GAR 2015 Main Report

Part I - Chapter 3

3.1 Accumulating contingent

liabilities

While historical losses can explain the past, they do not necessarily provide a good guide to the future. Most disasters that could happen have not happened yet (UNISDR, 2013a

UNISDR. 2013a,Global Assessment Report on Disaster Risk Reduction: From Shared Risk to Shared Value: the Business Case for Disaster Risk Reduction, Geneva, Switzerland: UNISDR.. .

). Probabilistic risk assessment simulates those future disasters which, based on scientific evidence, are likely to occur. As a result, these risk assessments resolve the problem posed by the limits of historical data. Even if a full century of historical data exists on extreme flooding and drought events in a country, any model derived from that data would not be able to forecast the previous extremes that had occurred over the past 1,000 years (Figure 3.1).

Probabilistic models therefore “complete” historical records by reproducing the physics of the phenomena and recreating the intensity of a large number of synthetic events. As such, they provide a more complete picture of the full spectrum of future risks than is possible with historical data. While the scientific data and knowledge used is still incomplete, provided that their inherent uncertainty is recognized, these models can provide guidance on the likely “order of magnitude” of risks.

The results of probabilistic risk models are normally presented in terms of metrics such as average annual loss (AAL). The AAL is the average expected loss annualized over a long time frame.

Figure 3.1 The small sample size of hazard records

(Source: GFDRR, 2014.)

While historical losses can explain the past, they do not necessarily provide a good guide to the future. Most disasters that could happen have not happened yet.

The global expected average annual loss (AAL) in the built environment associated with tropical cyclones (wind and storm surge), earthquakes, tsunamis and floods is now estimated at US$314 billion. This risk presents a real challenge to the global agenda of sustainable development.

	54 Part I - Chapter 3 3.1 Accumulating contingent liabilities While historical losses can explain the past, they do not necessarily provide a good guide to the future. Most disasters that could happen have not happened yet (UNISDR, 2013a x UNISDR. 2013a,Global Assessment Report on Disaster Risk Reduction: From Shared Risk to Shared Value: the Business Case for Disaster Risk Reduction, Geneva, Switzerland: UNISDR.. . ). Probabilistic risk assessment simulates those future disasters which, based on scientific evidence, are likely to occur. As a result, these risk assessments resolve the problem posed by the limits of historical data. Even if a full century of historical data exists on extreme flooding and drought events in a country, any model derived from that data would not be able to forecast the previous extremes that had occurred over the past 1,000 years (Figure 3.1). Probabilistic models therefore “complete” historical records by reproducing the physics of the phenomena and recreating the intensity of a large number of synthetic events. As such, they provide a more complete picture of the full spectrum of future risks than is possible with historical data. While the scientific data and knowledge used is still incomplete, provided that their inherent uncertainty is recognized, these models can provide guidance on the likely “order of magnitude” of risks. The results of probabilistic risk models are normally presented in terms of metrics such as average annual loss (AAL). The AAL is the average expected loss annualized over a long time frame. Figure 3.1 The small sample size of hazard records (Source: GFDRR, 2014.) While historical losses can explain the past, they do not necessarily provide a good guide to the future. Most disasters that could happen have not happened yet. The global expected average annual loss (AAL) in the built environment associated with tropical cyclones (wind and storm surge), earthquakes, tsunamis and floods is now estimated at US$314 billion. This risk presents a real challenge to the global agenda of sustainable development.	Page 1 Page 10 Page 20 Page 30 Page 40 Page 44 Page 45 Page 46 Page 47 Page 48 Page 49 Page 50 Page 51 Page 52 Page 53 Page 54 Page 55 ->Page 56 Page 57 Page 58 Page 59 Page 60 Page 61 Page 62 Page 63 Page 64 Page 65 Page 66 Page 67 Page 68 Page 70 Page 80 Page 90 Page 100 Page 110 Page 120 Page 130 Page 140 Page 150 Page 160 Page 170 Page 180 Page 190 Page 200 Page 210 Page 220 Page 230 Page 240 Page 250 Page 260 Page 270 Page 280 Page 290 Page 300 Page 310