Ocean Forecast Models Research Articles

Limitation of One-Dimensional Ocean Models for Coupled Hurricane–Ocean Model Forecasts

Abstract Wind stress imposed on the upper ocean by a hurricane can limit the hurricane’s intensity primarily through shear-induced mixing of the upper ocean and subsequent cooling of the sea surface. Since shear-induced mixing is a one-dimensional process, some recent studies suggest that coupling a one-dimensional ocean model to a hurricane model may be sufficient for capturing the storm-induced sea surface temperature cooling in the region providing heat energy to the hurricane. Using both a one-dimensional and a three-dimensional version of the same ocean model, it is shown here that the neglect of upwelling, which can only be captured by a three-dimensional ocean model, underestimates the storm-core sea surface cooling for hurricanes translating at <∼5 m s−1. For hurricanes translating at <2 m s−1, more than half of the storm-core sea surface cooling is neglected by the one-dimensional ocean model. Since the majority of hurricanes in the western tropical North Atlantic Ocean translate at <5 m s−1, the idealized experiments presented here suggest that one-dimensional ocean models may be inadequate for coupled hurricane–ocean model forecasting.

Improving the Ocean Initialization of Coupled Hurricane–Ocean Models Using Feature-Based Data Assimilation

Abstract Coupled hurricane–ocean forecast models require proper initialization of the ocean thermal structure. Here, a new feature-based (F-B) ocean initialization procedure in the GFDL/University of Rhode Island (URI) coupled hurricane prediction system is presented to account for spatial and temporal variability of mesoscale oceanic features in the Gulf of Mexico, including the Loop Current (LC), Loop Current eddies [i.e., warm-core rings (WCRs)], and cold-core rings (CCRs). Using only near-real-time satellite altimetry for the “SHA-assimilated” case, the LC, a single WCR, and a single CCR are assimilated into NAVOCEANO’s Global Digitized Environmental Model (GDEM) ocean temperature and salinity climatology along with satellite-derived daily sea surface temperature (SST) data from 15 September 2005 to produce a more realistic three-dimensional temperature field valid on the model initialization date (15 September 2005). For the “fully assimilated” case, both near-real-time altimetry and real-time in situ airborne XBT (AXBT) temperature profiles are assimilated into GDEM along with SST to produce the three-dimensional temperature field. Vertical profiles from the resulting SHA-assimilated and fully assimilated temperature fields are compared to 18 real-time AXBT temperature profiles, the ocean climatology (GDEM), and an alternative data-assimilated product [the daily North and Equatorial Atlantic Ocean Prediction System Best Estimate (RSMAS HYCOM), which uses an Optimal Interpolation (OI) based assimilation technique] to determine the relative accuracy of the F-B initialization procedure presented here. Also, the tropical cyclone heat potential (TCHP) from each of these profiles is calculated by integrating the oceanic heat content from the surface to the depth of the 26°C isotherm. Assuming the AXBT profiles are truth, the TCHP rms error for the F-B SHA-assimilated case, the F-B fully assimilated case, the GDEM ocean climatology, and the RSMAS HYCOM product is 12, 10, 45, and 26 kJ cm−2, respectively.

