Internal Modes of Multidecadal Variability in the Arctic Ocean

2010 ◽  
Vol 40 (11) ◽  
pp. 2496-2510 ◽  
Author(s):  
Leela M. Frankcombe ◽  
Henk A. Dijkstra
Keyword(s):  
Arctic Ocean ◽  
Time Scales ◽  
Climate Models ◽  
Climate Model ◽  
Salinity Gradient ◽  
Global Climate Models ◽  
The Arctic ◽  
Recent Analysis ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Intergovernmental Panel

Abstract Observations of sea ice extent and atmospheric temperature in the Arctic, although sparse, indicate variability on multidecadal time scales. A recent analysis of one of the global climate models [the Geophysical Fluid Dynamics Laboratory Climate Model, version 2.1 (CM2.1)] in the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change has indicated that Arctic Ocean variability on these time scales is associated with changes in basin-wide salinity patterns. In this paper the internal modes of variability in an idealized Arctic Basin are determined by considering the stability of salinity-driven flows. An internal ocean mode with a multidecadal time scale is found, with a spatial pattern similar to that obtained in the analysis of the CM2.1 results. The modes propagate as a “saline Rossby wave” induced by the background salinity gradient.

scholarly journals Global Warming Effects on U.S. Hurricane Damage

2011 ◽  
Vol 3 (4) ◽  
pp. 261-268 ◽  
Author(s):  
Kerry Emanuel
Keyword(s):  
Time Series ◽  
Global Warming ◽  
Time Scales ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Models ◽  
Intergovernmental Panel ◽  
Hurricane Damage

Abstract While many studies of the effects of global warming on hurricanes predict an increase in various metrics of Atlantic basin-wide activity, it is less clear that this signal will emerge from background noise in measures of hurricane damage, which depend largely on rare, high-intensity landfalling events and are thus highly volatile compared to basin-wide storm metrics. Using a recently developed hurricane synthesizer driven by large-scale meteorological variables derived from global climate models, 1000 artificial 100-yr time series of Atlantic hurricanes that make landfall along the U.S. Gulf and East Coasts are generated for four climate models and for current climate conditions as well as for the warmer climate of 100 yr hence under the Intergovernmental Panel on Climate Change (IPCC) emissions scenario A1b. These synthetic hurricanes damage a portfolio of insured property according to an aggregate wind-damage function; damage from flooding is not considered here. Assuming that the hurricane climate changes linearly with time, a 1000-member ensemble of time series of property damage was created. Three of the four climate models used produce increasing damage with time, with the global warming signal emerging on time scales of 40, 113, and 170 yr, respectively. It is pointed out, however, that probabilities of damage increase significantly well before such emergence time scales and it is shown that probability density distributions of aggregate damage become appreciably separated from those of the control climate on time scales as short as 25 yr. For the fourth climate model, damages decrease with time, but the signal is weak.

scholarly journals The Surface-Pressure Signature of Atmospheric Tides in Modern Climate Models

2011 ◽  
Vol 68 (3) ◽  
pp. 495-514 ◽  
Author(s):  
Curt Covey ◽  
Aiguo Dai ◽  
Dan Marsh ◽  
Richard S. Lindzen
Keyword(s):  
Surface Pressure ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Models ◽  
Atmospheric Tides ◽  
Intergovernmental Panel ◽  
Near Surface ◽  
Low Altitude ◽  
Upper Boundary

Abstract Although atmospheric tides driven by solar heating are readily detectable at the earth’s surface as variations in air pressure, their simulations in current coupled global climate models have not been fully examined. This work examines near-surface-pressure tides in climate models that contributed to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC); it compares them with tides both from observations and from the Whole Atmosphere Community Climate Model (WACCM), which extends from the earth’s surface to the thermosphere. Surprising consistency is found among observations and all model simulations, despite variation of the altitudes of model upper boundaries from 32 to 76 km in the IPCC models and at 135 km for WACCM. These results are consistent with previous suggestions that placing a model’s upper boundary at low altitude leads to partly compensating errors—such as reducing the forcing of the tides by ozone heating, but also introducing spurious waves at the upper boundary, which propagate to the surface.

