Static Source Error Calibration of a Nose Boom Mounted Air Data System on an Atmospheric Research Aircraft Using the Trailing Cone Method

This work demonstrates the calibration of an experimental air data probe on an atmospheric research aircraft by means of the Trailing Cone method. The probe under investigation is located on a nose boom in order to minimize the aerodynamic influence of the fuselage on the pressure measurement ahead of the aircraft. However, the data from this experiment proves that this configuration is still subject to significant pressure deviations from the undisturbed atmospheric values. This work demonstrates the determination of this error and presents an appropriate parameterization of the data which is prerequisite to provide accurately corrected pressure readings from this sensor. The experiment covers the determination of the proper configuration (length) for the Trailing Cone assembly, the validation of the method itself and the subsequent calibration of the air data sensor. Several improvements were applied to the Trailing Cone method in order to reduce the flight test effort as well as to significantly enhance the accuracy of the method itself. As a consequence a total of only three test flights was necessary to validate the method and to calibrate the air data sensor. The data analysis shows that the accuracy of the Trailing Cone reference measurement is very close to the pressure sensor calibration limit of 0.1hPa. The resulting accuracy of the corrected pressure measurement by the nose boom mounted pressure probe was demonstrated to be about 0.2 hPa, which represents the 3σ value

A new airborne broadband radiometer system and an efficient method to correct thermal offsets

The instrumentation of the High Altitude and Long Range (HALO) research aircraft is extended by the new Broadband AirCrAft RaDiometer Instrumentation (BACARDI) to quantify the radiative energy budget. Two sets of pyranometers and pyrgeometers are mounted to measure upward and downward solar (0.3&ndash;3 &mu;m) and thermal-infrared (3&ndash;100 &mu;m) irradiances. The radiometers are installed in a passively ventilated fairing to reduce the effects of the dynamic environment, e.g., fast changes of altitude and temperature. The remaining thermal effects range up to 20 W m-2 for the pyranometers and 10 W m-2 for the pyrgeometers; they are corrected using an new efficient method that is introduced in this paper. Using data collected by BACARDI during a night flight, the thermal offsets are parameterized by the rate of change of the radiometer sensor temperatures. Applying the sensor temperatures instead of ambient air temperature for the parameterization provides a linear correction function (200&ndash;600 W m-2 K-1 s), that depends on the mounting position of the radiometer on HALO. Furthermore, BACARDI measurements from the EUREC4A (Elucidating the role of clouds-circulation coupling in climate) field campaign are analyzed to characterize the performance of the radiometers and to evaluate all corrections applied in the data processing. Vertical profiles of irradiance measurements up to 10 km altitude show that the thermal offset correction limits the bias due to temperature changes to values below 10 W m-2. Measurements with BACARDI during horizontal, circular flight patterns in cloud-free conditions demonstrate that the common geometric attitude correction of the solar downward irradiance provides reliable measurements in this typical flight sections of EUREC4A, even without active stabilization of the radiometer.</p

Determination of the Measurement Errors for the HALO Basic Data System BAHAMAS by Means of Error Propagation

Der Forschungsbericht beschreibt die Bestimmung der Messfehler für die meteorologischen Basisdaten des Atmosphären-Forschungsflugzeugs HALO. Diese Daten werden von der vom DLR entwickelten Basismessanlage BAHAMAS erfasst. Die Fehleranalyse basiert auf einer Fehlerfortpflanzungs-Methode, bei der auf die originalen Messdaten ein künstliches weißes Rauschsignal aufsetzt wird, das auf diese Weise die gesamte Datenverarbeitung durchläuft. Die Fehlerrechnung umfasst sowohl statistische Messfehler in den originalen Rohdaten als auch systematischen Fehlerbeiträge in der Datenprozessierung, die durch Sensorkalibrierung, ungenaue Parametrisierungen von physikalischen Zusammenhängen oder Unsicherheiten aus Laborergebnissen herrühren. Die präsentierte Methode stellt eine echte Fehlerfortpflanzung da und basiert nicht auf Vereinfachungen oder Linearisierungs-Ansätzen wie bei einer klassischen Fehlerfortpflanzungsbetrachtung. Das Dokument präsentiert und diskutiert alle bekannten Fehlerquellen für Basismessdaten auf HALO. Abschließend werden Ergebnisse dieser Fehleranalyse für typische Flugszenarien dargestellt und mögliche Ansatzpunkte für eine weitere Minimierung dieser Fehler diskutiert

Climate change affects vegetation differently on siliceous and calcareous summits of the European Alps

