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IPCC Assessment Report: Chapter 11

IPCC Assessment Report: Chapter 11. Regional Climate Projections Summary by: Rich Higgins & Karen Akerlof. Table of Contents. 1. Regional Climate and Models’ Overview 2. Unifying Themes across Regions 3. Regional Climate Projection Methods 4. Africa 5. Europe & Mediterranean

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IPCC Assessment Report: Chapter 11

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

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

  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.

  15. 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

  16. 23 “GF” regions widely used to evaluate regional climate change FillipoGiorgi Giorgi and Francisco (2000)

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

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

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

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

  21. 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

  22. 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.

  23. PredictedPrecipitationChange 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.

  24. Source: United Nations Environmental Programme

  25. 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

  26. 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

  27. Reindeer Crossing, Finland…

  28. Paris, France…

  29. St Marks Square, Venice, Italy…

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

  31. Simulated changes in mean 10-m level wind speed from the years (1961 to 1990) – (2071 to 2100) ECHAM4 HadAM3H

  32. 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

  33. 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.

  34. 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

  35. 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

  36. 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.

  37. Flooding from cyclone in Bangladesh

  38. 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

  39. 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

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