Influence Of Mass Elevation Effect Factors On Latent And Sensible Heat Fluxes On The Tibetan Plateau

Mass elevation effect,which generates huge thermal forces(warming)due to the uplift of mountains and plateaus,changes the pattern of heat distribution in and around the mountains,and also changes the zonal pattern of the vertical zones of the mountains and shaping the non-zonality of vegetation and climate.Mass elevation effect,as a warming effect of mountains,alters the hydrothermal redistribution of mountains and provides continuous heating of the atmosphere through sensible heat transport and latent heat.The influence of mass elevation effect on the Tibet Plateau exceeds geographic zonality,causing a dramatic change in the zonality pattern of the natural element complex.The influence of mass elevation effect is so important that the study of heat change on the Tibetan plateau must consider the presence of mass elevation effect and the intensity and effect of its non-zonal effect.Therefore,this paper quantifies various mass elevation effect factors and constructs a model of the relationship between mass elevation effect factors and latent and sensible heat fluxes to explore the complexity of heat flux changes on the Tibetan Plateau.In this paper,based on ERA 5,GLDAS and MODIS data to obtain latent and sensible heat fluxes on the Tibetan Plateau from 2001 to 2020,and using observations from ten Flux Nets at different periods to validate the latent and sensible heat flux results obtained from the three datasets and verify the validity and reliability of the three datasets.After that,the spatial and temporal characteristics of latent and sensible heat fluxes in three data sets on the Tibetan Plateau from 2001 to 2020 were analyzed.Then based on SRTM DEM data,the topographic factors related to the mass elevation effect are extracted.Mass elevation effect factors Include: mountain base height,slope,slope,latitude,distance from the edge of large terrain,distance from the main ridgeline,base area,average elevation of the base,terrain undulation,roughness and depth of cut,etc.And analyze the spatial pattern of each factor.Then a random forest model approach was used to study the relationship between latent and sensible heat fluxes and each mountain effector on the Tibetan Plateau,and to analyze the trends of mass elevation effect factors on latent and sensible heat fluxes with key mass elevation effect factors.The main conclusions of this paper are as follows:(1)The accuracy verification of the latent and sensible heat fluxes of the ERA 5,GLDAS and MODIS datasets from the Flux Net observations on the Tibetan Plateau found that the correlation r values between the latent heat fluxes of the flux tower sites and the latent heat fluxes of the ERA 5 data were above 0.85,which were higher than the r values of the latent heat fluxes of the GLDAS and MODIS data.The RMSE of the sensible heat flux from the Flux Net site and the sensible heat flux from the ERA 5 data is 9.02 W/m2 minimum,which is smaller than that of 18.29 W/m2 for the GLDAS data and 57.89 W/m2 for the MODIS data,and the spatial distribution of latent and sensible heat fluxes from the ERA 5 data is continuous and has fewer null values.Therefore,this study analyzes the influence of mountain effectors on the latent and sensible heat fluxes based on the ERA 5 data.(2)The spatial and temporal analysis of latent and sensible heat fluxes on the Tibet Plateau from 2001 to 2020 shows that the latent heat fluxes vary in the range of 0-90 W/m2,showing an increasing trend from west to east,with the low value areas mainly distributed in the northern part of the plateau in the lowest elevation of the Qaidam Basin,and the high value areas mainly distributed in the southeastern scrub and densely forested areas of the plateau.The sensible heat flux of the Tibet Plateau varies in the range of 0-60 W/m2,showing a decreasing trend from west to east.The high value of sensible heat flux is mainly located in the southwestern region,and small parts of the Qaidam Basin in the north and the Hengduan Mountains in the southeast.In terms of temporal changes,the latent heat flux on the Tibet Plateau showed an overall increasing trend and the sensible heat flux showed a decreasing trend during the 20 years.Latent heat fluxes show a significant and highly significant increasing trend in the central and northern Kunlun Mountains and the northeastern Qilian Mountains of the plateau,and a significant and highly significant decreasing trend in the eastern and southern parts of the plateau and a small part of the western part.A significant and highly significant increasing trend of sensible heat flux was observed in the western Kunlun Mountains and Aljinshan region in the northwestern part of the plateau,and a significant and highly significant decreasing trend was observed in the northern part of the plateau,the Himalayas in the south,the Qilian Mountains in the northeastern part and the central-eastern part of the plateau.(3)The relationship between the mass elevation effect factors and latent heat and sensible heat fluxes based on the random forest model showed that the R2 of the random forest model based on the mass elevation effect factors and latent heat fluxes could reach 0.66(P<0.01),while the R2 of the model determination coefficient with sensible heat fluxes was 0.48(P<0.01).The mean elevation,depth of surface cut and slope of the basal partition had the greatest influence on the latent heat flux distribution,with the importance of 11.61,10.84 and 9.87,respectively.The distance between the basal partition and the large terrain boundary,the average elevation of the basal partition and the depth of surface cut were the three mass elevation effect factors with the greatest influence on the sensible heat flux,and their importance was 11.14,10.65 and 10.45,respectively.(4)According to the relationship between the key mass elevation effect factors and latent heat flux,it is known that the latent heat flux tends to decrease relatively with the increase of the average elevation of the base surface,and increases relatively with the increase of the cutting depth and slope.The high value area of latent heat flux is distributed in the southern,southeastern and eastern edges of the plateau where the average elevation of the basal surface is 2500-3000 m and the cutting depth is 90-115 m.The low value area of latent heat flux is distributed in the northwestern,southwestern and inner areas of the plateau where the average elevation of the basal surface is 5000-5500 m and the cutting depth is 20-35 m.In addition,the regions with a large share of significant increase in latent heat fluxes between 2001 and 2020 are most affected by the mean basal elevation.The regions with a large percentage of significant reductions in latent heat flux are strongly influenced by the average elevation of the basal surface and the depth of surface incision.(5)The relationship between key mass elevation effect factors and sensible heat fluxes shows that: the closer the boundary of the Tibetan Plateau,the greater the sensible heat flux is.The higher the average elevation of base surface,the greater the sensible heat flux.The greater the cutting depth,the lower the sensible heat flux.The zone of high values of sensible heat flux(33.11-33.84 W/m2)is distributed in the range of 0-100 km from the boundary of the Tibetan Plateau,as well as in the northwestern and southwestern regions of the plateau where the mean elevation of the basal plane is 5000-5500 m,and in the inner and northern regions of the plateau where the cutting depth is 20-35 m;The low value of sensible heat flux(23.54-26.52 W/m2)is distributed in the range of 500-600 km from the boundary of the Tibetan Plateau,as well as the southern and eastern edges of the plateau where the average elevation of the basal plane is 2500-3000 m,and the southern part of the plateau where the cutting depth is 115-130 m.In addition,the regions with a large percentage of both significant increases and significant decreases in sensible heat fluxes between 2001 and 2020 are most affected by the mean basal elevation.