Articles | Volume 15, issue 20
https://doi.org/10.5194/amt-15-6035-2022
© 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/amt-15-6035-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Oct 2022
Research article |
| 21 Oct 2022
| 21 Oct 2022
DeepPrecip: a deep neural network for precipitation retrievals
Dept. of Geography & Environmental Management, University of Waterloo, 200 University Ave W, Waterloo, Ontario, Canada
George Duffy
Jet Propulsion Laboratory, NASA, 4800 Oak Grove Dr, Pasadena, 91109, California, USA
Earth and Environmental Sciences, University of Syracuse, 900 South Crouse Ave, Syracuse, New York, USA
Lisa Milani
Goddard Space Flight Center, NASA, 8800 Greenbelt Rd, Greenbelt, Maryland, USA
Earth System Science Interdisciplinary Center, University of Maryland, 5825 University Research Ct suite 4001, College Park, Maryland, USA
Christopher G. Fletcher
Dept. of Geography & Environmental Management, University of Waterloo, 200 University Ave W, Waterloo, Ontario, Canada
Claire Pettersen
Climate and Space Sciences and Engineering, University of Michigan, Climate and Space Research Building, 2455 Hayward St, Ann Arbor, Michigan, USA
Kerstin Ebell
Institute for Geophysics and Meteorology, University of Cologne, Albertus-Magnus-Platz, Cologne, Germany
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Fraser King, Andre R. Erler, Steven K. Frey, and Christopher G. Fletcher
Hydrol. Earth Syst. Sci., 24, 4887–4902, https://doi.org/10.5194/hess-24-4887-2020, https://doi.org/10.5194/hess-24-4887-2020, 2020
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Snow is a critical contributor to our water and energy budget, with impacts on flooding and water resource management. Measuring the amount of snow on the ground each year is an expensive and time-consuming task. Snow models and gridded products help to fill these gaps, yet there exist considerable uncertainties associated with their estimates. We demonstrate that machine learning techniques are able to reduce biases in these products to provide more realistic snow estimates across Ontario.
Kerstin Ebell, Christian Buhren, Rosa Gierens, Giovanni Chellini, Melanie Lauer, Andreas Walbröl, Sandro Dahlke, Pavel Krobot, and Mario Mech
Atmos. Chem. Phys., 25, 7315–7342, https://doi.org/10.5194/acp-25-7315-2025, https://doi.org/10.5194/acp-25-7315-2025, 2025
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Ground-based observations of precipitation are rare in the Arctic. Since 2017, additional temporally highly resolved precipitation measurements have been carried out by a precipitation gauge and an optical precipitation sensor at Ny-Ålesund, Svalbard. These new data facilitate the distinction between liquid and solid precipitation. Using reanalysis data, we also find that water vapor transport contributes strongly to precipitation and especially to extreme precipitation events.
Denghui Ji, Mathias Palm, Matthias Buschmann, Kerstin Ebell, Marion Maturilli, Xiaoyu Sun, and Justus Notholt
Atmos. Chem. Phys., 25, 3889–3904, https://doi.org/10.5194/acp-25-3889-2025, https://doi.org/10.5194/acp-25-3889-2025, 2025
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Our study explores how certain aerosols, like sea salt, affect infrared heat radiation in the Arctic, potentially speeding up warming. We used advanced technology to measure aerosol composition and found that these particles grow with humidity, significantly increasing their heat-trapping effect in the infrared region, especially in winter. Our findings suggest these aerosols could be a key factor in Arctic warming, emphasizing the importance of understanding aerosols for climate prediction.
Andreas Walbröl, Hannes J. Griesche, Mario Mech, Susanne Crewell, and Kerstin Ebell
Atmos. Meas. Tech., 17, 6223–6245, https://doi.org/10.5194/amt-17-6223-2024, https://doi.org/10.5194/amt-17-6223-2024, 2024
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Andreas Walbröl, Janosch Michaelis, Sebastian Becker, Henning Dorff, Kerstin Ebell, Irina Gorodetskaya, Bernd Heinold, Benjamin Kirbus, Melanie Lauer, Nina Maherndl, Marion Maturilli, Johanna Mayer, Hanno Müller, Roel A. J. Neggers, Fiona M. Paulus, Johannes Röttenbacher, Janna E. Rückert, Imke Schirmacher, Nils Slättberg, André Ehrlich, Manfred Wendisch, and Susanne Crewell
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To support the interpretation of the data collected during the HALO-(AC)3 campaign, which took place in the North Atlantic sector of the Arctic from 7 March to 12 April 2022, we analyze how unusual the weather and sea ice conditions were with respect to the long-term climatology. From observations and ERA5 reanalysis, we found record-breaking warm air intrusions and a large variety of marine cold air outbreaks. Sea ice concentration was mostly within the climatological interquartile range.
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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.
Kameswara S. Vinjamuri, Marco Vountas, Luca Lelli, Martin Stengel, Matthew D. Shupe, Kerstin Ebell, and John P. Burrows
Atmos. Meas. Tech., 16, 2903–2918, https://doi.org/10.5194/amt-16-2903-2023, https://doi.org/10.5194/amt-16-2903-2023, 2023
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Clouds play an important role in Arctic amplification. Cloud data from ground-based sites are valuable but cannot represent the whole Arctic. Therefore the use of satellite products is a measure to cover the entire Arctic. However, the quality of such cloud measurements from space is not well known. The paper discusses the differences and commonalities between satellite and ground-based measurements. We conclude that the satellite dataset, with a few exceptions, can be used in the Arctic.
Charles Nelson Helms, Stephen Joseph Munchak, Ali Tokay, and Claire Pettersen
Atmos. Meas. Tech., 15, 6545–6561, https://doi.org/10.5194/amt-15-6545-2022, https://doi.org/10.5194/amt-15-6545-2022, 2022
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Giovanni Chellini and Kerstin Ebell
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-22, https://doi.org/10.5194/amt-2022-22, 2022
Preprint withdrawn
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Moisture inversions (MIs), i.e. atmospheric layers where specific humidity increases with height, are frequent in the Arctic. This study assesses the capability of two satellite instruments, IASI and AIRS, and one reanalysis, ERA5, to detect MIs at an Arctic site. The comparison with radiosonde data shows that humidity profiles from IASI and AIRS severely underestimate the occurrence of MIs. On the other hand, MI characteristics in ERA5 are comparable to those in the radiosonde data.
