short summary
Short summary
Commercial cellular networks are built for telecommunication purposes. These kinds of networks have lately been used to obtain rainfall maps at country-wide scales. From previous studies, we now quantify the uncertainties associated with such maps. To do so, we divided the sources or error into two categories: from microwave link measurements and from mapping. It was found that the former is the source that contributes the most to the overall error in rainfall maps from microwave link network.
Abbas El Hachem, Jochen Seidel, Tess O'Hara, Roberto Villalobos Herrera, Aart Overeem, Remko Uijlenhoet, András Bárdossy, and Lotte de Vos
Hydrol. Earth Syst. Sci., 28, 4715–4731, https://doi.org/10.5194/hess-28-4715-2024, https://doi.org/10.5194/hess-28-4715-2024, 2024
Short summary
Short summary
This study presents an overview of open-source quality control (QC) algorithms for rainfall data from personal weather stations (PWSs). The methodology and usability along technical and operational guidelines for using every QC algorithm are presented. All three QC algorithms are available for users to explore in the OpenSense sandbox. They were applied in a case study using PWS data from the Amsterdam region in the Netherlands. The results highlight the necessity for data quality control.
Job I. Wiltink, Hartwig Deneke, Yves-Marie Saint-Drenan, Chiel C. van Heerwaarden, and Jan Fokke Meirink
Atmos. Meas. Tech., 17, 6003–6024, https://doi.org/10.5194/amt-17-6003-2024, https://doi.org/10.5194/amt-17-6003-2024, 2024
Short summary
Short summary
Meteosat Spinning Enhanced Visible and Infrared Imager (SEVIRI) global horizontal irradiance (GHI) retrievals are validated at standard and increased spatial resolution against a network of 99 pyranometers. GHI accuracy is strongly dependent on the cloud regime. Days with variable cloud conditions show significant accuracy improvements when retrieved at higher resolution. We highlight the benefits of dense network observations and a cloud-regime-resolved approach in validating GHI retrievals.
Nikos Benas, Jan Fokke Meirink, Rob Roebeling, and Martin Stengel
EGUsphere, https://doi.org/10.5194/egusphere-2024-3135, https://doi.org/10.5194/egusphere-2024-3135, 2024
Short summary
Short summary
This study examines how ship emissions affect clouds over a shipping corridor in the southeastern Atlantic. Using satellite data from 2004 to 2023, we find that ship emissions increase the number of cloud droplets while reducing their size, and slightly decrease cloud water content. Effects on seasonal and daily patterns vary based on regional factors. The impact of emissions weakened after stricter regulations were implemented in 2020.
Abhay Devasthale, Sandra Andersson, Erik Engström, Frank Kaspar, Jörg Trentmann, Anke Duguay-Tetzlaff, Jan Fokke Meirink, Erik Kjellström, Tomas Landelius, Manu Anna Thomas, and Karl-Göran Karlsson
EGUsphere, https://doi.org/10.5194/egusphere-2024-1805, https://doi.org/10.5194/egusphere-2024-1805, 2024
Short summary
Short summary
Using the satellite-based climate data record CLARA-A3 spanning 1982–2020 and ERA5 reanalysis, we present climate regimes that are favourable or unfavourable for solar energy applications. We show that the favourable climate regimes are emerging over much of Europe during spring and early summer for solar energy exploitation.
Luuk D. van der Valk, Miriam Coenders-Gerrits, Rolf W. Hut, Aart Overeem, Bas Walraven, and Remko Uijlenhoet
Atmos. Meas. Tech., 17, 2811–2832, https://doi.org/10.5194/amt-17-2811-2024, https://doi.org/10.5194/amt-17-2811-2024, 2024
Short summary
Short summary
Microwave links, often part of mobile phone networks, can be used to measure rainfall along the link path by determining the signal loss caused by rainfall. We use high-frequency data of multiple microwave links to recreate commonly used sampling strategies. For time intervals up to 1 min, the influence of sampling strategies on estimated rainfall intensities is relatively little, while for intervals longer than 5–15 min, the sampling strategy can have significant influences on the estimates.
Mugni Hadi Hariadi, Gerard van der Schrier, Gert-Jan Steeneveld, Samuel J. Sutanto, Edwin Sutanudjaja, Dian Nur Ratri, Ardhasena Sopaheluwakan, and Albert Klein Tank
Hydrol. Earth Syst. Sci., 28, 1935–1956, https://doi.org/10.5194/hess-28-1935-2024, https://doi.org/10.5194/hess-28-1935-2024, 2024
Short summary
Short summary
We utilize the high-resolution CMIP6 for extreme rainfall and streamflow projection over Southeast Asia. This region will experience an increase in both dry and wet extremes in the near future. We found a more extreme low flow and high flow, along with an increasing probability of low-flow and high-flow events. We reveal that the changes in low-flow events and their probabilities are not only influenced by extremely dry climates but also by the catchment characteristics.
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.
Aart Overeem, Hidde Leijnse, Gerard van der Schrier, Else van den Besselaar, Irene Garcia-Marti, and Lotte Wilhelmina de Vos
Hydrol. Earth Syst. Sci., 28, 649–668, https://doi.org/10.5194/hess-28-649-2024, https://doi.org/10.5194/hess-28-649-2024, 2024
Short summary
Short summary
Ground-based radar precipitation products typically need adjustment with rain gauge accumulations to achieve a reasonable accuracy. Crowdsourced rain gauge networks have a much higher density than conventional ones. Here, a 1-year personal weather station (PWS) gauge dataset is obtained. After quality control, the 1 h PWS gauge accumulations are merged with pan-European radar accumulations. The potential of crowdsourcing to improve radar precipitation products in (near) real time is confirmed.
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.
Linda Bogerd, Hidde Leijnse, Aart Overeem, and Remko Uijlenhoet
Atmos. Meas. Tech., 17, 247–259, https://doi.org/10.5194/amt-17-247-2024, https://doi.org/10.5194/amt-17-247-2024, 2024
Short summary
Short summary
Algorithms merge satellite radiometer data from various frequency channels, each tied to a different footprint size. We studied the uncertainty associated with sampling (over the Netherlands using 4 years of data) as precipitation is highly variable in space and time by simulating ground-based data as satellite footprints. Though sampling affects precipitation estimates, it doesn’t explain all discrepancies. Overall, uncertainties in the algorithm seem more influential than how data is sampled.
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.
Karl-Göran Karlsson, Martin Stengel, Jan Fokke Meirink, Aku Riihelä, Jörg Trentmann, Tom Akkermans, Diana Stein, Abhay Devasthale, Salomon Eliasson, Erik Johansson, Nina Håkansson, Irina Solodovnik, Nikos Benas, Nicolas Clerbaux, Nathalie Selbach, Marc Schröder, and Rainer Hollmann
Earth Syst. Sci. Data, 15, 4901–4926, https://doi.org/10.5194/essd-15-4901-2023, https://doi.org/10.5194/essd-15-4901-2023, 2023
Short summary
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.
