Snow Layer Research Articles

The change and variability of snow cover in Kraków in a 100-year observation series

This article presents the results of research on the changes and variability of snow cover in Kraków in the 100-year period 1921/22–2020/21 and in its two sub-periods covering the years of the slow and rapid territorial, urban and industrial development of Kraków (respectively, 1921/22–1960/61 and 1961/62–2020/21). The long-term variability of the number of days with snow cover, the maximum depth of the snow layer, the dates of the beginning and end of snow cover duration in the winter season, the potential snow cover duration and the index of snow cover stability were analysed. The directions of changes in the snow cover in the last 100 winter seasons in Kraków correspond to the global changes in air temperature presented in the latest IPCC reports: until the end of the 1950s there were no significant trends, or only small trends were observed, whereas from the beginning of the 1960s faster changes in the snow cover duration and maximum seasonal snow depth have been visible. In the last 60 years (1961/62–2020/21), the impact of global changes in Kraków has been joined by the impact of territorial, demographic and industrial development of the city, causing significant negative trends in snow cover with relative values of less than −9% ∙ 10 years−1, both in the case of snow cover duration and its maximum depth in the winter season; these changes are statistically significant. Throughout the whole 100-year period (1921/22–2020/21) and in its second part (1961/62–2020/21), a decrease in snow cover stability has also been observed.

Rewilding Risks for Peatland Permafrost

Permafrost thaw is projected to reinforce climate warming by releasing large stocks of stored carbon. Rewilding northern high latitude regions with large herbivores has been proposed as a climate mitigation strategy to protect frozen soils and increase ecosystem resilience to climate warming. We explored the impact of summer reindeer density on subarctic peatlands by comparing 17 peatlands differing in reindeer density in Fennoscandia. We used a combination of high-resolution image analyses and field assessments along 50 transects to assess microtopography, surface water cover, vegetation, summer albedo, permafrost presence, soil temperature, soil nutrients and snow depth. Our results show that high summer reindeer densities fragment the characteristic bumpy topography of the peatlands, reducing the insulating soil properties and the probability of keeping permafrost in elevated hummocks. As a result, waterlogged lawns with surface water increase in size and reduce summer albedo. Furthermore, high reindeer density peatlands were associated with an increase in tall inedible shrubs and thicker snow layers. These changes may favor summer warming and reduce winter cooling of the soil thus accelerating permafrost loss. Our results suggest that high reindeer densities may reduce resilience of the peatland permafrost to climate warming. High densities of large herbivores will likely have different effects in well-drained uplands, but in the lowlands we studied, the complex cascading effects of summer trampling may well offset any climate-protection gained by browsing. Optimal use of wildlife management to mitigate global warming will thus require tuning herbivore densities to different ecosystem types across high northern landscapes.

Heterogeneous grain growth and vertical mass transfer within a snow layer under a temperature gradient

Abstract. Inside a snow cover, metamorphism plays a key role in snow evolution at different scales. This study focuses on the impact of temperature gradient metamorphism on a snow layer in its vertical extent. To this end, two cold-laboratory experiments were conducted to monitor a snow layer evolving under a temperature gradient of 100 K m−1 using X-ray tomography and environmental sensors. The first experiment shows that snow evolves differently in the vertical: in the end, coarser depth hoar is found in the center part of the layer, with covariance lengths about 50 % higher compared to the top and bottom areas. We show that this heterogeneous grain growth could be related to the temperature profile, to the associated crystal growth regimes, and to the local vapor supersaturation. In the second experiment, a non-disturbing sampling method was applied to enable a precise observation of the basal mass transfer in the case of dry boundary conditions. An air gap, characterized by a sharp drop in density, developed at the base and reached more than 3 mm after a month. The two reported phenomena, heterogeneous grain growth and basal mass loss, create heterogeneities in snow – in terms of density, grain and pore size, and ice morphology – from an initial homogeneous layer. Finally, we report the formation of hard depth hoar associated with an increase in specific surface area (SSA) observed in the second experiment with higher initial density. These microscale effects may strongly impact the snowpack behavior, e.g., for snow transport processes or snow mechanics.

