ASRAdvances in Science and ResearchASRAdv. Sci. Res.1992-0636Copernicus PublicationsGöttingen, Germany10.5194/asr-15-81-2018Comparison of radiation parametrizations within the HARMONIE–AROME NWP modelHARMONIE radiation comparisonRontuLauralaura.rontu@fmi.fihttps://orcid.org/0000-0003-1215-1546LindforsAnders V.https://orcid.org/0000-0001-9305-0864Finnish Meteorological Institute, Helsinki, FinlandLaura Rontu (laura.rontu@fmi.fi)22May20181581906February201824April201826April2018This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/This article is available from https://asr.copernicus.org/articles/15/81/2018/asr-15-81-2018.htmlThe full text article is available as a PDF file from https://asr.copernicus.org/articles/15/81/2018/asr-15-81-2018.pdf
Downwelling shortwave radiation at the surface (SWDS, global
solar radiation flux), given by three different parametrization schemes, was
compared to observations in the HARMONIE–AROME numerical weather
prediction (NWP) model experiments over Finland in spring 2017. Simulated
fluxes agreed well with each other and with the observations in the clear-sky
cases. In the cloudy-sky conditions, all schemes tended to underestimate SWDS
at the daily level, as compared to the measurements. Large local and temporal
differences between the model results and observations were seen, related to
the variations and uncertainty of the predicted cloud properties.
The results suggest a possibility to benefit from the use of different
radiative transfer parametrizations in a NWP model to obtain perturbations
for the fine-resolution ensemble prediction systems. In addition, we
recommend usage of the global radiation observations for the standard
validation of the NWP models.
Introduction
Future numerical weather prediction (NWP) models will increasingly be
devoted to very high-resolution and rapid updates due to the needs of
forecasting details in short timescales. In order to account for the details
of the cloud–aerosol–radiation and surface–radiation interactions in the
high-resolution forecasting systems, fast but physically based radiative
transfer parametrizations are necessary. In view of predictability challenges
at high resolution it is desirable to apply probabilistic methods even at the
short forecast ranges. Application of various radiation schemes may provide
the ensemble prediction systems with realistic physics perturbations.
In response to the ongoing rapid development of the solar energy sector, the
capability of NWP models to predict observed solar shortwave (SW) radiation
conditions at the surface has been put under scrutiny in recent studies
. Taking a step further,
NWP models are also being applied for predicting the “energy weather”. In
case of solar energy, this means forecasting the potential solar photovoltaic
energy production that corresponds to the weather conditions predicted by the
NWP e.g.. For the development of the
solar energetics, observational data of downwelling shortwave radiation at
the surface (SWDS) distribution are
increasingly needed and measurement stations are being set up globally.
Observed radiation fluxes offer a possibility to validate NWP model results
not only for the energy meteorology but also for general purposes
, or with respect to particular contributing factors
such as clouds . Both solar and terrestrial radiation
fluxes are related to the humidity and cloud physical properties, and terrestrial
also to the air temperature. Observed and predicted downwelling radiation
fluxes represent approximately the same spatial and temporal scales and are
thus directly comparable. This is less true for e.g. the observed and
predicted cloud cover or screen-level temperature that are routinely used for
verification of the weather forecasts. However, rapid variations in the solar
radiation fluxes on timescales of minutes, mostly related to the small-scale
cloud variability, remain unresolved by the kilometre-scale NWP models. For
model–observation comparisons, hourly and daily averaged observations are
thus expected to be the most suitable.
Validation of radiation output from a 3-D NWP model against the radiation
observations is useful for understanding the behaviour of the radiation
parametrizations and their influence on the NWP results in interaction with
all other simulated physical processes. Intercomparison of various
parametrization schemes within a single NWP model – instead of the comparison
of different NWP models containing specific radiation schemes – enables an
equal framework also for their validation against the observations.
