scholarly journals Cloud-Aerosol-Radiation (CAR) ensemble modeling system

2013 ◽  
Vol 13 (4) ◽  
pp. 10193-10261 ◽  
Author(s):  
X.-Z. Liang ◽  
F. Zhang

Abstract. A Cloud-Aerosol-Radiation (CAR) ensemble modeling system has been developed to incorporate the largest choices of alternative parameterizations for cloud properties (cover, water, radius, optics, geometry), aerosol properties (type, profile, optics), radiation transfers (solar, infrared), and their interactions. These schemes form the most comprehensive collection currently available in the literature, including those used by the world leading general circulation models (GCMs). The CAR provides a unique framework to determine (via intercomparison across all schemes), reduce (via optimized ensemble simulations), and attribute specific key factors for (via physical process sensitivity analyses) the model discrepancies and uncertainties in representing greenhouse gas, aerosol and cloud radiative forcing effects. This study presents a general description of the CAR system and illustrates its capabilities for climate modeling applications, especially in the context of estimating climate sensitivity and uncertainty range caused by cloud-aerosol-radiation interactions. For demonstration purpose, the evaluation is based on several CAR standalone and coupled climate model experiments, each comparing a limited subset of the full system ensemble with up to 896 members. It is shown that the quantification of radiative forcings and climate impacts strongly depends on the choices of the cloud, aerosol and radiation schemes. The prevailing schemes used in current GCMs are likely insufficient in variety and physically biased in a significant way. There exists large room for improvement by optimally combining radiation transfer with cloud property schemes.

2013 ◽  
Vol 13 (16) ◽  
pp. 8335-8364 ◽  
Author(s):  
X.-Z. Liang ◽  
F. Zhang

Abstract. A cloud–aerosol–radiation (CAR) ensemble modeling system has been developed to incorporate the largest choices of alternate parameterizations for cloud properties (cover, water, radius, optics, geometry), aerosol properties (type, profile, optics), radiation transfers (solar, infrared), and their interactions. These schemes form the most comprehensive collection currently available in the literature, including those used by the world's leading general circulation models (GCMs). CAR provides a unique framework to determine (via intercomparison across all schemes), reduce (via optimized ensemble simulations), and attribute specific key factors for (via physical process sensitivity analyses) the model discrepancies and uncertainties in representing greenhouse gas, aerosol, and cloud radiative forcing effects. This study presents a general description of the CAR system and illustrates its capabilities for climate modeling applications, especially in the context of estimating climate sensitivity and uncertainty range caused by cloud–aerosol–radiation interactions. For demonstration purposes, the evaluation is based on several CAR standalone and coupled climate model experiments, each comparing a limited subset of the full system ensemble with up to 896 members. It is shown that the quantification of radiative forcings and climate impacts strongly depends on the choices of the cloud, aerosol, and radiation schemes. The prevailing schemes used in current GCMs are likely insufficient in variety and physically biased in a significant way. There exists large room for improvement by optimally combining radiation transfer with cloud property schemes.


2013 ◽  
Vol 6 (2) ◽  
pp. 3349-3380 ◽  
Author(s):  
P. B. Holden ◽  
N. R. Edwards ◽  
P. H. Garthwaite ◽  
K. Fraedrich ◽  
F. Lunkeit ◽  
...  

Abstract. Many applications in the evaluation of climate impacts and environmental policy require detailed spatio-temporal projections of future climate. To capture feedbacks from impacted natural or socio-economic systems requires interactive two-way coupling but this is generally computationally infeasible with even moderately complex general circulation models (GCMs). Dimension reduction using emulation is one solution to this problem, demonstrated here with the GCM PLASIM-ENTS. Our approach generates temporally evolving spatial patterns of climate variables, considering multiple modes of variability in order to capture non-linear feedbacks. The emulator provides a 188-member ensemble of decadally and spatially resolved (~ 5° resolution) seasonal climate data in response to an arbitrary future CO2 concentration and radiative forcing scenario. We present the PLASIM-ENTS coupled model, the construction of its emulator from an ensemble of transient future simulations, an application of the emulator methodology to produce heating and cooling degree-day projections, and the validation of the results against empirical data and higher-complexity models. We also demonstrate the application to estimates of sea-level rise and associated uncertainty.


