Y. Zhang, Xiao-Gang Zheng, Xiufen Li, Jiaxin Lyu, Lanlin Zhao
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At the monthly scale, GPM-IMERG performed better during the wet season (April-September) (RBias=7.41%) than during the dry season (RBias=13.65%). (2) GPM-IMERG performed well in terms of precipitation estimation in Southwest China, Central China, East China and South China, followed by Northeast China and North China, but it performed poorly in Northwest China and Tibet. (3) The climate zone, followed by elevation, played a leading role in the GPM-IMERG accuracy in China, and the main sources of GPM-IMERG deviation in arid and semiarid regions were missed precipitation and false precipitation. However, the influences of missed precipitation and false precipitation gradually increased with increasing elevation. 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引用次数: 0
摘要
新一代多卫星降水算法GPM-IMERG (Integrated multi-satellite Retrievals for Global precipitation Measurement)第6版提供了高分辨率和大空间范围,可用于弥补地面观测的不足。本研究旨在评价2014-2020年GPM-IMERG V06终程产品(GPM-IMERG)在中国不同气候和地形区域的降水探测能力。研究表明:(1)GPM-IMERG能较好地捕捉中国降水的时空分布特征。在年尺度上,GPM-IMERG表现良好,相关系数(R)为0.95,相对偏倚比(RBias)为15.38% ~ 23.46%。在季节尺度上,GPM-IMERG在夏季表现最好。在月尺度上,雨季(4 - 9月)GPM-IMERG表现较好(RBias=7.41%),旱季的RBias=13.65%;(2) GPM-IMERG在西南、华中、华东、华南、东北、华北地区表现较好,在西北、西藏地区表现较差;(3)气候区对中国GPM-IMERG精度的影响最大,其次是海拔,干旱半干旱区GPM-IMERG偏差的主要来源是错过降水和假降水。而随海拔升高,误降水和假降水的影响逐渐增大。尽管GPM-IMERG与地面降水估计值之间存在明显差异,但研究结果强调了GPM-IMERG作为监测世界许多地区缺乏的高分辨率降水信息的宝贵资源的潜力。
Evaluation of the GPM-IMERG V06 Final Run products for monthly/annual precipitation under the complex climatic and topographic conditions of China
The new-generation multi-satellite precipitation algorithm, namely, Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM-IMERG) version 6, provides a high resolution and large spatial extent and can be used to offset the lack of surface observations. This study aimed to evaluate the precipitation detection capability of GPM-IMERG V06 Final Run products (GPM-IMERG) in different climatic and topographical regions of China for the 2014-2020 period. This study showed that (1) GPM-IMERG could capture the spatial and temporal precipitation distributions in China. At the annual scale, GPM-IMERG performed well, with a correlation coefficient (R) >0.95 and a relative bias ratio (RBias) between 15.38% and 23.46%. At the seasonal scale, GPM-IMERG performed best in summer. At the monthly scale, GPM-IMERG performed better during the wet season (April-September) (RBias=7.41%) than during the dry season (RBias=13.65%). (2) GPM-IMERG performed well in terms of precipitation estimation in Southwest China, Central China, East China and South China, followed by Northeast China and North China, but it performed poorly in Northwest China and Tibet. (3) The climate zone, followed by elevation, played a leading role in the GPM-IMERG accuracy in China, and the main sources of GPM-IMERG deviation in arid and semiarid regions were missed precipitation and false precipitation. However, the influences of missed precipitation and false precipitation gradually increased with increasing elevation. Despite the obvious differences between the GPM-IMERG and surface precipitation estimates, the study results highlight the potential of GPM-IMERG as a valuable resource for monitoring high-resolution precipitation information that is lacking in many parts of the world.
期刊介绍:
The Journal of Applied Meteorology and Climatology (JAMC) (ISSN: 1558-8424; eISSN: 1558-8432) publishes applied research on meteorology and climatology. Examples of meteorological research include topics such as weather modification, satellite meteorology, radar meteorology, boundary layer processes, physical meteorology, air pollution meteorology (including dispersion and chemical processes), agricultural and forest meteorology, mountain meteorology, and applied meteorological numerical models. Examples of climatological research include the use of climate information in impact assessments, dynamical and statistical downscaling, seasonal climate forecast applications and verification, climate risk and vulnerability, development of climate monitoring tools, and urban and local climates.