1. Investigations of Using TAMDAR Soundings in the NCAR Auto-Nowcaster H. Cai, C. Mueller, E. Nelson, and N. Rehak NCAR/RAL

2. Why We Need ANC ?

3. Detection and extrapolation of surface convergence boundaries …. ….that trigger thunderstorm initiation and impact storm evolution. The Auto-nowcaster System is unique in its ability to provide nowcasts of storm initiation by…..

4. Example of Auto-Nowcaster Initiation Forecast 1 hour forecastVerification Initiation nowcasts extrapolation nowcasts

5. Weather Forecast Office Washington DC Sydney Australia Forecast Office U. S. Army White Sands Missile Range Central U. S. for the FAA Where has the Auto-nowcaster been demonstrated ? Process of being transferred to: Bureau Meteorology Beijing China U.S National Weather Service – Dallas Weather Forecast Office AWIPS

6. AREA WEATHER UPDATE NATIONAL WEATHER SERVICE FORT WORTH TX 310 PM CDT SUN APR 10 2005 > WARNING DECISION UPDATE FOR NORTH TEXAS MESOANALYSIS PROGRAMS SHOW 1000-1500 J/KG CAPE ALONG AND JUST AHEAD OF DRYLINE. THUS...CU/DEVELOPING STORMS ALONG/E OF DRYLINE SHOULD CONTINUE TO INTENSIFY. STORM INITIATION TOOL ALSO SUGGESTS HIGH POSSIBILITY OF DEVELOPMENT FARTHER SW...OVER CORYELL/LAMPASAS COUNTY AREA. DEEP-LAYER SHEAR MORE THAN SUFFICIENT FOR ORGANIZED STORMS AND AT LEAST MID-LEVEL MESOS. AS STORMS EVOLVE INTO THE EVENING...A MORE LINEAR MODE IS EXPECTED. Auto-Nowcaster at Ft. Worth WFO

7. Data Sets Radar WSR-88D Satellite Mesonet Profiler Sounding Numerical Model Lightning Analysis Algorithms Predictor Fields Forecaster Input Fuzzy Logic Algorithm - Membership functions - weights - Combined likelihood field Final Prediction Flow Chart for the Auto-Nowcaster System

8. Data Sets Radar WSR-88D Satellite Mesonet Profiler Sounding Numerical Model Lightning Analysis Algorithms Predictor Fields Forecaster Input Fuzzy Logic Algorithm - Membership functions - weights - Combined likelihood field Final Prediction Flow Chart for the Auto-Nowcaster System

9. Environmental conditions (RUC) –Frontal likelihood –Layered stability –CAPE (max between 900 and 700 mb) –Mean 875 to 725 mb Relative Humidity –CIN (averaged between 975 and 700 mb) Boundary-layer –Convergence –LI (based on METARS) –Vertical velocity along boundary (maxW) –Boundary-relative steering flow –New storm development along boundary Clouds –Clear or Cumulus –Vertical develop as observed by drop in IR temps Blue Regions - Little chance of storm development Green Regions - Moderate likelihood Red Regions - Areas of forecast initiation Predictor Fields used for Combined Likelihood of Initiation

10. Predictor Fields Large-Scale Environment B-L characteristics Satellite Cloud Typing Boundary characteristics Cumulus development Storm motion and trends

11. Why TAMDAR Soundings Might Be Important for ANC ? Lack of high spatial and temporal resolution soundings data has been hampering storm initiation forecast both for ANC and forecasters (TAMDAR advantage over NWS soundings) Moisture information within and above the boundary layer is crucial for convection initiation (TAMDAR advantage over ACARS data)

12. How TAMDAR Data are Used in ANC ? Calculating 2D CIN field based on TAMDAR soundings and METAR observations, and comparing it with RUC-derived CIN ---- to be used mainly for reducing false alarm rate Calculating averaged relative humidity from TAMDAR soundings, and comparing it with RUC- derived averaged RH ---- to be used to modify storm initiation forecast

13. Flow Chart for TAMDAR Data Processing

14. Case Study Examples Six cases from Summer 2005 over IL/IN region TAMDAR- and RUC-derived CIN and averaged relative humidity fields are compared. Most of the time both fields compared favorably without causing differences in forecasting convection initiation There are cases where the differences between RUC- and TAMDAR-derived fields could cause a forecaster to change his/her storm initiation forecast

15. Comparisons of Averaged Relative Humidity Between RUC and TAMDAR 07/18/2005

16. Comparisons of Averaged Relative Humidity Between RUC and TAMDAR 08/12/2005

17. A Case for Reducing FAR in ANC

18. Comparison of CIN Between RUC and TAMDAR 07/26/2005 A forecaster could use the polygon tool to remove the storm initiation forecast at previous slide when he/she thought the convection would be capped based on large CIN from TAMDAR

19. Summary Based on limited number of case studies, it is found that TAMDAR-derived CIN field could have the potential to reduce false alarm rate for ANC storm initiation forecast. The averaged relative humidity field derived from TAMDAR also showed some values in estimating the moisture content more accurately in some cases, which could have significant impacts to models such as VDRAS. The TAMDAR impact depends heavily on the location and timing of convection. If the storms formed far away from where the TAMDAR soundings were located, the TAMDAR impacts are hard to show.

20. END THANK YOU !