Albedo of coastal landfast sea ice in Prydz Bay,Antarctica: Observations and parameterization

The snow/sea-ice albedo was measured over coastal landfast sea ice in Prydz Bay, East Antarctica(off Zhongshan Station)during the austral spring and summer of 2010 and 2011. The variation of the observed albedo was a combination of a gradual seasonal transition from spring to summer and abrupt changes resulting from synoptic events, including snowfall, blowing snow, and overcast skies. The measured albedo ranged from 0.94 over thick fresh snow to 0.36 over melting sea ice. It was found that snow thickness was the most important factor influencing the albedo variation, while synoptic events and overcast skies could increase the albedo by about 0.18 and 0.06, respectively. The in-situ measured albedo and related physical parameters(e.g., snow thickness, ice thickness, surface temperature, and air temperature) were then used to evaluate four different snow/ice albedo parameterizations used in a variety of climate models. The parameterized albedos showed substantial discrepancies compared to the observed albedo, particularly during the summer melt period, even though more complex parameterizations yielded more realistic variations than simple ones. A modified parameterization was developed,which further considered synoptic events, cloud cover, and the local landfast sea-ice surface characteristics. The resulting parameterized albedo showed very good agreement with the observed albedo.     

Ice-free glacial northern Asia due to dust deposition on snow

During the Last Glacial Maximum (LGM, 21 kyr BP), no large ice sheets were present in northern Asia, while northern Europe and North America (except Alaska) were heavily glaciated. We use a general circulation model with high regional resolution and a new parameterization of snow albedo to show that the ice-free conditions in northern Asia during the LGM are favoured by strong glacial dust deposition on the seasonal snow cover. Our climate model simulations indicate that mineral dust deposition on the snow surface leads to low snow albedo during the melt season. This, in turn, caused enhanced snow melt and therefore favoured snow-free peak summer conditions over almost the entire Asian continent during the LGM, whereas perennial snow cover is simulated over a large part of eastern Siberia when glacial dust deposition is not taken into account.     

Snow-albedo feedback and Swiss spring temperature trends

We quantify the effect of the snow-albedo feedback on Swiss spring temperature trends using daily temperature and snow depth measurements from six station pairs for the period 1961?C2011. We show that the daily mean 2-m temperature of a spring day without snow cover is on average 0.4?°C warmer than one with snow cover at the same location. This estimate is comparable with estimates from climate modelling studies. Caused by the decreases in snow pack, the snow-albedo feedback amplifies observed temperature trends in spring. The influence is small and confined to areas around the upward-moving snow line in spring and early summer. For the 1961?C2011 period, the related temperature trend increases are in the order of 3?C7?% of the total observed trend.     

Episodic Performance and Sensitivity of the Urbanized MM5 (uMM5) to Perturbations in Surface Properties in Houston Texas

We present an application of a fine-resolution, meso-urban meteorological model (urbanized MM5; uMM5) to a multi-day episode in August 2000 in the Houston-Galveston Texas, USA region. The model’s episodic performance and its response to small changes in land-cover and surface physical properties in the area, e.g., scenarios of urban heat island mitigation, are evaluated. The model formulation is reviewed along with its parameterizations, data needs, and fine-resolution geometrical input. Development of scenarios of increased urban albedo and vegetative cover is also discussed. This initial application of the uMM5 to the Houston-Galveston region serves as a basis for future model improvements, evaluation of newer data and parameterization applications, testing more aggressive surface modification scenarios, and performing fine-resolution photochemical modelling. It also provides data for comparison of model results with those from previous studies of this region.     

