Poster Abstracts, 3/9/04

**[1) Using ABI to help HES for atmospheric sounding and cloud
retrieval]{.underline}**

*Jun Li^\*^, Timothy, J. Schmit^@^ , W. Paul Menzel^@^, and James
Gurka^\#^*

^@^NOAA/NESDIS, Office of Research and Applications

Madison, WI 53706, U.S.A.

\*Cooperative Institute for Meteorological Satellite Studies (CIMSS)

University of Wisconsin-Madison

Madison, WI 53706, U.S.A.

#NOAA/NESDIS, Silver Spring, Maryland

Abstract

The Advanced Baseline Imager (ABI) and the Hyperspectral Environmental
Suite (HES) on GOES-R and beyond will enable improved monitoring of the
distribution and evolution of atmospheric thermodynamics and clouds. The
HES will be able to provide hourly atmospheric soundings with spatial
resolution of 4 \~ 10 km with high accuracy using its high spectral
resolution measurements. However, presence of clouds affects the
sounding retrieval and needs to be dealt with properly. The ABI is able
to provide at high spatial resolution (0.5 \~ 2km) a cloud mask, surface
and cloud types, cloud phase mask etc, cloud top pressure (CTP), cloud
particle size (CPS), and cloud optical thickness (COT). The combined
ABI/HES system offers the opportunity for atmospheric and cloud products
improved over those possible from either system alone. The key steps for
synergistic use of ABI/HES radiance measurements are 1) collocation in
space and time, and 2) ABI cloud amount, type, and phase determination
within the HES sub-pixel. The Moderate-Resolution Imaging
Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS)
measurements from the Earth Observing System's (EOS) Aqua satellite
provide the opportunity to study the synergistic use of advanced imager
and sounder measurements. The combined MODIS and AIRS data for various
scenes are analyzed to study the utility of synergistic use of ABI
products and HES radiances for better retrieving atmospheric soundings
and cloud properties.

**[2) ABI cloud mask study using MODIS data]{.underline}**

*Rich Frey^\*^, Jun Li^\*^, Timothy, J. Schmit^@^*

\*Cooperative Institute for Meteorological Satellite Studies (CIMSS)

University of Wisconsin-Madison

Madison, WI 53706, U.S.A.

^@^NOAA/NESDIS, Office of Research and Applications

Madison, WI 53706, U.S.A.

Abstract

The Advanced Baseline Imager (ABI) cloud mask is a very important
product needed for use in generating the atmospheric soundings, cloud
parameters, clear-sky radiances, and surface properties from ABI
radiances. ABI cloud mask information collocated with Hyperspectral
Environmental Suite (HES) data not only enables cloud detection within a
given HES footprint, but also helps cloud-clearing processing using
ABI/HES data. The cloud mask algorithm is the operational
Moderate-Resolution Imaging Spectroradiometer (MODIS) algorithm
developed at the Space Science and Engineering Center (SSEC), which uses
several cloud detection tests to indicate the level of confidence that
clear skies are being observed. The algorithm has been adjusted to the
currently selected ABI spectral bands, and uses ABI spectral bands to
maximize reliable cloud detection and to mitigate past difficulties
experienced by sensors with coarser spatial resolution or fewer spectral
bands. The algorithm identifies several conceptual domains according to
surface type and solar illumination including land, water, snow/ice,
desert, and coast for both day and night. Once a pixel has been assigned
to a particular domain (defining an algorithm path), a series of
threshold tests attempt to detect the presence of clouds in the ABI
field-of-view (FOV). Each cloud detection test returns a level of
confidence that a pixel is clear, ranging in value from 0 (low) to 1
(high). The ABI cloud mask algorithm has been tested with MODIS data
from both day and night. The ABI and MODIS cloud masks are compared for
both similarities and differences due to spectral differences between
the two instruments.

[3) NASA Technology Applicable to GOES-R Onboard Compression, Error
Control Coding and Digital Modulation]{.underline} (3 posters)

Pen-Shu Yeh and Wai Fong

NASA/GSFC Code 567

Abstract

Advanced technology development in data compression, error control
coding and digital modulation conducted at NASA's Goddard Space Flight
Center is targeted towards future missions requiring high-speed data
throughput on a constrained bandwidth channel. Each development is
implemented on a high-speed radiation tolerant flight hardware platform.
In-depth analysis of algorithms is performed to ensure optimal
implementation and to achieve the highest performance. .

In the data compression area, a new tunable compression scheme
applicable to both push-broom and frame instrument has been developed
for imaging and higher-dimensional data. The algorithm has been selected
by the CCSDS with the release of the recommendation expected summer
2004. The algorithm allows a user to select fixed rate compression or
quality controlled compression from high compression ratio to lossless
mode. Flight integrated circuit specified at over 20 Msamples/sec is
under development.

To improve the efficiency of channel coding, new bandwidth efficient
error control coding scheme, specifically the Low Density Parity Check
(LDPC) code, has been developed to effectively double the bandwidth
utilization as compared to the concatenated Reed-Solomon and
Convolutional codes. The code does not exhibit any error floor with BER
down to 10^-10^, a requirement dictated by the need to transport
compressed data reliably. This LDPC code has been proposed to CCSDS as a
candidate for a new channel coding standard. Flight LDPC coders of block
length 8k and 4k bits has been designed to operate at over 1 Gbps.

To satisfy the spectral mask recommended by the Space Frequency
Coordination Group (SFCG) and improve bandwidth efficiency, CCSDS has
published a set of new digital modulation schemes including
Filtered-OQPSK, GMSK, 8PSK-TCM for future missions. The narrow spectrum
is achieved by filtering the channel symbol to produce side-band
suppression. A multi-function digital modulation integrated circuit is
being developed for space missions with a target rate of over 300 Mbps
(Filtered-8PSK). A testbed built on an FPGA implementation has
demonstrated 40 Msps throughput and verified spectral performance.

This presentation gives only a top-level description of the three
technology developments that are applicable to the GOES-R mission.
Details of each will be provided in the poster.

**[4) Study of the Hyperspectral Environmental Suite (HES) on the GOES-R
and beyond]{.underline}**

*Jun Li^\*^, Timothy, J. Schmit^@^ , Fang Wang^\*^, W. Paul Menzel^@^,
and James Gurka^\#^*

\*Cooperative Institute for Meteorological Satellite Studies (CIMSS)

University of Wisconsin-Madison

Madison, WI 53706, U.S.A.

^@^NOAA/NESDIS, Office of Research and Applications

Madison, WI 53706, U.S.A.

#NOAA/NESDIS, Suitland, Maryland

Abstract

High spectral resolution infrared radiances from the Hyperspectral
Environmental Suite (HES) on Geostationary Operational Environmental
Satellite (GOES-R and beyond) will allow for monitoring the evolution of
atmospheric profiles and clouds. The HES is currently slated to be
launched in 2013. HES, together with the Advanced Baseline Imager (ABI)
will operationally provide enhanced spatial, temporal and vertical
information for atmospheric soundings and clouds. Trade-off studies have
been done on the spectral coverage, spectral resolution, spatial
resolution, temporal resolution, band-to-band co-registration and
signal-to-noise ratio. HES data applications investigated include
sounding temperature/moisture retrievals, trace gas estimation, cloud
retrieval and surface property retrieval. The accuracy and vertical
resolution of atmospheric temperature, moisture and trace gas associated
with HES are investigated. These will be contrasted with capabilities
from current sensors.

## 5) Quantization Noise for GOES-R ABI Bands

*Donald W. Hillger\* and Timothy, J. Schmit^@^*

\* NOAA/NESDIS/ORA, Regional and Mesoscale Meteorology Team, Fort
Collins CO 80523

^@^ NOAA/NESDIS/ORA, Advanced Satellite Products Team, Madison WI 53706

Abstract

Certain specifications are set for the GOES-R Advanced Baseline Imager
(ABI). Two of those specifications are allowable instrument noise and
the instrument maximum scene temperature for each band. As a result of
those specs, other characteristics of the ABI data stream (GOES
Re-Broadcast or GRB) can be determined. One of those characteristics is
the bit-depth or number of bits used to represent the radiances measured
by the ABI. This in turn determines the quantization of the measured
radiances and the quantization "step" or the minimum change that can be
described in the digitized scale. The desire is that this quantization
step per count be much less than the actual radiance noise in order to
not put an artificial limit on the radiance noise of the ABI.
Calculations are made and results will be presented on the minimum
number of bits needed to capture the desired range of temperatures as
well as exceed the noise spec for each ABI band. Of course it may turn
out that the maximum number of bits needed for any band will be used for
all bands. For example, the current-GOES instruments have 10-bit for the
Imager and 13-bit for the Sounder.

Among the ABI bands, the 3.9 μm band is of primary interest because its
greater sensitivity to warm temperatures and the desire to capture very
hot scene temperatures for detection and characterization of hot spots
(e.g., forest and range fires). Thus this shortwave infrared (IR) band
has a specified instrument maximum scene temperature of 400 K, much
greater than the specified temperatures for the other ABI bands. Due to
the finer field-of-view size of the ABI (compared to the current GOES
imager), this hotter saturation temperature is needed. However, of the
IR bands, this band suffers the most from increasing noise (in
temperature units) at low scene temperatures, as a result of the basic
physics of the Plank equation for shorter wavelengths. Of course this
same shortwave band is also used for cloud characterization on the cold
temperature end. Temperature noise in this band is much greater at low
temperatures than that for the other ABI bands and can be an undesirable
feature of the increased instrument maximum scene temperature. In
particular, this band seems to require a 15-bit scale to meet ABI
specifications, but that would still result in a quantization noise per
count step of 2.1 K \@200 K. Thus, it appears that a higher-resolution
scale, or a 16-bit scale in this case, is more desirable, resulting in a
quantization noise per count step of 1 K \@200 K.

[6) Using GOES-R to help fulfill NOAA's Mission Goals]{.underline}

Timothy, J. Schmit^@^, W.P. Menzel^@^, James Gurka^\#^, Jun Li^\*^, Mat
Gunshor\*, Nan D. Walker\^

^@^NOAA/NESDIS, Office of Research and Applications, Madison, WI 53706,
U.S.A.

#NOAA/NESDIS, Office of Systems Development, Silver Spring, Maryland

\*Cooperative Institute for Meteorological Satellite Studies (CIMSS),
University of Wisconsin-Madison

Madison, WI 53706, U.S.A.

\^Coastal Studies Institute, Louisiana State University

# Abstract

The great amount of information from the GOES-R series will both offer a
continuation of current product and services, but also allow for
improved or new capabilities. These products, based on validated
requirements, will cover a wide range of phenomena. This includes
applications relating to: weather, ocean, coastal zones, land, hazards,
solar and space. The geostationary perspective offers a rapid refresh
rate and constant viewing angles. The Advanced Baseline Imager (ABI),
the Hyperspectral Environmental Suite (HES), the Geo Lightning Mapper
(GLM), the space and solar instrument suites (Solar Imaging Suite (SIS)
and the Space Environment In-Situ Suite (SEISS)) on GOES-R will enable
much improved monitoring compared to current capabilities. The ABI will
have 16 spectral bands, compared with five on the current GOES imagers.
The ABI will improve the spatial coverage from nominally 4 to 2 km for
the infrared bands, as well as almost a five-fold increase in the
coverage rate. The HES-IR will be able to provide higher spectral
resolution observations (on the order of 1 cm^-1^, compared to 20 cm^-1^
on today's broadband sounders) with spatial resolutions of between 4 and
10 km. The HES-CW will allow high spatial resolution measurements in the
visible/near infrared region. These measurements will be used for unique
observations of the land and coastal regions. The GLM will offer unique
lightning observations over the land and sea for both nowcasting and NWP
(Numerical Weather Prediction) applications. The solar and space
observations will mean improved observations needed for a host of
applications. Information from each component of the GOES-R system will
help meet NOAA's mission goals. What follows are the four main mission
goals and the primary GOES-R instruments that will help meet the goals:\
1. Protect, restore, and manage the use of coastal and ocean resources
through ecosystem-based management (HES, ABI);\
2. Understand climate variability and change to enhance society's
ability to plan and respond (ABI, HES, GLM, SIS, SEISS);\
3. Serve society's needs for weather and water information (ABI, HES,
GLM);\
4. Support the Nation's commerce with information for safe, efficient,
and environmentally sound transportation (GLM, ABI, HES, SIS, SEISS).

# [7) Calibration of the reflective channels of the ABI with a full-disk ratioing radiometer]{.underline}

# James C. Bremer & Joseph C. Criscione, Swales Aerospace

Abstract

The Advanced Baseline Imager (ABI) will fly on the GOES-R series of
geosynchronous weather satellites. These satellites will be three-axis
stabilized to maintain a constant orientation with respect to the Earth.
Each ABI will scan the Earth's surface, requiring approximately five
minutes to make a full-disk image that covers most of one hemisphere in
six solar reflective channels and ten thermal infrared (TIR) channels.
The ABI will be required to have an onboard apparatus to perform
full-aperture, end-to-end calibration on all of its channels. The TIR
channels will be calibrated by viewing a full-aperture blackbody.

The reflective channels, ranging in wavelength from 470 nm to 2.26 um,
may be calibrated by viewing sunlight that is attenuated to the level of
the full Earth albedo, either by diffuse reflection from a Lambertian
radiator or by transmission through a perforated screen. We propose an
alternative technique in which the ratio between the solar irradiance
and the full-disk irradiance is measured by a small ratioing radiometer
with spectral channels matched to those of the ABI. This value of the
full-disk irradiance is then compared to the value derived from a
full-disk image made simultaneously by the ABI. This technique works
best from geostationary orbit, where the viewing geometry remains
constant throughout the ABI's full-disk scan and where the full disk
subtends a relatively small solid angle, in comparison to low-Earth
orbit.

