scholarly journals SEMIC: an efficient surface energy and mass balance model applied to the Greenland ice sheet

2016 ◽  
Author(s):  
Mario Krapp ◽  
Alexander Robinson ◽  
Andrey Ganopolski
Keyword(s):  
Surface Energy ◽  
Mass Balance ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Balance Model ◽  
Future Climate Change ◽  
Surface Model ◽  
Climate Change Scenarios ◽  
Mass Balance Model ◽  
Ice Sheet Modelling

Abstract. We present SEMIC, a Surface Energy and Mass balance model of Intermediate Complexity for snow and ice covered surfaces such as the Greenland ice sheet. SEMIC is fast enough for glacial cycle applications, making it a suitable replacement for simpler methods such as the positive degree day method often used in ice sheet modelling. Our model explicitly calculates the main processes involved in the surface energy and mass balance, while maintaining a simple interface and minimal data input to drive it. In this novel approach, we parameterise diurnal temperature variations in order to more realistically capture the daily thaw-freeze cycles that characterise the ice sheet mass balance. We show how to derive optimal model parameters for SEMIC to reproduce surface characteristics and day-to-day variations similar to the regional climate model MAR (Modèle Atmosphérique Régional) and its incorporated multi-layer snowpack model. A validation test shows that SEMIC simulates future changes in surface temperature and surface mass balance in good agreement with the more sophisticated multi-layer snowpack model included in MAR. With this paper, we present a physically-based surface model to the ice sheet-modelling community that is computationally fast enough for long-term integrations, such as glacial cycles or future climate change scenarios.

scholarly journals SEMIC: an efficient surface energy and mass balance model applied to the Greenland ice sheet

2017 ◽  
Vol 11 (4) ◽  
pp. 1519-1535 ◽  
Author(s):  
Mario Krapp ◽  
Alexander Robinson ◽  
Andrey Ganopolski
Keyword(s):  
Surface Energy ◽  
Mass Balance ◽  
Climate Model ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Balance Model ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Mass Balance Model ◽  
Ice Sheet Modelling

Abstract. We present SEMIC, a Surface Energy and Mass balance model of Intermediate Complexity for snow- and ice-covered surfaces such as the Greenland ice sheet. SEMIC is fast enough for glacial cycle applications, making it a suitable replacement for simpler methods such as the positive degree day (PDD) method often used in ice sheet modelling. Our model explicitly calculates the main processes involved in the surface energy and mass balance, while maintaining a simple interface and requiring minimal data input to drive it. In this novel approach, we parameterise diurnal temperature variations in order to more realistically capture the daily thaw–freeze cycles that characterise the ice sheet mass balance. We show how to derive optimal model parameters for SEMIC specifically to reproduce surface characteristics and day-to-day variations similar to the regional climate model MAR (Modèle Atmosphérique Régional, version 2) and its incorporated multilayer snowpack model SISVAT (Soil Ice Snow Vegetation Atmosphere Transfer). A validation test shows that SEMIC simulates future changes in surface temperature and surface mass balance in good agreement with the more sophisticated multilayer snowpack model SISVAT included in MAR. With this paper, we present a physically based surface model to the ice sheet modelling community that is general enough to be used with in situ observations, climate model, or reanalysis data, and that is at the same time computationally fast enough for long-term integrations, such as glacial cycles or future climate change scenarios.

scholarly journals A surface energy and mass balance model for simulations over multiple glacial cycles

2018 ◽  
Author(s):  
Andreas Born ◽  
Michael A. Imhof ◽  
Thomas F. Stocker
Keyword(s):  
Surface Energy ◽  
Mass Balance ◽  
Ice Sheet ◽  
Balance Model ◽  
Integration Time ◽  
Mass Balance Model ◽  
Glacial Cycles ◽  
Current Configuration ◽  
Large Ensembles ◽  
Continental Ice Sheets

