The general objective of this paper is to estimate the snow water equivalent (SWE) of the La Grande River watershed (northern Quebec), using passive-microwave data from the SSM/I sensor. Particular emphasis is placed on the analysis of SSM/I multitemporal variations.

The analysis of a database containing observations for three winters shows that the brightness temperatures of the snow decrease as the SWE increases for shallow snow covers. However, when the SWE is >180–200 mm, the relationship reverses. This is directly linked to the fraction of large snow crystals in the snow cover, since these are responsible for most of the volume scattering. The snow emissivity is lower for shallow snow covers, since the higher temperature gradient is responsible for the quick formation of large snow crystals. For SWE >80–200 mm, the temperature gradient decreases and large crystal formation is minimal. Since volume scattering is lower, snow emissivity tends to increase. The observations confirm what was observed by Mätzler and others (1982) and Mätzler (1994).

Two regression lines were used to estimate the SWE for the beginning and the end of winter. This approach appears to be better, since it takes into account the structure of snow cover. The results were used to derive representative maps of the SWE.

Northern Hemisphere snow cover varies greatly through the year, and the presence of snow has a large impact on interactions between the land surface and the atmosphere. This paper outlines the representation of snow cover in the Hadley Centre GCM, and compares simulated snow cover with satellite and ground-based observations. Climate warming in a simulation with increased concentrations of CO2 and sulphate aerosols is found to lead to larger reductions in snow cover over North Ameriea and Europe than over Asia.

Snow cover in the intermittent snow zone of the Sierra Nevada can occupy more than 10 000 km2 of the mountain range, but it has received relatively little attention in river forecasting. Snow is deposited at lower elevations only during the cold storms of winter, and remains there only for a few days or weeks. When cold storms have created a thin snow cover at low elevations, a subsequent warm storm can melt this snow in just a few hours and increase the runoff response dramatically. Operational hydrological models and river-forecasting procedures have tended to overlook contributions from the intermittent-snow zone, focusing instead on rainfall-runoff or melt from the snowpack zone at higher elevations. Data-collection efforts are minimal in this zone, too. Ideally, spatially distributed models of snowmelt and runoff generation are needed to account for the typically large differences in snow cover on different aspects in the intermittent snow zone. Although aircraft and satellite imagery would be most desirable to monitor the distribution of snow cover in the intermittent-snow zone, even a few climate stations that report precipitation type and snow presence would be a major improvement over the present situation in the Sierra Nevada.

The general status of cryospheric datasets required in climate model studies is reviewed. Datasets are necessary as boundary conditions, and for validation purposes. The former application is decreasing as cryospheric variables are increasingly being derived prognostically. By contrast, the scope of cryospheric parameters that can be validated is expanding. Cryospheric datasets suitable for validation studies are reported and areas where data are lacking are identified.

The perennial ice concentration in the Beaufort Sea was examined using active- and passive-microwave observations. We compared the ice type and concentration estimates from SSM/I and ERS-1 SAR data over a seasonal cycle from January 1992 to January 1993. It was found the multi-year (MY) ice-concentration estimates from the SAR data were very stable and were nearly equivalent to the ice concentration estimated at the end of the previous summer. We contrast this with the variability of the MY ice-concentration and ice-fraction estimates obtained using the NASA Team algorithm. The passive- and active-microwave algorithms provide total ice concentrations that are comparable during the winter, hut the passive estimates are significantly lower during the summer. Passive-microwave estimates of multi-year-ice concentrations are consistently lower (up to 30%) than those from the SAR data. We discuss reasons for these discrepancies and the possible biases introduced by the active and passive algorithms.

Although the formation and melt of sea ice are primarily functions of the annual radiation cycle, atmospheric sensible-heat forcing does serve to delay or advance the timing of such events. Additionally, if atmospheric conditions in the Arctic were to vary due to climate change it may have significant influence on ice conditions. Therefore, this paper investigates a methodology to determine melt-onset dale distribution, both spatially and temporally, in the Arctic Ocean and surrounding sea-ice covered regions.

Melt determination is made by a threshold technique using the spectral signatures of the horizontal brightness temperatures (19 GHz horizontal channel minus the 37 GHz horizontal channel) obtained from the Special Sensor Microwave Imager (SSM/I) passive-microwave sensor. Passive-microwave observations are used to identify melt because of the large increase in emissivity that occurs when liquid water is present. Emissivity variations are observed in the brightness temperatures due to the different scattering, absorption and penetration depths of the snowpack from the available satellite channels during melt. Monitoring the variations in the brightness temperatures allows the determination of melt-onset dates.

Analysis of daily brightness temperature data allows spatial variations in the date of the snow inch onset for sea ice to be detected. Since the data are gridded on a daily basis, a climatology of daily melt-onset dates can be produced for the Arctic region. From this climatology, progression of melt can be obtained and compared inter-annually.

