11-12 April 2005EC GLFE-TAMDAR Presentation1 Environment Canada “CMC Monitoring of GLFE TAMDAR...

11-12 April 2005 EC GLFE-TAMDAR Presentation 1

Environment Canada

“CMC Monitoring of GLFE TAMDAR Data”

Environment EnvironnementCanada Canada

Gilles Verner, Yulia Zaitseva, Réal Sarrazin / Gilles FournierCanadian Meteorological Centre / AMWSD


Outline

• Background on CMC models and monitoring

• Status of Canadian AMDAR Program Development

• Plans for the Future

• Monitoring of AMDAR data at CMC

• Monitoring of GLFE-TAMDAR at CMC

• Conclusion and Discussion


Background on CMC models and monitoring


CMC Operational Models

Global Model Regional Model• Uniform grid• Resolution of .9º (~100 km)• 28 eta levels• Kuo convection scheme• Sundqvist stratiform scheme• Force-restore surface module with climatogical soil moisture• 10 day forecasts at 00Z and 6 day forecasts at 12Z.• Cut-off of T+3h00

•Variable resolution grid•Resolution of .1375º (~15 km) • 58 eta levels• Kain-Fritsch scheme• Sundqvist stratiform scheme• ISBA surface module with

soil moisture pseudo-analysis(error feedback, no data)

• 48-hour forecasts (00Z -12Z)• Cut-off of T+1h40

GEM model used for both global and regional versions4D-var assimilation for global system as of March 15, 2005Regional system still using 3D-Var


Distribution maps of aircraft observations assimilated in 6-hour period: 3D-VAR analysis

CMC


Distribution maps of aircraft observations assimilated in 6-hour period: 4D-VAR analysis

The amount of aircraft data assimilated in 4D-VAR has tripled compared to 3D-VAR!CMC


Data assimilated in 3D-VAR Analysis

Global - Monthly mean number of assimilated observations per 24 hours over 6h- assimilation window: 3D-VAR analysis (green color –aircraft observations). CMC


Data assimilated in 4D-VAR Analysis

Global - Monthly mean number of assimilated observations per 24 hours over 6h- assimilation window: 4D-VAR analysis (green color –aircraft observations). CMC


Status of Canadian AMDAR Program Development


• Largest Regional with 67 DHC-8s and increasing fleet of CRJs to 73 by March 2006

• AMDAR started with 21 AC Jazz DHC-8 100 in June 2002 but T bias issue

• 24 AC Jazz CRJs reporting good T and wind data on GTS (73 by March 06)

• 24 AC Jazz upgraded DHC-8 reporting good T and wind data (67 Nov 05)

Development with AC Jazz

• Canadian AMDAR data: assimilated at CMC• distributed on GTS since 4 Jan 05• displayed on FSL web since 12 Jan 2005• C&C operational since 3 Feb 2005

Meteorological Reports

via VHF Data Link

Ground Reception

(ARINC)

ARINC

C-ADAS QC &

Processing

CMC

Storm Prediction Centres Canadian Met. Aviation Centres…

Jazz/Sabre AMDAR

Command & Control

AFTN-Halifax

GTS

NWP Products-General

Operational Aerodrome Forecasts & Services

NAV SYSTEMS

WX SYSTEMS ACARS

Jazz Extract meteo

SATNET

BUFR FM94 : IUAA01 (E 90W) IUAB01 (W 90W) a/c CNXXXYYY


Sabre C&C System


FSL web-Canadian data, 24 hrs, 5 Apr 05


Aircraft Profiles in Real-Time


Development with First Air

• First Proof Of Concept system about to be tested on a test B727• If test is positive and funds available, proceed with implementation on 8 aircraft by 31 March 06 and 6 in FY06/07


Historical Background• 4-phase development contract began in mid-2002:

• Phase 1 – feasibility analysis (completed by 31 March 2003): – not economically and technically possible to upgrade each aircraft– TAMDAR selected due to its promise to be easily adaptable to various

aircraft configurations and requiring minimal certification• Phase 2 – development of POC ISAT/TAMDAR/Internet (completed

in Fall 2003)• Phase 3 – POC system testing on a B727 (most of the delays - hope

to be completed by 30 June 2005):– certification by FAA and then Transport Canada generated significant

delays– lots of unexpected technical problems (GPS, data rates, calibration,

First Air/Skytrack/AirDat priorities)– capital procurement funding returned twice due to these delays

• Phase 4 – deployment on 15 aircraft (8 in FY05/06; 6 in FY06/07):– if test is positive and funding available– test to be difficult as, contrarily to GLFE, not much data in the north– calibration request heavier than anticipated– wind quality in the north is a big unknown– a lot of the QC moved to the ground processing centre


