MST14/iMST1 Conference

25-31 May 2014, Sao Jose dos Campos, Brazil

By Alex Chartier, SSI Fellow and Research Scientist at Johns Hopkins Applied Physics Laboratory  



  1. New ideas: Software-defined radio applications for ionospheric sensing. Low size, power, cost allows for distributed sensing on previously inaccessible platforms. Whole-atmosphere modelling performs well at high altitudes when dynamics are specified lower down - previously I thought the project was far from being mature.
  2. People met: Various, but included Erhan Kudeki (radio scientist at Altair radar - combined rocket and radar experiments), Diego Janches (mesospheric scientist and Low-Cost Access to Space program coordinator at NASA), Anja Stromme (manager of Sondrestrom Incoherent Scatter Radar), Juha Vierinen (software radio developer at MIT Haystack Observatory).
  3. Policy ideas: Push for open-source software in upper atmospheric research to avoid re-work and improve scientific robustness. Ideas taken up with US National Science Foundation.

Event report:

MST14/iMST1 was the first in a long-running series of Mesosphere-Stratosphere-Troposphere (MST) radar meetings to officially acknowledge the growing popularity of this class of radar for making ionospheric measurements. The meeting was attended by a mixture of scientists and instrumentalists. Attendees from Canada, Australia, USA, Germany, Norway, Brazil, Peru, Japan, France and Argentina were present.

This year, the meeting was filmed and broadcast online during the meeting. The process caused some problems – especially when members of the audience had to wait for microphones to ask questions. The online broadcast may also have contributed to lower than usual attendance.

One highlight of this year's meeting was the growing adoption of software-defined radio. Using the GNU Radio python software package, non-expert users have adapted mass-market digital TV receivers for use as scientific instruments. Software-defined radio allows traditional hardware components (mixers, filters, amplifiers etc.) to be implemented as software on a personal computer or a dedicated micro-controller such as the Arduino. The Universal Software Radio Peripheral (USRP) by Ettus Research is one popular software radio platform that can be easily coupled to a personal computer. One application has seen an $8 digital TV receiver employed to receive ionospheric echoes originating from local radio stations. This combination of free, easy-to-use software and low-cost hardware has resulted in orders-of-magnitude improvements to a common ionospheric sounder. Previously, ionosondes cost over $100 000 consumed hundreds of Watts. The new instrument can function on under one Watt of power and costs under $5000.

A number of new iMST radar installations are currently planned for development. These include EISCAT 3D in Scandinavia, as well as new installations in Antarctica and Japan. In particular, the EISCAT 3D installation presents an enormous computing challenge. The installation will produce petabytes of data each year. Beam-forming, beam-steering and a variety of data processing will be done digitally, so there are a range of software challenges. The project targets tropospheric, stratospheric, mesospheric, thermospheric and ionospheric areas of research.

Modelling plays a part in every atmospheric meeting. At this meeting, there were several talks focussed on comparing whole-atmosphere models with mesospheric and thermospheric observations. The Whole Atmosphere Community Climate Model (WACCM), which is based on the Community Earth Science Model framework, was the primary focus of modelling work at this meeting. WACCM represents atmospheric features from orography (mountains, valleys etc.), through to snow, lightning and all the way up to the thermosphere at 450 km altitude. The model runs on high-performance computers, typically using in excess of 100 processors in its configuration on the Yellowstone supercomputer in Wyoming. The model is freely available, but its recent thermospheric extension (WACCM-X) still contains significant biases.