scholarly journals Present-Day Arctic Sea Ice Variability in the Coupled ECHAM5/MPI-OM Model

2010 ◽  
Vol 23 (10) ◽  
pp. 2520-2543 ◽  
Author(s):  
Nikolay V. Koldunov ◽  
Detlef Stammer ◽  
Jochem Marotzke
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Ocean Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Heat Content ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Max Planck ◽  
Arctic Sea

Abstract As a contribution to a detailed evaluation of Intergovernmental Panel on Climate Change (IPCC)-type coupled climate models against observations, this study analyzes Arctic sea ice parameters simulated by the Max-Planck-Institute for Meteorology (MPI-M) fully coupled climate model ECHAM5/Max-Planck-Institute for Meteorology Hamburg Primitive Equation Ocean Model (MPI-OM) for the period from 1980 to 1999 and compares them with observations collected during field programs and by satellites. Results of the coupled run forced by twentieth-century CO2 concentrations show significant discrepancies during summer months with respect to observations of the spatial distribution of the ice concentration and ice thickness. Equally important, the coupled run lacks interannual variability in all ice and Arctic Ocean parameters. Causes for such big discrepancies arise from errors in the ECHAM5/MPI-OM atmosphere and associated errors in surface forcing fields (especially wind stress). This includes mean bias pattern caused by an artificial circulation around the geometric North Pole in its atmosphere, as well as insufficient atmospheric variability in the ECHAM5/MPI-OM model, for example, associated with Arctic Oscillation/North Atlantic Oscillation (AO/NAO). In contrast, the identical coupled ocean–ice model, when driven by NCEP–NCAR reanalysis fields, shows much increased skill in its ice and ocean circulation parameters. However, common to both model runs is too strong an ice export through the Fram Strait and a substantially biased heat content in the interior of the Arctic Ocean, both of which may affect sea ice budgets in centennial projections of the Arctic climate system.

scholarly journals Future Arctic marine access: analysis and evaluation of observations, models, and projections of sea ice

2012 ◽  
Vol 6 (5) ◽  
pp. 3963-3998 ◽  
Author(s):  
T. S. Rogers ◽  
J. E. Walsh ◽  
T. S. Rupp ◽  
L. W. Brigham ◽  
M. Sfraga
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Model Performance ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Sea Ice Extent ◽  
State And Local

Abstract. There is an emerging need for regional applications of sea ice projections to provide more accuracy and greater detail to scientists, national, state and local planners, and other stakeholders. The present study offers a prototype for a comprehensive, interdisciplinary study to bridge observational data, climate model simulations, and user needs. The study's first component is an observationally-based evaluation of Arctic sea ice trends during 1980–2008, with an emphasis on seasonal and regional differences relative to the overall pan-Arctic trend. Regional sea ice los has varied, with a significantly larger decline of winter maximum (January–March) extent in the Atlantic region than in other sectors. A lead-lag regression analysis of Atlantic sea ice extent and ocean temperatures indicates that reduced sea ice extent is associated with increased Atlantic Ocean temperatures. Correlations between the two variables are greater when ocean temperatures lag rather than lead sea ice. The performance of 13 global climate models is evaluated using three metrics to compare sea ice simulations with the observed record. We rank models over the pan-Arctic domain and regional quadrants, and synthesize model performance across several different studies. The best performing models project reduced ice cover across key access routes in the Arctic through 2100, with a lengthening of seasons for marine operations by 1–3 months. This assessment suggests that the Northwest and Northeast Passages hold potential for enhanced marine access to the Arctic in the future, including shipping and resource development opportunities.

scholarly journals Connecting Climate Model Projections of Global Temperature Change with the Real World

2016 ◽  
Vol 97 (6) ◽  
pp. 963-980 ◽  
Author(s):  
Ed Hawkins ◽  
Rowan Sutton
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Global Temperature ◽  
Climate Projections ◽  
Reference Period ◽  
Intergovernmental Panel ◽  
Temperature Levels

