Trends in the CERES Dataset, 2000–13: The Effects of Sea Ice and Jet Shifts and Comparison to Climate Models

2014 ◽  
Vol 27 (6) ◽  
pp. 2444-2456 ◽  
Author(s):  
Dennis L. Hartmann ◽  
Paulo Ceppi
Keyword(s):  
Southern Ocean ◽  
Sea Ice ◽  
Climate Models ◽  
Radiant Energy ◽  
Shortwave Radiation ◽  
Radiative Energy ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Sea Ice Extent ◽  
Intercomparison Project

Abstract The Clouds and the Earth’s Radiant Energy System (CERES) observations of global top-of-atmosphere radiative energy fluxes for the period March 2000–February 2013 are examined for robust trends and variability. The trend in Arctic ice is clearly evident in the time series of reflected shortwave radiation, which closely follows the record of ice extent. The data indicate that, for every 106 km2 decrease in September sea ice extent, annual-mean absorbed solar radiation averaged over 75°–90°N increases by 2.5 W m−2, or about 6 W m−2 between 2000 and 2012. CMIP5 models generally show a much smaller change in sea ice extent over the 1970–2012 period, but the relationship of sea ice extent to reflected shortwave is in good agreement with recent observations. Another robust trend during this period is an increase in reflected shortwave radiation in the zonal belt from 45° to 65°S. This trend is mostly related to increases in sea ice concentrations in the Southern Ocean and less directly related to cloudiness trends associated with the annular variability of the Southern Hemisphere. Models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) produce a scaling of cloud reflection to zonal wind increase that is similar to trend observations in regions separated from the direct effects of sea ice. Atmospheric Model Intercomparison Project (AMIP) model responses over the Southern Ocean are not consistent with each other or with the observed shortwave trends in regions removed from the direct effect of sea ice.

scholarly journals How does internal variability influence the ability of CMIP5 models to reproduce the recent trend in Southern Ocean sea ice extent?

2012 ◽  
Vol 6 (5) ◽  
pp. 3539-3573 ◽  
Author(s):  
V. Zunz ◽  
H. Goosse ◽  
F. Massonnet
Keyword(s):  
Southern Ocean ◽  
Sea Ice ◽  
Climate Models ◽  
Internal Variability ◽  
Cmip5 Models ◽  
Positive Trend ◽  
External Forcing ◽  
Sea Ice Extent ◽  
The One ◽  
The Impact

Abstract. Observations over the last 30 yr have shown that the sea ice extent in the Southern Ocean has slightly increased since 1979. Mechanisms responsible for this positive trend have not been well established yet and climate models are generally unable to simulate correctly this expansion. In this study, we focus on two related hypotheses that could explain the misrepresentation of the positive trend in sea ice extent by climate models: an unrealistic internal variability and an inadequate initialization of the system. For that purpose, we analyze the evolution of sea ice around the Antarctic simulated by 24 different general circulation models involved in the 5th Coupled Model Intercomparison Project (CMIP5). On the one hand, historical simulations, driven by external forcing and initialized without observations, are examined. They provide information about the mean state, the variability and the trend in sea ice extent simulated by each model. On the other hand, decadal prediction experiments, driven by external forcing and initialized with some observed fields, allow us to assess the impact of the representation of the observed initial state on the quality of model predictions. Our analyses show that CMIP5 models respond to the forcing, including the one induced by stratospheric ozone depletion, by reducing the sea ice cover in the Southern Ocean. Some simulations display an increase in sea ice extent. However, models strongly overestimate the variability of sea ice extent and the initialization methods currently used in models do not improve systematically the simulated trends in sea ice extent. On the basis of those results, a critical role of the internal variability in the observed increase in the sea ice extent in the Southern Ocean could not be ruled out but current models results appear inadequate to test more precisely this hypothesis.

scholarly journals An Initial Assessment of Antarctic Sea Ice Extent in the CMIP5 Models

