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subgrid scale, and improving their parameterizations. If parameterizations are good,
then the necessity to keep resolving smaller and smaller scales in one's numerical
model disappears.
Another class of problems is filling data holes and gaps. How can new tools
help us explore these holes and gaps between different kinds of observational data
collected at different scales, or between the hierarchies of numerical models that we
use to solve subsets of the problem that need to be merged to understand the relative
contribution or importance of the solutions to the subsets?
28.1.1 Systems of Systems
The challenges of multi-scale interactions in complex systems and processes has led
to new areas of research and refocusing of disciplines in engineering, as illustrated
by the evolution of industrial engineering to industrial and systems engineering, and
the development of the subarea of systems of systems research. Therefore, in order
for these multi-scale interactions to be investigated and explored, tools are needed
which scale to handle
systems of systems
[
2
]. These problems are common in science
and engineering, and may require analysis and combination of data across scales. For
example, macrobiology analysis may require understanding the interactions of data
simultaneously at the genome, protein, cell, organ, human, country, and ecosystem
levels. Cancer care treatment requires understanding and integrating data from the
biomarker level (e.g., integrating metabolics, lipidomics, genomics, and proteomics
data already at multiple scales) and cancer processes at the organ level, environmen-
tal exposure, and socioeconomic factors that affect the success and completion of
treatment regimens.
Weather and the environment provide further examples, such as clouds and pre-
cipitation. Clouds and precipitation affect our daily lives, personal safety, commer-
cial decisions, and our future sustainability on Earth. Clouds and precipitation are
important at all regional scales: local, state, national, and global. Clouds influence the
daily maximum and minimum temperatures over our homes and they modulate the
global temperature by affecting the amount of incoming solar radiation and outgoing
long wave radiation. Precipitation is likewise important at all scales. It directly affects
our quality of life: our food supply, drinking water supply, air purity, modes of trans-
portation, and many other human needs across the earth. As the inhabitants of earth
become increasingly concerned about global warming and climate change on global
and regional levels, it is necessary to understand the roles of clouds and precipitation
in the Earth's System in order to predict the future state of our planet. However, fun-
damental questions remain concerning cloud motions and evolution, cloud longevity,
and precipitation formation, and these gaps in our knowledge hamper our efforts to
understand and predict weather and climate. Understanding and predicting clouds
and precipitation are very difficult tasks which require the measurement and model-
ing of properties on a wide variety of scales (microscale, cloud scale, storm scale,
mesoscale, synoptic scale, global scale as shown in Fig.
28.1
), fusion of computa-
tional model data and measured data, and the simultaneous fusion of hundreds of
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