Design or develop new equipment or methods for meteorological data collection, remote sensing, or related applications.

“Design or develop new equipment or methods for meteorological data collection, remote sensing, or related applications.” is a core task performed by Atmospheric and Space Scientists. Among the occupation's 27 rated tasks, workers place it 10th by importance (#18 most important). About 65% 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.

• Develop research plans or methodologies. in Thinking Creatively

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: T1.

How AI is actually used on this kind of task

The Anthropic Economic Index observes how people actually use AI on tasks like this one across millions of real conversations.

• 0.003% share of AI-use records mapped to this task
• 56% of that use is work-related
• Most common interaction: directive
• Average autonomy of the AI: 3.5 (1–5; higher = more autonomous)
• 71% of interactions still needed a human in the loop

Observed AI use describes people choosing to use AI as a tool on this kind of task today. It is augmentation and assistance, not a measure of jobs replaced.

Working with AI vs. handing it off

Of the AI conversations mapped to this task, the split between people working alongside AI and people delegating the task to it.

How people interact with AI on this task

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
• Develop and deliver training on weather topics. · 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

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
• Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
• “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic

Data compiled June 2, 2026. Figures are estimates, not advice.

@misc{singulariki-task-9083,
  title  = {Design or develop new equipment or methods for meteorological data collection, remote sensing, or related applications.},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026},
  url    = {https://singulariki.com/tasks/task-9083}
}