Evidence map›Paper›PMID 31534949›Full record

ArticleFrontiers in Marine Science2019

Observational Needs for Improving Ocean and Coupled Reanalysis, S2S Prediction, and Decadal Prediction.

Stephen G Penny, Santha Akella, Magdalena A Balmaseda, Philip Browne, James A Carton, Matthieu Chevallier, Francois Counillon, Catia Domingues, Sergey Frolov, Patrick Heimbach and 21 more

Abstract read
In one paragraph

Article in Frontiers in Marine Science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

31 authors.

Stephen G PennyDepartment of Atmospheric and Oceanic Science, University of Maryland, College Park, MD, United States.
Santha AkellaNational Aeronautics and Space Administration, Goddard Space Flight Center, Greenbelt, MD, United States.
Magdalena A BalmasedaEuropean Centre for Medium-Range Weather Forecasts, Reading, United Kingdom.
Philip BrowneEuropean Centre for Medium-Range Weather Forecasts, Reading, United Kingdom.
James A CartonDepartment of Atmospheric and Oceanic Science, University of Maryland, College Park, MD, United States.
Matthieu ChevallierMétéo-France, Toulouse, France.
Francois CounillonNansen Environmental and Remote Sensing Center, Bergen, Norway.
Catia DominguesAntarctic Climate and Ecosystems Cooperative Research Centre, Hobart, TAS, Australia.
Sergey FrolovNaval Research Laboratory, Monterey, CA, United States.
Patrick HeimbachThe University of Texas at Austin, Austin, TX, United States.
Patrick HoganNaval Research Laboratory, Stennis Space Center, MS, United States.
Ibrahim HoteitKing Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
Doroteaciro IovinoEuro-Mediterranean Center on Climate Change, Lecce, Italy.
Patrick LaloyauxEuropean Centre for Medium-Range Weather Forecasts, Reading, United Kingdom.
Matthew J MartinMet Office, Exeter, United Kingdom.
Simona MasinaEuro-Mediterranean Center on Climate Change, Lecce, Italy.
Andrew M MooreUniversity of California, Santa Cruz, Santa Cruz, CA, United States.
Patricia de RosnayEuropean Centre for Medium-Range Weather Forecasts, Reading, United Kingdom.
Dinand SchepersEuropean Centre for Medium-Range Weather Forecasts, Reading, United Kingdom.
Bernadette M SloyanCommonwealth Scientific and Industrial Research Organisation, Canberra, ACT, Australia.
Andrea StortoNATO Centre for Maritime Research and Experimentation, La Spezia, Italy.
Aneesh SubramanianDepartment of Atmospheric and Oceanic Science, University of Colorado, Boulder, Boulder, CO, United States.
SungHyun NamSeoul National University, Seoul, South Korea.
Frederic VitartEuropean Centre for Medium-Range Weather Forecasts, Reading, United Kingdom.
Chunxue YangIstituto di Scienze Marine, Consiglio Nazionale delle Ricerche, Rome, Italy.
Yosuke FujiiJMA Meteorological Research Institute, Tsukuba, Japan.
Hao ZuoEuropean Centre for Medium-Range Weather Forecasts, Reading, United Kingdom.
Terry O'KaneCommonwealth Scientific and Industrial Research Organisation, Canberra, ACT, Australia.
Paul SanderyCommonwealth Scientific and Industrial Research Organisation, Canberra, ACT, Australia.
Thomas MooreCommonwealth Scientific and Industrial Research Organisation, Canberra, ACT, Australia.
Christopher C ChapmanCommonwealth Scientific and Industrial Research Organisation, Canberra, ACT, Australia.

Funding

Goddard Space Flight Center NASAIntramural NASA N-999999
6 · The paper itself

Abstract

Developments in observing system technologies and ocean data assimilation (DA) are symbiotic. New observation types lead to new DA methods and new DA methods, such as coupled DA, can change the value of existing observations or indicate where new observations can have greater utility for monitoring and prediction. Practitioners of DA are encouraged to make better use of observations that are already available, for example, taking advantage of strongly coupled DA so that ocean observations can be used to improve atmospheric analyses and vice versa. Ocean reanalyses are useful for the analysis of climate as well as the initialization of operational long-range prediction models. There are many remaining challenges for ocean reanalyses due to biases and abrupt changes in the ocean-observing system throughout its history, the presence of biases and drifts in models, and the simplifying assumptions made in DA solution methods. From a governance point of view, more support is needed to bring the ocean-observing and DA communities together. For prediction applications, there is wide agreement that protocols are needed for rapid communication of ocean-observing data on numerical weather prediction (NWP) timescales. There is potential for new observation types to enhance the observing system by supporting prediction on multiple timescales, ranging from the typical timescale of NWP, covering hours to weeks, out to multiple decades. Better communication between DA and observation communities is encouraged in order to allow operational prediction centers the ability to provide guidance for the design of a sustained and adaptive observing network.

Indexed as

coupled data assimilationdata assimilationdecadal predictionocean data assimilationocean observation networkocean reanalysisreanalysisS2S prediction

Identifiers

PMID31534949
PMCPMC6750049

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.