scholarly journals Evaluation of aerosol and cloud properties in three climate models using MODIS observations and its corresponding COSP simulator, and their application in aerosol-cloud interaction

2019 ◽  
Author(s):  
Giulia Saponaro ◽  
Moa K. Sporre ◽  
David Neubauer ◽  
Harri Kokkola ◽  
Pekka Kolmonen ◽  
...  
Keyword(s):  
Optical Depth ◽  
Climate Models ◽  
Cloud Droplet ◽  
Global Scale ◽  
Cloud Optical Depth ◽  
Aerosol Cloud ◽  
Cloud Properties ◽  
Direct Model ◽  
Land Surfaces ◽  
Aerosol Cloud Interactions

Abstract. The evaluation of modeling diagnostics with appropriate observations is an important task that establishes the capabilities and reliability of models. In this study we compare aerosol and cloud properties obtained from three different climate models ECHAM-HAM, ECHAM-HAM-SALSA, and NorESM with satellite observations using MOderate Resolution Imaging Spectrometer (MODIS) data. The simulator MODIS-COSP version 1.4 was implemented into the climate models to obtain MODIS-like cloud diagnostics, thus enabling model to model and model to satellite comparisons. Cloud droplet number concentrations (CDNC) are derived identically from MODIS-COSP simulated and MODIS-retrieved values of cloud optical depth and effective radius. For CDNC, the models capture the observed spatial distribution of higher values typically found near the coasts, downwind of the major continents, and lower values over the remote ocean and land areas. However, the COSP-simulated CDNC values are higher than those observed, whilst the direct model CDNC output is significantly lower than the MODIS-COSP diagnostics. NorESM produces large spatial biases for ice cloud properties and thick clouds over land. Despite having identical cloud modules, ECHAM-HAM and ECHAM-HAM-SALSA diverge in their representation of spatial and vertical distribution of clouds. From the spatial distributions of aerosol optical depth (AOD) and aerosol index (AI), we find that NorESM shows large biases for AOD over bright land surfaces, while discrepancies between ECHAM-HAM and ECHAM-HAM-SALSA can be observed mainly over oceans. Overall, the AIs from the different models are in good agreement globally, with higher negative biases on the Northern Hemisphere. We computed the aerosol-cloud interactions as the sensitivity of dln(CDNC)/dln(AI) on a global scale. However, one year of data may be considered not enough to assess the similarity or dissimilarities of the models due to large temporal variability in cloud properties. This study shows how simulators facilitate the evaluation of cloud properties and expose model deficiencies which are necessary steps to further improve the parametrization in climate models.

scholarly journals Evaluation of aerosol and cloud properties in three climate models using MODIS observations and its corresponding COSP simulator, as well as their application in aerosol–cloud interactions

2020 ◽  
Vol 20 (3) ◽  
pp. 1607-1626 ◽  
Author(s):  
Giulia Saponaro ◽  
Moa K. Sporre ◽  
David Neubauer ◽  
Harri Kokkola ◽  
Pekka Kolmonen ◽  
...  
Keyword(s):  
Optical Depth ◽  
Climate Models ◽  
Cloud Droplet ◽  
Global Scale ◽  
Cloud Optical Depth ◽  
Aerosol Cloud ◽  
Cloud Properties ◽  
Direct Model ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Aerosol Cloud Interactions

Abstract. The evaluation of modelling diagnostics with appropriate observations is an important task that establishes the capabilities and reliability of models. In this study we compare aerosol and cloud properties obtained from three different climate models (ECHAM-HAM, ECHAM-HAM-SALSA, and NorESM) with satellite observations using Moderate Resolution Imaging Spectroradiometer (MODIS) data. The simulator MODIS-COSP version 1.4 was implemented into the climate models to obtain MODIS-like cloud diagnostics, thus enabling model-to-model and model-to-satellite comparisons. Cloud droplet number concentrations (CDNCs) are derived identically from MODIS-COSP-simulated and MODIS-retrieved values of cloud optical depth and effective radius. For CDNC, the models capture the observed spatial distribution of higher values typically found near the coasts, downwind of the major continents, and lower values over the remote ocean and land areas. However, the COSP-simulated CDNC values are higher than those observed, whilst the direct model CDNC output is significantly lower than the MODIS-COSP diagnostics. NorESM produces large spatial biases for ice cloud properties and thick clouds over land. Despite having identical cloud modules, ECHAM-HAM and ECHAM-HAM-SALSA diverge in their representation of spatial and vertical distributions of clouds. From the spatial distributions of aerosol optical depth (AOD) and aerosol index (AI), we find that NorESM shows large biases for AOD over bright land surfaces, while discrepancies between ECHAM-HAM and ECHAM-HAM-SALSA can be observed mainly over oceans. Overall, the AIs from the different models are in good agreement globally, with higher negative biases in the Northern Hemisphere. We evaluate the aerosol–cloud interactions by computing the sensitivity parameter ACICDNC=dln⁡(CDNC)/dln⁡(AI) on a global scale. However, 1 year of data may be considered not enough to assess the similarity or dissimilarities of the models due to large temporal variability in cloud properties. This study shows how simulators facilitate the evaluation of cloud properties and expose model deficiencies, which are necessary steps to further improve the parameterisation in climate models.

