Snow Age Research Articles

Distributed energy balance modeling of South Cascade Glacier, Washington and assessment of model uncertainty

We have developed a physically based, distributed surface energy balance model to simulate glacier mass balance under meteorological and climatological forcing. Here we apply the model to estimate summer ablation on South Cascade Glacier, Washington, for the 2004 and 2005 mass balance seasons. To arrive at optimal mass balance simulations, we investigate and quantify model uncertainty associated with selecting from a range of physical parameter values that are not commonly measured in glaciological mass balance field studies. We optimize the performance of the model by varying values for atmospheric transmissivity, the albedo of surrounding topography, precipitation‐elevation lapse rate, surface roughness for turbulent exchange of momentum, and snow albedo aging coefficient. Of these the snow aging parameter and precipitation lapse rates have the greatest influence on the modeled ablation. We examined model sensitivity to varying parameters by performing an additional 103 realizations with parameters randomly chosen over a ±5% range centered about the optimum values. The best fit suite of model parameters yielded a net balance of −1.69 ± 0.38 m water equivalent (WE) for the 2004 water year and −2.10 ± 0.30 m WE up to 11 September 2005. The 2004 result is within 3% of the measured value. These simulations account for 91% and 93% of the variance in measured ablation for the respective years.

Use of atmospheric radiation measurement program data from Barrow, Alaska, for evaluation and development of snow-albedo parameterizations

Snow albedo is determined from the ratio of out-going to incoming solar radiation using three years of broadband shortwave radiometer data obtained from the Barrow, Alaska, Atmospheric Radiation Measurement (ARM) site. These data are used for the evaluation of various types of snow-albedo parameterizations applied in numerical weather prediction or climate models. These snow-albedo parameterizations are based on environmental conditions (e.g., air or snow temperature), snow related characteristics (e.g., snow depth, snow age), or combinations of both. The ARM data proved to be well suited for snow-albedo evaluation purposes for a low-precipitation tundra environment. The evaluation confirms that snow-age dependent parameterizations of snow albedo work well during snowmelt, while parameterizations considering meteorological conditions often perform better during snow accumulation. Current difficulties in parameterizing snow albedo occur for long episodes of snow-event free conditions and episodes with a high frequency of snow events or strong snowfall.

Present‐day climate forcing and response from black carbon in snow

We apply our Snow, Ice, and Aerosol Radiative (SNICAR) model, coupled to a general circulation model with prognostic carbon aerosol transport, to improve understanding of climate forcing and response from black carbon (BC) in snow. Building on two previous studies, we account for interannually varying biomass burning BC emissions, snow aging, and aerosol scavenging by snow meltwater. We assess uncertainty in forcing estimates from these factors, as well as BC optical properties and snow cover fraction. BC emissions are the largest source of uncertainty, followed by snow aging. The rate of snow aging determines snowpack effective radius (re), which directly controls snow reflectance and the magnitude of albedo change caused by BC. For a reasonable re range, reflectance reduction from BC varies threefold. Inefficient meltwater scavenging keeps hydrophobic impurities near the surface during melt and enhances forcing. Applying biomass burning BC emission inventories for a strong (1998) and weak (2001) boreal fire year, we estimate global annual mean BC/snow surface radiative forcing from all sources (fossil fuel, biofuel, and biomass burning) of +0.054 (0.007–0.13) and +0.049 (0.007–0.12) W m−2, respectively. Snow forcing from only fossil fuel + biofuel sources is +0.043 W m−2 (forcing from only fossil fuels is +0.033 W m−2), suggesting that the anthropogenic contribution to total forcing is at least 80%. The 1998 global land and sea‐ice snowpack absorbed 0.60 and 0.23 W m−2, respectively, because of direct BC/snow forcing. The forcing is maximum coincidentally with snowmelt onset, triggering strong snow‐albedo feedback in local springtime. Consequently, the “efficacy” of BC/snow forcing is more than three times greater than forcing by CO2. The 1998 and 2001 land snowmelt rates north of 50°N are 28% and 19% greater in the month preceding maximum melt of control simulations without BC in snow. With climate feedbacks, global annual mean 2‐meter air temperature warms 0.15 and 0.10°C, when BC is included in snow, whereas annual arctic warming is 1.61 and 0.50°C. Stronger high‐latitude climate response in 1998 than 2001 is at least partially caused by boreal fires, which account for nearly all of the 35% biomass burning contribution to 1998 arctic forcing. Efficacy was anomalously large in this experiment, however, and more research is required to elucidate the role of boreal fires, which we suggest have maximum arctic BC/snow forcing potential during April–June. Model BC concentrations in snow agree reasonably well (r = 0.78) with a set of 23 observations from various locations, spanning nearly 4 orders of magnitude. We predict concentrations in excess of 1000 ng g−1 for snow in northeast China, enough to lower snow albedo by more than 0.13. The greatest instantaneous forcing is over the Tibetan Plateau, exceeding 20 W m−2 in some places during spring. These results indicate that snow darkening is an important component of carbon aerosol climate forcing.