积雪季节变化特征的数值模拟及其敏感性试验

文中利用综合陆面模式 (ComprehensiveLandSurfaceModel,CLSM )对法国ColdePorte 1 993/ 1 994 ,1 994 / 1 995年及BOREASSSA OJP 1 994 / 1 995年积雪个例进行了模拟试验 ,通过模拟结果与观测资料的对比 ,检验了CLSM对积雪变化特征的模拟能力 ,并通过敏感性试验探讨了降雪密度、积雪持水量等积雪参数化方案及植被对积雪模拟可能产生的影响。结果表明 :(1 )CLSM能够准确地模拟出积雪的变化过程 ,对积雪的演变特征作出了合理的描述 ;(2 )降雪密度、积雪持水量参数化方案对积雪模拟结果均具有一定的影响 :降雪密度参数化主要对积雪深度的模拟产生影响 ;而积雪持水量参数化方案对积雪的演变过程 ,尤其是积雪的消融 ,具有重要的作用 ;(3)有、无植被存在的情况下 ,积雪 土壤系统的变化过程存在显著的差别 ,植被通过改变积雪 /土壤表面的能量平衡 ,对积雪及土壤的变化过程产生重要影响 :植被的存在有利于积雪的维持 ,使得积雪融化进程推迟 ,冻结土壤的增温明显偏慢     

青海省甘德两次降雪过程的微气象特征分析

利用青海省甘德两次降雪过程的微气象观测数据,探讨了两场降雪过程雪深、雪密度、雪中含冰量、雪中含水量和雪面温度的变化情况,分析了地表反照率与雪密度、雪中含冰量及雪中含水量的关系,结合降雪过程近地面温、湿、风廓线特征分析了积雪对近地面温、湿、风梯度的影响。结果表明:积雪覆盖会导致地表反照率显著增加,降雪过后正午时地表反照率可高达0.8～0.9。随着积雪的消融,地表反照率逐渐减小;积雪反照率与雪密度和雪中含冰量呈正相关,与雪中含水量呈负相关;地表积雪覆盖会导致近地面温度梯度绝对值减小,相对湿度梯度绝对值在凌晨减小、午后增大,地表积雪覆盖对近地面风速梯度变化并无特定的影响。     

On the role of high latitude ice,snow, and vegetation feedbacks in the climatic response to external forcing changes

A seasonal energy balance climate model containing a detailed treatment of surface and planetary albedo, and in which seasonally varying land snow and sea ice amounts are simulated in terms of a number of explicit physical processes, is used to investigate the role of high latitude ice, snow, and vegetation feedback processes. Feedback processes are quantified by computing changes in radiative forcing and feedback factors associated with individual processes. Global sea ice albedo feedback is 5–8 times stronger than global land snowcover albedo feedback for a 2% solar constant increase or decrease, with Southern Hemisphere cryosphere feedback being 2–5 times stronger than Northern Hemisphere cryosphere feedback.In the absence of changes in ice extent, changes in ice thickness in response to an increase in solar constant are associated with an increase in summer surface melting which is exactly balanced by increased basal winter freezing, and a reduction in the upward ocean-air flux in summer which is exactly balanced by an increased flux in winter, with no change in the annual mean ocean-air flux. Changes in the mean annual ocean-air heat flux require changes in mean annual ice extent, and are constrained to equal the change in meridional oceanic heat flux convergence in equilibrium. Feedback between ice extent and the meridional oceanic heat flux obtained by scaling the oceanic heat diffusion coefficient by the ice-free fraction regulates the feedback between ice extent and mean annual air-sea heat fluxes in polar regions, and has a modest effect on model-simulated high latitude temperature change.Accounting for the partial masking effect of vegetation on snow-covered land reduces the Northern Hemisphere mean temperature response to a 2% solar constant decrease or increase by 20% and 10%, respectively, even though the radiative forcing change caused by land snowcover changes is about 3 times larger in the absence of vegetational masking. Two parameterizations of the tundra fraction are tested: one based on mean annual land air temperature, and the other based on July land air temperature. The enhancement of the mean Northern Hemisphere temperature response to solar constant changes when the forest-tundra ecotone is allowed to shift with climate is only 1/3 to 1/2 that obtained by Otterman et al. (1984) when the mean annual parameterization is used here, and only 1/4 to 1/3 as large using the July parameterization.The parameterized temperature dependence of ice and snow albedo is found to enhance the global mean temperature response to a 2% solar constant increase by only 0.04 °C, in sharp contrast to the results of Washington and Meehl (1986) obtained with a mean annual model. However, there are significant differences in the method used here and in Washington and Meehl to estimate the importance of this feedback process. When their approach is used in a mean annual version of the present model, closer agreement to their results is obtained.     

