Abstract
Precipitation is the most important variable in the climate system and the dominant driver of land surface hydrologic conditions. Rain gauge measurement provides precipitation estimates on the ground surface; however, these measurements are sparse, especially in the high-elevation areas of Nepal. Reanalysis datasets are the potential alternative for precipitation measurement, although it must be evaluated and validated before use. This study evaluates the performance of second-generation Modern-ERA Retrospective analysis for Research and Applications (MERRA-2) datasets with the 141-gauge observations from Nepal between 2000 and 2018 on monthly, seasonal, and annual timescales. Different statistical measures based on the Correlation Coefficient (R), Mean Bias (MB), Root-Mean-Square Error (RMSE), and Nash–Sutcliffe efficiency (NSE) were adopted to determine the performance of both MERRA-2 datasets. The results revealed that gauge calibrated (MERRA-C) underestimated, whereas model-only (MERRA-NC) overestimated the observed seasonal cycle of precipitation. However, both datasets were able to reproduce seasonal precipitation cycle with a high correlation (R ≥ 0.95), as revealed by observation. MERRA-C datasets showed a more consistent spatial performance (higher R-value) to the observed datasets than MERRA-NC, while MERRA-NC is more reasonable to estimate precipitation amount (lower MB) across the country. Both MERRA-2 datasets performed better in winter, post-monsoon, and pre-monsoon than in summer monsoon. Moreover, MERRA-NC overestimated the observed precipitation in mid and high-elevation areas, whereas MERRA-C severely underestimated at most of the stations throughout all seasons. Among both datasets, MERRA-C was only able to reproduce the observed elevation dependency pattern. Furthermore, uncertainties in MERRA-2 precipitation products mentioned above are still worthy of attention by data developers and users.
Highlights
Precipitation is an important variable in atmospheric circulation for weather and climatic studies and is the dominant driver of land surface hydrologic conditions [1,2,3,4]
Overestimated, while Modern-ERA Retrospective analysis for Research and Applications (MERRA)-C underestimated the observed precipitation throughout the study period
The observed data revealed that precipitation peaks during the monsoon (June-September) season
Summary
Precipitation is an important variable in atmospheric circulation for weather and climatic studies and is the dominant driver of land surface hydrologic conditions [1,2,3,4]. Precipitation is a complex variable to predict and estimate as it varies highly in space and time due to large-scale atmospheric circulation patterns and the geographic and topographic factors of the region [2,5]. The spatial extent and temporal resolution of rain gauge-based precipitation measurements in the country are inadequate to support the creation of regional precipitation datasets. This is mainly true for high-elevation areas due to the complex geography and remote location [9,14]. The discontinuity and missing values in meteorological data records even worsened the results and interpretation of precipitation [15]
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