ALBERT

Description: ABSTRACT E-OBS(European Observations) is a gridded climate data set which contains maximum temperature, minimum temperature, and precipitation on a daily time step. The data can be as fine as 0.25° in resolution and extends over the entire European continent and parts of Africa and Asia. However, for studying regional or local climatic effects, a finer resolution would be more appropriate. A continental data set with resolution would allow research that is large in scale and still locally relevant. Until now, a climate data set with high spatial and temporal resolution has not existed for Europe. To fulfil this need, we produced a downscaled version of E-OBS, applying the delta method, which uses WorldClim climate surfaces to obtain a 0.008 ° (about 1 × 1 km) resolution climate data set on a daily time step covering the European Union. The new downscaled data set includes minimum and maximum temperature and precipitation for the years 1951–2012. It is analysed against weather station data from six countries: Norway, Germany, France, Italy, Austria, and Spain. Our analysis of the downscaled data set shows a reduction in the mean bias error of 3 °C for mean daily minimum temperature and of 4 °C for mean daily maximum temperature. Daily precipitation improved by 0.15 mm on average for all weather stations in the validation. The entire data set is freely and publically available at ftp://palantir.boku.ac.at/Public/ClimateData .

Description: ABSTRACT This work analysed the changes in air temperature in 25 meteorological stations in the Altiplano and the surrounding Andean slopes of Bolivia and Peru, and their relationship with El Niño-Southern Oscillation (SO) and the Pacific Decadal Oscillation (PDO). The analysis focused on annual, warm season (DJF) and cold season (JJA) maximum and minimum temperatures. All analyses were undertaken during 1965–2012, but some analyses were also from 1945 and 1955 when data were available. Principal component analysis was applied to the annual and seasonal series to identify spatial differences of changes in maximum and minimum air temperature. There was an overall increase of temperatures since the mid-20th century. The most intense and spatially coherent warming was observed for annual and warm season maximum temperature, with warming rates from 0.15 to 0.25 °C decade −1 . Changes in the cold season maximum temperature were more heterogeneous, and statistically significant trends were mostly in the Bolivian Altiplano. Minimum temperatures increased, but there was higher spatial variability and lower rates of warming. Maximum temperature was negatively correlated with the Southern Oscillation index (SO) in the warm season, and positively correlated with the SO in the cold season; there were less statistically significant correlations with the PDO, that exhibited inverse sign than those for SO. The strongest correlations were in the region near Lake Titicaca. The negative correlation of minimum temperatures with SO and the positive correlation of minimum temperatures with PDO were lower than the observed for maximum temperature. The changes in temperature and correlations with SO and PDO were highly dependent on the selected period, with stronger trends in the last 30–40 years. This suggests reinforcement of warming rates that cannot be only explained by SO and PDO variability.

Description: ABSTRACT Cape Verde is a semi-arid country conformed by a group of islands located off the west coast of Africa, with highly variable rainfall that appears during a single rainy season. Santiago Island, the biggest of the country, is characterized for abrupt changes of relief within small distances. The influence of geographic location and topographic parameters, such as slope gradient, exposition and elevation on the variability of rainfall in Santiago Island was studied using monthly rainfall data of 30 seasons (1981 to 2010), with daily rainfall data for 14 seasons (1997 to 2010). The number of rainfall days and the percentage of maximum daily rainfall within the monthly and seasonal totals were evaluated. Few rainy days can control the monthly and seasonal rainfall patterns of Santiago Island. Multivariate linear regressions among daily, monthly and seasonal rainfall and elevation, slope gradient, aspect, and geographic east and west coordinates as predictors were carried out. Elevation explains most of the variance in the rainfall. The coefficients of determination show an inverse relationship with the rainfall depth: moderate rainfall totals (120–150 mm monthly, 250–300 mm seasonal) produced the best correlations for seasonal and monthly rainfall, while very low (〈50 mm for monthly, 〈200 mm for seasonal) and very high amounts (〉250 mm for monthly, 〉350 mm for seasonal) resulted in poor correlations. Long-term mean rainfall was interpolated using ordinary kriging and kriging with external drift. In Santiago Island, high and more extreme rainfall events are less influenced by elevation, while low and medium rainfall events are significantly influenced by orography, with most of the rainfall appearing on high elevations. Copyright © 2013 Royal Meteorological Society

