The “Global Change Observation Mission-Climate” (GCOM-C) is a project of Japan Aerospace Exploration Agency
(JAXA) for the global and long-term observation of the Earth environment. The GCOM-C is a part of the JAXA’s
GCOM mission which consists of two satellite series, GCOM-C and GCOM-W (Water), spanning three generations in
order to perform uniform and stable global observations for 13 years. GCOM-C carries a multi-spectral optical
radiometer named Second Generation Global Imager (SGLI), which will have special features of wide spectral coverage
from 380nm to 12μm, a high spatial resolution of 250m, a field of view exceeding 1000km, two-direction simultaneous
observation, and polarization observation. The GCOM-C mission aims to improve our knowledge on the global carbon
cycle and radiation budget through high-accuracy observation of global vegetation, ocean color, temperature, cloud,
aerosol, and snow and ice. As for the cryosphere products, not only snow and ice cover extent but also snow physical
parameters are retrieved from SGLI data such as snow grain sizes at several surface levels (shallow layer, sub-surface
layer, and the top surface), temperature, and mass fraction of impurity mixed in snow layer and so on. These snow
physical parameters are important factors that determine spectral albedo and radiation budget at the snow surface. Thus it
is essential to monitor those parameters from space in order to better understand snow metamorphosis and melting
process and also to study the response of snow and sea-ice cover extent in the Polar Regions to a climate forcing such as
global warming. This paper will summarize the SGLI cryospheric products and validation plans.
For remote sensing over snow-covered surfaces, the bidirectional reflectance distribution function (BRDF) of snow plays an important role that should be considered in inverse algorithms for the retrieval of snow properties. However, to simplify retrievals, many researchers assume that snow is a Lambertian reflector. This “forward model” error affects the accuracy of retrieved snow parameters (such as albedo, snow grain size, and impurity concentration). To quantify this error and to compensate for it, we provide a simple yet accurate semi-empirical correction formula. It allows for easy conversion of top-of-the-atmosphere (TOA) reflectance arising from an anisotropically reflecting snow surface to an equivalent TOA reflectance for a Lambertian surface with the same albedo. Conversely, this correction can be used to translate TOA radiance computed with the Lambertian assumption into a more realistic value based on a BRDF treatment. The coefficients in this correction formula are stored in a look-up table (LUT), and a simple LUT interpolation program is provided to allow the user to extract TOA reflectances for any sun-satellite geometry by quick interpolation in the LUTs. For the first 8 channels of the VIIRS spectrometer, the R-square regression coefficient for fitting this correction formula is better than 0.95 for a wide range of sun-satellite geometries.
We discuss a new versatile setup for goniometric measurements of spectral radiances with two modes of operation: (1) it can operate as a 2-D goniometer for measurements in a horizontal plane of the singly scattered radiance from particles in suspension and (2) it can be used as a 3-D goniometer for measuring spectral radiances over an entire hemisphere. In our setup, various kinds of light sources and detectors can easily be inserted. Among the detectors, a spectral imager is designed and used. Proper hardware and software is chosen so as to make our setup fully automated and easy to operate. We present results from two different investigations to demonstrate the utilization of our setup. The first investigation is concerned with measurements of the volume scattering function (VSF) over a large forward and backward angular range. Our experimental results for the VSF show good agreement with theoretical simulations. We also use our setup to obtain a series of 1-D angular spectral images of the skin on the dorsal side of a human hand in vivo by employing various illumination angles. Our setup provides a robust, highly automated, and flexible framework for carrying out goniometric measurements in a variety of applications.
