The Effects of Anomalous Snow Cover of the Tibetan Plateau on the Surface Heating

On the basis of snow data and AWS (Automatic Weather Station) data obtained from the Tibetan Plateau in recent years (1993 to 1999), the features of sensible heat, latent heat and net long-wave radiations are estimated, and their variations in more-snow year (1997/ 1998) and less-snow year (1996/ 1997) are analyzed comparatively. The relationships between snow cover of the Tibetan Plateau and plateau’s surface heating to the atmospheric heating are also discussed. The difference between more-snow and less-snow year in spring is remarkably larger than that in winter. Therefore, the effect of anomalous snow cover of the Tibetan Plateau in winter on the plateau heating appears more clearly in the following spring of anomalous snow cover. Key words Tibetan Plateau - Snow cover - Effects - Surface heat fluxes This research was supported by the National Key Programme for Developing Basic Sciences G1998040900 (I), National Natural Science Foundation of China (40075018) and Sichuan Youth Science and Technology Fund.

Seasonal evolution of the dominant modes of the Eurasian snowpack and atmospheric circulation from autumn to the subsequent spring and the associated surface heat budget

This study investigates the seasonal evolution of the dominant modes of the Eurasian snowpack and atmospheric circulation from autumn to the subsequent spring using snow water equivalent （SWE）, snow cover frequency （SCF）, and 500 hPa geopotential height data. It is found that the Eurasian SWE/SCF and circulation dominant modes are stably coupled from autumn to the subsequent spring.The temporal coherence of the seasonal evolution of the dominant modes is examined.The seasonal evolution of the Eurasian circulation and SWE dominant modes exhibit good coherence, whereas the evolution of the Eurasian SCF dominant mode is incoherent during the autumn-winter transition season. This incoherence is associated with a sign-change in the SCF anomalies in Europe during the autumn-winter transition season, which is related to the wind anomalies over Europe. In addition, the surface heat budget associated with the Eurasian SWE/SCF and circulation dominant modes is analyzed. The sensible heat flux （SHF） related to the wind-induced thermal advection dominates the surface heat budget from autumn to the subsequent spring, with the largest effect during winter. The surface net shortwave radiation is mainly modulated by snow cover rather than cloud cover, which is estimated to be as important as, or likely superior to, the SHF for the surface heat budget during spring.The NCEP-NCAR surface heat flux reanalysis data demonstrate a consistency with the SWE/SCF and air temperature observational data, indicating a good capability for snow-atmosphere interaction analysis.

Significant Variations of Surface Albedo during a Snowy Period at Xianghe Observatory,China

Surface albedo over typical types of surfaces in the North China Plain was observed using a Multi-field Albedo Observation System before and after several snowfalls from 13 to 27 February 2005. Dramatic variations of the surface albedos of bare land, a frozen pond, and withered grassland during that period were analyzed. Under cloudy sky, the mean surface albedo of bare land was about 0.23, but it immediately rose to 0.85 when the surface was covered by fresh snow. The albedo decreased gradually to normal levels afterwards. The melting processes were different depending on the characteristics of the underlying surfaces. For example, over grassland the surface albedo was relatively lower after snowfall, and as a result, more solar energy could be absorbed and consequently the snow melting process was accelerated. Significant variations of surface albedo cannot be easily captured by satellite observations; therefore, detailed measurements of surface albedo and related parameters are essential for determining the impact of snow on the energy budget of the Earth.

Understanding the Soil Temperature Variability at Different Depths:Effects of Surface Air Temperature,Snow Cover,and the Soil Memory

The soil temperature(ST)is closely related to the surface air temperature(AT),but their coupling may be affected by other factors.In this study,significant effects of the AT on the underlying ST were found,and the time taken to propagate downward to 320 cm can be up to 10 months.Besides the AT,the ST is also affected by memory effects-namely,its prior thermal conditions.At deeper depth(i.e.,320 cm),the effects of the AT from a particular season may be exceeded by the soil memory effects from the last season.At shallower layers(i.e.,<80 cm),the effects of the AT may be blocked by the snow cover,resulting in a poorly synchronous correlation between the AT and the ST.In northeastern China,this snow cover blockage mainly occurs in winter and then vanishes in the subsequent spring.Due to the thermal insulation effect of the snow cover,the winter ST at layers above 80 cm in northeastern China were found to continue to increase even during the recent global warming hiatus period.These findings may be instructive for better understanding ST variations,as well as land−atmosphere interactions.

