ABOUT THE SPEAKER
Gavin Schmidt - Climate scientist
What goes into a climate model? Gavin Schmidt looks at how we use past and present data to model potential futures.

Why you should listen
Gavin Schmidt is a climate scientist at Columbia University's Earth Institute and is Deputy Chief at the NASA Goddard Institute for Space Studies. He works on understanding past, present and future climate change, using ever-more refined models and data sets to explore how the planet's climate behaves over time.
 
Schmidt is also deeply committed to communicating science to the general public. As a contributing editor at RealClimate.org, he helps make sure general readers have access to the basics of climate science, and works to bring the newest data and models into the public discussion around one of the most pressing issues of our time. He has worked with the American Museum of Natural History and the New York Academy of Sciences on education and public outreach, and he is the author of Climate Change: Picturing the Science, with Josh Wolfe.
More profile about the speaker
Gavin Schmidt | Speaker | TED.com
TED2014

Gavin Schmidt: The emergent patterns of climate change

加文·施密特: 氣候變遷的突現形態

Filmed:
1,270,244 views

你不能把氣候變遷拆開來理解,氣候科學家加文·施密特如是說。這是全有或全無。他在此富有啟發性的演說中,解釋如何以奇幻的模式,描繪出小規模環境事件無止盡的複雜交互作用,來研究氣候變遷的大圖像。
- Climate scientist
What goes into a climate model? Gavin Schmidt looks at how we use past and present data to model potential futures. Full bio

Double-click the English transcript below to play the video.

00:12
We live生活 in a very complex複雜 environment環境:
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我們活在非常複雜的環境裡:
00:15
complexity複雜 and dynamism力度
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複雜性及動力系統論
00:17
and patterns模式 of evidence證據
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及各式氣候變化形態的證據
00:19
from satellite衛星 photographs照片, from videos視頻.
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從衛星照相、從影片得之
00:22
You can even see it outside your window窗口.
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你甚至能從你的窗戶外面看到
00:25
It's endlessly不休 complex複雜, but somehow不知何故 familiar,
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無止盡的複雜又具某種程度的熟悉
00:28
but the patterns模式 kind of repeat重複,
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但形態的確有一定程度的重複
00:30
but they never repeat重複 exactly究竟.
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但從來沒有一模一樣過
00:33
It's a huge巨大 challenge挑戰 to understand理解.
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要了解它是很大的挑戰
00:37
The patterns模式 that you see
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你所看到的形態
00:39
are there at all of the different不同 scales,
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都以不同的尺度存在著
00:43
but you can't chop it into one little bit and say,
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但你不能切下一小塊然後說
00:46
"Oh, well let me just make a smaller climate氣候."
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「喔,那我做個小一點的氣候。」
00:48
I can't use the normal正常 products製品 of reductionism簡化論
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我不能以一般的化約論產品
00:53
to get a smaller and smaller thing that I can study研究
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得到愈來愈小的東西
00:55
in a laboratory實驗室 and say, "Oh,
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使我能在實驗室裡研究且說
00:58
now that's something I now understand理解."
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「喔,這是我能理解的了。」
01:00
It's the whole整個 or it's nothing.
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這是全有或全無
01:03
The different不同 scales that give you
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這些氣候形態
01:06
these kinds of patterns模式
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以不同的尺度呈現
01:08
range範圍 over an enormous巨大 range範圍 of magnitude大小,
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其範圍幅度非常大
01:12
roughly大致 14 orders命令 of magnitude大小,
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大約是 14 數量級的差距
01:14
from the small microscopic顯微 particles粒子
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從最小的顯微粒子
01:16
that seed種子 clouds
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以造雨
01:19
to the size尺寸 of the planet行星 itself本身,
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到這個星球本身的大小
01:21
from 10 to the minus減去 six
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從 10 的負六次方到
01:23
to 10 to the eight,
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10 的八次方
01:24
14 orders命令 of spatial空間的 magnitude大小.
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空間數量級的差距為 14
01:26
In time, from milliseconds毫秒 to millennia千年,
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在時間上,從毫秒到千年
01:29
again around 14 orders命令 of magnitude大小.
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同樣也是 14 數量級
01:32
What does that mean?
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這意味著什麼?
01:34
Okay, well if you think about how
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好,如果你想一想
01:36
you can calculate計算 these things,
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你要如何計算這些東西
01:38
you can take what you can see,
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你會把你見到的事物
01:40
okay, I'm going to chop it up
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好,我要把它切碎
01:41
into lots of little boxes盒子,
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成這些小方塊
01:43
and that's the result結果 of physics物理, right?
