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At least 91 records · Page 5

NASA Scatterometer Provides Global Ocean-Surface Wind Fields with More Structures than Numerical Weather Prediction

The major differences between monthly-mean ocean-surface wind fields derived from the observations of the National Aeronautics and Space Administration (NASA) Scatterometer (NSCAT) and produced by the operational numerical weather prediction (NWP) model of the European Center for Medium-Range Weather Forecasts are found in coastal and equatorial regions, where the sharp changes are smoothed over in NWP products.

scatterometer ocean surface wind weather predictio↗

Validating NASA's Airborne Multikilohertz Microlaser Altimeter (Microaltimeter) by Direct Comparison of Data Taken Over Ocean City, Maryland Against an Existing Digital Elevation Model

NASA's Airborne Multikilohertz Microlaser Altimeter (Microaltimeter) is a scanning, photon-counting laser altimeter, which uses a low energy (less than 10 microJuoles), high repetition rate (approximately 10 kHz) laser, transmitting at 532 nm. A 14 cm diameter telescope images the ground return onto a segmented anode photomultiplier, which provides up to 16 range returns for each fire. Multiple engineering flights were made during 2001 and 2002 over the Maryland and Virginia coastal area, all during daylight hours. Post-processing of the data to geolocate the laser footprint and determine the terrain height requires post- detection Poisson filtering techniques to extract the actual ground returns from the noise. Validation of the instrument's ability to produce accurate terrain heights will be accomplished by direct comparison of data taken over Ocean City, Maryland with a Digital Elevation Model (DEM) of the region produced at Ohio State University (OSU) from other laser altimeter and photographic sources. The techniques employed to produce terrain heights from the Microaltimeter ranges will be shown, along with some preliminary comparisons with the OSU DEM.

Abel, Peter↗

Salinity Measurements During the Gulf Stream Experiment

The salinity of the open ocean is important for understanding ocean circulation, for understanding energy exchange with the atmosphere and for improving models to predict weather and climate. Passive microwave sensors at L-band (1.4 GHz) operating from aircraft have demonstrated that salinity can be measured with sufficient accuracy (1 psu) to be scientifically meaningful in coastal waters. However, measuring salinity in the open ocean presents unresolved issues largely because of the much greater accuracy (approx. 0.1 psu) required to be scientifically viable. In the summer of 1999 a series of measurements called, The Gulf Stream Experiment, were conducted as part of research at the Goddard Space Flight Center to test the potential for passive microwave remote sensing of salinity in the open ocean. The measurements consisted of a compliment of airborne microwave instruments (radiometers and scatterometer) and ships and drifters for surface truth. The study area was a 200 km by 100 km rectangle about 250 km east of Delaware Bay between the continental shelf waters and north wall of the Gulf Stream. The primary passive instruments were the ESTAR radiometer (L-band, H-pol) and the SLFMR radiometer (L-band, V-pol). In addition, the compliment of instruments on the aircraft included a C-band radiometer (ACMR), an ocean wave scatterometer (ROWS) and an infrared radiometer. A GPS backscatter experiment was also part of the package. These instruments were mounted on the NASA P-3 Orion aircraft. Surface salinity measurements were provided by the RN Cape Henlopen and MN Oleander (thermosalinographs) plus salinity and temperature sensors on three surface drifters deployed from the RN Cape Henopen. The primary experiment period was August 26-September 2, 1999. During this period the salinity field within the study area consisted of a gradient on the order of 2-3 psu in the vicinity of the shelf break and a warm core ring with a gradient of 1-2 psu. Detailed maps were made with the airborne sensors on August 28 and 29 and on September 2 flights were made over the surface drifters to look for effects due to a change in surface roughness resulting from the passage of Hurricane Dennis. Preliminary results show a good agreement between the microwave measurements and ship measurements of salinity. The features of the brightness temperature maps correspond well with the features of the salinity field measured by the ship and drifters and a preliminary retrieval of salinity compares well with the ship data.

