scholarly journals Validation of the energy budget of an alpine snowpack simulated by several snow models (Snow MIP project)

2004 ◽  
Vol 38 ◽  
pp. 150-158 ◽  
Author(s):  
Pierre Etchevers ◽  
Eric Martin ◽  
Ross Brown ◽  
Charles Fierz ◽  
Yves Lejeune ◽  
...  
Keyword(s):  
Energy Budget ◽  
Longwave Radiation ◽  
Model Complexity ◽  
Shortwave Radiation ◽  
Avalanche Forecasting ◽  
Simple Index ◽  
Analysis Of Results ◽  
Snow Model ◽  
Global Atmospheric Circulation ◽  
The Impact

AbstractMany snow models have been developed for various applications such as hydrology, global atmospheric circulation models and avalanche forecasting. The degree of complexity of these models is highly variable, ranging from simple index methods to multi-layer models that simulate snow-cover stratigraphy and texture. In the framework of the Snow Model Intercomparison Project (SnowMIP), 23 models were compared using observed meteorological parameters from two mountainous alpine sites. The analysis here focuses on validation of snow energy-budget simulations. Albedo and snow surface temperature observations allow identification of the more realistic simulations and quantification of errors for two components of the energy budget: the net short- and longwave radiation. In particular, the different albedo parameterizations are evaluated for different snowpack states (in winter and spring). Analysis of results during the melting period allows an investigation of the different ways of partitioning the energy fluxes and reveals the complex feedbacks which occur when simulating the snow energy budget. Particular attention is paid to the impact of model complexity on the energy-budget components. The model complexity has a major role for the net longwave radiation calculation, whereas the albedo parameterization is the most significant factor explaining the accuracy of the net shortwave radiation simulation.

scholarly journals How Does Availability of Meteorological Forcing Data Impact Physically Based Snowpack Simulations?*

2015 ◽  
Vol 17 (1) ◽  
pp. 99-120 ◽  
Author(s):  
Mark S. Raleigh ◽  
Ben Livneh ◽  
Karl Lapo ◽  
Jessica D. Lundquist
Keyword(s):  
Snow Water Equivalent ◽  
Longwave Radiation ◽  
Data Availability ◽  
Model Complexity ◽  
Shortwave Radiation ◽  
Meteorological Forcing ◽  
Temperature And Precipitation ◽  
Physically Based ◽  
Snow Model ◽  
The Impact

Abstract Physically based models facilitate understanding of seasonal snow processes but require meteorological forcing data beyond air temperature and precipitation (e.g., wind, humidity, shortwave radiation, and longwave radiation) that are typically unavailable at automatic weather stations (AWSs) and instead are often represented with empirical estimates. Research is needed to understand which forcings (after temperature and precipitation) would most benefit snow modeling through expanded observation or improved estimation techniques. Here, the impact of forcing data availability on snow model output is assessed with data-withholding experiments using 3-yr datasets at well-instrumented sites in four climates. The interplay between forcing availability and model complexity is examined among the Utah Energy Balance (UEB), the Distributed Hydrology Soil Vegetation Model (DHSVM) snow submodel, and the snow thermal model (SNTHERM). Sixty-four unique forcing scenarios were evaluated, with different assumptions regarding availability of hourly meteorological observations at each site. Modeled snow water equivalent (SWE) and snow surface temperature Tsurf diverged most often because of availability of longwave radiation, which is the least frequently measured forcing in cold regions in the western United States. Availability of longwave radiation (i.e., observed vs empirically estimated) caused maximum SWE differences up to 234 mm (57% of peak SWE), mean differences up to 6.2°C in Tsurf, and up to 32 days difference in snow disappearance timing. From a model data perspective, more common observations of longwave radiation at AWSs could benefit snow model development and applications, but other aspects (e.g., costs, site access, and maintenance) need consideration.

scholarly journals Measuring the impact of a new snow model using surface energy budget process relationships

2020 ◽  
Author(s):  
Jonathan Day ◽  
Gabriele Arduini ◽  
Irina Sandu ◽  
Linus Magnusson ◽  
Anton Beljaars ◽  
...  
Keyword(s):  
Surface Energy ◽  
Energy Budget ◽  
Surface Energy Budget ◽  
Budget Process ◽  
Snow Model ◽  
The Impact

scholarly journals Near-surface climate and surface energy budget of Larsen C ice shelf, Antarctic Peninsula

2012 ◽  
Vol 6 (2) ◽  
pp. 353-363 ◽  
Author(s):  
P. Kuipers Munneke ◽  
M. R. van den Broeke ◽  
J. C. King ◽  
T. Gray ◽  
C. H. Reijmer
Keyword(s):  
Surface Energy ◽  
Antarctic Peninsula ◽  
Energy Budget ◽  
Heat Fluxes ◽  
Surface Energy Budget ◽  
Shortwave Radiation ◽  
Sensible Heat ◽  
Ice Shelf ◽  
Near Surface ◽  
The Impact

