Introduction
The ECHAM/Modular Earth Submodel System (MESSy) Atmospheric
Chemistry (EMAC) model is a numerical chemistry climate model system that
includes submodels describing tropospheric and middle atmosphere processes
and their interaction with ocean, land, and human influences
. The MESSy is used to link different submodels for
physical and chemical processes in the atmosphere . With
MESSy2 the second development cycle of the Modular Earth Submodel System
see is available. The core atmospheric model of EMAC
is the fifth generation of the ECHAM general circulation model, developed by
the Max Planck Institute for Meteorology . One of the
fundamental concepts of MESSy is the strict separation of process and
diagnostic implementations from the overall technical model infrastructure
(e.g. run-control, input/output, memory management). To achieve this, the
model code is organized in four different layers : the
base model layer (BML), the base model interface layer (BMIL), the submodel
interface layer (SMIL), and the submodel core layer (SMCL). For
process-describing submodels, this implies that the code is split into a SMIL
module and one or more SMCL modules, at which the SMIL module manages the
connections to the overlying standardized model infrastructure, and the SMCL
modules contain the actual process descriptions coded independently of the
overlying base model.
The EMAC radiation submodel RAD4ALL is a re-implementation of the ECHAM5
radiation code, calculating radiative temperature tendencies depending on
radiatively active parameters . The input parameters
needed for the calculation of the shortwave and longwave radiation fluxes are
radiatively active trace gases (O3, CH4, CO2,
N2O, CFC-11, and CFC-12), water vapour, cloud cover,
clear-sky index, cloud optical properties (shortwave and longwave optical
depth, asymmetry factor and single scattering albedo of cloud particles),
aerosol optical properties (shortwave and longwave optical thickness, single
scattering albedo, and asymmetry factor of aerosols), and orbital parameters
(zenith angle of the sun, distance between the earth and sun, and relative
day length). The parameterization of the radiative transfer in the
ultraviolet and visible (UV–vis; 0.25–0.69 µm) and the near
infrared (NIR; 0.69–4.00 µm) is based on the four band scheme of
. For the terrestrial (i.e. longwave) part of the
spectrum the RRTM Rapid Radiative Transfer Model; is
used, subdividing the longwave spectrum into 16 bands ranging from 3.33 to
1000 µm. Optionally, the high-resolution shortwave radiation scheme
FUBRAD is available within EMAC to increase the
spectral resolution of the single UV–vis band in the stratosphere and
mesosphere. If activated, FUBRAD replaces the shortwave radiation scheme of
in UV–vis for the layers between top of atmosphere
(TOA) and 70 hPa. FUBRAD has an improved spectral resolution of either 55 or
106 bands and is therefore especially suited for solar variability studies in
the middle atmosphere, where a sufficiently high spectral resolution leads to
an improved solar signal in shortwave heating rates and thus temperatures
. As it operates in the stratosphere and
mesosphere, the relevant radiative processes at this altitude are considered,
i.e. the heating due to absorption of UV by oxygen and ozone, whereas
Rayleigh scattering and scattering on aerosols and clouds are not considered
explicitly (for details see Sect. 2.2).
The development of a new EMAC radiation infrastructure was required, as the
infrastructure of the radiation submodel RAD4ALL has been associated with
many disadvantages:
in RAD4ALL a multitude of SMIL modules, one for each sub-process,
exists;
the calculation of orbital parameters, aerosol, and cloud optical
properties are performed within the radiation submodel RAD4ALL, partly even
within in the technically independent SMCL, although these calculations are
conceptually not subject
of the radiation calculation itself;
in RAD4ALL the import of prescribed gridded climatologies of radiatively
active gases directly utilizes the data import interface NCREGRID
see;
a very cryptic, partly confusing code structure makes the implementation of new code,
e.g. alternative radiation schemes, or the option of multiple diagnostic
calls in one model time step difficult and error-prone;
Hence, the model advancement described in this paper has been guided by the
intention to reorganize RAD4ALL towards a new, more flexible, easily
extendable and base-model-independent concept to couple the radiation submodel to the base model: only
structural changes have been applied, while changes with respect to the
radiation calculation have not been addressed in this development. Hence,
identical output to RAD4ALL is achieved with the revised radiation submodel
called RAD.
In the new radiation infrastructure, calculations of orbital parameters,
aerosol optical properties, and cloud optical properties are separated from
the radiation code, resulting in the new independent submodels RAD (including
the sub-submodel FUBRAD), ORBIT (calculation of orbital parameters), AEROPT
(calculation of aerosol optical properties), and CLOUDOPT (calculation of
cloud optical properties). The most important modifications of these new
submodels are as follows:
In RAD the optional import of external variables for the radiation
calculation (e.g. prescribed climatologies of radiatively active gases) is
now outsourced to the infrastructure submodel IMPORT unified data
import from external files; .
Within the submodel RAD a new important diagnostic feature is the
option to calculate radiative forcing by diagnostically calling the radiation
routines multiple times within one model time step.
AEROPT can be called multiple times per model time step, with different
settings for the required aerosol optical properties. At the moment three
options for the aerosol optical properties are available.
