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

2014 ◽  
Vol 11 (1) ◽  
pp. 223-263 ◽  
Author(s):  
C. B. Ménard ◽  
R. Essery ◽  
J. Pomeroy
Keyword(s):  
Energy Balance ◽  
Spatial Variability ◽  
Energy Budget ◽  
Snow Accumulation ◽  
Heat Fluxes ◽  
The Arctic ◽  
Balance Model ◽  
Blowing Snow ◽  
Shrub Cover ◽  
Shrub Expansion

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 blowing snow transport and sublimation model is used to simulate premelt snow distributions and a 3-source energy balance model, which calculates vertical and horizontal energy fluxes between the atmosphere, snow, snow-free ground and vegetation, is used to simulate melt. Vegetation is parametrized as shrub cover and the parametrization includes shrub bending and burial in winter and emergence in spring. The models are used to investigate the sensitivity of the snow regime in an upland tundra valley to varying shrub cover and topography. Results show that topography dominates the spatial variability of snow accumulation, which in turn dominates the pre and early melt energy budget. With topography removed from the simulations, modelled snow cover is uniform when there is no vegetation but increasing vegetation introduces spatial variability in snow accumulation which is then decreased as further increases in shrub cover suppress wind-induced redistribution of snow. The domain-averaged simulations of premelt snow accumulation also increases with increasing shrub cover because suppression of blowing snow by shrubs decreases sublimation. In simulations with topography, the increase in snow accumulation and its spatial variability with increasing vegetation is less marked because snow is also held in topography-driven drifts. With topography, the existence of wind-scoured snow-free patches at the onset of snowmelt causes exposed ground to contribute to the energy balance such that sensible, advective and radiative heat fluxes are higher than in the flat domain during this period. However, as snowmelt evolves, differences in the energy budget between runs with and without topography dramatically diminish. 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 snowcover.

scholarly journals The large-scale energy budget of the Arctic

2007 ◽  
Vol 112 (D11) ◽  
Author(s):  
Mark C. Serreze ◽  
Andrew P. Barrett ◽  
Andrew G. Slater ◽  
Michael Steele ◽  
Jinlun Zhang ◽  
...  
Keyword(s):  
Energy Budget ◽  
Large Scale ◽  
The Arctic

scholarly journals Trends and regime shifts in climatic conditions and river runoff in Estonia during 1951–2015

2017 ◽  
Vol 8 (4) ◽  
pp. 963-976 ◽  
Author(s):  
Jaak Jaagus ◽  
Mait Sepp ◽  
Toomas Tamm ◽  
Arvo Järvet ◽  
Kiira Mõisja
Keyword(s):  
Time Series ◽  
Snow Cover ◽  
Atmospheric Circulation ◽  
Air Temperature ◽  
Large Scale ◽  
Regime Shifts ◽  
The Arctic ◽  
Dry Period ◽  
Snow Cover Duration ◽  
Large Scale Atmospheric Circulation

Abstract. Time series of monthly, seasonal and annual mean air temperature, precipitation, snow cover duration and specific runoff of rivers in Estonia are analysed for detecting of trends and regime shifts during 1951–2015. Trend analysis is realised using the Mann–Kendall test and regime shifts are detected with the Rodionov test (sequential t-test analysis of regime shifts). The results from Estonia are related to trends and regime shifts in time series of indices of large-scale atmospheric circulation. Annual mean air temperature has significantly increased at all 12 stations by 0.3–0.4 K decade−1. The warming trend was detected in all seasons but with the higher magnitude in spring and winter. Snow cover duration has decreased in Estonia by 3–4 days decade−1. Changes in precipitation are not clear and uniform due to their very high spatial and temporal variability. The most significant increase in precipitation was observed during the cold half-year, from November to March and also in June. A time series of specific runoff measured at 21 stations had significant seasonal changes during the study period. Winter values have increased by 0.4–0.9 L s−1 km−2 decade−1, while stronger changes are typical for western Estonia and weaker changes for eastern Estonia. At the same time, specific runoff in April and May have notably decreased indicating the shift of the runoff maximum to the earlier time, i.e. from April to March. Air temperature, precipitation, snow cover duration and specific runoff of rivers are highly correlated in winter determined by the large-scale atmospheric circulation. Correlation coefficients between the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) indices reflecting the intensity of westerlies, and the studied variables were 0.5–0.8. The main result of the analysis of regime shifts was the detection of coherent shifts for air temperature, snow cover duration and specific runoff in the late 1980s, mostly since the winter of 1988/1989, which are, in turn, synchronous with the shifts in winter circulation. For example, runoff abruptly increased in January, February and March but decreased in April. Regime shifts in annual specific runoff correspond to the alternation of wet and dry periods. A dry period started in 1964 or 1963, a wet period in 1978 and the next dry period at the beginning of the 21st century.

