【資源0715】1961-2022年中國(guó)逐日降水?dāng)?shù)據(jù)集(0.1°/0.25°/0.5°)
資源介紹
中國(guó)逐日降水?dāng)?shù)據(jù)集(1961-2022,0.1°/0.25°/0.5°)


【數(shù)據(jù)集摘要】
CHM_PRE數(shù)據(jù)集基于中國(guó)境內(nèi)及周邊1961至今共2839個(gè)站點(diǎn)的日降水觀測(cè),在傳統(tǒng)的“降水背景場(chǎng) + 降水比值場(chǎng)”的數(shù)據(jù)集構(gòu)建思路上,嘗試應(yīng)用月值降水約束和地形特征校正,并依據(jù)中國(guó)范圍內(nèi)約4萬個(gè)高密度站點(diǎn)2015–2019年的日降水量插值后數(shù)據(jù)進(jìn)行精度評(píng)價(jià)。經(jīng)評(píng)估認(rèn)為,CHM_PRE可以較好的表征降水的空間變異性,其日值時(shí)間序列與高密度站點(diǎn)日值降水觀測(cè)結(jié)果之間的相關(guān)系數(shù)中位數(shù)為0.78,均方根誤差中位數(shù)為8.8 mm/d,KGE值中位數(shù)為0.69,與目前常用的降水?dāng)?shù)據(jù)集(CGDPA、CN05.1、CMA V2.0)有很好的一致性。數(shù)據(jù)集的時(shí)間范圍為1961年至今,空間分辨率為0.1°、0.25°和0.5°,經(jīng)緯度范圍為18°N–54°N, 72°E–136°E。
【數(shù)據(jù)文件命名方式和使用方法】
文件命名:日降水格點(diǎn)數(shù)據(jù)以NetCDF(nc)文件格式存儲(chǔ)?文件屬性:· Variable = daily precipitation (pre) · Variable = number of stations in each grid every year (station_number) · Date format = NetCDF · Temporal Range = 1961-01-01 to present · Spatial extent = 18°N–54°N, 72°E–136°E · Units = mm/day · Missing value = -99.9
【引用方式】數(shù)據(jù)引用必讀
【數(shù)據(jù)的引用】繆馳遠(yuǎn), 韓靜雅, 茍嬌嬌. (2023). 中國(guó)逐日降水?dāng)?shù)據(jù)集(1961-2022,0.1°/0.25°/0.5°). 國(guó)家青藏高原科學(xué)數(shù)據(jù)中心.Miao, C., Han, J., Gou, J. (2023). A daily gridded precipitation dataset based on gauge observations across mainland of China (1961-2022). National Tibetan Plateau Data Center.?https://doi.org/10.11888/Atmos.tpdc.300523.?https://cstr.cn/18406.11.Atmos.tpdc.300523.
【文章的引用】1、Han, J.Y., Miao, C.Y., Gou, J.J., Zheng, H.Y., Zhang, Q., & Guo, X.Y. (2022). A new daily gridded precipitation dataset based on gauge observations across mainland of China. Earth System Science Data Discussions, 1-33.?2、Miao, C.Y., Gou, J.J., Fu, B.J., Tang, Q.H., Duan, Q.Y., Chen, Z.S., Lei, H.M., Chen, J., Guo, J.L., Borthwick, A.G.L., Ding, W.F., Duan, X.W., Li, Y.G., Kong, D.X., Guo, X.Y., & Wu, J.W. (2022). High-quality reconstruction of China’s natural streamflow. Science Bulletin, 67(5), 547-556.?3、Gou, J.J., Miao, C.Y., Samaniego, L., Xiao, M., Wu, J.W., & Guo, X.Y. (2021). CNRD v1.0: a high-quality natural runoff dataset for hydrological and climate studies in China. Bulletin of the American Meteorological Society, 102(5), E929-E947.?
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