Week 1 Summary PDF

**Lecture 1 -- Introduction** A graph showing the temperature of the earth Description automatically generated Why are impact assessments useful for higher scenarios? 1. To be **prepared** for worse scenarios. But there is a large uncertainty in the higher scenarios. 2. To create **awarene...

**Lecture 1 -- Introduction** A graph showing the temperature of the earth Description automatically generated Why are impact assessments useful for higher scenarios? 1. To be **prepared** for worse scenarios. But there is a large uncertainty in the higher scenarios. 2. To create **awareness** for these higher scenarios 3. The goals of the Paris Agreement are very much unlikely, as most part of the world does not meet the requirements. Thus, higher scenarios need to be modelled uncertainty increases along the impact modeling chain.  The dotted line represents the past emissions A graph with blue and green bars Description automatically generated with medium confidence This data is from insurance: losses from natural disasters. The population and economic growth (wealth/assets) have increased. Thus, the losses are bigger. But what is the exact effect on the population? *Adaptation and mitigation policies limit climate impacts* **Adaptation:** - Avoid some of the **consequence** of climate change through automatic or planned adaptation - Policy question: where should which adaptation measures be implemented and how much is worthwhile avoided climate impacts? **Mitigation:** - Prevent climate change by **reducing** greenhouse gas emissions - Part of impact assessments via lower emissions and climate change scenarios - International mitigation efforts are insufficient for significantly reducing risk - Policy question: how much mitigation is worthwhile given avoided climate impacts? Different impacts of natural disasters / example Hurricane Katrina **Hazard conditions (immediate)** - Wind Speed - Surge - Water shortage - Example: wind speed of 130 -280 kmh/ flooded 80% of new Orleans **Direct Impacts (immediate)** - Property damage: 200k homes destroyed / 125 bln property damage - Infrastructure damage / crop losses: - Evacuation: 80% evacuated - Injuries - Casualties (deaths) : 1,836 deaths **Indirect Impacts** (**2 year statistics**): - Temporary migration / business interruption: 50% of evacuees did not return - Disrupted trade flows: disruption oil grain and timber trade - Reconstruction - Employment effects: 25% employ loss in 9/11 sectors and 7% employment rise in construction sector - Temporary (negative) effects economic growth: economic impact of 150 bln **Indirect Impacts (\>8 year statistics):** - Permanent migration: 33% of the evacuees did not return - Structural change market equilibrium: Unemployment effects disappear - Structural change trade flows - Change to a new (lower) economic growth path: Reduced savings and increase in income Computational and empirical methods for assessing the eoconomic impacts of natural disasters and climate change: 1. **Direct Impacts of Natural Disasters**: - Analyzed using Catastrophe Models which focus on hazards, exposure, and vulnerability. 2. **Indirect Economic Impacts of Natural Disasters**: - Studied through **Input-Output Models** (for short- to medium-term trade flow disruptions) and - Computable **General Equilibrium Models** (for long-term market shocks affecting supply and demand). 3. **Aggregated Economic Impacts from Climate Change**: - Assessed by **Integrated Assessment Models**, which incorporate climate and economic models to understand broader impacts. **Bottom-up appraoches:** collect (survey) data on recent past and present vulnerability to climate risk. - Finer geogrpahical scale, people-centered and focuso n physcial and social processes - Especially useful in data scarce regions for guilding climate policy and calibrating models - Involves econometric techniques, for exmaple for analyzing relations between climate varialbes and impats or adaptaion and its driver - **Complementary** to top-down models who give insights into both present and future climate risk - **Mixed Method approach:** interviews, forcus groups, surveys and models for understanding local climate risk and adaptation options. **Lecture 2 -- Scenarios as a tool to Explore Future Uncertainties in Climate Impacts** Why do a climate impact assessments? 