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Using PALM to integrate variational data assimilation algorithms with OPA ECMWF, 29 june 2005, Reading. Nicolas Daget CERFACS, Toulouse
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Using PALM to integrate variational data assimilation algorithms with OPA ECMWF, 29 june 2005, Reading. Nicolas Daget CERFACS, Toulouse.

Mar 28, 2015

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Page 1: Using PALM to integrate variational data assimilation algorithms with OPA ECMWF, 29 june 2005, Reading. Nicolas Daget CERFACS, Toulouse.

Using PALM to integrate variational data assimilation algorithms with OPA

ECMWF, 29 june 2005, Reading.

Nicolas DagetCERFACS, Toulouse

Page 2: Using PALM to integrate variational data assimilation algorithms with OPA ECMWF, 29 june 2005, Reading. Nicolas Daget CERFACS, Toulouse.

Dynamic coupling for parallel programs

Easy and user friendly to set up different assimilation systems

Independence of the components

High performance communications for data exchanges

Components can be launch dynamically

Complete independence between components and the algorithm

Distributed data exchange

Physics and algebraic computations are separated

PALM Philosophy

Algebraic computations can be done by PALM

Page 3: Using PALM to integrate variational data assimilation algorithms with OPA ECMWF, 29 june 2005, Reading. Nicolas Daget CERFACS, Toulouse.

PALM unit

Unit

Inputs

Outputs

Direct communication

Communication with a buffer

Priority

Inside a loop

Branch

Page 4: Using PALM to integrate variational data assimilation algorithms with OPA ECMWF, 29 june 2005, Reading. Nicolas Daget CERFACS, Toulouse.

Data assimilation algorithmsDirect model, tangent model

and adjoint model

Data assimilation

Page 5: Using PALM to integrate variational data assimilation algorithms with OPA ECMWF, 29 june 2005, Reading. Nicolas Daget CERFACS, Toulouse.

3DVAR Shallow Water

Model Read observations

Minimization

Page 6: Using PALM to integrate variational data assimilation algorithms with OPA ECMWF, 29 june 2005, Reading. Nicolas Daget CERFACS, Toulouse.

3DVAR with OPA

In situ temperature only

No background quality control

First prototype

Page 7: Using PALM to integrate variational data assimilation algorithms with OPA ECMWF, 29 june 2005, Reading. Nicolas Daget CERFACS, Toulouse.

3DVAR with OPA

Rea

d O

bser

vatio

nsC

ompu

te f

irst

Jo

Model

Compute first Jb and grad J

Minimizer

Com

pute Jo

Compute Jb and grad J

Page 8: Using PALM to integrate variational data assimilation algorithms with OPA ECMWF, 29 june 2005, Reading. Nicolas Daget CERFACS, Toulouse.

3DVAR with OPA

Read data

H

Initialization of R

1R

Reset variables

THFirst Jo

Page 9: Using PALM to integrate variational data assimilation algorithms with OPA ECMWF, 29 june 2005, Reading. Nicolas Daget CERFACS, Toulouse.

3DVAR with OPA

Read restart file, nit000, nitend, etc

Model initialization (opa.F without step.F)

Tangent model initialization

Model integration (step.F)

Mem

ory shared

Initialization of B

Page 10: Using PALM to integrate variational data assimilation algorithms with OPA ECMWF, 29 june 2005, Reading. Nicolas Daget CERFACS, Toulouse.

3DVAR with OPA

2BT

First grad J

First Jb

First Jo

Put inputs to minimizer

Control vector

2BT

Grad J

Jb2

1

B Put J and grad J

Minimizer : Lanczos algorithm linear equation and eigenvalue solver

Jo

Page 11: Using PALM to integrate variational data assimilation algorithms with OPA ECMWF, 29 june 2005, Reading. Nicolas Daget CERFACS, Toulouse.

3DVAR with OPA

Loop inside minimizer

Loop synchronized

with the minimizer

Page 12: Using PALM to integrate variational data assimilation algorithms with OPA ECMWF, 29 june 2005, Reading. Nicolas Daget CERFACS, Toulouse.

3DVAR with OPA

HTH

-1RJo

Page 13: Using PALM to integrate variational data assimilation algorithms with OPA ECMWF, 29 june 2005, Reading. Nicolas Daget CERFACS, Toulouse.

3DVAR with OPA

Direct Model

Read observation

H

H

HT

R-1

B1/2

BT/2

Minimizer

3DVAR

inner loop

outer loop

First version will come soon

In progress

Page 14: Using PALM to integrate variational data assimilation algorithms with OPA ECMWF, 29 june 2005, Reading. Nicolas Daget CERFACS, Toulouse.

Conclusions

• Hard work to split OPAVAR in units

• Direct, tangent and adjoint model can't be separated

• First 3DVar with OPA8.2 is not yet finished

• Easy to understand and modify algorithms

• Easiest to replace OPA8.2 by NEMO

• No information about optimization