DOCSLIB.ORG

Climate Datasets and Related Coastal Exposure Databases

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Climate Datasets and Related Coastal Exposure Databases European advances on CLImate Services for Coasts and SEAs Climate datasets and related Coastal Exposure databases Work Package 1 - Deliverable 1.A Authors: Acevedo A., Camus P., Menendez M., Meinke I., Le Cozannet G., Meyssignac B., Emmanouil G., Liu X. et al. Deliverable Leader: UC -IHC Project acronym: ECLISEA Participants: UC-IHC, HZG, BRGM, CNRS, NCSRD Funding scheme: ERA4CS Joint Call on Researching and Relevant WP: WP1- Review of existing data sets and Advancing Climate Services Development by Institutional stakeholders needs integration (Topic B) WP Leader: Insa Meinke (HZG) Date of the first version deliverable: March 1st, 2018 Date: March 15th, 2018 Date of final version: March 15th, 2018 Project ECLISEA is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by UC- IHCantabria, HZG, BRGM, NCSRD and CNRS with co-funding by the European Union. TABLE OF CONTENTS 1. INTRODUCTION ....................................................................................................................................... 4 2. CLIMATE OBSERVATIONAL DATASETS ..................................................................................................... 5 2.1 IN-SITU RECORDS ....................................................................................................................................... 5 2.1.1 Buoys ......................................................................................................................................................... 5 Spanish Port Authority...................................................................................................................................................................... 6 Hydrographic Institute of Portugal .................................................................................................................................................. 7 POSEIDON marine monitoring network........................................................................................................................................... 8 Italian national data buoy network (RON) .....................................................................................................................................10 WaveNet monitoring Network .......................................................................................................................................................12 MARNET monitoring network ........................................................................................................................................................15 Finnish Meteorological Institute ....................................................................................................................................................16 Rijkswaterstaat Waterinfo ..............................................................................................................................................................17 Meteo France ..................................................................................................................................................................................18 CANDHIS ..........................................................................................................................................................................................19 2.1.2 Tide gauges .............................................................................................................................................. 21 PSMSL ..............................................................................................................................................................................................21 UHSLC ..............................................................................................................................................................................................23 GLOSS ..............................................................................................................................................................................................24 GESLA-2 ...........................................................................................................................................................................................25 2.2 REMOTE OBSERVATIONS ........................................................................................................................... 26 2.2.1 Wave height altimeter measurements ...................................................................................................... 27 Global altimeter SWH data set .......................................................................................................................................................28 AVISO+ Gridded Wave products ....................................................................................................................................................28 2.2.2 Sea level data from satellite ..................................................................................................................... 29 Global Ocean Gridded L4 Sea Surface Heights and Derived Variables Reprocessed ...................................................................29 Mediterranean Sea Gridded L4 Sea Surface Heights and Derived Variables Reprocessed .........................................................30 SL_cci ECV v2.0 ................................................................................................................................................................................30 RADS ................................................................................................................................................................................................31 Global Ocean Along-Track L3 Sea Surface Heights Reprocessed ..................................................................................................32 3. HISTORICAL CLIMATE DATASETS ........................................................................................................... 33 3.1 SEA LEVEL DATASETS................................................................................................................................. 