• Kendal McGUFFIE & Ann HENDERSON-SELLERS, (1987, 1997, 2005), 2014: The Climate Modelling Primer, Fourth Edition. Wiley Blackwell, 438 pp. ISBN 978-1-119-94337-2 (pbk.)

2014年5月、Wiley社に本を注文するついでがあったので新刊案内を見たら、前から知っていた気候モデルに関する大学レベルの教科書の新版が出たばかりだったので、ついでに注文した。

初版から次のように変化している。
初版 1987年、Henderson-Sellersが筆頭著者、217ページ+フロッピーディスク。
第2版 1997年、この版からMcGuffieが筆頭著者、253ページ+CD-ROM。
第3版 2005年、280ページ+CD-ROM (ウェブサイトを併用)。
第4版 2014年、438ページ(CD-ROMなし、補足情報はウェブサイト)
わたしは第3版を見ていないが、第2版までの印刷が白黒だったのに対して第4版はほぼ全部のページが色刷りで印象がだいぶ変わった。これは英語圏の教科書類でよく見られる傾向だし、IPCC報告書も第3次(2001年)から第4次(2007年)で変わった。また、第4版は第2版までよりも判も少し大きくなったうえにページ数もふえた。第2版は日本の大学の半年1こま(90分×15回)にちょうどよい分量だと思ったが、第4版の内容をこなすには通年週2回くらいかかりそうだ。ただし第4版は囲み記事が異常に多い。まえがきで分類されているだけでも8種類の囲みがあり、それぞれが各章に出てくるのだ。その大部分は関心のある学生に向けたオプション的なものだとすれば、必須の部分はそれほどふえていないのかもしれない。内容が豊富になったのは、著者たちがいろいろな興味をもった学生に向けて授業をした経験を反映させたからだと思う。反面、初期の版を知らないと、とくに大事なところをつかまえそこなう心配もあると思う。

題名は初版から第3版まではA Climate Modelling Primerだったが、第4版では定冠詞のTheになった。決定版ということなのだろうか。内容の更新は今後もあると思うが。

補足情報が置かれるウェブサイトは、次の2つがある。
出版社のもの www.wiley.com/go/mcguffie/climatemodellingprimer
著者たちのもの www.climatemodellingprimer.net

章だては次のようになっている。
1. なぜ気候モデリングをするのか?
2. 気候モデルの(これまでの)発展
3. エネルギー収支気候モデル
4. 中間の複雑さのモデル
5. 多圏結合気候システムモデル
6. 学んだことをふりかえる

初版以来、この本の基本的構造は、気候モデルのうちにはいろいろな複雑さのものがあることを展望し(第4版では第2章)、そのうち簡単なほうの端に近い南北1次元エネルギー収支モデル(大気や海洋の運動を具体的には扱わず、南北方向のエネルギー輸送は拡散のような形で表現する)について学生が実際に動かしてみる機会を用意し(第3章)、他方、複雑なほうの端に近い、気候の変化を定量的にできるかぎり精密にシミュレートしようとしている人たちが使っているモデルがどんなものかを理解する(第5章)、というふうに整理すれば、変わっていないと思う。

ただし、1次元エネルギー収支モデルのプログラムは、初版ではBASIC言語のソースプログラムが本文に書かれていたが、第4版ではウェブサイトからダウンロードできるのは(わたしが見つけた限りでは)コンパイルずみのものだ。パラメータを変えて実行して結果をグラフにするためのしかけが含まれているので、動かす経験を積むことはできるのだが、モデルを作る人に近い立場で組み立てを理解することからは遠くなってしまったと思う。

複雑なモデルの章の対象は、世界の学問の進展を反映して、初版では、大気大循環モデルから大気海洋結合大循環モデルまでだったのだが、第4版では、大気海洋結合大循環モデルから、それに主要元素などの物質循環とそれにかかわる生態系の働きを加えた「地球システムモデル」までに変わった。

第4章では両極端の中間の複雑さのモデルが扱われている。そのうちの重要な種類のひとつとして、鉛直1次元の放射対流モデルも扱われている。その関係もあって、大循環モデルの部品として含まれるプロセスやそのモデル化技法の説明は、第4章と第5章とに分配されている。

