# Evidence of a dual African and Australian biomass burning influence on the vertical distribution of aerosol and carbon monoxide over the Southwest Indian Ocean basin in early 2020

Nelson Bègue, Alexandre Baron, Gisèle Krysztofiak, Gwenaël Berthet, Hassan Bencherif, Corinna Kloss, Fabrice Jégou, Sergey Khaykin, Marion Ranaivombola, Tristan Millet, et al.

<figure><img src="image_1.png" /></figure>

## To cite this version:

Nelson Bègue, Alexandre Baron, Gisèle Krysztofiak, Gwenaël Berthet, Hassan Bencherif, et al. Evidence of a dual African and Australian biomass burning influence on the vertical distribution of aerosol and carbon monoxide over the Southwest Indian Ocean basin in early 2020. Atmospheric Chemistry and Physics Discussions, In press, 10.5194/egusphere-2023-1946. insu-04208981

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https://insu.hal.science/insu-04208981

Submitted on 15 Sep 2023

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# Evidence of a dual African and Australian biomass burning influence on the vertical distribution of aerosol and carbon monoxide over the Southwest Indian Ocean basin in early 2020

Nelson Bègue, Alexandre Baron, Gisèle Krysztofiak, Gwenaël Berthet, Corinna Kloss, Fabrice Jégou, Sergey Khaykin, Marion Ranaivombola, Tristan Millet, Thierry Portafaix, et al.

► To cite this version:

Nelson Bègue, Alexandre Baron, Gisèle Krysztofiak, Gwenaël Berthet, Corinna Kloss, et al. Evidence of a dual African and Australian biomass burning influence on the vertical distribution of aerosol and carbon monoxide over the Southwest Indian Ocean basin in early 2020. Atmospheric Chemistry and Physics, 2024, 24 (13), pp.8031-8048. 10.5194/acp-24-8031-2024. insu-04208981v2

HAL Id: insu-04208981

https://insu.hal.science/insu-04208981v2

Submitted on 15 Aug 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_2.png" /></figure>

Evidence of a dual African and Australian biomass burning influence on the vertical distribution of aerosol and carbon monoxide over the Southwest Indian Ocean basin in early 2020

Nelson Bègue¹, Alexandre Baron²,³, Gisèle Krysztofiak⁴, Gwenaël Berthet⁴, Hassan Bencherif¹,⁵, Corinna Kloss⁴, Fabrice Jégou⁴, Sergey Khaykin⁶, Marion Ranaivombola¹, Tristan Millet¹, Thierry Portafaix¹, Valentin Duflot¹, Philippe Keckhut⁶, Hélène Vérèmes¹, Guillaume Payen⁷, Mahesh Kumar Sha⁸, Pierre-François Coheur⁹, Cathy Clerbaux⁹,¹⁰, Michaël Sicard¹, Tetsu Sakai¹¹, Richard Querel¹², Ben Liley¹², Dan Smale¹², Isamu Morino¹³, Osamu Ochino¹¹,¹³, Tomohiro Nagai¹¹, Penny Smale¹² and John Robinson¹²

[1] Laboratoire de l'Atmosphère et des Cyclones, UMR 8105 CNRS, Université de la Réunion, Reunion Island, France.

[2] Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, CO 80305, USA

[3] NOAA Chemical Sciences Laboratory (CSL), 325 Broadway, Boulder, CO 80305, USA

[4] Laboratoire de Physique et Chimie de l'Environnement et de l'Espace (LPC2E), Université d'Orléans, CNRS UMR7328, Orléans, France.

[5] School of Chemistry and Physics, University of KwaZulu-Natal, Durban 4041, South Africa

[6] Laboratoire Atmosphères, Observations Spatiales (LATMOS), IPSL, UVSQ Université Paris-Saclay, Sorbonne Université, CNRS, Guyancourt, France

[7] Observatoire des Sciences de l'Univers de La Réunion (OSU-Réunion), UAR3365, Saint-Denis de la Réunion, France

[8] Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium

[9] Université libre de Bruxelles (ULB), Spectroscopy, Quantum Chemistry and Atmospheric Remote Sensing (SQUARES), Brussels 1050, Belgium; Bruxelles (ULB), Brussels 1050, Belgium.

[10] Laboratoire Atmosphères, Observations Spatiales (LATMOS), IPSL, Sorbonne Université, UVSQ, CNRS, Paris, France

[11] Meteorological Research Institute, 1-1 Nagamine, Tsukuba, Ibaraki 305-0052, Japan

[12] National Institute of Water & Atmospheric Research (NIWA), Lauder, New Zealand

[13] National Institute for Environmental Studies, Tsukuba, Japan
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# Evidence of a dual African and Australian biomass burning influence on the vertical distribution of aerosol and carbon monoxide over the southwest Indian Ocean basin in early 2020

Nelson Bègue<fnref n="1" />, Alexandre Baron<fnref n="2" />,<fnref n="3" />, Gisèle Krysztofiak<fnref n="4" />, Gwenaël Berthet<fnref n="4" />, Corinna Kloss<fnref n="4" />,ª
Fabrice Jégou<fnref n="4" />, Sergey Khaykin<fnref n="5" />, Marion Ranaivombola<fnref n="1" />, Tristan Millet<fnref n="1" />, Thierry Portafaix<fnref n="1" />,
Valentin Duflot<fnref n="1" />,ᵇ, Philippe Keckhut<fnref n="5" />, Hélène Vérèmes<fnref n="1" />, Guillaume Payen<fnref n="6" />, Mahesh Kumar Sha<fnref n="7" />,
Pierre-François Coheur<fnref n="8" />, Cathy Clerbaux<fnref n="8" />,<fnref n="9" />, Michaël Sicard<fnref n="1" />, Tetsu Sakai<fnref n="10" />, Richard Querel<fnref n="11" />,
Ben Liley<fnref n="11" />, Dan Smale<fnref n="11" />, Isamu Morino<fnref n="12" />, Osamu Uchino<fnref n="10" />,<fnref n="12" />, Tomohiro Nagai<fnref n="10" />, Penny Smale<fnref n="11" />,
John Robinson<fnref n="11" />, and Hassan Bencherif<fnref n="1" />

**Correspondence:** Nelson Bègue (nelson.begue@univ-reunion.fr)

Received: 25 August 2023 – Discussion started: 31 August 2023

Revised: 18 April 2024 – Accepted: 11 May 2024 – Published: 16 July 2024

**Abstract.** During the 2020 austral summer, the pristine atmosphere of the southwest Indian Ocean (SWIO) basin experienced significant perturbations. This study examines the variability of aerosols and carbon monoxide (CO) over this remote oceanic region and investigates the underlying processes in the upper troposphere–lower stratosphere (UT-LS). Aerosol profiles in January and February 2020 revealed a multi-layer structure in the tropical UT-LS. Numerical models – the FLEXible PARTicle dispersion model (FLEXPART) and the Modèle Isentropique de transport Mésoéchelle de l’Ozone Stratosphérique par Advection (MIMOSA) – indicated

<footnote n="1">¹Laboratoire de l'Atmosphère et des Cyclones, UMR 8105 CNRS,
Université de la Réunion, Météo-France, Réunion Island, France</footnote>

<footnote n="2">²Cooperative Institute for Research in Environmental Sciences (CIRES),
University of Colorado, Boulder, CO 80305, USA</footnote>

<footnote n="3">³NOAA Chemical Sciences Laboratory (CSL), 325 Broadway, Boulder, CO 80305, USA</footnote>

<footnote n="4">⁴Laboratoire de Physique et Chimie de l'Environnement et de l'Espace (LPC2E),
Université d'Orléans, CNRS UMR7328, CNES, Orléans, France</footnote>

<footnote n="5">⁵Laboratoire Atmosphères, Observations Spatiales (LATMOS), IPSL, UVSQ Université
Paris-Saclay, Sorbonne Université, CNRS, Guyancourt, France</footnote>

<footnote n="6">⁶Observatoire des Sciences de l'Univers de La Réunion (OSU-Réunion),
UAR3365, Saint-Denis de la Réunion, France</footnote>

<footnote n="7">⁷Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium</footnote>

<footnote n="8">⁸Université libre de Bruxelles (ULB), Spectroscopy, Quantum Chemistry and Atmospheric Remote Sensing
(SQUARES), 1050 Brussels, Belgium</footnote>

<footnote n="9">⁹LATMOS/IPSL, Sorbonne Université, UVSQ, CNRS, Paris, France</footnote>

<footnote n="10">¹⁰Meteorological Research Institute, 1-1 Nagamine, Tsukuba, Ibaraki 305-0052, Japan</footnote>

<footnote n="11">¹¹National Institute of Water and Atmospheric Research (NIWA), Lauder, New Zealand</footnote>

<footnote n="12">¹²National Institute for Environmental Studies, Tsukuba, Japan</footnote>

<footnote>ªnow at: Institute for Energy and Climate Research – Stratosphere (IEK-7),
Forschungszentrum Jülich, Jülich, Germany</footnote>

<footnote>ᵇnow at: Department for Atmospheric and Climate Research,
NILU – Norwegian Institute for Air Research, Kjeller, Norway</footnote>
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## 2 Abstract

The pristine atmosphere of the southwest Indian Ocean (SWIO) basin underwent significant perturbations during the 2020 austral summer. This study documents the complex variability of aerosols and carbon monoxide (CO) over this remote oceanic region and identifies the processes governing it in the upper troposphere – lower stratosphere (UT-LS). Aerosol profiles exhibit a multi-layer structure in the tropical UT-LS in January and February 2020. The numerical models (FLEXPART and MIMOSA) showed that the modulation of the aerosol content in the lower stratosphere is due to the intense and persistent stratospheric aerosol smoke layer generated during the 2019-20 extreme Australian bushfire events. One part of this stratospheric aerosol smoke layer was advected zonally by the prevailing easterly winds and its passage over Reunion was recorded by increased aerosol extinction profiles on 27th and 28th January. The analysis of the advected potential vorticity highlights an isentropic transport of air masses containing Australian biomass burning aerosol from extra-tropical latitudes to Reunion at the 400 K isentropic level, on 28th January. Interestingly, our results show that the BB activity in eastern Africa, weak during this season, contributed to modulate (up to 90%) the vertical distribution of CO and aerosols in the upper troposphere over the SWIO basin. The simultaneous presence of African and Australian aerosols smoke layers has been recorded by ground-based observations at Reunion. This study highlights for the first time the influence of the African emissions from BB to the CO and aerosols distribution in the upper troposphere over the SWIO basin during the convective season. The results show that besides PyroCb - driven injection of BB products to the stratosphere, an alternative pathway may exist during the regular deep-convection season in the tropics.

## 1. Introduction

Large amounts of aerosols and active trace gases such as carbon monoxide (CO) are injected throughout the atmosphere during biomass burning (BB) events. The Southern American and Southern African regions are recognized to be significant primary sources of carbonaceous aerosols and active traces gases in the Southern Hemisphere through the BB season from July to November (Bencherif et al., 2020; Garstang et al., 1996; Holanda et al., 2020). Such BB activities have the potential to modulate the vertical distribution of trace gases and aerosols from the troposphere to the stratosphere (Andreae and Merlet, 2001; Duflot et al., 2010; Héron et al., 2020). Under favorable meteorological conditions, pyro-convection events can take place and have the potential to inject soot and smoke directly into the stratosphere (Dowdy and Pepler, 2018; Fromm et al., 2010). Radiative impact of the aerosols and traces gases is determined by

<footnote n="1">1 Correspondence to: N.Bègue (nelson.begue@univ-reunion.fr)</footnote>
that the lower-stratospheric aerosol content was influenced by the intense and persistent stratospheric aerosol layer generated during the 2019–2020 extreme Australian bushfire events. A portion of this layer was transported eastward by prevailing easterly winds, leading to increased aerosol extinction profiles over Réunion on 27 and 28 January. Analysis of advected potential vorticity revealed isentropic transport of air masses containing Australian biomass burning aerosols from extratropical latitudes to Réunion at the 400 K isentropic level on 28 January. Interestingly, we found that biomass burning (BB) activity in eastern Africa, though weak during this season, significantly influenced (contributed up to 90 % of) the vertical distribution of CO and aerosols in the upper troposphere over the SWIO basin. Ground-based observations at Réunion confirmed the simultaneous presence of African and Australian aerosol layers. This study provides the first evidence of African BB emissions impacting the CO and aerosol distribution in the upper troposphere over the SWIO basin during the convective season.

# 1 Introduction

Significant quantities of aerosols and trace gases, such as carbon monoxide (CO), are released into the atmosphere during biomass burning (BB) events in the Southern Hemisphere, particularly in South America and southern Africa from July to November (Bencherif et al., 2020; Garstang et al., 1996; Holanda et al., 2020). These activities disrupt the vertical distribution of gases and aerosols such that they potentially reach the stratosphere (Andreae and Merlet, 2001; Héron et al., 2020). Under specific meteorological conditions, pyro-convection events can directly inject soot and smoke into the stratosphere (Dowdy and Pepler, 2018; Fromm et al., 2010). The radiative impact of these particles and gases depends on their abundance, vertical distribution, and residence time, which influence their dispersion (Darbyshire et al., 2019; Morgan et al., 2020). Transported over long distances, these aerosols and gases can affect the atmospheric composition in traditionally aerosol-free regions.

The southwest Indian Ocean (SWIO) basin stands out as one of the Earth's pristine regions, where the aerosol concentration is predominantly governed by sea salts (Duflot et al., 2022). Characterized by a wet season (December to April) and a dry season (May to November), the SWIO region's atmospheric composition during the dry season is significantly influenced by Southern Hemisphere BB activity (Clain et al., 2009; Edwards et al., 2006; Kaufman et al., 2003; Swap et al., 2003). Studies have highlighted that BB plumes cross South Africa during the dry season, with southern African BB emissions primarily reaching the SWIO basin via five identified transportation modes (Edwards et al., 2006; Garstang et al., 1996). Situated in the subtropical southern Indian Ocean at the convergence of air masses from southern Africa, Réunion Island (21.0° S, 55.5° E) provides an ideal location to study the impact of regional transport on atmospheric composition over the SWIO basin. Ozone radiosonde and ground-based lidar observations at Réunion have revealed a significant annual increase in tropospheric ozone during the August–November period, which is aligned with the BB season in southern Africa and Madagascar (Clain et al., 2009).

Additionally, the long-range transport of BB plumes from South America can influence the tropical tropospheric composition over the SWIO basin (Duflot et al., 2010, 2022; Zhou et al., 2018). By combining ground-based observations of carbon monoxide (CO) from a Fourier-transform infrared (FTIR) spectrometer installed at Réunion with FLEXible PARTicle dispersion model (FLEXPART) model simulations, Duflot et al. (2010) demonstrated the potential of southern African and South American BB events to inject substantial quantities of ozone precursors such as CO and aerosols throughout the troposphere over the SWIO basin. This synergy of CO and aerosol observations aids in understanding the influence of BB events on aerosol burden evolution (Bègue et al., 2021; Bencherif et al., 2020; Jones et al., 2001). A recent analysis of aerosol optical depth (AOD) from sun-photometer data at Réunion over 12 years by Duflot et al. (2022) revealed that BB activity explains 67 % of the AOD variability, with southern Africa and South America contributing 22 % and 20 %, respectively. Despite Australia's reputation for intense BB events (Fromm et al., 2006, 2010; De Laat et al., 2012), their contribution to the observed AOD variability over Réunion is relatively low (4.7 %).