33 GOST ................................................................................................................................................................................................35 CoastDat ..........................................................................................................................................................................................35 LEGOS sea level reconstruction ......................................................................................................................................................36 LEGOS historical sea level hindcast ................................................................................................................................................37 AWI sea level reconstruction .........................................................................................................................................................37 CSIRO sea level reconstruction.......................................................................................................................................................38 CCAR sea level reconstruction........................................................................................................................................................38 GECCO2 ...........................................................................................................................................................................................39 ORAS4 ..............................................................................................................................................................................................39 Soda2.1.6 .........................................................................................................................................................................................40 Global Ocean Physics Reanalysis GLORYS2V4 ...............................................................................................................................41 Baltic Sea Physics Reanalysis From SMHI.......................................................................................................................................41 Mediterranean Sea Physics Reanalysis (1955-2015) .....................................................................................................................42 Mediterranean Sea Physics Reanalysis (1987-2015) .....................................................................................................................42 3.2 WAVE HINDCAST ..................................................................................................................................... 43 GOW ................................................................................................................................................................................................44 CoastDat ..........................................................................................................................................................................................45 Bobwa-h ..........................................................................................................................................................................................46
Load more

Recommended publications
  • A Metric for Quantifying El Niño Pattern Diversity with Implications for ENSO–Mean State Interaction
    Climate Dynamics (2019) 52:7511–7523 https://doi.org/10.1007/s00382-018-4194-3 A metric for quantifying El Niño pattern diversity with implications for ENSO–mean state interaction Danielle E. Lemmon1,2 · Kristopher B. Karnauskas1,2 Received: 7 September 2017 / Accepted: 26 March 2018 / Published online: 5 April 2018 © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract Recent research on the El Niño–Southern Oscillation (ENSO) phenomenon increasingly reveals the highly complex and diverse nature of ENSO variability. A method of quantifying ENSO spatial pattern uniqueness and diversity is presented, which enables (1) formally distinguishing between unique and “canonical” El Niño events, (2) testing whether historical model simulations aptly capture ENSO diversity by comparing with instrumental observations, (3) projecting future ENSO diversity using future model simulations, (4) understanding the dynamics that give rise to ENSO diversity, and (5) analyzing the associated diversity of ENSO-related atmospheric teleconnection patterns. Here we develop a framework for measur- ing El Niño spatial SST pattern uniqueness and diversity for a given set of El Niño events using two indices, the El Niño Pattern Uniqueness (EPU) index and El Niño Pattern Diversity (EPD) index, respectively. By applying this framework to instrumental records, we independently confirm a recent regime shift in El Niño pattern diversity with an increase in unique El Niño event sea surface temperature patterns. However, the same regime shift is not observed in historical CMIP5 model simulations; moreover, a comparison between historical and future CMIP5 model scenarios shows no robust change in future ENSO diversity. Finally, we support recent work that asserts a link between the background cooling of the eastern tropical Pacific and changes in ENSO diversity.
    [Show full text]
  • Interactive Comment on “C-Glorsv5: an Improved Multi-Purpose Global Ocean Eddy-Permitting Physical Reanalysis” by Andrea Storto and Simona Masina
    Discussions Earth System Earth Syst. Sci. Data Discuss., Science doi:10.5194/essd-2016-38-RC1, 2016 ESSDD © Author(s) 2016. CC-BY 3.0 License. Open Access Data Interactive comment Interactive comment on “C-GLORSv5: an improved multi-purpose global ocean eddy-permitting physical reanalysis” by Andrea Storto and Simona Masina Anonymous Referee #1 Received and published: 28 September 2016 This article generates an updated version of a previous Global reanalysis data. Part of the derived products has been made available in NetCDF format at doi:10.1594/PANGAEA.857995. The method used in generating the data has a num- ber of improvements in comparing with the one used in the old version. As a global ocean reanalysis dataset, they can be useful in many areas. Methods and materials are mostly described in sufficient detail to support the data. Printer-friendly version It is observed that there exist similar global reanalysis datasets, e.g., in in ma- rine.copernicus.eu, ECCO or US HYCOM etc. Many components of the method de- Discussion paper scription have also been published by the authors in other papers. However, these products haven’t been inter-compared with the V5 data, either qualitatively or quanti- C1 tatively. This makes it difficult to evaluate the “state-of-the-art” and “uniqueness” of the data. ESSDD The new data (V5) have been validated and compared with the old data (V4), which shows improvements in simulating variability of the sea ice and AMOC. However some Interactive features of the products have been degraded. Overall T/S validation in Fig.5 shows that comment only water temperature in upper 80m in V5 has smaller RSME than V4, T/S in other layers for V5 are worse than V4.
