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Commit b62e022a authored by Christoph Knote's avatar Christoph Knote
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Add high res option

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blueprints/highres_chemistry/VERSION 0 → 100644
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22
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blueprints/highres_chemistry/WRF_DOMAIN_PLOT_COAWST.png 0 → 100644
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blueprints/highres_chemistry/WRF_DOMAIN_PLOT_COAWST.png

80.7 KiB

blueprints/highres_chemistry/config.bash 0 → 100644
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#!/bin/bash
# ------------------------------------------------------------------------------
# WRFOTRON v 2.0b
# Christoph Knote (LMU Munich, Germany)
# 06/2016
# christoph.knote@lmu.de
# ------------------------------------------------------------------------------
# path to the WRFotron installation
chainDir=${HOME}/wrfotron
# --- Executable locations ---
# WPS installation directory
WPSDir=${WPS_SRC_PATH}
# WRF installation directory
WRFDir=${WRF_SRC_PATH}
# --- Input data settings ---
# path to geogrid input data
geogDir=/alcc/gpfs2/home/mbees/data/geog/
# meteo input
# Vtable for the chosen meteo input
metVtableFile=${WPS_SRC_PATH}/ungrib/Variable_Tables/Vtable.GFS
# time increment in hours
metInc=1
# full path to a met input file - you can use any "%<>" abbreviations known
# to the "date" command
metFilePattern="/alcc/gpfs2/home/mbees/data/meteo/GFS_OPR/GF%Y%m%d%H"
# example:
# "/glade/p/rda/data/ds083.2/grib2/%Y/%Y.%m/fnl_%Y%m%d_%H_00.grib2"
# --- Pre/Postprocessing settings ---
# prepararation script
preScriptPath=NONEXISTENT.bash
# postprocessing scripts (arbitrary)
postScriptPath=NONEXISTENT.bash
# postprocessing scripts (actions for each wrfout file)
postPerFileScriptPath=NONEXISTENT.bash
# --- Working directories ---
# where the WRF will be run (some fast, large disk like "scratch" or similar)
workDir=${SCRATCH}/WRF/work/
# where the unprocessed WRF output will be stored
stagingRootDir=${SCRATCH}/WRF/staging/
# where the WRF output will be stored
archiveRootDir=${SCRATCH}/archive/WRF/
# where the WRF restart files will be stored
restartRootDir=${SCRATCH}/WRF/restart/
# remove run directory after run is finished?
removeRunDir=false
# --- Chemistry ---
withChemistry=true
# WRF-Chem installation directory
WRFChemDir=${WRF_CHEM_SRC_PATH}
# path to utility executables
meganBioEmissBin=megan_bio_emiss
mozbcBin=mozbc
weselyBin=wesely
exo_coldensBin=exo_coldens
anthro_emisBin=anthro_emis
fire_emisBin=fire_emis
# path to Wesely and Exo_Coldens input data
wesColdensDataPath=${WESELY_EXO_COLDENS_DATA}
# path to MEGAN input data
MEGANdir=/alcc/gpfs2/home/mbees/data/emissions/biogenic/MEGAN
# use anthro_emiss or predefined files?
emissUseAnthroEmiss=false
# raw emission input - the files you read in with anthro_emiss
emissDir=/alcc/gpfs2/home/mbees/data/emissions/anthropogenic/EDGARv5/MOZART_MOSAIC
# emission conversion script for anthro_emis - must match emissions in emissDir
emissInpFile=emis_edgarv5_mozmos.inp
# year the emissions are valid for (for offset calculation)
emissYear=2015
# FINN fires
fireFilePattern="/alcc/gpfs2/home/mbees/data/emissions/fires/FINN/GLOB_MOZ4_%Y%j.txt"
fireInpFile=finn_fires.inp
# boundary condition input
chembcFilePattern="/alcc/gpfs2/home/mbees/data/chembc/WACCM/WACCM%Y%m%d"
chembcInpFile=waccm.inp
# TUV photolysis option 4 data file
TUVDataPath="/alcc/gpfs2/home/mbees/data/tuv/TUV.phot.bz2"
blueprints/highres_chemistry/emis_edgarv5_mozmos.inp 0 → 100644
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&CONTROL
domains = __domains__
anthro_dir = '__emissDir__'
src_file_prefix = 'edgar_v5_2015_'
src_file_suffix = '_0.1x0.1.nc'
src_names = 'CO(28)','NOx(30)','SO2(64)','NH3(17)','BC(12)','OC(12)','PM2.5(1)','PM10(1)','BENZENE(78)','BIGALK(72)','BIGENE(56)','C2H2(26)','C2H4(28)',
'C2H5OH(46)','C2H6(30)','C3H6(42)','C3H8(44)','CH2O(30)',
'CH3CHO(44)','CH3COCH3(58)','CH3OH(32)','CH3COOH(60)','HCOOH(46)',
'MEK(72)','TOLUENE(92)','XYLENES(106)'
sub_categories = 'TOTAL',
serial_output = .true.,
start_output_time = '__startDate__',
stop_output_time = '__startDate__',
