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1.
Observed reduction in recent sea ice areal extent and thickness has focused attention on the fact that the Arctic marine system appears to be responding to global‐scale climate variability and change. Passive microwave remote‐sensing data are the primary source underpinning these reports, yet problems remain in geophysical inversion of information on ice type and concentration. Uncertainty in sea‐ice concentration (SIC) retrievals is highest in the summer and fall, when water occurs in liquid phase within the snow–sea‐ice system. Of particular scientific interest is the timing and rate of new ice formation due to the control that this form of sea ice has on mass, energy and gas fluxes across the ocean–sea‐ice–atmosphere interface. In this paper we examine the critical fall freeze‐up period using in situ data from a ship‐based and aerial survey programme known as the Canadian Arctic Shelf Exchange study combined with microwave and optical Earth observations data. Results show that: (1) the overall physical conditions observed from aerial survey photography were well matched with coincident moderate‐resolution imaging spectroradiometer data and Radarsat ScanSAR imagery; (2) the shortwave albedo was linearly related to old ice concentration derived from survey photography; (3) the three SSM/I SIC algorithms (NASA Team (NT), NASA Team 2 (NT2), and Bootstrap (BT)) showed considerable discrepancies in pixel‐scale comparison with the Radarsat ScanSAR SICs well calibrated by the aerial survey data. The major causes of the discrepancies are attributed to (1) the inherent inability to detect the new thin ice in the NT and BT algorithms, (2) mismatches of the thin‐ice tie point of the NT2 algorithm, and (3) sub‐pixel ambiguity between the thin ice and the mixture of open water and sea ice. These results suggest the need for finer resolution of passive microwave sensors, such as AMSR‐E, to improve the precision of the SSM/I SIC algorithms in the marginal ice zone during early fall freeze‐up. Copyright © 2006 John Wiley & Sons, Ltd.  相似文献   

2.
An understanding of temporal evolution of snow on sea ice at different spatial scales is essential for improvement of snow parameterization in sea ice models. One of the problems we face, however, is that long‐term climate data are routinely available for land and not for sea ice. In this paper, we examine the temporal evolution of snow over smooth land‐fast first‐year sea ice using observational and modelled data. Changes in probability density functions indicate that depositional and drifting events control the evolution of snow distribution. Geostatistical analysis suggests that snowdrifts increased over the study period, and the orientation was related to the meteorological conditions. At the microscale, the temporal evolution of the snowdrifts was a product of infilling in the valleys between drifts. Results using two shore‐based climate reporting stations (Paulatuk and Tuktoyuktuk, NWT) suggest that on‐ice air temperature and relative humidity can be estimated using air temperature recorded at either station. Wind speed, direction and precipitation on ice cannot be accurately estimated using meteorological data from either station. The temporal evolution of snow distribution over smooth land‐fast sea ice was modelled using SnowModel and four different forcing regimes. The results from these model runs indicate a lack of agreement between observed distribution and model outputs. The reasons for these results are lack of meteorological measurements prior to the end of January, lack of spatially adequate surface topography and discrepancies between meteorological variables on land and ice. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

3.
Spring snow melt run‐off in high latitude and snow‐dominated drainage basins is generally the most significant annual hydrological event. Melt timing, duration, and flow magnitude are highly variable and influence regional climate, geomorphology, and hydrology. Arctic and sub‐arctic regions have sparse long‐term ground observations and these snow‐dominated hydrologic regimes are sensitive to the rapidly warming climate trends that characterize much of the northern latitudes. Passive microwave brightness temperatures are sensitive to changes in the liquid water content of the snow pack and make it possible to detect incipient melt, diurnal melt‐refreeze cycles, and the approximate end of snow cover on the ground over large regions. Special Sensor Microwave Imager (SSM/I) and Advanced Microwave Scanning Radiometer for EOS (AMSR‐E) passive microwave brightness temperatures (Tb) and diurnal amplitude variations (DAV) are used to investigate the spatial variability of snowmelt onset timing (in two stages, ‘DAV onset’ and ‘melt onset’) and duration for a complex sub‐arctic landscape during 2005. The satellites are sensitive to small percentages of liquid water, and therefore represent ‘incipient melt’, a condition somewhat earlier than a traditional definition of a melting snowpack. Incipient melt dates and duration are compared to topography, land cover, and hydrology to investigate the strength and significance of melt timing in heterogeneous landscapes in the Pelly River, a major tributary to the Yukon River. Microwave‐derived melt onset in this region in 2005 occurred from late February to late April. Upland areas melt 1–2 weeks later than lowland areas and have shorter transition periods. Melt timing and duration appear to be influenced by pixel elevation, aspect, and uniformity as well as other factors such as weather and snow mass distribution. The end of the transition season is uniform across sensors and across the basin in spite of a wide variety of pixel characteristics. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