Retrieval of snow layer and melt pond properties on Arctic sea ice from airborne imaging spectrometer observations

Abstract. A melting snow layer on Arctic sea ice, as a composition of ice, liquid water, and air, supplies meltwater that may trigger the formation of melt ponds. As a result, surface reflection properties are altered during the melting season and thereby may change the surface energy budget. To study these processes, sea ice surface reflection properties were derived from airborne measurements using imaging spectrometers. The data were collected over the closed and marginal Arctic sea ice zone north of Svalbard in May–June 2017. A retrieval approach based on different absorption indices of pure ice and liquid water in the near-infrared spectral range was applied to the campaign data. The technique enabled us to retrieve the spatial distribution of the liquid water fraction of a snow layer and the effective radius of snow grains. For observations from three research flights, liquid water fractions between 6.5 % and 17.3 % and snow grain sizes between 129 and 414 µm were derived. In addition, the melt pond depth was retrieved based on an existing approach that isolates the dependence of a melt pond reflection spectrum on the pond depth by eliminating the reflection contribution of the pond ice bottom. The application of the approach to several case studies revealed a high variability of melt pond depth, with maximum depths of 0.33 m. The results were discussed considering uncertainties arising from the airborne reflection measurements, the setup of radiative transfer simulations, and the retrieval method itself. Overall, the presented retrieval methods show the potential and the limitations of airborne measurements with imaging spectrometers to map the transition phase of the Arctic sea ice surface, examining the snow layer composition and melt pond depth.

Stress measurements in the weak layer during snow stability tests

Abstract The snow compression test is a snow stability test where an isolated column of snow is progressively loaded by tapping on it to induce failure in a possible weak layer. The test result provides valuable information about the propensity of failure initiation within the snowpack. However, different persons might tap with different force and thus reduce the reproducibility of the test results. The aim of this work was to quantify the influence of different test persons and different snowpacks on snow compression test results. We therefore let 62 persons tap on a stress measurement plate during a workshop of the European Avalanche Warning Services. Moreover, in the field, we performed stress measurements during 116 snow compression tests with 13 persons at eight different locations in the Alps. Data on persons’ body features and snow properties were also collected. Our results show that the stresses that reach a weak snow layer due to tapping are influenced by both the snowpack as well as different persons. Still, the data's scattering is surprisingly small for lower loading steps and decreases with depth. Therefore, we can deduce that, especially when avalanche conditions are particularly dangerous, snow compression test results are quite reproducible.

An empirical model to calculate snow depth from daily snow water equivalent: SWE2HS 1.0

Abstract. Many methods exist to model snow densification in order to calculate the depth of a single snow layer or the depth of the total snow cover from its mass. Most of these densification models need to be tightly integrated with an accumulation and melt model and need many forcing variables at high temporal resolution. However, when trying to model snow depth (HS) on climatological timescales, which is often needed for winter tourism-related applications, these preconditions can cause barriers. Often, for these types of applications, empirical snow models are used. These can estimate snow accumulation and snowmelt based on daily precipitation and temperature data only. To convert the resultant snow water equivalent (SWE) time series into snow depth, we developed the empirical model SWE2HS. SWE2HS is a multilayer densification model which uses daily snow water equivalent as sole input. A constant new snow density is assumed and densification is calculated via exponential settling functions. The maximum snow density of a single layer changes over time due to overburden and SWE losses. SWE2HS has been calibrated on a data set derived from a network of manual snow stations in Switzerland. It has been validated against independent data derived from automatic weather stations (AWSs) in the European Alps (Austria, France, Germany, Switzerland) and against withheld data from the Swiss manual observer station data set which was not used for calibration. The model fits the calibration data with root mean squared error (RMSE) of 8.4 cm, coefficient of determination (R2) of 0.97, and bias of −0.3 cm; it is able to achieve RMSE of 20.5 cm, R2 of 0.92, and bias of 2.5 cm on the validation data set from automatic weather stations and RMSE of 7.9 cm, R2 of 0.97, and bias of −0.3 cm on the validation data set from manual stations. The temporal evolution of the bulk density can be reproduced reasonably well on all three data sets. Due to its simplicity, the model can be used as post-processing tool for output of any other snow model that provides daily snow water equivalent output. Owing to its empirical nature, SWE2HS should only be used in regions with a similar snow climatology as the European Alps or has to be recalibrated for other snow climatological conditions. The SWE2HS model is available as a Python package which can be easily installed and used.

