Total Backscattering Coefficient Research Articles

Mediterranean intense desert dust outbreaks and their vertical structure based on remote sensing data

Abstract. The main aim of the present study is to describe the vertical structure of the intense Mediterranean dust outbreaks, based on the use of satellite and surface-based retrievals/measurements. Strong and extreme desert dust (DD) episodes are identified at 1° × 1° spatial resolution, over the period March 2000–February 2013, through the implementation of an updated objective and dynamic algorithm. According to the algorithm, strong DD episodes occurring at a specific place correspond to cases in which the daily aerosol optical depth at 550 nm (AOD550 nm) exceeds or equals the long-term mean AOD550 nm (Mean) plus two standard deviations (SD), which is also smaller than Mean+4 × SD. Extreme DD episodes correspond to cases in which the daily AOD550 nm value equals or exceeds Mean+4 × SD. For the identification of DD episodes, additional optical properties (Ångström exponent, fine fraction, effective radius and aerosol index) derived by the MODIS-Terra & Aqua (also AOD retrievals), OMI-Aura and EP-TOMS databases are used as inputs. According to the algorithm using MODIS-Terra data, over the period March 2000–February 2013, strong DD episodes occur more frequently (up to 9.9 episodes year−1) over the western Mediterranean, while the corresponding frequencies for the extreme ones are smaller (up to 3.3 episodes year−1, central Mediterranean Sea). In contrast to their frequency, dust episodes are more intense (AODs up to 4.1), over the central and eastern Mediterranean Sea, off the northern African coasts. Slightly lower frequencies and higher intensities are found when the satellite algorithm operates based on MODIS-Aqua retrievals, for the period 2003–2012. The consistency of the algorithm is successfully tested through the application of an alternative methodology for the determination of DD episodes, which produced similar features of the episodes' frequency and intensity, with just slightly higher frequencies and lower intensities. The performance of the satellite algorithm is assessed against surface-based daily data from 109 sun-photometric (AERONET) and 22 PM10 stations. The agreement between AERONET and MODIS AOD is satisfactory (R = 0.505 − 0.750) and improves considerably when MODIS level 3 retrievals with higher sub-grid spatial representativeness and homogeneity are considered. Through the comparison against PM10 concentrations, it is found that the presence of dust is justified in all ground stations with success scores ranging from 68 to 97 %. However, poor agreement is evident between satellite and ground PM10 observations in the western parts of the Mediterranean, which is attributed to the desert dust outbreaks' vertical extension and the high altitude of dust presence. The CALIOP vertical profiles of pure and polluted dust observations and the associated total backscatter coefficient at 532 nm (β532 nm), indicate that dust particles are mainly detected between 0.5 and 6 km, though they can reach 8 km between the parallels 32 and 38° N in warm seasons. An increased number of CALIOP dust records at higher altitudes is observed with increased latitude, northwards to 40° N, revealing an ascending mode of the dust transport. However, the overall intensity of DD episodes is maximum (up to 0.006 km−1 sr−1) below 2 km and at the southern parts of the study region (30–34° N). Additionally, the average thickness of dust layers gradually decreases from 4 to 2 km, moving from south to north. In spring, dust layers of moderate-to-high β532 nm values ( ∼ 0.004 km−1 sr−1) are detected over the Mediterranean (35–42° N), extending from 2 to 4 km. Over the western Mediterranean, dust layers are observed between 2 and 6 km, while their base height is decreased down to 0.5 km for increasing longitudes underlying the role of topography and thermal convection. The vertical profiles of CALIOP β532 nm confirm the multilayered structure of the Mediterranean desert dust outbreaks on both annual and seasonal bases, with several dust layers of variable geometrical characteristics and intensities. A detailed analysis of the vertical structure of specific DD episodes using CALIOP profiles reveals that the consideration of the dust vertical structure is necessary when attempting comparisons between columnar MODIS AOD retrievals and ground PM10 concentrations.