CLOUDOPT can be called multiple times per model time step, and the cloud
optical properties of cloud coverages and cloud perturbations can be
calculated individually.
FUBRAD has been updated with an increased spectral resolution.
In this paper we present the new modularized EMAC radiation code, which has
been derived from RAD4ALL. The new radiation infrastructure (with its new
independent submodels), as well as a test case based on it, is presented in
Sect. 2. An overview of the online radiative forcing calculation in EMAC and
examples of radiative forcing calculations are given in Sect. 3. A short
summary is provided in Sect. 4.
New infrastructure for the EMAC radiation code
Submodel RAD
The new submodel RAD now provides a flexible base-model-independent
infrastructure for radiation calculation according to the MESSy standard.
Figure shows the revised structure of RAD and its
connection to other submodels. The right side of the diagram displays the
relationship of the Fortran95 modules of the SMCL and the SMIL. In the
base-model-independent SMCL the Fortran95 modules RAD_ALBEDO, RAD_LONG and
RAD_SHORT (RAD_SHORT_v1 and RAD_SHORT_v2 respectively) are
USEd by the radiation SMCL module RAD. Two alternative shortwave
radiation schemes are possible: the standard ECHAM5 radiation scheme
(RAD_SHORT_v1) and the ECHAM5 radiation scheme modified according to
RAD_SHORT_v2. In RAD_SHORT_v1, simplified
assumptions for low aerosol loadings under clear-sky conditions are
considered. For the sake of efficiency, the effects of multiple reflection
and the interactions between aerosol scattering and gaseous absorption were
neglected . The assumptions made in RAD_SHORT_v1 are not
valid for high aerosol loadings after volcanic eruptions. Thus, in
RAD_SHORT_v2 modifications were made in the model to include these effects,
showing that multiple reflection is a dominant effect for particle scattering
for details see. Thus, RAD_SHORT_v2 is more accurate.
The RAD_SHORT_CMN module contains definitions and an initialisation
subroutine, which are commonly used in RAD_SHORT_v1 and RAD_SHORT_v2
respectively . If the improved high-resolution shortwave
radiation sub-submodel FUBRAD is switched on,
RAD_FUBRAD is called by RAD_SHORT_CMN from the shortwave calculation
RAD_SHORT_v1 or RAD_SHORT_v2. Shortwave radiation fluxes due to ozone and
oxygen are then calculated at pressures equal to or lower than 70 hPa in the
UV–vis with FUBRAD (replacing the shortwave radiation scheme in RAD). At
altitudes above 70 hPa the UV–vis shortwave radiation fluxes are either
calculated by RAD_SHORT_v1 in one spectral interval as in the original
ECHAM5 code or modified as in RAD_SHORT_v2. A detailed description of the
sub-submodel RAD_FUBRAD is presented in Sect. 2.2. In the SMIL the modules
RAD_E5 and RAD_FUB_E5 are responsible for the data transfer from the
ECHAM5 base model and other submodels to RAD and from RAD via RAD_E5 to the
base model. The calculated radiative temperature tendency of the first
radiation call provides the temperature feedback (ΔTfeed) to
the base model (see Fig. ). The radiative temperature
tendencies from multiple diagnostic calls are also available as diagnostic
variables (ΔTdiag).
Diagram of the revised radiation structure in EMAC. The relationship
between the various Fortran95 modules of RAD is given on the right-hand side.
The different MESSy layers SMCL and SMIL are indicated. The left-hand side
shows the connection of RAD to other submodels. The grey boxes indicate
existing submodels delivering input for the radiation, whereas the green
boxes show new submodels, which are now separated from the radiation code.
The blue arrows indicate the input to RAD and RAD_FUBRAD (dashed) via the
channel infrastructure and the red arrows indicate the trigger, passed from
RAD to ORBIT. The black arrows indicate the dependencies of the Fortran95
modules through Fortran USE statements. The direction of the arrows indicates
where the different modules are used. A detailed description is given in the
text.
The left side of Fig. shows the connections (mainly for
RAD input) via the MESSy infrastructure submodel CHANNEL
to other submodels. The RAD input variables are provided by the submodels
ORBIT, IMPORT data import from
external files, , AEROPT, and CLOUDOPT. The input for AEROPT is either provided from the
dynamical aerosol models MADE , MADE3
, M7 , GMXE , or
from external data via IMPORT. The input for the submodel CLOUDOPT can be
selected from the submodel CLOUD or from external data via IMPORT.
The RAD user interface (a specific Fortran95 namelist) allows for a trigger
(Δtrad), which explicitly enables radiation calculation, as
radiation is not obligatorily called every model time step, as it is
computationally intensive. The corresponding time offset is calculated and
provided as channel object to the submodel ORBIT. As ORBIT is
called every time step, the orbital
parameters are calculated with this time offset and are provided as channel
objects back to RAD (see Fig. ).
The submodel RAD is controlled by its namelists, which enable to select a
wide range of different setups without re-compiling the code. The Supplement
of this paper contains a detailed description of the namelist settings of
RAD. The main features of the radiation namelist are as follows.
A logical switch for the FUBRAD shortwave radiation scheme.