Classification of glacier zones in western Greenland using albedo and surface roughness from the Multi-angle Imaging SpectroRadiometer (MISR)

The Greenland ice sheet has been the subject of mass balance and melt measurements over the past two decades and its margins have shown significant thinning in recent years. Surface characteristics of the ice sheet margins are strongly modified by the annual process of snow accumulation and melt. In this work, we explore spatial and temporal relationships between near-infrared albedo and surface roughness from the Multi-angle Imaging SpectroRadiometer (MISR) aboard NASA's Terra satellite. Our study area is a region in western Greenland in the vicinity of Jakobshavn Glacier and its upland drainage basin. We compute near-infrared albedo from MISR data using imagery over the April to September period for 2000 through 2005. Near-infrared albedo is inversely related to both snow age and melt intensity. We map surface roughness using the Normalized Difference Angular Index (NDAI) applied to MISR atmospherically corrected surface hemispherical-directional reflectance. In previous work, the NDAI has been correlated with surface roughness on the scale of about 70 m. We have further substantiated that relationship here. The NDAI and albedo images for each of the six years are used in an ISODATA unsupervised classification. Classification results for the individual years show year-to-year differences, which appear to depend on the number and temporal distribution of images with minimal cloud cover as well as interannual differences in ice sheet surface properties. The year 2003, which had the greatest number of images with minimal cloud cover, shows good correspondence with previously mapped glacier zones. However, we do not have an ISODATA class that corresponds to the dry-snow zone and we see greater differentiation between zones at lower elevations. Within each ISODATA class, distinct relationships between near-infrared albedo and surface roughness emerge and in all cases but one there is an inverse temporal relationship between albedo and roughness. The one class that shows a direct relationship between albedo and surface roughness is hypothesized to be the superimposed-ice zone. While still somewhat preliminary, these results suggest that concurrent measurements of near-infrared albedo and surface roughness have significant potential for ice sheet surface characterization as well as for ongoing monitoring.

Evaluation of snow cover in CLASS for SnowMIP

An evaluation of the Canadian Land Surface Scheme (CLASS) 3.1 snow cover simulations at four sites included in the Snow Model Intercomparison Project (SnowMIP) revealed that CLASS was able to provide realistic representations of snow cover accumulation, melt and physical properties over a range of snow cover climates. The modified snow aging parametrization in CLASS 3.1 provided improved simulations of snowpack density which resulted in a marked reduction in the root‐mean‐square (rms) error for daily snow depth, and slight improvements in snow surface temperature. CLASS 3.1 still exhibited a tendency to overestimate snow cover duration which is attributed to the way shallow snow ablation is treated. CLASS provided generally realistic simulations of daily and seasonal variation in snow albedo although cold snow albedo was underpredicted by 0.10 to 0.15 at a site with a deep (> 2 m) cold snowpack. CLASS also exhibited a tendency to overpredict late spring snow albedo which was reduced by the addition of a snow layer subroutine that kept track of snow albedo by precipitation event. CLASS had a noticeable cold bias averaging 3°–4°C at two mountain sites included in the comparison. The bias was closely linked to atmospheric stability and could exceed 10°C under conditions of strong radiative cooling and low wind speeds. The CLASS energy deficit under these conditions was determined to be ∼20–40 W m−2 and was mostly accounted for by introducing a windless exchange coefficient into the calculation of sensible heat fluxes following the approach used in a number of other physical snowpack models. CLASS provided realistic simulations of daily snowmelt runoff with the exception of the Weissfluhjoch site which was characterized by a deep cold snowpack. A preliminary assessment of snow water equivalent (SWE) rms error for the 23 models participating in SnowMIP showed that CLASS was one of the better single layer snow models included in the comparison. CLASS performance was comparable to the multi‐layer CROCUS snowpack model in the evaluations carried out in this study.