The Australian BB activity primarily occurs in the northern part of the continent between September and January, although the most severe fires typically occur in southeastern Australia. Extreme fires in this region during the austral summer can lead to pyro-convection events, with a significant impact on the stratosphere at regional and global scales. The unprecedented 2019–2020 fire season, known as the “Black Summer”, witnessed numerous pyro-convection outbreaks, injecting approximately 0.9 Tg of smoke into the stratosphere (Yu et al., 2021). This smoke mass, containing 2.5 % black carbon, induced a 1 K warming in the stratosphere of the Southern Hemisphere mid-latitude for more than 6 months following its injection. The smoke layer was advected by westerly winds that dispersed across all extratropical latitudes in the Southern Hemisphere. The optical characteristics of the stratospheric smoke layer were measured by lidar systems in Chile and Argentina, with the smoke layer extending from 9 to over 30 km in height (Ohneiser et al., 2022).
<figure><img src="image_5.png" /></figure>

abundance, vertical distribution, and atmospheric residence time (which, in turn, will affect the resultant horizontal distribution following advection (Darbyshire et al., 2018; Morgan et al., 2019)). High concentrations of trace gases and aerosols from these fires can be transported far from the source regions. This intercontinental transport has the potential to affect the atmospheric composition of regions considered as aerosol-free areas.

The southwest Indian Ocean (SWIO) basin is known to be one of the few pristine regions on Earth where the aerosol concentration is mainly governed by sea salts (Duflot et al., 2022). The SWIO basin is characterized by a wet season (December to April) and a dry season (May to November). Previous works showed that the atmospheric composition over the SWIO region during the dry season is driven by the Southern Hemisphere BB activity (Clain et al., 2009; Duflot et al., 2022; Edwards et al., 2006; Kaufman et al., 2003, Swap et al., 2003). These studies pointed out that BB plumes cross South Africa during the dry season. Edwards et al. (2006) revealed that southern African BB emissions mostly find their way into the SWIO basin and follow the five transportation modes identified by Garstang et al. (1996). Being located in the subtropical southern Indian Ocean at the crossroads of the transport pathway bringing air masses from southern Africa, Reunion Island (21,0°S, 55.5°E) is a favorable location to study the effect of this regional transport on atmospheric composition over the SWIO basin. Based on ozone radiosonde and ground-based lidar observations recorded at Reunion, Clain et al. (2009) highlighted a significant annual increase of tropospheric ozone over Reunion Island during August-November period, in phase with the BB season in southern Africa and Madagascar. High concentrations of ozone precursors from these fires are vented into the free troposphere by convection and are subsequently advected into the SWIO basin by westerly winds. In addition to regional transport, the tropical tropospheric composition over the SWIO basin can be modulated by the long-range transport of BB plumes from South America (Duflot et al., 2010, 2022; Zhou et al., 2018). By combining ground-based observations of Carbon monoxide (CO) from a Fourier Transform Infrared (FTIR) spectrometer installed at Reunion and the FLEXPART model simulations, Duflot et al. (2010) showed that southern African and southern American BB events have the potential to inject large amounts of ozone precursors such as CO and aerosols throughout the troposphere over the SWIO basin. The synergy of CO and aerosols observations are helpful in discussions of the influence of BB events on the evolution of the aerosol burden (Bègue et al., 2021; Bencherif et al., 2020; Jones et al., 2001). Most recently, the analysis of Aerosols Optical Depth (AOD) recorded from sun-photometer at Reunion over a period of 12-years has been undertaken by Duflot et al. (2022). Duflot et al. (2022) showed that the BB activity explains 67 % of the variability of the AOD, within which
The presence of this smoke layer significantly impacted the record-breaking ozone hole over Antarctica in September–November 2020, as reported by Tencé et al. (2022). Despite the extensive research on the impact of Australian fires on the stratospheric composition and circulation over extratrop-ical latitudes, relatively little attention has been paid to their influence over tropical and subtropical latitudes.

This study aims to document the transport of the Aus-
tralian smoke layer in the southern subtropics over the Indian
Ocean during the January–February period, corresponding to
the wet season in the SWIO basin. The intensity of convec-
tive activity during this season, with the presence of the Inter-
tropical Convergence Zone (ITCZ) over the entire basin, of-
ten leads to tropical depressions that reach the stage of tropi-
cal cyclones (Lashkari et al., 2017; Barthe et al., 2021; Neu-
mann et al., 1993). The Regional Specialized Meteorological
Centre (RSMC) at Réunion reported the development of six
tropical cyclones and four tropical storms in the SWIO basin
during the 2019–2020 cyclone season.

The study is structured as follows: Sect. 2 outlines the
observations and the model employed to investigate aerosol
layer transport. Section 3 reviews the formation and transport
of the Australian aerosol layer across the Southern Hemi-
sphere. Section 4 analyses the impact of the Australian BB
plume on aerosol and CO variability over the SWIO basin.
Section 5 discusses the influence of convective activity on
aerosol smoke layer transport over the SWIO basin. Finally,
Sect. 6 provides a summary and future perspectives of the
study.

2 Instrumentation and model description

2.1 Aerosol datasets

The aerosol datasets used in this study resulted mainly from
two ground-based observation sites from the Network for the
Detection of Atmospheric Composition Change (NDACC,
https://www.ndacc.org, last access: 10 April 2024) as well
as a suite of spaceborne sensor products.

2.1.1 Lauder ground-based lidar

Measurements of aerosol optical properties at Lauder
(45.0° S; 169.7° E) have been performed using lidars since
1992. The lidar system, detailed by Sakai et al. (2016), uti-
lizes a Nd: YAG laser beam at 532 nm with linear polar-
ization. The lidar detects Rayleigh–Mie backscattering at
532 nm with parallel and perpendicular components. Ex-
tinction and backscatter coefficients were derived using the
methodology outlined by Fernald (1984), incorporating an
aerosol extinction-to-backscatter ratio known as the lidar ra-
tio (LR). LR values for January–May 2020 are 88 and 60 sr
for altitudes above and below 23 km, respectively, as deter-
mined through a signal attenuation methodology described
by Uchino et al. (1983) and Young (1995). Aerosol depolar-

ization was computed from the backscatter ratio and the total
linear volume depolarization ratio (Sakai et al., 2003), calcu-
lated as the ratio of the perpendicular to parallel components
of the backscattered signal at 532 nm. To analyse the aerosol
variability attributed to Australian fires, a background pro-
file was defined using measurements taken during periods
without significant atmospheric disturbances, such as vol-
canic eruptions or pyro-convection outbreaks. In this study,
the background extinction profile at Lauder was constructed
from measurements made between 1997 and 2004.

2.1.2 Réunion Island ground-based lidars

The Atmospheric Physics Observatory of La Réunion
(OPAR) serves as a permanent station for long-term atmo-
spheric observations (Baray et al., 2013). Two lidar systems
operating at Maïdo Observatory, situated 2200 m above mean
sea level (a.m.s.l.), retrieve ozone and aerosol profiles in the
UV (355 nm) and visible (532 nm) parts of the light spec-
trum. These systems, LiO3T (532 nm) and LiO3S (355 nm),
are described by Baray et al. (2006). Extending from approx-
imately 15 km to the middle stratosphere (~35 km), these
lidars provide high-resolution aerosol optical property mea-
surements (extinction and the backscatter ratio) with a ver-
tical resolution of 15 m. By employing two distinct wave-
lengths, the Réunion lidar profiles facilitate the assessment of
the Ångström exponent of aerosols between 355 and 532 nm,
providing insight into the aerosol’s extinction behaviour and
microphysical properties, particularly particle size. A small
Ångström exponent typically indicates that a coarse mode
is driving the aerosol’s optical properties. Further details on
the Ångström exponent, aerosol size, and their relative error
concerning extinction properties are elaborated in the study
by Baron et al. (2023) and its supplementary information.
The inversion process performed in this study utilized the
Klett method (Klett, 1985), assuming a lidar ratio of 60 sr,
typical of aged BB aerosols (Müller et al., 2007). Nine li-
dar profiles recorded during the January–March 2020 pe-
riod were employed, with the background extinction profile
at Réunion constructed from measurements taken between
2017 and 2019, excluding the perturbation induced by the
Calbuco eruption in April 2015 (Bègue et al., 2017).

2.1.3 CALIOP

Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) is a nadir-pointing lidar that has been orbiting the Earth on board the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite since 2006. CALIOP operates at two wavelengths (532 and 1064 nm) and measures total attenuated backscatter vertical profiles with vertical (30–300 m) and horizontal (300–5000 m) resolutions that vary with altitude. In the present study, we used the CALIOP product version 3.3 level 1B, which includes calibrated attenuated backscatter along with
<figure><img src="image_6.png" /></figure>

the contributions of the BB activity in Southern Africa and southern America are estimated at 22% and 20%, respectively. Although Australia is known for its intense BB events (Fromm et al., 2006; 2010; De Laat et al., 2012), the contribution of the Australian BB activity on the observed AOD variability over Reunion is relatively low (4.7%).

The Australian BB activity takes mainly place in the northern part of the continent between September and January (Russel-Smith et al., 2007). Nevertheless, the most disastrous fires burn in the southeastern region of Australia. Extreme fires occurring over southeastern Australia during the austral summer can lead to the development of pyro-convection events (Dowdy and Pepler, 2018; Fromm et al., 2010). Southeastern Australia has a long history of severe pyro-convection events which have significantly impacted the composition of the stratosphere at regional and global scales. The last and largest event occurred during the 2019-20 fire season (referred to as “Black Summer”). Previous works reported that this fire season is unrivaled with a surface burnt estimated at 19 million hectares (Boer et al., 2020; Cai et al., 2022; Levin et al., 2021). Furthermore, this extreme fire season can be considered as unprecedented due to persistent planetary-scale perturbations induced in the stratosphere (Kablick et al., 2020; Khaykin et al., 2020; Kloss et al., 2021; Ohneiser et al., 2020, 2022; Yu et al., 2020).

Kablick et al. (2020) showed at least 18 pyro-convection outbreaks occurred between 29th December 2019 and 12th January 2020 with the largest event occurring around 1st January 2020. Based on satellite observations and CESM-CARMA model results, Yu et al. (2021) showed that Australian wildfires burning from December 2019 to January 2020 injected approximately 0.9 Tg of smoke into the stratosphere. The analysis of the numerical simulations suggest that the smoke mass contained 2.5% black carbon which induced a 1 K warming in the stratosphere of the Southern Hemisphere mid-latitude for more than 6 months following its injection. The carbon-rich aerosol clouds were confined during their solar-driven rise by a persistent synoptic-scale anticyclone (Kablick et al., 2020; Khaykin et al., 2020). As a consequence, the highly-concentrated absorbing aerosols were lofted into the middle stratosphere, which prolongs their stratospheric residence time and radiative effect on climate. The combustion products injected into the stratosphere were advected by westerly winds and dispersed across all of the southern hemisphere extra-tropical latitudes (Khaykin et al., 2020; Ohneiser et al., 2020, 2022; Tencé et al., 2022; Yu et al., 2020). The stratospheric smoke layer was rapidly advected westward and its optical characteristics were measured by the lidar system installed at Punta Arena (53.2°S, 70.9°E; Chile) and Rio Grandé (53.8°S, 67.7°W, Argentina) one week following its injection (Ohneiser et al., 2022). Ohneiser et al. (2022) pointed out that the presence of the smoke layers extended, on average, from 9 to 24 km in height, with one part ascending to more than 30 km
collocated meteorological information provided by NASA's Global Modeling and Assimilation Office (GMAO). These data undergo postprocessing using a treatment described and validated by Vernier et al. (2009). Scattering ratio (SR) profiles used for the detection of the smoke plume are calculated following the methodology described by Khaykin et al. (2018). Initially, the collocated GMAO data correct the backscatter profiles of molecular attenuation and ozone absorption. Subsequently, the SR was calculated as the ratio of the total and molecular backscatter coefficients, with the latter derived from the GMAO air density. SR profiles were recalibrated at 36–39 km following the methodology given by Vernier et al. (2009). Data with a depolarization of larger than 30% were discarded from the treatment in order to avoid aliasing cirrus clouds above the thermal tropopause. CALIOP data were obtained from the Atmospheric Composition Data and Information Services Center (ACDISC) data archive (https://asdc.larc.nasa.gov/project/CALIPSO, last access: 29 June 2024) hosted by NASA's Goddard Space Flight Center.

### 2.1.4 OMPS-LP

The Ozone Mapper and Profiler Suite Limb Profiler (OMPS-LP) has been operational on the Suomi National Polar-orbiting Partnership (NPP) satellite platform since October 2011. In this study, we utilized aerosol extinction profiles from the NASA OMPS data product version 2.0 (Taha et al., 2021). These profiles were retrieved from the limb-scattered solar radiation measurements at wavelengths of 510, 600, 675, 745, 869, and 997 nm, chosen to minimize the impact of gaseous absorption. Aerosol extinction measurements are provided from 10 to 40 km altitude on a 1 km vertical grid, resulting in near-global coverage every 3–4 d. The OMPS data were employed to investigate the global transport of aerosol BB plumes and their influence on the aerosol variability over Réunion. Following the recommendation of Taha et al. (2021), we used aerosol extinction measurements at 745 nm. The background extinction profile was constructed using measurements obtained from 2012 to 2014 and from 2016 to 2018, excluding periods affected by the Calbuco eruption (Bègue et al., 2015). The OMPS data can be downloaded from https://ozoneaq.gsfc.nasa.gov/ (last access: 10 April 2024).

Additionally, we utilized aerosol absorbing index (AAI) data from OMPS to characterize the transport of the aerosol BB plume. The AAI enables the detection of absorbing aerosols by quantifying the spectral difference between specific pairs of UV wavelengths. Positive AAI values indicate the presence of UV-absorbing aerosols such as dust and smoke, while negative values suggest non-absorbing aerosols. Values close to zero typically correspond to the presence of clouds. The AAI data used in this work are available on the NASA Earth Data platform: https://earthdata.nasa.gov/earth-observation-data (last access: 10 April 2024).

## 2.2 CO and water vapour measurements

### 2.2.1 FTIR

Ground-based Fourier-transform infrared (FTIR) spectrometers enable the retrieval of total columns and volume mixing ratio profiles of trace gases like CO with high accuracy and precision (Clerbaux et al., 2008; Vigouroux et al., 2015; Zhou et al., 2019). In the present study, FTIR observations from Lauder and Réunion conducted as part of the framework of the NDACC and Total Carbon Column Observing Network (TCCON), respectively, are utilized. The FTIR systems and data retrieval methods are extensively described by de Mazière et al. (2018) and Wunch et al. (2015).

At Lauder, CO measurements have been made since the early 1990s using a Bruker high-resolution spectrometer over a wide spectral range (around 600–4500 cm⁻¹). The CO dataset used in this study aligns with that used by Bègue et al. (2021) and Kloss et al. (2019) and provides details on spectral measurements, the CO retrieval strategy, and derived CO column abundances. CO total columns and volume mixing ratio profiles for the Lauder site, spanning a 48-layer atmosphere (0.37–100 km a.s.l.), were obtained from the NDACC website (http://www.ndacc.org, last access: 10 April 2024).

At Réunion, FTIR measurements have been routinely conducted since 2011 within TCCON using a Bruker high-resolution spectrometer. The GGG2014 code (Wunch et al., 2015) was employed to simultaneously retrieve CO and O₂ total columns. The column-averaged dry-air mole fraction of CO was then determined as the ratio between the retrieved CO total columns and the total columns of dry air, leveraging the O₂ total columns provided by TCCON. CO abundance data for Réunion were sourced from the TCCON database (https://tccondata.org, last access: 5 April 2024). For this study, the background evolution of CO is established using measurements obtained between 2015 and 2018 (De Mazière et al., 2017).

