scholarly journals The Sensitivity of SeaWiFS Ocean Color Retrievals to Aerosol Amount and Type

2016 ◽  
Vol 33 (6) ◽  
pp. 1185-1209 ◽  
Author(s):  
Ralph A. Kahn ◽  
Andrew M. Sayer ◽  
Ziauddin Ahmad ◽  
Bryan A. Franz
Keyword(s):  
Ocean Color ◽  
Atmospheric Correction ◽  
Single Scattering ◽  
Medium Size ◽  
Wide Field ◽  
Anthropogenic Aerosols ◽  
Transport Pathways ◽  
Nonabsorbing Medium ◽  
Absorbing Aerosols ◽  
Aerosol Type

AbstractAs atmospheric reflectance dominates top-of-the-atmosphere radiance over ocean, atmospheric correction is a critical component of ocean color retrievals. This paper explores the operational Sea-viewing Wide Field-of-view Sensor (SeaWiFS) algorithm atmospheric correction with ~13 000 coincident surface-based aerosol measurements. Aerosol optical depth at 440 nm (AOD440) is overestimated for AOD below ~0.1–0.15 and is increasingly underestimated at higher AOD; also, single-scattering albedo (SSA) appears overestimated when the actual value <~0.96. AOD440 and its spectral slope tend to be overestimated preferentially for coarse-mode particles. Sensitivity analysis shows that changes in these factors lead to systematic differences in derived ocean water-leaving reflectance (Rrs) at 440 nm. The standard SeaWiFS algorithm compensates for AOD anomalies in the presence of nonabsorbing, medium-size-dominated aerosols. However, at low AOD and with absorbing aerosols, in situ observations and previous case studies demonstrate that retrieved Rrs is sensitive to spectral AOD and possibly also SSA anomalies. Stratifying the dataset by aerosol-type proxies shows the dependence of the AOD anomaly and resulting Rrs patterns on aerosol type, though the correlation with the SSA anomaly is too subtle to be quantified with these data. Retrieved chlorophyll-a concentrations (Chl) are affected in a complex way by Rrs differences, and these effects occur preferentially at high and low Chl values. Absorbing aerosol effects are likely to be most important over biologically productive waters near coasts and along major aerosol transport pathways. These results suggest that future ocean color spacecraft missions aiming to cover the range of naturally occurring and anthropogenic aerosols, especially at wavelengths shorter than 440 nm, will require better aerosol amount and type constraints.

scholarly journals Multi-Satellite Retrieval of SSA using OMI-MODIS algorithm

2018 ◽  
Author(s):  
Kruthika Eswaran ◽  
Sreedharan Krishnakumari Satheesh ◽  
Jayaraman Srinivasan
Keyword(s):  
Radiative Forcing ◽  
Single Scattering ◽  
Retrieval Algorithm ◽  
Ozone Monitoring Instrument ◽  
Aerosol Composition ◽  
Aerosol Radiative Forcing ◽  
Aerosol Absorption ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Absorbing Aerosols ◽  
Aerosol Type

Abstract. Single scattering albedo (SSA) represents a unique identification of aerosol type and aerosol radiative forcing. However, SSA retrievals are highly uncertain due cloud contamination and aerosol composition. Recent improvement in the SSA retrieval algorithm has combined the superior cloud masking technique of Moderate Resolution Imaging Spectroradiometer (MODIS) and the better sensitivity of Ozone Monitoring Instrument (OMI) to aerosol absorption. The combined OMI-MODIS algorithm has been validated over a small spatial and temporal scale only. The present study validates the algorithm over global oceans for the period 2008–2012. The geographical heterogeneity in the aerosol type and concentration over the Atlantic Ocean, the Arabian Sea and the Bay of Bengal was useful to delineate the effect of aerosol type on the retrieval algorithm. We also noted that OMI overestimates SSA when absorbing aerosols were present closer to the surface. We attribute this overestimation to data discontinuity in the aerosol height climatology derived from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. OMI uses pre-defined aerosol heights over regions where CALIPSO climatology is not present leading to overestimation of SSA. The importance of aerosol height was also studied using the Santa Barbara DISORT radiative transfer (SBDART) model. The results from the joint retrieval were validated with ground-based measurements and it was seen that OMI-MODIS SSA retrievals were better constrained than OMI only retrieval.

