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UW-CIMSS Advanced Satellite Aviation-weather Product Overview W. Feltz and ASAP Team 8 June 2005

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Presentation on theme: "UW-CIMSS Advanced Satellite Aviation-weather Product Overview W. Feltz and ASAP Team 8 June 2005"— Presentation transcript:

1 UW-CIMSS Advanced Satellite Aviation-weather Product Overview W. Feltz and ASAP Team 8 June 2005

2 ASAP Overview What is ASAP? Why is this being presented at the MURI workshop?? Aviation Satellite Research Products and Collaborations Data access and references

3 Advanced Satellite Aviation- weather Products (ASAP): Primary Goal: Develop and Provide High Resolution (Temporally and Spatially) Weather Products in Near Real-time to Improve Avaition Safety Who: A Collaborative Research Venture between NASA & FAA, NCAR, SSEC/CIMSS, & U-Alabama Huntsville, Funded by NASA to aid FAA in satellite data infusion into Aviation Meteorological Products How: Develop applications to support detection of aviation hazards (visibility, turbulence, volcanic ash, convection, etc) using current and future satellite based instrumentation -> FAA PDT’s

4 What NCAR Product Development Teams might Benefit from Satellite Data? The Product Development Teams (PDT)s are: In-Flight Icing Aviation Forecasts Quality Assessment Turbulence Winter Weather Research Convective Weather National Ceiling and Visibility NEXRAD Enhancements Juneau Terrain-Induced Turbulence Model Development and Enhancement Oceanic Weather

5 Why ASAP Overview Presented Here? ASAP has provided a “head start” towards Broadband/Narrowband IR derived interest fields used for detection of aviation hazards. The FAA PDT’s had been under utilizing satellite information. ASAP’s mission to tailor satellite products for use in PDT “smart algorithms”. MURI has provided the funding for basic research to improve our hyperspectral resolution, and we are looking to use these data sets to simulate future geostationary hyperspectral resolution derived aviation weather products relevant to FAA and Navy safety concerns.

6 UW-CIMSS ASAP TEAM PI Lead: Wayne Feltz (CIMSS Product Science Leads in Yellow) Clouds: Sarah Bedka, M. Pavolonis, and T. Schriener Convection: Kris Bedka and J. Mecikalski (UAH) Turbulence: Tony Wimmers, N. Uhlenbrock, and J. Mecikalski (UAH) Volcanic Ash: Mike Pavolonis, S. Ackerman, M. Richards, and J. Mecikalski (UAH) Winds: Tim Olander, K. Bedka, and C. Velden Oceanic Weather: Wayne Feltz and ASAP Team

7 Advanced Satellite Aviation-weather Products (ASAP) Satellite Derived Fields Turbulence Volcanic Ash Convection Cloud Top Altitude/Mask Validation

8 Cloud Mask and Heights (Sarah Bedka, Wayne Feltz, Anthony Schreiner, Mike Pavolonis) Products/Research: – CONUS GOES imager/sounder derived cloud mask and cloud top heights – Validation study completed (S. Bedka talk) – Composite upper tropospheric satellite cloud mask using MODIS/GOES/AVHRR – Cloud typing algorithm for GOES/AVHRR/MODIS Collaborations: Collaborations: P. Herzegh (C/V PDT) and C. Kessinger (OW PDT) ASAP Progress/Needs: ASAP Progress/Needs: Determine where satellite cloud products will be useful for C/V and OW PDT

9 CONUS Cloud Top Altitude/Mask Validation Global Composite Cloud Mask Cloud Typing

10 05 December 2003 The University of North Dakota Citation flew below the ER-2 and released dropsondes. NASA ER-2 Flight trackGOES-12 Imager 11 µm BT UTC ( EST)

11 05 December MAS image displayed with RGB (1.62µm, 0.65µm, 1.88µm) Courtesy of the AtREC MAS team Time (UTC) GOES-12 Imager Infrared Window method GOES-12 Imager CO 2 Ratio method

12 05 December 2003 Red: GOES Imager Orange: Scanning-HIS Blue: GOES Sounder Orange: Scanning-HIS

13 05 December 2003 Differences exist between the SHIS and planned space-borne hyperspectral instruments. However, preliminary results are encouraging for the future of satellite hyperspectral technology.

14 Winds (Kris Bedka, Tim Olander, and Chris Velden) Products/Research: – Mesoscale High Resolution Atmospheric Motion Vectors (AMV) – Synoptic scale satellite derived winds (with preservation of areas of high jet streak winds) – Interpolated to standard aviation flight levels with GFS model used to fill data sparse regions – Validation ongoing vs ACARS, wind profiler, and lidar Collaborations: Collaborations: J. Hawkins (NRL), C. Kessinger (OW PDT), R. Frielich/B. Sharman (Turb PDT) ASAP Needs: ASAP Needs: Guidance on oceanic wind needs and review possibility of satellite derived turbulence interest field with high density AMV’s

15 Oceanic Cloud Classification Multi-spectral GOES-12 data for can be used to classify the various cloud features present within a scene Features highlighted here represent 1) small, immature cumulus 2) mid-level cumulus 3) deep convection 4) thick cirrus anvil 5) thin clouds

16 mb 1/120 th of vectors shown 1/30 th of vectors shown 1/5 th of vectors shown Oceanic Satellite Atmospheric Motion Vectors Meso-scale satellite AMVs provide detailed depictions of flow near convective cloud features Validation of AMVs using ACARS and wind profiler data is a future ASAP effort