In this study, we report intercomparison of three alternative radiation
schemes that have been made available within the HARMONIE–AROME NWP model
(based on version 40h1)
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 (http://hirlam.org, last
access: 14 May 2018) and ALADIN (http://www.cnrm-game-meteo.fr/aladin/,
last access: 14 May 2018) consortia. The acronym HARMONIE (HIRLAM ALADIN
Regional Mesoscale Operational NWP in Europe) denotes the specific
configuration of the ALADIN–HIRLAM system that is maintained by the HIRLAM
consortium. The dynamical core and physical parametrizations of
HARMONIE–AROME are based on AROME, the
high-resolution limited-area model originally developed at
Météo-France .
and compare
the results to the global radiation measurements over Finland during
spring 2017. The aim of the study is to reveal and understand the differences
of the model results due to the different radiation parametrizations,
applying the full 3-D HARMONIE–AROME experiments.
Preliminary studies of this kind were reported by ,
and .
They found local and temporal differences of the NWP results due to the
different radiation parametrizations and suggested that these were mainly
related to the cloud variations and the uncertainties of cloud forecast. Here
we search for confirmation of the preliminary findings before suggesting
introduction of the three radiation schemes into operational usage within
HARMONIE–AROME. In particular, we would like to understand the possible
systematic differences in the model results due to application of radiation
parametrizations of different levels of complexity. Can we rely on every
scheme in spite of the possible differences? We expect to see local and
temporal variations due to the different parametrizations, especially with
respect to cloud–radiation interactions. Is it possible to benefit from these
differences when developing an ensemble forecasting system?
This article is outlined as follows: Sect. documents the
IFSRADIA, ACRANEB and HLRADIA radiative transfer schemes applied.
Section presents the spring 2017 comparisons:
observations and HARMONIE–AROME experiments as well as the diagnostic methods
used for intercomparison. Section presents and analyses the
results and Sect. concludes the study with a summary and outlook.
Radiation parametrizations of HARMONIE–AROME
Three schemes are available for radiative transfer parametrization within a
development version of HARMONIE–AROME (based on version 40h1): the default
IFS radiation , denoted hereafter as IFSRADIA, and the
single spectral interval schemes ACRANEB v.2 (,
hereafter denoted as ACRANEB) and HLRADIA
, which can be run at high temporal and spatial
resolutions at the expense of high spectral resolution.
The tasks, input and output of every radiation scheme within HARMONIE–AROME
are schematically depicted in Fig. . Radiation schemes
estimate the radiative heating in the atmosphere due to the vertical
divergence of the net longwave (LW, terrestrial) and net SW
(solar) radiation fluxes. The radiative heating is a source term in the
thermodynamics equation in the model and influences the development of
atmospheric temperatures and the evolution of clouds. At the surface level,
radiation parametrizations provide the model with the downward (LWDS, SWDS)
and upward (LWUS, SWUS) LW and SW radiation fluxes. These are part of the
surface energy balance and a lower boundary condition for the calculation of
atmospheric radiation transfer. Atmospheric gas composition, aerosol and
cloud liquid and ice particle mass distribution and optical properties are
used as input for the radiative transfer calculations at each time step in
every grid cell of the 3-D model. The radiative properties of the surface
(i.e. surface temperature, albedo and emissivity) are also required as input
to the radiation schemes.
Parametrization of the radiative transfer. qv, qi, ql, qs and qg refer
to specific content (kg kg-1 in a grid cell) of water vapour, cloud
ice, liquid and precipitating snow and graupel, respectively.
IFSRADIA
By default, a version of IFSRADIA applied before 2007 and based on cycle 25R
Sect. 2.2 is applied for the radiative transfer
calculations in the HARMONIE–AROME forecast model. It has 6 spectral
intervals in SW range between 0.2 and 12.195 µm and
16 in LW from 3.08 to 1000 µm. Cloud optical
properties are based on grid-scale temperature, cloud cover, liquid water and
ice crystal content and parametrized cloud particle effective radius.
Climatological fields of ozone and aerosol are used together with the
predicted water vapour content and prescribed values of the rest of
atmospheric gas concentrations. By default, this scheme is called every
15th minute during the model integration.
