Articles | Volume 25, issue 23
https://doi.org/10.5194/acp-25-17301-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-17301-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Understanding mesoscale convective processes over the Congo Basin using the Model for Prediction Across Scales-Atmosphere (MPAS-A)
Joint Institute for Regional Earth System Science & Engineering, University of California, Los Angeles, Los Angeles, CA, USA
Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, Los Angeles, CA, USA
Rong Fu
Joint Institute for Regional Earth System Science & Engineering, University of California, Los Angeles, Los Angeles, CA, USA
Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, Los Angeles, CA, USA
Kelly Núñez Ocasio
Department of Atmospheric Sciences, Texas A&M University, College Station, TX, USA
Robert Nystrom
Department of Earth, Atmosphere, and Climate, Iowa State University, Ames, IA, USA
Cenlin He
Research Applications Laboratory, NSF National Center for Atmospheric Research (NCAR), Boulder, CO, USA
Jiaying Zhang
Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, University of Illinois Urbana-Champaign, Urbana, IL, USA
Xianan Jiang
Joint Institute for Regional Earth System Science & Engineering, University of California, Los Angeles, Los Angeles, CA, USA
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Joao Teixeira
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
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Sarah Worden and Rong Fu
EGUsphere, https://doi.org/10.5194/egusphere-2025-4330, https://doi.org/10.5194/egusphere-2025-4330, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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We studied how the rainy seasons begin in the equatorial Congo Basin in Africa. Using satellite and climate data, we found they are triggered by shifts in large-scale winds that bring in ocean moisture. Evapotranspiration supplies most moisture but does not change during this period. These winds push atmospheric moisture up against the East African Rift mountains to moisten the atmosphere and start the rainy seasons.
Cenlin He, Tzu-Shun Lin, David M. Mocko, Ronnie Abolafia-Rosenzweig, Jerry W. Wegiel, and Sujay V. Kumar
Geosci. Model Dev., 18, 8439–8460, https://doi.org/10.5194/gmd-18-8439-2025, https://doi.org/10.5194/gmd-18-8439-2025, 2025
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This study integrates the refactored community Noah-MP version 5.0 model with the NASA Land Information System (LIS) version 7.5.2 to streamline the synchronization, development, and maintenance of Noah-MP within LIS and to enhance their interoperability and applicability. The model benchmarking and evaluation results reveal key model strengths and weaknesses in simulating land surface quantities and show implications for future model improvements.
Parag Joshi, Tzu-Shun Lin, Cenlin He, and Katia Lamer
Geosci. Model Dev., 18, 7869–7890, https://doi.org/10.5194/gmd-18-7869-2025, https://doi.org/10.5194/gmd-18-7869-2025, 2025
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Present study revisits model that represent urban effects in the Weather Research & Forecasting model. We propose methods to identify evaluable parameters via field measurements and found inconsistencies between physics and its code implementation. Simulations reveal small errors can significantly impact outputs.
Naoki Mizukami, Samar Minallah, Cenlin He, Chayan Roychoudhury, William Y.Y. Cheng, and Rajesh Kumar
EGUsphere, https://doi.org/10.5194/egusphere-2025-4586, https://doi.org/10.5194/egusphere-2025-4586, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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We examined how air pollution particles that darken snow affect water resources in High Mountain Asia, a region that supplies rivers vital to millions of populations. Using computer models, we found that these particles cause snow to melt two weeks to a month earlier, shifting when water becomes available. This leads to more runoff at first but less later in the year, slightly reducing annual river flow. The findings highlight the need to link air pollution control with water management.
Chayan Roychoudhury, Rajesh Kumar, Cenlin He, William Y. Y. Cheng, Kirpa Ram, Naoki Mizukami, and Avelino F. Arellano
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-275, https://doi.org/10.5194/essd-2025-275, 2025
Preprint under review for ESSD
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We present a 17-year, 12 km regional dataset for Asia that uniquely captures aerosol–weather–snow interactions. By assimilating satellite data into a chemistry–climate model, it provides hourly to three-hourly fields of meteorology, air quality, and snow-related variables. Evaluations show good agreement with observations, and source attribution of black carbon is also provided to quantify pollution pathways to Asia’s glaciers, major freshwater source for over a billion people.
