Total volcanic stratospheric aerosol optical depths and
implications for global climate change
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Citation
Ridley, D. A., S. Solomon, J. E. Barnes, V. D. Burlakov, T.
Deshler, S. I. Dolgii, A. B. Herber, et al. “Total Volcanic
Stratospheric Aerosol Optical Depths and Implications for Global
Climate Change.” Geophysical Research Letters 41, no. 22
(November 25, 2014): 7763–7769. © 2014 American
Geophysical Union
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http://dx.doi.org/10.1002/2014gl061541
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American Geophysical Union (AGU)
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Thu May 26 23:02:27 EDT 2016
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Geophysical Research Letters
RESEARCH LETTER
10.1002/2014GL061541
Key Points:
• Revised estimate and uncertainty
of post-2000 volcanic forcing
and temperature
• Significant unaccounted volcanic
aerosol between the tropopause
and 15 km
• Novel use of AERONET to derive total
stratospheric aerosol optical depth
Supporting Information:
• Readme
• Text S1, Tables S1 and S2, and
Figures S1–S5
Correspondence to:
D. A. Ridley,
daridley@mit.edu
Citation:
Ridley, D. A., et al. (2014), Total volcanic
stratospheric aerosol optical depths and
implications for global climate change,
Geophys. Res. Lett., 41, 7763–7769,
doi:10.1002/2014GL061541.
Received 14 AUG 2014
Accepted 29 OCT 2014
Accepted article online 31 OCT 2014
Published online 25 NOV 2014
Total volcanic stratospheric aerosol optical depths
and implications for global climate change
D. A. Ridley1, S. Solomon2, J. E. Barnes3, V. D. Burlakov4, T. Deshler5, S. I. Dolgii4, A. B. Herber6,
T. Nagai7, R. R. Neely III8, A. V. Nevzorov4, C. Ritter9, T. Sakai7, B. D. Santer10, M. Sato11, A. Schmidt12,
O. Uchino7, and J. P. Vernier13,14
1
Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts,
USA, 2Department of Earth, Atmospheric, and Planetary Science, Massachusetts Institute of Technology, Cambridge,
Massachusetts, USA, 3Mauna Loa Observatory, NOAA, Hilo, Hawaii, USA, 4V.E. Zuev Institute of Atmospheric Optics, Siberian
Branch, Russian Academy of Sciences, Tomsk, Russia, 5Department of Atmospheric Sciences, University of Wyoming,
Laramie, Wyoming, USA, 6Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven,
Germany, 7Meteorological Research Institute, Tsukuba, Ibaraki, Japan, 8Advanced Study Program, National Center for
Atmospheric Research, Boulder, Colorado, USA, 9Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research,
Potsdam, Germany, 10Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory,
Livermore, California, USA, 11The Earth Institute, Columbia University, New York, New York, USA, 12School of Earth and
Environment, University of Leeds, Leeds, UK, 13Science Systems and Applications, Inc., Hampton, Virginia, USA, 14NASA
Langley Research Center, Hampton, Virginia, USA
Abstract Understanding the cooling effect of recent volcanoes is of particular interest in the context of
the post-2000 slowing of the rate of global warming. Satellite observations of aerosol optical depth above
15 km have demonstrated that small-magnitude volcanic eruptions substantially perturb incoming solar
radiation. Here we use lidar, Aerosol Robotic Network, and balloon-borne observations to provide evidence
that currently available satellite databases neglect substantial amounts of volcanic aerosol between the
tropopause and 15 km at middle to high latitudes and therefore underestimate total radiative forcing
resulting from the recent eruptions. Incorporating these estimates into a simple climate model, we determine
the global volcanic aerosol forcing since 2000 to be 0.19 ± 0.09 Wm 2. This translates into an estimated
global cooling of 0.05 to 0.12°C. We conclude that recent volcanic events are responsible for more post-2000
cooling than is implied by satellite databases that neglect volcanic aerosol effects below 15 km.
1. Introduction
Over about the past 15 years, globally averaged surface temperatures have increased more slowly than
during the two previous decades (≈1980–2000), a phenomenon sometimes referred to as the “hiatus” or
“pause” in global warming. Suggested mechanisms that may contribute to this behavior include (but are not
limited to) increased heat uptake by the oceans, reduced solar output, and recent volcanic eruptions (see the
brief review by Schmidt et al. [2014, and references therein]).
It has often been assumed that only very explosive volcanic eruptions have pronounced effects on stratospheric
aerosol optical depth (SAOD) and that since Mount Pinatubo in 1991, no eruptions have contributed noticeably
to stratospheric aerosol content. However, observations since about 2005 revealed significant increases in
SAOD linked to a series of smaller eruptions [Vernier et al., 2011; Bourassa et al., 2012], with potentially important
cooling effects on global climate [Solomon et al., 2011; Fyfe et al., 2013; Haywood et al., 2014].
Available satellite observations of SAOD typically consider aerosol extinction only above 15 km to reduce
potential contamination by clouds. However, a portion of the lower stratosphere generally resides below
this altitude at middle and high latitudes, where the tropopause is frequently found at 10 km or lower.
Here we present evidence for a significant contribution to SAOD from the lowermost stratosphere region.
