Satellite Observations of El Niño Impacts on Eurasian Spring Vegetation Greenness during the Period 1982–2015
Abstract
:1. Introduction
2. Materials and Methods
2.1. NDVI and Climate Data
2.2. Data Processing
2.3. Methods of Spatiotemporal Pattern Analysis
3. Linkage between El Niño and Spring NDVI over Eurasia
3.1. Spatiotemporal Patterns of Spring NDVI
3.2. Correlations between Spring NDVI and El Niño
3.3. Relationship between Spring NDVI Changes and Winter SSTA over Equatorial Pacific
4. Possible Physical Mechanisms for the Teleconnection between ERNDVI and El Niño
4.1. Climatic Impacts on ERNDVI
4.2. Impacts of Atmospheric Teleconnections of El Niño on Spring ERNDVI
5. Discussion
6. Conclusions
- The second EOF mode of spring NDVI, with the “negative-positive-negative” values varying from Europe, West Siberia to East Asia, explains about 12.1% (NDVIsn) and 9.9% (NDVI3g) of the total variance and its time-series is more correlated to the El Niño indices, especially Niño3, Niño3.4 and Niño4, than other climate indices.
- The spatial patterns of correlation coefficients between Eurasian NDVI and different Niño indices also show the patterns of the “negative-positive-negative” values varying from Europe, West Siberia to East Asia, which are similar to the spatial patterns of the second EOF modes obtained from spring Eurasian NDVI.
- Various Niño indices affect spring NDVI changes differently over different areas in Eurasia to various degrees. SSTA in the Niño4 region (CP El Niño events) have closer connections to European NDVI variations (west to 70°E), while SSTA in the Niño3 region (EP El Niño events) impacts primarily East Russian NDVI changes (90°–130°E, 50°–65°N) significantly. The influence of SSTA in the Niño3.4 region seems to have the combined effects of Niño3 and Niño4 indices on Eurasian NDVI variations.
- Temperature anomalies play a leading role as the bridge in explaining the relationship between NDVI and El Niño over Eurasia. The spatial patterns of SST and SAT are similar to those of SST and NDVI via the SVD analysis, exhibiting the “negative-positive-negative” values both in the SAT and NDVI fields from west to east over Eurasia along with an El Niño signal in the SST field.
- East Russia (80°–130°E, 50°–70°N) is identified as the key region with the strongest negative influences from El Niño on spring NDVI growth.
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Dataset | Provider | Sensor | Temporal Span | Spatial Resolution | Compositing |
---|---|---|---|---|---|
NDVI3g | GIMMS | AVHRR | 1981–2015 | 1/12 deg | MVC |
NDVIsn | STAR | AVHRR | 1981–present | 16 km | MVC smoothed |
Indices | NDVIsn_ts1 | NDVIsn_ts2 | NDVI3g_ts1 | NDVI3g_ts2 |
---|---|---|---|---|
Niño1+2 | −0.21 | −0.04 | −0.14 | −0.07 |
Niño3 | −0.19 | −0.22 * | −0.07 | −0.24 * |
Niño3.4 | −0.12 | −0.29 † | −0.05 | −0.30 † |
Niño4 | 0.01 | −0.30 † | 0.01 | −0.31 † |
BEST | −0.20 | −0.24 * | −0.14 | −0.21 |
NAO | 0.40 ‡ | 0.20 | 0.39 ‡ | 0.23 * |
AO | 0.51 ‡ | 0.27 * | 0.40 ‡ | 0.36 ‡ |
Time-series | Niño3 | Niño4 | Niño3.4 | Niño1+2 | NAO | AO |
---|---|---|---|---|---|---|
SST_NDVIsn | 0.97 * | 0.82 | 0.97 | 0.86 | / | / |
NDVI_NDVIsn | 0.51 * | 0.31 | 0.45 | 0.50 | −0.01 | −0.15 |
SST_NDVI3g | 0.94 * | 0.83 | 0.94 | 0.79 | / | / |
NDVI_NDVI3g | 0.43 * | 0.28 | 0.38 | 0.40 | −0.27 | −0.37 |
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Li, J.; Fan, K.; Zhou, L. Satellite Observations of El Niño Impacts on Eurasian Spring Vegetation Greenness during the Period 1982–2015. Remote Sens. 2017, 9, 628. https://doi.org/10.3390/rs9070628
Li J, Fan K, Zhou L. Satellite Observations of El Niño Impacts on Eurasian Spring Vegetation Greenness during the Period 1982–2015. Remote Sensing. 2017; 9(7):628. https://doi.org/10.3390/rs9070628
Chicago/Turabian StyleLi, Jing, Ke Fan, and Liming Zhou. 2017. "Satellite Observations of El Niño Impacts on Eurasian Spring Vegetation Greenness during the Period 1982–2015" Remote Sensing 9, no. 7: 628. https://doi.org/10.3390/rs9070628