Principal Investigator:
Steven Ackerman
CIMSS Director
1225 W. Dayton
Cooperative Institute for Meteorological Satellite Studies (CIMSS)
University of Wisconsin – Madison
Madison, Wisconsin 53706
Program Manager/Co-I
Wayne F. Feltz University of Wisconsin-CIMSS
Co-Investigators:
Michael Pavolonis NOAA/NESDIS/ORA/UW-CIMSS (stationed at UW-CIMSS)
Liam Gumley University of Wisconsin-CIMSS
David Tobin University of Wisconsin-CIMSS
George Serafino NOAA/NESDIS/SSD/SAB DC VAAC
Team Partners:
Paul Herzegh NCAR
David Johnson NCAR
Jeffery Hawkins Navy Research Laboratory
Gary Ellrod NOAA/NESDIS
Gary Hufford NOAA/AAWU/VAAC
Andrew Tupper Darwin VAAC
John Zapotocny Air Force Weather Agency

Table of Contents
1.
Abstract
2.
Summary of Proposal Personnel and Work Efforts
3.
Decision Support Overview/Baseline
4.
Earth-Sun System Research Results
5.
Technical/Scientific/Management Section
6.
Transition Approach/Activities
7.
Performance Measures
8.
Anticipated Results/Improvements
9.
Schedule
10.
Statements of Commitment/Support
11.
Budget Details/Cost Plan
12.
Facilities and Equipment
13.
Curriculum Vitae: Principal Investigator
14.
each Co-Investigator
15.
Current/Pending Support
16.
References and citations
40
41
44
51
53
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20
20
21
21
23
32
3
4
5
7
2

This proposal aims to integrate and benchmark satellite-based best estimate volcanic ash location and altitude from current EOS and future NPP satellite imager/sounder data in a near real-time manner through Federal Aviation Administration (FAA), Volcanic Ash
Advisory Centers (VAAC), and military aviation forecast (Air Force Weather Agency
(AFWA) and Naval Research Laboratory (NRL)) decision support systems. This proposal would provide users of EOS satellite direct broadcast access to near real-time MODerateresolution Imaging Spectroradiometer/Atmospheric InfraRed Sounder (MODIS/AIRS) satellite derived products of volcanic ash properties using the International MODIS AIRS
Processing Package (IMAPP) package developed at the University of Wisconsin
Madison’s Space Science and Engineering Center/Cooperative Institute for Meteorological
Satellite Studies (UW-SSEC/CIMSS). This data is particularly important for the National
Airspace System (NAS) and international aviation systems to prevent catastrophic loss of commercial and military aircraft and lives including aviation over ocean at high latitudes were volcanic ash is a persistent threat.
Recent work at CIMSS has focused on developing robust automated satellite derived volcanic aerosol detection and height estimate algorithms using multi-spectral MODIS imager data (Pavolonis et al. 2005). These algorithms have been tested globally and the results have been compared to standard techniques, such as reverse absorption (e.g. split window technique, Prata 1989, Ellrod et al. 2003, Tupper et al. 2004). These algorithms have been shown to be more sensitive to the presence of volcanic aerosols, yet less prone to false alarms, than current standard operational algorithms. CIMSS scientists also have extensive experience using the CO
2
slicing technique (Wylie and Menzel 1989, Ellrod and
Schreiner 2004) to retrieve the height of volcanic clouds using MODIS. However, because the Visible/Infrared Imager/Radiometer Suite (VIIRS) will not have CO
2
absorption channels, CIMSS scientists have also developed a multi-spectral infrared 1DVAR optimal estimation (Heidinger et al. 2005, Pavolonis et al., 2005) approach to retrieve the height of volcanic plumes with MODIS. This 1DVAR algorithm, which only uses channels that will be available on VIIRS, also simultaneously retrieves particle size and optical depth. This proposal would provide users of EOS satellite direct broadcast (AIRS/MODIS) access to near real-time MODIS/AIRS satellite derived products of volcanic ash properties using the
International MODIS AIRS Processing Package (IMAPP) package developed at UW-
SSEC/CIMSS. UW-SSEC/CIMSS has been charged by NASA/IPO to provide this package for free distribution to all Direct Broadcast (DB) sites internationally (over 100 sites including high latitude volcanic zones in eastern Russia, Japan, and Alaska). IMAPP provides MODIS and AIRS calibrated radiances and atmospheric products, but currently does not contain volcanic ash location and height estimate logic. Derived in near real-time
(~5-15 minutes) at DB sites during Terra (MODIS) and Aqua (MODIS/AIRS) overpass time, the volcanic ash products will include ash location, altitude, and optical properties important for driving dispersion models such as VAFTAD/Hysplit and for general volcanic ash advisories. The IMAPP volcanic ash products will also help multiple agencies
(teaming partners include VAACs, FAA, NRL, AFWA) that have direct broadcast
3

capabilities for monitoring volcanic ash in aviation airways, particularly at high latitudes where polar orbiting temporal resolution is sufficient for near-realtime product generation.
The Principal Investigator (PI) for this project will be Dr. Steve Ackerman, CIMSS
Director, who has extensive scientific knowledge of infrared cloud, aerosol, and volcanic ash properties. As PI for the EOS MODIS cloud mask, Dr. Ackerman would bring a wealth of narrow-band (MODIS/VIIRS) and hyperspectral (AIRS/CrIS) scientific experience to the proposed work. Dr. Ackerman will be the overall project lead and will also be responsible for directing and monitoring activities at UW-CIMSS. Wayne Feltz will be the Program Manager and a Co-I for the proposal. For the last three years Mr. Feltz has lead the NASA funded Advanced Satellite Aviation-weather Product (ASAP) effort at
UW-CIMSS for the last three years, directing a group of researchers/scientists toward the goal of using current derived satellite based meteorological products to improve forecasting of aviation weather hazards through the Federal Aviation Administration (FAA) Product
Development Teams. Mr. Feltz will be responsible for directing, collaborating, and the transition of all proposal related activities among other CIMSS researchers and the
Decision Support System (DSS) teaming partners described below. Mr. Feltz will oversee day-to-day funding and labor management towards successful completion of this proposal work.
The following CIMSS research scientists will provide the necessary components for successful transition of the volcanic ash detection methodology from research to operations:

Mr. Michael Pavolonis NOAA/NESDIS stationed at CIMSS – volcanic ash infrared remote sensing expert will provide MODIS based volcanic ash science logic and oversee implementation of code into IMAPP

Mr. Liam Gumley CIMSS/SSEC – leader and program manager of International
MODIS/AIRS Processing Package (IMAPP) will provide skills and knowledge to implement volcanic ash location and height assessment within the freely available
IMAPP code. He will oversee a research programmer and MODIS volcanic ash algorithm validation expert during the transition process

Dr. David Tobin CIMSS/SSEC – infrared hyperspectral resolution radiation expert, has extensive experience retrieving and validating atmospheric parameters from infrared spectra. Dr. Tobin will guide use of hyperspectral observations for volcanic aerosols detection.
Co-I Mr. George Serafino, Branch Chief of the NOAA/NESDIS/SSD/Satellite Analysis
Branch will provide end-user feedback from the Washington DC Volcanic Ash Advisory
Center (VAAC). The Washington DC VAAC has extensively collaborated with CIMSS researchers on the current case studies using the improved volcanic ash retrieval logic. Mr.
Serafino and others at the Washington DC VAAC will evaluate the utility of the improved ash property information using the IMAPP software package and the NASA EOS “bentpipe” delivery of MODIS/AIRS data, improving global EOS satellite data timeliness from the NASA Goddard DAAC.
4

Other team partner end-users include Gary Hufford (Alaska NOAA/AAWU/VAAC), Dr.
Andrew Tupper (Senior Scientist at the Darwin VAAC), Dr. Paul Herzegh, (NCAR volcanic ash lead for the Ocean Weather Product Development Team (FAA OW PDT)),
Jeffery Hawkins (Senior Scientist Naval Research Laboratory (NRL)), and John Zapotocny
(Chief Scientist Air Force Weather Agency (AFWA)). All have sent letters of commitment and support (enclosed in proposal) for the work proposed. They have committed to incorporating the IMAPP software package into their existing system for improvement of hazardous volcanic ash detection and height estimates.
The national priority for the proposed project is aviation safety with a specific emphasis on airline routes over-ocean where limited emergency landing options exist when volcanic ash is encountered. This effort also supports the Air Force and Naval forecast branches where volcanic ash can be a persistent threat in their operational arenas.
Volcanic ash suspended in the atmosphere poses significant threats to the aviation community. These threats include loss of life and the severe damage to aircraft that can occur from airborne encounters with volcanic ash. Volcanic ash detection, height estimates, and the forecasting of the position of volcanic eruption clouds are necessary to ensure aircraft and passenger safety. Current volcanic ash information end-users include the Volcanic Ash Advisory Centers (VAACs), Air Force Weather Agency (AFWA), and
Naval Research Laboratory (NRL), all are responsible for dispensing near real-time warning of volcanic ash contaminated airspace to commercial and government aviation agencies.
The three end-user groups targeted for this proposal include:
1) Volcanic Ash Advisory Centers: The MODIS/AIRS volcanic ash product algorithm would be directly implemented within the NOAA Washington DC VAAC system using direct NASA fiber optic feed. This arrangement would provide data with lower time latency due to lack of direct broadcast data feed (and NASA preprocessing) but more universal access to VAAC’s for data anywhere in the world. This stepup would also allow more access points for the VAAC’s via McIDAS (Lazzara et al., 1999) or Advanced
Weather Interactive Processing System (AWIPS) and allow viewing of any worldwide volcanic ash properties.
2) NRL/AFWA Agencies: Another research to operations pathway is via the Naval
Research Laboratory and the newly consolidated global aviation research hub in the former research center in Norfolk. The Air Force Weather Agency acts as a backup to the
Washington VAAC so a consistent methodology would be implemented at AFWA. UW-
CIMSS would help transition the software to AFWA and NRL through established collaborations.
5

3) Direct Broadcast sites: The IMAPP package is freely available to over 100 international
DB sites including many near areas of frequent volcanic activity including Japan and
Russia.
IMAPP will be the decision support tool that will be extended to include volcanic ash property information. This proposal provides users of EOS satellite direct broadcast
(AIRS/MODIS) access to near real-time (<10 minutes after overpass time) MODIS/AIRS satellite derived products of volcanic ash properties using IMAPP released by UW-
SSEC/CIMSS. Mr. Liam Gumley is the IMAPP development lead at UW-SSEC/CIMSS and has been charged by NASA/IPO to provide this package for free distribution to all
Direct Broadcast (DB) sites internationally ( Figure 1 ). Volcanic ash detection is especially
important for the DB sites located near the “volcanic ring of fire” aviation routes of eastern
Russia, Japan, and Tropical Western Pacific.
Figure 1: Global map showing over 100 X-band direct broadcast sites registered with NASA.
IMAPP provides MODIS/AIRS calibrated radiances and atmospheric products but currently provides no volcanic aerosol property estimates. The volcanic ash properties will be derived in near real-time at DB sites during Terra (MODIS) and Aqua (MODIS/AIRS) overpass times including ash location, altitude, and optical properties important for driving dispersion models such as VAFTAD/Hysplit and for general volcanic ash advisories. The
IMAPP software will be able to provide McIDAS areas (system currently used at the
Washington, Alaska, and Darwin VAAC’s), HDF, or N-AWIPS so imagery can be quickly made available. The IMAPP volcanic ash products will also help multiple agencies
(NOAA, NRL, AFWA, and volcanically active DB locations) that have direct broadcast capabilities for monitoring volcanic ash in aviation airways, especially at high latitudes where temporal resolution is optimal. For more information on IMAPP: http://cimss.ssec.wisc.edu/~gumley/IMAPP
6

