Coupled Data Assimilation and Ensemble Initialization with Application to Multiyear ENSO Prediction

2019 ◽  
Vol 32 (4) ◽  
pp. 997-1024 ◽  
Author(s):  
Terence J. O’Kane ◽  
Paul A. Sandery ◽  
Didier P. Monselesan ◽  
Pavel Sakov ◽  
Matthew A. Chamberlain ◽  
...  
Keyword(s):  
Data Assimilation ◽  
General Circulation ◽  
Circulation Model ◽  
Sea Surface ◽  
Optimal Interpolation ◽  
Tropical Ocean ◽  
Enso Prediction ◽  
Bred Vectors ◽  
Coupled Data Assimilation ◽  
The Impact

We develop and compare variants of coupled data assimilation (DA) systems based on ensemble optimal interpolation (EnOI) and ensemble transform Kalman filter (ETKF) methods. The assimilation system is first tested on a small paradigm model of the coupled tropical–extratropical climate system, then implemented for a coupled general circulation model (GCM). Strongly coupled DA was employed specifically to assess the impact of assimilating ocean observations [sea surface temperature (SST), sea surface height (SSH), and sea surface salinity (SSS), Argo, XBT, CTD, moorings] on the atmospheric state analysis update via the cross-domain error covariances from the coupled-model background ensemble. We examine the relationship between ensemble spread, analysis increments, and forecast skill in multiyear ENSO prediction experiments with a particular focus on the atmospheric response to tropical ocean perturbations. Initial forecast perturbations generated from bred vectors (BVs) project onto disturbances at and below the thermocline with similar structures to ETKF perturbations. BV error growth leads ENSO SST phasing by 6 months whereupon the dominant mechanism communicating tropical ocean variability to the extratropical atmosphere is via tropical convection modulating the Hadley circulation. We find that bred vectors specific to tropical Pacific thermocline variability were the most effective choices for ensemble initialization and ENSO forecasting.

scholarly journals Impact of Atmospheric and Model Physics Perturbations On a High-Resolution Ensemble Data Assimilation System of the Red Sea

2020 ◽  
Author(s):  
siva reddy sanikommu ◽  
Habib Toye ◽  
Peng Zhan ◽  
Sabique Langodan ◽  
George Krokos ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Red Sea ◽  
General Circulation ◽  
Circulation Model ◽  
Sea Surface ◽  
Massachusetts Institute Of Technology ◽  
Basin Scale ◽  
Subsurface Layers ◽  
The Impact

<p>The Ensemble Adjustment Kalman Filter of the Data Assimilation Research Testbed is implemented to assimilate observations of satellite sea surface temperature, altimeter sea surface height and in-situocean temperature and salinity profiles into an eddy-resolving 4km-Massachusetts Institute of Technology general circulation model (MITgcm) of the Red Sea. We investigate the impact of three different assimilation strategies (1) <em>Iexp</em>– inflates filter error covariance by 10%, (2) <em>IAexp</em>– adds ensemble of atmospheric forcing to Iexp, and (3) <em>IAPexp</em>– adds perturbed model physics toIAexp. The assimilation experiments are run for one year, starting from the same initial ensemble on 1<sup>st</sup>January, 2011 and the data are assimilated every three days.</p><p>Results demonstrate that the <em>Iexp</em> mainly improved the model outputs with respect to assimilation-free MITgcm run in the first few months, before showing signs of dynamical imbalances in the ocean estimates, particularly in the data-sparse subsurface layers. The <em>IAexp</em> yielded substantial improvements throughout the assimilation period with almost no signs of imbalances, including the subsurface layers. It further well preserved the model mesoscales features resulting in an improved forecasts for eddies, both in terms of intensity and location. Perturbing model physics in <em>IAPexp</em> slightly improved the forecast statistics. It further increased smoothness in the ocean forecasts and improved the placement of basin-scale eddies, but caused loss of some high-resolution features. Increasing hydrographic coverage helps recovering the losses and yields more improvements in <em>IAPexp</em> compared to <em>IAexp</em>. Switching off inflation in <em>IAexp</em> and <em>IAPexp</em> leads to further improvements, especially in the subsurface layers.</p>

