scholarly journals <i>ESCIMO.spread</i> – a spreadsheet-based point snow surface energy balance model to calculate hourly snow water equivalent and melt rates for historical and changing climate conditions

2010 ◽  
Vol 3 (2) ◽  
pp. 643-652 ◽  
Author(s):  
U. Strasser ◽  
T. Marke
Keyword(s):  
Energy Balance ◽  
Snow Water Equivalent ◽  
Winter Season ◽  
Longwave Radiation ◽  
Energy Balance Model ◽  
Balance Model ◽  
Snow Surface ◽  
Point Energy ◽  
Climate Conditions ◽  
Snow Water

Abstract. This paper describes the spreadsheet-based point energy balance model ESCIMO.spread which simulates the energy and mass balance as well as melt rates at the snow surface. The model makes use of hourly recordings of temperature, precipitation, wind speed, relative humidity, and incoming global and longwave radiation. The effect of potential climate change on the seasonal evolution of the snow cover can be estimated by modifying the time series of observed temperature and precipitation by means of adjustable parameters. Model output is graphically visualized in hourly and daily diagrams. The results compare well with weekly measured snow water equivalent (SWE). The model is easily portable and adjustable, and runs particularly fast: an hourly calculation of a one winter season is instantaneous on a standard computer. ESCIMO.spread can be obtained from the authors on request.

scholarly journals <i>ESCIMO.spread</i> – a spreadsheet-based point snow surface energy balance model to calculate hourly snow water equivalent and melt rates for historical and changing climate conditions

2010 ◽  
Vol 3 (2) ◽  
pp. 627-649 ◽  
Author(s):  
U. Strasser ◽  
T. Marke
Keyword(s):  
Energy Balance ◽  
Snow Water Equivalent ◽  
Winter Season ◽  
Longwave Radiation ◽  
Energy Balance Model ◽  
Balance Model ◽  
Snow Surface ◽  
Point Energy ◽  
Climate Conditions ◽  
Snow Water

Abstract. This paper describes the spreadsheet-based point energy balance model ESCIMO.spread which simulates the energy and mass balance as well as melt rates of a snow surface. The model makes use of hourly recordings of temperature, precipitation, wind speed, relative humidity, global and longwave radiation. The effect of potential climate change on the seasonal evolution of the snow cover can be estimated by modifying the time series of observed temperature and precipitation by means of adjustable parameters. Model output is graphically visualized in hourly and daily diagrams. The results compare well with weekly measured snow water equivalent (SWE). The model is easily portable and adjustable, and runs particularly fast: hourly calculation of a one winter season is instantaneous on a standard computer. ESICMO.spread can be obtained from the authors on request (contact: [email protected]).

Snowpack energy balance and changes in the frequency and extremity of rain-on-snow events in the warming climate

2021 ◽  
Author(s):  
Ondrej Hotovy ◽  
Michal Jenicek
Keyword(s):  
Energy Balance ◽  
Air Temperature ◽  
Snow Water Equivalent ◽  
Hydrological Cycle ◽  
Winter Season ◽  
Catchment Scale ◽  
The Future ◽  
Snow Water ◽  
The Impact ◽  
Catchment Runoff

&lt;p&gt;Seasonal snowpack significantly influences the catchment runoff and thus represents an important input for the hydrological cycle. Changes in the precipitation distribution and intensity, as well as a shift from snowfall to rain is expected in the future due to climate changes. As a result, rain-on-snow events, which are considered to be one of the main causes of floods in winter and spring, may occur more frequently. Heat from liquid precipitation constitutes one of the snowpack energy balance components. Consequently, snowmelt and runoff may be strongly affected by these temperature and precipitation changes.&lt;/p&gt;&lt;p&gt;The objective of this study is 1) to evaluate the frequency, inter-annual variability and extremity of rain-on-snow events in the past based on existing measurements together with an analysis of changes in the snowpack energy balance, and 2) to simulate the effect of predicted increase in air temperature on the occurrence of rain-on-snow events in the future. We selected 40 near-natural mountain catchments in Czechia with significant snow influence on runoff and with available long-time series (&gt;35 years) of daily hydrological and meteorological variables. A semi-distributed conceptual model, HBV-light, was used to simulate the individual components of the water cycle at a catchment scale. The model was calibrated for each of study catchments by using 100 calibration trials which resulted in respective number of optimized parameter sets. The model performance was evaluated against observed runoff and snow water equivalent. Rain-on-snow events definition by threshold values for air temperature, snow depth, rain intensity and snow water equivalent decrease allowed us to analyze inter-annual variations and trends in rain-on-snow events during the study period 1965-2019 and to explain the role of different catchment attributes.&lt;/p&gt;&lt;p&gt;The preliminary results show that a significant change of rain-on-snow events related to increasing air temperature is not clearly evident. Since both air temperature and elevation seem to be an important rain-on-snow drivers, there is an increasing rain-on-snow events occurrence during winter season due to a decrease in snowfall fraction. In contrast, a decrease in total number of events was observed due to the shortening of the period with existing snow cover on the ground. Modelling approach also opened further questions related to model structure and parameterization, specifically how individual model procedures and parameters represent the real natural processes. To understand potential model artefacts might be important when using HBV or similar bucket-type models for impact studies, such as modelling the impact of climate change on catchment runoff.&lt;/p&gt;