4.
The geophysical, thermodynamic and dielectric properties of snow are important state variables that are known to be sensitive to Arctic climate variability and change. Given recent observations of changes in the Arctic physical system (Arctic Climate Impact Assessment, 2004), it is important to focus on the processes that give rise to variability in the horizontal, vertical and temporal dimensions of the life‐history of snow on sea ice. The objectives in this study are to present these ‘state’ variables and to investigate the processes that govern variability in the vertical, horizontal and temporal dimension by using a case study over land‐fast first‐year sea ice for the period December 2003 to June 2004. Results from two sampling areas (thin and thick snowpacks) show that differences in snowpack thickness can substantially change the vertical and temporal evolution of snow properties. During the late fall and early winter (cooling period) we measured no significant changes in the physical properties, except for thin snow‐cover salinity, which decreased throughout the period. Fall‐snow desalination was only observed under thin snowpacks with a rate of ?0·12 ppt day?1. Significant changes occurred in the late winter and early spring (warming period), especially for snow grain size. Snow grain kinetic growth of 0·25–0·48 mm·day?1 was measured coincidently with increasing salinity and wetness for both thin and thick snowpacks. Copyright © 2006 John Wiley & Sons, Ltd.  相似文献   

5.
Land surface albedo plays an important role in the radiation budget and global climate models. NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) provide 16‐day albedo product with 500‐m resolution every 8 days (MCD43A3). Some in‐situ albedo measurements were used as the true surface albedo values to validate the MCD43A3 product. As the 16‐day MODIS albedo retrievals do not include snow observations when there is ephemeral snow on the ground surface in a 16‐day period, comparisons between MCD43A3 and 16 day averages of field data do not agree well. Another reason is that the MODIS cannot detect the snow when the area is covered by clouds. The Advanced Microwave Scanning Radiometer for EOS (AMSR‐E) data are not affected by weather conditions and are a good supplement for optical remote sensing in cloudy weather. When the surface is covered by ephemeral snow, the AMSR‐E data can be used as the additional information to retrieve the snow albedo. In this study, we developed an improved method by using the MODIS products and the AMSR‐E snow water equivalent (SWE) product to improve the MCD43A3 short‐time snow‐covered albedo estimation. The MODIS daily snow products MOD10A1 and MYD10A1 both provide snow and cloud information from observations. In our study region, we updated the MODIS daily snow product by combining MOD10A1 and MYD10A1. Then, the product was combined with the AMSR‐E SWE product to generate new daily snow‐cover and SWE products at a spatial resolution of 500 m. New SWE datasets were integrated into the Noah Land Surface Model snow model to calculate the albedo above a snow surface, and these values were then utilized to improve the MODIS 16‐day albedo product. After comparison of the results with in‐situ albedo measurements, we found that the new corrected 16‐day albedo can show the albedo changes during the short snowfall season. For example, from January 25 to March 14, 2007 at the BJ site, the albedo retrieved from snow‐free observations does not indicate the albedo changes affected by snow; the improved albedo conforms well to the in‐situ measurements. The correlation coefficient of the original MODIS albedo and the in‐situ albedo is 0.42 during the ephemeral snow season, but the correlation coefficient of the improved MODIS albedo and the in‐situ albedo is 0.64. It is concluded that the new method is capable of capturing the snow information from AMSR‐E SWE to improve the short‐time snow‐covered albedo estimation. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