Based on observations from lidar retrievals, balloon-borne aerosol sondes, ground-based Aerosol Robotic
Network (AERONET) Sun photometers, and satellite data, we estimate increases in global total SAOD since
2000, together with associated uncertainties. The resulting total estimated volcanic aerosol forcing averaged
over the period 2000–2013 is found to be 0.19 ± 0.09 Wm 2, up to 80% larger than the estimate of Solomon
et al. [2011].
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2. Observational Data Sets
In this study we make use of SAOD retrievals from multiple observing systems: four lidars measuring
backscatter at 532 nm, a balloon-borne particle counter (aerosol sonde), Sun photometers in the Aerosol
Robotic Network (AERONET), and two satellite data sets. The polarization lidar at Tsukuba (36.1°N, 140.1°E)
provides backscatter integrals both above the tropopause and above 15 km [Uchino et al., 2012]. The lidar
based at Tomsk (56.5°N, 85.0°E) makes similar measurements of integrated backscatter both above 12 km and
15 km [Bazhenov et al., 2011]. At Ny Ålesund (78.9°N, 11.9°W), lidar backscatter was obtained both above
10 km and 15 km [Hoffmann et al., 2009], while at Mauna Loa (19.5°N, 155.6°W), backscatter integrated above
the tropopause (typically at 15–16 km) has been monitored since 2000 [Hofmann et al., 2009]. The Ny Ålesund
and Tomsk data presented here are integrations from fixed altitudes of 10 km and 12 km, rather than at the
tropopause; for simplicity, however, throughout the analysis, we will refer to the lidar retrievals as either
“above tropopause” or “above 15 km.” All of these integrated 532 nm backscatter measurements were
converted to SAOD using a lidar ratio (integrated extinction/backscatter) of 50 [see Jäger and Deshler, 2002,
2003]. The Laramie aerosol sondes have measured detailed particle size distributions since 2000 and were
used to confirm that a lidar extinction to backscatter ratio of 50 is still appropriate for the stratosphere; this
was found to be the case within an uncertainty of 10–20%.
The Laramie data extend from the surface to typically 30 km [Deshler et al., 2003]. SAOD is computed above
15 km and above the tropopause through integrations of 532 nm extinction calculated from the profile of size
distribution measurements, using a refractive index of 1.45—0i for stratospheric sulfate. Days with tropopause
heights above 15 km are not included in the comparisons presented here (14% of the observations).
Satellite retrievals of SAOD are presented below from two data sets, both of which integrate aerosol loads
above 15 km altitude. Sato et al. [1993], updated on the NASA Goddard Institute for Space Studies website,
and hereafter referred to as Sato et al., have produced a long-term (1850 to present) reconstruction from a
variety of observations, relying exclusively on Optical Spectrograph and InfraRed Imager System satellite
measurements [Bourassa et al., 2008] since 2001. We also show an updated version of the merged SAOD data
set developed by Vernier et al. [2011, hereafter referred to as Vernier et al.], which extends from 50°S to 50°N
and incorporates satellite data from multiple platforms (Stratospheric Aerosol and Gas Experiment (SAGE) II
between October 1984 and August 2005, SAGE III from February 2002 until the end of 2005, and Global
Ozone Monitoring by Occultation of Stars from 2006 onward).
3. Detecting Volcanic Aerosol With AERONET Observations
To provide an independent estimate of the total column SAOD, we make use of observations from AERONET
Sun photometers deployed at ground sites worldwide to measure total aerosol optical depth. The widespread
coverage of these stations, which span a wide range of elevations, is key to a global analysis. These
measurements are often used as calibration for satellite retrievals and are considered to have an aerosol optical
depth retrieval error of <0.01 at wavelengths 440 nm and greater [Holben et al., 1998]. While the majority of the
aerosol detected is often tropospheric, we will show that the quality of the retrieval, availability of daily data,
and the large number of stations providing information make estimation of SAOD feasible. Because the
measured SAOD at certain locations and times may be close to the retrieval accuracy of the instrument, we
employ a range of methods to ensure data quality and robust results (see supporting information).
Solomon et al. [2011] compared tropical satellite, lidar, and surface-based optical depth data for 21st century
volcanic eruptions. They showed that surface-based optical depth observations from the clearest days of the
year at Mauna Loa were dominated by stratospheric signals following volcanic eruptions and agreed well
with other observation methods. Here we perform a similar analysis at a variety of stations using AERONET data.
To ensure that AERONET measurements can provide a reliable estimate of volcanic SAOD, we demonstrate that
the timing of the increase in SAOD is significantly correlated with volcanic eruptions and that the ability to
detect volcanic signatures is not significantly affected by station location and sampling periods. We also
compare AERONET data to lidar observations.