### 2.2.2 IASI

The Infrared Atmospheric Sounding Interferometer (IASI) utilizes a Fourier-transform spectrometer to measure chemical species like CO (Clerbaux et al., 2009; Coheur et al., 2009). Operating aboard the three MetOp satellites, IASI retrieves CO total and partial columns in near-real time from the nadir radiances measured by the instrument in the thermal infrared, covering wavelengths from 6.62 to 15.5 µm. This enables the generation of global distributions for both day and night measurements covering the troposphere and lower stratosphere. Fast Optimal Retrievals on Layers for IASI (FORLI-CO; Hurtmans et al., 2012) was employed to retrieve total and partial CO columns while also flagging data contaminated by clouds. For this study, CO columns from IASI instruments on MetOp-A (operating since 2006) and MetOp-B (operating since 2012) are utilized. The IASI products used in this study can be accessed through the
<figure><img src="image_7.png" /></figure>

1 height as a result of self-lofting processes. The maximum smoke AOD was around 1.0 over
2 Punta Arenas in January 2020 and thus 2 to 3 orders of magnitude above the stratospheric
3 aerosol background of 0.005 (Ohneiser et al., 2022). Their results suggest an influence of this
4 stratospheric smoke layer on the record breaking ozone hole over Antarctica in September-
5 November 2020. This is consistent with the results reported by Tencé et al. (2022) from lidar
6 and ozonesondes measurements at the French Antarctic station Dumont d'Urville
7 (66.6°S, 140.0°E). Tencé et al. (2022) pointed out the persistence of smoke aerosols in the
8 southern high-latitude stratosphere following the pyro-convection events. They also reported
9 that the 2020 stratospheric ozone depletion is above the decadal average at Dumont d'Urville.

10 The common point among these studies is their interest for the perturbation induced by the
11 2019-20 Australian fires on the stratospheric composition, and on the dynamical circulation
12 over the extra-tropical latitudes. In contrast, relatively little attention has been paid to the
13 perturbation induced by this Australian smoke layer over the tropical/subtropical latitudes.

14 This study has two aims: 1) document the transport of the Australian smoke layer in the southern
15 subtropics over Indian Ocean during the January-February period which correspond to the wet
16 season, and 2) to investigate the influence of Australian aerosol smoke layers on variability of
17 the aerosol optical properties and CO in the Upper Troposphere-Lower Stratosphere (UT-LS)
18 of the SWIO basin accounting for convective activity. Convective activity is more intense
19 during this season as the Inter-Tropical Convergence Zone (ITCZ) is present over the whole
20 basin (Lashkari et al., 2017). Furthermore, the convective activity is often synonym of tropical
21 depression which can reach the stage of tropical cyclone (Barthe et al., 2021; Neuman et al.,
22 1993). The Regional Specialized Meteorological Centre (RSMC) at Reunion reported that the
23 cyclonic season 2019-20 was characterized by the development of 6 tropical cyclones and 4
24 tropical storms in the SWIO basin.

25 The study is organized as follows: Section 2 describes the observations and the model used for
26 the investigation of the transport of the aerosol smoke layer. A review of the formation and the
27 transport of the Australian aerosol smoke layer over the Southern Hemisphere is provided in
28 Section 3. An analysis of the influence of the Australian aerosol smoke layer on the aerosol and
29 CO variability over the SWIO basin is given in Section 4. The discussion on the influence of
30 the convective activity on the transport of the aerosol smoke layer over the SWIO basin is
31 provided in Section 5. A summary and the perspectives of this study are given in Section 6.

## 2. Instrumentation and Model description

### 2.1 Aerosols data sets
AERIS platform: https://iasi.aeris-data.fr/CO (last access: 10 April 2024).

### 2.2.3 MLS

The Microwave Limb Sounder (MLS) on board the Aura satellite has been conducting vertical profile measurements of various trace gases in the upper troposphere-lower stratosphere (UT-LS) since 2004 (Waters et al., 2006). For this study, CO and water vapour observations (version 5) from January 2017 to January 2020 were utilized, covering a global domain spanning between 10 and 25° S in latitude and 30 and 60° E in longitude. All MLS version 5 retrieval quality flags (quality, status, convergence, and precision) were meticulously followed for all analyses (Livesey et al., 2022). The recommended pressure levels for science applications with CO and water vapour MLS data range from 0.0215 to 215 hPa (see the version 5.0x level 2 and 3 data quality and description document at https://www.nasa.gov/last-access-10-april-2024). The CO and water vapour profiles from MLS were obtained from the ACDISC archive (ftp://acdisc.gsfc.nasa.gov, last access: 1 April 2024) hosted by the NASA Goddard Space Flight Center.

## 2.3 Numerical modelling

### 2.3.1 FLEXPART model

The Lagrangian transport and diffusion model FLEXPART version 10.4 is utilized in this study to simulate the long-range transport of atmospheric tracers (Pisso et al., 2019; Stohl et al., 2005). This version of FLEXPART incorporates improvements in various aspects, including microphysical and chemical parameterizations (Pisso et al., 2019). Source identification was achieved by releasing particles from a receptor location and simulating backward trajectories (Seibert and Frank, 2004). Model calculations rely on ERA5 reanalysis meteorological observations from ECMWF, extracted at 3-hourly intervals with a horizontal resolution of 0.5° × 0.5° and a vertical resolution of 137 hybrid model levels (Hersbach et al., 2020).

The model simulations involved aerosol – black carbon (BC) and organic carbon (OC) – and CO tracers and considered removal mechanisms such as dry and wet deposition for aerosols and OH reactions for CO. The parameterization (default values for the scavenging coefficient and the nucleation efficiency and size) for the BC was found in the paper by Grythe et al. (2017), and the chemical parameterization for CO was not found in FLEXPART data but can be found in the International Union of Pure and Applied Chemistry (IUPAC) reference kinetics database (Atkinson et al., 2006). Each simulation consists of 20 000 particles released over Réunion daily at altitudes between 15 and 19 km every 0.5 km, and it traces them backward in time over 1 month. Simulations of backward trajectories over long periods (1–2 months) have been explored in previous studies (Aliaga et

al., 2021; Eckhardt et al., 2017; Xu et al., 2021). The simulations included turbulence parameterization and convection activation (Forster et al., 2007).

Model outputs were distributed over a regular vertical grid from ground level to 25 km in altitude. These outputs were used to assess the residence times of the BB aerosols and CO, as well as their contributions to the variability of aerosol optical properties and CO over the SWIO basin. Discussions were based on emission sensitivity analysis using backward simulations. The residence time of particles was integrated over the entire atmospheric column and latitude to create averaged maps and longitudinal cross-sections, providing insights into the geographical and vertical dispersion of BB aerosols.

The BB contributions to the vertical distribution of CO and the aerosol optical properties were calculated by combining the potential emission sensitivity (PES) with an emission inventory, as explained in Stohl et al. (2003). The PES represents FLEXPART particles injected at the layer or altitude of emissions. Pyro-convection was not considered in the model. BB aerosol and CO mass concentration profiles were obtained by summing all output grid points. For BB emissions, the layer between 0 and 3 km was used for Africa and the layer between 9 and 16 km was used for Australian fires.

The Global Fire Assimilation System (GFAS) version 1.2 emission inventory (Kaiser et al., 2012) and the Global Air Pollutant Emissions – EDGAR v6.1 (Emission Database for Global Atmospheric Research) emission inventory (http://edgar.jrc.ec.europa.eu, last access: 10 April 2024) for CO were utilized. These emissions represent the total CO emissions from anthropogenic activities, excluding large-scale BB. Multiplying the CO emission flux from this inventory by the FLEXPART emission sensitivity for a layer between 0 and 1 km provides the contribution of anthropogenic sources to the total CO abundance. Finally, aerosol mass concentration profiles are converted into extinction profiles using the Mie scattering model, considering spherical particles with a density of 2 g cm⁻³ and a refractive index of 2.0 + 0.64i for optically absorbing aerosols.

### 2.3.2 MIMOSA model

The Modèle Isentropique de transport Mésoéchelle de l'Ozone Stratosphérique par Advection (MIMOSA) is a potential vorticity (PV) advection model designed to run on isentropic surfaces with a resolution of 0.3° × 0.3° (Hauchecorne et al., 2002). Its advection scheme is semi-Lagrangian with a time step of 1 h and is driven by ERA5 reanalysis meteorological observations. The model can be continuously run to track the evolution of PV filaments over several months. The accuracy of the MIMOSA model has been evaluated and validated in previous studies. Hauchecorne et al. (2002) assessed its accuracy, and it was validated against airborne lidar ozone measurements using a correlation between PV and ozone, as ozone behaves as a quasi-conserved
<figure><img src="image_8.png" /></figure>

1. The aerosol datasets used in this study resulted mainly from two ground-based observations sites from the Network for the Detection of Atmospheric Composition Change (NDACC, www.ndacc.org) network as well as a suite of spaceborne sensors products.

## 2.1.1 Lauder ground-based lidar

5. Aerosol optical properties measurements at Lauder (45.0°S; 169.7°E) have been performed using lidars since 1992. A detailed description of the lidar system operating at Lauder is given by Sakai et al. (2016), and it is summarized hereafter. The emitter system consists of a Nd:YAG laser beam at 532 nm and is linearly polarized. The lidar detects Rayleigh-Mie backscattering at 532 nm with parallel and perpendicular components. The methodology described by Fernald et al. (1984) is used to obtain the extinction and backscatter coefficient from a Rayleigh-Mie lidar. This methodology involves the use of an extinction-to-backscatter ratio for aerosol, also called lidar ratio (LR). For the January-May 2020 period, the values of LR derived with the lidar, are 88 and 60 sr for altitude above and below 23 km respectively. These values are obtained from the attenuation of the lidar signals by using the methodology described by Uchino et al. (1983) and by Young (1995). The aerosol depolarization is computed from the backscatter coefficient and the total linear volume depolarization ratio (Sakai et al., 2003). This latter is obtained by taking the ratio of the perpendicular to total components of the backscattered signal at 532 nm. To investigate the aerosol variability induced by the Australian fires, it is needed to define a background profile. The background profile is built from measurements performed when atmosphere is not undergoing major disturbance (e.g., volcanic eruptions, pyro-convection outbreaks). In the present work, the background extinction profile at Lauder is built from measurements performed between 1997 and 2004.

## 2.1.2 Reunion Island ground-based lidars

24. The Atmospheric Physics Observatory of La Réunion (OPAR) is a permanent station for long term atmospheric observations (Baray et al., 2013). In particular, two lidar systems operating in the UV (355 nm) and visible part of the light spectrum (532 nm) are used to retrieve ozone and aerosols profiles at the Maïdo Observatory situated at 2200 m above mean sea level (AMSL). These systems, named LiO3T (532 nm) and LiO3S (355 nm) are described by Duflot et al. (2017) and by Baray et al. (2006), respectively. These lidars measure aerosol optical properties (extinction, backscatter ratio) from ~15 km to the middle stratosphere, up to ~35 km, with a high vertical resolution (15 m). Operating at two distinct wavelengths, the synergy of Reunion lidar profiles allows us to assess the Angström exponent of aerosols between 355 nm and 532 nm. In this study, the inversion process used the Klett method (Klett, 1985) with an assumed lidar ratio of 60 sr, typical of aged BB aerosols (Müller et al., 2007). In the present
<figure><img src="image_4.png" /><figcaption>**Figure 1.** (a) Map of aerosol absorbing index obtained from OMPS observations and (b) scattering ratio profiles at 532 nm obtained from CALIOP observations on 1 January 2020. In panel (a), the orbit overpass of CALIOP is indicated by the blue curve, while the blue square corresponds to the Lauder site. The dashed black line in (b) corresponds to the 380 K isentropic level calculated from CALIOP observations.</figcaption></figure>

chemical tracer on timescales of a week or so within most of the lower stratosphere (Heese et al., 2001). Moreover, the MIMOSA model can be used to determine the origin of the air masses influencing a given site, similar to an isentropic Lagrangian trajectory model. This capability has been demonstrated in various studies (Bencherif et al., 2011; Hauchecorne et al., 2002; Portafaix et al., 2003; Bègue et al., 2017).

## 3 Formation of an intense stratospheric BB plume over Australia

Figure 1 shows the AAI obtained from OMPS on board CALIOP over New Zealand on 1 January. Following the strongest outbreak during New Year's Eve, a wide plume of BB aerosol with large values of AAI (higher than 12) is transported toward the Tasman Sea on 1 January 2020 (Fig. 1a). The CALIOP attenuated SR profiles are calculated along the CALIOP track (blue line in Fig. 1a) that crosses the absorbing aerosol plume above New Zealand. The CALIOP observations reveal a broad region of high values (ranging from 10 to 25) between 36 and 46° S that are centred at 16.5 km altitude (Fig. 1b).

Figure 2a illustrates the daily extinction profiles at 532 nm derived from lidar measurements over Lauder (New Zealand) between 1 December 2019 and 1 April 2020. Note that strong convective activity prevented lidar operations between mid-December 2019 and 1 January 2020. Figure 2a reveals high values for the extinction in the stratosphere over Lauder starting in mid-January 2020 (from $3 \times 10^{-3}$ to $9 \times 10^{-3}$ km$^{-1}$) that are 1 order of magnitude above the typical stratospheric aerosol background (Sakai et al., 2016). The vertical extent of the plume increased significantly between mid-January and 1 April 2020, with the aerosol layer spanning from 11.5

to 20 km. The ascent of the BB aerosol could be due to an adiabatic heating effect (De Laat et al., 2012). A statistically significant increase in sAOD (between 15 and 30 km) is observed in January 2020 (2.5 times higher than background value) and is still visible in April 2020 with same amplitude (Fig. 2b).

The same observation can be made for the carbon monoxide in the UT-LS over New Zealand, as shown in Fig. 3, based on observations made by the FTIR spectrometer at Lauder. Prior to the convective period, the maximum CO mixing ratio (120–130 ppbv) is observed in the troposphere (Fig. 3a). An increase in the CO mixing ratio in the lower stratosphere is visible from mid-December 2019, with the maximum (50–90 ppbv) observed in the UT-LS (9–13 km). The partial column of CO (between 9 and 30 km), calculated from the FTIR data, reaches its maximum values (~33% higher than the background value) in January 2020 and slightly decreases in April 2020 (~24% higher than the background value) (Fig. 3b). Above the lower stratosphere, the CO mixing ratio decreases significantly due to photochemical reactions which are more efficient with altitude (Brasseur and Solomon, 2005).

Our works suggest that the injected CO and absorbent aerosols end up de-correlated in altitude, given their different properties. In order to extend this discussion, the spatial dispersion of the Australian BB plume in the Southern Hemisphere will be discussed in the next section.
<figure><img src="image_9.png" /></figure>

study we used 9 lidar profiles recorded during the January-March 2020 period. The background extinction profile at Reunion is built from measurements performed between 2017 and 2019 excluding the perturbation induced by the Calbuco eruption in April 2015 (Bègue et al., 2017).

