CLIMATE CHANGE By ANDREW GARCIA, PhD Coastal Hydraulic Laboratory, - - PDF document

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CLIMATE CHANGE By ANDREW GARCIA, PhD Coastal Hydraulic Laboratory, - - PDF document

The University of the West Indies Organization of American States P ROFESSIONAL D EVELOPMENT P ROGRAMME : C OASTAL I NFRASTRUCTURE D ESIGN , C ONSTRUCTION AND M AINTENANCE A COURSE IN COASTAL


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The University of the West Indies Organization of American States

PROFESSIONAL DEVELOPMENT PROGRAMME: COASTAL INFRASTRUCTURE DESIGN, CONSTRUCTION AND MAINTENANCE

A COURSE IN COASTAL ZONE/ISLAND SYSTEMS MANAGEMENT

CHAPTER 8 (AS PRESENTED AT THE WORKSHOP)

CLIMATE CHANGE

By ANDREW GARCIA, PhD

Coastal Hydraulic Laboratory, US Army Corps of Engineers Vicksbury, MA, USA

Organized by Department of Civil Engineering, The University of the West Indies, in conjunction with Old Dominion University, Norfolk, VA, USA and Coastal Engineering Research Centre, US Army, Corps of Engineers, Vicksburg, MS , USA.

Antigua, West Indies, June 18-22, 2001

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Introduction to Climate Change

US Army Engineer Research and Development Center

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Course Outline

Part I. Indicators of climate change Proposed sources of climate change Attribution of climate change Part II. Effects of climate change Part III. El Nino and tropical cyclones

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Principle Material Sources

Intergovernmental Panel on Climate Change, Reports of Working Groups I and II Bulletin and journals of the American Meteorological Society NASA reports on Greenland ice cap (Krabill, et al.) and satellite derived atmospheric temperatures (Spencer and Christy) Various text books

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Introduction to Climate Change

Climate Change Definition… A measurable long-term change in an atmospheric or oceanic physical or chemical variable attributable to natural

  • r anthropogenic effects
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Climate Change Indicators

  • For the period 1901 – 2000, earth’s surface

temperature (land and ocean) has increased 0.6 ± 0.2°C

  • For the Northern Hemisphere, 1990’s was the

warmest decade and 1998 was the warmest year

  • For the Northern Hemisphere, there was ~ 10%

decrease in snow cover since the late 1960’s

(Continued)

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Climate Change Indicators

(Concluded)

  • There has been an overall retreat of mountain

glaciers in non-polar regions this century

  • El Nino (warm episodes) have been more

frequent, persistent, and intense since the 1970’s when compared with the previous one-hundred years

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Earth’s Surface Temperature

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Surface Temperature - 2

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Temperature by Hemisphere

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NH Proxy Temperature

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Northern Hemisphere Temperature

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Greenland Ice Cap

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NASA Airborne LASER

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NASA LASER Close-up

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Ice Accumulation - Loss

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Southern Greenland

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Southeast Greenland

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Greenland Close-up

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Absent Indicators of Climate Change

  • Southern Hemisphere oceans and parts of

Antarctica have not shown discernable warming

  • No significant trend observed in the extent of

Antarctic sea ice since 1978 using satellite

  • bservations

(Continued)

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Absent Indicators of Climate Change

(Concluded)

  • No discernable trend in tropical or extra-tropical

storm activity

  • No systematic changes in the frequency of

tornadoes, hail events, or severe thunderstorms

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Attributed Sources of Atmospheric Warming re 1750

“Greenhouse” gases…

  • Carbon dioxide (CO2) – 31%
  • Nitrous oxide (N2O) – 17%
  • Methane (CH4) – 151%
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Greenhouse Gas Growth

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Nitrous Oxide Increase

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Carbon Dioxide Increase

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Methane Increase

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Sulfate Aerosols in Greenland Ice

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What is the “Greenhouse” effect?

  • 1. Incoming solar radiation is strongest in the visible and

near UV wavelengths.

  • 2. Outgoing terrestrial radiation is strongest in the IR

wavelengths.

