Northern hemisphere snow: measurement, modelling and predictability

Northern hemisphere snow water equivalent (SWE) distribution from remote sensing (SSM/I), the ERA40 reanalysis product and the HadCM3 general circulation model are compared. Large differences are seen in the February climatologies, particularly over Siberia. The SSM/I retrieval algorithm may be overestimating SWE in this region, while comparison with independent runoff estimates suggest that HadCM3 is underestimating SWE. Treatment of snow grain size and vegetation parameterizations are concerns with the remotely sensed data. For this reason, ERA40 is used as `truth' for the following experiments. Despite the climatology differences, HadCM3 is able to reproduce the distribution of ERA40 SWE anomalies when assimilating ERA40 anomaly fields of temperature, sea level pressure, atmospheric winds and ocean temperature and salinity. However when forecasts are released from these assimilated initial states, the SWE anomaly distribution diverges rapidly from that of ERA40. No predictability is seen from one season to another. Strong links between European SWE distribution and the North Atlantic Oscillation (NAO) are seen, but forecasts of this index by the assimilation scheme are poor. Longer term relationships between SWE and the NAO, and SWE and the El Ni\~no-Southern Oscillation (ENSO) are also investigated in a multi-century run of HadCM3. SWE is impacted by ENSO in the Himalayas and North America, while the NAO affects SWE in North America and Europe. While significant connections with the NAO index were only present in DJF (and to an extent SON), the link between ENSO and February SWE distribution was seen to exist from the previous JJA ENSO index onwards. This represents a long lead time for SWE prediction for hydrological applications such as flood and wildfire forecasting. Further work is required to develop reliable large scale observation-based SWE datasets with which to test these model-derived connections.

The effects of variation in snow properties on snow mass estimation using the Chang algorithm

Estimating snow mass at continental scales is difficult but important for understanding landatmosphere interactions, biogeochemical cycles and Northern latitudes’ hydrology. Remote sensing provides the only consistent global observations, but the uncertainty in measurements is poorly understood. Existing techniques for the remote sensing of snow mass are based on the Chang algorithm, which relates the absorption of Earth-emitted microwave radiation by a snow layer to the snow mass within the layer. The absorption also depends on other factors such as the snow grain size and density, which are assumed and fixed within the algorithm. We examine the assumptions, compare them to field measurements made at the NASA Cold Land Processes Experiment (CLPX) Colorado field site in 2002–3, and evaluate the consequences of deviation and variability for snow mass retrieval. The accuracy of the emission model used to devise the algorithm also has an impact on its accuracy, so we test this with the CLPX measurements of snow properties against SSM/I and AMSR-E satellite measurements.

Snow-pit measurements on Atka Bay landfast sea ice during ANT-Land 2012/2013 season

Up to now, snow cover on Antarctic sea ice and its impact on radar backscatter, particularly after the onset of freeze/thaw processes, are not well understood. Here we present a combined analysis of in situ observations of snow properties from the landfast sea ice in Atka Bay, Antarctica, and high-resolution TerraSAR-X backscatter data, for the transition from austral spring (November 2012) to summer (January 2013). The physical changes in the seasonal snow cover during that time are reflected in the evolution of TerraSAR-X backscatter. We are able to explain 76-93% of the spatio-temporal variability of the TerraSAR-X backscatter signal with up to four snowpack parameters with a root-mean-squared error of 0.87-1.62 dB, using a simple multiple linear model. Over the complete study, and especially after the onset of early-melt processes and freeze/thaw cycles, the majority of variability in the backscatter is influenced by changes in snow/ice interface temperature, snow depth and top-layer grain size. This suggests it may be possible to retrieve snow physical properties over Antarctic sea ice from X-band SAR backscatter.

