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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 journal › Journal Article › peer-review

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

Bibliographical note

Publisher Copyright:
© The Author(s) 2018.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

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