Simulating airborne ‘snow walls’ of Antarctica using CRYOWRF v1.0

2021 ◽  
Author(s):  
Varun Sharma ◽  
Franziska Gerber ◽  
Michael Lehning
Keyword(s):  
Snow Cover ◽  
Hydraulic Jump ◽  
Large Scale ◽  
Satellite Images ◽  
Ice Sheet ◽  
Surface Radiation ◽  
Surface Model ◽  
Blowing Snow ◽  
Katabatic Flow ◽  
Surface Snow

<p>When a well-developed, high velocity katabatic flow draining down the ice sheet of Antarctica reaches the coast, it experiences an abrupt and rapid transition due to change in slope resulting in formation of a hydraulic jump. A remarkable manifestation of the hydraulic jump, given the ‘right’ surface conditions, is the large-scale entrainment and convergence of blowing snow particles within the hydraulic jump. This can result in formation of 100-1000 m high, highly localized ‘walls’ of snow in the air in an otherwise cloud-free sky.</p><p>Recent work by Vignon et al. (2020) has described in detail, the mechanisms resulting in the formation of hydraulic jumps and excitation of gravity waves during a particularly notable event at the Dumont d’Urville (DDU) station in August 2017. They used a combination of satellite images, mesoscale simulations with WRF and station measurements (including Micro Rain Radars) in their study, notably relying on the snow wall for diagnosing and quantifying the hydraulic jump in satellite images. On the other hand, relatively less importance was given towards the surface snow processes including the transport of snow particles in the wall.</p><p>In this presentation, we present results from simulations done using the recently developed CRYOWRF v1.0 to recreate the August 2017 episode at DDU and explicitly simulate the formation and the dynamics of the snow wall itself. CRYOWRF enhances the standard WRF model with the state-of-the-art surface snow modelling scheme SNOWPACK as well as a completely new blowing snow scheme. SNOWPACK essentially acts as a land surface model for the WRF atmospheric model, thus making a quantum leap over the existing snow cover models in WRF. Since SNOWPACK is a grain-scale snow model, it allows for the proper formulation of boundary conditions for simulating blowing snow dynamics.</p><p>Results show the formation of the snow wall due to large scale entrainment over a wide area of the ice sheet, the mass balance of the snow wall within the hydraulic jump and finally, the destruction of the snow wall and the ultimate fate of all the entrained snow. We also show results for the influence of the snow wall on the local surface radiation at DDU. Overall, we test the capabilities of CRYOWRF to simulate such a complex phenomenon and highlight possible applications now feasible due the tight coupling of an advanced snow cover model and a multi-scale, non-hydrostatic atmospheric flow solver.</p><p>Reference:</p><p>Vignon, Étienne, Ghislain Picard, Claudio Durán-Alarcón, Simon P. Alexander, Hubert Gallée, and Alexis Berne. " Gravity Wave Excitation during the Coastal Transition of an Extreme Katabatic Flow in Antarctica". <em>Journal of the Atmospheric Sciences</em> 77.4 (2020): 1295-1312. <>.</p>

scholarly journals Simulation of Northern Eurasian Local Snow Depth, Mass, and Density Using a Detailed Snowpack Model and Meteorological Reanalyses

2013 ◽  
Vol 14 (1) ◽  
pp. 203-219 ◽  
Author(s):  
Eric Brun ◽  
Vincent Vionnet ◽  
Aaron Boone ◽  
Bertrand Decharme ◽  
Yannick Peings ◽  
...  
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Snow Depth ◽  
Snow Water Equivalent ◽  
Land Surface Model ◽  
Northern Eurasia ◽  
Surface Model ◽  
Monthly Precipitation ◽  
Blowing Snow ◽  
Snow Water

