Harnessing phosphorus fertilizer to counteract warming-driven decline in maize water productivity under climate change Wei Chen, Hui Ju, Xin-Zhong Liang, William D. Batchelor, Qingquan Chu Agricultural Water Management, 2026 More judicious application of phosphorus (P) fertilizer can moderate the impacts of global warming on crop water productivity (WP) in (semi-)arid regions, but its long-term feedback on future climate and maize ecoregions remains unclear. This study quantified future changes in maize WP under multiple climate scenarios in the Yellow River Basin (YRB) of China and evaluated the potential of optimized P fertilization to mitigate WP decline. Based on the process-maize-model and combined with 5 global climate models (GCMs) × 3 shared socioeconomic pathway scenarios (SSPs; SSP126, SSP370, and SSP585), our results showed that WP of maize will decrease by an average of 5% in future relative to the baseline period in the whole YRB, with a greater decline under the SSP585 scenario. WP in different ecoregions also declined, particularly in the Huang-Huai region (II), which experienced significant decreases ( p < 0.05) under SSP585 in the 2021–2040 (2030s), 2041–2070 (2050s), and 2071–2100 (2080s). Rising temperatures were the primary driver, with a threshold effect observed: WP turned point at above 20℃ in eastern YRB (regions I and II), while in the rest of other ecoregions (III-V), it peaked around 12℃ then declining. After crossing temperature thresholds under an ensemble of projected climate scenarios, optimizing P fertilization increased maize WP by an average of 10.5% compared with the no-fertilization treatment. A combined nitrogen (N) and P application (180 kg ha −1 and 90 kg ha −1 respectively) maximized WP across all SSPs. These findings provide critical temperature thresholds and effective fertilization strategies for sustaining future maize production and water consumption in the YRB and similar regions.
Rising vapor pressure deficit threatens maize water productivity in the Yellow River Basin under climate warming Wei Chen, Hui Ju, Xin-Zhong Liang, William D. Batchelor, Xintong Wang Agricultural Water Management, 2026 Maize production is highly vulnerable to rising vapor pressure deficit (VPD), yet its agricultural-scale impacts remain insufficiently characterized due to the lack of integrated assessments linking spatiotemporal VPD dynamics with crop-level water productivity (WP), particularly the relative contributions of yield and evapotranspiration (ET) under varying atmospheric drought conditions. Using the Coupled Model Intercomparison Project Phase 6 (CMIP6) data, we analyzed the spatiotemporal evolution of VPD across five maize ecoregions in the Yellow River Basin (YRB) under three Shared Socioeconomic Pathway (SSP) scenarios (baseline: 1985–2014; future: 2021–2100) and quantified its effects on maize WP. Mean VPD across the YRB maize ecoregions is projected to increase by 21% from 2021 to 2100 (vs. 1985–2014), peaking in the 2080 s under SSP585. Eastern ecoregions (II > I) experience greater VPD escalation than western counterparts (V > III > IV), with post-2030s VPD growth accelerating to 0.036 kPa/yr under SSP585, while SSP126 stabilizes. Projected VPD increases may hinder WP sustainability in regions II-V across all climate scenarios. ET primarily governs WP under mild atmospheric drought (VPD ≤ 4 kPa), whereas yield constraints dominate under severe drought. Thus, a VPD-dependent shift in the WP demands a process-based optimization of irrigation and yield management under varying atmospheric drought conditions and offers actionable insights for climate-resilient agricultural strategies in (semi-)arid maize-growing regions. • Vapor pressure deficit is projected to increase by 21% across maize regions in the Yellow River Basin. • Eastern regions show faster increases in atmospheric dryness than western regions under future scenarios. • High vapor pressure deficit increases the frequency of low water productivity years. • Water productivity shifts from evapotranspiration control to yield limitation beyond 4 kPa. • Yield-limited water productivity shows higher sensitivity to vapor pressure deficit.
