Organization:
Research Title: Paleoclimatology Program (PAGES)
Funding Level (millions of dollars):
| FY94 | 4.1 |
|---|---|
| FY95 | 3.9 |
| FY96 | 3.9 |
Committee on Environment and Natural Resources (CENR) Component:
(a) Subcommittees: Global Change Research Subcommittee (100%)
Task Group on Observations and Data Management Committee on Fundamental
Science
(b) Environmental Issue: Natural Variability (primary) Climate Change
(secondary)
(c) Research Activity: Systems Structure and Function: Observations (45%);
Understanding (30%); Data Management (25%)
Organizational Component:
Office of Global Programs
NOAA/OGP
1100 Wayne Ave., Suite 1225
Silver Spring, MD, 20910
Point of Contact:
C. Mark Eakin
Phone: 301 427-2089 x710
E-Mail: eakin@ogp.noaa.gov
Research Goals:
To observe and identify the causes and processes responsible for natural climate
variability on annual to century scales, and to extend the baseline of natural climate
variability data over the last 2,000 years.
Research Description:
The reliable prediction of decade to century-scale climate variability requires
knowledge
of past climate variability and an understanding of how the climate system operates
on time scales longer than a few decades. Most 50 to 150-year long instrumental
records
of past
climate change are too short to obtain this knowledge. Development of centuries-
long
records of North American drought, ENSO-related changes, Asian monsoon
variability,
North Atlantic climate change, and marine ecosystem dynamics all receive high
priority.
Equally important are efforts to establish a paleoclimatic framework for testing
the ability of predictive models to simulate the observed decade- to century-scale
patterns of past climate, ocean, biosphere, and trace-gas change. The NOAA
Paleoclimatology
Program is backed by an enthusiastic research community, and is guided by strong
national and international advisory structures. While the NOAA paleoclimate
research
is global in scope, it also supports development of needed "paleo perspectives" for
other program elements in NOAA
and the USGCRP.
Understanding past climate changes (30%): An understanding of how the climate system responded to altered forcing in the past will be key to predicting how climatic variability will be affected by future greenhouse warming. This understanding may also help anticipate some types of climate system responses ("surprises") that are not apparent in the relatively benign record of climate change over the past 150 years.
Data management and access (25%): The ICSU World Data Center for Paleoclimatology, housed at NOAA's National Geophysical Data Center and managed by the NOAA Paleoclimatology Program, has built the largest public-domain databank of global paleoenvironmental information.
Program Interfaces:
The NOAA established ICSU (International Council of Scientific Unions) World
Data
Center for Paleoclimatology serves to coordinate paleoenvironmental data
generated
by US
agencies (NOAA, NSF, USGS, and USNPS), as well as data associated with the
activities
of the IGBP-PAGES (International Geosphere-Biosphere Programme, Past Global
Changes) Core Project and the IGBP-PAGES International Paleoclimate Modeling
Intercomparison Project (PMIP). In turn, PAGES and PMIP are focused on meeting
NOAA's goals of improving our ability to predict future climatic change. The
NOAA
Paleoclimatology Program contributes to the IPCC (Intergovernmental Panel on
Climate
Change) process via NOAA and IGBP PAGES channels.
Program Milestones:
Summer, 1994: Establish framework for international data exchange; Fall, 1994:
Distribute
free via Internet paleoclimatic data and PaleoVu browse and visualization software
tool;
Spring, 1995: Conduct PMIP past climate model intercomparison .
Policy Payoffs:
The NOAA Paleoclimatology Program contributes the long paleoclimatic time series
needed, as a baseline, to identify the extent to which recent climatic change is
driven by
human activity. The NOAA program also advances predictive skill by providing
critical
insights into the dynamics and causes of natural decade to century-scale climatic
variability,
as well as a validation framework for predictive models. This understanding of
long-term
climatic variability is critical to intelligent policy formulation.