scholarly journals Can CGCMs Simulate the Twentieth-Century “Warming Hole” in the Central United States?

2006 ◽  
Vol 19 (17) ◽  
pp. 4137-4153 ◽  
Author(s):  
Kenneth E. Kunkel ◽  
Xin-Zhong Liang ◽  
Jinhong Zhu ◽  
Yiruo Lin
Keyword(s):  
United States ◽  
Twentieth Century ◽  
General Circulation ◽  
Initial Conditions ◽  
Regional Scale ◽  
General Circulation Models ◽  
Internal Dynamic ◽  
External Forcings ◽  
Wide Range ◽  
Central United States

Abstract The observed lack of twentieth-century warming in the central United States (CUS), denoted here as the “warming hole,” was examined in 55 simulations driven by external historical forcings and in 19 preindustrial control (unforced) simulations from 18 coupled general circulation models (CGCMs). Twentieth-century CUS trends were positive for the great majority of simulations, but were negative, as observed, for seven simulations. Only a few simulations exhibited the observed rapid rate of warming (cooling) during 1901–40 (1940–79). Those models with multiple runs (identical forcing but different initial conditions) showed considerable intramodel variability with trends varying by up to 1.8°C century−1, suggesting that internal dynamic variability played a major role at the regional scale. The wide range of trend outcomes, particularly for those models with multiple runs, and the small number of simulations similar to observations in both the forced and unforced experiments suggest that the warming hole is not a robust response of contemporary CGCMs to the estimated external forcings. A more likely explanation based on these models is that the observed warming hole involves external forcings combined with internal dynamic variability that is much larger than typically simulated. The observed CUS temperature variations are positively correlated with North Atlantic (NA) sea surface temperatures (SSTs), and both NA SSTs and CUS temperature are negatively correlated with central equatorial Pacific (CEP) SSTs. Most models simulate rather well the connection between CUS temperature and NA SSTs. However, the teleconnections between NA and CEP SSTS and between CEP SSTs and CUS temperature are poorly simulated and the models produce substantially less NA SST variability than observed, perhaps hampering their ability to reproduce the warming hole.

scholarly journals Intermodel Variability and Mechanism Attribution of Central and Southeastern U.S. Anomalous Cooling in the Twentieth Century as Simulated by CMIP5 Models

2013 ◽  
Vol 26 (17) ◽  
pp. 6215-6237 ◽  
Author(s):  
Zaitao Pan ◽  
Xiaodong Liu ◽  
Sanjiv Kumar ◽  
Zhiqiu Gao ◽  
James Kinter
Keyword(s):  
United States ◽  
Twentieth Century ◽  
Land Surface ◽  
Regional Scale ◽  
Coupled Model ◽  
The United States ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Central United States ◽  
Intercomparison Project

Abstract Some parts of the United States, especially the southeastern and central portion, cooled by up to 2°C during the twentieth century, while the global mean temperature rose by 0.6°C (0.76°C from 1901 to 2006). Studies have suggested that the Pacific decadal oscillation (PDO) and the Atlantic multidecadal oscillation (AMO) may be responsible for this cooling, termed the “warming hole” (WH), while other works reported that regional-scale processes such as the low-level jet and evapotranspiration contribute to the abnormity. In phase 3 of the Coupled Model Intercomparison Project (CMIP3), only a few of the 53 simulations could reproduce the cooling. This study analyzes newly available simulations in experiments from phase 5 of the Coupled Model Intercomparison Project (CMIP5) from 28 models, totaling 175 ensemble members. It was found that 1) only 19 out of 100 all-forcing historical ensemble members simulated negative temperature trend (cooling) over the southeast United States, with 99 members underpredicting the cooling rate in the region; 2) the missing of cooling in the models is likely due to the poor performance in simulating the spatial pattern of the cooling rather than the temporal variation, as indicated by a larger temporal correlation coefficient than spatial one between the observation and simulations; 3) the simulations with greenhouse gas (GHG) forcing only produced strong warming in the central United States that may have compensated the cooling; and 4) the all-forcing historical experiment compared with the natural-forcing-only experiment showed a well-defined WH in the central United States, suggesting that land surface processes, among others, could have contributed to the cooling in the twentieth century.