A small integrating sphere with two pinhole apertures can be placed on
the nadir-facing surface of a GOES satellite and equipped with baffles
and with spectral channels that are matched to the reflective channels
of the ABI. One pinhole can be equipped with a baffle that restricts its
field-of-view (FOV) to a circle approximately 18^o^ in diameter,
centered at nadir, allowing it to view the Earth's full disk
continuously throughout its daily cycle. The second, smaller pinhole can
be equipped with a baffle that restricts its FOV to about 1^o^ in the
East-West direction and +/-25^o^ in the North/South direction. In this
configuration, the full direct solar irradiance, integrated over the
smaller pinhole, will be added to the Earth's irradiance during an
interval of about two minutes once each night. If the cross-section of
the pinhole that views the Sun is approximately 100 times smaller that
that of the Earth-viewing pinhole, then the solar flux in the sphere
during this brief solar-viewing interval will approximate the flux due
to the full-disk at noontime.

Detectors in the integrating sphere with spectral channels matched to
those of the ABI can measure the ratio of the full-disk irradiance to
the direct solar irradiance, independent of the detector's gain, the
filter's transmittance, and the sphere's reflectivity. Intervals when
direct solar or lunar irradiance enters the Earth-viewing pinhole
aperture can be disregarded, and the irradiance of other planets and
stars is negligible. ABI channels 1, 2, and 3 operate at wavelengths of
470 nm, 640 nm, and 860 nm. The corresponding channels in the full-disk
radiometer can use silicon detectors and can operate at ambient
temperature, or slightly below it. ABI channels 4, 5, and 6 operate at
wavelengths of 1.38 um, 1.61 um, and 2.26 um. The detectors for the
corresponding channels in the full-disk radiometer will require some
cooling.

In addition to calibrating the ABI, this full-disk radiometer on a
GOES-R satellite can make stable, long-term measurements of the daily
and seasonal variations in the albedo. The ongoing series of GOES-R
satellites enables cross-calibration between GOES East and GOES West and
transfer from decommissioned satellites to new satellites: valuable
capabilities for climatic studies. This proposed instrument can be small
and light, has no moving parts, can be hard-mounted to the nadir-viewing
face of the spacecraft, requires minimal electrical power, and has a low
data rate. It can operate without interrupting the ABI's data taking
operations and without inserting any obstructions into the ABI's field
of regard.

**[8) ISCCP Data at NCDC: A \[Not So\] New Climate
Resource]{.underline}**

Kenneth Knapp and John Bates, NCDC/NOAA, Asheville, NC

Abstract

The International Satellite Cloud Climatology Project data is archived
at the National Climatic Data Center. The various ISCCP data levels --
subsampled satellite data (e.g., B), cloud products (e.g., C1), and
pixel-level cloud products (e.g., DX) -- provide global observations
every three hours from July 1983 to present. In particular, the B1 level
data is a high resolution dataset that has yet to be used for research.
ISCCP B1 data is made up of Geostationary observations from JMA's GMS
series, EUMETSAT's Meteosat series and the NOAA GOES series of
geostationary satellites. The fulldisk imagery -- subsampled to \~10km
-- includes visible and infrared observations, but also may include
water vapor (e.g., from Meteosat), the full suite of channels from
GOES-8 through 12, and most recently all 12 channels of Meteosat-8
(formerly, Meteosat Second Generation, MSG). Until recently, access to
B1 data was limited by a lack of documentation and software support.
However, recent efforts by NCDC now provide information on reading,
navigating and calibrating the B1 data. This allows climatological
research from the B1 data at high spatial and temporal resolutions.

[9) Advance Mesoscale Product Development for GOES-R Using Operational
and Experimental Satellite Observations]{.underline}

Mark DeMaria\*, Donald Hillger\*, James Purdom#, Raymond Zehr\*, Hiro
Gosden#, David Watson#, John Knaff#, Daniel Lindsey#, and Daniel Bikos#

\*NOAA/NESDIS/ORA, Fort Collins, CO 80523

#Cooperative Institute for Research in the Atmosphere, Fort Collins, CO
80523

Abstract

Although the scheduled launch of GOES-R is almost a decade away, advance
preparation is necessary now to maximize the useful lifetime of this new
series of satellites. The high time resolution of GOES-R makes it highly
desirable for mesoscale weather events such as severe storms and
tropical cyclones. Observations that are similar to subsets of what will
be available from GOES-R are being collected from operational and
experimental satellites for severe weather and tropical cyclone cases.
Observations include those from the current GOES, AVHRR, MODIS and AIRS.
The Advanced Baseline Imager (ABI) will have much higher spatial
resolution than the current GOES satellites, and the AVHRR and MODIS
data are being used to evaluate the utility of this higher resolution
capability. Another major advance on GOES-R will be the Hyperspectral
Environmental Suite (HES) that has the potential to provide atmospheric
temperature and moisture soundings with a much higher vertical
resolution than those currently available. Soundings from the AIRS
instrument have been obtained for several case studies of mesoscale
weather events, and being evaluated by comparison with in situ
observations. Examples of potential applications of the ABI and HES to
severe weather and tropical cyclone forecasting will be presented.

[10) Applications of Simulated GOES-R Observations for Advance Product
Development for Mesoscale Weather Forecasting]{.underline}

Louis Grasso\*, Manajit Sengupta\*, Dusanka Zupanski\*, Milija
Zupanski\*, John Dostalek\* and Mark DeMaria#

\*Cooperative Institute for Research in the Atmosphere, Fort Collins, CO
80523

#NOAA/NESDIS/ORA, Fort Collins, CO 80523

Abstract

In preparation for GOES-R, we are developing a method to simulate
satellite observations using a cloud-scale numerical simulation model
and radiative transfer models. In short, a numerical cloud model is used
to simulate mesoscale weather events, including severe storms and
tropical cyclones. A second model is used to calculate the brightness
temperatures of the clear and cloud sky scenes from the model
simulations. This procedure allows for advanced product development for
severe weather (precipitation estimation, updraft diagnosis products)
and tropical cyclones (intensity estimation). The development of
products in advance of the satellite launch extends the useful life of
the satellite system. Examples of this method for severe storm and
tropical cyclone case studies will be described.

This modeling framework is also being used to prepare for assimilation
of GOES-R observations. For this purpose, simulated observations are
generated by sub-sampling the model initial condition based upon
current-day observing system capabilities, which are then used as input
to a data assimilation system. The simulated observations can be
supplemented by additional data that will be available from GOES-R. The
potential impact of the GOES-R data on forecasts can be estimated by
comparing the forecasts with and without the supplemental simulated
observations to the original model prediction. The plans and model
framework for this study will be described.

## 11) Applications of ABI and HES on GOES-R for monitoring of ocean temperature and color 

Richard Legeckis, Christopher W. Brown, Timothy Mavor and Paul S. Chang

NOAA/NESDIS, Office of Research and Applications, Silver Spring, MD
20910 U.S.A

Abstract

The planned combination of the Advanced Baseline Imager (ABI) and the
Hyperspectral Environmental Suite (HES) Coastal Water Imager on GOES-R
will enable the hourly and daily estimation of co-located sea surface
temperatures (SST) and ocean color (surface chlorophyll). This will
allow monitoring of the variability of ocean fronts, surface currents,
eddies, as well as coastal and equatorial upwelling. The co-location of
the SST and color observations will provide the first multi-spectral
view of the ocean surface from a geostationary platform. Efforts will be
made to combine GOES-R data with observations from other geostationary
satellites, such as the Meteosat Second Generation (MSG-4), as well as
from polar satellites such as NPOESS. The blended polar and
geostationary products will increase the cloud-free coverage of the
Atlantic and the Pacific Oceans. This should improve our ability to
monitor El Nino and La Nina cycles as well as ocean areas that tend to
spawn hurricanes. Furthermore, to improve estimation of SST in
persistently cloudy ocean areas, GOES-R products will be merged with
all-weather microwave measurements that penetrate cloud cover and
provide estimates of SST. To achieve this blended SST capability, the US
National Ocean Partnership Program (NOPP) is sponsoring the Global Ocean
Data Assimilation Experiment (GODAE). Due to the increased complexity of
products, it will be a challenge to provide an image product
architecture which allows for flexible product generation to meet the
needs of different users. A product system should provide a feedback
loop so GOES-R products can be modified in near real time to meet
evolving environmental or satellite instrument system conditions. In
effect, the satellite product producers and the product users have to be
part of an integrated, flexible system that is capable of responding to
change. The poster provides examples of the present GOES and MSG SST
products and SeaWiFS ocean color observations. Animations of large
quantities of satellite images, displayed at different spatial and
temporal scales, allow rapid evaluation and application of the present
satellite observations of the oceans.

12\) [Using GOES-R to Help Monitor SO~2~]{.underline}

Anthony J. Schreiner^\*^, Timothy, J. Schmit^@^ , Jun Li^\*^, Gary P.
Ellrod^\#^, Mat Gunshor^\*^, and Kris Karnauskas\*

\*Cooperative Institute for Meteorological Satellite Studies (CIMSS),
University of Wisconsin-Madison

Madison, WI 53706, U.S.A.

^@^NOAA/NESDIS, Office of Research and Applications, Madison, WI 53706,
U.S.A.

#NOAA/NESDIS, Office of Research and Applications, Camp Springs,
Maryland

# *Abstract*

Sulfur Dioxide (SO~2~) is often associated with volcanic eruptions. This
is important for aviation interests. Given the correct spectral
coverages, satellites can monitor the location and changes of volcanic
ash plumes. Geostationary satellites offer a rapid refresh rate and
constant viewing angle. The Advanced Baseline Imager (ABI) and the
Hyperspectral Environmental Suite (HES) on GOES-R will enable a much
improved monitoring of the upper-level SO~2~ distribution and evolution
from the geostationary perspective. The ABI will have 16 spectral bands,
compared with five on the current GOES Imagers. Most importantly for
SO~2~ detection, there will be spectral bands at 8.5 and at 7.34 μm. The
ABI will improve the spatial coverage from nominally 4 to 2 km for the
infrared bands, as well as almost a five-fold increase in the coverage
rate. The HES will be able to provide higher spectral resolution
observations (on the order of 1 cm^-1^, compared to 20 cm^-1^ on today's
broadband sounders) with spatial resolutions of between 4 and 10 km.
More importantly, the high spectral resolution observations will offer a
more detailed view for better monitoring the end of the life cycle of
thinner volcanic dust clouds. This will be demonstrated with data from
the NASA AIRS instrument and these high spectral resolution observation
convolved with mock ABI spectral response functions to simulate what
will be possible spectrally from the ABI. To date, it has not been
decided which side of the water vapor continuum that the HES will
observe. Of course, the longwave side would be needed for optimum SO~2~
monitoring in the 7.3 μm absorption region.

13\) [Realistic Performance Expectations for the Natural Color Rendering
Capabilities of GOES-R]{.underline}

Steven D. Miller^1^, Chris Schmidt^2^, and Tim Schmit^3^

^1^Naval Research Laboratory, Marine Meteorology Division, Monterey, CA
93943

^2^Cooperative Institute for Meteorological Satellite Studies,
University of Wisconsin-Madison Space Science and Engineering Center,
Madison, WI

^3^National Oceanographic and Atmospheric Administration, National
Environmental Satellite, Data, and Information Service-Office of
Research and Applications, Madison, WI

Abstract:

Operational applications involving satellite imagery interpretation
benefit greatly from the ability to present information from a complex
scene in a reference frame inherently familiar to the human
analyst---natural (or "true") color. A prime example of this benefit was
demonstrated recently during Operation Iraqi Freedom, when natural color
high resolution imagery products created in near real-time from the
Moderate Resolution Imaging Spectroradiometers (MODIS) aboard the
National Aeronautics and Space Administration (NASA) Earth Observing
System (EOS) Terra and Aqua satellites over southwest Asia were in such
high demand that the Commander, Naval Meteorology and Oceanography
Command (CNMOC) funded the installation of X-band receiving stations at
Navy Regional Centers in Bahrain (Arabian Gulf) and Rota (Spain) to
support operational requirements for real-time imagery. The 250 m
spatial resolution natural color imagery brought a paradigm shift to
feature interpretation capability and, by extension, the operational
utility of these data to the war fighter. Navy Aerographer's Mates (AGs)
used the information to track weather across the southwest Asia theater
of operations for the purposes of tactical decision making, including
strike/reconnaissance mission planning, ship and aircraft routing, and
weapons/sensor selection.

The wealth of additional information provided by natural color as
compared to standard 8-bit grayscale imagery (where only a small
fraction of these shades are optically differentiable by the human eye)
or false color composites (where additional training is often required)
bolsters the interpretive ability of even the most trained satellite
imagery analysts. The omission of the 0.555-micrometer (green) band upon
the GOES-R series limits the ability to produce geostationary versions
of the same high quality natural color depictions as those demonstrated
currently upon low-earth-orbiting platform radiometers (including MODIS,
Sea View Wide field-of--view Sensor (SeaWiFS), Ocean Color Mapper (OCM),
Feng Yun 1D, and the Medium Resolution Imaging Spectrometer (MERIS,
aboard Envisat)) and what will be available during a timeframe
contemporary to GOES-R upon the National Polar Orbiting Environmental
Satellite System (NPOESS) constellation.

Any attempts to reproduce natural color from GOES-R must therefore
resort to numerical approximations for synthesizing the missing green
channel. The complex spectral behavior of earth scenes in the visible
band precludes simple linear techniques for the approximation of 0.555
micrometer by available nearby narrowband red, blue, and near infrared
channels. So, instead statistical look-up-tables (LUTs) representative
of the full dynamic range of observations for a given region over time
are required. Using MODIS as a model for GOES-R, this paper demonstrates
various approximation techniques (including the application of general
LUTs, zone-dependent LUTs, and simple channel averages) and quantifies
the performance/limitations of each with respect to unapproximated
natural color results. The pre-computed LUTs have been applied to
independent datasets as a realistic determination of expected synthetic
natural color product performance. Preliminary findings indicate the
most significant departures occur for shallow and/or
suspended-particle-laden waters found most commonly in littoral zones,
islands, and atolls---areas where the GOES-R Hyperspectral Environmental
Suite's (HES) Coastal Imager will provide a compensatory role in regions
scanned by the HES-CW.

14\) **[Use of High Spectral Resolution Infrared Observations by
Ground-based, Aircraft, and Satellite Instruments to Simulate HES
Radiances over a Land Site]{.underline}**

*Robert O. Knuteson, Henry E. Revercomb, and David C. Tobin*

Cooperative Institute for Meteorological Satellite Studies (CIMSS)

University of Wisconsin-Madison

Madison, WI 53706, U.S.A.