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這就是物理學的結果,對吧?
01:45
And if I think about a weather天氣 model模型,
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如果我想到一個氣象模型
01:47
that spans跨度 about five orders命令 of magnitude大小,
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尺度橫跨五數量級
01:49
from the planet行星 to a few少數 kilometers公里,
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也就是從地球的大小到幾公里
01:53
and the time scale規模
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時間尺度則是
01:54
from a few少數 minutes分鐘 to 10 days, maybe a month.
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從幾分鐘到十天或者一個月
01:59
We're interested有興趣 in more than that.
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我們感興趣的不只這些
02:00
We're interested有興趣 in the climate氣候.
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我們對氣候感興趣
02:01
That's years年份, that's millennia千年,
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那是以年計的,是千年
02:03
and we need to go to even smaller scales.
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我們還需要看更小尺度的
02:06
The stuff東東 that we can't resolve解決,
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我們無法解決的東西
02:08
the sub-scale分度 processes流程,
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次網格尺度過程
02:09
we need to approximate近似 in some way.
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我們必須想辦法得到近似值
02:11
That is a huge巨大 challenge挑戰.
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那是很大的挑戰
02:13
Climate氣候 models楷模 in the 1990s
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1990 年代的氣候模式
02:15
took an even smaller chunk of that,
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是拿更小塊的規模來看
02:17
only about three orders命令 of magnitude大小.
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大約只有三數量級
02:19
Climate氣候 models楷模 in the 2010s,
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2010 年代的氣候模式
02:21
kind of what we're working加工 with now,
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就像我們現在正在使用的
02:23
four orders命令 of magnitude大小.
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是四數量級
02:26
We have 14 to go,
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我們還要繼續擴展到 14
02:29
and we're increasing增加 our capability能力
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而我們的
02:31
of simulating模擬 those at about
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模擬能力
02:33
one extra額外 order訂購 of magnitude大小 every一切 decade.
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每十年大約增加一數量級
02:36
One extra額外 order訂購 of magnitude大小 in space空間
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以空間而言每增加一數量級
02:38
is 10,000 times more calculations計算.
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就是增加一萬倍的計算
02:41
And we keep adding加入 more things,
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而我們還繼續加東西上去
02:44
more questions問題 to these different不同 models楷模.
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加更多問題到這些不同的模式上
02:46
So what does a climate氣候 model模型 look like?
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所以氣候模式是甚麼樣子?
02:49
This is an old climate氣候 model模型, admittedly固然,
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這是老式的氣候模式,無可否認
02:51
a punch沖床 card, a single line of FortranFortran語言 code.
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打孔卡,單行福傳語言
02:55
We no longer use punch沖床 cards.
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我們不再使用打孔卡了
02:57
We do still use FortranFortran語言.
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我們還是用福傳語言
02:59
New-fangled新發明 ideas思路 like C
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新的想法像使用 C 語言
03:01
really haven't沒有 had a big impact碰撞
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還沒有什麼大的影響力
03:05
on the climate氣候 modeling造型 community社區.
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在氣候模式族群裡
03:07
But how do we go about doing it?
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但這是怎麼做出來的?
03:08
How do we go from that complexity複雜 that you saw
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我們如何把你所看到的複雜
03:13
to a line of code?
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變成一行的程式?
03:16
We do it one piece at a time.
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我們一次做一件
03:17
This is a picture圖片 of sea ice
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這是一張海冰圖
03:19
taken採取 flying飛行 over the Arctic北極.
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飛越北極上空時照的
03:21
We can look at all of the different不同 equations方程
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我們可以看所有不同的方程式
03:23
that go into making製造 the ice grow增長
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使結冰量增加
03:26
or melt熔化 or change更改 shape形狀.
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或融化或改變形狀
03:28
We can look at the fluxes通量.
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我們可以看看各種通量
03:29
We can look at the rate at which哪一個
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我們可以看雪變成冰的速率
03:31
snow turns to ice, and we can code that.
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我們可以為之編寫程式
03:34
We can encapsulate封裝 that in code.
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我們可以封裝在程式裡
03:37
These models楷模 are around
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這些模式目前大約要以
03:38
a million百萬 lines of code at this point,
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一百萬行程式才做的出來
03:40
and growing生長 by tens of thousands數千 of lines of code
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每年還要以上萬行的程式
03:43
every一切 year.
