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27 páginas, 15 figuras, 6 tablas.-- El documento se encuentra en su versión post-print. ; This paper analyses the spatial and temporal variability of winter droughts in a semi-arid geographic gradient in Northeast Spain, from the Pyrenees in the north to the Mediterranean coastland in the south. Droughts that occurred between 1952 and 1999 were analysed by means of the Standardised Precipitation Index (SPI). The influence of the weather-type frequency and of the general North Atlantic atmospheric circulation patterns was analysed. The results indicate that winter droughts show an important spatial variability in the study area, differentiating three well-defined patterns. These correspond to the Pyrenees, the centre of the Ebro Valley, and the Mediterranean coastland. General negative trends in winter SPI have been found, which are indicative of the increase in winter drought conditions in the study area. Nevertheless, important spatial differences have also been recorded. Dominant north–south gradients in the influence of weather types are shown. Moreover, the negative trends in winter-SPI values agree with the negative trend in the frequency of the weather types prone to cause precipitation, such as the C, SW and W weather types and the increase in the frequency of A weather types. Nevertheless, in the Mediterranean coastland, the positive trend in SPI values agrees with the increase in the frequency of weather types of the east (E, SE), which are prone to cause precipitation in this area. Interannual variations in the frequency of the different weather types have been highly determined by different general atmospheric circulation patterns, mainly the North Atlantic Oscillation (NAO). Nevertheless, the correlation between the time series of weather-type frequency and the winter SPI is higher than that found between the SPI and the NAO. Thus, although the interannual NAO variability explains a high percentage of the interannual differences in the frequency of different weather types, it is not sufficient to explain the spatial and temporal variability of droughts, which respond better to atmospheric variability at more detailed (synoptic) spatial scales. ; This work has been supported by the projects: 'Caracterización espacio-temporal de las sequías en el valle medio del Ebro e identificación de sus impactos' (BSO2002-02743), 'Variabilidad climática y dinámica forestal en ecosistemas de ecotono' (REN2003-07453), Procesos hidrológicos y erosivos en cuencas pirenaicas en relación a cambios de usos de suelo y variabilidad climática (PIRIHEROS, REN2003-08678/HID) 'Caracterización y modelización de procesos hidrológicos en cuencas aforadas para predicción en cuencas no aforadas' (CANOA, CGL 2004-04919-c02-01), all funded by the Spanish Commission of Science and Technology (CICYT) and FEDER, and 'Programa de grupos de investigación consolidados' (grupo Clima, Cambio Global y Sistemas Naturales, BOA 48 of 20-04-2005), financed by the Aragón Government. We want to thank to the National Institute of Meteorology (INM) for providing the data used in this work. Research of the second author was supported by postdoctoral fellowships by the Ministerio de Educación, Cultura y Deporte (Spain). ; Peer reviewed

The definitive version is available at: http://www.agu.org/journals/jgr ; We used a novel method that combined probabilistic analysis and spatial modeling assisted by GIS to analyze the risk of extreme precipitation in northeast Spain related to three atmospheric circulation configurations: the North Atlantic Oscillation (NAO), the Mediterranean Oscillation, and the Western Mediterranean Oscillation (WeMO). The analysis was performed at an event-based scale using data obtained from daily atmospheric circulation indices. The maximum intensity and total precipitation magnitude recorded during positive and negative circulation events were obtained from the daily records of 174 observatories between 1950 and 2006. The series of both maximum intensity and magnitude for positive and negative phases of the three atmospheric circulation indices follow a generalized Pareto (GP) distribution. A regression-based interpolation procedure was used to generate distributed maps of GP parameters, enabling us to determine the probability of the magnitude and maximum intensity of precipitation and the quantile precipitation for any return period associated with the positive and negative phases of the three atmospheric circulation patterns. A high spatial variability in precipitation risk was found, depending on the positive/negative phases of the three atmospheric circulation patterns. Different phases of the circulation indices show contrasting effects on the two analyzed parameters. Thus the most extreme daily precipitation during winter months is expected for negative WeMO events, representing a markedly different result from those obtained for other events. In contrast, negative NAO events record the most extreme precipitation magnitude risk per event, although this is mainly restricted to mountainous areas. ; This work was supported by projects financed by the Spanish Commission of Science and Technology (CGL2005–04508/BOS and CGL2008–01189/BTE), the 7th framework program of the European Commission (projects ACQWA (FP7-ENV-2007-1-212250) and EUROGEOSS (FP7-ENV-2008-1-226487)), and the "Programa de grupos de investigación consolidados" financed by the Aragón Government. ; Peer reviewed

