scholarly journals Extreme temperature events on Greenland in observations and the MAR regional climate model

2017 ◽  
Author(s):  
Amber A. Leeson ◽  
Emma Eastoe ◽  
Xavier Fettweis
Keyword(s):  
Regional Climate Model ◽  
Sea Level ◽  
Climate Model ◽  
Regional Climate ◽  
Extreme Temperature ◽  
Ice Sheet ◽  
Extreme Value Analysis ◽  
Value Analysis ◽  
Extreme Temperature Events ◽  
Short Period

Abstract. Melt water from the Greenland ice sheet contributed 1.7–6.12 mm to global sea level between 1993 and 2010 and is expected to contribute 20–110 mm to future sea level rise by 2100. These estimates were produced by regional climate models which are known to be robust at the ice-sheet scale, but occasionally miss regional and local scale climate variability. To date, the fidelity of these models in the context of short period variability in time has not been assessed, for example their ability to simulate extreme temperature events. We use an event identification algorithm commonly used in Extreme Value Analysis, together with observations from the GC-Net, to assess the ability of the MAR RCM to reproduce observed extreme temperature events at 14 sites around Greenland. We find that MAR is able to accurately simulate the frequency and duration of these events but underestimates their magnitude by more than half a degree, although this bias is much smaller than that exhibited by coarse-scale Era-Interim reanalysis data. As a corollary, melt energy in MAR output is underestimated by between 16 % and 41 % depending on global forcing applied. Further work is needed to precisely determine the drivers of extreme temperature events, and why the model underperforms in this area, but our findings suggest that biases are passed into MAR from forcing data. This is important because these forcings are common between RCMs and their range of predictions of past and future ice sheet melting. We propose that examining extreme events should become a routine part of global and regional climate model evaluation and addressing shortcomings in this area should be a priority for model development.

scholarly journals Extreme temperature events on Greenland in observations and the MAR regional climate model

2018 ◽  
Vol 12 (3) ◽  
pp. 1091-1102 ◽  
Author(s):  
Amber A. Leeson ◽  
Emma Eastoe ◽  
Xavier Fettweis
Keyword(s):  
Regional Climate Model ◽  
Sea Level ◽  
Climate Model ◽  
Regional Climate ◽  
Extreme Temperature ◽  
Ice Sheet ◽  
Extreme Value Analysis ◽  
Positive Temperature ◽  
Extreme Temperature Events ◽  
Short Period

Abstract. Meltwater from the Greenland Ice Sheet contributed 1.7–6.12 mm to global sea level between 1993 and 2010 and is expected to contribute 20–110 mm to future sea level rise by 2100. These estimates were produced by regional climate models (RCMs) which are known to be robust at the ice sheet scale but occasionally miss regional- and local-scale climate variability (e.g. Leeson et al., 2017; Medley et al., 2013). To date, the fidelity of these models in the context of short-period variability in time (i.e. intra-seasonal) has not been fully assessed, for example their ability to simulate extreme temperature events. We use an event identification algorithm commonly used in extreme value analysis, together with observations from the Greenland Climate Network (GC-Net), to assess the ability of the MAR (Modèle Atmosphérique Régional) RCM to reproduce observed extreme positive-temperature events at 14 sites around Greenland. We find that MAR is able to accurately simulate the frequency and duration of these events but underestimates their magnitude by more than half a degree Celsius/kelvin, although this bias is much smaller than that exhibited by coarse-scale Era-Interim reanalysis data. As a result, melt energy in MAR output is underestimated by between 16 and 41 % depending on global forcing applied. Further work is needed to precisely determine the drivers of extreme temperature events, and why the model underperforms in this area, but our findings suggest that biases are passed into MAR from boundary forcing data. This is important because these forcings are common between RCMs and their range of predictions of past and future ice sheet melting. We propose that examining extreme events should become a routine part of global and regional climate model evaluation and that addressing shortcomings in this area should be a priority for model development.

scholarly journals Sensitivity of Greenland Ice Sheet Projections to Model Formulations

2013 ◽  
Vol 59 (216) ◽  
pp. 733-749 ◽  
Author(s):  
H. Goelzer ◽  
P. Huybrechts ◽  
J.J. Fürst ◽  
F.M. Nick ◽  
M.L. Andersen ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Sea Level ◽  
Flow Model ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Ice Flow ◽  
Outlet Glacier ◽  
Glacier Dynamics

AbstractPhysically based projections of the Greenland ice sheet contribution to future sea-level change are subject to uncertainties of the atmospheric and oceanic climatic forcing and to the formulations within the ice flow model itself. Here a higher-order, three-dimensional thermomechanical ice flow model is used, initialized to the present-day geometry. The forcing comes from a high-resolution regional climate model and from a flowline model applied to four individual marine-terminated glaciers, and results are subsequently extended to the entire ice sheet. The experiments span the next 200 years and consider climate scenario SRES A1B. The surface mass-balance (SMB) scheme is taken either from a regional climate model or from a positive-degree-day (PDD) model using temperature and precipitation anomalies from the underlying climate models. Our model results show that outlet glacier dynamics only account for 6–18% of the sea-level contribution after 200 years, confirming earlier findings that stress the dominant effect of SMB changes. Furthermore, interaction between SMB and ice discharge limits the importance of outlet glacier dynamics with increasing atmospheric forcing. Forcing from the regional climate model produces a 14–31 % higher sea-level contribution compared to a PDD model run with the same parameters as for IPCC AR4.

scholarly journals Probabilistic parameterisation of the surface mass balance–elevation feedback in regional climate model simulations of the Greenland ice sheet

