NOCS: NEMO activities in 2006 Preliminary tests of a full “LOBSTER” biogechemical model within the ORCA1 configuration. (6 extra passive tracers). Developed.

Slides:



Advertisements
Similar presentations
Experiences and expectations of NEMO
Advertisements

MEsoSCale dynamical Analysis through combined model, satellite and in situ data PI: Bruno Buongiorno Nardelli 1 Co-PI: Ananda Pascual 2 & Marie-Hélène.
Tuning and Validation of Ocean Mixed Layer Models David Acreman.
DOGEE-SOLAS: The UK SOLAS Deep Ocean Gas Exchange Experiment Matt Salter.
Geophysical Fluid Dynamics Laboratory Review June 30 - July 2, 2009 Geophysical Fluid Dynamics Laboratory Review June 30 - July 2, 2009.
HYCOM 2.1 Development at RSMAS George Halliwell HYCOM Development –Included several vertical mixing algorithms –Refine the hybrid vertical coordinate adjustment.
HYCOM and the need for overflow/entrainment parameterizations.
Preliminary results on Formation and variability of North Atlantic sea surface salinity maximum in a global GCM Tangdong Qu International Pacific Research.
CORE-II HYCOM Science application and test cases
Tracers in Ocean and Climate Models* Matthew England CEMAP, School of Mathematics The University of New South Wales * See also
Geophysical Fluid Dynamics Laboratory Review June 30 - July 2, 2009 Geophysical Fluid Dynamics Laboratory Review June 30 - July 2, 2009.
Chesapeake Bay Lagrangian Floats Analysis. Motivation Lagrangian float has its advantage in describing waters from different origins. We follow definition.
Climate modeling Current state of climate knowledge – What does the historical data (temperature, CO 2, etc) tell us – What are trends in the current observational.
Ocean Stratification and Circulation Martin Visbeck DEES, Lamont-Doherty Earth Observatory
US CLIVAR Themes. Guided by a set of questions that will be addressed/assessed as a concluding theme action by US CLIVAR Concern a broad topical area.
NEMO Developments and application at the Bedford Institute of Oceanography, Canada F. Dupont, Y. Lu, Z. Wang, D. Wright Nemo user meeting 2009Dalhousie-DFO.
Japan/East Sea Hybrid Coordinate Ocean Model (HYCOM) Patrick J. Hogan and Harley E. Hurlburt Naval Research Laboratory, Code 7323, Stennis Space Center,
EVALUATION OF UPPER OCEAN MIXING PARAMETERIZATIONS S. Daniel Jacob 1, Lynn K. Shay 2 and George R. Halliwell 2 1 GEST, UMBC/ NASA GSFC, Greenbelt, MD
Climate Variability and Change in the U.S. GLOBEC Regions as Simulated by the IPCC Climate Models: Ecosystem Implications PIs: Antonietta Capotondi, University.
Oceanic and Atmospheric Modeling of the Big Bend Region Steven L. Morey, Dmitry S. Dukhovksoy, Donald Van Dyke, and Eric P. Chassignet Center for Ocean.
1.Introduction 2.Description of model 3.Experimental design 4.Ocean ciruculation on an aquaplanet represented in the model depth latitude depth latitude.
Theme 3:. WP10 Future changes in ocean carbonate chemistry Objectives: Determine future changes in carbonate chemistry (pH, CaCO 3 saturation states,
1-Slide Summary Explicit Southern Ocean eddies respond to forcing differently than parameterizations.  We need eddy resolving ocean climate models. Spurious.
Collaborative Research: Toward reanalysis of the Arctic Climate System—sea ice and ocean reconstruction with data assimilation Synthesis of Arctic System.
Improvement of model configurations ORCA025, NATL12, NATL4-AGRIF Variability of the subpolar Atlantic (ORCA025, NATL12, NATL4) Variability of the Southern.
Ocean Data Variational Assimilation with OPA: Ongoing developments with OPAVAR and implementation plan for NEMOVAR Sophie RICCI, Anthony Weaver, Nicolas.
Dale haidvogel Nested Modeling Studies on the Northeast U.S. Continental Shelves Dale B. Haidvogel John Wilkin, Katja Fennel, Hernan.
Global, Basin and Shelf Ocean Applications of OPA An Inter-Agency Canadian Initiative EC-DFO-DND + Universities + Mercator-Ocean  CONCEPTS -- Canadian.
Developments within FOAM Adrian Hines, Dave Storkey, Rosa Barciela, John Stark, Matt Martin IGST, 16 Nov 2005.
Gent-McWilliams parameterization: 20/20 Hindsight
The Gent-McWilliams parameterization of ocean eddies in climate models Peter Gent National Center for Atmospheric Research.
Mediterranean Sea Basin Scale model P.Lazzari, S. Salon, A. Teruzzi, K.Beranger, A. Crise Sesame WP3 meeting Villefranche sur Mer, Februay 2008 OGS,
Ocean modelling activities in Japan (some of activities in China and Korea are included in the report) report to the CLIVAR Working Group for Ocean Model.
First results from the isopycnic ocean carbon cycle model HAMOCC & MICOM/BCM Karen Assmann, Christoph Heinze, Mats Bentsen, Helge Drange Bjerknes Centre.