Hélène Bresson, Annette Rinke, Mario Mech, Daniel Reinert, Vera Schemann, Kerstin Ebell, Marion Maturilli, Carolina Viceto, Irina Gorodetskaya, and Susanne Crewell
Atmos. Chem. Phys., 22, 173–196, https://doi.org/10.5194/acp-22-173-2022, https://doi.org/10.5194/acp-22-173-2022, 2022
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Heather Guy, Ian M. Brooks, Ken S. Carslaw, Benjamin J. Murray, Von P. Walden, Matthew D. Shupe, Claire Pettersen, David D. Turner, Christopher J. Cox, William D. Neff, Ralf Bennartz, and Ryan R. Neely III
Atmos. Chem. Phys., 21, 15351–15374, https://doi.org/10.5194/acp-21-15351-2021, https://doi.org/10.5194/acp-21-15351-2021, 2021
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We present the first full year of surface aerosol number concentration measurements from the central Greenland Ice Sheet. Aerosol concentrations here have a distinct seasonal cycle from those at lower-altitude Arctic sites, which is driven by large-scale atmospheric circulation. Our results can be used to help understand the role aerosols might play in Greenland surface melt through the modification of cloud properties. This is crucial in a rapidly changing region where observations are sparse.
Susanne Crewell, Kerstin Ebell, Patrick Konjari, Mario Mech, Tatiana Nomokonova, Ana Radovan, David Strack, Arantxa M. Triana-Gómez, Stefan Noël, Raul Scarlat, Gunnar Spreen, Marion Maturilli, Annette Rinke, Irina Gorodetskaya, Carolina Viceto, Thomas August, and Marc Schröder
Atmos. Meas. Tech., 14, 4829–4856, https://doi.org/10.5194/amt-14-4829-2021, https://doi.org/10.5194/amt-14-4829-2021, 2021
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Water vapor (WV) is an important variable in the climate system. Satellite measurements are thus crucial to characterize the spatial and temporal variability in WV and how it changed over time. In particular with respect to the observed strong Arctic warming, the role of WV still needs to be better understood. However, as shown in this paper, a detailed understanding is still hampered by large uncertainties in the various satellite WV products, showing the need for improved methods to derive WV.
Linn Karlsson, Radovan Krejci, Makoto Koike, Kerstin Ebell, and Paul Zieger
Atmos. Chem. Phys., 21, 8933–8959, https://doi.org/10.5194/acp-21-8933-2021, https://doi.org/10.5194/acp-21-8933-2021, 2021
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Aerosol–cloud interactions in the Arctic are poorly understood largely due to a lack of observational data. We present the first direct, long-term measurements of cloud residuals, i.e. the particles that remain when cloud droplets and ice crystals are dried. These detailed observations of cloud residuals cover more than 2 years, which is unique for the Arctic and globally. This work studies the size distributions of cloud residuals, their seasonality, and dependence on meteorology.
Elin A. McIlhattan, Claire Pettersen, Norman B. Wood, and Tristan S. L'Ecuyer
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Snowfall builds the mass of the Greenland Ice Sheet (GrIS) and reduces melt by brightening the surface. We present satellite observations of GrIS snowfall events divided into two regimes: those coincident with ice clouds and those coincident with mixed-phase clouds. Snowfall from ice clouds plays the dominant role in building the GrIS, producing ~ 80 % of total accumulation. The two regimes have similar snowfall frequency in summer, brightening the surface when solar insolation is at its peak.
Fraser King, Andre R. Erler, Steven K. Frey, and Christopher G. Fletcher
Hydrol. Earth Syst. Sci., 24, 4887–4902, https://doi.org/10.5194/hess-24-4887-2020, https://doi.org/10.5194/hess-24-4887-2020, 2020
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Snow is a critical contributor to our water and energy budget, with impacts on flooding and water resource management. Measuring the amount of snow on the ground each year is an expensive and time-consuming task. Snow models and gridded products help to fill these gaps, yet there exist considerable uncertainties associated with their estimates. We demonstrate that machine learning techniques are able to reduce biases in these products to provide more realistic snow estimates across Ontario.
Tatiana Nomokonova, Kerstin Ebell, Ulrich Löhnert, Marion Maturilli, and Christoph Ritter
Atmos. Chem. Phys., 20, 5157–5173, https://doi.org/10.5194/acp-20-5157-2020, https://doi.org/10.5194/acp-20-5157-2020, 2020
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This paper presents an influence of water vapor anomalies on cloud properties and their radiative effect at Ny-Ålesund. The study is based on a 2.5-year active and passive cloud observation and a radiative transfer model. The results show that moist and dry conditions are related to strong changes in cloud occurrence, phase partitioning, water path, and, consequently, modulate the surface radiative budget.
Rosa Gierens, Stefan Kneifel, Matthew D. Shupe, Kerstin Ebell, Marion Maturilli, and Ulrich Löhnert
Atmos. Chem. Phys., 20, 3459–3481, https://doi.org/10.5194/acp-20-3459-2020, https://doi.org/10.5194/acp-20-3459-2020, 2020
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Multiyear statistics of persistent low-level mixed-phase clouds observed at an Arctic fjord environment in Svalbard are presented. The effects the local boundary layer (i.e. the fjords' wind climate and surface coupling), regional wind direction, and seasonality have on the cloud occurrence and properties are evaluated using a synergy of ground-based remote sensing methods and auxiliary data. The phenomena considered were found to modify the amount of liquid and ice in the studied clouds.
Vera Schemann and Kerstin Ebell
Atmos. Chem. Phys., 20, 475–485, https://doi.org/10.5194/acp-20-475-2020, https://doi.org/10.5194/acp-20-475-2020, 2020
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In this study, we apply a high-resolution model at the observation supersite Ny-Ålesund (Svalbard) to evaluate mixed-phase clouds. These clouds are a potential driver for the stronger warming in the Arctic compared to the global mean, but their representation in climate models is typically rather poor due to complex microphysical processes. The presented combination of high-resolution modeling and long-term state-of-the-art observations can lead to improved process understanding.
