The Experts below are selected from a list of 10089 Experts worldwide ranked by ideXlab platform
Jacek Chowdhary - One of the best experts on this subject based on the ideXlab platform.
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Passive Remote Sensing of aerosol layer height using near uv multi angle polarization measurements
Geophysical Research Letters, 2016Co-Authors: Otto Hasekamp, Brian Cairns, Jacek Chowdhary, Bastiaan Van Diedenhoven, John E YorksAbstract:We demonstrate that multi-angle polarization measurements in the near-UV and blue part of the spectrum are very well suited for Passive Remote Sensing of aerosol layer height. For this purpose we use simulated measurements with different set-ups (different wavelength ranges, with and without polarization, different polarimetric accuracies) as well as airborne measurements from the Research Scanning Polarimeter (RSP) obtained over the continental USA. We find good agreement of the retrieved aerosol layer height from RSP with measurements from the Cloud Physics Lidar (CPL) showing a mean absolute difference of less than 1 km. Furthermore, we found that the information on aerosol layer height is provided for large part by the multi-angle polarization measurements with high accuracy rather than the multi-angle intensity measurements. The information on aerosol layer height is significantly decreased when the shortest RSP wavelength (410 nm) is excluded from the retrieval and is virtually absent when 550 nm is used as shortest wavelength.
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analysis of fine mode aerosol retrieval capabilities by different Passive Remote Sensing instrument designs
Optics Express, 2012Co-Authors: Kirk Knobelspiesse, Brian Cairns, Michael I Mishchenko, Jacek Chowdhary, Kostas Tsigaridis, Bastiaan Van Diedenhoven, William Gk Martin, Matteo Ottaviani, Mikhail D AlexandrovAbstract:Remote Sensing of aerosol optical properties is difficult, but multi-angle, multi-spectral, polarimetric instruments have the potential to retrieve sufficient information about aerosols that they can be used to improve global climate models. However, the complexity of these instruments means that it is difficult to intuitively understand the relationship between instrument design and retrieval success. We apply a Bayesian statistical technique that relates instrument characteristics to the information contained in an observation. Using realistic simulations of fine size mode dominated spherical aerosols, we investigate three instrument designs. Two of these represent instruments currently in orbit: the Multiangle Imaging SpectroRadiometer (MISR) and the POLarization and Directionality of the Earths Reflectances (POLDER). The third is the Aerosol Polarimetry Sensor (APS), which failed to reach orbit during recent launch, but represents a viable design for future instruments. The results show fundamental differences between the three, and offer suggestions for future instrument design and the optimal retrieval strategy for current instruments. Generally, our results agree with previous validation efforts of POLDER and airborne prototypes of APS, but show that the MISR aerosol optical thickness uncertainty characterization is possibly underestimated.
Bin Wang - One of the best experts on this subject based on the ideXlab platform.
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on the retrieval of sea ice thickness and snow depth using concurrent laser altimetry and l band Remote Sensing data
The Cryosphere, 2017Co-Authors: Lu Zhou, Jiping Liu, Bin WangAbstract:Abstract. The accurate knowledge of sea ice parameters, including sea ice thickness and snow depth over the sea ice cover, is key to both climate studies and data assimilation in operational forecasts. Large-scale active and Passive Remote Sensing is the basis for the estimation of these parameters. In traditional altimetry or the retrieval of snow depth with Passive microwave Remote Sensing, although the sea ice thickness and the snow depth are closely related, the retrieval of one parameter is usually carried out under assumptions over the other. For example, climatological snow depth data or as derived from reanalyses contain large or unconstrained uncertainty, which result in large uncertainty in the derived sea ice thickness and volume. In this study, we explore the potential of combined retrieval of both sea ice thickness and snow depth using the concurrent active altimetry and Passive microwave Remote Sensing of the sea ice cover. Specifically, laser altimetry and L-band Passive Remote Sensing data are combined using two forward models: the L-band radiation model and the isostatic relationship based on buoyancy model. Since the laser altimetry usually features much higher spatial resolution than L-band data from the Soil Moisture Ocean Salinity (SMOS) satellite, there is potentially covariability between the observed snow freeboard by altimetry and the retrieval target of snow depth on the spatial scale of altimetry samples. Statistically significant correlation is discovered based on high-resolution observations from Operation IceBridge (OIB), and with a nonlinear fitting the covariability is incorporated in the retrieval algorithm. By using fitting parameters derived from large-scale surveys, the retrievability is greatly improved compared with the retrieval that assumes flat snow cover (i.e., no covariability). Verifications with OIB data show good match between the observed and the retrieved parameters, including both sea ice thickness and snow depth. With detailed analysis, we show that the error of the retrieval mainly arises from the difference between the modeled and the observed (SMOS) L-band brightness temperature (TB). The narrow swath and the limited coverage of the sea ice cover by altimetry is the potential source of error associated with the modeling of L-band TB and retrieval. The proposed retrieval methodology can be applied to the basin-scale retrieval of sea ice thickness and snow depth, using concurrent Passive Remote Sensing and active laser altimetry based on satellites such as ICESat-2 and WCOM.