scholarly journals Performance evaluation of ocean color satellite models for deriving accurate chlorophyll estimates in the Gulf of Saint Lawrence

2014 ◽  
Vol 11 (6) ◽  
pp. 9299-9340
Author(s):  
M. Montes-Hugo ◽  
H. Bouakba ◽  
R. Arnone
Keyword(s):  
Chlorophyll Concentration ◽  
Ocean Color ◽  
Atmospheric Correction ◽  
Relative Bias ◽  
Wide Field ◽  
Absolute Bias ◽  
Analysis System ◽  
Data Analysis System ◽  
The Impact

Abstract. The understanding of phytoplankton dynamics in the Gulf of the Saint Lawrence (GSL) is critical for managing major fisheries off the Canadian East coast. In this study, the accuracy of two atmospheric correction techniques (NASA standard algorithm, SA, and Kuchinke's spectral optimization, KU) and three ocean color inversion models (Carder's empirical for SeaWiFS (Sea-viewing Wide Field-of-View Sensor), EC, Lee's quasi-analytical, QAA, and Garver- Siegel-Maritorena semi-empirical, GSM) for estimating the phytoplankton absorption coefficient at 443 nm (aph(443)) and the chlorophyll concentration (chl) in the GSL is examined. Each model was validated based on SeaWiFS images and shipboard measurements obtained during May of 2000 and April 2001. In general, aph(443) estimates derived from coupling KU and QAA models presented the smallest differences with respect to in situ determinations as measured by High Pressure liquid Chromatography measurements (median absolute bias per cruise up to 0.005, RMSE up to 0.013). A change on the inversion approach used for estimating aph(443) values produced up to 43.4% increase on prediction error as inferred from the median relative bias per cruise. Likewise, the impact of applying different atmospheric correction schemes was secondary and represented an additive error of up to 24.3%. By using SeaDAS (SeaWiFS Data Analysis System) default values for the optical cross section of phytoplankton (i.e., aph(443) = aph(443)/chl = 0.056 m2mg−1), the median relative bias of our chl estimates as derived from the most accurate spaceborne aph(443) retrievals and with respect to in situ determinations increased up to 29%.

scholarly journals Critical surface albedo and its implications to aerosol remote sensing

2012 ◽  
Vol 5 (7) ◽  
pp. 1653-1665 ◽  
Author(s):  
F. C. Seidel ◽  
C. Popp
Keyword(s):  
Remote Sensing ◽  
Surface Albedo ◽  
Atmospheric Correction ◽  
Single Scattering ◽  
Small Range ◽  
Critical Surface ◽  
Aerosol Absorption ◽  
Sensing Applications ◽  
Aerosol Remote Sensing ◽  
Absorbing Aerosols

Abstract. We analyse the critical surface albedo (CSA) and its implications to aerosol remote sensing. CSA is defined as the surface albedo where the reflectance at top-of-atmosphere (TOA) does not depend on aerosol optical depth (AOD). AOD retrievals are therefore inaccurate at the CSA. The CSA is obtained by derivatives of the TOA reflectance with respect to AOD using a radiative transfer code. We present the CSA and the effect of surface albedo uncertainties on AOD retrieval and atmospheric correction as a function of aerosol single-scattering albedo, illumination and observation geometry, wavelength and AOD. In general, increasing aerosol absorption and increasing scattering angles lead to lower CSA. In contrast to the strict definition of the CSA, we show that the CSA can also slightly depend on AOD and therefore rather represent a small range of surface albedo values. This was often neglected in previous studies. The following implications to aerosol remote sensing applications were found: (i) surface albedo uncertainties result in large AOD retrieval errors, particularly close to the CSA; (ii) AOD retrievals of weakly or non-absorbing aerosols require dark surfaces, while strongly absorbing aerosols can be retrieved more accurately over bright surfaces; (iii) the CSA may help to estimate aerosol absorption; and (iv) the presented sensitivity of the reflectance at TOA to AOD provides error estimations to optimise AOD retrieval algorithms.