2013 ◽  
Vol 26 (5) ◽  
pp. 1473-1484 ◽  
Author(s):  
John Turner ◽  
Thomas J. Bracegirdle ◽  
Tony Phillips ◽  
Gareth J. Marshall ◽  
J. Scott Hosking
Keyword(s):  
Sea Ice ◽  
Coupled Model ◽  
Initial Assessment ◽  
Cmip5 Models ◽  
Full Time ◽  
Model Intercomparison ◽  
Sea Ice Extent ◽  
Antarctic Sea Ice ◽  
Intercomparison Project ◽  
The Mean

Abstract This paper examines the annual cycle and trends in Antarctic sea ice extent (SIE) for 18 models used in phase 5 of the Coupled Model Intercomparison Project (CMIP5) that were run with historical forcing for the 1850s to 2005. Many of the models have an annual SIE cycle that differs markedly from that observed over the last 30 years. The majority of models have too small of an SIE at the minimum in February, while several of the models have less than two-thirds of the observed SIE at the September maximum. In contrast to the satellite data, which exhibit a slight increase in SIE, the mean SIE of the models over 1979–2005 shows a decrease in each month, with the greatest multimodel mean percentage monthly decline of 13.6% decade−1 in February and the greatest absolute loss of ice of −0.40 × 106 km2 decade−1 in September. The models have very large differences in SIE over 1860–2005. Most of the control runs have statistically significant trends in SIE over their full time span, and all of the models have a negative trend in SIE since the mid-nineteenth century. The negative SIE trends in most of the model runs over 1979–2005 are a continuation of an earlier decline, suggesting that the processes responsible for the observed increase over the last 30 years are not being simulated correctly.

scholarly journals Recent changes in Antarctic Sea Ice

2015 ◽  
Vol 373 (2045) ◽  
pp. 20140163 ◽  
Author(s):  
John Turner ◽  
J. Scott Hosking ◽  
Thomas J. Bracegirdle ◽  
Gareth J. Marshall ◽  
Tony Phillips
Keyword(s):  
Southern Ocean ◽  
Sea Ice ◽  
Climate Models ◽  
Surface Wind ◽  
The Arctic ◽  
Cmip5 Models ◽  
Intrinsic Variability ◽  
Sea Ice Extent ◽  
Amundsen Sea ◽  
Near Surface

In contrast to the Arctic, total sea ice extent (SIE) across the Southern Ocean has increased since the late 1970s, with the annual mean increasing at a rate of 186×10 3  km 2 per decade (1.5% per decade; p <0.01) for 1979–2013. However, this overall increase masks larger regional variations, most notably an increase (decrease) over the Ross (Amundsen–Bellingshausen) Sea. Sea ice variability results from changes in atmospheric and oceanic conditions, although the former is thought to be more significant, since there is a high correlation between anomalies in the ice concentration and the near-surface wind field. The Southern Ocean SIE trend is dominated by the increase in the Ross Sea sector, where the SIE is significantly correlated with the depth of the Amundsen Sea Low (ASL), which has deepened since 1979. The depth of the ASL is influenced by a number of external factors, including tropical sea surface temperatures, but the low also has a large locally driven intrinsic variability, suggesting that SIE in these areas is especially variable. Many of the current generation of coupled climate models have difficulty in simulating sea ice. However, output from the better-performing IPCC CMIP5 models suggests that the recent increase in Antarctic SIE may be within the bounds of intrinsic/internal variability.

scholarly journals The Southern Ocean in the Coupled Model Intercomparison Project phase 5

2014 ◽  
Vol 372 (2019) ◽  
pp. 20130296 ◽  
Author(s):  
A. J. S. Meijers
Keyword(s):  
Southern Ocean ◽  
Sea Ice ◽  
Atmospheric Chemistry ◽  
Global Climate ◽  
Coupled Model ◽  
Current Strength ◽  
Model Intercomparison ◽  
Sea Ice Extent ◽  
Intercomparison Project ◽  
Wind Sea