One-dimensional snow water and energy balance model for vegetated surfaces

1999 ◽  
Vol 13 (14-15) ◽  
pp. 2467-2482 ◽  
Author(s):  
Jiming Jin ◽  
Xiaogang Gao ◽  
Soroosh Sorooshian ◽  
Zong-Liang Yang ◽  
Roger Bales ◽  
...  
Keyword(s):  
Energy Balance ◽  
Energy Balance Model ◽  
Balance Model ◽  
One Dimensional ◽  
Snow Water

scholarly journals Estimation of surface energy fluxes in the Arctic tundra using the remote sensing thermal-based Two-Source Energy Balance model

2017 ◽  
Vol 21 (3) ◽  
pp. 1339-1358 ◽  
Author(s):  
Jordi Cristóbal ◽  
Anupma Prakash ◽  
Martha C. Anderson ◽  
William P. Kustas ◽  
Eugénie S. Euskirchen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Heat Flux ◽  
Energy Balance ◽  
Surface Energy ◽  
Arctic Tundra ◽  
Soil Heat Flux ◽  
Energy Balance Model ◽  
The Arctic ◽  
Balance Model ◽  
Climate Conditions

Abstract. The Arctic has become generally a warmer place over the past decades leading to earlier snow melt, permafrost degradation and changing plant communities. Increases in precipitation and local evaporation in the Arctic, known as the acceleration components of the hydrologic cycle, coupled with land cover changes, have resulted in significant changes in the regional surface energy budget. Quantifying spatiotemporal trends in surface energy flux partitioning is key to forecasting ecological responses to changing climate conditions in the Arctic. An extensive local evaluation of the Two-Source Energy Balance model (TSEB) – a remote-sensing-based model using thermal infrared retrievals of land surface temperature – was performed using tower measurements collected over different tundra types in Alaska in all sky conditions over the full growing season from 2008 to 2012. Based on comparisons with flux tower observations, refinements in the original TSEB net radiation, soil heat flux and canopy transpiration parameterizations were identified for Arctic tundra. In particular, a revised method for estimating soil heat flux based on relationships with soil temperature was developed, resulting in significantly improved performance. These refinements result in mean turbulent flux errors generally less than 50 W m−2 at half-hourly time steps, similar to errors typically reported in surface energy balance modeling studies conducted in more temperate climatic regimes. The MODIS leaf area index (LAI) remote sensing product proved to be useful for estimating energy fluxes in Arctic tundra in the absence of field data on the local biomass amount. Model refinements found in this work at the local scale build toward a regional implementation of the TSEB model over Arctic tundra ecosystems, using thermal satellite remote sensing to assess response of surface fluxes to changing vegetation and climate conditions.

scholarly journals Estimation of surface energy fluxes in the Arctic tundra using the remote sensing thermal-based Two-Source Energy Balance model

2016 ◽  
Author(s):  
Jordi Cristóbal ◽  
Anupma Prakash ◽  
Martha C. Anderson ◽  
William P. Kustas ◽  
Eugénie S. Euskirchen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Heat Flux ◽  
Energy Balance ◽  
Surface Energy ◽  
Arctic Tundra ◽  
Soil Heat Flux ◽  
Energy Balance Model ◽  
The Arctic ◽  
Balance Model ◽  
Climate Conditions

Abstract. The Arctic has become generally a warmer place over the past decades leading to earlier snow melt, permafrost degradation and changing plant communities. Increases in precipitation and local evaporation in the Arctic, known as one of the acceleration components of the hydrologic cycle, coupled with land cover changes, have resulted in significant changes in the regional surface energy budget. Quantifying spatiotemporal trends in surface energy flux partitioning is a key to forecasting ecological responses to changing climate conditions in the Arctic regions. An extensive evaluation of the two-source energy balance model (TSEB) – a remote sensing-based model using thermal infrared retrievals of land–surface temperature – was performed using tower measurements collected over different tundra types in Alaska in all sky conditions over the full growing season from 2008 to 2012. Based on comparisons with flux tower observations, refinements in the original TSEB net radiation, soil heat flux and canopy transpiration parameterizations were identified for the unique Arctic tundra conditions. In particular, a revised method for estimating soil heat flux based on relationships with soil temperature was developed, resulting in significantly improved performance. These refinements result in mean flux errors around 50 W m−2 at half-hourly timesteps similar to errors typically reported in surface energy balance modeling studies conducted in more temperate climatic regimes. MODIS LAI remote sensing product proved to be useful for estimating energy fluxes in Arctic tundra in the absence of field data. This work builds toward a regional implementation of the TSEB model over Arctic tundra ecosystems, using thermal satellite remote sensing to assess response of surface fluxes to changing vegetation and climate conditions.

