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DA-MEAP Task Team Workshop (DA-MEAP-TT)

UC Santa Cruz, Santa Cruz, California, USA, 11-13 July 2016


View the sessions/presentations by clicking on the title links:

 (File sizes larger than 5 MB are marked)


1.0Welcome and introductionAndrew MooreUC Santa Cruz
1.1Workshop aims and objectivesAndrew MooreMet Office
1.2Overview of GOVPaul DiGiacomoNOAA
1.3Overview and status of the MEAP-TTKatja Fennel and Marion GehlenDalhousie University
1.4Overview and status of the DA-TTAndrew MooreUC Santa Cruz


J1: Recent developments in global ocean data assimilation systems (physical and biogeochemical)

J1.1Biogeochemical data assimilation at the Met Office: recent results and planned developmentsDavid FordMet Office
J1.2The ERA-CLIM2 project: Production of extended climate reanalysis with associated carbon fluxes reconstructionPatrick LaloyauxECMWF
J1.3Data assimilation for improved estimation of autotrophic carbon using marine biogeochemical modelsShovonlal RoyUniversity of Reading
J1.4Implementation of the Ocean Data Assimilation Component in the ECMWF Object-Oriented Prediction SystemMarcin ChrustECMWF
J1.5OceanVar: an improved variational data assimilation system with variational quality control of observationsAndrea StortoCMCC
J1.6Reducing equatorial ocean model imbalances caused by data assimilationJennifer WatersMet Office


J2: Recent developments in regional ocean data assimilation systems (physical and biogeochemical)

J2.1Assimilation Impact of Physical Data on the California Coastal Ocean Circulation and BiogeochemistryJohn FarraraRemote Sensing Solutions
J2.2Data assimilation of physical and chlorophyll observations in the California Current System using two biogeochemical modelsJann Paul MatternUC Santa Cruz
J2.3Assimilation of biogeochemical data to improve the simulation, understanding and management of marine ecosystems: experiences in the North West European shelfStefano CiavattaPlymouth Marine Laboratory - National Centre for Earth Observation
J2.4Ocean Biogeochemical State-Parameters Estimation within the Norwegian Earth System Model: Ensemble Techniques and 1D Assimilation at Different Latitudes (25 MB)Mohamad El GharamtiNERSC
J2.5Assimilation of satellite-derived bio-optical properties into coupled bio-optical, physical modelSergey FrolovUCAR
J2.6Use of remote-sensing reflectance to constrain a data assimilating marine biogeochemical model of the Great Barrier ReefEmlyn JonesCSIRO
J2.7The data assimilation approach in the US West Coast Ocean Forecast SystemAlexander KurapovOregon State University
J2.8Regional State Estimation of the Circulation in the Northern Philippine SeaBruce CornuelleScripps Institution of Oceanography, UCSD
J2.9Mesoscale and submesoscale variability in the Luzon Strait: A data-assimilative two-way nested modeling approachJavier Zavala-GarayDepartment of Marine and Coastal Sciences, Rutgers University


J3: Impact of physical DA on coupled physical-biogeochemical models

J3.1Impact of assimilating physical oceanographic data on modeled ecosystem dynamics in the California Current System (15 MB)Christopher EdwardsUC Santa Cruz
J3.2Investigating the impact of physical data assimilation on biogeochemical fields in a global ocean modelDavid FordMet Office
J3.3Assessment of the global hindcast and real-time biogeochemical systems designed at Mercator Ocean: discussion on the impact of physical data assimilationCoralie PerrucheMercator-Ocean
J3.4Investigating the impacts of assimilating physical data and biological data jointly versus individually on ocean ecosystem dynamicsLiuqian YuDepartment of Oceanography, Dalhousie University


D1: Observation impact and sensitivity

D1.1Observation Impacts on Resolved Climate VariabilityAndrew MooreUC Santa Cruz
D1.2Inter-comparison of increments from multiple GOV systems using a set of idealised observationsJennifer WatersMet Office


D2: Model error and bias

D2.1Using temporally averaged data assimilation increments to understand biases in GOV model and data assimilation systems (9.5 MB)Daniel LeaMet Office


D3: Hybrid data assimilation

D3.1Developments in ensemble-variational data assimilation for the global oceanAnthony WeaverCERFACS
D3.2Error Covariance Estimates - A View Toward Hybrid DAAndrew MooreUC Santa Cruz
D3.3A Hybrid Variational-Ensemble data assimilation scheme with systematic error correction for limited area ocean modelPaolo OddoCMRE


D4: Error covariance modelling

D4.1Impact of the Background error Covariance Matrix formulation in the Copernicus Marine ServiceJenny PistoiaINGV
D4.2Modelling forecast error statistics in the Mercator ocean and sea-ice reanalysis systemCharles-Emmanuel TestutMercator-ocean
D4.3Handling boundaries with the recursive filterIsablle MirouzeCMCC foundation
D4.4Assimilating sparse historical data using large scale EOF error covariancesDaniel LeaMet Office


M1: Fisheries outreach session

M3.1Development of a Harmful Algal Bloom Forecast System for Coastal CaliforniaClarissa AndersonUC Santa Cruz
M3.2Predicting Toxic Algal Blooms: Can We Move From Weather Forecasts to Seasonal Forecasts? (6.1 MB)Raphael KudelaUniversity of California Santa Cruz
M3.3Operational Oceanography for Shellfish Aquaculture in a Changing Ocean: meeting needs through IOOSJan NewtonUniversity of Washington/NANOOS
M3.4Forecasting bycatch and ship strike risk, EcoCast and WhaleWatch for dynamic ocean management - NOT PUBLICLY AVAILBALE  please contact Elliott Hazen if you have any questionsElliott HazenNOAA SWFSC
M3.5From physics to fish to apex predators: A fully coupled ecosystem model framework for the California Current SystemJerome FiechterUC Santa Cruz
M3.6Tuna Stock Assessment Support SystemZach SiegristUniversity of Southern California




P.1Weak Constraint 4-Dimensional Variational Data Assimilation in a model of the California Current SystemWilliam CrawfordUC Santa Cruz
P.2Implications of ocean color and biological heating in a global ocean modeling framework: A modeling studyHae-Cheol KimIMSG at NCEP/NWS/NOAA
P.3High Resolution North Western Pacific Prediction System applying Ensemble Optimal InterpolationYoung Ho KimKorea Institute of Ocean Science & Technology
P.4An update on progress with coupled ocean/atmosphere/sea-ice/land data assimilation at the UK Met OfficeDaniel LeaMet Office
P.5Toward the assimilation of biogeochemical data in the CMEMS BIOMER coupled physical-biogeochemical operational systemJulien LamourouxMercator-Ocean