scholarly journals CMIP5 temperature biases and 21st century warming around the Antarctic coast

2016 ◽  
Vol 57 (73) ◽  
pp. 69-78 ◽  
Author(s):  
Christopher M. Little ◽  
Nathan M. Urban
Keyword(s):  
Mass Balance ◽  
21St Century ◽  
General Circulation ◽  
Large Scale ◽  
Ice Sheet ◽  
Coupled Model ◽  
General Circulation Models ◽  
Ensemble Mean ◽  
Rcp 8.5 ◽  
Ice Sheet Mass Balance

ABSTRACTProjections of ice-sheet mass balance require regional ocean warming projections derived from atmosphere-ocean general circulation models (AOGCMs). However, the coarse resolution of AOGCMs: (1) may lead to systematic or AOGCM-specific biases and (2) makes it difficult to identify relevant water masses. Here, we employ a large-scale metric of Antarctic Shelf Bottom Water (ASBW) to investigate circum-Antarctic temperature biases and warming projections in 19 different Coupled Model Intercomparison Project Phase 5 (CMIP5) AOGCMs forced with two different ‘representative concentration pathways’ (RCPs). For high-emissions RCP 8.5, the ensemble mean 21st century ASBW warming is 0.66, 0.74 and 0.58°C for the Amundsen, Ross and Weddell Seas (AS, RS and WS), respectively. RCP 2.6 ensemble mean projections are substantially lower: 0.21, 0.26, and 0.19°C. All distributions of regional ASBW warming are positively skewed; for RCP 8.5, four AOGCMs project warming of greater than 1.8°C in the RS. Across the ensemble, there is a strong, RCP-independent, correlation between WS and RS warming. AS warming is more closely linked to warming in the Southern Ocean. We discuss possible physical mechanisms underlying the spatial patterns of warming and highlight implications of these results on strategies for forcing ice-sheet mass balance projections.

scholarly journals Estimation of the Greenland ice sheet surface mass balance for the 20th and 21st centuries

2008 ◽  
Vol 2 (2) ◽  
pp. 117-129 ◽  
Author(s):  
X. Fettweis ◽  
E. Hanna ◽  
H. Gallée ◽  
P. Huybrechts ◽  
M. Erpicum
Keyword(s):  
Mass Balance ◽  
Multiple Regression ◽  
21St Century ◽  
General Circulation ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
General Circulation Models ◽  
Climate Simulation ◽  
Surface Mass Balance ◽  
Surface Mass

Abstract. Results from a regional climate simulation (1970–2006) over the Greenland ice sheet (GrIS) reveals that more than 97% of the interannual variability of the modelled Surface Mass Balance (SMB) can be explained by the GrIS summer temperature anomaly and the GrIS annual precipitation anomaly. This multiple regression is then used to empirically estimate the GrIS SMB since 1900 from climatological time series. The projected SMB changes in the 21st century are investigated with the set of simulations performed with atmosphere-ocean general circulation models (AOGCMs) of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). These estimates show that the high surface mass loss rates of recent years are not unprecedented in the GrIS history of the last hundred years. The minimum SMB rate seems to have occurred earlier in the 1930s and corresponds to a zero SMB rate. The AOGCMs project that the SMB rate of the 1930s would be common at the end of 2100. The temperature would be higher than in the 1930s but the increase of accumulation in the 21st century would partly offset the acceleration of surface melt due to the temperature increase. However, these assumptions are based on an empirical multiple regression only validated for recent/current climatic conditions, and the accuracy and time homogeneity of the data sets and AOGCM results used in these estimations constitute a large uncertainty.

scholarly journals Estimation of the Greenland ice sheet surface mass balance during 20th and 21st centuries

2008 ◽  
Vol 2 (2) ◽  
pp. 225-254 ◽  
Author(s):  
X. Fettweis ◽  
E. Hanna ◽  
H. Gallée ◽  
P. Huybrechts ◽  
M. Erpicum
Keyword(s):  
Mass Balance ◽  
Multiple Regression ◽  
21St Century ◽  
General Circulation ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
General Circulation Models ◽  
Climate Simulation ◽  
Surface Mass Balance ◽  
Surface Mass

