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Amy H. Butler, Dian J. Seidel, Steven C. Hardiman, Neal Butchart, Thomas Birner, and Aaron Match

Abstract

Sudden stratospheric warmings (SSWs) are large, rapid temperature rises in the winter polar stratosphere, occurring predominantly in the Northern Hemisphere. Major SSWs are also associated with a reversal of the climatological westerly zonal-mean zonal winds. Circulation anomalies associated with SSWs can descend into the troposphere with substantial surface weather impacts, such as wintertime extreme cold air outbreaks. After their discovery in 1952, SSWs were classified by the World Meteorological Organization. An examination of literature suggests that a single, original reference for an exact definition of SSWs is elusive, but in many references a definition involves the reversal of the meridional temperature gradient and, for major warmings, the reversal of the zonal circulation poleward of 60° latitude at 10 hPa.

Though versions of this definition are still commonly used to detect SSWs, the details of the definition and its implementation remain ambiguous. In addition, other SSW definitions have been used in the last few decades, resulting in inconsistent classification of SSW events. We seek to answer the questions: How has the SSW definition changed, and how sensitive is the detection of SSWs to the definition used? For what kind of analysis is a “standard” definition useful? We argue that a standard SSW definition is necessary for maintaining a consistent and robust metric to assess polar stratospheric wintertime variability in climate models and other statistical applications. To provide a basis for, and to encourage participation in, a communitywide discussion currently underway, we explore what criteria are important for a standard definition and propose possible ways to update the definition.

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Janet Sprintall, Victoria J. Coles, Kevin A. Reed, Amy H. Butler, Gregory R. Foltz, Stephen G. Penny, and Hyodae Seo

Abstract

Process studies are designed to improve our understanding of poorly described physical processes that are central to the behavior of the climate system. They typically include coordinated efforts of intensive field campaigns in the atmosphere and/or ocean to collect a carefully planned set of in situ observations. Ideally the observational portion of a process study is paired with numerical modeling efforts that lead to better representation of a poorly simulated or previously neglected physical process in operational and research models. This article provides a framework of best practices to help guide scientists in carrying out more productive, collaborative, and successful process studies. Topics include the planning and implementation of a process study and the associated web of logistical challenges; the development of focused science goals and testable hypotheses; and the importance of assembling an integrated and compatible team with a diversity of social identity, gender, career stage, and scientific background. Guidelines are also provided for scientific data management, dissemination, and stewardship. Above all, developing trust and continual communication within the science team during the field campaign and analysis phase are key for process studies. We consider a successful process study as one that ultimately will improve our quantitative understanding of the mechanisms responsible for climate variability and enhance our ability to represent them in climate models.

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Edwin P. Gerber, Amy Butler, Natalia Calvo, Andrew Charlton-Perez, Marco Giorgetta, Elisa Manzini, Judith Perlwitz, Lorenzo M. Polvani, Fabrizio Sassi, Adam A. Scaife, Tiffany A. Shaw, Seok-Woo Son, and Shingo Watanabe

Advances in weather and climate research have demonstrated the role of the stratosphere in the Earth system across a wide range of temporal and spatial scales. Stratospheric ozone loss has been identified as a key driver of Southern Hemisphere tropospheric circulation trends, affecting ocean currents and carbon uptake, sea ice, and possibly even the Antarctic ice sheets. Stratospheric variability has also been shown to affect short-term and seasonal forecasts, connecting the tropics and midlatitudes and guiding storm-track dynamics. The two-way interactions between the stratosphere and the Earth system have motivated the World Climate Research Programme's (WCRP) Stratospheric Processes and their Role in Climate's (SPARC) activity on Modelling the Dynamics and Variability of the Stratosphere-Troposphere System (DynVar) to investigate the impact of stratospheric dynamics and variability on climate. This assessment will be made possible by two new multimodel datasets. First, roughly 10 models with a well-resolved stratosphere are participating in the Coupled Model Intercomparison Project phase 5 (CMIP5), providing the first multimodel ensemble of climate simulations coupled from the stratopause to the sea floor. Second, the Stratosphere Resolving Historical Forecast Project (Strat-HFP) of WCRP's Climate Variability and Predictability (CLIVAR) program is forming a multimodel set of seasonal hind-casts with stratosphere-resolving models, revealing the impact of both stratospheric initial conditions and dynamics on intraseasonal prediction. The CMIP5 and Strat-HFP model datasets will offer an unprecedented opportunity to understand the role of the stratosphere in the natural and forced variability of the Earth system and to determine whether incorporating knowledge of the middle atmosphere improves seasonal forecasts and climate projections.

