A New Radiosonde System for Profiling the Lower Troposphere

Corner, Brian R.; Palmer, Robert D.; Larsen, M. F.

doi:10.1175/1520-0426(1999)016<0828:anrsfp>2.0.co;2

Cited by 5 publications

(4 citation statements)

References 1 publication

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“…Leiterer et al, 1997;Corner et al, 1999;Miloshevich et al, 2001), the quality of AMDAR data has been addressed only by a small number of investigations (Schwartz and Benjamin, 1995;Benjamin et al, 1999;Ballish and Kumar, 2006). These are mostly targeted at quantifying typical error ranges.…”

Section: Error Studiesmentioning

confidence: 99%

Aircraft type‐specific errors in AMDAR weather reports from commercial aircraft

Drüe

Frey

Hoff

et al. 2008

Quart J Royal Meteoro Soc

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AMDAR (Aircraft Meteorological DAta Relay) automated weather reports from commercial aircraft provide an increasing amount of input data for numerical weather prediction models. Previous studies have investigated the quality of AMDAR data. Few of these studies, however, have revealed indications of systematic errors dependent upon the aircraft type. Since different airlines use different algorithms to generate AMDAR reports, it has remained unclear whether a dependency on the aircraft type is caused by physical properties of the aircraft or by different data processing algorithms. In the present study, a special AMDAR dataset was used to investigate the physical type-dependent errors of AMDAR reports. This dataset consists of AMDAR measurements by Lufthansa aircraft performing over 300 landings overall at Frankfurt Rhein/Main (EDDF/FRA) on 22 days in 2004. All of this data has been processed by the same software, implying that influences from different processing algorithms should not be expected. From the comparison of single descents to hourly averaged vertical profiles, it is shown that temperature measurements by different aircraft types can have systematic differences of up to 1 K. In contrast, random temperature errors of most types are estimated to be less than 0.3 K. It is demonstrated that systematic deviations in AMDAR wind measurements can be regarded as an error vector, which is fixed to the aircraft reference system. The largest systematic deviations in wind measurements from different aircraft types (more than 0.5 m s −1 ) were found to exist in the longitudinal direction (i.e. parallel to the flight direction).

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Section: Error Studiesmentioning

confidence: 99%

Aircraft type‐specific errors in AMDAR weather reports from commercial aircraft

Drüe

Frey

Hoff

et al. 2008

Quart J Royal Meteoro Soc

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“…Unlike the quality of radiosonde data that has been subject to a large number of studies (Corner et al, 1999;Ingleby et al, 2016;Mapes et al, 2003;Miloshevich et al, 2001), only a small number of studies have investigated the quality of AMDAR data (e.g., Benjamin et al, 1999;Drüe et al, 2008). They assessed the accuracy of AMDAR data by comparing them against radiosonde data (Ding et al, 2015;Schwartz & Benjamin, 1995), wind profiler radar data (Drüe et al, 2010), or model-simulated fields (Ballish & Kumar, 2008;Moninger et al, 2010Moninger et al, , 2003.…”

Section: Introductionmentioning

confidence: 99%

Development and Evaluation of a Long‐Term Data Record of Planetary Boundary Layer Profiles From Aircraft Meteorological Reports

Zhang

Lin

et al. 2019

JGR Atmospheres

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High‐quality measurements of planetary boundary layer (PBL) profiles are important for advancing our understanding of land‐atmosphere coupling and PBL processes and improving the predictive capability of numerical models. Now with more than 10 years of observations from Aircraft Meteorological Data Reports (AMDAR), a decade‐long (from 2007 to 2016) data record of hourly PBL profiles is developed over 54 U.S. airports. Comparisons between the derived hourly profiles and nearby radiosonde data, which are typically only available twice a day (at 00 and 12 UTC), show good agreement between the two data sets. The root‐mean‐square errors (RMSEs) between the AMDAR and radiosonde data are found to be dependent on the distance between the two data sets, especially at lower levels. The RMSEs of temperature generally decrease as the altitude increases, while the RMSEs of specific humidity and wind are positively correlated with the measurement magnitude. At perfect collocations (i.e., the separation distance is zero), the seasonal RMSEs at measurement levels with pressure larger than 850 hPa are 1.16–1.52 K, 0.64–1.25 g/kg, and 2.00–2.26 m/s for temperature, humidity, and wind components, respectively. Compared to the RMSEs, the mean biases of AMDAR profiles are much smaller and are less dependent on the separation distance. The RMSEs show little dependence on flight phases (ascent or descent) in the lower troposphere. Overall, our results indicate that the aircraft measurements are accurate enough to be an alternative to the radiosonde data and are better suited for investigating the diurnal variation of PBL due to their higher temporal resolution.

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“…For troposphere temperatures for use in ''aeronautical meteorology,'' these are 5 K (threshold), 3 K (breakthrough), and 2 K (goal). The errors in AMDAR and radiosonde temperatures have been estimated to be ,0:5 and ,0:1 K, respectively (Painting 2003;Drüe et al 2008;Corner et al 1999). …”

Section: Discussionmentioning

confidence: 99%

Introducing an Approach for Extracting Temperature from Aircraft GNSS and Pressure Altitude Reports in ADS-B Messages

Stone

Kitchen

2015

Journal of Atmospheric and Oceanic Technology

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Recently work has been conducted in using routine air traffic management (ATM) data from aircraft to derive meteorological observations (de Haan; de Haan and Stoffelen). The paper at hand introduces and provides an initial analysis for a method of finding layer temperatures from aircraft broadcast messages. The method is analyzed using error analysis and is shown capable of producing mean layer temperatures with below 61-K error with a layer thickness of 2000 m. Observed aircraft data have been compared to the expected errors from the analysis and have shown to be consistent to within 0.01K. An initial comparison using four Aircraft Meteorological Data Relay (AMDAR) flights is also provided. The new layer temperature, existing Mode-S enhanced surveillance (EHS)-derived temperature, and an average Mode-S EHS-derived temperature are all compared to the AMDAR temperatures. The averaged Mode-S EHS-derived layer temperature is shown to have the lowest spread (mean standard deviation 5 0:76 K), followed by the layer temperature introduced by this paper (mean standard deviation 5 1:02 K), and then the unaveraged Mode-S EHS-derived temperature (mean standard deviation 5 1:95 K). The layer temperature method has the advantage that no requested data are required from the aircraft, as all of the required parameters are part of the routine broadcast messages, making the method ideal in areas with a limited air traffic management infrastructure where the existing methods would not work.

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A New Radiosonde System for Profiling the Lower Troposphere

Cited by 5 publications

References 1 publication

Aircraft type‐specific errors in AMDAR weather reports from commercial aircraft

Aircraft type‐specific errors in AMDAR weather reports from commercial aircraft

Development and Evaluation of a Long‐Term Data Record of Planetary Boundary Layer Profiles From Aircraft Meteorological Reports

Introducing an Approach for Extracting Temperature from Aircraft GNSS and Pressure Altitude Reports in ADS-B Messages

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