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More information on some input arrays can be found when moving the cursor above the corresponding field in the questionnaire. Those fields are also explained in the glossary.

LPDM : Lagrangian Particle Dispersion Model

General information

Model name and version

short nameLPDM
full nameLagrangian Particle Dispersion Model
revision
date28 Sep 2005
last change

Responsible for this information

nameBarbara Fay
instituteDWD
addressKaiserleistr. 42
zip63067
cityOffenbach
countryGermany
phone++49 69 8062 2748
fax++49 69 8062 3721
e-mailbarbara.fay(belongs-to)dwd.de

Additional information on the model

Contact person for model code

same as person above
nameHubert Glaab
instituteDWD
divisionsR&D, atmospheric dispersion modelling
streetKaiserleistr. 42
zip63067
cityOffenbach
countryGermany
phone++49 69 8062 2747
emailhubert.glaab@dwd.de
fax++49 69 8062 3721

Model developer and model user

developer and useras contact person, used by DWD and MeteoSwiss

Level of Knowledge needed to operate model

basic
intermediate
advanced
remarks

Model use at your institution

operational
for research
other use

Model code available?

is available?no
more details

Minimum computer resources required

typelarge supercomputers
time needed for run3 min for 24h forecast
storagevery extensive

Further information

documentation
model references FAY B., GLAAB H., JACOBSEN I., and KLEIN.; 'Air Pollution Forecasts of the German Weather Service for IMIS', Kerntechnik 69, No. 5-6, 209-213 (2004) GLAAB H., FAY B., and JACOBSEN I.,'Evaluation of the Emergency Dispersion Model at the Deutscher Wetterdienst using ETEX Data', Atmospheric Environment 32, 4359-4366 (1998) GALMARINI S. et al., 'Ensemble Dispersion Forecasting - Part I: Concept Approach and Indicators. Part II: Application and Evaluation', Atmospheric Environment 38, 4607-4632 (2004)
webpage
additional information

Model properties

Model type

2D
3D
meteorology
chemistry & transport

Model scale

microscale
mesoscale
macroscale
short term
long term

Meteorological variables

Input data
u
v
w
ζ
pv
T
θ
θl
p
Gph
ρ
qv
qt
qlc
qf
qsc
qlr
qsh
qsg
qss
N
E
ε
K
zi
other variables i
other variables ii
other variables iii

Chemical substances

PrognosticDiagnosticDry depositionWet depositionInput data
SO2
NO
NO2
NOX
NH3
HNO3
O3
CH4
DMS
H2O2
VOC
C6H6
HCHO
CO
CO2
POP
PM 10
PM 2.5
PPM10
PM 0.1
PM 1
NH4
SO4
dust
sea salt
BC
POM
SOA
NO3
Other gasesradioactivity forecasts:
1st radioactivity
2nd radioactivity
3rd radioactivity
Cd
Pb
other heavymetals
pesticides
1st radioactivityCs-137, I-131, Te-132, Zr-95,
2nd radioactivityBa-140, Ru-103
3rd radioactivity
remarkstracers chemically inert, but radioactive decay

Approximations

Boussinesq
anelastic
hydrostatic
flat earth
remarks

Parametrizations

Chemistry & transport

photolysis rate-
dry depositionisotope-specific deposition rates
wet depositionisotope-specific scavenging factors
remarksradioactive decay included

Chemical reactions

Gas & wet phase chemistry

chemical transformations calculated
chemical transformations neglected
other
gas phase chemistry (give details)-
wet phase chemistry (give details)-
more information

Aerosol chemistry

passive aerosol
dry aerosol
wet aerosol
sectional approach
modal approach
other
nucleation
coagulation
condensation
aerosol mixing
aerosol ageing
primary aerosol formation
aerosol-gas phase interactions
optical properties
give detailsonly radioactive decay modelled

Initialization & boundary treatment

Initialization

chemistry & transportsource term optional: data assimilation
meteorology

Input data (name sources for data, e.g. website)

orographyLME and GME parameters used
land useLME and GME parameters used
obstacles
vegetation
meteorologyall meteorological input data are output fields of the operational NWP models LME or GME.
concentrationsoptional measurement assimilation
emissionssource term
remarks

Data assimilation

Chemistry & transport
nudging technique
adjoint model
3D-VAR
4D-VAR
OI
detailsonly for meteorology, see LME and GME docus

Boundary conditions

Chemistry & transport
surfacemeteorology: as in LME and GME, see resp. docus radioactivity: reflection
topmeteorology: as in LME and GME, see resp. docus radioactivity: reflection
lateral inflowmeteorology: as in LME and GME, see resp. docus radioactivity: none
lateral outflowmeteorology: as in LME and GME, see resp. docus radioactivity: none

Nesting

Chemistry & transport
one way
two way
other
variables nested
nesting online
nesting offline
data exchange by array
data exchange by file
time step for data exchange
explain method
variables nested
other

Solution technique

Coordinate system and projection

Horizontal

cartesian
Lambert conformal
latitude / longitude
rotated lat. / long.

Vertical

z coordinate
surface fitted grid
pressurecoordinate
sigma coordinate
remarkshoizontal and vertical (hybrid sigma) grids identical with LME or GME NWP model grids, see resp. docus.

Numeric

Chemistry & transport

Grid

Arakawa A
Arakawa B
Arakawa C
Arakawa D
Arakawa E
uniform grid
nonuniform grid
Euler
Lagrange
Gauss

Time integration

explicit
split-explicit
semi-implicit
time step same as meteorology
other

Spatial discretisation

scalar quantities
additional information
other
chemistry solver

Model resolution

Chemistry & transport

HorizontalVertical
max60km
min1.1km10m=lowest GME layer

Domain size

Chemistry & transport

HorizontalVertical
maxglobaltropos plus lower stratosphere as LME and GME
minGermany

Model Validation and Application

Validation & evaluation

Used validation & evaluation methods

analytic solutions
evaluated reference dataset
model intercomparison
additional validation & evaluation efforts
remarks

Application examples

application examples...

Participation in specific model evaluation exercises

AQMEII
List experiments (AQMEII)
Cost728
List experiments (COST728)
HTAP
List experiments (HTAP)
MEGAPOLI
List experiments (MEGAPOLI)