OGP-IPIECA
OSR-JIP
REVIEW OF MODELS AND METOCEAN DATABASES
Final report
OGP-IPIECA REPORT № MOC-0970-01 V1.2 2015/02/23
ACTIMAR - 36, Quai de la Douane – F-29200 Brest - Tél: +33 256 35 56 20 - Fax: +33 298 46 91 04 e-mail: [email protected] - web: http://www.actimar.fr
OGP-IPIECA - Review of models and metocean databases Report № MOC-0970-01 - V1.2 – 2015/02/23
REVISIONS
Version Date Changes Written by Checked by S. Casitas 0.1 17/10/2014 Outline of the report S. Legac H. Pineau 0.2 04/11/2014 Misc corrections S. Casitas 1.0 23/12/2014 Models evaluation H. Pineau C. Heyraud Corrections after comments. S. Casitas 1.1 13/02/2014 Updated GFS information H. Pineau C. Heyraud Addition of filled questionnaires 1.2 23/02/2014 OGP-IPIECA reference H. Pineau
DISTRIBUTION
Addressee Company Date of review IPIECA
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OGP-IPIECA - Review of models and metocean databases Report № MOC-0970-01 - V1.2 – 2015/02/23
TABLE OF CONTENTS
ACRONYMS ...... 4
EXECUTIVE SUMMARY...... 11
1 INTRODUCTION...... 14 1.1 CONTEXT ...... 14 1.2 CONTENTS ...... 15 1.3 GLOSSARY ...... 15
2 WP3: MODELLING AND PREDICTION...... 17 2.1 METHODOLOGY ...... 17 2.1.1 General...... 17 2.1.2 Review of hydrodynamic models...... 18 2.1.3 Review of atmospheric models...... 22 2.2 REVIEW OF HYDRODYNAMIC MODELS ...... 25 2.2.1 Global configurations ...... 25 2.2.2 Brazil...... 27 2.2.3 Gulf of Mexico ...... 29 2.2.4 Gulf of Guinea...... 31 2.2.5 Australia NW shelf...... 33 2.2.6 North sea ...... 35 2.2.7 South China Sea...... 37 2.2.8 Caspian Sea ...... 39 2.2.9 Mediterranean Sea...... 40 2.2.10 Indian Ocean...... 42 2.3 REVIEW OF ATMOSPHERIC MODELS ...... 44 2.3.1 Global ...... 44 2.3.2 Brazil...... 48 2.3.3 Gulf of Mexico ...... 49 2.3.4 Gulf of Guinea...... 50 2.3.5 Australia NW shelf...... 51 2.3.6 North Sea...... 52 2.3.7 South China Sea...... 53 2.3.8 Caspian Sea ...... 54 2.3.9 Mediterranean Sea...... 55 2.3.10 Indian ocean ...... 57
3 WP4: METOCEAN DATABASES ...... 58 3.1 METHODOLOGY ...... 58 3.1.1 Definition...... 58 3.1.2 Inventory ...... 59
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3.2 DATA REVIEW ...... 60 3.2.1 Global ...... 60 3.2.2 Brazil...... 62 3.2.3 Gulf of Mexico ...... 63 3.2.4 Gulf of Guinea...... 64 3.2.5 Australia...... 66 3.2.6 North sea ...... 68 3.2.7 South China Sea...... 68 3.2.8 Caspian Sea ...... 68 3.2.9 Mediterranean Sea...... 69 3.2.10 Indian Ocean...... 69
4 CONCLUSIONS AND RECOMMENDATIONS...... 71 4.1 CONCLUSIONS ...... 71 4.2 RECOMMENDATIONS ON VALIDATION TECHNIQUES ...... 71 4.3 LIMITATIONS OF THE WORK ...... 72 4.4 FROM DATA TO BIG DATA ...... 72
5 REFERENCES...... 73
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ACRONYMS
General GCM General Circulation Model (or Global Climate Model) GIS Geographic Information System GoG Gulf of Guinea GoM Gulf of Mexico
GRIB GRidded Information in Binary ETOPO Earth Topographic dataset GEBCO General Bathymetric Chart of the Oceans JIP Joint Industry Project NE North East NetCDF Network Common Data format NW North West OGCM Ocean Global Circulation Model OSR Oil Spill and Response WP Work package
Organizations and companies AOML Atlantic Oceanographic and meteorological Laboratory (NOAA, USA) BOM Bureau of Meteorology (Australia) CLS Collecte Localisation Satellites (France) CMC Canadian Meteorological Center (Canada) CMCC Euro-Mediterranean Center on Climate Change (Italy) CNMCA National Center of Meteorology and Climatology (Italy) CNRS Centre National de la Recherche Scientifique (France) CPTEC/INPE Centro de Previsão de Tempo e Estudos Climáticos / Instituto National de Pesquisas Espaciais (Brazil) CUA Catholic University of America (USA) CSIRO Commonwealth Scientific and Industrial Research Organisation DHI Danish Hydraulic Institute (Denmark) DHN Navy Hydrology Center (Brazil)
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DWD Deutscher Wetterdienst (Germany) DMI Danish Meteorological Institute (Denmark) ECMWF European Centre for Medium-Range Weather Forecasts FMI Finnish Meteorological Institute (Finland) FNMOC Fleet Numerical Meteorology and Oceanography Center (USA) FSL Forecast System Laboratory (NOAA, USA) GMAO Global Modeling and Assimilation Office (USA) GNOO Gruppo Nazionale di Oceanografia Operativa (Italy) GODAE Global Ocean Data Assimilation Experiment HNMS Helenic National Meteorological Service (Greece) IFREMER Institut Français de Recherche pour l’Exploitation de la Mer (France) IMGW Institute of Meteorology and Water Management (Poland) INCOIS Indian National Centre for Ocean Information Services (India) INGV, Istituto Nazionale di Geofisica e Vulcanologia (Italy) IOC Intergovernmental Oceanographic Commission of UNESCO INMET Instituto nacional de meteorologia (Brazil) INPE Instituto Nacional de Pesquisas Espaciais IPIECA International Petroleum Industry Environmental Conservation Association ISO International Organization for Standardization JCOMM WMO-IOC Joint Technical Commission for Oceanography and Marine Meteorology JMA Japan Meteorological Agency KFUPM King Fahad University of Petroleum and Minerals (Saudi Arabia) KNMI Koninklijk Nederlands Meteorologisch Instituut LATMOS-IPSL Laboratoire Atmosphères, Milieux, Observations Spatiales - Institut Pierre et Simon Laplace (France) LOCEAN Laboratoire d’Oceanographie et du Climat (France) MET-Norway Norwegian Meteorological Institute (Norway) MCGA Maritime and Coastguard Agency (UK) MUMM Management Unit of the Mathematical Model (Belgium) NASA National Aeronautics and Space Administration (USA) NAVO Naval Oceanographic Office (USA)
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NCAR National Centre for Atmospheric Research (USA) NERC Natural Environment Research Council (UK) NERSC Nansen Environmental and Remote Sensing Center (Norway) NCEP National Centers for Environmental Prediction (USA) NCOF National Centre for Ocean Forecast (UK) NMA National Meteorological Administration NMEFC National Marine Environment Forecast Centre of China NOAA National Oceanic and Atmospheric Administration (USA) NODC National Oceanographic Data Center (UK) NOS NOAA National Ocean Service 5USA) NRL Naval Research Laboratory (US) OGP International Association of Oil and Gas Producers OWI OceanWeather Inc. (USA) OWS Ocean Weather Service REMO Rede de Modelagem e Observação Oceanográfica (Brazil) TGLO Texas Gen. Land Office (USA) UNESCO United Nations Educational, Scientific and Cultural Organization USAM Ufficio Generale Spazio Aereo e Meteorologia (Italy) USF University of South Florida (USA) UWA University of Western Australia WMO World Meteorological Organization
Hydrodynamic models codes ADCIRC Advanced Circulation Model COHERENS Coupled Hydrodynamical-Ecological Model for Regional and Shelf Seas DieCAST Dietrich Center for Air Sea Technology FVCOM Finite Volume Community Ocean Model HBM HIROMB-BOOS-Model1 HCM CLS Hybrid Current Model HYCOM HYbrid Coordinate Ocean Model MARS3D Model for Applications at Regional Scales MIKE DHI model
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MOHID MOdelo HIDrodinamico MOM Modular Ocean Model MSEAS Multidisciplinary Simulation, Estimation, and Assimilation Systems NEMO Nucleus for European Modelling POLCOMS Proudman Oceanographic Laboratory Coastal Ocean Modelling System POM Princeton Ocean Model ROMS Regional Ocean Modeling System
Hydrodynamic model configurations (not exhaustive selection) BRAN3 Bluelink ReANalysis BSHcmod Bundesamt für Seeschifffahrt und Hydrographie circulation model CASMOS OWI Caspian Sea Meteorological and Oceanographic Study ECMWF European Centre for Medium-Range Weather Forecasts GBOFS Galveston Bay Operational Forecast System GROW OWI Global reanalysis of Ocean Waves FOAM Forecast Ocean Assimilation Model IASNFS Intra-Americas Sea Nowcast/Forecast System INDOFOS Indian Ocean Forecast System MACH Mid Atlantic Current Hindcast NAMOS North Australia MetOcean Study NEXT Northern European Storm Study (NESS) eXTension NCOM Navy Coastal Ocean Model NGOFS Northern Gulf of Mexico Operational Forecast System OFAM3 Ocean Forecasting Australia Model ORCA name of the global ocean model NEMO configurations. PERGOS OWI Persian Gulf Oceanography Study RTOFS Real-Time Ocean Forecast System SABGOM South Atlantic Bight Gulf of Mexico SEAFINE SEAMOS-South Fine Grid Hindcast SEAMOS South East Asia Meteorological and Oceanographic Hindcast Study TBOFS Tampa Bay Operational Forecast System
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TOPAZ (Towards) an Operational Prediction system for the North Atlantic European coastal Zones WANE West Africa Normals and Extremes WFCOM USF West Florida Coastal Ocean Model Atmospheric models and products ACCESS Australian Community Climate and Earth-System Simulator ALADIN Aire Limitée Adaptation dynamique Développement InterNational ARPEGE Action de Recherche Petite Echelle Grande Echelle ARW Advanced Research WRF BOM GASP BOM Global/Regional Assimilation Prognosis CANARI Code for the Analysis Necessary for Arpege for its initialization CFSR Climate Forecast System Reanalysis COAMPS Coupled Ocean / Atmosphere Mesoscale Prediction System COSMO Consortium for Small-scale Modeling (COSMO) ERA-40 ECMWF re-analysis ERA-Interim ECMWF re-analysis FNL Final NCEPOperational Global Analysis GDAS Global data assimilation system GEM Global Environmental Multiscale Model GEOS-5 Goddard Earth Observing System Data Assimilation System Version 5 GFS Global Forecast System GME Generic Modeling Environment GPD Global Determinist Prediction HIRLAM Higth resolution limited area model ICLAMS Integrated Community Limited Area Modeling System IFS Integrated Forecast System LAPS Low Atmospheric Pressure system MERRA Modern-ERA Retrospective Analysis for Research And Applications MetUM Met Office Unified Model NAM North American Mesoscale Model NAM-HIRES NAM High Res Window NARR North American Regional Reanalysis
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NAVGEM Navy Global Environmental Model NCEP R1,R2 NCEP Reanalysis 1 and 2 NEXTRA Northern European Metocean Reanalysis NHM Non-Hydrostatic Model NMM Nonhydrostatic Mesoscale Model NOGAPS Navys Operational Global Atmospheric Prediction System NORA10 Norwegian reanalysis NRA NCEP Reanalysis RAM Regional Atmospheric Model RAMS Regional Atmospheric Modeling RAP Rapid Refresh RUC Rapid Update Cycle TXLAPS Tropical eXtended Area Prediction System UKV UK Variable model
Observation systems, sensors and parameters (selection) ADCP Acoustic Doppler Current Profiler COOS Coastal Ocean Observing System GOOS Global Ocean Observing System GCOM Global Coastal-Ocean Modelling GPD Global Drifter Program (AOML-NOAA) HF radar High Frequency radar SLA Sea Level Anomaly SMOS Soil Moisture and Ocean Salinity SSH Sea Surface Height SST Sea Surface Temperature
Data assimilation terms 3/4DVAR Three/four Dimensional Variational (assimilation) C&H Cooper & Haines scheme EnKF Ensemble Kalman Filter EnOI Ensemble Optimal Interpolation
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NCODA Navy Coupled Ocean Data Assimilation SEEK Singular Evolutive Extended Kalman SEIK Singular Evolutive Interpolation Kalman
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EXECUTIVE SUMMARY
This report is one of a series of reports in the OGP IPIECA Oil Spill JIP which examine the latest tools and techniques under the headings of "Surveillance, modelling and visualisation." Under the modelling heading, two reports cover models, metocean databases and validation techniques. This report provides information and recommendations on modelling and metocean databases.
