Abstract. The Airborne imaging differential optical absorption spectroscopy (DOAS) instrument for Measurements of Atmospheric Pollution (AirMAP) has been developed for the purpose of trace gas measurements and pollution mapping. The instrument has been characterized and successfully operated from aircraft. Nitrogen dioxide (NO 2 ) columns were retrieved from the AirMAP observations. A major benefit of the push-broom imaging instrument is the spatially continuous, gap-free measurement sequence independent of flight altitude, a valuable characteristic for mapping purposes. This is made possible by the use of a charge coupled device (CCD) frame-transfer detector. A broad field of view across track of around 48 • is achieved with wide-angle entrance optics. This leads to a swath width of about the same size as the flight altitude. The use of fibre coupled light intake optics with sorted light fibres allows flexible instrument positioning within the aircraft and retains the very good imaging capabilities. The measurements yield ground spatial resolutions below 100 m depending on flight altitude. The number of viewing directions is chosen from a maximum of 35 individual viewing directions (lines of sight, LOS) represented by 35 individual fibres. The selection is adapted to each situation by averaging according to signal-to-noise or spatial resolution requirements. Observations at 30 m spatial resolution are obtained when flying at 1000 m altitude and making use of all 35 viewing directions. This makes the instrument a suitable tool for mapping trace gas point sources and small-scale variability. The position and aircraft attitude are taken into account for accurate spatial mapping using the Attitude and Heading Reference System of the aircraft. A first demonstration mission using AirMAP was undertaken in June 2011. AirMAP was operated on the AWI Polar-5 aircraft in the framework of the AIRMETH-2011 campaign. During a flight above a medium-sized coal-fired power plant in north-west Germany, AirMAP clearly detected the emission plume downwind from the exhaust stack, with NO 2 vertical columns around 2 × 10 16 molecules cm −2 in the plume centre. NO x emissions estimated from the AirMAP observations are consistent with reports in the European Pollutant Release and Transfer Register. Strong spatial gradients and variability in NO 2 amounts across and along flight direction are observed, and small-scale enhancements of NO 2 above a motorway are detected.
A quality control method for combined online monitoring of weather radar antenna pointing biases and receiver calibration using solar signals detected by an operational radar is adapted for application to midrange radar data (80-150 km). As the original method was developed using long-range data, additional criteria based on robust statistical estimators are imposed in the sun signature detection and selection process, allowing to discard observations biased by ground clutter or precipitation and to remove very influential outliers. The validity ranges of the physical model describing the solar interferences detected by the scanning radar antenna are explicitly defined and an equation for estimation of the effective scanning width in reception is provided in a thorough theoretical derivation. The method proposed reveals its sensitivity to changes in the antenna pointing accuracy and receiver calibration when applied to operational data obtained with three C-band radars during one year. A comparative study on the goodness of fit between a three-and a five-parameter model highlights the effect on the stability and accuracy of the antenna and receiver parameters retrieved for each radar system, considering the dissimilar information content of the observations collected by each radar. The performance of the proposed methodology under the effects of the presence of ground clutter and radio local area network interferences is discussed in the results presented.
In Doppler weather radars, the presence of unfolding errors or outliers is a well-known quality issue for radial velocity fields estimated using the dual–pulse repetition frequency (PRF) technique. Postprocessing methods have been developed to correct dual-PRF outliers, but these need prior application of a dealiasing algorithm for an adequate correction. This paper presents an alternative procedure based on circular statistics that corrects dual-PRF errors in the presence of extended Nyquist aliasing. The correction potential of the proposed method is quantitatively tested by means of velocity field simulations and is exemplified in the application to real cases, including severe storm events. The comparison with two other existing correction methods indicates an improved performance in the correction of clustered outliers. The technique proposed is well suited for real-time applications requiring high-quality Doppler radar velocity fields, such as wind shear and mesocyclone detection algorithms, or assimilation in numerical weather prediction models.
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