|Hoogenboom, Gerrit - UNIV OF GEORGIA|
|Hoell, James - SAIC/LANGLEY RES CTR|
|Stackhouse, Paul - NASA LANGLEY RES CTR|
Submitted to: Agronomy Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: September 15, 2006
Publication Date: November 16, 2006
Citation: White, J.W., Hoogenboom, G., Hoell, J., Stackhouse, P.W. 2006. Utility of NASA's daily solar and meteorological data for regional level modeling of wheat phenology and yield potential. Agronomy Abstracts. [CD-ROM P23518) Technical Abstract: Data products from the NASA Science Mission Directorate's Applied Science Energy Managed Program provide estimates of long-term meteorological conditions from assimilation models and surface solar energy fluxes derived from satellite observations. NASA's Prediction Of Worldwide Energy Resource (POWER) web site (earth-www.larc.nasa.gov/power/) distributes these data in a format that contain daily values for maximum and minimum temperature, total surface solar radiation, and humidity from July 1983 through December 2004. The resolution is 1° latitude x 1° longitude for the entire globe. Validation studies of the solar data, and more recently the temperature data, through comparisons with observations from globally distributed ground site indicate that the POWER data accurately reflect variability for many sites, but further testing is needed to assess their utility for agricultural applications. Ecophysiological models provide a useful platform for testing since they are very responsive to temperature and solar radiation. We examine the utility of the data in modeling regional and seasonal variation in time of flowering and yield potential of winter wheat (Triticum aestivum L.) in the US using the CSM-CROPSIM-CERES model. Simulations using the POWER data for a 20-year period are compared to results obtained using daily data primarily from NOAA's National Climate Data Center. Since stations generally do not report solar radiation, these data were generated using a modification of the WGENR estimator. Two scales of analysis are considered. The US-wide scale indicates overall utility of the POWER data for regional analyses. Analysis of variability within four 1° x 1° cells from contrasting regions indicates tradeoffs in using "average" data over regions covering 8,000 to 11,000 km2 (depending on latitude) vs. using station data.