GMDGeoscientific Model DevelopmentGMDGeosci. Model Dev.1991-9603Copernicus PublicationsGöttingen, Germany10.5194/gmd-9-2701-2016The Model Intercomparison Project on the climatic response to
Volcanic forcing (VolMIP): experimental design and forcing
input data for CMIP6ZanchettinDavidedavide.zanchettin@unive.itKhodriMyriamTimmreckClaudiahttps://orcid.org/0000-0001-5355-0426TooheyMatthewhttps://orcid.org/0000-0002-7070-405XSchmidtAnjahttps://orcid.org/0000-0001-8759-2843GerberEdwin P.https://orcid.org/0000-0002-6010-6638HegerlGabrieleRobockAlanhttps://orcid.org/0000-0002-6319-5656PausataFrancesco S. R.BallWilliam T.https://orcid.org/0000-0002-1005-3670BauerSusanne E.https://orcid.org/0000-0001-7823-8690BekkiSlimanehttps://orcid.org/0000-0002-5538-0800DhomseSandip S.https://orcid.org/0000-0003-3854-5383LeGrandeAllegra N.MannGraham W.https://orcid.org/0000-0003-1746-2837MarshallLaurenMillsMichaelhttps://orcid.org/0000-0002-8054-1346MarchandMarionNiemeierUlrikehttps://orcid.org/0000-0003-0088-8364PoulainVirginieRozanovEugenehttps://orcid.org/0000-0003-0479-4488RubinoAngeloStenkeAndreahttps://orcid.org/0000-0002-5916-4013TsigaridisKostashttps://orcid.org/0000-0001-5328-819XTummonFionaDepartment of Environmental Sciences, Informatics and Statistics,
University of Venice, Mestre, ItalyIRD/IPSL/Laboratoire d'Océanographie et du Climat, Paris, FranceMax Planck Institute for Meteorology, Hamburg, GermanyGEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, GermanyInstitute for Climate and Atmospheric Science, School of Earth and
Environment, University of Leeds, Leeds, UKCourant Institute of Mathematical Sciences, New York University, New
York, NY, USASchool of Geosciences, University of Edinburgh, Edinburgh, UKDepartment of Environmental Sciences, Rutgers University, New
Brunswick, NJ, USADepartment of Meteorology, Stockholm University and Bolin Centre for
Climate Research, Stockholm, SwedenPMOD/WRC, Davos, SwitzerlandDepartment of
Environmental Systems Science, Institute for Atmospheric and Climate Science, ETH Zürich, Zürich, SwitzerlandNASA Goddard Institute for Space Studies and Center for Climate
Systems Research, Columbia University, New York, NY, USALATMOS/IPSL, UVSQ Université Paris-Saclay, UPMC, CNRS, Guyancourt, FranceNational Centre for Atmospheric Science, University of Leeds,
Leeds, UKAtmospheric Chemistry Division, National Center for Atmospheric
Research, Boulder, CO, USADavide Zanchettin (davide.zanchettin@unive.it)17August2016982701271930March20165April201628June201621July2016This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://gmd.copernicus.org/articles/9/2701/2016/gmd-9-2701-2016.htmlThe full text article is available as a PDF file from https://gmd.copernicus.org/articles/9/2701/2016/gmd-9-2701-2016.pdf
The enhancement of the stratospheric aerosol layer by
volcanic eruptions induces a complex set of responses causing global and
regional climate effects on a broad range of timescales. Uncertainties exist
regarding the climatic response to strong volcanic forcing identified in
coupled climate simulations that contributed to the fifth phase of the
Coupled Model Intercomparison Project (CMIP5). In order to better understand
the sources of these model diversities, the Model Intercomparison Project on
the climatic response to Volcanic forcing (VolMIP) has defined a coordinated
set of idealized volcanic perturbation experiments to be carried out in
alignment with the CMIP6 protocol. VolMIP provides a common stratospheric
aerosol data set for each experiment to minimize differences in the applied
volcanic forcing. It defines a set of initial conditions to assess how
internal climate variability contributes to determining the response. VolMIP
will assess to what extent volcanically forced responses of the coupled
ocean–atmosphere system are robustly simulated by state-of-the-art coupled
climate models and identify the causes that limit robust simulated behavior,
especially differences in the treatment of physical processes. This paper
illustrates the design of the idealized volcanic perturbation experiments in
the VolMIP protocol and describes the common aerosol forcing input data sets
to be used.
Introduction
Volcanic eruptions that eject substantial amounts of sulfur dioxide
(SO2) into the atmosphere have been one of the dominant natural causes
of externally forced annual to multidecadal climate variability during the
last millennium (Hegerl et al., 2003; Myhre et al., 2013; Schurer et al.,
2014). Significant advances have been made in recent years in our
understanding of the core microphysical, physical, and chemical processes
that determine the radiative forcing resulting from volcanic sulfur
emissions and the consequent dynamical responses of the coupled
ocean–atmosphere system (e.g., Timmreck, 2012). However, the fifth phase of
the Coupled Model Intercomparison Project (CMIP5) has demonstrated that
climate models' capability to accurately and robustly simulate observed and
reconstructed volcanically forced climate behavior remains poor.
For instance, the largest uncertainties in radiative forcings (Driscoll et
al., 2012) and in lower troposphere temperature trends (Santer et al., 2014)
from historical CMIP5 simulations occur during periods of strong volcanic
activity. CMIP5 models tend to overestimate the observed post-eruption
global surface cooling and subsequent warming (Marotzke and Forster, 2015),
although the discrepancy decreases when accounting for the post-eruption phase
of the El Niño–Southern Oscillation (ENSO) (Lehner et al., 2016).
Driscoll et al. (2012) and Charlton-Perez et al. (2013) found large
uncertainty across CMIP5 models concerning the average dynamical atmospheric
response during the first two post-eruption winters, especially the
post-eruption strengthening of the northern hemispheric (NH) winter polar vortex
and its tropospheric signature. Climate models reproduce the main features
of observed precipitation response to volcanic forcing but significantly
underestimate the magnitude of the regional responses in particular seasons
(Iles and Hegerl, 2014).
Volcanic events during the instrumental period are, however, few and of
limited magnitude, and their associated dynamical climatic response is very
noisy (e.g., Hegerl et al., 2011). Furthermore, there is inter-model
disagreement about post-eruption oceanic evolution, particularly concerning
the response of the thermohaline circulation (e.g., Mignot et al., 2011;
Hofer et al., 2011; Zanchettin et al., 2012; Ding et al., 2014). Substantial
uncertainties still exist about decadal-scale climate variability during
periods of strong volcanic forcing and in the role of the ocean in
determining the surface air temperature response to volcanic eruptions.
Climate-proxy-based reconstructions covering the last millennium are a major
source of information about how the climate system responds to volcanic
forcing (e.g., D'Arrigo et al., 2009; Corona et al., 2010; Gennaretti et al.,
2014). Recent studies have explored new reconstruction methods applied on
high-quality proxy records to produce more rigorous regional climate
reconstructions and allow for an improved evaluation of climate models
(e.g., Ortega et al., 2015; Luterbacher et al., 2016). However,
discrepancies exist between simulated and reconstructed climate variability
during periods of the last millennium characterized by strong volcanic
activity, concerning, for instance, the magnitude of post-eruption surface
cooling (e.g., Mann et al., 2012, 2013; Anchukaitis et al., 2012; Stoffel et
al., 2015; Luterbacher et al., 2016) and the interdecadal response to
volcanic clusters of tropical precipitation (Winter et al., 2015) and
large-scale modes of atmospheric variability (Zanchettin et al., 2015a).
