Monday, 7 November 2005 - 8:30 AM
26-3

A Global Agroclimatology Data Archive (Satellite and Model Inferred Parameters).

James Hoell1, Paul Stackhouse2, Charles Whitlock1, William Chandler1, and Taiping Zhang3. (1) SAIC/Langley Research Center, One Enterprise Parkway, Hampton, VA 23666-5845, (2) NASA Langley Research Center, 21 Langley Boulevard, Mail Stop 420, Hampton, VA 23681-2199, (3) Analytical Services and Materials, Inc., One Enterprise Parkway, Hampton, VA 23666-5845

NASA's Earth Science Enterprise (ESE) has long supported satellite systems and research providing data important to the study of climate and climate processes. These data include long-term estimates of meteorological quantities from assimilation models and surface solar energy fluxes from satellite observations. NASA supported the development of the Surface meteorology and Solar Energy (SSE) dataset providing Internet-based (http://eosweb.larc.nasa.gov/sse/) access to parameters formulated specifically for photovoltaic and renewable energy system design needs. Now, NASA has established an Energy Management theme within the ESE Applications Program. Under this program, the Prediction Of Worldwide Energy Resource (POWER) project has been initiated both to improve subsequent releases of SSE and to create new datasets directly applicable to other industries. This paper gives an overview of the NASA POWER activities related to the development of agroclimatology parameters for the agricultural industry.

The current SSE/POWER web site contains daily and seasonal monthly averages of over 200 parameters for the time period from July 1983 through October 1995 with a global resolution of 1-degree latitude x 1-degree longitude. The temporal coverage will soon be expanded to cover the time period from 1983 through 2003, with a longer-range goal (2 to 3 years) of providing near real time access to global estimates of parameters such as solar flux, air temperature, precipitation, and winds. During our presentation we will discuss results of analysis/comparisons of the agroclimatology parameters available in the POWER-archive to observations available from many of the automated agricultural weather stations in the US. Results from our analysis demonstrate that, in particular, the surface solar fluxes and near surface temperatures available through the SSE/POWER web site accurately captures the daily variability seen in ground site observations for most of the sites studied. We will also review the status of other parameters such as near surface winds and precipitation.


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