Long-term investigations on the water budget quantities predicted by the hydro-thermodynamic soil vegetation scheme (HTSVS) – Part II: Evaluation, sensitivity, and uncertainty

Summary ¶Various water budget elements (water supply to the atmosphere, ground water recharge, change in storage) are predicted by HTSVS for a period of 2050 days. The predicted water budget elements are evaluated by routine lysimeter data. The results show that land surface models need parameterizations for soil frost, snow effects and water uptake to catch the broad cycle of soil water budget elements. In principle, HTSVS is able to simulate the general characteristics of the seasonal changes in these water budget elements and their long-term accumulated sums. Compared to lysimeter data, there is a discrepancy in the predicted water supply to the atmosphere for summer and winter which may be attributed to the hardly observed plant physiological parameters like root depth, LAI, shielding factor, etc., the lack of measured downward long-wave radiation, and some simplifications made in the parameterizations of soil frost and snow effects. The fact that high resolution data for the evaluation of model results are missing and evaluation is made on the basis of the data from routine stations of a network is typical for the results of long-term studies on climate. Taking into account the coarse resolution of climate models, the coarse vertical resolution that is used in their LSMs, and the lack of suitable parameters needed, it seems that discrepancies in the order of magnitude found in this study are a general uncertainty in the results of land surface modeling on typical spatial and temporal scales of the climate system.Received October 8, 2001; revised February 15, 2002; accepted September 20, 2002 Published online: April 10, 2003     

有关雪盖模型内部及界面过程的参数化方案的敏感试验

In order to develop a seasonal snow model of land surface process as accurately as possible for climatic study, it is necessary to fully understand the effects of important snow internal processes and interaction with air and to get an insight into influence of several relevant parameterization schemes with parameters＇ uncertainty to some degree. Using the snow model (SAST) developed by first author and other one and some useful field observation data, this paper has conducted a series of sensitivity studies on the parameterization schemes. They are relative to compaction process, snow thermal conduction, methodology of layering snow pack and to key parameters such as snow albedo, water holding capacity. Then, based on the results from the sensitivity studies, some useful conclusions for snow cover model improvement are ob tained from the analysis of the results.     

Intercomparison and validation of snow albedo parameterization schemes in climate models

Snow albedo is known to be crucial for heat exchange at high latitudes and high altitudes, and is also an important parameter in General Circulation Models (GCMs) because of its strong positive feedback properties. In this study, seven GCM snow albedo schemes and a multiple linear regression model were intercompared and validated against 59 years of in situ data from Svalbard, the French Alps and six stations in the former Soviet Union. For each site, the significant meteorological parameters for modeling the snow albedo were identified by constructing the 95% confidence intervals. The significant parameters were found to be: temperature, snow depth, positive degree day and a dummy of snow depth, and the multiple linear regression model was constructed to include these. Overall, the intercomparison showed that the modeled snow albedo varied more than the observed albedo for all models, and that the albedo was often underestimated. In addition, for several of the models, the snow albedo decreased at a faster rate or by a greater magnitude during the winter snow metamorphosis than the observed albedo. Both the temperature dependent schemes and the prognostic schemes showed shortcomings.     

The impact of implementing the bare essentials of surface transfer land surface scheme into the BMRC GCM

This study describes the first order impacts of incorporating a complex land-surface scheme, the bare essentials of surface transfer (BEST), into the Australian Bureau of Meteorology Research Centre (BMRC) global atmospheric general circulation model (GCM). Land seasonal climatologies averaged over the last six years of integrations after equilibrium from the GCM with BEST and without BEST (the control) are compared. The modeled results are evaluated with comprehensive sources of data, including the layer-cloud climatologies from the international satellite cloud climatology project (ISCCP) data from 1983 to 1991 and the surface-observed global data of Warren et al., a five-year climatology of surface albedo estimated from earth radiation budget experiment (ERBE) top-of-the-atmosphere (TOA) radiatioe fluxes, global grid point datasets of precipitation, and the climatological analyses of surface evaporation and albedo. Emphasis is placed on the surface evaluation of simulations of landsurface conditions such as surface roughness, surface albedo and the surface wetness factor, and on their effects on surface evaporation, precipitation, layer-cloud and surface temperature. The improvements due to the inclusion of BEST are: a realistic geographical distribution of surface roughness, a decrease in surface albedo over areas with seasonal snow cover, and an increase in surface albedo over snow-free land. The simulated reduction in surface evaporation due, in part, to the biophysical control of vegetation, is also consistent with the previous studies. Since the control climate has a dry bias, the overall simulations from the GCM with BEST are degraded, except for significant improvements for the northern winter hemisphere because of the realistic vegetation-masking effects. The implications of our results for synergistic developments of other aspects of model parameterization schemes such as boundary layer dynamics, clouds, convection and rainfall are discussed.     