Modeling the Snowpack Energy Balance during Melt under Exposed Crop Stubble

2018 ◽  
Vol 19 (7) ◽  
pp. 1191-1214 ◽  
Author(s):  
Phillip Harder ◽  
Warren D. Helgason ◽  
John W. Pomeroy
Keyword(s):  
Energy Balance ◽  
Snow Water Equivalent ◽  
Agricultural Practices ◽  
Longwave Radiation ◽  
Areal Density ◽  
Turbulent Fluxes ◽  
Shortwave Radiation ◽  
Snow Surface ◽  
Canadian Prairies ◽  
Physically Based

Abstract On the Canadian Prairies, agricultural practices result in millions of hectares of standing crop stubble that gradually emerges during snowmelt. The importance of stubble in trapping wind-blown snow and retaining winter snowfall has been well demonstrated. However, stubble is not explicitly accounted for in hydrological or energy balance snowmelt models. This paper relates measurable stubble parameters (height, width, areal density, and albedo) to the snowpack energy balance and snowmelt with the new, physically based Stubble–Snow–Atmosphere Model (SSAM). Novel process representations of SSAM quantify the attenuation of shortwave radiation by exposed stubble, the sky and vegetation view factors needed to solve longwave radiation terms, and a resistance scheme for stubble–snow–atmosphere fluxes to solve for surface temperatures and turbulent fluxes. SSAM results were compared to observations of radiometric snow-surface temperature, stubble temperature, snow-surface solar irradiance, areal-average turbulent fluxes, and snow water equivalent from two intensive field campaigns during snowmelt in 2015 and 2016 over wheat and canola stubble in Saskatchewan, Canada. Uncalibrated SSAM simulations compared well with these observations, providing confidence in the model structure and parameterization. A sensitivity analysis conducted using SSAM revealed compensatory relationships in energy balance terms that result in a small increase in net snowpack energy as stubble exposure increases.

scholarly journals Snowmelt and sublimation: field experiments and modelling in the High Atlas Mountains of Morocco

2004 ◽  
Vol 8 (6) ◽  
pp. 1076-1089 ◽  
Author(s):  
O. Schulz ◽  
C. de Jong
Keyword(s):  
Energy Balance ◽  
Snow Cover ◽  
Energy Balance Model ◽  
Balance Model ◽  
Atmospheric Humidity ◽  
Point Energy ◽  
High Atlas ◽  
Atlas Mountains ◽  
High Atlas Mountains ◽  
Weather Stations

Abstract. Snow in the High Atlas Mountains is a major source for freshwater renewal and for water availability in the semi-arid lowlands of south-eastern Morocco. Snowfall- and snow-ablation monitoring and modelling is important for estimating potential water delivery from the mountain water towers to the forelands. This study is part of GLOWA-IMPETUS, an integrated management project dealing with scarce water resources in West Africa. The Ameskar study area is located to the south of the High Atlas Mountains, in their rain shadow. As a part of the M’Goun river basin within the upper Drâa valley, the study area is characterised by high radiation inputs, low atmospheric humidity and long periods with sub-zero temperatures. Its altitude ranges between 2000 m and 4000 m, with dominant north- and south-facing slopes. Snowfall occurs mainly from November to April but even summit regions can become repeatedly devoid of snow cover. Snow cover maps for the M’Goun basin (1240 km2) are derived from calculations of NDSI (Normalized Difference Snow Index) from MODIS satellite images and snow depth is monitored at four automatic weather stations between 2000–4000 m. Snowfall events are infrequent at lower altitudes. The presence of snow penitentes at altitudes above 3000 m indicates that snow sublimation is an important component of snow ablation. Snow ablation was modelled with the UEB Utah Energy Balance Model (Tarboton and Luce, 1996). This single layer, physically-based, point energy and mass balance model is driven by meteorological variables recorded at the automatic weather stations at Tounza (2960 m) and Tichki (3260 m). Data from snow pillows at Tounza and Tichki are used to validate the model’s physical performance in terms of energy and water balances for a sequence of two snowfall events in the winter of 2003/4. First UEB modelling results show good overall performance and timing of snowmelt and sublimation compared to field investigations. Up to 44% of snow ablation is attributed to snow sublimation in typical winters with subzero temperatures and low atmospheric humidity at an altitude of 3000 m. At altitudes below 3000 m snowmelt generally dominates over sublimation. Unfortunately, the highest altitude zones suffer long periods with direct water loss into the atmosphere by sublimation in the course of which they cannot contribute to direct runoff or groundwater formation in the southern High Atlas Mountains. Keywords: sublimation, snow ablation modelling, energy balance model, High Atlas Mountains

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