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Impact of the Incremental Analysis Updates on a Real-Time System of the North Atlantic Ocean

M. BenkiranCLS/DOS/OO, Ramonville Saint Agne, France

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E. GreinerCLS/DOS/OO, Ramonville Saint Agne, France

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Abstract

Incremental analysis updates (IAUs) are a procedure by which analysis increments can be incorporated into a model hindcast and forecast in a smooth manner. It is similar to nudging but has a better response, particularly in regions of missing data. The IAU procedure was popular in the late 1990s in weather forecasting centers, because it acts as a low-pass filter. The impact of the IAU is examined in the context of a real-time, eddy-permitting ocean forecasting system in the North Atlantic from Mercator Océan. Forecast scores and ocean physics are compared for the following three companion runs: a forced mode, a sequential analysis, and IAU. These comparisons confirm that the IAU is beneficial because it removes spinup effects such as spurious waves and tropical convective cells. Forecast scores are also slightly improved. In addition, contrary to the weather forecasting case where the model and data are fairly unbiased, the IAU has the advantage of correcting the systematic biases in the ocean data assimilation system.

Corresponding author address: Dr. Eric Greiner, CLS/DOS/OO, 8-10 Rue Hermes, Parc Technologique du Canal, 31526 Ramonville Saint Agne, France. Email: eric.greiner@cls.fr

Abstract

Incremental analysis updates (IAUs) are a procedure by which analysis increments can be incorporated into a model hindcast and forecast in a smooth manner. It is similar to nudging but has a better response, particularly in regions of missing data. The IAU procedure was popular in the late 1990s in weather forecasting centers, because it acts as a low-pass filter. The impact of the IAU is examined in the context of a real-time, eddy-permitting ocean forecasting system in the North Atlantic from Mercator Océan. Forecast scores and ocean physics are compared for the following three companion runs: a forced mode, a sequential analysis, and IAU. These comparisons confirm that the IAU is beneficial because it removes spinup effects such as spurious waves and tropical convective cells. Forecast scores are also slightly improved. In addition, contrary to the weather forecasting case where the model and data are fairly unbiased, the IAU has the advantage of correcting the systematic biases in the ocean data assimilation system.

Corresponding author address: Dr. Eric Greiner, CLS/DOS/OO, 8-10 Rue Hermes, Parc Technologique du Canal, 31526 Ramonville Saint Agne, France. Email: eric.greiner@cls.fr

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