Objective verification of World Area Forecast Centre clear air turbulence forecasts

Gill, Philip G.

doi:10.1002/met.1288

Cited by 46 publications

(51 citation statements)

References 9 publications

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“…Convective precipitation rate and convective precipitation accumulation from the Met Office convective parameterization scheme were proposed as predictors for convective turbulence by Gill and Stirling () and are used in this study. The convective precipitation rate is the average rate over the hour preceding validity and the precipitation accumulation is the accumulation over the preceding 6 h period.…”

Section: Turbulence Predictorsmentioning

confidence: 99%

“…Both light and moderate turbulence gridded climatologies were created using GADS data from the previous 12 months (November 2009 to October 2010) as described in Gill and Stirling () and used as an estimate of the climatological probability of experiencing turbulence. In an attempt to account for some of the seasonal variability in turbulent events, the 12 month period was split in two to give a climatology based on GADS observations from November 2009 to April 2010 and another from May 2010 to October 2010.…”

Section: Turbulence Predictorsmentioning

confidence: 99%

“…An objective verification scheme using automated aircraft observations from the GADS database (Tenenbaum, ) is used to verify both the probabilistic and deterministic turbulence predictors. For full details see Gill ().…”

Section: Verificationmentioning

confidence: 99%

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An ensemble based turbulence forecasting system

Gill

Buchanan

2013

Meteorological Applications

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Turbulence is a major source of weather-related aviation incidents. There are many different indicators used to try and predict where turbulence is likely to occur. The indicators are derived from deterministic models although they are often quoted as probabilities. This paper proposes the use of ensemble forecasts from the Met Office Global and Regional Ensemble Prediction System (MOGREPS) to produce a probabilistic indicator of wind shear and convectively induced moderate or greater turbulence. An objective verification scheme using high-resolution automated aircraft observations from the Global Aircraft Data Set is used to compare the skill with the routinely available World Area Forecast Centre gridded turbulence forecasts. The forecasts are assessed globally over a 12 month period from November 2010 to October 2011 looking at the skill, reliability and economic value of the forecasts.

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Section: Turbulence Predictorsmentioning

confidence: 99%

Section: Turbulence Predictorsmentioning

confidence: 99%

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An ensemble based turbulence forecasting system

Gill

Buchanan

2013

Meteorological Applications

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“…This includes a t þ 24 h significant weather (SIGWX) chart four times a day (0000, 0006, 0012, 0018 UTC) which displays multiple aviation hazards including icing, CAT, as well as the location of convective cloud. The WAFCs also produce a gridded turbulence forecast four times a day at five pressure levels with a lead time t þ 6 h to t þ 36 h (Gill 2014).…”

Section: Forecastingmentioning

confidence: 99%

“…The DEVG (Tenenbaum 1991;Gill 2014Gill , 2016Kim et al 2017) is calculated following Truscott (2000) using:…”

Section: Forecast Verificationmentioning

confidence: 99%

Aviation Turbulence: Dynamics, Forecasting, and Response to Climate Change

Storer

Williams

Gill

2018

Pure Appl. Geophys.

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Abstract-Atmospheric turbulence is a major hazard in the aviation industry and can cause injuries to passengers and crew. Understanding the physical and dynamical generation mechanisms of turbulence aids with the development of new forecasting algorithms and, therefore, reduces the impact that it has on the aviation industry. The scope of this paper is to review the dynamics of aviation turbulence, its response to climate change, and current forecasting methods at the cruising altitude of aircraft. Aviationaffecting turbulence comes from three main sources: vertical wind shear instabilities, convection, and mountain waves. Understanding these features helps researchers to develop better turbulence diagnostics. Recent research suggests that turbulence will increase in frequency and strength with climate change, and therefore, turbulence forecasting may become more important in the future. The current methods of forecasting are unable to predict every turbulence event, and research is ongoing to find the best solution to this problem by combining turbulence predictors and using ensemble forecasts to increase skill. The skill of operational turbulence forecasts has increased steadily over recent decades, mirroring improvements in our understanding. However, more work is needed-ideally in collaboration with the aviation industry-to improve observations and increase forecast skill, to help maintain and enhance aviation safety standards in the future.

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Regional downscaled future change of clear‐air turbulence over East Asia under RCP8.5 scenario within the CORDEX‐EA‐II project

Tang

Ding

et al. 2021

Intl Journal of Climatology

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Driven by four global coupled atmosphere–ocean models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble (CNRM‐CM5, GFDL‐ESM2M, EC‐EARTH, and MPI‐ESM‐LR), future changes (2040–2059) of clear‐air turbulence (CAT) in winter over East Asia under Representative Concentration Pathway 8.5 (RCP8.5) scenario are projected with the regional climate model (RCM) RegCM4 and 18 CAT diagnostics based on the second phase of Coordinated Regional Downscaling Experiment East Asia (CORDEX‐EA‐II) framework. Evaluation of RegCM4 with ERA‐Interim shows that RegCM4 and diagnostics can well reproduce the spatial distribution of CAT potential. The probability of CAT potential is expected to increase over most East Asia between 35°N and 50°N, Southeast China, western Pacific, and North India in the future. The CAT potential that significantly affects aviation safety shows a remarkable increase over North and Northeast China, part of East China, and Tibet‐Plateau. In the whole domain of East Asia, the multi‐diagnostics ensemble‐average frequency increase is 6.9% for light CAT (with an intra‐ensemble range of 4.1–18%), 9.1% (5.0–24%) for light‐to‐moderate CAT, 12% (5.9–26%) for moderate CAT, 13% (7.2–29%) for moderate‐to‐severe CAT, and 15% (8.5–33%) for severe CAT. Stronger CAT is more likely to happen, which would be a constant threat, although greater scatter exists among these diagnostics, which implies the uncertainties are also significant in the projection.

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Objective verification of World Area Forecast Centre clear air turbulence forecasts

Cited by 46 publications

References 9 publications

An ensemble based turbulence forecasting system

An ensemble based turbulence forecasting system

Aviation Turbulence: Dynamics, Forecasting, and Response to Climate Change

Regional downscaled future change of clear‐air turbulence over East Asia under RCP8.5 scenario within the CORDEX‐EA‐II project

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