End-users typically receive volcanic ash location from qualitative evaluation of satellite imagery, pilot reports, or visual ground to air reports. Once a volcanic ash cloud location is obtained, an estimate of height is needed as trajectory model input, so short-term forecasts can be provided to aviation interests. Volcanic ash cloud heights can be estimated using both space-borne and ground based techniques. At present, the most common methodology for ash cloud height estimation is correlating atmospheric profiles with infrared brightness temperatures (BT) retrieved from satellites (Holasek et al., 1996;
Sawada, 1987; Oppenheimer, 1998; Prata and Grant, 2001; Sawada, 2002; Tupper et al.,
2004). This method consists of comparing BTs retrieved from the ash cloud (normally utilizing the 11
 m window channel) with the local atmospheric temperature profile. The altitude at which the retrieved BT matches the atmospheric temperature profile is considered to be the height of the ash cloud. Oppenheimer (1998) and Prata and Grant
(2001) suggest there are several potential limiting factors to this technique, however.
These factors include assumptions made about the emissivity of volcanic ash, inaccuracies with the local atmospheric temperature profiles (often based on NWP model background fields), and potential ‘undercooling’ of stratosphere piercing clouds.
Our goal is to provide improved and automated objective MODIS/AIRS estimates of volcanic ash location and height within ten minutes of EOS Terra/Aqua overpass using the
IMAPP software. This software will be implemented at all teaming partner locations and freely available to any DB site internationally.
This proposal aims to provide best estimate volcanic ash locations and altitudes from current EOS and future NPP infrared satellite data (MODIS/AIRS transition to
VIIRS/CrIS) in a near real-time manner through the Federal Aviation Administration,
Volcanic Ash Advisory Centers, and military aviation forecast decision support systems.
This work is specifically important to the NAS to prevent catastrophic loss of commercial and military aircraft and lives including aviation over oceans at high latitudes were volcanic ash is a persistent threat.
Because of its high spatial resolution and many visible, near-infrared, and infrared channels, the MODIS instrument is a very valuable volcanic ash imaging and detection tool
(Hillger and Clark, 2002; Ellrod et al., 2003). On the Aqua platform, information from
MODIS can be supplemented with data from the Atmospheric Infrared Sounder (AIRS), which offers increased sensitivity to trace gases like SO
2
with day/night independence
(Schreiner et al., 2004). The MODIS/AIRS configuration is also a prototype for the
Visible/Infrared Imager/Radiometer Suit (VIIRS)/Cross-track Infrared Sounder (CrIS) imager/sounder system, which will be part of NASA's NPOESS Preparatory Project (NPP), tentatively scheduled for launch in 2008. After the launch of NPP, the VIIRS and CrIS will be the next generation operational polar-orbiting imager/sounder. Many algorithms developed for MODIS/AIRS can also be applied to VIIRS/CrIS. These instruments are particularly useful for high latitude volcano applications due to the greater temporal sampling.
7

NASA's innovative active sensors on the CALIPSO and CloudSat platforms will offer a unique opportunity to validate passive measurement ash detection capabilities and optical depth retrievals, especially in the high latitudes given the greater frequency of overpasses.
Only official CloudSat, CALIPSO, and the Ozone Monitoring Instrument (OMI) products will be used in this project. The Terra Multiangle Imaging SpectroRadiometer (MISR) stereographic cloud top estimates will also be used to provide another source of comparison/validation with the proposed infrared estimates.
Background/Objectives
In the past 30 years, more than 105 encounters of aircraft with airborne volcanic ash have been documented, with 25% of those encounters resulting in significant damage and/or engine failure (Miller and Casadevall, 2000). Fortunately, there have been no fatalities, but the financial impact of such encounters has been significant. For instance, damage in the past 15 years has been estimated at more than $250M. Regions far from volcanoes are also at risk, as volcanic aerosols could be present well over 1000 km away from the source volcano (e.g. Rose et al., 2004). Many of these encounters could have been prevented with more advanced use of satellite data to detect and monitor volcanic aerosols.
Current operational volcanic ash detection techniques used at the VAAC's are qualitative and require manual analysis. These qualitative techniques rely on a variety of imaging products from instruments such as MODIS, the Advanced Very High Resolution
Radiometer (AVHRR), and various geostationary imagers. Regardless of the instrument, reliance on qualitative techniques presents some problems. For instance, even significant eruptions may not be identified in a timely manner using qualitative techniques, if the eruption is unexpected and the volcano is unmonitored. The May 10, 2003 eruption of
Anatahan in the Northern Mariana Islands, which was thought to be an inactive volcano, was an example of a significant eruption that could have been identified very early by automated techniques, but was not noticed until 4 hours after the eruption due to reliance on manual analysis. Current operational techniques are also not particularly sensitive to volcanic aerosol plumes that are mixed with cloud water or gaseous SO
2
/H
2
SO
4
plumes, and false alarm rates can also be high, especially in the high latitudes (Pavolonis et al.,
2005b). Auto-generated volcanic aerosol detection products should not be a substitute for qualitative techniques used by trained analysts, but should be used as a complementary information source that can help increase the timeliness and accuracy of volcanic aerosol advisories.
Besides knowing the location of the volcanic ash clouds, it is also important to know where volcanic ash is located in the vertical, especially at aircraft cruising altitudes. The vertical location of ash also influences dispersion, hence accurate forecasts of the location of ash are highly dependent on knowing the correct plume height. At present, operational estimates of ash height are limited to surface and aircraft observations that are only accurate during the day, infrared window-based satellite methods, and wind correlation techniques. In order to use the wind correlation technique, volcanic cloud drift is
8

observed in a sequence of satellite images, and global model or rawinsonde wind fields are used to find the height of the wind vector inferred from the cloud drift. When the atmosphere exhibits directional shear and the volcanic cloud is observed via geostationary satellite (e.g. tropics and mid-latitudes), this can be an accurate approach, but because of the inherent limitations, cannot be relied upon in all situations. Further, the infrared window-based technique is only accurate for opaque clouds which is often the case for volcanic ash clouds. This result is due to the fact that the cloud top temperature, which can be converted into a height, is determined by simply matching the observed 11 um brightness temperature with a location in a radiosonde or model profile.
Thus, more advanced satellite-based techniques are needed to determine the height of volcanic clouds.
Cloud optical depth, particle size, and composition also affect the residence time and dispersion of volcanic clouds. Information on optical depth, particle size and composition is not currently utilized in operational volcanic aerosol dispersion model forecasts. Large concentrations of volcanic gases such as SO
2
may also be an aviation hazard; however, large concentrations of silicate ash and SO
2
are not always co-located. In order to provide a good estimate of all of the above parameters, a combined imager/sounder approach is needed. A quality volcanic aerosol mask is also needed to properly retrieve plume height, particle size, and optical depth at the pixel-level. The volcanic aerosol mask can only come from an automated detection system if these retrievals are to be done in near realtime.
Given the limitations in current operational techniques, we propose the following:
1.
Use the MODIS to automatically identify pixels containing volcanic ash plumes or meteorological clouds that are contaminated with volcanic ash and/or SO
2
and
H
2
SO
4
.
2.
Determine the height and emissivity of volcanic clouds from MODIS infrared measurements.
3.
Expand the current height retrieval techniques to more accurately account for the cloud particle size and shape distribution. An accurate cloud height determination is needed by the VAAC's in order to improve dispersion forecasts.
4.
Validate the MODIS volcanic aerosol mask, cloud heights, and emissivity retrievals against any volcanic aerosol cases observed by CloudSat/CALIPSO and use FAA OW PDT, VAACs, and NRL/AFWA as testbeds for validation.
5.
Incorporate all of the above products into the International MODIS/AIRS
Processing Package (IMAPP) allowing international conduit to Direct Broadcast site providing near real-time product creation.
6.
Use the AIRS to help validate and improve all MODIS volcanic cloud remote sensing techniques and to demonstrate combined imager/hyperspectral sounder techniques consistent with future operational capabilities expected with the
VIIRS/CrIS combination upon the launch of NPP and NPOESS.
9

7.
Transition the IMAPP volcanic ash products to make them compatible with the
NPP/NPOESS VIIRS/CrIS instrument.
Volcanic Cloud Detection
Current satellite-based volcanic cloud detection techniques most often utilize the reverse absorption technique (Prata 1989a, 1989b). The imaginary index of refraction, which is directly proportional to absorption/emission strength for a given species composition and particle distribution, is used for this technique. Because the imaginary index of refraction of volcanic ash (taken to be andesite mineral, Pollack et al., 1973) is larger near 11
 m than 12
 m, the 11
 m minus 12
 m brightness temperature difference (hereafter
BTD[11,12]) will be negative for a non-opaque volcanic ash cloud, as long as atmospheric water vapor does not mask the signal. In contrast, clear sky, non-opaque water clouds, and non-opaque ice clouds tend to have positive BTD[11,12] values. These properties form the basis of the reverse absorption technique, which in large part seeks to identify negative BTD[11,12] values. The reverse absorption technique, in its various forms, is the tool most commonly used by VAAC analysts. While the reverse absorption technique works well for many eruptions, it has several limitations, which are well understood and have been well documented (e.g. Prata et al., 2001). These limitations are as follows: (1) Strong surface-based temperature inversions may cause the
BTD[11,12] to be negative. (2) When viewing barren surfaces (e.g. deserts or bare mountains) under clear sky conditions, the BTD[11,12] can be negative. The same result can occur when viewing certain non-volcanic mineral-based aerosols (e.g. dust storm particles). (3) Ice cloud tops that overshoot the tropopause or liquid water or ice clouds that are opaque can have negative BTD[11,12] values. (4) Instrument noise and channel misregistration may cause a negative BTD[11,12]. (5) Volcanic ash clouds that are opaque or ash clouds mixed with a significant amount of cloud water will have a positive
BTD[11,12]. (6) High tropospheric water vapor burdens can mask the negative
BTD[11,12] signal when viewing an ash cloud that would have had a negative
BTD[11,12] in a drier atmosphere.
The goal when developing our volcanic cloud detection techniques was to offset each of the above limitations as much as possible by supplementing a form of the reverse absorption technique with additional spectral information. In summary, we have demonstrated that our detection methods are more sensitive to volcanic ash, yet less prone to false alarms compared to the standard reverse absorption method (Prata and
Grant, 2001)
During the day, a four-channel algorithm is used to detect the presence of volcanic aerosols, in particular airborne volcanic ash, in an automated pixel-by-pixel manner. A detailed discussion of the algorithm is given in Pavolonis et al. (2005b) and a brief summary is given here. The four-channel algorithm is physically based (not statistical in nature) and utilizes spectral channels centered near 0.65
 m, 3.75
 m, 11
 m, and 12
 m.
These channels are common to most current passive satellite instruments. Based on the optical properties of volcanic ash, assumed to be andesite mineral as in many previous studies, spherical liquid water droplets, and non-spherical ice crystals, the following
10

