A first approximation for the description of these fluxes is generated by WRF-VPRM (Weather and Research Forecasting - Vegetation Photosynthesis and Respiration Model) and afterwards they are refined by using inverse modeling. For both steps it is required an optimal representation of atmospheric conditions. For WRF-VPRM, WRF provide meteorological input to run VPRM module, which estimates CO2 fluxes that will be distributed spatial and temporal as a passive tracer (Ahmadov et al., 2007). By the other hand, the confidence and quality of inverse model results are highly dependent on model atmospheric transport representation (Pillai et al. 2012).
As urban characteristic affects atmospheric conditions (e.g. heat island), it’s important that atmospheric models have a reliable information of urban features with high spatial resolution. WUDAPT database by using Local Climate Classification (Stewart & Oke, 2012), has the potential to improve atmospheric simulations at urban scale for cities with lack of information of land cover and land use type.
We run a three domain simulation with 25 km, 5km and 1 km of grid resolution respectively. For the finest domain we test WUDAPT information against a default case where it’s used WRF urban data, and evaluate how this modification affects meteorological parameters simulation such as temperature at 2m, relative humidity and wind speed and direction and finally how it will affect fluxes estimation. Physics configuration is based in Vara-Vela et al. (2015). The results are being analyzed and will be presented.
(*This abstract is preferred to be submitted to the special WUDAPT session)
Keywords: CO2, WRF-VPRM, World Urban Database and Access Portal Tools (WUDAPT), Metropolitan Area of Sao Paulo
Ahmadov, R. et al., 2007. Mesoscale covariance of transport and CO 2 fluxes: Evidence from observations and simulations using the WRF-VPRM coupled atmosphere-biosphere model. Journal of Geophysical Research, 112(D22), p.D22107. Available at: http://doi.wiley.com/10.1029/2007JD008552.
Pillai, D. et al., 2012. Comparing Lagrangian and Eulerian models for CO2 transport – a step towards Bayesian inverse modeling using WRF/STILT-VPRM. Atmospheric Chemistry and Physics, 12(19), pp.8979–8991. Available at: http://www.atmos-chem-phys.net/12/8979/2012/.
Stewart, I.D. & Oke, T.R., 2012. Local climate zones for urban temperature studies. Bulletin of the American Meteorological Society, 93(12), pp.1879–1900.
Vara-Vela, a. et al., 2015. Impact of vehicular emissions on the formation of fine particles in the Sao Paulo Metropolitan Area: a numerical study with the WRF-Chem model. Atmospheric Chemistry and Physics Discussions, 15(10), pp.14171–14219. Available at: http://www.atmos-chem-phys-discuss.net/15/14171/2015/.