output_interval = 3600,
data_yrs_offset = __emissYearOffset__,
emissions_zdim_stag = 1,
emis_map = 'CO->CO','NO->0.8*NOx','NO2->0.2*NOx','SO2->SO2','NH3->NH3','BIGALK->BIGALK','BIGENE->BIGENE',
'C2H4->C2H4','C2H5OH->C2H5OH','C2H6->C2H6','CH2O->CH2O','CH3CHO->CH3CHO',
'CH3COCH3->CH3COCH3','CH3OH->CH3OH','MEK->MEK','TOLUENE->TOLUENE',
'C3H6->C3H6','C3H8->C3H8','ISOP->0.0*CO','C10H16->0.0*CO',
'SULF->0.0*SO2','C2H2->0.00561790*CO','BENZENE->BENZENE','XYLENE->XYLENES',
'GLY->0.0*CO','MACR->0.0*CO','MGLY->0.0*CO','MVK->0.0*CO',
'HCOOH->0.0*CO','HONO->0.0*CO','VOCA->0.04*CO','VOCBB->0.0*CO',
'ECI(a)->0.1*BC','ECJ(a)->0.9*BC','ORGI(a)->0.1*OC','ORGJ(a)->0.9*OC','PM25I(a)->0.1*PM2.5',
'PM25J(a)->0.9*PM2.5','PM_10(a)->PM10 + -1.0*PM2.5','SO4I(a)->0.0*PM10','SO4J(a)->0.0*PM10','NO3I(a)->0.0*PM10',
'NO3J(a)->0.0*PM10','NH4I(a)->0.0*PM10','NH4J(a)->0.0*PM10','NAI(a)->0.0*PM10','NAJ(a)->0.0*PM10',
'CLI(a)->0.0*PM10','CLJ(a)->0.0*PM10','CO_A->CO','CO_BB->0.0*CO','ORGI_A(a)->0.0*PM10',
'ORGI_BB(a)->0.0*PM10','ORGJ_A(a)->0.0*PM10','ORGJ_BB(a)->0.0*PM10'
/
blueprints/highres_chemistry/exo_coldens.inp 0 → 100644
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&control
wrf_dir = './'
domains = __domains__,
/
blueprints/highres_chemistry/finn_fires.inp 0 → 100644
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&control
fire_directory = './'
fire_filename(1) = 'FINN_FIRES.txt'
start_date = '__startYear__-__startMonth__-__startDay__',
end_date = '__endYear__-__endMonth__-__endDay__',
Model = 'WRF',
wrf_directory = './',
domains = __domain__,
defaultUnits = 'molecules/cm^2/s',
FinnVers = '1.5',
wrf2fire_map = 'co -> CO', 'no -> NO', 'no2 -> NO2', 'so2 -> SO2',
'nh3 -> NH3', 'open -> BIGALD', 'bigalk -> BIGALK',
'bigene -> BIGENE', 'apin -> C10H16', 'c2h4 -> C2H4',
'c2h5oh -> C2H5OH', 'c2h6 -> C2H6', 'c3h6 -> C3H6',
'c3h8 -> C3H8', 'ch2o -> CH2O', 'ald -> CH3CHO',
'ch3cn -> CH3CN', 'ACET -> CH3COCH3', 'mgly -> CH3COCHO',
'ch3cooh -> CH3COOH', 'ch3oh -> CH3OH', 'cres -> CRESOL',
'glyald -> GLYALD', 'hcn -> HCN', 'acetol -> HYAC',
'isop -> ISOP', 'macr -> MACR', 'mek -> MEK', 'mvk -> MVK',
'toluene -> TOLUENE', 'hcooh -> HCOOH', 'c2h2 -> C2H2',
'oc_a01 -> 0.01*OC;aerosol', 'oc_a02 -> 0.09*OC;aerosol',
'oc_a03 -> 0.70*OC;aerosol', 'oc_a04 -> 0.20*OC;aerosol',
'bc_a01 -> 0.01*BC;aerosol', 'bc_a02 -> 0.09*BC;aerosol',
'bc_a03 -> 0.70*BC;aerosol', 'bc_a04 -> 0.20*BC;aerosol',
'oin_a04 -> 1.00*PM10+-1.00*PM25+-0.20*OC+-0.20*BC;aerosol',
'oin_a01 -> 0.01*PM25+-0.01*OC+-0.01*BC;aerosol',
'oin_a02 -> 0.09*PM25+-0.09*OC+-0.09*BC;aerosol',
'oin_a03 -> 0.90*PM25+-0.90*OC+-0.90*BC;aerosol'
/
blueprints/highres_chemistry/iofields.chem 0 → 100644
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+:h:0:alt
+:h:0:gsw
+:h:0:extaer1
+:h:0:extaer2
+:h:0:extaer3
+:h:0:extaer4
+:h:0:tauaer1
+:h:0:tauaer2
+:h:0:tauaer3
+:h:0:tauaer4
+:h:0:gaer1
+:h:0:gaer2
+:h:0:gaer3
+:h:0:gaer4
+:h:0:waer1
+:h:0:waer2
+:h:0:waer3
+:h:0:waer4
+:h:0:brnch_rto
+:h:0:ccn1
blueprints/highres_chemistry/iofields.met 0 → 100644
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+:h:0:alt
+:h:0:gsw
+:h:0:tke
+:h:0:SWDDIF
\ No newline at end of file
blueprints/highres_chemistry/megan_bio_emiss.inp 0 → 100644
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&control
domains = __domains__,
start_lai_mnth = 1,
end_lai_mnth = 12,
wrf_dir = '.',
megan_dir = '__MEGANdir__'
/
blueprints/highres_chemistry/mozart4.inp 0 → 100644
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&control
do_ic = __do_ic__,
do_bc = __do_bc__,
domain = __domain__,
dir_wrf = './',
dir_moz = './',
fn_moz = 'moz0000.nc',
moz_var_suffix='',
spc_map =
'o3 -> O3',
'no -> NO',
'no2 -> NO2',
'hno3 -> HNO3',
'ho -> OH',
'ho2 -> HO2',
'h2o2 -> H2O2',
'so2 -> SO2',
'co -> CO',
'hcho -> CH2O',
'c2h4 -> C2H4',
'c2h6 -> C2H6',
'c3h6 -> C3H6',
'c3h8 -> C3H8',
'ald -> CH3CHO',
'acet -> CH3COCH3',
'ch3cooh -> CH3COOH',
'ch3oh -> CH3OH',
'ch3ooh -> CH3OOH',
'pan -> PAN',
'macr -> MACR',
'mvk -> MVK',
'c2h5oh -> C2H5OH',
!'etooh -> C2H5OOH',
'bigene -> BIGENE',
'bigalk -> BIGALK',
'tol -> TOLUENE',
'benzene -> BENZENE',
'xylenes -> XYLENES',
! http://www.atmos-chem-phys.net/12/7215/2012/acp-12-7215-2012.pdf Fig 6
'apin -> 0.75*MTERP',
'bpin -> 0.25*MTERP',
'isopr -> ISOP',
!
! aerosols
!
