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Statistical downscaling of climate projections is an active field of research and numerous intercomparison exercises of different techniques exist. Most evaluation studies make use of perfect predictors from a reanalysis, but neglect the analysis of how imperfect predictors from global climate models (GCMs) affect statistical downscaling. In this paper we evaluate and intercompare five statistical downscaling methods: (a) Analog, (b) Regression, (c) Artificial Neural Networks, (d) Support Vector Machines and (e) Kernel Ridge Regression, over a large ensemble of 18 GCMs participants in the CMIP5 project. These methods have been used to downscale maximum/minimum daily temperatures and daily accumulated precipitation on a high‐resolution observational grid (0.05°) over mainland Spain and the Balearic Islands. Our analysis focuses on the marginal aspects (mean values and tails) of the distributions by season. Results when driven by reanalysis and by GCMs have been compared in order to analyse the sensitivity of statistical downscaling methods to the use of imperfect predictors. Both for temperature and for precipitation all methods achieve, as expected, better results when applied over reanalysis, although no method displays a clearly higher sensitivity to the use of imperfect predictors from GCMs. We have found the existence of outlier GCMs, showing significantly higher errors than the rest of the ensemble. And we have quantified errors over GCMs, so this experiment provides a more precise idea of the reliability and accuracy of the overall performance (i.e., simulations by GCMs plus statistical downscaling) than the perfect predictor experiment and reveals an important source of uncertainty coming from GCMs even in a historical period. [ABSTRACT FROM AUTHOR]

The Spanish Meteorological Agency (AEMET) is responsible for the elaboration of downscaled climate projections over Spain to feed the Second National Plan of Adaptation to Climate Change (PNACC‐2) and this is the last of three papers aimed to evaluate and intercompare five empirical/statistical downscaling (ESD) methods developed at AEMET: (a) Analog, (b) Regression, (c) Artificial Neural Networks, (d) Support Vector Machines and (e) Kernel Ridge Regression, in order to decide which methods and under what configurations are more suitable for that purpose. Following the framework established by the EU COST Action VALUE, in this experiment we test the transferability of these methods to future climate conditions with the use of regional climate models (RCMs) as pseudo observations. We evaluate the marginal aspects of the distributions of daily maximum/minimum temperatures and daily accumulated precipitation, over mainland Spain and the Balearic Islands, analysed by season. For maximum/minimum temperatures all methods display certain transferability issues, being remarkable for Support Vector Machines and Kernel Ridge Regression. For precipitation all methods appear to suffer from transferability difficulties as well, although conclusions are not as clear as for temperature, probably due to the fact that precipitation does not present such a marked signal of change. This study has revealed how an analysis over a historical period is not enough to fully evaluate ESD methods, so we propose that some type of analysis of transferability should be added in a standard procedure of a complete evaluation. [ABSTRACT FROM AUTHOR]

