Numerical Simulation of Sea Fog over the Yellow Sea: Comparison between UM + PAFOG and WRF + PAFOG Coupled Systems

Kim, Wonheung; Yum, Seong Soo; Kim, Chang Ki

doi:10.1007/s13143-019-00134-9

Cited by 8 publications

(10 citation statements)

References 21 publications

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“…Our 3D WRF simulations also did not capture the onset and dissipation times of fog events well as described in Table 4, where the performance statistics for various model settings are listed. Moreover, unlike some previous studies that had reported improvement of fog simulation in the coupled modeling system (e.g., Shi et al, 2011 (MM5 + PAFOG); Kim et al, 2019c (WRF + PAFOG) [10,40]), the coupled modeling system based on 1D PAFOG and 3D WRF models (WP) produced only slightly better HR (0.27 ± 0.30) and no substantial improvement of CSI (0.14 ± 0.18). The main cause of meager improvement was because fog dissipation time was not simulated well despite some improvement in fog onset time simulation.…”

Section: Impact Of the Observation Data On Fog Predictabilitymentioning

confidence: 82%

“…More information on the PAFOG is available at Bott et al (1990) [39], Bott and Trautmann (2002) [35] and Siebert et al (1992) [38]. The 1D PAFOG model was coupled to the 3D WRF regional model (see Kim et al, 2019c [40] for details). Accordingly, boundary conditions for the PAFOG simulation were provided by the 3D WRF…”

Section: Pafog Simulationmentioning

confidence: 99%

“…Previous studies reported that 3D atmospheric model itself did not reproduce the formation (onset) and dissipation times of fog mainly because of coarse horizontal and vertical resolutions (Boutle et al, 2015; Philip et al, 2016; Kim et al, 2019c [40,43,44]) or inappropriate turbulent cooling near the cold sea surface (Kim et al, 2019c [40]). Our 3D WRF simulations also did not capture the onset and dissipation times of fog events well as described in Table 4, where the performance statistics for various model settings are listed.…”

Section: Impact Of the Observation Data On Fog Predictabilitymentioning

confidence: 99%

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Improvement of Fog Simulation by the Nudging of Meteorological Tower Data in the WRF and PAFOG Coupled Model

et al. 2020

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Improvement of fog simulation accuracy was investigated for the fogs that occurred on the south coast of the Korean Peninsula using the WRF (3D) and PAFOG (1D) coupled model. In total, 22 fog cases were simulated and accuracy of the fog simulation was examined based on Critical Success Index, Hit Rate and False Alarm Rate. The performance of the coupled WRF-PAFOG model was better than that of the single WRF model as expected. However, much more significant improvement appeared only when the data from a 300 m meteorological tower was not only used for the initial conditions but also nudged during the simulation. Moreover, a proper prescription of soil moisture was found to be important for accurate fog simulation especially for the fog cases with prior precipitation since efficient moisture supply from the precipitation-soaked soil might have been critical for fog formation. It was also demonstrated that with such optimal coupled model setting, a coastal radiation fog event with prior precipitation could be very realistically simulated: the fog onset and dissipation times matched so well with observation. In detail, radiative cooling at the surface was critical to form a surface inversion layer as the night fell. Then the vapor flux from the precipitation-soaked surface was confined within the inversion layer to form fog. It is suggested that a proper prescription of soil moisture in the model based on observations, if readily available, could be a cost-effective method for improving operational fog forecasting, considering the fact that tall meteorological towers are a rarity in the world.

