Relation between temperature sensitivity to doubled carbon dioxide and the distribution of clouds in current climate models

2008 ◽  
Vol 44 (3) ◽  
pp. 288-299 ◽  
Author(s):  
E. M. Volodin
Eos ◽  
2017 ◽  
Author(s):  
J. Campbell ◽  
Jürgen Kesselmeier ◽  
Dan Yakir ◽  
Joe Berry ◽  
Philippe Peylin ◽  
...  

Current climate models disagree on how much carbon dioxide land ecosystems take up for photosynthesis. Tracking the stronger carbonyl sulfide signal could help.


2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Philipp de Vrese ◽  
Tobias Stacke ◽  
Jeremy Caves Rugenstein ◽  
Jason Goodman ◽  
Victor Brovkin

AbstractSimple and complex climate models suggest a hard snowball – a completely ice-covered planet – is one of the steady-states of Earth’s climate. However, a seemingly insurmountable challenge to the hard-snowball hypothesis lies in the difficulty in explaining how the planet could have exited the glaciated state within a realistic range of atmospheric carbon dioxide concentrations. Here, we use simulations with the Earth system model MPI-ESM to demonstrate that terminal deglaciation could have been triggered by high dust deposition fluxes. In these simulations, deglaciation is not initiated in the tropics, where a strong hydrological cycle constantly regenerates fresh snow at the surface, which limits the dust accumulation and snow aging, resulting in a high surface albedo. Instead, comparatively low precipitation rates in the mid-latitudes in combination with high maximum temperatures facilitate lower albedos and snow dynamics that – for extreme dust fluxes – trigger deglaciation even at present-day carbon dioxide levels.


2016 ◽  
Vol 16 (15) ◽  
pp. 10083-10095 ◽  
Author(s):  
Nicholas A. Davis ◽  
Dian J. Seidel ◽  
Thomas Birner ◽  
Sean M. Davis ◽  
Simone Tilmes

Abstract. Model simulations of future climates predict a poleward expansion of subtropical arid climates at the edges of Earth's tropical belt, which would have significant environmental and societal impacts. This expansion may be related to the poleward shift of the Hadley cell edges, where subsidence stabilizes the atmosphere and suppresses precipitation. Understanding the primary drivers of tropical expansion is hampered by the myriad forcing agents in most model projections of future climate. While many previous studies have examined the response of idealized models to simplified climate forcings and the response of comprehensive climate models to more complex climate forcings, few have examined how comprehensive climate models respond to simplified climate forcings. To shed light on robust processes associated with tropical expansion, here we examine how the tropical belt width, as measured by the Hadley cell edges, responds to simplified forcings in the Geoengineering Model Intercomparison Project (GeoMIP). The tropical belt expands in response to a quadrupling of atmospheric carbon dioxide concentrations and contracts in response to a reduction in the solar constant, with a range of a factor of 3 in the response among nine models. Models with more surface warming and an overall stronger temperature response to quadrupled carbon dioxide exhibit greater tropical expansion, a robust result in spite of inter-model differences in the mean Hadley cell width, parameterizations, and numerical schemes. Under a scenario where the solar constant is reduced to offset an instantaneous quadrupling of carbon dioxide, the Hadley cells remain at their preindustrial width, despite the residual stratospheric cooling associated with elevated carbon dioxide levels. Quadrupled carbon dioxide produces greater tropical belt expansion in the Southern Hemisphere than in the Northern Hemisphere. This expansion is strongest in austral summer and autumn. Ozone depletion has been argued to cause this pattern of changes in observations and model experiments, but the results here indicate that seasonally and hemispherically asymmetric tropical expansion can be a basic response of the general circulation to climate forcings.


Eos ◽  
2020 ◽  
Vol 101 ◽  
Author(s):  
Hannah Thomasy

Scientists are concerned that current climate models do not fully account for the impact of atmospheric conditions on the Greenland Ice Sheet and, consequently, may dramatically underestimate melting.


Author(s):  
Geoff Russell

In Australia, the public got its first mass marketing about climate change and the measures that would be required to avoid it, by TV images of black balloons and Professor Tim Flannery turning off light switches. Journalistic coverage has been similarly dominated by household electricity. More technical literature is generally dominated by the concept of “carbon dioxide equivalence” (CO2eq) as spelled out in the Kyoto protocol. This concept isn't used in climate models because it makes no physical sense. The use of CO2eq and the focus on household electricity has lead to a profound mismatch between the causal factors as understood by climate scientists and causal factors as perceived by the public. “The public” here isn't just the general public, but people of many backgrounds with a strong interest in climate change but without the deep knowledge of professional climate scientists. We need images consistent with climate models, which accurately rank the causes of climate change and guide proposed actions. Such images point to meat as a key focal issue.