Spectral Reflectance Characteristics of Different Snow and Snow-Covered Land Surface Objects and Mixed Spectrum Fitting

The field spectroradiometer was used to measure spectra of different snow and snow-covered land surface objects in Beijing area.The result showed that for a pure snow spectrum,the snow reflectance peaks appeared from visible to 800 nm band locations;there was an obvious absorption valley of snow spectrum near 1 030 nm wavelength.Compared with fresh snow,the reflection peaks of the old snow and melting snow showed different degrees of decline in the ranges of 300～1 300,1 700～1 800 and 2 200～2 300 nm,the lowest was from the compacted snow and frozen ice.For the vegetation and snow mixed spectral characteristics,it was indicated that the spectral reflectance increased for the snow-covered land types(including pine leaf with snow and pine leaf on snow background), due to the influence of snow background in the range of 350～1 300 nm.However, the spectrum reflectance of mixed pixel remained a vegetation spectral characteristic.In the end,based on the spectrum analysis of snow,vegetation,and mixed snow/vegetation pixels,the mixed spectral fitting equations were established,and the results showed that there was good correlation between spectral curves by simulation fitting and observed ones(correlation coefficient R2=0.950 9).

Sensitivity of the Number of Snow Cover Days to Surface Air Temperature over the Qinghai-Tibetan Plateau

Based on the number of snow cover days （NSCDs） and homogenized surface air temperature data for the period 1951-2004, this study performs the quantitative analysis on the sensitivity of NSCDs to surface air temperature over the Qinghai-Tibetan Plateau （QTP）. Results show that both the extreme sensitivity and sensitivity under current climate are higher in the edge than in the central area of the QTP. There exists a strong negative correlation between station＇s elevation and critical temperature, at which the sensitivity reaches extremum. The negative correlation between the elevation and the extreme sensitivity is not as strong as the former one. Currently, the climatological temperatures in quite a few stations do not reach the critical stage. The sensitivity at these stations will become greater under the current background of climate warming, which means NSCDs will be more sensitive to surface air temperature.

Spatial variations of Pb,As,and Cu in surface snow along the transect from the Zhongshan Station to Dome A,East Antarctica

The spatial distributions of lead, arsenic, and copper （Pb, As, and Cu, respectively） in surface snow along the transect from the Zhongshan Station to Dome A, East Antarctica, are presented. The mean concentrations of Pb, As, and Cu are 1.04±1.56 pg/g, 0.39±0.08 pg/g, and 11.2±14.4 pg/g, respectively. It is estimated that anthropogenic contributions are dominant for Pb, As, and Cu. Spatially, Pb concentrations show an exponentially decreasing trend from the coast inland, while a moderate decreasing trend is observed for Cu concentrations in the coastal area （below 2,000 m above sea level （a.s.1.））. In the intermediate area （2,000-3,000 m a.s.1.）, the concentrations and enrichment factors of all these elements show high variability due to the complicated characteristics of climate and environment. On the inland plateau （above 3,000 m a.s.1.）, the high concentrations of As and Pb are induced by high deposition efficiency, the existence of polar stratospheric precipitation, and the different fraction deposition to East Antarctica. The extremely high concentrations with maximum values of 9.59 pg/g and 69.9 pg/g for Pb and Cu, respectively, are suggested to result mainly from local human activities at the station. Our results suggest that source, transport pathway, and deposition pattern, rather than distance from the coast or altitude, lead to the spatial distributions of Pb, As, and Cu; and it is further confirmed by spatial variations of the three metals deposited over the whole continent of Antarctica.

