1. IPCC Assessment Report: Chapter 11 Regional Climate Projections Summary by: Rich Higgins & Karen Akerlof

2. Table of Contents 1. Regional Climate and Models’ Overview 2. Unifying Themes across Regions 3. Regional Climate Projection Methods 4. Africa 5. Europe & Mediterranean 6. Asia 7. North America 8. Central & South America 9. Australia & New Zealand 10. Polar Regions 11. Small Islands

3. Regional Intro Climate varies region to region – change is not uniform across globe Driven by the uneven distribution of solar heating and the individual responses and interactions between atmosphere, oceans and land surface. Human activity can have significant local impact. Changing the land surface of a local area (forest converted to a city for example)

4. Background: Third Assessment Report (TAR) Regional climate change was largely based upon the rather coarse General Circulation Model (GCM) in 2001. The information regarding temperature change was fairly general, and regional precipitation statements were very limited in predictions. Assessment of regional climate extremes were too sparse to make many conclusive or meaningful statements

5. Current Models’ Overview Atmosphere-Ocean General Circulation Models (AOGCMs) developed from the GCMs. The AOGCMs computational grid is approximately 200km. While better, this still leaves room for improvement at the regional scale. Additional information at finer scales (less then 200km) can be achieved through using high resolution in these dynamic models or empirical statistical downscaling. Downscaling technique: This methodology is an important focus in the AR4 for regional climate studies and has only recently been able to be tailored to specific climate change

6. Current Models’ Overview – MMDs Multi-model dataset (MMDs) These calculated avgs from 21 models are important to note because the charts, graphs and maps contained within this chapter use these as a basis

7. Unifying Themes Across All Regions Warming is expected worldwide, however, the amount of projected warming generally increases from the tropics to the poles, particular in the northern hemisphere. Precipitation is latitude-dependant as high latitudes near the poles are generally expected to have an increase while many regions adjacent to the tropics are generally expected to have a decrease, a result of the poleward expansion of subtropical highs Interiors of continents are generally expected to warm more than coastal areas, as less water is available for evaporative cooling

8. Regional Climate Projection Methods

9. AOGCMs primary tool in creating global climate projections and are useful in evaluating regional processes and responses. However, with large grid sizes, other methods are needed to explore regional impacts in finer detail Three methods: – Downscaled AOGCMs Dynamical Statistical – AGCMs – RCMs

10. http://precis.metoffice.com/docs/PRECIS_Update2002.pdf Regional Climate Model

11. http://precis.metoffice.com/docs/PRECIS_Update2002.pdf Present-day precipitation patterns in the UK, Hadley Centre for Climate Prediction and Research

12. Regional Climate Projection Methods More on statistical downscaling – Large-scale atmospheric variables (predictors) linked to local/regional variables (predictands). – Other types of statistical downscaling: Statistical-dynamical downscaling Pattern scaling Much of SD work done for specific projects and not reported in the academic literature, especially work done in the developing world.

13. Regional Climate Projection Methods: Uncertainties Same global projection uncertainties (i.e. ENSO) applicable regionally, but especially relevant are uncertainties in land use, land cover, and aerosol forcing. Smaller ratio between signal to internal variability makes detection of responses difficult. Many regions are deficient in climate data. Finally, models’ performance adds to uncertainty, but hard to evaluate that contribution.

14. Regional Climate Projection Methods: Quantifying Uncertainties Definition of ensemble: A group of parallel model simulations used for climate projections. The variation of the results gives an estimate of uncertainty. There are three versions: Same model, different initial conditions characterize internal model variability Multi-model ensembles characterize inter-model variability Perturbed parameter models vary parameters systematically to produce more objective estimates of uncertainty than multi-model ensembles.