    [Show full text]
  • Measuring Global Mean Sea Level Changes with Surface Drifting Buoys
    Measuring global mean sea level changes with surface drifting buoys Shane Elipot Rosenstiel School of Marine and Atmospheric Science, University of Miami Abstract Combining ocean model data and in-situ Lagrangian data, I show that an array of surface drifting buoys tracked by a Global Navigation Satellite System (GNSS), such as the Global Drifter Program, could provide estimates of global mean sea level (GMSL) and its changes, including linear decadal trends. For a sustained array of 1250 globally distributed buoys with a standardized design, I demonstrate that GMSL decadal linear trend estimates with an uncertainty less than 0.3 mm yr−1 could be achieved with GNSS daily random error of 1.6 m or less in the vertical direction. This demonstration assumes that controlled vertical position measurements could be acquired from drifting buoys, which is yet to be demonstrated. Development and implementation of such measurements could ultimately provide an independent and resilient observational system to infer natural and anthropogenic sea level changes, augmenting the on-going tide gauge and satellites records. 1 Introduction Modern global mean sea level (GMSL) rise is an intrinsic measure of anthropogenic climate change. It is mainly the result of the thermal expansion of the warming ocean's water and the increase of ocean's mass from melting terrestrial ice (Rhein et al., 2013; Church et al., 2013; Frederikse et al., 2020). Global mean sea level rise is a major driver of the regional (Hamlington et al., 2018) and coastal sea level extremes (Woodworth and Men´endez,2015; Marcos and Woodworth, 2017) that impact millions of human lives and assets (Anthoff et al., 2006; Nicholls et al., 2011), and threatens ecosystems (Craft et al., 2009).
    [Show full text]
  • Latitudinal Structure of the Meridional Overturning Circulation Variability on Interannual to Decadal Time Scales in the North Atlantic Ocean
    1MAY 2020 Z O U E T A L . 3845 Latitudinal Structure of the Meridional Overturning Circulation Variability on Interannual to Decadal Time Scales in the North Atlantic Ocean a SIJIA ZOU AND M. SUSAN LOZIER Duke University, Durham, North Carolina XIAOBIAO XU Center for Ocean–Atmospheric Prediction Studies, Florida State University, Tallahassee, Florida (Manuscript received 22 March 2019, in final form 31 January 2020) ABSTRACT The latitudinal structure of the Atlantic meridional overturning circulation (AMOC) variability in the North Atlantic is investigated using numerical results from three ocean circulation simulations over the past four to five decades. We show that AMOC variability south of the Labrador Sea (538N) to 258N can be decomposed into a latitudinally coherent component and a gyre-opposing component. The latitudinally co- herent component contains both decadal and interannual variabilities. The coherent decadal AMOC vari- ability originates in the subpolar region and is reflected by the zonal density gradient in that basin. It is further shown to be linked to persistent North Atlantic Oscillation (NAO) conditions in all three models. The in- terannual AMOC variability contained in the latitudinally coherent component is shown to be driven by westerlies in the transition region between the subpolar and the subtropical gyre (408–508N), through sig- nificant responses in Ekman transport. Finally, the gyre-opposing component principally varies on interan- nual time scales and responds to local wind variability related to the annual
    [Show full text]
  • 2019 Ocean Surface Topography Science Team Meeting Convene
    2019 Ocean Surface Topography Science Team Meeting Convene Chicago 16 West Adams Street, Chicago, IL 60603 Monday, October 21 2019 - Friday, October 25 2019 The 2019 Ocean Surface Topography Meeting will occur 21-25 October 2019 and will include a variety of science and technical splinters. These will include a special splinter on the Future of Altimetry (chaired by the Project Scientists), a splinter on Coastal Altimetry, and a splinter on the recently launched CFOSAT. In anticipation of the launch of Jason-CS/Sentinel-6A approximately 1 year after this meeting, abstracts that support this upcoming mission are highly encouraged. Abstracts Book 1 / 259 Abstract list 2 / 259 Keynote/invited OSTST Opening Plenary Session Mon, Oct 21 2019, 09:00 - 12:35 - The Forum 12:00 - 12:20: How accurate is accurate enough?: Benoit Meyssignac 12:20 - 12:35: Engaging the Public in Addressing Climate Change: Patricia Ward Science Keynotes Session Mon, Oct 21 2019, 14:00 - 15:45 - The Forum 14:00 - 14:25: Does the large-scale ocean circulation drive coastal sea level changes in the North Atlantic?: Denis Volkov et al. 14:25 - 14:50: Marine heat waves in eastern boundary upwelling systems: the roles of oceanic advection, wind, and air-sea heat fluxes in the Benguela system, and contrasts to other systems: Melanie R. Fewings et al. 14:50 - 15:15: Surface Films: Is it possible to detect them using Ku/C band sigmaO relationship: Jean Tournadre et al. 15:15 - 15:40: Sea Level Anomaly from a multi-altimeter combination in the ice covered Southern Ocean: Matthis Auger et al.
