2. Observe
to
predict,
predict
to
prevent
The
Founda+on
A
few
minutes
on
the
organiza+on
• it
was
founded
as
the
development
of
a
previous
university
research
center
in
2007
• the
founders
were
the
Civil
Protec+on
Department
of
the
Presidency
of
the
Council
of
Ministers
(2
106
€),
the
regional
government
of
Liguria
(0.2
106
€)
and
the
University
of
Genoa
(use
without
charges
of
the
ac+vity
of
some
researchers
for
a
few
of
years)
• no
annual
monetary
support
from
the
founding
bodies.
The
Founda+on
supports
itself
on
the
basis
of
contracts
of
na+onal
and
interna+onal
research
and
consul+ng
3. Observe
to
predict,
predict
to
prevent
RESEARCH
THEMES
• Hydro-‐met
applica+ons
in
Civil
Protec+on
• Climate
Change
and
Disaster
Risk
Reduc+on:
Targe+ng
Extremes
• Marine
Biology
and
Ecosystem
Monitoring
• Liability,
Responsibility
&
Governance
of
risk
• EO
assisted
applica+ons
• ICT
Tools
in
support
of
research
• Capacity
building
and
Educa+on
from
the
interna+onal
to
the
local
dimension
6. Observe
to
predict,
predict
to
prevent
Report
to
Founda-on
the numbers of the Foundation
7. Observe
to
predict,
predict
to
prevent
Rapporto
a
Fondazione
Chairmanship
Administration Training
Management
Project
Leaders
Researchers
Ph.D and
Post Doc
Students
Report
to
Founda-on
8. Observe
to
predict,
predict
to
prevent
Rapporto
a
Fondazione
Staff
composi2on
(71)
Research staff
Administrative staff
Post-DocPh.D. Students
Occasional Staff
External
Consultants
Personnel
Appointed on
Project
Report
to
Founda-on
9. Observe
to
predict,
predict
to
prevent
Rapporto
a
Fondazione
how we map the Foundation on basic sciences
env.eng.
biologists
physicists
ICT people
social scientists
Research
staff
composi2on
env.eng.
biologists
physicists
ICT people
social scientists
Report
to
Founda-on
10. Observe
to
predict,
predict
to
prevent
Rapporto
a
Fondazione
How we map Foundation on peer review Int.Journals
0
1
2
3
4
5
6
JMEPS
JMS
AW
R
CSDA
IINMEQJRM
S
JGR
JMB
JHM
AM
SNHESS
W
RR
ESI
JAS
JMBA
EF
EM
SPh.Letters
FreseniusB.
11. Observe
to
predict,
predict
to
prevent
Rapporto
a
Fondazione
External
ConsultantsOccasional Staff
Personnel
Appointed on
Project
Ph.D. Students
Post-Doc
Staff
Research
staff
costs
(2014:1.8
M€)
12. Observe
to
predict,
predict
to
prevent
Personnel
Travels
Third Institutions
Operational costs
Training
Goods
Rapporto
a
Fondazione
anno
2009
Total
Founda2on
costs
(2014:
4.2
M€)
13. Observe
to
predict,
predict
to
prevent
Rapporto
a
Fondazione
our new goal for the second
decade of the third millennium
environment disasters food
and
poverty
Report
to
Founda-on
14. Observe
to
predict,
predict
to
prevent
a
few
historical
notes:
Mr.
Zamberle?
in
Italy
and
Mr.Tazieff
in
France
at
the
same
-me
appoint
at
the
na-onal
scale
three
Research
Groups
on
hydrological
and
meterological
hazards,
on
eartquake
hazard
and
on
volcano
hazard.
To
assist
the
Government
to
build
up
policies
to
manage
the
risk.
In
Italy
a
Dept.
of
the
Presidency
of
the
Council
of
Ministers
is
named
as
Protezione
Civile.
The
Head
of
Civil
Protec-on
is
in
charge
of
coordina-ng
the
country
resources
for
assessing
the
risk,
diffusing
in
real
-me
proper
alert
messages,
rescue
vic-ms
and
support
affected
people.
The
Presidency
of
the
Council
of
Ministers
is
assisted
by
a
network
of
research
Centers.
