scholarly journals High-resolution ensemble surface insolation estimates through assimilation of coarse-scale retrievals into a simple physical model: 1. Physical model development and accuracy tests

2007 ◽  
Vol 112 (D8) ◽  
Author(s):  
Songweon Lee ◽  
Steven A. Margulis
Keyword(s):  
High Resolution ◽  
Physical Model ◽  
Model Development ◽  
Coarse Scale ◽  
Simple Physical Model

Validation of GOES-Based Insolation Estimates Using Data from the U.S. Climate Reference Network

2005 ◽  
Vol 6 (4) ◽  
pp. 460-475 ◽  
Author(s):  
Jason A. Otkin ◽  
Martha C. Anderson ◽  
John R. Mecikalski ◽  
George R. Diak
Keyword(s):  
Physical Model ◽  
Land Surface ◽  
Radiative Transfer Model ◽  
Reference Network ◽  
Transfer Model ◽  
Model Errors ◽  
Diverse Range ◽  
Simple Physical Model ◽  
Averaged Model ◽  
The U.S

Abstract Reliable procedures that accurately map surface insolation over large domains at high spatial and temporal resolution are a great benefit for making the predictions of potential and actual evapotranspiration that are required by a variety of hydrological and agricultural applications. Here, estimates of hourly and daily integrated insolation at 20-km resolution, based on Geostationary Operational Environmental Satellite (GOES) visible imagery are compared to pyranometer measurements made at 11 sites in the U.S. 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 that is tested here yields good results, with seasonally averaged model errors of 62 (19%) and 15 (10%) W m−2 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 the result of inaccurate model precipitable water inputs or cloud-height assessments.

Physical Model Development To Study Sand Production

2007 ◽  
Author(s):  
Jothsimar del Valle Gonzalez ◽  
Jose Alvarellos ◽  
Hector Gonzalez ◽  
Victor Roman Lara
Keyword(s):  
Physical Model ◽  
Model Development ◽  
Sand Production
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