PASS#41573
Continuation Proposal to
National Oceanic and Atmospheric Administration
National Environmental Satellite, Data, and Information Service
Office of Systems Development
Washington DC
Research and Development for GOES-R Risk Reduction for
Mesoscale Weather Analysis and Forecasting
Cooperative Institute for Research in the Atmosphere
Colorado State University – DUNS #78-597-9618
Foothills Campus
Fort Collins CO 80523-1375
Dr. Thomas H. Vonder Haar,
Principal Investigator
In partnership with
Dr. Mark DeMaria
Regional and Mesoscale Meteorology Team Leader
NESDIS Office of Research and Applications
Telephone: 970-491-8405
Email: Mark.DeMaria@noaa.gov
Debra Molenar
CIRA/Regional and Mesoscale Meteorology (RAMM) Team
Colorado State University
Telephone: 970-491-8447
Email: Molenar@cira.colostate.edu
April 2004
Period of Activity: July 1, 2004 – June 30, 2005
____________________________
Dr. Thomas H. Vonder Haar, P.I.
Director, CIRA
(970) 491-8448
__________________________
Mary Atella
Senior Research Administrator
Office of Sponsored Programs
(970) 491-2083
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1. Introduction
The next generation GOES satellites (beginning with GOES-R) will include an
Advanced Baseline Imager (ABI) and Hyperspectral Environmental Suite (HES) with
vastly improved spectral, spatial and temporal resolution relative to the current GOES IM series satellites. The GOES-R era will begin early in the next decade, and will be part
of a global observing system that includes polar orbiting satellites with comparable
spatial and spectral resolution instrumentation. However, GOES-R will have superior
temporal resolution. A continuing science study is proposed to use numerical simulations
and existing in situ and satellite data to better understand the capabilities of these
advanced instruments for mesoscale weather analysis and prediction. This science study
will help to reduce the time needed to fully utilize GOES-R as soon as possible after
launch.
The first phase of this study is a three-project to simulate subsets of GOES-R
observations existing satellites and to create synthetic GOES-R observations using
numerical cloud model simulations coupled with radiative transfer code. A part of the
modeling project is to develop an advanced data assimilation method based upon the
ensemble Kalman filtering approach that can be used to assess the value of GOES-R data
for numerical weather prediction. This proposal is for the second year of the first phase,
which began in July of 2003.
The second phase of the study will make use of the knowledge gained in the first
phase to develop experimental products. The second phase will test these products when
possible using existing operational and experimental satellites. Data assimilation
experiments with real observations will also be performed in the second phase. This
aspect of the project will be closely coordinated with the Joint Center for Satellite Data
Assimilation (JCSDA). The second phase will also include a training and outreach
component on both the national and international levels. This work will be coordinated
with the Virtual Institute for Satellite Integration Training (VISIT) program and the
International Virtual Laboratory efforts of the World Meteorological Organization.
In the third phase, preparation will begin on the development of Day-1 operational
products, and training activities will increase. Increased coordination with the JCSDA
will occur during phase three to identify methods to utilize GOES-R data in operational
mesoscale numerical models.
One of the advantages of GOES-R is the high temporal resolution that is possible
from geostationary orbit. The emphasis of our science study is on mesoscale atmospheric
phenomena that evolve on time scales faster than that which can be sampled from polar
orbiting satellites. These phenomena include tropical cyclones, severe weather and
mesoscale aspects of winter weather, including lake-effect snowfall. This emphasis will
continue throughout the project. Results from year 1 are briefly summarized below,
followed by plans for year 2 (the current proposal). A research and budget outline of the
longer-term phases of the project is also provided, followed by a detailed budget for the
current year.
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2. Summary of Results from Year 1
The emphasis of the first year was on the establishment of the case study database,
and the set up of the numerical cloud model and radiative transfer code. The three initial
case studies were chosen as follows:
1. Hurricane Lili (Sept. 21-Oct. 5, 2002). Lili formed in the Caribbean, rapidly
intensified in the Gulf of Mexico, and then rapidly weakened just before making landfall
along the Louisiana coast.
2. The May 7-10, 2003 Severe Weather Outbreak. During this four-day period, 1463
severe weather reports were logged by the NCEP Storm Prediction Center, including 223
tornados. This outbreak affected a large area from the front range of the Rockies through
the Midwest.
3. The February 12-14, 2003 Lake-Effect Snow Storm “Newton”. A narrow band of
snow formed downwind of Lake Ontario and dropped about 50 inches of snow centered
on Oswego County, NY. A less intense snow band formed east of Lake Erie. This event
was nicknamed “Newton” by the Buffalo NWS office, who informally names the most
intense Lake-Effect snowstorms.