An Improved Method for Modeling Spatial Distribution of δD in Surface Snow over Antarctic Ice Sheet

Using the recent compilation of the isotopic composition data of surface snow of Antarctic ice sheet, we proposed an improved interpolation method of δD, which utilizes geographical factors （i.e., latitude and altitude） as the primary predictors and incorporates inverse distance weighting （IDW） technique. The method was applied to a high-resolution digital elevation model （DEM） to produce a grid map of multi-year mean δD values with lkm spatial resolution for Antarctica. The mean absolute deviation between observed and estimated data in the map is about 5.4‰, and the standard deviation is 9‰. The resulting δD pattern resembles well known characteristics such as the depletion of the heavy isotopes with increasing latitude and distance from coast line, but also reveals the complex topographic effects.

Impact of forcing data and land surface properties on snow simulation in a regional climate model:a case study over the Tianshan Mountains,Central Asia

Snow is a key variable that influences hydrological and climatic cycles.Land surface models employing snow physics-modules can simulate the snow accumulation and ablation processes.However,there are still uncertainties in modeling snow resources over complex terrain such as mountains.This study employed the National Center for Atmospheric Research’s Weather Research and Forecasting(WRF)model coupled with the Noah-Multiparameterization(Noah-MP)land surface model to run one-year simulations to assess its ability to simulate snow across the Tianshan Mountains.Six tests were conducted based on different reanalysis forcing datasets and different land surface properties.The results indicated that the snow dynamics were reproduced in a snow hydrological year by the WRF/Noah-MP model for all of the tests.The model produced a low bias in snow depth and snow water equivalent(SWE)regardless of the forcing datasets.Additionally,the underestimation of snow depth and SWE could be relatively alleviated by modifying the land cover and vegetation parameters.However,no significant improvement in accuracy was found in the date of snow depth maximum and melt rate.The best performance was achieved using ERA5 with modified land cover and vegetation parameters(mean bias=−4.03 mm and−1.441 mm for snow depth and SWE,respectively).This study highlights the importance of selecting forcing data for snow simulation over the Tianshan Mountains.

Methods for extraction of microorganism DNA from glacier surface snow

In order to thoroughly investigate the diversity of glacier microorganisms, four DNA extraction methods with differem lysis pat- terns were tested and two screened methods （the Bosshard-Bano method and the Zhou method） were optimized for the most ef- fective form of the filter membrane （cut vs. uncut）, the DNA extraction method, and the precipitation method. The two optimized methods were then compared with the commercial Mo-Bio DNA extraction kit, and the results showed that the kit was generally suitable for extraction of microorganism DNA fi＇om glacier surface snow. Procedurally, it was found that a modified Boss- hard-Bano method （i.e., cutting the filter membrane into pieces, using a specific lysis pattern [lysozyme （5 mg/mL）-protease K （ 1 mg/mL）-CTAB （ 1%）-SDS （ 1%）], performing the extraction only once by chloroform-isoamyl alcohol （24： 1）, and conducting DNA precipitation by pure ethanol） was also an effective and less expensive method for extraction of microorganism DNA from glacier surface snow.

Micro-particle in surface snow at Princess Elizabeth Land, East Antarctica

During the Austral summer of 1996/1997, the First Chinese Antarctic Inland Expedition reached the inland area about 330 km along the direction around 76°E from Zhongshan Station, and collected 84 surface snow samples at an interval of 4 km . Micro particle analysis of the samples indicates that the micro particle concentration apparently decreases with the increasing of altitude, and the amplitudes of micro particle concentration is much larger in the lower altitude than in the higher altitude. Further analysis of grain size distributions of micro particle, percentage of micro particles from different sources and variations with altitude suggest that micro particles in this area are from a considerably dominant source. Although this area is controlled by polar easterly wind and katabatic wind, transportation and deposition of the micro particles are mainly influenced by marine transportation in coastal area.