ESTIMATION OF PHYSICAL PARAMETERS OF A MULTILAYERED MULTI-SCALE VEGETATED SURFACE

Abstract. Soil moisture is important to enable the growth of vegetation in the way that it also conditions the development of plant population. Additionally, its assessment is important in hydrology and agronomy, and is a warning parameter for desertification. Furthermore, the soil moisture content affects exchanges with the atmosphere via the energy balance at the soil surface; it is significant due to its impact on soil evaporation and transpiration. Therefore, it conditions the energy transfer between Earth and atmosphere. Many remote sensing methods were tested. For the soil moisture; the first methods relied on the optical domain (short wavelengths). Obviously, due to atmospheric effects and the presence of clouds and vegetation cover, this approach is doomed to fail in most cases. Therefore, the presence of vegetation canopy complicates the retrieval of soil moisture because the canopy contains moisture of its own. This paper presents a synergistic methodology of SAR and optical remote sensing data, and it’s for simulation of statistical parameters of soil from C-band radar measurements. Vegetation coverage, which can be easily estimated from optical data, was combined in the backscattering model. The total backscattering was divided into the amount attributed to areas covered with vegetation and that attributed to areas of bare soil. Backscattering coefficients were simulated using the established backscattering model. A two-dimensional multiscale SPM model has been employed to investigate the problem of electromagnetic scattering from an underlying soil. The water cloud model (WCM) is used to account for the effect of vegetation water content on radar backscatter data, whereof to eliminate the impact of vegetation layer and isolate the contributions of vegetation scattering and absorption from the total backscattering coefficient.

ESTIMATION OF PHYSICAL PARAMETERS OF A MULTILAYERED MULTI-SCALE VEGETATED SURFACE

Soil moisture is important to enable the growth of vegetation in the way that it also conditions the development of plant population. Additionally, its assessment is important in hydrology and agronomy, and is a warning parameter for desertification. <br><br> Furthermore, the soil moisture content affects exchanges with the atmosphere via the energy balance at the soil surface; it is significant due to its impact on soil evaporation and transpiration. Therefore, it conditions the energy transfer between Earth and atmosphere. <br><br> Many remote sensing methods were tested. For the soil moisture; the first methods relied on the optical domain (short wavelengths). Obviously, due to atmospheric effects and the presence of clouds and vegetation cover, this approach is doomed to fail in most cases. Therefore, the presence of vegetation canopy complicates the retrieval of soil moisture because the canopy contains moisture of its own. <br><br> This paper presents a synergistic methodology of SAR and optical remote sensing data, and it’s for simulation of statistical parameters of soil from C-band radar measurements. Vegetation coverage, which can be easily estimated from optical data, was combined in the backscattering model. The total backscattering was divided into the amount attributed to areas covered with vegetation and that attributed to areas of bare soil. <br><br> Backscattering coefficients were simulated using the established backscattering model. A two-dimensional multiscale SPM model has been employed to investigate the problem of electromagnetic scattering from an underlying soil. The water cloud model (WCM) is used to account for the effect of vegetation water content on radar backscatter data, whereof to eliminate the impact of vegetation layer and isolate the contributions of vegetation scattering and absorption from the total backscattering coefficient.

Leaf Area Index Inversion of Winter Wheat Using Modified Water-Cloud Model

The inversion of vegetation parameters using microwave remote sensing is usually affected by the heterogeneous distribution of vegetation, sparse vegetation cover, and bare soil, which leads to unsatisfactory results in parameter estimation of agricultural applications. In this letter, in order to solve the problem of surface vegetation parameter retrieval by using microwave remote sensing, a modified water-cloud model (WCM) was developed to retrieve leaf area index (LAI) by adding vegetation coverage and direct effect of bare soil on the total backscatter coefficients, which fully took into account the distribution of vegetation cover. The modified model was validated between the simulated backscatter coefficients and measurements based on ground observations and RADARSAT-2 data in China. Then, a look-up table algorithm was applied to calculate the value of vegetation water content and retrieve LAI according to a linear relationship between vegetation water content and LAI. Results indicated that the modified model was more sensitive to vegetation condition and the estimation accuracy was higher than that of the original WCM. $R^{2}$ and rmse were 85.0% and 0.918 dB in HH polarization, and 73.9% and 1.475 dB in VV polarization, respectively. Meanwhile, the modified model could separate the scattering influences produced by the vegetation cover and bare soil components on the backscatter coefficients effectively. The accuracy of LAI retrieval was significantly high with $R^{2}$ and rmse of 84.1% and 0.233 m2/m2, respectively. This method will provide support for estimating LAI of winter wheat by using radar data in a wide range.

