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At least 145 records · Page 8

The EOS CERES Global Cloud Mask

To detect long-term climate trends, it is essential to produce long-term and consistent data sets from a variety of different satellite platforms. With current global cloud climatology data sets, such as the International Satellite Cloud Climatology Experiment (ISCCP) or CLAVR (Clouds from Advanced Very High Resolution Radiometer), one of the first processing steps is to determine whether an imager pixel is obstructed between the satellite and the surface, i.e., determine a cloud 'mask.' A cloud mask is essential to studies monitoring changes over ocean, land, or snow-covered surfaces. As part of the Earth Observing System (EOS) program, a series of platforms will be flown beginning in 1997 with the Tropical Rainfall Measurement Mission (TRMM) and subsequently the EOS-AM and EOS-PM platforms in following years. The cloud imager on TRMM is the Visible/Infrared Sensor (VIRS), while the Moderate Resolution Imaging Spectroradiometer (MODIS) is the imager on the EOS platforms. To be useful for long term studies, a cloud masking algorithm should produce consistent results between existing (AVHRR) data, and future VIRS and MODIS data. The present work outlines both existing and proposed approaches to detecting cloud using multispectral narrowband radiance data. Clouds generally are characterized by higher albedos and lower temperatures than the underlying surface. However, there are numerous conditions when this characterization is inappropriate, most notably over snow and ice of the cloud types, cirrus, stratocumulus and cumulus are the most difficult to detect. Other problems arise when analyzing data from sun-glint areas over oceans or lakes over deserts or over regions containing numerous fires and smoke. The cloud mask effort builds upon operational experience of several groups that will now be discussed.

Berendes, T. A.↗

A Look at a Day of Data from The TOPEX/POSEIDON GPS Receiver

Launched on 10 August, 1992, the Topex/Poseidon satellite is a joint project of NASA and the French space agency CNES. The purpose of this Earth orbiting altimetric satellite (for brevity, referred to as Topex) is to enable monitoring of the ocean topography to higher levels of accuracy than previously achieved. Essential to obtaining this greater level of accuracy is the use of improved navigational systems which can yield position estimates for Topex good to a few centimeters. One of the navigational systems utilized by Topex is the Global Positioning System (GPS) -- a network of navigational beacons that has become widely used in many areas beside spacecraft navigation...

Jee, J. Rodney↗

A Look at a Day of Data from the Topex/Poseidon GPS Receiver

Launched on August 10, 1992, the Topex/Poseidon satellite is a joint project of NASA and the French space agency CNES. The pupose of this Earth orbiting altimetric satellite (for brevity, referred to as Topex) is to enable monitoring of the ocean topography to higher levels of accuracy than previously achieved.

robust regression spline graphics↗

Sunglint-aided Methane Retrieval: Using Sentinel-2 to Quantify Offshore Oil and Gas Emissions

The extraction, production, and transportation of oil and gas via activities such as intentional venting and fugitive emissions are leading contributors to anthropogenic methane emissions. Offshore operations comprise a significant percentage of all oil and gas operations, yet emission monitoring over the ocean is insufficient. Due to low surface reflectance over the ocean, remote sensing measurements offshore are limited. Therefore offshore contributions to the overall global methane budget are unknown. Regulators such as the Bureau of Ocean and Energy Management (BOEM) and the Bureau of Safety and Environmental Enforcement (BSEE) are unable to validate operator-reported methane emission estimates. The NASA DEVELOP Program partnered with BOEM, BSEE, and SkyTruth to identify potential offshore methane sources in the Gulf of Mexico. Drawing upon existing retrieval methods to detect and quantify onshore methane emissions (Varon et al., 2021), we selected sunglint scenes to detect methane plumes over the ocean in Sentinel-2 imagery. We detected two methane plumes at the Constitution complex in the Gulf of Mexico and off the coast of Pointe-Noire, Congo. If expanded, these methods could serve a vital role in validating operator reporting and quantifying climate impacts of offshore oil and gas operations - complementing those of next generation satellites.