Abstract The Crocus snowpack model within the Interactions between Soil–Biosphere–Atmosphere (ISBA) land surface model was run over northern Eurasia from 1979 to 1993, using forcing data extracted from hydrometeorological datasets and meteorological reanalyses. Simulated snow depth, snow water equivalent, and density over open fields were compared with local observations from over 1000 monitoring sites, available either once a day or three times per month. The best performance is obtained with European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim). Provided blowing snow sublimation is taken into account, the simulations show a small bias and high correlations in terms of snow depth, snow water equivalent, and density. Local snow cover durations as well as the onset and vanishing dates of continuous snow cover are also well reproduced. A major result is that the overall performance of the simulations is very similar to the performance of existing gridded snow products, which, in contrast, assimilate local snow depth observations. Soil temperature at 20-cm depth is reasonably well simulated. The methodology developed in this study is an efficient way to evaluate different meteorological datasets, especially in terms of snow precipitation. It reveals that the temporal disaggregation of monthly precipitation in the hydrometeorological dataset from Princeton University significantly impacts the rain–snow partitioning, deteriorating the simulation of the onset of snow cover as well as snow depth throughout the cold season.

scholarly journals STATE OF THE ART IN DIGITAL SURFACE MODELLING FROM MULTI-VIEW HIGH-RESOLUTION SATELLITE IMAGES

2020 ◽  
Vol V-2-2020 ◽  
pp. 351-356 ◽  
Author(s):  
Y. Han ◽  
S. Wang ◽  
D. Gong ◽  
Y. Wang ◽  
Y. Wang ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Satellite Images ◽  
Satellite Image ◽  
Ground Truth ◽  
Semantic Interpretation ◽  
Surface Model ◽  
Three Solutions ◽  
Surface Modelling ◽  
High Resolution Satellite Images

Abstract. Data from the optical satellite imaging sensors running 24/7, is collecting in embarrassing abundance nowadays. Besides more suitable for large-scale mapping, multi-view high-resolution satellite images (HRSI) are cheaper when comparing to Light Detection And Ranging (LiDAR) data and aerial remotely sensed images, which are more accessible sources for digital surface modelling and updating. Digital Surface Model (DSM) generation is one of the most critical steps for mapping, 3D modelling, and semantic interpretation. Computing DSM from this dataset is relatively new, and several solutions exist in the market, both commercial and open-source solutions, the performances of these solutions have not yet been comprehensively analyzed. Although some works and challenges have focused on the DSM generation pipeline and the geometric accuracy of the generated DSM, the evaluations, however, do not consider the latest solutions as the fast development in this domain. In this work, we discussed the pipeline of the considered both commercial and opensource solutions, assessed the accuracy of the multi-view satellite image-based DSMs generation methods with LiDAR-derived DSM as the ground truth. Three solutions, including Satellite Stereo Pipeline (S2P), PCI Geomatica, and Agisoft Metashape, are evaluated on a WorldView-3 multi-view satellite dataset both quantitatively and qualitatively with the LiDAR ground truth. Our comparison and findings are presented in the experimental section.

Heterogenous snow cover derived uncertainty in Arctic carbon budget

2020 ◽  
Author(s):  
Hotaek Park ◽  
Youngwook Kim
Keyword(s):  
Greenhouse Gases ◽  
Snow Cover ◽  
Land Surface ◽  
Snow Depth ◽  
Environmental Changes ◽  
Moisture Stress ◽  
Surface Model ◽  
Active Layer Thickness ◽  
Blowing Snow ◽  
Permafrost Temperature

<p>The winter of northern Arctic regions is characterized by strong winds that lead to frequent blowing snow and thus heterogeneous snow cover, which critically affects permafrost hydrothermal processes and the associated feedbacks across the northern regions. However until now, observations and models have not documented the blowing snow impacts. The blowing snow process has coupled into a land surface model CHANGE, and the improved model was applied to observational sites in the northeastern Siberia for 1979–2016. The simulated snow depth and soil temperature showed general agreements with the observations. To quantify the impacts of blowing snow on permafrost temperatures and the associated greenhouse gases, two decadal experiments that included or excluded blowing snow, were conducted for the observational sites and over the pan-Arctic scale. The differences between the two experiments represent impacts of the blowing snow on the analytical components. The blowing snow-induced thinner snow depth resulted in cooler permafrost temperature and lower active layer thickness; this lower temperature limited the vegetation photosynthetic activity due to the increased soil moisture stress in terms of larger soil ice portion and hence lower ecosystem productivity. The cooler permafrost temperature is also linked to less decomposition of soil organic matter and lower releases of CO2 and CH4 to the atmosphere. These results suggest that the most land models without a blowing snow component likely overestimate the release of greenhouse gases from the tundra regions. There is a strong need to improve land surface models for better simulations and future projections of the northern environmental changes.</p>

