Evaluation of the Antarctic Circumpolar Wave Simulated by CMIP5 and CMIP6 Models

As a coupled large-scale oceanic and atmospheric pattern in the Southern Ocean, the Antarctic circumpolar wave (ACW) has substantial impacts on the global climate. In this study, using the European Centre for Medium-Range Weather Forecasts ERA5 dataset and historical experiment outputs from 24 models of the Coupled Model Intercomparison Project Phase 5 and Phase 6 (CMIP5/CMIP6) spanning the 1980s and 1990s, the simulation capability of models for sea-level pressure (SLP) and sea surface temperature (SST) variability of the ACW is evaluated. It is shown that most models can capture well the 50-month period of the ACW. However, many simulations show a weak amplitude, but with various phase differences. Selected models can simulate SLP better than SST, and CMIP6 models generally perform better than the CMIP5 models. The best model for SLP simulation is the CanESM5 model from CMIP6, whereas the best model for SST simulation is the ACCESS1.3 model from CMIP5. It seems that the SST simulation benefits from the inclusion of both a carbon cycle process and a chemistry module, while the SLP simulation benefits from only the chemistry module. When both SLP and SST are taken into consideration, the CanESM5 model performs the best among all the selected models.

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The Double-ITCZ Bias in CMIP6 Models

10.5194/egusphere-egu2020-21375 ◽

2020 ◽

Author(s):

Baijun Tian

Keyword(s):

Climate Models ◽

Global Climate ◽

Coupled Model ◽

Global Climate Models ◽

Cmip5 Models ◽

Tropical Precipitation ◽

Double Itcz ◽

Intercomparison Project ◽

Fully Coupled

The double-Intertropical Convergence Zone (ITCZ) bias is one of the most outstanding problems in climate models. This study seeks to examine the double-ITCZ bias in the latest state-of-the-art fully coupled global climate models that participated in Coupled Model Intercomparison Project (CMIP) Phase 6 (CMIP6) in comparison to their previous generations (CMIP3 and CMIP5 models). To that end, we have analyzed the long-term annual mean tropical precipitation distributions and several precipitation bias indices that quantify the double-ITCZ biases in 75 climate models including 24 CMIP3 models, 25 CMIP3 models, and 26 CMIP6 models. We find that the double-ITCZ bias and its big inter-model spread persist in CMIP6 models but the double-ITCZ bias is slightly reduced from CMIP3 or CMIP5 models to CMIP6 models.

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Saharan Heat Low Biases in CMIP5 Models

Journal of Climate ◽

10.1175/jcli-d-16-0134.1 ◽

2017 ◽

Vol 30 (8) ◽

pp. 2867-2884 ◽

Cited By ~ 10

Author(s):

Ross D. Dixon ◽

Anne Sophie Daloz ◽

Daniel J. Vimont ◽

Michela Biasutti

Keyword(s):

Large Scale ◽

Climate Models ◽

Climate Model ◽

Global Climate ◽

West African Monsoon ◽

West African ◽

Global Climate Models ◽

Cmip5 Models ◽

African Climate ◽

Heat Low

Representing the West African monsoon (WAM) is a major challenge in climate modeling because of the complex interaction between local and large-scale mechanisms. This study focuses on the representation of a key aspect of West African climate, namely the Saharan heat low (SHL), in 22 global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) multimodel dataset. Comparison of the CMIP5 simulations with reanalyses shows large biases in the strength and location of the mean SHL. CMIP5 models tend to develop weaker climatological heat lows than the reanalyses and place them too far southwest. Models that place the climatological heat low farther to the north produce more mean precipitation across the Sahel, while models that place the heat low farther to the east produce stronger African easterly wave (AEW) activity. These mean-state biases are seen in model ensembles with both coupled and fixed sea surface temperatures (SSTs). The importance of SSTs on West African climate variability is well documented, but this research suggests SSTs are secondary to atmospheric biases for understanding the climatological SHL bias. SHL biases are correlated across the models to local radiative terms, large-scale tropical precipitation, and large-scale pressure and wind across the Atlantic, suggesting that local mechanisms that control the SHL may be connected to climate model biases at a much larger scale.

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Carbon–concentration and carbon–climate feedbacks in CMIP6 models and their comparison to CMIP5 models

Biogeosciences ◽

10.5194/bg-17-4173-2020 ◽

2020 ◽

Vol 17 (16) ◽

pp. 4173-4222 ◽

Cited By ~ 19

Author(s):

Vivek K. Arora ◽

Anna Katavouta ◽

Richard G. Williams ◽

Chris D. Jones ◽

Victor Brovkin ◽

...

