Climate Change Impacts & Extreme Weather Events PDF

Toward More High-Resolution ENVR1150 [10 Sep] Climate Change Impacts & Extreme Weather Events IM, Eun-Soon Department of Civil and Environmental Engineering Division of Environment and Sustainability Natural and Anthropogenic...

Toward More High-Resolution ENVR1150 [10 Sep] Climate Change Impacts & Extreme Weather Events IM, Eun-Soon Department of Civil and Environmental Engineering Division of Environment and Sustainability Natural and Anthropogenic Climate Change  What is climate change? A change in the state of the climate that can be identified by changes in the mean and/or the variability of its properties and that persists for an extended period, typically decades or longer. Climate change may be due to natural internal processes or external forcings, or to persistent anthropogenic changes in the composition of the atmosphere or in land use. Natural Factors [From NASA GISS] [From Ahrens&Samson] Human Factors Two Sides of Greenhouse Effect Future emission scenario Natural Anthropogenic “Natural” greenhouse effect “Man-made” greenhouse keeps the Earth’s climate effect is the enhancement of warm and habitable. earth natural greenhouse Without natural greenhouse effect by the addition of effect, the average greenhouse gases from the temperature on earth would human activities such as be colder by about 30°C, far burning of fossil fuels, land too cold to sustain our use change, and so on current ecosystem. Global Energy Balance Energy from Sun Earth Energy radiated into space Net Incoming Solar Energy Outgoing Heat Energy (S (1-A) R2) = (4R2 kTe4) Where, S is the solar constant (1370 W m-2 ) Stefan-Boltzmann law A is average albedo, or reflectivity R is the radius of the earth k is Stefan-Boltzmann constant (5.67x10-8 W m-2 K-4) Te is earth’s effective temperature The earth’s effective temperature, Te, equals -18C Greenhouse effect Actual surface temperature is about 14C Natural Greenhouse Effect If the atmosphere includes greenhouse gases, Sun the atmosphere works as insulating blanket, so trapping the heat. Natural greenhouse effect warms the surface by 33C Atmosphere GHG GHG Earth Anthropogenic Greenhouse Effect Sun As anthropogenic greenhouse gases increase, more infrared radiation is trapped, which gradually increases the temperature of the Earth Surface Atmosphere GHG GHG Earth Greenhouse Gases Greenhouse gases are efficient in absorbing IR Nitrogen 78% wavelength range. Water vapor is the most abundant, but human Oxygen 21% activities have only small direct influence on the amount of atmospheric water vapor. Primary greenhouse gases due to human Other 1% activities : - Carbon Dioxide (CO2) - Methane (CH4) Other ~ 10% - Nitrous oxide (N2O) These gases are accumulated in the atmosphere, causing concentrations to Carbon Dioxide increase with time. ~ 25% Water Vapor ~ 65% Shortwave & Longwave Radiation Everything emits radiation. The wavelengths of radiation that an object emits depend primarily on the object’s temperature. If the object’s temperature is higher, the wavelengths of emitted radiation are shorter Since the sun radiates the majority of its energy at much shorter wavelengths than does the earth, solar radiation is often called shortwave radiation, whereas the earth’s radiation is referred to as longwave (or terrestrial) radiation. [Extreme Weather & Climate / Fig.2.9] Radiation characterized according to wavelength As the wavelength decreases, the energy carried per wave increases. [Extreme Weather & Climate / Fig.2.7] Effectiveness of Greenhouse Gases  Selective absorption Solar and terrestrial radiation occupy different ranges of the electromagnetic spectrum that we have been referring to as shortwave Absorption (%) (incoming) and longwave (outgoing) radiation. Water vapor and carbon dioxide absorb radiation more strongly in the longwave part of the spectrum occupied by outgoing radiation than the shortwave part occupied by incoming solar radiation. Hence, incoming solar radiation passes through the atmosphere quite freely, whereas [Extreme Weather & Climate / Fig.2.10] longwave radiation emitted from the Earth’s surface is absorbed through the atmosphere.  Carbon Dioxide vs. Water Vapor CO2 remains the atmospheric longer than other major heat-trapping gases, so its concentration is accumulated over time. The typical residence time of water vapor in the atmosphere is around 10 days. Greenhouse Effect of Water Vapor 22°C 17°C 12.8°C 21°C 15.5°C 10°C With the same initial evening air temperature 27 °C and with no change in weather conditions during the night, as the dew-point temperature lowers, the expected minimum temperature lowers. This situation occurs because a lower dew-point temperature means that there is less water vapor in the air to absorb and radiate infrared energy back to the surface. More infrared energy from the surface is able to escape into space, producing more rapid radiational cooling at the surface. Toward More High-Resolution ENVR1150 [12 Sep] Climate Change Impacts & Extreme Weather Events IM, Eun-Soon Department of Civil and Environmental Engineering Division of Environment and Sustainability Review If the concentration of CO2 in the atmosphere is doubled, Earth’s surface temperature will increase because more shortwave radiation is trapped. (True or False) The reason why we are concerned about CO2 in the context of global warming is that CO2 is the most abundant greenhouse gas in the atmosphere. (True or False) The reason why the actual global average temperature is much higher than the Earth’s effective temperature derived from the global energy balance is attributed to anthropogenic greenhouse gases. (True or False) The land-use changes due to deforestation, afforestation, and urban expansion could potentially be influencing the climate of certain regions. (True or False) The water vapor in the atmosphere plays an important role in absorbing infrared radiation. (True or False) The daily temperature range is normally greater on clear days than on cloudy days. (True or False) Evidence of Carbon Dioxide Increase De-seasonalized and adjusted to match the NOAA/ESRL surface average [Created by Robert A. Rohde] [Friedlingstein et al. 2012: Global Carbon Budget 2021] The increase in the concentration of carbon Surface average atmospheric CO2 dioxide has been carefully documented at concentration (ppm) based on an average of the Mauna Loa Observatory in Hawaii. direct atmospheric CO2 measurements from CO2 concentration has increased up to 389 multiple stations ppm in 2010. While emissions from fossil fuels started before The current observed amount of CO2 the Industrial Era, they became the dominant exceeds the geological record maxima (~300 source of anthropogenic emissions to the ppm) from ice core data. atmosphere from around 1950 and their relative share has continued to increase until the present.  The Life of Earth’s CO2 [From NASA Computer model simulation] The dispersion of carbon dioxide concentration is controlled by the large-scale weather patterns within the global circulation. The major emission sources are focused over North America, Europe and Asia. The seasonal variation of carbon dioxide concentration is related with the plant photosynthesis. During spring and summer in the Northern Hemisphere, plants absorb a substantial amount of carbon dioxide through photosynthesis, thus removing some of the gas from the atmosphere. About half of the carbon dioxide emitted from fossil fuel combustion remains in the atmosphere, while the other half is absorbed by natural land and ocean reservoirs.  