বায়ুমণ্ডলীয় বিজ্ঞানী

Name: বায়ুমণ্ডলীয় বিজ্ঞানী — published AI exposure indices
Creator: AI Changing Work

জীবন, ভৌত ও সামাজিক বিজ্ঞান

AI এক্সপোজার

ডেটার উৎস: BLSপ্রকাশকাল: '26.08
অত্যন্ত উচ্চ· আপেক্ষিক
কমচারটি আপেক্ষিক স্তরঅত্যন্ত উচ্চ
পেশা-গোষ্ঠী পর্যায়ের মান
স্কেল, ভিত্তি ও উৎস
চারটি আপেক্ষিক স্তর (কম / মাঝারি / উচ্চ / অত্যন্ত উচ্চ)
BLS কর্মসংস্থান পূর্বাভাস সারণির 831টি বিস্তারিত পেশার ভিত্তিতে। মান NEM (ন্যাশনাল এমপ্লয়মেন্ট ম্যাট্রিক্স) কোড অনুযায়ী দেওয়া হয়, তাই একই NEM কোডের পেশাগুলি একই ব্যান্ড পায়
উৎস ডেটাসেট (XLSX ফাইল ডাউনলোড)
ডেটার উৎস: Anthropicপ্রকাশকাল: '26.03
0.038
0.000এখানে থাকা মানগুলোর পরিসর0.745
স্কেল, ভিত্তি ও উৎস
পর্যবেক্ষিত এক্সপোজার সূচক, প্রকাশিত রূপে 0–1
O*NET টাস্কে ম্যাপ করা
উৎস ডেটাসেট
ডেটার উৎস: ILOপ্রকাশকাল: '25
0.54
0.09এখানে থাকা মানগুলোর পরিসর0.70
পেশা-গোষ্ঠী পর্যায়ের মান
স্কেল, ভিত্তি ও উৎস
জেনারেটিভ AI এক্সপোজার সূচক, প্রকাশিত রূপে 0–1
ISCO-08 ইউনিট গ্রুপ — একই কোডের সব পেশা এই মানই পায়
এটি এই সাইটের হিসাব, ILO-এর প্রকাশিত সংখ্যা নয়: এই সাইট ILO ডেটাসেটের সঙ্গে যুক্ত করা ১,০১২টি পেশার মধ্যে 13% এই মানের সমান বা তার বেশি।
উৎস ডেটাসেট

এই উৎস কী ধরনের মান প্রকাশ করে

BLS-এর শ্রেণিবিভাগ একটি আপেক্ষিক র্যাঙ্ক, পরম মাত্রা নয়, এবং এটি সরাসরি পরিমাপও নয়: এটি কয়েকটি প্রকাশিত গবেষণায় পাওয়া পেশার পার্সেন্টাইল র্যাঙ্কগুলিকে চারটি স্তরে ভাগ করে। এটি কর্মসংস্থান বা মজুরির পূর্বাভাস নয়, গ্রহণের সম্ভাবনাও নয়, এবং এটি স্বয়ংক্রিয়তা ও সম্প্রসারণের মধ্যে পার্থক্য করে না।

Task-level exposure

25টি লুকানো কাজ দেখুন

Task	Claude.aiRaw / share %	APIRaw / share %
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. 19-2021	0.00000.0	0.020066.7
Formulate predictions by interpreting environmental data, such as meteorological, atmospheric, oceanic, paleoclimate, climate, or related information. 19-2021	0.00000.0	0.010033.3

Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.