ACRANEB
ACRANEB radiation parametrization has been used in the ALADIN NWP model
since the 1990s. Its renewed version was introduced
also to HARMONIE–AROME in 2014. This is a broadband scheme with one spectral
band for SW and another for LW. The optical properties of atmospheric gases,
cloud and aerosol particles and the surface are derived from the same input
as for IFSRADIA. ACRANEB includes advanced treatment of LW interactions
between the atmospheric layers resolved by the NWP model, The intermittency
in time can be configured as requested by the NWP model setup. By default,
the cloud–radiation interactions are fully accounted for at each time step
while the impact of atmospheric gaseous components is calculated less frequently.
HLRADIA
This scheme originally comes from the HIRLAM NWP model
. A pioneering study by
suggested a fast radiation scheme for mesoscale NWP models in which the
radiative transfer was heavily parametrized in order to make the scheme very
fast for short-range, limited-area NWP use. This was achieved using one
vertical loop for both the LW and SW spectral intervals. This results in
simplified treatment of radiation interactions between atmospheric (cloud)
layers. HLRADIA has been used for operational weather prediction since 1994
. The scheme was implemented into
HARMONIE–AROME and its latest version is documented by
. HLRADIA is always called every time step. Input data
of the atmospheric gaseous components, cloud liquid and ice concentrations
are the same as for IFRADIA and ACRANEB while aerosol and ozone impacts are
approximated with constant coefficients for both the SW and LW intervals.
Model–observation comparisons in spring 2017
The period March–April–May (MAM) 2017 over Finland was chosen for the
model–observation intercomparison. Especially in May, the weather in
Scandinavia was dominated by a cold Arctic airflow. Convective clouds formed
over the land areas heated by the Sun and light snowfall was frequent until
the end of May in Finland. Over the cold sea and lake areas, clear skies were
prevalent. The composite Fig. illustrates the cloud
distribution during the 10-day period from 7 to 16 May, as seen in the images
of the VIIRS instrument onboard Suomi NPP polar-orbiting satellite
(https://lance.modaps.eosdis.nasa.gov/ cgi-bin/imagery/viirs.cgi, last
access: 14 May 2018).
In these conditions, comparing the coastal and inland global radiation
observations to the model output was expected to reveal interesting local
differences while the averaged verification statistics of the screen-level
variables were expected to show only minor differences.
VIIRS images from 7 to 16 May, satellite overpasses around midday
local time in this area. An example of forecasts valid at the 10 May will be
discussed in Sect. .
Observations
A map of the global radiation measurement stations used in this study
is shown in Fig. . These stations belong to the
solar radiation measurement network of the Finnish Meteorological
Institute (FMI), where global radiation is measured using ventilated
Kipp and Zonen CM11 secondary standard pyranometers. The instruments
are calibrated yearly or every second year. The data have been tested
using the quality assurance procedures defined for the Baseline
Surface Radiation Network , with minor modifications
to better suit Finnish conditions. In this study, hourly values of the
global radiation were used. Based on a more detailed analysis of the
Swedish radiation measurement network , the
uncertainty of these hourly values is estimated to be roughly 4 %, except
for low Sun elevations when larger uncertainty is expected.
Location of global radiation measurement stations in Finland. The
marked stations Helsinki-Kumpula (60.203∘ N, 24.961∘ E),
Utö (59.779∘ N, 21.375∘ E) and Utsjoki
(69.756∘ N, 27.007∘ E) are referred to in
Sect. .
Experiment setup
HARMONIE experiments run for MAM 2017 are summarized in
Table . In addition to the use of the different radiation
schemes, only minor changes with the respect to the default settings
were applied. Cloud liquid droplet and ice crystal
mass, along with 80 % of the precipitating graupel mass (specific content in
kg/kg per grid cell at each time step) were given as input to all three
radiation schemes. Inclusion of the precipitating solid particles (graupel,
snow) but assuming the same optical properties for them as for pristine ice
crystals has only been motivated empirically and
is expected to influence differently each of the three radiation schemes.