Ice and Snow on Lake Stemmevatnet, Spitsbergen, in Winter 2019/20

Received January 19, 2023 ;revised March 22, 2023; accepted June 27, 2023The results of observations and modeling of the formation of the snow-ice cover of Lake Stemme (West Svalbard Island) in winter 2019/20 are presented. The main information was obtained by two radar (GPR) survey, performed on the floating ice of the Lake on March 12 and April 22 of 2020. Authors believe that probably these observations were the first ones on the Lake. The use of the radar made it possible to obtain data on the dynamics of the thickness of the layers of snow and ice cover, the so-called “snow ice” which is formed when the boundary between snow and ice was submerged under water. During the time between records, the thickness of the last “snow ice” increased two to three times, i.e., from units to the first tens of cm, and it spread to the entire deep-water part of the Lake area. In addition, analysis of high-precision positioning of the radar records revealed a significant deflection in the ice surface in the central part of the Lake under the influence of snow load and the decreasing level of the reservoir. The calculations of the thermodynamics of the floating ice cover have shown that its thickening occurs as a result of the processes of congelation and isostatic ice formation, replacing each other at its lower and upper boundaries, respectively. At the same time, the formation of “snow ice” violates the characteristic feature of decreasing of ice thickness with growth of the snow thickness, which significantly influences on the thermal and mass balance of the Lake snow-ice cover. Results of calculations of the ice cover deformation did show that it takes place not only due to the elastic, but also to the viscous properties of ice, and it is concentrated in a narrow coastal zone. The maximum radial stress is reached at a distance of several meters from the shore, where a circular crack parallel to the shoreline is formed. Such a crack is formed at all ice thicknesses at about the same distance from the shore.

Numerical Simulations of the Driving Process of a Wheeled Machine Tire on a Snow-Covered Road

Wheeled machines, such as agricultural tractors, snowplows, and wheeled mobile robots, usually work on icy or snow-covered roads. Therefore, it is very important to study the driving and slip resistance of the tires of these machines. In this paper, we investigate the driving behavior of tires on snow-covered terrain by means of numerical simulations. A high-fidelity snow-covered road model is established, and smoothed particle hydrodynamics (SPH) and the finite element method (FEM) are employed to account for the behaviors of the snow layers and the pavement, respectively. We use the node-to-surface algorithm for the contact interactions between the snow and the pavement. The SPH parameters for the snow are calibrated by means of a triaxial compression experiment. A simplified tire model is established as well, using the FEM, and the effectiveness of the model is demonstrated via comparisons with the experimental data in terms of stiffness. Finally, the tire driving performance on the snow-covered road is simulated, and the influence of the tire surface configuration, external load, inflation pressure, and snowpack compression on the tire traction behaviors is systematically investigated.