Abstract. Results from a regional climate simulation (1970–2006) over the Greenland ice sheet (GrIS) reveals that more than 97% of the interannual variability of the modelled Surface Mass Balance (SMB) can be explained by the GrIS summer temperature anomaly and the GrIS annual precipitation anomaly. This multiple regression is then used to empirically estimate the GrIS SMB since 1900 from climatological time series. The projected SMB changes in the 21st century are investigated with the set of simulations performed with atmosphere-ocean general circulation models (AOGCMs) of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). These estimates show that the high surface mass loss rates of recent years are not unprecedented in the GrIS history of the last hundred years. The minimum SMB rate seems to have occurred earlier in the 1930s. The AOGCMs project that the SMB rate of the 1930s would be common at the end of 2100. The temperature would be higher than in the 1930s but the increase of accumulation in the 21st century would partly offset the acceleration of surface melt due to the temperature increase. However, these assumptions are based on an empirical multiple regression only validated for recent/current climatic conditions, and the accuracy and time homogeneity of the data sets and AOGCM results used in these estimations constitute a large uncertainty.

scholarly journals 21st century ocean forcing of the Greenland Ice Sheet for modeling of sea level contribution

2019 ◽  
Author(s):  
Donald A. Slater ◽  
Denis Felikson ◽  
Fiamma Straneo ◽  
Heiko Goelzer ◽  
Christopher M. Little ◽  
...  
Keyword(s):  
Sea Level ◽  
21St Century ◽  
General Circulation ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
General Circulation Models ◽  
Glacier Retreat ◽  
Small Scale ◽  
Intergovernmental Panel ◽  
Continental Scale

Abstract. Changes in the ocean are expected to be an important determinant of the Greenland Ice Sheet's future sea level contribution. Yet representing these changes in continental-scale ice sheet models remains challenging due to the small scale of the key physics, and limitations in processing understanding. Here we present the ocean forcing strategy for Greenland Ice Sheet models taking part in the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6), the primary community effort to provide 21st century sea level projections for the Intergovernmental Panel on Climate Change 6th Assessment Report. Beginning from global atmosphere-ocean general circulation models, we describe two complementary approaches to provide ocean boundary conditions for Greenland Ice Sheet models, termed the retreat and submarine melt implementations. The retreat implementation parameterizes glacier retreat as a function of projected submarine melting, is designed to be implementable by all ice sheet models, and results in retreat of around 1 and 15 km by 2100 in RCP2.6 and 8.5 scenarios respectively. The submarine melt implementation provides estimated submarine melting only, leaving the ice sheet model to solve for the resulting calving and glacier retreat, and suggests submarine melt rates will change little under RCP2.6 but will approximately triple by 2100 under RCP8.5. Both implementations have necessarily made use of simplifying assumptions and poorly-constrained parameterisations and as such, further research on submarine melting, calving and fjord-shelf exchange should remain a priority. Nevertheless, the presented framework will allow an ensemble of Greenland Ice Sheet models to be systematically and consistently forced by the ocean for the first time, and should therefore result in a significant improvement in projections of the Greenland ice sheet's contribution to future sea level change.

scholarly journals Evaluation of a unique approach to high-resolution climate modeling using the Model for Prediction Across Scales – Atmosphere (MPAS-A) version 5.1

2019 ◽  
Vol 12 (8) ◽  
pp. 3725-3743 ◽  
Author(s):  
Allison C. Michaelis ◽  
Gary M. Lackmann ◽  
Walter A. Robinson
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Sea Ice ◽  
Northern Hemisphere ◽  
General Circulation ◽  
Large Scale ◽  
Southern Oscillation ◽  
Spatial Scales ◽  
Coupled Model ◽  
General Circulation Models