LeVine, D. M.↗

Radar imaging of ocean surface patterns

The paper presents some examples of imaging radar oceanographic observations and discusses physical phenomena on the surface that may cause the radar image. The different ocean scattering theories are briefly discussed, including the tangent plane model, the Bragg-Rice model, and the Rayleigh scattering model. All but one of the images presented were obtained with an L-band HH-polarized radar; they include deep-ocean swells, coastal swells, wave refractions, internal waves, ship wakes, abrupt transitions in open-ocean surface roughness, surface slicks, island wind shadowing, and currents. Analyses are shown to suggest that the primary source of the L-band imagery of ocean surface patterns is the variation of small-scale surface roughness and local tilt angle. It is also noted that surface irregularities behave as isotropic scatterers for a radar wavelength of 25 cm.

Brown, W. E., Jr.↗

Ocean tide models for satellite geodesy and Earth rotation

A theory is presented which predicts tides in turbulent, self-gravitating, and loading oceans possessing linearized bottom friction, realistic bathymetry, and continents (at coastal boundaries no-flow conditions are imposed). The theory is phrased in terms of spherical harmonics, which allows the tide equations to be reduced to linear matrix equations. This approach also allows an ocean-wide mass conservation constraint to be applied. Solutions were obtained for 32 long and short period luni-solar tidal constituents (and the pole tide), including the tidal velocities in addition to the tide height. Calibrating the intensity of bottom friction produces reasonable phase lags for all constituents; however, tidal amplitudes compare well with those from observation and other theories only for long-period constituents. In the most recent stage of grant research, traditional theory (Liouville equations) for determining the effects of angular momentum exchange on Earth's rotation were extended to encompass high-frequency excitations (such as short-period tides).

Dickman, Steven R.↗

Improving NOAA's NWLON Through Enhanced Data Inputs from NASA's Ocean Surface Topography

This report assesses the benefit of incorporating NASA's OSTM (Ocean Surface Topography Mission) altimeter data (C- and Ku-band) into NOAA's (National Oceanic and Atmospheric Administration) NWLON (National Water Level Observation Network) DSS (Decision Support System). This data will enhance the NWLON DSS by providing additional inforrnation because not all stations collect all meteorological parameters (sea-surface height, ocean tides, wave height, and wind speed over waves). OSTM will also provide data where NWLON stations are not present. OSTM will provide data on seasurface heights for determining sea-level rise and ocean circulation. Researchers and operational users currently use satellite altimeter data products with the GSFCOO NASA data model to obtain sea-surface height and ocean circulation inforrnation. Accurate and tirnely inforrnation concerning sea-level height, tide, and ocean currents is needed to irnprove coastal tidal predictions, tsunarni and storm surge warnings, and wetland restoration.

Guest, DeNeice C.↗

Algorithm Development and Validation of CDOM Properties for Estuarine and Continental Shelf Waters Along the Northeastern U.S. Coast

An extensive set of field measurements have been collected throughout the continental margin of the northeastern U.S. from 2004 to 2011 to develop and validate ocean color satellite algorithms for the retrieval of the absorption coefficient of chromophoric dissolved organic matter (aCDOM) and CDOM spectral slopes for the 275:295 nm and 300:600 nm spectral range (S275:295 and S300:600). Remote sensing reflectance (Rrs) measurements computed from in-water radiometry profiles along with aCDOM() data are applied to develop several types of algorithms for the SeaWiFS and MODIS-Aqua ocean color satellite sensors, which involve least squares linear regression of aCDOM() with (1) Rrs band ratios, (2) quasi-analytical algorithm-based (QAA based) products of total absorption coefficients, (3) multiple Rrs bands within a multiple linear regression (MLR) analysis, and (4) diffuse attenuation coefficient (Kd). The relative error (mean absolute percent difference; MAPD) for the MLR retrievals of aCDOM(275), aCDOM(355), aCDOM(380), aCDOM(412) and aCDOM(443) for our study region range from 20.4-23.9 for MODIS-Aqua and 27.3-30 for SeaWiFS. Because of the narrower range of CDOM spectral slope values, the MAPD for the MLR S275:295 and QAA-based S300:600 algorithms are much lower ranging from 9.9 and 8.3 for SeaWiFS, respectively, and 8.7 and 6.3 for MODIS, respectively. Seasonal and spatial MODIS-Aqua and SeaWiFS distributions of aCDOM, S275:295 and S300:600 processed with these algorithms are consistent with field measurements and the processes that impact CDOM levels along the continental shelf of the northeastern U.S. Several satellite data processing factors correlate with higher uncertainty in satellite retrievals of aCDOM, S275:295 and S300:600 within the coastal ocean, including solar zenith angle, sensor viewing angle, and atmospheric products applied for atmospheric corrections. Algorithms that include ultraviolet Rrs bands provide a better fit to field measurements than algorithms without the ultraviolet Rrs bands. This suggests that satellite sensors with ultraviolet capability could provide better retrievals of CDOM. Because of the strong correlations between CDOM parameters and DOM constituents in the coastal ocean, satellite observations of CDOM parameters can be applied to study the distributions, sources and sinks of DOM, which are relevant for understanding the carbon cycle, modeling the Earth system, and to discern how the Earth is changing.

