Natural variability of aerosol inherent optical properties: consequences for atmospheric correction over water

A good knowledge of the inherent optical properties (IOPs) of aerosols is a strong requirement for accurately performing atmospheric correction over the ocean. For several decades, IOPs have been computed using standard aerosol models (SAMs) that characterize the micro-physical properties of aerosols. These SAMs were used in the last generation of the Medium Resolution Imaging Spectrometer (MERIS) auxiliary data files (ADFs) to feed the atmospheric correction algorithm. Alternatively, Aerosol Robotic Network (AERONET) measurements can also provide IOPs. We built a database with the aerosol IOPs encountered over four AERONET stations in the North Sea plus one at the Acqua Alta Oceanographic Tower (AAOT, Venice, Italy). Several thousands of data sequences containing the aerosol IOPs were processed with filtering techniques and statistical methods to produce 16 classes of IOPs. An analysis of the dispersion of the IOPs within each class was conducted to evaluate the induced errors in the MERIS level-2 (L2) products in European coastal waters. We also investigated the reduction in the errors that can be achieved if there is access to auxiliary meteorological data (i.e. the relative humidity) or by using the bidirectionality in the satellite measurements, such as for advanced along-track scanning radiometer (AATSR) data.     

The sensitivity of MERIS atmospheric correction over water to aerosol climatology

Performing a classical atmospheric correction over water requires a well-defined climatology representative of the aerosols encountered in the remote areas of oceans. Different climatologies built up at the global scale are candidates to be implemented, as an auxiliary data file (ADF) including look-up tables (LUTs) with radiative properties of the aerosols, in a traditional atmospheric correction algorithm. In addition to these, two regional climatologies were developed in the 2-Seas region, comprising both the Eastern English Channel and the North Sea, and at the Acqua Alta Oceanographic Tower (AAOT) in the Adriatic Sea. By using the optical data processor of the European Space Agency (ODESA), Medium Resolution Imaging Spectrometer (MERIS) level-1 (L1) data extracted from the MERis MAtchup In-situ Database (MERMAID) were processed to obtain the level-2 (L2) products over water. For a given climatology, a full processing chain was developed to generate the MERIS aerosol LUTs suitable to ODESA. The final step consisted of an analysis of the L2 products, for both the aerosols and marine reflectance, in the framework of the evaluation of the performance of each climatology in atmospheric correction over oceans. Finally, we recommend using the regional aerosol climatologies available from the AErosol RObotic NETwork (AERONET) database, at least for the retrieval of the L2 aerosol product. In regard to marine reflectance, this remains more challenging and needs a more extensive analysis.     

Validation of satellite ocean color primary products at optically complex coastal sites: Northern Adriatic Sea, Northern Baltic Proper and Gulf of Finland

