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基于区域数值模式的中国北方干旱预测系统及其检验应用研究OA

A drought prediction system and its application in northern China based on improved RegCM5.0

中文摘要英文摘要

中国北方受陡峭地形、复杂环流和强烈陆-气相互作用影响,干旱多发.近年来在全球持续变暖的背景下,该区域极端干旱事件增多,威胁着社会经济的持续发展;因此亟需提升区域数值模式对降水、气温等干旱因子的模拟性能,以提高极端干旱事件的预测水平.为此,本文开展区域气候模式 RegCM5.0的本地化改进研究,研制区域数值模式干旱预测系统;改进方案包含更新地表类型数据、导热率参数化模型修改、积云对流参数化方案优选.结果表明:通过改进,北方降水模拟误差平均减小了50%,2 m 气温误差平均减小了 1℃,降水相关系数由 0.61提高到 0.72(α=0.001),气温相关系数由 0.83提高到 0.88(α=0.001).干旱预测系统输出的标准化降水指数(Standardized Precipitation Index,SPI)和标准化降水蒸散指数(Standardized Precipitation Evapo-transpiration Index,SPEI)等干旱指数与基于观测资料计算的干旱指数的相关系数均超过 0.50(α=0.05);个例检验表明,该预测系统能准确预测出2020年夏季北方"旱涝急转"、2024年极端高温干旱事件.

Northern China is characterized by steep terrain,complex circulations and strong land-atmosphere interaction,which make it highly susceptible to frequent droughts.In recent years,extreme drought events have increased in this region under the background of global warming,posing a threat to socioeconomic sustainable development.To promote the prediction of extreme drought events,it is imperative to improve the performance of regional numerical models for the simulation of drought factors such as precipitation and temperature.Therefore,RegCM5.0 is localized and improved in this study to develop a drought prediction system.The improvements include surface type data update,thermal conductivity parameterization modification and cumulus convection scheme optimization.Results show that precipitation bias is reduced by 50%and 2 m air temperature bias is reduced by 1℃.The correlation coefficients of precipitation and 2 m air temperature with observations increase from 0.61 to 0.72(α=0.001)and from 0.83 to 0.88(α=0.001),respectively.The correlation coefficients of simulated drought indexes such as SPI(Standardized Precipitation Index)and SPEI(Standardized Precipitation Evapotranspiration Index)with those from observations can reach above 0.50(α=0.05).A case study shows that the prediction system can accurately forecast the extreme drought event in the summer of 2020 and those extreme heat and drought events in 2024.

任余龙;张强;岳平;张铁军;巩崇水;李忆平;颜鹏程;柳媛普;刘洋

中国气象局兰州干旱气象研究所,兰州,730020||兰州区域气候中心,兰州,730020||甘肃省信息保障中心,兰州,730020中国气象局兰州干旱气象研究所,兰州,730020||兰州区域气候中心,兰州,730020||甘肃省信息保障中心,兰州,730020中国气象局兰州干旱气象研究所,兰州,730020||兰州区域气候中心,兰州,730020||甘肃省信息保障中心,兰州,730020中国气象局兰州干旱气象研究所,兰州,730020||兰州区域气候中心,兰州,730020||甘肃省信息保障中心,兰州,730020中国气象局兰州干旱气象研究所,兰州,730020||兰州区域气候中心,兰州,730020||甘肃省信息保障中心,兰州,730020中国气象局兰州干旱气象研究所,兰州,730020||兰州区域气候中心,兰州,730020||甘肃省信息保障中心,兰州,730020中国气象局兰州干旱气象研究所,兰州,730020||兰州区域气候中心,兰州,730020||甘肃省信息保障中心,兰州,730020中国气象局兰州干旱气象研究所,兰州,730020||兰州区域气候中心,兰州,730020||甘肃省信息保障中心,兰州,730020中国气象局兰州干旱气象研究所,兰州,730020||兰州区域气候中心,兰州,730020||甘肃省信息保障中心,兰州,730020

天文与地球科学

中国北方区域数值模式陆面参数优化极端干旱事件预测

Northern ChinaRegional numerical modelOptimization of land surface parametersExtreme drought events prediction

《气象学报》 2026 (4)

749-763,15

国家自然科学基金重点项目(42230611)、甘肃省自然科学基金(24JRRA722)、中国气象局创新驱动发展重点项目(CXFZ2025J070).

10.11676/qxxb2026.20250125

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