'oc_a01->0.1216*pom_a1+0.9886*soa1_a2+0.1216*soa1_a1+0.9886*soa2_a2+ 0.1216*soa2_a1+0.9886*soa3_a2+0.1216*soa3_a1+0.9886*soa4_a2+0.1216*soa4_a1+ 0.9886*soa5_a2+ 0.1216*soa5_a1;1.e9',
'oc_a02->0.7618*pom_a1+0.0114*soa1_a2+0.7618*soa1_a1+0.0114*soa2_a2+ 0.7618*soa2_a1+0.0114*soa3_a2+0.7618*soa3_a1+0.0114*soa4_a2+0.7618*soa4_a1+ 0.0114*soa5_a2+ 0.7618*soa5_a1;1.e9',
'oc_a03->0.1164*pom_a1+0.0000*soa1_a2+0.1164*soa1_a1+0.0000*soa2_a2+ 0.1164*soa2_a1+0.0000*soa3_a2+0.1164*soa3_a1+0.0000*soa4_a2+0.1164*soa4_a1+ 0.0000*soa5_a2+ 0.1164*soa5_a1;1.e9',
'oc_a04->0.0002*pom_a1+0.0000*soa1_a2+0.0002*soa1_a1+0.0000*soa2_a2+ 0.0002*soa2_a1+0.0000*soa3_a2+0.0002*soa3_a1+0.0000*soa4_a2+0.0002*soa4_a1+ 0.0000*soa5_a2+ 0.0002*soa5_a1;1.e9',
'bc_a01->0.1216*bc_a1+0.1216*bc_a4;1.e9',
'bc_a02->0.7618*bc_a1+0.7618*bc_a4;1.e9',
'bc_a03->0.1164*bc_a1+0.1164*bc_a4;1.e9',
'bc_a04->0.0002*bc_a1+0.0002*bc_a4;1.e9',
'so4_a01->0.9886*so4_a2+0.1216*so4_a1+0.0000*so4_a3;1.e9',
'so4_a02->0.0114*so4_a2+0.7618*so4_a1+0.0000*so4_a3;1.e9',
'so4_a03->0.0000*so4_a2+0.1164*so4_a1+0.0995*so4_a3;1.e9',
'so4_a04->0.0000*so4_a2+0.0002*so4_a1+0.9003*so4_a3;1.e9',
'nh4_a01->0.1856*so4_a2+0.0050*so4_a1+0.0000*so4_a3;1.e9',
'nh4_a02->0.0021*so4_a2+0.0930*so4_a1+0.0000*so4_a3;1.e9',
'nh4_a03->0.0000*so4_a2+0.0203*so4_a1+0.0186*so4_a3;1.e9',
'nh4_a04->0.0000*so4_a2+0.0000*so4_a1+0.1690*so4_a3;1.e9',
'no3_a01->0.0000*so4_a2+0.0000*so4_a1+0.0000*so4_a3;1.e9',
'no3_a02->0.0000*so4_a2+0.0000*so4_a1+0.0000*so4_a3;1.e9',
'no3_a03->0.0000*so4_a2+0.0000*so4_a1+0.0000*so4_a3;1.e9',
'no3_a04->0.0000*so4_a2+0.0000*so4_a1+0.0000*so4_a3;1.e9',
'na_a01->0.3889*ncl_a2+0.0479*ncl_a1+0.0000*ncl_a3;1.e9',
'na_a02->0.0045*ncl_a2+0.2997*ncl_a1+0.0000*ncl_a3;1.e9',
'na_a03->0.0000*ncl_a2+0.0458*ncl_a1+0.0391*ncl_a3;1.e9',
'na_a04->0.0000*ncl_a2+0.0000*ncl_a1+0.3542*ncl_a3;1.e9',
'cl_a01->0.5996*ncl_a2+0.0737*ncl_a1+0.0000*ncl_a3;1.e9',
'cl_a02->0.0068*ncl_a2+0.4621*ncl_a1+0.0000*ncl_a3;1.e9',
'cl_a03->0.0000*ncl_a2+0.0709*ncl_a1+0.0604*ncl_a3;1.e9',
'cl_a04->0.0000*ncl_a2+0.0001*ncl_a1+0.5462*ncl_a3;1.e9',
'oin_a01->0.9886*dst_a2+0.1216*dst_a1+0.0000*dst_a3;1.e9',
'oin_a02->0.0114*dst_a2+0.7618*dst_a1+0.0002*dst_a3;1.e9',
'oin_a03->0.0000*dst_a2+0.1164*dst_a1+0.0995*dst_a3;1.e9',
'oin_a04->0.0000*dst_a2+0.0002*dst_a1+0.9003*dst_a3;1.e9',
'num_a01->0.9996*num_a2+0.7135*num_a1+0.0000*num_a3;1.0',
'num_a02->0.0004*num_a2+0.2470*num_a1+0.2118*num_a3;1.0',
'num_a03->0.0000*num_a2+0.0016*num_a1+0.6258*num_a3;1.0',
'num_a04->0.0000*num_a2+0.0000*num_a1+0.3501*num_a3;1.0',
/
blueprints/highres_chemistry/mozbc.inp 0 → 100644
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&control
do_ic = __do_ic__,
do_bc = __do_bc__,
domain = __domain__,
dir_wrf = './',
dir_moz = './',
fn_moz = 'moz0000.nc',
moz_var_suffix='',
def_missing_var = .true.