第3版を確認していないがおそらく第4版で新しく強調されたこととして、科学と社会のかかわりがある。囲みの1種類として「気候モデルに関するコミュニケーション」について考えさせるものがある。「地方自治体の議会から求められたとして気候モデルについてどう説明するか考えてみよう」などは、確かにこの内容の授業をとった人に実際に期待される可能性が高いことなのかもしれない。ただし、初めのほうで「ブログやTwitterで知識を発信しよう」と勧めながら敵対的批判者やネット荒らしにどう応じるかの話が見あたらないのはこわい気がした(簡単に書けるものではないので教科書には無理な注文かもしれないが)。また、気候モデルと社会のかかわりを論じる視点がIPCCにかかわる科学者のものに限られているように思われる(気候モデル自体を理解するための教科書でそれと政治とのかかわりを本格的に論じることもほぼ無理な注文だと思うが)。

囲みのうちには、人物紹介もある。人選は、気候モデルあるいはその応用の発展に大きく貢献した人、著者が出会って影響を受けた人やおもしろいと感じた人、女性研究者の活躍の例となる人、といった複数の観点があるように思われる。日本出身者では真鍋淑郎さんだけがあげられている。

折り返しのあとに詳しい目次をつける。参考文献リストと索引を除く400ページのほとんどのページに、本文の小節の見出しか、囲みの見出しがあるので、それを書き出していくととても長いものになってしまう。囲みの中身が特定の文献の紹介であるものについては、{…}の形で、文献の著者名・発行年も補っておいた。