OGP-IPIECA WP3: Modelling and Prediction The following tables present the recommended hydrodynamic and atmospheric models of interest in each basin. The selection criteria are discussed respectively in section 2.2 for hydrodynamic models and in section 2.3 for atmospheric models. These recommendations are based on the available information during the study.. They are subject to future revision based on experience in their application and feedback from operators and responders.
Basin Operational forecast Hindcast Brazil CLS-HCM (CLS, France) CLS-HCM (CLS, France) REMO (Brazil) in progress REMO (Brazil) in progress Gulf of Mexico HYCOM GoM (NRL, Stennis, USA) HYCOM GoM (NRL, Stennis, USA) NCOM AMSEAS (NAVO, USA) Coastal models (zooms) Gulf of Guinea SAT-OCEAN (France) SAT-OCEAN (France) MACH (UKMO, BMT ARGOSS, OWI) Australia – OFAM3 (BOM, BlueLink, Australia) NAMOS (OWI, USA) NW shelf
North Sea MIKE (DHI, Denmark) POLCOMS FOAM AMM Shelf Sea (UK MetOffice) FOAM AMM (UK MetOffice) OPTOS/COHERENS (MUMM, Belgium) South China HYCOM (NRL, USA) HYCOM Global Sea ORCA-INDESO (CLS, France) in SEAFINE (OWI, USA) progress Caspian Sea CASMOS (OWI, USA) Indian Ocean FOAM Indian Ocean (NCOF, UK) TAMOMS (SAT-OCEAN, France) Global HYCOM (NRL, USA) Mediterranean MFS (MyOCEAN) MFS (MyOcean) Sea
Table 0-1: Recommended hydrodynamic forecast and hindcast for oil spill response
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Basin Forecast Hindcast Brazil BRAMS (INPE, Brazil) Global (e.g. NCEP-CFSR) ETA (INPE, Brazil) Gulf of Mexico NAM (NCEP, USA) NARR (NCEP, USA) RUC (NOAA-NCEP, USA) Gulf of Guinea ARPEGE-TROPICS (Météo-France) Global (e.g. NCEP-CFSR) Global (e.g. GFS, USA) Australia – ACCESS (BOM) Global (e.g. NCEP-CFSR) NW shelf North Sea Unified Model (UK MetOffice) NORA-10 (Met Norway) HIRLAM (Denmark, Finland, Global (e.g. ERA-Interim, ECMWF) Netherland, Norway,) South China ACCESS (BOM) GASP (BOM, Australian) Sea Global (e.g. NCEP-CFSR) Caspian Sea CASMOS (OWI, USA) Indian Ocean NCMRWF (India) Global (e.g. NCEP-CFSR) Mediterranean SKIRON (University of Athens, SKIRON (University of Athens, Sea Greece) Greece) Global (e.g. ERA-Interim, ECMWF)
Table 0-2: Recommended atmospheric models for OSR
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OGP-IPIECA WP4: Metocean databases The principal meteocean observation databases are listed by basin in the following tables. The regional databases are given on the left column. The main global databases of interest for validation of models are presented in the right column. These recommendations are based on the available information during the study. They are subject to future revision based on experience in their application and feedback from operators and responders.
Basin Regional databases Global databases
Brazil OCEATLAN (Argentina, Brazil, and Uruguay)
REMO, PNBIOA (Brazil)
Gulf of Mexico GCOOS (USA)
Gulf of Guinea ODINAFRICA (UNESCO) AOML-NOAA Global Drifter program (GPD) Australia – NW IMOS facilities :including WAIMOS, ACORN shelf (Australia) NOAA-NDCD (USA)
North Sea BODC CORIOLIS
MyOCEAN MyOCEAN
South China NEAR-GOOS (China, Japan, the Republic of JCOMMOPS Sea Korea and the Russian Federation) SIMORC
Caspian Sea CASPINFO (EU) etc
Indian Ocean WIOCOS (South Africa) Mediterranean MOOSE network (France) Sea MONGOOS
Table 0-3: Useful regional and global metocean databases by basin
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1 INTRODUCTION
1.1 CONTEXT
OGP-IPIECA has requested Actimar to review and assess the hydrodynamic and wind models and metocean data for oil spill modelling in the scope of the Oil Spill Response (OSR) Joint Industry Project (JIP): The work consists of: - Inventory and inter-comparison of hydrodynamic and atmospheric models (hindcast and forecast) - Collating, reviewing and assessing the available metocean databases to provide in- situ data to calibrate and validate numerical models. The objective is to identity several good quality (standard) data sets to validate oil spill models in each basin. - Recommendations on validation technique for hydrodynamic models The complete list of regions of interest is given in Table 1-1 (sorted by high/medium priority)
Priority Basin Sea/Ocean Countries High Brazil Atlantic Ocean Brazil High Gulf of Mexico Gulf of Mexico US, Mexico High Gulf of Guinea Atlantic Ocean Côte d'Ivoire, Ghana, Benin, Nigeria, Cameroon, equatorial Guinea, Gabon, Congo, Dem. Rep. of Congo , Angola, Namibia High Australia - NW Shelf Indian Ocean, Timor Sea Australia High North Sea North Sea UK, Netherlands, Denmark, Norway High South China Sea South China Sea, Gulf of Thailand, Indonesia, Thailand, Malaysia, China, Java Sea and Makassar Strait Brunei, Vietnam High Caspian Sea Caspian Sea Azerbaijan, Kazakhstan, Russia, Turmenistan High Indian Ocean Indian Ocean, Arabian Sea, Gulf of Bangladesh, India, Oman, Yemen, Kenya, Oman, Bay of Bengal Tanzania, Mozambique, South Africa High NE Mediterranean Sea Mediterranean Sea Egypt Medium Persian Gulf Persian Gulf Iran, Irak, Kuwet, Qata, saudi Arabia, UAE
Medium Mediterranean Sea Mediterranean Sea Algeria, Lybia, Cyprius, Lebanon, Turkey Medium Black Sea Black Sea Russia, Ukrainia, Bulgaria, Turkey Medium Barents Sea Barents Sea Russia Medium Baltic Sea Baltic Sea Sweden, Finland Medium Norwegian Sea Norwegian Sea Norway Medium Irish Sea Irish Sea Ireland, UK Medium Andaman Sea Andaman Sea Myanmar Medium East China Sea East China Sea China Medium Carribean Sea Carribean Sea Aruba, Trindada & Tobago, Venezuela Medium North-west Atlantic Atlantic Ocean Ireland, UK Medium South-East Atlantic Atlantic Ocean Morrocco, Mauritania, South Africa Medium SouthWest Atlantic Atlantic Ocean Argentina, Uruguay, French Guinea, Guyana, Surinam Medium West coast of Canada Pacific Ocean Canada Medium East coast of Canada Atlantic Ocean Canada Medium Coral Sea Pacific Ocean Autralia, Papua New Guinea Table 1-1: Regions of interest
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1.2 CONTENTS
The present MOC-0970-01 report includes the listing of the reviewed hydrodynamic and atmospheric models (WP3) and the review of metocean databases (WP4). It is completed by the following EXCEL spreadsheets attached as appendix: - Summary spreadsheet with exhaustive list of identified hydrodynamic models. - Zipped files of model and database datasheets - Hydrodynamic model evaluation spreadsheet
The “ Recommendations on Validation Techniques ” MOC-0970-02 report is provided in a separate PDF document.
1.3 GLOSSARY
This section gives the WMO definitions of some terms relative to the hydrodynamic and atmospheric model and their outputs and other clarifications in the scope of this study. Ocean Global Circulation Model (OGCM) : mathematical model of the general circulation of a planetary atmosphere or ocean and based on the Navier–Stokes equations on a rotating sphere with thermodynamic terms for various energy sources (radiation, latent heat). Hydrodynamic model : Flow model where the movement of fluids is described by a set of hydrodynamic equations that represent, in general, the combination of a mass balance equation with either a velocity equation, resulting from an empirical relation such as Darcy's law, or momentum equations, such as Navier-Stokes equations. [International Glossary of Hydrology, WMO/UNESCO, 2011] Model code : generic computer code implementing the mathematical model. Model configuration : Set of parameter configuration, including selection of spatio-temporal grid, bathymetry, physical parameterization, forcings, etc Analysis : detailed study of the state of the atmosphere/ocean over a particular region based on the actual observations. [International Meteorological Vocabulary, WMO - No. 182] Archives : Archive data provide history of past weather/hydrodynamic forecast or analyses from operational forecasting systems. Forecast: Estimate of the magnitude and time of occurrence of a future event. [International Glossary of Hydrology, WMO/UNESCO, 2011] Hindcast: Archive of simulation results using past events as inputs into the operational numerical atmospheric/hydrodynamic model. A hindcast is produced with a consistent numerical model and is usually available for a period of several years. Hindcast is a more generic term than reanalysis and not always include analysis.
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Nowcast : description of current weather and a short-period (0-2 hours) forecast. [International Meteorological Vocabulary, WMO - No. 182 ] Reanalysis : atmospheric and oceanic analyses of temperature, wind, current, and other meteorological and oceanographic quantities, created by processing past meteorological and oceanographic data using fixed state-of-the-art weather forecasting models and data assimilation techniques. Using fixed data assimilation avoids effects from the changing analysis system that occurs in operational analyses. Although continuity is improved, global reanalyses still suffer from changing coverage and biases in the observing systems. [IPCC 4th Assessment Report, WG 1 Glossary] Mesoscale : Dimensions of an atmospheric layer which ranges from a few kilometres to some tens of kilometres horizontally and, vertically, from the ground to the top of the friction layer. [International Meteorological Vocabulary, WMO - No. 182] Geostrophic equilibrium : Condition of the field of motion of a non-viscous fluid in which the pressure-gradient force is exactly balanced by the Coriolis force. [International Meteorological Vocabulary, WMO - No. 182]
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2 WP3: MODELLING AND PREDICTION
2.1 METHODOLOGY
2.1.1 General The hydrodynamic models review is an update and completion of a previous study on the subject [Ref 1, Ref 2]. The atmospheric models review is a first inventory. The same key information was analyzed for both types of products (model resolution, data assimilation, availability etc) but at a more advanced stage for hydrodynamic models. For these reasons, the reviews of the hydrodynamic and atmospheric models were carried out separately. That is why the evaluations are presented differently in sections 2.2 and 2.3.
This report presents a summary of the review work which has been carried out. The detailed analysis and model spreadsheets are included in the following datasheets of appendices: • Two summary spreadsheets list the reviewed models. The active filters of the first line allow a quick model selection (e.g. overview of the available models in each basin). o WP3-Hydrodynamic-models-summary_v1.0.xls o WP3-Atmospheric-models-summary_v1.0.xls • Objective criteria and marks are used for the hydrodynamic model comparison whereas colors are used for the atmospheric model comparisons in the following spreadsheets o WP3-Hydrodynamic-models-evaluation_v1.0.xls o WP3-Atmospheric-models-evaluation_v1.0.xls • The individual datasheets are archived by topic and basin. The received questionnaires filled by the manufacturers are indicated by the “_answer” suffix.
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2.1.2 Review of hydrodynamic models 2.1.2.1 Definitions: model codes and configuration In this report, the models codes and configurations are distinguished as far as possible . The section 2.2 of this report focuses on the review of existing model configurations defined as sets of parameter configuration for a given model code. A list of the numerical model codes mentioned in this report is provided in Table 2-1.