Dynamics of the snow grain size in a windy coastal area of Antarctica from continuous in situ spectral-albedo measurements

Abstract. The grain size of the superficial snow layer is a key determinant of the surface albedo in Antarctica. Its evolution is the result of multiple interacting processes, such as dry and wet metamorphism, melt, snow drift, and precipitation. Among them, snow drift has the least known and least predictable impact. The goal of this study is to relate the variations in surface snow grain size to these processes in a windy location of the Antarctic coast. For this, we retrieved the daily grain size from 5-year-long in situ observations of the spectral albedo recorded by a new multi-band albedometer, unique in terms of autonomy and described here for the first time. An uncertainty assessment and a comparison with satellite-retrieved grain size were carried out to verify the reliability of the instrument, and an RMSE up to 0.16 mm in the observed grain size was found. By relating these in situ measurements to time series of snow drift, surface temperature, snow surface height and snowfall, we established that the evolution of the grain size in the presence of snow drift is complex and follows two possible pathways: (1) a decrease in the grain size (about half of our measurements) resulting from the deposition of small grains advected by the wind (surprisingly, this decrease is often – 2/3 of the cases– associated with a decrease in the surface height, i.e., a net erosion over the drift episode), (2) an increase in the grain size (the other half) due to either the removal of the surface layer or metamorphism. However, we note that this increase is often limited with respect to the increase predicted by a theoretical metamorphism model, suggesting that a concomitant deposition of small grains is likely. At last, we found that wind also completely impedes the deposition of snowfall during half of the observed precipitation events. When this happens, the grain size evolves as if precipitation were not occurring. As a result of all these processes, we conclude that the grain size in a windy area remains more stable than it would be in the absence of snow drift, hence limiting the variations in the albedo and in the radiative energy budget.

Lemming winter habitat: the quest for warm and soft snow.

During the cold arctic winter, small mammals like lemmings seek refuge inside the snowpack to keep warm and they dig tunnels in the basal snow layer, usually formed of a soft depth hoar, to find vegetation on which they feed. The snowpack, however, is a heterogenous medium and lemmings should use habitats where snow properties favor their survival and winter reproduction. We determined the impact of snow physical properties on lemming habitat use and reproduction in winter by sampling their winter nests for 13years and snow properties for 6years across 4 different habitats (mesic, riparian, shrubland, and wetland) on Bylot Island in the Canadian High Arctic. We found that lemmings use riparian habitat most intensively because snow accumulates more rapidly, the snowpack is the deepest and temperature of the basal snow layer is the highest in this habitat. However, in the deepest snowpacks, the basal depth hoar layer was denser and less developed than in habitats with shallower snowpacks, and those conditions were negatively related to lemming reproduction in winter. Shrubland appeared a habitat of moderate quality for lemmings as it favored a soft basal snow layer and a deep snowpack compared with mesic and wetland, but snow conditions in this habitat critically depend on weather conditions at the beginning of the winter. With climate change, a hardening of the basal layer of the snowpack and a delay in snow accumulation are expected, which could negatively affect the winter habitat of lemmings and be detrimental to their populations.

Using video detection of snow surface movements to estimate weak layer crack propagation speeds

Abstract Dry-snow slab avalanches release due to crack propagation in a weak snow layer under a cohesive snow slab. Crack propagation speeds can provide insights into the potential size of avalanches and inform fracture and avalanche release models. Despite their importance, slope-scale crack speed measurements from real avalanches are limited. Further, most existing slope-scale measurements utilize the appearance of slab fractures on the snow surface. However, we have no evidence that the appearance of surface cracking is a good indicator of the weak layer crack propagation tip. Here we present a novel method to estimate crack propagation speed from snow surface movements in avalanche videos. Our technique uses changes in frame pixel intensity, allowing us to detect the location of weak layer cracks well before slab fractures appear on the snow surface. We use field experiments and numerical simulations to validate our method before applying it to five avalanches. Our estimates show that cracks propagate faster up and down the slope than in the cross-slope direction; this suggests that different propagation regimes likely govern crack propagation up/down the slope, cross-slope and in flat terrain.

