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12/21/2015 TAMDAR Wikipedia, the free encyclopedia https://en.wikipedia.org/wiki/TAMDAR 1/4 TAMDAR From Wikipedia, the free encyclopedia TAMDAR (Tropospheric Airborne Meteorological Data Reporting) is a weather monitoring system that consists of an insitu atmospheric sensor mounted on commercial aircraft for data gathering. It collects information similar to that collected by radiosondes carried aloft by weather balloons. It was developed by AirDat LLC, which was acquired by Panasonic Avionics in April 2013 and now operates as Panasonic Weather Solutions based in the United States. Contents 1 History 2 System capabilities 2.1 Icing Observations 2.2 Turbulence Observations 3 Forecast Models And Validation 3.1 SkewT Profiles 4 External links History In response to a government aviation safety initiative in the early 2000s, NASA, in partnership with the FAA, NOAA, and private industry, sponsored the early development and evaluation of a proprietary multifunction insitu atmospheric sensor for aircraft. The predecessor to Panasonic Weather Solutions, AirDat (formerly ODS of Rapid City, SD), located in Morrisville, North Carolina and Lakewood, Colorado, was formed in 2003 to develop and deploy the Tropospheric Airborne Meteorological Data Reporting (TAMDAR) system based on requirements provided by the Global Systems Division (GSD) of NOAA's Earth System Research Laboratory, the FAA, and the World Meteorological Organization (WMO). The TAMDAR sensor was originally deployed in December 2004 on a fleet of 63 Saab SF340 aircraft operated by Mesaba Airlines in the Great Lakes region of the United States as a part of the NASA sponsored Great Lakes Fleet Experiment (GLFE). Over the last twelve years, equipage of the sensors has expanded beyond the continental US (CONUS) to include Alaska, Caribbean, Mexico, Central America, Europe, and Asia. Airlines flying the system include Icelandair, Horizon (Alaska Air Group), Chautauqua (Republic Airways), Piedmont (American Airlines), AeroMéxico, Ravn Alaska, Hageland, PenAir, Silver Airways and Flybe, as well as a few research aircraft including the UK Met Office BAe 146 FAAM aircraft. Recently, an installation agreement has been reached with a large Southeast Asian airline as well. The TAMDAR system has been in continuous operation since initial deployment in December 2004.

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12/21/2015 TAMDAR ­ Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/TAMDAR 1/4

TAMDARFrom Wikipedia, the free encyclopedia

TAMDAR (Tropospheric Airborne Meteorological Data Reporting) is a weather monitoring system thatconsists of an in­situ atmospheric sensor mounted on commercial aircraft for data gathering. It collectsinformation similar to that collected by radiosondes carried aloft by weather balloons. It was developedby AirDat LLC, which was acquired by Panasonic Avionics in April 2013 and now operates asPanasonic Weather Solutions based in the United States.

Contents

1 History

2 System capabilities

2.1 Icing Observations

2.2 Turbulence Observations

3 Forecast Models And Validation

3.1 Skew­T Profiles

4 External links

History

In response to a government aviation safety initiative in the early 2000s, NASA, in partnership with theFAA, NOAA, and private industry, sponsored the early development and evaluation of a proprietarymulti­function in­situ atmospheric sensor for aircraft. The predecessor to Panasonic Weather Solutions,AirDat (formerly ODS of Rapid City, SD), located in Morrisville, North Carolina and Lakewood,Colorado, was formed in 2003 to develop and deploy the Tropospheric Airborne Meteorological DataReporting (TAMDAR) system based on requirements provided by the Global Systems Division (GSD)of NOAA's Earth System Research Laboratory, the FAA, and the World Meteorological Organization(WMO).

The TAMDAR sensor was originally deployed in December 2004 on a fleet of 63 Saab SF340 aircraftoperated by Mesaba Airlines in the Great Lakes region of the United States as a part of the NASA­sponsored Great Lakes Fleet Experiment (GLFE). Over the last twelve years, equipage of the sensorshas expanded beyond the continental US (CONUS) to include Alaska, Caribbean, Mexico, CentralAmerica, Europe, and Asia. Airlines flying the system include Icelandair, Horizon (Alaska Air Group),Chautauqua (Republic Airways), Piedmont (American Airlines), AeroMéxico, Ravn Alaska, Hageland,PenAir, Silver Airways and Flybe, as well as a few research aircraft including the UK Met Office BAe­146 FAAM aircraft. Recently, an installation agreement has been reached with a large Southeast Asianairline as well. The TAMDAR system has been in continuous operation since initial deployment inDecember 2004.

12/21/2015 TAMDAR ­ Wikipedia, the free encyclopedia

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System capabilities

TAMDAR observations include temperature, pressure, winds aloft, relative humidity (RH), icing andturbulence that are critical to both aviation safety and the operational efficiency of the U.S. NationalAirspace System (NAS) and other world airspace management systems as well as other weather­dependent operational environments such as maritime, defense and energy. Additionally, eachobservation includes GPS­derived horizontal and vertical (altitude) coordinates, as well as a time stampto the nearest second. With a continuous stream of observations, TAMDAR provides higher spatial andtemporal resolution compared to the Radiosonde (RAOB) network, as well as better geographiccoverage, and a more complete data set than sent over Aircraft Communication Addressing andReporting System (ACARS), which lacks RH, icing, and turbulence.

Upper­air observing systems are normally subject to latency based on the communication networks usedand quality assurance protocol. TAMDAR observations are typically received, processed, qualitycontrolled, and available for distribution or model assimilation in less than one minute from thesampling time. The sensor requires no flight crew involvement; it operates automatically and samplingrates and calibration constants can be adjusted by remote command from a US­based operations center.TAMDAR sensors continuously transmit atmospheric observations via a global satellite network in real­time as the aircraft climbs, cruises, and descends.