The Southern Ocean is an important part of the global climate system, but its complex coupled nature makes both its present state and its response to projected future climate forcing difficult to model. Clear trends in wind, sea-ice extent and ocean properties emerged from multi-model intercomparison in the Coupled Model Intercomparison Project phase 3 (CMIP3). Here, we review recent analyses of the historical and projected wind, sea ice, circulation and bulk properties of the Southern Ocean in the updated Coupled Model Intercomparison Project phase 5 (CMIP5) ensemble. Improvements to the models include higher resolutions, more complex and better-tuned parametrizations of ocean mixing, and improved biogeochemical cycles and atmospheric chemistry. CMIP5 largely reproduces the findings of CMIP3, but with smaller inter-model spreads and biases. By the end of the twenty-first century, mid-latitude wind stresses increase and shift polewards. All water masses warm, and intermediate waters freshen, while bottom waters increase in salinity. Surface mixed layers shallow, warm and freshen, whereas sea ice decreases. The upper overturning circulation intensifies, whereas bottom water formation is reduced. Significant disagreement exists between models for the response of the Antarctic Circumpolar Current strength, for reasons that are as yet unclear.

scholarly journals The Transpose-AMIP II Experiment and Its Application to the Understanding of Southern Ocean Cloud Biases in Climate Models

2013 ◽  
Vol 26 (10) ◽  
pp. 3258-3274 ◽  
Author(s):  
K. D. Williams ◽  
A. Bodas-Salcedo ◽  
M. Déqué ◽  
S. Fermepin ◽  
B. Medeiros ◽  
...  
Keyword(s):  
Southern Ocean ◽  
Large Scale ◽  
Climate Models ◽  
Layer Structure ◽  
Coupled Model ◽  
Weather Forecast ◽  
Atmospheric Model ◽  
Shortwave Radiation ◽  
Model Intercomparison ◽  
Intercomparison Project

Abstract The Transpose-Atmospheric Model Intercomparison Project (AMIP) is an international model intercomparison project in which climate models are run in “weather forecast mode.” The Transpose-AMIP II experiment is run alongside phase 5 of the Coupled Model Intercomparison Project (CMIP5) and allows processes operating in climate models to be evaluated, and the origin of climatological biases to be explored, by examining the evolution of the model from a state in which the large-scale dynamics, temperature, and humidity structures are constrained through use of common analyses. The Transpose-AMIP II experimental design is presented. The project requests participants to submit a comprehensive set of diagnostics to enable detailed investigation of the models to be performed. An example of the type of analysis that may be undertaken using these diagnostics is illustrated through a study of the development of cloud biases over the Southern Ocean, a region that is problematic for many models. Several models share a climatological bias for too little reflected shortwave radiation from cloud across the region. This is found to mainly occur behind cold fronts and/or on the leading side of transient ridges and to be associated with more stable lower-tropospheric profiles. Investigation of a case study that is typical of the bias and associated meteorological conditions reveals the models to typically simulate cloud that is too optically and physically thin with an inversion that is too low. The evolution of the models within the first few hours suggests that these conditions are particularly sensitive and a positive feedback can develop between the thinning of the cloud layer and boundary layer structure.

scholarly journals Assessment of sea ice simulations in the CMIP5 models

2015 ◽  
Vol 9 (1) ◽  
pp. 399-409 ◽  
Author(s):  
Q. Shu ◽  
Z. Song ◽  
F. Qiao
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Linear Trend ◽  
Ocean Modeling ◽  
The Arctic ◽  
Cmip5 Models ◽  
Output Data ◽  
Sea Ice Extent ◽  
The Antarctic ◽  
Assimilation System

Abstract. The historical simulations of sea ice during 1979 to 2005 by the Coupled Model Intercomparison Project Phase 5 (CMIP5) are compared with satellite observations, Global Ice-Ocean Modeling and Assimilation System (GIOMAS) output data and Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) output data in this study. Forty-nine models, almost all of the CMIP5 climate models and earth system models with historical simulation, are used. For the Antarctic, multi-model ensemble mean (MME) results can give good climatology of sea ice extent (SIE), but the linear trend is incorrect. The linear trend of satellite-observed Antarctic SIE is 1.29 (±0.57) × 105 km2 decade−1; only about 1/7 CMIP5 models show increasing trends, and the linear trend of CMIP5 MME is negative with the value of −3.36 (±0.15) × 105 km2 decade−1. For the Arctic, both climatology and linear trend are better reproduced. Sea ice volume (SIV) is also evaluated in this study, and this is a first attempt to evaluate the SIV in all CMIP5 models. Compared with the GIOMAS and PIOMAS data, the SIV values in both the Antarctic and the Arctic are too small, especially for the Antarctic in spring and winter. The GIOMAS Antarctic SIV in September is 19.1 × 103 km3, while the corresponding Antarctic SIV of CMIP5 MME is 13.0 × 103 km3 (almost 32% less). The Arctic SIV of CMIP5 in April is 27.1 × 103 km3, which is also less than that from PIOMAS SIV (29.5 × 103 km3). This means that the sea ice thickness simulated in CMIP5 is too thin, although the SIE is fairly well simulated.