CRYOLOGICAL STUDY OF SNOW AND SOIL AT THE MSU SITE IN WINTER 2022/2023

The paper presents the results of field studies conducted at the MSU meteorological site for the winter period 2022/2023. The purpose of the observations was to study the development of the snow column and its spatial variability in one winter season. Field research consisted in the analysis of stratigraphic layers of snow and measuring their density. The data obtained made it possible to characterize and evaluate changes in snow layers, their structure and density in spatiotemporal terms. The results of the work are displayed on the graphs of the spatial and temporal variability of the snow cover for 2022/2023, the evolution of the snow column over the winter period is analyzed. The analysis of observations reflects a really high spatial and temporal variability of snow cover in winter, which allows not only to evaluate and compare the data obtained with past studies, but also to supplement and improve the already available information on the heterogeneity of snow cover. The purpose was also to assess the effect of snow cover on the temperature characteristics of the soil.

Numerical simulations of heat exchange and vapor flow in ice fractures on Enceladus

Cassini spacecraft observed plume of water vapor and ice particles above the south polar terrain (SPT) of Saturn's moon Enceladus in 2005. The area of the SPT is marked by four prominent linear depressions in the ice dubbed “tigers stripes” (TS) that appear to be the source of the plume. The area around TS is also the source of anomalously high heat flux. The current consensus based on analysis of Cassini observations and modeling suggests that TS are fractures in the ice that penetrate to warm sub-ice ocean. Escaping vapor laden with ice particles forms the visible plume and latent heat of condensing vapor serves as the source of the surface thermal anomaly. In the present work previously developed numerical model of vapor flow and heat exchange inside TS fractures is refined and used to explain Cassini observations. Model improvements include consideration of a possible snow layer on the surface and inclusion of surface ice sublimation into energy balance model. Results of the simulations with improved model suggest that Cassini observations of vapor mass flow and endogenic heat flux can be explained if the width of the ice fractures is in the range 0.05–0.1 m, similar to previously published results. Wider fractures are possible if only a small portion of TS total length produces vapor plume, but the whole ~500 km length of TS fractures still contributes to the surface thermal anomaly. Alternatively, wider fractures are also possible in fractures with high effective friction due to wall roughness or channel tortuosity. Simulated heat output of fractures with different widths and depths in the range of 1.5–3 km is ~2.5–3.0 GW and is only weakly dependent on fracture width. A 2-m-thick surface snow layer covering the fracture can significantly lower outgoing heat flux to 0.9–1.9 GW and reduce surface temperatures by 20–40 K. The total heat flow from different fractures (including conduction from the water-filled portion) is remarkably similar - it is ~3.3 GW and 2.3 GW for fractures without and with a surface snow layer, respectively. The simulated heat flow is lower than the observed heat flow, suggesting that each TS depression may host 2 to 6 narrow ice fractures. The long-standing puzzle of the large difference between the observed heat flow from near TS (~4.2 GW) and from the whole SPT (~15.8 GW) is explained by conduction of ~11 GW of heat from the ocean through the ~5 km-thick ice shell underlying the SPT. Predicted high surface temperatures near fracture exit result in high rates of ice sublimation, which may produce a secondary source of water vapor feeding the observed plume. Fracture outlet likely evolves into a cone-like cross-section widening towards the surface on timescales from 1 to 100 years.

A closed-form model for layered snow slabs

Abstract. We propose a closed-form analytical model for the mechanical behavior of stratified snow covers for the purpose of investigating and predicting the physical processes that lead to the formation of dry-snow slab avalanches. We represent the system of a stratified snow slab covering a collapsible weak layer by a beam composed of an arbitrary number of layers supported by an anisotropic elastic foundation in a two-dimensional plane-strain model. The model makes use of laminate mechanics and provides slab deformations, stresses in the weak layer, and energy release rates of weak-layer anticracks in real time. The quantities can be used in failure models of avalanche release. The closed-form solution accounts for the layering-induced coupling of bending and extension in the slab and of shear and normal stresses in the weak layer. It is validated against experimentally recorded displacement fields and a comprehensive finite-element model indicating very good agreement. We show that layered slabs cannot be homogenized into equivalent isotropic bodies and reveal the impact of layering on bridging with respect to weak-layer stresses and energy release rates. It is demonstrated that inclined propagation saw tests allow for the determination of mixed-mode weak-layer fracture toughnesses. Our results suggest that such tests are dominated by mode I when cut upslope and comprise significant mode II contributions when cut downslope. A Python implementation of the presented model is publicly available as part of the Weak Layer Anticrack Nucleation Model (WEAC) software package under https://github.com/2phi/weac (last access: 28 March 2023) and https://pypi.org/project/weac (last access: 28 March 2023, Rosendahl and Weißgraeber, 2022).

