Transcript Chapter 16 - Atmospheric Science Group

Chapter 16
Climate Forecasting
Figure CO: Chapter 16, Climate Forecasting--Ocean waves after storm
© Antonio S./ShutterStock, Inc.
Monthly Climate Forecasts
• Rely on established relationships between
climate and key climate forcing mechanisms—in
particular, El Niño Southern Oscillation (ENSO)
• Are a blend of statistics and model results
• Use the longest range weather forecasts from
numerical weather prediction models
– Exact timing is not so important as the overall pattern
• Use ensemble runs of a model augmented with a
more realistic ocean
Monthly Climate Forecasts
• Are modified based on ocean temperature
and soil moisture
Seasonal Climate Forecasts
• Most crucial component is ocean temperature
anomalies
– ENSO
– North Atlantic Oscillation
– Pacific Decadal Oscillation
• Methods include statistical versions of trend
and analog forecasting
• Use results of forecasting models augmented
for more realistic ocean and soil conditions
Figure 02: NCEP climate forecasts for temperature and precipitation
Courtesy of NOAA
A Problem with Seasonal Climate
Forecasts
• Forecasting changing phases of ENSO remains
a major problem
Figure 01: NCEP’s El Nino forecast. Only one out of the 40 ensemble runs
came close to predicting the rapid waning of El Niño conditions in early 2010.
Courtesy of NOAA
Interpreting Monthly and Seasonal
Climate Forecasts
• Maps look different than weather forecasts
• Maps show chances of above- or belownormal climate
– A for above normal
– B for below normal
– EC for equal chance of normal, above normal, and below
normal
– Labels, contours, and shading for odds favoring A or B
Figure 02: NCEP climate forecasts for temperature and precipitation
Courtesy of NOAA
Accuracy of Monthly and Seasonal
Climate Forecasts
• In some years, great accuracy in 90-day
temperature forecasts
• In other years, little skill in 90-day
temperature forecasts
• Precipitation forecasts show marginal skill
• Temperature and precipitation forecasts show
most skill in winter during strong El Niño or La
Niña events
Figure 03: NCEP climate forecasting inaccuracies
Source: Climate Prediction Center/NOAA
Figure 03: NCEP climate forecasting inaccuracies
Source: Climate Prediction Center/NOAA
Long-Range Climate Forecasts
• Include forecasts for decades and centuries
• Influenced by natural climate change
mechanisms like volcanoes
• Influenced by anthropogenic mechanism of
increases in greenhouse gases
• Use global climate models or GCMs
• Answer questions:
– Will global climate change in the future?
– If so, what will be causing the change?
Global climate models (GCMs)
• Make climate predictions
• Are computer programs using mathematical
equations like weather forecasting models
• Differ from weather forecasting models
– GCMs must include oceans, biosphere, cryosphere
– GCMs have coarser resolution
– GCMs often used to test the effect of changing a particular
parameter, like amount of greenhouse gases—called
sensitivity testing
Figure 04: GCM schematic flowchart
Verifying Global Climate Models
• Simulate climates of the past and compare the
simulations with data from that era
• Simulate recent climate change since the
Industrial Revolution began
• Spread of different model results is like an
ensemble forecast
– The models consistently predict “global warming”
Figure 05: The observed changes in global temperature over the past century.
Source: Intergovernmental Panel on Climate Change, "Climate Change
2007,” The Fourth Assessment Report, Working Group 1, Figure TS23;
Figure 06: 20th century climate simulated with natural and anthropogenic
climate change
Source: Intergovernmental Panel on Climate Change, "Climate Change
2007,” The Fourth Assessment Report, Working Group 1, Figure TS23;
Figure 07: Kasahara and Washington, climate modelers
Copyright, University Corporation for Atmospheric Research
Figure 08: GCM
family tree schematic
Reproduced from: Paul N. Edwards, A Vast Machine: Computer Models, Climate Data, and the
Politics of Global Warming (Cambridge: MIT Press, 2010), p. 168. Graphic by Trevor Burnham. A
clickable version of the AGCM Family Tree, with acronym expansions and information about each
lab and its models, may be found at http://pne.people.si.umich.edu/vastmachine/agcm.html
Figure 09: Jim Hansen testifies to the Senate about global warming
Courtesy of James Hansen, NASA
IPCC Scenarios of Greenhouse Gas
Emissions
• Take into account a variety of factors
– Whether the nations of the world join forces (A1 and B1)
or not (A2 and B2)
– When rapid economic growth is counterbalanced by a
leveling of population growth (A1)
– Fossil fuels used intensively (A1F1) or with nonfossil fuels
(A1B) or deemphasized in favor of nonfossil fuels (A1T)
• Most polluting is A1F1
• Least polluting are B1 and A1T
• A1B is “middle of the road”
IPCC Scenarios in Climate Models
• Give a spread like an ensemble forecast
• In the 23 GCMs of the IPCC report give an
even greater spread
• Are remarkably consistent in predicting
significant warming during the 21st century
– Greatest warming in the Arctic
• Predict a more active water cycle
– More rain in some latitudes with more water vapor
– Less rain in sinking branch of the Hadley Cell
Figure T01: IPCC scenarios for 21st-century greenhouse gas emissions
Data from IPCC
Figure 10: 3rd IPCC projections of global warming
Adapted from Robert A Rhode, ‘Global Warming Projections’, Global Warming Act.