Code name Organization ADCIRC University of North Carolina at Chapel Hill, USA Delft3D Deltares, Netherlands HIROMB-BOOS-Model1 (HBM) Danish Meteorological Institute in Copenhagen, Denmark COHERENS MUMM, Belgium CUA Model Catholic University of America. Environmental Fluid Dynamics Laboratory, National Taiwan DieCAST University Marine Ecosystem Dynamics Modeling Laboratory (MEDML), Marine Science and Technology, University of Massachusetts- FVCOM Dartmouth Hybrid Current Modelling (HCM) CLS, France HYCOM Naval Research Laboratory, Stennis Space Center, USA NOAA, NCEP, USA Miami University, USA KFUPM Model King Fahad University of Petroleum and Minerals, EUA MARS3D Ifremer, France MIKE 3/21 Danish Hydraulic Institute, Denmark. MOHID Technical University of Lisbon (IST), Portugal. Modular Ocean Model (MOM) NOAA / GFDL (Geophysical Fluid Dynamics Laboratory), USA JAPAN METEOROLOGY AGENCY and Meteorological MRI .COM Research Institute (MRI) Massachusetts Institute of Technology (MIT), Department of MSEAS Mechanical Engineering, USA. NEMO Consortium: CNRS (France), Mercator-Ocean (France), NEMO NERC (UK), UKMO (UK), CMCC (Italy), INGV (Italy) POLCOMS Proudman Oceanographic Laboratory (POL), UK POM Princeton University, USA ROMS Rutgers University, USA
Table 2-1: List of the main hydrodynamic codes reported in the study
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2.1.2.2 Data inventory sources The primary sources for data inventory are taken from the reference reports: - Ajilon / Euro Engineering (EE), Inter-comparison and validation in-situ of oil spill drift model, Final report, September 2011 [Ref 1] - TOTAL, Memo CFR11-276, Inter-comparison of oil spill drift models, December 2011 [Ref 2] The information of the hydrodynamic models already listed in both above reports is updated. The inventory of newly available products is mainly based on inputs from JIP members, general organization website (GODAE, JCOMM, MyOCEAN) and more general modeling experience.
At project start, a request for information was sent to the JIP partners in order to identify the most relevant models, including the following topics: - Identification and review of the high resolution hydrodynamic models used for supporting their maritime operations (e.g. GCOOS Gulf of Mexico evaluation matrix) - List of hindcast data among the identified operational models - Definition of target Some feedbacks were received from TOTAL and CHEVRON.
In order to better assess new identified data sources (recent products or products in new zones), a questionnaire was sent to the producers of these metocean data. The details of the answers are included in the spreadsheets appendix B attached to this report. The return ratio was little. The answers were very inhomogeneous. Some questionnaires were answered with details. Details are available upon request to Actimar. Since this task was time consuming for a poor added value, it was decided not to contact again the model producers but to complete the analysis using available publications and information (internet and previous project/experience).
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2.1.2.3 Inter-comparison of hydrodynamic models The Table 2-2 lists the criteria taken into account for the models evaluation. The application of the criteria for each considered model configuration is presented in appendix. For better readability in this report, the main axes of comparisons (availability, resolution, data assimilation and evaluation) are summarized as radar plots in each basin for forecast and hindcast when applicable.
Warning : the provided evaluations are highly sensible to the level of available information and should be revised according to newly available data or published validation.
Theme Criteria Values ranges Marks (0-10) criteria Weight
Availability Public Everyone or restricted High scope if open to Medium everyone
Availability of raw Yes / no High score if available High data files
Available raw NetCDF, GRIB, ASCII, Good mark if several format High data format other binary, etc including NetCDF/GRIB and (several answer are ASCII, GIS possibles)
Availability of Yes / no High score if available Low plot/animations
Availability of In days/ years High score if long duration High archives
Price Cost in dollar High score if free or Medium reasonable price
Operability Delay Real time/ near real Good if real time High time / delayed time
Near real time Permanent / occasional Good is permanent High running
Model Time resolution From seconds to month High if at least 3-hours High Resolution of output
Time average of Instantaneous / High if instantaneous medium the output average
Forecast update In hours/days At least every day (cf. Ref2) Medium
Temporal Forecast days ahead ~3 days are required Medium windows of the
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Theme Criteria Values ranges Marks (0-10) criteria Weight forecast
Spatial horizontal From meters to km According to oil spill High resolution scenarios, better if < 500 km
Vertical Number of vertical level Low resolution
Model Bathymetry Sources High score if good quality and High performan Spatial resolution high resolution (medium ces if deepwate r)
Data assimilation Yes/no High score if assimilation High
Assimilated data Number of data By decreasing interest: 1- High sources Water level 2-SST 3-Profiles Types of data sources 4-HF radars 5-drifter (satellite/ in situ)
Assimilation OI, 3D/4D-VAR, EnKF, EnKF better than EnOI medium scheme other
Turbulence parameters NB: difficult to assess Low scheme
Tidal forcing Yes/No Useful for coastal/island area medium
Validation Authorities List of authorities medium and recommendations feedback Customers Number of customers Medium
Satisfaction of medium customer
Comparisons List of references High with in-situ data
Validation Number of exercises Better if several exercises High exercises Quality of Good if well documented documentation methods
Integration to oil spill drift Yes / No and indicate High model which one(s)
Applications List of applications Medium
Table 2-2: Hydrodynamic model criteria used for inter-comparison / scores
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2.1.3 Review of atmospheric models 2.1.3.1 Inventory of atmospheric models and products The atmospheric model codes reported in this review are listed in Table 2-3. Long term achieves are summarized Table 2-4.
Model name Manufacturer (or user)
Global model GME DWD IFS ECMWF NRL NAVGEM (old NOGAPS) FNMOC GEM CMC GEOS-5 GMAO GFS NOAA/NCEP MCGA INPE
GSM global JMA ARPEGE Météo-France Met Office Unified Model Met Office, UK (MetUM) NAVGEM NRL Regional model ALADIN Météo-France, Maroc Météo
HIRLAM FMI, DMI, KNMI, MET- Norway
UKV Met Office, UK
Euro4 Met Office, UK
COSMO DWD, INMET , DHN ,HNMS,CNMCA SKIRON University of Athens WRF OWS, LATMOS-IPSL, Stormgeo, NCEP NAMOS, CASMOS, Oceanweather Inc. NEXTRA… COAMPS FNMOC RAM University of Hawai
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NHM Hong Kong Observatory RAMS University of Athens, INPE ETA NCEP, INPE FSL Forecast System Laboratory/OAR/NOAA AROME Météo-France REMO Max Planck Institute for Meteorology
LMDZ LMD (http://lmdz.lmd.jussieu.fr/) Table 2-3: Atmospheric models listing
Hindcast product (reanalysis, analysis…) Manufacturer
Global product BOM(GASP) CSIRO Australia CFSR and CFSRv2 NCEP
ERA 40, ERA 15, ERA Interim ECMWF Operational model analyses and products ECMWF derived from short term forecast NCEP R1 & R2 NCEP/NCAR FNL Operational global analysis - GDAS NCEP LAPS, TXLAPS NOAA/ESRL MERRA NASA Regional product NARR (North American Regional Reanalysis) NCEP from ETA model FSL Forecast System Laboratory/OAR/NOAA
GEM Canada MetOffice
NORA10 (HIRLAM-10) MET- Norway
Table 2-4: hindcast products.
2.1.3.2 Evaluation of the models Considering, firstly, the global area and, secondly, each region of interest, the atmospheric model and their configuration characteristics are detailed in dedicated tables and notations are given as follows:
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upon free charged Availibility request GRIB, ASCII Data format netcdf others Time resolution < 3 hours 3-6 hours > 6 hours Forecast length > 4 days 2-4 days < 2 days
Time coverage > 10 years 2-10 years < 2 years Spatial Resolution <10km 10-50km >50km
Assimilation yes no Validation yes no
Table 2-5: Classification criteria to evaluate model performances as good (yellow), medium (orange), poor (red)
Warning : the models list is not exhaustive and configuration characteristics have been detailed when the information were found available.
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2.2 REVIEW OF HYDRODYNAMIC MODELS
The tables below summarize the names of the identified models in each priority zone. More details are available in summary spreadsheet and datasheets attached in appendix.
2.2.1 Global configurations 2.2.1.1 Hydrodynamic processes The global model configurations aim at capturing the general circulation transport, geostrophic current, as well as processes induced by atmospheric forcing and mesoscale features. They are not dedicated to simulate tidal forcing or coastal processes.
2.2.1.2 Reviewed models The reviewed global model configurations provide ocean current forecast and reanalysis at 1/12°.
Hydrodynamic model name Manufacturer hindcast Forecast
analysis NRL Stennis Global HYCOM 1/12° NRL, Stennis archive yes forecast and hindcast reanalysis
analysis Navy global HYCOM 1/12° forecast NOAA/NCEP yes archive
NOAA/NCEP global RTOFS NOAA/NCEP no yes (HYCOM) 1/12°
analysis FOAM (ORCA025) Met Office yes archive analysis MERCATOR 1/12° Mercator / MyOcean archive yes reanalysis (1/4)
2.2.1.3 Forecast comparison The products based on HYCOM assimilate altimetry and satellite SST (using the same NCODA system based on 3Dvar scheme), as well as temperature and salinity vertical profiles of ARGO network. However they do not take into account the tide. The experience shows that HYCOM 1/12° and RTOFS 1/12° offshore current speed results are consistent with observations whereas they are not adapted to tidal influenced zone (North Sea for instance). Note also that that the river kinetic energy is not included in the model; for instance the Congo rive plume is not simulated.
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Several reasons tend to indicate that the NRL Stennis Global HYCOM/NCODA is the best compromise for hydrodynamic forecast and hindcast when no regional nor coastal model is available. The HYCOM forecasts are up to 7days ahead.
Forecast evaluation
Availability 10.0 FOAM Deep Ocean
5.0 HYCOM GLOBAL Validation Time resolution NOAA/NCEP HYCOM GLOBAL 0.0 NRL/STENNIS RTOFS GLOBAL NOAA/NCEP
Data assimilation Spatial resolution MERCATOR 1/12° GLOBAL
2.2.1.4 Hindcast comparison The global NRL Stennis HYCOM/NCODA reanalysis is available freely for a 20-year period.
Hindcast evaluation
Availability 10.0 FOAM Deep Ocean 8.0 6.0 HYCOM GLOBAL NOAA/NCEP 4.0 Validation Time resolution HYCOM GLOBAL NRL/STENNIS 2.0 0.0 RTOFS GLOBAL NOAA/NCEP
MERCATOR 1/12° GLOBAL
Data assimilation Spatial resolution REANALYSIS HYCOM GLOBAL NRL/STENNIS
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2.2.2 Brazil 2.2.2.1 Hydrodynamic processes The large-scale ocean circulation in Brazil is linked with the Brazil Current flowing south along the Brazilian coast to the mouth of the Río de la Plata. 2.2.2.2 Reviewed models
Hydrodynamic model name Manufacturer hindcast Forecast
analysis Oceanographic Modeling and REMO (HYCOM, ROMS) archive yes Observation Network reanalysis analysis CLS hybrid Current Model (HCM) CLS yes archive
MOHID Brazil Action Modulers reanalysis yes
2.2.2.3 Forecast comparison Only CLS forecast are already available. The REMO 1/12° EnOI and ROMS forecast are only available as plot on the REMO website. In the future, the REMO configuration implemented with various assimilation data and scheme will provide high resolution forecast of the Brazil zone:
Forecast evaluation
Availability 8.0 6.0 4.0 CLS Hybrid Current Model (CLS Validation Time resolution HCM) 2.0 REMO Forecasting Model 0.0 HYCOM/CHM/REMO 1/24 degree REMO Forecasting Model HYCOM/CHM/REMO 1/12 degree
Data assimilation Spatial resolution
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2.2.2.4 Hindcast comparison Only CLS hindcast are already available. In the future, the REMO configuration implemented with various assimilation data and scheme will provide high resolution reanalysis of the Brazil zone: o REMO Reanalysis Model HYCOM-UFRJ 1-12 C&H 21 layers o REMO Reanalysis Model HYCOM-UFRJ 1-12 EnOI 2 1layers o REMO Reanalysis Model HYCOM-UFRJ NCEP 1-24 C&H 21 layers o REMO Reanalysis Model HYCOM-UFRJ 1-24 CFSR EnOI 21 layers o REMO Reanalysis Model HYCOM-UFRJ 1-12 EnOI 32 layers o REMO Reanalysis Model HYCOM-UFRJ 1-24 KF 32 layers
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2.2.3 Gulf of Mexico 2.2.3.1 Hydrodynamic processes In the Gulf of Mexico (GoM), the main processes are loop current and eddies. On the continental shelf, current are mainly driven by the local wind. Tidal current zones are restricted to river mouth area (e.g. Mississipi) and around islands. 2.2.3.2 Reviewed models The “Summary of Near-Real Time Forecast Ocean Circulation Models Covering the Full GoMex”, supplied by Cort Cooper, Chevron [Ref 3] was used to review the available current.