2016 ◽  
Vol 29 (12) ◽  
pp. 4487-4508 ◽  
Author(s):  
Haikun Zhao ◽  
Xianan Jiang ◽  
Liguang Wu

During boreal summer, vigorous synoptic-scale wave (SSW) activity, often evident as southeast–northwest-oriented wave trains, prevails over the western North Pacific (WNP). In spite of their active role for regional weather and climate, modeling studies on SSWs are rather limited. In this study, a comprehensive survey on climate model capability in representing the WNP SSWs is conducted by analyzing simulations from 27 recent general circulation models (GCMs). Results suggest that it is challenging for GCMs to realistically represent the observed SSWs. Only 2 models out of the 27 GCMs generally well simulate both the intensity and spatial pattern of the observed SSW mode. Plausible key processes for realistic simulations of SSW activity are further explored. It is illustrated that GCM skill in representing the spatial pattern of the SSW is highly correlated to its skill in simulating the summer mean patterns of the low-level convergence associated with the WNP monsoon trough and conversion from eddy available potential energy (EAPE) to eddy kinetic energy (EKE). Meanwhile, simulated SSW intensity is found to be significantly correlated to the amplitude of 850-hPa vorticity, divergence, and conversion from EAPE to EKE over the WNP. The observed modulations of SSW activity by the Madden–Julian oscillation are able to be captured in several model simulations.


2020 ◽  
Author(s):  
Moetasim Ashfaq ◽  
Tereza Cavazos ◽  
Michelle Reboita ◽  
José Abraham Torres-Alavez ◽  
Eun-Soon Im ◽  
...  

<p>We use an unprecedented ensemble of regional climate model (RCM) projections over seven regional CORDEX domains to provide, for the first time, an RCM-based global view of monsoon changes at various levels of increased greenhouse gas (GHG) forcing. All regional simulations are conducted using RegCM4 at a 25km horizontal grid spacing using lateral and lower boundary forcing from three General Circulation Models (GCMs), which are part of the fifth phase of the Coupled Model Inter-comparison Project (CMIP5). Each simulation covers the period from 1970 through 2100 under two Representative Concentration Pathways (RCP2.6 and RCP8.5). Regional climate simulations exhibit high fidelity in capturing key characteristics of precipitation and atmospheric dynamics across monsoon regions in the historical period. In the future period, regional monsoons exhibit a spatially robust delay in the monsoon onset, an increase in seasonality, and a reduction in the rainy season length at higher levels of radiative forcing. All regions with substantial delays in the monsoon onset exhibit a decrease in pre-monsoon precipitation, indicating a strong connection between pre-monsoon drying and a shift in the monsoon onset. The weakening of latent heat driven atmospheric warming during the pre-monsoon period delays the overturning of atmospheric subsidence in the monsoon regions, which defers their transitioning into deep convective states. Monsoon changes under the RCP2.6 scenario are mostly within the baseline variability. </p>


2014 ◽  
Vol 44 (5) ◽  
pp. 435-469 ◽  
Author(s):  
Nils Randlev Hundebøl ◽  
Kristian H. Nielsen

