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NASA NTRS2019

Atmospheric Correction for Coastal Waters Based on Multi-Angle Polarimetric Observations

Atmospheric correction is an essential procedure of ocean color remote sensing, which obtains water-leaving signals from satellite or airborne sensors. Due to the small percentage of the water leaving signals in the total measurement, atmospheric correction requires precise evaluation of the radiometric contributions from the aerosol and ocean surface. It is often challenging over coastal waters when absorbing aerosols are present and when water leaving signals in the near infrared spectral region are non-negligible. In this work, we report on a joint retrieval algorithm that determines aerosol and ocean optical properties using the polarimetric measurements based on a coupled atmosphere and ocean radiative transfer model. Two bio-optical models are designed for ocean water properties. One model parameterizes the open ocean optical properties in terms of the concentration of chlorophyll a. The other is a generalized bio-optical model for coastal waters that describes the absorption and scattering by phytoplankton, colored dissolved organic matter and non-algal particles using multiple parameters. We applied the algorithm to the airborne Research Scanning Polarimeter (RSP) measurements acquired over both open and coastal ocean waters. Through the comparisons with in situ ocean color measurements, the flexibility and accuracy of the retrieval algorithm in retrieving aerosol and water leaving radiance properties are demonstrated under various aerosol and ocean water conditions.

Gao, Meng↗
NASA NTRSDate not supplied

Pushing the Limits of Aquatic Remote Sensing: Synthetic Data and Deep Learning for Fast Inverse Emulation of A Coupled Ocean-Atmosphere Radiative Transfer Model

The inversion of electromagnetic information to physical and biological properties of the water column is a notoriously difficult problem, yet fundamental to our ability of understanding aquatic processes on large time and space scales. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This presentation will discuss research integrating advanced biological and radiative modeling, high-end computation, and machine learning to develop a portable global processor for simultaneous retrieval of atmosphere and water optics for diverse aquatic systems from the open and coastal ocean to optically extreme inland waters and harmful algal blooms. We will discuss some of the basic concepts behind the forward modeling approach including DEAP, the novel Distributed Equivalent Algal Populations model, for developing large spectral libraries of aquatic particle optics to aid in our ability to distinguish phytoplankton functional types (PFTs) and inorganic material, as well as other factors which enable comprehensive modeling from the benthos to top-of-atmosphere (TOA). This information is being used to understand how we can leverage next-generation deep learning methods for maximum information retrieval and rapid image processing, while also providing capabilities to identify minimum sensor spectral requirements necessary for certain aquatic applications. Further, I will touch on how we envision this research to enable the aquatic community for science discovery and how we are moving closer towards the capability for high-fidelity global analysis of aquatic ecosystems.

Jeremy Alan Kravitz↗
NASA NTRS1999

Seasonal-to-Interannual Variability in Antarctic Sea-Ice Dynamics, and Its Impact on Surface Fluxes and Water Mass Production

Strong seasonal and interannual signals in Antarctic bottom-water outflow remain unexplained yet are highly correlated with anomalies in net sea-ice growth in coastal polynyas. The mechanisms responsible for driving salination and replenishment and rejuvenation of the dense shelf "source" waters likely also generate pulses of bottom water outflow. The objective of this research is to investigate time-scales of variability in the dynamics of sea-ice in the Southern Ocean in order to determine the primary sites for production of dense shelf waters. We are using a merged satellite/buoy sea-ice motion data set for the period 1978-present day to compute the dynamics of opening and closing of coastal polynyas over the continental shelf. The Ocean Circulation and Climate Advanced Model (OCCAM) ocean general circulation model with coupled sea-ice dynamics is presently forced using National Center for Environmental Prediction (NCEP) data to simulate fluxes and the salination impact of the ocean shelf regions. This work is relevant in the context of measuring the influence of polar sea-ice dynamics upon polar ocean characteristics, and thereby upon global thermohaline ocean circulation. Interannual variability in simulated net freezing rate in the Southern Weddell Sea is shown for the period 1986-1993. There is a pronounced maximum of ice production in 1988 and minimum in 1991 in response to anomalies in equatorward meridional wind velocity. This follows a similar approximate 8-year interannual cycle in Sea Surface Temperature (SST) and satellite-derived ice-edge anomalies reported elsewhere as the "Antarctic Circumpolar Wave." The amplitude of interannual fluctuations in annual net ice production are about 40% of the mean value, implying significant interannual variance in brine rejection and upper ocean heat loss. Southward anomalies in wind stress induce negative anomalies in open water production, which are observed in passive microwave satellite images. Thus, cycles of enhanced poleward wind stress reduce ice growth by compacting the ice along the coastline and closing open water in leads and polynyas. Model simulations confirm that years of low ice production, such as 1991, coincide with years of lower than normal bottom water outflow. Future plans include the assimilation of satellite ice concentrations and ice drift dynamics to more accurately constrain boundary conditions in the model.

