Input files

This chapter provides an overview on the necessary input files to run the EMEP/MSC-W model. A complete set of input files is provided as part of the EMEP/MSC-W Open Source release to allow model runs for the meteorological year 2015. Table 2 lists the input files.

In the latest release, meteorology is provided for 2 different model domains and resolutions:

• EECCA domain with a horizontal resolution of 50x50 km2 (at 60°N), on polar stereographic projection, and 20 vertical levels;

• EMEP01 domain with a 0.1x0.1 degrees on long-lat projection, and 34 vertical levels.

Download the input via the catalog tool (sec-ModelCode) as follows:

# download 2018 meteorology for the EMEP01 domain
catalog.py -Y 2018 -m --met-domain EMEP0201

# download other input files
catalog.py --input

The meteorology files will be placed under EMEP_MSC-W_model.v5.5.OpenSource/meteo2018/EMEP0201/, and the remaining input files will be placed under EMEP_MSC-W_model.v5.5.OpenSource/input/

This are all input files needed to run the EMEP/MSC-W model, except the aircraft emissions (AircraftEmis_FL.nc), and forest fire emissions (FINN_ForestFireEmis_2018.nc). See sections emisair and emisff for details about these emissions data.

IMPORTANT:

The input data available in the EMEP/MSC-W Open Source Web site should be appropriately acknowledged when used for model runs. If nothing else is specified according to references further in this chapter, please acknowledge EMEP/MSC-W in any use of these data.

Table 2 List of input data files

Data	Name	Format
Meteorology data	meteoYYYY/GRID
Meteorology	meteoYYYYMMDD.nc (365+1 files)	netCDF [1]
Degree-day factor	DegreeDayFactors.nc	netCDF
Other Input files	input/
Global Ozone	Logan_P.nc	netCDF [2]
BVOC emissions	EMEP_EuroBVOC.nc	netCDF
Landuse	glc2000xCLMf18.nc and Landuse_PS_5km_LC.nc	netCDF
N depositions	AnnualNdep_PS50x_EECCA2005_2009.nc or CAMS-GLOB-SOIL_Glb_0.5x0.5_soil_nox_v2.4clim_monthly.nc	netCDF
Road dust	RoadMap.nc and AVG_SMI_2005_2010.nc	netCDF [3]
Aircraft emissions	AircraftEmis_FL.nc	netCDF [3]
Surface Pressure	SurfacePressure.nc	netCDF [3]
Forest Fire	FINN_ForestFireEmis_YYYY.nc	netCDF [3]
Dust files	Soil_Tegen.nc	netCDF [3]
	SoilTypes_IFS.nc	netCDF [3]
Emissions	GNFREmis_EMEP01_2020_27062023.nc (regional, \(0.1\times 0.1\) lon-lat)	netCDF [3]
Vertical level distribution	Vertical_levels20_EC.txt (for 20lev runs)	ASCII
Time factors for monthly emissions	cams_tempo_v3_2_month.POLL (7 files)	ASCII [4]
Time factors for daily emissions	cams_tempo_v3_2_week.POLL (7 files)	ASCII [4]
Time factors for hourly emissions	cams_tempo_v3_2_hour.POLL (7 files)	ASCII [4]
Natural SO2	DMS_SOLAS.nc	netCDF
Volcanoes	columnsource_emission.csv_2023	ASCII
	columnsource_location.csv_2023	ASCII
Lightning emissions	lt21-nox.datMM (12 files)	ASCII [1]
Emissions speciation	emissplit.defaults.POLL	ASCII [4]
	emissplit.specials.POLL	ASCII [4] [3]
Emission factors for scenario runs	femis.dat	ASCII
Photo-dissociation rates	unified_cjx/* (8 files)	ASCII [6]
	OzoneObs_v3/* (216 files)	ASCII [5]
Landuse definitions	Inputs_LandDefs.csv	ASCII
Stomatal conductance	Inputs_DO3SE.csv	ASCII
Sites locations for surface output	sites.dat	ASCII
Sondes locations for vertical output	sondes.dat	ASCII

Footnotes

[1] (1,2)

YYYY: year, MM: month, DD: day.

[2]

O₃ boundary condition data in 30 levels.

[3] (1,2,3,4,5,6,7,8)

Optional, in most cases.

[4] (1,2,3,4,5)

POLL: pollutant type (NH₃, CO, NO_x, SO_x, NMVOC, PM_2.5 and PM_co).

