The Collection 6 MODIS aerosol products over land and ocean

被引:1707
|
作者
Levy, R. C. [1 ]
Mattoo, S. [1 ,2 ]
Munchak, L. A. [1 ,2 ]
Remer, L. A. [3 ]
Sayer, A. M. [1 ,4 ]
Patadia, F. [1 ,5 ]
Hsu, N. C. [1 ]
机构
[1] NASA, Goddard Space Flight Ctr, Climate & Radiat Lab, Greenbelt, MD 20771 USA
[2] Sci Syst & Applicat Inc, Lanham, MD 20709 USA
[3] Univ Maryland Baltimore Cty, JCET, Baltimore, MD 21228 USA
[4] Univ Space Res Assoc, Columbia, MD USA
[5] Morgan State Univ, Baltimore, MD 21239 USA
关键词
IMAGING SPECTRORADIOMETER MODIS; OPTICAL DEPTH; SIZE DISTRIBUTION; AIRBORNE SIMULATOR; DATA-ASSIMILATION; TREND ANALYSIS; RETRIEVAL; SYSTEM; CLOUD; VALIDATION;
D O I
10.5194/amt-6-2989-2013
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The twin Moderate resolution Imaging Spectroradiometer (MODIS) sensors have been flying on Terra since 2000 and Aqua since 2002, creating an extensive data set of global Earth observations. Here, we introduce the Collection 6 (C6) algorithm to retrieve aerosol optical depth (AOD) and aerosol size parameters from MODIS-observed spectral reflectance. While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there are significant impacts to the products and their interpretation. The C6 aerosol data set will be created from three separate retrieval algorithms that operate over different surface types. These are the two "Dark Target"(DT) algorithms for retrieving (1) over ocean (dark in visible and longer wavelengths) and (2) over vegetated/dark-soiled land (dark in the visible), plus the "Deep Blue"(DB) algorithm developed originally for retrieving (3) over desert/arid land (bright in the visible). Here, we focus on DT-ocean and DT-land (# 1 and # 2). We have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O-3, CO2, etc.) absorption corrections, while relaxing the solar zenith angle limit (up to <= 84 degrees) to increase poleward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season/location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence on the surface reflectance, updates to logic of QA Confidence flag (QAC) assignment, and additions of important diagnostic information. At the same time, we quantified how "upstream"changes to instrument calibration, land/sea masking and cloud masking will also impact the statistics of global AOD, and affect Terra and Aqua differently. For Aqua, all changes will result in reduced global AOD (by 0.02) over ocean and increased AOD (by 0.02) over land, along with changes in spatial coverage. We compared preliminary data to surface-based sun photometer data, and show that C6 should improve upon C5. C6 will include a merged DT/DB product over semi-arid land surfaces for reduced-gap coverage and better visualization, and new information about clouds in the aerosol field. Responding to the needs of the air quality community, in addition to the standard 10 km product, C6 will include a global (DT-land and DT-ocean) aerosol product at 3 km resolution.
引用
收藏
页码:2989 / 3034
页数:46
相关论文
共 50 条
  • [31] Evaluation of MODIS, MISR, and VIIRS daily level-3 aerosol optical depth products over land
    Chen, Qi-Xiang
    Han, Xin-Lei
    Gu, Yu
    Yuan, Yuan
    Jiang, Jonathan H.
    Yang, Xue-Bo
    Liou, Kuo-Nan
    Tan, He-Ping
    ATMOSPHERIC RESEARCH, 2022, 265
  • [32] Validation, Stability, and Consistency of MODIS Collection 6.1 and VIIRS Version 1 Deep Blue Aerosol Data Over Land
    Sayer, Andrew M.
    Hsu, N. Christina
    Lee, Jaehwa
    Kim, Woogyung, V
    Dutcher, Steven T.
    JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2019, 124 (08) : 4658 - 4688
  • [33] Can MODIS detect trends in aerosol optical depth over land?
    Fan, Xuehua
    Xia, Xiang'ao
    Chen, Hongbin
    ADVANCES IN ATMOSPHERIC SCIENCES, 2018, 35 (02) : 135 - 145
  • [34] Can MODIS Detect Trends in Aerosol Optical Depth over Land?
    Xuehua FAN
    Xiang'ao XIA
    Hongbin CHEN
    AdvancesinAtmosphericSciences, 2018, 35 (02) : 135 - 145
  • [35] Aerosol optical depth over land: Comparing AERONET, AVHRR and MODIS
    Hauser, A
    Oesch, D
    Foppa, N
    GEOPHYSICAL RESEARCH LETTERS, 2005, 32 (17) : 1 - 4
  • [36] Significant overestimation of global aerosol optical thickness by MODIS over land
    Xia Xiang'ao
    CHINESE SCIENCE BULLETIN, 2006, 51 (23): : 2905 - 2912
  • [37] Significant overestimation of global aerosol optical thickness by MODIS over land
    XIA Xiang’ao Institute of Atmospheric Physics
    ChineseScienceBulletin, 2006, (23) : 2905 - 2912
  • [38] Bayesian aerosol retrieval algorithm for MODIS AOD retrieval over land
    Lipponen, Antti
    Mielonen, Tero
    Pitkanen, Mikko R. A.
    Levy, Robert C.
    Sawyer, Virginia R.
    Romakkaniemi, Sami
    Kolehmainen, Ville
    Arola, Antti
    ATMOSPHERIC MEASUREMENT TECHNIQUES, 2018, 11 (03) : 1529 - 1547
  • [39] Can MODIS detect trends in aerosol optical depth over land?
    Xuehua Fan
    Xiang’ao Xia
    Hongbin Chen
    Advances in Atmospheric Sciences, 2018, 35 : 135 - 145
  • [40] Understanding MODIS dark-target collection 5 and 6 aerosol data over China: Effect of surface type, aerosol loading and aerosol absorption
    Mei, Linlu
    Zhao, Chuanxu
    de Leeuw, Gerrit
    Che, HuiZheng
    Che, Yahui
    Rozanov, Vladimir
    Vountas, Marco
    Burrows, John P.
    ATMOSPHERIC RESEARCH, 2019, 228 : 161 - 175