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We propose a new cloud screening method for sun photometry that is designed to effectively filter thin clouds. Our method is based on a k -nearest-neighbour algorithm instead of scanning time series of aerosol optical depth. Using 10 years of data from a precision filter radiometer in Innsbruck, we compare our new method and the currently employed screening technique. We exemplify the performance of the two routines in different cloud conditions. While both algorithms agree on the classification of a data point as clear or cloudy in a majority of the cases, the new routine is found to be more effective in flagging thin clouds. We conclude that this simple method can serve as a valid alternative for cloud detection, and we discuss the generalizability to other observation sites. [ABSTRACT FROM AUTHOR]

We describe and test a new versatile software tool for processing eddy covariance and disjunct eddy covariance flux data. We present an evaluation based on urban non-methane volatile organic compound (NMVOC) measurements using a proton transfer reaction quadrupole interface time-of-flight mass spectrometer (PTR-QiTOF-MS) at the Innsbruck Atmospheric Observatory. The code is based on MATLAB® and can be easily configured to process high-frequency, low-frequency and disjunct data. It can be applied to a wide range of analytical setups for NMVOC and other trace gas measurements, and is tailored towards the application of noisy data, where lag time corrections become challenging. Several corrections and quality control routines are implemented to obtain the most reliable results. The software is open source, so it can be extended and adjusted to specific purposes. We demonstrate the capabilities of the code based on a large urban dataset collected in Innsbruck, Austria, where three-dimensional winds and ambient concentrations of NMVOCs and auxiliary trace gases were sampled with high temporal resolution above an urban canopy. Concomitant measurements of 12C and 13C isotopic NMVOC fluxes allow testing algorithms used for determination of flux limits of detection (LOD) and lag time analysis. We use the high-frequency NMVOC dataset to generate a set of disjunct data and compare these results with the true eddy covariance method. The presented analysis allows testing the theory of disjunct eddy covariance (DEC) in an urban environment. Our findings confirm that the disjunct eddy covariance method can be a reliable tool, even in complex urban environments when fast sensors are not available, but that the increase in random error impedes the ability to detect small fluxes due to higher flux LODs. [ABSTRACT FROM AUTHOR]