16. Regional Climate Projection Methods: Quantifying Uncertainties In the TAR, few methods available to quantify uncertainties. Since then, studies have begun to use multi-model ensembles to provide uncertainty and probability information on regional scales. Why is this needed? “… a key goal for climate research is to predict (probability density functions) of transient climate change for plausible scenarios of future climate forcing. In particular, pdfs of transient changes at regional scales are required by the impacts community for risk assessment.” – Harris et al. 2006

17. Fillipo Giorgi 23 “GF” regions widely used to evaluate regional climate change Giorgi and Francisco (2000)

18. Using multi-model ensemble 2070-2099 minus 1962-1990; REA method in first column Giorgi and Mearns (2003)

19. Change in precipitation as atmospheric CO2 doubles Harris et al. (2006) Using perturbed physics ensemble

20. Change in surface temperature as atmospheric CO2 doubles Harris et al. (2006)Using perturbed physics ensemble

21. Tebaldi et al (2004), Greene et al (2006) Bayesian approach using multi-model ensemble 2090-2099 compared to 1980-1999

22. Africa: Key Climate Processes Majority of Africa is tropical or subtropical with the central phenomenon being the seasonal migration of tropical rainbelts. Small shifts in these belts can result in locally large precipitation changes. Northern and southern boundaries of the continent in the winter are governed by the passage of mid-latitude fronts bringing precipitation. Southern boundary of Sahara and Sahel (region of high interest due to prolonged drought in 1970’s and 1980’s) : – 1. Sea surface temp change: Colder northern hemisphere oceans moving equatorward have been correlated with a reduction in Sahel rainfall. – 2. This has created interest that localized aerosol cooling could dry the region

23. Africa: Overview It is unclear how precipitation in the Sahel region and southern Sahara will evolve Warming is very likely to be larger than annual global mean warming throughout the African continent during all seasons. Dry subtropical regions are expected to warm the most. Annual rainfall is likely to decrease in much of northern Africa, especially along the Mediterranean coast, as well as in southern Africa in the winter. Meanwhile, there is likely to be an increase in rainfall in east Africa.

26. Predicted Precipitation Change This map takes the difference between the recorded annual mean precipitation in Africa in the years of 1980-1999 and the predicted precipitation mean of the 21 MMD models.

27. Source: United Nations Environmental Programme

28. Europe & Mediterranean: Key Climate Processes Most of Europe, (especially western) owes its relatively mild climate to the northward heat transport of the Atlantic MOC. Most models suggest that increased greenhouse gases will weaken this current, however not enough to negate the overall effects of global warming in the region Variations in atmospheric circulation : 2003 heat wave associated with an extended anti-cyclonic pattern, while 2002 flooding was associated with a cyclone rotation Local thermodynamics associated with current snow cover in Europe. Removal is likely to have a positive feedback amplifying warming

29. Europe & Mediterranean: Overview Warming is likely to be larger than annual global mean warming throughout the region Seasonally, the largest warming is likely to take place in northern Europe during the winter months Annual precipitation is very likely to increase in northern Europe however is very likely to decrease in the Mediterranean area. Length of snow season and snow depth are both very likely to decrease

30. Reindeer Crossing, Finland…

32. Paris, France…

33. St Marks Square, Venice, Italy…

36. Mean pressure (hPa) at sea level in the Dec-Jan-Feb in the years of 1980-1999 Vs MMD multi model projected mean.

37. Simulated changes in mean 10-m level wind speed from the years (1961 to 1990) – (2071 to 2100) ECHAM4HadAM3H

38. Asia: Key Climate Processes Northern & Central Asia (including Tibet) Temperature response is strongly influence by changes in winter and spring snow cover. Polar fronts and westerly winds out of NW are responsible for most precipitation South, Southeast, and East Asia - Monsoons dominate climate Seasonal prevailing winds – linked to steep temp gradient between Tibetan plateau and coastal areas Precipitation in monsoon is affected by strength of monsoonal flow and amount of water vapor transported Tropical cyclones assist to strengthen monsoonal flow

39. Asia: Overview In southeast Asia, warming is likely to be similar to the global mean, while moving toward northern Asia and the Tibetan Plateau warming will likely increase beyond the global mean. Precipitation is very likely to increase in northern latitudes as well as in Tibet, especially in the winter. It is also likely to increase across eastern and some areas of southern Asia in the winter. The summer precipitation is likely to increase in most of Asia with the exception of central Asia.