[http://www.globalwarmingart.com/wiki/File:Global_Warming_Predictions_png]
Figure 11A: Global warming projections
Source: Intergovernmental Panel on Climate Change, "Climate Change
2007,” The Fourth Assessment Report, Working Group 1, Figure SPM5
Figure 11B: Global warming: spatial patterns during 2020s and 2090s
The Fourth Assessment Report "Climate Change 2007,” Intergovernmental Panel
on Climate Change, Working Group 1, Figure SPM6
Possible Impacts of Global Climate
Change with the A1B Scenario
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Droughts become more frequent
Warmer winters melt glaciers and snowpack
Habitats disappear and extinctions follow
Heat waves, droughts, floods take human toll
Tropical rain forests and coral reefs disappear
Extinctions of up to half of all species
Partial melting of ice sheets on Greenland and
Antarctica
– Massive coastal flooding, erosion, more hurricanes
Figure 12: Precipitation changes due to global warming
Source: Intergovernmental Panel on Climate Change, "Climate Change
2007,” The Fourth Assessment Report, Working Group 1, Figure SPM7
Figure 13: Global warming and impacts as labels
Figure 14: U.S. shoreline erosion
Courtesy of U.S. Global Change Research Program
(www.globalchange.gov)
Figure 15: Atlantic hurricane tracks now and with global warming
Courtesy of NOAA
More possible impacts
• Possible increase in forest growth and
productivity
• Availability of moisture and nutrients for trees
could change
• Trees forced to adopt, migrate, or die
• Trees forced northward and upwards
• Trees may run out of territory
• Frequency of fires, storms, droughts, outbreaks
of diseases and pests are tree risks
Figure 16: Current forest distribution
Courtesy of U.S. Global Change Research Program
(www.globalchange.gov)
Figure 17: Forecasts of forest changes
Courtesy of U.S. Global Change Research Program
(www.globalchange.gov)
Societal Responses to Global Climate
Change Forecasts
• Mitigation: a response to limit increases in
greenhouse gases to prevent worst impacts of
global warming
• Adaptation: steps to reduce vulnerability to
climate change and take advantage of its
benefits
Specific Societal Responses
• Kyoto Protocol took effect in 2005
– Limit greenhouse gas emissions to 5% below 1990 levels
– US never ratified
– Expires in 2012
• Carbon taxing and trading, “cap-and-trade”
– A trading option like commodity trading with government
setting prices, popular in Europe
– A tax on carbon would be simpler, but uncertainty about
amount of emissions allowed
Geoengineering
• Increase the Earth’s albedo
– Space-based mirrors
– Intentionally inject sulfur aerosols into the air
• Physically remove carbon dioxide from the air
– Widespread forestation
– Capture carbon dioxide and pump it underground
– Dumping iron into the ocean to create phytoplankton
blooms to draw down carbon dioxide
• Can have serious ecological consequences
Figure B01: Map of participants in climateprediction.net
Courtesy of Carl Christensen and Tolu Aina, climateprediction.net project,
Oxford e-Research Centre
Figure 18: Geoengineering schematic
Figure 19: digital combination of hi-res satellite data of land, sea,
topography, ice,clouds, and even city lights
Courtesy of NASA Goddard Space Flight Center Image by Reto Stöckli (land surface, shallow
water, clouds). Enhancements by Robert Simmon (ocean color, compositing, 3D globes,
animation). Data and technical support: MODIS Land Group; MODIS Science Data Support Team;
MODIS Atmosphere Group; MODIS Ocean Group Additional data: USGS EROS Data Center
(topography); USGS Terrestrial Remote Sensing Flagstaff Field Center (Antarctica); Defense
Meteorological Satellite Program (city lights).