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Temperature anomalies in the lower stratosphere (namely, at 50-hPa) poleward of 30°N (hereafter, T50) are analysed from reanalysis daily products (i.e. ERA-40 and NCEP/NCAR) in order to detect those regions with statistically significant trends of T50 during the common 1957–2002 period. We also analyse radiosonde data in order to validate the reanalyses results. The analyses are conducted for the extended polar winter (i.e. from November to May) in order to relate T50 changes to the northern polar vortex variability. In relation to the previous literature, the novelty of this study is double: first, temporal evolution is considered according to regions with similar T50 temporal variability in the Northern Hemisphere; second, trend analyses of stratospheric temperatures are obtained with the use of running windows with variable width of each principal component series computed from monthly mean values. Two main stratospheric regions were identified from both reanalyses, with a statistically significant cooling within the study period: one over the high latitudes and a second one tracing a subtropical ring. The first one was detected in November, December and May during several decades, particularly at the beginning and in the middle of the study period (i.e. 1957–1985). The second region (i.e. the subtropical ring) showed overall cooling for all months along the study period. In addition, the lower stratospheric temperature over northern Europe exhibited an outstanding cooling in May for the whole study period. The results obtained from both reanalyses are practically identical, a fact that provides robustness thereto. Radiosonde data confirm the above-mentioned results, but the magnitude of the trends given by reanalysis products is substantially overestimated in the winter months over high latitudes., This research was supported by the ANCESTRAL project (CGL2008-06295), which was funded by the Spanish Ministry of Science and Innovation, and the PRESTAMOS project (CGL2012-34997), which is funded by the Spanish Ministry of Economy and Competitiveness. The authors wish to thank Radan Huth (Institute of Atmospheric Physics, Prague, Czech Republic) for his suggestions regarding the principal components analysis (PCA) and the anonymous reviewers for their useful comments. One of the co-authors, J.A. Lopez-Bustins, is a member of the Climatology Group (2014 SGR 300, Catalan Govt). Arturo Sanchez-Lorenzo is supported by the ‘Comissionat per a Universitats i Recerca del Departament d'Innovació, Universitats i Empresa de la Generalitat de Catalunya’ (2011 BP-B 00078) and by a postdoctoral fellowship (JCI-2012-12508).

Ponencia presentada en: XXXI Jornadas Científicas de la AME y el XI Encuentro Hispano Luso de Meteorología celebrado en Sevilla, del 1 al 3 de marzo de 2010. En el mes de junio de 2008 se desarrolló una campaña de medidas en la Capa Límite Atmosférica en el CIBA (Centro de Investigación de la Baja Atmósfera), que se encuentra sobre un extenso páramo de la meseta norte (41º49’ N, 4º56’ W) de características de terreno homogéneo. Se dispuso de instrumentación en una nueva torre meteorológica de 10m, que incluye en varios niveles sensores de temperatura y humedad, anemómetros de cazoletas y veletas, así como un anemómetro sónico. También se dispuso de dos microbarómetros con tecnología de cuarzo en los niveles de 50 y 100m en la torre principal del CIBA (de 100m). Además, tres microbarómetros adicionales se situaron en una disposición triangular de unos 200m de lado en la superficie. Por otra parte, se utilizó un globo cautivo para la determinación de perfiles verticales de temperatura y viento hasta 1000 m de altura. Finalmente, un monitor de partículas GRIMM (MODELO 365), que permite la medida simultánea y continúa de la concentración de partículas materiales de diferentes tamaños (PM10, PM2.5 y PM1) cada 6 segundos, se instaló a 1.5m del suelo. Este trabajo muestra algunos resultados preliminares de la campaña CIBA2008, a partir del análisis de los principales procesos físicos presentes en la Capa Límite Nocturna (NBL), de los diferentes periodos de estabilidad observados y de los correspondientes parámetros turbulentos, así como de las estructuras coherentes detectadas. Las perturbaciones de presión medidas en los diferentes microbarómetros permiten estudiar los principales parámetros ondulatorios a través de transformadas wavelet, y comparar dichas estructuras con las detectadas en los registros de viento y de partículas. Proyectos CGL2006-12474-C03-03 y CGL2009- 12797-C03-03 del Ministerio de Ciencia e Innovación. Grupos de Investigación (Micrometeorología y Variabilidad Climática: 910437) financiados por el Banco Santander y la Universidad Complutense de Madrid (Financiación Grupos UCM-BSCH GR58/08).

