No abstract

Precipitation is an important natural resource relating to regional sustainability in arid central Asia, and the stable oxygen and hydrogen isotopes provide useful tracers to understand precipitation processes. In this study, we collected the hourly meteorological data at several stations on the southern slope of the Altai Mountains in arid central Asia, from March 2017 to June 2022, and examined the diurnal impact of below-cloud evaporation on stable isotope compositions of precipitation. During nighttime, the changes in isotope compositions below cloud base are generally weak. The enhanced impact of below-cloud evaporation can be found after around 15:00, and the impact is relatively strong in the afternoon, especially from 18:00 to 22:00. Summer and spring usually have a larger impact of below-cloud evaporation than autumn, and the winter precipitation is generally not influenced by below-cloud evaporation. On an annual basis, the differences in evaporation-led isotope changes between daytime and nighttime are 1.1‰ for stable oxygen isotope compositions, 4.0‰ for stable hydrogen isotope compositions and 4.7‰ for deuterium excess. The period from 2:00 to 10:00 shows relatively low sensitivity to relative humidity, and from 14:00 to 22:00 the impacts are sensitive. Considering the fluctuations of precipitation isotope compositions, the impact of below-cloud evaporation does not greatly modify the seasonal environmental signals.

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.