Cross-validating precipitation datasets in the Indus River basin

Abstract

Abstract. Large uncertainty remains about the amount of precipitation falling in the Indus River basin, particularly in the more mountainous northern part. While rain gauge measurements are often considered as a reference, they provide information for specific, often sparse, locations (point observations) and are subject to underestimation, particularly in mountain areas. Satellite observations and reanalysis data can improve our knowledge but validating their results is often difficult. In this study, we offer a cross-validation of 20 gridded datasets based on rain gauge, satellite, and reanalysis data, including the most recent and less studied APHRODITE-2, MERRA2, and ERA5. This original approach to cross-validation alternatively uses each dataset as a reference and interprets the result according to their dependency on the reference. Most interestingly, we found that reanalyses represent the daily variability of precipitation as well as any observational datasets, particularly in winter. Therefore, we suggest that reanalyses offer better estimates than non-corrected rain-gauge-based datasets where underestimation is problematic. Specifically, ERA5 is the reanalysis that offers estimates of precipitation closest to observations, in terms of amounts, seasonality, and variability, from daily to multi-annual scale. By contrast, satellite observations bring limited improvement at the basin scale. For the rain-gauge-based datasets, APHRODITE has the finest temporal representation of the precipitation variability, yet it importantly underestimates the actual amount. GPCC products are the only datasets that include a correction factor of the rain gauge measurements, but this factor likely remains too small. These findings highlight the need for a systematic characterisation of the underestimation of rain gauge measurements.

Independent validation of downscaled climate estimates from a coastal Alaska watershed using local historical weather journals

“…With an ever-growing need to compare the changes in the earth’s climate from historical times to present-day, validation of climate models with empirical data will continue to be an essential aspect of environmental research. Historical weather measurements collected from remote locations have the potential to underestimate actual conditions ( Baudouin, Herzog & Petrie, 2020 ) and be of questionable quality. To our knowledge, Hasselborg’s Mole River data set did not include a second observer or provide any methodological accounting.…”

Aerosol Trends during the Dusty Season over Iran

“…This data has also been applied in recent research [35][36][37][38]. Morerever, recent studies have evaluated and cross-checked the meteorological parameters from ERA5 data using different observation data [38][39][40][41] and high agreement has been reported. Moreover, ERA5 data assimilated ground base data from the developed countries in the Middle East region (https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5 (accessed on 8 March 2021)).…”

Synoptic processes of winter precipitation in the Upper Indus Basin

“…The Upper Indus River Basin (UIB) is a mountainous region that differs from the rest of the Indian subcontinent for the large amount of precipitation it receives outside of the summer monsoon season (56% or 505mm between October and May for ERA5 on the period 1979 and 2018, Baudouin et al, 2020b). Much of this precipitation falls as snow at altitude during the coldest part of the season (Hewitt, 2011;Dahri et al, 2018;Baudouin et al, 2020b).…”

“…The Upper Indus River Basin (UIB) is a mountainous region that differs from the rest of the Indian subcontinent for the large amount of precipitation it receives outside of the summer monsoon season (56% or 505mm between October and May for ERA5 on the period 1979 and 2018, Baudouin et al, 2020b). Much of this precipitation falls as snow at altitude during the coldest part of the season (Hewitt, 2011;Dahri et al, 2018;Baudouin et al, 2020b). The precipitation and the snowmelt later in the season are key for mitigating the seasonal drought that occurs for most of South Asia before the arrival of the summer monsoon (Singh et al, 2011;Dimri et al, 2015;Rana et al, 2015).…”