Yanyan Cheng, Kalli Furtado, Cenlin He, Fei Chen, Alan Ziegler, Song Chen, Matteo Detto, Yuna Mao, Baoxiang Pan, Yoshiko Kosugi, Marryanna Lion, Shoji Noguchi, Satoru Takanashi, Lulie Melling, and Baoqing Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-3898, https://doi.org/10.5194/egusphere-2025-3898, 2025
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Tropical land surface processes shape the Earth’s climate, but models often lack accuracy in the tropics due to limited data for validation. We improved the Noah-MP land surface model for the tropics using data from forests in Panama and Malaysia, and an urban site in Singapore. Calibration enhanced simulations of energy and water fluxes, and revealed key vegetation and soil parameters, as well as future directions for model improvement in tropical regions.
Chayan Roychoudhury, Cenlin He, Rajesh Kumar, and Avelino F. Arellano Jr.
Earth Syst. Dynam., 16, 1237–1266, https://doi.org/10.5194/esd-16-1237-2025, https://doi.org/10.5194/esd-16-1237-2025, 2025
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We present a novel data-driven approach to understand how pollution and weather processes interact to influence snowmelt in Asian glaciers and how these interactions are represented in three climate models. Our findings show where models need improvement in predicting snowmelt, particularly dust and its transport. This method can support future model development for reliable predictions in climate-vulnerable regions.
Rajesh Kumar, Piyush Bhardwaj, Cenlin He, Jennifer Boehnert, Forrest Lacey, Stefano Alessandrini, Kevin Sampson, Matthew Casali, Scott Swerdlin, Olga Wilhelmi, Gabriele G. Pfister, Benjamin Gaubert, and Helen Worden
Earth Syst. Sci. Data, 17, 1807–1834, https://doi.org/10.5194/essd-17-1807-2025, https://doi.org/10.5194/essd-17-1807-2025, 2025
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We have created a 14-year hourly air quality dataset at 12 km resolution by combining satellite observations of atmospheric composition with air quality models over the contiguous United States (CONUS). The dataset has been found to reproduce key observed features of air quality over the CONUS. To enable easy visualization and interpretation of county-level air quality measures and trends by stakeholders, an ArcGIS air quality dashboard has also been developed.
Mohamed Hamitouche, Giorgia Fosser, Alessandro Anav, Cenlin He, and Tzu-Shun Lin
Hydrol. Earth Syst. Sci., 29, 1221–1240, https://doi.org/10.5194/hess-29-1221-2025, https://doi.org/10.5194/hess-29-1221-2025, 2025
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This study evaluates how different methods of simulating runoff impact river flow predictions globally. By comparing seven approaches within the Noah-Multi-parameterisation (Noah-MP) land surface model, we found significant differences in accuracy, with some methods underestimating or overestimating runoff. The results are crucial for improving water resource management and flood prediction. Our work highlights the need for precise modelling to better prepare for climate-related challenges.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
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This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Tim Trent, Marc Schröder, Shu-Peng Ho, Steffen Beirle, Ralf Bennartz, Eva Borbas, Christian Borger, Helene Brogniez, Xavier Calbet, Elisa Castelli, Gilbert P. Compo, Wesley Ebisuzaki, Ulrike Falk, Frank Fell, John Forsythe, Hans Hersbach, Misako Kachi, Shinya Kobayashi, Robert E. Kursinski, Diego Loyola, Zhengzao Luo, Johannes K. Nielsen, Enzo Papandrea, Laurence Picon, Rene Preusker, Anthony Reale, Lei Shi, Laura Slivinski, Joao Teixeira, Tom Vonder Haar, and Thomas Wagner
Atmos. Chem. Phys., 24, 9667–9695, https://doi.org/10.5194/acp-24-9667-2024, https://doi.org/10.5194/acp-24-9667-2024, 2024
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In a warmer future, water vapour will spend more time in the atmosphere, changing global rainfall patterns. In this study, we analysed the performance of 28 water vapour records between 1988 and 2014. We find sensitivity to surface warming generally outside expected ranges, attributed to breakpoints in individual record trends and differing representations of climate variability. The implication is that longer records are required for high confidence in assessing climate trends.
