Air-Sea-Aerosol-Cloud Interactions

2008 ◽  
Author(s):  
Djamal Khelif ◽  
Carl Friehe
Keyword(s):  
Aerosol Cloud ◽  
Sea Aerosol ◽  
Aerosol Cloud Interactions

Air-Sea-Aerosol-Cloud Interactions

2009 ◽  
Author(s):  
Djamal Khelif ◽  
Carl Friehe
Keyword(s):  
Aerosol Cloud ◽  
Sea Aerosol ◽  
Aerosol Cloud Interactions

scholarly journals Significant underestimation of radiative forcing by aerosol–cloud interactions derived from satellite-based methods

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Hailing Jia ◽  
Xiaoyan Ma ◽  
Fangqun Yu ◽  
Johannes Quaas
Keyword(s):  
Radiative Forcing ◽  
Cloud Fraction ◽  
Future Climate Change ◽  
Satellite Measurements ◽  
Aerosol Cloud ◽  
Fine Mode ◽  
Sampling Biases ◽  
Aerosol Cloud Interactions ◽  
Significant Underestimation ◽  
Weak Satellite

AbstractSatellite-based estimates of radiative forcing by aerosol–cloud interactions (RFaci) are consistently smaller than those from global models, hampering accurate projections of future climate change. Here we show that the discrepancy can be substantially reduced by correcting sampling biases induced by inherent limitations of satellite measurements, which tend to artificially discard the clouds with high cloud fraction. Those missed clouds exert a stronger cooling effect, and are more sensitive to aerosol perturbations. By accounting for the sampling biases, the magnitude of RFaci (from −0.38 to −0.59 W m−2) increases by 55 % globally (133 % over land and 33 % over ocean). Notably, the RFaci further increases to −1.09 W m−2 when switching total aerosol optical depth (AOD) to fine-mode AOD that is a better proxy for CCN than AOD. In contrast to previous weak satellite-based RFaci, the improved one substantially increases (especially over land), resolving a major difference with models.

scholarly journals 100 Years of Progress in Cloud Physics, Aerosols, and Aerosol Chemistry Research

2019 ◽  
Vol 59 ◽  
pp. 11.1-11.72 ◽  
Author(s):  
Sonia M. Kreidenweis ◽  
Markus Petters ◽  
Ulrike Lohmann
Keyword(s):  
Radiative Forcing ◽  
Cloud Microphysics ◽  
Climate System ◽  
Mitigation Strategies ◽  
Climate Projections ◽  
Weather Modification ◽  
Theoretical Understanding ◽  
Aerosol Cloud ◽  
Chemistry Research ◽  
Aerosol Cloud Interactions

Abstract This chapter reviews the history of the discovery of cloud nuclei and their impacts on cloud microphysics and the climate system. Pioneers including John Aitken, Sir John Mason, Hilding Köhler, Christian Junge, Sean Twomey, and Kenneth Whitby laid the foundations of the field. Through their contributions and those of many others, rapid progress has been made in the last 100 years in understanding the sources, evolution, and composition of the atmospheric aerosol, the interactions of particles with atmospheric water vapor, and cloud microphysical processes. Major breakthroughs in measurement capabilities and in theoretical understanding have elucidated the characteristics of cloud condensation nuclei and ice nucleating particles and the role these play in shaping cloud microphysical properties and the formation of precipitation. Despite these advances, not all their impacts on cloud formation and evolution have been resolved. The resulting radiative forcing on the climate system due to aerosol–cloud interactions remains an unacceptably large uncertainty in future climate projections. Process-level understanding of aerosol–cloud interactions remains insufficient to support technological mitigation strategies such as intentional weather modification or geoengineering to accelerating Earth-system-wide changes in temperature and weather patterns.

scholarly journals Ocean Emission Effects on Aerosol-Cloud Interactions: Insights from Two Case Studies

2010 ◽  
Vol 2010 ◽  
pp. 1-9 ◽  
Author(s):  
Armin Sorooshian ◽  
Hanh T. Duong
Keyword(s):  
Case Studies ◽  
Field Experiments ◽  
Remote Sensing Data ◽  
Anthropogenic Pollution ◽  
Cloud Microphysics ◽  
Marine Aerosols ◽  
Aerosol Cloud ◽  
First Case ◽  
Wide Range ◽  
Aerosol Cloud Interactions