properties can be inferred. For a single layer liquid water cloud, ice cloud, and a volcanic ash cloud of the same optical depth: (1) The 0.65
 m reflectance (R[0.65]) of liquid water and ice clouds will tend to be greater than the R[0.65] for volcanic clouds, (2) Liquid water and volcanic clouds will often have similar reflectance values at 3.75
 m (R[3.75]), while both tend to be more reflective than ice clouds, (3) Thus, the ratio of
R[3.75]/R[0.65] (RAT[3.75,0.65]) for volcanic clouds will usually be greater than
RAT[3.75,0.65] for liquid water and ice clouds, (4) Very cold clouds (e.g. BT[11] < 233
K) that have a R[3.75] that is typical of a liquid water cloud, are likely heavily contaminated with aerosols, consistent with a volcanic eruption, (5) Non-volcanic dust aerosols tend to be warmer and have a smaller RAT[3.75,0.65] than volcanic aerosols.
Based on these properties, a robust threshold approach tests for the presence of volcanic ash. The thresholds are determined as a function of viewing and illumination geometry, surface type, and climate regime (e.g. tropical, mid-latitude, and polar) using radiative transfer model simulations and actual satellite measurements.
The four-channel algorithm was applied to Aqua MODIS data that captured an eruption
of Manam, Papua New Guinea (PNG) on October 24, 2004 (Figure 2). This eruption
occurred in a very moist environment. In the true color image (top, left panel), the volcanic ash dominated cloud appears brown. In the bottom left panel, the results of the new four-channel algorithm are overlaid, and in the bottom right panel pixels with a BTD
[11,12] < 0.0 K are highlighted. Thus, the bottom right panel is a representation of the current operational approach (note: current operational can have this capability). Finally, the top right panel shows a colorized BTD[11,12] image. The four-channel algorithm produces a mask with two volcanic cloud categories, ash-dominated and ice clouds that may be contaminated with volcanic aerosols. The standard reverse absorption algorithm is only able to detect a small portion of the core of the ash-dominated cloud. The new algorithm permits BTD[11,12] values that greatly exceed 0.0 K, which noticeably enhances the mask product compared to the standard method. The Pavolonis et al. algorithm also flags a large region adjacent to the main ash cloud as being an ice cloud contaminated with volcanic aerosol. This result cannot be verified by simply analyzing the true color imagery, so independent AIRS data were consulted to look for SO
2
levels
(SO
2
can be released in large quantities during volcanic eruptions). AIRS SO
2
imagery obtained from http://toms.umbc.edu
(not shown) indicates that this ice cloud region is characterized by a very large SO
2
signal. This cloud may or may not contain silicate ash, but nevertheless is a hazard to aviation in and of itself due to the corrosive nature of clouds with high SO
2
concentration. We plan on generating similar SO
2
products from
AIRS. Finally, the reverse absorption technique produces scattered false alarms associated with convective clouds while the four-channel algorithm produces no noticeable false alarms.
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Manam
Figure 2: A four-panel image showing an Aqua MODIS scene with a volcanic cloud produced from an eruption of Manam, PNG. The image is from October 24,
2004 at 03:55 UTC. A) a 1-km true color image created using the 0.65
 m, 0.56
 m, and 0.47
 m channels B) a color-enhanced 11
 m – 12
 m brightness temperature difference image C) the same as Panel A, except the results of the four channel volcanic cloud detection algorithm are overlaid D) the same as Panel
A, except the results of the reverse absorption detection algorithm are overlaid.
To further illustrate the ability of the four-channel algorithm to reduce alarms compared to the standard reverse absorption technique, a full day of descending node MODIS data was analyzed. A day on which there was little or no volcanic activity according to the
Smithsonian/United States Geological Survey weekly report
(http://www.volcano.si.edu/reports/usgs) was chosen to determine a rough false alarm
rate and to determine the cause of false alarms. Figure 3 shows the fraction of MODIS 1-
km pixels within a 0.5
o equal-area box that were classified as a volcanic cloud by the four-channel algorithm on the left. The same analysis for the standard reverse absorption technique is shown on the right. The four-channel algorithm produces only sporadic, generally low magnitude, false alarms. In contrast, the reverse absorption algorithm produces numerous false alarms. Globally, 0.06% of the total number of pixels tested positive for volcanic clouds using the four-channel algorithm, compared to 5.62% for the reverse absorption algorithm. The reverse absorption algorithm tends to classify nonvolcanic aerosols, opaque clouds, and clear sky in the polar regions as volcanic ash,
12

whereas the four-channel algorithm is most vulnerable to misclassifying meteorological cloud edges.
Figure 3: The fraction of Terra MODIS 1-km pixels within a 0.5
o equal-area grid box that were classified as a volcanic cloud by the four-channel algorithm are shown on the left. The results from the standard reverse absorption technique are shown on the right. Results from all descending node granules on April 4, 2003 are shown. These images are an indication of false alarm rate since no volcanic eruptions were reported on this day or the previous few days.
With no reflective channel data available, satellite-based detection of volcanic ash at night is much more challenging. To improve upon the standard reverse absorption technique, thermal infrared data from the 3.75
 m, 6.7
 m, 7.4
 m, and 8.5
 m region are utilized in addition to the BTD[11,12]. In order to reduce the number of false alarms associated with the standard reverse absorption technique, information from the 3.75
 m channel is used to create a tri-spectral approach that works as follows. Volcanic clouds must not only have small (positive) or negative BTD[11,12] values which are also typical of clear sky inversions or opaque meteorological clouds, but a large 3.75
 m – 11
 m brightness temperature difference, which is typical of cirrus clouds. This set of spectral conditions is not normally associated with meteorological clouds or clear sky, but is
typical of volcanic ash clouds. An example of this is shown in Figure 4 for the March 09,
2005 eruption of Mount St. Helens. In addition, volcanic clouds that are rich in cloud water (liquid or ice) or those that are mainly composed of SO
2
/H
2
SO
4
are best detected using other methods. For instance, the 8.5
 m and 11
 m band combination is useful for detecting SO
2
rich volcanic clouds or volcanic clouds that are rich in ice. These bands are best utilized by subtracting the observed radiance from the clear sky radiance, calculated using a transmittance model and a model profile, for each channel. The clear minus observed difference for the 8.5
 m channel is then subtracted from the clear minus observed difference for the 11
 m channel. If this quantity is less than some threshold, a
13

volcanic cloud is deemed to be present. This type of approach is effective because large
SO
2
amounts are not taken into account in the clear sky calculations and the 8.5
 m channel is more sensitive to SO
2
than the 11
 m channel. Similar tests can be performed with other channel combinations such as 7.4
 m and 11
 m to add more confidence to the mask. We should also note that we plan on adding nighttime infrared-only tests to the four-channel daytime algorithm to further increase performance.
Figure 4: A two-panel image showing a NOAA-17 AVHRR scene with a volcanic cloud produced from a small eruption of Mount St. Helens, WA. The image is from
March 9, 2005 at 05:05 UTC. Shown on the left is a 1-km two-channel (3.75
 m and
11
 m) RGB image. Shown on the right is the resulting pixel level cloud type produced from an automated algorithm. Volcanic ash clouds are shown in gray.
Throughout the development of our detection algorithms, we have been collaborating with members of the Washington, D.C. VAAC who have been supplying us with difficult case studies. As an example of such a case study, a warning statement on the October 1,
2005 eruption of Santa Ana, El Salvador was not issued immediately because the volcanic cloud was mistaken for a thunderstorm based on the VAAC’s current detection capabilities. However, the Pavolonis et al. technique was able to unambiguously identify the eruptive cloud shortly after the eruption using GOES-12 data. Even when current techniques are effective, our new detection techniques provides complementary information that will aid in volcanic aerosol forecasts and warnings.
Volcanic Cloud Height Determination
Identifying the height of a volcanic cloud from satellite observations can be very difficult, particularly when the cloud is semi-transparent. One method for retrieving the height of semi-transparent clouds is the CO
2
absorption (alternatively termed CO
2
slicing) technique (e.g. Wylie and Menzel, 1989, Platnick et al., 2003), which utilizes infrared channels dominated by CO
2
absorption to determine cloud top temperature. The CO
2 slicing technique is especially sensitive to high cloud. The method relies on the strong temperature sensitivity of the 15
 m CO
2
absorption band and the well-mixed nature of carbon dioxide in the atmosphere. The CO
2
Slicing equation is as follows:
14


I
I ( v
1
( v
2
)  I cl
)  I cl
( v
1
)
( v
2
)

N  ( v
1
)
 p s p c  ( v
1
, p )
N  ( v
2
)
 p c p s
 ( v
2
, p )

1
, T ( p )
2 dp
, T ( p )
 dp dp dp

(1) where I is the measured radiance at the spectral region v
1
, the subscripts reference the two channels selected for the retrieval. I cl is the clear sky radiance measured at the satellite,

(v) is the cloud emissivity at the channel frequency, N is the cloud fraction, p c is the cloud pressure, p s is the surface pressure,
 ( v
1
, p ) is the spectral transmittance between the pressure levels p to the instrument, and B(v,T(p)) is the Plank radiance for the selected channel frequency at pressure level p where T(p) is atmospheric temperature at pressure level p . In the current application, both I cl
(v) and
 ( v , p ) are computed using an appropriate clear-sky radiative transfer model and temperature and moisture profiles.
The CO
2
slicing retrieval assumes the cloud effective emissivity ( N

) difference between spectrally close channels is negligible. With this assumption Equation 1 becomes independent of the cloud/aerosol effective emissivity. The cloud/aerosol height is then determined by selecting the pressure that minimizes the difference between the right and left side of Equation 1.
Unfortunately, many current satellite imagers do not have CO
2
absorption channels (e.g.
AVHRR, MTSAT). Also the VIIRS, which is scheduled to be the next operational imager on NPOESS (~2008 launch), will not have CO
2
slicing channels. In addition, given the atmospheric weighting functions of the CO
2
channels, the CO
2
slicing technique is generally not sensitive to clouds that reside below about 700 hPa. Given these facts, it would be useful to have a method for retrieving the height of semitransparent clouds to complement the CO
2 slicing technique (especially for low clouds) on instruments that have CO
2
channels and to replace the CO
2
slicing method on imagers that do not have CO
2
absorption channels. An algorithm recently developed for the
Extended Clouds from AVHRR processing system (CLAVR-x) (Heidinger et al. 2004;
Heidinger and Pavolonis 2005; Pavolonis and Heidinger, 2005a) may address this void.
The CLAVR-x algorithm, which is also referred to as the “split window” algorithm, uses infrared window observations near 11
 m and 12
 m to simultaneously retrieve cloud top temperature (which can be converted into cloud top height) and cloud emissivity at 11
 m using an optimal estimation approach (e.g. Marks and Rodgers 1993). The split window technique operates under the premise that for a known atmospheric state, surface temperature, and surface emissivity, the 11
 m and 12
 m measurements for a single layer cloud are primarily determined by three factors: (1) Cloud temperature, (2) Cloud emissivity, and (3) Cloud particle size and shape distribution (including thermodynamic phase). The radiative effect of the particle size and shape distribution is captured in the quantity

(Parol et al., 1991), a ratio of the 12
 m and 11
 m cloud emissivities. If the cloud type (volcanic cloud/aerosol included) of an individual pixel is determined a priori, a reasonable assumption about the particle distribution can be made, leaving only the
15

cloud temperature and emissivity to be retrieved within the optimal estimation system from the measured 11
 m and 12
 m radiances. The resultant cloud temperature can then be matched to a pressure and/or height within a radiosonde or model profile, as occurs in the CO
2
slicing technique. To determine cloud type the techniques of Pavolonis and Heidinger (2004), Pavolonis et al. (2005a), Pavolonis and Heidinger (2005), and
Pavolonis et al. (2005b) are used to classify satellite pixels as having fog, liquid water cloud (fog not included), supercooled water cloud, opaque ice cloud, cirrus cloud, multilayered cloud, volcanic ash-dominated aerosol cloud, or volcanic ash mixed with significant ice. The cloud type is also used to determine the first guess estimate of cloud temperature and emissivity in the optimal estimation scheme.
Figure 5 shows the cloud heights retrieved from the MODIS CO
2
slicing technique
(Platnick et al., 2003) and the CLAVR-x split-window algorithm for the October 24,
2004 eruption on Manam, PNG that was shown earlier in Figure 2. The results in Figure
5 indicate that the CO
2
slicing algorithm tends to position high clouds higher and the split-window algorithm tends to position low clouds higher. This result is expected given the known sensitivities of each algorithm. The MODIS CO
2
channel weighting functions peek in the middle and upper troposphere and are not very sensitive to these lower clouds. When the difference between the observed CO
2
channel radiance and the clear sky calculated radiance is within the instrument noise level, as is usually the case for lower tropospheric clouds, the CO
2
slicing method is not used and an infrared window look-up is used instead. This infrared look-up will underestimate the cloud height for non-opaque clouds, as is the case in this scene. Studies presented in Heidinger and
Pavolonis (2005) indicate that the split-window algorithm, while very sensitive to the emissivity of high clouds, is more sensitive to the temperature of low clouds unless the
 factor is very accurately parameterized. Current efforts are aimed at improving the parameterization of

and the first guess for cirrus clouds in order to put the retrieved height more in line with the CO
2
high cloud heights. Nevertheless, a combined CO
2 slicing/split-window product may produce the most accurate representation of cloud height.
The decrease in spectral width of high spectral resolution infrared measurements results in narrower weighting functions offering the potential for improved vertical resolution of CO2 slicing method (Smith and Frey, 1990). However, the large increase in the number of channel pairs introduces the added complexity of selecting optimal CO
2
Slicing channel pairs, which are dependent on the cloud/aerosol height. The optimal channels are ones that have significant cloud/aerosol signal while reducing the sensitivity to the lower atmospheric emission that dominates the uncertainties in the clear-sky calculation.
Holz et al (2005) developed the CO
2
sorting method, which is designed to select the optimal channel pairs for CO2
2
Slicing using hyperspectral infrared measurements in the
15
 m CO
2
band (680 – 770 cm
-1
). Holz et al (2005) demonstrated that when CO
2
Sorting is combined with CO
2
Slicing there is an improvement in the retrieved cloud height when compared to coincident lidar observation for optically thin clouds (total optical depths less then 1.0).
16