Katherine Howell↗

Zarr stores in NASA's EOSDIS

Data hosted by the National Aeronautics and Space Administration (NASA) are expected to increase to over 600 PB by the end of the decade (see Figure 1). This rapid increase is, in part, driven by the launch of new, high-data-volume Earth observing missions, such as the NASA-Indian Space Research Organisation (ISRO) Synthetic Aperture Radar (NISAR), Surface Water and Ocean Topography (SWOT), Tropospheric Emissions: Monitoring of Pollution (TEMPO) and Plankton, Aerosol, Cloud ocean Ecosystem (PACE) missions.

Owen Littlejohns↗

Mobile Device Application for Monitoring Cyanobacteria Harmful Algal Blooms Using Sentinel-3 Satellite Ocean and Land Colour Instruments

Cyanobacterial harmful algal blooms (cyanoHAB) cause human and ecological health problems in lakes worldwide. The timely distribution of satellite-derived cyanoHAB data is necessary for adaptive water quality management and for targeted deployment of water quality monitoring resources. Software platforms that permit timely, useful, and cost-effective delivery of information from satellites are required to help managers respond to cyanoHABs. The Cyanobacteria Assessment Network (CyAN) mobile device application (app) uses data from the European Space Agency Copernicus Sentinel-3 satellite Ocean and Land Colour Instrument (OLCI) in near real-time to make initial water quality assessments and quickly alert managers to potential problems and emerging threats related to cyanobacteria. App functionality and satellite data were validated with 25 state health advisories issued in 2017. The CyAN app provides water quality managers with a user-friendly platform that reduces the complexities associated with accessing satellite data to allow fast, efficient, initial assessments across lakes.

Harmful Algal Bloom↗

Continuous Monitoring of the Jason-l and TOPEX/POSEIDON Ocean Altimetry Missions from Dedicated Calibration Sites

We present calibration results from Jason-1 and TOPEX/POSEIDON overflights of the three dedicated verification sites: 1) a California offshore oil platform (Harvest); 2) the Mediterranean island of Corsica (Cape Senetosa), and 3) the Bass Strait off the coast of Tasmania. The high-accuracy of the Jason-1 measurement system is evident in the results from the dedicated calibration experiments. These experiments do indicate, however, that the Jason-1 sea-surface-height (SSH) measurements are biased high by approximately 12-15 cm. We discuss the implications of geographically correlated errors on the determination of the SSH bias.

satellite altimerty↗

Earth physics, overview

Satellite applications in earth and ocean dynamic studies are considered for: earthquake hazard assessment and alleviation; prediction of general ocean circulation, surface currents, and heat transport; monitoring of transient phenomena of the ocean surface, such as sea state and wave conditions, wind-surface interactions and storm searches; and refinement of the global geoid, the gravity and magnetic fields of the earth.

Vonbun, F. O.↗

A Range Compensating Feed Motion Concept for Spaceborne Radar

Tropical cyclones can cause major loss of both life and property, so that improvements in forecasting motion, intensity, and rainfall are needed. Such forecasting requires accurate measurements of the current state of the cyclone. Ground-based Doppler radars have long been used as an effective means of monitoring severe precipitating storms. Because of the oceanic nature of tropical cyclones, remote monitoring from space is desirable. Recently, the Precipitation Radar (PR) [1] aboard the Tropical Rainfall Measuring Mission (TRMM) [2] satellite has demonstrated an unprecedented capacity for 3-D imaging of precipitating storms. Nonetheless, due to the relatively long TRMM return cycle (less than once per day) the value of PR data has primarily been limited to the understanding of climatological properties of tropical cyclones [3]. The return cycle can be substantially reduced by sensing from a geostationary platform.

reflector antennas↗

Discriminating Phytoplankton Functional Types (PFTs) in the Coastal Ocean Using the Inversion Algorithm Phydotax and Airborne Imaging Spectrometer Data

