Successes and Challenges for the Modern Sea Surface Temperature Observing System

Donlon, Craig; Casey, Kenneth S.; Gentemann, Chelle; Leborgne, P; Robinson, I. S.; Reynolds, Richard W.; Minnett, Peter J.; Piollé, Jean-François; Cornillon, Peter; Rayner, Nick; Brandon, T.; Vázquez, Jorge; Armstrong, E. M.; Beggs, Helen; Barton, I. J.; Wick, Gary A.; Castro, Sandra L.; Hoeyer, J.; Arino, Olivier; Evans, Robert H.; Mutlow, C. T.; Bingham, Andrew; Harris, Andrew R.

doi:10.5270/oceanobs09.cwp.24

Cited by 36 publications

(52 citation statements)

References 35 publications

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“…of Fisheries and Oceans, Ottawa, Canada, K1A 0E6, Email: Robert.Keeley@dfo-mpo.gc.ca (4) IFREMER, BP 70, 29280 Plouzané, France: Email: sylvie.pouliquen@ifremer.fr (5) National Oceanic and Atmospheric Administration, 1100 Wayne Ave #1225, Silver Spring MD 20910 USA, Email: Jeff.deLaBeaujardiere@noaa.gov (6) Institute of Marine and Coastal Sciences, Rutgers University, 71 Dudley Road, New Brunswick, New Jersey 08901-8521, USA, Email: evberghe@iobis.org (7) Australian Ocean Data Centre Joint Facility, Level 2, Building 89, Garden Island, Potts Point, New South Wales 2011, Email: greg@metoc.gov.au (8) Space Oceanography Division, CLS, Ramonville-St-Agne, France, Email: fblanc@cls.fr (9) U.S. National Oceanographic Data Center, 1315 East-West Highway, # 4820, Silver Spring, MD 20910, Email: margarita.gregg@noaa.gov (10) Woods Hole Oceanographic Institution, Woods Hole, MA 02540, Email: jfredericks@whoi.edu (11) NOAA/Climate Program Office, Silver Spring MD, USA, Email: Derrick.Snowden@noaa.gov…”

Section: )mentioning

confidence: 99%

“…This has led to a proliferation of online data sources, meaning that users frequently experience difficulties in finding the data they require, or in finding the authoritative copy of a dataset that appears on the Internet many times. Recent trends have focused on global data assembly centres such as Argo (Array for Real-time Geostrophic Oceanography), drifters, and OceanSITES (OCEAN Sustained Interdisciplinary Time series Environment observation System) and on assembling data from various platforms into consolidated collections in support of specific goals, such as the World Ocean Circulation Experiment (WOCE) Data Assembly Centres, the Coriolis database of in situ observations [5], the GHRSST (Group for High-Resolution Sea Surface Temperature) project for sea surface temperature [6], the AVISO (Archiving, Validation and Interpretation of Satellite Oceanographic data) [7] project for altimetry data and the U.S. Observing System Monitoring Center [8,9,10] Work still needs to be done in helping the many users of ocean data to discover, evaluate and access the data they need [11].…”

Section: Introductionmentioning

confidence: 99%

“…, J. de la Beaujardière (5) , E. Vanden Berghe (6) , G. Reed (7) , F. Blanc (8) , M.C. Gregg (9) , J. Fredericks (10) , D. Snowden (…”

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confidence: 99%

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Ocean Data Dissemination: New Challenges for Data Integration

Blower¹,

Hankin²,

Keeley³

et al. 2010

Proceedings of OceanObs'09: Sustained Ocean Observations and Information for Society

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In the decade since OceanObs`99, great advances have been made in the field of ocean data dissemination. The use of Internet technologies has transformed the landscape: users can now find, evaluate and access data rapidly and securely using only a web browser. This paper describes the current state of the art in dissemination methods for ocean data, focussing particularly on ocean observations from in situ and remote sensing platforms. We discuss current efforts being made to improve the consistency of delivered data and to increase the potential for automated integration of diverse datasets. An important recent development is the adoption of open standards from the Geographic Information Systems community; we discuss the current impact of these new technologies and their future potential. We conclude that new approaches will indeed be necessary to exchange data more effectively and forge links between communities, but these approaches must be evaluated critically through practical tests, and existing ocean data exchange technologies must be used to their best advantage. Investment in key technology components, cross-community pilot projects and the enhancement of end-user software tools will be required in order to assess and demonstrate the value of any new technology.

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Section: )mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Ocean Data Dissemination: New Challenges for Data Integration

Blower¹,

Hankin²,

Keeley³

et al. 2010

Proceedings of OceanObs'09: Sustained Ocean Observations and Information for Society

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show abstract

“…The most commonly used are seasurface height (SSH) anomalies from altimeters (e.g., TOPEX/Poseidon and JASON-1, -2 [15]), in situ temperature (T) profiles from XBTs/CTDs [16,17] , the global tropical moored buoy array [18], and Argo [19] and in situ salinity (S) profiles from Argo. Sea surface temperature (SST) estimates (e.g., [20], [21]) are either assimilated directly or used as a surface boundary condition. Salinity data from CTDs and velocity data from current meters and acoustic Doppler current profilers (ADCPs) are usually used for validation.…”

Section: The Current Global Synthesis Effortsmentioning

confidence: 99%

“…Each different observation type brings unique contributions to the GOOS and all observation types should be routinely assimilated by forecast and reanalysis products and, most importantly, maintained by the international community. The consistent use of and impact from SST observations is a credit to the GODAE High Resolution SST (GHRSST) program that provides high level quality controlled SST data in near real-time [21]. [100].…”

Section: 2mentioning

confidence: 99%

Synthesis and Assimilation Systems - Essential Adjuncts to the Global Ocean Observing System

Rienecker

Awaji

Balmaseda

et al. 2010

Proceedings of OceanObs'09: Sustained Ocean Observations and Information for Society

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Using a 1‐D model to reproduce the diurnal variability ofSST

2017

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A wide range of applications, from air‐sea interaction studies to fisheries and biological modeling, need accurate, high resolution SST which requires that the diurnal signal is known; for many applications, diurnal estimates are necessary and should be included in blended SST products. A widely preferred approach to bridge the gap between in situ and remotely sensed measurements and obtain diurnal warming estimates at large spatial scales is modeling of the upper ocean temperature. This study uses the one‐dimensional General Ocean Turbulence Model (GOTM) to resolve diurnal signals identified from satellite SSTs and in situ measurements. Focus is given on testing and validation of different parameterizations of the basic physical processes known to influence the generation of a warm surface layer. GOTM is tested and validated using in situ measurements obtained at three locations, two in the Atlantic Ocean and one in the Baltic Sea, where different oceanographic and atmospheric conditions occur, in order to obtain an insight into its general performance. It is found that the model, with a 9 band solar absorption model rather than the standard 2 band scheme, performs well when using 3 hourly NWP forcing fields and is able to resolve daily SST variability seen both from satellite and in situ measurements. As such, and due to its low computational cost, it is proposed as a candidate model for diurnal variability estimates.

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Successes and Challenges for the Modern Sea Surface Temperature Observing System

Cited by 36 publications

References 35 publications

Ocean Data Dissemination: New Challenges for Data Integration

Ocean Data Dissemination: New Challenges for Data Integration

Synthesis and Assimilation Systems - Essential Adjuncts to the Global Ocean Observing System

Using a 1‐D model to reproduce the diurnal variability ofSST

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