6.
We present a field‐data rich modelling analysis to reconstruct the climatic forcing, glacier response, and runoff generation from a high‐elevation catchment in central Chile over the period 2000–2015 to provide insights into the differing contributions of debris‐covered and debris‐free glaciers under current and future changing climatic conditions. Model simulations with the physically based glacio‐hydrological model TOPKAPI‐ETH reveal a period of neutral or slightly positive mass balance between 2000 and 2010, followed by a transition to increasingly large annual mass losses, associated with a recent mega drought. Mass losses commence earlier, and are more severe, for a heavily debris‐covered glacier, most likely due to its strong dependence on snow avalanche accumulation, which has declined in recent years. Catchment runoff shows a marked decreasing trend over the study period, but with high interannual variability directly linked to winter snow accumulation, and high contribution from ice melt in dry periods and drought conditions. The study demonstrates the importance of incorporating local‐scale processes such as snow avalanche accumulation and spatially variable debris thickness, in understanding the responses of different glacier types to climate change. We highlight the increased dependency of runoff from high Andean catchments on the diminishing resource of glacier ice during dry years.  相似文献   

7.
Dennis G. Dye 《水文研究》2002,16(15):3065-3077
This study investigated variability and trends in the annual snow‐cover cycle in regions covering high‐latitude and high‐elevation land areas in the Northern Hemisphere. The annual snow‐cover cycle was examined with respect to the week of the last‐observed snow cover in spring (WLS), the week of the first‐observed snow cover in autumn (WFS), and the duration of the snow‐free period (DSF). The analysis used a 29‐year time‐series (1972–2000) of weekly, visible‐band satellite observations of Northern Hemisphere snow cover from NOAA with corrections applied by D. Robinson of Rutgers University Climate Laboratory. Substantial interannual variability was observed in WLS, WFS and DSF (standard deviations of 0·8–1·1, 0·7–0·9 and 1·0–1·4 weeks, respectively), which is related directly to interannual variability in snow‐cover area in the regions and time periods of snow‐cover transition. Over the nearly three‐decade study period, WLS shifted earlier by 3–5 days/decade as determined by linear regression analysis. The observed shifts in the annual snow‐cover cycle underlie a significant trend toward a longer annual snow‐free period. The DSF increased by 5–6 days/decade over the study period, primarily as a result of earlier snow cover disappearance in spring. The observed trends are consistent with reported trends in the timing and length of the active growing season as determined from satellite observations of vegetation greenness and the atmospheric CO2 record. Copyright © 2002 John Wiley & Sons, Ltd.  相似文献   

8.
S. Pohl  P. Marsh 《水文研究》2006,20(8):1773-1792
Arctic spring landscapes are usually characterized by a mosaic of coexisting snow‐covered and bare ground patches. This phenomenon has major implications for hydrological processes, including meltwater production and runoff. Furthermore, as indicated by aircraft observations, it affects land‐surface–atmosphere exchanges, leading to a high degree of variability in surface energy terms during melt. The heterogeneity and related differences when certain parts of the landscape become snow free also affects the length of the growing season and the carbon cycle. Small‐scale variability in arctic snowmelt is addressed here by combining a spatially distributed end‐of‐winter snow cover with simulations of variable snowmelt energy balance factors for the small arctic catchment of Trail Valley Creek (63 km2). Throughout the winter, snow in arctic tundra basins is redistributed by frequent blowing snow events. Areas of above‐ or below‐average end‐of‐winter snow water equivalents were determined from land‐cover classifications, topography, land‐cover‐based snow surveys, and distributed surface wind‐field simulations. Topographic influences on major snowmelt energy balance factors (solar radiation and turbulent fluxes of sensible and latent heat) were modelled on a small‐scale (40 m) basis. A spatially variable complete snowmelt energy balance was subsequently computed and applied to the distributed snow cover, allowing the simulation of the progress of melt throughout the basin. The emerging patterns compared very well visually to snow cover observations from satellite images and aerial photographs. Results show the relative importance of variable end‐of‐winter snow cover, spatially distributed melt energy fluxes, and local advection processes for the development of a patchy snow cover. This illustrates that the consideration of these processes is crucial for an accurate determination of snow‐covered areas, as well as the location, timing, and amount of meltwater release from arctic catchments, and should, therefore, be included in hydrological models. Furthermore, the study shows the need for a subgrid parameterization of these factors in the land surface schemes of larger scale climate models. Copyright © 2005 John Wiley & Sons, Ltd.  相似文献   