scholarly journals Investigation of the adiabatic assumption for estimating cloud micro- and macrophysical properties from satellite and ground observations

2016 ◽  
Vol 16 (2) ◽  
pp. 933-952 ◽  
Author(s):  
D. Merk ◽  
H. Deneke ◽  
B. Pospichal ◽  
P. Seifert
Keyword(s):  
Optical Depth ◽  
Microwave Radiometer ◽  
Cloud Droplet ◽  
Satellite Observations ◽  
Data Set ◽  
Cloud Optical Depth ◽  
Cloud Radar ◽  
Aerosol Cloud ◽  
Droplet Concentration ◽  
Aerosol Cloud Interactions

Abstract. Cloud properties from both ground-based as well as from geostationary passive satellite observations have been used previously for diagnosing aerosol–cloud interactions. In this investigation, a 2-year data set together with four selected case studies are analyzed with the aim of evaluating the consistency and limitations of current ground-based and satellite-retrieved cloud property data sets. The typically applied adiabatic cloud profile is modified using a sub-adiabatic factor to account for entrainment within the cloud. Based on the adiabatic factor obtained from the combination of ground-based cloud radar, ceilometer and microwave radiometer, we demonstrate that neither the assumption of a completely adiabatic cloud nor the assumption of a constant sub-adiabatic factor is fulfilled (mean adiabatic factor 0.63 ± 0.22). As cloud adiabaticity is required to estimate the cloud droplet number concentration but is not available from passive satellite observations, an independent method to estimate the adiabatic factor, and thus the influence of mixing, would be highly desirable for global-scale analyses. Considering the radiative effect of a cloud described by the sub-adiabatic model, we focus on cloud optical depth and its sensitivities. Ground-based estimates are here compared vs. cloud optical depth retrieved from the Meteosat SEVIRI satellite instrument resulting in a bias of −4 and a root mean square difference of 16. While a synergistic approach based on the combination of ceilometer, cloud radar and microwave radiometer enables an estimate of the cloud droplet concentration, it is highly sensitive to radar calibration and to assumptions about the moments of the droplet size distribution. Similarly, satellite-based estimates of cloud droplet concentration are uncertain. We conclude that neither the ground-based nor satellite-based cloud retrievals applied here allow a robust estimate of cloud droplet concentration, which complicates its use for the study of aerosol–cloud interactions.

scholarly journals Constraining the instantaneous aerosol influence on cloud albedo

2017 ◽  
Vol 114 (19) ◽  
pp. 4899-4904 ◽  
Author(s):  
Edward Gryspeerdt ◽  
Johannes Quaas ◽  
Sylvaine Ferrachat ◽  
Andrew Gettelman ◽  
Steven Ghan ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Cloud Condensation Nuclei ◽  
Cloud Droplet ◽  
Anthropogenic Aerosol ◽  
Cloud Albedo ◽  
Aerosol Cloud ◽  
Cloud Properties ◽  
Aerosol Cloud Interactions ◽  
Aerosol Properties

Much of the uncertainty in estimates of the anthropogenic forcing of climate change comes from uncertainties in the instantaneous effect of aerosols on cloud albedo, known as the Twomey effect or the radiative forcing from aerosol–cloud interactions (RFaci), a component of the total or effective radiative forcing. Because aerosols serving as cloud condensation nuclei can have a strong influence on the cloud droplet number concentration (Nd), previous studies have used the sensitivity of theNdto aerosol properties as a constraint on the strength of the RFaci. However, recent studies have suggested that relationships between aerosol and cloud properties in the present-day climate may not be suitable for determining the sensitivity of theNdto anthropogenic aerosol perturbations. Using an ensemble of global aerosol–climate models, this study demonstrates how joint histograms betweenNdand aerosol properties can account for many of the issues raised by previous studies. It shows that if the anthropogenic contribution to the aerosol is known, the RFaci can be diagnosed to within 20% of its actual value. The accuracy of different aerosol proxies for diagnosing the RFaci is investigated, confirming that using the aerosol optical depth significantly underestimates the strength of the aerosol–cloud interactions in satellite data.

