H31A-1395
Spatio-Temporal Analysis of Model and Satellite Based Soil Moisture Estimations for Assessing Coupling Hot Spots in the Southern La Plata Basin
Abstract:
The southern La Plata Basin, located in southeastern South America (SESA), a region of great importance because of its hydrological characteristics, the fact that it has the largest population density and is one of the most productive regions in terms of agriculture, cattle raising and industry of the continent, has been identified as a strong hotspot between soil moisture (SM) and the atmosphere by different regional studies.Among them, Ruscica et al. (2014, Atmos. Sci. Let, Int. J. Climatol.), and Spennemann et al. (2015, Int. J. Climatol.) show, through different modeling approaches, the presence of strong soil moisture-precipitation and evapotranspiration interactions during austral summer in SESA, revealing similar hotspots. Nevertheless these studies have diverse limitations related to model assumptions and to vegetation parameterizations, as well as the lack of observational data for the evaluation of models performance (Ferguson and Wood, 2011, J. of Hydrometeorology).
On the other hand, in the last decade several instruments on board satellites are providing soil moisture products globally and in a continuous way. A recent work by Grings et al. (2015, IEEE JSTARS, in press), done over the Pampas Plains in SESA showed characteristic soil moisture patterns that follow the Standardized Precipitation Index (SPI) under extreme wet and dry conditions
In order to deepen and overcome some of the mentioned model limitations, this work adds satellite soil moisture and vegetation products in the spatio-temporal analysis of the regions of strong soil moisture-atmosphere interactions. The main objectives and related outcomes are: the verification of already identified regions where soil moisture anomalies may have an influence on subsequent precipitation, evapotranspiration and temperature anomalies, and the study of their seasonal characteristics and land cover influences.