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Annarita Mariotti, Cory Baggett, Elizabeth A. Barnes, Emily Becker, Amy Butler, Dan C. Collins, Paul A. Dirmeyer, Laura Ferranti, Nathaniel C. Johnson, Jeanine Jones, Ben P. Kirtman, Andrea L. Lang, Andrea Molod, Matthew Newman, Andrew W. Robertson, Siegfried Schubert, Duane E. Waliser, and John Albers

Abstract

There is high demand and a growing expectation for predictions of environmental conditions that go beyond 0–14-day weather forecasts with outlooks extending to one or more seasons and beyond. This is driven by the needs of the energy, water management, and agriculture sectors, to name a few. There is an increasing realization that, unlike weather forecasts, prediction skill on longer time scales can leverage specific climate phenomena or conditions for a predictable signal above the weather noise. Currently, it is understood that these conditions are intermittent in time and have spatially heterogeneous impacts on skill, hence providing strategic windows of opportunity for skillful forecasts. Research points to such windows of opportunity, including El Niño or La Niña events, active periods of the Madden–Julian oscillation, disruptions of the stratospheric polar vortex, when certain large-scale atmospheric regimes are in place, or when persistent anomalies occur in the ocean or land surface. Gains could be obtained by increasingly developing prediction tools and metrics that strategically target these specific windows of opportunity. Across the globe, reevaluating forecasts in this manner could find value in forecasts previously discarded as not skillful. Users’ expectations for prediction skill could be more adequately met, as they are better aware of when and where to expect skill and if the prediction is actionable. Given that there is still untapped potential, in terms of process understanding and prediction methodologies, it is safe to expect that in the future forecast opportunities will expand. Process research and the development of innovative methodologies will aid such progress.

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Adrian M. Tompkins, María Inés Ortiz De Zárate, Ramiro I. Saurral, Carolina Vera, Celeste Saulo, William J. Merryfield, Michael Sigmond, Woo-Sung Lee, Johanna Baehr, Alain Braun, Amy Butler, Michel Déqué, Francisco J. Doblas-Reyes, Margaret Gordon, Adam A. Scaife, Yukiko Imada, Masayoshi Ishii, Tomoaki Ose, Ben Kirtman, Arun Kumar, Wolfgang A. Müller, Anna Pirani, Tim Stockdale, Michel Rixen, and Tamaki Yasuda
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Eun-Pa Lim, Harry H. Hendon, Amy H. Butler, David W. J. Thompson, Zachary Lawrence, Adam A. Scaife, Theodore G. Shepherd, Inna Polichtchouk, Hisashi Nakamura, Chiaki Kobayashi, Ruth Comer, Lawrence Coy, Andrew Dowdy, Rene D. Garreaud, Paul A. Newman, and Guomin Wang

Capsule Summary

During austral spring 2019 the Antarctic stratosphere experienced record-breaking warming and a near-record polar vortex weakening, resulting in predictable extreme climate conditions throughout the Southern Hemisphere through December 2019.

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E. Povl Abrahamsen, Sandra Barreira, Cecilia M. Bitz, Amy Butler, Kyle R. Clem, Steve Colwell, Lawrence Coy, Jos de Laat, Marcel D. du Plessis, Ryan L. Fogt, Helen Amanda Fricker, John Fyfe, Alex S. Gardner, Sarah T. Gille, Tessa Gorte, L. Gregor, Will Hobbs, Bryan Johnson, Eric Keenan, Linda M. Keller, Natalya A. Kramarova, Matthew A. Lazzara, Jan T. M. Lenaerts, Jan L. Lieser, Hongxing Liu, Craig S. Long, Michelle Maclennan, Robert A. Massom, François Massonnet, Matthew R. Mazloff, David Mikolajczyk, A. Narayanan, Eric R. Nash, Paul A. Newman, Irina Petropavlovskikh, Michael Pitts, Bastien Y. Queste, Phillip Reid, F. Roquet, Michelle L. Santee, Susan Strahan, Sebastiann Swart, and Lei Wang
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William J. Merryfield, Johanna Baehr, Lauriane Batté, Emily J. Becker, Amy H. Butler, Caio A. S. Coelho, Gokhan Danabasoglu, Paul A. Dirmeyer, Francisco J. Doblas-Reyes, Daniela I. V. Domeisen, Laura Ferranti, Tatiana Ilynia, Arun Kumar, Wolfgang A. Müller, Michel Rixen, Andrew W. Robertson, Doug M. Smith, Yuhei Takaya, Matthias Tuma, Frederic Vitart, Christopher J. White, Mariano S. Alvarez, Constantin Ardilouze, Hannah Attard, Cory Baggett, Magdalena A. Balmaseda, Asmerom F. Beraki, Partha S. Bhattacharjee, Roberto Bilbao, Felipe M. de Andrade, Michael J. DeFlorio, Leandro B. Díaz, Muhammad Azhar Ehsan, Georgios Fragkoulidis, Sam Grainger, Benjamin W. Green, Momme C. Hell, Johnna M. Infanti, Katharina Isensee, Takahito Kataoka, Ben P. Kirtman, Nicholas P. Klingaman, June-Yi Lee, Kirsten Mayer, Roseanna McKay, Jennifer V. Mecking, Douglas E. Miller, Nele Neddermann, Ching Ho Justin Ng, Albert Ossó, Klaus Pankatz, Simon Peatman, Kathy Pegion, Judith Perlwitz, G. Cristina Recalde-Coronel, Annika Reintges, Christoph Renkl, Balakrishnan Solaraju-Murali, Aaron Spring, Cristiana Stan, Y. Qiang Sun, Carly R. Tozer, Nicolas Vigaud, Steven Woolnough, and Stephen Yeager

Abstract

Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-ocean temperatures, and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal variability and externally forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere–ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end-user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis.

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