scholarly journals Atmospheric circulation and hydroclimate impacts of alternative warming scenarios for the Eocene

2017 ◽  
Vol 13 (8) ◽  
pp. 1037-1048 ◽  
Author(s):  
Henrik Carlson ◽  
Rodrigo Caballero

Abstract. Recent work in modelling the warm climates of the early Eocene shows that it is possible to obtain a reasonable global match between model surface temperature and proxy reconstructions, but only by using extremely high atmospheric CO2 concentrations or more modest CO2 levels complemented by a reduction in global cloud albedo. Understanding the mix of radiative forcing that gave rise to Eocene warmth has important implications for constraining Earth's climate sensitivity, but progress in this direction is hampered by the lack of direct proxy constraints on cloud properties. Here, we explore the potential for distinguishing among different radiative forcing scenarios via their impact on regional climate changes. We do this by comparing climate model simulations of two end-member scenarios: one in which the climate is warmed entirely by CO2 (which we refer to as the greenhouse gas (GHG) scenario) and another in which it is warmed entirely by reduced cloud albedo (which we refer to as the low CO2–thin clouds or LCTC scenario) . The two simulations have an almost identical global-mean surface temperature and equator-to-pole temperature difference, but the LCTC scenario has  ∼  11 % greater global-mean precipitation than the GHG scenario. The LCTC scenario also has cooler midlatitude continents and warmer oceans than the GHG scenario and a tropical climate which is significantly more El Niño-like. Extremely high warm-season temperatures in the subtropics are mitigated in the LCTC scenario, while cool-season temperatures are lower at all latitudes. These changes appear large enough to motivate further, more detailed study using other climate models and a more realistic set of modelling assumptions.

2017 ◽  
Author(s):  
Henrik Carlson ◽  
Rodrigo Caballero

Abstract. Recent work in modelling the warm climates of the Early Eocene shows that it is possible to obtain a reasonable global match between model surface temperature and proxy reconstructions, but only by using extremely high atmospheric CO2 concentrations or more modest CO2 levels complemented by a reduction in global cloud albedo. Understanding the mix of radiative forcing that gave rise to Eocene warmth has important implications for constraining Earth's climate sensitivity, but progress in this direction is hampered by the lack of direct proxy constraints on cloud properties. Here, we explore the potential for distinguishing among different radiative forcing scenarios via their impact on regional climate changes. We do this by comparing climate model simulations of two end-member scenarios: one in which the climate is warmed entirely by CO2, and another in which it is warmed entirely by reduced cloud albedo (which we refer to as the low CO2-thin clouds or LCTC scenario) . The two simulations have almost identical global-mean surface temperature and equator-to-pole temperature difference, but the LCTC scenario has ~ 11 % greater global-mean precipitation. The LCTC simulation also has cooler midlatitude continents and warmer oceans than the high-CO2 scenario, and a tropical climate which is significantly more El Niño-like. We discuss the potential implications of these regional changes for terrestrial hydroclimate and vegetation.


Author(s):  
Weijia Qian ◽  
Howard H. Chang

Health impact assessments of future environmental exposures are routinely conducted to quantify population burdens associated with the changing climate. It is well-recognized that simulations from climate models need to be bias-corrected against observations to estimate future exposures. Quantile mapping (QM) is a technique that has gained popularity in climate science because of its focus on bias-correcting the entire exposure distribution. Even though improved bias-correction at the extreme tails of exposure may be particularly important for estimating health burdens, the application of QM in health impact projection has been limited. In this paper we describe and apply five QM methods to estimate excess emergency department (ED) visits due to projected changes in warm-season minimum temperature in Atlanta, USA. We utilized temperature projections from an ensemble of regional climate models in the North American-Coordinated Regional Climate Downscaling Experiment (NA-CORDEX). Across QM methods, we estimated consistent increase in ED visits across climate model ensemble under RCP 8.5 during the period 2050 to 2099. We found that QM methods can significantly reduce between-model variation in health impact projections (50–70% decreases in between-model standard deviation). Particularly, the quantile delta mapping approach had the largest reduction and is recommended also because of its ability to preserve model-projected absolute temporal changes in quantiles.