    [Show full text]
  • Evaluation of Four Global Ocean Reanalysis Products for New Zealand Waters–A Guide for Regional Ocean Modelling
    New Zealand Journal of Marine and Freshwater Research ISSN: 0028-8330 (Print) 1175-8805 (Online) Journal homepage: https://www.tandfonline.com/loi/tnzm20 Evaluation of four global ocean reanalysis products for New Zealand waters–A guide for regional ocean modelling Joao Marcos Azevedo Correia de Souza, Phellipe Couto, Rafael Soutelino & Moninya Roughan To cite this article: Joao Marcos Azevedo Correia de Souza, Phellipe Couto, Rafael Soutelino & Moninya Roughan (2020): Evaluation of four global ocean reanalysis products for New Zealand waters–A guide for regional ocean modelling, New Zealand Journal of Marine and Freshwater Research, DOI: 10.1080/00288330.2020.1713179 To link to this article: https://doi.org/10.1080/00288330.2020.1713179 Published online: 22 Jan 2020. Submit your article to this journal View related articles View Crossmark data Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=tnzm20 NEW ZEALAND JOURNAL OF MARINE AND FRESHWATER RESEARCH https://doi.org/10.1080/00288330.2020.1713179 RESEARCH ARTICLE Evaluation of four global ocean reanalysis products for New Zealand waters–A guide for regional ocean modelling Joao Marcos Azevedo Correia de Souza a, Phellipe Coutoa, Rafael Soutelinob and Moninya Roughanc,d aA division of Meteorological Service of New Zealand, MetOcean Solutions, Raglan, New Zealand; bOceanum Ltd, Raglan, New Zealand; cMeteorological Service of New Zealand, Auckland, New Zealand; dSchool of Mathematics and Statistics, University of New South Wales, Sydney, NSW, Australia ABSTRACT ARTICLE HISTORY A comparison between 4 (near) global ocean reanalysis products is Received 10 June 2019 presented for the waters around New Zealand.
    [Show full text]
  • Developing European Operational Oceanography for Blue Growth, Climate Change Adaptation and Mitigation, and Ecosystem-Based Management
    Ocean Sci., 12, 953–976, 2016 www.ocean-sci.net/12/953/2016/ doi:10.5194/os-12-953-2016 © Author(s) 2016. CC Attribution 3.0 License. Developing European operational oceanography for Blue Growth, climate change adaptation and mitigation, and ecosystem-based management Jun She1, Icarus Allen2, Erik Buch3, Alessandro Crise4, Johnny A. Johannessen5, Pierre-Yves Le Traon6, Urmas Lips7, Glenn Nolan4, Nadia Pinardi8, Jan H. Reißmann9, John Siddorn10, Emil Stanev11, and Henning Wehde12 1Department of Research, Danish Meteorological Institute, Copenhagen, Denmark 2Plymouth Marine Laboratory, Plymouth, UK 3EuroGOOS AISBL, Brussels, Belgium 4Istituto Nazionale di Oceanografia e di Geofisica Sperimentale, Trieste, Italy 5Nansen Environmental and Remote Sensing Center, Bergen, Norway 6Mercator Ocean and Ifremer, Ramonville St. Agne, France 7Marine Systems Institute, Tallinn University of Technology, Tallinn, Estonia 8Department of Physics and Astronomy, Alma Mater Studiorum University of Bologna, Italy 9Bundesamt für Seeschifffahrt und Hydrographie, Hamburg, Germany 10Met Office, Exeter, UK 11Department of Data Analysis and Data Assimilation, Helmholtz-Zentrum Geesthacht, Hamburg, Germany 12Institute of Marine Research, Bergen, Norway Correspondence to: Jun She ([email protected]) Received: 26 October 2015 – Published in Ocean Sci. Discuss.: 21 January 2016 Revised: 13 June 2016 – Accepted: 14 June 2016 – Published: 26 July 2016 Abstract. Operational approaches have been more and more Oceanography” and “Operational Ecology” aim at develop- widely developed and used for providing marine data and ing new operational approaches for the corresponding knowl- information services for different socio-economic sectors of edge areas. the Blue Growth and to advance knowledge about the marine environment. The objective of operational oceanographic re- search is to develop and improve the efficiency, timeliness, robustness and product quality of this approach.