The lack of robust behavior in climate simulations likely depends on various
reasons. First, inter-model spread can be caused by differences in the
models' characteristics, such as the spatial resolution, and the imposed
volcanic forcing. The latter stems from choices about the employed data set
describing climatically relevant parameters related to the eruption source
– especially the mass of emitted SO2 – and about the stratospheric
aerosol properties such as spatial extent of the cloud, optical depth, and
aerosol size distribution (e.g., Timmreck, 2012). As instrumental
observations of volcanic eruptions are limited, with the 1991 eruption of Mt.
Pinatubo being the best documented event (e.g., Minnis et al., 1993),
forcing characteristics must often be reconstructed based on indirect
evidence such as ice-core measurements (e.g., Devine et al., 1984; Sigl et
al., 2014). These reconstructions rely on a simplified hypothesis of scaling
between ice-core sulfate concentrations and aerosol optical depths based on
the relation observed for the 1991 eruption of Mt. Pinatubo (Crowley and
Unterman, 2013). The consideration of aerosol microphysical processes also
produces substantial inconsistencies between available volcanological
data sets (Timmreck, 2012). Furthermore, even when the same volcanic aerosol
forcing is used to force different models, these may generate different
radiative forcing due to the model-specific implementation of the volcanic
forcing (Timmreck, 2012; Toohey et al., 2014).
Uncertainty in radiative forcing and climatic response for the
early-19th-century eruptions. (a) Two estimates of annual-average
global aerosol optical depth (AOD) at 550 nm; (b) top-of-atmosphere
annual-average net clear-sky radiative flux anomalies for a multi-model
ensemble of last-millennium simulations (PMIP3; see: Braconnot et al., 2012);
(c) comparison between simulated (PMIP3, 11-year smoothing, colors)
and reconstructed (black line: mean; shading: 5th–95th percentile range)
Northern Hemisphere average summer temperature anomalies (relative to
1799–1808); (d) same as (c) but for a pre-PMIP3
single-model ensemble (ECHAM5/MPIOM; Zanchettin et al., 2013a, b).
Reconstructed data are the full raw calibration ensemble by Frank et
al. (2010).
The simulated climatic response to individual volcanic eruptions also
critically depends on the background climate, including the mean climate
state (Berdahl and Robock, 2013; Muthers et al., 2014, 2015), the ongoing
internal climate variability (e.g., Thomas et al., 2009; Pausata et al.,
2015a, 2016; Swingedouw et al., 2015; Zanchettin et al., 2013a; Lehner et al.,
2016), and the presence of additional forcing factors
such as variations in solar irradiance (Zanchettin et al., 2013a; Anet et
al., 2014). As a result, different models, forcing inputs, and internal
climate variability similarly contribute to simulation-ensemble spread. This
can be seen, for instance, by comparing hemispheric temperature evolution
from a multi-model ensemble and a single-model ensemble of last-millennium
simulations during the early 19th century (Fig. 1), a period characterized
by the close succession of two strong tropical volcanic eruptions in 1809
and 1815.
The individual impact of these sources of uncertainty can be hard to
distinguish in transient climate simulations. Therefore, the Model
Intercomparison Project on the climatic response to Volcanic forcing
(VolMIP) – an endorsed contribution to CMIP6 (Eyring et al., 2016, this
issue) – provides the basis for a coordinated multi-model assessment of
climate models' performances under strong volcanic forcing conditions. It
defines a set of idealized volcanic-perturbation experiments where volcanic
forcing – defined in terms of volcanic aerosol optical properties – is
well constrained across participating models. VolMIP will therefore assess
to what extent responses of the coupled ocean–atmosphere system to the same
applied strong volcanic forcing are robustly simulated across
state-of-the-art coupled climate models and identify the causes that limit
robust simulated behavior, especially differences in their treatment of
physical processes. Ensemble simulations sampling appropriate initial
conditions and using the same volcanic forcing data set accounting for
aerosol microphysical processes can help assess the signal-to-noise ratio
and reduce uncertainties regarding the magnitude of post-eruption surface
cooling (Stoffel et al., 2015). Careful sampling of initial climate
conditions and the opportunity to consider volcanic eruptions of different
strengths will allow VolMIP to better assess the relative role of internally
generated and externally forced climate variability during periods of strong
volcanic activity. VolMIP also contributes toward more reliable climate
models by helping to identify the origins and consequences of systematic
model biases affecting the dynamical climatic response to volcanic forcing.
As a consequence, VolMIP will improve our confidence in the attribution and
dynamical interpretation of reconstructed post-eruption regional features
and provide insights into regional climate predictability during periods of
strong volcanic forcing.
VolMIP experiments will provide context to CMIP6-DECK AMIP and “historical” simulations
(Eyring et al., 2016), the decadal climate prediction experiments of the
Decadal Climate Prediction Panel (DCPP) (Boer et al., 2016), and the
“past1000” simulations of the Paleoclimate Model Intercomparison Project (PMIP) (Kageyama et al., 2016) where
volcanic forcing is among the dominant sources of climate variability and
inter-model spread. The importance of VolMIP is enhanced as the
specification of the volcanic stratospheric aerosol for the CMIP6 historical experiment
is based on “time-dependent observations” (Eyring et al., 2016), and some
modeling groups may therefore perform the simulations using online
calculation of volcanic radiative forcing based on SO2 emissions.
This paper is organized as follows. First, in Sect. 2 we provide a general
description of the individual experiments included in the VolMIP protocol.
Then, Sect. 3 provides details about the volcanic forcing for each
experiment, including implementation and the forcing input data to be
employed, for which this paper also serves as a reference. We discuss the
limitations of VolMIP and potential follow-up research in Sect. 4, before
summarizing the most relevant aspects of this initiative in Sect. 5.
Experiments: rationale and general aspects
The VolMIP protocol consists of a set of idealized volcanic perturbation
experiments based on historical eruptions. In this context, “idealized”
means that the volcanic forcing is derived from radiation or source
parameters of documented eruptions but the experiments generally do not
include information about the actual climate conditions when these events
occurred. The experiments are designed as ensemble simulations, with sets of
initial climate states sampled from the CMIP6-DECK “piControl” (i.e., preindustrial
control) simulation describing unperturbed preindustrial climate conditions
(Eyring et al., 2016), unless specified otherwise.
VolMIP experiments are designed based on a multifold strategy. A first set
of experiments (“volc-pinatubo”) focuses on the systematical assessment of uncertainty and
inter-model differences in the seasonal-to-interannual climatic response to
an idealized 1991 Pinatubo-like eruption, chosen as representative of the
largest magnitude of volcanic events that occurred during the observational
period. volc-pinatubo experiments highlight the role of internal interannual variability
for volcanic events characterized by a rather low signal-to-noise ratio in
the response of global-average surface temperature. The short-term dynamical
response is sensitive to the particular structure of the applied forcing
(Toohey et al., 2014). Using carefully constructed forcing fields and
sufficiently large simulation ensembles, VolMIP allows us to investigate the
inter-model robustness of the short-term dynamical response to volcanic
forcing and elucidate the mechanisms through which volcanic forcing leads
to changes in atmospheric dynamics. The proposed set of volc-pinatubo experiments
includes sensitivity experiments designed to determine the different
contributions to such uncertainty that are due to the direct radiative
(i.e., surface cooling) and to the dynamical (i.e., stratospheric warming)
response.
