Aerosol–cloud interactions are explored using 1 km simulations of a case study of
predominantly closed-cell SE Pacific stratocumulus clouds. The simulations
include realistic meteorology along with newly implemented cloud microphysics
and sub-grid cloud schemes. The model was critically assessed against
observations of liquid water path (LWP), broadband fluxes, cloud fraction
(
Aerosol loading sensitivity tests showed that at low aerosol loadings,
changes to aerosol affected shortwave fluxes equally through changes to cloud
macrophysical characteristics (LWP,
Overall, the control model demonstrated a credible ability to reproduce
observations, suggesting that many of the important physical processes for
accurately simulating these clouds are represented within the model and
giving some confidence in the predictions of the model concerning
stratocumulus and the impact of aerosol. For example, the control run was
able to reproduce the shape and magnitude of the observed diurnal cycle of
domain mean LWP to within
The works published in this journal are distributed under the Creative Commons Attribution 3.0 License. This licence does not affect the Crown copyright work, which is reusable under the Open Government Licence (OGL). The Creative Commons Attribution 3.0 License and the OGL are interoperable and do not conflict with, reduce, or limit each other. © Crown copyright 2017
In this paper we describe 1 km horizontal grid-spacing simulations of marine stratocumulus clouds nested within a global operational analysis framework that provides realistic meteorological initial conditions and lateral boundary forcing. A grid spacing of this order bridges the gap between large eddy simulation (LES) and global model resolution, allowing larger domains than possible with LES, but the direct representation of more detailed processes than is possible with global models. We perform the first tests for stratocumulus of a newly implemented microphysics package that includes a detailed representation of the effects of aerosol upon clouds and a diagnostic cloud scheme. We use this model to examine the response of the cloud field to varying aerosol concentrations.
Stratocumulus clouds are the dominant cloud type in terms of area, covering
over one-fifth of the Earth's surface in the annual mean
Stratocumulus clouds are also important for numerical weather prediction (NWP) because they modulate the surface temperature through its influence on downwelling shortwave and long-wave radiation at the surface. Furthermore, their influence on visibility is a major consideration for aircraft operations. There is therefore a strong impact on both commercial and general public weather forecasts and applications.
For the climate system, the radiative impact of stratocumulus is strongly
dependent on macrophysical properties such as cloud fraction or cloud liquid
water path (LWP), which are likely to be heavily influenced by large-scale circulation and meteorological factors. However, microphysical
processes can also influence the macrophysical cloud properties, as well as
having important radiative impacts in their own right. If all else is equal,
i.e. a fixed liquid water content (LWC), increasing the concentration of
cloud condensation nuclei (CCN) leads to smaller droplets that in turn
produce more reflective clouds
Changes in precipitation and LWP that result from changes in aerosol can also
be accompanied by changes in cloud fraction
A compromise between LES and GCMs is a coarser-resolution (
It is an open question whether kilometre-scale grid spacings are adequate to
simulate the important processes involved in marine stratocumulus. For
example,
In this paper we present results using a regional nested configuration of the
Met Office Unified Model (UM). It is driven by realistic meteorology and
includes a new microphysics scheme called CASIM (Cloud AeroSol Interaction
Microphysics; see Sect.
Thus, we aim to address the following questions:
Can a regional model produce a realistic representation of stratocumulus clouds when compared to a diverse range of observations? How do the modelled clouds respond to aerosol? What is the relative importance of macrophysical and cloud albedo changes for aerosol-induced radiative effects? What is the relative importance of the sub-grid cloud scheme?
For this case study we simulate a near-coastal region of the SE Pacific (see
Fig.
A map of the SE Pacific region with the 1 km model domain shown as
a black box. The colours show the orography over land and the sea-surface
temperature over the ocean, both at the resolution of the global model (N512;
In this study we use the NWP configuration of
the UK Met Office UM. The global model used
here is the GA6 configuration of the UM at N512 resolution
(
The 1 km inner nest also employs 70 vertical levels, but with a lower domain
top of 40 km and thus a higher vertical resolution.
Table
The model vertical grid spacing (d
The global simulation uses the operational microphysics scheme based on
The recent previous studies of stratocumulus with the UM that employed high-resolution nests, e.g. BA12, used a sub-grid cloud scheme
When CASIM was implemented into the UM, it was done so with no sub-grid cloud
scheme. In this configuration there was a large under-prediction in the
amount of stratocumulus (see Sect.
