Adjustment of Color Indices for the Far East Region with the Use of MUMM Atmospheric Correction

Accurate surface reflectance retrieval is crucial for satellite-based Earth observation and various environmental applications. The radiative transfer model (RTM) known as the Second Simulation of a Satellite Signal in the Solar Spectrum vector (6SV) is widely utilized for atmospheric correction of optical satellite data, effectively accounting for various aerosol types and concentrations to derive surface reflectance. However, the accuracy of surface reflectance is significantly affected by the types and concentrations of aerosols in the atmosphere. In particular, anthropogenic aerosols generated from industrialization in East Asia, such as fine particulate matter (PM), constitute a significant proportion of continentally derived aerosols. In this complex atmospheric environment, coastal regions experience a mixture of marine-origin and continent-origin aerosols, which complicates the accurate retrieval of surface reflectance.Although previous studies have applied 6SV to high-resolution satellite data, comparative analyses of various aerosol types and studies reflecting the characteristics of coastal regions in East Asia remain limited. Therefore, this study focuses on the coastal regions of East Asia, comparing surface reflectance retrieved using standard aerosol models (Continental, Maritime, Urban) provided by 6SV with those officially provided by Sentinel-2A. Additionally, comparisons with surface reflectance derived from aerosol data provided by the AErosol RObotic NETwork (AERONET) were conducted to evaluate the accuracy of each method.This study is expected to contribute to enhancing the applicability and reliability of remote sensing data by incorporating and analyzing the aerosol characteristics of coastal regions in East Asia.AcknowledgmentsThis research was supported by Particulate Matter Management Specialized Graduate Program through the Korea Environmental Industry & Technology Institute(KEITI) funded by the Ministry of Environment(MOE). 

Predicting daily PM2.5 concentrations in Texas using high-resolution satellite aerosol optical depth

The impact of different aerosol layering conditions on the high-resolution MODIS/MAIAC AOD retrieval bias: The uncertainty analysis

The iron-oxide content of dust in the atmosphere and most notably its apportionment between hematite (α-Fe2O3) and goethite (α-FeOOH) are key determinants in quantifying dust's light absorption, its top of atmosphere UV radiances used for dust monitoring, and ultimately shortwave dust direct radiative effects (DRE). Hematite and goethite column mass concentrations and iron-oxide mass fractions of total dust mass concentration were retrieved from the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) measurements in the ultraviolet–visible (UV–Vis) channels. The retrievals were performed for dust-identified aerosol plumes using aerosol optical depth (AOD) and spectral imaginary refractive index provided by the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm over six continental regions (North America, North Africa, West Asia, Central Asia, East Asia, and Australia). The dust particles are represented as an internal mixture of non-absorbing host and absorbing hematite and goethite. We use the Maxwell–Garnett effective medium approximation with carefully selected complex refractive indices of hematite and goethite that produce mass fractions of iron oxides species consistent with in situ values found in the literature to derive the hematite and goethite volumetric/mass concentrations from MAIAC EPIC products. We compared the retrieved hematite and goethite concentrations with in situ dust aerosol mineralogical content measurements, as well as with published data. Our data display variations within the published range of hematite, goethite, and iron-oxide mass fractions for pure mineral dust cases. A specific analysis is presented for 15 sites over the main dust source regions. Sites in the central Sahara, Sahel, and Middle East exhibit a greater temporal variability of iron oxides relative to other sites. Niger site (13.52° N, 2.63° E) is dominated by goethite over Harmattan season with median of ~2 weight percentage (wt.%) of iron-oxide. Saudi Arabia site (27.49° N, 41.98° E) over Middle East also exhibited surge of goethite content with the beginning of Shamal season. The Sahel dust is richer in iron-oxide than Saharan and northern China dust except in Summer. The Bodélé Depression area shows a distinctively lower iron-oxide concentration (~1 wt. %) throughout the year. Finally, we show that EPIC data allow to constrain the hematite refractive index. Specifically, we select 5 out of 13 different number of hematite refractive indices widely variable in published laboratory studies by constraining the iron-oxide mass ratio to the known measured values. Provided climatology of hematite and goethite mass fractions across main dust regions of the Earth will be useful for dust shortwave DRE studies and climate modeling.

