Open AccessTemporal Patterns of Precipitation and Vegetation Variability over Zimbabwe during Extreme Dry and Wet Rainfall Seasons
Author(s) -
Seth Mberego,
Juliet Gwenzi
Publication year - 2014
Publication title -
journal of applied meteorology and climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.079
H-Index - 134
eISSN - 1558-8432
pISSN - 1558-8424
DOI - 10.1175/jamc-d-14-0006.1
Subject(s) - precipitation , normalized difference vegetation index , climatology , vegetation (pathology) , environmental science , dry season , wet season , period (music) , vegetation cover , climate change , physical geography , geography , geology , ecology , meteorology , oceanography , land use , biology , medicine , physics , cartography , pathology , acoustics
Climatic variability over southern Africa is a well-recognized phenomenon, yet knowledge about the temporal variability of extreme seasons is lacking. This study investigates the intraseasonal progression of extreme seasons over Zimbabwe using precipitation and normalized difference vegetation index (NDVI) data covering the 1981–2005 period. Results show that the greatest deficits/surpluses of precipitation occur during the middle of the rainfall season (January and February), and the temporal distribution of precipitation during extreme dry seasons seems to shift earlier than that of extreme wet seasons. Furthermore, anomalous wet (dry) conditions were observed prior to the development of extreme dry (wet) seasons. Impacts of precipitation variations on vegetation lag by approximately 1–2 months. The semiarid southern region experiences more variability of vegetation cover than do the northern and eastern regions. Three distinct temporal patterns of dry years were noted by considering the maximum NDVI level, the mid-postseason NDVI condition, and nested dry spells. The findings of this study emphasize that climate extremes ought not to be simply understood in terms of total seasonal precipitation, because they may have within them some nested distribution patterns that may have a strong influence on primary production.