The TOPAZ3 forecasting system. L. Bertino, K.A. Lisæter, Mohn-Sverdrup Center/NERSC
|
|
|
- Easter Armstrong
- 5 years ago
- Views:
Transcription
1 The TOPAZ3 forecasting system L. Bertino, K.A. Lisæter, Mohn-Sverdrup Center/NERSC LOM meeting, Bergen Beach, 20 th Aug. 2007
2
3 Introduction Main objective of data assimilation Estimate the most likely state(s) of the ocean Sub-objectives (cf. Crosnier & Le Provost) Accuracy (versus observations) Consistency (physical sense) Performance (forecast skills) These are strongly dependent on the data assimilation method Spatial interpolation Multivariate correlations
4 System description Doubling the horizontal resolution EnKF assimilation of sea ice drift
5 The TOPAZ model system TOPAZ: Atlantic and Arctic HYCOM v ( EVP ice model coupled km resolution -> km 22 hybrid layers EnKF, ( 100 members Sea Level Anomalies (CLS) Sea Surface Temperatures Sea Ice Concentrations (SSM/I) Sea ice drift (CERSAT) Runs weekly ECMWF forcing Class 1-4 products on the OPeNDAP (
6 TOPAZ2
7 TOPAZ3
8 Circulation in Nordic Seas on 15 th Aug 2007 TOPAZ2 TOPAZ3
9 Example of ice concentrations 15/03/07 TOPAZ2 SSM/I
10 Example of ice concentrations 15/03/07 TOPAZ3 SSM/I
11 The EnKF algorithm Forecast Analysis Member1 1 2 Member2 Member99 1. Initial uncertainty 2. Model uncertainty 3. Measurement uncertainty 3 Observations Member100
12 Example of ensemble error estimates Sea ice thickness Ensemble average 13 th March 2007 Ensemble standard dev. 13 th March 2007
13 Ice drift assimilation Why the EnKF?
14 Divergence from the coast Correlation ice drift (y) ice thickness When new ice is freezing, thinner ice replaces the thick ice positive correlation of y- component with ice thickness Convergence to the coast The ice is packing Negative correlation of y- component with ice thickness
15 Impact of assimilation On ice concentrations On ice thickness
16 Validation in the Arctic Accuracy? Consistency? Performance?
17 Assimilation every week Up to +10 days forecast
18 Sparse profiles under ice --- TOPAZ NPEO *: North Pole Environment Observatory
19 Ice drift validation In-situ Ice drifting buoys (Statoil/CMR) Manned expeditions Remote sensing ASAR (NERSC) WP2 QuickSCAT (Ifremer) Modelling TOPAZ2 A good agreement [ J. Wåhlin, S. Sandven, NERSC ]
20 Buoys on ice International Arctic Buoy Program (US, Can) Less on the European side Ex: Statoil/CMR in March Period: ASAR Wideswath Ifremer data TOPAZ model Drifting buoys Displacement (km) Direction ( ) [ J. Wåhlin, S. Sandven, NERSC ]
21 Do volume fluxes change with data assimilation?
22 Transports with/without assimilation Year 2006 F. Høydalsvik TOPAZ2 / EnKF TOPAZ2 Ctrl Obs. estimates Northwards volume into Nordic Seas... Atlantic water only (35psu+) Southwards volume out of Nordic Seas Volume: Nordic into Arctic (Fram Strait + Barents Sea) 11.1 Sv 3.5 Sv Sv 10 Sv 2.9 Sv Sv 9.5 Sv 0.4 Sv Sv 9.1 Sv 4.6 Sv Sv 8-9 Sv 3.7 Sv Sv 7.3 Sv 9.5 Sv? Sv? The assimilation improves the Northwards transport of Atlantic water, but not the total volume fluxes: it does not improve the deep circulation (only surface observations are assimilated).
23 Forecast skills Example of ice concentrations, 8 th November 2006 Barents Sea Greenland Sea Laptev Sea Bering Strait Kara Sea
24 Conclusions The TOPAZ3 upgrade does large improvements But maybe limited by HYCOM V2.1.03? The EnKF shows some skills in Accuracy Consistency Performance
25 Plans Upgrade to HYCOM V Assimilation of Argo data Inclusion of ecosystem model Exploitation of TOPAZ at met.no 30-years reanalysis (in 2009)
26 Open positions deadline 15 Sept Post-doc (Oceanographer): Eddy-resolving modelling of the Nordic Seas. Immediate Start. 2 years. Post-Doc (Oceanographer/mathematician): non-gaussian data assimilation in a coupled HYCOM-Ecosystem model. Start Summer years. PhD fellow (Mathematician): assimilation of sea-ice drift and parameters estimation. Start Jan years PhD fellow (Mathematician): Methodological developments of the EnKF for oil reservoir simulations. 3 years Director NERSC.