Synthetic Float Analysis in HYCOM Synthetic floats were released in an ocean model to study how the upper-limb (northward return flow) of the Atlantic.
1) What is the variability in eddy currents and the resulting impact on global climate and weather? Resolving meso-scale and sub- meso-scale ocean dynamics.
1 1 Morten D. Skogen WP10: Hindcast and scenario studies on coastal- shelf climate and ecosystem variability and change Overview and plans ECOOP annual.
Wayne G. Leslie 13 November 2002 Harvard Ocean Prediction System (HOPS) Operational Forecasting and Adaptive Sampling.
Near real time forecasting of biogeochemistry in global GCMs Rosa Barciela, NCOF, Met Office
Core Theme 5: Technological Advancements for Improved near- realtime data transmission and Coupled Ocean-Atmosphere Data Assimilation WP 5.2 Development.
O 2 Minimum zone of the South East Pacific PRIMO international Project Chili, Pérou, France U. Concepcion, U. Chili (Santiago) IGP, IMARPE (Pérou) CNRS/IRD/Université.
Role of the Gulf Stream and Kuroshio-Oyashio Systems in Large- Scale Atmosphere-Ocean Interaction: A Review Young-oh Kwon et al.
A Synthetic Drifter Analysis of Upper-Limb Meridional Overturning Circulation Interior Ocean Pathways in the Tropical/Subtropical Atlantic George Halliwell,
Marine Ecosystem Simulations in the Community Climate System Model
AOMIP status Experiments 1. Season Cycle 2. Coordinated - Spinup Coordinated - Analysis Coordinated 100-Year Run.
Current state of ECHAM5/NEMO coupled model Wonsun Park, Noel Keenlyside, Mojib Latif (IFM-GEOMAR) René Redler (NEC C&C Research Laboratories) DRAKKAR meeting.
OCB Scoping Workshop Observing biogeochemical cycles at global scales with floats and gliders April 2009, Moss Landing, CA
Ocean Climate Simulations with Uncoupled HYCOM and Fully Coupled CCSM3/HYCOM Jianjun Yin and Eric Chassignet Center for Ocean-Atmospheric Prediction Studies.
Page 1© Crown copyright Modelling the stable boundary layer and the role of land surface heterogeneity Anne McCabe, Bob Beare, Andy Brown EMS 2005.
Presented by LCF Climate Science Computational End Station James B. White III (Trey) Scientific Computing National Center for Computational Sciences Oak.
WCC-3, Geneva, 31 Aug-4 Sep 2009 Advancing Climate Prediction Science – Decadal Prediction Mojib Latif Leibniz Institute of Marine Sciences, Kiel University,
Multidecadal simulations of the Indian monsoon in SPEEDY- AGCM and in a coupled model Annalisa Bracco, Fred Kucharski and Franco Molteni The Abdus Salam.
G. Panteleev, P.Stabeno, V.Luchin, D.Nechaev,N.Nezlin, M.Ikeda. Estimates of the summer transport of the Kamchatka Current a variational inverse of hydrographic.
Evaluation of Upper Ocean Mixing Parameterizations S. Daniel Jacob 1, Lynn K. Shay 2 and George R. Halliwell 2 1 GEST, UMBC/ NASA GSFC, Greenbelt, MD
The effect of tides on the hydrophysical fields in the NEMO-shelf Arctic Ocean model. Maria Luneva National Oceanography Centre, Liverpool 2011 AOMIP meeting.
AO-FVCOM Development: A System Nested with Global Ocean Models Changsheng Chen University of Massachusetts School of Marine Science, USA
Arctic Ice-Ocean Modelling at BIO Shannon Nudds 1, Ji Lei 1, Youyu Lu 1, Charles Hannah 1, Frederic Dupont 2, Zeliang Wang 1, Greg Holloway 1, Michael.
Seasonal Variations of MOC in the South Atlantic from Observations and Numerical Models Shenfu Dong CIMAS, University of Miami, and NOAA/AOML Coauthors:
Gent-McWilliams parameterization: 20/20 Hindsight Peter R. Gent Senior Scientist National Center for Atmospheric Research.
AOMIP, October 2009 Katya Popova, Andrew Yool, Yevgenii Aksenov, Andrew Coward, Beverly de Cuevas National Oceanography Centre, Southampton, UK Arctic.
Impacts of Vertical Momentum Mixing in an Arctic Ocean Model Youyu Lu 1, Greg Holloway 2, Ji Lei 1 1 Bedford Institute of Oceanography 2 Institute of Ocean.
UPDATE FROM THE OCEAN MODEL WORKING GROUP
The Marine System Modelling group (MSM) at the UK's National Oceanography Centre (NOC) maintains and runs various NEMO configurations. Global, ocean-only,
AOMIP and FAMOS are supported by the National Science Foundation
WaveFlow KO Øyvind Breivik (MET Norway), Joanna Staneva (HZG), Jean Bidlot (ECMWF) and George Nurser (NOC)
RENUMERATE: Reducing numerical mixing resulting from applying tides explicitly in a global ocean model Alex Megann1 and Maria Luneva2 Project kickoff.
66-SE-CMEMS-CALL2: Lot-3 Benefits of dynamically modelled river discharge input for ocean and coupled atmosphere-land-ocean systems Hao Zuo, Fredrik Wetterhall,
Frontier Research System for Global Change,
CMEMS General Assembly, 23 May 2019
Presentation transcript:

NOCS: NEMO activities in 2006 Preliminary tests of a full “LOBSTER” biogechemical model within the ORCA1 configuration. (6 extra passive tracers). Developed “on-the-fly” interpolation of CORE forcing fields. Installed AGRIF capabilities. Configured an ORCA1 model with 1/4 o N.A. and 1/12 degree Flemish Cap region. Agreed common 64 level vertical grid with A.M. Treguier (replaces 66 level option) Obtained and tried the ORCA025 configuration. Attempted topographic and Straits modifications to improve inter-basin exchanges Tested Chris Harris’ (UKMO) implementation of Griffies’ skew-flux formulation of eddy induced transport. Preparing to test ORCA1 with DRAKKAR-compatible physical parameters and options in longer tests (DFS3 forcing)

OCEANS 2025: Themes and selected scientific objectives Theme 9: Next Generation Ocean Prediction Systems : ● How sensitive are climate models to the manner in which sea ice is coupled? ● Can nested models be trusted to give accurate results? ● Can an ocean model be made energetically self-consistent? ● What is the most appropriate level of complexity of biogeochemical models in climate studies? Approaches and methodologies: ● Develop NEMO as the core OGCM for use by the scientific community in the UK, at resolutions of 1°, ¼°and 1 / 12 °, and with nested grids (WP 9.10). ● Develop an ocean model testbed permitting objective intercomparison and validation of a range of ecosystem models, with a view to embedding the most promising in OGCMs (WP 9.11).

OCEANS 2025: Themes and selected scientific objectives Theme 2: Marine Biogeochemical Cycles ● To determine the sensitivity to future climate change of the mechanisms sustaining total nutrient supply to the photic zone over the three major biomes of the North Atlantic. Approaches and methodologies: ● Quantify the magnitude and sensitivity of nutrient fluxes associated with winter overturning and Ekman pumping. For overturning, this will be achieved using time-series stations, Argo floats and mooring data together with previous studies and basin-scale simulations (NEMO both at ¼º and with a smaller scale nested component at 1 / 12 º in the North Atlantic).

OCEANS 2025: Themes and selected scientific objectives Theme 1: Climate, Ocean Circulation, and Sea Level ● Model simulations of climate change in the ocean ● Identifying the causes of recent climate change in the ocean ● Physical-biogeochemical budgets and mixing in the Southern Ocean (DIMES) Research plan and deliverables: ● 2008: Completed simulation of changes in the ocean over the period obtained by running NEMO globally at 1/4° resolution (and with a nested 1/12° North Atlantic grid) using NCEP/NCAR (and possibly ECMWF) derived surface flux fields (WP 1.1b)

For comparison, a typical aeiu field using the H&L (default) scheme:

Aeiu field with the Visbeck scheme after 5 years integration.

Extra Physics in MOM4/OCCAM ● Horizontal K 11 term isn't truncated. This models horizontal diapycnal diffusivity in the ML ● Extra tapering near the surface (the sine taper) of all terms except K 11. Prevents too-strong surface-intensified GM velocities and allows smooth change from isopycnal to horizontal diffusion. ● Linear variation of the GM streamfunction between the ML base and surface to spread the GM flux through the ML. Otherwise, the steep-slope tapering brings the GM streamfunction to zero somewhere just above the ML base, and hence the GM flux is concentrated at the ML base ● Option to limit GM streamfunction at K GM S max instead of tapering it to zero for slopes exceeding S max. Allows more restratification.

Climatological Six hourly winds Assimilation runs Core strategic Modelling Infrastructure 66 vertical levels High frequency surface fluxes KPP mixed layer Isopycnic mixing Variable bottom box Sea ice