Climate is changing and will continue to change. Societies and ecosystems are affected by and often depend on climate and its variability. Already in 1992, the United Nations Framework Convention on Climate Change stated that all parties shall “cooperate in preparing for adaptation to the impacts of climate change” (United Nations 1992). Over the last decades, several countries have developed national adaptation strategies. The EU strategy on adaptation to climate change (European Commission 2013), for instance, acknowledges the need to take adaptation measures at all levels ranging from national to regional and local levels. The Global Framework for Climate Services (GFCS), established in 2009, sets out to develop and communicate climate information to “enable better management of the risks of climate variability and change and adaptation to climate change” (http://www.wmo.int/gfcs/vision). In short, there is an urgent demand for scientifically credible climate change information, in particular at the regional scale (Hewitt et al. 2012). One approach to obtain information about regional climate change is downscaling of global climate projections. In fact, a plethora of different data products have already been made available via internet portals.

Yet the provision of regional climate change information is one of the big challenges in climate science (Schiermeier 2010) and still a subject of essentially basic research (Hewitson et al. 2014). A Nature editorial prominently pointed out that “certainty is what current-generation regional studies cannot yet provide” (Nature 2010). Kundzewicz and Stakhiv (2010) argue that climate models have originally been developed to guide mitigation decisions. They could provide a broad picture of global climate change but would not yet be skillful to serve as input for regional adaptation planning. Kerr (2011b) brings forward a range of arguments which have been issued against current downscaling practice, and, in a later piece (Kerr 2011a), discusses the challenges of providing actionable climate information.

Against this background, the book at hand attempts to provide a reference for a range of approaches and methods often summarised as statistical downscaling. At the same time, the book aims to put the more technical issues of statistical downscaling into the broader context of user needs, regional climate modelling uncertainties and limitations, and good scientific practice. To begin with, we would like to sketch the scientific idea of statistical downscaling and then give some guidance on how to best approach this book.