Anthropogenic Carbon Flows Annual carbon emissions and their partitioning Cumulative carbon emissions and their partitioning [Friedlingstein et al. 2022: Global Carbon Budget 2021] The net CO2 flux from land use, land-use change, and forestry includes CO2 fluxes from deforestation, afforestation, logging and forest degradation, shifting cultivation (cycle of cutting forest for agriculture, then abandoning), and regrowth of forests following wood harvest or abandonment of agriculture. The partitioning is based on nearly independent estimates from observations and from process models and does not exactly add up to the sum of the emissions, resulting in a budget imbalance which is represented by the difference between the bottom red line (mirroring total emissions). Roughly, a half of CO2 emission remains in the atmosphere, while the other half is taken by the land and ocean COVID Effect on CO2 Emissions COVID curbed CO2 emissions in 2020. Widespread disruptions in the transport sector had the largest impact on emissions. By the end of 2020, COVID-19-related [Le Quéré et al. 2021 / Nature Climate Change] confinement measures were acting to decrease daily emissions by around 7% below 2019 levels. Atmospheric CO2 Concentrations & Emissions  Has the global CO2 concentration in the atmosphere decreased due to the reduction in CO2 emissions caused by the COVID pandemic? Monthly average atmospheric CO2 concentrations (1960–2021) Despite the continued economic drag of the COVID-19 pandemic, the global average carbon dioxide set a new record high in 2021: 414.72 parts per million (ppm). Atmospheric CO2 concentrations and annual emissions (1750–2021) Natural “sinks” on land and in the ocean absorbed the equivalent of about half of the carbon dioxide we emitted each year. Because we put more carbon dioxide into the atmosphere than natural processes can remove, the amount of carbon dioxide in the atmosphere increases every year. Global Anthropogenic GHG Emissions Global anthropogenic GHG emissions (1990–2019) [IPCCAR6 WG3/Figure SPM.1] Growth in anthropogenic emissions has persisted across all major groups of GHGs since 1990, albeit at different rates. By 2019, the largest growth in absolute emissions occurred in CO2 from fossil fuels and industry followed by CH4 (high confidence). However, net anthropogenic CO2 emissions from land-use change and forestry (CO2- LULUCF) are subject to large uncertainties. Historical Cumulative CO2 Emissions Historical cumulative anthropogenic CO2 emissions per region (1850–2019) Cumulative anthropogenic CO2 emissions have grown in most regions but are distributed unevenly since 1850. Historical contributions to cumulative anthropogenic CO2 emissions between 1850 and 2019 vary substantially across regions in terms of total magnitude, but also in terms of contributions to CO2 -FFI and net CO2 - LULUCF emissions. [IPCCAR6 WG3/Figure SPM.2] Globally, the major share of cumulative CO2 -FFI emissions is concentrated in a few regions, while cumulative CO2 - LULUCF emissions are concentrated in other regions. Global Warming Potential (GWP) 2% 4% 18% CO2: 75% [IPCCAR6 WG3/Figure SPM.1] [Environmental Protection Agency (EPA)] How effective the gas is at trapping heat. This is referred to as its global warming potential (GWP) and is a measure of the total energy that a gas absorbs over a given period of time (usually 100 years) relative to the emissions of 1 ton CO2. Although the relative contributions of CH4, N2O, and F-gases (e.g., hydrofluorocarbons) are smaller than that of CO2, their global warming impacts are much greater than that of CO2 over a 100-year period. Industrial growth across various sectors (e.g., Refrigeration and Air Conditioning, cold chain logistics) contributes to the increase in F-gases emissions. Radiative Forcing from GHGs Radiative forcing (RF) is a measure of the net change in the energy balance of the Earth system in response to some external perturbation, with positive RF leading to a warming and negative RF to a cooling. Total radiative forcing is positive, which means an uptake of energy by the climate system. The largest contribution to total radiative forcing is caused by the increase in the atmospheric concentration of CO2 since 1750. [Very High] [AR5 WG1/Figure SPM.5] Representative Concentration Pathway (RCP) Representative Concentration Pathways are a set of four pathways developed for common and standards of greenhouse gas concentrations that are used primarily by climate modellers. They describe four possible climate futures, all of which are considered possible depending on how much greenhouse gases are emitted in the years to come. Emissions in RCP 4.5 peak around 2040, then decline whereas in RCP 8.5, emissions continue to rise throughout the 21st century (e.g. Business-as-usual scenario). There are uncertainties in the translation of emissions profiles to concentrations and radiative forcing.  Emission scenarios Socio-Economic Assumptions behind RCPs *The dotted lines indicate four of the SRES marker scenarios. All scenarios, by 2100, still use a greater amount of coal and/or natural gas than in the year 2000. The RCP8.5 is a highly energy-intensive scenario. The use of non-fossil fuels increases in all scenarios, especially renewable resources (e.g. wind, solar), bio-energy and nuclear power. [van Vuuren et al. 2011] Shared Socioeconomic Pathway (SSP) The pathways were developed over the last years as a joint community effort and describe plausible major global developments that together would lead in the future to different challenges for mitigation and adaptation to climate change. The SSPs are based on five narratives describing alternative socio-economic developments, including sustainable development, regional rivalry, inequality, fossil-fueled development, and middle-of-the-road development. The long-term demographic and economic projections of the SSPs depict a wide uncertainty range consistent with the scenario literature. A multi-model approach was used for the elaboration of the energy, land-use and the emissions trajectories of SSP-based scenarios. Sustainability – Taking the Green Road (Low SSP1 challenges to mitigation and adaptation) Middle of the Road (Medium challenges to SSP2 mitigation and adaptation) Regional Rivalry – A Rocky Road (High SSP3 challenges to mitigation and adaptation) Inequality – A Road Divided (Low challenges to SSP4 mitigation, high challenges to adaptation) [Riahi et al. 2017] Fossil-fueled Development – Taking the SSP5 Highway (High challenges to mitigation, low challenges to adaptation) RCP vs. SSP The RCPs were the basis for climate model projections in CMIP5 and their assessment in the IPCC AR5(2013). The SSPs were the basis for climate model projections in RCP SSP CMIP6 and their assessment in the IPCC AR6(2021). [CMIP5(6): The Fifth (Sixth) Phase of Coupled Model Intercomparison Project] CMIP5 CMIP6 [AR5(6): The IPCC Fifth (Sixth) Assessment Report] AR5 AR6 [O’Neill et al. 2016] Future Emission Scenarios  Annual anthropogenic (human-caused) emissions over the 2015–2100 period along the different scenarios Net negative CO2 emissions are reached when removals of CO2 exceed anthropogenic emissions [IPCC AR6 WG1/Figure SPM.4] Emissions vary between scenarios depending on socio-economic assumptions and levels of climate change mitigation. Future emissions cause future additional warming, with total warming dominated by past and future CO₂ emissions Near-linear Relationship between CO2 & T Every tonne of CO2 emissions adds to global warming Near-linear relationship between cumulative CO2 emissions and the increase in global surface temperature.. Future cumulative CO₂ emissions differ across scenarios, and determine how much warming we will experience. [IPCC AR6 WG1/Figure SPM.10] Cumulative CO2 Emissions Uptaken in Land & Ocean [IPCCAR6 WG1/Figure SPM.7] Values in % indicate the proportion of the cumulative anthropogenic CO2 emissions taken up by the combined land and ocean sinks in the year 2100. Under scenarios with increasing CO2 emissions, the ocean and land carbon sinks are projected to be less effective at slowing the accumulation of CO2 in the atmosphere. Toward More High-Resolution ENVR1150 [17 Sep] Climate Change Impacts & Extreme Weather Events IM, Eun-Soon Department of Civil and Environmental Engineering Division of Environment and Sustainability Review The positive value of total radiative forcing leads to an uptake of energy by the climate system. (True or False) The value of “4.5” in the RCP4.5 scenario indicates that the approximate level of total radiative forcing reaches 4.5 𝑊𝑚 by the end of the 21st century. (True or False) The five stories of shared socioeconomic pathways (SSP) describe different assumptions of socio-economic developments, and SSP5 has a higher degree of realism than SSP1 because CO2 concentration is accumulated over time. (True or False) The RCP8.5 scenario, which is characterized by the largest increase in CO2 concentration among RCP scenarios, does not consider the energy generation of renewable resources. The uncertainty of RCP and SSP scenarios will increase towards the end of 21st century. (True or False) RCP and SSP scenarios do not consider a) Energy consumptions b) Evolution of land-use change c) Population growth d) Chaotic behavior of climate systems CO2, which accounts for approximately 75% of global anthropogenic greenhouse emissions, has the largest global warming potential compared to other greenhouse gases. (True or False) While low-income countries have dominant emission sources from land use change, anthropogenic greenhouse gas emissions in high-income countries mainly come from the fossil fuel and industry sectors. (True or False) If we reduce carbon dioxide emissions, its concentration in the atmosphere will reduce immediately. (True or False) What is Global Climate Model? Digital Twin Mimic of Earth’s Climate System [From Wikipedia] Climate model is a tool that can translate the physical process of climate system into tractable How ? numerical representation by means of computer interface. Climate models are essential tools for attributing and predicting future changes. Climate Model: State-of-the-art Scientific Tool Dynamics Physics Primitive equations for grid-resolving Parameterization of sub-grid process scale − Why Do We Need Global Climate Models?  