Contents
Preface
– Learning Objectives – for the whole book
– Illustrative climate model understanding boxes
– [Illustrative climate model understanding] Boiling a frog
– Technical/mathematical boxes
– [Tech Box 1] Very simple climate model (static version)
– Practical communication about climate modelling: learning by doing
– A, B, C to R, S, T of climate modelling
– – – Reasons for climate modelling
– – – Signposts to understanding
– – – Treasures of climate model discovery and insight
– [Climate Model Communication Box 1] Write a blog (diary) or tweet: action
– Downloadable, easy-to-use climate models to explore concepts
– Biographies of people who are/have been important in climate modelling
– [Biography Box 1] Meet the modeller: Isaac Asimov
– [Biobraphy Box 2] Meet a modeller: Ann Henderson-Sellers and Kendal McGuffie
– Chapter summary
– [1. Summary] Research for review
– Chapter closing showcase
Acknowledgements
About the companion website
(Vocabulary of Climate)
1. Why Model Climate?
– 1.1 Introduction
– 1.2 What is a climate model?
– – 1.2.1 Climate modelling and cooking: feeding good
– – [Speed Date Box 1] Gamers go-for-it: the 2007 Climate Challenge
– – 1.2.2 Climate models are much more than code
– 1.3 Multiple reasons for climate modelling
– – [Reflection on learning 1.1] Recognise the many reasons for having models
– – [Tech Box 1.1] Wath a climate model ‘flower’
– – 1.3.1 Climate models test the robustness of prevailing theory
– – [CSI (climate simulation intrigues) Box 1.1] Weirdness of Water: Great greenhosue gas
– – [Reflection on learning 1.2] Track the history of scientific theory becoming fact
– – 1.3.2 Climate models illuminate salient features and core uncertainties
– – [CSI Box 1.2] Weirdness of Water: Water, water, everywhere
– – [Climate Model Communication Box 1.1] Modelling hobbyists meeting
– – [Reflection on Learning 1.3] List the factors affecting planetary scale climate
– – 1.3.3 Climate models reveal the apparently simple to be complex and vice versa
– – [Tech Box 1.2] View the Lorenz Attractor unfolding
– – [Biography Box 1.1] Meet the modeller: Edward N. Lorenz
– – [Tech Box 1.3] Craft a double pendulum or crochet a Lorenz Manifold
– – 1.3.4 Climate models raise new questions and suggest analogies
– – [Feedback Box 1] The ‘CLAW’ {Charlson, Lovelock, Anderae & Warren 1987}
– – [Reflection on Learning 1.4] Explain the concept of climate feedback and give examples
– – [Tech Box 1.4: Planetary climate model – effective temperature and surface temperature
– – 1.3.5 Climate models expose prevailing wisdom as compatible or incompatible with existing data and hence direct collection of new data
– – [CSI Box 1.3] Weirdness of Water: Buddy, can you spare a dime-r
– – 1.3.6 Climate models explain
– – [Spotlight on Climate Models Box 1] Palaeoclimate modelling challenge {Braconnot, Harrison, Kageyama et al. 2012}
– – 1.3.7 Climate models bound (bracket) outcomes within plausible ranges
– – [CSI Box 1.4] Weirdness of Water: Isotopes and isotopologues
– – 1.3.8 Climate models train practitioners and educate the general public
– – [Model Validation Box 1] Regionalising climate with Thornthwaite {Elgundi and Grundstein 2012}
– – 1.3.9 Climate models discipline the policy dialogue
– – [Biography Box 1.2] Meet the modeller: Stephen H. Schneider
– – 1.3.10 Climate models encourage sensible thinking and informed discussion
– – [Biography Box 1.3] Meet the modeller: Susan Solomon
– 1.4 Climate models: sound components in careful combination
– – 1.4.1 Ingredients and method
– – [Wiring the World Box 1] Real wires and the real world
– – 1.4.2 Climate model prediction: getting the right result for the correct reason
– – 1.4.3 Climate models pushing the envelope
– – – Alien climate modelling
– – – Global governance outcomes from climate modelling
– – [Biography Box 1.4] Meet the modeller: Carl Sagan
– – [Climate Model Communication Box 1.2] Climate modelling shared with non-professionals
– – [Reflection on Learning 1.5] Recognise the mechanisms whereby presistent and widespread life affects climate
– 1.5 Climate modelling: about this book
– – 1.5.1 Climate modelling: read the label and exercise care
– – 1.5.2 The Climate Modelling Primer
