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).

Generating climate scenarios using climate models

• 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

Generating climate scenarios using climate models

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

Generating climate scenarios using climate models

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)

Constructing climate scenarios from existing databases

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

Constructing climate scenarios from existing databases

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.

Projections for Malawi

Projections for Malawi

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).

Projected changes in Malawi’s growing season. Clim Dyn (2015) 45:1673–1698

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).

Projected changes in Malawi’s growing season. Clim Dyn (2015) 45:1673–1698

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)

Important considerations (2/4)

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.

Important considerations (3/4)

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

Important considerations (4/4)

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