Drinkwater, Mark R.↗
NASA NTRS2013

CGILS: Results from the First Phase of an International Project to Understand the Physical Mechanisms of Low Cloud Feedbacks in Single Column Models

1] CGILS-the CFMIP-GASS Intercomparison of Large Eddy Models (LESs) and single column models (SCMs)-investigates the mechanisms of cloud feedback in SCMs and LESs under idealized climate change perturbation. This paper describes the CGILS results from 15 SCMs and 8 LES models. Three cloud regimes over the subtropical oceans are studied: shallow cumulus, cumulus under stratocumulus, and well-mixed coastal stratus/stratocumulus. In the stratocumulus and coastal stratus regimes, SCMs without activated shallow convection generally simulated negative cloud feedbacks, while models with active shallow convection generally simulated positive cloud feedbacks. In the shallow cumulus alone regime, this relationship is less clear, likely due to the changes in cloud depth, lateral mixing, and precipitation or a combination of them. The majority of LES models simulated negative cloud feedback in the well-mixed coastal stratus/stratocumulus regime, and positive feedback in the shallow cumulus and stratocumulus regime. A general framework is provided to interpret SCM results: in a warmer climate, the moistening rate of the cloudy layer associated with the surface-based turbulence parameterization is enhanced; together with weaker large-scale subsidence, it causes negative cloud feedback. In contrast, in the warmer climate, the drying rate associated with the shallow convection scheme is enhanced. This causes positive cloud feedback. These mechanisms are summarized as the "NESTS" negative cloud feedback and the "SCOPE" positive cloud feedback (Negative feedback from Surface Turbulence under weaker Subsidence-Shallow Convection PositivE feedback) with the net cloud feedback depending on how the two opposing effects counteract each other. The LES results are consistent with these interpretations

Single Column Models↗
NASA NTRS2011

Satellite-Derived Distributions, Inventories and Fluxes of Dissolved and Particulate Organic Matter Along the Northeastern U.S. Continental Margin

Estuaries and the coastal ocean experience a high degree of variability in the composition and concentration of particulate and dissolved organic matter (DOM) as a consequence of riverine and estuarine fluxes of terrigenous DOM, sediments, detritus and nutrients into coastal waters and associated phytoplankton blooms. Our approach integrates biogeochemical measurements, optical properties and remote sensing to examine the distributions and inventories of organic carbon in the U.S. Middle Atlantic Bight and Gulf of Maine. Algorithms developed to retrieve colored DOM (CDOM), Dissolved (DOC) and Particulate Organic Carbon (POC) from NASA's MODIS-Aqua and SeaWiFS satellite sensors are applied to quantify the distributions and inventories of DOC and POC. Horizontal fluxes of DOC and POC from the continental margin to the open ocean are estimated from SeaWiFS and MODIS-Aqua distributions of DOC and POC and horizontal divergence fluxes obtained from the Northeastern North Atlantic ROMS model. SeaWiFS and MODIS imagery reveal the importance of estuarine outflow to the export of CDOM and DOC to the coastal ocean and a net community production of DOC on the shelf.