Field measurements of the backscattering coefficient in a cascading reservoir system: first results from Nova Avanhandava and Barra Bonita Reservoirs (São Paulo, Brazil)

ABSTRACTIn this study, a data set of total suspended matter (TSM), chlorophyll-a (Chl-a), total backscattering coefficient (bb) and the remote sensing reflectance (Rrs) were measured in the euphotic zone of two hydroelectric reservoirs at 71 stations during field surveys in the wet and dry seasons. These two reservoirs are located in a cascading system in Tietê River, São Paulo State, Brazil. The limnological and optical data were interpolated using the ordinary kriging technique to map their spatial distribution. The differences in TSM, Chl-a and in bb in space and time were investigated. The profiling data from bb were analysed. All these data were used to explain the resulting Rrs spectra in these two reservoirs. For both reservoirs, the inorganic fraction of TSM was responsible for the bb variability and therefore modulates the Rrs spectra. The seasonally difference in the optical data will help to understand how the inherent optical properties and the apparent optical properties changes in a cascading reservoir system.

Retrieving the height of smoke and dust aerosols by synergistic use of VIIRS, OMPS, and CALIOP observations

AbstractThis study extends the application of the previously developed Aerosol Single‐scattering albedo and layer Height Estimation (ASHE) algorithm, which was originally applied to smoke aerosols only, to both smoke and dust aerosols by including nonspherical dust properties in the retrieval process. The main purpose of the algorithm is to derive aerosol height information over wide areas using aerosol products from multiple satellite sensors simultaneously: aerosol optical depth (AOD) and Ångström exponent from the Visible Infrared Imaging Radiometer Suite (VIIRS), UV aerosol index from the Ozone Mapping and Profiler Suite (OMPS), and total backscatter coefficient profile from the Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP). The case studies suggest that the ASHE algorithm performs well for both smoke and dust aerosols, showing root‐mean‐square error of the retrieved aerosol height as compared to CALIOP observations from 0.58 to 1.31 km and mean bias from −0.70 to 1.13 km. In addition, the algorithm shows the ability to retrieve single‐scattering albedo to within 0.03 of Aerosol Robotic Network inversion data for moderate to thick aerosol loadings (AOD of ~1.0). For typical single‐layered aerosol cases, the estimated uncertainty in the retrieved height ranges from 1.20 to 1.80 km over land and from 1.15 to 1.58 km over ocean when favorable conditions are met. Larger errors are observed for multilayered aerosol events, due to the limited sensitivities of the passive sensors to such cases.

Estimation of articular cartilage properties using multivariate analysis of optical coherence tomography signal

The aim was to investigate the applicability of multivariate analysis of optical coherence tomography (OCT) information for determining structural integrity, composition and mechanical properties of articular cartilage. Equine osteochondral samples (N=65) were imaged with OCT, and their total attenuation and backscattering coefficients (μt and μb) were measured. Subsequently, the Mankin score, optical density (OD) describing the fixed charge density, light absorbance in amide I region (Aamide), collagen orientation, permeability, fibril network modulus (Ef) and non-fibrillar matrix modulus (Em) of the samples were determined. Partial least squares (PLS) regression model was calculated to predict tissue properties from the OCT signals of the samples. Significant correlations between the measured and predicted mean collagen orientation (R(2)=0.75, P<0.0001), permeability (R(2)=0.74, P<0.0001), mean OD (R(2)=0.73, P<0.0001), Mankin scores (R(2)=0.70, P<0.0001), Em (R(2)=0.50, P<0.0001), Ef (R(2)=0.42, P<0.0001), and Aamide (R(2)=0.43, P<0.0001) were obtained. Significant correlation was also found between μb and Ef (ρ=0.280, P=0.03), but not between μt and any of the determined properties of articular cartilage (P>0.05). Multivariate analysis of OCT signal provided good estimates for tissue structure, composition and mechanical properties. This technique may significantly enhance OCT evaluation of articular cartilage integrity, and could be applied, for example, in delineation of degenerated areas around cartilage injuries during arthroscopic repair surgery.

