American Institute of Mathematical Sciences

Advanced
  • Previous Article
    Global asymptotics of Hermite polynomials via Riemann-Hilbert approach
  • DCDS-B Home
  • This Issue
  • Next Article
    The hypercircle theorem for elastic shells and the accuracy of Novozhilov's simplified equations for general cylindrical shells
May  2007, 7(3): 651-660. doi: 10.3934/dcdsb.2007.7.651

Simple climate modeling

Ka Kit Tung 1,

1. 

University of Washington, Department of Applied Mathematics, Box 352420, Seattle, WA 98195-2420

Received  October 2006 Revised  January 2007 Published  February 2007

We consider a simple climate model of global warming to help understand and constrain predictions from the more comprehensive General Circulation Models (GCMs). By using observations to constrain the climate gain factor, which presents the greatest uncertainty in GCMs, we discuss the atmosphere's response to a doubling of carbon dioxide concentration in the atmosphere in both equilibrium and time-dependent states.
Keywords: Global warming, mathematical modeling..
Mathematics Subject Classification: 86-01, 86A15, 86A1.
Citation: Ka Kit Tung. Simple climate modeling. Discrete & Continuous Dynamical Systems - B, 2007, 7 (3) : 651-660. doi: 10.3934/dcdsb.2007.7.651
[1]

Avner Friedman, Wenrui Hao. Mathematical modeling of liver fibrosis. Mathematical Biosciences & Engineering, 2017, 14 (1) : 143-164. doi: 10.3934/mbe.2017010
[2]

Gang Bao. Mathematical modeling of nonlinear diffracvtive optics. Conference Publications, 1998, 1998 (Special) : 89-99. doi: 10.3934/proc.1998.1998.89
[3]

Baba Issa Camara, Houda Mokrani, Evans K. Afenya. Mathematical modeling of glioma therapy using oncolytic viruses. Mathematical Biosciences & Engineering, 2013, 10 (3) : 565-578. doi: 10.3934/mbe.2013.10.565
[4]

Victor Fabian Morales-Delgado, José Francisco Gómez-Aguilar, Marco Antonio Taneco-Hernández. Mathematical modeling approach to the fractional Bergman's model. Discrete & Continuous Dynamical Systems - S, 2020, 13 (3) : 805-821. doi: 10.3934/dcdss.2020046
[5]

Karly Jacobsen, Jillian Stupiansky, Sergei S. Pilyugin. Mathematical modeling of citrus groves infected by huanglongbing. Mathematical Biosciences & Engineering, 2013, 10 (3) : 705-728. doi: 10.3934/mbe.2013.10.705
[6]

Bashar Ibrahim. Mathematical analysis and modeling of DNA segregation mechanisms. Mathematical Biosciences & Engineering, 2018, 15 (2) : 429-440. doi: 10.3934/mbe.2018019
[7]

Natalia L. Komarova. Mathematical modeling of cyclic treatments of chronic myeloid leukemia. Mathematical Biosciences & Engineering, 2011, 8 (2) : 289-306. doi: 10.3934/mbe.2011.8.289
[8]

Jeong-Mi Yoon, Volodymyr Hrynkiv, Lisa Morano, Anh Tuan Nguyen, Sara Wilder, Forrest Mitchell. Mathematical modeling of Glassy-winged sharpshooter population. Mathematical Biosciences & Engineering, 2014, 11 (3) : 667-677. doi: 10.3934/mbe.2014.11.667
[9]

Evans K. Afenya. Using Mathematical Modeling as a Resource in Clinical Trials. Mathematical Biosciences & Engineering, 2005, 2 (3) : 421-436. doi: 10.3934/mbe.2005.2.421
[10]

Adélia Sequeira, Rafael F. Santos, Tomáš Bodnár. Blood coagulation dynamics: mathematical modeling and stability results. Mathematical Biosciences & Engineering, 2011, 8 (2) : 425-443. doi: 10.3934/mbe.2011.8.425
[11]

Yueping Dong, Rinko Miyazaki, Yasuhiro Takeuchi. Mathematical modeling on helper T cells in a tumor immune system. Discrete & Continuous Dynamical Systems - B, 2014, 19 (1) : 55-72. doi: 10.3934/dcdsb.2014.19.55
[12]

Alacia M. Voth, John G. Alford, Edward W. Swim. Mathematical modeling of continuous and intermittent androgen suppression for the treatment of advanced prostate cancer. Mathematical Biosciences & Engineering, 2017, 14 (3) : 777-804. doi: 10.3934/mbe.2017043
[13]

Alexander V. Budyansky, Kurt Frischmuth, Vyacheslav G. Tsybulin. Cosymmetry approach and mathematical modeling of species coexistence in a heterogeneous habitat. Discrete & Continuous Dynamical Systems - B, 2019, 24 (2) : 547-561. doi: 10.3934/dcdsb.2018196
[14]

Elpiniki Nikolopoulou, Steffen E. Eikenberry, Jana L. Gevertz, Yang Kuang. Mathematical modeling of an immune checkpoint inhibitor and its synergy with an immunostimulant. Discrete & Continuous Dynamical Systems - B, 2021, 26 (4) : 2133-2159. doi: 10.3934/dcdsb.2020138
[15]

Loïc Louison, Abdennebi Omrane, Harry Ozier-Lafontaine, Delphine Picart. Modeling plant nutrient uptake: Mathematical analysis and optimal control. Evolution Equations & Control Theory, 2015, 4 (2) : 193-203. doi: 10.3934/eect.2015.4.193
[16]

Lisette dePillis, Trevor Caldwell, Elizabeth Sarapata, Heather Williams. Mathematical modeling of regulatory T cell effects on renal cell carcinoma treatment. Discrete & Continuous Dynamical Systems - B, 2013, 18 (4) : 915-943. doi: 10.3934/dcdsb.2013.18.915
[17]

Alessia Berti, Claudio Giorgi, Angelo Morro. Mathematical modeling of phase transition and separation in fluids: A unified approach. Discrete & Continuous Dynamical Systems - B, 2014, 19 (7) : 1889-1909. doi: 10.3934/dcdsb.2014.19.1889
[18]

John A. Adam. Inside mathematical modeling: building models in the context of wound healing in bone. Discrete & Continuous Dynamical Systems - B, 2004, 4 (1) : 1-24. doi: 10.3934/dcdsb.2004.4.1
[19]

Donna J. Cedio-Fengya, John G. Stevens. Mathematical modeling of biowall reactors for in-situ groundwater treatment. Mathematical Biosciences & Engineering, 2006, 3 (4) : 615-634. doi: 10.3934/mbe.2006.3.615
[20]

Urszula Ledzewicz, Shuo Wang, Heinz Schättler, Nicolas André, Marie Amélie Heng, Eddy Pasquier. On drug resistance and metronomic chemotherapy: A mathematical modeling and optimal control approach. Mathematical Biosciences & Engineering, 2017, 14 (1) : 217-235. doi: 10.3934/mbe.2017014

2020 Impact Factor: 1.327

Tools

Metrics

  • PDF downloads (55)
  • HTML views (0)
  • Cited by (2)

Other articles
by authors

[Back to Top]

Copyright © 2021 American Institute of Mathematical Sciences