Search Results

You are looking at 1 - 2 of 2 items for :

  • Author or Editor: Clark Evans x
  • Bulletin of the American Meteorological Society x
  • Refine by Access: Content accessible to me x
Clear All Modify Search
Clark Evans
,
Heather M. Archambault
,
Jason M. Cordeira
,
Cody Fritz
,
Thomas J. Galarneau Jr.
,
Saska Gjorgjievska
,
Kyle S. Griffin
,
Alexandria Johnson
,
William A. Komaromi
,
Sarah Monette
,
Paytsar Muradyan
,
Brian Murphy
,
Michael Riemer
,
John Sears
,
Daniel Stern
,
Brian Tang
, and
Segayle Thompson

The Pre-Depression Investigation of Cloud-systems in the Tropics (PREDICT) field experiment successfully gathered data from four developing and four decaying/nondeveloping tropical disturbances over the tropical North Atlantic basin between 15 August and 30 September 2010. The invaluable roles played by early career scientists (ECSs) throughout the campaign helped make possible the successful execution of the field program's mission to investigate tropical cyclone formation. ECSs provided critical meteorological information— often obtained from novel ECS-created products—during daily weather briefings that were used by the principal investigators in making mission planning decisions. Once a Gulfstream V (G-V) flight mission was underway, ECSs provided nowcasting support, relaying information that helped the mission scientists to steer clear of potential areas of turbulence aloft. Data from these missions, including dropsonde and GPS water vapor profiler data, were continually obtained, processed, and quality-controlled by ECSs. The dropsonde data provided National Hurricane Center forecasters and PREDICT mission scientists with real-time information regarding the characteristics of tropical disturbances. These data and others will serve as the basis for multiple ECS-led research topics over the years to come and are expected to provide new insights into the tropical cyclone formation process. PREDICT also provided invaluable educational and professional development experiences for ECSs, including the opportunity to critically evaluate observational evidence for tropical cyclone development theories and networking opportunities with their peers and established scientists in the field.

Full access
Morris L. Weisman
,
Robert J. Trapp
,
Glen S. Romine
,
Chris Davis
,
Ryan Torn
,
Michael Baldwin
,
Lance Bosart
,
John Brown
,
Michael Coniglio
,
David Dowell
,
A. Clark Evans
,
Thomas J. Galarneau Jr.
,
Julie Haggerty
,
Terry Hock
,
Kevin Manning
,
Paul Roebber
,
Pavel Romashkin
,
Russ Schumacher
,
Craig S. Schwartz
,
Ryan Sobash
,
David Stensrud
, and
Stanley B. Trier

Abstract

The Mesoscale Predictability Experiment (MPEX) was conducted from 15 May to 15 June 2013 in the central United States. MPEX was motivated by the basic question of whether experimental, subsynoptic observations can extend convective-scale predictability and otherwise enhance skill in short-term regional numerical weather prediction.

Observational tools for MPEX included the National Science Foundation (NSF)–National Center for Atmospheric Research (NCAR) Gulfstream V aircraft (GV), which featured the Airborne Vertical Atmospheric Profiling System mini-dropsonde system and a microwave temperature-profiling (MTP) system as well as several ground-based mobile upsonde systems. Basic operations involved two missions per day: an early morning mission with the GV, well upstream of anticipated convective storms, and an afternoon and early evening mission with the mobile sounding units to sample the initiation and upscale feedbacks of the convection.

A total of 18 intensive observing periods (IOPs) were completed during the field phase, representing a wide spectrum of synoptic regimes and convective events, including several major severe weather and/or tornado outbreak days. The novel observational strategy employed during MPEX is documented herein, as is the unique role of the ensemble modeling efforts—which included an ensemble sensitivity analysis—to both guide the observational strategies and help address the potential impacts of such enhanced observations on short-term convective forecasting. Preliminary results of retrospective data assimilation experiments are discussed, as are data analyses showing upscale convective feedbacks.

Full access