[5]

MONTHLY: monthly mean gridded stratospheric ozone and temperature data for years between 2005-2021. Also includes monthly climatologies constructed based on the years of available measurements.

[6]

MOLECULAR: spectral data on aerosol and cloud radiative scattering and absorption, as well as molecular data on reaction-specific cross-section and quantum yields.

NetCDF files

Meteorology

The daily meteorological input data (meteoYYYYMMDD.nc, where YYYY is year, MM is month and DD is day) used for the EMEP/MSC-W Model are based on forecast experiment runs with the Integrated Forecast System (IFS), a global operational forecasting model from the European Centre for Medium-Range Weather Forecasts (ECMWF).

The IFS forecasts has been run by MSC-W as independent experiments on the HPCs at ECMWF with special requests on some output parameters. The meteorological fields are retrieved on a \(0.1^\circ\times 0.1^\circ\) longitude latitude coordinates and interpolated to \(0.3^\circ\times 0.2^\circ\). Vertically, the fields on 60 eta (\(\eta\)) levels from the IFS model are interpolated onto the 37 EMEP eta (\(\eta\)) levels. The meteorology is prepared into 37 eta levels since the model is under test for a finer vertical resolution.

The open source code is released with 20 eta levels and to make the model read the meteorology properly, a description of the 20 vertical sigma levels is needed. This is provided in an ASCII file called Vertical_levels20_EC.txt together with the other input data (Table 2). The version of the IFS model used for preparing these fields for 2018 and earlier years, Cycle 40r1, is documented in https://www.ecmwf.int/en/forecasts/documentation-and-support/changes-ecmwf-model/cycle-40r1/cycle-40r1. 2019 and later years are based on Cycle 48r1, described in https://confluence.ecmwf.int/display/FCST/Implementation+of+IFS+Cycle+48r1. Some verification and description of 2018 meteorological fields are given in Chapter 2 of the EMEP Status Report 1/2020 https://www.emep.int/mscw/mscw_publications.html#2020.

Acknowledgement:

ECMWF, met.no

Table 3 Input meteorological data used in the EMEP/MSC-W Model

Parameter	Unit	Description
3D fields		for 37 \(\eta\)
\(u_wind, v_wind\)	\(m/s\)	Horizontal wind velocity components
\(etadot`\)	\(Pa/s`\)	Vertical velocity in \(\eta\) coords
\(specific_humidity\)	\(kg/kg\)	Specific humidity
\(potential_temperature\)	\(K\)	Potential temperature
\(cloudwater\)	\(kg/kg\)	Cloud water
\(cloudice\)	\(kg/kg\)	Ice cloud water
\(3D_cloudcover\)	\(\%\)	3D Cloud cover
\(convective_updraft_flux\)	\(kg/m^2/s\)	Convective updraft flux
\(convective_downdraft_flux\)	\(kg/m^2/s\)	Convective downdraft flux
\(precipitation\)	\(kg/m^2\)	Precipitation
2D fields		for surface
\(surface_pressure\)	\(hPa\)	Surface pressure
\(temperature_2m\)	\(K\)	Temperature at \(2 m\) height
\(relative_humidity_2m\)	\(\%\)	Relative humidity at \(2 m\) height
\(surface_flux_sensible_heat\)	\(W/m^2\)	Surface flux of sensible heat
\(surface_flux_latent_heat\)	\(W/m^2\)	Surface flux of latent heat
\(surface_stress\)	\(N/m^2\)	Surface stress
\(sea_surface_temperature\)	\(K\)	Sea surface temperature
\(soil_water_content\)	\(m^3/m^3\)	Soil water content
\(deep_soil_water_content\)	\(m^3/m^3\)	Deep soil water content
\(large_scale_precipitations\)	\(m/s\)	Large scale precipitation
\(convective_precipitations\)	\(m/s\)	Convective precipitation
\(snow_depth\)	\(m\)	Snow depth
\(fraction_of_ice\)	\(\%\)	Fraction of ice
\(SMI1\)		Soil moisture index level 1
\(SMI3\)		Soil moisture index level 3
\(pblh`\)	\(m\)	Planetary boundary layer height
\(u10, v10\)	\(m/s\)	Wind at \(10 m\) height

Gridded emissions

Gridded emissions in NetCDF care be used in conjunction with sector definitions. See section sec-emission-own-sectors Defining own sectors and sec-emission-cv-format Country Variable (CV) format

The main advantage of NetCDF emissions is that all the information about the data (projection, units) is given in the same file. This allows the code to reproject the emissions to any grid projection on the fly. It is easy to visualize the emissions of one country with simple tools, like ncview. The data is simple to interpret and it is possible to add new countries to an existing file (with appropriate tools).