Kelly M. Núñez Ocasio and Zachary L. Moon
Geosci. Model Dev., 17, 6035–6049, https://doi.org/10.5194/gmd-17-6035-2024, https://doi.org/10.5194/gmd-17-6035-2024, 2024
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TAMS is an open-source Python-based package for tracking and classifying mesoscale convective systems that can be used to study observed and simulated systems. Each step of the algorithm is described in this paper with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this tracker is its support for unstructured grids in the identification stage and grid-independent tracking.
João Teixeira, R. Chris Wilson, and Heidar Th. Thrastarson
Atmos. Chem. Phys., 24, 6375–6383, https://doi.org/10.5194/acp-24-6375-2024, https://doi.org/10.5194/acp-24-6375-2024, 2024
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This paper presents direct evidence from space (solely based on observations) that CO2 increase leads to the theoretically expected effects on longwave spectral radiances. This is achieved by using a methodology that allows us to isolate the CO2 effects from the temperature and water vapor effects. By searching for ensembles of temperature and water vapor profiles that are similar to each other but have different values of CO2, it is possible to estimate the direct effects of CO2 on the spectra.
Gaoyun Wang, Rong Fu, Yizhou Zhuang, Paul A. Dirmeyer, Joseph A. Santanello, Guiling Wang, Kun Yang, and Kaighin McColl
Atmos. Chem. Phys., 24, 3857–3868, https://doi.org/10.5194/acp-24-3857-2024, https://doi.org/10.5194/acp-24-3857-2024, 2024
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This study investigates the influence of lower-tropospheric humidity on land–atmosphere coupling (LAC) during warm seasons in the US Southern Great Plains. Using radiosonde data and a buoyancy model, we find that elevated LT humidity is crucial for generating afternoon precipitation events under dry soil conditions not accounted for by conventional LAC indices. This underscores the importance of considering LT humidity in understanding LAC over dry soil during droughts in the SGP.
Yizhou Zhuang and Rong Fu
Atmos. Chem. Phys., 24, 1641–1657, https://doi.org/10.5194/acp-24-1641-2024, https://doi.org/10.5194/acp-24-1641-2024, 2024
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This study investigated how atmospheric circulation affects precipitation variability and changes in the US Great Plains (GP) and southwest (SW). By developing a new method called self organizing map–analogue, we found that circulation significantly influences short-term precipitation variability, accounting for 54 %–61 % of the total variance. Furthermore, circulation contributes considerably to the multi-decadal changes in precipitation and its extremes, especially for the southern GP and SW.
Wenfu Tang, Louisa K. Emmons, Helen M. Worden, Rajesh Kumar, Cenlin He, Benjamin Gaubert, Zhonghua Zheng, Simone Tilmes, Rebecca R. Buchholz, Sara-Eva Martinez-Alonso, Claire Granier, Antonin Soulie, Kathryn McKain, Bruce C. Daube, Jeff Peischl, Chelsea Thompson, and Pieternel Levelt
Geosci. Model Dev., 16, 6001–6028, https://doi.org/10.5194/gmd-16-6001-2023, https://doi.org/10.5194/gmd-16-6001-2023, 2023
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The new MUSICAv0 model enables the study of atmospheric chemistry across all relevant scales. We develop a MUSICAv0 grid for Africa. We evaluate MUSICAv0 with observations and compare it with a previously used model – WRF-Chem. Overall, the performance of MUSICAv0 is comparable to WRF-Chem. Based on model–satellite discrepancies, we find that future field campaigns in an eastern African region (30°E–45°E, 5°S–5°N) could substantially improve the predictive skill of air quality models.