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 Strongly Coupled Data Assimilation Experiments with Linearized Ocean–Atmosphere Balance Relationships

2018 ◽  
Vol 146 (4) ◽  
pp. 1233-1257 ◽  
Author(s):  
Andrea Storto ◽  
Matthew J. Martin ◽  
Bruno Deremble ◽  
Simona Masina
Keyword(s):  
Data Assimilation ◽  
General Circulation ◽  
Circulation Model ◽  
Variational Data Assimilation ◽  
Global Ocean ◽  
Background Error ◽  
Near Surface ◽  
Strongly Coupled ◽  
Coupled Data Assimilation ◽  
The Impact

Coupled data assimilation is emerging as a target approach for Earth system prediction and reanalysis systems. Coupled data assimilation may be indeed able to minimize unbalanced air–sea initialization and maximize the intermedium propagation of observations. Here, we use a simplified framework where a global ocean general circulation model (NEMO) is coupled to an atmospheric boundary layer model [Cheap Atmospheric Mixed Layer (CheapAML)], which includes prognostic prediction of near-surface air temperature and moisture and allows for thermodynamic but not dynamic air–sea coupling. The control vector of an ocean variational data assimilation system is augmented to include 2-m atmospheric parameters. Cross-medium balances are formulated either through statistical cross covariances from monthly anomalies or through the application of linearized air–sea flux relationships derived from the tangent linear approximation of bulk formulas, which represents a novel solution to the coupled assimilation problem. As a proof of concept, the methodology is first applied to study the impact of in situ ocean observing networks on the near-surface atmospheric analyses and later to the complementary study of the impact of 2-m air observations on sea surface parameters, to assess benefits of strongly versus weakly coupled data assimilation. Several forecast experiments have been conducted for the period from June to December 2011. We find that especially after day 2 of the forecasts, strongly coupled data assimilation provides a beneficial impact, particularly in the tropical oceans. In most areas, the use of linearized air–sea balances outperforms the statistical relationships used, providing a motivation for implementing coupled tangent linear trajectories in four-dimensional variational data assimilation systems. Further impacts of strongly coupled data assimilation might be found by retuning the background error covariances.

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.

The new Black Sea Reanalysis System within CMEMS

2021 ◽  
Author(s):  
Leonardo Lima ◽  
Stefania Angela Ciliberti ◽  
Ali Aydogdu ◽  
Romain Escudier ◽  
Simona Masina ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Sea Level ◽  
Black Sea ◽  
General Circulation ◽  
Circulation Model ◽  
Sea Surface Height ◽  
Sea Surface ◽  
The Black Sea ◽  
Freshwater Flux ◽  
Sea Level Anomaly

