Abstract
Considering the noncore region influenced by El Nino-Southern Oscillation (ENSO) events, China is hardly investigated in terms of the vegetation variation during the ENSO period.Therefore, this study focused on increasing knowledge of vegetation growth and variation during the ENSO period.The novelty of this paper is introduced the moving window correlation analysis method to determine the thresholds of vegetation response to sea surface temperature anomaly (SSTa) and southern oscillation index (SOI) and analyze the main reasons for such variations.China was divided into seven areas based on different weather conditions, and the variations in vegetation growth in various areas during the ENSO period were analyzed. The response of vegetation to ENSO events in China was analyzed from the perspectives of precipitable water vapor (PWV), temperature, and precipitation, thereby revealing the interplay of multi-factors on vegetation growth.The main conclusions include (1) a positive vegetation response to El Nino exists all over China with thresholds of SSTa ≥ 1.87°C and SOI ≤ -3.27hPa, whereas a negative response of vegetation variation to La Nina exists with thresholds of SSTa ≤ -1.05°C and SOI ≥ 1.7hPa; (2) the correlations (p <; 0.05) of PWV to normalized difference vegetation index (NDVI) (PWV-NDVI), temperature-NDVI, and precipitation-NDVI reached 0.84, 0.86, and 0.68, respectively, and PWV, temperature, and precipitation were negatively/positively abnormal during El Nino/La Nina periods; (3) in coastal areas of Southeast China, correlations between NDVI and PWV/temperature/ precipitation are poor and the opposite anomalies of PWV/temperature/ precipitation existed when compared to other areas of China.
Highlights
In the past few decades, China has witnessed phenomena closely related to El Niño-Southern Oscillation (ENSO) events, including an upward trend in surface temperature, a weakening trend of Asian monsoon, and southern flooding and northern drought of precipitation [1], [2]
The frequency of tropical cyclone landings in Mainland China during La Niña period was higher than that during the non-La Niña period, a negative anomaly of precipitation and precipitable water vapor (PWV) still existed in the southeastern coastal areas of China (Figures 7(b and f) and 11), thereby indicating that precipitation and PWV were significantly lower than that in normal years during the non-tropical cyclone landing period. These results further proved the conclusion obtained above, that is, (1) precipitation and PWV increased, and solar radiation decreased in the southeastern coastal areas of China during El Niño period, thereby leading to the negative response of vegetation growth; (2) precipitation and PWV decreased, and solar radiation increased in the southeastern coastal areas of China during
The intensities of El Niño and La Niña events were first determined by using sea surface temperature anomaly (SSTa) and southern oscillation index (SOI)
Summary
In the past few decades, China has witnessed phenomena closely related to El Niño-Southern Oscillation (ENSO) events, including an upward trend in surface temperature, a weakening trend of Asian monsoon, and southern flooding and northern drought of precipitation [1], [2]. Several studies have been performed on ENSO and vegetation growth, few experiments are available on vegetation changes in China because the country is not a core region influenced by ENSO events. The impact of ENSO events on vegetation growth in different geographical regions of China and the extent to which ENSO intensity affects China remain unclear. Changes in precipitable water vapor (PWV), temperature, and precipitation were analyzed based on the actual situation of typhoon landings in China during the ENSO period. Mainland China features remarkable geographical differences, thereby causing varied distribution of atmospheric water vapor throughout the country with high and low content in the southeast coast and northwest inland region, respectively. To further reflect the influence of ENSO events on vegetation growth in China, the bilinear interpolation method was used to obtain the NDVI value of each meteorological station. Tial resolution of ERA-Interim data used in this paper was 0.125◦ × 0.125◦, and the grid PWV data were interpolated into the location of meteorological stations
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