– – [Climate Model Showcase Box 1] Checking 20 climate models {Bender, Rodhe, Charlson, Ekman and Loeb 2006}
– 1.6 Summary: research and review
– – Part 1 – Review questions
– – Part 2 – Discussion questions
– Your Climate Modelling Treasures
– Quick historical literature review
(History of Describing Climate Models)
2. The Evolution of Climate Models
– 2.1 Introducing climate modelling
– – 2.1.1 The need for simplification
– – [Wiring the World Box 2] Simple components show complexity
– – [CSI Box 2.1] Coincidence of co-evolution: climate chicken or computer egg?
– – 2.1.2 Resolution in time and space
– 2.2 Types of climate models
– – [Climate Model Communication Box 2] How the arts represent climate modelling
– – [Spotlight on Climate Models Box 2] First review of climate models {Schneider and Dickinson 1974}
– – [Reflection on Learning 2.1] Strategies for model simplification and their effect when constructing a climate model
– – 2.2.1 Energy balance climate models
– – 2.2.2 One-dimensional radiative-convective climate models
– – 2.2.3 Dimensionally constrained climate models
– – [CSI Box 2.2] Coincidence of co-evolution: supply or demand driven?
– – 2.2.4 General circulation models
– – [Biography Box 2.1] Meet the modeller: Joseph Smagorinsky
– – 2.2.5 Interactive biogeochemistry and stable isotopes
– – [Reflection on Learning 2.2] Problems different climate model types are best suited to address
– 2.3 History of climate modelling
– – 2.3.1 Genesis in post-World War 2 technology
– – – Simulating the atmosphere
– – [Biography Box 2.2] Meet the modeller: Suki Manabe
– – – Simulating the ocean
– – – Integrating climate
– – 2.3.2 Evolution of climate models – not a simple timeline
– – 2.3.2 The evolution of predictions, projections and forecasts
– – [Reflection on Learning 2.3] The historical development of climate modelling in the framework of technological and scientific achievement
– 2.4 Sensitivity of climate models
– – 2.4.1 Definition and terminology
– – [CSI Box 2.3] Coincidence of co-evolution: digital data deluge
– – [Tech Box 2.1] Feedback definitions
– – [Feedback Box 2] Clouds {Schneider 1972}
– – [Tech Box 2.2] Models estimate equilibrium climate sensitivity
– – [Reflection on Learning 2.4] Key terms associated with climate model sensitivity and how these can be used as a measure of model applicability
– – 2.4.2 Equilibrium climatic states
– – [Tech Box 2.3] Stability of model results
– – 2.4.3 Equilibrium conditions and transitivity of climate systems
– – [Speed Date Box 2] Chaotic attractor
– – 2.4.4 CLimate tipping points
– – [Tech Box 2.4] Defining climate tipping points
– 2.5 Parameterisation of climatic processes
– – 2.5.1 Interactions in the climate system
– – [Biography Box 2.3] Meet the modeller: Inez Fung
– – 2.5.2 Justifying and evaluating parameterisation
– – 2.5.3 The need for observations
– – [Model Validation Box 2] GISS vindicated {Hansen et al. 1981: van Oldenborgh and Haarsma 2012}
– – [Reflection on Learning 2.5] Examples of the process of parameterisation and the represntation of tipping points in climate modelling
– – [CSI Box 2.4] Coincidence of co-evolution: 21st-century power
– 2.6 Simulation of the full, interacting climate system: one goal of modelling
– – 2.6.1 A simple model of ‘climate control’
– – 2.6.2 Goals of this book and the 10 reasons for climate modelling
– – [Biography Box 2.4] Meet the modeller: Jean-Pascal van Ypersele
– – [Climate Model Showcase Box 2] Charney’s deserts {Charney 1975}
– 2.7 Summary: research and review
– – Part 1 – Review questions
– – Part 2 – Discussion questions
– R, S, T Keys to Climate Modelling: Resaons, Signposts and Treasures
– Quick historical literature review
(Climate Fundamentals)
3. Energy Balance Models
– 3.1 Balancing the planetary radiation budget
– 3.2 The structure of energy balance models
– – 3.2.1 Zero-dimensional energy balance models
– – [Biography Box 3.1] Meet the modeller: Mikhail Budyko
– – [Speed Date Box 3] Daisyworld – determined daisies {Watson and Lovelock 1983}
– – 3.2.2 One-dimensional energy balance models
– – [CSI Box 3.1] Clouds and the cryosphere: energy budgets and high albedos
– – [Reflection on Learning 3.1] The radiative components of energy balance in climate models
– – [Feedback Box 3] Sea-ice albedo {Curry, Schramm and Ebert 1995}