Jouke H. S. de Baar, Linh Nhat Luu, Gerard van der Schrier, Else J. M. van den Besselaar, and Irene Garcia-Marti
Adv. Sci. Res., 20, 91–95, https://doi.org/10.5194/asr-20-91-2023, https://doi.org/10.5194/asr-20-91-2023, 2023
Short summary
Short summary
In this work, we present the most recent updates in the E-OBS gridded data set for daily mean wind speed over Europe. The data set is provided as an ensemble of equally likely realisations. In addition, we make a preliminary study into possible causes of the observed terrestrial wind stilling effect, such as local changes in surface roughness length. As one of the results, we do observe a terrestrial wind stilling effect, however, the trend varies locally over Europe.
Jouke H. S. de Baar, Irene Garcia-Marti, and Gerard van der Schrier
Adv. Sci. Res., 20, 49–53, https://doi.org/10.5194/asr-20-49-2023, https://doi.org/10.5194/asr-20-49-2023, 2023
Short summary
Short summary
Combining high-fidelity official meteorological observations with low-fidelity crowd-sourced data in a single climate or weather map is challenging because of the significant bias and noise in the low-fidelity data. In this work, we present a method to treat this bias and noise in a statistical framework. In addition, we show that we can make an additional improvement in the quality of the map when we add high-resolution land use information.
Quintus Kleipool, Nico Rozemeijer, Mirna van Hoek, Jonatan Leloux, Erwin Loots, Antje Ludewig, Emiel van der Plas, Daley Adrichem, Raoul Harel, Simon Spronk, Mark ter Linden, Glen Jaross, David Haffner, Pepijn Veefkind, and Pieternel F. Levelt
Atmos. Meas. Tech., 15, 3527–3553, https://doi.org/10.5194/amt-15-3527-2022, https://doi.org/10.5194/amt-15-3527-2022, 2022
Short summary
Short summary
A new collection-4 dataset for the Ozone Monitoring Instrument (OMI) mission has been established to supersede the current collection-3 level-1b (L1b) data, produced with a newly developed L01b data processor based on the TROPOspheric Monitoring Instrument (TROPOMI) L01b processor. The collection-4 L1b data have a similar output format to the TROPOMI L1b data for easy connection of the data series. Many insights from the TROPOMI algorithms, as well as from OMI collection-3 usage, were included.
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.
Wagner Wolff, Aart Overeem, Hidde Leijnse, and Remko Uijlenhoet
Atmos. Meas. Tech., 15, 485–502, https://doi.org/10.5194/amt-15-485-2022, https://doi.org/10.5194/amt-15-485-2022, 2022
Short summary
Short summary
The existing infrastructure for cellular communication is promising for ground-based rainfall remote sensing. Rain-induced signal attenuation is used in dedicated algorithms for retrieving rainfall depth along commercial microwave links (CMLs) between cell phone towers. This processing is a source of many uncertainties about input data, algorithm structures, parameters, CML network, and local climate. Application of a stochastic optimization method leads to improved CML rainfall estimates.
Gerard van der Schrier, Richard P. Allan, Albert Ossó, Pedro M. Sousa, Hans Van de Vyver, Bert Van Schaeybroeck, Roberto Coscarelli, Angela A. Pasqua, Olga Petrucci, Mary Curley, Mirosław Mietus, Janusz Filipiak, Petr Štěpánek, Pavel Zahradníček, Rudolf Brázdil, Ladislava Řezníčková, Else J. M. van den Besselaar, Ricardo Trigo, and Enric Aguilar
Clim. Past, 17, 2201–2221, https://doi.org/10.5194/cp-17-2201-2021, https://doi.org/10.5194/cp-17-2201-2021, 2021
Short summary
Short summary
The 1921 drought was the most severe drought to hit Europe since the start of the 20th century. Here the climatological description of the drought is coupled to an overview of its impacts, sourced from newspapers, and an analysis of its drivers. The area from Ireland to the Ukraine was affected but hardest hit was the triangle between Brussels, Paris and Lyon. The drought impacts lingered on until well into autumn and winter, affecting water supply and agriculture and livestock farming.
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.
Ruben Imhoff, Claudia Brauer, Klaas-Jan van Heeringen, Hidde Leijnse, Aart Overeem, Albrecht Weerts, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 25, 4061–4080, https://doi.org/10.5194/hess-25-4061-2021, https://doi.org/10.5194/hess-25-4061-2021, 2021
Short summary
Short summary
Significant biases in real-time radar rainfall products limit the use for hydrometeorological forecasting. We introduce CARROTS (Climatology-based Adjustments for Radar Rainfall in an OperaTional Setting), a set of fixed bias reduction factors to correct radar rainfall products and to benchmark other correction algorithms. When tested for 12 Dutch basins, estimated rainfall and simulated discharges with CARROTS generally outperform those using the operational mean field bias adjustments.
Antje Ludewig, Quintus Kleipool, Rolf Bartstra, Robin Landzaat, Jonatan Leloux, Erwin Loots, Peter Meijering, Emiel van der Plas, Nico Rozemeijer, Frank Vonk, and Pepijn Veefkind
Atmos. Meas. Tech., 13, 3561–3580, https://doi.org/10.5194/amt-13-3561-2020, https://doi.org/10.5194/amt-13-3561-2020, 2020
Short summary
Short summary
After the Sentinel-5 Precursor satellite launch on 13 October 2017, its single payload, the TROPOspheric Monitoring Instrument (TROPOMI), was tested and calibrated extensively. Changes due to ageing of the instrument and new insights have led to updates to the L1b processor and its calibration key data, leading to improvements of the data quality. Regularly scheduled calibration measurements are used in the nominal operations phase (since 30 April 2018) to correct instrument degradation.
Thomas C. van Leth, Hidde Leijnse, Aart Overeem, and Remko Uijlenhoet
Atmos. Meas. Tech., 13, 1797–1815, https://doi.org/10.5194/amt-13-1797-2020, https://doi.org/10.5194/amt-13-1797-2020, 2020
Short summary
Short summary
We present a method of using collocated microwave link instruments to estimate the average size distribution of raindrops along a path of several kilometers. Our method is validated using simulated fields as well as five laser disdrometers installed along a path. We also present preliminary results from an experimental setup measuring at 26 and 38 GHz along a 2.2 km path. We show that a retrieval on the basis of microwave links can be highly accurate, provided the base power level is stable.
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.
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.
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.