Performance of a 23 years TOPAZ reanalysis
Performance of a 23 years TOPAZ reanalysis L. Bertino, F. Counillon, J. Xie,, NERSC LOM meeting, Copenhagen, 2 nd -4 th June 2015 Outline Presentation of the TOPAZ4 system Choice of modeling and assimilation
ICE DRIFT IN THE FRAM STRAIT FROM ENVISAT ASAR DATA
ICE DRIFT IN THE FRAM STRAIT FROM ENVISAT ASAR DATA Stein Sandven (1), Kjell Kloster (1), and Knut F. Dagestad (1) (1) Nansen Environmental and Remote Sensing Center (NERSC), Thormøhlensgte 47, N-5006
Uncertainty in Ocean Surface Winds over the Nordic Seas
Uncertainty in Ocean Surface Winds over the Nordic Seas Dmitry Dukhovskoy and Mark Bourassa Arctic Ocean Center for Ocean-Atmospheric Prediction Studies Florida State University Funded by the NASA OVWST,
Operational ice modelling and forecasting, sea ice data assimilation, impact of satellite observations
Operational ice modelling and forecasting, sea ice data assimilation, impact of satellite observations L. Bertino, J. Xie, E. Olason, P. Rampal, S. Bouillon, NERSC M. Müller, A. Melsom, G. Sutherland,
Dmitry Dukhovskoy and Mark Bourassa
Dmitry Dukhovskoy and Mark Bourassa Center for Ocean-Atmospheric Prediction Studies Florida State University Funded by the NASA OVWST, HYCOM consortium and NSF AOMIP Acknowledgement: P. Hughes (FSU), E.J.
Assimilation of ice concentration in a coupled ice ocean model, using the Ensemble Kalman Filter
Ocean Dynamics manuscript No. (will be inserted by the editor) Assimilation of ice concentration in a coupled ice ocean model, using the Ensemble Kalman Filter Knut Arild Lisæter, Julia Rosanova, Geir
O.M Smedstad 1, E.J. Metzger 2, R.A. Allard 2, R. Broome 1, D.S. Franklin 1 and A.J. Wallcraft 2. QinetiQ North America 2. Naval Research Laboratory
An eddy-resolving ocean reanalysis using the 1/12 global HYbrid Coordinate Ocean Model (HYCOM) and the Navy Coupled Ocean Data Assimilation (NCODA) scheme O.M Smedstad 1, E.J. Metzger 2, R.A. Allard 2,
FAMOS for YOPP Forum for Arctic Modeling and Observational Synthesis (FAMOS) for Year of Polar Prediction (YOPP)
FAMOS for YOPP Forum for Arctic Modeling and Observational Synthesis (FAMOS) for Year of Polar Prediction (YOPP) Andrey Proshutinsky (Woods Hole Oceanographic Institution) and research FAMOS team YOPP-Summit
On Modeling the Oceanic Heat Fluxes from the North Pacific / Atlantic into the Arctic Ocean
On Modeling the Oceanic Heat Fluxes from the North Pacific / Atlantic into the Arctic Ocean Wieslaw Maslowski Naval Postgraduate School Collaborators: Jaclyn Clement Kinney Terry McNamara, John Whelan
Canadian Ice Service
Canadian Ice Service Key Points and Details concerning the 2009 Arctic Minimum Summer Sea Ice Extent October 1 st, 2009 http://ice-glaces.ec.gc.ca 1 Key Points of Interest Arctic-wide The Arctic-wide minimum
Demonstration and Comparison of of Sequential Approaches for Altimeter Data Assimilation in in HYCOM
Demonstration and Comparison of of Sequential Approaches for Altimeter Data Assimilation in in HYCOM A. Srinivasan, E. P. Chassignet, O. M. Smedstad, C. Thacker, L. Bertino, P. Brasseur, T. M. Chin,, F.