Prediction Skill of the NAO and PNA from Daily to Seasonal Time Scales

AbstractThe skill of state-of-the-art operational dynamical models in predicting the two most important modes of variability in the Northern Hemisphere extratropical atmosphere, the North Atlantic Oscillation (NAO) and Pacific–North American (PNA) teleconnection patterns, is investigated at time scales ranging from daily to seasonal. Two uncoupled atmospheric models used for deterministic forecasting in the short to medium range as well as eight fully coupled atmosphere–land–ocean forecast models used for monthly and seasonal forecasting are examined and compared.For the short to medium range, the level of forecast skill for the two indices is higher than that for the entire Northern Hemisphere extratropical flow. The forecast skill of the PNA is higher than that of the NAO. The forecast skill increases with the magnitude of the NAO and PNA indices, but the relationship is not pronounced. The probability density function (PDF) of the NAO and PNA indices is negatively skewed, in agreement with the distribution of skewness of the geopotential field. The models maintain approximately the observed PDF, including the negative skewness, for the first week.Extreme negative NAO/PNA events have larger absolute values than positive extremes in agreement with the negative skewness of the two indices. Recent large extreme events are generally well forecasted by the models.On the intraseasonal time scale it is found that both NAO and PNA have lingering forecast skill, in contrast to the Northern Hemisphere extratropical flow as a whole. This fact offers some hope for extended range forecasting, even though the skill is quite low. No conclusive positive benefit is seen from using higher horizontal resolution or coupling to the oceans.On the monthly and seasonal time scales, the level of forecast skill for the two indices is generally quite low, with the exception of winter predictions at short lead times.

Validation of a hybrid optimal interpolation and Kalman filter scheme for sea surface temperature assimilation

A hybrid data assimilation scheme designed for operational assimilation of satellite sea surface temperatures (SST) into an ocean model has been developed and validated against in-situ observations. The scheme consists of an optimal interpolation (OI) part and a greatly simplified Kalman filter (KF) part. The OI is performed only in the longitudinal and latitudinal directions. A climatological field is used as a background field for the interpolation. It is constructed by fitting daily averages of satellite SST to the annual mean, annual, and semiannual harmonics in a 20 km by 20 km grid. The background error covariance is approximated by a spatially varying two-dimensional exponential covariance model. The parameters of the covariance model are fitted to the deviations of the satellite data from the background field using data from a full year. The simplified KF uses ocean model forecasts as a background field. It is based on the assumption that it is possible to neglect horizontal SST covariances in the filter and that the typical time scale for vertical mixing in the mixed layer is much shorter than the average time between observations. We therefore assume that the error variance in a column of water is evenly spread out throughout the mixed layer. The result of these simplifications is a computationally very efficient KF. A one year validation of the scheme is performed for year 2001 using an operational eddy resolving ocean model covering the North Sea and the Baltic Sea. It is found that assimilation of sea surface temperature data reduces the model root mean square error from 1.13 °C to 0.70 °C. The hybrid scheme is found to reduce the root mean square error slightly more than the simplified KF without OI to 0.66 °C. The inclusion of spatially varying satellite error variances does not improve the performance of the scheme significantly.

Operational multivariate ocean data assimilation

AbstractA fully three‐dimensional, multivariate, optimum‐interpolation ocean data assimilation system has been developed that produces simultaneous analyses of temperature, salinity, geopotential and vector velocity. The system is run in real‐time, and can be executed as a stand‐alone analysis or cycled with an ocean forecast model in a sequential incremental update cycle. Additional capabilities have been built into the system, including flow‐dependent background‐error correlations and background‐error variances that vary in space and evolve from one analysis cycle to the next. The ocean data types assimilated include: remotely sensed sea surface temperature, sea surface height, and sea‐ice concentration; plus in situ surface and sub‐surface observations of temperature, salinity, and currents from a variety of sources, such as ships, buoys, expendable bathythermographs, conductivity–temperature–depth sensors, and profiling floats. An ocean data quality‐control system is fully integrated with the multivariate analysis, and includes feedback of forecast fields and prediction errors in the quality control of new observations. The system is operational at the US Navy oceanographic production centres both in global and in regional applications. It is being implemented as the data assimilation component of the Hybrid Coordinate Ocean Model as part of the US contribution to the Global Ocean Data Assimilation Experiment, and in a limited‐area ensemble‐based forecasting system that will be used in an adaptive sampling, targeted observation application. Copyright © 2005 Royal Meteorological Society

Simulation of ENSO in the New NCEP Coupled Forecast System Model (CFS03)