(Table 3) Air temperatures, and snow and ice characteristics of fresh and brackish water lakes in the Northwest Territories, Canada

The algorithms designed to estimate snow water equivalent (SWE) using passive microwave measurements falter in lake-rich high-latitude environments due to the emission properties of ice covered lakes on low frequency measurements. Microwave emission models have been used to simulate brightness temperatures (Tbs) for snowpack characteristics in terrestrial environments but cannot be applied to snow on lakes because of the differing subsurface emissivities and scattering matrices present in ice. This paper examines the performance of a modified version of the Helsinki University of Technology (HUT) snow emission model that incorporates microwave emission from lake ice and sub-ice water. Inputs to the HUT model include measurements collected over brackish and freshwater lakes north of Inuvik, Northwest Territories, Canada in April 2008, consisting of snowpack (depth, density, and snow water equivalent) and lake ice (thickness and ice type). Coincident airborne radiometer measurements at a resolution of 80x100 m were used as ground-truth to evaluate the simulations. The results indicate that subsurface media are simulated best when utilizing a modeled effective grain size and a 1 mm RMS surface roughness at the ice/water interface compared to using measured grain size and a flat Fresnel reflective surface as input. Simulations at 37 GHz (vertical polarization) produce the best results compared to airborne Tbs, with a Root Mean Square Error (RMSE) of 6.2 K and 7.9 K, as well as Mean Bias Errors (MBEs) of -8.4 K and -8.8 K for brackish and freshwater sites respectively. Freshwater simulations at 6.9 and 19 GHz H exhibited low RMSE (10.53 and 6.15 K respectively) and MBE (-5.37 and 8.36 K respectively) but did not accurately simulate Tb variability (R= -0.15 and 0.01 respectively). Over brackish water, 6.9 GHz simulations had poor agreement with airborne Tbs, while 19 GHz V exhibited a low RMSE (6.15 K), MBE (-4.52 K) and improved relative agreement to airborne measurements (R = 0.47). Salinity considerations reduced 6.9 GHz errors substantially, with a drop in RMSE from 51.48 K and 57.18 K for H and V polarizations respectively, to 26.2 K and 31.6 K, although Tb variability was not well simulated. With best results at 37 GHz, HUT simulations exhibit the potential to track Tb evolution, and therefore SWE through the winter season.

Temperature time series and physical properties of snow samples of a high-arctic permafrost site on Svalbard, Norway

Independent measurements of radiation, sensible and latent heat fluxes and the ground heat flux are used to describe the annual cycle of the surface energy budget at a high-arctic permafrost site on Svalbard. During summer, the net short-wave radiation is the dominant energy source, while well developed turbulent processes and the heat flux in the ground lead to a cooling of the surface. About 15% of the net radiation is consumed by the seasonal thawing of the active layer in July and August. The Bowen ratio is found to vary between 0.25 and 2, depending on water content of the uppermost soil layer. During the polar night in winter, the net long-wave radiation is the dominant energy loss channel for the surface, which is mainly compensated by the sensible heat flux and, to a lesser extent, by the ground heat flux, which originates from the refreezing of the active layer. The average annual sensible heat flux of -6.9 W/m**2 is composed of strong positive fluxes in July and August, while negative fluxes dominate during the rest of the year. With 6.8 W/m**2, the latent heat flux more or less compensates the sensible heat flux in the annual average. Strong evaporation occurs during the snow melt period and particularly during the snow-free period in summer and fall. When the ground is covered by snow, latent heat fluxes through sublimation of snow are recorded, but are insignificant for the average surface energy budget. The near-surface atmospheric stratification is found to be predominantly unstable to neutral, when the ground is snow-free, and stable to neutral for snow-covered ground. Due to long-lasting near-surface inversions in winter, an average temperature difference of approximately 3 K exists between the air temperature at 10 m height and the surface temperature of the snow.

