Welcome guest. Please login.

List, classification & detail view

Note:
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.

NAME: Numerical Atmospheric-dispersion Modelling Environment

General information

Model name and version

short nameNAME
full nameNumerical Atmospheric-dispersion Modelling Environment
revisionNAME III version 5.0
date24/08/07
last change

Responsible for this information

nameMaria Athanassiadou
instituteMet Office
addressFitzRoy Road
zipEX1 3PB
cityExeter
countryU.K.
phone0044 1392 886096
fax0044 1392 885681
e-mailmaria.athanassiadou(belongs-to)metoffice.gov.uk

Additional information on the model

Contact person for model code

same as person above
nameMaria Athanassiadou
instituteMet Office
divisionsFitzRoy Road
street
zipEX1 3PB
cityExeter
countryU.K.
phone0044 1392 886096
emailmaria.athanassiadou(belongs-to)metoffice.gov.uk
fax0044 1392 885681

Model developer and model user

developer and userModel developer: Met Office, UK Model user: Mainly Met Office, UK

Level of Knowledge needed to operate model

basic
intermediate
advanced
remarksModel control is via text input file

Model use at your institution

operational
for research
other useCommercial projects

Model code available?

is available?yes
more detailsFor agreed collaborative research use only currently

Minimum computer resources required

typeDesktop pc (min 1Gb RAM)
time needed for runmins to weeks
storageOutput: 10's of Mb. Met Data input: upto 100's of Gb.

Further information

documentation
model referencesJones A.R., Thomson D.J., Hort M.C. and Devenish B.J., 2007, The U.K. Met Office’s next-generation atmospheric dispersion model, NAME III, to appear in Air pollution modeling and its application XVII, Edited by C Borrego and A-L Norman, Springer.
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 gases
1st radioactivity
2nd radioactivity
3rd radioactivity
Cd
Pb
other heavymetals
pesticides
1st radioactivity
2nd radioactivity
3rd radioactivity
remarksNAME models radioactive decay based on half life but does not include decay products. The current radioactive species list contains 51 members.

Approximations

Boussinesq
anelastic
hydrostatic
flat earth
remarks

Parametrizations

Chemistry & transport

photolysis rateChanges with zenith angle but assumes clear skies.
dry depositionYes - resistance scheme with species dependent surface resistance, or deposition velocity scheme
wet depositionYes - washout coefficients for convective and dynamic cloud
remarks

Chemical reactions

Gas & wet phase chemistry

chemical transformations calculated
chemical transformations neglected
other
gas phase chemistry (give details)Over a 100 reactions based on the STOCHEM model. Clear skies assumed. Reference: Collins, W.J., Stevenson, D.S., Johnson, C.E. and Derwent, R.G. (1997) Tropospheric ozone in a global scale three dimensional Lagrangian Model and its response to NOx emission controls; J of Atmospheric Chemistry, 26, 223-274
wet phase chemistry (give details)In cloud production of sulphate aerosol via O3 and H2O2. Scheme uses cloud liquid water amount.
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 details

Initialization & boundary treatment

Initialization

chemistry & transportSpun up using emission data plus background fields for Ozone and H2O2.
meteorology

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

orographyFrom meteorological model
land useFrom meteorological model
obstaclesUser provided data
vegetation
meteorologyFrom Met Office NWP model (the Unified Model). Configurations include: Global 40km, NAE 12km, UK 4km, South Asia model 20km Also from ECMWF ERA 40
concentrations
emissionsSource shape: cuboidal and elipsoidal. Source size: point to global. Number of sources only memory limited (> 10000 have been used) Emissions: total amount or rate. Steady or time dependant. Data from EMEP, NAEI and GEMS used.
remarks

Data assimilation

Chemistry & transport
nudging technique
adjoint model
3D-VAR
4D-VAR
OI
detailsNo data assimilation

Boundary conditions

Chemistry & transport
surfaceDeposition (using sedimentation rate and surface resistance or deposition velocity)
topOutflow
lateral inflowThe model is usually run with just the sources within the domain. It is possible however (although not straightforward) to specify the concentration of inflowing air.
lateral outflowYes

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 methodThe meteorology used in the model can be nested. Because the dispersion is computed using Lagrangian particles or puffs, there is no requirement to nest the dispersion calculation. Any chemistry is done on a single Eulerian grid (with no nesting of such grids).
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
remarksNAME can cope with a wide variety of coordinate systems both for input meteorology and for output data. Standard systems include: lat-long, rotated lat-long, UK national grid, EMEP grid. Further coordinate systems are user definable.

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
otherExplicit for Lagrangian particle or puff stochastic trajectories

Spatial discretisation

scalar quantitiesConcentration carried on Lagrangian particles or puffs (no grid) but converted to a user definable grid (uniform in the horizontal) for chemistry calculation. Output computed on a variety of user defined grids.
additional information
other
chemistry solverBackwards Euler

Model resolution

Chemistry & transport

HorizontalVertical
maxAnyAny
minAnyAny

Domain size

Chemistry & transport

HorizontalVertical
maxAnyAny
minAnyAny

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 examplesNuclear accidents, Volcanic eruptions, Industrial accidents, Air quality, Spread of foot and mouth and blue tongue disease References: Witham C.S., Hort M.C., Potts R., Servranckx R., Husson P. and Bonnardot F., 'Comparison of VAAC atmospheric dispersion models using the 1 November 2004 Grimsvötn eruption', Meteorological Applications 14, 27-38, 2007 Gloster J., Mellor P.S., Manning A.J., Webster H.N. and Hort M.C., 'Assessing the risk of windborne spread of bluetongue in the 2006 outbreak of disease in northern Europe', Veterinary Record 160, 54-56, 2007 Redington A.L. and Derwent R.G., 'Calculation of sulphate and nitrate aerosol concentrations over Europe using a Lagrangian dispersion model', Atmospheric Environment 36, 4425-4439, 2002 Ryall D.B. and Maryon R.H., 'Validation of the UK Met Office's NAME model against the ETEX dataset', Atmospheric Environment 32, 4265-4276, 1998. Gloster J., Sellers R., Webster H. and Valarcher J-F., 'Assessing the risk of airborne spread of foot-and-mouth disease - a case study, Weather 61, 137-142, 2006

Participation in specific model evaluation exercises

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