predictability of high impact weather during the cool season over the eastern u.s: cstar operational...
TRANSCRIPT
Predictability of High Impact Weather during the Cool Season over the Eastern U.S:
CSTAR Operational Aspects
Matthew Sardi and Jeffrey TongueNOAA/NWS, New York, NY
4 November 2010
Outline
• Who/Why
• WFO Goals
• Activities to Date:– Training Initiatives– Visualization Software
Who in NOAA• WFO’s– New York– Mt Holly– State College– Pittsburgh
• NCEP– EMC– HPC– OPC
• NOAA Earth System Research Laboratory
Motivation
• Prediction of mesoscale phenomenon within extratropical storms remains a major challenge.
Goal for the WFO
• Improvement in operational forecaster understanding of uncertainty/predictability.
• Improve communication of uncertainties to users/customers.
Specifics
• Upton, NY (KOKX): – Improved understanding of cyclone evolution and
precipitation bands– Ensemble Forecast Systems (EFS) application to Aviation
• Low-level winds• Precipitation type• Snowfall rate
– Mentors to the SBU students• 1 SCEP• 1 STEP• 4 Volunteers
Specifics (cont)
• WFO Philadelphia, PA (KPHI): – Storm surge– Coastal flooding
• State College, PA (KCTP): – Visualization Software– Training– Data management
• WFO Pittsburgh, PA (KPIT): – Training– Visualization– Graphical Forecast Editor (GFE) Applications
Specifics (cont)
• Hydrometeorological Prediction Center (HPC): – Precipitation banding.– Cyclone track verification for the winter weather desk, medium
range forecast products, as well as the snowfall and QPF products. – HPC will host visiting forecasters, scientists, and project students.
• Ocean Prediction Center (OPC): – EFS application to cyclone track and intensity.– East Coast Marine impacts - high winds and waves.
Specifics (cont)
• Environmental Modeling Center (EMC):– EFS sensitivities related to the Weather Storms Reconnaissance
Program– Impacts of wave packets – Training of forecasters:
• Impact of targeted observations • SREF system
– Cyclone verification
• Environmental System Research Laboratory (ESRL): – EFS sensitivities related to the Weather Reconnaissance Program– Training on the impact of targeted observations on predictability.
Current CSTAR Training Initiatives
• Wave Packets• Targeted Observations• ALPS
Wave Packets
Target Observations
Advanced Linux Prototype System(ALPS)
• Running on a “non-baseline” AWIPS Workstation.
• Looks and Feels like D2D • Designed for probabilistic forecasting• Visualizing Ensemble Data– Weighting Ensemble Members– Generating Probabilistic Grids– Etc
ALPS
New Projections
Statistical Functionality
A Brief Example
• The following are all 168 HR (7 Day) Forecasts from last Thursday
• Valid at 8 AM this Morning – Thursday, Nov 4th
GEFS Members + ECMWF
ECMWF
GEFS Mean
GEFS Mean + ECMWF = MEAN
Example Statistics - 850 Temperatures
850 Temperatures - cont
How do I get ALPS ?
• Visit the SBU CSTAR Page:
• http://dendrite.somas.stonybrook.edu/CSTAR/cstar.html
ALPS GFE - Future
• Deployment of Probabilistic Products• Aviation Specific Examples– Wind Speed– Wind Direction– Gusts (probability of being reported)
• No yet Loaded at OKX
Example Probabilistic Products
Example Probabilistic Products
BUFKIT 10
• SREF (21 Members)• WDTB WRF Ensemble– Resolution: 24 KM– Frequency: 00Z and 12Z– Members: 8 ensemble members (23) x 2
Initializations• NMM/ARW• NAM/GFS• KF/BMJ
Boundary Layer Winds - Aviation
Questions?
• CSTAR E-Mail List– Send Jeff Waldstreicher an e-mail
• CSTAR WEB PAGE:– http://dendrite.somas.stonybrook.edu/CSTAR/cstar.html