<p>Ocean reanalyses are becoming increasingly important to reconstruct and provide an overview of the ocean state from the past to the present-day. These products require advanced scientific methods and techniques to produce a more accurate ocean representation. In the scope of the Copernicus Marine Environment Monitoring Service (CMEMS), a new Black Sea (BS) reanalysis, BS-REA (BSE3R1 system), has been produced by using an advanced variational data assimilation method to combine the best available observations with a state-of-the-art ocean general circulation model. The hydrodynamical model is based on Nucleus for European Modeling of the Ocean (NEMO, v3.6), implemented for the BS domain with horizontal resolution of 1/27° x 1/36°, and 31 unevenly distributed vertical levels. NEMO is forced by atmospheric surface fluxes computed via bulk formulation and forced by ECMWF ERA5 atmospheric reanalysis product. At the surface, the model temperature is relaxed to daily objective analysis fields of sea surface temperature from CMEMS SST TAC. The exchange with Mediterranean Sea is simulated through relaxation of the temperature and salinity near Bosporus toward a monthly climatology computed from a high-resolution multi-year simulation, and the barotropic Bosporus Strait transport is corrected to balance the variations of the freshwater flux and the sea surface height measured by multi-satellite altimetry observations. A 3D-Var ocean data assimilation scheme (OceanVar) is used to assimilate sea level anomaly along-track observations from CMEMS SL TAC and available in situ vertical profiles of temperature and salinity from both SeaDataNet and CMEMS INS TAC products. Comparisons against the previous Black Sea reanalysis (BSE2R2 system) show important improvements for temperature and salinity, such that errors have significantly decreased (about 50%). Temperature fields present a continuous warming in the layer between 25-150 m, within which there is the presence of the Black Sea Cold Intermediate Layer (CIL). SST exhibits a positive bias and relatively higher root mean square error (RMSE) values are present in the summer season. Spatial maps of sea level anomaly reveal the largest RMSE close to the shelf areas, which are related to the mesoscale activity along the Rim current. The BS-REA catalogue includes daily and monthly means for 3D temperature, salinity, and currents and 2D sea surface height, bottom temperature, mixed layer fields, from Jan 1993 to Dec 2019.  The BSE3R1 system has produced very accurate estimates which makes it very suitable for assessing more realistic climate trends and indicators for important ocean properties.</p>

scholarly journals A STUDY OF THE IMPACT OF ALTIMETRY DATA ASSIMILATION ON SHORT-TERM PREDICTABILITY OF THE HYCOM OCEAN MODEL IN REGIONS OF THE TROPICAL AND SOUTH ATLANTIC OCEAN

2013 ◽  
Vol 31 (2) ◽  
pp. 271 ◽  
Author(s):  
Leonardo Nascimento Lima ◽  
Clemente Augusto Souza Tanajura
Keyword(s):  
Data Assimilation ◽  
Sea Surface Height ◽  
Ocean Model ◽  
South Atlantic ◽  
Sea Surface ◽  
Optimal Interpolation ◽  
Altimetry Data ◽  
Hybrid Coordinate Ocean Model ◽  
Along Track ◽  
The Impact

ABSTRACT. In this study, assimilation of Jason-1 and Jason-2 along-track sea level anomaly (SLA) data was conducted in a region of the tropical and South Atlantic (7◦N-36◦S, 20◦W up to the Brazilian coast) using an optimal interpolation method and the HYCOM (Hybrid Coordinate Ocean Model). Four 24 h-forecast experiments were performed daily from January 1 until March 31, 2011 considering different SLA assimilation data windows (1 day and 2 days) and different coefficients in the parameterization of the SLA covariance matrix model. The model horizontal resolution was 1/12◦ and the number of vertical layers was 21. The SLA analyses added to the mean sea surface height were projected to the subsurface with the Cooper & Haines (1996) scheme. The results showed that the experiment with 2-day window of along-track data and with specific parameterizations of the model SLA covariance error for sub-regions of the METAREA V was the most accurate. It completely reconstructed the model sea surface height and important improvements in the circulation were produced. For instance, there was a substantial improvement in the representation of the Brazil Current and North Brazil Undercurrent. However, since no assimilation of vertical profiles of temperature and salinity and of sea surface temperature was performed, the methodology employed here should be considered only as a step towards a high quality analysis for operational forecasting systems.   Keywords: data assimilation, optimal interpolation, Cooper & Haines scheme, altimetry data.   RESUMO. Neste estudo, a assimilação de dados de anomalia da altura da superfície do mar (AASM) ao longo da trilha dos satélites Jason-1 e Jason-2 foi conduzida em uma região do Atlântico tropical e Sul (7◦N-36◦S, 20◦W até a costa do Brasil) com o método de interpolação ótima e o modelo oceânico HYCOM (Hybrid Coordinate Ocean Model). Foram realizados quatro experimentos de previsão de 24 h entre 1 de janeiro e 31 de março de 2011, considerando diferentes janelas de assimilação de AASM (1 dia e 2 dias) e diferentes coeficientes na parametrização da matriz de covariância dos erros de AASM do modelo. A resolução horizontal empregada no HYCOM foi 1/12◦ para 21 camadas verticais. As correções de altura da superfície do mar devido à assimilação de AASM foram projetadas abaixo da camada de mistura através da técnica de Cooper & Haines (1996). Os resultados mostraram que o experimento com assimilação de dados ao longo da trilha dos satélites com a janela de 2 dias e com parametrizações da matriz de covariância específicas para sub-regiões da METAREA V foi o mais acurado. Ele reconstruiu completamente a altura da superfície do mar e também proporcionou melhorias na circulação oceânica reproduzida pelo modelo. Por exemplo, houve substancial melhoria da representação nos campos da Corrente do Brasil e Subcorrente Norte do Brasil. Entretanto, tendo em vista que não foi realizada a assimilação de perfis verticais de temperatura e de salinidade e da temperatura da superfície do mar, a metodologia apresentada deve ser considerada apenas como um passo na conquista de uma análise oceânica e de um sistema previsor de qualidade para fins operacionais.   Palavras-chave: assimilação de dados, interpolação ótima, técnica de Cooper & Haines, dados de altimetria.

