Retrievals of aerosol optical depth over the western North Atlantic Ocean during ACTIVATE

被引:0
作者
Siu, Leong Wai [1 ]
Schlosser, Joseph S. [2 ,3 ]
Painemal, David [2 ,4 ]
Cairns, Brian [5 ]
Fenn, Marta A. [2 ]
Ferrare, Richard A. [2 ]
Hair, Johnathan W. [2 ]
Hostetler, Chris A. [2 ]
Li, Longlei [6 ]
Kleb, Mary M. [2 ]
Scarino, Amy Jo [2 ,4 ]
Shingler, Taylor J. [2 ]
Sorooshian, Armin [1 ,7 ]
Stamnes, Snorre A. [2 ]
Zeng, Xubin [1 ]
机构
[1] Univ Arizona, Dept Hydrol & Atmospher Sci, Tucson, AZ 85721 USA
[2] Langley Res Ctr, NASA, Hampton, VA USA
[3] Langley Res Ctr, Postdoctoral Program, NASA, Hampton, VA USA
[4] Analyt Mech Associates Inc, Hampton, VA USA
[5] Goddard Inst Space Studies, NASA, New York, NY USA
[6] Cornell Univ, Dept Earth & Atmospher Sci, Ithaca, NY USA
[7] Univ Arizona, Dept Chem & Environm Engn, Tucson, AZ USA
基金
美国国家航空航天局;
关键词
SPECTRAL-RESOLUTION LIDAR; RESEARCH SCANNING POLARIMETER; SOIL-MOISTURE; CLOUD; ALGORITHM; CLIMATE; CALIBRATION; SATELLITE; PRODUCTS; REMOTE;
D O I
10.5194/amt-17-2739-2024
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Aerosol optical depth was retrieved from two airborne remote sensing instruments, the Research Scanning Polarimeter (RSP) and Second Generation High Spectral Resolution Lidar (HSRL-2), during the National Aeronautics and Space Administration (NASA) Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE). The field campaign offers a unique opportunity to evaluate an extensive 3-year dataset under a wide range of meteorological conditions from two instruments on the same platform. However, a long-standing issue in atmospheric field studies is that there is a lack of reference datasets for properly validating field measurements and estimating their uncertainties. Here we address this issue by using the triple collocation method, in which a third collocated satellite dataset from the Moderate Resolution Imaging Spectroradiometer (MODIS) is introduced for comparison. HSRL-2 is found to provide a more accurate retrieval than RSP over the study region. The error standard deviation of HSRL-2 with respect to the ground truth is 0.027. Moreover, this approach enables us to develop a simple, yet efficient, quality control criterion for RSP data. The physical reasons for the differences in two retrievals are determined to be cloud contamination, aerosols near the surface, multiple aerosol layers, absorbing aerosols, non-spherical aerosols, and simplified retrieval assumptions. These results demonstrate the pathway for optimal aerosol retrievals by combining information from both lidars and polarimeters for future airborne and satellite missions.
引用
收藏
页码:2739 / 2759
页数:21
相关论文
共 68 条
[1]   Sources, frequency, and chemical nature of dust events impacting the United States East Coast [J].
Aldhaif, Abdulmonam M. ;
Lopez, David H. ;
Dadashazar, Hossein ;
Sorooshian, Armin .
ATMOSPHERIC ENVIRONMENT, 2020, 231
[2]   Accuracy assessments of cloud droplet size retrievals from polarized reflectance measurements by the research scanning polarimeter [J].
Alexandrov, Mikhail D. ;
Cairns, Brian ;
Emde, Claudia ;
Ackerman, Andrew S. ;
van Diedenhoven, Bastiaan .
REMOTE SENSING OF ENVIRONMENT, 2012, 125 :92-111
[3]  
Anderson TL, 2003, J ATMOS SCI, V60, P119, DOI 10.1175/1520-0469(2003)060<0119:MVOTA>2.0.CO
[4]  
2
[5]   Correlation between cloud condensation nuclei concentration and aerosol optical thickness in remote and polluted regions [J].
Andreae, M. O. .
ATMOSPHERIC CHEMISTRY AND PHYSICS, 2009, 9 (02) :543-556
[6]   Bounding Global Aerosol Radiative Forcing of Climate Change [J].
Bellouin, N. ;
Quaas, J. ;
Gryspeerdt, E. ;
Kinne, S. ;
Stier, P. ;
Watson-Parris, D. ;
Boucher, O. ;
Carslaw, K. S. ;
Christensen, M. ;
Daniau, A. -L. ;
Dufresne, J. -L. ;
Feingold, G. ;
Fiedler, S. ;
Forster, P. ;
Gettelman, A. ;
Haywood, J. M. ;
Lohmann, U. ;
Malavelle, F. ;
Mauritsen, T. ;
McCoy, D. T. ;
Myhre, G. ;
Muelmenstaedt, J. ;
Neubauer, D. ;
Possner, A. ;
Rugenstein, M. ;
Sato, Y. ;
Schulz, M. ;
Schwartz, S. E. ;
Sourdeval, O. ;
Storelvmo, T. ;
Toll, V. ;
Winker, D. ;
Stevens, B. .
REVIEWS OF GEOPHYSICS, 2020, 58 (01)
[7]   Calibration of a high spectral resolution lidar using a Michelson interferometer, with data examples from ORACLES [J].
Burton, S. P. ;
Hostetler, C. A. ;
Cook, A. L. ;
Hair, J. W. ;
Seaman, S. T. ;
Scola, S. ;
Harper, D. B. ;
Smith, J. A. ;
Fenn, M. A. ;
Ferrare, R. A. ;
Saide, P. E. ;
Chemyakin, E. V. ;
Mueller, D. .
APPLIED OPTICS, 2018, 57 (21) :6061-6075
[8]   Aerosol classification from airborne HSRL and comparisons with the CALIPSO vertical feature mask [J].
Burton, S. P. ;
Ferrare, R. A. ;
Vaughan, M. A. ;
Omar, A. H. ;
Rogers, R. R. ;
Hostetler, C. A. ;
Hair, J. W. .
ATMOSPHERIC MEASUREMENT TECHNIQUES, 2013, 6 (05) :1397-1412
[9]   Aerosol classification using airborne High Spectral Resolution Lidar measurements - methodology and examples [J].
Burton, S. P. ;
Ferrare, R. A. ;
Hostetler, C. A. ;
Hair, J. W. ;
Rogers, R. R. ;
Obland, M. D. ;
Butler, C. F. ;
Cook, A. L. ;
Harper, D. B. ;
Froyd, K. D. .
ATMOSPHERIC MEASUREMENT TECHNIQUES, 2012, 5 (01) :73-98
[10]   Information content and sensitivity of the 3β+2α lidar measurement system for aerosol microphysical retrievals [J].
Burton, Sharon P. ;
Chemyakin, Eduard ;
Liu, Xu ;
Knobelspiesse, Kirk ;
Stamnes, Snorre ;
Sawamura, Patricia ;
Moore, Richard H. ;
Hostetler, Chris A. ;
Ferrare, Richard A. .
ATMOSPHERIC MEASUREMENT TECHNIQUES, 2016, 9 (11) :5555-5574