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The paper presents the fundamental characteristics of bistatic altimetry performed using the Global Positioning System (GPS) signal scattered off the ocean surface and collected by a receiver in space.
We generate and tabulate reflectance values of the Stokes parameters I, Q, and U of upwelling radiance just above a rough ocean surface and at the top of the atmosphere (TOA) for 100 scattering geometries, four atmosphere-ocean systems, and four wavelengths. The atmosphere-ocean systems increase in complexity from (a) a molecular atmosphere above a rough ocean surface (AOS-I model); to (b) a pure water body below a rough ocean surface (AOS-II model); to (c) a fully-coupled simple atmosphere-ocean system (AOS-III model) containing a molecular atmosphere, rough ocean surface, and pure water; to (d) a fully-coupled complex atmosphere-ocean system (AOS-IV model) that includes scattering by molecules, rough ocean surface, pure water, and hydrosols. Our wavelengths (350, 450, 550, and 650 nm) capture the ultraviolet-visible range. Our tables provide radiative transfer (RT) testbed results for atmosphere-ocean systems with an accuracy that surpasses the measurement accuracy of state-of-the-art polarimeters. To validate the accuracy of these tables we performed computations using three independent RT codes that provide deterministic numerical solutions for the RT equation. The agreement is 10(exp –5) for AOS-IV model, and 10(exp –6) for the other models. The degree of linear polarization computed by these RT codes differs by ≤0.2% for 15 isolated cases of tabulated reflectance values, and by ≤0.1% for all remaining cases. We also provide comparisons with results obtained by a stochastic RT code for AOS-I model. The agreement between the deterministic and stochastic results for this model is 10(exp –5) at TOA, and 10(exp –6) above the ocean surface.
In the microwave region combined active (scatterometer) and passive (radiometer) remote sensors over the ocean show promise of providing surface wind speeds and weather information to the oceanographer and meteorologist. This has aroused great interest in the investigation of the scattering of waves from the sea surface. A composite surface scattering theory is investigated. The two-scale scattering theory proposed by Semyonov was specifically extended to compute the emmision and scattering characteristics of ocean surfaces. The effects of clouds and rain on the radiometer and scatterometer observations are also investigated using horizontally stratified model atmospheres with rough sea surfaces underneath. Various cloud and rain models proposed by meteorologist were employed to determine the rise in the microwave temperature when viewing downward through these model atmospheres. For heavy rain-fall rates the effects of scattering on the radiative transfer process are included.
Ocean phytoplankton, detrital material, and water absorb and scatter light spectrally. The Ocean- Atmosphere Spectral Irradiance Model (OASIM) is intended to provide surface irradiance over the oceans with sufficient spectral resolution to support ocean ecology, biogeochemistry, and heat exchange investigations, and of sufficient duration to support inter-annual and decadal investigations. OASIM total surface irradiance (integrated 200 nm to 4 microns) was compared to in situ data and three publicly available global data products at monthly 1-degree resolution. OASIM spectrally-integrated surface irradiance had root mean square (RMS) difference= 20.1 W/sq m (about 11%), bias=1.6 W/sq m (about 0.8%), regression slope= 1.01 and correlation coefficient= 0.89, when compared to 2322 in situ observations. OASIM had the lowest bias of any of the global data products evaluated (ISCCP-FD, NCEP, and ISLSCP 11), and the best slope (nearest to unity). It had the second best RMS, and the third best correlation coefficient. OASIM total surface irradiance compared well with ISCCP-FD (RMS= 20.7 W/sq m; bias=-11.4 W/sq m, r=0.98) and ISLSCP II (RMS =25.2 W/sq m; bias= -13.8 W/sq m; r=0.97), but less well with NCEP (RMS =43.0 W/sq m ;bias=-22.6 W/sq m; x=0.91). Comparisons of OASIM photosynthetically available radiation (PAR) with PAR derived from SeaWiFS showed low bias (-1.8 mol photons /sq m/d, or about 5%), RMS (4.25 mol photons /sq m/d ' or about 12%), near unity slope (1.03) and high correlation coefficient (0.97). Coupled with previous estimates of clear sky spectral irradiance in OASIM (6.6% RMS at 1 nm resolution), these results suggest that OASIM provides reasonable estimates of surface broadband and spectral irradiance in the oceans, and can support studies on ocean ecosystems, carbon cycling, and heat exchange.