    [Show full text]
  • ANALYZING EL NIÑO- SOUTHERN OSCILLATION SENSITIVITY in a LARGE ENSEMBLE of OCEAN REANALYSES a Thesis by KELLEY BRADLEY Submitt
    ANALYZING EL NIÑO- SOUTHERN OSCILLATION SENSITIVITY IN A LARGE ENSEMBLE OF OCEAN REANALYSES A Thesis by KELLEY BRADLEY Submitted to the Office of Graduate and Professional Studies of Texas A&M University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE Chair of Committee, Benjamin Giese Committee Members, Achim Stössel Ping Chang Howard Seidel Head of Department, Debbie Thomas May 2015 Major Subject: Oceanography Copyright 2015 Kelley Bradley ABSTRACT A 56-member ensemble of ocean reanalyses is used to explore strong El Niño events in two 5-year periods, 1916 to 1920 and 1996 to 2000, that have markedly different quantities of observations. To generate the 56 forcing fields, we use a 56 member atmospheric reanalysis (20CRv2 system). Prescribed as boundary conditions were 8 different sea surface temperature (SST) estimates from an ocean reanalysis system, SODA with sparse input (SODA.si1), resulting in 8 sets of 7 ensemble members each. The 56 atmospheric reanalyses were used to force an ocean reanalysis for the same two time periods. The ocean reanalyses, SODA_XP, are used to explore ENSO sensitivity in the tropical Pacific Ocean. Results from the two periods show two sources of uncertainty in the reanalyses. One source is the inherent atmospheric noise that partially causes the representation of the same ENSO event to vary widely in strength, duration, and location among the 56 ensemble members. For example, warming during the 1918/1919 event in some members is far in the eastern equatorial Pacific Ocean while in other members the major warming is in the central Pacific.
    [Show full text]
  • Steric Sea Level Changes from Ocean Reanalyses at Global and Regional Scales
    water Article Steric Sea Level Changes from Ocean Reanalyses at Global and Regional Scales Andrea Storto 1,*, Antonio Bonaduce 2, Xiangbo Feng 3,4 and Chunxue Yang 5 1 Centre for Maritime Research and Experimentation, 19126 La Spezia SP, Italy 2 Helmholtz-Zentrum Geesthacht Centre for Materials and Coastal Research (HZG), 21502 Geesthacht, Germany; [email protected] 3 National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading RG6 6AH, UK; [email protected] 4 State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China 5 Institute of Marine Sciences, National Research Council of Italy, 00133 Rome, Italy; [email protected] * Correspondence: [email protected] Received: 31 July 2019; Accepted: 10 September 2019; Published: 24 September 2019 Abstract: Sea level has risen significantly in the recent decades and is expected to rise further based on recent climate projections. Ocean reanalyses that synthetize information from observing networks, dynamical ocean general circulation models, and atmospheric forcing data offer an attractive way to evaluate sea level trend and variability and partition the causes of such sea level changes at both global and regional scales. Here, we review recent utilization of reanalyses for steric sea level trend investigations. State-of-the-science ocean reanalysis products are then used to further infer steric sea level changes. In particular, we used an ensemble of centennial reanalyses at moderate spatial resolution (between 0.5 0.5 and 1 1 degree) and an ensemble of eddy-permitting reanalyses to × × quantify the trends and their uncertainty over the last century and the last two decades, respectively.
    [Show full text]
  • Ocean Reanalyses
    Ocean reanalyses Book or Report Section Published Version Haines, K. (2018) Ocean reanalyses. In: Chassignet, E. P., Pascual, A., Tintoré, J. and Verron, J. (eds.) New Frontiers in Operational Oceanography. GODAE OceanView. ISBN 9781720549970 doi: https://doi.org/10.17125/gov2018 Available at http://centaur.reading.ac.uk/80495/ It is advisable to refer to the publisher’s version if you intend to cite from the work. See Guidance on citing . Identification Number/DOI: https://doi.org/10.17125/gov2018 <https://doi.org/10.17125/gov2018> Publisher: GODAE OceanView All outputs in CentAUR are protected by Intellectual Property Rights law, including copyright law. Copyright and IPR is retained by the creators or other copyright holders. Terms and conditions for use of this material are defined in the End User Agreement . www.reading.ac.uk/centaur CentAUR Central Archive at the University of Reading Reading’s research outputs online C HAPTER 19 Ocean Reanalyses Keith Haines Meteorology Dept., University of Reading, Earley Gate, Reading RG6 6AL, UK Ocean reanalyses are becoming increasingly available and useful, and may eventually attract a similar applications base as atmospheric reanalyses. Here we look at how they are being evaluated against both assimilated and independent data, and emphasise that circulation and transport estimates are critical. The Ocean Reanalysis Intercomparison project, ORA-IP, has been comparing many products for consistency on a regional and global basis, including ocean heat content, air-sea fluxes, and recently polar properties including sea ice. The Atlantic meridional overturning circulation as measured by the RAPID array at 26N, is now a challenging new target for simulation.
