Regional Model Simulations of the 2008 Drought in Southern South America Using a Consistent Set of Land Surface Properties

Publicado en Journal of Climate, v. 27(17):6754–6778

Müller, O.V., Berbery, E.H., Alcaraz-Segura, D. and Ek, M.B.

Año de publicación 2014
  • CEVARCAM, Facultad de Ingeniería y Ciencias Hídricas, Universidad Nacional del Litoral and CONICET, Santa Fe, Argentina
  • Cooperative Institute for Climate and Satellites-Maryland, Earth System Science Interdisciplinary Center, University of Maryland, College Park, College Park, Maryland
  • Departamento de Botánica, Campus de Fuente Nueva, Universidad de Granada, Granada, Spain
  • Environmental Modeling Center, NOAA/NCEP/NWS, College Park, Maryland




Proyecto CRN3035


This work discusses the land surface&ndashatmosphere interactions during the severe drought of 2008 in southern South America, which was among the most severe in the last 50 years in terms of both intensity and extent. Once precipitation returned to normal values, it took about two months for the soil moisture content and vegetation to recover. The land surface effects were examined by contrasting long-term simulations using a consistent set of satellite-derived annually varying land surface biophysical properties against simulations using the conventional land-cover types in the Weather Research and Forecasting Model&ndashNoah land surface model (WRF&ndashNoah). The new land-cover dataset is based on ecosystem functional properties that capture changes in vegetation status due to climate anomalies and land-use changes.

The results show that the use of realistic information of vegetation states enhances the model performance, reducing the precipitation biases over the drought region and over areas of excessive precipitation. The precipitation bias reductions are attributed to the corresponding changes in greenness fraction, leaf area index, stomatal resistance, and surface roughness. The temperature simulation shows a generalized increase, which is attributable to a lower vegetation greenness and a doubling of the stomatal resistance that reduces the evapotranspiration rate. The increase of temperature has a beneficial effect toward the eastern part of the domain with a notable reduction of the bias, but not over the central region where the bias is increased. The overall results suggest that an improved representation of the surface processes may contribute to improving the predictive skill of the model system.