Analyzing climate change risks_constructing climate scenarios

Least Developed Countries Expert Group (LEG)
Regional training workshop on National Adaptation Plans (NAP) for Anglophone Africa
27 February to 03 March 2017
Bingu International Convention Centre
Lilongwe, Malawi
Analyzing climate change risks
- constructing climate scenarios

Changes in the climate – the global picture
Source: Climate Lab Book (2017). Climate spirals. Available at <http://www.climate-lab-book.ac.uk/spirals>. Accessed 20
February 2017

Changes in the climate – trends in extreme events in Malawi
• Floods,
hailstorms,
strong winds,
droughts
• Occurred more
frequently in
the 21st century
• Erratic rainfall
(late onset and
early cessation
of rains)
• Prolonged dry
spells
• Etc.

Trends in temperature indices for Malawi for the period 1961-2000

Defining climate scenarios
A plausible and often simplified representation of the future climate,
based on an internally consistent set of climatological relationships
that has been constructed for explicit use in investigating the
potential consequences of anthropogenic climate change, often
serving as input to impact models. Climate projections often serve
as the raw material for constructing climate scenarios, but climate
scenarios usually require additional information such as the
observed current climate. A climate change scenario is the
difference between a climate scenario and the current climate.
Source: Figure TS-15 in Stocker et al., 2013: Technical Summary. In: Climate Change 2013: The Physical Science Basis.
Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker,
T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge
University Press, Cambridge, United Kingdom and New York, NY, USA.

Risk of climate-related impacts
Source: Figure SPM.1 in IPCC, 2014: Summary for policymakers. In: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and
Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Field, C.B., V.R.
Barros, D.J. Dokken, K.J. Mach, M.D. Mastrandrea, T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S.
MacCracken, P.R. Mastrandrea, and L.L. White (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1-32.

Types of climate scenarios
•Incremental
scenarios
• Assume a realistic
incremental
change in climate
over time
• e.g. decline of
summer rains by
5% per decade
Analogue
scenarios
• Spatial -
projecting climate
of one location
from another
• Temporal -
reconstruction of
past climate
Climate model
based scenarios
• Mathematical
representation of
the climate
system
• Coupled
Atmosphere-
Ocean Climate
Models
• Dynamically
downscaled
AOGCMs
• Statistically
downscaled
AOGCMs

(a) previous sequential approach; (b) parallel approach. Numbers indicate
analytical steps (2a and 2b proceed concurrently). Arrows indicate transfers
of information (solid), selection of RCPs (dashed), and integration of
information and feedbacks (dotted). Source: Moss et al. (2008).
Approaches to the development of global scenarios

Generating climate scenarios using climate models
Climate models
• Mathematical representation of the climate system based on the
physical, chemical and biological properties of its components,
their interactions and feedback processes, and accounting for
some of its known properties;
• Coupled Atmosphere–Ocean General Circulation Models
(AOGCMs) provide a representation of the climate system that is
near or at the most comprehensive end of the spectrum currently
available;
• There are two levels or hierarchy:
a) General Circulation Models providing information at global
scale – they have coarse resolution (250 – 600 km over land)
b) Regional Climate Models providing information at regional
scale – have higher resolution (~ 50km and less).

• Depict the climate
using a three
dimensional grid over
the globe;
• Horizontal resolution of
between 250 and 600
km;
• 10 to 20 vertical layers
in the atmosphere and
sometimes as many as
30 layers in the
oceans.
General circulation models
Source: http://www.ipcc-data.org/guidelines/pages/gcm_guide.html

Regional Climate
Models
List of Regional Climate Models which are officially registered with CORDEX.
Available at www.cordex.org
• Involve
dynamically
downscaling
GCM data
• Run at
continental
scale with
boundary
conditions
from GCMs
• Good for
investigating
variability

Steps Construction of relationships between local climate
variables (e.g. surface air temperature and precipitation)
and large-scale predictors (e.g., pressure fields);
Application of the relationships to the largescale climate
variables from the GCMs to estimate corresponding local
and regional characteristics.
Assumptions High quality large-scale and local data being available
for a sufficiently long period to establish robust
relationships in the current climate;
Relationships which are derived from recent climate
being relevant in a future climate.
Statistical downscaling

Constructing climate scenarios from existing databases
Accessing CORDEX data
 Open www.cordex.org
 Go to Data access and
select ESGF – A page that
has ESGF nodes will appear
 Select any of the nodes (e.g.
DKRZ, Germany) – a
separate page will appear
with data search
 Under Search Data click on
create account (if you do not
have it yet)

Accessing CORDEX data
(contd.)
 Join a research group: click
Group Registration: CORDEX
Research.
 Insert you OpenID and you will
loged in
 Go back to the ESGF site and
click CORDEX Data Search – a
page with various filter will
appear
 After filtering click search
button and data files will display
below it

Accessing CORDEX data (contd.)
 Add files to cart and then download wget script
 Before running the script you need to download credential certificate
at https://meteo.unican.es/trac/wiki/ESGFGetCredentials go to
download folder on terminal and run the command: java -jar
getESGFCredentials.jar – a window will appear
 Under ID provider select custome, then provide your OpenID and
password.
 Select another folder (where your certificates are)
 Check credential… and egs.truststores
 Run wget script on terminal
 Your files will start downloading
 Beginning of analysis

Temperature: observed trends and projections by the IPCC for Africa
Source: Excerpt from Fig 22-1. IPCC, 2014: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B:Regional Aspects. Contribution of Working Group
II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Barros, V.R.,C.B. Field, D.J. Dokken, M.D. Mastrandrea, K.J. Mach, T.E. Bilir,
M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L. White (eds.)]. Cambridge
University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 688.

