Volcanic and desert dust alerts for aviation using temporally high-resolved EARLINET profiles
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Volcanic and desert dust alerts for aviation using temporally high-resolved EARLINET profiles N. Papagiannopoulos, L. Mona, G. D’Amico [CNR-IMAA] V. Amiridis, A. Gialitaki [NOA] EUNADICS-AV Final Meeting 11.9.2019 @Meteo France, Toulouse The EUNADICS-AV project has received funding from the European Union’s Horizon 2020 research programme for www.eunadics.eu Societal challenges - smart, green and integrated transport under grant agreement no. 723986.
Objectives • We present the methodology for an early warning system (EWS) for aviation for airborne hazards, such as volcanic dust and desert dust, using EARLINET (European Aerosol Research Lidar Network) high resolution products. • The system is being developed for the purposes of the H- 2020 EUNADICS-AV project (European Natural Airborne Disaster Information and Coordination System for Aviation). • www.eunadics.eu The EUNADICS-AV project has received funding from the European Union’s Horizon 2020 research programme for www.eunadics.eu Societal challenges - smart, green and integrated transport under grant agreement no. 723986.
Background • The disruption to aviation that resulted from the 2010 Eyjafjallajökull eruption led to introduction of procedures through the International Civil Aviation Organization (ICAO). • The procedures marked a move away from the conservative “AVOID AVOID AVOID” approach. • According to ICAO (2014), three thresholds have been devised for the mass concentration. • No contamination:
Methodology: the EARLINET data • As a starting point, we make use of the new data products of the EARLINET SCC (Single Calculus Chain), namely the calibrated high resolution data, which can be available in near-real-time (NRT): • calibrated attenuated backscatter coefficient, • calibrated volume depolarization ratio, and • cloud mask. • Then, based on the methodology of Baars et al. (2017), we can estimate several particle-like high resolution products: • Particle-like backscatter coefficient • Particle-like depolarization ratio • Particle-like Ångström exponent • Particle classification mask The EUNADICS-AV project has received funding from the European Union’s Horizon 2020 research programme for www.eunadics.eu Societal challenges - smart, green and integrated transport under grant agreement no. 723986.
Methodology: the alert scheme • Finally, an alert scheme is devised for aerosol hazards (volcanic dust/desert dust; used interchangeably) based on profiles of the particle-like β and δ. • The ICAO mass concentration levels are converted into particle backscatter coefficient using the formula of Ansmann et al. (2012). = c: coarse particles (i.e. volcanic dust / desert dust) β c: particle backscatter coefficient (the unknown) mc: mass concentration (used: ICAO advisory) ρc: particle density (used: 2.6 g/cm3) S c: particle lidar ratio (used: 55 sr) : volume to extinction conversion factor (used: ???) The EUNADICS-AV project has received funding from the European Union’s Horizon 2020 research programme for www.eunadics.eu Societal challenges - smart, green and integrated transport under grant agreement no. 723986.
Methodology: the conversion factor • The conversion factor is estimated from meticulous selected AERONET observations or a site climatological mean. • Here, we use: 0.74×10-6 m, an all-mean from literature references (Papagiannopoulos et al., in preparation, 2019). V: Volcanic – D: Dust
Methodology: Aviation alert delivery β1 = 1.9×10-6 m-1sr-1 β2 = 1.9×10-5 m-1sr-1 β3 = 3.8×10-5 m-1sr-1 The EUNADICS-AV project has received funding from the European Union’s Horizon 2020 research programme for www.eunadics.eu Societal challenges - smart, green and integrated transport under grant agreement no. 723986.
Results Antikythera Finokalia The EUNADICS-AV project has received funding from the European Union’s Horizon 2020 research programme for www.eunadics.eu Societal challenges - smart, green and integrated transport under grant agreement no. 723986.
Case study: Finokalia • An intense Saharan dust outbreak in Greece a year ago (21-22 March 2018) resulted in the closure of the Heraklion airport (Solomos et al., 2018). • In situ measurements showed aerosol mass concentration exceeding 6 mg/m3 (22/03). www.efsyn.gr Courtesy of NOA, Athens.