Linking snowpack microphysics and albedo evolution

Snow aging causes reflectance to vary significantly on timescales of days. This variability influences the strength of snow albedo feedback and can affect the timing of snowmelt. However, climate models have yet to incorporate important controls on snow aging and albedo evolution. We develop a physically based model that predicts evolution of dry, pure snow specific surface area, and apply aspherical ice particle theory to link these results with albedo evolution. This is the first theoretical study to quantify the relative roles of initial size distribution, vertical temperature gradient, and snow density in snow albedo evolution. Vapor diffusion caused by curvature differences causes rapid albedo decay in the first day following snowfall. Vertical temperature gradient generally dominates grain growth processes afterward but is modulated by snow density, irregularity in particle spacing, and temperature. These processes operate as a coupled system, which we uniquely represent without abrupt transitions between regimes. Model results agree very well with measurements of isothermal snow evolution and are within reasonable range of temperature gradient observations. We show that different snow state regimes cause albedo of nonmelting snow surfaces with identical initial albedo to vary by 0.12 or more after 14 days. Lack of quality observational data illuminates the need for well‐controlled snow studies that simultaneously monitor specific surface area, temperature gradient, and albedo. Accounting for snow aging processes, especially temperature gradient, will improve understanding and assessment of snow albedo feedback and climate sensitivity. The modeling framework we develop will also be useful for air‐snow chemistry studies that consider specific surface area.

Comparison of ground‐based and airborne snow surface albedo parameterizations in an alpine watershed: Impact on snowpack mass balance

Two commonly used snow surface albedo models were evaluated using albedo data from the Airborne Visible/Infrared Imaging Spectroradiometer (AVIRIS), and their influence on snowmelt timing and magnitude was assessed using a net radiation/temperature index snowmelt model, a series of satellite‐based snow covered area scenes, and on‐site snow surveys. Albedo estimates using an explicit representation of snow surface temperature, snow age, and solar illumination angle, based on the Biosphere Atmosphere Transfer Scheme (BATS), were within the 0.02 AVIRIS measurement error for 78% of the snow‐covered portions of the watershed. Conversely, albedo values estimated using a simple model based solely on snow surface age underestimated AVIRIS‐observed albedo. Correlations between the timing of snowmelt and observed runoff using the BATS albedo model (R2 = 0.69) were significantly better than those using the age‐based approach (R2 = 0.59) and were comparable to using AVIRIS data (R2 = 0.73). Snow extent was simulated most accurately with the AVIRIS parameterization; average map accuracy was 79 and 10% greater than when using the age‐based and BATS albedo parameterizations, respectively. The error in snow water equivalent for April was 14% for BATS versus 39% for the age‐based albedo; however, it was less than 1% for simulations using AVIRIS albedo data. Thus the BATS albedo estimates performed better than the age‐based albedo but did not outperform simulations using AVIRIS albedo data.

Possible Effect of Anthropogenic Aerosol Deposition on Snow Albedo Reduction at Shinjo, Japan

We observed broadband snow albedos in the visible and the near infrared spectral regions with snow pit works of several-day intervals, during the winters of 2001/2002 and 2002/2003 at Shinjo, Japan. We examined the dependence of albedos on snow grain size and on concentration of snow impurities, comparing observations and theoretical calculations using a radiative transfer model for atmosphere-snow system. The comparisons revealed that the snow was contaminated by strong absorptive impurities such as soot additional to moderate absorptive impurities such as mineral dust. Snow albedo reduction after snowfalls (snow aging effect on albedo) observed in both spectral regions corresponded to the growth tendency of snow grains and the increasing concentration of snow impurities with elapsed time after snowfalls. Measurement of the atmospheric aerosols above the snow surface using a laser optical particle counter suggested that wet deposition of atmospheric aerosols caused snow impurities of more than 1 ppmw in mass concentration.

