Juan J. Gomez-Navarro

European summer temperatures since Roman times

The spatial context is criticalwhen assessing present-day climate anomalies, attributing them to potential forcings and making statements regarding their frequency and severity in a long-term perspective. Recent international initiatives have expanded the number of high-quality proxy-records and developed new statistical reconstruction methods. These advances allow more rigorous regional past temperature reconstructions and, in turn, the possibility of evaluating climate models on policy-relevant, spatiotemporal scales. Here we provide a new proxy-based, annually-resolved, spatial reconstruction of the European summer (June-August) temperature fields back to 755 CE based on Bayesian hierarchical modelling (BHM), together with estimates of the European mean temperature variation since 138 BCE based on BHM and composite-plus-scaling (CPS). Our reconstructions compare well with independent instrumental and proxy-based temperature estimates, but suggest a larger amplitude in summer temperature variability than previously reported. Both CPS and BHM reconstructions indicate that the mean 20th century European summer temperature was not significantly different from some earlier centuries, including the 1st, 2nd, 8th and 10th centuries CE. The 1st century (in BHM also the 10th century) may even have been slightly warmer than the 20th century, but the difference is not statistically significant. Comparing each 50 yr period with the 1951-2000 period reveals a similar pattern. Recent summers, however, have been unusually warm in the context of the last two millennia and there are no 30 yr periods in either reconstruction that exceed the mean average European summer temperature of the last 3 decades (1986-2015 CE). A comparison with an ensemble of climate model simulations suggests that the reconstructed European summer temperature variability over the period 850-2000 CE reflects changes in both internal variability and external forcing on multi-decadal time-scales. For pan-European temperatures we find slightly better agreement between the reconstruction and the model simulations with high-end estimates for total solar irradiance. Temperature differences between the medieval period, the recent period and the Little Ice Age are larger in the reconstructions than the simulations. This may indicate inflated variability of the reconstructions, a lack of sensitivity and processes to changes in external forcing on the simulated European climate and/or an underestimation of internal variability on centennial and longer time scales.

A multi-physics ensemble of present-day climate regional simulations over the Iberian Peninsula

This work assesses the influence of the model physics in present-day regional climate simulations. It is based on a multi-phyiscs ensemble of 30-year long MM5 hindcasted simulations performed over a complex and climatically heterogeneous domain as the Iberian Peninsula. The ensemble consists of eight members that results from combining different parametrization schemes for modeling the Planetary Boundary Layer, the cumulus and the microphysics processes. The analysis is made at the seasonal time scale and focuses on mean values and interannual variability of temperature and precipitation. The objectives are (1) to evaluate and characterize differences among the simulations attributable to changes in the physical options of the regional model, and (2) to identify the most suitable parametrization schemes and understand the underlying mechanisms causing that some schemes perform better than others. The results confirm the paramount importance of the model physics, showing that the spread among the various simulations is of comparable magnitude to the spread obtained in similar multi-model ensembles. This suggests that most of the spread obtained in multi-model ensembles could be attributable to the different physical configurations employed in the various models. Second, we obtain that no single ensemble member outperforms the others in every situation. Nevertheless, some particular schemes display a better performance. On the one hand, the non-local MRF PBL scheme reduces the cold bias of the simulations throughout the year compared to the local Eta model. The reason is that the former simulates deeper mixing layers. On the other hand, the Grell parametrization scheme for cumulus produces smaller amount of precipitation in the summer season compared to the more complex Kain-Fritsch scheme by reducing the overestimation in the simulated frequency of the convective precipitation events. Consequently, the interannual variability of precipitation (temperature) diminishes (increases), which implies a better agreement with the observations in both cases. Although these features improve in general the accuracy of the simulations, controversial nuances are also highlighted.

The role of the land-surface model for climate change projections over the Iberian Peninsula

The importance of land-surface processes within Regional Climate Models for accurately reproducing the present-day climate is well known. However, their role when projecting future climate is still poorly reported. Hence, this work assesses the influence of the land-surface processes, particularly the contribution of soil moisture, when projecting future changes for temperature, precipitation and wind over a complex area as the Iberian Peninsula, which, in addition, shows great sensitivity to climate change. The main signals are found for the summer season, when the results indicate a strengthening in the increases projected for both mean temperature and temperature variability as a consequence of the future intensification of the positive soil moisture-temperature feedback. The more severe warming over the inner dry Iberian Peninsula further implies an intensification of the Iberian thermal low and, thus, of the cyclonic circulation. Furthermore, the land-atmosphere coupling leads to the projection of a wider future daily temperature range, since maximum temperatures are more affected than minima, a feature absent in non-coupled simulations. Regarding variability, the areas where the land-atmosphere coupling introduces larger changes are those where the reduction in the soil moisture content is more dramatic in future simulations, i.e., the so-called transitional zones. As regards precipitation, weaker positive signals for convective precipitation and more intense negative signals for non-convective precipitation are obtained as a result of the soil moisture-atmosphere interactions. These results highlight the crucial contribution of soil moisture to climate change projections and suggest its plausible key role for future projections of extreme events.

