In 1963 a series of eruptions of Mt. Agung, Indonesia, resulted in
the third largest eruption of the 20th century and claimed about 1900 lives. Two eruptions of this series injected SO2 into the
stratosphere, which can create a long-lasting stratospheric
sulfate layer. The estimated mass flux of the
first eruption was about twice as large as the mass flux of the
second eruption. We followed the estimated emission profiles and
assumed for the first eruption on 17 March an injection rate of 4.7 TgSO2 and 2.3 TgSO2 for the
second eruption on 16 May. The injected sulfur forms a
sulfate layer in the stratosphere. The evolution of sulfur is
nonlinear and depends on the injection rate and aerosol background
conditions. We performed ensembles of two model experiments, one
with a single eruption and a second one with two eruptions. The two smaller
eruptions result in a lower sulfur burden, smaller aerosol particles, and 0.1 to 0.3 Wm-2 (10 %–20 %) lower radiative forcing in monthly mean
global average compared to the individual eruption experiment. The
differences are the consequence of slightly stronger meridional
transport due to different seasons of the eruptions, lower injection
height of the second eruption, and the resulting different aerosol
evolution.
Overall, the evolution of the volcanic clouds is different in case
of two eruptions than with a single eruption only. The differences
between the two experiments are significant. We conclude that there
is no justification to use one eruption only and both climatic
eruptions should be taken into account in future emission datasets.
Introduction
In September 2017 Mt. Agung, a volcano on Bali, Indonesia
(8.342∘ S, 115.58∘ E), became restless. Earthquakes,
steam, ash clouds, and lahars resulted in the evacuation of nearly
150 000 people from the volcano's environment within a radius of 9–12 km in November 2017 . The eruption resulted in an
ash cloud reaching up to an altitude of about 9.3 km
and about 10 DU SO2 above Bali
, which was not large and high enough to result in a
climatic impact. The last climatic eruption of Mt. Agung dates back
more than 50 years. From February 1963 to January 1964 a series of
eruptions from Mt. Agung are documented . The
initial unrest resulted in the third largest eruption of the 20th
century global volcano record and claimed about 1900 lives. Revising
the literature, it is obvious that not just one of the eruptions was
strong enough to inject SO2 into the stratosphere, a
requirement of creating a long-lasting stratospheric sulfate layer, but
also a second one . The mass flux of the second
eruption on 16 March was about half the size of the mass flux of the
first eruption on 17 March. estimate the volumetric
eruption rate for 17 March to be ∼1.8×104m3s-1 over a ∼3.5h duration. The volumetric eruption
rate of the 16 May event was ∼0.9×104m3s-1 over a ∼4h duration. The resulting sulfate
layer caused a climatic impact by scattering and absorbing solar and
terrestrial radiation leading to a temperature decrease of about 0.4 K in the tropical troposphere .
The sulfate load of the Mt. Agung eruptions was
estimated to 7–7.5 TgSO2 from observations of
aerosol optical depth (AOD) a couple of months after the eruption
. It was impossible to
distinguish between single eruptions with this method. This could be
the reason that up to now, recent volcanic forcing datasets
assume one large eruption phase of 7 TgSO2 for Mt. Agung, the one in March 1963, but neglect the
second one.
Within this paper we examine whether or not it is
important to consider both eruption phases individually when
simulating sulfate evolution and transport, as well as the impact on
radiative forcing of the Mt. Agung eruption.
The radiative forcing of the sulfate aerosols can be
simulated by either calculating the evolution and transport of sulfur with an
aerosol microphysical model or, much simpler, prescribing the
optical parameters of the volcanic aerosols. The first needs volcanic
injection data and information on emission strength and altitude, and
the latter optical properties like the aerosol optical depth
(AOD). Most datasets base the estimated global coverage of sulfate
aerosols after the Mt. Agung eruption on ground-based measurements
and on ice core measurements, and provide the AOD
e.g.,. Satellite data were not yet
available in 1963. Newer datasets not only rely on measurements, but they
also include simulated sulfate distributions, e.g., results of an empirical aerosol forcing generator like
Easy Volcanic Aerosol (EVA) or complex aerosol models, which
simulate the evolution of the aerosol, e.g., for the SAGE-4λ dataset.
