VARIATIONS OF SNOW DEPTH AND DURATION IN THE SWISS ALPS OVER THE LAST 50 YEARS: LINKS TO CHANGES IN LARGE-SCALE CLIMATIC FORCINGS

A study of snow statistics over the past 50 years at several climatological stations in the Swiss Alps has highlighted periods in which snow was either abundant or not. Periods with relative low snow amounts and duration are closely linked to the presence of persistent high surface pressure fields over the Alpine region during late Fall and in Winter. These high pressure episodes are accompanied by large positive temperature anomalies and low precipitation, both of which are unfavorable for snow accumulation during the Winter. The fluctuations of seasonal to annual pressure in the Alpine region is strongly correlated with anomalies of the North Atlantic Oscillation index, which is a measure of the strength of the westerly flow over the Atlantic. This implies that large-scale forcing, and not local or regional factors, plays a dominant role in controling the timing and amount of snow in the Alps, as evidenced by the abundance or dearth of snow over several consecutive years. Furthermore, since the mid-1980s, the length of the snow season and snow amount have substantially decreased, as a result of pressure fields over the Alps which have been far higher and more persistent than at any other time this century. A detailed analysis of a number of additional Alpine stations for the last 15 years shows that the sensitivity of the snow-pack to climatic fluctuations diminishes above 1750 m. In the current debate on anthropogenically-induced climatic change, this altitude is consistent with other studies and estimates of snow-pack sensitivity to past and projected future global warming.     

Snow measurement techniques for land-surface-atmosphere exchange studies in boreal landscapes

Summary  Snow has been studied widely in hydrology for many decades whereas recent meteorological interest in snow is caused by increased emphasis on high latitudes and wintertime in climate-change research as well as by the need to improve weather-forecast models during these conditions. Ground-based measurements of snow properties are needed both to improve understanding of surface-atmosphere exchange processes and to provide ground truth to new remote-sensing algorithms. This justifies a review of techniques to measure snow in combination with establishment of criteria for the suitability of the methods for process studies. This review assesses the state-of-art in ground-based snow-measurement techniques in the end of the 1990s in view of their accuracy, time resolution, possibility to automate, practicality and suitability in different terrain. Methods for snow-pack water equivalent, depth, density, growth, quality, liquid-water content and water leaving the snow pack are reviewed. Synoptic snow measurements in Fennoscandian countries are widely varying and there is no single standard on which process-related studies can build. A long-term, continuous monitoring of mass and energy properties of a snow cover requires a combination of point-measurement techniques. Areally representative values of snow properties can be achieved through a combination of automatically collected point data with repeated manual, areally covering measurements, remote-sensing data and digital elevation models, preferably in a GIS framework. Received August 27, 1999     

Simulation Of Blowing Snow In The Canadian Arctic Using A Double-Moment Model

We describe in this paper the development of a double-moment modelof blowing snow and its application to the Canadian Arctic. Wefirst outline the formulation of the numerical model, whichsolves a prognostic equation for both the blowing snow mixingratio and total particle numbers, both moments of particles thatare gamma-distributed. Under idealized simulations, the modelyields realistic evolutions of the blowing snow particledistributions, transport and sublimation rates as well as the thermodynamic fields at low computational costs. A parametrizationof the blowing snow sublimation rate is subsequently derived. The model and parametrization are then applied to a Canadian Arctictundra site prone to frequent blowing snow events. Over a period of210 days during the winter of 1996/1997, the near-surfacerelative humidity consistently approaches saturationwith respect to ice. These conditions limit snowpack erosion byblowing snow sublimation to 3 mm snow water equivalent (swe)with surface sublimation removing an additional 7 mm swe.We find that our results are highly sensitiveto the proper assimilation of the humidity measurements and the evolving thermodynamic fields in the atmospheric boundary layer during blowingsnow. These factors may explain the lower values of blowing snow sublimationreported in this paper than previously published for the region.     

Snow contribution to springtime atmospheric predictability over the second half of the twentieth century

