Abstract
Global ocean forecast systems, developed under the Global Ocean Data Assimilation Experiment (GODAE), are a powerful means of assessing the impact of different components of the Global Ocean Observing System (GOOS). Using a range of analysis tools and approaches, GODAE systems are useful for quantifying the impact of different observation types on the quality of analyses and forecasts. This assessment includes both existing and future observation platforms. Many important conclusions can be drawn from these studies. It is clear that altimeter data are extremely important for constraining mesoscale variability in ocean forecast systems. The number of altimeters is also important. For example, near-real-time applications need data from four altimeters to achieve skill that is similar to systems using data from two altimeters in delayed mode. Another important result is that sea surface temperature is the only observation parameter that adequately monitors ocean properties in coastal regions and shallow seas. Assimilation of Argo data provides a significant, measurable improvement to GODAE systems, and is the only observation platform that provides global-scale information for constraining salinity. The complementary nature of different components of GOOS is now clear and the emergence of new assimilation techniques for observing system evaluation provides the GODAE community with a practical path toward routine GOOS monitoring.
Highlights
The impact of each observation type may strongly depend on the details of the model into which they are assimilated, the method of assimilation, and the errors assumed at the assimilation step
The inaugural Ocean Observing Panel for Climate (OOPC)-Global Ocean Data Assimilation Experiment (GODAE) meeting on Observing System Simulation Experiments (OSSEs) and Observing System Experiments (OSEs) was held at UNESCO/IOC in Paris, France, in November 2007
Altimetry is the only observation type that even comes close to constraining mesoscale ocean circulation, and Argo observations are the only observation type that constrains subsurface temperature and salinity. These results indicate that while there is some redundancy for representing broadscale circulation, all observation types are required for constraining mesoscale circulation models
Summary
The OSEs using the UK Met Office system are evaluated against data from independent drifting buoys, and produce correlation coefficients between the forecast and drifterderived near-surface velocity of about 0.16, 0.26, and 0.30 when data from zero, one, and three altimeters, respectively, are assimilated These results indicate that for both the Mercator Océan and UK Met Office systems, the addition of the first altimeter has the greatest impact on forecast skill—and there are diminishing returns from each additional altimeter. The difference in the quality and coverage of near-real-time (NRT) and delayed-time (DT) altimeter data can be significant and is as important as the number of altimeters These differences impact the accuracy of analysis products that use altimeter data because of the different orbit errors, data latency, and the use of asymmetrical observation windows that necessarily favor “old” data for NRT systems. These results indicate that while there is some redundancy for representing broadscale circulation, all observation types are required for constraining mesoscale circulation models
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