CDOM Properties↗

The Sensitivity of the Equatorial Pacific ODZ to Particulate Organic Matter Remineralization in A Climate Model Under Pre-Industrial Conditions

Marine oxygen plays a fundamental role in regulating the transfer of organic carbon and nutrients to their dissolved inorganic forms, serving as the terminal electron acceptor for heterotrophic respiration. Oxygen can become limiting to these processes in coastal and open-ocean oxygen deficient zones (ODZs). The maintenance of ODZs depends on the balance between physical processes such as ventilation and biogeochemical processes such as remineralization. These two processes act in opposing directions on ODZs, with ventilation responsible for transporting oxygen from the surface, where it is near saturation with the partial pressure of O2 in the atmosphere, to deeper oxygen-depleted layers, and remineralization acting to consume oxygen through biogeochemical processes such as microbial degradation throughout the water column. Remineralization is represented in all CMIP6 models, but the actual parameterizations, as well as their magnitude, are widely varying. In this study, we examine the sensitivity to remineralization of the equatorial Pacific ODZ O2 ol/kg) in a model; the NASA GISS Ocean Biogeochemical Model (NOBM-G) embedded in the NASA-GISS coupled atmosphere-ocean model. We find that increasing the remineralization rate shoals the ODZ onset depth (i.e. the regionally averaged upper bound of the ODZ), and decreases ODZ volume and regional-averaged thickness. Changes in biological consumption and vertical convergence of oxygen are identified as the primary contributors to changes in ODZ onset depth. ODZ thickness is mainly influenced by the shoaling of the bottom boundary of the ODZ, which decreases with maximum remineralization rate due to decreasing oxygen consumption and increasing horizontal oxygen convergence in deep waters. On the other hand, vertically-averaged ODZ area has a more complex, non-monotonic relationship with maximum remineralization rate. While these findings suggest an important role for remineralization in determining the shape of the ODZ in our model, the relative importance of remineralization vs. other physical parameterizations remains to be established. While our results reflect the structure of our ocean biogeochemical model, the relationship of remineralization to ODZ characteristics in other models should be examined to better inform model inter-comparisons.

Oxygen-deficient zone↗

Joint Projections of US East Coast Sea Level and Storm Surge

Future coastal flood risk will be strongly influenced by sea-level rise (SLR) and changes in the frequency and intensity of tropical cyclones. These two factors are generally considered independently. Here, we assess twenty-first century changes in the coastal hazard for the US East Coast using a flood index (FI) that accounts for changes in flood duration and magnitude driven by SLR and changes in power dissipation index (PDI, an integrated measure of tropical cyclone intensity, frequency and duration). Sea-level rise and PDI are derived from representative concentration pathway (RCP) simulations of 15 atmosphere- ocean general circulation models (AOGCMs). By 2080-2099, projected changes in the FI relative to 1986-2005 are substantial and positively skewed: a 10th-90th percentile range 4-75 times higher for RCP 2.6 and 35-350 times higher for RCP 8.5. High-end Fl projections are driven by three AOGCMs that project the largest increases in SLR, PDI and upper ocean temperatures. Changes in PDI are particularly influential if their intra-model correlation with SLR is included, increasing the RCP 8.5 90th percentile FI by a further 25%. Sea-level rise from other, possibly correlated, climate processes (for example, ice sheet and glacier mass changes) will further increase coastal flood risk and should be accounted for in comprehensive assessments.

