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John M. Hanesiak
,
Ronald E. Stewart
,
Kit K. Szeto
,
David R. Hudak
, and
Henry G. Leighton

Abstract

On 30 September 1994 an Arctic low pressure system passed over the southern Beaufort Sea area of northern Canada and research aircraft observations were made within and around the warm front of the storm. This study is unique in that the warm front contained subzero centigrade temperatures across the entire frontal region. The overall structure of the warm front and surrounding region was similar to midlatitude storms; however, the precipitation rates, liquid water content magnitudes, horizontal and vertical winds, vertical wind shear, turbulence, and thermal advection were very weak. In addition, a low-level jet and cloud bands were aligned parallel to the warm front, near-neutral stability occurred within and around the front, and conditional symmetric instability was likely occurring. A steep frontal region resulted from strong Coriolis influences that in turn limited the amount of cloud and precipitation ahead of the system. The precipitation efficiency of the storm was high (60%) but is believed to be highly dependent on the stage of development. The mesoscale frontogenetic forcing was primarily controlled by the tilting of isentropic surfaces with confluence/convergence being the secondary influence. Sublimation contributions may have been large in the earlier stages of storm development. Satellite and aircraft radiometers underestimated cloud top heights by as much as 4 km and this was mostly due to the near transparency of the lofted ice layer in the upper portion of the storm. Maximum surface solar radiation deficits ranged between 91 W m−2 and 187 W m−2 at two surface observing sites. This common type of cloud system must have a major impact on the water and energy cycles of northern Canada in the autumn and therefore must be well accounted for within climate models.

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Julian Brimelow
,
Kit Szeto
,
Barrie Bonsal
,
John Hanesiak
,
Bohdan Kochtubajda
,
Fraser Evans
, and
Ronald Stewart

Abstract

In the spring and early summer of 2011, the Assiniboine River basin in Canada experienced an extreme flood that was unprecedented in terms of duration and severity. The flood had significant socioeconomic impacts and caused over $1 billion (Canadian dollars) in damage. Contrary to what one might expect for such an extreme flood, individual precipitation events before and during the 2011 flood were not extreme; instead, it was the cumulative impact and timing of precipitation events going back to the summer of 2010 that played a key role in the 2011 flood. The summer and fall of 2010 were exceptionally wet, resulting in above-normal soil moisture levels at the time of freeze-up. This was followed by record high snow water equivalent values in March and April 2011. Cold temperatures in March delayed the spring melt, resulting in the above-average spring freshet occurring close to the onset of heavy rains in May and June. The large-scale atmospheric flow during May and June 2011 favored increased cyclone activity in the region, which produced an anomalously large number of heavy rainfall events over the basin. All of these factors combined generated extreme flooding. Japanese 55-year Reanalysis Project (JRA-55) data are used to quantify the relative importance of snowmelt and spring precipitation in contributing to the unprecedented flood and to demonstrate how the 2011 flood was unique compared to previous floods. This study can be used to validate and improve flood forecasting techniques over this important basin; the findings also raise important questions regarding floods in a changing climate over basins that experience pluvial and nival flooding.

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Tammy M. Weckwerth
,
John Hanesiak
,
James W. Wilson
,
Stanley B. Trier
,
Samuel K. Degelia
,
William A. Gallus Jr.
,
Rita D. Roberts
, and
Xuguang Wang

Abstract

Nocturnal convection initiation (NCI) is more difficult to anticipate and forecast than daytime convection initiation (CI). A major component of the Plains Elevated Convection at Night (PECAN) field campaign in the U.S. Great Plains was to intensively sample NCI and its near environment. In this article, we summarize NCI types observed during PECAN: 1 June–16 July 2015. These NCI types, classified using PECAN radar composites, are associated with 1) frontal overrunning, 2) the low-level jet (LLJ), 3) a preexisting mesoscale convective system (MCS), 4) a bore or density current, and 5) a nocturnal atmosphere lacking a clearly observed forcing mechanism (pristine). An example and description of each of these different types of PECAN NCI events are presented. The University of Oklahoma real-time 4-km Weather Research and Forecasting (WRF) Model ensemble forecast runs illustrate that the above categories having larger-scale organization (e.g., NCI associated with frontal overrunning and NCI near a preexisting MCS) were better forecasted than pristine. Based on current knowledge and data from PECAN, conceptual models summarizing key environmental features are presented and physical processes underlying the development of each of these different types of NCI events are discussed.

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Neil M. Taylor
,
David M. L. Sills
,
John M. Hanesiak
,
Jason A. Milbrandt
,
Craig D. Smith
,
Geoff S. Strong
,
Susan H. Skone
,
Patrick J. McCarthy
, and
Julian C. Brimelow

Severe thunderstorms are a common occurrence in summer on the Canadian prairies, with a large number originating along the Alberta, Canada, foothills, just east of the Rocky Mountains. Most of these storms move eastward to affect the Edmonton–Calgary corridor, one of the most densely populated and fastest-growing regions in Canada. Previous studies in the United States, Europe, and Canada have stressed the importance of mesoscale features in thunderstorm development. However, such processes cannot be adequately resolved using operational observation networks in many parts of Canada. Current conceptual models for severe storm outbreaks in Alberta were developed almost 20 years ago and do not focus explicitly on mesoscale boundaries that are now known to be important for thunderstorm development.