2017 ◽  
Vol 30 (20) ◽  
pp. 8275-8298 ◽  
Author(s):  
Melissa S. Bukovsky ◽  
Rachel R. McCrary ◽  
Anji Seth ◽  
Linda O. Mearns

Abstract Global and regional climate model ensembles project that the annual cycle of rainfall over the southern Great Plains (SGP) will amplify by midcentury. Models indicate that warm-season precipitation will increase during the early spring wet season but shift north earlier in the season, intensifying late summer drying. Regional climate models (RCMs) project larger precipitation changes than their global climate model (GCM) counterparts. This is particularly true during the dry season. The credibility of the RCM projections is established by exploring the larger-scale dynamical and local land–atmosphere feedback processes that drive future changes in the simulations, that is, the responsible mechanisms or processes. In this case, it is found that out of 12 RCM simulations produced for the North American Regional Climate Change Assessment Program (NARCCAP), the majority are mechanistically credible and consistent in the mean changes they are producing in the SGP. Both larger-scale dynamical processes and local land–atmosphere feedbacks drive an earlier end to the spring wet period and deepening of the summer dry season in the SGP. The midlatitude upper-level jet shifts northward, the monsoon anticyclone expands, and the Great Plains low-level jet increases in strength, all supporting a poleward shift in precipitation in the future. This dynamically forced shift causes land–atmosphere coupling to strengthen earlier in the summer, which in turn leads to earlier evaporation of soil moisture in the summer, resulting in extreme drying later in the summer.


2014 ◽  
Vol 27 (17) ◽  
pp. 6799-6818 ◽  
Author(s):  
Christian Kerkhoff ◽  
Hans R. Künsch ◽  
Christoph Schär

Abstract Climate scenarios make implicit or explicit assumptions about the extrapolation of climate model biases from current to future time periods. Such assumptions are inevitable because of the lack of future observations. This manuscript reviews different bias assumptions found in the literature and provides measures to assess their validity. The authors explicitly separate climate change from multidecadal variability to systematically analyze climate model biases in seasonal and regional surface temperature averages, using global and regional climate models (GCMs and RCMs) from the Ensemble-Based Predictions of Climate Changes and Their Impacts (ENSEMBLES) project over Europe. For centennial time scales, it is found that a linear bias extrapolation for GCMs is best supported by the analysis: that is, it is generally not correct to assume that model biases are independent of the climate state. Results also show that RCMs behave markedly differently when forced with different drivers. RCM and GCM biases are not additive, and there is a significant interaction component in the bias of the RCM–GCM model chain that depends on both the RCM and GCM considered. This result questions previous studies that deduce biases (and ultimately projections) in RCM–GCM combinations from reanalysis-driven simulations. The authors suggest that the aforementioned interaction component derives from the refined RCM representation of dynamical and physical processes in the lower troposphere, which may nonlinearly depend upon the larger-scale circulation stemming from the driving GCM. The authors’ analyses also show that RCMs provide added value and that the combined RCM–GCM approach yields, in general, smaller biases in seasonal surface temperature and interannual variability, particularly in summer and even for spatial scales that are, in principle, well resolved by the GCMs.


Water ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 978 ◽  
Author(s):  
Marco D’Oria ◽  
Maria Tanda ◽  
Valeria Todaro

This study provides an up-to-date analysis of climate change over the Salento area (southeast Italy) using both historical data and multi-model projections of Regional Climate Models (RCMs). The accumulated anomalies of monthly precipitation and temperature records were analyzed and the trends in the climate variables were identified and quantified for two historical periods. The precipitation trends are in almost all cases not significant while the temperature shows statistically significant increasing tendencies especially in summer. A clear changing point around the 80s and at the end of the 90s was identified by the accumulated anomalies of the minimum and maximum temperature, respectively. The gradual increase of the temperature over the area is confirmed by the climate model projections, at short—(2016–2035), medium—(2046–2065) and long-term (2081–2100), provided by an ensemble of 13 RCMs, under two Representative Concentration Pathways (RCP4.5 and RCP8.5). All the models agree that the mean temperature will rise over this century, with the highest increases in the warm season. The total annual rainfall is not expected to significantly vary in the future although systematic changes are present in some months: a decrease in April and July and an increase in November. The daily temperature projections of the RCMs were used to identify potential variations in the characteristics of the heat waves; an increase of their frequency is expected over this century.


