Search Results

You are looking at 1 - 9 of 9 items for

  • Author or Editor: Andrew J. Charlton-Perez x
  • All content x
Clear All Modify Search
Andrew J. Charlton-Perez and Alan O’Neill

Abstract

Long decorrelation time scales of the annular mode are observed in the lower stratosphere. This study uses a simple dynamical model, which has been used extensively to study stratosphere–troposphere coupling to investigate the origin of the long dynamical time scales. Several long runs of the model are completed, with different imposed thermal damping time scales in the stratosphere. The dynamical time scales of the annular mode are found to be largely insensitive to the input thermal damping time scales, producing similar dynamical time scales in all cases below 50 hPa. This result suggests that the hypothesis that long time scales in the lower stratosphere are due to long radiative time scales in this region is false.

Full access
Andrew J. Charlton-Perez and Lorenzo M. Polvani
Full access
Daniel M. Mitchell, Andrew J. Charlton-Perez, and Lesley J. Gray

Abstract

The mean state, variability, and extreme variability of the stratospheric polar vortices, with an emphasis on the Northern Hemisphere (NH) vortex, are examined using two-dimensional moment analysis and extreme value theory (EVT). The use of moments as an analysis tool gives rise to information about the vortex area, centroid latitude, aspect ratio, and kurtosis. The application of EVT to these moment-derived quantities allows the extreme variability of the vortex to be assessed. The data used for this study are 40-yr ECMWF Re-Analysis (ERA-40) potential vorticity fields on interpolated isentropic surfaces that range from 450 to 1450 K.

Analyses show that the most extreme vortex variability occurs most commonly in late January and early February, consistent with when most planetary wave driving from the troposphere is observed. Composites around sudden stratospheric warming (SSW) events reveal that the moment diagnostics evolve in statistically different ways between vortex splitting events and vortex displacement events, in contrast to the traditional diagnostics. Histograms of the vortex diagnostics on the 850-K (~10 hPa) surface over the 1958–2001 period are fitted with parametric distributions and show that SSW events constitute the majority of data in the tails of the distributions. The distribution of each diagnostic is computed on various surfaces throughout the depth of the stratosphere; it shows that in general the vortex becomes more circular with higher filamentation at the upper levels. The Northern and Southern Hemisphere (SH) vortices are also compared through the analysis of their respective vortex diagnostics, confirming that the SH vortex is less variable and lacks extreme events compared to the NH vortex. Finally, extreme value theory is used to statistically model the vortex diagnostics and make inferences about the underlying dynamics of the polar vortices.

Full access
Kieran J. Lynch, David J. Brayshaw, and Andrew Charlton-Perez

Abstract

Analysis of the forecasts and hindcasts from the ECMWF 32-day forecast model reveals that there is statistically significant skill in predicting weekly mean wind speeds over areas of Europe at lead times of at least 14–20 days. Previous research on wind speed predictability has focused on the short- to medium-range time scales, typically finding that forecasts lose all skill by the later part of the medium-range forecast. To the authors’ knowledge, this research is the first to look beyond the medium-range time scale by taking weekly mean wind speeds, instead of averages at hourly or daily resolution, for the ECMWF monthly forecasting system. It is shown that the operational forecasts have high levels of correlation (~0.6) between the forecasts and observations over the winters of 2008–12 for some areas of Europe. Hindcasts covering 20 winters show a more modest level of correlation but are still skillful. Additional analysis examines the probabilistic skill for the United Kingdom with the application of wind power forecasting in mind. It is also shown that there is forecast “value” for end users (operating in a simple cost/loss ratio decision-making framework). End users that are sensitive to winter wind speed variability over the United Kingdom, Germany, and some other areas of Europe should therefore consider forecasts beyond the medium-range time scale as it is clear there is useful information contained within the forecast.

Full access
Daniel M. Mitchell, Lesley J. Gray, James Anstey, Mark P. Baldwin, and Andrew J. Charlton-Perez

Abstract

A strong link exists between stratospheric variability and anomalous weather patterns at the earth’s surface. Specifically, during extreme variability of the Arctic polar vortex termed a “weak vortex event,” anomalies can descend from the upper stratosphere to the surface on time scales of weeks. Subsequently the outbreak of cold-air events have been noted in high northern latitudes, as well as a quadrupole pattern in surface temperature over the Atlantic and western European sectors, but it is currently not understood why certain events descend to the surface while others do not. This study compares a new classification technique of weak vortex events, based on the distribution of potential vorticity, with that of an existing technique and demonstrates that the subdivision of such events into vortex displacements and vortex splits has important implications for tropospheric weather patterns on weekly to monthly time scales. Using reanalysis data it is found that vortex splitting events are correlated with surface weather and lead to positive temperature anomalies over eastern North America of more than 1.5 K, and negative anomalies over Eurasia of up to −3 K. Associated with this is an increase in high-latitude blocking in both the Atlantic and Pacific sectors and a decrease in European blocking. The corresponding signals are weaker during displacement events, although ultimately they are shown to be related to cold-air outbreaks over North America. Because of the importance of stratosphere–troposphere coupling for seasonal climate predictability, identifying the type of stratospheric variability in order to capture the correct surface response will be necessary.

