Articles | Volume 9, issue 1
https://doi.org/10.5194/esd-9-167-2018
https://doi.org/10.5194/esd-9-167-2018
Research article
 | 
26 Feb 2018
Research article |  | 26 Feb 2018

A new moisture tagging capability in the Weather Research and Forecasting model: formulation, validation and application to the 2014 Great Lake-effect snowstorm

Damián Insua-Costa and Gonzalo Miguez-Macho

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Cited articles

Arnault, J., Knoche, R., Wei, J., and Kunstmann, H.: Evaporation tagging and atmospheric water budget analysis with WRF: A regional precipitation recycling study for West Africa, Water Resour. Res., 52, 1544–1567, https://doi.org/10.1002/2015WR017704, 2016. a
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Bosilovich, M. G., Sud, Y. C., Schubert, S. D., and Walker, G. K.: Numerical simulation of the large-scale North American monsoon water sources, J. Geophys. Res., 108, 8614, https://doi.org/10.1029/2002JD003095, 2003. a
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Bosilovich, M. G. and Schubert, S. D.: Water Vapor Tracers as Diagnostics of the Regional Hydrologic Cycle, J. Hydrometeorol., 3, 149–165, https://doi.org/10.1175/1525-7541(2002)003<0149:WVTADO>2.0.CO;2, 2002. a, b, c, d, e
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Short summary
We present here a newly implemented water vapor tracer tool into the WRF meteorological model (WRF-WVT). A detailed validation shows high accuracy, with an error of much less than 1 % in moisture traceability. As an example application, we show that for the 2014 Great Lake-effect snowstorm, above 30 % of precipitation in the regions immediately downwind originated from lake evaporation, with contributions exceeding 50 % in the areas with highest snowfall accumulations.
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