Validation of Oil Spill Transport and Fate Modeling in Arctic Ice
Validation of Oil Spill Transport and Fate Modeling in Arctic Ice Authors: * 1 Deborah P. French-McCay, 1 Tayebeh Tajalli-Bakhsh, 1 Kathy Jayko, 2 Malcolm L. Spaulding, and 3 Zhengkai Li 1 RPS ASA 55 Village
Arctic sea ice in IPCC climate scenarios in view of the 2007 record low sea ice event A comment by Ralf Döscher, Michael Karcher and Frank Kauker
Arctic sea ice in IPCC climate scenarios in view of the 2007 record low sea ice event A comment by Ralf Döscher, Michael Karcher and Frank Kauker Fig. 1: Arctic September sea ice extent in observations
Intercomparison of the Arctic sea ice cover in global ocean-sea ice reanalyses
Intercomparison of the Arctic sea ice cover in global ocean-sea ice reanalyses Matthieu Chevallier (CNRM, Météo France/CNRS) Greg Smith, Frédéric Dupont, Jean-François Lemieux (ECC Canada), Gilles Garric
Advancements and Limitations in Understanding and Predicting Arctic Climate Change
Advancements and Limitations in Understanding and Predicting Arctic Climate Change Wieslaw Maslowski Naval Postgraduate School Collaborators: Jaclyn Clement Kinney, Rose Tseng, Timothy McGeehan - NPS Jaromir
Evaluation of the sea ice forecast at DMI
DMI Evaluation of the sea ice forecast at DMI Till A. S. Rasmussen 1 Kristine S. Madsen 1, Mads H. Ribergaard 1, Leif T.Pedersen 1, Jacob L Høyer 1, Gorm Dybkjær 1, Mads Bruun Poulsen 2 and Sofie Abildgaard
QUALITY INFORMATION DOCUMENT For Arctic Ocean Physical Analysis and Forecast Product ARCTIC_ANALYSIS_FORECAST_PHYS_002_001_A
QUALITY INFORMATION DOCUMENT For Arctic Ocean Physical Analysis and Forecast Issue: 6.0 Contributors: Arne Melsom, Magne Simonsen, Laurent Bertino, Bruce Hackett, Geir Arne Waagbø, Roshin Raj Approval
MERSEA IP WP 5 Integrated System Design and Assessment. Internal Metrics for the MERSEA Global Ocean: Specifications for Implementation
MERSEA IP WP 5 Integrated System Design and Assessment Internal Metrics for the MERSEA Global Ocean: Specifications for Implementation Planning Workshop CSIRO Hobart, Australia 17-18 March 7 Participants
Arctic Regional Ocean Observing System Arctic ROOS Report from 2012
Arctic Regional Ocean Observing System Arctic ROOS Report from 2012 By Stein Sandven Nansen Environmental and Remote Sensing Center (www.arctic-roos.org) Focus in 2012 1. Arctic Marine Forecasting Center
Observed rate of loss of Arctic ice extent is faster than IPCC AR4 predictions
When will Summer Arctic Sea Ice Disappear? Wieslaw Maslowski Naval Postgraduate School Collaborators: Jaclyn Clement Kinney, Andrew Miller, Terry McNamara, John Whelan - Naval Postgraduate School Jay Zwally
Overview of data assimilation in oceanography or how best to initialize the ocean?
Overview of data assimilation in oceanography or how best to initialize the ocean? T. Janjic Alfred Wegener Institute for Polar and Marine Research Bremerhaven, Germany Outline Ocean observing system Ocean
Using Arctic Ocean Color Data in ocean-sea ice-biogeochemistry seasonal forecasting systems
Using Arctic Ocean Color Data in ocean-sea ice-biogeochemistry seasonal forecasting systems Matthieu Chevallier 1 The POLARIS project David Salas y Mélia 1, Roland Séférian 1, Marion Gehlen 2, Gilles Garric
The Arctic Energy Budget
The Arctic Energy Budget The global heat engine [courtesy Kevin Trenberth, NCAR]. Differential solar heating between low and high latitudes gives rise to a circulation of the atmosphere and ocean that
GOCINO GOCINO. Final Activity Report. GOCE in Ocean Modelling. Specific Support Action. Contract N o SSA5-CT
GOCINO Contract N o SSA5-CT-2006-030756 GOCINO GOCE in Ocean Modelling Specific Support Action Final Activity Report Start date of project: 1 June 2007 Date of preparation: 14 March 2010 Project coordinator
High-Resolution Satellite-Derived Ocean Surface Winds in the Nordic-Barents Seas Region in : Implications for Ocean Modeling
High-Resolution Satellite-Derived Ocean Surface Winds in the Nordic-Barents Seas Region in 2007-2008: Implications for Ocean Modeling Векторные поля приповерхностных скоростей ветра над Cеверным и Баренцевым
The Arctic Ocean Climate a balance between local radiation, advected heat and freshwater
The Arctic Ocean Climate a balance between local radiation, advected heat and freshwater Bert Rudels Finnish Meteorological Institute, Helsinki, Finland French Arctic Initiative, Collège de France, Paris,
Title. Author(s)Maslowski, Wieslaw. Citation 地球温暖化による劇変を解明する. 平成 20 年 6 月 24 日. 札幌市. Issue Date Doc URL. Type.