CASIM is a new multi-moment microphysics scheme for the UM that includes the effects of aerosol upon clouds and vice versa. This provides enhanced capability over the old operational scheme in which the cloud droplet concentration was constant throughout the domain.
As with other bulk microphysics schemes, the cloud and rainwater are
separated into two hydrometeor classes. In each class the drop size
distributions are described using a gamma distribution with a prescribed shape
parameter and prognosed bulk mass and number concentration, i.e. double
moment cloud and rain
If a model grid box is deemed to be sufficiently humid by the
above-mentioned cloud scheme, then cloud water condenses and the number of
droplets activated is determined using the scheme described in
CASIM microphysics scheme parameterization summary.
Five different size modes are available to represent soluble and insoluble aerosol, but only a single soluble accumulation mode is used here. The aerosol mode has a lognormal size distribution with a fixed width. In this paper the aerosol is initially spatially uniform in both the vertical and horizontal and the same aerosol profiles are applied as lateral boundary conditions to the inner nest. There are no local sources of aerosol at present. However, aerosol is advected and thus concentrations can change locally due to convergence and divergence. Details of the aerosol concentrations used in the different runs of this work are given in the next section. CASIM includes the option of aerosol processing, which includes activation scavenging; in-cloud mechanical processing into fewer, but larger aerosol particles (via collision coalescence); precipitation washout of both in-cloud and out-of-cloud aerosol; and evaporative regeneration. These processes can lead to an overall reduction in the aerosol available for forming cloud droplets. However, aerosol processing is not switched on for the runs in this work, but will be considered in a later paper.
We have performed several model runs that are listed in
Table
The microphysical parameters used in the simulations for the
equations described in
Aerosol sensitivity runs have been performed where the soluble accumulation
mode aerosol mass and number have been reduced by factors of 10 and 40
(CASIM-Ndvar-0.1 and CASIM-Ndvar-0.025 respectively) and increased by a
factor of 10 (CASIM-Ndvar-10). This range of aerosol concentrations creates
clouds with droplet numbers that bracket the range observed during the VOCALS
field campaign, as we will show in Sect.
UM model runs. “Standard RH
Data from a variety of instruments onboard several observational platforms,
including satellite, ship, and aircraft, have been used to validate the model.
The data used (including error estimates from the literature) are described
in Appendix
In this paper we choose to define cloud using an LWP threshold of
20
Details on the observations used in this study.
n/a
Figure
The
Snapshots of LWP (
Figure
PDFs of the
cloud droplet number concentration for the model domain region. A snapshot
time of 14:12 LST on 13 November is used
for the model and 13:57 LST for the GOES-10 satellite, which is the nearest
available data point. Three-dimensional model data are first converted to 2-D
data, taking the
The observations from GOES-10 show that there is a two-mode PDF, with a mode
of very low
The control model (CASIM-Ndvar) has a
Figure
Figure
Time series of the mean LWP over the region of the UM domain for the
different model simulations, the microwave satellite instruments, and the
GOES-10 instrument. There are several microwave instruments that give
snapshots throughout the diurnal cycle, as labelled in the legend; they are
joined by the blue line. GOES-10 data are only used for the daytime, but they give
higher time resolution. Retrievals where the solar zenith angle is larger
than 65
The model runs produce the observed peaks and troughs in LWP and even capture
the secondary peak on 13 November at around 08:00 LST. The higher aerosol runs
(CASIM-Ndvar and CASIM-Ndvar-10) and the old microphysics run (Old-mphys)
also capture the magnitude of the LWP values well, although all simulations
overestimate the daytime LWP values. There is better agreement for Old-mphys (overestimate of around 10
In the lower-aerosol runs (CASIM-Ndvar-0.1 and CASIM-Ndvar-0.025), LWP values
are significantly lower, indicating a cloud macrophysical response via the
precipitation rate. For the high-aerosol case, little impact of aerosol on the
cloud field was found relative to the control case (CASIM-Ndvar). This is
because little rain production occurs in the control case and
hence the addition of more aerosol cannot have much of a precipitation
suppression impact. This is demonstrated in Fig.
As for Fig.
Daytime snapshots of LWP (
CASIM-Ndvar-RHcrit0.999 is a model run where the sub-grid cloud scheme has been switched off, which results in a very large LWP reduction compared to the control case, with LWP values similar to those from CASIM-Ndvar-0.025 for the first day and CASIM-Ndvar-0.1 for the second day. The results clearly highlight that while it is possible for the aerosol environment to have a large impact on the structure of the stratocumulus cloud deck (see CASIM-Ndvar-0.025 and CASIM-Ndvar), the role of the treatment of subgrid humidity, even for grid spacings of 1 km, is still as important as a factor of 10–40 reduction in aerosol loading (see CASIM-Ndvar and CASIM-Ndvar-0.025 or CASIM-Ndvar-0.1). Given the unrealistically low LWP values in the CASIM-Ndvar-RHcrit0.999 case, the results from this run will not be included in future plots for clarity.
