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Christopher M. Fuhrmann, Charles E. Konrad II, Margaret M. Kovach, Jordan T. McLeod, William G. Schmitz, and P. Grady Dixon

Abstract

The calendar year 2011 was an extraordinary year for tornadoes across the United States, as it marked the second highest annual number of tornadoes since 1950 and was the deadliest tornado year since 1936. Most of the fatalities in 2011 occurred in a series of outbreaks, highlighted by a particularly strong outbreak across the southeastern United States in late April and a series of outbreaks over the Great Plains and Midwest regions in late May, which included a tornado rated as a category 5 event on the enhanced Fujita scale (EF5) that devastated the town of Joplin, Missouri. While most tornado-related fatalities often occur in outbreaks, very few studies have examined the climatological characteristics of outbreaks, particularly those of varying strength. In this study a straightforward metric to assess the strength, or physical magnitude, of tornado outbreaks east of the Rocky Mountains from 1973 to 2010 is developed. This measure of outbreak strength, which integrates the intensity of tornadoes [Fujita (F)/EF-scale rating] over their distance traveled (pathlength), is more highly correlated with injuries and fatalities than other commonly used variables, such as the number of significant tornadoes, and is therefore more reflective of the potential threat of outbreaks to human life. All outbreaks are then ranked according to this metric and their climatological characteristics are examined, with comparisons made to all other tornadoes not associated with outbreaks. The results of the ranking scheme are also compared to those of previous studies, while the strongest outbreaks from 2011 are ranked among other outbreaks in the modern record, including the April 1974 Super Outbreak.

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David M. Schultz, Anna L. Beukenhorst, Belay Birlie Yimer, Louise Cook, Huai Leng Pisaniello, Thomas House, Carolyn Gamble, Jamie C. Sergeant, John McBeth, and William G. Dixon

Abstract

The belief that weather influences people’s health has been prevalent for millennia. Recent studies on the relationship between weather and pain for those who suffer from chronic pain remain indeterminate, with some studies finding strong effects and others finding no effects; most studies face limitations to their study design or dataset size. To address these limitations, a U.K.-wide smartphone study Cloudy with a Chance of Pain was conducted over 15 months with 10,584 citizen scientists who suffer from chronic pain, producing the largest dataset both in duration and number of participants. Compared to other similar citizen-science studies, our retention of participants was substantially better, with 15% still entering data nearly every day after 200 days. Analysis of the dataset using synoptic climatology and compositing revealed the daily weather associated with a prevalence of high pain and low pain across the population. Specifically, our results indicate that the top 10% of days with a high percentage of participants (about 20%) experiencing a pain event (represented here by a +1 change or greater in their pain level on a 5-point scale; referred to as a high-pain day) were associated with below-normal pressure, above-normal humidity, higher precipitation rate, and stronger wind. In contrast, the bottom 10% of days with a small percentage of participants (about 10%) experiencing a pain event (a low-pain day) were associated with above-normal pressure, below-normal humidity, lower precipitation rate, and weaker wind. Thus, these synoptic weather patterns support the beliefs of many participants who said that low pressure—and its accompanying weather—was associated with a pain event.

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David M. Schultz, Anna L. Beukenhorst, Belay Birlie Yimer, Louise Cook, Huai Leng Pisaniello, Thomas House, Carolyn Gamble, Jamie C. Sergeant, John McBeth, and William G. Dixon
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Liwei Jia, Xiaosong Yang, Gabriel A. Vecchi, Richard G. Gudgel, Thomas L. Delworth, Anthony Rosati, William F. Stern, Andrew T. Wittenberg, Lakshmi Krishnamurthy, Shaoqing Zhang, Rym Msadek, Sarah Kapnick, Seth Underwood, Fanrong Zeng, Whit G. Anderson, Venkatramani Balaji, and Keith Dixon

Abstract

This study demonstrates skillful seasonal prediction of 2-m air temperature and precipitation over land in a new high-resolution climate model developed by the Geophysical Fluid Dynamics Laboratory and explores the possible sources of the skill. The authors employ a statistical optimization approach to identify the most predictable components of seasonal mean temperature and precipitation over land and demonstrate the predictive skill of these components. First, the improved skill of the high-resolution model over the previous lower-resolution model in seasonal prediction of the Niño-3.4 index and other aspects of interest is shown. Then, the skill of temperature and precipitation in the high-resolution model for boreal winter and summer is measured, and the sources of the skill are diagnosed. Last, predictions are reconstructed using a few of the most predictable components to yield more skillful predictions than the raw model predictions. Over three decades of hindcasts, the two most predictable components of temperature are characterized by a component that is likely due to changes in external radiative forcing in boreal winter and summer and an ENSO-related pattern in boreal winter. The most predictable components of precipitation in both seasons are very likely ENSO-related. These components of temperature and precipitation can be predicted with significant correlation skill at least 9 months in advance. The reconstructed predictions using only the first few predictable components from the model show considerably better skill relative to observations than raw model predictions. This study shows that the use of refined statistical analysis and a high-resolution dynamical model leads to significant skill in seasonal predictions of 2-m air temperature and precipitation over land.

