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At least 325 records · Page 18

Implementation of an Analytical Raman Scattering Correction for Satellite Ocean-Color Processing

Raman scattering of photons by seawater molecules is an inelastic scattering process. This effect can contribute significantly to the water-leaving radiance signal observed by space-borne ocean-color spectroradiometers. If not accounted for during ocean-color processing, Raman scattering can cause biases in derived inherent optical properties (IOPs). Here we describe a Raman scattering correction (RSC) algorithm that has been integrated within NASA's standard ocean-color processing software. We tested the RSC with NASA's Generalized Inherent Optical Properties algorithm (GIOP). A comparison between derived IOPs and in situ data revealed that the magnitude of the derived backscattering coefficient and the phytoplankton absorption coefficient were reduced when the RSC was applied, whilst the absorption coefficient of colored dissolved and detrital matter remained unchanged. Importantly, our results show that the RSC did not degrade the retrieval skill of the GIOP. In addition, a timeseries study of oligotrophic waters near Bermuda showed that the RSC did not introduce unwanted temporal trends or artifacts into derived IOPs.

SeaDAS↗

Simulating PACE Global Ocean Radiances

The NASA PACE mission is a hyper-spectral radiometer planned for launch in the next decade. It is intended to provide new information on ocean biogeochemical constituents by parsing the details of high resolution spectral absorption and scattering. It is the first of its kind for global applications and as such, poses challenges for design and operation. To support pre-launch mission development and assess on-orbit capabilities, the NASA Global Modeling and Assimilation Office has developed a dynamic simulation of global water-leaving radiances, using an ocean model containing multiple ocean phytoplankton groups, particulate detritus, particulate inorganic carbon (PIC), and chromophoric dissolved organic carbon (CDOC) along with optical absorption and scattering processes at 1 nm spectral resolution. The purpose here is to assess the skill of the dynamic model and derived global radiances. Global bias, uncertainty, and correlation are derived using available modern satellite radiances at moderate spectral resolution. Total chlorophyll, PIC, and the absorption coefficient of CDOC (aCDOC), are simultaneously assimilated to improve the fidelity of the optical constituent fields. A 5-year simulation showed statistically significant (P < 0.05) comparisons of chlorophyll (r = 0.869), PIC (r = 0.868), and a CDOC (r =0.890) with satellite data. Additionally, diatoms (r = 0.890), cyanobacteria (r = 0.732), and coccolithophores (r = 0.716) were significantly correlated with in situ data. Global assimilated distributions of optical constituents were coupled with a radiative transfer model (Ocean-Atmosphere Spectral Irradiance Model, OASIM) to estimate normalized water-leaving radiances at 1 nm for the spectral range 250-800 nm. These unassimilated radiances were within 0.074 mW/sq cm/micron/sr of MODIS-Aqua radiances at 412, 443, 488, 531, 547, and 667 nm. This difference represented a bias of 10.4% (model low). A mean correlation of 0.706 (P < 0.05) was found with global distributions of MODIS radiances. These results suggest skill in the global assimilated model and resulting radiances. The reported error characterization suggests that the global dynamical simulation can support some aspects of mission design and analysis. For example, the high spectral resolution of the simulation supports investigations of band selection. The global nature of the radiance representations supports investigations of satellite observing scenarios. Global radiances at bands not available in current and past missions support investigations of mission capability. PACE, ocean color, water-leaving radiances, biogeochemical model, radiative transfer model

PIC↗

In Situ Aerosol Optical Thickness Collected by the SIMBIOS Program (1997-2000): Protocols, and and Data QC and Analysis

The purpose of this technical report is to provide current documentation of the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project Office activities on in situ aerosol optical thickness (i.e., protocols, and data QC and analysis). This documentation is necessary to ensure that critical information is related to the scientific community and NASA management. This critical information includes the technical difficulties and challenges of validating and combining ocean color data from an array of independent satellite systems to form consistent and accurate global bio-optical time series products. This technical report is not meant as a substitute for scientific literature. Instead, it will provide a ready and responsive vehicle for the multitude of technical reports issued by an operational project.

