This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
Preliminary Work on the Prediction
of Extreme Rainfall Events and
Flood Events in Australia
Kevin Fergusson
Centre for Actuarial Studies
The University of Melbourne
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
Outline
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Current flood warning systems
Background on Australia’s weather
Historical flood events
Prediction techniques
Conclusions
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
History
• First weather warning system used the telegraph
• 1788 Lt William Dawes, First Fleet, took weather
observations
• 1922 Richardson’s “Weather Prediction by Numerical
Process”
• 1st April 1960 First launch of meteorological satellite,
Cape Canaveral, Florida
• BoM’s Global Analysis and Prediction System (85km
resolution) uses consensus of 7 models
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
Current Flood Warning Systems
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Rainfall and streamflow observations
Numerical weather predictions
Hydrologic models
BoM is responsible for effective forecasting
National arrangements focus on riverine
floods after heavy rainfall
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
Australia’s Weather
• Solar influences: Sunspot number, seasons
• Climatic indices: IOD, SOI, SAM, MJO
• Locational influences: Proximity to ocean,
latitude, altitude
• Temporal statistics: Average daily rainfall
for the month
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
Solar Influences
• Sunspots are areas of intense magnetic activity
• Source of most solar flares and coronal mass
ejections
• Their number varies with the 11-year solar cycle
• Their link to other kinds of solar activity means that
their number can predict space weather
• Tilt, precession and eccentricity of Earth’s orbit,
Milankovic 1920
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
Indian Ocean Dipole
• Measures the difference between sea surface
temperatures of one pole located in the Arabian Sea
and another pole in the eastern Indian Ocean
• Has 3 phases: neutral, positive and negative
• In negative phase, westerly winds blowing along the
Equator allow a concentration of warmer water near
Australia, resulting in higher than average rainfall over
parts of southern Australia during Winter and Spring
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
Southern Oscillation Index
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Calculated as difference in sea level barometric pressure between Tahiti and
Darwin, adjusting for standard deviation
Measures the strength of the Walker Circulation associated with El Nino Southern
Oscillation
La Nina climatic event refers to a sustained warming of the tropical area of the
Western Pacific
Results in higher than average rainfall over Northern and Eastern Australia
and potentially Central Australia
La Nina event involves trade winds blowing westward along the surface of the
Pacific Ocean causing moisture laden air rising over the warmer area in the
Western Pacific
The rising air in the Western Pacific is blown eastward at higher altitudes, resulting in
the Walker Circulation
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
Southern Annular Mode
• Describes north–south movement of westerly wind
belt circling Antarctica
• Negative phase indicative of:
• Band of westerly winds expanding towards the
Equator
• More / stronger low pressure systems over
southern Australia
• Increased storms and rain
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
Madden-Julian Oscillation
• Major fluctuation in tropical weather on weekly to
monthly timeframe
• Pulse of cloud and rainfall moving eastward over the
tropics, circling the globe
• Has a periodicity of roughly 30 to 60 days
• Two-dimensional index developed from combinations of
outgoing long wave radiation, 850-hPa zonal winds and
200-hPa zonal winds averaged over latitudes 15 degrees
South to 15 degrees North
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
Rainfall Distribution in Australia
• Rainfall data from BoM for 181 rainfall
stations
• Wet season in northern Australia during
summer months
• Southern Australia receives most rainfall
during winter months
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
Historical Flood Events
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Brisbane February1893
Northern Tasmania February 1929
Hunter Valley February 1955
Brisbane January 1974
Brisbane January 2011
Katherine December 2011
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
Historical Flood Events
Flood Event
Northern Tasmania
(April 1929)
Hunter Valley
(February 1955)
Brisbane
( January 1974)
Brisbane
(January 2011)
Katherine
(December 2011)
Rf Stn
YOLLA
NEWC