Hydrodynamic model name Manufacturer Hindcast Forecast analysis HYCOM Gulf of Mexico 1/25° NRL, Stennis yes archive analysis NAVO AMSEAS (NCOM) 3km NOAA/NCEP yes archive analysis NC States SABGOM (ROMS) 5 km NC State yes archive NOAA-NOS FVCOM and ROMS configs (NGOFS, TBOFS, NOAA-NOS NWGOBS, NEGOFS) NOAA-NOS NGOFS NOAA/NCEP unknown yes Texas TGLO (ROMS) 3-5 km Texas Gen. Land Office/TAMU unknown yes USF WFS ROMS University of South Florida unknown yes analysis USF WFS FVCOM and WFCOM University of South Florida yes archive GoMex PPP unknown DHI MIKE forecast DHI unknown yes analysis NRL IASNFS (NCOM) 6 km Naval Research Laboratory (NRL) yes archive
2.2.3.3 Forecast comparison Among the Ocean Circulation model configuration covering the full Gulf of Mexico, NRL HYCOM 1/25°, RTOFS, AMSEAS and SABGOM are compared in the following radar plots. Both HYCOM 1/25° in Gulf of Mexico and NCOM AMSEAS offer high resolution and data assimilation. The NRL HYCOM 1/25° provides a longer archive dataset. Refer also to the Gulf of Mexico Operational Ocean Forecast System Pilot Prediction Project (GoMEX PPP) for the assessment of the skills of several ocean circulation models in a series of forecast experiments. An extended range (~60 days) ocean forecasting system based on probabilistic methods was implemented for the Gulf of Mexico in a second phase [Ref 3]. None of the listed coastal models of Ref 3 include data assimilation system.
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Forecast evaluation
Availability 10.0 8.0 6.0 4.0 Validation Time resolution HYCOM 1/25°- NRL 2.0 NCOM AMSEAS NOAA 0.0 SABCOM RTOFS GLOBAL NOAA/NCEP
Data assimilation Spatial resolution
2.2.3.4 Hindcast comparison Both HYCOM 1/25° in Gulf of Mexico and NCOM AMSEAS offer high resolution and data assimilation. The NRL HYCOM 1/25° provides a longer archive dataset.
Hindcast evaluation
Availability 10.0 8.0 6.0 4.0 Validation Time resolution HYCOM 1/25°- NRL 2.0 NCOM AMSEAS NOAA 0.0 SABCOM RTOFS GLOBAL NOAA/NCEP
Data assimilation Spatial resolution
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2.2.4 Gulf of Guinea 2.2.4.1 Hydrodynamic processes The complex dynamics is due to several forcing processes: general circulation (Angola Current flowing South-East and the Benguela Current flowing Northwest.), seasonal variations in relation with wind forcing and air-sea interactions, river discharge, etc. The development of eddies in the upper layers is related with the various forcing phenomena.
2.2.4.2 Reviewed models
Hydrodynamic model name Manufacturer Hindcast Forecast CLS (Collecte Localisation analysis CLS hybrid Current Model (HCM) yes Satellites) archive OWI WANE Oceanweather Inc hindcast no analysis SAT-OCEAN SAT-OCEAN yes archive MACH : NEWA 1/36° + ESA 1/12 OWI/ BMT ARGOS / UK MetOffice hindcast no MOHID Angola Action Modulers reanalysis yes
2.2.4.3 Forecast comparison The experience has shown that SAT-OCEAN forecast in West Africa is satisfactory. This 1/64° is the present recommended forecast and hindcast in the Gulf of Guinea. Thanks to its assimilation systems, the global NRL HYCOM 1/12° model can be used offshore where the surface currents seems in agreements with in-situ observations. However, it should not be used in coastal area nor in the Congo river plume.
Availability 8.0 6.0 4.0 Validation Time resolution 2.0 CLS Hybrid Current Model (HCM) 0.0 SATOCEAN 1/64°
Data assimilation Spatial resolution
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2.2.4.4 Hindcast comparison The OWI WANE hindcast is available but it seems not reliable everywhere. The just released MACH hindcast is promising. Some user feedbacks are required in order to evaluate this product in terms of Lagrangian current performances.
Hindcast evaluation
Availability 10.0 8.0 6.0 4.0 Validation Time resolution CLS Hybrid Current Model (HCM) 2.0 SATOCEAN 1/64° 0.0 OWI - WANE MACH
Data assimilation Spatial resolution
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2.2.5 Australia NW shelf 2.2.5.1 Hydrodynamic processes Offshore the Australian North West Shelf (NWS), the large scale regional circulation has a major influence. On the shelf, the transport is dominated by wind-driven flow, which follows the seasonal switch from summer monsoon winds to south-easterly trades in winter. The area is subject to cyclones. Instantaneous current are controlled by tides. 2.2.5.2 Reviewed models
Hydrodynamic model name Manufacturer Hindcast Forecast analysis Bluelink OFAM3 (MOM) yes Australian Bureau of meteorology archive Bluelink BRAN3 (MOM) / Bluelink reanalysis no Bluelink OceanMAPS (MOM) forecast DHI MIKE forecast DHI unknown yes OWI NAMOS Oceanweather Inc hindcast no UWA ROMS University of Western Australia
2.2.5.3 Forecast comparison The OFAM3 forecast produced by the Australian BOM present satisfactory characteristics. For an example of mixed eulerian/lagrangian validation of the BlueLink Model in Australia, please refer to section 4.1.2.2 of the “Recommendation on Validation Techniques” report MOC-0970-02 and refer to the cited article by Chiswell and Rickard [Ref 6].
Forecast evaluation
Availability 8.0 6.0 4.0 Validation Time resolution 2.0 OFAM - ROAM 0.0 OFAM3 DHI MIKE
Data assimilation Spatial resolution
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2.2.5.4 Hindcast comparison
Hindcast evaluation
Availability 10.0 8.0 6.0 OFAM - ROAM 4.0 Validation Time resolution 2.0 OFAM3 0.0 DHI MIKE BRAN3 OWI-NAMOS
Data assimilation Spatial resolution
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2.2.6 North sea 2.2.6.1 Hydrodynamic processed In North Sea, tidal currents represent the main hydrodynamic processes. The main requirement for the model is mainly the spatial and temporal resolutions. As explained in the “Recommendations on validation Techniques”, the data assimilation is a lower priority criteria. 2.2.6.2 Reviewed model Note that the newly available FOAM AMM system replaces the POCOMS AMM models.
Hydrodynamic model name Manufacturer Hindcast Forecast
analysis DMI BSHcmod yes Danish Meteorological Institute archive Danish Meteorological Institute analysis DMI HBM yes (DMI), Denmark. archive
Management Unit of the North Sea analysis OPTOS/COHERENS yes Mathematical Models, Belgium. archive
Danish Meteorological Institute DHI MIKE forecast (DMI), Denmark. POLCOMS (AMM, MRCS, Irish NCOF, UK unknown yes Sea) HIROMB SMHI (Swedish Meteorological and analysis yes Hydrological Institute). archive FOAM AMM Shelf Seas UK MetOffice yes yes
2.2.6.3 Forecast comparison The spatial resolution in the area of interest is an important selection criteria.
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Forecast evaluation
Availability 10.0 8.0 HIROMB 6.0 BSHcmod 4.0 Validation Time resolution 2.0 COHERENS-OPTOS 0.0 HBM - DMI FOAM AMM Shelf Seas TOPAZ - Atlantic DHI MIKE Data assimilation Spatial resolution
2.2.6.4 Hindcast comparison
Hindcast evaluation
Availability 10.0 8.0 6.0 DMI HIROMB 4.0 DMI BSHcmod Validation Time resolution 2.0 MUMM COHERENS-OPTOS 0.0 HBM - DMI FOAM AMM Shelf Seas TOPAZ - Atlantic DHI MIKE Data assimilation Spatial resolution
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2.2.7 South China Sea 2.2.7.1 Regional climate The monsoon pattern governs the climate in the South China Sea. The influence of tidal current is significant in island area. 2.2.7.2 Reviewed models
Hydrodynamic model name Manufacturer hindcast Forecast
LOCEAN ORCA12 INDO Mercator hindcast no CLS ORCA INDESO SYSTEM CLS no not yet LOCEAN ITF025 LOCEAN, Paris hindcast no DHI MIKE forecast DHI OWI SEAFINE Oceanweather Inc hindcast no NMEFC South China Sea NMEFC, China yes
2.2.7.3 Forecast comparison About forecast, INDESO system will be operational at the end of the year 2014. The DHI Mike models are certainly of interest but it is difficult to get precise information about their configuration in each zone.
Availability 8.0
6.0
4.0 ORCA INDESO Systeme CLS Validation Time resolution 2.0 NMEFS South China Sea 0.0 NMEFS East China Sea NMEFS NW Pacific DHI MIKE
Data assimilation Spatial resolution
2.2.7.4 Hindcast comparison The OWI SEAFINE hindcast is the most complete hindcast in the area for the SEAFINE JIP members. However it seems to under-estimate the current velocity.
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The SEAGOOS systems (not fully reviewed) provide also archives offshore Malaysia. The website also offers a particle tracking system. HYCOM might also be used after evaluation at the site of interest.
Availability 10.0 8.0 6.0 4.0 Validation Time resolution 2.0 NEMO-ITF025 LOCEAN 0.0 ORCA 12 INDO LOCEAN OWI SEAFINE
Data assimilation Spatial resolution
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2.2.8 Caspian Sea 2.2.8.1 Hydrodynamic processes In Caspian Sea, a complex combination of current driven largely by regional weather systems and currents raised by the topography occurs. The tide is very small. 2.2.8.2 Reviewed models
Hydrodynamic model name Manufacturer Hindcast Forecast
OWI CASMOS Oceanweather Inc hindcast no NRL Stennis HYCOM caspian NRL, Stennis hindcast no 2.2.8.3 Hindcast evaluation
Hindcast evaluation
Availability 10.0 8.0 6.0 4.0 Validation Time resolution 2.0 HYCOM Caspian Sea Model (NRL Stennis) 0.0 CASMOS OWI
Data assimilation Spatial resolution
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2.2.9 Mediterranean Sea 2.2.9.1 Hydrodynamic processes The Mediterranean Sea currents are governed by general circulation and mesoscale patterns (eddies, etc). 2.2.9.2 Reviewed models Hydrodynamic model name Manufacturer Hindcast Forecast analysis ALERMO 1/50° (POM) forecast University of Athens (Greece) yes archive Oceanography Center of the CYCOFOS (POM) yes yes University of Cyprus. PREVIMER MENOR IFREMER GNOO (Gruppo Nazionale di analysis MyOCEAN MFS (NEMO 3.4) yes Oceanografia Operativa) archive
POSEIDON MED 1/10° Hellenic Centre for Marine Research unknown yes
FOAM Mediterranean (NEMO) analysis UK Metoffice yes MED12 archive DHI MIKE forecast DHI unknown yes
2.2.9.3 Forecast comparison All systems use MFS for boundary conditions. MFS is freely available and validations show that main circulation scheme is correctly simulated Tonani et all, 2008, Note that work is in progress for surface current assimilation in POSEIDON system. Please also refer to 4.1.2.1 of the “Recommendation on Validation Techniques” report MOC- 0970-02 and refer to the cited article by Lacorata et al. [Ref 7] for an example of application of Finite Size Lyapunov Exponents as an estimation of lagrangian error in the MFS system.
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Forecast evaluation
Availability 10.0 MFS MyOcean
5.0 ALERMO Validation Time resolution CYCOFOS 0.0 FOAM MED PREVIMER MENOR POSEIDON MED Data assimilation Spatial resolution DHI MIKE
2.2.9.4 Hindcast comparison
Hindcast evaluation
Availability 10.0 MFS MyOcean 5.0 ALERMO Validation Time resolution CYCOFOS 0.0 FOAM MED PREVIMER MENOR POSEIDON MED Data assimilation Spatial resolution DHI MIKE
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2.2.10 Indian Ocean 2.2.10.1 Hydrodynamic processes The Indian Ocean is mainly governed by the monsoon regimes and the main circulation.