The study presents and discusses the application of in situ data from the ocean color component of the Aerosol Robotic Network (AERONET-OC) to assess primary remote sensing products from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the AQUA platform and from the Sea-viewing Wide-Field-of-view Sensor (SeaWiFS) on the OrbView-2 spacecraft. Three AERONET-OC European coastal sites exhibiting different atmospheric and marine optical properties were considered for the study: the Acqua Alta Oceanographic Tower (AAOT) in the northern Adriatic Sea representing Case-1 and Case-2 moderately sediment dominated waters; and, the Gustaf Dalen Lighthouse Tower (GDLT) in the northern Baltic Proper and the Helsinki Lighthouse Tower (HLT) in the Gulf of Finland, both characterized by Case-2 waters dominated by colored dissolved organic matter (CDOM). The analysis of MODIS derived normalized water-leaving radiance at 551 nm, L_WN(551), has shown relatively good results for all sites with uncertainties of the order of 10% and biases ranging from − 1 to − 4%. Larger uncertainty and bias have been observed at 443 nm for the AAOT (i.e., 18 and − 7%, respectively). At the same center wavelength, results for GDLT and HLT have exhibited much larger uncertainties (i.e., 56 and 67%, respectively) and biases (i.e., 18 and 25%, respectively), which undermine the possibility of presently using remote sensing L_WN data at the blue center wavelengths for bio-optical investigations in the Baltic Sea. An evaluation of satellite derived aerosol optical thickness, τ_a, has shown uncertainties and biases of the order of tens of percent increasing with wavelength at all sites. Specifically, MODIS derived τ_a at 869 nm has shown an overestimate of 71% at the AAOT, 101% at GDLT and 91% at HLT, respectively. This result highlights the effects of a limited number of aerosol models for the atmospheric correction process, and might also indicate the need of applying a vicarious calibration factor to the remote sensing data at the 869 nm center wavelength to remove the effects of uncertainties in the atmospheric optical model and the space sensor radiometric calibration. Similar results have been obtained from the analysis of SeaWiFS data. Finally, in view of illustrating the possibility of increasing the accuracy of satellite regional radiometric products, AERONET-OC data have been applied to reduce systematic errors in MODIS and Medium Resolution Imaging Spectrometer (MERIS) L_WN data likely due to the atmospheric correction process. Results relying on MODIS match-ups for the Baltic Sites (i.e., GDLT and HLT) and MERIS matchups for the AAOT, have indicated a substantial reduction of both uncertainty and bias in the blue and red center wavelengths.     

In situ validation of MERIS marine reflectance off the southwest Iberian Peninsula: assessment of vicarious adjustment and corrections for near-land adjacency

Water-leaving reflectance (ρ_w) data from the European Space Agency ocean colour sensor Medium Resolution Imaging Spectrometer (MERIS) was validated with in situ ρ_w between October 2008 and November 2011, off Sagres on the southwest coast of the Iberian Peninsula. The study area is exceptional, since Stations A, B, and C at 2, 10, and 18 km offshore are in optically deep waters at approximately 40, 100, and 160 m, respectively. These stations showed consistently similar bio-optical properties, characteristic of Case 1 waters, enabling the evaluation of adjacency effects independent of the usual co-varying inputs of coastal waters. Using the third reprocessing of MERIS with the standard MEGS 8.1 processor, four different combinations of procedures were tested to improve the calibration between MERIS products and in situ data. These combinations included no vicarious adjustment (NoVIC), vicarious adjustment (VIC), and, for mitigating the effects of land adjacency on MERIS ρ_w, the improved contrast between ocean and land (ICOL) processor (version 2.7.4) and VIC + ICOL. Out of approximately 130 potential matchups for each station, 38–77%, 74–86%, and 88–90% were achieved at Stations A, B, and C, respectively, depending on which of the four combinations were used. Analyses of ρ_w comparing these various procedures, including statistics, scatter plots, histograms, and MERIS full-resolution images, showed that the VIC procedure compared with NoVIC produced minimal changes to the calibration. For example, at the oceanic Station C, the regression slope was closer to unity at all wavelengths with NoVIC compared to VIC, whereas, with the exception of wavelengths 412 and 443 nm, the intercept, mean ratio (MR), absolute percentage difference (APD), and relative percentage difference (RPD) were better with NoVIC. The differences for MR and APD indicate that there was marginal improvement for these two bands with VIC, and an over-adjustment with RPD. ICOL also showed inconsistent results for improving the retrieval of the near-shore conditions, but under some conditions, such as ρ_w at wavelength 560 nm, the improvement was striking. VIC + ICOL showed results intermediate between those of VIC and ICOL implemented separately. In relation to other validation sites, the offshore Station C at Sagres had much in common with the Mediterranean deep water, BOUSSOLE buoy, although the matchup statistics between MERIS ρ_w and in situ ρ_w were much better for Sagres than for BOUSSOLE. Strikingly, the matchup statistics for ρ_w at Sagres were very similar to those for the Acqua Alta Oceanographic Tower (AAOT), where the AAOT showed more scatter at 412 nm, probably because of the atmospheric correction where the aerosol optical thickness is higher at the AAOT. Conversely, Sagres showed much greater scatter at 665 nm in the red as the values were generally close to the limits of detection owing to the clearer waters at Sagres compared to the more turbid waters at the AAOT.     