Abstract. The iron-oxide content of dust in the atmosphere and most notably its apportionment between hematite (α-Fe2O3) and goethite (α-FeOOH) are key determinants in quantifying dust's light absorption, its top of atmosphere UV radiances used for dust monitoring, and ultimately shortwave dust direct radiative effects (DRE). Hematite and goethite column mass concentrations and iron-oxide mass fractions of total dust mass concentration were retrieved from the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) measurements in the ultraviolet–visible (UV–Vis) channels. The retrievals were performed for dust-identified aerosol plumes using aerosol optical depth (AOD) and spectral imaginary refractive index provided by the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm over six continental regions (North America, North Africa, West Asia, Central Asia, East Asia, and Australia). The dust particles are represented as an internal mixture of non-absorbing host and absorbing hematite and goethite. We use the Maxwell–Garnett effective medium approximation with carefully selected complex refractive indices of hematite and goethite that produce mass fractions of iron oxides species consistent with in situ values found in the literature to derive the hematite and goethite volumetric/mass concentrations from MAIAC EPIC products. We compared the retrieved hematite and goethite concentrations with in situ dust aerosol mineralogical content measurements, as well as with published data. Our data display variations within the published range of hematite, goethite, and iron-oxide mass fractions for pure mineral dust cases. A specific analysis is presented for 15 sites over the main dust source regions. Sites in the central Sahara, Sahel, and Middle East exhibit a greater temporal variability of iron oxides relative to other sites. Niger site (13.52° N, 2.63° E) is dominated by goethite over Harmattan season with median of ~2 weight percentage (wt.%) of iron-oxide. Saudi Arabia site (27.49° N, 41.98° E) over Middle East also exhibited surge of goethite content with the beginning of Shamal season. The Sahel dust is richer in iron-oxide than Saharan and northern China dust except in Summer. The Bodele Depression area shows a distinctively lower iron-oxide concentration (~1 wt. %) throughout the year. Finally, we show that EPIC data allow to constrain the hematite refractive index. Specifically, we select 5 out of 13 different number of hematite refractive indices widely variable in published laboratory studies by constraining the iron-oxide mass ratio to the known measured values. Provided climatology of hematite and goethite mass fractions across main dust regions of the Earth will be useful for dust shortwave DRE studies and climate modeling.

The iron-oxide content of dust in the atmosphere and most notably its apportionment between hematite (α-Fe2O3) and goethite (α-FeOOH) are key determinants in quantifying dust's light absorption, its top of atmosphere UV radiances used for dust monitoring, and ultimately shortwave dust direct radiative effects (DRE). Hematite and goethite column mass concentrations and iron-oxide mass fractions of total dust mass concentration were retrieved from the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) measurements in the ultraviolet–visible (UV–Vis) channels. The retrievals were performed for dust-identified aerosol plumes using aerosol optical depth (AOD) and spectral imaginary refractive index provided by the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm over six continental regions (North America, North Africa, West Asia, Central Asia, East Asia, and Australia). The dust particles are represented as an internal mixture of non-absorbing host and absorbing hematite and goethite. We use the Maxwell–Garnett effective medium approximation with carefully selected complex refractive indices of hematite and goethite that produce mass fractions of iron oxides species consistent with in situ values found in the literature to derive the hematite and goethite volumetric/mass concentrations from MAIAC EPIC products. We compared the retrieved hematite and goethite concentrations with in situ dust aerosol mineralogical content measurements, as well as with published data. Our data display variations within the published range of hematite, goethite, and iron-oxide mass fractions for pure mineral dust cases. A specific analysis is presented for 15 sites over the main dust source regions. Sites in the central Sahara, Sahel, and Middle East exhibit a greater temporal variability of iron oxides relative to other sites. Niger site (13.52° N, 2.63° E) is dominated by goethite over Harmattan season with median of ~2 weight percentage (wt.%) of iron-oxide. Saudi Arabia site (27.49° N, 41.98° E) over Middle East also exhibited surge of goethite content with the beginning of Shamal season. The Sahel dust is richer in iron-oxide than Saharan and northern China dust except in Summer. The Bodélé Depression area shows a distinctively lower iron-oxide concentration (~1 wt. %) throughout the year. Finally, we show that EPIC data allow to constrain the hematite refractive index. Specifically, we select 5 out of 13 different number of hematite refractive indices widely variable in published laboratory studies by constraining the iron-oxide mass ratio to the known measured values. Provided climatology of hematite and goethite mass fractions across main dust regions of the Earth will be useful for dust shortwave DRE studies and climate modeling.

