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Title: On the utilization of aircraft derived observations for operational meteorology and numerical weather prediction
Author: Mirza, Andrew Karl
ISNI:       0000 0004 6423 7613
Awarding Body: University of Reading
Current Institution: University of Reading
Date of Award: 2017
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This thesis analyses a new source of observations, Mode-Select Enhanced Surveillance (Mode-S EHS), obtained from reports exchanged between aircraft and air-traffic control. These reports contain the aircrafts speed, direction, altitude and Mach number. Observations of temperature and horizontal wind can be derived from the reports. However, Mode-S EHS processing reduces the reporting precision from 16-bit to 10-bit representation. We aim to understand the observation errors that are due to the reduced precision of Mode-S EHS reports, how accurately these derived observations represent vertical profiles of wind and temperature and the benefit they bring to convection-permitting NWP. We derive new models to estimate the observation errors and validate them using research grade instruments on board the Facility for Atmospheric Airborne Measurements. For the cases studied, the temperature observation error increases from 1.25 K to 2.5 K between an altitude of 10 km and the surface, due to its dependence on Mach number and Mode-S EHS precision. The zonal wind error is around 0.50 ms−1 and the meridional wind error is 0.25 ms−1. The horizontal wind is also subject to directionally dependent systematic errors. We aggregate Mode-S EHS reports from multiple aircraft to construct vertical pro- files of temperature and demonstrate their ability to resolve temperature inversions. However, there are large errors in the aggregated observations that are still dominated by the effects of reduced precision. We assess the benefits of Mode-S EHS for data assimilation in the Met Office convection-permitting NWP model. We find that assimilation of Mode-S EHS has a neutral impact. Using assimilation output statistics, we find that the observation uncertainties for AMDAR and Mode-S EHS horizontal wind are similar in magnitude, while for Mode-S EHS Mach temperature the diagnosed errors are similar to our new error model. Our new results may assist with utilising Mode-S EHS reports in operational forecasting.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available