Fargion, Giulietta S.↗

A new type of overshoot phenomenon in wind wave development and its implication in remote sensing of the ocean

Laboratory measurements using both wave probes (contact and optical) and radar confirm the existence of a new type of overshoot phenomenon in the wind-wave development processes. This type of overshoot, which occurs at gravity-capillary wavelengths, is practically a function of local wind stress only. It is named the overshoot phenomenon of the third kind. With the existence of this overshoot it becomes obvious that the assumed simple power-law relationship between the rms value of surface slope at a fixed wavelength and the wind stress is untenable. Since such a relationship is one of the key assumptions invoked in the development of algorithms used in scatterometry, the published scatterometer data are reexamined, pointing out the implications of this overshoot phenomenon. Recommendations for improvement of the performance of the scatterometer are also made in light of this new understanding of the wind-wave development processes.

Huang, N. E.↗

Directional and polarimetric effects in the optical domain

Papers focused on land surface, atmospheric, and ocean properties are reported. Specific comments pertaining to polarization, models and inversion, and measurements, are given. Recommendations are: continued research into the application potential of the BRDF (Bidirectional Reflectance Distribution Function) and polarization properties of ground surface and atmospheric targets; three dimensional models, which account for the statistical behavior of remotely sensed data, should be extended and inverted in order to support analysis of data potentially covering rolling terrain such that pixels represent heterogeneous mixtures of surface cover types and project ground footprints with sizes between 10 to 6 km, the ground pixel sizes of planned future sensors; available reflectance models should be further validated by means of multi dimensional (directional, spectral, temporal) field data and existing models should be intercompared in more depth to evaluate their performance and limitations; existing methods for model inversion should be validated in more depth in order to quantify the practical limitations and the expected accuracy of the parameters retrieved and new approaches should be developed based upon apriori knowledge of plant canopy development and spectral BRDF properties; there is a need to establish a protocol of validation and intercomparison of the indices and compositing techniques which have been proposed during these last years.

Vanderbilt, V. C.↗

Interpretable ensemble learning unveils main aerosol optical properties in predicting cloud condensation nuclei number concentration

Variations in cloud condensation nuclei number concentration (N CCN ) significantly influence cloud microphysics, yet direct N CCN measurements remain challenging. Here, we present an N CCN ensemble learning (NEL) model utilizing ensemble learning and interpretability analysis on aerosol optical parameters. Validated at two land sites, two ocean sites and one polar site within the Atmospheric Radiation Measurement program, the mean absolute percentage error range of the NEL model across different environments is from 12% to 36%, demonstrating high accuracy. Key findings reveal that aerosol optical parameters can serve as predictors for N CCN . Aerosol scattering and backscattering coefficients, absorption coefficient, backscatter fraction (BSF), and Ångström exponent (AE) are positively correlated with N CCN , while single scattering albedo shows negative correlations. N CCN prediction at land sites is highly sensitive to BSF, largely driven by the backscattering coefficient, as fine particles dominate in these sites. At ocean sites, N CCN prediction is more sensitive to AE, primarily influenced by the scattering coefficient, due to the higher proportion of larger particles. At the polar site, N CCN prediction shows sensitivity to both BSF and AE, mainly driven by the scattering coefficient, as polar sites are cleaner and contain larger particles. These differences reflect the variation in particle size and number concentration across different environments.

