Spatial performance of multiple reanalysis precipitation datasets on the southern slope of central Himalaya

The performance of gridded precipitation products is especially important over mountainous regions because of the lack of observations. This study provides a detailed evaluation of the spatial precipitation patterns presented by the ERA-Interim, ERA5, ERA5-Land, and refined HAR datasets with spatial resolutions from coarse to fine (0.7 degrees, 0.25 degrees, 0.1 degrees, and 0.1 degrees, respectively) over the southern slope of central Himalaya, Nepal. The major findings are as follows: (1) The high-resolution ERA5-Land and ERA5 datasets well present the observed spatial pattern of precipitation but with a generally overestimated amount; the refined HAR dataset also presents many fine-scale details, while the coarse resolution ERA-Interim dataset tends to exhibit a too gentle spatial characteristic in mountainous Nepal. (2) The four datasets well reproduce the seasonal precipitation variation (R > 0.90) over the country; however, their performance varies spatially across the western, central, and eastern regions. The spatial resolution is also important in representing the terrain blocking of water vapor from the Bay of Bengal, which is transported from east to west in Nepal. (3) The high-resolution datasets can reproduce the elevation dependency as revealed by the observed dataset, while the coarse-resolution cannot capture the elevation dependency in the high-elevation regions. Moreover, all four datasets show very similar performance in low-elevation plane areas, however, higher resolution simulations (ERA5, ERA5-Land, and HAR) better reflect blocking effect of orographic precipitation and outperform ERA-Interim in high-elevation areas where the terrain is very complex and the slope is very steep.

Automated summary

This study evaluates different resolution precipitation datasets over the southern slope of central Himalaya in Nepal, finding that high-resolution datasets better present observed spatial patterns but generally overestimate precipitation, and can better reproduce seasonal precipitation variations. Coarse resolution datasets perform poorly in mountainous regions.