The Role of an Advanced Land Model in Seasonal Dynamical Downscaling for Crop Model Application

• Published in: Journal of applied meteorology (1988) 2006-05, Vol.45 (5), p.686-701
• Main Authors: Shin, D. W., Bellow, J. G., LaRow, T. E., Cocke, S., O’Brien, James J.
• Format: Article
• Language: English
• Subjects: Agricultural and forest climatology and meteorology. Irrigation. Drainage; Agricultural and forest meteorology; Agricultural land; Agricultural production; Agronomy. Soil science and plant productions; Atmosphere; Atmospheric models; Atmospheric research; Biological and medical sciences; Climate; Climate models; Climatic models of plant production; Climatology; Computer simulation; Crop yield; Crops; Earth, ocean, space; Estimating techniques; Exact sciences and technology; External geophysics; Fundamental and applied biological sciences. Psychology; General agronomy. Plant production; Generalities. Techniques. Climatology. Meteorology. Climatic models of plant production; Greenhouse gases; Land; Meteorological applications; Meteorology; Modeling; Peanuts; Precipitation; Rain; Regional; Simulations; Spectra; Statistical methods; Studies; Temperature; Weather
• ISSN: 1558-8424; 0894-8763; 1558-8432; 1520-0450
• DOI: 10.1175/jam2366.1

An advanced land model [the National Center for Atmospheric Research (NCAR) Community Land Model, version 2 (CLM2)] is coupled to the Florida State University (FSU) regional spectral model to improve seasonal surface climate outlooks at very high spatial and temporal resolution and to examine its potential for crop yield estimation. The regional model domain is over the southeast United States and is run at 20-km resolution, roughly resolving the county level. Warm-season (March–September) simulations from the regional model coupled to the CLM2 are compared with those from the model with a simple land surface scheme (i.e., the original FSU model). In this comparison, two convective schemes are also used to evaluate their roles in simulating seasonal climate, primarily for rainfall. It is shown that the inclusion of the CLM2 produces consistently better seasonal climate scenarios of surface maximum and minimum temperatures, precipitation, and shortwave radiation, and hence provides superior inputs to a site-based crop model to simulate crop yields. The FSU regional model with the CLM2 exhibits some capability in the simulation of peanut (Arachis hypogaeaL.) yields, depending upon the convective scheme employed and the site selected.