Atmosphere ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 822
Author(s):  
Abdullah Kahraman ◽  
Deniz Ural ◽  
Barış Önol

Convective scale processes and, therefore, thunderstorm-related hazards cannot be simulated using regional climate models with horizontal grid spacing in the order of 10 km. However, larger-scale environmental conditions of these local high-impact phenomena can be diagnosed to assess their frequency in current and future climates. In this study, we present a daytime climatology of severe thunderstorm environments and its evolution for a wide Euro-Mediterranean domain through the 21st century, using regional climate model simulations forced by Representative Concentration Pathway (RCP) 8.5 scenario. Currently, severe convective weather is more frequently favored around Central Europe and the Mediterranean Sea. Our results suggest that with a steady progress until the end of the century, Mediterranean coasts are projected to experience a significantly higher frequency of severe thunderstorm environments, while a slight decrease over parts of continental Europe is evaluated. The increase across the Mediterranean is mostly owed to the warming sea surface, which strengthens thermodynamic conditions in the wintertime, while local factors arguably keep the shear frequency relatively higher than the entire region. On the other hand, future northward extension of the subtropical belt over Europe in the warm season reduces the number of days with severe thunderstorm environments.


2015 ◽  
Vol 8 (2) ◽  
pp. 897-933
Author(s):  
M. A. Thomas ◽  
M. Kahnert ◽  
C. Andersson ◽  
H. Kokkola ◽  
U. Hansson ◽  
...  

Abstract. To reduce uncertainties and hence, to obtain a better estimate of aerosol (direct and indirect) radiative forcing, next generation climate models aim for a tighter coupling between chemistry transport models and regional climate models and a better representation of aerosol–cloud interactions. In this study, this coupling is done by first forcing the Rossby Center regional climate model, RCA4 by ERA-Interim lateral boundaries (LBCs) and SST using the standard CDNC (cloud droplet number concentration) formulation (hereafter, referred to as the "stand-alone RCA4 version" or "CTRL" simulation). In this simulation, the CDNCs are assigned fixed numbers based on if the underlying surface is land or oceanic. The meteorology from this simulation is then used to drive the chemistry transport model, MATCH which is coupled online with the aerosol dynamics model, SALSA. CDNC fields obtained from MATCH-SALSA are then fed back into a new RCA4 simulation. In this new simulation (referred to as "MOD" simulation), all parameters remain the same as in the first run except for the CDNCs provided by MATCH-SALSA. Simulations are carried out with this model set up for the period 2005–2012 over Europe and the differences in cloud microphysical properties and radiative fluxes as a result of local CDNC changes and possible model responses are analyzed. Our study shows substantial improvements in the cloud microphysical properties with the input of the MATCH-SALSA derived 3-D CDNCs compared to the stand-alone RCA4 version. This model set up improves the spatial, seasonal and vertical distribution of CDNCs with higher concentration observed over central Europe during summer half of the year and over Eastern Europe and Russia during the winter half of the year. Realistic cloud droplet radii (CD radii) values have been simulated with the maxima reaching 13 μm whereas in the stand-alone version, the values reached only 5 μm. A substantial improvement in the distribution of cloud liquid water path was observed when compared to the satellite retrievals from MODIS for the boreal summer months. The median and SD values from the "MOD" simulation are closer to observations than those obtained using the stand-alone RCA4 version. These changes resulted in a significant decrease in the total annual mean net fluxes at the top of the atmosphere (TOA) by −5 W m−2 over the domain selected in the study. The TOA net fluxes from the "MOD" simulation show a better agreement with the retrievals from CERES instrument. The aerosol indirect effects are evaluated based on 1900 emissions. Our simulations estimated the domain averaged annual mean total radiative forcing of −0.64 W m−2 with larger contribution from the first indirect aerosol effect than from the second indirect aerosol effect.


