Peter Michael Inness & Steve Dorling 
Operational Weather Forecasting 

This book offers a complete primer, covering the end-to-end
process of forecast production, and bringing together a description
of all the relevant aspects together in a single volume; with
plenty of explanation of some of the more complex issues and
examples of current, state-of-the-art practices.

Operational Weather Forecasting covers the whole process
of forecast production, from understanding the nature of the
forecasting problem, gathering the observational data with which to
initialise and verify forecasts, designing and building a model (or
models) to advance those initial conditions forwards in time and
then interpreting the model output and putting it into a form which
is relevant to customers of weather forecasts. Included is the
generation of forecasts on the monthly-to-seasonal timescales,
often excluded in text-books despite this type of forecasting
having been undertaken for several years.

This is a rapidly developing field, with a lot of variations in
practices between different forecasting centres. Thus the
authors have tried to be as generic as possible when describing
aspects of numerical model design and formulation. Despite
the reliance on NWP, the human forecaster still has a big part to
play in producing weather forecasts and this is described, along
with the issue of forecast verification – how forecast
centres measure their own performance and improve upon it.

Advanced undergraduates and postgraduate students will use this
book to understand how the theory comes together in the day-to-day
applications of weather forecast production. In addition,
professional weather forecasting practitioners, professional users
of weather forecasts and trainers will all find this new member of
the RMet S Advancing Weather and Climate series a
valuable tool.

* Provides an end-to-end description of the weather forecasting
process

* Clearly structured and pitched at an accessible level, the book
discusses the practical choices that operational forecasting
centres have to make in terms of what numerical models they use and
when they are run.

* Takes a very practical approach, using real life case-studies
to contextualize information

* Discusses the latest advances in the area, including ensemble
methods, monthly to seasonal range prediction and use of
‘nowcasting’ tools such as radar and satellite
imagery

* Full colour throughout

* Written by a highly respected team of authors with experience
in both academia and practice.

* Part of the RMet S book series ‘Advancing Weather and
Climate’

Table of Content

Series Foreword vii

Preface ix

Acknowledgements xiii

1 Introduction 1

1.1 A brief history of operational weather forecasting 2

2 The Nature of the Weather Forecasting Problem 9

2.1 Atmospheric predictability 9

2.2 The importance of observations in weather forecasting 13

2.3 An overview of the operational forecast process 17

Summary 25

3 Meteorological Observations 27

3.1 What do we need from a meteorological observing system?
27

3.2 Data transmission and processing 29

3.3 Observing platforms 31

Summary 51

4 NWP Models – the Basic Principles 53

4.1 The basic ingredients of an NWP model 55

4.2 Building the physical principles into a model 79

4.3 Setting the initial conditions for the forecast 89

Summary 107

5 Designing Operational NWP Systems 109

5.1 Practical considerations for an NWP suite 109

5.2 Ensemble prediction systems 124

5.3 Model output – what can NWP models produce? 130

5.4 Using NWP output to drive other forecast models 144

Summary 148

6 The Role of the Human Forecaster 149

6.1 The role of the senior forecasting team 150

6.2 Production of forecasts for customers 163

Summary 175

7 Forecasting at Longer Time Ranges 177

7.1 Where does the predictability come from in longer range
forecasts? 178

7.2 Observations of ocean and land surface variables 185

7.3 Monthly to seasonal forecasting systems 187

7.4 Presentation of longer range forecasts 200

Summary 204

8 Forecast Verification 205

8.1 Deterministic forecast verification 208

8.2 Verification of probability forecasts 216

8.3 Subjective verification 219

Summary 222

References 223

Index 227

About the author

Peter Inness is a lecturer in the Meteorology Department of Reading University having previously been a Reasearch fellow in the Climate Division of the NERC funded National Centre for Atmospheric Science based at the University of Reading.

Steve Dorling is Senior Lecturer and Researcher in the School of Environmental Sciences at the University of East Anglia (UEA). Steve is also Innovations Director at UEA-based Weatherquest Ltd.