Ralf Bennartz, Frank Fell, Claire Pettersen, Matthew D. Shupe, and Dirk Schuettemeyer
Atmos. Chem. Phys., 19, 8101–8121, https://doi.org/10.5194/acp-19-8101-2019, https://doi.org/10.5194/acp-19-8101-2019, 2019
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The Greenland Ice Sheet (GrIS) is rapidly melting. Snowfall is the only source of ice mass over the GrIS. We use satellite observations to assess how much snow on average falls over the GrIS and what the annual cycle and spatial distribution of snowfall is. We find the annual mean snowfall over the GrIS inferred from CloudSat to be 34 ± 7.5 cm yr−1 liquid equivalent.
Tatiana Nomokonova, Kerstin Ebell, Ulrich Löhnert, Marion Maturilli, Christoph Ritter, and Ewan O'Connor
Atmos. Chem. Phys., 19, 4105–4126, https://doi.org/10.5194/acp-19-4105-2019, https://doi.org/10.5194/acp-19-4105-2019, 2019
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In this study, properties of clouds at the French–German Arctic research station in Ny-Ålesund are related to in-cloud thermodynamic conditions. The dataset used was collected within the Arctic Amplification project with a set of active and passive remote instruments. The results are compared with a model output. Significant divergence in observations and modelling of single-layer ice and mixed-phase clouds was found.
Marion Maturilli and Kerstin Ebell
Earth Syst. Sci. Data, 10, 1451–1456, https://doi.org/10.5194/essd-10-1451-2018, https://doi.org/10.5194/essd-10-1451-2018, 2018
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We present a 25-year data record of cloud base height measured by ceilometer at the Ny-Ålesund, Svalbard, Arctic site. The long-term time series allows derivation of an annual cycle of the cloud occurrence frequency, revealing more frequent cloud cover in summer and the lowest cloud cover amount in April. The cloud base data further provide essential information for the interpretation of the surface radiation balance and contribute to understanding meteorological processes at high latitudes.
Claire Pettersen, Ralf Bennartz, Aronne J. Merrelli, Matthew D. Shupe, David D. Turner, and Von P. Walden
Atmos. Chem. Phys., 18, 4715–4735, https://doi.org/10.5194/acp-18-4715-2018, https://doi.org/10.5194/acp-18-4715-2018, 2018
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A novel method for classifying Arctic precipitation using ground based remote sensors is presented. The classification reveals two distinct, primary regimes of precipitation over the central Greenland Ice Sheet: snowfall coupled to deep, fully glaciated ice clouds or to shallow, mixed-phase clouds. The ice clouds are associated with low-pressure storm systems from the southeast, while the mixed-phase clouds slowly propagate from the southwest along a quiescent flow.
Claire Pettersen, Ralf Bennartz, Mark S. Kulie, Aronne J. Merrelli, Matthew D. Shupe, and David D. Turner
Atmos. Chem. Phys., 16, 4743–4756, https://doi.org/10.5194/acp-16-4743-2016, https://doi.org/10.5194/acp-16-4743-2016, 2016
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We examined four summers of data from a ground-based atmospheric science instrument suite at Summit Station, Greenland, to isolate the signature of the ice precipitation. By using a combination of instruments with different specialities, we identified a passive microwave signature of the ice precipitation. This ice signature compares well to models using synthetic data characteristic of the site.
D. Casella, G. Panegrossi, P. Sanò, L. Milani, M. Petracca, and S. Dietrich
Atmos. Meas. Tech., 8, 1217–1232, https://doi.org/10.5194/amt-8-1217-2015, https://doi.org/10.5194/amt-8-1217-2015, 2015
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The CCA algorithm is applicable to any modern passive microwave radiometer on board polar orbiting satellites; it has been developed using a data set of co-located SSMIS and TRMM-PR measurements and AMSU-MHS and TRMM-PR measurements. The algorithm shows a small rate of false alarms and superior detection capability and can efficiently detect (POD between 0.55 and 0.71) minimum rain rate varying from 0.14 mm/h (AMSU over ocean) to 0.41 (SSMIS over coast).
J. Slobodda, A. Hünerbein, R. Lindstrot, R. Preusker, K. Ebell, and J. Fischer
Atmos. Meas. Tech., 8, 567–578, https://doi.org/10.5194/amt-8-567-2015, https://doi.org/10.5194/amt-8-567-2015, 2015
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In this paper the representativeness of ground-based cloud observatories and their comparability to satellite data and weather prediction models is examined. It is performed by analysing correlation of time series of SEVIRI pixels. The representativeness strongly depends on the used channels and ranges between 1km and over 20km.
L. Milani, F. Porcù, D. Casella, S. Dietrich, G. Panegrossi, M. Petracca, and P. Sanò
The Cryosphere Discuss., https://doi.org/10.5194/tcd-9-141-2015, https://doi.org/10.5194/tcd-9-141-2015, 2015
Revised manuscript not accepted
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The aim of this work is to show that the CloudSat Cloud Profiling Radar (CPR) can be a valuable source of snowfall rate data in Antarctica that can be used at different temporal scales. Two years of CloudSat data over Antarctica are analyzed and two different approaches for precipitation estimates are considered. The results show that CPR can provide valuable support to the sparse network of ground-based instruments both for numerical model validation and climatological studies.
A. Mugnai, D. Casella, E. Cattani, S. Dietrich, S. Laviola, V. Levizzani, G. Panegrossi, M. Petracca, P. Sanò, F. Di Paola, D. Biron, L. De Leonibus, D. Melfi, P. Rosci, A. Vocino, F. Zauli, P. Pagliara, S. Puca, A. Rinollo, L. Milani, F. Porcù, and F. Gattari
Nat. Hazards Earth Syst. Sci., 13, 1959–1981, https://doi.org/10.5194/nhess-13-1959-2013, https://doi.org/10.5194/nhess-13-1959-2013, 2013
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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Juliëtte C. S. Anema, K. Folkert Boersma, Lieuwe G. Tilstra, Olaf N. E. Tuinder, and Willem W. Verstraeten
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Atmos. Meas. Tech., 18, 1823–1839, https://doi.org/10.5194/amt-18-1823-2025, https://doi.org/10.5194/amt-18-1823-2025, 2025
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Atmos. Meas. Tech., 18, 1841–1857, https://doi.org/10.5194/amt-18-1841-2025, https://doi.org/10.5194/amt-18-1841-2025, 2025
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Matthieu Vernay, Matthieu Lafaysse, and Clotilde Augros
Atmos. Meas. Tech., 18, 1731–1755, https://doi.org/10.5194/amt-18-1731-2025, https://doi.org/10.5194/amt-18-1731-2025, 2025
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Atmos. Meas. Tech., 18, 1591–1607, https://doi.org/10.5194/amt-18-1591-2025, https://doi.org/10.5194/amt-18-1591-2025, 2025
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Information on the energy transported by atmospheric gravity waves (GWs) is crucial for improving atmosphere models. Most space-based studies report the potential energy. We use Aeolus wind data to estimate the kinetic energy (density). However, the data quality is a challenge for such analyses, as the accuracy of the data is in the range of typical GW amplitudes. We find a temporal coincidence between enhanced or breaking planetary waves and enhanced gravity wave kinetic energy density.
