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NASA NTRS1994

SeaWiFS technical report series. Volume 21: The heritage of SeaWiFS. A retrospective on the CZCS NIMBUS Experiment Team (NET) program

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission is based on the scientific heritage of the Coastal Zone Color Scanner (CZCS), a proof-of-concept instrument carried on the National Aeronautics and Space Administration (NASA) NIMBUS-7 environmental satellite for the purpose of measuring upwelling radiance from the ocean surface. The CZCS mission provided the first observations of ocean color from space, and over the mission lifetime of 1978-1986, allowed oceanographers an initial opportunity to observe the variable patterns of global biological productivity. One of the key elements of the CZCS mission was the formation of the CZCS NIMBUS Experiment Team (NET), a group of optical physicists and biological oceanographers. The CZCS NET was designated to validate the accuracy of the CZCS radiometric measurements and to connect the instrument's measurements to standard measures of oceanic biological productivity and optical seawater clarity. In the period following the cessation of CZCS observations, some of the insight and experience gained by the CZCS NET activity has dissipated as several proposed follow-on sensors failed to achieve active status. The Sea WiFS mission will be the first dedicated orbital successor to CZCS it in turn precedes observations by the Moderate Resolution Imaging Spectroradiometer (MODIS) of the Earth Observing System (EOS). Since the CZCS NET experience is an important model for Sea WiFS and MODIS surface truth efforts, this document is intended to provide a comprehensive review of the validation of oceanographic data for the first orbital ocean color sensor mission. This document also summarizes the history of the CZCS NET activities. The references listed in the Bibliography are a listing of published scientific research which relied upon the CZCS BET algorithms, or research which was conducted on the basis of CZCS mission elements.

Acker, James G.↗
NASA NTRS2003

NASA GPM GV Science Requirements

An important scientific objective of the NASA portion of the GPM Mission is to generate quantitatively-based error characterization information along with the rainrate retrievals emanating from the GPM constellation of satellites. These data must serve four main purposes: (1) they must be of sufficient quality, uniformity, and timeliness to govern the observation weighting schemes used in the data assimilation modules of numerical weather prediction models; (2) they must extend over that portion of the globe accessible by the GPM core satellite to which the NASA GV program is focused - (approx.65 degree inclination); (3) they must have sufficient specificity to enable detection of physically-formulated microphysical and meteorological weaknesses in the standard physical level 2 rainrate algorithms to be used in the GPM Precipitation Processing System (PPS), i.e., algorithms which will have evolved from the TRMM standard physical level 2 algorithms; and (4) they must support the use of physical error modeling as a primary validation tool and as the eventual replacement of the conventional GV approach of statistically intercomparing surface rainrates fiom ground and satellite measurements. This approach to ground validation research represents a paradigm shift vis-&-vis the program developed for the TRMM mission, which conducted ground validation largely as a statistical intercomparison process between raingauge-derived or radar-derived rainrates and the TRMM satellite rainrate retrievals -- long after the original satellite retrievals were archived. This approach has been able to quantify averaged rainrate differences between the satellite algorithms and the ground instruments, but has not been able to explain causes of algorithm failures or produce error information directly compatible with the cost functions of data assimilation schemes. These schemes require periodic and near-realtime bias uncertainty (i.e., global space-time distributed conditional accuracy of the retrieved rainrates) and local error covariance structure (i.e., global space-time distributed error correlation information for the local 4-dimensional space-time domain -- or in simpler terms, the matrix form of precision error). This can only be accomplished by establishing a network of high quality-heavily instrumented supersites selectively distributed at a few oceanic, continental, and coastal sites. Economics and pragmatics dictate that the network must be made up of a relatively small number of sites (6-8) created through international cooperation. This presentation will address some of the details of the methodology behind the error characterization approach, some proposed solutions for expanding site-developed error properties to regional scales, a data processing and communications concept that would enable rapid implementation of algorithm improvement by the algorithm developers, and the likely available options for developing the supersite network.

