Gary B. Brassington

The Southwest Pacific Ocean circulation and climate experiment (SPICE)

The Southwest Pacific Ocean Circulation and Climate Experiment (SPICE) is an international research program under the auspices of CLIVAR. The key objectives are to understand the Southwest Pacific Ocean circulation and the South Pacific Convergence Zone (SPCZ) dynamics, as well as their influence on regional and basin-scale climate patterns. South Pacific thermocline waters are transported in the westward flowing South Equatorial Current (SEC) toward Australia and Papua-New Guinea. On its way, the SEC encounters the numerous islands and straits of the Southwest Pacific and forms boundary currents and jets that eventually redistribute water to the equator and high latitudes. The transit in the Coral, Solomon, and Tasman Seas is of great importance to the climate system because changes in either the temperature or the amount of water arriving at the equator have the capability to modulate the El Nino-Southern Oscillation, while the southward transports influence the climate and biodiversity in the Tasman Sea. After 7 years of substantial in situ oceanic observational and modeling efforts, our understanding of the region has much improved. We have a refined description of the SPCZ behavior, boundary currents, pathways, and water mass transformation, including the previously undocumented Solomon Sea. The transports are large and vary substantially in a counter-intuitive way, with asymmetries and gating effects that depend on time scales. This paper provides a review of recent advancements and discusses our current knowledge gaps and important emerging research directions.

Adaptive nonlinear dynamical initialization

[1] An adaptive nonlinear initialization scheme is presented that provides improvements over linear relaxation methods for approaching the target state while minimizing discontinuities in dynamical models. The method adds an adaptive nonlinear forcing term to the model equations that is a function of the difference between the model field and its target value. A new feature is that the amplitude of the forcing is nonlinearly adapted to the size of the difference, allowing for stronger relaxation where differences are large and weaker relaxation where differences are small. We find that the function leads to more optimal introduction of new information by working hardest at the beginning of the initialization period while converging toward a steady condition for the majority of the domain at the end of the initialization period. Experiments with a limited area ocean model, with different dynamical regimes, show that the adaptive scheme leads to less shock than standard linear approaches and permits the model to converge to a state away from the target field if the target is not a priori dynamically balanced. Results indicate that the method has the potential to lower forecast error. This suggests that it will have a broad range of applications in dynamical prediction systems.

Ocean data assimilation: a case for ensemble optimal interpolation

The Bluelink forecast and reanalysis system is comprised of a high resolution ocean general circulation model and an ensemble optimal interpolation (EnOI) system. The Bluelink system has been integrated for a series of 15-year reanalyses and is run operationally at the Bureau of Meteorology to produce short-range ocean forecasts. This system has performed robustly, demonstrating reliable skill that is comparable to other ocean forecast systems around the world. One of the key components of Bluelink is the EnOI system. This system has proved to be a valuable and flexible tool for both operational and research applications. Drawing on Bluelink outcomes and a series of experiments with simple models, a case for using EnOI for ocean data assimilation is made. This includes a discussion of the benefits of EnOI as well as its known limitations. EnOI is robust, flexible, portable and inexpensive, and is not burdened with the technical difficulties that some other methods carry. EnOI is readily applied for coupled data assimilation and may be an appropriate choice for coupled forecast systems.

Assessing the impact of observations on ocean forecasts and reanalyses: Part 2, Regional applications

The value of global (e.g. altimetry, satellite sea-surface temperature, Argo) and regional (e.g. radars, gliders, instrumented mammals, airborne profiles and biogeochemical) observation-types for monitoring the mesoscale ocean circulation and biogeochemistry is demonstrated using a suite of global and regional prediction systems and remotely-sensed data. A range of techniques is used to demonstrate the value of different observation-types to regional systems and the benefit of high-resolution and adaptive sampling for monitoring the mesoscale circulation. The techniques include Observing System Experiments, Observing System Simulation Experiments, adjoint sensitivities, representer matrix spectrum, observation footprints and spectral analysis. It is shown that local errors in global and basin-scale systems can be significantly reduced when assimilating observations from regional observing systems.

Status and future of global and regional ocean prediction systems

Operational evolution of global and regional ocean forecasting systems has been extremely significant in recent years. Global Ocean Data Assimilation Experiment (GODAE) Oceanview supports the national research groups providing them with coordination and sharing expertise among the partners. Several systems have been set up and developed pre-operationally, and the majority of these are now fully operational; at the present time, they provide medium- and long-term forecasts of the most relevant ocean physical variables. These systems are based on ocean general circulation models and data-assimilation techniques that are able to correct the model with the information inferred from different types of observations. A few systems also incorporate a biogeochemical component coupled with the physical system, while others are based on coupled ocean–wave–ice–atmosphere models. The products are routinely validated with observations in order to assess their quality. Data and product implementation and organization, as well as service, for users have been well tried and tested, and most of the products are now available to users. The interaction with different users is an important factor in the development process. This paper provides a synthetic overview of the GODAE OceanView prediction systems.