scholarly journals Comparison of Aerosol Reflectance Correction Schemes Using Two Near-Infrared Wavelengths for Ocean Color Data Processing

2018 ◽  
Vol 10 (11) ◽  
pp. 1791 ◽  
Author(s):  
Jae-Hyun Ahn ◽  
Young-Je Park ◽  
Hajime Fukushima
Keyword(s):  
Radiative Transfer ◽  
Near Infrared ◽  
Ocean Color ◽  
Atmospheric Correction ◽  
Single Scattering ◽  
Weighting Factor ◽  
Simulation Code ◽  
Aerosol Model ◽  
Median Error ◽  
Visible Wavelengths

This paper reanalyzes the aerosol reflectance correction schemes employed by major ocean color missions. The utilization of two near-infrared (NIR) bands to estimate aerosol reflectance in visible wavelengths has been widely adopted, for example by SeaWiFS/MODIS/VIIRS (GW1994), OCTS/GLI/SGLI (F1998), MERIS/OLCI (AM1999), and GOCI/GOCI-II (A2016). The F1998, AM1999, and A2016 schemes were developed based on GW1994; however, they are implemented differently in terms of aerosol model selection and weighting factor computation. The F1998 scheme determines the contribution of the most appropriate aerosol models in the aerosol optical thickness domain, whereas the GW1994 scheme focuses on single-scattering reflectance. The AM1999 and A2016 schemes both directly resolve the multiple scattering domain contribution. However, A2016 also considers the spectrally dependent weighting factor, whereas AM1999 calculates the spectrally invariant weighting factor. Additionally, ocean color measurements on a geostationary platform, such as GOCI, require more accurate aerosol correction schemes because the measurements are made over a large range of solar zenith angles which causes diurnal instabilities in the atmospheric correction. Herein, the four correction schemes were tested with simulated top-of-atmosphere radiances generated by radiative transfer simulations for three aerosol models. For comparison, look-up tables and test data were generated using the same radiative transfer simulation code. All schemes showed acceptable accuracy, with less than 10% median error in water reflectance retrieval at 443 nm. Notably, the accuracy of the A2016 scheme was similar among different aerosol models, whereas the other schemes tended to provide better accuracy with coarse aerosol models than the fine aerosol models.

scholarly journals Atmospheric Correction of Satellite Ocean Color Remote Sensing in the Presence of High Aerosol Loads

2019 ◽  
Vol 12 (1) ◽  
pp. 31
Author(s):  
Zhihua Mao ◽  
Bangyi Tao ◽  
Peng Chen ◽  
Jianyu Chen ◽  
Zengzhou Hao ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Rayleigh Scattering ◽  
Layer Structure ◽  
Ocean Color ◽  
Atmospheric Correction ◽  
Wide Field ◽  
Systematic Bias ◽  
Multiple Reflections ◽  
Process Data ◽  
Scattering Layer

