Abstract
Satellite altimetry allows the study of sea-level long-term variability on a global and spatially uniform basis. Here quantile regression is applied to derive robust median regression trends of mean sea level as well as trends in extreme quantiles from radar altimetry time series. In contrast with ordinary least squares regression, which only provides an estimate on the rate of change of the mean of data distribution, quantile regression allows the estimation of trends at different quantiles of the data distribution, yielding a more complete picture of long-term variability. Trends derived from basin-wide averaged regional mean sea level time series are robust and similar for all quantiles, indicating that all parts of the data distribution are changing at the same rate. In contrast, trends are not robust and diverge across quantiles in the case of local time series. Trends are under- (over-)estimated in the western (eastern) equatorial Pacific. Furthermore, trends in the lowermost quantile (0.05) are larger than the median trend in the western Pacific, while trends in the uppermost quantile (0.95) are lower than the median trend in the eastern Pacific. These differences in trends in extreme mean sea level quantiles are explained by the exceptional effect of the strong 1997-1998 El Nino-Southern Oscillation (ENSO) event.

Abstract
The classification ofmultivariate time series in terms of their corresponding temporal dependence patterns is a common problem in geosciences, particularly for large datasets resulting from environmental monitoring networks. Here a wavelet-based clustering approach is applied to sea level and atmospheric pressure time series at tide gauge locations in the Baltic Sea. The resulting dendrogram discriminates three spatially-coherent groups of stations separating the southernmost tide gauges, reflecting mainly high-frequency variability driven by zonal wind, from the middle-basin stations and the northernmost stations dominated by lower-frequency variability and the response to atmospheric pressure.

Abstract
A monthly index based on the persistence of the westerly winds over the English Chanel is constructed for 1685-2008 using daily data from ships' logbooks and comprehensive marine meteorological datasets. The so-called Westerly Index (WI) provides the longest instrumental record of atmospheric circulation currently available. Anomalous WI values are associated with spatially coherent climatic signals in temperature and precipitation over large areas of Europe, which are stronger for precipitation than for temperature and in winter and summer than in transitional seasons. Overall, the WI series accord with the known European climatic history, and reveal that the frequency of the westerlies in the eastern Atlantic during the twentieth century and the Late Maunder Minimum was not exceptional in the context of the last three centuries. It is shown that the WI provides additional and complementary information to the North Atlantic Oscillation (NAO) indices. The analysis of WI series during the industrial era indicates an overall good agreement with the winter and high-summer NAO, with the exception of several multidecadal periods of weakened correlation. These decoupled periods between the frequency and the intensity of the zonal flow are interpreted on the basis of several sources of non-stationarity affecting the centres of the variability of the North Atlantic and their teleconnections. Comparisons with NAO reconstructions and long instrumental indices extending back to the seventeenth century suggest that similar situations have occurred in the past, which call for caution when reconstructing the past atmospheric circulation from climatic proxies. The robustness and extension of its climatic signal, the length of the series and its instrumental nature make the WI an excellent benchmark for proxy calibration in Europe and Greenland.

Abstract
The atmospheric electric field near the Earth's surface is dominated by atmospheric pollutants and natural radioactivity, with the latter directly linked to radon (Rn-222) gas. For a better comprehension on the temporal variability of both the atmospheric electric field and the radon concentration and its relation with local atmospheric variables, simultaneous measurements of soil-emitted gamma radiation and potential gradient (defined from the vertical component of the atmospheric electric field) were taken every minute, along with local meteorological parameters (e.g., temperature, atmospheric pressure, relative humidity and daily solar radiation). The study region is Amieira, part of the Alqueva lake in Alentejo Portugal, where an interdisciplinary meteorological campaign, ALEX2014, took place from June to August 2014. Soil gamma radiation is more sensitive to small concentrations of radon as compared with alpha particles measurements, for that reason it is more suited for sites with low radon levels, as expected in this case. Preliminary results are presented here: statistical and spectral analysis show that i)the potential gradient has a stronger daily cycle as compared with the gamma radiation, ii) most of the energy of the gamma signal is concentrated in the low frequencies (close to 0), contrary to the potential gradient that has most of the energy in frequency 1 (daily cycle) and iii) a short-term relation between gamma radiation and the potential gradient has not been found. Future work and plans are also discussed.

Abstract
This study addresses long-term sea level variability in Macaronesia from a holistic perspective using all available instrumental records in the region, including a dense network of GPS continuous stations, tide gauges and satellite observations. A detailed assessment of vertical movement from GPS time series underlines the influence of the complex volcano-tectonic setting of the Macaronesian islands in local uplift/subsidence. Relative sea level for the region is spatially highly variable, ranging from -1.1 to 5.1 mm yr(-1). Absolute sea level from satellite altimetry exhibits consistent trends in the Macaronesia, with a mean value of 3.0 +/- 0.5 mm yr(-1). Typically, sea level trends from tide gauge records corrected for vertical movement using the estimates from GPS time series are lower than uncorrected estimates. The agreement between satellite altimetry and tide gauge trends corrected for vertical land varies substantially from island to island. Trends derived from the combination of GPS and tide gauge observations differ by less than 1 mm yr(-1) with respect to absolute sea level trends from satellite altimetry for 56 per cent of the stations, despite the heterogeneity in length of both GPS and tide gauge series, and the influence of volcanic-tectonic processes affecting the position of some GPS stations.

Abstract
The seasonal cycle accounts for about 40 % of the total sea level variability in the Baltic Sea. In a climate change context, changes are expected to occur, not only in mean levels but also in the seasonal characteristics of sea level. The present study addresses the quantification of changes in the seasonal cycle of sea level from a set of century-long tide gauge records in the Baltic Sea. In order to obtain robust estimates of the changes in amplitude and phase of the seasonal cycle, we apply different methods, including continuous wavelet filtering, multi-resolution decomposition based on the maximal overlap discrete wavelet transform, auto-regressive-based decomposition, singular spectrum analysis and empirical mode decomposition. The results show that all methods generally trace a similar long-term variability of the annual cycle amplitudes, and we focus on discrete wavelet analysis as the natural counterpart of classical moving Fourier analysis. In contrast to previous studies suggesting the existence of long-term changes in the seasonal cycle, in particular an increase of the annual amplitude, we find alternating periods of high and low amplitudes without any clear indication of systematic long-term trends. The derived seasonal patterns are spatially coherent, discriminating the stations in the Baltic entrance from the remaining stations in the Baltic basin, for which zonal wind accounts for typically more than 40 % of the variations in amplitude.