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Data Assimilation Education Forum Part I: Overview of Data Assimilation

Data Assimilation Education Forum Part I: Overview of Data Assimilation. Challenges and practical applications of data assimilation in numerical weather prediction. January 21, 2008 presented by Stephen Lord Director, Environmental Modeling Center NCEP/NWS/NOAA. WHY Data Assimilation.

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Data Assimilation Education Forum Part I: Overview of Data Assimilation

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  1. Data Assimilation Education ForumPart I: Overview of Data Assimilation Challenges and practical applications of data assimilation in numerical weather prediction January 21, 2008 presented by Stephen Lord Director, Environmental Modeling CenterNCEP/NWS/NOAA

  2. WHY Data Assimilation • Data assimilation brings together all available information to make the best possible estimate of: • The atmospheric state • The initial conditions to a model which will produce the best forecast.

  3. Data Assimilation Information Sources • Observations • Background (forecast) • Dynamics (e.g., balances between variables) • Physical constraints (e.g., q > 0) • Statistics • Climatology

  4. Atmospheric analysis problem (theoretical) J = Jb + Jo + Jc J = (x-xb)TBx-1(x-xb) + (K(x)-O)T(E+F)-1(K(x)-O) + JC J = Fit to background + Fit to observations + constraints x = Analysis xb = Background Bx = Background error covariance K = Forward model (nonlinear) O = Observations E+F = R = Instrument error + Representativeness error JC = Constraint term

  5. Data Assimilation Techniques

  6. Data Assimilation Development Strategy (1) • Three closely related efforts • Develop Situation-Dependent Background Errors (SDBE) and Simplified 4D-Var (S4DV) • “Classical” 4D-Var (C4DV) • Ensemble Data Assimilation (EnsDA) • Partners • NCEP/EMC • NASA/GSFC/GMAO • THORPEX consortium (TC) • NOAA/ESRL • CIRES • U. Maryland • U. Washington • NCAR

  7. Data Assimilation Development Strategy (2)

  8. NCEP Data Assimilation (1) • 3d-var system: Gridpoint Statistical Interpolation (GSI) • 19 million gridpoints (768x386x64) • 7 analysis variables [T, Q, Ps, wind (2), ozone, cloud water] • 28 minutes • 160 IBM Power 5 processors

  9. NCEP Data Assimilation (2)

  10. NCEP Data Assimilation (3) • Plans • Implement FOTO – Spring 2008 • Collaborate with GMAO to work on 4d-var system (if resources available) • Add new observations – Summer 2008 (or earlier) • ASCAT – surface winds • NOAA-18 ozone • SSM/IS – microwave sounding radiances • IASI – European advanced IR sounder

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