This paper proposes an interpolation model for monthly rainfall in large areas of complex orography. It has been implemented in the Iberian Peninsula (continental territories of Spain and Portugal), Balearic and Canary Islands covering a territory of almost 600.000 km2. To do this a data set that comprises a total number of 11,822 monthly precipitation series has been created (11,042 provided by the Spanish Meteorological Agency and 780 provided by the National Water Resources Information System of the Portuguese Water Institute). The data set covers the period from October 1940 until September 2005. The interpolation model has been based on the assumption of two different components on monthly precipitation. The first component reflects local and seasonal characteristics and 24 different mean monthly precipitation maps (12) and SDs maps (12) compose it. It considers the varying influence of physiographic variables such as altitude and orientation. The second precipitation component reflects the synoptic pattern that dominated each month of the series and it is composed by series of anomalies of monthly precipitation (780). Anomalies have been interpolated by means of ordinary kriging once local spatial continuity was assumed. Gridded maps of each variable have been developed at 200 m resolution following a hybrid methodology that implements two different interpolation techniques. The first technique applies a regression analysis to derive maps depending on altitude and orientation; the second one is a weighting technique to consider the non‐linearity of the precipitation/altitude dependence. Cross validation has been applied to estimate the goodness of both techniques. Results show an average annual precipitation of 655 mm/year. Although this figure is only 4% less than the estimate of MAGRAMA (2004), regional and local differences are highlighted when the spatial distribution is considered. The model constitutes a comprehensive implementation considering the availability of historical records and the need of avoiding slow calculations in large territories. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper analyses the radiometric properties of aerosol column over Western Spain. It is based on 7-year data series of aerosol parameters at the AERONET Cáceres station (Spain) as measured by CIMEL sun-photometers. The study period extends along almost 7 years: from July 2005 to June 2012. The paper aims at analysing the temporal evolution, mean values and spectral dependence of some fundamental aerosol parameters such as aerosol optical depth ( τ), Ångström parameter ( α), single scattering albedo (ω), asymmetry parameter ( g) and volume size distribution ( dV dlogr−1); and their relationship with the most frequent air masses that arrive at Western Spain. Mean values correspond to aerosols of small size and low concentration (mean τ500 = 0.11; mean α = 1.38). In fact, 50% of days correspond to 'continental-clean' type. However, there is a certain variability of conditions, with more than 25% of medium and high turbidity cases with τ500 higher than 0.20. These episodes of high turbidity occur more frequently in August and September and are usually due to the influence of desert-dust aerosol, biomass burning, continental aerosol, or a mixture of them. The analysis of the all basic and derived aerosol parameters is explained by the main influences: continental location, exposed to maritime aerosols coming from the Atlantic Ocean, and affected by Saharan dust intrusions. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper is concentrated on the evaluation of circulation type classifications (CTCs) from the European Action COST733 catalogue version 2.0 in terms of their ability to capture winter precipitation, expressed as percentage, over Spanish Iberia and the Balearic Islands. The explained variation, the pseudo-F statistics and the Brier skill score are used to quantify the explanatory power of circulation classifications. As secondary aims, the impact of using different number of circulation types, additional types of variables and 4-day sequences in the generation of classifications is analysed. Although no optimal method has been found, nevertheless, the results suggest that the use of CTCs based on optimization algorithms are, in general, performing better than those which are based on other algorithms (i.e. leader algorithms). Distinct variations in skill exist not only among classifications from different groups of basic methods but as well between classifications from the same method group; being remarkable the behaviour of the optimum random centroid method. Results are very dependent on the metric, for the explained variation, and the Brier skill score, the larger the number of circulation types, the better the performance; contrary to the behaviour of the pseudo-F statistic. The inclusion of 500 hPa vorticity in the generation of classifications improves results while a general deterioration is observed when considering 4-day sequences. These results are only valid for the selected season and cannot be transferred to other locations and seasons. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper analyses the daily precipitation data recorded for the last 75-80 years in SE Spain. Prior to statistical analysis, homogeneity tests were performed to determine the usefulness of the data (recorded in six pluviometric stations). If the data were homogeneous, the Mann-Kendall test was performed to detect monotonic trends for variables such as total precipitation, number of days with precipitation greater than 1, 20 or 40 mm, number of consecutive dry days and number of consecutive wet days. Moreover, the linear tendency was calculated and accepted (or rejected) by performing a Student's t-test of the calculated residual values. The results showed, on average, a clear change in precipitation patterns for the last 20 years. Annual rainfall had decreased, with values ranging from 0 to 15%, dry periods had increased in length, and the number of rainy days had decreased (especially when high daily precipitation was considered). This latter notion did not exactly concur with the conclusions of the Intergovernmental Panel on Climate Change ( IPCC) 2014 Synthesis Report related to the study area. [ABSTRACT FROM AUTHOR]

