[1] We developed a modeling system which combines a mesoscale meteorological model, the Weather Research and Forecasting (WRF) model, with a diagnostic biospheric model, the Vegetation Photosynthesis and Respiration (VPRM). The WRF-VPRM modeling system was designed to realistically simulate high-resolution atmospheric CO 2 concentration fields. In the system, WRF takes into account anthropogenic and biospheric CO 2 fluxes and realistic initial and boundary conditions for CO 2 from a global model. The system uses several ''tagged'' tracers for CO 2 fields from different sources. VPRM uses meteorological fields from WRF and high-resolution satellite indices to simulate biospheric CO 2 fluxes with realistic spatiotemporal patterns. Here we present results from the application of the model for interpretation of measurements made within the CarboEurope Regional Experiment Strategy (CERES). Simulated fields of meteorological variables and CO 2 were compared against ground-based and airborne observations. In particular, the characterization by aircraft measurements turned out to be crucial for the model evaluation. The comparison revealed that the model is able to capture the main observed features in the CO 2 distribution reasonably well. The simulations showed that daytime CO 2 measurements made at coastal stations can be strongly affected by land breeze and subsequent sea breeze transport of CO 2 respired from the vegetation during the previous night, which can lead to wrong estimates when such data are used in inverse studies. The results also show that WRF-VPRM is an effective modeling tool for addressing the near-field variability of CO 2 fluxes and concentrations for observing stations around the globe.Citation: Ahmadov, R., C. Gerbig, R. Kretschmer, S. Koerner, B. Neininger, A. J. Dolman, and C. Sarrat (2007), Mesoscale covariance of transport and CO 2 fluxes: Evidence from observations and simulations using the WRF-VPRM coupled atmospherebiosphere model,

Abstract. In order to better understand the effects that mesoscale transport has on atmospheric CO 2 distributions, we have used the atmospheric WRF model coupled to the diagnostic biospheric model VPRM, which provides high resolution biospheric CO 2 fluxes based on MODIS satellite indices. We have run WRF-VPRM for the period from 16 May to 15 June in 2005 covering the intensive period of the CERES experiment, using the CO 2 fields from the global model LMDZ for initialization and lateral boundary conditions. The comparison of modeled CO 2 concentration time series against observations at the Biscarosse tower and against output from two global models -LMDZ and TM3 -clearly reveals that WRF-VPRM can capture the measured CO 2 signal much better than the global models with lower resolution. Also the diurnal variability of the atmospheric CO 2 field caused by recirculation of nighttime respired CO 2 is simulated by WRF-VRPM reasonably well. Analysis of the nighttime data indicates that with high resolution modeling tools such as WRF-VPRM a large fraction of the time periods that are impossible to utilize in global models, can be used quantitatively and may help to constrain respiratory fluxes. The paper concludes that we need to utilize a highresolution model such as WRF-VPRM to use continental observations of CO 2 concentration data with more spatial and temporal coverage and to link them to the global inversion models.

Abstract. Accurate simulation of the spatial and temporal variability of tracer mixing ratios over complex terrain is challenging, but essential in order to utilize measurements made in complex orography (e.g. mountain and coastal sites) in an atmospheric inverse framework to better estimate regional fluxes of these trace gases. This study investigates the ability of high-resolution modeling tools to simulate meteorological and CO 2 fields around Ochsenkopf tall tower, situated in Fichtelgebirge mountain range-Germany (1022 m a.s.l.; 50 • 1 48" N, 11 • 48 30" E). We used tower measurements made at different heights for different seasons together with the measurements from an aircraft campaign. Two tracer transport models -WRF (Eulerian based) and STILT (Lagrangian based), both with a 2 km horizontal resolution -are used together with the satellite-based biospheric model VPRM to simulate the distribution of atmospheric CO 2 concentration over Ochsenkopf. The results suggest that the high-resolution models can capture diurnal, seasonal and synoptic variability of observed mixing ratios much better than coarse global models. The effects of mesoscale transports such as mountain-valley circulations and mountain-wave activities on atmospheric CO 2 distributions are reproduced remarkably well in the high-resolution models. With this study, we emphasize the potential of using high-resolution models in the context of inverse modeling frameworks to utilize measurements provided from mountain or complex terrain sites.

Abstract.One of the dominant uncertainties in inverse estimates of regional CO 2 surface-atmosphere fluxes is related to model errors in vertical transport within the planetary boundary layer (PBL). In this study we present the results from a synthetic experiment using the atmospheric model WRF-VPRM to realistically simulate transport of CO 2 for large parts of the European continent at 10 km spatial resolution. To elucidate the impact of vertical mixing error on modeled CO 2 mixing ratios we simulated a month during the growing season (August 2006) with different commonly used parameterizations of the PBL (Mellor-Yamada-Janjić (MYJ) and Yonsei-University (YSU) scheme). To isolate the effect of transport errors we prescribed the same CO 2 surface fluxes for both simulations. Differences in simulated CO 2 mixing ratios (model bias) were on the order of 3 ppm during daytime with larger values at night. We present a simple method to reduce this bias by 70-80 % when the true height of the mixed layer is known.

Abstract. Satellite retrievals for column CO 2 with better spatial and temporal sampling are expected to improve the current surface flux estimates of CO 2 via inverse techniques. However, the spatial scale mismatch between remotely sensed CO 2 and current generation inverse models can induce representation errors, which can cause systematic biases in flux estimates. This study is focused on estimating these representation errors associated with utilization of satellite measurements in global models with a horizontal resolution of about 1 degree or less. For this we used simulated CO 2 from the high resolution modeling framework WRF-VPRM, which links CO 2 fluxes from a diagnostic biosphere model to a weather forecasting model at 10×10 km 2 horizontal resolution. Sub-grid variability of column averaged CO 2 , i.e. the variability not resolved by global models, reached up to 1.2 ppm with a median value of 0.4 ppm. Statistical analysis of the simulation results indicate that orography plays an important role. Using sub-grid variability of orography and CO 2 fluxes as well as resolved mixing ratio of CO 2 , a linear model can be formulated that could explain about 50% of the spatial patterns in the systematic (bias or correlated error) component of representation error in column and near-surface CO 2 during day-and night-times. These findings give hints for a parameterization of representation error which would allow for the representation error to taken into account in inverse models or data assimilation systems.