Introduction
The direct radiative effect of aerosols resulting from scattering and
absorption of electromagnetic radiation at shortwave (SW) and longwave (LW)
wavelengths has an impact on the Earth's radiation budget (e.g. Haywood and
Boucher, 2000; Bellouin et al., 2005; Jacobson, 2001; Myhre et al., 2013; Yu
et al., 2006; Loeb and Manalo-Smith, 2005) and on meteorology (e.g. Cook and
Highwood, 2004; Takemura et al., 2005; Wang, 2004; Mulcahy et al., 2014;
Bangert et al., 2012) which needs to be accounted for in numerical weather
prediction (NWP) models. Climatological distributions of aerosols are
commonly used in present-day operational NWP models for calculating the
direct radiative effect of aerosols.
Using unrealistic aerosol distributions can lead to considerable errors in
meteorological forecasts. Milton et al. (2008) showed that excluding the
direct radiative effect of mineral dust and biomass burning aerosols in
forecasts using the UK Met Office Unified Model during the dry season in
West Africa, resulted in an inaccurate representation of the surface energy
budget and a warm bias in screen level temperature. Carmona et al. (2008)
presented significant correlations between errors in the aerosol optical
depth (AOD) assumed in an NWP model and temperature forecast errors.
Accurate simulation of the direct radiative effect of aerosols on SW
radiation is important to the growing solar energy industry because under
clear-sky conditions aerosols are the main modulator of SW fluxes
(Breitkreuz et al., 2009).
The monthly aerosol climatology described in Tegen et al. (1997) is used in
ECMWF's (the European Centre for Medium Range Weather Forecasts) global Integrated Forecast System (IFS) and in the Aire Limitee
Adaptation dynamique Developpement InterNational – High Resolution Limited
Area Model (ALADIN-HIRLAM) limited area modelling system used in this study.
Tompkins et al. (2005) showed that replacing the Tanré at al. (1984)
fixed average aerosol distribution in ECMWF's IFS model by the Tegen
climatology improved forecasts of the African Easterly Jet. This change in
the aerosol climatology also improved the forecast skill and seasonal mean
errors (Rodwell and Jung, 2008).
Including a more complete representation of the effects of aerosols in NWP
models can improve the meteorological forecasts and is an active area of
research (e.g. Mulcahy et al., 2014; Bangert et al., 2012). Using real-time
aerosol distributions, rather than climatological data sets, to account for
the direct radiative effect of aerosols further improves the quality of the
forecasts. Toll et al. (2015b) showed that the accuracy of the forecasts of
near-surface conditions by the ALADIN-HIRLAM system during severe wildfires
in summer 2010 in eastern Europe were improved when the direct radiative
effect of the realistic aerosol distribution was included in the model
hindcasts. Palamarchuk et al. (2016) also found a noticeable sensitivity of
the ALADIN-HIRLAM forecasts to the treatment of aerosols where experiments
were carried out under aerosol-free conditions, using sea salt aerosols only
and using the default aerosols in the model. On the other hand, Toll et al. (2016) showed that when observed aerosol distributions are close to average,
improvements in the SW radiation, temperature and humidity forecasts in the
lower troposphere are only slightly greater when time-varying realistic
aerosol data from the Monitoring Atmospheric Composition and Climate (MACC)
reanalysis (Inness et al., 2013) is used in place of the Tegen climatology.
Similar conclusions were drawn by Zamora et al. (2005) who showed that, for
small AODs, accounting for the climatological average direct radiative effect
of aerosols gives very good estimates of SW fluxes, but large biases occur
when the AOD is large.
Baklanov et al. (2014), Grell and Baklanov (2011), Zhang (2008) and Vogel et
al. (2009) have suggested using coupled air quality and NWP models to
improve forecasts of both air quality and weather. However, for operational
NWP such coupled models are still too demanding computationally, and this
added cost has to be evaluated against improvements in the meteorological
forecasts. Mulcahy et al. (2014), Morcrette et al. (2011) and Reale et al. (2011) describe improved forecasts of the radiation budget and near surface
conditions in global NWP models when prognostic aerosols are included;
however the impact of aerosols on large-scale atmospheric dynamics is
generally weak.
The AOD at the wavelength of 550 nm (AOD550 hereafter) and
aerosol inherent optical properties (IOPs: spectral dependence of AOD,
single scattering albedo, SSA and asymmetry factor g) depend on the size,
shape and the complex refractive indices of the aerosols and have a
significant effect on global downwelling SW (SWD) fluxes. Changes in the IOPs
of different aerosols types induced by hygroscopic growth also alter the
radiative effect of aerosols (e.g. Cheng et al., 2008; Bian et al., 2009;
Markowicz et al., 2003; Zieger et al., 2013). For example, Magi and Hobbs
(2003) present measurements of enhanced backscatter by biomass burning
aerosols when the relative humidity (RH) is high. Pilinis et al. (1995)
estimated that the global radiative forcing due to aerosols doubles for a relative
humidity increase from 40 to 80 %.
The vertical profile of aerosols is also very important when estimating their
direct radiative effect, and there are considerable variations in the vertical
distributions of aerosols over Europe (Guibert et al., 2005; Matthias et al.,
2004). For example, Huang et al. (2009) showed that vertical profiles of
heating rates can vary depending on the vertical profile of dust aerosol.
Therefore, inaccuracies result when constant climatological profiles per
aerosol species are used (as is the case in ALADIN-HIRLAM which uses the
profiles of Tanré et al., 1984). For example, Guibert et al. (2005)
analysed the vertical profiles of aerosol extinction over Europe and found
that aerosols over southern Europe are concentrated higher in the atmosphere
due to the occurrence of dust storm episodes. Meloni et al. (2005) showed
that under clear-sky conditions the direct radiative effect of aerosols on
surface radiation has a low dependence on the aerosol vertical profile, but
that the profile has an impact on the top of the atmosphere forcing,
especially for absorbing aerosols. Toll et al. (2015b) evaluated the profile of the aerosol attenuation
coefficient for land aerosols in ALADIN-HIRLAM against observations for the
summer 2010 Russian wildfires. They found good agreement between the
distribution assumed in the model and CALIOP measurements. However, a more
general evaluation of the vertical profile of aerosols in the system has not
been performed.