A second set of experiments (“volc-long”) is designed to systematically investigate
inter-model differences in the long-term (up to the decadal timescale)
dynamical climatic response to volcanic eruptions that are characterized by a
high signal-to-noise ratio in the response of global-average surface
temperature. A third set of experiments (“volc-cluster”) is designed to investigate the
climatic response to a close succession of strong volcanic eruptions. The
main goal of volc-long and volc-cluster experiments is to assess how volcanic perturbation signals
propagate within the simulated climates, e.g., into the subsurface ocean,
the associated determinant processes, and their representation across models.
The VolMIP protocol defines criteria for sampling desired initial conditions
whenever this is necessary to ensure comparability across different climate
models. Desired initial conditions and hence ensemble size are determined
based on the state of dominant modes of climate variability, which are
specifically defined for each experiment. The ensemble size must be
sufficiently large to account for the range of climate variability
concomitantly depicted by such modes. As a general rule, three
initialization states are determined for each given mode based on an index
describing its temporal evolution. Specifically, the predetermined ranges
for the sampling are: the lower tercile (i.e., the range of values between
the minimum and the 33rd percentile) for the negative/cold state, the
mid-tercile (i.e., the range of values between the 33rd and 66th
percentiles) for the neutral state, and the upper tercile (i.e., the range
of values between the 66th percentile and the maximum) for the
positive/warm state. If n modes are sampled concomitantly, this yields an
ensemble with 3n members. For instance, in the case of two modes, an
ensemble of at least nine simulations is requested. The choice of the
climate modes to be considered for initialization essentially depends on the
timescales of interest: seasonal to interannual modes for volc-pinatubo experiments and
interannual and decadal modes for volc-long experiments (selection of initialization
states is less important for volc-cluster experiments). The sampled years refer to the
second integration year of the VolMIP experiment, when the volcanic forcing
is generally strongest. Therefore, if, for instance, year Y of the control
integration matches the desired conditions for the sampling, then the
corresponding VolMIP simulation should start with restart data from
year Y-1
of the control, for the day of the year specified for the experiment.
Restart files from piControl must be accordingly selected and documented in the
metadata of each simulation. If no restart data are available for the day of
the year when the experiment starts, the control simulation must be re-run
based on the first (backward in time) available restart file until the start
date of the VolMIP experiment. All experiments except the decadal prediction
experiment (Sect. 2.1.4) and the millennium cluster experiment (Sect. 2.4.4) maintain the same constant boundary forcing as the piControl integration,
except for the volcanic forcing.
Some experiments are designed in cooperation with the Dynamics and
Variability of the Stratosphere–Troposphere System Model Intercomparison Project (DynVarMIP) (Gerber
and Manzini, 2016, this issue). DynVarMIP defines requirements for
diagnosing the atmospheric circulation and variability in the context of
CMIP6. DynVarMIP diagnostics include a refinement of the vertical resolution
of standard variables archived as daily and monthly means, zonal mean
diagnostics focused on the transport and exchange of momentum within the
atmosphere and between the atmosphere and surface, and zonal mean
diagnostics describing the interaction between radiation, moisture, and the
circulation. For a detailed description of these diagnostics and the output
format requested by DynVarMIP see Gerber and Manzini (2016).
Illustrating the dominant processes linking volcanic eruptions and
climatic response, with an overview of VolMIP experiments: 1 is volc-long-eq; 2 is
volc-pinatubo-full; 3 is volc-pinatubo-surf; 4 is volc-pinatubo-strat; 5 is
volc-long-hlN/-hlS; 6 is volc-cluster-ctrl/-mill/-21C; 7 is
volc-pinatubo-slab;
8 is volc-pinatubo-ini. The red box encompasses the processes related to the
climatic response to volcanic forcing that are accounted for in VolMIP; the
green box encompasses the processes regarding volcanic forcing that are
neglected by VolMIP.
Tier 1 VolMIP experiments.
NameDescriptionParent experiment, start dateEns. sizeYears per simulation (minimum)Total yearsGaps of knowledge being addressed with this experimentvolc-long-eqIdealized equatorial eruption corresponding to an initial emission of 56.2 Tg of SO2. The eruption magnitude corresponds to recent estimates for the 1815 Tambora eruption (Sigl et al., 2015), the largest tropical eruption of the last 5 centuries, which was linked to the so-called “year without a summer” in 1816.piControl, 1 April920180Uncertainty in the climatic response to strong volcanic eruptions, with focus on coupled ocean–atmosphere feedbacks and interannual-to-decadal global as well as regional responses. The mismatch between reconstructed and simulated climatic responses to historical strong volcanic eruptions, with focus on the role of simulated background internal climate variability.volc-pinatubo-full1991 Pinatubo forcing as used in the CMIP6 historical simulations. Requires special diagnostics of radiative and latent heating rates. A large number of ensemble members are required to address internal atmospheric variability.piControl, 1 June25375Uncertainty in the climatic response to strong volcanic eruptions with focus on short-term response. Robustness of volcanic impacts on Northern Hemisphere's winter climate and of associated dynamics.volc-pinatubo-surfAs volc-pinatubo-full but with prescribed perturbation to the shortwave flux to mimic the attenuation of solar radiation by volcanic aerosols.piControl, 1 June25375Mechanism(s) underlying the dynamical atmospheric response to large volcanic eruptions, in particular in Northern Hemisphere's winters. The experiment considers only the effect of volcanically induced surface cooling. Complimentary experiment to volc-pinatubo-strat.volc-pinatubo-stratAs volc-pinatubo-full but with prescribed perturbation to the total (LW + SW) radiative heating rates.piControl 1 June25375Mechanism(s) underlying the dynamical atmospheric response to large volcanic eruptions, in particular in Northern Hemisphere's winter. The experiment considers only the effect of volcanically induced stratospheric heating. Complimentary experiment to volc-pinatubo-surf.
volc is volcano; long is long-term simulation; pinatubo is short-term
simulation of the 1991 Pinatubo eruption; eq is Equator; full is full-forcing simulation; surf is shortwave
forcing only; strat is stratospheric thermal forcing only.
Tier 2 VolMIP experiments.
NameDescriptionParent experiment, start dateEns. sizeYears per simulationTotal yearsGaps of knowledge being addressed with this experimentvolc-long-hlNIdealized northern hemispheric high-latitude eruption emitting 28.1 Tg of SO2.piControl 1 April920180Uncertainty in climatic response to strong high-latitude volcanic eruptions (focus on coupled ocean–atmosphere). Outstanding questions about the magnitude of the climatic impact of high-latitude eruptions.volc-cluster-ctrlEarly-19th-century cluster of strong tropical volcanic eruptions, including the 1809 event of unknown location and the 1815 Tambora and 1835 Cosigüina eruptions.piControl 1 January1809350150Uncertainty in the multi-decadal climatic response to strong volcanic eruptions (focus on long-term climatic implications). Contribution of volcanic forcing to the climate of the early 19th century, the coldest period in the past 500 years. Discrepancies between simulated and reconstructed climates of the early 19th century.
volc is volcano; long is long-term simulation; hlN is Northern Hemisphere
high latitude; ctrl is initial state from control simulation.
An overview of the experimental design of the proposed experiments is
provided in Tables 1, 2, and 3, where they are summarized according to their
prioritization: Tier 1 experiments are mandatory; Tier 2 and Tier 3
experiments have decreasing priority. The experiments are individually
described in the following subsections. Figure 2 sketches how the different
experiments included in CMIP6 tackle different aspects of the climatic response to volcanic forcing. The codes for the naming conventions of the
experiments are in Tables 1–3.
