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Development and coordination of practical balloon swarms for persistent, in situ, real-time measurement of hurricane development


This project proposes a low-cost balloon observation system for sustained (in time), broadly distributed (in space), in-situ (between 1-8km altitude), real-time measurement (from data acquisition to NCAR within 20 minutes) of hurricane development. The high density (in both space and time) measurements from such a robotic vehicle swarm will be invaluable in significantly improving our ability to estimate and forecast such extreme and dangerous atmospheric events.

Challenges in this over-arching problem, which is of acute societal relevance, include:

  1. the design of small (3 kg, 5.5 m3 at 8 km altitude), inexpensive (< $ 2k), robust, sensor-laden, buoyancy-controlled balloons that don’t accumulate ice, and are deployable from the launch chutes (13 cm diameter x 91 cm long) of existing NOAA P3 aircraft [mbdb17],

  2. the implementation of a self-reconfiguring Mobile Ad hoc Network (MANET) over the (mobile) balloon swarm, leveraging ultra-low-power cellphone (LTE-Direct) or IoT (Sub-1 GHz) radios communicating in the UHF band over (typically) 10 to 30 km distances, and

  3. the development of efficient hierarchical systems-level control algorithms to autonomously coordinate the vertical motion of the balloons in the swarm to move them with the hurricane, simultaneously achieving both good coverage and good connectivity while minimizing the control energy used, leveraging the strong vertical stratification of the horizontal winds.  We have so far developed two algorithms for this problem, which we now work to combine:

  • a (centralized) Model Predictive Control (MPC) strategy for coordinating the large-scale balloon distribution, leveraging the coarse flow forecasts developed with the cutting-edge hurricane Weather and Research Forecasting (WRF) code developed at NOAA [BM16], and

  • a (decentralized) Three-Level Control (TLC) strategy for rejecting the smaller-scale disturbances that arise due to unresolved flowfield fluctuations, which induce a statistical “random walk” in the balloon trajectory away from that planned by the MPC formulation [mlb16], [MLB17].

 Typical (and, discouraging!) spread of the zero- to five-day forecasts of the track of Hurricane Matthew, as performed by the major hurricane forecasting centers on (left) Oct 3, (middle) Oct 6, and (right) Oct 7, 2016.  Data from NOAA.  The high temporal and spatial density of in situ measurements to be made available by the proposed sensor vehicle swarms should be instrumental in significantly improving our ability to estimate and forecast such extreme and dangerous atmospheric events. 
For further information about this project, in addition to the above links, please see the nice press release by the UCSD Jacobs School of Engineering regarding this project. 
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