A long and complete series of monthly rainfall amounts corresponding to Barcelona city (Catalonia, NE Spain), exceeding two centuries (years 1786–2019), is analysed in detail. The obtained results of periodicity (annual scale), time trends (monthly, seasonal and annual scales), statistical distribution (seasonal and annual scale) and fractal/multifractal structures and self‐similarity at monthly scale depict the complex structure of this pluviometric regime, which is characterized by moderate increasing and decreasing trends on rain amounts, varying from +0.08 mm·year−1 (February) to −0.07 mm·year−1 (September) and quite evident changes on the pluviometric trends at annual and seasonal scales when the rainfall data are analysed for segments of 50 years from 1800 up to 2019. A good example could be the relevant change on the annual scale time trend, from +0.77 mm·year−1 (years 1800–1850) to −0.17 mm·year−1 (years 1950–2019). Clear evidences of decreasing pluviometry for spring, summer and autumn for the last segment (1950–2019) in comparison with the other three segments, including years 1800–1950, are also detected. Additionally, increasing rainfall patterns complexity, expected difficulties on monthly rainfall forecasting and the increasing irregularity of monthly amounts is also detected by interpreting fractal and multifractal results. Irregularity increases on the monthly rainfall series and on the rainfall regime complexity derived from multifractal parameters, could be associated with the very notable increase of CO2 emissions into the atmosphere, globally varying from 51.1 × 106 metric tonnes (year 1820) to 36.6 × 109 metric tonnes (year 2019) and the tropospheric concentration increasing from 280.8 ppm (year 1850) to 397.5 ppm (year 2014), being the probable relationship between tropospheric concentrations and changes on rainfall patterns the objective of future researches. [ABSTRACT FROM AUTHOR]

Trends in seasonal mean values of maximum and minimum temperature are analysed in the Spanish mainland from the new MOTEDAS_century database. This new data set has been developed combining the digitalized archives from the Spanish Meteorological Agency (AEMET) with information retrieved from Annual Books published by the former Meteorological Agency dating back to 1916, and covers the period 1916–2015. In all four seasons, mean seasonal temperature of maximum (Tmax) and minimum (Tmin) increased. The raising occurred in two main pulses separated by a first pause around the middle of the 20th century, but differed among seasons and also between maximum and minimum temperature. Analysis of the percentage of land affected by significant trends in maximum temperature reveals two increasing phases in spring and summer for Tmax, and in spring, summer, and autumn for Tmin. However, winter Tmax only rose during the recent decades, and autumn Tmax in the first decades. Negative significant trends were found in extended areas in spring Tmax, and in spring, autumn, and summer Tmin, confirming the first pause around the 1940's–1960's. Trends of seasonal mean values of Tmax and Tmin are not significant for at least the last 25–35 years of the study period, depending on the season. The areas under significant positive trend are usually more extended for Tmin than Tmax at any season and period. Areas with significant trend expand and contract in time according to two spatial gradients: south‐east to north‐west (east‐west) for Tmax, and west to east for Tmin. We hypothesize a relationship between atmospheric prevalent advection and relief as triggering factors to understand spatial and temporal differences in seasonal temperatures at regional scale during the 20th century in the Iberian Peninsula. [ABSTRACT FROM AUTHOR]

This study presents a climatology and trend analysis of reference crop evapotranspiration (ETo) over continental Spain and the Balearic Islands. Geographic features of the study region play a substantial role in the climatology of ETo. The highest values (in excess of 1,200 mm y−1) are found at lower elevations in the south, while the lowest values (less than 900 mm y−1) are found in the highest elevations in the north. A deep analysis reveals: (a) a low interannual variability; (b) summer accumulates more than 50% of annual values; and (c) the radiative component contribution is higher than 50%. A positive long‐term trend (1961–2014) has been detected for most of the study area, but showing contrasting situations when shorter periods (20–30 years) are analysed. A short initial period of negative trend was followed by a longer period of a positive trend. We argue that global dimming/brightening played a role in this process, as these two contrasting periods are clearly guided by the radiative component. A seasonal analysis of the trends reveals that spring and summer are the seasons showing the long‐term positive trends. Interestingly, a monthly analysis shows that spring trends are guided by March and April and summer trends are mostly guided by June, which is the month showing the highest relative changes. This could have important consequences for agriculture and natural ecosystems since this month represents the start of the summer (dry) period. [ABSTRACT FROM AUTHOR]