Impact of land cover change on land surface temperature: A case study of Spiti Valley

Land surface temperature(LST) is the skin temperature of the earth surface. LST depends on the amount of sunlight received by any geographical area. Apart from sun light, LST is also affected by the land cover, which leads to change in land surface temperature. Impact of land cover change(LCC) on LST has been assessed using Landsat TM5, Landsat 8 TIRS/OLI and Digital Elevation Model(ASTER) for Spiti Valley, Himachal Pradesh, India. In the present study, Spiti valley was divided into three altitudinal zones to check the pattern of changing land cover along different altitudes and LST was calculated for all the four land cover categories extracted from remote sensing data for the years of 1990 and 2015. Matrix table was used as a technique to evaluate the land cover change between two different years. Matrix table shows that as a whole, about 2,151,647 ha(30%) area of Spiti valley experienced change in land cover in the last 25 years. The result also shows vegetation and water bodies increased by 107,560.2 ha(605.87%) and 45 ha(0.98%), respectively. Snow cover and barren land decreased by 19,016.5 ha(23.92%) and 88,589(14.14%), during the study period. A significant increase has been noticed in vegetation amongst all land cover types. Minimum, maximum and mean LST for three altitudinal zones have been calculated. The mean LST recorded was 11℃ in 1990 but it rose by 2℃ and reached to 13℃ in 2015. Changes in LST were obtained for each land cover categories. The mean temperature of different land cover types was calculated by averaging value of all pixels of a given land cover types. The mean LST of vegetation, barren land, snow cover and water body increased by 6℃, 9℃, 1℃, and 7℃, respectively. Further, relationships between LST, Normalized Difference Snow Index(NDSI), and Normalised Difference Vegetation Index(NDVI) were established using Linear Regression.

Velocity of Surface Ice Flow on Amery Ice Shelf Determined with PPP

The main activities in the joint expedition between CHINARE and ANARE on Amery ice shelf are introduced. Five day continuous GPS observation data collected on the site which locates at the frontal part of Amery ice shelf was processed with precise point positioning (PPP) technology based on precise products from IGS. Velocity of the surface ice flow on Amery can be derived from the PPP solution. Preliminary result shows that the surface ice flow velocity of the site is 2.25 meters per day, the motion direction is northeastward. Semidiurnal oceanic tide and diurnal oceanic tide signal of that site can be recovered from the height variation series of PPP solution. These above solutions can be used to the consequent mass balance calculation.

Spatiotemporal variation of surface albedo and its influencing factors in northern Xinjiang, China

Surface albedo is a quantitative indicator for land surface processes and climate modeling,and plays an important role in surface radiation balance and climate change.In this study,by means of the MCD43A3 surface albedo product developed on the basis of Moderate Resolution Imaging Spectroradiometer(MODIS),we analyzed the spatiotemporal variation,persistence status,land cover type differences,and annual and seasonal differences of surface albedo,as well as the relationship between surface albedo and various influencing factors(including Normalized Difference Snow Index(NDSI),precipitation,Normalized Difference Vegetation Index(NDVI),land surface temperature,soil moisture,air temperature,and digital elevation model(DEM))in the north of Xinjiang Uygur Autonomous Region(northern Xinjiang)of Northwest China from 2010 to 2020 based on the unary linear regression,Hurst index,and Pearson's correlation coefficient analyses.Combined with the random forest(RF)model and geographical detector(Geodetector),the importance of the above-mentioned influencing factors as well as their interactions on surface albedo were quantitatively evaluated.The results showed that the seasonal average surface albedo in northern Xinjiang was the highest in winter and the lowest in summer.The annual average surface albedo from 2010 to 2020 was high in the west and north and low in the east and south,showing a weak decreasing trend and a small and stable overall variation.Land cover types had a significant impact on the variation of surface albedo.The annual average surface albedo in most regions of northern Xinjiang was positively correlated with NDSI and precipitation,and negatively correlated with NDVI,land surface temperature,soil moisture,and air temperature.In addition,the correlations between surface albedo and various influencing factors showed significant differences for different land cover types and in different seasons.To be specific,NDSI had the largest influence on surface albedo,followed by precipitation,land surface temperature,and soil moisture;whereas NDVI,air temperature,and DEM showed relatively weak influences.However,the interactions of any two influencing factors on surface albedo were enhanced,especially the interaction of air temperature and DEM.NDVI showed a nonlinear enhancement of influence on surface albedo when interacted with land surface temperature or precipitation,with an explanatory power greater than 92.00%.This study has a guiding significance in correctly understanding the land-atmosphere interactions in northern Xinjiang and improving the regional land-surface process simulation and climate prediction.