Abstract. Data collected by two automatic weather stations (AWS) on the Larsen C ice shelf, Antarctica, between 22 January 2009 and 1 February 2011 are analyzed and used as input for a model that computes the surface energy budget (SEB), which includes melt energy. The two AWSs are separated by about 70 km in the north–south direction, and both the near-surface meteorology and the SEB show similarities, although small differences in all components (most notably the melt flux) can be seen. The impact of subsurface absorption of shortwave radiation on melt and snow temperature is significant, and discussed. In winter, longwave cooling of the surface is entirely compensated by a downward turbulent transport of sensible heat. In summer, the positive net radiative flux is compensated by melt, and quite frequently by upward turbulent diffusion of heat and moisture, leading to sublimation and weak convection over the ice shelf. The month of November 2010 is highlighted, when strong westerly flow over the Antarctic Peninsula led to a dry and warm föhn wind over the ice shelf, resulting in warm and sunny conditions. Under these conditions the increase in shortwave and sensible heat fluxes is larger than the decrease of net longwave and latent heat fluxes, providing energy for significant melt.

scholarly journals Characterizing energy budget variability at a Sahelian site: a test of NWP model behaviour

2017 ◽  
Vol 17 (24) ◽  
pp. 15095-15119 ◽  
Author(s):  
Anna Mackie ◽  
Paul I. Palmer ◽  
Helen Brindley
Keyword(s):  
Energy Budget ◽  
Radiation Flux ◽  
Linear Models ◽  
Longwave Radiation ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
Daily Average ◽  
Radiation Fluxes ◽  
Nwp Model

Abstract. We use observations of surface and top-of-the-atmosphere (TOA) broadband radiation fluxes determined from the Atmospheric Radiation Measurement programme mobile facility, the Geostationary Earth Radiation Budget (GERB) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) instruments and a range of meteorological variables at a site in the Sahel to test the ability of the ECMWF Integrated Forecasting System cycle 43r1 to describe energy budget variability. The model has daily average biases of −12 and 18 W m−2 for outgoing longwave and reflected shortwave TOA radiation fluxes, respectively. At the surface, the daily average bias is 12(13) W m−2 for the longwave downwelling (upwelling) radiation flux and −21(−13) W m−2 for the shortwave downwelling (upwelling) radiation flux. Using multivariate linear models of observation–model differences, we attribute radiation flux discrepancies to physical processes, and link surface and TOA fluxes. We find that model biases in surface radiation fluxes are mainly due to a low bias in ice water path (IWP), poor description of surface albedo and model–observation differences in surface temperature. We also attribute observed discrepancies in the radiation fluxes, particularly during the dry season, to the misrepresentation of aerosol fields in the model from use of a climatology instead of a dynamic approach. At the TOA, the low IWP impacts the amount of reflected shortwave radiation while biases in outgoing longwave radiation are additionally coupled to discrepancies in the surface upwelling longwave flux and atmospheric humidity.

The Impact of Snow Model Complexity at Three CLPX Sites

2008 ◽  
Vol 9 (6) ◽  
pp. 1464-1481 ◽  
Author(s):  
Xia Feng ◽  
Alok Sahoo ◽  
Kristi Arsenault ◽  
Paul Houser ◽  
Yan Luo ◽  
...  
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Snow Depth ◽  
Snow Water Equivalent ◽  
Snow Accumulation ◽  
Model Complexity ◽  
Snow Albedo ◽  
Community Land Model ◽  
Snow Model ◽  
The Impact

