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  • 1
    Publication Date: 2021-06-16
    Description: Analyzing ocean variability, understanding its importance for the climate system, and quantifying its socio-economic impacts are among the primary motivations for obtaining ongoing global ocean observations. There are several possible approaches to address these tasks. One with much potential for future ocean information services and for climate predictions is called ocean synthesis, and is concerned with merging all available ocean observations with the dynamics embedded in an ocean circulation model to obtain estimates of the changing ocean that are more accurate than either system alone can provide. The field of ocean synthesis has matured over the last decade. Several global ocean syntheses exist today and can be used to investigate key scientific questions, such as changes in sea level, heat content, or transports. This CWP summarizes climate variability as “seen” by several ocean syntheses, describes similarities and differences in these solutions and uses results to highlight developments necessary over the next decade to improve ocean products and services. It appears that multi-model ensemble approaches can be useful to obtain better estimates of the ocean. To make full use of such a system, though, one needs detailed error information not only about data and models, but also about the estimated states. Results show that estimates tend to cluster around methodologies and therefore are not necessarily independent from each other. Results also reveal the impact of a historically under-sampled ocean on estimates of inter-decadal variability in the ocean. To improve future estimates, we need not only to sustain the existing observing system but to extend it to include full-depth ARGO-type measurements, enhanced information about boundary currents and transports through key regions, and to keep all important satellite sensors flying indefinitely, including altimetry, gravimetry and ice thickness, microwave SST observations, wind stress measurements and ocean color. We also need to maintain ocean state estimation as an integral part of the ocean observing and information system.
    Description: Published
    Description: Venice, Italy
    Description: 3.7. Dinamica del clima e dell'oceano
    Description: open
    Keywords: ocean modelling ; Global climate models ; reanalysis ; coupled models ; ensemble ocean syntheses ; 03. Hydrosphere::03.01. General::03.01.03. Global climate models
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: Conference paper
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  • 2
    Publication Date: 2021-06-16
    Description: Spurred by the sustained operation and new development of satellite and in-situ observing systems, global ocean state estimation efforts that gear towards climate applications have flourished in the past decade. A hierarchy of estimation methods is being used to routinely synthesize various observations with global ocean models. Many of the estimation products are available through public data servers. There have been an increasingly large number of applications of these products for a wide range of research topics in physical oceanography as well as other disciplines. These studies often provide important feedback for observing systems design. This white paper describes the approaches used by these estimation systems in synthesizing observations and model dynamics, highlights the applications of their products for climate research, and addresses the challenges ahead in relation to the observing systems. Additional applications to study climate variability using an ensemble of state estimation products are described also by a white paper by Stammer et al.
    Description: Published
    Description: Venice, Italy
    Description: 3.7. Dinamica del clima e dell'oceano
    Description: open
    Keywords: ocean modelling ; Global climate models ; reanalysis ; coupled models ; observing systems ; 03. Hydrosphere::03.01. General::03.01.03. Global climate models
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: Conference paper
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  • 3
    Publication Date: 2022-06-20
    Description: Uncertainty in ocean analysis methods and deficiencies in the observing system are major obstacles for the reliable reconstruction of the past ocean climate. The variety of existing ocean reanalyses is exploited in a multi-reanalysis ensemble to improve the ocean state estimation and to gauge uncertainty levels. The ensemble-based analysis of signal-to-noise ratio allows the identification of ocean characteristics for which the estimation is robust (such as tropical mixed-layer-depth,upper ocean heat content), and where large uncertainty exists (deep ocean, Southern Ocean, sea-ice thickness, salinity), providing guidance for future enhancement of the observing and data assimilation systems.
    Description: This work has been partially funded by the European Commission funded projects MyOcean, MyOcean2 and COMBINE; by the GEMINA project-funded bythe Italian Ministry for Environment; by the NERC-funded VALOR project; by the NERC-funded NCEO program; by the Research Program on Climate Change adaptation of the Ministry of Education, Culture, Sports, Science and Technology of the Japanese government; by the Joint UK DECC/Defra Met Office Hadley Centre Climate Programme (GA01101); by NASA’s Modeling Analysis and Prediction Program under WBS 802678.02.17.01.25 and by the NASA Physical Oceanography Program; by the NOAA's Climate Observation Division (COD); by the LEFE/GMMC French national program.
    Description: Published
    Description: s80-s97
    Description: 4A. Clima e Oceani
    Description: JCR Journal
    Description: open
    Keywords: Global ocean–sea-ice modelling ; Ocean model comparisons ; DATA ASSIMILATION SCHEME ; multi-analysis ensemble ; Ocean climate ; 03. Hydrosphere::03.01. General::03.01.04. Ocean data assimilation and reanalysis
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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