Abstract

The Hyperspectral Environmental Suite (HES) on GOES-R and beyond will
enable improved monitoring of the temporal evolution of land surface
temperature and infrared surface emissivity. The HES is expected to
provide hourly top of atmosphere radiance observations with a spatial
resolution of better than 10 km and a spectral resolving power of
greater than 1000. The University of Wisconsin is using existing
observations from ground-based, aircraft, and satellite platforms to
develop a simulation of the outgoing surface radiation of a land site in
North Central Oklahoma. The Department of Energy Atmospheric Radiation
Measurement Program Southern Great Plains (DOE ARM SGP) site is being
used because of the extensive network of atmospheric profiling
measurements routinely collected at that site. High spectral resolution
infrared observations from the ground-based UW Atmospheric Emitted
Radiance Interferometer (AERI) have been made of the time rate of change
of surface emitted thermal radiance at this site but only for select
land cover types. Similar aircraft observations have been made of the
DOE ARM SGP site by the UW Scanning High-resolution Interferometer
Sounder (S-HIS) at a spatial resolution of about 2 kilometers from a
high altitude aircraft platform. Likewise, the recently launched EOS
Aqua platform with the Atmospheric InfraRed Sounder (AIRS) instrument
has been used to obtain high spectral resolution satellite observations
at a spatial resolution of about 15 km. The combination of these
instruments with the 1 km observations of the Moderate-Resolution
Imaging Spectroradiometer (MODIS) and the infrared channels of the
current GOES instrument are being used to simulate what would be
observed by a future geostationary infrared spectrometer. These
simulations will be used to develop algorithms for the generation of
effective land surface emissivity and effective land surface temperature
products derived from the geostationary observations anticipated in the
GOES-R time frame.

15\) **[GOES R and the Global Carbon and Water Cycle]{.underline}**

Forrest G. Hall^1^, Robert Knox^2^, Elizabeth Middleton^2^, Karl F.
Hummerich^1^, Alexei Lyapustin^1^ and Jan Gervin^2^

^1^ Joint Center for Earth Systems Technology GSFC/UMBC

^2^ Goddard Space Flight Center

Abstract

Land vegetation affects weather, weather affects vegetation, and by
monitoring land vegetation with the HESS instrument planned for GOES R,
we can improve weather forecasts as well as our understanding of
linkages between climate and the global carbon cycle.

The global carbon and water cycle are intimately linked through land
vegetation physiological processes. Land surface vegetation exerts
strict controls on land-atmosphere exchanges of carbon, water and energy
as result of biological processes evolved to optimize the plant's
allocation of light, nutrients and water for survival. The
land-atmosphere mass and energy balance is in turn intimately linked to
meteorological processes influencing resource availability, including
precipitation rates and boundary layer structure, to name two examples,
which in turn feedback strongly to plant photosynthetic rates,
respiration and in the longer term, through vegetation succession, the
structure of the landscape.

The importance of these land surface-atmosphere processes to atmospheric
dynamics are recognized, and are represented in atmospheric general
circulation and global carbon cycling models by a general class of
models called Surface-Vegetation-Atmosphere Transfer (SVAT) models.
SVATs attempt to represent vegetation physiology and soil hydrology
using different schemes, all generally requiring knowledge of
instantaneous downwelling Photosynthetically Active Radiation (PAR), the
capacity of the vegetated surface to absorb PAR (Fpar) and finally the
rate at which the vegetation converts the absorbed photons to carbon,
the plant light use efficiency (LUE). Together, these process rates are
linked physiologically to evapotranspiration. Through these processes
the mass and energy budget over vegetated surfaces is controlled
primarily by just these three variables.

Tower eddy-correlation measurements in a large number of ecosystems show
that the mass-energy budget of a vegetated surface is quite variable on
a diurnal scale since these three controlling variables can vary
considerably over time scales of just seconds. Over the past 20 to 30
years, a number of satellite methodologies have been developed to
measure PAR and Fpar globally. However LUE has been traditionally
modeled as a function of vegetation type, soil moisture, nutrient
availability, air temperature and humidity to which plant LUE responds.
The physiological processes related to LUE are not always completely
represented in the models, and in any case, the input variables are
quite difficult to measure at the large geographic scales required for
general circulation and carbon cycling models. In just the last 10
years, a growing body of literature has recognized that variations in
LUE induced by environmental stress, is manifest by changes in leaf
pigments and in leaf and canopy optical properties. These changes can be
measured remotely using multispectral sensors that can measure changes
in plant reflectance at 531 nm, and 570 nm. The HES GOES R is planned to
include both a 531 and 570 nm band, hence is suitable for monitoring
changes in plant LUE, thus changes in the surface energy and mass budget
induced by plant stress, and ultimately the effects of feedbacks between
the atmospheric boundary layer and vegetation on weather. These
measurements should significantly improve weather forecast accuracies as
well as our understanding of the links between carbon and climate. This
poster presents a brief history of these developments, as well as recent
advances in algorithms for using narrow-waveband spectrometers for
measuring surface-atmosphere carbon dioxide exchange over vegetated
surfaces.

16\) **[Applications of the HES Coastal Water Imager]{.underline}**

Christopher W. Brown^\*^, Michael Ondrusek^\*^ and Richard P. Stumpf^@^

\* NOAA/NESDIS, Office of Research and Applications

^@^ NOAA/NOS, National Centers for Coastal Ocean Science

Abstract

> The Coastal Water Imager (CWI) is a proposed component of the
> Hyperspectral Environmental Suite (HES) that would be flown on the
> Geostationary Operational Environmental Satellite R Series (GOES-R) to
> acquire multispectral to hyperspectral visible - near infrared images
> of the Earth's surface at high spatial (150 - 300 meters) and temporal
> (every three hours or better) resolution. Its data would fill an
> existing gap in the time-space domain of available observations
> obtained from existing space-borne sensors. In its survey mode, CWI
> will improve our ability to monitor the coastal ocean (out to the
> Exclusive Economic Zone) of the US east coast from Texas to Maine by
> providing observations of this region at least three times a day.
> Cloud filtering, through compositing of these multiple images, will
> also increase the amount of surface area exposed on a daily basis. In
> its localized mode, the repeated collection of CWI data from a
> selectable region (ca. 400 km x 400 km) at high frequencies will
> permit short-term processes and events of the ocean, land, and
> atmosphere to be detected, monitored, and quantified. These
> observations will enable the investigation of the dynamic coastal
> ocean and the study and tracking of ephemeral events in the
> terrestrial and atmospheric environments, including storm development,
> volcanic ash plumes, and pollutants. The poster will describe a few of
> the many applications of the CWI.

17\) **[Volcanic Ash Detection Capabilities from GOES-R Based on
Experiments Using NASA Moderate Resolution Imaging Spectroradiometer
(MODIS) Data]{.underline}**

Gary P. Ellrod ^1^, Jung-Sun Im ^2^

^1^ Office of Research and Applications (NOAA/NESDIS), Camp Springs,
Maryland

^2^ IM Systems Group, Camp Springs, Maryland

Abstract:

The advanced GOES-R satellite (scheduled for launch in 2012) will have
greatly improved capabilities, such as a sixteen channel Imager, better
geographic coverage, faster imaging rates (full disk every 15 minutes),
and higher resolution (0.5 km visible, 2.0 km Infrared (IR)). The
proposed suite of IR channels on the GOES-R Imager features a number of
spectral bands that have been shown to be useful for volcanic ash
detection based on prior research. While some of the proposed IR bands
have been available on prior GOES (3.9, 10.7 and 12.0 um for example),
there are several new bands proposed (such as those centered near 7.3,
8.6, and 9.7 um), with which users have had little prior experience.
Also, the 12.0 um band will be restored, following an absence of nearly
ten years (beginning with GOES-12 in 2003). Recent experiments have been
conducted using data from NASA's Moderate Resolution Imaging
Spectroradiometer (MODIS) instruments on Aqua and Terra spacecraft,
which have 1 km resolution IR channels similar to those proposed for
GOES-R. Using data sets for several recent volcanic eruptions, optimum
detection was obtained from a three-channel combination of Band 29 (8.5
um), Band 31 (11.0 um) and Band 32 (12.0 um). Since Band 29 is affected
by absorption from airborne sulfur dioxide and sulfates, in addition to
volcanic ash, its use improves the likelihood of observing airborne
volcanic clouds. Comparisons with current GOES products show significant
improvements. Color composite versions of this product have also been
developed which incorporate visible (0.6 um) and near-IR (1.6 um) bands
to assist users in interpretation. Test images of this three-band
algorithm are being generated using near real-time MODIS data by the
NESDIS Interactive Processing Branch for evaluation by the Washington
Volcanic Ash Advisory Center (VAAC) for selected regions under their
responsibility. The Hemispheric coverage and rapid updates of this type
of image product from GOES-R should result in significantly better
monitoring of active volcanoes by the next decade.

18\) **[Number range CHAPTERProjected Impacts of ABI Data on
Satellite-Based Precipitation Estimation Part I: Enhanced Temporal
Resolution]{.underline}**

Robert J. Kuligowski

NOAA/NESDIS Office of Research and Applications, Camp Springs, MD

The Advanced Baseline Imager (ABI) on the GOES-R series of satellites
will provide much more frequent imagery than is available from the
present generation of GOES\--every 5 minutes over the CONUS as compared
to every 15 minutes at present. Given the rapid life cycle of convective
precipitation, the capability to estimate precipitation from satellite
data would be enhanced by the improvement in temporal resolution. This
is demonstrated using 5-minute GOES-11 data obtained when the satellite
was active in support of the International H~2~O Project (IHOP) during
the summer of 2002.

19\) **[Projected Impacts of ABI Data on Satellite-Based Precipitation
Estimation Part II: Additional Spectral Information]{.underline}**

Robert J. Kuligowski

NOAA/NESDIS Office of Research and Applications, Camp Springs, MD

Abstract:

In the GOES-R era, the number of available Imager channels is planned to
increase from 5 on the current-generation Imager to 16 on the Advanced
Baseline Imager (ABI). Many of these channels contain information
pertinent to cloud and precipitation processes because of their
sensitivity to cloud-top particle phase and size. In this work, MODIS
data are used as a proxy for selected ABI channels to demonstrate their
potential impact on precipitation estimates. This impact is particularly
notable in discriminating non-raining cirrus clouds from raining cumulus
clouds and thus reducing the overestimation of precipitation that
frequently occurs with satellite-based techniques.

# 20) [Outgoing Longwave Radiation Products from GOES-R as part of the Global Observing System]{.underline}

Hai-Tien Lee^(1)^, Arnold Gruber^(2)^ and Robert G. Ellingson^(3)^

^(1)^ University of Maryland, Cooperative Institute for Climate Studies
(CICS), Earth System Science Interdisciplinary Center (ESSIC), Computer
and Space Sciences Building, Room 4115B, College Park, Maryland 20742.
Email: LEE@ESSIC.UMD.EDU.

^(2)^ NOAA/NESDIS, Cooperative Institute for Climate Studies, Earth
System Science Interdisciplinary Center, 2207 Computer and Space
Sciences Building, Room 4115D, College Park, Maryland 20742

^(3)^ Florida State University, Department of Meteorology, Tallahassee,
Florida 32306

Abstract:

The outgoing longwave radiation (OLR) at the top of the atmosphere is a
very important radiation parameter for earth's radiation budget study as
well for weather/climate model validation purposes. Accurate OLR
measurement can lead to improvement of numerical weather and climate
prediction and thus enhance our understanding of the weather and climate
system. NOAA has been producing OLR estimates operationally using
narrowband radiance observations from the Advanced Very High Resolution
Radiometer (AVHRR) onboard the Polar Orbiting Environmental Satellites
(POES) since late 1970's and has added another operational OLR product
using High-resolution Infrared Sounder (HIRS) data since 1998. The AVHRR
OLR product has been used in many climate monitoring and assessment
purposes. NASA conducted earth radiation budget studies with the Earth
Radiation Budget Experiment (ERBE) and the Cloud and Earth's Radiant
Energy System (CERES) experiments onboard various satellites, primarily
polar orbiters. Recognizing that the combination of limited temporal
sampling by polar orbiters and diurnal variation can cause large
interpolation errors, analysis methods that employ geostationary
satellite observations were developed for CERES and HIRS OLR. Past
studies have found that the use of geostationary observations can reduce
the ERBE-like mean instantaneous interpolation rms errors by 50%. The
Geostationary Earth Radiation Budget (GERB) experiment onboard EUMESAT's
Meteosat Second Generation (MSG) satellites measures the short- and
long- wave radiation from the Earth every 15 minutes and it will provide
strong synergy with OLR estimated from polar orbiters in addressing the
diurnal variation issues. Similarly, we propose to use GOES-R's Advanced
Baseline Imager (ABI) to provide high temporal sampling of OLR that is
compatible with ERBE/CERES to reduce the interpolation errors in the OLR
estimates made with polar orbiters. Past efforts at CICS have
successfully adapted the HIRS OLR algorithm to the GOES Imager and
Sounder instruments. Currently, the GOES Imager OLR is operationally
produced under the full disk GOES Surface and Insolation Project (GSIP)
(A. Heidinger, personal communication). We will use the GOES Imager OLR
from GOES 10 and 12 to demonstrate the values and benefits of this
proposed product, particularly as to how it supplements the global
observing system.

21\) [Simulation of the spectral bands on the Advanced Baseline Imager
(ABI)]{.underline}

Mathew M. Gunshor\*, Timothy, J. Schmit^@^, Kristopher B. Karnauskas\*

\*Cooperative Institute for Meteorological Satellite Studies (CIMSS),
University of Wisconsin-Madison

Madison, WI 53706, U.S.A.

^@^NOAA/NESDIS, Office of Research and Applications, Madison, WI 53706,
U.S.A.

