◆ Geography & Environment

What a climate analyst
really does.

20 tasks, each one witnessed by the sources that watched the job — and behind every one, a prompt you can use tonight.

20evidenced tasks
89,250in the US (2025)
$82,220median pay / year
9systems it runs on
See the 20 tasks ↓Open in the atlasThe full career map →
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Analyze climate policy data
Clean and merge the national emissions and temperature station dataset…2 sources agree

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The work, task by task

20 tasks
Hands on the work12
Analyze climate policy data+
Clean and merge the national emissions and temperature station datasets, run exploratory statistics to detect trends and anomalies for 1990–2025, and deliver a methods note plus a reproducible dataset with code and diagnostics for peer review.
jdonet2 agree
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Prepare policy briefs+
Draft a two-page policy brief for DEFRA summarising projected coastal flood risk under the central and high emissions scenarios, four clear policy recommendations, and one slide-ready figure showing affected population by 2050.
escojd2 agree
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Evaluate climate initiatives+
Evaluate the three city heat-pump incentive pilots using project-level KPIs, cost per tonne CO2e abated, and participant uptake; produce a ranked recommendation with sensitivity to 20% higher equipment costs.
escojd2 agree
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Prepare grant applications to obtain funding for programs related to climate change, environmental management, or sustainability.+
Prepare and submit the grant application for the coastal resilience study due next month, drafting aims, methods, budget justification, and a two‑page significance statement, then assemble CVs and letters of support for the funder review panel.
onet
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Collaborate with stakeholders+
Coordinate a stakeholder workshop with municipal planners, water utility leads and two NGO partners next Wednesday, circulate an agenda with data products to review, collect their feedback on proposed indicators, and record commitments for the follow‑up technical memo.
jd
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Analyse historic weather conditions+
Analyse historic weather conditions for the 1981–2010 baseline across the river basin, quality‑control station records, compute seasonal means and extremes, and produce a concise methods appendix with plots and data provenance.
esco
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Apply statistical analysis techniques+
Apply statistical analysis to the flood frequency dataset to estimate return periods, run uncertainty bounds with bootstrapping, compare three candidate distributions, and produce a short decision note recommending the preferred approach.
esco
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Advise on weather-related issues+
Advise the regional emergency manager on likely weather impacts for the next 72 hours, outline confidence levels and recommended actions for transport and utilities, and send the briefing to Hannah Park and the duty director by 10:00 tomorrow morning.
esco
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
Watch and assess4
Grow the practice4

What the work runs on

named inside the evidenced tasks
7 tasksPythoningests, cleans and performs statistical analysis with reproducible code and figures
7 tasksMicrosoft Wordformats concise policy text, headings and embeds the figure for circulationOpen its task library → 6 tasksMicrosoft Excelquick checks, pivot summaries and final table exports for reviewersOpen its task library →
5 tasksThe MathWorks MATLABoffers additional tools for time‑series analysis and figure production when needed
2 tasksMicrosoft PowerPointprepares the slide-ready figure for presentations
2 tasksESRI ArcGISmaps habitats, quantifies land-use change and supports spatial analysis for the assessment
2 tasksSASperforms rigorous statistical modelling, distribution fitting and bootstrapped uncertainty estimations for hydrological datasets
1 taskMicrosoft Officemanages calendaring, email invites, and shared agendas for stakeholder coordination
Browse every evidenced software task →

The same task, four heights

this page is height one
ExecuteDo today's task, with fewer mistakesyou are here → ImproveMake it easy for the next person to acceptin the atlas → DecideWork out the right move when it is unclearin the atlas → BecomeLearn the pattern so it stops coming backin the atlas →

Can AI actually do this job?

the honest answer

It can

where it genuinely helps
  • Explain the theory behind the work
  • Draft, tidy and structure your writing
  • Rehearse a hard conversation before you have it
  • Build a study plan that fits your gaps

It cannot

where it stops, completely
  • Be in the room where a climate analyst actually works
  • Carry the responsibility when the call is wrong — that weight stays yours
  • Notice what no one wrote down: the hesitation, the thing left unsaid
  • Live with the outcome

What the work pays

two countries, two different measures

United States

this exact occupation · BLS 2025
  • $82,220 a year — the middle: half earn more, half earn less
  • The lowest tenth earn near $52,520; the top tenth near $140,010
  • 89,250 people employed in this occupation

India

the occupation GROUP, not this job · PLFS via ILOSTAT 2025
  • ₹38,298 a month — the median for Professionals, the group this work sits in
  • India publishes pay by broad occupation group, so this covers many jobs besides this one. It is a shape, not a salary.
read this carefullyThese two numbers are not comparable and must not be converted into each other. One is a yearly figure for this job alone; the other is a monthly figure for a whole family of jobs. What travels between them is the pattern, not the amount: experience lifts pay almost everywhere.

Where the evidence lives

open any of it yourself
O*NETThe US Department of Labor's own record of this job4 of these tasks ESCOThe European skills and occupations register14 of these tasks Job descriptionsReal postings, in the wild6 of these tasks US Bureau of Labor StatisticsPay and employment, by occupation2025 figures UK NOS COS25Prepare a climate briefnational standard

Close to this work

12 nearby
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Questions people actually ask

You’ll split time between data work, meetings, and writing. Mornings often mean cleaning and analysing data in Python, R, SAS, or Excel and running models in MATLAB or GIS.

Afternoons go to meetings with stakeholders, preparing policy briefs or PowerPoint slides, and writing sections of environmental impact assessments or grant applications. Some days are fieldwork collecting weather data or checking instruments; other days are mostly desk-based modelling and report writing.

Start with Python and Excel. Python handles data cleaning, statistical analysis, and scripting; Excel is used for quick tables and basic charts that managers expect.

Next learn R for statistics, ESRI ArcGIS for maps, and MATLAB if your team runs custom numerical models. Word and PowerPoint are essential for reports and presentations. SAS is useful in some agencies; learn it if your job posting lists it.

According to the U.S. Bureau of Labor Statistics (BLS) for 2025, 89,250 people were employed as climate analysts or similar positions. The median pay was $82,220 per year.

The lowest tenth earned $52,520 and the top tenth earned $140,010. Use these as a range: local agency, level of experience, and whether you do grant-funded research affect where you land in that range.

Focus on a degree in atmospheric science, environmental science, geography, statistics, or a related field. Take courses in statistics, coding (Python or R), and GIS (ESRI ArcGIS).

Practice by doing small projects: analyse historic weather data, run a simple climate model in MATLAB or Python, and write a short policy brief. Contribute to open datasets or join internships to show hands-on skills.

A meteorologist focuses on short-term weather forecasting and advising on immediate weather issues, often using operational models and measurement instruments.

A climate analyst studies long-term climate trends, evaluates policy and climate initiatives, runs statistical analyses and climate models, and writes policy briefs or impact assessments. Both may use similar tools (Python, MATLAB, instruments), but the time scale and goals differ.

Use AI to speed routine tasks: draft text for policy briefs, summarize papers, or generate code templates in Python or R. Always check AI outputs against your data, models, and primary sources; AI can invent numbers or citations.

For model work, never accept AI-suggested results without rerunning analyses, verifying statistical assumptions, and checking code in your environment (e.g., MATLAB, SAS). Keep a reproducible workflow and document every step for audits and grant applications.

Clear technical writing and the ability to prepare focused policy briefs and grant applications matter a lot. Many candidates excel at modelling but struggle to explain results to non-technical stakeholders.

Also overlooked: reproducible coding practices (version control, well-documented Python/R scripts), and basic GIS skills to make maps in ESRI ArcGIS. Those make your work usable by policy teams and funders.