Main Title |
United States Meteorological Data: Daily and Hourly Files to Support Predictive Exposure Modeling. |
Author |
Burns, L. A. ;
Suarez, L. A. ;
Prieto, L. M. ;
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CORP Author |
Environmental Protection Agency, Athens, GA. |
Publisher |
May 2007 |
Year Published |
2007 |
Report Number |
EPA/600/R-07/053; |
Stock Number |
PB2007-110161 |
Additional Subjects |
Meteorological data ;
Pesticides ;
United States ;
Air pollution monitoring ;
Data files ;
Numerical models ;
Exposure ;
Spray drift ;
Predictive exposure modeling ;
Climatological databases ;
National Weather Service (NWS) datasets
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Internet Access |
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Holdings |
Library |
Call Number |
Additional Info |
Location |
Last Modified |
Checkout Status |
NTIS |
PB2007-110161 |
Some EPA libraries have a fiche copy filed under the call number shown. |
|
07/26/2022 |
|
Collation |
397p |
Abstract |
ORD numerical models for pesticide exposure include a model of spray drift (AgDisp), a cropland pesticide persistence model (PRZM), a surfacewater exposure model (EXAMS), and a model of fish bioaccumulation (BASS). A unified climatological database for these models has been assembled from several National Weather Service (NWS) datasets, including Solar and Meteorological Surface Observation Network (SAMSON) data for 1961-1990 (versions 1.0 and 1.1), combined with NWS precipitation and evaporation data. Together these NWS products provide coordinated access to solar radiation, sky cover, temperature, relative humidity, station atmospheric pressure, wind direction and speed, and precipitation. The resulting hourly and daily weather parameters providea unified dataset for use in coordinated exposure modeling. The data files, which include some derived data of use to exposure modeling (e.g., short-grass crop standard evapotranspiration ET(sub 0)) are publicly available (gratis) on EPA's Center for Exposure Assessment Modeling (CEAM) web site at http://www.epa. gov/ceampubl/tools/ metdata/index.htm. By using observational data for models, trace-matching Monte Carlo simulation studies can transmit the effects of environmental variability directly to exposure metrics, by-passing issues of correlation (covariance) amongexternal driving forces. This report covers a period from May 2, 2001 toDecember 27, 2004 and work was completed as of December 27, 2004. |
Availability Notes |
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Category Codes |
55C; 57P; 68A |
NTIS Prices |
PC A18/MF A04 |
Document Type |
NT |
Cataloging Source |
NTIS/MT |
Control Number |
019103260 |
Origin |
NTIS |
Type |
CAT |