2007 ◽  
Vol 20 (18) ◽  
pp. 4548-4571 ◽  
Author(s):  
Tristan S. L’Ecuyer ◽  
Graeme L. Stephens

Abstract The impact of clouds and precipitation on the climate is a strong function of their spatial distribution and microphysical properties, characteristics that depend, in turn, on the environments in which they form. Simulating feedbacks between clouds, precipitation, and their surroundings therefore places an enormous burden on the parameterized physics used in current climate models. This paper uses multisensor observations from the Tropical Rainfall Measuring Mission (TRMM) to assess the representation of the response of regional energy and water cycles in the tropical Pacific to the strong 1998 El Niño event in (Atmospheric Model Intercomparison Project) AMIP-style simulations from the climate models that participated in the Intergovernmental Panel on Climate Change’s (IPCC’s) most recent assessment report. The relationship between model errors and uncertainties in their representation of the impacts of clouds and precipitation on local energy budgets is also explored. With the exception of cloud radiative impacts that are often overestimated in both regions, the responses of atmospheric composition and heating to El Niño are generally captured in the east Pacific where the SST forcing is locally direct. Many models fail, however, to correctly predict the magnitude of induced trends in the west Pacific where the response depends more critically on accurate representation of the zonal atmospheric circulation. As a result, a majority of the models examined do not reproduce the apparent westward transport of energy in the equatorial Pacific during the 1998 El Niño event. Furthermore, the intermodel variability in the responses of precipitation, total heating, and vertical motion is often larger than the intrinsic ENSO signal itself, implying an inherent lack of predictive capability in the ensemble with regard to the response of the mean zonal atmospheric circulation in the tropical Pacific to ENSO. While ENSO does not necessarily provide a proxy for anthropogenic climate change, the results suggest that deficiencies remain in the representation of relationships between radiation, clouds, and precipitation in current climate models that cannot be ignored when interpreting their predictions of future climate.


2021 ◽  
Author(s):  
Miguel Perpina ◽  
Vincent Noel ◽  
Helene Chepfer ◽  
Rodrigo Guzman ◽  
Artem Feofilov

<p><span>Climate models predict a weakening of the tropical atmospheric circulation, more specifically a slowdown of Hadley and Walker circulations. Many climate models predict that global warming will have a major impact on cloud properties, including their geographic and vertical distribution. Climate feedbacks from clouds, which amplify warming when positive, are today the main source of uncertainty in climate forecasts. Tropical clouds play a key role in the redistribution of solar energy and their evolution will likely affect climate. Therefore, it is crucial to better understand how tropical clouds will evolve in a changing climate. Among cloud properties, the vertical distribution is sensitive to climate change. Active sensors integrated into satellites, such as CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization), make it possible to obtain a detailed vertical distribution of clouds. CALIOP measurements and calibration are more stable over time and more precise than passive remote sensing satellite detectors. CALIOP observations can be simulated in the atmospheric conditions predicted by climate models using lidar simulators such as COSP (</span><span>CFMIP Observation Simulator Package). Moreover, </span><span>cloud properties directly drive the Cloud Radiative Effect (CRE). Understanding how models predict cloud vertical distribution will evolve in the future has implications for how models predict the Cloud Radiative Effect (CRE) at the Top of the Atmosphere (TOA) will evolve in the future. </span></p><p><span>The purpose of our study is to compare, firstly, based on satellite observations (GOCCP) and reanalyzes (ERA5), we will establish the relationship between atmospheric dynamic circulation, opaque cloud properties and TOA CRE. Then, we will compare this observed relationship with the one found in climate model simulations of current climate conditions (CESM1 and IPSL-CM6). Finally, we will identify how model biases in present climate conditions influence the cloud feedback spread between models in a warmer climate.</span></p>


2013 ◽  
Vol 10 (5) ◽  
pp. 6807-6845
Author(s):  
M. C. Demirel ◽  
M. J. Booij ◽  
A. Y. Hoekstra