Effects of snow physical parameters on shortwave broadband albedos

Snow pit work of several‐day intervals was performed simultaneously with radiation budget observations during two winters in eastern Hokkaido, Japan. From these data we investigated the effects of elapsed time after snowfall (snow aging), air temperature, snow surface temperature, snow grain size, and snow impurities on the visible and the near infrared albedos for improving the snow albedo scheme in the land surface process from an empirical model to a physically based model. The dependence of albedos on elapsed time after snowfall could be clearly classified by dividing the snow‐covered period into a dry snow season and a wet snow season rather than by snow surface temperature. The albedo reduction by snow aging statistically depends on the snow surface temperature, which is often used to predict the snow albedo in the empirical model of land surface process. However, the albedo reduction rate was very scattered for snow surface temperatures above −10°C. This is because the snow albedo reduction essentially depends on the snow grain size and the concentration of snow impurities. Using the radiative transfer model for the atmosphere‐snow system, the effects of these snow physical parameters on broadband albedos are calculated and compared with the observed ones. The measured broadband albedos fell close to the range of theoretically calculated ones as functions of these snow physical parameters. In particular, the measured near infrared albedo agreed well with the theoretically calculated ones both for the dependence of snow grain size and snow impurities but not as well for the visible albedo in detail. In the near infrared region the light absorption by ice is strong, and thus the snow albedo contains the information of snow physical parameters near the surface where these parameters are measured. In contrast, the visible albedo contains the snow information in the deeper layer because the ice is relatively transparent in the visible region. This suggests the necessity of the multiple‐snow‐layer model for the visible region in the physically based snow albedo model.

Measurement of the specific surface area of 176 snow samples using methane adsorption at 77 K

To help quantify exchanges between the atmosphere and the snow cover, we have measured the specific surface area (SSA) of 176 snow samples taken from the seasonal snowpack in the Alps, Svalbard, and the Canadian high Arctic around Alert. A volumetric method was used, and the adsorption isotherm of CH4 on snow at 77 K was recorded. The data were analyzed by the Brunauer‐Emmett‐Teller method to yield SSA and ΔQCH4, the mean heat of adsorption of the first CH4 monolayer. SSA values obtained were between 100 and 1580 cm2/g. The reproducibility of the method is estimated at 6%, and the accuracy is estimated at 12%. We propose that ΔQCH4 = 2240 ± 200 J/mol should be used as a criterion of reliability of the measurement. The method is described in detail to promote its use. Aged snow samples have lower SSA than fresh ones. The lowest values were found for faceted crystals and depth hoar, and the highest values were found for fresh rimed dendritic snow. A method that field investigators can use to estimate SSA from a visual examination of the snow and from a density measurement is suggested. Snow samples are classified into 14 types based on snow age and crystal shapes. Within each type, a density versus SSA correlation is determined. Our data indicate that, depending on snow type, SSA can then be estimated within 25 to 40% at the 1σ confidence level with the method proposed. Preliminary data suggest that SSA spatial variability of a given snow layer is low (<5%), but metamorphism can increase it.

Refinements to SSiB with an Emphasis on Snow Physics: Evaluation and Validation Using GSWP and Valdai Data

Refinements to the snow-physics scheme of SSiB (Simplified Simple Biosphere Model) are described and evaluated. The upgrades include a partial redesign of the conceptual architecture to better simulate the diurnal temperature of the snow surface. For a deep snowpack, there are two separate prognostic temperature snow layers - the top layer responds to diurnal fluctuations in the surface forcing, while the deep layer exhibits a slowly varying response. In addition, the use of a very deep soil temperature and a treatment of snow aging with its influence on snow density is parameterized and evaluated. The upgraded snow scheme produces better timing of snow melt in GSWP-style simulations using ISLSCP Initiative I data for 1987-1988 in the Russian Wheat Belt region. To simulate more realistic runoff in regions with high orographic variability, additional improvements are made to SSiB's soil hydrology. These improvements include an orography-based surface runoff scheme as well as interaction with a water table below SSiB's three soil layers. The addition of these parameterizations further help to simulate more realistic runoff and accompanying prognostic soil moisture fields in the GSWP-style simulations. In intercomparisons of the performance of the new snow-physics SSiB with its earlier versions using an 18-year single-site dataset from Valdai Russia, the version of SSiB described in this paper again produces the earliest onset of snow melt. Soil moisture and deep soil temperatures also compare favorably with observations.

