Develop and deliver training on weather topics.
Work task
“Develop and deliver training on weather topics.” is a core task performed by Atmospheric and Space Scientists. Among the occupation's 27 rated tasks, workers place it 17th by importance (#11 most important). About 85% of workers say it is relevant to their job.
This is a single occupation-specific task statement from O*NET. The figures below describe how central the task is to the job and what independent studies measure about AI and this kind of work — not a prediction that the task will be automated.
Work activities this task rolls up to
O*NET groups concrete tasks into broader work activities shared across many occupations.
AI exposure
The OpenAI / Eloundou “GPTs are GPTs” study rates this task E2. Exposure with tools — software built on top of a language model (not the model alone) could cut the time by at least half.
Exposure measures whether a model could meaningfully speed the task up — it is an estimate of overlap with model capabilities, not a measure of whether the work will be done by software. The study's intermediate score (β) for this task is 0.50. Automation potential label: T2.
Other tasks in this occupation
- Develop or use mathematical or computer models for weather forecasting. · importance 4.5
- Interpret data, reports, maps, photographs, or charts to predict long- or short-range weather conditions, using computer models and knowledge of climate theory, physics, and mathematics. · importance 4.4
- Conduct meteorological research into the processes or determinants of atmospheric phenomena, weather, or climate. · importance 4.3
- Formulate predictions by interpreting environmental data, such as meteorological, atmospheric, oceanic, paleoclimate, climate, or related information. · importance 4.3
- Broadcast weather conditions, forecasts, or severe weather warnings to the public via television, radio, or the Internet or provide this information to the news media. · importance 4.1
- Prepare forecasts or briefings to meet the needs of industry, business, government, or other groups. · importance 4.1
- Direct forecasting services at weather stations or at radio or television broadcasting facilities. · importance 4.1
- Gather data from sources such as surface or upper air stations, satellites, weather bureaus, or radar for use in meteorological reports or forecasts. · importance 4.0
- Develop computer programs to collect meteorological data or to present meteorological information. · importance 4.0
- Prepare weather reports or maps for analysis, distribution, or use in weather broadcasts, using computer graphics. · importance 3.9
- Prepare scientific atmospheric or climate reports, articles, or texts. · importance 3.8
- Collect air samples from planes or ships over land or sea to study atmospheric composition. · importance 3.8
- Analyze climate data sets, using techniques such as geophysical fluid dynamics, data assimilation, or numerical modeling. · importance 3.8
- Analyze historical climate information, such as precipitation or temperature records, to help predict future weather or climate trends. · importance 3.7
See all tasks on the Atmospheric and Space Scientists page.
Sources for this page
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
- O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
- “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
Data compiled June 2, 2026. Figures are estimates, not advice.
Cite this page
Singulariki. "Develop and deliver training on weather topics.." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026. https://singulariki.com/tasks/task-21105
Singulariki. (2026). Develop and deliver training on weather topics.. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/tasks/task-21105
@misc{singulariki-task-21105,
title = {Develop and deliver training on weather topics.},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026},
url = {https://singulariki.com/tasks/task-21105}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.