Exploring the use of atmospheric infrasound to enhance long-term weather forecasting

Microbaroms are ocean-generated acoustic waves with peak frequency at ~0.2 Hz. These are generated continuously in specific ocean regions by the nonlinear interaction between counter-propagating waves, e.g., ocean swells and marine storms. There is a such hot-spot of particular interest close to Greenland and Iceland. These waves radiate into the atmosphere as microbaroms, as well as through the seafloor into the solid earth as microseisms. Microbaroms can be utilized to probe the atmospheric wind structure, in particular for the upper stratosphere layer for which there are few other technologies that sample the wind field. The stratosphere is an elevated layer in the atmosphere starting at around 15 km and reaching up to around 50 km altitude. 

Previous works have shown that continuous microbarom measurements provide insights on atmospheric properties. The detection or non-detection of microbaroms at an infrasound station is determined by the strength and direction of the stratospheric winds and temperature. Sudden Stratospheric Warming events can be characterized using infrasound as the temperature increases by up to 50 degrees in the upper stratosphere and the polar eastward jet is slowed or reversed, and this is a key mechanism which can couple down to the surface to cause prolonged winter cold spells in Europe and densely populated parts of North America.

You will work with array data recorded at an infrasound station in Bardufoss, northern Norway. This is one of the world's largest infrasound arrays with 10 elements distributed over an aperture of almost 2 km. Many standard infrasound array signal processing recipes and pipelines are tailored for analysis of transient explosion-like signals. However, the continuous-wave nature of microbarom signals, see below, has sparked the application of array signal processing approaches that provide enhanced characterization. You will explore parameter tuning possibilities for conventional delay-and-sum beamformers and inter-element correlation-based beamformers, as well as adaptive and more advanced beamformers based on for example Capon’s method, CLEAN and MUSIC.

You will hence work on the enhancement methods to allow for a continuous monitoring of the stratosphere, and maybe you will even be able to predict the prospects of greater snowfall and better skiing conditions based on a continuous monitoring of the stratospheric circulation?

The below figure provides an analysis of the direction towards the dominating mircrobarom wavefront arrival at the station in Bardufoss before and after three different Sudden Stratospheric Warming events:

Microbarom, infrasound
A composite picture of microbarom direction-of-arrival at the IS37 infrasound station in Bardufoss, Norway. The horizontal axis shows time-difference relative to the event onsets at 6 March 2016, 14 February 2018, and 22 December 2018. This analysis highlights clearly different characteristics in the direction of arrival before and after the SSW, which would be attributed to an altered stratospheric wind pattern between the microbarom hot-spot close to Greenland and the station in Bardufoss.

Necessary experience:

  •  IN5450 - Array signal processing, or similar coursework

  •  Solid Python / Matlab scientific programming and data analysis skills

Additional beneficial competence:

  • Acoustical wave propagation

  • Digital signal processing

  • The ObsPy Python package

  • Atmospheric dynamics and meteorology

Emneord: signal processing, beamforming, microbarom, infrasound
Publisert 9. sep. 2020 13:23 - Sist endret 13. sep. 2020 21:55

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