Figure 5: The results of the MODIS CO
2
slicing (left) and split-window (right) cloud height (top) and emissivity (bottom) retrievals for the October 24, 2004
Manam, PNG scene (same scene as in Figure 2).
The accuracy of both height retrieval techniques needs to be thoroughly evaluated via comparison to independent and more accurate references of cloud height. Once such reference is provided by stereoscopic heights (Moroney et al., 2002 and Muller et al.,
2002) from MISR on the Terra platform. Unlike infrared-derived heights, the MISR heights will be a better representation of the cloud top, since the MISR measurements are nearly insensitive to the vertical distribution of water in the cloud. These comparisons are already underway (Richards et al., 2006) for volcanic ash.
In addition to the MISR comparisons, we will also compare the MODIS CO
2
slicing and split-window retrievals to the AIRS CO
2
slicing/sorting technique described earlier.
Finally, with the anticipated launch of CALIPSO/CloudSat (Stephens et al., 2005), we will use any volcanic cloud cases observed by the cloud radar and lidar instruments on these platforms to further validate the CO
2
slicing and split-window techniques.
To take full advantage of the MODIS spectral resolution, we plan on improving cloud height/emissivity retrievals to better account for the ash cloud particle distribution. In the
CO
2
slicing technique, it is assumed that the emissivity of clouds is constant across the 11
 m window and the longwave CO
2
absorption bands. This assumption may not always be valid. Current work has focused on eliminating the gray body assumption by determining the relationship between the emissivity in channel pairs as a function of
17

cloud type. To improve the split window algorithm, 8.5
 m (channel 29) MODIS data can be added to the optimal estimation retrieval so that the

factor (i.e. the ratio of the 12
 m and 11
 m cloud/aerosol emissivity), which depends on the particle size distribution, may be retrieved along with the ash plume temperature and 11
 m emissivity. This can be accomplished by simply relating the ratio of 8.5
 m and 11
 m emissivity to

. Such a relationship will allow for a more accurate assumption concerning the effect of the particle distribution on the retrieval. This work, too, is in progress and funded under a separate project.
Management Approach:
Dr. Steve Ackerman and Mr. Wayne Feltz will conduct overall management of proposal
goals. Figure 6 provides the Integrated System Solution flowchart for this EOS satellite
derived volcanic ash product effort. The specific management approach proposed is:
Year 1:
UW-CIMSS researchers will use MODIS radiances to automatically identify pixels containing volcanic ash plumes or meteorological clouds that are contaminated with volcanic ash and/or SO
2
and H
2
SO
4
. UW-CIMSS will integrate the volcanic ash detection methodology into the IMAPP software. This will include close day-to-day collaboration between the scientists that have developed the current ash detection software with UW programmers that adhere to UW-CIMSS/NASA IMAPP programming guidelines. Once the ash detection logic is working within IMAPP, extensive validation will be conducted by processing previous MODIS/AIRS overpasses over known volcanic eruptions. UW-
CIMSS scientists will transition the MODIS volcanic aerosol mask allowing retrieval of height, particle, and optical depth using MODIS data. Implementation of the MODIS volcanic ash property logic into the IMAPP software will occur. Mr. Wayne Feltz will monitor and lead day-to-day activities through close collaboration with Mr. Liam Gumley
(IMAPP lead), Michael Pavolonis (MODIS/AIRS volcanic ash detection expert), and Dr.
David Tobin (high spectral resolution atmospheric gas detection lead). Mr. Gumley will oversee IMAPP implementation of volcanic ash detection software. Mr. Feltz will consult with Washington DC VAAC to formalize transition to operations during year 2.
Year 2:
Extensive validation of MODIS volcanic aerosol mask, plume heights, particle size, and optical depth retrievals will be conducted by Mr. Richard Frey (MODIS cloud mask development expert) under the leadership of Dr. Steve Ackerman and Mr. Gumley.
Validation resources will include any volcanic aerosol cases observed by
CloudSat/CALIPSO/MISR. Hyperspectral (AIRS) cloud top height estimates, SO
2
plumes, and SO
2
concentration will be provided and implemented into IMAPP with leadership from
Dr. David Tobin. Full volcanic ash detection suite will be tested in near real-time using the
NASA Goddard DAAC “bent-pipe” which allows less time latency for global radiance processing. This “beta” volcanic ash IMAPP software version will be transitioned to the
Washington DC VAAC first for testing. UW-CIMSS will work with Mr. George Serafino
(Branch Chief, NOAA/NESDIS/SSD/SAB) for seamless transition to DC VAAC. Co-I
18

Mr. Serafino will provide contractor support and year 2 budget includes funding for hardware implementation at the DC VAAC. Regular teleconferences providing feedback from DC VAAC will be conducted to improve UW-CIMSS volcanic ash logic and output format needs (McIDAS and N-AWIPS).
Year 3:
IMAPP software package will be completed with necessary improvements with DC VAAC collaboration. Year 3 proposal funding provides DC VAAC labor resources for continued
IMAPP version upgrades as software matures and validation/feedback for real-time eruption monitoring. IMAPP package will also be implemented at AFWA/NRL with onsite UW-CIMSS IMAPP expertise. Mr. Feltz will brief other end-users on package availability and arrange any needed support for training/implementation. IMAPP package will also be made freely available to over 100 (and expanding) international DB sites and will be announced at international direct broadcast conferences. Finally, transition of
IMAPP logic to newly funded International Polar Orbiting Package (IPOP), which will allow volcanic ash detection from VIIRS, CrIS, METOP, and IASI satellite radiances.
IPOP will be made freely available to DB community under leadership of Mr. Gumley.
Figure 6: Schematic diagram illustrating the overall Integrated System Solution for automated/objective EOS satellite derived volcanic ash location and height.
19

The International MODIS/AIRS Processing Package will be the main mechanism for transitions to VAAC, military, and DB site operations. The EOS MODIS/AIRS volcanic ash detection logic will be incorporated into IMAPP and then IMAPP will be transitioned to the NOAA Washington DC VAAC. UW-CIMSS has successfully worked with NOAA to transition over 20 research algorithms into operations, and we bring this experience to this project. The DC VAAC has access to 3-hour delayed global MODIS/AIRS radiance data that is much more timely than the Goddard DAAC and will allow extensive testing over volcanically active areas around the world.
After transition to the DC VAAC, UW-CIMSS will distribute software to the rest of the
VAACs and provide on site help with software implementation if the need arises. In addition, the new volcanic ash detection product will be released to the global community of IMAPP users who receive and process Terra and Aqua MODIS in near real time. Most of these users are already creating a suite of MODIS products using real-time MODIS data.
UW-CIMSS will beta test the new algorithm with several of the user sites, and make sure the software is properly documented and tested on the supported IMAPP platforms
(including Intel Linux). UW-CIMSS conducts regular workshops for IMAPP users around the world, and will add training modules on the volcanic ash detection algorithm and product. UW-CIMSS will continue to support IMAPP throughout the lifetime of the Terra and Aqua missions. UW-CIMSS will also work towards incorporating the volcanic ash detection algorithm into the direct broadcast processing software for NPP and NPOESS, using other funding.
The final measures of the success for this project will be as follows: (i) Our products from
NASA datasets are successfully distributed to end-users, including the Volcanic Ash
Advisory Centers (VAACs), Air Force Weather Agency (AFWA), and Naval Research
Laboratory (NRL); ii) the near-real time derived products are used in general volcanic ash advisories issued by our partners; and (iii) the results from this work are used by Direct
Broadcast sites that are in the vicinity of active volcanoes to detect and monitor volcanic ash.
Intermediate performance measures will include positive evaluations of (i) the completion of deliverables on schedule; (ii) the assessment of the capability and timeliness of derived volcanic products from the NASA observations; (iii) the use of NASA observations in forecast evaluation algorithms. The measures will demonstrate the benefits of the NASA observations in issuing aviation advisories. Project issues and deviations from the schedule or proposed plan will be immediately communicated to NASA and resolved as quickly as possible.
20

Results of this work will be presented at appropriate scientific conferences and published in peer-reviewed journal articles. In addition, the use of the NASA observations will be documented as part of the IMAPP package.
Several expected improvements the IMAPP volcanic ash detection and height assignment will offer over current baseline decision support tools and methodologies used at the
VAAC’s include:
1) Objective and automated detection of volcanic ash in near real time from DB locations will now be possible. When volcanic ash is detection via logic in the IMAPP software, email will be sent to end-user informing them of the detection so they can focus on the event quickly. Currently volcanic ash is subjectively located using the reverse absorption technique that is prone to false alarms and does not work very well over certain land surfaces. Otherwise, pilot reports are relied upon for volcanic ash detection, which is not an ideal method to warn aviation commerce.
2) A satellite-based objective height assignment of the ash cloud will now be possible.
Currently height is assigned visually by pilots near the cloud or inferred by ash movement with geostationary satellites through weather model wind profiles, this method involves a list of assumptions and only works at latitudes that geostationary imagery is available. This new objective height estimate can then be quickly used with a VAAC trajectory model for nowcast of ash location.
Year 1:

Use MODIS radiances to automatically identify pixels containing volcanic ash plumes or meteorological clouds that are contaminated with volcanic ash and/or
SO
2
and H
2
SO
4

Implement MODIS ash identification logic in IMAPP software

Transition the volcanic aerosol mask generated by the MODIS to retrieve the height, particle size, and optical depth of the volcanic cloud using MODIS data.
This is information that VAAC's can potentially incorporate this information into their respective dispersion models.

Implement MODIS volcanic ash property logic in IMAPP
Year 2:

Validate the MODIS volcanic aerosol mask, plume heights, particle size retrievals, and optical depth retrievals against any volcanic aerosol cases observed by CloudSat/CALIPSO/MISR
21


Use the AIRS to provide hyperspectral cloud top height estimates and identify gaseous SO
2
plumes and estimate SO
2
concentrations.

