C23A-0764
Aridity changes over the Tibetan Plateau in recent three decades

Tuesday, 15 December 2015
Poster Hall (Moscone South)
Li Xia and Yanhong Gao, CAREERI/CAS Cold and Arid Regions Environmental and Engineering Research Institute, Lanzhou, China
Abstract:
The Tibetan Plateau (TP) is the highest and widest plateau in the world and it plays an important role in Asian and global climate and climate impacts. The ecosystems over the TP are rather fragile. Studies show the terrestrial changes in the TP in recent decades including desertification (Dong et al. 2012; Gao et al. 2014, 2015a, 2015b; Li et al. submitted; Gao et al. submitted). Arid climate plays a vital role in the presence of desertication. Aridity, as defined by the shortage of moisture, is a climatic phenomenon that is based on average climatic conditions over a region. Numerous indices have been proposed to quantify the degree of dryness of a climate at a given location. Ratio of precipitation and potential evapotranspiration (P/PET) describing the degree of moisture deficiency at a given location is worldwide used.

In this study, P/PET was calculated to explore the aridity changes over the TP (Gao et al. 2015a). PET in 1979-2011 was calculated using the Penman-Monteith formulation based on the observed meteorological records at 83 China Meteorological Administration (CMA) stations in the TP. And the dominate factors on P/PET change are analyzed. The results indicate that stations located in the northwestern TP are becoming wetter and half of the stations in the eastern TP are becoming drier in recent three decades. The change patterns of precipitation, sunshine duration and diurnal temperature range have great influences on aridity change pattern especially precipitation. Precipitation is the dominant factors that affect aridity change on TP.

How the aridity will change in the future under the warming has drawn great attention given the importance of the TP in the water resources in the Asia. GCMs output from CMIP5 could do the projection but with spread biases. Dynamic downscaling (DDM) could somehow reduce the local biases of the GCMs (Gao et al. 2011, 2015c). P/PET projections will be calculated through the bias corrected GCMs and DDM outputs.