Mannino, A.↗
NASA NTRS2018

The Ocean Carbon States Database: A Proof-of-Concept Application of Cluster Analysis in the Ocean Carbon Cycle

In this paper, we present a database of the basic regimes of the carbon cycle in the ocean, the 'ocean carbon states', as obtained using a data mining/pattern recognition technique in observation-based as well as model data. The goal of this study is to establish a new data analysis methodology, test it and assess its utility in providing more insights into the regional and temporal variability of the marine carbon cycle. This is important as advanced data mining techniques are becoming widely used in climate and Earth sciences and in particular in studies of the global carbon cycle, where the interaction of physical and biogeochemical drivers confounds our ability to accurately describe, understand, and predict CO2 concentrations and their changes in the major planetary carbon reservoirs. In this proof-of-concept study, we focus on using well-understood data that are based on observations, as well as model results from the NASA Goddard Institute for Space Studies (GISS) climate model. Our analysis shows that ocean carbon states are associated with the subtropical-subpolar gyre during the colder months of the year and the tropics during the warmer season in the North Atlantic basin. Conversely, in the Southern Ocean, the ocean carbon states can be associated with the subtropical and Antarctic convergence zones in the warmer season and the coastal Antarctic divergence zone in the colder season. With respect to model evaluation, we find that the GISS model reproduces the cold and warm season regimes more skillfully in the North Atlantic than in the Southern Ocean and matches the observed seasonality better than the spatial distribution of the regimes. Finally, the ocean carbon states provide useful information in the model error attribution. Model air-sea CO2 flux biases in the North Atlantic stem from wind speed and salinity biases in the subpolar region and nutrient and wind speed biases in the subtropics and tropics. Nutrient biases are shown to be most important in the Southern Ocean flux bias.

carbon cycle↗
NASA NTRS2002

Mapping CDOM Concentration in Waters Influenced by the Mississippi River Plume

Colored dissolved organic matter (CDOM) is often an important component of the organic carbon pool in river-dominated coastal margins. CDOM directly influences remote sensing applications through its strong absorption in the UV and blue regions of the spectrum. This effect can complicate the use of chlorophyll a retrieval algorithms and phytoplankton production models that are based on remotely sensed ocean color. As freshwater input is the principle source of CDOM in coastal margins, CDOM distribution can often be described by conservative mixing with open ocean waters and may serve as an optical tracer of riverine water. Hence, there is considerable interest in the ability to accurately measure and map CDOM concentrations as well as understand the processes that govern the optical properties and distribution of CDOM in coastal environments. We are examining CDOM dynamics in the waters influenced by the Mississippi River plume. Our program incorporates discrete samples, flow-through measurements, and remote sensing. CDOM absorption spectra of discrete samples are measured at sea using a portable, multiple pathlength waveguide system. A SAFire multi-spectral fluorescence meter provides spectral characterization of CDOM (fluorescence and absorption) using a ship flow-through system for continuous surface mapping. In situ reflectance spectra are obtained by a hand held spectroradiometer. Remotely sensed images are obtained from the SeaWiFS and CRIS (Coastal Research Imaging Spectrometer) instruments. We describe here the instruments used, sampling protocols employed, and the relationships derived between in situ measurements and remotely sensed data for this optically complex environment.

