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Temperature and wind observations from aircraft are regarded of major importance for aviation meteorology and numerical weather prediction (NWP). The European Meteorological Aircraft Derived Data Center (EMADDC) system processes aircraft surveillance data received from air traffic control (ATC) and converts it into observations of wind and temperature. Only so-called Mode-S Enhanced Surveillance data can be used, because this data contains the air vector and ground vector of the aircraft, from which a wind vector can be inferred. To acquire high quality observations, the data is processed in three steps: pre-processing, processing, and post-processing. The pre-processing is needed to obtain high-quality information and to calculate several correction values such as temperature corrections and heading corrections. Processing converts the aircraft data into meteorological information and finally post-processing guarantees that only high-quality information is made available. The quality of the observations produced is verified by comparing these observation to other upper air wind and temperature observations from radiosondes and comparing them with NWP data. This paper presents the EMADDC system, operational since 2019. [ABSTRACT FROM AUTHOR]

Some aircraft temperature observations, retrieved through the Aircraft Meteorological Data Relay (AMDAR), suffer from a significant warm bias when comparing observations with numerical weather prediction (NWP) model. In this manuscript we show that this warm bias of AMDAR temperature can be characterized and consequently reduced substantially. The characterization of this warm bias is based on the methodology of measuring temperature with a moving sensor and can be split into two separate processes. The first process depends on the flight phase of the aircraft and relates to difference of timing, as it appears that the time of measurement of altitude and temperature differ. When an aircraft is ascending or descending this will result in small bias in temperature due to the (on average) presence of an atmospheric temperature lapse rate. The second process is related to internal corrections applied to pressure altitude without feedback to temperature observation measurement. Based on NWP model temperature data combined with additional information on Mach number and true airspeed, we were able to estimate corrections using an 18 months period from January 2017 to July 2018. Next, the corrections were applied on AMDAR observations over the period from September 2018 to mid-December 2019. Comparing these corrected temperatures with (independent) radiosonde temperature observations demonstrates a reduction of the temperature bias from 0.5 K to around zero and reduction of standard deviation of almost 10 %. [ABSTRACT FROM AUTHOR]