Title When will Summer Arctic Sea Ice Disappear? Author(s)Maslowski, Wieslaw Citation 地球温暖化による劇変を解明する. 平成 20 年 6 月 24 日. 札幌市 Issue Date 2008-06-24 Doc URL http://hdl.handle.net/2115/34395 Type conference
TOPAZ4: an ocean-sea ice data assimilation system for the North Atlantic and Arctic
Ocean Sci., 8, 633 656, 212 www.ocean-sci.net/8/633/212/ doi:1.5194/os-8-633-212 Author(s) 212. CC Attribution 3. License. Ocean Science TOPAZ4: an ocean-sea ice data assimilation system for the North
Enhancing predictability of the Loop Current variability using Gulf of Mexico Hycom
Enhancing predictability of the Loop Current variability using Gulf of Mexico Hycom Matthieu Le Hénaff (1) Villy Kourafalou (1) Ashwanth Srinivasan (1) Collaborators: O. M. Smedstad (2), P. Hogan (2),
The Mediterranean Operational Oceanography Network (MOON): Products and Services
The Mediterranean Operational Oceanography Network (MOON): Products and Services The MOON consortia And Nadia Pinardi Co-chair of MOON Istituto Nazionale di Geofisica e Vulcanologia Department of Environmental
Current status and plans for developing sea ice forecast services and products for the WMO Arctic Regional Climate Centre Sea Ice Outlook
Current status and plans for developing sea ice forecast services and products for the WMO Arctic Regional Climate Centre 2018 Sea Ice Outlook 13 WMO Global Producing Centres providing seasonal forecasts
Pacific HYCOM. E. Joseph Metzger, Harley E. Hurlburt, Alan J. Wallcraft, Luis Zamudio and Patrick J. Hogan
Pacific HYCOM E. Joseph Metzger, Harley E. Hurlburt, Alan J. Wallcraft, Luis Zamudio and Patrick J. Hogan Naval Research Laboratory, Stennis Space Center, MS Center for Ocean-Atmospheric Prediction Studies,
WP 4 Testing Arctic sea ice predictability in NorESM
WP 4 Testing Arctic sea ice predictability in NorESM Jens Boldingh Debernard SSPARSE Kick-off meeting 08.11.2016 Norwegian Meteorological Institute Background Inherent coupled problem Time-frame relevant
Comparison of of Assimilation Schemes for HYCOM
Comparison of of Assimilation Schemes for HYCOM Ashwanth Srinivasan, C. Thacker, Z. Garraffo, E. P. Chassignet, O. M. Smedstad, J. Cummings, F. Counillon, L. Bertino, T. M. Chin, P. Brasseur and C. Lozano
Applications of an ensemble Kalman Filter to regional ocean modeling associated with the western boundary currents variations
Applications of an ensemble Kalman Filter to regional ocean modeling associated with the western boundary currents variations Miyazawa, Yasumasa (JAMSTEC) Collaboration with Princeton University AICS Data
(1) Arctic Sea Ice Predictability,
(1) Arctic Sea Ice Predictability, (2) It s Long-term Loss and Implications for Ocean Conditions Marika Holland, NCAR With contributions from: David Bailey, Alex Jahn, Jennifer Kay, Laura Landrum, Steve
Recent and future changes of the Arctic sea-ice cover
Click Here for Full Article GEOPHYSICAL RESEARCH LETTERS, VOL. 35, L20503, doi:10.1029/2008gl034813, 2008 Recent and future changes of the Arctic sea-ice cover Lars H. Smedsrud, 1 Asgeir Sorteberg, 1 and
Cruise Report R.V. Oceania, AREX2004
Powstaców Warszawy, PL - 81-71 Sopot, P.O. Box 68 November 16. 4 Cruise Report R.V. Oceania, AREX4 Ship: Cruise: R.V. Oceania Arex4 Dates: 8.6.4 19.7.4 Port Calls: Sopot (Poland) Longyearbyen (Spitsbergen)
Update on Coupled Air-Sea-Ice Modelling
Update on Coupled Air-Sea-Ice Modelling H. Ritchie 1,4, G. Smith 1, J.-M. Belanger 1, J-F Lemieux 1, C. Beaudoin 1, P. Pellerin 1, M. Buehner 1, A. Caya 1, L. Fillion 1, F. Roy 2, F. Dupont 2, M. Faucher
Developing Operational MME Forecasts for Subseasonal Timescales
Developing Operational MME Forecasts for Subseasonal Timescales Dan C. Collins NOAA Climate Prediction Center (CPC) Acknowledgements: Stephen Baxter and Augustin Vintzileos (CPC and UMD) 1 Outline I. Operational
Validation of sea ice concentration in the myocean Arctic Monitoring and Forecasting Centre 1
Note No. 12/2010 oceanography, remote sensing Oslo, August 9, 2010 Validation of sea ice concentration in the myocean Arctic Monitoring and Forecasting Centre 1 Arne Melsom 1 This document contains hyperlinks
Modeling of the sea ice and the ocean in the Nares Strait
Danish Meteorological Institute Modeling of the sea ice and the ocean in the Nares Strait Till Andreas Soya Rasmussen 1 Eigil Kaas 2 Nicolai Kliem 1 1/ Danish Meteorological Institute 2/ University of
Causes of Changes in Arctic Sea Ice
Causes of Changes in Arctic Sea Ice Wieslaw Maslowski Naval Postgraduate School Outline 1. Rationale 2. Observational background 3. Modeling insights on Arctic change Pacific / Atlantic Water inflow 4.