Implement AIRS methodology in IMAPP software for EOS Aqua overpasses

Begin to transition IMAPP software to VAACs beginning with the Washington
DC VAAC

Improve package as feedback from Washington VAAC is received via teleconferences and site visit(s)
Year 3

Install IMAPP at VAAC’s, AFWA, and NRL and provide access to all DB sites for installation

Present software package availability at International Direct Broadcast conference(s)

Transition IMAPP volcanic ash products to International Polar Orbiting Package
(IPOP) allowing volcanic ash products to be derived for NPP VIIRS/CrIS,
METOP, and IASI instrument radiance data

Test/validate IPOP and provide free access to end-user organizations
22

14 November 2005
This letter is to express the commitment and support of the University of Wisconsin-Madison,
Space Science and Engineering Center (SSEC) to participate in the NASA ROSES 2005 proposal, " Satellite-based Estimates of Volcanic Ash Location and Altitude for FAA, VAAC, and Navy/AFWA Decision Support Systems" which describes a project SSEC scientists are developing in collaboration team partnering members of other VAAC’s, FAA, and military agencies.
The Principle Investigator for this work will be Dr. Steve Ackerman CIMSS director who has a extensive scientific knowledge of infrared cloud, aerosol, and volcanic ash properties. He is PI for the EOS MODIS cloud mask bringing a wealth of narrow-band (MODIS/VIIRS) and hyperspectral (AIRS/CrIS) scientific experience to the proposed work. The overall project lead will be Dr. Ackerman, who will also be responsible for directing and monitoring activities at UW-CIMSS.
The SSEC PM and a Co-I for this project will be Mr. Wayne Feltz. Mr. Feltz is the leader of the NASA funded Advanced Satellite Aviation-weather Product (ASAP) effort at UW-CIMSS for the last three years, directing a group of researchers/scientists toward the goal of using current derived satellite based meteorological products to improve forecasting of aviation weather hazards through the Federal Aviation Administration (FAA) Product Development
Teams. Mr. Feltz will be responsible for directing, collaborating, and transition of all proposal related activities with other CIMSS researchers and the DSS teaming partners described below.
Mr. Feltz will oversee day to day funding and labor management towards successful completion of this proposal work.
Co-investigator Michael Pavolonis, formerly of CIMSS/SSEC, now with the
NOAA/NESDIS Office of Research and Applications (ORA) has served as the lead scientist for the volcanic aerosol component of the Advanced Satellite Aviation – weather Product
(ASAP) effort at CIMSS/SSEC for the past year. The ASAP effort is aimed at using satellitederived products to improve forecasting of aviation weather hazards. Mr. Pavolonis leads the
23

effort to develop and document (via publications) automated satellite-based algorithms that detect the presence of volcanic aerosols, especially ash, and determine volcanic aerosol properties such as vertical location (e.g. height) and optical depth. He is also involved in developing volcanic aerosol and cloud algorithms for future sensors such as the
Visible/Infrared Imager/Radiometer Suite (VIIRS) and the GOES-R Advanced Baseline
Imager and Hyperspectral Environmental Suite (HES). As a Co-I or collaborator on other projects, Mr. Pavolonis has experience in transitioning algorithms to operational processing systems. In this project, Mr. Pavolonis will continue his role as lead algorithm scientist. He will work to ensure that all algorithms are developed to full maturity, help to ensure that algorithms are properly implemented within our proposed operational framework, and that the scientific foundation of all algorithms is fully documented via publications and Algorithm
Theoretical Basis Document’s (ATBD’s).
Dr. David Tobin is a research scientist at CIMSS/SSEC/UW-Madison. He has considerable experience with radiative transfer and calibration/validation of high spectral resolution satellite observations, and is a member of the current AIRS science team. He will contribute to the proposed efforts in the interpretation of dust and aerosol signatures from the AIRS observations.
Mr. Liam Gumley is a researcher at CIMSS, and is the project manager and co-investigator for the International MODIS/AIRS Processing Package (IMAPP). He has been associated with the MODIS program since 1991, and is a member of the NASA MODIS Science Team. He also manages the SSEC EOS Direct Broadcast Reception and Processing Facility. He will be responsible for overseeing the implementation of the volcanic ash detection algorithm in
IMAPP, and for ensuring the successful transition of the package to operational agencies including the VAACs and the global direct broadcast community.
Sincerely,
Thomas H. Achtor
Executive Director-Science
Space Science and Engineering Center
University of Wisconsin-Madison
24

25

26

27

28

29

30

31

The budgets are presented from the two groups requesting direct NASA funding conduit
(no overhead assumed for NOAA subcontract through U of Wisconsin, instead direct
NASA to NOAA if possible), namely:
1) University of Wisconsin – SSEC/CIMSS - A year-one budget breakdown is attached at the end of this proposal. The first budget section lists the labor costs for the project, broken down by the type of activity. The budget includes funding for a graduate and undergraduate student worker. Mr. Mike Pavolonis (e) is a NOAA/NESDIS employee, thus no funding is required for his salary. Section 2 contains travel costs for UW-CIMSS personnel to travel to and from the a conference and collaborative meetings with other team partners. Section 3 contains material costs to support daily scientific research needs such as printer copies, ink, paper, etc. Section 4 contains an estimate of a peer reviewed publication charge to report results of this research effort. Section 5 is the university overhead, currently at 47%, which is directly negotiated with the U.S. government and is charged to those items discussed above. And finally section 6 provides funding for computer equipment needed to test, transition, and provide testbed for near real-time EOS volcanic ash detection logic into the IMAPP software and to simulate end-user processing.
The year-two budget includes labor costs for IMAPP transition to operations, validation, and collaboration with team partners. Section 2 again provides for travel to/from DC
VAAC for collaboration and conference attendance to show research results.
The year-three budget provides for UW-CIMSS labor costs to implement IMAPP at all teaming organizations, transition of IMAPP to IPOP, and any necessary improvements for a mature IMAPP/IPOP package. Section 2 increases funding for travel to allow UW-
CIMSS researcher(s) to transition software to various end-user organizations and attend DB conference(s) to announce general availability of the package to volcanically active DB areas.
2) Washington DC NOAA/NESDIS VAAC – who will integrate and validate IMAPP volcanic ash software and provide feedback for proposal success metric. Year 2 funding includes $20K to upgrade computer facilities to allow world-wide automated processing of
NASA DAAC EOS data via NOAA bent-pipe. Year 3 funding includes $35.8K for contractor support and training with the IMAPP volcanic ash products, NOAA will provide cost sharing funding also in year 3.
The cost plans are based on the following:

Assume a 1 July 2006 start date

Period of performance 1 July 2006 – 30 June 2006

Assume a 4% annual cost of living increase
32

University of Wisconsin – SSEC/CIMSS 3-Year NASA ROSES Budget
I.
Budget Summary: Satellite Based Estimates of Volcanic Ash Location and
Altitude for FAA, VAAC and Navy/AFWA Decision Support Systems
Year 1: 1 July 2006 to 30
June 2007
Labor and Fringe Benefits Hours Rate Salary Fringe Cost
a) PI - Steve Ackerman
b) Co-I Wayne Feltz
c) Co-I Liam Gumley
d) Co-I Dave Tobin
300 88.54
900 40.11
600 44.52
150 48.25
$26,562 $9,031 $35,593
36,099 12,274
26,712
7,238
9,082
2,461
48,373
35,794
9,699
e) Co-I Mike Pavolonis
f) Researcher - Rich Frey
g) Graduate Student
h) Student
II.
Subtotal
Travel
a)
2 airline tickets
(Madison-DC)
Per diem: 10 people days x
b)
c)
$50/day
Lodging: 10 nights x
$110/day
d) Car Rental (5 days)
Conference
e) Registration (2)
III. Materials and Supplies
300 0.00 - - -
900 36.48 32,832 11,163 43,995
900 20.13 18,117 4,710 22,827
240 10.78 2,587 52 2,639
1,000
500
1,100
200
500
IV.
V. Fees and Services
VI.
Publications
University Indirect Cost at
47%
VII.
Graduate Student Tuition
Remission
VIII. Capital Equipment
TOTAL
Totals
$198,920
3,300
500
4,000
0
97,158
4,529
20,000
$328,407
33

I.
III.
IV.
V.
VI.
II.
Budget Summary: Satellite Based Estimates of Volcanic Ash Location and Altitude
for FAA, VAAC and Navy/AFWA Decision Support Systems
Year 2: 1 July 2007 to 30 June 2008
Labor and Fringe Benefits
a) PI - Steve Ackerman
b) Co-I Wayne Feltz
Hours Rate Salary Fringe Cost
300 95.77 $28,731 $9,769 $38,500
900 43.39 39,051 13,277 52,328
c) Co-I Liam Gumley
d) Co-I Dave Tobin
e) Co-I Mike Pavolonis
450
150
300
48.16
52.18
0.00
21,672
7,827
-
7,368
2,661
-
29,040
10,488
-
f) Researcher - Rich Frey
g) Graduate Student
h) Student
Subtotal
Travel
a) 2 airline tickets (Madison-DC)
b) Per diem: 10 people days x $50/day
c) Lodging: 10 nights x $110/day
d) Car Rental (5 days)
e) Conference Registration (2)
900
900
240 11.66
39.45
21.78
35,505 12,072
19,602 5,097
2,798 56
47,577
24,699
2,854
1,000
500
1,100
200
500
Publications
Fees and Services
University Indirect Cost at 47%
Materials and Supplies
VII. Graduate Student Tuition Remission
VIII. NOAA Consultant
IX. Capital Equipment
TOTAL
34
Totals
$205,486
3,300
500
4,000
0
100,244
4,901
20,000
0
$338,431

I.
Budget Summary: Satellite Based Estimates of Volcanic Ash Location and
Altitude for FAA, VAAC and Navy/AFWA Decision Support Systems
Year 3: 1 July 2008 to 30
June 2009
Labor and Fringe Benefits Hours Rate Salary Fringe
a) PI - Steve Ackerman
Cost
300 99.60 $29,880 $10,159 $40,039
b) Co-I Wayne Feltz
c) Co-I Liam Gumley
d) Co-I Dave Tobin
e) Co-I Mike Pavolonis
450 45.12
450 50.08
150 54.27
300 0.00
20,304
22,536
8,141
-
6,903
7,662
2,768
-
27,207
30,198
10,909
-
II.
III.
f) Researcher - Rich Frey 900 41.03 36,927 12,555 49,482
g) Graduate Student 900 22.65 20,385 5,300 25,685
h) Student 240 12.13 2,911 58 2,969
Subtotal
Travel
6 airline tickets
a) (Madison-DC)
Per diem: 20 people days x
b) $50/day
Lodging: 20 nights x
c) $110/day
d) Car Rental (10 days)
e)
Conference
Registration (2)
3,000
1,000
2,200
400
500
Materials and Supplies
IV. Publications
V. Fees and Services
VI.
University Indirect Cost at
47%
Graduate Student Tuition
VII. Remission
VIII. NOAA Consultant
IX. Capital Equipment
Totals
$186,489
7,100
500
4,000
0
93,102
5,096
35,800
0
TOTAL $332,087
35

NOAA Budget Summary
For period from July 1, 2006 to June 30, 2009
• Assume a July 1, 2006 project start date
• Projects may have up to a 3-year duration
• Enter the proposed estimated costs in each column.
1. Direct Labor (salaries, wages, and
fringe benefits)
2. Other Direct Costs: a. Subcontracts b. Consultants c. Equipment d. Supplies e. Travel f. Data Costs g. Other
-OR-
Year 1
FY06
Year 2
FY07
Year 3
FY08 FY09
Total
Total
0.0 K 0.0 K 41.7 K ______ 41.7 K
0.0 K __ 0.0 K __ 30.0 K ______ 30.0 K
______ ______ ______ ______ ______
0.0 K __ 20.0 K 0.0 K ______ 20.0 K _
______ ______ ______ ______ ______
0.0 K __ 0.0 K _ 0.0 K ______ 0.0 K _
______ ______ ______ ______ ______
0.0 K __ 0.0 K __ 0.0 K ______ 0.0 K
3. Facilities and Administrative Costs 0.0 K __ 0.0 K _ 5.8 ____ ______ 5.8 K __
4. Other Applicable Costs:
5. SUBTOTAL--Estimated Costs
6. Less Proposed Cost Sharing (if any)
7. Total NASA Cost
______ ______ ______ ______ ______
0.0 K 20.0 K 77.5 K _ ______ 97.5 K
0.0 K 0.0 K _ 41.7 K ______ 41.7 K
0.0 K __ 20.0 K _ 35.8 K _ ______ 55.8 K
36

1. Direct Labor (NOAA/NESDIS Civil Servants; assumes 3% inflation rate per year)
George Serafino (0.10 FTE/yr) @ 136 K/yr (salary + 21.8 % benefits)
George Stephens (0.10 FTE/yr) @ 112 K/yr (salary + 21.8 % benefits)
Satellite Analysis Branch evaluators (0.10 FTE /yr) @ 95 K/yr (salary + 21.8 % benefits)
IT Support / System Administration (0.05 FTE/yr) @ 100 K/yr (salary + 21.8 % benefits)
Year 1 Year 2 Year 3
$0 K $0 K $41.7K
2. Other Direct Costs (assumes 3% inflation rate per year for labor) a. Subcontracts (QSS Group, Inc) Year 1 Year 2 Year 3
Data acquisition / ingest 0 0 0
Algorithm Integration & Test 0 0 0.10
Validation & Verification 0 0 0.05
Documentation (SOP, Data Products, metadata) 0 0 0.05
System Admin 0 0 0
Web site enhancements 0 0 0
Total FTE 0 0 0.20
@140K/FTE (loaded + 3% annual inflation) $0 K $0 K $30 K
FY06 senior scientific programmer labor rate
Yellow highlights are NOAA cost share items
c. Equipment $0 K $20 K $0 K
NOAA/NESDIS is requesting $20K during the second year of the proposal to procure a linux workstation with necessary disk storage for use as a pre-operational product generation and
QC/QA platform for volcanic cloud products. e. Travel
None g. Other
None
37