CIMA
Research
Founda-on
deals
with
the
floods,
landslides,
drougts
and
forest
fires
risks.
Understanding
the
climate
change
impact
on
the
extreme
phenomena
is
a
key
issue
for
predic-ng
and
planning.
1985
1987
1987
1999
2000
2015
15. Observe
to
predict,
predict
to
prevent
hydro-‐meteo
risk;
earthquake
risk,
volcanic
risk
CIMA
Res.
Founda-on
Univ.
Of
Genoa
Dept.
Prot.
Civile
Fond.EUCENTRE
Univ.
of
Pavia
Dept.
Prot.
Civile
Observatory
of
Mount
Vesuvius
17. Observe
to
predict,
predict
to
prevent
the
Italian
Civil
Protec+on
Department
of
the
Presidency
of
the
Council
of
Ministers
18. Presidency
of
the
Council
of
Ministers
-‐
Department
of
Civil
Protec2on,
ROME
19. Observe
to
predict,
predict
to
prevent
re-‐building
preven7on
mi7ga7on
emergency
back
to
life
Disaster
Disaster
Risk
Reduc-on
Cycle
preparedness
PROPER
CIVIL
PROTECTION
ACTIONS
WHERE
DOES
THE
DEPARTMENT
OF
CIVIL
PROTECTION
WORKS
IN
THE
CYCLE
OF
THE
RISK
REDUCTION
..Pre-‐disaster
ac2vi2es
that
are
undertaken
within
the
context
of
disaster
risk
management
and
are
based
on
sound
risk
analysis.
This
includes
the
development/
enhancement
of
an
overall
preparedness
strategy,
policy,
ins2tu2onal
structure,
warning
and
forecas2ng
capabili2es,
and
plans
that
define
measures
geared
to
helping
at-‐risk
communi2es
safeguard
their
lives
and
assets
by
being
alert
to
hazards
and
taking
appropriate
ac2on
in
the
face
of
an
imminent
threat
or
an
actual
disaster
(ISDR’s
defini2on)…
UN-‐ISDR
20. Observe
to
predict,
predict
to
prevent
Presidency
of
the
Council
of
Ministers
-‐
Department
of
Civil
Protec2on
Steps
for
the
prepara2on
1. KNOW
THE
VULNERABILITY
AND
RISK
SCENARIOS
2. IMPLEMENTING
RISK
PREDICTION
AND
EARLY
WARNING
3. BUILDING
A
GOOD
PERFORMANCE
IN
BACK
TO
LIFE
ACTIVITY
21. Observe
to
predict,
predict
to
prevent
Presidency
of
the
Council
of
Ministers
-‐
Department
of
Civil
Protec2on
PREPARE
A
RISK
SCENARIO
…figures
dendent
on
space
and
2me….
q Iden2fying,
zoning,
quan2fying
the
DANGER
(P)
q Loca-on
and
evalua-on
of
the
numbers
(N)
and
the
value,
social
and
economic,
for
different
categories
of
exposed
en--es(E)
q Determina2on
of
the
overall
vulnerability(V)
q Defini2on
of
the
expected
damage
(D)
given
the
event.
D=
E
x
V
R = P x E x V = P x D
Uff.
Previsione
e
Prevenzione
22. Observe
to
predict,
predict
to
prevent
Presidency
of
the
Council
of
Ministers
-‐
Department
of
Civil
Protec2on
An example of residual risk
the
effect
of
ac-ons
can
be
considered
in
the
defini-on
of
risk
through
indices
(Iv)
of
effec-veness
of
specific
interven-ons:example
q IV
interven-ons
to
reduce
vulnerability
Uff.