scholarly journals The source of discrepancies in aerosol–cloud–precipitation interactions between GCM and A-Train retrievals

2016 ◽  
Vol 16 (23) ◽  
pp. 15413-15424 ◽  
Author(s):  
Takuro Michibata ◽  
Kentaroh Suzuki ◽  
Yousuke Sato ◽  
Toshihiko Takemura
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Circulation Model ◽  
Cloud Droplet ◽  
Systematic Difference ◽  
Liquid Water Path ◽  
Light Rain ◽  
Aerosol Cloud ◽  
Nonlinear Complexity ◽  
Aerosol Cloud Interactions

Abstract. Aerosol–cloud interactions are one of the most uncertain processes in climate models due to their nonlinear complexity. A key complexity arises from the possibility that clouds can respond to perturbed aerosols in two opposite ways, as characterized by the traditional “cloud lifetime” hypothesis and more recent “buffered system” hypothesis. Their importance in climate simulations remains poorly understood. Here we investigate the response of the liquid water path (LWP) to aerosol perturbations for warm clouds from the perspective of general circulation model (GCM) and A-Train remote sensing, through process-oriented model evaluations. A systematic difference is found in the LWP response between the model results and observations. The model results indicate a near-global uniform increase of LWP with increasing aerosol loading, while the sign of the response of the LWP from the A-Train varies from region to region. The satellite-observed response of the LWP is closely related to meteorological and/or macrophysical factors, in addition to the microphysics. The model does not reproduce this variability of cloud susceptibility (i.e., sensitivity of LWP to perturbed aerosols) because the parameterization of the autoconversion process assumes only suppression of rain formation in response to increased cloud droplet number, and does not consider macrophysical aspects that serve as a mechanism for the negative responses of the LWP via enhancements of evaporation and precipitation. Model biases are also found in the precipitation microphysics, which suggests that the model generates rainwater readily even when little cloud water is present. This essentially causes projections of unrealistically frequent and light rain, with high cloud susceptibilities to aerosol perturbations.

scholarly journals Reducing uncertainties in satellite estimates of aerosol-cloud interactions over the subtropical ocean by integrating vertically resolved aerosol observations

2019 ◽  
Author(s):  
David Painemal ◽  
Fu-Lung Chang ◽  
Richard Ferrare ◽  
Sharon Burton ◽  
Zhujun Li ◽  
...  
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Cloud Condensation Nuclei ◽  
Cloud Droplet ◽  
Global Climate Models ◽  
Orthogonal Polarization ◽  
Near Surface ◽  
Aerosol Cloud ◽  
Error Characterization ◽  
Aerosol Cloud Interactions

Abstract. Satellite quantification of aerosol effects on clouds relies on aerosol optical depth (AOD) as a proxy for aerosol concentration or cloud condensation nuclei (CCN). However, the lack of error characterization of satellite-based results hampers their use for the evaluation and improvement of global climate models. We show that the use of AOD for assessing aerosol-cloud interactions (ACI) is inadequate over vast oceanic areas in the subtropics. Instead, we postulate that a more physical approach that consists of matching vertically resolved aerosol data from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite at the cloud-layer height with Aqua Moderate-resolution Imaging Spectroradiometer (MODIS) cloud retrievals reduces uncertainties in satellite-based ACI estimates. Combined aerosol extinction coefficients (σ) below cloud-top (σBC) from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and cloud droplet number concentrations (Nd) from Aqua-MODIS yield high correlations across a broad range of σBC values, with σBC quartile correlations > 0.78. In contrast, CALIOP-based AOD yields correlations with MODIS Nd of less than 0.62 for the two lower AOD quartiles. Moreover, σBC explains 41 % of the spatial variance in MODIS Nd, whereas AOD only explains 17 %, primarily caused by the lack of spatial covariability in the eastern Pacific. Compared with σBC, near-surface σ weakly correlates in space with MODIS Nd, accounting for a 16 % variance. It is concluded that the linear regression calculated from ln(Nd)−ln(σBC) (the standard method for quantifying ACI) is more physically meaningful than that derived from the Nd−AOD pair.

