Total suspended matter concentration (TSM) algorithms for ocean color sensors use empirical relationship between
satellite-retrieved remote sensing reflectances and TSM. However the estimated-TSM has no enough accuracy because
the reflectance at visible bands has error after atmospheric correction in high turbid area. The purpose of this study is to
estimate simultaneously total suspended matter concentration, aerosol optical thickness and Angstrom exponent using
three bands at near infrared from MODIS/Aqua and SeaWiFS data. We applied this scheme to MODIS/Aqua and
SeaWiFS data, and satellite-derived TSM were compared with ship-observed TSM dataset in Yellow Sea and East China
Sea. RMSE of TSM was 0.338 in log-log coordinates and correlation coefficient was 0.850. The scheme was better than
Clark’s or Tassan’s TSM algorithm.
KEYWORDS: Carbon, Satellites, Ecosystems, Remote sensing, Climate change, Temperature metrology, Data modeling, Current controlled current source, Data analysis, Composites
The purpose of this works was to investigate temporal and spatial variation of chlorophyll-a concentration and sea
surface temperature before and after the typhoon Ketsana passage in subtropical western North Pacific Ocean and to
evaluate primary production enhancement by satellite data. Chlorophyll-a concentration kept higher level (>0.1mg/m3)
for one month after typhoon Ketsana passage Maximum value of chlorophyll-a concentration was 3.5 mg/m3 that is 70
times more than a normal condition of the area in the seventh day after the passage. Sea surface temperature decreased
from 30 to 22 °C. The lowest Sea surface temperature was recorded in Oct. 25 after two days the passage. Time rag was
4 days between Sea surface temperature minimum and chlorophyll-a concentration maximum. Primary production
enhancement by the typhoon was estimated 727 Gg Carbon. Carbon fixation by typhoon Ketsana was estimated about
0.11% of western North Pacific's annual new production.
Ocean color products (aerosol, normalized water-leaving radiance, and chlorophyll-a concentration) were produced using 250-m resolution data (center wavelengths at 462, 543, 661, 824, 1645, and 2194nm) of Global Imager (GLI) on ADEOS-II by GLI standard ocean atmospheric correction algorithms (i.e., basically same as the 1-km algorithm). The 250-m ocean color products can show finer spatial structures than standard 1km products, but we found some problems; (a) there is large noise because GLI 250-m channels were designed originally for bright area (land vegetation), (b) we have to use channels which are not optimized for the atmospheric correction (wide bandwidth, large noise, and including slight water-vapor absorption), and (c) we need more consideration about cloud shadow, sea-surface reflectance (sunglint and white cap), and shallow bottom. Sea surface reflectance has fine spatial structures in the actual ocean due to fine structure of surface winds influenced by the coastal topography, and we often cannot distinguish the surface reflection from aerosol scattering above the sea surface. JAXA is planning a new mission, "Second generation GLI (SGLI) on GCOM satellites", which has visible and near-infrared channels with 250-m spatial resolution improving noise level and bandwidth applicable to the coastal ocean-color observations.
This study shows match-up analysis of chlorophyll-a concentration in coastal area in Upper Gulf of Thailand. An applicability of atmospheric correction are investigated in turbid area. When a suspended matter concentration is over 7 g/m3 in a mouth of Bangpakong river, atmospheric correction was failed, then chlorophyll-a concentration could not be estimated. Three algorithms which are MODIS (Moderate Resolution Imaging Spectroradiometer) standard, neural network for GLI (Global Imager) and regional empirical algorithm are compared using match-up data set. The regional algorithm has better correlation than other algorithms and its RMSE was minimum in three algorithms. MODIS standard algorithm has good performance in higher than 1mg/m3, however, CHL was overestimated in lower concentration.
The paper compares GLI-derived estimates obtained under "version 2" GLI standard atmospheric correction algorithm with in situ measured data collected by SIMBADA handheld above-water radiometer, intending the evaluating the performance of the algorithm which includes empirical absorptive aerosol correction as well as sun glint correction. Over 395 match-up data, average estimation error (difference between GLI-derived and SIMBADA-measured data) in
normalized water-leaving radiance (nLW) is 0.3 μW/cm2/nm/sr in 412 and in 443 nm bands, showing improvement from version 1 GLI atmospheric correction by 10-30 %, whereas estimation bias is reduced significantly. The GLI-derived
aerosol optical thickness (AOT) in 865 nm band show 0.1 RMS error against SIMBADA measurement on average, whereas Angstrom exponent estimate shows significant bias, suggesting potential calibration offset among GLI near-infrared bands. Despite relatively large scattering in nLW match-up analysis, comparison between GLI chlorophyll a concentration estimates and SIMBADA-derived estimation show highly correlated and consistent relation. This will suggest that fluctuations in nLW estimate are systematic over GLI visible channels although the nature of the variability requires further investigation.