Previsione
e
Prevenzione
T=50an
ni
T=200
years
rischio
residuo
difesa
domes-ca
da
inondazione
riduce
la
frequenza
dei
danni
inondazione
molto
frequente,
T=5-‐10
anni
elevata
vulnerabilità
the
low
probability
events
remain
unchanged
–
PROCIV
early
warnings
Insurance
23. Observe
to
predict,
predict
to
prevent
Presidency
of
the
Council
of
Ministers
-‐
Department
of
Civil
Protec2on
They
say,
in
Rome,
that
the
Early
Warning
System
of
Italian
Civil
Protec-on
is
among
the
most
advanced
in
the
world:
Understanding
and
mapping
the
danger
Monitoring
physical
processes
and
predict
upcoming
events
Dissemina-ng
clear
alerts
by
poli-cal
authori-es
Popula-on
undertaking
appropriate
-mely
ac-on
as
a
result
of
warnings
1
2
3
4
24. Observe
to
predict,
predict
to
prevent
Presidency
of
the
Council
of
Ministers
-‐
Department
of
Civil
Protec2on
Strategy:
integra-ng
the
tools
for
real
-me
and
the
tools
for
mi-ga-on
-me
Policy
of
Early
Warning
Previsioni
modellis2che
Inondazioni
storiche
-‐
AGGIORNAMENTO
Espos2
–
Centri
abita2
Strategy:
public
and
private
sector
coopera-ng
in
the
collec-ng
observa-ons
and
informa-ons
to
build
scenarios
25. Observe
to
predict,
predict
to
prevent
Presidency
of
the
Council
of
Ministers
-‐
Department
of
Civil
Protec2on
early
warning
systems
are
much
more
than
a
technological
tool,
are
a
whole
technological
system,
social,
even
cultural.
The
civil
protec-on
system
includes
ci-zens
and
their
consciousness
of
the
risk
as
ac-ve
component:
ci-zens
must
believe
on
the
effec-veness
of
an
early
warning
system
and
should
know
how
to
behave
once
alerted.
Civil
Protec2on
System
for
Early
Warning
INSURANCE
“Empowering
the
ci-zens”
airaverso
l’interoperabilità
fra
sistemi,
necessità
di
una
determinazione
del
rischio
sul
territorio
condivisa
(pubblico,
privato,
ciiadini)
the
biggest
barrier
to
the
penetra-on
of
insurance
is
the
lack
of
risk
percep-on
CICLO
VIRTUOSO
26. Observe
to
predict,
predict
to
prevent
The
NP-‐HFA
is
(
or
beier
should
be)
an
en-ty
that
promotes
a
more
open
and
effec-ve
dialogue
between
stakeholders
in
a
shared
interna-onally.
It
promotes
the
development
of
financial
mechanisms
and
risk
transfer,
in
par-cular
insurance
and
re-‐insurance
against
disasters
It
encourages
the
forma-on
of
partnerships
to
increase
public-‐private
partnerships
involving
the
private
sector
in
the
ac-vi-es
of
risk
reduc-on:
Sponsors
of
a
risk
culture
Allocates
of
resources
in
the
pre-‐event
for
risk
assessment
and
for
the
implementa-on
of
early
warning
systems
Develops
and
promotes
alterna-ve
and
innova-ve
financial
instruments
to
deal
with
disasters.
Na2onal
Plagorm
of
Hyogo
Framework
for
Ac2on
(NP-‐HFA)
DPC
è
il
coordinatore
della
piaiaforma
Presidency
of
the
Council
of
Ministers
-‐
Department
of
Civil
Protec2on
28. Observe
to
predict,
predict
to
prevent
Predictability
of
meteorological
extremes
Modeling
and
predic-on
of
floods
and
droughts
Observa-on
of
hydro-‐meteorological
variables
Data
fusion
and
data
assimila-on
Modeling
and
predic-on
of
forest
fires
Modeling
and
predic-on
of
pollutants
dispersion
in
water,
s
soil
and
atmosphere
CIMA
Research
Founda-on
ac-vity
is
financed
by
research
and
technological
innova-on
contracts
with
the
Italian
Civil
Protec-on
and
regional
governments,
with
UNDP,
UN-‐ISDR,
UE,
NGO
and
public
and
private
companies.
Predictive
ability
of
severe
rainfall
events
over
Catalonia
for
year
2008
master
thesis
report
Directors:
Dra.
Maria
Carme
Llasat
Botija
(UB)
Dr.
Antonio
Parodi
(CIMA
Res.