Keyword(s):

Carbon Concentration ◽

Global Climate ◽

Coupled Model ◽

Co2 Concentration ◽

Climate Feedback ◽

Cmip5 Models ◽

Climate Feedbacks ◽

Transient Climate Response ◽

Order Of Magnitude ◽

Intercomparison Project

Abstract. Results from the fully and biogeochemically coupled simulations in which CO2 increases at a rate of 1 % yr−1 (1pctCO2) from its preindustrial value are analyzed to quantify the magnitude of carbon–concentration and carbon–climate feedback parameters which measure the response of ocean and terrestrial carbon pools to changes in atmospheric CO2 concentration and the resulting change in global climate, respectively. The results are based on 11 comprehensive Earth system models from the most recent (sixth) Coupled Model Intercomparison Project (CMIP6) and compared with eight models from the fifth CMIP (CMIP5). The strength of the carbon–concentration feedback is of comparable magnitudes over land (mean ± standard deviation = 0.97 ± 0.40 PgC ppm−1) and ocean (0.79 ± 0.07 PgC ppm−1), while the carbon–climate feedback over land (−45.1 ± 50.6 PgC ∘C−1) is about 3 times larger than over ocean (−17.2 ± 5.0 PgC ∘C−1). The strength of both feedbacks is an order of magnitude more uncertain over land than over ocean as has been seen in existing studies. These values and their spread from 11 CMIP6 models have not changed significantly compared to CMIP5 models. The absolute values of feedback parameters are lower for land with models that include a representation of nitrogen cycle. The transient climate response to cumulative emissions (TCRE) from the 11 CMIP6 models considered here is 1.77 ± 0.37 ∘C EgC−1 and is similar to that found in CMIP5 models (1.63 ± 0.48 ∘C EgC−1) but with somewhat reduced model spread. The expressions for feedback parameters based on the fully and biogeochemically coupled configurations of the 1pctCO2 simulation are simplified when the small temperature change in the biogeochemically coupled simulation is ignored. Decomposition of the terms of these simplified expressions for the feedback parameters is used to gain insight into the reasons for differing responses among ocean and land carbon cycle models.

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Interactions between Antarctic sea ice and large-scale atmospheric modes in CMIP5 models

10.5194/tc-2016-200 ◽

2016 ◽

Author(s):

Serena Schroeter ◽

Will Hobbs ◽

Nathaniel L. Bindoff

Keyword(s):

Sea Ice ◽

Large Scale ◽

Coupled Model ◽

Southern Annular Mode ◽

Cmip5 Models ◽

Atmospheric Variability ◽

Annular Mode ◽

Antarctic Sea Ice ◽

Ice Retreat ◽

Sea Ice Retreat

Abstract. The response of Antarctic sea ice to large-scale patterns of atmospheric variability varies according to sea ice sector and season. In this study, interannual atmosphere-sea ice interactions were explored using observation-based data and compared with simulated interactions by models in the Coupled Model Intercomparison Project Phase 5. Simulated relationships between atmospheric variability and sea ice variability generally reproduced the observed relationships, though more closely during the season of sea ice advance than the season of sea ice retreat. Atmospheric influence on sea ice is known to be strongest during its advance, with the ocean emerging as a dominant driver of sea ice retreat; therefore, while it appears that models are able to capture the dominance of the atmosphere during advance, simulations of ocean-atmosphere-sea ice interactions during retreat require further investigation. A large proportion of model ensemble members overestimated the relative importance of the Southern Annular Mode compared with other modes on high southern latitude climate, while the influence of tropical forcing was underestimated. This result emerged particularly strongly during the season of sea ice retreat. The amplified zonal patterns of the Southern Annular Mode in many models and its exaggerated influence on sea ice overwhelm the comparatively underestimated meridional influence, suggesting that simulated sea ice variability would become more zonally symmetric as a result. Across the seasons of sea ice advance and retreat, 3 of the 5 sectors did not reveal a strong relationship with a pattern of large-scale atmospheric variability in one or both seasons, indicating that sea ice in these sectors may be influenced more strongly by atmospheric variability unexplained by the major atmospheric modes, or by heat exchange in the ocean.