spc_map = 'o3 -> O3', 'n2o -> N2O', 'no -> NO',
'no2 -> NO2', 'nh3 -> NH3', 'hno3 -> HNO3', 'hno4 -> HO2NO2', 'n2o5 -> N2O5', 'h2o2 -> H2O2',
'ch4 -> CH4', 'co -> CO', 'ch3ooh -> CH3OOH',
'hcho -> CH2O', 'ch3oh -> CH3OH', 'c2h4 -> C2H4',
'ald -> CH3CHO', 'acet -> CH3COCH3', 'mgly -> CH3COCHO',
'pan -> PAN', 'mpan -> MPAN', 'macr -> MACR',
'mvk -> MVK', 'c2h6 -> C2H6', 'c3h6 -> C3H6', 'c3h8 -> C3H8', 'c2h5oh -> C2H5OH', 'c10h16 -> MTERP',
'isopr -> ISOP','acetol -> HYAC', 'mek -> MEK',
'bigene -> BIGENE', 'bigalk -> BIGALK',
'tol -> TOLUENE+BENZENE+XYLENES', 'cres -> CRESOL', 'dms -> DMS', 'so2 -> SO2',
'oc_a01->0.12*pom_a1+0.99*soa1_a2+0.12*soa1_a1+0.99*soa2_a2+0.12*soa2_a1+0.99*soa3_a2+0.12*soa3_a1+0.99*soa4_a2+0.12*soa4_a1+0.99*soa5_a2+0.12*soa5_a1;1.e9',
'oc_a02->0.76*pom_a1+0.01*soa1_a2+0.76*soa1_a1+0.01*soa2_a2+0.76*soa2_a1+0.01*soa3_a2+0.76*soa3_a1+0.01*soa4_a2+0.76*soa4_a1+0.01*soa5_a2+0.76*soa5_a1;1.e9',
'oc_a03->0.12*pom_a1+0.00*soa1_a2+0.12*soa1_a1+0.00*soa2_a2+0.12*soa2_a1+0.00*soa3_a2+0.12*soa3_a1+0.00*soa4_a2+0.12*soa4_a1+0.00*soa5_a2+0.12*soa5_a1;1.e9',
'oc_a04->0.00*pom_a1+0.00*soa1_a2+0.00*soa1_a1+0.00*soa2_a2+0.00*soa2_a1+0.00*soa3_a2+0.00*soa3_a1+0.00*soa4_a2+0.00*soa4_a1+0.00*soa5_a2+0.00*soa5_a1;1.e9',
'bc_a01->0.1216*bc_a1+0.1216*bc_a4;1.e9',
'bc_a02->0.7618*bc_a1+0.7618*bc_a4;1.e9',
'bc_a03->0.1164*bc_a1+0.1164*bc_a4;1.e9',
'bc_a04->0.0002*bc_a1+0.0002*bc_a4;1.e9',
'so4_a01->0.9886*so4_a2+0.1216*so4_a1+0.0000*so4_a3;1.e9',
'so4_a02->0.0114*so4_a2+0.7618*so4_a1+0.0002*so4_a3;1.e9',
'so4_a03->0.0000*so4_a2+0.1216*so4_a1+0.0995*so4_a3;1.e9',
'so4_a04->0.0000*so4_a2+0.0002*so4_a1+0.9003*so4_a3;1.e9',
'nh4_a01->0.1856*so4_a2+0.0050*so4_a1+0.0000*so4_a3;1.e9',
'nh4_a02->0.0021*so4_a2+0.0930*so4_a1+0.0000*so4_a3;1.e9',
'nh4_a03->0.0000*so4_a2+0.0203*so4_a1+0.0186*so4_a3;1.e9',
'nh4_a04->0.0000*so4_a2+0.0000*so4_a1+0.1690*so4_a3;1.e9',
'no3_a01->0.0000*so4_a2+0.0000*so4_a1+0.0000*so4_a3;1.e9',
'no3_a02->0.0000*so4_a2+0.0000*so4_a1+0.0000*so4_a3;1.e9',
'no3_a03->0.0000*so4_a2+0.0000*so4_a1+0.0000*so4_a3;1.e9',
'no3_a04->0.0000*so4_a2+0.0000*so4_a1+0.0000*so4_a3;1.e9',
'na_a01->0.3889*ncl_a2+0.0479*ncl_a1+0.0000*ncl_a3;1.e9',
'na_a02->0.0045*ncl_a2+0.2997*ncl_a1+0.0000*ncl_a3;1.e9',
'na_a03->0.0000*ncl_a2+0.0458*ncl_a1+0.0391*ncl_a3;1.e9',
'na_a04->0.0000*ncl_a2+0.0000*ncl_a1+0.3542*ncl_a3;1.e9',
'cl_a01->0.5995*ncl_a2+0.0737*ncl_a1+0.0000*ncl_a3;1.e9',
'cl_a02->0.0068*ncl_a2+0.4621*ncl_a1+0.0000*ncl_a3;1.e9',
'cl_a03->0.0000*ncl_a2+0.0709*ncl_a1+0.0604*ncl_a3;1.e9',
'cl_a04->0.0000*ncl_a2+0.0001*ncl_a1+0.5462*ncl_a3;1.e9',
'oin_a01->0.9886*dst_a2+0.1216*dst_a1+0.0000*dst_a3;1.e9',
'oin_a02->0.0114*dst_a2+0.7618*dst_a1+0.0002*dst_a3;1.e9',
'oin_a03->0.0000*dst_a2+0.1216*dst_a1+0.0995*dst_a3;1.e9',
'oin_a04->0.0000*dst_a2+0.0002*dst_a1+0.9003*dst_a3;1.e9',
'num_a01->0.9996*num_a2+0.7135*num_a1+0.0000*num_a3;1.0',
'num_a02->0.0004*num_a2+0.2847*num_a1+0.0239*num_a3;1.0',
'num_a03->0.0000*num_a2+0.0016*num_a1+0.6258*num_a3;1.0',
'num_a04->0.0000*num_a2+0.0000*num_a1+0.3501*num_a3;1.0',
/
blueprints/highres_chemistry/namelist.chem 0 → 100644
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&chem
kemit = 1,
chem_opt = 202, 202, 202,
bioemdt = 12., 4., 4.,
photdt = 12., 4., 4.,
chemdt = 12., 4., 4.,
io_style_emissions = 2,
emiss_inpt_opt = 102, 102, 102,
emiss_opt = 10, 10, 10,
chem_in_opt = 1, 2, 2,
phot_opt = 4, 4, 4,
gas_drydep_opt = 1, 1, 1,
aer_drydep_opt = 1, 1, 1,
bio_emiss_opt = 3, 3, 3,
gas_bc_opt = 1, 1, 1,
gas_ic_opt = 1, 1, 1,
aer_bc_opt = 1, 1, 1,
aer_ic_opt = 1, 1, 1,
gaschem_onoff = 1, 1, 1,
aerchem_onoff = 1, 1, 1,
wetscav_onoff = 1, 1, 1,
cldchem_onoff = 0, 0, 0,
vertmix_onoff = 1, 1, 1,
chem_conv_tr = 1, 1, 1,
conv_tr_wetscav = 1, 1, 1,
conv_tr_aqchem = 1, 1, 1,
seas_opt = 2,
dust_opt = 3,
dmsemis_opt = 1,
aer_ra_feedback = 1, 1, 1,
aer_op_opt = 1, 1, 1,
ne_area = 500,
opt_pars_out = 1,
have_bcs_chem = .true.,
have_bcs_upper = .false.,
biomass_burn_opt = 5, 5, 5,
plumerisefire_frq = 30, 30, 30,
scale_fire_emiss = .true., .true., .true.,
n2o5_hetchem = 1,
lnox_opt = 1, 1, 1,
diagnostic_chem = 0, 0, 0,
diagnostic_dep = 0, 0, 0,
/
blueprints/highres_chemistry/namelist.wps 0 → 100644
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&share