cyclones↗

Simulated laser fluorosensor signals from subsurface chlorophyll distributions

A semianalytic Monte Carlo model has been used to simulate laser fluorosensor signals returned from subsurface distributions of chlorophyll. This study assumes the only constituent of the ocean medium is the common coastal zone dinoflagellate Prorocentrum minimum. The concentration is represented by Gaussian distributions in which the location of the distribution maximum and the standard deviation are variable. Most of the qualitative features observed in the fluorescence signal for total chlorophyll concentrations up to 1.0 microg/liter can be accounted for with a simple analytic solution assuming a rectangular chlorophyll distribution function.

Venable, D. D.↗

Towards Improved MODIS Aerosol Retrieval over the US East Coast Region: Re-examining the Aerosol Model and Surface Assumptions

The MODerate resolution Imaging Spectrometer (MODIS) aboard the Terra and recently the Aqua platform, produces a set of aerosol products over both ocean and land regions. Previous validation efforts have shown that from a global perspective, aerosol optical depth (AOD) is successfully retrieved from MODIS. Even over coastal regions, the over- land and over-ocean retrievals are consistent with each other, and well matched with ground-based sunphotometer measurements (such as AERONET). However, the East Coast of the United States is one region where there is consistently a discrepancy between land and ocean retrievals. Over the ocean, MODIS AODs are consistent with coastal sunphotometer measurements, but over land, AODs are consistently over- estimated. In this study we use field data from the Chesapeake Lighthouse and Aircraft Measurements for Satellites experiment (CLAMS), (held during summer 2001) to determine the aerosol properties at a number of sites. Using the 6-S radiative transfer package, we compute simulated satellite radiances and compare them with observed MODIS radiances. We believe that the AOD over-estimation is not likely due to an incorrect choice of the urban/industrial aerosol models. Using 6-S to do an atmospheric correction for a very low AOD case, we show rather, that the discrepancies are likely a result of incorrect assumptions about the surface reflectance properties. Understanding and improving MODIS retrievals over the East Coast will not only improve the global quality of MODIS, but also would enable the use of MODIS as a tool for monitoring regional aerosol events.

Levy, R. C.↗

Annual and interannual variations of phytoplankton pigment concentration and upwelling along the Pacific equator

The following variables along the Pacific equator from 145 deg E to 95 deg W were employed: surface layer phytoplankton pigment concentrations derived from Nimbus 7 coastal zone color scanner (CZCS) measurements of ocean color radiances; vertical velocities simulated at the 90-m bottom of the euphotic layer from a wind-driven ocean general circulation model; and nitrate concentrations estimated from model-simulated temperature. The upward flux of nitrate into the euphotic layer was calculated from the simulated vertical motion and nitrate concentration. The CZCS-derived phytoplankton pigment concentration was uniform from 175 deg to 95 deg W. Longitudinal profiles of upwelling, phytoplankton biomass, and 90-m nitrate flux were of different shapes. The small annual cycles of the phytoplankton pigment and nitrate flux were in phase: increased phytoplankton biomass was associated with increased upward nitrate flux, but the phase was not consistent with the annual cycles of the easterly wind or of the upwelling intensity. Variation of phytoplankton pigment concentration was greater during El Nino than during the annual cycle. The substantially reduced phytoplankton pigment concentration observed during El Nino was associated with smaller upward nitrate flux. Phytoplankton biomass during non-El Nino conditions was not related to nitrate flux into the euphotic layer.