VolMIP has defined a new group of variables (volcanic instantaneous
radiative forcing, or VIRF; see Table 4), which includes additional
variables that were not in the CMIP5 data request and are necessary to
generate the volcanic forcing for the “volc-pinatubo-surf”/“strat” experiments (see Sect. 3.3). In
particular, all VIRF diagnostics are instantaneous 6 h data, so some
interpolation in time may be required.
volc-pinatubovolc-pinatubo-full
Tier 1 experiment based on a large ensemble of short-term “Pinatubo”
climate simulations aimed at accurately estimating simulated responses to
volcanic forcing that may be comparable to the amplitude of internal
interannual climate variability (Table 1). Initialization is based on
equally distributed predefined states of ENSO (cold/neutral/warm states) and
of the North Atlantic Oscillation (NAO, negative/neutral/positive states).
Sampling of an eastern phase of the Quasi-Biennial Oscillation (QBO), as
observed after the 1991 Pinatubo eruption, is preferred for those models
that spontaneously generate such mode of stratospheric variability. VIRF
diagnostics must be calculated for this experiment for the whole integration
and for all ensemble members, as these are required for the
“volc-pinatubo-strat”/“surf” experiments (see Sect. 2.1.2). For models participating in DynVarMIP,
DynVarMIP diagnostics shall be calculated for all simulations and for the
whole integration period. A minimum length of integration of 3 years is
requested.
The recommended ENSO index is the NH winter (DJF, with
January as reference for the year) Nino3.4 sea-surface temperature index,
defined as the spatially averaged, winter-average sea-surface temperature
over the region bounded by 120–170∘ W and
5∘ S–5∘ N. The recommended NAO index is calculated
based on the latitude–longitude two-box method by Stephenson et al. (2006)
applied on Z500 data, i.e., as the pressure difference between spatial averages
over (20–55∘ N; 90∘ W–60∘ E)
and (55–90∘ N; 90∘ W–60∘ E).
volc-pinatubo-surf and volc-pinatubo-strat
Tier 1 simulations aimed at investigating the mechanism(s) connecting
volcanic forcing and short-term climate anomalies (Table 1). These
experiments aim to disentangle the dynamical responses to the two primary
thermodynamic consequences of aerosol forcing: stratospheric heating
(volc-pinatubo-strat) and surface cooling (volc-pinatubo-surf). Both experiments are built upon
“volc-pinatubo-full” and use the VIRF diagnostics calculated from the different realizations of
this experiment. Integration length, ensemble size, and restart files are the
same as for volc-pinatubo-full. For models participating in DynVarMIP, DynVarMIP diagnostics
shall be calculated for both experiments, for all simulations and for the
whole integration period.
Tier 3 VolMIP experiments.
NameDescriptionParent experiment, start dateEns. sizeYears per simulationTotal yearsGaps of knowledge being addressed with this experimentcontrol-slabSlab ocean control run, necessary for volc-pinatubo-slab–13030–volc-pinatubo-slabAs volc-pinatubo-full but with a slab oceancontrol-slab25375Effects of volcanic eruptions on ENSO dynamics.volc-pinatubo-ini/ DCPP C3.4As volc-pinatubo-full but as decadal prediction runs joint experiment with DCPP. Forcing input and implementation of the forcing fully comply with the VolMIP protocol.2015 (initialization date depends on the system)10(5)550Influence of large volcanic eruptions on future climate. Influence of large volcanic eruptions on seasonal and decadal climate predictabilityvolc-cluster-millParallel experiment to volc-cluster-ctrl but with initial conditions taken from last-millennium simulation to account for the effects of a more realistic history of past natural forcing.past1000, 1 January 18093(1)69207Contribution of volcanic forcing to the climate of the early 19th century, the coldest period in the past 500 years. Discrepancies between simulated and reconstructed climates of the early 19th century. Effect of history of volcanic forcing on the response to volcanic eruptions.volc-cluster-21CParallel experiment to volc-cluster-ctrl, using restart files from the end of the historical simulation instead of from piControl, and boundary conditions from the 21st-century SSP2-4.5 scenario experiment of ScenarioMIP.historical, 1 January 20153(1)85255Contribution of volcanic forcing uncertainty to uncertainty in future climate projections Long-term climatic response to volcanic eruptions under warm background climate conditionsvolc-long-hlSIdealized southern hemispheric high-latitude eruption emitting 28.1 Tg of SO2.piControl 1 April920180Uncertainty in climatic response to strong high-latitude volcanic eruptions (focus on coupled ocean–atmosphere). Outstanding questions about the magnitude of the climatic impact of high-latitude eruptions.
volc is volcano; long is long-term simulation; pinatubo is short-term
simulation of the 1991 Pinatubo eruption; eq is Equator; slab is slab
ocean simulation; ini is simulation initialized for decadal prediction;
mill is initial conditions from full forcing transient simulation of the
last millennium; 21C is 21st-century scenario experiment; hlS is southern hemispheric high-latitude
eruption.
volc-pinatubo-slab
Non-mandatory slab-ocean experiment, which is proposed to clarify the role
of coupled atmosphere–ocean processes (most prominently linked to ENSO) in
determining the dynamical response (Table 3). A reference simulation
(“control-slab”) shall be set up using the spatially nonuniform annual-average mixed
layer depth climatology of the coupled model. control-slab should include a minimum of
20-year spin-up followed by a 10-year control integration. A minimum length
of integration of 3 years and at least 25 ensemble members are requested
for “volc-pinatubo-slab”. VIRF diagnostics shall be calculated for all simulations and for the
whole integration period. For models participating in DynVarMIP, DynVarMIP
diagnostics shall be calculated for all simulations and for the whole
integration period.
volc-pinatubo-ini
Non-mandatory experiment to address the impact of volcanic forcing on
seasonal and decadal climate predictability (Table 3). The experiment will
address the climatic implication of a future Pinatubo-like eruption. The
experiment is designed in cooperation with DCPP and is the same as DCPP
experiment C3.4 (Boer et al., 2016). It complies with the VolMIP protocol
about the forcing and its implementation. The experiment is initialized on
1 November 2015 or on any other date in November or December for which
initialized hindcasts are available (depending on the modeling center). Ten
decadal simulations are requested for this experiment. Calculation of
DynVarMIP diagnostics is recommended for the first 3 years of
integration for at least one realization, but preferably for all of them.
DCPP diagnostics must be calculated for all realizations and for the whole
integration period.
volc-longvolc-long-eq
Tier 1 experiment designed to understand the long-term response to a single
volcanic eruption with radiative forcing comparable to that estimated for
the 1815 eruption of Mt. Tambora, Indonesia (e.g., Oppenheimer, 2003) (Table 1). A recent review paper (Raible et al., 2016) describes the 1815 Tambora
eruption as a test case for high impacts on the Earth system. Initialization
spans cold/neutral/warm states of ENSO and weak/neutral/strong states of the
Atlantic Meridional Overturning Circulation (AMOC), resulting in a nine-member
ensemble. A minimum length of integration of 20 years is requested to cover
the typical duration of the simulated initial post-eruption AMOC anomaly
(e.g., Zanchettin et al., 2012). Longer integration times (50 years) are
recommended to capture the later AMOC evolution (Swingedouw et al., 2015;
Pausata et al., 2015b) and related climate anomalies. The recommended AMOC
index is defined as the annual-average time series of the maximum value of
the zonally integrated meridional stream function in the North Atlantic Ocean
in the latitude band 20–60∘ N. VIRF diagnostics shall
be calculated for the first 3 years of integration and for just one
realization. For models participating in DynVarMIP, DynVarMIP diagnostics
shall be calculated for the first 3 years of integration and for all
realizations.
volc-long-hlN and volc-long-hlS
Non-mandatory experiments that apply the same approach as “volc-long-eq” and allow extending the
investigation to the case of idealized strong high-latitude volcanic
eruptions (Tables 2 and 3).
