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Claire Sarrat, Joël Noilhan, Pierre Lacarrère, Sylvie Donier et al.

Atmospheric CO 2 modeling at the regional scale: A bottom – up approach applied to the CarboEurope Regional Experiment campaign (CERES). Claire Sarrat, Joël Noilhan, Pierre Lacarrère, Sylvie Donier et al. OUTLINE. I Objectives of CERES and meso scale modeling

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Claire Sarrat, Joël Noilhan, Pierre Lacarrère, Sylvie Donier et al.

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  1. Atmospheric CO2 modeling at the regional scale: A bottom – up approach applied to the CarboEurope Regional Experiment campaign (CERES) Claire Sarrat, Joël Noilhan, Pierre Lacarrère, Sylvie Donier et al.

  2. OUTLINE • I Objectives of CERES and meso scale modeling • II Atmospheric CO2 modeling at the regional scale with Meso-NH • A ‘golden day’ case study: may-27 • A ‘lagrangian experiment’ case study : june-06 • III Intercomparisons of atmospheric meso-scale models

  3. Objectives of the CERES campaign (Dolman et al., BAMS, 2006) I Objectives II Atmospheric CO2 modeling III Intercomparisons of models • Objectives :to establish a regional budget of CO2 : • 10 surface flux sites (energy, water and CO2) on different types of land cover (forest, vineyards, maize, wheat, rapeseed, beans, grassland, bare soil) • Atmospheric Boundary Layer (ABL) data: RS, aircrafts, radar UHF… • CO2 concentrations observations in and above the ABL: Biscarosse, La Cape Sud, Marmande + aircrafts: Piper Aztec, Dimona, Sky Arrow • ‘Flux divergence’ flights • LAI monitoring • Surface and soil properties (Ts, soil water content…) • Experiment in Les Landes, S-W of France: - from may-16 to june-25 2005 - 21 IOP days

  4. Objectives of the modeling activity I Objectives II Atmospheric CO2 modeling III Intercomparisons of models • CO2 regional budgetusing a meteorological meso-scale model Meso-NH and the CERES data: - Test the model ability to simulate the strong surface heterogeneities - Simulate the CO2 transfers at the boundaries: surface – ABL and entrainment at the ABL top • Simulate the complex interactions of CO2, heat and water surface fluxes within a regional model • Simulate correctly the concentrations in the PBL as a necessary condition to retrieve the surface fluxes by inverse modeling (see T. Lauvaux presentation) Surface Meteorological Model LE, H, Rn, W, Ts… Meso-NH ISBA-A-gs CO2 Fluxes Atmospheric [CO2] Anthropogenic Sea Noilhan et al. 89 Calvet et al., 98 Lafore et al., 98

  5. Atmospheric CO2 modelingMeso-NH configuration Altitude (m) 320 km 900 km I Objectives II Atmospheric CO2 modeling III Intercomparisons of models • Nesting 2 ways • Land use: Ecoclimap (Masson et al., 2003) • Initialization and lateral boundaries forcing: ECMWF model • Anthropogenic CO2 emissions from Stuttgart Univ. at 10km resolution Large domain : France Horizontal resolution: 10 km Small domain: CERES domain Horizontal resolution: 2 km

  6. Atmospheric CO2 modeling may–27 Sea breeze effects (Sarrat et al., JGR, 2006) S-E FOREST AREA AGRICUL. AREA AGRICUL. AREA CO2 concentrations Wind direction FOREST AREA S-W S-E I Objectives II Atmospheric CO2 modeling III Intercomparisons of models CO2 concentrations (ppm) may-27 9HUTC CO2 concentrations (ppm) may-27 14HUTC S-W

  7. Atmospheric CO2 modelling may–27 Boundary layer heterogeneity Simulated vertical cross section of the mixing ratio at 14UTC Zi = 1600m Zi = 900m OCEAN FOREST AREA AGRICUL. AREA obs model Forest obs model Crops

  8. Atmospheric CO2 modelling : may–27 A scheme of main processes

  9. Atmospheric CO2 modelling : june-06Lagrangian experiment N-W I Objectives II Atmospheric CO2 modeling III Intercomparisons of models

