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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.

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Presentation on theme: "Claire Sarrat, Joël Noilhan, Pierre Lacarrère, Sylvie Donier et al. Atmospheric CO 2 modeling at the regional scale: A bottom – up approach applied to."— Presentation transcript:

1 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)

2 OUTLINE I Objectives of CERES and meso scale modeling II Atmospheric CO 2 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 : to establish a regional budget of CO 2 : 10 surface flux sites (energy, water and CO 2 ) on different types of land cover (forest, vineyards, maize, wheat, rapeseed, beans, grassland, bare soil) Atmospheric Boundary Layer (ABL) data: RS, aircrafts, radar UHF…  Experiment in Les Landes, S-W of France: - from may-16 to june-25 2005 - 21 IOP days Objectives of the CERES campaign (Dolman et al., BAMS, 2006) I Objectives II Atmospheric CO 2 modeling III Intercomparisons of models CO 2 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…)

4 Objectives of the modeling activity  CO 2 regional budget using a meteorological meso-scale model Meso-NH and the CERES data: - Test the model ability to simulate the strong surface heterogeneities - Simulate the CO 2 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) I Objectives II Atmospheric CO 2 modeling III Intercomparisons of models ISBA-A-g s Meso-NH LE, H, Rn, W, Ts… Atmospheric [CO 2 ] Anthropogenic Sea Meteorological Model Surface Lafore et al., 98 Noilhan et al. 89 Calvet et al., 98 CO 2 Fluxes

5 Atmospheric CO 2 modeling Meso-NH configuration I Objectives II Atmospheric CO 2 modeling III Intercomparisons of models Large domain : France Horizontal resolution : 10 km Small domain: CERES domain Horizontal resolution : 2 km   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 900 km 320 km Altitude (m)

6 CO2 concentrations (ppm) may-27 9HUTC Atmospheric CO 2 modeling may–27 Sea breeze effects (Sarrat et al., JGR, 2006) I Objectives II Atmospheric CO 2 modeling III Intercomparisons of models S-W S-E CO2 concentrations (ppm) may-27 14HUTC FOREST AREA AGRICUL. AREA S-ES-W Wind direction FOREST AREA AGRICUL. AREA CO2 concentrations

7 Atmospheric CO 2 modelling may–27 Boundary layer heterogeneity OCEANFOREST AREA AGRICUL. AREA Simulated vertical cross section of the mixing ratio at 14UTC Zi = 900m Zi = 1600m Forest Crops obs model obs model

8 Atmospheric CO 2 modelling : may–27 A scheme of main processes

9 Atmospheric CO 2 modelling : june-06 Lagrangian experiment N-W I Objectives II Atmospheric CO 2 modeling III Intercomparisons of models

10 Atmospheric CO 2 modelling : june-06 Lagrangian experiment : Budget calculation N-W 6 UTC 15 UTC CO 2 turb. flux CO 2 advection CO 2 variation

11 Conclusion (1) : Atmospheric CO2 modeling with Meso-NH  The CERES database is well adapted to study the CO 2 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 CO 2 concentrations in the ABL  The atmospheric CO 2 budgeting using meso-scale modelling allows to estimate the contribution of advection and turbulent transport processes on the spatio-temporal variation of the regional CO 2 concentration

12 Intercomparison of 5 meteorological 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  CO 2 anthropogenic emissions at 10 km resolution from Stuttgart Univ.  2 golden days of the CERES campaign: may-27 and june-06 2005 I Objectives II Atmospheric CO 2 modeling III Intercomparisons of models

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

14 Intercomparison of 5 meteorological models: Atmospheric Boundary Layer  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 RS june-06 05H FOREST Potential temp RS june-06 14H FOREST obs Potential temp Z (m) night day

15 Intercomparison of 5 meteorological models Vertical profiles of CO 2 concentrations (may-27) morning vertical profile afternoon vertical profile Crops ABL height vs CO 2 concentrations:  the CO 2 concentrations decrease when the ABL is developing due to vertical mixing and assimilation  the CO 2 depletion is higher over the crops area whereas the vertical mixing in lower than over the forest  Generally, the models reproduce the observed trend. Forest zi CO2 concentrations zi CO2 concentrations

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 CO 2 concentrations simulated in the ABL present a correct evolution between the morning and the afternoon profiles.

17 Atmospheric CO 2 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   CO 2 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 june-06 Sensitivity to initial conditions Intercomparison of 5 meteorological models Vertical profiles of CO 2 concentrations

19 Intercomparison of 5 meteorological models Aircraft fluxes Crops Forest  The observed aircraft fluxes over forest and crops present large horizontal variations  For MNH-CNRM and RAMS-ALTE CO 2 fluxes look consistents  For MNH-CNRM the LE fluxes are overestimated over crops because of an overestimation of the LAI June-06, 9-11UTC BOWEN RATIOFORCROP OBS 1.7 MNH-CNRM 1.5.7 RAMS-AMVU.8.7 RAMS-ALTE 1.71.3 RAMS-CEAM 2.31


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