Articles | Volume 14, issue 2
https://doi.org/10.5194/essd-14-885-2022
© Author(s) 2022. 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-14-885-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
24 Feb 2022
Data description paper |
| 24 Feb 2022
| 24 Feb 2022
The Large eddy Observatory, Voitsumra Experiment 2019 (LOVE19) with high-resolution, spatially distributed observations of air temperature, wind speed, and wind direction from fiber-optic distributed sensing, towers, and ground-based remote sensing
Micrometeorology Group, University of Bayreuth, Bayreuth, Germany
Bayreuth Center of Ecology and Environmental Research, BayCEER, Bayreuth, Germany
Anita Freundorfer
Micrometeorology Group, University of Bayreuth, Bayreuth, Germany
Antonia Fritz
Micrometeorology Group, University of Bayreuth, Bayreuth, Germany
now at: Institute for Meteorology and Geophysics, University of Innsbruck, Innsbruck, Austria
Johann Schneider
Micrometeorology Group, University of Bayreuth, Bayreuth, Germany
Johannes Olesch
Micrometeorology Group, University of Bayreuth, Bayreuth, Germany
Wolfgang Babel
Micrometeorology Group, University of Bayreuth, Bayreuth, Germany
Bayreuth Center of Ecology and Environmental Research, BayCEER, Bayreuth, Germany
Christoph K. Thomas
Micrometeorology Group, University of Bayreuth, Bayreuth, Germany
Bayreuth Center of Ecology and Environmental Research, BayCEER, Bayreuth, Germany
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Mohammad Abdoli, Karl Lapo, Johann Schneider, Johannes Olesch, and Christoph K. Thomas
Atmos. Meas. Tech., 16, 809–824, https://doi.org/10.5194/amt-16-809-2023, https://doi.org/10.5194/amt-16-809-2023, 2023
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In this study, we compute the distributed sensible heat flux using a distributed temperature sensing technique, whose magnitude, sign, and temporal dynamics compare reasonably well to estimates from classical eddy covariance measurements from sonic anemometry. Despite the remaining uncertainty in computed fluxes, the results demonstrate the potential of the novel method to compute spatially resolving sensible heat flux measurement and encourage further research.
Marie-Louise Zeller, Jannis-Michael Huss, Lena Pfister, Karl E. Lapo, Daniela Littmann, Johann Schneider, Alexander Schulz, and Christoph K. Thomas
Earth Syst. Sci. Data, 13, 3439–3452, https://doi.org/10.5194/essd-13-3439-2021, https://doi.org/10.5194/essd-13-3439-2021, 2021
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The boundary layer (BL) is well understood when convectively mixed, yet we lack this understanding when it becomes stable and no longer follows classic similarity theories. The NYTEFOX campaign collected a unique meteorological data set in the Arctic BL of Svalbard during polar night, where it tends to be highly stable. Using innovative fiber-optic distributed sensing, we are able to provide unique insight into atmospheric motions across large distances resolved continuously in space and time.
Olli Peltola, Karl Lapo, Ilkka Martinkauppi, Ewan O'Connor, Christoph K. Thomas, and Timo Vesala
Atmos. Meas. Tech., 14, 2409–2427, https://doi.org/10.5194/amt-14-2409-2021, https://doi.org/10.5194/amt-14-2409-2021, 2021
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We evaluated the suitability of fiber-optic distributed temperature sensing (DTS) for observing spatial (>25 cm) and temporal (>1 s) details of airflow within and above forests. The DTS measurements could discern up to third-order moments of the flow and observe spatial details of coherent flow motions. Similar measurements are not possible with more conventional measurement techniques. Hence, the DTS measurements will provide key insights into flows close to roughness elements, e.g. trees.
Karl Lapo, Anita Freundorfer, Lena Pfister, Johann Schneider, John Selker, and Christoph Thomas
Atmos. Meas. Tech., 13, 1563–1573, https://doi.org/10.5194/amt-13-1563-2020, https://doi.org/10.5194/amt-13-1563-2020, 2020
Short summary
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Most observations of the atmosphere are
point observations, which only measure a small area around the sensor. This limitation creates problems for a number of disciplines, especially those that focus on how the surface and atmosphere exchange heat, mass, and momentum. We used distributed temperature sensing with fiber optics to demonstrate a key breakthrough in observing wind direction in a distributed way, i.e., not at a point, using small structures attached to the fiber-optic cables.
Andrew W. Seidl, Aina Johannessen, Alena Dekhtyareva, Jannis M. Huss, Marius O. Jonassen, Alexander Schulz, Ove Hermansen, Christoph K. Thomas, and Harald Sodemann
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-293, https://doi.org/10.5194/essd-2024-293, 2024
Preprint under review for ESSD
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ISLAS2020 set out to measure the stable water isotopic composition of Arctic moisture. By not only measuring at different sites around Ny-Ålesund, Svalbard, but also measuring at variable heights above surface level, we aim to characterize processes that produce or modify the isotopic composition. We also collect precipitation samples from sites that were typically downstream of Ny-Ålesund, so as to capture the isotopic composition during removal from the atmospheric water cycle.
Eike Maximilian Esders, Christoph Georgi, Wolfgang Babel, Andreas Held, and Christoph Karl Thomas
Aerosol Research, 2, 235–243, https://doi.org/10.5194/ar-2-235-2024, https://doi.org/10.5194/ar-2-235-2024, 2024
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Our study explores how tiny plastic particles, known as microplastics (MPs), move through the air. We focus on their journey in a wind tunnel to mimic atmospheric transport. Depending on the air speed and the height of their release, they move downwards or upwards. These results suggest that MPs behave like mineral particles and that we can expect MPs to accumulate where natural dust also accumulates in the environment, offering insights for predicting the spread and impacts of MPs.