Foundation)
Albert
Comellas
Prat
29. Observe
to
predict,
predict
to
prevent
1-‐Climate
change
impacts
on
the
organiza-on
of
the
date
base
of
events
severity,
which
is
a
cri-cal
issue
for
predic-ng
and
planning
30. Observe
to
predict,
predict
to
prevent
2-‐Climate
change
impacts
on
the
rate
of
transforma-on
of
the
territory,
which
is
a
cri-cal
issue
for
adapta-on
31. Observe
to
predict,
predict
to
prevent
3-‐Climate
change
impacts
on
the
legisla-on
for
risk
mi-ga-on,
which
is
a
cri-cal
issue
for
social
responsibility
Italian
direc-ve
2004
European
direc-ve
2008
1992
Italian
Civil
Protec-on
legisla-on
1993-‐98
Regional
Civil
Protec-on
regula-ons
33. Observe
to
predict,
predict
to
prevent
modern
predic-on
and
communica-on
of
the
ground
effects
greatly
improves
the
social
response
tradi-onal
modeling
DEWETRA – Real Time fields of
rain intensity, Temperature, …..
RT- Rain Intensity mapTime range
distributed
complex
modeling
34. Observe
to
predict,
predict
to
prevent
The
Founda+on
and
the
role
of
remote
sensing
35. Observe
to
predict,
predict
to
prevent
new
modelling
with
up
to
date
DEM
and
data
observed
by
sensors
on
board
of
satellites
do
deserve
for
improving
ground
processes
predic-on
DEWETRA – Risk Assessment
An example.
RISICO model gives a Wildfire risk index which represents
the potential fire linear intensity (kW/m). It also estimate
the wildfire risk index forecast for the next 72 hours.
36. Observe
to
predict,
predict
to
prevent
december
30
2009
–
inunda-on
of
Massaciuccoli
area,
reclaimed
by
Medici
family,
1570,
Pisa-‐Italy
Elabora-on
from
the
SAR
data
flying
on
the
Cosmo
SkyMed
fleet
of
the
Italian
Space
Agency
with
the
system
DEWETRA
of
the
Civil
Protec-on-‐Cima
Research
Founda-on.
37. Observe
to
predict,
predict
to
prevent
January
9
2010
–
inunda-on
of
Skutari
area,
reclaimed
by
Venice,
1550,
Skutari-‐Albania
Elabora-on
from
the
SAR
data
flying
on
the
Cosmo
SkyMed
fleet
of
the
Italian
Space
Agency
with
the
system
DEWETRA
of
the
Civil
Protec-on-‐Cima
Research
Founda-on.
38. Observe
to
predict,
predict
to
prevent
July
2010,
Indo
river
flooding,
water
depth
near
Peshawuar
Elabora-on
from
the
SAR
data
flying
on
the
Cosmo
SkyMed
fleet
of
the
Italian
Space
Agency
with
the
system
DEWETRA
of
the
Civil
Protec-on-‐Cima
Research
Founda-on.
39. Observe
to
predict,
predict
to
prevent
Cosmo/Skymed
images
acquired
near
Scutari
(Albania)
in
Stripmap
mode
(pixel
resampling
at
10
meters),
in
descending
configura7on
with
right
look
angle
Delle
Piane
et
al.,
FR4.L07.5,
Fr.
17:00
Pierdicca
et
al.,
FR4.L07.1,
Fr.
15:40
CIMA
RESEARCH
FOUNDATION
40. Observe
to
predict,
predict
to
prevent
2007-‐2012
Demonstra-ve
pilot
project
of
ASI
(Italian
Space
Agency)
and
DPC
(Department
for
Civil
Protec-on)
for
EO-‐based
applica-ons
Mul--‐mission,
focus
on
COSMO-‐Skymed
Elena Angiati3, Giorgio Boni2, Laura Candela1, Fabio
Castelli4, Silvana Dellepiane3, Fabio Delogu2, Fabio Pintus5,
Roberto Rudari2, Sebastiano B. Serpico3, Stefania Traverso2,
Cosimo Versace6.
1Italian
Space
Agency,
Unità
Osservazione
Della
Terra,
CGS,
Contrada
Terlecchia,
75100
Matera
(Italy)
2CIMA
Research
Founda-on,
Savona
University
Campus,Via
Armando
Maglioio
2,
I-‐17100
Savona
(Italy)
3University
of
Genoa,
Dept.
of
Biophysical
and
Electronic
Eng.