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成長
03:45
So you can look at that piece,
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所以你看這件是這樣
03:46
but you can look at the other pieces too.
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別件也是如此
03:48
What happens發生 when you have clouds?
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有雲的時候怎麼辦?
03:50
What happens發生 when clouds form形成,
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雲形成的時候怎麼辦?
03:52
when they dissipate消散, when they rain out?
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雲散了呢?下雨了呢?
03:54
That's another另一個 piece.
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這是一件
03:56
What happens發生 when we have radiation輻射
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有太陽輻射怎麼辦?
03:58
coming未來 from the sun太陽, going through通過 the atmosphere大氣層,
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輻射穿過大氣層
04:00
being存在 absorbed吸收 and reflected反射的?
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被吸收及反射又怎麼辦?
04:02
We can code each of those
very small pieces as well.
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我們也能為這些非常小的東西寫程式
04:06
There are other pieces:
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還有其他的
04:08
the winds changing改變 the ocean海洋 currents電流.
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風改變洋流
04:11
We can talk about the role角色 of vegetation植被
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我們也能談植被
04:15
in transporting傳輸 water from the soils土壤
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從土壤中輸送水分
04:17
back into the atmosphere大氣層.
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回到大氣層的角色
04:19
And each of these different不同 elements分子
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每一種不同的要素
04:22
we can encapsulate封裝 and put into a system系統.
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我們都可以封裝寫進系統內
04:26
Each of those pieces ends結束 up adding加入 to the whole整個.
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每一件最後都會加在整體上
04:31
And you get something like this.
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那你就得到一個像這樣的東西
04:33
You get a beautiful美麗 representation表示
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你會得到漂亮的圖表
04:36
of what's going on in the climate氣候 system系統,
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告訴你氣候系統發生什麼事
04:39
where each and every一切 one of those
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每一個像這樣
04:42
emergent應急 patterns模式 that you can see,
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你看到的突現形態
04:45
the swirls漩渦 in the Southern南部的 Ocean海洋,
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南冰洋的旋渦
04:47
the tropical熱帶 cyclone氣旋 in the Gulf海灣 of Mexico墨西哥,
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墨西哥灣的熱帶颶風
04:49
and there's two more that are going to pop流行的 up
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還有兩個隨時都要跑出來
04:51
in the Pacific和平的 at any point now,
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在太平洋形成
04:53
those rivers河流 of atmospheric大氣的 water,
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那些大氣水氣形成的河流
04:56
all of those are emergent應急 properties性能
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這些都是突現性質
04:59
that come from the interactions互動
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從我剛剛談到的次網格尺度過程
05:01
of all of those small-scale小型 processes流程 I mentioned提到.
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交互作用而來
05:05
There's no code that says,
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沒有什麼程式會說
05:07
"Do a wiggle擺動 in the Southern南部的 Ocean海洋."
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「在南冰洋擺動一下。」
05:08
There's no code that says, "Have two
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也沒有程式會說:「讓兩個
05:11
tropical熱帶 cyclones旋風 that spin around each other."
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熱帶颶風互相繞著旋轉。」
05:14
All of those things are emergent應急 properties性能.
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這些都是突現性質
05:18
This is all very good. This is all great.
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這很好,這很棒
05:20
But what we really want to know
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但我們真的想知道的
05:21
is what happens發生 to these emergent應急 properties性能
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是這些突現性質會怎麼辦
05:23
when we kick the system系統?
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在我們系統改變的時候
05:25
When something changes變化, what
happens發生 to those properties性能?
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當情況改變了那些性質會怎麼辦?
05:28
And there's lots of different不同 ways方法 to kick the system系統.
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有很多方法會讓系統改變
05:31
There are wobbles擺動 in the Earth's地球 orbit軌道
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地球的軌道
05:33
over hundreds數以百計 of thousands數千 of years年份
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在過去數萬年的擺動
05:35
that change更改 the climate氣候.
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會改變氣候
05:37
There are changes變化 in the solar太陽能 cycles週期,
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太陽週期的改變
05:39
every一切 11 years年份 and longer, that change更改 the climate氣候.
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每 11 年或更長的時間
也會改變氣候
05:43
Big volcanoes火山 go off and change更改 the climate氣候.
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大的火山爆發會改變氣候
05:46
Changes變化 in biomass生物質 burning燃燒, in smoke抽煙,
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生質燃燒的改變,煙霧
05:49
in aerosol氣霧劑 particles粒子, all of those things
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氣膠粒子,這些東西
05:51
change更改 the climate氣候.
