MARCOOS/ESPreSSO ROMS RU Coastal Ocean Modeling and Prediction group John Wilkin, Gordon Zhang, Julia Levin, Naomi Fleming, Javier Zavala-Garay, Hernan.

Slides:



Advertisements
Similar presentations
Introduction Objective: Develop regional ocean forecasting capability AU$15M co-investment for Phase 1 Partners: Bureau, CSIRO, Navy Launched 2003, Phase1.
Advertisements

ROMS User Workshop, October 2, 2007, Los Angeles
ECOOP Meeting March 14-21, 2005 ECOOP WP7 Pierre-Yves LE TRAON Better use of remote sensing and in-situ observing systems for coastal/regional seas Objective.
The Inverse Regional Ocean Modeling System:
Assessing the Information Content and Impact of Observations on Ocean Circulation Estimates using 4D-Var Andy Moore Dept. of Ocean Sciences UC Santa Cruz.
SIO 210: I. Observational methods and II. Data analysis (combined single lecture) Fall 2013 Remote sensing In situ T, S and tracers Velocity Observing.
John Wilkin US East Coast ROMS/TOMS Projects North Atlantic Basin (NATL) Northeast North American shelf (NENA) NSF CoOP Buoyancy.
Kevin O’Brien University of Washington/JISAO NOAA/PMEL Interoperable Access to Near Real Time Ocean Observations with the Observing System Monitoring Center.
1 Development of a Regional Ocean Modeling System (ROMS) for Real-Time Forecasting in Prince William Sound and Adjacent Alaska Coastal Waters YI CHAO,
ROMS User Workshop: Modern Observational and Modeling Systems Rio de Janeiro, Brazil, October 3-4.
OPeNDAP/DODS Data URL: a_221_ _0000_000 Description: Select North American.
Rutgers Ocean Modeling Group ROMS 4DVar data assimilation Mid-Atlantic Bight and Gulf of Maine John Wilkin with Julia Levin, Javier Zavala-Garay, Hernan.
1 Accomplishments: * Nested ROMS in larger domain forward simulation (MABGOM-ROMS) with configuration suitable for IS4DVAR experimentation. Considerations:
1 4-Dimensional Variational Assimilation of Satellite Temperature and Sea Level Data in the Coastal Ocean and Adjacent Deep Sea John Wilkin Javier Zavala-Garay.
Building Bluelink David Griffin, Peter Oke, Andreas Schiller et al. March 2007 CSIRO Marine and Atmospheric Research.
Sensitivity Analysis of SST along NJ coast with ADROMS Weifeng (Gordon) Zhang John Wilkin Julia Levin Hernan Arango Institute of Marine and Coastal Sciences,
Application of Satellite Data in the Data Assimilation Experiments off Oregon Peng Yu in collaboration with Alexander Kurapov, Gary Egbert, John S. Allen,
ROMS/TOMS Tangent Linear and Adjoint Models Andrew Moore, CU Hernan Arango, Rutgers U Arthur Miller, Bruce Cornuelle, Emanuele Di Lorenzo, Doug Neilson.
The ROMS TL and ADJ Models: Tools for Generalized Stability Analysis and Data Assimilation Hernan Arango, Rutgers U Emanuele Di Lorenzo, GIT Arthur Miller,
ROMS surface temperature and velocity for 2001-Jul-23 (day 20 of 60-day simulation). Model grid resolution is 1 km. Velocity vectors are plotted for every.
Coastal Ocean Observation Lab John Wilkin, Hernan Arango, John Evans Naomi Fleming, Gregg Foti, Julia Levin, Javier Zavala-Garay,
Coastal Ocean Observation Lab John Wilkin, Hernan Arango, Julia Levin, Javier Zavala-Garay, Gordon Zhang Regional Ocean.
4DVar Assimilation (physics) in ROMS ESPreSSO * John Wilkin, Julia Levin, Javier Zavala-Garay 2006 reanalysis (SW06) Operational system for OOI CI OSSE.
The Global Ocean Data Assimilation System (GODAS) at NCEP
Forecasting the dispersal of the Hudson River Plume John Wilkin Gregg Foti Byoung-Ju Choi Institute of Marine and Coastal Sciences Rutgers, The State University.
Dale haidvogel US East Coast ROMS/TOMS Projects North Atlantic Basin (NATL) Northeast North American shelf (NENA) NSF CoOP Buoyancy.
ROMS/TOMS TL and ADJ Models: Tools for Generalized Stability Analysis and Data Assimilation Andrew Moore, CU Hernan Arango, Rutgers U Arthur Miller, Bruce.
Observing System Monitoring Center Integrating data and information across observing system networks.
The Inverse Regional Ocean Modeling System: Development and Application to Data Assimilation of Coastal Mesoscale Eddies. Di Lorenzo, E., Moore, A., H.
Adjoint Sensitivity Stidues in the Philippine Archipelago Region –Julia Levin –Hernan Arango –Enrique Curchitser –Bin Zhang
JERICO KICK OFF MEETINGPARIS – Maison de la recherche - 24 & 25 May 2011 WP9: New Methods to Assess the Impact of Coastal Observing Systems Presented by.
Andy Moore, UCSC Hernan Arango, Rutgers Gregoire Broquet, CNRS Chris Edwards & Milena Veneziani, UCSC Brian Powell, U Hawaii Jim Doyle, NRL Monterey Dave.
NOPP Project: Boundary conditions, data assimilation, and predictability in coastal ocean models OSU: R. M. Samelson (lead PI), J. S. Allen, G. D. Egbert,
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.