On the other hand
new volcanic eruption datasets are released, providing the
SO2 injection rate for large climate-relevant volcanic eruptions, e.g.
Volcanic Emissions for Earth System Models (VolcanEESM) and the eVolv2k dataset , and sulfur injection data. These newer
datasets include one eruption phase only for Mt. Agung, the main
eruption in March 1963, and assume the injected amount of SO2 of 7 Tg following the estimates of .
The evolution of the volcanic aerosols is
strongly nonlinear. In particular, the particle size depends on the
erupted mass and sulfur
injected into an existing volcanic sulfate layer evolves differently
than sulfur injected into background conditions
. Additionally, many chemical processes
depend on particle size and sulfate concentrations. For example stratospheric
OH, NOx, and ozone concentrations change under high sulfur load.
shows in Figure 8.20 the
temperature response of different stratospheric chemistry
models to volcanic sulfate aerosols. Models using full aerosol
microphysics or prescribing surface aerosol density tend to
overestimate the measured heating in the stratosphere after the Mt. Agung eruption.
This might be related to the assumption of one eruption phase only, especially
as for the Mt. Pinatubo eruption in 1991 the models show a
slightly better result.
In this study we would like to address the following question:
is there a significant difference when simulating two medium eruptions
instead of a single large one? We performed two experiments
to provide an answer to this question. We describe the model and
the simulations in more detail in
Sect. , and show results in Sect.
where we describe the different burden results of the two experiment ensembles
(Sect. ) and the cumulative impact of the eruptions
(Sect. ). Finally, we compare our results to
measurements in Sect. before we conclude in
Sect. .
Model and observation dataModel setup
The model simulations of this study were performed with the middle
atmosphere version of the general circulation model (GCM) MAECHAM5
. The aerosol microphysical model HAM
is interactively coupled to the GCM and was extended to a
stratospheric version .
MAECHAM5–HAM, ECHAM–HAM later in the text, was applied with the spectral truncation at wave number
42 (T42), a horizontal grid size of about 2.8∘, and 90 vertical layers (L90) up
to 0.01 hPa. The model is not coupled to an ocean model and shows pure volcanic forcing response only. The sea surface temperatures (SSTs) are set to monthly mean
climatological values based on the Atmospheric Model Intercomparison
Project (AMIP) SST observational dataset .
Thus, the SST does not reflect the historical date but rather represents a climatological mean.
HAM calculates the evolution of sulfate from the injected SO2
to sulfate aerosol, including nucleation, accumulation, condensation,
and coagulation, as well as transport and sink processes like sedimentation
and deposition . A simple stratospheric sulfur chemistry is applied
above the tropopause and the sulfate
is radiatively active. The model setup is described in more detail in
and .
The L90 version of MAECHAM5–HAM interactively generates a quasi-biennial oscillation (QBO) . However, we decided to nudge the QBO in the tropical stratosphere
to the observed monthly mean winds at the Equator (updated
), as described in .
This allows us to inject the volcanic sulfur into the observed QBO phase and still
include the better resolved transport processes of the L90 version, e.g., a
less permeable subtropical transport barrier .
Nudging the QBO prescribes the feedbacks of the sulfate aerosol heating in the
stratosphere on the QBO winds as observed. However, the QBO winds are
prescribed on a monthly basis. This may suppress very short-term
changes in the transport due to dynamical changes caused by aerosol
heating at the equatorial stratosphere.
Model simulations
We performed experiments of two scenarios for the 1963 eruption of
Mt. Agung. We assumed for the first experiment one eruption phase at 17 March
(AGUNG1) with an injection of 7 Tg SO2 over 3 h.