### 2.1.3 CALIOP

Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) is a nadir pointing lidar orbiting the Earth onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite since 2006. CALIOP is a two-wavelength polarization-sensitive lidar (532 and 1064 nm) that measures total attenuated backscatter vertical profiles with altitude-varying vertical (30-300 m) and horizontal (300-5000 m) resolution. In the present study, we used CALIOP product version 3.3 level 1B which includes calibrated attenuated backscatter along with collocated meteorological information provided by the National Aeronautics and Space Administration Global Modeling and Assimilation Office (GMAO). These data are postprocessed using a treatment described and validated by Vernier et al. (2009). The Scattering Ratio (SR) profiles used for the detection of the smoke plume are calculated following the methodology described by Khaykin et al. (2018). As a first step, the collocated GMAO data is used to correct the backscatter profiles of molecular attenuation and ozone absorption. Then, the SR is calculated as the ratio of total and molecular backscatter coefficients, with the latter derived from GMAO air density. The SR profiles are recalibrated at 36-39 km, following the methodology given by Vernier et al. (2009). The data with depolarization larger than 30 % are discarded to the treatment in order to avoid aliasing cirrus clouds above the thermal tropopause.

The CALIOP data were obtained from the ACDISC data archive (ftp://acdisc.gsfc.nasa.gov) hosted by NASA Goddard Space Flight Center.

### 2.1.4 Sun photometry measurements: Sky radiometer

A sky radiometer is a scanning sun-sky photometer able to perform measurements of direct sun and diffuse sky irradiance under clear sky conditions, at seven wavelengths (between 315 and 1020 nm) and at several scattering angles. The direct solar extinction and diffuse sky radiance measurements are used to derive the aerosol optical properties such as Aerosol Optical Depth (AOD), Single Scattering Albedo (SSA) and aerosol size-distributions using the algorithm developed by Nakajima et al. (1996). A detailed description of the sky radiometer and the associated data retrieval is given by Hashimoto et al. (2012). In the present study, we used the sky radiometer observations performed at Lauder in the framework of the SKYNET network. SKYNET is a ground-based network of sky radiometers with observation sites spread over Asia and other areas. Previous works have shown that the AOD from SKYNET is obtained with high accuracy similar with that of the standard Langley method and with those from AERONET
<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /></figure>

**Figure 2.** Time series of (a) daily profiles of aerosol extinction and (b) monthly means of the stratospheric AOD (sAOD; between 15 and 30 km) at 532 nm obtained from lidar observations made between 1 December 2019 and 1 April 2020. In order to screen non-aerosol contributors (such as clouds) to the extinction measurements, a mask based on the method reported by Nicolae et al. (2013), which considers plausible aerosol properties, was used. Specifically, we only kept profile parts with positive depolarization values, and the Ångström exponent ranges from 0.1 to 4. The grey line indicates the tropopause height obtained from radiosonde measurements. The background evolution of aerosol data and the associated standard deviation are shown by the black line and grey area, respectively.

# 4 Transport of the Australian BB plume over the SWIO basin

## 4.1 Aerosol and CO variability over a subtropical site: Réunion

Figure 4 shows time-averaged maps of AOD from OMPS and CO partial column (9–30 km) from IASI observations. The transport of the aerosol (with values ranging from $6 \times 10^{-3}$ to $1 \times 10^{-2}$ km$^{-1}$) and CO (with values ranging from 6 to $8 \times 10^{17}$ molec.cm$^{-2}$) plume over the southern Pacific oc-

<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /></figure>

**Figure 3.** Time series of (a) daily profiles of CO mixing ratio and (b) monthly means of the partial column of CO (between 9 and 30 km) obtained from FTIR at Lauder between 1 December 2019 and 1 April 2020. The background evolution of the partial column of CO and the associated standard deviation are shown as the black line and grey area, respectively.

curred mainly within the 18–60° S latitudinal band. One can observe an aerosol band (with values ranging from $5 \times 10^{-3}$ to $9 \times 10^{-3}$ km$^{-1}$) across the Southern Hemisphere between 40 and 60° S during the period from 9–16 January 2020 (Fig. 4a). The Australian aerosol plume circled the Southern Hemisphere during the first 2 weeks of January 2020. The same conclusion cannot be made for CO from space-borne observations (Fig. 4b). One can observe weak values of CO (less than $5 \times 10^{17}$ molec.cm$^{-2}$) over the southern Atlantic that are not significantly linked with the large plume observed over the southern Pacific (Fig. 4b).

Figure 5a depicts the evolution of the sAOD (between 15 and 30 km) at 532 nm calculated from ground-based lidar and OMPS observations over Réunion from 1 January to 1 March
<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

1 (Campanelli et al., 2007; Che et al., 2008). At Lauder, the sky radiometer measurements have

2 been made since 2011. These observations are used in the present study to investigate the

3 aerosol variability induced by the passage of the Australian BB plume over Lauder. The

4 background evolution of AOD is built with measurements performed between 2011 and 2018.

5 The sky radiometer data used in this work are available on the SKYNET platform:

6 https://www.skynet-isdc.org/

## 2.1.5 OMPS-LP

8 The Ozone Mapper and Profiler Suite Limb profiler (OMPS-LP) has been flying on the Suomi

9 National Polar Partnership (NPP) satellite platform since October 2011. In the present study,

10 we use aerosol extinction profile from the NASA OMPS data product version 2.0 (Taha et al.,

11 2021). The aerosol extinction profiles are retrieved from the limb scattering solar radiation. The

12 V2.0 algorithm uses OMPS-LP measurements at wavelengths 510, 600, 675, 745, 869 and 997

13 nm, selected to minimize the effect of gaseous absorption (Taha et al., 2021). Aerosol extinction

14 measurements are provided from 10 to 40 km altitude on a 1 km vertical grid. A near-global

15 coverage is produced within 3-4 days. The OMPS data are used in the present study to

16 investigate the global transport of aerosol BB plume and its influence on the aerosol variability

17 over Reunion. As recommended by Taha et al. (2021), we use aerosol extinction measurements

18 at 745 nm. The background extinction profile is built with measurements performed from 2012

19 to 2014 and from 2016 to 2018. These periods are chosen in order to discard the perturbation

20 induced by the Calbuco eruption (Bègue et al., 2015). The OMPS data are downloaded from:

21 https://ozoneaq.gsfc.nasa.gov/.

22 The aerosol absorbing index (AAI) data from OMPS are also used to describe the transport of

23 the aerosol BB plume. This index allows the detection of absorbing aerosols through the

24 spectral difference between a given pair of UV wavelength. When its value is positive, it

25 indicates the presence of UV-absorbing aerosols such as dust and smoke. Conversely, a

26 negative value indicates the presence of non-absorbing aerosols while values close to zero are

27 found in the presence of clouds. The AAI data used in this work are available on the NASA

28 Earth Data platform: https://earthdata.nasa.gov/earth-observation-data

## 2.2 CO and water vapor measurements

### 2.2.1 FTIR

31 The total columns and volume mixing ratio profiles of trace gases such as CO are retrieved with

32 high accuracy and precision with ground-based Fourier Transform Infrared (FTIR)

33 spectrometers (Clerbaux et al., 2008; Vigouroux et al., 2015; Zhou et al., 2019). In the present

34 study, we use the FTIR observations performed at Lauder and Reunion sites in the framework
<figure><img src="image_9.png" /><figcaption>**Figure 4.** Time-averaged (from 9 to 16 January 2020) maps of (a) sAOD (between 15 and 30 km at 532 nm) obtained from OMPS observations and (b) the partial column of CO (averaged between 9 and 30 km) obtained from IASI observations. The locations of the Réunion and Lauder sites are indicated by “R” and “L”, respectively.</figcaption></figure>

2020. OMPS extinctions are converted to 532 nm using an Ångström exponent for the 532–745 nm wavelength pair of 1.9, as prescribed by Taha et al. (2021). Réunion witnessed an abrupt increase in the aerosol loading (3 times the typical background) as of 16 January 2020, according to satellite observations. The sAOD values observed between 16 January and 1 March 2020 are higher than those observed during the passage of the Calbuco plume over the Réunion site, which did not exceed 0.013 (Bègue et al., 2017). The increase in sAOD in mid-January coincided with an increase in CO, as shown in Fig. 5b based on the use of partial columns (between 9 and 30 km) and the CO abundance from IASI and FTIR data at the same site over the same period. The ground-based observations show that the CO abundance observed during this increased phase is on average 20% higher than the values observed during the background period (Fig. 5b). The evolution of the sAOD and CO observations in mid-January suggests that Réunion and its surroundings were influenced by the transport of the Australian BB plume.

Figure 6 shows aerosol extinction profiles at 355 nm over Réunion for selected days in January or February compared to the January or February background profiles. The first 2 weeks of January 2020 are representative of the typical background in January (shaded area), as illustrated for 13 January 2020 (Fig. 6a). Conversely, the extinction profiles at the end of January 2020 (27 and 28 January) are marked by a significant increase (4 times higher than the background values) in the lower stratosphere between 16.8 and 18 km altitude (equivalent to potential temperature levels of 380–

404 K). On 28 January, the extinction profile exhibits a sudden increase at 17.4 km (~400 K) but quickly decreases afterwards to values observed the previous day (Fig. 6a). The values of extinction (10 to 17 × 10⁻³ km⁻¹) observed in the lower stratosphere on these 2 d are of the same order as those observed at Lauder a few days after the pyro-convective event (Fig. 2). In February, the extinction profiles clearly exhibit two significant aerosol layers, with the first one located between 16 and 19.5 km (370–440 K) and the second one between 20 and 22.5 km (465–500 K) (Fig. 6b).

To further discuss the optical properties of these aerosol layers, the Ångström exponent has been calculated between 355 and 532 nm from the ground-based lidar measurements (Fig. 6c and d). In February, the Ångström exponent values reveal that the two aerosol layers consist mainly of small aerosol particles (Fig. 6d), consistent with a stratospheric smoke layer (Haarig et al., 2018; Hu et al., 2019; Ohneiser et al., 2021). In January, the profile of the Ångström exponent exhibits more variability in the UT-LS (Fig. 6c), with values ranging from 0.6 to 1.9 on 27 and 28 January. The wide range of Ångström exponent values suggests that the aerosol layer is not homogeneously distributed at this stage and might be interpreted as a mixture of fresh and aged smoke layers (Fig. 6c). Indeed, Müller et al. (2007) showed that the ageing of transported smoke translates into a decrease in the Ångström exponent. This may indicate growth and removal processes (e.g. coagulation, condensation, and sedimentation) which can modulate the morphology and mixing
<figure><img src="image_12.png" /></figure>

1 of the NDACC and Total Carbon Column Observing Network (TCCON) networks
2 respectively. A detailed description of the FTIR systems involved in both networks and the
3 associated data retrieval is given by de Mazière et al. (2018) and Wunch et al. (2015). A brief
4 description is given hereafter. The CO measurements from FTIR at Lauder have been made
5 since the early 1990s. The measurements are made using a Bruker high-resolution spectrometer
6 over a wide spectral range (around 600–4500 cm⁻¹). The CO dataset used in this study is the
7 same as that used by Bègue et al., (2021) and Kloss et al., (2019). Details on the spectral
8 measurements, CO retrieval strategy and derived CO column abundances can be found within
9 these references. The CO total columns and volume mixing ratio profiles on 48-layer
10 atmosphere (0.37–100 km asl) used in this study for the Lauder site are downloaded from the
11 NDACC website (http://www.ndacc.org).

12 The FTIR measurements at Reunion have been routinely performed in the framework of the
13 TCCON network since 2011. A Bruker high-resolution spectrometer over a wide spectral range
14 is also used at Reunion. The CO and O₂ total columns are simultaneously retrieved by using the
15 GGG2014 code (Wunch et al., 2015). Column-averaged dry-air mole fraction of CO are
16 obtained from the retrieval of these two components. TCCON uses the O₂ total to determine
17 the total column of the dry air. Then, the column-averaged dry-air mole fraction of CO is
18 calculated as the ratio between the retrieved CO total columns and the total columns of the dry
19 air. The abundance of CO used in the study for Reunion are downloaded from the TCCON
20 database (http://www.ndaccdemo.org/about/cooperating-networks/total-carbon-column-
21 observing-network). In the present study, the background evolution of CO is built with
22 measurements performed between 2015 and 2018 (De Mazière et al., 2017).

2.2.2 IASI

24 The Infrared Atmospheric Sounding Interferometer (IASI) measures chemical species such as
25 CO by using a Fourier Transform spectrometer (Clerbaux et al., 2009; Coheur et al., 2009). It
26 is flying onboard the three Metop satellites. Retrieval of CO total and partial columns occurs in
27 near real-time from the nadir radiances measured by the instrument in the thermal infrared
28 radiation covering wavelengths from 6.62 to 15.5 µm. Global distributions are obtained for day
29 and night measurements, with a vertical range covering the troposphere and the lower
30 stratosphere. The total and partial column of CO are retrieved by using the Fast-Optimal
31 Retrievals on Layers for IASI (FORLI-CO, Hurtmans et al., 2012). Furthermore, the
32 contamination of the data by clouds is checked and flagged. In the present study, we used CO
33 columns from IASI instruments on Metop-A and Metop-B, which have been operating since
<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

**Figure 5.** Daily mean evolution of aerosol (a) and CO (b) abundances obtained from ground-based and satellite observations at Réunion between 1 January and 1 March 2020. The partial column (molec. cm⁻²) and abundance (ppb) of CO obtained from IASI (blue line) and FTIR (red line) data, respectively, are given in the lower panel (b), while the sAOD obtained from OMPS (red line) and lidar (blue and green dots) is given in the upper panel (a). The black line and shaded region correspond to the monthly mean and the associated standard deviation calculated for the background period, respectively.

state of the aerosol layer during its transport (Burton et al., 2015; Hamil et al., 1997).

## 4.2 Origin of the air masses

To analyse the origin of the air masses at Réunion on 27 and 28 January, 1-month backward trajectories were calculated using FLEXPART (Aliaga et al., 2021; Eckhardt et al., 2017; Xu et al., 2021). A period of 1 month was chosen because it refers to the time lapse separating the pyroconvective outbreak event and the day of the measurement at Réunion. The representation of the potential emission sensitivity (PES) from back-trajectory simulations initialized at

<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /></figure>

<figure><img src="image_15.png" /></figure>

**Figure 6.** Aerosol extinction (at 355 nm) (a, b) and the Ångström exponent (355–532 nm) (c, d) obtained from lidar observations at Réunion in the months of January and February 2020. The tropopause height is indicated by the horizontal orange lines.

18 km and originating from Réunion on 27 and 28 January 2020 is presented in Fig. 7.

Figure 7a and c display the horizontal trajectories, whereas vertical movement is shown in Fig. 7b and d, respectively. The vertical transect of FLEXPART back trajectories in Fig. 7b confirms a high probability of an air mass contribution from Australia if the fire emissions are directly injected into the stratosphere by convection (black rectangle in the figure), i.e. injection into the layer from 9 to 16 km is used for the PES; see Sect. 2.3.1. According to the FLEXPART results, part of the Australian smoke layer is advected zonally by the prevailing easterly winds and is observed over Réunion on 27 and 28 January 2020 at 18 km. The FLEXPART simulations also suggest that Réunion is influenced by eastward transport of air masses. This pathway is clearly visible on 28 January 2020 (Fig. 7c and d). Air masses from high latitudes seem to cross the subtropical latitudes along a wave-shaped path and reach the SWIO basin by passing over the Cape of Good Hope (Fig. 7c).
<figure><img src="image_13.png" /></figure>

1 2006 and 2012, respectively. The IASI products used in this work are available on the AERIS

2 platform: https://iasi.aeris-data.fr/CO.

