Estimating the direct radiative effect of absorbing aerosols overlying marine boundary layer clouds in the southeast Atlantic using MODIS and CALIOP

Absorbing aerosols such as smoke strongly absorb solar radiation, particularly at ultraviolet and visible/near-infrared (VIS/NIR) wavelengths, and their presence above clouds can have considerable implications. It has been previously shown that they have a positive (i.e., warming) direct aerosol radiative effect (DARE) when overlying bright clouds. Additionally, they can cause biased passive instrument satellite retrievals in techniques that rely on VIS/NIR wavelengths for inferring the cloud optical thickness (COT) and effective radius (re) of underlying clouds, which can in turn yield biased above-cloud DARE estimates. Here we investigate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical property retrieval biases due to overlying absorbing aerosols observed by Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and examine the impact of these biases on above-cloud DARE estimates. The investigation focuses on a region in the southeast Atlantic Ocean during August and September (2006-2011), where smoke from biomass burning in southern Africa overlies persistent marine boundary layer stratocumulus clouds. Adjusting for above-cloud aerosol attenuation yields increases in the regional mean liquid COT (averaged over all ocean-only liquid clouds) by roughly 6%; mean re increases by roughly 2.6%, almost exclusively due to the COT adjustment in the non-orthogonal retrieval space. It is found that these two biases lead to an underestimate of DARE. For liquid cloud Aqua MODIS pixels with CALIOP-observed above-cloud smoke, the regional mean above-cloud radiative forcing efficiency (DARE per unit aerosol optical depth (AOD)) at time of observation (near local noon for Aqua overpass) increases from 50.9Wm(sup-2)AOD(sup-1) to 65.1Wm(sup-2)AOD(sup -1) when using bias-adjusted instead of nonadjusted MODIS cloud retrievals.

[1]  B. Albrecht.  Aerosols, Cloud Microphysics, and Fractional Cloudiness , 1989, Science.

[2]  Steven Platnick,et al.  An initial analysis of the pixel-level uncertainties in global MODIS cloud optical thickness and effective particle size retrievals , 2004, SPIE Asia-Pacific Remote Sensing.

[3]  Lorraine Remer,et al.  A Color Ratio Method for Simultaneous Retrieval of Aerosol and Cloud Optical Thickness of Above-Cloud Absorbing Aerosols From Passive Sensors: Application to MODIS Measurements , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[4]  Stephen J. Lord,et al.  The New Global Operational Analysis System at the National Meteorological Center , 1991 .

[5]  S. Twomey,et al.  Determining the Susceptibility of Cloud Albedo to Changes in Droplet Concentration with the Advanced Very High Resolution Radiometer , 1994 .

[6]  W. Paul Menzel,et al.  The MODIS cloud products: algorithms and examples from Terra , 2003, IEEE Trans. Geosci. Remote. Sens..

[7]  D. Tanré,et al.  ALGORITHM FOR REMOTE SENSING OF TROPOSPHERIC AEROSOL OVER DARK TARGETS FROM MODIS : Collections 005 and 051 : Revision 2 ; Feb 2009 Product ID : MOD 04 / MYD 04 , 2009 .

[8]  J. Joseph,et al.  The delta-Eddington approximation for radiative flux transfer , 1976 .

[9]  Zhaoyan Liu,et al.  Quantifying above‐cloud aerosol using spaceborne lidar for improved understanding of cloudy‐sky direct climate forcing , 2008 .

[10]  Steven A. Ackerman,et al.  Global Moderate Resolution Imaging Spectroradiometer (MODIS) cloud detection and height evaluation using CALIOP , 2008 .

[11]  J. Haywood,et al.  Solar radiative forcing by biomass burning aerosol particles during SAFARI 2000: A case study based on measured aerosol and cloud properties , 2003 .

[12]  M. McCormick,et al.  Development of global aerosol models using cluster analysis of Aerosol Robotic Network (AERONET) measurements , 2005 .

[13]  David M. Winker,et al.  Use of probability distribution functions for discriminating between cloud and aerosol in lidar backscatter data , 2004 .

[14]  S. Twomey.  Pollution and the Planetary Albedo , 1974 .

[15]  D. Winker,et al.  The CALIPSO Automated Aerosol Classification and Lidar Ratio Selection Algorithm , 2009 .

[16]  Mark A. Vaughan,et al.  The Retrieval of Profiles of Particulate Extinction from Cloud-Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) Data: Algorithm Description , 2009 .

[17]  M. King,et al.  Determination of the Optical Thickness and Effective Particle Radius of Clouds from Reflected Solar Radiation Measurements. Part II: Marine Stratocumulus Observations , 1991 .