The Understanding Severe Thunderstorms and Alber ta Boundary Layers Experiment (UNSTABLE) is a field and modeling study aiming to improve our understanding of the processes associated with the initiation of severe thunderstorms, to refine associated conceptual models, and to assess the ability of convectivescale NWP models to simulate relevant physical processes. As part of UNSTABLE in 2008, Environment Canada and university scientists conducted a pilot field experiment over the Alberta foothills to investigate mesoscale processes associated with the development of severe thunderstorms. Networks of fixed and mobile surface and upper-air instrumentation provided observations of the atmospheric boundary layer at a level of detail never before seen in this region. Preliminary results include the most complete documentation of a dryline in Canada and an analysis of variability in boundary layer evolution across adjacent forest and crop vegetation areas. Convective-scale NWP simulations suggest that although additional information on convective mode may be provided, there is limited benefit overall to downscaling to smaller grid spacing without assimilation of mesoscale observations.

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John Hanesiak
,
Ronald Stewart
,
Peter Taylor
,
Kent Moore
,
David Barber
,
Gordon McBean
,
Walter Strapp
,
Mengistu Wolde
,
Ron Goodson
,
Edward Hudson
,
David Hudak
,
John Scott
,
George Liu
,
Justin Gilligan
,
Sumita Biswas
,
Danielle Desjardins
,
Robyn Dyck
,
Shannon Fargey
,
Robert Field
,
Gabrielle Gascon
,
Mark Gordon
,
Heather Greene
,
Carling Hay
,
William Henson
,
Klaus Hochheim
,
Alex Laplante
,
Rebekah Martin
,
Marna Albarran Melzer
, and
Shunli Zhang

The Storm Studies in the Arctic (STAR) network (2007–2010) conducted a major meteorological field project from 10 October–30 November 2007 and in February 2008, focused on southern Baffin Island, Nunavut, Canada—a region that experiences intense autumn and winter storms. The STAR research program is concerned with the documentation, better understanding, and improved prediction of meteorological and related hazards in the Arctic, including their modification by local topography and land–sea ice–ocean transitions, and their effect on local communities. To optimize the applicability of STAR network science, we are also communicating with the user community (northern communities and government sectors). STAR has obtained a variety of surface-based and unique research aircraft field measurements, high-resolution modeling products, and remote sensing measurements (including Cloudsat) as part of its science strategy and has the first arctic Cloudsat validation dataset. In total, 14 research flights were flown between 5 and 30 November 2007, with eight coinciding with Cloudsat passes. The aircraft was outfitted with many instruments that measure cloud microphysical parameters and three unique Doppler-polarized airborne radars operating in Ka, X and W bands. The project area, instrumentation platforms, real-time forecasts, storm cases, and results thus far are discussed in this article. A number of synoptic and mesoscale features were sampled—such as fronts, upslope/terrain-enhanced precipitation, convective precipitation, and boundary layer clouds/precipitation—as well as targeted Cloudsat missions. One significant and unique event included a research flight into an intense high-latitude storm leftover from Hurricane Noel—an intense tropical and extratropical disturbance that caused many fatalities in the tropics and extensive damage on the eastern North American seaboard. These synoptic and mesoscale features and high-latitude storms will be studied in detail over the next several years. It is anticipated that scientific progress in better understanding the nature of these arctic storms and their hazards will lead to improved conceptual models and improved prediction of such events.

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Bart Geerts
,
David Parsons
,
Conrad L. Ziegler
,
Tammy M. Weckwerth
,
Michael I. Biggerstaff
,
Richard D. Clark
,
Michael C. Coniglio
,
Belay B. Demoz
,
Richard A. Ferrare
,
William A. Gallus Jr.
,
Kevin Haghi
,
John M. Hanesiak
,
Petra M. Klein
,
Kevin R. Knupp
,
Karen Kosiba
,
Greg M. McFarquhar
,
James A. Moore
,
Amin R. Nehrir
,
Matthew D. Parker
,
James O. Pinto
,
Robert M. Rauber
,
Russ S. Schumacher
,
David D. Turner
,
Qing Wang
,
Xuguang Wang
,
Zhien Wang
, and
Joshua Wurman

Abstract

The central Great Plains region in North America has a nocturnal maximum in warm-season precipitation. Much of this precipitation comes from organized mesoscale convective systems (MCSs). This nocturnal maximum is counterintuitive in the sense that convective activity over the Great Plains is out of phase with the local generation of CAPE by solar heating of the surface. The lower troposphere in this nocturnal environment is typically characterized by a low-level jet (LLJ) just above a stable boundary layer (SBL), and convective available potential energy (CAPE) values that peak above the SBL, resulting in convection that may be elevated, with source air decoupled from the surface. Nocturnal MCS-induced cold pools often trigger undular bores and solitary waves within the SBL. A full understanding of the nocturnal precipitation maximum remains elusive, although it appears that bore-induced lifting and the LLJ may be instrumental to convection initiation and the maintenance of MCSs at night.

To gain insight into nocturnal MCSs, their essential ingredients, and paths toward improving the relatively poor predictive skill of nocturnal convection in weather and climate models, a large, multiagency field campaign called Plains Elevated Convection At Night (PECAN) was conducted in 2015. PECAN employed three research aircraft, an unprecedented coordinated array of nine mobile scanning radars, a fixed S-band radar, a unique mesoscale network of lower-tropospheric profiling systems called the PECAN Integrated Sounding Array (PISA), and numerous mobile-mesonet surface weather stations. The rich PECAN dataset is expected to improve our understanding and prediction of continental nocturnal warm-season precipitation. This article provides a summary of the PECAN field experiment and preliminary findings.

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