– 3.3 Parameterising the climate system for energy balance models
– – 3.3.1 Energy balance model parameters
– – – Albedo
– – – Outgoning infrared radiation
– – [Biography Box 3.2] Meet the modeller: Veerabhadran Ramanathan (Ram)
– – [Tech Box 3.1] Sellers’ latitudinal transport
– – – Heat transport
– – 3.3.2 Comparing Budyko’s and Sellers’ energy balance models
– – [Biography Box 3.3] Meet the modeller: Michael Ghil
– – [Reflection on Learning 3.2] The non-radiative components of the climate in energy balance models
– 3.4 Simple climate models
– – 3.4.1 Energy balance model – a spreadsheet climate model
– – 3.4.2 Energy balance model implementation in Xojo[TM]
– – – Description of the energy balance model
– – 3.4.3 Gaian geophysiology
– – [Spotlight on Climate Models Box 3] EBM early analysis {Gal-Chen and Schneider 1976}
– – [Reflection on Learning 3.3] The strengths and the limitations of zero-dimensional and one-dimensional climate models
– 3.5 Energy balance and glacier models
– – [CSI Box 3.2] Clouds and the cryosphere: ice sheets and isotopes
– – 3.5.1 Isotopic EBM-like model with a dynamic ice sheet
– – 3.5.2 Milankovitch cycles and ice sheets
– – 3.5.3 Glaciers: energy-based components of global climate models
– – 3.5.4 Snowball Earth
– – [Reflection on Learning 3.4] The history of energy balance climate models
– 3.6 Box models – another form of energy balance model
– – 3.6.1 Zonal box models that maximise planetary entropy production
– – [Wiring the World Box 3] Bretherton’s original and a simpler version {NASA 1988}
– – 3.6.2 A simple box model of the ocean-atmosphere
– – [Tech Box 3.2] Box diffusion model
– – 3.6.3 MAGICC: box model development of great value
– – 3.6.4 A coupled atmosphere, land and ocean energy balance box model
– – [Model Validation Box 3] Checking a simple represenative concentration pathway model {Good, Gregory, Lowe and Andrews 2012}
– – [Biography Box 3.4] Meet the modeller: Gabriele (Gabi) Clarissa Hegerl
– – [CSI Box 3.3] Clouds and the cryosphere: ice clouds, a tough challenge
– – 3.6.5 Super simple simulator: clouds and rain in chaos
– – [Tech Box 3.3] The Lotka-Volterra prey-predator model
– – [Reflection on Learning 3.5] How to modify a zero-dimensional model to become one-, two- and even three-dimensional
– – [Climate Model Communication Box 3] Prepare a presentation for your local council
– 3.7 Energy balance models: deceptively simple
– – [CSI Box 3.4] Clouds and the cryosphere: a less cloudy future?
– – [Climate Model Showcase Box 3] Energy balance models: water on Mars {Hoffert, Callegari, Hsieh and Ziegler 1981}
– 3.8 Summary: research and review
– – Part 1 – Review questions
– – Part 2 – Discussion questions
– R, S, T Keys to Climate Modelling: Reasons, Signposts and Treasures
– Quick historical literature review
(Simplification is Essential to Understanding)
4. Intermediate Complexity Models
– 4.1 Why lower complexity?
– – [Wiring the World Box 4] MESSAGE in a model
– 4.2 One-dimensional radiative-convective models
– – [Speed Date Box 4] IMAGE: moving up dimensions
– – [Biography Box 4.1] Meet the modeller: James E. Hansen
– – [CSI Box 4.1] Committing to confidence: clear communication
– – 4.2.1 The structure of global radiative-convective models
– 4.3 Radiation: the driver of climate
– – [Tech Box 4.1] Energy budget
– – 4.3.1 Shortwave radiation
– – [Tech Box 4.2] Radiataive parameters
– – – Albedo
– – – Shortwave radiation subject to scattering
– – – Shortwave radaition subject to absorption
– – 4.3.2 Longwave radiation
– – 4.3.3 Heat balance at the surface
– – 4.3.4 Convective adjustment
– – – Clouds in model columns
– 4.4 Experiments with radiative-convective models
– – 4.4.1 One-dimensional radiative-convective model sensitivity testing
– – [CSI Box 4.2] Committing to confidence: credibility and truth
– – – Sensitivity to humidity
– – – Sensitivity to clouds
– – – Senstivitity to lapse rate selected for convective adjustment
– – 4.4.2 One-dimensional radiative-convective model applied to the very early Earth
– – – Model sensitivity
– – [CSI Box 4.3] Comitting to conficence: certainty in climate
– – 4.4.3 Development of radiative-convective models
– – – Physics in ‘connecting’ columns
– – – Convection
