Coupled weather research and forecasting-stochastic time-inverted lagrangian 
transport (WRF-STILT) model

Nehrkorn, T.; Eluszkiewicz, J.; Wofsy, S. C.; Lin, J. C.; Gerbig, C.; Longo, M.; Freitas, S.

doi:10.1007/s00703-010-0068-x

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Coupled weather research and forecasting-stochastic time-inverted lagrangian transport (WRF-STILT) model

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Gerbig, C.
Airborne Trace Gas Measurements and Mesoscale Modelling, Dr. habil. C. Gerbig, Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Citation

Nehrkorn, T., Eluszkiewicz, J., Wofsy, S. C., Lin, J. C., Gerbig, C., Longo, M., et al. (2010). Coupled weather research and forecasting-stochastic time-inverted lagrangian transport (WRF-STILT) model. Meteorology and Atmospheric Physics, 107(1-2), 51-64. doi:10.1007/s00703-010-0068-x.

Cite as: https://hdl.handle.net/11858/00-001M-0000-000E-DA53-5

Abstract

This paper describes the coupling between a mesoscale numerical weather prediction model, the Weather Research and Forecasting (WRF) model, and a Lagrangian Particle Dispersion Model, the Stochastic Time-Inverted Lagrangian Transport (STILT) model. The primary motivation for developing this coupled model has been to reduce transport errors in continental-scale top-down estimates of terrestrial greenhouse gas fluxes. Examples of the model's application are shown here for backward trajectory computations originating at CO₂ measurement sites in North America. Owing to its unique features, including meteorological realism and large support base, good mass conservation properties, and a realistic treatment of convection within STILT, the WRF-STILT model offers an attractive tool for a wide range of applications, including inverse flux estimates, flight planning, satellite validation, emergency response and source attribution, air quality, and planetary exploration.