scholarly journals Projection of Future Heat Waves in the United States. Part I: Selecting a Climate Model Subset

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 587
Author(s):  
Javad Shafiei Shiva ◽  
David G. Chandler
Keyword(s):  
United States ◽  
General Circulation ◽  
Climate Model ◽  
Heat Waves ◽  
Well Being ◽  
General Circulation Models ◽  
The United States ◽  
Wide Range ◽  
Overall Performance ◽  
Impact Predictions

The widespread increase in global temperature is driving more frequent and more severe local heatwaves within the contiguous United States (CONUS). General circulation models (GCMs) show increasing, but spatially uneven trends in heatwave properties. However, the wide range of model outputs raises the question of the suitability of this method for indicating the future impacts of heatwaves on human health and well-being. This work examines the fitness of 32 models from CMIP5 and their ensemble median to predict a set of heatwave descriptors across the CONUS, by analyzing their capabilities in the simulation of historical heatwaves during 1950–2005. Then, we use a multi-criteria decision-making tool and rank the overall performance of each model for 10 locations with different climates. We found GCMs have different capabilities in the simulation of historical heatwave characteristics. In addition, we observed similar performances for GCMs over the areas with a partially similar climate. The ensemble model showed better performance in simulation of historical heatwave intensity in some locations, while other individual GCMs represented heatwave time-related components more similar to observations. These results are a step towards the use of contemporary weather models to guide heatwave impact predictions.

scholarly journals GCM Simulations of the Climate in the Central United States

2005 ◽  
Vol 18 (7) ◽  
pp. 1016-1031 ◽  
Author(s):  
Kenneth E. Kunkel ◽  
Xin-Zhong Liang
Keyword(s):  
United States ◽  
General Circulation ◽  
Coupled Model ◽  
Scalar Fields ◽  
General Circulation Models ◽  
Atmospheric Model ◽  
Model Intercomparison ◽  
Central United States ◽  
Intercomparison Project ◽  
Precipitation Changes

Abstract A diagnostic analysis of relationships between central U.S. climate characteristics and various flow and scalar fields was used to evaluate nine global coupled ocean–atmosphere general circulation models (CGCMs) participating in the Coupled Model Intercomparison Project (CMIP). To facilitate identification of physical mechanisms causing biases, data from 21 models participating in the Atmospheric Model Intercomparison Project (AMIP) were also used for certain key analyses. Most models reproduce basic features of the circulation, temperature, and precipitation patterns in the central United States, although no model exhibits small differences from the observationally based data for all characteristics in all seasons. Model ensemble means generally produce better agreement with the observationally based data than any single model. A fall precipitation deficiency, found in all AMIP and CMIP models except the third-generation Hadley Centre CGCM (HadCM3), appears to be related in part to slight biases in the flow on the western flank of the Atlantic subtropical ridge. In the model mean, the ridge at 850 hPa is displaced slightly to the north and to the west, resulting in weaker southerly flow into the central United States. The CMIP doubled-CO2 transient runs show warming (1°–5°C) for all models and seasons and variable precipitation changes over the central United States. Temperature (precipitation) changes are larger (mostly less) than the variations that are observed in the twentieth century and the model variations in the control simulations.

scholarly journals Contributors to linkage between Arctic warming and East Asian winter climate

2021 ◽  
Author(s):  
Xinping Xu ◽  
Shengping He ◽  
Yongqi Gao ◽  
Botao Zhou ◽  
Huijun Wang
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Initial Conditions ◽  
Wave Train ◽  
East Asian ◽  
Surface Air Temperature ◽  
General Circulation Models ◽  
The Arctic ◽  
Winter Climate ◽  
Arctic Warming