Julius Seidler, Markus N. Friedrich, Christoph K. Thomas, and Anke C. Nölscher
Atmos. Chem. Phys., 24, 137–153, https://doi.org/10.5194/acp-24-137-2024, https://doi.org/10.5194/acp-24-137-2024, 2024
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Here, we study the transport of ultrafine particles (UFPs) from an airport to two new adjacent measuring sites for 1 year. The number of UFPs in the air and the diurnal variation are typical urban. Winds from the airport show increased number concentrations. Additionally, considering wind frequencies, we estimate that, from all UFPs measured at the two sites, 10 %–14 % originate from the airport and/or other UFP sources from between the airport and site.
Eike Maximilian Esders, Sebastian Sittl, Inka Krammel, Wolfgang Babel, Georg Papastavrou, and Christoph Karl Thomas
Atmos. Chem. Phys., 23, 15835–15851, https://doi.org/10.5194/acp-23-15835-2023, https://doi.org/10.5194/acp-23-15835-2023, 2023
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Do microplastics behave differently from mineral particles when they are exposed to wind? We observed plastic and mineral particles in a wind tunnel and measured at what wind speeds the particles start to move. The results indicate that microplastics start to move at smaller wind speeds as they weigh less and are less sticky. Hence, we think that microplastics also move more easily in the environment.
Mohammad Abdoli, Karl Lapo, Johann Schneider, Johannes Olesch, and Christoph K. Thomas
Atmos. Meas. Tech., 16, 809–824, https://doi.org/10.5194/amt-16-809-2023, https://doi.org/10.5194/amt-16-809-2023, 2023
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In this study, we compute the distributed sensible heat flux using a distributed temperature sensing technique, whose magnitude, sign, and temporal dynamics compare reasonably well to estimates from classical eddy covariance measurements from sonic anemometry. Despite the remaining uncertainty in computed fluxes, the results demonstrate the potential of the novel method to compute spatially resolving sensible heat flux measurement and encourage further research.
Wolfgang Fischer, Christoph K. Thomas, Nikita Zimov, and Mathias Göckede
Biogeosciences, 19, 1611–1633, https://doi.org/10.5194/bg-19-1611-2022, https://doi.org/10.5194/bg-19-1611-2022, 2022
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Arctic permafrost ecosystems may release large amounts of carbon under warmer future climates and may therefore accelerate global climate change. Our study investigated how long-term grazing by large animals influenced ecosystem characteristics and carbon budgets at a Siberian permafrost site. Our results demonstrate that such management can contribute to stabilizing ecosystems to keep carbon in the ground, particularly through drying soils and reducing methane emissions.
Teresa Vogl, Amy Hrdina, and Christoph K. Thomas
Biogeosciences, 18, 5097–5115, https://doi.org/10.5194/bg-18-5097-2021, https://doi.org/10.5194/bg-18-5097-2021, 2021
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The relaxed eddy accumulation technique is a method used for measuring fluxes of chemical species in the atmosphere. It relies on a proportionality factor, β, which can be determined using different methods. Also, different techniques for sampling can be used by only drawing air into the measurement system when vertical wind velocity exceeds a certain threshold. We compare different ways to obtain β and different threshold techniques to direct flux measurements for three different sites.
Marie-Louise Zeller, Jannis-Michael Huss, Lena Pfister, Karl E. Lapo, Daniela Littmann, Johann Schneider, Alexander Schulz, and Christoph K. Thomas
Earth Syst. Sci. Data, 13, 3439–3452, https://doi.org/10.5194/essd-13-3439-2021, https://doi.org/10.5194/essd-13-3439-2021, 2021
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The boundary layer (BL) is well understood when convectively mixed, yet we lack this understanding when it becomes stable and no longer follows classic similarity theories. The NYTEFOX campaign collected a unique meteorological data set in the Arctic BL of Svalbard during polar night, where it tends to be highly stable. Using innovative fiber-optic distributed sensing, we are able to provide unique insight into atmospheric motions across large distances resolved continuously in space and time.
Olli Peltola, Karl Lapo, Ilkka Martinkauppi, Ewan O'Connor, Christoph K. Thomas, and Timo Vesala
Atmos. Meas. Tech., 14, 2409–2427, https://doi.org/10.5194/amt-14-2409-2021, https://doi.org/10.5194/amt-14-2409-2021, 2021
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We evaluated the suitability of fiber-optic distributed temperature sensing (DTS) for observing spatial (>25 cm) and temporal (>1 s) details of airflow within and above forests. The DTS measurements could discern up to third-order moments of the flow and observe spatial details of coherent flow motions. Similar measurements are not possible with more conventional measurement techniques. Hence, the DTS measurements will provide key insights into flows close to roughness elements, e.g. trees.
Karl Lapo, Anita Freundorfer, Lena Pfister, Johann Schneider, John Selker, and Christoph Thomas
Atmos. Meas. Tech., 13, 1563–1573, https://doi.org/10.5194/amt-13-1563-2020, https://doi.org/10.5194/amt-13-1563-2020, 2020
Short summary
Short summary
Most observations of the atmosphere are
point observations, which only measure a small area around the sensor. This limitation creates problems for a number of disciplines, especially those that focus on how the surface and atmosphere exchange heat, mass, and momentum. We used distributed temperature sensing with fiber optics to demonstrate a key breakthrough in observing wind direction in a distributed way, i.e., not at a point, using small structures attached to the fiber-optic cables.