Cenlin He, Prasanth Valayamkunnath, Michael Barlage, Fei Chen, David Gochis, Ryan Cabell, Tim Schneider, Roy Rasmussen, Guo-Yue Niu, Zong-Liang Yang, Dev Niyogi, and Michael Ek
Geosci. Model Dev., 16, 5131–5151, https://doi.org/10.5194/gmd-16-5131-2023, https://doi.org/10.5194/gmd-16-5131-2023, 2023
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Noah-MP is one of the most widely used open-source community land surface models in the world, designed for applications ranging from uncoupled land surface and ecohydrological process studies to coupled numerical weather prediction and decadal climate simulations. To facilitate model developments and applications, we modernize Noah-MP by adopting modern Fortran code and data structures and standards, which substantially enhance model modularity, interoperability, and applicability.
Zhe Zhang, Yanping Li, Fei Chen, Phillip Harder, Warren Helgason, James Famiglietti, Prasanth Valayamkunnath, Cenlin He, and Zhenhua Li
Geosci. Model Dev., 16, 3809–3825, https://doi.org/10.5194/gmd-16-3809-2023, https://doi.org/10.5194/gmd-16-3809-2023, 2023
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Crop models incorporated in Earth system models are essential to accurately simulate crop growth processes on Earth's surface and agricultural production. In this study, we aim to model the spring wheat in the Northern Great Plains, focusing on three aspects: (1) develop the wheat model at a point scale, (2) apply dynamic planting and harvest schedules, and (3) adopt a revised heat stress function. The results show substantial improvements and have great importance for agricultural production.
Wenfu Tang, Simone Tilmes, David M. Lawrence, Fang Li, Cenlin He, Louisa K. Emmons, Rebecca R. Buchholz, and Lili Xia
Atmos. Chem. Phys., 23, 5467–5486, https://doi.org/10.5194/acp-23-5467-2023, https://doi.org/10.5194/acp-23-5467-2023, 2023
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Globally, total wildfire burned area is projected to increase over the 21st century under scenarios without geoengineering and decrease under the two geoengineering scenarios. Geoengineering reduces fire by decreasing surface temperature and wind speed and increasing relative humidity and soil water. However, geoengineering also yields reductions in precipitation, which offset some of the fire reduction.
Maria J. Chinita, Mikael Witte, Marcin J. Kurowski, Joao Teixeira, Kay Suselj, Georgios Matheou, and Peter Bogenschutz
Geosci. Model Dev., 16, 1909–1924, https://doi.org/10.5194/gmd-16-1909-2023, https://doi.org/10.5194/gmd-16-1909-2023, 2023
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Low clouds are one of the largest sources of uncertainty in climate prediction. In this paper, we introduce the first version of the unified turbulence and shallow convection parameterization named SHOC+MF developed to improve the representation of shallow cumulus clouds in the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM). Here, we also show promising preliminary results in a single-column model framework for two benchmark cases of shallow cumulus convection.
Dalei Hao, Gautam Bisht, Karl Rittger, Edward Bair, Cenlin He, Huilin Huang, Cheng Dang, Timbo Stillinger, Yu Gu, Hailong Wang, Yun Qian, and L. Ruby Leung
Geosci. Model Dev., 16, 75–94, https://doi.org/10.5194/gmd-16-75-2023, https://doi.org/10.5194/gmd-16-75-2023, 2023
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Snow with the highest albedo of land surface plays a vital role in Earth’s surface energy budget and water cycle. This study accounts for the impacts of snow grain shape and mixing state of light-absorbing particles with snow on snow albedo in the E3SM land model. The findings advance our understanding of the role of snow grain shape and mixing state of LAP–snow in land surface processes and offer guidance for improving snow simulations and radiative forcing estimates in Earth system models.