Smith, E.↗
NASA NTRS2001

Bio-Optical Measurement and Modeling of the California Current and Polar Oceans

The principal goals of our research are to validate standard or experimental products through detailed bio-optical and biogeochemical measurements, and to combine ocean optical observations with advanced radiative transfer modeling to contribute to satellite vicarious radiometric calibration and advanced algorithm development. To achieve our goals requires continued efforts to execute complex field programs globally, as well as development of advanced ocean optical measurement protocols. We completed a comprehensive set of ocean optical observations in the California Current, Southern Ocean, Indian Ocean requiring a large commitment to instrument calibration, measurement protocols, data processing and data merger. We augmented separately funded projects of our own, as well as others, to acquire ill situ data sets we have collected on various global cruises supported by separate grants or contracts. In collaboration with major oceanographic ship-based observation programs funded by various agencies (CalCOFI, US JGOFS, NOAA AMLR, INDOEX and Japan/East Sea) our SIMBIOS effort has resulted in data from diverse bio-optical provinces. For these global deployments we generate a high-quality, methodologically consistent, data set encompassing a wide-range of oceanic conditions. Global data collected in recent years have been integrated with our on-going CalCOFI database and have been used to evaluate SeaWiFS algorithms and to carry out validation studies. The combined database we have assembled now comprises more than 700 stations and includes observations for the clearest oligotrophic waters, highly eutrophic blooms, red-tides and coastal case 2 conditions. The data has been used to validate water-leaving radiance estimated with SeaWiFS as well as bio-optical algorithms for chlorophyll pigments. The comprehensive data is utilized for development of experimental algorithms (e.g. high-low latitude pigment transition, phytoplankton absorption, and cDOM). During this period we completed 9 peer-reviewed publications in high quality journals, and presented aspects of our work at more than 10 scientific conferences.

Mitchell, B. Greg↗
NASA NTRS2015

Estimating Viscoelastic Deformation Due to Seasonal Loading

Scientists have been making summer-­‐time geodetic measurements in south central Alaska for decades to estimate the rate at which a continental-­‐ocean terrane is accreting to the North American continent. Southern Alaska has big earthquakes every century and large, rapidly changing glaciers. In the last decade, primarily as part of the EarthScope Plate Boundary Observatory project, continuous GPS measurements have recorded the response of sites such as the near-­‐coastal geodetic site, AB35 to competing processes: uplift and movement to the northwest due to tectonic forces and the response of the solid Earth to seasonal and longer-­‐term changes in the cryosphere (snow and ice) surrounding the site. Which process causes the largest displacements of the site? Figure 1 (Blewitt, Nevada Geodetic Lab, 2015) shows the Northward, Eastward, and Upward motion of AB35 between 2007 and 2015. The site is moving rapidly to the north and west reflecting the tectonic convergence of site toward interior Alaska but there is small wiggle on the North component reflecting seasonal displacements of the site associated with snow loading and unloading. However, the Up component, shows a large seasonal signal due to snow loading in the winter (down) and ice and snow melting in the warmer months (site goes up). Between 2007 and the present, the site position is slowly moving upward, due to tectonic forcing but probably associated with longer-­‐ term ice melting as well. We are using the CIG finite element modeling (FEM) program Pylith to estimate the surface displacements and stresses associated with seasonal loading changes (top figure and Figure 2 far right) for water year 2012, 2011.8 - 2012.8) and the longer-­‐term retreat of the surrounding glaciers.

Alaska↗
NASA NTRSDate not supplied

Enabling Interoperability in Earth System Digital Twins (ESDT): Integrating Observations, Models, and AI for Actionable Insights Through NASA'S Intelligent Systems Technology Program