I. Moya - One of the best experts on this subject based on the ideXlab platform.
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a new instrument for Passive Remote Sensing 2 measurement of leaf and canopy reflectance changes at 531 nm and their relationship with photosynthesis and chlorophyll fluorescence
Remote Sensing of Environment, 2004Co-Authors: S Evain, Jaume Flexas, I. MoyaAbstract:Abstract A previously described Passive Remote Sensing fluorimeter (see companion paper) was modified to detect changes in the reflectance of vegetation. The utility of this Remote Sensing technique to measure the Physiological Reflectance Index (PRI) is shown at both leaf level under laboratory conditions and at the canopy level in the field. PRI, defined as the relative changes in reflectance at 531 nm with respect to those at 570 nm (PRI=R531−R570/R531+R570), is related to xanthophyll-related, dynamic changes of non-photochemical quenching of chlorophyll fluorescence. The robustness of this relationship by simultaneous Remote Sensing of PRI and chlorophyll fluorescence is strengthened. At the leaf level, the existence of two kinetically distinct components of PRI is shown. A fast (within seconds) component that is partly attributed to ΔpH induced chloroplast shrinkage, and a slow (within minutes), main component that is related to xanthophyll de-epoxidation, as demonstrated by its disappearance in the presence of DTT. Overall, PRI correlated better with non-photochemical quenching of chlorophyll fluorescence (NPQ) than with any other measured parameter, including the photochemical efficiency of PSII. Finally, at the canopy level and under field conditions, it is shown that PRI can be a useful tool for Remote Sensing of water stress in grapevines.
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A new instrument for Passive Remote Sensing 1. Measurements of sunlight-induced chlorophyll fluorescence
Remote Sensing of Environment, 2004Co-Authors: I. Moya, L. Camenen, S Evain, Y. Goulas, Zoran G. Cerovic, Gwendal Latouche, Jaume Flexas, Abderrahmane OunisAbstract:Abstract Under natural sunlight illumination, the chlorophyll fluorescence emitted by the vegetation represents less than 3% of the reflected light in the near infrared part of the spectrum. This small amount is difficult to quantify except at certain wavelengths, where the solar spectrum is attenuated (Fraunhofer lines). An instrument measuring the in-filling of the atmospheric oxygen absorption band at 760 nm by chlorophyll fluorescence has been designed and constructed at the “Laboratoire pour l'Utilisation du Rayonnement Electromagnetique” in Orsay, France. The system was calibrated against a pulsed fluorimeter (FIPAM), especially developed for monitoring chlorophyll fluorescence at distance. The penetration of diuron, a herbicide acting on photosynthesis, was monitored by the Passive instrument for several days on a corn canopy. A good agreement was found between gas exchange and variable chlorophyll fluorescence at the canopy level and variable fluorescence at the leaf level. The potential application of the Passive chlorophyll fluorescence measurements for long range vegetation Remote Sensing is discussed.
