Evaluating the impacts of the tropical Pacific observing system on the ocean analysis fields in the global ocean data assimilation system for operational seasonal forecasts in JMA

Fujii, Yosuke; Ogawa, Koji; Brassington, Gary B.; Ando, Kenji; Yasuda, Tohya; Kuragano, Tsurane

doi:10.1080/1755876x.2015.1014640

Cited by 11 publications

(11 citation statements)

References 46 publications

(44 reference statements)

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“…[], and Fujii et al . [] suggested. In addition, a large computational resource is required for OSEs for eddy‐scale phenomena in the global ocean.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the Argo network using statistical space‐time scales derived from satellite altimetry data

2015

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This study evaluates capability of the Argo observation network for monitoring ocean variation, especially for eddy‐scale variation, by using an optimum interpolation (OI) procedure. Sea surface dynamic height anomalies (DHAs) are derived from Argo temperature and salinity profile data, and DHA fields are obtained by the OI based on the space‐time correlation scales estimated from along‐track sea level anomaly (SLA) data by satellite altimetry. The DHA fields are compared with the SLA fields derived from the same OI applied to the along‐track SLA data. The results show that the equatorial Kelvin waves and tropical instability waves are well captured by Argo floats. Eddies are also monitored effectively in the subtropical western North Pacific. The OI results of DHA do not agree well with those of SLA in the high latitudes. A simple test of the space‐time OI analysis shows that more than six data in the e‐folding domain, where the correlation coefficient of ocean variation is above e−1, are required for the reliable analysis with 99% confidence level. Argo floats provide sufficient number of observations for the reliable analysis in the low latitudes and some areas in the North Pacific. Two to three times more Argo data would be required in most of midlatitudes and much more in high latitudes for capturing eddy‐scale variation.

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“…[], and Fujii et al . [] suggested. In addition, a large computational resource is required for OSEs for eddy‐scale phenomena in the global ocean.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the Argo network using statistical space‐time scales derived from satellite altimetry data

2015

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“…JMA/MRI also conducted a series of OSEs to evaluate the relative impact of Argo floats and TAO/TRITON buoys on the ocean DA fields and ENSO forecasts using an operational seasonal forecasting system (Fujii et al , , ). The system uses the nearly‐global ocean DA system, MOVE‐G (Multivariate Ocean Variational Estimation System Global Version; Fujii et al , ), for the ocean initialization, in which a multivariate 3D‐Var scheme assimilates satellite SSH, gridded SST, and in situ temperature and salinity profiles, including data from Argo, XBT, and tropical moorings.…”

Section: Observing System Evaluationsmentioning

confidence: 99%

“…The accuracy of the run without TAO/TRITON (noTTA80) is roughly similar to the ARGO40 run in NINO‐3 and NINO‐4 regions, implying impacts of TAO/TRITON is similar to 40% of Argo data. It should be noted that we evaluated here the impacts of TAO/TRITON complementary to all other available data, including Argo and altimetry data, and that the intrinsic impact of TAO/TRITON is larger (Fujii et al , ). Accuracy of the salinity field is not degraded if data from extra‐equatorial buoys outside of 2.5°S–2.5°N are withheld (TTeqA80) in the two regions, although assimilation of extratropical buoys has some impacts on temperature there.…”

Section: Observing System Evaluationsmentioning

confidence: 99%

Evaluation of the Tropical Pacific Observing System from the ocean data assimilation perspective