A Modified Semianalytical Algorithm for Remotely Estimating Euphotic Zone Depth in Turbid Inland Waters

Euphotic zone depth (Z <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">eu</sub> ), defined as the depth where photosynthetic available radiation (PAR) is 1% of its surface value, is of great importance in studies of water biogeochemical processes. Satellite remote sensing is a powerful technique to obtain Z <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">eu</sub> , as it can cover large areas at very frequent intervals. Several remote-sensing algorithms for estimating Z <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">eu</sub> have been developed for oceanic water bodies; however, remote estimation of Z <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">eu</sub> is still a challenging task for inland waters. In this study, an existing semianalytical algorithm (named as Lee07 in this study) was modified for remotely estimating Z <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">eu</sub> in turbid inland waters by replacing the original quasi-analytical algorithm (QAA) by QAA_Turbid, an algorithm specially developed for remotely estimating total absorption and backscattering coefficients in turbid waters. Performance of the modified algorithm was evaluated using in situ radiometric data collected in Japan's Lake Kasumigaura, known to be turbid. Results showed that yielded acceptable estimation accuracy for Z <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">eu</sub> (ranging from 1.15 to 2.26 m) with root-mean-square error (RMSE) of 0.12 m, normalized root-mean-square error (NRMS) of 8.01%, and mean normalized bias (MNB) of -1.84%, significantly outperforming the original version as well as three other Z <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e</sub> u retrieval algorithms. These results indicate its great potential for accurately estimating Z <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">eu</sub> over widespread turbid inland waters from satellite images.

Significance of scattering by oceanic particles at angles around 120 degree.

Field observations and theoretical studies have shown that shapes of the volume scattering functions (VSFs) of oceanic particles in the backward directions, i.e., VSFs normalized by the total backscattering coefficient, exhibit a surprisingly low variability at angles near 120 degree, which is also confirmed by measurements of VSFs in coastal waters around the US. To investigate what this minimum variability angle (θ*) represents, we estimated mean values of the VSFs in the backward angles using four mean value theorems: mean value for integral, weighted mean value for integral, classic mean value for differentiation and Cauchy's mean value. We also estimated the angles corresponding to the minimum values of the VSFs. We found θ* to be very close to the angles representing the classic mean values for differentiation of the VSFs. The low variability is due to the fact that the classic mean values vary little with the composition and sizes of particles.

1D-Var multilayer assimilation of X-band SAR data into a detailed snowpack model

Abstract. The structure and physical properties of a snowpack and their temporal evolution may be simulated using meteorological data and a snow metamorphism model. Such an approach may meet limitations related to potential divergences and accumulated errors, to a limited spatial resolution, to wind or topography-induced local modulations of the physical properties of a snow cover, etc. Exogenous data are then required in order to constrain the simulator and improve its performance over time. Synthetic-aperture radars (SARs) and, in particular, recent sensors provide reflectivity maps of snow-covered environments with high temporal and spatial resolutions. The radiometric properties of a snowpack measured at sufficiently high carrier frequencies are known to be tightly related to some of its main physical parameters, like its depth, snow grain size and density. SAR acquisitions may then be used, together with an electromagnetic backscattering model (EBM) able to simulate the reflectivity of a snowpack from a set of physical descriptors, in order to constrain a physical snowpack model. In this study, we introduce a variational data assimilation scheme coupling TerraSAR-X radiometric data into the snowpack evolution model Crocus. The physical properties of a snowpack, such as snow density and optical diameter of each layer, are simulated by Crocus, fed by the local reanalysis of meteorological data (SAFRAN) at a French Alpine location. These snowpack properties are used as inputs of an EBM based on dense media radiative transfer (DMRT) theory, which simulates the total backscattering coefficient of a dry snow medium at X and higher frequency bands. After evaluating the sensitivity of the EBM to snowpack parameters, a 1D-Var data assimilation scheme is implemented in order to minimize the discrepancies between EBM simulations and observations obtained from TerraSAR-X acquisitions by modifying the physical parameters of the Crocus-simulated snowpack. The algorithm then re-initializes Crocus with the modified snowpack physical parameters, allowing it to continue the simulation of snowpack evolution, with adjustments based on remote sensing information. This method is evaluated using multi-temporal TerraSAR-X images acquired over the specific site of the Argentière glacier (Mont-Blanc massif, French Alps) to constrain the evolution of Crocus. Results indicate that X-band SAR data can be taken into account to modify the evolution of snowpack simulated by Crocus.