Atmospheric correction algorithm for MERIS above case‐2 waters

The development and validation of an atmospheric correction algorithm designed for the Medium Resolution Imaging Spectrometer (MERIS) with special emphasis on case‐2 waters is described. The algorithm is based on inverse modelling of radiative transfer (RT) calculations using artificial neural network (ANN) techniques. The presented correction scheme is implemented as a direct inversion of spectral top‐of‐atmosphere (TOA) radiances into spectral remote sensing reflectances at the bottom‐of‐atmosphere (BOA), with additional output of the aerosol optical thickness (AOT) at four wavelengths for validation purposes. The inversion algorithm was applied to 13 MERIS Level1b data tracks of 2002–2003, covering the optically complex waters of the North and Baltic Sea region. A validation of the retrieved AOTs was performed with coincident in situ automatic sun–sky scanning radiometer measurements of the Aerosol Robotic Network (AERONET) from Helgoland Island located in the German Bight. The accuracy of the derived reflectances was validated with concurrent ship‐borne reflectance measurements of the SIMBADA hand‐held field radiometer. Compared to the MERIS Level2 standard reflectance product generated by the processor versions 3.55, 4.06 and 6.3, the results of the proposed algorithm show a significant improvement in accuracy, especially in the blue part of the spectrum, where the MERIS Level2 reflectances result in errors up to 122% compared to only 19% with the proposed algorithm. The overall mean errors within the spectral range of 412.5–708.75 nm are calculated to be 46.2% and 18.9% for the MERIS Level2 product and the presented algorithm, respectively.     

The atmospheric correction of water colour and the quantitative retrieval of suspended particulate matter in Case II waters: Application to MERIS

The remote sensing of turbid waters (Case II) using the Medium Resolution Imaging Spectrometer (MERIS) requires new approaches for atmospheric correction of the data. Unlike the open ocean (Case I waters) there are no wavelengths where the water-leaving radiance is zero. A coupled hydrological atmospheric model is described here. The model solves the water-leaving radiance and atmospheric path radiance in the near-infrared (NIR) over Case II turbid waters. The theoretical basis of this model is described, together with its place in the proposed MERIS processing architecture. Flagging procedures are presented that allow seamless correction of both Case I waters, using conventional models, and Case II waters using the proposed model. Preliminary validation of the model over turbid waters in the Humber estuary, UK is presented using Compact Airborne Spectrographic Imager (CASI) imagery to simulate the MERIS satellite sensor. The results presented show that the atmospheric correction scheme has superior performance over the standard single scattering approach, which assumes that water-leaving radiance in the NIR is zero. Despite problems of validating data in such highly dynamic tidal waters, the results show that retrievals of sediments within 50% are possible from algorithms derived from the theoretical models.     

Simultaneous determination of aerosol optical thickness and surface reflectance using ASTER visible to near-infrared data over land