For the second scenario two eruptions were simulated with a ratio of the injection rate of 2:1. This reflects the ratio of the volumetric eruption rate and the mass flux of 4 and 2 kgs-1 given in Table 3 in . The altitudes of the eruptions were taken as the average of the range of estimated altitudes in . This resulted for the second experiment in the following assumption of two eruption phases (AGUNG2): the first on
17 March, over 3 h with an injection rate of 4.7 TgSO2 at an altitude of 50 hPa, and a second on 16 May, over 4 h with an injection rate of 2.3 TgSO2 at a slightly lower altitude of 70 hPa. The ECHAM5–HAM input data for the eruptions are summarized in Table .
We performed a set of six ensemble members for each eruption case. See Supplement for further details.
All six simulations were used to calculate an ensemble
mean. Additionally, we performed a single simulation where an eruption altitude of 50 hPa was assumed for both eruptions (AGUNG2-50hPa).
Overview of the performed simulations and information to the eruption details, after .
SimulationEruptionEruptionEruptionEruptionEnsembleOH limitationnamemassaltitudedurationdatemembersAGUNG17 TgSO250 hPa06:00–09:00 UTC17 Mar 1963sixnoAGUNG24.7 TgSO250 hPa06:00–09:00 UTC17 Mar 1963sixno2.3 TgSO270 hPa17:00–21:00 UTC16 May 1963AGUNG2-50hPa4.7 TgSO250 hPa06:00–09:00 UTC17 Mar 1963oneno2.3 TgSO250 hPa17:00–21:00 UTC16 May 1963Observations
We compare our simulation results to observations and volcanic datasets provided for the Climate Model Intercomparison Project (CMIP).
The AOD prescribed for the years 1963 to 1964
in the CMIP5 simulations of the Max Planck Institute for Meteorology
is based on and . The data rely
mainly on astronomical observations summarized by , as
no satellite data are available for the period. The AOD data for CMIP6
were taken from the SAGE-3λ database
. They combine ice core data
and AOD data with aerosol
microphysical model simulations and include only one eruption of
Mt. Agung in their preparatory model simulations .
assembled a revised chronology of observed AOD
after the Mt. Agung eruption. The data contain mainly measurements
of atmospheric attenuation of starlight and direct
sunlight. provides values of monthly mean AOD data
as an average over different measurement sites, between 20 and
40∘ N and 20 and 40∘ S and results of monthly mean
data of single measurement sites. excluded data of
tropical measurement sites because they were not reliable.
Radiosonde temperature measurements provide information on the
heating of the stratospheric aerosol layer after the eruption. This heating causes
changes in stratospheric dynamics and is,
therefore, an important value
which should be taken into account correctly. provide vertical
temperature anomalies after volcanic eruptions from radiosonde data
(RATPAC). The carefully examined dataset contains data of 85 radiosonde
stations, 32 of them in the tropics .
The QBO and El Niño–Southern Oscillation (ENSO) signals in the temperature were removed.
To calculate the temperature anomalies, the average of
the 2 years before the eruption was subtracted from the
average over the 2 years after the eruption.
The corresponding model data of AGUNG1
and AGUNG2 were calculated by averaging over the 2 years after the
first eruption and subtracting an ensemble mean of control
simulations with nudged QBO data, but no volcanic eruption, for the
years 1964 to 1965. This provides the anomaly and removes the QBO
signal at the same time.
Ensemble mean of sulfate burden of experiments AGUNG1 (a) and AGUNG2 (b). Absolute (c) and relative differences (d) of the two ensembles. The x axis gives the months after the first eruption in March 1963. Stippling indicates non-significant differences at the 99 % level, following a Student's t test. The gray dots mark the location and size of the volcanic eruptions.
Results
Figure shows the monthly and zonally averaged sulfate
burden of the ensemble mean. Mt. Agung is located at 8∘ in the
Southern Hemisphere (SH) tropics. Thus, the main transport direction of the aerosols is
southward and, hence, burden values in the Northern Hemisphere (NH)
remain small. The ensemble mean shows for both experiments, AGUNG1 and
AGUNG2, two areas with high burden: a maximum in the
southern tropics in the months 1 to 3 after the eruption, and about four months later in
the SH midlatitudes and high latitudes with a secondary maximum between
30 and 60∘ S. The maximum burden is slightly above 14 mgm-2 in the ensemble of AGUNG1 and 10 mgm-2, about
30 % lower, in the ensemble of AGUNG2, reflecting the ratio of the initial injection.