These first case studies were supplemented by two additional case studies as follows:
4. Hurricane Isabel Near Peak Intensity, Sept. 11-13, 2003: During this period, hurricane
Isabel was at or near category 5 intensity in the central-west Atlantic, and had interesting
mesoscale structure within its eye. GOES super-rapid scan observations and extensive in
situ data from hurricane aircraft were available during most of this period.
5. California, Utah, Colorado Fog Outbreak, Jan.12, 2004: A large and long-lasting fog
outbreak occurred on this day, with considerable economic impact due to the closure of
the Fresno, California airport for nearly an entire day. This case study will be useful for
development of GOES-R fog detection algorithms over relatively flat (the Sacramento
Valley) and mountainous terrain (Utah and Colorado).
Imager and sounder data from GOES, AVHRR data from POES, AIRS soundings, and
MODIS imagery were collected for all of the case studies. Routine in situ data and
special observations such as those from the ARM-site and hurricane aircraft were also
collected for these cases. Further details of the case studies and sample images can be
found at http://www.cira.colostate.edu/ramm/KFIntranet/GOESR_IPO/GOESR_IPO_case_study_database.html
Numerical model simulations of the severe weather event and the lake effect snow
case were performed, and the simulations for other case studies are under development.
Radiative transfer code is also being developed to create synthetic GOES-R observations
from the numerical model output. This is the only way that the temporal aspects of
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GOES-R can be simulated before the launch of GOES-R, unless the GIFTS program was
fully successful, which does not appear likely at this point.
Preliminary results from the first year will be presented at the GOES Users
Conference in May of 2004, at the SPIE conference in Denver, in August of 2004, and at
the AMS Conference on Satellite Meteorology and Oceanography, in September of 2004.
Titles of the presentations are listed in the references section at the end of this proposal.
Further details of the first year progress can be found in the project quarterly reports
provided to Paul Menzel, or at
http://www.cira.colostate.edu/ramm/KFIntranet/ProposalReports/GOESR_FY04_2ndq_prog_rep.doc
and
http://www.cira.colostate.edu/ramm/KFIntranet/ProposalReports/prevgoes_r.html
3. Current Year Plans
In the second year of phase one, the data collection activities will continue. At least
one more case of a polar low will be added to the database. Polar lows are mesoscale
disturbances with some characteristics in common with tropical cyclones. However, polar
lows occur at very high latitudes, where the time continuity of polar orbiting data is
optimized. Using data from multiple satellites, it should be possible to obtain coverage
with temporal resolution on the order of one hour, which is much better than what is
possible at low latitudes.
The generation of synthetic data using numerical and radiative transfer models will
also continue. The simulation of Hurricane Lili will be completed, and synthetic imagery
of multiple channels of the ABI will be generated. For this purpose, the radiative transfer
model coefficients for the MODIS channels being developed by the JCSDA will be
utilized. The MODIS instrument has channels similar to nearly all of the ABI channels.
Using the GOES-R data simulated from existing satellites, and the synthetic GOESR data from the coupled numerical/radiative transfer model, the following six science
studies will be performed.
1. Evaluation of Hyperspectral IR Soundings in Tropical Cyclone Environments: One of
the first questions that will be explored is the information content of IR soundings from
hyperspectral instruments. Temperature and moisture retrievals from the AIRS
instrument for Hurricane Lili have been obtained and will be compared with in-situ data
and from NCEP model analyses. Special GPS soundings from the NOAA Gulfstream jet
in the data void regions of the Gulf of Mexico have been obtained for comparison. This
study will be expanded by comparing AIRS and in situ soundings for other cases. This
evaluation is the first step towards utilizing hyperspectral IR soundings in numerical
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model simulations if it can be shown that these sounding provide information not
contained within current operational analyses.
2. Hyperspectral Environmental Suite (HES) Data Availability Study: One of the
potential advantages of the HES is the high temporal resolution provided by the
geostationary platform. The numerical model simulations will be used to estimate the
number of relatively cloud free regions (determined by the cloud concentrations in the
predictions) to determine potential usefulness of the HES for these types of
meteorological phenomena. The impact of the required horizontal and temporal
resolution of the HES will also be addressed.
3. Data Assimilation Studies: The impact of HES soundings will be assessed for the case
studies using an idealized “identical twin” framework, followed by impact studies where
AIRS and other GOES-R-like data are assimilated using an Ensemble Kalman Filter
(EKF) data assimilation system. The EKF method has the advantage that the background
error covariance matrix is predicted, rather than specified, and so it is flow dependent.
Another advantage of the EKF method is that the adjoints of the cloud and radiative
transfer models are not required. This assimilation system is much more adapted to the
assimilation of satellite and other data in mesoscale environments, and this method is
under consideration for future versions of the NCEP mesoscale model. In phase one of
this project, the emphasis will be on the identical twin experiments.