Methane seepage is indicative of petroleum or natural gas reserves. Techniques aimed at detecting methane seepage with surface-based instrumentation have progressed significantly in recent years. These techniques rely on measurement of light attenuation due to methane absorption of short wave infrared (SWIR) radiation. Detection of methane seepage over water bodies with electro-optical remote sensing has been limited by the low surface reflectance of water. Also, due to sensor saturation, imagery over sunglint is commonly discarded in satellite remote sensing, because the glint conditions produce high surface reflectance. However, recent measurements in the SWIR of sunglint regions have revealed that the surface reflectance is spectrally flat and enhanced without causing saturation. This higher surface reflectance in sunglint regions allow for retrieval of the total column methane amount using ratios of measured radiances at wavelengths inside and outside the methane SWIR-absorbing channels. The methane retrieval method presented here, based on shortwave infrared band ratios in sunglint regions, allows for detection of methane seepage over the Earth's oceans and lakes, and the detection of possible petroleum or natural gas reserves. Radiative transfer simulations are used to demonstrate the capabilities offered by this technique.
Recent technological advances have made measurements of UV doses and ozone column amounts with multichannel filter instruments not only possible, but also an attractive alternative to other more labor-intensive and weather-dependent methods. Filter instruments can operate unattended for long periods of time, and it is possible to obtain accurate ozone column amounts even on cloudy days. We present results from extensive comparisons of the performance of several Norwegian Institute for Air Research UV (NILU-UV) and ground-based (GUV) filter instruments against Dobson and Brewer instruments and the earth probe–total ozone mapping spectrometer (EP-TOMS) instrument. The data used in the comparisons are from four different sites where we have had the opportunity to operate more than one type of UV instrument for extended periods of time. The sites include the University of Oslo, Norway; Ny-Ålesund, Spitzbergen, Norway; the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center facilities at Wallops Island, Virginia, and Greenbelt, Maryland; and the University of Alaska, Fairbanks. Our results show that ozone column amounts obtained with current filter-type instruments have an accuracy similar to those obtained with the Dobson instrument. The mean difference between NILU-UV and Dobson direct sun measurements were 0.4±1.9% (1) in Oslo for the period 2000 to 2003. The difference between a GUV and the same Dobson was 1.7±1.4% for the same time period. The mean difference between GUV and TOMS in Ny-Ålesund 79 deg N and Oslo 60 deg N in the period 1996 to 1999 was <0.5±3% for days with noon solar zenith angles (SZAs)<80 deg.
Successful retrieval of surface properties from space is hampered by the presence of atmospheric aerosol particles that contribute significantly to the measured signal. Our ability to obtain reliable information about surface properties depends to a large extent on how well we can account for the influence of aerosols. The problem is complicated by the fact that aerosols often consist of a multicomponent mixture of particles with different chemical compositions and different affinities to water. For example, to predict how the optical properties of such particles change with increasing humidity, we must make assumptions about how the particles grow, change their refractive indices, and mix as a function of humidity. We discuss possible strategies for reliable atmospheric correction over dark as well as bright surfaces. Also, we discuss the role of realistic simulations of the radiative transfer process in the coupled atmosphere-ocean system in the solution of the inverse problem required to retrieve surface properties is also discussed.
Recent work has shown the need for accurate treatment of radiative transfer in ocean color retrieval. The plane-parallel coupled atmosphere-ocean discrete ordinate model CAO-DISORT has been used to investigate the validity of current approximative inverse methods and to study new techniques for improved ocean color retrieval. In this paper we show that CAO-DISORT is fully differentiable with respect to its input optical properties, so that we can define analytic Jacobians with respect to any profile element in the atmosphere and ocean. A single call to the linearized model will produce radiances and Jacobians at arbitrary optical depth and viewing geometry in either medium. The model also has a pseudo-spherical treatment for solar beam attenuation in a curved atmosphere. The linearized model can be used directly in iterative least-squares retrievals requiring forward model simulations of backscatter measurements and their parameter derivatives; there is no need for approximations involving an atmospheric correction. We demonstrate the model's new capability by performing closed-loop least squares fitting to simultaneously retrieve the aerosol optical thickness and marine chlorophyll concentration from a set of 6 synthetic measurements at SeaWifs wavelengths.