Task	βE1 + 0.5 × E2
Develop or use mathematical or computer models for weather forecasting. O*NET Task ID 20208	1.0
Prepare scientific atmospheric or climate reports, articles, or texts. O*NET Task ID 20211	1.0
Speak to the public to discuss weather topics or answer questions. O*NET Task ID 21103	1.0
Develop computer programs to collect meteorological data or to present meteorological information. O*NET Task ID 21104	1.0
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. O*NET Task ID 9068	0.5
Gather data from sources such as surface or upper air stations, satellites, weather bureaus, or radar for use in meteorological reports or forecasts. O*NET Task ID 9069	0.5
Prepare forecasts or briefings to meet the needs of industry, business, government, or other groups. O*NET Task ID 9070	0.5
Direct forecasting services at weather stations or at radio or television broadcasting facilities. O*NET Task ID 9076	0.5
Conduct numerical simulations of climate conditions to understand and predict global or regional weather patterns. O*NET Task ID 9079	0.5
Design or develop new equipment or methods for meteorological data collection, remote sensing, or related applications. O*NET Task ID 9083	0.5
Analyze climate data sets, using techniques such as geophysical fluid dynamics, data assimilation, or numerical modeling. O*NET Task ID 19755	0.5
Conduct wind assessment, integration, or validation studies. O*NET Task ID 19756	0.5
Create visualizations to illustrate historical or future changes in the Earth's climate, using paleoclimate or climate geographic information systems (GIS) databases. O*NET Task ID 19757	0.5
Estimate or predict the effects of global warming over time for specific geographic regions. O*NET Task ID 19758	0.5
Formulate predictions by interpreting environmental data, such as meteorological, atmospheric, oceanic, paleoclimate, climate, or related information. O*NET Task ID 19759	0.5
Perform managerial duties, such as creating work schedules, creating or implementing staff training, matching staff expertise to situations, or analyzing performance of offices. O*NET Task ID 20202	0.5
Consult with other offices, agencies, professionals, or researchers regarding the use and interpretation of climatological information for weather predictions and warnings. O*NET Task ID 20203	0.5
Teach college-level courses on topics such as atmospheric and space science, meteorology, or global climate change. O*NET Task ID 20204	0.5
Analyze historical climate information, such as precipitation or temperature records, to help predict future weather or climate trends. O*NET Task ID 20205	0.5
Prepare weather reports or maps for analysis, distribution, or use in weather broadcasts, using computer graphics. O*NET Task ID 20206	0.5
Apply meteorological knowledge to issues such as global warming, pollution control, or ozone depletion. O*NET Task ID 20207	0.5
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. O*NET Task ID 20209	0.5
Conduct meteorological research into the processes or determinants of atmospheric phenomena, weather, or climate. O*NET Task ID 20210	0.5
Research the impact of industrial projects or pollution on climate, air quality, or weather phenomena. O*NET Task ID 20212	0.5
Develop and deliver training on weather topics. O*NET Task ID 21105	0.5
আরও 15টি কাজ দেখুন ▾কম দেখুন ▴

β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.

Data sources & licenses — O*NET®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page

পেশাগত তথ্য

ILO

আইএলও পেশাগত বিবরণ

Meteorologists

আবহাওয়াবিদ

উৎস: বাংলা পেশার নামসমূহ বাংলাদেশ পরিসংখ্যান ব্যুরো (বিবিএস) প্রকাশিত 'বাংলাদেশ পেশাগত শ্রেণিবিন্যাস (বিএসসিও)-২০২০, ভলিউম-২' থেকে অপরিবর্তিতভাবে উদ্ধৃত। উৎস: https://bbs.gov.bd/pages/static-pages/6922dce2933eb65569e128ee । বিএসসিও-২০২০ আইএলও-এর আইএসসিও-০৮ (CC BY 4.0) এর ভিত্তিতে প্রণীত। এই উপস্থাপনা বিবিএস বা আইএলও কর্তৃক প্রস্তুত, পর্যালোচিত বা অনুমোদিত নয়।

মূল উৎস দেখুন অপসারণের অনুরোধ

Meteorologists prepare short-term or long-term weather forecasts used in aviation, shipping, agriculture and other areas and for the information of the general public. They conduct research related to the composition, structure and dynamics of the atmosphere.