The alpine life zone is expected to undergo major changes with ongoing climate change. While an increase of plant species richness on mountain summits has generally been found, competitive displacement may result in the long term. Here, we explore how species richness and surface cover types (vascular plants, litter, bare ground, scree and rock) changed over time on different bedrocks on summits of the European Alps. We focus on how species richness and turnover (new and lost species) depended on the density of existing vegetation, namely vascular plant cover. We analyzed permanent plots (1 x 1 m) in each cardinal direction on 24 summits (24 x 4 x 4), with always four summits distributed along elevation gradients in each of six regions (three siliceous, three calcareous) across the European Alps. Mean summer temperatures derived from downscaled climate data increased synchronously over the past 30 years in all six regions. During the investigated 14 years, vascular plant cover decreased on siliceous bedrock, coupled with an increase in litter, and it marginally increased on higher calcareous summits. Species richness showed a unimodal relationship with vascular plant cover. Richness increased over time on siliceous bedrock but slightly decreased on calcareous bedrock due to losses in plots with high plant cover. Our analyses suggest contrasting and complex processes on siliceous versus calcareous summits in the European Alps. The unimodal richness-cover relationship and species losses at high plant cover suggest competition as a driver for vegetation change on alpine summits

Use of Numerical Weather Prediction Analysis for Testing Pressure Altitude Measurements on Aircraft - An Application Example

Accurate static pressure measurements are essential for safe navigation. Aircraft static pressure measurements need to be calibrated and verified. We recently compared trailing cone static pressure measurements behind two different jet aircraft up to flight level 450 during 6 flights on different days with numerical weather prediction (NWP) data. The GNSS height above mean sea level measured during these flights is compared to NWP geopotential height. The NWP data were provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). The height differences at same pressure are 0.6±2.8 m on average. The corresponding pressure difference was determined to be -0.01±0.15 hPa. The method of comparing operational pressure/GNSS measurements on aircraft with NWP analysis or predictions can be used for testing the height keeping performance of aircraft after or during operation. Here we present an application example of the method. We show static pressure measured by research instruments on the German atmospheric research aircraft HALO compared to ECMWF analysis for 57 hours of data from an atmospheric research project over Europe in 2014. The method is used to derive corrected static pressure data. The corrected pressure also leads to a slightly better agreement between temperature measurements and ECMWF data which differed more when using the uncorrected pressure data as input for interpolation in the NWP data

Static Source Error Calibration of a Nose Boom Mounted Air Data System on an Atmospheric Research Aircraft Using the Trailing Cone Method

This work demonstrates the calibration of an experimental air data probe on an atmospheric research aircraft by means of the Trailing Cone method. The probe under investigation is located on a nose boom in order to minimize the aerodynamic influence of the fuselage on the pressure measurement ahead of the aircraft. However, the data from this experiment proves that this configuration is still subject to significant pressure deviations from the undisturbed atmospheric values. This work demonstrates the determination of this error and presents an appropriate parameterization of the data which is prerequisite to provide accurately corrected pressure readings from this sensor. The experiment covers the determination of the proper configuration (length) for the Trailing Cone assembly, the validation of the method itself and the subsequent calibration of the air data sensor. Several improvements were applied to the Trailing Cone method in order to reduce the flight test effort as well as to significantly enhance the accuracy of the method itself. As a consequence a total of only three test flights was necessary to validate the method and to calibrate the air data sensor. The data analysis shows that the accuracy of the Trailing Cone reference measurement is very close to the pressure sensor calibration limit of 0.1hPa. The resulting accuracy of the corrected pressure measurement by the nose boom mounted pressure probe was demonstrated to be about 0.2 hPa, which represents the 3σ value

Calibration of a Nose Boom Mounted Airflow Sensor on an Atmospheric Research Aircraft by Inflight Maneuvers

The document demonstrates the complete calibration of an air data sensor on the German atmospheric research aircraft HALO. The airflow probe which is mounted on the tip of a nose boom measures static and dynamic pressure as well as the two airflow angles: angle of attack and angle of sideslip. These four units and a temperature measurement are required to calculate the complete 3-dimensional airflow vector which is used for flight testing as well as for the determination of the wind speed vector in atmospheric research. The report is based on the preceding static source calibration of this sensor by means of a trailing cone which is documented in a preceeding DLR Forschungsbericht (2019-07). The document demonstrates step by step how to determine the necessary corrections which are required to calculate the true airflow vector with extremely small measurement errors and a high temporal resolution. The calibration uses known properties of the atmospheric wind and therefore requires the establishment of a 3-dim wind measurement on the aircraft. The necessary experimental flight test effort concerns static calibration procedures for the mean air data units as well as dynamic maneuvers which are required to investigate the response of the experimental air data system to fast airflow fluctuations. The dynamic corrections prove that the direct measurement of vertical and horizontal wind fluctuations shows a directional sensitivity which must be corrected if the data is used for meteorological investigations. (Published in English

