A Reanalysis of Ocean Climate Using Simple Ocean Data Assimilation (SODA)

2008 ◽  
Vol 136 (8) ◽  
pp. 2999-3017 ◽  
Author(s):  
James A. Carton ◽  
Benjamin S. Giese
Keyword(s):  
Data Assimilation ◽  
Interannual Variability ◽  
General Circulation ◽  
Heat Content ◽  
Circulation Model ◽  
Surface Boundary ◽  
Model Forecast ◽  
Simple Ocean Data Assimilation ◽  
Ocean Climate ◽  
Ocean Data Assimilation

Abstract This paper describes the Simple Ocean Data Assimilation (SODA) reanalysis of ocean climate variability. In the assimilation, a model forecast produced by an ocean general circulation model with an average resolution of 0.25° × 0.4° × 40 levels is continuously corrected by contemporaneous observations with corrections estimated every 10 days. The basic reanalysis, SODA 1.4.2, spans the 44-yr period from 1958 to 2001, which complements the span of the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis (ERA-40). The observation set for this experiment includes the historical archive of hydrographic profiles supplemented by ship intake measurements, moored hydrographic observations, and remotely sensed SST. A parallel run, SODA 1.4.0, is forced with identical surface boundary conditions, but without data assimilation. The new reanalysis represents a significant improvement over a previously published version of the SODA algorithm. In particular, eddy kinetic energy and sea level variability are much larger than in previous versions and are more similar to estimates from independent observations. One issue addressed in this paper is the relative importance of the model forecast versus the observations for the analysis. The results show that at near-annual frequencies the forecast model has a strong influence, whereas at decadal frequencies the observations become increasingly dominant in the analysis. As a consequence, interannual variability in SODA 1.4.2 closely resembles interannual variability in SODA 1.4.0. However, decadal anomalies of the 0–700-m heat content from SODA 1.4.2 more closely resemble heat content anomalies based on observations.

On the Accuracy of the Simple Ocean Data Assimilation Analysis for Estimating Heat Budgets of the Near-Surface Arabian Sea and Bay of Bengal*

2005 ◽  
Vol 35 (3) ◽  
pp. 395-400 ◽  
Author(s):  
S S C. Shenoi ◽  
D. Shankar ◽  
S. R. Shetye
Keyword(s):  
Data Assimilation ◽  
Bay Of Bengal ◽  
Arabian Sea ◽  
Heat Budget ◽  
Heat Content ◽  
Heat Fluxes ◽  
Simple Ocean Data Assimilation ◽  
Near Surface ◽  
Surface Heat Fluxes ◽  
Ocean Data Assimilation

Abstract The accuracy of data from the Simple Ocean Data Assimilation (SODA) model for estimating the heat budget of the upper ocean is tested in the Arabian Sea and the Bay of Bengal. SODA is able to reproduce the changes in heat content when they are forced more by the winds, as in wind-forced mixing, upwelling, and advection, but not when they are forced exclusively by surface heat fluxes, as in the warming before the summer monsoon.

Global Decadal Upper-Ocean Heat Content as Viewed in Nine Analyses

2008 ◽  
Vol 21 (22) ◽  
pp. 6015-6035 ◽  
Author(s):  
James A. Carton ◽  
Anthony Santorelli
Keyword(s):  
Data Assimilation ◽  
North Atlantic ◽  
General Circulation ◽  
Heat Content ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Global Ocean ◽  
Warm Bias ◽  
The North ◽  
Ocean General Circulation