Abstract Many studies have developed snow process understanding by exploring the impact of snow model complexity on simulation performance. This paper revisits this topic using several recently developed land surface models, including the Simplified Simple Biosphere Model (SSiB); Noah; Variable Infiltration Capacity (VIC); Community Land Model, version 3 (CLM3); Snow Thermal Model (SNTHERM); and new field measurements from the Cold Land Processes Field Experiment (CLPX). Offline snow cover simulations using these five snow models with different physical complexity are performed for the Rabbit Ears Buffalo Pass (RB), Fraser Experimental Forest headquarters (FHQ), and Fraser Alpine (FA) sites between 20 September 2002 and 1 October 2003. These models simulate the snow accumulation and snowpack ablation with varying skill when forced with the same meteorological observations, initial conditions, and similar soil and vegetation parameters. All five models capture the basic features of snow cover dynamics but show remarkable discrepancy in depicting snow accumulation and ablation, which could result from uncertain model physics and/or biased forcing. The simulated snow depth in SSiB during the snow accumulation period is consistent with the more complicated CLM3 and SNTHERM; however, early runoff is noted, owing to neglected water retention within the snowpack. Noah is consistent with SSiB in simulating snow accumulation and ablation at RB and FA, but at FHQ, Noah underestimates snow depth and snow water equivalent (SWE) as a result of a higher net shortwave radiation at the surface, resulting from the use of a small predefined maximum snow albedo. VIC and SNTHERM are in good agreement with each other, and they realistically reproduce snow density and net radiation. CLM3 is consistent with VIC and SNTHERM during snow accumulation, but it shows early snow disappearance at FHQ and FA. It is also noted that VIC, CLM3, and SNTHERM are unable to capture the observed runoff timing, even though the water storage and refreezing effects are included in their physics. A set of sensitivity experiments suggest that Noah’s snow simulation is improved with a higher maximum albedo and that VIC exhibits little improvement with a larger fresh snow albedo. There are remarkable differences in the vegetation impact on snow simulation for each snow model. In the presence of forest cover, SSiB shows a substantial increase in snow depth and SWE, Noah and VIC show a slight change though VIC experiences a later onset of snowmelt, and CLM3 has a reduction in its snow depth. Finally, we observe that a refined precipitation dataset significantly improves snow simulation, emphasizing the importance of accurate meteorological forcing for land surface modeling.

scholarly journals Near-surface climate and surface energy budget of Larsen C ice shelf, Antarctic Peninsula

2011 ◽  
Vol 5 (5) ◽  
pp. 2665-2697
Author(s):  
P. Kuipers Munneke ◽  
M. R. van den Broeke ◽  
J. C. King ◽  
T. Gray ◽  
C. H. Reijmer
Keyword(s):  
Surface Energy ◽  
Antarctic Peninsula ◽  
Energy Budget ◽  
Heat Fluxes ◽  
Surface Energy Budget ◽  
Shortwave Radiation ◽  
Sensible Heat ◽  
Ice Shelf ◽  
Near Surface ◽  
The Impact

Abstract. Data collected by two automatic weather stations (AWS) on the Larsen C ice shelf, Antarctica, between 22 January 2009 and 1 February 2011 are analyzed and used as input for a model that computes the surface energy budget (SEB), including melt energy. The two AWSs are separated by about 70 km in the north-south direction, and both the near-surface meteorology and the SEB show similarities, although small differences in all components (most notably the melt flux) can be seen. The impact of subsurface absorption of shortwave radiation on melt and snow temperature is significant, and discussed. In winter, longwave cooling of the surface is entirely compensated by a downward turbulent transport of sensible heat. In summer, the positive net radiative flux is compensated by melt, and quite frequently by upward turbulent diffusion of heat and moisture, leading to sublimation and weak convection over the ice shelf. The month of November 2010 is highlighted, when strong westerly flow over the Antarctic Peninsula led to a dry and warm föhn wind over the ice shelf, resulting in warm and sunny conditions. Under these conditions the increase in shortwave and sensible heat fluxes is larger than the reduction of net longwave and latent heat fluxes, providing energy for significant melt.

scholarly journals The Impact of Variable Horizon Shade on the Growing Season Energy Budget of a Subalpine Headwater Wetland

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1473
Author(s):  
Dylan M. Hrach ◽  
Richard M. Petrone ◽  
Brandon Van Huizen ◽  
Adam Green ◽  
Myroslava Khomik
Keyword(s):  
Soil Moisture ◽  
Surface Energy ◽  
Energy Budget ◽  
Growing Season ◽  
Shortwave Radiation ◽  
Energy Budgets ◽  
Water Storage Capacity ◽  
Headwater Wetland ◽  
Downstream Flow ◽  
The Impact

Surface energy budgets are important to the ecohydrology of complex terrain, where land surfaces cycle in and out of shadows creating distinct microclimates. Shading in such environments can help regulate downstream flow over the course of a growing season, but our knowledge on how shadows impact the energy budget and consequently ecohydrology in montane ecosystems is very limited. We investigated the influence of horizon shade on the surface energy fluxes of a subalpine headwater wetland in the Canadian Rocky Mountains during the growing season. During the study, surface insolation decreased by 60% (32% due to evolving horizon shade and 28% from seasonality). The influence of shade on the energy budget varied between two distinct periods: (1) Stable Shade, when horizon shade was constant and reduced sunlight by 2 h per day; and (2) Dynamic Shade, when shade increased and reduced sunlight by 0.18 h more each day, equivalent to a 13% reduction in incoming shortwave radiation and 16% in net radiation. Latent heat flux, the dominant energy flux at our site, varied temporally because of changes in incoming radiation, atmospheric demand, soil moisture and shade. Horizon shade controlled soil moisture at our site by prolonging snowmelt and reducing evapotranspiration in the late growing season, resulting in increased water storage capacity compared to other mountain wetlands. With the mounting risk of climate-change-driven severe spring flooding and late season droughts downstream of mountain headwaters, shaded subalpine wetlands provide important ecohydrological and mitigation services that are worthy of further study and mapping. This will help us better understand and protect mountain and prairie water resources.