An innovative method for the determination of aerosol optical thickness (AOT) and surface reflectance for operational use of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) visible to near-infrared data is presented. This method is designed to obtain the atmospheric parameters needed in the correction of the image. This method is based on a simplified radiative transfer equation describing the relation between the ground surface reflectance, AOT and top-of-atmosphere reflectance. By exploiting the ASTER dual-angle view capabilities in band 3N (Nadir) and band 3B (Backwards), surface reflectance and AOT can be retrieved synchronously. Thus, it solves the problem of separating atmospheric radiance from the transmitted radiance of the surface to some extent. After applying this new atmospheric correction method to three areas of ASTER images, Beijing urban city, the Heihe River Basin and Hong Kong of China, ASTER surface reflectance products (AST07) were obtained. AOT values from in situ measurements of CIMEL Electronique 318 Sun Photometers or AERONET (AErosol RObotic NETwork) and surface reflectance in situ measured using an Analytical Spectral Device (ASD) Field Spec spectral radiometer are used for validation. AOT derived from the new method is consistent with in situ station measurements from CIMEL Electronique 318 Sun Photometer and level 2.0 data from AERONET, with correlation coefficient (R ²) of 0.98 and root mean square error of 0.05, whereas Multi-angle Imaging Spectroradiometer AOT products underestimate AERONET AOT and Moderate-Resolution Imaging Spectroradiometer AOT products overestimate AERONET AOT in these regions. More encouraging is the comparison between the corrected surface reflectance, AST07 and ASD measurements. Root mean square error of AST07 and retrieved surface reflectance are as follows: band 1 (556 nm) = 0.04 and 0.05; band 2 (661 nm) = 0.036 and 0.035; band 3 (807 nm) = 0.056 and 0.038, which suggests that compared with AST07 in bands 2 and 3, retrieved surface reflectance has better agreement with measured reflectance from ASD.     

Estimation of variable atmospheric parameters for the atmospheric correction of satellite images

The information about variable components of the atmosphere (aerosol, water vapour, and ozone) during acquisition is required for the atmospheric correction of spectral images acquired by shortwave sensors of the Earth observing remote-sensing satellites. The procedure to estimate aerosol optical depth and columnar water vapour by the inversion of the atmospheric radiative transfer model 6S using moderate-resolution spectra of incident solar radiation is proposed. Comparison to the results obtained by the Aerosol Robotic Network AERONET at an AERONET site at the distance of 50 km on days when both sensors were in the same air mass shows systematic overestimation both of aerosol optical depth and of columnar water vapour if aerosol optical depth is estimated in the wavelength range of 365–425 nm and columnar water in the range of 895–985 nm using spectra of total irradiance. If more wavelengths and diffuse-to-total spectral irradiance ratio are implemented in the inversion, the bias of estimated water vapour decreases, but aerosol optical depth is underestimated. The estimates at 50 km distance are well correlated. The modelled spectral irradiance using estimated atmospheric parameters matches the measured spectra with high accuracy. In the spectral bands of the Sentinel-2 MultiSpectral Instrument (MSI), the differences do not exceed 2%.     

MERIS atmospheric correction over coastal waters: validation of the MERIS aerosol models using AERONET

Standard aerosol models (SAMs) are used for the Medium-Resolution Imaging Spectrometer (MERIS) level-2 processing over water, first to remotely sense the aerosols in the near-infrared and secondly to perform the atmospheric correction for ocean colour analysis. However, are these SAMs still suitable over coastal areas? The present work was intended to answer that question through the use of the Aerosol Robotic Network (AERONET) by selecting CIMEL radiometers operating over the sea surface or near the coastline. The current official MERIS algorithm overestimates aerosol optical thickness (AOT) over coastal waters at 865 nm. This can be related either to incorrect assumptions of the underlying surface assumption or to the assumptions of the aerosol properties (e.g. phase function). This study looks at the importance of aerosol modelling and confirms that the improved aerosol models must be used in the retrieval chain. Extinction measurements were first used to derive the aerosol optical thicknesses (AOTs). The spectral dependency of the AOTs between 670 nm and 865 nm allowed the selection of a standard aerosol model. The ability of the standard aerosol models to retrieve the AOTs at 440 nm was then analysed as a key element in the extrapolation of the aerosol path radiance from the near-infrared to the blue spectral range. The two outputs of this analysis are systematic biases in this retrieval process and accordingly they are an estimation of the dispersion. The first output can be defined as a corrective factor in the aerosol path radiance at 440 nm and the second output can be used for error analysis. A radiative transfer code was used to simulate the sky radiance in the principal plane of acquisition. Comparisons at 870 nm illustrated the ability of the standard aerosol models to retrieve the aerosol path radiances with a direct impact on the AOT retrieval from satellite observations at 865 nm.     