কার্য

(a) investigating direction and speed of air movements, pressures, temperatures, humidity, physical and chemical transformation of pollutants and other phenomena such as cloud formation and precipitation, electrical disturbances or solar radiation;
(b) studying data collected from meteorological stations, radar and satellite imagery and computer model output to plot and forecast weather conditions;
(c) preparing and reporting short-term or long-term weather maps, forecasts and warnings relating to atmospheric phenomena such as cyclones, storms and other hazards to life and property and disseminating information about atmospheric conditions through a variety of media including radio, television, print and the Internet;
(d) conducting experiments in fog dispersal, cloud seeding, rain enhancement and other types of weather modification programmes;
(e) developing and testing mathematical computer models of weather and climate for experimental or operational use;
(f) participating in studies of the effect of weather on the environment;
(g) analysing the impact of industrial projects and human activity on the climate and quality of the air and working with the social science, engineering and economic communities to develop appropriate mitigation strategies;
(h) engaging in the design and development of new equipment and procedures for meteorological data collection, remote sensing, or for related applications;
(i) conducting research on and improving or developing concepts, theories and operational methods related to the composition, structure and dynamics of the atmosphere and preparing scientific papers and reports on the outcome of this research.

উদাহরণ পেশা

Climatologist · Hydrometeorologist · Meteorologist · Weather forecaster

ISCO-08 2112

Sources: ILO ISCO-08 (CC BY 4.0) — details: Credits

KEIS'25

Shown in the original Korean. This dataset is published under KOGL Type 4, which prohibits derivative works including translation, so the text is reproduced unaltered.

자연과학 시험원KNOW K000000825
Job outlook: 증가(0%) 현상유지(40%) 감소(60%)
Wages (10,000 KRW): lower(25%) 3.95K average(50%) 4.75K upper(25%) 5.5K
minacross 461 KNOW occupationsmax
Job satisfaction: 70
minacross 461 KNOW occupationsmax
Details
Duties
- -표본을 수집하고 실험, 검사 및 분석용 재료와 장비를 준비한다.
- -실험, 검사 및 분석을 보조하거나 직접 수행한다.
- - 프로젝트에 필요한 재료 등의 세부 견적서를 주어진 명세서에 따라 작성하여 준비한다.
- -프로젝트에 필요한 재료 및 인력의 양과 배용의 세부 견적서를 작성한다.
- -실험용 재료와 장비를 준비하고, 실험기구 및 장비를 설치 조작하여 실험을 보조한다.
- -물질을 구성하고 있는 성분의 종류와 조성비 분석 등의 검사 및 분석업무를 보조하거나 자연과학자의 지시하에 직접 실험을 수행하기도 한다.
- -실험이 끝나면 사용한 실험기구 및 장비를 정리하고, 유지·관리한다.
- -공학적 계산을 하며, 각종 도표 및 보고서를 작성한다.
- -연구과정에서 야기되는 문제들을 확인하고, 이를 해결하기 위하여 기술적인 지식을 응용한다.
See details on KNOW (Korea Employment Information Service) (external site)
Work abilities
수리력(96) · 품질관리분석(94) · 장비 선정(93) · 추리력(91) · 조작 및 통제(90)
Knowledge
화학(92) · 물리(81) · 영어(77) · 사무(70) · 생물(70)
Work environment
위험한 상태 노출(93) · 정확성, 정밀성 유지(92) · 반복적인 신체행동, 정신적 활동(91) · 마감시간(85) · 이메일 이용하기(85)

The KNOW occupations and KECO codes listed here were linked to this page's occupation by this site; this is not a correspondence defined by the Korea Employment Information Service or the Ministry of Employment and Labor.

এই পেশা সংক্রান্ত সাম্প্রতিক পরিবর্তন

মার্চ ২০২৬: Published evergreen blog post analyzing AI impact on meteorology: 55% exposure, 42% risk, communication and extreme events require human judgment.

[সূত্র: AI Changing Work Blog]

AI এক্সপোজার

Task-level exposure

পেশাগত তথ্য

আইএলও পেশাগত বিবরণ

ESCO পেশাগত শব্দভাণ্ডার

এই পেশা সংক্রান্ত সাম্প্রতিক পরিবর্তন