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Key considerations for simulating Arctic weather and climatewith limited area models
Nicole Mölders
University of Alaska Fairbanks, Geophysical Institute and College of Natural Sciences, and Mathematics,
Atmospheric Science Program
Various scales have to be bridged
Step 1:Observe processat laboratory/field
scale
Step 2:Generalized
constitutive laws
Step 3:Conservation laws to derive partial
differential equation
Step 4:Predict system behavior
at different scalesthan lab/field scale
Methods for scaling of processes at the
atmosphere-surface interfaceAggregation (upscaling) distribution to mean (lumping of info)
Disaggregation (downscaling) mean to distribution!!!! (transfer to more detail)
n
1iin321 n
1,,
)),t(BIAS,t,z,y,x,c,b,a,(f???,?, in321 ?
atmospheric grid cell at the surface
Schematic view of aggregation methods
M
1m
kmj
kj F
M
1F
explicit subgrid scheme(e.g. Seth et al. 1994)GESIMA
kdom,j
kj FF
several km
strategy of dominance
e.g. MM5, WRF
mosaic approach (e.g. Avissar & Pielke1989)RAMS, GESIMA,CCSM, most GCMs
n
1iij
kij
n
1iij
kj 1awithFaF
Aggregation method may affect results
From Mölders 2001
mosaic approach
dominance strategy
explicit subgrid
>0.0 0.01 0.03 0.05 0.07 0.09
Scales problematic in coupling
Modified after Mölders et al. 1999
>0.0 0.01 0.03 0.05 0.07 0.09
No feedback (one-way) With feedback (two-way)
1mm/h=106l/h=103m3/h
riverdischarge
runo
ff g
ener
atio
n
Hydrological approach
lower saturated zone
upper unsaturated zone
soil moisture
gravity
gravity
lakes
snow
ETinterception
Research interest-specific modeling approaches
gravity
gravity
runoff generation
ETinterception
Meteorological approach
snowsoil moisture 1
soil moisture 2
soil moisture n
diffusivity
diffusivity
runo
ff g
ener
atio
n
Model inconsistency potential error source
0 1 2 3
From Mölders et al. 1994
Cloud properties differ in meteorological & chemistry part of EURAD
Gas phase concentrations after cloud event differ for all species affected by cloud processes
Consistency required
Investigate uncertainty range resulting from parameterizations
Fulfill six important evaluation criteria for scientific credibility
Comparison to known analytical solutions
Determination of mass and energy budgets to determine conservations of these quantities
Comparison of model results with those of other models (model inter-comparison)
Comparison of model results to observations
Publication of model description/parts/modules in peer-reviewed journals
Code must be available on request
Sparse data, network design/density aggravate evaluationHistoric Network
Modified after PaiMazumder & Mölders 2007
100 sites network
400 sites network
Arctic networks along haul waysLess 1st class sites for precip than WMO recommends
Is error within uncertainty range of observations?Right or wrong for what reasons?
Skill scores, methods for identification of error sources
-4
-3
-2
-1
0
1
2
3
4
5
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154
156
158
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164
166
168
170
172
174
176
178
180
DOY
erro
rs T
mea
n (
K)
BIASRMSESDEcorrelation
Modified after Mölders 2007
External forcing may introduce errors
Develop evaluation strategies
Which errors are due to external forcing?
Which errors are due to the limited area model?
Modified after Brown & Mölders 2007
Key considerations
Identify state-of-the-art and work/start from thereBridging of scales
Couple where necessary, not everywhere you couldCheck whether one or two-way coupling is requiredDefine data exchange (bottleneck in parallel processing!)Consistency within the model
Evaluation and analysis strategies6 criteriaIdentification of external error sourcesIdentification of “imported errors” from driving modelDetermination/definition of “investigation area”Identify & reduce uncertaintyHeuristic/indirect evaluations may be a chance
…