To understand the physical mechanism behind emerging patterns Temperature Anomaly (°C) [IPCC AR6 SPM 2021]  It is unequivocal that human influence has warmed the atmosphere, ocean and land.  Widespread and rapid changes in the atmosphere, ocean, cryosphere and biosphere have occurred. Why Do We Need Global Climate Models?  To predict future climate change in response to given forcings Global mean temperature anomaly CO2 concentration SSP585 SSP585 SSP245 SSP245 SSP126 SSP126 2000 2020 2040 2060 2080 2100 The Shared Socioeconomic Pathways (SSPs) are based on the narratives describing plausible [Anomaly = Individual years – Climatological mean between 1850–1900] major global developments Improving Horizontal Resolution of Climate Model  Climate model has improved in accordance with computer power. ~500km ~250km ~180km ~110km [IPCC AR4, 2007] AR5 Necessity of High Resolution I  Successful linkage between climate and impact sectors It is needed to bridge scaling gap between the climate models and various impact assessment models because the impact assessments are mostly valid in regional and local sector. Example: Hydrological assessment at basin level Coarse Resolution Fine resolution Real Feature Necessity of High Resolution II  Improving the simulation of extreme events Only high-resolution is capable of producing extreme precipitation episodes and this result supports the use of finer scale models to simulate extreme events. Model -1.32 Model -0.44 Model -0.11 Observation 80 10 50 50 50 10 50 Ave=80 300 100 100 Precipitation intensity (mm/day) [Torma et al. 2015] Necessity of High Resolution III  Elevation-Dependency of Climate Change Signal High elevation region tends to be more enhanced response due to global warming. The detailed topographic forcing in the climate model is essential for accurately simulate snow-albedo feedback Topography (m) over Alps High Resolution Present Future Snow (mm) Elevation (m) Low Resolution Present Elevation (m) Future Snow (mm) Dynamical & Statistical Downscaling  Dynamical downscaling using regional climate model (RCM) Regional climate model is nested within global climate model over specific interest region with high resolution. Therefore, a very fine-scale climate dataset can be obtained only over the limited target area from coarse-grid global climate model information without tremendous computational cost.  Statistical downscaling using statistical transfer function Relationship between local observations and large scale patterns obtained from GCMs 𝑿𝒏 𝒀𝒏 Statistical methods 𝒀𝒏 =𝒇 (𝑿𝒏 ) [https://www.meteo.unican.es/downscaling/intro.html] Concept of Weather & Climate Future emission scenario Weather Climate Weather in any location or region Climate is defined as average can change quickly from hour to weather. hour, day to day, and season to Climate prediction is to estimate the season. statistical properties of the climate Weather prediction aims at system in response to external forecasting how specific weather forcing. patterns evolve based on the Climate is largely determined by knowledge of the atmosphere state global and regional geophysical at a certain time. processes that change slowly. Weather prediction is close to Climate prediction is close to initial value problems. boundary value problems. Ex1 The amount of annual rainfall is larger in Southern China than in Northern China. Ex2 Hong Kong has hot and humid summer. Ex3 It will be heavy rainfall tomorrow afternoon. How to Project Far Future Climate Information  Different concept between weather forecast and climate projection Initial Value Problem Boundary Value Problem Hours Days Months Years Decades Centuries Exact timing & location Statistics in response to changing boundary conditions, in particular emission scenarios of greenhouse gases  Initial conditions: Initial state of meteorological variables (e.g. temperature, wind, pressure) to run the climate model  Boundary conditions: Fixed: surface conditions prescribed (e.g. topography, land-use, soil texture) Time-varying: composition of the atmosphere (e.g. yearly varying GHGs concentration) Boundary conditions are not predicted by the model and must be specified.  Example for projection Deadly heat waves projected in the densely-populated agriculture regions of South Asia. Initial Condition vs. Boundary Condition  Schematic figure to show the temporal evolution of the temperature simulated with the same initial conditions, but at the different locations. January mean temperature at the location (5°N, 10m) Temperature January mean temperature at the location (50°N, 3000m) Time Same initial condition Different boundary conditions :Topography, incoming solar radiation Toward More High-Resolution ENVR1150 [19 Sep] Climate Change Impacts & Extreme Weather Events IM, Eun-Soon Department of Civil and Environmental Engineering Division of Environment and Sustainability Review Seasonal variation of CO2 emission is related to the plant activity through photosynthesis. (True or False) The ocean carbon sink is projected to be less effective in SSP5-8.5 than in SSP1-2.6 scenario because ocean warming reduces the solubility of CO2. (True or False) The large uncertainty of future temperature projections at the end of the 21st century is primarily due to the imperfection of available climate models rather than to different emission scenarios. (True or False) Since the climate system is extraordinarily complex, it would not be possible to detect a relationship between cumulative anthropogenic CO2 emissions and global mean temperature. (True or False) Climate model, a complex computer code based on the physical processes and mathematical formulas, is the state-of-the-art scientific tool to provide physically-based climate information until far into the future. (True or False) Climate model is a useful scientific tool that can isolate the physical processes of the climate system in response to external forcings such as greenhouse gases from natural climate variability. (True or False) Increasing spatial resolution (e.g., 300km  100km) can be a way to improve the performance of climate model due to more realistic topography and land-sea contrast. (True or False) Although the high-resolution simulation shows better performance in capturing mean climatology compared to low-resolution simulation, it can not improve the simulation of extreme events. (True or False) Reliability of Future Anthropogenic Climate Change  Three Criteria for Assessing Reliability of Future Climate Simulation 1(1) Comparison of (2) 2 Simulation of past 3 Intercomparison (3) Intercomparisonofof simulated present- climate changes climate change climate change day climate with (e.g., 20th century) simulations between simulations between observations different models different models All these methods include uncertainties and none of them provides absolute standard. Three methods together provide more robustness than any of them alone. The large uncertainty of future temperature projections at the end of the 21st century is primarily due to the imperfection of available climate models rather than to different emission scenarios.  