Natalie E. Theeuwes, Janet F. Barlow, Antti Mannisenaho, Denise Hertwig, Ewan O'Connor, and Alan Robins
Atmos. Meas. Tech., 18, 1355–1371, https://doi.org/10.5194/amt-18-1355-2025, https://doi.org/10.5194/amt-18-1355-2025, 2025
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A Doppler lidar was placed in a highly built-up area in London to measure wakes from tall buildings during a period of 1 year. We were able to detect wakes and assess their dependence on wind speed, wind direction, and atmospheric stability.
Chengli Ji, Qiankai Jin, Feilong Li, Yuyang Liu, Zhicheng Wang, Jiajia Mao, Xiaoyu Ren, Yan Xiang, Wanlin Jian, Peitao Zhao, and Zhenyi Chen
EGUsphere, https://doi.org/10.5194/egusphere-2025-1171, https://doi.org/10.5194/egusphere-2025-1171, 2025
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This study presents the humidity measurements with a synergetic algorithm combining Raman lidar, MVR, and satellite. The results from 47 sites in China show the best correlation over 0.9 concerning the radiosonde measurements. It validates the RH accuracy with various data integrations. Three representative sites present the different seasonal characteristics indicating the geographic and height influences on the RH vertical distribution.
Maurice Roots, John T. Sullivan, and Belay Demoz
Atmos. Meas. Tech., 18, 1269–1282, https://doi.org/10.5194/amt-18-1269-2025, https://doi.org/10.5194/amt-18-1269-2025, 2025
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This paper presents a supervised-machine-learning approach for the automatic isolation of nocturnal low-level jets (NLLJs) using observations from a radar wind profiler. This analysis isolated 90 southwesterly NLLJs observed from May to September 2017–2021, highlighting key features in the evolution and morphology of the mid-Atlantic NLLJ.
Linda Megner, Jörg Gumbel, Ole Martin Christensen, Björn Linder, Donal Patrick Murtagh, Nickolay Ivchenko, Lukas Krasauskas, Jonas Hedin, Joachim Dillner, Gabriel Giono, Georgi Olentsenko, Louis Kern, and Jacek Stegman
EGUsphere, https://doi.org/10.5194/egusphere-2025-265, https://doi.org/10.5194/egusphere-2025-265, 2025
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The MATS satellite mission studies atmospheric gravity waves, crucial for momentum transport between atmospheric layers. Launched in November 2022, MATS uses a limb-viewing telescope to capture high-resolution images of Noctilucent clouds and airglow, visualizing wave patterns in the high atmosphere. This paper accompanies the public release of the level 1b data set, i.e. calibrated limb images. Later products will provide global maps of gravity wave properties, airglow and Noctilucent clouds.
Padmanabhan Thiruvengadam, Guillaume Lesage, Ambinintsoa Volatiana Ramanamahefa, and Joël Van Baelen
Atmos. Meas. Tech., 18, 1185–1191, https://doi.org/10.5194/amt-18-1185-2025, https://doi.org/10.5194/amt-18-1185-2025, 2025
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This study explores how the joints in a weather radar's protective cover affect its measurements. We developed a new method to correct these errors, improving the accuracy of the radar's data. Our method was tested during an intense cyclone on Réunion Island, demonstrating significant improvements in data accuracy. This research is crucial for enhancing weather predictions and understanding, particularly in challenging terrains.
Dong L. Wu, Valery A. Yudin, Kyu-Myong Kim, Mohar Chattopadhyay, Lawrence Coy, Ruth S. Lieberman, C. C. Jude H. Salinas, Jae N. Lee, Jie Gong, and Guiping Liu
Atmos. Meas. Tech., 18, 843–863, https://doi.org/10.5194/amt-18-843-2025, https://doi.org/10.5194/amt-18-843-2025, 2025
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Global Navigation Satellite System radio occultation data help monitor climate and weather prediction but are affected by residual ionospheric errors (RIEs). A new excess-phase-gradient method detects and corrects RIEs, showing both positive and negative values, varying by latitude, time, and solar activity. Tests show that RIE impacts polar stratosphere temperatures in models, with differences up to 3–4 K. This highlights the need for RIE correction to improve the accuracy of data assimilation.
Damao Zhang, Jennifer Comstock, Chitra Sivaraman, Kefei Mo, Raghavendra Krishnamurthy, Jingjing Tian, Tianning Su, Zhanqing Li, and Natalia Roldán-Henao
EGUsphere, https://doi.org/10.5194/egusphere-2024-3959, https://doi.org/10.5194/egusphere-2024-3959, 2025
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Planetary boundary layer height (PBLHT) is an important parameter in atmospheric process studies and numerical model simulations. We use machine learning methods to produce a best-estimate planetary boundary layer height (PBLHT-BE-ML) by integrating four PBLHT estimates derived from remote sensing measurements. We demonstrated that PBLHT-BE-ML greatly improved the comparisons against sounding-derived PBLHT.
Miguel Aldana, Seppo Pulkkinen, Annakaisa von Lerber, Matthew R. Kumjian, and Dmitri Moisseev
Atmos. Meas. Tech., 18, 793–816, https://doi.org/10.5194/amt-18-793-2025, https://doi.org/10.5194/amt-18-793-2025, 2025
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Accurate KDP estimates are crucial in radar-based applications. We quantify the uncertainties of several publicly available KDP estimation methods for multiple rainfall intensities. We use C-band weather radar observations and employed a self-consistency KDP, estimated from reflectivity and differential reflectivity, as a framework for the examination. Our study provides guidance for the performance, uncertainties, and optimisation of the methods, focusing mainly on accuracy and robustness.