# Abstract 

The Advanced Baseline Imager (ABI) expands the capabilities for short
time interval multispectral observations on the next generation
Geostationary Operational Environmental Satellites (GOES) --R platform.
This instrument will be used for a wide range of applications including
weather, oceanography, numerical weather prediction, climate, natural
hazards and hydrology. The ABI will have 16 total spectral bands; three
in the visible, three in the near infrared and 10 in the infrared
spectral regions, compared with five total bands on the current GOES
imagers. These additional bands will enable improved and new products.
The ABI will also improve the spatial resolution from nominally 4 to 2
km at nadir view for the infrared bands and increase the temporal
coverage rate five-fold. Mock spectral response functions have been
created for all bands and are available for other interested parties.
Studies are underway in preparation for GOES-R using forward model
calculations in both real and simulated atmospheres with weighting
functions created to compare to similar bands on other instruments such
as the current GOES Imagers. Simulated images of ABI bands are created
daily from direct broadcast AIRS and MODIS data received at the
University of Wisconsin-Madison. These are posted in near real-time to
the World Wide Web. Simulations of ABI spectral and spatial advances are
presented using data from aircraft (AVIRIS) and research satellites
(AIRS, and MODIS).

22\) **[Operational Air Quality Monitoring from GOES
Imager]{.underline}**

S. Kondragunta, A. I. Prados, and I. Laszlo

NOAA/NESDIS Center for Satellite Applications and Research

Abstract:

We conducted a pilot study to demonstrate the usefulness of GOES Aerosol
and Smoke Product (GASP) in operational air quality monitoring.
NOAA/NESDIS has been retrieving near real-time column aerosol optical
depths in the visible channel from GOES for the past three years
(<http://orbit-net.nesdis.noaa.gov/crad3/gasp/RealTime.html>). We
focused on three different scenarios under which air quality can
deteriorate - dust storms, forest fires, and urban/industrial pollution.
We reprocessed GASP retrievals with the best calibration available for
pollution episodes of June 2001 (dust storm), forest fires (July 2002),
and urban pollution (June 2003). Positive correlations between GASP and
particulate pollution measured near the surface (PM2.5, particulate mass
of particles \< 2.5 microns in median diameter) suggest that GOES
aerosol retrievals can be used to monitor and track pollution transport.
Despite their ability to detect pollution, GASP retrievals have an
offset when compared to Moderate Resolution Imaging Spectroradiometer
(MODIS) aerosol optical depths and the offset is different for GOES-8
and GOES-12. Based on our analysis of the three episodes, we find that
the major limitations of the current GOES imager are uncertainties in
estimates of surface reflectance, calibration, and aerosol model
assumptions. We will provide an analysis of the spatial and temporal
features present in the GASP retrievals, comparisons to ground-based and
MODIS observations, an assessment of the retrieval algorithm
performance, a discussion on planned improvements to the current
algorithm, and a discussion on further improvements possible with the
GOES-R Advanced Baseline Imager (ABI).

**[23) Near-Real Time Cloud and Radiation Products from GOES-R
ABI]{.underline}**

*Patrick Minnis, L. Nguyen, D. F. Young, W. L. Smith, Jr.*

Atmospheric Sciences, NASA Langley Research Center, Hampton, VA 23692
USA

Abstract

The Advanced Baseline Imager (ABI) on GOES-R will provide data that will
greatly enhance the retrieval of cloud properties and the estimation of
radiative fluxes within the atmosphere and at the surface. These
products have a variety of applications. A suite of algorithms,
currently applied to 30-min GOES-9/10/12 data for the Atmospheric
Radiation Measurement (ARM) and the NASA Advanced Satellite Aviation
Products (ASAP) programs and to continuous Moderate-Resolution Imaging
Spectroradiometer (MODIS) data for the Clouds and Earth's Radiant Energy
System (CERES) Project, will be adapted to match the ABI spectral bands
for application to 15-min GOES-R data. The algorithms first identify
each pixel as cloudy or clear. Surface skin temperature and albedo are
retrieved for each clear pixel. Cloud-top and base heights and
temperature are estimated for each pixel along with the cloud phase,
effective particle size, and liquid or ice water path. Groups of clear
and cloudy pixels are then combined at a prescribed scale (20- 50 km)
and used compute the surface and top-of-atmosphere radiation budget for
the clear and cloudy parts of the group with input from the cloud
retrievals and numerical weather analyses/forecasts. The products are
currently being used to diagnose aircraft icing conditions, validate
mesoscale and general circulation model predictions of clouds and
radiative fluxes, and develop climatological statistics over selected
parts of the globe. A variety of other applications are envisioned for
the future including solar energy, agriculture, weather forecasting, and
contrail diagnosis for flight rerouting. The current methodologies are
limited by the resolution and spectral suite on the current GOES
imagers. The availability of additional solar and infrared channels as
well as enhanced spatial resolution will permit better cloud, phase, and
height determination plus improved detection of multilayered clouds.
Channels similar to those on the ABI are being used by CERES and are
being tested in a geostationary mode using the 3-km resolution Spinning
Enhanced Visible and Infrared Imager (SEVIRI) on Meteosat-8. Examples of
the near real time products from the various satellites and the
improvements that can be accomplished with GOES-R are presented.

24\) **[The Imager-Sounder Paradigm Revisited]{.underline}**

Joe Criscione, Jim Bremer, Don Chu

Swales Aerospace

Abstract:

The possibility of having two GOES satellites over each coast was
originally proposed for scheduling flexibility, but it also affords the
opportunity to redefine the instruments. The traditional imager/sounder
partitioning of requirements could be replaced with a
full-disk/region-of-interest partitioning with extraordinary benefit to
the coastal waters imaging and the severe weather/mesoscale sounding
observations. These gains are possible because the region-of-interest
instrument could be flown on its own spacecraft and that instrument
would not require a scan mechanism. Eliminating the scan mechanism
enables a doubling of the instrument aperture at a reduction in
cost/complexity with order of magnitude improvements in performance.
This proposed instrument architecture coupled with the distributed
architecture would better exploit the benefits of geostationary orbit
with some impact to the full-disk sounding requirements.

25\) **[Atmospheric Motion Vectors from the Current GOES-I/M Series with
an Eye on Opportunities with the Future GOES-R/U Series]{.underline}**

Jaime M. Daniels^@^, Wayne Bresky^+^, Chris Velden^\*^, and Antonio
Irving#

^@^NOAA/NESDIS Office of Research and Applications, NOAA Science Center

Camp Springs, Maryland 20746, U.S.A.

^+^Raytheon Information Technology and Scientific Services, Lanham,
Maryland 20706

^\*^Cooperative Institute for Meteorological Satellite Studies (CIMSS),
University of Wisconsin-Madison

Madison, Wisconsin 53706, U.S.A.

^\#^NOAA/NESDIS Office of Satellite Data Processing and Distribution,
NOAA Science Center

Camp Springs, Maryland 20746, U.S.A.

Abstract

Atmospheric motion vectors (AMVs), derived from the current GOES-I/M
series of satellites, continue to provide invaluable wind information to
the meteorological community. AMVs obtained from tracking features
(i.e., clouds and moisture gradients) are used for: i) Improving
numerical weather prediction (NWP) analyses and forecasts; ii)
Supporting short term forecasting activities at National Weather Service
(NWS) field offices; and iii) Generating tropical and mesoscale wind
analyses.

The future Advanced Baseline Imager (ABI) planned for the GOES-R/U
series of satellites offers exciting new capabilities which should
directly benefit and improve the derivation and quality of the AMVs.
These new capabilities include: continuous scanning with no loss of
imagery due to eclipse or conflicting scanning schedules, higher
resolution (spatial and temporal) imagery, and improved navigation. The
future Hyperspectral Environmental Suite (HES) planned for the GOES-R/U
series will offer increased spectral resolution which will enable
increased vertical resolution of the derived AMVs.

Today, areas of active AMV research include the generation, validation,
and impact assessment of rapid scan winds derived from high temporal
frequency imagery, error characterization and improvement of tracer
height assignment, and improved utilization of AMVs in NWP systems. This
research will lay the scientific foundation so that the anticipated
improvements in AMVs in the GOES-R era can be realized. This poster will
highlight many of these active AMV research topics.

26\) **[Cloud and Aerosol Properties using High Spectral Resolution
Infrared Measurements]{.underline}**

Steve Ackerman

Cooperative Institute for Meteorological Satellite Studies (CIMSS),
University of Wisconsin-Madison

Madison, WI 53706, U.S.A

Abstract:

High spectral resolution infrared measurements provide increased

capabilities over imaging radiometers for detecting clouds and aerosols

and for characterizing their optical properties. A variet of research

groups has been developing algorithms for detecting clouds and aerosols

using high-spectral resolution infrared measurements. The goal has been

to apply these algorithms to current and future hyperspectral sensors on

polar orbiting and geostationary satellite platforms with a view to

improving our understanding of the Earth\'s hydrological cycle and
energy

budget. This paper reviews the advantages and disadvantages of using

high-spectral resolution infrared observations to detect cloud and

aerosol and, where feasible, retrieve their microphysical properties.

Presented is an overview of these algorithms and a demonstration of

their capabilities as applied to aircraft (HIS/S-HIS/NAST-I) as

preparation for GOES-R

27\) **[Automated Snow Mapping And Monitoring With Goes Imager:
Perspectives For GOES-R]{.underline}**

Peter Romanov, Dan Tarpley

Office of Research and Applications, NOAA/NESDIS, Camp Springs, MD

ABSTRACT

Observations from geostationary satellites have long been used to map
and monitor snow cover. Availability of measurements in the visible,
middle-infrared and infrared spectral bands from GOES Imager allows for
an automated identification and mapping of snow. In this presentation we
will describe the retrieval technique and demonstrate current
operational and experimental automated snow and ice products derived at
NESDIS from GOES data. These products include snow and ice cover, snow
fraction and estimates of the snow depth over non-forested areas.
GOES-based retrievals will be compared with other remote sensing
products derived from different instruments and with surface
observations. We will discuss perspectives to improve snow detection and
mapping with the Advanced Baseline Imager (ABI) onboard GOES-R. The key
factor in the improvement is a broader and more detailed spectral
coverage of ABI as compared to the current GOES Imager. MODIS data will
be used to assess the effect of additional spectral information in ABI
measurements on the accuracy of future snow products.

28\) [Smooth transitions toward GOES-R: Simulation of high temporal
resolution imagery using advanced morphing algorithms]{.underline}

Anthony J. Wimmers^\*^

\*Cooperative Institute for Meteorological Satellite Studies (CIMSS)

University of Wisconsin-Madison, Madison, WI 53706, U.S.A.

Abstract

"Morphing" is a term that describes a broad category of digital image
algorithms used to create smooth, seamless transitions between two or
more images. In satellite imagery, morphing can be used to simulate
image sequences at a temporal resolution that is higher than the
original instrument capabilities. This makes morphing a necessary tool
for visualizing the five-minute full disk updates planned for the GOES-R
Advanced Baseline Imager (ABI) channels, and indicates a future role
that morphing can play in further enhancing the temporal quality of ABI
imagery in post-processing. Before the GOES-R deployment, morphing could
be used to create realistic five-minute full disk simulations from
existing GOES or Meteosat Second Generation imagery to prepare for the
data-delivery requirements of GOES-R. After deployment, morphing could
be used to create \<5 minute resolution "interpolations" of ABI imagery
in rapidly developing events, and could be used to repair sectors
corrupted by operational errors.

A simulation of five-minute resolution full-disk imagery produced by
morphing GOES-12 images will be presented. A regional-scale example
using morphed images from the Moderate Resolution Imaging
Spectroradiometer (MODIS) will also be presented in order to demonstrate
the infrared ABI bands at full 2-km resolution.

# 29) [Aerosol Correction for NPOESS VIIRS Sea Surface Temperature]{.underline}

Dorlisa L. Hommel^1^, Richard J. Sikorski^1^, Yunyue Yu^1^, Thomas P.
DeFelice^1^, Phillip Ardanuy^1^, Doug May^2^, Wallace McMillan^3^

1\. Raytheon ITSS, 4400 Forbes Blvd., Lanham, MD, USA, phone
(301)794-5351, fax (301) 794-7106, e-mail Dorlisa_L_Hommel@raytheon.com

2\. Remote Sensing Branch, Naval Oceanographic and Atmospheric Research
Laboratory, Stennis Space Center, Mississippi, USA

3\. Physics Department, UMBC, 1000 Hilltop Circle, Baltimore, MD, USA

Satellite sea surface temperature (SST) retrieval has been available for
nearly three decades. The effects of high aerosol concentrations on SST
retrievals are not well characterized and are a significant concern in
the Visible/IR Imager/Radiometer Suite (VIIRS) retrieval algorithm.
VIIRS will fly as a primary sensor on the National Polar-orbiting
Operational Environmental Satellite System (NPOESS) program. The first
opportunity for VIIRS will be as a payload on the NPOESS Preparatory
Project (NPP), currently scheduled for launch in 2006, which provides a
great opportunity to investigate this problem. This study utilizes VIIRS
proxy imagery and VIIRS aerosol products to study this source of error.
Preliminary results will be presented at the meeting. A comparison
between the aerosol-corrected SST's and non-corrected SST's indicates
that the VIIRS aerosol products are useful for applying aerosol
correction in the SST retrieval.

# 30) [GOES-R ABI Impacts on Operational Cloud Analysis at AFWA]{.underline}

Mark Conner, Gary Gustafson, Francis Bieker^1^, Bruce Thomas^2^ and
Thomas Kopp^2^

Atmospheric and Environmental Research (AER), 131 Hartwell Avenue,
Lexington, MA 02421-3126 ^1^Headquarters Air Force Weather Agency, 106
Peacekeeper Dr., STE 2N3,

Offutt Air Force Base, NE 68113

^2^The Aerospace Corporation, 2350 E. El Segundo Blvd., El Segundo, CA
90245-4691

Abstract

For over three decades the Air Force Weather Agency (AFWA) has produced
an operational global cloud analysis product based on analysis of
polar-orbiting satellite observations from DMSP and TIROS. In June of
2002 the existing nephanalysis model underwent a significant upgrade
that included addition of data from the international constellation of
geostationary environmental satellites (i.e., GOES, Meteosat, and GMS).
Understandably, this resulted in major improvements of timeliness,
accuracy, and coverage over mid-latitudes to the tropics. New algorithms
were developed specifically to exploit the high temporal refresh and,
where applicable, the multispectral capabilities of the respective
sensors. The most capable of the extant systems are the GOES
five-channel imaging sensors with their frequent updates (15 minutes
over much of the coverage areas) and true multispectral capabilities.