3 **2.2.3 MLS**

4 The Microwave Limb Sounder (MLS) performs vertical profile measurements of multiple trace
5 gases in the UT-LS onboard Aura satellite since 2004 (Waters et al., 2006). In the present study,
6 the CO and water vapor observations (version 5) from January 2017 to January 2020 over a
7 global domain extending between 10°S and 25°S in latitude and 30°E and 60°E in longitude have
8 been used. All MLS version 5 retrieval quality flags (quality, status, convergence, and
9 precision) were properly adhered to for all of our analyses (Livesey et al., 2020). Generally,
10 recommended pressure levels for science applications with CO and water vapor MLS data range
11 from 0.0215 to 215 hPa (http://mls.jpl.nasa.gov/data/v4-2_data质量_document.pdf). The
12 CO and water vapor profiles from MLS are obtained from the Atmospheric Composition Data
13 and Information Services Center (ACDISC) archive (ftp://acdisc.gsfc.nasa.gov) hosted by the
14 NASA Goddard Space Flight Center.

15 **2.3 Numerical Modelling**

16 **2.3.1 FLEXPART Model**

17 The Lagrangian transport and diffusion model FLEXPART version 10.4 is used to simulate
18 long-range transport of atmospheric tracers (Pisso et al., 2019; Stohl et al., 2005). This version
19 of FLEXPART includes improvements in different aspects such as physico-chemical
20 parameterizations (Pisso et al., 2019). Source identification occurs via the release of particles
21 from a receptor location and the simulation of backward trajectories. Model calculations are
22 based on ERA5 (Hersbach et al., 2020) meteorological data from the European Center for
23 Medium-Range Weather Forecasts (ECMWF) extracted at 3-hourly intervals with a horizontal
24 resolution of 0.5° × 0.5° and a vertical resolution of 137 hybrid model levels (from the ground
25 to 0.01 hPa pressure altitude).

26 The model simulations are run with the aerosol (BC and OC) and CO tracers assuming removal
27 by dry and wet deposition for aerosols and OH reactions for CO. Each simulation consists of
28 20,000 particles released over Reunion during one day at altitudes between 15 and 19 km every
29 0.5 km and followed backward in time during one month. The simulation of backward
30 trajectories with FLEXPART for a long period (1-2 months) were previously explored in
31 previous studies (Aliaga et al., 2021; Eckhardt et al., 2017; Xu et al., 2021). The simulations
32 include the parameterization of turbulence and the activation of the convection. FLEXPART
33 model outputs are distributed over a regular vertical grid of 0.5°x 0.5° from ground to 25 km in
34 altitude. The model outputs are used to discuss the residence time of the BB aerosols and CO,
<figure><img src="image_16.png" /></figure>

**Figure 7.** FLEXPART 30 d back trajectories initialized from Réunion (black cross) at 18 km on 27 January 2020 (a, b) and 28 January 2020 (c, d). Panels (a) and (c) correspond to the integration of the trajectory positions over the whole altitude range. Panels (b) and (c) show the vertical views integrated over the whole latitude ranges of the back trajectories in (a) and (c), respectively. The black rectangle represents the injection height of the BB aerosols.

In order to delve further into this eastward transport of air masses over the SWIO basin, the MIMOSA model has been used to produce a continuous evolution of PV fields for the period from 1 to 31 January 2020 for the 400 K isentropic level. The localization of the aerosol plume obtained from OMPS observations at the 400 ± 5 K isentropic level is also superimposed (Fig. 8). The 400 K isentropic level is chosen according to the layers observed in the extinction profiles over Réunion between the 390 and 404 K isentropic levels on 27 and 28 January 2020 (Fig. 6a). Air masses from mid-latitudes (40–60° S) cross the subtropical latitudes (20–40° S) and are advected eastward between South Africa and Madagascar along a wave-shaped path (Fig. 8). Given that the Australian BB aerosol is mainly located in the mid-latitudes (Fig. 4a), we can reasonably conclude that the filament reaching the SWIO basin contains aerosol from the Australian BB event. On 27 January, air masses containing aerosol are observed at Madagascar and its surroundings (Fig. 8a). These air masses are advected eastward and reach Réunion on 28 January (Fig. 8b).

<figure><img src="image_17.png" /></figure>

**Figure 8.** Advected PV map at the 400 K level obtained from the MIMOSA model (a) for 27 January 2022 and (b) for 28 January 2022. The white dots represent the localization of the aerosol plume at 400 ± 5 K obtained from OMPS observations, while the black cross indicates Réunion.

Our analysis demonstrated that the Australian BB plume was transported over the SWIO basin along two distinct pathways.

### 4.3 Contribution of the Australian BB plume to the CO and aerosol variability

Because a significant simultaneous increase in CO and sAOD is observed over Réunion and its surroundings from 16 to 29 January 2020, the investigation will focus on this period. The emission sensitivity from FLEXPART at the altitude where the emissions are injected is combined with the CO and aerosol (BC and OC) emission inventory. The CO emissions due to anthropogenic activity are also taken into account by coupling the FLEXPART model with the EDGAR inventory information. The simulated sAOD compares fairly well with the available satellite observations during the 15–
<figure><img src="image_14.png" /></figure>

and their contributions on the variability of the aerosol optical properties and CO over the SWIO basin. Discussions are based on the analysis of the emission sensitivity obtained from backward simulations. The residence time of particles are integrated over the entire atmospheric column and over the latitude to create averaged-map and longitudinal cross-section map and to provide information on the geographical and vertical dispersion of BB aerosols in the atmosphere. The BB contributions on the vertical distribution of CO and the aerosol optical properties can be calculated by combining the potential emission sensitivity (PES) with an emission inventory. PES represents FLEXPART particles only in the layer/altitude at which the emissions are injected. Pyro-convection is not taking into account in the model (nor ECMWF data). Then, a mass concentration profile of BB aerosol and CO is extracted by summing all the output grid-points. A layer between 0 and 3 km is used for the BB in Africa (as observed in GFAS "top altitude of plume", Kaiser et al., 2012) and between 9 and 16 km for the Australian fires (as observed by CALIOP observations)

In the present study, the Global Fire Assimilation System (GFAS) version 1.2 emission (Kaiser et al., 2012) has been used for the calculation. In addition, the Global Air Pollutant Emissions - EDGAR v6.1 emission inventory (Kaiser et al., 2012, http://edgar.jrc.ec.europa.eu) is used for CO for the year 2018 with a 0.1° × 0.1° grid. These emissions represent the total CO emissions by anthropogenic activities by excluding large scale BB with Savannah burning, forest fires. As for the BB emissions, multiplying the CO emission flux from this inventory with the FLEXPART emission sensitivity for a layer between 0 and 1 km gives access to the contribution of anthropogenic sources to the total CO abundance. At the end of the process, in the case of aerosols, the mass concentration profile is converted in extinction profile in order to discuss on the contribution of BB aerosols on the vertical distribution of the aerosol extinction observed from Lidar over Reunion. The conversion is performed by the use of Mie scattering model assuming spherical particles with a density of 2 g.cm⁻³ and a refractive index of 2.0 + 0.64i adapted to optically absorbing aerosols.

### 2.3.2 MIMOSA Model

The Modèle Isentropique de transport Mésoéchelle de l'Ozone Stratosphérique par Advection (MIMOSA) model is a potential vorticity (PV) advection model running on isentropic surfaces at a resolution of 0.3° × 0.3° (Hauchecorne et al., 2002). The advection scheme is semi-Lagrangian with a time step of 1 h and driven by ECMWF meteorological analyses. The model can be run continuously in order to follow the evolution of PV filaments for several months. The accuracy of the model has been evaluated by Hauchecorne et al. (2002) and validated against airborne lidar ozone measurements using a correlation between PV and ozone, a quasi-
<figure><img src="image_18.png" /><figcaption>**Figure 9.** (a) Daily evolution of sAOD (calculated between 15 and 30 km at 532 nm) obtained from OMPS-LP (red line) and lidar (blue dots) and simulated by FLEXPART (orange line) over Réunion from 15 to 29 January 2020. (b) Daily evolution of the partial column (calculated between 9 and 30 km) of CO observed by IASI (red line) and simulated by FLEXPART (orange line) over Réunion from 15 to 29 January 2020. The CO evolution is simulated by FLEXPART, with only the CO emissions (including BB and anthropogenic activity) considered from among the Australian emissions. The simulated sAOD is calculated by considering only the aerosol emissions (BC and OC) from among the Australian emissions.</figcaption></figure>

29 January period, and the peak observed in mid-January is acceptably well reproduced. Conversely, the partial column of CO seems less consistent with the observations made by IASI.

The discrepancies between FLEXPART and observations may be attributable to several possible caveats. One could be the lack of the vertical motion induced by pyro-convection in FLEXPART. We tested this issue by applying an injection height in agreement with CALIOP observations (9–16 km, Fig. 1) for the Australian plume (Khaykin et al., 2020). The injection height of the plume plays a key role in its long-range transport (Sofiev et al., 2012). An inappropriate or unrealistic injection height can lead to either a dilution or an overestimation of the plume. The injection height depends on the intensity of the fire as well as on the meteorological conditions. Another possible explanation for these differences could come from the duration of the backward calculation

(1 month) and an underestimation of the emission by GFAS (Brocchi et al., 2018). Using FLEXPART simulations, Brocchi et al. (2018) revealed that an amplification factor of 2 can be applied to CO emissions from GFAS to obtain CO quantities comparable with observations. The other source of difference between the model and the observations stems mainly from whether or not FLEXPART takes several regions into account as a source of pollution. The results shown in Fig. 9 target emissions from Australia only. The contribution of other regions is discussed in Sect. 5.

On average, the aerosol emissions from Australia contributed up to 95% of the sAOD variability over Réunion from 15 to 29 January (Fig. 9a). Conversely, the CO emissions from Australia contributed up to 10% of the enhancement of the partial column of CO from 15 to 29 January (Fig. 9b). Therefore, the CO plume induced by Australian sources is not efficiently transported over the SWIO basin. The variability in CO over the SWIO basin in January is therefore not significantly driven by emissions from Australian fires.

## 5 Discussion of the influence of regional sources

The fire radiation power (FRP) gives quantitative information on the combustion rate and intensity (Fig. 10a). The sparse activity of African fires in January is clearly illustrated in Fig. 11a, with moderate values of FRP ranging from 20 to 200 MW m⁻². These values are 10 times lower than those observed over southeastern Australia between 30 December 2019 and 12 January 2020 (Bègue et al., 2021). The off-season African BB activity in January 2020 is mainly located over the northwestern (near the Equator) and southeastern sides of southern Africa. The most intense values (100–200 MW m⁻²) are observed over the southeastern side.

Despite this sparse activity of BB, the amount of CO injected into the atmosphere is fairly significant (from 5 to 6 × 10¹⁷ molec. cm⁻²), as shown in Fig. 10b. The partial column of CO (between 9 and 30 km) over southern Africa from 16 and 29 January is characterized by two regions of high values (higher than 5 × 10¹⁷ molec. cm⁻²; Fig. 10b). The first region stretches between the eastern side of southern Africa and the western side of Madagascar, which corresponds to a domain extending between 10 and 25° S in latitude and between 30 and 45° E in longitude (Fig. 10b). The second region is located on the opposite side, over a domain extending between latitudes 10 and 15° S and longitudes 5 and 15° E.

The main convective regions presenting negative outgoing longwave radiation anomalies are located in mainland Africa between 12 and 25° S and on the northern side of the SWIO basin between 16 and 29 January, as shown in Fig. 10c, based on observations obtained from the National Centers for Environmental Prediction (NCEP). The daily brightness temperature values obtained from MODIS during the same period (not shown) range from 195 to 210 K over the eastern side
<figure><img src="image_15.png" /></figure>

conserved chemical tracer on timescales of a week or so within most of the lower stratosphere (Heese et al., 2001). The MIMOSA model can also be used to determine the origin of air masses influencing a given site, similar to an isentropic Lagrangian trajectory model (Bencherif et al., 2011; Hauchecorne et al., 2002; Portafaix et al., 2003; Bègue et al., 2017).

# 3. Transport of the Australian BB plume over the Southern Hemisphere

## 3.1 Formation of an intense stratospheric smoke layer

Following the strongest outbreak during New Year's Eve, a wide plume of BB aerosol with large values of AAI (higher than 12) is transported toward the Tasman Sea on 1st January 2020 (Fig. 1a). Figure 1b depicts the CALIOP attenuated scattering ratio (SR) profiles on 1st January 2020 above New-Zealand. The CALIOP attenuated SR profiles are calculated along the CALIOP track (blue line in Fig. 1a) crossing the absorbing aerosol plume. CALIOP observations reveal a broad region of high values (ranging from 10 to 25) between 36° S and 46°S centered at 16.5 km altitude (Fig. 1b). Khaykin et al. (2018) reported similar values during the passage of the 2017 Canadian smoke plume over Observatoire de Haute-Provence (OHP, France). Figure 1 reveals that New Zealand was significantly exposed to the transport of the Australian BB plume. The ground-based measurements recorded in New-Zealand are helpful to investigate the evolution of the aerosol smoke. Figure 2a illustrates the daily extinction profiles at 532 nm derived from lidar measurements over Lauder between 1st December 2019 and 1st April 2020. Note that a strong convective activity prevented lidar operations between mid-December 2019 and the 1st January 2020. Figure 2a reveals a sharp increase in the extinction in the stratosphere over Lauder starting from mid-January 2020 with values ranging from $3 \times 10^{-3}$ km$^{-1}$ to $9 \times 10^{-3}$ km$^{-1}$, one order of magnitude above the typical stratospheric aerosol background (Vernier et al., 2012). The vertical extent of the plume increased significantly between mid-January and 1st April 2020 with an aerosol layer spanning from 11.5 to 20 km. The ascent of the aerosol plume could be attributed to efficient adiabatic heating as a result of the strong absorption of solar radiation by this black carbon rich plume. This is consistent with the results found by De Laat et al. (2012) during the Australian Black Saturday fires occurring on February 2009. They showed a strong ascent of the BB aerosol due to adiabatic heating effect. Figure 2b depicts the daily evolution of CO mixing ratio profile obtained from FTIR measurements over Lauder between 1st December 2019 and 1st April 2020. Prior to the convective period, the maximum of CO mixing ratio (120-130 ppbv) is observed in the troposphere. An increase of CO mixing ratio in the lower stratosphere is visible from mid-
<figure><img src="image_19.png" /><figcaption>**Figure 10.** (a) The total number of fire pixels and the associated fire radiative power obtained from MODIS observations made between 16 and 29 January 2020. The red line indicates the average position of the ITCZ (from Lashkari et al., 2017). (b) Time-average map of the partial column of CO (calculated between 9 and 30 km) obtained from IASI observations averaged between 16 and 29 January 2020. The black square corresponds to the study domain where the vertical cross-section of CO and the water vapour mixing ratio are calculated and reported in Fig. 11. (c) Time-average map of outgoing longwave radiation anomalies obtained from the National Centers for Environmental Prediction (NCEP) between 16 and 29 January 2020. The red curve corresponds to the trajectory followed by the strong tropical storm Diane from 22 to 29 January 2020. This trajectory was obtained from the RSMC (Regional Specialized Meteorological Center) of Réunion best-track database.</figcaption></figure>

of southern Africa and the northern tip of Madagascar. These values of brightness temperature can be attributed to deep convection clouds (Héron et al., 2020; Young et al., 2013).

On average, the motion of the ITCZ over southern Africa in January is characterized by southward motion from 5°N to 20°S in latitude and between 20 and 35°E in longitude (Fig. 10a; Lashkari et al., 2017). A tropical depression formed near the northwestern side of Madagascar between 20 and 22 January 2020. This tropical depression reached the stage of a strong tropical storm on 24 January 2020 and was named Diane by the RSMC of Réunion. The tropical depression intensified into a strong tropical storm around the northern tip of Madagascar. Diane passed near Réunion on 25 January 2020 (Fig. 10c). The convective activity over southern Africa and the SWIO basin may hence be due to both the proximity of the ITCZ and the activity of Diane.

