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