AOSC614

Atmospheric Modeling, Data Assimilation and Predictability

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Prerequisite: AOSC610; or permission of instructor. Solid foundation for atmospheric and oceanic modeling and numerical weather prediction: numerical methods for partial differential equations, an introduction to physical parameterizations, modern data assimilation, and predictability.

Past Semesters

Eugenia Kalnay

0 reviews
Average rating: N/A

Eugenia Kalnay

0 reviews
Average rating: N/A

During the Spring 2020 and Spring 2021 semesters, students could choose to take some of their courses pass-fail mid-semester which skews grade data aggregated across multiple semesters.

Average GPA of 3.69 between 65 students*

AOSC614 Grade Distribution+-051015202530354045505560657075% of studentsABCDFWother
A-: 16.92%
A: 29.23%
A+: 27.69%
B: 7.69%
B+: 12.31%
C+: 1.54%
W: 1.54%
other: 3.08%
* "W"s are considered to be 0.0 quality points. "Other" grades are not factored into GPA calculation. Grade data not guaranteed to be correct.