To further investigate the convection-driven pathway, the vertical cross-sections of the CO and water vapour mixing ratio anomalies calculated from MLS observations between 16 and 29 January 2020 are analysed (Fig. 11a and b). The CO and water vapour mixing ratio anomalies are calculated as relative differences by considering the monthly background means as the reference values. The calculations are performed over a domain extending between 10 and 25°S in latitude and 30 and 60°E in longitude (the black box in Fig. 10b). This domain includes both the region of deep convection and the first region of high values of CO. The monthly background is calculated from available MLS observations in January between 2017 and 2019. Figure 12a exhibits two regions of high values of CO mixing ratio anomalies (higher than 15%) centred at 37 and 50°E in longitude at 146 hPa (~15 km) and 100 hPa (~17 km). These regions of CO mixing ratio anomalies are coincident with two regions
<figure><img src="image_16.png" /></figure>

December 2019. One can observe that the maximum of the CO mixing ratio (50-90 ppbv) is mainly observed in the UT-LS (9-13 km) during the February-April 2020 period.

The injection of BB aerosols and CO in the stratosphere induced significant disturbance evident in the total columns over Lauder (Fig. 3a). Figure 3a depicts the monthly mean evolution of AOD and total columns of CO (TCO) at Lauder between 1st December 2019 and 1st April 2020 obtained from sky-radiometer and FTIR measurements respectively. AOD reaches its maximum value (0.17, 3 times higher than background value) in January 2020, decreasing to background values in February 2020 (Fig. 3a). The similar evolution is also observed for the TCO values. An abrupt increase in TCO (~9 % of the pre-event levels) is observed in January 2020 and the return to pre-event values is observed as of February 2020 as also already shown in Kloss et al. (2021). Conversely, the perturbation on the stratospheric columns still persisting after February 2020. Figure 3b illustrates the monthly mean evolution of stratospheric AOD (sAOD) and CO columns (sCO) at Lauder between 1st December 2019 and 1st April 2020. The sAOD and sCO are calculated between 12 and 30 km from lidar and FTIR measurements, respectively. Figure 3b indicates that the evolution of sAOD and sCO is fairly similar. A statistically significant increase of sAOD is observed in January 2020 (2.5 times higher than background value) and still visible in April 2020 with same amplitude. sCO reaches its maximum values (~24 % of the pre-event levels) in January 2020 and slightly decreases in April 2020 (~14% of the pre-event). This result is consistent with results found by Khaykin et al. (2020). Based on the MLS observations, Khaykin et al. (2020) showed that the stratospheric mass of CO within the southern extra-tropics increased abruptly by around 20% compared to the observed value during the pre-event period.

Our results agree with previous studies (Kablick et al., 2020; Khaykin et al., 2020, Kloss et al., 2021) and confirm a persistent perturbation on the atmospheric composition of the extra-tropical stratosphere. In order to extend the discussion, the spatial dispersion of the smoke layer will be discussed in the next section.

## 3.2 Spatial dispersion of sAOD and CO

Figure 4 depicts a time-averaged map of partial columns of aerosols (between 16 and 30 km, sAOD) and CO (between 9 and 30 km) obtained from OMPS and IASI observations between 9th and 16th January 2020, respectively. One can observe the correlation in the shape and spatio-temporal distribution between CO and sAOD over the Southern Pacific (Figs 4a and 4b). It is worthwhile mentioning that the transport of the aerosol (with values ranging from $6 \times 10^{-3}$ to $1 \times 10^{-2}$ km$^{-1}$) and CO (with values ranging from $6 \times 8 \times 10^{17}$ molecules. cm$^{-2}$) plume over the Southern Pacific occurred mainly within the 18°S–60°S latitudinal band. The plume’s structure
<figure><img src="image_20.png" /></figure>

<figure><img src="image_21.png" /><figcaption>**Figure 11.** Vertical cross-sections of (a) CO and (b) water vapour mixing ratio anomalies obtained from MLS observations over southern Africa and the SWIO basin (black box in Fig. 10b) between 16 and 29 January 2020.</figcaption></figure>

of high values (higher than 20%) of water vapour mixing ratio anomalies (Fig. 11b). This is consistent with the FLEXPART simulations shown in Fig. 12, which highlight a lifting of air masses from the lower troposphere to the lower stratosphere between 25 and 55°E in longitude. The convective activity induced by Diane near Madagascar may have contributed to the lifting of air masses enriched in CO from the lower troposphere.

Figure 9 also depicts the evolution of the contribution of African emissions to CO partial columns obtained from satellite observations and simulated by FLEXPART from 15 to 29 January over Réunion. An injection height ranging up to 3 km was chosen for the African fires (Labonne et al., 2007). The Australian contribution to the observed partial column was also plotted (as in Fig. 9). On average, the CO emissions from Africa contribute up to 90% of the enhancement of the partial column of CO from 15 to 29 January (Fig. 13b). The

<figure><img src="image_22.png" /><figcaption>**Figure 12.** Same as Fig. 7 but with the injection height initialized at 16 km.</figcaption></figure>

total CO contribution from Africa and Australia reproduces the observations fairly well.

Our results suggest that the variability in the CO over the SWIO basin can be explained by the influence of regional transport from southern Africa enhanced by convective activity due to the passage of a tropical storm.

# 6 Summary and conclusion

The complex aerosol and CO variabilities over the SWIO basin during the 2020 austral summer have been investigated. The meteorological context and the extensive fires over southeastern Australia were favourable for triggering pyroconvective events between 29 December 2019 and 12 January 2020. These pyro-convective events led to a massive injection of combustion products into the stratosphere. The ground-based and spaceborne lidars revealed the presence of an intense stratospheric aerosol layer over the southeastern Australia region. Over the Lauder site in New Zealand, this smoke layer was detected in the stratosphere (centred at 16 km) until at least April. The analysis of the spatial and temporal dispersion of the Australian BB plume highlighted that it was quickly transported – it circled the entire Southern Hemisphere in less than 2 weeks. Furthermore, the satellite observations revealed that the transport of the Australian
<figure><img src="image_17.png" /></figure>

over the Southern Pacific can be explained by the fact that the core plume started to encapsulate
into a compact bubble-like structure (with 4 km vertically extended and 1000 km horizontally
wide) on 7th January 2020 (Khaykin et al., 2020). Figures 4a and 4b reveals that the aerosol and
CO plume cross the Southern Pacific fairly quickly. Based on CALIOP and Lidar observations
at Punta Arenas (53.2°S, 70.9°E, Chile), Ohneiser et al. (2020) showed that aerosols injected
into the lower stratosphere over southeastern Australia crossed the Pacific Ocean within 10
days. On 10th January 2020, the aerosol plume is already visible over Punta Arenas and
structured into two layers. One can observe an aerosol band (with values ranging from 5 × 10⁻³
to 9 × 10⁻³ km⁻¹) across the Southern Hemisphere between 40°S and 60°S during the 9-16th
January 2020 period (Figure 4a). Therefore, the Australian aerosol plume has already circled
the Southern Hemisphere during the first two weeks of January 2020. Based on MLS and
CALIOP observations, Khaykin et al. (2020) showed that the smoke layer dispersed across the
whole Southern Hemisphere extra-tropics in less than two weeks whereas the carbon-rich core
remained bounded within the mid-latitudes (30°S-50°S). The fastest patches of smoke returned
over Australia by 13th January 2020 (Khaykin et al., 2020). The same conclusion cannot be
made for CO from space-borne observations (Figure 4b). One can observe weak values of CO
(less than 5 × 10¹⁷ molecule.cm⁻²) over southern Atlantic and without real link with the large
plume observed over southern Pacific (Fig. 4b). Except for the bubble structure, it seems that
the main part of the Australian BB plume has been transported bounded within the extra-tropical
latitudinal band. Further discussions the dispersion of the Australian smoke layer over the
SWIO basin will be given in the next section.

# 4. Presence of aerosols smoke layer over the SWIO basin

## 4.1 Aerosol and CO variability over a subtropical site: Reunion

Figure 5a depicts the evolution of the sAOD at 532 nm calculated between 15 and 30 km from the ground-based lidars (LiO3T and LiO3S) and OMPS observations over Reunion from 1st January to 1st March 2020. The Angström exponent for the 532–745 nm wavelength pair is adopted from methodology in Taha et al. (2021) and set to 1.9. lidar observations over Reunion are also used to calculate the aerosol Angstrom exponent (using 355 nm and 532 nm pairs). An abrupt increase in the aerosol loading is clearly observed over Reunion as of 16th January 2020 according to satellite observations. This increase of the aerosol loading, three times above the typical background, was still visible until 1st March 2020. It is worthwhile mentioning that the sAOD values observed between 16th January and 1st March 2020 are higher than those observed during the passage of the Calbuco plume over Reunion site, which did not exceed 0.013 (Bègue et al., 2017). The increase of sAOD in mid-January coincided with an increase of CO, as shown
<figure><img src="image_23.png" /><figcaption>**Figure 13.** Daily evolution of the partial column (calculated between 9 and 30 km) of CO observed by IASI (red line) and simulated by FLEXPART (black line) over Réunion from 15 to 29 January 2020. The CO evolution was simulated by FLEXPART considering only the CO emissions (including BB and anthropogenic activity). The contributions from the African and Australian emissions are shown as a cyan line and an orange line, respectively.</figcaption></figure>

smoke layer occurred mainly within an extratropical latitudinal band.

Nevertheless, the numerical models clearly showed the influence of the Australian smoke layer on the variability of aerosol over the SWIO basin. Over Réunion, the aerosol extinction profiles exhibited a significant increase in the lower stratosphere during the end of January. The MIMOSA simulations highlighted the isentropic transport of the Australian BB aerosol from extratropical latitudes to Réunion at the 400 K isentropic level on 28 January. As a consequence, the corresponding aerosol extinction profile exhibited a sudden increase, leading to a structure similar to laminae, at the 400 K isentropic level. The aerosol extinction profiles also exhibited a moderate increase in the upper troposphere.

According to our simulations, the CO variability over the SWIO cannot be explained by the Australian Black Summer. Rather, the CO in the UT-LS is likely driven by African BB emissions during the convective season. The analysis of satellite observations and FLEXPART simulations suggests that, because of the convective activity, air masses enriched in CO were lifted from the lower troposphere to the lower stratosphere. Air masses from Africa contributed up to 90% of the variability in the partial column (between 9 and 30 km) of CO over Réunion and its surroundings. The simulations show that the modulation of the CO and aerosol extinction in the upper troposphere and the lower stratosphere over Réunion was driven by the transport of air masses from Africa and Australia, respectively.

**Data availability.** The data used for this study are open-access and available on request from particular authors or through specific links: the lidar measurements can be requested via tetsu@mri-jma.go.jp and nelson.begue@univ-reunion.fr, the

FTIR measurements from TCCON can be requested via makhesh.sha@aeronomie.be, the Lauder FTIR data are available from the NDACC public-access database at https://www-air.larc.nasa.gov/missions/ndacc/data.html (NASA, 2024), and the satellite observations and the emissions inventory used are available online from the sources stated in the manuscript. The FLEXPART and MIMOSA codes are available on the FLEXPART (https://www.flexpart.eu/, ZAMG, 2024) and AERIS (http://espri.aeris-data.fr/, ESPRI, 2017) websites, respectively.

**Author contributions.** Conceptualization, NB; methodology and software, NB, AB, and GK; validation and data curation, NB, AB, GK, SK, CC, PFC, DS, JR, RQ, BL, TS, and PS; original draft preparation and writing, NB. The FLEXPART and MIMOSA simulations were performed by GK and NB, respectively. All authors have read and agreed to the published version of the paper.

**Competing interests.** The contact author has declared that none of the authors has any competing interests.

**Disclaimer.** Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors.

**Acknowledgements.** Data used in this publication were obtained from the NDACC network and are available through its website (http://www.ndacc.org/, last access: 10 April 2024).

**Financial support.** The work of Sergey Khaykin was supported by the Agence Nationale de la Recherche project PyroStrat (grant no. 21-CE01-335 0007-01). The French research infrastructure of ACTRIS-FR and CNES is also acknowledged for their support in the upgrade and operation of the Maïdo Observatory lidars. Lauder observations are funded by the New Zealand Government's Strategic Science Investment Fund (SSIF), administered by the Ministry of Business, Innovation and Employment (MBIE). The TC-CON site at Réunion Island is operated by the Royal Belgian Institute for Space Aeronomy, with financial support from the EU project ICOS-Inwire since 2014, the ministerial decree for ICOS (grant nos. FR/35/IC1 to FR/35/C6), and the ESFRI-FED ICOS-BE project, with local activities supported by the Université de La Réunion (grant nos. LACy/UMR8105 and OSU-R/UMS3365). The lidar measurements at Lauder are supported by funding from the GOSAT series project. This study is integrated and supported by the CNES project Extra-Sat.

**Review statement.** This paper was edited by Suvarna Fadnavis and reviewed by two anonymous referees.
<figure><img src="image_18.png" /></figure>

in Figure 5b based on the use of total columns and CO abundance from IASI and FTIR at the same site and over the same period. The evolution of CO obtained from IASI and FTIR measurements correlate. The ground-based and satellite observations clearly indicate a significant increase of CO with a peak observed in mid-January. The ground-based observations show that the CO abundance observed during this increased phase is on average 20% higher than the values observed during the background period (Fig. 5b). The evolution of sAOD and CO observations in mid-January suggests that Reunion, and its surrounding, have been influenced by the transport of smoke aerosol layers.

Figures 6a and 6b illustrate the night-averaged extinction profiles at 355 nm derived from lidar measurements over Reunion on January and February 2020, respectively. The two first weeks of January 2020 are representative of the January typical background (shaded area), as illustrated on 13th January 2020 (Fig. 6a). Conversely, the extinction profiles at the end of January 2020 (27th and 28th) are marked by a significant increase (4 times higher than the background values) located in the lower stratosphere between 16.8 and 18 km altitude (equivalent to potential temperature levels 380-404 K). One can observe that the structure of the extinction profile in the lower stratosphere has changed between these two days. On 28th January, the extinction profile exhibits a sudden increase at 17.4 km (~400 K) and quickly decreased afterwards to values observed the previous day (Fig. 6a). It is worthwhile mentioning that the values of extinction (10 to 17 × 10⁻³ km⁻¹) observed in the lower stratosphere on these two days are of the same order as those observed at Lauder a few days after the pyro-convective event (Fig. 2). Figure 6a reveals a statistically significant increase (4 times higher than background values) in aerosol extinction between 15 and 16.5 km altitude (361-375 K), on 27th and 28th January 2020. Over Reunion, the lidar observations hence confirm the presence of a significant aerosol layer in the UT-LS by the end of January. In February, the extinction profiles clearly exhibit two significant aerosol layers with the first one located between 16 and 19.5 km (370-440 K) and the second one between 20 and 22.5 km (465-500 K) (Fig. 6b).