scholarly journals Accuracy Validation of Large-scale Block Adjustment without Control of ZY3 Images over China

2016 ◽  
Vol III-1 ◽  
pp. 105-112 ◽  
Author(s):  
Bo Yang
Keyword(s):  
Large Scale ◽  
Satellite Images ◽  
Ground Control ◽  
Surface Model ◽  
Geometric Accuracy ◽  
Single Image ◽  
Control Block ◽  
Optical Satellite Images ◽  
Excessive Accumulation ◽  
Better Than

Mapping from optical satellite images without ground control is one of the goals of photogrammetry. Using 8802 three linear array stereo images (a total of 26406 images) of ZY3 over China, we propose a large-scale and non-control block adjustment method of optical satellite images based on the RPC model, in which a single image is regarded as an adjustment unit to be organized. To overcome the block distortion caused by unstable adjustment without ground control and the excessive accumulation of errors, we use virtual control points created by the initial RPC model of the images as the weighted observations and add them into the adjustment model to refine the adjustment. We use 8000 uniformly distributed high precision check points to evaluate the geometric accuracy of the DOM (Digital Ortho Model) and DSM (Digital Surface Model) production, for which the standard deviations of plane and elevation are 3.6 m and 4.2 m respectively. The geometric accuracy is consistent across the whole block and the mosaic accuracy of neighboring DOM is within a pixel, thus, the seamless mosaic could take place. This method achieves the goal of an accuracy of mapping without ground control better than 5 m for the whole China from ZY3 satellite images.

scholarly journals Development of the Pan-Arctic Snowfall Reconstruction: New Land-Based Solid Precipitation Estimates for 1940–99

2007 ◽  
Vol 8 (6) ◽  
pp. 1243-1263 ◽  
Author(s):  
J. E. Cherry ◽  
L-B. Tremblay ◽  
M. Stieglitz ◽  
G. Gong ◽  
S. J. Déry
Keyword(s):  
Land Surface ◽  
Snow Depth ◽  
Large Scale ◽  
Land Surface Model ◽  
Seasonal Prediction ◽  
The United States ◽  
Cold Season ◽  
Surface Model ◽  
Blowing Snow ◽  
Solid Precipitation

Abstract A new product, the Pan-Arctic Snowfall Reconstruction (PASR), is developed to address the problem of cold season precipitation gauge biases for the 1940–99 period. The method used to create the PASR is different from methods used in other large-scale precipitation data products and has not previously been employed for estimating pan-arctic snowfall. The NASA Interannual-to-Seasonal Prediction Project Catchment Land Surface Model is used to reconstruct solid precipitation from observed snow depth and surface air temperatures. The method is tested at four stations in the United States and Canada where results are examined in depth. Reconstructed snowfall at Dease Lake, British Columbia, and Barrow, Alaska, is higher than gauge observations. Reconstructed snowfall at Regina, Saskatchewan, and Minot, North Dakota, is lower than gauge observations, probably because snow is transported by wind out of the Prairie region and enters the hydrometeorological cycle elsewhere. These results are similar to gauge biases estimated by a water budget approach. Reconstructed snowfall is consistently higher than snowfall from the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) but does not have a consistent relationship with snowfall derived from the WMO Solid Precipitation Intercomparison Project correction algorithms. Advantages of the PASR approach include that 1) the assimilation of snow depth observations captures blowing snow where it is deposited and 2) the modeling approach takes into account physical snowpack evolution. These advantages suggest that the PASR product could be a valuable alternative to statistical gauge corrections and that arctic ground-based solid precipitation observing networks might emphasize snow depth measurements over gauges.