There is a need in the Biological Oceanography community to discriminate among phytoplankton groups within the bulk chlorophyll pool to understand energy flow through ecosystems, to track the fate of carbon in the ocean, and to detect and monitor-for harmful algal blooms (HABs). The ocean color community has responded to this demand with the development of phytoplankton functional type (PFT) discrimination algorithms. These PFT algorithms fall into one of three categories depending on the science application: size-based, biogeochemical function, and taxonomy. The new PFT algorithm Phytoplankton Detection with Optics (PHYDOTax) is an inversion algorithm that discriminates taxon-specific biomass to differentiate among six taxa found in the California Current System: diatoms, dinoflagellates, haptophytes, chlorophytes, cryptophytes, and cyanophytes. PHYDOTax was developed and validated in Monterey Bay, CA for the high resolution imaging spectrometer, Spectroscopic Aerial Mapping System with On-board Navigation (SAMSON - 3.5 nm resolution). PHYDOTax exploits the high spectral resolution of an imaging spectrometer and the improved spatial resolution that airborne data provides for coastal areas. The objective of this study was to apply PHYDOTax to a relatively lower resolution imaging spectrometer to test the algorithm's sensitivity to atmospheric correction, to evaluate capability with other sensors, and to determine if down-sampling spectral resolution would degrade its ability to discriminate among phytoplankton taxa. This study is a part of the larger Hyperspectral Infrared Imager (HyspIRI) airborne simulation campaign which is collecting Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery aboard NASA's ER-2 aircraft during three seasons in each of two years over terrestrial and marine targets in California. Our aquatic component seeks to develop and test algorithms to retrieve water quality properties (e.g. HABs and river plumes) in both marine and in-land water bodies. Results presented are from the 10 April 2013 overflight of the Monterey Bay region and focus primarily on the first objective - sensitivity to atmospheric correction. On-going and future work will continue to evaluate if PHYDOTax can be applied to historical (SeaWiFS and MERIS), existing (MODIS, VIIRS, and HICO), and future (PACE, GEO-CAPE, and HyspIRI) satellite sensors. Demonstration of cross-platform continuity may aid in calibration and validation efforts of these sensors.

Biological Oceanography↗

Solutions Network Formulation Report. The Potential Contribution of the Ocean Surface Topography Mission to the General NOAA Oil Monitoring Environment

Data collected by the OSTM could be used to provide a solution for the GNOME DST. GNOME, developed by NOAA?s Office of Response and Restoration Hazardous Materials Response Division, geospatially models oil spill trajectories using wind, current, river flow, and tidal data. Data collected by the OSTM would supply information about ocean currents and wind speeds. This Candidate Solution is in alignment with the Coastal Management, Water Management, Disaster Management, Public Health, Ecological Forecasting, and Homeland Security National Applications and will benefit society by improving the capabilities of emergency responders who evaluate an oil spill?s probable threat.

Hilbert, Kent↗

Global Ocean Studies from ICESat-2 Mission

The primary purpose of ICESat-2 mission is to monitor changes in the cryosphere. Fortunately, additional, and unrealized information from the penetration of laser light below ocean surface offers a new and exciting opportunity to study the ocean biology globally. The objective of this study is to provide the global ocean subsurface results (e.g., depolarization ratio and particulate backscattering coefficient) from ATLAS/ICESat-2 lidar measurements. The seasonal maps of ATLAS retrieved subsurface results exhibit all the major ocean plankton features anticipated from the earlier passive ocean color and CALIOP/CALIPSO lidar measurements. The ICESat-2 ATLAS lidar can continue to monitor global ocean phytoplankton properties after CALIOP/CALIPSO mission. Moreover, the ICESat-2 ocean subsurface results provide unique information to augment existing ocean color measurements by adding nighttime observations and the depth dimension with high horizontal and vertical resolutions.

ICESat2↗

Wavelet Analysis of SAR Images for Coastal Monitoring

The mapping of mesoscale ocean features in the coastal zone is a major potential application for satellite data. The evolution of mesoscale features such as oil slicks, fronts, eddies, and ice edge can be tracked by the wavelet analysis using satellite data from repeating paths. The wavelet transform has been applied to satellite images, such as those from Synthetic Aperture Radar (SAR), Advanced Very High-Resolution Radiometer (AVHRR), and ocean color sensor for feature extraction. In this paper, algorithms and techniques for automated detection and tracking of mesoscale features from satellite SAR imagery employing wavelet analysis have been developed. Case studies on two major coastal oil spills have been investigated using wavelet analysis for tracking along the coast of Uruguay (February 1997), and near Point Barrow, Alaska (November 1997). Comparison of SAR images with SeaWiFS (Sea-viewing Wide Field-of-view Sensor) data for coccolithophore bloom in the East Bering Sea during the fall of 1997 shows a good match on bloom boundary. This paper demonstrates that this technique is a useful and promising tool for monitoring of coastal waters.