We briefly describe the approach taken to derive stratospheric information from AERONET data, see
supporting information for a detailed discussion. At each station, the minimum AOD at 500 nm (AODmin)
observed on the five cleanest days within a year is averaged. The data are quality checked by ensuring that
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Figure 1. (a) The SAOD time series for the period 1995–2013 for satellite data from Vernier et al. (blue), Sato et al. (orange),
AERONET mean, averaged from 30–45°N, (white) with 25th to 75th percentile uncertainty (grey shading), Tsukuba lidar
retrievals (36.1°N, 140.1°E) above the tropopause (thick black line) and 15 km (thin black line), and aerosol sonde measurements at Laramie (41°N) above the tropopause (red dots) and 15 km (red crosses). Potentially important equatorial
(solid lines) and middle to high latitude (dashed lines) volcanic eruptions are shown for Ulawun, Shiveluch, Ruang,
Reventador, Manam, Soufrière Hills, Tavurvur, Kasatochi, Sarychev, Eyjafjallajökull, and Nabro. (b) Ratio of integrated optical
depth above the tropopause to that above 15 km from three different lidars and from the in situ observations. The inset
contains the same data on a log scale to indicate the ratios greater than 5 that are cropped for clarity on Figure 1a.
these minimum AOD observations are within a factor of 2 of one another. Any values that fail these criteria
are discarded to remove bias by potential individual measurement errors (this rarely occurs). The averaging
removes transient tropospheric features, such as anthropogenic pollution episodes and biomass burning
events, but should capture persistent enhancements in the stratospheric aerosol observed after eruptions.
Systematic enhancements in AODmin are evident following the series of recent eruptions (Figures S1 and S3
in the supporting information). Two different Monte Carlo tests were used to check the robustness of the link
of these apparent AERONET enhancements in AODmin to the eruptions: first, by randomizing the timing of
the 11 larger eruptions since 2000 and second, by randomizing the years of the AERONET data. These tests
showed that the increases in AERONET-based AODmin measurements following the 11 selected eruptions are
significant at the 10% level or better (see supporting information).
We find that the lowest AOD measured at each AERONET station is strongly dependent on station elevation,
which is key to our analysis. Stations closer to sea level do not sample conditions as pristine as those at higher
elevations, leading to a robust relationship between the logarithm of a station’s elevation and the minimum
AOD at that station. Using this relationship, we obtain the AOD as the measured enhancement above the
clean background SAOD and tropospheric AOD for the time series (see Figure S2 in the supporting
information); a clean background stratospheric AOD of 0.0015 is then added to each data point to obtain the
total SAOD. The estimated SAOD is averaged across all available AERONET stations within four latitude bands:
30°S–30°N (8 stations), 30°N–45°N (22 stations), 45°N–60°N (6 stations), and 60°N–90°N (8 stations). A
sampling uncertainty range for the AERONET estimate of SAOD is developed by creating ensembles of three
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randomly selected stations in each
latitude band, from which we determine
the mean annual SAOD. The 25th to
75th percentiles of the ensemble means
are considered the uncertainty range,
thereby minimizing the chance of the
AERONET SAOD estimate being
dominated by a single station.
4. Multi-Instrument Estimates
of SAOD Above and
Below 15 km
Figure 1a shows the observed SAOD
time series for 1995–2013 obtained
from the annual averages of AERONET
data from 30 to 45°N and compared
with satellite data (Vernier et al.; Sato
et al.), the lidar at Tsukuba (36°N), and
aerosol sondes from Laramie, WY (41°N).
Because of strong zonal winds, we
assume that stratospheric aerosol at a
given latitude becomes well mixed
within a few weeks or so, allowing
Figure 2. SAOD time series for the period 2004–2013 between (a) 30°S–30°N,
meaningful comparisons within a
(b) 45°N–60°N, and (c) 60°N–90°N. As in Figure 1, satellite data from
latitude band. The satellite and Tsukuba
Vernier et al. (blue), Sato et al. (orange), and the AERONET mean (light grey)
lidar data integrated above 15 km agree
as well as the 25th to 75th percentile uncertainty (grey shading). Lidar
retrievals at 15 km (thin black lines) and 10 km/12 km (thick black lines) are on the magnitude and timing of SAOD
enhancements associated with known
shown. At Mauna Loa, the tropopause is at 15–16 km, so only a single
line is shown. The solid and dashed vertical lines indicate the tropical and
eruptions. However, at this latitude, the
higher-latitude eruptions, respectively.
lidar reveals substantially larger SAOD
when integrated above the tropopause.
The ratio of the lidar data above the tropopause to that above 15 km (Figure 1b) demonstrates the key role of
the lowermost stratosphere for total SAOD. The Laramie balloon data are sparse and are generally lower in
absolute values than the lidar but display ratios of the SAOD integrated above the tropopause and above
15 km that are very similar to those measured by the Tsukuba lidar, again showing the importance of the
contribution from the lower stratosphere. Based on the Tsukuba lidar and aerosol sonde observations, an
average of 28–39% of the optical depth observed above the tropopause resides below 15 km. At times, the
contribution of this region to total SAOD is as large as 66–82%. We note, however, that not all of the SAOD
contribution below 15 km can be attributed to volcanic aerosol, especially in the winter and spring months
when the tropopause is lowest. This is evident from the seasonal variations in SAOD.
The AERONET SAOD values are generally larger than those of the satellite data sets but are in good
agreement with the lidar SAOD above the tropopause (see Figure S4 in the supporting information). Prior
to 2007, the mean AERONET SAOD often exceeds the satellite SAOD by over a factor of 2, although the
uncertainty range generally encompasses the Vernier data. The fact that the aerosol sonde SAOD shows
very similar enhancements following eruptions to that found at Tsukuba, but is generally lower than the
satellite and lidar data, adds to the uncertainty in the absolute values of SAOD.