scholarly journals Modelled sensitivity of the snow regime to topography, shrub fraction and shrub height

2014 ◽  
Vol 18 (6) ◽  
pp. 2375-2392 ◽  
Author(s):  
C. B. Ménard ◽  
R. Essery ◽  
J. Pomeroy
Keyword(s):  
Snow Cover ◽  
Energy Budget ◽  
Large Scale ◽  
Heat Fluxes ◽  
The Arctic ◽  
Balance Model ◽  
Blowing Snow ◽  
Shrub Cover ◽  
Shrub Expansion ◽  
Shrub Tundra

Abstract. Recent studies show that shrubs are colonizing higher latitudes and altitudes in the Arctic. Shrubs affect the wind transport, accumulation and melt of snow, but there have been few sensitivity studies of how shrub expansion might affect snowmelt rates and timing. Here, a three-source energy balance model (3SOM), which calculates vertical and horizontal energy fluxes – thus allowing within-cell advection – between the atmosphere, snow, snow-free ground and vegetation, is introduced. The three-source structure was specifically adopted to investigate shrub–tundra processes associated with patchy snow cover that single- or two-source models fail to address. The ability of the model to simulate the snow regime of an upland tundra valley is evaluated; a blowing snow transport and sublimation model is used to simulate premelt snow distributions and 3SOM is used to simulate melt. Some success at simulating turbulent fluxes in point simulations and broad spatial pattern in distributed runs is shown even if the lack of advection between cells causes melt rates to be underestimated. The models are then used to investigate the sensitivity of the snow regime in the valley to varying shrub cover and topography. Results show that, for domain average shrub fractional cover ≤0.4, topography dominates the pre- and early melt energy budget but has little influence for higher shrub cover. The increase in domain average sensible heat fluxes and net radiation with increasing shrub cover is more marked without topography where shrubs introduce wind-induced spatial variability of snow and snow-free patches. As snowmelt evolves, differences in the energy budget between simulations with and without topography remain relatively constant and are independent of shrub cover. These results suggest that, to avoid overestimating the effect of shrub expansion on the energy budget of the Arctic, future large-scale investigations should consider wind redistribution of snow, shrub bending and emergence, and sub-grid topography as they affect the variability of snow cover.

scholarly journals The Land Surface, Snow and Soil moisture Model Intercomparison Program (LS3MIP): aims, set-up and expected outcome

2016 ◽  
Author(s):  
Bart van den Hurk ◽  
Hyungjun Kim ◽  
Gerhard Krinner ◽  
Sonia I. Seneviratne ◽  
Chris Derksen ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Land Surface ◽  
Large Scale ◽  
Surface Radiation ◽  
The Arctic ◽  
Model Intercomparison ◽  
Soil Moisture Model ◽  
Surface Snow ◽  
Systematic Biases

Abstract. The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow, and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth System Models (ESMs). The solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both strongly affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. However, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode ("LMIP", building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework ("LFMIP", building upon the GLACE-CMIP blueprint).

What drives the isotopic composition of vapor, precipitation and surface snow in a coastal site of East Anrctica: Adelie Land

2020 ◽  
Author(s):  
Christophe Leroy-Dos Santos ◽  
Amaelle Landais ◽  
Elise Fourre ◽  
Cecile Agosta ◽  
Mathieu Casado ◽  
...  
Keyword(s):  
Isotopic Composition ◽  
Large Scale ◽  
Hydrological Cycle ◽  
Specific Humidity ◽  
Data Series ◽  
Blowing Snow ◽  
Transport Pathway ◽  
Stable Isotopic Composition ◽  
Stable Isotopic ◽  
Surface Snow