17 Low Vectors (> 700 mb) Speed RMS: 4.15 m/s Speed Bias:.87 m/s Direction RMS: 42.7 ° Middle Vectors ( mb) Speed RMS: 4.52 m/s Speed Bias: -.41 m/s Direction RMS: 27 ° High Vectors (< 400 mb) Speed RMS: 7.94 m/s Speed Bias: -.05 m/s Direction RMS: 17.9 ° Okolona, MS: Differences by HeightSpeedDirection

18 Land/Oceanic Convection (John Mecikalski (UAH), K. Bedka, and T. Berendes) Products/Research: Satellite derived convective growth product using eight test methodolgy and mesoscale High Resolution Atmospheric Motion Vectors (AMV) Mature convective cloud mask (T. Berendes UAH) Oceanic product underdevelopment Collaborations: Collaborations: C. Kessinger/C. Mueller/R. Roberts (Conv/OW PDT) ASAP Progress/Needs: ASAP Progress/Needs: Five GOES imager satellite derived CI interest case studies have been delivered to Conv PDT and in testing

19 Utilize GOES-12 Rapid Scan VIS and IR imagery to produce min forecasts of new thunderstorm development and the first occurrence of cloud lightning for use in improving aviation safety through the ASAP initiative High-density satellite winds used to identify rapidly cooling cumulus cloud tops, which coincide with regions of dangerous convectively-induced turbulence GOES Visible DataHigh-Density WindsCloud-Top CoolingThunderstorm Forecast Current Radar Reflectivity and Lightning Counts Radar/Lightning 45 Minutes Later ASAP Convective Weather Analysis & Nowcasting

20 GOES CI Product Tested By Convective PDT (Only High Resolution AMV and 10.7 um Cloud Cooling Rate)

21 Oceanic Convective Cloud Growth Product Satellite AMVs are used to track clouds in sequential images and compute cloud-top cooling rates Rapid cloud-top cooling induced by convective cloud growth likely correlate well with vigorous updrafts and strong CIT 30 Minute

22 Turbulence (Tony Wimmers, N. Uhlenbrock, T. Berendes, K. Bedka, and J. Mecikalski) Products/Research: Development of satellite/RUC derived tropopause fold product - verification ongoing Investigation into a combined NWP - Satellite mountain wave turbulence nowcasting technique Pattern recognition using statistical clustering algorithm (UAH) Study relationships between rapid convective development and turbulence Collaborations: Collaborations: B. Sharman, R. Friedlich, and T. Lane (Turb PDT), S. Koch (NOAA FSL) ASAP Needs: ASAP Needs: Investigation into how satellite turbulence interest fields can enhance GTG nowcasting, EDR data

23 Experimental tropopause folding product: As part of the ASAP program, a product has been developed that uses gradients in the water vapor channel to estimate areas of tropopause folding, which can cause turbulence. The product is compared in real time to pilot reports of turbulence in a web-based java animation.

24 GOES Satellite Winds (Blue) Winds Rejected by Model (Yellow) Winds were rejected due to slower model backing winds. These diagonostic winds would be preserved for ASAP product purposes.

25 MODIS Water Vapor Detection of Mountain Wave Turbulence (ASAP Program) /06/04 MODIS WV image showing mountain waves and turbulence reports with 0=negative report and 9=severe turbulence 2. 05/11/04 MODIS WV image 3. IDV cross section of zonal wind speeds along 39 th parallel (direction of flow) 4. IDV cross section of wind speeds along flow direction with turbulence plotted

26 13km 8km 0km100km200km The high spatial frequency structure was removed by application of a 20-level (1km) vertical averaging kernel followed by a 25x25 (km) horizontal averaging kernel. LBLRTM (v6.01) was used to compute TOA clear-sky radiances across the SE/NW transect for each of the 5 time steps for both HVR-T and HVR-S. These were spectrally reduced by Kaiser-Bessel filter at GIFTS central wavenumbers for 3 bandwidths (1.10 which is GIFTS, 0.55 and /cm).

27 Volcanic Ash (Mike Pavolonis, Steve Ackerman, and Mike Richards) Products/Research: – Development of operational satellite (GOES, AVHRR, MODIS) volcanic ash mask, height estimate, and ash property algorithm – Operational products would be delivered through NOAA CLAVR-X product and MODIS cloud typing products – Validation of volcanic ash satellite cloud top estimates – CO2 slicing and statistical cloud mask (UAH) is being analyzed Collaborations: Collaborations: D. Johnson (NCAR), G. Ellrod (NOAA NESDIS), P. Herzegh (OW PDT), B. Rose (Mich Tech), F. Prada (CISRO - Australia) ASAP Needs: ASAP Needs: Guidance on input into OW PDT volcanic ash product

28 9 March 2005 Mount St. Helens AVHRR Example “Easy Case” with Strong Split Window Signal VAAC Height up to m VAAC Height up to 6000 m Retrieved heights agree well with VAAC analysis in the thickest regions of the plume.

29 Manam, PNG October 24, 2004 “Hard Case” - High PW, Cirrus, Land/Ocean

30 MODIS Volcanic Ash Cloud Top Retrieval (ASAP Program - M. Richards Graduate Student)

31 Comparison to MODIS CO 2 Darwin VAAC estimated plume to be at about 15,000 feet (~ m). **Image area and color scales are different.

32 Summary Several products have matured and ready for FAA PDT evaluation (convection and turbulence in use) Validation efforts are ongoing for all derived satellite interest field and products Means to operations or software exchange with PDT is a high priority for all ASAP fields The ASAP focus will turn to IR hyperspectral research in FY2006 which will include convection, turbulence, and volcanic ash research complementing Navy MURI goals ASAP Research/Data/Publications/References:


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