wrf_core = 'ARW',
max_dom = 3,
start_date = '__startDate__','__startDate__','__startDate__'
end_date = '__endDate__','__startDate__','__startDate__',
interval_seconds = __metIncSec__,
io_form_geogrid = 2,
/
&geogrid
parent_id = 1, 1, 2,
parent_grid_ratio = 1, 9, 5,
i_parent_start = 1, 96, 69,
j_parent_start = 1, 75, 74,
e_we = 185, 172, 151,
e_sn = 186, 163, 156,
! geog_data_res = 'modis_fpar+modis_lai+modis_lakes+modis_30s+modis_15s+30s', 'modis_fpar+modis_lai+modis_lakes+modis_30s+modis_15s+30s',
! 'modis_fpar+modis_lai+modis_lakes+modis_30s+modis_15s+30s',
dx = 20000,
dy = 20000,
map_proj = 'lambert',
ref_lat = 50.0,
ref_lon = 7.5,
truelat1 = 30.0,
truelat2 = 60.0,
stand_lon = 7.5,
geog_data_path = '__geogDir__'
/
&ungrib
out_format = 'WPS',
prefix = 'FILE',
/
&metgrid
fg_name = 'FILE',
constants_name = 'TAVGSFC',
io_form_metgrid = 2,
/
blueprints/highres_chemistry/namelist.wrf 0 → 100644
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&time_control
start_year = __startYear__, __startYear__, __startYear__,
start_month = __startMonth__, __startMonth__, __startMonth__,
start_day = __startDay__, __startDay__, __startDay__,
start_hour = __startHour__, __startHour__, __startHour__,
start_minute = 00, 00, 00,
start_second = 00, 00, 00,
end_year = __endYear__, __endYear__, __endYear__,
end_month = __endMonth__, __endMonth__, __endMonth__,
end_day = __endDay__, __endDay__, __endDay__,
end_hour = __endHour__, __endHour__, __endHour__,
end_minute = 00, 00, 00,
end_second = 00, 00, 00,
interval_seconds = __metIncSec__,
input_from_file = .true., .true., .true.,
history_interval = 60, 60, 60,
frames_per_outfile = 1, 1, 1,
restart = __isRestart__,
restart_interval = __restartInterval__,
override_restart_timers = .true.,
io_form_history = 2
io_form_restart = 2
io_form_input = 2
io_form_boundary = 2
debug_level = 0
iofields_filename = "iofields" ,"iofields", "iofields",
force_use_old_data = .true.,
! CHEM
/
&domains
use_adaptive_time_step = .false.,
step_to_output_time = .true.,
target_cfl = 1.0, 1.0, 1.0,
max_step_increase_pct = 5, 51, 51,
starting_time_step = -1, -1, -1,
max_time_step = 200, 40, 3,
min_time_step = -1, -1, -1,
adaptation_domain = 3,
time_step = 120,
time_step_fract_num = 0,
time_step_fract_den = 1,
max_dom = 3,
e_we = 185, 172, 151,
e_sn = 186, 163, 156,
e_vert = 33, 33, 33,
num_metgrid_levels = 34,
num_metgrid_soil_levels = 4,
dx = 20000, 2222, 400,
dy = 20000, 2222, 400,
grid_id = 1, 2, 3,
parent_id = 0, 1, 2,
i_parent_start = 1, 96, 69,
j_parent_start = 1, 75, 74,
parent_grid_ratio = 1, 9, 5,
parent_time_step_ratio = 1, 9, 5,
feedback = 0,
/
&physics
mp_physics = 10, 10, 10,
progn = 1, 1, 1,
prec_acc_dt = 60., 60., 60.,
ra_lw_physics = 4, 4, 4,
ra_sw_physics = 4, 4, 4,
radt = 16, 4, 4,
aer_opt = 1,
sf_sfclay_physics = 5, 5, 5, ! Ravans suggestion
sf_surface_physics = 2, 2, 2, ! NOAH
sf_surface_mosaic = 0,
sf_lake_physics = 1, 1, 1,
sf_urban_physics = 1, 1, 1,
bl_pbl_physics = 5, 5, 5, ! MYNN 2.5
bl_mynn_cloudpdf = 1,
bl_mynn_cloudmix = 1,
scalar_pblmix = 1,
tracer_pblmix = 1,
! grav_settling = 0, 2, 2, ! settling of fog / cloud droplets
bldt = 0, 0, 0,
cu_physics = 5, 5, 0, ! Grell 3D
cudt = 1,
cugd_avedx = 1, ! set to 3 for 4km run, 1 for 36km
ishallow = 0,
iz0tlnd = 1, ! thermal roughness length over land determined by vegetation type
isfflx = 1,
ifsnow = 1,
icloud = 1,
icloud_bl = 1,
num_soil_layers = 4,
cu_rad_feedback = .true., .true.,.false.,
cu_diag = 1, 1, 0,
slope_rad = 0, 0, 1,
topo_shading = 0, 0, 0,
num_land_cat = 21,
/
&fdda
grid_fdda = 1, 0, 0,
gfdda_inname = "wrffdda_d<domain>",
gfdda_end_h = 312, 0, 0,
gfdda_interval_m = 60, 0, 0,
if_no_pbl_nudging_uv = 1, 1, 1,
if_no_pbl_nudging_t = 1, 1, 1,
if_no_pbl_nudging_q = 1, 1, 1,
if_zfac_uv = 0, 0, 0,
k_zfac_uv = 2,
if_zfac_t = 0, 0, 0,
k_zfac_t = 2,
if_zfac_q = 0, 0, 0,
k_zfac_q = 2,
guv = 0.0006, 0.0006, 0.0006,
gt = 0.0006, 0.0006, 0.0006,
gq = 0.0006, 0.0006, 0.0006,
if_ramping = 0,
dtramp_min = 360,
io_form_gfdda = 2,
/
&dynamics
rk_ord = 3,
time_step_sound = 4, 4, 4,
w_damping = 1,
diff_opt = 1, 1, 2,
km_opt = 4, 4, 4,
diff_6th_opt = 0, 0, 0,
diff_6th_factor = 0.12, 0.12, 0.75,
epssm = 0.1, 0.1, 0.5,
sfs_opt = 0, 0, 0,
base_temp = 290.
