Land-atmosphere interactions in an high resolution atmospheric simulation coupled with a surface data assimilation scheme
- 1Dipartimento di Ingegneria Civile e Ambientale, Università degli Studi di Firenze, Via S. Marta 3, 50139 Firenze, Italy
- 2Parsons Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- 3Eumechanos – Via La Marmora 22, 50121 Firenze, Italy
Abstract. A valid tool for the retrieving of the turbulent fluxes that characterize the surface energy budget is constituted by the remote sensing of land surface states. In this study sequences of satellite-derived observations (from SEVIRI sensors aboard the Meteosat Second Generation) of Land Surface Temperature have been used as input in a data assimilation scheme in order to retrieve parameters that describe energy balance at the ground surface in the Tuscany region, in central Italy, during summer 2005. A parsimonious 1-D multiscale variational assimilation procedure has been followed, that requires also near surface meteorological observations. A simplified model of the surface energy balance that includes such assimilation scheme has been coupled with the limited area atmospheric model RAMS, in order to improve in the latter the accuracy of the energy budget at the surface. The coupling has been realized replacing the assimilation scheme products, in terms of surface turbulent fluxes and temperature and humidity states during the meteorological simulation. Comparisons between meteorological model results with and without coupling with the assimilation scheme are discussed, both in terms of reconstruction of surface variables and of vertical characterization of the lower atmosphere. In particular, the effects of the coupling on the moisture feedback between surface and atmosphere are considered and estimates of the precipitation recycling ratio are provided. The results of the coupling experiment showed improvements in the reconstruction of the surface states by the atmospheric model and considerable influence on the atmospheric dynamics.