Capturing Spatiotemporal and Subgrid Variability in Global Land Surface Albedo Parameterization Akarsh Ralhan, Xin‐Zhong Liang Journal of Advances in Modeling Earth Systems, 2026 Accurate surface albedo parameterization is critical for modeling Earth's energy balance. Yet, many schemes rely on static look‐up tables or semi‐empirical formulations that fail to capture spatiotemporal variations and complex radiative interactions. This study develops a physics‐informed machine‐learning parameterization using 19 years (2003–2021) of MODIS Bidirectional Reflectance Distribution Function data to predict direct and diffuse albedo in the visible and near‐infrared bands across major land‐cover categories. The framework leverages 10 biogeophysical predictors, including solar geometry, vegetation state, soil moisture, soil texture (STX), topography, and background climate. It comprises a dynamic component that resolves physical spatiotemporal patterns and a static correction, the Surface Albedo Localization Factor, which accounts for subgrid heterogeneity, together explaining most of the observed variability. The parameterization shows strong agreement with MODIS albedo (overall R 2 = 0.88, mean absolute percentage error [MAPE] = 7.5%), with performance ranging from R 2 = 0.85 in direct visible to R 2 = 0.90 in diffuse near‐infrared, and generally higher accuracy in the near‐infrared parts. It performs well across diverse LCCs, including grasslands, shrublands, croplands, and challenging barren regions where empirical methods underperform. SALF improves accuracy across all albedo parts (average R 2 increase of 0.16 and MAPE reduction of 5.1%). Feature‐importance analysis indicates that solar zenith angle and leaf area index are the dominant drivers of dynamic variability, whereas STX and topography influence static variability. Counterfactual experiments confirm biophysically consistent albedo responses, enhancing interpretability and model trust. This framework offers a physically grounded alternative to empirical schemes and has strong potential for integration into Earth system models to improve the representation of surface energy exchange.
Appreciation of Peer Reviewers for 2025 Abdelwahid Mellouki, Christian George, Filippo Giorgi, Gang Chen, Hella Garny, Manfred Wendisch, Nicole Riemer, Robert F. Rogers, William Randel, Xin‐Zhong Liang, Xiushu Qie, Yafang Cheng, Yongyun Hu, Yun Qian Journal of Geophysical Research Atmospheres, 2026 The editorial board of Journal of Geophysical Research (JGR): Atmospheres thanks the reviewers who refereed papers in 2025. The editors and associate editors wish to sincerely thank the 3,434 outstanding scientists who dedicated their time and expertise to reviewing manuscripts for the journal in 2025. We also extend our gratitude to those who recommended reviewers and volunteered to contribute to the peer review process. Peer review is a crucial process to ensure the integrity and rigor of science. Your thoughtful and constructive reviews have helped to improve the quality of papers in the journal, stimulated new ideas, and advanced the careers of many young scientists. They contributed to the high quality of JGR: Atmospheres and the standard of science in our discipline.
Appreciation of Peer Reviewers for 2024 Yafang Cheng, Rong Fu, Christian George, Filippo Giorgi, Yongyun Hu, Xin‐Zhong Liang, Abdelwahid Mellouki, Yun Qian, Xiushu Qie, William Randel, Nicole Riemer, Robert Rogers, Manfred Wendisch, Ping Yang Journal of Geophysical Research Atmospheres, 2025 The editorial board of JGR Atmospheres thanks the reviewers who refereed papers in 2024. The editors of Journal of Geophysical Research (JGR): Atmospheres wish to sincerely thank the 3,028 outstanding scientists who dedicated their time and expertise to reviewing manuscripts for the journal in 2024. We also extend our gratitude to those who recommended reviewers and volunteered to contribute to the peer review process. Peer review is a crucial process to ensure the integrity and rigor of science. Your thoughtful and constructive reviews have helped to improve the quality of papers in the journal, stimulated new ideas, and advanced the careers of many young scientists. They contributed to the high quality of JGR‐Atmospheres and the standard of science in our discipline.
