Simulating multi-decadal variability of Caspian Sea level changes using regional climate model outputs

2005 ◽  
Vol 26 (2-3) ◽  
pp. 167-181 ◽  
Author(s):  
N. Elguindi ◽  
F. Giorgi
Keyword(s):  
Regional Climate Model ◽  
Sea Level ◽  
Caspian Sea ◽  
Climate Model ◽  
Decadal Variability ◽  
Regional Climate ◽  
Sea Level Changes

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 DOWNSCALING TROPICAL CYCLONES FROM GLOBAL RE-ANALYSIS AND SCENARIOS: STATISTICS OF MULTI-DECADAL VARIABILITY OF TC ACTIVITY IN E ASIA

2011 ◽  
Vol 1 (32) ◽  
pp. 17 ◽  
Author(s):  
Hans Von Storch ◽  
Frauke Feser ◽  
Monika Barcikowska
Keyword(s):  
Regional Climate Model ◽  
Tropical Cyclones ◽  
Climate Model ◽  
Decadal Variability ◽  
Tracking System ◽  
Regional Climate ◽  
Automated Tracking ◽  
Stationary Intensity ◽  
Environmental Prediction

An atmospheric regional climate model was employed for describing weather of E Asia for the last decades as well as for the coming century. Re-analyses provided by Global National Center for Environmental Prediction - National Center for Atmospheric Research (NCEP-NCAR) for the past six decades, as well a scenario generated by the ECHAM5/MPI-OM model were dynamically downscaled to a 50 km grid using a state-of-the-art regional climate model (CCLM). Using an automated tracking system, all tropical cyclones (TCs) are identified in the multi-decadal simulations. The different analysis products of TC-statistics were found to differ strongly, also in recent times when the data base was good, so that in the long-term statistics 1950-2010 inhomogeneities mask real climatic variations. The 1948-2009 time series of the annual numbers of TCs in the NCEP-driven simulation and in the JMA best track data (BT) correlate favourably. The number is almost constant, even if there is a slight tendency in BT to show less storms, whereas CCLM shows somewhat more storms, which became more intense. The ECHAM5/MPI-OM-driven scenario simulation, subject to 1959-2100 observed and projected greenhouse gas concentrations, shows a reduction of the number of storms, which maintains a stationary intensity in terms of maximum sustained winds and minimum pressure. Thus, BT-trends and downscaled trends were found to be inconsistent, but also the downscaled trends 1948-2009 and the trends derived from the A1B-scenario were different.

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 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 Caspian Sea south coast future climate change estimations through regional climate model

2019 ◽  
Vol 6 (1) ◽  
pp. 111-138
Author(s):  
Fardin Saberi Louyeh ◽  
Bohlol Alijani ◽  
Shahriar Khaledi ◽  
◽  
◽  
...  
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Caspian Sea ◽  
Climate Model ◽  
Regional Climate ◽  
Future Climate ◽  
South Coast ◽  
Future Climate Change

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.

Sign in / Sign up

Export Citation Format

Share Document