While analysis of GOES data provides a vastly superior cloud analysis
relative to the legacy two-channel polar-orbiting algorithm, there
remain limitations that negatively impact overall accuracy. These
include loss of continuity across the day/night terminator;
discrimination of low cloud/fog over problematic backgrounds such as
ice, snow, desert, and sun-glint; detection and accurate
characterization of transmissive cirrus, particularly during daytime;
complete identification of multi-layer cloud systems; and correct
classification of ice, water, and mixed-phase clouds. Satellite
limitations such as eclipse outages, sensor noise and reduced spatial
coverage during rapid-scan also affect the operational products.
On-going research to utilize the high spectral resolution of new and
upcoming sensors such as MAS, MODIS, VIIRS, and the GOES-R ABI have
shown promise toward addressing the known weaknesses associated with
existing sensor systems. Existing rapid prototype facilities at AFWA
provide an optimal environment for evaluating new sensor data and
processing algorithms prior to incorporation into the operational
system. The imminent introduction of 12-channel SEVIRI data from an
operational Meteosat-8 is expected to provide a first indication of how
well the AFWA operational model can adapt to an expanded sensor
capability. In our poster we will present real-world examples of current
algorithm performance using the existing GOES imager, describe the rapid
prototyping facilities that are in use today, and overview cloud
algorithm upgrades that are potentially supported by the ABI.

31\) **[Utilization of GOES-R Measurements at NESDIS for the Real-Time
Analysis and Monitoring of Environmental Events]{.underline}**

Number range CHAPTERJohn Paquette and Brian Hughes

NOAA/National Environmental Satellite, Data, and Information Service

The Satellite Services Division (SSD) intends to improve its suite of
hazards products through the application of GOES-R data and products.
The spectral channels that are currently only available from NOAA's
Polar-orbiting Operational Environmental Satellites (POES) along with
other essential channels to sense more of the earth's environment will
be available from the GOES-R Advanced Baseline Imager (ABI).

Due to its high spatial and temporal resolutions, the use of the GOES
ABI and Hyperspectral Environmental Suite (HES) data and products at the
SSD is paramount to support near real-time analyses of significant
global hazard events including tropical cyclones, heavy precipitation,
volcanic ash, and fires and smoke. SSD's analysis of snow and ice will
also benefit from the use of the ABI. In the next series of GOES,
starting with GOES-R, SSD plans to fully exploit the increased number of
spectral channels (16) and the improved temporal resolution (full disk
scan every five minutes) and spatial resolution of the ABI ( .5 km for
visible channel and 2 km for infrared channels). In accordance with
NOAA's strategic goals of serving society's needs for weather and water
information and supporting the nation's commerce with information for
safe and efficient transportation, it is SSD's fundamental goal to
improve its products for the National Weather Service's advanced warning
and forecast services and other federal and state agencies. As
aforementioned, derived products from the HES (GOES-R Sounder) will also
be utilized by SSD to complement the analyses of environmental events,
particularly volcanic ash detection and heavy precipitation.

32\) [**A System Design for Storing, Archiving, and Retrieving
Hyperspectral Data**.]{.underline}

## Ralph G. Dedecker\*, Tom Whittaker\*, Ray K. Garcia\*, Robert O. Knuteson\*

# \*University of Wisconsin-Madison, Space Science and Engineering Center

Cooperative Institute for Meteorological Satellite Studies (CIMSS)

University of Wisconsin-Madison

Madison, WI 53706, U.S.A.

Abstract

Hyperspectral data and products derived from instrumentation such as
GOES-R HES, AIRS, CrIS, and GIFTS will impose storage and data retrieval
requirements that far exceed the demands of earlier generation remote
sensing instrumentation used for atmospheric science research. Efforts
at the University of Wisconsin - Space Science and Engineering Center
(UW-SSEC) are underway to develop a new architecture designed to address
projected real time and research needs.

The large volume of data collected and products produced from
hyperspectral instrumentation will require large distributed storage
devices employing several servers. The hardware infrastructure must be
implemented to allow component augmentation, replacement, and
maintenance without undue demands to modify user applications. User
applications will need tools to simplify locating data files. User data
selection facilities for retrieving specific information from storage
devices for calibration, analysis, instrument inter-comparison, or
reference purposes will also be necessary due to the large data volume
and standardized data formats and data delivery schemes will be
important.

This poster will outline a prototyped infrastructure for data archiving
and cataloging, data storage, metadata search and query, and retrieved
data delivery schemes to be utilized for real time operations and by
research users.

33\) [Environmental product VErification and REmote SEnsing Testbed
utility for HES]{.underline}

Jay Marmo and Jerome Luine

Northrop Grumman Space Technology, Redondo Beach, CA 90278

Abstract

Northrop Grumman Space Technology\'s Environmental product VErification
and REmote Sensing Testbed (EVEREST) is a tool  that has been developed
by NGST at its  Environmental Sensing Center in Redondo Beach,
CA. EVEREST produces  simulated sensor data sets derived from detailed
sensor performance models, platform characteristics and simulated
earth surface and atmospheric scenes. This high fidelity modeling and
simulation testbed is currently supporting the National Polar-orbiting
Operational Environmental  Satellite System (NPOESS)   Program.  Current
capabilities and planned upgrades can aide HES users developing
applications and data products to meet NOAA\'s strategic goals.  Users
may also benefit from the EVEREST\'s simulation capability to evaluate
the impact of sensor performance characteristics or post-processing
techniques on potential applications and algorithms.  In this poster
we will describe the EVEREST\'s current and future capabilities and
its potential utility to HES users.

34\) [Advanced Spacecraft Stellar Inertial Attitude Control Technology
to Enhance the Quality of NOAA's GOES Weather Data]{.underline}

Loren Slafer

Boeing Satellite Systems

Abstract

In January 1998, Boeing Satellite Systems (BSS) of El Segundo, CA, began
development of a unique spacecraft bus design concept for the
next-generation Geostationary Operational Environmental Satellites,
GOES-N, GOES-O, and GOES-P. The goal of this new design was to
substantially improve the quality of NOAA's GOES weather data. The key
features of this design concept included a stellar inertial attitude
determination (SIAD) control system which is integrated directly with
the imager and sounder on a precision optical bench to have the bus
design focus on 'flying the instruments' for the next-generations of
GOES.

This new GOES N-P design enables the precision spacecraft performance
that will be required for the GOES-R high-resolution instruments. The
goal of the GOES program's design features was to improve the spacecraft
performance using SIAD to:

-   Enhanced instrument accommodation

-   Significantly improved image navigation and registration (INR)
    performance

-   Provide extensive on-board autonomy for reduced ground interaction

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-   Provide ability for the instruments to perform service quickly after
    orbit control operations (after a 10 minute housekeeping period)

-   Maintain continuous environmental and storm warning systems with an
    enhanced ground resolution (1.5 km ground resolution at nadir) and
    to monitor the Earth's surface and space environmental conditions.

The BSS developed SIAD system uses star measurements provided by star
trackers (3-for-2 redundancies), spacecraft rates measured by
Hemispheric Inertia Reference Unit (HIRU), and a 6-states Kalman filter
implemented in the spacecraft control processor to determine spacecraft
3-axis attitude. It has the advantage of two orders of magnitude
improvement in accuracy over existing earth/sun sensor-based attitude
determination systems.

To meet this never-before achieved 10 microradian bus pointing for GOES
N-P, BSS created many innovative solutions including: a method to
account for the star tracker's non-Gaussian, non-white spatial dependent
errors in the Kalman filter design to optimize SIAD performance, a
45-degree star tracker boresight orientation to attenuate star tracker
high spatial frequency error, a time-matching technique to minimize
attitude error between star tracker based attitude and gyro based
attitude introduced during spacecraft slews, use of an equalized star
catalog to minimize on-board catalog size while enhancing SIAD
performance, and a Kalman filter implementation with weighted
measurement noise covariance matrices.

The Imager and Sounder are collocated with the stellar inertial attitude
sensors on a common base plate supported by structural flexures and
attached to the nadir panel. Reaction wheels are mounted to the aft
corners of the spacecraft main body. The single panel solar array
provides a clear field of view (FOV) for the Imager and Sounder cool­ers,
maximizing their radiometric performance.

The benefits of the precision SIAD control system design for the
improved GOES weather data was discussed by the Boeing team with Joe
Friday, Director, US National Weather Service, 1988-1997. His ideas for
improved weather data was that the improvements in the data quality over
the present system will continue to allow the National Weather Service
to improve its ability to protect the life and property of the nation's
citizens. The main benefits of improved spacecraft performance for
improved data quality described by Joe Friday include improvements in
the ability to detect and locate weather events including flash flood
situations, typhoon tracking, valley fog, and hazards to aviation. The
present capabilities are not sufficient to distinguish between adjacent
valleys in rough terrain, or meet the FAA goals for aircraft safety. The
additional objectives of enhanced spacecraft performance includes'
improving weather and flood forecasts. NWS goals for flash floods
anticipate improvement with GOES N-P to\
60 minutes lead-time with false alarm rates improved. NWS goals for
severe storms anticipate improvement with GOES N-P to 20 - 25 minutes
lead-time. False alarm rates will improve. Improved air traffic control,
separating aircraft from weather thunderstorms and rain cells.

35\) [GOES-R Data Fusion for Atmospheric HazMat Detection, Dispersion
and Concentration Models -- A Case Study in Northeastern Iran Using
MODIS and AIRS Data]{.underline}

# Gary Alexander, Kevin M. Lausten, Mary Tutzu, Brenda Zuzolo, Phil Zuzolo

The Boeing Company, Springfield, VA 22153, U.S.A.

The Hyperspectral Environment Suite (HES) and Advanced Baseline Imager
(ABI) on GOES-R will provide near real time observation and
quantification of catastrophic atmospheric events, both at the Earth's
surface and in the near-surface regime. ABI's high spatial (0.5km) and
temporal resolution (30 minutes, Full Disk) will provide the capability
to not only discern dangerous event locations, but also define multiple
clear atmosphere (cloud, smoke, and obscurant free) viewing windows for
the HES. Algorithms using the high spectral and temporal resolution of
the HES will enable identification of many gaseous materials harmful to
human health. In addition, parameters such as relative humidity, wind
speed/direction, and cloud particle size, required as inputs for
accurate dispersion modeling, can be determined from HES data. The data
products can be used in conjunction to create models for the
distribution of harmful materials, assisting decision makers in
evacuations, remediation/containment actions, and post-event
decontamination activities. The synergistic relationship of these
sensors is maximized by their collocation. A case study over
Northeastern Iran, incorporating high spatial resolution MODIS data with
high spectral resolution AIRS data will illustrate the efficiency and
effectiveness of an integrated approach.

36\) [Synergistic Approach to Aerosol Observations Using the
Hyperspectral Environmental Suite (HES) and the Advanced Baseline Imager
(ABI) On GOES-R]{.underline}

# Gary Alexander, Kevin M. Lausten, Mary Tutzu, Brenda Zuzolo, Phil Zuzolo

The Boeing Company, Springfield, VA 22153, U.S.A.

Abstract:

The Hyperspectral Environment Suite (HES) and Advanced Baseline Imager
(ABI) on GOES-R allow for the most accurate observation and
quantification of aerosol optical properties. Aerosols can affect
climate by scattering or reflecting solar radiation, and by altering
cloud microphysics, cloud brightness, and precipitation. The high
spatial (.5 km) and temporal (30 minutes, Full Disk) resolution of the
ABI allows for up to date cloud masking capabilities and the accurate
location of multiple clear atmospheric windows. The high spectral (TBD)
and radiometric resolution functionality of the HES enables algorithms
to acquire valuable aerosol information. Such products as aerosol
optical thickness (AOT), particle size, and relative humidity (RH) can
be calculated over oceans and ideal continental regions in near real
time due to the co-location of the ABI and HES. The Moderate Resolution
Imaging Spectroradiomter (MODIS) and Atmospheric Infrared Sounder (AIRS)
instruments relate well to the ABI and HES, respectively, and are used
in this study to display a synergistic relationship between sensors to
develop aerosol products.

37\) **[Thetus Publisher, Data Management Software for Satellite and
other Scientific/Research Data]{.underline}**

Danielle Forsyth, Thetus Corporation

Abstract:

Current data management systems and practices have not kept pace with
data production. Data is isolated in silos with incomplete metadata.
When metadata has been captured, it has not been made available for
users to search. Metadata has not continued to evolve as data processing
continues. Automated notification has not been done to notify
researchers and data users when specific data is available. There has
been no scientifically defensible record of data processing throughout
the data lifecycle.

Thetus developed a new data management solution tuned for scientific and
research data management to address these problems. One of the company's
early customers was the College of Oceanic & Atmospheric Science (COAS)
at Oregon State University. They needed to bring order to their NASA
MODIS satellite direct broadcast data streams and make subsets of the
data available to internal and external researchers and the public. They
needed a system which would support the on-going discovery inherent to
satellite data and they needed to be able to do track this data as it
was fused with other data sets.

Thetus automated the data processing workflow (automatically generating
products), tracked the metadata throughout the data lifecycle and
provided researchers and web users with a seamless way to search,
retrieve and understand satellite data and its relationship to other
remotely sensed data.

The Thetus Publisher is a solution for proactive ontology-based
classification of data and a rich metadata search and retrieval.
Ontologies provide a structure for understanding and relating metadata
from varied sources. COAS used Thetus to build a MODIS Satellite data
ontology. This ontology can be readily shared with other Satellite data
collection organizations who want to start with a geospatial semantic
description. By sharing ontologies between organizations and using them
to keep metadata and process information at the sites where it can best
be maintained, the Publisher provides an extensible framework for data
management, searching and notification, data routing and storage
management.

Using the RDF standard and providing the web service interfaces also
means that the ontology and data classification descriptors can be made
available to other data processing sites and, if the sites agree on an
ontology, all sites can reference classification elements between
systems. A major advantage to the RDF/OWL versus a rigid schema approach
is that the assertions and annotations associated with any data or
dataset can continually evolve as advances are made in scientific
analysis methods or additional information about the dataset is
discovered. This approach enables greater collaboration between the
diverse communities using satellite and other geospatial data streams,
including communities outside the research community.