A new method for simultaneous retrieval of aerosol properties and marine constituents in turbid waters is described. This method is an extension to turbid waters of an approach developed previously for simultaneous retrieval of aerosol properties and chlorophyll concentrations in clear waters. This extension is accomplished by employing near-infrared (NIR) channels not available on the SeaWiFS and MERIS instruments to help retrieve aerosol parameters over turbid waters. Optimal estimation theory is used to retrieve in-water parameters from multi- and hyperspectral information. Both forward and inverse modeling strategies will be discussed, as well as the uniqueness of the solutions, the information content available in multi- and hyperspectral data, and the error analysis approach. Our results indicate that it is important to use forward models that accurately treat the radiative transfer in the coupled (combined) atmosphere-ocean system, and to carefully select the most suitable bio-optical models for the in-water inherent optical properties (IOPs). Synthetic data, as well as multi- and hyperspectral images of data obtained over clear as well as turbid waters, are used to test the validity of the new retrieval approach.
Retrieval of surface properties of highly reflecting targets such as snow and ice is a challenging problem due to the influence of aerosols
which varies considerably in space and time. Also, accounting for the bidirectional properties of a bright surface such as snow is very important for reliable retrievals. The main purpose of the work described in this paper is to explore the opportunities and possibilities offered by multi- and hyperspectral data such as those available provided by MODIS, GLI, the Advanced Land Imager (ALI), and Hyperion to retrieve reliable aerosol and surface properties. Over snow and ice surfaces these include aerosol optical depth and single scattering albedo, the mean size of snow grains and ice "particles" (inclusions), and the spectral and broadband snow/ice albedo. In particular the following question will be addressed: To what extent can multi- and hyperspectral data help improve our knowledge of snow and ice parameters that are important for understanding global climate change?
For optical satellite remote sensing of the marine arctic environment
it is essential to establish appropriate knowledge of its optical
properties. To that end we used a multi stream radiative transfer (RT)
code to study the penetration of spectral irradiances in a coupled
atmosphere-ice-ocean system. The code account for the change in the
refractive index at the atmosphere-ice interface. To validate and tune this coupled RT model we ran the code with input from in situ measurements of optical properties and compared the computed results with in situ spectral irradiance measurements. The field work was done in Kongsfjorden, Svalbard, and the measurements were performed for first year ice. One goal of this study was to establish a model for the optical properties of the marine arctic environment that can be used in the interpretation of satellite remote sensing data.
A number of remote sensing instruments with multi-spectral imaging capabilities (SeaWiFS, MODIS, GLI on ADEOS-II, and others) have recently been launched on earth-orbiting satellites or will soon be launched into space. Many of these sensors offer unique opportunities for studies of sea ice and ocean properties at high latitudes. There are a number of challenges associated with the inversion of data received from satellite such instruments in order to retrieve meaningful information. Here we discuss some of these challenges with emphasis on the derivation of sea ice and marine parameters from satellite data.
Successful retrieval of surface properties from space is hampered by the presence of atmospheric aerosol particles that contribute significantly to the measured signal. Our ability to obtain reliable information about surface properties depends to a large extent on how well we can account for the influence of aerosols. The problem is complicated by the fact that these aerosols often consist of a multi-component mixture of particles with different chemical compositions and different affinities to water. For example, in order to predict how the optical properties of such particles change with increasing humidity, we need to make assumptions about how the particles grow, change their refractive indices, and mix as a function of humidity. The purpose of this paper is to discuss possible strategies for reliable atmospheric correction over dark as well as bright surfaces. The role of realistic simulations of the radiative transfer process in the coupled atmosphere-surface system in order to solve the inverse problem required to retrieve surface properties will also be discussed.
Recent technology advances have made measurements of UV doses and ozone column amounts with multi-channel filter instruments not only possible, but also an attractive alternative to other more labor-intensive and weather dependent methods. Filter instruments can operate unattended for long periods of time, and it is possible to obtain accurate ozone column amounts even on cloudy days. We present results from extensive comparisons of the performance of several NILU-UV and GUV filter instruments against Dobson and Brewer instruments and the EP-TOMS instrument. The data used in the comparisons are from four different sites where we have had the opportunity to operate more than one type of UV instruments for extended periods of time. The sites include the University of Oslo, Norway, Ny-Alesund, Spitzbergen, Norway, the NASA Goddard Space Flight Center facilities at Wallops Island, VA, and Greenbelt, MD and the University of Alaska, Fairbanks. Our results show that ozone column amounts obtained with current filter-type instruments are just as good as those obtained with the Dobson instrument. The mean difference between NILU-UV and Dobson direct sun measurements were 0.4% ± 1.9% (1σ) in Oslo 2000-2003. The difference between a GUV and the same Dobson was 1.7% ± 1.4% for the same time period. The mean difference between GUV and TOMS in Ny-Alesund 79°N and Oslo 60°N in the period 1996-1999 was < 0.5% ± 3% for days with noon SZA < 80°.