Global Ozone

Initial concentration of ozone are required in order to initialize the model runs. Boundary conditions along the sides of the model domain and at the top of the domain are then required as the model is running.

The Logan_P.nc file contains monthly averaged fields in NetCDF format. The initial and background concentrations are based on the Logan (1998) climatology. The Logan climatology is scaled on run time according to the Mace Head measurements as described in Simpson et al. (2003). For a number of other species, background/initial conditions are set within the model using functions based on observations (Simpson et al., 2003 and Fagerli et al., 2004).

BVOC emissions

Biogenic emissions of isoprene and monoterpene are calculated in the model as a function of temperature and solar radiation, using the landuse datasets. The light and temperature dependencies follow the ideas proposed in Guenther et al (1993,1995), the first step in the emission processing is to define ‘standard’ emission potentials, which give the emissions of particular land-covers at standard environmental conditions (\(30^\circ C\) and photosynthetically active radiation of 1000 \(\mu mole/m^2/s\)).

European forests are treated in most detail. For these, BVOC emission potentials have been created from the the map of forest species generated by Koeble and Seufert (2001). This work provided maps for 115 tree species in 30 European countries, based upon a compilation of data from the ICP-forest network. The emission potentials for each species are as given in Simpson et al., 2012, and have been aggregated into the four default forest classes used by EMEP over Europe (DF, CF, NF, BF). The NetCDF file EMEP_EuroBVOC.nc provides the aggregated emission potenitals for these 4 categories. These emission potentials have unit \(\mu g/m^2/h\), and refer to emissions per area of the appropriate forest category.

On the global scale, new landcover maps were created as a combination of GLC2000 and Community Land Model (CLM) data as described in Simpson et al., 2017. The default emission potentials are given for these extra CLM categories, and for any non-forest land-cover on Europe in the file Inputs_LandDefs.csv. The underlying emission potentials, land-cover data bases, and model coding have however changed substantially since model version v.2011-06. The new approach is documented in Simpson et al., 2012 and Simpson et al. 2017.

Landuse

Landuse data are required for modelling boundary layer processes (i.e. dry deposition, turbulent diffusion). The EMEP/MSC-W model can accept landuse data from any data set covering the whole of the domain, providing reasonable resolution of the vegetation categories. Gridded data sets providing these landuse categories across the EMEP domain have been created based on the data from the Stockholm Environment Institute at York (SEI-Y) and from the Coordinating Center for Effects (CCE). 16 basic landuse classes have been identified for use in the deposition module in the model, and three additional “fake” landuse classes are used for providing results for integrated assessment modeling and effects work.

There are two NetCDF files included, one file Landuse_PS_5km_LC.nc on 5 km resolution over the EMEP domain, and a global LanduseGLC.nc which combines data from GLC2000 with the Community Land Model (CLM). The different landuse types are desribed in Simpson et al (2012) and Simpson et al. (2017).

Degree-day factor

Domestic combustion which contribute to a large part of GNFR C (SNAP 2), varies on the daily mean temperature. The variation is based on the heating degree-day concept. These degree days are pre-calculated for each day and stored in the file DegreeDayFactors.nc. See Simpson et al. (2012) section 6.1.2.

NO_x depositions

Areas with high NO deposition loads have greater soil-NO emissions. To include this in the model, a NetCDF file where pre-calculated N-depositions are included. The file made by the results from the EMEP/MSC-W model runs over a 5-year period.

Road Dust

Road traffic produces dust. These can be handled as separate emission inputs in the EMEP/MSC-W model using the Emissions_mod.f90 module. To include road dust, set USES%ROADDUST=T in config_emep.nml. There are two files included in input data, RoadMap.nc and AVG_SMI_2005_2010.nc. RoadMap.nc include gridded roads and PM emissions over Europe, while the Soil Moisture Index (SMI) file AVG_SMI_2005_2010.nc used to estimate emissions is global. Hence road dust emissions can currently only be calculated for the European domain. However, some countries for which road dust is important (e.g., Scandinavian countries), reported emissions already include road dust. By default we therefore set USES%ROADDUST=F, with road dust as a separate emission source effectively being deprecated.

