Evaluating soil moisture-precipitation interactions using remote sensing: A sensitivity analysis

Trent W. Ford, Steven M. Quiring, Balbhadra Thakur, Rohit Jogineedi, Adam Houston, Shanshui Yuan, Ajay Kalra, Noah Lock

Research output: Contribution to journalArticlepeer-review

Abstract

The complex interactions between soil moisture and precipitation are difficult to observe, and consequently there is a lack of consensus as to the sign, strength, and location of these interactions. Inconsistency between soil moisture-precipitation interaction studies can be attributed to a multitude of factors, including the difficulty of demonstrating causal relationships, dataset differences, and precipitation autocorrelation. The purpose of this study is to explore these potential confounding factors and determine which are most important for consideration when assessing statistical coupling between soil moisture and precipitation. Soil moisture is assessed via three remote sensing datasets: the Advanced Microwave Scanning Radiometer for Earth Observing System, the Tropical Rainfall Measuring Mission Microwave Imager, and the Essential Climate Variable Soil Moisture. Estimates of soil moisture are coupled with afternoon thunderstorm events identified by the Thunderstorm Observation by Radar (ThOR) algorithm, and dry soil or wet soil preferences for convection initiation are determined for over 16 000 thunderstorm events between 2005 and 2007. Differences in soil moisture datasets were found to have the largest impact with regard to determining wet or dry soil preferences. Precipitation autocorrelation is prevalent in the data; however, precipitation autocorrelation did not influence the results with regard to dry or wet soil preferences. Consideration of the convective environment (i.e., weakly or synoptically forced) did result in significant differences in wet/dry soil preference, but only for certain soil moisture datasets. The results suggest that observation-driven soil moisture-precipitation interaction studies should both consider the convective environment and implement multiple soil moisture datasets to assure robust results.

Original languageEnglish (US)
Pages (from-to)1237-1253
Number of pages17
JournalJournal of Hydrometeorology
Volume19
Issue number8
DOIs
StatePublished - Aug 1 2018
Externally publishedYes

Keywords

  • Atmosphere-land interaction
  • Remote sensing
  • Soil moisture

ASJC Scopus subject areas

  • Atmospheric Science

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