Abstract
The quantification of CO2 emissions from cities using atmospheric measurements requires accurate knowledge of the atmospheric transport. Complex urban terrains significantly modify surface roughness, augment surface energy budgets, and create heat islands, all of which lead to lower horizontal winds and enhanced convection over urban areas. The question remains whether these processes should be included in atmospheric transport models that are used for city scale CO2 inversion, and whether they need to be tailored on a city basis. In this study, we use the WRF model over Paris to address the following research question: does WRF runs at a 3 km resolution, including urban effects and the assimilation of local weather data, perform better than ECMWF forecasts that give fields at 16 km resolution? The analysis of model performances focuses on three variables: air temperature, wind and the planetary boundary layer (PBL) height. The results show that the use of objective analysis and nudging tools are required to obtain good agreements between WRF simulated fields with observations. Surface temperature is well reproduced by both WRF and ECMWF forecasts, with correlation coefficients with hourly observations larger than 0.92 and MBEs within 1°C over one month. Wind speed correlations with hourly observations are similar for WRF (range 0.76~0.85 across stations) and ECMWF (0.79~0.84), but the associated RMSEs and MBEs are better for ECMWF. Conversely, WRF outperforms ECMWF forecasts for its description of wind direction, horizontal and vertical gradients. Sensitivity tests with different WRF physics schemes show that the wind speed and the PBL height are strongly influenced by PBL schemes. The marginal advantage of WRF over ECMWF for the desired application is sufficient to motive additional testing with prescribed CO2 flux maps for comparing modeled CO2 concentrations with available observations in an urban environment.
Highlights
Analyses and re-analyses weather products based on global circulation models (GCMs) are generated through the assimilation of various observations at difference temporal and spatial scales
As a consequence, the OA version of WRF is recommended for the interpretation of temperature, wind or atmospheric transport when an accurate description of reality is needed
This work shows that it provides a better representation of vertical temperature gradients by strongly reducing negative biases from European Center for Medium Range Weather Forecast (ECMWF) (0.52~0.86°C) to slightly warm biases (0.48~0.72°C) at 00 UTC
Summary
Analyses and re-analyses weather products based on global circulation models (GCMs) are generated through the assimilation of various observations at difference temporal and spatial scales. They are usually designed to reproduce the large-scale or mesoscale patterns of atmospheric circulations. State-of-the-art for global scale products, such spatial resolutions may be insufficient to represent small-scale and terrain-driven meteorological features (Carvalho et al, 2014). Regional numerical models, such as the Weather Research and Forecasting Model (WRF, Skamarock et al, 2008) are used to describe the atmospheric state for small-scale regional meteorological fields or to account for specific dynamical processes, e.g. in urban areas
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