Aircraft emissions

In the EMEP/MSC-W model aircraft emissions are ‘ON’ by default. It can be switched ‘OFF’ by setting USES%AIRCRAFT_EMIS=F in config_emep.nml. When using aircraft emissions there are two options: Either the dataset provided by the EU-Framework Programme 6 Integrated Project QUANTIFY (http://www.pa.op.dlr.de/quantify), or the more recent CAMS-GLOB-AIR dataset which can be downloaded from the Atmosphere Data Store (https://ads.atmosphere.copernicus.eu/cdsapp#!/dataset/cams-global-emission-inventories?tab=form). However, before using these data a protocol has to be signed, which is why the data file can not be provided directly on the EMEP MSC-W Open Source website. Since rv4.39, CAMS-GLOB-AIR has been the default dataset. Registering at the Atmosphere Data Store is straightforward (https://ads.atmosphere.copernicus.eu/user/register?destination=/cdsapp) (If you rather want to use older QUANTIFY dataset go to http://www.pa.op.dlr.de/quantify, click on ‘QUANTIFY emission inventories and scenarios’, and then on ‘Register’. That page will provide information about the registration process and the protocol that has to be signed. Once you are registered, click ‘Login’ and provide user name and password. On the new page, search for ‘Emissions for EMEP’, which links directly to the Readme file and the emission data file in NetCDF format. Download the emission data file and place it in the input folder.)

Natural SO₂

Natural SO₂ emissions (dimethylsulfide (DMS) from sea) are provided as monthly gridded files. The values are computed taking into account sea surface temperature and wind speed. Surface water concentrations of DMS (needed for the flux calculation) are taken from SOLAS (Surface Ocean Lower Atmosphere Study) and were downloaded from https://www.bodc.ac.uk/solas_integration/implementation_products/group1/dms/.

Surface Pressure

Unless aircraft emissions are switched ‘OFF’ by setting USES%AIRCRAFT_EMIS=F in config_emep.nml, in addition to the Aircraft Emission file, there will be need for a SurfacePressure.nc file, which is already in the /input folder. The NetCDF file consists of surface pressure fields for each of the months in 2008 called surface_pressure, and one field for the whole year called surface_pressure_year. All fields are given in Pa.

Forest Fire

Since model version rv3.9 (November 2011), daily emissions from forest and vegetation fires are taken from the “Fire INventory from NCAR version 1.0” (FINNv1, Wiedinmyer et al. 2011). Data are available from 2005, with daily resolution, on a fine \(1 km\times1 km\) grid. We store these data on a slightly coarser grid (\(0.2^\circ\times 0.2^\circ\)) globally for access by the EMEP MSC-W model. To include forest fire emissions set USES%FOREST_FIRES=.true. in config_emep.nml and download the 2012 GEOS-chem daily data http://bai.acom.ucar.edu/Data/fire/. The data needs to be stored with units mole/day in a NetCDF file called FINN_ForestFireEmis_2015.nc compatible with the ForestFire_mod.f90 module.

Dust files

The annual ASCII data for sand and clay fractions as well as the monthly data for boundary and initial conditions for dust from Sahara are replaced with a single NetCDF file Soil_Tegen.nc since 2013. This covers data for a global domain in \(0.5\times 0.5\) degree resolution.

The variables ‘sand’ and ‘clay’ gives the fraction (in %) of sand an clay in the soil for each grid cell over land.

The files are used by the module DustProd_mod.f90, which calculates windblown dust emissions from soil erosion. Note that the parametrization is still in the development and testing phase, and is by default ‘turned off’. To include it in the model calculations, set USE_DUST=.true. in config_emep.nml. The user is recommended to read carefully documentation and comments in the module DustProd_mod.f90.

There is also a possibility to include boundary and initial conditions for dust from Sahara. The input file gives monthly dust mixing ratios (MM - month, e.g. 01, 02, 03,…) for fine and coarse dust from Sahara. The files are based on calculations from a global CTM at the University of Oslo for 2000. To include Saharan dust, set USE_SAHARA=.true. in config_emep.nml.

Another source for dust is an arid surface. This is accounted for by soilmosture calculations in DustProd_mod.f90. Together with Soil Water Index from the meteorology files and permanent wilting point (pwp) from SoilTypes_IFS.nc. This file is global and NetCDF. See Simpson et al. (2012) section 6.10.