scholarly journals Effective radiative forcing and adjustments in CMIP6 models

2020 ◽  
Vol 20 (16) ◽  
pp. 9591-9618 ◽  
Author(s):  
Christopher J. Smith ◽  
Ryan J. Kramer ◽  
Gunnar Myhre ◽  
Kari Alterskjær ◽  
William Collins ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Climate Models ◽  
Coupled Model ◽  
Internal Variability ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Aerosol Forcing ◽  
Intercomparison Project ◽  
Effective Radiative Forcing

Abstract. The effective radiative forcing, which includes the instantaneous forcing plus adjustments from the atmosphere and surface, has emerged as the key metric of evaluating human and natural influence on the climate. We evaluate effective radiative forcing and adjustments in 17 contemporary climate models that are participating in the Coupled Model Intercomparison Project (CMIP6) and have contributed to the Radiative Forcing Model Intercomparison Project (RFMIP). Present-day (2014) global-mean anthropogenic forcing relative to pre-industrial (1850) levels from climate models stands at 2.00 (±0.23) W m−2, comprised of 1.81 (±0.09) W m−2 from CO2, 1.08 (± 0.21) W m−2 from other well-mixed greenhouse gases, −1.01 (± 0.23) W m−2 from aerosols and −0.09 (±0.13) W m−2 from land use change. Quoted uncertainties are 1 standard deviation across model best estimates, and 90 % confidence in the reported forcings, due to internal variability, is typically within 0.1 W m−2. The majority of the remaining 0.21 W m−2 is likely to be from ozone. In most cases, the largest contributors to the spread in effective radiative forcing (ERF) is from the instantaneous radiative forcing (IRF) and from cloud responses, particularly aerosol–cloud interactions to aerosol forcing. As determined in previous studies, cancellation of tropospheric and surface adjustments means that the stratospherically adjusted radiative forcing is approximately equal to ERF for greenhouse gas forcing but not for aerosols, and consequentially, not for the anthropogenic total. The spread of aerosol forcing ranges from −0.63 to −1.37 W m−2, exhibiting a less negative mean and narrower range compared to 10 CMIP5 models. The spread in 4×CO2 forcing has also narrowed in CMIP6 compared to 13 CMIP5 models. Aerosol forcing is uncorrelated with climate sensitivity. Therefore, there is no evidence to suggest that the increasing spread in climate sensitivity in CMIP6 models, particularly related to high-sensitivity models, is a consequence of a stronger negative present-day aerosol forcing and little evidence that modelling groups are systematically tuning climate sensitivity or aerosol forcing to recreate observed historical warming.

Simulation of wind damages associated with the PRIMAVERA European windstorm event set

2021 ◽  
Author(s):  
Tristan Perotin
Keyword(s):  
Climate Models ◽  
Dynamical Downscaling ◽  
Insurance Industry ◽  
Coupled Model ◽  
Correction Method ◽  
Weather Data ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Insurance Sector ◽  
Intercomparison Project

