A Comparison between 3DVAR and EnKF for Data Assimilation Effects on the Yellow Sea Fog Forecast

Gao, Xiaoyu; Gao, Shanhong; Yang, Yue

doi:10.20944/preprints201807.0577.v1

Cited by 7 publications

(9 citation statements)

References 30 publications

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“…Only the mechanism of gravitational settling is considered for a smooth surface, for instance, bare soil and ocean when calculating deposition velocity (Katata et al, ). A threshold of 0.016 g kg −1 for LWC is generally adopted to diagnose simulated sea fog (e.g., Gao et al, ; Wang et al, ; Yang et al, ; Zhou & Du, ).…”

Section: Methodsmentioning

confidence: 99%

“…The statistical scores shown in Table quantitatively evaluate the last 24‐hr simulation of sea fog area. The values are obtained using the objective evaluation method widely used in previous sea fog numerical studies (e.g., Gao et al, ; Wang et al, ; Yang et al, ; Zhou & Du, ). The results show that Exp‐TOP has a smaller false alarm ratio (FAR; 0.423 versus 0.473) and a bias value (Bias) closer to 1.0 (0.968 versus 1.179) than Exp‐noTOP.…”

Section: Improvements Of Sea Fog Simulation Caused By the Top‐driven mentioning

confidence: 99%

“…For instance, the annual number of fog days observed at Chengshantou (CS in Figure ) reaches up to 83 days (e.g., Cho et al, ; Gao et al, ; Zhang et al, ). In order to mitigate socioeconomic impacts of sea fog over the Yellow Sea and meet increasing practical demands, it is urgent to improve the forecast skill of sea fog (Gao et al, ; Wang et al, ). For accurate sea fog prediction, one major prerequisite is to well understand the physical mechanism of its evolution.…”

Section: Introductionmentioning

confidence: 99%

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The Impact of Turbulent Diffusion Driven by Fog‐Top Cooling on Sea Fog Development

Yang

Gao

2020

JGR Atmospheres

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Turbulent mixing driven by cloud/fog‐top radiative and evaporative cooling (hereafter top‐driven diffusion), including top‐down mixing and top‐cooling entrainment, is critical for the development of cloud/fog. Previous work mainly focused on impacts of top‐driven diffusion on stratocumulus‐topped planetary boundary layer (PBL) and radiation fog over land. However, its exact role in sea fog process is yet unclear. Using the Weather Research and Forecasting (WRF) model with the updated Yonsei University (YSU) PBL scheme, in which the ysu_topdown_pblmix option is responsible for the parameterization of the top‐driven diffusion, the present study investigates respective effects of the top‐cooling entrainment and top‐down mixing on an advection fog event over the Yellow Sea that occurred on 20–21 May 2014. Evaluation of the modeling results confirms that the top‐driven diffusion significantly improves the sea fog simulation. The top‐cooling entrainment allows more relatively quiescent air above the fog top to mix into the sea fog layer, leading to a higher mixed layer with increased temperature and decreased humidity. With the enhancement of buoyant turbulence, the warming and dehumidifying moderately lift the sea fog bottom and reduce the false fog area. The top‐down mixing performs quite well in reproducing a stable structure near the fog top, which results from the added turbulent mixing determined by a revised K profile. Note that the effect of top‐driven diffusion shows high sensitivities to shortwave radiation and vertical resolution. Besides the fog‐top cooling, the fog‐droplet sedimentation is necessary to be included in the top‐cooling entrainment.

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Section: Methodsmentioning

confidence: 99%

Section: Improvements Of Sea Fog Simulation Caused By the Top‐driven mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Impact of Turbulent Diffusion Driven by Fog‐Top Cooling on Sea Fog Development

Yang

Gao

2020

JGR Atmospheres

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“…a first-order nonlocal scheme). It has been widely used for sea fog forecasting (e.g., Gao et al, 2018), air quality assessments (Hu et al, 2013), wind resources (Hu et al, 2013), etc. The PBL top was defined at the maximum entrainment layer using a critical bulk Richardson number of zero (Hong et al, 2006).…”

