Scenario development and analysis

Question 1

Swart et al. - Plausible future pathways of combined social and environmental systems under conditions of uncertainty, surpise, choice, complexity

Answer 1

–> Scenario analysis !
including new participatory and problem oriented approaches
= tool
for integrating knowledge, scanning the future and internalising human choice in SScience

Question 2

Swart et al. - Maintaining resilience: 3 imperatives for SD

Answer 2

1. ecological - staying with biophysical carrying capacity
2. social - systems of gov propagating values people want to live by
3. material - adequate material standard of living for all

Question 3

Swart et al. - Core questions for sustainability

Answer 3

• Understanding and integrating system complexity including provision of information
• Representing interactions, behaviors and emergent properties of combined natural and social systems
• Providing decision makers with advice
• etc. - there are a lot of core questions however they don’t envision alternative futures

Question 4

Swart et al. - Why scenarios are the GOAT

Answer 4

• broaden focus to encompass a richer set of considerations
• Derives from ‘human sciences’ emphasizing:
  –> develop approaches to evaluate future options
  –> recognizing diverse epistemologies & problem definitions
  –> encopassing the normative nature of SD

Question 5

Swart et al: Scenario definition

Answer 5

• integrated scenarios may be thought of as coherent and plausible stories, told in words and numbers, about the possible co-evolutionary pathways of combined human and environmental systems
• NOT predictions or forecasts
• need for flexibility and creative exploration

Question 6

Swart et al: Scenarios are made up of…

Answer 6

• problem boundaries
• characterization of current conditions and processes driving change
• critical uncertainties and assumptions on how they are resolved
• images of the future

& human and environmental responses

Question 7

Swart et al: Quantitative v.s. Qualitative

Answer 7

Quantitative
using mathematical algorithms and relationships to represent key features of human and environmental systems

Qualitative
other factors influencing the future eg. system shifts, , surprises and non-quantifiables eg.
values, behaviors and institutions, providing a broader perspective

Question 8

Swart et al: Descriptive vs normative scenarios

Answer 8

descriptive scenarios
- i.e., scenarios describing possible developments starting from what we know about current conditions and trends
- Aim: evaluating feasability and consequences or desirable or undesirable outcomes

normative scenarios
- i.e., scenarios which are constructed to lead to a future that is afforded a specific subjective value by the scenario authors
- Aim: articulating different plausible future societal developments & exploring their consequences

In practice, scenarios have elements of both types

Question 9

Swart et al: What-if analysis & backcasting scenarios

Answer 9

What-if analysis
-> imagining feasability and implications of desirable futures (forwards looking analysis)
–> identifying bandwidth of initial trajectories & available actions to bend the curve

Backcasting
-> imagining risks of undesirable futures (possible end states)
–> identifying long term risks

–> Need a combination of both

Question 10

Swart et al: How must scenario analysis contribute? (5)

Answer 10

1. must consider the interplay and dynamic evolution of social, economic and natural systems, by being an integrated and long-term perspective
2. must address S as tentative, open and iterative
3. must involve science and policy and public participation
4. must capture structural discontinuity & surprise in SES
5. must recognize the power of alternatives

Question 11

Swart et al: How can scenario analysis contribute? (9)

Answer 11

1. Spanning spatial scales - local to global –> linkages
2. Accounting for temporal inertia and urgency –> backcasting from long-term goals
3. Recognizing the wide range of outlooks - wide range of usable knowledge
4. Reflecting functional complexity and multiple stresses –> What-if scenarios for charting complex linkages
5. Integrating across themes and issues - ecological, social, economic, ethical and institutional dimensions –> Integrated analysis
6. Reflecting uncertainties, incorporating surprise, critical thresholds and abrupt change –> in what-if scenarios
7. Accounting for volition –> exploring normative aspects, reflecting worldviews and biases
8. Combining qualitative and quantitative analysis –> complementary
9. Engaging stakeholders (engaging stakeholder participation for more policy action) –> incorporating feedback

Question 12

Swart et al: Aspects of scenarios deserving special attention (2)

Answer 12

1. scenarios can legitimize rather than inform policy decisions
   (v.s. simple information provided to improve decisions)
2. important role for more public and stakeholder involvement in scientific activities –> participatory forms of scenario analysis can address normative aspects by incorporating values and preferences

Question 13

Swart et al: Aspects to consider when making scenarios (5)

Answer 13

1. sufficiently large & diverse group of participants -> mutual learning and co-production of knowledge
2. Adequate time for problem definition, knowledge base, iterative scenario analysis, review & outreach; for trust and effective communication among parties!
3. Full account of available scientific knowledge and rigor of methods; including uncertainties
4. Explicit discussion about normative scenario elements; (1) assumptions about future behaviors and worldviews & (2) the worldviews of the scenario-makers affect how the story is told and lessons drawn from it –> Through communication, challenge mental maps of participants
5. Development of coherent, engaging stories about the future; incorportaing beliefs, hopes and dreams with a consistent logic

