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IPILPS Workshop ANSTO 18-22 April 2005

IsoTrans: Isotopes in the boundary layer Alastair Williams. IPILPS Workshop ANSTO 18-22 April 2005. Modelling. Process studies. Introduction. IsoTrans ( Isotopic Tracers in Atmospheric Transport ): ANSTO “mother” Project for IPILPS Broader scope Purpose of presentation:

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IPILPS Workshop ANSTO 18-22 April 2005

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  1. IsoTrans:Isotopes in the boundary layerAlastair Williams IPILPS Workshop ANSTO 18-22 April 2005

  2. Modelling Process studies Introduction • IsoTrans (Isotopic Tracers in Atmospheric Transport): • ANSTO “mother” Project for IPILPS • Broader scope • Purpose of presentation: • Introduction to IsoTrans (very short) • How is IsoTrans contributing to the improvement of surface and boundary layer representations in models? • Evaluation and development of LSSs in isotope-enabled hydroclimate models (main subject of current workshop) • How can SWI obs “add value” to our understanding of moisture exchange in plant canopies, particularly ET partitioning? • Natural radionuclides and turbulent mixing in the lower atmosphere

  3. Sources & sinks Physical processes Predictive modelling Problem Current models do not reproduce well the complex cycles of exchange, mixing and transport in the lower atmosphere IsoTrans: Drivers Effective Environmental Management Strategies need … Informed predictions of mixing and movement

  4. Sources & sinks Physical processes Predictive modelling • International scientific community • (1) Inability to accurately reproduce diurnal cycle a severe limiting factor for weather and climate models • (2) Need new methods to accurately track down the origins and dynamics of atmospheric pollution • (3) Lack of independent methods for evaluation of numerical weather and climate prediction models Modelling & Prediction Panel IAEA Nuclear tools applied to contemporary atmospheric issues IsoTrans: Drivers Effective Environmental Management Strategies need … Informed predictions of mixing and movement

  5. (2) Regional transport • Wider Sydney region / Eastern Sea Board • Pollution sources & dynamics • Horizontal array of surface measurements (1) Local mixing • Vertical mixing processes in the lower atmosphere • Towers and aircraft • Sydney area Brisbane (3) Isotopes at the land surface • Stable water isotopes • Land surface processes • Diurnal observations • Model evaluations • Major river basins, including the MDB 100km Sydney 1000km 0 200km Melbourne IsoTrans: 3 Foci, 3 Scales

  6. IsoTrans Process Studies • IsoTrans Task 3 (IPILPS) • How can SWI observations “add value” to our understanding of moisture exchange in plant canopies, particularly evapo-transpiration partitioning? • Discuss the Keeling approach for estimating the transpired component of ET in vegetation canopies • Examine turbulent transport within vegetation canopies • Analyze SWI behaviour in Tumbarumba air space • Present first guess at ET partition for Tumbarumba • Thanks to David Griffith (Wollongong Uni) for providing the vertical D data, and Helen Cleugh / Ray Leuning for providing the met data

  7. Use of SWIs to Partition ET Concept: simple mix of 2 fluxes with distinct isotopic signatures (): evap (frac) and transp (non-frac) T, E: composition of contributing sources (measured / calculated) ET: “effective” combined source FET: from EC  FT How to estimate ET?

  8. Keeling (1958) • Carbon isotope ratio closely follows concn in diurnal time series over different vegetated surfaces • Mutual variation suggests simple 2-part mixing (air and plants)

  9. “Keeling” Analysis (1) 2-part mixing model (ambient + combined ET) Cm, mx: measured Ca, ax: background component from atmosphere CET, ETx: combined component from evap and transp  Linear relation if Ca, ax and ETx constant, with intercept ETx

  10. Yakir and Sternberg (2000) “Keeling” Analysis (2) • Versatile (temporal & vertical gradients) • Problems: • Extrapolated intercept susceptible to large errors • Breakdown of assumptions • Simple mixing of two major sources/sinks (atmos & ET) • No sources/sinks other than evap & transp (eg. dew, fog) • Relative contribution of all subsources remains fixed (eg. “non-fractionating” transpiration assumption true only when averaged over whole day: Harwood et al. 1998)

  11. Harwood et al. (1998) Diurnal variation of 18O of transpired water vapour for leaves on day 1 () and day 2 ( ,,) indicating the vapour pressure deficit (VPD) status and general trend over the day (solid line).

  12. Yepez et al. (2003) Vertically-distrib D and 18O in semi-arid savanna woodland Upper/lower profiles: analysed total and understory flux Post-monsoon: transp 85% total, grass 50% understorey ET Total ET 3.5mm/d = 2.5 (70%) tree trans + 0.5 (15%) grass

  13. Williams et al. (2004) Vert distrib D Moroccoolive orchard following 100mm irrig Keeling vs sap flow (v. hard to get representative data) Trans/soil evap by isotope method within 4%/15% sap flow Transpiration: pre-irrig 100%, post-irrig 70-85%

  14. Complex Canopies How can use of isotopes “add value” to understanding of ET from a complex canopy/ecosystem such as Tumbarumba?

