Literature DB >> 20935700

New aerosol models for the retrieval of aerosol optical thickness and normalized water-leaving radiances from the SeaWiFS and MODIS sensors over coastal regions and open oceans.

Ziauddin Ahmad1, Bryan A Franz, Charles R McClain, Ewa J Kwiatkowska, Jeremy Werdell, Eric P Shettle, Brent N Holben.   

Abstract

We describe the development of a new suite of aerosol models for the retrieval of atmospheric and oceanic optical properties from the SeaWiFS and MODIS sensors, including aerosol optical thickness (τ), angstrom coefficient (α), and water-leaving radiance (L(w)). The new aerosol models are derived from Aerosol Robotic Network (AERONET) observations and have bimodal lognormal distributions that are narrower than previous models used by the Ocean Biology Processing Group. We analyzed AERONET data over open ocean and coastal regions and found that the seasonal variability in the modal radii, particularly in the coastal region, was related to the relative humidity. These findings were incorporated into the models by making the modal radii, as well as the refractive indices, explicitly dependent on relative humidity. From these findings, we constructed a new suite of aerosol models. We considered eight relative humidity values (30%, 50%, 70%, 75%, 80%, 85%, 90%, and 95%) and, for each relative humidity value, we constructed ten distributions by varying the fine-mode fraction from zero to 1. In all, 80 distributions (8 Rh×10 fine-mode fractions) were created to process the satellite data. We also assumed that the coarse-mode particles were nonabsorbing (sea salt) and that all observed absorptions were entirely due to fine-mode particles. The composition of the fine mode was varied to ensure that the new models exhibited the same spectral dependence of single scattering albedo as observed in the AERONET data. The reprocessing of the SeaWiFS data show that, over deep ocean, the average τ(865) values retrieved from the new aerosol models was 0.100±0.004, which was closer to the average AERONET value of 0.086±0.066 for τ(870) for the eight open-ocean sites used in this study. The average τ(865) value from the old models was 0.131±0.005. The comparison of monthly mean aerosol optical thickness retrieved from the SeaWiFS sensor with AERONET data over Bermuda and Wallops Island show very good agreement with one another. In fact, 81% of the data points over Bermuda and 78% of the data points over Wallops Island fall within an uncertainty of ±0.02 in optical thickness. As a part of the reprocessing effort of the SeaWiFS data, we also revised the vicarious calibration gain factors, which resulted in significant improvement in angstrom coefficient (α) retrievals. The average value of α from the new models over Bermuda is 0.841±0.171, which is in good agreement with the AERONET value of 0.891±0.211. The average value of α retrieved using old models is 0.394±0.087, which is significantly lower than the AERONET value.

Entities:  

Year:  2010        PMID: 20935700     DOI: 10.1364/AO.49.005545

Source DB:  PubMed          Journal:  Appl Opt        ISSN: 1559-128X            Impact factor:   1.980


  14 in total

1.  Observation-based study on aerosol optical depth and particle size in partly cloudy regions.

Authors:  T Várnai; A Marshak; T F Eck
Journal:  J Geophys Res Atmos       Date:  2017-09-04       Impact factor: 4.261

2.  Cross-calibration of S-NPP VIIRS moderate resolution reflective solar bands against MODIS Aqua over dark water scenes.

Authors:  A M Sayer; N C Hsu; C Bettenhausen; R E Holz; J Lee; G Quinn; P Veglio
Journal:  Atmos Meas Tech       Date:  2017-04-13       Impact factor: 4.176

3.  Satellite Ocean Aerosol Retrieval (SOAR) algorithm extension to S-NPP VIIRS as part of the 'Deep Blue' aerosol project.

Authors:  A M Sayer; N C Hsu; J Lee; C Bettenhausen; W V Kim; A Smirnov
Journal:  J Geophys Res Atmos       Date:  2017-11-17       Impact factor: 4.261

4.  Evaluation of NASA Deep Blue/SOAR aerosol retrieval algorithms applied to AVHRR measurements.

Authors:  A M Sayer; N C Hsu; J Lee; N Carletta; S-H Chen; A Smirnov
Journal:  J Geophys Res Atmos       Date:  2017-07-20       Impact factor: 4.261

5.  Exploring systematic offsets between aerosol products from the two MODIS sensors.

Authors:  Robert C Levy; Shana Mattoo; Virginia Sawyer; Yingxi Shi; Peter R Colarco; Alexei I Lyapustin; Yujie Wang; Lorraine A Remer
Journal:  Atmos Meas Tech       Date:  2018-07-13       Impact factor: 4.176

6.  An Aerosol Climatology and Implications for Clouds at a Remote Marine Site: Case Study Over Bermuda.

Authors:  Abdulmonam M Aldhaif; David H Lopez; Hossein Dadashazar; David Painemal; Andrew J Peters; Armin Sorooshian
Journal:  J Geophys Res Atmos       Date:  2021-04-07       Impact factor: 4.261

7.  Retrieval of aerosol properties and water-leaving reflectance from multi-angular polarimetric measurements over coastal waters.

Authors:  Meng Gao; Peng-Wang Zhai; Bryan Franz; Yongxiang Hu; Kirk Knobelspiesse; P Jeremy Werdell; Amir Ibrahim; Feng Xu; Brian Cairns
Journal:  Opt Express       Date:  2018-04-02       Impact factor: 3.894

8.  Water-leaving contribution to polarized radiation field over ocean.

Authors:  Peng-Wang Zhai; Kirk Knobelspiesse; Amir Ibrahim; Bryan A Franz; Yongxiang Hu; Meng Gao; Robert Frouin
Journal:  Opt Express       Date:  2017-08-07       Impact factor: 3.894

9.  Simultaneous polarimeter retrievals of microphysical aerosol and ocean color parameters from the "MAPP" algorithm with comparison to high-spectral-resolution lidar aerosol and ocean products.

Authors:  S Stamnes; C Hostetler; R Ferrare; S Burton; X Liu; J Hair; Y Hu; A Wasilewski; W Martin; B van Diedenhoven; J Chowdhary; I Cetinić; L K Berg; K Stamnes; B Cairns
Journal:  Appl Opt       Date:  2018-04-01       Impact factor: 1.980

10.  Uncertainty in global downwelling plane irradiance estimates from sintered polytetrafluoroethylene plaque radiance measurements.

Authors:  Alexandre Castagna; B Carol Johnson; Kenneth Voss; Heidi M Dierssen; Heather Patrick; Thomas A Germer; Koen Sabbe; Wim Vyverman
Journal:  Appl Opt       Date:  2019-06-01       Impact factor: 1.980

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