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Historical climatology has remarkable potentialities to produce climatic reconstructions with high temporal resolution. However, some methodological limitations hinder the spatial development of this discipline. This study presents a new approach to historical climatology that overcomes some of the limitations of classical approaches, such as the rogation method or content analysis: the Cost Opportunity for Small Towns (COST). It analyses historic documents and takes advantage of all sorts of meteorological information available in written documents, and not only the severest events, to therefore overcome the most prominent bottlenecks of former approaches. COST relies on the fact that using paper is very costly, so its use to describe meteorological conditions is hypothesised as being proportional to the impact they had on society. To prove the validity of this approach to reconstruct climate conditions, this article exemplarily uses the Municipal Chapter Acts of a small town in southern Spain (Caravaca de la Cruz), which span the 1600–1900 period, and allows reconstructions to be obtained on a monthly basis. Using the same documentary source, the three approaches were used to derive respective climate reconstructions, which were then compared to assess climate signal consistency and to identify possible caveats in the methods. The three approaches led to a generally coherent series of secular variability in the hydrological conditions, which agrees well with previous study results. The COST approach is arguably more objective and less affected by changes in societal behaviour, which allows it to perform comparative studies in regions with different languages and traditions.

This study addresses the possibility of carrying out spatially resolved global reconstructions of annual mean temperature using a worldwide network of proxy records and a method based on the search of analogues. Several variants of the method are evaluated, and their performance is analysed. As a test bed for the reconstruction, the PAGES 2k proxy database (version 1.9.0) is employed as a predictor, the HadCRUT4 dataset is the set of observations used as the predictand and target, and a set of simulations from the PMIP3 simulations are used as a pool to draw analogues and carry out pseudo-proxy experiments (PPEs). The performance of the variants of the analogue method (AM) is evaluated through a series of PPEs in growing complexity, from a perfect-proxy scenario to a realistic one where the pseudo-proxy records are contaminated with noise (white and red) and missing values, mimicking the limitations of actual proxies. Additionally, the method is tested by reconstructing the real observed HadCRUT4 temperature based on the calibration of real proxies. The reconstructed fields reproduce the observed decadal temperature variability. From all the tests, we can conclude that the analogue pool provided by the PMIP3 ensemble is large enough to reconstruct global annual temperatures during the Common Era. Furthermore, the search of analogues based on a metric that minimises the RMSE in real space outperforms other evaluated metrics, including the search of analogues in the range-reduced space expanded by the leading empirical orthogonal functions (EOFs). These results show how the AM is able to spatially extrapolate the information of a network of local proxy records to produce a homogeneous gap-free climate field reconstruction with valuable information in areas barely covered by proxies and make the AM a suitable tool to produce valuable climate field reconstructions for the Common Era.

We analyse the variability of the probability distribution of daily wind speed in wintertime over Northern and Central Europe in a series of global and regional climate simulations covering the last centuries, and in reanalysis products covering approximately the last 60 years. The focus of the study lies on identifying the link of the variations in the wind speed distribution to the regional near-surface temperature, to the meridional temperature gradient and to the North Atlantic Oscillation. Our main result is that the link between the daily wind distribution and the regional climate drivers is strongly model dependent. The global models tend to behave similarly, although they show some discrepancies. The two regional models also tend to behave similarly to each other, but surprisingly the results derived from each regional model strongly deviates from the results derived from its driving global model. In addition, considering multi-centennial timescales, we find in two global simulations a long-term tendency for the probability distribution of daily wind speed to widen through the last centuries. The cause for this widening is likely the effect of the deforestation prescribed in these simulations. We conclude that no clear systematic relationship between the mean temperature, the temperature gradient and/or the North Atlantic Oscillation, with the daily wind speed statistics can be inferred from these simulations. The understanding of past and future changes in the distribution of wind speeds, and thus of wind speed extremes, will require a detailed analysis of the representation of the interaction between large-scale and small-scale dynamics.