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都會改變氣候
05:53
The ozone臭氧 hole changed the climate氣候.
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臭氧洞會改變氣候
05:57
Deforestation森林砍伐 changes變化 the climate氣候
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森林除伐會改變氣候
05:59
by changing改變 the surface表面 properties性能
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因為這改變了地表性質
06:01
and how water is evaporated蒸發
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也改變水分如何蒸發
06:03
and moved移動 around in the system系統.
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並在系統內移動
06:06
Contrails凝結 change更改 the climate氣候
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凝結尾會改變氣候
06:08
by creating創建 clouds where there were none沒有 before,
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因為會在以前無雲的地方產生雲
06:11
and of course課程 greenhouse溫室 gases氣體 change更改 the system系統.
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當然溫室氣體也會改變系統
06:15
Each of these different不同 kicks
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這些不同的改變因素
06:18
provides提供 us with a target目標
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提供我們一個目標
06:21
to evaluate評估 whether是否 we understand理解
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以評估我們是否瞭解
06:23
something about this system系統.
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這個系統
06:26
So we can go to look at
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所以我們可以去看
06:28
what model模型 skill技能 is.
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模式預測技巧是什麼
06:31
Now I use the word "skill技能" advisedly故意地:
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那我非常審慎的用「技巧」這個字
06:33
Models楷模 are not right or wrong錯誤; they're always wrong錯誤.
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模式沒有對錯;它們永遠是錯的
06:35
They're always approximations近似值.
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它們永遠是近似值
06:37
The question you have to ask
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你該問的問題是
06:39
is whether是否 a model模型 tells告訴 you more information信息
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模式能否告訴你更多的資訊
06:42
than you would have had otherwise除此以外.
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比你沒用模式時所得的還多
06:44
If it does, it's skillful熟練.
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如果是,那它就是技巧很好
06:47
This is the impact碰撞 of the ozone臭氧 hole
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這是臭氧洞
06:50
on sea level水平 pressure壓力, so
low pressure壓力, high pressures壓力,
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對海平面氣壓的影響
所以低氣壓高氣壓
06:52
around the southern南部的 oceans海洋, around Antarctica南極洲.
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在南冰洋四周,在南極洲四周
06:55
This is observed觀察到的 data數據.
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這是觀測數據
06:57
This is modeled仿照 data數據.
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這是模式推測出的數據
06:59
There's a good match比賽
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這兩者匹配度很高
07:01
because we understand理解 the physics物理
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因為我們瞭解
07:03
that controls控制 the temperatures溫度 in the stratosphere平流層
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控制平流層溫度的物理
07:06
and what that does to the winds
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及其對
07:07
around the southern南部的 oceans海洋.
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南冰洋四周的風的作用
07:10
We can look at other examples例子.
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我們還可以看看其他例子
07:11
The eruption噴發 of Mount安裝 Pinatubo皮納圖博火山 in 1991
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1991 年皮納土波火山爆發
07:14
put an enormous巨大 amount of aerosols氣溶膠, small particles粒子,
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將大量的氣膠,微粒
07:17
into the stratosphere平流層.
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噴入平流層中
07:18
That changed the radiation輻射
balance平衡 of the whole整個 planet行星.
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那件事改變了整個地球的輻射平衡
07:22
There was less energy能源 coming未來
in than there was before,
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與之前相比,較少的能量進入地球
07:24
so that cooled冷卻 the planet行星,
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導致地球變冷
07:26
and those red lines and those green綠色 lines,
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而那些紅線及那些綠線
07:28
those are the differences分歧 between之間 what we expected預期
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那些是我們所預期
07:31
and what actually其實 happened發生.
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及實際狀況的差別
07:32
The models楷模 are skillful熟練,
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這些模式很有技巧
07:34
not just in the global全球 mean,
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不僅在全球平均上很準確
07:36
but also in the regional區域性 patterns模式.
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在區域形態上也如此
07:39
I could go through通過 a dozen more examples例子:
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我還可以講上打的例子:
07:42
the skill技能 associated相關 with solar太陽能 cycles週期,
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與太陽週期
07:45
changing改變 the ozone臭氧 in the stratosphere平流層;
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平流層臭氧變化相關的預測技巧
07:47
the skill技能 associated相關 with orbital軌道的 changes變化
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與六千年來地球軌道變化
07:49
over 6,000 years年份.
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相關的預測技巧
07:51
We can look at that too, and the models楷模 are skillful熟練.