To further discuss the optical properties of these aerosol layers, the Angstrom exponent has been calculated between 355 nm and 532 nm from the LiO3S and LiO3T measurements (Figs. 6c and 6d). In February, the Angström exponent values reveal that the two aerosol layers consist mainly of small aerosol particles (Fig. 6d), consistent with a stratospheric smoke layer (Haarig et al., 2018; Hu et al., 2019; Ohneiser et al., 2021). In January, the profile of Angström exponent exhibits more variability in the UT-LS (Fig. 6c) with values ranging from 0.6 to 1.9, on 27th and 28th January. Based on the literature, the largest proportion of the observed Angström exponent range (up to ~1.5) within the plume, points to the presence of an aerosol smoke layer
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<figure><img src="image_19.png" /></figure>

1 (Das et al., 2021; Haarig et al., 2018; Hu et al., 2019; Kloss et al., 2019). The wide range of
2 Angström exponent values suggests that the aerosol layer is not homogeneously distributed at
3 this stage and might be interpreted as a mixture of fresh and aged smoke layers (Fig. 6c). This
4 may indicate growth and removal processes (e.g., coagulation, condensation, sedimentation)
5 which can modulate the morphology and mixing state of the aerosol layer during its transport
6 (Burton et al., 2015; Hamil et al., 1997). The residence time of the aerosol particles in the
7 atmosphere depends on the balance between the growth processes and the removal processes,
8 which are likely to be controlled by the dynamical context. Previous works showed that the
9 dynamical context can modulate the structure and optical properties of the aerosol layer over a
10 given site from day to day (Bègue et al., 2017; Kremser et al., 2016). Fresh aerosols can be
11 rapidly transported and mixed with pre-existing aged aerosol. Given the fact that the Angström
12 exponent values decrease with the duration of transport, we cannot exclude that the vertical
13 distribution of optical properties of aerosol over Reunion may also be explained by the regional
14 transport of air masses.

## 4.2 Origin of the air masses

16 To analyze the origin of air masses at Reunion on 27th and 28th January, one-month backward
17 trajectories are calculated using FLEXPART (Aliaga et al., 2021; Eckhardt et al., 2017; Xu et
18 al., 2021). A period of one month is chosen because it refers to time separating the pyro-
19 convective outbreak event and the day of the measurement at Reunion. The representation of
20 the PES (potential emission sensitivity) from back-trajectories simulations initialized at 18 km
21 originating from Reunion on 27th and 28th January 2020 are presented in Figure 7.
22 Figures 7A-1 and 7B-1 display the horizontal trajectory paths, whilst vertical movement is
23 shown in Figures 7A-2 and 7B-2, respectively. The vertical transect of FLEXPART back
24 trajectories in Figure 7A-2 confirms a high probability of air mass contribution from the
25 Australia if the fires emissions are directly injected into the stratosphere by convection (black
26 rectangle in the figure), (i.e. layer of 9 to 16 km of injection taken for the PES, see section
27 2.3.1). Then, according to FLEXPART results, the air masses at 18 km over Australia moved
28 westward and reached Reunion on 27th January. One can observe that the same pattern is
29 observed on 28th January 2020 (Figs. 7B-1 and 7B-2). One part of the Australian smoke layer
30 is advected zonally by the prevailing easterly winds and is observed over Reunion on 27th and
31 28th January 2020 at 18 km. It is worthwhile mentioning that the same pattern has been observed
32 during the volcanic eruption of the Hunga Tonga on January 2022 (Baron et al., 2023, Kloss et
33 al., 2022; Sellitto et al., 2022). The FLEXPART simulations also suggest that Reunion is also
34 influenced by eastward transport of air masses. This pathway is clearly visible on 28th January
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<figure><img src="image_20.png" /></figure>

1 2020 (Figs. 7B-1 and 7B-2). Figure 7B-1 reveals that air masses coming from the South
2 American region and Australia region both reach the SWIO basin by passing over southern
3 Africa. Furthermore, air masses from high latitudes seem to cross the subtropical latitudes
4 following a wave shape and reach the SWIO basin by passing over the Cape of Good Hope
5 (Figure 7B-1).

6 In order to improve the discussion on this eastward transport of air masses over the SWIO basin,
7 the MIMOSA model has been used to produce a continuous evolution of PV fields for the period
8 from 1st to 31st January 2020. Two advected PV maps derived for the 400 K isentropic level
9 from the MIMOSA model are depicted in Figure 8. The localization of the aerosol plume
10 obtained from OMPS observations at the 400 K ± 5 K isentropic level are also superimposed
11 (Fig. 8). The 400 K isentropic level is chosen according to the layers observed in the extinction
12 profiles over Reunion between 390 and 404 K isentropic level on 27th and 28th January 2020
13 (Fig. 6a). Figure 8 reveals significant wave activity during these two days. It is clearly shown
14 that air masses from mid-latitudes (40-60°S) cross the subtropical latitudes (20-40°S) and are
15 advected eastward between South Africa and Madagascar following a wave shape. Given the
16 Australian BB aerosol are mainly located in the mid-latitudes (Fig. 4a), we can reasonably
17 conclude that the filament reaching the SWIO basin contains aerosol from Australian BB event.
18 On 27th January, air masses containing aerosol are observed at Madagascar and its surroundings
19 (Fig. 8a). These air masses are advected eastward following the displacement of the wave shape
20 and reach Reunion, on 28th January (Fig. 8b). These results demonstrate that the unusual aerosol
21 load observed in the UT-LS above SWIO is to be linked to the Australian fires. Parts of the
22 smoke plume underwent an isentropic transport from the mid to tropical latitudes following two
23 distinct pathways to reach Reunion.

24 Nevertheless, the contribution of the Australian BB event on the variability of aerosols in the
25 upper troposphere (15-16.5 km; 361-375 K) remains ambiguous. The representation of the PES
26 from back-trajectories simulations initialized at 16 km originating from Reunion for the 27th
27 and 28th January 2020 are presented in Figure 9. Figure 9A-1 and 9B-1 reveal that the
28 trajectories from Reunion at 16 km pass over southern Africa and Madagascar. One can observe
29 that the highest values of PES are located over southern Africa and Madagascar (Figs. 9A-1
30 and 9B-1). Furthermore, the FLEXPART simulations suggest that air masses from southern
31 Africa and Madagascar might have reached altitudes up to 16 km between 25°E and 55°E in
32 longitude and reached Reunion on 27th and 28th January 2020 (Figs. 9A-2 and 9A-2). The results
33 of Figure 9 show an influence of air masses coming from Africa and reaching the SWIO basin
34 at 16 km. Thus, the moderate increase in aerosol extinction observed in the upper troposphere
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<figure><img src="image_21.png" /></figure>

<figure><img src="image_22.png" /></figure>

1 (between 16 and 17 km altitude) on 27th and 28th January in Figure 6a may be attributed to air

2 masses from regional sources, namely southern Africa and Madagascar.

3 In summary, our analysis suggests that the variability of CO and aerosols in the UT-LS over

4 the SWIO basin in January is explained both by long-range and regional transport of air masses.

5 The extent to which regional sources have contributed to the variability of the atmospheric

6 compounds over the SWIO is now investigated.

## 5. Discussion on the influence of the regional sources

8 We investigate the contribution of the African and Australian BB activity on the atmospheric
9 composition in the UT-LS over the SWIO basin. Because a significant simultaneous increase
10 of CO and sAOD is observed over Reunion and its surroundings from 16th to 29th January 2020,
11 the discussion will focus on this period. In order to assess the contribution of African and
12 Australian BB activity, FLEXPART is coupled with the GFAS inventory.

13 **5.1 Presence of African air masses in the UT-LS**

14 The location of fire-flagged pixels and the associated Fire Radiation Power (FRP) values from
15 MODIS between 16th and 29th January 2020 are reported in Figure 10a. FRP gives quantitative
16 information on combustion rates and its intensity. The sparse activity of the African fires in
17 January is clearly illustrated in Figure 10a with moderate values of FRP ranging from 20 to 200
18 MW.m⁻². These values are ten times lower than those observed over the southeastern Australia
19 between 30th December 2019 and 12th January 2020 (Bègue et al., 2021). One can observe that
20 the African BB activity in January 2020 is mainly located over the northwestern (near the
21 Equator) and southeastern side of southern Africa. The most intense values (100-200 MW.m⁻²)
22 are observed over the southeastern side.

23 Despite this sparse activity of BB, the amount of CO injected into the atmosphere is fairly
24 significant and ranging from 5 to 6 × 10¹⁷ molecules.cm⁻². Time-averaged map of the partial
25 column of CO (between 9 and 30 km) from IASI observations between 16th and 29th January
26 2020 over the SWIO basin is reported on Figure 10b. The partial column of CO over the
27 southern Africa is characterized by two regions of high values (higher than 5 × 10¹⁷
28 molecules.cm⁻²). The first region stretches between the eastern side of southern Africa and
29 western side of Madagascar which corresponds to a domain extending between 10°S and 25°S
30 in latitude and 30°E and 45°E in longitude (Fig. 10b). The second region is located on the
31 opposite side, over a domain extending between 10°S and 15°S in latitude and 5°E and 15°E in
32 longitude. These regions of high values of CO seem to be mainly related to BB activities located
33 over the northwestern side of southern Africa (Fig. 10a). Although these BB activities are less
34 intense than those observed over the southeastern side, they seem to have the potential to impact
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<figure><img src="image_23.png" /></figure>

1 the variability of CO between 9 and 30 km over the SWIO basin. This could be explained by
2 convective activity which can rapidly transport air masses from the boundary layer to the upper
3 troposphere (Pfister et al., 2010; Blamey and Reason, 2012). Previous works showed that,
4 during the southern summer, the convective activity over southern Africa and the SWIO basin
5 is triggered either from the ITCZ or tropical storms (Barimala et al., 2018; Héron et al., 2020;
6 Lashkari et al., 2017).

7 Figure 10c depicts a time-averaged map of OLR (Outgoing Longwave Radiation) anomalies
8 from NCEP analysis between 16th and 29th January 2020. One can observe that the main
9 convective regions (region of negative OLR anomalies) are located in mainland Africa between
10 12° S and 25° S and the northern side of the SWIO basin. It is worthwhile mentioning that the
11 daily brightness temperature values obtained from MODIS between 16th and 29th January 2020
12 (not shown) are ranging from 195 to 210 K over the eastern side of southern Africa and the
13 Mozambique Channel (around the north tip of Madagascar). These values of brightness
14 temperature can be attributed to deep convection clouds (Héron et al., 2020; Young et al., 2013).
15 In most tropical basins, the deep convection can be separated into local convection and tropical
16 storms (Bovalo et al., 2012). In our case, the deep convection activity could be explained by
17 the ITCZ activity moving southward, near the subtropical latitudes, during the austral summer
18 (Barimala et al., 2018; Lashkari et al., 2017). Through the analysis of ERA-Interim data over a
19 period of 66 years, Lashkari et al. (2017) investigated the annual and seasonal displacement of
20 the ITCZ. On average, the motion of ITCZ over southern Africa on January is characterized by
21 southward move from 5°N to 20°S in latitude occurring between 20° E and 35° E in longitude
22 (Lashkari et al., 2017). Over the Mozambique Channel, the deep convection can be explained
23 by the tropical storm activity. Indeed, a tropical depression has been formed in the east side of
24 the Mozambique Channel (near the northwestern side of Madagascar) between 20th and 22nd
25 January 2020. This tropical depression reached the stage of strong tropical storm on 24th January
26 2020 and was called Diane by the RMSC (Regional Specialized Meteorological Center) of
27 Reunion. The intensification of the tropical depression into strong tropical storm occurred
28 around the north tip of Madagascar. Diane passed near Reunion on 25th January 2020 (Fig. 10c).
29 In the present study, the convective activity over southern Africa and the SWIO basin may
30 hence be due to both ITCZ proximity and Diane activity. This convective activity also explains
31 the gap of CO observations from satellites over Madagascar and the northern side of southern
32 Africa (Fig. 10b).

33 To further discuss the vertical distribution of CO in the UT-LS within the region of deep
34 convection, the vertical cross section of CO and water vapor mixing ratio anomalies calculated
<figure><img src="image_24.png" /></figure>

from MLS observations between 16th to 29th January 2020 are analyzed (Figs. 11a and 11b).

The CO and water vapor mixing ratio anomalies are calculated as a relative difference by considering the monthly background means as the reference values. The calculations are performed over a domain extending between 10°S and 25°S in latitude and 30°E and 60°E in longitude (black box in Fig. 10b). The altitude-longitude cross-section is averaged for all latitudes covering the study domain. This domain includes both the region of deep convection and the first region of high values of CO. The monthly background is calculated from available MLS observations between 2017 and 2019. The altitude-longitude cross-section is averaged for all latitudes covering the study domain. Figure 11a exhibits two regions of high values of CO mixing ratio anomalies (higher than 15%) centered at 37°E and 50°E in longitude. The maximum CO mixing ratio anomalies in the first region are centered at 215 hPa (~12 km) with anomalies ranging from 25% to 30%. The values of the anomalies decreased rapidly with altitude. Indeed, the anomalies values obtained at 146 hPa (~15 km) and 100 hPa (~17 km) ranged from 20% to 25% and from 15% to % respectively. In the second region, the maximum CO mixing ratio anomalies are also centered in the middle troposphere (215 hPa). One can observe that these regions of CO mixing ratio anomalies are in coincidence with two regions of high values (higher than 20%) of water vapor mixing anomalies (Fig. 11b). The maxima of water vapor mixing ratio anomalies are centered at 146 hPa with values ranging from 40% to 50%. This coincidence suggests a significant perturbation of the vertical distribution of CO and water vapor mixing ratio induced by the convective activity over southern Africa and the SWIO basin. Given the localization of the Diane tropical storm over the SWIO basin, we can reasonably assume that it contributed significantly to impact the vertical distribution of CO and water vapor in the second region aforementioned. One can observe that fire flagged pixels (with FRP values range between 10 and 30 MW.m⁻²) are detected by MODIS over the East of Madagascar (Fig. 10a). We can assume that the convective activity induced by Diane near Madagascar may have contributed to lift air masses enriched in CO from the lower troposphere. This could explain the high values of CO mixing ratio anomalies observed in the second region. This is consistent with the FLEXPART simulations which highlight a lift of air masses from the lower troposphere to lower stratosphere between 25°E to 55°E in longitude (Figure 9). One can observe that the most significant anomalies of the vertical distribution of CO and water vapor mixing ratio stretch from the middle troposphere (215 hPa) up to the tropopause layer (100 hPa,). The values observed in the lower stratosphere are less than those observed in the troposphere. Indeed, the CO and water vapor mixing ratio anomalies at 68 hPa (~19 km) are less than 10% and 20% respectively. At 68 hPa, it can be observed that high values of water
<figure><img src="image_25.png" /></figure>

1 vapor mixing ratio anomalies are not in coincidence with high values of CO mixing ratio
2 anomalies, but located along the vertical extent of the maxima of CO mixing ratio anomalies in
3 the troposphere.

4 Our analysis corroborates the results found by Héron et al. (2020). Based on radiosonde and
5 satellite observations, Héron et al. (2020) showed that convective activity over the SWIO basin
6 has the potential to influence the variability of ozone and water vapor in the upper-troposphere
during the austral summer. In the present study, the satellite observations and FLEXPART
8 simulations strongly suggests that African air masses enriched in CO and aerosols were lifted
9 from the lower troposphere to the lower stratosphere due to convective activity. Our results
10 demonstrate that the variability of CO and aerosol over the SWIO basin can be explained both
11 by the influence of long-range transport of the Australian fires plumes, together with regional
12 transport from southern Africa, enhanced by convective activity due to the passage of a tropical
13 storm.