At Stevens Institute of Technology, Hoboken, NJ we have operated a site with NILU-UV instruments for nearly two years. For most of this time only one instrument has been in operation, but we also have
data for extended periods of time when up to three instruments have been working in parallel. The site is in close proximity to New York City and it is equipped with basic radiation sensors in addition to the NILU-UV sensors. In a companion paper we present results from intercomparisons between filter-based instruments, such as the NILU-UV, and the Dobson and Brewer instruments. Here we describe our experience operating filter-based radiation instruments. In particular, we discuss data quality issues and describe how one can detect and correct for drift in filter-based instruments. We also investigate the effect of elevated detector temperatures due to over-heating of the instrument by solar radiation on very warm days. Our experience with the newer versions of the filter instruments is that most of them have only minor problems with filter drift over time, and that this drift (if any) is easily detectable and can be corrected for. A potential problem is that varying detector temperature can degrade the instrument performance. Since filter UV instruments are normally set to operate with detector temperatures much higher than ambient temperatures this is a minor issue for most locations, and one that can easily be prevented.
In order to retrieve accurate information about surface physical and biogeochemical properties from space-borne sensors removal of the atmospheric signal is required. On the other hand, the retrieval of aerosol properties from space is hampered by the necessity to remove the signal originating from the underlying surface. Instead of retrieving surface (aerosol) properties in a two-step procedure in which an "atmospheric (surface) correction" is followed by retrieval of the desired quantity, it may be advantageous to attempt a simultaneous retrieval of atmospheric and surface parameters. The forward and inverse modeling strategies associated with this approach are discussed. This approach is particularly useful over bright surfaces, and can be used for simultaneous retrieval of snow and aerosol properties.
A tutorial review is provided of UV radiation transport in the atmosphere-ocean system. Emphasis is placed on the basic physical principles involved rather than on mathematical/numerical aspects. To illustrate the application of the theory, the effects of an ozone depletion on UV irradiance at the surface are discussed. A comparison of measured and predicted UV penetration into the ocean under the Antarctic ozone hole is also provided.
Radiance multiply scattered from clouds and thick aerosols is a significant component in the short wave IR through the visible region of the electro-optical (EO) spectrum. In MODTRAN, until very recently, multiple scattering predictions could not vary with the azimuth of the line-of-sight (LOS), although the single scattering component of the radiance did take the azimuthal variation into account. MODTRAN has now been upgraded to incorporate the dependence of multiple scattering (MS) on the azimuth of the LOS. This was accomplished by upgrading the interface between MODTRAN and DISORT, which is used as an MS subroutine in MODTRAN. Results from the upgraded MODTRAN are compared against measurements of radiance in a cloudy sky in the 1.5 - 2.5 micrometer region. Furthermore, taking advantage of DISORT, the upgraded version of MODTRAN can accommodate parameterized BRDFs (Bi-Directional Reflectance Distribution Functions) for surfaces. Some results, which demonstrate the new MODTRAN capabilities, are presented. Additionally, MS results from MODTRAN are compared to results obtained from a Monte-Carlo model.
