Use of Models and Facility-Level Data in Greenhouse Gas Inventories

Use of Models and Facility-Level Data in Greenhouse Gas Inventories
What is inter-annual variability and what causes it?
Put simply, inter-annual variability is the year-to-year change in the estimates of emissions and removals above and
below an underlying trend (see Figure 1 below).
Figure 1
As the inter-annual variability in AFOLU can be greater than the trend change in any one year, or even over a short
reporting period, the reported inter-annual variability can mask the underlying trend. Also, if the variability remains
consistently either above or below the trend change for two or more years, it can potentially infer a false change in trend.
The extended period over which data would need to be analysed to stabilise a trend depends on both the magnitude and
temporal characteristics of the variability. There may be circumstances where the variability is such that a trend cannot
be confidently identified. Exacerbating the problem of determining trends in variable emissions estimates is the impact
of ‘extreme’ results, such as emissions from very infrequent but severe events. A good example of this is wildfire. The
inclusion of extreme events in emissions estimates makes it much more difficult to find an underlying trend in interannual
variability. Figure 2 below highlights the impact that such events can have on time-series emissions data.
Figure 2
On cause of emissions, extreme events in AFOLU would typically relate to a source of emissions beyond human control,
a natural disturbance such as heatwave, fire or cold-snap. Inter-annual variability could derive from either natural or
human causes. For example, climate influences the rate of growth and turn-over rates in biological process. Human
causes can be from changes in rates of activity driven by external factors, such as commodity prices. And of course,
both human activity and biological response are not independent and can interact to either ameliorate, or by
convergence, exacerbate inter-annual variability.
IPCC Expert Meeting Report 35 TFI