Intercomparison of gridded precipitation datasets for prospective hydrological applications in Sri Lanka

Abstract

The aim of this study was to assess the application of gridded precipitation datasets for applications in Sri Lanka and to identify suitable products that can be used for hydrological applications in data sparse regions. Here, nine global datasets were considered for this study, and after initial screening, four datasets, such as Integrated Multi-Satellite Retrievals for GPM (IMERG) early run calibrated, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), European Center for Medium range Weather Forecasting (ECMWF)-ReAnalysis (ERA5) and Indian Monsoon Data Assimilation and Reanalysis (IMDAA), were selected for detailed comparison. These data products were analysed at monthly, seasonal and annual time scale for whole Sri Lanka and also for three distinguished climate zones (wet, intermediate and dry) for the period 2001-2015. The datasets were further evaluated based on their ability to capture the extreme events, based on recent designated dry year and wet year. All four datasets represent the annual and monthly climatology of Sri Lanka well; however, discrepancies are seen at seasonal scale.CHIRPS had the best performance in the wet zone and ERA5 in dry and intermediate zones. Although all datasets distinctly identified the wet year and dry year with respect to the normal average, the interannual variability was explicitly identified by CHIRPS and ERA5. Therefore, for replicating the national and zonal climatology, both ERA5 (dry and intermediate zones) and CHIRPS (wet zone) are suitable. With the perspective of hydrological applications, both datasets can be used in development of hydrological models for applications such as flood forecasting, reservoir management and climate change impact assessment as an alternative to observed rainfall data in data scarce regions.

El Niño‐Southern Oscillation Modulation of Springtime Diurnal Rainfall Over a Tropical Indian Ocean Island

“…The spatial and temporal resolution of IMERG.v6 is 0.1° × 0.1° and 30 min, respectively. The capability of both TMPA.v7 and IMERG.v6 have been validated by earlier studies against station observations and shown reasonable correlations for the rainfall variations over SL (Bandara et al, 2021;Huang et al, 2023;Perera et al, 2022;Yoshimoto & Amarnath, 2017). Due to the end of TMPA.v7 in 2019 and the availability of IMERG.v6 data starting in 2001, this study focused on the period from 2001 to 2019 for all analyses.…”

The Influence of Weather Patterns and the Madden‐Julian Oscillation on Extreme Precipitation Over Sri Lanka

“…Bandara et al. (2022) compared nine gridded precipitation datasets from reanalysis and remote sensing products for meteorological and hydrological applications in Sri Lanka. They inferred that ERA5 had the best performance since it replicated the observed precipitation climatology of Sri Lanka very well.…”

“…Thus, the precipitation threshold for an extreme precipitation event is 15.6 mm day −1 , and extreme precipitation events occurred on 694 of 13,880 days in the analysis period. Bandara et al (2022) compared nine gridded precipitation datasets from reanalysis and remote sensing products for meteorological and hydrological applications in Sri Lanka. They inferred that ERA5 had the best performance since it replicated the observed precipitation climatology of Sri Lanka very well.…”