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The Climatology of the Atmospheric Boundary Layer in Contemporary Global Climate Models

Journal of Climate ◽

10.1175/jcli-d-17-0498.1 ◽

2018 ◽

Vol 31 (22) ◽

pp. 9151-9173 ◽

Cited By ~ 6

Author(s):

Richard Davy

Keyword(s):

Boundary Layer ◽

General Circulation ◽

Climate Models ◽

Global Climate ◽

Coupled Model ◽

General Circulation Models ◽

Global Climate Models ◽

Cmip5 Models ◽

Seasonal Cycles ◽

Layer Depth

Here, we present the climatology of the planetary boundary layer depth in 18 contemporary general circulation models (GCMs) in simulations of the late-twentieth-century climate that were part of phase 5 of the Coupled Model Intercomparison Project (CMIP5). We used a bulk Richardson methodology to establish the boundary layer depth from the 6-hourly synoptic-snapshot data available in the CMIP5 archives. We present an ensemble analysis of the climatological mean, diurnal cycle, and seasonal cycle of the boundary layer depth in these models and compare it to the climatologies from the ECMWF ERA-Interim reanalysis. Overall, we find that the CMIP5 models do a reasonably good job of reproducing the distribution of mean boundary layer depth, although the geographical patterns vary considerably between models. However, the models are biased toward weaker diurnal and seasonal cycles in the boundary layer depth and generally produce much deeper boundary layers at night and during the winter than are found in the reanalysis. These biases are likely to reduce the ability of these models to accurately represent other properties of the diurnal and seasonal cycles, and the sensitivity of these cycles to climate change.

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Past and future trends in large-scale atmospheric circulations over Europe: Assessment of the Jenkinson-Collison classification with reanalyses and CMIP6.

10.5194/dkt-12-32 ◽

2020 ◽

Author(s):

Pedro Herrera-Lormendez ◽

Nikolaos Mastrantonas ◽

Jörg Matschullat ◽

Hervé Douville

Keyword(s):

General Circulation ◽

Large Scale ◽

Western Europe ◽

Climate Models ◽

Global Climate ◽

Coupled Model ◽

Global Climate Models ◽

Extreme Weather Events ◽

Dynamical Response ◽

Weather Patterns

Circulation classifications are a simple tool given their ability to portray aspects of day-to-day weather. As we start facing a dynamical response in general circulation patterns due to anthropogenic global warming, circulation changes can enhance or mitigate regional and local behaviour of extreme weather events. A weather type (WT) automatic classification, developed by Jenkinson-Collison (JC), is used to evaluate past and future changes in the seasonal frequencies of synoptic weather patterns over central and western Europe. A set of three reanalyses and four Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) are used, based on daily Sea Level Pressure (SLP) data. Discrepancies are found in the model outputs as they fall short of capturing interannual variabilities when compared to the reanalyses. Cyclonic and westerly circulations tend to be overestimated, whereas anticyclonics are underestimated. The projected frequencies, based on the Shared Socioeconomic Pathway 5 (SSP5) experiment, suggest significant increasing trends for unclassified WT (characterized by weak pressure gradients) during their summer half-year persistency for the coming 21st century. Winter trends indicate a surge in westerlies and a reduction in the events of cyclonic circulations and easterly flows. The results of this study support evidence of emergent changes in the occurrence of major synoptic configurations over Europe.

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Cloud and Water Vapor Feedbacks to the El Niño Warming: Are They Still Biased in CMIP5 Models?

Journal of Climate ◽

10.1175/jcli-d-12-00575.1 ◽

2013 ◽

Vol 26 (14) ◽

pp. 4947-4961 ◽

Cited By ~ 50

Author(s):

Lin Chen ◽

Yongqiang Yu ◽

De-Zheng Sun

Keyword(s):

Water Vapor ◽

El Niño ◽

Radiative Forcing ◽

Large Scale ◽

El Nino ◽

Coupled Model ◽

Cmip5 Models ◽

Cold Tongue ◽

Key Factor ◽

Intercomparison Project

Abstract Previous evaluations of model simulations of the cloud and water vapor feedbacks in response to El Niño warming have singled out two common biases in models from phase 3 of the Coupled Model Intercomparison Project (CMIP3): an underestimate of the negative feedback from the shortwave cloud radiative forcing (SWCRF) and an overestimate of the positive feedback from the greenhouse effect of water vapor. Here, the authors check whether these two biases are alleviated in the CMIP5 models. While encouraging improvements are found, particularly in the simulation of the negative SWCRF feedback, the biases in the simulation of these two feedbacks remain prevalent and significant. It is shown that bias in the SWCRF feedback correlates well with biases in the corresponding feedbacks from precipitation, large-scale circulation, and longwave radiative forcing of clouds (LWCRF). By dividing CMIP5 models into two categories—high score models (HSM) and low score models (LSM)—based on their individual skills of simulating the SWCRF feedback, the authors further find that ocean–atmosphere coupling generally lowers the score of the simulated feedbacks of water vapor and clouds but that the LSM is more affected by the coupling than the HSM. They also find that the SWCRF feedback is simulated better in the models that have a more realistic zonal extent of the equatorial cold tongue, suggesting that the continuing existence of an excessive cold tongue is a key factor behind the persistence of the feedback biases in models.