The main goal of the present study is to focus on the impact of AOD550,
aerosol IOPs, the vertical distribution of aerosols, relative humidity and
radiative transfer algorithms on SW fluxes in diagnostic single-column,
clear-sky experiments using the ALADIN-HIRLAM system. Such experiments are
useful for developing and testing parameterisations and for running idealised
experiments that focus on atmospheric physics in a simplified framework.
With these experiments we can evaluate the strengths and weaknesses of the
NWP model regarding the treatment of the direct radiative effect of
aerosols.
The paper is structured as follows: the model setup and radiation schemes
are described in Sect. 2; the aerosol data sets and atmospheric and surface
input used in the experiments are given in Sect. 3; descriptions of each
of the experiments and sensitivity tests are provided in Sect. 4; the
results and discussion are presented in Sect. 5, while conclusions and
future work are summarised in Sect. 6.
Model setup
ALADIN-HIRLAM
The ALADIN-HIRLAM NWP system is used for
operational weather forecasting by 26 national meteorological services in
Europe and North Africa which form the HIRLAM and ALADIN consortia.
Pottier (2016) summarises 42 limited area configurations of the system used
by the consortia members. This system can also be used for regional climate
simulations (Lindstedt et al., 2015), where the direct radiative effect of
aerosols can be of greater importance than in short-range NWP applications.
The HARMONIE-AROME configuration based on Seity et al. (2011) was used in
this study. HARMONIE (HIRLAM ALADIN Regional Mesoscale Operational NWP in
Europe) denotes the specific configuration of the ALADIN-HIRLAM system
maintained by the HIRLAM consortium; AROME is a limited area model developed
at Météo-France. The default setup of HARMONIE-AROME for operational
NWP uses a 2.5 km horizontal grid and 65 hybrid model levels with deep
convection treated explicitly. This configuration uses ALADIN non-hydrostatic
dynamics (Bénard et al., 2010), non-hydrostatic mesoscale (Meso-NH) physics (Mascart and Bougeault,
2011) and the SURFEX externalised surface scheme (Masson et al., 2013).
Surface physiographies are prescribed using the 1 km resolution ECOCLIMAP II
database (Faroux et al., 2013) and surface
elevation is based on GTOPO30 (USGS, 1998).
We used the single-column version of HARMONIE-AROME (also with 65 vertical
levels) based on Malardel et al. (2006) for the experiments detailed in this
paper. As in Malardel et al. (2006), we will refer to this model
configuration as MUSC (Modèle Unifé Simple Colonne). It includes all of the atmospheric and surface
parameterisations of HARMONIE-AROME but lacks the large-scale dynamics,
horizontal advection, pressure gradient force and large-scale vertical
motion. Because of the simplifying assumptions, MUSC is not suitable for
operational weather forecasting. However, its value lies in the fact that it
provides a useful means of studying the sensitivity of the model output to
realistic atmospheric conditions and different physical parameterisations.
The input to MUSC is derived from the output of a 3-D HARMONIE-AROME
experiment. This includes the initial conditions of the atmosphere and
surface, surface properties, atmospheric temperatures, specific humidities
and wind speeds. Details on the input data used in our experiments are
provided in Sect. 3.4.
Radiation schemes
In this study, three shortwave radiation schemes were applied in MUSC: (1) the
IFS radiation scheme based on cycle 25R1 (Morcrette, 1991; White, 2004),
(2) a new version of the HIRLAM radiation scheme called hlradia
(Savijärvi, 1990) containing aerosol parameterisations, and (3) the acraneb2
scheme (Mašek et al., 2016). Table 1 summarises the main characteristics
of these radiation schemes.
Summary of aerosol radiation experiments including details of the
radiation schemes and aerosol data sets used.
IFS
Hlradia
Acraneb2
SW bands
6
1
1
LW bands
14
1
1
Ozone
Monthly climatology
Impact of O3 constant over time and space
Monthly climatology
Radiatively active gases
Fixed composition mixture of CO2, N2O, CH4 and O2
Impact of CO2 and O2 constant over time and space
Fixed composition mixture of CO2, N2O, CH4 and O2
Radiative transfer
Fouquart and Bonnel (1980) two-stream equations
Savijärvi (1990) and the Thomas and Stamnes (2002) two-stream equations
Ritter and Geleyn (1992) delta two-stream system
Each scheme treats the atmosphere as a 1-D column consisting of a set of
plane-parallel homogeneous layers. The grid box is split into a cloudy
fraction and a clear-sky fraction and does not allow lateral exchanges
between them. Atmospheric composition (i.e. aerosols, clouds and atmospheric
gases) and the radiative properties of the surface are required as input to
the radiation schemes. MUSC was run under clear-sky conditions for the
experiments and sensitivity studies presented in this paper. Thus, details
on cloud particles and cloud cover are not included. Further information on
the basic differences between the radiation schemes is given in the
following sub-sections.