The iron-oxide content of dust in the atmosphere and most notably its apportionment between hematite (α-Fe2O3) and goethite (α-FeOOH) are key determinants in quantifying dust's light absorption, its top of atmosphere UV radiances used for dust monitoring, and ultimately shortwave dust direct radiative effects (DRE). Hematite and goethite column mass concentrations and iron-oxide mass fractions of total dust mass concentration were retrieved from the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) measurements in the ultraviolet–visible (UV–Vis) channels. The retrievals were performed for dust-identified aerosol plumes using aerosol optical depth (AOD) and spectral imaginary refractive index provided by the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm over six continental regions (North America, North Africa, West Asia, Central Asia, East Asia, and Australia). The dust particles are represented as an internal mixture of non-absorbing host and absorbing hematite and goethite. We use the Maxwell–Garnett effective medium approximation with carefully selected complex refractive indices of hematite and goethite that produce mass fractions of iron oxides species consistent with in situ values found in the literature to derive the hematite and goethite volumetric/mass concentrations from MAIAC EPIC products. We compared the retrieved hematite and goethite concentrations with in situ dust aerosol mineralogical content measurements, as well as with published data. Our data display variations within the published range of hematite, goethite, and iron-oxide mass fractions for pure mineral dust cases. A specific analysis is presented for 15 sites over the main dust source regions. Sites in the central Sahara, Sahel, and Middle East exhibit a greater temporal variability of iron oxides relative to other sites. Niger site (13.52° N, 2.63° E) is dominated by goethite over Harmattan season with median of ~2 weight percentage (wt.%) of iron-oxide. Saudi Arabia site (27.49° N, 41.98° E) over Middle East also exhibited surge of goethite content with the beginning of Shamal season. The Sahel dust is richer in iron-oxide than Saharan and northern China dust except in Summer. The Bodélé Depression area shows a distinctively lower iron-oxide concentration (~1 wt. %) throughout the year. Finally, we show that EPIC data allow to constrain the hematite refractive index. Specifically, we select 5 out of 13 different number of hematite refractive indices widely variable in published laboratory studies by constraining the iron-oxide mass ratio to the known measured values. Provided climatology of hematite and goethite mass fractions across main dust regions of the Earth will be useful for dust shortwave DRE studies and climate modeling.