Atmospheric science↗

Multi-Band Atmospheric Correction Algorithm for Ocean Color Retrievals

NASA's current Atmospheric Correction (AC) algorithm for ocean color utilizes two bands and their ratio in the Near Infrared (NIR) to estimate aerosol reflectance and aerosol type. The algorithm then extrapolates the spectral dependence of aerosol reflectance to the visible wavelengths based on modeled spectral dependence of the identified aerosol type. Future advanced ocean color sensors, such as the Ocean Color Instrument (OCI) that will be carried on the Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) satellite, will be capable of measuring the hyperspectral radiance from 340 to 890 nm at 5-nm spectral resolution and at 7 discrete Short-wave Infrared (SWIR) channels: 940, 1038,1250, 1378, 1615, 2130, and 2260 nm. To optimally employ this unprecedented instrument capability, we propose an improved AC algorithm that utilizes all atmospheric-window channels in the NIR to SWIR spectral range to reduce the uncertainty in the AC process. A theoretical uncertainty analysis of this, namely Multi-Band AC (MBAC), indicates that the algorithm can reduce the uncertainty in remote sensing reflectance (Rrs) retrievals of the ocean caused by sensor random noise. Furthermore, in optically complex waters, where the NIR signal is affected by contributions from highly-reflective turbid waters, the MBAC algorithm can be adaptively weighted to the strongly-absorbing SWIR channels to enable improved ocean color retrievals in coastal waters. We provide here a description of the algorithm and demonstrate the improved performance in ocean color retrievals, relative to the current NASA standard AC algorithm, through comparison with field measurements and assessment of propagated uncertainties in applying the MBAC algorithm to MODIS and simulated PACE OCI data.

PACE↗

Simultaneous Retrieval of Aerosol Properties and Clear-Sky Direct Radiative Effect Over the Global Ocean from MODIS

A unified satellite algorithm is presented to simultaneously retrieve aerosol properties (aerosol optical depth; AOD and aerosol type) and clear-sky shortwave direct radiative effect (hereafter, DREA) over ocean. The algorithm is applied to Moderate Resolution Imaging spectroradiometer (MODIS) observations for a period from 2003 to 2010 to assess the DREA over the global ocean. The simultaneous retrieval utilizes lookup table (LUT) containing both spectral reflectances and solar irradiances calculated using a single radiative transfer model with the same aerosol input data. This study finds that aerosols cool the top-of-atmosphere (TOA) and bottom-of-atmosphere (BOA) by 5.2 +/- 0.5 W/sq m and 8.3 W/sq m, respectively, and correspondingly warm the atmosphere (hereafter, ATM) by 3.1 W/sq m. These quantities, solely based on the MODIS observations, are consistent with those of previous studies incorporating chemical transport model simulations and satellite observations. However, the DREAs at BOA and ATM are expected to be less accurate compared to that of TOA due to low sensitivity in retrieving aerosol type information, which is related with the atmospheric heating by aerosols, particularly in low AOD conditions; consequently, the uncertainties could not be quantified. Despite the issue in the aerosol type information, the present method allows us to confine the DREA attributed only to fine-mode dominant aerosols, which are expected to be mostly anthropogenic origin, in the range from 1.1 W/sq m to 1.3 W/sq m at TOA. Improvements in size-resolved AOD and SSA retrievals from current and upcoming satellite instruments are suggested to better assess the DREA, particularly at BOA and ATM, where aerosol absorptivity induces substantial uncertainty.

MODIS↗

Background Maritime Aerosol: Their Optical Thickness and Scattering Properties

The effect of human induced change in the aerosol concentration and properties, or the aerosol response to climate change (e.g. droughts producing fires or dust) should be measured relative to a "background aerosol". How to define this background aerosol, so that it is both measurable and useful? Here we use 10 stations located in the Pacific, Atlantic and Indian Oceans to answer this question. Using a data set of the spectral optical thickness measured by the Aerosol Robotic network (AERONET), extending 1-3 years, we find the background conditions for these stations. The oceanic background aerosol is the result of ocean emission and spray, and some residual long lived continental aerosol. Its source is very broadly spread and is expected to vary little in time. Pollution or dust sources are from specific locations, emitted and transported to the measuring site in specific combination of meteorological conditions. Therefore they are expected to vary with time. It follows that the background aerosol can be identified as the median for conditions with small variations. To define the background we compute the median of N consequent measurements. We use N=50 that in average cloudy conditions corresponds to 2-3 days of measurements and N=100 (4-5 days). Most high polluted or dusty conditions correspond to data sequences with high standard deviation (greater than 0.02 in optical thickness) and are excluded. From the remaining N point running medians with low standard deviations we derive again the median. This excludes those rare cases of pollution or dust that is stable during the N measurements. The results show that the background aerosol over the Pacific Ocean is characterize by optical thickness of 0.055 at 500 nm and Angstrom exponent of 0.74. Over the Atlantic Ocean the values are 0.070 and 1.1 respectively, with little influence of the assumed value of N (50 or 100). The derivation of the background uses 20,000 and 5000 medians respectively that passed the criteria. The contribution of coarse and fine aerosol to the background aerosol is also calculated.