Description: Abstract The presence of a seasonal snowpack determines the hydrology, geomorphology and ecology of wide parts of the Iberian Peninsula, with strong implications for the economy, transport and risk management. Thus, reliable information on snow is necessary from a scientific and operational point of view. This is the case of the Iberian Peninsula where, lack of observation has impeded proper analysis of snowpack duration, magnitude and interannual variability. In this study we present the first snow climatology of the entire Iberian Peninsula. The scarcity of in situ observations has been overcome, using a newly developed remote sensing snow database from MODIS satellite sensors for the period 2000 ‐ 2014 and a physically based snow model (Factorial Snow Model‐ FSM), driven by a regional atmospheric model (Weather Research and Forecast model‐ WRF) over the Iberian Peninsula for the period 1980 ‐ 2014. The snowpack of the main mountain areas (Pyrenees, Cantabrian, Central, Iberian range and Sierra Nevada) are described, estimated from the generated databases. The information has been processed using a k‐means cluster algorithm, looking for similarities in snow indices at different elevation bands. Results show four different types of snowpack in terms of depth, duration and interannual variability, lying over different elevation bands in the different ranges, proving the variability of the snowpack over Iberia. Analyses reveal areas characterised by ephemeral snowpacks, while in some sectors snowpack lasts, on average, 198 days per year with 3.02 meters of peak snow depth. The coefficient of variation of interannual peak snow depth oscillated between 35.2% and 162.4%. All the analysed indices show that at common elevations the Cantabrian range and the Pyrenees host the deepest and longest lasting snowpacks, followed by the Central and Iberian ranges. The Sierra Nevada exhibits the shortest, shallowest snowpack and more year‐to‐year variability. This article is protected by copyright. All rights reserved.

Description: This paper gives the complete details of the protocols applied for developing a spatially and temporarily high-resolution dataset of temperature for northeastern Spain. Our methodologies used data from a large number of observatories (1583) spanning some portions of the period between 1900 and 2006. The raw dataset was first tested for internal and external consistency to check data quality. To improve data completeness, a linear regression model was then utilized to infill gaps in the daily temperature series using the best correlated data from nearby sites. Discontinuities in the reconstructed series were determined by combining the results of three homogeneity-relative tests: the Standard Normal Homogeneity Test (SNHT), the Eastrerling and Peterson two-phased regression method and the Vincent test. To assess the possible impact of data homogenisation on trends and statistical properties of the final series, a set of tests (e.g. semivariance models and L-moment statistics) was applied to the series before and after correction. Semivariance models suggest a significant improvement in the spatial dependence of the corrected dataset on both seasonal and annual timescales. Also, L-moments gave no evidence of significant changes in the probability distribution of daily temperature series after correction. Taken together, the newly compiled dataset seems to be more robust and reveals more coherent spatial and temporal patterns of temperature compared with the original dataset. From the temporal and spatial perspectives, the new dataset comprises the most complete register of temperature in northeast Spain (1900–2006), with a reasonably spatial coverage. Accordingly, this database can provide a more reliable base for studying temperature changes and variability in the region. This dataset can also be of particular relevance to a number of meteorological, ecological, hydrological and agricultural applications on local, regional and continental scales. Copyright © 2011 Royal Meteorological Society

Description: ABSTRACT In this study we analyze the observed trends for the period 1950–2006 in a number of climate indices related to the occurrence of winter warm events in the Ebro basin, northeast Iberian Peninsula. Climatic simulations using 12 regional climate models (RCMs) from the ENSEMBLES database enable calculation of the multi-model means for the projected evolution of these climatic indices for the time periods 2021–2050 and 2051–2080. The results based on observations indicate a significant increase in occurrence of warm and very warm days and nights, melting events at 2000 m a.s.l. and the duration of warm spells across most of the study area. The number of warm spells comprising at least five consecutive warm days or nights also tends to increase, although the trend is not statistically significant for many of the observatories involved in the study. The RCMs project that the trends observed during the observation period will continue, and that the occurrence of warm day and night events and spells are very likely to increase during this century. In some cases the occurrence of warm events is projected to double during the period 2021–2050, and continue increasing for the period 2051–2080. For both the observed and projected periods, most of the indices show a greater increase in the occurrence of these events in the mountain areas of the basin (the Pyrenees and the Iberian mountains). Copyright © 2013 Royal Meteorological Society

Description: Assessing the risk, the severity and the likely evolution of droughts are key tasks for improving preparedness of regions prone to drought conditions, and mitigation of drought consequences. The access to real-time and high-quality climatic information is essential for this purpose. Different climatic databases are being developed and made available on real time by climatic research institutions, but their capability for quantifying droughts characteristics including severity, or spatio-temporal variability, is uncertain given their low spatial resolution. In this study, we assessed the capability of three databases with contrasted spatial resolution for measuring spatial and temporal variability of drought occurrence. The standardized precipitation index, calculated for each database, showed that the low resolution datasets allow an acceptable measurement of the magnitude, intensity and duration of droughts, while failing mostly in detecting the spatial patterns of the specific drought episodes. Moreover, the capability of the datasets for assessing the impacts of droughts on surface hydrology and tree growth was examined. Results confirmed the usefulness of the drought index for assessing drought impacts on water resources and forest ecosystems even when low resolution databases are used. Copyright © 2012 Royal Meteorological Society