Application of a Semianalytical Algorithm to Remotely Estimate Diffuse Attenuation Coefficient in Turbid Inland Waters

Remote estimation of the vertically averaged diffuse attenuation coefficient over a water layer Kd(λ) is of great importance in understanding and modeling the physical, chemical, and biological processes in water bodies. A semianalytical algorithm was previously proposed to remotely estimate Kd( λ) based on the retrieval of the total absorption and backscattering coefficients ( a and bb ). The algorithm has been effectively applied to clear and slightly turbid oceanic waters, but its applicability in turbid inland waters is still unknown. In this study, the relationship between a and bb on the one hand with Kd(λ) used in the semianalytical algorithm was first validated by the measured a and bb. Second, the semianalytical algorithm was combined with the so-called QAA_Turbid (quasi-analytical algorithm for turbid waters) to remotely estimate Kd(λ) for highly turbid waters. We tested the performance of the combined algorithm at wavelengths of 443, 556, and 669 nm by using a data set collected from a turbid lake in Japan. The validation results demonstrated that it could estimate Kd(λ) (ranging from 1.94 to 9.47 m-1) with root-mean-square error and relative error values of 0.17 and 12.96%, respectively. These results indicate the great potential of the semianalytical algorithm to accurately monitor the spectra of Kd(λ) for turbid inland waters from satellite observations.

Modeling ultrasonic scattering from high-concentration cell pellet biophantoms using polydisperse structure functions

Backscattering coefficient (BSC) has been used extensively to characterize tissue. In most cases, sparse scatterer concentrations are assumed. However, many types of tissues have dense scattering media. This study models the scattering of dense media. Structure functions (defined herein as the total BSC divided by incoherent BSC) are used to take into account the correlation among scatterers for dense media. Structure function models are developed for polydisperse scatterers. The models are applied to cell pellet biophantoms that are constructed by placing live cells of known concentration in a mixture of bovine plasma and thrombin to form a clot. The BSCs of the biophantoms were measured using single-element transducers over 11–105 MHz. Experimental structure functions were derived by comparing the BSCs of two cell concentrations, a lower concentration (volume fraction: <5%, incoherent scattering only) and a higher concentration (volume fraction: ~74%). The structure functions predicted by the models agreed with the experimental data. Fitting the models yielded cell radius estimates (Chinese hamster ovary cell: 6.9 microns, MAT cell: 7.1 microns, 4T1 cell: 8.3 microns) that were consistent with direct light microscope measures (Chinese hamster ovary: 6.7 microns, MAT: 7.3 microns, 4T1: 8.9 microns). [Work supported by NIH CA111289.]