Liu, Antony K.↗

Optical Characterisation of Suspended Particles in the Mackenzie River Plume (Canadian Arctic Ocean) and Implications for Ocean Colour Remote Sensing

Climate change significantly impacts Arctic shelf regions in terms of air temperature, ultraviolet radiation, melting of sea ice, precipitation, thawing of permafrost and coastal erosion. Direct consequences have been observed on the increasing Arctic river flow and a large amount of organic carbon sequestered in soils at high latitudes since the last glacial maximum can be expected to be delivered to the Arctic Ocean during the coming decade. Monitoring the fluxes and fate of this terrigenous organic carbon is problematic in such sparsely populated regions unless remote sensing techniques can be developed and proved to be operational. The main objective of this study is to develop an ocean colour algorithm to operationally monitor dynamics of suspended particulate matter (SPM) on the Mackenzie River continental shelf (Canadian Arctic Ocean) using satellite imagery. The water optical properties are documented across the study area and related to concentrations of SPM and particulate organic carbon (POC). Robust SPM and POC : SPM proxies are identified, such as the light backscattering and attenuation coefficients, and relationships are established between these optical and biogeochemical parameters. Following a semi-analytical approach, a regional SPM quantification relationship is obtained for the inversion of the water reflectance signal into SPM concentration. This relationship is reproduced based on independent field optical measurements. It is successfully applied to a selection of MODIS satellite data which allow estimating fluxes at the river mouth and monitoring the extension and dynamics of the Mackenzie River surface plume in 2009, 2010 and 2011. Good agreement is obtained with field observations representative of the whole water column in the river delta zone where terrigenous SPM is mainly constrained (out of short periods of maximum river outflow). Most of the seaward export of SPM is observed to occur within the west side of the river mouth. Future work will require the validation of the developed SPM regional algorithm based on match-ups with field measurements, then the routine application to ocean colour satellite data in order to better estimate the fluxes and fate of SPM and POC delivered by the Mackenzie River to the Arctic Ocean.

Mackenzie River plume↗

Predictability of Ocean Heat Content From Electrical Conductance

Ocean heat content (OHC) is a key climate variable that needs to be monitored to know how Earth's energy imbalance is changing, yet observing OHC remains a challenge. The present study examines whether a depth integral of the ocean's electrical conductivity (“conductance”), which may be inferred from both in situ methods and satellite magnetometers over the global ocean, could help monitor OHC. The ocean's electrical conductivity locally depends on temperature, salinity, and pressure, but it is not as well known how the conductance depends on OHC and ocean salt content. By examining the output of an ocean state estimate shown to agree well with observations that have not been assimilated, this study evaluates the fundamental limitations of using perfectly known ocean conductance to predict OHC, rather than the challenges associated with accounting for observational error. It is found that the ocean's conductance and OHC fields are nonlinearly related but nevertheless highly correlated. A statistical framework tends to predict OHC more accurately than ocean salt content from ocean conductance in regions where conductivity is more sensitive to salinity than temperature. The annually (bidecadally) averaged OHC can be predicted from a combination of conductance and depth‐averaged conductivity ocean fields to within nearly 0.1% (1%) error globally and even more accurately in many poorly observed (e.g., ice‐covered) regions. Practical application of this statistical framework to monitor OHC requires examination of the effect of uncertainties in the observed bathymetry and ocean conductance, which vary with application.

