Evaluate before use – temporal performance differences of gridded precipitation products in complex terrain

Gridded precipitation data is of central importance for various geoscientific research applications and is often the only available resource to derive spatial and temporal rainfall quantities. Numerous studies exist that evaluate respective products using gauge measurements. However, many existing approaches ignore the impact of temporal changes in incorporated observation data, the location of the observations and the potential overlap of evaluation and dataset stations. Considering these issues, we quantitatively evaluated monthly precipitation values of frequently used precipitation raster datasets (GPCC Full Data Monthly Product Version 2018, GPCC Monitoring Product Version 6, CRU TS 4.03, GPCP Version 2.3, PERSIANN-CDR, TRMM 3B43, MERRA-2, MERRA-2 bias corrected, ERA5) in the peripheral Pamir mountains with a focus on the two periods 1980–1994 and 1998–2012 as they are characterized by considerable observation data changes. The coefficient of efficiency, a dimensionless hydroclimatic evaluation measure, showed that only three of the precipitation raster datasets (GPCC Full Data Monthly Product Version 2018, GPCC Monitoring Product Version 6, MERRA-2 bias corrected) are able to provide better surface precipitation values than the long-term station mean in this observation data poor region. Results of the gauge-based products also document a fourfold increase of errors during periods with low availability of station data compared to periods with higher observation data inputs. In conclusion, the study clearly illustrates that gridded precipitation products may be connected to major problems in peripheral mountain regions with limited measurement infrastructure as most datasets directly or indirectly depend on observation networks. Significant differences of errors related to incorporated observation data variations demonstrate the need for temporal and spatial evaluation approaches as a prerequisite for the scientific utilization of precipitation raster datasets.