Abstract Current state-of-the-art global climate models produce different values for Earth’s mean temperature. When comparing simulations with each other and with observations, it is standard practice to compare temperature anomalies with respect to a reference period. It is not always appreciated that the choice of reference period can affect conclusions, both about the skill of simulations of past climate and about the magnitude of expected future changes in climate. For example, observed global temperatures over the past decade are toward the lower end of the range of the phase 5 of the Coupled Model Intercomparison Project (CMIP5) simulations irrespective of what reference period is used, but exactly where they lie in the model distribution varies with the choice of reference period. Additionally, we demonstrate that projections of when particular temperature levels are reached, for example, 2 K above “preindustrial,” change by up to a decade depending on the choice of reference period. In this article, we discuss some of the key issues that arise when using anomalies relative to a reference period to generate climate projections. We highlight that there is no perfect choice of reference period. When evaluating models against observations, a long reference period should generally be used, but how long depends on the quality of the observations available. The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) choice to use a 1986–2005 reference period for future global temperature projections was reasonable, but a case-by-case approach is needed for different purposes and when assessing projections of different climate variables. Finally, we recommend that any studies that involve the use of a reference period should explicitly examine the robustness of the conclusions to alternative choices.

scholarly journals An Assessment of a Model-, Grid-, and Basin-Independent Tropical Cyclone Detection Scheme in Selected CMIP3 Global Climate Models

2013 ◽  
Vol 26 (15) ◽  
pp. 5508-5522 ◽  
Author(s):  
K. J. Tory ◽  
S. S. Chand ◽  
R. A. Dare ◽  
J. L. McBride
Keyword(s):  
Tropical Cyclone ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Max Planck ◽  
Detection Scheme ◽  
Coarse Resolution

Abstract A novel tropical cyclone (TC) detection technique designed for coarse-resolution models is tested and evaluated. The detector, based on the Okubo–Weiss–Zeta parameter (OWZP), is applied to a selection of Coupled Model Intercomparison Project, phase 3 (CMIP3), models [Commonwealth Scientific and Industrial Research Organisation Mark, version 3.5 (CSIRO-Mk3.5); Max Planck Institute ECHAM5 (MPI-ECHAM5); and Geophysical Fluid Dynamics Laboratory Climate Model, versions 2.0 (GFDL CM2.0) and 2.1 (GFDL CM2.1)], and the combined performance of the model and detector is assessed by comparison with observed TC climatology for the period 1970–2000. Preliminary TC frequency projections are made using the three better-performing models by comparing the detected TC climatologies between the late twentieth and late twenty-first centuries. Very reasonable TC formation climatologies were detected in CSIRO-Mk3.5, MPI-ECHAM5, and GFDL CM2.1 for most basins, with the exception of the North Atlantic, where a large underdetection was present in all models. The GFDL CM2.0 model was excluded from the projection study because of a systematic underdetection in all basins. The above detection problems have been reported in other published studies, which suggests model rather than detector limitations are mostly responsible. This study demonstrates that coarse-resolution climate models do in general produce TC-like circulations with realistic geographical and seasonal distributions detectable by the OWZP TC detector. The preliminary projection results are consistent with the published literature, based on higher-resolution studies, of a global reduction of TCs between about 6% and 20%, with a much larger spread of results (about +20% to −50%) in individual basins.

scholarly journals The Eastern Subtropical Pacific Origin of the Equatorial Cold Bias in Climate Models: A Lagrangian Perspective

2017 ◽  
Vol 30 (15) ◽  
pp. 5885-5900 ◽  
Author(s):  
Matthew D. Thomas ◽  
Alexey V. Fedorov
Keyword(s):  
Time Scales ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Vertical Mixing ◽  
Global Climate Models ◽  
Cold Bias ◽  
Equatorial Undercurrent ◽  
Back Trajectories ◽  
Source Regions

