Land surface temperature(LST)is the key variable in land-atmosphere interaction,having an important impact on weather and climate forecasting.However,achieving consistent analysis of LST and the atmosphere in assimila...Land surface temperature(LST)is the key variable in land-atmosphere interaction,having an important impact on weather and climate forecasting.However,achieving consistent analysis of LST and the atmosphere in assimilation is quite challenging.This is because there is limited knowledge about the cross-component background error covariance(BEC)between LST and atmospheric state variables.This study aims to clarify whether there is a relationship between the error of LST and atmospheric variables,and whether this relationship varies spatially and temporally.To this end,the BEC coupled with atmospheric variables and LST was constructed(LST-BEC),and its characteristics were analyzed based on the 2023 mei-yu season.The general characteristics of LST-BEC show that the LST is mainly correlated with the atmospheric temperature and the correlation decreases gradually with a rise in atmospheric height,and the error standard deviation of the LST is noticeably larger than that of the low-level atmospheric temperature.The spatiotemporal characteristics of LST-BEC on the heavy-rain day and light-rain day show that the error correlation and error standard deviation of LST and low-level atmospheric temperature and humidity are closely related to the weather background,and also have obvious diurnal variations.These results provide valuable information for strongly coupled land-atmosphere assimilation.展开更多
依托国家气象信息中心研发的省级多源融合实况分析系统,以逐小时和逐分钟的多要素站点数据为观测场,以ECWMF C1D预报数据为背景场,利用时空多尺度分析系统(The Space and Time Multiscale Analysis System,STMAS)开展产品生成试验。在...依托国家气象信息中心研发的省级多源融合实况分析系统,以逐小时和逐分钟的多要素站点数据为观测场,以ECWMF C1D预报数据为背景场,利用时空多尺度分析系统(The Space and Time Multiscale Analysis System,STMAS)开展产品生成试验。在对观测场进行质量控制和对背景场进行偏差订正的基础上,通过网格层数阈值参数和地面网格影响半径优化实验,构建针对温湿风多源资料的有效融合分析模型,实现内蒙古自治区逐小时、逐10 min的1 km分辨率的温湿风融合实况分析产品的生成,最后对2023年10—11月的融合实况分析产品与EC背景场和观测数据进行对比,评估融合实况分析产品的质量。结果表明:与EC背景场相比,各要素的融合实况分析产品与观测值具有更小的偏差、更小的均方根误差、更大的相关系数值;实况分析产品的评估指标在时间序列上也平稳低于EC背景场,在空间刻画上,与地面观测结果更为接近,能够体现出更多的小尺度信息;实况分析产品与赛区站点观测值非常接近,评估指标表现较好。内蒙古自治区1 km温湿风实况分析产品具有较高质量,能够满足实时业务需要,为第十四届全国冬季运动会观测、预报和服务提供数据支撑。展开更多
基金sponsored by the National Natural Science Foundation of China[grant number U2442218]。
文摘Land surface temperature(LST)is the key variable in land-atmosphere interaction,having an important impact on weather and climate forecasting.However,achieving consistent analysis of LST and the atmosphere in assimilation is quite challenging.This is because there is limited knowledge about the cross-component background error covariance(BEC)between LST and atmospheric state variables.This study aims to clarify whether there is a relationship between the error of LST and atmospheric variables,and whether this relationship varies spatially and temporally.To this end,the BEC coupled with atmospheric variables and LST was constructed(LST-BEC),and its characteristics were analyzed based on the 2023 mei-yu season.The general characteristics of LST-BEC show that the LST is mainly correlated with the atmospheric temperature and the correlation decreases gradually with a rise in atmospheric height,and the error standard deviation of the LST is noticeably larger than that of the low-level atmospheric temperature.The spatiotemporal characteristics of LST-BEC on the heavy-rain day and light-rain day show that the error correlation and error standard deviation of LST and low-level atmospheric temperature and humidity are closely related to the weather background,and also have obvious diurnal variations.These results provide valuable information for strongly coupled land-atmosphere assimilation.
文摘依托国家气象信息中心研发的省级多源融合实况分析系统,以逐小时和逐分钟的多要素站点数据为观测场,以ECWMF C1D预报数据为背景场,利用时空多尺度分析系统(The Space and Time Multiscale Analysis System,STMAS)开展产品生成试验。在对观测场进行质量控制和对背景场进行偏差订正的基础上,通过网格层数阈值参数和地面网格影响半径优化实验,构建针对温湿风多源资料的有效融合分析模型,实现内蒙古自治区逐小时、逐10 min的1 km分辨率的温湿风融合实况分析产品的生成,最后对2023年10—11月的融合实况分析产品与EC背景场和观测数据进行对比,评估融合实况分析产品的质量。结果表明:与EC背景场相比,各要素的融合实况分析产品与观测值具有更小的偏差、更小的均方根误差、更大的相关系数值;实况分析产品的评估指标在时间序列上也平稳低于EC背景场,在空间刻画上,与地面观测结果更为接近,能够体现出更多的小尺度信息;实况分析产品与赛区站点观测值非常接近,评估指标表现较好。内蒙古自治区1 km温湿风实况分析产品具有较高质量,能够满足实时业务需要,为第十四届全国冬季运动会观测、预报和服务提供数据支撑。