&lt;p&gt;Winter windstorms are one of the major natural hazards affecting Europe, potentially causing large damages. The study of windstorm risks is therefore particularly important for the insurance industry. Physical natural catastrophe models for the insurance industry appeared in the 1980s and enable a fine analysis of the risk by taking into account all of its components (hazard, vulnerability and exposure). One main aspect of this catastrophe modeling is the production and validation of extreme hazard scenarios. As observational weather data is very sparse before the 1980s, estimates of extreme windstorm risks are usually based on climate models, despite the limited resolution of these models. Even though this limitation can be partially corrected by statistical or dynamical downscaling and calibration techniques, new generations of climate models can bring new understanding of windstorm risks.&lt;/p&gt;&lt;p&gt;In that context, PRIMAVERA, a European Union Horizon2020 project, made available a windstorm event set based on 21 tier 1 (1950-2014) highresSST-present simulations of the High Resolution Model Intercomparison Project (HighResMIP) component of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The events were identified with a storm tracking algorithm, footprints were defined for each event as maximum gusts over a 72 hour period, and the footprints were re-gridded to the ERA5 grid and calibrated with a quantile mapping correction method. The native resolution of these simulations ranges from 150km (typical resolution of the CMIP5 models) to 25km.&lt;/p&gt;&lt;p&gt;We have studied the applicability of the PRIMAVERA European windstorm event set for the modeling of European windstorm risks for the insurance sector. Preliminary results show that losses simulated from the event set appear to be consistent with historical data for all of the included simulations. The event set enables a better representation of attritional events and storm clustering than other existing event sets. An alternative calibration technique for extreme gusts and potential future developments of the event set will be proposed.&lt;/p&gt;

scholarly journals New Perspectives on Observed and Simulated Antarctic Sea Ice Extent Trends Using Optimal Fingerprinting Techniques*

2015 ◽  
Vol 28 (4) ◽  
pp. 1543-1560 ◽  
Author(s):  
William Richard Hobbs ◽  
Nathaniel L. Bindoff ◽  
Marilyn N. Raphael
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Ross Sea ◽  
Internal Variability ◽  
Ice Cover ◽  
Natural Variability ◽  
Forced Response ◽  
Cmip5 Models ◽  
Sea Ice Extent ◽  
Optimal Fingerprinting

Abstract Using optimal fingerprinting techniques, a detection analysis is performed to determine whether observed trends in Southern Ocean sea ice extent since 1979 are outside the expected range of natural variability. Consistent with previous studies, it is found that for the seasons of maximum sea ice cover (i.e., winter and early spring), the observed trends are not outside the range of natural variability and in some West Antarctic sectors they may be partially due to tropical variability. However, when information about the spatial pattern of trends is included in the analysis, the summer and autumn trends fall outside the range of internal variability. The detectable signal is dominated by strong and opposing trends in the Ross Sea and the Amundsen–Bellingshausen Sea regions. In contrast to the observed pattern, an ensemble of 20 CMIP5 coupled climate models shows that a decrease in Ross Sea ice cover would be expected in response to external forcings. The simulated decreases in the Ross, Bellingshausen, and Amundsen Seas for the autumn season are significantly different from unforced internal variability at the 95% confidence level. Unlike earlier work, the authors formally show that the simulated sea ice response to external forcing is different from both the observed trends and simulated internal variability and conclude that in general the CMIP5 models do not adequately represent the forced response of the Antarctic climate system.

scholarly journals On the improvement of sea-ice models for climate simulations: the Sea Ice Model Intercomparison Project

1997 ◽  
Vol 25 ◽  
pp. 183-187 ◽  
Author(s):  
Peter Lemke ◽  
W.D. Hibler ◽  
G. Flato ◽  
M. Harder ◽  
M. Kreyscher
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Strong Dependence ◽  
Research Programme ◽  
The Arctic ◽  
Model Parameters ◽  
Model Intercomparison ◽  
Climate Research ◽  
Intercomparison Project ◽  
Ice Model

Experiments with dynamic thermodynamic sea-ice models indicate a strong dependence of the net freezing rate, sea-ice transport and variability on dynamic model parameters. Although current dynamic—thermodynamic sea-ice models show relatively good agreement with observations, an optimization seems to be necessary, especially for the parameterizations of dynamic processes.Presently, only a few coupled climate models use dynamic-thermodynamic sea-ice models. In order to promote, by means of coordinated numerical experiments, the development of an optimal sea-ice model for climate research, the Sea Ice Ocean Modelling Panel of the Arctic Climate System Study (ACSYS, a project of the World Climate Research Programme has initiated the Sea Ice Model Intercomparison Project (SIMIP). The first results from this model hierarchy approach are presented.

Sign in / Sign up

Export Citation Format

Share Document