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HU Credits:
2
Degree/Cycle:
1st degree (Bachelor)
Responsible Department:
Atmospheric Sciences
Semester:
1st Semester
Teaching Languages:
Hebrew
Campus:
E. Safra
Course/Module Coordinator:
Dr. Chaim Garfinkel
Coordinator Office Hours:
Teaching Staff:
Dr. Chaim Garfinkel
Course/Module description:
Detailed projections of future climate change are created using sophisticated computational models that simulate the physical dynamics of the oceans and atmosphere and their interaction with biological and chemical processes around the globe. These models have evolved over the last 60 years as scientists' understanding of the climate system has improved. This course provides an introduction to the science behind climate change, to the computational techniques used in constructing global climate models, and to the successes and failures of modern climate models. The course will also provide a historical perspective on climate modelling, from the early ENIAC weather simulations created by von Neumann and Charney, through to today's Earth System Models, and the role that these models play in the scientific assessments of the UN's Intergovernmental Panel on Climate Change (IPCC). The course will also address lingering uncertainties in projected future climate, and specifically the aspects of these models that are still undergoing improvement.
Additional topics, based on the availability of guest lecturers, may include the use of computational models for hydrological flood assessments, inner earth processes, and the demonstration of how computer science tools, such as stochastic approaches, machine learning and big data, and pattern recognition, are used in earth sciences research.
Course/Module aims:
Learning outcomes - On successful completion of this module, students should be able to:
Students will be able to
Explain fundamental principles and theoretical concepts of simulating Earth’s climate system, its components, and energy and material fluxes among them
Simulate climate using a range of computer programs
Analyze large datasets of complex climate model simulations
Compare climate model output to observations
Evaluate the accuracy of a given numerical scheme for computing a spatial derivative or integrating forward in time.
Understand problems, challenges and uncertainties in climate modeling
Attendance requirements(%):
100
Teaching arrangement and method of instruction:
Lectures+6 assignments +project+final
Course/Module Content:
Draft set of weekly topics:
(1) History of climate and weather numerical modelling. Early climate science and weather forecasting before the advent of the computer. ENIAC runs. Co-development of climate models and super-computers. Quick overview of range of current models.
(2) Crash course on the thermodynamics of the atmosphere and ocean. What equations need to be solved? (HW #1)
(3) What governs Earth's surface temperature? energy balance model with no atmosphere and with a single atmospheric level. Adding latitudinal dependence. The need for computational solutions (HW #2)
(4+5+6) Numerical solutions of partial differential equations. von Neuman Stability Analysis. CFL condition. The diversity of methods to compute spatial derivatives. (HW #3-5)
(7) Intermediate climate models. Adding a layered atmosphere to a basic energy balance model. Multiple equilibria. Coupling in other earth systems (e.g. glaciers and sea ice). 3-D models. The importance of the PDE solver. (HW #6)
(8) Comprehensive earth system climate models - Using models to study interactions in the earth system. Overview of key systems (carbon cycle, hydrology, ice dynamics, biogeochemistry). Comparing models against observations. Model intercomparison projects.
(9-13) Lectures by faculty members from the Earth Science Institute on numerical models in the earth science. (project to be coordinated with faculty member or with Chaim). Possible topics include hydrological flood assessment models. stochastic weather generators, and models of the Earth's interior.
(14) The future. Projecting future climates. Role of modelling in the IPCC assessments. Uncertainties in model projections
Required Reading:
Goosse H., P.Y. Barriat, W. Lefebvre, M.F. Loutre and V. Zunz. Introduction to climate dynamics and climate modeling. Free online textbook available at http://www.climate.be/textbook.
Additional Reading Material:
Course/Module evaluation:
End of year written/oral examination 60 %
Presentation 0 %
Participation in Tutorials 0 %
Project work 20 %
Assignments 20 %
Reports 0 %
Research project 0 %
Quizzes 0 %
Other 0 %
Additional information:
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