IFS
The IFS SW radiation scheme (ECMWF, 2004; IFS cycle 25R1) is used by default
in MUSC and is the most detailed of the three schemes applied in our
experiments. It contains six SW spectral bands
(0.185–0.25–0.44–0.69–1.19–2.38–4.00 µm), three in the
ultraviolet/visible spectral range and three in the solar infrared range
(Mascart and Bougeault, 2011; White, 2004), and 14 LW bands. The IFS
clear-sky SW radiative transfer is calculated using the Fouquart and Bonnel (1980) two-stream equations in Mascart and Bougeault (2011) where the
reflectance, absorption and transmittance of the atmospheric layers are
calculated in a similar manner to that outlined in Coakley and Chylek (1975). These calculations use the IOPs of aerosols and atmospheric
molecules. Monthly climatologies of vertically integrated AOD550 for six
aerosol categories – continental, sea, urban, desert, volcanic and
background stratospheric are used (Tegen et al., 1997). These aerosols are
distributed among the model levels using Tanré et al. (1984)
climatological vertical profiles for each type as described in Sect. 3.1;
these profiles are used in the calculations of model-level fluxes and
heating rates. The aerosol IOPs are parameterised following Hess et al. (1998). Monthly climatologies of ozone and a fixed composition mixture of
CO2, N2O, CH4 and O2 are also used. Further details
on the aerosols are given in Sect. 3.1.
Hlradia
Hlradia, the simplest of the three schemes, considers one SW and one LW spectral
band. Clear-sky transmittance, reflectance and absorptance of SW flux are
taken into account at each model level to obtain the radiative heating
(vertical divergence of the net SW flux) and net SW fluxes. The radiative
transfer is parameterised rather than solved explicitly, in order to make the
scheme very fast for NWP use (Savijärvi, 1990). The impact of ozone,
oxygen and carbon dioxide on SW irradiance is assumed to be constant over
time and space. In older versions of the scheme, aerosols were accounted for
using constant coefficients. However, the scheme has recently been modified
to include parameterisations of the direct and semi-direct effects of
aerosols, calculated using the two-stream approximation equations for
anisotropic non-conservative scattering described by Thomas and Stamnes (2002).
Hlradia uses the GADS/OPAC aerosols of Koepke et al. (1997) and includes the
following species: soot, minerals (nucleation, accumulation, coarse and
transported modes), sulphuric acid, sea salt (accumulation and coarse
modes), water soluble and water insoluble aerosols. The IFS aerosols types
described in Sect. 2.2.1 are mapped to GADS/OPAC species in accordance
with ECMWF (2004). The aerosol IOPs are averaged over the entire SW spectrum
using spectral weightings calculated, using the libRadtran/DISORT software
package (Mayer and Kylling, 2005; Stamnes et al., 1988), at a height of 2 km
and a solar zenith angle of 45 degrees for a standard mid-latitude summer
atmosphere (Anderson et al., 1986). These IOPs are referred to as broadband
IOPs hereafter in the paper. Hlradia uses the same vertical distributions of
aerosols as the IFS scheme.
Acraneb2
The acraneb2 scheme (Mašek et al., 2016), which is more complex than
hlradia but simpler than IFS, was developed as part of the ALARO-1 suite of
physics parameterisations. Similar to hlradia, it is a broadband scheme using
a single SW radiation interval. However, it uses the Ritter and Geleyn (1992) delta two-stream system for the clear-sky radiative transfer
calculations with coefficients computed according to Räisänen (2002)
i.e. by averaging the coefficients of all of the radiatively active species,
weighted by their optical thicknesses. Acraneb2 uses the same climatologies
of ozone and fixed composition mixture of CO2, N2O, CH4 and
O2 as IFS. It also uses the same aerosol climatology as IFS but where
the IOPs are spectrally averaged over the six IFS bands as is done for
hlradia. One of the strengths of acraneb2 is that it possesses selective
intermittency where slowly varying gaseous transmissions are updated on a
timescale of hours (using a simple correction for the actual sun elevation).
Input and validation data
Aerosol climatology
The direct SW radiative effect of aerosols in MUSC is calculated using
vertically integrated AOD550 and the following aerosol IOPs: AOD spectral
scaling coefficients, spectral SSA and g. The spectral scaling coefficients
are particularly important in the wildfire case study experiments because of
the high dependence of the AOD of biomass burning aerosols on wavelength.
The indirect radiative effect of aerosols is not included in the current
version of the ALADIN-HIRLAM NWP system.
Monthly climatologies of Tegen et al. (1997) vertically integrated AOD550
for six aerosol categories (see Sect. 2.2.1) are used by default in MUSC.
The aerosol IOPs for each spectral band and aerosol type are parameterised
following Hess et al. (1998). The default aerosol types in MUSC are
translated to GADS aerosol species before being used by hlradia as outlined
in Sect. 2.2.2. Spectrally averaged IOPs are used in both hlradia and
acraneb2 as outlined in Sect. 2.2.2 and 2.2.3.
Each radiation scheme uses Tanré et al. (1984) climatological vertical
profiles to distribute the AODs on model levels for each aerosol type. In
these schemes the surface-normalized vertical distribution of AOD, α(z), is described using the following exponential form which results in a
decrease in aerosol attenuation with height
α(z)=exp(-z/h),
where z is the height above the ground and h is a vertical scale height.
It is also possible to replace the monthly Tegen climatology available in
MUSC with other data sets such as the Max-Planck-Institute Aerosol
Climatology version 1 (MACv1, Kinne et al., 2013) or the MACC reanalysis
(Inness et al., 2013) data set, which includes assimilated AOD measurements.
For comparison, the MACC and Tegen aerosol data sets for August 2010 are
shown in Fig. 1 (see Sect. 5.1 for further details).
Aerosol observations
In the Russian wildfire case study (see Sect. 4.1 for details) we ran some
of the simulations using AOD and IOPs derived from CIMEL sun/sky radiometer
measurements recorded at the Aerosol Robotic Network (AERONET, Holben et
al., 1998) station in Tõravere (58.3∘ N; 26.5∘ E),
Estonia. Quality-controlled level 2 AERONET data (Smirnov et al., 2000) were
used. The AOD was derived (by AERONET) from measurements of the direct SW
radiation flux at various wavelengths (Holben et al., 1998). SSA and g were
calculated from diffuse irradiance measurements using an inversion algorithm
by Dubovik and King (2000).