Abstract. We present multi-seasonal simulations representative of present-day and future environments using the global Model for Prediction Across Scales – Atmosphere (MPAS-A) version 5.1 with high resolution (15 km) throughout the Northern Hemisphere. We select 10 simulation years with varying phases of El Niño–Southern Oscillation (ENSO) and integrate each for 14.5 months. We use analyzed sea surface temperature (SST) patterns for present-day simulations. For the future climate simulations, we alter present-day SSTs by applying monthly-averaged temperature changes derived from a 20-member ensemble of Coupled Model Intercomparison Project phase 5 (CMIP5) general circulation models (GCMs) following the Representative Concentration Pathway (RCP) 8.5 emissions scenario. Daily sea ice fields, obtained from the monthly-averaged CMIP5 ensemble mean sea ice, are used for present-day and future simulations. The present-day simulations provide a reasonable reproduction of large-scale atmospheric features in the Northern Hemisphere such as the wintertime midlatitude storm tracks, upper-tropospheric jets, and maritime sea-level pressure features as well as annual precipitation patterns across the tropics. The simulations also adequately represent tropical cyclone (TC) characteristics such as strength, spatial distribution, and seasonal cycles for most Northern Hemisphere basins. These results demonstrate the applicability of these model simulations for future studies examining climate change effects on various Northern Hemisphere phenomena, and, more generally, the utility of MPAS-A for studying climate change at spatial scales generally unachievable in GCMs.

scholarly journals Seasonal Forecasts of Canadian Winter Precipitation by Postprocessing GCM Integrations

2008 ◽  
Vol 136 (3) ◽  
pp. 769-783 ◽  
Author(s):  
Hai Lin ◽  
Gilbert Brunet ◽  
Jacques Derome
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
General Circulation Models ◽  
Winter Precipitation ◽  
Second Phase ◽  
Seasonal Forecasts ◽  
Large Area ◽  
Ensemble Forecasts ◽  
The North ◽  
Ensemble Mean

Abstract In the second phase of the Canadian Historical Forecasting Project (HFP2), four global atmospheric general circulation models (GCMs) were used to perform seasonal forecasts over the period of 1969–2003. Little predictive skill was found from the uncalibrated GCM ensemble seasonal predictions for the Canadian winter precipitation. This study is an effort to improve the precipitation forecasts through a postprocessing approach. Canadian winter precipitation is significantly influenced by two of the most important atmospheric large-scale patterns: the Pacific–North American pattern (PNA) and the North Atlantic Oscillation (NAO). The time variations of these two patterns were found to be significantly correlated with those of the leading singular value decomposition (SVD) modes that relate the ensemble mean forecast 500-mb geopotential height over the Northern Hemisphere and the tropical Pacific SST in the previous month (November). A statistical approach to correct the ensemble forecasts was formulated based on the regression of the model’s leading forced SVD patterns and the observed seasonal mean precipitation. The performance of the corrected forecasts was assessed by comparing its cross-validated skill with that of the original GCM ensemble mean forecasts. The results show that the corrected forecasts predict the Canadian winter precipitation with statistically significant skill over the southern prairies and a large area of Québec–Ontario.

scholarly journals Evaluation of Historical CMIP5 GCM Simulation Results Based on Detected Atmospheric Teleconnections

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 723 ◽  
Author(s):  
Erzsébet Kristóf ◽  
Zoltán Barcza ◽  
Roland Hollós ◽  
Judit Bartholy ◽  
Rita Pongrácz
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Evaluation Method ◽  
Polynomial Regression ◽  
Diversity Index ◽  
Regional Climate ◽  
Coupled Model ◽  
General Circulation Models ◽  
Teleconnection Patterns ◽  
Atmospheric Teleconnections

Atmospheric teleconnections are characteristic to the climate system and exert major impacts on the global and regional climate. Accurate representation of teleconnections by general circulation models (GCMs) is indispensable given their fundamental role in the large scale circulation patterns. In this study a statistical method is introduced to evaluate historical GCM outputs of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) with respect to teleconnection patterns. The introduced method is based on the calculation of correlations between gridded time series of the 500 hPa geopotential height fields in the Northern Hemisphere. GCMs are quantified by a simple diversity index. Additionally, potential action centers of the teleconnection patterns are identified on which the local polynomial regression model is fitted. Diversity fields and regression curves obtained from the GCMs are compared against the NCEP/NCAR Reanalysis 1 and the ERA-20C reanalysis datasets. The introduced method is objective, reproducible, and reduces the number of arbitrary decisions during the analysis. We conclude that major teleconnection patterns are positioned in the GCMs and in the reanalysis datasets similarly, however, spatial differences in their intensities can be severe in some cases that could hamper the applicability of the GCM results for some regions. Based on the evaluation method, best-performing GCMs can be clearly distinguished. Evaluation of the GCMs based on the introduced method might help the modeling community to choose GCMs that are the most applicable for impact studies and for regional downscaling exercises.