“Volc-long-hlN” and “volc-long-hlS” are designed as a NH and a southern
hemispheric (SH) extratropical eruption, respectively, both with SO2
injection equal to half the total amount injected for the volc-long-eq experiment. This
choice was based on the assumption that for an equatorial eruption the
injected mass is roughly evenly distributed between the two hemispheres,
increasing comparability between volc-long-eq and volc-long-hlN/hlS as both should yield similar forcing
over the eruption's hemisphere (but see Sect. 3.3). The initialization
procedure and required integration length are the same as for
volc-long-eq. Both experiments are expected to contribute to open questions about the
magnitude of the climatic impact of high-latitude eruptions, especially
concerning the interhemispheric response. VIRF diagnostics shall be
calculated for the first 3 years of integration and for just one
realization. For models participating in DynVarMIP, DynVarMIP diagnostics
shall be calculated for the first 3 years of integration, for all
realizations.
The eruption strength is about 4 times stronger than that estimated for the
Mt. Katmai/Novarupta eruption in 1912 (Oman et al., 2005). The eruption used
in volc-long-hlN should not be considered directly comparable to the 1783–84 Laki
eruption – one of the strongest high-latitude eruptions that occurred in
historical times – since the experiment does not try to reproduce the very
specific characteristics of Laki, including multistage releases of large
SO2 mass paced at short temporal intervals (e.g., Thordarson and Self,
2003; Schmidt et al., 2010; Pausata et al., 2015b).
volc-long-hlN (Tier 2) has a higher priority than volc-long-hlS (Tier 3).
volc-clustervolc-cluster-ctrl
This non-mandatory experiment investigates the climatic response to a close
succession of strong volcanic eruptions, so-called “volcanic cluster”
(Table 2). The experiment is motivated by the large uncertainties in the
multidecadal and longer-term climate repercussions of multiple eruptions,
including volcanic double events (e.g., Toohey et al., 2016b) and prolonged
periods of strong volcanic activity (e.g., Miller et al., 2012; Schleussner
and Feulner, 2013; Zanchettin et al., 2013a; Moreno-Chamarro et al., 2016).
The proposed experiment is designed to realistically reproduce the volcanic
forcing generated by the early-19th-century volcanic cluster, which included
the 1809 eruption of unknown location and the 1815 Tambora and 1835
Cosigüina eruptions. The early 19th century is the coldest period in the
past 500 years (Cole-Dai et al., 2009) and therefore of special interest for
interdecadal climate variability (Zanchettin et al., 2015a; Winter et al.,
2015). In addition, long-term repercussions may be relevant for the
initialization of CMIP6 historical simulations.
At least an ensemble of three 50-year simulations is requested. Due to
the long-term focus of the experiment, selection of initialization states is
of second-order importance. Nonetheless, it is recommended to sample initial
states pacing them at a minimum 50-year intervals. Initial states shall be
sampled from the piControl for consistency with the volc-long experiments.
volc-cluster-mill
A parallel experiment to “volc-cluster-ctrl” using restart files from PMIP-past1000 instead of from
piControl (see Table 3). Starting from a climate state that experienced realistic
past natural forcing, this experiment allows us to explore the sensitivity of
the ocean response to the initial state (e.g., Gregory, 2010; Zanchettin et
al., 2013a). “volc-cluster-mill” is more suitable for a direct comparison with early
instrumental data and paleoclimate reconstructions and allows one to
explore the role of ocean initial conditions on sea ice response, ocean
response, and surface temperature response by comparison with
volc-cluster-ctrl.
This non-mandatory experiment requires that at least one PMIP-past1000 realization
has been performed. One simulation is requested, but an ensemble of three
simulations is recommended. The proper experiment starts in the year 1809 as
volc-cluster-ctrl. However, the simulation must be initialized in 1 January 1790 to
avoid interferences due to the decadal drop of solar activity associated
with the Dalton Minimum. Hence, the experiment proper lasts 50 years as
volc-cluster-ctrl, but a total of 69 years for each ensemble member are actually requested.
Different members of the volc-cluster-mill ensemble can be obtained by either using restart
files from different ensemble members of PMIP-past1000, if available, or through
introducing small perturbations to the same restart file. All external
forcings, except volcanic forcing, are set as a perpetual repetition of the
year 1790 for the full duration of the experiment.
volc-cluster-21C
A parallel experiment to volc-cluster-ctrl using restart files from the end of the
historical simulation instead of from piControl, and boundary conditions from the
21st-century SSP2-4.5 scenario experiment of ScenarioMIP (O'Neill et al., 2016),
except for volcanic forcing during the volcanic cluster period (see Table 3). The experiment is designed to explore the climatic response to volcanic
eruptions under warmer background conditions compared to preindustrial
climates and to investigate the potential uncertainties in future climate
projections due to volcanic activity. The experiment uses the same volcanic
forcing used in volc-cluster-ctrl/mill, with the first eruption of the cluster (i.e., the 1809
eruption) placed on the year 2015. Simulations shall be run to the end of the
21st century for full comparability with the corresponding scenario
simulation. At the end of the volcanic cluster, volcanic forcing input shall
be kept constant at the same constant value prescribed for the piControl simulation
for consistency with the SSP2-4.5 scenario experiment.
We encourage modeling groups that are interested in both VolMIP and
ScenarioMIP to also coordinate experiments where the same volcanic cluster
is placed later on in the scenario integration (e.g., with the first
eruption in the year 2050).
Definition of new variables requested by VolMIP.
These have not been previously used in CMIP5, CCMI, CORDEX, or SPECS. Shape
is defined as time (T), longitude (X), latitude (Y), and height (Z). TOA is top of atmosphere.
Short nameStandard nameUnitsDescription/commentsShapeLevelsTimeaod550volso4stratosphere optical thickness due to volcanic aerosol particlesaerosol optical thickness at 550 nm due to stratospheric volcanic aerosolsXYT1daily meanzmswaerotendency of air temperature due to shortwave heating from volcanic aerosol particlesK s-1shortwave heating rate due to volcanic aerosols to be diagnosed through double radiation call, zonal average values requiredYZTallinstantaneouszmlwaerotendency of air temperature due to longwave heating from volcanic aerosol particlesK s-1longwave heating rate due to volcanic aerosols to be diagnosed through double radiation call, zonal average values requiredYZTallinstantaneousswsffluxaerosurface downwelling shortwave flux in air due to volcanic aerosolsW m-2downwelling shortwave flux due to volcanic aerosols at the surface to be diagnosed through double radiation callXYT1instantaneouslwsffluxaerosurface downwelling longwave flux in air due to volcanic aerosolsW m-2downwelling longwave flux due to volcanic aerosols at the surface to be diagnosed through double radiation callXYT1instantaneousswtoafluxaerocsTOA outgoing shortwave flux due to volcanic aerosols assuming clear skyW m-2downwelling shortwave flux due to volcanic aerosols at TOA under clear sky to be diagnosed through double radiation callXYT1instantaneouslwtoafluxaerocsTOA outgoing longwave flux due to volcanic aerosols assuming clear skyW m-2downwelling longwave flux due to volcanic aerosols at TOA under clear sky to be diagnosed through double radiation callXYT1instantaneous
Protocol for the chemistry–climate model experiment to
assess volcanic forcing uncertainty for the
volc-long-eq experiment.