Impacts of land surface processes on summer extreme precipitation in Eastern China: Insights from CWRF simulations Chenyi Zhang, Qingquan Li, Xin-Zhong Liang, Lili Dong, Bing Xie, Weiping Li, Chao Sun Atmospheric Research, 2025 Understanding the impacts of land surface processes on summer extreme precipitation is crucial for accurate climate predictions. This study investigated these impacts across three subregions of eastern China (North China, Central China, and South China) using the regional Climate–Weather Research and Forecasting model with two land surface parameterization schemes: the Conjunctive Surface–Subsurface Process (CSSP) scheme and the NOAH Land Surface Model (NOAH). When compared with observational and reanalysis data, both schemes were found to successfully reproduce the spatial distribution of extreme precipitation, with the CSSP scheme showing distinct advantages in simulating evapotranspiration. The influence of land surface processes on summer extreme precipitation varies among the three subregions, largely depending on soil moisture conditions. In North China, a transitional zone between arid and humid regions, soil moisture primarily influences extreme precipitation, with biases arising from difference between the lifting condensation level and the planetary boundary layer height. In Central China, where soil moisture is moderate, soil moisture and net radiation jointly influence extreme precipitation, with biases linked to the planetary boundary layer height. In South China, where soil moisture is mostly saturated during summer, net radiation dominates the variability of land surface variables, with latent heat bias leading to extreme precipitation bias. Overall, soil moisture affects extreme precipitation by altering the energy and stability of the planetary boundary layer and the lifting condensation level. These findings could inform the assessment and future improvement of models, and support the monitoring and predicting of extreme precipitation events. • Conjunctive Surface–Subsurface Process scheme can simulate realistically evapotranspiration and land–atmosphere interactions. • Relative contributions of individual land surface variables to summer extreme precipitation differ across three subregions in eastern China. • Soil moisture affects summer extreme precipitation by altering the state of the planetary boundary layer and the lifting condensation level.
Appreciation of Peer Reviewers for 2023 Yafang Cheng, Rong Fu, Christian George, Filippo Giorgi, Ruby Leung, Xin‐Zhong Liang, Wahid Mellouki, William Randel, Nicole Riemer, Robert Rogers, Lynn Russell, Ping Yang, Xiushu Qie, Yun Qian, Yongyun Hu Journal of Geophysical Research Atmospheres, 2024
Regional climate model intercomparison over the Tibetan Plateau in the GEWEX/LS4P Phase I Jianping Tang, Yongkang Xue, Mengyuan Long, Mengnan Ma, Xin-Zhong Liang, Shiori Sugimoto, Kun Yang, Zhenming Ji, Jinkyu Hong, Jeongwon Kim, Haoran Xu, Xu Zhou, Tomonori Sato, Hiroshi G. Takahashi, Shuyu Wang, Guiling Wang, Sin Chan Chou, Weidong Guo, Miao Yu, Xiaoduo Pan Climate Dynamics, 2024