Here, addition of only 80 % of graupel and no snow was chosen as a
compromise for testing. Aerosol optical depth (AOD at 550 nm), based on
2003–2011 CAMS climatology , was used as input for
IFSRADIA and ACRANEB instead of the default Tegen AOD ,
while the HLRADIA used constant coefficients to account for aerosol
absorption and scattering .
HARMONIE experiments for MAM 2017.
DomainFinlandModel horizontal/vertical resolution2.5 km/65 levelsHARMONIE version40h1.radiationRadiation schemesIFSRADIA, ACRANEB, HLRADIAData assimilationDefault atmospheric (3DVAR) and surface analysisLateral boundariesECMWF forecastForecastup to +27 h initiated every 3 h for 1 March–31 MayDiagnostics
Model–observation intercomparisons included standard verification against the
screen-level temperature (T2m) and total cloud cover for each month of
MAM 2017. Comparison of the predicted daily and hourly global radiation
fluxes (SWDS) at selected measurement stations in Finland was done for the
same 3-month period. In addition, the experiment results were compared to
each other. For this, the monthly mean accumulated SWDS and LWDS as well as
the average instantaneous cloud condensate content and T2m were
considered, all based on +24 h forecasts starting at midnight or midday.
Results representing a typical day of evolving convection, 10 May 2017,
are demonstrated separately.
Monthly mean SWDS for May 2017, based on accumulated flux by the
+24 h forecasts started every 00:00 UTC (W m-2). Upper row
panels: (a) ACRANEB, (b) IFSRADIA and (c) their
difference. Lower row panels: (a) HLRADIA, (b) IFSRADIA and
(c) their difference. Minimum, maximum and mean values are shown
under the colour scales for each subfigure. Note that for clarity the same
IFSRADIA figure is shown in the middle of both panels.
ResultsForecast radiation fluxes and weather parameters
The standard station verification of T2m and the total cloud cover
showed a small bias, standard deviation error and minor differences between
the experiments over the study area during the 3-month periods (not
shown). As expected, these indicators tend to smooth out local and temporal
features and are thus less suitable for detailed studies related to the
impact of different physical parametrizations. However, we can conclude that
the use of the different radiation schemes did not lead to significant
changes in model quality as measured with T2m and cloudiness.
Monthly mean SWDS for May 2017 resulting from the application of IFSRADIA,
ACRANEB and HLRADIA and the difference of ACRANEB and HLRADIA from IFSRADIA
is shown in Fig. ; the LWDS is shown in
Fig. . Compared to HARMONIE–AROME, which used IFSRADIA, the
broadband schemes ACRANEB and HLRADIA tended to overestimate SWDS by 4 and
12 W m-2, respectively. Usage of ACRANEB results in LWDS which was on
average 2 W m-2 larger than that by IFSRADIA, while HLRADIA usage results
in 9 W m-2 smaller LWDS compared to IFSRADIA. The cloud liquid water
path of the ACRANEB experiment was 0.016 g m-2 smaller than that of the
IFSRADIA experiment, while HLRADIA experiment showed a larger deviation,
0.064 g m-2 smaller mean value than IFSRADIA.
As in Fig. but for LWDS.
HARMONIE forecast SWDS (W m-2) vs. observed global
radiation daily averaged from 00:00 UTC+24 h for MAM 2017:
Utö (a) and Utsjoki (b). Observations are shown with
cyan dots, the forecasts with lines: IFSRADIA is blue, ACRANEB is red and
HLRADIA is green.
The larger SWDS and smaller LWDS due to HLRADIA usage were related to more
transparent clouds. For ACRANEB, the main difference from IFSRADIA in SWDS
seems to come from the Baltic Sea area while for HLRADIA the (less cloudy
than the IFSRADIA experiment) land areas seem to be the main source of the
SWDS difference. For LWDS, HLRADIA values were systematically smaller than
those due to IFSRADIA, also with the maximum difference over the eastern land
area. At the monthly level, the mean differences and areal variations of both
SW and LW downwelling radiation fluxes were thus related to the cloud
properties and their variations. Next, we will compare the details of the
predicted SWDS to the observations over land and sea areas.