Two case studies are discussed that evaluate the effect of ocean emissions on aerosol-cloud interactions. A review of the first case study from the eastern Pacific Ocean shows that simultaneous aircraft and space-borne observations are valuable in detecting links between ocean biota emissions and marine aerosols, but that the effect of the former on cloud microphysics is less clear owing to interference from background anthropogenic pollution and the difficulty with field experiments in obtaining a wide range of aerosol conditions to robustly quantify ocean effects on aerosol-cloud interactions. To address these limitations, a second case was investigated using remote sensing data over the less polluted Southern Ocean region. The results indicate that cloud drop size is reduced more for a fixed increase in aerosol particles during periods of higher ocean chlorophyll A. Potential biases in the results owing to statistical issues in the data analysis are discussed.

scholarly journals Evaluation of modeled aerosol-cloud interactions using data from the ORACLES and LASIC field campaigns

2020 ◽  
Author(s):  
Calvin Howes ◽  
Pablo Saide ◽  
Paquita Zuidema ◽  
Jianhao Zhang ◽  
Michael Diamond ◽  
...  
Keyword(s):  
Aerosol Cloud ◽  
Field Campaigns ◽  
Using Data ◽  
Aerosol Cloud Interactions

Evaluation of Scalar Advection Schemes in the Advanced Research WRF Model Using Large-Eddy Simulations of Aerosol–Cloud Interactions

2009 ◽  
Vol 137 (8) ◽  
pp. 2547-2558 ◽  
Author(s):  
Hailong Wang ◽  
William C. Skamarock ◽  
Graham Feingold
Keyword(s):  
Large Eddy Simulations ◽  
Numerical Dispersion ◽  
Integration Scheme ◽  
Cloud Albedo ◽  
Flux Limiter ◽  
Aerosol Cloud ◽  
Advection Schemes ◽  
Large Eddy ◽  
Runge Kutta ◽  
Aerosol Cloud Interactions

Abstract In the Advanced Research Weather Research and Forecasting Model (ARW), versions 3.0 and earlier, advection of scalars was performed using the Runge–Kutta time-integration scheme with an option of using a positive-definite (PD) flux limiter. Large-eddy simulations of aerosol–cloud interactions using the ARW model are performed to evaluate the advection schemes. The basic Runge–Kutta scheme alone produces spurious oscillations and negative values in scalar mixing ratios because of numerical dispersion errors. The PD flux limiter assures positive definiteness but retains the oscillations with an amplification of local maxima by up to 20% in the tests. These numerical dispersion errors contaminate active scalars directly through the advection process and indirectly through physical and dynamical feedbacks, leading to a misrepresentation of cloud physical and dynamical processes. A monotonic flux limiter is introduced to correct the generally accurate but dispersive solutions given by high-order Runge–Kutta scheme. The monotonic limiter effectively minimizes the dispersion errors with little significant enhancement of numerical diffusion errors. The improvement in scalar advection using the monotonic limiter is discussed in the context of how the different advection schemes impact the quantification of aerosol–cloud interactions. The PD limiter results in 20% (10%) fewer cloud droplets and 22% (5%) smaller cloud albedo than the monotonic limiter under clean (polluted) conditions. Underprediction of cloud droplet number concentration by the PD limiter tends to trigger the early formation of precipitation in the clean case, leading to a potentially large impact on cloud albedo change.

scholarly journals The Dynamical Core, Physical Parameterizations, and Basic Simulation Characteristics of the Atmospheric Component AM3 of the GFDL Global Coupled Model CM3

2011 ◽  
Vol 24 (13) ◽  
pp. 3484-3519 ◽  
Author(s):  
Leo J. Donner ◽  
Bruce L. Wyman ◽  
Richard S. Hemler ◽  
Larry W. Horowitz ◽  
Yi Ming ◽  
...  
Keyword(s):  
Twentieth Century ◽  
Sea Ice ◽  
System Component ◽  
Dynamical Core ◽  
Atmospheric Component ◽  
Clear Sky ◽  
Aerosol Cloud ◽  
Droplet Activation ◽  
Aerosol Cloud Interactions ◽  
Physical Parameterizations