Advantages offered by a pluviometric network in Catalonia (NE Spain) have permitted a detailed analysis of the two primary results derived from the autoregressive ARIMA process applied to monthly rainfall amounts. The first was the spatial distribution of the necessary number of previous monthly amounts needed to predict the next amount. The second was the spatial distribution of discrepancies between the real recorded amount and those derived from the autoregressive process. The heterogeneous spatial distribution of both parameters of the ARIMA process is in accordance with the complex spatial distribution of the monthly rainfall regime in Catalonia and fractal/multifractal analyses of several monthly rainfall time series. The statistical distribution of monthly discrepancies also permits a prediction of the probable evolution at monthly scale of drought episodes in terms of length and accumulated rainfall deficit. The results of the ARIMA algorithm are characterized by a few cases of rain gauges with remarkable differences (10–20 mm⋅month–1) between real and autoregressive amounts, a predominant number of emplacements lowering 10 mm⋅month–1 and a not negligible number of cases with discrepancies lower than 5 mm⋅month–1. In terms of percentages with respect to average monthly amounts, most of discrepancies do not exceed 15%, and only in a very few cases they are within the 20–40% range. It is also worth mentioning that the discrepancies between real and predicted drought lengths use to be no longer than 1 month. Results corresponding to monthly series recorded at two Earth Sciences observatories are described with more detail to illustrate the advantages offered by the ARIMA autoregressive process in the prediction of beginning, continuity and end of drought episodes. [ABSTRACT FROM AUTHOR]

Precipitation constitutes a particularly variable climatic element in Spain. Study of teleconnection indices, closely related to precipitation, enables us to establish to a greater or lesser degree the mechanisms regulating pluviometric variability; these are vital for planning and managing water resources in semiarid regions. In the present article we attempt to identify the low‐frequency patterns that present the closest statistical relationship with rainfall for each of the points on the MOPREDAS pluviometric data grid, covering the whole area of peninsular Spain. The results obtained reveal the clear dominance of Mediterranean Basin patterns, specifically of the Mediterranean Oscillation (MO) and of its version in the mid‐levels of the troposphere (ULMO). Results, however, show a significant dominance of the Western Mediterranean Oscillation (WeMO) in the east of the Iberian Peninsula and the eastern part of the Cantabrian façade. Also noteworthy is the control exerted by the NAO over much of the centre and southwest of Spain, as well as the surprising dominance of an index that heretofore has not been used much, known as the Paris‐London Westerly Index. Finally, we performed a regionalisation based upon the correlations between the teleconnection and precipitation indices by means of a principal components analysis, which revealed the existence of three differentiated pluviometric regions in peninsular Spain: Atlantic (centre and south), Mediterranean (east) and Cantabrian (north). [ABSTRACT FROM AUTHOR]

Information was retrieved from the Annual Climate Summaries (ACS) on average monthly temperatures in Spain for the period 1916–1949, and combined with the digitalized data from the National Climate Data Bank of the Spanish meteorological service (AEMET) to create the new MOTEDAS_century (MOnthly Temperature Dataset of Spain) database of mean monthly maximums (Tmax) and minimums (Tmin). This database was used to calculate a high‐resolution (10 × 10 km) grid that allowed to make a detailed analysis of the temporal evolution of temperature in Spain during the period 1916–2015. Over the period, mean Tmax increased by 1.2°C, while Tmin increased by 1.0°C (this ratio is reversed in the second half of the century). In the last 30 years, however, mean annual Tmax and Tmin trends have not been significant. There are some differences between the new mean annual maximum and minimum temperature series and previous versions, which seem to arise from the much higher number of weather stations analysed, their location and the processing used. There is a discussion on the improved spatial representativeness of the new MOTEDAS_century that provides a more detailed representation of the spatial variability of temperatures in continental Spain. [ABSTRACT FROM AUTHOR]

