SER REQUIREMENTS FROM THE SOLAR SECTOR. Concentrating solar power (CSP) systems use lenses or mirrors and tracking systems to focus a large area of sunlight onto a small area. A working fluid is heated by the concentrated sunlight, and this thermal energy can be stored or immediately used to produce electricity via a steam turbine. Alternatively, concentrating photovoltaics (CPV) are a future technology with growing interest among industries, where sunlight is concentrated on smaller and highly

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... efficient but rather expensive photovoltaic cells. Concentrating technologies utilize direct normal irradiance (DNI), which is the direct irradiance on the normal plane with respect to the incoming beam. Typically, DNI is measured as the incoming irradiance from the Sun's disc together with circumsolar diffuse irradiance within a cone of 2.5° around the Sun's center (WMO 2010) . Sunlight is the fuel for each solar energy conversion system. Like any generation source, knowledge about the fuel's quality and future reliability is essential for an accurate estimate of technical system performance and financial viability of a project. For site selection, choosing the optimum energy conversion technology, or designing systems for specific locations, it is necessary to understand the long-term spatial and temporal variability of available solar resources. For these applications long-term annual or monthly irradiation sums together with accurate frequency distributions of solar irradiance are needed and provided with the help of satellite data (Cano et al. 1986; Beyer et al. 1996; Rigollier et al. 2004 ). However, short-and medium-term forecasts of the solar resource will remain essential to the plant's efficient operations and its integration into the electricity grid throughout its lifetime. It has to be noted that users from the nonconcentrating photovoltaic technology sector require a high global irradiance forecast accuracy. This can mainly be achieved through high cloud forecast accuracy, while aerosols are of only minor importance for this purpose. On the other hand, users from the CSP sector need a high DNI forecast accuracy especially in cloud-free cases with high DNI. Additionally, CSP users request a good forecast on the occurrence of low DNI cases-which refers mainly to a good water cloud mask forecast-and a good forecast of medium DNI cases-which refers to the cirrus cloud optical properties forecast. CSP technologies generally operate only in areas with high DNI and small cloud cover. Therefore, depending on the geographical region of interest and its vicinity to global aerosol sources, the priority is set either on good aerosol or cirrus forecasts. This paper focuses on the aerosol forecast accuracy, while assessing the requirements on cirrus clouds and the modeling capabilities in today's NWP would be a separate subject. CSP electrical energy production can be calculated by using a power plant model and DNI as an input parameter. The power plant model has to simulate 903 JUNE 2013 AMERICAN METEOROLOGICAL SOCIETY | the thermal state of the heat transfer fluid and its pumping through the solar field; the hot and cold heat storage tank's status; heat exchangers used between the solar field, tanks, and the turbine; technical turbine specifics; and, finally, a model of the manual and interactive control of the power plant by its operator team (e.g., Wittmann et al. 2008; Klein et al. 2010; Wagner and Gilman 2011) . The strong dependency between DNI and CSP electricity production makes forecasting of direct solar irradiance essential (Pulvermüller et al. 2009; Wittmann et al. 2008 ). In the Spanish electricity market, for example, the hourly electrical energy production forecast for a given day has to be delivered on the previous day before 1000 LT (Ministerio de Industria, Turismo y Comercio 2007). A high-quality forecasting system reduces the power plant operator's risk of penalty payments due to inaccurate production forecasts and helps the transmission grid operator to keep operations stable. According to the Spanish regulation, penalties apply to cover additional costs occurring for the electricity grid operator in case of inaccurate electricity production forecasts provided by the power plant operator. For example, in case of a lower production than predicted in a certain hour of the day, the electricity grid operator might need to purchase additional electricity from other sources on the short-term electricity market. These extra costs can be forwarded to the power plant operator as a penalty. Penalties may apply if production forecasts are too small-resulting in additional purchase needs-or too high-resulting in additional selling needs at the grid operator's side. Penalties apply only if costs occurred in reality-for example, a lower production than predicted, which occurs in a situation with lower electricity consumption than predicted, might not cause any additional purchase needs and therefore no costs. Kraas et al. (2010Kraas et al. ( , 2011 analyzed how a good DNI forecast can enhance the profitability of a power plant when operating at a day-ahead electricity market. In their case study for a power plant in southern Spain, a relative DNI forecasting error magnitude of 10%-20% and 20%-30% respectively led to €1.5 (MWh) -1 and €2.5 (MWh) -1 penalties in a reference year based on actual market conditions. A 10% improvement in forecasting leads to a penalty reduction of about 7%. Additionally, an accurate production forecast can increase plant profits by optimizing energy dispatch into the time periods of greatest value on the electricity markets. The current state of the art in NWP provides rather inaccurate DNI forecasts. Lara-Fanego et al. (2012) found a relative RMSE of 60% for hourly DNI forecasts in Spain using an Advanced Research Weather Research and Forecasting model (ARW-WRF) (version 3) model implementation for all sky conditions (cloudy as well as cloud free). In overcast skies, knowledge of cloud cover and type is most important. Nevertheless, in high solar resource regions as the Mediterranean and northern Africa, because less cloudy aerosol loading is the most critical atmospheric parameter since up to 30% of additional direct irradiance extinction have been reported (e.g., Wittmann et al. 2008) . In dust outbreak events, the extinction of DNI reaches even up to 100%. Breitkreuz et al. (2009) compared direct irradiances calculated from Aerosol Robotic Network (AERONET) measurements, the European Centre for Medium-Range Weather Forecasts (ECMWF) operational model, and forecasted aerosol optical depth (AOD) of the European Dispersion and Deposition model (EURAD)-based AOD forecasts in order to quantify the effects of varying AOD forecast quality on solar energy applications. They show that a chemical transport model designed for air quality research is strongly needed for solar irradiance forecasting in clear-sky conditions. It improves the relative RMSE from 31% to 19% in clear-sky conditions. As pa r t of t he Monitor i ng At mospher ic Composition and Climate (MACC) project within the European Union's Global Monitoring of Environment and Security (GMES) program, the ECMWF Integrated Forecast System (IFS) has recently been modified to include a chemical weather prediction suite, which provides an analysis and subsequent forecast of aerosols (Benedetti et al. 2009 ; Morcrette