damp_opt = 3,
zdamp = 5000., 5000., 5000.,
dampcoef = 0.15, 0.15, 0.15,
khdif = 0, 0, 0,
kvdif = 0, 0, 0,
mix_isotropic = 0, 0, 1,
non_hydrostatic = .true.,
moist_adv_opt = 2, 2, 4,
scalar_adv_opt = 2, 2, 4,
tke_adv_opt = 2, 2, 4,
do_avgflx_em = 1, 1, 1,
hybrid_opt = 0,
use_theta_m = 1,
/
&bdy_control
spec_bdy_width = 5,
spec_zone = 1,
relax_zone = 4,
specified = .true., .false., .false.,
nested = .false., .true., .true.,
/
&grib2
/
&namelist_quilt
nio_tasks_per_group = 0,
nio_groups = 1
/
blueprints/highres_chemistry/namelist_timecontrol_chem_patch.wrf 0 → 100644
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io_form_auxinput5 = 2,
auxinput5_inname = 'wrfchemi_d<domain>_<date>',
auxinput5_interval_h = 1, 1,
frames_per_auxinput5 = 1, 1,
io_form_auxinput6 = 2,
auxinput6_inname = 'wrfbiochemi_d<domain>'
auxinput6_interval_h = 2400, 2400,
io_form_auxinput7 = 2,
auxinput7_inname = 'wrffirechemi_d<domain>_<date>',
auxinput7_interval_m = 60, 60,
frames_per_auxinput7 = 1, 1,
\ No newline at end of file
blueprints/highres_chemistry/pp/plotting/crontab 0 → 100644
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# Edit this file to introduce tasks to be run by cron.
#
# Each task to run has to be defined through a single line
# indicating with different fields when the task will be run
# and what command to run for the task
#
# To define the time you can provide concrete values for
# minute (m), hour (h), day of month (dom), month (mon),
# and day of week (dow) or use '*' in these fields (for 'any').#
# Notice that tasks will be started based on the cron's system
# daemon's notion of time and timezones.
#
# Output of the crontab jobs (including errors) is sent through
# email to the user the crontab file belongs to (unless redirected).
#
# For example, you can run a backup of all your user accounts
# at 5 a.m every week with:
# 0 5 * * 1 tar -zcf /var/backups/home.tgz /home/
#
# For more information see the manual pages of crontab(5) and cron(8)
#
# m h dom mon dow command
HOME=/home/m/met-wrf-chem
MAILTO=christoph.knote@physik.uni-muenchen.de
# wrf meteogram
52 * * * * /usr/bin/sbatch /alcc/gpfs2/home/u/knotechr/wrfotron/blueprints/operational_chemistry/pp/plotting/meteograms/run.sh
# wrf maps
00 07 * * * /usr/bin/sbatch /alcc/gpfs2/home/u/knotechr/wrfotron/blueprints/operational_chemistry/pp/plotting/maps/run.sh
# wrf geotiffs
17 6,12,18 * * * /usr/bin/sbatch /alcc/gpfs2/home/u/knotechr/wrfotron/blueprints/operational_chemistry/pp/plotting/geotiffs/run.sh
blueprints/highres_chemistry/pp/plotting/geotiffs/run.sh 0 → 100755
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#!/bin/bash -l
#SBATCH --partition=alcc1
#SBATCH -o /alcc/gpfs2/scratch/mbees/knotechr/WRF/postprocessing/geotiffs.%j.%N.out
#SBATCH -J geotiffs
#SBATCH --ntasks=1
#SBATCH --mem=5G
#SBATCH --mail-type=FAIL
#SBATCH --mail-user=christoph.knote@med.uni-augsburg.de
#SBATCH --time=00:30:00
module load gnu gdal geos proj
scriptPath=/alcc/gpfs2/home/u/knotechr/wrfotron/tools/nc_2_geotiff.py
wrfDataPathPattern="/alcc/gpfs2/scratch/mbees/knotechr/archive/WRF/operational_chemistry/wrfout___domain___%Y-%m-%d_%H:%M:%S"
firstDateToProcess=`date --date="2 days ago" "+%Y-%m-%d"`
intervalHours=1
rangeHours=120
plotDirPattern="/alcc/gpfs2/scratch/mbees/knotechr/plots/WRF/operational_chemistry/__domain__/geotiffs/%Y/%m/%d"
for domain in d01 d02
do
plotPathPattern="${plotDirPattern/__domain__/${domain}}/{species:s}_%Y-%m-%d_%H-%M.tif"
for anHour in $(seq 0 ${intervalHours} ${rangeHours})
do
aWRFDataPath=$(date -u --date="${firstDateToProcess} 0 UTC +${anHour} hours" "+${wrfDataPathPattern/__domain__/${domain}}")
aPlotDir=$(date -u --date="${firstDateToProcess} 0 UTC +${anHour} hours" "+${plotDirPattern/__domain__/${domain}}")
aPlotPath=$(date -u --date="${firstDateToProcess} 0 UTC +${anHour} hours" "+${plotPathPattern}")
if [ -f ${aWRFDataPath} ]
then
mkdir -p $aPlotDir
python3 $scriptPath -s "o3,O3" -s "no2,NO2" -s "co,CO" -s "PM2_5_DRY,PM2.5" -s "PM10,PM10" "${aWRFDataPath}" "${aPlotPath}"
fi
done
done
blueprints/highres_chemistry/pp/plotting/maps/plots.py 0 → 100644
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from wrf import to_np, getvar, smooth2d, latlon_coords, interplevel, get_cartopy
import numpy as np
import matplotlib
from matplotlib import pyplot as plt
import cartopy.feature as cfeature
import cartopy.crs as ccrs
from matplotlib.colors import LinearSegmentedColormap, ListedColormap
from tools import total_prec, cartopy_lim_buffered, make_fig_and_ax, add_title_and_description
def slp_map(t, nc, prec_prev, output_path, plevels=np.arange(950, 1050, 5)):
#
slp = getvar(nc, "slp")
mid_clouds = getvar(nc, "mid_cloudfrac")
prec = total_prec(nc, prec_prev)
#
# Smooth the sea level pressure since it tends to be noisy near the
# mountains
smooth_slp = smooth2d(slp, 5, cenweight=4)
# Get the latitude and longitude points
lats, lons = latlon_coords(slp)
#
# Get the WRF projection (CRS) object
crs = get_cartopy(slp)
#
# Create a figure
fig, ax, ax_cbarv, ax_cbarh = make_fig_and_ax(plt, crs, add_horiz_cbar=True)
#
# Draw the contours and filled contours
cmap = LinearSegmentedColormap.from_list("", ["white", "silver"])
cmap2 = matplotlib.cm.viridis_r
#
con = ax.contourf(to_np(lons), to_np(lats), to_np(mid_clouds),
levels=[1/10, 1/4, 1/2, 3/4, 1], cmap=cmap, zorder=2,
transform=ccrs.PlateCarree())
con2 = ax.contourf(to_np(lons), to_np(lats), to_np(prec),
levels=[0.5, 1, 2, 5, 10, 25, 50], cmap=cmap2, zorder=2, extend='max',
transform=ccrs.PlateCarree())
#
linewidths = np.ones(plevels.shape)
