scholarly journals Aerosol indirect effects in a multi-scale aerosol-climate model PNNL-MMF

2011 ◽  
Vol 11 (1) ◽  
pp. 3399-3459 ◽  
Author(s):  
M. Wang ◽  
S. Ghan ◽  
M. Ovchinnikov ◽  
X. Liu ◽  
R. Easter ◽  
...  
Keyword(s):  
Indirect Effects ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Models ◽  
Anthropogenic Aerosols ◽  
Anthropogenic Aerosol ◽  
Aerosol Indirect Effects ◽  
Multi Scale

Abstract. Much of the large uncertainty in estimates of anthropogenic aerosol effects on climate arises from the multi-scale nature of the interactions between aerosols, clouds and large-scale dynamics, which are difficult to represent in conventional global climate models (GCMs). In this study, we use a multi-scale aerosol-climate model that treats aerosols and clouds across multiple scales to study aerosol indirect effects. This multi-scale aerosol-climate model is an extension of a multi-scale modeling framework (MMF) model that embeds a cloud-resolving model (CRM) within each grid cell of a GCM. The extension allows the explicit simulation of aerosol/cloud interactions in both stratiform and convective clouds on the global scale in a computationally feasible way. Simulated model fields, including liquid water path (LWP), ice water path, cloud fraction, shortwave and longwave cloud forcing, precipitation, water vapor, and cloud droplet number concentration are in agreement with observations. The new model performs quantitatively similar to the previous version of the MMF model in terms of simulated cloud fraction and precipitation. The simulated change in shortwave cloud forcing from anthropogenic aerosols is −0.77 W m−2, which is less than half of that in the host GCM (NCAR CAM5) (−1.79 W m−2) and is also at the low end of the estimates of most other conventional global aerosol-climate models. The smaller forcing in the MMF model is attributed to its smaller increase in LWP from preindustrial conditions (PI) to present day (PD): 3.9% in the MMF, compared with 15.6% increase in LWP in large-scale clouds in CAM5. The much smaller increase in LWP in the MMF is caused by a much smaller response in LWP to a given perturbation in cloud condensation nuclei (CCN) concentrations from PI to PD in the MMF (about one-third of that in CAM5), and, to a lesser extent, by a smaller relative increase in CCN concentrations from PI to PD in the MMF (about 26% smaller than that in CAM5). The smaller relative increase in CCN concentrations in the MMF is caused in part by a smaller increase in aerosol lifetime from PI to PD in the MMF, a positive feedback in aerosol indirect effects induced by cloud lifetime effects. The smaller response in LWP to anthropogenic aerosols in the MMF model is consistent with observations and with high resolution model studies, which may indicate that aerosol indirect effects simulated in conventional global climate models are overestimated and point to the need to use global high resolution models, such as MMF models or global CRMs, to study aerosol indirect effects. The simulated total anthropogenic aerosol effect in the MMF is −1.05 W m−2, which is close to the Murphy et al. (2009) inverse estimate of −1.1 ± 0.4 W m−2 (1σ) based on the examination of the Earth's energy balance. Further improvements in the representation of ice nucleation and low clouds are needed.

scholarly journals Aerosol indirect effects in a multi-scale aerosol-climate model PNNL-MMF

2011 ◽  
Vol 11 (11) ◽  
pp. 5431-5455 ◽  
Author(s):  
M. Wang ◽  
S. Ghan ◽  
M. Ovchinnikov ◽  
X. Liu ◽  
R. Easter ◽  
...  
Keyword(s):  
Indirect Effects ◽  
Climate Models ◽  
Climate Model ◽  
Relative Increase ◽  
Cloud Fraction ◽  
Anthropogenic Aerosols ◽  
Anthropogenic Aerosol ◽  
Aerosol Indirect Effects ◽  
Cloud Forcing ◽  
Multi Scale