scholarly journals Multi-Scale Evaluation of the TSEB Model over a Complex Agricultural Landscape in Morocco

2020 ◽  
Vol 12 (7) ◽  
pp. 1181
Author(s):  
Jamal Elfarkh ◽  
Jamal Ezzahar ◽  
Salah Er-Raki ◽  
Vincent Simonneaux ◽  
Bouchra Ait Hssaine ◽  
...  
Keyword(s):  
Latent Heat ◽  
Complex Terrain ◽  
Large Scale ◽  
Agricultural Landscape ◽  
Local Scale ◽  
Heat Fluxes ◽  
Balance Model ◽  
Modis Data ◽  
Multi Scale ◽  
Basin Scale

An accurate assessment of evapotranspiration (ET) is crucially needed at the basin scale for studying the hydrological processes and water balance especially from upstream to downstream. In the mountains, this term is poorly understood because of various challenges, including the vegetation complexity, plant diversity, lack of available data and because the in situ direct measurement of ET is difficult in complex terrain. The main objective of this work was to investigate the potential of a Two-Source-Energy-Balance model (TSEB) driven by the Landsat and MODIS data for estimating ET over a complex mountain region. The complexity is associated with the type of the vegetation canopy as well as the changes in topography. For validating purposes, a large-aperture scintillometer (LAS) was set up over a heterogeneous transect of about 1.4 km to measure sensible (H) and latent heat (LE) fluxes. Additionally, two towers of eddy covariance (EC) systems were installed along the LAS transect. First, the model was tested at the local scale against the EC measurements using multi-scale remote sensing (MODIS and Landsat) inputs at the satellite overpasses. The obtained averaged values of the root mean square error (RMSE) and correlation coefficient (R) were about 72.4 Wm−2 and 0.79 and 82.0 Wm−2 and 0.52 for Landsat and MODIS data, respectively. Secondly, the potential of the TSEB model for evaluating the latent heat fluxes at large scale was investigated by aggregating the derived parameters from both satellites based on the LAS footprint. As for the local scale, the comparison of the latent heat fluxes simulated by TSEB driven by Landsat data performed well against those measured by the LAS (R = 0.69, RMSE = 68.0 Wm−2), while slightly more scattering was observed when MODIS products were used (R = 0.38, RMSE = 99.8 Wm−2). Based on the obtained results, it can be concluded that (1) the TSEB model can be fairly used to estimate the evapotranspiration over the mountain regions; and (2) medium- to high-resolution inputs are a better option than coarse-resolution products for describing this kind of complex terrain.

scholarly journals High resolution snow distribution data from complex Arctic terrain: a tool for model validation

2002 ◽  
Vol 2 (3/4) ◽  
pp. 147-155 ◽  
Author(s):  
Ch. Jaedicke ◽  
A. D. Sandvik
Keyword(s):  
High Resolution ◽  
Snow Cover ◽  
Numerical Models ◽  
The Arctic ◽  
Distribution Data ◽  
Blowing Snow ◽  
Data Set ◽  
Meteorological Model ◽  
Drift Model ◽  
Snow Distribution

Abstract. Blowing snow and snow drifts are common features in the Arctic. Due to sparse vegetation, low temperatures and high wind speeds, the snow is constantly moving. This causes severe problems for transportation and infrastructure in the affected areas. To minimise the effect of drifting snow already in the designing phase of new structures, adequate models have to be developed and tested. In this study, snow distribution in Arctic topography is surveyed in two study areas during the spring of 1999 and 2000. Snow depth is measured by ground penetrating radar and manual methods. The study areas encompass four by four kilometres and are partly glaciated. The results of the surveys show a clear pattern of erosion, accumulation areas and the evolution of the snow cover over time. This high resolution data set is valuable for the validation of numerical models. A simple numerical snow drift model was used to simulate the measured snow distribution in one of the areas for the winter of 1998/1999. The model is a two-level drift model coupled to the wind field, generated by a mesoscale meteorological model. The simulations are based on five wind fields from the dominating wind directions. The model produces a satisfying snow distribution but fails to reproduce the details of the observed snow cover. The results clearly demonstrate the importance of quality field data to detect and analyse errors in numerical simulations.

