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James A. Carton, Gennady Chepurin, and Xianhe Cao

Abstract

The authors explore the accuracy of a comprehensive 46-year retrospective analysis of upper-ocean temperature, salinity, and currents. The Simple Ocean Data Assimilation (SODA) analysis is global, spanning the latitude range 62°S–62°N. The SODA analysis has been constructed using optimal interpolation data assimilation combining numerical model forecasts with temperature and salinity profiles (MBT, XBT, CTD, and station), sea surface temperature, and altimeter sea level. To determine the accuracy of the analysis, the authors present a series of comparisons to independent observations at interannual and longer timescales and examine the structure of well-known climate features such as the annual cycle, El Niño, and the Pacific–North American (PNA) anomaly pattern.

A comparison to tide-gauge time series records shows that 25%–35% of the variance is explained by the analysis. Part of the variance that is not explained is due to unresolved mesoscale phenomena. Another part is due to errors in the rate of water mass formation and errors in salinity estimates. Comparisons are presented to altimeter sea level, WOCE global hydrographic sections, and to moored and surface drifter velocity. The results of these comparisons are quite encouraging. The differences are largest in the eddy production regions of the western boundary currents and the Antarctic Circumpolar Current. The differences are generally smaller in the Tropics, although the major equatorial currents are too broad and weak.

The strongest basin-scale signal at interannual periods is associated with El Niño. Examination of the zero-lag correlation of global heat content shows the eastern and western tropical Pacific to be out of phase (correlation −0.4 to −0.6). The eastern Indian Ocean is in phase with the western Pacific and thus is out of phase with the eastern Pacific. The North Pacific has a weak positive correlation with the eastern equatorial Pacific. Correlations between eastern Pacific heat content and Atlantic heat content at interannual periods are modest. At longer decadal periods the PNA wind pattern leads to broad patterns of correlation in heat content variability. Increases in heat content in the central North Pacific are associated with decreases in heat content in the subtropical Pacific and increases in the western tropical Pacific. Atlantic heat content is positively correlated with the central North Pacific.

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James A. Carton, Gennady A. Chepurin, and Ligang Chen

Abstract

This paper describes version 3 of the Simple Ocean Data Assimilation (SODA3) ocean reanalysis with enhancements to model resolution, observation, and forcing datasets, and the addition of active sea ice. SODA3 relies on the ocean component of the NOAA/Geophysical Fluid Dynamics Laboratory CM2.5 coupled model with nominal ¼° resolution. A scheme has also been implemented to reduce bias in the surface fluxes. A 37-yr-long ocean reanalysis, SODA3.4.2, created using this new SODA3 system is compared to the previous generation of SODA (SODA2.2.4) as well as to the Hadley Centre EN4.1.1 no-model statistical objective analysis. The comparison is carried out in the tropics, the midlatitudes, and the Arctic and includes examinations of the meridional overturning circulation in the Atlantic. The comparison shows that SODA3.4.2 has reduced systematic errors to a level comparable to those of the no-model statistical objective analysis in the upper ocean. The accuracy of variability has been improved particularly poleward of the tropics, with the greatest improvements seen in the Arctic, accompanying a substantial reduction in surface net heat and freshwater flux bias. These improvements justify increasing use of ocean reanalysis for climate studies including the higher latitudes.

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Gennady A. Chepurin, James A. Carton, and Dick Dee

Abstract

Numerical models of ocean circulation are subject to systematic errors resulting from errors in model physics, numerics, inaccurately specified initial conditions, and errors in surface forcing. In addition to a time-mean component, the systematic errors include components that are time varying, which could result, for example, from inaccuracies in the time-varying forcing. Despite their importance, most assimilation algorithms incorrectly assume that the forecast model is unbiased. In this paper the authors characterize the bias for a current assimilation scheme in the tropical Pacific. The characterization is used to show how relatively simple empirical bias forecast models may be used in a two-stage bias correction procedure to improve the quality of the analysis.

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James A. Carton, Gennady Chepurin, Xianhe Cao, and Benjamin Giese

Abstract

The authors describe a 46-year global retrospective analysis of upper-ocean temperature, salinity, and currents. The analysis is an application of the Simple Ocean Data Assimilation (SODA) package. SODA uses an ocean model based on Geophysical Fluid Dynamics Laboratory MOM2 physics. Assimilated data includes temperature and salinity profiles from the World Ocean Atlas-94 (MBT, XBT, CTD, and station data), as well as additional hydrography, sea surface temperature, and altimeter sea level.

After reviewing the basic methodology the authors present experiments to examine the impact of trends in the wind field and model forecast bias (referred to in the engineering literature as “colored noise”). The authors believe these to be the major sources of error in the retrospective analysis. With detrended winds the analysis shows a pattern of warming in the subtropics and cooling in the Tropics and at high latitudes. Model forecast bias results partly from errors in surface forcing and partly from limitations of the model. Bias is of great concern in regions of thermocline water-mass formation. In the examples discussed here, the data assimilation has the effect of increasing production of these water masses and thus reducing bias.

Additional experiments examine the relative importance of winds versus subsurface updating. These experiments show that in the Tropics both winds and subsurface updating contribute to analysis temperature, while in midlatitudes the variability results mainly from the effects of subsurface updating.

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Benjamin S. Giese, Gennady A. Chepurin, James A. Carton, Tim P. Boyer, and Howard F. Seidel

Abstract

Historical bathythermograph datasets are known to be biased, and there have been several efforts to model this bias. Three different correction models of temperature bias in the historical bathythermograph dataset are compared here: the steady model of Hanawa et al. and the time-dependent models of Levitus et al. and Wijffels et al. The impact of these different models is examined in the context of global analysis experiments using the Simple Ocean Data Assimilation system. The results show that the two time-dependent bias models significantly reduce warm bias in global heat content, notably in the 10 years starting in the early 1970s and again in the early 1990s. Overall, the Levitus et al. model has its greatest impact near the surface and the Wijffels et al. model has its greatest impact at subtropical thermocline depths. Examination of the vertical structure of temperature error shows that at thermocline depths the Wijffels et al. model overcompensates, leading to a slight cool bias, while at shallow levels the same model causes a slight warm bias in the central and eastern subtropics and at thermocline depths on the equator in the Pacific Ocean as a result of reduced vertical entrainment. The results also show that the bias-correction models may alter the representation of interannual variability. During the 1997/98 El Niño and the subsequent La Niña the Levitus et al. model, which has its main impact at shallow depths, reduces the 50-m temperature anomalies in the eastern equatorial Pacific by 10%–20% and strengthens the zonal currents by up to 50%. The Wijffels et al. correction, which has its main impact at deeper levels, has much less effect on the oceanic expression of ENSO.

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