NASA’s Intelligent Systems Technology Program (IST) is driving a paradigm shift in Earth science through the development of Earth System Digital Twins (ESDT). These integrated information systems create a dynamic "digital replica" of the Earth by harmonizing continuous, multi-source observations with high-fidelity models and state-of-the-art artificial intelligence (AI) that enable “What now?”, “What next?”, and “What if?” scenario building. These scenarios are reflected in NASA IST’s series of ESDTs, from the Coastal Zone Digital Twin that integrates complex data on the current state of the Chesapeake Bay to the Terrestrial Environmental Rapid-Replication and Assimilation Hydrometeorological (TerraHydro) AI-based ESDT that forecasts water movement across Earth’s surface, to the Agriculture Land Information System (AgLIS) which can be used to assess optimal planting dates and crop yield estimates. By bridging the gap between vast data archives and actionable insights, these projects enable a system-of-systems approach to understanding complex, interacting Earth processes. This poster will highlight recent innovations and future directions from NASA’s ESDT initiatives: Continuous Data Assimilation & Multi-Source Fusion. A core requirement of the ESDT work is the transition from static models to dynamic "living" replicas. This involves creating frameworks for the continual assimilation of near-real-time data from uncoordinated, heterogeneous sources, including satellite observations and airborne assets, and ground-based Internet of Things (IoT) sensors. These systems link design, operational status, and environmental data, ensuring the digital twin accurately reflects the current state of the physical Earth system. High-Fidelity Hybrid Modeling & Computational Acceleration to enable interactive "what-if" explorations, programs are moving beyond traditional, slow physical solvers by developing fast surrogate machine learning models and Deep Generative Models (DGMs). These hybrid approaches use neural networks to emulate complex physics, such as cloud feedback or ocean dynamics, at a fraction of the original computing cost, often leveraging advanced hardware like Graphics Processing Units (GPUs) to achieve the necessary scale. Federated Ecosystems & Interoperable Frameworks rather than building isolated tools, NASA IST is moving toward federated ESDTs and reusable analytic collaborative frameworks. This theme focuses on interoperability standards and common ontologies that allow specialized digital twins to interact and share data. This system-of-systems architecture supports multi-discipline investigations, such as analyzing how upstream watershed changes impact downstream urban flooding or how wildfire emissions affect regional air quality. By leveraging these advancements, ESDTs empower researchers and decision-makers to conduct real-time analysis and run complex hypothetical scenarios, ultimately improving our understanding of Earth’s evolving systems and informing critical real-world applications.

Earth System↗
NASA NTRS2006

Remote Sensing Reflectance and Inherent Optical Properties in the Mid-mesohaline Chesapeake Bay

We used an extensive set of bio-optical data and radiative transfer (RT) model simulations of radiation fields to investigate relationships between inherent optical properties and remotely sensed quantities in the optically complex, mid-mesohaline Chesapeake Bay waters. Field observations showed that the chlorophyll algorithms used by the MODIS (MODerate resolution Imaging Spectroradiometer) ocean color sensor (i.e. Chlor_a, chlor_MODIS, chlor_a_3 products) do not perform accurately in these Case 2 waters. This is because, when applied to waters with high concentrations of chlorophyll, all MODIS algorithms are based on empirical relationships between chlorophyll concentration and blue-green wavelength remote sensing reflectance (Rrs) ratios that do not account for the typically strong blue-wavelength absorption by non-covarying, dissolved and non-algal particulate components. Stronger correlation was observed between chlorophyll concentration and Rrs ratios in the red (i.e. Rrs(677)/Rrs(554)) where dissolved and non-algal particulate absorption become exponentially smaller. Regionally-specific algorithms that are based on the phytoplankton optical properties in the red wavelength region provide a better basis for satellite monitoring of phytoplankton blooms in these Case 2 waters. Good optical closure was obtained between independently measured Rrs spectra and the optical properties of backscattering, b(sub b), and absorption, a, over the wide range of in-water conditions observed in the Chesapeake Bay. Observed variability in the quantity f/Q (proportionality factor in the relationship between Rrs and the water inherent optical properties ratio b(sub b)/(a+b(sub b)) was consistent with RT model calculations for the specific measurement geometry and water bio-optical characteristics. Data and model results showed that f/Q values in these Case 2 coastal waters are not considerably different from those estimated in previous studies for Case 1 waters. Variation in surface backscattering significantly affected Rrs magnitude across the visible spectrum and was most strongly correlated (R(sup 2)=0.88) with observed variability in Rrs at 670 nm. Surface values of particulate backscattering were strongly correlated with non-algal particulate absorption, a(sub nap), in the blue wavelengths (R(sup 2)=0.83). These results, along with the measured values of backscattering fraction magnitude and non-algal particulate absorption spectral slope, suggest that suspended non-algal particles with high inorganic content are the major water constituents regulating b(sub b) variability in the mid-mesohaline Chesapeake Bay. Remote retrieval of surface b(sub b) and (a(sub nap), from Rrs(670) can be used in regionally-specific satellite algorithms to separate contribution by non-algal particles and dissolved organic matter to total light absorption in the blue, and monitor non-algal suspended particle concentration and distribution in these Case 2 waters.