Rohith Thundathil, Florian Zus, Galina Dick, and Jens Wickert
EGUsphere, https://doi.org/10.5194/egusphere-2025-19, https://doi.org/10.5194/egusphere-2025-19, 2025
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Tropospheric gradients provide information on the moisture distribution, whereas ZTDs provide the absolute amount of moisture through integrated water vapor. When TGs are assimilated with ZTDs, it helps the model actuate the moisture fields, correcting its dynamics. In our research, we show evidence that in particular regions with very few GNSS stations, the assimilation of gradients on top of ZTDs can provide the same impact as the assimilation of only ZTDs with dense coverage of GNSS stations.
Lei Liu, Natalia Bliankinshtein, Yi Huang, John R. Gyakum, Philip M. Gabriel, Shiqi Xu, and Mengistu Wolde
Atmos. Meas. Tech., 18, 471–485, https://doi.org/10.5194/amt-18-471-2025, https://doi.org/10.5194/amt-18-471-2025, 2025
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This study evaluates and compares a new microwave hyperspectrometer with an infrared hyperspectrometer for clear-sky temperature and water vapor retrievals. The analysis reveals that the information content of the infrared hyperspectrometer exceeds that of the microwave hyperspectrometer and provides higher vertical resolution in ground-based zenith measurements. Leveraging the ground–airborne synergy between the two instruments yielded optimal sounding results.
David D. Turner, Maria P. Cadeddu, Julia Simonson, and Timothy J. Wagner
EGUsphere, https://doi.org/10.5194/egusphere-2024-4124, https://doi.org/10.5194/egusphere-2024-4124, 2025
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When deriving a geophysical variable from remote sensors, the uncertainty and information content are critical. The latter quantify specifies what fraction of a real perturbation would be observed in the derived variable. This paper outlines, for the first time, a methodology for propagating the information content from multiple remote sensors into a derived product, using horizontal advection as an example.
Endrit Shehaj, Stephen Leroy, Kerri Cahoy, Alain Geiger, Laura Crocetti, Gregor Moeller, Benedikt Soja, and Markus Rothacher
Atmos. Meas. Tech., 18, 57–72, https://doi.org/10.5194/amt-18-57-2025, https://doi.org/10.5194/amt-18-57-2025, 2025
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This work investigates whether machine learning (ML) can offer an alternative to existing methods to map radio occultation (RO) products, allowing the extraction of information not visible in direct observations. ML can further improve the results of Bayesian interpolation, a state-of-the-art method to map RO observations. The results display improvements in horizontal and temporal domains, at heights ranging from the planetary boundary layer up to the lower stratosphere, and for all seasons.
Luuk D. van der Valk, Oscar K. Hartogensis, Miriam Coenders-Gerrits, Rolf W. Hut, Bas Walraven, and Remko Uijlenhoet
EGUsphere, https://doi.org/10.5194/egusphere-2024-2974, https://doi.org/10.5194/egusphere-2024-2974, 2025
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Commercial microwave links (CMLs), part of mobile phone networks, transmit comparable signals as instruments specially designed to estimate evaporation. Therefore, we investigate if CMLs could be used to estimate evaporation, even though they have not been designed for this purpose. Our results illustrate the potential of using CMLs to estimate evaporation, especially given their global coverage, but also outline some major drawbacks, often a consequence of unfavourable design choices for CMLs.
Andreas Foth, Moritz Lochmann, Pablo Saavedra Garfias, and Heike Kalesse-Los
Atmos. Meas. Tech., 17, 7169–7181, https://doi.org/10.5194/amt-17-7169-2024, https://doi.org/10.5194/amt-17-7169-2024, 2024
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Microwave radiometers are usually not able to provide atmospheric quantities such as temperature profiles during rain. We present a method based on a selection of specific frequencies and elevation angles from microwave radiometer observations. A comparison with a numerical weather prediction model shows the presented method allows low-level temperature profiles during rain to be resolved, with rain rates of up to 2.5 mm h−1,, which was not possible before with state-of-the-art retrievals.
Lev D. Labzovskii, Gerd-Jan van Zadelhoff, David P. Donovan, Jos de Kloe, L. Gijsbert Tilstra, Ad Stoffelen, Damien Josset, and Piet Stammes
Atmos. Meas. Tech., 17, 7183–7208, https://doi.org/10.5194/amt-17-7183-2024, https://doi.org/10.5194/amt-17-7183-2024, 2024
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The Atmospheric Laser Doppler Instrument (ALADIN) on the Aeolus satellite was the first of its kind to measure high-resolution vertical profiles of aerosols and cloud properties from space. We present an algorithm that produces Aeolus lidar surface returns (LSRs), containing useful information for measuring UV reflectivity. Aeolus LSRs matched well with existing UV reflectivity data from other satellites, like GOME-2 and TROPOMI, and demonstrated excellent sensitivity to modeled snow cover.
Thomas Hocking, Thorsten Mauritsen, and Linda Megner
Atmos. Meas. Tech., 17, 7077–7095, https://doi.org/10.5194/amt-17-7077-2024, https://doi.org/10.5194/amt-17-7077-2024, 2024
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The imbalance between the energy the Earth absorbs from the Sun and the energy the Earth emits back into space gives rise to climate change, but measuring the small imbalance is challenging. We simulate satellites in various orbits to investigate how well they sample the imbalance and find that the best option is to combine at least two satellites that see complementary parts of the Earth and cover the daily and annual cycles. This information is useful when planning future satellite missions.
Almudena Velázquez Blázquez, Carlos Domenech, Edward Baudrez, Nicolas Clerbaux, Carla Salas Molar, and Nils Madenach
Atmos. Meas. Tech., 17, 7007–7026, https://doi.org/10.5194/amt-17-7007-2024, https://doi.org/10.5194/amt-17-7007-2024, 2024
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This paper focuses on the BMA-FLX processor, in which thermal and solar top-of-atmosphere radiative fluxes are obtained from longwave and shortwave radiances measured along track by the EarthCARE Broadband Radiometer (BBR). The BBR measurements, at three fixed viewing angles (fore, nadir, aft), are co-registered either at the surface or at a reference level. A combined flux from the three BRR views is obtained. The algorithm has been successfully validated against test scenes.
