Precipitation Variability and Predictability over the Arabian Peninsula, Central Southwest Asia, and Southern Africa

• Main Author: Horan, Matthew Francis
• Format: Text
• Language: unknown
• Published: TRACE: Tennessee Research and Creative Exchange 2023
• Subjects: precipitation; climate variability; teleconnections; Arabian Peninsula; Southeast Africa; Central Southwest Asia; Atmospheric Sciences; Climate; Indian; South Atlantic Ocean
• Online Access: https://trace.tennessee.edu/utk_graddiss/8627; https://trace.tennessee.edu/context/utk_graddiss/article/9833/viewcontent/Horan_Dissertation____final.pdf

The Northern Hemisphere winter is the main rainy season for the Arabian Peninsula (AP), Central Southwest Asia (CSWA), and Southern Africa (SF), where precipitation predictability is limited or understudied. This dissertation research focuses on improving our understanding of these regions' wet-season precipitation characteristics and predictability. First, I have identified the AP's key moisture sources through a Lagrangian back-trajectory algorithm. Mid-latitude land and water bodies, such as the Mediterranean and Caspian Seas, are the primary moisture sources in the northern region. Areas further south rely on moisture transport from the Western Indian Ocean and the African continent. A significant drying trend in parts of the Peninsula is partly attributed to anomalies in moisture advection from the Congo Basin and South Atlantic Ocean. Next, I have identified key tropical and extratropical forcings that explain about three-quarters of winter precipitation variability in CSWA. Tropical forcing comes from an indirect ENSO forcing pathway, the dominant mode of precipitation variability in the Indian Ocean referred to as Indian Ocean Precipitation Dipole (IOPD). Extratropical forcing arises from a large-scale mode due to internal atmospheric variability. Seasonal forecasting systems effectively depict the characteristics of tropical forcing and its teleconnection with CSWA. Extratropical forcing spatial structure has also been skillfully represented. However, a lack of skill is noted in depicting its interannual seasonal variability and teleconnection with CSWA, which is the main driver of limited prediction skills in models. Lastly, I developed an empirical model using ENSO, Indian Ocean Dipole (IOD), and IOPD as precursors to investigate SF monsoon variability and predictability. I note that a reasonable skill in predicting SF monsoon precipitation can be achieved by preconditioning these modes as early as five months before the monsoon season. Seasonal forecasting systems that represent the interplay of ...