ASCII files

Volcanoes

Emissions from volcanic passive degassing of SO₂ are included for the active Italian volcanoes, Etna, Vulcano and Stromboli, and based upon the officially submitted data. To consider these volcanic emissions, we need to feed the locations and heights of volcanoes into the model. The input file columnsource_location.csv_2023 contains the geographical coordinates (latitudes and longitudes) and the heights (in meters) of the included volcanoes, while columnsource_emission.csv_2023 contains the emission parameters.

Since 2010 the EMEP/MSC-W model has also been used to model the transport of ash and SO₂ from volcanic eruptions. In addition to data for passive degassing of SO₂, the above two input files also contain locations and emission parameters for two recent eruptions of Icelandic volcanoes (Eyjafjallajökull in 2010 and Grimsvötn in 2011). In order to include emissions from these eruptions one needs to set USES%ASH=.true. in config_emep.nml.

Time factors for emissions

The default emission time factors are a mixtue of CAMS-TEMPO v3.2 and v4.1 regional clilatological time factors, which are briefly descrived on Simpson et al., 2023. Monthly emission time factors for non-livestock agricultural emissions (GNFR Sector L) are tanken from CAMS-REG-TEMPO v4.1 and from v3.2 for all other sctors and frequencies.

The emission time factors can be changed in config_emep.nml. Listing 1 shows the relevant default values as they would be written on config_emep.nml, and Listing 2 shows an example configuration using time factors included with version 5.0 release. For runs outsude Europe, Listing 3 shows how configure the model for using gridded montly factors from CAMS-TEMPO v3.2/v4.1 descrived on Simpson et al., 2023.

Monthly, daily and hourly emission time factors can be specified on serparate ASCII files for the 7 compounds (CO, NH₃, NO_x, PM_2.5, PM_co, SO_x and VOC). On all time factor files the first two columns in the files contrain the country code (ISO02, http://www.emep.int/grid/country_numbers.txt) and the the GNFR sector code as defined on Listing 33.

In the monthly files, defined by MonthlyFacFile, the time factors corresponding for January to December are listed on columnss 3 to 14. These time factors are interpolated according to whether the “current” simulation day is in the first or second half of the month. For days in the first half of the month, the monthly factor is a combination of the factor of the previous month and the current month. For days in the second half of the month, the monthly factor combines the factor of the current and the next month (for details, see the source code).

In the daily files, defined by DailyFacFile, the time factors for Monday to Sunday are listed from columns 4 to 9. The monthly timefactors are normalized in such a way that when combined with the daily timefactors, the total emission stays the same.

In the hourly file, defined by HourlyFacFile, column 3 represents the day of the week (1 for Monday to 7 for Sunday) and time factors for 00 UTC to 23 UTC are listed on columns 4 to 27.

Before version 5.5, hourly time factors were defined on a single file, including factors for each of the eleven SNAP sectors for every hour (the columns) for each day of the week, see Simpson et al. (2012) section 6.1.2. Listing 2 shows an example configuration using emission time factors from a previous release.

Listing 1 Default configuration for CAMS-TEMPO emission time factors.

  timeFacs%Monthly = 'CAMS_TEMPO_CLIM',
  MonthlyFacFile   = 'DataDir/Timefactors/CAMS_TEMPO/cams_tempo_v3_2/GapFilled/cams_tempo_v3_2_month.POLL',

  timeFacs%Daily   = 'CAMS_TEMPO_CLIM',
  DailyFacFile     = 'DataDir/Timefactors/CAMS_TEMPO/cams_tempo_v3_2/GapFilled/cams_tempo_v3_2_week.POLL',

  timeFacs%Hourly  = 'CAMS_TEMPO_CLIM',
  HourlyFacFile    = 'DataDir/Timefactors/CAMS_TEMPO/cams_tempo_v3_2/GapFilled/cams_tempo_v3_2_hour.POLL',

Listing 2 Alternative configuration for emission time factors from version 5.0 release.

  timeFacs%Monthly = 'GENEMIS',
  MonthlyFacFile   = 'DataDir/MonthlyFacs_eclipse_V6b_snap_xJun2012/MonthlyFacs.POLL',

  timeFacs%Daily   = 'Legacy', ! anything other than 'CAMS_TEMPO_CLIM' will work
  DailyFacFile     = 'DataDir/DailyFac.POLL',

  timeFacs%Hourly  = 'Legacy', ! anything other than 'CAMS_TEMPO_CLIM' will work
  HourlyFacFile    = 'DataDir/HourlyFacs.INERIS',

Listing 3 Alternative configuration for CAMS-TEMPO gridded monthly emission time factors.

  timeFacs%Monthly      = 'GRIDDED',
  GriddedMonthlyFacFile = 'DataDir/Timefactors/CAMS_TEMPO/CAMS_TEMPO_GLOB4emep_v2024-1.nc',

Emission heights

In previous versions the emission height distributions was given in a separate file. Now it is part of the code, and can also be modified by the users using config_emep.nml setting (see section “defining own sectors).

