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23% (낮은 위험)

저위험 (21-40%): 이 수준의 직업은 기술적인 능력과 인간 중심의 기술을 모두 요구하기 때문에 자동화 위험이 제한적입니다.

이 점수가 무엇인지, 그리고 어떻게 계산되는지에 대한 자세한 정보는 여기에 있습니다.

사용자 설문조사

감정

다음 그래프는 의미 있는 데이터를 제공할 수 있을 만큼 충분한 투표 수가 있을 때마다 포함됩니다. 이러한 시각적 표현은 시간 경과에 따른 사용자 투표 결과를 보여주며, 감정 추세에 대한 중요한 지표를 제공합니다.

임금

다른 직업에 비해 매우 높은 급여를 받는다.

2023년에 'Atmospheric and Space Scientists'의 중앙값 연간 급여는 $92,860이며, 시간당 $44입니다.

'Atmospheric and Space Scientists'은 전국 중위임금인 $48,060보다 93.2% 더 높은 금액을 지불받았습니다.

시간에 따른 임금

댓글

whetherweather101 (적당한) 7 months ago

AI will soon (and already is) predicting weather as or more accurately than human forecasters.

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Thomas (매우 가능성이 높음) 1 year ago

I went to school for this. I think that computer processing power will increase over the years. When this happens, the grid cells of the model will become smaller (look up climate modeling). This has happened for decades now. Eventually, the grid cells of the model become so small that the errors in model forecasts will decrease leaving no need for humans to fix them. This doesn't apply to research scientists.

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atmospheric scientist contractor person (불확실한) 2 years ago

There are many areas where AI could replace the work of scientists, but the adoption of new technology often lags behind what is seen in industry. This is partly due to the fact that this field is driven by government funding, which is often allocated inefficiently compared to the private sector. In addition, scientist salaries are low and require extensive schooling (Master's/PhD), so change is happening very slowly.

0 0 Reply

Mike (기회 없음) 3 years ago

There is a difference between weather forecaster (already replaced) and atmospheric/space science.

0 0 Reply

Chris (적당한) 5 years ago

At least the weather forecasting side, automation has already taken over the job. Models are getting so much better and in the next decade it will likely be unnecessary to 'forecast' in the traditional sense.

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Nicholas 5 years ago

Forecasting is only a tiny part of what atmospheric and space scientist do. As space scientist I do not work with forecasting at all. Then given the poor amount of data, the result is also very poor.

0 0 Reply