The value of historic observational weather data for reconstructing long-term climate patterns and the detailed analysis of extreme weather events has long been recognized (Le Roy Ladurie, 1972; Lamb, 1977). In some regions however, observational data has not been kept regularly over time, or its preservation and archiving has not been considered a priority by governmental agencies. This has been a particular problem in Southeast Asia where there has been no systematic country-by-country method of keeping or preserving such data, the keeping of data only reaches back a few decades, or where instability has threatened the survival of historic records. As a result, past observational data are fragmentary, scattered, or even absent altogether. The further we go back in time, the more obvious the gaps. Observational data can be complimented however by historical documentary or proxy records of extreme events such as floods, droughts and other climatic anomalies. This review article highlights recent initiatives in sourcing, recovering, and preserving historical weather data and the potential for integrating the same with proxy (and other) records. In so doing, it focuses on regional initiatives for data research and recovery – particularly the work of the international Atmospheric Circulation Reconstructions over the Earth's (ACRE) Southeast Asian regional arm (ACRE SEA) – and the latter's role in bringing together disparate, but interrelated, projects working within this region. The overarching goal of the ACRE SEA initiative is to connect regional efforts and to build capacity within Southeast Asian institutions, agencies and National Meteorological and Hydrological Services (NMHS) to improve and extend historical instrumental, documentary and proxy databases of Southeast Asian hydroclimate, in order to contribute to the generation of high-quality, high-resolution historical hydroclimatic reconstructions (reanalyses) and, to build linkages with humanities researchers working on issues in environmental and climatic history in the region. Thus, this article also highlights the inherent value of multi/cross/inter-disciplinary projects in providing better syntheses and understanding of human and environmental/climatic variability and change.

Quantifying signals and uncertainties in climate models is essential for the detection, attribution, prediction and projection of climate change1,2,3. Although inter-model agreement is high for large-scale temperature signals, dynamical changes in atmospheric circulation are very uncertain4. This leads to low confidence in regional projections, especially for precipitation, over the coming decades5,6. The chaotic nature of the climate system7,8,9 may also mean that signal uncertainties are largely irreducible. However, climate projections are difficult to verify until further observations become available. Here we assess retrospective climate model predictions of the past six decades and show that decadal variations in North Atlantic winter climate are highly predictable, despite a lack of agreement between individual model simulations and the poor predictive ability of raw model outputs. Crucially, current models underestimate the predictable signal (the predictable fraction of the total variability) of the North Atlantic Oscillation (the leading mode of variability in North Atlantic atmospheric circulation) by an order of magnitude. Consequently, compared to perfect models, 100 times as many ensemble members are needed in current models to extract this signal, and its effects on the climate are underestimated relative to other factors. To address these limitations, we implement a two-stage post-processing technique. We first adjust the variance of the ensemble-mean North Atlantic Oscillation forecast to match the observed variance of the predictable signal. We then select and use only the ensemble members with a North Atlantic Oscillation sufficiently close to the variance-adjusted ensemble-mean forecast North Atlantic Oscillation. This approach greatly improves decadal predictions of winter climate for Europe and eastern North America. Predictions of Atlantic multidecadal variability are also improved, suggesting that the North Atlantic Oscillation is not driven solely by Atlantic multidecadal variability. Our results highlight the need to understand why the signal-to-noise ratio is too small in current climate models10, and the extent to which correcting this model error would reduce uncertainties in regional climate change projections on timescales beyond a decade. ; DMS, AAS, NJD, LH and RE were supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra and by the European Commission Horizon 2020 EUCP project (GA 776613). FJDR, LPC, SW and RB also acknowledge the support from the EUCP project (GA 776613) and from the Ministerio de Econom´ıa y Competitividad (MINECO) as part of the CLINSA project (Grant No. CGL2017-85791-R). SW received funding from the innovation programme under the Marie Sk´lodowska-Curie grant agreement H2020-MSCA-COFUND-2016-754433 and PO from the Ramon y Cajal senior tenure programme of MINECO. The EC-Earth simulations were performed on Marenostrum 4 (hosted by the Barcelona Supercomputing Center, Spain) using Auto-Submit through computing hours provided by PRACE.WAM, HP, KMand KP were supported by the German FederalMinistry for Education and Research (BMBF) project MiKlip (grant 01LP1519A). NK, IB, FC and YW were supported by the Norwegian Research Council projects SFE (grant 270733) the Nordic Center of excellent ARCPATH (grant 76654) and the Trond Mohn Foundation, under the project number : BFS2018TMT01 and received grants for computer time from the Norwegian Program for supercomputing (NOTUR2, NN9039K) and storage grants (NORSTORE, NS9039K). JM, LFB and DS are supported by Blue-Action (European Union Horizon 2020 research and innovation program, Grant Number: 727852) and EUCP (European Union Horizon 2020 research and innovation programme under grant agreement no 776613) projects. The National Center for Atmospheric Research (NCAR) is a major facility sponsored by the US National Science Foundation (NSF) under Cooperative Agreement No. 1852977. NCAR contribution was partially supported by the National Oceanic and Atmospheric Administration (NOAA) Climate Program Office under Climate Variability and Predictability Program Grant NA13OAR4310138 and by the US NSF Collaborative Research EaSM2 Grant OCE-1243015. ; Peer Reviewed ; Postprint (author's final draft)