This study compares gridded European seasonal series of surface air temperature (SAT) and precipitation (PRE) reconstructions with a regional climate simulation over the period 1500–1990. The area is analysed separately for nine subareas that represent the majority of the climate diversity in the European sector. In their spatial structure, an overall good agreement is found between the reconstructed and simulated climate features across Europe, supporting consistency in both products. Systematic biases between both data sets can be explained by a priori known deficiencies in the simulation. Simulations and reconstructions, however, largely differ in the temporal evolution of past climate for European subregions. In particular, the simulated anomalies during the Maunder and Dalton minima show stronger response to changes in the external forcings than recorded in the reconstructions. Although this disagreement is to some extent expected given the prominent role of internal variability in the evolution of regional temperature and precipitation, a certain degree of agreement is a priori expected in variables directly affected by external forcings. In this sense, the inability of the model to reproduce a warm period similar to that recorded for the winters during the first decades of the 18th century in the reconstructions is indicative of fundamental limitations in the simulation that preclude reproducing exceptionally anomalous conditions. Despite these limitations, the simulated climate is a physically consistent data set, which can be used as a benchmark to analyse the consistency and limitations of gridded reconstructions of different variables. A comparison of the leading modes of SAT and PRE variability indicates that reconstructions are too simplistic, especially for precipitation, which is associated with the linear statistical techniques used to generate the reconstructions. The analysis of the co-variability between sea level pressure (SLP) and SAT and PRE in the simulation yields a result which resembles the canonical co-variability recorded in the observations for the 20th century. However, the same analysis for reconstructions exhibits anomalously low correlations, which points towards a lack of dynamical consistency between independent reconstructions.

The consistency of an existing reconstructed annual (December–November) temperature series for the Lisbon region (Portugal) from 1600 onwards, based on a European-wide reconstruction, with (1) five local borehole temperature–depth profiles; (2) synthetic temperature–depth profiles, generated from both reconstructed temperatures and two regional paleoclimate simulations in Portugal; (3) instrumental data sources over the twentieth century; and (4) temperature indices from documentary sources during the late Maunder Minimum (1675–1715) is assessed. The low-frequency variability in the reconstructed temperature in Portugal is not entirely consistent with local borehole temperature–depth profiles and with the simulated response of temperature in two regional paleoclimate simulations driven by reconstructions of various climate forcings. Therefore, the existing reconstructed series is calibrated by adjusting its low-frequency variability to the simulations (first-stage adjustment). The annual reconstructed series is then calibrated in its location and scale parameters, using the instrumental series and a linear regression between them (second-stage adjustment). This calibrated series shows clear footprints of the Maunder and Dalton minima, commonly related to changes in solar activity and explosive volcanic eruptions, and a strong recent-past warming, commonly related to human-driven forcing. Lastly, it is also in overall agreement with annual temperature indices over the late Maunder Minimum in Portugal. The series resulting from this post-reconstruction adjustment can be of foremost relevance to improve the current understanding of the driving mechanisms of climate variability in Portugal.

We present and analyse a high-resolution regional climate palaeosimulation encompassing the European region for the period 1500–1990. We use the regional model MM5 driven at the boundaries by the global model ECHO-G. Both models are forced by reconstructions of three external factors: greenhouse gas concentrations, total solar irradiance and volcanic activity. The simulation skill is assessed in a recent period by comparing the model results with the Climate Research Unit (CRU) database. The results show that although the regional model is tightly driven by the boundary conditions, it is able to improve the reliability of the simulations, narrowing the differences to the observations, especially in areas of complex topography. Additionally, the evolution of the spatial distributions of temperature and precipitation through the last five centuries is analysed, showing that the mean values of temperature reflects the influence of the external forcings. However, contrary to the results obtained under climate change scenario conditions, higher-order momenta of seasonal temperature and precipitation are hardly affected by changes in the external forcings.

Past temperature variations are usually inferred from proxy data or estimated using general circulation models. Comparisons between climate estimations derived from proxy records and from model simulations help to better understand mechanisms driving climate variations, and also offer the possibility to identify deficiencies in both approaches. This paper presents regional temperature reconstructions based on tree-ring maximum density series in the Pyrenees, and compares them with the output of global simulations for this region and with regional climate model simulations conducted for the target region. An ensemble of 24 reconstructions of May-to-September regional mean temperature was derived from 22 maximum density tree-ring site chronologies distributed over the larger Pyrenees area. Four different tree-ring series standardization procedures were applied, combining two detrending methods: 300-yr spline and the regional curve standardization (RCS). Additionally, different methodological variants for the regional chronology were generated by using three different aggregation methods. Calibration verification trials were performed in split periods and using two methods: regression and a simple variance matching. The resulting set of temperature reconstructions was compared with climate simulations performed with global (ECHO-G) and regional (MM5) climate models. The 24 variants of May-to-September temperature reconstructions reveal a generally coherent pattern of inter-annual to multi-centennial temperature variations in the Pyrenees region for the last 750 yr. However, some reconstructions display a marked positive trend for the entire length of the reconstruction, pointing out that the application of the RCS method to a suboptimal set of samples may lead to unreliable results. Climate model simulations agree with the tree-ring based reconstructions at multi-decadal time scales, suggesting solar variability and volcanism as the main factors controlling preindustrial mean temperature variations in the Pyrenees. Nevertheless, the comparison also highlights differences with the reconstructions, mainly in the amplitude of past temperature variations and in the 20th century trends. Neither proxy-based reconstructions nor model simulations are able to perfectly track the temperature variations of the instrumental record, suggesting that both approximations still need further improvements.

