Manoj K. Nambiar, Julie M. Thériault and Alejandro Di Luca (2022). Comparison of different satellite-derived precipitation products over the Western Canada. Proceedings of the GWF Annual Open Science Meeting, May 16-18, 2022.

Precipitation is a critical element of the hydrological cycle and it is an especially important variable associated with atmospheric circulation in weather and climate studies. In this study, we evaluate the quality of four different satellite-based (SB) precipitation products (Multi-Source Weighted-Ensemble Precipitation (MSWEP), Climate Prediction Center morphing technique (CMORPH), Global Satellite Mapping of Precipitation (GSMaP), and Integrated Multi-satellite Retrievals for Global Precipitation Mission (IMERG) against surface meteorological stations from Environment and Climate Change Canada (ECCC) in western Canada over the period 2014-2019. To evaluate the quality of different SB precipitation retrieval products for different climate regimes, the study area is divided into six zones, which include Pacific North West, Great Basin, North Rockies, North Plains, West Boreal and West Taiga. We test several statistics based on daily accumulated precipitation from SB products against ECCC gauge data. The preliminary results suggest that the overall performance of MSWEP estimate in capturing the observed rain-gauge precipitation is better than CMORPH, IMERG and GSMaP across all the climatic regions tested. One main reason behind the better performance of MSWEP precipitation estimate maybe because of the use of daily gauges and reanalysis corrections whereas most other datasets use monthly data. Another reason could be the correction of precipitation underestimation due to gauge under-catch and orographic effects in MSWEP data. Even when the temporal correlation between SB products and rain gauge data are low the overall precipitation distributions are similar. We noticed that the performance of the SB products varies across warm (MJJASO) and cold (NDJFMA) seasons with a better overall performance during the warm season across all the climatic zones.

AOSM2022 GWF core modelling First Author: Manoj K. Nambiar, University of Quebec at Montreal Additional Authors: Julie M. Thériault and Alejandro Di Luca (University of Quebec at Montreal)