– – – – Kuo convection
– – – – Mass flux convection
– – – Probing cluod parameterisation
– – – Precipitation
– – [Biography Box 4.2] Meet the Modeller: Lisa V. Alexander
– – [Tech Box 4.3] Boundary layer stability
– – – Surface boundary
– – 4.4.4 ‘Singling out’ column models
– – [Tech Box 4.4] Eddy diffusivity
– – – More complicate boundary interactions
– – [Reflection on Learning 4.1] Parameterisation techniques that are used to simulate radiative properties of the atmosphere
– 4.5 Reduced complexity models
– – 4.5.1 Deterministic versus stochastic approach
– – [Tech Box 4.5] Two-dimensional atmospheric equations
– – 4.5.2 Parameterisations for two-dimensional statistical dynamical modelling
– – [Tech Box 4.6] Eddy fluxes
– – [Reflection on Learning 4.2] Modelling atmospheric convection and oceanic stratification and the potential for climatic cascades from these processes
– – 4.5.3 ‘Column’ processes in two-dimensional statistical dynamical models
– – [Feedback Box 4] Carbon {Luo, Yan, Hui and Wallace 2001}
– – [Reflection on Learning 4.3] The history of EMICs
– 4.6 The spectrum of Earth system models of intermedeiate complexity
– – 4.6.1 An upgraded energy balance model
– – 4.6.2 Multi-column radiative-convective models
– – [Biography Box 4.3] Meet the modeller: André Berger
– – [Climate Model Communication Box 4] Prediction and policy {Thompson and Schneider 1986; Victor, Kennel and Ramanathan 2012}
– – [Tech Box 4.7] Modelling oceanic phytoplankton biomass
– – [Biography Box 4.4] Meet the modeller: Corinne Le Quéré
– – 4.6.3 A severly truncated spectral general circulation climate model
– – [Reflection on Learning 4.4] How all aspects of a fully three-dimensional climate can be captured in a model that takes less time per simulation than a GCM
– – 4.6.4 Repeating sctors in a global ‘grid’ model
– – 4.6.5 A two-and-a-half dimensional model: CLIMBER-2
– – 4.6.6 McGill palaeoclimate model
– – [CSI Box 4.4] Committing to confidence: copying climate communication
– – 4.6.7 A simplified global climate model with water isotopologues: the LMDZ-iso GCM
– – 4.6.8 An all-aspects, severely truncated Earth system model of intermediate complexity: MoBidiC
– – 4.6.9 Earth system models of intermediate complexity predict future release of radiocabons from the oceans
– – [Model Validation Box 4] Checking the Holocene {Crucifix, Loutre, Tulkens, Fichefet and Berger 2002}
– – 4.6.10 The forthcoming interglacial protracted
– – [Spotlight on Climate Models Box 4] The MAGICC of volcanoes {Wigley 2006}
– – [Reflection on Learning 4.5] The reasons why climate models of intermediate complexity are built and used
– 4.7 Why are some climate modellers Flatlanders?
– – [Climate Model Showcase Box 4] Costing Climate {Nordhaus 2010}
– 4.8 Summary: research and review
– – Part 1 – Review questions
– – Part 2 – Discussion questions
– R, S, T Keys to Climate Modelling: Reasons, Signposts and Treasures
– Quick historical literature review
(Prediction: an Important Reason for Modelling)
5. Coupled Climate System Models
– 5.1 Three-dimensional model sof the climate system
– – [CSI Box 5.1] Climate models and the law: whether the weather’s changed
– 5.2 Configuring the climate
– – 5.2.1 Finite grid formulation
– – [Speed Date Box 5] Community Earth System Model (CESM)
– – [Biography Box 5.1] Meet the modeller: Warren Washington
– – [Tech Box 5.1] Gravity wave drag
– – – Discretisation of the ocean
– – 5.2.2 Spectral atmospheric models
– – – Representing the atmosphere with waves
– – – Structure of a spectral model
– – – Truncation
– – [Tech Box 5.2] Slicing space spectrally
– – [Climate Model Communication Box 5] Climate models in the mass media: review the explanation of climate modelling and model results in the mass media {Akerlof et al. 2012}
– – 5.2.3 Re-gridding the planet
– – [Reflection on Learning 5.1] The many ways in whcih the atmosphere, ocean, etc., are discretised so that values of the variables chosen to represent the climate can be calculated at each timestep
– 5.3 Computers for modelling climate
– – 5.3.1 Computer architechture and numerical modelling
– – – Machine memory
– – – Fitting climate into the computer
– – – Computer ‘effect’ in climate model results
– – [Biograph Box 5.2] Meet the modeller: Carlos A. Nobre
