New Approaches to Data Assimilation THORPEX Pacific Predictability Experiment workshop 6 June 2005 Greg Hakim1 & Pierre Gauthier2 1University of Washington 2Meteorological Service of Canada Contributors: Jeff Anderson, John Derber, Brian Etherton, Geoff DiMego, Josh Hacker, Tom Hamill, Jim Hansen, Steve Lord, Sharan Majumdar, Michael Morgan, Rebecca Morss, Carolyn Reynolds, Chris Snyder, & Istvan Szunyogh.

Hakim & Gauthier---New Approaches to Data Assimilation Goals & Background How can THORPEX accelerate progress in DA? What DA advances would most impact THORPEX? Answer depends upon whether THORPEX aims for: incremental improvements to existing systems OR forward-looking research to next-generation systems? Main issues: model error. targeted data assimilation. observing network design. needs for OSSEs/OSEs and field campaigns. 6 June 2005 Hakim & Gauthier---New Approaches to Data Assimilation

Research & Operational Communities Complementary strengths and agendas. THORPEX provides an opportunity for greater interaction between these two communities: faster progress 6 June 2005 Hakim & Gauthier---New Approaches to Data Assimilation

Strengths / Role / Interests of the Research Community basic science new DA techniques. predictability DA as a tool for dynamics. idealized testing & rapid prototyping (e.g. DART). pseudo-operational DA on small scale. interest mainly in ensemble filters 3dvar (mainly for testing new ob types) 4dvar too hard for academic community? 6 June 2005 Hakim & Gauthier---New Approaches to Data Assimilation

Strengths / Role / Interests of the operational community controlled, incremental changes to operational systems. obs gathering, quality control, and error specification. forward operators. satellite radiance assimilation. supercomputing facilities. OSE/OSSEs with operational systems. Main interest: 4dvar minority interest in ensemble filters. 6 June 2005 Hakim & Gauthier---New Approaches to Data Assimilation

Generic DA Future Issues multi-scale obs & increments. convective scale ---> planetary scale. model error. observation data deluge. automatic data selection "crucial" for future. non-Gaussian errors. coupled DA; chemistry DA. 6 June 2005 Hakim & Gauthier---New Approaches to Data Assimilation

Hakim & Gauthier---New Approaches to Data Assimilation Ensemble Filters  Analyses Forecasts Analyses model runs observation assimilation Essential aspect: ensemble estimate of background error covariance matrix 6 June 2005 Hakim & Gauthier---New Approaches to Data Assimilation

MSLP ob: 500 hPa Analysis Increment 3DVAR EnKF 6 June 2005 Hakim & Gauthier---New Approaches to Data Assimilation

Mesoscale Example: cov(|V|, qrain) 6 June 2005 Hakim & Gauthier---New Approaches to Data Assimilation

Hakim & Gauthier---New Approaches to Data Assimilation 4dvar background analysis observations t0 t Essential aspect: fits observations over a time period that satisfy model dynamics. 6 June 2005 Hakim & Gauthier---New Approaches to Data Assimilation

Ensemble Filter Issues model error: background. sampling error. balance. serial obs. processing some solutions exist. sequential update problematic for predominantly asynchronous obs. tighter coupling at expense of modularity? filter wrapping in e.g. Python. 6 June 2005 Hakim & Gauthier---New Approaches to Data Assimilation

Hakim & Gauthier---New Approaches to Data Assimilation 4DVAR Issues model error: background & obs estimates. adjoint model linearity (multi-scale). ~fixed background errors (multi-scale). initial time. deterministic analysis. NCEP: cost-effective 4dvar limited run-time availability. “situation dependent” background errors. 6 June 2005 Hakim & Gauthier---New Approaches to Data Assimilation

4DVAR-Ensemble Filter Fusion Ensemble background errors in 4dvar: ETKF + 4dvar update for mean. 4dvar update on members. EnKF/3DVAR hybrids. Kalman smoothers. “Analysis of record” 6 June 2005 Hakim & Gauthier---New Approaches to Data Assimilation

Key DA Research & Applications [Operational systems]. Model error. Targeted data assimilation. Dynamics. Observing network design. 6 June 2005 Hakim & Gauthier---New Approaches to Data Assimilation

Hakim & Gauthier---New Approaches to Data Assimilation Model Error model calibration. e.g. parameter estimation. systematic, conditional, development. new changes conditioned on existing model structure. use DA to construct frameworks. e.g. state-dependent model error. non-Gaussian errors. 6 June 2005 Hakim & Gauthier---New Approaches to Data Assimilation

Targeted Data Assimilation metric-dependent filtered obs stream. not just satellite data thinning! e.g. ob usage depends on forecast lead time. e.g. ob usage depends on forecast metric. required for THORPEX wide-ranging time/space scales? 6 June 2005 Hakim & Gauthier---New Approaches to Data Assimilation

Hakim & Gauthier---New Approaches to Data Assimilation Dynamics scale interactions. predictability error growth. errors conditioned on flow structure. new tool for dynamics. e.g. ensemble potential vorticity inversion. balance equations ensemble inversion recovered divergence 6 June 2005 Hakim & Gauthier---New Approaches to Data Assimilation

Observing Network Design transition the “organically grown” network. where to move old obs and/or when to use. e.g. radiosondes. new fixed optimal obs sites & types. basic science and practical aspects. entanglement with DA approach & norms try many. 6 June 2005 Hakim & Gauthier---New Approaches to Data Assimilation

Hakim & Gauthier---New Approaches to Data Assimilation Summary THORPEX and DA need each other. basic science & operational advances. Ensemble filters, 4dvar, fusion. Pacific campaign Model error. best obs for state-dependent calibration. Targeted data assimilation. Oversampling for OSEs. 6 June 2005 Hakim & Gauthier---New Approaches to Data Assimilation