The initially higher injection
in the ensemble of AGUNG1 results in a higher burden over almost all
simulated months and regions. The strongest absolute difference
between the two ensembles occurs in the time period between both
climatic eruptions, when the injected sulfur amount in AGUNG2 is still
smaller. The relative difference highlights that more aerosols are
transported into the NH tropics in AGUNG2 in the first months after the second
eruption (months 4 to 6). The burden of AGUNG2 increases slightly after the second
eruption but, overall, the tropical maximum of the burden is smaller
and occurs later than in AGUNG1. In the SH extratropics the
differences between the two ensembles are below 20 %, 1 to 2 mgm-2. In contrast, the burden is up to 50 % larger in AGUNG2 in
months 6 to 10 in the NH extratropics, poleward of 30∘ N, but
with small absolute values. Also towards NH winter the relative
difference between the two simulations is larger in the NH than in the
SH, which indicates differences in the transport regime and wind
systems.
Transport of aerosols
The ensemble of AGUNG2 results in a lower sulfate burden than AGUNG1 in most areas and at most times (Fig. ). An exception is the sulfate burden in the extratropics in the first months after the second eruption. This indicates a stronger meridional transport in AGUNG2. The second eruption occurs 2 months later and thus in a different season with a different stratospheric transport pattern. Additionally, the injection altitude is lower, 70 hPa instead of 50 hPa. Figure shows the monthly mean zonal wind (shaded) and the residual stream function for April and June 1963, 1 month after the eruption each, of AGUNG2 (see Fig. S5 for results of AGUNG1). Nudging of the QBO at the Equator results in similar zonal mean zonal winds in the tropics between the two experiments. Differences of the zonal mean zonal wind in the extratropics, around ±10 %, are not significant and are mainly caused by a meridional shift of the higher-latitude wind systems.
Monthly mean zonal wind (ms-1) of AGUNG2 for April (a) and June (b) 1963 in shading. Contour lines show the stream function (kgs-1). Positive (solid) streamlines describe clockwise circulation, negative (dashed) ones counterclockwise circulation. The gray dots mark the injection location of the two volcanic eruptions.
showed that meridional transport in the tropics and subtropics depends on the QBO phase. Figure shows that both eruption phases inject into easterly zonal wind. Thus, the QBO phase should not play an important role in transport characteristics of both experiments. Seasonality seems more important. The streamlines show that the zero line, indicating the tropical pipe, is shifted northward in June, allowing more sulfate to be transported into the NH. Additionally, the second eruption occurs at a lower altitude, 70 hPa, where the subtropical transport barrier is weaker than at 50 hPa. This allows more meridional transport than at 50 hPa: the streamline at 70 hPa in June is stronger than at 50 hPa in April, 100 kgs-1 and around 50 kgs-1, respectively.
Cumulative impact – a sum over time
The zonally averaged cumulative burden (Fig. a), time integrated monthly mean values over 21 months, starting with the month of the first eruption, is roughly 20 % lower for AGUNG2 than AGUNG1. The difference between the two results is larger in the tropics than in the secondary maximum around 50∘ S. This results from the stronger meridional transport towards the SH in AGUNG2. Thus, one eruption with larger SO2 injection results in higher burden than the same injected amount of SO2, but split into two eruptions and in a slightly stronger tropical confinement of the aerosols. However, the shaded areas indicate that the variance within each ensemble is larger than the differences between the ensemble mean values.
Cumulative values, integral over 21 monthly mean values, of (a) zonally averaged sulfate burden and (b) AOD at 550 nm. The shadings indicate the maximum and minimum values of the single simulations in the ensemble.