A suite of Arctic and Antarctic products is being prepared from Advanced Very High Resolution Radiometer (AVHRR) and ancillary data as part of NASA’s Polar Pathfinder effort. These products consist of twice-daily gridded fields of clear-sky surface temperature, surface albedo and cloud fraction, as well as daily ice velocities, for 1983–96. The products and their production methodology are summarized here, with examples demonstrating applications of the Pathfinder products for process studies and modeling.

A one-dimensional, atmospheric boundary-layer model is coupled to a thermodynamic ice model to estimate the surface turbulent fluxes over thick sea ice. The principal forcing parameters in this time-dependent model are the air temperature, humidity, and wind speed at a specified level (either at 2 m or at 850 mb) and the down-welling surface radiative fluxes, The free parameters are the air temperature, humidity, and wind-speed profiles below the specified level, the surface skin temperature and ice-temperature profile, and the surface turbulent fluxes. The goal is to determine how well we can estimate the turbulent surface heat and momentum fluxes using forcing parameters from atmospheric temperatures and radiative fluxes retrieved Irom the TlROS-N Operational Vertical Sounder TOVS) data.

Meteorological observations from the Lead Experiment (LeadEx, April 1992) ice camp are used to validate turbulent fluxes computed with the surface observations, and the results are used to compare with estimates based on radiosonde observations or with estimates based on TOVS data. We and that the TOVS-based estimates of the stress are significantly more accurate than those found with a constant geostrophic drag coefficient, with a rool mean square error about half as large. This improvement is due to stratification effects included in the boundary-layer model. The errors in the sensible heat flux estimates, however, are large compared Io the small mean values observed during the field experiment.

While the capability of global and regional climate models in reproducing current climate has significantly improved over the past few years, the confidence in model results for remote regions, or those where complex orography is a dominant feature, is still relatively low. This is, in part, linked to the lack of observational data for model verification and intercomparison purposes.

Glacier and permafrost observations are directly related to past and present energy flux patterns at the Earth-atmosphere interface and could be used as a proxy for air temperature and precipitation, particularly of value in remote mountain regions and boreal and Arctic zones where instrumental climate records are sparse or non-existent. It is particularly important to verify climate-model performance in these regions, as this is where most general circulation models (GCMs) predict the greatest changes in air temperatures in a warmer global climate.

Existing datasets from glacier and permafrost monitoring sites in remote and high altitudes are described in this paper; the data could be used in model-verification studies, as a means to improving model performance in these regions.

The effect of the spatial pattern of mass balance on the steady-state geometry of a glacier is examined using a Vialov -Nye glacier-flow model based on non-linear internal deformation of the ice with no basal motion. Surface profiles are predicted using a range of spatial variations of mass balance that include uniform shifts that cause a change in the mean and spatial patterns with zero mean representing changes in balance gradient and curvature. The corresponding effect on geometry induced by the different mass-balance patterns are described in terms of the volume and measures of surface slope and convexity. The change in glacier volume, slope and convexity induced by uniform changes in mass balance with non-zero mean are more than one order of magnitude larger than corresponding changes caused by spatial patterns of similar amplitude, but with zero mean. These results show that the mean mass balance contains most of the mass-balance information relevant to the dynamic changes of a glacier. An important consequence is that the memory of a change in climate, which is controlled by the consequent volume change, should be insensitive to the spatial pattern other than how that affects the mean. The spatial pattern of mass balance does induce small changes in the shape of the steady-state profile, which indicates the spatial pattern could affect the short time-scale response characteristics.

A prime input variable to uncoupled ice-sheet models, or for estimating the mass budget of present-day ice sheets, is the distribution of net surface mass balance. In most eases this is extrapolated from relatively few direct measurements over a limited time period, and parameterised in terms of continentality, surface elevation and other broad-scale indicators. Between 1989 and 1995 a series of oversnow traverses around the interior of the Lambert Glacier basin gathered a comprehensive set of data on snow accumulation and surface properties, surface climatology, ice-sheet velocities, elevations and thicknesses. Above the 2000 m level accumulation averages were found to be 76 kg ma−2a−1 (σ = 74), much lower than at similar elevations in Wilkes Land. The traverse route contains three distinct accumulation regimes: a relatively high accumulation zone along the western side despite higher average elevations, a very low accumulation zone in the south due to the effect of inereased continentality and an eastern sector that exhibits a rain-shadow effect in predominantly easterly wind fields. Inter-annual variability is high- with 1993 a colder year, recording only half the longer term average accumulation over the portion of the route that was measured.

An important component of models of the cryosphere is the calculation of accumulation rates over polar ice sheets. As a first-order approximation, many models rely on the assumption that temperature is the main controlling factor for precipitation. However, compilation of available ice-core data, including a new core from Taylor Dome, East Antarctica, suggests that precipitation is significantly decoupled from temperature for a large proportion of both the Greenland and Antarctic ice sheets. While the estimated glacial-to-interglacial change in temperature does not differ greatly among ice cores from each ice sheet, the estimated change in accumulation rate varies by more than a factor of 2. A simple vapor-pressure parameterization gives reasonable estimates of accumulation in the ice-sheet interior, but this is not necessarily the case close to the ice-sheet margin, where synoptic weather systems are important.

