Possible aerosol-cloud-precipitation effects over Germany are investigated using the COSMO model in a convection-permitting configuration close to the operational COSMO-DE. Aerosol effects on clouds and precipitation are modeled by using an advanced two-moment microphysical parameterization taking into account aerosol assumptions for cloud condensation nuclei (CCN) as well as ice nuclei (IN). Simulations of three summer seasons have been performed with various aerosol assumptions, and are analysed regarding surface precipitation, cloud properties, and the indirect aerosol effect on near-surface temperature. We find that the CCN and IN assumptions have a strong effect on cloud properties, like condensate amounts of cloud water, snow and rain as well as on the glaciation of the clouds, but the effects on surface precipitation are – when averaged over space and time – small. This robustness can only be understood by the combined action of microphysical and dynamical processes. On one hand, this shows that clouds can be interpreted as a buffered system where significant changes to environmental parameters, like aerosols, have little effect on the resulting surface precipitation. On the other hand, this buffering is not active for the radiative effects of clouds, and the changes in cloud properties due to aerosol perturbations may have a significant effect on radiation and near-surface temperature

Possible aerosol-cloud-precipitation effects over Germany are investigated using the COSMO model in a convection-permitting configuration close to the operational COSMO-DE. Aerosol effects on clouds and precipitation are modeled by using an advanced two-moment microphysical parameterization taking into account aerosol assumptions for cloud condensation nuclei (CCN) as well as ice nuclei (IN). Simulations of three summer seasons have been performed with various aerosol assumptions, and are analysed regarding surface precipitation, cloud properties, and the indirect aerosol effect on near-surface temperature. We find that the CCN and IN assumptions have a strong effect on cloud properties, like condensate amounts of cloud water, snow and rain as well as on the glaciation of the clouds, but the effects on surface precipitation are – when averaged over space and time – small. This robustness can only be understood by the combined action of microphysical and dynamical processes. On one hand, this shows that clouds can be interpreted as a buffered system where significant changes to environmental parameters, like aerosols, have little effect on the resulting surface precipitation. On the other hand, this buffering is not active for the radiative effects of clouds, and the changes in cloud properties due to aerosol perturbations have a significant effect on radiation and near-surface temperature

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Designing, financing, and operating successful solar heating, concentrating solar power, and photovoltaic systems requires reliable information about the solar resource available and its variability over time. In the past, seasonal and daily variability has been studied and understood; however, with new solar technologies becoming more important in energy supply grids, small time-scale effects are critical to successful deployment of these important low carbon technologies. A vital part of the bankability of solar projects is to understand the variability of the solar resource so that supply and storage technologies can be optimized. This handbook is the result of 10 years of international collaboration carried out by experts from the International Energy Agency's (IEA's) Solar Heating and Cooling (SHC), Solar PACES, and Photovoltaic Power Systems Technology Collaboration Programmes. Under IEA SHC Task 46: Solar Resource Assessment and Forecasting, experts from 11 countries produced information products and best practices on solar energy resources that will greatly benefit project developers and system operators as well as assist policymakers in advancing renewable energy programs worldwide.Meteorologists, mathematicians, solar technology specialists, and other key solar resource experts from around the world joined forces to further our understanding of the sun's temporal and spatial variability through benchmarking satellite-derived solar resource data and solar forecasts, developing best practices for measuring the solar resource, and conducting research to improve satellite-based algorithms. The results of IEA SHC Task 46 are useful to a wide range of users of solar heating and cooling, photovoltaics, and concentrating solar power systems and of building developers and owners as well as anyone else who needs to understand and predict sunlight for agricultural or other purposes.The earlier edition of the handbook, which was published in 2015, is used worldwide as a reference for each stage of a solar energy project. Since that time, there has been substantial growth in the interest in high-quality "bankable" solar resource data. This revision adds significant new methods so it will be even more useful. This publication is a summary that details the fundamentals of solar resources as well as captures the state of the art. For those wanting more depth, it also provides the references where more detailed information can be found. I would like to acknowledge the leadership of the National Renewable Energy Laboratory and express appreciation to the U.S. Department of Energy for producing the handbook and incorporating results from IEA SHC Task 46.