A set of global atmospheric simulations has been performed with the ARPEGE-Climat model in order to quantify the contribution of realistic snow conditions to seasonal atmospheric predictability in addition to that of a perfect sea surface temperature (SST) forcing. The focus is on the springtime boreal hemisphere where the combination of a significant snow cover variability and an increasing solar radiation favour the potential snow influence on the surface energy budget. The study covers the whole 1950?C2000 period through the use of an original snow mass reanalysis based on an off-line land surface model and possibly constrained by satellite snow cover observations. Two ensembles of 10-member AMIP-type experiments have been first performed with relaxed versus free snow boundary conditions. The nudging towards the monthly snow mass reanalysis significantly improves both potential and actual predictability of springtime surface air temperature over Central Europe and North America. Yet, the impact is confined to the lower troposphere and there is no clear improvement in the predictability of the large-scale atmospheric circulation. Further constraining the prescribed snow boundary conditions with satellite observations does not change much the results. Finally, using the snow reanalysis only for initializing the model on March 1st also leads to a positive impact on predicted low-level temperatures but with a weaker amplitude and persistence. A conditional skill approach as well as some selected case studies provide some guidelines for interpreting these results and suggest that an underestimated snow cover variability and a misrepresentation of ENSO teleconnections may hamper the benefit of an improved snow initialization in the ARPEGE-Climat model.     

RESPONSE OF THE ATMOSPHERIC GENERAL CIRCULATION TO WINTER SNOW COVER ANOMALY

In this paper,the response of the atmospheric general circulation to winter anomalous snowcover was investigated through observations studies and model simulation.Results from the observations show that:(1)the anomalous winter snow cover in theextratropics of Eurasian Continent bears an intimate relation to the contemporary atmosphericgeneral circulation.The positive anomaly of winter snow cover is usually accompanied by positiveatmospheric EUP teleconnection pattern and stronger East Asian winter monsoon:or vice versa.(2)The linkage between them suggests that the abnormal winter snow cover has an importantimpact on winter atmospheric general circulation.The anomalous snow cover pattern can lead tothe anomaly of winter atmospheric EUP teleconnection pattern and thus influence East AsianWinter monsoon.With NCAR CCM2 including BATS land surface scheme,three groups of experiments wereperformed to examine the atmospheric response to the anomalous snow cover pattern and explorethe relevant mechanism.Simulated results agree well with the observations,which testify thesignificant response of the atmosphere to snow cover anomaly.It is found that the radiative coolinginduced by anomalous snow cover plays an important role in above processes,and the feedback oflong-wave radiation can not be neglected.     

RESPONSE OF THE ATMOSPHERIC GENERAL CIRCULATION TO WINTER SNOW COVER ANOMALY*

In this paper,the response of the atmospheric general circulation to winter anomalous snow cover was investigated through observations studies and model simulation.Results from the observations show that:(1)the anomalous winter snow cover in the extratropics of Eurasian Continent bears an intimate relation to the contemporary atmospheric general circulation.The positive anomaly of winter snow cover is usually accompanied by positive atmospheric EUP teleconnection pattern and stronger East Asian winter monsoon:or vice versa.(2)The linkage between them suggests that the abnormal winter snow cover has an important impact on winter atmospheric general circulation.The anomalous snow cover pattern can lead to the anomaly of winter atmospheric EUP teleconnection pattern and thus influence East Asian Winter monsoon.With NCAR CCM2 including BATS land surface scheme,three groups of experiments were performed to examine the atmospheric response to the anomalous snow cover pattern and explore the relevant mechanism.Simulated results agree well with the observations,which testify the significant response of the atmosphere to snow cover anomaly.It is found that the radiative cooling induced by anomalous snow cover plays an important role in above processes,and the feedback of long-wave radiation can not be neglected.     

Snow pack in the Swiss Alps under changing climatic conditions: an empirical approach for climate impacts studies

Summary ?In many instances, snow cover and duration are a major controlling factor on a range of environmental systems in mountain regions. When assessing the impacts of climatic change on mountain ecosystems and river basins whose origin lie in the Alps, one of the key controls on such systems will reside in changes in snow amount and duration. At present, regional climate models or statistical downscaling techniques, which are the principal methods applied to the derivation of climatic variables in a future, changing climate, do not provide adequate information at the scales required for investigations in which snow is playing a major role. A study has thus been undertaken on the behavior of snow in the Swiss Alps, in particular the duration of the seasonal snow-pack, on the basis of observational data from a number of Swiss climatological stations. It is seen that there is a distinct link between snow-cover duration and height (i.e., temperature), and that this link has a specific “signature” according to the type of winter. Milder winters are associated with higher precipitation levels than colder winters, but with more solid precipitation at elevations exceeding 1,700–2,000 m above sea-level, and more liquid precipitation below. These results can be combined within a single diagram, linking winter minimum temperature, winter precipitation, and snow-cover duration. The resulting contour surfaces can then be used to assess the manner in which the length of the snow-season may change according to specified shifts in temperature and precipitation. While the technique is clearly empirical, it can be combined with regional climate model information to provide a useful estimate of the length of the snow season with snow cover, for various climate-impacts studies. Received May 14, 2002; revised August 12, 2002; accepted August 17, 2002     