Description: This paper gives the complete details of the protocols applied for developing a spatially and temporarily high-resolution dataset of temperature for northeastern Spain. Our methodologies used data from a large number of observatories (1583) spanning some portions of the period between 1900 and 2006. The raw dataset was first tested for internal and external consistency to check data quality. To improve data completeness, a linear regression model was then utilized to infill gaps in the daily temperature series using the best correlated data from nearby sites. Discontinuities in the reconstructed series were determined by combining the results of three homogeneity-relative tests: the Standard Normal Homogeneity Test (SNHT), the Eastrerling and Peterson two-phased regression method and the Vincent test. To assess the possible impact of data homogenisation on trends and statistical properties of the final series, a set of tests (e.g. semivariance models and L-moment statistics) was applied to the series before and after correction. Semivariance models suggest a significant improvement in the spatial dependence of the corrected dataset on both seasonal and annual timescales. Also, L-moments gave no evidence of significant changes in the probability distribution of daily temperature series after correction. Taken together, the newly compiled dataset seems to be more robust and reveals more coherent spatial and temporal patterns of temperature compared with the original dataset. From the temporal and spatial perspectives, the new dataset comprises the most complete register of temperature in northeast Spain (1900–2006), with a reasonably spatial coverage. Accordingly, this database can provide a more reliable base for studying temperature changes and variability in the region. This dataset can also be of particular relevance to a number of meteorological, ecological, hydrological and agricultural applications on local, regional and continental scales. Copyright © 2011 Royal Meteorological Society

Description: This work is focused on the characterization and parameterisation of the downward atmospheric irradiance (LW) for clear and cloudy skies. LW is a component of the surface radiation budget that is present throughout the day. Unlike solar irradiance, LW is not measured routinely in extended networks, so it must be estimated indirectly. We evaluated five parameterisations for estimating LW under clear skies. After some consideration regarding the local fitting of the parameterisations, we analysed their different behaviour during day and night and propose a correction model for this effect. We use measurements registered at Tabernas (Spain) from 2001 to 2003. For the locally adjusted parameterisations the root mean square deviation (RMSD) and the mean bias deviation (MBD) are smaller than 5.7 and 0.6%, respectively. The combination of the more complex correction parameterisation of the day/night differences with the locally adjusted formula of Brutsaert and the original formula of Berdalh and Martin leads to estimations with RMSD below 3.1%. Using data registered at Palaiseau (France) the proposed parameterisations yields MBD close to 0% and RMSD below 3.2%. Cloudy conditions were analysed and two different approaches were used to estimate the cloud effect. Both approaches determine all sky LW using a clear-sky formulae and a cloud modification factor, computed with the solar global irradiance on a horizontal surface. The results show that LW can be estimated under all-sky conditions during the daytime with a RMSD of 5.8 and 6.2%, and a MBD of 1.6 and − 2.2% for the Crawford and Duchon scheme and the parameterisation in k t , respectively, at Tabernas. The application of the same parameterisations to Palaiseau yields RMSD of 6.7 and 7.7%, and MBD of − 2.5 and 0.7%. Copyright © 2011 Royal Meteorological Society

Description: ABSTRACT In this study, the spatio-temporal variability and trends of droughts across Bolivia between 1955 and 2012 were investigated using two climate drought indices: the Standardized Precipitation Index (SPI), which is based on precipitation data, and the Standardized Precipitation Evapotranspiration Index (SPEI), which is based on the difference between the precipitation and the reference evapotranspiration (ETo). We found that the average drought conditions across the country showed a temporal behaviour mainly characterized by decadal variations. The spatial pattern of drought evolution showed marked differences between the Amazonian region and the Bolivian Altiplano. Both regions showed different drought periods, a lower frequency of drought variability in the Amazon region and trends towards drier conditions in the Altiplano, mainly due to a higher atmospheric water demand as a consequence of increased ETo. We also showed that inclusion of ETo, obtained from maximum and minimum temperature records, increased the spatial heterogeneity of the drought evolution in relation to the evolution observed when only precipitation droughts were considered. The SPEI, the calculation of which includes precipitation and ETo, indicated intensification in drought severity in the last years analysed relative to the pattern found when precipitation droughts alone were considered, and also indicated an increase in the magnitude and duration of drought events. The potential for increasing drought conditions under various climate change scenarios is discussed.