Uncertainties in radiative transfer computations: consequences on the MERIS products over land

The main objectives of MERIS (MEdium Resolution Imaging Spectrometer) consist of atmospheric processes related to the water vapour column and aerosol optical properties designed for meteorological applications, and the land surface properties as well as the bio‐optical oceanography. In this context, operational MERIS level‐2 processing uses auxiliary data generated by two radiative transfer tools. These two codes simulate upwelling radiances within a coupled ‘atmosphere–land’ system, using different approaches based on the matrix‐operator method (FUB, Freie Universität Berlin), the discrete ordinate method and the successive orders technique (ULCO, Université du Littoral Côte d'Opale). Intervalidation of these two radiative transfer tools was performed in order to implement them in the MERIS level‐2 processing. For cases without gaseous absorption, the scattering processes both by the molecules and the aerosols were retrieved within a few tenths of a percentage point. Nevertheless, some substantial discrepancies occur if the polarization is not accounted for, mainly in the Rayleigh scattering computations. Errors on the aerosol optical thickness reach up to 25% in some geometries as observed in the MERIS images. The parametrization of gaseous absorption (H₂O and O₂) defined for each of these two codes leads to a good agreement for the MERIS bands with residual absorption. In the strong absorption bands (761.75 nm and 900 nm), the FUB computations well match the results derived from a line‐by‐line (LBL) code with a very high spectral resolution. Note that the oxygen absorption at 761.75 nm is very sensitive to the characteristics of the sensor spectral response and requires accurate calculations with the LBL code. Consequently, the ULCO code has been implemented in the MERIS level‐2 processing to include polarization in the scattering processes and to correct for slightly gaseous absorption, the FUB code to derive the water vapour abundance, and the LBL code to determine the barometric pressure. Impacts of the differences in the look‐up table generation on the level‐2 products (aerosol model, surface reflectance and barometric pressure) are also analysed and illustrated.     

Validating a new algorithm for estimating aerosol optical depths over land from MODIS imagery

Aerosols greatly affect the signals of satellite sensor imagery for remote sensing of land surfaces and play a dual role in global climate change and the hydrological cycle. However, there has not been a reliable method for estimating aerosol properties over land directly from multispectral remotely sensed imagery. In a recent study, a new algorithm to estimate aerosol optical depths (AODs) from Moderate‐Resolution Imaging Spectroradiometer (MODIS) imagery suitable for all land surfaces was proposed. It is based on a sequence of imagery over a period of time with the assumption that the surface property is relatively stable and atmospheric conditions vary much more dramatically. Although this algorithm was validated over several sites, more validation was necessary. In this study, this algorithm was validated using 3‐month measurements at 25 AErosol RObotic NETwork (AERONET) sites in North America. The validation results show that this algorithm can estimate AODs with close agreement with the AERONET measurements [R ² = 0.69, root mean square error (RMSE) 0.06].     

Atmospheric correction of ENVISAT/MERIS data over inland waters: Validation for European lakes

Traditional methods for aerosol retrieval and atmospheric correction of remote sensing data over water surfaces are based on the assumption of zero water reflectance in the near-infrared. Another type of approach which is becoming very popular in atmospheric correction over water is based on the simultaneous retrieval of atmospheric and water parameters through the inversion of coupled atmospheric and bio-optical water models. Both types of approaches may lead to substantial errors over optically-complex water bodies, such as case II waters, in which a wide range of temporal and spatial variations in the concentration of water constituents is expected. This causes the water reflectance in the near-infrared to be non-negligible, and that the water reflectance response under extreme values of the water constituents cannot be described by the assumed bio-optical models. As an alternative to these methods, the SCAPE-M atmospheric processor is proposed in this paper for the automatic atmospheric correction of ENVISAT/MERIS data over inland waters. A-priori assumptions on the water composition and its spectral response are avoided by SCAPE-M by calculating reflectance of close-to-land water pixels through spatial extension of atmospheric parameters derived over neighboring land pixels. This approach is supported by the results obtained from the validation of SCAPE-M over a number of European inland water validation sites which is presented in this work. MERIS-derived aerosol optical thickness, water reflectance and water pigments are compared to in-situ data acquired concurrently to MERIS images in 20 validation match-ups. SCAPE-M has also been compared to specific processors designed for the retrieval of lake water constituents from MERIS data. The performance of SCAPE-M to reproduce ground-based measurements under a range of water types and the ability of MERIS data to monitor chlorophyll-a and phycocyanin pigments using semiempirical algorithms after SCAPE-M processing are discussed. It has been found that SCAPE-M is able to provide high accurate water reflectance over turbid waters, outperforming models based on site-specific bio-optical models, although problems of SCAPE-M to cope with clear waters in some cases have also been identified.     