Figure
The control and high-aerosol simulations qualitatively represent the diagonal
band structures and the low LWP values near the coast (in the NE corner of
the domain) very well, despite the fact that there is no spatial gradient in
the aerosol field of the model, as there would be in reality. This indicates
a general dominance of the meteorological state over the macrophysical
properties of the clouds. However, in the very-low-aerosol run
(CASIM-Ndvar-0.025), LWP values and the cloud fraction are significantly
lower,
indicating a cloud macrophysical response via the precipitation rate, which
is similar to what has been observed in LES studies
The CASIM-Ndvar and CASIM-Ndvar-10 cases display some clear regions in between the diagonal bands of high LWP, but they are much smaller than the observed POC regions. The low-aerosol run produces small-sized convective cells surrounded by clear air that are reminiscent of the observed POC regions, but they occur throughout the whole domain. Thus, this suggests that the model is capable of producing open-cell features given low enough aerosol concentrations, but cannot reproduce isolated POC regions in amongst the closed-cell convection.
The nighttime LWP maps in Fig.
As for Fig.
PDFs of LWP for daytime (left) and nighttime (right) time periods
for the model and for satellite observations. “REMSS” refers to the several
available REMSS microwave instruments, each of which provides a snapshot LWP
field. For the daytime, the times surrounding the minima in the LWP diurnal
cycle (see Fig.
PDFs of LWP for the period from 06:00 UTC on 12 November to
00:00 UTC on 14 November 2008 from the RV
Figure
Also shown are nighttime LWP PDFs from the REMSS satellites only. The models
all show some degree of underestimate for LWP values at around
130
In addition to spatial satellite PDFs, the microwave radiometer onboard the
RV
Figure
Figure
Cloud fraction cumulative distribution functions between 08:12 and
16:12 LST for the model and 07:57 and 15:57 for GOES-10 sampled every
30 min. Here each cloud fraction value is calculated as the fraction of
data points with LWP greater than 20
Shortwave (left) and long-wave (right) top of the atmosphere radiative flux PDFs from CERES and the model for daytime periods for the region of the model domain. This is a combined PDF from the three separate snapshot overpass times of the CERES satellite for the model domain that were available for the simulation period: 10:24 LST (15:12 UTC) on 12 November (Terra satellite), 14:19 LST (19:06 UTC) on 12 November (Aqua satellite), and 11:07 am LST (15:55 UTC) on 13 November (Terra). For the model, the three closest available times were used: 15:00 and 19:00 UTC on 12 November 16:00 UTC on 13 November. Note that CERES–Aqua data are not available for the afternoon (local time) of 13 November. The model data were first coarse-grained to 20 km, which is the approximate resolution of the CERES data.
Figure
The low-aerosol case (CASIM-Ndvar-0.025) showed a much greater frequency of the lower cloud fractions and very few fully overcast data points, which is consistent with the results and discussion of the snapshot maps (discussed above).
A distribution plot is not possible for the nighttime where only coarse
resolution (0.25
Figure
The CASIM-Ndvar, CASIM-Ndvar-10 and Old-mphys runs all produce SW and LW
distributions that are relatively close to those observed. There are a few
discrepancies for the SW fluxes such as the observed peak in frequencies
between 500 and
700
Figure
As for Fig.
Regular radiosondes were released from the RV
For the first time shown (15:55 LST on 12 November, i.e. daytime), the
Profiles of potential temperature (top row) and water vapour
mixing ratio (bottom row) from radiosondes released from the RV
Also onboard the RV
Two-dimensional relative frequency plot for radar
reflectivity vs. height from the RV
The CASIM-Ndvar (control model) and CASIM-Ndvar-10 model results are
similar to each other, but show some significant differences compared to the
observations. The cloud from the model does not extend much above 1200 m, in
contrast to the observed cloud reaching 1460 m. This height difference
corresponds to approximately two model levels at these altitudes. Also, the
model reflectivities do not tend to reduce with height towards the cloud top
as they do in reality. The model also has a higher frequency of points at
lower altitudes compared to the observations, e.g. the maximum height of the
However, there are also some similarities; both the models and the
observations show a general increase in reflectivity in the lower regions of
the clouds, with a vertical gradient that is similar to that observed. Also,
the highest dBZ values reached (99.9th percentile of all data, including
cloud free regions) were around
A kilometre-scale regional model using cloud aerosol interacting microphysics has been used to simulate stratocumulus in the SE Pacific. It was seen that the introduction of the treatment of subgrid humidity (the cloud scheme) was important for simulating the observations. The range of aerosol loading used in the sensitivity studies resulted in droplet concentrations that included the observed range and captured extreme conditions for stratocumulus cloud. This provided insight into the relative importance of cloud brightening versus macrophysical changes such as cloud cover and LWP, which will be discussed further in this section.