linewidths[np.where(plevels == 1015)[0]] = 3
cs = ax.contour(to_np(lons), to_np(lats), to_np(smooth_slp), levels=plevels,
linewidths=linewidths, colors="black", zorder=4,
transform=ccrs.PlateCarree())
plt.clabel(cs, fmt='%1.0f', fontsize=8)
#
ax.coastlines(linewidth=0.3, zorder=2)
countries = cfeature.NaturalEarthFeature(category='cultural', name='admin_0_countries', scale='50m')
ax.add_feature(countries, facecolor='none', edgecolor='black', linewidth=0.3, zorder=3)
#
cbar = plt.colorbar(con, cax=ax_cbarv, ticks=[1/10, 1/4, 1/2, 3/4, 1])
cbar2 = plt.colorbar(con2, cax=ax_cbarh, orientation="horizontal")
#
try:
cbar.ax.set_yticklabels(["1/10", "1/4", "1/2", "3/4", "1"], fontsize=10)
except:
print("Plotting tick labels failed")
#
ax.set_xlim(cartopy_lim_buffered(slp, "x"))
ax.set_ylim(cartopy_lim_buffered(slp, "y"))
add_title_and_description(nc, "Sea Level Pressure [hPa], Mid-Level Cloud Cover, Total prec. in the last hour [mm] \n"
"WRF {init:s} +{fcsthour:d}", ax)
#
plt.savefig(output_path, bbox_inches='tight', pad_inches=0.1)
plt.close()
return prec
def plevel_map(t, nc, output_path, plevel, phi_contour_intervals=np.arange(400, 800, 8)):
#
def interp_var(nc, variablename, p, plevel):
var = getvar(nc, variablename)
return interplevel(var, p, plevel)
#
p = getvar(nc, "p", units='hPa')
#
geop = interp_var(nc, "geopt", p, plevel)
geop = smooth2d(geop, 5, cenweight=4)
#
temp = interp_var(nc, "tc", p, plevel)
#
u, v = interp_var(nc, "uvmet", p, plevel)
#
# Get the latitude and longitude points
lats, lons = latlon_coords(temp)
#
# Get the WRF projection (CRS) object
crs = get_cartopy(temp)
#
# Create a figure
fig, ax, ax_cbarv, ax_cbarh = make_fig_and_ax(plt, crs)
#
# Temperature
lab = np.array([-46, -41, -36, -31, -26, -21, -16, -11, -6, -1, 4])
con = ax.contourf(to_np(lons), to_np(lats), temp, levels=lab,
transform=ccrs.PlateCarree(),
cmap='viridis', zorder=0, extend='both')
#
# Geopotential height
linewidths = np.ones(phi_contour_intervals.shape)
linewidths[np.where(phi_contour_intervals == 552)[0]] = 3
cs = ax.contour(to_np(lons), to_np(lats), geop/98.0, levels=phi_contour_intervals,
linewidths=linewidths, colors="black",
zorder=1,
transform=ccrs.PlateCarree())
plt.clabel(cs, fmt='%1.0f', fontsize=10)
#
#
ax.coastlines(linewidth=0.3, zorder=2)
countries = cfeature.NaturalEarthFeature(category='cultural', name='admin_0_countries', scale='50m')
ax.add_feature(countries, facecolor='none', edgecolor='black', linewidth=0.3, zorder=3)
#
nb = 20
brsb = ax.barbs(to_np(lons[::nb,::nb]), to_np(lats[::nb,::nb]),
to_np(u[::nb,::nb]), to_np(v[::nb,::nb]),
transform=ccrs.PlateCarree(),
length=4.5, zorder=4, linewidth=0.3)
#
ax.set_xlim(cartopy_lim_buffered(temp, "x"))
ax.set_ylim(cartopy_lim_buffered(temp, "y"))
#
cbar = plt.colorbar(con, cax=ax_cbarv)
add_title_and_description(nc, "{:d}".format(plevel) + " hPa level Geopotential [gpdm], Temperature [°C] and Wind \n"
"WRF {init:s} +{fcsthour:d}", ax)
#
plt.savefig(output_path, bbox_inches='tight', pad_inches=0.1)
plt.close()
# https://stackoverflow.com/questions/37327308/add-alpha-to-an-existing-matplotlib-colormap
def alphafy_colormap(name, mina=0.0, maxa=0.8):
# Choose colormap
cmap = matplotlib.cm.get_cmap(name)
# Get the colormap colors
my_cmap = cmap(np.arange(cmap.N))
# Set alpha
my_cmap[:,-1] = np.linspace(mina, maxa, cmap.N)
# Create new colormap
return ListedColormap(my_cmap)
def sfc_map(t, nc, get_var_fun, levels, ticks, label, bg_function, output_path, cmap="YlOrRd", extend='both'):
#
var = get_var_fun(nc)
u, v = getvar(nc, 'uvmet10')
#
# Get the latitude and longitude points
lats, lons = latlon_coords(u)
#
# Get the WRF projection (CRS) object
crs = get_cartopy(u)
#
# Create a figure
fig, ax, ax_cbarv, ax_cbarh = make_fig_and_ax(plt, crs)
#
# Draw the contours and filled contours
lab = np.array(levels)
con = ax.contourf(to_np(lons), to_np(lats), var, levels=lab,
transform=ccrs.PlateCarree(),
cmap=alphafy_colormap(cmap), zorder=1, extend=extend)
#
linewidths = np.ones(lab.shape)/2
linewidths[np.where(lab == 0)[0]] = 1
cs = ax.contour(to_np(lons), to_np(lats), var, levels=lab[::2],
linewidths=linewidths, colors="black", alpha=0.5,
zorder=2,
transform=ccrs.PlateCarree())
plt.clabel(cs, fmt='%1.0f', fontsize=8)
#
# Add background (needs to happen after map is already created...)
bg_function(ax, crs)
#
nb = 10
brsb = ax.barbs(to_np(lons[::nb,::nb]), to_np(lats[::nb,::nb]),
to_np(u[::nb,::nb]), to_np(v[::nb,::nb]),
transform=ccrs.PlateCarree(),
length=4.5, zorder=4, linewidth=0.5)
xlim = cartopy_lim_buffered(u, "x")
ylim = cartopy_lim_buffered(u, "y")
#
ax.set_xlim(xlim)
ax.set_ylim(ylim)
#
cbar = plt.colorbar(con, cax=ax_cbarv)
cbar.set_ticks(ticks)
#
add_title_and_description(nc, label + " and Wind (10m) \n" + "WRF {init:s} +{fcsthour:d}", ax)
#
plt.savefig(output_path, bbox_inches='tight', pad_inches=0.1)
plt.close()
blueprints/highres_chemistry/pp/plotting/maps/pois.py 0 → 100644
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blueprints/highres_chemistry/pp/plotting/maps/run.py 0 → 100644
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− 0
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import datetime
from argparse import ArgumentParser, ArgumentTypeError
def valid_date(s):
try:
return datetime.datetime.strptime(s, "%Y-%m-%d")
except ValueError:
raise ArgumentTypeError("Not a valid date: '{0}'.".format(s))
parser = ArgumentParser()
parser.add_argument('wrf_data_fpath_pattern', type=str, help='WRF input data path pattern (including strptime pattern for date and {domain:02d} for domain (01, 02, ...))')
