Download CLIME-DSS: A decision support system for assessing impacts of

Climate and Water Presentation of climate change and its
impacts on quantity and quality of water
Harri Koivusalo1, Teemu Kokkonen2,
Ari Jolma3, Hanne Laine2, Olli Varis2
1
Finnish Forest Research Institute, Joensuu Research Unit
2 Helsinki University of Technology, Laboratory of Water Resources
3 Helsinki University of Technology, Laboratory of Geoinformation and Positioning
Technology
Terms of reference
• Considering the potential impacts of climate
variability and change on water resources, as well
as uncertainties involved in assessing the impacts
– To study and report how scenarios provided by regional
climate models should be presented to the end users
dealing with water resources management
– To study and report how assessments based on
environmental simulation models and regional climate
scenarios can be condensed and presented to the endusers in a readily comprehensible form
– To liaise with and receive feedback from those experts of
the Association working on assessing the effects of climate
change on water resources
Background
Climate and lake impacts
in Europe (2003-2005)
• Participants
• Project outline
PROJECTION
Developing scenarios
of the future climate
ATTRIBUTION
Quantifying the effects of
historical changes in the
climate on lake dynamics
SIMULATION
Modelling the effects of
future changes in the
climate on lake dynamics
PREDICTION
Assessing- the impact of
the projected changes on
lake dynamics
IMPLICATION
Policy and
socio-economics
Climate and lake modelling in CLIME
Weather
generator
Observations
HadAM3
UK Metoffice
PROBE
HadRM3p
ECHAM4/OPYC3
Max-Planck,
Germany
UK Metoffice
RCAO
SMHI
GWLF
PROTECH
CLIME-DSS
• Visualises climate change across
Europe
• Summarises how climate change
affects lake characteristics
– Visualise the difference between control
(1961-1990) and future (2071-2100)
periods
• How successful was the presentation
in CLIME-DSS?
Expert opinions about
dissemination of
climate change
Esurveyspro survey service
http://www.esurveyspro.com
Respondents
a)
Southern Europe
Northern Europe
Caucasus / Middle East
Other (Central Europe / Turkey)
Eastern Europe
• Internet survey to
> 160 people in
RA VI countries
• 37 replies
Western Europe
0
b)
10
20
30
Governance
Research
Consultancy
Other
Teaching
Industry
0
c)
10
20
30
40
50
hydrology
meteorology
water and sanitary engineering
information technology
agricultural and forest sciences
0
10
20
30
Respondents %
40
50
Wintertime prepitation
(RCAO-E)
• Clarity of the mapbased presentation
of precipitation?
sufficiently
All
North Europe
Outside North Europe
well
poorly
0
10
20
30
40
50
Respondents %
60
70
80
Different ways representing
climate change impact on
precipitation
Respondents %
50
change in the mean annual
precipitation
40
30
change in the mean seasonal
precipitation
20
change in the minimum annual
precipitation
10
re
so
le
va
m
nt
ew
ha
tr
el
ev
an
no
t
nre
le
va
nt
no
op
in
io
n
re
le
va
nt
change in the maximum short term
precipitation
50
predicted mean annual future
precipitation
40
30
predicted mean seasonal future
precipitation
20
predicted minimum annual future
precipitation
10
predicted minimum seasonal future
precipitation
re
le
so
va
m
nt
ew
ha
tr
el
ev
an
no
t
nre
le
va
nt
no
op
in
io
n
re
le
va
nt
0
ve
ry
b)
Respondents %
• Absolute
precipitation in
future
change in the minimum seasonal
precipitation
0
ve
ry
• Change between
future (20702100) and control
(1960-1990)
periods
a)
predicted maximum short term future
precipitation
• Clarity of the mapbased presentation
of air temperature?