Reliability Criteria I  Verification of Present-day Climate | Temperature & Precipitation There is high confidence that large-scale patterns of surface temperature are well simulated by the CMIP5 models, with correlations above 0.95. However, for precipitation, the correlations between models and observations are below 0.90, and there is considerable scatter among model results In most areas the multi-model mean agrees with the observations to within 2°C, but there are several locations where the errors are much larger, particularly at high elevations over the Himalayas and parts of both Greenland and Antarctica. The inconsistency across the three available global observations provides an indication of observational uncertainty. Although the observational inconsistency is smaller than the mean absolute bias in almost all regions, areas where inconsistency is largest tend to be the same Temperature Precipitation regions where the CMIP5 models show largest mean absolute error. [IPCC AR5 WG1/Figure 9.2 & 9.6 ] CMIP5 Multi-Model Mean Temp Multi-Model Mean of Absolute Error Observational Inconsistency Reliability Criteria I  Verification of Present-day Climate | Sea Ice Extent CMIP5 models reproduce the seasonal cycle of sea ice extent in both hemispheres. The CMIP5 multi-model ensemble exhibits improvements over CMIP3 in simulation of sea ice extent in both hemispheres. Arctic Sea Ice Extent (1980-1999) The performance improvements are not only a result of improvements in sea ice components (e.g., ice concentration and thickness) themselves but also in atmospheric circulation because sea ice is a product of atmosphere–ocean interaction. In many models the regional distribution of sea ice concentration is poorly simulated, even if the hemispheric extent is approximately correct. Evaluation of sea ice performance requires accurate information, but caveats exist related to the uneven reliability of different sources of sea ice extent estimates (e.g., satellite Antarctic Sea Ice Extent (1980-1999) vs. pre-satellite observations). February September Observational boundary based on Hadley Center Sea Ice & SST data [IPCC AR5 WG1/Figure 9.22& 9.23] Reliability Criteria II  Estimation of Past Climate Change The performance how accurately the models simulate past climate change can be the most objective test. Although biases in mean temperature are apparent, models have successfully simulated general warming trend with similarity to observation. In addition, the episodic volcanic forcing (e.g., prescribed volcanic aerosol data sets) that is applied to models leads to the multi-model agreement with the observed cooling, particularly noticeable after the 1991 Pinatubo eruption. OBS Observed and CMIP5 simulated global mean surface air temperature Major volcanic eruptions Reference Period (1961-1990) [IPCC AR5 WG1/Figure 9.8] Reliability Criteria III  Model agreement or Statistical Significance Temperature change shows a more robust pattern of their forced response to global warming compared to precipitation change. Hatching: the multi-model mean is small compared to internal variability (i.e., one standard deviation). Stippling: regions where the multi-model mean is large compared to natural internal variability (i.e., greater than two standard deviations of natural internal variability in 20- year means) and where at least 90% of models agree on the sign of change [WG1AR5/Figure SPM.8] Mean Change vs. Variability | Temperature Mean Change vs. Variability | Precipitation How Reliable Are Climate Simulations?  Global climate models show substantial skill in simulation both the present-day climate and 20th century climate change, particularly the large-scale temperature evolution.  Nevertheless, the climate models are not perfect!  Inter-model variation gives the first-order estimate of uncertainty in future climate changes. Cascade of Uncertainty in Climate Change Projection The cascade consists of uncertainties in Socio-Economic Assumptions calculations of concentrations of greenhouse gases in the atmosphere used for the forcing within the climate system. Emissions Scenarios The other uncertainties are the climate modeling of the response of the climate system to a given forcing, i.e., the GHGs Concentration Calculations responses of different climate models. There is a further uncertainty in regionalization for use in detailed Global Climate Change Simulations regional impacts assessment. Downscaling / Regionalization Impacts Assessment Models Policy Responses How to Measure Uncertainty Sources Quantifying the uncertainty sources can provide valuable insight into the respective importance or sensitivity to emerging patterns of climate change, which eventually contributes to assessing the reliability of future projections.  Internal or natural variability : Different initial conditions  Emission scenario : Different emission scenarios  Climate model : Different climate models [Schematic figure to explain the experiments with different initial conditions] 1980 2100 Day1 Day2 Day3 Day4 Day5 Day6 Day7 Day8 Exp1 M1 Exp2 M2 Exp3 M3 Exp4 M4 Exp5 M5 Exp6 M6 Exp7 M7 Exp8 M8 Fraction of Uncertainty : Temperature Internal variability Emission Scenario uncertainty Climate model uncertainty For time horizons of many decades or longer, the dominant sources of uncertainty are model uncertainty and scenario uncertainty. However, for time horizons of one or two decades, the dominant sources of uncertainty are model uncertainty and internal variability. In general, the importance of internal variability increases at smaller spatial scales and shorter time scales. [WG1AR5/Figure 11.8] Fraction of Uncertainty [From Hawkins and Sutton 2009] For predictions of the next few decades, model uncertainty and internal variability are the dominant contributions. It is likely that the uncertainty in regional climate predictions for the next few decades is dominated by sources (model uncertainty and internal variability) that are potentially reducible through progress in climate science. For predictions of the ninth decade ahead, scenario uncertainty, as expected, is the dominant contribution over much of the globe, but at high latitudes it is still model uncertainty that accounts for the largest fraction of variance. Fraction of Uncertainty : Precipitation Internal variability Emission Scenario uncertainty Climate model uncertainty Throughout the century, model uncertainty is the dominant contributor. This dominance of model uncertainty for precipitation can be contrasted with the situation for temperature which shows that scenario uncertainty is more important than model uncertainty from mid-century onwards. [From Hawkins and Sutton 2011] For regional scale, the contribution from internal variability becomes large. Internal climate fluctuations could potentially mask or enhance, for a decade or so, the signal of anthropogenic changes. [WG1AR5/Figure 11.8] Treatment of Uncertainty A level of confidence is expressed qualitatively using five qualifiers very low, low, medium, high, and very high Quantified measures of uncertainty in a finding expressed probabilistically (based on statistical analysis of observations or model results). [WG1AR5/Box TS.1] Statistical Likelihood of Temp. & Precpi. Change (2081-2100) Black: AR5 / Blue: Report on Managing the Risk of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) / Red: AR4 [WG1AR5/Thematic Focus Elements.9, Table 1] Toward More High-Resolution ENVR1150 [24Sep] Climate Change Impacts & Extreme Weather Events IM, Eun-Soon Department of Civil and Environmental Engineering Division of Environment and Sustainability Review Climate projection refers to how the statistics of the climate system will change in response to the boundary conditions such as CO2 concentration. (True or False) Climate model simulations show the different seasonality between the equatorial region and high latitude region, which results from a difference in initial conditions. (True or False) Climate model simulations on decadal and longer time scales depend primarily on boundary conditions such as topography. (True or False) Inadequately prescribed complex terrain could be one reason that explains the limited performance of climate model simulations. (True or False) Greenhouse gas concentration is an important initial condition to determine the accuracy of weather forecast. (True or False) Bridging the spatial scale gap between climate information generated using climate models and various impact models is a central issue for climate change impact assessment studies. (True or False) Downscaling technique can be used to derive fine-scale local climate data from coarse grid climate model simulations. (True or False) Since the concept of weather and climate is quite different, the fundamental principles for numerical models to simulate weather and climate differ significantly. (True or False) Review If a certain climate variable is characterized by a large variability, it is difficult to assess the robust signal in response to enhanced greenhouse gas concentrations compared to the variable with less variability. (True or False) The dominance of model uncertainty for precipitation projections implies the diverse performances of current climate models in capturing the characteristics of precipitation. (True or False) The performance of how reasonably the climate models simulate current climate conditions can be one of the indicators to estimate the reliability of future climate projections. (True or False) The use of multiple models could help us