Joan Ramon Coll, Gerard van der Schrier, Enric Aguilar, Dubravka Rasol, Roberto Coscarelli, and Andrés Bishop
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2019-6, https://doi.org/10.5194/essd-2019-6, 2019
Revised manuscript not accepted
Short summary
Short summary
Around 610K climate station-based observations were rescued over European regions for the main climate variables (maximum and minimum temperature, rainfall, sunshine duration and snow depth) along the 20th century at daily scale in the INDECIS Project. Rescued data will constitute the INDECIS-Raw-Dataset, which will expand current European data coverage contained in the European Climate Assessment & Dataset (ECA&D). The expansion of ECA&D will improve the high-quality of future climate products.
Eveline C. van der Linden, Reindert J. Haarsma, and Gerard van der Schrier
Hydrol. Earth Syst. Sci., 23, 191–206, https://doi.org/10.5194/hess-23-191-2019, https://doi.org/10.5194/hess-23-191-2019, 2019
Short summary
Short summary
This paper provides a process-based assessment of the impact of spatial model resolution on future projections of European soil moisture changes. In central-western Europe, simulated future drying is more severe and starts earlier in the season at higher global resolution compared to conventional resolution simulations. The enhanced drying suggests that future projections of central-western European drying by conventional resolution global climate models have been potentially underestimated.
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.
Quintus Kleipool, Antje Ludewig, Ljubiša Babić, Rolf Bartstra, Remco Braak, Werner Dierssen, Pieter-Jan Dewitte, Pepijn Kenter, Robin Landzaat, Jonatan Leloux, Erwin Loots, Peter Meijering, Emiel van der Plas, Nico Rozemeijer, Dinand Schepers, Daniel Schiavini, Joost Smeets, Giuseppe Vacanti, Frank Vonk, and Pepijn Veefkind
Atmos. Meas. Tech., 11, 6439–6479, https://doi.org/10.5194/amt-11-6439-2018, https://doi.org/10.5194/amt-11-6439-2018, 2018
Short summary
Short summary
This paper reports on the pre-launch calibration of the TROPOMI instrument on board ESA's Sentinel 5P satellite. This calibration is needed to convert the raw instrument digital data to physical quantities like Earth radiance and Sun irradiance. From these quantities atmospheric properties can be derived. The paper shows that the chosen approach to calibration and analysis was successful and that
the achieved accuracy makes high-quality observations of the Earth's atmosphere feasible.
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.
Thomas C. van Leth, Aart Overeem, Hidde Leijnse, and Remko Uijlenhoet
Atmos. Meas. Tech., 11, 4645–4669, https://doi.org/10.5194/amt-11-4645-2018, https://doi.org/10.5194/amt-11-4645-2018, 2018
Short summary
Short summary
We present a campaign to address several error sources associated with rainfall estimates from microwave links in cellular communication networks. The set-up consists of three co-located links, complemented with reference instruments. We investigate events covering different attenuating phenomena: Rainfall, solid precipitation, temperature, fog, antenna wetting due to rain or dew, and clutter.
Manuel F. Rios Gaona, Aart Overeem, Timothy H. Raupach, Hidde Leijnse, and Remko Uijlenhoet
Atmos. Meas. Tech., 11, 4465–4476, https://doi.org/10.5194/amt-11-4465-2018, https://doi.org/10.5194/amt-11-4465-2018, 2018
Short summary
Short summary
Rainfall estimates from commercial microwave links were obtained for the city of Sao Paulo (Brazil). The results show the potential of such networks as complementary rainfall measurements for more robust networks (e.g. radars, gauges, satellites).
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.
Christophe Lavaysse, Carmelo Cammalleri, Alessandro Dosio, Gerard van der Schrier, Andrea Toreti, and Jürgen Vogt
Nat. Hazards Earth Syst. Sci., 18, 91–104, https://doi.org/10.5194/nhess-18-91-2018, https://doi.org/10.5194/nhess-18-91-2018, 2018
Short summary
Short summary
Extreme-temperature anomalies such as heat and cold waves may have strong impacts on human activities and health. Providing a robust operational system to monitor extreme-temperature anomalies in Europe, developed and validated in this study, is thus of prime importance. This work exposes the methodology and the climatology of these events. It also discusses the associated uncertainties according to the datasets and the methods used.
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.
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.
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).
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.
Gerard van der Schrier and Rob Groenland
Nat. Hazards Earth Syst. Sci., 17, 157–170, https://doi.org/10.5194/nhess-17-157-2017, https://doi.org/10.5194/nhess-17-157-2017, 2017
Short summary
Short summary
On 1 August 1674, very severe thunderstorms occurred along a squall line from northern France to the northern parts of Holland, where damages were particularly severe. Using reported and pictured observations of damages, a reconstruction of this storm is made and an interpretation using modern meteorological concepts is given. Special attention is given to the city of Utrecht, which was hit hardest and where the impact of this storm is still recognisable in the cityscape.
Lotte de Vos, Hidde Leijnse, Aart Overeem, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 21, 765–777, https://doi.org/10.5194/hess-21-765-2017, https://doi.org/10.5194/hess-21-765-2017, 2017
Short summary
Short summary
Recent developments have made it possible to easily crowdsource meteorological measurements from automatic personal weather stations worldwide. This has offered free access to rainfall ground measurements at spatial and temporal resolutions far exceeding those of national operational sensor networks, especially in cities. This paper is the first step to make optimal use of this promising source of rainfall measurements and identify challenges for future implementation for urban applications.
C. Z. van de Beek, H. Leijnse, P. Hazenberg, and R. Uijlenhoet
Atmos. Meas. Tech., 9, 3837–3850, https://doi.org/10.5194/amt-9-3837-2016, https://doi.org/10.5194/amt-9-3837-2016, 2016
Short summary
Short summary
Quantitative precipitation estimation using weather radar is affected by many sources of error. This study is an attempt to separate and quantify sources of error very close to the radar. A 3-day event is analyzed using radar, rain gauge and disdrometer data. Without correction, the radar severely underestimates the total rain amount by more than 50 %. After correction for the errors, a good match with rain gauge measurements is found, with 5 to 8 % difference.
Aart Overeem, Hidde Leijnse, and Remko Uijlenhoet
Atmos. Meas. Tech., 9, 2425–2444, https://doi.org/10.5194/amt-9-2425-2016, https://doi.org/10.5194/amt-9-2425-2016, 2016
Short summary
Short summary
Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide rainfall maps can be derived from the signal attenuations of microwave links in such a network. Here we give a detailed description of the employed rainfall retrieval algorithm and the corresponding code, which is freely provided at GitHub.