Figure 1b also presents ratios between the SAOD integrated above the tropopause and above 15 km from
two higher-latitude lidar stations, Tomsk and Ny Ålesund. It provides further evidence that at certain
locations, the region below 15 km contributes markedly to total SAOD, particularly in the winter season or
immediately following nearby eruptions (e.g., Ny Ålesund in summer 2009, which directly sampled the
Sarychev Peak plume). The observational study by Jégou et al. [2013] independently confirms the importance
of volcanic aerosol below 15 km following Sarychev.
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Figure 3. (a) Estimated global mean radiative
forcing is shown for data sets from Sato et al.
(orange), Vernier et al. (blue), and AERONET
mean (black) with 25th to 75th percentile ranges
(grey). The dotted line indicates the baseline
model used in many climate model studies to
date, which includes no stratospheric aerosol
changes after 2000. (b) The temperature anomaly, relative to the baseline model, including the
AERONET mean (black), median (white), and 25th
to 75th percentile ranges (grey); Vernier et al.
(blue); and Sato et al. (orange) forcing computed
for each data set. (c) The total global temperature
change predicted by the Bern 2.5cc EMIC in
response to combined anthropogenic and natural forcing, including the reduced warming
when considering the stratospheric aerosol forcing from the three data sets.
10.1002/2014GL061541
Figure 2 displays the comparisons between the satelliteinferred SAOD at a range of latitude bands and corresponding
SAOD estimates from the Mauna Loa, Tomsk, and Ny Ålesund
lidars between 2004 and 2013. Agreement between lidar,
AERONET, and the Vernier et al. and Sato et al. data sets is
excellent in the tropics (30°S–30°N; Figure 2a), where the
tropopause is close to 15 km. Aerosols from tropical eruptions
will, however, be transported downward and poleward over
time, so that the aerosol column burden above the tropopause
at the middle and high latitudes will be larger than that above
15 km, especially in winter (just as occurs for column ozone). At
subpolar midlatitudes (45–60°N; Figure 2b), the Tomsk lidar
retrievals also suggest that a substantial amount of the total
stratospheric optical depth (about 50% on average) comes
from the region between 12 km and 15 km. However, unlike the
other locations, the Tomsk lidar SAOD above 15 km is generally
0.005 greater than the satellite data sets during clean periods,
and the integral above 12 km is often 0.01 higher than the
AERONET mean. Because the altitude is fixed at 12 km, rather
than tracking the tropopause height, there is potential for
tropospheric aerosol to be present in this measurement. At
high latitudes (60–90°N; Figure 2c), the Ny Ålesund lidar
indicates that 72% of the SAOD resides between 10 km and
15 km between 2008 and 2010. After the Sarychev Peak (48°N)
eruption, almost all the SAOD is present below 15 km.
Therefore, while the Sato data set is in good agreement with
lidar retrievals at Ny Ålesund above 15 km, the Sato data set
does not account for the vast majority of the SAOD at this
latitude. Although the lidar data are limited, the annual
AERONET SAOD appears to represent well the SAOD before
and after the Sarychev Peak eruption when compared with the
lidar above 10 km. Our study does not quantify all of the many
possible sources of structural uncertainty. While it is clear that
the Sato et al. and Vernier et al. data sets neglect important
contributions from the lowermost stratosphere below 15 km
that are evident in both aerosol sonde and lidar data, the
former also suggest that uncertainties in optical properties are
important and the lidar data could be biased high.
5. SAOD Radiative Forcing and Global Mean Climate Response
Figure 3 presents estimates of the effect of the SAOD (from Vernier et al., Sato et al., and AERONET, with the
previously described uncertainty bound on the latter) on radiative forcing and global-mean temperature
change based on the Bern 2.5cc Earth Model of Intermediate Complexity (EMIC) [Plattner et al., 2008], which
was run in the same configuration used by Solomon et al. [2011]. The SAOD from each AERONET latitude band
is weighted by the band surface area and combined to produce a global average, and this is converted to a
forcing using a scaling factor of 25 Wm 2, following Solomon et al. [2011]. Since most AERONET stations are
located north of 30°S, we obtain a conservative estimate of global-mean SAOD by making the simplifying
assumption that the SAOD between 30°S and 90°S is the same as in the tropics. The global-mean SAOD is
assumed to be suitable approximation for an EMIC. The Vernier et al. data set is only available equatorward of
50°N and 50°S; we therefore assume that SAOD poleward of 50° is the same as at 50°. AERONET data are
limited prior to 2000; therefore, we only introduce the SAOD forcing from each data set in 1999.
The AERONET SAOD produces a mean global radiative forcing of 0.19 ± 0.09 Wm 2 between 2000 and 2013
(Figure 3a). Over the same period, the AERONET forcing results in a global temperature reduction ranging
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from 0.05°C to 0.12°C, with peak reductions in 2012. With forcings inferred from the Vernier et al. and Sato
et al. data sets, temperature changes are smaller ( 0.04°C in both cases, see Figures 3b and 3c). Some
volcanic aerosol enhancements are expected in the upper troposphere and would be captured by AERONET;
on the other hand, tropospheric pollution could lead to a high bias in AERONET despite the approach taken
to minimize these effects. Figure 3 suggests a larger volcanic contribution to recent global temperature
changes than has been inferred from previous work. Clearly, it is desirable to obtain a more reliable
quantification of the contribution of this and other forcings (such as changes in solar activity) to the hiatus
[Schmidt et al., 2014] and to reduce uncertainties in observational estimates of the decadal rate of change of
global mean temperature [Cowtan and Way, 2014].
