OPERATION OF A DATA ACQUISITION CENTER FOR INTERNATIONAL
CLIMATE PREDICTION PROGRAMS
PROJECT GOALS AND METHODOLOGY:
We collect data from scientists from thirteen countries
who deploy high-quality drifting buoys throughout the world.
This data is then pooled and subjected to strict quality-
control to provide a uniform, global data set of SST and
surface velocity which is made available to the public. For
buoys deployed as part of the large U.S. program, we manage
the dissemination of the data over the Global
Telecommunications System, which provides operational weather
and climate prediction centers with real-time data. Finally,
we provide maps of the status of the global array each month
to help monitor and evaluate the array on an ongoing basis.
DATA COLLECTION AND ANALYSIS:
Since we began operation in 1990, we have collected data
from nearly 2500 buoys, including a small amount of
historical data from as early as 1979. This represents a
total of over 2200 buoy-years of data. We archive this data
at regular intervals with the Marine and Environmental Data
Service of Canada (MEDS), which is the agency responsible for
making the data available to the public. Information needed
to contact MEDS can be found at:
gopher://diu.cms.udel.edu:/00/woce_diu/data/dacs/drifters/dr
ifters_dac_staff.txt. We also have a DAC World Wide Web
homepage on which we put higher level products on a monthly
basis.
RESULTS AND ACCOMPLISHMENTS:
Many scientists and operational centers throughout the
world rely on the products of the Data Assembly Center (DAC)
at AOML to provide the high-quality SST and surface velocity
data that their research and predictions require. The
National Weather Service, for example, produces daily
analyses of global SST that serve as the basis for nearly all
realistic predictions and studies of short term climate
variability such as the El Nino phenomena. El Nino refers to
an ocean-atmosphere interaction that leads to anomalous and
stable weather changes for several seasons over much of the
world. Such research has made skillful El Nino predictions a
reality and now gives society a tool to help in planning
economic activities to help minimize the disruption that El
Nino causes.
Research intended to improve the models used for climate
prediction also benefit from the high-quality data that is
produced from our work. Surface velocity measurements have
been used to evaluate the fidelity of the ocean model
component of eight climate models in the tropical Pacific,
which is the source of El Nino, and found that some basic
processes are not well modeled by any formulation. This
points the way to improve the model physics and thereby
improve the climate predictions. These measurements are
also used to study a wide range of basic questions in
oceanography that help to provide constraints on the
performance of the models. Nearly 100 scientific papers, for
example, have been based in part on data processed by the
DAC.
FUTURE WORK:
The scope of the global drifter array continues to grow
as the potential for skillful climate predictions becomes
closer to reality. We expect to obtain data from over 900
buoys per year in 1995 and beyond. Recent technical
improvements in buoy design have made possible the
measurement of sea level pressure (SLP), which is of great
interest to those tasked with making both numerical weather
predictions and numerical climate predictions. Observations
of SLP in data sparse areas, such as the Southern Ocean and
South Pacific Ocean, can be of great benefit to numerical
weather prediction schemes. Improved weather predictions,
in turn, provide better estimates of surface wind stress on
the ocean. Lack of adequate knowledge of surface wind stress
over the global ocean has been a major factor hindering the
development of climate prediction schemes, so SLP
observations can be of great help here, as well. These
rising demands will provide us with commensurate challenges
to
meet the needs of the climate prediction community.
Drifter Data Figures
Mean sea surface temperature (SST) analysis
Drifter tracks in the Pacific Ocean from January
1979 through April 1994
Mean current
estimates in the North Atlantic Ocean, 1989-1994
Amount of data from the global
drifting buoy array as a function of time
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