Armin Sigmund, Korbinian Freier, Till Rehm, Ludwig Ries, Christian Schunk, Anette Menzel, and Christoph K. Thomas
Atmos. Chem. Phys., 19, 12477–12494, https://doi.org/10.5194/acp-19-12477-2019, https://doi.org/10.5194/acp-19-12477-2019, 2019
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Air masses at the Schneefernerhaus mountain site at Zugspitze Mountain, Germany, were classified with respect to the atmospheric layer from which they originated and their degree of pollution. Measurements of several gases, particulate matter, and standard meteorological quantities indicated that polluted air was lifted to the site in 31 % of cases and clean air descended to the site in approximately 14 % cases while most of the remaining cases were ambiguous.
Tobias Linhardt, Joseph S. Levy, and Christoph K. Thomas
The Cryosphere, 13, 2203–2219, https://doi.org/10.5194/tc-13-2203-2019, https://doi.org/10.5194/tc-13-2203-2019, 2019
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This study presents surface energy fluxes in an Antarctic polar desert in the summer season, comparing wetted soil at a water track with dominating dry soils. Elevated energy uptake, evaporation, and soil heat fluxes at the water track highlight the importance of wetted soils for water and energy cycling in polar deserts. This connection will grow more relevant, as wetted soils are expected to expand due to climate warming, with implications for landscape-scale hydrology and soil ecosystems.
Anne Klosterhalfen, Alexander Graf, Nicolas Brüggemann, Clemens Drüe, Odilia Esser, María P. González-Dugo, Günther Heinemann, Cor M. J. Jacobs, Matthias Mauder, Arnold F. Moene, Patrizia Ney, Thomas Pütz, Corinna Rebmann, Mario Ramos Rodríguez, Todd M. Scanlon, Marius Schmidt, Rainer Steinbrecher, Christoph K. Thomas, Veronika Valler, Matthias J. Zeeman, and Harry Vereecken
Biogeosciences, 16, 1111–1132, https://doi.org/10.5194/bg-16-1111-2019, https://doi.org/10.5194/bg-16-1111-2019, 2019
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To obtain magnitudes of flux components of H2O and CO2 (e.g., transpiration, soil respiration), we applied source partitioning approaches after Scanlon and Kustas (2010) and after Thomas et al. (2008) to high-frequency eddy covariance measurements of 12 study sites covering various ecosystems (croplands, grasslands, and forests) in different climatic regions. We analyzed the interrelations among turbulence, site characteristics, and the performance of both partitioning methods.
Thomas Foken, Wolfgang Babel, and Christoph Thomas
Atmos. Meas. Tech., 12, 971–976, https://doi.org/10.5194/amt-12-971-2019, https://doi.org/10.5194/amt-12-971-2019, 2019
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Recently reported trends of carbon dioxide uptake pose the question of whether trends may be the result of the limited digitalization of gas analysers and sonic anemometers used in the 1990s. Modifying a 12 bit digitalization and the instrument error reported for the R2 and R3 sonic anemometers found elsewhere, the influence of these deficits in comparison to the now commonly used 16 bit digitalization were quantified. Both issues have an effect only on trace gas fluxes of small magnitude.
Kathrin Gatzsche, Wolfgang Babel, Eva Falge, Rex David Pyles, Kyaw Tha Paw U, Armin Raabe, and Thomas Foken
Biogeosciences, 15, 2945–2960, https://doi.org/10.5194/bg-15-2945-2018, https://doi.org/10.5194/bg-15-2945-2018, 2018
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The ecosystem is a significant sink of carbon dioxide. To quantify this sink, very complex and validated models are required. However, the comparison of modeled and measured energy and matter fluxes in a heterogeneous landscape is still a challenge. On the one hand, models must be applied for various surface types, while on the other hand the comparison of the fluxes is only possible based on the flux source areas. This paper treats the potential aggregation of modeled fluxes and its validation.
Armin Sigmund, Lena Pfister, Chadi Sayde, and Christoph K. Thomas
Atmos. Meas. Tech., 10, 2149–2162, https://doi.org/10.5194/amt-10-2149-2017, https://doi.org/10.5194/amt-10-2149-2017, 2017
W. Babel, T. Biermann, H. Coners, E. Falge, E. Seeber, J. Ingrisch, P.-M. Schleuß, T. Gerken, J. Leonbacher, T. Leipold, S. Willinghöfer, K. Schützenmeister, O. Shibistova, L. Becker, S. Hafner, S. Spielvogel, X. Li, X. Xu, Y. Sun, L. Zhang, Y. Yang, Y. Ma, K. Wesche, H.-F. Graf, C. Leuschner, G. Guggenberger, Y. Kuzyakov, G. Miehe, and T. Foken
Biogeosciences, 11, 6633–6656, https://doi.org/10.5194/bg-11-6633-2014, https://doi.org/10.5194/bg-11-6633-2014, 2014
J. Hübner, J. Olesch, H. Falke, F. X. Meixner, and T. Foken
Atmos. Meas. Tech., 7, 2967–2980, https://doi.org/10.5194/amt-7-2967-2014, https://doi.org/10.5194/amt-7-2967-2014, 2014
M. Li, W. Babel, K. Tanaka, and T. Foken
Atmos. Meas. Tech., 6, 221–229, https://doi.org/10.5194/amt-6-221-2013, https://doi.org/10.5194/amt-6-221-2013, 2013
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Observations of surface energy fluxes and meteorology in the seasonally snow-covered high-elevation East River watershed during SPLASH, 2021–2023
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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
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Earth Syst. Sci. Data, 17, 2113–2133, https://doi.org/10.5194/essd-17-2113-2025, https://doi.org/10.5194/essd-17-2113-2025, 2025
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Susana Barbosa, Nuno Dias, Carlos Almeida, Guilherme Amaral, António Ferreira, António Camilo, and Eduardo Silva
Earth Syst. Sci. Data, 17, 1393–1405, https://doi.org/10.5194/essd-17-1393-2025, https://doi.org/10.5194/essd-17-1393-2025, 2025
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The electric field in the Earth's atmosphere reflects global planetary conditions. It is influenced by both atmospheric processes (such as thunderstorms, pollution, and aerosols) and space weather. Marine measurements of the electric field are rare. Here, we present a unique dataset of atmospheric electric field measurements taken over the Atlantic Ocean. This dataset is valuable not only for atmospheric electricity studies but also for research on climate and space–Earth interactions.
