A Research Plan for GOES-R Risk Reduction



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@

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. Mary Atella

Director, CIRA Senior Research Administrator

(970) 491-8448 Office of Sponsored Programs

(970) 491-2083

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 I-M 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.

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

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 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



and



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 GOES-R 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 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 satellite-derived 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

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

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.

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 long-standing 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.

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.

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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