Trossman, D. S.↗

Waterway Ice Thickness Measurements

The ship on the opposite page is a U. S. Steel Corporation tanker cruising through the ice-covered waters of the Great Lakes in the dead of winter. The ship's crew is able to navigate safely by plotting courses through open water or thin ice, a technique made possible by a multi-agency technology demonstration program in which NASA is a leading participant. Traditionally, the Great Lakes-St. Lawrence Seaway System is closed to shipping for more than three months of winter season because of ice blockage, particularly fluctuations in the thickness and location of ice cover due to storms, wind, currents and variable temperatures. Shippers have long sought a system of navigation that would allow year-round operation on the Lakes and produce enormous economic and fuel conservation benefits. Interrupted operations require that industrial firms stockpile materials to carry them through the impassable months, which is costly. Alternatively, they must haul cargos by more expensive overland transportation. Studies estimate the economic benefits of year-round Great Lakes shipping in the hundreds of millions of dollars annually and fuel consumption savings in the tens of millions of gallons. Under Project Icewarn, NASA, the U.S. Coast Guard and the National Oceanic Atmospheric Administration collaborated in development and demonstration of a system that permits safe year-round operations. It employs airborne radars, satellite communications relay and facsimile transmission to provide shippers and ships' masters up-to-date ice charts. Lewis Research Center contributed an accurate methods of measuring ice thickness by means of a special "short-pulse" type of radar. In a three-year demonstration program, Coast Guard aircraft equipped with Side-Looking Airborne Radar (SLAR) flew over the Great Lakes three or four times a week. The SLAR, which can penetrate clouds, provided large area readings of the type and distribution of ice cover. The information was supplemented by short-pulse radar measurements of ice thickness. The radar data was relayed by a NOAA satellite to a ground station where NOAA analyzed it and created picture maps, such as the one shown at lower left, showing where icebreakers can cut paths easily or where shipping can move through thin ice without the aid of icebreakers. The ice charts were then relayed directly to the wheelhouses of ships operating on the Lakes. Following up the success of the Great Lakes program, the icewarn team applied its system in another demonstration, this one a similarly successful application designed to aid Arctic coast shipping along the Alaskan North Slope. Further improvement of the ice-monitoring system is planned. Although aircraft-mounted radar is effective, satellites could provide more frequent data. After the launch this year of Seasat, an ocean-monitoring satellite, NASA will conduct tests to determine the ice-mapping capability and accuracy of satellite radar images.

Source record↗

Estimates of the geostrophic stream function in the western North Pacific from XBT surveys

Bernstein and White (1981) have argued that the 300 m temperature field in the western North Pacific reflects the 100/1000 dbar geostrophic stream function of the upper ocean where 100/1000 dbar implies the 100 dbar surface relative to the 1000 dbar surface. The correlation between upper ocean dynamic height and temperature in this region provides the basis for their argument. The involved relationship suggests that it may be possible to monitor the relative upper ocean geostrophic transport, as well as energy relations and heat fluxes with expendable bathythermograph (XBT) surveys. Certain discrepancies between data from different sources are felt to result from problems with the XBT observations. The present investigation is concerned with the determination of the ability of XBT surveys to estimate geostrophic currents, taking into account a comparison of directly measured data with estimated shears. Discrepancies are found to be related to an underestimation of the dynamic height gradients.

Koblinsky, C. J.↗

PACE OCI Short-Wave Infrared Detection Assembly frequency-dependent linearity characterization and uncertainty analysis

The Ocean Color Instrument (OCI), the primary payload of the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE)observatory, will collect data to monitor the health of Earth’s oceans and atmosphere. The Short-Wave Infrared(SWIR) Detection Assembly (SDA) was built and characterized by the Utah State University Space DynamicsLaboratory (SDL) and is a subsystem of OCI. The SDA measures seven bands centered at 940, 1038, 1250, 1378,1615, 2130, and 2260 nm, with standard- and high-gain varieties for the 1250 and 1615 nm bands, resulting in nine total detection configurations in the SWIR. The delivery of high-quality science data is critically dependent upon accurately characterizing the linearity of the SDA. Two metrology techniques were employed to measure the linearity and characterize the frequency-dependent linearity uncertainty of the system. The first technique used superposition linearity measurements to determine the DC linearity, and the second technique involved an oscillating small-signal response at seven frequencies to determine the frequency-dependent linearity. Discrepancies between the DC and frequency-dependent linearities constrain the uncertainty between the two. Examining the difference between these two methods for all SDA channels, we find most channels experience an uncertainty below0.2% with a worst-case measurement uncertainty of 0.31%. Averaging SDA channels with similar detectors, optical filters, and electronics to simulate the flight-like data products yields a worst-case frequency-dependence linearity uncertainty of 0.12%, demonstrating minimal frequency dependence, implying an excellent linearity knowledge.Detailed performance knowledge, including linearity performance, verifies data quality and builds confidence in the success of the PACE mission.

PACE↗