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The regional climate model (RCM) is a tool to fill the gap between the outcome of global climate model and the demand of regional government and society for regional climate information. The current Weather Research and Forecasting (WRF) RCM inherits several advantages of the original WRF model. For example, (1) it can be used for multiple scale applications from large eddy to planetary scale; (2) it can be coupled to other climate system component models; (3) it has multiple physical options for different purposes of research; and (4) it has parallel infrastructure to distinguish the scientific problems from engineering problems. In order to adapt WRF for long term integration for climate application, the model and its pre- and post-processors are modified in several aspects, including SST and other surface parameters treatment, and exponential relaxation lateral boundary. In this study, we also transferred a pre-released version of CAM3 radiation scheme that was first implemented into WRF by NCAR Regional Climate Modeling team to the WRF standard release versions (2.1.1 released as of November 8, 2005 and 2.1.2 released as of January 30, 2006). The preliminary investigation demonstrates that the model has shown the encouraging and promising results on simulating regional climate. The objective of this study is to investigate the hydrological cycle in the East Africa region. Through data analysis, the water channel in the East Africa region is determined. The moisture transport from the Indian Ocean is the main source of the water vapor for precipitation in "short rain" season from October to December (OND). The variability of the moisture transport directly results in the variability of precipitation in OND. The local soil moisture, which directly connects to evaporation, does not substantially contribute to precipitation in the region. To investigate the physical processes of the variability of the moisture transport, five seasonal simulations from September to D.

The regional climate model (RCM) is a tool to fill the gap between the outcome of global climate model and the demand of regional government and society for regional climate information.

In recent decades, science has experienced a revolutionary shift. The development and extensive application of computer modelling and simulation has transformed the knowledge‐making practices of scientific fields as diverse as astro‐physics, genetics, robotics and demography. This epistemic transformation has brought with it a simultaneous heightening of political relevance and a renewal of international policy agendas, raising crucial questions about the nature and application of simulation knowledges throughout public policy. Through a diverse range of case studies, spanning over a century of theoretical and practical developments in the atmospheric and environmental sciences, this book argues that computer modelling and simulation have substantially changed scientific and cultural practices and shaped the emergence of novel ‘cultures of prediction’. Making an innovative, interdisciplinary contribution to understanding the impact of computer modelling on research practice, institutional configurations and broader cultures, this volume will be essential reading for anyone interested in the past, present and future of climate change and the environmental sciences.

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.

In this book the authors consider the natural environment as an integrated system. The physical, chemical and biological processes that govern the behaviour of the environmental system can thus be understood through mathematical modelling, and their evolution can be studied by means of numerical simulation. The book contains a summary of various efficient approaches in atmospheric prediction, such as numerical weather prediction and statistical forecast of climate change, as well as other successful methods in land surface modelling. The authors explore new theories and methods in environment prediction such as systems analysis and information theory. Attention is given to new achievements in remote sensing tele-metering and geographic information systems.

This book provides a collection of the state-of-the-art methodologies and approaches suggested for detecting extremes, trend analysis, accounting for nonstationarities, and uncertainties associated with extreme value analysis in a changing climate. This volume is designed so that it can be used as the primary reference on the available methodologies for analysis of climate extremes. Furthermore, the book addresses current hydrometeorologic global data sets and their applications for global scale analysis of extremes. While the main objective is to deliver recent theoretical concepts, several case studies on extreme climate conditions are provided. Audience The book is suitable for teaching in graduate courses in the disciplines of Civil and Environmental Engineering, Earth System Science, Meteorology and Atmospheric Sciences.