M. F. Rios Gaona, A. Overeem, H. Leijnse, and R. Uijlenhoet
Hydrol. Earth Syst. Sci., 19, 3571–3584, https://doi.org/10.5194/hess-19-3571-2015, https://doi.org/10.5194/hess-19-3571-2015, 2015
Short summary
Short summary
Commercial cellular networks are built for telecommunication purposes. These kinds of networks have lately been used to obtain rainfall maps at country-wide scales. From previous studies, we now quantify the uncertainties associated with such maps. To do so, we divided the sources or error into two categories: from microwave link measurements and from mapping. It was found that the former is the source that contributes the most to the overall error in rainfall maps from microwave link network.
Y. Brugnara, R. Auchmann, S. Brönnimann, R. J. Allan, I. Auer, M. Barriendos, H. Bergström, J. Bhend, R. Brázdil, G. P. Compo, R. C. Cornes, F. Dominguez-Castro, A. F. V. van Engelen, J. Filipiak, J. Holopainen, S. Jourdain, M. Kunz, J. Luterbacher, M. Maugeri, L. Mercalli, A. Moberg, C. J. Mock, G. Pichard, L. Řezníčková, G. van der Schrier, V. Slonosky, Z. Ustrnul, M. A. Valente, A. Wypych, and X. Yin
Clim. Past, 11, 1027–1047, https://doi.org/10.5194/cp-11-1027-2015, https://doi.org/10.5194/cp-11-1027-2015, 2015
Short summary
Short summary
A data set of instrumental pressure and temperature observations for the early instrumental period (before ca. 1850) is described. This is the result of a digitisation effort involving the period immediately after the eruption of Mount Tambora in 1815, combined with the collection of already available sub-daily time series. The highest data availability is therefore for the years 1815 to 1817. An analysis of pressure variability and of case studies in Europe is performed for that period.
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
A. A. Cimatoribus, S. S. Drijfhout, V. Livina, and G. van der Schrier
Clim. Past, 9, 323–333, https://doi.org/10.5194/cp-9-323-2013, https://doi.org/10.5194/cp-9-323-2013, 2013
Related subject area
Domain: ESSD – Atmosphere | Subject: Meteorology
The PAZ polarimetric radio occultation research dataset for scientific applications
Water vapor Raman lidar observations from multiple sites in the framework of WaLiNeAs
SARAH-3 – satellite-based climate data records of surface solar radiation
A database of deep convective systems derived from the intercalibrated meteorological geostationary satellite fleet and the TOOCAN algorithm (2012–2020)
Generation of global 1 km all-weather instantaneous and daily mean land surface temperatures from MODIS data
A New High-Resolution Multi-Drought Indices Dataset for Mainland China
Special Observing Period (SOP) data for the Year of Polar Prediction site Model Intercomparison Project (YOPPsiteMIP)
Dataset of spatially extensive long-term quality-assured land–atmosphere interactions over the Tibetan Plateau
Multifrequency radar observations of marine clouds during the EPCAPE campaign
Data collected using small uncrewed aircraft systems during the TRacking Aerosol Convection interactions ExpeRiment (TRACER)
LGHAP v2: a global gap-free aerosol optical depth and PM2.5 concentration dataset since 2000 derived via big Earth data analytics
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
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
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
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
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
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
Ramon Padullés, Estel Cardellach, Antía Paz, Santi Oliveras, Douglas C. Hunt, Sergey Sokolovskiy, Jan-Peter Weiss, Kuo-Nung Wang, F. Joe Turk, Chi O. Ao, and Manuel de la Torre Juárez
Earth Syst. Sci. Data, 16, 5643–5663, https://doi.org/10.5194/essd-16-5643-2024, https://doi.org/10.5194/essd-16-5643-2024, 2024
Short summary
Short summary
This dataset provides, for the first time, combined observations of clouds and precipitation with coincident retrievals of atmospheric thermodynamics obtained from the same space-based instrument. Furthermore, it provides the locations of the ray trajectories of the observations along various precipitation-related products interpolated into them with the aim of fostering the use of such dataset in scientific and operational applications.
Frédéric Laly, Patrick Chazette, Julien Totems, Jérémy Lagarrigue, Laurent Forges, and Cyrille Flamant
Earth Syst. Sci. Data, 16, 5579–5602, https://doi.org/10.5194/essd-16-5579-2024, https://doi.org/10.5194/essd-16-5579-2024, 2024
Short summary
Short summary
We present a dataset of water vapor mixing ratio profiles acquired during the Water Vapor Lidar Network Assimilation campaign in fall and winter 2022 and summer 2023, using three lidar systems deployed on the western Mediterranean coastline. This innovative campaign provides access to lower-tropospheric water vapor variability to constrain meteorological forecasting models. The scientific objective is to improve forecasting of heavy-precipation events that lead to flash floods and landslides.
Uwe Pfeifroth, Jaqueline Drücke, Steffen Kothe, Jörg Trentmann, Marc Schröder, and Rainer Hollmann
Earth Syst. Sci. Data, 16, 5243–5265, https://doi.org/10.5194/essd-16-5243-2024, https://doi.org/10.5194/essd-16-5243-2024, 2024
Short summary
Short summary
The energy reaching Earth's surface from the Sun is a quantity of great 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 Climate Monitoring Satellite Application Facility (CM SAF). SARAH-3 covers more than 4 decades and provides a high spatial and temporal resolution, and its validation shows good accuracy and stability.
Thomas Fiolleau and Rémy Roca
Earth Syst. Sci. Data, 16, 4021–4050, https://doi.org/10.5194/essd-16-4021-2024, https://doi.org/10.5194/essd-16-4021-2024, 2024
Short summary
Short summary
This paper presents a database of tropical deep convective systems over the 2012–2020 period, built from a cloud-tracking algorithm called TOOCAN, which has been applied to homogenized infrared observations from a fleet of geostationary satellites. This database aims to analyze the tropical deep convective systems, the evolution of their associated characteristics over their life cycle, their organization, and their importance in the hydrological and energy cycle.
Bing Li, Shunlin Liang, Han Ma, Guanpeng Dong, Xiaobang Liu, Tao He, and Yufang Zhang
Earth Syst. Sci. Data, 16, 3795–3819, https://doi.org/10.5194/essd-16-3795-2024, https://doi.org/10.5194/essd-16-3795-2024, 2024
Short summary
Short summary
This study describes 1 km all-weather instantaneous and daily mean land surface temperature (LST) datasets on the global scale during 2000–2020. It is the first attempt to synergistically estimate all-weather instantaneous and daily mean LST data on a long global-scale time series. The generated datasets were evaluated by the observations from in situ stations and other LST datasets, and the evaluation indicated that the dataset is sufficiently reliable.