The role of soil characteristics on measured and modelled carbon dioxide and energy fluxes for Arctic dwarf shrub tundra sites

2020 ◽  
Author(s):  
Gesa Meyer ◽  
Elyn Humphreys ◽  
Joe Melton ◽  
Peter Lafleur ◽  
Philip Marsh ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Growing Season ◽  
Cold Season ◽  
Soil Characteristics ◽  
Heat Fluxes ◽  
Dwarf Shrub ◽  
The Arctic ◽  
Sensible Heat ◽  
Shrub Tundra ◽  
Tundra Ecosystems

<p>Four years of growing season eddy covariance measurements of net carbon dioxide (CO<sub>2</sub>) and energy fluxes were used to examine the similarities/differences in surface-atmosphere interactions at two dwarf shrub tundra sites within Canada’s Southern Arctic ecozone, separated by approximately 1000 km. Both sites, Trail Valley Creek (TVC) and Daring Lake (DL1), are characterised by similar climate (with some differences in radiation due to latitudinal differences), vegetation composition and structure, and are underlain by continuous permafrost, but differ in their soil characteristics. Total atmospheric heating (the sum of latent and sensible heat fluxes) was similar at the two sites. However, at DL1, where the surface organic layer was thinner and mineral soil coarser in texture, latent heat fluxes were greater, sensible heat fluxes were lower, soils were warmer and the active layer thicker. At TVC, cooler soils likely kept ecosystem respiration relatively low despite similar total growing season productivity. As a result, the 4-year mean net growing season ecosystem CO<sub>2 </sub>uptake (May 1 - September 30) was almost twice as large at TVC (64 ± 19 g C m<sup>-2</sup>) compared to DL1 (33 ± 11 g C m<sup>-2</sup>). These results highlight that soil and thaw characteristics are important to understand variability in surface-atmosphere interactions among tundra ecosystems.</p><p>As recent studies have shown, winter fluxes play an important role in the annual CO<sub>2</sub> balance of Arctic tundra ecosystems. However, flux measurements were not available at TVC and DL1 during the cold season. Thus, the process-based ecosystem model CLASSIC (the Canadian Land Surface Scheme including biogeochemical Cycles, formerly CLASS-CTEM) was used to simulate year-round fluxes. In order to represent the Arctic shrub tundra better, shrub and sedge plant functional types were included in CLASSIC and results were evaluated using measurements at DL1. Preliminary results indicate that cold season CO<sub>2</sub> losses are substantial and may exceed the growing season CO<sub>2</sub> uptake at DL1 during 2010-2017. The joint use of observations and models is valuable in order to better constrain the Arctic CO<sub>2</sub> balance.  </p>

scholarly journals Arctic Ocean sea ice snow depth evaluation and bias sensitivity in CCSM

2013 ◽  
Vol 7 (2) ◽  
pp. 1495-1532 ◽  
Author(s):  
B. A. Blazey ◽  
M. M. Holland ◽  
E. C. Hunke
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Large Scale ◽  
System Model ◽  
Arctic Climate ◽  
The Arctic ◽  
Blowing Snow ◽  
Climate System Model ◽  
The Arctic Ocean ◽  
Ice Conditions

Abstract. Sea ice cover in the Arctic Ocean is a continued focus of attention. This study assesses the capability of hindcast simulations of the Community Climate System Model (CCSM) to reproduce observed snow depths and densities overlying the Arctic Ocean sea ice. The model is evaluated using measurements provided by historic Russian polar drift stations. Following the identification of seasonal biases produced in the simulations, the thermodynamic transfer through the snow – ice column is perturbed to determine model sensitivity to these biases. This study concludes that perturbations on the order of the observed biases result in modification of the annual mean conductive flux of 0.5 W m−2 relative to an unmodified simulation. The results suggest that the ice has a complex response to snow characteristics, with ice of different thicknesses producing distinct reactions. Consequently, we suggest that the inclusion of additional snow evolution processes such as blowing snow, densification, and seasonal changes in snow conductivity in sea ice models would increase the fidelity of the model with respect to the physical system. Moreover, our results suggest that simulated high latitude precipitation biases have important effects on the simulated ice conditions, resulting in impacts on the Arctic climate in general in large-scale climate.

scholarly journals Model simulations of arctic biogeochemistry and permafrost extent are highly sensitive to the implemented snow scheme in LPJ-GUESS