Summertime air
temperature
sufficiently
All
Hydrologists
Meteorologists
poorly
well
0
10
20
30
40
Respondents %
50
60
Different ways representing
climate change impact on air
temperature
• Absolute air
temperature in
future
b)
Respondents %
• Change
between future
(2070-2100)
and control
(1960-1990)
periods
a)
60
50
40
30
20
10
re
le
so
va
m
nt
ew
ha
tr
el
ev
an
no
t
nre
le
va
nt
no
op
in
io
n
50
40
30
20
10
re
le
so
va
m
nt
ew
ha
tr
el
ev
an
t
no
nre
le
va
nt
no
op
in
io
n
re
le
va
nt
0
ve
ry
Respondents %
ve
ry
re
le
va
nt
0
change in the mean annual air
temperature
change in the mean seasonal air
temperature
change in the annual maximum air
temperature
change in the seasonal maximum air
temperature
change in the annual minimum air
temperature
change in the seasonal minimum air
temperature
predicted mean annual future air
temperature
predicted mean seasonal future air
temperature
predicted annual maximum future
air temperature
predicted seasonal maximum future
air temperature
predicted annual minimum future air
temperature
predicted seasonal minimum future
air temperature
• Clarity in presenting seasonal
values of hydrometeorological
variables in selected location?
informative
somewhat informative
very informative
no opinion
non-informative
0.00
10.00
20.00
30.00
Respondents %
40.00
50.00
• Clarity in presenting range of
seasonal runoff in selected
location?
informative
somewhat informative
very informative
no opinion
non-informative
0.00
10.00
20.00
30.00
Respondents %
40.00
50.00
• Clarity in presenting change in climate
depicted as climate migration from one
region to another?
informative
somewhat informative
very informative
no opinion
non-informative
0.00
10.00
20.00
30.00
Respondents %
40.00
50.00
Relevance of selected lake
variables
Different ways representing
climate change impact on water
quality
50
40
30
20
10
Respondents
Respondents
% %
• Change
between future
and control
algae level
50
60
40
50
30
40
20
30
10
20
10
0
0
ve ve
ry ry
re re
le lev
va a
nt nt
r r
so so ele elev
m me va an
ew w nt t
ha ha
tr tr
el ele
ev v
a a
n
no o nt nt
n- nre re
le lev
va a
nt nt
no no
op op
in ini
io on
n
b)
a)
re
le
so
va
m
nt
ew
ha
tr
el
ev
an
t
no
nre
le
va
nt
no
op
in
io
n
re
le
va
nt
0
ve
ry
• Change
between future
and control
nutrient level
Respondents %
a)
change in the
load
change in the
nutrient load
change in the
nutrient load
change in the
nutrient load
change in the
nutrient load
change in the
nutrient load
mean annual nutrient
mean seasonal
maximum annual
maximum seasonal
minimum annual
minimum seasonal
predicted mean annual nutrient load
(in
the future)
change
in the mean annual algae
predicted
mean seasonal nutrient
concentration
load
change in the mean seasonal algae
predicted
maximum annual nutrient
concentration
load
change in the maximum annual
predicted
maximum seasonal
algae concentration
nutrient
load
change in the maximum seasonal
predicted
minimum annual nutrient
algae concentration
load
change in the minimum annual
predicted
minimum seasonal nutrient
algae concentration
load
change in the minimum seasonal
algae concentration
Change in
hydrometeorological
variables → Change
in a lake variable
Current level of a lake
variable in a season
Projected level of a
lake variable
Probability
distributions
characterise current
and projected levels
of a lake variable
• Clarity in presenting the current and
predicted distributions for average
summer time DOC concentration?
a)
b)
while direction of change can be
detected it is not easy
no opinion
direction of change can be easily
detected
while change in variability can be
detected it is not easy
no opinion
change in variability can be easily
detected
direction of change cannot be detected
change in variability cannot be detected
0
10
20
30
Respondents %
40
0
10
20
30
Respondents %
40
50
Conclusions
• Map-based tool well suited for disseminating
RCM results
– view large areas or select a point for detailed
examination
• Coloured visualisations and tabulated
information equally informative and useful
• Methods behind the visualisations and
tables should be more transparent
• Web pages: http://clime.tkk.fi/jrc/
– Contact:
• [email protected]
• [email protected]
Future activities on “Climate and
Water” in WMO RA VI WGH
• Role of reservoirs in the changing climate
– Implications on water balance, greenhouse
gases, etc.
– Exploitation of global GIS data
– Reservoirs and climate change in RA VI
countries
• Adaptation to climate change
– Water resources management in changing
climate
– Use of reservoirs in the adaptation
– Flood risk mitigation, drought risk alleviation
MANY THANKS TO ALL RESPONDENTS
River Iijoki, 65°22’ 26°47’, 27 Nov 08