The poster will describe and demonstrate satellite (MODIS and AVHRR) and
coastal radar data and metadata processing, automated retrieval of
up-to-date processing algorithms and cross site data search. The
advantages of automated processing and metadata management will be shown
through the search interface, data provenance reporting, automated user
notification and selective data re-processing .. Migration of data and
metadata to new generations of satellite data collection systems (ie.
GOES-R) will be presented.

[**38) Current GOES Data Capability Within The CLASS System And New GOES
Capabilities in Development Or Planning Stages**.]{.underline}

Richard G. Reynolds, Chief, Ground Systems Division, Office of Systems
Development, NESDIS

Carlos Martinez, Vice-President, TMC Technologies, Inc.

Abstract:

NOAA has developed the Comprehensive Large Array-data Stewardship System
(CLASS) to archive and provide access to the data from current
satellite-based observing systems (e.g., Polar-orbiting Operational
Environmental Satellites -- POES and Geostationary Operational
Environmental Satellites - GOES) and ground-based observing systems
(e.g., Next Generation Weather Radar - NEXRAD). CLASS is also is being
designed to handle the significant increases in data volume that will
come from planned satellite launches (e.g., National Polar-orbiting
Operational Environmental Satellite System - NPOESS, NPOESS Preparatory
Project - NPP and Earth Observing System - EOS satellites). Finally,
CLASS will ultimately be capable of supporting current in situ data
sources (e.g., Automated Surface Observing System - ASOS).

Current GOES data is now available through CLASS and has been since
December 1, 2003. The data can be searched in a variety of ways,
including by data type, satellite, date and time range, and spatial
coverage. GOES data can be delivered in several different formats,
including McIDAS area format, NetCDF, GIF, JPEG, and raw GVAR. Plans are
being formulated to backfill some or all of the more than 200 terabytes
of historical GOES data to make it available to researchers, scientists,
and the general public.

GOES operational capabilities:

-   GOES data archive and access capability became operational on
    December 1, 2003

-   Available data formats are: McIDAS area format, NetCDF, GIF, JPEG,
    and raw GVAR.

-   Spatial resolutions are: 1km, 4km, 8km, and 16km. (approx. at
    subsatellite point)

-   Bands are: Imager bands 1-5/6, Sounder bands 1-19

-   Search capabilities include:

    -   Coverage (e.g., CONUS, Full disk, Northern or Southern
        Hemisphere)

    -   Satellite schedule (e.g., routine, rapid scan, super rapid scan)

    -   Data type (e.g., Block 11, imager, sounder)

    -   Satellite (e.g., GOES-8, GOES-9, GOES-10, GOES-12)

    -   Date and time range

    -   Spatial coverage using a bounded box or entering lat/long
        coordinates

Current development activities:

-   Dual site operations

    -   Suitland, MD (OSDPD) and Asheville, NC (NCDC)

    -   Planned to be operational March 15, 2004

-   Planning for ingest of historical GOES data

-   Statistical analysis of Imager data

-   New Global Imaging GOES ingestors replacing data feed from
    University of Wisconsin

-   Evaluating GOES products

Supports the following NOAA Strategic Goals:

-   Understand climate variability and change in order to enhance
    society's ability to respond

-   Serve society's needs for weather and water information

-   Support the Nation's commerce with information for safe and
    efficient transportation

# 39) [The SDO EUV Variability Experiment (EVE): Research to Operations]{.underline}

F. G. Eparvier, T. N. Woods, and the EVE Science Team\*

The EUV Variability Experiment (EVE) on the upcoming NASA Solar Dynamics
Observatory mission has four primary science objectives: (1) Specify the
solar EUV irradiance and its variability on time scales from seconds to
years; (2) Advance current understanding of how and why the solar EUV
irradiance varies; (3) Improve the capability to predict (nowcast and
forecast) the EUV irradiance variations; and (4) Understand the response
of the geospace environment to solar EUV variability and the impact on
human endeavors. This poster will describe the EVE science plans, going
beyond accurate and precise irradiance measurements to encompass
improvements in models of the sources of solar EUV and the effects on
the Earth\'s atmosphere. EVE has the ultimate goal of improving space
weather operations and will provide a transition to the future of space
weather monitoring systems.

\* The EVE Science Team:

Eparvier, F. G., Woods, T. N., G. Rottman (University of Colorado --
LASP)

A. Jones, D. Judge (University of Southern California)

J. Lean, J. Mariska, D. McMullin, H. Warren (Naval Research Laboratory)

G. Berthiaume (MIT -- Lincoln Labs)

S. Bailey (University of Alaska -- Geophysical Institute)

T. Fuller-Rowell, R. Viereck (NOAA -- Space Environment Center)

J. Sojka (Utah State University)

K. Tobiska (Space Environment Technologies)

40\) [Distributed Computing for the Extraction of Meteorological
Products from the GIFTS Imaging Interferometer]{.underline}

# Raymond K. Garcia, Maciej J. Smuga-Otto, Hung-Lung Huang, Paolo Antonelli

Cooperative Institute for Meteorological Satellite Studies (CIMSS)

University of Wisconsin-Madison, Madison, WI 53706, U.S.A.

Abstract

Faced with the challenge of terabyte-scale data volumes specified by
forthcoming imaging infrared interferometers, such as those planned for
the Hyperspectral Environmental Suite (HES), and the necessity for
timely delivery of meteorological products derived from these data, we
are conducting design studies and prototyping a distributed data
processing system capable of meeting throughput and latency
requirements. We summarize methodologies and technologies appropriate to
near-real-time extraction of products, including atmospheric vertical
temperature and moisture profiles as well as wind vector fields, from
data to be delivered by the Geosynchronous Imaging Fourier Transform
Spectrometer (GIFTS).

41\) **[The Future of Infrared Geostationary Ozone Detection: HES and
ABI]{.underline}**

Christopher C. Schmidt, Jun Li

Cooperative Institute for Meteorological Satellite Studies (CIMSS)

University of Wisconsin-Madison, Madison, WI 53706, U.S.A.

Abstract:

The GOES I-M series of satellites are endowed with an ozone sensitive
band located at 9.6 μm. Estimates of hourly, 10 km resolution total
column ozone are possible utilizing the ozone band and the other Sounder
bands at 4 μm and longer wavelengths via a linear regression technique.
GOES I-M ozone estimates have allowed for the detection of features that
reflect both synoptic and mesoscale dynamics. Current GOES Sounder
estimates lack the temporal and spatial resolution to routinely detect
mesoscale airmass exchange events, such as those that cause clear air
turbulence, though case studies have shown that it is possible to do so
on occasion.

While the Imager on GOES I-M does not have the ability to assist the
Sounder in ozone detection, GOES satellites carrying the Hyperspectral
Environmental Suite (HES) and the Advanced Baseline Imager (ABI) will
have two instruments capable of generating ozone values, both separately
and in concert with one another. ABI, while achieving less accuracy than
the current GOES Sounder, has a high refresh rate with Continental
United States (CONUS) scans every 5 minutes and full disk scans every 15
minutes at a resolution of 2 km. HES is capable of achieving much higher
accuracies (relative to current GOES and ABI) at 4 km resolution, yet at
a lower refresh rate. HES and ABI could be used synergistically to
achieve high accuracy and high temporal and spatial resolution ozone
retrievals that will allow rapid and accurate detection of ozone
features that could lead to identification of events such as clear air
turbulence.

Simulations of HES, ABI, and GOES ozone regression techniques have been
compared and illustrate the advantages of the GOES-R platform over
current GOES.

42\) **[Design of a Compression Algorithm for GOES Data.]{.underline}**

Irina Gladkova ¹, Leonid Roytman ¹, Mitch Goldberg ², John Weber ¹

¹ City College of New York, ² NOAA/NESDIS

Abstract

We are developing a novel approach for the compression of the next
generation GOES sounding data that includes over 2,000 channels and
arranged in granules that consist of 135 scan lines containing 90

cross-track footprints per scan line resulting in total 135 x 90
footprints.

The proposed algorithm is based on adaptive clustering procedure that
extracts the characteristic features of the sensor measurements. The
clustering is performed recursively and at each iteration the set of
features is modified so that the classification performance is
maximized. Several elements of the proposed algorithm are similar to
(available in the literature) pattern recognition approaches and the
vector quantization techniques. The challenge is to derive an organic
compression scheme that is the most appropriate for the sounder data.
Hence, the main objective of the project is to incorporate a priori
knowledge of the physical

characteristics of the sounder data into compression process in order to
achieve an optimal compression ratio. Our overall strategy is to use the
data itself as the prime driver in the search for the optimum solution.

43**[) EXPLORES! - A K-12 Educational Outreach Program for NOAA GOES and
POES Satellites Products]{.underline}**

Paul Ruscher

Department of Meteorology, Florida State University, Tallahassee FL
32306-4520

ruscher@met.fsu.edu

This poster will outline the goals and accomplishments of the
international EXPLORES! program, which has been deployed in six states
and in Mexico. The program began in 1992 as a way to bring NOAA direct
readout (APT and WEFAX) into the K-12 classroom, and continues with the
delivery of real-time digital data into the classroom today (HRPT and
GVAR). EXPLORES! is adapting to the newer satellite constellations, and
also has developed a K-12 curriculum that is tied to Florida state
science standards as well as National Standards. A distance learning
course on using geoscience imagery, including NOAA satellite data, in
the classroom will be piloted during summer 2004. We also maintain the
international weather satellite professional and enthusiast list,
WXSAT-L.

One of our most popular features is daily weather satellite discussions,
done during the school year. These features were added after the old
NESDIS regional satellite discussions were discontinued in the 1990s. In
addition, we have a complete history of the U. S. Weather Satellite
program online. We also participate in the GLOBE program, and have
developed a separate educational outreach program for schools with
automated weather stations, called REALM.

The EXPLORES! program has operated a site on the World Wide Web for
teachers forcussing on satellite meteorology and tropical weather (in
response to a request from for our Florida teachers) since 1995; it is
available at <http://www.met.fsu.edu/explores/>.

44\) **[Using GOES-R for Land Surface Temperature
Estimation]{.underline}**

*Andrew Heidinger@, Aleksandar Jelenak\*, Dan Tarpley\*, Mike Walters#*

^@^NOAA/NESDIS, Office of Research and Applications

Madison, WI 53706, U.S.A.

\*NOAA/NESDIS, Office of Research and Applications

Camp Springs, MD 20746, U.S.A.

\# UW/CIMSS, Madison WI, 53706, U.S.A.

Abstract

The Advanced Baseline Imager (ABI) and the Hyperspectral Environmental
Suite (HES) will provide a vast improvement in the current capability in
monitoring the land surface temperature (LST). LST is a critical product
from GOES and is used in defining the lower boundary condition in
numerical weather prediction models. The current GOES N-P series of
imager lacks a 12 um channel which complicates the estimation of the
LST. In addition, the lack of hemispheric scanning of the GOES N-P
sounder limits the ability of using sounder channels to assist in the
LST generation. All of these limitations will be removed with GOES-R.
This poster will present the current state of LST generation with GOES
N-P within the NESDIS Office of Research and Applications and will give
preliminary results on the improvements expected with GOES-R.

45\) **[Transition from NPOESS-CrIMSS toward GOES-HES: Algorithm
Overview and Initial Results]{.underline}**

Richard Lynch, Jean-Luc Moncet, T. Scott Zaccheo, Hilary E. Snell

Atmospheric and Environmental Research, Inc.,

131 Hartwell Avenue, Lexington, MA 02421

The Hyperspectral Environmental Sensor (HES), scheduled for flight on
GOES-R, will dramatically enhance atmospheric, surface and cloud
characterization capabilities from the geostationary platform. The
proposed channel set and spectral resolution for HES are similar to both
AIRS, which is presently on the EOS-Aqua platform, and the Cross-track
Infrared Microwave Sounder Suite (CrIMSS), which will fly on the NPP and
NPOESS platforms. We have developed an algorithm to generate temperature
and moisture soundings operationally from microwave and infrared
sounders using a physical retrieval method. This algorithm, based upon
well-known minimization methods but optimized for the new generation of
high spectral resolution instruments, is the basis for the CrIMSS
temperature and moisture profile retrieval algorithm. The algorithm is
extremely flexible and is designed to allow for the retrieval of surface
properties and/or trace gas profiles in addition to temperature and
moisture profiles. For test and verification it has been applied to
simulated CrIMSS data, along with actual NAST-I, AIRS and AMSU
measurements. For example, as an on-going, daily algorithm validation
effort at AER, global retrievals of NOAA-16 AMSU data are compared with
co-located radiosonde measurements. The key to the flexibility of the
retrieval algorithm is in the forward radiative transfer model, the
Optimal Spectral Sampling (OSS) method. This is a state-of-the-art, fast
radiative transfer model that allows for tuning of model accuracy to
meet user run-time requirements. Specific features incorporated into OSS
eliminate the need for re-training the model when performing
phenomenology studies, such as retrieval of trace gases, or to vary the
instrument spectral characteristics. This feature also allows for a
straightforward transition of the algorithms from current sounder
configurations to HES and provides a mechanism for the inter-comparison
of sensor data using a common retrieval algorithm. In this poster we
will present an overview of the NPOESS-CrIMSS algorithms, describe the
OSS method and discuss specifics about the implementation that maximize
flexibility for transition to future sensors. Retrievals using AIRS
measurements and simulated GOES-HES measurements will also be presented.

46\) Multi-Spectral Infrared Sea Surface Temperature Algorithms for
GOES-R

David Hogan, William Gallery, Scott Zaccheo and Xu Liu

Atmospheric and Environmental Research, Inc.

131 Hartwell Avenue, Lexington, MA 02421

<dhogan@aer.com>

The advanced imaging and sounding capability planned for GOES-R can
provide improved sea surface temperatures (SST) with benefits to diverse
applications including weather forecasting, climate, fisheries and
shipping. The additional channels, higher spatial resolution and lower
noise of the Advanced Baseline Imager will lead to improvements in SST
generated by standard multi-channel regression approaches. The
Hyperspectral Environmental Sensor (HES) can provide dramatically
improved characterization of the atmospheric and surface state and
offers the possibility of highly accurate physically-based SST
determination.

