Lecture of Introduction to Sustainability/Survivability Science

1. 京都大學　グロバールCOEプログラム2009-2014 • 極端気象と適応社会の生存科学 • Sustainability/Survivability Science for a Resilient Society Adaptable to Extreme Weather Condition 1 Lecture of Introduction to Sustainability/Survivability Science Extreme weather and its prediction (1) Dr. Bin HE hebin@flood.dpri.kyoto-u.ac.jp Disaster Prevention Research Institute Kyoto University, Japan

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3. 1. What is Extreme Weather? Did anyone experience it? Floods Heat waves Droughts blogs.msdn.com ens-newswire.com Cyclones Tidal waves nowpublic.com qwickstep.com spacebeaglenotes.blogspot.com spacebeaglenotes.blogspot.com

4. IPCC TAR 2001 definitions Extreme event: “an average of a number of weather events over a certain period of time which is itself extreme (e.g. rainfall over a season)” Simple extremes: “individual local weather variables exceeding critical levels on a continuous scale” Complex extremes: “severe weather associated with particular climatic phenomena, often requiring a critical combination of variables” Extreme weather includes weather phenomena that are at the extremes of the historical distribution, especially severe or unseasonal weather. The most commonly used definition of extreme weather is based on an event's climatological distribution. Extreme weather occurs only 5% or less of the time.

5. TYPEs of Extreme Weather • Hurricanes • Tornadoes • Typhoons • Flooding • Thunderstorms • Monsoons • Lightning • Bizarre Storms wet and windy extremes http://www.google.co.jp/imghp?hl=ja&tab=wi

6. TYPEs of Extreme Weather Dry and hot extremes • Drought • Dust storm • Wild fire • MORE……!! http://www.google.co.jp/imghp?hl=ja&tab=wi

7. Characteristics of Extreme Weather • Nonlinear process • . Uncertainty. • . Model's limitation to predict extreme. • Combination • . Snow covers, cloud covers… • . Minimum and maximum temperature. • . Combined high temperature and high humidity . • . Wind speed, cold temperature and wind sheer. • . Precipitation amount and concentration. • . Time, location and etc... Is outside the normal range of intensity that a region experiences. Complicated and very difficult to understand weather patterns fully, but we can understand it well enough to make useful decisions for society.

8. Characteristics of Extreme Weather 90th percentile Severity large impacts (extreme loss): • Injury and loss of life • Damage to the environment • Damage to ecosystems Extremeness large values of variables: • maxima or minima • exceedance above a high threshold • exceedance above all previous recorded values Frequency Longevity • Acute: Having a rapid onset and following a short but severe course • Chronic: Lasting for a long period of time (> 3 months) Source: www6.cptec.inpe.br/caio/talks/cuba-coelho

9. In order to understand climate change, we must have an understanding about both weather and climate. What is the difference between Climate and weather? ‘Climate is what we expect, weather is what we get.’ Climate is the average of daily weather parameters over many years and characterizes seasons as well as geography. Weather is what we experience on a day to day basis and what guides our daily outfit and plans for local travel and recreation… Weather adds up to climate over time and climate informs weather predictions - they are connected through time and dependent on place. www.lmnts.org http://www.clipartpal.com/clipart/science/rain_116296.html

10. Linking Weather and Climate • “weather” and “climate” treated separately. • (1) How do climate variations and change affect weather phenomena? • (2)  How do weather phenomena affect climate variations and change?  • (3)  What are key phenomena and processes that bridge the time scales between synoptic-scale weather (time scales of order a few days) and climate variations of a season or longer? • Real physical system is a continuum: • Fast “weather” processes • Slower “climate” fluctuations • Understanding connections between weather and climate is required to make progress in addressing important societal issues: • Assessing risks • Abrupt climate change www.atmos.umd.edu/~martini/wrfchem

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12. 2. Extreme weather and global change • Difference between climate change and global warming? Global Warming involves warming up of the Earth based on its average temperature, while climate change is more broad and involves the change in the average weather, such as temperature, wind patterns, and precipitation, than an area experiences. • Examples of extreme weather events being affected by global warming? Some events are floods, droughts, hurricanes, tornadoes, changes in precipitation and temperature, and more. • Connection between global warming and extreme weather: Global warming changes the circulation of heat around earth and as a result it changes how energy flows through weather systems. For example, areas of the ocean will heat differently and air masses will heat differently as well. Also the evaporation and precipitation patterns will likely change. IPCC 2007

13. http://maps.grida.no/go/graphic/trends_in_natural_disasters

14. Trends in temperature and rainfall • The Earth’s surface has warmed about 0.6 degrees in the past 100 years, with the 10 warmest years all occurring since 1990. • Other evidence of global warming includes more heatwaves, warming of the oceans and lower atmosphere, less snow, and glacial retreat. Arctic summer sea ice loss: Predictions v reality ‘We are basically looking now at a future climate that's beyond anything we've considered seriously in climate model simulations’: Christopher Field, Director, Carnegie Institute Department of Global Ecology, Stanford University, IPCC . Feb 15 2009. IPCC 2007

