Modeling Dynamic Climate Systems (Modeling Dynamic Systems)

This ability to model dynamic systems is already having a powerful influence on teaching and studying complexity. The books in this series will promote this.
Table of contents

Earth system modelling

General circulation models GCMs are valuable tools for developing a quantitative understanding of climate dynamics and climate change, and studies conducted using GCMs have provided important insights into the climate of the Last Glacial Maximum LGM. The equations are sufficiently complex that analytic solutions do not exist, and thus the equations must be solved by numerical methods. The atmosphere and ocean are divided into grid boxes, and the equations are solved for each of the boxes. The numerical solution of the equations governing fluid motion for this large number of grid boxes requires substantial computing power.

Article in

Washington and Parkinson provided a detailed description of GCMs and their construction. GCMs are among the most comprehensive members of the more general category of climate models.


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Simpler climate models reduce the complexity of the climate system, most often by averaging over one or more spatial dimensions. Although such simpler climate models have been useful in understanding Quaternary climate change, they are not the focus of this article. Instead, the focus is limited to results that have been obtained with the following types of climate models, listed in order of increasing complexity: The decision to narrow the focus is made in order to keep the scope of this article manageable and to recognize the historical importance of these models.

The geometric and the ergodic theories of dynamical systems represent significant achievements of the twentieth century.

Modeling and Simulation of Dynamical Systems

Historically, theoretical developments in climate dynamics have been largely motivated by these two complementary approaches, based on the works of Lorenz and that of Hasselmann, respectively. It now seems clear that these two approaches complement, rather than exclude each other. Incomplete knowledge of small-, subgrid-scale processes, as well as computational limitations, will always require one to account for these processes in a stochastic way. As a result of sensitive dependence on initial data and on parameters, numerical weather forecasts and climate projections are both expressed these days in probabilistic terms.

We summarize here the results on the surprisingly complex statistical structure that characterizes stochastic nonlinear systems.

Climate Dynamics

The greater American Southwest of the North American continent is a region typified by great topographic diversity formed by a complex interaction of numerous continental plates. During the Holocene the region has been characterized by dynamic climate and vegetation change that has been amplified by topography, that has served both to impede the flow of moisture-laden storms from the Pacific to the west and to channel monsoonal storms northward from the Gulf of California and the Gulf of Mexico.

Climatically, the region has been influenced by three weather patterns characterized by differences in seasonal distribution of rainfall and temperature. Displacement of winter and summer storm tracks, and variations in the penetration of summer monsoon have all been affected by the realignment of these weather patterns through time. Movements of these systems during the Holocene have had a dynamic affect upon both local and regional climates, and is reflected in the palaeoecological proxy record by changes in hydrology, erosion and deposition processes, as well as in vegetation.

It is the pollen and plant macrofossil records of the region that provide some of the basic information for reconstructing this climate history. Cenozoic climate changes provide a great opportunity to study climate processes under boundary conditions different from today.


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The transition from the warm climates of the Paleocene to the glacial world of the Pleistocene offers the possibility to study long-term climate changes on a million-year scale as well as short-term events occurring within millennia or even decades. A better understanding can be achieved by simplified and idealized models. Such models often stimulate the formulation of new theoretical concepts and new directions of thought.

In this spirit the research group is currently concerned with the following projects:. The role of convective available potential enery for tropical cyclone intensification. CRG Dynamical Systems On the role of convective available potential energy CAPE in tropical cyclone intensification. Journal of Advances in Modeling Earth Systems, 9 , Climate Change Joseph Romm.

Wine and Place Patrick J. Introducing Meteorology Jon Shonk. Teach Yourself Peter Inness. Top 10 of Everything Paul Terry. The Almanac Lia Leendertz.

Information on CliSAP Publications

Expaining the Weather Jim Ross. A Vast Machine Paul N. The Weather Experiment Peter Moore. Climate Wars Gwynne Dyer. Global Crisis Geoffrey Parker. Hunting Nature's Fury Roger Hill. Cloud and Precipitation Microphysics Jerry M. The Nature of the Environment Andrew S.

Introduction to climate dynamics and climate modelling - Modelling the climate system

Other books in this series. Landscape Simulation Modeling A. Dynamic Modeling Bruce Hannon.