scholarly journals Characterising energy budget variability at a Sahelian site: a test of NWP model behaviour

2017 ◽  
Author(s):  
Anna Mackie ◽  
Paul I. Palmer ◽  
Helen Brindley
Keyword(s):  
Energy Budget ◽  
Linear Models ◽  
Longwave Radiation ◽  
Surface Radiation ◽  
Shortwave Radiation ◽  
Broadband Radiation ◽  
Radiation Fluxes ◽  
Forecasting System ◽  
Multivariate Linear Models ◽  
Nwp Model

Abstract. We use observations of surface and top-of-the-atmosphere (TOA) broadband radiation fluxes determined from the Atmospheric Radiation Measurement program Mobile Facility, and GERB/SEVIRI,and a range of meteorological variables, at a site in the Sahel to test the ability of the ECMWF Integrated Forecasting System cycle 43r1 to describe energy budget variability. The model has daily average bias of −12 W m-2 and 18 W m-2 for outgoing longwave and reflected shortwave TOA radiation fluxes, respectively. Using multivariate linear models of observation minus model differences, we attribute radiation flux discrepancies to physical processes, and link surface and TOA fluxes. We find that model biases in surface radiation fluxes are mainly due to a low bias in ice-water path (IWP), poor description of surface albedo, and model-observation differences in surface temperature. At the TOA, the low IWP impacts the amount of reflected shortwave radiation while biases in outgoing longwave radiation are additionally coupled to discrepancies in the surface upwelling longwave flux and atmospheric humidity.

scholarly journals Measuring the Impact of a New Snow Model Using Surface Energy Budget Process Relationships

2020 ◽  
Vol 12 (12) ◽  
Author(s):  
Jonathan J. Day ◽  
Gabriele Arduini ◽  
Irina Sandu ◽  
Linus Magnusson ◽  
Anton Beljaars ◽  
...  
Keyword(s):  
Surface Energy ◽  
Energy Budget ◽  
Surface Energy Budget ◽  
Budget Process ◽  
Snow Model ◽  
The Impact

scholarly journals Sensitivity of the surface energy budget to drifting snow as simulated by MAR in coastal Adelie Land, Antarctica

2021 ◽  
Vol 15 (8) ◽  
pp. 3595-3614
Author(s):  
Louis Le Toumelin ◽  
Charles Amory ◽  
Vincent Favier ◽  
Christoph Kittel ◽  
Stefan Hofer ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Surface Energy ◽  
Energy Budget ◽  
Climate Models ◽  
Longwave Radiation ◽  
Surface Energy Budget ◽  
Near Surface ◽  
Surface Atmosphere ◽  
Drifting Snow ◽  
The Impact

Abstract. In order to understand the evolution of the climate of Antarctica, dominant processes that control surface and low-atmosphere meteorology need to be accurately captured in climate models. We used the regional climate model MAR (v3.11) at 10 km horizontal resolution, forced by ERA5 reanalysis over a 9-year period (2010–2018) to study the impact of drifting snow (designating here the wind-driven transport of snow particles below and above 2 m) on the near-surface atmosphere and surface in Adelie Land, East Antarctica. Two model runs were performed, one with and one without drifting snow, and compared to half-hourly in situ observations at D17, a coastal and windy location of Adelie Land. We show that sublimation of drifting-snow particles in the atmosphere drives the difference between model runs and is responsible for significant impacts on the near-surface atmosphere. By cooling the low atmosphere and increasing its relative humidity, drifting snow also reduces sensible and latent heat exchanges at the surface (−5.7 W m−2 on average). Moreover, large and dense drifting-snow layers act as near-surface cloud by interacting with incoming radiative fluxes, enhancing incoming longwave radiation and reducing incoming shortwave radiation in summer (net radiative forcing: 5.7 W m−2). Even if drifting snow modifies these processes involved in surface–atmosphere interactions, the total surface energy budget is only slightly modified by introducing drifting snow because of compensating effects in surface energy fluxes. The drifting-snow driven effects are not prominent near the surface but peak higher in the boundary layer (fourth vertical level, 12 m) where drifting-snow sublimation is the most pronounced. Accounting for drifting snow in MAR generally improves the comparison at D17, especially for the representation of relative humidity (mean bias reduced from −14.0 % to −0.7 %) and incoming longwave radiation (mean bias reduced from −20.4 W m−2 to −14.9 W m−2). Consequently, our results suggest that a detailed representation of drifting-snow processes is required in climate models to better capture the near-surface meteorology and surface–atmosphere interactions in coastal Adelie Land.

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