Global radiation at the measurement stations
Time series of the forecast SWDS vs. the observed global radiation daily
averages for the whole MAM period are shown in Fig. for the
southernmost measurement station Utö, representing open sea conditions, and
for the northernmost station Utsjoki, representing Arctic land area
environment. The forecast values by the different experiments follow each
other more closely than they follow the observed values. Usage of HLRADIA
seems to lead to the largest SWDS and IFSRADIA to the smallest. The observed
daily averages tend to be lower than the forecast ones, especially when the
fluxes are smaller due to clouds and lower solar elevation. Most probably the
differences between the observed and forecast SWDS are due to the differences
in observed and simulated clouds as already indicated by the comparisons in
Sect. . However, when the solar elevation is small and
cloudy conditions prevail, also the observation uncertainty may influence the
comparison (Sect. ). The Utö and Utsjoki examples were
representative among all stations for this period (not shown).
Hourly SWDS forecasts, based on the +3 to +6 h forecasts initiated every
3 h, are compared to hourly observations for the period from 8 to 16 May
in Fig. . During this week, evolution of convection and its
inhibition over cold sea and lake areas were evident (see the satellite
images in Fig. ). This is seen especially clearly on 10 May.
Utö and Helsinki-Kumpula measurements were selected for comparison.
The influence of convective clouds on SWDS is seen 8–11 and 15 May in
Kumpula, while in Utö clear skies prevailed all days but 15 May
(Fig. ). The difference between the radiation
parametrizations showed up during the cloudy-sky cases while the predicted
global radiation flux was very close to observed during the clear-sky cases.
In these cases, the maximum values were slightly underestimated by all
experiments compared to observations.
HARMONIE forecast SWDS (W m-2) hourly averaged from
00:00 UTC+04–03, +05–+04 and +06–+05 h vs. observed hourly
global radiation for 8–16 May 2017: Utö (a) and
Helsinki-Kumpula (b). Observations are shown with cyan dots, the
forecasts with lines: IFSRADIA is blue, ACRANEB is red and HLRADIA is
green.
The difference between HARMONIE forecasts using ACRANEB and HLRADIA from
those using IFSRADIA is further demonstrated by the maps for 10 May
(Figs. and ), which depict the
differences of predicted SWDS, LWDS, T2m and total cloud cover for
ACRANEB–IFSRADIA and HLRADIA–IFSRADIA forecasts valid at 12:00 UTC
(2017050912+24 h). Note that the radiation fluxes are accumulated during the
forecast while T2m and total cloud cover represent instantaneous values
at 12:00 UTC. The local differences are most clearly seen for the screen-level
temperature and the cloud cover which both show a spotty structure. In
addition, the daily average SWDS shows a systematic larger-scale
overestimation by ACRANEB (+8 W m-2 averaged over the experiment domain)
and HLRADIA (+12 W m-2). An underestimation of LWDS (-13 W m-2) by
HLRADIA as compared to IFSRADIA is seen, while the ACRANEB result
(+3 W m-2) was close to IFSRADIA. Correspondingly, the area-averaged
T2m and total cloud cover were slightly overestimated for both ACRANEB
and HLRADIA as compared to IFSRADIA.
For this +24h period, the average observed SWDS over all Finnish measurement
stations was ca. 200 W m-2, while the average SWDS forecast over the land
areas of Finland varied from 231 W m-2 (IFSRADIA) to 236 W m-2 (ACRANEB)
and 243 W m-2 (HLRADIA). This indicates similar overestimation
of SWDS by the model that was seen in Fig. for the selected
stations. However, the averages of measured and simulated fluxes are not
directly comparable due to the different domains represented by the
observations and by the model.