Pantelis Georgiades, Theo Economou, Yiannis Proestos, Jose Araya, Jos Lelieveld, and Marco Neira
Earth Syst. Sci. Data, 17, 1153–1171, https://doi.org/10.5194/essd-17-1153-2025, https://doi.org/10.5194/essd-17-1153-2025, 2025
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Climate change is posing increasing challenges in the dairy cattle farming sector, as heat stress adversely affects the animals' health and milk production. To accurately assess these impacts, we developed a machine learning model to downscale daily climate data to hourly Temperature Humidity Index (THI) values. We utilized historical weather data to train our model and applied them to future climate projections, under two climate scenarios.
Deli Meng, Jianping Guo, Juan Chen, Xiaoran Guo, Ning Li, Yuping Sun, Zhen Zhang, Na Tang, Hui Xu, Tianmeng Chen, Rongfang Yang, and Jiajia Hua
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-138, https://doi.org/10.5194/essd-2025-138, 2025
Revised manuscript accepted for ESSD
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This study provides a high-resolution dataset of low-level atmospheric turbulence across China, using radar and weather balloon observations. It reveals regional and seasonal variations in turbulence, with stronger activity in spring and summer. The dataset supports weather forecasting, aviation safety, and low-altitude flight planning, aiding China’s growing low-altitude economy and accessible at https://doi.org/10.5281/zenodo.14959025.
Qi Zhang, Chiyuan Miao, Jiajia Su, Jiaojiao Gou, Jinlong Hu, Xi Zhao, and Ye Xu
Earth Syst. Sci. Data, 17, 837–853, https://doi.org/10.5194/essd-17-837-2025, https://doi.org/10.5194/essd-17-837-2025, 2025
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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.
Zhiqi Xu, Jianping Guo, Guwei Zhang, Yuchen Ye, Haikun Zhao, and Haishan Chen
Earth Syst. Sci. Data, 16, 5753–5766, https://doi.org/10.5194/essd-16-5753-2024, https://doi.org/10.5194/essd-16-5753-2024, 2024
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Tropical cyclones (TCs) are powerful weather systems that can cause extreme disasters. Here we generate a global long-term TC size and intensity reconstruction dataset, covering a time period from 1959 to 2022, with a 3 h temporal resolution, using machine learning models. These can be valuable for filling observational data gaps and advancing our understanding of TC climatology, thereby facilitating risk assessments and defenses against TC-related disasters.
Matilde García-Valdecasas Ojeda, Feliciano Solano-Farias, David Donaire-Montaño, Emilio Romero-Jiménez, Juan José Rosa-Cánovas, Yolanda Castro-Díez, Sonia Raquel Gámiz-Fortis, and María Jesús Esteban-Parra
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-522, https://doi.org/10.5194/essd-2024-522, 2024
Revised manuscript accepted for ESSD
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This work aims to present a series of climate datasets for Sierra Nevada, a region especially vulnerable to climate change in Southern Spain. The database consists of primary climate variables such as precipitation, temperature, radiation, wind speed, pressure, and atmospheric humidity, but also bioclimatic variables and extreme indices, both useful information for assessing the impact of climate change in this region. These datasets are only available on https://doi.org/10.5281/zenodo.14364865
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
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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
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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
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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.
David Bromwich, Sheng-Hung Wang, Xun Zou, and Alexandra Ensign
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-353, https://doi.org/10.5194/essd-2024-353, 2024
Revised manuscript accepted for ESSD
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Antarctica is a major player in Earth’s climate with the most direct influence arising from its potential to raise global sea level by a meter or more in the coming decades. Near-surface air temperature is the primary variable used to monitor the climate of this remote but important region. Continent-wide direct but sparse measurements that started around 1958 are used to construct a monthly air temperature data set for all of Antarctica spanning 1958–2022.
Xinyan Liu, Tao He, Qingxin Wang, Xiongxin Xiao, Yichuan Ma, Yanyan Wang, Shanjun Luo, Lei Du, and Zhaocong Wu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-458, https://doi.org/10.5194/essd-2024-458, 2024
Revised manuscript accepted for ESSD
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This study addresses the challenge of how clouds affect the Earth's energy balance, which is vital for understanding climate change. We developed a new method to create long-term cloud radiative kernels to improve the accuracy of sunlight reaching the surface, which significantly reduces errors. Findings suggest that prior estimates of cloud cooling effects may have been overstated, emphasizing the need for better strategies to manage climate change impacts in the Arctic.