RAMSSA - An operational, high-resolution, Regional Australian Multi-Sensor Sea surface temperature Analysis over the Australian region

An operational, high-resolution, Regional Australian Multi-Sensor Sea surface temperature Analysis (RAMSSA) system has been developed at the Australian Bureau of Meteorology as part of the BLUElink Ocean Forecasting Australia project. The pre-existing operational, 1/4° resolution, regional sea surface temperature (SST) analysis system has been modified to produce 1/12° resolution, daily SST analyses over the Australian region (20°N–70°S, 60°E–170°W). The new RAMSSA system combines SST data from infrared and microwave sensors on polar-orbiting satellites with in situ measurements to produce daily ‘foundation’ SST estimates, free of nocturnal cooling and diurnal warming effects. The RAMSSA analyses exhibited significantly less standard deviation than the pre-existing regional SST analyses when compared with independent buoy SST observations for the period 1 October 2007 to 31 March 2008 (0.42 °C compared with 0.55 °C) and agreed closely with those from daily foundation SST analyses produced by the UK Met Office and Ifremer using similar data sources (0.39 °C and 0.49 °C, respectively). The major differences between RAMSSA and these other foundation SST analyses relate to RAMSSA’s method for creating super-observations and assigning weights to the various input data streams, and Ifremer and the Met Office analysis systems’ bias-correction of all satellite input data using SST data from the Advanced Along Track Scanning Radiometer (AATSR). The lack of bias-correction of data input into RAMSSA has minimal effect north of 40°S where RAMSSA is on average within ±0.07 °C of other multi-sensor SST analyses. South of 40°S, RAMSSA is on average 0.09 °C to 0.25 °C warmer than bias-corrected analyses studied, mainly due to systematic biases over this region in satellite SST data streams from the Advanced Very High Resolution Radiometer (AVHRR) and Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E) input into the analyses.

Status and future of data assimilation in operational oceanography

The GODAE OceanView systems use various data assimilation algorithms, including 3DVar, EnOI, EnKF and the SEEK filter with a fixed basis, using different time windows. The main outputs of the operational data assimilation systems, the increments, have been compared for February 2014 in various regions. The eddy-permitting systems’ increments are similar in a number of the regions, indicating similar forecast errors are being corrected, while the eddy-resolving systems represent smaller-scale structures in the mid-latitude regions investigated and appear to have smaller biases. Monthly average temperature increments show significant SST biases, particularly in the systems which assimilate swath satellite SST data, indicating systematic errors in the surface heat fluxes and the way in which they are propagated vertically by the ocean models. On-going developments to the data assimilation systems include improvements to the specification of error covariances, improving assimilation of data near the equator, and understanding the effect of assimilation on the Atlantic Meridional Overturning Circulation. Longer term developments are expected to include the implementation of more advanced algorithms to make use of flow-dependent error covariance information. Assimilation of new data sources over the coming years, such as wide-swath altimetry, is also expected to improve the accuracy of ocean state estimates and forecasts provided by the GODAE OceanView systems.

Precipitation changes due to the introduction of eddy-resolved sea surface temperatures into simulations of the “Pasha Bulker” Australian east coast low of June 2007

Weather research and forecast (WRF) model simulations are used to investigate how the distribution of precipitation is related to the distribution of sea surface temperatures (SSTs) during the life cycle of the Australian east coast low of 7–9 June 2007. The focus is placed on investigating changes caused by the introduction of complex ocean eddy and filament structures present in the Bluelink ReANalysis (BRAN) SST data set. In the simulations, enhancement of rainfall is found over and downwind of warmer SSTs and suppression of rainfall over and downwind of cooler SSTs. Specifically, a large warm eddy present during this case is associated with an enhancement of rainfall along its downwind (southern) flank where a strong SST gradient exists. Overall, the model demonstrates considerable skill in simulating the event, although the simulated main rainband propagates southward earlier than observed. However, the maximum one hourly rainfall totals at the stations that received the greatest rainfall are greater and closer to the observed maxima when the BRAN SSTs are used. Global position and tracking system lightning data are overlaid on maps of SST and used to investigate whether a thunderstorm–SST relationship is discernable. An ensemble of WRF simulations is used to establish what atmospheric changes contribute to the observed distributions of thunderstorms. It is concluded that the complex upper ocean heat content structure present during this case significantly influenced the storm’s impact. Therefore, an accurate eddy resolving SST data set may be important for accurate forecasts of future storms of similar nature.

Recent progress in performance evaluations and near real-time assessment of operational ocean products

Operational ocean forecast systems provide routine marine products to an ever-widening community of users and stakeholders. The majority of users need information about the quality and reliability of the products to exploit them fully. Hence, forecast centres have been developing improved methods for evaluating and communicating the quality of their products. Global Ocean Data Assimilation Experiment (GODAE) OceanView, along with the Copernicus European Marine Core Service and other national and international programmes, has facilitated the development of coordinated validation activities among these centres. New metrics, assessing a wider range of ocean parameters, have been defined and implemented in real-time. An overview of recent progress and emerging international standards is presented here.

Progress and challenges in short- to medium-range coupled prediction

The availability of GODAE Oceanview-type ocean forecast systems provides the opportunity to develop high-resolution, short- to medium-range coupled prediction systems. Several groups have undertaken the first experiments based on relatively unsophisticated approaches. Progress is being driven at the institutional level targeting a range of applications that represent their respective national interests with clear overlaps and opportunities for information exchange and collaboration. The applications include forecasting of the general circulation, hurricanes, extra-tropical storms, high-latitude weather and coastal air–sea interaction. In some cases, research has moved beyond case and sensitivity studies to controlled experiments to obtain statistically significant metrics and operational predictions.