Ocean Science ◽  
2021 ◽  
Vol 17 (1) ◽  
pp. 181-186
Author(s):  
Aslak Grinsted ◽  
Jens Hesselbjerg Christensen

Abstract. Recent assessments from the Intergovernmental Panel on Climate Change (IPCC) imply that global mean sea level is unlikely to rise more than about 1.1 m within this century but will increase further beyond 2100. Even within the most intensive future anthropogenic greenhouse gas emission scenarios, higher levels are assessed to be unlikely. However, some studies conclude that considerably greater sea level rise could be realized, and a number of experts assign a substantially higher likelihood of such a future. To understand this discrepancy, it would be useful to have scenario-independent metrics that can be compared between different approaches. The concept of a transient climate sensitivity has proven to be useful to compare the global mean temperature response of climate models to specific radiative forcing scenarios. Here, we introduce a similar metric for sea level response. By analyzing the mean rate of change in sea level (not sea level itself), we identify a nearly linear relationship with global mean surface temperature (and therefore accumulated carbon dioxide emissions) both in model projections and in observations on a century scale. This motivates us to define the “transient sea level sensitivity” as the increase in the sea level rate associated with a given warming in units of meters per century per kelvin. We find that future projections estimated on climate model responses fall below extrapolation based on recent observational records. This comparison suggests that the likely upper level of sea level projections in recent IPCC reports would be too low.


2005 ◽  
Vol 5 (5) ◽  
pp. 9039-9063 ◽  
Author(s):  
R.-M. Hu ◽  
J.-P. Blanchet ◽  
E. Girard

Abstract. Cloud radiative forcing is a very important concept to understand what kind of role the clouds play in climate change with thermal effect or albedo effect. In spite of that much progress has been achieved, the clouds are still poorly described in the climate models. Due to the complex aerosol-cloud-radiation interactions, high surface albedo of snow and ice cover, and without solar radiation in long period of the year, the Arctic strong warming caused by increasing greenhouse gases (as most GCMs suggested) has not been verified by the observations. In this study, we were dedicated to quantify the aerosol effect on the Arctic cloud radiative forcing by Northern Aerosol Regional Climate Model (NARCM). Major aerosol species such as Arctic haze sulphate, black carbon, sea salt, organics and dust have been included during our simulations. By inter-comparisons with the Atmospheric Radiation Measurement (ARM) data, we find surface cloud radiative forcing (SCRF) is −22 W/m2 for shortwave and 36 W/m2 for longwave. Total cloud forcing is 14 W/m2 with minimum of −35 W/m2 in early July. If aerosols are taken into account, the SCRF has been increased during winter while negative SCRF has been enhanced during summer. Our estimate of aerosol forcing is about −6 W/m2 in the Arctic.


2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Tony W. Li ◽  
Noel C. Baker

The observed slow-down in the global-mean surface temperature (GST) warming from 1998 to 2012 has been called a “warming hiatus.” Certain climate models, operating under experiments which simulate warming by increasing radiative forcing, have been shown to reproduce periods which resemble the observed hiatus. The present study provides a comprehensive analysis of 38 CMIP5 climate models to provide further evidence that models produce warming hiatus periods during warming experiments. GST rates are simulated in each model for the 21st century using two experiments: a moderate warming scenario (RCP4.5) and high-end scenario (RCP8.5). Warming hiatus periods are identified in model simulations by detecting (1) ≥15-year periods lacking a statistically meaningful trend and (2) rapid changes in the GST rate which resemble the observed 1998–2012 hiatus. Under the RCP4.5 experiment, all tested models produce warming hiatus periods. However, once radiative forcing exceeds 5 W/m2—about 2°C GST increase—as simulated in the RCP8.5 experiment after 2050, nearly all models produce only positive warming trends. All models show evidence of rapid changes in the GST rate resembling the observed hiatus, showing that the climate variations associated with warming hiatus periods are still evident in the models, even under accelerated warming conditions.


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