Springer Theses

Sources of Uncertainty in the Tropical Pacific Warming Pattern under Global Warming Projected by Coupled Ocean-Atmosphere Models

Authors: Ying, Jun

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  • Offers readers a comprehensive understanding of the various formation mechanisms of the tropical Pacific SST warming pattern
    Proposes two major sources of uncertainty in model projections of the tropical Pacific SST warming pattern under global warming
    Provides an improved projection of the tropical Pacific SST warming pattern by eliminating certain climatological model biases

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eBook $89.00
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  • ISBN 978-981-329-844-6
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Hardcover $159.99
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Softcover $119.99
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About this book

This book discusses the sources of uncertainty in future model projections of the tropical Pacific SST warming pattern under global warming. It mainly focuses on cloud radiation feedback and ocean dynamical effect, which reveal to be the two greatest sources of uncertainty in the tropical Pacific SST warming pattern. Moreover, the book presents a correction for model projections of the tropical Pacific SST warming pattern based on the concept of “observational constraints”; the corrected projection exhibits a more El Niño-like warming pattern.


About the authors


Area of work: Tropical ocean-atmosphere interaction; Climate change; El Niño–Southern Oscillation.

Honors:

The excellent doctoral dissertation of institute of atmospheric physics, Chinese academy of science in 2016;

The excellent doctoral dissertation of Chinese academy of science in 2017.

Publications:

(1) Ying Jun and Ping Huang, Cloud-radiation feedback as a leading source of uncertainty in the tropical Pacific SST warming pattern in CMIP5 models. Journal of Climate, 2016, 29: 3867-3881.

(2) Ying Jun, Ping Huang, and Ronghui Huang, Evaluating the formation mechanisms of the equatorial Pacific SST warming pattern in CMIP5 models. Advances in Atmospheric Sciences, 2016, 33(4): 433-441.

(3) Ying Jun and Ping Huang, The large-scale ocean dynamical effect on uncertainty in the tropical Pacific SST warming pattern in CMIP5 models. Journal of Climate, 2016, 29: 8051-8065.

(4) Ying Jun, Ping Huang, Tao Lian and Hongjian Tan, Understanding the effect of an excessive cold tongue bias on projecting the tropical Pacific SST warming pattern in CMIP5 models. Climate Dynamics, 2019, 52,1805-1818.

(5) Ying, Jun., P. Huang, T. Lian, and D. Chen, Intermodel Uncertainty in the Change of ENSO’s Amplitude under Global Warming: Role of the Response of Atmospheric Circulation to SST Anomalies. Journal of Climate, 2019, 32, 369-383.

(6) Huang Ping and Jun Ying, A multimodel ensemble pattern regression method to correct the tropical Pacific SST change patterns under global warming. Journal of Climate, 2016, 28: 4706-4723.

Table of contents (7 chapters)

Table of contents (7 chapters)
  • Introduction

    Pages 1-14

    Ying, Jun

  • Evaluating the Formation Mechanisms of the Tropical Pacific SST Warming Pattern in CMIP5 Multi-model Ensemble

    Pages 15-27

    Ying, Jun

  • Influence of Cloud Radiation Feedback on the Uncertainty in Projecting Tropical Pacific SST Warming Pattern

    Pages 29-44

    Ying, Jun

  • Effects of Large-Scale Ocean Dynamics on the Uncertainty in Projecting Tropical Pacific SST Warming Pattern

    Pages 45-64

    Ying, Jun

  • Correcting the Multi-model Ensemble Tropical Pacific SST Warming Pattern

    Pages 65-75

    Ying, Jun

Buy this book

eBook $89.00
price for Mexico
  • ISBN 978-981-329-844-6
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase Institutional customers should get in touch with their account manager
Hardcover $159.99
price for Mexico
Softcover $119.99
price for Mexico
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Bibliographic Information

Bibliographic Information
Book Title
Sources of Uncertainty in the Tropical Pacific Warming Pattern under Global Warming Projected by Coupled Ocean-Atmosphere Models
Authors
Series Title
Springer Theses
Copyright
2020
Publisher
Springer Singapore
Copyright Holder
Springer Nature Singapore Pte Ltd.
eBook ISBN
978-981-329-844-6
DOI
10.1007/978-981-32-9844-6
Hardcover ISBN
978-981-329-843-9
Softcover ISBN
978-981-329-846-0
Series ISSN
2190-5053
Edition Number
1
Number of Pages
XII, 81
Topics