Optical remote sensing of ocean color is a well-established technique. But most algorithms developed hitherto have been based on the assumption that only the phytoplankton affect the optical properties of the ocean. Such algorithms are often based on assumptions that become questionable in coastal areas. The assumption of a near-infrared dark pixel in the satellite image, will no longer be valid, and the band-ratio technique used for computing the algae concentration will also become inaccurate. To overcome these limitations we have developed an inverse-modeling algorithm for retrieval of marine constituents. Here the determination of ocean color is based on a three-component optical model consisting of chlorophyll-a, suspended matter, and yellow substance. We also use one parameter to describe the thickness of the aerosol layer. A simulated-annealing optimization scheme is employed to minimize the difference between measured satellite data and corresponding simulated data obtained using a coupled atmosphere-ocean radiative transfer code. The same optimization method has also been applied to the problem of retrieving the algae concentration in waters with vertical structure. In this case the marine parameters of interest are the algae concentration in two different layers as well as the thickness of the first layer.
By using a new method of solving the radiative transfer equation, we calculate the diffuse (i.e. scattered) radiance due to a Gaussian beam incident on a slab of finite thickness filled with scattering particles. The radiance is calculated for several observation angles and at any point inside or at the boundaries of the slab, both for isotropically and weakly anisotropically scattering media.
A recently developed radiative transfer model is applied to study the transport of photosynthetically active radiation (PAR) in the whole coupled atmosphere, sea ice and ocean system. This model rigorously accounts for the multiple scattering and absorption by the atmospheric molecules, clouds, snow and sea water, as well as the brine pockets and air bubbles trapped in sea ice. Both the spectral distribution and the seasonal variation of PAR at various levels in the ice and ocean have been investigated for different conditions. Results show that clouds, snow and ice algae all have important effects on the PAR availability to the microbial community under ice. The algae in the ice also significantly alters the spectral distribution of PAR transmitted to the ocean. Compared with the effects of clouds, snow and ice algae, the effect of changes in the amount of ozone in the atmosphere, the main absorptive gas in the PAR spectrum, on the amount of PAR entering the ice and ocean is negligible.
The effect of ozone depletion on penetration of UVB radiation through the atmosphere and into an aquatic system is investigated with the use of a newly developed radiation model pertinent for the coupled atmosphere-ocean system. The atmosphere and underlying water are each divided into a sufficient number of horizontal layers to resolve the changes in model accounts for all orders of multiple scattering and the change in index of refraction across the air- water interface. The penetration of UVB radiation into the aquatic system is examined by assuming `normal' ozone abundance, taken to be 350 DU, and about 30% reduction from normal (250 DU), at 70 degree(s) N. The effect of ozone depletion on the UVB penetration into the water is more pronounced in early spring than in summer. The UVB enhancements are up to 36% at the earth surface and 33% 10 meters below the sea surface on April 1 at 70 degree(s) N as a consequence of ozone depletion from normal level to 250 DU.
Measurements of surface radiation fluxes and radiosonde sounding data under overcast cloud situations during spring-summer 1988 at Barrow (Alaska) are analyzed. These data were combined with calculations from simple radiation models to estimate the surface radiation budget as well as reflectance, transmittance, and absorptance of the earth-atmosphere system on an hourly basis. Warming/cooling rates of the whole atmosphere were computed. These parameters for clear sky conditions are also presented.
The North Slope of Alaska and the adjacent Arctic Ocean has been chosen as the primary high-latitude ARM site. This is a region of the globe where, on average, the planet loses more energy to space than it receives from the sun. Global climate models appear to be particularly sensitive to climate perturbations at high Northern latitudes. It is therefore important to pay careful attention to these heat sink regions and incorporate high-latitude climate processes correctly. Once we get high latitude processes `right,' we can use the polar regions as a diagnostic for global climate change. The Arctic is characterized by extreme seasonal variation in insolation, surface properties, and exchange of water vapor between the surface and the atmosphere. This extreme variation leads to important climate feedback mechanisms involving the interaction between surface temperature and water vapor, cloud cover, and surface albedo. The challenge for the North Slope of Alaska ARM site is to capture these high-latitude feedback processes for inclusion in global climate models.
Quantitative spectral, solar UV measurements are introduced together with lunar spectral measurements in arbitrary units. Meteorological factors have a more pronounced effect on the UV irradiance than the ozone layer, and the ozone layer has an increasing attenuation effect towards higher latitudes. Coordinated biological and spectral lunar observations are outlined.
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