Applications of SHEBA/FIRE data to evaluation of snow/ice albedo parameterizations

Climate models use a wide variety of parameterizations for surface albedos of the ice‐covered ocean. These range from simple broadband albedo parameterizations that distinguish among snow‐covered and bare ice to more sophisticated parameterizations that include dependence on ice and snow depth, solar zenith angle, and spectral resolution. Several sophisticated parameterizations have also been developed for thermodynamic sea ice models that additionally include dependence on ice and snow age, and melt pond characteristics. Observations obtained in the Arctic Ocean during 1997–1998 in conjunction with the Surface Heat Budget of the Arctic Ocean (SHEBA) and FIRE Arctic Clouds Experiment provide a unique data set against which to evaluate parameterizations of sea ice surface albedo. We apply eight different surface albedo parameterizations to the SHEBA/FIRE data set and evaluate the parameterized albedos against the observed albedos. Results show that these parameterizations yield very different representations of the annual cycle of sea ice albedo. The importance of details and functional relationships of the albedo parameterizations is assessed by incorporating into a single‐column sea ice model two different albedo parameterizations, one complex and one simple, that have the same annually averaged surface albedo. The baseline sea ice characteristics and strength of the ice‐albedo feedback are compared for the simulations of the different surface albedos.

Air permeability and capillary rise as measures of the pore structure of snow: an experimental and theoretical study

Air permeability and capillary pressure are macroscopic snow properties that are influenced by the pore structure of the snow cover. Formulas for predicting fluid transport, species elution, and acoustive wave propagation require parameterization of one or both of these properties. We report paired measurements of permeability and capillary rise from snow samples at field sites in Hanover, New Hampshire, and Sleepers River Research Watershed, Danville, Vermont. We augment these data with laboratory tests on sieved snow and glass beads. Our measurements demonstrate a linear relationship between permeability and the ratio of porosity and the square of capillary rise, which we corroborate theoretically using a simple conduit model of the pore space. We propose that scatter in the data results, in part, from the effect of crystal shape on air flow and imbibition contact angle. Since the early measurements and classification schemes of Bader in 1939, many investigators have expanded the database of permeability observations for a wide range of snow types. We summarize these data and report our own recent observations from the New England sites and from an additional site in Manitoba, Canada. Our measurements are in the high range of reported values. However, after normalizing our data by the square of grain diameter, they follow the empirical function of Shimizu fairly closely. This agreement supports our measurements, and demonstrates the usefulness of Shimizu's function for snow types other than the relatively dense, fine-grained snow used in his analysis. Our normalized permeability data for low density snow, as well as the Shimizu function, are below theoretical predictions for suspensions of spheres and infinite cylinders. By extending the model for spheres to oblate spheroids and discs, we estimate permeability that is in closer agreement with our data. We suggest that a decrease in surface-to-volume ratio as snow ages may account for a relative increase in normalized permeability. Copyright © 1999 John Wiley & Sons, Ltd.

Method to determine snow albedo values in the ultraviolet for radiative transfer modeling

For many cases modeled and measured UV global irradiances agree to within +/-5% for cloudless conditions, provided that all relevant parameters for describing the atmosphere and the surface are well known. However, for conditions with snow-covered surfaces this agreement is usually not achievable, because on the one hand the regional albedo, which has to be used in a model, is only rarely available and on the other hand UV irradiance alters with different snow cover of the surface by as much as 50%. Therefore a method is given to determine the regional albedo values for conditions with snow cover by use of a parameterization on the basis of snow depth and snow age, routinely monitored by the weather services. An algorithm is evolved by multiple linear regression between the snow data and snow-albedo values in the UV, which are determined from a best fit of modeled and measured UV irradiances for an alpine site in Europe. The resulting regional albedo values in the case of snow are in the 0.18-0.5 range. Since the constants of the regression depend on the area conditions, they have to be adapted if the method is applied for other sites. Using the algorithm for actual cases with different snow conditions improves the accuracy of modeled UV irradiances considerably. Compared with the use of an average, constant snow albedo, the use of actual albedo values, provided by the algorithm, halves the average deviations between measured and modeled UV global irradiances.