Abstract This paper examines nine analyses of global ocean 0-/700-m temperature and heat content during the 43-yr period of warming, 1960–2002. Among the analyses are two that are independent of any numerical model, six that rely on sequential data assimilation, including an ocean general circulation model, and one that uses four-dimensional variational data assimilation (4DVAR), including an ocean general circulation model and its adjoint. Most analyses show gradual warming of the global ocean with an ensemble trend of 0.77 × 108 J m−2 (10 yr)−1 (=0.24 W m−2) as the result of rapid warming in the early 1970s and again beginning around 1990. One proposed explanation for these variations is the effect of volcanic eruptions in 1963 and 1982. Examination of this hypothesis suggests that while there is an oceanic signal, it is insufficient to explain the observed heat content variations. A second potential cause of decadal variations in global heat content is the uncorrelated contribution of heat content variations in individual ocean basins. The subtropical North Atlantic is warming at twice the global average, with accelerated warming in the 1960s and again beginning in the late 1980s and extending through the end of the record. The Barents Sea region of the Arctic Ocean and the Gulf of Mexico have also warmed, while the western subpolar North Atlantic has cooled. Heat content variability in the North Pacific differs significantly from the North Atlantic. There the spatial and temporal patterns are consistent with the decadal variability previously identified through observational and modeling studies examining SST and surface winds. In the Southern Hemisphere large heat content anomalies are evident, and while there is substantial disagreement among analyses on average the band of latitudes at 30°–60°S contribute significantly to the global warming trend. Thus, the uncorrelated contributions of heat content variations in the individual basins are a major contributor to global heat content variations. A third potential contributor to global heat content variations is the effect of time-dependent bias in the set of historical observations. This last possibility is examined by comparing the analyses to the unbiased salinity–temperature–depth dataset and finding a very substantial warm bias in all analyses in the 1970s relative to the latter decades. This warm bias may well explain the rapid increase in analysis heat content in the early 1970s, but not the more recent increase, which began in the early 1990s. Finally, this study provides information about the similarities and differences between analyses that are independent of a model and those that use sequential assimilation and 4DVAR. The comparisons provide considerable encouragement for the use of the sequential analyses for climate research despite the presence of erroneous variability (also present in the no-model analyses) resulting from instrument bias. The strengths and weaknesses of each analysis need to be considered for a given application.

Application of Coupled Bred Vectors to Seasonal-to-Interannual Forecasting and Ocean Data Assimilation

2009 ◽  
Vol 22 (11) ◽  
pp. 2850-2870 ◽  
Author(s):  
Shu-Chih Yang ◽  
Christian Keppenne ◽  
Michele Rienecker ◽  
Eugenia Kalnay
Keyword(s):  
Data Assimilation ◽  
General Circulation ◽  
Coupled Model ◽  
Circulation Model ◽  
Model Errors ◽  
Background Error ◽  
Salinity Field ◽  
Ocean Data Assimilation ◽  
Bred Vectors ◽  
The Impact

Abstract Coupled bred vectors (BVs) generated from the NASA Global Modeling and Assimilation Office (GMAO) coupled general circulation model are designed to capture the uncertainties related to slowly varying coupled instabilities. Two applications of the BVs are investigated in this study. First, the coupled BVs are used as initial perturbations for ensemble-forecasting purposes. Results show that the seasonal-to-interannual variability forecast skill can be improved when the oceanic and atmospheric perturbations are initialized with coupled BVs. The impact is particularly significant when the forecasts are initialized from the cold phase of tropical Pacific SST (e.g., August and November), because at these times the early coupled model errors, not accounted for in the BVs, are small. Second, the structure of the BVs is applied to construct hybrid background error covariances carrying flow-dependent information for the ocean data assimilation. Results show that the accuracy of the ocean analyses is improved when Gaussian background covariances are supplemented with a term obtained from the BVs. The improvement is especially noticeable for the salinity field.

scholarly journals Assessment of Several Ocean Reanalyzes about North Equatorial Current at 160° E

2020 ◽  
Vol 8 (9) ◽  
pp. 648
Author(s):  
Jiahao Wang ◽  
Kefeng Mao ◽  
Xi Chen
Keyword(s):  
Data Assimilation ◽  
General Circulation ◽  
Single Point ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Ocean Model ◽  
North Equatorial Current ◽  
Satellite Measurement ◽  
Ocean Data Assimilation ◽  
Equatorial Current

Three ocean reanalyzes including Simple Ocean Data Assimilation (SODA), Hybrid Coordinate Ocean Model, and the Navy Coupled Ocean Data Assimilation (HYCOM+NCODA) analysis, and the Ocean General Circulation Model for the Earth Simulator (OFES) are assessed about their ability of depicting the structure of North Equatorial Current (NEC) at 160° E. We found that these products could reflect the structure of NEC relatively well at the whole section, but not at the single point through comparing their results with mooring and cruising measurement, and the OFES is the best choice to study mesoscale processes versus the other two reanalyzes through comparing their results with satellite measurement.