Section: Model Configurationsmentioning

confidence: 99%

A High‐Resolution Simulation of Roll Convection Over the Yellow Sea During a Cold Air Outbreak

2019

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Horizontal convective rolls (HCRs) are significant for vertical transport of momentum, heat, and moisture, which is not fully understood partly due to lack of adequate observations. Previous high‐resolution modeling studies of roll convection mainly focused on idealized simulations. This study is one of the first simulations of HCRs with high‐resolution numerical weather prediction models in the real world, aiming to assess the modeling ability of realistic roll structure and investigate the characteristics of roll‐to‐cell transition. A real case of roll convection over the Yellow Sea during a cold air outbreak has been simulated, using the Weather Research and Forecasting (WRF) model at resolutions of 1 (WRF1) and 3 km (WRF3). Compared with the WRF3 simulation, the cloud water, vertical velocity, and the fine‐scale secondary circulations of HCRs are enhanced in WRF1 simulation, and the geometrical and physical parameters are consistent with the observations of satellite images (viewed as cloud streets) or previous studies. In this case, the 1‐km WRF simulation is able to reproduce the HCRs with a roll size of ~5 km. When the rolls transform to open cells downstream, the friction velocity and sensible heat flux gradually reduce following the prevailing wind, and the stability parameter –zi/L (the ratio of planetary boundary layer depth to Obukhov length) tends to increase with larger variances. During the roll‐to‐cell transition, the associated thermodynamic conditions are well simulated, with an average –zi/L ~ 22. In the future, reliable high‐resolution simulations can serve as an alternative to quantitatively investigate roll characteristics when observations are sparse or unavailable.

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“…At the same time, some water-soluble aerosol particles absorb water and grow, forming high-concentration liquid particles, which can form fog droplets in the subsaturated condition [12]. Many scholars have observed and simulated the formation, dissipation mechanism, microphysical characteristics, and chemical composition of fog in different areas of China [13][14][15][16][17][18][19]. For example, Li et al [20,21] have carried out a large number of fog-observation experiments in Chongqing, Nanjing, and other places.…”

Section: Introductionmentioning

confidence: 99%

Study on a Large-Scale Persistent Strong Dense Fog Event in Central and Eastern China

Wang

Zhang²,

Liu

et al. 2020

Advances in Meteorology

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A large-scale persistent strong dense fog (SDF) event that occurred from December 30, 2016, to January 5, 2017, in central and eastern China is analyzed by using a variety of data, including high-resolution satellite and surface observations, meteorological tower observations, fine-resolution sounding observations, and NCEP/NCAR reanalysis data. The results show the following: (1) The SDF event has the characteristics of long duration, wide influence range, large intensity, and serious air pollution. During the study period, there are 531 stations with SDF events, covering an area of over 360,000 km2. There were five stations in Hebei province where the fog lasted for more than 77 hours, and even some stations did not dissipate during the day. (2) Radiation fog and advection fog alternate in this SDF event, namely, radiation fog (20:00 BT on December 30 to 14:00 on January 1), advection radiation fog (20:00 on January 1 to 08:00 on January 2), radiation fog (night on January 2 to daytime on January 3), and advection radiation fog (night on January 3 to January 5). The characteristic of radiation fog is that the central and eastern part of China was controlled by “L” type high pressure. In the stage of advection radiation fog, the combined effect of weak cold advection and radiation cooling leads to the occurrence of SDF. (3) Regarding the duration of the fog event, the inversion structure is continuously maintained at night and in the morning near the stratum, and when the fog intensity is strong, the inversion intensity is correspondingly large, the fog top is lower than the inversion layer top, and the top of the SDF is between 80 and 400 meters.

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A Comparison between 3DVAR and EnKF for Data Assimilation Effects on the Yellow Sea Fog Forecast

Cited by 7 publications

References 30 publications

The Impact of Turbulent Diffusion Driven by Fog‐Top Cooling on Sea Fog Development

The Impact of Turbulent Diffusion Driven by Fog‐Top Cooling on Sea Fog Development

A High‐Resolution Simulation of Roll Convection Over the Yellow Sea During a Cold Air Outbreak

Study on a Large-Scale Persistent Strong Dense Fog Event in Central and Eastern China

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