Observed Southern Ocean Cloud Properties and Shortwave Reflection. Part II: Phase Changes and Low Cloud Feedback*

2014 ◽  
Vol 27 (23) ◽  
pp. 8858-8868 ◽  
Author(s):  
Daniel T. McCoy ◽  
Dennis L. Hartmann ◽  
Daniel P. Grosvenor
Keyword(s):  
Solar Radiation ◽  
Optical Depth ◽  
Climate Models ◽  
Phase Changes ◽  
Shortwave Radiation ◽  
Cloud Optical Depth ◽  
Cloud Properties ◽  
Low Cloud ◽  
Model Transition ◽  
Comparable Magnitude

Abstract Climate models produce an increase in cloud optical depth in midlatitudes associated with climate warming, but the magnitude of this increase and its impact on reflected solar radiation vary from model to model. Transition from ice to liquid in midlatitude clouds is thought to be one mechanism for producing increased cloud optical depth. Here observations of cloud properties are used from a suite of remote sensing instruments to estimate the effect of conversion of ice to liquid associated with warming on reflected solar radiation in the latitude band from 40° to 60°S. The calculated increase in upwelling shortwave radiation (SW↑) is found to be important and of comparable magnitude to the increase in SW↑ associated with warming-induced increases of optical depth in climate models. The region where the authors' estimate increases SW↑ extends farther equatorward than the region where optical depth increases with warming in models. This difference is likely caused by other mechanisms at work in the models but is also sensitive to the amount of ice present in climate models and its susceptibility to warming.

scholarly journals A long-term study of aerosol–cloud interactions and their radiative effect at a mid latitude continental site using ground-based measurements

2016 ◽  
Author(s):  
Elisa T. Sena ◽  
Allison McComiskey ◽  
Graham Feingold
Keyword(s):  
Great Plains ◽  
Climate Models ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Radiative Effect ◽  
Aerosol Cloud ◽  
Long Term Study ◽  
Cloud Radiative Effect ◽  
Aerosol Cloud Interactions

Abstract. Empirical estimates of the microphysical response of cloud droplet size distribution to aerosol perturbations are commonly used to constrain aerosol–cloud interactions in climate models. Instead of empirical microphysical estimates, here macroscopic variables are analyzed to address the influences of aerosol particles and meteorological descriptors on instantaneous cloud albedo and radiative effect of shallow liquid water clouds. Long-term ground-based measurements from the Atmospheric Radiation Measurement (ARM) Program over the Southern Great Plains are used. A broad statistical analysis was performed on 14-years of coincident measurements of low clouds, aerosol and meteorological properties. Two cases representing conflicting results regarding the relationship between the aerosol and the cloud radiative effect were selected and studied in greater detail. Microphysical estimates are shown to be very uncertain and to depend strongly on the methodology, retrieval technique, and averaging scale. For this continental site, the results indicate that the influence of aerosol on shallow cloud radiative effect and albedo is weak and that macroscopic cloud properties and dynamics play a much larger role in determining the instantaneous cloud radiative effect compared to microphysical effects.

scholarly journals The hemispheric contrast in cloud microphysical properties constrains aerosol forcing

2020 ◽  
Vol 117 (32) ◽  
pp. 18998-19006 ◽  
Author(s):  
Isabel L. McCoy ◽  
Daniel T. McCoy ◽  
Robert Wood ◽  
Leighton Regayre ◽  
Duncan Watson-Parris ◽  
...  
Keyword(s):  
Southern Ocean ◽  
Northern Hemisphere ◽  
Radiative Forcing ◽  
Climate Models ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Global Climate Models ◽  
Aerosol Cloud ◽  
Cloud Droplet Number Concentration ◽  
Aerosol Cloud Interactions

The change in planetary albedo due to aerosol−cloud interactions during the industrial era is the leading source of uncertainty in inferring Earth’s climate sensitivity to increased greenhouse gases from the historical record. The variable that controls aerosol−cloud interactions in warm clouds is droplet number concentration. Global climate models demonstrate that the present-day hemispheric contrast in cloud droplet number concentration between the pristine Southern Hemisphere and the polluted Northern Hemisphere oceans can be used as a proxy for anthropogenically driven change in cloud droplet number concentration. Remotely sensed estimates constrain this change in droplet number concentration to be between 8 cm−3and 24 cm−3. By extension, the radiative forcing since 1850 from aerosol−cloud interactions is constrained to be −1.2 W⋅m−2to −0.6 W⋅m−2. The robustness of this constraint depends upon the assumption that pristine Southern Ocean droplet number concentration is a suitable proxy for preindustrial concentrations. Droplet number concentrations calculated from satellite data over the Southern Ocean are high in austral summer. Near Antarctica, they reach values typical of Northern Hemisphere polluted outflows. These concentrations are found to agree with several in situ datasets. In contrast, climate models show systematic underpredictions of cloud droplet number concentration across the Southern Ocean. Near Antarctica, where precipitation sinks of aerosol are small, the underestimation by climate models is particularly large. This motivates the need for detailed process studies of aerosol production and aerosol−cloud interactions in pristine environments. The hemispheric difference in satellite estimated cloud droplet number concentration implies preindustrial aerosol concentrations were higher than estimated by most models.