Assessing the Impacts of Eurasian Snow Conditions on Climate Predictability with a Global Climate Model

On the basis of two ensemble experiments conducted by a general atmospheric circulation model (Institute of Atmospheric Physics nine-level atmospheric general circulation model coupled with land surface model, hereinafter referred to as IAP9L_CoLM), the impacts of realistic Eurasian snow conditions on summer climate predictability were investigated. The predictive skill of sea level pressures (SLP) and middle and upper tropospheric geopotential heights at mid-high latitudes of Eurasia was enhanced when improved Eurasian snow conditions were introduced into the model. Furthermore, the model skill in reproducing the interannual variation and spatial distribution of the surface air temperature (SAT) anomalies over China was improved by applying realistic (prescribed) Eurasian snow conditions. The predictive skill of the summer precipitation in China was low; however, when realistic snow conditions were employed, the predictability increased, illustrating the effectiveness of the application of realistic Eurasian snow conditions. Overall, the results of the present study suggested that Eurasian snow conditions have a significant effect on dynamical seasonal prediction in China. When Eurasian snow conditions in the global climate model (GCM) can be more realistically represented, the predictability of summer climate over China increases.     

一个简单的雪晶辐射参数化方案及雪晶辐射对中尺度降水的影响

文章提出一个简单的雪晶辐射性质参数化方案, 并利用1998年6月8日华南暴雨资料研究了雪晶的辐射性质对于中尺度降水的影响。结果表明:雪晶的辐射性质对中尺度降水的影响是不可忽略的, 白天尤为显著; 它能够明显地改变中尺度降水的局部特征, 特别是降水中心的强度和位置, 而对降水的分布影响不大。因此, 建立独立的雪晶辐射参数化对提高中尺度模式对中尺度降水的预报能力是必要的。     

Seasonal Variations in Drag Coefficient over a Sastrugi-Covered Snowfield in Coastal East Antarctica

The surface of windy Antarctic snowfields is subject to drifting snow, which leads to the formation of sastrugi. In turn, sastrugi contribute to the drag exerted by the snow surface on the atmosphere and hence influence drifting snow. Although the surface drag over rough sastrugi fields has been estimated for individual locations in Antarctica, its variation over time and with respect to drifting snow has received little attention. Using year-round data from a meteorological mast, seasonal variations in the neutral drag coefficient at a height of 10 m \((C_{{ DN}10})\) in coastal Adelie Land are presented and discussed in light of the formation and behaviour of sastrugi based on observed aeolian erosion patterns. The measurements revealed high \(C_{{ DN}10} \) values \((\ge \) 2 \(\times \) 10\(^{-3})\) and limited drifting snow (35% of the time) in summer (December–February) versus lower \(C_{{ DN}10} \) values \((\approx \) 1.5 \(\times \) \(10^{-3})\) associated with more frequent drifting snow (70% of the time) in winter (March–November). Without the seasonal distinction, there was no clear dependence of \(C_{{ DN}10} \) on friction velocity or wind direction, but observations revealed a general increase in \(C_{{ DN}10} \) with rising air temperature. The main hypothesis defended here is that higher temperatures increase snow cohesion and the development of sastrugi just after snow deposition while inhibiting the sastrugi streamlining process by raising the erosion threshold. This increases the contribution of the sastrugi form drag to the total surface drag in summer when winds are lighter and more variable. The analysis also showed that, in the absence of erosion, single snowfall events can reduce \(C_{{ DN}10} \) to \(1\,\times \,10^{-3}\) due to the burying of pre-existing microrelief under newly deposited snow. The results suggest that polar atmospheric models should account for spatial and temporal variations in snow surface roughness through a dynamic representation of the sastrugi form drag.     

A New Triple-Moment Blowing Snow Model

This paper presents a new triple-moment blowing snow model PIEKTUK-T by including predictive equations for three moments of the gamma size distribution. Specifically, predictive equations for the total number concentration, total mass mixing ratio, and total radar reflectivity for blowing snow are included. Tests in the context of idealized experiments and observed case studies demonstrate that the triple-moment model performs better than the double-moment model PIEKTUK-D in predicting the evolution of the number concentration, mixing ratio, shape parameter, and visibility in blowing snow, provided that the fall velocities for the total number concentration, mass mixing ratio, and radar reflectivity are weighted by the same order of the respective moments in both models. The power law relationship between the radar reflectivity factor and particle extinction coefficient found in PIEKTUK-T is consistent with one observed in snow storms. Coupling of the triple-moment blowing snow model to an atmospheric model would allow realistic studies of the effect of blowing snow on weather and climate.     