Albedo Variations and Surface Energy Balance in Different Snow-Ice Media in Antarctica

The present study is aimed at investigating the radiation budget in different snow-ice media (shelf ice,continental ice and natural snow) at three different elevated sites in the general area of Prince Astrid Coast of EastAntarctica. Measurements of the dependence of albedo in different snow and ice media on solar elevation angle,cloud cover, liquid water content, grain size, etc. can be interpreted in terms of single and multiple scatteringradiative transfer theory. Detailed albedo measurements were carried out during summer and winter in differentsnow and ice media in 1997-98 at different selected sites at Antarctica. The average albedo values were found to behigh (90 per cent) in snow medium, moderate (83 per cent) in shelf ice and very low (50 per cent) in continentalice medium. The albedo was found to be a function of cloud amount, increasing with the amount and thickness. Inwhite-out condition during blizzards, high albedo (average 83 per cent) was found as compared to clear sky day(76 per cent) and after blizzard (average 78 per cent). It showed dependence on the type and age of snow also. Newsnowfall over old snow displayed higher values (90 per cent) than older snow (70 per cent) and decreased with theageof snow from 13- 16 per cent. Naturalmelt-water in snowpack increases from 1- 10 per cent, resulting in albedodecay from 7-10 per cent. As the minimum solar elevation angle in Antarctica goes to 3O, strong qualitativeanalyses have been ma e of the dependenceof albedo on the solar elevation angle. Albedo values showed diurnalhysteresis and m in values were found to be higher than evening values at the same angle of elevation. Thedependence was 4 sligh or solar elevations during day time when 0 % 12-IS0, but became larger with low angleswhen 8 = 3-12'. Solar insolations were also calculated for different months in order to calculate short waveradiation absorbed by snow and ice media. Insolations in different months at different selected sites lie in theranges 10-540 lnlday (August-October), 350-911 lnlday (November-December) and 190-755 lnlday(January-February). Net energy balance was calculted usingmodel and was found to benegativemost of the time.

SSiBを改良した新雪モデル

In evaluation (s) as a part of the Global Soil Wetness Project using ISLSCP Initiative-I data, the snow-melt in SSiB in the Russian Wheat Belt region (RWB) was found to be substantially delayed, with very deficient meltwater infiltration as compared to observations. Furthermore, most of the meltwater emerged as runoff, as opposed to soil moisture recharge. The deficiency emanated from the crudeness of snow-physics of the combined snow and ground layer of SSiB. In the current work, a new snow model employing a separate snow-layer was included. The snow-pack absorbs and transmits the incoming solar flux, thereby affecting the snow and ground temperatures through the winter and snow-melt periods. In the ISLSCP Initiative-I data evaluations, the snow-melt over the RWB region occurs 2-3 weeks sooner in the new model, and its soil thaws quite early in the snow-melt duration, which helps to infiltrate more meltwater into the soil. The new-model produces a more realistic simulation of soil-moisture, as well as Volga river runoff in RWB evaluations. Some residual delay in the snow-melt (varying from 1-4 weeks) seems to be related to the following: (1) inaccuracies in the satellite retrievals of snow under dense forest canopies; (2) the modeling assumptions, e. g., neglecting the influence of snow aging on its thermal diffusivity, and simplifications in absorption of solar-flux in the snow cover, leading to an inadequate distinction between snow-pack surface and mean temperatures; and, (3) possible cold bias of the ISLSCP surface air temperature data.