Twenty-First-Century Snowfall and Snowpack Changes over the Southern California Mountains

2015 ◽  
Vol 29 (1) ◽  
pp. 91-110 ◽  
Author(s):  
Fengpeng Sun ◽  
Alex Hall ◽  
Marla Schwartz ◽  
Daniel B. Walton ◽  
Neil Berg
Keyword(s):  
General Circulation ◽  
Southern California ◽  
Snow Water Equivalent ◽  
Coupled Model ◽  
General Circulation Models ◽  
First Century ◽  
Climate Projections ◽  
Rcp Scenarios ◽  
Ensemble Mean ◽  
Twenty First Century

Abstract Future snowfall and snowpack changes over the mountains of Southern California are projected using a new hybrid dynamical–statistical framework. Output from all general circulation models (GCMs) in phase 5 of the Coupled Model Intercomparison Project archive is downscaled to 2-km resolution over the region. Variables pertaining to snow are analyzed for the middle (2041–60) and end (2081–2100) of the twenty-first century under two representative concentration pathway (RCP) scenarios: RCP8.5 (business as usual) and RCP2.6 (mitigation). These four sets of projections are compared with a baseline reconstruction of climate from 1981 to 2000. For both future time slices and scenarios, ensemble-mean total winter snowfall loss is widespread. By the mid-twenty-first century under RCP8.5, ensemble-mean winter snowfall is about 70% of baseline, whereas the corresponding value for RCP2.6 is somewhat higher (about 80% of baseline). By the end of the century, however, the two scenarios diverge significantly. Under RCP8.5, snowfall sees a dramatic further decline; 2081–2100 totals are only about half of baseline totals. Under RCP2.6, only a negligible further reduction from midcentury snowfall totals is seen. Because of the spread in the GCM climate projections, these figures are all associated with large intermodel uncertainty. Snowpack on the ground, as represented by 1 April snow water equivalent is also assessed. Because of enhanced snowmelt, the loss seen in snowpack is generally 50% greater than that seen in winter snowfall. By midcentury under RCP8.5, warming-accelerated spring snowmelt leads to snow-free dates that are about 1–3 weeks earlier than in the baseline period.

scholarly journals Unprecedented 21st century drought risk in the American Southwest and Central Plains

2015 ◽  
Vol 1 (1) ◽  
pp. e1400082 ◽  
Author(s):  
Benjamin I. Cook ◽  
Toby R. Ault ◽  
Jason E. Smerdon
Keyword(s):  
21St Century ◽  
General Circulation ◽  
General Circulation Models ◽  
American Southwest ◽  
Drought Severity ◽  
Historical Event ◽  
Drought Risk ◽  
Central Plains ◽  
Emissions Scenarios ◽  
Rcp 8.5

In the Southwest and Central Plains of Western North America, climate change is expected to increase drought severity in the coming decades. These regions nevertheless experienced extended Medieval-era droughts that were more persistent than any historical event, providing crucial targets in the paleoclimate record for benchmarking the severity of future drought risks. We use an empirical drought reconstruction and three soil moisture metrics from 17 state-of-the-art general circulation models to show that these models project significantly drier conditions in the later half of the 21st century compared to the 20th century and earlier paleoclimatic intervals. This desiccation is consistent across most of the models and moisture balance variables, indicating a coherent and robust drying response to warming despite the diversity of models and metrics analyzed. Notably, future drought risk will likely exceed even the driest centuries of the Medieval Climate Anomaly (1100–1300 CE) in both moderate (RCP 4.5) and high (RCP 8.5) future emissions scenarios, leading to unprecedented drought conditions during the last millennium.

scholarly journals Deglacial evolution of regional Antarctic climate and Southern Ocean conditions in transient climate simulations

