Using a mesoscale model to identify convective initiation in an artcc cwsu environment
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Using a Mesoscale Model to Identify Convective Initiation in an ARTCC/CWSU Environment. Warren R. Snyder NOAA/NWS Weather Forecast Office Albany, New York Mark R. McKinley NOAA/NWS Center Weather Service Unit Oberlin, Ohio Allison R. Vegh Department of Earth and Atmospheric Sciences

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Using a Mesoscale Model to Identify Convective Initiation in an ARTCC/CWSU Environment

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Using a mesoscale model to identify convective initiation in an artcc cwsu environment

Using a Mesoscale Model to Identify Convective Initiation in an ARTCC/CWSU Environment

Warren R. Snyder

NOAA/NWS Weather Forecast Office

Albany, New York

Mark R. McKinley

NOAA/NWS Center Weather Service Unit

Oberlin, Ohio

Allison R. Vegh

Department of Earth and Atmospheric Sciences

University at Brockport State University of New York

Brockport, New York


Why does convective initiation matter to the national airspace system nas

Why does convective initiation matter to the National Airspace System (NAS)

  • Causes of air traffic Delays

    • 76 % of involve weather

    • 24% involve thunderstorms

    • 17% Ceilings

    • 14% each for visibilities and wind

  • Result…Ground Stops & Delays

    • Significant costs from $3K to 300K/flight

    • Safety Issues

    • Your sitting in the airport delayed for hours or days !!!


Purpose of the study

Purpose of the Study

  • Improve convection initiation forecasts of CWSU Oberlin using a mesoscale model

  • Can better forecasts reduce ground stops, improving convection avoidance, and earlier or later re-routings

  • Proof of concept

  • How much $$$ can the industry save?

  • To run the full modeling system in a CWSU costs $49 a month for a T1 and $4000 for the PC

  • How much does jet fuel cost?


Wseta project at cwsu oberlin ohio and wfo albany ny

WSETA project at CWSU Oberlin, Ohio and WFO Albany, NY

  • Training Provided to CWSU Staff April 2004

  • Model data posted on CSTAR server twice a day via gempak graphics on the internet.

  • SUNY Student compared six fields identified by MIC/SOO as most likely to be indicative of convective initiation using data from Summer 2004 to early June 2005.

  • Parameters with best performance

    • Hourly Convective Precipitation

    • 700 HPA Omega

  • Modeling system - Dell Pentium 4 , 2400 mHz Linux PC

  • Model run for 24 hours. 06 UTC and 18 UTC runs with output posting 0800 UTC/2000 UTC

  • Kain-Fritcsh Convective Parameterization, Nested - Outer nest resolution is 15 km, Inner Nest 7.5 km resolution, Diffusion is 0.30 versus 1.0 in operational models. Most parameters configured at SOO/STRC baseline.


Study area oberlin service area squared off

Study Area – Oberlin Service Area Squared off


Results part i

Results Part I

  • Definitions - % of convection in area forecasted by model parameter

    • Good – 75% or more

    • Acceptable – 25% to 75%

    • Poor – Less than 25%

HCP - Acceptable or Good 83%

700 hPa Omega- Acceptable or Good 93%


Hourly convective precipitation hcp vs 700 hpa omega

Hourly Convective Precipitation (HCP) vs. 700 hPa Omega


Part ii comparing 700 hpa omega and hcp forecasts to nldn data

Part II – Comparing 700 hPa Omega and HCP forecasts to NLDN Data

  • Used all convective events from June to September 2005 in CWSU Oberlin area

  • NLDN data plots every lightning stroke at exact lat/lon points

  • Assess accuracy of model parameters in time and space

  • UAlbany students extracted the data

  • Software developed by Vasil Koleci to plot lighting data hourly over the area

  • 87 events identified, 3 dropped as only SHRA and no lightning occurred


Comparison of model 700 hpa omega hcp convective configuration with nldn data

Comparison of Model 700 hPa Omega/HCP Convective Configuration with NLDN data

  • Excellent (4)–Model data match in location, and structure/orientation.

  • Good – (3) If structure/orientation are very similar but location is off by 160 km, or location is within 160 km and structure/orientation are different

  • Fair – (2) If they are both in the same ¼ of a state or states, or overlap each other 25% or less

  • Poor – (1) No match


Results for configuration

Results for Configuration

  • 700 hPa Omega had an average of 3.08 configuration. 74 events where good or excellent, only 10 fair and poor

  • HCP – Had an average 2.81 configuration. 63 Events good or excellent, 21 Fair or Poor


Results for timeliness

Results for Timeliness

  • 700 hPa Omega and HCP forecasted the time of initiation at the same time in all but 9 cases

  • Average model time error for convective initiation was 37.5 minutes

    • 54 events were forecast within an hour

    • 19 events between one and two hours

    • 11 events between two and three hours


Distance error

Distance Error

  • Distance from the model convection to the actual lighting at initiation

  • Average for 700 hPA Omega 33 km

    • All but one event within 240 km

    • 240 km is the distance a jet travels in 15 minutes

  • Average for HCP 86 km.

    • All but 5 events within 240 km

  • Difference likely the result of the much more specific locations of HCP versus the general broader areas of 700 hPa Omega


Future directions

Future Directions

  • Model converted over to the WRF

  • WRF data being provided to CWSUs at Nashua and Oberlin

  • Will undertake a similar study during the 2007 convective season using the WRF

  • New products available such as model Composite Reflectivity


References

References

  • Based on ER Tech Attachment 2006-01 “Using a Mesoscale Model to Identify Convective Initiation in an ARTCC/CWSU Environment” 2006: Snyder W.R, McKinley M.R. and Vegh A.R.

  • Original Paper can be found online at

  • http://www.werh.noaa.gov/SSD/erps/ta/ta2006-01.pdf


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