(DIBE),Via
Opera
Pia
11a,
I-‐16145,
Genoa
(Italy)
4University
of
Florence,
Dept.
of
Civil
and
Environmental
Eng.
(DICEA),
via
S.
Marta,
3
-‐
50139
Firenze
(Italy)
5ACROTEC
S.r.L.,
Via
Armando
Maglioio,
2
17100
Savona
(Italy)
6CONSORZIO
COS
(OT),
Via
Casalnuovo,
86,
75100
Matera
(Italy)
41. Observe
to
predict,
predict
to
prevent
And
now
the
NASA
puzzle
(courtesy
of
NASA-‐restricted
circula-on):why
NASA
distributes
such
a
trick?
At
the
Founda-on
we
feel
there
is
a
basic
misunderstanding.
§
The
Founda-on
unit
dealing
with
satellite
sensors
for
environmental
monitoring
shares
the
interest
on
satellites
images
but
our
paradigm
is
slightly
different
then
NASA
§
Not
from
data
to
images,
but
from
data
to
models
and
possibly,
when
needed
for
communica-on
purposes,
from
models
to
images:
in
the
analysis
of
environmental
transforma-ons
and
environmental
disasters,
images
are
not
enough.
42. Observe
to
predict,
predict
to
prevent
The
Founda+on
and
the
new
paradigms
in
modelling
Con+nuous
chains
from
meteorology
to
hydrology
and
hydraulics
45. Observe
to
predict,
predict
to
prevent
NASA
EARTH
Observatory.
Image
acquired
December
30
2004
by
the
European
Space
Agency
astronaut
Alexander
Gerst.
On
upper
les
corner,
the
orography
46. Observe
to
predict,
predict
to
prevent
9
October
2014.
Mean
sea
level
pressure
(Pa)
at
00UTC
from
ECMWF
re-‐analysis
on
October
9
2014
run
at
00UTC.
A
pressure
gradient
of
the
order
of
4%0
in
a
space
not
exceeding
100
km
is
established
between
the
western
Po
floodplain
and
the
Ligurian
sea.
9
October
2014.
Daily
mean
T2m
temperature
provided
by
the
Italian
Civil
Protec-on
Department
ground
network.
Sea
Surface
Temperature
provided
by
the
Global
1-‐km
Sea
Surface
Temperature
data
set
produced
by
the
JPL
Regional
Ocean
Modelling
System
(ROMS).
A
temperature
gradient
of
8-‐9
C
is
established
between
the
western
Po
floodplain
and
the
Ligurian
sea.
47. Observe
to
predict,
predict
to
prevent
observed
reflec-vity
field
evolu-on
at
eleva-on
z=
3000
m
amsl
(Seiepani
meteo
radar)
from
01:30UTC
to
07:00UTC
48. Observe
to
predict,
predict
to
prevent
Horizontal
wind
and
ver2cal
thermals
at
01:30,
02:00
and
02:30
UTC
49. Observe
to
predict,
predict
to
prevent
The
Founda+on
and
the
uncertainty
in
predic+ng
50. understanding
the
uncertainty
is
a
ques-on
of
swans
I’ll
open
this
part
of
the
lecture
with
a
quite
exhaus-ve
example.
The
example
is
aimed
to
introduce,
without
lengthy
use
of
the
concept
of
probability,
a
discussion
on
the
uncertainty
in
the
hydrometeorogical
predic-ons
and
its
social
relevance.
In
fact
the
decision
maker
of
Civil
Protec-on,
in
any
of
his
levels,
from
municipal
to
suprana-onal
agencies,
is
confronted
with
uncertainty.
51. Observe
to
predict,
predict
to
prevent
Taleb's
thesis
"Simply,
we
cannot
predict"
is
the
-tle
of
the
second
part
of
his
book
The
Black
Swan.
The
impact
of
the
highly
improbable
Mediocristan:
a
world
in
which
the
experts
are
able
to
measure
the
uncertainty
of
future
observa-ons
from
the
observa-ons
of
the
past
Extremistan:
a
world
where
in
some
cases
the
future
eludes
the
measurements
of
the
experts
and
catches
them
Where
we
live?
