Richard Swinbank – författare

Based largely on an International Commission on Dynamical Meteorology (ICDM) workshop, this timely volume, written by leading researchers in the field, covers a range of important research issues related to high-impact weather and extreme climate events. Dynamical linkages between these extremes and various atmospheric and ocean phenomena are examined, including Atlantic Multidecadal, North Atlantic, and Madden-Julian Oscillations; Annular Modes; tropical cyclones; and Asian monsoons. This book also examines the predictability of high-impact weather and extreme climate events on multiple time scales. Highlighting recent research and new advances in the field, this book enhances understanding of dynamical and physical processes associated with these events to help managers and policy makers make informed decisions to manage risk and prevent or mitigate disasters. It also provides guidance on future research directions in atmospheric science, meteorology, climate science, and weather forecasting, for experts and young scientists.

Data assimilation is the combination of information from observations and models of a particular physical system in order to get the best possible estimate of the state of that system. The technique has wide applications across a range of earth sciences, a major application being the production of operational weather forecasts. Others include oceanography, atmospheric chemistry, climate studies, and hydrology. Data Assimilation for the Earth System is a comprehensive survey of both the theory of data assimilation and its application in a range of earth system sciences. Data assimilation is a key technique in the analysis of remote sensing observations and is thus particularly useful for those analysing the wealth of measurements from recent research satellites. This book is suitable for postgraduate students and those working on the application of data assimilation in meteorology, oceanography and other earth sciences.

Data assimilation is the combination of information from observations and models of a particular physical system in order to get the best possible estimate of the state of that system. The technique has wide applications across a range of earth sciences, a major application being the production of operational weather forecasts. Others include oceanography, atmospheric chemistry, climate studies, and hydrology. Data Assimilation for the Earth System is a comprehensive survey of both the theory of data assimilation and its application in a range of earth system sciences. Data assimilation is a key technique in the analysis of remote sensing observations and is thus particularly useful for those analysing the wealth of measurements from recent research satellites. This book is suitable for postgraduate students and those working on the application of data assimilation in meteorology, oceanography and other earth sciences.

Data engineers who need to hit the ground running will use this book to build skills in Azure Data Factory v2 (ADF). The tutorial-first approach to ADF taken in this book gets you working from the first chapter, explaining key ideas naturally as you encounter them. From creating your first data factory to building complex, metadata-driven nested pipelines, the book guides you through essential concepts in Microsoft’s cloud-based ETL/ELT platform. It introduces components indispensable for the movement and transformation of data in the cloud. Then it demonstrates the tools necessary to orchestrate, monitor, and manage those components.The hands-on introduction to ADF found in this book is equally well-suited to data engineers embracing their first ETL/ELT toolset as it is to seasoned veterans of Microsoft’s SQL Server Integration Services (SSIS). The example-driven approach leads you through ADF pipeline construction from the ground up, introducing important ideas and making learning natural and engaging. SSIS users will find concepts with familiar parallels, while ADF-first readers will quickly master those concepts through the book’s steady building up of knowledge in successive chapters. Summaries of key concepts at the end of each chapter provide a ready reference that you can return to again and again.What You Will LearnCreate pipelines, activities, datasets, and linked servicesBuild reusable components using variables, parameters, and expressionsMove data into and around Azure services automaticallyTransform data natively using ADF data flows and Power Query data wranglingMaster flow-of-control and triggers for tightly orchestrated pipeline executionPublish and monitor pipelines easily and with confidenceWho This Book Is ForData engineers and ETL developers taking their first steps in Azure Data Factory, SQL Server Integration Services users making the transition toward doing ETL in Microsoft’s Azure cloud, and SQL Server database administrators involved in data warehousing and ETL operations

Data assimilation is the combination of information from observations and models of a particular physical system in order to get the best possible estimate of the state of that system. The technique has wide applications across a range of earth sciences, a major application being the production of operational weather forecasts. Others include oceanography, atmospheric chemistry, climate studies, and hydrology. Data Assimilation for the Earth System is a comprehensive survey of both the theory of data assimilation and its application in a range of earth system sciences. Data assimilation is a key technique in the analysis of remote sensing observations and is thus particularly useful for those analysing the wealth of measurements from recent research satellites. This book is suitable for postgraduate students and those working on the application of data assimilation in meteorology, oceanography and other earth sciences.

Data engineers who need to hit the ground running will use this book to build skills in Azure Data Factory v2 (ADF). The tutorial-first approach to ADF taken in this book gets you working from the first chapter, explaining key ideas naturally as you encounter them. From creating your first data factory to building complex, metadata-driven nested pipelines, the book guides you through essential concepts in Microsoft’s cloud-based ETL/ELT platform. It introduces components indispensable for the movement and transformation of data in the cloud. Then it demonstrates the tools necessary to orchestrate, monitor, and manage those components.This edition, updated for 2024, includes the latest developments to the Azure Data Factory service:Enhancements to existing pipeline activities such as Execute Pipeline, along with the introduction of new activities such as Script, and activities designed specifically to interact with Azure Synapse Analytics.Improvements to flow control provided by activity deactivation and the Fail activity.The introduction of reusable data flow components such as user-defined functions and flowlets.Extensions to integration runtime capabilities including Managed VNet support.The ability to trigger pipelines in response to custom events.Tools for implementing boilerplate processes such as change data capture and metadata-driven data copying.What You Will LearnCreate pipelines, activities, datasets, and linked servicesBuild reusable components using variables, parameters, and expressionsMove data into and around Azure services automaticallyTransform data natively using ADF data flows and Power Query data wranglingMaster flow-of-control and triggers for tightly orchestrated pipeline executionPublish and monitor pipelines easily and with confidenceWho This Book Is ForData engineers and ETL developers taking their first steps in Azure Data Factory, SQL Server Integration Services users making the transition toward doing ETL in Microsoft’s Azure cloud, and SQL Server database administrators involved in data warehousing and ETL operations