2019 ◽  
Vol 15 (1) ◽  
pp. 189-215 ◽  
Author(s):  
Daniel P. Lowry ◽  
Nicholas R. Golledge ◽  
Laurie Menviel ◽  
Nancy A. N. Bertler
Keyword(s):  
Mass Balance ◽  
Ocean Circulation ◽  
Large Scale ◽  
Ice Sheet ◽  
Surface Air Temperature ◽  
Temporal Analysis ◽  
Time Interval ◽  
Climate Simulations ◽  
Climate Evolution ◽  
Ice Sheet Mass Balance

Abstract. Constraining Antarctica's climate evolution since the end of the Last Glacial Maximum (∼18 ka) remains a key challenge, but is important for accurately projecting future changes in Antarctic ice sheet mass balance. Here we perform a spatial and temporal analysis of two transient deglacial climate simulations, one using a fully coupled GCM (TraCE-21ka) and one using an intermediate complexity model (LOVECLIM DGns), to determine regional differences in deglacial climate evolution and identify the main strengths and limitations of the models in terms of climate variables that impact ice sheet mass balance. The greatest continental surface warming is observed over the continental margins in both models, with strong correlations between surface albedo, sea ice coverage, and surface air temperature along the coasts, as well as regions with the greatest decrease in ice surface elevation in TraCE-21ka. Accumulation–temperature scaling relationships are fairly linear and constant in the continental interior, but exhibit higher variability in the early to mid-Holocene over coastal regions. Circum-Antarctic coastal ocean temperatures at grounding line depths are highly sensitive to the meltwater forcings prescribed in each simulation, which are applied in different ways due to limited paleo-constraints. Meltwater forcing associated with the Meltwater Pulse 1A (MWP1A) event results in subsurface warming that is most pronounced in the Amundsen and Bellingshausen Sea sector in both models. Although modelled centennial-scale rates of temperature and accumulation change are reasonable, clear model–proxy mismatches are observed with regard to the timing and duration of the Antarctic Cold Reversal (ACR) and Younger Dryas–early Holocene warming, which may suggest model bias in large-scale ocean circulation, biases in temperature reconstructions from proxy records, or that the MWP1A and 1B events are inadequately represented in these simulations. The incorporation of dynamic ice sheet models in future transient climate simulations could aid in improving meltwater forcing representation, and thus model–proxy agreement, through this time interval.

scholarly journals Quantifying Uncertainty in the Modelling Process; Future Extreme Flood Event Projections Across the UK

Geosciences ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 33
Author(s):  
Cameron Ellis ◽  
Annie Visser-Quinn ◽  
Gordon Aitken ◽  
Lindsay Beevers
Keyword(s):  
General Circulation ◽  
Coupled Model ◽  
General Circulation Models ◽  
Extreme Value ◽  
Extreme Flood ◽  
Emissions Scenarios ◽  
Rcp 8.5 ◽  
Intercomparison Project ◽  
The Uk ◽  
Model Chain

With evidence suggesting that climate change is resulting in changes within the hydrologic cycle, the ability to robustly model hydroclimatic response is critical. This paper assesses how extreme runoff—1:2- and 1:30-year return period (RP) events—may change at a regional level across the UK by the 2080s (2069–2098). Capturing uncertainty in the hydroclimatic modelling chain, flow projections were extracted from the EDgE (End-to-end Demonstrator for improved decision-making in the water sector in Europe) multi-model ensemble: five Coupled Model Intercomparison Project (CMIP5) General Circulation Models and four hydrological models forced under emissions scenarios Representative Concentration Pathway (RCP) 2.6 and RCP 8.5 (5 × 4 × 2 chains). Uncertainty in extreme value parameterisation was captured through consideration of two methods: generalised extreme value (GEV) and generalised logistic (GL). The method was applied across 192 catchments and aggregated to eight regions. The results suggest that, by the 2080s, many regions could experience large increases in extreme runoff, with a maximum mean change signal of +34% exhibited in East Scotland (1:2-year RP). Combined with increasing urbanisation, these estimates paint a concerning picture for the future UK flood landscape. Model chain uncertainty was found to increase by the 2080s, though extreme value (EV) parameter uncertainty becomes dominant at the 1:30-year RP (exceeding 60% in some regions), highlighting the importance of capturing both the associated EV parameter and ensemble uncertainty.

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