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United States Department of Agriculture

Agricultural Research Service

Research Project: INSOLATION MAPPING OVER THE CONTINENTAL U.S. USING GOES IMAGERY
2012 Annual Report


1a.Objectives (from AD-416):
Produce near-real-time maps of hourly insolation maps at 20km resolution over the continental U.S. for the year 2009-2010 using GOES imagery. This product will be used in realtime execution of the Atmosphere-Land Exchange Inverse (ALEXI) model, developed at the USDA-ARS, to estimate evapotranspiration (ET) and other land surface fluxes.


1b.Approach (from AD-416):
Work with UW scientists to coordinate production and daily transfer of insolation dataset to HRSL. In addition, the UW cooperators will work on improvements to the existing algorithms, including a) incorporation of more reliable estimates of precipitable water from the NCEP GFS model; b) development of a validation/calibration procedure using pyranometer data from the U.S. Climatological Radiation Network; and c) transitioning of this new insolation algorithm to operations (including documentation).


3.Progress Report:

This product is being used in real time execution of the Atmosphere-Land Exchange (ALEXI) model, developed at the USDA-ARS, to estimate evapotranspiration and other land-surface fluxes. Legacy code was updated and optimized for execution speed. A calibration technique was developed using ground-based pyranometer data which is used to adjust model cloud albedo using an objective analysis technique. The resulting calibration coefficient has dramatically improved the estimation of insolation from Geostationary Operational Environmental Satellite (GOES) measurements at high-reflectance (high cloud albedo, low insolation) situations. Atmospheric total precipitable water (TPW) is another important variable in the estimation of insolation from GOES data. Code has been written that accesses the National Oceanic and Atmospheric Administration (NOAA) Global Forecast System (GFS) TPW, a reliable and general source obtainable from the NOAA website.

A new model framework including these improvements has been constructed and is easily portable to any McIDAS (Man computer Interactive Data System) location. USCRN (U.S. Climate Reference Network) pyranometer data access has been automated in order to validate satellite daily and hourly insolation estimates from the new insolation model and calibrate the visible channel on GOES satellites via newly-developed techniques. Model resolution has been improved to 10-km spatial (down from 20 km), and half-hour temporal (up from hourly) to facilitate higher resolution mapping applications. Finally, it is apparent that errors in hourly satellite estimates of insolation can often be related to the bidirectional components of radiation that the insolation model does not take into account. We are researching simple bidirectional models that might be used to improve the accuracy of the hourly satellite estimates. Methods researched to date either require pre-classification of the scene type (clear, partly cloudy, ocean, land, etc.), which would make the estimation of insolation from GOES an iterative and computationally-expensive effort, or simply too much computer time due to the complexity of the radiative transfer model.

The new insolation model has been transferred to Space Science and Engineering Center (SSEC) Data Center at the University of Wisconsin, where it underwent debugging and testing. This model was transferred to operations. Both the old model and the new model are running simultaneously to allow further comparisons between the two versions. Although the new model tends to have large errors under the same conditions as the old version, the overall mean error is smaller due to the improved calibration.


Last Modified: 11/23/2014
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