A Bulk Blowing Snow Model

We present in this paper a simple and computationally efficient numerical model that depicts a column of sublimating, blowing snow. This bulk model predicts the mixing ratio of suspended snow by solving an equation that considers the diffusion, settling and sublimation of blowing snow in a time-dependent mode. The bulk model results compare very well with those of a previous spectral version of the model, while increasing its computational efficiency by a factor of about one hundred. This will allow the use of the model to estimate the effects of blowing snow upon the atmospheric boundary layer and to the mass balance of such regions as the Mackenzie River Basin of Canada.     

The effect of snow on Antarctic sea ice simulations in a coupled atmosphere-sea ice model

 The effect of a snow cover on sea ice accretion and ablation is estimated based on the ‘zero-layer’ version sea ice model of Semtner, and is examined using a coupled atmosphere-sea ice model including feedbacks and ice dynamics effects. When snow is disregarded in the coupled model the averaged Antarctic sea ice becomes thicker. When only half of the snowfall predicted by the atmospheric model is allowed to land on the ice surface sea ice gets thicker in most of the Weddell and Ross Seas but thinner in East Antarctic in winter, with the average slightly thicker. When twice as much snowfall as predicted by the atmospheric model is assumed to land on the ice surface sea ice also gets much thicker due to the large increase of snow-ice formation. These results indicate the importance of the correct simulation of the snow cover over sea ice and snow-ice formation in the Antarctic. Our results also illustrate the complex feedback effects of the snow cover in global climate models. In this study we have also tested the use of a mean value of 0.16 Wm^-1 K^-1 instead of 0.31 for the thermal conductivity of snow in the coupled model, based on the most recent observations in the eastern Antarctic and Bellingshausen and Amundsen Seas, and have found that the sea ice distribution changes greatly, with the ice becoming much thinner by about 0.2 m in the Antarctic and about 0.4 m in the Arctic on average. This implies that the magnitude of the thermal conductivity of snow is of considerable importance for the simulation of the sea ice distribution. An appropriate value of the thermal conductivity of snow is as crucial as the depth of the snow layer and the snowfall rate in a sea ice model. The coupled climate models require accurate values of the effective thermal conductivity of snow from observations for validating the simulated sea ice distribution under the present climate conditions. Received: 20 November 1997/Accepted: 27 July 1998     

基于常规气象资料融雪模式的建立及应用

以能量平衡方程为基础,考虑太阳短波辐射、大气和地面的长波辐射、潜热、感热传输以及下垫面的热传导等能量之间的平衡,建立了利用常规气象观测资料预测雪面温度和积雪深度变化的融雪模型。利用2009年1—3月以及2009年12月—2010年1月在湖北恩施雷达站的积雪观测数据进行模拟和验证,结果表明：该模型对于雪面温度和积雪深度都有较好的模拟效果。当下垫面导热系数λg〈0.5时,下垫面对雪深的影响很小;当λg≥0.5时,积雪融化速度随λg的增大而加快,说明下垫面的热传导是影响积雪深度变化的主要因素之一。     

A retrospective analysis of pan Arctic permafrost using the JULES land surface model

There is mounting evidence that permafrost degradation has occurred over the past century. However, the amount of permafrost lost is uncertain because permafrost is not readily observable over long time periods and large scales. This paper uses JULES, the land surface component of the Hadley Centre global climate model, driven by different realisations of twentieth century meteorology to estimate the pan-arctic changes in near-surface permafrost. Model simulations of permafrost are strongly dependent on the amount of snow both in the driving meteorology and the way it is treated once it reaches the ground. The multi-layer snow scheme recently adopted by JULES significantly improves its estimates of soil temperatures and permafrost extent. Therefore JULES, despite still having a small cold bias in soil temperatures, can now simulate a near-surface permafrost extent which is comparable to that observed. Changes in snow cover have been shown to contribute to changes in permafrost and JULES simulates a significant decrease in late twentieth century pan-Arctic spring snow cover extent. In addition, large-scale modelled changes in the active layer are comparable with those observed over northern Russia. Simulations over the period 1967–2000 show a significant loss of near-surface permafrost—between 0.55 and 0.81 million km² per decade with this spread caused by differences in the driving meteorology. These runs also show that, for the grid cells where the active layer has increased significantly, the mean increase is ~10 cm per decade. The permafrost degradation discussed here is mainly caused by an increase in the active layer thickness driven by changes in the large scale atmospheric forcing. However, other processes such as thermokarst development and river and coastal erosion may also occur enhancing permafrost loss.     