Second Session of the Pan-Arctic Regional Climate Outlook Forum (PARCOF-2), virtual forum, October 2018
Second Session of the Pan-Arctic Regional Climate Outlook Forum (PARCOF-2), virtual forum, October 2018 Consensus Statement for the Arctic Winter 2018-2019 Season Outlook Climate change in the Arctic is
The Ensemble Kalman Filter:
p.1 The Ensemble Kalman Filter: Theoretical formulation and practical implementation Geir Evensen Norsk Hydro Research Centre, Bergen, Norway Based on Evensen 23, Ocean Dynamics, Vol 53, No 4 p.2 The Ensemble
T2.2: Development of assimilation techniques for improved use of surface observations
WP2 T2.2: Development of assimilation techniques for improved use of surface observations Matt Martin, Rob King, Dan Lea, James While, Charles-Emmanuel Testut November 2014, ECMWF, Reading, UK. Contents
DEMOSS. Title: Development of Marine Oil Spills/slicks Satellite monitoring System elements for the Black Sea, Caspian Sea and /Kara/Barents Seas
DEMOSS Title: Development of Marine Oil Spills/slicks Satellite monitoring System elements for the Black Sea, Caspian Sea and /Kara/Barents Seas INTAS Thematic Call on Earth Sciences and Environment in
Climate reanalysis and reforecast needs: An Ocean Perspective
Climate reanalysis and reforecast needs: An Ocean Perspective Hao Zuo with M. Balmaseda, S. Tietsche, P. Browne, B. B. Sarojini, E. de Boisseson, P. de Rosnay ECMWF Hao.Zuo@ecmwf.int ECMWF January 23,
MERSEA Marine Environment and Security for the European Area
MERSEA Marine Environment and Security for the European Area Development of a European system for operational monitoring and forecasting of the ocean physics, biogeochemistry, and ecosystems, on global
Assimilating Altimetry Data into a HYCOM Model of the Pacific: Ensemble Optimal Interpolation versus Ensemble Kalman Filter
APRIL 2010 W A N E T A L. 753 Assimilating Altimetry Data into a HYCOM Model of the Pacific: Ensemble Optimal Interpolation versus Ensemble Kalman Filter LIYING WAN National Marine Environmental Forecasting
North Atlantic circulation in three simulations of 1/12, 1/25, and 1/50
North Atlantic circulation in three simulations of 1/12, 1/2, and 1/ Xiaobiao Xu and Eric Chassignet Center for ocean-atmospheric prediction studies Florida State University Motivation Numerical models
Operational Ocean and Climate Modeling at NCEP
Operational Ocean and Climate Modeling at NCEP 5 th Annual CoRP Science Symposium Corvallis, OR Aug. 12-13, 2008 Hua-Lu Pan and Hendrik Tolman Environmental Modeling Center NCEP 1.7B Obs/Day Satellites
The Northern Hemisphere Sea ice Trends: Regional Features and the Late 1990s Change. Renguang Wu
The Northern Hemisphere Sea ice Trends: Regional Features and the Late 1990s Change Renguang Wu Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing World Conference on Climate Change
A New Global Ice Analysis System
A New Global Ice Analysis System Seminar CMC, Dorval Alain Caya and Mark Buehner Meteorological Research Division Manon Lajoie Prediction Development Branch Tom Carrieres and Lynn Pogson Marine and Ice
Data assimilation for marine monitoring and prediction: The MERCATOR operational assimilation systems and the MERSEA developments
Q. J. R. Meteorol. Soc. (2005), 131, pp. 3561 3582 doi: 10.1256/qj.05.142 Data assimilation for marine monitoring and prediction: The MERCATOR operational assimilation systems and the MERSEA developments
Mersea Oil Spill Drift Forecast Demonstrations in TOP2
Mersea Oil Spill Drift Forecast Demonstrations in TOP2 Bruce Hackett (met.no), George Zodiatis (UCY), Pierre Daniel (MeteoFrance), Francois Parthiot (Cedre) Presented at 3rd Mersea Plenary Meeting, CNR,
Validation of Oil Spill Transport and Fate Modeling in Arctic Ice
Page 1 of 64 Validation of Oil Spill Transport and Fate Modeling in Arctic Ice Authors: * 1 Deborah P. French-McCay, 1 Tayebeh Tajalli-Bakhsh, 1 Kathy Jayko, 2 Malcolm L. Spaulding, and 3 Zhengkai Li 1
A Dressed Ensemble Kalman Filter Using the Hybrid Coordinate Ocean Model in the Pacific
ADVANCES IN ATMOSPHERIC SCIENCES, VOL. 26, NO. 5, 2009, 1042 1052 A Dressed Ensemble Kalman Filter Using the Hybrid Coordinate Ocean Model in the Pacific WAN Liying 1 (!"#), ZHU Jiang 2 ($%), WANG Hui