  15. (Stull, 1988) Atmospheric Boundary Layer First need to understand turbulent mixing processes in the canopy, and interactions with atmospheric boundary layer

  16. ABL Structure and Turbulence (Holtslag and Duynkerke, 1998) Day (Wyngaard, 1990) Night

  17. Vegetation Canopies “The essential differences between turbulence in the canopy air space and that in the boundary layer above result from the sources and sinks of momentum and scalars that are spread through the canopy” (Kaimal and Finnigan, 1994) Canopy turbulence is dominated by the large eddies that form in the intense shear layer confined to the crown or upper part of the canopy

  18. Day (gradient + inflection) Night (calm) Wind in Vegetation Canopies Similar behaviour over large range of obs/model canopies Wind-shear max canopy top Attenuation below, foliage density determines rate Canopy turbulence strongly inhomogeneous in vertical All momentum absorbed in upper part of canopy (c.f. constant stress layer above) Large momentum gradient required to sustain steady air flow against aerodynamic drag of foliage

  19. Turbulence in Vegetation Canopies • Skewness • Measure of turbulent intermittency • Zero in surface layer • Canopy: SKu +ve & SKw=-ve • Turbulence is dominated by intermittent downward moving gusts (large eddies) (Kaimal and Finnigan, 1994) • Spectral peaks • Canopy: peak positions constant • “Large eddies” extend through whole depth of foliage and into the air above

  20. Turbulence in Vegetation Canopies • TKE budget • Shear prodn peaks near canopy top • Wake prodn high in upper third • Turbulent transport: sink of TKE at canopy top, source in lower canopy • Lower canopy TKE not locally produced: imported from above by “large eddies” • Dissipation much higher than free stream: wake and waving terms convert dominant large scale motions to smaller eddies (Kaimal and Finnigan, 1994) • Canopy turbulence dominated by canopy-scale “large eddies” • Cool dry gusts displacing warm moist canopy air at all levels • Counter-grad fluxes; non-local mixing; turb transport; distributed sources • Surface layer flux-profile mixing relationships (“K-theory”) are inapplicable in vegetation canopies

  21. Turbulence in Tumbarumba Quiescent at night Strong in daytime (9:00-15:00): ABL convective motions

  22. Temperature in Vegetation Canopies • Night: • lower canopy unstable strat - enhanced mixing • upper canopy stable strat (no turb - dew formation possible) • Tumbarumba: slightly stable (suppresses mixing) • Daytime: • crown max (sun on foliage), with stable strat below. But +ve (counter-grad) flux, so bimodal • Intermittent mixing by large eddies + quiescent periods • Tumbarumba: rapid increase of whole profile in morning; unstable for remainder of day

  23. Humidity in Vegetation Canopies • Night: • Tumbarumba. Saturated (>80% at 70m, colder below), with slow decrease of whole profile: dew/fog • Morning: • Tumbarumba. Rapid increase of whole profile: dew/fog re-evap as temp incr + transpiration “kicks in” • Day: • Negative gradient + progressive decrease of whole profile: dry air intrusion • Transpiration (secondary maximum in crown) • Large values near ground: surface moisture in leaf litter after rain

  24. thunderstorm Isotope obs Precipitation 1-20 March 2005

  25. Spread: fog/dew re-evaporates from top down Morning warming: fog/dew re-evaporates + transpiration “kicks in” Afternoon: dry air intrusion + transpiration Evening: mixing stops, temperature drops Night: saturated (fog/dew dries air) Humidity in Vegetation Canopies Surface moisture in leaf litter after rain

  26. Humidity gradients only in afternoon Isotopes in Vegetation Canopies Isotope gradients all day

  27. Morning Afternoon Night Isotopes in Vegetation Canopies Transp. ~ -40 o/oo Atmos. ~ -150 o/oo Soil evap. ~ -95 o/oo Night. +ve grad: condensation onto surface/plants (temp dep) Morning. Re-evap of (heavy) dew/fog + transp + soil evap Afternoon. -ve grad: transp + soil evap + mixing from above

  28. Vertical Keeling Analysis Transp. ~ -40 o/oo Soil evap. ~ -95 o/oo Atmos. ~ -150 o/oo

  29. Tumbarumba Keeling Analysis • Intercept from Keeling plots: DET • Guesses for D source values: • Soil evap -950 • Transpiration -40 • Total FT(%): • n/a at night • 20% morning (dodgy) • 80% afternoon • Understorey • 60% at night (no!) • 20% morning (dodgy) • 50% afternoon

  30. Tumbarumba Keeling Analysis r2 values: only high in afternoon

  31. Time-varying Keeling Analysis Transp. ~ -40 o/oo Intercept -66.6 R2=0.762 Soil evap. ~ -95 o/oo Atmos. ~ -150 o/oo

  32. Conclusions Vertically varying SWI data can be used to “add value” to our understanding of moisture exchange in plant canopies, particularly the partitioning of evapotranspiration The combination of time-varying and vertically-varying mixing analyses (Keeling+better?) of both D and 18O promises to be a very powerful tool for analysing ET in complex ecosystems such as Tumbarumba But … Need to understand the “whole picture” in terms of the airflow/turbulence regime within and above the canopy, so supporting meteorological data is essential.

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