This paper proposes scheme of absorptive aerosol correction for ocean color data of Global Imager (GLI). 380 nm band (GLI band 1) is used to detect absorptive aerosol, and to correct absorption. Spectral dependency of absorption is given empirically from GLI scenes with absorptive aerosol. It is built in GLI atmospheric correction. Satellite-derived water-leaving radiance is compared with in-situ data over East China Sea under presence of absorptive aerosol. Estimation error of water-leaving radiance is decreased from 79 to 49% at 380nm, though error still remained. The scheme applied to GLI data with absorptive aerosol, and it was confirmed that this atmospheric correction was effective.
Global Imager (GLI) is the visible to infrared imager aboard ADEOS-II satellite with 30 and 6 channels for 1 km and 250m resolutions, respectively. The sensor was successfully captured the first image on January 25, 2003. Sea surface temperature (SST) will be retrieved in combination with simultaneous SST observation by low-resolution microwave sensor, AMSR-E. Distribution of chlorophyll and other constituents will be obtained from ocean color channels. Frequent observations with 250 m visible channels will be also available, and combination with 1 km ocean color and SST will be useful for coastal applications. Early scientific results of GLI ocean group will be presented in this presentation.
The paper presents initial results of atmospherically corrected ocean color data from the Global Imager (GLI), a moderate resolution spectrometer launched in December 2002 aboard ADEOS-II satellite. The standard GLI atmospheric correction algorithm, which includes an iterative procedure based on in-water optical modeling is first described, followed by brief description of standard in-water algorithms for output geophysical parameters. Ship/buoy-observed and satellite-derived marine reflectances, or normalized water-leaving radiance, are then compared, under vicarious calibration correction factors based on global GLI-SeaWiFS data comparison. The results, over 15 water-leaving radiance match-up data collected mostly off California and off Baja California, show standard errors in GLI estimate of 0.1 to 0.36 μW/cm2/nm/sr for 412, 443, 490, and 565 nm bands, with improved standard errors of 0.09 to 0.14 μW/cm2/nm/sr if in situ data set is limited to those obtained by in-water radiance measurement. Under provisional de-striping procedure, satellite-derived chlorophyll a estimates compares well with 35 ship-measured data collected off California within one day difference from the satellite observation, showing standard error factor of 1.73 (+73% or -43% error).
The presentation focuses on the peculiarity of Asian waters with respect to the atmospheric correction of the satellite ocean color data such as of Ocean Color and Temperature Scanner (OCTS). We first demonstrate the effect of highly turbid case 2 waters on the atmospheric correction via non- zero water reflectance in the near infrared region. The results of applying the OCTS standard correction scheme to typical Chinese coastal OCTS scenes reveal that a significant portion of the area is masked due to the negative water reflectance retrieved by the scheme, even using 765 nm and 865 nm bands instead of 670 and 865 nm pair to determine aerosol contribution. An optical model that relates suspended solid (SS) and chlorophyll-a (Chl-a) concentrations to the near infrared water reflectances was implemented into the atmospheric correction, together with a neural network that estimates Chl-a and SS concentrations. The new iterative scheme is applied to the Chinese coastal scenes and the results are assessed to be favorable. The paper then discuss the modeling of Asian dust aerosol in hope of establishing aerosol models that can be used for atmospheric correction. A set of models are designed with varying controlling parameters such as size distribution, vertical profile, and imaginary part of the refractive index. A series of radiative transfer simulation is conducted and the spectrum of the top-of- atmosphere radiance is compared to that of a Sea Wide Filed- of-view Scanner (SeaWiFS) data obtained under Asian dust event. The results of the comparison suggest that the Asian dust aerosol has unique spectral absorption feature at the blue region (in 412 nm band, i.e.).
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