We investigate two algorithm approaches for Sea Surface Temperature
(SST) for GOES-R: (a) multi-channel regression-based approach using only
channels from an imaging sensor; and (b) physical retrieval combining
high spatial resolution infrared imaging data with high spectral
resolution sounder data. The regression algorithm employs multiple
channels in thermal infrared wavelengths from 3.7 to 12 μm. The
Non-Linear SST (NLSST) algorithm (the current operational POES SST
algorithm used with the AVHRR) is compared to several alternative
algorithms. These alternative algorithms include use of the 8.5 μm
channel (to improve tropical SSTs) and corrections for aerosols. The
combined imager/ sounder algorithm applies a two-step physical retrieval
algorithm. First an iterative physical retrieval algorithm is applied
using only the HES data to derive a low spatial resolution specification
of the atmospheric and sea surface state. Then a second physical
retrieval is performed by adding the ABI infrared radiances. The
physical retrieval algorithm employs an iterative, non-linear optimal
estimation technique. This physical retrieval algorithm is shown to
result in reduced measurement uncertainty because of the improved
atmospheric correction compared to multi-channel regression algorithms.

These analyses were performed using a comprehensive algorithm test-bed
at AER. This test-bed includes end-to-end modeling tools, sensor
simulators, extensive environmental databases, state of art radiative
modeling tools, interactive analysis software and real-time satellite
data feeds. The radiative transfer modeling used in this work includes a
wind and angle-dependent ocean emissivity model and an ocean
reflectivity model that calculates solar reflection from a wind-ruffled
ocean surface. The latter effect is essential for accurate assessment of
the use of mid-wave infrared channels in the daytime.

47\) **[EOS Data in NWS Forecast Offices: A Test Bed for GOES-R
Applications]{.underline}**

Gary Jedlovec^1^, Stephanie Haines^2^, Ron Suggs^1^, Tom Bradshaw^3^,
Jason Burks^3^, and Kevin Schrab^4^

^1^ Earth Science Department, NASA/MSFC, Huntsville, AL

^2^ Earth System Science Center, University of Alabama at Huntsville,
Huntsville, AL

^3^ NWS Forecast Office, Huntsville, AL

^4^Office of Science and Technology, DOC/NOAA/NWS, Silver Spring, MD

Abstract:

Imagery and derived products from MODIS, on NASA\'s Terra and Aqua
satellites, are being used operationally by several NWS Forecast Offices
to assist in the preparation of short-term forecasts. A subset of MODIS
channels with spectral characteristics similar to those planned for the
GOES-R ABI are obtained in real-time by the NASA/MSFC, as part of the
Short-term Prediction Research Transition (SPoRT) program. The data are
reformatted, sectorized, and disseminated to Forecast Offices for
operational use directly in AWIPS. Several images generated from more
than one channel, such as true and false color composite imagery and a
11-3.9 micrometer "fog" image, are produced from the real-time data
stream. Additionally, a number of products, such as lifted index, land
surface temperature and cloud phase, generated either from EOS
institutional or NASA/MSFC in-house algorithms, are made available to
the offices in near real-time.

This transition activity, from research to operations, serves to prepare
forecasters for the next generation of satellite observing capabilities
through real-time, hands-on applications to their forecast problems. The
SPoRT program provides training on the new data and products and their
applications. Forecasters provide immediate feedback on product
improvement and an assessment of the value of the new data or product.
The poster will present examples of this transition and preliminary
assessments on the utility of the EOS products for improving short-term
forecasts.

48\) **[Application of Principal Component Analysis (PCA) to AIRS
Data]{.underline}**

M. Goldberg(2), L. Zhou(1), and W. Wolf(1)

\(1\) QSS Group Inc, Lanham, MD, USA

\(2\) NOAA/NESDIS/STAR, Camp Springs, MD, USA

Abstract

Observations from high spectral resolution Atmospheric InfraRed Sounder
(AIRS)

are now routinely provided in near real-time to the NWP community by

NOAA/NESDIS.

The main benefits of high spectral resolution infrared data are vastly
improved

information of the temporal and spatial structure of key atmospheric
parameters,

such as temperature, moisture and clouds, which are needed to
significantly

improve real-time, weather forecasting, and climate monitoring and
prediction

capabilities. Also important trace gases such as ozone, carbon dioxide,
carbon

monoxide, and methane can be derived. Our processing of AIRS data is
also

providing important risk reduction activities for future sensors,
including

GOES-R

A very important part of our AIRS processing is to apply Principal

Component Analysis (PCA) to the original AIRS 2000+ channel radiances.

PCA is used for detector monitoring and noise filtering/estimating,
channel

recovery and radiance reconstruction, and for deriving profiles of

temperature, moisture, ozone and other geophysical parameters.

Since PCA has the ability to reduce the dimensionality of a dataset

while retaining most of the information, investigations are being done
on

its applications to AIRS data compression and archiving. Data
compression is

one of the key issues for GOES-R.

Our research and prototyping will allow us to provide valuable
information and

lessons learned to the GOES-R effort. Some examples

of each application, along with the details on the generation and
application

of eigenvectors, will be presented at the meeting.

49\) **[The Case for the Green Band on ABI]{.underline}**

Christopher C. Schmidt

Cooperative Institute for Meteorological Satellite Studies (CIMSS)

University of Wisconsin-Madison, Madison, WI 53706, U.S.A.

The most widely used and most efficient processor of sensor information
in the world utilizes an array of detectors that are sensitive to
radiation from the visible portion of the spectrum. While the processor
in question is capable of functioning without some or all of this
radiance information, extra cost and effort is required to make up for
the loss. There are currently over 6 billion of these processors in
existence, and new ones are coming online every day.

While often referred to as merely a "qualitative" product, natural color
imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS)
has proven to be highly desired by scientists, the military, commercial
enterprises, and the general public alike. While no requirements from a
select pool of users specified a 0.55 μm ("green") band on the Advanced
Baseline Imager (ABI), the omission of that band, and subsequent loss of
natural color (also known as true color or "red, green, and blue")
imagery capability, will incur extra cost and effort to generate the
pseudo-color imagery that will function as a replacement. Look-up tables
(LUTs) have the greatest capability thus far to represent green
utilizing information from the red, blue, and 0.86 μm (near infrared)
bands that are planned for ABI. The LUTs fail under certain
circumstances to produce acceptable results and by necessity result in a
loss of data resolution. LUTs also incur costs related to their
generation and application, costs that will be shouldered by every
agency and commercial entity that desires an approximation of natural
color imagery. Whereas natural color images are readily interpreted by
everyone from a five year old child to the President of the United
States, pseudo-color images will require training in order to demarcate
the limitations of the images to users who must make decisions based on
what they see. From a quantitative, derived product standpoint, some
algorithms that could benefit from a green band have been overlooked,
particularly with respect to aerosol optical depth. Examples of ABI
images made from LUTs and of quantitative products made using the green
band will be simulated from MODIS.

The ultimate end user for any publicly funded satellite program is the
public. Discounting the positive impact that high resolution natural
color imagery could have upon the perception of the utility of the GOES
series should not be dismissed out of hand. Natural color imagery is the
primary and most effective method of outreach for earth and space
science, and that imagery has always proven to be the most effective in
that regard as it is in the form that our minds were built to
understand. What is called "good enough" today will be seen as flawed
when tens of thousands of users, accustomed to MODIS and similar
platforms, begin to discover the inadequacies of pseudo-color imagery.

50\) **[Applications of the Advanced Baseline Imager for Fire Detection
and]{.underline}**

# [Characterization]{.underline}

Christopher C. Schmidt\* and Elaine M. Prins@

\* Cooperative Institute for Meteorological Satellite Studies (CIMSS)

University of Wisconsin-Madison, Madison, WI 53706, U.S.A.

@ NOAA/NESDIS/ORA, Advanced Satellite Products Team, Madison WI 53706,
U.S.A.

Abstract

The current GOES Wildfire Automated Biomass Burning Algorithm (WF_ABBA)
has provided diurnal information on wildfires, prescribed burns, and
agricultural fires for the Western Hemisphere since the year 2000 for
hazard support activities and for documenting and evaluating the impact
of biomass burning on the environment. The international environmental
monitoring and scientific research communities have stressed the
importance of utilizing operational satellites to produce routine fire
products and to ensure long-term stable records of fire activity for
applications such as land-use/land-cover change analyses and global
climate change research. The Advanced Baseline Imager on GOES-R and
beyond will enable

continued analysis of fire activity throughout the Western Hemisphere
with significant improvements in fire detection and sub-pixel fire
characterization. Full disk coverage every 15 minutes and conus every 5

minutes will ensure that even short-lived burning can be monitored. With
the improved spatial resolution on ABI in the infrared bands (2 km), the
minimum detectable fire size burning at an average temperature of 750 K
will be approximately .04 ha with the size increasing to .08 ha at 50
°N. The elevated saturation temperature of 400 K in the 3.9 micron band
limits the number of saturated fire pixels to less than 10% of all
observed fires. Simulations of enhanced GOES ABI fire monitoring
capabilities will be demonstrated using MODerate-resolution Imaging
Spectroradiometer (MODIS) observations of fires in the Western U.S.

51\) **[On The Spatial And Spectral Requirements To Effectively Resolve
The Coastal Ocean Environment]{.underline}**

W. Paul Bissett, Daniel Dye, Sharon DeBra, and David D. R. Kohler

1Florida Environmental Research Institute, Tampa, FL USA

Abstract

The anticipated Hyperspectral Environment Suite (HES) sensor on the GOES
R will provide a revolutionary new tool to the fields of ocean and
climate monitoring. This sensor will provide continuous data streams
necessary for effective monitoring, management, and forecasting in the
near-shore coastal environment. Previous, multi-spectral satellite
sensors have contributed greatly to the biological, chemical, and
physical characterization of the open ocean. However, in the coastal
zone, the spatial and spectral resolution of these satellites have been
insufficient to resolve the complicated commingled signals of bottom
reflectance, suspended sediments, and other non-phytoplankton optical
properties from the bio-optical signals of CDOM and phytoplankton
pigments. High resolution HyperSpectral Imagery (HSI) offers the promise
to deliver the needed spectral and spatial resolution to characterize
the coastal zone, as well as the high signal-to-noise ratio required to
adequately remove atmospheric interference, which is currently
unavailable from space-borne satellite sensors.

The Florida Environmental Research Institute, in collaboration with the
Naval Research Laboratory, has been operating the Portable Hyperspectral
Imager for Low-Light Spectroscopy (PHILLS) in a variety of coastal ocean
environments, ranging from clear tropical environments to turbid
estuarine waters. The spectral resolution required to separate the
water-quality and organic material from bottom type and bathymetry is
approximately 10 nm in these near-shore waters. The spatial resolution
required to resolve these optical constituents, as well as to resolve
physical circulation features such as tidal fronts and river plumes,
ranges from meters to 100's of meters within 20 km of the shoreline. In
this paper, we describe the required spectral and spatial resolution to
effectively resolve important coastal ocean features, e.g. Harmful Algal
Blooms, as well as product generation and data delivery systems for high
resolution HSI data streams.

52\) **[SST retrieval using scene dependant two band and three band
multi-window algorithms for the GOES-R Advanced Baseline Imager
(ABI)]{.underline}**

Barry Gross, Leona Charles, Min Min Oo, Fred Moshary, Samir Ahmed

Optical Remote Sensing Lab, City College of New York; NOAA-CREST

Abstract

Retrieval of Sea Surface Temperature (SST) in tropical or sub-tropical
regions within the 0.2C errors needed for accurate climatology is
complicated by corrections due to atmospheric corrections for water
vapor. This effect is magnified by large satellite zenith angles where
the water vapor path increases. Present operational algorithms work on
near water free bands at \~ 10um and 11um under the assumptions that the
water vapor path is small enough for linear corrections. However, this
approximation degrades for large water vapor paths and non-linear
corrections need to be applied. Improvements under these conditions may
be expected to occur if data from a water vapor sensitive channel is
included which will allow more robust water vapor removal. In addition,
particularly over sub-tropical and tropical regions, strong correlations
exist between total column water vapor (TCWV) and SST which may be used
to improve retrievals. In this presentation, a comparative sensitivity
study between algorithms developed for the ABI channels 14 (11.2um) , 15
(12.3um) bands comparable to operational AVHRR are compared to
algorithms including the use of an extra water vapor channel 16 (13.3um)
as well as "smart" algorithms using correlation relations between SST
and TCWV is performed and significant improvements are seen. Algorithms
are based on a physical retrieval method employing Radiative Transfer
derived channel radiances sampled from TIGR atmospheric profile data
base.

**[53) Insight on HES Coastal Water Imager Inwater Turbidity Product
based on MODIS Observations]{.underline}**

C. Moeller\*, J. Davies\*, M. Gunshor\*, T. Schmit^\#^

\* Cooperative Institute for Meteorological Satellite Studies (CIMSS)

University of Wisconsin-Madison Madison, WI 53706, U.S.A.

^\#^ NOAA/NESDIS, Office of Research and Applications

Madison, WI 53706, U.S.A.

Terra MODIS 250m observations are being applied to a Suspended Sediment
Concentration (SSC) algorithm under development for coastal case 2
waters. This new product provides insight into possible contributions to
coastal monitoring by the HES Coastal Water Imager. The SSC product
algorithm applies an atmospheric correction to isolate the remote
sensing reflectance in the MODIS 650 and 865 nm bands. The atmospheric
correction is based on MODIS observations in the 500 m 1.6 and 2.1 um
bands. Similar spectral bands will be on the Advanced Baseline Imager
(ABI) on GOES-R. The HES-CW will have more spectral bands and be at a
finer spatial resolution than the ABI. The ABI will afford much improved
spatial and temporal coverages. Together the ABI and HES-CW may be
useful complements to capture fine spatial detail and temporal
variability in an SSC product. SSC estimates from remote sensing
reflectance are based on accepted inherent optical properties of
sediment types known to be prevalent in the U.S. Gulf of Mexico coastal
zone. The MODIS SSC product along the U.S. Gulf Coast gives a first look
at possible information content of HES Coastal Water Imager
observations. The influence of spatial resolution will be examined.