(a) AOD550 for August in the default climatology in the
ALADIN-HIRLAM NWP system (Tegen et al., 1997). (b) AOD for 8 August
2010 from the MACC reanalysis (Inness et al., 2013). The location of
Tõravere (58.3∘ N, 26.5∘ E), for which the MUSC single-column
experiments are run, is shown as a red dot in both panels. Note the
factor of 10 difference in AOD between the Tegen climatology and the MACC
reanalysis.
![]()
AOD550 and AOD scaling coefficients for the six IFS SW bands, assumed valid
for the land (soot) aerosol type, were derived from the spectral AERONET
measurements. These measurements range from 340 to 1020 nm whereas the IFS
radiation scheme includes SW wavelengths from 185 to 4000 nm in the SW.
Therefore, aerosol inputs for the first and sixth SW bands in the IFS scheme (1.19–2.38 and 2.38–4.00 µm) were extrapolated from the AERONET measurements.
This may result in an error in these bands but the majority of the SW flux
is contained in the remaining bands. As in the case of climatological
aerosols, spectral averages of the IOPs are derived for use in the hlradia
and acraneb2 schemes.
BSRN radiative flux measurements
Global SWD radiation measurements recorded at Tõravere were compared to
simulated fluxes for the August 2010 wildfire case study (see Sect. 4.1).
These measurements are independent of the AERONET network but are part of
the Baseline Surface Radiation Network (BSRN, Kallis, 2010) measurements
described by Ohmura et al. (1998).
Summary of aerosol radiation experiments including details of the
radiation schemes and aerosol data sets used.
Experiment
SW radiation scheme
AOD550
Other IOPs (AOD scaling,
SSA, g)
Russian wildfire
IFS
Aerosol-free
Aerosol-free
experiments: WFEXP
Tegen climatology
Hess parameterisation
Observed
Hess parameterisation
Observed
Observed
hlradia
Aerosol-free
Aerosol-free
Tegen climatology
Hess parameterisation
Observed
Hess parameterisation
Observed
Observed
acraneb2
Aerosol-free
Aerosol-free
Tegen climatology
Hess parameterisation
Observed
Hess parameterisation
Observed
Observed
AOD550 experiments:
IFS
Range [0,5] in steps of 0.1
Hess parameterisation
AODEXP
Observed
hlradia
Range [0,5] in steps of 0.1
Hess parameterisation
Observed
acraneb2
Range [0,5] in steps of 0.1
Hess parameterisation
Observed
Vertical profile of aerosols
IFS
Observed (10:00 UTC)
Observed (10:00 UTC)
experiments: VPEXP
Relative humidity
hlradia
0.1
Hess parameterisation
experiments: RHEXP
1.0
Hess parameterisation
IFS
0.1
Hess parameterisation
1.0
Hess parameterisation
Radiative transfer
IFS
Total AOD (not 550 nm) in the range [0.01,5]
SSA = 0.95, g=0.7
experiments: RTEXP
hlradia
Total AOD in the range [0.01,5]
SSA = 0.95, g=0.7
acraneb2
Total AOD in the range [0.01,5]
SSA = 0.95, g=0.7
DISORT
Total AOD in the range [0.01,5]
SSA = 0.95, g=0.7
Atmospheric and surface input for MUSC
The input atmospheric and surface fields for the severe wildfire experiments
at Tõravere were generated from hourly output snapshots from a 3-D
HARMONIE-AROME simulation. The simulation was carried out on a 2.5 km grid
with 65 vertical levels over Estonia for 8 August 2010 as described in Toll
et al. (2015a) and the outputs were interpolated to the geographical
coordinates of Tõravere for use by MUSC. As the experiments in this
paper were run assuming clear-sky conditions, model-level cloud water and
cloud ice values were manually removed from each of the hourly atmospheric
profile files generated for MUSC. These values were small but needed to be
removed to allow direct comparison with observations because cloud cover
observations recorded at the Tõravere synoptic station showed that the
sky was clear until 14:00 UTC.
Experiments
Three sets of experiments were conducted in this study (short names for each
experiment have been included in brackets): (1) a case study of the summer 2010 Russian wildfires where smoke plumes affected Estonia (WFEXP) and the
global SWD irradiance from MUSC was compared to observations, (2) the
sensitivity of SWD fluxes to AOD (AODEXP), the aerosol vertical profile
(VPEXP) and relative humidity (RHEXP) and (3) aerosol radiative transfer
(transmittances) compared to the accurate DISORT scheme (RTEXP). (2) and (3)
are sensitivity experiments and do not simulate the summer 2010 wildfires. A
summary of these experiments in terms of the aerosols and radiation schemes
used is given in Table 2.
Russian wildfire case study (WFEXP)
One of the worst cases of atmospheric pollution over Estonia in recent
decades (Witte et al., 2011; Huijnen et al., 2012) occurred on 8 August
2010 when forest fires in the Baltic region coincided with severe
thunderstorms (Toll and Männik, 2015). To study this extreme pollution
event, we focussed MUSC single-column experiments on the Tõravere
location in Estonia. This location was selected for three reasons: (1) the
smoke plume had a strong impact on the area, (2) measurements of aerosol IOPs
were available from a local AERONET station and (3) radiation flux
measurements were available from the BSRN archive. We ran a series of 12
experiments using MUSC; 4 aerosol scenarios for each of the 3 radiation
schemes (see Table 2 for summary). In particular, the following aerosol
treatments were considered: (1) aerosol-free, (2) climatological AOD550 and
parameterised IOPs, (3) observed AOD550 and parameterised IOPs and (4) aerosol
observations (AOD550 and IOPs). In the experiments using observations
(either AOD550 or both AOD550 and IOPs) the aerosols were assigned to the
land/continental aerosol category while the remaining five categories of IFS
aerosols (see Sect. 2.2.1) were set to zero. Accordingly, the
climatological vertical distribution of IFS land aerosols was assumed.
