Regression Model for Estimating Vegetation Index in South Asia Using the ENSO-related Indices
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초록
This study identified statistical relationships between vegetation activity in South Asia and the tropical climate related to El Niño-Southern Oscillation (ENSO) events. Normalized difference vegetation index (NDVI) in South Asia is significantly correlated with the oceanic and atmospheric variables of the ENSO-related climate. NDVI in South Asia has significant positive correlations with upward long wave radiation flux at the top of atmosphere and sea level pressure in the NINO 3.4 region, and it has significant negative correlations with sea surface temperature and 850 hPa u-wind in the region. A negative relationship of vegetation activity in South Asia with ENSO (warm) climate is related to dry conditions in the South Asian region during the years of El Niño. Regression model for the seasonal NDVI in South Asia is developed using the advanced statistical methods, i.e., several stepwise procedures, a first-order autoregressive method, cross-validated estimation, and withholding data verification. 58% of the variance of NDVI in South Asia can be explained by two selected ENSOrelated predictors, which are ocean heat content and upward long wave radiation flux at the top of atmosphere in the NINO 3.4 region. Model results and verification by statistical inspections indicate the normality and independence of the residuals and good agreements between the estimated and observed NDVI in South Asia.
Abstract
This study identified statistical relationships between vegetation activity in South Asia and the tropical climate related to El Niño-Southern Oscillation (ENSO) events. Normalized difference vegetation index (NDVI) in South Asia is significantly correlated with the oceanic and atmospheric variables of the ENSO-related climate. NDVI in South Asia has significant positive correlations with upward long wave radiation flux at the top of atmosphere and sea level pressure in the NINO 3.4 region, and it has significant negative correlations with sea surface temperature and 850 hPa u-wind in the region. A negative relationship of vegetation activity in South Asia with ENSO (warm) climate is related to dry conditions in the South Asian region during the years of El Niño. Regression model for the seasonal NDVI in South Asia is developed using the advanced statistical methods, i.e., several stepwise procedures, a first-order autoregressive method, cross-validated estimation, and withholding data verification. 58% of the variance of NDVI in South Asia can be explained by two selected ENSOrelated predictors, which are ocean heat content and upward long wave radiation flux at the top of atmosphere in the NINO 3.4 region. Model results and verification by statistical inspections indicate the normality and independence of the residuals and good agreements between the estimated and observed NDVI in South Asia.
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