54\) **[Regional and Global NWP Data Denial Experiments]{.underline}**

Tom Zapotocny^\*^, James A. Jung^\*^ , W. Paul Menzel^@^ , and James P.
Nelson III^\*^

\*Cooperative Institute for Meteorological Satellite Studies (CIMSS)

University of Wisconsin-Madison

Madison, WI 53706, U.S.A.

^@^NOAA/NESDIS, Office of Research and Applications

Madison, WI 53706, U.S.A.

Abstract

While the impact of data from GOES-R in numerical weather prediction
models is difficult to quantify at this point in time, it is reasonable
to assume that the impact will be at least as large as that seen from
current instruments in geostationary orbit.  In fact, the improved
spectral, temporal and spatial resolutions of the data should ideally
lead to even greater model forecast impacts.  Currently,  the impact of
in-situ and remotely-sensed observations is being studied quantitively
at CIMSS via model data denial experiments, using both regional and
global models supplied by NCEP.   The regional work has been ongoing for
several years, using NCEP\'s Eta Data Assimilation/Forecast System
(EDAS).  Recently, global studies have been initiated that use the
Global Forecast System (GFS). \
\
In the most recent regional work,  the impact of in-situ rawinsonde data
and remotely sensed geostationary and polar orbiting satellite data
routinely used in the EDAS was studied for extended length time periods
during four seasons.   The case studies chosen consisted of 15-day
periods during Fall 2001, Winter 2001/2002, Spring 2002 and Summer
2002.  The model runs included a control run, which utilized all data
types routinely used in the EDAS, and three experimental runs in which
either all rawinsonde, GOES or POES data was denied. Differences between
the experimental and control runs were then accumulated over the 15-day
periods and analyzed to demonstrate the 24 and 48-hr forecast impact of
these data types in the EDAS.   The diagnostics were computed over both
the entire horizontal model domain, and within a subsection covering the
continental United States and adjacent coastal waters (extended CONUS).\
\
The 24-hr domain-wide results showed that a positive forecast impact was
achieved from all three data sources during all four seasonal time
periods.  Cumulatively, the rawinsonde data had the largest positive
impact over both the entire model domain and extended CONUS.  However,
GOES data had the largest contribution for several fields, especially
moisture during summer and fall.  In general, GOES data also provided
larger forecast impacts than POES data, especially for the wind
components and moisture.\
\
In terms of global modelling studies, Observing System Experiments
(OSEs) with NCEP's Global Forecast System (GFS) are currently being
conducted to evaluate the impact of various operational observing
systems on NCEP's global forecasts.  Both winter and summer six week
periods are being evaluated, with the last four weeks being used to
generate forecast impact statistics.  In this work, the NCEP Global Data
Assimilation System (GDAS) is being run at the full operational
resolution of T254 (55 km) and 64 levels vertically.  Currently, all
Advanced Microwave Sounder Unit (AMSU) and High-resolution Infrared
Radiation Sounder (HIRS) observing system data are being evaluated by
denying each system separately in the GDAS.  Both systems for these data
consist of instrumentation on NOAA-15, -16 and -17.  In addition, denial
experiments for each AMSU instrument are planned.  The impact statistics
computed include the percent change in root mean square (rms) for sea
level pressure, and mandatory level (100-1000 hPa) relative humidity,
temperature and zonal wind.  In addition, geopotential height anomaly
correlation at 500 and 1000 hPa for both the Northern and Southern
Hemispheres is being evaluated, and tropical rms vector errors at both
200 and 850 hPa will be calculated.  Results indicate that the largest
forecast difference between the control experiment and the denied
experiment is obtained when denying AMSU data, and the differences
observed to this point are significantly larger than those seen in the
HIRS denials.  The AMSU impact is as large as a 40% improvement in state
fields on mandatory pressure levels, and an anomaly correlation
improvement of 0.1 for 500 hPa heights at forecasts longer than  8 days.

55\) **[An Objective Nowcasting Tool that Optimizes the Impact of
Geostationary Satellite Observations in Short-Range
Forecasts]{.underline}**

Ralph Petersen

Cooperative Institute for Meteorological Satellite Studies (CIMSS),

University of Wisconsin -- Madison

Madison, Wisconsin

Robert M. Aune

NOAA/NESDIS/ORA

NESDIS/Advanced Satellite Products Team,

Madison, Wisconsin

Future geostationary hyper-spectral instruments, such as the HES planned
for GOES-R, will have the sensitivity necessary to resolve atmospheric
features above and beyond the capabilities of today's geostationary
sounders. Although HES data will most likely generate improvements in
numerical forecast guidance out to 48 hours and beyond, a greater
benefit may come from the use of HES data in real time objective
nowcasting systems designed to assist forecasters with identifying
rapidly developing, small-scale extreme weather events. Such a system
will need to detect and retain extreme variations in the atmosphere,
incorporate large volumes of high-resolution asynoptic data from
satellites and other high-resolution systems, and be computationally
very efficient. Accomplishing this may require numerical approaches and
techniques that are notably different from those used in numerical
weather prediction where the forecast objectives cover longer time
periods. The nowcasting systems will need to place an emphasis on the
accuracy of individual observations and retaining the large gradients
seen in these data through time, and thereby serve as a means of
frequently updating more traditional numerical prediction models.

The basis for a new approach to objective nowcasting is presented that
uses LaGrangian techniques to optimize the impact and retention of
information provided by multiple observing systems. The system is
designed to detect extreme variations in atmospheric parameters and
preserve vertical and horizontal gradients observed in the various data
fields - with the goals of identifying details of the environments
associated with the onset of significant weather events several hours in
advance. Analytical tests of such an approach have been performed to
determine the ability of the method to retain gradients and extremes in
meteorological fields. These tests show that the technique is
computationally efficient, is able to retain sharp gradients and
observed maxima and minima, and has the capability of providing timely
updates to forecast guidance provided by operational forecast models.
Initial real data tests are currently being conducted with a
proof-of-concept prototype are being tested at the Cooperative Institute
for Meteorological Satellite Studies (CIMSS), University of Wisconsin
using full resolution (10 km) derived layer moisture products from the
GOES-10/12 sounders. Initial tests have focused on the use of
multi-layer GOES moisture data. Results of these tests will be shown
which focus on the ability of the proposed system to capture and retain
details important to the development of convective instability 3-6 hours
into the future, even after IR observations in the areas of severe
weather may no longer be available due to cloud development.

56\) [The Advanced Satellite Aviation-Weather Products Initiative for
Diagnosing and Nowcasting Weather Hazards for Improved Aviation
Safety]{.underline}

Wayne F. Feltz^1^, John R. Mecikalski^2^, John Murray^4^, Dave
Johnson^3^, Kristopher Bedka^1^, Sarah M. Thomas^1^, Anthony J.
Wimmers^1^, and Christopher C. Schmidt^1^

^1^Cooperative Institute for Meteorological Satellite Studies,
University of Wisconsin-Madison

^2^University of Alabama-Huntsville

^3^Research Applications Program, National Center for Atmospheric
Research

^4^NASA Langley Research Center, Norfolk, Virginia

A new NASA effort, the Advanced Satellite Aviation Weather Products
(ASAP) initiation, has been developed to provide satellite derived
meteorological products and expertise to the Federal Aviation
Administration (FAA) weather research community. University of
Wisconsin-Madison SSEC/CIMSS has been tasked to provide satellite
information to the NCAR-based Aviation Weather Research Program's (AWRP)
11 Product Development Teams (PDT).

Satellite derived products that ASAP will develop and provide to the
AWRP PDTs will be value-added information for forecasting/nowcasting
aviation hazards such as those caused by low ceiling/visibility,
convection, turbulence, icing, volcanic ash, and wind shear. Much of the
satellite data provided to NCAR will be infused into each PDT's unique
system for diagnosing a particular hazard. For ASAP in 2004 and beyond,
UW will collaborate with the University of Alabama in Huntsville and
NASA's Marshall Space Flight Center. This collaboration will bolster
UW's ASAP activities by offering expertise in data mining, pattern
recognition, as well as through introduction of other remote sensing
data sets (e.g., lightning). Phase 2 of ASAP activities will include
incorporation of hyperspectral satellite data (AIRS, CrIS, and HES)
products into the FAA PDT's aviation hazard algorithms. This poster will
present an overview of current ASAP research and products.

57\) **[Improvement in Groundbased Infrared Hyperspectral Retrieval of
Thermodynamic Profiles]{.underline}**

Wayne F. Feltz^1^, Hugh B. Howell^1^, David D. Turner^2^, Ralph G.
Dedecker^1^,

Harold M. Woolf^1^, Robert O. Knuteson^1^, Hank Revercomb^1^, and Kris
Bedka^1^

^1^Space Science and Engineering Center, University of Wisconsin -
Madison

Madison, Wisconsin

^2^Pacific Northwest National Laboratories (PNNL)

Richland, Washington

The United States Department of Energy\'s Atmospheric Radiation
Measurement (ARM) program has funded the successful development of the
Atmospheric Emitted Radiance Interferometer (AERI) instrument during the
past decade. This has led to a hardened, autonomous system that measures
downwelling infrared (IR) radiance at high-spectral resolution. Seven
Hyperspectral AERI systems have been deployed around the world as part
of the ARM program. The initial goal of these instruments was to
characterize the clear-sky IR emission from the atmosphere for
thermodynamic profiling, thus a temporal sampling was chosen (8-10 min
per spectrum) to minimize random noise in the AERI observations. Recent
research emphasis has been placed on the improvement of vertical
resolution and temporal sampling on AERI derived atmospheric boundary
layer thermodynamic profiles and cloud property retrievals.

Results indicate that the AERI derived temperature profiles more
accurately represent strong surface based temperature inversions common
through nocturnal radiative cooling with a higher vertical resolution
line-by-line fast model. AERI retrieval results from the International
H~2~0 Program (IHOP) demonstrate that improved vertical resolution of
temperature within the lowest one kilometer of atmosphere has been
achieved implementation of a new more accurate and higher vertical
resolution fast model. The University of Wisconsin-Madison deployed an
AERI instrument in its mobile AERIBago in 40-second rapid-scan mode
during the CRYSTAL-FACE experiment in southern Florida. Temperature and
moisture retrievals from the rapid-scan data also demonstrate
fluctuations in the boundary layer thermo-dynamic profile that are lost
due to averaging with the nominal sampling strategy. This poster will
present AERI thermodynamic retrieval progress with applications directly
linked to future GOES-R HES derived meteorological products.

58\) **[Lossless Data Compression Studies for NOAA Hyperspectral
Environmental Suite]{.underline}**

Bormin Huang, Hung-Lung Huang, Alok Ahuja, and Hao Chen

CIMSS, University of Wisconsin-Madison

Timothy J. Schmit and Roger W. Heymann

NOAA, National Environmental Satellite, Data, and Information Service

The Hyperspectral Environmental Suite (HES) aboard the next-generation
Geostationary Operational Environmental Satellite (GOES)-R in 2012 will
provide critical atmospheric, oceanic, land information. The sounder
will have high spectral resolution (over one thousand channels), high
temporal

resolution (1 hour), high spatial resolution (less than 10 km), and
hemispheric coverage. Given such a high volume of data, the use of
robust data compression techniques will be beneficial to data transfer
and archive. Unlike hyperspectral imaging data compression,
hyperspectral sounding data compression is desired to be lossless or
near-lossless to avoid potentially significant degradation of
geophysical retrievals.

Several state-of-the-art lossless compression schemes are studied,
including 3D wavelet-based EZW and SPIHT, 2D wavelet-based JPEG2000, 2D
predicton-based CALIC and JPEG-LS, and the 1D block-sorting-based
Burrows-Wheeler transform (BWT). A novel data preprocessing technique is
utilized to improve the compression gain for each scheme. Their
compression ratios for the AIRS hyperspectral sounding data are
presented.

59\) **[Lossy Data Compression and Retrieval Impact Studies for NOAA
Hyperspectral]{.underline}**

**[Environmental Suite]{.underline}**

Bormin Huang, Alok Ahuja and Hung-Lung Huang

CIMSS, University of Wisconsin-Madison

Timothy J. Schmit and Roger W. Heymann

NOAA, National Environmental Satellite, Data, and Information Service

The Hyperspectral Environmental Suite (HES) aboard the next-generation
Geostationary Operational Environmental Satellite (GOES)-R in 2012 will
scan the Earth nearly five times faster than the current GOES. The
sounder will provide the user community with about one hundred times the
amount of data currently provided. It will have higher spectral
resolution (over one thousand channels) and high spatial resolution
(less than 10 km). Given the unprecedented volume of data HES will
generate, the use of robust data compression techniques will be
beneficial to data transfer and archive. Hyperspectral sounding data
compression is desired to be lossless or near-lossless to avoid
potentially significant degradation of atmospheric state and surface
property retrievals. Lossy compression of hyperspectral sounding data
via JPEG 2000 and JPEG-LS is presented. The impact of lossy compression
on the retrieval of atmospheric temperature and absorbing gases profiles
is studied for various compression ratios.

60\) **[Preparing for GOES-R+ -]{.underline}**

**[Critical Role of A Vibrant Continuous Learning Program]{.underline}**

Anthony Mostek^1^, Mark DeMaria^2^ and Jim Gurka^2^

^1^NOAA/NWS, ^2^NOAA/NESDIS

As NOAA begins building the next generation of GOES, it may appear that
there is plenty of time to get operational users prepared for the
arrival of the new data and products. However, with the complex and

evolving nature of NOAA\'s operational environmental monitoring and
forecast programs, it is critical that a vibrant and continuous learning
program is already in place. To get NOAA users ready, the poster will
review the progress being made on the Satellite HydroMeteorology
(SHyMet) course. The SHyMet course will begin in 2005 and will continue
well into the GOES-R+ era. The SHyMet course will evolve to incorporate
new advances in both polar and geostationary platforms. The SHyMet
course is the final step in the development of a \"Proving Ground\"
system for NOAA operations. The \"Proving Ground\" will ensure that any
new products, techniques or algorithms are completely checked out and
that there is comprehensive training in place.