40. Mountainous Regions: Tibet Tibet: roof of the world, high mountains contain the some of the largest ice fields outside of the poles. Tibet is the source of ten major rivers in Asia serving millions of people in surrounding lowland areas

41. Mountains: Difficulties in predictions Tibet prediction is a warming trend of 2-4 degrees Celsius 1 degree Celsius increase in mean temperature = 150m rise of snowline Rapid and systematic changes can occur in climate over very short distances and elevations, leading to issue with predicting change in mountainous areas Few models can address such localized details in mountains as currently the spatial resolution is still too coarse; therefore this region is one where the prediction is somewhat uncertain

45. Asia: Climate Extremes In east Asia hot spells will be very likely to be longer, hotter and more frequent, and it is very likely that fewer very cold days will occur. Cyclones in south, east, and southeast Asia are likely to have more extreme rainfall and winds resulting in more devastating wind damage and flooding.

46. Flooding from cyclone in Bangladesh

47. North America: Key Climate Processes Central and northern regions influenced by mid latitude fronts and cyclones. Slight poleward shift in these storm tracks is predicted. Much of central and eastern USA influenced by Great Plains low-level jet stream pulling moisture in from Gulf of Mexico Southwest region fairly arid due to subtropical ridge of high pressure. Projection of warming of Pacific Ocean nearby is likely to push this high northward and further decrease precipitation in the region

48. North America: Overview Annual mean warming is likely to exceed global mean warming in most areas Annual mean precipitation is very likely to increase in Canada and the northeast US, and likely to decrease in the southwest. Snow season length and depth are very likely to decrease throughout the continent. The exception to this is in northernmost Canada where it is likely to increase

54. Death Valley, CA

56. Central and South America: Overview Annual mean warming is likely to equal global mean warming in southern South America, but larger than mean in other areas. Annual precipitation is likely to decrease in most of Central America and the southern Andes. Precipitation is likely to increase in Tierra del Fuego in the winter, and in south-eastern South America in the summer. Northern South America rainfall patterns uncertain.

57. Central and South America http://daac.gsfc.nasa.gov/oceancolor/images/central_america_topo_sml.jpg http://photojournal.jpl.nasa.gov/jpegMod/PIA03388_modest.jpg Amazonia La Plata Basin Andes Edge of Caribbean plate

58. Central and South America: Uncertainties Problems in simulating current tropical climate variability There are inter-model differences in future ENSO patterns Reproducing precipitation patterns is difficult (Amazon) Andes mountains unresolved in low-res models Amazon biochemical processes present large uncertainties Cyclones source of summer rainfall uncertainty in CAM

59. Central and South America: Key processes Mexico, Central America have dry winter and rainy season May-Oct. South American Monsoon System dominates seasonal precipitation in tropical/sub-tropical South America. Strongly influenced by ENSO. Amazonia has had increasing rainfall over last 40 yrs, even with deforestation The Amazon is central to global carbon cycle, regional climate

60. Temperature changes between 1980-1999 and 2080-2099

61. Precipitation changes between 1980-1999 and 2080-2099

62. Land Use and Land Cover Changes in vegetation cause changes in surface properties Human induced land cover change increases GHG emissions Agricultural expansion in mid-latitude areas causes cooling Tropical plant losses may result in warming of up to 2 degrees Celsius due to decreased transpiration

64. Australia and New Zealand: Overview All of Australia and New Zealand are very likely to warm this century similar to overall global mean. Increased frequency of extreme high daily temps and decrease in frequency of cold extremes is very likely. Extremes in daily precipitation likely to increase. Precipitation likely to decrease in southern Australia in winter/spring, and is likely to increase in the west of the South Island of New Zealand.

65. Australia and New Zealand http://maps.grida.no/

67. Australia and New Zealand: Key processes Affecting Australia: Australian monsoon, Southeast trade winds, subtropical high-pressure belt, mid-latitude westerly winds Affecting New Zealand: Subtropical high-pressure belt, mid- latitude westerly winds Tropical cyclones provide much rainfall/winds for north coast of Australia, sometimes North Island of New Zealand as well Rainfall in New Zealand influenced by westerly winds interacting with mountainous topography

68. Australia and New Zealand: Uncertainties ENSO significantly impacts rainfall, drought and tropical cyclones in area. Future behavior of ENSO pattern uncertain. Large inter-model differences in monsoon rainfall projections, so little confidence in predictions for Northern Australia. Continental rainfall projections generally vary substantially. No assessment of MMD projections for region available. No downscaled MMD projections for New Zealand.