A set of vertical distribution for different sectors are predefined in the model. The release heights are defined as a set of fractions released into predefined layers.

The release height definitions are independent of the layers used by the model.

There are 8 predefined release heights distributions. Those can also be defined through the config_emep.nml setting. The following will give exactly the same distributions as the predefined. You can then modify the values, or add new defined distributions.

Listing 4 Default definition of emission height distributions

Emis_Zlevels(1:)20.0,   50.0,   92.0,  184.0,  324.0,  522.0,  781.0, 1106.0,
Emis_h(1:,1) = 0.000,  0.000,  0.000,  0.003,  0.147,  0.400,  0.300,  0.150,
Emis_h(1:,2) = 1.000,  0.000,  0.000,  0.000,  0.000,  0.000,  0.000,  0.000,
Emis_h(1:,3) = 0.060,  0.067,  0.093,  0.750,  0.030,  0.000,  0.000,  0.000,
Emis_h(1:,4) = 0.050,  0.063,  0.087,  0.700,  0.100,  0.000,  0.000,  0.000,
Emis_h(1:,5) = 0.020,  0.034,  0.046,  0.600,  0.300,  0.000,  0.000,  0.000,
Emis_h(1:,6) = 0.000,  0.000,  0.000,  0.410,  0.570,  0.020,  0.000,  0.000,
Emis_h(1:,7) = 0.200,  0.300,  0.020,  0.044,  0.066,  0.094,  0.123,  0.153,
Emis_h(1:,8) = 0.200,  0.800,  0.000,  0.000,  0.000,  0.000,  0.000,  0.000,

The Emis_Zlevels defines the height of the layer boundaries for emissions in meters. (Standard atmosphere is assumed to transform those in Pressure by the model). The first layers is from surface to 20 meters, the second layer from 20 to 50 m… until the eigth and last layer which runs from 781 to 1106 meters.

For example sectors defined with the height index “1”, will release nothing in the three lowest layers, 0.3% into the fourth layer, 14.7% into the fifth layer etc.

The layers defined in Emis_h are independent from the layers used in the model run and do not need to be adapted if the number of model layers is modified. The actual resulting distribution of emissions into model layers is computed by the model and will be shown in the standard output.

Emission factor for scenario runs

Scenario run in the case of the EMEP/MSC-W model means a run to test the impact of one or more pollutants from a particular country.

Emission factors are applied to specified countries and emission sectors and can be set by changing the ASCII file femis.dat. This file can be changed by the users according to their needs. See the Source Receptor (SR) Runs section for details.

Vertical_levels20_EC.txt

Defines the vertical model layers. The numbers in Vertical_levels20_EC.txt correspond to the “A” and “B” coefficients of the hybrid (:math:``eta`) coordinates (P=A+B*Psurf).

Close to the surface, A should be small, and higher up we should use pressure levels. Then there is a gradual transition from surface to pressure levels.

If the file is not provided, the meteorological vertical levels are used. In principle the model levels can be completely different, but it is more sensible to define layer boundaries that match the meteorological levels.

NB: it is important not to define a lowest layer thinner than about 45 meters; the deposition scheme will fail if the middle of the lowest layer is smaller than the highest defined vegetation.

Chemical speciation of emissions

Many of the emission files give emissions of a group of compounds, e.g. NO_x includes NO+|NO2|, and VOC can include many compounds. The information needed to retrieve emissions of individual compounds from these the gridded files is given in files labelled emissplit.defaults.POLL or emissplit.specials.POLL, where POLL can be NO_x, VOC, etc.

The defaults file give the emission split for each sector split index (one per row, with second index being the sector split index), which is applied to all countries by default. For VOC this split was derived from the UK inventory of Passant (2002), as part of the chemical comparison project of Hayman et al. (2011).

The specials files are in general optional, and can be used to specify speciation for particular countries or sectors. The 1^st column specifies the country code of interest, the second the sector index.