Kaufman, Yoram J.↗

Modeling Sea Ice Albedo and Transmittance Measurements With A Fully-Coupled Radiative Transfer Model

A rigorous treatment of the sea ice medium has been incorporated in the advanced Coupled Ocean-Atmosphere Radiative Transfer (COART) model. The inherent optical properties (IOPs) of brine pockets and air bubbles over the 0.25-4.0 μm spectral region are parameterized as a function of the vertical profile of the sea ice physical properties (temperature, salinity and density). We test the model performance using available albedo and transmittance measurements collected during the Impacts of Climate on the Ecosystems and Chemistry of the Arctic Pacific Environment (ICESCAPE) and the Surface Heat Budget of the Arctic Ocean (SHEBA) field campaigns. The observations are adequately simulated when at least three layers are used to represent bare (first-year and multi-year) ice, including a thin top layer characterized by low density and high scattering. Two layers can be sufficient to model isolated cases of multi-year ice, and apply well to ponded ice except for shallow ponds over thick ice. The albedo and transmittance of ponded ice in the visible are mainly determined by the optical properties of the ice underlying the water layer used to model the pond. Sensitivity results indicate that the air volume or ice density has the largest impact on the simulated fluxes. Possible contamination from light-absorbing impurities, such as black carbon or ice algae, is also implemented in the model and is able to effectively reduce the albedo and transmittance in the visible spectrum to further improve the model-observation agreement. The agreement between the observed and modeled spectra validates the parameterization of the sea ice IOPs, and endorses COART as an accurate tool for radiation studies in the cryosphere.

Coupled Ocean-9 Atmosphere Radiative Transfer (COA↗

The Ocean Colour Climate Change Initiative: III. A Round-Robin Comparison on In-Water Bio-Optical Algorithms

Satellite-derived remote-sensing reflectance (Rrs) can be used for mapping biogeochemically relevant variables, such as the chlorophyll concentration and the Inherent Optical Properties (IOPs) of the water, at global scale for use in climate-change studies. Prior to generating such products, suitable algorithms have to be selected that are appropriate for the purpose. Algorithm selection needs to account for both qualitative and quantitative requirements. In this paper we develop an objective methodology designed to rank the quantitative performance of a suite of bio-optical models. The objective classification is applied using the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Using in situ Rrs as input to the models, the performance of eleven semianalytical models, as well as five empirical chlorophyll algorithms and an empirical diffuse attenuation coefficient algorithm, is ranked for spectrally-resolved IOPs, chlorophyll concentration and the diffuse attenuation coefficient at 489 nm. The sensitivity of the objective classification and the uncertainty in the ranking are tested using a Monte-Carlo approach (bootstrapping). Results indicate that the performance of the semi-analytical models varies depending on the product and wavelength of interest. For chlorophyll retrieval, empirical algorithms perform better than semi-analytical models, in general. The performance of these empirical models reflects either their immunity to scale errors or instrument noise in Rrs data, or simply that the data used for model parameterisation were not independent of NOMAD. Nonetheless, uncertainty in the classification suggests that the performance of some semi-analytical algorithms at retrieving chlorophyll is comparable with the empirical algorithms. For phytoplankton absorption at 443 nm, some semi-analytical models also perform with similar accuracy to an empirical model. We discuss the potential biases, limitations and uncertainty in the approach, as well as additional qualitative considerations for algorithm selection for climate-change studies. Our classification has the potential to be routinely implemented, such that the performance of emerging algorithms can be compared with existing algorithms as they become available. In the long-term, such an approach will further aid algorithm development for ocean-colour studies.

