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:
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