We have shown that the UM regional model with the sub-grid cloud scheme
reproduced many important physical observations for the control case. The
shape and magnitude of the observed diurnal cycle of domain mean LWP was captured to within
Thus, there is good evidence that the model correctly captures the physical processes that are of first-order importance for producing a realistic stratocumulus deck. However, there are some model deficiencies, which we now discuss, that were highlighted in the comparison to the observations.
Section
BA12 found a similar daytime overestimate of LWP, but were only considering
the near-coastal region where the ship was located. The reason for this was
attributed to the sub-grid cloud scheme, which created too much cloud when
supplied with the observed thermodynamic profiles. Since we use the same
cloud fraction approach as BA12, albeit linked to a different microphysics
scheme, this may also be an issue in this work. However, we note that the run
with the old microphysics scheme (Old-mphys), which will be similar to the
runs in BA12 since the same microphysics and cloud schemes are used, shows a
domain-mean LWP value that is quite similar to that observed at the time of
the daytime minima. This suggests that the overestimate in the near-coastal
region that was observed in BA12 does not have a large impact on the overall
domain mean. In addition, Fig.
Another issue with the model was that the cloud-top heights were too low
compared to shipborne radar observations (Fig.
The fact that the modelled boundary layer height was too low is also
consistent with the overestimate of the LW TOA upwards fluxes during both the
daytime and the nighttime (Figs.
The results presented in this paper suggest that the UM regional model with a
relatively coarse horizontal and vertical resolution (1 km and
Figure
Summary plots of domain- and time-mean quantities for the different
model runs. The time average is weighted by the incoming SW TOA flux
time series to give extra weighting to times when the cloud properties
contribute to the SW flux, i.e. mainly in the daytime. The
This variation in response is due to the influence of aerosol on the suppression of rain. As shown in Fig.
The simulations in A04 also showed that once precipitation had been
completely suppressed, LWP tended to decrease, with further
Cloud fraction generally only increases between the CASIM-Ndvar-0.025 and
CASIM-Ndvar-0.1 runs, indicating that the change in LWP between those runs is
due to an increase in both
Thus, the cloud fraction exhibits a step change, which only occurs at very
low
Since the impact on SW
Estimated individual contributions to changes in the shortwave
upwelling TOA radiation flux (
The results indicate that the cloud-albedo effect (i.e. the change due to
For these simulations we introduced a sub-grid cloud scheme, which was shown
in Fig.
The credible simulation of closed-cell stratocumulus using a horizontal
resolution (
However, it is likely that a
Despite this, we note that LES simulations looking at such aspects have been
successfully performed, with little sensitivity to using a higher resolution,
when using
As discussed above, our fairly coarse vertical resolution is not adequate to
explicitly simulate the entrainment process; previous studies have shown
Stratocumulus clouds are very important for the earth's radiative budget. Aerosols form an integral part of the stratocumulus system and aerosol perturbations can significantly alter the radiative properties of these clouds. Thus, the realistic simulation of stratocumulus and its interaction with aerosol is vital for weather and climate predictions. In this paper we have addressed the question of whether the UM regional model with a new microphysics scheme and a newly coupled sub-grid cloud scheme can produce such a realistic representation of closed-cell stratocumulus and its response to aerosol when employing relatively coarse horizontal and vertical resolutions (1 km and 100 m at the inversion respectively).