3. Facilities and Administrative Costs (13.8 % Direct Labor)
Contact: Cynthia Brown, NOAA/NESDIS/OSDPD
Phone : ( 301) 457-5120 cynthia.d.brown@noaa.gov
$ 0 K $ 0 K $ 5.8K
$ 0 K $ 0 K $ 0 K
$ 0 K $20 K $77.5K
$ 0 K $ 0 K $41.7K
$ 0 K $20K $35.8K
38

II.
I.
III.
IV.
Budget Summary: Satellite Based Estimates of Volcanic Ash Location and Altitude for FAA, VAAC and Navy/AFWA Decision Support Systems
Three Year Summary: 1 July 2006 to 30 June
2009
Labor and Fringe Benefits Hours Salary Fringe Cost
a) PI - Steve Ackerman
b) Co-I Wayne Feltz
c) Co-I Liam Gumley
d) Co-I Dave Tobin
e) Co-I Mike Pavolonis
Researcher - Rich
f) Frey
g) Graduate Student
0 $85,173 $28,959 $114,132
900
2250
1500
450
900
2700
2700
95,454
70,920
23,206
-
105,264
58,104
8,296
32,454
24,112
7,890
-
35,790
15,107
166
127,908
95,032
31,096
-
141,054
73,211
8,462 h) Student
Subtotal
Travel
a) Year 1
b) Year 2
c) Year 3
3,300
3,300
7,100
Materials and Supplies
V. Fees and Services
VI.
Publications
University Indirect Cost at
47%
Graduate Student Tuition
VII. Remission
VIII. NOAA Consultant
IX. Capital Equipment
TOTAL
Totals
$590,895
13,700
1,500
12,000
-
290,504
14,526
55,800
20,000
$998,925
39

The UW-SSEC CIMSS has a long and successful record in the development of hardware and software to exploit the use of passive remote sensing measurements of the earth’s surface and atmosphere. The Space Science and Engineering Center is housed in a 15 story building on the University of Wisconsin-Madison campus. The facilities at SSEC include multiple LINUX clusters for computational tasks as well as high-speed networking to foster a collaborative environment. The SSEC Data Center provides researchers with a comprehensive selection of both polar and geostationary real-time data from around the globe. Finally, the SSEC staff consists of scientists, engineers, computer programmers and support staff who provide the highest level of expertise and professionalism. All this provides a broad array of experience in fields related to atmospheric measurements that is available within the building.
Within SSEC, the Cooperative Institute for Meteorological Satellite Studies (CIMSS) was established in 1980 to formalize and support cooperative research between the National
Oceanic and Atmospheric Administration's (NOAA) National Environmental Satellite,
Data, and Information Service (NESDIS) and the University of Wisconsin-Madison's
Space Science and Engineering Center. Sponsorship and membership of the Institute was expanded to include the National Aeronautics and Space Administration (NASA) in 1988.
40

STEVEN A ACKERMAN
E D U C A T I O N
1985-1987
1976-1979
1972-1976
Colorado State University; Ph.D. - Atmospheric Science, Advisor: Dr. Stephen K. Cox;
Dissertation: "Radiative Characteristics of a Dust Lade Atmosphere"
Colorado State University. M.S. - Atmospheric Science Advisor: Dr. Stephen K. Cox
Thesis: "GATE Phase III Mean Synoptic-Scale Radiative Convergence Profiles"
State University of New York – Oneonta B.S. – Physics Minor: Mathematics Graduated
Cum Laude
P R O F E S S I O N A L E X P E R I E N C E
1999-Present Director, Cooperative Institute for Meteorological Satellite Studies
1992-Present Professor Atmospheric and Oceanic Sciences, University of Wisconsin-Madison
1989-1992
1987-1989
Assistant Scientist Cooperative Institute for Meteorological Satellite Studies
Associate Researcher Cooperative Institute for Meteorological Satellite Studies
H O N O R S A N D A W A R D S
July 2004:
May 2003:
April 1999:
Dec 1996:
UW-Madison Vilas Associate
Group Achievement Award for Outstanding Teamwork on the Earth Observing
System (EOS), Aqua Mission Team
Chancellor's Award for Distinguished Teaching
NASA Group Achievement Award: FIRE II Science and Operations Team
April 1996:
April 1995:
Winner of a Lilly Teaching Fellowship
Inducted as a Fellow in the University of Wisconsin-Madison Teaching Academy
Sept 1992: NASA ERBE Program Award "For outstanding contributions to the intercomparison and validation of ERBE scanner and non-scanner results,"
S E L E C T E D P U B L I C A T I O N S
Knox, J. A., and S. A. Ackerman, 2005: What do Introductor Meteorology Students want to
Learn? BAMS 86, 1431-1435
Ackerman, S. A., S. Bachmeier, K. Strabala, and M. Gunshor, 2005: A Satellite View of the Cold
Air Outbreak of 13-14 January 2004. Wea. Forecast., 20, 222-225.
Hawkinson, J. A., W. Feltz, and S. A. Ackerman, 2005: A Comparison Study using the GOES
Sounder Cloud Top Pressure Product and Cloud Lidar and Radar, Jour Appl. Meteor. 44,
1234-1242.
McCourt, M. L., W. W. McMillan, S. Ackerman, R. Holz, H. E. Revercomb, and D. Tobin, 2004:
Using the “blue-spike” to characterize biomass-burning sites during Southern African
Regional Science Initiative (SAFARI) 2000, Jour Geo. Res, 109,
Huang, H.L., P. Yang, H. L. Wei, B. A. Baum, Y. X. Hu, P. Antonelli, and S. A. Ackerman, 2004:
Inference of Ice Cloud Properties From High Spectral Resolution Infrared Observations.
IEEE Trans. Geosci. Remote Sens. 42, 842-853.
Lee, Y., G. Wahba, and S. A. Ackerman, 2004: Cloud Classification of Satellite Radiance Data by
Multicategory Support Vector Machines. Jour. Atmos. Ocean. Tech. 21, 159-169.
Yang, P., B.A. Baum, A.J. Heymsfield, Y.-X. Hu, H.-L. Huang, S.-C. Tsay, and S.A. Ackerman,
41

2003: Single scattering properties of droxtals. J. Quant. Spectros. Rad. Transfer. 79, 1159-1169.
Special Issue.
King, M. D., W. P. Menzel, Y. J. Kaufman, D. Tanré, B. C. Gao, S. Platnick, S. A. Ackerman, L. A.
Remer, R. Pincus, and P. A. Hubanks, 2003: Cloud and aerosol properties, precipitable water, and profiles of temperature and humidity from MODIS. IEEE Trans. Geosci. Remote
Sens., 41, 442-458.
Liu, Yinghui, Key, Jeffrey R., Frey, Richard A., Ackerman, Steven A., and Menzel, W. Paul, 2004:
Nighttime polar cloud detection with MODIS. Remote Sensing of Environment, Volume 92,
2004, pp.181-194.
Turner, D. D., S. A. Ackerman, and B. A. Baum, 2003. Determination of cloud phase using ground-based observations at 9, 12, and 18 µm. J. Appl. Meteor., 42, 701-715.
Li, J., Z. Yang, W.P. Menzel, Z. Yang, R.A. Frey, and S.A. Ackerman, 2003: High spatial resolution surface and cloud-type classification from MODIS multi-spectral band measurements. J. Appl. Meteor., 42, 204-225.
Sunggi C., S. Ackerman, P. F. van Delst, and W. P. Menzel, 2000: Model Calculations and
Interferometer Measurements of Ice Cloud Characteristics. J. Appl. Meteor., 39, 634-644.
Baum, B. A., P. F. Soulen, K. I. Strabala, M. D. King, S. A. Ackerman, W. P. Menzel, 2000: Remote sensing of cloud properties using MODIS Airborne Simulator imagery during SUCCESS II.
Cloud thermodynamic phase. J. Geophys. Res., 105, 11781-11792.
Chang, F., Z. Li, and S. A. Ackerman, 1999: Examining the relationship between cloud and radiation quantities derived from satellite observations and model calculations. J. Climate,
13, 3842–3859.
Frey, R. A., B. A. Baum, W. P. Menzel, S. A. Ackerman, C. C. Moeller, J. D. Spinhirne, 1999: A comparison of cloud top heights computed from airborne lidar and MAS radiacne data using CO2 slicing. J. Geophys. Res., 104, 24547-24555.
Ackerman, S. A., K. I. Strabala, W. P. Menzel, R. A. Frey, C. C. Moeller and L. E. Gumley
Discriminating Clear-sky from Clouds with MODIS, 1998: J. Geophys. Res., 103, D24, p.
32,141
King, M. D., S.-C. Tsay, S. A. Ackerman and N. F. Larsen, 1998: Discriminating Heavy Aerosol,
Clouds, and Fires During SCAR-B: Application of Airborne Multispectral MAS Data J.
Geophys. Res., 103, D24, p. 31,989-31,999.
Ackerman, S. A., C. C. Moeler, K. I. Strabala, H. E. Gerber, L. E. Gumley, W. P. Menzel, S-C. Tsay,
1998: Retrieval of Effective Microphyscial Properties of Clouds: a Wave Cloud Case Study,
J. Geophys. Res. Lett., 25, 1121-1124.
Smith, W. L., S. A. Ackerman, H. Revercomb, H. Huang, D. H. DeSlover, W. Feltz, L. Gumley and
A. Collard, 1998: Infrared spectral absorption of nearly invisible cirrus clouds. J. Geophys.
Res. Lett., 25, 1137-1140.
Ackerman, S. A., 1997: Remote sensing aerosols from satellite infrared observations. J. Geophys.
Res., 102, 17069-17079.
Ackerman, S. A., 1996: Global satellite observations of negative brightness temperature difference between 11 and 6.7  m. J. Atmos. Sci. 53, 2803-2812.
Ackerman, S. A., W. L. Smith, A. D. Collard, X. L. Ma, H. E. Revercomb and R. O. Knuteson, 1995:
Cirrus cloud properties derived from high-spectral resolution infrared spectrometry during
FIRE II, Part II: Aircraft HIS results. Jour. Atmos Sci. 52, 4246-4263.
Ackerman, S. A., K. I. Strabala, 1994: Satellite remote sensing of H2SO4 aerosol using the 8 - 12
42

 m window region: Application to Mount Pinatubo. J. Geo. Res. 99, 18,639-18,649.
Strabala, K. I., S. A. Ackerman and W. P. Menzel, 1994: Cloud properties inferred from 8-12  m data. Jour. Appl. Met. 2, 212-229.
Ackerman, S. A., and T. Inoue, 1994: Radiation Energy Budget Studies using collocated AVHRR and ERBE observations, Jour. Appl. Met. 3, 370-378.
Limaye, S. S., S. A. Ackerman, P. M. Fry, M. Isa, H. Ali, G. Ali and A. Wright, 1992: Satellite monitoring smoke from the Kuwait oil fires. J. Geo. Res. 97, 14551-14563.
43