Advanced InSAR atmospheric correction: MERIS/MODIS combination and stacked water vapour models

A major source of error for repeat‐pass Interferometric Synthetic Aperture Radar (InSAR) is the phase delay in radio signal propagation through the atmosphere (especially the part due to tropospheric water vapour). Based on experience with the Global Positioning System (GPS)/Moderate Resolution Imaging Spectroradiometer (MODIS) integrated model and the Medium Resolution Imaging Spectrometer (MERIS) correction model, two new advanced InSAR water vapour correction models are demonstrated using both MERIS and MODIS data: (1) the MERIS/MODIS combination correction model (MMCC); and (2) the MERIS/MODIS stacked correction model (MMSC). The applications of both the MMCC and MMSC models to ENVISAT Advanced Synthetic Aperture Radar (ASAR) data over the Southern California Integrated GPS Network (SCIGN) region showed a significant reduction in water vapour effects on ASAR interferograms, with the root mean square (RMS) differences between GPS‐ and InSAR‐derived range changes in the line‐of‐sight (LOS) direction decreasing from ～10 mm before correction to ～5 mm after correction, which is similar to the GPS/MODIS integrated and MERIS correction models. It is expected that these two advanced water vapour correction models can expand the application of MERIS and MODIS data for InSAR atmospheric correction. A simple but effective approach has been developed to destripe Terra MODIS images contaminated by radiometric calibration errors. Another two limiting factors on the MMCC and MMSC models have also been investigated in this paper: (1) the impact of the time difference between MODIS and SAR data; and (2) the frequency of cloud‐free conditions at the global scale.     

A multiple scattering algorithm for atmospheric correction of remotely sensed ocean colour (MERIS instrument): Principle and implementation for atmospheres carrying various aerosols including absorbing ones

A multiple scattering algorithm for atmospheric correction of satellite ocean colour observations is described. This algorithm, precisely designed for the MERIS instrument, globally assesses the combined contributions of aerosols and molecules to the multiple scattering regime. The approach was introduced in a previous work, where it was shown that, for a given aerosol, multiple scattering effects can be assessed through the relationship between the aerosol optical thickness and the relative increase in the path radiance that results from the progressive introduction of this aerosol within an aerosol-free atmosphere. Based on considerations about the accuracy to which the water-leaving radiances should be retrieved, the need to account for multiple scattering is argued. The principle of the algorithm is then presented, and tests and sensitivity studies (especially as regards aerosol type and vertical distribution) are performed to assess its performance in terms of errors on the retrieved water-leaving reflectances and pigment concentrations. The algorithm is able to perform the correction for atmospheres carrying several aerosol types, including absorbing ones, through their identification in the near-infrared, and through the detection of their absorption by means of appropriate assumptions on the marine signals at 510 and 705nm.     

