Investigation of the Relation between South and Southwest Iran\'s Heavy Rainfall with Atmospheric Rivers (ARs). by Nesa sepandar, kamal omidvar

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The Study of the Impact of Temperature and Wind In the Southern Low Pressure Systems by mahboobeh pouratashi, mohammad moradi, ebrahim fattahi

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Monitoring Agricultural Land Changes in Peri-Urban Oran, Algeria: A Mixed Methods Analysis by Rabia Samah Choukri, Tarik Ghodbani, Muhammad Salem

“…In the peri-urban areas of Oran, Algeria, the rapid conversion of agricultural land, particularly along the main highways in the south and southwest regions, underscores the urgent need for focused research. …”
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Spatial Characteristics and Connectivity of Urban Floods in Eastern China: Insights From a Newly Established Data Set During 2010–2020 by Zhenghui Lu, Linhao Zhong, Yang Yang, Xinlei Han, Xiaoling Jiang, Zitong Shi, Dabang Jiang

“…Based on this data set, our analysis identified four high‐frequency urban flood centers in South, Southeast, Southwest, and North China. Distinct regional differences are revealed for regions from south to north, with monthly peaks shifting from May to August and precipitation thresholds decreasing from high to low. …”
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Climatic Background and Prediction of Boreal Winter PM2.5 Concentrations in Hubei Province, China by Yuanyue Huang, Zijun Tang, Zhengxuan Yuan, Qianqian Zhang

“…Conversely, the South Atlantic–Southwest Indian Ocean SST mode (SAIO) and the Ross Sea sea-ice mode (ROSIC) contribute to more stable local atmospheric conditions, which reduce pollutant dispersion and increase PM2.5 accumulation, thus exhibiting a positive correlation with DJF-HBPMC. (3) A multiple linear regression (MLR) model, using selected seasonal SST and SIC indices, effectively predicts DJF-HBPMC, showing high correlation coefficients (CORR) and anomaly sign consistency rates (AS) compared to real-time values. (4) In daily HBPMC forecasting, both the Reversed Unrestricted Mixed-Frequency Data Sampling (RU-MIDAS) and Reversed Restricted-MIDAS (RR-MIDAS) models exhibit superior skill using only monthly precipitation, and the RR-MIDAS offers the best balance in prediction accuracy and trend consistency when incorporating monthly precipitation along with monthly SST and SIC indices.…”
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