Tzortziou, Maria↗
NASA NTRS2014

ENSO Effect on East Asian Tropical Cyclone Landfall via Changes in Tracks and Genesis in a Statistical Model

Improvements on a statistical tropical cyclone (TC) track model in the western North Pacific Ocean are described. The goal of the model is to study the effect of El Nino-Southern Oscillation (ENSO) on East Asian TC landfall. The model is based on the International Best-Track Archive for Climate Stewardship (IBTrACS) database of TC observations for 1945-2007 and employs local regression of TC formation rates and track increments on the Nino-3.4 index and seasonally varying climate parameters. The main improvements are the inclusion of ENSO dependence in the track propagation and accounting for seasonality in both genesis and tracks. A comparison of simulations of the 1945-2007 period with observations concludes that the model updates improve the skill of this model in simulating TCs. Changes in TC genesis and tracks are analyzed separately and cumulatively in simulations of stationary extreme ENSO states. ENSO effects on regional (100-km scale) landfall are attributed to changes in genesis and tracks. The effect of ENSO on genesis is predominantly a shift in genesis location from the southeast in El Nino years to the northwest in La Nina years, resulting in higher landfall rates for the East Asian coast during La Nina. The effect of ENSO on track propagation varies seasonally and spatially. In the peak activity season (July-October), there are significant changes in mean tracks with ENSO. Landfall-rate changes from genesis- and track-ENSO effects in the Philippines cancel out, while coastal segments of Vietnam, China, the Korean Peninsula, and Japan show enhanced La Nina-year increases.

simulation↗
NASA NTRS2023

Decoupling in the Vertical Shape of HCHO During a Sea Breeze Event: the Effect on Trace Gas Satellite Retrievals and Column-to-Surface Translation

The effect of sea breeze circulation on stratification of the vertical formaldehyde (HCHO) concentration vertical profiles is explored using a regional atmospheric chemical transport model (CTM) for three synoptically stagnant days focused on the east coast of the U.S in June 2018. During this event, a significant thermal contrast between the Atlantic Ocean and the terrestrial regions (12–17 °C), observed by moderate resolution imaging spectroradiometer (MODIS) and well-captured by the WRF-CMAQ model (15–18 °C), is conducive to monsoon-like flow, perpendicular to the shorelines, carrying clean marine air masses over the land within a few hundreds of meters above the surface. In contrast, the westerly continental polluted air masses prevail in higher altitudes. These two conflicting flows result in atypical vertical shapes of HCHO concentrations increasing with altitude. This decoupling pattern is so pronounced that we observe total column HCHO negatively correlate with surface concentrations. Comparisons of an accredited global model, GEOS-CF, to surface wind measurements and MODIS skin temperature indicate its poor representation of the sea breeze timing and strength, resulting in GEOS-CF HCHO vertical shapes being drastically different from the WRF-CMAQ. Based on radiative transfer calculations, the differences in the vertical distribution of HCHO between the WRF-CMAQ and that of GEOS-CF in the first 3 km are sufficient to induce a 20–30% error in air mass factors (thus total vertical HCHO column abundances). Through an experiment involving converting HCHO total columns to surface mixing ratios, we demonstrate that GEOS-CF allocates noticeably more HCHO molecules (40–150%) to the surface layer due to the misrepresentation of the vertical shape of HCHO during the sea breeze event. It is known that a significant fraction of the human population lives in coastal areas prone to detrimental effects caused by air pollution, and elevated pollutant concentrations usually occur in synoptically stagnant atmospheric conditions when local circulation patterns come into play; accordingly, our experiments emphasize the importance of the effect a priori profiles can have on satellite-derived applications under such conditions. To ensure that the quantitative representation of satellite-based trace gas retrievals on a daily basis is trustworthy and useable for air quality applications, atmospheric models providing a priori profiles for satellite retrievals should be well-tuned to reproduce complex local circulation such as sea-land breezes.