6. Discussion
Satellite observations have shown that volcanic eruptions since 2000 introduced aerosol into the
stratosphere, and this represents a forcing overlooked in climate models until very recently. The climate
model simulations evaluated in the fifth assessment report of the Intergovernmental Panel on Climate Change
[2014] generally assumed zero stratospheric aerosol after about 2000 and hence neglect any cooling effect of
recent volcanoes [see Solomon et al., 2011, Figure 3]. We find that satellite-based SAOD data sets generally
agree well with SAOD inferred from lidar measurements above 15 km; however, they do not capture the full
magnitude of the SAOD signal above the tropopause. Lidar and balloon-borne observations indicate that
aerosol loading between the tropopause and 15 km contributes roughly 30 to 70% of the total SAOD and this
percentage can increase further immediately following eruptions. We have shown that AERONET Sun
photometers are capable of detecting SAOD sufficiently well to identify enhancements following volcanic
eruptions, albeit with large quantitative uncertainties. The magnitude and interannual variability of the
AERONET ensemble mean are in good agreement with many independent ground-based lidar observations
integrated above the tropopause. The resulting post-2000 global forcing from AERONET data is 0.19
± 0.09 Wm 2, suggesting that the global mean volcanic aerosol forcing could be substantially larger than that
used in previous studies.
The SAOD below 15 km may help to explain certain aspects of the sensitivity of lower tropospheric
temperature (TLT) to SAOD found by Santer et al. [2014]. They showed that decreases in TLT are negatively
correlated with enhancements in SAOD following eruptions; however, the magnitude of the TLT fluctuations
(and the high statistical significance of the correlations between Vernier et al. SAOD and TLT) implied a larger
TLT response to recent volcanic eruptions than would be expected based solely on the SAOD data above
15 km. Including the substantial “below 15 km” contributions to volcanically induced SAOD signals found in
the present study will lead to a more realistic sensitivity of TLT to SAOD, further strengthening the case that
“smaller” eruptions have substantially influenced tropospheric temperature in the past decade.
Acknowledgments
The Laramie in situ aerosol measurements have been supported primarily by
the National Science Foundation, with
the current measurements funded under
grant 1011827. Measurements at Tomsk
were supported in part by the Ministry of
Science and Education of the Russian
Federation (agreements 14.604.21.0046
and 14.604.21.0100) and the Russian
Science Foundation (agreement 14-2700022). The authors would like to thank
the PIs of AERONET stations used in this
study, the data from which can be
obtained at http://aeronet.gsfc.nasa.gov/.
The Editor thanks two anonymous
reviewers for their assistance in
evaluating this paper.
RIDLEY ET AL.
Finally, the SAOD above 15 km most noticeably underestimates the total SAOD at high latitudes following an
eruption, particularly a high-latitude eruption. The polar regions account for less than 15% of the global
surface area; therefore, while these regions do not contribute greatly to the global forcing, the regional
forcing can be markedly affected, for example following high-latitude eruptions such as Sarychev Peak.
Further investigation of the regional and global impact of stratospheric aerosol in the current generation of
climate models should account for the observational uncertainties in SAOD discussed here. Such studies will
help to elucidate the contribution of volcanic aerosol to the warming hiatus.
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aerosol layer and global climate change, Science, 333(6044), 866–870, doi:10.1126/science.1206027.
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RIDLEY ET AL.
©2014. American Geophysical Union. All Rights Reserved.
7769
1
Auxiliary Material for
2
Uncertainties in recent volcanic aerosol optical depths and implications for global climate
3
change
4
D. A Ridley1, S. Solomon2, J. E. Barnes3, V.D. Burlakov4, T. Deshler5, S.I. Dolgii4, A.B.
5
Herber6, T. Nagai7, R. R. Neely III8, A.V. Nevzorov4, C. Ritter9, T. Sakai7, B. D. Santer10, M.
6
Sato11, A. Schmidt12, O.Uchino7, J. P. Vernier13,14
7
1
Department of Civil and Environmental Engineering, Massachusetts Institute of Technology,
Cambridge, MA 02139
8
2
9
Department of Earth, Atmospheric, and Planetary Science, Massachusetts Institute of
Technology, Cambridge, MA 02139
10
3
11
12
4
V.E. Zuev Institute of Atmospheric Optics, Siberian Branch, Russian Academy of Sciences,
Academician Zuev square 1, 634021, Tomsk, Russia
13
5
14
7
17
8
9
22
Meteorological Research Institute, 1-1 Nagamine, Tsukuba, Ibaraki 305-0052, Japan
Advanced Study Program, National Center for Atmospheric Research, Boulder, CO, 80307
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, 14473 Potsdam,
Germany
20
21
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, 14473
Bremerhaven, Germany
16
19
Department of Atmospheric Sciences, University of Wyoming, Laramie, WY 82071
6
15
18
NOAA/Mauna Loa Observatory, Hilo, HI 96720
10
Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National
Laboratory, Livermore, CA 94550
11
23
24
12
The Earth Institute, Columbia University, New York, NY 10115
School of Earth and Environment, University of Leeds, Leeds, UK, LS2 9JT
13
25
Science Systems and Applications, Inc., Hampton, VA, USA
14
26
NASA Langley Research Center, Hampton, VA, USA
27
28
Introduction
29
These supplementary materials elaborate on the filtering and processing of the AERONET
30
station measurements to produce the stratospheric aerosol optical depth (SAOD) estimate and
31
uncertainty. We also include a comparison of annually averaged SAOD from lidar with
32
AERONET and the satellite datasets discussed in the paper.