Abstract The value of historic observational weather data for reconstructing long-term climate patterns and the detailed analysis of extreme weather events has long been recognized (Le Roy Ladurie, 1972; Lamb, 1977). In some regions however, observational data has not been kept regularly over time, or its preservation and archiving has not been considered a priority by governmental agencies. This has been a particular problem in Southeast Asia where there has been no systematic country-by-country method of keeping or preserving such data, the keeping of data only reaches back a few decades, or where instability has threatened the survival of historic records. As a result, past observational data are fragmentary, scattered, or even absent altogether. The further we go back in time, the more obvious the gaps. Observational data can be complimented however by historical documentary or proxy records of extreme events such as floods, droughts and other climatic anomalies. This review article highlights recent initiatives in sourcing, recovering, and preserving historical weather data and the potential for integrating the same with proxy (and other) records. In so doing, it focuses on regional initiatives for data research and recovery – particularly the work of the international Atmospheric Circulation Reconstructions over the Earth's (ACRE) Southeast Asian regional arm (ACRE SEA) – and the latter's role in bringing together disparate, but interrelated, projects working within this region. The overarching goal of the ACRE SEA initiative is to connect regional efforts and to build capacity within Southeast Asian institutions, agencies and National Meteorological and Hydrological Services (NMHS) to improve and extend historical instrumental, documentary and proxy databases of Southeast Asian hydroclimate, in order to contribute to the generation of high-quality, high-resolution historical hydroclimatic reconstructions (reanalyses) and, to build linkages with humanities researchers working on issues in environmental and climatic history in the region. Thus, this article also highlights the inherent value of multi/cross/inter-disciplinary projects in providing better syntheses and understanding of human and environmental/climatic variability and change.

The value of historic observational weather data for reconstructing long-term climate patterns and the detailed analysis of extreme weather events has long been recognized (Le Roy Ladurie, 1972; Lamb, 1977). In some regions however, observational data has not been kept regularly over time, or its preservation and archiving has not been considered a priority by governmental agencies. This has been a particular problem in Southeast Asia where there has been no systematic country-by-country method of keeping or preserving such data, the keeping of data only reaches back a few decades, or where instability has threatened the survival of historic records. As a result, past observational data are fragmentary, scattered, or even absent altogether. The further we go back in time, the more obvious the gaps. Observational data can be complimented however by historical documentary or proxy records of extreme events such as floods, droughts and other climatic anomalies. This review article highlights recent initiatives in sourcing, recovering, and preserving historical weather data and the potential for integrating the same with proxy (and other) records. In so doing, it focuses on regional initiatives for data research and recovery – particularly the work of the international Atmospheric Circulation Reconstructions over the Earth's (ACRE) Southeast Asian regional arm (ACRE SEA) – and the latter's role in bringing together disparate, but interrelated, projects working within this region. The overarching goal of the ACRE SEA initiative is to connect regional efforts and to build capacity within Southeast Asian institutions, agencies and National Meteorological and Hydrological Services (NMHS) to improve and extend historical instrumental, documentary and proxy databases of Southeast Asian hydroclimate, in order to contribute to the generation of high-quality, high-resolution historical hydroclimatic reconstructions (reanalyses) and, to build linkages with humanities researchers working on issues in environmental and climatic history in the region. Thus, this article also highlights the inherent value of multi/cross/inter-disciplinary projects in providing better syntheses and understanding of human and environmental/climatic variability and change.

Abstract. The Dolomite Alps of northeastern Italy experience debris flows with great frequency during the summer months. An ample supply of unconsolidated material on steep slopes and a summer season climate regime characterized by recurrent thunderstorms combine to produce an abundance of these destructive hydro-geologic events. In the past, debris flow events have been studied primarily in the context of their geologic and geomorphic characteristics. The atmospheric contribution to these mass-wasting events has been limited to recording rainfall and developing intensity thresholds for debris mobilization. This study aims to expand the examination of atmospheric processes that preceded both locally intense convective rainfall (LICR) and debris flows in the Dolomite region. 500 hPa pressure level plots of geopotential heights were constructed for a period of 3 days prior to debris flow events to gain insight into the synoptic-scale processes which provide an environment conducive to LICR in the Dolomites. Cloud-to-ground (CG) lightning flash data recorded at the meso-scale were incorporated to assess the convective environment proximal to debris flow source regions. Twelve events were analyzed and from this analysis three common synoptic-scale circulation patterns were identified. Evaluation of CG flashes at smaller spatial and temporal scales illustrated that convective processes vary in their production of CF flashes (total number) and the spatial distribution of flashes can also be quite different between events over longer periods. During the 60 min interval immediately preceding debris flow a majority of cases exhibited spatial and temporal colocation of LICR and CG flashes. Also a number of CG flash parameters were found to be significantly correlated to rainfall intensity prior to debris flow initiation.

