How do scientists predict the weather? What tools and instruments help them make forecasts? How far in advance can they make good predictions? Weather forecasting is a tricky science. In this fact-packed book, discover what it really takes to forecast Earths weather.

A highly-illustrated manual for meteorology students and operational weather forecasters.

From the acclaimed author of Tubes, a lively and surprising tour through the global network that predicts our weather, the people behind it, and what it reveals about our climate and our planet The weather is the foundation of our daily lives. It’s a staple of small talk, the app on our smartphones, and often the first thing we check each morning. Yet, behind all these humble interactions is the largest and most elaborate piece of infrastructure human beings have ever constructed—a triumph of both science and global cooperation. But what is the weather machine, and who created it? In The Weather Machine, Andrew Blum takes readers on a fascinating journey through the people, places, and tools of forecasting, exploring how the weather went from something we simply observed to something we could actually predict. As he travels across the planet, he visits some of the oldest and most important weather stations and watches the newest satellites blast off. He explores the dogged efforts of forecasters to create a supercomputer model of the atmosphere, while trying to grasp the ongoing relevance of TV weather forecasters. In the increasingly unpredictable world of climate change, correctly understanding the weather is vital. Written with the sharp wit and infectious curiosity Andrew Blum is known for, The Weather Machine pulls back the curtain on a universal part of our everyday lives, illuminating our changing relationships with technology, the planet, and our global community.

This workshop report examines the capability of the forecast system to efficiently transfer weather and climate research findings into improved operational forecast capabilities. It looks in particular at the Environmental Modeling Center of the National Weather Service and environmental observational satellite programs. Using these examples, the report identifies several shortcomings in the capability to transition from research to operations. Successful transitions from R&D to operational implementation requires (1) understanding of the importance (and risks) of the transition, (2) development and maintenance of appropriate transition plans, (3) adequate resource provision, and (4) continuous feedback (in both directions) between the R&D and operational activities.

Weather Analysis and Forecasting is a practical guide to using potential vorticity fields and water vapor imagery from satellites to elucidate complex weather patterns and train meteorologists to improve operational forecasting. In particular, it details the use of the close relationship between satellite imagery and the potential vorticity fields in the upper troposphere and lower stratosphere. It shows how to interpret water vapor patterns in terms of dynamical processes in the atmosphere and their relation to diagnostics available from weather prediction models. The book explores topics including: a dynamical view of synoptic development; the interpretation problem of satellite water vapor imagery; practical use of water vapor imagery and dynamical fields; significant water vapor imagery features associated with synoptic dynamical structures; and use of water vapor imagery for assessing NWP model behavior and improving forecasts. Applications are illustrated with color images based on real meteorological situations. The book's step-by-step pedagogy makes this an essential training manual for forecasters in meteorological services worldwide, and a valuable text for graduate students in atmospheric physics and satellite meteorology. * Shows how to analyze current satellite images for assessing weather models' behavior and improving forecasts * Provides step-by-step pedagogy for understanding and interpreting meteorological processes * Includes full-color throughout to highlight "real-world" models, patterns, and examples

The science behind global warming, and its history: how scientists learned to understand the atmosphere, to measure it, to trace its past, and to model its future. Global warming skeptics often fall back on the argument that the scientific case for global warming is all model predictions, nothing but simulation; they warn us that we need to wait for real data, “sound science.” In A Vast Machine Paul Edwards has news for these skeptics: without models, there are no data. Today, no collection of signals or observations—even from satellites, which can “see” the whole planet with a single instrument—becomes global in time and space without passing through a series of data models. Everything we know about the world's climate we know through models. Edwards offers an engaging and innovative history of how scientists learned to understand the atmosphere—to measure it, trace its past, and model its future.

They explore how weather forecasters today formulate their ideas through state-of-the-art mathematics, taking into account limitations to predictability.