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GOES Aviation Products in AWIPS February 2007 Short-term Prediction Research and Transition (SPoRT) Center Training Module.

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Presentation on theme: "GOES Aviation Products in AWIPS February 2007 Short-term Prediction Research and Transition (SPoRT) Center Training Module."— Presentation transcript:

1 GOES Aviation Products in AWIPS February 2007 Short-term Prediction Research and Transition (SPoRT) Center Training Module

2 Research to Operations -- NASA and Southern Region weather forecast offices testbed for new products to operations training modules and science sharing sessions product assessments of impact Focus NASA EOS satellite observations modeling and data assimilation nowcasting and lightning Collaborative Research Area Mission: Apply NASA measurement systems and unique Earth science research to improve the accuracy of short-term (0-24 hr) weather prediction at the regional and local scale NASAs SPoRT Center

3 Objective: Describe the NESDIS GOES aviation research products available in AWIPS in advance of their operational implementation. Outline: Motivation Product description Examples References and links GOES Aviation Products in AWIPS

4 Products require thorough testing before dissemination via AWIPS In a testbed mode, products can be made available ahead of time This allows the forecasters to evaluate the products This testbed approach provides advanced exposure and training to the forecaster. This training module will: describe the experimental aviation products available to selected offices in AWIPS describe how to access and interpret them in AWIPS Motivation

5 Products are available hourly Cloud and fog properties can be descriminated Additional information from these products help the forecasters awareness of the current environment and can also be used when producing TAFs In the future, these products will be widely disseminated to all WFOs Benefit of Products to Forecasters

6 These experimental products are produced hourly by NESDIS from the Imager or Sounder on the GOES-12 satellite at 4 km resolution. The four GOES aviation products, developed by Gary Ellrod of NESDIS, are: icing – mask of region where aircraft icing may occur icing height – maximum height of icing above surface fog depth – thickness or depth of fog low cloud base – height of cloud base above ground surface GOES Aviation Products

7 Access to Aviation Products in AWIPS Aviation products in D2D: access through the Satellite menu default enhancement curves correspond to office projections at 4 km data available hourly

8 Aircraft Icing

9 Icing Mask and Height Basic criteria for aircraft icing: liquid phase clouds with temperatures in the 0 to -25 °C range large droplet diameters (> 50 μm) upward motion to replenish the available supercooled water large liquid water contents long exposure to icing conditions during flight GOES satellite data can be used to estimate: cloud phase cloud top temperature cloud drop size and liquid water content (WMO 1954; Hansman 1989; Schultz and Politovich 1992).

10 Are super-cooled drops present? 248 K < T 11 < 273 K Is water phase present? night T 3.7 - T 11 < - 2 K day T 3.7 - T 11 > 0 K ---- dependant on thickness of clouds with use of visible data Detecting Regions of Aircraft Icing Icing likely in blue regions Strengths: POD: 55-70% FAR: 25% 4 km (Imager) product Limitations: detection obscured by high clouds only a threshold -- no estimate of amount of icing

11 Icing Cloud-top Height > 18,000 ft BLUE > 12,000 ft CYAN > 6,000 ft YELLOW < 6,000 ft ORANGE If icing is possible, assign a height to the tops of the super-cooled clouds. Use cloud-top pressure/height from corresponding GOES Sounder data mixture of CO2 slicing and IR assignment techniques icing height given in units of thousands of feet Icing Enhanced Cloud-top Altitude Product (ICECAP)

12 Fog Detection and Vertical Thickness (depth)

13 Fog Detection: Variations in Channel Emission This technique can be used not only on GOES satellite imagers, but also MODIS (Terra and Aqua) and VIIRS (on NPOESS). Night-time differences: T 11 – T 3.9 > 0 K fog An example which validates the fog depth product against observations is shown at the right. Figures courtesy of Gary Ellrod Emissivity differences between the 11 and 3.9 μm bands are used to determine the fog depth.

14 GOES Fog Depth Product in AWIPS Colors indicate depth of fog, and non-fog or middle/high cloud regions are denoted in shades of cyan. Limitations: sub-pixel clouds add to the uncertainty of the fog depth not applicable in multi-layer cloud regions product uncertainty over non-vegetated (low emissivity) surfaces only valid at night Fog Depth < 200 m GREEN 200-300 m BLUE 300-400 m RED 400-500 m YELLOW Non-Fog CYAN

15 Low Cloud Base Estimation

16 Low Cloud Base The POD and FAR statistics are based on more than 1500 cases (Ellrod 1996). Ceiling Height < 1,000 ft RED > 1,000 ft GREEN Cirrus CYAN Low Cloud Base Strengths: POD: 70% FAR: 10% Limitations: sub-pixel clouds add to the uncertainty of the cloud base estimates not applicable in multi-layer cloud regions Instrument Flight Rule (IFR) ceilings (< 1000 ft) are likely to occur when: T 11 – T sfc < 4 K Red regions indicate the likelihood of ceilings < 1000 ft; green for ceilings above 1000 ft. Cyan shades highlight regions of high clouds.

17 Summary of GOES Aviation Products Icing MaskIcing HeightFog DepthLow Cloud Base HourlyHourly15 min.HourlyNight-time *all products are available at 4 km resolution

18 SPoRT Program - main SPoRT web page SPoRT Satellite Observations - real-time data from MODIS and AMSR-E GOES Products for SPoRT - GOES products produced for SPoRT including NESDIS aviation products Additional Information -- SPoRT

19 Additional Information -- Aviation Products COMET Aviation Training Resources MetEd Module: Fog and Low Cloud: Web-based Products NESDIS - Operational Products Development Branch Aviation Products: Cloud and Fog Products: NWS - Aviation Weather Center (AWC) Forecast Icing Potential (FIP): Current Icing Potential (CIP):

20 Additional Information -- References Brown, B., 1996: Verification of in-flight icing forecasts: Methods and issues. FAA Intl. Conf. on Aircraft Icing, Springfield, VA, May 6-8, 1996. Ellrod, G. P., 1995: Advances in the detection and analysis of fog at night using GOES multispectral infrared imagery. Wea. Forecasting, 10, 606-619. Ellrod, G. P., 1996: The use of GOES-8 multispectral imagery for the detection of aircraft icing regions. Preprint Volume, 8th Conf. on Satellite Meteorology and Oceanography, January 28-February 2, 1996, Atlanta, AMS, 168-171. Ellrod, G. P., 2000: Proposed improvements to the nighttime GOES fog product to improve ceiling and visibility information. Preprint Volume, 10th Conf. on Satellite Meteorology and Oceanography, 9-14 January, 2000, Long Beach, AMS, 454-456. Hansman, R. J., 1989: The influence of ice accretion physics on the forecasting of aircraft icing conditions. Preprint Volume, 3rd Intl. Conf. on the Aviation Weather System, January 30-February 3, 1989, Anaheim, AMS, 154-158. Schultz, P. and M. Politovich, 1992: Toward the improvement of aircraft-icing forecasts for the continental United States. Wea. Forecasting, 7, 491-500. Vivekanandan, J., G. Thompson, and T. F. Lee, 1996: Aircraft icing detection using satellite data and weather forecast model results. FAA Intl. Conf. on Aircraft Icing, Springfield, VA, May 6-8, 1996. WMO, 1954: Meteorological aspects of aircraft icing. WMO Tech. Note No. 3, WMO - No. 30. TP9, World Meteor. Org., Geneva, 18 pp.

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