In this work, a reconstruction of climatic conditions in Andalusia (southern Iberian Peninsula) during the period 1701–1850, as well as an evaluation of its associated uncertainties, is presented. This period is interesting because it is characterized by a minimum in solar irradiance (Dalton Minimum, around 1800), as well as intense volcanic activity (for instance, the eruption of Tambora in 1815), at a time when any increase in atmospheric CO2 concentrations was of minor importance. The reconstruction is based on the analysis of a wide variety of documentary data. The reconstruction methodology is based on counting the number of extreme events in the past, and inferring mean value and standard deviation using the assumption of normal distribution for the seasonal means of climate variables. This reconstruction methodology is tested within the pseudoreality of a high-resolution paleoclimate simulation performed with the regional climate model MM5 coupled to the global model ECHO-G. The results show that the reconstructions are influenced by the reference period chosen and the threshold values used to define extreme values. This creates uncertainties which are assessed within the context of climate simulation. An ensemble of reconstructions was obtained using two different reference periods (1885–1915 and 1960–1990) and two pairs of percentiles as threshold values (10–90 and 25–75). The results correspond to winter temperature, and winter, spring and autumn rainfall, and they are compared with simulations of the climate model for the considered period. The mean value of winter temperature for the period 1781–1850 was 10.6 ± 0.1 °C (11.0 °C for the reference period 1960–1990). The mean value of winter rainfall for the period 1701–1850 was 267 ± 18 mm (224 mm for 1960–1990). The mean values of spring and autumn rainfall were 164 ± 11 and 194 ± 16 mm (129 and 162 mm for 1960–1990, respectively). Comparison of the distribution functions corresponding to 1790–1820 and 1960–1990 indicates that during the Dalton Minimum the frequency of dry and warm (wet and cold) winters was lower (higher) than during the reference period: temperatures were up to 0.5 °C lower than the 1960–1990 value, and rainfall was 4% higher.

In this study we analyse the role of internal variability in regional climate simulations through a comparison of two regional paleoclimate simulations for the last millennium. They share the same external forcings and model configuration, differing only in the initial condition used to run the driving global model simulation. A comparison of these simulations allows us to study the role of internal variability in climate models at regional scales, and how it affects the long-term evolution of climate variables such as temperature and precipitation. The results indicate that, although temperature is homogeneously sensitive to the effect of external forcings, the evolution of precipitation is more strongly governed by random unpredictable internal dynamics. There are, however, some areas where the role of internal variability is lower than expected, allowing precipitation to respond to the external forcings. In this respect, we explore the underlying physical mechanisms responsible for it. This study identifies areas, depending on the season, in which a direct comparison between model simulations of precipitation and climate reconstructions would be meaningful, but also other areas where good agreement between them should not be expected even if both are perfect.

A high-resolution (30 km) regional paleoclimate simulation of the last millennium over the Iberian Peninsula (IP) is presented. The simulation was performed with a climate version of the mesoscale model MM5 driven by the global model ECHO-G. Both models were driven by the same reconstructions of several external forcing factors. The high spatial resolution of the regional model allows climatologists to realistically simulate many aspects of the climate in the IP, as compared to an observational data set in the reference period 1961–1990. Although the spatial-averaged values developed by the regional model are tightly driven by the boundary conditions, it is capable to develop a different realisation of the past climate at regional scales, especially in the high-frequency domain and for precipitation. This has to be considered when comparing the results of climate simulations versus proxy reconstructions. A preliminary comparison of the simulation results with reconstructions of temperature and precipitation over the IP shows good agreement in the warming trends in the last century of the simulation, although there are large disagreements in key periods such as the precipitation anomalies in the Maunder Minimum.