Amphibian species are declining at an alarming rate on a global scale in large part owing to an infectious disease caused by the chytridiomycete fungus, Batrachochytrium dendrobatidis . This disease of amphibians has recently emerged within Europe, but knowledge of its effects on amphibian assemblages remains poor. Importantly, little is known about the environmental envelope that is associated with chytridiomycosis in Europe and the potential for climate change to drive future disease dynamics. Here, we use long-term observations on amphibian population dynamics in the Peñalara Natural Park, Spain, to investigate the link between climate change and chytridiomycosis. Our analysis shows a significant association between change in local climatic variables and the occurrence of chytridiomycosis within this region. Specifically, we show that rising temperature is linked to the occurrence of chytrid-related disease, consistent with the chytrid-thermal-optimum hypothesis. We show that these local variables are driven by general circulation patterns, principally the North Atlantic Oscillation. Given that B. dendrobatidis is known to be broadly distributed across Europe, there is now an urgent need to assess the generality of our finding and determine whether climate-driven epidemics may be expected to impact on amphibian species across the wider region.

It is well known how mountains play a crucial role in the climate system and have very particular climate features compared to other regions. Sierra de Guadarrama is a part of the Iberian Peninsula Central System (Spain), a mountain range located in the center of an extensive plateau, dominated by a continental Mediterranean climate but under a strong Atlantic influence. This range provides fresh water to the different settlements in its vicinity, providing enough water resources to several millions of inhabitants, crop fields, industries and the city of Madrid, the capital of Spain. Nevertheless, there is no work studying the role of the synoptic scale in relation to the precipitation in this mountain range. To tackle this problem, this work calculates water vapour flux patterns (WVFPs) using total column water vapour flux as a predictor field due to the close relation between this parameter and the precipitation in mountainous areas. A clustering analysis on the first three principal components of the predictor field was performed and seven differentiated WVFPs were found using a cost function considering local precipitation data for optimum number of cluster determination. Then, an analysis is made for each component in terms of synoptic relation with other fields and well-known broader teleconnection patterns. Finally, an analysis in terms of their contribution to total precipitation, mean rain intensity and probability of precipitation is made. This work is expected to bring new light on the knowledge of precipitation climatology over this crucial and still not very well-known area, and it is a solid step for future precipitation modelling tools validation that combined with reliable measurements will allow to produce realistic precipitation assessments and forecasts in order to improve the hydrological management of this complex area.

A linear model of orographic precipitation is validated at Sierra de Guadarrama (Iberian Central System) using ERA‐Interim as input and a historical set of precipitation data. It is the first time that a linear precipitation model is tested in a semi‐arid region like this. The historical precipitation data come from three high‐quality observatories located at the south, north and top of the mountain range. Different timescales ranging from daily, monthly and annual precipitation are analysed. Phenomena not generally taken into account in linear models like a sub‐saturated air condition and topographic mesoscale flow blocking are included in the modelling. Model results show a good agreement with observations at annual and monthly scales. The model reproduces well the high inter‐annual variability and the annual cycle, including the pronounced summer drought. Bigger differences between observed and modelled precipitations are found for some winter months and for May. Winter overestimation is attributed to measurement undersampling during snowy conditions. The underestimation in May is likely related to thermally driven convective precipitation, which is not modelled. Results also show how orographic precipitation is an important contributor to total precipitation in this area. The high‐resolution precipitation fields obtained can be used in the future for precipitation assessment and other hydrological applications. Modelled time series can also be very helpful for completing and validating the precipitation observations for the winter months.

This work describes a mountain meteorological network that was in operation from 1999 to 2014 in a mountain range with elevations ranging from 1104 to 2428 m in Central Spain. Additionally, some technical details of the network are described, as well as variables measured and some meta information presented, which is expected to be useful for future users of the observational database. A strong emphasis is made on showing the observational methods and protocols evolution, as it will help researchers to understand the sources of errors, data gaps and the final stage of the network. This paper summarizes mostly the common sources of errors when designing and operating a small network of this kind, so it can be useful for individual researchers and small size groups that undertake a similar task on their own. Strengths and weaknesses of some of the variables measured are discussed and some basic calculations are made in order to show the otential of the database and to anticipate future deeper climatological analyses over the area. Finally, the configuration of an automatic mountain meteorology station is suggested as a result of the lessons learned and the the common state of the art automatic measuring techniques