4. Tropical Cyclone Intensity and Structure Diagnostic Algorithms: Both simulated and
real data will be used to investigate new algorithms for estimating tropical cyclone wind
structure and intensity from GOES-R observations. For this project, additional tropical
cyclone observations, with emphasis on AVHRR and MODIS will be obtained.
5. Severe Weather Nowcast Algorithms: Both simulated and real data will be used to
investigate new algorithms for nowcasting and short-term forecasting of severe weather
in the GOES-R era. The initial emphasis is on applications that rely on a combination of
storm environmental parameters (thermodynamic profiles, etc) and storm parameters as
determined by satellite-derived storm top structure and vertical profiles of satellitederived estimates of effective radius versus temperature.
6. ABI Information Content Analysis: ABI imagery simulated from MODIS is being used
in an information content analysis, to identify potential new products for mesoscale
weather analysis and forecasting. Principal components are being calculated from a
subset of the MODIS channels that are close to the ABI channels for each of the case
studies. The contributions to the principal components from each MODIS channel helps
to identify new methods for extracting information from combinations of the ABI bands.
A detailed budget for the current year can be found in the Appendix.
4. Longer Range Plans
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As described in the Introduction, this project is part of a longer-range science plan for
GOES-R Risk Reduction for mesoscale weather. Brief summaries and proposed budgets
are provided below.
Phase 1: FY03-FY05:
Phase 1 will use a case study approach to simulate subsets of GOES-R observations
existing satellites and to create synthetic GOES-R observations using numerical cloud
model simulations coupled with radiative transfer code. The emphasis will be to
demonstrate the utility of GOES-R and development of an advanced data assimilation
system that can optimize the use of satellite observations for mesoscale weather
forecasting. Section 3 described the primary science studies in phase 1. The budget for
phase 1 is summarized below.
Budget for Phase 1:
FY03 – 350 K (already funded)
FY04 – 197 K (this proposal)
FY05 – 315 K (proposed)
Phase 2: FY06-FY09:
In phase 2, the results from the phase 1 case studies will be applied to experimental
product development when possible using existing experimental and operational
satellites. These products will be applied to similar mesoscale weather events as in the
case studies, and experimental real-time results will be made available via the Internet.
The numerical modeling studies will transition from the underlying CSU RAMS model to
the Weather Research and Forecast (WRF) model, to become more aligned with the
efforts at operational forecast centers. In addition, the emphasis of the assimilation
experiments will shift from idealized identical twin experiments to those with real data. It
is anticipated that the EKF assimilation system will be in a mature stage when phase 2
starts. A new aspect of phase 2 will be the emphasis on training material through
coordination with the Virtual Institute for Satellite Integration and the International
Virtual Laboratory in coordination with the WMO and the Regional Meteorological
Training Centers. Training material will be developed and delivered, sample simulated
data sets will be made available via the web, and experimental products using existing
satellite data will be provided.
Proposed Budget for Phase 2:
FY06 – 450 K
FY07 - 500 K
FY08 - 550 K
FY09 - 600 K
Phase 3 – FY10-FY12
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In the third phase, preparations will begin for testing experimental GOES-R mesoscale
products based upon the results from phases 1 and 2. Education and training activities
will increase in preparation for the launch of GOES-R. The numerical modeling aspects
of the project will be even more closely coordinated with NCEP and other operational
forecast centers.
Proposed Budget for Phase 3:
FY10 – 600 K
FY11 – 600 K
FY12 – 650 K
5. Project Personnel
Project Oversight will be provided by Prof. Thomas Vonder Haar (CIRA/CSU) and Dr.
Mark DeMaria (NESDIS/ORA). Scientific guidance will also be provided by Dr. James
Purdom, a CIRA Senior Research Scientist, and former Director of ORA.
The numerical modeling studies will primarily be performed by Drs. Dusanka Zupanski,
Louis Grasso, M. Sengupta with oversight from Mark DeMaria. Dusanka is a CIRA
employee who formerly worked for the NCEP Environmental Modeling Center, and is an
expert on mesoscale modeling and data assimilation. Louis Grasso has extensive
experience with the RAMS model, and was a former student of Dr. Bill Cotton, the
original developer of RAMS. M. Sengupta will lead the radiative transfer modeling
activities. M. DeMaria is a NESDIS ORA employee with an extensive background in
tropical cyclone analysis and forecasting, and numerical weather prediction.
The database development will be overseen by Debra Molenar and M. DeMaria. Debra
leads the RAMM Team computer infrastructure group and has considerable experience in
database management, satellite data processing and programming. A 1/4 time CIRA
computer programmer will also be supported to assist with the database development, as
well as with analysis of the numerical modeling output.
Don Hillger will lead the information component analysis segment of the project, and is
the primary focal point for coordination with ORA to obtain AIRS temperature and
moisture retrievals.
