Numbering Code	G-SCI31 65051 LJ58	Year/Term	2022 ・ Second semester
Number of Credits	2	Course Type	Lecture
Target Year	Master's students	Target Student
Language	Japanese	Day/Period
Instructor name	ENOMOTO TAKESHI (Disaster Prevention Research Institute Professor) YOSHIDA AKIRA (Disaster Prevention Research Institute Associate Professor)
Outline and Purpose of the Course	Numerical Weather Prediction is based on computer simulation of the atmospheric motion. A computer program based on the equations of fluid dynamics and thermodynamics, or atmospheric general circulation model (AGCM), is used to simulate planetary scale flows. The initial values of the simulation is produced from observations by data assimilation (DA). The overview of AGCM and DA is given in this course. NWP is conducted repeating forecast by AGCM and analysis by DA. AGCM is used not only in NWP, but in numerical experiments to understand various atmospheric phenomena as a ‘virtual laboratory.’ In addition AGCM is an essential component of atmosphere-ocean coupled models or earth-system models that are used in climate prediction and global warming projection. Simulations produced with an AGCM and reanalysis that assimilates observations are used in analytic studies or as initial and boundary conditions. Therefore, the knowledge on AGCM and DA is essential not just in the development of AGCM and DA themselves, but in research in all areas of meteorology in various temporal and spatial scales.
Course Goals	* To acquire knowledge on the components, formulations, and numerical methods of AGCM as well as the mathematical background and various algorithms of DA. * To become familiar with the kinds and features of datasets produced using AGCM and DA. * To understand the atmospheric predictability and its variation and to learn various techniques used in ensemble forecast as an application.
Schedule and Contents	1. History of NWP 2. Governing equations and atmospheric waves 3. Dynamical process of AGCM 4. Physical process of AGC 5. Basics of DA 6. Advanced DA algorithms 7. Atmospheric predictability 8. Ensemble forecast
Course Requirements	Assumes basic understanding of Calculus, Linear Algebra, Vector Analysis, Dynamics, Thermodynamics. Knowledge on Dynamic Meteorology and numerical methods would help a deeper understanding of the course. Necessary topics in mathematics, classical physics and meteorology will be reviewed in the course.
Study outside of Class (preparation and review)	Assignments must be finished by the next class. The answers are presented by appointed students.
Textbooks	Textbooks/References	Lecture notes (in Japanese) are provided.
References, etc.	Atmospheric Modeling, Data Assimilation and Predictability, Eugenia Kalnay, (Cambridge), ISBN:9780521796293, Many topics appear in the course are covered, but somewhat outdated. The Emergence of Numerical Weather Prediction, Peter Lynch, (Cambridge), ISBN:9780521857291, Describes the history and numerical methods of NWP. An Introduction to Dynamic Meteorology, Jame R. Holton and Gregory Hakim, (Elsevier), ISBN:9780123848666, A must-read for students who are not familiar with dynamic meteorology.