Remote effects of Tibetan Plateau spring land temperature on global subseasonal to seasonal precipitation prediction and comparison with effects of sea surface temperature: the GEWEX/LS4P Phase I experiment Yongkang Xue, Ismaila Diallo, Aaron A. Boone, Yang Zhang, Xubin Zeng, William K. M. Lau, J. David Neelin, Tandong Yao, Qi Tang, Tomonori Sato, Myung-Seo Koo, Frederic Vitart, Constantin Ardilouze, Subodh K. Saha, Stefano Materia, Zhaohui Lin, Yuhei Takaya, Jing Yang, Tetsu Nakamura, Xin Qi, Yi Qin, Paulo Nobre, Retish Senan, Hailan Wang, Hongliang Zhang, Mei Zhao, Hara Prasad Nayak, Yan Pan, Xiaoduo Pan, Jinming Feng, Chunxiang Shi, Shaocheng Xie, Michael A. Brunke, Qing Bao, Marcus Jorge Bottino, Tianyi Fan, Songyou Hong, Yanluan Lin, Daniele Peano, Yanling Zhan, Carlos R. Mechoso, Xuejuan Ren, Gianpaolo Balsamo, Sin Chan Chou, Patricia de Rosnay, Peter J. van Oevelen, Daniel Klocke, Michael Ek, Xin Li, Weidong Guo, Yuejian Zhu, Jianping Tang, Xin-Zhong Liang, Yun Qian, Ping Zhao Climate Dynamics, 2024
Dashboard for Agricultural Water Use and Nutrient Management—A Predictive Decision Support System to Improve Crop Production in a Changing Climate Xin-Zhong Liang, Drew Gower, Jennifer A. Kennedy, Melissa Kenney, Michael C. Maddox, Michael Gerst, Guillermo Balboa, Talon Becker, Ximing Cai, Roger Elmore, Wei Gao, Yufeng He, Kang Liang, Shane Lotton, Leena Malayil, Megan L. Matthews, Alison M. Meadow, Christopher M. U. Neale, Greg Newman, Amy Rebecca Sapkota, Sanghoon Shin, Jonathan Straube, Chao Sun, You Wu, Yun Yang, Xuesong Zhang Bulletin of the American Meteorological Society, 2024
Spring Land Temperature in Tibetan Plateau and Global-Scale Summer Precipitation Yongkang Xue, Ismaila Diallo, Aaron A. Boone, Tandong Yao, Yang Zhang, Xubin Zeng, J. David Neelin, William K. M. Lau, Yan Pan, Ye Liu, Xiaoduo Pan, Qi Tang, Peter J. van Oevelen, Tomonori Sato, Myung-Seo Koo, Stefano Materia, Chunxiang Shi, Jing Yang, Constantin Ardilouze, Zhaohui Lin, Xin Qi, Tetsu Nakamura, Subodh K. Saha, Retish Senan, Yuhei Takaya, Hailan Wang, Hongliang Zhang, Mei Zhao, Hara Prasad Nayak, Qiuyu Chen, Jinming Feng, Michael A. Brunke, Tianyi Fan, Songyou Hong, Paulo Nobre, Daniele Peano, Yi Qin, Frederic Vitart, Shaocheng Xie, Yanling Zhan, Daniel Klocke, Ruby Leung, Xin Li, Michael Ek, Weidong Guo, Gianpaolo Balsamo, Qing Bao, Sin Chan Chou, Patricia de Rosnay, Yanluan Lin, Yuejian Zhu, Yun Qian, Ping Zhao, Jianping Tang, Xin-Zhong Liang, Jinkyu Hong, Duoying Ji, Zhenming Ji, Yuan Qiu, Shiori Sugimoto, Weicai Wang, Kun Yang, Miao Yu Bulletin of the American Meteorological Society, 2022
Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction Project, Phase i (LS4P-I): Organization and experimental design Yongkang Xue, Tandong Yao, Aaron A. Boone, Ismaila Diallo, Ye Liu, Xubin Zeng, William K. M. Lau, Shiori Sugimoto, Qi Tang, Xiaoduo Pan, Peter J. van Oevelen, Daniel Klocke, Myung-Seo Koo, Tomonori Sato, Zhaohui Lin, Yuhei Takaya, Constantin Ardilouze, Stefano Materia, Subodh K. Saha, Retish Senan, Tetsu Nakamura, Hailan Wang, Jing Yang, Hongliang Zhang, Mei Zhao, Xin-Zhong Liang, J. David Neelin, Frederic Vitart, Xin Li, Ping Zhao, Chunxiang Shi, Weidong Guo, Jianping Tang, Miao Yu, Yun Qian, Samuel S. P. Shen, Yang Zhang, Kun Yang, Ruby Leung, Yuan Qiu, Daniele Peano, Xin Qi, Yanling Zhan, Michael A. Brunke, Sin Chan Chou, Michael Ek, Tianyi Fan, Hong Guan, Hai Lin, Shunlin Liang, Helin Wei, Shaocheng Xie, Haoran Xu, Weiping Li, Xueli Shi, Paulo Nobre, Yan Pan, Yi Qin, Jeff Dozier, Craig R. Ferguson, Gianpaolo Balsamo, Qing Bao, Jinming Feng, Jinkyu Hong, Songyou Hong, Huilin Huang, Duoying Ji, Zhenming Ji, Shichang Kang, Yanluan Lin, Weiguang Liu, Ryan Muncaster, Patricia de Rosnay, Hiroshi G. Takahashi, Guiling Wang, Shuyu Wang, Weicai Wang, Xu Zhou, Yuejian Zhu Geoscientific Model Development, 2021
