Aerosol indirect effects ĝ€" general circulation model intercomparison and evaluation with satellite data

Atmospheric Chemistry and Physics 9:22 (2009) 8697-8717

Authors:

J Quaas, Y Ming, S Menon, T Takemura, M Wang, JE Penner, A Gettelman, U Lohmann, N Bellouin, O Boucher, AM Sayer, GE Thomas, A McComiskey, G Feingold, C Hoose, JE Kristj́nsson, X Liu, Y Balkanski, LJ Donner, PA Ginoux, P Stier, B Grandey, J Feichter, I Sednev, SE Bauer, D Koch, RG Grainger, A Kirkevaring, T Iversen, O Seland, R Easter, SJ Ghan, PJ Rasch, H Morrison, JF Lamarque, MJ Iacono, S Kinne, M Schulz

Abstract:

Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterises aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (τ a) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. It is found that the model-simulated influence of aerosols on cloud droplet number concentration (Nd) compares relatively well to the satellite data at least over the ocean. The relationship between τa and liquid water path is simulated much too strongly by the models. This suggests that the implementation of the second aerosol indirect effect mainly in terms of an autoconversion parameterisation has to be revisited in the GCMs. A positive relationship between total cloud fraction (fcld) and τ a as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strongfcldĝ€"τa relationship, our results indicate that none can be identified as a unique explanation. Relationships similar to the ones found in satellite data between τa and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLRĝ€"τ a relationship show a strong positive correlation between τa andfcld. The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of τa, and parameterisation assumptions such as a lower bound onNd. Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of −1.5±0.5 Wm−2. In an alternative approach, the radiative flux perturbation due to anthropogenic aerosols can be broken down into a component over the cloud-free portion of the globe (approximately the aerosol direct effect) and a component over the cloudy portion of the globe (approximately the aerosol indirect effect). An estimate obtained by scaling these simulated clear- and cloudy-sky forcings with estimates of anthropogenic τa and satellite-retrievedNdĝ€"τa regression slopes, respectively, yields a global, annual-mean aerosol direct effect estimate of −0.4±0.2 Wm−2 and a cloudy-sky (aerosol indirect effect) estimate of −0.7±0.5 Wm−2, with a total estimate of −1.2±0. 4 Wm−2.

Cloud detection for MIPAS using singular vector decomposition

Atmospheric Measurement Techniques 2:2 (2009) 533-547

Authors:

J Hurley, A Dudhia, RG Grainger

Abstract:

Satellite-borne high-spectral-resolution limb sounders, such as the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) onboard ENVISAT, provide information on clouds, especially optically thin clouds, which have been difficult to observe in the past. The aim of this work is to develop, implement and test a reliable cloud detection method for infrared spectra measured by MIPAS. Current MIPAS cloud detection methods used operationally have been developed to detect cloud effective filling more than 30% of the measurement field-of-view (FOV), under geometric and optical considerations - and hence are limited to detecting fairly thick cloud, or large physical extents of thin cloud. In order to resolve thin clouds, a new detection method using Singular Vector Decomposition (SVD) is formulated and tested. This new SVD detection method has been applied to a year's worth of MIPAS data, and qualitatively appears to be more sensitive to thin cloud than the current operational method.

The GRAPE aerosol retrieval algorithm

Atmospheric Measurement Techniques 2:2 (2009) 679-701

Authors:

GE Thomas, CA Poulsen, AM Sayer, SH Marsh, SM Dean, E Carboni, R Siddans, RG Grainger, BN Lawrence

Abstract:

The aerosol component of the Oxford-Rutherford Aerosol and Cloud (ORAC) combined cloud and aerosol retrieval scheme is described and the theoretical performance of the algorithm is analysed. ORAC is an optimal estimation retrieval scheme for deriving cloud and aerosol properties from measurements made by imaging satellite radiometers and, when applied to cloud free radiances, provides estimates of aerosol optical depth at a wavelength of 550 nm, aerosol effective radius and surface reflectance at 550 nm. The aerosol retrieval component of ORAC has several incarnations - this paper addresses the version which operates in conjunction with the cloud retrieval component of ORAC (described by Watts et al., 1998), as applied in producing the Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE) data-set. The algorithm is described in detail and its performance examined. This includes a discussion of errors resulting from the formulation of the forward model, sensitivity of the retrieval to the measurements and a priori constraints, and errors resulting from assumptions made about the atmospheric/surface state.