Full access
Kelsey J. Mulder, Matthew Lickiss, Natalie Harvey, Alison Black, Andrew Charlton-Perez, Helen Dacre, and Rachel McCloy

Abstract

During volcanic eruptions, Volcanic Ash Advisory Centres issue ash advisories for aviation showing the forecasted outermost extent of the ash cloud. During the 2010 Icelandic volcano Eyjafjallajökull eruption, the Met Office produced supplementary forecasts of quantitative ash concentration, due to demand from airlines. Additionally, satellite retrievals of estimated volcanic ash concentration are now available. To test how these additional graphical representations of volcanic ash affect flight decisions, whether users infer uncertainty in graphical forecasts of volcanic ash, and how decisions are made when given conflicting forecasts, a survey was conducted of 25 delegates representing U.K. research and airline operations dealing with volcanic ash. Respondents were more risk seeking with safer flight paths and risk averse with riskier flight paths when given location and concentration forecasts compared to when given only the outermost extent of the ash. Respondents representing operations were more risk seeking than respondents representing research. Additionally, most respondents’ hand-drawn no-fly zones were larger than the areas of unsafe ash concentrations in the forecasts. This conservatism implies that respondents inferred uncertainty from the volcanic ash concentration forecasts. When given conflicting forecasts, respondents became more conservative than when given a single forecast. The respondents were also more risk seeking with high-risk flight paths and more risk averse with low-risk flight paths when given conflicting forecasts than when given a single forecast. The results show that concentration forecasts seem to reduce flight cancellations while maintaining safety. Open discussions with the respondents suggested that definitions of uncertainty may differ between research and operations.

Full access
Daniel M. Mitchell, Scott M. Osprey, Lesley J. Gray, Neal Butchart, Steven C. Hardiman, Andrew J. Charlton-Perez, and Peter Watson

Abstract

With extreme variability of the Arctic polar vortex being a key link for stratosphere–troposphere influences, its evolution into the twenty-first century is important for projections of changing surface climate in response to greenhouse gases. Variability of the stratospheric vortex is examined using a state-of-the-art climate model and a suite of specifically developed vortex diagnostics. The model has a fully coupled ocean and a fully resolved stratosphere. Analysis of the standard stratospheric zonal mean wind diagnostic shows no significant increase over the twenty-first century in the number of major sudden stratospheric warmings (SSWs) from its historical value of 0.7 events per decade, although the monthly distribution of SSWs does vary, with events becoming more evenly dispersed throughout the winter. However, further analyses using geometric-based vortex diagnostics show that the vortex mean state becomes weaker, and the vortex centroid is climatologically more equatorward by up to 2.5°, especially during early winter. The results using these diagnostics not only characterize the vortex structure and evolution but also emphasize the need for vortex-centric diagnostics over zonally averaged measures. Finally, vortex variability is subdivided into wave-1 (displaced) and -2 (split) components, and it is implied that vortex displacement events increase in frequency under climate change, whereas little change is observed in splitting events.

Full access
Daniel M. Mitchell, Scott M. Osprey, Lesley J. Gray, Neal Butchart, Steven C. Hardiman, Andrew J. Charlton-Perez, and Peter Watson
Full access
David C. Leon, Jeffrey R. French, Sonia Lasher-Trapp, Alan M. Blyth, Steven J. Abel, Susan Ballard, Andrew Barrett, Lindsay J. Bennett, Keith Bower, Barbara Brooks, Phil Brown, Cristina Charlton-Perez, Thomas Choularton, Peter Clark, Chris Collier, Jonathan Crosier, Zhiqiang Cui, Seonaid Dey, David Dufton, Chloe Eagle, Michael J. Flynn, Martin Gallagher, Carol Halliwell, Kirsty Hanley, Lee Hawkness-Smith, Yahui Huang, Graeme Kelly, Malcolm Kitchen, Alexei Korolev, Humphrey Lean, Zixia Liu, John Marsham, Daniel Moser, John Nicol, Emily G. Norton, David Plummer, Jeremy Price, Hugo Ricketts, Nigel Roberts, Phil D. Rosenberg, David Simonin, Jonathan W. Taylor, Robert Warren, Paul I. Williams, and Gillian Young

Abstract

The Convective Precipitation Experiment (COPE) was a joint U.K.–U.S. field campaign held during the summer of 2013 in the southwest peninsula of England, designed to study convective clouds that produce heavy rain leading to flash floods. The clouds form along convergence lines that develop regularly as a result of the topography. Major flash floods have occurred in the past, most famously at Boscastle in 2004. It has been suggested that much of the rain was produced by warm rain processes, similar to some flash floods that have occurred in the United States. The overarching goal of COPE is to improve quantitative convective precipitation forecasting by understanding the interactions of the cloud microphysics and dynamics and thereby to improve numerical weather prediction (NWP) model skill for forecasts of flash floods. Two research aircraft, the University of Wyoming King Air and the U.K. BAe 146, obtained detailed in situ and remote sensing measurements in, around, and below storms on several days. A new fast-scanning X-band dual-polarization Doppler radar made 360° volume scans over 10 elevation angles approximately every 5 min and was augmented by two Met Office C-band radars and the Chilbolton S-band radar. Detailed aerosol measurements were made on the aircraft and on the ground. This paper i) provides an overview of the COPE field campaign and the resulting dataset, ii) presents examples of heavy convective rainfall in clouds containing ice and also in relatively shallow clouds through the warm rain process alone, and iii) explains how COPE data will be used to improve high-resolution NWP models for operational use.

Full access