2.2.10.2 Reviewed models Hydrodynamic model name Manufacturer Hindcast Forecast TAMOMS Oceanweather Inc / SAT-OCEAN reanalysis no
The National Centre fo Ocean analysis FOAM Indian Ocean (NEMO) 1/12° yes Forecast (NCOF, UK) archive
Indian National Centre for Ocean analysis INDOFOS yes Information Services (INCOIS) archive
2.2.10.3 Forecast comparison INDOFOS system has low resolution and does not yet assimilate SLA not SST. However INDOFOS is currently testing data assimilation in a new ROMS configuration [GODAE 2014]. It is better recommended to use the FOAM Indian Ocean model forecast.
Availability 10.0 8.0 6.0 4.0 Validation Time resolution 2.0 FOAM Indian Ocean 0.0 INDOFOS
Data assimilation Spatial resolution
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2.2.10.4 Hindcast comparison The recommended hindcast is SAT-OCEAN TAMOMS for the TAMOMS JIP members. The Global HYCOM 1/12° reproduces also correctly the global circulation offshore the shelves.
Hindcast evaluation
Availability 10.0 8.0 6.0 4.0 Validation Time resolution 2.0 FOAM Indian Ocean 0.0 INDOFOS TAMOMS OWI
Data assimilation Spatial resolution
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2.3 REVIEW OF ATMOSPHERIC MODELS
2.3.1 Global Operational forecast systems Operational forecast systems have been listed and classified according to their relevance and accessibility (Table 2-6). The better “charged free” selected one are: - GFS (Global Forecast System) product from NOAA; - GSM (Global Spectral Model) from Japan Meteorological Agency, particularly reliable in the Norh West Pacific area. - GEM (Global Environment Multiscale Model) from the Canadian MetOffice, are more reliable in the Northern atmosphere One can also add few paying but very high quality product such as ECMWF, UK MetOffice and Météo-France forecast. ECMWF forecast presents one of the best score (WMO sources) as shown Figure 2-1.
Figure 2-1: WMO-exchanged scores using radiosondes: 500 hPa height (top) and 850 hPa wind (bottom) RMS error over Europe (annual mean August 2012–July 2013).
Noaa provides global model performances: http://www.emc.ncep.noaa.gov/gmb/STATS_vsdb/
As free product and real time product, GFS may be recommended but SPECIAL ATTENTION should be paid if tropical cyclones appear in the area.
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The main meteorological centers providing cyclone trajectory forecast are: • Joint Typhoon Warning Center (JTWC) de la NOAA ; • Japan Meteorological Agency (JMA) ; • European Center for Medium-Range Weather forecast (ECMWF) ; • Korean Meteorological Agency (KMA) ; • UK MetOffice ; • National Hurricane Center de Miami.
The most reliable forecasts are those of JTWC and JMA (especially in the North West Pacific area).
A limitation of this work is the constant evolution of models and products available. NOTE: Since January 2015, GFS model has been strongly updated (http://www.nco.ncep.noaa.gov/pmb/changes/ ). This report does not take into account these late updates as they have been published after our deliverable date. Serious changes concern: - Changes to the model components - Increases in horizontal resolution - Addition of 0.25 degree gridded output - Addition of new product fields - Change to product naming convention - Changes in product timeliness - Changes to downstream model impacts (for more details see http://www.nws.noaa.gov/om/notification/tin14-46gfs_cca.txt ) The NOAA products may be affected by this update: namely GFS forecast and GDAS analysis.
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Global NRL GEOS-5 Met Office Environmen Global NAVGEM AOGCM -- Unified Model IFS tal GFS MCGA GSM global ARPEGE model GME (old > GEOS-5 Model Multiscale NOGAPS) FP product (MetUM) Model GEM ACCESS ECMWF Global (European FNMOC Modeling Deutscher Center for http://www.n Canadian and Japan MET Météo- Met Office, Manufacturer Wetterdiens Medium- rlmry.navy. Meteorologi INPE BOM Assimilation Office France UK t (DWD) Range mil/metoc/n cal Center Office Weather ogaps/ NOAA (GMAO) forecast) /NCEP
Charged (around 30 000€ for available for contact/discu charged free free free free free free charged external use ss for one year under licence licensing forecast 0.5°x0.5°) Availibility
UM pp-files, GRIB2 GRIB GRIB2 netcdf GRIB2 GRIB GRIB GRIB/ASCII … Grib1 Data format
first 78 hours de T+0hà : hourly T+144h à instantaneou intervals 3h s, hourly (for beyond 78 de T+150h 3 à 6 hours 3 hours 6 hours 3 hours 6 hours 6 hours 3 hours forecast 2D hours a three- à T+240h à data) or more Time hour time 6h resolution interval
forecast: 10 days at 00z and 5 days 7.5 days 10 days (00 10 days at 12z , forecast + and 12Z 7 days 10 days 6 days (25km) and 6 analysis 7 days 11 days 4.25 days 6 days runs), 3.25 assimilated days (66km) (GDAS days (6Z and field: 6 product) 18Z runs) Forecast snapshot/da length ys
Time Starting in since March- 28, 2012 to coverage February 2013 today
0.375 deg T239 (~0.50 0.5°(World) / (latitude), 0.125°x0.12 degree on 25 km and 66 20 km 0.25° 1° and 0.5° 45km 0.5°x0.5° 0.1degree 17 km 0.5626 deg the Gaussian km 5° (France) (longitude) Spatial grid) => 40 km Resolution NAVDAS data 3D or 4D Grid Point 4D assimilation variational Statistical initialisation Variational 3D-VAR 4D-VAR system data Interpolation from previous 3D Var 4D-VAR 3D VAR 4D-Var Assimilation, operational assimilation (4 available six-hourly as initial cycle times/days) analysis Assimilation condition (FNL)
very good quality : Forecasts using the http://www.e yes GEOS yes cmwf.int/en/ http://weather http://www.e yes but system are yes forecasts/to .gc.ca/verific mc.ncep.noa yes yes yes yes yes limitations experimental ols-and- ation/index_e and are a.gov/GFS/p guidance/qu .html produced for erf.php ality-our- research forecasts purposes Validation only. Table 2-6: Atmospheric model characteristics and notations for the global area.
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Archived products Archived products are listed in Table 2-7. Analysis and hindcast at global scale have been listed and classified Table 2-8. . Hindcast product (reanalysis, analysis…) Manufacturer
Global product BOM(GASP) CSIRO Australia CFSR and CFSRv2 NCEP
ERA 40, ERA 15, ERA Interim ECMWF Operational model analyses and products ECMWF derived from short term forecast NCEP R1 & R2 NCEP/NCAR FNL – GDAS NCEP LAPS, TXLAPS NOAA/ESRL MERRA NASA Regional product NARR (North American Regional Reanalysis) NCEP from ETA model FSL Forecast System Laboratory/OAR/NOAA
GEM CMC
NORA10 (HIRLAM-10) MET- Norway
Table 2-7: hindcast products.
FNL Operational model FNL Operational Operationa analyses and Model CFSR and CFSRv2 NCEP R1 & R2 MERRA global analysis l global products derived analysis from short term ERA 40 Era-Interim forecast Manufacturer NCEP NCEP/NCAR NCEP NCEP ECMWF ECMWF ECMWF NASA Availibility free free free free Restricted Restricted Restricted free Data format GRIB2 GRIB1 GRIB1 GRIB1 HDF-EOS 1 hour (surface and 2D diagnostic), 6 6 hourly, daily hourly (3D analysis) hourly and 6 hourly 6 hourly 6 hourly and monthly and 3 hours (3D fields with diagnostics), Time resolution monthly mean Sept1957- Jan 1989- Time coverage 1979-present 1948-present 1997-2007 1999-present Aug 2002 present 2011 to 2014 since 1979 to present 0.2, 0.5, 1.0 AND 2.5° 2.5° 1° 1/2° x 2/3° Spatial Resolution 2.5° 1.125° O.703125° 0.141°x0.141° Table 2-8: Archived atmospheric products and notations for the global area
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CFSR reanalysis data cover a relatively long period with the best resolution and may be recommended as free product. Ref 16 compared NCAR Reanalysis, CFSR and MERRA over Sweden and they highlight the benefit of the best resolution CFSR. ECMWF reanalysis are paying but very high quality products. FNL are free operational GFS analysis, this product are also reliable but with a poor resolution.
2.3.2 Brazil 2.3.2.1 Regional climate Given the large disparity of the Brazil covered latitudes, a brief description of the main weather features is not possible. However, prevailing winds are trades winds and sea breezes. Local winds may also be notified as Pamperos and Sudestadas on the SE coast of Brazil. 2.3.2.2 Models comparison Models and their performances are summarized in Table 2-9. A regional atmospheric model, such as BRAMS or ETA forecast produced by INPE, is recommended. These products are free and may be downloaded easily. On the contrary, COSMO model configurations do not seem available.
Model COSMO COSMO BRAMS ETA INMET (instituto DHN (Navy Manufacturer nacional de INPE Hydrology center) meteorologia) CPTEC/INPE Availibility free free data format GRIB GRIB Time resolution 3 hours 3 hours 6 hours 3 hours 7.25 (00, 12UTC) and 3 3.25 days 11 days Forecast length (06, 18UTC) days 3 days Time coverage 7 km x 7 km (coastal 5km 15km Spatial Resolution zoom 2.8km) Assimilation yes yes Validation yes yes Table 2-9: Atmospheric model characteristics and notations for the Brazil area.
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2.3.3 Gulf of Mexico 2.3.3.1 Regional climate In the Gulf of Mexico, general atmospheric circulation is driven by the North Atlantic subtropical high. Mid-latitude winds from West blow in the northern part of Gulf and easterly trade winds are dominant in the southern area (South of 26°N). The region is subject to tropical cyclones (hurricanes). 2.3.3.2 Models comparison Models and their performances are summarized in Table 2-10.
NARR RAP: (North NAM-HIRES GCIP NCEP Rapid American NCEP Meso NCEP NAM (218 LAPS Model COAMPS GoMex (United States ETA 212 grid LAPS NAV Refresh RUC FSL Regional ETA (218 grid) grid) AOML-H1 Mesoscale Model) and NAM (new Reanalysis) RUC) from ETA model
Forecast NOAA/NCE System Manufacturer FNMOC NCEP NCEP NCEP NCEP NOAA/NCEP NCEP NOAA/ES NOAA/ES P Laboratory/ RL RL OAR/NOAA Availibility free free free free free free free free free data format GRIB GRIB2 GRIB2 GRIB2 GRIB2 … … GRIB GRIB … GRIB1 6-hourly analysis and 3- 3 hours 6 hours 6 hours hourly hourly hourly hourly 3 hours 3 hours hourly Time resolution forecast Nominally 48 h (72 for European Area and West 60 hours 60 hours 84 hours 60 hours Forecast Atlantic. 84 hours length for West Pacific) 1995- 2010 : since 2002 to after 2005 and near since 2012 since 1997 to Time coverage before 2005 ETA and 2013- present (RUC 1979-present real time to present 2011 present: NAM 20km), 2011-
20 (Domain 252), 13 km 20 (Domain 12 km (grid 221: 27 km 4 km 12 km 40km 10 km 9 km (Domain 252) and 13 km 40km 32km 32km) 130), 32 km (Domain 130) Spatial (grid 221) Resolution initialized with a no : initialized with a 12- 12-h run of the no : initialisation no (initial condition: initialisation yes … h run of the NAM NAM Data …… field is an …… GFS) field is an Data Assimilation Assimilation analyse Assimilation System System analyse Validation yes yes yes yes yes yes yes yes yes yes yes Table 2-10: Atmospheric model characteristics and notations for the Gulf of Mexico area
Numerous forecast products are available over the Gulf of Mexico area. The NCEP NAM forecast seems a good compromise between large coverage, reasonable horizontal resolution and data assimilation (analyse at initialization). Near real time RUC product seem also reliable.
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2.3.4 Gulf of Guinea 2.3.4.1 Regional climate In the Gulf of Guinea area, dominant winds are trade winds, blowing from the South-East to South-West and with the strongest intensity during the wet season. Squall lines occur frequently in the area. 2.3.4.2 Models comparison Models and their performances are summarized Table 2-11.