Abstract. Much of the large uncertainty in estimates of anthropogenic aerosol effects on climate arises from the multi-scale nature of the interactions between aerosols, clouds and dynamics, which are difficult to represent in conventional general circulation models (GCMs). In this study, we use a multi-scale aerosol-climate model that treats aerosols and clouds across multiple scales to study aerosol indirect effects. This multi-scale aerosol-climate model is an extension of a multi-scale modeling framework (MMF) model that embeds a cloud-resolving model (CRM) within each vertical column of a GCM grid. The extension allows a more physically-based treatment of aerosol-cloud interactions in both stratiform and convective clouds on the global scale in a computationally feasible way. Simulated model fields, including liquid water path (LWP), ice water path, cloud fraction, shortwave and longwave cloud forcing, precipitation, water vapor, and cloud droplet number concentration are in reasonable agreement with observations. The new model performs quantitatively similar to the previous version of the MMF model in terms of simulated cloud fraction and precipitation. The simulated change in shortwave cloud forcing from anthropogenic aerosols is −0.77 W m−2, which is less than half of that (−1.79 W m−2) calculated by the host GCM (NCAR CAM5) with traditional cloud parameterizations and is also at the low end of the estimates of other conventional global aerosol-climate models. The smaller forcing in the MMF model is attributed to a smaller (3.9 %) increase in LWP from preindustrial conditions (PI) to present day (PD) compared with 15.6 % increase in LWP in stratiform clouds in CAM5. The difference is caused by a much smaller response in LWP to a given perturbation in cloud condensation nuclei (CCN) concentrations from PI to PD in the MMF (about one-third of that in CAM5), and, to a lesser extent, by a smaller relative increase in CCN concentrations from PI to PD in the MMF (about 26 % smaller than that in CAM5). The smaller relative increase in CCN concentrations in the MMF is caused in part by a smaller increase in aerosol lifetime from PI to PD in the MMF, a positive feedback in aerosol indirect effects induced by cloud lifetime effects from aerosols. The smaller response in LWP to anthropogenic aerosols in the MMF model is consistent with observations and with high resolution model studies, which may indicate that aerosol indirect effects simulated in conventional global climate models are overestimated and point to the need to use global high resolution models, such as MMF models or global CRMs, to study aerosol indirect effects. The simulated total anthropogenic aerosol effect in the MMF is −1.05 W m−2, which is close to the Murphy et al. (2009) inverse estimate of −1.1±0.4 W m−2 (1σ) based on the examination of the Earth's energy balance. Further improvements in the representation of ice nucleation and low clouds in MMF are needed to refine the aerosol indirect effect estimate.

scholarly journals Saharan Heat Low Biases in CMIP5 Models

2017 ◽  
Vol 30 (8) ◽  
pp. 2867-2884 ◽  
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.

scholarly journals Process-oriented analysis of aircraft soot-cirrus interactions constrains the climate impact of aviation

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Bernd Kärcher ◽  
Fabian Mahrt ◽  
Claudia Marcolli
Keyword(s):  
Radiative Forcing ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Climate Impact ◽  
Global Climate Models ◽  
Soot Particles ◽  
Cloud Ice ◽  
The Impact

AbstractFully accounting for the climate impact of aviation requires a process-level understanding of the impact of aircraft soot particle emissions on the formation of ice clouds. Assessing this impact with the help of global climate models remains elusive and direct observations are lacking. Here we use a high-resolution cirrus column model to investigate how aircraft-emitted soot particles, released after ice crystals sublimate at the end of the lifetime of contrails and contrail cirrus, perturb the formation of cirrus. By allying cloud simulations with a measurement-based description of soot-induced ice formation, we find that only a small fraction (<1%) of the soot particles succeeds in forming cloud ice alongside homogeneous freezing of liquid aerosol droplets. Thus, soot-perturbed and homogeneously-formed cirrus fundamentally do not differ in optical depth. Our results imply that climate model estimates of global radiative forcing from interactions between aircraft soot and large-scale cirrus may be overestimates. The improved scientific understanding reported here provides a process-based underpinning for improved climate model parametrizations and targeted field observations.

