Abstract: Magnetic observatories currently distribute two types of data: preliminary data, available in less than 72 hrs in the case of INTERMAGNET observatories, and definitive baseline-corrected data, produced only once a year. Several users and groups of users have expressed the need for baseline-corrected observatory data produced in a continuous manner. The main applications for such quasi-definitive data include geomagnetic field modeling and the calculation of geomagnetic activity indices. We present an original method for producing quasi-definitive data at the end of each calendar month using temporary baselines. Preliminary and definitive data at nine INTERMAGNET observatories are used to test this method, simulating the production of quasi-definitive data throughout the year 2008. The temporary baselines obtained are very close to the definitive ones, except during the last few days of each time interval. The means and standard deviations of the differences between quasi-definitive and definitive data do not exceed 0.3 nT, well below the current INTERMAGNET standard of accuracy. This result demonstrates the feasibility of promptly producing quasi-definitive data at most magnetic observatories of INTERMAGNET type.

Abstract: This study deals with the problem of identifying atmospheric data influenced by local emissions that can result in spikes in time series of greenhouse gases and long-lived tracer measurements. We considered three spike detection methods known as coefficient of variation (COV), robust extraction of baseline signal (REBS) and standard deviation of the background (SD) to detect and filter positive spikes in continuous greenhouse gas time series from four monitoring stations representative of the European ICOS (Integrated Carbon Observation System) Research Infrastructure network. The results of the different methods are compared to each other and against a manual detection performed by station managers. Four stations were selected as test cases to apply the spike detection methods: a continental rural tower of 100?m height in eastern France (OPE), a high-mountain observatory in the south-west of France (PDM), a regional marine background site in Crete (FKL) and a marine clean-air background site in the Southern Hemisphere on Amsterdam Island (AMS). This selection allows us to address spike detection problems in time series with different variability. Two years of continuous measurements of CO2, CH4 and CO were analysed. All methods were found to be able to detect short-term spikes (lasting from a few seconds to a few minutes) in the time series. Analysis of the results of each method leads us to exclude the COV method due to the requirement to arbitrarily specify an a priori percentage of rejected data in the time series, which may over- or underestimate the actual number of spikes. The two other methods freely determine the number of spikes for a given set of parameters, and the values of these parameters were calibrated to provide the best match with spikes known to reflect local emissions episodes that are well documented by the station managers. More than 96?% of the spikes manually identified by station managers were successfully detected both in the SD and the REBS methods after the best adjustment of parameter values. At PDM, measurements made by two analyzers located 200?m from each other allow us to confirm that the CH4 spikes identified in one of the time series but not in the other correspond to a local source from a sewage treatment facility in one of the observatory buildings. From this experiment, we also found that the REBS method underestimates the number of positive anomalies in the CH4 data caused by local sewage emissions. As a conclusion, we recommend the use of the SD method, which also appears to be the easiest one to implement in automatic data processing, used for the operational filtering of spikes in greenhouse gases time series at global and regional monitoring stations of networks like that of the ICOS atmosphere network.