NASA Scientific and Technical Aerospace Reports

microphysical algorithms (visible, NIR, and SWIR spectral windows) are primarily affected by water vapor, and to a lesser
extent by well-mixed gases. For water vapor, the above-cloud column amount, or precipitable water, provides adequate
information for an atmospheric correction; details of the vertical vapor distribution are not typically necessary for the level
of correction required. Cloud-top pressure has a secondary effect due to pressure broadening influences. For well- mixed gases,
cloud-top pressure is also required for estimates of above-cloud abundances. We present a method for obtaining above-cloud
precipitable water over dark Ocean surfaces using the MODIS 0.94 pm vapor absorption band. The retrieval includes an
iterative procedure for establishing cloud-top temperature and pressure, and is useful for both single layer water and ice clouds.
Knowledge of cloud thermodynamic phase is fundamental in retrieving cloud optical and microphysical properties. However,
in cases of optically thin cirrus overlapping lower water clouds, the concept of a single unique phase is ill- defined and
depends, at least, on the spectral region of interest. We will present a method for multi-layer and multi-phase cloud detection
which uses above-cloud precipitable water retrievals along with several existing MODIS operational cloud products (cloud-top
pressure derived from a C02 slicing algorithm, IR and SWIR phase retrievals). Results are catagorized by whether the radiative
signature in the MODIS solar bands is primarily that of a water cloud with ice cloud contamination, or visa-versa. Examples
in polar and mid-latitude regions will be shown.
Author
Cloud Physics; Cirrus Clouds; Atmospheric Correction; Vertical Distribution
20040074250 NASA Goddard Space Flight Center, Greenbelt, MD, USA
Spatially Complete Surface Albedo Data Sets: Value-Added Products Derived from Terra MODIS Land Products
Moody, E. G.; King, M. D.; Platnick, S.; Schaaf, C. B.; Gao, F.; [2004]; 1 pp.; In English; AGU Fall 2003 Meeting, 8-12 Dec.
2003, San Francisco, CA, USA; No Copyright; Avail: Other Sources; Abstract Only
Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly
it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological
effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such
as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical,
oceanographic, and meteorological studies. The availability of global albedo data over a large range of spectral channels and
at high spatial resolution has dramatically improved with the launch of the Moderate Resolution Imaging Spectroradiometer
(MODIS) instrument aboard NASA s Earth Observing System (EOS) Terra spacecraft in December 1999. However, lack of
spatial and temporal coverage due to cloud and snow effects can preclude utilization of official products in production and
research studies. We report on a technique used to fill incomplete MOD43 albedo data sets with the intention of providing
complete value-added maps. The technique is influenced by the phenological concept that within a certain area, a pixel s
ecosystem class should exhibit similar growth cycle events over the same time period. The shape of an area s phenological
temporal curve can be imposed upon existing pixel-level data to fill missing temporal points. The methodology will be
reviewed by showcasing 2001 global and regional results of complete albedo and NDVl data sets.
Author
Spatial Resolution; Albedo; Data Acquisition; Snow; Climatology; Clouds (Meteorology)
20040074253 NASA Goddard Space Flight Center, Greenbelt, MD, USA
The CEOP Inter-Monsoon Studies (CIMS)
Lau, William K. M.; [2003]; 1 pp.; In English; AGU Fall 2003 Meeting, 8-12 Dec. 2003, San Francisco, CA, USA; No
Copyright; Avail: Other Sources; Abstract Only
Prediction of climate relies on models, and better model prediction depends on good model physics. Improving model
physics requires the maximal utilization of climate data of the past, present and future. CEOP provides the first example of
a comprehensive, integrated global and regional data set, consisting of globally gridded data, reference site in-situ
observations, model location time series (MOLTS), and integrated satellite data for a two-year period covering two complete
annual cycles of 2003-2004. The monsoon regions are the most important socio-economically in terms of devastation by floods
and droughts, and potential impacts from climate change md fluctuatinns nf the hydrologic cyc!e. Scientifically, it is most
challenging, because of complex interactions of atmosphere, land and oceans, local vs. remote forcings in contributing to
climate variability and change in the region. Given that many common features, and physical teleconnection exist among
different monsoon regions, an international research focus on monsoon must be coordinated and sustained. Current models of
the monsoon are grossly inadequate for regional predictions. For improvement, models must be confronted with relevant
observations, and model physic developers must be made to be aware of the wealth of information from existing climate data,
field measurements, and satellite data that can be used to improve models. Model transferability studles must be conducted.
CIMS is a major initiative under CEOP to engage the modeling and the observational communities to join in a coordinated
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