1. Explore severity of (future) climate impacts - Changes in the climate system - Changes in socioeconomic conditions 2. Inform climate policy: how can impacts be reduced? - Mitigation - Adaptation **First Part: IPCC assessments** IPCC AR (assessments reports) *synthesize* the current litereature on climate change **AR5/AR6**: these are reports. AR6 is just completed. Then the new assessment cycle for AR7 is started. **Working groups I, II, III**: are part of the IPCC, I is working on the physical, II is working on climate adatpation and III is working on mitigation **Paris Agreement (2016**): main goal is to keep climate change below 1.5 degrees after industralisation. **COP29:** every year countries come together to make agreements about clmate topics. **Second Part: Climate Impact Assessments**  Scenarios: "how the economy will develop" Impacts: you will also account for mitigation strategies and adaptation strategies, and you will see how this will react to the impact model or climate model. **Climate models:** - Depict the climate system using a three-dimensional grid over the globe - Physical processes averaged over larger scales (parametrization) - Used to simulate response global climate system to increasing GHGs **Impacts models:** - Simulate the effects of physical events, disasters, and climate change on natural/human systems. - Represent physical and socioeconomic processes - Different impact models for different sectors. ISIMIP: Inter-sectoral Impact Model Intercomparison project Intercomparison of \> 120 impact models from local to global scales Goals (selected): - Synthesis of impacts - Quantification of uncertaintites - Model improvement - Cross-sectoral interactions Show how different sectors interact with each other. (cross-sectional interactions) **PART 3: Uncertainties in Impact Assesments** Sources of uncertainty in climate impact assessments 1. Input data: data scarcity, measurement errors, representativeness of measurement sites 2. Process understanding and modellingL climate change dynamics/natural complexity, deficienceis in our knowledge, paratmerization and parameter estimation 3. Unknown future: societal change/change in valuee, stringency of policy **Uncertianty increases along the impact modelling chain** **PART 4: Scenarios as a tool to explore future uncertainty** Scenarios: a tool to explore future uncertianty - A scenario is a coherent, internally consistent and plausible description of a possible future state of the world. - It is not a forecast; rather, each scenario is one alternative image of how the future can unfold. - The goal of working with scenario is not to predict the future, but to better understasnd uncertainties in order to reach decisions that are robust under a wide range of possible futures  **RCPs: representative concentration pathways** - Initially four RCPS, extended for IPCC aR6 - Describe the intensity of anthropogenic radiative forcing - Direct input into climate models - Shown in CO2 concentration: pre-industrial 280 ppm - Today: 423 ppm - Also shown in temperature degrees **SSPs: shared socioeconomic pathways** Scenarios how the society will develop / "plausible alternative trends in the evolution of society and natural systems over the 21st century at the level of the world A diagram of a road Description automatically generated with medium confidence Q: what socioeconomic developments may drive the challenges for adaptation and mitigation per SSP? **SSP1 - Sustainability**: Low challenges for both adaptation and mitigation, focusing on sustainable development. - Shift toward sustainability, stabilizing population, medium to high economic growth... **SSP2 - Middle of the Road**: Moderate challenges for adaptation and mitigation, with a balance between development and environmental goals. **SSP3 - Regional Rivalry**: High challenges for both adaptation and mitigation, with countries focusing on national priorities and limited cooperation - Resurgent nationalism ,rapid population growth, slow economic growth, low urbanization, slow technological advancement, high resource intensity, fossil fuels. Etc... **SSP4 - Inequality**: High adaptation challenges due to inequalities, but lower mitigation challenges for some, reflecting a divided world with significant disparities. **SSP5 - Fossil-fueled Development**: High mitigation challenges as economies grow rapidly based on fossil fuels, but with lower adaptation challenges due to increased wealth and infrastructure.. Which combinations between RCPs and SSPTS are plausible for intergrated climate change scenarios: IPCC reports are for policy makers, so that is why they mostly focus on the scenarios to reach the paris agreement!  A diagram of a greenhouse effect Description automatically generated Scientists want to reduce uncertainty by generating more information and by improving the knowledge base Policy makers want to reduce their chances for making political mistakes - Make "hard" decisions based on "soft" scientific information with considerable uncertainty - Develop adaptation strategies that use projection ranges and uncertainty estimates - **Precautionary principle**: choose the approach minimizing the worst outcome ("climate proofing") - **Adaptive management**: adaptive planning based on ensembles and multi-model probabilistic approaches ("no regret measures") Key messages: - Climate impact assessments provide an important basis for informing climate policy - Results of impact assessments are uncertain, stemming from uncertainties in input data, models, and how the future may unfold - Scenarios provide a tool to explore future uncertainties in