Abstract. The impacts of climate change on the seasonality of low flows are analysed for 134 sub-catchments covering the River Rhine basin upstream of the Dutch–German border. Three seasonality indices for low flows are estimated, namely seasonality ratio (SR), weighted mean occurrence day (WMOD) and weighted persistence (WP). These indices are related to the discharge regime, timing and variability in timing of low flow events respectively. The three indices are estimated from: (1) observed low flows; (2) simulated low flows by the semi distributed HBV model using observed climate; (3) simulated low flows using simulated inputs from seven climate scenarios for the current climate (1964–2007); (4) simulated low flows using simulated inputs from seven climate scenarios for the future climate (2063–2098) including different emission scenarios. These four cases are compared to assess the effects of the hydrological model, forcing by different climate models and different emission scenarios on the three indices. The seven climate scenarios are based on different combinations of four General Circulation Models (GCMs), four Regional Climate Models (RCMs) and three greenhouse gas emission scenarios. Significant differences are found between cases 1 and 2. For instance, the HBV model is prone to overestimate SR and to underestimate WP and simulates very late WMODs compared to the estimated WMODs using observed discharges. Comparing the results of cases 2 and 3, the smallest difference is found in the SR index, whereas large differences are found in the WMOD and WP indices for the current climate. Finally, comparing the results of cases 3 and 4, we found that SR has decreased substantially by 2063–2098 in all seven subbasins of the River Rhine. The lower values of SR for the future climate indicate a shift from winter low flows (SR > 1) to summer low flows (SR < 1) in the two Alpine subbasins. The WMODs of low flows tend to be earlier than for the current climate in all subbasins except for the Middle Rhine and Lower Rhine subbasins. The WP values are slightly larger, showing that the predictability of low flow events increases as the variability in timing decreases for the future climate. From comparison of the uncertainty sources evaluated in this study, it is obvious that the RCM/GCM uncertainty has the largest influence on the variability in timing of low flows for future climate.


2015 ◽  
Vol 6 (1) ◽  
pp. 761-818 ◽  
Author(s):  
N. Mahowald ◽  
F. Lo ◽  
Y. Zheng ◽  
L. Harrison ◽  
C. Funk ◽  
...  

Abstract. The amount of leaves in a plant canopy (measured as leaf area index, LAI) modulates key land–atmosphere interactions, including the exchange of energy, moisture, carbon dioxide (CO2), and other trace gases, and is therefore an essential variable in predicting terrestrial carbon, water, and energy fluxes. The latest generation of Earth system models (ESMs) simulate LAI, as well as provide projections of LAI in the future to improve simulations of biophysical and biogeochemical processes, and for use in climate impact studies. Here we use satellite measurements of LAI to answer the following questions: (1) are the models accurately simulating the mean LAI spatial distribution? (2) Are the models accurately simulating the seasonal cycle in LAI? (3) Are the models correctly simulating the processes driving interannual variability in the current climate? And finally based on this analysis, (4) can we reduce the uncertainty in future projections of LAI by using each model's skill in the current climate? Overall, models are able to capture some of the main characteristics of the LAI mean and seasonal cycle, but all of the models can be improved in one or more regions. Comparison of the modeled and observed interannual variability in the current climate suggested that in high latitudes the models may overpredict increases in LAI based on warming temperature, while in the tropics the models may overpredict the negative impacts of warming temperature on LAI. We expect, however, larger uncertainties in observational estimates of interannual LAI compared to estimates of seasonal or mean LAI. Future projections of LAI by the ESMs are largely optimistic, with only limited regions seeing reductions in LAI. Future projections of LAI in the models are quite different, and are sensitive to climate model projections of precipitation. They also strongly depend on the amount of carbon dioxide fertilization in high latitudes. Based on comparisons between model simulated LAI and observed LAI in the current climate, we can reduce the spread in model future projections, especially in the tropics, by taking into account model skill. In the tropics the models which perform the best in the current climate tend to project a more modest increase in LAI in the future compared to the average of all models. These top performing models also project an increase in the frequency of drought in some regions of the tropics, with droughts being defined as minus one standardized deviation events.


2016 ◽  
Author(s):  
J. C. Hargreaves ◽  
J. D. Annan

Abstract. The mid-PlioceneWarm Period (mPWP) is the most recent interval in which atmospheric carbon dioxide was substantially higher than in modern pre-industrial times. It is, therefore, a potentially valuable target for testing the ability of climate models to simulate climates warmer than the pre-industrial state. The recent Pliocene model inter-comparison Project (PlioMIP) presented boundary conditions for the mPWP, and a protocol for climate model experiments. Here we analyse results from the PlioMIP and, for the first time, discuss the potential for this interval to usefully constrain the equilibrium climate sensitivity. We present an estimate of 1.8–3.6 °C, but there are considerable uncertainties surrounding the analysis. We consider the extent to which these uncertainties may be lessened in the next few years.


Sign in / Sign up

Export Citation Format

Share Document