Treatment of frozen soil and snow cover in the land surface model SEWAB

Summary  The land surface model SEWAB (Surface Energy and Water Balance) is designed to be coupled to both, atmospheric and hydrological models. Its application in mid and high latitudes requires the inclusion of freezing and thawing processes within the soil and the accumulation and ablation of a snow cover. These winter processes are parameterised with a minimum number of empirical formulations in order to assure reasonable computation times for an application in climate and sensitivity studies yet accounting for all important processes. Meteorological forcing data and measurements of snow depth, soil temperature and liquid soil water content at two locations in the mid-west of North America are used to test the model. Generally the simulated snow depth matches the measurements, remaining differences in snow depth can be explained by uncertainties in snow density, blowing snow and errors in precipitation measurements. The simulated soil temperature and liquid soil water content compare well with the measurements, showing the isolating effect of the snow cover. Received August 25, 2000 Revised January 19, 2001     

Physical mechanisms of European winter snow cover variability and its relationship to the NAO

Annual snow cover in the Northern Hemisphere has decreased in the past two decades, an effect associated with global warming. The regional scale changes of snow cover during winter, however, vary significantly from one region to another. In the present study, snow cover variability over Europe and its connection to other atmospheric variables was investigated using Cyclostationary Empirical Orthogonal Function (CSEOF) analysis. The evolution of atmospheric variables related to each CSEOF mode of snow cover variability was derived via regression analysis in CSEOF space. CSEOF analysis clearly shows that the North Atlantic Oscillation (NAO) is related to European snow cover, particularly in January and February. A negative NAO phase tends to result in a snow cover increases, whereas a positive NAO phase results in snow cover decreases. The temporal changes in the connection between the NAO and European snow cover are explained by time-dependent NAO-related temperature anomalies. If the NAO phase is negative, the temperature is lower in Europe and snow cover increases; by contrast, when the NAO phase is positive, the temperature is higher and snow cover decreases. Temperature and snow cover variations in Europe are associated with the thermal advection by anomalous wind by NAO. CSEOF analysis also shows an abrupt increase of snow cover in December and January and a decrease in February and March since the year 2000, approximately. This abrupt change is associated with sub-seasonal variations of atmospheric circulation in the study region.     

Blowing Snow Forecast Using Numerical Atmospheric Model Output Data

The object under study is the blowing snow, i.e., the transport of snow lifted from the snow surface. The method is described for predicting the blowing snow initiation using the output data of the WRF-ARW numerical atmospheric model. The skill scores are presented for the forecasts for January 2013 calculated from data of 10 stations of the Canadian weather observation network.     

冬季积雪的异常分布型及其与冬、夏大气环流的耦合关系

采用 ECMWF1 979～ 1 993年 2 .5°× 2 .5°的网格点积雪深度资料 ,研究了较为细致的积雪异常的空间分布特征 ,揭示了欧亚大陆冬季积雪的异常空间分布型 ;并采用 SVD方法研究了冬季积雪的异常分布型与冬、夏大气环流的耦合关系。结果表明 :欧亚大陆冬季积雪深度存在典型的异常空间分布型 ;积雪的异常分布型与冬、夏大气环流之间均存在一定的耦合关系。冬季积雪的异常分布型与大气 EU遥相关型存在明显的同时性相互作用 ,大气 EU遥相关型有利于冬季积雪异常分布型的出现和维持 ,而积雪异常分布型对大气 EU遥相关型的发生起一定的作用 ,进而对冬季风活动产生影响。冬季积雪的这种异常分布型与夏季大气环流 ,尤其是东亚地区的夏季大气环流 ,也存在一定的联系。积雪异常分布型可以通过影响副热带高压的南北进退 ,对东亚季风及中国夏季雨带产生影响。     

青藏高原东西部积雪效应的模拟对比分析

采用引入次网格尺度地形重力波拖曳的NCAR区域气候模式(RegCM2),以SMMR微波逐候积雪深度观测值为依据,加入较合理的积雪强迫,通过数值模拟,研究了青藏高原(下称高原)东、西部积雪异常对后期区域环流的不同影响。模拟结果的对比分析表明,高原西部多雪对高原东部积雪存在正的反馈作用,有利于高原东部积雪的增加,而高原东部多雪对高原西部积雪的影响很小。高原西部积雪偏多和高原东部积雪偏多对后期大气温度场和高度场的影响具有基本相同的分布形态,只是影响强度有所不同。高原西部积雪的融化要迟于高原东部积雪,高原西部积雪效应的持续性较强。另外,高原西部多雪对高原东部积雪存在正的反馈作用,高原东部积雪的增加进一步加大了整个高原积雪的异常,因此,高原西部积雪偏多对后期环流的综合影响明显大于高原东部积雪偏多的影响。