Recent Developments in Automated Prediction of Ceiling and Visibility

Bocchieri, Joseph R.; Crisci, Richard L.; Glahn, Harry R.; Lewis, Frank L.; Globokar, Frank T.

doi:10.1175/1520-0450(1974)013<0277:rdiapo>2.0.co;2

Cited by 13 publications

(6 citation statements)

References 4 publications

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“…In this method, both in developing and implementing the statistically established forecast system, predictors are derived from the NWP model output, observations, and climatic data. BOCCHIERI et al (1974) applied linear regression to both observations and output from atmospheric models as predictors in an automated system for predicting ceiling and visibility.…”

Section: B) Statistical Models Versus Learning and Application Datamentioning

confidence: 99%

Fog Research: A Review of Past Achievements and Future Perspectives

Gültepe

Tardif

Michaelides³

et al. 2007

Pure appl. geophys.

562

348

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The scientific community that includes meteorologists, physical scientists, engineers, medical doctors, biologists, and environmentalists has shown interest in a better understanding of fog for years because of its effects on, directly or indirectly, the daily life of human beings. The total economic losses associated with the impact of the presence of fog on aviation, marine and land transportation can be comparable to those of tornadoes or, in some cases, winter storms and hurricanes. The number of articles including the word ''fog'' in Journals of American Meteorological Society alone was found to be about 4700, indicating that there is substantial interest in this subject. In spite of this extensive body of work, our ability to accurately forecast/nowcast fog remains limited due to our incomplete understanding of the fog processes over various time and space scales. Fog processes involve droplet microphysics, aerosol chemistry, radiation, turbulence, large/small-scale dynamics, and surface conditions (e.g., partaining to the presence of ice, snow, liquid, plants, and various types of soil). This review paper summarizes past achievements related to the understanding of fog formation, development and decay, and in this respect, the analysis of observations and the development of forecasting models and remote sensing methods are discussed in detail. Finally, future perspectives for fog-related research are highlighted.

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Section: B) Statistical Models Versus Learning and Application Datamentioning

confidence: 99%

Fog Research: A Review of Past Achievements and Future Perspectives

Gültepe

Tardif

Michaelides³

et al. 2007

Pure appl. geophys.

562

348

View full text Add to dashboard Cite

show abstract

“…Hastie et al (2001) distinguish between two basic methods for statistical learning and prediction: 1) parametric linear models and least squares, and 2) nonparametric k-NN methods. Based on a review of postprocessing systems for prediction of the ceiling and visibility, the former approach has been applied and tested much more than has the latter (e.g., Glahn and Lowry 1972;Bocchieri and Glahn 1972;Bocchieri et al 1974;Wilson and Sarrazin 1989;Vislocky and Fritsch 1997;Leyton and Fritsch 2003;Leyton and Fritsch 2004;Jacobs and Maat 2005). The systems reviewed are largely (but not completely) based on the former type of method.…”

Section: December 2007mentioning

confidence: 99%

A Fuzzy Logic–Based Analog Forecasting System for Ceiling and Visibility

Hansen

2007

Weather and Forecasting

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WIND-3 is an application for aviation weather forecasting that uses the analog method to produce deterministic predictions of cloud ceiling height and horizontal visibility at airports. For data, it uses historical and current airport observations [routine aviation weather reports (METARs)], and model-based guidance. It uses the perfect prognosis assumption as it is designed to use any model-based predictions of wind direction and speed, temperature and humidity, and precipitation occurrence and type to specify conditions in the 1-24-h projection period. To identify and rank analogs, according to their degree of similarity with the present situation, it uses a fuzzy logic-based algorithm to measure similarity between past situations, which are complete series of METARs, and current situations, which are a composite of recent METARs and model-based guidance. It uses the retrieved analog ensemble, the set of most similar analogs, to make predictions of ceiling and visibility in the 1-24-h projection period. WIND-3 has been tested by being run continuously in real time for 1 yr, producing forecasts for 190 major Canadian airports. It produces accurate forecasts, based on summaries of Heidke skill score (HSS) statistics, and compared to two benchmarks, persistence and official aerodrome forecasts [terminal aerodrome forecasts (TAFs)]. WIND-3 predictions of instrument flight regulation (IFR) conditions in the 0-6-h period have an HSS of 0.56, and in the 7-24-h period have an HSS of about 0.40, compared to respective HSS scores for persistence forecasts of 0.53 and less than 0.20.

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“…Hence, statistical models and observation-based techniques are also valid options for short-term forecasting and nowcasting of fog (Bocchieri et al, 1974;Pasini et al, 2001;Fabbian et al, 2007). In this context, Menut et al (2014) (hereinafter M14) have recently published a method based on threshold values of key variables for radiation fog (Roach et al, 1976;Guedalia and Bergot, 1994) formation around the SIRTA area in Paris (Haeffelin et al, 2005(Haeffelin et al, , 2010.…”

Section: Introductionmentioning

confidence: 99%

Forecasting radiation fog at climatologically contrasting sites: evaluation of statistical methods and WRF

Román‐Cascón

Steeneveld

Yagüe

et al. 2016

Quart J Royal Meteoro Soc

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A six‐year climatology of radiation fog has been compiled at two sites: the Research Centre for the Lower Atmosphere (CIBA, Spain) and the Cabauw Experimental Site for Atmospheric Research (CESAR, The Netherlands). These sites are contrasted in terms of geographical situation, climate zone, altitude, humidity and soil water availability. Therefore, several climatological differences in fog abundance, onset, dissipation and duration have been quantified between the two sites. The more humid site (CESAR) is characterised by relatively short radiation fog events distributed throughout the year. However, radiation fog at the drier site (CIBA) is more persistent and appears during late autumn/winter months. In general, its formation requires more time after sunset (∼2 h more), since further cooling is required to reach saturation. The forecast of these fog events has been evaluated through two different approaches. First, we extend the statistical method presented by Menut et al. (2014) (M14). This method uses statistics to define threshold values on key variables for fog formation (pre‐fog) and verifies its predictability using observations and numerical model output. We present some of the most appropriate threshold values for the forecasting of pre‐fog periods at both sites, which differ from those presented in M14 and depend on the optimisation of the hit rate or the false‐alarm rate. Additionally, we also extend M14 by suggesting other variables as potential predictors for fog formation (friction velocity and visibility tendency). Finally, we focus on fog simulation by the Weather Research and Forecasting (WRF) model in terms of liquid water content. The WRF model was able to simulate radiation fog when configured with sophisticated physical options and high resolution. However it failed in simulating the onset, dissipation and the vertical extent of fog (which was overestimated). The model results were extremely sensitive to the spin‐up time.

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Recent Developments in Automated Prediction of Ceiling and Visibility

Cited by 13 publications

References 4 publications

Fog Research: A Review of Past Achievements and Future Perspectives

Fog Research: A Review of Past Achievements and Future Perspectives

A Fuzzy Logic–Based Analog Forecasting System for Ceiling and Visibility

Forecasting radiation fog at climatologically contrasting sites: evaluation of statistical methods and WRF

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