Abstract A new global coupled atmosphere–ocean forecast system model (CFS03) has recently been developed at the National Centers for Environmental Prediction (NCEP). The new coupled model consists of a T62L64 version of the operational NCEP Atmospheric Global Forecast System model and the Geophysical Fluid Dynamics Laboratory Modular Ocean Model version 3, and is expected to replace the current NCEP operational coupled seasonal forecast model. This study assesses the performance of the new coupled model in simulating El Niño–Southern Oscillation (ENSO), which is considered to be a desirable feature for models used for seasonal prediction. The diagnoses indicate that the new coupled model simulates ENSO variability with realistic frequency. The amplitude of the simulated ENSO is similar to that of the observed strong events, but the ENSO events in the simulation occur more regularly than in observations. The model correctly simulates the observed ENSO seasonal phase locking with the peak amplitude near the end of the year. On average, however, simulated warm events tend to start about 3 months earlier and persist longer than observed. The simulated ENSO is consistent with the delayed oscillator, recharge oscillator, and advective–reflective oscillator theories, suggesting that each of these mechanisms may operate at the same time during the ENSO cycle. The diagnoses of the simulation indicate that the model may be suitable for real-time prediction of ENSO.

Development of a Real-Time Regional Ocean Forecast System with Application to a Domain off the U.S. East Coast

This paper discusses the needs to establish a capability to provide real-time regional ocean forecasts and the feasibility of producing them on an operational basis. Specifically, the development of a Regional Ocean Forecast System using the Princeton Ocean Model (POM) as a prototype and its application to the East Coast of the U.S. are presented. The ocean forecasts are produced using surface forcing from the Eta model, the operational mesoscale weather prediction model at the National Centers for Environmental Prediction (NCEP). At present, the ocean forecast model, called the East Coast-Regional Ocean Forecast System (EC-ROFS) includes assimilation of sea surface temperatures from in situ and satellite data and sea surface height anomalies from satellite altimeters. Examples of forecast products, their evaluation, problems that arose during the development of the system, and solutions to some of those problems are also discussed. Even though work is still in progress to improve the performance of EC-ROFS, it became clear that the forecast products which are generated can be used by marine forecasters if allowances for known model deficiencies are taken into account. The EC-ROFS became fully operational at NCEP in March 2002, and is the first forecast system of its type to become operational in the civil sector of the United States.

Applications of satellite remote sensing in numerical weather and climate prediction

The year 2000 marks the 40 th anniversary of the launch of the first weather satellite. The images of cloud systems from the early satellites enabled forecasters to locate and monitor the movements of storms. Today's satellites provide a wealth of quantitative information about the constantly changing state of the Earth's atmosphere, ocean, and land surface. Significant strides are being made by operational centers around the world to effectively use these remotely-sensed observations in forecast models. The satellite measurements are used to initialize, provide boundary conditions for, and verify predictions of models. As an example of the state of the art, this paper reviews how satellite observations are used in the numerical weather and climate prediction models of the U.S. National Weather Service. The National Weather Service, National Centers for Environmental Prediction (NCEP), Environmental Modeling Center (EMC) develops regional and global weather prediction models, coupled ocean-atmosphere models for seasonal to interannual climate predictions, and a coastal ocean forecast model. A three dimensional variational data assimilation system is used to specify the initial conditions for the forecast models. Data from the following satellite instruments are currently used in one or more of these models: High Resolution Infrared Sounder (HIRS), Microwave Sounding Unit (MSU), Advanced Microwave Sounding Unit-A (AMSU-A), Geostationary Operational Environmental Satellites (GOES) sounder, GOES, METEOSAT, and Geostationary Meteorology Satellite (GMS) imagers, Advanced Very High Resolution Radiometer (AVHRR), Special Sensor Microwave/Imager (SSM/I), ESA Remote-sensing Satellite-2 (ERS-2) scatterometer, Solar Backscatter Ultraviolet Spectrometer/2 (SBUV/2), and Oceanic Topography Experiment (TOPEX) and ERS-2 altimeters.

