格网降水产品

下载网址：

CMORPH_blended: http://data.cma.cn/data/cdcdetail/dataCode/SEVP_CLI_CHN_MERGE_CMP_PRE_HOUR_GRID_0.10.html.

PERSIANN_CDR: https://climatedataguide.ucar.edu/climate-data/persiann-cdr-precipitation-estimation-remotely-sensed-information-using-artificial.

TMPA 3B42 V7: https://pmm.nasa.gov/data-access/downloads/trmm.

GSMAP_MVK: https://sharaku.eorc.jaxa.jp/GSMAP/index.htm.

MSWEP V1.1: http://www.gloh2o.org.

CN05.1: http://data.cma.cn/data/cdcdetail/dataCode/SEVP_CLI_CHN_PRE_DAY_GRID_0.25.html.

（中国气象站点降水数据：http://data.cma.cn/en/?r=data/detail&dataCode=A.0012.0001）

如果有长时间的观测站点数据，可以在日、月、年尺度对不同遥感降水产品进行验证与比较

点与点：气象站点与站点位置对应的遥感影像网格中心值（气象站点插值会带来误差）

Yang Y, Wu J, Bai L, Wang B. Reliability of Gridded Precipitation Products in the Yellow River Basin, China. Remote Sensing. 2020; 12(3):374.  https://doi.org/10.3390/rs12030374

 验证指标：

the Pearson’s correlation coefficient (CC), relative bias (RB), and relative error (RE) were used to assess consistency between the satellite products and station observations in this study. The formulae for these indicators are as follows:

         

 

RB > 0 implies that the satellite product has overestimated precipitation and RB < 0 means that it has underestimated precipitation.

Basically, the satellite data have less volatility 波动性 when there is a smaller RE value.