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Calculating the Standardized Precipi...

Satterlee, Leonard.

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Calculating the Standardized Precipitation Index Using a Moving Window Approach.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Calculating the Standardized Precipitation Index Using a Moving Window Approach./
作者:	Satterlee, Leonard.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:	49 p.
附註:	Source: Masters Abstracts International, Volume: 81-04.
Contained By:	Masters Abstracts International81-04.
標題:	Climate change. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=22585467
ISBN:	9781088349182

Calculating the Standardized Precipitation Index Using a Moving Window Approach.
Satterlee, Leonard.

Calculating the Standardized Precipitation Index Using a Moving Window Approach. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 49 p.

Source: Masters Abstracts International, Volume: 81-04.

Thesis (M.S.)--Indiana University, 2019.

Improved understanding of the timing and duration of droughts and pluvials increases our ability to adapt while minimizing the financial cost of these natural disasters. Here, using daily precipitation data from across the United States, we develop a method that reformulates the traditional Standardized Precipitation Index (SPI) to use a moving-window approach. This reformulation allows for fine temporal-scale monitoring of drought and pluvial conditions, with the drought index updated daily. Using moving-window SPI, drought and pluvial periods reach greater extremes than indicated by monthly SPI. Most stations did not have higher SPI variance with moving-window SPI compared to monthly SPI. The few that did were mainly with short calculation periods (i.e., for 1-month SPI) as opposed to long calculation periods (i.e., for 3-or 6- month SPI), where essentially no stations experienced higher variance. In nearly all cases, moving-window SPI resulted in a greater number of drought and pluvial events being detected.For most stations, 90- and 180-day approaches made these events up to twice as frequent, whereas the 30-day approach made them mainly 1.5x to 4x more frequent, depending on the severity threshold being used. Moving-window SPI also produced drought and pluvial durations that were longer than with monthly SPI, as much as 50 days longer in some cases. Overall, the differences between moving-window and monthly SPI tend to be larger for shorter monitoring periods.

ISBN: 9781088349182Subjects--Topical Terms:

2079509
Climate change.
Subjects--Index Terms:

Drought

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500 $a Advisor: Robeson, Scott.
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520 $a Improved understanding of the timing and duration of droughts and pluvials increases our ability to adapt while minimizing the financial cost of these natural disasters. Here, using daily precipitation data from across the United States, we develop a method that reformulates the traditional Standardized Precipitation Index (SPI) to use a moving-window approach. This reformulation allows for fine temporal-scale monitoring of drought and pluvial conditions, with the drought index updated daily. Using moving-window SPI, drought and pluvial periods reach greater extremes than indicated by monthly SPI. Most stations did not have higher SPI variance with moving-window SPI compared to monthly SPI. The few that did were mainly with short calculation periods (i.e., for 1-month SPI) as opposed to long calculation periods (i.e., for 3-or 6- month SPI), where essentially no stations experienced higher variance. In nearly all cases, moving-window SPI resulted in a greater number of drought and pluvial events being detected.For most stations, 90- and 180-day approaches made these events up to twice as frequent, whereas the 30-day approach made them mainly 1.5x to 4x more frequent, depending on the severity threshold being used. Moving-window SPI also produced drought and pluvial durations that were longer than with monthly SPI, as much as 50 days longer in some cases. Overall, the differences between moving-window and monthly SPI tend to be larger for shorter monitoring periods.
590 $a School code: 0093.
650 4 $a Climate change. $2 bicssc $3 2079509
650 4 $a Atmospheric sciences. $3 3168354
650 4 $a Water resources management. $3 794747
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653 $a Pluvial
653 $a SPI
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690 $a 0725
690 $a 0595
710 2 $a Indiana University. $b Geography. $3 1675492
773 0 $t Masters Abstracts International $g 81-04.
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793 $a English
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