quantify uncertainty in future projections. (True or False) The Concept of Feedback Input Output Forcing Climate System Response Process Anthropogenic forcing : GHGs (CO2) : Land-use change Feedback A feedback occurs when a portion of the output from the climate system process is added to the input and subsequently alters the output. An initial change in a process will tend to either reinforce the process (positive feedback) or weaken the process (negative feedback). Climate feedback is important in the understanding of global warming because feedback processes may amplify or diminish the effect of GHG forcing, so in determining the overall climate sensitivity. Some feedback mechanisms (e.g., cloud-radiation feedback) are still mostly uncertain and greatly controversial. The combined effect of all climate feedback processes is to amplify the climate response to forcing (virtually certain). [IPCC AR6 WG1] Feedback Loops Related to Global Warming Decreases ice/snow Increases evaporation Increasing Increases photosynthesis Decreases T vertical gradient CO2 Increases longwave emission Creates Creates changes changes Slower Faster Global Warming Speeds up Slow down warming warming Amplifying Stabilizing [Adopted from Met Office ] Ice Albedo Feedback |Arctic Warming Amplification Ice (or Snow) – albedo feedback is a positive feedback climate process where a change in the area of snow-covered land alters the albedo. Warming tends to decrease ice cover and hence the albedo, increasing the amount of solar energy absorbed, leading to more warming. The differential rate of seasonal or regional warming can be explained by snow– albedo feedback. For example, it can be seen noticeably more warming in response to the elevation during the winter season. Warmer Surface Less snow or ice  Temperature Decrease in albedo More absorbed solar radiation Arctic Warming | Four Times Faster than Global The observations systematically indicate larger AA than CMIP6 models around the year. The Arctic (66.5∘–90∘N) (dark colours) and globally (light colours) during 1950–2021 derived from the various observational datasets. Temperature anomalies have been calculated relative to the standard 30-year period of 1981–2010. Arctic amplification (AA) is defined as the ratio of Arctic warming to the global-mean warming. Frequency distributions of all possible 43-year AA Arctic has been warming nearly four times faster than the globe. ratios between 1970 and 2040 in (a) CMIP5 and (b) CMIP6. The red line denotes the observed 43-year [Rantanen et al. 2022 | Communications Earth& Environment ] AA ratio, as calculated for 1979–2021. Water Vapor Feedback The water vapor feedback is positive feedback because the initial increase in temperature is reinforced by the additional warming. As the atmosphere warms due to greenhouse gases, its concentration of water vapor increases, further intensifying the greenhouse effect. This in turn causes more warming, which causes an additional increase in water vapor. Based on the Clausius-Clapeyron relationship, the atmospheric moisture-holding capacity increases approximately 7% for each 1 K increases in temperature. Warmer Higher Moisture 35.3 − 26.5 Temperature Holding Capacity 35.3 26.5 × 100 /5 26.5 26.5 − 19.7 × 100 /5 Enhanced 19.7 19.7 Greenhouse Effect Planck Feedback The Planck feedback refers to the increase in longwave emission to space with surface warming due to the Planck blackbody radiation law (warmer temperatures = higher emission). A warming planet emits more infrared radiation, and therefore the increase in radiant energy from the surface would greatly slow the rise in temperature and help to stabilize the climate. The increase in radiant energy from the surface as the planet warms is the negative feedback in the climate system, and greatly lowers the possibility of a runaway greenhouse effect. Cloud-Radiation Feedback  Contrast effects of clouds on climate : Clouds reflect a certain proportion of solar radiation back to space, so reducing total energy available to the earth system. : Clouds act as blankets to longwave radiation from the Earth’s surface, so reducing the heat loss to space by the surface. The dominant effect depends on the cloud temperature (height) and optical properties (thickness). The overall cloud effect of clouds can be either positive or negative. Because of the complexity of the processes, cloud feedback is one of the less well- understood feedbacks, and this uncertainty is largely responsible for the spread of climate sensitivity in the present generation of climate models. Diverse cloud regimes [IPCC AR5 WGI | Fig. 7.4] Model’s Uncertainty in Low-level Cloud Feedback  Importance of low-level cloud feedback Low cloud is capable of particularly strong climate feedback because of its broad coverage. The change in low cloud varies greatly depending on the model, causing most of the overall spread in cloud feedbacks and climate sensitivities among climate models. No compelling theory of low cloud amount has yet emerged.  Difference between low (1.5-3°C) and high (3°C) over sensitivity models under CO2 doubling  Presence of lower-tropospheric convective mixing The vertical mixing accompanying a shallow lower troposphere circulation progressively dries the boundary layer as climate warms. If the layer deepens in a warmer climate, more dry air can be drawn down towards the surface, desiccating the layer and reducing cloud amount. No reality [Sherwood et al. 2014 |Nature] CO2 Positive & Negative Feedbacks  CO2 fertilization feedback [Negative] Higher atmospheric CO2 levels increase plant growth rates, which reduces atmospheric CO2 levels. Higher Atmos Accelerate Plant CO2 Level Growth Faster Removal of CO2 from the air  CO2 – water temperature feedback [Positive] Higher atmospheric CO2 increases ocean temperature, which reduces ocean CO2 update and therefore atmospheric CO2 further increases. Higher Atmos Higher Ocean CO2 Level Temperature [https://gotbooks.miracosta.edu/oceans/chapter7.html] Less Ocean CO2 Uptake Example for Feedback Amplification Loops  Estimation of the amplified warming due to water vapor feedback loop From the Global Energy Balance 1 𝜎𝑇 = 𝑆(1 − 𝛼) 4 For the Earth, 𝑇 = 𝟐𝟓𝟓, 𝐹 = 239.7 𝑇 = 𝟐𝟓𝟔, 𝐹 = 243.5 Δ1℃ ≈ 3.8 𝑊𝑚 It is expected that the increase in temperature would be around 1℃ if the increase in radiative forcing would reach around 3.8 𝑊𝑚 , which roughly corresponds to the CO2 doubling. However, IPCC AR5 gives a likely range of 1℃ to 4.5 ℃. It’s due to the amplification of the initial warming due to feedback loops. 0.852 0.224 It is expected that the water vapor feedback loop can amplify 1°C warming by more than 1.8 0.473 1.7°C. [For every degree that the temperature rises, it is well known 3.8 1 that the water vapor feedback cycle will add 1.8 𝑊𝑚 to the X0.263 energy imbalance.] Radiative Forcing Temperature Change Toward More High-Resolution ENVR1150 [26 Sep] Climate Change Impacts & Extreme Weather Events IM, Eun-Soon Department of Civil and Environmental Engineering Division of Environment and Sustainability Review It is virtually certain that increases in the frequency and intensity of heavy precipitation will occur in the 21st century. (True or False) It is very likely that there has been an overall decrease in the number of cold days and nights, and an overall increase in the number of warm days and nights since 1950 over most land areas. (True or False) Assessment of a human contribution to the increase in intensity of drought indicates low confidence, which means that no human impact occurred in drought. (True or False) A wealth of observations such as long-term measurement and satellite products can be helpful to enhance the confidence level of detection and attribution of climate change impacts. (True or False) Ice-albedo feedback contributes to the arctic warming amplification, which is an example of negative feedback. (True or False) A more refined representation of topography in the climate model can improve the accuracy to simulate Ice-albedo feedback. (True or False) The water-holding capacity of the atmosphere will increase by approximately 7% for each 1°C warming, which implies that the atmosphere is easily saturated under warmer climate conditions. (True or False) Review The sensitivity to different emission scenarios is larger in changes in precipitation than changes in temperature. (True or False) The emission scenarios are the main cause for the large uncertainty of global mean temperature projection at the end of the 21st century. (True or False) The confidence level of detection is generally lower than that of attribution. (True or False) James Balog, who is a professional nature photographer, described the ice as “the canary in the global coal mine” in his TED Talk entitled “Time-lapse proof of extreme ice loss”. What does it mean in the context of climate change?  