The Long-term Ecosystem Observatory: an integrated coastal observatory

An integrated ocean observatory has been developed and operated in the coastal waters off the central coast of New Jersey, USA. One major goal for the Long-term Ecosystem Observatory (LEO) is to develop a real-time capability for rapid environmental assessment and physical/biological forecasting in coastal waters. To this end, observational data are collected from satellites, aircrafts, ships, fixed/relocatable moorings and autonomous underwater vehicles. The majority of the data are available in real-time allowing for adaptive sampling of episodic events and are assimilated into ocean forecast models. In this observationally rich environment, model forecast errors are dominated by uncertainties in the model physics or future boundary conditions rather than initial conditions. Therefore, ensemble forecasts with differing model parameterizations provide a unique opportunity for model refinement and validation. The system has been operated during three annual coastal predictive skill experiments from 1998 through 2000. To illustrate the capabilities of the system, case studies on coastal upwelling and small-scale biological slicks are discussed. This observatory is one part of the expanding network of ocean observatories that will form the basis of a national observation network.

Towards an Ocean Forecasting System for the Aegean Sea

A first approach towards an ocean forecasting system for the Aegean Sea is presented in this paper. The ocean forecasting component is part of the POSEIDON system which includes high resolution atmospheric and wave modeling of the Aegean Sea together with an extended network of observational buoys for the continuous monitoring of physical, biological and chemical parameters. The ocean forecast model system consists of a high-resolution (1/20° times; 1/20°) implementation of the Princeton Ocean Model (POM) forced by forecast surface fluxes of momentum, heat and freshwater provided by the regional ETA atmospheric model. The climatological runs of the model reproduce the basic features of the general circulation in the Aegean Sea. In the forecasting mode the model shows skill in forecasting the sea surface temperature (SST) phenomenology when compared with satellite-derived SST. Sensitivity tests (such as the inclusion of sea surface atmospheric pressure) have been performed in order to improve the model's n...

Frictional Formulations in Numerical Ocean Models and Their Effect on Simulated Acoustic Fields

Abstract This study has examined the effects of frictional formulations in numerical ocean models on simulated acoustic fields. Starting from the same initial state of a perturbation to a simple linear front, comparisons are made of numerically simulated frontal environments, with biharmonic and Laplacian (harmonic) friction operators, to describe subgrid-scale mixing. Using a just stable harmonic simulation as a “control” for the effects of small-scale processes (wavelength of order 10 km), comparisons of the energetics and spectra of the simulated environments have confirmed the effect of biharmonic friction in suppressing small-scale motion while maintaining the mesoscale. However, a new result concerns the impact of this scale selectivity on simulated underwater acoustic fields and the possible consequences of this for ocean forecast models and acoustic tomography applications. Acoustic effects have been quantified in terms of the differences in predicted sound intensity levels between harmonic and bi...

Three-dimensional acoustic mode propagation in the Gulf Stream

Based on the coupled mode theory, an efficient 3-D (i.e., three-dimensional) acoustic code for the computation of sound propagation through mesoscale ocean features was developed. The technique numerically integrates a set of first-order differential equations governing the complex envelopes that modulate, mode by mode, the adiabatic mode solution. Sensitivity studies showed that the slowly varying envelopes associated with the forward propagating components can be computed accurately using a step size much longer than the acoustic wavelength. Calculations further showed that the backscattered field is negligible even in frontal systems having extremely large sound-speed gradients. Gulf Stream sound-speed fields generated by a Harvard University ocean forecast model were used to investigate the three-dimensional environmental effects on sound propagation, both cross and along stream. In order to examine the significance of horizontal sound diffraction, the 3-D solution was compared to the N by 2-D solution. Comparison between the 3-D coupled mode and adiabatic approximation calculations was also made in an effort to quantify the validity of the adiabatic approximation.