33
34
AERONET data filtering
35
The initial analysis was repeated using two different AOD retrievals provided by the AERONET
36
team: the standard level 2.0 data, interpolated to 500 nm, and the retrieval used to derive fine and
37
coarse AOD fraction (O’Neill et al., 2003). Both result in similar AOD enhancements following
38
eruptions even though different subsets of data are available for each. The results throughout this
39
work are for the standard level 2.0 data, simply because that is the larger dataset of the two and
40
therefore gives a better estimate of the uncertainty.
41
Here we describe the filtering used on the AERONET data. A site must have at least 6 years of
42
data to be considered, leaving 260 of the 600+ AERONET sites. At a site, the minimum hourly
43
AOD observation made within a day is taken. If no hourly data are available we use the daily
44
average. For years with at least 90 measurements, all AOD data within a year are sorted and the
45
lowest 5 values are checked to ensure that they fall within a factor of 2 of one another; if not, the
46
lowest value is discarded and the new lowest 5 values are checked. This is to ensure that a small
47
number of extremely low AOD results that may be due to retrieval error do not bias the
48
minimum AOD. The average of the 5 values is taken and this is considered as the minimum
49
AOD for that year. We then filter out sites that have mean minimum AOD of greater than 0.02 to
50
remove the sites that do not detect pristine enough conditions. The average Arctic sites are only
51
able to make measurements from spring to fall, therefore we relax the measurements per year
52
criteria from 90 to 45, the minimum number of years to 3 and the minimum AOD threshold to
53
0.05 for sites above 60°N.
54
Figure S1 shows all AERONET data at three sites from each latitude band used in this study, as
55
an example of how the calculated minimum AOD varies, and showing how increases coincide
56
with the key volcanic eruptions in 2006, 2009 and 2011. Table S2 lists all 44 AERONET sites
57
used in this study.
58
59
Deriving the tropospheric and stratospheric background AOD
60
The relationship between site elevation and the minimum AOD is critical for combining data
61
from multiple AERONET sites. The minimum AOD for a specific elevation represents the
62
combined tropospheric and stratospheric background AOD above which we assume any increase
63
in AOD to be a stratospheric enhancement. To determine the SAOD we must reintroduce the
64
clean stratospheric background AOD, estimated to be approximately 0.0015 based on the
65
minimum SAOD retrieved from the multiple lidar observations used in this study. The results are
66
not sensitive to a 50% change in the assumed background; however, on rare occasions the
67
calculated annual SAOD can be negative because the enhancement derived from the AERONET
68
observation can be negative compared to this baseline. In these cases we set the SAOD to the
69
background value. We calculate the regression between elevation and minimum AOD for sites in
70
each latitude band (Fig. S2).
71
For a site to be used in determining the relationship between the elevation and the minimum
72
AOD, we require that at least 5 years of data are available and that data be present prior to 2004.
73
This ensures that only sites with data available prior to the period of significant eruptions, and
74
therefore sampling the persistent background SAOD, are included. Note: all sites are included in
75
the full analysis, just not in the derivation of the regression between minimum AOD and
76
elevation. Figure S2 illustrates the robust relationship for most sites in a latitude band. Arctic
77
sites have fewer observations per year; therefore, we choose to apply a fixed background of 0.03
78
based on the available data prior to 2004 from Ny Alesund and Barrow that appears to represent
79
Arctic sites well.
80
81
Assessing the significance of AERONET AOD enhancements
82
The relationship between the minimum AOD and the site elevation is robust only as an annual
83
average. Seasonality confounds the relationship; however, to determine whether the AERONET
84
minimum AOD is influenced by eruptions requires a temporal resolution finer than annual. We
85
normalize the minimum AOD for each month to the climatological monthly mean for an
86
AERONET site with at least 5 years of data. The normalization allows use of a moving 90-day
87
averaging window, rather than a year, giving higher temporal resolution at the expense of
88
determining the absolute SAOD (Fig S3). This normalized AOD is an AOD enhancement factor
89
(AEF) from the climatological mean and shows remarkably good agreement with the Sato et al.
90
and Vernier et al. datasets.
91
To assess the significance of the timing of enhancements in the AERONET AOD we randomize
92
the timing of the 11 eruptions (shown on Fig S3) and calculate the corresponding AEF for the
93
following period, averaged across all AERONET sites. We find that the AEF averaged over the
94
150-day periods following the eruptions is greater than 94% of 10,000 randomized eruptions.
95
A second significance test evaluates the coherence between AERONET sites that are spread
96
across the northern hemisphere. The AEF for each site is randomized by reordering the years, but
97
not the months, so that seasonality is retained. For a 10,000 member ensemble, we calculate the
98
AEF after the 11 eruptions and average for all sites. The observed AEF is greater than 96% of
99
the randomized cases.
100
These results suggest that the increase in the minimum AOD observed by AERONET is a
101
consequence of volcanic eruptions and that the coherence between sites is unlikely to be chance.