The Thermodynamic Effects of Sublimating, Blowing Snow in the Atmospheric Boundary Layer

A seasonal snowcover blankets much of Canada during wintertime. In such an environment, the frequency of blowing snow events is relatively high and can have important meteorological and hydrological impacts. Apart from the transport of snow, the thermodynamic impact of sublimating blowing snow in air near the surface can be investigated. Using a time or fetch-dependent blowing snow model named 'PIEKTUK' that incorporates prognostic equations for a spectrum of sublimating snow particles, plus temperature and humidity distributions, it is found that the sublimation of blowing snow can lead to temperature decreases of the order of 0.5 °C and significant water vapour increases in the near-surface air. Typical predicted snow removal rates due to sublimation of blowing snow are several millimetres snow water equivalent per day over open Arctic tundra conditions. The model forecast sublimation rates are most sensitive to humidity, as well as wind speed, temperature and particle distributions, with a maximum value in sublimation typically found approximately 1 km downstream from blowing snow initiation. This suggests that the sublimation process is self-limiting despite ongoing transport of snow by wind, yielding significantly lower values of blowing snow sublimation rates (nearly two-thirds less) compared to situations where the thermodynamic feedbacks are neglected. The PIEKTUK model may provide the necessary thermodynamic inputs or blowing snow parameterizations for mesoscale models, allowing the assessment of the contribution of blowing snow fluxes, in more complex situations, to the moisture budgets of high-latitude regions.     

Cloud albedo feedback and the super greenhouse effect in a global coupled GCM

Two competing cloud-radiative feedbacks identified in previous studies i.e., cloud albedo feedback and the super greenhouse effect, are examined in a sensitivity study with a global coupled ocean-atmosphere general circulation model. Cloud albedo feedback is strengthened in a sensitivity experiment by lowering the sea-surface temperature (SST) threshold in the specified cloud albedo feedback scheme. This simple parameterization requires coincident warm SSTs and deep convection for upper-level cloud albedos to increase. The enhanced cloud albedo feedback in the sensitivity experiment results in decreased maximum values of SST and cooler surface temperatures over most areas of the planet. There is also a cooling of the tropical troposphere with attendant global changes of atmospheric circulation reminiscent of those observed during La Niña or cold events in the Southern Oscillation. The strengthening of the cloud albedo feedback only occurs over warm tropical oceans (e.g., the western Pacific warm pool), where there is increased albedo, decreased absorbed solar radiation at the surface, stronger surface westerlies, enhanced westward currents, lower temperatures, and decreased precipitation and evaporation. However, the weakened convection over the tropical western Pacific Ocean alters the large-scale circulation in the tropics such that there is increased upper-level divergence over tropical land areas and the tropical Indian Ocean. This results in increased precipitation in those regions and intensified monsoonal regimes. The enhanced precipitation over tropical land areas produces increased clouds and albedo and wetter and cooler land surfaces. These additional contributions to decreased absorbed solar input at the surface combine with similar changes over the tropical oceans to produce the global cooling associated with the stronger cloud albedo feedback. Increased low-level moisture convergence and precipitation over the tropical Indian Ocean enhance slightly the super greenhouse effect there. But the stronger cloud albedo feedback is still the dominant effect, although cooling of SSTs in that region is less than in the tropical western Pacific Ocean. The sensitivity experiment demonstrates how a regional change of radiative forcing is quickly transmitted globally through a combination of radiative and dynamical processes in the coupled model. This study points to the uncertainties involved with the parameterization of cloud albedo and the major implications of such parameterizations concerning the maximum values of SST, global climate sensitivity, and climate change.Support is provided by the Office of Health and Environmental Research of the U.S. Department of Energy, as part of its Carbon Dioxide Research Program.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

