Toward a South America Land Data Assimilation System: Aspects of land surface model spin‐up using the Simplified Simple Biosphere

Abstract

This paper describes a spin‐up experiment conducted over South America using the Simplified Simple Biosphere (SSiB) land surface model to study the process of model adjustment to atmospheric forcing data. The experiment was carried out as a precursor to the use of SSiB in a South American Land Data Assimilation System (SALDAS). The results from an 11 year long recursive simulation using three different initial conditions of soil wetness (control, wet and dry) are examined. The control run was initiated by interpolation of the NCEP/DOE Global Reanalysis‐2 (NCEP/DOE R‐2) soil moisture data set. In each case the time required for the model to reach equilibrium was calculated. The wet initialization leads to a faster adjustment of the soil moisture field, followed by the control and then the dry initialization. Overall, the final spin‐up states using the SSiB‐based SALDAS are generally wetter than both the NCEP/DOE R‐2 and the Centro de Previsao do Tempo e Estudos Climaticos (CPTEC–Brazilian Center for Weather Forecast and Climate Studies) operational initial soil moisture states, consequently modeled latent heat is higher and sensible heat lower in the final year of simulation when compared with the first year. Selected regions, i.e., in semiarid northeastern Brazil, the transition zone to the south of the Amazon tropical forest, and the central Andes were studied in more detail because they took longer to spin up (up to 56 months) when compared with other areas (less than 24 months). It is shown that there is a rapid change in the soil moisture in all layers in the first 2 months of simulation followed by a subsequent slow and steady adjustment: This could imply there are increasing errors in medium range simulations. Spin‐up is longest where frozen soil is present for long periods such as in the central Andes.