Case study: Finokalia – 21 March 2018
Case study: Finokalia – 21 March 2018 200
Case study: Antikythera – June 2019
Case study: Antikythera – June 2019 tres = 5 min rres = 60 m
Case study: Antikythera – June 2019 23:00 00:00 01:00
Case study: Antikythera – June 2019 • The eruption of volcano Mount Etna which began in the early hours of 30 May, 2019, injected ash particles and SO2 in the atmosphere in the altitude of 3.5–4.0 km (VAAC Toulouse report at 11:21 UTC, 30 May). • The volcanic activity ceased most likely on 3 June (https://ingvvulcani.wordpress.com) Courtesy of NOA, Athens.
• CALIPSO indicated active dust sources along its northward orbit. • The NMMB-BSC-Dust model forecast the existence of dust particles over the study area. • Indication of co-existence of volcanic sulfate particles and Saharan desert dust.
EARLINET in the EUNADICS-AV Exercise 17
EARLINET observations 2019-03-05 12:00-18:00 UTC • The NRT data delivery was demonstrated and the EWS showed the potential to work in an operational environment. 18
The EUNADICS-AV portal: a fictitious example • http://portal.eunadics.eu.s3-website-eu-west-1.amazonaws.com/#/layermanager The EUNADICS-AV project has received funding from the European Union’s Horizon 2020 research programme for www.eunadics.eu Societal challenges - smart, green and integrated transport under grant agreement no. 723986.
Conclusions • The methodology • uses EARLINET high-resolution data for an EWS for volcanic dust/desert dust. • requires single-wavelength polarization lidar (i.e. particle-like β and δ). • can be applied EARLINET-wide and adjusted to the station needs. • can be applied to other networks (e.g. MPLNET, LALINET, ADNET…). • EARLINET can provide NRT hazard relevant information and this information could be deployed operationally (e.g. EUNADICS-AV portal). • The E-shape, 4y project funded by H2020, started on 1 May 2019 and will allow to increase the readability of the tailored product and its TRL.
Conclusions • However, • the method is based on lidar elastic channels. • there is no discrimination between volcanic dust and desert dust. • numerous assumptions are required (ε is around 30% and exceeds 100% in case of very large particles). • there is underestimation/overestimation of cloud pixels (testing is required). • it is a considerable challenge in case of attenuation of the lidar signal (e.g. low lying clouds, opaque aerosol plume). • what is the threshold value between a thick aerosol plume and cloud? The EUNADICS-AV project has received funding from the European Union’s Horizon 2020 research programme for www.eunadics.eu Societal challenges - smart, green and integrated transport under grant agreement no. 723986.
References • Ansmann et al.: Profiling of fine and coarse particle mass: case studies of Saharan dust and Eyjafjallajökull/Grimsvötn volcanic plumes, Atmos. Chem. Phys., 12, 9399-9415, https://doi.org/10.5194/acp-12-9399-2012, 2012. • Baars et al.: Target categorization of aerosol and clouds by continuous multiwavelength-polarization lidar measurements, Atmos. Meas. Tech., 10, 3175-3201, https://doi.org/10.5194/amt-10-3175-2017, 2017. • ICAO, 2014. Volcanic Ash Contingency Plan - EUR Region. EUR Doc 019.https://www.icao.int/EURNAT/EUR%20and%20NAT%20Documents/EUR+ NAT%20VACP.pdf. • Papagiannopoulos et al.: An EARLINET prototype for early warning system, in preparation, 2019. • Solomos et al.: From Tropospheric Folding to Khamsin and Foehn Winds: How Atmospheric Dynamics Advanced a Record-Breaking Dust Episode in Crete, Atmosphere 2018, 9, 240, https://doi.org/doi:10.3390/atmos9070240, 2018. The financial support for EARLINET in the ACTRIS-2 Research Infrastructure Project by the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 654169 in the Seventh Framework Programme (FP7/2007– 2013) is gratefully acknowledged. The research leading to these results has received funding from European Union’s Horizon 2020 Research and Innovation Programme under grant agreement no. 723986 (project EUNADICS-AV (European Natural Disaster Coordination and Information System for Aviation)).
Thank you! nikolaos.papagiannopoulos@imaa.cnr.it The EUNADICS-AV project has received funding from the European Union’s Horizon 2020 research programme for www.eunadics.eu Societal challenges - smart, green and integrated 23 transport under grant agreement no. 723986.
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