Model COAMPS West Africa WRF ARPEGE-TROPICS LATMOS-IPSL, Universite Pierre et Marie Manufacturer FNMOC Curie, Paris, France Météo-France Availibility free charged data format GRIB NetCDF Time resolution Nominally 48 h (72 for European Area and West Atlantic. 84 hours for West Forecast length Pacific) Time coverage Spatial Resolution 15 km 25 km 50km (0.5x0.5deg) Assimilation yes Validation yes- Research purpose yes Table 2-11: Atmospheric model characteristics and notations for the Gulf of Guinea area
In this area, most of the models available are dedicated to research and are not available (as the LATMOS WRF configuration for example Ref 17). Arpege Tropics products are the most reliable product but they are charged products. As an alternative, global product should be considered.
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2.3.5 Australia NW shelf 2.3.5.1 Regional climate During the northwest monsoon, convective cloud and heavy rainfall are produced by an inflow of moist winds blowing from west to northwest. During the southeast monsoon, a south-easterly dominates. Numerous topical cyclones occur around the Australian northern coats. 2.3.5.2 Models comparison Models and their performances are summarized in Table 2-12.
Model ACCESS ACCESS R WRF NAMOS TXLAPS Oceanweather Manufacturer BOM BOM Offshore Weather Services (Australia) Inc. Available to NAMOS contact/discuss for licensing contact/discuss for licensing charged charged charged Partcipants Availibility Only data format UM pp-files, GRIB1 UM pp-files, GRIB1 GRIB netcdf GRIB netcdf GRIB netcdf Time resolution 3 hours 1 hour 1 hour 1 hour 1 hour 15 Minutes 10 days (00 and 12Z runs), 3.25 days (6Z and 18Z 3 days 3 days (18 hours) N/A Forecast length runs) 3 days 3 days since March-28, 2012 to Time coverage since April-17 2013 to today 1979 to present 1970 and 2010 today 3 days 3 days 0.375 deg (latitude), 0.5626 0.11 deg (latitude), 0.11 deg ~26 / 9 / 3 km deg (longitude) => ~ 18/ 6 / 2 km 12/4/1.333 km 7 km (longitude) => appoximately 12 km (12/4/1.333km) Spatial Resolution appoximately 40 km 0.375° 4D Variational Assimilation, 4D Variational Assimilation, six-hourly N/A Assimilation six-hourly N/A N/A N/A various Oill various Oill Yes, all various Oill Companies, Companies, proprietary to yes yes Companies, sailors sailors and sailors and NAMOS JIP and Universities Validation Universities Universities Participants Table 2-12: Atmospheric model characteristics and notations for the Australia area No free regional products have been listed in this area. Among the charged products, the Bureau of Meteorology (BOM) products should be the more reliable as they have an assimilation system and numerous references dedicated to their validation. However, Offshore Weather Service forecast and NAMOS hindcast have a better resolution and should be also interesting product.
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2.3.6 North Sea 2.3.6.1 Regional climate In winter, intense depressions associated with frontal systems occur and generate extreme of wind over the North Sea. 2.3.6.2 Models comparison Models and their performances are summarized in Table 2-13.
NORA10 HIRLAM- HIRLAM-T HIRLAM-S COSMO- Model ALADIN HIRLAM HIRLAM-12 HIRLAM-8 UKV Euro4 COSMO SKIRON for NEXTRA (HIRLAM- V74 (T15) (SKA 3km) EU North 10) Atlantic and Europe
Met Met University of Météo- MET- MET- Oceanweath MET- Manufacturer FMI DMI DMI KNMI Office, Office, Athens, France Norway Norway national er Inc. Norway UK UK meteorolog (AM&WFG) ical service of Poland, DWD IMGW available available for for external upon on request free charged charged free free free external restricted charged use request use under under licence Availibility licence GRIB, GRIB1, GRIB/ASCII GRIB GRIB GRIB GRIB GRIB GRIB GRIB1 BINARY, GRIB2 data format ASCII Time 1hour- resolution 3 hours 1 hour 1 hour 6 hours 3hours 1hour-3hour 3hour 1 hour 3 hour 1 hour 1 hour 1hour (surface) prediction at 06 and 36 (54) at 18 UTC 54 hours 54 hours 60 hours 48 hours 66 hours 66 hours 36 hours 48 hours hours and 78-h at Forecast 00 UTC length and 12 5 days from Time 10/1/1964 to September coverage 12/31/2012 1957 to August 2002 1.5 km 30 km, 10 inner 7 - 10 km 7.5 km 16km 5km 11km 12km 7km 12 km km, 3km 10 km Spatial 4 km and 1km Resolution outer 7km 14 km 10 km
4D-VAR (6h Increme Increment 3D-VAR assimilatio yes yes yes yes yes ntal 3D- no 3-D … yes al 3D-Var n Var frequency) observation Assimilation al nudging Validation Table 2-13: Atmospheric model characteristics and notations for the North Sea area
Among free product available for the North Sea area, the HIRLAM (FMI or MetNo) and the SKIRON products should be considered. One can add charged product such as Meteo-France (ALADIN) and MetOffice forecast (UKV), which are recognized for their very good performances. The NORA10 hindcast is a high resolution hindcast database compared to ERA 40 in Ref 15.
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2.3.7 South China Sea 2.3.7.1 Regional climate This region is submitted to the seasonal position of the Intertropical Convergence Zone and the associated NE and SW monsoons winds. Squall lines and cyclones (north of 6°N) may occur in the South China area. Local topography may have a major role at mesoscale (land breezes). 2.3.7.2 Models comparison Models and their performances are summarized Table 2-14.
Model ACCESS R COAMPS West Pacific RAM WRF NHM
International Manufacturer BOM FNMOC Pacific Research Center (IPRC), Hong Kong University of Hawai OWS Observatory Availibility contact/discuss for licensing free Researh purpose data format UM pp-files, GRIB1 GRIB Time resolution 1 hour 6 hours 10km model: 72 hours Nominally 48 h (72 for European Area (and 2-km NHM is run 3 days and West Atlantic. 84 hours for West every hour to generate Forecast length Pacific) 15 hour forecasts) Time coverage since April-17 2013 to today 2 km (inner domain) 0.11 deg (latitude), 0.11 deg 18 km 20km (0.2°) and 10 km (outer Spatial Resolution (longitude) => appoximately 12 km domain) NOGAPS forecast fields at 3-hour Assimilation 4D Variational Assimilation, six-hourly intervals no 3DVAR yes Validation yes yes Wang et al. 2003 Table 2-14: Atmospheric model characteristics and notations for the South China Sea area. Wang et al 2003 is Ref 13.
BOM forecast product should be firstly considered even if paying. COAMPS products may also be a good alternative but presently we can not be more encouraging in using them. NHM products do not seem available.
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2.3.8 Caspian Sea 2.3.8.1 Regional climate In the Caspian Sea area, dominant winds blow usually from North in summer and from South-East in winter. The area is under a continental climate regime. 2.3.8.2 Models comparison CASMOS products were the only regional product found and, should be reliable (Table 2-15).
Model CASMOS Manufacturer Oceanweather Inc. and DHI Availibility Inquire within Shell data format ASCII Time resolution 0.25 Hours Forecast length The hindcast extended to 100 storms over a 52-year period Time coverage 1948-2000 and to the 10-year continuous period 1991- 2000. Spatial Resolution 10 km Assimilation Validation Yes, all proprietary to CASMOS JIP Participants Table 2-15: Atmospheric model characteristics and notations for the Caspian Sea area
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2.3.9 Mediterranean Sea 2.3.9.1 Regional climate North-westerly winds are dominant in the Mediterranean basin. Local winds related with topography or thermal conditions are to be considered (Mistral, Foehn, Sirroco, Harmattan..). 2.3.9.2 Model comparison Models and their performances are summarized in Table 2-16. Free SKIRON forecast appears to be a good quality product with a high horizontal resolution and a relatively long forecast length (5 days). In addition, surface winds from few NWP models (ECMWF IFS, WRF, ALADIN, COSMO- LAMI (Italy)) were compared with Scatterometer data over the Adriatic Sea (Figure 2-2, Ref 14). This study illustrates model performances: ECMWF is the best model, ALADIN and WRF produce good results and the COSMO model appears to be less efficient.
Figure 2-2: Scatterplot of the wind speed of the QuikSCAT scatterometer and the four NWP models for the satellite passes of 18 November (right ). Extracted from De Biasio et al, 2014 [ Ref 14 ].
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SKIRON SKIRON for Aladin (installed in COAMPS COSMO- COSMO- Model Albachir Mediterrane COSMO Noraf POSEIDON RAMS/ICLA Europe ME (and EU an II) MS COSMO-IT)
Maroc Maroc Météo - Météo - Aéroport Aéroport Casa-Anfa, Casa-Anfa, University of University of University of Face Face Athens, Athens, Athens/ Préfecture Préfecture Atmospheric Atmospheric Atmospheric Manufacturer Hay Hay Modeling & Modeling & Modeling & FNMOC Hassani - Hassani - Weather weather weather B.P. 8106 B.P. 8106 Forecasting Forecasting Forecasting Group Group Group Italian Casa Oasis Casa Oasis national National - - meteorologic Center of Casablanc Casablanc al service of Meteorology a - Maroc a - Maroc Greece, and HNMS in Climatology Athens (CNMCA) DWD
charged charged upon request upon request upon request free Availibility
GRIB, ASCII BINARY, GRIB, HDF5 GRIB data format ASCII
6-hourly 6-hourly 1 hour 1 hour 1 hour forecast forecast Time resolution
Nominally 48 h (72 for European 48-h 72 hours 72 hours 5 days 5 days Area and prediction at West 06 and at 18 Atlantic. 84 UTC and 78- hours for h at 00 UTC Forecast length 48h West Pacific) 72 hours 78 hours and 12 UTC
since 2000 to since 2000 to from 2004 Time coverage today today until today
31km 16km 5km 5km 15 km Spatial 36km, 6km, Resolution 3km 7km 7km 7km CANARI Ensemble (Optimum 3-D (and 4-D Kalman Filter 3-D 3-D yes no Interpolation var) (EnKF) observational Assimilation analysis) approach nudging • Sadiki, W., C. • Najmi H., "Validation Fischer and Sayouri F., Test Report J.-F. Geleyn, Afifi, for the 2000: HDIDOU F., Coupled Mesoscale Sahlaoui Z. : Ocean Background Mise en Atmosphere Erreur place d'une yes yes yes Mesoscale Covariances, chaîne Prediction Recent d'assimilation System Results pour Albachir (COAMPS)" , Obtained with basée sur la NRL, the Limited- technique Monterey, area model variationnelle CA, June, Validation ALADIN over 3D-var. 2002. 1996. Table 2-16: Atmospheric model characteristics and notations for the Mediterranean area
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2.3.10 Indian ocean 2.3.10.1 Regional climate North to the equator, the monsoons dominate the climate with strong NE or SW winds depending on the season. Southward equator, winds are less strong but summer storm may occur. Cyclones are numerous in this area. 2.3.10.2 Models comparison The following models have been listed in the Indian Ocean area: NCMRWF model, COAMPS North Indian Ocean and ARPEGE TROPICS. These models do not cover the same domain (NCRMWF: India and surrounding area, COAMPS: North Indian ocean, ARPEGE TROPICS: Madagascar surrounding area) and therefore the comparison is difficult. Note that the NCMRWF provides the longest forecast.
Model NCMRWF COAMPS North Indian Ocean ARPEGE-TROPICS
National Centre for Medium Range Weather Manufacturer FNMOC Météo-France Forecasting (NCMRWF)
Availibility free free charged data format GRIB2 GRIB NetCDF Time resolution .25x0.25 deg. 27 km 0.5x0.5deg Forecast length 7 days 48 h Time coverage Spatial Resolution 6h 3h Assimilation yes yes Validation yes yes Table 2-17: Atmospheric model characteristics and notations for the Indian Ocean area.
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3 WP4: METOCEAN DATABASES
3.1 METHODOLOGY
3.1.1 Definition The following Table 3-1 and Table 3-2 give some lists of instrument types and deployment methods. The section 3 and 4 of the attached “Recommendations for validation techniques” MOC- 0970-02 report indicates the diagnostics that can be carried out according to the available data types.
