Interannual variability in dry and wet spell characteristics over Zambia

Climate Research

S. Hachigonta¹  C. J. C. Reason¹ 

关键词: Dry spell frequency;    Zambia;    ENSO;    Interannual variability;   

DOI  :  10.3354/cr032049

来源: Inter-Research Science Publishing

【 摘 要 】

ABSTRACT: We studied the variability of dry and wet spell frequency over Zambia during the core of the rainy season (December to February, DJF), and associated circulation anomalies. Zambia’s large rural population depends critically on rain-fed agriculture; in general, the southern part of Zambia is prone to a high number of dry spells during DJF, and to wet spells of short duration, while the northern regions of the country more typically have a large number of wet spells during DJF, which can lead to flooding. Good rainfall over southern Zambia is typically associated with low level convergence of moisture emanating from the tropical southeast Atlantic Ocean and the tropical western Indian Ocean. During seasons with increased numbers of dry spells over Zambia, low level easterly anomalies typically exist over Zambia, thereby reducing moisture from the tropical southeast Atlantic. Seasons with reduced dry spell frequency and more wet spells tend to be characterised by low level westerly anomalies over southern Angola and western Zambia. Furthermore, DJF seasons occurring during the mature phase of El Niño (La Niña) events tend to show above (below) average dry spell frequency. All El Niño seasons during the period of study showed reduced frequency of wet spells over Zambia, but not all La Niña events were associated with above average wet spell frequency. In fact, wet spell frequency over Zambia during several neutral seasons was greater than that observed during some La Niña events. A relatively strong relationship between anomalies in dry spell frequency and Niño 3.4 sea surface temperature (SST) was found. Relationships with Indian Ocean SST anomalies were also explored, but these were weaker than those found for Niño 3.4 SST.

【 授权许可】

Unknown