WAYNE FREDERICK FELTZ
Researcher
CIMSS/SSEC University of Wisconsin-Madison
1225 West Dayton Street Rm 235
Madison, WI 53706
Email: wayne.feltz@ssec.wisc.edu
EDUCATION
1991-1994 University of Wisconsin – Madison
M.S. - Atmospheric and Oceanic Science
Advisor: Dr. William Smith
Thesis: "Meteorological Applications of the Atmospheric Emitted Radiance Interferometer"
1987-1991 Northland College
B.S. – Earth Science
Minor: Mathematics
Graduated Magna Cum Laude
EXPERIENCE
1998-Present Researcher
Cooperative Institute for Meteorological Satellite Studies
1994-1998 Research Specialist
Cooperative Institute for Meteorological Satellite Studies
Mr. Feltz is the leader of the Advanced Satellite Aviation-weather Product (ASAP) effort at UW-CIMSS, directing a group of researchers/scientists toward the goal of using current derived satellite based meteorological products to improve forecasting of aviation weather hazards through the FAA PDT’s. Mr.
Feltz is involved with validation of future meteorological in situ and remote sensing instrumentation and currently has PI, PM, and Co-I responsibilities on five satellite remote sensing related research projects.
HONORS AND AWARDS
Member of AMS Satellite Committee 2006-2009
NASA Earth Sciences Application Team Group Award 2005
NASA Aviation Safety and Security Program Award 2005
University of Wisconsin Committee on Academic Staff Issues Representative 2003-2006
University of Wisconsin-Madison Lettau Award for "Thesis of the Year" April 1995
SCIENTIFIC PUBLICATIONS
Mr. Feltz has authored or coauthored over 25 peer reviewed scientific publications relating to satellite and groundbased passive meteorological infrared remote sensing/aviation products, validation of remote sensing and in situ meteorological instrumentation, and the detection of mesoscale meteorological events. References are available at http://www.ssec.wisc.edu/~waynef including:
Feltz, W. F.
, H. B. Howell, R. O. Knuteson, H. M. Woolf, and H E. Revercomb, 2003: Near Continuous
Profiling of Temperature, Moisture, and Atmospheric Stability using the Atmospheric Emitted Radiance
Interferometer (AERI). . J. Appl. Meteor., 42 , 584-597.
Hawkinson, J. A., W. Feltz, and S. A. Ackerman, 2005: A Comparison Study using the GOES
Sounder Cloud Top Pressure Product and Cloud Lidar and Radar, Jour Appl. Meteor. 44,
1234-1242.
Mecikalski, J. R., W. F. Feltz , J. J. Murray, D. B. Johnson, K. M. Bedka, S. M. Bedka, A. J. Wimmers, M.
Pavolonis, T. A. Berendes, J. Haggerty, P. Minnus, and B. Bernstein, 2006: Aviation applications for satellite-based observations of cloud properties, convection initiation, in-flight icing, turbulence and volcanic ash. Bull. Amer. Meteor. Soc. In preparation.
Pavolonis, M. J., W. F. Feltz , A. K. Heidinger, and G. Gallina 2005: "A daytime complement to the reverse absorption technique for automated detection of volcanic ash", Submitted to the J Oceanic and Atmos.
44

Tech. (September 2005).
45

Michael J. Pavolonis
Education
2002
2000
M.S. University of Wisconsin, Madison; in Atmospheric and Oceanic Sciences
B.S. The Pennsylvania State University; in Meteorology
Professional Experience
09/2005 – present
07/2005 – 09/2005
2003 - 2005
Physical Scientist, NOAA/NESDIS, Office of Research and Applications
Associate Researcher, Cooperative Institute for Meteorological Satellite
Studies, University of Wisconsin-Madison
Assistant Researcher, Cooperative Institute for Meteorological Satellite
Studies, University of Wisconsin-Madison
2002 - 2003 Research Intern, Cooperative Institute for Meteorological Satellite Studies,
University of Wisconsin-Madison
National and International Activities
VIIRS Operational Algorithm Team - Advisor (2005-present)
GOES-R Algorithm Working Group (2005-present)
Selected Publications
Heidinger, A. K., and M. J. Pavolonis , 2005: A multi-year global climatology of cloud temperature and emissivity from the AVHRR split-window observations. Part I: Approach and expected accuracy. In prep.
Pavolonis, M. J.
, and A. K. Heidinger, 2005: A multi-year global climatology of cloud temperature and emissivity from the AVHRR split-window observations. Part II: A 20 year climatology. In prep.
Pavolonis, M. J.
, W.F. Feltz, A.K. Heidinger, G. Gallina, 2005: A daytime complement to the reverse absorption technique for improved automated detection of volcanic ash. Submitted to J. Oceanic and
Atmos. Tech .
Mecikalski, J. R., W. F. Feltz, J. J. Murray, D. B. Johnson, K. M. Bedka, S. T. Bedka, A. J. Wimmers, T. A.
Berendes, and M. J. Pavolonis , 2005: The Advanced Satellite Aviation Weather Products (ASAP) initiative Phase I efforts 2003-2005., Submitted to the Bull. Amer. Meteor. Soc.
Evan, A. T., A. K. Heidinger, and M. J. Pavolonis , 2005: Development of a new over-water Advanced Very
High Resolution Radiometer dust detection algorithm. Conditionally accepted by Inter. J. Rem. Sens.
Pavolonis, M. J ., A. K. Heidinger, and T. Uttal, 2005: Daytime global cloud typing from AVHRR and
VIIRS: Algorithm description, validation, and comparisons. J. Appl. Meteor ., 44 , 804-826.
Heidinger, A. K., and M. J. Pavolonis , 2005: Global daytime distribution of overlapping cloud from NOAA's
Advanced Very High Resolution Radiometer. J. Climate, 18 (22) , 4772-4784.
Hutchison, K., J. Roskovensky, J. Jackson, M. J. Pavolonis , and R. Frey, 2005: Automated cloud detection and typing of data collected by the Visible Infrared Imager Radiometer Suite (VIIRS). Accepted by the
Int. J. Rem. Sens.
Thomas, S. M., A. K. Heidinger, and M. J. Pavolonis , 2005: Comparison of NOAA's operational AVHRR derived cloud amount to other satellite derived cloud climatologies. J. Climate ., 17 (24) , 4805-4822.
Pavolonis, M. J.
, and A. K. Heidinger, 2004: Daytime cloud overlap detection from AVHRR and VIIRS. J.
Appl. Meteor ., 43 (5), 762-778.
Heidinger, A. K, R. Frey and M.J. Pavolonis , 2004: Relative Merits of the 1.6 and 3.75 micron channels of the AVHRR/3 for cloud detection. Canadian J. Rem. Sen ., 30 (2), 1-13.
Pavolonis, M. J.
and J. Key, 2003: Antarctic cloud radiative forcing at the surface estimated from the
AVHRR Polar Pathfinder and ISCCP D1 data sets, 1985-1993 . J. Appl. Meteor., 42 , 827-840.
46

Liam E. Gumley
Associate Instrument Innovator
Cooperative Institute for Meteorological Satellite Studies
Space Science and Engineering Center, University of Wisconsin-Madison
Liam.Gumley@ssec.wisc.edu
Education
M. S. (Meteorology), University of Wisconsin-Madison (1990)
B. App. Sc. (Applied Physics Major), Curtin University of Technology (1988)
Professional Experience
1994 - Present
Researcher, Space Science and Engineering Center, University of Wisconsin-Madison.

Member of NASA MODIS Science Team

Manager of EOS Direct Broadcast Bacility at SSEC

Project Manager and Co-Investigator for NASA IMAPP and NPP PEATE projects
1991 - 1994 Scientific Programmer, NASA Goddard Space Flight Center.
1988 – 1990 Research Assistant, Department of Meteorology, UW-Madison.
1986 – 1988 Research Assistant, Department of Applied Physics, Curtin University
Awards
NASA Group Achievement Award; Earth Sciences Applications Team (2005)
NASA Group Achievement Award; Intercontinental Chemical Transport Experiment North America Science
Team (2005)
Books Published
Gumley, Liam E. (2001). Practical IDL Programming: Creating Effective Data Analysis and Visualization
Applications. Morgan Kaufmann Publishers, San Francisco.
Selected Publications
Al-Saadi, J., J. Szykman, R. B. Pierce, C. Kittaka, D. Neil, D. Chu, L. Remer, L. Gumley, E. Prins, L.
Weinstock, C. Macdonald, R. Wayland, F. Dimmick, and J. Fishman (2005). Improving National Air
Quality Forecasts with Satellite Aerosol Observations. Bull. of the Amer. Meteor. Soc., 86, 1249-1261.
Ma, X. L., Z. Wan, C.C. Moeller, W.P. Menzel, and L.E. Gumley (2002). Simultaneous retrieval of atmospheric profiles, land-surface temperature and emissivity from Moderate Resolution Imaging
Spectroradiometer thermal infrared data: extension of a two-step physical algorithm. Appl. Optics, 41 ,
909-924.
Ackerman, S. A., Strabala, K. I., Menzel, W. P., Frey, R. A., Moeller, C. C., and Gumley, L. E. (1998).
Discriminating clear-sky from clouds with MODIS. Journal of Geophysical Research-Atmospheres, 103
(D24), 32141-32157.
Ackerman, S. A., C. C. Moeller, K. I. Strabala, H. E. Gerber, L. E. Gumley, W. P. Menzel, S-C. Tsay (1998).
Retrieval of effective microphysical properties of clouds: A wave cloud case study. Geophysical
Research Letters, 25, 1121-1124.
Smith, W. L., S. Ackerman, H. Revercomb, H. Huang, D. H. DeSlover, W. Feltz, L. Gumley, A. Collard
(1998). Infrared spectral absorption of nearly invisible cirrus clouds. Geophysical Research Letters, 25,
1137-1140.
King, M. D., Menzel, W. P., Grant, P. S., Myers, J. S., Arnold, G. T., Platnick, S. E., Gumley, L. E., Tsay, S.
C., Moeller, C. C., Fitzgerald, M., Brown, K. S., Osterwisch, F. G. (1996). Airborne scanning spectrometer for remote sensing of cloud, aerosol, water vapor and surface properties. J. Atmos. Oceanic
Technol., 13, 777–794.
Gumley, L.E., King, M.D. (1995). Remote Sensing of Flooding in the US Upper Midwest During the Summer of 1993. Bulletin of the American Meteorological Society, 76, 933-943.
47

David C. Tobin
Assistant Scientist
Cooperative Institute for Meteorological Satellite Studies
Space Science and Engineering Center, University of Wisconsin-Madison
1225 West Dayton St., Madison, WI 53706-1695
Tel: (608) 265-6281; Fax: (608) 262-5974; Email: dave.tobin@ssec.wisc.edu
Education:
Ph.D. Applied Physics, 1996. University of Maryland Baltimore County. Dissertation: Infrared Spectral
Lineshape Studies of Water Vapor and Carbon Dioxide.
M.S. Applied Physics, 1993. University of Maryland Baltimore County. Thesis: Carbon Dioxide Lineshapes in Pi-
Sigma and Pi-Delta Vibrational Transitions.
B.S. Physics, 1991. University of Maryland Baltimore County.
Research Areas:
Infrared molecular spectroscopy and atmospheric radiative transfer, Atmospheric water vapor, Infrared spectroradiometer calibration and validation, Infrared remote sensing.
Selected Publications:
Tobin, D. C. and co-authors, Radiometric and Spectral Validation of AIRS Observations with the Aircraft based
Scanning High resolution Interferometer Sounder, J. Geophys. Res.
, 2005, accepted.
Tobin, D. C., H. E. Revercomb, C. C. Moeller, and T. S. Pagano, Use of AIRS high spectral resolution infrared spectra to assess the calibration of MODIS on EOS Aqua, J. Geophys. Res.
, 2005, accepted.
Tobin, D. C. and co-authors, ARM Site Atmospheric State Best Estimates for AIRS Forward Model and Retrieval
Validation, JGR special issue on AIRS Validation, 2005, accepted.
Turner, D. D., D. C. Tobin, S. A. Clough, P. D. Brown, R. G. Ellingson, E. J. Mlawer, R. O. Knuteson, H. E.
Revercomb, T. J. Shippert, W. L. Smith, The AERI LBLRTM QME: A closure experiment for downwelling high spectral resolution infrared radiance, J. Atmos. Sci.
, 61, 2657-2675, 2004.
Revercomb, H. E. and co-authors, The Atmospheric Radiation Measurement Program's Water Vapor Intensive
Observation Periods: Overview, Accomplishments, and Future Challenges, BAMS , 84, 217-236, 2003.
Tobin, D. C., C. Velden, N. Pougatchev, S. Ackerman, Geosynchronous Imaging Fourier Transform
Spectrometer (GIFTS) Measurement Concept Validation Plan, GIFTS Project Document GIFTS-MCVP-
02-002, 12 February 2001.
Tobin, D. C., R. K. Garcia, H. E. Revercomb, R. O. Knuteson, A. H. Huang, J. Thom, B. Osborne, GIFTS
Simulated Dataset Description Document, NMP GIFTS UW-GIFTS-04-007, 30 August 2000.
Tobin, D. C. and co-authors, Downwelling Spectral Radiance Observations at the SHEBA Ice Station: Water
Vapor Continuum Measurements from 17-26  m, J. Geophys. Res.
, 104, 2081-2092, 1999.
Strow, L. L., D. C. Tobin, W. W. McMillan, S. E. Hannon, W. L. Smith, H. E. Revercomb, and R. O. Knuteson,
Impact of a New Water Vapor Continuum and Line Shape Model on Observed High Resolution Infrared
Radiances, JQSRT, 59, 303-318, 1998.
-broadened Tobin, D. C., L. L. Strow, W. J. Lafferty, W. B. Olson, Experimental Investigation of the Self- and N
2
Continuum within the 
2
Band of Water Vapor, Applied Optics, 35, 4724-4734, 1996.
Committees, Awards, Memberships:
Member, NASA Atmospheric Infrared Sounder Science Team
Member, AMS Atmospheric Radiation Committee
Group Achievement Award, NASA Earth Observing System (EOS) Aqua Mission Team
Associate Team Member, Atmospheric Radiation Measurement Science Team
Co-investigator, EOS Aqua Validation, EOS Aura Validation, NPOESS Preparatory Project Team
Most outstanding graduating senior award, UMBC, 1991.
NIST cooperative fellowship award and appointment, 1988-1991.
48