ROMS User Workshop, Rovinj, Croatia May 2014 Coastal Mean Dynamic Topography Computed Using.
PS4a: Real-time modelling platforms during SOP/EOP Chairs: G. Boni, B. Ivancan Picek, J.M. Lellouche 3 rd HyMex Workshop, 1-4 June 2009 Mistral Tramontane.
INTEGRATION OF MODELING AND OBSERVING SYSTEMS BIO-PHYSICAL MODELING ATMOSPHERE-OCEAN INTERACTION DATA ASSIMILATION MODEL COUPLING AND ADAPTIVE GRIDS HURRICANE/SEVERE.
Weak and Strong Constraint 4DVAR in the R egional O cean M odeling S ystem ( ROMS ): Development and Applications Di Lorenzo, E. Georgia Institute of Technology.
SCCOOS Goals and Efforts Within COCMP, SCCOOS aims to develop products and procedures—based on observational data—that effectively evaluate and improve.
Overview of Rutgers Ocean Modeling Group activities with 4DVar data assimilation in the Mid-Atlantic Bight John Wilkin NOS Silver Spring Feb 28-29, 2012.
Dale haidvogel Nested Modeling Studies on the Northeast U.S. Continental Shelves Dale B. Haidvogel John Wilkin, Katja Fennel, Hernan.
Use of sea level observations in DMIs storm surge model Jacob L. Høyer, Weiwei Fu, Kristine S. Madsen & Lars Jonasson Center for Ocean and Ice, Danish.
WP5 Task T5.4 WP5-T5.4 : Regional Iberia-Biscay-Irlande (IBI) integrated system ECOOP Annual Meeting.
ROMS 4D-Var: The Complete Story Andy Moore Ocean Sciences Department University of California Santa Cruz & Hernan Arango IMCS, Rutgers University.
Potential impact of HF radar and gliders on ocean forecast system Peter Oke June 2009 CSIRO Marine and Atmospheric Research.
The I nverse R egional O cean M odeling S ystem Development and Application to Variational Data Assimilation of Coastal Mesoscale Eddies. Di Lorenzo, E.
Modeling the biological response to the eddy-resolved circulation in the California Current Arthur J. Miller SIO, La Jolla, CA John R. Moisan NASA.
The Mediterranen Forecasting System: 10 years of developments (and the next ten) N.Pinardi INGV, Bologna, Italy.
ROMS hydrodynamic model ROMS-RCA model for hypoxia prediction RCA biogeochemical model Model forced by NARR/WRF meteorological forcing, river discharge.
The OR-WA coastal ocean forecast system Initial hindcast assimilation tests 1 Goals for the COMT project: -DA in presence of the Columbia River -Develop.
Wayne G. Leslie 13 November 2002 Harvard Ocean Prediction System (HOPS) Operational Forecasting and Adaptive Sampling.
Modeling the Gulf of Alaska using the ROMS three-dimensional ocean circulation model Yi Chao 1,2,3, John D. Farrara 2, Zhijin Li 1,2, Xiaochun Wang 2,
Hindcast Simulations of Hydrodynamics in the Northern Gulf of Mexico Using the FVCOM Model Zizang Yang 1, Eugene Wei 1, Aijun Zhang 2, Richard Patchen.
Weak Constraint 4DVAR in the R egional O cean M odeling S ystem ( ROMS ): Development and application for a baroclinic coastal upwelling system Di Lorenzo,
Predictability of Mesoscale Variability in the East Australian Current given Strong Constraint Data Assimilation John Wilkin Javier Zavala-Garay and Hernan.
Weak and Strong Constraint 4D variational data assimilation: Methods and Applications Di Lorenzo, E. Georgia Institute of Technology Arango, H. Rutgers.
Mediterranean- Gaps and Needs Nadia Pinardi University of Bologna Istituto Nazionale di Geofisica e Vulcanologia Italy.
The I nverse R egional O cean M odeling S ystem Development and Application to Variational Data Assimilation of Coastal Mesoscale Eddies. Di Lorenzo, E.
Impact of TAO observations on Impact of TAO observations on Operational Analysis for Tropical Pacific Yan Xue Climate Prediction Center NCEP Ocean Climate.
1 A multi-scale three-dimensional variational data assimilation scheme Zhijin Li,, Yi Chao (JPL) James C. McWilliams (UCLA), Kayo Ide (UMD) The 8th International.
Observations and Ocean State Estimation: Impact, Sensitivity and Predictability Andy Moore University of California Santa Cruz Hernan Arango Rutgers University.
The Mediterranean Forecasting INGV-Bologna.
Ocean Data Assimilation for SI Prediction at NCEP David Behringer, NCEP/EMC Diane Stokes, NCEP/EMC Sudhir Nadiga, NCEP/EMC Wanqiu Wang, NCEP/EMC US GODAE.
Predictability of Mesoscale Variability in the East Australia Current given Strong Constraint Data Assimilation Hernan G. Arango IMCS, Rutgers John L.
Real-Time Oregon Coastal Ocean Forecast System Alexander Kurapov, S. Erofeeva, P. Yu, G. D. Egbert, J. S. Allen, P. T. Strub, P. M. Kosro, D. Foley
Local Ensemble Transform Kalman Filter for ROMS in Indian Ocean
Y. Xue1, C. Wen1, X. Yang2 , D. Behringer1, A. Kumar1,
Adjoint Sensitivity Analysis of the California Current Circulation and Ecosystem using the Regional Ocean Modeling System (ROMS) Andy Moore, Emanuele.
Adjoint Sensitivity Studies on the US East Coast
COAS-CIOSS Coastal Ocean Modeling Activities
Presentation transcript:

MARCOOS/ESPreSSO ROMS RU Coastal Ocean Modeling and Prediction group John Wilkin, Gordon Zhang, Julia Levin, Naomi Fleming, Javier Zavala-Garay, Hernan Arango 5 km resolution for assimilation 1 km resolution for forecast NCEP NAM 3-hour meteorology 1-day average USGS gauge river flow Open boundaries: ROMS MAB-GoM nested within GODAE-HyCOM operational N. Atlantic (He/NCSU) > OPeNDAP data portal > Assimilation experiments in 2006 (4DVar) > Glider observation analysis (Representers)

Assimilation and observing system design experiments in 2006 (LaTTE and SW06) > LaTTE subdomain RU CODAR (with tides) All glider CTD All moored T/S > SW06/MARCOOS/ESPreSSO Now:Climatology (Hydrobase); AVISO altimetry in Slope Sea; SST (AVHRR/MODIS/GOES blended from PFEL CoastWatch) Soon:regional climatology; glider; VOS/XBT; Argo Future:coastal along-track altimetry; in situ and satellite optics and ocean color > Glider observing system design use representers to analyse information content of MARCOOS glider tracks

Forecast skill improvement with assimilation of CODAR 60-day ensemble of all analyses/forecasts u “along-shelf” component

Forecast skill improvement with assimilation of CODAR 60-day ensemble of all analyses/forecasts v “across-shelf” component

The “Representer” (Bennett) is a measure of the covariance/correlation between ocean state variables and a pattern of observations Method: integrate the adjoint model backwards forced at observational locations, then the tangent linear model forward to carry “information” to analysis/forecast times Cost function: Covariance between J and temperature,, reflects the influence of glider observation At time = finish of glider mission

At time = 5 days after finish of glider mission Cost function: Covariance between J and temperature,, reflects the influence of glider observation