Impacts of Winter Eurasian Snow Cover Anomalies on the Surface Air Temperature Variability over West Asia

Previous research has shown that land surface thermal anomalies in West Asia(WA) can impact regional and global climate,particularly affecting China through the eastward propagation of wave trains.However,the factors driving these anomalies in WA have not been extensively studied.Based on the observation data,this work focuses on examining the impacts of Eurasian winter snow cover on winter surface air temperature(SAT) variability over WA from 1978/1979 to 2017/2018 and explores the underlying physical mechanisms.The results indicate that a crucial snow anomaly area extending from the Baltic Sea to eastern Ural significantly influences the winter SAT anomaly in WA.An anomalous increase(decrease) in winter snow cover in this key area corresponds to the anomalously warmer(cooler) SAT in WA.This relationship is primarily driven by the albedo effects of snow cover,where more(less)snow cover induces cooling(warming) of the overlying air,altering upper-level geopotential height and influencing the intensity,duration,and frequency of local blocking events.Additionally,changes in the air temperature above the key area modify the meridional temperature gradient(MTG) between high and low latitudes,affecting the mean zonal flow in the midlatitude.Diagnosis of the thermodynamic energy equation for SAT reveals that the combined effects of variations in blocking events in high latitudes and mean zonal flow in midlatitudes alter the advection of climatological temperature by anomalous winds,which is caused by the anomalous increase(decrease) of snow cover in the key area.Consequently,this leads to changes in cold advection transported to WA,contributing to the occurrence of a warmer(colder) SAT over WA in winter.

Autumn Snow Cover Variability over Northern Eurasia and Roles of Atmospheric Circulation

This study analyzes the variability of northern Eurasian snow cover（SC） in autumn and the impacts of atmospheric circulation changes. The region of large SC variability displays a southward shift from September to November, following the seasonal progression of the transition zones of surface air temperature（SAT）. The dominant pattern of SC variability in September and October features a zonal distribution, and that in November displays an obvious west-east contrast. Surface air cooling and snowfall increase are two factors for larger SC. The relative contribution of SAT and snowfall changes to SC, however, varies with the region and depends upon the season. The downward longwave radiation and atmospheric heat advection play important roles in SAT changes. Anomalous convergence of water vapor flux contributes to enhanced snowfall.The changes in downward longwave radiation are associated with those in atmospheric water content and column thickness.Changes in snowfall and the transport of atmospheric moisture determine the atmospheric moisture content in September and October, and the snowfall appears to be a main factor for atmospheric moisture change in November. These results indicate that atmospheric circulation changes play an important role in snow variability over northern Eurasia in autumn. Overall, the coupling between autumn Eurasian snow and atmospheric circulation may not be driven by external forcing.

Origin and advances in implementing blowing-snow effects in the Community Land Model

Snow cover on the Tibetan Plateau(TP)is closely related to regional and continental biological and hydrological processes.The vast snow cover,special climatic conditions,and sparse vegetative cover over the TP facilitate the occurrence of blowing snow,leading to substantial heterogeneities in the snow cover and great promotion in the moisture supply from the land surface to the overlying atmospheric boundary layer.However,blowing-snow processes are significantly misrepresented or even neglected in current models,which causes considerable uncertainties of numerical model simulations and leads to erroneous estimates of snow-related processes in mountainous terrain.We present in this paper a brief review of our work in the past 5 years to serve as a basis for further development and improvement of the land-surface model.These studies can be divided into three parts:detection of the problems,development of the land-surface model,and application of the coupled model over the TP(the logical framework is presented in Figure 1).The origin and advances in the development of a land-surface model with consideration of blowing-snow effects are described herein;and the importance of blowing-snow processes in the land-surface model,especially over the TP,is highlighted.We expect that the blowingsnow studies over the TP will play a key role in documenting and understanding the land-surface processes(LSPs)and the cryospheric changes over the TP.

