Sudden Stratospheric Warming in 2015–2016: Study with Satellite Passive Microwave Data and ERA5 Reanalysis

Kuleshov

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

et al. 2022

The Meteor-M No. 2-2 meteorological satellite with the microwave radiometer MTVZA-GY on board was launched into a circular sun-synchronous orbit on July 5, 2019. The radiometer conducts a conical scanning at 65-degree incidence angle and receives the Earth's outgoing radiation in the frequency range ν ≈ 6-190 GHz. The swath width is 2500 km on ascending orbits and 1500 km on descending orbits. The parameters of the ocean, land surface, and troposphere are extracted from brightness temperatures T B (ν) measured at imager frequencies of 6.9,

“…Sudden warming events in the stratosphere of the Northern Hemisphere were recorded by MTVZA-GY in 2015-2016 with Meteor-M No. 2 [5] and in January 2021 with Meteor-M No. 2-2 [33].…”

Section: Discussionmentioning

confidence: 97%

“…SSWs in the Northern Hemisphere were detected by MTVZA-GY from Meteor-M No. 2 in 2015-2016 [5] and from Meteor-M No. 2-2 in January 2021 [33].…”

Section: Sudden Stratospheric Warmingmentioning

confidence: 99%

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Microwave Radiometer MTVZA-GY on New Russian Satellite Meteor-M No. 2-2 and Sudden Stratospheric Warming Over Antarctica

Kuleshov

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

et al. 2022

“…During the period of our consideration, three major and three minor SSWs occurred. Major SSWs took place with onsets on 5-6 March 2016 (Manney and Lawrence, 2016), 11 February 2018Lü et al, 2020), and 1 January 2019 (Rao et al, , 2020, while the minor events occurred with onsets on 4 January 2015 (Manney et al, 2015;Mitnik et al, 2018) and 1 and 26 February 2017 (Eswaraiah et al, 2020). Note that there can be an error of up to several days in determining the SSW onset day, since there is no single way to define the onset, and different authors use different definitions.…”

Section: Examination Of Major Sudden Stratospheric Warmingsmentioning

confidence: 99%

Benchmarking microbarom radiation and propagation model against infrasound recordings: a vespagram-based approach

et al. 2021

Abstract. This study investigates the use of a vespagram-based approach as a tool for multi-directional comparison between simulated microbarom soundscapes and infrasound data recorded at ground-based array stations. Data recorded at the IS37 station in northern Norway during 2014–2019 have been processed to generate vespagrams (velocity spectral analysis) for five frequency bands between 0.1 and 0.6 Hz. The back azimuth resolution between the vespagram and the microbarom model is harmonized by smoothing the modeled soundscapes along the back azimuth axis with a kernel corresponding to the frequency-dependent array resolution. An estimate of similarity between the output of the microbarom radiation and propagation model and infrasound observations is then generated based on the image-processing approach of the mean square difference. The analysis reveals that vespagrams can monitor seasonal variations in the microbarom azimuthal distribution, amplitude, and frequency, as well as changes during sudden stratospheric warming events. The vespagram-based approach is computationally inexpensive, can uncover microbarom source variability, and has the potential for near-real-time stratospheric diagnostics and atmospheric model assessment.

“…Major SSWs took place with onsets on 5-6 March 2016 (Manney and Lawrence, 2016), 11 February 2018 Lü et al, 2020) and 1 January 2019 (Rao et al, , 2020, while the minor events occurred with onsets on 4 January 2015 (Manney et al, 2015;Mitnik et al, 2018), 1 and 26 February 2017 (Eswaraiah et al, 2020). Note that there can be an error up to several days in determining SSW onset day since there is no single way to define the onset, and different authors use different definitions.…”

Section: Examination Of Major Sudden Stratospheric Warmingsmentioning

confidence: 99%

Microbarom radiation and propagation model assessment using infrasound recordings: a vespagram-based approach

Vorobeva

Carlo

Pichon

et al. 2020

Preprint

Abstract. This study investigates the use of a vespagram-based approach as a tool for multi-directional comparison between simulated microbarom soundscapes and infrasound data recorded at ground-based array stations. Data recorded at the IS37 station in northern Norway during 2014–2019 have been processed to generate vespagrams (velocity spectral analysis) for five frequency bands between 0.1 and 0.6 Hz. The back-azimuth resolution between vespagrams and a microbarom model is harmonized by smoothing the modelled soundscapes along the back-azimuth axis with a kernel corresponding to the frequency-dependent array resolution. An estimate of similarity between the output of a microbarom radiation and propagation model and infrasound observations is then generated based on the image processing approach of mean-square difference. The analysis revealed that vespagrams can monitor seasonal variations in the microbarom azimuth distribution, amplitude, and frequency, as well as changes during sudden stratospheric warming. The vespagram-based approach is computationally inexpensive, can uncover microbarom source variability, and has potential for near-real-time stratospheric diagnostics and atmospheric model assessment.