Abstract
A comprehensive validation of three satellite precipitation datasets (SPDs), including (1) the Climate Prediction Center Morphing algorithm (CMORPH), (2) Global Satellite Mapping of Precipitation (GSMaP) Reanalysis, and (3) Tropical Rainfall Measuring Mission multi-satellite precipitation analysis (TRMM) 3B42, was conducted using the rain gauge-based Vietnam Gridded Precipitation dataset (VnGP) and rain gauge station data for Central Vietnam. The three SPDs were compared and evaluated for two contrasting topographic regions, i.e., the Vietnam Central Highlands (VCH) and the Vietnam Central Coast (VCC), during the rainy seasons from 2001 to 2010 at different spatial (grid and regional) and temporal (daily and monthly) scales. Widespread heavy rainfall (WHR) days caused by the Northeast Winter Monsoon (NM), the Inter-tropical Convergence Zone (ITCZ), and tropical cyclones (TCs) were also identified, and the accuracies of the SPDs in detecting heavy rainfall during the WHR days were evaluated. TRMM was shown to exhibit advantages over the other SPDs, regardless of the spatial and temporal scales. Although the CMORPH and GSMaP datasets appeared to correlate moderately well with the VnGP dataset and proved able to capture the spatial distribution of rainfall characteristics in the VCC, they significantly underestimated rainfall in the VCH. Regarding the capability to reproduce WHR events, the three SPDs exhibited better performance for TCs and the ITCZ than for the NM. TRMM exhibited the best performance among the three datasets, especially for rainfall thresholds ranging from 25 to 80 mm day−1. The GSMaP and CMORPH biases showed a clear dependence on elevation and zonal wind speed, indicating the need to improve correction methods.
Highlights
Rainfall is extremely important for human life, agriculture, and the global water cycle
Tropical Rainfall Measuring Mission multi-satellite precipitation analysis (TRMM) generally represents the Vietnam Gridded Precipitation dataset (VnGP) patterns well, while Center Morphing algorithm (CMORPH) and Global Satellite Mapping of Precipitation (GSMaP) do not. Both CMORPH and GSMaP underestimate the precipitation amount compared to VnGP, especially in the southeastern and northern regions of the Vietnam Central Highlands (VCH) in which high mountains are found
Low Correlation coefficient (CORR) values are obtained with CMORPH and GSMaP compared to that with TRMM over the same region
Summary
Rainfall is extremely important for human life, agriculture, and the global water cycle. Satellite products can determine the distribution of precipitation with great spatial and temporal accuracy. They have proven to be capable of providing data over areas inaccessible for ground weather radars or other in situ instruments. According to Dinku et al (2008) and Gao and Liu (2013), two types of radiometric observations are popularly used to create satellite precipitation products, i.e., 1) infrared imagery, which has a high sampling frequency and produces precipitation estimates based on an indirect relationship with cloud-top temperature (the use of infrared algorithms is typically problematic for estimations involving warm orographic rain) and 2) microwave, including both passive imagery and microwave radar, which has fewer temporal sampling intervals but can provide precipitation estimates with higher accuracy due to the direct connection of the data with precipitation hydrometers. The combination of microwave and infrared data has generated precipitation products with
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