Time series of monthly mean effective radius (µm) of sulfate at the grid point corresponding to 8∘ S (a, b) and 50∘ S (c, d).
This result is confirmed in the cumulative AOD (Fig. b). But the AOD of AGUNG1 and AGUNG2 differs less (about 10 %)
than the burden (about 20 %) in the tropics and even less in the SH
extratropics (about 6 %). The reason for this is different particle
radii. Scattering of sulfate aerosols decreases with increasing
particle radius. The maximum effective radii of the sulfate aerosols
reach 0.5 µm at 8∘ S for AGUNG1 and stay below 0.45 µm for AGUNG2 (Fig. a, b). Sulfate particles
are 0.05 µm smaller in AGUNG2. Thus, they scatter more
intensely and the AOD difference between the two experiments gets
smaller. These smaller radii are the consequence of the lower
injection rate of the first eruption in AGUNG2. Particle sizes
increase with increasing injection rate
. simulated a volcanic eruption
into background sulfate level and into elevated sulfate level from
continuous injections for climate engineering (CE). They show a
shorter lifetime and larger particles under CE conditions. Thus,
following , we would expect stronger coagulation
after the second eruption, as newly formed particles coagulate fast
with available larger particles. But the second eruption occurs at
lower altitude, where sulfate concentration and particle radii are
smaller. Thus, coagulation is less important. We performed an
additional sensitivity study where we injected the SO2 in both
eruptions at 50 hPa to differentiate better between injection rates
and emission height. The sensitivity simulation AGUNG2-50hPa, with both
eruptions at the same altitude, results in particle radii very similar to
AGUNG1 and about 0.05 µm larger
than in AGUNG2. This reflects the results of . See
Sect. 2 in the Supplement for more information and
figures.
Top of the atmosphere (TOA) radiative
forcing of sulfate aerosols under all-sky conditions. Aerosol forcing
was calculated using a radiation double call. (a) Global mean TOA
forcing over time.
The shadings indicate the 2σ variability range for both ensembles.
(b) Zonally averaged radiative forcing as an average over time (21 months).
The climatic impact can be derived from the aerosol radiative forcing
at the top of the atmosphere (TOA), which was calculated with a radiation double call
(Fig. a). The spread of the single ensemble members is large, but the average of the AGUNG2 ensemble is just outside of the 2σ ensemble variability of AGUNG1. The global monthly mean TOA
forcing of sulfate is about 0.1 to 0.3 Wm-2 larger in AGUNG1.
The average difference in the short-term volcanic forcing over the first 21 post-eruption months is 3 to 10 times larger than the long-term forcing radiative forcing of stratospheric ozone (-0.033 Wm-2) in CMIP6 and comparable to the long-term radiative forcing of the total ozone column (0.28 Wm-2 in CMIP6). The long-term radiative forcing of anthropogenic sulfate aerosols is assumed to be -0.4 Wm-2.
We estimate surface temperature
changes (ΔTs) to give a rough estimate of the consequences of this forcing difference. ΔTs relates to forcing as ΔTs=αF,
with F the radiative forcing and α the climate sensitivity
. α is a constant which differs for each
model. Thus in our case
ΔTs(AGUNG1)ΔTs(AGUNG2)=F(AGUNG1)F(AGUNG2)=-1.35Wm-2-1.23Wm-2=1.1,
with F(AGUNG1) and F(AGUNG2) the averages over the global
radiative forcing of months 3 to 9 after the eruption
(Fig. a). Thus, we overestimate
the surface cooling in AGUNG1 by a factor of
1.1 or 10 %. Both experiments show the
strongest difference of radiative forcing in the tropics
(Fig. b) and the strongest surface cooling
occurs in the tropics as well.
Comparison to observations
The zonally averaged AOD of AGUNG1 and AGUNG2 differs mainly in the tropics (Fig. a, b) and is rather similar in the SH extratropics. Our results agree quite well with the CMIP6 AOD (Fig. 6d), which shows, however, slower transport into the extratropics and no secondary maximum at 40 to 50∘ S. Less aerosol reaches the SH high latitudes in CMIP6, but it has a longer lifetime.
