High-resolution gridded soil moisture and soil temperature datasets for the indian monsoon region

H. P. Nayak, K. K. Osuri, Palash Sinha, Raghu Nadimpalli, U. C. Mohanty, Fei Chen, M. Rajeevan, D. Niyogi*

*Corresponding author for this work

Research output: Contribution to journalJournal Articlepeer-review

44 Citations (Scopus)

Abstract

High-resolution soil moisture/temperature (SM/ST) are critical components of the growing demand for fine-scale products over the Indian monsoon region (IMR) which has diverse land-surface characteristics. This demand is fueled by findings that improved representation of land-state help improve rainfall/flood prediction. Here we report on the development of a high-resolution (4 km and 3 hourly) SM/ST product for 2001–2014 during Indian monsoon seasons (June–September). First, the quality of atmospheric fields from five reanalysis sources was examined to identify realistic forcing to a land data assimilation system (LDAS). The evaluation of developed SM/ST against observations highlighted the importance of quality forcing fields. There is a significant relation between the forcing error and the errors in the SM/ST. A combination of forcing fields was used to develop 14-years of SM/ST data. This dataset captured inter-annual, intraseasonal, and diurnal variations under different monsoon conditions. When the mesoscale model was initialized using the SM/ST data, improved simulations of heavy rain events was evident, demonstrating the value of the data over IMR.

Original languageEnglish
Article number180264
JournalScientific Data
Volume5
DOIs
Publication statusPublished - 2018
Externally publishedYes

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© The Author(s) 2018.

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