scholarly journals The assessment of temperature and salinity sampling strategies in the Mediterranean Sea: idealized and real cases

Ocean Science ◽  
2006 ◽  
Vol 2 (2) ◽  
pp. 97-112 ◽  
Author(s):  
F. Raicich
Keyword(s):  
Data Assimilation ◽  
General Circulation ◽  
Regional Scale ◽  
Optimal Interpolation ◽  
Data Sets ◽  
Sampling Strategies ◽  
Argo Data ◽  
Basin Scale ◽  
The Mediterranean ◽  
The Impact

Abstract. Temperature and salinity sampling strategies are studied and compared by means of the Observing System Simulation Experiment technique in order to assess their usefulness for data assimilation in the framework of the Mediterranean Forecasting System. Their impact in a Mediterranean General Circulation Model is quantified in numerical twin experiments via bivariate data assimilation of temperature and salinity profiles in summer and winter conditions, using the optimal interpolation algorithm implemented in the System for Ocean Forecasting and Analysis. The data impact is quantified by the error reduction in the assimilation run relative to the free run. The sampling strategies studied here include various combinations of temperature and salinity profiles collected along Volunteer Observing Ship (VOS) tracks, by Mediterranean Multi-sensor Moored Arrays (M3A), a Glider and ARGO floating profilers. Idealized sampling strategies involving VOS data allow to recognize the impact of individual tracks. As a result, the most effective tracks are those crossing regions characterized by high mesoscale variability and the presence of frontal structures between water masses. Sampling strategies adopted in summer–autumn 2004 and winter 2005 are studied to assess the impact of VOS and ARGO data in real conditions. The combination of all available data allows to achieve up to 30% error reductions. ARGO data produce a small impact when alone, but represent the only continuous coverage of the basin and are useful as a complement to VOS data sets. Localized data sets, as those obtained by M3As and the Glider, seem to have an almost negligible impact in the basin-scale assessment, and are expected to be more effective at regional scale.

The Role of Radiative Interactions in Tropical Cyclone Development under Realistic Boundary Conditions

2020 ◽  
pp. 1-38
Author(s):  
Bosong Zhang ◽  
Brian J. Soden ◽  
Gabriel A. Vecchi ◽  
Wenchang Yang
Keyword(s):  
Boundary Conditions ◽  
General Circulation ◽  
Circulation Model ◽  
Sea Surface ◽  
Latent Heat Release ◽  
Synoptic Scale ◽  
Spatially Varying ◽  
The Impact ◽  
Realistic Boundary Conditions

