The Tibetan Plateau (TP) has experienced rapid warming in recent decades, causing glaciers and permafrost to melt away and endangering water supply to surrounding regions. Forecasting future climate pattern in this region is, therefore, crucial. However, internal climate variation makes near-term climate prediction difficult. Researchers from the Chinese Academy of Sciences have now developed a post-processing procedure that can make realistic predictions from large ensembles of climate models, opening doors to water resource management in the regions around TP.
After the polar regions, the Tibetan Plateau (TP) contains the largest volume of glaciers. The region, also known as the “Third Pole” or the “Asian Water Tower” supplies meltwater from the glaciers to more than 2 billion people residing in river basins downstream. However, the region has undergone warming in recent decades, evidenced by melting glaciers and permafrost. This poses a substantial risk of water shortage for the surrounding regions. Predicting near-term future climate change in TP is, therefore, crucial to address this impending threat.
The warming of the Tibetan Plateau can severely affect water supply in the downstream regions, with devastating consequences for the population. Now, researchers have provided hope for water resource management in this region with their near-term climate change predictions. Photo Credit: Pixabay
One of the immediate goals is to use prediction models to obtain decadal climate information for the period 2021-2040. However, current near-term scenario-based climate projections do not account for internal climate variability and, consequently, suffer from large uncertainties in their predictions.
In a recent study published in Science Advances, researchers rose to the occasion, reliably forecasting the near-term variations in precipitation levels in the TP with a low uncertainty. To achieve this feat, they used historical rainfall observations to build a variance adjustment procedure that could accurately replicate hindcasts for the previous trends in the rainfall patterns. “The prediction reasonably captures the decrease from the 1960s to the 1990s and the rapid increase in the summer ITP rainfall in the late 1990s,” said
Dr. Tianjun Zhou, corresponding author of the study at the
Chinese Academy of Sciences, China.
The researchers were especially interested in the consequences of precipitation levels on the lake expansion in the region and focused on forecasting summer rainfall in the inner regions of the Tibetan Plateau (ITP) that have the largest number of natural lakes.
In the research, the researchers found that the summer ITP rainfall is highly predictable on multi-year time scales. To determine the reason for this observed predictability, the researchers examined the average summer sea surface temperatures of the subpolar gyre region (SPG) in the North Atlantic and found correlations with the rainfall patterns in the ITP. Linking the two phenomena together, Dr. Zhou said, “We see significant decadal scale warming over the SPG region, indicating that the decadal change of ITP summer rainfall is linked to the Atlantic multidecadal variabilities.”
Specifically, the researchers attributed the predictability in the summer ITP rainfall to the two-key upper troposphere circulation systems of the interdecadal Silk Road circulation system that spans the Eurasian geographic region. “Both the upper troposphere anticyclone over the northeast of the TP and the cyclone over the west TP are the key circulation systems that dominate the influence of interdecadal Silk Road pattern on summer ITP rainfall,” explained Dr. Zhou.
Using the large ensembles of climate models and the post-processing procedure, the researchers forecasted a 12.8% increase in rainfall for 2020-2027 compared to 1986-2005. The forecast shows that the rainfall will increase in the central region of the eastern TP but decrease in parts of southwestern TP.
These results suggest the need for contingency and emergency preparedness measures in the TP and could greatly inform water resource management in this ecologically vulnerable region.
Editor’s note: the study was supported by Pan-TPE, a TPE related science project.