In each experiment, a single time step diagnostic MUSC simulation was run
using the relevant input file (see Sect. 3.4) as the starting point and
repeated for each hour between 00:00 and 24:00 UTC. Thus, a series of single time step
simulations were run starting from the 00:00 UTC input file,
01:00 UTC input file and so on up to 24:00 UTC. The model was run in
diagnostic mode in order to focus on the radiative properties when the state
of the atmosphere and surface had not yet evolved from the initial values.
Aerosol sensitivity experiments (AODEXP, RHEXP and VPEXP)
In the aerosol sensitivity experiments outlined below, the 10:00 UTC
atmospheric and surface files generated for the wildfire case study were
used as input. In each of the experiments the relative effect of a different
aerosol characteristic (AOD550, relative humidity and the vertical
distribution of aerosols) on SWD fluxes was investigated. In each case,
single time step diagnostic MUSC simulations were conducted for a range of
values of each aerosol characteristic (see Table 2 for the summary).
Six experiments were carried out to investigate the effect of AOD550 on SWD
fluxes (AODEXP). In particular, two aerosol IOP configurations (observed and
parameterised) were used with the IFS, hlradia and acraneb2 radiation
schemes. In each case we varied AOD550 from 0 (no aerosols) to 5 (extremely
polluted) in steps of 0.1 to investigate its influence on SW radiation
fluxes at the surface.
The aerosol radiative transfer algorithms in the IFS and acraneb2 radiation
schemes in the current version of the ALADIN-HIRLAM system assume a constant
RH of 80 %. In this regard, the hlradia scheme is more advanced as the RH
dependence has been incorporated into the calculation of the radiative
effect of aerosol IOPs. Four RH experiments (RHEXP) were carried out: two using hlradia and two using IFS where the latter were used to normalise the
results from hlradia. As in AODEXP, the 10:00 UTC atmospheric and surface input
files were used for the RHEXP experiments. Parameterised aerosol IOPs were
employed in each case. Using hlradia, a series of single time step
diagnostic MUSC experiments were run for RH in the range 0–1.0 in
increments of 0.1. The input atmospheric file was not edited to achieve the
required RH. Instead, we hard-coded RH only for the aerosol transmission
calculations. The series of RH simulations were run for AOD550 values of 0.1 and
1.0, which covers average and extreme aerosol quantities. Using IFS, it was
only necessary to run one diagnostic MUSC simulation for each AOD550 because
the IFS aerosol calculations were formulated using an assumed RH of 80 %.
In the VPEXP experiments we tested the sensitivity of SWD fluxes and the SW
heating rate to the vertical scale height h (see Sect. 3.1) using MUSC with
the IFS radiation scheme. The experiments were initialised using the 10:00 UTC
input files from the wildfire experiment and observed AOD550 and IOPs
assigned to the land aerosol category. In MUSC, h has a default value of 1000 m for land aerosols. We ran single time step diagnostic experiments using
the following values of h for land aerosols: 527, 1000 (default), 2109
and 8343 m (experiments were also run using other values of h but the four
values included here capture the range of sensitivity of the SWD fluxes and
SW heating rate). For smaller h, the aerosols are concentrated closer to the
ground while larger values of h spread the aerosols higher into the
atmosphere. The acraneb2 and hlradia schemes use the same vertical
distribution of aerosols as IFS and exhibit a similar sensitivity in terms
of SWD fluxes and the SW heating rate (results not included).
Aerosol radiative transfer (RTEXP)
Accurate aerosol radiative transfer is of equal importance to accurate
aerosol IOPs. To examine the performance of the aerosol radiative transfer
algorithms in MUSC, we extracted the relevant subroutines from the IFS,
hlradia and acraneb2 radiation scheme codes and ran these as stand-alone
formulations. These calculations require optical thickness, SSA, g and the
cosine of the solar zenith angle as input.
We ran experiments using the IFS Fouquart and Bonnel (1980) clear-sky
formulation, the two-stream approximation (Thomas and Stamnes, 2002) used
in hlradia and the acraneb2 Ritter and Geleyn (1992) two-stream
approximation to calculate SW transmission through a homogeneous atmospheric
layer with optical properties resembling those of aerosols. In particular,
we used SSA = 0.95, g=0.7 and cosine of the solar zenith angle of 0.6
while varying the optical depth between 0.1 and 5. Additionally, we used the
accurate DISORT radiative transfer scheme (Stamnes et al., 1988) with 30 streams and the same input as the IFS, hlradia and acraneb2 radiative
transfer calculations.
Results and discussion
Russian wildfire case study (WFEXP)
The results presented in this section include a comparison of AOD550 for the
Tegen and MACC reanalysis climatologies, time series of spectral AOD, SSA
and g from AERONET and experiments run using MUSC with observed and
climatological aerosol data and the IFS, hlradia and acraneb2 radiation
schemes. Figure 1 shows the AOD550 over northwestern Europe on 8 August
2010 for the Tegen climatology used in MUSC and the MACC reanalysis data set
(Inness et al., 2013). It is clear that the Tegen climatology greatly
underestimates aerosols when pollution is heavy, as was the case over
Estonia and eastern Russia on 8 August 2010. Overall, over northwestern
Europe, the values of the realistic MACC AOD550 (maximum 3.5) are an order of
magnitude higher than in the Tegen climatology (maximum 0.33) for August
which highlights a drawback of using the Tegen data set.
AERONET measurements of AOD at Tõravere on 8 August 2010 for
seven SW wavelengths (nm). The AOD550 derived from these measurements (black
dashed line) and the default climatological AOD550 at Tõravere (red
dashed line) are also shown in the figure. Data are not available after
14:00 UTC due to the presence of clouds.
