Article citationsMore>>

Nguyen, P., Shearer, E.J., Tran, H., Ombadi, M., Hayatbini, N., Palacios, T., et al. (2019) The CHRS Data Portal, an Easily Accessible Public Repository for PERSIANN Global Satellite Precipitation Data. Scientific Data, 6, Article No. 180296.
https://doi.org/10.1038/sdata.2018.296

has been cited by the following article:

• TITLE: A Comparison between the Rainfall Observation and Global Rainfall Data Including Satellite and Reanalysis

  AUTHORS: Kahlan Al Toubi

  KEYWORDS: Reanalysis Data, Monthly and Daily Data, Root Mean Square Error, Mean Bias Error, Correlation Coefficient

  JOURNAL NAME: Atmospheric and Climate Sciences, Vol.16 No.1, January 26, 2026

  ABSTRACT: The study focuses on the accuracy of reanalysis and satellite rainfall data by comparing them with ground rain gauges. Using different statistical techniques, it is shown that the global data struggles to estimate rainfall at both daily and monthly intervals. The study divided the analysis into annual and seasonal scales, applied to daily and monthly data. The results show that the global datasets vary with time and space, which means that the performance of all datasets is unstable. Also, the study shows that most of the datasets underestimated the rainfall in all time scales except IMERG 0.2 & 0.5, which overestimated the rainfall. Furthermore, the correlation coefficient shows that the datasets struggled with the local convection during the summertime. However, they show a good performance during springtime, which is associated with torrential and widespread rainfall. The satellite data overestimated the rainfall by 4 mm to 20 mm at the best performing locations, where the reanalysis underestimated the rainfall by 0.2 mm to 4 mm in general, which is applied to all reanalysis datasets.