Clare Marie Flynn, Julia Moemken, Joaquim G. Pinto, and Gabriele Messori
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-298, https://doi.org/10.5194/essd-2024-298, 2024
Revised manuscript accepted for ESSD
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We created a new, publicly available database of the Top 50 most extreme European winter windstorms from each of four different meteorological input data sets covering the years 1995–2015. We found variability in all aspects of our database, from which storms were included in the Top 50 storms for each input to their spatial variability. We urge users of our database to consider the storms as identified from two or more input sources within our database, where possible.
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
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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
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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.
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
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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
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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.
Jianfeng Li, Andrew Geiss, Zhe Feng, L. Ruby Leung, Yun Qian, and Wenjun Cui
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-112, https://doi.org/10.5194/essd-2024-112, 2024
Revised manuscript accepted for ESSD
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We develop a high-resolution (4 km and hourly) observational derecho dataset over the United States east of the Rocky Mountains from 2004 to 2021 by using a mesoscale convective system dataset, bow echo detection based on a machine learning method, hourly gust speed measurements, and physically based identification criteria.
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
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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
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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.
Zhiwei Yang, Jian Peng, Yanxu Liu, Song Jiang, Xueyan Cheng, Xuebang Liu, Jianquan Dong, Tiantian Hua, and Xiaoyu Yu
Earth Syst. Sci. Data, 16, 2407–2424, https://doi.org/10.5194/essd-16-2407-2024, https://doi.org/10.5194/essd-16-2407-2024, 2024
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We produced a monthly Universal Thermal Climate Index dataset (GloUTCI-M) boasting global coverage and an extensive time series spanning March 2000 to October 2022 with a high spatial resolution of 1 km. This dataset is the product of a comprehensive approach leveraging multiple data sources and advanced machine learning models. GloUTCI-M can enhance our capacity to evaluate thermal stress experienced by the human, offering substantial prospects across a wide array of applications.
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
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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
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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.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
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To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
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
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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
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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.
Leah Bertrand, Jennifer E. Kay, John Haynes, and Gijs de Boer
Earth Syst. Sci. Data, 16, 1301–1316, https://doi.org/10.5194/essd-16-1301-2024, https://doi.org/10.5194/essd-16-1301-2024, 2024
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The vertical structure of clouds has a major impact on global energy flows, air circulation, and the hydrologic cycle. Two satellite instruments, CloudSat radar and CALIPSO lidar, have taken complementary measurements of cloud vertical structure for over a decade. Here, we present the 3S-GEOPROF-COMB product, a globally gridded satellite data product combining CloudSat and CALIPSO observations of cloud vertical structure.
Jiye Leng, Jing M. Chen, Wenyu Li, Xiangzhong Luo, Mingzhu Xu, Jane Liu, Rong Wang, Cheryl Rogers, Bolun Li, and Yulin Yan
Earth Syst. Sci. Data, 16, 1283–1300, https://doi.org/10.5194/essd-16-1283-2024, https://doi.org/10.5194/essd-16-1283-2024, 2024
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We produced a long-term global two-leaf gross primary productivity (GPP) and evapotranspiration (ET) dataset at the hourly time step by integrating a diagnostic process-based model with dynamic parameterizations. The new dataset provides us with a unique opportunity to study carbon and water fluxes at sub-daily time scales and advance our understanding of ecosystem functions in response to transient environmental changes.
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
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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
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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
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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
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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
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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
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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
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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.
Solomon H. Gebrechorkos, Jian Peng, Ellen Dyer, Diego G. Miralles, Sergio M. Vicente-Serrano, Chris Funk, Hylke E. Beck, Dagmawi T. Asfaw, Michael B. Singer, and Simon J. Dadson
Earth Syst. Sci. Data, 15, 5449–5466, https://doi.org/10.5194/essd-15-5449-2023, https://doi.org/10.5194/essd-15-5449-2023, 2023
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Drought is undeniably one of the most intricate and significant natural hazards with far-reaching consequences for the environment, economy, water resources, agriculture, and societies across the globe. In response to this challenge, we have devised high-resolution drought indices. These indices serve as invaluable indicators for assessing shifts in drought patterns and their associated impacts on a global, regional, and local level facilitating the development of tailored adaptation strategies.
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
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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
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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
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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
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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
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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.
Jinghua Xiong, Abhishek, Li Xu, Hrishikesh A. Chandanpurkar, James S. Famiglietti, Chong Zhang, Gionata Ghiggi, Shenglian Guo, Yun Pan, and Bramha Dutt Vishwakarma
Earth Syst. Sci. Data, 15, 4571–4597, https://doi.org/10.5194/essd-15-4571-2023, https://doi.org/10.5194/essd-15-4571-2023, 2023
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To overcome the shortcomings associated with limited spatiotemporal coverage, input data quality, and model simplifications in prevailing evaporation (ET) estimates, we developed an ensemble of 4669 unique terrestrial ET subsets using an independent mass balance approach. Long-term mean annual ET is within 500–600 mm yr−1 with a unimodal seasonal cycle and several piecewise trends during 2002–2021. The uncertainty-constrained results underpin the notion of increasing ET in a warming climate.
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
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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
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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
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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
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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
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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.
Cited articles
Abraham, C. and Monahan, A. H.: Spatial Dependence of Stably Stratified
Nocturnal Boundary-Layer Regimes in Complex Terrain, Bound.-Lay.