Phytoplankton↗

Assessment of space sensors for ocean pollution monitoring

Several passive and active microwave, as well as passive optical remote sensors, applicable to the monitoring of oil spills and waste discharges at sea, are considered. The discussed types of measurements relate to: (1) spatial distribution and properties of the pollutant, and (2) oceanic parameters needed to predict the movement of the pollutants and their impact upon land. The sensors, operating from satellite platforms at 700-900 km altitudes, are found to be useful in mapping the spread of oil in major oil spills and in addition, can be effective in producing wind and ocean parameters as inputs to oil trajectory and dispersion models. These capabilities can be used in countermeasures.

Alvarado, U. R.↗

Bio-Optical Measurements in Upwelling Ecosystems in Support of SIMBIOS

The upwelling region of the equatorial Pacific Ocean, which spans one quarter of the earth s circumference, strongly impacts global biogeochemistry. This upwelling system has significant implications for global CO2 fluxes (Tans et al., 1990; Takahashi et al., 1997; Feely et al., 1999), as well as primary and secondary production (Chavez and Barber, 1987; Chavez and Toggweiler, 1995; Chavez et al., 1996; Dugdale and Wilkerson, 1998; Chavez et al., 1999; Strutton and Chavez, 2000). In addition, the region represents a vast oceanic (case 1) region over which validation data for SeaWiFS are needed. This project consists of an optical mooring program and cruise-based measurements focused on measuring biological and chemical variability in the equatorial Pacific and obtaining validation data for SeaWiFS.

Chavez, Francisco P.↗

Variability in Ocean Color Associated with Phytoplankton and Terrigenous Matter: Time Series Measurements and Algorithm Development at the FRONT Site on the New England Continental Shelf

Fronts in the coastal ocean describe areas of strong horizontal gradients in both physical and biological properties associated with tidal mixing and freshwater estuarine output (e.g. Simpson, 1981 and O Donnell, 1993). Related gradients in optically important constituents mean that fronts can be observed from space as changes in ocean color as well as sea surface temperature (e.g., Dupouy et al., 1986). This research program is designed to determine which processes and optically important constituents must be considered to explain ocean color variations associated with coastal fronts on the New England continental shelf, in particular the National Ocean Partnership Program (NOPP) Front Resolving Observational Network with Telemetry (FRONT) site. This site is located at the mouth of Long Island sound and was selected after the analysis of 12 years of AVHRR data showed the region to be an area of strong frontal activity (Ullman and Cornillon, 1999). FRONT consists of a network of modem nodes that link bottom mounted Acoustic Doppler Current Profilers (ADCPs) and profiling arrays. At the center of the network is the Autonomous Vertically Profiling Plankton Observatory (AVPPO) (Thwaites et al. 1998). The AVPPO consists of buoyant sampling vehicle and a trawl-resistant bottom-mounted enclosure, which holds a winch, the vehicle (when not sampling), batteries, and controller. Three sampling systems are present on the vehicle, a video plankton recorder, a CTD with accessory sensors, and a suite of bio-optical sensors including Satlantic OCI-200 and OCR-200 spectral radiometers and a WetLabs ac-9 dual path absorption and attenuation meter. At preprogrammed times the vehicle is released, floats to the surface, and is then winched back into the enclosure with power and data connection maintained through the winch cable. Communication to shore is possible through a bottom cable and nearby surface telemetry buoy, equipped with a mobile modem, giving the capability for near-real time data transmission and interactive sampling control.