Miller, Richard L.↗
NASA NTRS1989

Continental shelf fish production estimation from CZCS chlorophyll data

A method for ocean fish production estimation was proposed for development. The method was to use data acquired with the Coastal Zone Color Scanner, and processed into chlorophyll concentrations by the GSFC ocean Sciences Division, in combination with fish production and primary production data acquired from different ocean areas. A linear relation exits between annual fish production and annual phytoplankton carbon production for a wide range of coastal ocean environments. The uses of several existing algorithms which relate primary production to CZCS chlorophyll data as input to the fish production regression model is proposed. A question relating phytoplankton production to CZCS chlorophyll was obtained by Eppley (1984) using chlorophyll data obtained from field samples, equivalent to chlorophyll data obtained from CZCS imagery, and primary production data obtained from ship-board observations on a wide variety of coastal and open ocean environments. This equation was modified with additional data and was successfully tested using CZCS data and field chlorophyll and phytoplankton production data obtained from northeastern North American continental shelf waters and Atlantic open ocean waters. The modified Eppley (1984) relation also estimated phytoplankton annual carbon production in the Sargasso Sea within the confidence limits of a mean value obtained from the Eppley (1984) equation for oceanic waters that provide about 90 percent of total ocean primary production. The modified Eppley production formula applied to CZCS chlorophyll data obtained from several northeastern North American coastal environments gave phytoplankton annual carbon production values similar to the values used in the fish production regression equation.

Iverson, Richard L.↗
NASA NTRS2010

Finding the Missing Stratospheric Br(sub y): A Global Modeling Study of CHBr3 and CH2Br2

Recent in situ and satellite measurements suggest a contribution of ~5 pptv to stratospheric inorganic bromine from short-lived bromocarbons. We conduct a modeling study of the two most important short-lived bromocarbons, bromoform (CHBr3) and dibromomethane (CH2Br2), with the Goddard Earth Observing System Chemistry Climate Model (GEOS CCM) to account for this missing stratospheric bromine. We derive a "top-down" emission estimate of CHBr3 and CH2Br2 using airborne measurements in the Pacific and North American troposphere and lower stratosphere obtained during previous NASA aircraft campaigns. Our emission estimate suggests that to reproduce the observed concentrations in the free troposphere, a global oceanic emission of 425 Gg Br yr(exp -1) for CHBr3 and 57 Gg Br yr(exp -l) for CH2Br2 is needed, with 60% of emissions from open ocean and 40% from coastal regions. Although our simple emission scheme assumes no seasonal variations, the model reproduces the observed seasonal variations of the short-lived bromocarbons with high concentrations in winter and low concentrations in summer. This indicates that the seasonality of short-lived bromocarbons is largely due to seasonality in their chemical loss and transport. The inclusion of CHBr3 and CH2Br2 contributes ~5 pptv bromine throughout the stratosphere. Both the source gases and inorganic bromine produced from source gas degradation (Br~SLS) in the troposphere are transported into the stratosphere, and are equally important. Inorganic bromine accounts for half (2.5 pptv) of the bromine from the inclusion of CHBr3 and CHzBr2 near the tropical tropopause and its contribution rapidly increases to ~ 100% as altitude increases. More than 85% of the wet scavenging of Br(sub y)(sup VSLS) occurs in large-scale precipitation below 500 hPa. Our sensitivity study with wet scavenging in convective updrafts switched off suggests that Br(sub y)(sup SLS) in the stratosphere is not sensitive to convection. Convective scavenging only accounts for ~0.2 pptv (4%) difference in inorganic bromine delivered to the stratosphere.

Liang, Q.↗
NASA NTRS2008

High-Resolution Specification of the Land and Ocean Surface for Improving Regional Mesoscale Model Predictions