Temperature sensitivity to the land-surface model in MM5 climate simulations over the Iberian Peninsula

Three different Land Surface Models have been used in three high resolution climate simulations performed with the mesoscale model MM5 over the Iberian Peninsula. The main difference among them lies in the soil moisture treatment, which is dynamically modelled by only two of them (Noah and Pleim & Xiu models), while in the simplest model (Simple Five-Layers) it is fixed to climatological values. The simulated period covers 1958-2002, using the ERA40 reanalysis data as driving conditions. Focusing on near-surface air temperature, this work evaluates the skill of each simulation in reproducing mean values and temporal variability, by comparing the simulations with observed temperature series. When the simplest simulation was analyzed, the greatest discrepances were observed for the summer season, when both, the mean values and the temporal variability of the temperature series, were badly underestimated. These weaknesses are largely overcome in the other two simulations (performed by coupling a more advanced soil model to MM5), and there was greater concordance between the simulated and observed spatial patterns. The influence of a dynamic soil moisture parameterization and, therefore, a more realistic simulation of the latent and sensible heat fluxes between the land and the atmosphere, helps to explain these results.

Warming patterns in regional climate change projections over the Iberian Peninsula

A set of four regional climate change projections over the Iberian Peninsula has been performed. Simulations were driven by two General Circulation Models (consisting of two versions of the same atmospheric model coupled to two different ocean models) under two different SRES scenario. The XXI century has been simulated following a full-transient approach with a climate version of the mesoscale model MM5. An Empirical Orthogonal Function analysis (EOF) is applied to the monthly mean series of daily maximum and minimum 2-metre temperature to extract the warming signal. The first EOF is able to capture the spatial structure of the warming. The obtained warming patterns are fairly dependent on the month, but hardly change with the tested scenarios and GCM versions. Their shapes are related to geographical parameters, such as distance to the sea and orography. The main differences among simulations mostly concern the temporal evolution of the warming. The temperature trend is stronger for maximum temperatures and depends on the scenario and the driving GCM. This asymmetry, as well as the different warming rates in summer and winter, leads to a continentalization of the climate over the IP.

A multi-physics ensemble of regional climate change projections over the Iberian Peninsula

This study illustrates the sensitivity of regional climate change projections to the model physics. A single-model (MM5) multi-physics ensemble of regional climate simulations over the Iberian Peninsula for present (1970–1999) and future (2070–2099 under the A2 scenario) periods is assessed. The ensemble comprises eight members resulting from the combination of two options of parameterization schemes for the planetary boundary layer, cumulus and microphysics. All the considered combinations were previously evaluated by comparing hindcasted simulations to observations, none of them providing clearly outlying climates. Thus, the differences among the various ensemble members (spread) in the future projections could be considered as a matter of uncertainty in the change signals (as similarly assumed in multi-model studies). The results highlight the great dependence of the spread on the synoptic conditions driving the regional model. In particular, the spread generally amplifies under the future scenario leading to a large spread accompanying the mean change signals, as large as the magnitude of the mean projected changes and analogous to the spread obtained in multi-model ensembles. Moreover, the sign of the projected change varies depending on the choice of the model physics in many cases. This, together with the fact that the key mechanisms identified for the simulation of the climatology of a given period (either present or future) and those introducing the largest spread in the projected changes differ significantly, make further claims for efforts to better understand and model the parameterized subgrid processes.

A seasonal study of the atmospheric dynamics over the Iberian Peninsula based on circulation types

A seasonal analysis of the atmospheric circulation over the Iberian Peninsula (IP) based on circulation types (CTs) obtained from sea level pressure and 500-hPa geopotential height is presented. The study covers the period of 1958–2008, when a high variability and important changes in winter and spring precipitation and temperature have been reported. Frequency, persistence, and the most probable transitions of the circulation types are analyzed. Among the clustering methods available in the literature, two of the most reliable classification methods have been tested, K-means and simulated annealing and diversified randomization. A comparison of both methods over the IP is presented for winter (DJF). The quality of the circulation types obtained through both methods as well as the better stability achieved by K-means suggest this method as more appropriated for our target area. Twelve CTs were obtained for each season and were analyzed. The patterns obtained were regrouped in five general situations: anticyclonic, cyclonic, zonal, summertime, and hybrid-mixed. The analysis of frequencies of these situations offers a similar characterization of the atmospheric circulation that others previously obtained by subjective methods. The analysis of the trends in frequency and persistence for each CT shows few significant trends, mainly in winter and spring with a general decrease of the cyclonic patterns and an increase of the anticyclonic situations. This can be related to the negative precipitation trends reported by other authors. Regarding the persistence, an interesting result is that there is a high interannual variability of the persistence in autumn and spring, when patterns can persist longer than in other seasons. An analysis of the most probable transitions between the CTs has been performed, revealing the existence of cyclic sequences in all seasons. These sequences are related to the high frequency of certain patterns such as the anticyclonic situations in winter. Finally, a clear seasonal dependence of the transitions between cyclonic situations associated with extratropical disturbances was found. This dependence suggests that the transitions of low-pressure systems towards the south of the IP are more likely in spring and autumn than in winter.

