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Combining ground-based and space-bas...

Yesalusky, Melissa Ann.

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Combining ground-based and space-based remote sensing to validate climate.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Combining ground-based and space-based remote sensing to validate climate./
作者:	Yesalusky, Melissa Ann.
面頁冊數:	187 p.
附註:	Source: Dissertation Abstracts International, Volume: 77-08(E), Section: B.
Contained By:	Dissertation Abstracts International77-08B(E).
標題:	Atmospheric sciences. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10092243
ISBN:	9781339597416

Combining ground-based and space-based remote sensing to validate climate.
Yesalusky, Melissa Ann.

Combining ground-based and space-based remote sensing to validate climate. - 187 p.

Source: Dissertation Abstracts International, Volume: 77-08(E), Section: B.

Thesis (Ph.D.)--Hampton University, 2015.

The goal of this research was to develop a technique that combined ground-based and space-based remote sensing measurements to obtain the properties necessary to calculate atmospheric flux and their associated heating and cooling rates for validating climate models. This study was conducted and validated using seasonal data from the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in Lamont Oklahoma. Data were collected over four nonconsecutive months, representing one month for each season, during 2010 and 2011, from the ARM-SGP site and associated collocated satellites. The data collected were used to determine the properties of the atmosphere and clouds for integration into the MODerate resolution atmospheric TRANsmission (MODTRAN) model to assess the upwelling and downwelling atmospheric flux of the atmosphere.

ISBN: 9781339597416Subjects--Topical Terms:

3168354
Atmospheric sciences.

Combining ground-based and space-based remote sensing to validate climate.
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500 $a Adviser: Wlliam L. Smith.
502 $a Thesis (Ph.D.)--Hampton University, 2015.
520 $a The goal of this research was to develop a technique that combined ground-based and space-based remote sensing measurements to obtain the properties necessary to calculate atmospheric flux and their associated heating and cooling rates for validating climate models. This study was conducted and validated using seasonal data from the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in Lamont Oklahoma. Data were collected over four nonconsecutive months, representing one month for each season, during 2010 and 2011, from the ARM-SGP site and associated collocated satellites. The data collected were used to determine the properties of the atmosphere and clouds for integration into the MODerate resolution atmospheric TRANsmission (MODTRAN) model to assess the upwelling and downwelling atmospheric flux of the atmosphere.
520 $a The atmospheric flux was calculated using a variety of combinations of ground-based and satellite-based data to determine a combination that reveals the best comparison with the top of the atmosphere and surface flux measurements from the Clouds and the Earth's Radiant Energy System (CERES) satellite and ARMS's Solar Infrared Radiation Stations (SIRS), respectively. After validating the flux and determining the ideal data combinations, the atmospheric heating and cooling profiles were calculated and compared with three current reanalysis model results to determine the feasibility of using this new technique for climate model validation. This comparison revealed good agreement with the models. In general, the differences were less than 0.5 K Day-1 for both the clear and cloudy sky conditions. The month of July was the exception for the longwave spectral region; however, the sources of uncertainty during this month are high, with a high frequency of multilevel cloud cases that are either not detected or not represented correctly in the datasets. The use of satellite cloud climatological data based on the complete system of polar orbiting and geostationary satellite measurements is one approach to improve the results from applying this technique for the cloudy situations. Since there are currently numerous ARM sites around the world with similar instrumentation, this technique can be expanded to validate climate model results in other regions using ARM's historical and future datasets.
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