The specification of the radiation time step.
The possibility to modify the solar constant.
Logical switches for diagnostically calling the radiation scheme multiple
times within one model time step. These switches are required for radiative
forcing calculations (see details in Sect. 3).
The choice between the shortwave radiation scheme RAD_SHORT_v1 and RAD_SHORT_v2.
The selection of 18 input variables (listed in the Supplement of this paper),
required for the radiation calculation. These input variables are given by
channel and channel object selection, for instance, from the channels ORBIT,
AEROPT, CLOUDOPT, and IMPORT respectively (see Fig. ). The
radiative relevant input variables can either be provided online (via the
submodels ORBIT, AEROPT, CLOUDOPT) or offline (e.g. via IMPORT in case the
variables are available on a geographical grid). For greenhouse gases (GHGs),
two other offline options are possible besides import of external data fields
via IMPORT: the import of constant mixing ratios and of mixing ratios
decaying with altitude.
The FUBRAD namelists are included in the radiation namelist file. Here,
the solar cycle conditions and the spectral resolution can be set.
Sub-submodel RAD_FUBRAD
To achieve a higher spectral resolution for the UV–vis band, the
sub-submodel RAD_FUBRAD is used. It operates
at pressure levels above 70 hPa, i.e. in the stratosphere and mesosphere.
RAD_FUBRAD substitutes the UV–vis band (250–690 nm) of the RAD shortwave
radiation parameterization by either 49 original version of FUBRAD,
, 55, or alternatively, by 106 bands . The
scheme is based on the Beer–Lambert law and includes the calculation of
shortwave heating rates from the absorption of UV by O2 at the
Lyman-α line 121.5 nm, , the
Schumann–Runge continuum and bands 125.5–205 nm, ,
the calculation of shortwave heating rates from the absorption of UV by
O2 and O3 in the Herzberg continuum (206.2–243.9 nm), and
by O3 in the Hartley (243.9–277.8 nm), Huggins (277.8–362.5 nm),
and Chappuis (407.5–690 nm) bands. Efficiency factors according to
are included to account for energy loss due to
airglow for the Lyman-α line, the Schumann–Runge continuum, and the
Hartley bands. Instead of using Rayleigh scattering in a two stream
approximation, backscattering of the atmosphere and surface is considered,
where the albedo at p=70 hPa in the UV–vis (albtsw), calculated
as the ratio of upward ↑ and downward ↓ directed flux in
the UV–vis (FUV–vis), is used to define the upward directed flux
in the Huggins and Chappuis bands within FUBRAD:
albtsw=FUV–vis↑(p=70hPa)FUV–vis↓(p=70hPa)
The coupling to the single UV–vis band, operating at altitudes below
70 hPa, is done via a coefficient (FUV–vis_frac), representing
the fraction of downward directed UV–vis flux at 70 hPa to the respective
flux at TOA:
FUV–vis_frac=FUV–vis↓(p=70hPa)FUV–vis↓(p=0hPa).
When calculating the transmission functions for clear-sky and all-sky
conditions at altitudes below 70 hPa, FUV–vis_frac is the only
parameter determined by FUBRAD that is taken into account to attenuate the
TOA UV–Vis fluxes. The updated version of RAD_FUBRAD has an increased
spectral resolution of the Chappuis band (407.5–690 nm) from one band in
the original version to either 6 or 57 in the new version
. The band widths and the corresponding O3
absorption cross sections of the additional Chappuis bands are taken from
. With the finer spectral resolution it is now possible to use
the observed solar fluxes within each Chappuis band, rather than the original
single value, which was scaled to reproduce the correct heating rate in the
original version . The application of non-scaled fluxes
allows to create a consistent UV–vis flux profile of the two combined
parameterizations over the complete vertical model domain and consistent flux
diagnostics at TOA and the surface. FUBRAD is fully included in RAD with
corrected diagnostics as shown in Fig. . If the
sub-submodel FUBRAD is switched on, RAD_FUBRAD is called from the shortwave
calculation RAD_SHORT_v1 or RAD_SHORT_v2. In the SMIL the module
RAD_FUBRAD_E5 is responsible for the data transfer from the ECHAM5 base
model and other submodels to RAD and from RAD via RAD_E5 to the base model.
The sub-submodel RAD_FUBRAD is controlled by its namelists, featuring the
FUBRAD CTRL and CPL namelist,
included in the radiation namelist file. Here the spectral resolution and the
solar cycle conditions can be set.
Submodel AEROPT
The submodel AEROPT carries out the calculation of aerosol optical
properties, which are required as input values for the radiation scheme and
are provided by coupling the two submodels via the MESSy CHANNEL
infrastructure.
AEROPT includes several options to provide these required aerosol optical
properties to the radiation scheme, i.e. the aerosol optical thickness per
grid cell (the total extinction by scattering and absorption of aerosol
particles integrated vertically over each grid box), the single scattering
albedo (i.e. the ratio of scattering to absorption by the aerosol), and the
asymmetry factor (describing the angular distribution of scattering
intensity).
Currently there are three options to provide the above mentioned variables to
the radiation scheme.
