Evaluation of wind and temperature profiles from ECMWF analysis on two hemispheres using volcanic infrasound

Abstract

In this paper, we evaluate vertical wind and temperature profiles that are produced by the European Centre for Medium‐Range Weather Forecasts (ECMWF) atmospheric analysis. The evaluation is carried out on both hemispheres: we make use of stratospheric infrasound arrivals from Mount Etna (37°N) and Mount Yasur (22°S). The near‐continuous, high activity of both volcanoes permits the study of stratospheric propagation along well‐defined paths with a time resolution ranging from hours to multiple years. Infrasound observables are compared to theoretical estimates obtained from acoustic propagation modeling using the ECMWF analysis. While a first‐order agreement is found for both hemispheres, we report on significant discrepancies around some of the equinox periods and other intervals during which the atmosphere is in a state of transition and dynamical oscillations of the atmosphere dominate over the general circulation. We present an inversion study in which we make use of measured trace velocity estimates to estimate first‐order effective sound speed model updates in a Bayesian framework. Deviations from the a priori models around the stratopause up to 10% (≈ 30 m s−1) are estimated. Such updates are in line with the results from comparisons between ECMWF analysis and observations from lidar and microwave Doppler spectroradiometer facilities that were colocated during the course of the 2012–2013 Atmospheric dynamics Research and InfraStructure in Europe (ARISE) measurement campaign.

Comparison of co‐located independent ground‐based middle atmospheric wind and temperature measurements with numerical weather prediction models

“…This has motivated the development of atmospheric remote sensing methods [e.g., Drob et al, 2010;Lalande et al, 2012;Landès et al, 2014;Assink et al, 2014a]. In particular, the main characteristics of SSW events have been successfully derived from directional microbarom amplitude variations resulting from changes in stratospheric propagation conditions [Evers and Siegmund, 2009;Smets and Evers, 2014].…”

“…In a related study [Assink et al, 2014a], an evaluation of ECMWF analyses using volcanic signals has been performed. While a first-order agreement was found, large discrepancies during the equinox periods were observed when the atmosphere is in a state of transition.…”

Toward an Improved Representation of Middle Atmospheric Dynamics Thanks to the ARISE Project

“…The cyan and red lines represent the maximum likelihood and a priori models, respectively. While a first-order agreement is generally found between wind model and the observations in summer, significant discrepancies during the equinox periods and some anomalous wintertime periods during the occurrence of major SSW events were reported (Assink et al 2014a). The example of October 2, 2008 illustrates the effective sound speed underestimation by the model by at least 25 m/s at 50 km altitude near the equinox period.…”

“…IMS stations, quasi-continuously detecting infrasound from volcanoes, are well-adapted to these studies. Systematic differences between simulations and observations of the infrasound produced by the Lopevi volcano, detected in the New Caledonia IS22 station, were used to correct winds in the upper stratosphere and mesosphere (Le Pichon et al 2005a, b), and new methods were further developed for infrasound inversions (Millet et al 2007;Drob et al 2010;Lalande et al 2012;Assink et al 2014a). Ocean swell at the origin of microbaroms detected at most infrasound stations could also be used as a natural and continuous source for passive acoustic tomography of the stratosphere and lower mesosphere in a global way (Le Pichon et al 2006).…”

Automated detection and cataloging of global explosive volcanism using the International Monitoring System infrasound network

“…Comparison of (a) the "sensitive" Run 8 (Table 1) larger pixel threshold for defining a station association (m = 500 pixels). A linear feature also extends from IS48 (Tunisia) toward Mount Etna (Figure 13a) [Assink et al, 2014]. The linear feature from IS48 to Mount Etna (Figure 13a) apparently results from real volcanic signals of interest at a given station (IS48) becoming spuriously linked with clutter (nonvolcanic signals) at other stations.…”