Model Uncertainty in Cloud–Circulation Coupling, and Cloud-Radiative Response to Increasing CO2, Linked to Biases in Climatological Circulation

2018 ◽  
Vol 31 (24) ◽  
pp. 10013-10020
Author(s):  
Bernard R. Lipat ◽  
Aiko Voigt ◽  
George Tselioudis ◽  
Lorenzo M. Polvani
Keyword(s):  
Model Uncertainty ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Hadley Cell ◽  
Temperature Structure ◽  
Climatological Circulation

Recent analyses of global climate models suggest that uncertainty in the coupling between midlatitude clouds and the atmospheric circulation contributes to uncertainty in climate sensitivity. However, the reasons behind model differences in the cloud–circulation coupling have remained unclear. Here, we use a global climate model in an idealized aquaplanet setup to show that the Southern Hemisphere climatological circulation, which in many models is biased equatorward, contributes to the model differences in the cloud–circulation coupling. For the same poleward shift of the Hadley cell (HC) edge, models with narrower climatological HCs exhibit stronger midlatitude cloud-induced shortwave warming than models with wider climatological HCs. This cloud-induced radiative warming results predominantly from a subsidence warming that decreases cloud fraction and is stronger for narrower HCs because of a larger meridional gradient in the vertical velocity. A comparison of our aquaplanet results with comprehensive climate models suggests that about half of the model uncertainty in the midlatitude cloud–circulation coupling stems from this impact of the circulation on the large-scale temperature structure of the atmosphere, and thus could be removed by improving the climatological circulation in models. This illustrates how understanding of large-scale dynamics can help reduce uncertainty in clouds and their response to climate change.

scholarly journals Summer Season Squall-Line Simulations: Sensitivity of Gravity Waves to Physics Parameterization and Implications for Their Parameterization in Global Climate Models

2014 ◽  
Vol 71 (9) ◽  
pp. 3376-3391 ◽  
Author(s):  
Claudia Stephan ◽  
M. Joan Alexander
Keyword(s):  
Gravity Waves ◽  
Momentum Flux ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Middle Atmosphere ◽  
Global Climate ◽  
Global Climate Models ◽  
Squall Line ◽  
The Impact

Abstract Gravity waves have important effects on the middle atmosphere circulation, and those generated by convection are prevalent in the tropics and summer midlatitudes. Numerous case studies have been carried out to investigate their characteristics in high-resolution simulations. Here, the impact of the choice of physics parameterizations on the generation and spectral properties of these waves in models is investigated. Using the Weather Research and Forecasting Model (WRF) a summertime squall line over the Great Plains is simulated in a three-dimensional, nonlinear, and nonhydrostatic mesoscale framework. The distributions of precipitation strength and echo tops in the simulations are compared with radar data. Unsurprisingly, those storm features are most sensitive to the microphysics scheme. However, it is found that these variations in storm morphology have little influence on the simulated stratospheric momentum flux spectra. These results support the fundamental idea behind climate model parameterizations: that the large-scale storm conditions can be used to predict the spectrum of gravity wave momentum flux above the storm irrespective of the convective details that coarse-resolution models cannot capture. The simulated spectra are then contrasted with those obtained from a parameterization used in global climate models. The parameterization reproduces the shape of the spectra reasonably well but their magnitudes remain highly sensitive to the peak heating rate within the convective cells.

scholarly journals GCMs Derived Projection of Precipitation and Analysis of Spatio-Temporal Variation over N-W Himalayan Region

2016 ◽  
Vol 9 (1) ◽  
pp. 1-14
Author(s):  
Dharmaveer Singh ◽  
R.D. Gupta ◽  
Sanjay K. Jain
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
Global Climate Models ◽  
Himalayan Region ◽  
Mean Annual Precipitation ◽  
Hadcm3 Model