CURRICULUM VITAE - George N. Serafino
Supervisory Physical Scientist, Satellite Services Division
NOAA/NESDIS
Camp Springs, MD
George.Serafino@noaa.gov
Education:

B.S. (Physics), Trinity College, Hartford, CT (1975)

M.S. (Meteorology), University of Maryland (1979)
Experience:

2002-Present : Branch Chief, NOAA/NESDIS/SSD/Satellite Analysis Branch

1991-2002 : Science Data Manager, EOS Distributed Active Archive Center, NASA/Goddard Space
Flight Center

1989-1991 : Senior Scientist, ST Systems Corporation

1983-1989 : Research Scientist, Applied Research Corporation
George Serafino has been head of the Satellite Analysis Branch of the Satellite Services Division since
August 2002, part of the NOAA/NESDIS Office of Satellite Data Processing and Distribution. The Satellite
Analysis Branch continuously provides the National Weather Service, the National Center for
Environmental Prediction and other users of environmental data with near real-time satellite imagery and products from geostationary and polar orbiting instruments in support of hazards monitoring and disaster mitigation. Previously, he worked as a contract scientist at NASA/GSFC from 1983-1991, developing remote sensing techniques for ozone and temperature profile determination involving both traditional and combinatorial optimization methods. He joined NASA/GSFC as a civil servant in 1991 specializing in large scale scientific data processing, data management and science data support for the EOSDIS Distributed
Active Archive Center (DAAC) before joining the NOAA/NESDIS Satellite Analysis Branch.
Honors and Awards:

Goddard Certificate of Outstanding Performance (1993, 1994)

Goddard Performance Award (1993, 1994, 1996, 1997, 1999, 2000)

Goddard Special Act Award (1995, 1998)

Goddard Quality Increase Award (1995)

Goddard Productivity Group Award (1996)

Goddard Group Achievement Award (1995, 1999)

Goddard Customer Service Group Achievement Award (2001)
 Goddard “Best of the Best” Customer Service Group Award (2001)

Goddard Quality and Process Improvement Award (2002)
Select Publications:
Frederick, J. E., G. N. Serafino and A. R. Douglass, "An Analysis of the Annual Cycle in Upper
Stratospheric Ozone", JGR , 89 , 9547-9555, 1984.
Ellingson, R. G., and G. N. Serafino, "Observations and Calculations of Aerosol Heating over the Arabian Sea during MONEX", JAS , 41, 575-589, 1984.
Frederick, J. E., and G. N. Serafino, "The Detection of Long-Term Changes in Stratospheric Ozone: Scientific
Requirements and Current Results from Satellite Based Measurement Systems", J. Clim. and Appl.
Meteor ., 24 , 904-914, 1985.
Frederick, J. E., and G. N. Serafino, "Satellite Observations of Nitric Oxide Dayglow: Implications for the
Behavior of Mesospheric and Lower Thermospheric Odd Nitrogen", JGR , 90 , 3821-3830, 1985.
Frederick, J. E., and G. N. Serafino, "The Ultraviolet Spectral Albedo of the Planet Earth", Tellus , 39B , 261-
270, 1987.
49

Hudson, R. D., J. R. Herman and G. N. Serafino, "On the Determination of Long-Term Trends from SBUV
Ozone Data", in Ozone In The Atmosphere , R. D. Bojkov and P. Fabian (eds), A. Deepak
Publishing, 1989.
50

STEVE ACKERMAN
STATEMENT OF CURRENT AND
PENDING SUPPORT
Agency Project Title Award Period
________ ___________
NOAA
(Co-I)
Cooperative
Agreement between
ONR (Co-
I)
CIMSS and NOAA
Physical Modeling for
Processing
Geostationary
Imaging Fourier
NASA
Transform
Spectrometer Indian
Ocean METOC
Imager (IOMI)
Graduate Research
Assistantships at the
University of
Wisconsin in
Cooperation with the
Suomi-Simpson
SAIC
NSF
NASA
NASA
NASA
NASA
(Co-I)
______
$20,019,619.
00
$4,091,765.0
0
$98,851.00
______
10/1/00-
12/31/05
5/1/01-
4/30/06
7/15/02-
7/14/05
Graduate
Fellowships
Professional
Technical Services for Asratss
A Land Surface
Model Hind-Cast For
$88,216.00 10/30/02-
11/30/05
$199,425.00 1/1/03-
12/31/07 the Terrestrial Arctic
Drainage System
Suomi-Simpson $425,000.00 1/15/04 -
Graduate Fellowship
Refinement and
Maintenance of the
MODIS Cloud Mask
Algorithm on TERRA and Aqua $189,510.00
01/14/09
5/12/04-
5/11/07
Global Analysis of
MODIS Level-3
Cloud Properties and
Their Sensitivity to
Aggregation
Strategie
Land Surface
Characterization
Using High Spectral
Resolution AIRS and
Moderate Spatial
Resolution MODIS
Observations from the EOS Aqua
Platform
$259,374.00
$100,000.00
6/1/04 -
5/31/07
05/1/04-
4/30/07
*Commi tted Location
______
__ ______
5 UW-
Madison
13
0.5
0.2
0.7
0.3
UW-
Madison
UW-
Madison
UW-
Madison
UW-
Madison
UW-
Madison
4
UW-
Madison
6
UW-
Madison
1.3
UW-
Madison
51

STATEMENT OF CURRENT AND PENDING SUPPORT
Supporting
Wayne F. Feltz
Award
______
Remaining
Agency
_________
Project Title
__________
Period **Committed
______ __________
NASA (PI,PM)
Advanced Satellite Aviation-Weather
$720,000 9/1/03 - 12/31/05 4
Products Prod (subcontract)
Univ of Miami
(Co-I)
M-AERI AIRS Validation $250,000 1/1/04 - 8/31/06 2
NOAA
NAVY
(Co-I/PM)
WVSS-II Validation
Multiple University Research Initiative
NASA (Co-I) DOE ARM Site AIRS Validation
NASA (Co-PI)
Decision Support for Aircraft Avoidance
of Convectively-Induced Turbulence
NASA (PI) TAMDAR Validation
$184,000 6/1/05
– 5/30/07 1
$4,091,765 5/1/01 - 4/30/06 1
$128,000
$280,000
3/13/04-3/14/07 1
1/1/06-12/31/08 2
**Represents Work Months for the Period Covered.
$140,000 2/1/05-12/31/05 1
(Co-I)
STATEMENT OF CURRENT AND PENDING SUPPORT
Agency Project Title
DOE
David Tobin
High Spectral Resolution
FTIR Observations for the ARM Program:
Award Period
$1,421,293 11/1/99
10/31/0
-
**Com mitted FTE Location
5 0.08 UW-
Madison
5
NASA
(Co-I)
NASA
(Co-I)
Continued Technique
Development, Evaluation and Analysis
ARM Site Atmospheric
State Best Estimates for
Aqua: Retrieval,
Radiance, and Forward
Model Validation
Government Study in
Support of a Broad
Scope of NPOESS
Calibration and
Validation Activities:
$389,609
$1,299,966
3/15/04
3/14/07
1/1/04-
12/31/0
-
4
11.4
6.75
0.3
0.56
UW-
Madison
UW-
Madison
ONR
(Co-I)
NASA
(Co-I)
NPOESS/IPO Contract
50-SPNA-1-00039
Physical Modeling for
Processing
Geosynchronous
Imaging Fourier
Transform Spectrometer-
Indian Ocean Metoc imager (GIFTS-IOMI)
Hyperspectral Data
Particpation on the NPP
Science Team
$3,851,765
$527,557
5/1/01 -
4/30/06
2/15/04
-
4.1
5.6
0.06
0.01
UW-
Madison
UW-
Madison
52

NASA
(Co-I)
NASA
JPL
Using AIRS to Assess the Consistency and
Stability of EOS IR
Measurements for
Climate Studies: Aircraft
Based Validation of AIRS
Provides a Key Link
GIFTS
AIRS Surface Emissivity
Retrieval Algorithm
$749,144
2/14/07
1/10/03
-
9/30/06
$3,154,460 10/1/00
- 7/1/05
$50,000 4/1/04-
6/30/05
4.5
0.5
0.5
0.1 UW
Madison
UW
0.01 Madison
0.01 UW
Madison
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Ash using Multi-spectral Infrared Imagery. J. Geophy. Res., 108, D12, 4356.
Ellrod, G. P. and A. J. Schreiner, 2004: Volcanic ash and cloud top estimates from
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Hillger, D. W. and J. D. Clark, 2002: Principal Component Image Analysis of MODIS for Volcanic Ash. Part I: Most Important Bands and Implications for Future GOES
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Holasek, R. E., Self, S., and Woods, A. W. (1996) Satellite observations and interpretation of the 1991 Mount Pinatubo eruption plumes. Journal of Geophysical
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Holz, R. E., S. A. Ackerman, P. Antonelli, F. Nagle, R. O. Knuteson , M. McGill, D. L.
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Slicing Cloud Top Altitude Retrieval, Accepted Jour. Atmos. Ocean. Tech.
Lazzara, M. A., J. M. Benson, R. J. Fox, D. J. Laitsch, J. P. Rueden, D. A. Santek, D. M.
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Miller, T. P., and T. J. Casadevall, 2000: Volcanic ash hazards to aviation. Encyclopedia of
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Oppenheimer, C. (1998) Volcanological applications of meteorological satellites.
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Parol, F., J. C. Buriez, G. Brogniez, and Y. Fouquart, 1991: Information content of AVHRR channels 4 and 5 with respect to the effective radius of cirrus cloud particles. Jour. Appl.
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Pavolonis, M. J. and A. K. Heidinger, 2004: Daytime cloud overlap detection from AVHRR and
VIIRS. J. Appl. Meteorol.
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Pavolonis, M. J., A. K. Heidinger, and T. Uttal, 2005a: Daytime global cloud typing from
AVHRR and VIIRS: Algorithm description, validation, and comparisons. J. Appl. Meteorol.
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Pavolonis, M. J., W. F. Feltz, ,A. K. Heidinger, and G. M. Gallina 2005b: "A daytime complement to the reverse absorption technique for automated detection of volcanic ash", Submitted to JTECH
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Pavolonis, M. J. and A. K. Heidinger, 2005b: Advancements in identifying cirrus and multilayered cloud systems from operational satellite imagers at night. International Asia-
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55