000005688 001__ 5688
000005688 005__ 20220215111132.0
000005688 0247_ $$2DOI$$a10.1080/00224065.2022.2041376
000005688 037__ $$aSCART-2022-0041
000005688 100__ $$aMathieu, Sophie
000005688 245__ $$aNonparametric monitoring of sunspot number observations. 
000005688 260__ $$c2022
000005688 520__ $$aSolar activity is an important driver of long-term climate trends and must be accounted for in climate models. Unfortunately, direct measurements of this quantity over long periods do not exist. The only observation related to solar activity whose records reach back to the seventeenth century are sunspots. Surprisingly, determining the number of sunspots consistently over time has remained until today a challenging statistical problem. It arises from the need of consolidating data from multiple observing stations around the world in a context of low signal-to-noise ratios, non-stationarity, missing data, non-standard distributions and errors of different kind. The data from some stations experience therefore severe and various deviations over time. In this paper, we apply a systematic statistical approach for monitoring these complex and important series. It consists of three steps essential for successful treatment of the data: smoothing on multiple time-scales, monitoring using block bootstrap calibrated CUSUM charts and classifying of out-of-control situations by support vector techniques. This approach allows us to detect a wide range of anomalies (such as sudden jumps or more progressive drifts), unseen in previous analyses. It helps us to identify the causes of major deviations, which are often observer or equipment related. Their detection and identification will contribute to improve future observations. Their elimination or correction in past data will lead to a more precise reconstruction of the world reference index for solar activity: the International Sunspot Number.
000005688 594__ $$aNO
000005688 6531_ $$asolar activity
000005688 6531_ $$asunspot number
000005688 6531_ $$amonitoring
000005688 700__ $$aLefèvre, Laure 
000005688 700__ $$avon Sachs, Rainer 
000005688 700__ $$aDelouille, Veronique 
000005688 700__ $$aRitter, Christian 
000005688 700__ $$aClette, Frédéric 
000005688 773__ $$pJournal of Quality Technology,$$y2022
000005688 8560_ $$fveronique.delouille@observatoire.be
000005688 905__ $$ain press to
000005688 980__ $$aREFERD