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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Quantifying seasonal and annual precipitation variability on San Salvador Island, Bahamas using surface observations and satellite estimates.

Wells, John Bryson 12 May 2023 (has links) (PDF)
San Salvador Island is a small Bahamian island located in the subtropics just north of the Tropic of Cancer. Due to its subtropical location, the island is influenced by both mid-latitude and tropical weather patterns. These weather patterns vary in scale from localized convective uplift to synoptic-scale systems. This study compares satellite-derived estimates of precipitation and rain gauge observations from June 2019 through September 2021 to evaluate the relationship between the two datasets. This study then uses the satellite-derived estimates of precipitation over a 20-year period to quantify annual and seasonal variability in precipitation on San Salvador. Corroborating past research, the island exhibits a bimodal pattern of precipitation during the year, but rainfall is highly variable across seasons and between years. Atmospheric fields from a reanalysis dataset indicate the North Atlantic subtropical high influences summertime rainfall, but a relationship between upper-level wind patterns and rainfall is less clear.
2

Surface and satellite perspectives on precipitation variability across San Salvador Island, Bahamas

Landress, Christana 01 May 2020 (has links)
Located in the subtropical central-eastern Bahamas, San Salvador Island is impacted by both synoptic-scale weather systems as well as local features and the North Atlantic Subtropical High. This study explores rainfall variability via one year of daily rain gauge observations in relation to daily weather patterns identified from 18 UTC surface analyses. Satellite-derived rainfall estimates are then compared to gauge observations to look at days when gauge data was missing. Though non-synoptic classifications comprised 61.1% of the days and synoptic classifications comprised 38.9% of the days, more rainfall was produced by synoptic days. Unlike other studies done on San Salvador, this study uses multiple observations—in situ, surface analyses, and satellite—to further our understanding of San Salvador’s rainfall. This study also establishes methods to explore synoptic and non-synoptic impacts on the island’s rainfall using additional years as more rain gauge data become available.

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