Assessing Gridded Precipitation and Air Temperature Products in the Ayakkum Lake, Central Asia

Abstract

We evaluated the performance of gridded precipitation and air temperature datasets near the Ayakkum Lake at the southern margin of Xinjiang, arid central Asia. Statistical measures were applied to assess these climate products on a monthly basis from 2013 to 2018. For monthly precipitation amount, the European Centre for Medium-Range Weather Forecasts Reanalysis 5 shows a good performance among the five products based on most statistical measures, and the China Meteorological Forcing Dataset can also be used as an alternative, especially for estimating the long-term annual mean. For monthly air temperature, WorldClim historical weather data are recommended because of the low mean absolute error, root mean square error and distance between indices of simulation and observation. Better spatial and temporal coverages of in-situ observations are still needed to produce an optimal correction scheme for the mountainous regions of arid central Asia.

CA-discharge: Geo-Located Discharge Time Series for Mountainous Rivers in Central Asia

“…We thus have to rely on publicly available gridded data products. We calculate average annual precipitation for each basin as mean over 7 gridded precipitation products (P mean ): CHELSA v2.1 (P CHELSA ), WorldClim v21 32 , CHPclim 34 , CRU 49 , GPM IMERG 50 , CHIRPS 51 , and APHRODITE 52 which all have shown acceptable performance in Central Asia [53][54][55][56][57] . Depending on the basin, the difference in precipitation can be up to 1'000 mm/a from one precipitation product to another.…”