If dangerous gases such as carbon monoxide collected in the mine, the gases would kill the canary before killing the miners, thus providing a warning to exit the tunnels immediately. Similarly, ice loss can play a role in providing early warning signal for global warming. Changes in Extremes Under Global Warming Heat Waves  How are future projections in extreme events under global warming ? Cold Waves  What is the main mechanism leading to the Drought changes in extreme events under global warming? Wildfire  What are determinants of risk caused by these extremes ? Floods Sea Level Rise Tropical Cyclone What Are Heat Waves?  Definitions No formal heat wave definition exists. Definitions of “heat wave” vary among countries and even within a country.  Characteristics Extreme heat may be one of the most underestimated and least understood of the deadly weather phenomena. Heat waves casualties In contrast to the visible, destructive and violent nature associated with severe weather events like floods, hurricanes, and typhoons, heat waves are “silent killer. It is very likely that global warming is brining more frequent and severe heat waves. [“Guidelines for Preparation of Action Plan Prevention and Management of Heat Wave” in India] Examples for Heat Waves Warning System  Meteorological Service of Canada  Korea Meteorological Administration The KMA has issued heatwave warnings if it occurs consecutively two days with maximum temperature exceeding 33°C.  India Meteorological Department Heat Wave need not be considered till maximum temperature of a station reaches at least 40°C for Plains and at least 30°C for Hilly regions. When normal maximum temperature of a station is less than or equal to 40°C Heat Wave Departure from normal is 5°C to 6°C Severe Heat Wave Departure from normal is 7°C or more. When normal maximum temperature of a station is more than 40°C Heat Wave Departure from normal is 4°C to 5°C Severe Heat Wave Departure from normal is 6°C or more. Meteorological Condition Favorable for Heat Waves  Typical meteorological condition favorable for heat waves High Pressure System : Sinking motion ( unfavorable for the formation of clouds and precipitation) Strong Incident Solar Radiation and Less Cloud Cover Atmospheric stagnation and Temperature Inversion : Less air movement. These factors are coupled and collectively contribute to severe heat waves Where Is the Hottest Location in the World?  Spatial distribution of the maximum temperature climatology Do the region characterized by highest maximum temperature coincide with the region where the people suffer from the worst heat stress Maximum Wet-Bulb Temperature  Yearly Maximum 3-hour WBT from ERA Interim Reanalysis (1979-2015)  WBT can be a good indicator for quantifying mugginess during a heat wave Relationship T & RH & Moist Temp. (WBT) Saturation vapor pressure (hPa) Hot & Dry Hot & Wet es = 6.112*exp((17.67*T)/(T+243.5)) TW TW RH=70.7% RH=23.5% Td Tw Td Tw Wet-bulb temperature is particularly useful in human health applications associated with heat stress, because evaporation is the primary means by which bodies cool in hot environments; thus, when Tw is high, evaporative cooling is restricted and the body core temperature may rise (Davis et al. 2016). 35°C is the threshold value of WBT beyond which any exposure for more than 6-hour would likely be intolerable even for the fittest of humans resulting in hyperthermia. In current climate, TW rarely exceeds 31°C. NOAA Heat Index The heat index is a measure of how hot it feels when relative humidity is taken into account along with the actual air temperature. It is important to note that since heat index values were devised for shady, light wind conditions, exposure to full sunshine can increase heat index values by up to 15°F. HI = -42.379 + 2.04901523*T + 10.14333127*RH - 0.22475541*T*RH - 0.00683783*T*T- 0.05481717*RH*RH + 0.00122874*T*T*RH + 0.00085282*T*RH*RH - 0.00000199*T*T*RH*RH  No perfect single index Heat Stress Indices Combined effect of temperature and humidity Dc: dew point temperature in °C Tc: air temperature in °C H: relative humidity in °C [From Anderson et al. 2013 ] Factors Influencing Human Heat Stress  Meteorological Factors Based on the principle of thermodynamics, diffusion of heat takes Temperature place between environment and human body. When sweat evaporates into vapor, heat will be transferred from Humidity the body to the environment by evaporation. Radiation directly applies heat to the body. Radiation The air movement around the body can influence the rate of heat flow Wind velocity away from the body.  Physiological factors  Sociological factors Break/rest regimes, use Heath / Age Occupational adaptation of cooling system, type of clothing. Labor Intensity Buildings & other structures Acclimatization to heat Toward More High-ResolutionENVR1150 [3 Oct] Climate Change Impacts & Extreme Weather Events IM, Eun-Soon Department of Civil and Environmental Engineering Division of Environment and Sustainability Review Snow-albedo feedback is a positive feedback process that can amplify the warming in the area covered with snow or ice by increasing albedo. (True or False) The uncertainty in cloud-radiation feedback could lead to a large spread of the temperature increase across climate models. (True or False) The locations with the highest maximum temperature coincide with the places where the people mostly suffer from the deadly heat stress. (True or False) Many different heat stress indices have been developed because there is no single index that is universally applicable and each index has its strength and weakness based on different assumptions. (True or False) The stagnant atmospheric condition with less air movement can worsen the negative impacts of heat wave by elevating the level of air pollutions. (True or False) Although most heat stress indices are computed based on temperature and humidity, solar radiation and wind velocity can aggravate or alleviate human heat stress. (True or False) Extreme hot days typically occur under a strong low-pressure system at the surface. (True or False) Case Studies: Chicago Heat Waves 1995 vs 1999 Range of observed daily temperature  Critical Issues Identified in 1995 1995 Most of the victims of the heat wave were elderly poor residents of the inner city, who could not afford air conditioning and did not open windows or sleep outside for fear of crime. No official heat emergency warning was 1999 released until the last day of the heat wave. Thus, emergency measures such as Chicago’s five cooling centers were not fully utilized. The city’s health-care system was severely taxed as thousands were taken to local [Hayhoe et al. 2010] hospitals with heat-related problems, such as In Chicago, the temperatures during the peak dehydration, heat stroke, and heat of the 1999 heat wave were similar to those exhaustion. during the 1995 heat wave peak, especially with the extreme nocturnal conditions. However, both event left quite different The map of heat-related deaths in Chicago heatwave death toll in Chicago, reducing it mirrors the map of poverty and urban from about 700 in 1995 to 114 in 1999. abandonment (Eric Klinenberg, 2002). Weather condition alone was insufficient to explain the excessive mortality rate. Case Studies: Chicago Heat Waves 1995 vs 1999  Non-Meteorological Factors Contributing to the improved response in 1999 There is a much improved heat watch/warning/advisory system in place now compared to 1995. Timely warnings were issued throughout the region by both the National Weather Service and by governments. Many more inner city households have air-conditioning units at their disposal now than they did in 1995. The city designated 34 cooling centers, provided free bus service to anyone needing to reach a cooling center, and announced plans to check on the elderly and public housing residents. Many of these heat wave plans had been developed in the wake of the 1995 heat wave. The experience of Chicago in 1995 exemplified the need for the improvement of heat wave responses. Case Studies: Chicago Heat Waves Future Projection Projected changes in heat wave events Climate model simulations indicate that the “1995-like” heat wave and associated atmospheric circulation patterns are expected to become more intense and more frequent in the second half of the 21st century. Although the people of Chicago are likely to become more acclimatized to higher temperatures