Model of the attenuation coefficient of daily photosynthetically available radiation in the upper ocean

Penetration of the photosynthetically available radiation (PAR, over 400–700 nm) in the upper ocean is important for many processes such as water radiant heating and primary productivity. Because of this importance, daily PAR at sea surface (PAR¯(0+)) is routinely generated from ocean-color images for global studies. To propagate this broadband solar radiation through the upper ocean, an attenuation coefficient of PAR (KPAR) is also generated from the same ocean-color measurements. However, due to the empirical nature of the KPAR algorithm, this KPAR product corresponds to an instantaneous PAR at a fixed sun angle, with no diurnal variability. It is hence necessary to have an attenuation coefficient matching the temporal characteristics of daily PAR. This paper represents an effort to meet this need. Using ECOLIGHT, the subsurface light field for a wide range of water bodies was simulated, from which the attenuation coefficient (KPAR¯) of daily PAR was calculated. We presented the diurnal and vertical variation of this attenuation coefficient, and found that it can be well predicted (within ∼7%) as a function of the total absorption coefficient and backscattering coefficient at 490 nm and the noontime solar zenith angle. This new model offers an efficient and reasonably accurate approach for quantifying daily upper water column PAR within the global ocean from satellite measurements of water color.

Remote sensing backscattering model for sea ice: Theo-retical modelling and analysis

Remote sensing has been used in Antarctic studies as an earth observation technique to study the polar region. A remote sensing forward model is an important tool in polar research to study and understand scattering mechanisms and sensitivity of physical parameters of snow and sea ice. In this paper, a reliable theoretical model to study sea ice is developed. The theoretical model in a prior work was improved by including multiple-surface scattering, based on an existing integral equation model and additional second-order surface-volume scattering. This model is applied to a desalinated ice layer above thick saline ice and analyzed using different frequencies, bottom surface roughness and sea-ice layer thickness. Improvement in calculation of the backscattering coefficient of the sea-ice layer is investigated for both co-polarized and cross-polarized returns. The effect on each scattering mechanism is also investigated, to understand in more detail the effect of surface multiple scattering and second-order surface- volume scattering. Comparisons are also made with field measurement results, to validate the theoretical model. Results show improvement in the total backscattering coefficient for cross-polarized return in the studied range, suggesting that multiple-surface scattering and surface-volume scattering up to second order are important scattering mechanisms in the sea-ice layer and should not be ignored in polar research.

Modeling the loss of echogenicity from ultrasound contrast agents

Acoustically induced loss of echogenicity (LOE) from ultrasound contrast agents (UCAs) has been exploited in imaging techniques to improve delineation of pathology. Determination of the type of cavitation that accompanies LOE can be experimentally difficult to determine due to the complex microbubble activity elicited. A theoretical model has been derived to predict the LOE originating from rupture of the UCA shell, from stable cavitation, or from inertial cavitation. The predictions of the model for each cavitation phenomena will be compared to recent experimental LOE measurements of the lipid-based UCA Definity® and echogenic liposomes insonified by Doppler pulses from a clinical scanner. The backscatter coefficient was calculated for a population of UCAs exposed to 6-MHz pulsed ultrasound of duration 1.67μs—8.33 μs. The change in the total backscatter coefficient was used to predict the LOE. The size distribution of UCAs was adjusted according to the specific type of cavitation triggered by the ultrasound exposure. Comparison of the theoretical predictions and experimental measurements suggest that shell rupture is the dominant mechanism for LOE for both Definity® and echogenic liposomes. These results will be discussed in conjunction with a recently developed cavitation index to predict the LOE of UCAs.

Retrieval of Inherent Optical Properties for Turbid Inland Waters From Remote-Sensing Reflectance

Remote estimation of inherent optical properties (IOPs) for water bodies cannot only provide indicators of water quality, but also be used in the study on biological and biogeochemical processes of waters. The quasi-analytical algorithm (QAA) is a simple and effective method to retrieve IOPs from remote-sensing reflectance ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rs</sub> ). The QAA has been widely validated and applied in oceans, but its application in inland waters is far less extensive. In this paper, the QAA was enhanced to retrieve IOPs for turbid inland waters based on the bandwidths of Medium Resolution Imaging Spectrometer (MERIS). The enhancement was achieved by proposing a semi-analytical model to estimate the spectral slope of particle backscattering, as well as a novel estimation model for phytoplankton absorption coefficient at 443 nm. Two data sets (i.e., noise-free synthetic data and in-situ data) were collected to assess the performance of the enhanced algorithm. Results show that the algorithm yields almost error-free estimations for total absorption and backscattering coefficients and estimations for phytoplankton absorption at 443 nm with acceptable accuracy in the case of synthetic data set. For the in-situ data set, the algorithm retrieves the total absorption coefficients (ranging 0.337-8.331 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> ) with root-mean-square-error in log scale (RMSE) and bias in log scale lower than 0.130 and 0.094, respectively, and phytoplankton absorption at 443 nm (ranging 0.378-4.669 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> ) with RMSE and bias in log scale of 0.151 and 0.096, respectively. These results indicate the potential of the enhanced QAA to accurately retrieve the IOPs from MERIS satellite observations for inland waters.