How
we
learn
from
the
past?
Which
errors
are
possible?
Which
is
our
responsibility
when
we
do
wrong?
The
society
is
equipped
to
respond
to
the
impact
of
the
highly
improbable?
53. each of them with identical Thirrenian seas, with the same
topography and hydrography of the coastal area
Genoa
54. Observe
to
predict,
predict
to
prevent
the stream
the soccer
stadium
with ten thousand identical cities of
Genoa with the same urban planning
developed in the same way
the stream
covered
the stream
mouth
the
stream
the
soccer
stadium
55. Observe
to
predict,
predict
to
prevent
with
ten
thousand
iden-cal
streams
covered
by
an
en-re
monumental
district
designed
by
the
archistar
of
the
fascist
period
56. Observe
to
predict,
predict
to
prevent
the
urban
development
from
1400
to
1937,
five
years
aser
the
stream
was
covered
the
event
theater
57. Observe
to
predict,
predict
to
prevent
57
full
bank
level
flooding
level
when an extreme flood is carried to the sea the
space under the cover is not enough. The
water level rises and touches the inner surface
of the cover. The flow under the cover is
suddenly reduced and a wave of reflux
propagates back. Suddenly the excess
discharge inundates the streets on the two
enbankments.
58. Observe
to
predict,
predict
to
prevent
58
Sunday it will rain for at
least twelve hours, and
the rain depth will
possibly be equal or
exceeding 200 mm
now let us suppose that out of the
ten thousand universes a fall
extreme storm is announced in,
say, three hundred of them
59. Observe
to
predict,
predict
to
prevent
59
Sunday,
october
xx
199y
0
50
100
150
200
250
mm
A
let us choose now, at random, the universe A,
one out of the three hundred universes in which
Sunday it will rain a lot. Describe the event. It
starts raining at noon and it rains until midnight,
but more than two third of the total depth fall
continuously at the beginning of the event.
60. Observe
to
predict,
predict
to
prevent
60
.
teams had to play
their first league
match in the soccer
stadium near the
stream
capacity of 40,000. Heavy rains. Only
10,000 soaked fans under their umbrellas
waiting to see if the match will start.
Three o’ clock sharp. The referee comes
out and throws the ball to see if it
bounces over the green. SPLASH. Again
SPLASH and again SPLASH.
. the referee whistles: game postponed.
Ten thousand people leaving, walking
along the streets on the embankments.
The stream exceeds the full bank flow.
The water touches the cover.The reflux
wave explodes back. The river
inundates the two roads. The water
drags pedestrians and cars
62. Observe
to
predict,
predict
to
prevent
Sunday,
xx
oiobre
199y
B
0
50
100
150
200
250
1 2 3 4 5 6 7 8 9 101112
let us continue to examine the three
hundred universes. Call B the second one.
It starts raining at noon and it rains until
midnight. More than 200 mm. Less than
half in the three hours at the beginning of
the event and the most at the end.
63. Observe
to
predict,
predict
to
prevent
63
teams had to play
their first league
match in the soccer
stadium near the
stream
capacity of 40,000. Heavy rains. Only
10,000 soaked fans under their umbrellas
waiting to see if the match will start.
Three o’ clock sharp. The referee comes
out and throws the ball to see if it
bounces over the green. SPLASH. Again
SPLASH and again SPLASH.
. the referee whistles: game postponed.
Ten thousand people leaving, walking
along the streets on the embankments.
The stream does not exceed the full
bank flow. 10000 fans reached back
their destinations soaked under their
umbrellas.
64. Observe
to
predict,
predict
to
prevent
64
about nine o'clock in the evening it starts again to rain
hard. It rains for three hours continuously. The
stream
exceeds
the
level
of
full
bank
flow.
Same scenario that
we've seen in the universe A. The difference is that in
the universe B it happens shortly after midnight.
Subways are closed. No one in the streets. Only
parked cars. The buses are in the night garages.
Many damages. No victims.