Abstract. A comprehensive understanding of the state and dynamics of the land cryosphere and associated sea level rise is not possible without taking into consideration the intrinsic time scales of the continental ice sheets. At the same time, the ice sheet mass balance is the result of seasonal variations in the meteorological conditions. Simulations of the coupled climate-ice sheet system thus face the dilemma of skillfully resolving short-lived phenomena, while also being computationally fast enough to run over tens of thousands of years. Further complications arise from the fact that the mass balance is a small residual of various contributions that individually are much larger, and that even a marginal bias will develop into an erroneous solution over the long integration time and when amplified by strong positive feedback mechanisms. As a possible solution, we present the BErgen Snow SImulator (BESSI), a surface energy and mass balance model that achieves computational efficiency while simulating all surface and internal fluxes of heat and mass explicitly and based on physical first principles. In its current configuration it covers most land areas of the Northern Hemisphere. Two large ensembles of simulations are investigated, one to calibrate the model and another one to assess its sensitivity to variations in air temperature.

scholarly journals A surface mass balance model for the Greenland Ice Sheet

2005 ◽  
Vol 110 (F4) ◽  
pp. n/a-n/a ◽  
Author(s):  
Marion Bougamont ◽  
Jonathan L. Bamber ◽  
Wouter Greuell
Keyword(s):  
Mass Balance ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Balance Model ◽  
Surface Mass Balance ◽  
Mass Balance Model ◽  
Surface Mass

scholarly journals An efficient surface energy–mass balance model for snow and ice

2019 ◽  
Vol 13 (5) ◽  
pp. 1529-1546 ◽  
Author(s):  
Andreas Born ◽  
Michael A. Imhof ◽  
Thomas F. Stocker
Keyword(s):  
Surface Energy ◽  
Mass Balance ◽  
Ice Sheet ◽  
Surface Air Temperature ◽  
Shortwave Radiation ◽  
Balance Model ◽  
Mass Balance Model ◽  
Current Configuration ◽  
Temperature And Precipitation ◽  
Continental Ice Sheets

Abstract. A comprehensive understanding of the state and dynamics of the land cryosphere and associated sea level rise is not possible without taking into consideration the intrinsic timescales of the continental ice sheets. At the same time, the ice sheet mass balance is the result of seasonal variations in the meteorological conditions. Simulations of the coupled climate–ice-sheet system thus face the dilemma of skillfully resolving short-lived phenomena, while also being computationally fast enough to run over tens of thousands of years. As a possible solution, we present the BErgen Snow SImulator (BESSI), a surface energy and mass balance model that achieves computational efficiency while simulating all surface and internal fluxes of heat and mass explicitly, based on physical first principles. In its current configuration it covers most land areas of the Northern Hemisphere. Input data are daily values of surface air temperature, total precipitation, and shortwave radiation. The model is calibrated using present-day observations of Greenland firn temperature, cumulative Greenland mass changes, and monthly snow extent over the entire domain. The results of the calibrated simulations are then discussed. Finally, as a first application of the model and to illustrate its numerical efficiency, we present the results of a large ensemble of simulations to assess the model's sensitivity to variations in temperature and precipitation.

scholarly journals COSIPY v1.2 – An open-source coupled snowpack and ice surface energy and mass balance model

2020 ◽  
Author(s):  
Tobias Sauter ◽  
Anselm Arndt ◽  
Christoph Schneider
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Mass Balance ◽  
Surface Energy Balance ◽  
Balance Model ◽  
Surface Mass Balance ◽  
Mass Balance Model ◽  
Physical Processes ◽  
Surface Mass ◽  
Ice Surface