Ground‐based validation of CALIPSO observations of dust and smoke in the Cape Verde region

Ground‐based Raman lidar measurements during the second Saharan Mineral Dust Experiment (SAMUM‐2) in 2008 were used for validation of measurements of the lidar aboard the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite within the dusty environment of the Cape Verde region. SAMUM‐2 featured two one‐month campaigns in January/February and May/June 2008 to cover different modes of aerosol transport to the tropical Atlantic: dust from northern Africa and biomass‐burning smoke from western Africa during winter, and pure Saharan dust during summer. During the investigated time period, 33 CALIPSO overflights occurred at a distance of less than 500 km from the location of the ground‐based lidar. Fifteen out of these 33 cases were found suitable for comparing the findings of the two instruments. The parameters for this comparison are the particle backscatter coefficient at 532 and 1064 nm, the extinction coefficient, the lidar ratio (aerosol type), and the particle depolarization ratio at 532 nm, as well as the backscatter‐related Ångström exponent for the wavelength pair 532/1064 nm. Best agreement was found for the 532 nm backscatter coefficient, while the 532 nm extinction coefficient is underestimated by up to 30%. The latter is due to the use of an effective dust lidar ratio that gives reliable backscatter coefficients but is not suitable to transform these to extinction coefficients. CALIPSO particle depolarization ratios provided in the current (version 3.01) aerosol profile product were found to be affected by a computing error and should be calculated from the perpendicular and total particle backscatter coefficients provided in the same data file. CALIPSO aerosol classification was found to be mostly correct but a demand for homogeneous aerosol layers could improve the retrieval. Suggestions for the improvement of the CALIPSO retrieval by introducing iterative procedures are provided.

Influence of biogenic pollen on optical properties of atmospheric aerosols observed by lidar over Gwangju, South Korea

For the first time, optical properties of biogenic pollen, i.e., backscatter coefficients and depolarization ratios at 532 nm were retrieved by lidar observations. The extinction coefficient was derived with the assumption of possible values of the extinction-to-backscatter (lidar) ratio. We investigate the effect of the pollen on the optical properties of the observed atmospheric aerosols by comparing lidar and sun/sky radiometer measurements carried out at the lidar site. The observations were made with a depolarization lidar at the Gwangju Institute of Science & Technology (GIST) in Gwangju, Korea (35.13°N, 126.50°E) during an intensive observational period that lasted from 5 to 7 May 2009. The pollen concentration was measured with a Burkard trap sampler at the roof top of the Gwangju Bohoon hospital which is located 1 km away from the lidar site. During the observation period, high pollen concentrations of 1360, 2696, and 1952 m−3 day−1 were measured on 5, 6, and 7 May, respectively. A high lidar depolarization ratio caused by biogenic pollen was only detected during daytime within the planetary boundary layer which was at 1.5–2.0 km height above ground during the observational period. The contribution of biogenic pollen to the total backscatter coefficient was estimated from the particle depolarization ratio. Average hourly values of pollen optical depth were retrieved by integrating the pollen extinction coefficients. We find average values of 0.062 ± 0.037, 0.041 ± 0.028 and 0.067 ± 0.036 at 532 nm on 5, 6, and 7 May, respectively. The contribution of pollen optical depth to total aerosol optical depth was 2–34%. The sun/sky radiometer data show that biogenic pollen can affect optical properties of atmospheric aerosol by increasing aerosol optical depth and decreasing the Ångström exponent during daytime during the season of high pollen emission.