Abstract. The iron-oxide content of dust in the atmosphere and most notably its apportionment between hematite (α-Fe2O3) and goethite (α-FeOOH) are key determinants in quantifying dust's light absorption, its top of atmosphere ultraviolet (UV) radiances used for dust monitoring, and ultimately shortwave dust direct radiative effects (DREs). Hematite and goethite column mass concentrations and iron-oxide mass fractions of total dust mass concentration were retrieved from the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) measurements in the ultraviolet–visible (UV–Vis) channels. The retrievals were performed for dust-identified aerosol plumes over land using aerosol optical depth (AOD) and the spectral imaginary refractive index provided by the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm over six continental regions (North America, North Africa, West Asia, Central Asia, East Asia, and Australia). The dust particles are represented as an internal mixture of non-absorbing host and absorbing hematite and goethite. We use the Maxwell Garnett effective medium approximation with carefully selected complex refractive indices of hematite and goethite that produce mass fractions of iron-oxide species consistent with in situ values found in the literature to derive the hematite and goethite volumetric/mass concentrations from MAIAC EPIC products. We compared the retrieved hematite and goethite concentrations with in situ dust aerosol mineralogical content measurements, as well as with published data. Our data display variations within the published range of hematite, goethite, and iron-oxide mass fractions for pure-mineral-dust cases. A specific analysis is presented for 15 sites over the main dust-source regions. Sites in the central Sahara, Sahel, and Middle East exhibit a greater temporal variability of iron oxides relative to other sites. The Niger site (13.52∘ N, 2.63∘ E) is dominated by goethite over the Harmattan season with a median of ∼ 2 weight percentage (wt %) of iron oxide. The Saudi Arabia site (27.49∘ N, 41.98∘ E) over the Middle East also exhibited a surge of goethite content with the beginning of the shamal season. The Sahel dust is richer in iron oxide than Saharan and northern China dust except in summer. The Bodélé Depression area shows a distinctively lower iron-oxide concentration (∼ 1 wt %) throughout the year. Finally, we show that EPIC data allow the constraining of the hematite refractive index. Specifically, we select 5 out of 13 different hematite refractive indices that are widely variable in published laboratory studies by constraining the iron-oxide mass ratio to the known measured values. The provided climatology of hematite and goethite mass fractions across the main dust regions of Earth will be useful for dust shortwave DRE studies and climate modeling.

The paper proposes an alternative method of atmospheric correction using the OLCI satellite data for the Black Sea as an example. Currently, for remote sensing problems, the standard Gordon and Wang atmospheric correction algorithm is used in most cases (GW94). Unfortunately, its operation is often accompanied by the appearance of negative values of the spectral radiance coefficient of the sea (remote sensing reflectance) rs( ) in the shortwave region, which means a sufficient number of physically incorrect values and subsequent incorrect calculation of the concentration of chlorophyll-a and yellow matter. In this paper, a simple algorithm is proposed, built exclusively on analytical formulas, where two procedures of interpolation and extrapolation are conceptually implemented simultaneously, extrapolation - via two channels, interpolation based on the constancy of the color index ratio (CI = rs(412)/ rs(443) = 0.8). Using individual examples of OLCI scanner data, the performance GW94 of the new algorithm was tested for different states of the atmosphere and sea surface by comparing the results with in-kind measurements of the AERONET-OC platforms, with Level-2 data and with the operation of the regional method of additional correction. The new algorithm was tested under the following conditions: clear atmosphere (presence of background aerosol), presence of dust aerosol, cloud boundaries, presence of sun glare, coccolithophore bloom. When analyzing a number of Sentinel 3A/3B satellite images, it was found that the new simple algorithm was, on average, better than the standard one, which means that there is a prospect for its improvement. The advantage of this approach is its universality and the possibility of its implementation for other water areas, if there are patterns in the variability of the "blue" color index.

A new empirical algorithm is proposed to estimate surface chlorophyll a (Chl) concentrations in the global ocean for Chl ≤ 0.25 mg m−3(∼78% of the global ocean area). The algorithm is based on a color index (CI), defined as the difference between remote‐sensing reflectance (Rrs, sr−1) in the green and a reference formed linearly between Rrsin the blue and red. For low‐Chl waters, in situ data showed a tighter (and therefore better) relationship between CI and Chl than between traditional band ratios and Chl, which was further validated using global data collected concurrently by ship‐borne and Sea‐viewing Wide Field‐of‐view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua instruments. Model simulations showed that for low‐Chl waters, compared with the band‐ratio algorithm, the CI‐based algorithm (CIA) was more tolerant to changes in chlorophyll‐specific backscattering coefficient and performed similarly for different relative contributions of nonphytoplankton absorption. Simulations using existing atmospheric correction approaches further demonstrated that the CIA was much less sensitive than band‐ratio algorithms to various errors induced by instrument noise and imperfect atmospheric correction (including sun glint and whitecap corrections). Image and time series analyses of SeaWiFS and MODIS/Aqua data also showed improved performance in terms of reduced image noise, more coherent spatial and temporal patterns, and better consistency between the two sensors. The reduction in noise and other errors is particularly useful to improve the detection of various ocean features such as eddies. Preliminary tests over Medium‐Resolution Imaging Spectrometer and Coastal Zone Color Scanner data indicate that the new approach should be generally applicable to all past, current, and future ocean color instruments.