sea breeze↗
NASA NTRS2015

Integrated Assessments of the Impact of Climate Change on Agriculture: An Overview of AgMIP Regional Research in South Asia

South Asia encompasses a wide and highly varied geographic region, and includes climate zones ranging from the mountainous Himalayan territory to the tropical lowland and coastal zones along alluvial floodplains. The region's climate is dominated by a monsoonal circulation that heralds the arrival of seasonal rainfall, upon which much of the regional agriculture relies. The spatial and temporal distribution of this rainfall is, however, not uniform over the region. Northern South Asia, central India, and the west coast receive much of their rainfall during the southwest monsoon season, between June and September. These rains partly result from the moisture transport accompanying the monsoonal winds, which move in the southwesterly direction from the equatorial Indian Ocean. Regions further south, such as south/southeast India and Sri Lanka, may receive rains from both the southwest monsoon, and also during the northeast monsoon season between October and December (with northeasterly monsoon wind flow and moisture flux), which results in a bi- or multi-modal rainfall distribution. In addition, rainfall across South Asia displays a large amount of intraseasonal and interannual variability. Interannual variability is influenced by many drivers, both natural (e.g., El Ni-Southern Oscillation; ENSO) and man-made (e.g., rising temperatures due to increasing greenhouse gas concentrations), and it is challenging to obtaining accurate time-series of annual rainfall, even amongst various observed data products, which display inconsistencies amongst themselves. These climatic and rainfall variations can further complicate South Asia's agricultural and water management. Agriculture employs at least 65 of the workforce in most South Asian countries, and nearly 80 of South Asia's poor inhabit rural areas. Understanding the response of current agricultural production to climate variability and future climate change is of utmost importance in securing food and livelihoods for South Asia's growing population. In order to assess the future of food and livelihood security across South Asia, the Agricultural Model Intercomparison and Improvement Project (AgMIP) has undertaken integrated climate-crop-economic assessments of the impact of climate change on food security and poverty in South Asia, encompassing Bangladesh, India, Nepal, Pakistan, and Sri Lanka. AgMIP has funded, on a competitive basis, four South Asian regional research teams (RRTs) and one South Asian coordination team (CT) to undertake climate-crop-economic integrated assessments of food security for many districts in each of these countries, with the goal of characterizing the state of food security and poverty across the region, and projecting how these are subject to change under future climate change conditions.

mountains↗
NASA NTRS2015

New York City Panel on Climate Change 2015 Report: Climate Observations and Projections - Chapter 1