Determining climate effects on US total agricultural productivity Xin-Zhong Liang, You Wu, Robert G. Chambers, Daniel L. Schmoldt, Wei Gao, Chaoshun Liu, Yan-An Liu, Chao Sun, Jennifer A. Kennedy Proceedings of the National Academy of Sciences of the United States of America, 2017
Regional climate-weather research and forecasting model Xin-Zhong Liang, Min Xu, Xing Yuan, Tiejun Ling, Hyun I. Choi, Feng Zhang, Ligang Chen, Shuyan Liu, Shenjian Su, Fengxue Qiao, Yuxiang He, Julian X. L. Wang, Kenneth E. Kunkel, Wei Gao, Everette Joseph, Vernon Morris, Tsann-Wang Yu, Jimy Dudhia, John Michalakes Bulletin of the American Meteorological Society, 2012
Analysis of the structure of the temperature field in relation to the persistent snowy and cold weather in South China in early 2008 Acta Meteorologica Sinica, 2010
A preliminary synthesis of modeled climate change impacts on U.S. regional ozone concentrations C. P. Weaver, X.-Z. Liang, J. Zhu, P. J. Adams, P. Amar, J. Avise, M. Caughey, J. Chen, R. C. Cohen, E. Cooter, J. P. Dawson, R. Gilliam, A. Gilliland, A. H. Goldstein, A. Grambsch, D. Grano, A. Guenther, W. I. Gustafson, R. A. Harley, S. He, B. Hemming, C. Hogrefe, H.-C. Huang, S. W. Hunt, D.J. Jacob, P. L. Kinney, K. Kunkel, J.-F. Lamarque, B. Lamb, N. K. Larkin, L. R. Leung, K.-J. Liao, J.-T. Lin, B. H. Lynn, K. Manomaiphiboon, C. Mass, D. McKenzie, L. J. Mickley, S. M. O'neill, C. Nolte, S. N. Pandis, P. N. Racherla, C. Rosenzweig, A. G. Russell, E. Salathé, A. L. Steiner, E. Tagaris, Z. Tao, S. Tonse, C. Wiedinmyer, A. Williams, D. A. Winner, J.-H. Woo, S. WU, D. J. Wuebbles Bulletin of the American Meteorological Society, 2009
Regional climate change projections for the Northeast USA Katharine Hayhoe, Cameron Wake, Bruce Anderson, Xin-Zhong Liang, Edwin Maurer, Jinhong Zhu, James Bradbury, Art DeGaetano, Anne Marie Stoner, Donald Wuebbles Mitigation and Adaptation Strategies for Global Change, 2008
Global modeling studies of potential climate change effects on U.S. air quality - Part 1: How well can PCM drive the chemical transport model? 86th Ams Annual Meeting, 2006
Comparison of the seasonal change in cloud-radiative forcing from atmospheric general circulation models and satellite observations R. D. Cess, M. H. Zhang, G. L. Potter, V. Alekseev, H. W. Barker, S. Bony, R. A. Colman, D. A. Dazlich, A. D. Del Genio, M. Déqué, M. R. Dix, V. Dymnikov, M. Esch, L. D. Fowler, J. R. Fraser, V. Galin, W. L. Gates, J. J. Hack, W. J. Ingram, J. T. Kiehl, Y. Kim, H. Le Treut, X.‐Z. Liang, B. J. McAvaney, V. P. Meleshko, J. J. Morcrette, D. A. Randall, E. Roeckner, M. E. Schlesinger, P. V. Sporyshev, K. E. Taylor, B. Timbal, E. M. Volodin, W. Wang, W. C. Wang, R. T. Wetherald Journal of Geophysical Research Atmospheres, 1997
Uncertainties in carbon dioxide radiative forcing in atmospheric general circulation models R. D. Cess, M.-H. Zhang, G. L. Potter, H. W. Barker, R. A. Colman, D. A. Dazlich, A. D. Del Genio, M. Esch, J. R. Fraser, V. Galin, W. L. Gates, J. J. Hack, W. J. Ingram, J. T. Kiehl, A. A. Lacis, H. Le Treut, Z.-X. Li, X.-Z. Liang, J.-F. Mahfouf, B. J. McAvaney, V. P. Meleshko, J.-J. Morcrette, D. A. Randall, E. Roeckner, J.-F. Royer, A. P. Sokolov, P. V. Sporyshev, K. E. Taylor, W.-C. Wang, R. T. Wetherald Science, 1993
