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Modeling the Space-Time Variability ...
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Broman, Daniel Paul.
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Modeling the Space-Time Variability of Hydroclimate Over the Monsoon Regions of East and West Africa for Water Resources and Livestock Management.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Modeling the Space-Time Variability of Hydroclimate Over the Monsoon Regions of East and West Africa for Water Resources and Livestock Management./
作者:
Broman, Daniel Paul.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:
122 p.
附註:
Source: Dissertations Abstracts International, Volume: 80-12, Section: B.
Contained By:
Dissertations Abstracts International80-12B.
標題:
Climate Change. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13856446
ISBN:
9781392164877
Modeling the Space-Time Variability of Hydroclimate Over the Monsoon Regions of East and West Africa for Water Resources and Livestock Management.
Broman, Daniel Paul.
Modeling the Space-Time Variability of Hydroclimate Over the Monsoon Regions of East and West Africa for Water Resources and Livestock Management.
- Ann Arbor : ProQuest Dissertations & Theses, 2019 - 122 p.
Source: Dissertations Abstracts International, Volume: 80-12, Section: B.
Thesis (Ph.D.)--University of Colorado at Boulder, 2019.
This item must not be sold to any third party vendors.
There has been an increasing interest in and need for the application of climate information to address societal issues. Partially arising from the increasing confidence in anthropogenic climate change (Stocker et al. 2013) and partially from increasingly complex and resource-limited conditions, climate impacts are now considered in fields as diverse as natural hazards, public health, and agriculture. This research looks to show the utility of existing data analysis and statistical tools in providing actionable information to decision makers. Though this information is relevant in a wide variety of locations and conditions, the focus of this research has been on producing information for applications in the developing world. Climate variability at multiple timescales can have an outsized impact in the developing world given the often limited infrastructure, and weaker social and economic institutions (Field et al. 2014). There is a need for tools and analyses that translate climate information at coarse space and time scales to local scales where decisions of resource management are made. Through climate diagnostics, precipitation associated with the West African and East African monsoons show variations both subseasonally and interseasonally over the 20th and early 21st centuries. While prominent events including a wet period in the middle of the 20th century and a drought in the late 20th century have been well documented, this research highlights how this interseasonal variability can be linked to changes in large-scale teleconnections. In examining these teleconnections this research also notes that these teleconnections have entered into a new epoch. Tools that translate this information to address local issues have been developed. In West Africa, a stochastic weather generator can simulate the weather variables required to assess livestock heat stress and offer a means of forecasting and spatial modeling. This information can provide pastoralists better information during their seasonal migration. In East Africa, an understanding of precipitation variability and its coupling with the Madden-Julian Oscillation can be used to improve the sub-seasonal to seasonal forecasts of precipitation which can be used to improve water management.
ISBN: 9781392164877Subjects--Topical Terms:
894284
Climate Change.
Subjects--Index Terms:
Hydroclimate
Modeling the Space-Time Variability of Hydroclimate Over the Monsoon Regions of East and West Africa for Water Resources and Livestock Management.
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There has been an increasing interest in and need for the application of climate information to address societal issues. Partially arising from the increasing confidence in anthropogenic climate change (Stocker et al. 2013) and partially from increasingly complex and resource-limited conditions, climate impacts are now considered in fields as diverse as natural hazards, public health, and agriculture. This research looks to show the utility of existing data analysis and statistical tools in providing actionable information to decision makers. Though this information is relevant in a wide variety of locations and conditions, the focus of this research has been on producing information for applications in the developing world. Climate variability at multiple timescales can have an outsized impact in the developing world given the often limited infrastructure, and weaker social and economic institutions (Field et al. 2014). There is a need for tools and analyses that translate climate information at coarse space and time scales to local scales where decisions of resource management are made. Through climate diagnostics, precipitation associated with the West African and East African monsoons show variations both subseasonally and interseasonally over the 20th and early 21st centuries. While prominent events including a wet period in the middle of the 20th century and a drought in the late 20th century have been well documented, this research highlights how this interseasonal variability can be linked to changes in large-scale teleconnections. In examining these teleconnections this research also notes that these teleconnections have entered into a new epoch. Tools that translate this information to address local issues have been developed. In West Africa, a stochastic weather generator can simulate the weather variables required to assess livestock heat stress and offer a means of forecasting and spatial modeling. This information can provide pastoralists better information during their seasonal migration. In East Africa, an understanding of precipitation variability and its coupling with the Madden-Julian Oscillation can be used to improve the sub-seasonal to seasonal forecasts of precipitation which can be used to improve water management.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13856446
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