The Model Evaluation Consortium for Climate Assessment (MECCA) from 1990–95 was an international consortium involving industry partners as well as research institutions in the dual attempt to advance basic science and to impact public and industrial policy-making. Led by the Electric Power Research Institute (EPRI) and the University Corporation for Atmospheric Research (UCAR), MECCA sponsored many numerical experiments on a CRAY-YMP supercomputer dedicated to climate modeling and produced information material with particular emphasis on assessing uncertainties involved in climate modeling for a range of potential users of climate predictions. As it turned out, it was difficult to align the goals of the climate modeling community with those of the climate impacts assessment community. Modelers primarily wanted to advance state-of-the-art General Circulation Models (GCMs). Impact analysts were interested in model evaluation in order to improve confidence levels in impacts predictions. An unconventional organizational scheme in climate science, MECCA also was a “social experiment” in bringing together diverse communities and overcoming mutual skepticism. Climate scientists were skeptical about the policy-making ambitions of MECCA and about industry’s motivation for getting involved in climate science, while industry doubted whether the scientists really made efforts to direct their work toward policy-relevant research questions. MECCA taught some scientists key lessons about the interactions between science and politics, but MECCA as such provided no effective answers to some of the basic skepticisms in the climate regime and consequently failed to reduce uncertainty on climate change issues.


2013 ◽  
Vol 70 (4) ◽  
pp. 1291-1296 ◽  
Author(s):  
Mao-Chang Liang ◽  
Li-Ching Lin ◽  
Ka-Kit Tung ◽  
Yuk L. Yung ◽  
Shan Sun

Abstract The equilibrium climate sensitivity (ECS) has a large uncertainty range among models participating in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) and has recently been presented as “inherently unpredictable.” One way to circumvent this problem is to consider the transient climate response (TCR). However, the TCR among AR4 models also differs by more than a factor of 2. The authors argue that the situation may not necessarily be so pessimistic, because much of the intermodel difference may be due to the fact that the models were run with their oceans at various stages of flux adjustment with their atmosphere. This is shown by comparing multimillennium-long runs of the Goddard Institute for Space Studies model, version E, coupled with the Hybrid Coordinate Ocean Model (GISS-EH) and the Community Climate System Model, version 4 (CCSM4) with what were reported to AR4. The long model runs here reveal the range of variability (~30%) in their TCR within the same model with the same ECS. The commonly adopted remedy of subtracting the “climate drift” is ineffective and adds to the variability. The culprit is the natural variability of the control runs, which exists even at quasi equilibration. Fortunately, for simulations with multidecadal time horizon, robust solutions can be obtained by branching off thousand-year-long control runs that reach “quasi equilibration” using a new protocol, which takes advantage of the fact that forced solutions to radiative forcing forget their initial condition after 30–40 yr and instead depend mostly on the trajectory of the radiative forcing.


2014 ◽  
Vol 7 (1) ◽  
pp. 433-451 ◽  
Author(s):  
P. B. Holden ◽  
N. R. Edwards ◽  
P. H. Garthwaite ◽  
K. Fraedrich ◽  
F. Lunkeit ◽  
...  

Abstract. Many applications in the evaluation of climate impacts and environmental policy require detailed spatio-temporal projections of future climate. To capture feedbacks from impacted natural or socio-economic systems requires interactive two-way coupling, but this is generally computationally infeasible with even moderately complex general circulation models (GCMs). Dimension reduction using emulation is one solution to this problem, demonstrated here with the GCM PLASIM-ENTS (Planet Simulator coupled with the efficient numerical terrestrial scheme). Our approach generates temporally evolving spatial patterns of climate variables, considering multiple modes of variability in order to capture non-linear feedbacks. The emulator provides a 188-member ensemble of decadally and spatially resolved (~ 5° resolution) seasonal climate data in response to an arbitrary future CO2 concentration and non-CO2 radiative forcing scenario. We present the PLASIM-ENTS coupled model, the construction of its emulator from an ensemble of transient future simulations, an application of the emulator methodology to produce heating and cooling degree-day projections, the validation of the simulator (with respect to empirical data) and the validation of the emulator (with respect to high-complexity models). We also demonstrate the application to estimates of sea-level rise and associated uncertainty.