O.M Smedstad 1, E.J. Metzger 2, R.A. Allard 2, R. Broome 1, D.S. Franklin 1 and A.J. Wallcraft 2. QinetiQ North America 2. Naval Research Laboratory
An eddy-resolving ocean reanalysis using the 1/12 global HYbrid Coordinate Ocean Model (HYCOM) and the Navy Coupled Ocean Data Assimilation (NCODA) scheme O.M Smedstad 1, E.J. Metzger 2, R.A. Allard 2,
The impact of polar mesoscale storms on northeast Atlantic Ocean circulation
The impact of polar mesoscale storms on northeast Atlantic Ocean circulation Influence of polar mesoscale storms on ocean circulation in the Nordic Seas Supplementary Methods and Discussion Atmospheric
S12. The Arctic Ocean and Nordic Seas: Supplementary Materials
C H A P T E R S12 The Arctic Ocean and Nordic Seas: Supplementary Materials FIGURE S12.1 Principal currents of the Nordic Seas. Shaded currents show upper ocean circulation; thin black arrows show deep
- Global Reanalysis of Ocean biogeochemistry : GREEN Grog -
Journées GMMC Toulon, 7-9 juin 2016 - Global Reanalysis of Ocean biogeochemistry : - Marion Gehlen (IPSL/LSCE) marion.gehlen@lsce.ipsl.fr and the consortium A new PPR associating : Mercator-Océan CLS,
Numerical Weather Prediction: Data assimilation. Steven Cavallo
Numerical Weather Prediction: Data assimilation Steven Cavallo Data assimilation (DA) is the process estimating the true state of a system given observations of the system and a background estimate. Observations
IABP Deployment Plans for 2004
IABP Buoy Positions IABP Deployment Plans for 2004 SPRING NPEO (Multiple buoys provided by NOAA/PMEL, JAMSTEC, & CRREL) EC/NIC- CES (80N 120W, & 80N 130W) SUMMER IARC/NABOS Cruise 2 NOAA-PSC IMB (North
Sea Ice Forecast Verification in the Canadian Global Ice Ocean Prediction System
Sea Ice Forecast Verification in the Canadian Global Ice Ocean Prediction System G Smith 1, F Roy 2, M Reszka 2, D Surcel Colan, Z He 1, J-M Belanger 1, S Skachko 3, Y Liu 3, F Dupont 2, J-F Lemieux 1,
Arctic Ocean-Sea Ice-Climate Interactions
Arctic Ocean-Sea Ice-Climate Interactions Sea Ice Ice extent waxes and wanes with the seasons. Ice extent is at a maximum in March (typically 14 million square km, about twice the area of the contiguous
Estimate for sea ice extent for September, 2009 is comparable to the 2008 minimum in sea ice extent, or ~ km 2.
September 2009 Sea Ice Outlook: July Report By: Jennifer V. Lukovich and David G. Barber Centre for Earth Observation Science (CEOS) University of Manitoba Estimate for sea ice extent for September, 2009
Extreme, transient Moisture Transport in the high-latitude North Atlantic sector and Impacts on Sea-ice concentration:
AR conference, June 26, 2018 Extreme, transient Moisture Transport in the high-latitude North Atlantic sector and Impacts on Sea-ice concentration: associated Dynamics, including Weather Regimes & RWB
Sea-ice change around Alaska & Impacts on Human Activities
Sea-ice change around Alaska & Impacts on Human Activities Hajo Eicken Geophysical Institute University of Alaska Fairbanks, hajo.eicken@gi.alaska.edu Introduction The Arctic sea-ice cover: Observations
A data assimilation approach for reconstructing sea ice volume in the Southern Hemisphere
Harmony on Ice 2 meeting Paris, 28-29 Nov. 2011 A data assimilation approach for reconstructing sea ice volume in the Southern Hemisphere F. Massonnet, P. Mathiot, T. Fichefet, H. Goosse, C. König Beatty,
Recent Improvements in the U.S. Navy s Ice Modeling Efforts Using CryoSat-2 Ice Thickness for Model Initialization
Recent Improvements in the U.S. Navy s Ice Modeling Efforts Using CryoSat-2 Ice Thickness for Model Initialization Richard Allard 1, David Hebert 1, Pamela Posey 1, Alan Wallcraft 1, Li Li 2, William Johnston
Early results and plans for the future. Robert Atlas
Observing System Simulation Experiments: Methodology, Early results and plans for the future Robert Atlas National Oceanic and Atmospheric Administration Atlantic Oceanographic and Meteorological Laboratory
The Maritime Continent as a Prediction Barrier
The Maritime Continent as a Prediction Barrier for the MJO Augustin Vintzileos EMC/NCEP SAIC Points to take back home. Forecast of the MJO is at, average, skillful for lead times of up to circa 2 weeks.