Meteorol., 177, 19–47, https://doi.org/10.1007/s10546-020-00532-x, 2020. a, b, c, d
Acevedo, O. C., Costa, F. D., Oliveira, P. E., Puhales, F. S., Degrazia, G. A.,
and Roberti, D. R.: The influence of submeso processes on stable boundary
layer similarity relationships, J. Atmos. Sci., 71,
207–225, https://doi.org/10.1175/JAS-D-13-0131.1, 2014. a, b
Brantley, S. L., Goldhaber, M. B., and Ragnarsdottir, K. V.: Crossing disciplines and scales to understand the
critical zone, Elements, 3, 307–314, https://doi.org/10.2113/gselements.3.5.307,
2007. a
Browning, K. A. and Wexler, R.: The Determination of Kinematic Properties of a
Wind Field Using Doppler Radar, J. Appl. Meteorol., 7, 105–113,
https://doi.org/10.1175/1520-0450(1968)007<0105:TDOKPO>2.0.CO;2, 1968. a
Cava, D., Mortarini, L., Giostra, U., Richiardone, R., and Anfossi, D.: A
wavelet analysis of low-wind-speed submeso motions in a nocturnal boundary
layer, Q. J. Roy. Meteorol. Soc., 143, 661–669,
https://doi.org/10.1002/qj.2954, 2017. a, b
Cava, D., Mortarini, L., Anfossi, D., and Giostra, U.: Interaction of Submeso Motions in the Antarctic Stable Boundary Layer, Bound.-Lay. Meteorol., 171, 151–173, https://doi.org/10.1007/s10546-019-00426-7, 2019. a, b, c
des Tombe, B., Schilperoort, B., and Bakker, M.: EStimation of Temperature and
Associated Uncertainty from Fiber-Optic Ramen-Spectrum Distributed
Temperature Sensing, Sensors, 20, 2235–2256, https://doi.org/10.3390/s20082235, 2020. a, b, c
Euser, T., Luxemburg, W. M. J., Everson, C. S., Mengistu, M. G., Clulow, A. D., and Bastiaanssen, W. G. M.: A new method to measure Bowen ratios using high-resolution vertical dry and wet bulb temperature profiles, Hydrol. Earth Syst. Sci., 18, 2021–2032, https://doi.org/10.5194/hess-18-2021-2014, 2014. a
Farr, T. G., Rosen, P. A., Caro, E., Crippen, R., Duren, R., Hensley, S.,
Kobrick, M., Paller, M., Rodriguez, E., Roth, L., Seal, D., Shaffer, S.,
Shimada, J., Umland, J., Werner, M., Oskin, M., Burbank, D., and Alsdorf, D.: The shuttle radar topography mission, Rev. Geophys., 45, 1–33,
https://doi.org/10.1029/2005RG000183, 2007. a
Freundorfer, A., Lapo, K., Schneider, J., and Thomas, C. K.: Distributed sensing of wind direction using fiber-optic cables, J. Atmos. Ocean. Technol., 38, 1871–1883, https://doi.org/10.1175/JTECH-D-21-0019.1, 2021. a, b, c
Higgins, C., Wing, M., Kelley, J., Sayde, C., Burnett, J., and Holmes, H.: A high resolution measurement of the morning ABL transition using distributed temperature sensing and an unmanned aircraft system, Environ. Fluid Mech., 18, 683–693, https://doi.org/10.1007/s10652-017-9569-1, 2018. a
Kang, Y., Belušić, D., and Smith-Miles, K.: Classes of structures in the stable atmospheric boundary layer, Q. J. Roy. Meteor. Soc., 141, 2057–2069, https://doi.org/10.1002/qj.2501, 2015. a
Keller, C. A., Huwald, H., Vollmer, M. K., Wenger, A., Hill, M., Parlange, M. B., and Reimann, S.: Fiber optic distributed temperature sensing for the determination of the nocturnal atmospheric boundary layer height, Atmos. Meas. Tech., 4, 143–149, https://doi.org/10.5194/amt-4-143-2011, 2011. a
Kral, S. T., Reuder, J., Vihma, T., Suomi, I., Haualand, K. F., Urbancic,
G. H., Greene, B. R., Steeneveld, G.-J., Lorenz, T., Maronga, B., Jonassen,
M. O., Ajosenpää, H., Båserud, L., Chilson, P. B., Holtslag,
A. A. M., Jenkins, A. D., Kouznetsov, R., Mayer, S., Pillar-Little, E. A.,
Rautenberg, A., Schwenkel, J., Seidl, A. W., and Wrenger, B.: The Innovative
Strategies for Observations in the Arctic Atmospheric Boundary Layer Project
(ISOBAR) – Unique fine-scale observations under stable and very stable
conditions, B. Am. Meteorol. Soc., 102, E218–E243,
https://doi.org/10.1175/bams-d-19-0212.1, 2020. a
Lang, F., Belušic, D., and Siems, S.: Observations of wind-direction
variability in the nocturnal boundary layer, Bound.-Lay. Meterol., 166, 51–68, https://doi.org/10.1007/s10546-017-0296-4, 2018. a
Lapo, K.: Isolated submeso motion in the very stable boundary layer observed by Distributed Temperature Sensing, TIB [video], https://doi.org/10.5446/53539, 2021. a
Lapo, K. and Freundorfer, A.: klapo/pyfocs v0.5, Zenodo [code], https://doi.org/10.5281/zenodo.4292491, 2020. a, b, c, d
Lenschow, D. H., Wulfmeyer, V., and Senff, C.: Measuring Second- through
Fourth-Order Moments in Noisy Data, J. Atmos. Ocean. Tech., 17, 1330–1347,