Wei Gong - One of the best experts on this subject based on the ideXlab platform.
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satellite derived aerosol optical depth fusion combining active and Passive Remote Sensing based on bayesian maximum entropy
IEEE Transactions on Geoscience and Remote Sensing, 2021Co-Authors: Xinghui Xia, Bin Zhao, Tianhao Zhang, Luyao Wang, Kuonan Liou, Feiyue Mao, Boming Liu, Yusi Huang, Jiadan Dong, Wei GongAbstract:Satellite-derived aerosol optical depth (AOD) is an important parameter for studies related to atmospheric environment, climate change, and biogeochemical cycle. Unfortunately, the relatively high data missing ratio of satellite-derived AOD limits the atmosphere-related research and applications to a certain extent. Accordingly, numerous AOD fusion algorithms have been proposed in recent years. However, most of these algorithms focused on merging AOD products from multiple Passive sensors, which cannot complementarily recover the AOD missing values due to cloud obscuration and the misidentification between optically thin cloud and aerosols. In order to address these issues, a spatiotemporal AOD fusion framework combining active and Passive Remote Sensing based on Bayesian maximum entropy methodology (AP-BME) is developed to provide satellite-derived AOD data sets with high spatial coverage and good accuracy in large scale. The results demonstrate that AP-BME fusion significantly improves the spatial coverage of AOD, from an averaged spatial completeness of 27.9%-92.8% in the study areas, in which the spatial coverage improves from 91.1% to 92.8% when introducing Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) AOD data sets into the fusion process. Meanwhile, the accuracy of recovered AOD nearly maintains that of the original satellite AOD products, based on evaluation against ground-based Aerosol Robotic Network (AERONET) AOD. Moreover, the efficacy of the active sensor in AOD fusion is discussed through overall accuracy comparison and two case analyses, which shows that the provision of key aerosol information by the active sensor on haze condition or under thin cloud is important for not only restoring the real haze situations but also avoiding AOD overestimation caused by cloud optical depth (COD) contamination in AOD fusion results.
Ping Yang - One of the best experts on this subject based on the ideXlab platform.
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single scattering properties of ice particles in the microwave regime temperature effect on the ice refractive index with implications in Remote Sensing
Journal of Quantitative Spectroscopy & Radiative Transfer, 2017Co-Authors: Jiachen Ding, Ping Yang, George W Kattawar, Fuzhong Weng, Quanhua Liu, Thomas J GreenwaldAbstract:Abstract An ice crystal single-scattering property database is developed in the microwave spectral region (1 to 874 GHz) to provide the scattering, absorption, and polarization properties of 12 ice crystal habits (10-plate aggregate, 5-plate aggregate, 8-column aggregate, solid hexagonal column, hollow hexagonal column, hexagonal plate, solid bullet rosette, hollow bullet rosette, droxtal, oblate spheroid, prolate spheroid, and sphere) with particle maximum dimensions from 2 µm to 10 mm. For each habit, four temperatures (160, 200, 230, and 270 K) are selected to account for temperature dependence of the ice refractive index. The microphysical and scattering properties include projected area, volume, extinction efficiency, single-scattering albedo, asymmetry factor, and six independent nonzero phase matrix elements (i.e. P11, P12, P22, P33, P43 and P44). The scattering properties are computed by the Invariant Imbedding T-Matrix (II-TM) method and the Improved Geometric Optics Method (IGOM). The computation results show that the temperature dependence of the ice single-scattering properties in the microwave region is significant, particularly at high frequencies. Potential active and Passive Remote Sensing applications of the database are illustrated through radar reflectivity and radiative transfer calculations. For cloud radar applications, ignoring temperature dependence has little effect on ice water content measurements. For Passive microwave Remote Sensing, ignoring temperature dependence may lead to brightness temperature biases up to 5 K in the case of a large ice water path.