Estimation of Arctic sea ice thickness from CryoSat-2 altimetry data

ABSTRACT Arctic sea ice change is one of the critical factors affecting the global climate environment; hence, it is crucial to obtain sea ice thickness with high accuracy while studying polar and global climate change. In the process of using altimetry data to estimate sea ice thickness, the mean sea surface height will bring greater uncertainty to the extraction of sea ice freeboard, which will affect the accuracy of sea ice thickness. Also, the influence of snow cover on radar signal penetration will bring greater uncertainty to sea ice thickness. In this paper, we present a processing chain for sea ice thickness estimation. First, we compare the effect of four different MSS models on the freeboard estimation. Then, considering the incomplete penetration of radar signals and the different speeds of radar signals penetrating the snow layer and the vacuum, the traditional sea ice thickness model is optimized to obtain the sea ice thickness. Compared with the Operation IceBridge (OIB) sea ice thickness, the accuracy of sea ice thickness obtained by the optimized model is better than 0.350 m, with a root mean square error of 0.260 m and a mean bias of 0.048 m. The comparison results show that the combination of the latest DTU18 MSS model and sea ice thickness optimization model effectively improve the accuracy of sea ice thickness.

Local variability of a taiga snow cover due to vegetation and microtopography

ABSTRACT The taiga snow cover accumulates in relatively stable and windless weather. This should produce a uniform snow cover with continuous, laterally homogeneous stratigraphy and snow properties when the snow is deposited on a level, smooth substrate. However, such substrates are rare, and local variations in vegetation and ground surface topography alter the structure of the snow cover and produce irregular snow layers. In this study, we investigated the effects of vegetation, microtopography, and microclimatic variability on the taiga snow near Fairbanks, Alaska. Through the winter of 2019–2020, in situ measurements were made at three locations with distinctly different local microtopographic features and radically different (but typical) vegetation. One site was an open grassy field, the second a mature spruce forest, and the third a birch forest located on thermokarst terrain with steep microrelief where ice wedges had degraded. Widely different canopy interception processes proved to have the strongest impact on the resulting snow cover heterogeneity by altering the initial deposition, with surface microtopography having the second strongest influence through postdepositional processes. In this article, we suggest a conceptual framework for understanding and modeling taiga snow variability in terms of the vegetation and microtopography that created it.

Snow Layer Prediction Model using Back Scattering Co-efficient

Abstract: In this study, the objective is to estimate the physical parameters of each snow layer at a given certain altitude, which is according to the problem will always be between other altitudes, whose profile data is entirely provided. The provided data for the target profile will also consist of the number of layers, height of each layer, the back-scattering coefficient and the altitude. The goal is to estimate the interval [࢔࢏࢓࢟ ,࢞ࢇ࢓࢟ [for each parameter, which are sphericity, diameter and density of the snowflakes. We are using here a multilayer snow profile and then applying the back scattering coefficients to calculate the snow layer altitude and height. Further, by correct prediction we can preserve the snow layers by continuously monitoring the snow model at the correct altitude throughout the year. Our aim demonstrates the comparatively better way to predict the best snow profile at right altitudes.