2007 ◽  
Vol 7 (6) ◽  
pp. 1629-1643 ◽  
Author(s):  
A. Gettelman ◽  
D. E. Kinnison

Abstract. Ice supersaturation is important for understanding condensation in the upper troposphere. Many general circulation models however do not permit supersaturation. In this study, a coupled chemistry climate model, the Whole Atmosphere Community Climate Model (WACCM), is modified to include supersaturation for the ice phase. Rather than a study of a detailed parameterization of supersaturation, the study is intended as a sensitivity experiment, to understand the potential impact of supersaturation, and of expected changes to stratospheric water vapor, on climate and chemistry. High clouds decrease and water vapor in the stratosphere increases at a similar rate to the prescribed supersaturation (20% supersaturation increases water vapor by nearly 20%). The stratospheric Brewer-Dobson circulation slows at high southern latitudes, consistent with slight changes in temperature likely induced by changes to cloud radiative forcing. The cloud changes also cause an increase in the seasonal cycle of near tropopause temperatures, increasing them in boreal summer over boreal winter. There are also impacts on chemistry, with small increases in ozone in the tropical lower stratosphere driven by enhanced production. The radiative impact of changing water vapor is dominated by the reduction in cloud forcing associated with fewer clouds (~+0.6 Wm−2) with a small component likely from the radiative effect (greenhouse trapping) of the extra water vapor (~+0.2 Wm−2), consistent with previous work. Representing supersaturation is thus important, and changes to supersaturation resulting from changes in aerosol loading for example, might have a modest impact on global radiative forcing, mostly through changes to clouds. There is no evidence of a strong impact of water vapor on tropical tropopause temperatures.


2019 ◽  
Vol 10 (1) ◽  
pp. 135-155
Author(s):  
Mohammad M. Khabbazan ◽  
Hermann Held

Abstract. In the following, we test the validity of a one-box climate model as an emulator for atmosphere–ocean general circulation models (AOGCMs). The one-box climate model is currently employed in the integrated assessment models FUND, MIND, and PAGE, widely used in policy making. Our findings are twofold. Firstly, when directly prescribing AOGCMs' respective equilibrium climate sensitivities (ECSs) and transient climate responses (TCRs) to the one-box model, global mean temperature (GMT) projections are generically too high by 0.5 K at peak temperature for peak-and-decline forcing scenarios, resulting in a maximum global warming of approximately 2 K. Accordingly, corresponding integrated assessment studies might tend to overestimate mitigation needs and costs. We semi-analytically explain this discrepancy as resulting from the information loss resulting from the reduction of complexity. Secondly, the one-box model offers a good emulator of these AOGCMs (accurate to within 0.1 K for Representative Concentration Pathways, RCPs, namely RCP2.6, RCP4.5, and RCP6.0), provided the AOGCM's ECS and TCR values are universally mapped onto effective one-box counterparts and a certain time horizon (on the order of the time to peak radiative forcing) is not exceeded. Results that are based on the one-box model and have already been published are still just as informative as intended by their respective authors; however, they should be reinterpreted as being influenced by a larger climate response to forcing than intended.


Atmosphere ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1131
Author(s):  
Arturo Corrales-Suastegui ◽  
Osias Ruiz-Alvarez ◽  
José Abraham Torres-Alavez ◽  
Edgar G. Pavia

One simple way to estimate the relationship between air temperature and the energy needed for heating and cooling is to use the concept of degree day. Cooling degree days (CDD) and heating degree days (HDD) are indicators of the energy required to reach comfort levels and are related directly to energy demands. Therefore, using a novel approach, we examine the current conditions and future projections in degree days over Mexico using observations (Livneh and CPC), ERA5 reanalysis, and simulations from the Regional Climate Model (RegCM4). The RegCM4 experiments were driven by different General Circulation Models for two Representative Concentration Pathways scenarios. We consider three 20-year periods as “present conditions” (1995–2014), “near-future conditions” (2041–2060), and “far-future conditions” (2080–2099). The results suggest that in the future, under the lowest radiative forcing scenario there will be a smaller increase (decrease) in CDD (HDD) for the far-future, as compared to the near-future. This could represent the model’s response to the peak of radiative forcing at mid-century and its subsequent decline. For the highest radiative forcing scenario, we found a greater increase (decrease) in CDD (HDD) for the far-future, which could be explained by the response of the RegCM4 to the warming increase projected for 2100.


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