The system is normally installed on fixed­wing airframes ranging from small, unmanned aerial systems(UAS) to long­range wide­bodies such as the Boeing 777 or Airbus A380. Upon completion of theinstallations scheduled for 2015, more than 6,000 daily soundings will be produced in North America,Europe, and Asia at more than 400 locations. Emphasis has been placed on equipping regional carriersas these flights tend to (i) fly into more remote and diverse locations and (ii) be of shorter durationthereby producing more daily vertical profiles while remaining in the boundary layer for longerdurations.

Icing Observations

TAMDAR icing data provides the first high volume, objective icing data available to the airlineindustry. Ice reporting is normally available via pilot reports (PIREPs); while helpful, these subjectivereports do not provide objective accuracy and density. High­density, real­time TAMDAR icing reportsprovide accurate spatial and temporal distribution of icing hazards, as well as real­time observationswhere icing is not occurring. The icing data can be made available in raw observation form, or it can beused to improve icing potential model forecasts.

Turbulence Observations

The TAMDAR sensor provides objective, high­resolution eddy dissipation rate (EDR) turbulenceobservations. These data are collected for both median and peak turbulence measurements and arecapable of being sorted on a finer (7­point) scale than current subjective pilot reports (PIREPs), whichare reported as light, moderate, or severe. The EDR turbulence algorithm is aircraft­configuration andflight­condition independent, thus it does not depend on the type of plane, nor does it depend on loadand flight capacity.

This high­density real­time in­situ turbulence data can be used to alter flight arrival and departure routes.It also can be assimilated into models to improve predictions of threatening turbulence conditions, aswell as being used as a verification tool for longer­range numerical weather prediction (NWP)­basedturbulence forecasts. As with the icing observations, potential utility of this data in air traffic controldecision making for avoidance and mitigation of severe turbulence encounters can be significant.

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Forecast Models And Validation

Third­party studies have been conducted by NOAA­GSD, the National Center for AtmosphericResearch (NCAR), and various universities and government agencies to verify the accuracy ofTAMDAR data against that of weather balloons and aircraft test instrumentation, as well as quantifyingthe TAMDAR­related impacts on NWP. Ongoing data denial experiments show that the inclusion ofTAMDAR data can significantly improve forecast model accuracy with the greatest gains realizedduring more dynamic and severe weather events.

Upper­air observations are the single most important data set driving a forecast model. Fine­scaleregional forecast accuracy is dependent on a representation of the mid and upper­level atmospheric flow,moisture, and wave patterns. If these features are properly analyzed during the model initializationperiod, then an accurate forecast will ensue. TAMDAR data has been shown to increase forecastaccuracy over the U.S. on the order of 30­ to 50­percent for a monthly average, even for 3D­Var (GSI)models.

The FAA funded a four­year TAMDAR impact study that was concluded in January 2009. The studywas conducted by the Global Systems Division (GSD) of NOAA under an FAA contract to ascertain thepotential benefits of including TAMDAR data to the 3D­Var Rapid Update Cycle (RUC) model, whichwas the current operational aviation­centric model run by National Centers for Environmental Prediction(NCEP). Two parallel versions of the model were run with the control withholding the TAMDAR data.The results of this study concluded that significant gains in forecast skill were achieved with theinclusion of the data despite using 3D­Var assimilation methods. The reduction in 30­day running meanRMS error averaged throughout the CONUS domain within the boundary layer for model state variableswere:

• Up to 50% reduction in RH error

• 35% reduction in temperature error

• 15% reduction in wind error

This study was conducted using a 3D­Var model on a 13 km horizontal grid. Likewise, the nature of the30­day mean statistics dilutes the actual impact provided by TAMDAR's higher resolution data duringcritical weather events. The forecast skill gain during dynamic events is typically much greater thanwhat is expressed in a CONUS­wide monthly average. In other words, the increase in model accuracy isgreatest during dynamic weather events where air traffic and other operational impacts are greatest.

The Panasonic Weather Solutions RT­FDDA­WRF forecast runs on a North America domain with 4 kmgrid spacing and can include multiple nested 1 km domains. A four­year collaborative study with NCARusing the same data as in the studies referenced above has shown that the FDDA/4D­Var assimilationmethodology can nearly double the improvement in forecast skill over an identical model running a 3D­Var configuration. Results from this study are summarized below using the same 30­day running meanverification statistics as employed by NOAA. TAMDAR impact using FDDA/4D­Var resulted in:

• Reduction in humidity forecast error of 74%

• Reduction in temperature forecast error of 58%

• Reduction in wind forecast error of 63%

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Forecast skill, like the example presented above, is made possible by having (i) an asynoptic in­situobserving system like TAMDAR that streams continuous real­time observations to (ii) a forecast model(deterministic or probabilistic) that has the ability to assimilate asynoptic data in four dimensions.

Skew­T Profiles

TAMDAR sensors are currently set to sample at 300­ft intervals on ascent and descent. This resolutioncan be adjusted in real time to whatever interval is desired for the receiving forecasting model. Thesatellite connection to the sensor is a two­way connection so sampling rates, calibration constants,variables and parameters, and reporting frequencies can all be changed remotely from a ground­basedlocation. The sampling rate in cruise is time­based. The soundings, or vertical profiles, are built as eachobservation is received. All of the profile­based variable calculations (e.g., CAPE, CIN, etc.) arecalculated when an aircraft enters cruise or touches down. When an airport is selected, successivesoundings can be displayed within a certain time window. This enables the user to view the evolution ofthe profile.

External links

Panasonic Weather Solutions (http://www.panasonicweather.com/)Panasonic Avionics Corporation

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Categories: Meteorological data and networks

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