Roberto Buizza (Professor of Physics, Professor of Physics, Scuola

Weather Prediction: What Everyone Needs to KnowRG

What Everyone Needs to Knowr

• Broschiertes Buch

Produktbeschreibung

Weather Prediction: What Everyone Needs to Know® introduces readers to the science behind numerical weather prediction and considers its increasing importance. Like the other books in the What Everyone Needs to Know® series, this book is intended for a wide audience, including policy makers, environmentalists, students, scientists in other fields, and the general public interested in weather prediction. Weather Prediction takes readers on a fascinating journey into numerical weather prediction, an activity that has been helping humans to live better.

Produktdetails

• WHAT EVERYONE NEEDS TO KNOW
• Verlag: Oxford University Press Inc
• Seitenzahl: 304
• Erscheinungstermin: 5. Dezember 2023
• Englisch
• Abmessung: 210mm x 142mm x 20mm
• Gewicht: 354g
• ISBN-13: 9780197652121
• ISBN-10: 0197652123
• Artikelnr.: 67712930

Autorenporträt

Roberto Buizza is Professor in Physics at Scuola Superiore Sant'Anna, and Honorary Research Fellow at Imperial College Grantham Institute for Climate Change. He has a degree in physics, a PhD in mathematics, and a master's in business administration. From 1991 to 2018 he worked at the European Centre for Medium-Range Weather Forecasts, where he was a key developer of its prediction systems and served as Head of the Predictability Division and Lead Scientist.

