J. Tovar-Pescador

On the use of the digital elevation model to estimate the solar radiation in areas of complex topography

The development of solar energy as a power source in the next few years requires reliable estimation of available solar energy resources. At local scales, topography is the most important factor in determining the distribution of solar radiation at the surface. Interpolation techniques are usually employed to estimate solar radiation where stations are not available, but their usefulness is limited where topography is an important source of variability. The use of satellite data and more recently of models based on techniques GIS, have contributed to solve this difficulty. In this work the usefulness of a digital elevation model (DEM) in providing topographic information for the estimation of solar radiation in areas of complex topography is analysed. Daily global radiation values were generated using the Solar Analyst software, which uses topographic information to generate radiation data. The generated data were compared with the experimental data obtained from 14 radiometric stations located within the Sierra Nevada Natural Park (southern Spain), an area of complex topography. Results show the usefulness of the topographic information derived from a DEM to estimate the solar radiation in areas of complex topography. Nevertheless, results depend on the DEM resolution and it is important that other factors, such as the albedo, should also be taken into account to obtain better estimates. Copyright

Analysis of WRF Model Wind Estimate Sensitivity to Physics Parameterization Choice and Terrain Representation in Andalusia (Southern Spain)

AbstractThis paper reports on an evaluation of the relative roles of choice of parameterization scheme and terrain representation in the Weather Research and Forecasting (WRF) mesoscale model, in the context of a regional wind resource assessment. As a first step, 32 configurations using two different schemes for microphysics, cumulus, planetary boundary layer (PBL), or shortwave and longwave radiation were evaluated. In a second step, wind estimates that were obtained from various experiments with different spatial resolution (1, 3, and 9 km) were assessed. Estimates were tested against data from four stations, located in southern Spain, that provided hourly wind speed and direction data at 40 m above ground level. Results from the first analysis showed that wind speed standard deviation (STD) and bias values were mainly sensitive to the PBL parameterization selection, with STD differences up to 10% and bias differences between −15% and 10%. The second analysis showed a weak influence of spatial resoluti...

Analysis of Spatiotemporal Balancing between Wind and Solar Energy Resources in the Southern Iberian Peninsula

AbstractElectricity from wind and, to a lesser extent, solar energy is intermittent and not controllable. Unlike conventional power generation, therefore, this electricity is not suitable to supply base-load electric power. In the future, with greater penetration of these renewable sources, intermittency and control problems will become critical. Here, the authors explore the use of canonical correlation analysis (CCA) for analyzing spatiotemporal balancing between regional solar and wind energy resources. The CCA allows optimal distribution of wind farms and solar energy plants across a territory to minimize the variability of total energy input into the power supply system. The method was tested in the southern half of the Iberian Peninsula, a region covering about 350 000 km2. The authors used daily-integrated wind and solar energy estimates in 2007 from the Weather Research and Forecasting (WRF) mesoscale model, at a spatial resolution of 9 km. Results showed valuable balancing patterns in the study r...

A High-Resolution Topographic Correction Method for Clear-Sky Solar Irradiance Derived with a Numerical Weather Prediction Model

AbstractRugged terrain is a source of variability in the incoming solar radiation field, but the influence of terrain is still not properly included by most current numerical weather prediction (NWP) models. In this work, a downscaling postprocessing method for NWP-model solar irradiance through terrain effects is presented. It allows one to decrease the estimation bias caused by terrain shading and sky-view reduction, and to account for elevation variability, surface orientation, and surface albedo. The method has been applied to a case study in southern Spain using the Weather Research and Forecasting (WRF) mesoscale model with a spatial resolution of 30 arc s, resulting in disaggregated maps of 3 arc s. The validation was based on a radiometric network made of eight stations located in the Natural Park of Sierra Magina over an area of roughly 30 × 35 km2 and 12 carefully selected cloudless days during a year. Three of the stations were equipped with tilted pyranometers. Their inclination and aspect wer...

Modelling the Statistical Properties of Solar Radiation and Proposal of a Technique Based on Boltzmann Statistics

Solar radiation affects all the Earth’s processes related to the environment and plays a fundamental role in the development of human activities. Among these processes, solar radiation influences water evaporation into the atmosphere and, consequently, also humidity of ground and air. Therefore, solar radiation strongly affects the agricultural and ecological processes. The knowledge of solar radiation is also important for solar energy conversion systems, such as photovoltaic, thermal and thermosyphon applications. Finally, solar radiation determines the Earth’s energy balance and, therefore even, it is a key parameter for the understanding of the climatic change. Solar radiation has been measured for a long time, but even today there are many unknown characteristics of its behaviour for remote areas with no direct measurement. Along the last century, and particularly in its second half, a notably theoretical and experimental research effort has been conducted to develop solar energy conversion devices. These studies have contributed to great technological know-how in the use of solar energy and, nowadays, thermoelectric and photovoltaic solar energy production facilities are found in many countries of the world. The need of use of renewable energies, particularly in recent years, has contributed to the use of solar energy, too. The latter represents a small amount in relation to other type of energies, but a significant increase of solar facilities both thermal and photovoltaic is foreseen for the next years. Data given by the Official Energy Statistics of the U.S. Government in February 2007 [Report DOE/EIA-0383(2007) table 16] foresee a great increase in the renewable energy sector during the next years. Particularly, photovoltaic solar energy will undergo the most important increases between 2005 and 2030.