Under-Ice Development of Silica-Scaled Chrysophytes with Different Trophic Mode in Two Ultraoligotrophic Lakes of Yakutia

Silica-scaled chrysophytes are a widespread group of microeukaryotes, an important component of aquatic habitats. They belong to different evolutionary lineages and they are characterized by the presence of siliceous scales, but differ in trophic mode. We studied the diversity of these organisms in different months of the ice cover period in two subarctic lakes of Yakutia, Labynkyr and Vorota. Silica-scaled chrysophytes, due to various trophic modes, have a competitive advantage in conditions of a long period of ice cover. Statistical analysis has shown the relationship between the relative abundance of mixotrophic and photoautotrophic representatives of silica-scaled chrysophytes with the thickness of the snow cover and the transparency of the ice. An increase in snow cover thickness and the process of melting ice with a decrease in its transparency reduce the relative abundance of photoautotrophic and mixotrophic species. Photoautotrophic representatives of silica-scaled chrysophytes begin to develop already in April, when a thick, solid, and transparent layer of ice and a small layer of snow were observed. During the research period, from April to June, the relative abundance of colorless heterotrophic silica-scaled chrysophytes genera Paraphysomonas and Lepidochromonas was more or less stable. A new species of Spiniferomonas heterospina sp. nov. has been discovered in Lake Labynkyr.

Wind tunnel experiment and thermodynamic modeling for dry-snow accretion on a heated surface

Wind tunnel experiments and modeling of dry-snow accretion on a heated surface were performed to estimate the characteristics of dry-snow accretion occurring in sub-freezing temperatures by using cold-climate facilities. The experiments encompassed a wide range of meteorological conditions—air temperature, wind speed, and snow flux—and were conducted over a surface heat flux range of 300–1800 W/m2. The measurements were performed with respect to the snow properties, including growth rate, sticking efficiency, and liquid water content (LWC), and were used to analyze the impact of dry-snow accretion on a heated surface. The experimental results demonstrated the distinct influence of the surface heat flux on the snow accretion process. The sticking efficiency was found to highly correlate with the LWC of the accreted snow and meteorological parameters, and the accreted snow layer was shed from the surfaces when the LWC was slightly above 40%. Moreover, on the basis of heat and mass transfer during the accretion process, models for estimating sticking efficiency and LWC were developed for dry-snow accretion on a heated surface. The effects of convective cooling and evaporation of liquid water inside the accreted snow were incorporated, and the models were cross-validated with the experimental results. The equation was applied to the determination of the minimum value for sticking efficiency, and a linear proportional relation between sticking efficiency and meteorological parameters was demonstrated.

Assessing Snow Water Retrievals over Ocean from Coincident Spaceborne Radar Measurements

Spaceborne snow water retrievals over oceans are assessed using a multiyear coincident dataset of CloudSat Cloud Profiling Radar (CPR) and Global Precipitation Mission (GPM) Dual-frequency Precipitation Radar (DPR). Various factors contributing to differences in snow water retrievals between CPR and DPR are carefully considered. A set of relationships between radar reflectivity (Ze) and snow water content (SWC) at Ku- and W-bands is developed using the same microphysical assumptions. It is found that surface snow water contents from CPR are much larger than those from DPR at latitudes above 60°, while surface snow water contents from DPR slightly exceed those from CPR at latitudes below 50°. Coincident snow water content profiles between CPR and DPR are further divided into two conditions. One is that only CPR detects the falling snow. Another is that both CPR and DPR detect the falling snow. The results indicate that about 88% of all snow water content profiles are under the first condition and usually associated with light snowfall events. The remaining snow water content profiles are generally associated with moderate and heavy snowfall events. Moreover, CPR surface snow water contents are larger than DPR ones at high latitudes because most light snowfall events are misdetected by DPR due to its low sensitivity. DPR surface snow water contents exceed CPR ones at low latitudes because CPR may experience a significant reduction in backscattering efficiency of large particles and attenuation in heavy snowfall events. The low sensitivity of DPR also causes a noticeable decrease in detected snow layer depth. The results presented here can help in developing global snowfall retrieval algorithms using multi-radars.