Detection of blue-absorbing aerosols using near infrared and visible (ocean color) remote sensing observations

An algorithm is presented, which is designed to identify blue-absorbing aerosols from near infrared and visible remote-sensing observations, as they are in particular collected by satellite ocean color sensors. The technique basically consists in determining an error budget at one wavelength around 510 nm, based on a first-guess estimation of the atmospheric path reflectance as if the atmosphere was of a maritime type, and on a reasonable hypothesis about the marine signal at this wavelength. The budget also includes the typical calibration uncertainty and the natural variability in the ocean optical properties. Identification of blue-absorbing aerosols is then achieved when the error budget demonstrates a significant over-correction of the atmospheric signal when using non-absorbing maritime aerosols. Implementation of the algorithm is presented, and its application to real observations by the MERIS and SeaWiFS ocean color sensors is discussed. The results demonstrate the skill of the algorithm in various regions of the ocean where absorbing aerosols are present, and for two different sensors. A validation of the results is also performed against in situ data from the AERONET, and further illustrates the skill of the algorithm and its general applicability.     

Coupled retrieval of aerosol optical thickness, columnar water vapor and surface reflectance maps from ENVISAT/MERIS data over land

An algorithm for the derivation of atmospheric parameters and surface reflectance data from MEdium Resolution Imaging Specrometer Instrument (MERIS) on board ENVIronmental SATellite (ENVISAT) images has been developed. Geo-rectified aerosol optical thickness (AOT), columnar water vapor (CWV) and spectral surface reflectance maps are generated from MERIS Level-1b data over land. The algorithm has been implemented so that AOT, CWV and reflectance products are provided on an operational manner, making no use of ancillary parameters apart from those attached to MERIS products. For this reason, it has been named Self-Contained Atmospheric Parameters Estimation from MERIS data (SCAPE-M). The fundamental basis of the algorithm and applicable error figures are presented in the first part of this paper. In particular, errors of ± 0.03, ± 4% and ± 8% have been estimated for AOT, CWV and surface reflectance retrievals, respectively, by means of a sensitivity analysis based on a synthetic data set simulated under a usual MERIS scene configuration over land targets. The assumption of a fixed aerosol model, the coarse spatial resolution of the AOT product and the neglection of surface reflectance directional effects were also identified as limitations of SCAPE-M. Validation results are detailed in the second part of the paper. Comparison of SCAPE-M AOT retrievals with data from AErosol RObotic NETwork (AERONET) stations showed an average Root Mean Square Error (RMSE) of 0.05, and an average correlation coefficient R² of about 0.7-0.8. R² values grew up to more than 0.9 in the case of CWV after comparison with the same stations. A good correlation is also found with the MERIS Level-2 ESA CWV product. Retrieved surface reflectance maps have been successfully compared with reflectance data derived from the Compact High Resolution Imaging Spectrometer (CHRIS) on board the PRoject for On-Board Autonomy (PROBA) in the first place. Reflectance retrievals have also been compared with reflectance data derived from MERIS images by the Bremen AErosol Retrieval (BAER) method. A good correlation in the red and near-infrared bands was found, although a considerably higher proportion of pixels was successfully processed by SCAPE-M.     

Aerosol characteristics during the coolest June month over New Delhi,northern India

June 2008, which is also the transition month between two major seasons for Indo-Gangetic Basin (IGB), has been identified the coolest June over New Delhi during the past century, showing mean temperature of 31.6 ± 1.7°C, which was found to be ～2°C less than its climatological mean (33.9°C). Aerosol optical properties for this month and thus obtained physical parameters have been studied using data from the CIMEL sun/sky radiometer, installed in New Delhi under the Aerosol Robotic Network (AERONET) programme. Results reveal bimodal aerosol volume size distribution. The monthly mean values for aerosol optical depth (AOD) at 500 nm (0.96 ± 0.31) and Ångström exponent at the wavelength pair of 440–870 nm (0.79 ± 0.42) show significant lower values whereas single scattering albedo at 675 nm shows a significantly larger value (0.94 ± 0.04) compared with previous measurements over the station. Results suggest dominance of scattering-type particles such as water-soluble aerosols from anthropogenic sources and dust aerosols from natural sources with higher relative humidity over the station. Radiative forcing caused due to the aerosols for the month of June 2008, which have been computed using the radiative-transfer model, informs low forcing at the top of atmosphere (TOA,?+14 W m^?2) as well as at surface (?33 W m^?2). The resultant atmospheric forcing (+47 W m^?2) indicates warming effect that caused heating of lower atmosphere at the rate of 0.89 K day^?1.     