SO2 emissionEruption lengthLatitudeQBO phase at time of eruptionSO2 height injectionSSTOther radiative forcingDurationEns. size60 Tg SO224 hCentered at the EquatorEasterly phase (as for Pinatubo and El Chichón)Same as Pinatubo; 100 % of the mass between 22 and 26 km, increasing linearly with height from zero at 22 to max at 24 km, and then decreasing linearly to zero at 26 km.Climatological from preindustrial control runPreindustrial CO2, other greenhouse gases, tropospheric aerosols (and O3 if specified)5-year long5 membersForcingImplementation: general aspects
VolMIP identifies a volcanic forcing data set for each experiment included in
the protocol. The forcing parameters either are provided in terms of aerosol
optical properties and distributions in time and space, as for the case when
available data were identified as consensus reference, or can be calculated
based on the tool and guidelines described in the protocol. The latter is
the case for the volc-long and volc-cluster experiments that use forcing input data specifically
generated for VolMIP.
In addition, the implementation of the forcing (e.g., spectral
interpolation) is constrained to ensure that the imposed radiative forcing
is consistent across the participating models. Surface albedo changes due to
tephra deposition and indirect cloud radiative effects are neglected in all
the experiments.
volc-pinatubo
volc-pinatubo-full will use the CMIP6 stratospheric aerosol data set (Thomason et al., 2016)
for the volcanic forcing of the 1991 Pinatubo eruption, which is compiled
for the CMIP6 historical experiment. Specifically, the reference stratospheric aerosol
forcing data set for the CMIP6 historical experiment includes model-specific data for
aerosol extinction, single scattering albedo, and asymmetry factor, all as a
function of latitude, height, and the spectral bands of the model (see
ftp://iacftp.ethz.ch/pub_read/luo/CMIP6 and
https://pcmdi.llnl.gov/projects/input4mips). We recommend following the same
protocol for implementation of the forcing in the historical experiment and therefore
recommend to replace forcing input data below the model tropopause by
climatological or other values of tropospheric aerosol used by the models.
volc-pinatubo-surf and volc-pinatubo-strat will not account for forcing based on imposed aerosol optical
properties as is the usual approach in VolMIP. Instead, they will use output
from the corresponding volc-pinatubo-full experiment. Specifically, volc-pinatubo-surf will specify a prescribed
perturbation to the shortwave flux to mimic the attenuation of solar
radiation by volcanic aerosols, and therefore the cooling of the surface.
The goal is to isolate the impact of shortwave reflection from the impact of
aerosol heating in the stratosphere. The changes must be prescribed at the
top of atmosphere under clear sky conditions (variable swtoafluxaerocs
of VIRF). Similarly, volc-pinatubo-strat will specify a prescribed perturbation to the total
(longwave plus shortwave) radiative heating rates, seeking to mimic the
local impact of volcanic aerosol (variables zmlwaero and zmswaero of VIRF).
This must be implemented by adding an additional temperature tendency.
VolMIP does not enforce the same perturbation across all models in volc-pinatubo-surf and
volc-pinatubo-strat, as for both experiments priority is given to the consistency with the
corresponding volc-pinatubo-full experiment.
volc-long and volc-cluster
These experiments are based on pre-industrial volcanic events for which no
direct observation is available. VolMIP recognizes the need to overcome the
uncertainties and the limitations of currently available volcanic forcing
data sets for the pre-industrial period (see Fig. 1a), which poses the need
to identify a single, consensus forcing data set for each one of the
volc-long and volc-cluster experiments. Therefore, for the volc-long-eq experiment, coordinated simulations
of the 1815 eruption of Mt. Tambora (see Table 5) were performed with
different climate models including modules for stratospheric aerosol
microphysics and chemistry (chemistry–climate models). The imposed SO2
injection of 60 Tg at the Equator used in these simulations is deduced from
reanalysis of bipolar ice-core data used in recent volcanic forcing
reconstructions (Stoffel et al., 2015; Gao et al., 2008) and calculations
based on geological data (Self et al., 2004). The easterly QBO phase and
altitude of injection are based on satellite and lidar observations of QBO,
SO2, and sulfate after the Pinatubo eruption (McCormick and Veiga,
1992; Read et al., 1993; Herzog and Graf, 2010). The results show large
uncertainties in the estimate of volcanic forcing parameters derived from
different state-of-the-art chemistry–climate models perturbed with the same
sulfur injections (Fig. 3a). How these results are traced back to the
different treatment of aerosol microphysics and climate physical processes
in the different models is the subject of a dedicated study. Here, we only
conclude that existing uncertainties prevent the identification, within the
time constraints of the CMIP6 schedule, of a single consensus forcing
estimate for a given volcanic eruption based on a multi-model ensemble with
current chemistry–climate models.
Therefore, VolMIP proposes for the volc-long and volc-cluster experiments forcing data sets
constructed with the Easy Volcanic Aerosol (EVA) module version 1.0 (Toohey
et al., 2016a). EVA provides an analytic representation of volcanic
stratospheric aerosol forcing, prescribing the aerosol's radiative
properties and primary modes of spatial and temporal variability. It creates
volcanic forcing from a given eruption sulfur injection and latitude with an
idealized spatial and temporal structure, constructed so as to produce good
agreement with observations of the aerosol evolution following the 1991
Pinatubo eruption. Scaling to larger eruption magnitudes is performed in a
manner similar to the forcing reconstruction of Crowley and Unterman (2013).
EVA is also used to construct the volcanic forcing data set used for the
PMIP-past1000 experiment (Kageyama et al., 2016). This augments the comparability
between PMIP and VolMIP results concerning those eruptions that are featured
by both MIPs. The EVA module outputs data resolved for given latitudes,
heights, and wavelength bands. It therefore is an improvement compared to
previously available volcanic forcing data sets for the pre-observational
period. The forcing sets produced with EVA have the same format as the CMIP6
standard forcing files, i.e., aerosol extinction, single scattering albedo,
and asymmetry factor, all as a function of latitude, height, and the spectral
bands of the model. The aerosol forcing produced by EVA decays to 0
around the tropopause. Therefore, differently from the forcing used in the
volc-pinatubo experiments, no clipping of the forcing is necessary at the tropopause for
experiments using EVA forcing. Toohey et al. (2016a) provide technical
details about EVA.
(a) Uncertainty in estimates of radiative forcing
parameters for the 1815 eruption of Mt. Tambora: global-average aerosol
optical depth (AOD) in the visible band from an ensemble of simulations with
chemistry–climate models forced with a 60 Tg SO2 equatorial eruption,
from the Easy Volcanic Aerosol (EVA) module with 56.2 Tg SO2 equatorial
eruptions (magenta thick dashed line), from Stoffel et al. (2015), from
Crowley and Unterman (2013), and from Gao et al. (2008, aligned so that the
eruption starts on April 1815). The estimate for the Pinatubo eruption as
used in the CMIP6 historical experiment is also reported for
comparison. (b) Time–latitude plot of the AOD in the visible band
produced by EVA for a 56.2 Tg SO2 equatorial eruption, illustrating the
consensus forcing for the volc-long-eq experiment. The black
triangle shows latitudinal position and timing of the eruption. Chemistry–climate models are CESM (WACCM) (Mills et al., 2016), MAECHAM5-HAM (Niemeier
et al., 2009), SOCOL (Sheng et al., 2015), UM-UKCA (Dhomse et al., 2014), and
CAMB-UPMC-M2D (Bekki, 1995; Bekki et al., 1996). For models producing an
ensemble of simulations, the line and shading are the ensemble mean and
ensemble standard deviation respectively.
VolMIP requests that all modeling groups use EVA to generate the specific
forcing input data set for their model, using the same sulfur emission
estimates to be specified for use in the PMIP-past1000 experiment. Figure 3 provides
an overview of the EVA forcing for an estimated SO2 injection for the
1815 Tambora eruption of 56.2 Tg to be used in volc-long-eq and volc-cluster experiments. volc-cluster experiments also include all eruptions
represented in the PMIP-past1000 experiment for the overlapping period.