In general, terrestrial scenes remain stable in content from both temporal and spacial considerations. Ocean scenes, on the other hand, are constantly changing in content and position. The solar energy that enters the ocean waters undergoes a process of scattering and selective spectral absorption. Ocean scenes are thus characterized as low level radiance with the major portion of the energy in the blue region of the spectrum. Terrestrial scenes are typically of high level radiance with their spectral energies concentrated in the green-red regions of the visible spectrum. It appears that for the evaluation and calibration of ocean color remote sensing instrumentation, an ocean area whose optical ocean and atmospheric properties are known and remain seasonably stable over extended time periods is needed. The Tongue of the Ocean, a major submarine channel in the Bahama Banks, is one ocean are for which a large data base of oceanographic information and a limited amount of ocean optical data are available.
The daily, synoptic images provided by satellite ocean color instruments provide viable data streams for observing changes in the biogeochemistrY of marine ecosystems. Ocean reflectance inversion models (ORMs) provide a common mechanism for inverting the "color" of the water observed a satellite into marine inherent optical properties (lOPs) through a combination of empiricism and radiative transfer theory. lOPs, namely the spectral absorption and scattering characteristics of ocean water and its dissolved and particulate constituents, describe the contents of the upper ocean, information critical for furthering scientific understanding of biogeochemical oceanic processes. Many recent studies inferred marine particle sizes and discriminated between phytoplankton functional groups using remotely-sensed lOPs. While all demonstrated the viability of their approaches, few described the vertical distributions of the water column constituents under consideration and, thus, failed to report the biophysical conditions under which their model performed (e.g., the depth and thickness of the phytoplankton bloom(s)). We developed an ORM to remotely identifY Noctiluca miliaris and other phytoplankton functional types using satellite ocean color data records collected in the northern Arabian Sea. Here, we present results from analyses designed to evaluate the applicability and sensitivity of the ORM to varied biophysical conditions. Specifically, we: (1) synthesized a series of vertical profiles of spectral inherent optical properties that represent a wide variety of bio-optical conditions for the northern Arabian Sea under aN Miliaris bloom; (2) generated spectral remote-sensing reflectances from these profiles using Hydrolight; and, (3) applied the ORM to the synthesized reflectances to estimate the relative concentrations of diatoms and N Miliaris for each example. By comparing the estimates from the inversion model to those from synthesized vertical profiles, we were able to identifY those bio-optical conditions under which the inversion model performs both well and poorly.
In this study, aerosol optical depths over oceans are analyzed from satellite and surface perspectives. Multiangle Imaging SpectroRadiometer (MISR) aerosol retrievals are investigated and validated primarily against Maritime Aerosol Network (MAN) observations. Furthermore, AErosol RObotic NETwork (AERONET) data from 19 island and coastal sites is incorporated in this study. The 270 MISRMAN comparison points scattered across all oceans were identified. MISR on average overestimates aerosol optical depths (AODs) by 0.04 as compared to MAN; the correlation coefficient and root-mean-square error are 0.95 and 0.06, respectively. A new screening procedure based on retrieval region characterization is proposed, which is capable of substantially reducing MISR retrieval biases. Over 1000 additional MISRAERONET comparison points are added to the analysis to confirm the validity of the method. The bias reduction is effective within all AOD ranges. Setting a clear flag fraction threshold to 0.6 reduces the bias to below 0.02, which is close to a typical ground-based measurement uncertainty. Twelve years of MISR data are analyzed with the new screening procedure. The average over ocean AOD is reduced by 0.03, from 0.15 to 0.12. The largest AOD decrease is observed in high latitudes of both hemispheres, regions with climatologically high cloud cover. It is postulated that the screening procedure eliminates spurious retrieval errors associated with cloud contamination and cloud adjacency effects. The proposed filtering method can be used for validating aerosol and chemical transport models.