Abstract. Glacial changes play a key role both from a socio-economical and political, and scientific point of view. The identification and the understanding of the nature of these changes still poses fundamental challenges for climate, glacier and water research. Many studies aim to identify the climatic drivers behind the observed glacial changes using distributed surface mass and energy balance models. Distributed surface mass balance models, which translate the meteorological conditions on glaciers into local melting rates, thus offer the possibility to attribute and detect glacier mass and volume responses to changes in the climatic forcings. A well calibrated model is a suitable test-bed for sensitivity, detection and attribution analyses for many scientific applications and often serves as a tool for quantifying the inherent uncertainties. Here we present the open-source coupled snowpack and ice surface energy and mass balance model in Python COSIPY, which provides a lean, flexible and user-friendly framework for modelling distributed snow and glacier mass changes. The model has a modular structure so that the exchange of routines or parameterizations of physical processes is possible with little effort for the user. The model has a modular structure so that the exchange of routines or parameterizations of physical processes is possible with little effort for the user. The framework consists of a computational kernel, which forms the runtime environment and takes care of the initialization, the input-output routines, the parallelization as well as the grid and data structures. This structure offers maximum flexibility without having to worry about the internal numerical flow. The adaptive sub-surface scheme allows an efficient and fast calculation of the otherwise computationally demanding fundamental equations. The surface energy-balance scheme uses established standard parameterizations for radiation as well as for the energy exchange between atmosphere and surface. The schemes are coupled by solving both surface energy balance and subsurface fluxes iteratively in such that consistent surface skin temperature is returned at the interface. COSIPY uses a one-dimensional approach limited to the vertical fluxes of energy and matter but neglects any lateral processes. Accordingly, the model can be easily set up in parallel computational environments for calculating both energy balance and climatic surface mass balance of glacier surfaces based on flexible horizontal grids and with varying temporal resolution. The model is made available on a freely accessible site and can be used for non-profit purposes. Scientists are encouraged to actively participate in the extension and improvement of the model code.

scholarly journals Forcing a Distributed Glacier Mass Balance Model with the Regional Climate Model REMO. Part I: Climate Model Evaluation

2010 ◽  
Vol 23 (6) ◽  
pp. 1589-1606 ◽  
Author(s):  
Sven Kotlarski ◽  
Frank Paul ◽  
Daniela Jacob
Keyword(s):  
Regional Climate Model ◽  
Mass Balance ◽  
Climate Model ◽  
Regional Climate ◽  
Global Radiation ◽  
High Elevation ◽  
Balance Model ◽  
Future Climate Change ◽  
Glacier Mass Balance ◽  
Mass Balance Model

Abstract A coupling interface between the regional climate model REMO and a distributed glacier mass balance model is presented in a series of two papers. The first part describes and evaluates the reanalysis-driven regional climate simulation that is used to force a mass balance model for two glaciers of the Swiss mass balance network. The detailed validation of near-surface air temperature, precipitation, and global radiation for the European Alps shows that the basic spatial and temporal patterns of all three parameters are reproduced by REMO. Compared to the Climatic Research Unit (CRU) dataset, the Alpine mean temperature is underestimated by 0.34°C. Annual precipitation shows a positive bias of 17% (30%) with respect to the uncorrected gridded ALP-IMP (CRU) dataset. A number of important and systematic model biases arise in high-elevation regions, namely, a negative temperature bias in winter, a bias of seasonal precipitation (positive or negative, depending on gridbox altitude and season), and an underestimation of springtime and overestimation of summertime global radiation. These can be expected to have a strong effect on the simulated glacier mass balance. It is recommended to account for these shortcomings by applying correction procedures before using the RCM output for subsequent mass balance modeling. Despite the obvious model deficiencies in high-elevation regions, the new interface broadens the scope of application of glacier mass balance models and will allow for a straightforward assessment of future climate change impacts.

scholarly journals Effect of uncertainty in surface mass balance–elevation feedback on projections of the future sea level contribution of the Greenland ice sheet