The first option is using the aerosol climatology TANRE
as in the original radiation code of the ECHAM5 and ECHAM6 models. The TANRE
climatology provides aerosol concentrations and related aerosol optical
properties per unit mass for five different aerosol types, which can be
individually turned on or off. The climatology is implemented in the form of
spectral coefficients, which are converted to grid point space during the
model initialisation. During runtime, the model calculates relative humidity
at each grid cell, which is used in conjunction with the climatological
aerosol concentrations from the climatology to calculate the required
parameters for the radiation scheme with the help of simplified functions.
In the second option, the variables can directly be imported from a file
via the MESSy submodel IMPORT. Therefore, the variables are required on a
geographical grid as, for instance, provided by the Chemistry-Climate Model
Initiative (CCMI) for stratospheric and volcanic aerosols (see
ftp://iacftp.ethz.ch/pub_read/luo/ccmi).
In the third option the optical properties can be calculated online with
the help of aerosol tracer concentrations (component mass and particle
number) and their corresponding size distributions. These data can either be
provided by external data sources and using passive tracers or calculated
online by microphysical aerosol submodels including gas–aerosol
partitioning. In the EMAC system there are several aerosol submodels
available such as the modal aerosol models MADE , MADE3
, M7 , or GMXE .
The online calculation of the aerosol optical properties is then performed
with the help of pre-calculated 3-D lookup tables. The lookup tables provide
optical properties of aerosol modes as a function of the real and imaginary
part of the refractive index and the Mie size parameter (i.e. aerosol size
divided by wavelength, 2πr/λ). The lookup tables are calculated
with the radiative transfer model code libradtran .
Libradtran is used to perform the required Mie calculations for a given
aerosol population. Here, it is assumed that the aerosol population is
log-normally distributed with a given modal width (σ). The radiation
scheme then takes the particle number weighted average of the values for
extinction cross section, single scattering albedo and asymmetry factor from
the lookup table as input for the radiative transfer calculations. During
runtime, a set of lookup tables covering all modal widths used within the
aerosol submodel is required. For the longwave spectrum only the extinction
value is calculated, as the current radiation scheme requires only this
parameter.
Aerosol species explicitly considered are water soluble inorganic ions
(WASO), black carbon (BC), organic carbon (OC), sea salt (SS), mineral dust
(DU), and aerosol water (H2O). The refractive indices for those
aerosol species are extracted from various data sources (most of the data are
compiled in the HITRAN2004 database) and include wavelength dependencies. The
original references are WASO (mainly using ammonium sulphate values following
), BC , SS , H2O
, OC (), and DU
().
The refractive indices for each aerosol mode required as input for the lookup
tables are calculated assuming an internal mixture of the aerosol components
for the hydrophilic modes. A mean refractive index is calculated for each
mode–wavelength combination by averaging the refractive indices of the
individual components weighted with their volume contributions. The
corresponding Mie size parameters are derived from the median radii of the
log-normally distributed modes and the respective wavelengths. The
wavelength-dependent particle extinction cross section, single scattering
albedo, and asymmetry parameter for each mode are then obtained from the
lookup table for the appropriate modal width (σ). For the hydrophobic
modes the same approach can be selected as well as assuming an external
mixture, which results in an averaging of the optical properties of the
individual components. Taking into account the particle number concentrations
and the grid box's vertical extension, the extinction cross sections can be
converted into aerosol optical thicknesses. The optical thickness of the
whole aerosol population in the grid cell is then calculated as the sum over
all modes. The mean values of the single scattering albedo and the asymmetry
parameter are obtained by averaging over the modes weighted with their
optical thickness. To represent mean radiative properties of the aerosol
particles for each radiation band, the extinction, single scattering albedo,
and the asymmetry factor are determined for fixed representative wavelength
values and then mapped onto the corresponding radiation bands using a
weighting with the solar spectrum.
This technique of calculating the aerosol optical properties online from the
simulated aerosol concentrations and lookup tables has been applied earlier
by , , ,
, , and .
As the calculation is fully diagnostic, the AEROPT submodel can be called
several times per model time step with different settings simultaneously,
such as, for instance, different lookup tables, the exclusion of individual
aerosol species or with the TANRE aerosol climatology. All values which are
required for the radiation calculation are provided via the MESSy CHANNEL
interface. Consequently, the coupling structure of the respective radiation
call can be provided with the information of aerosol optical properties,
which are supposed to be used for the respective radiative transfer
calculations. Note that multiple diagnostic calls of the radiation with
different aerosol settings are possible.
As mentioned before, AEROPT is equipped with the option to collect data from
external sources, e.g. imported from files via IMPORT, or from alternative
aerosol schemes, which provide their own calculation of the respective values
required for aerosol–radiation interactions. In addition, AEROPT can provide
the aerosol optical properties required for the calculation of photolysis
rates, as e.g. used by the submodel JVAL . For this purpose
scattering, absorption, and asymmetry factor can be calculated at additional
wavelengths required by JVAL and provided as channel objects.