Wolf Knöller, Gholamhossein Bagheri, Philipp von Olshausen, and Michael Wilczek
Atmos. Meas. Tech., 17, 6913–6931, https://doi.org/10.5194/amt-17-6913-2024, https://doi.org/10.5194/amt-17-6913-2024, 2024
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Three-dimensional (3D) wind velocity measurements are of major importance for the characterization of atmospheric turbulence. This paper presents a detailed study of the measurement uncertainty of a three-beam wind lidar designed for mounting on airborne platforms. Considering the geometrical constraints, the analysis provides quantitative estimates for the measurement uncertainty of all components of the 3D wind vector. As a result, we propose optimized post-processing for error reduction.
Bianca Adler, David D. Turner, Laura Bianco, Irina V. Djalalova, Timothy Myers, and James M. Wilczak
Atmos. Meas. Tech., 17, 6603–6624, https://doi.org/10.5194/amt-17-6603-2024, https://doi.org/10.5194/amt-17-6603-2024, 2024
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Continuous profile observations of temperature and humidity in the lowest part of the atmosphere are essential for the evaluation of numerical weather prediction models and data assimilation for better weather forecasts. Such profiles can be retrieved from passive ground-based remote sensing instruments like infrared spectrometers and microwave radiometers. In this study, we describe three recent modifications to the retrieval framework TROPoe for improved temperature and humidity profiles.
Yunfan Yang, Wei Han, Haofei Sun, Jun Li, Jiapeng Yan, and Zhiqiu Gao
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-175, https://doi.org/10.5194/amt-2024-175, 2024
Revised manuscript accepted for AMT
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Our research improves satellite-based precipitation monitoring by using deep learning to reconstruct radar observations from passive microwave radiances. Active radar is costly, so we focus on a more accessible approach. Using data from the FengYun-3G satellite, we successfully tracked severe weather like Typhoon Khanun and heavy rainfall in Beijing in 2023. This method enhances global precipitation data and helps better understand extreme weather.
Bernat Puigdomènech Treserras and Pavlos Kollias
Atmos. Meas. Tech., 17, 6301–6314, https://doi.org/10.5194/amt-17-6301-2024, https://doi.org/10.5194/amt-17-6301-2024, 2024
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The paper presents a comprehensive approach to improve the geolocation accuracy of spaceborne radar and lidar systems, crucial for the successful interpretation of data from the upcoming EarthCARE mission. The paper details the technical background of the presented methods and various examples of geolocation analyses, including a short period of CloudSat observations when the star tracker was not operating properly and lifetime statistics from the CloudSat and CALIPSO missions.
Andreas Walbröl, Hannes J. Griesche, Mario Mech, Susanne Crewell, and Kerstin Ebell
Atmos. Meas. Tech., 17, 6223–6245, https://doi.org/10.5194/amt-17-6223-2024, https://doi.org/10.5194/amt-17-6223-2024, 2024
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We developed retrievals of integrated water vapour (IWV), temperature profiles, and humidity profiles from ground-based passive microwave remote sensing measurements gathered during the MOSAiC expedition. We demonstrate and quantify the benefit of combining low- and high-frequency microwave radiometers to improve humidity profiling and IWV estimates by comparing the retrieved quantities to single-instrument retrievals and reference datasets (radiosondes).
Tessa E. Rosenberger, Thijs Heus, Girish N. Raghunathan, David D. Turner, Timothy J. Wagner, and Julia M. Simonson
EGUsphere, https://doi.org/10.5194/egusphere-2024-2894, https://doi.org/10.5194/egusphere-2024-2894, 2024
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Entrainment is key in understanding temperature and moisture changes within the boundary layer, but it is difficult to observe using ground-based observations. This work used simulations to verify an assumption that simplifies entrainment estimations from ground-based observational data, recognizing that entrainment is the combination of the transfer of heat and moisture from above the boundary layer into it and the change in concentration of heat and moisture as boundary layer depth changes.
Giulia Roccetti, Luca Bugliaro, Felix Gödde, Claudia Emde, Ulrich Hamann, Mihail Manev, Michael Fritz Sterzik, and Cedric Wehrum
Atmos. Meas. Tech., 17, 6025–6046, https://doi.org/10.5194/amt-17-6025-2024, https://doi.org/10.5194/amt-17-6025-2024, 2024
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The amount of sunlight reflected by the Earth’s surface (albedo) is vital for the Earth's radiative system. While satellite instruments offer detailed spatial and temporal albedo maps, they only cover seven wavelength bands. We generate albedo maps that fully span the visible and near-infrared range using a machine learning algorithm. These maps reveal how the reflectivity of different land surfaces varies throughout the year. Our dataset enhances the understanding of the Earth's energy balance.
Ollie Lewis, Chris Brunt, Malcolm Kitchen, Neill E. Bowler, and Edmund K. Stone
EGUsphere, https://doi.org/10.5194/egusphere-2024-2273, https://doi.org/10.5194/egusphere-2024-2273, 2024
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Humidity observations are crucial for an accurate weather forecast. We propose a new way to measure humidity by measuring how radio signals from commercial aircraft are refracted by the atmosphere. Humidity affects the refractive index of air, allowing its presence to be detected. With thousands of flights in the airspace over the United Kingdom every day, there is the potential for a large increase in the number of humidity measurements for use in weather forecasting models.
Dianrun Zhao, Shanshan Du, Chu Zou, Longfei Tian, Meng Fan, Yulu Du, and Liangyun Liu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3118, https://doi.org/10.5194/egusphere-2024-3118, 2024
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The TanSat-2 satellite is designed for global carbon monitoring. It provides high-resolution, dual-band observations of solar-induced chlorophyll fluorescence, a key indicator of plant photosynthesis. Through simulations, we optimized the satellite's data processing and found it can retrieve this fluorescence with great accuracy. These findings suggest that TanSat-2 will enhance global monitoring of carbon cycles and vegetation health, offering valuable insights for climate change research.