AbstractPrevious modelling and observational studies have shown discrepancies in the interannual relationship of winter surface air temperature (SAT) between Arctic and East Asia, stimulating the debate about whether Arctic change can influence midlatitude climate. This study uses two sets of coordinated experiments (EXP1 and EXP2) from six different atmospheric general circulation models. Both EXP1 and EXP2 consist of 130 ensemble members, each of which in EXP1 (EXP2) was forced by the same observed daily varying sea ice and daily varying (daily climatological) sea surface temperature (SST) for 1982–2014 but with different atmospheric initial conditions. Large spread exists among ensemble members in simulating the Arctic–East Asian SAT relationship. Only a fraction of ensemble members can reproduce the observed deep Arctic warming–cold continent pattern which extends from surface to upper troposphere, implying the important role of atmospheric internal variability. The mechanisms of deep Arctic warming and shallow Arctic warming are further distinguished. Arctic warming aloft is caused primarily by poleward moisture transport, which in conjunction with the surface warming coupled with sea ice melting constitutes the surface-amplified deep Arctic warming throughout the troposphere. These processes associated with the deep Arctic warming may be related to the forcing of remote SST when there is favorable atmospheric circulation such as Rossby wave train propagating from the North Atlantic into the Arctic.

scholarly journals The faint young Sun problem revisited with a 3-D climate–carbon model – Part 1

2014 ◽  
Vol 10 (2) ◽  
pp. 697-713 ◽  
Author(s):  
G. Le Hir ◽  
Y. Teitler ◽  
F. Fluteau ◽  
Y. Donnadieu ◽  
P. Philippot
Keyword(s):  
Radiative Forcing ◽  
General Circulation ◽  
Freezing Point ◽  
Climatic Factors ◽  
General Circulation Models ◽  
Companion Paper ◽  
One Dimensional ◽  
Carbon Dioxide Concentrations ◽  
Wide Range ◽  
High Concentrations

Abstract. During the Archaean, the Sun's luminosity was 18 to 25% lower than the present day. One-dimensional radiative convective models (RCM) generally infer that high concentrations of greenhouse gases (CO2, CH4) are required to prevent the early Earth's surface temperature from dropping below the freezing point of liquid water and satisfying the faint young Sun paradox (FYSP, an Earth temperature at least as warm as today). Using a one-dimensional (1-D) model, it was proposed in 2010 that the association of a reduced albedo and less reflective clouds may have been responsible for the maintenance of a warm climate during the Archaean without requiring high concentrations of atmospheric CO2 (pCO2). More recently, 3-D climate simulations have been performed using atmospheric general circulation models (AGCM) and Earth system models of intermediate complexity (EMIC). These studies were able to solve the FYSP through a large range of carbon dioxide concentrations, from 0.6 bar with an EMIC to several millibars with AGCMs. To better understand this wide range in pCO2, we investigated the early Earth climate using an atmospheric GCM coupled to a slab ocean. Our simulations include the ice-albedo feedback and specific Archaean climatic factors such as a faster Earth rotation rate, high atmospheric concentrations of CO2 and/or CH4, a reduced continental surface, a saltier ocean, and different cloudiness. We estimated full glaciation thresholds for the early Archaean and quantified positive radiative forcing required to solve the FYSP. We also demonstrated why RCM and EMIC tend to overestimate greenhouse gas concentrations required to avoid full glaciations or solve the FYSP. Carbon cycle–climate interplays and conditions for sustaining pCO2 will be discussed in a companion paper.

Forecast skill of autumn snow for European winter climate during the 20th century: A multi member seasonal prediction experiment

2021 ◽  
Author(s):  
Martin Wegmann ◽  
Yvan Orsolini ◽  
Antje Weisheimer ◽  
Bart van den Hurk ◽  
Gerrit Lohmann
Keyword(s):  
Snow Cover ◽  
General Circulation ◽  
Initial Conditions ◽  
Internal Variability ◽  
Seasonal Prediction ◽  
General Circulation Models ◽  
Reanalysis Data ◽  
Winter Climate ◽  
European Continent ◽  
Near Surface

