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Spatio-temporal prediction of meteorological drought and analysis of influencing factors in Southwest China based on a CNN-LSTM model
TANG Ning, LI Jinne, SHI Yan, LI Jue, BAI Tao
Journal of Arid Meteorology, 2026 44 (3): 357
Southwest China is characterized by complex topography, diverse climatic conditions, and frequent drought events. To improve the representation of spatiotemporal characteristics in drought prediction, this paper developed a coupled Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model using precipitation, air temperature, total solar radiation, wind speed, and other factors as inputs. The model was employed to analyze the spatiotemporal evolution characteristics and driving mechanisms of meteorological drought in Southwest China and project drought conditions in 2030. The results indicate that the CNN-LSTM model effectively captures the spatiotemporal variability of drought an. . .
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Analysis of characteristics of regional drought variability in Shandong
ZOU Jin, TANG Zidong, QIU Can, KONG Xiangning, FENG Xiaofan
Journal of Arid Meteorology, 2026 44 (3): 368
Studying the variation characteristics of regional drought in Shandong Province is of great significance for drought disaster prevention and mitigation. Using daily temperature and precipitation data from 123 national meteorological stations in Shandong Province, this study identified regional meteorological drought processes from 1961 to 2024 based on the MCI (Meteorological Drought Composite Index) and the monitoring and assessment method of regional drought process, and analyzed the spatio-temporal evolution features of these drought processes and their responses to climate warming. The results show that Shandong experienced 1-2 regional meteorological drought events annually with distinc. . .
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Analysis of solar radiation variation characteristics in arid region of China
ZHAO long, LIU Yuwei, JIANG Xue, ZHOU Qiang, SHEN Weicheng, REN Yulong
Journal of Arid Meteorology, 2026 44 (3): 386
Solar energy development is the key way for China to achieve dual carbon goals. China’s arid regions cover a vast territory and abound in solar energy resources. However, limited by scarce ground observation sites and insufficient in-situ data, the spatiotemporal variations and influencing factors of solar radiation in this region under climate warming since 1980 have not been fully clarified, which restricts the site selection of photovoltaic power stations and the development and utilization of regional solar energy resources to a certain extent. Therefore, based on solar radiation observations from 25 national ground radiation stations, cloud cover data from 218 national benchmark climate. . .
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Application of machine learning in the ensemble projection of regional extreme climate indices over China
LIU Mingming, XU Ying
Journal of Arid Meteorology, 2026 44 (3): 411
Under the background of climate warming, changes in extreme climate events have received increasing attention. In this study, three machine learning models, namely Random Forest, Extremely Randomized Trees, and Ridge Regression, were used to evaluate their capability in simulating extreme climate indices over China, including the warm day index (TX90p), cold night index (TN10p), maximum 1-day precipitation (RX1day), and maximum consecutive 5-day precipitation (RX5day). Their performances were compared with that of the traditional globally bias-corrected multi-model ensemble method to determine the optimal model schemes. Furthermore, the spatial distributions and temporal trends of the select. . .
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Spatio-temporal characteristics of compound high temperature and drought events during critical rice growth periods in Sichuan Province based on the Copula function
PU Changlin, CHEN Dongdong, ZHANG Yufang, WANG Xiaodong, ZOU Yujia
Journal of Arid Meteorology, 2026 44 (2): 188
Under global warming, compound events of heat and drought pose a far greater threat to agricultural production than individual extremes. Based on daily precipitation and maximum temperature data from 92 meteorological stations in Sichuan Province druing 1981-2022, this study employed the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Temperature Index (STI) to characterize drought intensity and high temperature intensity， respectively. A joint probability distribution model of heat and drought intensities was constructed using the Copula function, and the spatiotemporal characteristics of compound heat-drought events during the critical rice growth periods (b. . .
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Identification and evolution characteristics of sub-seasonal drought-flood abrupt alternation events in Ningxia
GAO Na, WANG Suyan, LI Xin, GAO Ruina, WANG Dai
Journal of Arid Meteorology, 2026 44 (2): 199
Against the backdrop of global warming and intensifying human activities, extreme drought and flood events have shown a trend of increasing frequency and intensity. However, research on sub-seasonal drought-flood abrupt alternation events remains relatively limited. In light of this, this study utilizes daily precipitation data from 20 national meteorological observation stations in Ningxia from 1961 to 2023 and employs the multi-threshold run theory to propose a method for sub-seasonal drought-flood abrupt alternation events, which is subsequently validated. Based on this method, drought-flood abrupt alternation events in Ningxia from April to October during 1961-2023 are statistically anal. . .