Qi Zhang, Chiyuan Miao, Jiajia Su, Jiaojiao Gou, Jinlong Hu, Xi Zhao, and Ye Xu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-270, https://doi.org/10.5194/essd-2024-270, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
Our study introduces CHM_Drought, an advanced meteorological drought dataset covering mainland China, offering detailed insights from 1961 to 2022 at a spatial resolution of 0.1°. This dataset incorporates six key drought indices, including multi-scale versions, facilitating early detection and monitoring of droughts. Through the provision of consistent and reliable data, CHM_Drought enhances our understanding of drought patterns, aiding in effective water management and agricultural planning.
Zen Mariani, Sara M. Morris, Taneil Uttal, Elena Akish, Robert Crawford, Laura Huang, Jonathan Day, Johanna Tjernström, Øystein Godøy, Lara Ferrighi, Leslie M. Hartten, Jareth Holt, Christopher J. Cox, Ewan O'Connor, Roberta Pirazzini, Marion Maturilli, Giri Prakash, James Mather, Kimberly Strong, Pierre Fogal, Vasily Kustov, Gunilla Svensson, Michael Gallagher, and Brian Vasel
Earth Syst. Sci. Data, 16, 3083–3124, https://doi.org/10.5194/essd-16-3083-2024, https://doi.org/10.5194/essd-16-3083-2024, 2024
Short summary
Short summary
During the Year of Polar Prediction (YOPP), we increased measurements in the polar regions and have made dedicated efforts to centralize and standardize all of the different types of datasets that have been collected to facilitate user uptake and model–observation comparisons. This paper is an overview of those efforts and a description of the novel standardized Merged Observation Data Files (MODFs), including a description of the sites, data format, and instruments.
Yaoming Ma, Zhipeng Xie, Yingying Chen, Shaomin Liu, Tao Che, Ziwei Xu, Lunyu Shang, Xiaobo He, Xianhong Meng, Weiqiang Ma, Baiqing Xu, Huabiao Zhao, Junbo Wang, Guangjian Wu, and Xin Li
Earth Syst. Sci. Data, 16, 3017–3043, https://doi.org/10.5194/essd-16-3017-2024, https://doi.org/10.5194/essd-16-3017-2024, 2024
Short summary
Short summary
Current models and satellites struggle to accurately represent the land–atmosphere (L–A) interactions over the Tibetan Plateau. We present the most extensive compilation of in situ observations to date, comprising 17 years of data on L–A interactions across 12 sites. This quality-assured benchmark dataset provides independent validation to improve models and remote sensing for the region, and it enables new investigations of fine-scale L–A processes and their mechanistic drivers.
Juan M. Socuellamos, Raquel Rodriguez Monje, Matthew D. Lebsock, Ken B. Cooper, Robert M. Beauchamp, and Arturo Umeyama
Earth Syst. Sci. Data, 16, 2701–2715, https://doi.org/10.5194/essd-16-2701-2024, https://doi.org/10.5194/essd-16-2701-2024, 2024
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 distribution within clouds and precipitation.
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, Steven Borenstein, Troy Thornberry, Brian Argrow, and Elizabeth Pillar-Little
Earth Syst. Sci. Data, 16, 2525–2541, https://doi.org/10.5194/essd-16-2525-2024, https://doi.org/10.5194/essd-16-2525-2024, 2024
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 part of the TRacking Aerosol Convection interactions ExpeRiment (TRACER) campaign. The data were collected through boundary layer transitions, through sea breeze circulations, and in the pre- and near-storm environment to understand how these processes influence the coastal environment.
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, 16, 2425–2448, https://doi.org/10.5194/essd-16-2425-2024, https://doi.org/10.5194/essd-16-2425-2024, 2024
Short summary
Short summary
A global gap-free high-resolution air pollutant dataset (LGHAP v2) was generated to provide spatially contiguous AOD and PM2.5 concentration maps with daily 1 km resolution from 2000 to 2021. This gap-free dataset has good data accuracies compared to ground-based AOD and PM2.5 concentration observations, which is a reliable database to advance aerosol-related studies and trigger multidisciplinary applications for environmental management, health risk assessment, and climate change 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.
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.
Karl-Göran Karlsson, Martin Stengel, Jan Fokke Meirink, Aku Riihelä, Jörg Trentmann, Tom Akkermans, Diana Stein, Abhay Devasthale, Salomon Eliasson, Erik Johansson, Nina Håkansson, Irina Solodovnik, Nikos Benas, Nicolas Clerbaux, Nathalie Selbach, Marc Schröder, and Rainer Hollmann
Earth Syst. Sci. Data, 15, 4901–4926, https://doi.org/10.5194/essd-15-4901-2023, https://doi.org/10.5194/essd-15-4901-2023, 2023
Short summary
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.
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.
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.
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.
Cited articles
Al-Sakka, H., Boumahmoud, A.-A., Fradon, B., Frasier, S. J., and Tabary, P.: A
new fuzzy logic hydrometeor classification scheme applied to the French
X-, C-, and S-band polarimetric radars, J. Appl. Meteorol. Clim.,
52, 2328–2344, https://doi.org/10.1175/JAMC-D-12-0236.1, 2013. a
Allen, R. J. and DeGaetano, A. T.: Considerations for the use of
radar-derived precipitation estimates in determining return intervals for
extreme areal precipitation amounts, J. Hydrol., 315, 203–219,
https://doi.org/10.1016/j.jhydrol.2005.03.028, 2005. a
Barnes, S. L.: A technique for maximizing details in numerical weather map
analysis, J. Appl. Meteorol., 3, 396–409, 1964. a
Barton, Y., Sideris, I., Raupach, T., Gabella, M., Germann, U., and Martius,
O.: A multi-year assessment of sub-hourly gridded precipitation for
Switzerland based on a blended radar–Rain-gauge dataset, Int. J.
Climatol., 40, 5208–5222, https://doi.org/10.1002/joc.6514, 2020. a
Benas, N., Finkensieper, S., Stengel, M., van Zadelhoff, G.-J., Hanschmann, T., Hollmann, R., and Meirink, J. F.: The MSG-SEVIRI-based cloud property data record CLAAS-2, Earth Syst. Sci. Data, 9, 415–-434, https://doi.org/10.5194/essd-9-415-2017, 2017. a
Berenguer, M., Sempere-Torres, D., Corral, C., and Sánchez-Diezma, R.: A fuzzy
logic technique for identifying nonprecipitating echoes in radar scans, J.