Inhaltsangabe

* Preface
* 1 Weather And Climate
* 1.1 What Is The Key Difference Between Weather And Climate?
* 1.2 Do Weather And Climate Vary Spatially And Temporally?
* 1.3 Is There A Clear Separation Between Weather And Climate?
* 1.4 Is Weather Affected By All (Small-And-Fast And Large-And-Slow)
Phenomena?
* 1.5 Which Coordinate System Is Used To Study Atmospheric And Oceanic
Motions?
* 1.6 What Are The Key Weather Variables?
* 1.7 Why Does Weather Change?
* 1.8 How Are Motions In The Atmosphere Generated?
* 1.9 Key Points Discussed In Chapter One 'Weather And Climate'
* 2 The Earth System
* 2.1 What Does 'Earth System' Mean In Numerical Weather Prediction?
* 2.2 What Is An Accurate And Skilful Forecast?
* 2.3 What Are The Key Building Blocks Of An Earth System Model?
* 2.4 What Are The Key Processes Simulated By An Earth System Model?
* 2.5 How Is Heat Transported And Exchanged In The Earth System?
* 2.6 Where Does The Energy That Drives The Earth Climate Come From?
* 2.7 What Are The Key Similarities And Differences Of The Atmosphere
And The Ocean?
* 2.8 Key Points Discussed In Chapter Two 'The Earth-System'
* 3 Observing The Earth System
* 3.1 Why Do We Need Observations?
* 3.2 What Are The Key Observation Types?
* 3.3 Are Observations Affected By Errors?
* 3.4 How Do Observation Information And Errors Propagate?
* 3.5 Did Covid Affect Weather Forecast Quality?
* 3.6 How Do We Observe The State Of The Atmosphere Using Satellites?
* 3.7 Do We Have Enough Observations To Determine The State Of The
Earth-System?
* 3.8 Is It Important To Observe The Whole Atmosphere?
* 3.9 Key Points Discussed In Chapter Three 'Observing The Earth
System'
* 4 Modelling The Earth System
* 4.1 From Where Should We Start To Model The Earth System?
* 4.2 What Are The State Variables Of A System?
* 4.3 How Many Variables Define The State Of The Whole Earth System?
* 4.4 What Is An Equation?
* 4.5 What Are Analytical And Numerical Solutions Of An Equation?
* 4.6 How Do We Deduce The Equations Used To Predict The Weather And
The Climate?
* 4.7 What Is An Example Of A Set Of Equations That Can Predict The
Weather?
* 4.8 How Do We Solve The Primitive Equations?
* 4.9 What Is The Difference Between A Prognostic And A Diagnostic
Equation?
* 4.10 Can We Use Simple Models To Understand The Behaviour Of Complex
Systems?
* 4.11 Key Points Discussed In Chapter Four 'Modelling The Earth
System'
* 5 Numerical Weather Prediction
* 5.1 How Do We Solve Numerically The Primitive Equations?
* 5.2 What Are The Key Steps Involved In Operational Weather
Prediction?
* 5.3 How Do We Determine The Initial Conditions?
* 5.4 What Is Data Assimilation?
* 5.5 Do We Need A Super-Computer For Numerical Weather Prediction?
* 5.6 Do We Need An Earth-System Model To Predict The Weather?
* 5.7 What Are The Key Differences Between A Global And A Limited-Area
Model?
* 5.8 How Can We Assess Whether A Model Is Realistic And Accurate?
* 5.9 How Much Data Is Involved In Weather Prediction?
* 5.10 Key Points Discussed In Chapter Five 'Numerical Weather
Prediction'
* 6 Chaos And Weather Prediction
* 6.1 What Is A Chaotic System?
* 6.2 What Is The Lorenz' 3-Dimensional Model?
* 6.3 What Is The 'Butterfly Effect'?
* 6.4 What Are The Sources Of Forecast Error?
* 6.5 How Can We Reduce Initial Condition Uncertainties?
* 6.6 How Can We Reduce Model Uncertainties?
* 6.7 How Do We Measure Forecast Errors?
* 6.8 What Is An Ensemble?
* 6.9 Are Ensemble Forecasts More Valuable Than Single Ones?
* 6.10 Key Points Discussed In Chapter Six 'Chaos And Weather
Prediction'
* 7 Dealing With Uncertainties And Probabilistic Forecasting
* 7.1 How Do We Build An 'Accurate And Reliable' Ensemble?
* 7.2 What Is A Probabilistic Forecast?
* 7.3 How Can We Communicate Forecast Uncertainty?
* 7.4 How Can We Take Decisions Using Probabilistic Forecasts?
* 7.5 What Is A Scenario Forecast?
* 7.6 What Is A Cluster Analysis?
* 7.7 How Do We Measure The Accuracy And Reliability Of A Probabilistic
Forecast?
* 7.8 What Are Reforecasts And Reanalyses?
* 7.9 Why Are Reanalyses And Reforecasts Useful?
* 7.10 Key Points Discussed In Chapter Seven 'Dealing With
Uncertainties And Probabilistic Forecasting'
* 8 The Forecast Skill Horizon
* 8.1 Are Weather Forecasts More Accurate And Reliable Today Than In
The Past?
* 8.2 How Did We Succeed To Improve The Accuracy And Reliability Of
Weather Forecasts?
* 8.3 Can We Visualize In A Single Diagram Our Prediction Capabilities?
* 8.4 Why Does The Forecast Skill Depend On The Phenomena We Are Trying
To Predict?
* 8.5 Are Extreme Events More Difficult To Predict Than The 'Normal'
Weather?
* 8.6 What Is The Minimum Spatial Scale That A Model Can Simulate
Realistically?
* 8.7 What Is The Minimum Spatial Scale Properly Resolved In Data
Assimilation?
* 8.8 How Can We Further Extend Predictability?
* 8.9 Key Points Discussed In Chapter Eight 'The Forecast Skill
Horizon'
* 9 Climate Change And Numerical Weather Prediction
* 9.1 Why Should We Talk About Climate Change In This Book?
* 9.2 What Is The Greenhouse Effect?
* 9.3 What Is The State Of The Climate?
* 9.4 How Much Greenhouse Gases Do We Emit In The Atmosphere?
* 9.5 Is There A Link Between Greenhouse Gas Emissions And Average
Global Warming?
* 9.6 Are We Responsible For Climate Change?
* 9.7 What Are The Key Sources Of Uncertainty Affecting Climate
Predictions?
* 9.8 What Do We Mean With 'Initial Value' And 'Boundary Condition'
Problems?
* 9.9 Has Climate Change Impacted Weather Prediction?
* 9.10 Has Numerical Weather Prediction Helped Understanding Climate
Change?
* 9.11 Which Aspects Of The Future Climate Can We Predict?
* 9.12 Key Points Discussed In Chapter Nine 'Climate Change And
Numerical Weather Prediction'
* 10 A Look Into The Future
* 10.1 What Are The Focus Areas Of Research In Numerical Weather
Prediction?
* 10.2 What Is An Earth Digital Twin?
* 10.3 Will We Be Able To Continue To Improve The Quality Of Weather
Forecasts?
* 10.4 Will We Ever Be Able To Issue A 'Perfect' Forecast?
* 10.5 In 2050, Will We Be Able To Predict The Local Weather Of The
Next Season?
* 10.6 Can Artificial Intelligence Lead To Improve Predictions?
* 10.7 What Is An 'Environmental Prediction Model'?
* 10.8 Is Weather Prediction Evolving Into Environmental Prediction?
* 10.9 As Global Models Keep Increasing Resolution, Will We Still Use
Limited-Area Model?
* 10.10 Would A Future Operational Suite Look Very Different From
Today's One?
* 10.11 Key Points Discussed In Section 10 'A Look Into The Future'
* Essential Glossary
* Further Reading
* Useful Links
* The Author