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GLFEStatus Meeting
April 11-12, 2004
Presentation topics
• Deployment status
• Data quality control
• Data distribution
• NCEP meeting
• AirDat display work• Icing displays
• Turbulence displays
• AirDat/NCAR data impact studies
GENERALSTATUS TOPICS
Deployment status
• 62 Mesaba aircraft equipped to date
• One additional Saab 340A yet to come on line for total of 63
• Data being delivered from majority of aircraft
• Troubleshooting of some aircraft ongoing• Shadin heading data converters
• Sensing board connectors
Deployment status
• Mesaba incentives being supported• Important for any GLFE extension• Incentives
• OOOI and flight numbers• System functional and working well• Impact observed by Mesaba• Will become operation in next two months
• Text messaging• AirDat contractual obligation to Mesaba• Hardware design being developed
Data quality
• Atmospheric data looks good
• Quality of data a function of TAMDAR sensor and AirDat ground system
• Innate trade-offs with multi-function sensor
• CRITICALLY important that AirDat flagged data be eliminated prior to sensor performance evaluation and model ingestion
• Quality flags implemented in BUFR format based on AirDat real time checks
• Statistical QA prior to model ingestion
Data quality
• Ongoing improvements in data quality• Sensor firmware refinements• Ground based QA improvements
• Sensors can be re-calibrated by ground command• Algorithms include constants• Roughly 100 constants can be commanded
• IMPORTANT: systematic biases can be removed• Must be fully verified • Must be agreed to by participating parties
• Long-term drift can be corrected
Data quality
• Humidity accuracy calculation included in BUFR format• High quality in regions of significant water vapor content
impacting forecasting accuracies• Should be considered in input to forecast models
• Additional humidity sensors being evaluated for future improvements
• FAA has approved field replacement of sensing boards
Data distribution• Several distribution formats and methods
• BUFR and tab-delimited formats• Major effort for each distribution method
• Distribution list expanding• Early recipients included:
• FSL• UK Met Offices and ECMWF• Environment Canada
• NCEP receiving via MADIS• Recent additions include:
• NRL Fleet Numerical Modeling Center• Ohio Air National Guard
Data distribution• FSL
• Real-time distribution in BUFR via LDM• Provides all data with quality flags
• UK Met Offices and ECMWF• Distribution in BUFR format• FTP site updated at 15 minute intervals• Provided in a per sensor format
• Environment Canada• Distribution in BUFR format • FTP site updated at 15 minute intervals
• NRL and National Guard-• Tab-delimited• Flagged data not provided
NCEP meeting
• Met March 31 with NCEP in Camp Springs
• Very strong interest in TAMDAR
• Data potential for NAM (ETA) and global modeling
• Value of ascent/descent (Skew-T’s) for verification of model outputs
• Access to data via MADIS
• Interest in receiving data directly from AirDat
AirDat display work
• AirDat working on displays to increase usefulness of data to FAA for aviation safety
• Map display evolved from FSL display developed by Bill Moninger
• Enhanced with visual displays of icing and turbulence
• Downloadable application accessible from AirDat website
• Icing and turbulence will be added to Skew-T diagram
AIRDAT/NCARDATA IMPACT STUDIES
AirDat computing cluster
• Small cluster at AirDat Data Center• Support evaluation of data quality
• Conduct TAMDAR data denial studies
• Conduct case studies
• Contract with NCAR for data studies using cluster
• Very positive results being obtained
• Cluster being expanded
• Cluster available to support additional TAMDAR research studies
AirDat/NCAR data studies
• Forecasting system• RT/FDDA data assimilation system
• Real time four dimensional data analysis
• Continuous assimilation of data during forecasting runs
• MM5 forecasting model
• Utilize AirDat real-time QA, then NCAR statistical QA prior to model ingestion
• Boundary conditions established from NAM (ETA)
• NOAA/FSL MADIS data feed
AirDat/NCAR data studies
• TAMDAR data weighting being optimized
• Error improvement statistics compiled
• Case studies conducted
• Data denial studies
• Comparisons to RUC and NAM outputs
• Very significant improvements observed
RTFDDA/MM5 Forecast Domain
D1—36 km
D2—12 km
D3—4 km
TAMDAR error impact
• Significant reduction in bias and RMS errors• Temperature• Water vapor mixing ratio• Wind vector magnitude• True for analysis, 6, and 12 hour forecasts
• RMS error reductions • 20-30% for moisture and temperature• 35+% for winds
• Error reductions in lower and upper troposphere
Temperature
Water Vapor Mixing Ratio
Vector Wind Magnitude
Key:
Blue-w/o TAMDAR
Red-with TAMDAR
Solid-analysis
Dotted-6 hour forecast
Dashed with triangles-12 hour forecast
Snowbands 18Z, Feb. 02, 2005 Radar reflectivity
RTFDDA Analyses
Without TAMDAR
With TAMDAR WSR-88D
Fig. C6
Rainbands:15Z, March 12, 2005,1-h accu. rain (mm)
RTFDDA 4h Forecast
RUC3h forecast WSR-88D
Fig. C12
Stage II
NOTE: 13 Km Research RUC used
Rainbands: 00Z, March 13, 2005,1-h accu. rain (mm)
RTFDDA 10h Forecasts
RUC09h forecast WSR-88D
Fig. C17
Stage II
Rainbands 06Z, March 12, 2005 3-h accu. rain (mm)
RTFDDA presents betterRain distribution and Structures in all areas
RTFDDA 7h Forecasts
ETA6h forecast Stage II
Fig. C19
Rainbands 21Z, March 12, 2005 3-h accu. rain (mm)
RTFDDA presents betterDistribution and structuresRTFDDA
10h Forecasts
ETA9h forecast Stage II
Fig. C22