Major mid-winter stratospheric sudden warmings (SSWs) are the largest instance of wintertime variability in the Arctic stratosphere. Because SSWs are able to cause significant surface weather anomalies on intra-seasonal timescales, several previous studies have focused on their potential future change, as might be induced by anthropogenic forcings. However, a wide range of results have been reported, from a future increase in the frequency of SSWs to an actual decrease. Several factors might explain these contradictory results, notably the use of different metrics for the identification of SSWs and the impact of large climatological biases in single-model studies. To bring some clarity, we here revisit the question of future SSW changes, using an identical set of metrics applied consistently across 12 different models participating in the Chemistry–Climate Model Initiative. Our analysis reveals that no statistically significant change in the frequency of SSWs will occur over the 21st century, irrespective of the metric used for the identification of the event. Changes in other SSW characteristics – such as their duration, deceleration of the polar night jet, and the tropospheric forcing – are also assessed: again, we find no evidence of future changes over the 21st century.

Major sudden stratospheric warmings (SSWs) represent one of the most abrupt phenomena of the boreal wintertime stratospheric variability, and constitute the clearest example of coupling between the stratosphere and the troposphere. A good representation of SSWs in climate models is required to reduce their biases and uncertainties in future projections of stratospheric variability. The ability of models to reproduce these phenomena is usually assessed with just one reanalysis. However, the number of reanalyses has increased in the last decade and their own biases may affect the model evaluation. Here we compare the representation of the main aspects of SSWs across reanalyses. The examination of their main characteristics in the pre- and post-satellite periods reveals that reanalyses behave very similarly in both periods. However, discrepancies are larger in the pre-satellite period compared to afterwards, particularly for the NCEP-NCAR reanalysis. All datasets reproduce similarly the specific features of wavenumber-1 and wavenumber-2 SSWs. A good agreement among reanalyses is also found for triggering mechanisms, tropospheric precursors, and surface response. In particular, differences in blocking precursor activity of SSWs across reanalyses are much smaller than between blocking definitions.

Major mid-winter stratospheric sudden warmings (SSWs) are the largest instance of wintertime variability in the Arctic stratosphere. Because SSWs are able to cause significant surface weather anomalies on intra-seasonal timescales, several previous studies have focused on their potential future change, as might be induced by anthropogenic forcings. However, a wide range of results have been reported, from a future increase in the frequency of SSWs to an actual decrease. Several factors might explain these contradictory results, notably the use of different metrics for the identification of SSWs and the impact of large climatological biases in single-model studies. To bring some clarity, we here revisit the question of future SSW changes, using an identical set of metrics applied consistently across 12 different models participating in the Chemistry–Climate Model Initiative. Our analysis reveals that no statistically significant change in the frequency of SSWs will occur over the 21st century, irrespective of the metric used for the identification of the event. Changes in other SSW characteristics – such as their duration, deceleration of the polar night jet, and the tropospheric forcing – are also assessed: again, we find no evidence of future changes over the 21st century., Atmospheric Chemistry and Physics, 18 (15), ISSN:1680-7375, ISSN:1680-7367

