Climate Models: Basics and Uncertainties

Related lectures (30)

Covers numerical differentiation, forward differences, Taylor's expansion, Big O notation, and error minimization.

Covers the Runge-Kutta method for approximating solutions of differential equations.

Explores inverse monotonicity in numerical methods for differential equations, emphasizing stability and convergence criteria.

Explores climate scenarios, tipping points, and cost-benefit uncertainties in climate change.

Covers error division and schemes for solving differential equations.

Covers the basics of the climate system, climate change, and the Earth's energy balance.

Explores transient stability in power systems dynamics, covering algebraic equations, generator models, and numerical integration techniques.

Covers Euler and Crank-Nicolson methods for solving differential equations.

Explores the Predictor-Corrector method for the harmonic oscillator and Runga-Kutta method in differential equations.

Covers the analysis of speed variation using differential equations and small time intervals.

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