Besides the three options of providing optical properties to AEROPT, it is
also possible to merge two different datasets for aerosol optical properties
in the vertical, e.g. using prognostic tropospheric aerosol values combined
with the values provided by CCMI for the stratospheric aerosol for the
radiation calculations. The merging of two datasets can be done at a given
height or as a linear interpolation in pressure between two reference values.
It is also possible to add two datasets, for instance in the case of missing
volcanic aerosols, the corresponding aerosol optical properties can be
provided by an external data source and combined with the online calculated
values for prognostic aerosols. The user settings are controlled via
namelists (a detailed description of the namelist settings of AEROPT can be
found in the Supplement of this paper):
the information (a counting index and the corresponding filenames
of the lookup tables) about the desired lookup tables used (shortwave and
longwave spectrum are handled separately);
the information about the sets of aerosol radiative properties (e.g.
GMXE, M7, MADE, MADE3, TANRE), which explain how the optical properties are
going to be calculated (mixing rules, exclusion for certain species, coupling
to required input parameters, etc.);
the option to read a set of aerosol radiative properties from external
sources;
the feature to merge two different datasets of aerosol radiative
properties, as required for the RAD submodel, which can either be read
in via the external interface or be calculated by AEROPT (or an
alternative submodel for calculating aerosol optical properties).
Additionally, optional weighting factors can be included.
Submodel CLOUDOPT
The optical properties of clouds are now calculated in the EMAC submodel
CLOUDOPT. The input variables needed for calculating cloud optical properties
are cloud cover, cloud liquid and cloud ice water, and cloud nuclei
concentration. These optical properties are diagnosed at each band to account
for their wavelength dependency. The specific relations for the solar
spectral bands are based on Mie calculations as given by .
A specific correction for the asymmetry factor is applied to account for the
non-sphericity of ice crystals . Coefficients for the
single scattering albedo, the asymmetry factor, and the mass extinction are
given for cloud liquid droplets and ice crystals. These coefficients are
provided for four bands of the shortwave spectrum and for 16 bands of the
longwave spectrum. Mass absorption coefficients for liquid and ice clouds are
parameterized as described by based on classical
approaches from and . Calculated cloud
optical properties then serve as input for the radiation calculation
comprising the shortwave and longwave optical depth, the asymmetry factor,
and the single scattering albedo of cloud particles. For the 2-D or total
cover in the radiation computation of EMAC the default cloud overlap
assumption is maximum-random overlap; maximum overlap and random overlap are
also possible.
The CLOUDOPT namelists (see detailed description in the Supplement of this
paper) comprise mainly four items.
The model resolution-dependent parameters are set, such as a
correction factor for the asymmetry factor of ice clouds, the cloud
inhomogeneity factors of ice and liquid water, and a parameter to correct the
asymmetry factor of ice clouds. The corresponding
(hard-wired) default values of these
parameters can thus be overwritten without re-compilation of the code.
The channel and channel object names of the required input fields
are specified: cloud cover, cloud
liquid water, cloud ice, and cloud nuclei concentration.
The effective radii of liquid droplets and/or ice can be
calculated internally or provided by an external channel object.
The number of (diagnostic) calls of CLOUDOPT in each model time step is
selected. The required input is set individually for
each call.
The submodel CLOUDOPT was further adapted to enable the separate or
cumulative calculation of radiative properties for different cloud coverages
and/or perturbations, e.g. the coverages with natural clouds and additional
contrail coverage. Furthermore, properties of artificial coverages can be
determined, e.g. the additional coverage of ice clouds in only one vertical
level with a constant optical depth. This allows for example the evaluation
of the performance of the radiation code with respect to a benchmark test,
similar to see the example benchmark test in Sect. 3.4.
Submodel ORBIT
In the new infrastructure of the EMAC radiation calculation the orbital
parameters are separated from the radiation calculation. They are now
calculated in the submodel ORBIT. Orbital parameters are depending on the
time of the day and the year. The basic equations used are the Kepler
equation for the eccentric anomaly and Lacaille's formula
see.
The radiation submodel RAD now accesses the necessary channel objects of the
orbital parameters, including the distance of the sun to the earth, the
cosines of the zenith angle, and the relative day length. As the radiation is
not calculated every time step, ORBIT also receives information from RAD (see
Fig. ), namely the offset for the radiation calculation
(Δtrad).
The ORBIT namelists (see detailed description of these namelists in the
Supplement of the paper) comprise
the selection/setting of the orbital parameters, such as the eccentric
anomaly, the inclination, and the longitude of perihelion;
the possibility to distinguish between two orbit calculations, for
either annual cycle or perpetual month experiments respectively;
the channel object containing the radiation calculation offset Δtrad.
Example application: volcanic heating rates
To demonstrate the functionality of the new radiation infrastructure, we show
a test case: the eruption of Mt. Pinatubo in June 1991, which injected
SO2 into the stratosphere and thus modified the radiative balance by
additional radiative heating. For our simulations with the revised EMAC
radiation infrastructure, we chose a 90-layer model setup (up to
0.01 hPa, approx. 80 km) with a spectral truncation T42 of
the dynamical ECHAM5 core. Interactive chemistry was not simulated, but
AEROPT was used to provide two different sets of aerosol optical properties:
(1) the standard TANRE climatology (i.e. without additional volcanic aerosol)
and (2) the standard TANRE climatology combined (MERGED) with the offline
stratospheric aerosol data as provided by CCMI. Note that the gas phase of
SO2 is not radiatively active in our model. In one model simulation,
the RAD calculation was performed four times every third model time step:
each aerosol input (TANRE or MERGED) combined with each shortwave radiation
scheme (SW-v1 or SW-v2). The simulation has been performed twice, without and
with the FUBRAD scheme respectively. The resulting eight different radiation
setups are summarized in Table .