Major mid-winter stratospheric sudden warmings (SSWs) are the largest instance of wintertime variability in the Arctic stratosphere. Because SSWs are able to cause significant surface weather anomalies on intra-seasonal timescales, several previous studies have focused on their potential future change, as might be induced by anthropogenic forcings. However, a wide range of results have been reported, from a future increase in the frequency of SSWs to an actual decrease. Several factors might explain these contradictory results, notably the use of different metrics for the identification of SSWs and the impact of large climatological biases in single-model studies. To bring some clarity, we here revisit the question of future SSW changes, using an identical set of metrics applied consistently across 12 different models participating in the Chemistry–Climate Model Initiative. Our analysis reveals that no statistically significant change in the frequency of SSWs will occur over the 21st century, irrespective of the metric used for the identification of the event. Changes in other SSW characteristics – such as their duration, deceleration of the polar night jet, and the tropospheric forcing – are also assessed: again, we find no evidence of future changes over the 21st century., Blanca Ayarzagüena was funded by the European Project 603557-STRATOCLIM under the FP7-ENV.2013.6.1-2 programme and “Ayudas para la contratación de personal postdoctoral en formación en docencia e investigación en departamentos de la Universidad Complutense de Madrid”. Blanca Ayarzagüena and Ulrike Langematz wish to acknowledge the Deutsche Forschungsgemeinschaft (DFG) within the research programme SHARP under the grant LA 1025/15-1. Lorenzo M. Polvani is grateful for the continued support of the US National Science Foundation. The work of Neal Butchart, Steven C. Hardiman, and Fiona M. O'Connor was supported by the Joint BEIS/Defra Met Office Hadley Centre Climate Programme (GA01101). Neal Butchart and Steven C. Hardiman were supported by the European Community within the StratoClim project (grant 603557). Olaf Morgenstern and Guang Zeng acknowledge the UK Met Office for use of the Met Office Unified Model (MetUM). This research was supported by the New Zealand Government's Strategic Science Investment Fund (SSIF) through the NIWA programme CACV. Olaf Morgenstern acknowledges funding by the New Zealand Royal Society Marsden Fund (grant 12-NIW-006) and by the Deep South National Science Challenge (http://www.deepsouthchallenge.co.nz, last access: 21 March 2018). The authors wish to acknowledge the contribution of New Zealand eScience Infrastructure (NeSI) high-performance computing (HPC) facilities to the results of this research. New Zealand's national facilities are provided by NeSI and funded jointly by NeSI's collaborator institutions and through the Ministry of Business, Innovation & Employment's Research Infrastructure programme (https://www.nesi.org.nz, last access: 21 March 2018). The EMAC simulations were performed at the German Climate Computing Centre (DKRZ) through support from the Bundesministerium für Bildung und Forschung (BMBF). DKRZ and its Scientific Steering Committee are gratefully acknowledged for providing the HPC and data archiving resources for the consortial project ESCiMo (Earth System Chemistry integrated Modelling). CCSRNIES's research was supported by the Environment Research and Technology Development Funds of the Ministry of the Environment (2-1303) and Environment Restoration and Conservation Agency (2-1709), Japan, and computations were performed on NEC-SX9/A(ECO) and NEC SX-ACE computers at the Center for Global Environmental Research, NIES. The authors wish to thank two anonymous referees for their helpful comments.

The European precipitation response to El Niño (EN) has been found to present interdecadal changes, with alternated periods of important or negligible EN impact in late winter. These periods are associated with opposite phases of multi-decadal sea surface temperature (SST) variability, which modifies the tropospheric background and EN teleconnections. In addition, other studies have shown how SST anomalies in the equatorial Pacific, and in particular, the location of the largest anomalous SST, modulate the stratospheric response to EN. Nevertheless, the role of the stratosphere on the stationarity of EN response has not been investigated in detail so far. Using reanalysis data, we present a comprehensive study of EN teleconnections to Europe including the role of the ocean background and the stratosphere in the stationarity of the signal. The results reveal multidecadal variability in the location of EN-related SST anomalies that determines different teleconnections. In periods with relevant precipitation signal over Europe, the EN SST pattern resembles Eastern Pacific EN and the stratospheric pathway plays a key role in transmitting the signal to Europe in February, together with two tropospheric wavetrains that transmit the signal in February and April. Conversely, the stratospheric pathway is not detected in periods with a weak EN impact on European precipitation, corresponding to EN-related SST anomalies primarily located over the central Pacific. SST mean state and its associated atmospheric background control the location of EN-related SST anomalies in different periods and modulate the establishment of the aforementioned stratospheric pathway of EN teleconnection to Europe too., BA was supported by the Natural Environment Research Council grant NE/M006123/1, the European Project 603557-STRATOCLIM and “Ayudas para la contratación de personal postdoctoral en formación en docencia e investigación en departamentos de la UCM”. JLP and BRF were funded by the European Project PREFACE. MI and NC acknowledge support from the European Project 603557-STRATOCLIM under program FP7-ENV.2013.6.1-2. NC was also supported in part by the Spanish Ministry of Economy and Competitiveness through the PALEOSTRAT (CGL2015-69699-R)