This study characterizes the climatology of drought events over the mainland Spain and the Balearic Islands using high‐resolution (1.21 km2) meteorological data from 1961 to 2014. The climatology of drought was assessed based on two widely‐recognized drought indices: the Standardized Precipitation Index (SPI) and the Standardized Precipitation‐Evapotranspiration Index (SPEI), considering four different timescales (1‐, 3‐, 6‐ and 12‐months). Drought events were simply defined as sequences of months with negative values of the indices. We analysed the spatial and temporal variability of the frequency, duration and magnitude of the drought events. In general, the frequency of drought events is higher in the northern than in the southern regions. Conversely, the average duration and magnitude of the drought events in central and southwestern regions duplicate those recorded in northern areas. Although drought characteristics exhibit a general north–south gradient irrespective of the drought timescale and the drought index analysed, we found important spatial differences in terms of both drought duration and severity. As opposed to the SPI, the SPEI shows, on average, higher drought durations and magnitudes at 1‐, 3‐ and 6‐months timescales. Albeit of the absence of significant temporal changes in drought duration or magnitude at the regional scale, a nonsignificant tendency toward higher drought duration and magnitude is observed over the majority of Spain. Our result provide valuable guidance to stakeholders and decision‐makers on detecting, monitoring and adapting to drought impacts at local, regional and national scale in Spain. [ABSTRACT FROM AUTHOR]

This work analyses three uncertainty sources affecting the observation‐based gridded data sets: station density, interpolation methodology and spatial resolution. For this purpose, we consider precipitation in two countries, Poland and Spain, three resolutions (0.11, 0.22 and 0.44°), three interpolation methods, both areal‐ and point‐representative implementations, and three different densities of the underlying station network (high/medium/low density). As a result, for each resolution and interpolation approach, nine different grids have been obtained for each country and inter‐compared using a variance decomposition methodology. Results indicate larger differences among the data sets for Spain than for Poland, mainly due to the larger spatial variability and complex orography of the former region. The variance decomposition points out to station density as the most influential factor, independent of the season, the areal‐ or point‐representative implementation and the country considered, and slightly increasing with the spatial resolution. In contrast, the decomposition is stable when extreme precipitation indices are considered, in particular for the 50‐year return value. Finally, the uncertainty due to station sub‐sampling inside a particular grid box decreases with the number of stations used in the averaging/interpolation. In the case of spatially homogeneous grid boxes, the interpolation approach obtains similar results for all the parameters, excepting the wet day frequency, independently of the number of stations. When there is a more significant internal variability in the grid box, the interpolation is more sensitive to the number of stations, pointing out to a minimum stations' density for the target resolution (six to seven stations). [ABSTRACT FROM AUTHOR]

The objective of this work is to present new meteorological data from southern Spain corresponding to the period 1785–1830. Data sources are early newspapers and medical studies interested in the influence of environment conditions on health and illness. Data correspond to five cities in the area (Cádiz, Seville, Málaga, Granada, and Cartagena). Around 16,000 new meteorological observations (temperature, pressure, number of rainy days, wind direction, and qualitative statements on rainfall, wind force, cloudiness, fog, and storms) were recorded. Database obtained is a set of scattered meteorological series, with short periods of observation, fragmented and with no homogeneous characteristics. However, these data may offer an overview on the climatic conditions in the area during the studied period, as well as interesting information on extreme events, as for instance floods in the 1780s decade, and the so‐called "year without summer" 1816. [ABSTRACT FROM AUTHOR]

