Downscaling Techniques For High Resolution Climate Projections

A practical guide to understanding, using and producing downscaled climate data, for researchers, graduate students, policy makers and practitioners.

Empirical-statistical downscaling (ESD) is a method for estimating how local climatic variables are affected by large-scale climatic conditions. ESD has been applied to local climate/weather studies for years, but there are few ? if any ? textbooks on the subject. It is also anticipated that ESD will become more important and commonplace in the future, as anthropogenic global warming proceeds. Thus, a textbook on ESD will be important for next-generation climate scientists.

A comprehensive and practical guide, providing technical background and user context for researchers, graduate students, practitioners and decision makers. This book presents the main approaches and describes their underlying assumptions, skill and limitations. Guidelines for the application of downscaling and the use of downscaled information in practice complete the volume.

​This book is an update of the first BACC assessment, published in 2008. It offers new and updated scientific findings in regional climate research for the Baltic Sea basin. These include climate changes since the last glaciation (approx. 12,000 years ago), changes in the recent past (the last 200 years), climate projections up until 2100 using state-of-the-art regional climate models and an assessment of climate-change impacts on terrestrial, freshwater and marine ecosystems. There are dedicated new chapters on sea-level rise, coastal erosion and impacts on urban areas. A new set of chapters deals with possible causes of regional climate change along with the global effects of increased greenhouse gas concentrations, namely atmospheric aerosols and land-cover change. The evidence collected and presented in this book shows that the regional climate has already started to change and this is expected to continue. Projections of potential future climates show that the region will probably become considerably warmer and wetter in some parts, but dryer in others. Terrestrial and aquatic ecosystems have already shown adjustments to increased temperatures and are expected to undergo further changes in the near future. The BACC II Author Team consists of 141 scientists from 12 countries, covering various disciplines related to climate research and related impacts. BACC II is a project of the Baltic Earth research network and contributes to the World Climate Research Programme.

As climate change has pushed climate patterns outside of historic norms, the need for detailed projections is growing across all sectors, including agriculture, insurance, and emergency preparedness planning. A National Strategy for Advancing Climate Modeling emphasizes the needs for climate models to evolve substantially in order to deliver climate projections at the scale and level of detail desired by decision makers, this report finds. Despite much recent progress in developing reliable climate models, there are still efficiencies to be gained across the large and diverse U.S. climate modeling community. Evolving to a more unified climate modeling enterprise-in particular by developing a common software infrastructure shared by all climate researchers and holding an annual climate modeling forum-could help speed progress. Throughout this report, several recommendations and guidelines are outlined to accelerate progress in climate modeling. The U.S. supports several climate models, each conceptually similar but with components assembled with slightly different software and data output standards. If all U.S. climate models employed a single software system, it could simplify testing and migration to new computing hardware, and allow scientists to compare and interchange climate model components, such as land surface or ocean models. A National Strategy for Advancing Climate Modeling recommends an annual U.S. climate modeling forum be held to help bring the nation's diverse modeling communities together with the users of climate data. This would provide climate model data users with an opportunity to learn more about the strengths and limitations of models and provide input to modelers on their needs and provide a venue for discussions of priorities for the national modeling enterprise, and bring disparate climate science communities together to design common modeling experiments. In addition, A National Strategy for Advancing Climate Modeling explains that U.S. climate modelers will need to address an expanding breadth of scientific problems while striving to make predictions and projections more accurate. Progress toward this goal can be made through a combination of increasing model resolution, advances in observations, improved model physics, and more complete representations of the Earth system. To address the computing needs of the climate modeling community, the report suggests a two-pronged approach that involves the continued use and upgrading of existing climate-dedicated computing resources at modeling centers, together with research on how to effectively exploit the more complex computer hardware systems expected over the next 10 to 20 years.

Climate projections are in immediate demand by scientists, governments and non-governmental organizations. In climate-sensitive sectors such as forestry and agriculture, the biological relevance of the climate data is of equal importance as its resolution and accuracy. In the last decades, continental-scale high-resolution climate projections have become globally available. Majority of these climate surfaces are empirically downscaled directly from Global climate models. Downscaling is a general concept that embraces various methods for increasing spatial resolution and reduces some of the biases in order to improve the usability of climate scenarios. Two major approaches to downscaling climate data are, statistical and dynamic. For robust predictions, a dynamic approach is often recommended because it is based on the dynamical and physical processes that govern the weather and thus the climate.EURO-CORDEX is an initiative of the World Climate Research Program for coordinating dynamic regional downscaling of the global climate projections from the CMIP5 (Coupled Model Intercomparison Project Phase 5. We used five bias-corrected regional climate model (RCM) projections of daily temperature and precipitation from the EURO-CORDEX database and downscaled them from 10km resolution to 1km with the delta-algorithm of spatial downscaling. Using this approach we calculated 83 biologically relevant climate variables for both historic periods (mean of 1961-90) and future periods (2041-2060, 2061-2080, 2081-2100) under RCP4.5 and RCP8.5 scenarios. An evaluation with independent data from approximately 3000 weather stations across Europe showed promising results with high correlations between observed and predicted data. The dataset is available for free public use.