65. Observe
to
predict,
predict
to
prevent
The
event
in
the
universe
B,
that
did
happen
late
in
the
night,
when
the
Genoeses
were
all
home,
is
almost
as
unlikely-‐or
likely-‐
as
that
of
the
Universe
A.
And
so,
among
others,
two
professors
of
Civil
Engineering
are
s-ll
teaching
at
the
University
of
Genoa.
They
went
to
watch
the
match
between
Sampdoria
and
Milan,
and
survived.
Why?
Because
they
were
in
the
universe
B,
so
we
discovered
aser
the
event.
Do
you
perceive
how
thin
is
the
physical
role
of
the
uncertainty
and
how
large
is
the
social
one?
66. Observe
to
predict,
predict
to
prevent
A
few
weeks
aser
the
presenta-on
of
such
an
example
in
Rome
an
extreme
event
hit
the
area
I
just
described.
Very
similar
flooding,
around
one
o’
clock
in
the
asernoon,
with
pupils
leaving
the
schools.
Six
casual-es.
Warnings
were
issued
the
day
before.
I
had
to
explain
to
newspaper
and
tv
people
that’s
impossible
to
predict
weeks
before
the
event.
That
my
tale
at
the
conference
was
not
a
forecast.
Because
to
predict
where
and
how
it’s
easy,
but
to
forecast
when
and
how
much
is
quite
another
maier.
That’s
the
reason
why
the
2011
event
in
Genoa
was
chosen
as
a
study
case
for
Founda-on.
67. Observe
to
predict,
predict
to
prevent
Why
e-‐infrastructures
for
Civil
Protec-on?
Thirty
years
ago
I
began,
with
a
few
friends,
the
construc-on
of
the
system
of
Italian
Civil
Protec-on.
We
put
every
effort
in
so-‐called
non-‐structural
measures,
those
useful
measures
to
alert
the
authori-es
and
ci-zens
when
a
paroxysm
of
meteorology
could
bring
water
to
their
homes,
and
kill
and
destroy
proper-es
and
means
of
produc-on.
So
they
could
be
ready
to
accept
resctric-ons
on
the
use
of
the
land
and
proper-es,
but
also
so
that
they
could
take
simple
temporary
protec-ve
measures.
Because
we
can
-‐
it
always
has
been
-‐
live
in
flood
prone
areas.
The
paroxysmal
events
are
rare
and
do
not
strike
in
the
same
place.
68. Observe
to
predict,
predict
to
prevent
Dealing
with
uncertainty.
By
the
use
of
ensemble
predic-on
in
meteorology
and
by
the
use
of
disaggrega-on
of
predicted
rainfall
fields
from
meteo
to
hydro
scales.
The
Italian
system
for
predic-ons
is
now
distributed
into
a
number
of
technical
groups
of
meteo
and
hydro
experts
at
the
local
scale
and
a
coordina-ng
group
at
the
na-onal
scale.
More
than
one
hundred
skilled
people.
The
procedures
are
extending
to
the
whole
Europe
as
a
best
prac-ce
for
the
European
Civil
Protec-on,
presently
under
transforma-on
and
strengthening.
That’s
the
reason
why
I
think
that
DRIHM
e-‐infrastructure
is
a
very
promising
hot
spot
in
hydrometeorological
research.
69. Observe
to
predict,
predict
to
prevent
S-ll
research
needs?
Oh,
yes.
Nassim
N.
Taleb,
published
in
2007
"The
black
swan:
the
impact
of
the
highly
improbable".
The
book
created
intense
controversy
in
mathema-cal
circles.
It
deeply
revises
the
paradigms
of
the
forecast
of
future
states
of
a
system,
based
on
the
observa-on
of
past
states.
The
Taleb
thesis,
in
essence,
is
that
the
human
condi-on,
which
learns
from
experience,
forces
into
a
mental
tunnel
the
predic-ons
of
what
might
happen.
The
predic-on
tunnel
is
formed
by
the
experience
of
past
events,
among
which
the
highly
unlikely
event
almost
never
appears
because
it
is
very
rare
and
therefore
almost
never
belonged
to
the
experience.
70. Observe
to
predict,
predict
to
prevent
I
did
try
to
offer
the
example
in
a
way
that
I
hope
is
readable.