Radiation setups (modified heating rates due to the eruption of
Mt. Pinatubo) used for testing the new radiation infrastructure. Both
simulations cover the years 1991–1993. Varied parameters are the shortwave
scheme (SW-v1 or SW-v2), the selection of the FUBRAD radiation scheme, and
the selected aerosol input to AEROPT (TANRE or MERGED).
Simulations
SW scheme
FUBRAD
Aerosol
1
SW-v1
yes
TANRE
1
SW-v2
yes
TANRE
1
SW-v1
yes
MERGED
1
SW-v2
yes
MERGED
2
SW-v1
no
TANRE
2
SW-v2
no
TANRE
2
SW-v1
no
MERGED
2
SW-v2
no
MERGED
Figure shows the resulting simulated volcanic heating rates
(in K day-1) for the years 1991 to 1993 from the eruption of
Mt. Pinatubo. The volcanic heating rates are given as difference between the
heating rates simulated with volcanic aerosol (MERGED) and the heating rate
simulated without volcanic aerosol (TANRE). The values are averaged for the
tropics, i.e. over 5∘ N–5∘ S. The comparison of our model
results with the study of shows that in August 1991
and January 1992 the zonally averaged heating rates (pictures are not shown)
are structurally in good agreement: in August 1991 the maximum is between 0
and 10∘ S at 20 hPa but up to 0.9 K day-1 larger in
our model setup. Also, January 1992 shows structurally good agreement with
the study of . As expected, the patterns in
Fig. are similar for the different setups, since the aerosol
optical properties are prescribed. Nevertheless, in the pattern for the
different setups differences with respect to the absolute values occur. The
maximum heating rates are larger for the SW-v1 scheme compared to the SW-v2
scheme. Shortwave heating rates are overestimated by SW-v1 as a result of the
simplified assumptions for low aerosol loadings under clear-sky conditions;
these assumptions are not valid for high aerosol loadings after volcanic
eruptions. The heating rates from SW-v2 are more accurate, as the effects of
multiple reflection and the interactions between aerosol scattering and
gaseous absorption (which are important for high aerosol loadings after
volcanic eruptions) are considered here, in contrast to SW-v1
.
Simulated temporal evolution versus pressure
altitude of the volcanic heating rates (in K day-1) in the tropics
(5∘ S–5∘ N) due to the eruption of Mt. Pinatubo in June
1991. The different panels show the results for SW-v1 and SW-v2 of the shortwave
scheme, both with and without FUBRAD (as indicated).
The application of FUBRAD also decreases the absolute values, as all effects
of scattering are not included in FUBRAD. The simulations including FUBRAD
thus only show the effect of volcanic aerosols on the NIR heating rates.
Calculation of radiative forcing
Technical implementation of radiative forcing calculation in RAD
A new feature in the radiation submodel RAD is the user-friendly and flexible
implementation of the online radiative forcing calculation. It is now
possible to determine instantaneous as well as stratosphere-adjusted
radiative forcing online, i.e. during the model simulation, by multiple calls
of the radiation scheme. Instantaneous radiative forcing is defined as the
change in the net radiative flux with atmospheric temperatures held fixed to
unperturbed values. In contrast, the concept of stratosphere-adjusted
radiative forcing, also known as the fixed dynamic heating concept
, allows stratospheric temperatures to adjust
to a new radiative equilibrium, without changes in tropospheric variables and
stratospheric dynamics. Since the first IPCC report ,
stratosphere-adjusted radiative forcing has been the preferred metric used to
quantify and rank the numerous components impacting the global climate.
The technical procedure to determine the stratosphere-adjusted radiative
forcing within a climate model simulation was introduced by
to the climate model ECHAM4. A second diagnostic
temperature field is implemented to calculate the stratosphere-adjusted
radiative forcing. The reference atmosphere controlled by the first radiation
call is not subject to the perturbations; however, the temperature field of
the extra diagnostic radiation call experiences additional radiative heating
above the tropopause, with dynamical heating remaining identical to the
unperturbed reference atmosphere. In the troposphere, the reference
temperature and the perturbated diagnostic temperature are identical. To
enable the stratospheric temperature to readjust to the new equilibrium, a
spin-up period of at least 3 months must be considered .