Projected Weekly Ascents/Descents

Notes: 1. Includes expected CRJ and DHC-8 operated by Jazz and 15 aircraft operated by First Air2. Does not cover WestJet and Air Canada3. Canadian North would add 30% more data in North4. AFIRS/UpTime would be deployed to fill holes


Development with AFIRS/UpTime

• AFIRS = Automated Flight Information and Reporting System• Independent datalink system for small airlines that cannot afford ACARS • Per flight hour data fees – No upfront costs to clients• Partnership with TC’s Flight Data Monitoring (FDM) program• AMDAR capability was developed and tested on 3 HawkAir DHC-8s operating in BC (T-bias issue)

• AMDAR system based on AMS AFIRS expected to be on all 5 B737 aircraft from Canadian North by 30 June 2005• A dedicated T/RH sensor integrated to AFIRS is being investigated


Plans for the Future


Plans for the Future

• Impact studies of Canadian AMDAR data by CMC and Canadian operational forecasters(?) in FY05/06

• On-going activities:– Internal development (CMC…) – AC Jazz comms– First Air comms; TAMDAR LCM– AMS AFIRS/UpTime comms (Canadian North, HawkAir, etc.)– WestJet, Air Canada… comms– LCM for required non aircraft critical systems

• Remaining development activities:– Implement on 15 First Air aircraft– Expand coverage through AFIRS/UpTime– AMDAR development on WestJet (B737 aircraft)– AMDAR development on Air Canada Embraers ERJs– Business Case to EC for the measurement of humidity– Aviation-related (icing, turbulence) – BC to NAV CANADA


BC to NAV CANADA

Objectives: contribution of NAV CANADA sought on development and operation of:– AMDAR turbulence reporting capacity;– AMDAR icing reporting capacity; – AMDAR Program on-going communication

costs associated with expanding AMDAR coverage


AMDAR VS GEOSS• AMDAR meets all global GEOSS requirements:

– Affordable– Expandable– Sustainable– Global coverage– International standards– Can target observations– Best global in-situ tropospheric data for satellite

calibration

• Air Quality Sensing Load?• Aircraft mesoscale network filling hi-res plume

dispersion model in case of a NCB attack?


Monitoring of AMDAR data at CMC


Aircraft Sensor Monitoring

• Meteorological Centres such as CMC that run Numerical Weather Prediction (NWP) models can monitor the performance of aircraft sensors used in AMDAR on a continuous and real-time basis

• Monitoring based on observed minus first guess values (innovations), as well as data rejection statistics, extracted from operational data assimilation system

• Monitoring is performed for individual aircrafts as well as by AMDAR programs (e.g. E-AMDAR, GLFE, etc).

• Time evolution of innovations, as well as their statistical distribution are extremely useful tools


QC techniques at CMC

• In CMC 3D and 4D-Var, data QC based on 2 checks:– A simple background check (comparison with first

guess, data are rejected if departure from first guess is larger than pre-specified limits (4-5 times the normalised std deviations). This is used to identify large (or gross) errors

– A more sophisticated variational quality control which is applied during the minimisation process, taking into account the consistency of the observations with other observations as well as the first guess and the final analysis. QC decisions can (and do) change during the minimisation process


Ex. T Bias on DHC-8 Aircraft

Unacceptable mean T-bias over 2C from DHC-8 using original OEM temperature probe CMC

Aug 02



Significant change in TT/UV biases: probes changes by Jazz in Dec 04!CMC

Aug 02



Density plot of innovations of temperature, all data for month of October 2004.

Note the known temperature bias of the DHC-8

CMC



Density plot of innovations of temperature, all data for month of January 2005.

Note that the temperature bias of the DHC-8 is gone!

CMC


Ex. DHC-8 Aircraft Wind Monitoring

Scatter plot for wind, all data for month of March 2005.

Note a few bad values when forecasting light winds!

CMC


AC Jazz Data assimilated at CMC

CMC

Impact of 4D-Var


Monitoring of GLFE-TAMDAR at CMC


Monitoring of GLFE TAMDAR at CMC

• Data in BUFR format obtained from AIRDAT ftp server and processed like other AMDAR

• Special care was taken to properly interpret quality flags which are present in the BUFR files: TAMDAR data flagged as SUSPECT or BAD were NOT included in the monitoring, but are available in the database. Counts on how many data are flagged.

• Monitoring done for all data as well as for individual aircraft.

• Tables of “suspect” data generated on a monthly basis using the standard WMO criteria

• Results available on a monitoring web site (intranet)• Test restricted to temperature and wind


GLFE Data Received at CMC

CMC

GLFE observations decoded by CMC. About 4700 observations from all levels, over a 6-hour window centered at 18 UTC on 04 April 2005.