– – 5.3.2 Coupling the climate
– – [Wiring the World Box 5] Nitrogen cycling
– – [Reflection on Learning 5.2] What coupling means in the context of climate models and its importance
– – 5.3.3 Creating cliamte ensembles
– – [CSI Box 5.2] Climate models and the law: success and failure
– – – Regional ‘hotspots’ identified from CMIP5 ensembles
– – [Spotlight on Climate Models Box 5] CMIP5 forcing, feedback and sensitivity {Andrews, Gregory, Webb and Taylor 2012}
– – – Ocean oscillations and shifts probed by simple ensembles of opportunity
– – [Feedback Box 5] Oceaning thermohaline modelling {Yin, Schlesinger, Andronova and Li 2006}
– 5.4 Modelling climate components
– – 5.4.1 Atmospheric formulation
– – [Tech Box 5.3] Formulating atmospheric dynamics for a climate model
– – [Biography Box 5.3] Meet the modeller: Robert E. Dickinson
– – – Mesoscale convection
– – – Superparameterisation
– – 5.4.2 Atmospheric chemsitry
– – [Model Validation Box 5] Coupled climate system models: cloud water ice in CMIP3 and CMIP5 {Li, Waliser, Chen et al. 2012}
– – 5.4.3 The ocean
– – [CSI Box 5.3] Climate models and the law: work in progress — Kyoto protocol
– – – Oceanic co-ordinate system
– – – Ocean-atmosphere coupling: a significant test of climate models
– – 5.4.4 Carbon modelling and validating
– – – Modelling the global carbon budget
– – [Biography Box 5.4] Meet the modeller: Claire Granier
– – – Ocean parameterisation evaluation using ¹⁴C isotopes
– – – Future of the carbon budget
– – 5.4.5 Sea-ice
– – 5.4.6 Land surface
– – – Frozen land surfaces
– – – ‘SVATS’ to interactive vegatation
– – [Reflection on Learning 5.3] How GCM parameters that represent the climate are selected and how their selection has evolved over the history of climate modelling
– 5.5 Localising climate models
– – 5.5.1 Regional climate modelling
– – – Limited area models
– – [CSI Box 5.4] Climate models and the law: geoengineering governance {CBD 2010}
– – [Reflection on Learning 5.4] Recognising a fully coupled cliamte model and understanding the limitations of its simulations
– 5.6 ‘Complete’ coupled climate models
– – 5.6.1 Climate model prediction skills
– – – Evaluation of decadal predictability in CMIP5: assessing hindcast skill
– – – Weather forecast skill linked to climate model improvement
– – [Reflection on Learning 5.5] The desire for simplification and the growth of complexity in climate modelling
– – 5.6.2 Earth system and climate models
– 5.7 Summary: research and review
– – Part 1 – Review questions
– – [Climate Model Showcase Box 5] Searching for real-world coupling {Koster, Dirmeyer, Guo et al. 2004}
– – Part 2 – Discussion questions
– R, S, T Keys to Climate Modelling: Reasons, Signposts and Treasures
– Quick historical literature review
(Climate Model Activism)
6. Through the Looking Glass
– 6.1 First reflection: a chef or a modeller?
– – [Confirming Learning 1] Be familiar with the history of climate modelling and understand its achievements to date and its goals for the future
– 6.2 Second reflection: knowledge ‘boxes’
– – [Confirming Learning 2] Understand how climate models are used in simulations of past, future and current climates at a variety of scales
– – The global scale
– – Regional scale (of global scale importance)
– 6.3 Third reflection: climate modelling collection
– – [Your Climate Modelling Treasures]
– – [Confirming Learning 3] Be able to assess a wide range of communication forms employed to share results from climate mocel simulations with different audiences
– 6.4 Fourth reflection: meeting real climate modellers
– – [Biography Box 6.1] Meet the modeller: Hans Joachim (John) Schellnhuber
– – [Confirming Learning 4] Recognise the variety of confidence and uncertainty measures associated with climate model comparisons and outputs and know how to interpret them
– 6.5 Fifth reflectoin: reasons for modelling
– – [Confirming Learning 5] Appreciate the ways in which results from climate models affect 21st-century policy, laws, international trade and human development
– 6.6 Reflections overview — book summary: research and review
– – Part 1 – Review questions
– – Part 2 – Discussion questions
Collected endnotes
Hints and solutions
List of abbreviations
List of symbols
Bibliography
Index