Radiation in the Atmosphere and Ocean
ATMOCN 640 introduces radiation laws, radiative transfer, scattering, and energy budget applications in the atmosphere and ocean.
Summary
Recent recorded grades — Spring 2024: 3.57 GPA, 81.0% A/AB (n=21 letter grades); Spring 2025: 3.63 GPA, 94.7% A/AB (n=19 letter grades); Spring 2026: 3.75 GPA, 90.0% A/AB (n=20 letter grades).
Grade history
↗letter grades
All recorded terms · compare terms & instructors
Prerequisites
Course map(PHYSICS 202, 208, or 248) and MATH 234, or graduate/professional standing
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Prerequisite text tree
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Professors
Fall 2026No instructors recorded for this selection.
Historical instructors & teaching patterns
Recorded history may be incomplete and does not establish a future schedule.
Calendar & sections
Fall 2026Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
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Times are Central. Select a meeting for details; export includes recorded dates for the selected sections.
Meeting source records
No records available.
Student experience
the class
Recent recorded grades — Spring 2024: 3.57 GPA, 81.0% A/AB (n=21 letter grades); Spring 2025: 3.63 GPA, 94.7% A/AB (n=19 letter grades); Spring 2026: 3.75 GPA, 90.0% A/AB (n=20 letter grades).
difficulty & workload
No workload feedback recorded.
Topics
Skills
Grades
Latest available · Spring 2026— not enough history to project Fall 2026.
Grade distribution · % of letter grades
Grades over time
Through Spring 2026
More grade details Grade mix, volume & source data
Not enough comparable courses for Fall 2026 in UW–Madison.
Sources & history
Catalog & offerings
Descriptions, prerequisites, and recorded course offerings.
Catalog observation history
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Selected offering source records
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Raw records
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Student reviews
Original comments behind the course and instructor summaries.
Read original reviews
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Grade history
Recorded grade distributions by term, section, and instructor.
Explore recorded gradesModel outputs & technical records
LLM outputs across runs
Full model traces
Recorded model configuration, reasoning, and tool conversations.
Model & dataset provenance
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"model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
"task_version": "14",
"output_id": "2bc5e4560c6cd77e8915b020394e14aae519b526901e6e36f0c8e119b39605f9",
"requirements_status": "valid",
"dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
"observed_at": "2026-09-07 15:55:43.033547+00:00"
}