In this study, 169 meteorological stations are used as the "ground truth" to assess the Tropical Rainfall Measuring Mission (TRMM) and Global Satellite Mapping of Precipitation (GSMaP) products in estimating tropical cyclone (T.C.)-induced rainfall over Vietnam's mainland during the 2000-2019 period. Various statistical indices compare two satellite rain datasets with rain gauge observations. In this study, the performance of satellite-based precipitation datasets was investigated for T.C.s affecting the entire Vietnam's mainland, mainly focusing on the position of surface weather stations relative to the landfall and movement directions of the T.C.s. The results indicate that both satellite rain datasets accurately provide the radial distribution of TC-induced rainfall, concentrated within 500 km from the T.C. center, and decreases as the distance from the T.C. center increases. Significantly, the verifications show the close similarity between the TRMM and GSMaP products in estimating TC-induced rainfall. In particular, the assessments considering T.C. intensities and T.C. landing sub-regions suggest that the performance of two satellite rain datasets in evaluating TC-induced rainfall over Vietnam's mainland strongly depends on the intensity of TC-induced rainfall. Light rainfall is estimated more accurately than heavy rainfall. As a result, the performance of the TRMM and GSMaP show higher errors in the coastal areas, where most TC-induced rainfall concentrates, particularly within a 200 km radius of the T.C. center. Besides, M.A.E. exhibits higher values on the left side of the T.C. track compared to those on the right side for all T.C. intensities while showing differences in T.C. landing sub-regions for both datasets.
No takes yet. Share an insight, caveat, or question.
Pham‐Thanh et al. (2024) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: