Header menu link for other important links
X
Performance analysis of imd high-resolution gridded rainfall (0.25° ☓ 0.25°) and satellite estimates for detecting cloudburst events over the Northwest Himalayas
, Sourabh Garg, Sarita Azad
Published in
2020
Volume: 21
   
Issue: 7
Abstract
The presence of a sparse rain gauge network in complex terrain like the Himalayas has encouraged the present study for the concerned evaluation of Indian Meteorological Department (IMD) ground-based gridded rainfall data for highly prevalent events like cloudbursts over the northwest Himalayas (NWH). To facilitate the abovementioned task, we intend to evaluate the performance of these observations at 0.25° ☓ 0.25° (latitude–longitude) resolution against a predefined threshold (i.e., 99.99th percentile), thereby initially comprehending the success of IMD data in capturing the cloudburst events reported in media during 2014–16. Further, seven high-resolution satellite products, namely, CMORPH V0.x, PERSIANN-CDR, TMPA 3B42RT V7, IMERG V06B, INSAT-3D multispectral rainfall (IMR), CHIRPS V.2 and PERSIANN-CCS are evaluated against the IMD dataset. The following are our main results. 1) Six out of 18 cloudburst events are detected using IMD gridded data. 2) The contingency statistics at the 99.99th percentile reveal that the probability of detection (POD) of TMPA varies from 19.4{\%} to 53.9{\%} over the geographical stretch of NWH, followed by PERSIANN-CDR (18.6{\%}–48.4{\%}) and IMERG (4.9{\%}–17.8{\%}). 3) A new metric proposed as improved POD (IPOD) has been developed in this work, which takes into account the temporal lag that exists between observed and satellite estimates during an event period. Results show that for an event analysis IPOD provides a better comparison. The IPOD for TMPA is 32.8{\%}–74.4{\%}, followed by PERSIANN-CDR (34.4{\%}–69.11{\%}) and IMERG (15.3{\%}–39.0{\%}). 4) The conclusion stands as precipitation estimates obtained from CHIRPS are most suitable for monitoring cloudburst events over NWH with IPOD of 60.5{\%}–78.6{\%}.
About the journal
JournalJournal of Hydrometeorology
ISSN15257541
Open AccessNo