Atmos. Ocean. Tech., 23, 1157–1180, https://doi.org/10.1175/JTECH1914.1, 2006. a
Berg, P., Christensen, O. B., Klehmet, K., Lenderink, G., Olsson, J., Teichmann, C., and Yang, W.: Summertime precipitation extremes in a EURO-CORDEX 0.11∘ ensemble at an hourly resolution, Nat. Hazards Earth Syst. Sci., 19, 957–971, https://doi.org/10.5194/nhess-19-957-2019, 2019. a
Bližňák, V., Kašpar, M., and Müller, M.: Radar-based summer
precipitation climatology of the Czech Republic, Int. J. Climatol., 38,
677–691, https://doi.org/10.1002/joc.5202, 2018. a
Carey, L. D., Rutledge, S. A., Ahijevych, D. A., and Keenan, T. D.: Correcting
propagation effects in C-band polarimetric radar observations of tropical
convection using differential propagation phase, J. Appl. Meteorol., 39,
1405–1433, https://doi.org/10.1175/1520-0450(2000)039<1405:CPEICB>2.0.CO;2, 2000. a
Cornes, R. C., Van der Schrier, G., Van den Besselaar, E. J. M., and Jones,
P. D.: An ensemble version of the E-OBS temperature and precipitation data
sets, J. Geophys. Res.-Atmos., 123, 9391–9409,
https://doi.org/10.1029/2017JD028200, 2018. a, b, c
Crisologo, I., Vulpiani, G., Abon, C. C., David, C. P. C., Bronstert, A., and
Heistermann, M.: Polarimetric rainfall retrieval from a C-band weather
radar in a tropical environment (the Philippines), Asia-Pac. J. Atmos.
Sci., 50, 43–55, https://doi.org/10.1007/s13143-014-0049-y, 2014. a
De Vos, L. W., Leijnse, H., Overeem, A., and Uijlenhoet, R.: Quality control
for crowdsourced personal weather stations to enable operational rainfall
monitoring, Geophys. Res. Lett., 46, 8820–8829,
https://doi.org/10.1029/2019GL083731, 2019. a
Derrien, M. and Le Gléau, H.: MSG/SEVIRI cloud mask and type from SAFNWC,
Int. J. Remote Sens., 26, 4707–4732, 2005. a
Doviak, R. J. and Zrnić, D. S.: Doppler Radar and Weather Observations, second edn.,
Dover Publications, Inc., Mineola, New York, ISBN 0-486-45060-0, 1993. a
Durrans, S. R., Julian, L. T., and Yekta, M.: Estimation of depth-area
relationships using radar-rainfall data, J. Hydrol. Eng., 7, 356–367,
https://doi.org/10.1061/(ASCE)1084-0699(2002)7:5(356), 2002. a
Fabry, F.: Radar Meteorology: Principles and Practice, Cambridge University
Press, Cambridge, U.K., https://doi.org/10.1017/CBO9781107707405, 2015. a, b
Fabry, F., Meunier, V., Treserras, B. P., Cournoyer, A., and Nelson, B.: On the
climatological use of radar data mosaics: possibilities and challenges,
B. Am. Meteorol. Soc., 98, 2135–2148, https://doi.org/10.1175/BAMS-D-15-00256.1,
2017. a, b
Finkensieper, S., Meirink, J.-F., van Zadelhoff, G.-J., Hanschmann, T., Benas,
N., Stengel, M., Fuchs, P., Hollmann, R., and Werscheck, M.: CLAAS-2: CM SAF
CLoud property dAtAset using SEVIRI – Edition 2, Satellite Application
Facility on Climate Monitoring, https://doi.org/10.5676/EUM_SAF_CM/CLAAS/V002, 2016. a
Frech, M., Hagen, M., and Mammen, T.: Monitoring the absolute calibration of a
polarimetric weather radar, J. Atmos. Ocean. Tech., 34, 599–615,
https://doi.org/10.1175/JTECH-D-16-0076.1, 2017. a
Frederick, R. H., Myers, V. A., and Auciello, E. P.: Storm depth-area relations
from digitized radar returns, Water Resour. Res., 13, 675–679, 1977. a
Gabella, M. and Notarpietro, R.: Ground clutter characterization and
elimination in mountainous terrain, in: Proceedings of the 2nd European conference on radar meteorology ERAD and the COST 717 mid-term seminar, https://www.copernicus.org/erad/online/erad-305.pdf (last access: 23 March 2023), 2002. a, b
Garcia-Marti, I., Overeem, A., Noteboom, J. W., de Vos, L., de Haij, M., and
Whan, K.: From proof-of-concept to proof-of-value: approaching third-party
data to operational workflows of national meteorological services, Int. J.
Climatol., 43, 275–292, https://doi.org/10.1002/joc.7757, 2023. a
Goudenhoofdt, E. and Delobbe, L.: Evaluation of radar-gauge merging methods for quantitative precipitation estimates, Hydrol. Earth Syst. Sci., 13, 195–203, https://doi.org/10.5194/hess-13-195-2009, 2009. a
Goudenhoofdt, E. and Delobbe, L.: Generation and verification of rainfall
estimates from 10-yr volumetric weather radar measurements, J. Hydrometeorol.,
17, 1223–1242, https://doi.org/10.1175/JHM-D-15-0166.1, 2016. a, b, c
Gourley, J. J., Tabary, P., and Parent du Chatelet, J.: A fuzzy logic algorithm
for the separation of precipitating from nonprecipitating echoes using
polarimetric radar observations, J. Atmos. Ocean. Tech., 24,
1439–1451, https://doi.org/10.1175/JTECH2035.1, 2007. a, b
Graf, M., Chwala, C., Polz, J., and Kunstmann, H.: Rainfall estimation from a German-wide commercial microwave link network: optimized processing and validation for 1 year of data, Hydrol. Earth Syst. Sci., 24, 2931–2950, https://doi.org/10.5194/hess-24-2931-2020, 2020. a
Graf, M., El Hachem, A., Eisele, M., Seidel, J., Chwala, C., Kunstmann, H.,
and Bárdossy, A.: Rainfall estimates from opportunistic sensors in
Germany across spatio-temporal scales, J. Hydrol.: Regional Studies, 37,
1448–1463, https://doi.org/10.1016/j.ejrh.2021.100883, 2021. a, b
Hazenberg, P., Torfs, P. J. J. F., Leijnse, H., Delrieu, G., and Uijlenhoet,