Sebastian Rhode, Peter Preusse, Jörn Ungermann, Inna Polichtchouk, Kaoru Sato, Shingo Watanabe, Manfred Ern, Karlheinz Nogai, Björn-Martin Sinnhuber, and Martin Riese
Atmos. Meas. Tech., 17, 5785–5819, https://doi.org/10.5194/amt-17-5785-2024, https://doi.org/10.5194/amt-17-5785-2024, 2024
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We investigate the capabilities of a proposed satellite mission, CAIRT, for observing gravity waves throughout the middle atmosphere and present the necessary methodology for in-depth wave analysis. Our findings suggest that such a satellite mission is highly capable of resolving individual wave parameters and could give new insights into the role of gravity waves in general atmospheric circulation and atmospheric processes.
Xiaoye Wang, Jing Xu, Songhua Wu, Qichao Wang, Guangyao Dai, Peizhi Zhu, Zhizhong Su, Sai Chen, Xiaomeng Shi, and Mengqi Fan
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-156, https://doi.org/10.5194/amt-2024-156, 2024
Revised manuscript accepted for AMT
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In this paper, we proposed a data fusion method to obtain the no-blind zone wind speed profiles covering the whole Atmospheric Boundary Layer based on the joint measurements of coherent Doppler lidar (CDL), radar wind profiler (RWP) and automatic weather station (AWS). Since above instruments are widely deployed in China, we believe this method has broad application prospects on the improvement of the boundary layer parameterization scheme in numerical forecast models.
Suyoung Sim, Sungwon Choi, Daeseong Jung, Jongho Woo, Nayeon Kim, Sungwoo Park, Honghee Kim, Ukkyo Jeong, Hyunkee Hong, and Kyung-Soo Han
Atmos. Meas. Tech., 17, 5601–5618, https://doi.org/10.5194/amt-17-5601-2024, https://doi.org/10.5194/amt-17-5601-2024, 2024
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This study evaluates the use of background surface reflectance (BSR) derived from a semi-empirical bidirectional reflectance distribution function (BRDF) model based on GEMS satellite images. Analysis shows that BSR provides improved accuracy and stability compared to Lambertian-equivalent reflectivity (LER). These results indicate that BSR can significantly enhance climate analysis and air quality monitoring, making it a promising tool for accurate environmental satellite applications.
Daniel Durbin, Yadong Wang, and Pao-Liang Chang
Atmos. Meas. Tech., 17, 5397–5411, https://doi.org/10.5194/amt-17-5397-2024, https://doi.org/10.5194/amt-17-5397-2024, 2024
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A method for determining drop size distributions (DSDs) for rain using radar measurements from two frequencies at two polarizations is presented. Following some preprocessing and quality control, radar measurements are incorporated into a model that uses swarm intelligence to seek the most suitable DSD to produce the input measurements.
Witali Krochin, Axel Murk, and Gunter Stober
Atmos. Meas. Tech., 17, 5015–5028, https://doi.org/10.5194/amt-17-5015-2024, https://doi.org/10.5194/amt-17-5015-2024, 2024
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Atmospheric tides are global-scale oscillations with periods of a fraction of a day. Their observation in the middle atmosphere is challenging and rare, as it requires continuous measurements with a high temporal resolution. In this paper, temperature time series of a ground-based microwave radiometer were analyzed with a spectral filter to derive thermal tide amplitudes and phases in an altitude range of 25–50 km at the geographical locations of Payerne and Bern (Switzerland).
Matteo Ottaviani, Gabriel Harris Myers, and Nan Chen
Atmos. Meas. Tech., 17, 4737–4756, https://doi.org/10.5194/amt-17-4737-2024, https://doi.org/10.5194/amt-17-4737-2024, 2024
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We analyze simulated polarization observations over snow to investigate the capabilities of remote sensing to determine surface and atmospheric properties in snow-covered regions. Polarization measurements are demonstrated to aid in the determination of snow grain shape, ice crystal roughness, and the vertical distribution of impurities in the snow–atmosphere system, data that are critical for estimating snow albedo for use in climate models.
Yudong Gao, Lidou Huyan, Zheng Wu, and Bojun Liu
Atmos. Meas. Tech., 17, 4675–4686, https://doi.org/10.5194/amt-17-4675-2024, https://doi.org/10.5194/amt-17-4675-2024, 2024
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A symmetric error model built by symmetric rain rates handles the non-Gaussian error structure of the reflectivity error. The accuracy and linearization of rain rates can further improve the Gaussianity.
José Alex Zenteno-Hernández, Adolfo Comerón, Federico Dios, Alejandro Rodríguez-Gómez, Constantino Muñoz-Porcar, Michaël Sicard, Noemi Franco, Andreas Behrendt, and Paolo Di Girolamo
Atmos. Meas. Tech., 17, 4687–4694, https://doi.org/10.5194/amt-17-4687-2024, https://doi.org/10.5194/amt-17-4687-2024, 2024
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We study how the spectral characteristics of a solid-state laser in an atmospheric temperature profiling lidar using the Raman technique impact the temperature retrieval accuracy. We find that the spectral widening, with respect to a seeded laser, has virtually no impact, while crystal-rod temperature variations in the laser must be kept within a range of 1 K for the uncertainty in the atmospheric temperature below 1 K. The study is carried out through spectroscopy simulations.
Robert Reichert, Natalie Kaifler, and Bernd Kaifler
Atmos. Meas. Tech., 17, 4659–4673, https://doi.org/10.5194/amt-17-4659-2024, https://doi.org/10.5194/amt-17-4659-2024, 2024
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Imagine you want to determine how quickly the pitch of a passing ambulance’s siren changes. If the vehicle is traveling slowly, the pitch changes only slightly, but if it is traveling fast, the pitch also changes rapidly. In a similar way, the wind in the middle atmosphere modulates the wavelength of atmospheric gravity waves. We have investigated the question of how strong the maximum wind may be so that the change in wavelength can still be determined with the help of wavelet transformation.
Qiang Guo, Yuning Liu, Xin Wang, and Wen Hui
Atmos. Meas. Tech., 17, 4613–4627, https://doi.org/10.5194/amt-17-4613-2024, https://doi.org/10.5194/amt-17-4613-2024, 2024
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Non-linearity (NL) correction is a critical procedure to guarantee that the calibration accuracy of a spaceborne sensor approaches a reasonable level. Different from the classical method, a new NL correction method for a spaceborne Fourier transform spectrometer is proposed. To overcome the inaccurate linear coefficient from two-point calibration influencing NL correction, an iteration algorithm is established that is suitable for NL correction of both infrared and microwave sensors.