The ensembles of two Global Climate Models (GCMs) namely, third generation Canadian Coupled Global Climate Model (CGCM3) and Hadley Center Coupled Model, version 3 (HadCM3) are used to project future precipitation in a part of North-Western (N-W) Himalayan region, India. Statistical downscaling method is used to downscale and generate future scenarios of precipitation at station scale from large scale climate variables obtained from GCMs. The observed historical precipitation data has been collected for three metrological stations, namely, Rampur, Sunni and Kasol falling in the basin for further analysis. The future trends and patterns in precipitation under scenarios A2 and A1B for CGCM3 model, and A2 and B2 for HadCM3 model are analyzed for these stations under three different time periods: 2020’s, 2050’s and 2080’s. An overall rise in mean annual precipitation under scenarios A2 and A1B for CGCM3 model have been noticed for future periods: 2020’s, 2050’s and 2080’s. Decrease, in precipitation has been found under A2 and B2 scenarios of HadCM3 model for 2050’s and slight increase for 2080’s periods. Based on the analysis of results, CGCM3 model has been found better for simulation of precipitation in comparison to HadCM3 model.Journal of Hydrology and Meteorology, Vol. 9(1) 2015, p.1-14

scholarly journals Technical Note: On the use of nudging for aerosol-climate model intercomparison studies

2014 ◽  
Vol 14 (7) ◽  
pp. 10311-10343 ◽  
Author(s):  
K. Zhang ◽  
H. Wan ◽  
X. Liu ◽  
S. J. Ghan ◽  
G. J. Kooperman ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Cloud Amount ◽  
Temperature Fields ◽  
Specific Humidity ◽  
Radiation Budget ◽  
Anthropogenic Aerosols ◽  
Anthropogenic Aerosol ◽  
The Impact

Abstract. Nudging is an assimilation technique widely used in the development and evaluation of climate models. Constraining the simulated wind and temperature fields using global weather reanalysis facilitates more straightforward comparison between simulation and observation, and reduces uncertainties associated with natural variabilities of the large-scale circulation. On the other hand, the forcing introduced by nudging can be strong enough to change the basic characteristics of the model climate. In the paper we show that for the Community Atmosphere Model version 5, due to the systematic temperature bias in the standard model and the sensitivity of simulated ice formation to anthropogenic aerosol concentration, nudging towards reanalysis results in substantial reductions in the ice cloud amount and the impact of anthropogenic aerosols on longwave cloud forcing. In order to reduce discrepancies between the nudged and unconstrained simulations and meanwhile take the advantages of nudging, two alternative experimentation methods are evaluated. The first one constrains only the horizontal winds. The second method nudges both winds and temperature, but replaces the long-term climatology of the reanalysis by that of the model. Results show that both methods lead to substantially improved agreement with the free-running model in terms of the top-of-atmosphere radiation budget and cloud ice amount. The wind-only nudging is more convenient to apply, and provides higher correlations of the wind fields, geopotential height and specific humidity between simulation and reanalysis. This suggests nudging the horizontal winds but not temperature is a good strategy for the investigation of aerosol indirect effects through ice clouds, since it provides well-constrained meteorology without strongly perturbing the model's mean climate.

scholarly journals Global Warming Effects on U.S. Hurricane Damage

2011 ◽  
Vol 3 (4) ◽  
pp. 261-268 ◽  
Author(s):  
Kerry Emanuel
Keyword(s):  
Time Series ◽  
Global Warming ◽  
Time Scales ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Models ◽  
Intergovernmental Panel ◽  
Hurricane Damage