Drought indices revisited – improving and testing of drought indices in a simulation of the last two millennia for Europe

Over the past decades, different drought indices have been suggested in the literature. This study tackles the problem of how to characterize droughts by defining a framework and proposing a generalized family of drought indices that is flexible regarding the use of different hydrological fluxes in the water balance. The sensitivity of various indices and its skill to represent drought conditions is evaluated using a regional model simulation for Europe spanning the last two millennia as test bed. The framework combines an exponentially damped memory with a normalization method based on quantile mapping. Both approaches are more robust and physically meaningful compared to the existing methods used to define drought indices. Still, the framework is flexible with respect to hydrological fluxes used for the water balance, enabling users to adapt the index formulation to the data availability of different locations. Based on it, indices using different hydrological fluxes in the water balance are compared with each other showing that a drought index considering only precipitation in the water balance is sufficient for western to central Europe. In the Mediterranean, temperature effects via evapotranspiration rather than potential evapotranspiration, need to be considered to produce meaningful indices representative of water deficit. In addition, our results indicate that in north-eastern Europe and Scandinavia, snow and run-off effects need to be considered simultaneously in the index definition to obtain accurate results.

Evaluation of downscaled wind speeds and parameterised gusts for recent and historical windstorms in Switzerland

Assessments of local-scale windstorm hazard require highly resolved spatial information on wind speeds and gusts. In this study, maximum (peak) sustained wind speeds on a 3-km horizontal grid over Switzerland are obtained by dynamical downscaling from the Twentieth Century Reanalysis (20CR) employing the Weather Research and Forecasting (WRF) model. Subsequently, simulated peak gusts are derived using four wind gust parameterizations (WGPs). Evaluations against observations at 63 locations in complex terrain include four high-impact windstorms (occurring in 1919, 1935, 1990, and 1999) and 14 recent windstorms (occurring between 1993 and 2011). Peak sustained wind speeds and directions are generally well simulated, although wind speeds are mostly overestimated. In general, performance and skill measures are best for locations on the Swiss Plateau and inferior for Alpine mountain and valley locations. An independent ERA-Interim WRF downscaling configuration produces overall comparable results, implying that the 20CR ensemble mean is a reliable data set in dynamical downscaling exercises. The four evaluated WGPs largely reproduce the observed gustiness, although the timing and magnitude of the peak gusts are not regularly captured. None of the WGPs stands out as single best for the complex topography of Switzerland. Differences among the WGPs are small compared to the biases inherited from the sustained-wind part in the WGP formulations. All WGPs transform overestimated peak sustained winds into underestimated peak gusts, which points to an underrepresentation of the turbulent part in the WGP formulations. The range of simulated peak gusts from downscaling all 20CR ensemble members does not reliably include the observed peak gust, indicating limited benefit in applying an ensemble approach. Despite the limitations, we infer that with spatial optimisations of the simulation (e.g. by bias correction or adaptation of the WGP schemes), downscaling of 20CR input is an efficient option for high-resolution assessments of windstorm hazard and risk in Switzerland.

From global circulation to local flood loss: Coupling models across the scales

Comprehensive flood risk modeling is crucial for understanding, assessing, and mitigating flood risk. Modeling extreme events is a well-established practice in the atmospheric and hydrological sciences and in the insurance industry. Several specialized models are used to research extreme events including atmospheric circulation models, hydrological models, hydrodynamic models, and damage and loss models. Although these model types are well established, and coupling two to three of these models has been successful, no assessment of a full and comprehensive model chain from the atmospheric to local scale flood loss models has been conducted. The present study introduces a model chain setup incorporating a GCM/RCM to model atmospheric processes, a hydrological model to estimate the catchments runoff reaction to precipitation inputs, a hydrodynamic model to identify flood-affected areas, and a damage and loss model to estimate flood losses. Such coupling requires building interfaces between the individual models that are coherent in terms of spatial and temporal resolution and therefore calls for several pre- and post-processing steps for the individual models as well as for a computationally efficient strategy to identify and model extreme events. The results show that a coupled model chain allows for good representation of runoff for both long-term runoff characteristics and extreme events, provided a bias correction on precipitation input is applied. While the presented approach for deriving loss estimations for particular extreme events leads to reasonable results, two issues have been identified that need to be considered in further applications: (i) the identification of extreme events in long-term GCM simulations for downscaling and (ii) the representativeness of the vulnerability functions for local conditions.