Although the mean environmental lapse rate (MELR) value (a linear decrease of −6.5 °C/km) is the most widely used, near‐surface (i.e., non‐free atmosphere) air temperature lapse rates (NSLRs; measured at ~1.5 m height) are variable in space and time because of their dependence on topography and meteorological conditions. In this study we conducted the first analysis of the spatial and temporal variability of NSLRs for continental Spain and their relationship to synoptic atmospheric circulation (circulation weather types [CWTs]), focusing on major mountain areas including the Pyrenees, Cantabrian, Central, Baetic, and Iberian ranges. The results showed that the NSLR varied markedly at spatial and seasonal scales and depended on the dominant atmospheric conditions. The median NSLR values were weaker (less negative) than the MELR for the mountain areas (Pyrenees −5.17 °C/km; Cantabrian range −5.22 °C/km; Central range −5.78 °C/km; Baetic range −4.83 °C/km; Iberian range −5.79 °C/km) and for the entire continental Spain (−5.28 °C/km). For the entire continental Spain the steepest NSLR values were found in April (−5.80 °C/km), May (−5.58 °C/km), and October (−5.54 °C/km) because of the dominance of northerly and westerly advections of cold air. The weakest NSLR values were found in July (−4.67 °C/km) and August (−4.78 °C/km) because of the inland heating, and in winter because of the occurrence of thermal inversions. As the use of the MELR involves the assumption of large errors, we propose 1 zonal, 12 monthly, 11 CWTs, and 132 hybrid monthly–CWTs NSLRs for each of the mountain ranges and for the entire continental Spain. More regional studies are urgently needed to accurately assess the NSLR as a function of atmospheric circulation conditions. [ABSTRACT FROM AUTHOR]

ABSTRACT Climate variability and change can have important impacts for crop production. Therefore, the aim of this study is to investigate projections of the wheat yield in an increasingly warm climate. To address our objectives, we determined relationships between wheat yield in Spain and large-scale variables. Partial least squares regression was applied to determine the modes of the climate variables that drive wheat-yield variability, revealing a significant influence of surface solar radiation. Based on seasonal patterns of solar radiation, we determine models to estimate inter-annual wheat-yield variability. We find that the performance of the models based on solar radiation is better than that of earlier studies based on temperatures and precipitation variables. In this way, we use simulations of the Coupled Model Intercomparison Project Phase 5 ( CMIP5) to project wheat-yield trend under warming climate by implementing direct statistical downscaling. The expected range of projected wheat yield trend for 21st century indicates decreases of about 6-8% across Spain. The suggested models could be applied for adaptation and planning. [ABSTRACT FROM AUTHOR]

ABSTRACT Hailstorms have become a serious meteorological risk in mid-latitude countries because of their small-scale development and short time span, and their forecasting remains problematic. Moreover, the lack of reliable hailstorm databases is an important handicap for Numerical Weather Prediction (NWP) model validation, time trend studies and establishment of hailstorm relationships with global warming and climate change. However, this can be overcome by ascertaining physical relationships between favourable synoptic patterns and mesoscale trigger factors for hailstorm development in a local study area. North-eastern Spain is one of the European regions with largest number of hailstorm days ( HD) observed in the summer. Since 2001, from May through September, reliable databases of hailstorm occurrence in the middle Ebro Valley have been constructed, which include intensity, temporal frequency and spatial coordinate data. June and July 2006 had the largest number of HD in 2001-2010. With the objective of analysing meteorological factors responsible for this anomaly, atmospheric patterns at low and mid-tropospheric levels were studied. We determined a set of special synoptic configurations, with an evident deviation from climatic values generating anomalies of 850 hPa temperature relative to the characteristic values of 2001-2010 and 1950-2010. An analysis of these anomalies detected a positive trend of 850 hPa temperature and geopotential height in the western Mediterranean area. As a consequence, the characteristic synoptic circulation has changed since 1950, towards low-level patterns favouring adequate thermodynamic environments for hailstorm development in north-eastern Spain. Finally, after a cluster analysis, we studied periodicities in the monthly 850 hPa temperature field to improve knowledge for seasonal forecasting of hailstorms. [ABSTRACT FROM AUTHOR]