15. Potential negative effects SRES Sea-Level Rise • Higher sea levels Global Warming melts ice caps and expands water, resulting in a rising sea level. • Erosion of coastal areas Effected by Storms, Precipitation, Sea level rise - Damage to estuaries • Decline in water quality Increase salinity of bays, rivers, and groundwater tables - Decreasing yield for fisheries - Decrease in marine biodiversity/ migration of species - Increase in extreme weather events Property damage Higher insurance costs Negative impacts on tourism etc… IPCC 2007

17. Disasters from extreme weather show vulnerability to climate change • 95% of disaster deaths over last 25 years in low- and middle-income countries • Rapid growth in number of extreme weather ‘natural’ disasters: • storms, floods and droughts rather than earthquakes, volcanic eruptions and industrial accidents Severe weather affects everyone on our planet! Impacts individuals, economies, governments, wars….. http://www.huffingtonpost.com/news/extreme-weather

18. Extremes and global warming • Global Warming is linked to extremes in weather conditions. • Increase in the number and intensity of extreme weather events such as hurricanes, floodings, droughts, cyclones and other severe storms. • Costs of damage from extreme weather events linked to global warming are very high. • Increase in number and severity of extreme events due to global warming. • More heat waves. • More floods, hurricanes. http://www.huffingtonpost.com/news/extreme-weather

19. Extreme Weather Events • (IPCC, 2007) The availability of water plays a more important role on these impacts than temperature itself IPCC 2007

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21. 3. Effect of extreme weather • Extreme weather has an enormous impact on people around the world. • It affects the production of food, because droughts and floods interfere with agriculture. • Severe storms can take lives and destroy coastal communities. • The economic impact of lost buildings, jobs, and homes can be devastating. http://www.huffingtonpost.com/news/extreme-weather

22. Extreme Risk and Extreme Weather Severe events (extreme loss events) caused by: • Rare weather events • Extreme weather events (amenable to EVT) • Clustered weather events (e.g. climate event) Extreme weather Damage Loss Extreme loss is not always due to extreme weather! http://www.huffingtonpost.com/news/extreme-weather

23. Who is most at risk... Urban population in low-elevation coastal zone • Urban populations already facing difficulties with extreme weather events • High vulnerability of infants & children including impacts on long term development as well as more immediate impacts • Disruptions that affect urban livelihoods • Urban centres at risk of sea-level rise - on coasts with settlements and water sources at risk • Urban populations with the least resilience • How large their impact is so dependent on what is done in advance regarding preparedness http://www.huffingtonpost.com/news/extreme-weather

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25. 4. Prediction of extreme weather • General information • No specific tools or procedures in generally. • Necessary to improve model forecast accuracy. • Numerical model based probabilistic forecast. • Increase model's predictability to extreme. • Seasonal dependence. • Experiences of forecasters • Statistical model based probabilistic forecast. • Ensemble or single forecast. • Multi-methods • Considering the ratio of cost/loss http://www.wmo.int/pages/prog/gcos/scXVI/09.4_WCAS_Kolli

26. Dependence of socio-economic activities on weather and climatic factors • Reliability of climate products including awareness of associated uncertainties and their implications to decision-making • Accessibility of useful weather/climate information for decision making • Ability of users to act on the basis of climate information Value of weather prediction information to Society http://www.wmo.int/pages/prog/gcos/scXVI/09.4_WCAS_Kolli

27. General Frame Modified from www.wmo.int/pages/prog/gcos/scXVI/09.4_WCAS_Kolli

28. Seamless Suite of Forecasts Source: http://www.cgd.ucar.edu/cas/Trenberth/Presentations/ClimForecastsTrenberth www.casc.org/meetings/aug07/Buja

29. Weather Prediction – Early 20 Century • Forecasting was a subjective art • Based on surface observations • Forecasts of extreme events were poor beyond 12 hours Source: www.nws.noaa.gov/com/files/50thsymposium3animation

30. Weather Prediction -Today • Based on sophisticated global and regional numerical models • Initialized with global observations, satellites, aircraft, ships, buoys, radar • Produce accurate forecasts of extreme events 5-7 days in advance • Including “hazards assessment” product to day 14 • Receives Over 116 Million Global Observations Daily • Sustained Computational Speed: 450 Billion Calculations/Sec • Generates More Than 5.7 Million Model Fields Each Day • Global Models (Weather, Ocean, Climate) • Regional Models (Aviation, Severe Weather, Fire Weather) • Hazards Models (Hurricane, Volcanic Ash, Dispersion) • Quick updating www.cpc.noaa.gov/products

31. In recent decade: Internet opencongress.org http://wirelessbroadband.seesaa.net/article/131781801.html

32. Satellites in Orbit http://www.google.co.jp/images

33. Data archive Some figure from commons.wikimedia.org

34. Data sources • In-situ Data • Monthly means/extremes of temp. & total precip • Daily max/min mean temperatures • Hourly data • Marine surface observations (ships/buoys) • Aircraft observations e.g. 1850 or 1900-current • Satellite Data • Polar Orbiting Environmental Satellites (POES) • 1978-current • Geostationary Operational Environmental Satellites (GOES) • 1978-current 300,000GB • Radar Data • Radar (NEXRAD) – U.S. 1995-current 360,000GB http://www.dfo-mpo.gc.ca/media/back-fiche/2003/mar10-eng.htm