ATTU
TOOW
ALDE
ALDE
MT MEE
KATH
KOOL
Day 1
19290403
6.1
19550223
0
22.9
19740125
104.6
62
20110109
23.4
64.6
20111225
0
Day 2
19290404
114.3
19550224
83.8
38.9
19740126
Day 3
19290405
101.6
19550225
24.6
89.4
19740127
Day 4
19290406
83.8
19550226
40.1
109
19740128
224
20110110
123.2
189.6
20111226
0
220
20110111
28.2
185
20111227
255
143
43
20110112
54.2
176
20111228
1
0
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
Prediction Techniques
• Ordinary least squares (OLS) regression
• Regression trees
• Bootstrapped aggregation
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
R-Squared Statistic of a Model
• Actual Value = Predicted Value + Error
• Calculated as:
• R2 = 1 – VAR(Error)/VAR(Actual Value)
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
OLS Regression
• For each of the durations of one to five days, the four most
important predictor variables are:
o Average daily rainfall over previous years in that month at
location
o Intensity of Sun at rainfall station
o Latitude of rainfall station
o Standard deviation of daily rainfall over previous years in
that month at location
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
Regression Trees
• Simplest case is a node and two emanating
branches
• Choose the node, i.e. predictive factor and
demarcation, which minimises the variability within
each partition
• Recursively split each partition
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
Bootstrapping and Aggregation
• Bootstrapping is the process of creating a new data
set by sampling with replacement from the original
data
• Each new data set is used to build a regression tree
• The prediction is taken as consensus of the trees
• Better performance out-of-sample
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
Results for 1 Day’s Duration
odel
OLS
RT 100 Splits
RT 50000
Splits
69%
-122%
BAGGING
200 Splits,
40 Trees
14%
8%
BAGGING
50000 Splits,
200 Trees
66%
5%
In-sample
Out-ofsample
RF>=15mm
RF>=30mm
RF>=45mm
RF>=60mm
RF>=75mm
RF>=90mm
8%
8%
11%
3%
-10%
N/A
N/A
N/A
N/A
N/A
-40%
-113%
-294%
-180%
-180%
-111%
-329%
-427%
-639%
-863%
-1056%
-1558%
-2%
-32%
-22168%
-22168%
-22168%
N/A
-2%
-4%
-4%
-15%
-1455%
N/A
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
Results for 2 Days’ Duration
Model
OLS
RT 100 Splits
RT 50000
Splits
79%
-121%
BAGGING
200 Splits,
40 Trees
19%
12%
BAGGING
50000 Splits,
200 Trees
78%
8%
In-sample
Out-ofsample
RF>=15mm
RF>=30mm
RF>=45mm
RF>=60mm
RF>=75mm
RF>=90mm
12%
10%
16%
-13%
-19%
N/A
N/A
N/A
N/A
N/A
-173%
-401%
-67%
-67%
0%
0%
-242%
-289%
-364%
-384%
-351%
-384%
-3%
-13%
N/A
N/A
N/A
N/A
-1%
-3%
-5%
-22%
N/A
N/A
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
Results for 3 Days’ Duration
Model
OLS
RT 100 Splits
RT 50000
Splits
84%
-113%
BAGGING
200 Splits,
40 Trees
24%
15%
BAGGING
50000 Splits,
200 Trees
84%
12%
In-sample
Out-ofsample
RF>=15mm
RF>=30mm
RF>=45mm
RF>=60mm
RF>=75mm
RF>=90mm
15%
13%
20%
13%
-29%
N/A
N/A
N/A
N/A
N/A
-8%
-1033%
0%
0%
0%
N/A
-231%
-302%
-234%
-228%
-206%
-213%
0%
-10%
N/A
N/A
N/A
N/A
0%
-5%
-6%
N/A
N/A
N/A
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
Results for 4 Days’ Duration
Model
OLS
RT 100 Splits
RT 50000
Splits
87%
-86%
BAGGING
200 Splits,
40 Trees
27%
18%
BAGGING
50000 Splits,
200 Trees
88%
15%
In-sample
Out-ofsample
RF>=15mm
RF>=30mm
RF>=45mm
RF>=60mm
RF>=75mm
RF>=90mm
18%
15%
23%
14%
-37%
N/A
N/A
N/A
N/A
N/A
-21%
-328%
-66%
0%
N/A
N/A
-184%
-229%
-242%
-362%
-488%
-553%
-1%
N/A
N/A
N/A
N/A
N/A
-1%
-1%
-45%
N/A
N/A
N/A
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
Results for 5 Days’ Duration
Model
OLS
RT 100 Splits
RT 50000
Splits
90%
-84%
BAGGING
200 Splits,
40 Trees
30%
21%
BAGGING
50000 Splits,
200 Trees
91%
17%
In-sample
Out-ofsample
RF>=15mm
RF>=30mm
RF>=45mm
RF>=60mm
RF>=75mm
RF>=90mm
21%
18%
26%
17%
-46%
N/A
N/A
N/A
N/A
N/A
-16%
-347%
-74%
0%
N/A
N/A
-153%
-154%
-131%
-124%
-172%
-1261%
-2%
-563%
N/A
N/A
N/A
N/A
0%
-5%
52%
N/A
N/A
N/A
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.
Conclusions
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Bootstrapped aggregation with large number of splits and trees will
likely predict extreme events
R-squared values are higher for rainfall intensities over longer
durations
But most floods are associated with high intensities over short
durations
Predictive power of model is limited by the information content of the
data used
Can improve the modelling by incorporating temperature data,
pressure data, river gauge readings, hydrological maps and
topographical maps
This presentation has been prepared for the 2016 General Insurance Seminar.
The Institute Council wishes it to be understood that opinions put forward herein are not necessarily
those of the Institute and the Council is not responsible for those opinions.