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我們也可以看那個
而模式的技巧也很好
07:53
The models楷模 are skillful熟練 in response響應 to the ice sheets床單
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對二萬年前的冰層
07:56
20,000 years年份 ago.
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這些模式的技巧也很好
07:58
The models楷模 are skillful熟練
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這些模式在過去幾十年
08:00
when it comes to the 20th-centuryTH-世紀 trends趨勢
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談到二十世紀的趨勢時
08:03
over the decades幾十年.
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其技巧很好
08:04
Models楷模 are successful成功 at modeling造型
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模式很成功地
08:06
lake outbursts爆發 into the North Atlantic大西洋
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將八千年前北極冰湖潰決
08:09
8,000 years年份 ago.
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模式化
08:11
And we can get a good match比賽 to the data數據.
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我們在數據上的匹配度很高
08:15
Each of these different不同 targets目標,
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每一個不同的目標
08:17
each of these different不同 evaluations評估,
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每一個不同的評估
08:19
leads引線 us to add more scope範圍
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都導致我們加大範圍
08:22
to these models楷模,
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到這些模式中
08:23
and leads引線 us to more and more
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導致日益加增的
08:26
complex複雜 situations情況 that we can ask
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複雜情況,使我們不禁要問
08:30
more and more interesting有趣 questions問題,
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更多有意思的問題
08:32
like, how does dust灰塵 from the Sahara撒哈拉,
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像是撒哈拉塵
08:35
that you can see in the orange橙子,
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也就是這些橘色的東西
08:37
interact相互作用 with tropical熱帶 cyclones旋風 in the Atlantic大西洋?
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與大西洋的熱帶颶風如何交互作用?
08:40
How do organic有機 aerosols氣溶膠 from biomass生物質 burning燃燒,
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生質燃燒所產生的有機氣膠
08:44
which哪一個 you can see in the red dots,
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也就是這些紅點
08:46
intersect相交 with clouds and rainfall雨量 patterns模式?
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與雲及雨型如何交互作用?
這些汙染,就是你看到
08:49
How does pollution污染, which哪一個 you can see
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08:51
in the white白色 wisps縷縷 of sulfate硫酸 pollution污染 in Europe歐洲,
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在歐洲上方,一縷縷的白色硫酸
08:55
how does that affect影響 the
temperatures溫度 at the surface表面
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這些如何影響地面溫度
08:58
and the sunlight陽光 that you get at the surface表面?
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以及你在地表上得到的太陽光量?
09:02
We can look at this across橫過 the world世界.
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我們可以看看世界各地的狀況
09:05
We can look at the pollution污染 from China中國.
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我們可以看從中國來的汙染
09:09
We can look at the impacts影響 of storms風暴
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我們可以看暴風
09:13
on sea salt particles粒子 in the atmosphere大氣層.
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對大氣層內海鹽粒子的影響
09:16
We can see the combination組合
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我們可以看
09:19
of all of these different不同 things
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這些同時發生的
09:21
happening事件 all at once一旦,
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不同東西的組合
09:22
and we can ask much more interesting有趣 questions問題.
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我們可以問更有意思的問題
09:25
How do air空氣 pollution污染 and climate氣候 coexist共存?
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空氣汙染與氣候如何共存?
09:29
Can we change更改 things
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我們是否能改變
09:31
that affect影響 air空氣 pollution污染 and
climate氣候 at the same相同 time?
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對空氣汙染及氣候
同時產生影響的事物?
09:33
The answer回答 is yes.
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答案是肯定的
09:36
So this is a history歷史 of the 20th century世紀.
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這是二十世紀的歷史
09:39
The first one is the model模型.
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第一個是模式
09:41
The weather天氣 is a little bit different不同
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天氣與實際狀況
09:42
to what actually其實 happened發生.
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有一點不同
09:44
The second第二 one are the observations意見.
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第二個是觀察
09:46
And we're going through通過 the 1930s.
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我們來看 1930 年代的情況
09:48
There's variability變化性, there are things going on,
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總是有變數,總是有狀況發生
09:51
but it's all kind of in the noise噪聲.
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但是都有點像是雜音
09:53
As you get towards the 1970s,
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然後時間接近 1970 年代
09:56
things are going to start開始 to change更改.
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事情開始有了變化
09:58
They're going to start開始 to look more similar類似,
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它們開始看起來愈來愈接近
10:00
and by the time you get to the 2000s,
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而到了 2000 年代
10:03
you're already已經 seeing眼看 the
patterns模式 of global全球 warming變暖,
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你已經可以看到全球暖化的型態
10:05
both in the observations意見 and in the model模型.
