Atmospheric and Space Scientists
In short: today's best AI models could do about 29% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about 76% by the end of 2028 if progress keeps its long-run pace. The people and hands-on work, about 9% of the time, stays with people.
Investigate atmospheric phenomena and interpret meteorological data, gathered by surface and air stations, satellites, and radar to prepare reports and forecasts for public and other uses. Includes weather analysts and forecasters whose functions require the detailed knowledge of meteorology.
10,000 people do this job in the US. $99,070 a year.
A typical 40-hour week
Not yet reviewed task by task- AI could take on12 h
- A person checks AI's work0 h
- Desk work AI can't do yet25 h
- Stays with people3 h
Atmospheric and Space Scientists, now: of a 40-hour week, AI could take on 12 hours, 0 hours become checking its work, 25 hours are desk work it can't do yet, and 3 hours stay with people.
The largest pieces: Formulate predictions by interpreting environmental data, such as meteorological, atmospheric, oceanic, paleoclimate, climate, or related information (about 2 h); 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 (about 2 h); Develop or use mathematical or computer models for weather forecasting (about 1 h).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 91%
- 6%
- 3%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 0%. With Claude Mythos Preview (early), measured in April 2026, 8%. Today's estimate: 29%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, no reportable share went to this job's tasks in May 2026; 0 of its 27 tasks showed up. Within each of Anthropic's methods, never across a change: 0.075% to 0.12% (released February and March 2025); 0.096% to 0.064% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.075% | 215 of 708 | 5 of 27 |
| Released March 2025 | 0.12% | 133 of 703 | 10 of 27 |
| The week of Aug 4, 2025 (released September 2025) | 0.096% | 160 of 655 | 5 of 27 |
| The week of Nov 13, 2025 (released January 2026) | 0.052% | 229 of 672 | 6 of 27 |
| The week of Feb 5, 2026 (released March 2026) | 0.064% | 217 of 677 | 9 of 27 |
| April 2026 (released June 2026) | none | n/a | 0 of 27 |
| May 2026 (released June 2026) | none | n/a | 0 of 27 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates 1% of this job's working time as physical work. For 1% of the working time, a robot has been shown doing most of the task somewhere: 1% in a structured facility. 0.03 of 3, the 633rd highest of the 923 jobs.
- Not physical 99%
- In a structured facility 1%
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
The tasks
Sorted by . 27 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Develop or use mathematical or computer models for weather forecasting.Done hourly or more by most who do it. | 7% | 6.7 h1.7 h to 2.5 work days | 55%Half by now | |
| Develop computer programs to collect meteorological data or to present meteorological information.Done more than monthly by most who do it. | 7% | 1.7 work days3.3 h to 1.7 work weeks | 20%Half by Aug 2027 | |
| Analyze climate data sets, using techniques such as geophysical fluid dynamics, data assimilation, or numerical modeling.Done more than yearly by most who do it. | 7% | 2.5 work days3.3 h to 2.5 work weeks | 9%Half by Mar 2028 | |
| Prepare scientific atmospheric or climate reports, articles, or texts.Done more than yearly by most who do it. | 7% | 4.2 work days6.7 h to 3.5 work weeks | 5%Half by Apr 2028 | |
| Design or develop new equipment or methods for meteorological data collection, remote sensing, or related applications.Done yearly or less by most who do it. | 7% | 1.7 work weeks1.7 work days to 2.3 work months | 1%Half by Jan 2029 | |
| Research the impact of industrial projects or pollution on climate, air quality, or weather phenomena.Done yearly or less by most who do it. | 7% | 1.7 work weeks1.7 work days to 1.5 work months | 1%Half by Oct 2028 | |
| Conduct meteorological research into the processes or determinants of atmospheric phenomena, weather, or climate.Done more than monthly by most who do it. | 7% | 3.3 work weeks4.2 work days to 2.4 work months | 0%Half by Jan 2029 | |
| Analyze historical climate information, such as precipitation or temperature records, to help predict future weather or climate trends.Done more than monthly by most who do it. | 7% | 1.7 work days2.5 h to 1.7 work weeks | 16%Half by Oct 2027 | |
| Conduct wind assessment, integration, or validation studies.Done more than monthly by most who do it. | 5% | 4.2 work days6.7 h to 3.3 work weeks | 5%Half by Apr 2028 | |
| Formulate predictions by interpreting environmental data, such as meteorological, atmospheric, oceanic, paleoclimate, climate, or related information.Done several times a day by most who do it. | 5% | 2.5 h50 min to 1.3 work days | 87%Half by now | |
| Apply meteorological knowledge to issues such as global warming, pollution control, or ozone depletion.Done more than yearly by most who do it. | 4% | 2.5 work days3.3 h to 1.7 work weeks | 12%Half by Nov 2027 | |
| Direct forecasting services at weather stations or at radio or television broadcasting facilities.Done daily by most who do it. | 4% | 6.7 h1.7 h to 4.2 work days | Stays with people |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
- Hydrologists6% now, 66% by 2028
- Geoscientists, Except Hydrologists and Geographers20% now, 80% by 2028
- Remote Sensing Scientists and Technologists34% now, 79% by 2028
- Data Scientists71% now, 95% by 2028
- Geographic Information Systems Technologists and Technicians68% now, 99% by 2028
- Geological Technicians, Except Hydrologic Technicians34% now, 41% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of Atmospheric and Space Scientists is within reach of AI now?
- An estimated 29% of the working time is within reach of AI models now and 76% by the end of 2028, on METR's long-run pace at four in five (52% to 88% across the three paces the site shows). Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Atmospheric and Space Scientists come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Formulate predictions by interpreting environmental data, such as meteorological, atmospheric, oceanic, paleoclimate, climate, or related information (87% of the task's time now, 100% by the end of 2028); 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 (94% of the task's time now, 100% by the end of 2028); and Develop or use mathematical or computer models for weather forecasting (55% of the task's time now, 100% by the end of 2028).
- Which tasks of Atmospheric and Space Scientists stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Direct forecasting services at weather stations or at radio or television broadcasting facilities; Collect air samples from planes or ships over land or sea to study atmospheric composition; and Teach college-level courses on topics such as atmospheric and space science, meteorology, or global climate change. Together such tasks are about 9% of the working time.
- Do people already use AI for the work of Atmospheric and Space Scientists?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 4%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Atmospheric and Space Scientists?
- Anthropic's robot exposure rating (September 2026) finds 1% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 1% of the working time, 1% in a structured facility. Its index is 0.03 of 3. One example: NOAA GML Programmable Flask Package (PFP) + Programmable Compressor Package (PCP) for "collect air samples from planes or ships over land or sea to study atmospheric composition". A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 27 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, each classed as desk, people or body work, and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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