The coverage of valid pixels of remote-sensing reflectance (Rrs) from ocean color imagery is relatively low due to the presence of clouds. In fact, it is also related to the presence of high aerosol optical depth (AOD) and other factors. In order to increase the valid coverage of satellite-retrieved products, a layer removal scheme for atmospheric correction (LRSAC) has been developed to process the ocean color data. The LRSAC used a five-layer structure including atmospheric absorption layer, Rayleigh scattering layer, aerosol scattering layer, sea surface reflection layer, and water-leaving reflectance layer to deal with the relationship of the components of the atmospheric correction. A nonlinear approach was used to solve the multiple reflections of the interface between two adjoining layers and a step-by-step procedure was used to remove effects of each layer. The LRSAC was used to process data from the sea-viewing wide field-of-view sensor (SeaWiFS) and the results were compared with standard products. The average of valid pixels of the global daily Rrs images of the standard products from 1997 to 2010 is only 11.5%, while it reaches up to 30.5% for the LRSAC. This indicates that the LRSAC recovers approximately 1.65 times of invalid pixels as compared with the standard products. Eight-day standard composite images exhibit many large areas with invalid values due to the presence of high AOD, whereas these areas are filled with valid pixels wusing the LRSAC. The ratio image of the mean valid pixel of the LRSAC to that of the standard products indicates that the number of valid pixels of the LRSAC increases with an increase of AOD. The LRSAC can increase the number of valid pixels by more than two times in about 33.8% of ocean areas with high AOD values. The accuracy of Rrs from the LRSAC was validated using the following two in situ datasets: the Marine Optical BuoY (MOBY) and the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Most matchup pairs are distributed around the 1:1 line indicating that the systematic bias of the LRSAC is relatively small. The global mean relative error (MRE) of Rrs is 7.9% and the root mean square error (RMSE) is 0.00099 sr−1 for the MOBY matchups. Similarly, the MRE and RMSE are 2.1% and 0.0025 sr−1 for the NOMAD matchups, respectively. The accuracy of LRSAC was also evaluated by different groups of matchups according to the increase of AOD values, indicating that the errors of Rrs were little affected by the presence of high AOD values. Therefore, the LRSAC can significantly improve the coverage of valid pixels of Rrs with a similar accuracy in the presence of high AOD.

scholarly journals Updated MISR dark water research aerosol retrieval algorithm – Part 1: Coupled 1.1 km ocean surface chlorophyll <i>a</i> retrievals with empirical calibration corrections

2017 ◽  
Vol 10 (4) ◽  
pp. 1539-1555 ◽  
Author(s):  
James A. Limbacher ◽  
Ralph A. Kahn
Keyword(s):  
Storage System ◽  
Ocean Color ◽  
Atmospheric Correction ◽  
Ocean Surface ◽  
Single Scattering ◽  
Single Scattering Albedo ◽  
Retrieval Algorithm ◽  
Radiometric Calibration ◽  
Color Analysis

Abstract. As aerosol amount and type are key factors in the atmospheric correction required for remote-sensing chlorophyll a concentration (Chl) retrievals, the Multi-angle Imaging SpectroRadiometer (MISR) can contribute to ocean color analysis despite a lack of spectral channels optimized for this application. Conversely, an improved ocean surface constraint should also improve MISR aerosol-type products, especially spectral single-scattering albedo (SSA) retrievals. We introduce a coupled, self-consistent retrieval of Chl together with aerosol over dark water. There are time-varying MISR radiometric calibration errors that significantly affect key spectral reflectance ratios used in the retrievals. Therefore, we also develop and apply new calibration corrections to the MISR top-of-atmosphere (TOA) reflectance data, based on comparisons with coincident MODIS (Moderate Resolution Imaging Spectroradiometer) observations and trend analysis of the MISR TOA bidirectional reflectance factors (BRFs) over three pseudo-invariant desert sites. We run the MISR research retrieval algorithm (RA) with the corrected MISR reflectances to generate MISR-retrieved Chl and compare the MISR Chl values to a set of 49 coincident SeaBASS (SeaWiFS Bio-optical Archive and Storage System) in situ observations. Where Chlin situ < 1.5 mg m−3, the results from our Chl model are expected to be of highest quality, due to algorithmic assumption validity. Comparing MISR RA Chl to the 49 coincident SeaBASS observations, we report a correlation coefficient (r) of 0.86, a root-mean-square error (RMSE) of 0.25, and a median absolute error (MAE) of 0.10. Statistically, a two-sample Kolmogorov–Smirnov test indicates that it is not possible to distinguish between MISR Chl and available SeaBASS in situ Chl values (p > 0.1). We also compare MODIS–Terra and MISR RA Chl statistically, over much broader regions. With about 1.5 million MISR–MODIS collocations having MODIS Chl < 1.5 mg m−3, MISR and MODIS show very good agreement: r = 0. 96, MAE  =  0.09, and RMSE  =  0.15. The new dark water aerosol/Chl RA can retrieve Chl in low-Chl, case I waters, independent of other imagers such as MODIS, via a largely physical algorithm, compared to the commonly applied statistical ones. At a minimum, MISR's multi-angle data should help reduce uncertainties in the MODIS–Terra ocean color retrieval where coincident measurements are made, while also allowing for a more robust retrieval of particle properties such as spectral single-scattering albedo.

