Parametrization of the Tidal Effect for Use in the Noah Land-Surface Model: Development and Validation

Lee, Younghee; Ahn, Kwang-Deuk; Lee, Yong Hee

doi:10.1007/s10546-016-0178-1

Cited by 4 publications

(6 citation statements)

References 18 publications

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“…A land breeze developed every night except for the evening of 8 September. Due to location of the flux tower, the tower provided good upwind fetches over the tidal flats only during westerly wind conditions (Lee et al 2016). Therefore, to compare turbulent fluxes between the model and observation we focused on the westerly wind condition (135° < WD < 345°).…”

Section: Comparison Of the Modelled Results With Observationsmentioning

confidence: 99%

“…The parameterizations chosen for this study include the Dudhia simple cloud-interactive shortwave radiation scheme (Dudhia 1989), Rapid Radiative Transfer Model (RRTM) longwave radiation scheme (Mlawer et al 1997), YSU planetary boundary layer (PBL) scheme (Hong et al 2006), revised MM5 Monin-Obukhov scheme, and the Goddard microphysics scheme (Tao et al 1989). In order to examine the tidal effects on the simulation, two land surface schemes were used, namely, the Noah land surface scheme (Chen and Dudhia 2001), and the Noah land surface scheme with tidal parameterization (Lee et al 2016). The Kain-Fritsch cumulus parametrization scheme (Kain and Fritsch 1993) was used for the three outer domains.…”

Section: Model Setup and Datamentioning

confidence: 99%

“…All energy fluxes were calculated at 30 min intervals. The data processing is described in Lee et al (2016). The measurement period was from 12 August to 26 September 2014.…”

Section: Model Setup and Datamentioning

confidence: 99%

“…The tidal parameterization was based on the water layer energy budget with changing thickness above the soil. Details of the parameterization are described in Lee et al (2016). Here, we briefly describe the features related to implementing the tidal parameterization into the WRF model.…”

Section: Implementation Of Tidal Parameterization Into Wrf Modelmentioning

confidence: 99%

“…However, as the spatial resolution of a model increases with increasing computational speed (Hong and Dudhia 2012), some grid points near the shorelines can correspond to tidal flats. For better simulations of the surface fluxes on tidal flats, a parameterization for tidal flats has been developed and validated against eddy covariance data obtained at a single tower over a tidal flat in offline mode (Lee et al 2016). The parameterization is based on the energy budget of a water layer with varying thickness above the soil.…”

Section: Introductionmentioning

confidence: 99%

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Implementation of tidal parameterization in the Weather Research and Forecasting (WRF) model

Lee¹,

Ahn²,

Lee³

et al. 2020

Terr. Atmos. Ocean. Sci.

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In this study, the Noah land surface model with a tidal parameterization was implemented in the WRF model. Newly added inputs included gridded tidal data that indicated the presence of a tidal flat, and a time varying water layer thickness over the tidal flat. Two simulations were performed in an online mode, namely, a simulation without tidal effects (CNTL) and simulation with tidal effects (TIDE). A comparison between the simulations and observations at flux tower showed that the surface heat and momentum fluxes were well reproduced in the TIDE simulation both in the magnitude and variation. In spite of better surface flux simulations, the air temperatures were slightly better simulated in the TIDE simulation than in the CNTL simulation during nighttime only. The 10 m wind speed was slightly overestimated in the TIDE compared to the CNTL simulation. The mean differences in the field variables between the TIDE and CNTL simulations were examined for four cases during the simulation period (inundation and exposed conditions at night and inundation and exposed conditions during the day). Tidal grids were classified into two groups depending on the land use type in the CNTL simulation as either the land to tide (LT) group or the water to tide (WT) group. The magnitude of the 2 m air temperature difference between the two simulations was generally larger on LT group than on WT group. During the day, both the 2 m air temperature and the planetary boundary layer height (PBLH) decreased under inundation conditions over LT group. The impact of the tidal flat on 10 m wind and PBLH extended inland beyond the tidal flats during the daytime inundation period.

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Section: Comparison Of the Modelled Results With Observationsmentioning

confidence: 99%

Section: Model Setup and Datamentioning

confidence: 99%

“…All energy fluxes were calculated at 30 min intervals. The data processing is described in Lee et al (2016). The measurement period was from 12 August to 26 September 2014.…”

Section: Model Setup and Datamentioning

confidence: 99%

Section: Implementation Of Tidal Parameterization Into Wrf Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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