1. Page 1© Crown copyright 2004 Data Assimilation at the Met Office Hadley Centre, Met Office, Exeter.CTCD Workshop. 8 th Nov, 2005 Chris Jones

2. Page 2© Crown copyright 2004 Outline  Intro  2 interpretations of DA  Current DA at the Met Office  Plans/hopes for future

3. Page 3© Crown copyright 2004 Met Office Data Assimilation  The Met Office has a long history of data assimilation in an operational (NWP) framework  Currently running operational 4D-Var scheme.  DA now appealing to a much wider audience  Ocean forecasting  Seasonal/decadal forecasting  Carbon cycle/ecosystem research  Keen to make most of existing expertise internal and external to Met Office  Central part of CarboEurope  Not my area of expertise, despite a chequered past…

4. Page 4© Crown copyright 2004 What does DA mean?  2 different interpretations of the phrase “data assimilation”  i. Conventional, “NWP” style:  Model formulation is fixed  Uses “current” or “new” data  Constrains model prognostic variables  Product is  Analysis – best estimate of snapshot of reality  Initialsed state from which to produce best forecast  ii. Parameter optimisation:  A form of what used to be called “tuning” (which was highly subjective)  Generally uses “historical” data or climatology  Multiple model runs to constrain internal parameters  Product is the model itself (optimised)

5. Page 5© Crown copyright 2004 Data Assimilation applications at the Met Office  Climate/Carbon cycle related data assimilation does already exist at the Met Office.  1. “DePreSys” (Decadal Prediction System)  Run climate model, nudging sea surface temperature and salinity to observations  Assimilate atmospheric variables too (better first season, better surface fluxes into ocean)  Run climate model for next 10 years as a forecast  Hindcasts show some skill relative to persistence

6. Page 6© Crown copyright 2004 Data Assimilation applications at the Met Office  Climate/Carbon cycle related data assimilation does already exist at the Met Office.  2. NCOF/CASIX ocean biogeochemistry modelling  Run ocean carbon cycle model (HadOCC) in operational (“FOAM”) hi-res ocean model.  Assimilate physical variables (in-situ + satellite)  Drive with atmos fluxes from NWP model  produces realistic ocean state  Allows simulation of ocean pCO2, and air-sea CO2 flux  Aim to also assimilate ocean colour obs from satellite (as a proxy for chlorophyll concentration)  Better constraint on biological variables

7. Page 7© Crown copyright 2004 pCO2 in North Atlantic Climate model (no DA) FOAM (HadOCC + physical DA) obs Better ocean simulation (through DA) improves C-cycle simulation

8. Page 8© Crown copyright 2004 Attribution of mechanisms  Given confidence in simulation we can learn from the mechanisms in the model  Spring draw-down of pCO2 is biologically driven.  Rest of year is physically driven (mainly response to SSTs)

9. Page 9© Crown copyright 2004 Data Assimilation applications at the Met Office  Climate/Carbon cycle related data assimilation does already exist at the Met Office.  3. CAMELS (Carbon Assimilation and Modelling of the European Land Surface)  Optimisation of terrestrial carbon cycle models using observed carbon cycle data  Results promising to date  Will feed into integration component of CarboEurope

10. Page 10© Crown copyright 2004 Prior and optimised diurnal cycle at Bray in Orchidee: means over 1997 Growing Season (days 195-216) Black: data with uncertainties Green: prior Red: optimized

11. Page 11© Crown copyright 2004 BETHY simulated carbon flux

12. Page 12© Crown copyright 2004 A success… and a caveat  TRIFFID modelled NEP saturates very quickly with light levels  Can’t represent diurnal cycle of productivity  Requires better treatment of light penetration into canopy

13. Page 13© Crown copyright 2004  “light mod” allows better treatment  Parameters optimally determined using observed data from Loobos  Original model could be optimised too  Get decent looking performance  Parameters outside “physical” range  Danger of optimising deficient model… A success… and a caveat

14. Page 14© Crown copyright 2004 Future Plans: CarboEurope-IP  CarboEurope aims to, “ understand and quantify the present terrestrial carbon balance of Europe”  4 components.  “continental integration”  Make use of all different data streams to constrain models  Make use of models to give full coverage of European land surface Essentially a Data Assimilation problem