  10. Atmospheric CO2 modelling : june-06Lagrangian experiment : Budget calculation <CO2> N-W 6 UTC 15 UTC CO2 variation CO2 advection CO2 turb. flux

  11. Conclusion (1) :Atmospheric CO2 modeling with Meso-NH • The CERES database is well adapted to study the CO2 and water budget at the regional scale • The meso-scale dynamical processes such as sea and vegetation breezes have a strong impact on the spatial and temporal variability of CO2 concentrations in the ABL • The atmospheric CO2 budgeting using meso-scale modelling allows to estimate the contribution of advection and turbulent transport processes on the spatio-temporal variation of the regional CO2 concentration

  12. Intercomparison of 5 meteorological models I Objectives II Atmospheric CO2 modeling III Intercomparisons of models • Participation of 5 models: RAMS from Amsterdam Vrije Univ., RAMS from Alterra, RAMS from CEAM, WRF from MPI, Meso-NH from CNRM • Experimental Protocol agreed on: • Domain of simulation at 2km resolution • Initialization and lateral boundaries forcing for meteorological and surface variables with ECMWF model • Land cover by the Ecoclimap database including 61 surface classes, summer crops/winter crops • CO2 anthropogenic emissions at 10 km resolution from Stuttgart Univ. • 2 golden days of the CERES campaign: may-27 and june-06 2005

  13. Intercomparison of 5 meteorological models:Surface fluxes Auradé winter crop Le Bray forest may-27 • Auradé winter crop site is well simulated by all the models RN RN H H • Simulations for Le Bray forest site more difficult for all models • Bsimu[.5, 2] • CO2 flux overestimated due to too high respiration? LE LE SFCO2 SFCO2

  14. Intercomparison of 5 meteorological models:Atmospheric Boundary Layer obs • Most of the models simulate the nocturnal stable ABL and humidity accumulation at low level • At 14H large variation for ABL development : -> 800m RAMS-ALTE ->1500m WRF-MPI day night Z (m) Z (m) Potential temp Potential temp RS june-06 05H FOREST RS june-06 14H FOREST

  15. Intercomparison of 5 meteorological modelsVertical profiles of CO2 concentrations (may-27) Crops afternoon vertical profile morning vertical profile Forest zi zi CO2 concentrations CO2 concentrations • ABL height vs CO2 concentrations: • the CO2 concentrations decrease when the ABL is developing due to vertical mixing and assimilation • the CO2 depletion is higher over the crops area whereas the vertical mixing in lower than over the forest • Generally, the models reproduce the observed trend.

  16. Conclusion (2) :Intercomparison of 5 regional meteorological models • 5 models have simulated two contrasted days of CERES according a similar model configuration • The surface fluxes are easier to simulate over fully developed crops than over the pine forest. The windy june-06 case is better simulated. • The surface CO2 fluxes on the warm may-27 are poorly simulated by most models. • Large discrepancies are observed in the simulation of the ABL development and potential temperature • The CO2 concentrations simulated in the ABL present a correct evolution between the morning and the afternoon profiles.

  17. Atmospheric CO2 modelling Conditions of simulation :  Initialisation of CO2 the day before the simulated day at 18HUTC with a homogeneous vertical profile over the domain of simulations  Meteorological and surface moisture initialisation, lateral boundaries forcing : ECMWF analyses  CO2 anthropogenic emissions from Stuttgart Univ. at 10 km  Land use : Ecoclimap (Masson, 2003, Champeaux et al., 2005) 62 classes of vegetation: Ecoclimap processed from CORINE 2000 and Vegetation NDVI. Anthropogenic emissions interpolated at 2km

  18. Intercomparison of 5 meteorological modelsVertical profiles of CO2 concentrations june-06 Sensitivity to initial conditions

  19. Intercomparison of 5 meteorological modelsAircraft fluxes Forest Crops June-06, 9-11UTC • The observed aircraft fluxes over forest and crops present large horizontal variations • For MNH-CNRM and RAMS-ALTE CO2 fluxes look consistents • For MNH-CNRM the LE fluxes are overestimated over crops because of an overestimation of the LAI

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