Ocean color measured from satellites provides daily global, synoptic views of spectral water-leaving reflectances that can be used to generate estimates of marine inherent optical properties (IOPs). These reflectances, namely the ratio of spectral upwelled radiances to spectral downwelled irradiances, describe the light exiting a water mass that defines its color. IOPs are the spectral absorption and scattering characteristics of ocean water and its dissolved and particulate constituents. Because of their dependence on the concentration and composition of marine constituents, IOPs can be used to describe the contents of the upper ocean mixed layer. This information is critical to further our scientific understanding of biogeochemical oceanic processes, such as organic carbon production and export, phytoplankton dynamics, and responses to climatic disturbances. Given their importance, the international ocean color community has invested significant effort in improving the quality of satellite-derived IOP products, both regionally and globally. Recognizing the current influx of data products into the community and the need to improve current algorithms in anticipation of new satellite instruments (e.g., the global, hyperspectral spectroradiometer of the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission), we present a synopsis of the current state of the art in the retrieval of these core optical properties. Contemporary approaches for obtaining IOPs from satellite ocean color are reviewed and, for clarity, separated based their inversion methodology or the type of IOPs sought. Summaries of known uncertainties associated with each approach are provided, as well as common performance metrics used to evaluate them. We discuss current knowledge gaps and make recommendations for future investment for upcoming missions whose instrument characteristics diverge sufficiently from heritage and existing sensors to warrant reassessing current approaches.
The wind-scale relationships for L band radar wavelengths near 25 cm and 20 deg angle of incidence and HH polarization are reviewed using a number of aircraft and Seasat-1 SAR observations. The dependence of the L band backscatter coefficient from the ocean upon surface wind speed and direction is stated. The wind speed coefficient is 0.5 + or - 0.1 for a wide range of wind speeds. The wind direction coefficient is near zero for lower winds and stable marine boundary layers, but may be 0.20 + or - 0.05 for moderate wind speeds and an unstable marine boundary layer. These results are interpreted in terms of existing theoretical models for radar scattering from the ocean.
A composite scattering model, suitable for explaining the behavior of measured scattering cross sections of the ocean surface, is presented. Furthermore, utilizing this scattering model, the spectrums of the small gravity, gravity-capillary, waves will be predicted for MSA/MSC, 13.3 GHz Scatterometer data.
The paper analyzes the effects of atmospheric and sea surface scattering on the determination of ocean color from satellite imagery and proposes an algorithm for removing a large portion of these effects. The algorithm is based on the observations that (1) the upward radiance from the unwanted photons can be divided into effects resulting from Rayleigh scattering alone and those resulting from aerosol scattering alone, (2) the aerosol scattering phase function should be nearly independent of wavelength, and (3) the Rayleigh component can be computed without a knowledge of the sea surface roughness. The ratio of the aerosol optical thickness at the wavelength of interest to the aerosol optical thickness at 750 nm is used in the algorithm since it is assumed that the ocean is totally absorbing in a band of wavelengths around 750 nm. The calculation of this ratio from satellite measurements alone and the accuracy of the procedure are considered.
The applicability of the various electromagnetic models of scattering from the ocean are reviewed. These models include the small perturbation method, the geometric optics solution, the composite model, and the exact integral equation solution. The restrictions on the electromagnetic models are discussed.
Satellite-borne radar altimeters include waveform sampling gates providing point samples of the transmitted radar pulse after its scattering from the ocean's surface. Averages of the waveform sampler data can be fitted by varying parameters in a model mean return waveform. The theoretical waveform model used is described as well as a general iterative nonlinear least squares procedures used to obtain estimates of parameters characterizing the modeled waveform for SEASAT-1 data. The six waveform parameters recovered by the fitting procedure are: (1) amplitude; (2) time origin, or track point; (3) ocean surface rms roughness; (4) noise baseline; (5) ocean surface skewness; and (6) altitude or off-nadir angle. Additional practical processing considerations are addressed and FORTRAN source listing for subroutines used in the waveform fitting are included. While the description is for the Seasat-1 altimeter waveform data analysis, the work can easily be generalized and extended to other radar altimeter systems.
In 1986, H. Berber and Hooper examined the signals that could be detected by an airborne lidar flying above the marine boundary layer (MBL). One signal (aureole) formed from laser light returned to the receiver after a reflect off the ocean and forward scatter off the aerosol particles appeared to be both detectable and related to the optical depth of the MBL. Now, research has been directed towards developing a practical instrument to measure the aureole and finding an algorithm to use the information. Unlike the lidar backscatter which typically requires a telescope with a narrow field of view (0.5 mrad), the aureole signal occurs over a wide field of view (50 mrad). To accommodate the totally different needs, a standard commercial Cassegrainian telescope was modified to yield a telescope with two focal planes. The secondary mirror was replaced by a lens, whose front surface was half silvered and curved to match the replaced mirror. Light reflecting off the lens focused behind the primary mirror. The back lens surface was curved to allow unreflected light to focus at the natural focus of the primary mirror. This focal plane which is behind the lens has a wide field of view. To calculate an extinction profile, the aureole optical depth estimate is combined with the lidar backscatter profile.