The CMIP5 volcanic forcing data used for the MPI-ESM simulations show a very different evolution (Fig. 6c), which might be related to not reliable measurements in the tropics .
Monthly mean AOD at 550 µm over time. (a, b) AGUNG1 and AGUNG2 ensembles. (c) AOD used for CMIP5 simulations and (d) AOD for CMIP6 simulations . Overlaid as colored circles are measurements of monthly mean AOD averaged over the regions 20 to 40∘ N and 20 to 40∘ S, given in Table 3 of , and single values for the south pole (after Fig. 2, same paper). The gray circles mark the volcanic eruptions, and the size represents the size of the eruption.
Both AGUNG experiments fit in general well to the measurements of
, which are included as circles in Fig. . The simulated NH AOD is slightly larger than the
measurements. Thus, it seems that ECHAM–HAM overestimates the
northward transport, but we have to take into account that
noted the measured NH AOD is barely above noise
level. In the SH the modeled AOD is smaller than the measurements, but
larger than the CMIP6 data. In ECHAM–HAM, meridional exchange within
the subtropics results in lower values between 20 and
30∘ S and a maximum at 50∘ S where the meridional
transport is blocked by the edge of the polar vortex. This maximum
AOD, above 0.2, is more similar to the measured AOD between 20 and 40∘ S which could be an indication of too strong
meridional transport in ECHAM–HAM. The AOD measurements of the months 19 to 21 and the CMIP6 data may indicate a too short lifetime of the
simulated aerosols at the SH high latitudes. This is most probably
related to too intense sedimentation at high latitudes
in the T42 resolution of ECHAM5. The consequence is too high wet deposition at
high latitudes, a well-known phenomena of ECHAM–HAM.
Monthly mean SH AOD (550 µm) over time. Colored lines show model results averaged over 25 to 30∘ S (blue) and 35 to 40∘ S (orange) each for both ensembles. The black line gives data of , the average of measurements between 20 and 40∘ S. Single markers show single measurement data, estimated from Fig. 1 in , with a similar color code to the model data.
A more detailed analysis of the SH extratropics is shown in Fig. . We averaged the model data over latitude bands
25 to 30∘ S and 35 to 40∘ S to compare
those to the single measurement data given in Fig. 1 of
. The simulated AOD is clearly smaller than the
point measurements, but one should take into account that horizontal
gradients in a volcanic cloud can be large. Thus, a point measurement
should give a higher value than an area mean of a model, which
represents an area of several hundred kilometers. Additionally,
measurements and simulated values depend not only on sulfate evolution
but also on transport. Further possible reasons for the differences
were stated before. In the first 3 months after the eruption, the
simulated AOD agrees well with the measurements. The onset of the
meridional transport is similar, but the simulated volcanic cloud
arrives slightly later in 25 to 30∘ S (see also Fig. ). The agreement between the model simulations and the
individual stations differs with time. Between 35 and
40∘ S, the model agrees better with the data of Mt. Bingar
(yellow cross) than with the Aspendale data (red triangle) in the first
months after the eruption, where the sulfate values increase 2
months earlier although the station is closer to the tropics. This may
indicate the dependency of the point source on the position of the
volcanic cloud. Both the timing of the maximum and the onset of the
decline agree well in measurements and model results.
