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1. FY09 GIMPAP Project Proposal Title Page Revised: October 31, 2008. Title : Enhanced Utilization of GOES I/M Project Type : Product Improvement Status : Renewal Duration : 2 years Leads: Robert M Rabin NOAA/ National Severe Storms Laboratory (NSSL) Other Participants :
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1. FY09 GIMPAP Project Proposal Title PageRevised: October 31, 2008 • Title: Enhanced Utilization of GOES I/M • Project Type: Product Improvement • Status: Renewal • Duration: 2 years • Leads: • Robert M Rabin NOAA/National Severe Storms Laboratory (NSSL) • Other Participants: • Phillip Bothwell, Steve Weiss NOAA/Storm Prediction Center • V. Lakshmanan NOAA/NSSL and CIMMS/Univ. of Oklahoma
2. Project Summary • Work closely with the NSSL and NESDIS, the Cooperative Institutes (CIMSS & CIRA), MDL and SPC on several projects, which utilize satellite observations to mitigate deficiencies in the national radar network. • Incorporation of storm tracking, satellite winds, and fire products into N-AWIPS to meet the needs of the NOAA/Storm Prediction Center (SPC). • Incorporation of existing satellite rainfall algorithms into National grid (NMQ) and evaluation in collaboration with OHD, NESDIS, CREST. • Implementation of precipitation efficiency algorithm and mesoscale winds at the NESDIS SAB • Collaboration with CIRA on microphysical storm severity techniques. • Consulting and training on the use and interpretation of satellite data with emphasis on the SPC and NSSL.
3. Motivation/Justification • Support NOAA Mission Goal(s): Serve society's needs for weather and water information. • Develop applications to enhance utilization of GOES I/M in conjunction with Doppler radar & other data sources for the detection and forecasting of hazardous weather. • Optimize synergistic use of national satellite and radar networks • Explore new uses of current sensors • Future application to enhanced features of GOES-R • Collaboration of NOAA/OAR and NESDIS/ORA on NOAA wide efforts
4. Methodology • Implement GOES-based storm tracking and 1-hr forecasts (storm relative applications). • Monitor fires with rapid scan data, collaboration with E. Prins & SPC • Maintain and improve mesoscale winds and fire products in N-AWIPS at the SPC and SAB. • Explore use of high temporal resolution data in product development (1 –min GOES-10 and GOES-13 datasets). • Explore the use of Cloudsat data as validation for cloud-top heights. • GOES rainfall verification with radar and gauges. • Apply latest techniques to radar & multispectral satellite data • Probabilistic QPE using radar and satellite data as predictors • Apply sounder and imager cloud products to radar quality control • Evaluation of precipitation efficiency techniques during winter season • Further development storm severity techniques and evaluation • Possible implementation to web-based tools and N-AWIPS
Greensburg, KS Storm 05 May 2007 WV 0215 UTC VIS 0115 UTC
5. Expected Outcomes • Improved tracking tool for MCS including 1-hr nowcast • link storm attribute and environmental information from Doppler radar and satellite • storm top features (e.g., warm-cold couplet, 4 micron reflectivity) vs. storm intensity • web-based, output to N-AWIPS (possibly AWIPS). • Additional applications of MWV including combined wind analysis with WSR-88D VWP and divergence profiles, storm relative wind flow, use of rapid-scan data. • Wind fire intensity product, possible combination with wind estimation from smoke plume tracking, and WSR-88D data. • New techniques to diagnose storm intensity • Benchmark for QPE skill, short-term QPF, precipitation efficiency. • Storm top studies: synergism with research satellites (CloudSat, etc).
6. Progress in FY08 • FY08 • improved MCS tracking tool developed for web (to include time trends and 1-2 hr forecast) • improved mesoscale wind analysis to utilize new first guess and visible winds (GFS model). Operational use at SAB. • inclusion of RISOP data at SPC & collaborate with CIMSS on development of fire intensity product. Exploration of combined GOES WSR-88D fire & smoke detection. • further develop new techniques for storm intensity: visible overshooting tops,IR couplets • evaluation and improvement of existing QPE techniques • K-means tracking and nowcasting • Hydroestimator vs. WSR-88 comparisons • Evaluation of Dendritic Ice Growth identification technique at SAB • evaluate storm height comparisons with GOES, WSR-88D and CloudSat • In progress, New Mexico Ozone-lightning expeirment.
"K-means" technique for tracking satellite cloud top and radar reflectivity features.
Wind vectors and horizontal divergence at 300 mb (green contours) from GOES water vapor imagery.
Combined smoke plume + fire source image from 2130 UTC 12 March 2008 over Oklahoma. Smoke plumes (WSR-88D radar reflectivity in color) superimposed on GOES-12 3.9 micron brightness temperature (hot spots: dark). Distance between range rings is 50 km.
GOES 1km visible probability of “overshooting tops”: 11 June 08 2332 UTC
1745Z Heavy Snow Signature Heavy snow signature from Dendritic Growth Algorithm 8 March 2008, 1745 UTC. (Cloud top pressure for clouds < -15 deg C with UVV < -5 microbar/s).
1745Z Image 17Z Weather Moderate to Heavy Snows Location of moderate and heavy snow, 8 march 2008, 1800 UTC.
7. FY09 Milestones • FY09 • testing of improved MCS tracking and nowcasting tool in N-AWIPS • development of combined real-time mesoscale wind analysis (WSR-88D and GOES) • testing the utility of fire intensity product at SPC (comparison with surface winds) • further testing of dendritic growth algorithm with relative humidity, orographic factors • document applications which go directly to NWS
Funding Sources Procurement Office Purchase Items FY07 FY08 FY09 StAR Total Project Funding $32 $32 $32 GIMPAP 0 0 0 0 0 0 Other Sources $58K $56 $22 $20K $18 $18 $38K $38 $4 $8K 0 ? NASA 8. Funding Profile (K) GOES-R3 NOAA-HPCC • Summary of leveraged funding • GOES-R3: Shared development of nowcasting and precipitation tracking • NOAA-HPCC: Investigate use of environmental conditions for nowcasting MCS intensity trends. • NASA Sensor-web: Development of enhanced-V, overshooting top algorithm development for possible use in nowcasting. • OAR/NSSL: Use of IT resources at NSSL
9. Expected Purchase Items • $32,000 FY09 Total Project Budget • BOP to NSSL • Salary: R. Rabin, V. Lakshaman (CIMMS, Univ. Okla) $21,000 • Federal Travel: R. Rabin. Norman,OK to: Madison,WI;approx 12 trips Ft. Collins,CO;approx 2 trips $4,000 • IT support (NSSL) $7000