Abstract While many studies of the effects of global warming on hurricanes predict an increase in various metrics of Atlantic basin-wide activity, it is less clear that this signal will emerge from background noise in measures of hurricane damage, which depend largely on rare, high-intensity landfalling events and are thus highly volatile compared to basin-wide storm metrics. Using a recently developed hurricane synthesizer driven by large-scale meteorological variables derived from global climate models, 1000 artificial 100-yr time series of Atlantic hurricanes that make landfall along the U.S. Gulf and East Coasts are generated for four climate models and for current climate conditions as well as for the warmer climate of 100 yr hence under the Intergovernmental Panel on Climate Change (IPCC) emissions scenario A1b. These synthetic hurricanes damage a portfolio of insured property according to an aggregate wind-damage function; damage from flooding is not considered here. Assuming that the hurricane climate changes linearly with time, a 1000-member ensemble of time series of property damage was created. Three of the four climate models used produce increasing damage with time, with the global warming signal emerging on time scales of 40, 113, and 170 yr, respectively. It is pointed out, however, that probabilities of damage increase significantly well before such emergence time scales and it is shown that probability density distributions of aggregate damage become appreciably separated from those of the control climate on time scales as short as 25 yr. For the fourth climate model, damages decrease with time, but the signal is weak.

scholarly journals Analyzing the Climate Sensitivity of the HadSM3 Climate Model Using Ensembles from Different but Related Experiments

2009 ◽  
Vol 22 (13) ◽  
pp. 3540-3557 ◽  
Author(s):  
Jonathan Rougier ◽  
David M. H. Sexton ◽  
James M. Murphy ◽  
David Stainforth
Keyword(s):  
Climate Sensitivity ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Models ◽  
Model Parameters ◽  
Entrainment Rate ◽  
Cloud Parameters ◽  
Hadley Centre

Abstract Global climate models (GCMs) contain imprecisely defined parameters that account, approximately, for subgrid-scale physical processes. The response of a GCM to perturbations in its parameters, which is crucial for quantifying uncertainties in simulations of climate change, can—in principle—be assessed by simulating the GCM many times. In practice, however, such “perturbed physics” ensembles are small because GCMs are so expensive to simulate. Statistical tools can help in two ways. First, they can be used to combine ensembles from different but related experiments, increasing the effective number of simulations. Second, they can be used to describe the GCM’s response in ways that cannot be extracted directly from the ensemble(s). The authors combine two experiments to learn about the response of the Hadley Centre Slab Climate Model version 3 (HadSM3) climate sensitivity to 31 model parameters. A Bayesian statistical framework is used in which expert judgments are required to quantify the relationship between the two experiments; these judgments are validated by detailed diagnostics. The authors identify the entrainment rate coefficient of the convection scheme as the most important single parameter and find that this interacts strongly with three of the large-scale-cloud parameters.

scholarly journals Large-scale industrial cloud perturbations confirm bidirectional cloud water responses to anthropogenic aerosols

2020 ◽  
Author(s):  
Heido Trofimov ◽  
Velle Toll
Keyword(s):  
Large Scale ◽  
Satellite Images ◽  
Climate Models ◽  
Hot Spot ◽  
Cloud Water ◽  
Global Climate Models ◽  
Small Scale ◽  
Liquid Water Path ◽  
Anthropogenic Aerosols ◽  
Anthropogenic Aerosol

&lt;p&gt;Aerosols offset poorly quantified fraction of anthropogenic greenhouse gas warming, whereas the aerosol impact on clouds is the most uncertain mechanism of anthropogenic climate forcing. In this research, we extend satellite observations of polluted cloud tracks from Toll et al. (2019, Nature, https://doi.org/10.1038/s41586-019-1423-9) with analysis of larger scale polluted cloud areas detected in MODerate-resolution Imaging Spectroradiometer satellite images. We demonstrate that large-scale anthropogenic aerosol-induced cloud perturbations exist at various major industrial aerosol source regions. The areal extent of the polluted cloud areas detected in MODIS satellite images extended to hundreds by hundreds of kilometres. Polluted clouds detected in satellite images in the global anthropogenic air pollution hot spot of Norilsk, Russia, and in other regions show close compensation between aerosol-induced cloud water increases and decreases. On average, there is relatively weak decrease in cloud water in the large areas with strong decreases in cloud droplet radii. This is in very good agreement with previous results based on small-scale polluted cloud tracks (Toll et al., 2019) and strongly disagrees with unidirectionally increased liquid water path in global climate models.&lt;/p&gt;

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