If forest fires are used, then the file emissplit.specials.voc is required (not optional), and the country-code 101 used to specify the VOC speciation of forest fires in this file.

Lightning emissions

Emissions of NO_x from lightning are included in the model as monthly averages on T21 (\(5.65^\circ\times 5.65^\circ\)) resolution (Køhler et al., 1995). The lightning emissions are defined on a \(64\times 32\) grid with 17 vertical levels, with global coverage, and are provided as 12 ASCII files lightningMM.dat.

Landuse definitions

For the vegetative landuse categories where stomatal modelling is undertaken, the start and end of the growing season (SGS, EGS, in days) must be specified. The calculation of SGS and EGS with respect to latitude is done in the module LandDefs_mod.f90. The parameters needed to specify the development of the leaf area index (LAI) within the growing season are given in the ASCII file Inputs_LandDefs.csv. For more information, see chapter 5 of the EMEP Status Report 1/2003 Part I (Simpson et al., 2003).

The file, designed to be opened with excel or gnumeric, contains a header briefly explaining the contents of the 14 columns. The first three columns are representing the landuse name, code (which are consistent with those in Landuse.Input file) and type (grouping of the landuse classes). The fourth column (PFT) gives a plant-functional type code (for future use), the fifth gives the maximum height of vegetation (m), the sixth indicates albedo (%) and the seventh indicates possible source of NH_x (0 off/1 on, curently not used). Columns 8 to 11 define the growing season (day number), column 12 and 13 lists the LAI minimum and maximum (\(m^2/m^2\)) and columns 14 and 15 defines the length of the LAI increase and decline periods (no. of days). Finally, the last four columns give default values of foliar biomass and biogenic VOC emission potentials. See Simpson et al., (2012) for details.

Stomatal conductance

Parameters for the stomatal conductance model, deposition of O₃ and stomatal exchange (DO3SE) must be specified. That are based upon the ideas in Emberson et al., 2000, and are discussed in Simpson and Emberson, 2006 and Tuovinen et al. 2004.

The ASCII file Inputs_DO3SE.csv provides land-phenology data of each landuse type for stomatal conductance calculations. The data are summarised in Table 5.1 in Chapter 5 of the EMEP Status Report 1/2003 Part I (Simpson et al., 2003).

The file contains a header with the contents of the file, with different factors needed for each of the landuse classes used in the EMEP/MSC-W model. The first two columns represent the landuse code (which are consistent with those in Landuse.Input file) and name. The next 22 values are different phenology factors.

Photo-dissociation rates

The photo-dissociation rates (J-values) are calculated using the online Cloud-J v7.3e radiative transfer code (Prather, 2015), with the old system based on tabulated values being deprecated. Cloud-J calculates aerosol and cloud radiative scattering and reaction-specific photolysis rates at model run time, based on the instantaneous modeled abundance of radiatively active species. The implemention of Cloud-J in the EMEP model and the input files are described in detail in van Caspel et al. (2023).

The input files include molecular cross-section and quantum yield data (FJX_spec), determining the reaction rates of each individual photolysis reaction. For the photo-dissociation of tropospheric ozone, absorption of the relevant wavelengths by stratospheric ozone is important. Monthly mean overhead stratospheric ozone concentrations based on the MEGRIDOP dataset (Sofieva et al., 2021) are provided as separate input files, which are read in automatically when the model is configured to use these files (available between 2005-2021). However, by default the EMEP model uses climatological monthly mean files, which are provided as separate inputs.

Input files further include cloud and aerosol radiative scattering and absorption phase functions, as well as parameter fields representative of a climatological background atmosphere. Lastly, the input files include a file describing the mapping of photolysis rates to reactions present in the EMEP model chemistry (FJX_j2j.dat).

Site and Sonde files

The model provides a possibility for extra output data of surface concentration for a set of specified measurement site locations and concentrations for the vertical column above a set of specified locations. These site and sonde locations are listed in the ASCII files sites.dat and sondes.dat files. These files can be changed by the user, and provide the outputs described in sec-sitesonde.

Two main options are available for the output of ASCII files for comparison with measurements or detailed model analysis. These are

sites

output of surface concentrations for a set of specified measurement site locations.

sondes

output of concentrations for the vertical column above a set of specified locations.