https://doi.org/10.1175/1520-0426(2000)017<1330:MSTFOM>2.0.CO;2, 2000. a, b, c
Mahrt, L.: Mesoscale wind direction shifts in the stable boundary-layer,
Tellus, 60A, 700–705, https://doi.org/10.1111/j.1600-0870.2008.00324.x, 2008. a
Mahrt, L.: Variability and Maintenance of Turbulence in the Very Stable
Boundary Layer, Bound.-Lay. Meteorol., 135, 1–18,
https://doi.org/10.1007/s10546-009-9463-6, 2010. a
Mahrt, L.: Lee Mixing and Nocturnal Structure over Gentle Topography, J. Atmos. Sci., 74, 1989–1999, https://doi.org/10.1175/JAS-D-16-0338.1, 2017. a
Mahrt, L. and Thomas, C. K.: Surface Stress with Non-stationary Weak Winds and Stable Stratification, Bound.-Lay. Meteorol., 159, 3–21,
https://doi.org/10.1007/s10546-015-0111-z, 2016. a, b, c
Mahrt, L., Thomas, C. K., and Prueger, J.: Space–time structure of mesoscale
motions in the stable, Q. J. Roy. Meteor. Soc., 135, 67–75, https://doi.org/10.1002/qj.348, 2009. a, b, c, d
Mahrt, L., Pfister, L., and Thomas, C. K.: Small-Scale Variability in the
Nocturnal Boundary Layer, Bound.-Lay. Meteorol., 174, 81–98,
https://doi.org/10.1007/s10546-019-00476-x, 2020. a, b
Mortarini, L., Cava, D., Giostra, U., Denardin Costa, F., Degrazia, G.,
Anfossi, D., and Acevedo, O.: Horizontal meandering as a distinctive feature of the stable boundary layer, J. Atmos. Sci., 76,
3029–3046, https://doi.org/10.1175/JAS-D-18-0280.1, 2019. a, b
Peltola, O., Lapo, K., Martinkauppi, I., O'Connor, E., Thomas, C. K., and Vesala, T.: Suitability of fibre-optic distributed temperature sensing for revealing mixing processes and higher-order moments at the forest–air interface, Atmos. Meas. Tech., 14, 2409–2427, https://doi.org/10.5194/amt-14-2409-2021, 2021. a, b, c, d
Petenko, I., Argentini, S., Casasanta, G., Genthon, C., and Kallistratova, M.:
Stable Surface-Based Turbulent Layer During the Polar Winter at Dome C,
Antarctica: Sodar and In Situ Observations, Bound.-Lay. Meteorol., 171,
101–128, https://doi.org/10.1007/s10546-018-0419-6, 2019. a
Petrides, A. C., Huff, J., Arik, A., Giesen, N. V. D., Kennedy, A. M., Thomas,
C. K., and Selker, J. S.: Shade estimation over streams using distributed
temperature sensing, Water Resour. Res., 47, 2–5,
https://doi.org/10.1029/2010WR009482, 2011. a
Pfister, L., Lapo, K., Sayde, C., Selker, J., Mahrt, L., and Thomas, C. K.:
Classifying the nocturnal atmospheric boundary layer into temperature and
flow regimes, Q. J. Roy. Meteor. Soc., 145,
1515–1534, https://doi.org/10.1002/qj.3508, 2019. a, b, c, d
Pillar-Little, E. A., Greene, B. R., Lappin, F. M., Bell, T. M., Segales, A. R., de Azevedo, G. B. H., Doyle, W., Kanneganti, S. T., Tripp, D. D., and Chilson, P. B.: Observations of the thermodynamic and kinematic state of the atmospheric boundary layer over the San Luis Valley, CO, using the CopterSonde 2 remotely piloted aircraft system in support of the LAPSE-RATE field campaign, Earth Syst. Sci. Data, 13, 269–280, https://doi.org/10.5194/essd-13-269-2021, 2021. a
Schilperoort, B., Coenders-Gerrits, M., Luxemburg, W., Jiménez Rodríguez, C., Cisneros Vaca, C., and Savenije, H.: Technical note: Using distributed temperature sensing for Bowen ratio evaporation measurements, Hydrol. Earth Syst. Sci., 22, 819–830, https://doi.org/10.5194/hess-22-819-2018, 2018. a
Selker, J. S., Thévenaz, L., Huwald, H., Mallet, A., Luxemburg, W.,
Giesen, N. V. D., Stejskal, M., Zeman, J., Westhoff, M., and Parlange, M. B.:
Distributed fiber-optic temperature sensing for hydrologic systems, Water Resour. Res., 42, 1–8, https://doi.org/10.1029/2006WR005326, 2006. a, b
Sigmund, A., Pfister, L., Sayde, C., and Thomas, C. K.: Quantitative analysis of the radiation error for aerial coiled-fiber-optic distributed temperature sensing deployments using reinforcing fabric as support structure, Atmos. Meas. Tech., 10, 2149–2162, https://doi.org/10.5194/amt-10-2149-2017, 2017. a
Stull, R. B.: An Introduction to Bound.-Lay. Meteorol., 1st Edn., Springer Netherlands, Dordrecht, The Netherlands, xiii, 666, ISBN9027727686, 1988. a
Sun, J., Mahrt, L., Banta, R. M., and Pichugina, Y. L.: Turbulence Regimes and
Turbulence Intermittency in the Stable Boundary Layer during CASES-99,
J. Atmos. Sci., 69, 338–351, https://doi.org/10.1175/JAS-D-11-082.1, 2012. a, b, c
Sun, J., Nappo, C. J., Mahrt, L., Belušic, D., Grisogono, B., Stauffer,