The exchange of energy and moisture between the Earth's surface and the atmospheric boundary layer plays a critical role in many meteorological processes. High-resolution, accurate representations of surface properties such as sea-surface temperature (SST), soil temperature and moisture content, ground fluxes, and vegetation are necessary to better understand the Earth-atmosphere interactions and improve numerical predictions of sensible weather. The NASA Short-term Prediction Research and Transition (SPoRT) Center has been conducting separate studies to examine the impacts of high-resolution land-surface initialization data from the Goddard Space Flight Center Land Information System (LIS) on subsequent WRF forecasts, as well as the influence of initializing WRF with SST composites derived from the MODIS instrument. This current project addresses the combined impacts of using high-resolution lower boundary data over both land (LIS data) and water (MODIS SSTs) on the subsequent daily WRF forecasts over Florida during May 2004. For this experiment, the WRF model is configured to run on a nested domain with 9- km and 3-kin grid spacing, centered on the Florida peninsula and adjacent coastal waters of the Gulf of Mexico and Atlantic Ocean. A control configuration of WRF is established to take all initial condition data from the NCEP Eta model. Meanwhile, two WRF experimental runs are configured to use high-resolution initialization data from (1) LIS land-surface data only, and (2) a combination of LIS data and high-resolution MODIS SST composites. The experiment involves running 24-hour simulations of the control WRF configuration, the MS-initialized WRF, and the LIS+MODIS-initialized WRF daily for the entire month of May 2004. All atmospheric data for initial and boundary conditions for the Control, LIS, and LIS+MODIS runs come from the NCEP Eta model on a 40-km grid. Verification statistics are generated at land surface observation sites and buoys, and the impacts of the high-resolution lower boundary data on the development and evolution of mesoscale circulations such as sea and land breezes are examined, This paper will present the results of these WRF modeling experiments using LIS and MODIS lower boundary datasets over the Florida peninsula during May 2004.

Case, Jonathan L.↗
NASA NTRS2001

Ocean-Science Mission Needs: Real-Time AUV Data for Command, Control, and Model Inputs

Predictive models for tides, hydrodynamics, and bio-optical properties affecting the visibility and buoyancy of coastal waters are needed to evaluate the safety of personnel and equipment engaged in maritime operations under potentially hazardous conditions. Predicted currents can be markedly different for two-layer systems affected by terrestrial runoff than for well-mixed conditions because the layering decouples the surface and bottom Ekman layers and rectifies the current response to oscillatory upwelling-and downwelling-favorable winds. Standard ocean models (e.g. Princeton Ocean Model) require initial-and boundary data on the physical and optical properties of the multilayered water column to provide accurate simulations of heat budgets and circulation. Two observational systems are designed to measure vertically structured conditions on the West Florida Shelf (WFS): a tethered buoy network and an autonomous underwater vehicle (AUV) observational system. The AUV system is described with a focus on the observational systems that challenge or limit the communications command and control network for various types of measurement programs. These include vertical oscillatory missions on shelf transects to observe the optical and hydrographic properties of the water column, and bottom-following missions for measuring the bottom albedo. Models of light propagation, absorption, and conversion to heat as well as determination of the buoyancy terms for physical models require these measurements. High data rates associated with video bottom imagery are the most challenging for the real-time, command and control communications system, but they are met through a combination of loss-less and lossy data-compression methods, depending upon the data-rate of the radio links.

Carder, Kendall L.↗
NASA NTRS1994

Model for the Interpretation of Hyperspectral Remote-Sensing Reflectance

Remote-sensing reflectance is easier to interpret for the open ocean than for coastal regions because the optical signals are highly coupled to the phytoplankton (e.g., chlorophyll) concentrations. For estuarine or coastal waters, variable terrigenous colored dissolved organic matter (CDOM), suspended sediments, and bottom reflectance, all factors that do not covary with the pigment concentration, confound data interpretation. In this research, remote-sensing reflectance models are suggested for coastal waters, to which contributions that are due to bottom reflectance, CDOM fluorescence, and water Raman scattering are included. Through the use of two parameters to model the combination of the backscattering coefficient and the Q factor, excellent agreement was achieved between the measured and modeled remote-sensing reflectance for waters from the West Florida Shelf to the Mississippi River plume. These waters cover a range of chlorophyll of 0.2-40 mg/cu m and gelbstoff absorption at 440 nm from 0.02-0.4/m. Data with a spectral resolution of 10 nm or better, which is consistent with that provided by the airborne visible and infrared imaging spectrometer (AVIRIS) and spacecraft spectrometers, were used in the model evaluation.

