Juan Pedro Montavez

Natural and anthropogenic modes of surface temperature variations in the last thousand years

The spatial patterns of surface air-temperature variations in the period 1000 to 2100, simulated with the ECHO-G atmosphere-ocean coupled model, are analyzed. The model was driven by solar, volcanic and greenhouse gas forcing. The leading mode of temperature variability in the preindustrial period represents an almost global coherent variation of temperatures, with larger amplitudes over the continents and Northern Hemisphere. This mode also describes a large part of the spatial structure of the warming simulated in the 21st century. However, in the 21st century, regional departures from this spatial structure are also present and can be ascribed to atmospheric circulation responses to anthropogenic forcing in the last decades of the 21st century.

Surface wind regionalization over complex terrain: Evaluation and analysis of a high-resolution WRF simulation

This study analyzes the daily-mean surface wind variability over an area characterized by complex topography through comparing observations and a 2-km-spatial-resolution simulation performed with the Weather Research and Forecasting (WRF) model for the period 1992–2005. The evaluation focuses on the performance of the simulation to reproduce the wind variability within subregions identified from observations over the 1999–2002 period in a previous study. By comparing with wind observations, the model results show the ability of the WRF dynamical downscaling over a region of complex terrain. The higher spatiotemporal resolution of the WRF simulation is used to evaluate the extent to which the length of the observational period and the limited spatial coverage of observations condition one’s understanding of the wind variability over the area. The subregions identified with the simulation during the 1992–2005 period are similar to those identified with observations (1999–2002). In addition, the reduced number of stations reasonably represents the spatial wind variability over the area. However, the analysis of the full spatial dimension simulated by the model suggests that observational coverage could be improved in some subregions. The approach adopted here can have a direct application to the design of observational networks.

Sensitivity of the MM5 mesoscale model to physical parameterizations for regional climate studies: Annual cycle

We present an analysis of the sensitivity to different physical parameterizations of a high-resolution simulation of the MM5 mesoscale model over the Iberian Peninsula. Several (16) 5-year runs of the MM5 model with varying parameterizations of microphysics, cumulus, planetary boundary layer and longwave radiation have been carried out. The results have been extensively compared with observational precipitation and surface temperature data. The parameterization uncertainty has also been compared with that related to the boundary conditions and the varying observational data sets. The annual cycles of precipitation and surface temperature are well reproduced. The summer season presents the largest deviations, with a 5 K cold bias in the southeast and noticeable precipitation errors over mountain areas. The cold bias seems to be related to the surface, probably because of the excessive moisture availability of the five-layer soil scheme used. No parameterization combination was found to perform best in simulating both precipitation and surface temperature in every season and subregion. The Kain-Fritsch cumulus scheme was found to produce unrealistically high summer precipitation. The longwave radiation parameterizations tested were found to have little impact on our target variables. Other factors, such as the choice of boundary conditions, have an impact on the results as large as the selection of parameterizations. The range of variability in the MM5 physics ensemble is of the same order of magnitude as the observational uncertainty, except in summer, when it is larger and probably related to the inaccuracy of the model to reproduce the summer precipitation over the area.

The Impact of the North Atlantic Oscillation on Renewable Energy Resources in Southwestern Europe

AbstractEurope is investing considerably in renewable energies for a sustainable future, with both Iberian countries (Portugal and Spain) promoting significantly new hydropower, wind, and solar plants. The climate variability in this area is highly controlled by just a few large-scale teleconnection modes. However, the relationship between these modes and the renewable climate-dependent energy resources has not yet been established in detail. The objective of this study is to evaluate the impact of the North Atlantic Oscillation (NAO) on the interannual variability of the main and primary renewable energy resources in Iberia. This is achieved through a holistic assessment that is based on a 10-km-resolution climate simulation spanning the period 1959–2007 that provides physically consistent data of the various magnitudes involved. A monthly analysis for the extended winter (October–March) months shows that negative NAO phases enhance wind speeds (10%–15%) and, thereby, wind power (estimated around 30% at ...

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.

Quality assurance of surface wind observations from automated weather stations

Abstract Meteorological data of good quality are important for understanding both global and regional climates. In this respect, great efforts have been made to evaluate temperature- and precipitation-related records. This study summarizes the evaluations made to date of the quality of wind speed and direction records acquired at 41 automated weather stations in the northeast of the Iberian Peninsula. Observations were acquired from 1992 to 2005 at a temporal resolution of 10 and 30 min. A quality assurance system was imposed to screen the records for 1) manipulation errors associated with storage and management of the data, 2) consistency limits to ensure that observations are within their natural limits of variation, and 3) temporal consistency to assess abnormally low/high variations in the individual time series. In addition, the most important biases of the dataset are analyzed and corrected wherever possible. A total of 1.8% wind speed and 3.7% wind direction records was assumed invalid, pointing to...

Surface Wind Regionalization in Complex Terrain

Abstract Daily wind variability in the Comunidad Foral de Navarra in northern Spain was studied using wind observations at 35 locations to derive subregions with homogeneous temporal variability. Two different methodologies based on principal component analysis were used to regionalize: 1) cluster analysis and 2) the rotation of the selected principal components. Both methodologies produce similar results and lead to regions that are in general agreement with the topographic features of the terrain. The meridional wind variability is similar in all subregions, whereas zonal wind variability is responsible for differences between them. The spectral analysis of wind variability within each subregion reveals a dominant annual cycle and the varying presence of higher-frequency contributions in the subregions. The valley subregions tend to present more variability at high frequencies than do higher-altitude sites. Last, the influence of large-scale dynamics on regional wind variability is explored by studying ...

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.

The impact of climate change on photovoltaic power generation in Europe

Ambitious climate change mitigation plans call for a significant increase in the use of renewables, which could, however, make the supply system more vulnerable to climate variability and changes. Here we evaluate climate change impacts on solar photovoltaic (PV) power in Europe using the recent EURO-CORDEX ensemble of high-resolution climate projections together with a PV power production model and assuming a well-developed European PV power fleet. Results indicate that the alteration of solar PV supply by the end of this century compared with the estimations made under current climate conditions should be in the range (−14%;+2%), with the largest decreases in Northern countries. Temporal stability of power generation does not appear as strongly affected in future climate scenarios either, even showing a slight positive trend in Southern countries. Therefore, despite small decreases in production expected in some parts of Europe, climate change is unlikely to threaten the European PV sector.

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.