I
did
it
in
order
to
avoid
that
e-‐infrastructures
are
perceived
as
the
saving
solu-on
to
all
the
problems
of
dealing
with
uncertainty.
e-‐infrastructures
allow
the
operators
to
operate
repeated
simula-ons
of
reality
much
faster
than
before
and
so
give
the
operators
-me
to
think.
The
basic
problems,
why
we
have
to
think
the
members
of
the
ensembles,
true
ensambles
or
poor
man
ensembles,
equiprobable,
or
why
we
have
to
think
members
of
the
rainfall
field
disaggrega-on
indipendent
on
the
terrain
orography,
are
s-ll
there
as
food
for
the
minds
of
young
researchers.
71. Observe
to
predict,
predict
to
prevent
Why
e-‐infrastructures
for
DRR?
For
climate
change
applica-ons
the
Taleb’s
effect
stays
upstream
of
the
future
meteorological
possible
states.
The
uncertainty
is
absorbed
into
the
construc-on
of
future
clima-c
systems.
Their
effects
are
highly
unlikely
events
per
se.
Contrary
DHIHM
e-‐infrastructure
plays
the
essen-al
role
of
a
specific
tool,
a
quite
powerful
tool,
to
inves-gate
the
effects
at
small
scale,
i.e.
the
scale
of
the
impacts,
condi-onal
on
possible
meteorological
states.
It’s
the
tool
for
evalua-ng
the
effects
of
disaster
scenarios
through
repeated
simula-on
experiments
that
the
e-‐
infrastructure
easily
allows.
72. Observe
to
predict,
predict
to
prevent
Why
DRIHM,
in
essence?
There
is
no
doubt
that
the
e-‐infrastructure
is
the
most
appropriate
tool
to
facilitate
the
work
of
forecasters
in
the
field
of
civil
protec-on
and
simplify
the
role
of
risk
managers
or
planners
in
the
field
of
disaster
risk
reduc-on.
However,
as
I
hinted,
here
and
there,
there
is
s-ll
a
lot
of
food
for
the
mind.
I
wish
you
a
long
career
of
reflec-ons
and
successes.
Like
I
had.
Thanks
for
your
aien-on.
73. Monitoring
the
effec2veness
of
the
Italian
Civil
Protec2on
System:
Decision
making
in
a
overcau2ous
jurispruden2al
environment
A
few
word
more
on
trial
environment
74. Observe
to
predict,
predict
to
prevent
20
mm
July
2nd,
2006
200
mm
July
3rd,
2006
75. Observe
to
predict,
predict
to
prevent
Our
Observatory
>200
casual2es
0
2
4
6
8
10
12
14
16
18
20
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
Number
of
Proceedings
Years
#
procedimen-
Proceedings
>50
pending
proceedings
>150
duty
holders
involved
17/20
Regions
involved
76. Observe
to
predict,
predict
to
prevent
Observed
cri-cali-es
Civil
Protec-on
effec-veness
0
50
100
150
200
250
300
350
400
450
500
0
2
4
6
8
10
12
14
16
18
20
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
Number
of
Events
Number
of
Proceedings
Year
#
procedimen-
#
even-
Proceedings
Events
78. Observe
to
predict,
predict
to
prevent
• Increased
number
of
alerts;
• Increased
level
of
alerts;
• Adop-on
of
restric-ve
measures
(i.e.
evacua-ons,
mobility
limita-ons…);
• Preven-ve
shutdown
of
public,
private
produc-ve
buildings.
Ac-ve
“defensive
behaviour”:
• Resigna-on
from
appointments
(lowered
professional
level
of
CP
operators);
• Fragmenta-on
of
mandates
(nobody
wants
to
take
decisions
in
an
uncertain
world);
• Suppression
of
services.
Passive
“defensive
behaviour”:
• Fears
of
dutyholders;
• Inflexibility
of
the
system.
Impossibility
of
valorising
mistakes:
Observed
Cri-cali-es
79. Observe
to
predict,
predict
to
prevent
Access
to
informa2on
Consulta2on
of
available
documenta2on
Par2cipatory
approaches
for
emergency
planning
Resilienceand
responsibilityof
communities
One
(out
of
many)
possible
way
foreward