2021 ◽  
Vol 18 (20) ◽  
pp. 5767-5787
Author(s):  
Alexandra Pongracz ◽  
David Wårlind ◽  
Paul A. Miller ◽  
Frans-Jan W. Parmentier
Keyword(s):  
Snow Cover ◽  
Large Scale ◽  
Single Layer ◽  
Physical Factor ◽  
Cold Season ◽  
The Arctic ◽  
Soil Conditions ◽  
Cold Bias ◽  
Climate Feedbacks ◽  
Realistic Simulation

Abstract. The Arctic is warming rapidly, especially in winter, which is causing large-scale reductions in snow cover. Snow is one of the main controls on soil thermodynamics, and changes in its thickness and extent affect both permafrost thaw and soil biogeochemistry. Since soil respiration during the cold season potentially offsets carbon uptake during the growing season, it is essential to achieve a realistic simulation of the effect of snow cover on soil conditions to more accurately project the direction of arctic carbon–climate feedbacks under continued winter warming. The Lund–Potsdam–Jena General Ecosystem Simulator (LPJ-GUESS) dynamic vegetation model has used – up until now – a single layer snow scheme, which underestimated the insulation effect of snow, leading to a cold bias in soil temperature. To address this shortcoming, we developed and integrated a dynamic, multi-layer snow scheme in LPJ-GUESS. The new snow scheme performs well in simulating the insulation of snow at hundreds of locations across Russia compared to observations. We show that improving this single physical factor enhanced simulations of permafrost extent compared to an advanced permafrost product, where the overestimation of permafrost cover decreased from 10 % to 5 % using the new snow scheme. Besides soil thermodynamics, the new snow scheme resulted in a doubled winter respiration and an overall higher vegetation carbon content. This study highlights the importance of a correct representation of snow in ecosystem models to project biogeochemical processes that govern climate feedbacks. The new dynamic snow scheme is an essential improvement in the simulation of cold season processes, which reduces the uncertainty of model projections. These developments contribute to a more realistic simulation of arctic carbon–climate feedbacks.

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 Comparing Simulated and Measured Sensible and Latent Heat Fluxes over Snow under a Pine Canopy to Improve an Energy Balance Snowmelt Model

2008 ◽  
Vol 9 (6) ◽  
pp. 1506-1522 ◽  
Author(s):  
D. Marks ◽  
A. Winstral ◽  
G. Flerchinger ◽  
M. Reba ◽  
J. Pomeroy ◽  
...  
Keyword(s):  
Energy Balance ◽  
Snow Cover ◽  
Eddy Covariance ◽  
Latent Heat ◽  
Energy Content ◽  
Heat Fluxes ◽  
Balance Model ◽  
Mass Fluxes ◽  
Model Efficiency ◽  
Snowmelt Model

Abstract During the second year of the NASA Cold Land Processes Experiment (CLPX), an eddy covariance (EC) system was deployed at the Local Scale Observation Site (LSOS) from mid-February to June 2003. The EC system was located beneath a uniform pine canopy, where the trees are regularly spaced and are of similar age and height. In an effort to evaluate the turbulent flux calculations of an energy balance snowmelt model (SNOBAL), modeled and EC-measured sensible and latent heat fluxes between the snow cover and the atmosphere during this period are presented and compared. Turbulent fluxes comprise a large component of the snow cover energy balance in the premelt and ripening period (March–early May) and therefore control the internal energy content of the snow cover as melt accelerates in late spring. Simulated snow cover depth closely matched measured values (RMS difference 8.3 cm; Nash–Sutcliff model efficiency 0.90), whereas simulated snow cover mass closely matched the few measured values taken during the season. Over the 927-h comparison period using the default model configuration, simulated sensible heat H was within 1 W m−2, latent heat LυE within 4 W m−2, and cumulative sublimation within 3 mm of that measured by the EC system. Differences between EC-measured and simulated fluxes occurred primarily at night. The reduction of the surface layer specification in the model from 25 to 10 cm reduced flux differences between EC-measured and modeled fluxes to 0 W m−2 for H, 2 W m−2 for LυE, and 1 mm for sublimation. When only daytime fluxes were compared, differences were further reduced to 1 W m−2 for LυE and <1 mm for sublimation. This experiment shows that in addition to traditional mass balance methods, EC-measured fluxes can be used to diagnose the performance of a snow cover energy balance model. It also demonstrates the use of eddy covariance methods for measuring heat and mass fluxes from snow covers at a low-wind, below-canopy site.

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