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Xiaosong Yang, Anthony Rosati, Shaoqing Zhang, Thomas L. Delworth, Rich G. Gudgel, Rong Zhang, Gabriel Vecchi, Whit Anderson, You-Soon Chang, Timothy DelSole, Keith Dixon, Rym Msadek, William F. Stern, Andrew Wittenberg, and Fanrong Zeng

Abstract

The decadal predictability of sea surface temperature (SST) and 2-m air temperature (T2m) in the Geophysical Fluid Dynamics Laboratory (GFDL) decadal hindcasts, which are part of the Fifth Coupled Model Intercomparison Project experiments, has been investigated using an average predictability time (APT) analysis. Comparison of retrospective forecasts initialized using the GFDL Ensemble Coupled Data Assimilation system with uninitialized historical forcing simulations using the same model allows identification of the internal multidecadal pattern (IMP) for SST and T2m. The IMP of SST is characterized by an interhemisphere dipole, with warm anomalies centered in the North Atlantic subpolar gyre region and North Pacific subpolar gyre region, and cold anomalies centered in the Antarctic Circumpolar Current region. The IMP of T2m is characterized by a general bipolar seesaw, with warm anomalies centered in Greenland and cold anomalies centered in Antarctica. The retrospective prediction skill of the initialized system, verified against independent observational datasets, indicates that the IMP of SST may be predictable up to 4 (10) yr lead time at 95% (90%) significance level, and the IMP of T2m may be predictable up to 2 (10) yr at the 95% (90%) significance level. The initialization of multidecadal variations of northward oceanic heat transport in the North Atlantic significantly improves the predictive skill of the IMP. The dominant roles of oceanic internal dynamics in decadal prediction are further elucidated by fixed-forcing experiments in which radiative forcing is returned abruptly to 1961 values. These results point toward the possibility of meaningful decadal climate outlooks using dynamical coupled models if they are appropriately initialized from a sustained climate observing system.

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Ian M. Brooks, Margaret J. Yelland, Robert C. Upstill-Goddard, Philip D. Nightingale, Steve Archer, Eric d'Asaro, Rachael Beale, Cory Beatty, Byron Blomquist, A. Anthony Bloom, Barbara J. Brooks, John Cluderay, David Coles, John Dacey, Michael Degrandpre, Jo Dixon, William M. Drennan, Joseph Gabriele, Laura Goldson, Nick Hardman-Mountford, Martin K. Hill, Matt Horn, Ping-Chang Hsueh, Barry Huebert, Gerrit De Leeuw, Timothy G. Leighton, Malcolm Liddicoat, Justin J. N. Lingard, Craig Mcneil, James B. Mcquaid, Ben I. Moat, Gerald Moore, Craig Neill, Sarah J. Norris, Simon O'Doherty, Robin W. Pascal, John Prytherch, Mike Rebozo, Erik Sahlee, Matt Salter, Ute Schuster, Ingunn Skjelvan, Hans Slagter, Michael H. Smith, Paul D. Smith, Meric Srokosz, John A. Stephens, Peter K. Taylor, Maciej Telszewski, Roisin Walsh, Brian Ward, David K. Woolf, Dickon Young, and Henk Zemmelink

Abstract

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Ian M. Brooks, Margaret J. Yelland, Robert C. Upstill-Goddard, Philip D. Nightingale, Steve Archer, Eric d'Asaro, Rachael Beale, Cory Beatty, Byron Blomquist, A. Anthony Bloom, Barbara J. Brooks, John Cluderay, David Coles, John Dacey, Michael DeGrandpre, Jo Dixon, William M. Drennan, Joseph Gabriele, Laura Goldson, Nick Hardman-Mountford, Martin K. Hill, Matt Horn, Ping-Chang Hsueh, Barry Huebert, Gerrit de Leeuw, Timothy G. Leighton, Malcolm Liddicoat, Justin J. N. Lingard, Craig McNeil, James B. McQuaid, Ben I. Moat, Gerald Moore, Craig Neill, Sarah J. Norris, Simon O'Doherty, Robin W. Pascal, John Prytherch, Mike Rebozo, Erik Sahlee, Matt Salter, Ute Schuster, Ingunn Skjelvan, Hans Slagter, Michael H. Smith, Paul D. Smith, Meric Srokosz, John A. Stephens, Peter K. Taylor, Maciej Telszewski, Roisin Walsh, Brian Ward, David K. Woolf, Dickon Young, and Henk Zemmelink

As part of the U.K. contribution to the international Surface Ocean-Lower Atmosphere Study, a series of three related projects—DOGEE, SEASAW, and HiWASE—undertook experimental studies of the processes controlling the physical exchange of gases and sea spray aerosol at the sea surface. The studies share a common goal: to reduce the high degree of uncertainty in current parameterization schemes. The wide variety of measurements made during the studies, which incorporated tracer and surfactant release experiments, included direct eddy correlation fluxes, detailed wave spectra, wind history, photographic retrievals of whitecap fraction, aerosolsize spectra and composition, surfactant concentration, and bubble populations in the ocean mixed layer. Measurements were made during three cruises in the northeast Atlantic on the RRS Discovery during 2006 and 2007; a fourth campaign has been making continuous measurements on the Norwegian weather ship Polarfront since September 2006. This paper provides an overview of the three projects and some of the highlights of the measurement campaigns.

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