Intercomparison and interpretation of surface energy fluxes in atmospheric general circulation models D. A. Randall, R. D. Cess, J. P. Blanchet, G. J. Boer, D. A. Dazlich, A. D. Del Genio, M. Deque, V. Dymnikov, V. Galin, S. J. Ghan, A. A. Lacis, H. Le Treut, Z.‐X. Li, X.‐Z. Liang, B. J. McAvaney, V. P. Meleshko, J. F. B. Mitchell, J.‐J. Morcrette, G. L. Potter, L. Rikus, E. Roeckner, J. F. Royer, U. Schlese, D. A. Sheinin, J. Slingo, A. P. Sokolov, K. E. Taylor, W. M. Washington, R. T. Wetherald, I. Yagai, M.‐H. Zhang Journal of Geophysical Research, 1992
Interpretation of snow-climate feedback as produced by 17 general circulation models R. D. Cess, G. L. Potter, M.-H. Zhang, J.-P. Blanchet, S. Chalita, R. Colman, D. A. Dazlich, A. D. Del Genio, V. Dymnikov, V. Galin, D. Jerrett, E. Keup, A. A. Lacis, H. Le Treut, X.-Z. Liang, J.-F. Mahfouf, B. J. McAvaney, V. P. Meleshko, J. F. B. Mitchell, J.-J. Morcrette, P. M. Norris, D. A. Randall, L. Rikus, E. Roeckner, J.-F. Royer, U. Schlese, D. A. Sheinin, J. M. Slingo, A. S. Sokolov, K. E. Taylor, W. M. Washington, R. T. Wetherald, I. Yagai Science, 1991
Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models Journal of Geophysical Research, 1990
Rising Greenhouse Gas Emissions from Global Rice Paddies and Mitigation Strategies J Zhang, ... Nature Food , 2026 2026
A sub-seasonal to seasonal climate forecast informed irrigation scheduling tool for the Contiguous United States H Shi, X Cai, X Hu, A Jamal, D Li, C Sun, XZ Liang Environmental Modelling & Software, 106819 , 2025 2025 Citations: 1
Quantifying aggregated economic damages from “fat-tail” extremes high-temperature events in climate change H Deng, X Wu, H Xu, Y Wu, XZ Liang Structural Change and Economic Dynamics 75, 108-121 , 2025 2025 Citations: 2
Future implications of climate change on maize yield and quality in the Yellow River Basin of China W Chen, X Long, J Wang, XZ Liang, D Zhang, H Ju Theoretical and Applied Climatology 156 (5), 253 , 2025 2025 Citations: 1
Impacts of land surface processes on summer extreme precipitation in Eastern China: Insights from CWRF simulations C Zhang, Q Li, XZ Liang, L Dong, B Xie, W Li, C Sun Atmospheric Research 314, 107783 , 2025 2025 Citations: 7
Impacts of bioenergy crop cultivation on regional climate, hydrology, and water quality in the US Northern high plains S Dangol, X Zhang, C Sun, K Liang, XZ Liang Water Resources Research 61 (2), e2024WR037782 , 2025 2025
Improved simulation of compound drought and heat extremes in eastern China through CWRF downscaling H Zhang, S Zhang, H Xu, G Zhang, Y Dai, XZ Liang Environmental Research Letters 19 (12), 124037 , 2024 2024 Citations: 2
A prototype early warning system for diarrhoeal disease to combat health threats of climate change in the asia-pacific region R Cruz Cano, H He, S Aryal, M Dhimal, DTA Thu, L Zhang, T Ma, ... Environmental Research Letters 19 (11), 114094 , 2024 2024 Citations: 3
CWRF downscaling with improved land surface initialization enhances spring–summer seasonal climate prediction skill in China H Zhang, XZ Liang, Y Dai, L Song, Q Li, F Wang, S Zhang Journal of Climate 37 (17), 4437-4459 , 2024 2024 Citations: 4
Comparative analysis of gravity wave characteristics in China and the United States using high vertical resolution radiosonde observations Q Chen, H Wu, H Long, XZ Liang Journal of Geophysical Research: Atmospheres 129 (14), e2023JD040492 , 2024 2024 Citations: 5