Both sites and sondes are specified and handled in similar ways, in the module Sites_mod.f90, so we treat them both together below. Locations are specified in the input files sites.dat and sondes.dat. The files start with a description of its content followed by a list of the stations. For example, a sondes.dat input file may look like this: .. literalinclude:: sites.dat

caption:

Site location definition (sites.dat) example.

Listing 5 Site location definition, LatLonHrel Coords example.

# "Sites: names, locations, relative elevations"
# "lev: vertical coordinate m above local topography
: Units index
: Coords LatLonHrel
: DomainName NA
#
name ix iy lev #HEADERS
-    index index level #SKIP
#DATA:
DK0005R  54.74650  10.73616      10 !  Keldsnor (10m a.s.l, terrain 0m)
NO0002R  58.38853   8.25200     109 !  Birkenes_II (219m a.s.l, terrain 110m)
SE0013R  67.88333  21.06667     184 !  Esrange (475m a.s.l., terrain 291m)

Listing 6 Site location definition, LatLonZm Coords example.

# "Sites: names, locations, relative elevations"
# "lev: vertical coordinate m above local topography
: Units index
: Coords LatLonZ
: DomainName NA
#
name ix iy lev #HEADERS
-    index index level #SKIP
#DATA:
DK0005R  54.74650  10.73616      10 !  Keldsnor, 10m a.s.l
NO0002R  58.38853   8.25200     219 !  Birkenes_II, 219m a.s.l
SE0013R  67.88333  21.06667     475 !  Esrange, 475m a.s.l.

The first line in each file is a header with file content. Then, the contents are described in more detail. Text strings after # are just clarifying comments. ‘Area’, e.g., is the domain to which the stations belong, e.g. ‘Northern Hemisphere’.

Text after : is read in by the model:

Units

Either ‘deg’ (degrees) or ‘index’ (model grid indices).

Coords

Vertical coordinate system that is used in the model - see below.

The VertCoords system was changed in rv4.36, to allow several options. Specifying altitude rather than model coordinate is of course an obvious alternative to the model layer number that was previously used, but it is also easily mis-used and mis-understood too. For example, a site at 500m might need vertical profile and/or deposition correction if sitting on a 500m high plateau (hence it has a relative altitude of 0m, and should use iz=KMAX_MID), but if sitting on an isolated mountain in terrain of height 0m, the relative altitude would indeed to 500m and we should pick from some model level which represents that. Tricky! (Best might be to give station altitude and relative altitude in separate columns, so it is explicit at least.)

Briefly though, one can now set the “Coords” parameter (in the header of the sites.dat input file, used to be just “LatLong”) to be one of:

1. LatLonKdown - same as older LatLong, with lat/lon coordinates, then k-number with ground level being e.g. 20

2. LatLonZm - give lat, long, then altitude in metres. The model will then compare that altitude with the model’s topography, to estimate a relative altitude (Hrel). It then calculates which model layer corresponds to that altitude.

3. LatLonHrel - give lat, long, and then your own preferred relative altitude (Hrel). This relative altitude may be calculated by comparison to digital elevation model (see for example, Loibl, W.; Winiwarter, W.; Kopsca, A.; Zufger, J. & Baumann, R. Estimating the spatial distribution of ozone concentrations in complex terrain Atmos. Environ., 1994, 28, 2557-2566).

4. IJKdown - does everything in model’s i, j and k coordinates

In principle (3) should produce the best results, with relative altitudes calculated compared to local topography (e.g. < 5km). Option (3) also allows the same Hrel to be used regardless of the underlying meteo resolution. One can also get Hrel from the TOAR database for some sites (Schultz, MG, et al 2017 Tropospheric Ozone Assessment Report: Database and metrics data of global surface ozone observations. Elem Sci Anth, 5: 58, DOI: https://doi.org/10.1525/elementa.244).

However, testing of these systems against e.g. diunral profiles of ozone shows rather unpredictable results in some cases, and often just using the model’s surface concentrations procudes results which are as good as those based upon altitude. The new systems are very fliexble thouhg, and allow the user to explore different methodologies.

Both sites.dat and sondes.dat files are optional, but recommended. The species and meteorological data requested for site and sonde output are specified in Config_module.f90 by the use of arrays. Only a few met fields are defined so far but more can be added into Sites_mod.f90 as required.

The output files sites_2018.csv and sondes_2018.csv are comma separated files that can be read by excel. netcdf versions of these files are also provided, sites_2018.nc and sondes_2018.nc. If you include the whole year, or the 31^st December, sites_2019.csv and sondes_2019.csv are also included in the output.