9 research outputs found

    Covariability of seasonal temperature and precipitation over the Iberian Peninsula in high-resolution regional climate simulations (1001–2099)

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    recipitation and surface temperature are interdependent variables, both as a response to atmospheric dynamics and due to intrinsic thermodynamic relationships and feedbacks between them. This study analyzes the covariability of seasonaltemperature (T) and precipitation (P) across the Iberian Peninsula(IP)usingregional climate paleosimulations for the period 1001–1990, driven by reconstructions of external forcings. Future climate (1990–2099) was simulated according to SRES scenarios A2 and B2. These simulations enable exploring, at high spatial resolution, robust and physically consistent relationships. In winter, positive P-T correlations dominate west-central IP (Pearson correlation coef ficient ρ= +0.43, for 1001–1990), due to prevalent cold-dry and warm-wet conditions, while this relationship weakens and become negative towards mountainous, northern and eastern regions. In autumn, negative correlations appear in similar regions as in winter, whereas for summer they extend also to the N/NW of the IP. In spring, the whole IP depicts significant negative correlations, strongest for eastern regions (ρ=−0.51). This is due to prevalent frequency of warm-dry and cold-wet modes in these regions and seasons. At the temporal scale, regional correlation series between seasonal anomalies of temperature and precipitation (assessed in 31 years running windows in 1001–1990) show very large multidecadal variability. For winter and spring, periodicities of about 50– 60 years arise. The frequency of warm-dry and cold-wet modes appears correlated with the North Atlantic Oscillation (NAO), explaining mainly co-variability changes in spring. For winter and some regions in autumn, maximum and minimum P-T correlations appear in periods with enhanced meridional or easterly circulation (low or high pressure anomalies in the Mediterranean and Europe). In spring and summer, the Atlantic Multidecadal Oscillation shows some fingerprint on the frequency of warm/cold modes. For future scenarios, an intensification of the negative P-T relationship is generally found, as a result of an increased frequency of the warm-dry mode

    Future changes, or lack thereof, in the temporal variability of the combined wind-plus-solar power production in Europe

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    Here we present the first assessment of climate change impacts on the temporal variability of the joint production of wind and solar photovoltaic (PV) power across Europe. For that we adopted regional and continental perspectives (assuming a single European electricity grid), considered several temporal frequencies (from daily to annual), used state-of-the-art regional climate projections together with a climate-production model, and assumed a future massive deployment of wind and PV power installations. Results support that the spatio-temporal complementarity between the wind and solar resources helps to minimize the temporal variability of the combined production under both present (1971 e2000) and future (2070e2099) climate conditions similarly. Thus the projected changes are overall negligible (well below ±5%). However, an additional assessment of theoretical upper/bottom bounds for these changes indicated significant potential increases in the stability of the joint production ranging from 5 to 25% across regions, 15% at the continental scale. This would be subordinated to the feasibility of reaching, with the future deployment strategies, individual wind and PV power production series with a perfect temporal anticorrelation. These results may encourage stakeholders to take holistically optimized decisions

    The Effect of Heat Waves and Drought on Surface Wind Circulations in the Northeast of the Iberian Peninsula during the Summer of 2003

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    Variations in the diurnal wind pattern associated with heat waves and drought conditions are investigated climatologically at a regional level (northeast of the Iberian Peninsula). The study, based on high-density observational evidence and fine spatial-scale mesoscale modeling for the 1992–2004 period, shows that wind speed can decrease up to 22% under situations characterized by extremely high temperatures and severe drought, such as the European summer of 2003. By examining the role of the different atmospheric scales of motion that determine the wind diurnal variability, it is found that the 2003 synoptic conditions are the main driver for changes in the wind speed field. In turn, these changes are modulated by mesoscale circulations influenced by the soil moisture availability. The results have implications for broad regional modeling studies of current climate and climate change simulations in as much as the study demonstrates that a correct representation of local soil moisture conditions impacts atmospheric circulation and therefore the regional climate stat

    An evaluation of WRF's ability to reproduce the surface wind over complex terrain based on typical circulation patterns.

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    [1] The performance of the Weather Research and Forecasting (WRF) model to reproduce the surface wind circulations over complex terrain is examined. The atmospheric evolution is simulated using two versions of the WRF model during an over 13¿year period (1992 to 2005) over a complex terrain region located in the northeast of the Iberian Peninsula. A high horizontal resolution of 2km is used to provide an accurate representation of the terrain features. The multiyear evaluation focuses on the analysis of the accuracy displayed by the WRF simulations to reproduce the wind field of the six typical wind patterns (WPs) identified over the area in a previous observational work. Each pattern contains a high number of days which allows one to reach solid conclusions regarding the model performance. The accuracy of the simulations to reproduce the wind field under representative synoptic situations, or pressure patterns (PPs), of the Iberian Peninsula is also inspected in order to diagnose errors as a function of the large-scale situation. The evaluation is accomplished using daily averages in order to inspect the ability of WRF to reproduce the surface flow as a result of the interaction between the synoptic scale and the regional topography. Results indicate that model errors can originate from problems in the initial and lateral boundary conditions, misrepresentations at the synoptic scale, or the realism of the topographic features

    Surface Wind Regionalization over Complex Terrain: Evaluation and Analysis of a High-Resolution WRF Simulation

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    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

    Estimating 750 years of temperature variations and uncertainties in the Pyrenees by tree-ring reconstructions and climate simulations.

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    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

    Characterization of the wind speed variability and future change in the Iberian Peninsula and the Balearic Islands

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    Wind energy is susceptible to global climate change because it could alter the wind patterns. Then, improvement of our knowledge of wind field variability is crucial to optimize the use of wind resources in a given region. Here, we quantify the effects of climate change on the surface wind speed field over the Iberian Peninsula and Balearic Islands using an ensemble of four regional climate models driven by a global climate model. Regions of the Iberian Peninsula with coherent temporal variability in wind speed in each of the models are identified and analysed using cluster analysis. These regions are continuous in each model and exhibit a high degree of overlap across the models. The models forced by the European Reanalysis Interim (ERA-Interim) reanalysis are validated against the European Climate Assessment and Dataset wind. We find that regional models are able to simulate with reasonable skill the spatial distribution of wind speed at 10 m in the Iberian Peninsula, identifying areas with common wind variability. Under the Special Report on Emissions Scenarios (SRES) A1B climate change scenario, the wind speed in the identified regions for 2031–2050 is up to 5% less than during the 1980–1999 control period for all models. The models also agree on the time evolution of spatially averaged wind speed in each region, showing a negative trend for all of them. These tendencies depend on the region and are significant at p = 5% or slightly more for annual trends, while seasonal trends are not significant in most of the regions and seasons. Copyright © 2015 John Wiley & Sons, Ltd
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