The project also will include a graduate student to focus on a specific aspect of the
research, depending upon her interests, and a student hourly employee to assist with data
processing. The inclusion of students will help cultivate future scientists that have
familiarity with the GOES-R program.
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5. Proposed Budget
The proposed budget for the current year of the project is $197 K. A detailed breakdown
of the costs is provided in the attached spreadsheet. Budget estimates for the out-years of
this proposal are included in section 4.
6. Project Coordination and Documentation
This research is part of a larger GOES-R Risk Reduction program that is being
coordinated with NESDIS/ORA and NESDIS/OSD. Quarterly progress reports will be
provided to OSD and ORA management, and research results will be presented at annual
activities reviews.
7. Budget Explanation
I and II. PERSONNEL and FRINGE BENEFITS
Salaries and benefits are requested for the personnel that will be performing this research,
and providing administrative and computer support. In a basis consistent with our longstanding Memorandum of Understanding between NOAA and Colorado State University,
the enclosed budget specifically includes support for administrative and clerical
personnel (Fryer) directly associated with the technical and managerial administration of
GIMPAP. This support is “quid pro quo” for the reduced indirect cost rate agreed upon
in the long-standing subject memoranda. K. Fryer will provide communication and
collaboration support, assist in the acquisition and distribution of reference materials
relevant to the conception and execution of the project, technical editing of scientific
manuscripts, specialized reports and conference papers. All other budgeted personnel are
directly involved in the research which is identified in the Statement of Work (SOW).
III. DOMESTIC TRAVEL
Funds are requested for two trips to Washington, DC for coordination with ORA
scientists. These trips are required to obtain the necessary radiative transfer modeling
capabilities, and training on some of the specialized experimental satellite data to be used
in this research. One trip to Norfolk, VA is requested to present results from this research
at the AMS Conference on Satellite Meteorology and Oceanography.
IV. OTHER
1. The NT computer charges provide computer and data support associated with this
project. The NT hourly rate is determined by CIRA and depends on the actual cost of the
CIRA computer operations. CIRA charges Windows NT computer costs on an hourly
basis, based on log-on time collected electronically via infrastructure programs.
2. Much of this research is performed in a McIDAS programming environment. A
McIDAS Users Group (MUG) fee is necessary to use and update this software.
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3. Funds are requested for publication of research results.
V. TUITION
It is anticipated that one graduate student will be supported as part of this research
project.
8. References
Posters to be presented at the GOES-R User’s Conference, May 10-13, 2004, Boulder,
CO
DeMaria, M., D.W. Hillger, J.F.W. Purdom, R.M. Zehr, H. Gosden, D.L. Watson, J.A.
Knaff, D.T. Lindsey, and D.E. Bikos: Advance Mesoscale Product Development for
GOES-R Using Operational and Experimental Satellite Observations.
Grasso, L.D., M. Sengupta, D. Zupanski, M. Zupanski, J.F. Dostalek, and M. DeMaria:
Applications of Simulated GOES-R Observations for Advance Product Development
for Mesoscale Weather Forecasting.
Papers to be presented at the International Society for Optical Engineering Conference
session on Weather and Environmental Satellites, August 2-6, 2004, Denver, CO
Hillger, D.W., M. DeMaria, and R.M. Zehr: Advance Mesoscale Product Development
for GOES-R Using Operational and Experimental Satellite Observations.
Grasso, L.D., M. Sengupta, and M. DeMaria: Applications of Simulated GOES-R
Observations for Advance Product Development for Mesoscale Weather Forecasting.
Posters to be presented at the AMS 13th Conference on Satellite Meteorology and
Oceanography, Sept. 20-24, 2004, Norfolk, VA
Combs, C.L., M. DeMaria, W. Blier, and W. Strach: Exploring the timing of fog
formation and dissipation over the San Francisco Bay area using satellite cloud
climatologies.
DeMaria, M., D.W. Hillger, C.D. Barnet, J.P. Dunion, and R.T. DeMaria: Evaluation of
Hyperspectral Infrared Soundings in Tropical Cyclone Environments.
Dostalek, J.F., L.D. Grasso, M. Sengupta, and M. DeMaria: Applications of synthetic
GOES-R observations for mesoscale weather analysis and forecasting.
Hillger, D.W., and T.J. Schmit: Quantization Noise for GOES-R ABI Bands.
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Hillger, D.W., M. DeMaria, and J.F.W. Purdom: Analysis of Simulated GOES-R Data
and Products for Mesoscale Meteorology.
Sengupta, M., L.D. Grasso, and M. DeMaria: Simulation of Visible/Infrared
Imager/Radiometer Suite (VIIRS) Observations for Application to Mesoscale Analysis
and Forecasting.
Zehr, R.M.: Satellite Products and Imagery with Hurricane Isabel.
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