The efficient estimation of ocean wave-structure parameters with a remote, narrow-beam, pulsed, microwave radar at intermediate incidence angles is discussed. The sea surface is described as the sum of random small- and large-scale structures (waves), the latter the sum of a sinusoid and a random field. It is shown that the small-scale structure is responsible for scattering and that the scatter depends parametrically on the large-scale structure. For the estimation problem it is assumed, reasonably, that the received signal is normally distributed: a relatively simple processor which will efficiently estimate parameters of the sinusoidal structure is illustrated and its performance discussed. A brief comparison is made with a normal incidence system with which the variance of the large-scale random roughness can be estimated.
Consideration is given to the use of the Defense Meteorological Satellite Program's Special Sensor Microwave/Imager (SSM/I) to identify precipitation in warm and cold land and ocean environments. It is shown that the polarization diversity of the SSM/I operating at 85.5 GHz makes it possible to discriminate between low brightness temperatures due to surface water bodies and those due to precipitation. The theoretical sensitivity of SSM/I between 19.35 and 8.5. GHz and the polarization correction for water surfaces and the effects of cloud water are discussed. Examples are presented of observational studies using SSM/I for the delineation of precipitation over land and oceans.
NASA has launched the ICESat-2 mission in September 2018 with the primary purpose of monitoring changes in the cryosphere. Fortunately, the measured photons over ocean region provide great opportunity for the ocean subsurface study. We have proposed a novel algorithm to determine ocean subsurface optical properties, such as, diffuse attenuated coefficient, kd (/m), total backscattering coefficients bb (/m), attenuated backscatter coefficient and particulate backscattering coefficients b(sub bp) (/m) from ICESat-2/ATLAS lidar measurements. Our ICESat-2 ocean subsurface results reveal high vertical resolution of these optical properties through the water column that are hidden from the passive ocean color record. Moreover, we can estimate the particulate organic carbon (POC) and phytoplankton carbon biomass based on the ICESat-2 retrieved particulate backscattering coefficients b( sub bp) results. We will present and discuss the first ICESat-2 ocean subsurface profile results, especially in polar region where passive ocean color measurements are difficult to make. We will also present the multiple scattering effects on the ocean subsurface optical properties retrieval.
Microwave rain rate retrieval algorithms have most often been formulated in terms of the raw brightness temperatures observed by one or more channels of a satellite radiometer. Taken individually, single-channel brightness temperatures generally represent a near-arbitrary combination of positive contributions due to liquid water emission and negative contributions due to scattering by ice and/or visibility of the radiometrically cold ocean surface. Unfortunately, for a given rain rate, emission by liquid water below the freezing level and scattering by ice particles above the freezing level are rather loosely coupled in both a physical and statistical sense. Furthermore, microwave brightness temperatures may vary significantly (approx. 30-70 K) in response to geophysical parameters other than liquid water and precipitation. Because of these complications, physical algorithms which attempt to directly invert observed brightness temperatures have typically relied on the iterative adjustment of detailed micro-physical profiles or cloud models, guided by explicit forward microwave radiative transfer calculations. In support of an effort to develop a significantly simpler and more efficient inversion-type rain rate algorithm, the physical information content of two linear transformations of single-frequency, dual-polarization brightness temperatures is studied: the normalized polarization difference P of Petty and Katsaros (1990, 1992), which is intended as a measure of footprint-averaged rain cloud transmittance for a given frequency; and a scattering index S (similar to the polarization corrected temperature of Spencer et al.,1989) which is sensitive almost exclusively to ice. A reverse Monte Carlo radiative transfer model is used to elucidate the qualitative response of these physically distinct single-frequency indices to idealized 3-dimensional rain clouds and to demonstrate their advantages over raw brightness temperatures both as stand-alone indices of precipitation activity and as primary variables in physical, multichannel rain rate retrieval schemes. As a byproduct of the present analysis, it is shown that conventional plane-parallel analyses of the well-known foot-print-filling problem for emission-based algorithms may in some cases give seriously misleading results.