A Review of the Literature -- Data and Methods -- Variability in Atmospheric Circulation in the Arctic between 1939 and 1990 -- Variability of Air Temperature -- Variability of Atmospheric Precipitation -- Scenarios of Thermal-Precipitation Conditions in a Warmer World -- Conclusions -- Variability of Air Temperature and Atmospheric Precipitation in the Arctic: An Update to 2000.

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Surveys in Geophysics 38 (2017): 1529–1568, doi:10.1007/s10712-017-9428-0. ; Trade-wind cumuli constitute the cloud type with the highest frequency of occurrence on Earth, and it has been shown that their sensitivity to changing environmental conditions will critically influence the magnitude and pace of future global warming. Research over the last decade has pointed out the importance of the interplay between clouds, convection and circulation in controling this sensitivity. Numerical models represent this interplay in diverse ways, which translates into different responses of trade-cumuli to climate perturbations. Climate models predict that the area covered by shallow cumuli at cloud base is very sensitive to changes in environmental conditions, while process models suggest the opposite. To understand and resolve this contradiction, we propose to organize a field campaign aimed at quantifying the physical properties of trade-cumuli (e.g., cloud fraction and water content) as a function of the large-scale environment. Beyond a better understanding of clouds-circulation coupling processes, the campaign will provide a reference data set that may be used as a benchmark for advancing the modelling and the satellite remote sensing of clouds and circulation. It will also be an opportunity for complementary investigations such as evaluating model convective parameterizations or studying the role of ocean mesoscale eddies in air–sea interactions and convective organization. ; The EUREC4A project is supported by the European Research Council (ERC), under the European Union's Horizon 2020 research and innovation programme (Grant Agreement No. 694768), by the Max Planck Society and by DFG (Deutsche Forschungsgemeinschaft, German Research Foundation) Priority Program SPP 1294.

In the paper dynamical-stochastically method of the non-convective cloudiness parameterization in the general circulation model is formulated. This algorithms is evaluated on the basis of general circulation model with given see surface temperature of oceans. The results of calculations were compared with observational data and the results simulations with sophisticated couple GCM full filled in frame of CMIP5 program. These results showed the perspectives of suggested dynamical-stochastically approach.

Abstract. This study investigates the atmospheric pattern circulations associated with heavy rainfall (HR) days in Calabria, southern Italy, and contributes to the understanding of the dynamical mechanisms that produce those events. Heavy rainfall days are extracted from the raingauge database of the "Protezione Civile Regionale", which has more than a hundred pluviometric stations for the period 1999–2007 (eight years). To study the synoptic atmospheric circulations associated with HR we use the Regional Atmospheric Modeling System (RAMS) gridded data field of 925 hPa and 500 hPa geopotential height. First the number of variables is reduced by principal component analysis (PCA), then a cluster analysis (CA) is applied on those new atmospheric variables and eleven atmospheric patterns are obtained. Clear associations emerged between each of the circulation types and rainfall patterns over Calabria for HR days. These associations can be explained by the interaction between the complex orography of the region, the sea and the synoptic scale flow.

This paper presents a classification of the atmospheric circulations producing extreme precipitation events in Bulgaria. Heavy precipitation data set from the National Institute of Meteorology and Hydrology, Bulgaria, atmospheric fields of geopotential height at 1000 hPa, at 500 hPa and temperature at 850 hPa of the ECMWF operational analysis are used to determine the atmospheric patterns (AP). Other atmospheric fields such as geopotential height at 850 hPa, at 700 hPa and relative humidity at 700 hPa are also depicted to analyze the AP. Two statistical methods are used to obtain the AP. Principal Component Analysis (PCA) was applied to reduce the number of variables. Then, Cluster Analysis (CA) was performed and four main AP were obtained. For two AP, heavy precipitation is associated with a low-level cyclone. They can occur in all seasons. For the cold season (October to March), the trajectories of the cyclones are represented. Another pattern, which occurs mainly in the warm season (April to September), depicts an upperlevel cyclonic disturbance associated with heavy precipitation. The last AP represents a weak cyclonic circulation. Finally, a more detailed nine-cluster classification has been also obtained by adding some regional and seasonal features of the heavy precipitation events. ; This research was supported by the Ministry of Environment of the Government of the Kingdom of Spain.