GLFE Data Received at CMC

CMCTime series of the amount of data received, 25 day period.


Monitoring of GLFE TAMDAR Data at CMC

CMCInnovations of MVD and speed bias, all data with good flag only. Note speed bias.



CMC

Innovation of temperature, all data with good flag only. Note occasional larger deviations, but biases remain small.



CMC

Innovation of temperature, all data with good flag only, month of February. Note more frequent larger deviations, but biases remain small.



CMC

Density plot of innovations of temperature, all data with good flag only, month of February. Note some very bad data (large deviations) but with good flag.

These bad data are flagged by CMC background check.

Bad data



CMC

Scatter plot for wind, all data for month of March 2005.

Note some bad wind data (larger deviations) but with good flag.

These bad data are affecting the overall statistics.

Bad data


Single Aircraft: GLFE-0217

CMC

Density plot of innovations of temperature for aircraft GLFE-0217, all data with good flag only, month of March.

Note some very bad data (large deviations) but with good flag



CMC

Density plot of innovations of temperature for aircraft GLFE-0205, all data with good flag only, month of March.

TAMDAR TT data is generally of very good quality.



CMC

Scatter plot for wind for aircraft GLFE-0205, all data with good flag only, month of March.

TAMDAR wind data is generally of very good quality. Some positive speed bias a small concern.


Monitoring criteria for Suspect Aircraft

March 2005 TAMDAR

Pressure Categories (hPa) LOW PRESS: 701 - SFC MID PRESS: 301 - 700 HIGH PRESS: 300 - 100 ID: is the aircraft tail number NA: is the total number of available observations NE: is the total number of erroneous observations NR: is the number of rejected observations NG: is the number of gross observations excluding erroneous data NC: is the number of exactly calm winds excluding erroneous data TBIAS: is the temperature bias for non-gross temperatures and non-erroneous data TRMS: is the RMS temperature difference excluding gross errors and erroneous data SBIAS: is the speed bias for non-gross winds and non-erroneous data WRMS: is the RMS wind difference excluding gross errors and erroneous data Selection criteria : num obs >= LOW:20, MID:50, HIGH:50 SUSPECT CRITERIA Temperature Bias: LOW 3.0; MID 2.0; HIGH 2.0 Temperature RMS: LOW 4.0; MID 3.0; HIGH 3.0 Wind Speed Bias: LOW 3.0; MID 2.5; HIGH 2.5 Wind RMS: LOW 10.0; MID 8.0; HIGH 10.0 More than 2% of observations are gross


Results as a tableBUFR FORMAT TEMPERATURE OBSERVATIONS

SUSPECT TEMPERATURES

ID ELEM LEVEL NA NE NG NR TRMS TBIAS GLFE0238 TEMP 301-700 156 6 32 36 1.9 -1.1 GLFE0283 TEMP 301-700 338 106 61 120 1.1 -0.8 GLFE0217 TEMP 301-700 2392 163 140 196 1.5 -0.6 GLFE0251 TEMP 301-700 2034 110 82 142 1.2 -0.4 GLFE0238 TEMP 701-SFC 213 92 56 109 1.9 -0.2 GLFE0283 TEMP 701-SFC 509 119 113 201 4.1 0.6 GLFE0217 TEMP 701-SFC 3757 195 297 585 3.7 0.6 GLFE0242 TEMP 301-700 616 9 0 13 3.3 3.0

NON-SUSPECT TEMPERATURES

ID ELEM LEVEL NA NE NG NR TRMS TBIAS GLFE0247 TEMP 701-SFC 647 456 0 342 1.9 -1.2 GLFE0262 TEMP 301-700 2131 63 0 16 1.4 -1.0 GLFE0244 TEMP 301-700 2788 1961 0 1946 1.4 -0.9 GLFE0203 TEMP 301-700 1643 221 0 33 1.5 -0.9 GLFE0266 TEMP 301-700 1630 69 0 16 1.4 -0.9ETC…


Conclusion and Discussion


Conclusion and Discussion• Summary of monitoring results:

– TAMDAR data generally of good quality. Some concern about a small positive wind bias

– Some obviously bad data are making it to the BUFR files and are corrupting the overall statistics. This is affecting a few aircraft (for February, GLFE 217,225, 240,244,248,249,253,255,270,271,275,279 and 287.

– These bad data are transmitted with a good quality flag (data with the bad flags are not used).

– A more stringent QC at the source should be considered to remove these bad data

– These bad data are usually identified by the NWP QC processes. This would prevent their assimilation.

– Monitoring by NWP process important and useful to identify issues with data

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11-12 April 2005EC GLFE-TAMDAR Presentation1 Environment Canada “CMC Monitoring of GLFE TAMDAR...

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