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

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 RUC 3h 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 RUC 09h forecast WSR-88D Fig. C17 Stage II

Rainbands 06Z, March 12, h accu. rain (mm) RTFDDA presents better Rain distribution and Structures in all areas RTFDDA 7h Forecasts ETA 6h forecast Stage II Fig. C19

Rainbands 21Z, March 12, h accu. rain (mm) RTFDDA presents better Distribution and structures RTFDDA 10h Forecasts ETA 9h forecast Stage II Fig. C22