<p>Studying the drivers of the water stable isotopic composition at coastal Antarctic sites is useful for the interpretation of coastal ice-core signal or the analysis of recent mass balance evolution. In addition to the classical fingerprint of temperature, the water isotopic composition in water vapor and snow carries a fingerprint of the humidity transport pathway, from evaporation to precipitation. Blowing snow in very windy coastal regions is also expected to carry a particular signature affected by snow-air exchanges as observed for surface snow on the East Antarctic plateau.</p><p>Since November 2018, we have been continuously measuring the water stable isotopic composition of vapor at Dumont D’Urville station (Adélie Land) using laser spectrometers in addition to isotopic composition of precipitation, blowing snow and surface snow samples. We present here the full 2019 data series. We focus on the two main weather regimes, in summer and winter, that affect the local hydrological cycle. In summer, temperature and specific humidity signals are characterized by large diurnal cycles due to katabatic winds. Winter variability is largely influenced by large scale synoptic events. We also investigate a few specific cases of precipitation/sublimation and compare two summer periods with opposite sea-ice conditions.</p>

scholarly journals Accuracy Validation of Large-scale Block Adjustment without Control of ZY3 Images over China

2016 ◽  
Vol III-1 ◽  
pp. 105-112
Author(s):  
Bo Yang
Keyword(s):  
Large Scale ◽  
Satellite Images ◽  
Ground Control ◽  
Surface Model ◽  
Geometric Accuracy ◽  
Single Image ◽  
Control Block ◽  
Optical Satellite Images ◽  
Excessive Accumulation ◽  
Better Than

Mapping from optical satellite images without ground control is one of the goals of photogrammetry. Using 8802 three linear array stereo images (a total of 26406 images) of ZY3 over China, we propose a large-scale and non-control block adjustment method of optical satellite images based on the RPC model, in which a single image is regarded as an adjustment unit to be organized. To overcome the block distortion caused by unstable adjustment without ground control and the excessive accumulation of errors, we use virtual control points created by the initial RPC model of the images as the weighted observations and add them into the adjustment model to refine the adjustment. We use 8000 uniformly distributed high precision check points to evaluate the geometric accuracy of the DOM (Digital Ortho Model) and DSM (Digital Surface Model) production, for which the standard deviations of plane and elevation are 3.6 m and 4.2 m respectively. The geometric accuracy is consistent across the whole block and the mosaic accuracy of neighboring DOM is within a pixel, thus, the seamless mosaic could take place. This method achieves the goal of an accuracy of mapping without ground control better than 5 m for the whole China from ZY3 satellite images.

scholarly journals Seasonal dynamics of snow ablation on selected glaciers in central Spitsbergen derived from Sentinel-2 satellite images

2021 ◽  
pp. 1-6
Author(s):  
Jan Kavan ◽  
Vincent Haagmans
Keyword(s):  
Snow Cover ◽  
Wind Direction ◽  
Satellite Images ◽  
Prevailing Wind ◽  
Seasonal Snow ◽  
Glacier Melt ◽  
Prevailing Wind Direction ◽  
Surface Snow ◽  
Temporal And Spatial ◽  
Sentinel 2

Abstract The dynamics of seasonal snow ablation on six glaciers in central Spitsbergen (Dicksonland) were assessed by examining a set of Sentinel-2 satellite images covering the summer ablation season for the period 2016–19. All glaciers lost 80% or more of their surface snow cover during the studied ablation seasons. This bolsters the recently observed trend of local glacier thinning, even at higher altitudes. Snow ablation dynamics are highly dependent on the glaciers altitudes, their position relative to the prevailing wind direction and the exposure to insolation. The accumulation areas of the studied glaciers were delimited based on the overlap of the minimum extent of snow-covered areas in the four consecutive studied summer seasons. The high temporal and spatial resolutions of available images enabled a detailed description of the seasonal snow ablation dynamics. Moreover, an estimate of the average number of days with below threshold glacier snow cover was made. This study contributes to our understanding of recent processes and might further support the modelling of glacier melt and subsequent runoff.

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