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 Correlations and bias numbers provide a metric of overall model performance with respect to simulating tropospheric ozone Young et al, ACPD

Tropospheric ozone column: models vs OMI/MLS Agreement with OMI/MLS also a measure of model performance Young et al, ACPD

CO @ 500 hPa: Models - MOPITT Similarly, agreement of CO with 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? But these sort of evaluations do not isolate single processes, such as transport…

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’ 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.: 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 Longitudinal section at equator Latitudinal sections at Testing large scale dynamical variability Oman et al. (2011) Geophys. Res. Lett., 38, L13706, doi:10.1029/2011GL047865 Latitudinal sections at different longitudes Ozone-ENSO Index – it is the monthly mean O3 column for two broad regions of E and W Pacific, differenced. Closely correlates with ENSO itself. Column O3 responds to changes in convection and large-scale dynamics. If model can capture observed behaviour, indicates that large scale response of O3 to changes in dynamics and convection are correctly represented. It is still an integrated metric, as it is unclear how much of the ozone response is due to transport and how much is due to chemistry. Could run an additional passive tracer within such simulations to separate out effects (but can’t do this in the observations of course).

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 Anomalous CO detected Fires Days 1-7 post-fires MLS observations of this rare event Enhanced CO between tropopause and 46 hPa seen for a month post-fires Days 8-13 post-fires Evidence of a filament of high CO heading west These data could test large scale advection in UTLS, for CTMs or nudged CCMs. Initial pyrocumulus convection associated with fire unlikely to be captured in reanalyses, but subsequent advection and mixing should be. Days 14-19 post-fires Pumphrey et al., 2011 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) Anomalously high values in the extratropical lower stratosphere for ERA-40 trajectories kin - kinematic (vertical velocity calculated from continuity equation) dia - diabatic (vertical motion from heating rates) Liu et al., 2010

Diagnostic for TST - location of LDP LDP occur mostly at the tropical tropopause (lowest T) Large number of trajectories attain LDP near the extra-tropical 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