Evaluation and Correction of GPM IMERG Precipitation Products over the Capital Circle in Northeast China at Multiple Spatiotemporal Scales

Abstract EN

Accurate remote-sensed precipitation data are crucial to the effective monitoring and analysis of floods and climate change.

The Global Precipitation Measurement (GPM) satellite product offers new options for the global study of precipitation.

This paper evaluates the applicability of GPM IMERG products at different time resolutions in comparison to ground-measured data.

Based on precipitation data from 107 meteorological stations in the Beijing-Tianjin-Hebei region, GPM products were analysed at three timescales: half-hourly (GPM-HH), daily (GPM-D), and monthly (GPM-M).

We use a cumulative distribution function (CDF) model to correct GPM-D and GPM-M products to analyse temporal and spatial distributions of precipitation.

We came to the following conclusions: (1) The GPM-M product is strongly correlated with ground station data.

Based on five evaluation indexes, NRMSE (Normalized Root Mean Square Error), NSE (Nash-Sutcliffe), FAR (False Alarm Ratio), UR (Underreporting Rate), and CSI (Critical Success Index), the monthly GPM products showed the best performance, better than GPM-HH products and GPM-D products.

(2) The performance of GPM products in summer and autumn was better than in winter and spring.

However, the GPM satellite’s precision in undulating terrain was poor, which could easily lead to serious errors.

(3) CDF models were successfully used to modify GPM-D and GPM-M products and improve their accuracy.

(4) The range of 0–100 mm precipitation could be corrected best, but the GPM-M products were underestimated.

Corrected GPM-M data in the range >100 mm were overestimated.

According to this analysis, the GPM IMERG Final Run products at daily and monthly timescales have good detection ability and can provide data support for long-time series analyses in the Beijing-Tianjin-Hebei region.