9.
We apply the process‐based, distributed TOPKAPI‐ETH glacio‐hydrological model to a glacierized catchment (19% glacierized) in the semiarid Andes of central Chile. The semiarid Andes provides vital freshwater resources to valleys in Chile and Argentina, but only few glacio‐hydrological modelling studies have been conducted, and its dominant hydrological processes remain poorly understood. The catchment contains two debris‐free glaciers reaching down to 3900 m asl (Bello and Yeso glaciers) and one debris‐covered avalanche‐fed glacier reaching to 3200 m asl (Piramide Glacier). Our main objective is to compare the mass balance and runoff contributions of both glacier types under current climatic conditions. We use a unique dataset of field measurements collected over two ablation seasons combined with the distributed TOPKAPI‐ETH model that includes physically oriented parameterizations of snow and ice ablation, gravitational distribution of snow, snow albedo evolution and the ablation of debris‐covered ice. Model outputs indicate that while the mass balance of Bello and Yeso glaciers is mostly explained by temperature gradients, the Piramide Glacier mass balance is governed by debris thickness and avalanches and has a clear non‐linear profile with elevation as a result. Despite the thermal insulation effect of the debris cover, the mass balance and contribution to runoff from debris‐free and debris‐covered glaciers are similar in magnitude, mainly because of elevation differences. However, runoff contributions are distinct in time and seasonality with ice melt starting approximately four weeks earlier from the debris‐covered glacier, what is of relevance for water resources management. At the catchment scale, snowmelt is the dominant contributor to runoff during both years. However, during the driest year of our simulations, ice melt contributes 42 ± 8% and 67 ± 6% of the annual and summer runoff, respectively. Sensitivity analyses show that runoff is most sensitive to temperature and precipitation gradients, melt factors and debris cover thickness. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

10.
Based on the analysis of data of many-year actinometric observations, a considerable temporal (interannual, seasonal, synoptic, and diurnal) and spatial variability of the albedo of the snow-and-ice cover of a shallow lake is shown. The ranges of variations in the albedo of snow and ice for a wide spectrum of the state of surface and weather conditions are presented. The variability of the thickness and structure of snow-and-ice cover is analyzed for different periods in winter. The results of field experiments aimed to determine the degree of absorption of solar radiation by snow and ice are presented. The effective coefficients of absorption of solar radiation by snow and ice are determined. The comparison of the observed and calculated values of the under-ice radiation has shown that the determined coefficients adequately describe the absorption of solar radiation by snow-and-ice cover.  相似文献   

11.
It is well known that snow plays an important role in land surface energy balance; however, modelling the subgrid variability of snow is still a challenge in large‐scale hydrological and land surface models. High‐resolution snow depth data and statistical methods can reveal some characteristics of the subgrid variability of snow depth, which can be useful in developing models for representing such subgrid variability. In this study, snow depth was measured by airborne Lidar at 0.5‐m resolution over two mountainous areas in south‐western Wyoming, Snowy Range and Laramie Range. To characterize subgrid snow depth spatial distribution, measured snow depth data of these two areas were meshed into 284 grids of 1‐km × 1‐km. Also, nine representative grids of 1‐km × 1‐km were selected for detailed analyses on the geostatistical structure and probability density function of snow depth. It was verified that land cover is one of the important factors controlling spatial variability of snow depth at the 1‐km scale. Probability density functions of snow depth tend to be Gaussian distributions in the forest areas. However, they are eventually skewed as non‐Gaussian distribution, largely due to the no‐snow areas effect, mainly caused by snow redistribution and snow melt. Our findings show the characteristics of subgrid variability of snow depth and clarify the potential factors that need to be considered in modelling subgrid variability of snow depth.  相似文献   