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Figure 2 shows a time series of AOD at Tõravere on 8 August 2010 for
seven wavelengths (measurements from the AERONET archive). The strong
spectral dependence of AOD is clear from the figure; AOD is higher for
shorter wavelengths. This notable wavelength dependence is characteristic of
biomass burning aerosols (Slutsker and Kinne, 1999). The AOD550, also shown
in Fig. 2 (black dashed line),
used in the experiments involving observations rather than the Tegen
climatology, was calculated using the AERONET AOD at 500 nm (cyan line)
and the Ångström exponent in the 440–675 nm spectral interval. For
comparison, the significantly lower AOD550 from the Tegen climatology (red
dashed line) is also included in the figure.
The remaining aerosol IOPs, SSA and g, from the AERONET inversion products
database are shown in Fig. 3 (continuous curves) where daily averages are plotted as a
function of wavelength. Although daily averages are shown, the time
dependence of SSA and g on 8 August was small. The asymmetry factor, g,
varies from 0.56 to 0.7 across the wavelength range and has an average value
of 0.634. The latter was used in the wildfire experiments run using hlradia
or acraneb2 with aerosol observations. The spectral values of g were
interpolated to the six SW bands of IFS for experiments using this scheme.
Single scattering albedo (SSA, red continuous) and asymmetry
factor (g, blue continuous) at Tõravere on 8 August 2010, as a function
of wavelength, attained from the AERONET inversion products database. The
data are averaged over the day – data at three different times were
available and the time dependence was small. The parameterised SSA and g for
the six IFS SW bands (points are plotted at the midpoint between each of the
bands) are depicted by the dashed lines. Both observed and parameterised SSA
and g values are spectrally averaged for use by the hlradia and acraneb2
radiation schemes.
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The aerosol scattering per extinction ratio, represented by SSA, is high
(close to 0.96 with a spectral average of 0.955) at each wavelength with
little SW spectral dependence (Fig. 3, red continuous curve). This is
similar to results by Dubovik et al. (2002) who showed that the typical SSA
of smoke from biomass burning in Boreal forests is high. However, the
scattering of smoke particles from this Russian wildfire event was higher
than that of plumes from typical biomass burning in Boreal forests (Chubarova
et al., 2012). As in the case of g, the average SSA was used in the hlradia
and acraneb2 wildfire experiments involving aerosol observations while the
spectral SSAs were interpolated to the IFS SW bands before use in the
corresponding IFS experiments. The Hess et al. (1998) parameterised values of
SSA and g for the six IFS SW bands in MUSC are also shown in Fig. 3
(dashed lines). As in the case of SSA and g based on observations, the
parameterised values are spectrally averaged for use by hlradia and acraneb2.
(a) Time series of global SWD radiation flux (W m-2)
at Tõravere on 8 August 2010 simulated using MUSC (with the IFS radiation
scheme) for four aerosol scenarios (red: aerosol free; black:
climatological AOD550 and parameterised IOPs; green: observed AOD550 and
parameterised IOPs; cyan: observed AOD550 and IOPs). BSRN global SWD flux
measurements are shown in blue. (b) Time series of the bias in
global SWD flux relative to BSRN observations for the same four aerosol
scenarios as in panel (a). The results when the IFS radiation scheme
was used are depicted by a dotted continuous line; the hlradia (hlr) and
acraneb2 (acr) biases are shown using continuous and dashed lines,
respectively. Only data up to 14:00 UTC are shown because clouds developed
after that, which were not included in the MUSC simulations.
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Figure 4a shows the global SWD radiative flux at the Earth's surface
simulated using MUSC with the IFS radiation scheme for 8 August 2010 at
Tõravere. We ran an experiment for each of the following four aerosol
scenarios (also summarised in Table 2): (1) aerosol-free (red curve), (2) climatological AOD550 and parameterised IOPs (black curve), (3) observed AOD550 and
parameterised IOPs (green curve) and (4) observed AOD550 and IOPs (cyan curve) and compared the
global SWD fluxes to BSRN observations (blue curve). The discrepancy between simulated
and observed SWD irradiance after 14:00 UTC is due to the development of
convective clouds (Toll et al., 2015a) which are not accounted for in the
MUSC clear-sky simulations.
The biases in global SWD flux (relative to observations) for the experiments
using each radiation scheme (and not just IFS) and the four different aerosol
scenarios are depicted in Fig. 4b (IFS dotted continuous lines, hlradia continuous lines, acraneb2 dashed lines; the aerosol scenario colour
scheme is the same as in Fig. 4a). Overall, the results for the three
schemes are similar (mostly to within 10–20 W m-2 of each other for
global SWD irradiance which can be seen by comparing each group of three
curves of the same colour), particularly in their response to the different
aerosol scenarios. The largest discrepancies occur in the early
morning; in hlradia this occurs because the sphericity of the atmosphere is
not taken into account. The early morning discrepancies in SWD for the IFS
scheme are thought to be due to the delta two-stream formulation but further
work is required on this topic. When the direct radiative effect of aerosols
was excluded, global SWD fluxes were overestimated by ∼ 120 W m-2 or 19 % (red curves) at midday compared to BSRN observations. Accounting
for the climatological average effect of aerosols using the Tegen et al. (1997) data set and Hess et al. (1998) IOP parameterisations (black curves) improves the
simulation of global SWD flux compared to the aerosol-free simulation.
However, there is still an overestimation of 60 W m-2 or 10 % at
noon, because the observed AOD is higher than the climatological average
(see Figs. 1 and 2).
The use of AOD550 and IOPs derived from AERONET observations gives very good
agreement between the modelled and observed global SWD fluxes for each of
the three radiation schemes (cyan curves, bias < 20 W m-2 or 4 % at
noon). SWD flux was underestimated by ∼ 70 W m-2 or 11 % (green curves) at noon when the direct radiative effect of aerosols was accounted
for using the observed AOD550 combined with parameterised SSA, g and spectral
scaling factors of land aerosols. This underestimation can be explained by
two factors.