Instruments Physical parameters Examples of manufacturers CTD (Conductivity, Temperature Teledyne RDI Temperature, and Lockheed Martin Sippican (XCTD) Depth) Sea-Bird Electronics SBE XBT (Expendable Temperature Lockheed Martin Sippican (XBT) bathythermograph) ADCP (Acoustic Doppler Current, temperature, salinity Teledyne RDI Current Profiler) Nortek AS 5Aquadopp, AWAC) Waves Current Meter Current Nortek AS (Aquadopp) Aanderaa (RCM) Tide gauge Sea level Aanderaa RBR Wave buoy Wave spectra (directional or AXYS (TRYAXIS) not) Fugro Oceanor (WaveScan, SeaWatch) Drifting buoy Current MetOcean WOCE-SVP MetOcean CODE/DAVIS drifter High Frequency HF Current, Wave, wind WERA radar direction CODAR Advanced Synthetic Current Aperture Radar ASAR
Table 3-1: List of reviewed types of instruments
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Deployment Instruments Examples of systems Argo float CTD NKE (PROVOR, ARVOR) Teledyne (APEX) Moored lines CTD, ADCP, current meter, tide gauge Vessel, shipboard CTD Aiborne Photography Fugro ROCIS (Remote Ocean Current Imaging System) Gliders, AUV CTD, ADCP iRobot Seaglider ACSA SeaExplorer Telegyne Slocus Glider Satellite ASAR ASA/ENVISAT
Table 3-2: List of reviewed deployment systems
3.1.2 Inventory The primary sources for data inventory are taken from the reference report Ajilon / Euro Engineering (EE), Inter-comparison and validation in-situ of oil spill drift model, Final report, September 2011 [Ref 1] The information of the data already listed in the above reports is updated. The inventory of newly available data is mainly based on inputs from JIP members and experience.
In order to better assess new identified data sources, a questionnaire was sent to the producers of these metocean data. The level of information is quite poor. The data portal includes most of the time very inhomogeneous information. The review presents the major metocean data server. The complete review of the data is provided in excel spreadsheet of appendix.
The lagrangian data available in each priority basin are presented with more details in the report. The user should refer to the data provider website to get updated information.
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3.2 DATA REVIEW
3.2.1 Global
Name Website Description (further information in the questionnaire) The data used at the Atlantic Oceanographic and Meteorological Laboratory of the National Oceanographic and Atmospheric Administration’s (AOML – NOAA) are provided by CLS America (Argos) and the NOAA’s Global Drifter Program. The Global Drifter Program (GDP) is the principal component of the Global Surface Drifting Buoy Array, a branch of NOAA’s Global Ocean Observing System (GOOS) AOML- www.aoml.noaa.gov and Global Climate Observing System (GCOS) and a NOAA scientific project of the Data Buoy Cooperation Panel. Its objectives are to (a) maintain a global 5ºx5º array of Argos- tracked Lagrangian surface drifters to meet the need for an accurate and globally dense set of in-situ observations of mixed layer currents, sea surface temperature, atmospheric pressure and winds and (b) provide a data processing system for scientific use of these data. The Center for Ocean-Atmospheric Prediction Studies (COAPS) gathers metocean data and makes them public. The center has a wide range of funding sources (NOAA, NSF, NASA, etc) and collaborates with a number of centres and consortiums. COAPS- http://samos.coaps.fsu.edu COAPS is home to the Research Vessel Surface Meteorology FSU /html/ Data Centre which provides high-quality meteorological observations for validation of satellite and model derived products. The centre also is the project office for the Shipboard Automated Meteorological and Oceanographic System (SAMOS) initiative. Open ocean data and coastal data (river flows, high frenquency observing systems). Data are daily sent for ocean modeling (Mercator Ocean, SOAP/soprane and Previmer) and CORIOLIS http://www.coriolis.eu.org to the European MyOcean project. Data coming from French sources are sent on the GTS (worldwide meteorological network). Those data are also sent to scientific teams working on climatological studies. The Global Sea Level Observing System (GLOSS) is an international programme conducted under the auspices of the Joint Technical Commission for Oceanography and Marine Meteorology (JCOMM) of the World Meteorological Organisation (WMO) and the Intergovernmental http://www.gloss- GLOSS Oceanographic Commission (IOC). GLOSS aims at the sealevel.org establishment of high quality global and regional sea level networks for application to climate, oceanographic and coastal sea level research. The programme became known as GLOSS as it provides data for deriving the 'Global Level of the Sea Surface'. The International Comprehensive Ocean-Atmosphere Data Set (ICOADS) is a global ocean marine meteorological and surface ocean dataset. These data are provided by many ICOADS http://icoads.noaa.gov/ national and international data sources that contain measurements and visual observations from ships, moored and drifting buoys, coastal stations, and other marine
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Name Website Description (further information in the questionnaire) platforms.
The Joint WMO-IOC Technical Commission for Oceanography and Marine Meteorology (JCOMM) in situ Observing Platform Support Centre (JCOMMOPS) provides coordination at the international level for oceanographic and JCOMMO http://www.jcomm.info marine observations from drifting buoys, moored buoys in the PS http://ioc-goos.org/ high seas, ships of opportunity and sub-surface profiling floats. JCOMMOPS collects and makes public data of providers: Argo subsurface floats, DBCP surface drifters, SOT (Ship Observations Team) and OceanSITES moorings. MyOcean aims at providing a sustainable service for Ocean Monitoring and Forecasting validated and commissioned by users. The MyOcean information includes observations, analysis, reanalysis and forecasts describing the physical state of the ocean and its primary biogeochemical parameters. It also contributes to research on climate by providing long time-series of reanalysed parameters. Myocean is a European project which provides ocean data MYOCEA www.myocean.eu.org from Mercator-Ocean forecasting. The processed data are N distributed by Observation Data Providers that are national data centers or operational agencies: Argo, Oceansites, Gosud, DBCP: DBCP is an international program, under JCOMM , that collects current information from surface drifters data, transmits them in real-time. These data are provided by the In Situ Thematic Center (INS TAC).The global component of the INS TAC collects the data on GTS, qualifies them and provides them to the MYocean users, GLOSS The NOAA National Data Buoy Center (NDBC) designs, NDBC- http://www.ndbc.noaa.gov develops, operates, and maintains a network of data collecting NOAA buoys and coastal stations. The NODC manages the world’s largest collection of publicly available oceanographic data. NODC holdings include in situ and remotely sensed physical, chemical, and biological oceanographic data from coastal and deep ocean areas. These were originally collected for a variety of operational and NODC- research missions by U.S. Federal agencies, including the http://www.nodc.noaa.gov/ NOAA Department of Defense (primarily the U.S. Navy); by State and local government agencies; by universities and research institutions; and private industry. NODC data holdings extend back over one hundred years, and the volume is expected to grow exponentially as new ocean observing systems are deployed. The SIMORC service gives an overview of and access to an increasing volume of metocean data sets, collected by the oil & gas industry at various sites on the globe in the past and continuing at present. Major oil & gas companies are SIMORC http://www.simorc.org participating via the International Association of Oil & Gas Producers (OGP) and its OGP Metocean Committee. They submit data sets to SIMORC on a regular basis, that are indexed in the SIMORC metadatabase and stored in the
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Name Website Description (further information in the questionnaire) SIMORC database.
Argo data is freely available from two GDACs; one in the USA and one in France. Argo is a major contributor to the WCRP’s Climate Variability and Predictability Experiment (CLIVAR) project and to the Global Ocean Data Assimilation Experiment UCSD (GODAE). The Argo array is part of the Global Climate University Observing System/Global Ocean Observing System GCOS/ of www.argo.ucsd.edu GOOS). Argo is a global array of 3,500+ free-drifting profiling California, floats that measures the temperature and salinity of the upper San Diego 2000 m of the ocean. This allows continuous monitoring of the temperature, salinity, and velocity of the upper ocean, with all data being relayed and made publicly available within hours after collection.
3.2.2 Brazil The PNBOIA includes of fixed and drifting buoy buoys data that can be downloaded. Refer also to the 2007 MONDO experiment for the use of Lagrangian statistics (FLSE) offshore Brazil.
Name Website Description (further information in the questionnaire) The Regional Alliance for the Upper Southwest and Tropical Atlantic (OCEATLAN) represents the regional efforts of institutions from Argentina, Brazil, and OCEATLAN http://oceatlan.org/ Uruguay to jointly develop and implement an operational oceanographic system to monitor and investigate the oceanic processes in the Upper Southwest and Tropical Atlantic. http://www.goosbrasil.org/t GOOS-Brazil is the Brazilian national GOOS iki- component of the Regional Alliance for the Upper index.php?page=PNBOIA GOOS BRAZIL Southwest and Tropical Atlantic, OCEATLAN. %20Data PNBOIA The Brazilian ocean observing system includes https://www.mar.mil.br/dhn gathering, coordination, quality control, and operational /chm/meteo/prev/dados/da distribution of oceanographic data. dos.htm The paper below provides information about REMO's observational program: Lima JAM, Martins RP, Tanajura CAS, Paiva AM, Campos E, Soares ID, Cirano M, França GB, Obino RS and Alvarenga JBR. REMO http://www.rederemo.org Design and implementation of the oceanographic modeling and observation network (REMO) for physical oceanography studies and ocean forecasting. Revista Brasileira de Geofísica, 31(2): 209–228.
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3.2.3 Gulf of Mexico The Gulf of Mexico Coastal Ocean observing Systems (GCOOS) data Portal aggregates data from the regional data provider including: - ADCP buoy - observations from HF radar - glider data (including for oil spill) Name Website Description (further information in the questionnaire)
see http://data.gcoos.org/52N_SOS.php for details on how to GCOOS http://data.gcoos.org access data and list system capabilities.
The Southeast Coastal Ocean Observing Regional Association SECOORA is the regional solution to integrating coastal and ocean observing data in the Southeast United States to inform SECOORA http://secoora.org decision makers and the general public. The SECOORA region encompasses 4 states, over 42 million people and spans the coastal ocean from North Carolina to the west Coast of Florida.
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3.2.4 Gulf of Guinea ODINAFRICA is the reference database for west Africa. The SIMORC database provides also some isolated buoys that can be used for Eulerian statistics validation.
Description (further information in the Name Website questionnaire) The National Commision of the Guinea Current DRC / in Democratic Republic of Congo The Laboratoire d’Etude en Géophysique et Océanographie Spatiales (LEGOS) is one of a research lab of IRD FRANCE. One of the activities of this lab is to participate at the management of 5 observation networks and data providers: - PIRATA (Prediction and Research Moored Array in the Atlantic) network developed in 1997 through a multinational partnership between France, Brazil and USA, provides data from deep ocean moored buoys in the tropical Atlantic for climate research and prediction. - DORIS (Détermination d'Orbite et Radio positionnement Intégrés par Satellite) provides geophysics informations and data with satellite system. - SSS (Sea Surface Salinity) Observation IRD France – http://www.legos.obs-mip.fr Service aims at collecting, validating, archiving LEGOS and distributing in situ SSS measurements derived from Voluntary Observing Ship programs. - ROSAME (Réseau d'Observation Subantarctique et Antarctique du niveau de la MEr) provides tide data. - CTOH (Centre of Topography of the Oceans and the Hydrosphere) french Observation Service maintains homogeneous altimetric data bases for the long-term monitoring of sea level and ocean currents, lake and river levels, the cryosphère, and the planet's climate.
IRD collaborates to improve and maintain these data provider networks. Others data used by IRD are provided by others providers: Coriolis, PMEL/NOAA …
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Description (further information in the Name Website questionnaire) IRHOB -ex_CRHOB Institute of Ocean and Fisheries Research of (Institute of Ocean Benin (IRHOB, ex-CRHOB), localized at and Fisheries Cotonou, was created in 2002 under the Research of Benin, administrative authority of Benin Center for Cotonou) PROPAO http://www.nodc-benin.org Scientific Research and Technology (CBRST). (Regional Program IRHOB has developed the Regional Program of of Physical Physical Oceanography in West Africa Oceanography in (PROPAO), a regional marine databank to make West africa) public metocean data for the Gulf of Guinea. The Nigerian Institute for Oceanography and Marine Research (NIOMR) was established in November 1975 by the Research Institutes Establishment Order of 1975. The Institute conducts research in the several areas, and in particularly on: - Physical, geological and NIOMR / geophysical characteristics of the Nigerian territorial waters and the high seas beyond; - The nature of the marine environment, including weather forecasting, seabed topography and characteristics and deposits; The provider is IRD France. The Ocean Data and Information Network for Africa (ODINAFRICA) network wants to ensure that ocean and coastal data and information generated in national, regional and global programmes are readily available to a wide ODINAFRICA www.vliz.be/vmdcdata/iode/ range of users in an easily understandable format. For that, ODINAFRICA network builds and maintains an archive of marine and coastal data at National Oceanographic Data (and Information) Centres in Africa. The UROPB (Unité de Recherche d’Océanographie et de Biologie des Pêches) is a recent structure which belongs to the DGRST UROPB Congo / (Direction Générale de la Recherche Scientifique et Technique) of Congo. UROPB collects and provides metocean data.