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Section: Impact Of the Observation Data On Fog Predictabilitymentioning

confidence: 82%

Section: Pafog Simulationmentioning

confidence: 99%

Section: Impact Of the Observation Data On Fog Predictabilitymentioning

confidence: 99%

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Improvement of Fog Simulation by the Nudging of Meteorological Tower Data in the WRF and PAFOG Coupled Model

et al. 2020

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“…With the recent rapid growth of computational resources, numerical weather simulations have been used in recent studies of sea fog formation and its mechanism, using different physics parameterizations (e.g., S. Gao et al., 2007; Heo & Ha, 2010; C. K. Kim and Yum, 2012; W. Kim et al. 2020; Koračin et al., 2001). Most of these studies have emphasized the impact of initial condition and associated atmospheric boundary layer on the sea fog forecasts.…”

Section: Introductionmentioning

confidence: 99%

A Coupled Numerical Modeling Study of a Sea Fog Case After the Passage of Typhoon Muifa Over the Yellow Sea in 2011

2021

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Satellite remote sensing data revealed a widespread sea fog event over the central/southern Yellow Sea (YS), following Typhoon Muifa passage in August 2011. Despite the importance of sea fog prediction for coastal safety, improving accuracy remains a challenging issue. By analyzing results from air‐sea coupled and uncoupled simulations, this study aims to investigate how the air‐sea coupling improves the sea fog formation and duration and examine atmospheric responses to spatiotemporally varying sea surface temperature (SST) over the YS. Unlike the uncoupled model, the SST simulated by the coupled model dramatically decreased and maintained its low temperature for more than a week after the typhoon passed over the YS, showing better agreement with the observations. The sharp SST decrease over the YS cools the air temperature at low‐level atmosphere and enhances horizontal convergence in the moisture flux over the cooler ocean, which provides favorable conditions for sea fog formation. The long‐lasting oceanic cooling stabilizes the atmospheric boundary layer and suppresses atmospheric vertical mixing, delaying the dissipation of sea fog for more than a week. This study highlights that air‐sea coupling can improve the sea fog simulation by providing more realistic oceanic conditions.

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“…However, several applications exist where the model has been combined with a chemical reaction mechanism simulating in a singlecolumn model version gas and aqueous phase chemical reactions during a fog event (Bott and Carmichael 1993) and the cloud-topped MBL (von Glasow et al 2002;Pechtl et al 2007;Bobrowski et al 2007Bobrowski et al , 2015. The PaFog model, on the other hand, has already been implemented in three-dimensional dynamical models describing there the spatio-temporal evolution of fog events (Masbou 2008;Müller et al 2010;Kim et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Comparison of a Spectral Microphysics and a Two-Moment Cloud Scheme: Numerical Simulations of the Cloud-Topped Marine Boundary Layer

Bott

2020

Boundary-Layer Meteorol

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A comparison between the spectral microphysics cloud scheme (MiStra) and the parametrized cloud scheme (PaStra) is presented. The main feature of MiStra consists of the treatment of aerosol particles, cloud droplets, and drizzle particles in a joint two-dimensional particle size distribution, whereas PaStra consists of a two-moment scheme for cloud droplets combined with a one-moment scheme for drizzle. Both cloud schemes have been implemented in a single-column model of the cloud-topped marine boundary layer. Numerical sensitivity studies are presented demonstrating that MiStra is capable of simulating in great detail the major cloud microphysical processes occurring in low-level stratiform clouds. While in MiStra no empirical parameter is available to tune the model, the empirical model parameters of PaStra have been tuned by means of the MiStra model results. By comparing the numerical results of PaStra with those of MiStra it is found that PaStra simulates the overall characteristics of the cloud-topped marine boundary layer quite well. At the same time, however, the effects of single cloud microphysical processes differ substantially from those of MiStra. Finally, it is shown that even in PaStra the inclusion of all major cloud microphysical processes is mandatory in order to obtain appropriate results.

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Numerical Simulation of Sea Fog over the Yellow Sea: Comparison between UM + PAFOG and WRF + PAFOG Coupled Systems

Cited by 8 publications

References 21 publications

Improvement of Fog Simulation by the Nudging of Meteorological Tower Data in the WRF and PAFOG Coupled Model

Improvement of Fog Simulation by the Nudging of Meteorological Tower Data in the WRF and PAFOG Coupled Model

A Coupled Numerical Modeling Study of a Sea Fog Case After the Passage of Typhoon Muifa Over the Yellow Sea in 2011

Comparison of a Spectral Microphysics and a Two-Moment Cloud Scheme: Numerical Simulations of the Cloud-Topped Marine Boundary Layer

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