Validation of satellite and model aerosol optical depth and precipitable water vapour observations with AERONET data over Pune,India

ABSTRACT

The present work concerns with a detailed study of the validation of the Moderate Resolution Imaging Spectroradiometer (MODIS) and model products, and investigates the spatial and temporal variations in the correlation coefficient of the validation results obtained from the analysis of Aerosol Robotic Network (AERONET) sun–sky radiometer data archived at Pune during 2005–2015. Combining the confidence intervals and prediction levels, the ground-based AERONET aerosol optical depth (AOD) at 550 nm and precipitable water vapour (PWV) have been used to validate the MODIS, model AOD (550 nm), and PWV (cm) observations. The correlation coefficients (r) of AOD for the linear regression fits are 0.73, 0.75, and 0.79, and of PWV are 0.88, 0.89, and 0.97 for Terra, Aqua, and model simulations, respectively. Month-to-month/seasonal variation of AOD (550 nm) and PWV observations of satellite and model observations are also compared with AERONET observations. Additionally, various statistical metrics, including the root mean square error, mean absolute error, and root mean bias values were calculated using AERONET, satellite, and model simulations data. Furthermore, a frequency distribution of AOD (550 nm) and PWV observations are studied from AERONET, satellite, and model data. The study emphasizes that the globally distributed AERONET observations help to improve the satellite retrievals and model predictions to enrich our knowledge of aerosols and their impact on climate, the hydrological cycle, and air quality.     

Atmospheric correction of ENVISAT/MERIS data over case II waters: the use of black pixel assumption in oxygen and water vapour absorption bands

The Medium Resolution Imaging Spectrometer (MERIS) sensor, with its good physical design, can provide excellent data for water colour monitoring. However, owing to the shortage of shortwave-infrared (SWIR) bands, the traditional near-infrared (NIR)–SWIR algorithm for atmospheric correction in inland turbid case II waters cannot be extended to the MERIS data directly, which limits its applications. In this study, we developed a modified NIR black pixel method for atmospheric correction of MERIS data in inland turbid case II waters. In the new method, two special NIR bands provided by MERIS data, an oxygen absorption band (O₂ A-band, 761 nm) and a water vapour absorption band (vapour A-band, 900 nm), were introduced to keep the assumption of zero water-leaving reflectance valid according to the fact that both atmospheric transmittance and water-leaving reflectance are very small at these two bands. After addressing the aerosol wavelength dependence for the cases of single- and multiple-scattering conditions, we further validated the new method in two case lakes (Lake Dianchi in China and Lake Kasumigaura in Japan) by comparing the results with in situ measurements and other atmospheric correction algorithms, including Self-Contained Atmospheric Parameters Estimation for MERIS data (SCAPE-M) and the Basic ERS (European Remote Sensing Satellite) & ENVISAT (Environmental Satellite) (A)ATSR ((Advanced) Along-Track Scanning Radiometer) and MERIS (BEAM) processor. We found that the proposed method had acceptable accuracy in the bands within 560–754 nm (MERIS bands 5–10) (average absolute deviation (AAD) = 0.0081, average deviation (AD) = 0.0074), which are commonly used in the estimation models of chlorophyll-a (chl-a) concentrations. In addition, the performance of the new method was superior to that of the BEAM processor and only slightly worse than that of SCAPE-M in these bands. Considering its acceptable accuracy and simplicity both in principle and at implementation compared with the SCAPE-M method, the new method provides an option for atmospheric correction of MERIS data in inland turbid case II waters with applications aiming for chl-a estimation.