12.
As large, high‐severity forest fires increase and snowpacks become more vulnerable to climate change across the western USA, it is important to understand post‐fire disturbance impacts on snow hydrology. Here, we examine, quantify, parameterize, model, and assess the post‐fire radiative forcing effects on snow to improve hydrologic modelling of snow‐dominated watersheds having experienced severe forest fires. Following a 2011 high‐severity forest fire in the Oregon Cascades, we measured snow albedo, monitored snow, and micrometeorological conditions, sampled snow surface debris, and modelled snowpack energy and mass balance in adjacent burned forest (BF) and unburned forest sites. For three winters following the fire, charred debris in the BF reduced snow albedo, accelerated snow albedo decay, and increased snowmelt rates thereby advancing the date of snow disappearance compared with the unburned forest. We demonstrate a new parameterization of post‐fire snow albedo as a function of days‐since‐snowfall and net snowpack energy balance using an empirically based exponential decay function. Incorporating our new post‐fire snow albedo decay parameterization in a spatially distributed energy and mass balance snow model, we show significantly improved predictions of snow cover duration and spatial variability of snow water equivalent across the BF, particularly during the late snowmelt period. Field measurements, snow model results, and remote sensing data demonstrate that charred forests increase the radiative forcing to snow and advance the timing of snow disappearance for several years following fire. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

13.
The magnitude and spatial distribution of snow on sea ice are both integral components of the ocean–sea‐ice–atmosphere system. Although there exists a number of algorithms to estimate the snow water equivalent (SWE) on terrestrial surfaces, to date there is no precise method to estimate SWE on sea ice. Physical snow properties and in situ microwave radiometry at 19, 37 and 85 GHz, V and H polarization were collected for a 10‐day period over 20 first‐year sea ice sites. We present and compare the in situ physical, electrical and microwave emission properties of snow over smooth Arctic first‐year sea ice for 19 of the 20 sites sampled. Physical processes creating the observed vertical patterns in the physical and electrical properties are discussed. An algorithm is then developed from the relationship between the SWE and the brightness temperature measured at 37 GHz (55°) H polarization and the air temperature. The multiple regression between these variables is able to account for over 90% of the variability in the measured SWE. This algorithm is validated with a small in situ data set collected during the 1999 field experiment. We then compare our data against the NASA snow thickness algorithm, designed as part of the NASA Earth Enterprise Program. The results indicated a lack of agreement between the NASA algorithm and the algorithm developed here. This lack of agreement is attributed to differences in scale between the Special Sensor Microwave/Imager and surface radiometers and to differences in the Antarctic versus Arctic snow physical and electrical properties. Copyright © 2003 John Wiley & Sons, Ltd.  相似文献   

14.
2010年春季至夏季在中山站附近的固定冰面开展了固定冰反照率观测.在春夏过渡期,观测期间的表面反照率呈下降趋势,平均反照率从9月的0.80下降到12月的0.62,整个观测期间的平均值为0.70.雪厚是影响反照率变化的重要因子,融化前期的反照率受表面温度影响较大,干雪期反照率对表面温度并不敏感.降雪可通过增加表面雪厚和减小表面积雪粒径显著增加反照率,云层则可通过吸收入射太阳光中的近红外波段增加反照率,降雪和阴天反照率可比晴天观测平均增加0.18和0.06;吹雪则可通过改变积雪光学厚度导致反照率发生显著变化.受太阳天顶角变化和积雪变性的共同影响,晴天或少云时的反照率在上午随太阳天顶角呈准线性递减,下午则几乎不发生变化;最高值、最低值分别出现在凌晨和下午.本文提出了一组分别表述厚干雪、薄干雪和湿雪反照率日变化的参数化方案,通过太阳天顶角的线性函数隐式考虑进了积雪变性的影响.相比常数反照率方案,该参数化方案能有效提高对反照率日变化的估算能力.  相似文献   