During 2013 and 2014, numerous international (IPCC, 2013) and national (Melillo et al., 2014; Gordon, 2014) reports have concluded that human activities are changing the climate, leading to increased vulnerability and risk. Since the industrial revolution, fossil fuel burning, industrial activity, and land use changes have led to a 40% increase in heat-trapping carbon dioxide (CO2), and an approximately 150% increase in methane (CH4), another powerful greenhouse gas (GHG), has been observed. Global temperatures have increased by close to 1 C since 1880 as the upper oceans have warmed and polar ice has retreated. These and other climate changes are projected to accelerate as greenhouse gas concentrations continue to rise. In the coming decades, climate change is extremely likely to bring warmer temperatures in the New York metropolitan region (see Box. 1.1 and Fig.1.1 for key definitions and terms). Heat waves are very likely to increase; total annual precipitation will likely increase and brief, intense rainstorms are very likely to increase. Because of incomplete knowledge about exactly how much climate change will occur, choosing among policies for reducing future damages requires prudent risk management (Yohe and Leichenko, 2010; Kunreuther et al., 2013). Given differing risk tolerances among stakeholders, a risk management approach allows for a range of possible climate change outcomes to be examined with associated uncertainties surrounding their likelihoods. The New York City Panel on Climate Change 2 (NPCC2) projections can be used to inform planning across multiple governmental scales (e.g., city, county, state) in the New York metropolitan region. Such coordinated efforts can serve as test cases for successful local, state, and federal coordination for integrated climate adaptation initiatives. This chapter describes the global climate system, and presents observed temperature and precipitation trends and projections for the region. Chapter 2 (NPCC, 2015) focuses on sea level rise and possible changes in coastal storms. Chapter 3 and Chapter 4 (NPCC, 2015) describe efforts to better understand the region's vulnerability to coastal flooding during coastal storms. The treatment of likelihood related to the NPCC projections is similar to that developed by the Intergovernmental Panel on Climate Change Fourth and Fifth Assessment Reports (IPCC, 2007; 2013), with six likelihood categories (Box 1.1 and Fig. 1.1). The assignment of climate hazards to these categories is based on observed data, global climate model simulations, published literature, and expert judgment.

climate change↗
NASA NTRS2015

Evaluation of the 7-km GEOS-5 Nature Run

This report documents an evaluation by the Global Modeling and Assimilation Office (GMAO) of a two-year 7-km-resolution non-hydrostatic global mesoscale simulation produced with the Goddard Earth Observing System (GEOS-5) atmospheric general circulation model. The simulation was produced as a Nature Run for conducting observing system simulation experiments (OSSEs). Generation of the GEOS-5 Nature Run (G5NR) was motivated in part by the desire of the OSSE community for an improved high-resolution sequel to an existing Nature Run produced by the European Centre for Medium-Range Weather Forecasts (ECMWF), which has served the community for several years. The intended use of the G5NR in this context is for generating simulated observations to test proposed observing system designs regarding new instruments and their deployments. Because NASA's interest in OSSEs extends beyond traditional weather forecasting applications, the G5NR includes, in addition to standard meteorological components, a suite of aerosol types and several trace gas concentrations, with emissions downscaled to 10 km using ancillary information such as power plant location, population density and night-light information. The evaluation exercise described here involved more than twenty-five GMAO scientists investigating various aspects of the G5NR performance, including time mean temperature and wind fields, energy spectra, precipitation and the hydrological cycle, the representation of waves, tropical cyclones and midlatitude storms, land and ocean surface characteristics, the representation and forcing effects of clouds and radiation, dynamics of the stratosphere and mesosphere, and the representation of aerosols and trace gases. Comparisons are made with observational data sets when possible, as well as with reanalyses and other long model simulations. The evaluation is broad in scope, as it is meant to assess the overall realism of basic aspects of the G5NR deemed relevant to the conduct of OSSEs. However, because of the relatively short record and other practical considerations, these comparisons cannot provide a definitive, statistically sound assessment of all model deficiencies, or guarantee the G5NR's suitability for all OSSE applications. Differences between the observed and simulated behavior also must be judged in the context of basic internal atmospheric variability which can introduce variations that are not necessarily controlled by the prescribed sea surface temperatures used in generating the G5NR. The results show that the G5NR performs well as measured by the majority of metrics applied in this evaluation. Particular benefits derived from the 7-km resolution of G5NR include realistic representations of extreme weather events in both the tropics and extratropics including tropical cyclones, Nor'easters and mesoscale convective complexes; improved representation of the diurnal cycle of precipitation over land; well-resolved surface-atmosphere interactions such as katabatic wind flows over Antarctica and Greenland; and resolution of orographically generated gravity waves that propagate into the upper atmosphere and influence the large scale circulation. Obvious deficiencies in the G5NR include a "splitting" of the inter-tropical convergence zone, which leads to a weaker-than-observed Hadley circulation and related deficiencies in the depiction of stationary wave patterns. Also, while the G5NR captures global cloud features and radiative effects well in general, close comparison with observations reveals higher-than-observed cloud brightness, likely due to an overabundance of cloud condensate; less distinct cloud minima in subtropical subsidence zones, consistent with a weak Hadley circualtion; and too few near-coastal marine stratocumulus clouds.