2014 ◽  
Vol 8 (1) ◽  
pp. 195-208 ◽  
Author(s):  
T. L. Edwards ◽  
X. Fettweis ◽  
O. Gagliardini ◽  
F. Gillet-Chaulet ◽  
H. Goelzer ◽  
...  
Keyword(s):  
Mass Balance ◽  
Sea Level ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Future Climate Change ◽  
Climate Projections ◽  
Surface Mass Balance ◽  
Credibility Interval ◽  
Surface Mass ◽  
Best Estimate

Abstract. We apply a new parameterisation of the Greenland ice sheet (GrIS) feedback between surface mass balance (SMB: the sum of surface accumulation and surface ablation) and surface elevation in the MAR regional climate model (Edwards et al., 2014) to projections of future climate change using five ice sheet models (ISMs). The MAR (Modèle Atmosphérique Régional: Fettweis, 2007) climate projections are for 2000–2199, forced by the ECHAM5 and HadCM3 global climate models (GCMs) under the SRES A1B emissions scenario. The additional sea level contribution due to the SMB–elevation feedback averaged over five ISM projections for ECHAM5 and three for HadCM3 is 4.3% (best estimate; 95% credibility interval 1.8–6.9%) at 2100, and 9.6% (best estimate; 95% credibility interval 3.6–16.0%) at 2200. In all results the elevation feedback is significantly positive, amplifying the GrIS sea level contribution relative to the MAR projections in which the ice sheet topography is fixed: the lower bounds of our 95% credibility intervals (CIs) for sea level contributions are larger than the "no feedback" case for all ISMs and GCMs. Our method is novel in sea level projections because we propagate three types of modelling uncertainty – GCM and ISM structural uncertainties, and elevation feedback parameterisation uncertainty – along the causal chain, from SRES scenario to sea level, within a coherent experimental design and statistical framework. The relative contributions to uncertainty depend on the timescale of interest. At 2100, the GCM uncertainty is largest, but by 2200 both the ISM and parameterisation uncertainties are larger. We also perform a perturbed parameter ensemble with one ISM to estimate the shape of the projected sea level probability distribution; our results indicate that the probability density is slightly skewed towards higher sea level contributions.

scholarly journals Calibration and evaluation of a high-resolution surface mass-balance model for Paakitsoq, West Greenland

2012 ◽  
Vol 58 (212) ◽  
pp. 1047-1062 ◽  
Author(s):  
Alison F. Banwell ◽  
Ian C. Willis ◽  
Neil S. Arnold ◽  
Alexandra Messerli ◽  
Cameron J. Rye ◽  
...  
Keyword(s):  
Mass Balance ◽  
Model Performance ◽  
Greenland Ice Sheet ◽  
Balance Model ◽  
Threshold Temperature ◽  
Mass Balance Model ◽  
Surface Mass ◽  
West Greenland ◽  
Landsat 7 ◽  
Normalized Difference Snow Index

AbstractModelling the hydrology of the Greenland ice sheet, including the filling and drainage of supraglacial lakes, requires melt inputs generated at high spatial and temporal resolution. Here we apply a high spatial (100 m) and temporal (1 hour) mass-balance model to a 450 km2 subset of the Paakitsoq region, West Greenland. The model is calibrated by adjusting the values for parameters of fresh snow density, threshold temperature for solid/liquid precipitation and elevation-dependent precipitation gradient to minimize the error between modelled output and surface height and albedo measurements from three Greenland Climate Network stations for the mass-balance years 2000/01 and 2004/05. Bestfit parameter values are consistent between the two years at 400 kg m-3, 2°C and +14% (100 m)-1, respectively. Model performance is evaluated, first, by comparing modelled snow and ice distribution with that derived from Landsat-7 ETM+ satellite imagery using normalized-difference snow index classification and supervised image thresholding; and second, by comparing modelled albedo with that retrieved from the MODIS sensor M0D10A1 product. Calculation of mass-balance components indicates that 6% of surface meltwater and rainwater refreezes in the snowpack and does not become runoff, such that refreezing accounts for 31% of the net accumulation.

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