Balanced Ocean-Data Assimilation near the Equator

2002 ◽  
Vol 32 (9) ◽  
pp. 2509-2519 ◽  
Author(s):  
Gerrit Burgers ◽  
Magdalena A. Balmaseda ◽  
Femke C. Vossepoel ◽  
Geert Jan van Oldenborgh ◽  
Peter Jan van Leeuwen
Keyword(s):  
Data Assimilation ◽  
Shallow Water ◽  
General Circulation ◽  
General Circulation Models ◽  
Density Field ◽  
Water Model ◽  
Optimal Interpolation ◽  
Shallow Water Model ◽  
Ocean Data Assimilation ◽  
Zonal Velocity

Abstract The question is addressed whether using unbalanced updates in ocean-data assimilation schemes for seasonal forecasting systems can result in a relatively poor simulation of zonal currents. An assimilation scheme, where temperature observations are used for updating only the density field, is compared to a scheme where updates of density field and zonal velocities are related by geostrophic balance. This is done for an equatorial linear shallow-water model. It is found that equatorial zonal velocities can be detoriated if velocity is not updated in the assimilation procedure. Adding balanced updates to the zonal velocity is shown to be a simple remedy for the shallow-water model. Next, optimal interpolation (OI) schemes with balanced updates of the zonal velocity are implemented in two ocean general circulation models. First tests indicate a beneficial impact on equatorial upper-ocean zonal currents.

scholarly journals Coupled Ocean–Atmosphere Response to Seasonal Modulation of Ocean Color: Impact on Interannual Climate Simulations in the Tropical Pacific

2007 ◽  
Vol 20 (2) ◽  
pp. 353-374 ◽  
Author(s):  
J. Ballabrera-Poy ◽  
R. Murtugudde ◽  
R-H. Zhang ◽  
A. J. Busalacchi
Keyword(s):  
Solar Radiation ◽  
Interannual Variability ◽  
Seasonal Cycle ◽  
General Circulation ◽  
Ocean Color ◽  
Circulation Model ◽  
Enso Events ◽  
Ocean Atmosphere ◽  
Atmosphere Model ◽  
The Impact

Abstract The ability to use remotely sensed ocean color data to parameterize biogenic heating in a coupled ocean–atmosphere model is investigated. The model used is a hybrid coupled model recently developed at the Earth System Science Interdisciplinary Center (ESSIC) by coupling an ocean general circulation model with a statistical atmosphere model for wind stress anomalies. The impact of the seasonal cycle of water turbidity on the annual mean, seasonal cycle, and interannual variability of the coupled system is investigated using three simulations differing in the parameterization of the vertical attenuation of downwelling solar radiation: (i) a control simulation using a constant 17-m attenuation depth, (ii) a simulation with the spatially varying annual mean of the satellite-derived attenuation depth, and (iii) a simulation accounting for the seasonal cycle of the attenuation depth. The results indicate that a more realistic attenuation of solar radiation slightly reduces the cold bias of the model. While a realistic attenuation of solar radiation hardly affects the annual mean and the seasonal cycle due to anomaly coupling, it significantly affects the interannual variability, especially when the seasonal cycle of the attenuation depth is used. The seasonal cycle of the attenuation depth interacts with the low-frequency equatorial dynamics to enhance warm and cold anomalies, which are further amplified via positive air–sea feedbacks. These results also indicate that interannual variability of the attenuation depths is required to capture the asymmetric biological feedbacks during cold and warm ENSO events.

scholarly journals Impact of an observational time window on coupled data assimilation: simulation with a simple climate model

2017 ◽  
Vol 24 (4) ◽  
pp. 681-694 ◽  
Author(s):  
Yuxin Zhao ◽  
Xiong Deng ◽  
Shaoqing Zhang ◽  
Zhengyu Liu ◽  
Chang Liu ◽  
...  
Keyword(s):  
Data Assimilation ◽  
General Circulation ◽  
Climate Model ◽  
Time Window ◽  
Coupled Model ◽  
Circulation Model ◽  
Scale Interactions ◽  
Climate Signals ◽  
Coupled Data Assimilation ◽  
Climate Analysis

Abstract. Climate signals are the results of interactions of multiple timescale media such as the atmosphere and ocean in the coupled earth system. Coupled data assimilation (CDA) pursues balanced and coherent climate analysis and prediction initialization by incorporating observations from multiple media into a coupled model. In practice, an observational time window (OTW) is usually used to collect measured data for an assimilation cycle to increase observational samples that are sequentially assimilated with their original error scales. Given different timescales of characteristic variability in different media, what are the optimal OTWs for the coupled media so that climate signals can be most accurately recovered by CDA? With a simple coupled model that simulates typical scale interactions in the climate system and twin CDA experiments, we address this issue here. Results show that in each coupled medium, an optimal OTW can provide maximal observational information that best fits the characteristic variability of the medium during the data blending process. Maintaining correct scale interactions, the resulting CDA improves the analysis of climate signals greatly. These simple model results provide a guideline for when the real observations are assimilated into a coupled general circulation model for improving climate analysis and prediction initialization by accurately recovering important characteristic variability such as sub-diurnal in the atmosphere and diurnal in the ocean.

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