Firstly, using the climatological AOD scaling factors for Tõravere in
August leads to AOD values which are 60 % higher than those estimated
from the AERONET spectral measurements. Secondly, using a delta-Eddington
optical depth scaling factor (1-SSAg2; Joseph et al., 1976)
based on the climatological SSA and g values causes this factor to be
approximately 7 % lower than the corresponding scaling factor based on
the observed SSA and g values. The combination of these two factors results
in a scaled SW AOD of land aerosols that is 48 % larger than the
observation-based value.
Aerosol sensitivity tests
AOD (AODEXP)
The sensitivity of global SWD fluxes to AOD550 is shown in Fig. 5a for
MUSC experiments run using the IFS, hlradia and acraneb2 radiation schemes.
The results depicted by the cyan curves are for the case where observed IOPs
(i.e. 10:00 UTC observation at Tõravere from the AERONET archive) were used
in the simulations. Parameterised IOPs were used where the experiment results
are shown in green. For an AOD550 of 1, global SWD irradiance is ∼ 100 W m-2 lower when parameterised rather than observed IOPs were used,
regardless of the radiation scheme. The reason for this difference has been
discussed in Sect. 5.1.
Global SWD flux as a function of AOD550 for MUSC experiments run
using the IFS (dotted continuous curve), hlradia (continuous curve) and
acraneb2 (dashed curve) radiation schemes. The results depicted by the
cyan curves are for the cases where observed IOPs (SSA, g and AOD
scaling) were used. Parameterised IOPs were used for those shown in green.
The direct SWD flux for MUSC experiments using the same aerosol scenarios and
radiation schemes as in panel (a) is shown in panel (b).
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The effect of AOD550 on direct SWD flux is shown in Fig. 5b for the three
radiation schemes and observed (cyan curves) and parameterised (green curves) IOPs. For example,
when parameterised IOPs were used, an increase in AOD550 from 0 to 1 (i.e. no
aerosols to heavy pollution) reduced the global SWD irradiance by
∼ 200 W m-2 or 27 % (Fig. 5a) but had a greater
effect on the direct SWD flux (∼ 330 W m-2 or 49 %,
Fig. 5b). Direct SWD flux is very sensitive to AOD because it is
extinguished by both absorption and scattering. Due to forward scattering,
the global SWD flux is less affected because the forward scattered
irradiance reaches the surface as diffuse SWD irradiance (i.e. some of the
direct beam extinguished by scattering reaches the surface as diffuse
irradiance, resulting in an increase in diffuse flux). The influence of
AOD550 on global SWD flux is similar for each radiation scheme. Global SWD
fluxes are lower when the parameterised IOPs are used; this is because of the
combination of a higher AOD scaling factor and lower delta-Eddington optical
depth scaling factor than based on observations as discussed in Sect. 5.1.
This sensitivity test clearly illustrates the large effect AOD550 and the
IOPs have on SW radiative fluxes at the surface and emphasises the
importance of using the correct aerosol IOPs in NWP.
(a) Global (dotted continuous curves) and direct
(continuous curves) SWD fluxes, as a function of relative humidity,
simulated using MUSC with the hlradia radiation scheme for AOD550 values of
0.1 (grey) and 1.0 (black). (b) Similar to panel (a)
but shows global SWD flux normalised relative to a corresponding experiment
run using the IFS radiation scheme. The IFS scheme assumes a RH of 80 %
for land aerosols.
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Relative humidity (RHEXP)
The impact of relative humidity (RH), accounted for in the aerosol radiative
transfer calculations in the hlradia scheme, on global and direct SWD fluxes
is shown in Fig. 6a. RH was varied from 0 to 1 in steps of 0.1; the AOD550
was set to 0.1 in the grey curves and to 1.0 (significant pollution) in the
black curves. IFS land aerosol parameterised IOPs at Tõravere were used.
Increasing RH from 0 to 1 increases global SWD flux by 1.5 % when AOD550 = 0.1 (grey line with filled circles)
and by 12 % when AOD550 = 1.0 (black line with filled circles). The effect on the
corresponding direct SWD fluxes is greater as expected (increases of 2.5 and 24 % for AOD550 = 0.1
and 1.0, respectively, grey and black continuous lines). Figure 6b shows
global SWD irradiance from the experiments run using hlradia, an AOD550 of
0.1 (grey) and 1.0 (black) and RH varying from 0 to 1.0 as before. In this case, the
global SWD fluxes are normalised using output from a corresponding
experiment run using the IFS radiation scheme. In the IFS scheme, a constant
RH of 80 % is assumed for “land” aerosols. For AODs close to the
climatological value (i.e. 0.1 here) the relative differences between global
SWD fluxes for experiments using hlradia and IFS are small and negligible
at a RH of 0.8. As the humidity deviates from 0.8, particularly for larger
AODs, the differences between the global SWD fluxes from experiments using
hlradia and IFS grow to ±6 %. When the AODs are close to the
climatological average (of the order of 0.1), the influence of RH on aerosol
radiative transfer is less than 1 %. In such cases, the assumption of a
constant RH by the IFS and acraneb2 schemes is acceptable and is not a major
source of error. On the other hand, for cases where pollution is high, the
influence of RH on global SWD flux is ∼ ±6 % and
could be important, particularly for solar energy applications.
Vertical distribution of aerosols (VPEXP)
The inherent uncertainties associated with assuming fixed vertical profiles
were investigated by modifying the assumptions about the shape of the IFS
climatological vertical aerosol profile. Figure 7a shows normalised net SW
fluxes on pressure levels for MUSC experiments run with the IFS radiation
scheme and vertical scale heights (h, of land aerosols) of 527 m (red), 1000 m
(default, green), 2109 m (cyan) and 8343 m (blue). AERONET aerosol observations at 10:00 UTC over
Tõravere were used as input. The net SW flux is normalised relative to the
aerosol-free case and varies by no more than 4 % at each pressure level
for the range of h plotted. For example, at 1000 hPa the net SW flux varies by less
than 3 % with h, and by less than 4 % at 800 hPa.
