Chapter 16Chapter 16

Climate ForecastingClimate 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 below-

normal 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

• 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 warmingCourtesy 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).