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3.2.5 Australia The Australian Integrated Marine Observing System (IMOS) facilities are funded to deploy equipment and deliver data streams. Name Website Description (further information in the questionnaire) The Australian Integrated Marine Observing System (IMOS) is designed to be a fully-integrated, national system, observing at ocean-basin and regional scales, and covering physical, chemical and biological variables. IMOS http://imos.org.au Since 2006, IMOS has been routinely operating a wide range of observing equipment throughout Australia’s coastal and open oceans, making all of its data accessible to the marine and climate science community, other stakeholders and users, and international collaborators.
3.2.5.1 North West Shelf (NSW) The Australian National Facility for Ocean Gliders (ANFOG) is responsible for the operation and maintenance of the ocean glider fleet (Figure 3-1) The NSW-IMOS node deploys Seagliders off the NSW coast with the aim of increasing the understanding of the dynamics and variability of the East Australian Current (EAC), the Tasman Front, and eddies shed by the EAC: - two deployments of Seagliders of five months each occur every year targeting the eddy field south of the EAC separation zone. - Slocum gliders are also deployed in this area to make cross-shelf transects of the adjacent shelf, investigating the challenging environment of the continental shelf off Stockton Bight, Jervis Bay and Eden.
Figure 3-1: The WAIMOS northern observation array [Source IMOS]
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3.2.5.2 Coral sea The Australian Coastal Ocean Radar Network (ACORN) operates, maintains and processes HF radar data (Figure 3-2) . A WERA HF radar system has been recently deployed within the Great Barrier Reef in Queensland, Australia.
Figure 3-2: Location of ACORN radar sites [Source IMOS] ANFOG: In the Coral Sea region off northern Queensland, two Seagliders undertake permanent transects along the coast collecting observations of temperature, salinity and oxygen in top 1000 m, as well as chlorophyll and backscatter from the mixed layer. The observations collected by these gliders will be incorporated into the nested hydrodynamic models being developed for Queensland to track changes in the coastal flows near the continental margin and on the shelf.
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3.2.6 North Sea
Name Website Description (further information in the questionnaire) The British Oceanographic Data Centre (BODC) is a national facility for looking after and distributing data concerning the marine environment and is hosted by the National BODC www.bodc.ac.uk Oceanography Centre (NOC). BODC's holdings and data inventories available from https://www.bodc.ac.uk/data/where_to_find_data/ eKlima is a web portal which gives free access to the climate database of the Norwegian Meteorological Institute, for all. The climate database contains data from all present and past eKlima http://sharki.oslo.dnmi.no weather stations of the Norwegian Meteorological institute, as well as data from other institutions (owners) that are allowed distributed. The Norwegian Meteorological Institute (met.no) produce and manage data which is of relevance for a number of different users, ranging from the general public to highly http://met.no/Hav_og_is/ Met No specialised users. The general public is served mainly English/Access_to_data/ through http://yr.no/. However, many users are looking for data and not the interpretation of data that is served through http://yr.no/.
Available data on the site met.no are mostly modelled data. Some of the relevant data portals hosted by met.no are OSISAF, MyOcean, Arctic Data Centre and NORMAP.
3.2.7 South China Sea
Name Website Description (further information in the questionnaire) NEAR-GOOS is the North-East Asian Regional GOOS program. It is being implemented by China, Japan, the Republic of Korea and the Russian Federation as a WESTPAC project. It is intended to provide an http://near- operational demonstration of the usefulness of a regional NEAR-GOOS goos.coi.gov.cn/ ocean observing system in the achievement of its own specific goals and as a pilot project for other parts of the world. NEAR-GOOS project covers the Yellow Sea, East-China Sea and Japan Sea.
3.2.8 Caspian Sea
Name Website Description (further information in the questionnaire) CASPINFO aims to provide access to high quality, up-to- date marine, environmental datasets on metadata level, and CASPINFO http://www.caspinfo.net/ it will even go as far as direct access to partners data itsself. This means that the data (after registration) can directly be downloaded from partner with online database or file
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systems.
3.2.9 Mediterranean Sea
Name Website Description (further information in the questionnaire) The Mediterranean Ocean Observing System for the Environment (MOOSE) network includes all observation activities of the Three Mediterranean marine Observatories (Banyuls, Marseille and Villefranche) and the French laboratories working in on the NW Mediterranean Sea (CEFREM-Perpignan, LOCEAN-Paris, http://www.moose- MOOSE L.A.-Toulouse) in the framework of the MOOSE scientific network.fr/ questions. It will be based on a multisite system of continental-shelf and deep-sea fixed stations as well as Lagrangian platform network to observe the spatio- temporal variability of processes interacting between the coastal-open ocean and the ocean-atmosphere components The Mediterranean Oceanography Network for the Global Ocean Observing System MONGOOS is engaged in MONGOOS http://www.mongoos.eu/ activities related to the production and use of operational oceanography services
A Mediterranean Ocean Observing System on Environment (MOOSE) has been set up as an interactive, distributed and integrated observatory system of the North West Mediterranean Sea in order to detect and identify long-term environmental anomalies. MOOSE provides data for the MISTRALS project and uses MyOcean insitu data distribution infrastructure. In the framework of the French MOOSE project, the Mediterranean Institute of Oceanography (M.I.O.) is operating High Frequency Surface Wave Radars (HFSWR) on the North Western Mediterranean coast. Data collected from MONGOOS members are distributed also by MyOcean.
3.2.10 Indian Ocean
Name Website Description (further information in the questionnaire)
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The Western Indian Ocean Coastal Observing System WIOCOS is part of the CFOO. CFOO is a regional, multi- institutional, Centre of Excellence in observational and operational oceanography and associated applied research. Based in Cape Town at Oceans & Coasts (Department of Environmental Affairs), CFOO was established as one of 4 http://www.cfoo.co.za/ WIOCOS core components of the OceansAfrica Initiative intent on wiocos.php developing in situ observational and operational oceanography for the region through cost effective, high quality and technically advanced measurement and ocean observing systems for research, state of the ocean reporting, forecasting, engineering and renewable energy applications.
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4 CONCLUSIONS AND RECOMMENDATIONS
4.1 CONCLUSIONS
OGP-IPIECA WP3: Modelling and Prediction The main selected hydrodynamic and atmospheric models are presented by basin in the Executive summary of this MOC-0970-01 report . This selection of hindcast and forecast might be revised under request according to JIP members experience and feedbacks.
The review of hydrodynamic models is presented in section 2.2. The evaluation has been carried out on the basis of defined criteria including: - model availability (file format, prices, etc) - model performance (time and spatial resolution, data assimilation, etc) - model validation (publication, customer feedback, etc) The detailed evaluation results are provided as spreadsheets in appendix. A first inventory of atmospheric models hindcast and forecast has been established. A summary of the model comparison is presented by priority basin in section 2.3.
OGP-IPIECA WP4: Metocean databases The principal meteocean databases by basin are listed in the Executive summary. A synthesis is presented in section 3 of the report. The report points out in particular the available lagrangian datasets that can be used for model evaluation as recommended in the MOC-0970-02 report.
4.2 RECOMMENDATIONS ON VALIDATION TECHNIQUES
The “Recommendations on validation techniques” MOC-0970-02 report is delivered in a second document. The recommendations provide practical recipes according to the available model and data in a given zone. In the optimal configuration of having good lagrangian data and suitable model outputs, good knowledge of important processes to evaluate the model is required and some generality are reminded in the first section of the report. The second section gives an overview of requirements for hydrographic models. The third section presents the useful observations types. The validation recipes depending on the available data are then detailed. The key points are summarized in the last section.
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4.3 LIMITATIONS OF THE WORK
This work has raised the following comments and suggestions. As a general comment it is increasingly difficult to locate relevant datasets, due to the rapidly growing volume, variety, and complexity of data available. About metadata dynamics: the model information is constantly updated. For instance, during the few months of inventory work, several websites addresses and contents (COHERENS, Mercator and others) was changed. It would be worth to integrate the spreadsheet into a maintained database. For ocean forecasting products, the GODAE OceanView Science Team GOVST maintains a list of national and regional efforts and produce annual report of their systems [Ref 11]. Thank you to the JIP members who have provided very useful feedbacks. However, the present document could be improved a lot using more O&G engineer’s feedback.
4.4 FROM DATA TO BIG DATA
Big data is a term in vogue that might be used in the context on this study. Indeed there is a paradox between the mass of ocean and atmospheric information available and the regular quest for the relevant data for environmental studies. One of the important challenges is to store data set with enough metadata for describing how the data should be interpreted and used [Ref 12].
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5 REFERENCES
Ref 1: Ajilon / Euro Engineering (EE), Inter-comparison and validation in-situ of oil spill drift model, Final report, September 2011 Ref 2: Summary of Near-Real Time Forecast Ocean Circulation Models Covering the Full GoMex, supplied by Cort Cooper, Chevron. Ref 3: Gulf of Mexico 3-D Operational Ocean Forecast System Pilot Prediction Project (GOMEX-PPP) Ref 4: ISO/DIS 19901-1 Petroleum and natural gas industries -- Specific requirements for offshore structures -- Part 1: Metocean design and operating considerations Ref 5: Energinet.dk, Horns Rev 3 Offshore Wind Farm, VALIDATION OF DMI’S MODEL SUITE FOR THE HORNS REV 3 AREA, MAY 2013 Ref 6: Chiswell, S. M., Rickard, and G. J. (2008). Eulerian and lagrangian statistics in the bluelink numerical model and aviso altimetry: Validation of model eddy kinetics. Journal of Geophysical Research: Oceans 113 (C10). Ref 7: Lacorata, G., L. Palatella, and R. Santoleri (2014). Lagrangian predictability characteristics of an ocean model. Journal of Geophysical Research: Oceans, n/a–n/a. Ref 8: Blockley et al, 2012, Validation of FOAM near-surface ocean current forecasts using Lagrangian drifting buoys E.W. Blockley, M. J. Martin, and P. Hyder Ref 9: Blockley et al., 2014. "Recent development of the Met Office operational ocean forecasting system: an overview and assessment of the new Global FOAM forecasts" Contains a description of the system and validation of the global analysis and forecast Ref 10: Francis et al, 2013, The Indian Ocean Forecast System Ref 11: GODAE OceanView Science Team GOVST national systems annual report https://www.godae-oceanview.org/documents/q/category/govst/system-reports/ (last visited 21/12/2014) Ref 12: SciServer: Big Data infrastructure for science, http://www.nsf.gov/discoveries/disc_summ.jsp?cntn_id=133526& (last visited 18/12/2014) Ref 13: Wang Y, Sen OL, Wang B (2003) A highly resolved regional climate model (IPRC- RegCM) and its simulation of the 1998 severe precipitation event over China. Part I: Model description and verification of simulation. J Climate 16: 1721–38 Ref 14: De Biasio, F., Miglietta, M. M., Zecchetto, S ., and della Valle, A.: Numerical models sea surface wind compared to scatterometer observations for a single Bora event in the Adriatic Sea, Adv. Sci. Res. , 11, 41-48, 2014 (doi:10.5194/asr-11-41-2014). Ref 15: Reistad, M, Ø Breivik, H Haakenstad, O J Aarnes, B R Furevik, and J Bidlot, 2011: A high-resolution hindcast of wind and waves for the North Sea, the Norwegian Sea, and the Barents Sea, J Geophys Res, 116, C05019, doi:10.1029/2010JC006402
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Ref 16: Liléo S, Petrik O. Investigation on the use of NCEP/NCAR, MERRA and NCEP/CFSR reanalysis data in wind resource analysis. EWEA 2011 conference proceedings, 2011. Ref 17: Sensitivity Testing of WRF parameterizations on air-sea interaction and its impact on water cycle in the Gulf of Guinea Meynadier R., de Coëtlogon G., Bastin S., Eymard L., Janicot S. Quarterly Journal of the Royal Meteorological Society, Royal Meteorological Society, 2014, (in press).
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End of report
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