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Northeast Winter C&V Program

Northeast Winter C&V Program . Roy Rasmussen NCAR Wes Wilson MIT/LL. Motivation. 1. Air traffic significantly impacted by fog, low clouds, precipitation and snowstorms in this region.

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Northeast Winter C&V Program

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  1. Northeast Winter C&V Program Roy Rasmussen NCAR Wes Wilson MIT/LL

  2. Motivation 1. Air traffic significantly impacted by fog, low clouds, precipitation and snowstorms in this region. 2. A significant number of major airports located in the NE (JFK, LGA, EWR, Logan, Philadelphia, Washington D.C. area airports)

  3. C&VImpacts on Major Delay Airports SFO MS MS++ NE WS WS++ AVERAGE ANNUAL AIRPORT IMPACTS

  4. Additional factors making the NE a desirable location 1. Experience working with the aviation community at the New York airports through WSDDM and ITWS programs. 2. Relatively high frequency of fog, allowing for studies on this important phenomenon. 3. Relatively high density of ASOS surface stations and NexRad radars in the New York City metropolitan area.

  5. Plan for NE C&V Program 1. Conduct a meeting of the C&V User's Group User groups are an effective way to establish goals that match user needs. Working with users from the NYC aviation community through the NYC ITWS and WSDDM will provide an opportunity to understand the forecast products that are needed during CVWW impacts. Users will include representatives from FAA TMU, FAA Command Center, FAA Technical Center, Airlines, and CDM. 2. Assess needs for aviation C&V products Based on the lessons learned from the User's Group, document specific aviation needs, and address product concepts that could meet these needs. 3. Identity scientific areas where more basic understanding is needed to support operational C&V forecasting

  6. Plan for NE C&V Program (cont..) 4) Field data collection phase for at least three years. - Fog sensor deployment year one. 5) Development of a short-term C&V nowcast technique based on snowgauge and radar data using WSDDM-developed techniques as a basis. 6) Develop 0-1 hour fog nowcast method based on obs. 7) Development of improved methods to combine model forecasts and observations using regression and fuzzy logic technique to produce an improved 1-12 hour forecast. Inputs include observations as well as the RUC and COBEL model output. 8) Development of a cloud layer product based on radar, satellite, and surface sensor data. 9) Improve the RUC model microphysics based on comparison to the data. 10) Transfer forecast algorithm to the National C&V product.

  7. Fog sensors • Multi-channel radiometer to identify the depth and liquid water content of fog (Radiometrics). • Fog spectrometer probe to determine the droplet size distribution in fog (Droplet Measurement Techonology). 3. One minute data from the ASOS instruments (EWR, LGA, JFK).

  8. MM5 forecast (left) and microwave profiler observations (right) at Boulder CO on 16 Feb 2001. A supercooled fog was observed after 1130 UT but was not forecast.

  9. Denver radiosonde (50-km SE of Boulder)

  10. Microwave profiler observation of temperature inversion and supercooled fog at Boulder 16 Feb 2001,18:22 UT

  11. Visibility Reduction due to Snow Product • Perform real-time correlation to snowfall rate and visibility (similar to real-time Z-S). Visibility sensor either RVR or the ASOS sensor. • Use the one hour snow forecast to produce a one hour visibility forecast at the airport.

  12. Development of short term forecasts based on obs 1. Investigate the development of short term fog forecasts (0-1 hour) using the one minute ASOS and RVR data. 2. Verify the fog forecasts using the radiometer and the fog droplet size distribution sensor. 3. Investigate the use of additional data to improve the forecast.

  13. 1-12 hour fog forecast product • Based on the one minute ASOS and RVR visibiity data, NexRad and TDWR radar data, satellite data and RUC and COBEL model output, develop 1-12 hour forecast of fog for Newark. The various inputs will be combined using regression analysis and fuzzy logic. • Verification of the technique will be made using the fog sensor data and ASOS reports of fog every one minute. 3. Investigate the applicability of mesoscale model forecasts initialized with radar data to forecast low visibility due to snow and fog (WWR PDT ongoing effort).

  14. COBEL 1. Identify the key factors needed to improve the forecast of fog and low clouds at EWR using COBEL. 2. Verify the COBEL model runs using the data. 3. Investigate embedding COBEL into the 3-D RUC/WRF model.

  15. Develop a Cloud Layer Product • Investigate the use of existing radars (NexRad and/or TDWR) to identity cloud layers. - Investigate possibly increasing the radar sensitivity by special processing. • Investigate the use of multi-channel satellite and ASOS ceilometer data to detect cloud layers. • If funding permits, use K-band radar to verify the location of cloud layers (also detects fog).

  16. RUC/WRF Model Improvements 1. Improve the microphysics in MM5/WRF for fog and cloud forecasting based on comparison to the EWR data. 2. Transfer improvements to FSL for implementation into the operational RUC and/or WRF model. • FSL investigate possible improvements to PBL and surface physics based on comparison to EWR data. Possible Implementation of COBEL into RUC.

  17. Summary 1. A Ceiling and Visibility Program Associated with Winter Weather is proposed to be conducted in the New York City area with special fog sensors. 2. The program will result in improved methods to nowcast reduced visibility and ceiling due to fog, snow, precipitation, and low clouds in the New York area. • The algorithms developed from this program can be used in the National C&V product for the NE, and also potentially for visibility reduction due to fog, snow, precipitation and low clouds in other regions as well. 4. Funding for the program will come from the National C&V PDT, Terminal Area C&V PDT, and the Winter Weather PDT.

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