Improving diurnal precipitation forecasts through coherent coupling of cumulus and planetary boundary layer parameterizations H Mei, XZ Liang, M Zeng, Y Yang, C Sun, X Li Journal of Geophysical Research: Atmospheres 129 (11), e2023JD040295 , 2024 2024 Citations: 2
Enhancing summer extreme precipitation prediction in the Yangtze River Basin through CWRF downscaling and its skillful multi-physics ensemble approach Y Zhao, XZ Liang Climate Dynamics 62 (6), 5107-5128 , 2024 2024 Citations: 2
Remote effects of Tibetan Plateau spring land temperature on global subseasonal to seasonal precipitation prediction and comparison with effects of sea surface temperature: the … Y Xue, I Diallo, AA Boone, Y Zhang, X Zeng, WKM Lau, JD Neelin, T Yao, ... Climate Dynamics 62 (4), 2603-2628 , 2024 2024 Citations: 21
Understanding and improving Yangtze River Basin summer precipitation prediction using an optimal multi-Physics ensemble Y Zhao, F Qiao, XZ Liang, J Yu Frontiers of Earth Science 18 (1), 256-277 , 2024 2024 Citations: 3
DAWN: Dashboard for Agricultural Water Use and Nutrient Management—A Predictive Decision Support System to Improve Crop Production in a Changing Climate XZ Liang, D Gower, JA Kennedy, M Kenney, MC Maddox, M Gerst, ... Bulletin of the American Meteorological Society 105 (2), E432-E441 , 2024 2024 Citations: 9
Balancing Non‐CO 2 GHG Emissions and Soil Carbon Change in U.S. Rice Paddies: A Retrospective Meta‐Analysis and Agricultural Modeling Study J Zhang, H Tian, Y You, XZ Liang, Z Ouyang, N Pan, S Pan AGU Advances 5 (1), e2023AV001052 , 2024 2024 Citations: 8
Biomass yield potential on U.S. marginal land and its contribution to reach net-zero emission Y He, D Jaiswal, SP Long, XZ Liang, ML Matthews Global Change Biology-Bioenergy 16, e13128 , 2024 2024 Citations: 22
Net greenhouse gas balance in US croplands: How can soils be part of the climate solution? Y You, H Tian, S Pan, H Shi, C Lu, WD Batchelor, B Cheng, D Hui, ... Global Change Biology 30 (1), e17109 , 2024 2024 Citations: 19
Advancing the SWAT model to simulate perennial bioenergy crops: A case study on switchgrass growth S Dangol, X Zhang, XZ Liang, E Blanc-Betes Environmental Modelling & Software 170, 105834 , 2023 2023 Citations: 8
Simulating agroecosystem soil inorganic nitrogen dynamics under long-term management with an improved SWAT-C model K Liang, X Zhang, XZ Liang, VL Jin, G Birru, MR Schmer, GP Robertson, ... Science of the Total Environment 879, 162906 , 2023 2023 Citations: 24
MOST CITED SCHOLAR PUBLICATIONS
Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models RD Cess, GL Potter, JP Blanchet, GJ Boer, AD Del Genio, M Deque, ... Journal of Geophysical Research: Atmospheres (1984–2012) 95 (D10), 16601-16615 , 1990 1990 Citations: 1194
Interpretation of cloud-climate feedback as produced by 14 atmospheric general circulation models RD Cess, GL Potter, JP Blanchet, GJ Boer, SJ Ghan, JT Kiehl, H Le Treut, ... Science 245 (4917), 513-516 , 1989 1989 Citations: 766
Observed diurnal cycle climatology of planetary boundary layer height S Liu, XZ Liang Journal of Climate 23 (21), 5790-5809 , 2010 2010 Citations: 588
A thermal infrared radiation parameterization for atmospheric studies MD Chou, MJ Suarez, XZ Liang, MMH Yan, C Cote 2001 Citations: 443
