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.

Fog Research: A Review of Past Achievements and Future Perspectives

Efforts to quantify the uncertainty in weather forecasts began more than 75 years ago, and many studies and experiments involving objective and subjective probability forecasting have been conducted in meteorology in the intervening period Moreover, the US National Weather Service (NWS) initiated a nationwide program in 1965 in which precipitation probability forecasts were formulated on an operational basis and routinely disseminated to the general public In addition, the NWS now prepares objective probability forecasts for many variables, using statistical procedures Hence probability forecasting in meteorology is unique in that very large sets of probability forecasts that have been subjected to detailed evaluation are available This article has four objectives: (a) to review the history of probability forecasting in meteorology to acquaint statisticians with this body of literature; (b) to describe recent methodological, experimental, and operational activities in this field; (c) to exa

Probability Forecasting in Meteorology

Measurements of aircraft icing environments that include supercooled large drops (SLD) greater than 50 μm in diameter have been made during 38 research flights. These flights were conducted during the First and Third Canadian Freezing Drizzle Experiments. A primary objective of each project was the collection of in situ microphysics data in order to characterize aircraft icing environments associated with SLD. In total there were 2793 30-s averages obtained in clouds with temperatures less than or equal to 0°C, maximum droplet sizes greater than or equal to 50 μm, and ice crystal concentrations less than 1 L−1. The data include measurements from 12 distinct environments in which SLD were formed through melting of ice crystals followed by supercooling in a lower cold layer and from 27 distinct environments in which SLD were formed through a condensation and collision–coalescence process. The majority of the data were collected at temperatures between 0° and −14°C, in stratiform winter clouds assoc...

Characterizations of Aircraft Icing Environments that Include Supercooled Large Drops

The dependence of precipitation types on surface elevation and meteorological conditions and its parameterization

A method to diagnose surface precipitation types is suggested. Most cases of freezing rain and ice pellets occur with a layer warmer than 08C extending above a surface-based layer of air colder than 08C. The procedure uses predictors proportional to the product of the mean temperature of a layer and its depth. These predictors can be seen as areas on aerological diagrams. A positive area is associated with a layer warmer than 08C, conversely a negative area is associated with a layer colder than 08C. The same predictor is used to discriminate snow from rain. A statistical analysis was applied using the North American aerological stations network to determine a set of criteria for discriminating freezing rain, ice pellets, snow, and rain. Once the criteria are known, the precipitation type can be easily diagnosed using temperature profiles from upper-air observations or from numerical weather prediction models. The method has been in operational use at the Canadian Meteorological Centre since 1995.

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A Method to Determine Precipitation Types

Linear screening regression is used to derive relationships between parameters computed from observed upper air soundings (RAOBS) and concurrent observations of precipitation type. Precipitation type is defined as three categories: liquid (rain or drizzle), freezing (freezing rain or freezing drizzle) and frozen (snow or ice pellets). Statistical screening results indicate that of the parameters tried the following are important: the mean temperature in the surface–1000 m and 500–2500 m layers; the depth of the warm layer (temperature >0°C), if one exists; the area between the temperature profile and the 0°C isotherm in the warm layer, the depth of the surface-based cold layer, if one exists, with respect to the wet-bulb temperature profile; and the area between the wet-bulb temperature profile and the 0°C isotherm in the surface-based cold layer. Verification of the specification equations on both developmental and independent data samples indicates that the scores are generally stable. The equa...

The Objective Use of Upper Air Soundings to Specify Precipitation Type

The history of the National Weather Service's development efforts in terminal weather prediction for aviation is discussed and results from recent experiments involving three approaches are presented. In one approach, single-station equations for predicting the probability of specific ceiling and visibility categories are developed. The equations are based upon weather observations at the local terminal only and are derived by using the Regression Estimation of Event Probabilities screening technique. In another approach, Model Output Statistics (MOS) is used to develop probability forecast equations for ceiling and visibility. MOS consists of determining a statistical relationship between a predictand and the forecast output of numerical prediction models. The statistical relationship is determined by screening regression in this paper. The two numerical models used are the National Meteorological Center's (NMC) primitive equation (PE) model and the Techniques Development Laboratory's Subsynopti...

Recent Developments in Automated Prediction of Ceiling and Visibility

A new system is developed which gives conditional probability forecasts for three precipitation type categories: snow or sleet, freezing rain and rain. Also, the probability forecasts are transformed into categorical forecasts so that a “best category”is provided. The Model Output Statistics (MOS) technique is used with output from the Limited-area Fine Mesh (LFM) model to develop statistical forecast equations for each of several regions in the conterminous United States. To help account for the evaporational cooling effect, predictors such as LFM forecasts of boundary layer and 850 mb wet-bulb temperatures and observed surface and dew-point temperatures are included. Also, joint predictors are designed to help account for predictor interactions. The values of the joint predictors are relative frequencies of the freezing rain or snow categories taken from graphs that show these frequencies as joint functions of various pairs of LFM predictors. Results from a statistical screening procedure vary ...

A New Operational System for Forecasting Precipitation Type

The model output statistics (MOS) technique consists of determining a statistical relationship between the forecast output of numerical prediction models and a predictand This paper presents some results obtained in applying the MOS technique to the prediction of ceiling height by means of screening regression Data from 3 winter seasons and 95 eastern US stations are combined in a generalized operator approach to develop multiple regression equations The potential predictors subjected to screening include surface variables observed at 0700 GMT and forecast output from both the National Meteorological Center's primitive-equation model and the Techniques Development Laboratory's subsynoptic advection model Prediction equations are developed for 5-, 11-, and 17-hr forecast projections representing ceiling height forecasts valid at 1200, 1800, and 2400 GMT, respectively Ceiling height is treated both as a categorized and as a continuous predictand Where ceiling height is categorized, the regr

Use of Model Output Statistics for Predicting Ceiling Height

In this paper, we present trends in the verification scores of the Techniques Development Laboratory's (TDL's) operational guidance forecasts and the National Weather Service local forecasts made at Weather Service Forecast Offices (WSFO's). Verification statistics for objective guidance and subjective local forecasts of probability of precipitation (PoP), precipitation type, surface wind, opaque sky cover, ceiling height and maximum/minimum (max/min) temperature are shown for the cool and warm seasons as these guidance products became operational during the period 1970–77. TDL's forecasts are based on the Model Output Statistics (MOS) technique. The primary input to the MOS prediction equations comes from forecast fields from the Limited-area Fine-Mesh, Trajectory, and/or Primitive Equation models. For some equations, surface observations and other variables such as station elevation are also used as predictors. Verification shows that through the years TDL's aviation/public weather guidance for...

Joseph R. Bocchieri

Papers

The Objective Use of Upper Air Soundings to Specify Precipitation Type

Recent Developments in Automated Prediction of Ceiling and Visibility

A New Operational System for Forecasting Precipitation Type

Use of Model Output Statistics for Predicting Ceiling Height

Trends in Comparative Verification Scores for Guidance and Local Aviation/Public Weather Forecasts