A Comparison of Water Vapor Quantities from Model Short-Range Forecasts and ARM Observations
Model evolution and improvement is complicated by the lack of high quality observational data. To address a major limitation of these measurements the Atmospheric Radiation Measurement (ARM) program was formed. For the second quarter ARM metric we will make use of new water vapor data that has becom...
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ftosti:oai:osti.gov:948516 2023-07-30T04:05:44+02:00 A Comparison of Water Vapor Quantities from Model Short-Range Forecasts and ARM Observations Hnilo, J. 2016-04-06 application/pdf http://www.osti.gov/servlets/purl/948516 https://www.osti.gov/biblio/948516 https://doi.org/10.2172/948516 unknown http://www.osti.gov/servlets/purl/948516 https://www.osti.gov/biblio/948516 https://doi.org/10.2172/948516 doi:10.2172/948516 54 ENVIRONMENTAL SCIENCES 2016 ftosti https://doi.org/10.2172/948516 2023-07-11T08:46:55Z Model evolution and improvement is complicated by the lack of high quality observational data. To address a major limitation of these measurements the Atmospheric Radiation Measurement (ARM) program was formed. For the second quarter ARM metric we will make use of new water vapor data that has become available, and called the “Mergedsounding” value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Darwin Australia (DAR) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both DAR and NSA. The merged-sounding data have been interpolated to 37 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3 hourly data for direct comparison to our model output. Other/Unknown Material north slope Alaska SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) |
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SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) |
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54 ENVIRONMENTAL SCIENCES |
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54 ENVIRONMENTAL SCIENCES Hnilo, J. A Comparison of Water Vapor Quantities from Model Short-Range Forecasts and ARM Observations |
topic_facet |
54 ENVIRONMENTAL SCIENCES |
description |
Model evolution and improvement is complicated by the lack of high quality observational data. To address a major limitation of these measurements the Atmospheric Radiation Measurement (ARM) program was formed. For the second quarter ARM metric we will make use of new water vapor data that has become available, and called the “Mergedsounding” value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Darwin Australia (DAR) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both DAR and NSA. The merged-sounding data have been interpolated to 37 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3 hourly data for direct comparison to our model output. |
author |
Hnilo, J. |
author_facet |
Hnilo, J. |
author_sort |
Hnilo, J. |
title |
A Comparison of Water Vapor Quantities from Model Short-Range Forecasts and ARM Observations |
title_short |
A Comparison of Water Vapor Quantities from Model Short-Range Forecasts and ARM Observations |
title_full |
A Comparison of Water Vapor Quantities from Model Short-Range Forecasts and ARM Observations |
title_fullStr |
A Comparison of Water Vapor Quantities from Model Short-Range Forecasts and ARM Observations |
title_full_unstemmed |
A Comparison of Water Vapor Quantities from Model Short-Range Forecasts and ARM Observations |
title_sort |
comparison of water vapor quantities from model short-range forecasts and arm observations |
publishDate |
2016 |
url |
http://www.osti.gov/servlets/purl/948516 https://www.osti.gov/biblio/948516 https://doi.org/10.2172/948516 |
genre |
north slope Alaska |
genre_facet |
north slope Alaska |
op_relation |
http://www.osti.gov/servlets/purl/948516 https://www.osti.gov/biblio/948516 https://doi.org/10.2172/948516 doi:10.2172/948516 |
op_doi |
https://doi.org/10.2172/948516 |
_version_ |
1772817855024201728 |