Bing Cao, Jennifer S. Haase, Michael J. Murphy Jr., and Anna M. Wilson
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-119, https://doi.org/10.5194/amt-2024-119, 2024
Revised manuscript accepted for AMT
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This paper describes an Airborne Radio Occultation (ARO) observation system installed on reconnaissance aircraft that uses GPS signal refraction in the atmosphere to retrieve information about the temperature and moisture in the storm environment as far away as 400 km surrounding the flight track. The characteristics and quality of 1700 ARO refractivity profiles were assessed. These observations are collected to help understand atmospheric rivers and improve their forecasting.
Yuanxin Pan, Grzegorz Kłopotek, Laura Crocetti, Rudi Weinacker, Tobias Sturn, Linda See, Galina Dick, Gregor Möller, Markus Rothacher, Ian McCallum, Vicente Navarro, and Benedikt Soja
Atmos. Meas. Tech., 17, 4303–4316, https://doi.org/10.5194/amt-17-4303-2024, https://doi.org/10.5194/amt-17-4303-2024, 2024
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Crowdsourced smartphone GNSS data were processed with a dedicated data processing pipeline and could produce millimeter-level accurate estimates of zenith total delay (ZTD) – a critical atmospheric variable. This breakthrough not only demonstrates the feasibility of using ubiquitous devices for high-precision atmospheric monitoring but also underscores the potential for a global, cost-effective tropospheric monitoring network.
Almudena Velázquez Blázquez, Edward Baudrez, Nicolas Clerbaux, and Carlos Domenech
Atmos. Meas. Tech., 17, 4245–4256, https://doi.org/10.5194/amt-17-4245-2024, https://doi.org/10.5194/amt-17-4245-2024, 2024
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The Broadband Radiometer measures shortwave and total-wave radiances filtered by the spectral response of the instrument. To obtain unfiltered solar and thermal radiances, the effect of the spectral response needs to be corrected for, done within the BM-RAD processor. Errors in the unfiltering are propagated into fluxes; thus, accurate unfiltering is required for their proper estimation (within BMA-FLX). Unfiltering errors are estimated to be <0.5 % for the shortwave and <0.1 % for the longwave.
Qihou Zhou, Yanlin Li, and Yun Gong
Atmos. Meas. Tech., 17, 4197–4209, https://doi.org/10.5194/amt-17-4197-2024, https://doi.org/10.5194/amt-17-4197-2024, 2024
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We discuss several robust estimators to compute the variance of a normally distributed random variable to deal with interference. Compared to rank-based estimators, the methods based on the geometric mean are more accurate and are computationally more efficient. We apply three robust estimators to incoherent scatter power and velocity processing, along with the traditional sample mean estimator. The best estimator is a hybrid estimator that combines the sample mean and a robust estimator.
Zhao Shi, Yuxiang Wen, and Jianxin He
Atmos. Meas. Tech., 17, 4121–4135, https://doi.org/10.5194/amt-17-4121-2024, https://doi.org/10.5194/amt-17-4121-2024, 2024
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The squall line is a type of convective system. Squall lines are often associated with damaging weather, so identifying and tracking squall lines plays an important role in early meteorological disaster warnings. A clustering-based method is proposed in this article. It can identify the squall lines within the radar scanning range with an accuracy rate of 95.93 %. It can also provide the three-dimensional structure and movement tracking results for each squall line.
Elizabeth N. Smith and Jacob T. Carlin
Atmos. Meas. Tech., 17, 4087–4107, https://doi.org/10.5194/amt-17-4087-2024, https://doi.org/10.5194/amt-17-4087-2024, 2024
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Boundary-layer height observations remain sparse in time and space. In this study we create a new fuzzy logic method for synergistically combining boundary-layer height estimates from a suite of instruments. These estimates generally compare well to those from radiosondes; plus, the approach offers near-continuous estimates through the entire diurnal cycle. Suspected reasons for discrepancies are discussed. The code for the newly presented fuzzy logic method is provided for the community to use.
Laura Bianco, Bianca Adler, Ludovic Bariteau, Irina V. Djalalova, Timothy Myers, Sergio Pezoa, David D. Turner, and James M. Wilczak
Atmos. Meas. Tech., 17, 3933–3948, https://doi.org/10.5194/amt-17-3933-2024, https://doi.org/10.5194/amt-17-3933-2024, 2024
Short summary
Short summary
The Tropospheric Remotely Observed Profiling via Optimal Estimation physical retrieval is used to retrieve temperature and humidity profiles from various combinations of passive and active remote sensing instruments, surface platforms, and numerical weather prediction models. The retrieved profiles are assessed against collocated radiosonde in non-cloudy conditions to assess the sensitivity of the retrievals to different input combinations. Case studies with cloudy conditions are also inspected.
Björn Linder, Peter Preusse, Qiuyu Chen, Ole Martin Christensen, Lukas Krasauskas, Linda Megner, Manfred Ern, and Jörg Gumbel
Atmos. Meas. Tech., 17, 3829–3841, https://doi.org/10.5194/amt-17-3829-2024, https://doi.org/10.5194/amt-17-3829-2024, 2024
Short summary
Short summary
The Swedish research satellite MATS (Mesospheric Airglow/Aerosol Tomography and Spectroscopy) is designed to study atmospheric waves in the mesosphere and lower thermosphere. These waves perturb the temperature field, and thus, by observing three-dimensional temperature fluctuations, their properties can be quantified. This pre-study uses synthetic MATS data generated from a general circulation model to investigate how well wave properties can be retrieved.
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Short summary
Under warmer global temperatures, precipitation patterns are expected to shift substantially, with critical impact on the global water-energy budget. In this work, we develop a deep learning model for predicting snow and rain accumulation based on surface radar observations of the lower atmosphere. Our model demonstrates improved skill over traditional methods and provides new insights into the regions of the atmosphere that provide the most significant contributions to high model accuracy.
Under warmer global temperatures, precipitation patterns are expected to shift substantially,...