Huilin Huang, Yun Qian, Ye Liu, Cenlin He, Jianyu Zheng, Zhibo Zhang, and Antonis Gkikas
Atmos. Chem. Phys., 22, 15469–15488, https://doi.org/10.5194/acp-22-15469-2022, https://doi.org/10.5194/acp-22-15469-2022, 2022
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Using a clustering method developed in the field of artificial neural networks, we identify four typical dust transport patterns across the Sierra Nevada, associated with the mesoscale and regional-scale wind circulations. Our results highlight the connection between dust transport and dominant weather patterns, which can be used to understand dust transport in a changing climate.
Chaman Gul, Shichang Kang, Siva Praveen Puppala, Xiaokang Wu, Cenlin He, Yangyang Xu, Inka Koch, Sher Muhammad, Rajesh Kumar, and Getachew Dubache
Atmos. Chem. Phys., 22, 8725–8737, https://doi.org/10.5194/acp-22-8725-2022, https://doi.org/10.5194/acp-22-8725-2022, 2022
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This work aims to understand concentrations, spatial variability, and potential source regions of light-absorbing impurities (black carbon aerosols, dust particles, and organic carbon) in the surface snow of central and western Himalayan glaciers and their impact on snow albedo and radiative forcing.
Mark G. Flanner, Julian B. Arnheim, Joseph M. Cook, Cheng Dang, Cenlin He, Xianglei Huang, Deepak Singh, S. McKenzie Skiles, Chloe A. Whicker, and Charles S. Zender
Geosci. Model Dev., 14, 7673–7704, https://doi.org/10.5194/gmd-14-7673-2021, https://doi.org/10.5194/gmd-14-7673-2021, 2021
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We present the technical formulation and evaluation of a publicly available code and web-based model to simulate the spectral albedo of snow. Our model accounts for numerous features of the snow state and ambient conditions, including the the presence of light-absorbing matter like black and brown carbon, mineral dust, volcanic ash, and snow algae. Carbon dioxide snow, found on Mars, is also represented. The model accurately reproduces spectral measurements of clean and contaminated snow.
Sudip Chakraborty, Jonathon H. Jiang, Hui Su, and Rong Fu
Atmos. Chem. Phys., 21, 12855–12866, https://doi.org/10.5194/acp-21-12855-2021, https://doi.org/10.5194/acp-21-12855-2021, 2021
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Boreal autumn is the main wet season over the Congo basin. Thus, changes in its onset date have a significant impact on the rainforest. This study provides compelling evidence that the cooling effect of aerosols modifies the timing and strength of the southern African easterly jet that is central to the boreal autumn wet season over the Congo rainforest. A higher boreal summer aerosol concentration is positively correlated with the boreal autumn wet season onset timing.
Julián Gelman Constantin, Lucas Ruiz, Gustavo Villarosa, Valeria Outes, Facundo N. Bajano, Cenlin He, Hector Bajano, and Laura Dawidowski
The Cryosphere, 14, 4581–4601, https://doi.org/10.5194/tc-14-4581-2020, https://doi.org/10.5194/tc-14-4581-2020, 2020
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We present the results of two field campaigns and modeling activities on the impact of atmospheric particles on Alerce Glacier (Argentinean Andes). We found that volcanic ash remains at different snow layers several years after eruption, increasing light absorption on the glacier surface (with a minor contribution of soot). This leads to 36 % higher annual glacier melting. We find remarkably that volcano eruptions in 2011 and 2015 have a relevant effect on the glacier even in 2016 and 2017.
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Short summary
The Congo Basin has frequent organized thunderstorms producing much of the region’s rainfall, yet their development remains unclear due to limited data. Using a high-resolution global model, it shows the long-lasting storm is significantly linked to and supported by vertical wind shear up to 400 km ahead, with the mid-level jet stream playing a role in maintaining the shear. The findings highlight the value of such model in data-sparse regions for examining storms and their impacts.
The Congo Basin has frequent organized thunderstorms producing much of the region’s rainfall,...
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