Calibration of a Nose Boom Mounted Airflow Sensor on an Atmospheric Research Aircraft by Inflight Maneuvers

The document demonstrates the complete calibration of an air data sensor on the German atmospheric research aircraft HALO. The airflow probe which is mounted on the tip of a nose boom measures static and dynamic pressure as well as the two airflow angles: angle of attack and angle of sideslip. These four units and a temperature measurement are required to calculate the complete 3-dimensional airflow vector which is used for flight testing as well as for the determination of the wind speed vector in atmospheric research. The report is based on the preceding static source calibration of this sensor by means of a trailing cone which is documented in a preceeding DLR Forschungsbericht (2019-07). The document demonstrates step by step how to determine the necessary corrections which are required to calculate the true airflow vector with extremely small measurement errors and a high temporal resolution. The calibration uses known properties of the atmospheric wind and therefore requires the establishment of a 3-dim wind measurement on the aircraft. The necessary experimental flight test effort concerns static calibration procedures for the mean air data units as well as dynamic maneuvers which are required to investigate the response of the experimental air data system to fast airflow fluctuations. The dynamic corrections prove that the direct measurement of vertical and horizontal wind fluctuations shows a directional sensitivity which must be corrected if the data is used for meteorological investigations. (Published in English

Comparison of Static Pressure from Aircraft Trailing Cone Measurements and Numerical Weather Prediction Analysis

Accurate static pressure measurements are a prerequisite for safe navigation and precise air data measurements on aircraft. Pressure is also fundamental to assess winds and air temperature and, hence, important for meteorology. The direct static pressure measurement by aircraft is disturbed by the aircraft aerodynamics and needs to be corrected using proper calibration. In this paper we compare static pressure measured by means of a trailing cone (TC) in the undisturbed atmosphere behind two different jet aircraft (Dassault FALCON 20E and Gulfstream 550 “HALO”) at flight levels (FL) from 40 to 450 during 6 flights on different days with data from numerical weather predictions (NWP). The height is derived from differential Global Navigation Satellite System (GNSS) measurements. The GNSS height is compared to NWP geopotential height. The NWP data were provided by the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). The IFS model assumes constant gravity g. For constant g, the pressure differences (at same height) have mean values and standard deviations of 0.40±0.17 hPa for 159 individual measurements of 43±31 s duration each. The respective height differences (at same pressure) are -10±5 m on average over the same measurements. When computing the geopotential with latitude/height dependent gravity (which is 0.4 % smaller at FL 450 than at 0 km) the agreement becomes significantly better: -0.01±0.15 hPa for pressure, 0.6±2.8 m for height. This pressure accuracy implies NWP temperature errors <0.1 K on average below 10 km altitude. Standard deviations of random errors in the TC-NWP difference are 0.06 hPa and 1 m. The TC measurements provide a first quantification of the case-specific accuracy of NWP pressure geopotential relationships. The method of comparing operational pressure/GNSS measurements on aircraft with NWP analysis or predictions can be used to test the height keeping performance of aircraft after or during operation

Static Pressure from Aircraft Trailing-Cone Measurements and Numerical Weather-Prediction Analysis

Accurate static pressure measurements are a prerequisite for safe navigation and precise air data measurements on aircraft. Pressure is also fundamental for wind and air temperature analysis in meteorology. Static pressure measurement by aircraft is disturbed by aerodynamics and needs to be corrected using calibration. In this paper we compare static pressure measured by means of a trailing cone (TC) in the atmosphere behind two different jet aircraft at flight levels up to 450 with data from numerical weather predictions (NWP). The height is derived from differential Global Navigation Satellite System (GNSS) measurements. The GNSS height is compared to NWP geopotential height. The NWP data were provided by the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). When computing the geopotential with latitude/height dependent gravity the pressure/height differences are -0.01+-0.15 hPa and 0.6+-2.8 m. This pressure accuracy implies NWP temperature errors <0.1 K on average below 10 km altitude. The TC measurements provide a first quantification of the case-specific accuracy of NWP pressure-geopotential relationships. The method of comparing operational pressure/GNSS measurements on aircraft with NWP analysis or predictions can be used to test the height keeping performance of aircraft after or during operation