A Study of Fog Characteristics Using a Coupled WRF–COBEL Model Over Thessaloniki Airport, Greece

Stolaki, S.; Pytharoulis, I.; Karacostas, T.

doi:10.1007/s00024-011-0393-0

Cited by 32 publications

(14 citation statements)

References 22 publications

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“…The COBEL-ISBA model also integrates external mesoscale forcings from 3D mesoscale NWP models (e.g., AROME at DMN; WRF in Greece, Stolaki et al (2012) [21]) to take into account the influence of possible horizontal heterogeneities on the local forecast scale. These forcings include horizontal advection of potential temperature and moisture, geostrophic wind, local pressure tendencies, and cloud cover.…”

Section: The Cobel-isba Fog Forecast Systemmentioning

confidence: 99%

A Preliminary Impact Study of Wind on Assimilation and Forecast Systems into the One-Dimensional Fog Forecasting Model COBEL-ISBA over Morocco

Bari

2019

Atmosphere

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The assimilation impact of wind data from aircraft measurements (AMDAR), surface synoptic observations (SYNOP) and 3D numerical weather prediction (NWP) mesoscale model, on short-range numerical weather forecasting (up to 12 h) and on the assimilation system, using the one-dimensional fog forecasting model COBEL-ISBA (Code de Brouillard à l’Échelle Locale-Interactions Soil Biosphere Atmosphere), is studied in the present work. The wind data are extracted at Nouasseur airport, Casablanca, Morocco, over a winter period from the national meteorological database. It is the first time that wind profiles (up to 1300 m) are assimilated in the framework of a single-column model. The impact is assessed by performing NWP experiments with data denial tests, configured to be close to the operational settings. The assimilation system estimates the flow-dependent background covariances for each run of the model and takes the cross-correlations between temperature, humidity and wind components into account. When assimilated into COBEL-ISBA with an hourly update cycle, the wind field has a positive impact on temperature and specific humidity analysis and forecasts accuracy. Thus, a superior fit of the analysis background fields to observations is found when assimilating AMDAR without NWP wind data. The latter has shown a detrimental impact in all experiments. Besides, wind assimilation gave a clear improvement to short-range forecasts of near-surface thermodynamical parameters. Although, assimilation of SYNOP and AMDAR wind measurements slightly improves the probability of detection of fog but also increases the false alarms ratio by a lower magnitude.

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Section: The Cobel-isba Fog Forecast Systemmentioning

confidence: 99%

A Preliminary Impact Study of Wind on Assimilation and Forecast Systems into the One-Dimensional Fog Forecasting Model COBEL-ISBA over Morocco

Bari

2019

Atmosphere

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“…To measure the cloud condensation nuclei (CCN) number concentration, a miniature continuous flow streamwise thermal gradient CCN chamber (m-CCNC; Sullivan et al, 2009) was installed downstream of the total inlet. This instrument was constructed at Scripps Institution of Oceanography based on the design of Roberts and Nenes (2005).…”

Section: Instrumentationmentioning

confidence: 99%

Size-dependent particle activation properties in fog during the ParisFog 2012/13 field campaign

et al. 2014

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Fog-induced visibility reduction is responsible for a variety of hazards in the transport sector. Therefore there is a large demand for an improved understanding of fog formation and thus improved forecasts. Improved fog forecasts require a better understanding of the numerous complex mechanisms during the fog life cycle. During winter 2012/13 a field campaign called ParisFog aiming at fog research took place at SIRTA (Instrumented Site for Atmospheric Remote Sensing Research). SIRTA is located about 20 km southwest of the Paris city center, France, in a semi-urban environment. In situ activation properties of the prevailing fog were investigated by measuring (1) total and interstitial (non-activated) dry particle number size distributions behind two different inlet systems; (2) interstitial hydrated aerosol and fog droplet size distributions at ambient conditions; and (3) cloud condensation nuclei (CCN) number concentration at different supersaturations (SS) with a CCN counter. The aerosol particles were characterized regarding their hygroscopic properties, fog droplet activation behavior and contribution to light scattering for 17 developed fog events. Low particle hygroscopicity with an overall median of the hygroscopicity parameter, κ, of 0.14 was found, likely caused by substantial influence from local traffic and wood burning emissions. Measurements of the aerosol size distribution at ambient RH re-vealed that the critical wet diameter, above which the hydrated aerosols activate to fog droplets, is rather large (with a median value of 2.6 µm) and is highly variable (ranging from 1 to 5 µm) between the different fog events. Thus, the number of activated fog droplets was very small and the nonactivated hydrated particles were found to contribute significantly to the observed light scattering and thus to the reduction in visibility. Combining all experimental data, the effective peak supersaturation, SS peak , a measure of the peak supersaturation during the fog formation, was determined. The median SS peak value was estimated to be in the range from 0.031 to 0.046 % (upper and lower limit estimations), which is in good agreement with previous experimental and modeling studies of fog.

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“… 2007 ; Stolaki et al. 2012 ), with more time needed between plane takeoffs and landings causing delays, as well as the need to cancel flights.…”

Section: Introductionmentioning

confidence: 99%

Understanding and Reducing False Alarms in Observational Fog Prediction

Izett

Wiel

Baas

et al. 2018

Boundary-Layer Meteorol

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The reduction in visibility that accompanies fog events presents a hazard to human safety and navigation. However, accurate fog prediction remains elusive, with numerical methods often unable to capture the conditions of fog formation, and observational methods having high false-alarm rates in order to obtain high hit rates of prediction. In this work, 5 years of observations from the Cabauw Experimental Site for Atmospheric Research are used to further investigate how false alarms may be reduced using the statistical method for diagnosing radiation-fog events from observations developed by Menut et al. (Boundary-Layer Meteorol 150:277–297, 2014). The method is assessed for forecast lead times of 1–6 h and implementing four optimization schemes to tune the prediction for different needs, compromising between confidence and risk. Prediction scores improve significantly with decreased lead time, with the possibility of achieving a hit rate of over 90% and a false-alarm rate of just 13%. In total, a further 31 combinations of predictive variables beyond the original combination are explored (including mostly, e.g., variables related to moisture and static stability of the boundary layer). Little change to the prediction scores indicates any appropriate combination of variables that measure saturation, turbulence, and near-surface cooling can be used. The remaining false-alarm periods are manually assessed, identifying the lack of spatio–temporal information (such as the temporal evolution of the local conditions and the advective history of the airmass) as the ultimate limiting factor in the methodology’s predictive capabilities. Future observational studies are recommended that investigate the near-surface evolution of fog and the role of non-local heterogeneity on fog formation.

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A Study of Fog Characteristics Using a Coupled WRF–COBEL Model Over Thessaloniki Airport, Greece

Cited by 32 publications

References 22 publications

A Preliminary Impact Study of Wind on Assimilation and Forecast Systems into the One-Dimensional Fog Forecasting Model COBEL-ISBA over Morocco

A Preliminary Impact Study of Wind on Assimilation and Forecast Systems into the One-Dimensional Fog Forecasting Model COBEL-ISBA over Morocco

Size-dependent particle activation properties in fog during the ParisFog 2012/13 field campaign

Understanding and Reducing False Alarms in Observational Fog Prediction

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