over time (e.g., with increasing temperatures more people are likely to choose to install window and central air conditioning units), these results suggest that aggressive adaptation measures may be needed to prevent climate change induced increases in extreme heat from taking their toll on Chicago's population. [Hayhoe et al. 2010] Case Studies: European Heat Waves 2003 Observed Characteristics of 2003 heat wave Model Simulation JJA Temperature Anomaly w.r.t.1961-90 mean [Swiss] [Distribution of Swiss JJA mean summer temperatures for 1864–2003] [Death toll: more than 70,000 in Europe] [Schar et al. 2004] [Why: No physiological acclimatization opportunity & No societal adaptation opportunity] Case Studies: European Heat Waves 2003 vs 2006 Efforts to minimize the public health impact for the heat wave in 2003 were hampered by denial of the event’s seriousness and the inability of many institutions to instigate emergency-level responses. The difference in impact between the heat waves in 2003 and 2006 may be at least partly attributed to the difference in the intensity and geographic scope of the hazard. The 2006 heat wave was longer in duration than that of 2003, but was less intense and covered less geographical area. France, the country hit hardest, developed a national heat wave plan, clinical treatment guidelines for heat-related illness, identification of vulnerable populations, infrastructure improvements, and home visiting plans for future heat waves (Laaidi et al., 2004). As a result, France can significantly reduce mortality from 2016 heat waves. : Infrastructural considerations are critical to reducing urban vulnerability to extreme heat events. For example, building techniques can reduce energy consumption and the expansion of green space. : Through understanding local conditions and experiences and current and projected risks, it will be possible to develop strategies for improving heat preparedness in the context of climate change. The specificity of heat risks to particular sub-populations can facilitate appropriate interventions and preparedness. [IPCC. 2012] Case Studies: Korean Heat Waves 2018 At least 42 people have died in South Korea, as the country grapples with a record heatwave with temperatures unseen in more than 100 years. More than 3,400 people have been treated for heat-related illnesses, such as heat stroke, since the end of May. Temperatures in the capital Seoul, which is home to about half the country’s population, reached 39.6 C last week, the hottest temperature in 111 years. OBS [CLIM] OBS RCM [Ref] RCM [+20C] RCM [+30C] [Im et al. 2019] The uncommonly high Tmax under the current climate could become characterized as the new normal in the future if the global average temperature is allowed to increase by up to 3°C. Case Studies: Mecca Heat Waves 2015  Climate impact on Muslim pilgrimage to Mecca For the world’s estimated 1.8 billion Muslims, making a pilgrimage to Mecca in the Saudi Arabian desert is considered an important religious. This ritual, known as the Hajj, includes about five days of activities, of which 20 to 30 hours involve being outside in the open air. Therefore, adverse weather conditions during Hajj are likely to result in significant death. There have already been signs of this risk becoming real. Under the harsh weather condition measured by the combined temperature and humidity in the region like 2015, the Hajj left 769 dead and 934 injured. Pilgrims walk on a road near the holy city of Mecca, September 2015 [Kang et al. 2019] Case Studies: Mecca  Temperature & Humidity & Wind at Mecca station on 11 September 2015 Topo The westerly winds from the Red Sea [Dasari et al. 2017]  Climate change could pose danger for Muslim pilgrimage A low-level moisture supply Daily Wet-bulb Temp. during Hajj under RCP8.5 Because of climate change, there is an increasing risk that in coming years, conditions of heat and humidity in the areas of Saudi Arabia where the Hajj takes place could worsen, to the point that people face “extreme danger” from harmful health effects. [Kang et al. 2019] Toward More High-Resolution ENVR1150 [08 Oct] Climate Change Impacts & Extreme Weather Events IM, Eun-Soon Department of Civil and Environmental Engineering Division of Environment and Sustainability Mid-term Exam  Mid-term Exam (30%) : 15 Oct / 70min / Proctored Exam in the classroom : Closed book / T&F and short answer questions Classroom: LTB Time:10:30AM – 11:40AM Review A larger difference between dry-bulb temperature and wet-bulb temperature indicates lower humidity in the air. (True or False) Relative humidity indicates the absolute amount of moisture in the air. (True or False) The effectiveness of managing non-meteorological factors such as heat warming systems can lead to significantly different rates of excessive mortality, even in the presence of similar levels of extreme heat events. (True or False) The evident correlation between heat-related deaths and poverty observed during the 1995 Chicago heatwave supports the idea that climate change and wealth inequality are interconnected issues. (True or False) Assuming negligible moisture transport, heat stress mostly peaks in the afternoon because both temperature and relative humidity can reach the maximum. (True or False) The future change in the occurrence of extreme temperature is mostly affected by the mean temperature increases, but not variability. (True or False) Negative Impacts of Extreme Temperature  Extreme Heat Events Those at greatest risk are the urban-dwelling elderly without access Public Health to an air conditioned for at least part of the day. During the heat waves, air pollutions levels are mostly high. Livestock such as rabbits and poultry are severely impacted by heat waves. Agriculture Milk production and cattle reproduction also decrease. Crop yields can be significantly reduced by extreme high temperature at key developing stages. The electric transmission system is impacted when power lines sag in Energy high temperatures. The combination of extreme heat and the added demand for electricity causes transmission line temperatures to rise. Extreme heat made aircraft operations unsafe. Transportation Highways and roads are damaged by excessive heat. Stress on automobile cooling systems lead to an increase in mechanical failure. Refrigerated goods experience a significant greater rate of spoilage due to extreme heat. The high demand for water causes a reduced water supply. Water Resources The rise in water temperature contributes to the degradation of water quality and negatively impacts fish populations. Adverse Effects of Extreme Heat Events on Air Quality Heatwaves are often associated with stable weather conditions, characterized by high- pressure systems and reduced wind speeds. These stagnant air masses can trap pollutants close to the ground, preventing their dispersion and leading to the accumulation of pollutants in localized areas. This can result in the buildup of pollutants and worsen air quality during heatwaves. High temperatures accelerate chemical reactions in the atmosphere, leading to increased production of secondary pollutants such as ground-level ozone (O3) especially in urban areas, which is harmful to human health, causing respiratory problems and exacerbating conditions like asthma. High temperatures can cause vehicles and some industrial processes to emit more pollutants. For instance, gasoline evaporation from vehicles increases with temperature, releasing more volatile organic compounds (VOCs) into the air. Heatwaves lead to higher energy demands, especially for air conditioning. This can result in increased emissions from power plants, especially if the energy is sourced from fossil fuels. Health Impacts from Climate Change IPCC AR5 WGII / Figure 11-6 | Conceptual presentation of the health impacts from climate change and the potential for impact reduction through adaptation. Impacts are identified in eight health-related sectors. The width of the slices indicates in a qualitative way the relative importance in terms of burden of ill health globally at present. Impact levels are presented for the near- term “era of committed climate change” (2030–2040), in which projected levels of global mean temperature increases do not diverge substantially across emissions scenarios. Estimated impacts are also presented for the longer-term “era of climate options” (2080–2100), for global mean temperature increase of 4°C above preindustrial levels, which could potentially be avoided by vigorous mitigation efforts taken soon. For each timeframe, impact levels are estimated for the current state of adaptation and for a