Uncertainties in Greenhouse Gas Inventories - Helsinki Sept 2005

Current IPCC Guidance

Jim Penman

Global Atmosphere Division

UK Defra

Development

IPCC 96 Guidelines

• Quality indicators (H,M,L)

• Some quantitative guidance (Vol 1, Annex 1)

GPG 2000

• Discussion of conceptual basis

• Fully integrated practical methods

Uncertainties central to the definition of GPG

‘To be consistent with good practice as defined in this report, inventories should contain neither over nor underestimates so far as can be judged, and the uncertainties in these estimates should be reduced as far as practicable.’ (GPG 2000)

In fact the whole purpose of GPG and its subsequent developments to is to give confidence in uncertain estimates

Dual approach

• Eliminate bias (so far as can be judged) by use of defined good practice methods

• Reduce uncertainty (so far as practicable) by choice amongst tiers guided by key source analysis

Quantified estimates

Are needed to:

• input to key source analysis

• facilitate verification

• demonstrate methodological improvement over time

Quantification (Approach 1)• Pragmatic combination of observed data

and formalised expert judgement – best available estimates

• Repeated application of sum of squares rule for propagation of uncertainties – approximate for large uncertainty ranges

• Source category correlations treated by aggregation

• Temporal correlations treated by simplifying assumption

Assessment• Approach 1 theoretically and demonstrably

correct on the basis of the assumptions made – derivation available.

• Yields both trend and absolute uncertainty

• All assumptions can be relaxed via Approach 2 (Monte Carlo Analysis) if sufficient information is available

• MCA can also be used for Approach 1

In summary

• Uncertainties central to GPG idea

• GPG provides excellent example of practical application of statistical methods

• Approach has proved successful in building confidence in inventory estimates for review, compliance etc..