Lee, Zhongping↗
NASA NTRS1992

The influence of the Alaskan Gyre on the coastal circulation in the Gulf of Alaska

The circulation of the northeast Pacific Ocean and the Gulf of Alaska is simulated by means of a reduced-gravity wind-driven model to study seasonal and interannual flow variability. The circulation in the NE Pacific is discussed emphasizing its ramifications for the physical domain, equations, and boundary conditions of the numerical model. The pseudostress fields used to drive the model are based on 20 years of data from the Comprehensive Ocean-Atmosphere Data Set and are analyzed with empirical orthogonal function analysis. The monthly stresses from 1986-89 are used to drive the model, and regional oceanographic features are reproduced including the Alaskan Gyre, Coastal Current, the Sitka eddy, and a severe cyclonic eddy. Comparisons with experimental data show that the high-resolution baroclinic model is valid and demonstrates the applicability of reduced-gravity models.

Heim, Paul K., II↗
NASA NTRS2021

Impact of Spectral Resolution on Quantifying Cyanobacteria in Lakes and Reservoirs: A Machine-Learning Assessment

Cyanobacterial harmful algal blooms are an increasing threat to coastal and inland waters. These blooms can be detected using optical radiometers due to the presence of phycocyanin (PC) pigments. The spectral resolution of best-available multispectral sensors limits their ability to diagnostically detect PC in the presence of other photosynthetic pigments. To assess the role of spectral resolution in the determination of PC, a large ( N=905 ) database of colocated in situ radiometric spectra and PC are employed. We first examine the performance of selected widely used machine-learning (ML) models against that of benchmark algorithms for hyperspectral remote sensing reflectance ( R_(rs) ) spectra resampled to the spectral configuration of the Hyperspectral Imager for the Coastal Ocean (HICO) with a full-width at half-maximum (FWHM) of < 6 nm. Results show that the multilayer perceptron (MLP) neural network applied to HICO spectral configurations (median errors < 65%) outperforms other ML models. This model is subsequently applied to R_(rs) spectra resampled to the band configuration of existing satellite instruments and of the one proposed for the next Landsat sensor. These results confirm that employing MLP models to estimate PC from hyperspectral data delivers tangible improvements compared with retrievals from multispectral data and benchmark algorithms (with median errors between ∼73 % and 126%) and shows promise for developing a globally applicable cyanobacteria measurement approach.

hyperspectral↗
NASA NTRS1994

The contribution of Alaskan, Siberian, and Canadian coastal polynas to the cold halocline layer of the Arctic Ocean

Numerous Arctic Ocean circulation and geochemical studies suggest that ice growth in polynyas over the Alaskan, Siberian, and Canadian continental shelves is a source of cold, saline water which contributes to the maintenance of the Arctic Ocean halocline. The purpose of this study is to estimate for the 1978-1987 winters the contributions of Arctic coastal polynyas to the cold halocline layer of the Arctic Ocean. The study uses a combination of satellite, oceanographic, and weather data to calculate the brine fluxes from the polynyas; then an oceanic box model is used to calculate their contributions to the cold halocline layer of the Arctic Ocean. This study complements and corrects a previous study of dense water production by coastal polynyas in the Barents, Kara, and Laptev Seas.

Cavalieri, Donald J.↗
NASA NTRS2012

Spatial Variability in Column CO2 Inferred from High Resolution GEOS-5 Global Model Simulations: Implications for Remote Sensing and Inversions

