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GEOS-Chem Adjoint: construction and long-term maintainability

GEOS-Chem Adjoint: construction and long-term maintainability. A. Sandu , K. Singh: Virginia Tech D. Henze: Caltech K. Bowman: JPL. Adjoints enable sensitivity analysis and information feedback loops between GEOS-Chem and observations. Transport Meteorology. Optimal analysis state.

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GEOS-Chem Adjoint: construction and long-term maintainability

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  1. GEOS-Chem Adjoint: construction and long-term maintainability A. Sandu, K. Singh: Virginia Tech D. Henze: Caltech K. Bowman: JPL

  2. Adjoints enable sensitivity analysis and information feedback loops between GEOS-Chem and observations Transport Meteorology Optimal analysis state Chemical kinetics Observations GEOS-Chem 4D-Var Data Assimilation Aerosols Targeted Observ. Improved: • forecasts • science • field experiment design • models • emission estimates Emissions April 11, 2007

  3. The sensitivity can be obtained either via the direct chain rule (TLM/DDM) or via its transpose (ADJ) TLM (DDM) = source-oriented approach ADJ = receptor-oriented approach April 11, 2007

  4. Adjoint variables describe areas of influence where changes in conc. impact the receptor (observations) 48 hrs areas of influence for a hypothetical TES sequence of observations April 11, 2007

  5. Adjoints can provide the sensitivities of ozone observations with respect to NOx emissions 1 week sensitivities of TES O3 w.r.t. athropogenic and lightning NOx emissions April 11, 2007

  6. Data assimilation combines multiple sources of information to estimate concentrations, emissions, etc Model (encapsulating knowledge on the physics, chemistry, thermodynamics, etc) Background (encapsulating best a-priori knowledge of the state) Observations (encapsulating new information about reality) Optimization uses gradients obtained via adjoint modeling April 11, 2007

  7. Assimilation of ICARTT data adjusts O3 predictions considerably at 4pm EDT on July 20, 2004 Observations: circles, color coded by O3 mixing ratio Surface O3 (forecast) Surface O3 (analysis) [Chai et al., 2006] April 11, 2007

  8. Assimilation of ozonesonde data and of DC-8 lidar observations for July 20, 2004 [Chai et al., 2006] April 11, 2007

  9. Targeted observations are deployed to areas where they provide maximum of information Verification: Korea, ground O3 0 GMT, Mar/4/2001 (criterion based on SVs) O3 HCHO NO2 [Liao and Sandu, 2005] April 11, 2007

  10. Construction of GEOS-Chem Adjoint is non-trivial Transport (continuous) Optimal analysis state Chemical Kinetics (KPP) Observation Operators (av. Kernels, intp.) GEOS-Chem Data Assimilation Aerosols (TAMC) Targeted Observ. Improved: • forecasts • science • field experiment design • models • emission estimates Emissions April 11, 2007

  11. K P P KPP automatically generates simulation and direct/adjoint sensitivity code for chemistry Simulation code Chemical mechanism SUBROUTINE FunVar ( V, F, RCT, DV )INCLUDE 'small.h'REAL*8 V(NVAR), F(NFIX) REAL*8 RCT(NREACT), DV(NVAR)C A - rate for each equationREAL*8 A(NREACT)C Computation of equation rates A(1) = RCT(1)*F(2) A(2) = RCT(2)*V(2)*F(2) A(3) = RCT(3)*V(3) A(4) = RCT(4)*V(2)*V(3) A(5) = RCT(5)*V(3) A(6) = RCT(6)*V(1)*F(1) A(7) = RCT(7)*V(1)*V(3) A(8) = RCT(8)*V(3)*V(4) A(9) = RCT(9)*V(2)*V(5) A(10) = RCT(10)*V(5)C Aggregate function DV(1) = A(5)-A(6)-A(7) DV(2) = 2*A(1)-A(2)+A(3)-A(4)+A(6)-&A(9)+A(10) DV(3) = A(2)-A(3)-A(4)-A(5)-A(7)-A(8) DV(4) = -A(8)+A(9)+A(10) DV(5) = A(8)-A(9)-A(10)END #INCLUDE atoms #DEFVAR O = O; O1D = O; O3 = O + O + O; NO = N + O; NO2 = N + O + O; #DEFFIX O2 = O + O; M = ignore; #EQUATIONS{ Small Stratospheric }O2 + hv = 2O : 2.6E-10*S; O + O2 = O3 : 8.0E-17; O3 + hv = O + O2 : 6.1E-04*S; O + O3 = 2O2 : 1.5E-15; O3 + hv = O1D + O2 : 1.0E-03*S; O1D + M = O + M : 7.1E-11; O1D + O3 = 2O2 : 1.2E-10; NO + O3 = NO2 + O2 : 6.0E-15; NO2 + O = NO + O2 : 1.0E-11; NO2 + hv = NO + O : 1.2E-02*S; [Damian et.al., 1996; Sandu et.al., 2002] April 11, 2007

  12. KPP has been tested in GEOS-Chem (Henze) April 11, 2007

  13. GEOS-Chem Adjoint History • Offline aerosol (D. Henze, Caltech, 2005) • TAF (M. Kopacz, Harvard, 2005) • Full chemistry (D. Henze, Caltech) Wed. 1:45 • v6-02-05, GEOS-3 met, gas-phase, aerosols • Tagged CO, CO2 (M. Kopacz, Harvard) Thur. 12:15 • Black Carbon (Q. Li, JPL) Wed. 2:30 Goal: develop a standardized GEOS-Chem adjoint model (VT, JPL, Harvard, Caltech, Toronto …) April 11, 2007

  14. Towards a standardized GEOS-Chem adjoint model • Adjoints to use GEOS-4/GEOS-5 met • Update from GEOS-Chem v6 to v7 • Adjoints of different convection models • Better integrate Kpp with GEOS-Chem. Develop ability to read the same chemical input files directly. • Observation operators for specific satellites (TES, MOPPITT, OMI) • Different adjoints for different processes (continuous/discrete, full/simplified). See algorithmic issues. • Checkpoints: how often? After each process? Optimal log storage size? • Optimization procedures • Parallelization of adjoint over MPI April 11, 2007

  15. Keeping the 4D-Var/adjoint up-to-date when GEOS-Chem is continuously evolving Community can help: • Encapsulate each science process, and have it communicate with the model through interfaces. Derivatives should not depend on global variables or on I/O. (e.g., deposition) • Avoid large nonlinearities and points of non-differentiability in the forward model if at all possible (e.g., limiters) • Allow simplified versions of science processes that will result in simplified adjoints (e.g., simplified advection adjoint) • Prepare for automatic adjoint code generation: • Implementation should allow the use of automatic differentiation without other code transformations. (Which AD engine of choice? TAMC, TAF, OpenAD? Full F90 support?) • KPP for the automatic implementation of the direct/adjoint chemistry April 11, 2007

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