Morrison, John R.↗

The variation of radar cross section with wind

X-band (8910 megahertz) and C-band (4455 megahertz) measurements indicate that two domains exist in the variation of radar cross section with wind at incident angles far from the normal. The first domain for flow windspeeds is characterized by a rapid variation of radar cross section with wind and the second domain at higher windspeeds by an asymptotic approach to an upper limit (saturation). The transaction between the two domains occurs at a windspeed of approximately 10 knots. Recent Joint Ocean Surface Study I observations tend to confirm this observation and offer additional proof of the validity of a composite surface model which relates the radar cross section of the sea to the wave-height spectrum. This confirmation was obtained by comparing the radar cross section measured by the four-frequency radar system with the radar cross section calculated from the ocean wave-height spectrum that had been determined by the optical analysis of photographs taken at the same time. A possible explanation for the wind variation of the radar cross section of the open ocean also was evolved, based on radar measurements in a wave tank under various wind conditions and subsequent comparison with optically determined spectra.

Guinard, N. W.↗

Bio-Optical Properties of the Arabian Sea as Determined by In-Situ and SeaWifs Data

The overall objective of this work was to characterize optical and fluorescence properties in the euphotic zone during two British Ocean Flux Study (BOFS) Arabian Sea cruises. This was later expanded in 1995 to include three U.S. Joint Global Ocean Flux Study (JGOFS) Arabian Sea Cruises. The region was to be divided into one or more "bio-optical provinces", within each of which a single set of regression models was to be developed to relate the vertical distribution of irradiance attenuation and normalized fluorescence (SF and NF) to remote sensing reflectance and diffuse attenuation coefficient [K(490)]. The working hypothesis was that over relatively large spatial and temporal scales, the vertical profiles of bio-optical properties were predictable.

Trees, Charles C.↗

OCTS and SeaWiFS Bio-Optical Algorithm and Product Validation and Intercomparison in US Coastal Waters

The successful launch of the National Space Development Agency of Japan (NASDA) Ocean Color and Temperature Sensor (OCTS) in August 1996, and the launch of Orbital Science Corporation's (OSC) Sea-viewing Wide-Field-of-view Sensor (SeaWiFS) in August 1997 signaled the beginning of a new era for ocean color research and application. These data may be used to remotely evaluate 1) water quality, 2) transport of sediments and adhered pollutants, 3) primary production, upon which commercial shellfish and finfish populations depend for food, and 4) harmful algal blooms which pose a threat to public health and economies of affected areas. Several US government agencies have recently expressed interest in monitoring U.S. coastal waters using optical remote sensing. This renewed interest is broadly driven by 1) resource management concerns over the impact of coastward shifts in population and land use on the ecosystems of estuaries, wetlands, nearshore benthic environments and fisheries, 2) recognition of the need to understand short time scale global change due to urbanization of sensitive land-margin ecosystems, and 3) national security issues. Satellite ocean color sensors have the potential to furnish data at the appropriate time and space scales to evaluate and resolve these concerns and problems. In this draft technical memorandum, we outline our progress during the first year of our SIMBIOS project to evaluate ocean color bio-optical algorithms and products generated using OCTS and SeaWiFS data in coastal US waters.

Brown, Christopher W.↗

Seasonal variability of bio-optical and physical properties in the Sargasso Sea

The seasonal variability of bio-optical and physical properties within the upper ocean at a site in the Sargasso Sea has been observed in multivariable moored systems during a 9-month period. In addition, complementary meteorological data, sea surface height and sea surface temperature maps, and expendable bathythermograph and shipboard profile data have been utilized for interpretation. The observations during March are characteristic of late wintertime conditions of a deep isothermal layer, but with intervening periods of warming due to the advection of warm outbreak waters associated with Gulf Stream meanders. The mixed layer depth shoals from greater than 160 m to about 25 m in late March (spring transition). Phytoplankton blooms follow the mixed layer shoaling. A succession of phytoplankton populations occurs during this transitional interval. The mixed layer remains near 25 m for the summer and deepens in mid-September. A relatively intense subsurface maximum in chlorophyll develops at about 75 m following the spring transition. The maximum persists, but weakens in mid-summer.

Dickey, T.↗