[18]  David M. Winker,et al.  The CALIPSO Lidar Cloud and Aerosol Discrimination: Version 2 Algorithm and Initial Assessment of Performance , 2009 .

[19]  Zhaoyan Liu,et al.  Retrieving Optical Depths and Lidar Ratios for Transparent Layers Above Opaque Water Clouds From CALIPSO Lidar Measurements , 2007, IEEE Geoscience and Remote Sensing Letters.

[20]  John A. Smith,et al.  Modeling the transport and optical properties of smoke aerosols from African savanna fires during the Southern African Regional Science Initiative campaign (SAFARI 2000) , 2007 .

[21]  Steven Platnick,et al.  Estimate of the impact of absorbing aerosol over cloud on the MODIS retrievals of cloud optical thickness and effective radius using two independent retrievals of liquid water path , 2009 .

[22]  M. King,et al.  Determination of the optical thickness and effective particle radius of clouds from reflected solar , 1990 .

[23]  David M. Winker,et al.  Fully Automated Detection of Cloud and Aerosol Layers in the CALIPSO Lidar Measurements , 2009 .

[24]  David M. Winker,et al.  The global 3-D distribution of tropospheric aerosols as characterized by CALIOP , 2012 .

[25]  Hiren Jethva,et al.  Retrieval of Aerosol Optical Depth above Clouds from OMI Observations: Sensitivity Analysis and Case Studies , 2012 .

[26]  Thomas F. Eck,et al.  Variability of biomass burning aerosol optical characteristics in southern Africa during the SAFARI , 2003 .

[27]  K. Stamnes,et al.  CALIPSO/CALIOP Cloud Phase Discrimination Algorithm , 2009 .

[28]  K. Stamnes,et al.  Numerically stable algorithm for discrete-ordinate-method radiative transfer in multiple scattering and emitting layered media. , 1988, Applied optics.

[29]  M. King,et al.  Cloud Retrieval Algorithms for MODIS : Optical Thickness , Effective Particle Radius , and Thermodynamic Phase , 2000 .

[30]  H. Barker,et al.  Accounting for subgrid‐scale cloud variability in a multi‐layer 1d solar radiative transfer algorithm , 1999 .

[31]  W. Weaver,et al.  Two-Stream Approximations to Radiative Transfer in Planetary Atmospheres: A Unified Description of Existing Methods and a New Improvement , 1980 .

[32]  S. Twomey.  The Influence of Pollution on the Shortwave Albedo of Clouds , 1977 .

[33]  Jim Haywood,et al.  The effect of overlying absorbing aerosol layers on remote sensing retrievals of cloud effective radius and cloud optical depth , 2004 .

[34]  Eric M. Wilcox,et al.  Direct and semi-direct radiative forcing of smoke aerosols over clouds , 2011 .

[35]  W. Munk,et al.  Measurement of the Roughness of the Sea Surface from Photographs of the Sun’s Glitter , 1954 .

[36]  C. Cox.  Statistics of the sea surface derived from sun glitter , 1954 .

[37]  W. Wiscombe.  Improved Mie scattering algorithms. , 1980, Applied optics.

[38]  W. Collins,et al.  Radiative forcing by long‐lived greenhouse gases: Calculations with the AER radiative transfer models , 2008 .

[39]  T. Bond,et al.  Light Absorption by Carbonaceous Particles: An Investigative Review , 2006 .

[40]  Robert Pincus,et al.  Reconciling Simulated and Observed Views of Clouds: MODIS, ISCCP, and the Limits of Instrument Simulators in Climate Models , 2011 .

[41]  J. Randerson,et al.  Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997-2009) , 2010 .

[42]  Steven Platnick,et al.  An assessment of differences between cloud effective particle radius retrievals for marine water clouds from three MODIS spectral bands , 2011 .

[43]  M. Thomas,et al.  A global survey of aerosol-liquid water cloud overlap based on four years of CALIPSO-CALIOP data , 2010 .

[44]  D. Winker,et al.  Overview of the CALIPSO Mission and CALIOP Data Processing Algorithms , 2009 .

[45]  Piet Stammes,et al.  Retrieval of the aerosol direct radiative effect over clouds from spaceborne spectrometry , 2012 .

[46]  S. Solomon.  The Physical Science Basis : Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change , 2007 .

[47]  Shepard A. Clough,et al.  Atmospheric radiative transfer modeling: a summary of the AER codes , 2005 .

[48]  M. Kirkpatrick,et al.  The impact of humidity above stratiform clouds on indirect aerosol climate forcing , 2004, Nature.

[49]  Robert Wood,et al.  Satellite-derived direct radiative effect of aerosols dependent on cloud cover , 2009 .