We compared UM runs with the recent CASIM microphysics scheme, along with a
newly implemented sub-grid cloud scheme against a range of observational
metrics. The run with control aerosol concentrations captured the shape of
the domain-mean LWP diurnal cycle as observed by satellite microwave
instruments and agreed quantitatively for most of the diurnal cycle, being
within around 10
Daytime cloud fraction distributions from the model matched those from the
GOES-10 satellite very closely for the control and high-aerosol cases,
especially for cloud fraction values
Radar observations showed that the modelled and observed cloud depths were
quite similar (agreement within
Our model simulated a monotonic increase in the domain- and time-mean
shortwave TOA flux (SW
The in-cloud LWP (LWP
This study suggests that it may be necessary to employ a sub-grid cloud scheme within the UM model for stratocumulus, even at 1 km horizontal resolution. This finding may also apply to other models. Without the cloud scheme, mean LWP values were up to around 50 % too small, which is a difference that is comparable to that between the lowest and highest aerosol runs (representing an increase in aerosol by a factor of 400) during the first half of the simulation. It may also be the case that a cloud scheme needs to be considered for other aerosol–cloud interaction regional models in order to simulate realistic stratocumulus macrophysical properties.
The use of lower resolution paves the way for larger-area, longer-timescale
simulations than have been previously possible with very-high-resolution LES
models, or it may even allow global simulations. Domain size could be important
to allow the representation of large meteorological features and dynamical
feedbacks between large area features such as between open-cell and
non-open-cell regions, as well as for examining the wider-scale dynamical
impact of cloud–aerosol interactions. Thus, the realistic meteorology of our
model represents an important advantage over LES models, which are generally
run over smaller domains and employ idealized set-ups that do not allow
spatially inhomogeneous meteorological forcing
It is envisioned that the model described here will facilitate the development of sub-grid parameterizations for the aerosol–cloud interaction processes described above for the global model. The use of a nested high-resolution model embedded within an operational model framework, such as is employed here, will allow straightforward testing of the parameterizations against observations since the global and nested models share the same meteorology.
Raw model data are kept on tape archive available through
the JASMIN (
The sub-grid cloud scheme is based on the scheme described in
The assumed triangular-shaped PDF,
This sub-grid distribution of
Therefore, for there to be cloud requires that
The solution for
The mean liquid water mass mixing ratio is calculated as follows:
The solution to this is
Thus, the solution for
Advection operates upon the grid-box mean mixing ratio and number
concentrations of liquid water (denoted as
It is also possible to estimate a fraction over which precipitation is likely
to be present. For example
The RH
The observations used for the model evaluation in this paper are now described. See Table
There are several satellites that have microwave radiometer instruments
onboard and that provide coverage of the study region. These instruments
include AMSR-E (onboard Aqua), the SSMI–SSMIS instruments (onboard the f13,
f15, f16, and f17 satellites), TMI (onboard TRMM), and Windsat (onboard
Coriolis). These instruments report an overall average LWP for the cloudy and
clear parts of a given region (i.e. no attempt is made to separate cloudy and
clear pixels). We use the gridded daily data that are provided at
0.25
Microwave radiometers provide a fairly reliable estimate of cloud LWP, although some errors have been identified in the form of
non-zero values being reported in clear-sky situations. However, examining
AMSR-E data,
Data from the GOES-10 geostationary satellite are also extensively used in our
study. A special data set was created for the VOCALS field campaign that
covers the location and period of the simulations performed in this study.
The data were analysed as in
Estimates of cloud droplet concentrations are also made using the technique
described in
Long-wave (LW) and shortwave (SW) top-of-the-atmosphere (TOA) radiative fluxes
are obtained from the CERES instruments
The RV
The shortwave top-of-the-atmosphere (TOA) upwards radiative flux
(SW
The cloud albedo (
The shortwave upwards flux at cloud top (SW
Here we are assuming that the downward transmission is equal to the upward transmission.
Using these formulae, we calculated SW
D. P. Grosvenor, P. R. Field, and A. A. Hill developed the concepts and ideas for the direction of the paper. B. S. Shipway wrote the CASIM microphysics code. D. P. Grosvenor, A. A. Hill, and P. R. Field helped to further develop the CASIM microphysics code and performed the coupling of the sub-grid cloud scheme parameterization. D. P. Grosvenor, P. R. Field, and A. A. Hill helped set up and complete the model runs. D. P. Grosvenor performed the model data analysis, complied and analysed the observational data sets, and wrote the majority of the manuscript, along with input and comments by P. R. Field, A. A. Hill, and B. S. Shipway.
The authors declare that they have no conflict of interest.
This work was funded by both the University of Leeds and the NERC CLARIFY
grant number NE/L013479/1. We acknowledge use of the MONSooN system, a
collaborative facility supplied under the Joint Weather and Climate Research
Programme, a strategic partnership between the Met Office and the Natural
Environment Research Council. The GOES-10 and the RV