Assessing the Surface Solar Radiation Budget in the WRF Model: A Spatiotemporal Analysis of the Bias and Its Causes

AbstractSolar radiation plays a key role in the atmospheric system but its distribution throughout the atmosphere and at the surface is still very uncertain in atmospheric models, and further assessment is required. In this study, the shortwave downward total solar radiation flux (SWD) predicted by the Weather Research and Forecasting (WRF) Model at the surface is validated over Spain for a 10-yr period based on observations of a network of 52 radiometric stations. In addition to the traditional pointwise validation of modeled data, an original spatially continuous evaluation of the SWD bias is also conducted using a principal component analysis. Overall, WRF overestimates the mean observed SWD by 28.9 W m−2, while the bias of ERA-Interim, which provides initial and boundary conditions to WRF, is only 15.0 W m−2. An important part of the WRF SWD bias seems to be related to a very low cumulus cloud amount in the model and, possibly, a misrepresentation of the radiative impact of this type of cloud.

Evaluation of DNI forecast based on the WRF mesoscale atmospheric model for CPV applications

The integration of large-scale solar electricity production into the energy supply structures depends es-sentially on the precise advance knowledge of the available resource. Numerical weather prediction (NWP) models provide a reliable and comprehensive tool for short-and medium-range solar radiation forecasts. The methodology followed here is based on the WRF model. For CPV systems the primary energy source is the direct normal irradi-ance (DNI), which is dramatically affected by the presence of clouds. Therefore, the reliability of DNI forecasts is directly related to the accuracy of cloud information. Two aspects of this issue are discussed here: (i) the effect of the model’s horizontal spatial resolution; and (ii) the effect of the spatial aggregation of the predicted irradiance. Results show that there is no improvement in DNI forecast skill at high spatial resolutions, except under clear-sky conditions. Furthermore, the spatial averaging of the predicted irradiance noticeably reduces their initial e...

One-Day-Ahead Streamflow Forecasting Using Artificial Neural Networks and a Meteorological Mesoscale Model

AbstractAn approach to modeling daily flows using artificial neural networks (ANNs) is presented. In addition to previous streamflow values and mean areal rainfall sequences, a new runoff index was used and tested as ANN input. This runoff index was generated as a combination of two output variables of the weather research and forecasting (WRF) mesoscale model, which contains an integrated land surface model. Inclusion of the new index improved ANN model performance and increased simulation skill. A case study was conducted for the northeast Guadalquivir catchment in southeastern Spain. Accurate one-day-ahead streamflow forecasts were achieved in terms of overall fit and timing of peaks. Model performance was satisfactory, with a persistence index (PI) equal to 0.81 and a Nash–Sutcliffe efficiency R2 equal to 0.95 for an independent data set. These favorable results prove that WRF outputs contain useful information on the hydrologic state of a basin and can therefore be used as valuable ANN inputs.

The Impact of the NAO on the Solar and Wind Energy Resources in the Mediterranean Area

The influence of the NAO on the solar and wind energy resources in the Mediterranean area, in particular, and over the whole North Atlantic area, in general, has been explored based on the analysis of 20 years of reanalysis and satellite data. The analysis was carried out for the winter and annual periods and proved the existence of a marked influence of the NAO pattern on the spatial and temporal variability of the solar and wind energy resources in the study area. Particularly, the NAO signature on the solar/wind energy resources was found to be a north-south dipolar pattern, with the positive/negative centre over the Mediterranean area. Although the spatial patterns obtained are similar, the nature of the relationship obtained for wind energy was found to be less linear and more complex than that attained for solar energy. A composite analysis revealed that interannual variability of the solar and wind energy resources in the Mediterranean area can reach values above 20% in winter and 10% in the annual case associated with changes in the NAO phase. Finally, the analysis of the spatial patterns of the NAO influence on the solar and wind energy resources revealed the existence of spatial and local balancing between these two energy resources in the study area. Results are of interest regarding the estimation of the expected interannual variability of the wind farms and solar plants production in the study region.

Macroscopic cloud properties in the WRF NWP model. An assessment using sky camera and ceilometer data

The ability of six microphysical parameterizations included in the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model to represent various macroscopic cloud characteristics at multiple spatial and temporal resolutions is investigated. In particular, the model prediction skills of cloud occurrence, cloud base height, and cloud cover are assessed. When it is possible, the results are provided separately for low-, middle-, and high-level clouds. The microphysical parameterizations assessed are WRF single-moment six-class, Thompson, Milbrandt-Yau, Morrison, Stony Brook University, and National Severe Storms Laboratory double moment. The evaluated macroscopic cloud properties are determined based on the model cloud fractions. Two cloud fraction approaches, namely, a binary cloud fraction and a continuous cloud fraction, are investigated. Model cloud cover is determined by overlapping the vertically distributed cloud fractions following three different strategies. The evaluation is conducted based on observations gathered with a ceilometer and a sky camera located in Jaen (southern Spain). The results prove that the reliability of the WRF model mostly depends on the considered cloud parameter, cloud level, and spatiotemporal resolution. In our test bed, it is found that WRF model tends to (i) overpredict the occurrence of high-level clouds irrespectively of the spatial resolution, (ii) underestimate the cloud base height, and (iii) overestimate the cloud cover. Overall, the best cloud estimates are found for finer spatial resolutions (1.3 and 4 km with slight differences between them) and coarser temporal resolutions. The roles of the parameterization choice of the microphysics scheme and the cloud overlapping strategy are, in general, less relevant.