Oregano (Origanum syriacum) is popularly called za’atar in the Middle East region. It is widely used in the Mediterranean diet as an aromatic herb. This study aimed to evaluate the preservation effect of natural additives, vacuum packaging, and refrigeration on the quality traits of fresh oregano. In total, 132 fresh oregano samples were formulated and split into 4 groups (n = 33) labeled group A (100% fresh oregano leaves, Control), group B (fresh oregano 63.2%, 15% fresh onion, 20% oil, 1.8% salt), group C (fresh oregano 61.91%, 15% fresh Allium cepa, 20% oil, 1.8% salt, 1.29% sumac), and group D (fresh oregano 59.2%, 15% fresh Allium cepa, 20% corn oil, 1.8% salt, 4% lactic acid, ultimate pH 4.4). Different quality traits such as color index (L*a*b*), microbiological analysis (total aerobic, anaerobic, and psychrotrophic bacteria and yeasts and molds), and sensory features (taste, flavor, appearance, saltiness, and overall acceptance) were assessed during the storage period (42 days) for all groups. Our study showed that the addition of lactic acid (group D) exhibited a strong preservation effect against aerobic and anaerobic bacteria. In this context, group D had significantly lower aerobic and anaerobic bacterial counts (5.12 vs. 6.7, 6, and 6.7 log (cfu/g); p < 0.05) and (4.75 vs. 6.6, 6.1, 6.77 (cfu/g); p < 0.05) than group A, B, and C; respectively. Group D exhibited significantly (p < 0.05) lower psychrotrophic bacterial count (3.6 log (cfu/g)) during the whole period of storage compared with control. Group B had a lower redness index (a*) (−3.3 vs. −1.8, −1.65, −1.23; p < 0.05) than groups A, C, and D; respectively. In conclusion, our study showed that there is a possibility of improving the preservation of oregano (Origanum syriacum) by using lactic acid and sumac combined with vacuum packaging under refrigeration conditions.

A new algorithm for estimating particulate inorganic carbon (PIC) concentrations from ocean color measurements is presented. PIC plays an important role in the global carbon cycle through the oceanic carbonate pump, therefore accurate estimations of PIC concentrations from satellite remote sensing are crucial for observing changes on a global scale. An extensive global data set was created from field and satellite observations for investigating the relationship between PIC concentrations and differences in the remote sensing reflectance (Rrs) at green, red, and near‐infrared (NIR) wavebands. Three color indices were defined: two as the relative height of Rrs(667) above a baseline running between Rrs(547) and an Rrs in the NIR (either 748 or 869 nm), and one as the difference between Rrs(547) and Rrs(667). All three color indices were found to explain over 90% of the variance in field‐measured PIC. But, due to the lack of availability of Rrs(NIR) in the standard ocean color data products, most of the further analysis presented here was done using the color index determined from only two bands. The new two‐band color index algorithm was found to retrieve PIC concentrations more accurately than the current standard algorithm used in generating global PIC data products. Application of the new algorithm to satellite imagery showed patterns on the global scale as revealed from field measurements. The new algorithm was more resistant to atmospheric correction errors and residual errors in sun glint corrections, as seen by a reduction in the speckling and patchiness in the satellite‐derived PIC images.