102
103
Deriving the uncertainty estimate in SAOD
104
To estimate the uncertainty in the AERONET SAOD we generate ensembles of 3 sites and use
105
the statistics to determine an average SAOD for each latitude band and the 25-75% distribution
106
range (described in the main paper). Furthermore, we account for potential sampling issues that
107
result from the chosen start day of each annual average by repeating the analysis for 6 different
108
offsets between 0 and 150 days from January 1st 1995. When multiple sites are available the
109
annual SAOD is generally consistent between offsets; however, the SAOD can vary in years
110
with limited data. Therefore, we take the average of each annual SAOD at the different offsets.
111
The 1-σ uncertainty in the regression between elevation and minimum AOD (Fig S2) represents
112
another method to assess the uncertainty in the SAOD. Repeating the EMIC simulations using
113
these upper and lower bounds for the SAOD regression yields an uncertainty in the post-2000
114
radiative forcing of ±0.05Wm-2 (Fig S4). This is roughly half of the uncertainty derived when
115
taking random selections of AERONET sites; therefore, we consider our post-2000 forcing
116
estimate and uncertainty (-0.19 ± 0.09 Wm-2) to be reasonable.
117
118
Annual comparison between AERONET, satellite and lidar
119
The comparison of the satellite and AERONET datasets with lidar is summarized in Figure S5.
120
The lidar AOD from 15km upwards is shown in grey and the lidar retrieval from levels
121
approximating the tropopause, and therefore expected to represent the full stratospheric aerosol
122
column, are shown in black (only the total column is shown for Mauna Loa, as this is similar to
123
the SAOD above 15km in the tropics). The satellite annual averages only include months in
124
which lidar data are also available.
125
For the Vernier and Sato datasets we find that the annual average SAOD is generally within a
126
factor 2 of the lidar SAOD above 15 km at Mauna Loa and Tsukuba, but usually lower in the
127
Sato dataset. When the lidar retrieval above the tropopause is used the agreement worsens
128
dramatically, especially at Tomsk and Ny Alesund. This suggests that a significant amount of
129
stratospheric aerosol resides below 15 km that is not captured by either satellite dataset.
130
Comparing the annually average SAOD from lidar above the tropopause and AERONET,
131
agreement is generally within a factor of two, demonstrating both the importance of stratospheric
132
aerosol below 15 km and the ability of AERONET to observe it. The Tomsk lidar data are
133
consistently higher than the satellite and AERONET data, both above 15 km and above 12 km,
134
indicating that the lidar may be including tropospheric aerosol when the tropopause is above 12
135
km, as mentioned in the main text.
136
137
References
138
Bazhenov, O. E., Burlakov, V. D., Dolgii, S. I. and Nevzorov, A. V.: Lidar observations of the
139
stratosphere aerosol disturbances over Tomsk (56.5 N; 85.0 E) in period of volcanic activity of
140
2006-2010, Opt Atmosf Okeana, 24(12), 1031–1040, 2011.
141
Deshler, T., Hervig, M. E., Hofmann, D. J., Rosen, J. M. and Liley, J. B.: Thirty years of in situ
142
stratospheric aerosol size distribution measurements from Laramie, Wyoming (41°N), using
143
balloon-borne instruments, J. Geophys. Res. Atmospheres, 108(D5), 4167,
144
doi:10.1029/2002JD002514, 2003.
145
Hoffmann, A., Ritter, C., Stock, M., Shiobara, M., Lampert, A., Maturilli, M., Orgis, T., Neuber,
146
R. and Herber, A.: Ground-based lidar measurements from Ny-Ålesund during ASTAR 2007,
147
Atmos Chem Phys, 9(22), 9059–9081, doi:10.5194/acp-9-9059-2009, 2009.
148
Hofmann, D., Barnes, J., O’Neill, M., Trudeau, M. and Neely, R.: Increase in background
149
stratospheric aerosol observed with lidar at Mauna Loa Observatory and Boulder, Colorado,
150
Geophys. Res. Lett., 36(15), L15808, doi:10.1029/2009GL039008, 2009.
151
O’Neill, N. T., Eck, T. F., Smirnov, A., Holben, B. N. and Thulasiraman, S.: Spectral
152
discrimination of coarse and fine mode optical depth, J. Geophys. Res. Atmospheres, 108(D17),
153
4559, doi:10.1029/2002JD002975, 2003.
154
Sato, M., Hansen, J. E., McCormick, M. P. and Pollack, J. B.: Stratospheric aerosol optical
155
depths, 1850–1990, J. Geophys. Res. Atmospheres, 98(D12), 22987–22994,
156
doi:10.1029/93JD02553, 1993.
157
Uchino, O., Sakai, T., Nagai, T., Nakamae, K., Morino, I., Arai, K., Okumura, H., Takubo, S.,
158
Kawasaki, T., Mano, Y., Matsunaga, T. and Yokota, T.: On recent (2008–2012) stratospheric
159
aerosols observed by lidar over Japan, Atmos Chem Phys, 12(24), 11975–11984,
160
doi:10.5194/acp-12-11975-2012, 2012.
161
Vernier, J.-P., Thomason, L. W., Pommereau, J.-P., Bourassa, A., Pelon, J., Garnier, A.,
162
Hauchecorne, A., Blanot, L., Trepte, C., Degenstein, D. and Vargas, F.: Major influence of
163
tropical volcanic eruptions on the stratospheric aerosol layer during the last decade, Geophys.