R.: Identification and uncertainty estimation of vertical reflectivity
profiles using a Lagrangian approach to support quantitative precipitation
measurements by weather radar, J. Geophys. Res.-Atmospheres, 118,
10243–10261, https://doi.org/10.1002/jgrd.50726, 2013. a, b
Heistermann, M., Jacobi, S., and Pfaff, T.: Technical Note: An open source library for processing weather radar data (wradlib), Hydrol. Earth Syst. Sci., 17, 863–871, https://doi.org/10.5194/hess-17-863-2013, 2013. a, b
Hitschfeld, W. and Bordan, J.: Errors inherent in the radar measurement of
rainfall at attenuating wavelengths, J. Meteorol., 11, 58–67,
https://doi.org/10.1175/1520-0469(1954)011<0058:EIITRM>2.0.CO;2, 1954. a
Holleman, I.: Bias adjustment and long-term verification of radar-based
precipitation estimates, Meteor. Appl., 14, 195–203, https://doi.org/10.1002/met.22,
2007. a
Huuskonen, A., Saltikoff, E., and Holleman, I.: The operational weather radar
network in Europe, B. Am. Meteorol. Soc., 95, 897–907,
https://doi.org/10.1175/BAMS-D-12-00216.1, 2014. a
Jacobi, S. and Heistermann, M.: Benchmarking attenuation correction procedures
for six years of single-polarized C-band weather radar observations in
South-West Germany, Geomat. Nat. Haz. Risk, 7, 1785–1799,
https://doi.org/10.1080/19475705.2016.1155080, 2016. a, b
Kitchen, M. and Blackall, R. M.: Representativeness errors in comparisons
between radar and gauge measurements of rainfall, J. Hydrol., 134, 13–33,
1992. a
Klein Tank, A. M. G., Wijngaard, J. B., Können, G. P., et al.: Daily dataset of 20th-century surface air
temperature and precipitation series for the European Climate
Assessment, Int. J. Climatol., 22, 1441–1453, https://doi.org/10.1002/joc.773,
2002. a
Klok, E. J. and Klein Tank, A. M. G.: Updated and extended European dataset of daily
climate observation, Int. J. Climatol., 29, 1182–1191,
https://doi.org/10.1002/joc.1779, 2008. a
KNMI: Precipitation – 5 minute precipitation accumulations from climatological
gauge-adjusted radar dataset for The Netherlands (1 km, extended mask) in
KNMI HDF5 format, KNMI Data Platform [data set], https://dataplatform.knmi.nl/dataset/rad-nl25-rac-mfbs-em-5min-2-0, last access: 27 March 2023. a
Krause, J. M.: A simple algorithm to discriminate between meteorological and
nonmeteorological radar echoes, J. Atmos. Ocean. Tech., 33, 1875–1885,
https://doi.org/10.1175/JTECH-D-15-0239.1, 2016. a
Leijnse, H., Uijlenhoet, R., and Stricker, J. N. M.: Rainfall measurement using
radio links from cellular communication networks, Water Resour. Res., 43,
W03201, https://doi.org/10.1029/2006WR005631, 2007. a
Lengfeld, K., Winterrath, T., Junghänel, T., Hafer, M., and Becker, A.:
Characteristic spatial extent of hourly and daily precipitation events in
Germany derived from 16 years of radar data, Meteorol. Z., 28, 363–378,
https://doi.org/10.1127/metz/2019/0964, 2019. a
Lengfeld, K., Walawender, E., Winterrath, T., and Becker, A.: CatRaRE: A
Catalogue of radar-based heavy rainfall events in Germany derived from 20
years of data, Meteorol. Z., 30, 469–487, https://doi.org/10.1127/metz/2021/1088, 2021. a
Lochbihler, K., Lenderink, G., and Siebesma, A. P.: The spatial extent of
rainfall events and its relation to precipitation scaling, Geophys. Res.
Lett., 44, 8629–8636, https://doi.org/10.1002/2017GL074857, 2017. a
Marra, F. and Morin, E.: Use of radar QPE for the derivation of
Intensity–Duration–Frequency curves in a range of climatic regimes, J.
Hydrol., 531, 427–440, https://doi.org/10.1016/j.jhydrol.2015.08.064, 2015. a
McGraw, D., Nikolopoulos, E. I., Marra, F., and Anagnostou, E. N.:
Precipitation frequency analyses based on radar estimates: An evaluation over
the contiguous United States, J. Hydrol., 573, 299–310,
https://doi.org/10.1016/j.jhydrol.2019.03.032, 2019. a
Messer, H. A., Zinevich, A., and Alpert, P.: Environmental monitoring by
wireless communication networks, Science, 312, 713,
https://doi.org/10.1126/science.1120034, 2006. a
Met Office: Cartopy: a cartographic python library with a Matplotlib
interface, https://scitools.org.uk/cartopy (last access: 23 March 2023), 2022. a
Michelson, D. B., Lewandowski, R., Szewczykowski, M., Beekhuis, H., Haase, G.,
Mammen, T., Faure, D., Simpson, M., Leijnse, H., and Johnson, D.:
EUMETNET OPERA weather radar information model for implementation
with the HDF5 file format Version 2.3, EUMETNET OPERA,
https://www.eumetnet.eu/wp-content/uploads/2019/01/ODIM_H5_v23.pdf (last access: 23 March 2023),
2019. a, b, c
Mühlbauer, K., Heistermann, M., and Goudenhoofdt, E.: wradlib/wradlib:
wradlib release v1.9.0 (1.9.0), Zenodo [code], https://doi.org/10.5281/zenodo.4290240, 2020. a, b
Nelson, B. R., Prat, O. P., Seo, D.-J., and Habib, E.: Assessment and
implications of NCEP Stage IV quantitative precipitation estimates for
product intercomparisons, Weather Forecast., 31, 371–394,
https://doi.org/10.1175/WAF-D-14-00112.1, 2016. a
NWC SAF: Algorithm Theoretical Basis Document for ”Cloud Products”
(CMa-PGE01 v3.2, CT-PGE02 v2.2 & CTTH-PGE03 v2.2), Tech. Rep.