69. Temperature changes between 1980-1999 and 2080-2099

70. Precipitation changes between 1980-1999 and 2080-2099

72. Polar Regions: Overview Annual mean warming in the Artic is very likely to exceed the global mean with largest increases in winter and smallest in summer. Annual Arctic precipitation is very likely to increase, again largest increases in winter and smallest in summer. Arctic sea ice is very likely to decrease in extent, thickness. It is very likely that the Antarctic will be warmer and precipitation will increase.

73. Arctic and Antarctica http://maps.grida.no/

74. Polar Regions: Uncertainties Large natural variabilities on many time scales Important teleconnections highly uncertain (ENSO) Complex interactions and feedbacks not well understood Clouds, sea ice, planetary boundary layer processes not well represented in models Lack of observation, especially over Antarctica

75. Polar Regions: Key processes in Arctic Sea ice plays crucial role in climate due to albedo Large multi-decadal variabilities (warming 1920s-1940s, cooling 1940s-1960s) Patterns of variability difficult to sort out because so many (Northern Annular Mode, Pacific-North American Pattern, and Pacific Decadal Oscillation) NAM/NAO was in positive phase last 3-4 decades, now in mean state. Positive trend predicted for this century

76. Polar Regions: Key processes in Antarctica Warming should increase precipitation, but circulation pattern changes could modify temp and snowfall patterns Dominant patterns are the Southern Annual Mode and ENSO. Positive phase of SAM associated with cold anomalies over most of Antarctica and warm anomalies over the peninsula. Recent multi-decadal drift is toward a positive phase. Pronounced warming over peninsula has been observed, but there’s been little change over rest of continent over last half decade

77. http://maps.grida.no/

78. Annual mean temp response AntarcticaArctic

79. Annual mean precip response AntarcticaArctic

81. Small Islands Overview Sea levels will continue to rise around islands of Caribbean, Indian Ocean and Northern and Southern Pacific Oceans – but not geographically uniformly Large deviations in sea rise models All island areas very likely to warm, but somewhat less than global mean Areas of rainfall decrease and increase likely in various island regions

82. Small Islands: Caribbean, Indian Ocean, Pacific www.satsig.net/lat_long.htm

83. Small Islands Uncertainties AOCGMs too coarse to distinguish islands; little downscaling work has been done Climate processes not well understood such as midsummer drought in the Caribbean and ocean-atmosphere interaction in the Indian Ocean Not enough information on future SST to predict regional cyclone changes Few models address storm surges

84. Small Islands Key processes: Caribbean Dominant influence is North Atlantic Subtropical High (NAH) In winter, NAH at southernmost and region dry As NAH moves north, spring trade winds increase and easterly waves move into the Caribbean Primary rainfall source is storms/hurricanes that mature from these waves from June-Nov. (rainy season) Rainfall variability affected by ENSO

85. Small Islands Key processes: Indian Ocean Influenced primarily by Asian monsoons Monsoonal variability is of weeks to years, is associated with ocean feedback, and is not understood At times, there is a correlation between ENSO and monsoonal variation There are different responses in the northern and southern Indian Ocean based on wind stress and precipitation

86. Small Islands Key processes: Pacific Warm, maritime climate with large rainfall Biggest influences: easterly trade winds, southern hemisphere high pressure belt, Intertropical Convergence Zone and South Pacific Convergence Zone Largest rainfall occurs after migration of ITCZ and SPCZ Variability strongly impacted by ENSO Tropical cyclones prominent feature

88. Impacts: inundation, erosion, salt water intrusion. Problems for models: Not enough information on changes in waves, near-coastal currents to assess erosion. Sparse tide gauge networks and short data records make risk of extreme sea levels hard to define. Extreme sea levels result from increases in mean sea level and changes in the track, frequency and/or intensity of storms. GCMs are required for large-scale context of changes, but resolution too coarse for cyclones and extreme winds. Coastal Zone Climate Change