Effect of implementing ecosystem functional type data in a mesoscale climate model

Abstract

In this paper, we introduce a new concept of land-surface state representation for southern South America, which is based on “functional” attributes of vegetation, and implement a new land-cover (Ecosystem Functional Type, hereafter EFT) dataset in the Weather and Research Forecasting (WRF) model. We found that the EFT data enabled us to deal with functional attributes of vegetation and time-variant features more easily than the default land-cover data in the WRF. In order to explore the usefulness of the EFT data in simulations of surface and atmospheric variables, numerical simulations of the WRF model, using both the US Geological Survey (USGS) and the EFT data, were conducted over the La Plata Basin in South America for the austral spring of 1998 and compared with observations. Results showed that the model simulations were sensitive to the lower boundary conditions and that the use of the EFT data improved the climate simulation of 2-m temperature and precipitation, implying the need for this type of information to be included in numerical climate models.

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Correspondence to Seung-Jae Lee.

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Lee, SJ., Berbery, E.H. & Alcaraz-Segura, D. Effect of implementing ecosystem functional type data in a mesoscale climate model. Adv. Atmos. Sci. 30, 1373–1386 (2013). https://doi.org/10.1007/s00376-012-2143-3

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Key words

  • Ecosystem Functional Type
  • WRF
  • land cover
  • climate simulation