Improving the CALIOP aerosol optical depth using combined MODIS‐CALIOP observations and CALIOP integrated attenuated total color ratio

[1] This paper aims to evaluate CALIOP aerosol optical depth (AOD) retrieval using MODIS AOD with the goal of improving the CALIOP selection of the lidar ratio leveraging the vertical resolved CALIOP and multispectral MODIS observations. Comparing the MODIS fine mode ratio to CALIOP, we find that the CALIOP integrated attenuated total color ratio provides sensitivity to the aerosol size and type. This finding can be used to better constrain the lidar ratio and improve the CALIOP AOD independent from MODIS.To retrieve the aerosol optical depth from CALIOP requires knowledge of the aerosol lidar ratio that varies significantly as a function of aerosol type. For most CALIOP retrievals the lidar ratio is estimated by correlating CALIOP observables (depolarization and backscatter) with precomputed lidar ratio climatologies. Applying a lidar ratio not representative of the observed aerosols can result in significant AOD biases and is one of the primary sources of uncertainty in the current CALIOP AOD. We demonstrate that over ocean the MODIS sensitivity to the fine- and coarse-mode aerosol mixing ratios provides additional constraints to the aerosol lidar ratio. When MODIS fine-mode retrievals are collocated with CALIOP, the improved lidar ratio significantly reduces the CALIOP AOD mean biases from ∣0.064∣ to ∣0.020∣ when compared to MODIS. In addition, we demonstrate that the CALIOP integrated attenuated total color ratio is correlated with the MODIS fine and coarse mixing ratios in marine environments. This finding suggests that for a CALIOP-only AOD retrieval the integrated attenuated total color ratio can be used to better constrain the lidar ratio. Using the CALIOP integrated attenuated total color ratio, the CALIOP-only AOD retrieval improves the AOD mean biases (∣0.064∣ to ∣0.007∣) when compared to the MODIS AOD.

[1]  Zhaoyan Liu,et al.  On the spectral dependence of backscatter from cirrus clouds: Assessing CALIOP's 1064 nm calibration assumptions using cloud physics lidar measurements , 2010 .

[2]  Y. Sasano,et al.  Light scattering characteristics of various aerosol types derived from multiple wavelength lidar observations. , 1989, Applied optics.

[3]  W. Paul Menzel,et al.  Remote sensing of cloud, aerosol, and water vapor properties from the moderate resolution imaging spectrometer (MODIS) , 1992, IEEE Trans. Geosci. Remote. Sens..

[4]  Yoram J. Kaufman,et al.  Evaluation of the MODIS Aerosol Retrievals over Ocean and Land during CLAMS , 2005 .

[5]  Lorraine A. Remer,et al.  Using Airborne High Spectral Resolution Lidar Data to Evaluate Combined Active Plus Passive Retrievals of Aerosol Extinction Profiles , 2010 .

[6]  A. Ansmann,et al.  Aerosol-type-dependent lidar ratios observed with Raman lidar , 2007 .

[7]  T. Eck,et al.  Comparison of Moderate Resolution Imaging Spectroradiometer (MODIS) and Aerosol Robotic Network (AERONET) remote-sensing retrievals of aerosol fine mode fraction over ocean , 2005 .

[8]  Yoram J. Kaufman,et al.  Retrievals of profiles of fine and coarse aerosols using lidar and radiometric space measurements , 2003, IEEE Trans. Geosci. Remote. Sens..

[9]  D. Winker,et al.  Strategies for Improved CALIPSO Aerosol Optical Depth Estimates , 2010 .

[10]  S. Twomey,et al.  Aerosols, clouds and radiation , 1991 .

[11]  R. Levy,et al.  Testing aerosol properties in MODIS Collection 4 and 5 using airborne sunphotometer observations in INTEX-B/MILAGRO , 2009 .

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

[13]  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 .

[14]  Yoram J. Kaufman,et al.  An Emerging Global Aerosol Climatology from the MODIS Satellite Sensors , 2008 .

[15]  David M. Winker,et al.  Fully automated analysis of space-based lidar data: an overview of the CALIPSO retrieval algorithms and data products , 2004, SPIE Remote Sensing.

[16]  Yoram J. Kaufman,et al.  Profiling of a Saharan dust outbreak based on a synergy between active and passive remote sensing , 2003 .

[17]  O. Dubovik,et al.  Variability of aerosol and spectral lidar and backscatter and extinction ratios of key aerosol types derived from selected Aerosol Robotic Network locations , 2005 .

[18]  David M. Winker,et al.  Global view of aerosol vertical distributions from CALIPSO lidar measurements and GOCART simulations: Regional and seasonal variations , 2010 .

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

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

[21]  John A. Reagan,et al.  AERONET, airborne HSRL, and CALIPSO aerosol retrievals compared and combined: A case study , 2010 .

[22]  X. Wang,et al.  Spaceborne lidar aerosol retrieval approaches based on aerosol model constraints , 2004, IGARSS 2004. 2004 IEEE International Geoscience and Remote Sensing Symposium.

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

[24]  Wayne C. Welch,et al.  Airborne high spectral resolution lidar for profiling aerosol optical properties. , 2008, Applied optics.

[25]  David M. Winker,et al.  Intercomparison of CALIOP and MODIS aerosol optical depth retrievals , 2010 .

[26]  D. Chu,et al.  Testing the MODIS Satellite Retrieval of Aerosol Fine-Mode Fraction , 2005 .

[27]  Steven A. Ackerman,et al.  Cloud Detection with MODIS. Part II: Validation , 2008 .

[28]  J. Coakley,et al.  Climate Forcing by Anthropogenic Aerosols , 1992, Science.

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

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

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

[32]  Mark A. Vaughan,et al.  Backscatter-to-Extinction Ratios in the Top Layers of Tropical Mesoscale Convective Systems and in Isolated Cirrus from LITE Observations. , 1999 .

[33]  Robert E. Holz,et al.  Computationally Efficient Methods of Collocating Satellite, Aircraft, and Ground Observations , 2009 .

[34]  A. Smirnov,et al.  AERONET-a federated instrument network and data archive for aerosol Characterization , 1998 .