Halpern, David↗

Seagrass Health Modeling and Prediction with NASA Science Data

Previous research has demonstrated that MODIS data products can be used as inputs into the seagrass productivity model developed by Fong and Harwell (1994). To further explore this use to predict seagrass productivity, Moderate Resolution Imaging Spectroradiometer (MODIS) custom data products, including Sea Surface Temperature, Light Attenuation, and Chlorophyll-a have been created for use as model parameter inputs. Coastal researchers can use these MODIS data products and model results in conjunction with historical and daily assessment of seagrass conditions to assess variables that affect the productivity of the seagrass beds. Current monitoring practices involve manual data collection (typically on a quarterly basis) and the data is often insufficient for evaluating the dynamic events that influence seagrass beds. As part of a NASA-funded research grant, the University of Mississippi, is working with researchers at NASA and Radiance Technologies to develop methods to deliver MODIS derived model output for the northern Gulf of Mexico (GOM) to coastal and environmental managers. The result of the project will be a data portal that provides access to MODIS data products and model results from the past 5 years, that includes an automated process to incorporate new data as it becomes available. All model parameters and final output will be available through the use National Oceanic and Atmospheric Administration?s (NOAA) Environmental Research Divisions Data Access Program (ERDDAP) tools as well as viewable using Thematic Realtime Environmental Distributed Data Services (THREDDS) and the Integrated Data Viewer (IDV). These tools provide the ability to create raster-based time sequences of model output and parameters as well as create graphs of model parameters versus time. This tool will provide researchers and coastal managers the ability to analyze the model inputs so that the factors influencing a change in seagrass productivity can be determined over time.

Robinson, Harold D.↗

The Madden-Julian oscillation and the angular momentum balance in a barotropic ocean model

The oceanic response to the Madden and Julian (1971, 1972) oscillation (MJO) wind stresses are studied with special attention given to the nature of the related angular momentum exchanges between the ocean and the solid earth for idealized 40- and 50-day fluctuations of Pacific winds. The character of these exchanges is illustrated with the use of numerical solutions of a shallow water ocean model, which were found for a constant depth basin centered on the equator and extending over 140 deg in longitude. Solutions also suggest that even small (0.5-1.5-cm) coastal sea level fluctuations can cause variations in the length of day comparable to observed values in the 40- to 50-day band.

Ponte, Rui M.↗

The interaction of light with phytoplankton in the marine environment

In many regions of the ocean, the phytoplankton population dominates both the attenuation and scattering of light. In other regions, non-phytoplankton contributions to the absorption and scattering may change the remote sensing reflectance and thus affect the ability to interpret remotely sensed ocean color. Hence, variations in the composition of both the phytoplankton population and of the non-phytoplankton material in the water can affect the optical properties of the sea. The effects of these contributions to the remote sensing reflectance and the submarine light field are modeled using scattering and absorption measurements of phytoplankton cultures obtained at the Friday Harbor Laboratory of the University of Washington. These measurements are used to develop regional chlorophyll algorithms specific to the summer waters of Puget Sound for the Coastal Zone Color Scanner, Thematic Mapper and future Ocean Color Imager, and their accuracies are compared for high chlorophyll waters with little or no Gelbstoff, but with variable detrital and suspended material.

Carder, Kendall L.↗

A Chlorophyll-a Algorithm for Landsat-8 Based on Mixture Density Networks

Retrieval of aquatic biogeochemical variables, such as the near-surface concentration of chlorophyll-a (Chla) in inland and coastal waters via remote observations, has long been regarded as a challenging task. This manuscript applies Mixture Density Networks (MDN) that use the visible spectral bands available by the Operational Land Imager (OLI) aboard Landsat-8 to estimate Chla. We utilize a database of co-located in situ radiometric and Chla measurements (N = 4,354), referred to as Type A data, to train and test an MDN model (MDN(A)). This algorithm’s performance, having been proven for other satellite missions, is further evaluated against other widely used machine learning models (e.g., support vector machines), as well as other domain-specific solutions (OC3), and shown to offer significant advancements in the field. Our performance assessment using a held-out test data set suggests that a 49% (median) accuracy with near-zero bias can be achieved via the MDN(A) model, offering improvements of 20 to 100% in retrievals with respect to other models. The sensitivity of the MDN(A) model and benchmarking methods to uncertainties from atmospheric correction (AC) methods, is further quantified through a semi-global matchup dataset (N = 3,337), referred to as Type B data. To tackle the increased uncertainties, alternative MDN models (MDN(B)) are developed through various features of the Type B data (e.g., Rayleigh-corrected reflectance spectra ρ(s)). Using held-out data, along with spatial and temporal analyses, we demonstrate that these alternative models show promise in enhancing the retrieval accuracy adversely influenced by the AC process. Results lend support for the adoption of MDN(B) models for regional and potentially global processing of OLI imagery, until a more robust AC method is developed. Index Terms—Chlorophyll-a, coastal water, inland water, Landsat-8, machine learning, ocean color, aquatic remote sensing.