Aerosol indirect effects - general circulation model intercomparison and evaluation with satellite data

ATMOS CHEM PHYS 9 (2009) 8697–8717-8697–8717

Authors:

J Quaas, Y Ming, S Menon, T Takemura, M Wang, JE Penner, A Gettelman, U Lohmann, N Bellouin, O Boucher, AM Sayer, GE Thomas, A McComiskey, G Feingold, C Hoose, JE Kristjansson, X Liu, Y Balkanski, LJ Donner, PA Ginoux, P Stier, B Grandey, J Feichter, I Sednev, SE Bauer, D Koch, RG Grainger, A Kirkevag, T Iversen, O Seland, R Easter, SJ Ghan, PJ Rasch, H Morrison, JF Lamarque, MJ Iacono, S Kinne, M Schulz

Abstract:

Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterises aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (tau(a)) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. It is found that the model-simulated influence of aerosols on cloud droplet number concentration (N-d) compares relatively well to the satellite data at least over the ocean. The relationship between tau(a) and liquid water path is simulated much too strongly by the models. This suggests that the implementation of the second aerosol indirect effect mainly in terms of an autoconversion parameterisation has to be revisited in the GCMs. A positive relationship between total cloud fraction (f(cld)) and tau(a) as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong f(cld)-tau(a) relationship, our results indicate that none can be identified as a unique explanation. Relationships similar to the ones found in satellite data between tau(a) and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR-tau(a) relationship show a strong positive correlation between tau(a) and f(cld). The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of tau(a), and parameterisation assumptions such as a lower bound on N-d. Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of -1.5 +/- 0.5 Wm(-2). In an alternative approach, the radiative flux perturbation due to anthropogenic aerosols can be broken down into a component over the cloud-free portion of the globe (approximately the aerosol direct effect) and a component over the cloudy portion of the globe (approximately the aerosol indirect effect). An estimate obtained by scaling these simulated clear- and cloudy-sky forcings with estimates of anthropogenic tau(a) and satellite-retrieved N-d-tau(a) regression slopes, respectively, yields a global, annual-mean aerosol direct effect estimate of -0.4 +/- 0.2 Wm(-2) and a cloudy-sky (aerosol indirect effect) estimate of -0.7 +/- 0.5 Wm(-2), with a total estimate of -1.2 +/- 0.4 Wm(-2).

Automatic detection of ship tracks in ATSR-2 satellite imagery

ATMOS CHEM PHYS 9 (2009) 1899–1905-1899–1905

Authors:

E Campmany, RG Grainger, SM Dean, AM Sayer

Abstract:

Ships modify cloud microphysics by adding cloud condensation nuclei (CCN) to a developing or existing cloud. These create lines of larger reflectance in cloud fields that are observed in satellite imagery. An algorithm has been developed to automate the detection of ship tracks in Along Track Scanning Radiometer 2 (ATSR-2) imagery. The scheme has been integrated into the Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE) processing chain. The algorithm firstly identifies intensity ridgelets in clouds which have the potential to be part of a ship track. This identification is done by comparing each pixel with its surrounding ones. If the intensity of three adjacent pixels is greater than the intensity of their neighbours, then it is classified as a ridgelet. These ridgelets are then connected together, according to a set of connectivity rules, to form tracks which are classed as ship tracks if they are long enough. The algorithm has been applied to two years of ATSR-2 data. Ship tracks are most frequently seen off the west coast of California, and the Atlantic coast of both West Africa and South Western Europe. The global distribution of ship tracks shows strong seasonality, little inter-annual variability and a similar spatial pattern to the distribution of ship emissions.