Dataset of Comparative Observations for Land Surface Processes over the Semi-Arid Alpine Grassland against Alpine Lakes in the Source Region of the Yellow River

Thousands of lakes on the Tibetan Plateau(TP) play a critical role in the regional water cycle, weather, and climate. In recent years, the areas of TP lakes underwent drastic changes and have become a research hotspot. However, the characteristics of the lake-atmosphere interaction over the high-altitude lakes are still unclear, which inhibits model development and the accurate simulation of lake climate effects. The source region of the Yellow River(SRYR) has the largest outflow lake and freshwater lake on the TP and is one of the most densely distributed lakes on the TP. Since 2011,three observation sites have been set up in the Ngoring Lake basin in the SRYR to monitor the lake-atmosphere interaction and the differences among water-heat exchanges over the land and lake surfaces. This study presents an eight-year(2012–19), half-hourly, observation-based dataset related to lake–atmosphere interactions composed of three sites. The three sites represent the lake surface, the lakeside, and the land. The observations contain the basic meteorological elements,surface radiation, eddy covariance system, soil temperature, and moisture(for land). Information related to the sites and instruments, the continuity and completeness of data, and the differences among the observational results at different sites are described in this study. These data have been used in the previous study to reveal a few energy and water exchange characteristics of TP lakes and to validate and improve the lake and land surface model. The dataset is available at National Cryosphere Desert Data Center and Science Data Bank.

Numerical simulation of the climate effect of high-altitude lakes on the Tibetan Plateau

Lakes regulate the water and heat exchange between the ground and the atmosphere on different temporal and spatial scales. However, studies of the lake effect in the high-altitude Tibetan Plateau(TP) rarely have been performed until recently, and little attention has been paid to modelling of frozen lakes. In this study, the Weather Research and Forecasting Model(WRF v. 3.6.1) is employed to conduct three numerical experiments in the Ngoring Lake Basin(the original experiment, an experiment with a tuned model, and a no-lake experiment) to investigate the influences of parameter optimization on the lake simulation and of the high-altitude lake on the regional climate. After the lake depth, the roughness lengths, and initial surface temperature are corrected in the model, the simulation of the air temperature is distinctly improved. In the experiment using a tuned model, the simulated sensible-heat flux(H) is clearly improved, especially during periods of ice melting(from late spring to early summer) and freezing(late fall). The improvement of latent-heat flux(LE) is mainly manifested by the sharp increase in the correlation coefficient between simulation and observation, whereas the improvement in the average value is small. The optimization of initial surface temperature shows the most prominent effect in the first year and distinctly weakens after a freezing period. After the lakes become grassland in the model, the daytime temperature clearly increases during the freezing and melting periods; but the nocturnal cooling appears in other stages, especially from September to October. The annual mean H increases by 6.4 times in the regions of the Ngoring Lake and the Gyaring Lake, and the LE declines by 56.2%. The sum of H and LE increases from 71.2 W/m2(with lake) to 84.6 W/m2(no lake). For the entire simulation region, the sum of H and LE also increases slightly. After the lakes are removed, the air temperature increases significantly from June to September over the area corresponding to the two lakes, and an abnormal convergence field appears; at the same time, the precipitation clearly increases over the two lakes and surrounding areas.

Winter estimation of surface roughness length over eastern Qinghai-Tibetan Plateau

Based on the Monin-Obulchov similarity theory, a scheme was developed to calculate surface roughness length. Surface roughness length over the eastern Qinghai-Tibetan Plateau during the winter season was then estimated using the scheme and eddy covariance measurement data. Comparisons of estimated and measured wind speeds show that the scheme is feasible to calculate surface roughness length. The estimated roughness lengths at the measurement site during unfrozen, frozen and melted periods are 3.23x10(-3), 2.27x10(-3) and 1.92x10(-3) m, respectively. Surface roughness length demonstrates a deceasing trend with time during the winter season. Thereby, setting the roughness length to be a constant value in numerical models could lead to certain degree of simulation errors. The variation of surface roughness length may be caused by the change in land surface characteristic.

A descriptor for the local dust storm occurrence probability constituted by meteorological factors

Based on daily data sets of 17 meteorological factors during the period of 1954-2005 for 60 gauge stations distributed over Gansu Province of China and the corresponding dust storm records, the dust storm probabilities related to different classes of each factor have been calculated and analyzed. On the basis of statistical analysis, a meteorological descriptor quantifying the daily dust storm occurrence probability for each station, which is referred to as the Dust Storm Occurrence Probability Index （DSOPI）, has been effectively established. According to the statistical characteristics of DSOPI for each station, a feasible judging criterion for a dust storm event has been determined, which can greatly contribute to forecasting dust storms and completing the unavailable historic dust storm records. Meanwhile, the average daily dust storm probability related to each factor on the dust storm day for each station has been specially analyzed in detail, finally disclosing that, in general, the more signifi- cant one factor＇s influence on dust storms, the greater its contribution to them; and each factor＇s contribution clearly varies from place to place. Moreover, on average, maximum and mean wind speeds, maximum-speed wind direction, daily sunny hours, evaporation, mean and lowest relative humidity, lowest surface air pressure and vapor pressure contribute to dust storm events in Gansu Province most greatly in order among all the 17 involved factors.