SAF/NWC/CDOP2/MFL/SCI/ATBD/01, Issue 3, Rev. 2.1, EUMETSAT Satellite
Application Facility on Nowcasting and Short range Forecasting, https://www.nwcsaf.org/AemetWebContents/ScientificDocumentation/Documentation/MSG/SAF-NWC-CDOP2-MFL-SCI-ATBD-01_v3.2.1.pdf (last access: 27 March 2023), 2013. a
OPERA: OPERA – Eumetnet,
https://www.eumetnet.eu/activities/observations-programme/current-activities/opera/ (last access: 23 March 2023),
2022. a
Overeem, A.: EURADCLIM-tools (v.1.0), Zenodo [code], https://doi.org/10.5281/zenodo.7473816, 2022. a
Overeem, A., Buishand, T. A., and Holleman, I.: Extreme rainfall analysis and
estimation of depth-duration-frequency curves using weather radar, Water
Resour. Res., 45, W10424, https://doi.org/10.1029/2009WR007869,
2009a. a
Overeem, A., Holleman, I., and Buishand, A.: Derivation of a 10-year
radar-based climatology of rainfall, J. Appl. Meteorol. Clim., 48,
1448–1463, https://doi.org/10.1175/2009JAMC1954.1, 2009b. a, b
Overeem, A., Buishand, T. A., Holleman, I., and Uijlenhoet, R.: Extreme value
modeling of areal rainfall from weather radar, Water Resour. Res., 46,
W09514, https://doi.org/10.1029/2009WR008517, 2010. a
Overeem, A., Leijnse, H., and Uijlenhoet, R.: Two and a half years of
country‐wide rainfall maps using radio links from commercial cellular
telecommunication networks, Water Resour. Res., 52, 8039–8065,
https://doi.org/10.1002/2016WR019412, 2016. a
Overeem, A., Uijlenhoet, R., and Leijnse, H.: Full-year evaluation of
non-meteorological echo removal with dual-polarization fuzzy logic for two
C-band radars in a temperate climate, J. Atmos. Ocean. Tech., 37,
1643–1660, https://doi.org/10.1175/JTECH-D-19-0149.1, 2020. a, b
Overeem, A., de Vries, H., Al Sakka, H., Uijlenhoet, R., and Leijnse, H.:
Rainfall-induced attenuation correction for two operational dual-polarization
C-band radars in the Netherlands, J. Atmos. Ocean. Tech., 38,
1125–1142, https://doi.org/10.1175/JTECH-D-20-0113.1, 2021. a, b
Overeem, A., van den Besselaar, E., van der Schrier, G., Meirink, J., van der
Plas, E., and Leijnse, H.: EURADCLIM: The European climatological
gauge-adjusted radar precipitation dataset (1-h accumulations), KNMI Data Platform [data set],
https://doi.org/10.21944/7ypj-wn68, 2022a. a, b
Overeem, A., van den Besselaar, E., van der Schrier, G., Meirink, J., van der
Plas, E., and Leijnse, H.: EURADCLIM: The European climatological
gauge-adjusted radar precipitation dataset (24-h accumulations), KNMI Data Platform [data set],
https://doi.org/10.21944/1a54-gg96, 2022b. a, b
Project team ECA&D and Royal Netherlands Meteorological Institute KNMI:
European Climate Assessment & Dataset (ECA&D), Algorithm
Theoretical Basis Document (ATBD), Version 11,
https://knmi-ecad-assets-prd.s3.amazonaws.com/documents/atbd.pdf (last access: 23 March 2023), 2021. a
Rauber, R. M. and Nesbitt, S. L.: Radar Meteorology: A First Course, John Wiley
& Sons, Hoboken, NJ, USA, https://doi.org/10.1002/9781118432662, 2018. a
Ryzhkov, A. V. and Zrnic, D. S.: Radar Polarimetry for Weather Observations,
Springer Nature Switzerland AG, Cham, Switzerland,
https://doi.org/10.1007/978-3-030-05093-1, 2019. a
Saltikoff, E., Cho, J. Y. N., Tristant, P., Huuskonen, A., Allmon, L., Cook,
R., Becker, E., and Joe, P.: The threat to weather radars by wireless
technology, B. Am. Meteorol. Soc., 97, 1159–1167,
https://doi.org/10.1175/BAMS-D-15-00048.1, 2016. a
Saltikoff, E., Friedrich, K., Soderholm, J., Lengfeld, K., Nelson, B., Becker,
A., Hollmann, R., Urban, B., Heistermann, M., and Tassone, C.: An overview of
using weather radar for climatological studies: successes, challenges, and
potential, B. Am. Meteorol. Soc., 100, 1739–1752,
https://doi.org/10.1175/BAMS-D-18-0166.1, 2019a. a
Saltikoff, E., Haase, G., Delobbe, L., Gaussiat, N., Martet, M., Idziorek, D.,
Leijnse, H., Novák, P., Lukach, M., and Stephan, K.: OPERA the radar
project, Atmosphere, 10, 320, https://doi.org/10.3390/atmos10060320, 2019b. a, b
Skofronick‐Jackson, G., Kirschbaum, D., Petersen, W., Huffman, G., Kidd, C., Stocker, E., and Kakar, R.: The
Global Precipitation Measurement (GPM) mission's scientific
achievements and societal contributions: reviewing four years of advanced
rain and snow observations, Q. J. Roy. Meteorol. Soc., 144, 27–48,
https://doi.org/10.1002/qj.3313, 2018. a
Sun, Q., Miao, C., Duan, Q., Ashouri, H., Sorooshian, S., and Hsu, K.-L.: A
review of global precipitation data sets: data sources, estimation, and
intercomparisons, Rev. Geophys., 56, 79–107, https://doi.org/10.1002/2017RG000574,
2018. a
Tabary, P., Vulpiani, G., Gourley, J. J., Illingworth, A. J., Thompson, R. J.,
and Bousquet, O.: Unusually high differential attenuation at C Band:
results from a two-year analysis of the French Trappes polarimetric radar
data, J. Appl. Meteorol. Clim., 48, 2037–2053,
https://doi.org/10.1175/2009JAMC2039.1, 2009. a
Testud, J., Le Bouar, E., Obligis, E., and Ali-Mehenni, M.: The rain profiling
algorithm applied to polarimetric weather radar, J. Atmos. Oceanic
Technol., 17, 332–356,
https://doi.org/10.1175/1520-0426(2000)017<0332:TRPAAT>2.0.CO;2, 2000. a
Van de Beek, C. Z., Leijnse, H., Torfs, P. J. J. F., and Uijlenhoet, R.:
Seasonal semi-variance of Dutch rainfall at hourly to daily scales, Adv.
Water Resour., 45, 76–85, https://doi.org/10.1016/j.advwatres.2012.03.023, 2012. a, b
Van der Plas, E., Schmeits, M., Hooijman, N., and Kok, K.: A comparative
verification of high-resolution precipitation forecasts using model output
statistics, Mon. Weather Rev., 145, 4037–4054, https://doi.org/10.1175/MWR-D-16-0256.1,
2017. a
Vulpiani, G., Montopoli, M., Passeri, L. D., Gioia, A. G., Giordano, P., and
Marzano, F. S.: On the use of dual-polarized C-band radar for operational
rainfall retrieval in mountainous areas, J. Appl. Meteorol. Clim., 51,
405–425, https://doi.org/10.1175/JAMC-D-10-05024.1, 2012.
a
Winterrath, T., Brendel, C., Hafer, M., Junghänel, T., Klameth, A.,
Lengfeld, K., Walawender, E., Weigl, E., and Becker, A.: RADKLIM
Version 2017.002: Reprocessed gauge-adjusted radar data, one-hour
precipitation sums (RW), DWD [data set], https://doi.org/10.5676/DWD/RADKLIM_RW_V2017.002, 2018. a, b
Wradlib: wradlib.clutter.histo_cut, wradlib,
https://docs.wradlib.org/en/stable/generated/wradlib.clutter.histo_cut.html (last access: 23 March 2023),
2022. a
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).
EURADCLIM is a new precipitation dataset covering a large part of Europe. It is based on weather...
Altmetrics
Final-revised paper
Preprint