Evaluation of climate reanalysis and space-borne precipitation products over Bangladesh
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Cartwright, Nick
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Abstract
This study aims to quantify the spatial distribution of errors in two climate reanalysis (ERA5 and CFSR) and two satellite (TMPA-RT and TMPA-V7) precipitation products over Bangladesh. The datasets are assessed against ground-based rain gauge observations to capture the extreme rainfall accumulations at daily temporal scale over a 5-year period (January 2010–December 2014). The bias ratio scores indicate that CFSR and TMPA-RT seriously overestimate the rainfall values over much of the study area. Whilst TMPA-V7 performs better than the other precipitation products, all datasets lose their detection skills substantially for higher quantile thresholds (i.e. above 50th and 75th percentiles). With respect to rainfall detection metrics – probability of detection (POD) and volumetric hit index (VHI) – both ERA5 and CFSR show superior performance (in the range 0.9–1.0 for all the analysis grid boxes). All rainfall datasets are equally good in terms of false alarm ratio (FAR) and volumetric FAR (VFAR), even though the lowest values are associated with ERA5 for higher quantiles. All products demonstrate a decrease in skill to capture the amount of rainfall but show satisfactory results to detect the rainfall events when using higher quantile thresholds (i.e. rainfall above the 50th and 75th percentiles) to sample the data before computing product skill.
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Hydrological Sciences Journal
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65
Issue
7
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This is an Author's Accepted Manuscript of an article published in the Hydrological Sciences Journal, 65 (7), pp. 1112-1128, 27 Feb 2020, copyright Taylor & Francis, available online at: https://doi.org/10.1080/02626667.2020.1730845
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Physical geography and environmental geoscience
Civil engineering
Environmental engineering
Science & Technology
Physical Sciences
Water Resources
Bangladesh
monsoon
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Islam, MA; Cartwright, N, Evaluation of climate reanalysis and space-borne precipitation products over Bangladesh, Hydrological Sciences Journal , 2020, 65 (7), pp. 1112-1128