## 5.2 Discussion on the variability of the total and partial column of CO

15 The African and Australian BB contributions to CO measured concentrations over Reunion are
assessed by coupling the FLEXPART model with gases emissions from the GFAS inventory.
17 The emission sensitivity from FLEXPART, only at the altitude where the emissions are injected
18 (0-3 km for Africa fires and 9-16 km for Australian fires), is combined with CO emission
19 inventory. The CO emissions due to anthropogenic activity are also taken considered by
coupling the FLEXPART model with the EDGAR inventory. The evolutions of the total and
20 partial column of CO observed by IASI and simulated by FLEXPART from 15th to 29th January
21 over Reunion are depicted in Figure 12.
22

23 Despite the underestimation of the simulated total and partial column of CO, their overall
24 temporal evolution is fairly well reproduced by FLEXPART (Fig. 12). The discrepancies
25 between FLEXPART and IASI may be attributable to several possible caveats. A possible
26 source of error can be due to the fact that the vertical motion induced by pyro-convection is not
27 included in FLEXPART. We address this issue by applying an injection height in agreement
28 with CALIOP observations (9-16 km, Fig. 1) for the Australian plume (Khaykin et al., 2020).
29 An injection height ranging up to 3 km was chosen for the African fires (Labonne et al., 2007).
30 The injection height of the plume plays a key role in its long-range transport (Sofiev et al.,
31 2012). An inappropriate or unrealistic injection height can lead to either a dilution or an
32 overestimation of the plume. The injection height depends on the intensity of the fire, as well
33 as on the meteorological conditions. Another possible explanation in these differences can come
34 from the duration of the backward calculation (1 month) (Brocchi et al., 2018). Underestimation
<figure><img src="image_26.png" /></figure>

of the total and partial columns of CO may also be the result of an underestimation of the CO emissions by GFAS. In the framework of their FLEXPART simulation, Brocchi et al. (2018) reveal that an amplification factor of 2 has been applied to CO emissions from GFAS to get similar CO quantities to observations. Nevertheless, these simulations can reasonably be used to discuss the contribution of CO emissions from Africa and Australia on the variability of the total and partial columns of CO over the SWIO basin.

The contribution of the CO emissions from Africa and Australia on the total and partial columns of CO over Reunion is isolated and depicted in Figure 12. On average, the CO emissions from Africa contribute up to 90% of the enhancement of the total and partial column of CO from 15th to 29th January. The transport of the CO plume induced by the Australian sources have not been efficient over the SWIO basin. This could be explained by the fact that CO decays quickly due to photochemical oxidation whose efficiency increase with altitude. Khaykin et al. (2020) showed that the decay of CO within the bubble occurred during its transport over the Southern Pacific on its way to the Indian ocean. The variability of CO over the SWIO basin is hence mainly explained by the regional transport of air masses.

## 5.3 Discussion on the variability of the aerosols

The FLEXPART simulations for the contribution of aerosol (BC and OC) emissions from Africa and Australia on the sAOD over Reunion use the same parameters as for CO, in particular the injection height. The emission sensitivity from FLEXPART is combined with BC and OC from the GFAS emission inventory. Figure 13 depicts the evolution of the sAOD observed by OMPS and simulated by FLEXPART from 15th to 29th January over Reunion. Unfortunately, few data have been recorded during the period aforementioned. Nevertheless, the simulated sAOD compares fairly well with the available OMPS observations during this period, and the sAOD peak observed on 19th January is acceptably well reproduced. Figure 13 reveals that the variability of the sAOD between 15 and 30 km altitude is mainly driven by the aerosol emissions from Australia. On average, the aerosol emissions from Australia contributed up to 95% of the sAOD variability over Reunion from 15th to 29th January. One can observe that the evolution of sAOD is not correlated to the evolution of the aerosol emission from Africa which is marked by an increase from 21th to 29th January. The weak contribution of African component on the sAOD can be explained by the fact that the amounts of African BB aerosols injected in the atmosphere by the convective activity decrease with altitude. Moreover, it is likely that aerosol would be scavenged by cloud droplets (taken into account in FLEXPART) in a strongly convective environment such as tropical storm Diane. Overall, FLEXPART simulations clearly suggested the contribution of African and Australian BB aerosols.
<figure><img src="image_27.png" /></figure>

# 6. Summary and Conclusion

The complex aerosol and CO variabilities over the SWIO basin during the 2020 austral summer have been investigated. The meteorological context and the extensive fires over southeastern Australia were favorable to trigger pyro-convective events between 29th December 2019 and 12th January 2020. These pyro-convective events led to massive injection of combustion products in the stratosphere. The ground-based and space-borne lidars revealed the presence of an intense stratospheric smoke layer over the southeastern Australia region. Over the Lauder site in New Zealand, this smoke layer was detected in the stratosphere (centered at 16 km) until April and beyond. The analysis of the spatial and temporal dispersion of the Australian smoke layer highlighted its quick transport circling the entire Southern Hemisphere in less than two weeks. Furthermore, the satellite observations revealed that the transport of the Australian smoke layer has been mainly bounded within an extra-tropical latitudinal band.

Nevertheless, the numerical models clearly showed the influence of the Australian smoke layer on the variability of aerosol over the SWIO basin. Over Reunion, the aerosol extinction profiles exhibited a significant increase in the lower stratosphere during the end of January. The MIMOSA simulations highlighted the isentropic transport of the Australian BB aerosols from extra-tropical latitudes to Reunion at 400 K isentropic level, on 28th January. As a consequence, the corresponding aerosol extinction profile exhibited a sudden increase by drawing a structure similar to a laminae at the 400 K isentropic level. The aerosol extinction profiles also exhibited a moderate increase in the upper troposphere.

This paper investigates for the first time the possibility of the African emissions from BB to influence the CO and aerosol distribution in the UT-LS during the convective season. Despite the fact that African BB activity is usually sparse in January, it contributed to modulate the vertical distribution of CO and aerosols in the upper troposphere over the SWIO basin. The analysis of satellite observations and FLEXPART simulations suggested that because of the convective activity, air masses enriched in CO and aerosols have been lifted from the lower troposphere to the lower stratosphere. Air masses from Africa contributed up to 90% of the total and partial column (between 9 and 30 km) of CO variability over Reunion and its surroundings. The simulations shows that the modulation of the aerosol extinction in the upper troposphere and the lower stratosphere, over Reunion, was driven by the transport of air masses from both Africa and Australia, respectively. Our findings suggest simultaneous presence of African and Australian aerosol smoke layers at Reunion.

33

34
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1 Acknowledgements

2 We thank Isamu Morino and his staff for their effort in establishing and maintaining the sun-
3 sky radiometer at Lauder. Data used in this publication were obtained from NDACC network
4 and are available through its website (http://www.ndacc.org/). The work of S. Khaykin has been
5 supported by the Agence Nationale de la Recherche PyroStrat project (21-CE01-335 0007-01).

6 IASI was developed and built under the responsibility of the “Centre National d’Etudes
7 Spatiales” (CNES, France) and flown on board the MetOp satellites as part of the EUMETSAT
8 Polar System. The authors thank the AERIS infrastructure (https://iasi.aeris-data.fr/) for
9 providing access to the IASI data, the National Aeronautical and Space Administration (NASA)
10 for providing CALIOP data, MLS and MODIS fire products. We would especially like to thank
11 the staff of the team working on the lidar systems at the Maïdo observatory. The French
12 Research Infrastructure ACTRIS-FR, CNES and the EU project REALISTIC (GA 101086690)
13 are also acknowledged for their support in the upgrade and operation of the Maïdo observatory
14 lidars. Lauder observations are funded by the New Zealand Government's Strategic Science
15 Investment Fund (SSIF), administered by the Ministry of Business, Innovation and
16 Employment (MBIE). The TCCON site at Réunion Island has been operated by the Royal
17 Belgian Institute for Space Aeronomy with financial support since 2014 by the EU project
18 ICOS-Inwire, the ministerial decree for ICOS (FR/35/IC1 to FR/35/C6), ESFRI-FED ICOS-
19 BE project and local activities supported by LACy/UMR8105 and by OSU-R/UMS3365 –
20 Université de La Réunion. The lidar measurements are supported by the funding of GOSAT
21 series project.

22 Data availability

23 The data used for this study are available and open access by request to scientist mentioned or
24 through the link hereafter: Lidar measurements (tetsu@mri-jma.go.jp, nelson.begue@univ-
25 reunion.fr), radiometer measurements (ben.liley@niwa.co.nz), FTIR measurements from
26 TCCON network (mahesh.sha@aeronomie.be); Lauder FTIR data available on the NDACC
27 public access database (https://www-air.larc.nasa.gov/missions/ndacc/data.html); The satellite
28 observations and emission inventory used are available on-line from the sources as stated in the
29 manuscript.
30

30
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## FIGURES AND TABLE

<figure><img src="image_39.png" /><figcaption>**Figure 1:** (a) Map of Aerosol Absorbing Index obtained from OMPS observations and (b) scattering ratio profiles at 532 nm obtained from CALIOP observations on 1st January 2020. The orbit overpass of CALIOP is indicated by the blue curve, while the blue square corresponds to the Lauder site in plot (a). The black dashed line in (b) corresponds to the 380 K isentropic level calculated from CALIOP observations.</figcaption></figure>
<figure><img src="image_40.png" /></figure>

<figure><img src="image_41.png" /><figcaption>**Figure 2:** Time series of daily profiles at Lauder of (a) aerosol extinction at 532 nm obtained from lidar and (b) CO mixing ratio obtained from FTIR between 1st December 2019 and 1st April 2020. In order to screen non-aerosol contributors (such as clouds) on the extinction measurements, a mask based on the method reported by Nicolae et al. (2013) that includes consideration on plausible aerosols properties was used. Namely, we only kept profile parts with positive depolarization values, and Angström exponent ranges from 0.1 to 4. The grey line indicates the tropopause height obtained from radiosonde measurements.</figcaption></figure>
<figure><img src="image_42.png" /></figure>

<figure><img src="image_43.png" /></figure>

1

<figure><img src="image_44.png" /><figcaption>**Figure 3:** (a) Monthly mean evolution of total column of aerosol (AOD at 500 nm) and CO obtained from SKYNET radiometer and FTIR respectively over Lauder from 1st December 2019 to 1st April 2020. (b) Monthly mean evolution of the stratospheric AOD (sAOD) and CO (sCO) columns at Lauder between 1st December 2019 and 1st April 2020. The sAOD and sCO are calculated between 12 and 30 km from lidar and FTIR measurements respectively. The background evolution of aerosol data (AOD: 2011-2018 and sAOD: 1997-2004) and the associated standard deviation are given in black lines and grey areas, respectively.</figcaption></figure>
<figure><img src="image_45.png" /></figure>

<figure><img src="image_46.png" /></figure>

1

2

<figure><img src="image_47.png" /></figure>

3 **Figure 4:** Time-averaged map (from 9th to 16th January 2020) of (a) sAOD (between 16 and 30 km at 745 nm) obtained from OMPS observations and (b) partial column of CO (averaged between 9 and 30 km) obtained from IASI observations. The location of Reunion and Lauder sites are indicated by R and L respectively.

4 km at 745 nm) obtained from OMPS observations and (b) partial column of CO (averaged

5 between 9 and 30 km) obtained from IASI observations. The location of Reunion and Lauder

6 sites are indicated by R and L respectively.

7
<figure><img src="image_48.png" /></figure>

1

2

<figure><img src="image_49.png" /><figcaption>Figure 5: Daily mean evolution of aerosol (a) and CO (b) abundances obtained from ground-</figcaption></figure>

based and satellite observations at Reunion between 1st January and 1st March 2020. Total

column (molecule.cm⁻²) and abundance (ppb) of CO obtained from IASI (blue line) and FTIR

(red line) respectively are given in the lower panel (b), while sAOD obtained from OMPS (red

line) and Lidar (blue and green dots) are given in the upper panel (a). The black and dashed

lines correspond to monthly mean and the associated standard deviation calculated during the

background period.

10
<figure><img src="image_50.png" /></figure>

<figure><img src="image_51.png" /></figure>

<figure><img src="image_52.png" /><figcaption>Figure 6: Aerosol extinction (at 355 nm) (a, b) and Angström exponent (355-532 nm) (c, d)</figcaption></figure>

obtained from lidar observations at Reunion in the months January and February 2020. The

tropopause height is indicated by the orange horizontal lines.
<figure><img src="image_53.png" /></figure>

<figure><img src="image_54.png" /><figcaption>Figure 7: FLEXPART 30-day back trajectories initialized from Reunion (black cross) at 18 km on 27th January 2020 (A-1-2) and 28th January 2020 (B-1-2). A-1 and B-1 correspond to an integration of the trajectory positions over the whole altitude range. A-2 and B-2 are the vertical view integrated over the whole latitude range of the back trajectories A-1 and B-1. The black rectangle represented the injection height of the biomass burning aerosols.</figcaption></figure>

16

17

18
<figure><img src="image_55.png" /></figure>

<figure><img src="image_56.png" /></figure>

1

<figure><img src="image_57.png" /><figcaption>**Figure 8:** Advected PV map at the 400 K level obtained from the MIMOSA model (a) on 27 January 2022 and (b) on 28 January 2022. The white dots represent the localization of the aerosol plume at 400 K ± 5 K obtained from OMPS observations, while the black cross indicates Reunion.</figcaption></figure>

6
<figure><img src="image_58.png" /></figure>

<figure><img src="image_59.png" /><figcaption>10 **Figure 9:** Same as figure 7 with an injection height initialized at 16 km.</figcaption></figure>

11

12
<figure><img src="image_60.png" /></figure>

<figure><img src="image_61.png" /><figcaption>**Figure 10:** a) The total number of fire pixel and the associated fire radiative power obtained from MODIS observation between 16th and 29th January 2020. b) Time-average map of partial column of CO (calculated between 9 and 30 km) obtained from IASI observations averaged between 16th and 29th January 2020. The black square corresponds to the study domain where the vertical cross-section of CO and water vapor mixing ratio are calculated and reported in Figure 11. c) Time-average map of outgoing longwave radiation anomalies obtained from NCEP between 16th and 29th January 2020. The red curve corresponds the trajectory followed by the Diane strong tropical storm from 22nd to 29th January 2020. This trajectory is obtained from the RSMC (Regional Specialized Meteorological Center) of Reunion best-track database.</figcaption></figure>
<figure><img src="image_62.png" /></figure>

1

2

<figure><img src="image_63.png" /><figcaption>Figure 11: Vertical cross section of (a) CO and (b) water vapor mixing ratio anomalies obtained</figcaption></figure>

from MLS observation over southern Africa and the SWIO basin (black box in Figure 10b)

between 16th and 29th January 2020.

6
<figure><img src="image_64.png" /></figure>

<figure><img src="image_65.png" /></figure>

1

<figure><img src="image_66.png" /><figcaption>Figure 12: Daily evolution of (a) total column and (b) partial column (calculated between 9 and 30 km) of CO observed by IASI (red line) and simulated by FLEXPART (black line) over</figcaption></figure>

Reunion from 15th to 29th January 2020. The CO evolution is simulated by FLEXPART in

considering only the CO emission (including BB and anthropogenic activity) from African

7

(cyan line) and Australian (orange line) BB sources.
<figure><img src="image_67.png" /></figure>

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2

3

4

5

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8

9

<figure><img src="image_68.png" /><figcaption>**Figure 13:** Daily evolution of sAOD (calculated between 15 and 30 km at 532 nm) obtained from OMPS (red line), lidar (blue dots) and simulated by FLEXPART (black line) over Reunion from 15th to 29th January 2020. The simulated sAOD are calculated in considering only the aerosol emission (BC and OC) from African (cyan line) and Australian (orange line) BB sources.</figcaption></figure>