Impacts of topographic factors on regional snow cover characteristics

At a local scale,snow cover is influenced by terrain properties,and it affects water availability across some arid and semiarid regions.This study aimed to quantify the spatial heterogeneity of snow cover due to topographic effects based on moderate-resolution image spectroradiometer(MODIS)daily snow cover products,processed with spatial and backward temporal filters.A snow-dominant region in the middle section of the northern Tianshan Mountains in China was selected,and the snow cover ratio(SCR)and the number of snow cover days(SCD)were investigated.The results suggest that MODIS images are biased toward underestimation of the snow cover in the study region,and the error is primarily manifested within the elevation band of 1500e2500 m.The snow cover is mainly affected by elevation,and snow mostly accumulates above 3800 m.In addition,the differences in SCR and SCD between the south-and north-facing slopes are more significant than those between the east-and west-facing slopes.Notably,the north-facing slopes have the maximum values of SCR and SCD,whereas the south-facing slopes have the minimum values of SCR and SCD.Furthermore,the impact of slope gradients on snow cover varies across seasons.Snow cover on a sloped surface decreases with the slope gradient during winter,while it tends to increase with the slope gradient during the other seasons.Overall,this study presents a useful perspective on the variance in regional snow cover and provides guidance for the water resources management of snow meltwater with different terrain features.

Snow Cover Area Estimation Using Radar and Optical Satellite Information

Obtaining the seasonal variation of snow cover in areas of the Argentinian Andes is important for hydrological studies and can facilitate proper planning of water resources, with regard to irrigation, supply, flood attenuation and hydroelectricity. Remote sensors that work in the visible and infrared wavelength range are operational tools for monitoring the snow in clear skies. However, microwave satellites are able to obtain data regardless of atmospheric conditions. The advantage of using radar images is that they are very useful to obtain highly accurate parameters such as snow moisture depth, density and water equivalent resulting in improved forecasting models. In this paper, we analyze an ERS-2 image of the Andes mountain range in the northern region of the Neuquén province, Patagonia, Argentina. The objective was to obtain the spatial distribution of wet and dry snow and to compare these results with data from optical sensors (LANDSAT) in order to understand the topographic variables that influence the spatial distribution of wet snow. Optical information from sensors like LANDSAT TM 5 was analyzed to obtain fractional and binary snow indexes during a passage simultaneously with radar data. Surface temperature is used to study the association between the different types of snow altitudinal ranges and surface temperature. In this paper, we selected a scene on October 8th 2005. The entire methodology was systematized in a code implemented in IDL language.

1974—2020年大兴安岭北部多年冻土区积雪变化及其与地面、空气温度的关系

基于大兴安岭北部多年冻土区5个气象站1974—2020年逐日气温、地面温度、积雪深度资料,利用气象统计方法分析了积雪气候特征及长期变化、积雪物候变化及积雪对温度的影响,结果表明:大兴安岭北部冻土区积雪深度年内变化呈单峰型,积雪深度最大出现在2月,平均17.9 cm,年积雪日数为161.5 d,积雪日数和积雪深度最大月份不重合。年均积雪深度为10.6 cm,最大积雪深度平均为22.6 cm,近47 a年均积雪深度呈弱的上升趋势。积雪初日显著推迟,终日显著提前,使得积雪持续日数明显缩短。研究区年均积雪深度和冷季地面−雪面温差呈较好的正相关,年最大积雪深度和冷季地面−雪面温差亦呈较好的正相关,积雪深度越大其对地面的隔热作用越大,年均积雪深度每增加1 cm,地面−雪面温差升高0.4211℃,年最大积雪深度每增加1 cm,地面−雪面温差升高0.2889℃,年均积雪深度对冷季地面−雪面温差的影响更大。