每日英語跟讀 Ep.K234: Physics Nobel rewards work on climate change, other forces
Three scientists won the Nobel Prize in physics Tuesday last week for work that found order in seeming disorder, helping to explain and predict complex forces of nature, including expanding our understanding of climate change.
致力於在看似無序中找到秩序的三位科學家，上週二獲得了諾貝爾物理學獎。他們的研究有助於解釋及預測複雜的自然力量，包括增進我們對氣候變化的理解。
Syukuro Manabe, originally from Japan, and Klaus Hasselmann of Germany were cited for their work in developing forecast models of Earth’s climate and “reliably predicting global warming.” The second half of the prize went to Giorgio Parisi of Italy for explaining disorder in physical systems, ranging from those as small as the insides of atoms to the planet-sized.
原籍日本的真鍋淑郎與德國的克勞斯‧哈斯曼，因研發地球氣候預測模型，以及「可靠地預測全球暖化」而獲獎。獎金的另一半，則是授予義大利籍的喬吉歐‧帕里西，因他解釋了物理系統──小至原子內部，大至行星大小──其中的無序。
Hasselmann told the Associated Press that he “would rather have no global warming and no Nobel Prize.” Calling climate change “a major crisis,” Manabe said that figuring out the physics behind climate change was “1,000 times” easier than getting the world to do something about it.
哈斯曼對美聯社表示，他「寧願沒有全球暖化，也沒有諾貝爾獎」。真鍋稱氣候變化為「一場重大危機」，並說弄清楚氣候變化背後的物理學，要比促世界採取行動容易「一千倍」。
All three scientists work on what are known as “complex systems,” of which climate is just one example. But the prize went to two fields of study that are opposite in many ways, though they share the goal of making sense of what seems random and chaotic so that it can be predicted.
這三位科學家都在研究所謂的「複雜系統」，氣候只是其中一個例子。獲獎的兩個研究領域，在許多方面都大相逕庭，雖然其共同目標皆為理解看似隨機與混亂的事物，以便能夠預測。
The research of Parisi, of Sapienza University of Rome, largely centers around subatomic particles, predicting how they move in seemingly chaotic ways and explaining why. It is somewhat esoteric, while the work by Manabe and Hasselmann is about large-scale global forces that shape our daily lives.
羅馬大學的帕里西，其研究主要圍繞次原子粒子，探究它們如何以及為何以看似混亂的方式運動，並加以預測。帕里西的研究有時深奧難解，而真鍋及哈斯曼的研究，則是有關型塑我們日常生活的大規模全球力量。
Parisi “built a deep physical and mathematical model” that made it possible to understand complex systems in fields as different as mathematics, biology, neuroscience and machine learning.
帕里西「建立了一個深刻的物理及數學模型」，使得理解數學、生物學、神經科學和機器學習等不同領域的複雜系統成為可能。Source article: https://www.taipeitimes.com/News/lang/archives/2021/10/11/2003765868