EcoTas13 BradEvans e-MAST data

TERN Australia
TERN AustraliaTERN Australia
Data user perspective: Ecosystem
data and tool requirements for
modelling applications
ecosystem Modelling And Scaling infrasTructure
(eMAST)
Presentation by Brad Evans based on contributions by Colin
Prentice, Michael Hutchinson, Gab Abramowitz, Ben Evans,
Rhys Whitley, Julie Pauwels
eMAST’s objectives 2013-2015
DELIVER research data infrastructure to
integrate TERN (and other) data streams on the
National Computing Infrastructure

ENABLE data assimilation, model evaluation and
accreditation and ecosystem model optimization
DRIVE advances in ecosystem science, impact
assessment and land management
Driving science questions
CARBON: How much CO2 is exchanged? How
much carbon can be stored and where?
WATER: What drives water use by ecosystems,
and runoff in rivers?
CLIMATE CHANGE: How does it change the
rules?
LAND MANAGEMENT: What will work, in a
changing climate?
More driving science questions
FIRE: What are the risks? How can they be
mitigated?
CLIMATE FEEDBACKS: How will ecosystem
changes influence the exchanges of
carbon, water and energy with the atmosphere?
BIODIVERSITY: What species are threatened?
Where are likely refugia? Is there a tipping
point?
Data: Climate data sets (1 km)
Tmin

Tmax

vp

P

daily
✔
1970-2011

✔

✔

✔

monthly
✔
1970-2011

✔

✔

✔

✔

mean
monthly

pan
evap.

wet
days

✔

✔

✔

✔

✔

✔

solar
rad.

wind
speed

✔

✔
Bioclimate data sets (1 km T, P and R)
Tools
Data assimilation collaboration with NEON and
NCAR, CSIRO, Macquarie University and the
Australian National University : DART (NCAR)
eMAST : An R-Package ‘emast’ for the computation
and visualization of bioclimatic indices
ePiSaT 2.0 : Use of eMAST, OzFlux and AusCover
data to model Gross Primary Production across the
landscape, an R-Package ‘ePiSaT’.
Protocol for the Analysis of Land Surface Models
(PALS) for evaluation of data and models
User example: ePiSaT
How does gross primary productivity
(GPP) vary in space and time across
Australia?
How can we ‘simply’ estimate GPP
across Australia?
What data does TERN provide that
might be useful for addressing this
research question?
User workflow: ePiSaT GPP
Choose the ePiSaT
model from the TERN
portal

Produce continental
scale estimates of GPP
and evaluate them

Obtain OzFlux data via
the TERN/ OzFlux
portals

Obtain climate (eMAST)
and satellite data
(AusCover) to scale the
ePiSaT parameters

Run the ePiSaT model –
generate estimates of
ecosystem parameters,
evaluate them
OzFlux
ePiSaT: Flux partitioning
1
Respiration
R=

1
Data filtering:
Removal of outliers
etc.. Gap filling of
PAR (PPFD) for GPP

Amax = - 2

Quantum

3

Rectangular
Hyperbole
3 parameter

1

Assimilation

2

2

Efficiency
2

Φ=
3

3

FC = R -

Amax * Φ I
Amax +Φ I
ePiSaT : Flux tower scaling
http://episat-software.blogspot.com.au/

This project is supported by the Australian National Data Service (ANDS). ANDS is supported by the Australian Government through the National Collaborative Research Infrastructure Strategy
Program and the Education Investment Fund (EIF) Super Science Initiative. For more information visit the ANDS website ands.org.au and Research Data Australia services.ands.org.au.
ePiSaT : Partitioning evaluation
Model data evaluation

from Gab Abramowitz (UNSW)
eMAST in 2014
Delivery of our key datasets through the RDSI,
Data Discovery, Visualization & Exploitation…
consolidation of our tools and porting them to
Raijin.
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EcoTas13 BradEvans e-MAST data

  • 1. Data user perspective: Ecosystem data and tool requirements for modelling applications ecosystem Modelling And Scaling infrasTructure (eMAST) Presentation by Brad Evans based on contributions by Colin Prentice, Michael Hutchinson, Gab Abramowitz, Ben Evans, Rhys Whitley, Julie Pauwels
  • 2. eMAST’s objectives 2013-2015 DELIVER research data infrastructure to integrate TERN (and other) data streams on the National Computing Infrastructure ENABLE data assimilation, model evaluation and accreditation and ecosystem model optimization DRIVE advances in ecosystem science, impact assessment and land management
  • 3. Driving science questions CARBON: How much CO2 is exchanged? How much carbon can be stored and where? WATER: What drives water use by ecosystems, and runoff in rivers? CLIMATE CHANGE: How does it change the rules? LAND MANAGEMENT: What will work, in a changing climate?
  • 4. More driving science questions FIRE: What are the risks? How can they be mitigated? CLIMATE FEEDBACKS: How will ecosystem changes influence the exchanges of carbon, water and energy with the atmosphere? BIODIVERSITY: What species are threatened? Where are likely refugia? Is there a tipping point?
  • 5. Data: Climate data sets (1 km) Tmin Tmax vp P daily ✔ 1970-2011 ✔ ✔ ✔ monthly ✔ 1970-2011 ✔ ✔ ✔ ✔ mean monthly pan evap. wet days ✔ ✔ ✔ ✔ ✔ ✔ solar rad. wind speed ✔ ✔
  • 6. Bioclimate data sets (1 km T, P and R)
  • 7. Tools Data assimilation collaboration with NEON and NCAR, CSIRO, Macquarie University and the Australian National University : DART (NCAR) eMAST : An R-Package ‘emast’ for the computation and visualization of bioclimatic indices ePiSaT 2.0 : Use of eMAST, OzFlux and AusCover data to model Gross Primary Production across the landscape, an R-Package ‘ePiSaT’. Protocol for the Analysis of Land Surface Models (PALS) for evaluation of data and models
  • 8. User example: ePiSaT How does gross primary productivity (GPP) vary in space and time across Australia? How can we ‘simply’ estimate GPP across Australia? What data does TERN provide that might be useful for addressing this research question?
  • 9. User workflow: ePiSaT GPP Choose the ePiSaT model from the TERN portal Produce continental scale estimates of GPP and evaluate them Obtain OzFlux data via the TERN/ OzFlux portals Obtain climate (eMAST) and satellite data (AusCover) to scale the ePiSaT parameters Run the ePiSaT model – generate estimates of ecosystem parameters, evaluate them
  • 11. ePiSaT: Flux partitioning 1 Respiration R= 1 Data filtering: Removal of outliers etc.. Gap filling of PAR (PPFD) for GPP Amax = - 2 Quantum 3 Rectangular Hyperbole 3 parameter 1 Assimilation 2 2 Efficiency 2 Φ= 3 3 FC = R - Amax * Φ I Amax +Φ I
  • 12. ePiSaT : Flux tower scaling
  • 13. http://episat-software.blogspot.com.au/ This project is supported by the Australian National Data Service (ANDS). ANDS is supported by the Australian Government through the National Collaborative Research Infrastructure Strategy Program and the Education Investment Fund (EIF) Super Science Initiative. For more information visit the ANDS website ands.org.au and Research Data Australia services.ands.org.au.
  • 14. ePiSaT : Partitioning evaluation
  • 15. Model data evaluation from Gab Abramowitz (UNSW)
  • 16. eMAST in 2014 Delivery of our key datasets through the RDSI, Data Discovery, Visualization & Exploitation… consolidation of our tools and porting them to Raijin.