Fujii

Cummings

Xue

et al. 2015

Quart J Royal Meteoro Soc

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The drastic reduction in the number of observation data from the Tropical Atmospheric Ocean (TAO)/Triangle Trans-Ocean Buoy Network (TRITON) array since 2012 has given rise to a need to assess the impact of those data in ocean data assimilation (DA) systems. This article provides a review of existing studies evaluating the impacts of data from the TAO/TRITON array and other components of the Tropical Pacific Observing System (TPOS) on current ocean DA systems used for a variety of operational and research applications. It can be considered as background information that can guide the evaluation exercise of TPOS. Temperature data from TAO/TRITON array are assimilated in most ocean DA systems which cover the tropical Pacific in order to constrain the ocean heat content, stratification, and circulation. It is shown that the impacts of observation data depend considerably on the system and application. The presence of model error often makes the results difficult to interpret. Nevertheless there is consensus that the data from TAO/TRITON generally have positive impacts complementary to Argo floats. In the equatorial Pacific, the impacts are generally around the same level or larger than those of Argo. We therefore conclude that, with the current configuration of TPOS, the loss of the TAO/TRITON data is having a significant detrimental impact on many applications based on ocean DA systems. This conclusion needs to be kept under review because the equatorial coverage by Argo is expected to improve in the future.

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“…In the OSE framework, reduction of errors cannot be estimated accurately because the true state is unknown. Instead, errors are evaluated using reference data, which are preferably independent from the data assimilation process performed in advance in the OSEs in order to perform fair evaluation (Fujii et al, 2015b). Adjoint based sensitivity methods are also very applicable for OS-Eval.…”

Section: Introductionmentioning

confidence: 99%

Observing System Evaluation Based on Ocean Data Assimilation and Prediction Systems: On-Going Challenges and a Future Vision for Designing and Supporting Ocean Observational Networks

et al. 2019

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This paper summarizes recent efforts on Observing System Evaluation (OS-Eval) by the Ocean Data Assimilation and Prediction (ODAP) communities such as GODAE OceanView and CLIVAR-GSOP. It provides some examples of existing OS-Eval methodologies, and attempts to discuss the potential and limitation of the existing approaches. Observing System Experiment (OSE) studies illustrate the impacts of the severe decrease in the number of TAO buoys during 2012-2014 and TRITON buoys since 2013 on ODAP system performance. Multi-system evaluation of the impacts of assimilating satellite sea surface salinity data based on OSEs has been performed to demonstrate the need to continue and enhance satellite salinity missions. Impacts of underwater gliders have been assessed using Observing System Simulation Experiments (OSSEs) to provide guidance on the effective coordination of the western North Atlantic observing system elements. OSSEs are also being performed under H2020 AtlantOS Fujii et al.Observing System Evaluation project with the goal to enhance and optimize the Atlantic in-situ networks. Potential of future satellite missions of wide-swath altimetry and surface ocean currents monitoring is explored through OSSEs and evaluation of Degrees of Freedom for Signal (DFS). Forecast Sensitivity Observation Impacts (FSOI) are routinely evaluated for monitoring the ocean observation impacts in the US Navy's ODAP system. Perspectives on the extension of OS-Eval to coastal regions, the deep ocean, polar regions, coupled data assimilation, and biogeochemical applications are also presented. Based on the examples above, we identify the limitations of OS-Eval, indicating that the most significant limitation is reduction of robustness and reliability of the results due to their system-dependency. The difficulty of performing evaluation in near real time is also critical. A strategy to mitigate the limitation and to strengthen the impact of evaluations is discussed. In particular, we emphasize the importance of collaboration within the ODAP community for multi-system evaluation and of communication with ocean observational communities on the design of OS-Eval, required resources, and effective distribution of the results. Finally, we recommend further developing OS-Eval activities at international level with the support of the international ODAP (e.g., OceanPredict and CLIVAR-GSOP) and observational communities.

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Evaluating the impacts of the tropical Pacific observing system on the ocean analysis fields in the global ocean data assimilation system for operational seasonal forecasts in JMA

Cited by 11 publications

References 46 publications

Evaluation of the Argo network using statistical space‐time scales derived from satellite altimetry data

Evaluation of the Argo network using statistical space‐time scales derived from satellite altimetry data

Evaluation of the Tropical Pacific Observing System from the ocean data assimilation perspective

Observing System Evaluation Based on Ocean Data Assimilation and Prediction Systems: On-Going Challenges and a Future Vision for Designing and Supporting Ocean Observational Networks

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