35. Examples of prediction . Extreme Weather and Climate Events Web Page • Description • One of NCDC’s most popular web pages • More than 100K accesses per month • Central NOAA web page for information/links on hurricanes, tornadoes, storm events, drought, extreme temperatures, heavy precipitation, etc. • Billion dollar weather disasters Applications • Natural hazards mitigation • Insurance claims • Agriculture • Many others http://lwf.ncdc.noaa.gov/oa/climate/severeweather/extremes.html Hurricane Mitch

36. New probe to help predict extreme weather A water tracking satellite launched by the European Space Agency is designed to help give faster predictions of floods and other extreme weather incidents caused by climate change. The 315 million euro Soil Moisture and Ocean Salinity (SMOS) probe was carried into space on a Russian Rockot launcher from the Plesetskcosmodrome in northern Russia on Monday, local time, and is now orbiting 760 km above Earth from where it will gauge the impact of climate change on the movement of water across land, air and sea. By providing precise measures of soil moisture and ocean surface salt levels, SMOS will fill important gaps in scientific knowledge about the water cycle and help meteorologists make more accurate forecasts in near-real time, say experts. http://www.cosmosmagazine.com/news/3108/probe-will-monitor-climate-impact-water

37. Examples of prediction Future Scenarios for Summer Monsoon Rainfall and Annual Temperature over South Asia under A2 Scenario The general conclusion that emerges of the diagnostics of the IPCC AR4 simulations: Asian summer monsoon rainfall is likely to be enhanced. From Kumar et al.

38. Examples of prediction • We can’t make accurate predictions about the rate of extreme weather because climatic patterns are too complex and have too many variables. • Predictions are based on computer models that predict how phenomena such as temperature, rainfall patterns, & sea level will be affected. • Computer models are becoming more reliable as more data are available, additional factors are considered, & faster computers are built. Source: www.nws.noaa.gov/com/files/50thsymposium3animation.ppt

39. Example findings for temperature extremes in Africa 10th percentile 90th percentile • Shift in the frequency distribution towards larger values • Frequency of extremely cold days and nights has decreased • Frequency of extremely hot days and nights has increased • No trends found in many stations • Only a few stations show statistically significant trends • Some stations are getting drier • Longest dry spells are getting longer for a few stations www6.cptec.inpe.br/caio/talks/cuba-coelho

40. Predictability of weather and climate www.nws.noaa.gov/com/files/50thsymposium3animation http://www.cgd.ucar.edu/cas/Trenberth/Presentations/ClimForecastsTrenberth

41. Statistical tools used in analysis of extreme weather events Detection of extreme weather changes… changes in mean changes in variance Statistical tests detection of trend http://www.cgd.ucar.edu/cas/Trenberth/Presentations/ClimForecastsTrenberth

42. Detection of extreme weather changes… • Spatio-temporal exploratory methods and probability models • Analysis of extremes with covariates indices of large scale flow regimes. • Characterize completely extremes properties • Improve the methods to compare observed extremes to simulated ones. • Percentile analysis, use of extreme indices (number of frost days, number wet days, etc.) • Multivariate extreme analysis • Software: Statistica, R, SPSS, etc. http://www.cgd.ucar.edu/cas/Trenberth/Presentations/ClimForecastsTrenberth.

43. Type of statistical tests Non-parametric test which does not make assumptions about the population distribution; Parametric test Which is based upon the assumption that the data are sampled from a Gaussian distribution.

44. Steps to apply a statistical test : • 1) The first step in any hypothesis testing is to state the relevant null (H0) andalternative hypotheses (H1) to be tested; • 2) The second step is to consider the assumptions being made in doing the test; • 3) Compute the relevant test statistic (the distribution of such a statistic under the null hypothesis can be derived from the assumptions); • 4) Compare the test-statistic (S) to the relevant critical values (CV) ; • 5) Decide to either fail to reject the null hypothesis or reject it in favor of the alternative. The decision rule is to reject the null hypothesis (H0) if S > CV and vice versa. http://www.atmosphere.mpg.de/enid/1__Weather___Fronts/-_Weather_and_Climate_15x.html

45. Length of the records – how many years…? • Internationally accepted convention recommended by the WorldMeteorological Organization (WMO) that the 30-year period is a basicclimatic time scale, and the statistical properties calculated for theconsecutive 30-year periods 1901-1930, 1931-1960, and mostfrequently used 1961-90. These are called limatologically standardnormals.

46. Trend analysis of extreme weather events He and Takara, et al. 2010

47. 1910-2009 He and Takara, et al. 2010

48. Detection of long term trend positive and significant trends positive and significant trends He and Takara, et al. 2010

49. Changes of future projections Changes in annual precipitation a), soil moisture (b) For the period 2080-2099 respect to 1980-1999, A1B Probability density functions from different studies for global Tmean change for the different SRES ( source IPCC,2007)

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