Source: Figure AI.49 in IPCC, 2013: Annex I: Atlas of Global and Regional Climate Projections [van Oldenborgh, G.J., M. Collins, J. Arblaster, J.H. Christensen, J.
Marotzke, S.B. Power, M. Rummukainen and T. Zhou (eds.)]. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth
Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V.
Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
Temperature change in Southern Africa, June-August

Precipitation: observed trends and projections by the IPCC for Africa

Precipitation change in Southern Africa, October-March
Source: Figure AI.50 in IPCC, 2013: Annex I: Atlas of Global and Regional Climate Projections [van Oldenborgh, G.J., M. Collins, J. Arblaster, J.H. Christensen, J.
Marotzke, S.B. Power, M. Rummukainen and T. Zhou (eds.)]. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth
Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V.
Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

Applying climate scenarios in impact studies (example)
Projected changes in Malawi’s growing season a
a source: Vizy, E. K., Cook, H. K., Chimphamba, J. and McCusker, B. (2015).
Projected changes in Malawi’s growing season. Clim Dyn (2015) 45:1673–1698
Analysis of
projected
future
changes
• Confidence test
• Simulating present
• Student’s t-test, etc.
• Differences between
climatology and future
simulations
Estimation
of the
growing
season
• Length, onset, demise
• Methods
• Prec./PET water
balance
• Root zone soil
moisture approaches
RCM
simulations
• 1989-2008 (climatology)
• 2041-2060 (mid-century)
• 2081-2100 (late-century)

Applying climate scenarios in impact studies (growing season example)
a source: Figure 4 in Vizy, E. K., Cook, H. K., Chimphamba, J. and McCusker, B. (2015).
MID21–LATE20 growing season length difference (days) for the (a) FAO-
updated, (b) SMA-U, and (c) SMA-V methods a

Applying climate scenarios in impact studies (growing season example)
a source: Figure 6 in Vizy, E. K., Cook, H. K., Chimphamba, J. and McCusker, B. (2015).
LATE21–LATE20 growing season length difference (days) for the (a) FAO-
updated, (b) SMA-U, and (c) SMA-V methods a

Important considerations (1/4)
Baseline climate data
• Helps to identify characteristics of the
current climate regime such as means,
seasonal patters, trends, variability,
extremes, etc.;
• Based on at least 30 years of observed
data – see WMO climatological
standard normals
(http://www.wmo.int/pages/prog/wcp/wc
dmp/GCDS_1.php);
• Current climatological standard normal
period is 1961-1990
Map source: Malawi Department of Climate Change and Meteorological Services (2017). Climate of
Malawi. Available at http://www.metmalawi.com/climate/climate.php (Accessed 22 February 2017)

Uncertainty
• Sources
a) Uncertainties in
future emissions
b) Uncertainties in
future
concentrations
c) Uncertainties in the
response of the
climate
The global goals under the Paris Agreement provide a basis for
removing the uncertainties in decision-making
Figure source: Preliminary Scenario MIP SSP for the Coupled Model Intercomparison Project 6, O’Neil et al,
GMD Discussion 2016, from Riahi, K., van Vuuren, D.P., Kriegler, E., Edmonds, J., O’Neill, B.C., et al.: The
Shared Socioeconomic Pathways: An Overview, Global Environmental Change (submitted), 2016.

Global goals under the Paris Agreement a
Article 2.1(a)
“Holding the increase in the global average temperature to well
below 2 °C above pre-industrial levels and pursuing efforts to limit the
temperature increase to 1.5 °C above pre-industrial levels,
recognizing that this would significantly reduce the risks and impacts
of climate change”
Article 7.1
Parties hereby establish the global goal on adaptation of enhancing
adaptive capacity, strengthening resilience and reducing vulnerability
to climate change, with a view to contributing to sustainable
development and ensuring an adequate adaptation response in the
context of the temperature goal referred to in Article 2.
a Complete information on the Paris Agreement is available at http://unfccc.int/9485

Resource requirements for generating climate scenarios
• Good technical capacity on the climate science
• Large computer resources
• Stable power supply
• Institutional support

Contact:
The Chair
Least Developed Countries Expert Group (LEG)
leghelp@unfccc.int

Analyzing climate change risks_constructing climate scenarios

More Related Content

What's hot (20)

Viewers also liked (20)

Similar to Analyzing climate change risks_constructing climate scenarios (20)

More from NAP Events (20)

Recently uploaded (20)

Analyzing climate change risks_constructing climate scenarios