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land surface phenology, Central Asia, regional climate patterns, large scale climate oscillation


Central Asia has been rapidly changing in multiple ways over the past few decades. Increases in temperature and likely decreases in precipitation in Central Asia as the result of global climate change are making one of the most arid regions in the world even more susceptible to large-scale droughts. Global climate oscillations, such as the El Ni ̃no–Southern Oscillation, have previously been linked to observed weather patterns in Central Asia. However, until now it has been unclear how the different climate oscillations act simultaneously to affect the weather and subsequently the vegetated land surface in Central Asia.We fit well-established land surface phenology models to two versions of MODIS data to identify the land surface phenology of Central Asia between 2001 and 2016. We then combine five climate oscillation indices into one regression model and identify the relative importance of each of these indices on precipitation, temperature, and land surface phenology, to learn where each climate index has the strongest influence. Our analyses illustrate that the North Atlantic Oscillation, the East Atlantic/West Russia pattern, and the AtlanticMulti-Decadal Oscillation predominantly influence temperature in the northern part of Central Asia.We also show that the Scandinavia index and the Multivariate ENSO index both reveal significant impacts on the precipitation in this region. Thus, we conclude that the land surface phenology across Central Asia is affected by several climate modes, both those that are strongly linked to far northern weather patterns and those that are forced by southern weather patterns, making this region a 'climate change hotspot’ with strong spatial variations in weather patterns.We also show that regional climate patterns play a significant role in Central Asia, indicating that global climate patterns alone might not be sufficient to project weather patterns and subsequent land surface changes in this region.

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Environmental Research Letters





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IOP Publishing Ltd


© 2018 The Author(s)

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Creative Commons Attribution 3.0 License
This work is licensed under a Creative Commons Attribution 3.0 License.