2014 ◽  
Vol 8 (1) ◽  
pp. 181-194 ◽  
Author(s):  
T. L. Edwards ◽  
X. Fettweis ◽  
O. Gagliardini ◽  
F. Gillet-Chaulet ◽  
H. Goelzer ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Mass Balance ◽  
Sea Level ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
The North

Abstract. We present a new parameterisation that relates surface mass balance (SMB: the sum of surface accumulation and surface ablation) to changes in surface elevation of the Greenland ice sheet (GrIS) for the MAR (Modèle Atmosphérique Régional: Fettweis, 2007) regional climate model. The motivation is to dynamically adjust SMB as the GrIS evolves, allowing us to force ice sheet models with SMB simulated by MAR while incorporating the SMB–elevation feedback, without the substantial technical challenges of coupling ice sheet and climate models. This also allows us to assess the effect of elevation feedback uncertainty on the GrIS contribution to sea level, using multiple global climate and ice sheet models, without the need for additional, expensive MAR simulations. We estimate this relationship separately below and above the equilibrium line altitude (ELA, separating negative and positive SMB) and for regions north and south of 77° N, from a set of MAR simulations in which we alter the ice sheet surface elevation. These give four "SMB lapse rates", gradients that relate SMB changes to elevation changes. We assess uncertainties within a Bayesian framework, estimating probability distributions for each gradient from which we present best estimates and credibility intervals (CI) that bound 95% of the probability. Below the ELA our gradient estimates are mostly positive, because SMB usually increases with elevation: 0.56 (95% CI: −0.22 to 1.33) kg m−3 a−1 for the north, and 1.91 (1.03 to 2.61) kg m−3 a−1 for the south. Above the ELA, the gradients are much smaller in magnitude: 0.09 (−0.03 to 0.23) kg m−3 a−1 in the north, and 0.07 (−0.07 to 0.59) kg m−3 a−1 in the south, because SMB can either increase or decrease in response to increased elevation. Our statistically founded approach allows us to make probabilistic assessments for the effect of elevation feedback uncertainty on sea level projections (Edwards et al., 2014).

scholarly journals Regional climate-model performance in Greenland firn derived from in situ observations

1969 ◽  
Vol 35 ◽  
pp. 75-78 ◽  
Author(s):  
Charalampos Charalampidis ◽  
Dirk Van As ◽  
Peter L. Langen ◽  
Robert S. Fausto ◽  
Baptiste Vandecrux ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Model Performance ◽  
Mass Conservation ◽  
Mass Budget ◽  
Run Off ◽  
In Situ Observations

Recent record-warm summers in Greenland (Khan et al. 2015) have started affecting the higher regions of the ice sheet (i.e. the accumulation area), where increased melt has altered the properties of firn (i.e. multi-year snow). At high altitudes, meltwater percolates in the porous snow and firn, where it refreezes. The result is mass conservation, as the refrozen meltwater is essentially stored (Harper et al. 2012). However, in some regions increased meltwater refreezing in shallow firn has created thick ice layers. These ice layers act as a lid, and can inhibit meltwater percolation to greater depths, causing it to run off instead (Machguth et al. 2016). Meltwater at the surface also results in more absorbed sunlight, and hence increased melt in the accumulation area (Charalampidis et al. 2015). These relatively poorly understood processes are important for ice-sheet mass-budget projections.

Improved modelling of the present-day Greenland firn layer

2021 ◽  
Author(s):  
Max Brils ◽  
Peter Kuipers Munneke ◽  
Willem Jan van de Berg ◽  
Achim Heilig ◽  
Baptiste Vandercrux ◽  
...  
Keyword(s):  
Mass Loss ◽  
Sea Level Rise ◽  
Sea Level ◽  
Climate Model ◽  
Pore Space ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Mass ◽  
Meltwater Runoff

<p>Recent studies indicate that a declining surface mass balance will dominate the Greenland Ice Sheet’s (GrIS) contribution to 21<sup>st</sup> century sea level rise. It is therefore crucial to understand the liquid water balance of the ice sheet and its response to increasing temperatures and surface melt if we want to accurately predict future sea level rise. The ice sheet firn layer covers ~90% of the GrIS and provides pore space for storage and refreezing of meltwater. Because of this, the firn layer can retain up to ~45% of the surface meltwater and thus act as an efficient buffer to ice sheet mass loss. However, in a warming climate this buffer capacity of the firn layer is expected to decrease, amplifying meltwater runoff and sea-level rise. Dedicated firn models are used to understand how firn layers evolve and affect runoff. Additionally, firn models are used to estimate the changing thickness of the firn layer, which is necessary in altimetry to convert surface height change into ice sheet mass loss.</p><p>Here, we present the latest version of our firn model IMAU-FDM. With respect to the previous version, changes have been made to the handling of the freshly fallen snow, the densification rate of the firn and the conduction of heat. These changes lead to an improved representation of firn density and temperature. The results have been thoroughly validated using an extensive dataset of density and temperature measurements that we have compiled covering 126 different locations on the GrIS. Meltwater behaviour in the model is validated with upward-looking GPR measurements at Dye-2. Lastly, we present an in-depth look at the evolution firn characteristics at some typical locations in Greenland.</p><p>Dedicated, stand-alone firn models offer various benefits to using a regional climate model with an embedded firn model. Firstly, the vertical resolution for buried snow and ice layers can be larger, improving accuracy. Secondly, a stand-alone firn model allows for spinning up the model to a more accurate equilibrium state. And thirdly, a stand-alone model is more cost- and time-effective to use. Firn models are increasingly capable of simulating the firn layer, but areas with large amounts of melt still pose the greatest challenge.</p>

Sign in / Sign up

Export Citation Format

Share Document