An algorithm to retrieve absorption coefficient of chromophoric dissolved organic matter from ocean color

We extended the quasi-analytical algorithm (QAA) architecture to analytically derive absorption coefficient of chromophoric dissolved organic matter (ag). Specifically, we used an empirical formula based on total absorption and particle backscattering coefficients to estimate and then remove detritus absorption coefficient (ad), and developed a scheme to use absorption coefficients at three wavelengths (412, 443, and 490nm) for the separation of ag and aph (absorption coefficient of phytoplankton). The algorithm was tested using an in situ data set collected in the South China Sea and the Taiwan Strait and a global in situ data set—the NASA Bio-Optical Marine Algorithm Data set (NOMAD). Our results indicated that this new analytical algorithm for retrieving ag performed reasonably well with a mean absolute percentage error of approximately 45% for ag(412), while it also presented a satisfactory performance for aph and ad in both coastal and oceanic waters. Furthermore, the applicability of this new algorithm for general oceanographic studies was briefly illustrated by applying it to MODIS measurements over the Taiwan Strait and the shelf region near the Mississippi River delta. Nevertheless, more independent tests with in situ and satellite data are needed to further validate and improve this innovative approach.

Absorption and backscattering coefficients and their relations to water constituents of Poyang Lake, China

The measurement and analysis of inherent optical properties (IOPs) of the main water constituents are necessary for remote-sensing-based water quality estimation and other ecological studies of lakes. This study aimed to measure and analyze the absorption and backscattering coefficients of the main water constituents and, further, to analyze their relations to the water constituent concentrations in Poyang Lake, China. The concentrations and the absorption and backscattering coefficients of the main water constituents at 47 sampling sites were measured and analyzed as follows. (1) The concentrations of chlorophyll a (C(CHL)), dissolved organic carbon (C(DOC)), suspended particulate matter (C(SPM)), including suspended particulate inorganic matter (C(SPIM)) and suspended particulate organic matter (C(SPOM)), and the absorption coefficients of total particulate (a(p)), phytoplankton (a(ph)), nonpigment particulate (a(d)), and colored/chromophoric dissolved organic matter (a(g)) were measured in the laboratory. (2) The total backscattering coefficients, including the contribution of pure water at six wavelengths of 420, 442, 470, 510, 590, and 700 nm, were measured in the field with a HydroScat-6 backscattering sensor. (3) The backscattering coefficients without the contribution of pure water (b(b)) were then derived by subtracting the backscattering coefficients of pure water from the total backscattering coefficients. (4) The C(CHL), C(SPM), C(SPIM), C(SPOM), and C(DOC) of the 41 remaining water samples were statistically described and their correlations were analyzed. (5) The a(ph), a(d), a(p), a(g), and b(b) were visualized and analyzed, and their relations to C(CHL), C(SPM), C(SPIM), C(SPOM), or C(DOC) were studied. Results showed the following. (1) Poyang Lake was a suspended particulate inorganic matter dominant lake with low phytoplankton concentration. (2) One salient a(ph) absorption peak was found at 678 nm, and it explained 72% of the variation of C(CHL). (3) The a(d) and a(p) exponentially decreased with increasing wavelength, and they explained 74% of the variation of C(SPIM) and 71% variation of C(SPM), respectively, at a wavelength of 440 nm. (4) The a(g) also exponentially decreased with increasing wavelength, and it had no significant correlation to C(DOC) at a significance level of 0.05. (5) The b(b) decreased with increasing wavelength, and it had strong and positive correlations to C(SPM), C(SPIM) and C(SPOM), a strong and negative correlation to C(CHL), and no correlation to C(DOC) at a significance level of 0.05. Such results will be helpful for the understanding of the IOPs of Poyang Lake. They, however, only represented the IOPs during the sampling time period, and more measurements and analyses in different seasons need to be carried out in the future to ensure a comprehensive understanding of the IOPs of Poyang Lake.