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In this multi-center collaborative project,
researchers from the Center for Hybrid
Multicore Productivity Research (CHMPR)
at UMBC and the Center for Advanced
Knowledge Enablement (CAKE) at FIU
and FAU have developed the capability to
deliver a decade of 3-D gridded arrays of
animated visualizations of spectral IR satellite
radiance data from instruments on AQUA.
These animations render in 3-D the vertical
structure of a decade of global and regional
temperature trends occurring at the surface
and lower troposphere. In addition, the
gridding algorithm developed by CHMPR
has been applied to providing CAKE with
3-D temperature profiles that specify the
thermal structure around hurricanes in
Measuring the surface temperature of the
entire Earth on a daily basis is a difficult
challenge because 75% of the planet is
covered with oceans and ice. Continuously
determining, for several days to weeks, the
vertical thermal field around a hurricane
surrounded by dynamically rotating clouds
is needed for more accurate landfall
predictions. Thus, for applications ranging
from climate change to hurricanes, satellite
measure the Earth’s emitted infrared radiation
twice daily with sufficiently high spatial and
spectral resolution to provide an estimate of
vertical profiles of regional or global surface
brightness temperature (BT). However,
in order to assess global warming, these
temperatures need to be measured to within
an accuracy of 0.10 °C per year since models
indicate CO2 warming of ~20-30 over 100
years. Moreover, to resolve the structure
around hurricanes, infrared data at resolutions
of 1-5 km are needed. Not until 2002, when
the Aqua satellite was launched, has there
been a single satellite with instruments that
can meet both the accuracy and the spatial
resolution required.
This study is a collaboration between CAKE (FIU and FAUCenters) and the Center for Hybrid
Multicore Productivity Research at University of Maryland Baltimore County. The NSF
Compendium is available at: www.nsf.gov/eng/iip/iucrc/compendium/index.jsp
Distributed Cloud Computing: 3-D Visualization Services for
Climate Data on Demand
Borko Furht and Hari Kalva, PIs
l
Student: Reena Friedel