The amount of Arctic sea ice predicted by the Hadley Centre Global Cilimate Model (GCM) is evaluated using 15 years of passive-microwave data. While the Hadley model reproduces the seasonal cycle reasonably well, it underestimates the total area of sea ice by more than 3 × 106 km2 for most of the year. In the winter months, most of the underestimate in ice area results from the prediction of far too little ice in Hudson Bay and the Sea of Okhotsk, leading to an excess of up to 0.2 PW heat input to the atmosphere from Hudson Bay alone. The surface-energy budget of Hudson Bay is investigated using a mixture of surface observations (POLES), satellite data (ATSR, SSM/I and ISCCP) and output from the Goddard Data Assimilation Office analysis. Flux adjustments of the order of 200 Wm−2, resulting from anomalously high sea-surface temperatures in the Levitus (1982) climatology, are found to be the cause of the model’s underestimation of sea ice in both Hudson Bay and the Sea of Okhotsk. The fact that flux adjustments based on an inaccurate climatology will produce errors, even if the model physics is correct, underlines the need both for improved climatologies and for models accurate enough not to require flux adjustment.

Arctic precipitation as depicted in the National Center for Environmental Prediction (NGEP) and the National Center for Atmospheric Research (NCAR) reanalysis effort is evaluated using 6 hourly model output for the period 1986–93 in conjunction with gauge-corrected climatologies. Climatological fields from the model agree favorably with observations in terms of general spatio-temporal patterns, but with some notable differences. In particular, the precipitation maximum over the central Arctic (the region north of 70°N) is depicted in July, one month too early. Values are too low from August through December, resulting in underestimates of annual precipitation of about 40 mm. Despite these shortcomings, the modeled precipitation fields appear to be sufficiently realistic to represent a base for blending with other data to provide gridded fields suitable for use in climate studies and sea-ice models.

The surface-energy budget of the Arctic Ocean depends on the distribution of various sea-ice features that form by both mechanical and thermodynamic processes. Melt ponds, new ice and open water greatly affect the determination of surface albedo. However, even basic measurements of some surface-feature characteristics, such as areal extent of melt ponds, remain rare.

A method has been developed to assess the areal coverage of melt ponds, new ice and open water using video data from the Beaufort and Arctic Storms Experiment (BASE). A downward-looking video camera mounted on the underside of a Hercules C-130 aircraft provided clear images of the surface. Images acquired over multi-year ice on 21 September 1994 were analyzed using a spectral technique to determine the areal coverage of melt ponds, new ice and open water. Statistics from this analysis were then compared to previous field studies and to the Schramm and others (in press) sea-ice model.

Recent studies by several groups have indicated that the performance of general circulation models (GCMs) over the ice sheets is severely limited by the relatively low resolution of the models at the margins, where surface slopes are greatest. To provide accurate energy-budget estimates, resolutions of better than 0.5° are desirable, requiring nested or multiple gridding and accurate, high-resolution boundary conditions. Here we present a new, high-resolution (5 km) digital elevation model for the Antarctic ice sheet, derived from radar-altimeter data obtained from the geodetic phase of the satellite, ERS-1. These data have been combined with the revised ice-thickness grid reported in Bamber and Huybrechts (1996) to produce a bed- and surface-elevation dataset for use in regional and global climate and paleo-climaie modelling applications. The real level of spatial detail in the datasets has been examined with the aid of Landsat Thematic Mapper data. Imagery around Ice Stream D, West Antarctica, shows that the revised ice-thickness grid is accurately geolocated, and contains valuable fine-scale topographic detail beyond that available from the cartographic version of the data (Drewry, 1983). The surface topography in the region of the Ross Ice Shelf has been used to illustrate the level of detail in both the vertical and horizontal resolution of (he surface dataset. Laudsat data has also been used to examine features in the surface-elevation data. In particular, the location of the grounding zone, for Ice Streams D and E, derived from the two data sources shows good agreement. The results of this validation underscore the utility of the new datasets for high-resolution modelling, and highlight the limitations of the Folio maps for such applications.

Understanding the interaction of solar radiation with the ice cover is critical in determining the heat and mass balance of the Arctic ice pack, and in assessing potential impacts due to climate change. Because of the importance of the ice-albedo feedback mechanism, information on the surface state of the ice cover is needed. Observations of the surface slate of sea ice were obtained from helicopter photography missions made during the 1994 Arctic Ocean Section cruise. Photographs from one flight, taken during the height of the melt season (31 July 1994) at 76° N, 172° W, were analyzed in detail. Bare ice covered 82% of the total area, melt ponds 12%, and open water 6%, There was considerable variability in these area fractions on scales < 1 km2. Sample areas >2 3 km2 gave representative values of ice concentration and pond fraction. Melt ponds were numerous, with a number density of 1800 ponds km-2. The melt ponds had a mean area of 62 m2 a median area of 14 m2, and a size distribution that was well lit by a cumulative lognormal distribution. While leads make up only a small portion of the total area, they are the source of virtually all of the solar energy input to the ocean.