  • 3. “Greenhouse gases” (including water vapor) absorb
  • utgoing IR radiation thereby trapping energy.
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Incoming Solar Spectrum

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Idealized Outgoing Spectrum

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Atmospheric Absorption Spectrum

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Anthropogenic Sources of “Greenhouse” Gases

  • Carbon dioxide – burning of fossil fuels,

deforestation

  • Nitrous oxide – use of chemical fertilizers,

animal feedlots, chemical industries

  • Methane – burning of fossil fuels, rice

agriculture, deforestation (termites)

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Simulated Surface Temperature, Natural

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Simulated Surface Temperature, Anthropogenic

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Simulated Surface Temperature, Combined

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Total Radiative Forcing

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Atmospheric Temperature Trend, Troposphere

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Atmospheric Temperature Trend, Stratosphere

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Big Picture

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Summary on Detection and Attribution

Recent changes in global climate inferred from near-surface atmospheric temperatures cannot be readily explained by natural climate variability. Greenhouse warming alone is insufficient to explain the observed climate change pattern.

Barnett et al., BAMS, 1999 (continued)

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Summary on Detection and Attribution

The most probable cause of observed warming is a combination of internally and externally forced natural variability and anthropomorphic sources.

Barnett et al., BAMS, 1999 (concluded)

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Natural Systems at Risk Include -

  • Glaciers
  • Coral-reefs and atolls
  • Mangrove swamps
  • Tropical and boreal forests
  • Prairie wetlands
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Human Systems Sensitive to Change Include -

  • Water resources
  • Agriculture and forestry
  • Coastal zones and marine fisheries
  • Human health
  • Insurance and financial services
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Possible Adverse Affects Include -

  • Reduction in potential crop yields, particularly in

tropical and sub-tropical regions

  • Decreased water availability in present water scarce

regions, particularly in the sub-tropics

  • Increased flooding risk from both more frequent

heavy precipitation events and sea-level rise

(Continued)

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Possible Adverse Affects Include -

(Concluded)

  • Increased energy demand for summertime

cooling

  • Increased geographic range of vector-borne

infections

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Possible Beneficial Effects Include -

  • Increased potential crop yields in some mid-latitude

regions

  • Increased potential global timber supply from

appropriately managed forests

  • Increased water availability in some present water-

scarce regions, e.g., parts of southeast Asia

(Continued)

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Possible Beneficial Effects Include -

(Concluded)

  • Reduced human mortality in mid- and high

latitudes

  • Reduced wintertime demand for heating
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Observed Climate Trends in Caribbean Islands

  • Mean annual temperature increase of >0.5°C

during the period 1900-1995*

  • Mean annual precipitation increase of

~250mm*

* Based upon data obtained in Cuba?

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Predicted Climate Change for Island Basins

  • Inter-model agreement on climatic effects of

CO2 doubling is poor for the Western Atlantic, Caribbean and Mediterranean Seas

  • There appears to be no clear trend as to

frequency, intensity, or distribution of topical cyclones in these basins

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El Nino Region Definition

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El Nino and Hurricane Seasons

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El Nino Damage Estimates

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El Nino, La Nina, and Atlantic Hurricanes

  • La Nina episode means a greater frequency of

damaging storms and more damage per storm

  • El Nino episode does not mean no hurricanes, as

several El Nino years have seen large effects

  • Mid-Pacific equatorial SST anomaly can provide a

statistically significant indicator of damage

(Continued)

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El Nino, La Nina, and Atlantic Hurricanes

(Concluded)

  • Mid-Pacific equatorial SST anomaly is not the only

climate factor related to hurricane damage

  • There appears to be no skill in forecasting Nino SST

anomalies other than simple climatology and persistence, which is good only to 8 months

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Conditions for Tropical Cyclone Formation

  • 1. Warm ocean surface waters, ~26 degrees C, of sufficient

depth, ~50m.

  • 2. Conditionally unstable atmosphere, one that cools with

height.

  • 3. Sufficient atmospheric moisture at lower-levels, ~5km.

(continued)

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Conditions for Tropical Cyclone Formation

  • 4. At least ~5 degrees distance from the equator; sufficient

Coriolis force to produce gradient wind balance to maintain low surface pressure.

  • 5. An initiating disturbance, e.g., tropical wave.
  • 6. Low vertical wind shear between the surface and upper

troposphere. (concluded)

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Hurricane Processes,I

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Hurricane Processes, II

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Hurricane Processes, III

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Hurricane Probability

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Intense Hurricane Probability

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Closing Quote

“Models are what we use when we don’t have data.”

  • R. E. L. Pickett, 1967