(a) Net SW radiation fluxes (normalised relative to the
aerosol-free case) as a function of atmospheric pressure for four vertical
scale heights (h) of IFS land aerosols. (b) Similar to
panel (a) but shows the normalised SW heating rate. The experiments
were carried out using the IFS radiation scheme.
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Figure 7b shows the SW heating rates for the same experimental setup as in
Fig. 7a, where the heating rate is normalised relative to the
corresponding aerosol-free simulations. The heating rates in the boundary
layer changed by up to a factor of 2 in response to the aerosol vertical
distribution (e.g. when h is halved (red curve) compared to the default (green curve) the SW
heating rate approximately doubles). Figure 7b also clearly illustrates that
large values of h spread the aerosol higher in the atmosphere (blue curve) while for
smaller values, the aerosols are concentrated closer to the ground
(red curve).
(a) Transmission as a function of optical depth through a
homogeneous atmospheric layer containing aerosol (SSA = 0.95, g=0.7,
cosine of the solar zenith angle set to 0.6) for the following radiative
transfer algorithms: IFS Fouquart and Bonnel (1980) clear-sky radiative
transfer formulation (cyan curve), the Thomas and Stamnes (2002) two-stream
approximation used for aerosol transmittance in hlradia (black curve),
the Ritter and Geleyn (1992) two-stream approximation used in acraneb2 (red
curve) and the accurate 30-stream DISORT (Stamnes et al., 1988) radiative
transfer scheme (blue curve). Panel (b) is the same as panel (a) but
shows the transmission differences relative to the accurate DISORT scheme.
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Aerosol radiative transfer (RTEXP)
Figure 8a shows transmission as a function of optical depth through a
homogeneous atmospheric layer containing aerosol (SSA = 0.95, g=0.7,
cosine of the solar zenith angle set to 0.6). Transmittances calculated with
the IFS Fouquart and Bonnel (1980) clear-sky radiative transfer formulation,
the Thomas and Stamnes (2002) two-stream approximation used for aerosol
transmittance in hlradia and the Ritter and Geleyn (1992) two-stream
approximation used in acraneb2 are compared to the transmittance from the
accurate DISORT radiative transfer scheme (Stamnes et al., 1988) run using
30 streams. Figure 8b shows the relative differences in transmittance between
these radiative transfer schemes and DISORT. As can be seen from Fig. 8a and
b, the IFS, hlradia and acraneb2 radiative transfer approximations give
transmittances that are within a few percent of the accurate 30-stream DISORT
calculations for optical thicknesses less than 1. Even for optical
thicknesses of up to 5, the approximations remain within ±13 % of the
DISORT results.
Conclusions and future work
We carried out single-column diagnostic experiments using the MUSC model and
three radiation schemes (IFS, hlradia and acraneb2) to examine the influence of the direct radiative
effects of aerosols on SW radiative flux. In particular, we focused on the
effect of AOD550, aerosol IOPs, the relative humidity, vertical profile of
AOD and the radiative transfer formulations on SW fluxes.
In the wildfire case study, we showed that the bias in modelled global SWD
flux relative to observations was lowest when observed AOD550 and IOPs were
included in the simulations (within ±4 % at midday). This was true
irrespective of the radiation scheme and its spectral resolution. Global SWD
flux was greatly overestimated, by more than 15 % at midday, when
aerosols were excluded and by +10 % at midday when the climatological
aerosols were used (Tegen et al., 1997). On the other hand, global SWD
irradiance was underestimated by 11 % at noon, when observed AOD550 and
parameterised IOPs, as opposed to observed IOPs, were used in the
experiments. This highlights the need for accurate information on both
aerosol concentration and aerosol IOPs in order to improve the simulated
radiation budget in the model. The importance of all of the aerosol IOPs,
and not just AOD550, in the direct radiative effect of aerosols on solar
radiation was clearly demonstrated. The over- and under-estimation of global
SWD flux leads to errors in model temperatures and energy fluxes. Therefore,
during heavy pollution episodes the use of real-time aerosols would greatly
improve the radiation budget and meteorological forecasts. The wildfire
experiments also illustrate that the performance of the broadband hlradia
and acraneb2 schemes is comparable to that of the spectral IFS scheme. The
results attained for the three schemes were similar, with simulated global
SWD fluxes mostly within 10–20 W m-2 of each other for each aerosol
scenario.
The dependency of the direct radiative effect of aerosols on relative
humidity was up to ±6 % for an AOD of 1.0. As a first approximation,
assuming a constant relative humidity is acceptable but we suggest that
relative-humidity-dependent parameterisations of aerosol IOPs should be used.
The effect of the vertical profile
of IFS land aerosols (via the vertical scale height) on net SW irradiance
near the surface was found to be up to 4 %. This is consistent with the
finding of Meloni et al. (2005). The influence of the vertical profile on
model-level SW heating rates was large, changing by up to a factor of 2 in
the boundary layer in response to the aerosol vertical distribution. This
highlights the need for using realistic vertical profiles of aerosols. In
reality, aerosols are distributed in discrete rather than continuous layers.
We investigated the influence of the vertical scale height on SW fluxes and
heating rates. Non-exponential forms of the profile could also be tested. The
IFS, hlradia and acraneb2 radiative transfer approximations were tested for a
range of optical depths and found to be accurate to within ±13 %
compared to the DISORT model, even for large aerosol loads.
The influence of improvements in the representation of the direct radiative
effect of aerosols on meteorological forecasts needs further study using 3-D
simulations. We plan to upgrade the aerosol climatology in the
HARMONIE-AROME configuration of the ALADIN-HIRLAM system to the more
realistic MACC reanalysis data set. We will also investigate the option of
acquiring real-time aerosol input, including the vertical profile of the
aerosol properties, from 3-D aerosol IOP estimates from the C-IFS model or
chemical transport model simulations, possibly coupled to the NWP model. We
also plan to carry out a similar study to the one presented here for all-sky
fluxes.