scholarly journals Critical surface albedo and its implications to aerosol remote sensing

2011 ◽  
Vol 4 (6) ◽  
pp. 7725-7750 ◽  
Author(s):  
F. C. Seidel ◽  
C. Popp
Keyword(s):  
Remote Sensing ◽  
Surface Albedo ◽  
Atmospheric Correction ◽  
Single Scattering ◽  
Critical Surface ◽  
Aerosol Absorption ◽  
Sensing Applications ◽  
Aerosol Remote Sensing ◽  
Absorbing Aerosols ◽  
Observation Geometry

Abstract. We analyse the critical surface albedo (CSA) and its implications to aerosol remote sensing. CSA is defined as the surface albedo, where the reflectance at top-of-atmosphere (TOA) does not depend on aerosol optical depth (AOD). AOD retrievals are therefore inaccurate at the CSA. The CSA is obtained by derivatives of the TOA reflectance with respect to AOD using a radiative transfer code. We present the CSA and the effect of surface albedo uncertainties on AOD retrieval and atmospheric correction as a function of aerosol single-scattering albedo, illumination and observation geometry, wavelength and AOD. In general, increasing aerosol absorption and increasing scattering angles lead to lower CSA. We show that the CSA also depends on AOD, which was often neglected in previous studies. The following implications to aerosol remote sensing applications were found: (i) surface albedo uncertainties result in large AOD retrieval errors, particularly close to the CSA; (ii) AOD retrievals of non-absorbing aerosols require dark surfaces, while strong absorbing aerosols can be retrieved more accurately over bright surfaces; (iii) the CSA may help to estimate aerosol absorption; and (iv) the presented sensitivity of the reflectance at TOA to AOD provides error estimations to optimise AOD retrieval algorithms.

scholarly journals Variability of Major Aerosol Types in China Classified Using AERONET Measurements

2019 ◽  
Vol 11 (20) ◽  
pp. 2334 ◽  
Author(s):  
Lu Zhang ◽  
Jing Li
Keyword(s):  
Temporal Distribution ◽  
Northwest China ◽  
Single Scattering ◽  
Self Organizing Map ◽  
Satellite Retrieval ◽  
Aerosol Forcing ◽  
Absorbing Aerosols ◽  
Autumn And Winter ◽  
Aerosol Types ◽  
Aerosol Type

Aerosol type is a critical piece of information in both aerosol forcing estimation and passive satellite remote sensing. However, the major aerosol types in China and their variability is still less understood. This work uses direct sun measurements and inversion derived parameters from 47 sites within the Aerosol Robotic Network (AERONET) in China, with more than 39,000 records obtained between April 1998 and January 2017, to identify dominant aerosol types using two independent methods, namely, K means and Self Organizing Map (SOM). In total, we define four aerosol types, namely, desert dust, scattering mixed, absorbing mixed and scattering fine, based on their optical and microphysical characteristics. Seasonally, dust aerosols mainly occur in the spring and over North and Northwest China; scattering mixed are more common in the spring and summer, whereas absorbing aerosols mostly occur in the autumn and winter during heating period, and scattering fine aerosols have their highest occurrence frequency in summer over East China. Based on their spatial and temporal distribution, we also generate seasonal aerosol type maps that can be used for passive satellite retrieval. Compared with the global models used in most satellite retrieval algorithms, the unique feature of East Asian aerosols is the curved single scattering albedo spectrum, which could be related to the mixing of black carbon with dust or organic aerosols.

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