The Albedo of Vegetated Land Surfaces: Systems Analysisand Mathematical Modeling

Summary The albedo of vegetated land surfaces (surface albedo) is a key factor in climate modeling and in mechanistic accounting of many ecological processes. This paper proposes a testable numerical equation for the analysis and projection of surface albedo. Conceptualized as the manifestation of a canopy elements-determined basic property after modifications by temporal and spatial circumstances, surface albedo was depicted analytically in relation to 11 driving variables (leaf size, leaf life span, relative leaf age, canopy leaf cover, relative stem cover, vegetation height, stress-calendar day, drought indicator, optical air mass, station atmospheric pressure, snow cover). With peripheral algorithms developed to derive all but two of those variables, surface albedo was linked ultimately to eight rudimentary factors (calendar day, latitude, elevation, vegetation height, dominant plant species, monthly air temperature, monthly precipitation, snow cover). The analytical framework, and then its coefficient values, for surface albedo were generally supported by a series of statistical evaluations in terms of: (i) the equation’s ability to capture, by regression fitting, the variation in the surface albedo of 26 forests (135 data points) distributed around the world; (ii) the quantitative significance of individual driving variables; (iii) the randomness of residual or error distributions; (iv) the performance of the forests-fitted equation in extrapolative prediction of surface albedo against independent data for 8 deforested sites (93 data points) and for 3 types of vegetation (7 data points) at the Arctic treeline. Compared to the data, the fitted or projected albedo values had a margin of error generally within ±10%. The individual coefficient values and component functions of the final equation were consistent with their supposed mechanistic underpinnings, based on independent information from the literature. The equation shed new insight into the quantitative behavior of surface albedo, and upon further validation, should be useful for modeling surface albedo as a key land surface-atmosphere feedback link that varies and interacts with climate and vegetation. Received August 18, 1997     

Assessment of GCM simulated snow albedo using direct observations

 Annual cycles of monthly albedos simulated with a general circulation model (GCM) are compared with surface observations. The data observed at 35 stations are retrieved from the Global Energy Balance Archive (GEBA) and drawn from the soil moisture and meteorological observations in the former Soviet Union. The model data are obtained with the ECHAM4 GCM in a ten-year simulation of the present-day climate at T106 resolution. The model calculated albedo values are modified before they are compared with the surface observations: They are interpolated to the stations and adjusted to account for altitude differences and fractional forest area. During the snow-free period, the model underestimates the albedo by up to 0.05 at the stations (with values between 0.2 and 0.25 measured over short grass) because the albedo for grassland is too low in the model. During the period with seasonal snow cover, the model underestimates the albedo by up to 0.2 at stations in Russia, Scandinavia and Canada, which experience severe winters. This underestimation is due to an oversimplified parameterization of the snow covered grid fraction and an inadequate linear relation between snow albedo and temperature. The derivative of albedo with respect to the forest fraction implemented in ECHAM is in line with the observations, although a small overestimation of the model’s gradient has been detected. Received: 3 July 1998 / Accepted: 24 December 1998     

Investigations on meteorological conditions for elevated PM2.5 in Fairbanks,Alaska

The relationships between meteorological conditions (temperature, wind-speed and direction, relative humidity, surface-inversion depth and strength, and stability) and PM_2.5 concentrations in Fairbanks, Alaska were investigated using ten years of observational data. The results show that during wintertime (November through February) PM_2.5 concentrations exceeding the 24 h National Air Quality Standard (35 μg/m³) occurred under calm wind, extremely low temperature (≤20 °C) and moisture (water-vapor pressure < 2 hPa) multiday surface-inversion conditions that trap the pollutants in the breathing level and inhibit transport of polluted air out of Fairbanks. PM_2.5 concentrations tend to be higher under stable than other conditions, but are not sensitive to the degree of stability. The presence of a surface inversion and calm wind are necessary, but in combination with low temperatures and humidity, the conditions are sufficient for high PM_2.5 concentrations. The low temperatures are required because they lead to increased emission rates from domestic heating and power production. During multiday inversions with temperatures above ? 20 °C, high relative humidity (> 75%) partly caused by water-vapor emission reduces PM_2.5 concentrations.     

