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The North American Carbon Program
(NACP)
is designed to provide the scientific underpinning to inform future
policy decisions involving the carbon cycle, such as managing carbon
sources and sinks by efficient and effective options to reduce emission
or enhance carbon sinks (Wofsy and Harriss, 2002). Information from
earth observing satellites plays a major role in providing spatial
and temporal information required to address the carbon accounting
sought by the NACP. The programs hopes to capitalize on the information
gained from the current generation of satellite data. In particular,
MODIS is expected to play a major role in regional and global analysis
inherent to NACP.
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However, current NASA-funded NACP investigators are
experiencing significant challenges in their attempts to utilize MODIS data.
Our discussions of this issue with these investigators have led to a strong
interest in our approach that they feel with satisfy their needs. The
“one-size-fits-all” tools that have been developed in the past
do not address NACP investigators' particular needs. The tools provide a
fraction of the functionality needed and there remains significant
overhead involved with ingesting and processing MODIS data for a
particular use. The additional effort required to process the MODIS
products is often prohibitive. The result is that MODIS data are not
currently serving to their full potential within the NACP.
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Our strategy is to offer a
wide range of processing capabilities
to be applied to any of the MODIS land and atmosphere
products for a focus group of NACP investigators. This would involve
5-10 investigators in year one. During this first year we will develop
the capacity to provide these investigators with very specific products
that precisely match their needs. In year two we will expand the
number of users to ~30 while assessing which requests/tools are most
common among users. Year three would then develop an operational
capacity for the most requested and/or critical tools.
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In addition to the NACP concerns, atmospheric researchers
have also identified “gaps” in the data distribution process:
- parameter reprojection onto fixed grids as specified by the user
including day-to-day time series on such grids;
- custom products that combine satellite parameters and
simultaneous ancillary meteorological data such as wind fields;
- a menu of product and image formats that will allow common
projections of data acquired from various sources; and finally
- a mechanism for machine-to-machine ordering that makes most
web-based functionality available for scripted procedures.
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The research community requires that EOS platforms provide regional
time-dependent parameters as well as long-term global data for climate
studies. Regional analyses like NACP are connecting atmospheric
constituents (mainly greenhouse gases) with surface processes on the
land and ocean. MODIS data are key to providing detailed spatial and
temporal information about the surface condition and dynamics (Denning
et al., 2004) as well as refining physical models of diverse phenomena
such as aerosol/cloud interactions, radiative forcing and
aerosol/chemical transport (Chin et al., 2004). We are proposing to
address a major challenge for researchers, namely, acquiring EOS data
at suitable spatial-temporal resolutions and in formats consistent with
data integration into model studies |