164
Res. Lett., 38(12), L12807, doi:10.1029/2011GL047563, 2011.
165
166
Table S1 – Summary of observational datasets used.
Dataset Name
Type
Altitude for SAOD
Latitude
Reference
Ny Alesund
Lidar
>10 km, >15 km
79°N
Hoffmann et al. (2009)
Tomsk
Lidar
>12 km, >15 km
56°N
Bazhenov et al. (2011)
Laramie
Balloonborne particle counter
>TP, >15 km
41°N
Deshler et al. (2003)
Tsukuba
Lidar
>TP, >15 km
36°N
Uchino et al. (2012)
Mauna Loa
Lidar
>TP, >15 km
19°N
Hofmann et al. (2009)
Sato
Satellite composite
>~15 km
90°S – 90°N
Sato et al. (1993)
Vernier
Satellite composite
>~15 km
50°S - 50°N
Vernier et al. (2011)
167
168
Table S2 – AERONET sites used in the analysis.
AERONET site
Longitude
Latitude
Elevation (m)
Data (years)
Tinga Tingana
139.99
-28.98
38
7
Birdsville
139.35
-25.9
46
8
Reunion St Denis
55.48
-20.88
0
7
Lake Argyle
128.75
-16.11
150
11
Mauna Loa
-155.58
19.54
3397
18
Lanai
-156.92
20.74
20
6
Dry Tortugas
-82.87
24.63
0
6
Izana
-16.5
28.31
2391
9
White Sands
-106.34
32.63
1207
8
Maricopa
-111.97
33.07
360
7
San Nicolas
-119.49
33.26
133
6
Sevilleta
-106.89
34.35
1477
16
Table Mountain
-117.68
34.38
2200
9
Monterey
-121.86
36.59
50
6
Cart_Site
-97.49
36.61
318
14
Frenchman Flat
-115.93
36.81
940
6
Cove
-75.71
36.9
37
9
Red Mountain Pass
-107.72
37.91
3368
6
Railroad Valley
-115.96
38.5
1435
11
Konza
-96.61
39.1
341
9
Burjassot
-0.42
39.51
30
6
Boulder
-105.01
40.04
1604
13
Barcelona
2.12
41.39
125
10
Palencia
-4.52
41.99
750
8
Billerica
-71.27
42.53
82
10
Issyk-Kul
76.98
42.62
1650
6
Toulon
6.01
43.14
50
7
Observatoire Haute-Provence
5.71
43.94
680
9
Carpentras
5.06
44.08
100
11
HJ Andrews
-122.22
44.24
830
13
Howland
-68.73
45.2
100
8
Venise
12.51
45.31
10
15
-111.04
45.66
1507
6
Ispra
8.63
45.8
235
17
Davos
9.84
46.81
1596
6
Bratts Lake
-104.7
50.28
586
13
Ittoqqortoormiit
-21.95
70.49
68
4
Barrow
-156.66
71.31
0
13
Resolute Bay
-94.9
74.73
40
4
Thule
-68.77
76.52
225
7
Hornsund
15.56
77
10
7
12
79
184
12
OPAL
-85.94
79.99
0
5
PEARL
-86.42
80.05
615
5
Bozeman
Ny Alesund
169
170
171
Fig. S1 – AOD observations at select AERONET sites across the 4 latitude bands used in this
172
study. Lower AOD observations are shown in darker red to highlight, along with the annual
173
average minimum AOD (solid black line) and the tropospheric and stratospheric background
174
inferred from the site elevation (red line). Tropical and higher latitude eruptions are shown as
175
vertical solid and dashed lines, respectively.
176
177
Fig. S2 – The annual average minimum AOD for AERONET sites with data prior to 2005 are
178
displayed relative to the elevation of the site. Sites are grouped into latitude bands and
179
regressions for each indicated on the figure. A constant minimum AOD of 0.03 is assumed for
180
the Arctic sites because of limited data (see supplemental text).
181
182
183
184
Fig. S3 - Aerosol Enhancement Factor (AEF) derived from minimum AOD observed at
185
AERONET sites in the Northern Hemisphere (NH) using a 90-day moving average (black line).
186
Individual sites are shown in grey and the multi-site mean in black. The AEF derived from
187
satellite observations of SAOD in the NH (Vernier et al., 2011) is shown (blue) and from Sato et
188
al. (orange). Solid and dashed vertical lines indicate tropical and mid-latitude eruptions,
189
respectively.
190
191
Fig. S4 - Estimated global radiative forcing is shown for AERONET (black). The forcing
192
uncertainty that results from the 1-σ uncertainty in the regression of elevation with minimum
193
AOD is shown in grey. The dashed line indicates the baseline forcing used in many climate
194
model studies to date, which includes no stratospheric aerosol after 2000.
195
196
197
Fig. S5 - Annual average SAOD from multiple lidar sites (indicated by symbol) above 15 km
198
(grey) and above tropopause (black) plotted against the SAOD derived from AERONET (a),
199
Sato et al. (b) and Vernier et al. (c). The error bars represent the AERONET uncertainty estimate.
200
Solid line is the 1:1 line and dotted lines are the 2:1 and 1:2 lines. Note: No comparison is made
201
between SAOD>15 km datasets and AERONET, and no comparison between Ny Alesund and
202
Vernier et al. because the satellite dataset ends at 50°N.
203