Parametrization schemes of incident radiation in the North Water polynya

Abstract

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.     

Evaluation of a high-resolution regional climate simulation over Greenland

A simulation of the 1991 summer has been performed over south Greenland with a coupled atmosphere–snow regional climate model (RCM) forced by the ECMWF re-analysis. The simulation is evaluated with in-situ coastal and ice-sheet atmospheric and glaciological observations. Modelled air temperature, specific humidity, wind speed and radiative fluxes are in good agreement with the available observations, although uncertainties in the radiative transfer scheme need further investigation to improve the model’s performance. In the sub-surface snow-ice model, surface albedo is calculated from the simulated snow grain shape and size, snow depth, meltwater accumulation, cloudiness and ice albedo. The use of snow metamorphism processes allows a realistic modelling of the temporal variations in the surface albedo during both melting periods and accumulation events. Concerning the surface albedo, the main finding is that an accurate albedo simulation during the melting season strongly depends on a proper initialization of the surface conditions which mainly result from winter accumulation processes. Furthermore, in a sensitivity experiment with a constant 0.8 albedo over the whole ice sheet, the average amount of melt decreased by more than 60%, which highlights the importance of a correctly simulated surface albedo. The use of this coupled atmosphere–snow RCM offers new perspectives in the study of the Greenland surface mass balance due to the represented feedback between the surface climate and the surface albedo, which is the most sensitive parameter in energy-balance-based ablation calculations.     

CO2 climate sensitivity and snow-sea-ice albedo parameterization in an atmospheric GCM coupled to a mixed-layer ocean model

The snow-sea-ice albedo parameterization in an atmospheric general circulation model (GCM), coupled to a simple mixed-layer ocean and run with an annual cycle of solar forcing, is altered from a version of the same model described by Washington and Meehl (1984). The model with the revised formulation is run to equilibrium for 1 × CO₂ and 2 × CO₂ experiments. The 1 ×CO₂ (control) simulation produces a global mean climate about 1° warmer than the original version, and sea-ice extent is reduced. The model with the altered parameterization displays heightened sensitivity in the global means, but the geographical patterns of climate change due to increased carbon dioxide (CO₂) are qualitatively similar. The magnitude of the climate change is affected, not only in areas directly influenced by snow and ice changes but also in other regions of the globe, including the tropics where sea-surface temperature, evaporation, and precipitation over the oceans are greater. With the less-sensitive formulation, the global mean surface air temperature increase is 3.5 °C, and the increase of global mean precipitation is 7.12%. The revised formulation produces a globally averaged surface air temperature increase of 4.04 °C and a precipitation increase of 7.25%, as well as greater warming of the upper tropical troposphere. Sensitivity of surface hydrology is qualitatively similar between the two cases with the larger-magnitude changes in the revised snow and ice-albedo scheme experiment. Variability of surface air temperature in the model is comparable to observations in most areas except at high latitudes during winter. In those regions, temporal variation of the sea-ice margin and fluctuations of snow cover dependent on the snow-ice-albedo formulation contribute to larger-than-observed temperature variability. This study highlights an uncertainty associated with results from current climate GCMs that use highly parameterized snow-sea-ice albedo schemes with simple mixed-layer ocean models.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

Studying the wintering conditions of winter crops from the satellite and ground-based observations (A case study for the Belgorod oblast)

The method is proposed for assessing the wintering conditions of winter crops with the accuracy to separate sown areas based on the joint use of the data of remote sensing and ground-based observations. The dependence is revealed between snow depth and snow albedo in the red band (MOD09GQ data). Geoinformation mapping of wintering conditions of winter crops cultivated in the Belgorod oblast is carried out for the winter period of 2012/2013.