15.
Lake ice supports a range of socio‐economic and cultural activities including transportation and winter recreational actives. The influence of weather patterns on ice‐cover dynamics of temperate lakes requires further understanding for determining how changes in ice composition will impact ice safety and the range of ecosystem services provided by seasonal ice cover. An investigation of lake ice formation and decay for three lakes in Central Ontario, Canada, took place over the course of two winters, 2015–2016 and 2016–2017, through the use of outdoor digital cameras, a Shallow Water Ice Profiler (upward‐looking sonar), and weekly field measurements. Temperature fluctuations across 0°C promoted substantial early season white ice growth, with lesser amounts of black ice forming later in the season. Ice thickening processes observed were mainly through meltwater, or midwinter rain, refreezing on the ice surface. Snow redistribution was limited, with frequent melt events limiting the duration of fresh snow on the ice, leading to a fairly uniform distribution of white ice across the lakes in 2015–2016 (standard deviations week to week ranging from 3 to 5 cm), but with slightly more variability in 2016–2017 when more snow accumulated over the season (5 to 11 cm). White ice dominated the end‐of‐season ice composition for both seasons representing more than 70% of the total ice thickness, which is a stark contrast to Arctic lake ice that is composed mainly of black ice. This research has provided the first detailed lake ice processes and conditions from medium‐sized north‐temperate lakes and provided important information on temperate region lake ice characteristics that will enhance the understanding of the response of temperate lake ice to climate and provide insight on potential changes to more northern ice regimes under continued climate warming.  相似文献   

16.
A one‐dimensional energy and mass balance snow model (SNTHERM) has been modified for use with supraglacial snowpacks and applied to a point on Haut Glacier d'Arolla, Switzerland. It has been adapted to incorporate the underlying glacier ice and a site‐specific, empirically derived albedo routine. Model performance was tested against continuous measurements of snow depth and meltwater outflow from the base of the snowpack, and intermittent measurements of surface albedo and snowpack density profiles collected during the 1993 and 2000 melt seasons. Snow and ice ablation was simulated accurately. The timing of the daily pattern of meltwater outflow was well reproduced, although magnitudes were generally underestimated, possibly indicating preferential flow into the snowpack lysimeter. The model was used to assess the quantity of meltwater stored temporally within the unsaturated snowpack and meltwater percolation rates, which were found to be in agreement with dye tracer experiments undertaken on this glacier. As with other energy balance studies on alpine valley glaciers, the energy available for melt was dominated by net radiation (64%), with a sizable contribution from sensible heat flux (36%) and with a negligible latent heat flux overall, although there was more complex temporal variation on diurnal timescales. A basic sensitivity analysis indicated that melt rates were most sensitive to radiation, air temperature and snowpack density, indicating the need to accurately extrapolate/interpolate these variables when developing a spatially distributed framework for this model. Copyright © 2008 John Wiley & Sons, Ltd.  相似文献   

17.
The performance of temperature‐index melt models is particularly affected by the choice of near‐surface lapse rate used to determine the sum of positive daily temperatures at different elevations, and by the choice of factor used to relate this sum to the rate of melting. Data from the Langjökull ice cap are used in this study to quantify the influence of lapse‐rate and degree‐day factor variation on temperature‐index melt simulations. The lapse rate was significantly lower during summer than in spring or autumn, as a result of diabatic cooling, reducing boundary‐layer sensitivity to free‐air temperature change. The summer lapse rate was also significantly lower than the saturated adiabatic lapse rate. A sensitivity of approximately 600 mm water equivalent (w.e.) cumulative June–August melt per 0.1 °C 100 m–1 change in lapse rate was found across a 500‐m altitude range. The sensitivity to a 1‐mm w.e. °C–1 day–1 change in degree‐day factors varied more: from approximately 500 mm w.e. cumulative summer melt at low elevation to approximately 200 mm w.e. at high elevation, reflecting the decline in melt rates associated with the greater persistence of snow with increasing altitude. The determination of a degree‐day factor for snow is complicated by the densification of the ageing snowpack, but the application of a parameterization for near‐surface density on the basis of albedo helped account for the development of snow water equivalence. Lapse rate was parameterized as a function of standardized anomalies in 750 hPa reanalysis temperature and significantly improved the simulation of cumulative summer melt compared with models applying the saturated adiabatic lapse rate. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

