Estimating Marine Fog Probability Using a Model Output Statistics Scheme

Koziara, Michael; Renard, Robert J.; Thompson, William J.

doi:10.1175/1520-0493(1983)111<2333:emfpua>2.0.co;2

Cited by 23 publications

(13 citation statements)

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“…Kang et al (2005) compared different metrics with three sets of model systems and pointed out that no single metric was sufficient but rather a suit of measures was required to fully evaluate a model's performance spatially and temporally in ozone simulations. Several metrics were used in this study to compare between CMAQ and ground-level observations quantitatively, which included the commonly used "discrete statistics" (Kang et al 2005) as well as a method called "categorical-type forecast evaluation" that has been originally used to evaluate precipitation forecasting (Koziara et al 1983;Kang et al 2005;Wilks 2006).…”

Section: Statistical Measuresmentioning

confidence: 99%

The efficacy of satellite information in improving CMAQ/Models-3 prediction of ozone episodes in the US–Mexico border

Shi

Fernando

Seto

et al. 2010

Air Qual Atmos Health

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The possibility of improving ozone predictions of the Community Multiscale Air Quality (CMAQ) air quality modeling system by ingesting tropospheric emission spectrometer (TES) data to specify initial/boundary conditions (IC/BC) was investigated for the southwest USA. The aim was to help develop a modeling-based health warning system for the US-Mexico border, where the ground-station coverage is sparse. Simulations were conducted with default IC/BC and those derived using TES. The CMAQ output was validated by comparing with the ground-level hourly, 1-and 8-h maximum ozone, satellitemeasured 3D ozone concentrations in the middle to upper troposphere and satellite-measured ozone profiles. The validation of CMAQ output against surface ozone measurements indicates that the predictions of both runs are acceptable on the basis of commonly recommended statistical standards and are comparable to other reported studies. Results revealed that the TES-derived IC/BC did not show glaringly better performance in predicting surface ozone when the evaluations were conducted with the hourly data, but it did show evidence of improvements when the statistics were done with the 1-and 8-h maximum ozone by both discrete and categorical-type evaluations. From the perspective of air quality forecasting, TES-derived IC/BC did show potential for improving the ground-level ozone concentration predictions. Additionally, improvements could be noted for upper-tropospheric ozone (<500 hPa), as well as to a certain extent the middle tropospheric ozone, when evaluated against satellite-measured ozone profiles and 3D ozone concentrations.

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Section: Statistical Measuresmentioning

confidence: 99%

The efficacy of satellite information in improving CMAQ/Models-3 prediction of ozone episodes in the US–Mexico border

Shi

Fernando

Seto

et al. 2010

Air Qual Atmos Health

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“…Most of the current operational systems for forecasting the fog and ceiling at an airport rely on statistical methods like model output statistics (MOS; Glahn and Lowry 1972;Koziara et al 1983) or artificial neural networks (ANNs; Fabbian et al 2007;Bremnes and Michaelides 2007;Marzban et al 2007). These methods use statistical postprocessing of numerical model outputs to improve forecast quality, especially when model outputs are combined with surface observations.…”

Section: Introductionmentioning

confidence: 99%

Skill of a Ceiling and Visibility Local Ensemble Prediction System (LEPS) according to Fog-Type Prediction at Paris-Charles de Gaulle Airport

Roquelaure

Tardif

Rémy

et al. 2009

Weather and Forecasting

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A specific event, called a low-visibility procedure (LVP), has been defined when visibility is under 600 m and/or the ceiling is under 60 m at Paris-Charles de Gaulle Airport, Paris, France, to ensure air traffic safety and to reduce the economic issues related to poor visibility conditions. The Local Ensemble Prediction System (LEPS) has been designed to estimate LVP likelihood in order to help forecasters in their tasks. This work evaluates the skill of LEPS for each type of LVP that takes place at the airport area during five winter seasons from 2002 to 2007. An event-based classification reveals that stratus base lowering, advection, and radiation fogs make up for 78% of the LVP cases that occurred near the airport during this period. This study also demonstrates that LEPS is skillful on these types of event for short-term forecasts. When the ensemble runs start with initialized LVP events, the prediction of advection fogs is as skillful as the prediction of radiation fog events and stratus base lowering. At 3 and 6 h before the runs where LVP events were initialized, LEPS still shows positive skill for radiation fog events and stratus base lowering cases.

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“…Along with NWP model data, observations are also used to develop MOS regression equations for ceiling and visibility, temperature and dewpoint, wind speed and direction, probability of precipitation, precipitation amount, and cloud cover. MOS techniques, applied to various NWP models, have also been used to develop specific algorithms to forecast the occurrence of Levante wind regimes during the warm season (Godfrey 1982), marine fog probability for the northern Pacific Ocean (Koziara et al 1983), maximum and minimum temperatures for seven Australian cities (Woodcock 1984), and the probability of precipitation and rain amount in Australia (Tapp et al 1986). More recently, Norquist (1999) presented a MOS approach to diagnose cloud characteristics, including cloud-base height, from a mesoscale NWP model.…”

Section: Introductionmentioning

confidence: 99%

Data Mining Numerical Model Output for Single-Station Cloud-Ceiling Forecast Algorithms

Bankert

Hadjimichael

2007

Weather and Forecasting

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Accurate cloud-ceiling-height forecasts derived from numerical weather prediction (NWP) model data are useful for aviation and other interests where low cloud ceilings have an impact on operations. A demonstration of the usefulness of data-mining methods in developing cloud-ceiling forecast algorithms from NWP model output is provided here. Rapid Update Cycle (RUC) 1-h forecast data were made available for nearly every hour in 2004. Various model variables were extracted from these data and stored in a database of hourly records for routine aviation weather report (METAR) station KJFK at John F. Kennedy International Airport along with other single-station locations. Using KJFK cloud-ceiling observations as ground truth, algorithms were derived for 1-, 3-, 6-, and 12-h forecasts through a data-mining process. Performance of these cloud-ceiling forecast algorithms, as evaluated through cross-validation testing, is compared with persistence and Global Forecast System (GFS) model output statistics (MOS) performance (6 and 12 h only) over the entire year. The 1-h algorithms were also compared with the RUC model cloud-ceiling (or cloud base) height translation algorithms. The cloud-ceiling algorithms developed through data mining outperformed these RUC model translation algorithms, showed slightly better skill and accuracy than persistence at 3 h, and outperformed persistence at 6 and 12 h. Comparisons to GFS MOS (which uses observations in addition to model data for algorithm derivation) at 6 h demonstrated similar performance between the two methods with the cloud-ceiling algorithm derived through data mining demonstrating more skill at 12 h.

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Estimating Marine Fog Probability Using a Model Output Statistics Scheme

Cited by 23 publications

References 0 publications

The efficacy of satellite information in improving CMAQ/Models-3 prediction of ozone episodes in the US–Mexico border

The efficacy of satellite information in improving CMAQ/Models-3 prediction of ozone episodes in the US–Mexico border

Skill of a Ceiling and Visibility Local Ensemble Prediction System (LEPS) according to Fog-Type Prediction at Paris-Charles de Gaulle Airport

Data Mining Numerical Model Output for Single-Station Cloud-Ceiling Forecast Algorithms

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