Consensus forcing for the volc-long-hlN experiment.
(a) Northern Hemisphere average aerosol optical depth (AOD) at
550 nm produced by the Easy Volcanic Aerosol (EVA) module for a 56.2 Tg
equatorial eruption (volc-long-eq, black line) and for a 28.1 Tg
SO2 Northern Hemisphere extratropical eruption (volc-long-hlN,
blue line). (b) Time–latitude plots of the AOD at 550 nm from EVA
for the 28.1 Tg SO2 Northern Hemisphere extratropical eruption. The
black triangle shows latitudinal position and timing of the eruption.
The reference SO2 emission for the volc-long-hlN/hlS experiments is equal to one-half
the Tambora value. The evolution of aerosol optical depth (AOD) by EVA for a
NH high-latitude injection of 28.1 Tg of SO2 is illustrated in Fig. 4. The NH average AOD for the volc-long-hlN and volc-long-eq experiments are quite similar in
magnitude and temporal structure. Differences occur mainly due to the
seasonal dependence of the tropical-to-extratropical transport parameterized
in EVA. The reduced stratospheric transport into the NH in
the summer months after the April eruptions leads to a time lag in the peak
NH mean AODs for volc-long-eq compared to volc-long-hlN. It also leads to generally somewhat less
aerosol transported to the Northern compared to the Southern Hemisphere for
volc-long-eq, which explains the lower peak AOD for this experiment than for
volc-long-hlN. Similar considerations stand for volc-long-hlS.
Follow-up research and synergies with other modeling activities
We expect the VolMIP experiments not only to generate broad interest within
the climate modeling community but also to stimulate research across many
different branches of climate sciences.
Cooperation between VolMIP and other ongoing climate modeling initiatives
and MIPs increases VolMIP's relevance for climate model evaluation. In
particular, synergies between VolMIP and the WCRP/SPARC Stratospheric Sulfur
and its Role in Climate (SSiRC) coordinated multi-model initiative (Timmreck
et al., 2016b) as well as between VolMIP and the Radiative Forcing Model Intercomparison Project
(RFMIP) (Pincus et al., 2016, this issue) will help to building a scientific
basis to distinguish between differences in volcanic radiative forcing data
and differences in climate model response to volcanic forcing. VolMIP
provides a well-defined set of forcing parameters in terms of aerosol
optical properties and is thus complementary to SSiRC, which uses global
aerosol models to investigate radiative forcing uncertainties associated
with given SO2 emissions. Precise quantification of the forcing to
which models are subject is central for both RFMIP and VolMIP: RFMIP has
planned transient volcanic and solar forcing experiments with fixed
preindustrial sea-surface temperature to diagnose volcanic and solar
effective forcing, instantaneous forcing, and adjustments, which is
complementary to the volc-pinatubo experiments of VolMIP.
VolMIP has synergies with the Geoengineering Model Intercomparison Project
(GeoMIP; Kravitz et al., 2015), which includes proposals to simulate a
long-duration stratospheric aerosol cloud to counteract global warming.
Furthermore, PMIP and VolMIP provide complementary perspectives on one of
the most important and less understood factors affecting climate variability
during the last millennium. Specifically, VolMIP systematically assesses
uncertainties in the climatic response to volcanic forcing associated with
different initial conditions and structural model differences. In contrast,
the PMIP-past1000 experiment describes the climatic response to volcanic forcing in
long transient simulations where related uncertainties are due to the
reconstruction of past volcanic forcing, the implementation of volcanic
forcing within the models, initial conditions, the presence and strength of
additional forcings, and structural model differences. The
“past1000_volc_cluster” experiment of PMIP consists of an ensemble of full-forcing simulations
covering the early 19th century whose design is aligned with VolMIP
volc-cluster experiments (Jungclaus et al., 2016, this issue). This hierarchy of
volcanic cluster experiments will allow us to investigate the interactions
between different natural forcing factors and the role of background climate
conditions during one of coldest periods of the last millennium, when
discrepancies exist between information from available climate simulations
and reconstructions (e.g., Winter et al., 2015; Zanchettin et al., 2015a).
Modeling groups who participate in both VolMIP and PMIP are encouraged to
output the VIRF diagnostics for the following tropical eruptions simulated
in the past1000 experiment: 1257 Samalas, 1453 Kuwae, 1600 Huaynaputina, 1809
Unidentified, and 1815 Tambora. VIRF diagnostics will be calculated for a
period of 5 years starting from the eruption year and will be useful for
future studies to expand the investigation based on volc-pinatubo-strat and
volc-pinatubo-surf.
VolMIP and the Detection and Attribution Model Intercomparison Project (DAMIP) (Gillet et al., 2016, this issue)
share the CMIP6 science theme of characterizing forcing. The experiments
“histALL”, “histNAT”, “histVLC”, and “histALL_estAER2” of DAMIP include the 1991 Pinatubo eruption within transient
climate situations and therefore provide context to the volc-pinatubo set of VolMIP
experiments. The experiment “volc-cluster-21C” is built on and complements the SSP2-4.5
scenario experiment of ScenarioMIP.
VolMIP and DCPP are working closely together on the impact of volcanic
eruptions on seasonal and decadal predictions, and they have designed a common
experiment (“volc-pinatubo-ini” and the DCPP experiment C3.4 are different labels for the same
experiment). DynVarMIP puts a particular emphasis on the two-way coupling
between the troposphere and the stratosphere, and it is therefore deeply
involved in the design and analysis of the volc-pinatubo-full/strat/surf experiments.
We envisage follow-up research stimulated by VolMIP's links to the Grand
Challenges of the World Climate Research Program (Brasseur and Carlson,
2015) focusing on the following.
“Clouds, circulation, and climate sensitivity,” in particular through
improved characterization of volcanic forcing and improved understanding of how
the hydrological cycle and the large-scale circulation respond to volcanic forcing.
Volcanic sulfate aerosols can affect clouds also by acting as cloud condensation
nuclei (Graf et al., 1997; see also: Mather et al., 2004; Seifert et al., 2011;
Schmidt et al., 2012; Meyer et al., 2015), thereby affecting regional precipitation
(e.g., Zhao et al., 2012). Volcanic eruptions are among the natural aerosol sources
producing the strongest simulated cloud albedo effect (Rap et al., 2013). Assessments
of cloud responses to volcanic forcing in VolMIP must take into account that in all
experiments only the radiative effects of volcanic aerosols are represented (see Sect. 3).
VolMIP further contributes to the initiative on leveraging the past record through planned
experiments describing the climatic response, in an idealized context, to historical
eruptions that are not (or not sufficiently) covered by CMIP6-DECK, historical, or other MIPs.
“Climate extremes,” in particular through a more systematical assessment of
regional climate variability – and associated predictability and prediction – during
periods of strong volcanic forcing at both intraseasonal-to-seasonal (e.g., post-eruption
NH winter warming) and interannual-to-decadal (e.g., post-eruption delayed
winter warming; Zanchettin et al., 2013b; Timmreck et al., 2016a) timescales.
“Water availability,” in particular through the assessment of how strong volcanic
eruptions affect the monsoon systems and the occurrence of extensive and prolonged droughts.
“Melting ice and global consequences,” in particular concerning the onset of
volcanically forced long-term feedbacks involving the cryosphere, which is suggested by
recent studies (e.g., Miller et al., 2012, Berdahl and Robock, 2013; Zanchettin et al., 2014).