hypothetical highly adapted state, indicated by different colors. Occupational Health Risk: Heat Strain & Heat Stroke Agricultural and construction workers in tropical developing countries are therefore among the most exposed, but heat stress is also an issue for those working indoors in environments that are not temperature-controlled, and even for some workers in high-income countries such as the USA. Moreover, at higher temperatures there is potential conflict between health protection and economic productivity: as workers take longer rests to prevent heat stress, hourly productivity goes down. Four different work intensities 200W: Office desk work 300W: Manufacturing industry work 400W: Construction or agricultural work 500W: Very heavy laboring work IPCC AR5 WGII / Figure 11-5 | The 1980–2009 average of the hottest months globally, measured in web bulb globe temperature (WBGT), which combines temperature, humidity, and other factors into a single index of the impact on work capacity and threat of heat exhaustion. The insert shows the International Organization for Standardization standard (ISO,1989) for heat stress in the workplace that leads to recommendations for increased rest time per hour to avoid heat exhaustion at different work levels. Changes in Heat-related Mortality [Vicedo-Cabrera et al. 2021] Temperature modelled under the factual (with both anthropogenic and natural forcings) and counterfactual (with only natural forcings) scenarios  General Concept of Heat-related Mortality A temperature at which mortality becomes lowest is called the optimum temperature (OT). Heat-related excess mortality is considered as the area with hatching. If the temperature increases under global warming, the area with hatching also increases under the assumption that there is no change in heat acclimatization. [Honda et al. 2014] Changes in Heat-related Mortality  Heat-mortality associations in 16 representative locations Relative risk is a measure of association which represents the change in mortality risk at any given temperature compared with “optimum temperature”. The relationship between mortality and temperature displays a J-shape with a minimum “optimum temperature” representing the thermo-comfort zone and increases in mortality along the temperature increases. The displayed curves indicate potential geographical patterns in the heat- mortality relationship across regions The estimated heat-related mortality burden by country for each scenario is derived by applying the location-specific exposure-response functions to the corresponding modelled location- specific daily mean warm-season temperature series and average [Vicedo-Cabrera et al. 2021] baseline mortality between 1991 and 2018 Changes in Heat-related Mortality  Heat-related mortality and the contribution of human-induced climate change, 1991–2018 a | Heat-related mortality as a percentage of total mortality during warm season (mortality fraction (%)) estimated in the 43 countries under the factual (all anthropogenic and natural forcings (shaded)) and counterfactual (natural forcings only (unshaded)) climate b A particular model’s behavior scenarios. a The uncertainty of “b” b | Percentage of total deaths during is described by the spread of 10 models. warm season attributable to heat-related human-induced climate change, estimated as the difference in heat- related mortality in the factual compared to the counterfactual scenario. The difference between the factual and counterfactual scenarios is interpretable as the proportion of total deaths attributable to human-induced climate change. [Vicedo-Cabrera et al. 2021] Changes in Heat-related Mortality  Proportion of heat-related mortality attributed to human-induced climate change A substantial proportion of total and heat-related deaths can be attributed to human- induced climate change. The negative health impacts of 𝒃 climate change have already × 𝟏𝟎𝟎 𝒂 emerged in a disproportionate manner, showing the wide and heterogeneous geographical distributions. Proportion of heat-related mortality attributable to human-induced climate change estimated as the fraction of heat-related mortality in the factual scenario that results from the contribution of anthropogenic forcings. The largest climate change-induced contributions (>50%) were in southern and western Asia (Iran and Kuwait), southeast Asia (Philippines and Thailand) and several countries in Central and South America. [Vicedo-Cabrera et al. 2021] Vulnerable Population in HK 0.2Million people live in subdivided units [2017 The Thematic Household Survey Report No. 60] 0.1 Million cage home dwellers [2017 The Thematic Household Survey Report No. 60] [Presented by Chao Ren] Accumulated Heat Stress over Urban Areas in HK Urban areas in Hong Kong cannot be cooled down in the night. High mortality risk is expected under night-time prolonged heat. [Red color: T>=28C] 19pm 20pm 21pm 22pm 23pm 24pm 1am 2am 3am 4am 5am 6am [Presented by Chao Ren] Toward More High-Resolution ENVR1150 [10 Oct] Climate Change Impacts & Extreme Weather Events IM, Eun-Soon Department of Civil and Environmental Engineering Division of Environment and Sustainability Review The urban heat island effect is often more pronounced at night, as urban areas retain heat absorbed during the day, leading to higher nighttime temperatures compared to surrounding rural areas. (True or False) The synergistic effect of urbanization and global warming can exacerbate heat stress conditions. (True or False) The combination of extreme temperatures and elevated humidity can significantly escalate health risks and discomfort for individuals attending large-scale gatherings, potentially leading to serious health emergencies. (True or False) The optimum temperature representing the thermo-comfort range varies from region to region, depending on the historical climatology of each location. (True or False) Do Cold Extremes Disappear under Global Warming?  Long-term global warming trend vs. local extreme weather events Extreme cold weather events happen even while man-made greenhouse gases build up in the atmosphere leading to a long-term warming trend. Increase (decrease) in mean seasonal or annual temperature does not necessary mean increase (decrease) in temperature extremes.  IPCC : Models project substantial warming in temperature extremes by the end of 21st century It is virtually certain that increases in the frequency and magnitude of warm daily temperature extremes and decreases in cold extremes will occur in the 21st century at the global scale. It should further be noted that not only do regional extremes not necessarily scale with global mean changes, but also mean global warming does not exclude the possibility of cooling in some regions and seasons, both in the recent past and in the coming decades. Misperception of Global Warming [Choi et al. 2020 |The Review of Financial Studies ] Counterintuitive, but Extreme Cold under Global Warming [From Wikipedia] Rome, 26 Feb. 2018 The Impact of Melting Arctic Sea Ice Sea Ice [1980 Sep] Sea Ice [2007 Sep] [From satellite image]  Weakening the temperature gradient (south-north) Less Temperature Weakening Weakening Gradient Westerlies Polar Vortex  Providing the plenty of moisture Moisture source for heavy snow How Global Warming Causes Extreme Cold Temperature Zonal Wind [Upper Level] Jetstream 𝑅 𝜕𝑻 𝑝0 𝒖=− ln Relationship between zonal 𝑓 𝜕𝑦 𝑝1 wind and temperature gradient. Global warming tends to reduce meridional temperature gradient. If the Arctic surface warms faster than that at lower latitudes, the temperature difference between the tropics and the pole will decrease. This reduced temperature gradient may lead to weakening of the intensity of jet stream, which help arctic cold air expand southward. How Global Warming Causes Extreme Cold  Connection between Arctic warming and more extreme weather events The jet stream that surrounds the polar vortex, a large mass of cold air in the Arctic area, is weakened due to global warming, expanding the cold air mass southward. Arctic sea ice loss and cold winters in extra-polar regions are dynamically connected. [From NASA Website] NOAA Wind Chill Temperature  Wind Chill Temperature (°F) WCT (°F) = 35.74 + 0.6215T −35.75 (V0.16) + 0.4275T(V0.16) The Wind Chill Temperature (WCT) index uses to provide an accurate, understandable, and useful formula for calculating the dangers from winter winds and freezing temperature. It incorporates heat transfer theory based on heat loss from the body to its surroundings during cold and breezy/windy days. Icy start to a cold Sunday atop Hong Kong’s highest peak Tai Mo Shan. Photo: Felix Wong Distortion of t