Column CO2 observations from current and future remote sensing missions represent a major advancement in our understanding of the carbon cycle and are expected to help constrain source and sink distributions. However, data assimilation and inversion methods are challenged by the difference in scale of models and observations. OCO-2 footprints represent an area of several square kilometers while NASA s future ASCENDS lidar mission is likely to have an even smaller footprint. In contrast, the resolution of models used in global inversions are typically hundreds of kilometers wide and often cover areas that include combinations of land, ocean and coastal areas and areas of significant topographic, land cover, and population density variations. To improve understanding of scales of atmospheric CO2 variability and representativeness of satellite observations, we will present results from a global, 10-km simulation of meteorology and atmospheric CO2 distributions performed using NASA s GEOS-5 general circulation model. This resolution, typical of mesoscale atmospheric models, represents an order of magnitude increase in resolution over typical global simulations of atmospheric composition allowing new insight into small scale CO2 variations across a wide range of surface flux and meteorological conditions. The simulation includes high resolution flux datasets provided by NASA s Carbon Monitoring System Flux Pilot Project at half degree resolution that have been down-scaled to 10-km using remote sensing datasets. Probability distribution functions are calculated over larger areas more typical of global models (100-400 km) to characterize subgrid-scale variability in these models. Particular emphasis is placed on coastal regions and regions containing megacities and fires to evaluate the ability of coarse resolution models to represent these small scale features. Additionally, model output are sampled using averaging kernels characteristic of OCO-2 and ASCENDS measurement concepts to create realistic pseudo-datasets. Pseudo-data are averaged over coarse model grid cell areas to better understand the ability of measurements to characterize CO2 distributions and spatial gradients on both short (daily to weekly) and long (monthly to seasonal) time scales

Ott, L.↗
NASA NTRS1980

Planetary boundary-layer wind model evaluation at a mid-Atlantic coastal site

Detailed measurements of the mean flow and turbulence were made with the use of a micrometeorological facility consisting of an instrumented 76-m tall tower located within a 100-m distance from the Atlantic Ocean at Wallops Island, Virginia. Under moderately strong wind conditions, the popular neutral boundary layer flow model fails to provide an adequate description of the actual flow. In addition to detailed flow information for all wind directions, averages of the important flow parameters used for design such as vertical distribution of mean velocity, turbulence intensities and turbulence integral scales were presented for wind direction sectors with near uniform upstream terrain. Power spectra of the three velocity components for the prevailing northwesterly and southerly winds are discussed.

Tieleman, H. W.↗
NASA NTRS2008

Tide Corrections for Coastal Altimetry: Status and Prospects

Knowledge of global oceanic tides has markedly advanced over the last two decades, in no small part because of the near-global measurements provided by satellite altimeters, and especially the long and precise Topex/Poseidon time series e.g. [2]. Satellite altimetry in turn places very severe demands on the accuracy of tidal models. The reason is clear: tides are by far the largest contributor to the variance of sea-surface elevation, so any study of non-tidal ocean signals requires removal of this dominant tidal component. Efforts toward improving models for altimetric tide corrections have understandably focused on deep-water, open-ocean regions. These efforts have produced models thought to be generally accurate to about 2 cm rms. Corresponding tide predictions in shelf and near-coastal regions, however, are far less accurate. This paper discusses the status of our current abilities to provide near-global tidal predictions in shelf and near-coastal waters, highlights some of the difficulties that must be overcome, and attempts to divine a path toward some degree of progress. There are, of course, many groups worldwide who model tides over fairly localized shallow-water regions, and such work is extremely valuable for any altimeter study limited to those regions, but this paper considers the more global models necessary for the general user. There have indeed been efforts to patch local and global models together, but such work is difficult to maintain over many updates and can often encounter problems of proprietary or political nature. Such a path, however, might yet prove the most fruitful, and there are now new plans afoot to try again. As is well known, tides in shallow waters tend to be large, possibly nonlinear, and high wavenumber. The short spatial scales mean that current mapping capabilities with (multiple) nadir-oriented altimeters often yield inadequate coverage. This necessitates added reliance on numerical hydrodynamic models and data assimilation, which in turn necessitates very accurate bathymetry with high spatial resolution. Nonlinearity means that many additional compound tides and overtides must be accounted for in our predictions, which increases the degree of modeling effort and increases the amounts of data required to disentangle closely aliased tides.

Ray, Richard D.↗