Measured data of particle radii are not available, but the following
references provide some estimates, which are helpful for a rough comparison.
simulated for the SAGE-4λ dataset effective
radii of 0.3 to 0.4 µm for eruptions of the size of the Agung eruption.
estimates a radius of 0.35 µm from the
measurement data of the year 1963 at Bloemfontein, South Africa (29∘ S). Our simulated radii at the Equator (above 0.45 µm) and
at 50∘ S (above 0.4 µm) are larger
than these values for both experiments (Fig. ), with a better agreement in
AGUNG2. A smaller radius of the aerosols would cause a larger
AOD. The larger radii in our experiments lead us to the question of the requirement to include an
OH-limitation process for modeling the sulfate evolution, which is a still open
research question. In the case of high SO2 concentrations OH might
be limited for further SO2 oxidation . The slower formation of
sulfuric acid vapor would result in smaller
particles. assumed that OH limitation occurs only in
the case of a super-eruption, but show OH limitation
after the Mt. Pinatubo eruption as well. On the other hand,
showed that water vapor in the eruption cloud increases the amount of
available OH. This reaction was not included in the two studies cited
above. The results presented here use a fixed monthly mean OH concentration
which is not influenced by the volcanic cloud. Following ,
this missing OH limitation leads to
faster formation of sulfate resulting in larger sulfate
particles. Therefore, we performed one simulation with a simple
parameterization of OH limitation; see the Supplement for
details. This simulation shows slower sulfate formation, which agrees less
with the measurements, and only a slightly higher AOD half a year after the
eruption (Figs. S4 and S5) for the OH-limited case. As we use a simplistic parameterization these results are very limited.
Profiles of temperature anomaly (K) for the model data and RATPAC
radiosonde measurements taken from Free and Lanzante (2009), averaged over 2 years after the Agung eruption(s). Model results are averaged over 30∘ N to 30∘ S (black) and 15∘ N to 15∘ S (gray), whereas radiosonde data are averaged for the tropics only (30∘ N to 30∘ S; red line). The horizontal lines mark the 95 % confidence interval for the RATPAC radiosonde data.
Sulfate aerosol absorbs terrestrial radiation and warms the
stratosphere. This temperature signal depends in the model on the
coupling to radiation. We compare the results of the ensemble mean
temperature data to radiosonde data of . Both model
and measurement data are independent of QBO temperature relations (see
Sect. ). The measurements, averaged
over stations between 30∘ N and 30∘ S, shows a strong
maximum at 70 hPa (Fig. ). The average
over 30∘ N to 30∘ S of the model results (black lines)
show a smaller anomaly and a stronger vertical extension of the
heated area, more in AGUNG1 than in AGUNG2. Below the maximum at 70 hPa the simulated temperature is lower than the measurements. Both
features indicate too strong vertical lofting in the model. Figures and indicated a too low AOD in the model
results around 30∘ S. Therefore, we added a second temperature
profile, averaged over the main volcanic cloud at 15∘ N to
15∘ S (gray line), to Fig. . Now, the
maximum is represented better. However, more important is the
better agreement with the temperature decrease between 50 hPa
and 70 hPa, especially for AGUNG2. The easterly phase of the
QBO is related to downward motion and suppresses the vertical
lofting caused by the heating, but is also related to stronger
vertical transport in the secondary meridional circulation around
30∘ north and south. This upwelling seems to be stronger in
the model than in the measurements, causing the too high vertical extension
of the simulated volcanic cloud. While these results compare well to the
radiosonde data, simulated temperature anomalies are only half of those
observed in the SH (not shown). This may hint towards a too short
lifetime of the simulated sulfate aerosols (see Fig. a, b).
Summary and conclusions
We compared results of two scenarios for the Mt. Agung eruption in
1963: the commonly used one-eruption scenario with a strength of 7 TgSO2 and a scenario with two
eruptions. From AOD measurements one single number of the injected
sulfur amount was estimated, but observation and detection of the mass
flux show a scenario of two eruptions. Therefore, we assumed a
scenario with two climatic eruptions of 4.7 TgSO2 and
2.3 TgSO2 respectively. We simulated a lower burden in
the tropics, but slightly stronger meridional flow into the
extratropics in the simulation with two eruptions, AGUNG2, compared to AGUNG1. We relate
the stronger meridional flow to the lower injection altitude of the
second eruption, where the tropical transport barrier is
weaker. Additionally, the position of the tropical pipe is further
northward in May than in March. This allows more aerosols to be
transported into the NH. The smaller injection rate and the two
different injection altitudes cause the particles to grow less than in
AGUNG1. These processes result in 10 % to 20 % lower radiative
forcing, or 0.1 to 0.3 Wm-2 in monthly mean global average,
and estimated 10 % less surface cooling in AGUNG2. The strongest
signal would occur in the tropics.