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Analysis of Long-Term Moon-Based Observation Characteristics for Arctic and Antarctic

Remote Sensing ◽

10.3390/rs11232805 ◽

2019 ◽

Vol 11 (23) ◽

pp. 2805 ◽

Cited By ~ 1

Author(s):

Yue Sui ◽

Huadong Guo ◽

Guang Liu ◽

Yuanzhen Ren

Keyword(s):

Global Climate Change ◽

Large Scale ◽

Global Climate ◽

Earth Observation ◽

Polar Regions ◽

The Moon ◽

The North ◽

The Earth ◽

The Antarctic

The Antarctic and Arctic have always been critical areas of earth science research and are sensitive to global climate change. Global climate change exhibits diversity characteristics on both temporal and spatial scales. Since the Moon-based earth observation platform could provide large-scale, multi-angle, and long-term measurements complementary to the satellite-based Earth observation data, it is necessary to study the observation characteristics of this new platform. With deepening understanding of Moon-based observations, we have seen its good observation ability in the middle and low latitudes of the Earth’s surface, but for polar regions, we need to further study the observation characteristics of this platform. Based on the above objectives, we used the Moon-based Earth observation geometric model to quantify the geometric relationship between the Sun, Moon, and Earth. Assuming the sensor is at the center of the nearside of the Moon, the coverage characteristics of the earth feature points are counted. The observation intervals, access frequency, and the angle information of each point during 100 years were obtained, and the variation rule was analyzed. The research showed that the lunar platform could carry out ideal observations for the polar regions. For the North and South poles, a continuous observation duration of 14.5 days could be obtained, and as the latitude decreased, the duration time was reduced to less than one day at the latitude of 65° in each hemisphere. The dominant observation time of the North Pole is concentrated from mid-March to mid-September, and for the South Pole, it is the rest of the year, and as the latitude decreases, it extends outward from both sides. The annual coverage time and frequency will change with the relationship between the Moon and the Earth. This study also proves that the Moon-based observation has multi-angle observation advantages for the Arctic and the Antarctic areas, which can help better understand large-scale geoscientific phenomena. The above findings indicate that the Moon-based observation can be applied as a new type of remote sensing technology to the observation field of the Earth’s polar regions.

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A hydrological toolkit to delineate patterns of blue and green water in a regional semi-arid climate in Iran via CMIP5 models

Időjárás ◽

10.28974/idojaras.2021.2.7 ◽

2021 ◽

Vol 125 (2) ◽

pp. 291-319

Author(s):

Amirhosein Aghakhani Afshar ◽

Yousef Hassanzadeh

Keyword(s):

Hydrological Modeling ◽

Assessment Tool ◽

Coupled Model ◽

Climate Change Impacts ◽

Green Water ◽

Cmip5 Models ◽

Historical Period ◽

Near Future ◽

Better Than ◽

Far Future

Water scarcity and the climate change impacts on water components will drastically alter everybody's life. The Soil and Water Assessment Tool (SWAT) has been utilized in this study in combination with Sequential Uncertainty Fitting Program (SUFI-2) to simulate precipitation (P), temperature (T), blue water (BW), green water flow (GWF), and green water storage (GWS) in Kashafrood River Basin, Iran. The outputs of two Coupled Model Intercomparison Project Phase 5 (CMIP5) models (MIROC-ESM and GFDL-ESM2G) are selected for hydrological modeling under Representative Concentration Pathways (RCPs) of 4.5 and 8.5 and for the near future (2014-2042) and far future (2043-2100( periods compared to historical period (1995-2011). The results of RCPs, in comparison with the historical period, show that P and BW are increased and in GFDL-ESM2G are better than MIROC-ESM, while T tends to increase, and MIROC-ESM is better than GFDL-ESM2G. GWF, in all future periods (except in MIROC-ESM in near future and under RCP4.5 and 8.5) and in all RCPs tend to decrease, and the results of MIROC-ESM are better than those of GFDL-ESM2G in near future and are vice versa in far future. It is anticipated that GWS continues its historical trend in the future.

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