climate change impacts - IPCC AR6 synthesizes climate impacts based on integrated SSP-RCP scenarios. **LECTURE 3 -- EXTREME WEATHER AND CLIMATE SCENARIOS** Northern Hemisphere summer (June /July/august): heatwaves - Dutch summer was fairly normal summer compared to other years, not colder at all - June, July, Augusts is the warmest on average around the globe, because the northern hemisphere has the most land and land warms quicker than the ocean. Last few years in the northern hemisphere summer: - Records for highest temperatures (heatwaves) - Extreme rainfall  More **heatwaves:** Shift in mean summer temperature drastically increases chance of heatwaves. So probability (pdf) will change. **More rainfall:** now 30% more daily rainfall records aroudn the global as warm air can hold more water vapor driving extreme rainfall. More drying: many regions with an already dry climate have seen further drying since 1950 To measure differences in precipitation, a much denser network is needed. This is because precipitation is very localized, requiring many observational stations to capture its variability. Human contributions to increased precipitation are considered low. This is because climate models struggle to reproduce extreme rainfall events. Due to this limitation, there is low confidence in attributing these events to human activity. The IPCC, therefore, makes conservative statements on this topic. **Jetstream:** is really important for extreme weather events. During the 2021 Limburg floods the jetstream is very "wavy" and there was a low pressure system voer western europe. September 2023: saw the opposite, wave jet stream but with a hihg pressure over western europe.. Thus tropical weather around western europe and stroms around Greece.  These type of jetstream states could have occurred in a pre-indsutrial climate (causing some type of extermes). But the surface extrems are now amplified in a warmer world due to thermodynamics. *How will global warming affect atmospheric dynamics*? Next to thermodynamics, also atmospheric dyanmics is expected to change with AGW and this can have a pronounced effect on regional climate and extremes, particularly rainfall. Still large **uncertainties** to do with how AGW changes circulation. *Can we say something about the role of global warming on individual extremes? **Event Attribution** (how often an extreme event will take place)* Example: European heatwave of 2003 is wake up call for climate scientists as the death toll exceeding 70,000 and there was severe harvest losses. Event atribution: the 2003 heatwave has become much more likely due to AGW at least a ten fold increase in the frequency of 2003-like heatwaves (comparing early 21st cnetury with pre-industrial. A graph of a graph of temperature Description automatically generated with medium confidence To detect extremes: dense observation network needed To simulate extremes: very high resolution climate model needed The most intense, short lived events are not in climate models. For those weather models are needed extreme rainfall. Assume that rainfall extremese scale with Clausissu -clapyeron euqaiton: warmer air can hold more water vapor:  Only thermodyanmics is a poor estiamte for rainfall, this is due dyanmics. They change in a lot more ways. Convective rainfall extremes increase stronger than expected by Clausius-Clapeyron due to *amplified convective dyanmics* in a warmer world roughly 2 x clausius clapeyron The absolute increase in rainfall largest where rainfall is already most extrem (=tropical regions) Extreme waather -- Key Messages: 1. Simple warming of the air has already increased the number of heat extremes, heavy rainfall and also drought. 2. More future warming means more increases in those extremes 3. Atmosphere dynamical changes are much more uncertain. **PART 2: Climate Models** Essence of climate models - Conservation Laws: Energym Mass (water) momentum conservation **Importance of resolution**: any sub gird process 9process operating at smaller temporal or spatial scale) cannot be resolved. It needs to be *paramterized*. Even highest resolution global climate models do not resolve small-scale convective rainfall extremes (thunderstorms) so to study those you need weather models. Large-scale features of the climate system naturally emerge ( trade winds, dest regions, jetstreams...) Important feedbacks in climate: - Cloud feedbacks: big challenge in climate modelling very uncertain about cloud feedbacks. - Albedo feedbacks - Water vapor feedback **Climate sensitivity:** how much will earth warm with a doubling of CO2? uncertianty in feedbacks prime reason for uncertainty in climate sensitivity and thus uncertainty in future global mean temperature projections  How do climate models work? 1. Based on conservation of mass, energy, and momentum 2. Subgird processes need paramterization and introduce uncertainty 3. Uncertainty amplified by internal climate feedbacks 4. Faithfully represent many aspects of climate