Unraveling the distribution patterns of near-surface temperature lapse rates in the Northwestern Kunlun Mountains

The near-surface temperature lapse rates for the core area of the Kunlun Mountains remain critically unresolved due to data scarcity.Here,we revealed the spatial and temporal patterns of nearsurface temperature lapse rate in the Kunlun Mountain regions based on both long-term meteorological records(1961-2017)and field surveys measured data(2012-2017).The results showed that(1)The near-surface temperature lapse rates(β;)has spatiotemporal distribution patterns on the Northwestern Kunlun Mountains(NWKM),and in complex terrain areas the complexity of the temperature-elevation relationship cannot be explained by the constant environmental temperature lapse rate(0.65℃/100 m)throughout alone.(2)Theβ;for the daily mean,minimum,and maximum temperature on the north slopes in the Kunlun mountain area are 0.41,0.47,and 0.37℃/100 m and on the Tiznafu River(TR)basin are 0.51,0.47 and 0.53℃/100 m,respectively.(3)The variations ofβ;for daily maximum and minimum temperature of the two regions exhibit similar monthly characteristics,which are lower in the winter and spring months than in other months.A greatest variability ofβ;for the daily mean,minimum,and maximum temperature appears in winter and a light variability ofβ;occurs in spring.The seasonal variability ofβ;for daily maximum temperature is greater than that for daily minimum temperature,and the seasonal variability ofβ;for daily average temperature has the smallest variability.(4)There is no significant trend of change occurred in theβ;of NWKM.(5)The spatial and temporal variations ofβ;for the NWKM are linked to the geographic differences and climate factors.The results of Grey Relational Analysis showed that theβ;distribution is mainly influenced by the wind speed and relative humidity of the NWKM.

Impact of temperature and precipitation lapse rate on hydrological modelling over Himalayan Gandak River Basin

The hydrology of Himalayan region is influenced by temperature lapse rate(TLAPS)and precipitation lapse rate(PLAPS).Therefore,hydrological modeling considering TLAPS and PLAPS is crucial to manage the water resources in these terrains.In this research,Himalayan Gandak River basin is considered as the study area where TLAPS and PLAPS vary significantly due to high altitude of Himalayas.To assess the impact of TLAPS and PLAPS on water balance components,Soil Water Assessment Tool(SWAT)model was calibrated(2000-2007)and validated(2008-2014)on daily time step for three projects i.e.,Reference Project(RP),Snowmelt Project(SP)and distributed elevation band snowmelt project(SWAT-ETISM).The analysis discloses that SWAT-ETISM model(which has TLAPS and PLAPS parameters)outperforms the RP and the SP models in predicting streamflow with improved statistical indicators R2=0.88,NSE=0.84 and PBIAS=11.9.Furthermore,it was observed that SWAT-ETISM model comprehensively improved the streamflow statistics by improving the snow water equivalent and water balance components through the consideration of TLAPS and PLAPS values for the region.Hence,the proposed SWAT-ETISM model can be used for estimation of the water budget at the high-altitude and data scarce alpine Himalayan regions and worldwide,where PLAPS and TLAPS are substantial due to altitudinal variation.

Elevational patterns of temperature and humidity in the middle Tianshan Mountain area in Central Asia

The vertical distribution of vegetation types along an elevational gradient in mountain areas largely depends on the elevational changes in air temperature and humidity. In this study, we presented the seasonal and diurnal variations in the elevational gradients of air temperature and humidity on the southern and northern slopes in the middle Tianshan Mountain Range using data collected throughout the year via HOBO data loggers. The measurements were conducted at 12 different elevations from 1548 to 3277 m from September 2004 to August 2005. The results showed that the annual mean air temperature decreased along the elevational gradients with temperature lapse rates of(0.71±0.20)°C/100 m and(0.59±0.05)°C/100 m on the northern and southern slopes, respectively. The annual mean absolute humidity significantly decreased with increasing elevation on the northern slope but showed no significant trend on the southern slope. The annual mean relative humidity did not show a significant trend on the northern slope but increased with increasing elevation on the southern slope. The mean air temperature lapse rate exhibited significant seasonal variation, which is steeper insummer and shallower in winter, and this value varied between 0.37°C/100 m and 0.75°C/100 m on the southern slope and between 0.30°C/100 m and 1.02°C/100 m on the northern slope. The mean absolute and relative humidity also exhibited significant seasonal variations on both slopes, with the maximum occurring in summer and the minimum occurring in winter or spring. The monthly diurnal range of air temperature on both slopes was higher in spring than in winter. The annual range of air temperature on the southern slope was higher than that on the northern slope. Our results suggest that significant spatiotemporal variations in humidity and temperature lapse rate are useful when analyzing the relationships between species range sizes and climate in mountain areas.

地理加权回归模型在地表气温直减率估算中的应用

The surface air temperature lapse rate(SATLR)plays a key role in the hydrological,glacial and ecological modeling,the regional downscaling,and the reconstruction of high-resolution surface air temperature.However,how to accurately estimate the SATLR in the regions with complex terrain and climatic condition has been a great challenge for researchers.The geographically weighted regression(GWR)model was applied in this paper to estimate the SATLR in China’s mainland,and then the assessment and validation for the GWR model were made.The spatial pattern of regression residuals which was identified by Moran’s Index indicated that the GWR model was broadly reasonable for the estimation of SATLR.The small mean absolute error(MAE)in all months indicated that the GWR model had a strong predictive ability for the surface air temperature.The comparison with previous studies for the seasonal mean SATLR further evidenced the accuracy of the estimation.Therefore,the GWR method has potential application for estimating the SATLR in a large region with complex terrain and climatic condition.