ACITES Edinburgh:
Metrics of model transport
David Stevenson, Sue Liu
(Fiona O’Connor, Martyn Chipperfield,
Mat Evans, Oliver Wild)
(+thanks to: Luke Oman, Franz Conen)
ACITES Networking Meeting, York, 8-9th January 2013
How good are global atmospheric models?
• Recent ACCMIP (and earlier ACCENT, HTAP)
model inter-comparisons had ‘limited’ model
evaluation…
• E.g. ACCMIP O3, CO etc figs Young, Naik
Ozone: Sondes, TES vs models
Young et al, ACPD
Tropospheric ozone column:
models vs OMI/MLS
Young et al, ACPD
CO @ 500 hPa: Models - MOPITT
Naik et al, ACPD
How good are global atmospheric models?
• Models overestimate (+20%) NH ozone,
underestimate (-20%) SH ozone
• Models underestimate (-20 ppb) NH mid-lat CO,
overestimate (+30 ppb) tropical CO
• (NB assuming we believe observational datasets…)
• Why? Emissions, Chemistry, Transport, … ?
• These evaluations test many model processes
integrated together
• Can we isolate processes?
• E.g. just evaluate model transport schemes?
How can we test a
model’s transport?
Schematic section through
atmosphere to identify some transport
processes (e.g. HTAP 2010)
Transport and mixing processes
• Many different processes:
– Large scale advection/mixing
• Horizontal and vertical
– Sub-grid scale advection:
• Convection
• Boundary layer mixing
– Transport/mixing across significant ‘transport barriers’
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Boundary layer – free troposphere
Tropopause
Inter-hemispheric transport
Between air masses at fronts
Current Plans
• Sue Liu to start on 1st April 2013
• Identify relevant observational datasets to assess a
variety of model transport/mixing processes, e.g.:
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Strat-trop exchange: O3/CO/H2O distributions
Tropopause location: tracers, e.g. e90
Convection: 222-Rn, CO, CH3I, LiNOx
Large scale dynamical variability: O3-ENSO index
Horizontal advection: volcanic ash/SO2, Fukushima/nuclear
accidents, tracer experiments
– BL/free troposphere exchange: 222-Rn profiles
• Test within UKCA/other UK models
• Test more widely within other international models
An appeal to the community
• If you have ideas of datasets/methods for
testing model transport that you would like to
share, please let us know
ENSO-Ozone
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•
Testing large scale dynamical
variability
Oman et al. (2011) Geophys. Res.
Lett., 38, L13706,
doi:10.1029/2011GL047865
Longitudinal
section at
equator
Latitudinal
sections at
different
longitudes
222-Rn
• Franz Conen’s data from Bern/Jungfraujoch
BL vs Free troposphere
http://radon.unibas.ch
222-Rn: diurnal cycles
http://radon.unibas.ch
222-Rn: vertical profiles
*
Williams et al 2011
Black Saturday Fires
Australia Feb 2009
Fires
Anomalous
CO detected
Days 1-7 post-fires
• MLS
observations of
this rare event
• Enhanced CO
between
tropopause and
46 hPa seen for
a month postfires
Pumphrey et al., 2011
Days 8-13 post-fires
Evidence of a
filament of high
CO heading west
Days 14-19 post-fires
Days 20-25 post-fires
Tracers: e.g., e90 to define tropopause
• e90 tracer
– Surface source, 90-day e-fold
– Arbritrary emissions strength chosen to
yield global mean steady state abundance
of 100 ppb
– Troposphere, on annual average = 80% of
atmosphere
– Using UCI CTM yields an e90 tropopause
value of 90 ppb
White line
e90 = 90 ppb
Prather et al 2011
Hand over to Sue…
TST from a Lagrangian perspective
METHOD: Ensembles of trajectories
are initialised in the lower
stratosphere and are integrated
BACKWARD in time using ECMWF
reanalysis winds and heating rates
Define the “tropospheric ensemble”
by a TST criterion (e.g. trajectories
must experience Pot. Temp. <340K
within some time limit)
Trajectories can be traced through
meteorological fields (e.g.
TEMPERATURE) or other passive
tracers and used to reconstruct high
resolution observed fields
Lagrangian dry point
e.g. ADVECTION-CONDENSATION MODEL for stratospheric water vapour:
Water vapour at the endpoint of the trajectory is given by the Lagrangian Dry Point (LDP) (T,
lat, lon, pres, time) of the tropospheric-ensemble: this is the last point at which trajectories
encounter 100% RH before the endpoint.
Sensitivity of modelled H2O
Water vapour from TST-ensemble only
E4 - ERA-40
(3D-var assimilation)
EI
- ERA-Interim
(4D-var assimilation)
kin - kinematic
(vertical velocity
calculated from
continuity equation)
dia - diabatic
(vertical motion
from heating rates)
Liu et al., 2010
Anomalously high values
in the extratropical lower stratosphere for ERA-40
trajectories
Diagnostic for TST - location of LDP
LDP occur
mostly at the
tropical
tropopause
(lowest T)
Large number
of trajectories
attain LDP
near the extratropical
tropopause in
ERA-40
kinematic
calculation
Liu et al., 2010
Defining the tropopause using trajectories
Transport statistics derived from
trajectories can be used to give
alternative definitions of the
tropopause (e.g. Berthet et al. 2007)
Coloured contours show the
proportion of backward trajectories
that encountered the boundary layer
(defined as log pressure height
<1km) within the last 30 days. Solid
line (20%) may be used to define the
tropopause for all latitudes.
Significant differences from PV
(white contours) especially in high
latitudes and NH summer
midlatitudes (influences of the Indian
monsoon)
Liu, 2010 (PhD thesis)
Transport timescales - alternative view
For the inverse problem, here we
initialise trajectories on 100hPa
on 1x1 grids and integrate
backwards for 5 years and study
the distribution of TIME since last
encountering the boundary layer
(z* < 1km)
Note significant seasonal
difference, especially role of the
Tibetan plateau/Indian ocean in
NH summer
We can convolute this with an
idealised surface-emitting tracer
to produce an estimate of its
distribution on 100hPa based on
transport alone, in a Lagrangian
analogy of the e90 tracer (Prather
et al. 2011)
Lifetime of the tracer will highlight
transport features of
corresponding timescales.
Summary
• Identify a range of transport metrics, based on
observational datasets
• Test behaviour in UKCA and other UK models
• Encourage use in wider model
intercomparisons/evaluations (e.g. CCMI,
HTAP)
• This part of ACITES runs April 2013 for 2 years
• We encourage your suggestions