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Estimation of precipitable water ove...

Callahan, John Andrew.

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Estimation of precipitable water over the Amazon Basin using GOES imagery.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Estimation of precipitable water over the Amazon Basin using GOES imagery./
作者:	Callahan, John Andrew.
面頁冊數:	221 p.
附註:	Source: Masters Abstracts International, Volume: 53-04.
Contained By:	Masters Abstracts International53-04(E).
標題:	Remote sensing. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1562375
ISBN:	9781321094749

Estimation of precipitable water over the Amazon Basin using GOES imagery.
Callahan, John Andrew.

Estimation of precipitable water over the Amazon Basin using GOES imagery. - 221 p.

Source: Masters Abstracts International, Volume: 53-04.

Thesis (M.S.)--University of Delaware, 2014.

The Amazon Rainforest is the largest continuous rainforest on Earth. It holds a rich abundance of life containing approximately one-half of all existing plant and animal species and 20% of the world's fresh water. Climatologically, the Amazon Rainforest is a massive storehouse of carbon dioxide and water vapor and hosts hydrologic and energy cycles that influence regional and global patterns. However, this region has gone through vast land cover changes during the past several decades. Lack of conventional, in situ data sources prohibits detailed measurements to assess the climatological impact these changes may cause. This thesis applies a satellite-based, thermal infrared remote sensing algorithm to determine precipitable water in the Amazon Basin to test its applicability in the region and to measure the diurnal changes in water vapor.

ISBN: 9781321094749Subjects--Topical Terms:

535394
Remote sensing.

Estimation of precipitable water over the Amazon Basin using GOES imagery.
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520 $a The Amazon Rainforest is the largest continuous rainforest on Earth. It holds a rich abundance of life containing approximately one-half of all existing plant and animal species and 20% of the world's fresh water. Climatologically, the Amazon Rainforest is a massive storehouse of carbon dioxide and water vapor and hosts hydrologic and energy cycles that influence regional and global patterns. However, this region has gone through vast land cover changes during the past several decades. Lack of conventional, in situ data sources prohibits detailed measurements to assess the climatological impact these changes may cause. This thesis applies a satellite-based, thermal infrared remote sensing algorithm to determine precipitable water in the Amazon Basin to test its applicability in the region and to measure the diurnal changes in water vapor.
520 $a Imagery from the GOES geostationary satellite and estimated atmospheric conditions and radiance values derived from the NCEP/NCAR Reanalysis project were used as inputs to the Physical Split Window (PSW) technique. Retrievals of precipitable water were made every 3 hours throughout each day from 12Z to 24Z for the months of June and October, 1988 and 1995. These months correspond to when the atmosphere is not dominated by clouds during the rainy (wet) season or smoke and haze during the burning (dry) season. Monthly, daily, and diurnal aggregates of precipitable water Fields were analyzed spatially through seven zones located uniformly throughout the region. Monthly average precipitable water values were found to be 20mm to 25mm in the southeast and 45mm to 50mm in the northwest zones. Central and northwest zones showed little variation throughout the day with most areas peaking between 15Z and 21Z, representing early to late afternoon local time. Comparisons were made to nearby, coincident radiosonde observations with r ranging from 0.7 to 0.9 and MAE from 6mm to 12 mm.
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