Presentation of met.no s experience and expertise related to high resolution reanalysis
Presentation of met.no s experience and expertise related to high resolution reanalysis Oyvind Saetra, Ole Einar Tveito, Harald Schyberg and Lars Anders Breivik Norwegian Meteorological Institute Daily
Data assimilation for ocean climate studies
Data assimilation for ocean climate studies James Carton, Gennady Chepurin, Steven Penny, and David Behringer (thanks Eugenia) University of Maryland, NOAA/NCEP, College Park, MD USA Chl concentration
Improving numerical sea ice predictions in the Arctic Ocean by data assimilation using satellite observations
Okhotsk Sea and Polar Oceans Research 1 (2017) 7-11 Okhotsk Sea and Polar Oceans Research Association Article Improving numerical sea ice predictions in the Arctic Ocean by data assimilation using satellite
Upper Ocean Mixing Processes and Circulation in the Arabian Sea during Monsoons using Remote Sensing, Hydrographic Observations and HYCOM Simulations
DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Upper Ocean Mixing Processes and Circulation in the Arabian Sea during Monsoons using Remote Sensing, Hydrographic Observations
In-situ and airborne sea ice observations for better sea ice prediction and climate analysis. Christian Haas
In-situ and airborne sea ice observations for better sea ice prediction and climate analysis Christian Haas Data assimilation improves sea ice forecasts Most important parameters are: Concentration (SIC),
South African Weather Service SWIOCOF-5 Pre-Forum. Seasonal Forecast, Water Resources and Expected Outcomes
South African Weather Service SWIOCOF-5 Pre-Forum Seasonal Forecast, Water Resources and Expected Outcomes Marc de Vos, September 2016 South Africa: Context BCRE, 2016, adapted from Boebel et al., 2003
Распространение плотных придонных
Распространение плотных придонных вод на шельфе Арктических морей Dense bottom water transport over the shelf of Arctic seas Платов Г. А. (Platov G. A.) ИВМиМГ СОРАН, Новосибирск ICMMG, Novosibirsk Problems
Ocean Observations for an End-to-End Seasonal Forecasting System
Ocean Observations for an End-to-End Seasonal Forecasting System Magdalena A. Balmaseda Yosuke Fujii Oscar Alves Tong Lee Michele Rienecker Tony Rosati Detlef Stammer Yan Xue Howard Freeland Michael McPhaden
Arctic Ocean simulation in the CCSM4
Arctic Ocean simulation in the CCSM4 Alexandra Jahn National Center for Atmospheric Sciences, Boulder, USA Collaborators: K. Sterling, M.M. Holland, J. Kay, J.A. Maslanik, C.M. Bitz, D.A. Bailey, J. Stroeve,
North Pacific Climate Overview N. Bond (UW/JISAO), J. Overland (NOAA/PMEL) Contact: Last updated: September 2008
North Pacific Climate Overview N. Bond (UW/JISAO), J. Overland (NOAA/PMEL) Contact: Nicholas.Bond@noaa.gov Last updated: September 2008 Summary. The North Pacific atmosphere-ocean system from fall 2007
Toward Environmental Predictions MFSTEP. Executive summary
Research Project co-funded by the European Commission Research Directorate-General 5 th Framework Programme Energy, Environment and Sustainable Development Contract No. EVK3-CT-2002-00075 Project home
Bering Strait, AMOC hysteresis, and abrupt climate change
DOE/UCAR Cooperative Agreement Regional and Global Climate Modeling Program Bering Strait, AMOC hysteresis, and abrupt climate change Aixue Hu Gerald A. Meehl, Weiqing Han, Axel Timmerman, Bette Otto-Bliester,
Modelling approaches for MOSAiC. Klaus Dethloff, A. Rinke, A. Sommerfeld, D. Klaus T. Vihma, M. Müller, J. Inoue, W. Maslowski & modelling team
Modelling approaches for MOSAiC Klaus Dethloff, A. Rinke, A. Sommerfeld, D. Klaus T. Vihma, M. Müller, J. Inoue, W. Maslowski & modelling team Why do we need MOSAiC? High quality co-observations of A-O-I-BGC-E
The Bering Sea/Bering Strait Relationship. Bering Strait and the Chukchi Sea
