Science
for Society: Extending Earth Science Research
Results into Decision Support Tools
(Continued)
Benchmarking
Earth Model Predictions
For 40 years, NASA has been developing the capability
to use the perspective of space to provide global
observations of the key parameters of our Earth system.
NASA uses a systems approach to enable the measurements
to be explored rigorously and scientifically. The
NASA science community uses the measurements to advance
global and regional models and improve predictive
capability. Advanced computer technologies are used
to visualize the resulting global observations and
predictions to generate excitement about, and understanding
of, our home planet.
NASA has successfully developed and deployed the flagship
Earth Observation System (EOS). As of April 2003,
the US space agency has 18 Earth observation satellites
on orbit carrying 80 sensors. These remote sensing
satellites are observing the Earth’s atmosphere,
land surfaces, ice covers, ecosystems, gravity fields,
and surface deformations. About 3 terabytes of data
are collected daily and transmitted to Earth receiving
stations. These measurements are filtered, assimilated,
and digested into the Earth Observations System Data
Information System (EOSDIS) through intelligent data
assimilation and modeling processes. The resulting
calibrated and validated measurements of key parameters
of Earth processes are assimilated into Earth science
models that are responsible for producing predictions
– and related knowledge useful in decision support
systems. Since the Earth science research community
cannot perform large-scale experiments on our environment,
the Earth system model is the most optimal tool for
Earth system scientists to use to perform simulations
and produce “what if” scenarios of the
evolution of our environment.
Earth science models represent a consolidation of
scientific understanding of the range of physical
processes associated with the Earth system. It is
estimated that physical process field studies and
routine observations must be conducted for at least
10 years before a given physical process can be represented
in an integrated Earth science model. In a special
issue of the EOM journal (http://www.eomonline.com),
NASA presents articles on eight of the Earth science
models. These include a global and regional weather
prediction model, a near-term coupled atmosphere-ocean
model, a seasonal-to-interannual prediction model,
a long-term climate change model, a coastal biological-physical
oceanography model, a land surface hydrology model,
and a bio-geochemistry model. These models represent
years of Earth science modeling advancement and the
consolidation of scientific findings from many of
the Earth science disciplines. These state-of-the-science
research and operational models are used in many decision
support systems today.
NASA's High-End Atmospheric Model for Climate and
Weather Predictions describes an advanced high-end
atmospheric model designed to produce weather and
climate predictions is introduced. Although it is
still viewed as an experimental model, this has been
the highest resolution global weather and climate
model running routinely.
Seasonal Climate Prediction and Predicting Seasonal
to Interannual Climate Variations describe a class
of climate models designed to predict seasonal to
interannual climate variations. Since the seasonal
variation of the climate system depends heavily on
the ocean – which carries the memory of the
past and forces the future evolution of the climate
system – coupled models are used for this type
of prediction. These seasonal to interannual climate
models have been used to guide water management, energy
consumption prediction, and fishery production predictions.
Using Earth Science Tools to Improve Seasonal Climate
Prediction for Agriculture addresses spatial resolution
in global climate change research. The current climate
change models do not have sufficient spatial resolution
for regional assessments. Due to the lack of computational
resources, techniques have been developed to downscale
the global model outputs to a regional spatial scale.
The downscaled information can then be used in agriculture
decision-making.
In Using Regional Atmospheric Models for Commercial
Applications, a regional weather forecast model is
introduced. The model is used commercially and operationally
at many installations, including the Kennedy Space
Flight center.
Modeling the Coastal Ocean Processes Within the U.S.
Continental Margins, Incorporating the Land Data Assimilation
System into Water Resource Management and Decision
Support Systems, and Biospheric Monitoring and Ecological
Forecasting represent specific purpose models on coastal
ocean modeling and regional water monitoring to agriculture
production prediction. These NASA-supported models
are producing predictions for specialized purposes.
It is easy to see from the broad range of applications
that use Earth science model products that it will
be helpful to have an integrated framework for Earth
system modeling. The benefits of a common framework
are the driver for the next phase of the consolidation
of Earth system science research results. As stated
in the ESE
Research Strategy: “The ultimate challenge
of Earth System Science is to consolidate the scientific
findings in the different disciplines into an integrated
representation of the coupled atmosphere, ocean, ice,
land and biosphere system.” The integrated Earth
system model – currently consisting of coupled
atmosphere, ocean, and land components – is
used to contribute to science-based assessments of
potential future changes. In the next 10 years, additional
components will be added into the integrated Earth
system model. These components will include ice, biosphere,
solid earth, and chemistry transport models. NASA
has already started projects to build a national Earth
System Modeling Framework (ESMF). Through this modeling
framework, various Earth science models will be able
to communicate and exchange information inputs from
Earth observation systems and outputs to decision
support systems. The ESMF provides a unified external
interface to serve a range of applications for Earth
science model predictions. We are on a path towards
creating a comprehensive description of the whole
Earth model and an end-to-end system ranging from
satellite data acquisition, data analysis, and modeling,
all the way to the decision support systems.
Next Steps
As the Earth science community continues to increase
our understanding of Earth system processes, there
will be continued opportunities to assimilate observations
and predictions into decision support tools and thereby
increase the capacity to protect the home planet.
Your contributions in Earth science research and technology
development are greatly valued and appreciated as
the “stock-in-trade” to serve our society
through applications of national priority. Our world
needs the best available information and information
infrastructure to enable decisions on policy and management
of natural resources. To quote Dr. Jack Kaye, Director
of our Earth Science Research Division,
“Science allows it,
Technology enables it,
Society requires it,
And the time is now!”
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