When comparing to the few available measurements we see that the differences to the measurements are larger than the differences between the two experiments. We seem to underestimate the observed AOD and simulate larger particle radii. The timing of the aerosol evolution in the model seems to be supported by the measurements. Given the low number of observations at that time, especially in the tropics, it is difficult to validate the two experiments. Overall, the smaller particle size and slightly better shape of the temperature anomaly in the vertical profile of AGUNG2 are consequences of different transport and microphysical processes between the two experiments. These are arguments to include both climatic eruptions in future emission datasets.
One could also argue that the large model spread, as described by
and , limits the
interpretation of our model results. Other models may obtain
quantitatively different results, but most probably the simulated
difference between the two eruption scenarios would be qualitatively
similar: a lower radiative forcing of the Agung 1963 eruption when
including two eruption phases. Including a more sophisticated
atmospheric chemistry (including OH chemistry, water vapor, and ozone)
may increase the differences between the scenarios. Lower SO2
injection rates in AGUNG2 would cause less impact on OH and ozone, and
thus on chemical species in the stratosphere. Taking two eruption
phases into account will be important for processes in the early
evolution of sulfate. Ash and ice are important species in this early
phase. Both were not taken into account in the
simulations presented here but are planned for the future.
Overall, differences of around 10 % in the global annual averaged radiative forcing between
AGUNG1 and AGUNG2 should justify changes in the volcanic emission
datasets. The more recent volcano datasets are rather detailed. Also,
future studies using high horizontal and vertical resolution and more
sophisticated models will demand detailed input data. Details of our
assumptions on the Agung eruptions might be critically reviewed again
but, we recommend including both eruptions of Mt. Agung in upcoming
datasets.
Data availability
Primary data and scripts used in the analysis and
Supplement that may be useful in reproducing the
author's work are archived by the Max Planck Institute for
Meteorology and can be obtained by contacting
publications@mpimet.mpg.de. Model results are available under
https://cera-www.dkrz.de/WDCC/ui/cerasearch/entry?acronym=DKRZ_LTA_550_ds00002 Niemeier et al., 2019.
The supplement related to this article is available online at: https://doi.org/10.5194/acp-19-10379-2019-supplement.
Author contributions
CT had the main idea for the study. UN, CT, and KK discussed the experiment design. UN performed the experiments. UN prepared the text with contributions of all co-authors.
Competing interests
The authors declare that they have no conflict of interest.
Special issue statement
This article is part of the special issue “The Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP) (ESD/GMD/ACP/CP inter-journal SI)”. It is not associated with a conference.
Acknowledgements
We thank Hauke Schmidt for implementing
the QBO nudging into ECHAM5–HAM and Elisa Manzini, Alan Robock, and the anonymous reviewer for valuable comments. A discussion about the OH limitation in WACCM with Simone Tilmes helped to modify ECHAM5–HAM. The simulations were performed on the computer of the Deutsches Klima Rechenzentrum (DKRZ). Kirstin Krüger would like to thank Hauke Schmidt and MPI for Meteorology for the Guest Scientist invitation and UiO for the sabbatical that allowed the scientific exchange.
Financial support
This research has been supported by FP7
Environment STRATOCLIM (grant no. FP7-ENV.2013.6.1-2), the Deutsche Forschungsgemeinschaft priority program “Climate Engineering:
Risks, Challenges, Opportunities?” (grant no. SPP1689, project CELARIT, UN), the German federal Ministry of Education research program MiKlip (grant no. FKZ:01LP1517(CT)), and the DFG Research Unit VollImpact (FOR2820, UN CT). The article processing charges for this open-access publication were covered by the Max Planck Society.
Review statement
This paper was edited by Slimane Bekki and reviewed by Alan Robock and one anonymous referee.
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