parser.add_argument('date', type=valid_date, help='Date to process (YYYY-mm-dd)')
parser.add_argument('interval_hours', type=int, help='Time interval in hours for plotting')
parser.add_argument('fcst_time_hours', type=int, help='Forecast time in hours')
parser.add_argument('plot_fpath_pattern', type=str, help='Plot output path pattern (including strptime pattern for date, {plot:s} for plot identifier (e.g., 500hPa...) and {domain:02d} for domain (01, 02)')
args = parser.parse_args()
from plots import plevel_map, sfc_map, slp_map
import pois
import netCDF4
from wrf import getvar
import numpy as np
import cartopy.feature as cfeature
import contextily
import rasterio
times = [ args.date + datetime.timedelta(hours=t) for t in range(0, args.fcst_time_hours, args.interval_hours) ]
# for calculating delta precip
prec_prev = None
def bg_function(ax, wrfcrs):
wrfcrs_proj4 = wrfcrs.proj4_init
wrfcrs_proj4 = wrfcrs_proj4.replace('+nadgrids=@null', '')
rasteriocrs = rasterio.crs.CRS.from_proj4(wrfcrs_proj4)
contextily.add_basemap(ax, source=contextily.providers.Stamen.TonerLite, crs=rasteriocrs, zorder=0)
for t in times:
input_path_d01 = t.strftime(args.wrf_data_fpath_pattern).format(domain=1)
input_path_d02 = t.strftime(args.wrf_data_fpath_pattern).format(domain=2)
try:
nc_d01 = netCDF4.Dataset(input_path_d01)
nc_d02 = netCDF4.Dataset(input_path_d02)
except Exception as e:
print("Not all data available for step {:s}: {:s}".format(t.strftime("%Y-%m-%d %H"), str(e)))
continue
print(t)
# 500 hPa Europe domain
# output_path = t.strftime(args.plot_fpath_pattern).format(plot='500hPa', domain=1)
# plevel_map(t, nc_d01, output_path, 500)
# Surface Europe domain
# temperature
# sfc_map(t, nc_d01, lambda nc: getvar(nc, 'T2') - 273.15,
# levels=[-25, -20, -15, -12.5, -10, -7.5, -5, -2.5, 0, 2.5, 5, 7.5, 10, 12.5, 15, 17.5, 20, 22.5, 25, 27.5, 30, 32.5, 35],
# ticks=[-25, -15, -10, -5, 0, 5, 10, 15, 20, 25, 30, 35],
# label="Temperature (2m) [°C]", pois=pois.capitals,
# output_path=t.strftime(args.plot_fpath_pattern).format(plot='T', domain=1))
# Ozone
for domain, nc_d, poilist in zip([1,2],[nc_d01, nc_d02], [pois.capitals, pois.southern_germany]):
sfc_map(t, nc_d, lambda nc: getvar(nc, 'o3')[0,:,:] * 1e3,
levels=range(0, 160, 10),
ticks=range(0, 150, 20),
label="Ozone (ground level) [ppbv]", bg_function=bg_function,
output_path=t.strftime(args.plot_fpath_pattern).format(plot='O3', domain=domain),
extend='max')
# NO2
sfc_map(t, nc_d, lambda nc: getvar(nc, 'no2')[0,:,:] * 1e3,
levels=range(0, 110, 10),
ticks=range(0, 110, 20),
label="NO$_2$ (ground level) [ppbv]", bg_function=bg_function,
output_path=t.strftime(args.plot_fpath_pattern).format(plot='NO2', domain=domain),
extend='max')
# PM
def get_pm(nc, bins=[ 1, 2, 3 ]) :
pmspecs = [ "so4", "no3", "smpa", "smpbb", "glysoa_sfc", "biog1_c", "biog1_o", "cl", "co3", "nh4", "na", "cl", "oin", "oc", "bc", "water" ] # ug kg-1
alt = getvar(nc, "ALT")[0,:,:] # inverse density m3 kg-1
all = [ getvar(nc, spec + "_a{:02d}".format(bin))[0,:,:] / alt for spec in pmspecs for bin in bins ]
return np.sum(all, axis=0)
# sfc_map(t, nc_d, lambda nc: get_pm(nc, bins=[1]),
# levels=range(0, 130, 10),
# ticks=range(0, 130, 20),
# label="UFP (ground level) [$\mu$g m$^{{-3}}$]", bg_function=bg_function,
# output_path=t.strftime(args.plot_fpath_pattern).format(plot='UFP', domain=domain),
# extend='max')
sfc_map(t, nc_d, lambda nc: get_pm(nc, bins=[1,2,3]),
levels=range(0, 130, 10),
ticks=range(0, 130, 20),
label="PM$_{{2.5}}$ (ground level) [$\mu$g m$^{{-3}}$]", bg_function=bg_function,
output_path=t.strftime(args.plot_fpath_pattern).format(plot='PM2_5', domain=domain),
extend='max')
sfc_map(t, nc_d, lambda nc: get_pm(nc, bins=[1,2,3,4]),
levels=range(0, 130, 10),
ticks=range(0, 130, 20),
label="PM$_{{10}}$ (ground level) [$\mu$g m$^{{-3}}$]", bg_function=bg_function,
output_path=t.strftime(args.plot_fpath_pattern).format(plot='PM10', domain=domain),
extend='max')
# SLP Europe
# output_path = t.strftime(args.plot_fpath_pattern).format(plot='SLP', domain=1)
# prec_prev = slp_map(t, nc_d01, prec_prev, output_path)
nc_d01.close()
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