(Table 4) Daily mean spectral snow albedo at different wavelengths measured at Neumayer, Antarctica

Spectral albedo in high resolution, from 290 to 1050 nm, has been measured at Neumayer, Antarctica, (70°39' S, 8°15' W) during the austral summer 2003/2004. At 500 nm, the spectral albedo nearly reaches unity, with slightly lower values below and above 500 nm. Above 600 nm, the spectral albedo decreases to values between 0.45 and 0.75 at 1000 nm. For one cloudless case an albedo up to 1.01 at 500 nm could be determined. This can be explained by the larger directional component of the snow reflectivity for direct incidence, combined with a slightly mislevelled sensor and the snow surface not being perfectly horizontal. A possible explanation for an observed decline in albedo is an increase in snow grain size. The theoretically predicted increase in albedo with increasing solar zenith angle (SZA) could not be observed. This is explained by the small range of SZA during albedo measurements, combined with the effect of changing snow conditions outweighing the effect of changing SZA. The measured spectral albedo serves as input for radiative transfer models, describing radiation conditions in Antarctica.

Évaluation de la modélisation de la taille de grain de neige du modèle multi-couches thermodynamique SNOWPACK: implication dans l'évaluation des risques d'avalanches

Résumé: L’Institut pour l'étude de la neige et des avalanches en Suisse (SLF) a développé SNOWPACK, un modèle thermodynamique multi-couches de neige permettant de simuler les propriétés géophysiques du manteau neigeux (densité, température, taille de grain, teneur en eau, etc.) à partir desquelles un indice de stabilité est calculé. Il a été démontré qu’un ajustement de la microstructure serait nécessaire pour une implantation au Canada. L'objectif principal de la présente étude est de permettre au modèle SNOWPACK de modéliser de manière plus réaliste la taille de grain de neige et ainsi obtenir une prédiction plus précise de la stabilité du manteau neigeux à l’aide de l’indice basé sur la taille de grain, le Structural Stability Index (SSI). Pour ce faire, l’erreur modélisée (biais) par le modèle a été analysée à l’aide de données précises sur le terrain de la taille de grain à l’aide de l’instrument IRIS (InfraRed Integrated Sphere). Les données ont été recueillies durant l’hiver 2014 à deux sites différents au Canada : parc National des Glaciers, en Colombie-Britannique ainsi qu’au parc National de Jasper. Le site de Fidelity était généralement soumis à un métamorphisme à l'équilibre tandis que celui de Jasper à un métamorphisme cinétique plus prononcé. Sur chacun des sites, la stratigraphie des profils de densités ainsi des profils de taille de grain (IRIS) ont été complétés. Les profils de Fidelity ont été complétés avec des mesures de micropénétromètre (SMP). L’analyse des profils de densité a démontré une bonne concordance avec les densités modélisées (R[indice supérieur 2]=0.76) et donc la résistance simulée pour le SSI a été jugée adéquate. Les couches d’instabilités prédites par SNOWPACK ont été identifiées à l’aide de la variation de la résistance dans les mesures de SMP. L’analyse de la taille de grain optique a révélé une surestimation systématique du modèle ce qui est en accord avec la littérature. L’erreur de taille de grain optique dans un environnement à l’équilibre était assez constante tandis que l’erreur en milieux cinétique était plus variable. Finalement, une approche orientée sur le type de climat représenterait le meilleur moyen pour effectuer une correction de la taille de grain pour une évaluation de la stabilité au Canada.

Inorganic carbon and geochemistry measurements from landfast sea ice in Resolute Passage, Nunavut, Canada, as part of the Arctic-ICE project, May - June 2010

We conducted a six-week investigation of the sea ice inorganic carbon system during the winter-spring transition in the Canadian Arctic Archipelago. Samples for the determination of sea ice geochemistry were collected in conjunction with physical and biological parameters as part of the 2010 Arctic-ICE (Arctic - Ice-Covered Ecosystem in a Rapidly Changing Environment) program, a sea ice-based process study in Resolute Passage, Nunavut. The goal of Arctic-ICE was to determine the physical-biological processes controlling the timing of primary production in Arctic landfast sea ice and to better understand the influence of these processes on the drawdown and release of climatically active gases. The field study was conducted from 1 May to 21 June, 2010.