After improving the radiation code structure (see Sect. 2.1), multiple
diagnostic calls of the radiation routine can easily be made in order to
determine radiative forcing. Via namelist selection (for detailed description
of the radiation namelist see Supplement) radiation routines can be called
several times within one simulation. The first call is always the reference
call and provides the temperature feedback ΔTfeed (see
Fig. ), the other calls are of diagnostic nature. Either
instantaneous or stratosphere-adjusted radiative forcing can be selected by a
namelist switch. With this setup the radiative forcing of various GHG,
aerosol, or cloud perturbations can be calculated simultaneously in one model
simulation. GHG perturbations can be given as constant mixing ratios with or
without vertical gradient, as externally prescribed 3-D distributions, or as
online calculated, 3-D fields. All perturbed values are specified via channel
object selection in the radiation namelist (see detailed description in the
Supplement). Hence, radiative forcing can be calculated without extra
simulation.
Annually and globally averaged shortwave (SW), longwave (LW), and
net instantaneous and stratosphere-adjusted radiative forcing at the
tropopause due to changes in CO2 and stratospheric O3 between
1980 and 2000 and due to additional homogeneous 1 % contrail cover. The
respective values of the radiative forcing at TOA are given in parentheses.
Instantaneous RF
Adjusted RF
CO2
Strat. O3
Contrail
CO2
Strat. O3
Contrail
SW
0.002 (0.05)
0.08 (-0.13)
-0.088 (-0.086)
0.002 (0.05)
0.08 (-0.14)
-0.088 (-0.086)
LW
0.48 (0.23)
-0.02 (-0.03)
0.203 (0.195)
0.45 (0.40)
-0.09 (0.13)
0.201 (0.199)
Net
0.48 (0.27)
0.06 (-0.16)
0.115 (0.109)
0.45 (0.45)
-0.01 (-0.01)
0.113 (0.113)
Radiative forcing can be determined either at TOA or at the tropopause.
However, the radiative forcing at the respective annual mean tropopause is
usually the preferred metric for comparing the climate impact of different
GHG perturbations. The annual mean tropopause must be used, as the
temperature equilibrium can only be archived with a fixed tropopause height.
In RAD it is possible to calculate radiative forcing at the tropopause via
the submodel VISO , which maps 3-D scalar fields in
Eulerian representation on arbitrary horizontal surfaces. Moreover, by
providing a reference state from offline (e.g. from a pre-calculated
stationary reference simulation), it is also possible with this framework to
perform an analysis of feedback during the course of any climate change
simulation by multiple call radiative transfer calculations
.
In the following subsections we demonstrate the practical advantage of the
extended radiative forcing calculation options by a selection of three
showcases.
Example 1: radiative forcing of CO2 increase
The concept of stratosphere-adjusted radiative forcing is well known and well
established for the case of CO2 change. Its features and merits are
repeated here mainly to set the scene for the more interesting
non-CO2 cases. The first example, thus, forms a radiative forcing
calculation with EMAC using a CO2 increase of 28.8 ppmv,
representing the change of CO2 in 2000 relative to 1980. This
CO2 change was calculated by the EMAC hind-cast simulation
RC1-base-08. The model setup of this simulation is described in detail by
. Table lists global mean values for the
instantaneous and stratosphere-adjusted radiative forcing, both at TOA (given
in brackets) and at the annual mean tropopause, while Fig.
illustrates the vertical structure of the longwave, shortwave, and net
radiative flux changes induced by the CO2 increase.
Vertical profile of the global and annual mean net, shortwave, and
longwave instantaneous radiative flux change (top) and of the
stratosphere-adjusted radiative flux change (bottom) in Wm-2,
resulting from CO2 change between 1980 and 2000.
The main radiative impact of CO2 occurs in the longwave part of the
spectrum, whereas the shortwave forcing component is almost zero at the
tropopause (but about 18 % of the net at TOA because of NIR absorption in
the middle atmosphere). The stratosphere-adjusted net radiative forcing
(0.45 Wm-2) is about 7 % smaller than the instantaneous net
radiative forcing at the tropopause, qualitatively confirming previous
findings. The reason for the dampening, when stratospheric adjustment is
included, is the cooling effect of additional CO2 in the
stratosphere, reducing the downward longwave flux into the troposphere. The
instantaneous net radiative forcing is considerably smaller at TOA compared
to the tropopause for the CO2 case (0.27 and 0.48 Wm-2
respectively). The effect of stratospheric temperature adjustment is to
create a new balance of shortwave and longwave fluxes, leading to vertically
constant net radiative flux changes above the tropopause (Fig. ,
bottom). Hence, the stratosphere-adjusted net radiative forcing has the same
value at TOA and at the tropopause. Note, however, that this does not hold
for the shortwave and longwave components.
Model dependencies in radiative forcing may arise not only from the specific
radiative transfer scheme used in a given model (here: EMAC) but also from
methodical aspects as discussed by e.g. . In particular,
as mentioned above, in our showcases a fixed tropopause from an EMAC
reference simulation is used to define the domain where stratospheric
temperature adjustment takes place. The temperature adjustment evolves
seasonally depending on the EMAC calculation procedure
, which may lead to slight deviations from the
stratosphere adjustment, that is applied when offline radiative transfer
models are used for stratosphere-adjusted forcing calculations. A consequence
is that the stratosphere-adjusted radiative forcing profile above the
tropopause is constant only in the annual mean. However, as already discussed
by , this must not be viewed as a conceptual disadvantage,
and the online radiative forcing calculations in a chemistry–climate model
(CCM)like EMAC may have dedicated advantages for many non-CO2
forcings (see Sect. 3.3).