The Bering Sea/ Relationship ANSF= Aleutian North Slope Current BSC = Bering Slope Current Anadyr (colder, saltier, nutrient-rich) Bering Shelf Waters (in between!) Exit route! From Stabeno, Schumacher
IAOOS EQUIPEX ANR 10 EQPX Ice Atmosphere Arctic Ocean Observing System
EQUIPEX ANR 10 EQPX 32 01 IAOOS 2011 2019 Ice Atmosphere Arctic Ocean Observing System PI: C. Provost LOCEAN, J. Pelon LATMOS http://www.iaoos-equipex.upmc.fr/ 1 34 ITP Ice Tethered Profilers 2006 2010
Challenges and Observational Requirements for Advancement of Process-Oriented Regional Arctic Climate Modeling and Prediction
Challenges and Observational Requirements for Advancement of Process-Oriented Regional Arctic Climate Modeling and Prediction Wieslaw Maslowski 2 and Annette Rinke 1 1 Alfred Wegener Institute (AWI), 2
An Update on the 1/12 Global HYCOM Effort
An Update on the 1/12 Global HYCOM Effort E. Joseph Metzger, Alan J. Wallcraft, Jay F. Shriver and Harley E. Hurlburt Naval Research Laboratory 10 th HYCOM Consortium Meeting 7-99 November 2006 FSU-COAPS,
The ECMWF coupled data assimilation system
The ECMWF coupled data assimilation system Patrick Laloyaux Acknowledgments: Magdalena Balmaseda, Kristian Mogensen, Peter Janssen, Dick Dee August 21, 214 Patrick Laloyaux (ECMWF) CERA August 21, 214
Modelling forecast error statistics in the Mercator ocean and sea-ice reanalysis system.
Modelling forecast error statistics in the Mercator ocean and sea-ice reanalysis system. C.E Testut 1, G. Ruggiero 1, L. Parent 1, J.M. Lellouche 1, O. Legalloudec 1, C. Bricaud 1, J. Chanut 1, G. Smith
Implementation of the SEEK filter in HYCOM
Implementation of the SEEK filter in HYCOM P. Brasseur, J. Verron, J.M. Brankart LEGI/CNRS, Grenoble, France HYCOM model SST, SSH, ocean colour Assimilation SEEK filter Y H x f In situ, XBT K x a Real-time
An analysis of the Atlantic Meridional Overturning Circulation (MOC) in an Atmosphere-Ocean General Circulation Model
An analysis of the Atlantic Meridional Overturning Circulation (MOC) in an Atmosphere-Ocean General Circulation Model Virginie Guemas, David Salas-Mélia Centre National de Recherches Météorologiques (CNRM)
Sea Ice Motion: Physics and Observations Ron Kwok Jet Propulsion Laboratory California Institute of Technology, Pasadena, CA
Sea Ice Motion: Physics and Observations Ron Kwok Jet Propulsion Laboratory California Institute of Technology, Pasadena, CA 7 th ESA Earth Observation Summer School ESRIN, Frascati, Italy 4-14 August
An Assessment of the Navy's Sea Ice Outlook Predictions for 2014
An Assessment of the Navy's Sea Ice Outlook Predictions for 2014 Pam Posey 1, Rick Allard 1, David Hebert 1, Joe Metzger 1, Ruth Preller 1, Alan Wallcraft 1, Ole Martin Smedstad 2, Michael Phelps 3 and
The ECMWF Extended range forecasts
The ECMWF Extended range forecasts Laura.Ferranti@ecmwf.int ECMWF, Reading, U.K. Slide 1 TC January 2014 Slide 1 The operational forecasting system l High resolution forecast: twice per day 16 km 91-level,
Biogeochemical modelling and data assimilation: status in Australia
Biogeochemical modelling and data assimilation: status in Australia Richard Matear, Andrew Lenton, Matt Chamberlain, Mathieu Mongin, Emlyn Jones, Mark Baird www.cmar.csiro.au/staff/oke/ Biogeochemical
From short range forecasts to climate change projections of extreme events in the Baltic Sea region
Great Baltic Sea flood, November 13, 1872 Farm houses in Niendorf (near Lübeck) being torn away. Privately owned, Fam. Muuß, Hotel Friedrichsruh. Sea level 3.50 m above normal. From short range forecasts
Evolution of the Mercator Océan system, main components for reanalysis and forecast
Evolution of the Mercator Océan system, main components for reanalysis and forecast Y. Drillet, J.M. Lellouche, O. Le Galloudec, M. Drévillon, G. Garric, R. Bourdallé- Badie, C. Bricaud, J. Chanut, G.