D. R., Pulido, M., Staquet, C., Jiang, Q., Pouquet, A., Yagüe, C.,
Galperin, B., Smith, R. B., Finnigan, J. J., Mayor, S. D., Svensson, G.,
Grachev, A. A., and Neff, W. D.: Review of wave-turbulence interactions in
the stable atmospheric boundary layer, Rev. Geophys., 53, 956–993,
https://doi.org/10.1002/2015RG000487, 2015. a, b, c, d, e, f
Sun, J., Takle, E. S., and Acevedo, O. C.: Understanding Physical Processes
Represented by the Monin-Obukhov Bulk Formula for Momentum Transfer,
Bound.-Lay. Meteorol., 177, 69–95, https://doi.org/10.1007/s10546-020-00546-5, 2020. a, b
Thomas, C. K.: Variability of Sub-Canopy Flow, Temperature, and Horizontal
Advection in Moderately Complex Terrain, Bound.-Lay. Meteorol., 139,
61–81, https://doi.org/10.1007/s10546-010-9578-9, 2011. a, b
Thomas, C. K. and Selker, J.: Optical fiber-based distributed sensing methods, chap. 20, in: Springer Handbook of Atmospheric Measurements, edited by: Foken, T., 609–631, Springer Handbooks, Springer Nature Switzerland AG, https://doi.org/10.1007/978-3-030-52171-4_20, 2021. a, b, c, d
Thomas, C. K., Mayer, J. C., Meixner, F. X., and Foken, T.: Analysis of
low-frequency turbulence above tall vegetation using a Doppler sodar,
Bound.-Lay. Meteorol., 119, 563–587, https://doi.org/10.1007/s10546-005-9038-0,
2006. a
Thomas, C. K., Law, B. E., Irvine, J., Martin, J. G., Pettijohn, J. C., and
Davis, K. J.: Seasonal hydrology explains interannual and seasonal variation
in carbon and water exchange in a semiarid mature ponderosa pine forest in
central Oregon, J. Geophys. Res., 114, G04006,
https://doi.org/10.1029/2009JG001010, 2009. a
Thomas, C. K., Kennedy, A. M., Selker, J. S., Moretti, A., Schroth, M. H.,
Smoot, A. R., Tufillaro, N. B., and Zeeman, M. J.: High-resolution
fibre-optic temperature sensing: A new tool to study the two-dimensional
structure of atmospheric surface layer flow, Bound.-Lay. Meteorol.,
142, 177–192, https://doi.org/10.1007/s10546-011-9672-7, 2012. a, b, c, d, e, f, g, h
Tyler, S. W., Selker, J. S., Hausner, M. B., Hatch, C. E., Torgersen, T.,
Thodal, C. E., and Schladow, S. G.: Environmental temperature sensing using
Raman spectra DTS fiber-optic methods, Water Resour. Res., 45, 1–11,
https://doi.org/10.1029/2008WR007052, 2009. a, b
van de Giesen, N., Steele-Dunne, S. C., Jansen, J., Hoes, O., Hausner, M. B.,
Tyler, S., and Selker, J.: Double-ended calibration of fiber-optic raman
spectra distributed temperature sensing data, Sensors, Switzerland, 12,
5471–5485, https://doi.org/10.3390/s120505471, 2012. a, b, c, d
Van de Wiel, B. J. H., Vignon, E., Baas, P., van Hooijdonk, I. G., Van der
Linden, Steven, J. A., van Hooft, J. A., Bosveld, F. C., de Roode, S. R.,
Moene, A. F., and Genthon, C.: Regime Transitions in Near-Surface
Temperature Inversions: A Conceptual Model, J. Atmos. Sci., 74, 1057–1073, https://doi.org/10.1175/JAS-D-16-0180.1, 2017. a, b
van Ramshorst, J. G. V., Coenders-Gerrits, M., Schilperoort, B., van de Wiel, B. J. H., Izett, J. G., Selker, J. S., Higgins, C. W., Savenije, H. H. G., and van de Giesen, N. C.: Revisiting wind speed measurements using actively heated fiber optics: a wind tunnel study, Atmos. Meas. Tech., 13, 5423–5439, https://doi.org/10.5194/amt-13-5423-2020, 2020.
a, b, c, d, e
Wilczak, J. M., Oncley, S. P., and Stage, S. A.: Sonic anemometer tilt
correction algorithms, Bound.-Lay. Meteorol., 99, 127–150,
https://doi.org/10.1023/A:1018966204465, 2001. a
Zeller, M.-L., Huss, J.-M., Pfister, L., Lapo, K. E., Littmann, D., Schneider, J., Schulz, A., and Thomas, C. K.: The NY-Ålesund TurbulencE Fiber Optic eXperiment (NYTEFOX): investigating the Arctic boundary layer, Svalbard, Earth Syst. Sci. Data, 13, 3439–3452, https://doi.org/10.5194/essd-13-3439-2021, 2021. a, b
Short summary
The layer of air near the surface is poorly understood during conditions with weak winds. Further, it is even difficult to observe. In this experiment we used distributed temperature sensing to observe air temperature and wind speed at thousands of points simultaneously every couple of seconds. This incredibly rich data set can be used to examine and understand what drives the mixing between the atmosphere and surface during these weak-wind periods.
The layer of air near the surface is poorly understood during conditions with weak winds....
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