geos-chem adjoint: construction and long-term maintainability
DESCRIPTION
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. - PowerPoint PPT PresentationTRANSCRIPT
GEOS-Chem Adjoint: construction and long-term
maintainability
A. Sandu, K. Singh: Virginia TechD. Henze: CaltechK. Bowman: JPL
April 11, 2007
Adjoints enable sensitivity analysis and information feedback loops between GEOS-Chem and observations
Optimal analysis state
Chemical kinetics
Aerosols
GEOS-Chem
TransportMeteorology
Emissions
Observations4D-VarData
Assimilation
Targeted Observ.
Improved:• forecasts• science• field experiment design• models • emission estimates
Improved:• forecasts• science• field experiment design• models • emission estimates
April 11, 2007
The sensitivity can be obtained either via the direct chain rule (TLM/DDM) or via its transpose (ADJ)
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TLM (DDM) = source-oriented approach
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ADJ = receptor-oriented approach
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April 11, 2007
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
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
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)
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Optimization uses gradients obtained via adjoint modeling
April 11, 2007
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
Assimilation of ozonesonde data and of DC-8 lidar observations for July 20, 2004
[Chai et al., 2006]
April 11, 2007
Targeted observations are deployed to areas where they provide maximum of information
1
22max
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(criterion based on SVs)
[Liao and Sandu, 2005]
Verification:Korea, ground O3
0 GMT, Mar/4/2001
O3 NO2 HCHO
April 11, 2007
Construction of GEOS-Chem Adjoint is non-trivial
Optimal analysis state
Chemical Kinetics (KPP)
Transport(continuous)
Emissions
Data Assimilation
Targeted Observ.
Improved:• forecasts• science• field experiment design• models • emission estimates
Improved:• forecasts• science• field experiment design• models • emission estimates
Aerosols (TAMC)
GEOS-Chem
ObservationOperators
(av. Kernels, intp.)
April 11, 2007
KPP automatically generates simulation and
direct/adjoint sensitivity code for chemistry
#INCLUDE atoms
#DEFVARO = O; O1D = O; O3 = O + O + O; NO = N + O; NO2 = N + O + O;
#DEFFIXO2 = 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;
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 equation REAL*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
K P P
[Damian et.al., 1996; Sandu et.al., 2002]
Chemical mechanism Simulation code
April 11, 2007
KPP has been tested in GEOS-Chem (Henze)
April 11, 2007
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
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
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