AbstractThe impact of radiative interactions on tropical cyclones (TC) climatology is investigated using a global, TC-permitting general circulation model (GCM) with realistic boundary conditions. In this model, synoptic-scale radiative interactions are suppressed by overwriting the model-generated atmospheric radiative cooling rates with its monthly-varying climatological values. When radiative interactions are suppressed, the global TC frequency is significantly reduced, indicating that radiative interactions are a critical component of TC development even in the presence of spatially varying boundary conditions. The reduced TC activity is primarily due to a decrease in the frequency of pre-TC synoptic disturbances (“seeds”), whereas the likelihood that the seeds undergo cyclogenesis is less affected. When radiative interactions are suppressed, TC genesis shifts toward coastal regions, whereas TC lysis locations stay almost unchanged; together the distance between genesis and lysis is shortened, reducing TC duration. In a warmer climate, the magnitude of TC reduction from suppressing radiative interactions is diminished due to the larger contribution from latent heat release with increased sea surface temperatures. These results highlight the importance of radiative interactions in modulating the frequency and duration of TCs.

scholarly journals Using Temperature–Salinity Relations in a Global Ocean Implementation of a Multivariate Data Assimilation Scheme

2007 ◽  
Vol 135 (11) ◽  
pp. 3785-3807 ◽  
Author(s):  
A. Bellucci ◽  
S. Masina ◽  
P. DiPietro ◽  
A. Navarra
Keyword(s):  
Data Assimilation ◽  
General Circulation ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Global Ocean ◽  
Special Focus ◽  
Background Error ◽  
Background Error Covariance ◽  
Error Covariance ◽  
The Impact

Abstract In this paper results from the application of an ocean data assimilation (ODA) system, combining a multivariate reduced-order optimal interpolator (OI) scheme with a global ocean general circulation model (OGCM), are described. The present ODA system, designed to assimilate in situ temperature and salinity observations, has been used to produce ocean reanalyses for the 1962–2001 period. The impact of assimilating observed hydrographic data on the ocean mean state and temporal variability is evaluated. A special focus of this work is on the ODA system skill in reproducing a realistic ocean salinity state. Results from a hierarchy of different salinity reanalyses, using varying combinations of assimilated data and background error covariance structures, are described. The impact of the space and time resolution of the background error covariance parameterization on salinity is addressed.

scholarly journals Incremental Analysis Update Implementation into a Sequential Ocean Data Assimilation System

2006 ◽  
Vol 23 (12) ◽  
pp. 1729-1744 ◽  
Author(s):  
Y. Ourmières ◽  
J-M. Brankart ◽  
L. Berline ◽  
P. Brasseur ◽  
J. Verron
Keyword(s):  
Data Assimilation ◽  
High Frequency ◽  
General Circulation ◽  
Circulation Model ◽  
Low Rank ◽  
Incremental Analysis ◽  
High Frequency Oscillations ◽  
The Impact ◽  
Data Assimilation System ◽  
Assimilation System

Abstract This study deals with the enhancement of a sequential assimilation method applied to an ocean general circulation model (OGCM). A major drawback of sequential assimilation methods is the time discontinuity of the solution resulting from intermittent corrections of the model state. The data analysis step can induce shocks in the model restart phase, causing spurious high-frequency oscillations and data rejection. A method called Incremental Analysis Update (IAU) is now recognized to efficiently tackle these problems. In the present work, an IAU-type method is implemented into an intermittent data assimilation system using a low-rank Kalman filter [Singular Evolutive Extended Kalman (SEEK)] in the case of an OGCM with a 1/3° North Atlantic grid. A 1-yr (1993) experiment has been conducted for different setups in order to evaluate the impact of the IAU scheme. Results from all of the different tests are compared with a specific interest in high-frequency output behaviors and solution consistency. The improvements brought up by the IAU implementation, such as the disappearance of spurious high-frequency oscillations and the time continuity of the solution, are shown. An overall assessment of the impact of this new approach on the assimilated runs is discussed. Advantages and drawbacks of the IAU method are pointed out.

Sign in / Sign up

Export Citation Format

Share Document