We call a photometric system the set of passbands used in astronomy for photometric measurements. A photometric system contains at least two passbands. The maximum number of bands is only limited by the capacity of the data processing equipment which the investigator has at his disposal. Usually, astronomical reasons will determine the choice of the shape of the passbands and their number. This explains the diversity of photometric systems, which is sometimes strongly criticized in astronomical circles. The criticism is not entirely justified. Each system has been chosen and constructed by its author to satisfy the requirements of a well-defined problem. Existing systems rarely meet the needs of a new problem, and the lack of suitability often causes a loss of information. On the other hand, it is valid to criticize the publication of photometric measurements which do not give very accurate information about the shape of the passbands. In the preceding chapters we have shown the effects of differences in μ and λ0 upon the relationships between colour indices, upon atmospheric extinction corrections, and upon the shapes and slopes of reddening lines. Precise knowledge of the shapes of the passbands is indispensable: (a) to reproduce the photometric system technically; (b) to preserve the system over the course of time; and (c) to compare the results of measurements with theoretical modelshistory

In this paper, we propose to analyze the values of the “blue” color index for further use in additional atmospheric correction of Level 2 remote sensing reflectance data for the waters of the Black Sea. Regardless of seasonal phenomena, atmospheric conditions, and the type of water, the average color index in the short-wave region, according to in situ measurements CI(412/443), varies from 0.77 to 0.83. The most frequently observed value is 0.8. In turn, the values of the “blue” color index CI(412/443) according to the satellite data of MODIS Aqua/Terra, VIIRS SNPP, and OLCI Sentinel 3A scanners showed a large scatter in values based on the standard deviation of the sample. The paper proposes to introduce the value of the minimum allowable threshold CI(412/443) &gt; 0.59 based on the small variance found from in situ measurements, as well as on the basis of a theoretical estimate of the possible values of the index CI(412/443) when varying the backscattering exponent and the exponent for the absorption approximation. The quality check of the remote sensing data showed that, according to this selection criterion, 15% of data are physically incorrect for MODIS Aqua, 30% for MODIS Terra, 20% for Sentinel 3A, and 26% for VIIRS SNPP. In the course of the work, it was shown that the MODIS Aqua satellite provides the most high-quality and reliable information about the optical characteristics of the Black Sea.

Ocean color remote sensing is vital for monitoring marine ecosystems, but accurate retrieval of ocean color parameters remains challenging in regions affected by strongly absorbing aerosols such as dust, biomass burning, and industrial pollution. To address this issue, we leveraged the Ocean Color–XGBoost with Radiative Transfer simulation (OC-XGBRT) atmospheric correction (AC) algorithm to improve the accuracy of remote sensing reflectance ( R r s (λ)) in blue bands (412, 443, and 488 nm) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor under the absorbing aerosol conditions. We integrated the OC-XGBRT AC algorithm with traditional bio-optical retrieval models (Ocean Color Index (OCI), KD2M, and Quasi-Analytical Algorithm (QAA)) to estimate chlorophyll-a concentration (CHL), diffuse attenuation coefficient for downwelling irradiance at 490 nm ( K d ( 490 ) ), and absorption coefficient of detritus and gelbstoff at 443 nm ( a d g ( 443 ) ), and further compared the retrieval results with those derived from three widely used AC algorithms (NASA NIR, OC-SMART, and POLYMER). Results of validation against in situ measurements from the SeaWiFS Bio-optical Archive and Storage (SeaBASS), Aerosol Robotic Network-Ocean Color (AERONET-OC), and GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments (GLORIA) demonstrated that the OC-XGBRT outperformed three comparative AC algorithms (NASA NIR, OC-SMART, and POLYMER) under the absorbing aerosol conditions. Specifically, the proposed algorithm achieved markedly higher coefficient of determination (R 2 ) values (0.57 for CHL and 0.45 for a d g ( 443 ) ) and lower Mean Absolute Percentage Deviation (MAPD) values (58.4% for CHL and 63.7% for a d g ( 443 ) ), representing a clear improvement over other algorithms under absorbing aerosol conditions. Applications in five typical oceanic regions frequently influenced by absorbing aerosols, including the west coast of North Africa, the Persian Gulf, the west coast of North America, the Black Sea, and the Chinese Bohai-Yellow Sea, showed that the proposed approach substantially improved the spatial coverage and temporal continuity of ocean color products, especially for a d g ( 443 ) , which is most sensitive to the interference of absorbing aerosol. Overall, OC-XGBRT algorithm provides an effective solution for improving ocean color products in complex atmospheric conditions and supports more reliable monitoring of coastal ecosystems.