Brandon Smith↗

A Hyperspectral Inversion Framework for Estimating Absorbing Inherent Optical Properties and Biogeochemical Parameters in Inland and Coastal Waters

The simultaneous remote estimation of biogeochemical parameters (BPs) and inherent optical properties (IOPs) from hyperspectral satellite imagery of globally distributed optically distinct inland and coastal waters is a complex, unsolved, non-unique inverse problem. To tackle this problem, we leverage a machine-learning model termed Mixture Density Networks (MDNs). MDNs outperform operational algorithms by calculating the covariance between the simultaneously estimated products. We train the MDNs on a large ( N = 8237) dataset of co-aligned, in situ measured, hyperspectral remote sensing reflectance (R rs ), BPs, and absorbing IOPs from globally representative optically distinct inland and coastal waters. The estimated IOPs include absorption due to phytoplankton (a ph ), chromophoric dissolved organic matter (a cdom ), and non-algal particles (a nap ). The estimated BPs include chlorophyll-a, total suspended solids, and phycocyanin (PC). MDNs dramatically reduce uncertainty in the retrievals, relative to operational algorithms, when using a 50/50 dataset split, where the MDNs are trained on a randomly selected half of the in situ dataset and validated on the other half. Our model is shown to have higher, or equivalent, generalization performance than the calculated operational algorithms available for all BPs and IOPs (except PC) via a leave-one-out cross-validation assessment. The MDNs are sensitive to uncertainties in the hyperspectral satellite R rs , resulting from instrument noise and atmospheric correction; there is a difference of ~37.4–62.8% (using median symmetric accuracy) between the MDNs’ estimates derived from co-located satellite-derived R rs and in situ R rs . Of the IOPs, a cdom and a nap are less sensitive to uncertainties in hyperspectral satellite imagery relative to a ph , with remote estimates of a ph exhibiting incorrect spectral shape and magnitude relative to in situ measured IOPs. Despite the uncertainties in satellite derived R rs , the spatial distributions of BPs and IOPs in MDN-derived product maps of Lake Erie and the Curonian Lagoon, based on imagery taken with the Hyperspectral Imager for the Coastal Ocean (HICO) and PRecursore Iper-Spettrale della Missione Applicativa (PRISMA), are confirmed via co-aligned in situ measurements and agree with the literature’s understanding of these well-studied regions. The consistency and accuracy of the model on HICO and PRISMA imagery, despite radiometric uncertainties, demonstrate its applicability to future hyperspectral missions, such as the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, where the simultaneous estimation model will serve as a key part of phytoplankton community composition analysis.

Ryan E. O'Shea↗

Remote sensing of coastal fronts and their effects on oil dispersion

The use of remote sensing techniques to determine the properties of coastal and estuarine fronts, which represent regions of discontinuities and high gradients in ocean physical parameters such as velocity and density, and to assess the influence of such fronts on oil pollutants is discussed. Results of an aircraft and boat verification study of an oil drift and spread model in Delaware Bay are indicated which illustrate the tendency of oil slicks to be attracted to frontal regions, where a denser fluid underlies a lighter fluid giving rise to an inclined interface with convergence zones. Landsat imagery of the bay acquired in order to incorporate frontal information into the interactive computer model is then presented which allows the locations of coastal fronts to be charted throughout a tidal cycle. It is noted that satellite observations of flood-associated fronts on the New Jersey side of the bay and ebb-associated fronts on the Delaware side agree with boat measurements and model predictions, and that the remote tracking of fronts by aircraft and satellites will aid in oil slick clean-up operations.

Klemas, V.↗