Question 14

Swart et al: revealing and addressing critical questions (2)

Answer 14

1. Exploring possible surprise events & addressing possible seeds of change (social and natural developments with the potential to significantly change society)
2. Place the focal problem in a broader context –> Systemic, integrated perspective to reveal key linkages between problems that influence key problem

Question 15

Model: definition

Answer 15

A simplified description, especially a mathematical one, of a system or process, to assist calculations and predictions

Be clear with your model goal, and what it can and cannot do

Question 16

Types of models

Answer 16

1. Conceptual models
- Mental models
- Ideas
- Causal-loop diagrams
- Social sciences/psychology
–> Visual but simplistic

2. Physical models
–> easier than conceptual models, but time-consuming and expensive

3. Mathematical/computational models
- Statistical models
- Theoretical models
- Process-based models
–> quantified but not necessarily always adaptable

Question 17

Uncertainty

Answer 17

1. Parameter uncertainty
   - Assumes the model is perfect, but certain variables are not known accurately
   –> “FInd best fit” , there’s an uncertainty range ~quadratic line 96% = 95 of data is below - low, medium and high line
2. Uncertainty of the model itself
   –> Lack of understanding of the process
   –> Wrong assumptions
   –> Too simple representation of reality

• GARBAGE IN = GARBAGE OUT
• internal (mistakes, lack of understanding) or external (uncertain future developments)

–>Scenarios consider uncertainty outside the model

Question 18

Model quote

Answer 18

All models are wrong, but some models are useful

Question 19

When is a model correct?

Answer 19

–> We cannot know for sure, we can only know the past

1. Test model structure (logic)
   - are equations correct?
   - are units correct?
   - are parameters logically defined?
2. Test model behavior
   - sensitivity analysis to determine key parameters
   - compare model behavior with past data (backcasting)
   - evaluate models against other models

Question 20

Use of scenarios

Answer 20

• explore possible futures using consistent models/within plausible range of options
• ## test the consequences of policy decisons –> inform policy makers

Question 21

Uncertainties:
Scenarios, speculation, predictions/forecasts

Answer 21

From least uncertain to most uncertain:
1. predictions/forecasts
2. scenarios
3. speculation

Question 22

Scenarios: definition

Answer 22

• For multiple goals and figuring out how to get there (like a ski touring outing) = possible future stories (qualitative or quantitative) with a goal
• relations and interactions
• assess uncertainties
• calculate boundaries

Question 23

How to build a scenario

Answer 23

1. Focal question: concise question
2. Key factors affecting the question: trends and events
3. Driving forces: the underlying causes that drive the factors
4. Rank critical uncertainties: which drivers have the highest impact and uncertainties
5. Scenario logic: logicall develop a scenario based on the most important drivers
6. Scenario development: a story/narrative of the future developments depending on how drivers play out
7. Implications: use scenarios as vehicles for conversation
8. Early signs: detect early warning signals that a scenario may be unfolding

Question 24

Scenario matrix

Answer 24

• map uncertainties in a 2 by 2 matrix with high and low for each
• eg. challenge for adaptation (low to high) & challenge for mitigation (low to high)
• eg. individual to collective values & distributed to centralised support

Question 25

Variables for SD considered by Club Of Rome

Answer 25

1. population
2. industrialisation
3. pollution
4. food production
5. resource depletion

Question 26

RCPs numbers

Answer 26

RCP 8.5 = ~4°C
RCP 6.0
RCP 4.5
RCP 2.6 =~2°C
RCP 1.9 =~1.5°C

Question 27

RCP

Answer 27

trajectories of emissions and concentrations

Representative concentration pathways
= describe radiative forcing [W/m2] in 2100 based on socio-economic development and their GHG emissions

Scenarios used as input for modelling CC

Question 28

Sequential approach: linear chain of causes and consequences of CC

Answer 28

1. Socio-economic scenarios (population, GDP, energy…)
2. Emissions scenarios (GHG, land use and land cover…)
3. Radiative forcing scenarios (atmospheric concentrations, carbon cycles…)
4. Climate model scenarios (temperature, humidity…)
5. Impact, adaptations, vulnerability studies (coastal zones, food security…)

Developed by communities from 1 then 2 and so on

Question 29

SSPs

Answer 29

Alternative societal pathways
Trends of socio-economic developments & narrative descriptions & quantifications

Shared socio-economic pathways - developed in parallel to RCPs but focused socio-economic developments and mitigation

Scenario matrix: challenges for mitigation & challenges for adaptation

Question 30

RCPs & SSPs

Answer 30

• Used to quantify impact and mitigation of future CC

Question 31

Why RCPs OR concentrations OR temperature?

Answer 31

RCPs
- because temperature changes depending on where you are
- it is less uncertain, easy to calculate

Concentrations
- Too GHG/CO2 specific

Temperature
- more intuituive
- all GHGs

Using RCPs to lower uncertainty
Each step in model adds uncertainties