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effects of ice particle size vertical inhomogeneity on the Passive Remote Sensing of ice clouds
Journal of Geophysical Research, 2010Co-Authors: Zhibo Zhang, Steven Platnick, Ping Yang, Andrew K Heidinger, Jennifer M ComstockAbstract:The solar reflectance bi-spectral (SRBS) and infrared split-window (IRSpW) methods are two of the most popular techniques for Passive ice cloud property retrievals from multispectral imagers. Ice clouds are usually assumed to be vertically homogeneous in global operational algorithms based on these methods, although significant vertical variations of ice particle size are typically observed in ice clouds. In this Study we investigate uncertainties in retrieved optical thickness, effective particle size, and ice water path introduced by a homogeneous cloud assumption in both the SRBS and IRSpW methods, and focus on whether the assumption can lead to significant discrepancies between the two methods. The study simulates the upwelling spectral radiance associated with vertically structured clouds and passes the results through representative SRBS and IRSpW retrieval algorithms. Cloud optical thickness is limited to values for which IRSpW retrievals are possible (optical thickness less than about 7). When the ice cloud is optically thin and yet has a significant ice particle size vertical variation, it is found that both methods tend to underestimate the effective radius and ice water path. The reason for the underestimation is the nonlinear dependence of ice particle scattering properties (extinction and single scattering albedo) on the effective radius. Because the nonlinearity effect is stronger in the IRSpW than the SRBS method, the IRSpW-based IWP tends to be smaller than the SRBS counterpart. When the ice cloud is moderately optically thick, the IRSpW method is relatively insensitive to cloud vertical structure and effective radius retrieval is weighted toward smaller ice particle size, while the weighting function makes the SRBS method more sensitive to the ice particle size in the upper portion of the cloud. As a result, when ice particle size increases monotonically toward cloud base, the two methods are in qualitative agreement; in the event that ice particle size decreases toward cloud base, the effective radius and ice water path retrievals based on the SRBS method are substantially larger than those from the IRSpW. The main findings of this Study Suggest that the homogenous cloud assumption can affect the SRBS and IRSpW methods to different extents and, consequently, can lead to significantly different retrievals. Therefore caution should be taken when comparing and combining the ice cloud property retrievals from these two methods.
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effect of cavities on the optical properties of bullet rosettes implications for active and Passive Remote Sensing of ice cloud properties
Journal of Applied Meteorology and Climatology, 2008Co-Authors: Ping Yang, Zhibo Zhang, George W Kattawar, Stephen G Warren, Bryan A Baum, Hunglung Huang, David M Winker, Jean IaquintaAbstract:Bullet rosette particles are common in ice clouds, and the bullets may often be hollow. Here the singlescattering properties of randomly oriented hollow bullet rosette ice particles are investigated. A bullet, which is an individual branch of a rosette, is defined as a hexagonal column attached to a hexagonal pyramidal tip. For this study, a hollow structure is included at the end of the columnar part of each bullet branch and the shape of the hollow structure is defined as a hexagonal pyramid. A hollow bullet rosette may have between 2 and 12 branches. An improved geometric optics method is used to solve for the scattering of light in the particle. The primary optical effect of incorporating a hollow end in each of the bullets is to decrease the magnitude of backscattering. In terms of the angular distribution of scattered energy, the hollow bullets increase the scattering phase function values within the forward scattering angle region from 1° to 20° but decrease the phase function values at side- and backscattering angles of 60°–180°. As a result, the presence of hollow bullets tends to increase the asymmetry factor. In addition to the scattering phase function, the other elements of the phase matrix are also discussed. The backscattering depolarization ratios for hollow and solid bullet rosettes are found to be very different. This may have an implication for active Remote Sensing of ice clouds, such as from polarimetric lidar measurements. In a comparison of solid and hollow bullet rosettes, the effect of the differences on the retrieval of both the ice cloud effective particle size and optical thickness is also discussed. It is found that the presence of hollow bullet rosettes acts to decrease the inferred effective particle size and to increase the optical thickness in comparison with the use of solid bullet rosettes.