Global climate models frequently exhibit cold biases in tropical sea surface temperature (SST) in the central and eastern equatorial Pacific. Here, Lagrangian particle back trajectories are used to investigate the source regions of the water that upwells along the equator in the IPSL climate model to test and confirm the hypothesis that the SST biases are caused by remote biases advected in from the extratropics and to identify the dominant source regions. Water in the model is found to be sourced primarily from localized regions along the western and eastern flanks of the subtropical gyres. However, while the model SST bias is especially large in the northwestern subtropical Pacific (about −5°C), it is found that the eastern subtropics contribute to the equatorial bias the most. This is due to two distinct subsurface pathways connecting these regions to the equator. The first pathway, originating in the northwestern subtropical Pacific, has relatively long advection time scales close to or exceeding 60 yr, wherein particles recirculate around the subtropical gyres while descending to approximately 500 m before then shoaling toward the equatorial undercurrent. The second pathway, from the eastern subtropics, has time scales close to 10 yr, with particles following a shallow and more direct route to the equator within the upper 200 m. The deeper and longer pathway taken by the western subtropical water ensures that vertical mixing can erode the bias. Ultimately, it is estimated that relatively confined regions in the eastern subtropics of both hemispheres control approximately half of the equatorial bias.

scholarly journals Future Arctic marine access: analysis and evaluation of observations, models, and projections of sea ice

2013 ◽  
Vol 7 (1) ◽  
pp. 321-332 ◽  
Author(s):  
T. S. Rogers ◽  
J. E. Walsh ◽  
T. S. Rupp ◽  
L. W. Brigham ◽  
M. Sfraga
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Model Performance ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Sea Ice Extent ◽  
State And Local

Abstract. There is an emerging need for regional applications of sea ice projections to provide more accuracy and greater detail to scientists, national, state and local planners, and other stakeholders. The present study offers a prototype for a comprehensive, interdisciplinary study to bridge observational data, climate model simulations, and user needs. The study's first component is an observationally based evaluation of Arctic sea ice trends during 1980–2008, with an emphasis on seasonal and regional differences relative to the overall pan-Arctic trend. Regional sea ice loss has varied, with a significantly larger decline of winter maximum (January–March) extent in the Atlantic region than in other sectors. A lead–lag regression analysis of Atlantic sea ice extent and ocean temperatures indicates that reduced sea ice extent is associated with increased Atlantic Ocean temperatures. Correlations between the two variables are greater when ocean temperatures lag rather than lead sea ice. The performance of 13 global climate models is evaluated using three metrics to compare sea ice simulations with the observed record. We rank models over the pan-Arctic domain and regional quadrants and synthesize model performance across several different studies. The best performing models project reduced ice cover across key access routes in the Arctic through 2100, with a lengthening of seasons for marine operations by 1–3 months. This assessment suggests that the Northwest and Northeast Passages hold potential for enhanced marine access to the Arctic in the future, including shipping and resource development opportunities.

scholarly journals Observation-based selection of climate models projects Arctic ice-free summers around 2035

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
David Docquier ◽  
Torben Koenigk
Keyword(s):  
Model Selection ◽  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Arctic Sea ◽  
Area And Volume

AbstractArctic sea ice has been retreating at an accelerating pace over the past decades. Model projections show that the Arctic Ocean could be almost ice free in summer by the middle of this century. However, the uncertainties related to these projections are relatively large. Here we use 33 global climate models from the Coupled Model Intercomparison Project 6 (CMIP6) and select models that best capture the observed Arctic sea-ice area and volume and northward ocean heat transport to refine model projections of Arctic sea ice. This model selection leads to lower Arctic sea-ice area and volume relative to the multi-model mean without model selection and summer ice-free conditions could occur as early as around 2035. These results highlight a potential underestimation of future Arctic sea-ice loss when including all CMIP6 models.

scholarly journals Observations and Simulations of Meteorological Conditions over Arctic Thick Sea Ice in Late Winter during the Transarktika 2019 Expedition

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 174
Author(s):  
Günther Heinemann ◽  
Sascha Willmes ◽  
Lukas Schefczyk ◽  
Alexander Makshtas ◽  
Vasilii Kustov ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Open Water ◽  
The Arctic ◽  
Late Winter ◽  
Good Representation ◽  
Hourly Temperature ◽  
Ice Model

The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.

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