Project Storm

The United States experiences over 1,000 tornado’s per year; causing an average of $5 billion in damage, 80 fatalities, and over 1,500 injuries.  The most destructive and deadly tornados occur in supercells – rotating thunderstorms with a well-defined circulation called a mesocyclone. Collection and processing of in situ data pertaining to thermodynamic conditions in tornadic supercell thunderstorms is critical to enhancing severe weather forecasting and mitigating the destructive effects of these tornados.

Project Storm leverages the CU-Boulder’s proven expertise and extensive capability in nomadic, integrated collection of real-time supercell data using unmanned aircraft systems (UAS) to better predict tornadogenesis and dramatically increase Tornado Warning lead-time.  CU-Boulder collaborates with an established network of government, academic, and industry partners to improve measurement and collection of supercell data.  The CU-Boulder Earth Lab works closely with IRISS to process and distribute datasets for improved tornado forecasting techniques.

Goals of Project

  • Deployment to verify CONOPS for autonomous, integrated, multi-UAS collection of In Situ Tornadic Supercell data
  • Collaboration with NOAA/NSSL and University partners to increase understanding of the Rear-Flank Downdraft/ Forward-Flank Downdraft (RFD/FFD)-Tornado connection in Supercells
  • Data assimilation strategy with the goal to double current supercell tornado-warning lead time (15 minutes to 30 minutes) through improved warning accuracy and reduced false alarms
  • Leverage the Mobile Research Collaboratory (MRC) and CU-Boulder Earth Lab to enable in-field deployment of high-performance computing in support of real-time UAS path-planning for targeted storm observations, and data management

Primary Contact

, Professor, Aerospace Engineering Sciences (AES), Director, Integrated Remote & In Situ Sensing (IRISS), Research & Engineering Center for Unmanned Vehicles (RECUV), Aerospace Engineering Sciences (AES) | brian.argrow@colorado.edu | 303-492-5312

Researchers & Collaborators

, Professor, Aerospace Engineering Sciences (AES), Â鶹ÊÓƵ
Mission-derived unmanned aircraft systems design, high-speed & hypersonic aerodynamics, dense gas dynamics, rarefied gas dynamics

, Associate Professor, Aerospace Engineering Sciences (AES), Â鶹ÊÓƵ
Networked heterogeneous unmanned aircraft systems, optimal distributed sensing by mobile robots, controlled mobility in ad-hoc sensor networks, miniature self-deploying systems, guidance and control of unmanned aircraft in complex atmospheric phenomena

, Assistant Professor, Earth and Atmospheric Sciences, University of Nebraska Lincoln
Atmospheric convection, mesoscale processes, severe weather, instrumentation, climate diagnostics

, Associate Professor, Atmospheric Science, Texas Tech University
Severe storm dynamics and tornadogenesis, the initiation and sustenance of deep moist convection (particularly as related to High Plains drylines), radar meteorology

, PhD, Meteorologist, National Severe Storms Laboratory
Mesoscale meteorology, severe convective storms, forecasting of storms, tornadogenesis

, PhD, President, Center for Severe Weather Research
Tornadogenesis, tornado structure, hurricane boundary layers and surface wind damage, radar technology

, PhD, Researcher, Center for Severe Weather Research
Characterization of low-level wind structure in tornadoes, supercell storm dynamics, quantifying boundary layer winds in hurricanes

Research Facilities

 (RECUV)

RECUV is a university, government, and industry partnership dedicated to development and application of Unmanned Aircraft Systems (UAS).  Facilities include the Mobile Research Collaboratory (MRC), an indoor flying-robot lab, a systems-integration lab, ground-based LIDAR capability, and a fixed-wing and rotary-wing unmanned aircraft fleet integrated with a variety of sensors.  RECUV also possesses the most expansive university network of FAA Certificates of Authorization (COAs), allowing UAS operation and research over more than 100,000 square miles of space in CO, OK, KS, TX, NE, WY, and AK.

Commercialization/Impact

The Tempest UAS Airframe was designed by UASUSA in collaboration with CU-Boulder’s RECUV for the National Science Foundation (NSF) Tornado Research Project VORTEX-2, and was integral to the 2014 Longmont, Colorado Start-up that develops UAS technology to apply to many of society’s greatest commercial, environmental, and scientific challenges for governments, businesses, and non-governmental organizations.

Black Swift is a Boulder-based engineering firm, founded by CU-Boulder Alumni, specializing in high capability small unmanned aircraft systems. Black Swift leverages a history of collaboration with CU-Boulder in UAS atmospheric research. With an array of in-house developed plug-and-play technologies, Black Swift provides a broad range of UAS support including Avionics and Ground Support, Customized User Interface, Airframe Selection and Integration, and Flight Management Software.

Research Partners

 (C-UAS)
 (USSRG)
(UNL)
 (NWI)
 (NSSL)
 (CSWR)
 (CIMMS)

Related Projects

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Energy-Aware Aerial Systems for Persistent Sampling and Surveillance

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  • Goal of this work is to create energy-aware, airborne, dynamic data-driven application systems for persistent sensing in complex atmospheric conditions.
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Verification of the Origins of Rotation in Tornados Experiment 2 (VORTEX-2)

(NOAA, NSF, and 100 scientists and researchers from around the globe)

  • NSF/NOAA-funded tornado research project to explore how, when, and why tornados form
  • Incorporated 100 scientists from government and universities around the world to collect weather measurements around and under supercell thunderstorms
  • Teams employed 10 mobile radars and over 70 measurement instruments, all equipped with cutting-edge communication and computer technologies
  • Partners roamed more than 10,000 miles across the southern and central plains in 2009-2010 and collected data on 11 supercells, including 1 tornadic supercell
  • Results from VORTEX-2 data collection will continue to enhance cloud models and storm forecasting well into the future