Meteorology and Atmospheric Physics

, Volume 107, Issue 1–2, pp 51–64 | Cite as

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

  • Thomas NehrkornEmail author
  • Janusz Eluszkiewicz
  • Steven C. Wofsy
  • John C. Lin
  • Christoph Gerbig
  • Marcos Longo
  • Saulo Freitas
Original Paper


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.


Mass Flux Numerical Weather Prediction Model Planetary Boundary Layer Height Regional Atmospheric Modeling System Convective Mass Flux 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Work at AER has been supported by the NASA Terrestrial Ecology Program (contract NNH05CC42C) and the National Science Foundation Atmospheric Chemistry Program (Grant ATM-0836153). The original manuscript was improved through constructive reviews by Arlyn Andrews (NOAA/Earth System Research Laboratory) and an anonymous reviewer.


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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Thomas Nehrkorn
    • 1
    Email author
  • Janusz Eluszkiewicz
    • 1
  • Steven C. Wofsy
    • 2
  • John C. Lin
    • 3
  • Christoph Gerbig
    • 4
  • Marcos Longo
    • 2
  • Saulo Freitas
    • 5
  1. 1.Atmospheric and Environmental Research, Inc.LexingtonUSA
  2. 2.Harvard UniversityCambridgeUSA
  3. 3.University of WaterlooWaterlooCanada
  4. 4.Max-Planck-Institut für BiogeochemieJenaGermany
  5. 5.Center for Weather Forecasts and Climate Studies (CPTEC), INPECachoeira PaulistaBrazil

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