    [Show full text]
  • Altimetry for the Future: Building on 25 Years of Progress
    Available online at www.sciencedirect.com ScienceDirect Advances in Space Research xxx (xxxx) xxx www.elsevier.com/locate/asr Altimetry for the future: Building on 25 years of progress International Altimetry Teamà Received 16 August 2020; received in revised form 11 January 2021; accepted 13 January 2021 Abstract In 2018 we celebrated 25 years of development of radar altimetry, and the progress achieved by this methodology in the fields of glo- bal and coastal oceanography, hydrology, geodesy and cryospheric sciences. Many symbolic major events have celebrated these devel- opments, e.g., in Venice, Italy, the 15th (2006) and 20th (2012) years of progress and more recently, in 2018, in Ponta Delgada, Portugal, 25 Years of Progress in Radar Altimetry. On this latter occasion it was decided to collect contributions of scientists, engineers and man- agers involved in the worldwide altimetry community to depict the state of altimetry and propose recommendations for the altimetry of the future. This paper summarizes contributions and recommendations that were collected and provides guidance for future mission design, research activities, and sustainable operational radar altimetry data exploitation. Recommendations provided are fundamental for optimizing further scientific and operational advances of oceanographic observations by altimetry, including requirements for spatial and temporal resolution of altimetric measurements, their accuracy and continuity. There are also new challenges and new openings men- tioned in the paper that are particularly crucial for observations at higher latitudes, for coastal oceanography, for cryospheric studies and for hydrology. The paper starts with a general introduction followed by a section on Earth System Science including Ocean Dynamics, Sea Level, the Coastal Ocean, Hydrology, the Cryosphere and Polar Oceans and the ‘‘Green” Ocean, extending the frontier from biogeochemistry to marine ecology.
    [Show full text]
  • The ECMWF Operational Ensemble Reanalysis-Analysis System for Ocean and Sea-Ice
    Ocean Sci. Discuss., https://doi.org/10.5194/os-2018-154 Manuscript under review for journal Ocean Sci. Discussion started: 8 January 2019 c Author(s) 2019. CC BY 4.0 License. The ECMWF operational ensemble reanalysis-analysis system for ocean and sea-ice: a description of the system and assessment Hao Zuo1, Magdalena Alonso Balmaseda1, Steffen Tietsche1, Kristian Mogensen1, and Michael Mayer1 1The European Centre for Medium-Range Weather Forecasts, Shinfield Rd, Reading U.K. RG2 9AX Correspondence: Hao Zuo ([email protected]) Abstract. The ECMWF OCEAN5 system is a global ocean and sea-ice ensemble of reanalysis and real-time analysis. This manuscript gives a full description of the OCEAN5 system, with the focus on upgrades of system components with respect to its predecessors ORAS4 and ORAP5. An important novelty in OCEAN5 is the ensemble generation strategy that includes perturbation of initial conditions, and a generic perturbation scheme for observations and forcing fields. Other upgrades include 5 revisions to the a-priori bias correction scheme, observation quality control and assimilation method for sea-level anomaly. The OCEAN5 historical reconstruction of the ocean and sea-ice state is the ORAS5 reanalysis, which includes 5 ensemble members and covers the period from 1979 onwards, and with a backward extension until 1958. Updated version of observation data sets are used in ORAS5 production, with special attention devoted to the consistency of sea surface temperature (SST) and sea-ice observations. Assessment of ORAS5 in the observation space suggests that assimilation of observations contribute to reducing 10 the analysis error, with the most prominent contribution from direct assimilation of ocean in-situ observations.
    [Show full text]