GEOS-5↗
NASA NTRS2008

Ocean Carbon and Biogeochemistry Scoping Workshop on Terrestrial and Coastal Carbon Fluxes in the Gulf of Mexico, St. Petersburg, FL

Despite their relatively small surface area, ocean margins may have a significant impact on global biogeochemical cycles and, potentially, the global air-sea fluxes of carbon dioxide. Margins are characterized by intense geochemical and biological processing of carbon and other elements and exchange large amounts of matter and energy with the open ocean. The area-specific rates of productivity, biogeochemical cycling, and organic/inorganic matter sequestration are high in coastal margins, with as much as half of the global integrated new production occurring over the continental shelves and slopes (Walsh, 1991; Doney and Hood, 2002; Jahnke, in press). However, the current lack of knowledge and understanding of biogeochemical processes occurring at the ocean margins has left them largely ignored in most of the previous global assessments of the oceanic carbon cycle (Doney and Hood, 2002). A major source of North American and global uncertainty is the Gulf of Mexico, a large semi-enclosed subtropical basin bordered by the United States, Mexico, and Cuba. Like many of the marginal oceans worldwide, the Gulf of Mexico remains largely unsampled and poorly characterized in terms of its air-sea exchange of carbon dioxide and other carbon fluxes. The goal of the workshop was to bring together researchers from multiple disciplines studying terrestrial, aquatic, and marine ecosystems to discuss the state of knowledge in carbon fluxes in the Gulf of Mexico, data gaps, and overarching questions in the Gulf of Mexico system. The discussions at the workshop were intended to stimulate integrated studies of marine and terrestrial biogeochemical cycles and associated ecosystems that will help to establish the role of the Gulf of Mexico in the carbon cycle and how it might evolve in the face of environmental change.

Air sea exchanges↗
NASA NTRS2014

Detecting Trend and Seasonal Changes in Bathymetry Derived from HICO Imagery: A Case Study of Shark Bay, Western Australia

The Hyperspectral Imager for the Coastal Ocean (HICO) aboard the International Space Station has offered for the first time a dedicated space-borne hyperspectral sensor specifically designed for remote sensing of the coastal environment. However, several processing steps are required to convert calibrated top-of-atmosphere radiances to the desired geophysical parameter(s). These steps add various amounts of uncertainty that can cumulatively render the geophysical parameter imprecise and potentially unusable if the objective is to analyze trends and/or seasonal variability. This research presented here has focused on: (1) atmospheric correction of HICO imagery; (2) retrieval of bathymetry using an improved implementation of a shallowwater inversion algorithm; (3) propagation of uncertainty due to environmental noise through the bathymetry retrieval process; (4) issues relating to consistent geo-location of HICO imagery necessary for time series analysis, and; (5) tide height corrections of the retrieved bathymetric dataset. The underlying question of whether a temporal change in depth is detectable above uncertainty is also addressed. To this end, nine HICO images spanning November 2011 to August 2012, over the Shark Bay World Heritage Area, Western Australia, were examined. The results presented indicate that precision of the bathymetric retrievals is dependent on the shallow water inversion algorithm used.Within this study, an average of 70% of pixels for the entire HICO-derived bathymetry dataset achieved a relative uncertainty of less than +/-20%. A per-pixel t-test analysis between derived bathymetry images at successive timestamps revealed observable changes in depth to as lowas 0.4 m. However, the present geolocation accuracy of HICO is relatively poor and needs further improvements before extensive time series analysis can be performed.

Geolocations accuracy↗