Ocean heating and circulation, annual-to-decadal timescales, and short-lived
climate forcers were identified among those areas where the WCRP's grand
challenges seem most in need of broadened or expanded research (Brasseur and
Carlson, 2015). VolMIP is expected to advance knowledge in all such areas.
VolMIP is designed based on a limited number of idealized volcanic forcing
experiments. We recognize that an eruption's characteristics are a major
source of uncertainty for its climatic impacts. We encourage modeling groups
interested in performing sensitivity experiments based on the experiments
proposed here and concerning, e.g., the magnitude and the season of the
eruption to use VolMIP as a platform for coordinating such efforts within a
multi-model framework. The flexibility of the EVA module is, in this regard,
a valuable advantage.
Follow-up research must take into account that the design of the simulations
reflects necessary constraints on the overall resources required to perform
the whole set of mandatory experiments. This implies limitations such as the
possibly insufficient representation of the whole range of variability of
climate modes not explicitly accounted in the design. This includes, for
instance, the SH annular mode (e.g., Karpechko et al., 2010; Zanchettin et
al., 2014) and modes of internal stratospheric variability like the QBO.
VolMIP's experiments are designed based on observed or reconstructed forcing
characteristics of historical volcanic eruptions (1815 Tambora and 1991
Pinatubo for the Tier 1 experiments). Comparison with observational or
reconstructed evidence must, however, take into account the idealized
character of VolMIP's experiments, including the simplified setting for
generating volcanic forcing parameters provided by the EVA module.
Specifically, the evolution of the volcanic aerosol cloud in EVA does not
account for the meteorological conditions at the time of the eruption and
cannot represent the aerosol properties at anything other than the largest
scales. Eccentricities of the aerosol evolution, due to variations in
stratospheric transport such as the QBO, midlatitude mixing, and the polar
vortex, cannot be reliably included in any reconstruction of aerosol forcing
which relies only on sparse proxy records. Additionally,
observation–simulation assessments need to include the identification of
the origins and consequences of systematic model biases affecting the
dynamical climatic response to volcanic forcing.
Summary
VolMIP is a coordinated climate modeling activity to advance our
understanding of how the climate system responds to volcanic forcing. VolMIP
contributes to identifying the causes that limit robustness in simulated
volcanically forced climate variability, especially concerning differences
in models' treatment of physical processes. It further allows for the
evaluation of key climate feedbacks in coupled climate simulations following
relatively well-observed eruptions.
The protocol detailed in this paper aims at improving comparability across
the participating climate models by (i) constraining the applied radiative
forcing, prescribing for each experiment a consensus set of forcing
parameters to be employed, and (ii) constraining the background climate
conditions upon which the volcanic forcing is applied. The protocol entails
three main sets of experiments: the first focusing on the short-term
(seasonal to interannual) atmospheric response, the second focusing on the
long-term (interannual to decadal) response of the coupled ocean–atmosphere
system, and the third focusing on the climatic response to close successions
of volcanic eruptions (so-called volcanic clusters). Experiments are further
prioritized into three tiers. Careful sampling of initial climate conditions
and the opportunity to consider volcanic eruptions of different strengths
will allow a better understanding of the relative role of internal and
externally forced climate variability during periods of strong volcanic
activity, hence improving both the evaluation of climate models and our
ability to accurately simulate past and future climates.
Code and data availability
The model output from the all simulations described in this paper will be
distributed through the Earth System Grid Federation (ESGF) with digital
object identifiers (DOIs) assigned. As in CMIP5, the model output will be
freely accessible through data portals after registration. In order to
document CMIP6's scientific impact and enable ongoing support of CMIP, users
are obligated to acknowledge CMIP6, the participating modeling groups, and
the ESGF centers (see details on the CMIP Panel website at
http://www.wcrp-climate.org/index.php/wgcm-cmip/about-cmip). Further information about the
infrastructure supporting CMIP6, the metadata describing the model output,
and the terms governing its use are provided by the WGCM Infrastructure Panel
(WIP) in their invited contribution to this Special Issue. Along with the
data, the provenance of the data will be recorded, and DOIs will be
assigned to collections of output so that they can be appropriately cited.
This information will be made readily available so that published research
results can be verified and credit can be given to the modeling groups
providing the data. In order to run the experiments, data sets for natural
and anthropogenic forcings defined for the DECK and the CMIP6 historical
simulations are required. These forcing data sets are described in separate
invited contributions to this special issue. In addition, specific volcanic
forcings are required for the VolMIP experiments that are described in this
paper. The forcing data sets for the volc-pinatubo experiments will
be made available through the ESGF with version control and DOIs assigned.
EVA version 1.0 code, a user's manual, sample input data files, and driver
scripts are included as a Supplement by Toohey et al. (2016a). The data request, which contains the list of all
variables requested for each model intercomparison project, is available at
https://www.earthsystemcog.org/projects/wip/CMIP6DataRequest.
Acknowledgements
VolMIP is dedicated to the memory of Thomas Crowley (1948–2014), whose
pioneering work on volcanic forcing on climate has inspired many researchers
and strongly contributed to the foundation upon which VolMIP was built. We
thank the broad scientific community for the stimulating discussions that
motivated VolMIP and for their contribution to the definition of the
experiments and the comments on this draft. We thank the climate modeling
groups who have committed to perform the VolMIP experiments. We are grateful
to the CMIP6 Panel who guided our work throughout the endorsement process,
in particular concerning their recommendation to upgrade the
volc-pinatubo-strat/surf experiments, which led to a stronger Tier 1 experimental palette. We thank
Christoph Raible and an anonymous reviewer for their helpful comments on the
manuscript and on the VolMIP protocol. The volc-cluster-21C experiment was added to the
VolMIP protocol following a suggestion by Ingo Bethke. We thank Martin Juckes for his assistance in preparing the CMIP6 data request and
Karl Taylor for his assistance throughout the endorsement process. We thank
Andrew Schurer for discussion about solar forcing. We acknowledge the
support provided by the World Climate Research Programme (WCRP), which is
responsible for the CMIP5. M. Khodri
acknowledges grant support from the LABEX L-IPSL, funded by the French
Agence Nationale de la Recherche under the “Programme d'Investissements
d'Avenir”(grant no. ANR-10-LABX-18-01), a grant from the Agence Nationale
de la Recherche MORDICUS, under the “Programme Environnement et
Société” (rant no. ANR-13-SENV-0002-02) and benefited from the
IPSL data access PRODIGUER. C. Timmreck acknowledges support from the German
Federal Ministry of Education (BMBF), research program “MiKlip” (FKZ:
01LP1517B/01LP1130A) and the European Project 603557-STRATOCLIM under
program FP7-ENV.2013.6.1-2; STRAOCLIM also partially supported S. Bekki's
work. M. Toohey acknowledges support from the BMBF, research program “MiKlip” (FKZ: 01LP1130B). A. Robock is
supported by US National Science Foundation (NSF) grant AGS-1430051. E. P. Gerber
acknowledges NSF grant AGS-1264195. A. Schmidt was supported by an
Academic Research Fellowship from the University of Leeds and NERC grant
NE/N006038/1. W. T. Ball was funded by the Swiss National Science Foundation
projects 149182 and 163206. G. Hegerl is supported by the ERC project TITAN
(EC-320691), by NCAS and the Wolfson Foundation and the Royal Society as a
Royal Society Wolfson Research Merit Award (WM130060) holder. E. Rozanov was
partially supported by the Swiss National Science Foundation under grant
CRSII2_147659 (FUPSOL II).
Edited by: S. Valcke
Reviewed by: C. C. Raible and one anonymous referee
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