<p>As the leading climate mode to explain wintertime climate variability over Europe, the North Atlantic Oscillation (NAO) has been extensively studied over the last decades. Recently, studies highlighted the state of the Northern Hemispheric cryosphere as possible predictor for the wintertime NAO (Cohen et al. 2014). Although several studies could find seasonal prediction skill in reanalysis data (Orsolini et al. 2016, Duville et al. 2017,Han & Sun 2018), experiments with ocean-atmosphere general circulation models (AOGCMs) still show conflicting results (Furtado et al. 2015, Handorf et al. 2015, Francis 2017, Gastineau et al. 2017). </p><p>Here we use two kinds ECMWF seasonal prediction ensembles starting with November initial conditions taken from the long-term reanalysis ERA-20C and forecasting the following three winter months. Besides the 110-year ensemble of 50 members representing internal variability of the atmosphere, we investigate a second ensemble of 20 members where initial conditions are split between low and high snow cover years for the Northern Hemisphere. We compare two recently used Eurasian snow cover indices for their skill in predicting winter climate for the European continent. Analyzing the two forecast experiments, we found that prediction runs starting with high snow index values in November result in significantly more negative NAO states in the following winter (DJF), which in turn modulates near surface temperatures. We track the atmospheric anomalies triggered by the high snow index through the tropo- and stratosphere as well as for the individual winter months to provide a physical explanation for the formation of this particular climate state.</p><p> </p>

Hadley Cell Widening: Model Simulations versus Observations

2009 ◽  
Vol 22 (10) ◽  
pp. 2713-2725 ◽  
Author(s):  
Celeste M. Johanson ◽  
Qiang Fu
Keyword(s):  
Twentieth Century ◽  
General Circulation ◽  
Large Scale ◽  
General Circulation Models ◽  
Hadley Cell ◽  
Climate Projections ◽  
The West ◽  
Model Simulations ◽  
Stratospheric Cooling ◽  
Future Climate Projections

Abstract Observations show that the Hadley cell has widened by about 2°–5° since 1979. This widening and the concomitant poleward displacement of the subtropical dry zones may be accompanied by large-scale drying near 30°N and 30°S. Such drying poses a risk to inhabitants of these regions who are accustomed to established rainfall patterns. Simple and comprehensive general circulation models (GCMs) indicate that the Hadley cell may widen in response to global warming, warming of the west Pacific, or polar stratospheric cooling. The combination of these factors may be responsible for the recent observations. But there is no study so far that has compared the observed widening to GCM simulations of twentieth-century climate integrated with historical changes in forcings. Here the Hadley cell widening is assessed in current GCMs from historical simulations of the twentieth century as well as future climate projections and preindustrial control runs. The authors find that observed widening cannot be explained by natural variability. This observed widening is also significantly larger than in simulations of the twentieth and twenty-first centuries. These results illustrate the need for further investigation into the discrepancy between the observed and simulated widening of the Hadley cell.

scholarly journals Mathematics applied to the climate system: outstanding challenges and recent progress

2013 ◽  
Vol 371 (1991) ◽  
pp. 20120518 ◽  
Author(s):  
Paul D. Williams ◽  
Michael J. P. Cullen ◽  
Michael K. Davey ◽  
John M. Huthnance
Keyword(s):  
General Circulation ◽  
Recent Progress ◽  
Initial Conditions ◽  
Global Climate ◽  
Climate Science ◽  
General Circulation Models ◽  
Climate System ◽  
Future Research ◽  
Theme Issue ◽  
Physically Based

The societal need for reliable climate predictions and a proper assessment of their uncertainties is pressing. Uncertainties arise not only from initial conditions and forcing scenarios, but also from model formulation. Here, we identify and document three broad classes of problems, each representing what we regard to be an outstanding challenge in the area of mathematics applied to the climate system. First, there is the problem of the development and evaluation of simple physically based models of the global climate. Second, there is the problem of the development and evaluation of the components of complex models such as general circulation models. Third, there is the problem of the development and evaluation of appropriate statistical frameworks. We discuss these problems in turn, emphasizing the recent progress made by the papers presented in this Theme Issue. Many pressing challenges in climate science require closer collaboration between climate scientists, mathematicians and statisticians. We hope the papers contained in this Theme Issue will act as inspiration for such collaborations and for setting future research directions.

scholarly journals Improvement of the Simulation of Cloud Longwave Scattering in Broadband Radiative Transfer Models