18.
To improve simulations of regional‐scale snow processes and related cold‐season hydroclimate, the Community Land Model version 3 (CLM3), developed by the National Center for Atmospheric Research (NCAR), was coupled with the Pennsylvania State University/NCAR fifth‐generation Mesoscale Model (MM5). CLM3 physically describes the mass and heat transfer within the snowpack using five snow layers that include liquid water and solid ice. The coupled MM5–CLM3 model performance was evaluated for the snowmelt season in the Columbia River Basin in the Pacific Northwestern United States using gridded temperature and precipitation observations, along with station observations. The results from MM5–CLM3 show a significant improvement in the SWE simulation, which has been underestimated in the original version of MM5 coupled with the Noah land‐surface model. One important cause for the underestimated SWE in Noah is its unrealistic land‐surface structure configuration where vegetation, snow and the topsoil layer are blended when snow is present. This study demonstrates the importance of the sheltering effects of the forest canopy on snow surface energy budgets, which is included in CLM3. Such effects are further seen in the simulations of surface air temperature and precipitation in regional weather and climate models such as MM5. In addition, the snow‐season surface albedo overestimated by MM5–Noah is now more accurately predicted by MM5–CLM3 using a more realistic albedo algorithm that intensifies the solar radiation absorption on the land surface, reducing the strong near‐surface cold bias in MM5–Noah. The cold bias is further alleviated due to a slower snowmelt rate in MM5–CLM3 during the early snowmelt stage, which is closer to observations than the comparable components of MM5–Noah. In addition, the over‐predicted precipitation in the Pacific Northwest as shown in MM5–Noah is significantly decreased in MM5–CLM3 due to the lower evaporation resulting from the longer snow duration. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

19.
The retreat of mountain glaciers and ice caps has dominated the rise in global sea level and is likely to remain an import component of eustatic sea‐level rise in the 21st century. Mountain glaciers are critical in supplying freshwater to populations inhabiting the valleys downstream who heavily rely on glacier runoff, such as arid and semi‐arid regions of western China. Owing to recent climate warming and the consequent rapid retreat of many glaciers, it is essential to evaluate the long‐term change in glacier melt water production, especially when considering the glacier area change. This paper describes the structure, principles and parameters of a modified monthly degree‐day model considering glacier area variation. Water balances in different elevation bands are calculated with full consideration of the monthly precipitation gradient and air temperature lapse rate. The degree‐day factors for ice and snow are tuned by comparing simulated variables to observation data for the same period, such as mass balance, equilibrium line altitude and glacier runoff depth. The glacier area–volume scaling factor is calibrated with the observed glacier area change monitored by remote sensing data of seven sub‐basins of the Tarim interior basin. Based on meteorological data, the glacier area, mass balance and runoff are estimated. The model can be used to evaluate the long‐term changes of melt water in all glacierized basins of western China, especially for those with limited observation data. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

20.
The observed retreat of several Himalayan glaciers and snow packs is a cause of concern for the huge population in southern Asia that is dependent on the glacial‐fed rivers emanating from Himalayas. There is considerable uncertainty about how cryospheric recession in the Himalayan region will respond to climate change, and how the water resource availability will be affected. As a first step towards quantifying the contribution of glacier‐melt water, hydrograph separation of River Ganga at Rishikesh into its constituent components, namely (i) surface runoff, (ii) glacial ice‐melt and (iii) groundwater discharge has been done in this paper. A three‐component mixing model has been employed using the values of δ18O and electrical conductivity (EC) of the river water, and its constituents, to estimate the time‐varying relative fraction of each component. The relative fraction of the surface runoff peaks (70–90%) during winter, due to the near‐zero contribution of glacial ice‐melt, essentially represents the melting of surface snow from the catchment. The contribution of glacial ice‐melt to the stream discharge peaks during summer and monsoon reaches a maximum value of ～40% with an average of 32%. The fraction of groundwater discharge varies within a narrow range (15 ± 5%) throughout the year. On the basis of the variation in the d‐excess values of river water, it is also suggested that the snow‐melt and ice‐melt component has a significant fraction derived from winter precipitation with moisture source from mid‐latitude westerlies (also known as western disturbances). Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

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