Abstract The Geophysical Fluid Dynamics Laboratory (GFDL) has developed a coupled general circulation model (CM3) for the atmosphere, oceans, land, and sea ice. The goal of CM3 is to address emerging issues in climate change, including aerosol–cloud interactions, chemistry–climate interactions, and coupling between the troposphere and stratosphere. The model is also designed to serve as the physical system component of earth system models and models for decadal prediction in the near-term future—for example, through improved simulations in tropical land precipitation relative to earlier-generation GFDL models. This paper describes the dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component (AM3) of this model. Relative to GFDL AM2, AM3 includes new treatments of deep and shallow cumulus convection, cloud droplet activation by aerosols, subgrid variability of stratiform vertical velocities for droplet activation, and atmospheric chemistry driven by emissions with advective, convective, and turbulent transport. AM3 employs a cubed-sphere implementation of a finite-volume dynamical core and is coupled to LM3, a new land model with ecosystem dynamics and hydrology. Its horizontal resolution is approximately 200 km, and its vertical resolution ranges approximately from 70 m near the earth’s surface to 1 to 1.5 km near the tropopause and 3 to 4 km in much of the stratosphere. Most basic circulation features in AM3 are simulated as realistically, or more so, as in AM2. In particular, dry biases have been reduced over South America. In coupled mode, the simulation of Arctic sea ice concentration has improved. AM3 aerosol optical depths, scattering properties, and surface clear-sky downward shortwave radiation are more realistic than in AM2. The simulation of marine stratocumulus decks remains problematic, as in AM2. The most intense 0.2% of precipitation rates occur less frequently in AM3 than observed. The last two decades of the twentieth century warm in CM3 by 0.32°C relative to 1881–1920. The Climate Research Unit (CRU) and Goddard Institute for Space Studies analyses of observations show warming of 0.56° and 0.52°C, respectively, over this period. CM3 includes anthropogenic cooling by aerosol–cloud interactions, and its warming by the late twentieth century is somewhat less realistic than in CM2.1, which warmed 0.66°C but did not include aerosol–cloud interactions. The improved simulation of the direct aerosol effect (apparent in surface clear-sky downward radiation) in CM3 evidently acts in concert with its simulation of cloud–aerosol interactions to limit greenhouse gas warming.

scholarly journals Implementation of aerosol–cloud interactions in the regional atmosphere–aerosol model COSMO-MUSCAT(5.0) and evaluation using satellite data

2017 ◽  
Vol 10 (6) ◽  
pp. 2231-2246 ◽  
Author(s):  
Sudhakar Dipu ◽  
Johannes Quaas ◽  
Ralf Wolke ◽  
Jens Stoll ◽  
Andreas Mühlbauer ◽  
...  
Keyword(s):  
Satellite Data ◽  
Transport Model ◽  
Cloud Condensation Nuclei ◽  
Cloud Droplet ◽  
Atmospheric Model ◽  
Horizontal Resolution ◽  
Small Scale ◽  
Aerosol Model ◽  
Aerosol Cloud ◽  
Aerosol Cloud Interactions

Abstract. The regional atmospheric model Consortium for Small-scale Modeling (COSMO) coupled to the Multi-Scale Chemistry Aerosol Transport model (MUSCAT) is extended in this work to represent aerosol–cloud interactions. Previously, only one-way interactions (scavenging of aerosol and in-cloud chemistry) and aerosol–radiation interactions were included in this model. The new version allows for a microphysical aerosol effect on clouds. For this, we use the optional two-moment cloud microphysical scheme in COSMO and the online-computed aerosol information for cloud condensation nuclei concentrations (Cccn), replacing the constant Cccn profile. In the radiation scheme, we have implemented a droplet-size-dependent cloud optical depth, allowing now for aerosol–cloud–radiation interactions. To evaluate the models with satellite data, the Cloud Feedback Model Intercomparison Project Observation Simulator Package (COSP) has been implemented. A case study has been carried out to understand the effects of the modifications, where the modified modeling system is applied over the European domain with a horizontal resolution of 0.25°  ×  0.25°. To reduce the complexity in aerosol–cloud interactions, only warm-phase clouds are considered. We found that the online-coupled aerosol introduces significant changes for some cloud microphysical properties. The cloud effective radius shows an increase of 9.5 %, and the cloud droplet number concentration is reduced by 21.5 %.

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