2018 ◽  
Vol 75 (7) ◽  
pp. 2217-2233 ◽  
Author(s):  
Guanglin Tang ◽  
Ping Yang ◽  
George W. Kattawar ◽  
Xianglei Huang ◽  
Eli J. Mlawer ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Multiple Scattering ◽  
General Circulation ◽  
General Circulation Models ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Discrete Ordinate ◽  
Wide Range ◽  
Scaling Methods ◽  
Computational Errors

Abstract Cloud longwave scattering is generally neglected in general circulation models (GCMs), but it plays a significant and highly uncertain role in the atmospheric energy budget as demonstrated in recent studies. To reduce the errors caused by neglecting cloud longwave scattering, two new radiance adjustment methods are developed that retain the computational efficiency of broadband radiative transfer simulations. In particular, two existing scaling methods and the two new adjustment methods are implemented in the Rapid Radiative Transfer Model (RRTM). The results are then compared with those based on the Discrete Ordinate Radiative Transfer model (DISORT) that explicitly accounts for multiple scattering by clouds. The two scaling methods are shown to improve the accuracy of radiative transfer simulations for optically thin clouds but not effectively for optically thick clouds. However, the adjustment methods reduce computational errors over a wide range, from optically thin to thick clouds. With the adjustment methods, the errors resulting from neglecting cloud longwave scattering are reduced to less than 2 W m−2 for the upward irradiance at the top of the atmosphere and less than 0.5 W m−2 for the surface downward irradiance. The adjustment schemes prove to be more accurate and efficient than a four-stream approximation that explicitly accounts for multiple scattering. The neglect of cloud longwave scattering results in an underestimate of the surface downward irradiance (cooling effect), but the errors are almost eliminated by the adjustment methods (warming effect).

scholarly journals Comparison of the Northwestern Pacific Summer Climate Simulated by AMIP II AGCMs

2012 ◽  
Vol 25 (17) ◽  
pp. 6036-6056 ◽  
Author(s):  
Minghong Zhang ◽  
Shuanglin Li ◽  
Jian Lu ◽  
Renguang Wu
Keyword(s):  
General Circulation ◽  
Diabatic Heating ◽  
General Circulation Models ◽  
Northwestern Pacific ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Summer Climate ◽  
Walker Cell ◽  
Wide Range ◽  
Atmosphere Model ◽  
The Difference

Abstract This study examines the skills in simulating interannual variability of northwestern Pacific (NWP) summer climate in 12 atmospheric general circulation models (AGCMs) attending the Atmospheric Model Intercomparison Project phase 2 (AMIP II). The models show a wide range of skills, among those version 1 of the Hadley Centre Global Atmosphere Model (HadGAM1) showed the highest fidelity and thus may be a better choice for studying East Asian–NWP summer climate. To understand the possible causes for the difference among the models, five models {HadGAM1; ECHAM5; the Geophysical Fluid Dynamics Laboratory Atmosphere Model, version 2.1 (AM2.1); Model for Interdisciplinary Research on Climate 3.2, high-resolution version [MIROC3.2(hires)]; and the fourth-generation National Center for Atmospheric Research Community Atmosphere Model (CAM3)} that have various skill levels, ranging from the highest to the moderate to the minor, were selected for analyses. The simulated teleconnection of NWP summer climate with sea surface temperatures (SSTs) in the tropical Indian and Pacific Oceans was first compared. HadGAM1 reproduces suppressed (intensified) rainfall during El Niño (La Niña) events and captures well the remote connection with the tropical Indian Ocean, while the other models either underestimate [ECHAM5, AM2.1, MIROC3.2(hires)] or fail to reproduce (CAM3) these teleconnections. The Walker cell and diabatic heating were further compared to shed light on the underlying physical mechanisms for the difference. Consistent with the best performance in simulating interannual rainfall, HadGAM1 exhibits the highest-level skill in capturing the observed climatology of the Walker cell and diabatic heating. These results highlight the key roles of the model’s background climatology in the Walker cell and diabatic heating, thus providing important clues to improving the model’s ability.

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