# Atmospheric and Space Scientists

> 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.

- **SOC code:** 19-2021.00
- **Canonical URL:** https://singulariki.com/roles/role-19-2021-00
- **Also known as:** Forecaster, General Forecaster, Meteorologist, Research Meteorologist, Broadcast Meteorologist, Hydrometeorological Technician (Hydrometeorological Tech), Ocean Monitoring and Data Assimilation Scientist, Service Hydrologist
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Develop or use mathematical or computer models for weather forecasting.
- 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.
- Conduct meteorological research into the processes or determinants of atmospheric phenomena, weather, or climate.
- Formulate predictions by interpreting environmental data, such as meteorological, atmospheric, oceanic, paleoclimate, climate, or related information.
- 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.
- Prepare forecasts or briefings to meet the needs of industry, business, government, or other groups.
- Direct forecasting services at weather stations or at radio or television broadcasting facilities.
- Gather data from sources such as surface or upper air stations, satellites, weather bureaus, or radar for use in meteorological reports or forecasts.
- Develop computer programs to collect meteorological data or to present meteorological information.
- Prepare weather reports or maps for analysis, distribution, or use in weather broadcasts, using computer graphics.
- Prepare scientific atmospheric or climate reports, articles, or texts.
- Develop and deliver training on weather topics.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Mathematics _(knowledge)_
- Physics _(knowledge)_
- Geography _(knowledge)_
- Oral Expression _(ability)_
- Computers and Electronics _(knowledge)_
- Reading Comprehension _(essential_skill)_
- Oral Comprehension _(ability)_
- Written Comprehension _(ability)_
- Inductive Reasoning _(ability)_
- Active Listening _(essential_skill)_
- Speaking _(essential_skill)_
- Science _(essential_skill)_

**Skills in demand:**
- Mathematics _(Common Skill)_
- Physics _(Specialized Skill)_
- Geography _(Specialized Skill)_
- Reading Comprehension _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Active Listening _(Common Skill)_
- Active Learning _(Common Skill)_
- Writing _(Common Skill)_
- Complex Problem Solving _(Common Skill)_
- English Language _(Common Skill)_

**Tools & technology:**
- Microsoft Office software _(hot technology, in demand)_
- Adobe Photoshop _(hot technology)_
- C++ _(hot technology)_
- Facebook _(hot technology)_
- IBM SPSS Statistics _(hot technology)_
- Linux _(hot technology)_
- Microsoft Access _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Windows _(hot technology)_
- Microsoft Word _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 96th percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 94th percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 87th percentile (High) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 92nd percentile (High) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 56th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 0.7% growth (About average); 0.7k annual openings; 9.4k → 9.5k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $97,450; 8,780 employed.

## How people actually use AI here

Anthropic Economic Index — measured AI conversations mapped to this occupation's tasks:

- **Automation vs augmentation:** 25% automation, 51% augmentation (usage-weighted).
- **Autonomy median:** 3.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** learning.

**Tasks most handed to AI here:**
- 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. _(2.0% of measured AI use; learning)_
- Conduct meteorological research into the processes or determinants of atmospheric phenomena, weather, or climate. _(0.9% of measured AI use; learning)_
- Gather data from sources such as surface or upper air stations, satellites, weather bureaus, or radar for use in meteorological reports or forecasts. _(0.9% of measured AI use; directive)_
- Design or develop new equipment or methods for meteorological data collection, remote sensing, or related applications. _(0.5% of measured AI use; directive)_
- Prepare weather reports or maps for analysis, distribution, or use in weather broadcasts, using computer graphics. _(0.4% of measured AI use; task iteration)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me 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.
- Help me conduct meteorological research into the processes or determinants of atmospheric phenomena, weather, or climate.
- Help me gather data from sources such as surface or upper air stations, satellites, weather bureaus, or radar for use in meteorological reports or forecasts.
- Help me design or develop new equipment or methods for meteorological data collection, remote sensing, or related applications.
- Help me prepare weather reports or maps for analysis, distribution, or use in weather broadcasts, using computer graphics.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-19-2021-00_