scholarly journals The Influence of Entrainment and Mixing Assumption on Aerosol–Cloud Interactions in Marine Stratocumulus

2009 ◽  
Vol 66 (5) ◽  
pp. 1450-1464 ◽  
Author(s):  
Adrian A. Hill ◽  
Graham Feingold ◽  
Hongli Jiang
Keyword(s):  
Optical Depth ◽  
Relative Sensitivity ◽  
Number Concentration ◽  
Liquid Water Path ◽  
Marine Stratocumulus ◽  
Cloud Optical Depth ◽  
Aerosol Cloud ◽  
Aerosol Cloud Interactions ◽  
Entrainment Effect ◽  
The Impact

Abstract This study uses large-eddy simulation with bin microphysics to investigate the influence of entrainment and mixing on aerosol–cloud interactions in the context of idealized, nocturnal, nondrizzling marine stratocumulus (Sc). Of particular interest are (i) an evaporation–entrainment effect and a sedimentation–entrainment effect that result from increasing aerosol concentrations and (ii) the nature of mixing between clear and cloudy air, where homogeneous and extreme inhomogeneous mixing represent the bounding mixing types. Simulations are performed at low resolution (Δz = 20 m; Δx, y = 40 m) and high resolution (Δz = 10 m; Δx, y = 20 m). It is demonstrated that an increase in aerosol from clean conditions (100 cm−3) to polluted conditions (1000 cm−3) produces both an evaporation–entrainment and a sedimentation–entrainment effect, which couple to cause about a 10% decrease in liquid water path (LWP) when all warm microphysical processes are included. These dynamical effects are insensitive to both the resolutions tested and the mixing assumption. Regardless of resolution, assuming extreme inhomogeneous rather than homogeneous mixing results in a small reduction in cloud-averaged drop number concentration, a small increase in cloud drop effective radius, and ∼1% decrease in cloud optical depth. For the case presented, these small changes play a negligible role when compared to the impact of increasing aerosol and the associated entrainment effects. Finally, it is demonstrated that although increasing resolution causes an increase in LWP and number concentration, the relative sensitivity of cloud optical depth to changes in aerosol is unaffected by resolution.

scholarly journals Reducing uncertainties in satellite estimates of aerosol–cloud interactions over the subtropical ocean by integrating vertically resolved aerosol observations

2020 ◽  
Vol 20 (12) ◽  
pp. 7167-7177 ◽  
Author(s):  
David Painemal ◽  
Fu-Lung Chang ◽  
Richard Ferrare ◽  
Sharon Burton ◽  
Zhujun Li ◽  
...  
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Cloud Condensation Nuclei ◽  
Cloud Droplet ◽  
Global Climate Models ◽  
Orthogonal Polarization ◽  
Near Surface ◽  
Aerosol Cloud ◽  
Error Characterization ◽  
Aerosol Cloud Interactions

Abstract. Satellite quantification of aerosol effects on clouds relies on aerosol optical depth (AOD) as a proxy for aerosol concentration or cloud condensation nuclei (CCN). However, the lack of error characterization of satellite-based results hampers their use for the evaluation and improvement of global climate models. We show that the use of AOD for assessing aerosol–cloud interactions (ACIs) is inadequate over vast oceanic areas in the subtropics. Instead, we postulate that a more physical approach that consists of matching vertically resolved aerosol data from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite at the cloud-layer height with Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua cloud retrievals reduces uncertainties in satellite-based ACI estimates. Combined aerosol extinction coefficients (σ) below cloud top (σBC) from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and cloud droplet number concentrations (Nd) from MODIS Aqua yield high correlations across a broad range of σBC values, with σBC quartile correlations ≥0.78. In contrast, CALIOP-based AOD yields correlations with MODIS Nd of 0.54–0.62 for the two lower AOD quartiles. Moreover, σBC explains 41 % of the spatial variance in MODIS Nd, whereas AOD only explains 17 %, primarily caused by the lack of spatial covariability in the eastern Pacific. Compared with σBC, near-surface σ weakly correlates in space with MODIS Nd, accounting for a 16 % variance. It is concluded that the linear regression calculated from ln(Nd)–ln(σBC) (the standard method for quantifying ACIs) is more physically meaningful than that derived from the Nd–AOD pair.

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