Regional climate change projections for the Northeast USA K Hayhoe, C Wake, B Anderson, XZ Liang, E Maurer, J Zhu, J Bradbury, ... Mitigation and Adaptation Strategies for Global Change 13 (5-6), 425-436 , 2008 2008 Citations: 401
Associations between China monsoon rainfall and tropospheric jets XZ Liang, WC Wang Quarterly Journal of the Royal Meteorological Society 124 (552), 2597-2623 , 1998 1998 Citations: 341
Impact of atmospheric moisture storage on precipitation recycling F Dominguez, P Kumar, XZ Liang, M Ting Journal of climate 19 (8), 1513-1530 , 2006 2006 Citations: 340
Determining climate effects on US total agricultural productivity XZ Liang, Y Wu, RG Chambers, DL Schmoldt, W Gao, C Liu, YA Liu, ... Proceedings of the National Academy of Sciences 114 (12), E2285-E2292 , 2017 2017 Citations: 275
Interpretation of snow-climate feedback as produced by 17 general circulation models RD Cess, GL Potter, MH Zhang, JP Blanchet, S Chalita, R Colman, ... Science 253 (5022), 888-892 , 1991 1991 Citations: 258
Regional climate model simulation of summer precipitation diurnal cycle over the United States XZ Liang, L Li, A Dai, KE Kunkel Geophysical Research Letters 31 (24) , 2004 2004 Citations: 241
Regional climate model simulation of US precipitation during 1982-2002. Part I: Annual cycle XZ Liang, L Li, KE Kunkel, M Ting, JXL Wang Journal of Climate 17 (18), 3510-3529 , 2004 2004 Citations: 237
A preliminary synthesis of modeled climate change impacts on US regional ozone concentrations CP Weaver, XZ Liang, J Zhu, PJ Adams, P Amar, J Avise, M Caughey, ... Bulletin of the American Meteorological Society 90 (12), 1843-1863 , 2009 2009 Citations: 220
Climatic forcing of nitrogen oxides through changes in tropospheric ozone and methane; global 3D model studies JS Fuglestvedt, TK Berntsen, ISA Isaksen, H Mao, XZ Liang, WC Wang Atmospheric Environment 33 (6), 961-977 , 1999 1999 Citations: 210
Development of a regional climate model for US Midwest applications. Part I: Sensitivity to buffer zone treatment XZ Liang, KE Kunkel, AN Samel Journal of Climate 14 (23), 4363-4378 , 2001 2001 Citations: 198
Regional Climate–Weather Research and Forecasting model XZ Liang, M Xu, X Yuan, T Ling, HI Choi, F Zhang, L Chen, S Liu, S Su, ... Bull. Amer. Meteor. Soc 93, 1363-1387 , 2012 2012 Citations: 197
Regional climate model downscaling of the U.S. summer climate and future change XZ Liang, J Pan, J Zhu, KE Kunkel, JXL Wang, A Dai Journal of Geophysical Research: Atmospheres 111 (D10) , 2006 2006 Citations: 189
Regional climate models downscaling analysis of general circulation models present climate biases propagation into future change projections XZ Liang, KE Kunkel, GA Meehl, RG Jones, JXL Wang Geophysical research letters 35 (8) , 2008 2008 Citations: 186
Can CGCMs simulate the twentieth-century “warming hole” in the central United States? KE Kunkel, XZ Liang, J Zhu, Y Lin Journal of Climate 19 (17), 4137-4153 , 2006 2006 Citations: 180
A general method for validating statistical downscaling methods under future climate change M Vrac, ML Stein, K Hayhoe, XZ Liang Geophysical Research Letters 34 (18) , 2007 2007 Citations: 177
The Practitioner's Dilemma: How to Assess the Credibility of Downscaled Climate Projections JJ Barsugli, G Guentchev, RM Horton, A Wood, LO Mearns, XZ Liang, ... Eos, Transactions American Geophysical Union 94 (46), 424-425 , 2013 2013 Citations: 159