Difference of HARMONIE forecasts 2017050912+24 h valid at
2017051012 using ACRANEB vs. IFSRADIA: (a)T2m
(∘C), (b) total cloud cover [0, 1], (c) average
LWDS (W m-2) and (d) 24 h average SWDS (W m-2).
As in Fig. but for HLRADIA vs. IFSRADIA.
Conclusions and outlook
Global radiation (SWDS) fluxes due to three radiation schemes – IFSRADIA,
ACRANEB and HLRADIA – showed similar results and the time series at
observation stations agreed generally well with the measurements. Typically,
+24h averaged model results were overestimated as compared to the daily
mean observations, presumably due to the inaccuracies in the cloud
simulation. The relative difference was the largest when the flux was small.
According to the hourly observations, slight underestimation of SWDS, based
on the +3–+6 h HARMONIE forecasts, occurred only in very clear, clean cases.
Generally, the agreement between the model and observations was better than
in the comparison of daily averages. The reason is again most probably
related to the cloud uncertainties, which would influence the shorter
forecasts less than the longer ones.
In cloudy-sky cases, there were large temporal and spatial variations
of SWDS and LWDS between the schemes. Differences between observed and
simulated SWDS could be locally large. Averaged over the domain, T2m and
cloud fraction showed only small differences, which are not easy to detect or
interpret based on the standard station verification.
The cloud liquid water mass, resulting from the application of HLRADIA, seems
underestimated when compared to IFSRADIA and ACRANEB. This suggests stronger
cloud–radiation interactions in HARMONIE when using HLRADIA. Correspondingly,
SWDS became overestimated and LWDS underestimated by HLRADIA compared to
IFSRADIA/ACRANEB. Further comparisons, which would use also cloud liquid and
ice content observations, are needed to understand the interactions better.
We found a systematic difference of LW downwelling radiation fluxes
between HLRADIA on one hand and IFSRADIA and ACRANEB on the other hand. A
further study using LWDS measurements is needed to confirm whether this difference
indicates a need for serious improvements in the HLRADIA LW
parametrizations (as suggested by ).
To summarize the results in terms of the questions stated in the
introduction: we found systematic difference between the observed and
predicted daily global radiation by all three schemes. In this respect all
schemes showed up equally reliable. We saw local and temporal variations
between the schemes and observations, related to cloudiness and
cloud–radiation interactions. Dedicated experiments should be set up to study
whether these variations would give sufficient spread for an ensemble system,
influencing the important output variables like solar energy potential or the
near-surface weather characteristics.
In this study we used regular global radiation observations from the FMI
solar radiation measurement network. A simple comparison of time series
turned out to be useful for the model–observation comparisons. Inclusion of
SWDS observations in the operational NWP verification system would allow
systematic comparisons and application of more advanced verification scores
on a regular basis.
Underlying research data consist of hourly
global radiation measurements picked from the FMI climate data base and
HARMONIE–AROME forecasts for the period MAM 2017. Attached to this article
are files containing point values picked from the +3–+6 h forecasts of
the three experiments and the corresponding SWDS measurements. Selected
HARMONIE–AROME forecast grib files from the three experiments (ca. 20 GB of
data extracted from the experiment output) are available from the authors
upon request.
The Supplement related to this article is available online at https://doi.org/10.5194/asr-15-81-2018-supplement.
The authors declare that they have no conflict of
interest.
This article is part of the special issue “17th EMS Annual
Meeting: European Conference for Applied Meteorology and Climatology 2017”.
It is a result of the EMS Annual Meeting: European Conference for Applied
Meteorology and Climatology 2017, Dublin, Ireland, 4–8 September 2017.
Acknowledgements
The support of the International HIRLAM-C and ALADIN programmes
is acknowledged. We thank the Strategic Research Council at the Academy of
Finland for funding through the BCDC Energy project (decision 292854 and
314167). Edited by: Emily Gleeson
Reviewed by: two anonymous referees
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