Post Processing
RCP Adjustments for Lower Emissions Scenarios
The Climate Risk Engines aim to ensure that the full extreme weather and climate change risk space has been properly explored. Practically this means selecting high emission pathways and testing hazards using the individual regional models which most exacerbate each hazard. Conducting analysis using other RCP models involves computational trade-offs as the requirements for assessing large portfolios of assets requires substantial setup time and processing on large multi-core servers is costly. Rather than testing lower emissions outcomes (which can be considered to have been covered by a high emissions scenario that will bring on impacts more significantly or more rapidly) it may be more useful to test other effects e.g. different archetypes (with different vulnerabilities) using the same RCP model or analysing a set of hazards at greater resolution. To avoid computational reruns, yet still meet requests to provide estimates of the impact of lower emission scenarios, the Climate Risk Engines apply RCP adjustments that reduce climate impacts based on lower emissions and lower levels of warming. The logic is that the RCP8.5 world passes through lower emission worlds on its way, and these worlds can be extracted as a subset of the RCP8.5 data. An adjustment factor has been calculated for all years based on the difference in the global average temperature increases between IPCC aggregations of RCP modelling scenarios. For each asset, the relevant hazard probabilities are scaled according to the adjustment factor for each year. Sea level rise and coastal inundation are managed separately because of the high levels of inertia in the ocean and ice systems. The RCP outcomes are mapped based on IPCC trajectories for sea level rise.
Flood/Inundation Defences and Lifting
Implied Coastal Protections
The Climate Risk Engines use Digital Elevation Models in conjunction with tide data, storm surge data and tectonic adjustments to compute the risk of coastal inundation. But there are instances where the location of an asset implies that it is already being regularly inundated by high sea events, even without sea level rise. This is highly implausible and has the effect of swamping risk results – because the system might assume that the asset is being destroyed and rebuilt every few years at great cost. In these instances, it is useful to implement a common-sense test which assumes that no one would in good sense build a property that was being inundated every few years.
Implied Flood Exposure Limits
Extrapolating hazard results can lead to strange and implausible projections. As such, controls are needed to avoid run-away outcomes. This post-processing technique “sense checks” results to ensure they do not extend past the realms of the external expert flood maps used.
Tropical Cyclone Truncation
Locations experiencing tropical cyclone wind speeds relatively frequently by 2100 are in regions where there is confidence in the model results. Locations that are either already in cyclone regions, or in nearby areas where the cyclone belt will likely expand with global warming. There is less confidence in regions far beyond current cyclone zones as they encounter conditions deleterious to cyclone development and maintenance even when Sea Surface Temperatures (SSTs) might be favourable (such as higher wind shear).
