|Otkin, Jason - UNIVERSITY OF WISCONSIN|
|Mecikalski, John - UNIVERSITY OF ALABAMA|
|Diak, George - UNIVERSITY OF WISCONSIN|
Submitted to: Journal of Hydrometeorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: March 8, 2005
Publication Date: August 31, 2005
Repository URL: http://handle.nal.usda.gov/10113/59929
Citation: Otkin, J., Anderson, M.A., Mecikalski, J.R., Diak, G.R. 2005. Validation of GOES-Based insolation estimates using data from the United States Climate Reference Network. Journal of Hydrometerorology. 6:475-640. Interpretive Summary: Solare radiation at hourly and daily timesteps is a critical input to crop growth, hydrologic and meteotological models. Historically, model inputs of solar radiation have been derived from measurements made at weather stations - discrete observations made at specific points in space. Point measurements of insolation cannot be spatially interpolated in a reliable way to provide watershed, state or continental-scale maps due to high spatial vairiability imposed by convective cloud structure. Therefore, a robust remote-sensing bades approach to mapping insolation, using high temporal frequency satellite imagery, is highly desirable. In this paper, an insolation model using hourlyimagery from the Geostationary Operational Environmental Satellite (GOES) is validated against model Using hourly observations collected at 11 sites within the U.S. Climate Reference Network (USCRN), representing a large range in climatic and geographic locations. The model works very well over these diverse set of conditions, yielding 20% errors at hourly timesteps and 10% errors for daily-averaged insolation. This level of accuracy is comparable or superior to results that have been obtained with more complex models of atmospheric radiative transfer. This insolation processing algorithm has been automated and real-time insolation maps are currently being used in regional-scale models of evapotranspiration, vegetation and soil moisture stress, carbon flux, and surface hydrology. For example, the USGS is using these GOES-based insolation maps to estimate groundwater recharge over the Florida Everglades.
Technical Abstract: Reliable procedures that accurately map surface insolation over large domains at high spatial and temporal resolution are of great benefit for making the predictions of potential and actual evapotranspiration required by a variety of hydrological and agricultural applications. Here, estimates of hourly and daily-integrated insolation at 20-km resolution based on GOES visible imagery are compared to pyranometer measurements made at 11 sites in the United States Climate Reference Network (USCRN) over a continuous 15-month period. Such a comprehensive survey is necessary in order to examine the accuracy of the satellite insolation estimates over a diverse range of seasons and land-surface types. The relatively simple physical model of insolation tested here yields good results, with seasonally averaged model errors of 62 Wm-2 (19%) and 15 Wm-2 (10%) for hourly- and daily-averaged insolation, respectively, including both clear and cloudy-sky conditions. This level of accuracy is comparable or superior to results that have been obtained with more complex models of atmospheric radiative transfer. Model performance can be improved in the future by addressing a small elevation-related bias in the physical model, which is likely due to inaccurate model precipitable water inputs or cloud height assessments.