Near-real-time one-kilometre Soil Moisture Active Passive soil moisture data product

Jifu Yin, Xiwu Zhan, Jicheng Liu, Hamid Moradkhani, Li Fang, Jeffrey P. Walker

Research output: Contribution to journalArticleResearchpeer-review

Abstract

The coarse resolution soil moisture (SM) data from NASA SMAP mission have been steadily produced with the expected performance since April 2015. These coarse resolution observations could be downscaled to fine resolution using fine scale observations of SM sensitive quantities from existing satellite sensors. For operational users who need near-real-time (NRT) high resolution SM data, the downscaling approach should be feasible for operational implementation, requiring limited ancillary information and primarily depending on readily available satellite observations. Based on these principles, nine potential candidate downscaling schemes were selected for developing an optimal downscaling strategy. Using remotely sensed land surface temperature (LST) and enhanced vegetation index (EVI) observations, the optimal downscaling approach was tested for operational producing a NRT 1 km SM data product from SMAP. Comprehensive assessments on the 1 km SM product were conducted based on agreement statistics with in-situ SM measurements. Statistical results show that the accuracy of the original coarse spatial resolution SMAP SM product can be significantly improved by 8% by the downscaled 1 km SM. With respect to the in-situ measurements, the 1 km SM mapping capability developed here presents a clear advantage over the SMAP/Sentinel SM data product; and it also provides better data availability for users. This study suggests that a NRT 1 km SMAP SM data product could be routinely generated from SMAP at the centre for Satellite Applications and Research of NOAA NESDIS for operational users.

Original languageEnglish
Pages (from-to)4083-4096
Number of pages14
JournalHydrological Processes
Volume34
Issue number21
DOIs
Publication statusPublished - 15 Oct 2020

Keywords

  • downscale
  • near real time
  • SMAP
  • soil moisture
  • spatial resolution

Cite this