The Simulation of Thermal Properties of Qinghai Lake and the Potential Change in the Future

运用基于湖泊热量收支与湍流扩散的湖泊热力学模型模拟了青海湖近30年来湖水热力状况，内容包括湖泊水面温度；温度沿深度的垂直分布；冬季结冰与融冰的起迄时间，冰盖厚度；积雪深度与天数等．在此基础上，运用4个GCMs模型输出的CO₂倍增情景下该地区的气候状况，评价了湖泊热力状况在未来的可能变化情况。;Based on the lake energy budget and fake eddy diffusion equation * the lake thermal model was constructed and used in the simulation of thermal properties of Qinghai Lake, the largest saline and deep lake in China,The simulated items include the water surface temperature? tem perature profile, ice formation and thaw procedure? snow aging process etc. With the aid of the four-GCMs output about the climate condition of doubling C0₂ in this area,the potential change degree of the water thermal properties has been evaluated and discussed.

Probability of occurrence of blowing snow

Blowing snow (snow transport) affects snow cover distribution and snowmelt runoff patterns in cold, wind‐swept regions. This paper uses a statistical method to examine the occurrence of blowing snow and the meteorological conditions recorded for 16 stations on the prairies of western Canada over six winters. The results show that the occurrence probability is highly related to wind speed, air temperature and snow age. For the same air temperature and snow age, the occurrence probability increases with increasing wind speed. The probability distribution of occurrence with respect to wind speed approximates a cumulative normal probability distribution, depending on the mean and variance of wind speed: the location and scale parameters of the normal distribution. It was found that these two statistical parameters essentially indicate snow resistance and sensitivity to wind transport. Analysis of the probability distributions for the occurrence of blowing snow for different classes of air temperature and snow age reveals that the mean wind speed of the normal distribution generally increases with increasing air temperature and snow age, and the variance of wind speed increases with increasing air temperature. This leads to the development of a model which first estimates the two parameters of the normal distribution using air temperature and snow age, and then estimates the probability of the occurrence of blowing snow using wind speed and the two parameters with the cumulative normal probability function. Comparison of hours of occurrence of blowing snow and of fluxes of snow transport and sublimation estimated using the model to those determined using observations of occurrence of blowing snow shows good agreement. The results of this study can be used to estimate the frequency of blowing snow events using standard meteorological data, to determine the snow transport and snow sublimation fluxes, and to examine the effect of meteorological conditions on blowing snow processes.

Racial composition of breeding and wintering Snow BuntingsPlectrophenax nivalisin the north‐east Scottish uplands

This paper quantifies variation in several plumage features between and within Snow Bunting races and age groups, and stresses the importance of correcting for such variation, and observer variation, when estimating the racial composition of a sample of Snow Buntings. I show that the majority of Snow Buntings caught at North‐east Scottish upland sites during winters 1987/88 to 1992/93 were of the dark Icelandic race Plectrophenax nivalis insulae. Birds more characteristic of the nominate nivalis race (from Greenland and/or Scandinavia) were more frequent amongst males (up to 40%) than females (0–10%). An even greater predominance of P.n. insulae was noted amongst birds remaining to breed on the Scottish Cairngorm Mountains.

The albedo of temperate and boreal forest and the Northern Hemisphere climate: a sensitivity experiment using the LMD GCM

A deforestation experiment is performed using the Laboratoire de Meteorologie Dynamique Atmospheric General Circulation Model (LMD GCM) to determine the climatic role of the largest vegetation formation in the Northern Hemisphere, localized mostly north of latitude 45{degree}N, which is called the temperate and boreal forest. For this purpose, an iterative albedo scheme based on vegetation type, snow age, snowfall rate and area of snow cover, is developed for snow-covered surfaces. The results show a cooling of Northern Hemisphere soil and an increase in the snow cover when the forest is removed, as found by previous similar experiments. In our study this cooling is related to different causes, depending on the season. It is linked to modifications in the soil radiative properties, like surface albedo, due to the disappearance of forest, and consequently, to a greater exposure of the snow-covered soil underneath. It is also related to alterations in the hydrological cycle, observed mainly in summer and autumn at middle latitudes. The model shows a strong sensitivity to the coupled surface albedo - soil temperature - fractional snow cover response in the spring. A later and longer snowmelt season is also detected. This study adds to our understanding of climatic variationmore » on longer time scales, since it is widely accepted that the formation and disappearance of different vegetation formations is closely related to climatic evolution patterns, in particular on the time scale of the glacial oscillations. 32 refs., 12 figs.« less