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Discussion of deployment status, data quality control, data distribution, NCEP meeting, AirDat display work, icing displays, turbulence displays, and AirDat/NCAR data impact studies.
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GLFE Status 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
GENERAL STATUS 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/NCAR DATA 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
Fig. C6 Without TAMDAR Snowbands 18Z, Feb. 02, 2005 Radar reflectivity RTFDDA Analyses WSR-88D With TAMDAR
Fig. C12 Rainbands:15Z, March 12, 2005,1-h accu. rain (mm) RTFDDA 4h Forecast Stage II RUC 3h forecast WSR-88D NOTE: 13 Km Research RUC used
Fig. C17 Rainbands: 00Z, March 13, 2005,1-h accu. rain (mm) RTFDDA 10h Forecasts Stage II RUC 09h forecast WSR-88D
Fig. C19 Rainbands 06Z, March 12, 2005 3-h accu. rain (mm) RTFDDA presents better Rain distribution and Structures in all areas RTFDDA 7h Forecasts ETA 6h forecast Stage II
Fig. C22 Rainbands 21Z, March 12, 2005 3-h accu. rain (mm) RTFDDA presents better Distribution and structures RTFDDA 10h Forecasts ETA 9h forecast Stage II