一般に物事の予測をするには微分方程式を解く。
スーパーコンピュータをつかった天気予報もそのようにしているはずだ。
それでも初期条件の複雑さやパラメターのおおさで正しい予報あるいは満足できる予報はできない。
ところが最近はdeep learningを使って予測をしようという試みがでてきた。
たとえば天気予報をdeep learningでやろうという試みである。
本来、統計的データを扱うだけだから予測はできないはずなのだが
成功するとしたら
そのメカニズムはなんだろうか？
How Machine Learning Could Help to Improve Climate Forecasts
Mixing artificial intelligence with climate science helps researchers to identify previously unknown atmospheric processes and rank climate models
By Nicola Jones, Nature magazine on August 23, 2017
As Earth-observing satellites become more plentiful and climate models more powerful, researchers who study global warming are facing a deluge of data. Some are now turning to the latest trend in artificial intelligence (AI) to help trawl through all the information, in the hope of discovering new climate patterns and improving forecasts.
“Climate is now a data problem,” says Claire Monteleoni, a computer scientist at George Washington University in Washington DC who has helped to pioneer the marriage of machine-learning techniques with climate science. In machine learning, AI systems improve in performance as the amount of data that they analyse grows. This approach is a natural fit for climate science: a single run of a high-resolution climate model can produce a petabyte of data, and the archive of climate data maintained by the UK Met Office, the national weather service, now holds about 45 petabytes of information—and adds 0.085 petabytes a day.
Researchers hoping to wrangle all these data will meet next month in Boulder, Colorado, to assess the state of science in the field known as climate informatics. Work in this area has grown rapidly. In the past several years, researchers have used AI systems to help them to rank climate models, spot cyclones and other extreme weather events—in both real and modelled climate data—and identify new climate patterns. “The pace seems to be picking up,” says Monteleoni.
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スーパーコンピュータをつかった天気予報もそのようにしているはずだ。
それでも初期条件の複雑さやパラメターのおおさで正しい予報あるいは満足できる予報はできない。
ところが最近はdeep learningを使って予測をしようという試みがでてきた。
たとえば天気予報をdeep learningでやろうという試みである。
本来、統計的データを扱うだけだから予測はできないはずなのだが
成功するとしたら
そのメカニズムはなんだろうか？
How Machine Learning Could Help to Improve Climate Forecasts
Mixing artificial intelligence with climate science helps researchers to identify previously unknown atmospheric processes and rank climate models
By Nicola Jones, Nature magazine on August 23, 2017
As Earth-observing satellites become more plentiful and climate models more powerful, researchers who study global warming are facing a deluge of data. Some are now turning to the latest trend in artificial intelligence (AI) to help trawl through all the information, in the hope of discovering new climate patterns and improving forecasts.
“Climate is now a data problem,” says Claire Monteleoni, a computer scientist at George Washington University in Washington DC who has helped to pioneer the marriage of machine-learning techniques with climate science. In machine learning, AI systems improve in performance as the amount of data that they analyse grows. This approach is a natural fit for climate science: a single run of a high-resolution climate model can produce a petabyte of data, and the archive of climate data maintained by the UK Met Office, the national weather service, now holds about 45 petabytes of information—and adds 0.085 petabytes a day.
Researchers hoping to wrangle all these data will meet next month in Boulder, Colorado, to assess the state of science in the field known as climate informatics. Work in this area has grown rapidly. In the past several years, researchers have used AI systems to help them to rank climate models, spot cyclones and other extreme weather events—in both real and modelled climate data—and identify new climate patterns. “The pace seems to be picking up,” says Monteleoni.
...