Example 2: radiative forcing of an ozone-hole like perturbation
The challenge to provide a meaningful indicator of the expected climate
effect of ozone concentration perturbations led to establishing
stratosphere-adjusted radiative forcing as a standard procedure for a long
time. This example uses a stratospheric ozone change due to stratospheric
ozone destruction evolving between 1980 and 2000, again from the EMAC
hind-cast simulation RC1-base-08 (see above). The respective stratospheric
ozone change pattern, shown in Fig. as an annual mean, is in
good agreement with observations (see , their Fig. 8).
However, the seasonal cycle is included in the radiative forcing
calculations.
Zonal geographical distribution of the annual mean stratospheric
O3 change between 1980 and 2000.
In agreement with previous experience
the
instantaneous net radiative forcing turns out to be extremely ambiguous for this kind of
stratospheric ozone perturbation. It changes sign (see Table )
from TOA (-0.16 Wm-2) to the tropopause
(+0.06 Wm-2), a feature controlled by the shortwave component:
less ozone absorption above the tropopause means an energy gain for the
troposphere/surface system but an energy loss for the whole atmosphere. Less
shortwave absorption above the troposphere, as occurring in this case, means
a cooling and changes the downward longwave radiative flux at the tropopause
to an extent that the net radiative forcing at the tropopause changes sign
(Fig. ), giving a small negative value of
-0.01 Wm-2 for the stratosphere-adjusted radiative forcing. As
pointed out by the negative net forcing has the correct
sign to predict a cooling effect in the troposphere/surface system as a
result of ozone depletion. Quantitatively our value is smaller than the
respective estimate given in the last two IPCC reports
(-0.05 Wm-2), which are based on ozone loss over the period
where ozone depleting substances have increased. However, our value is close
to the estimate of -0.02 Wm-2 provided within the ACCMIP
project (, their Table 8.3), where simulated ozone changes
induced by various effects were used for the calculation. In the present
paper our key point is to underpin the usefulness of having a method at hand,
which allows to calculate the stratosphere-adjusted forcing at the tropopause
online in a CCM.
Vertical profile of the global and annual mean net, shortwave, and
longwave instantaneous radiative flux change (top) and of the
stratosphere-adjusted radiative flux change (bottom) in Wm-2,
resulting from stratospheric O3 change between 1980 and
2000.
Example 3: cloud perturbations
The necessity to calculate radiative forcings for cloud changes may arise in
context of direct anthropogenic cloud cover change as induced by contrails or
ship tracks. It is more realistic to perform such calculations on a time step
basis within a CCM rather than using monthly mean input for an offline
radiative transfer model. For example, found a
reduction of contrail radiative forcing of about 20 % when time-varying
(instead of time-averaged) contrail optical depth is used.
even report a reduction of all-sky contrail radiative forcing of more than
35 % when daily correlation of contrails and natural clouds is accounted
for rather than using time mean cloud and contrail properties.
To evaluate the performance of the EMAC radiation parameterisation in
comparison to other radiative transfer codes with respect to thin ice clouds
(similar to aviation induced contrails), we carried out an experiment similar
to . In this benchmark test we add a 1 % homogeneous
contrail cover in one model level with a contrail top of 11 km. The
contrails have a constant optical depth of 0.3, while the other optical
properties are similar to those reported by . The
instantaneous as well as the stratosphere-adjusted radiative forcing are
calculated at the tropopause and at TOA (see corresponding shortwave,
longwave, and net forcing in Table ). The global annual mean
instantaneous net radiative forcing at TOA is 0.109 Wm-2. This
result is at the lower end but within the range given by
from 0.097 to 0.190 Wm-2. Note that most of the radiation codes
tested by are more sophisticated than the one presented
here which is implemented in a CCM, where a reasonable compromise between
accuracy and resource efficiency is essential. In addition to the
instantaneous radiative forcing at TOA, we determine the net radiative
forcing at the mean tropopause, which is 0.115 Wm-2.
Furthermore, we calculated the stratosphere-adjusted radiative forcing, which
was found to be 0.113 Wm-2 (net), deviating only by 4 % from
the instantaneous radiative forcing at TOA.
Figure shows the geographical distribution of the annual
mean net radiative forcing at TOA for 1 % homogeneous contrail cover. The
spatial pattern is dominated by the distribution of natural clouds. The net
radiative forcing of the added contrails is high where natural cloud cover is
low, e.g. over deserts, and is comparatively low in regions with high natural
cloud cover, e.g. over the tropics and mid-latitudes. The magnitude of the
minima and maxima, as well as the spatial pattern of the net radiative
forcing, looks similar to the results presented in the intercomparison study
of . Despite its conceptual advantages over offline
radiative transfer models, this benchmark test confirms the suitability of
the submodel RAD with respect to calculating the radiative effects of thin
ice clouds and contrails.
Geographical distribution of the annual mean net instantaneous
radiative forcing at TOA for a homogeneous 1 % contrail
cover.