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觀察及模式預測兩者皆是
10:08
We know what happened發生 over the 20th century世紀.
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我們知道二十世紀發生了什麼
10:10
Right? We know that it's gotten得到 warmer回暖.
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對吧?我們知道一定會更熱
10:12
We know where it's gotten得到 warmer回暖.
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我們還知道哪裡一定會更熱
10:13
And if you ask the models楷模 why did that happen發生,
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如果你問模式為什麼這種情形會發生
10:16
and you say, okay, well, yes,
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然後你說,對,嗯,沒錯
10:18
basically基本上 it's because of the carbon dioxide二氧化碳
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基本上就是因為二氧化碳
10:20
we put into the atmosphere大氣層.
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我們把它排放到大氣層
10:22
We have a very good match比賽
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我們的匹配度
10:24
up until直到 the present當下 day.
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到今天為止都很高
10:26
But there's one key reason原因 why we look at models楷模,
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但我們為什麼要看模式
有個關鍵的理由
10:30
and that's because of this phrase短語 here.
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而那就是因為這句話
10:32
Because if we had observations意見 of the future未來,
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因為「假設我們能直接觀察未來,
10:35
we obviously明顯 would trust相信 them more than models楷模,
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與其相信模式,
我們顯然會更相信觀察數據。
10:38
But unfortunately不幸,
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但不幸的是…
10:40
observations意見 of the future未來
are not available可得到 at this time.
256
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…對未來的觀察目前行不通。」
10:45
So when we go out into the
future未來, there's a difference區別.
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所以當我們預測未來
就會產生差異
10:48
The future未來 is unknown未知, the future未來 is uncertain不確定,
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未來是未知的;未來是不確定的
10:51
and there are choices選擇.
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但我們有選擇
10:53
Here are the choices選擇 that we have.
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以下是我們的選擇
10:55
We can do some work to mitigate減輕
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我們能做點什麼以減少
10:57
the emissions排放 of carbon dioxide二氧化碳 into the atmosphere大氣層.
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二氧化碳排放入大氣層
11:00
That's the top最佳 one.
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這是最重要的
11:02
We can do more work
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我們還能做更多
11:04
to really bring帶來 it down
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以真正減少排放量
11:06
so that by the end結束 of the century世紀,
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所以到了本世紀末
11:08
it's not much more than there is now.
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排放量不會比現在更多
11:11
Or we can just leave離開 it to fate命運
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或者我們就看天命
11:14
and continue繼續 on
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並繼續著
11:16
with a business-as-usual照常營業 type類型 of attitude態度.
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一切如常的態度
11:20
The differences分歧 between之間 these choices選擇
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這兩種選擇的差異
11:23
can't be answered回答 by looking at models楷模.
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看模式是回答不了的
11:28
There's a great phrase短語
273
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有句名言
11:29
that Sherwood舍伍德 Rowland羅蘭,
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是弗蘭克‧羅蘭說的
11:31
who won韓元 the Nobel諾貝爾 Prize for the chemistry化學
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他是諾貝爾化學獎得主
11:35
that led to ozone臭氧 depletion消耗,
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他的研究發現了臭氧耗竭
11:37
when he was accepting驗收 his Nobel諾貝爾 Prize,
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他在領取他的諾貝爾獎時
11:40
he asked this question:
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他問了這個問題
11:41
"What is the use of having developed發達 a science科學
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「這到底有甚麼用呢?
某項科學發展的很好,
11:43
well enough足夠 to make predictions預測 if, in the end結束,
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好到能做出預測,但最後
11:47
all we're willing願意 to do is stand around
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我們只願意袖手旁觀,
11:50
and wait for them to come true真正?"
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冷眼看著它們成真?」
11:52
The models楷模 are skillful熟練,
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模式的預測技巧很好
11:55
but what we do with the
information信息 from those models楷模
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但我們要怎麼使用
模式預測出來的數據
11:58
is totally完全 up to you.
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就全看你們了
12:00
Thank you.
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謝謝
12:02
(Applause掌聲)
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(掌聲)
Translated by Regina Chu
Reviewed by Tsz Ying Choi

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ABOUT THE SPEAKER
Gavin Schmidt - Climate scientist
What goes into a climate model? Gavin Schmidt looks at how we use past and present data to model potential futures.

Why you should listen
Gavin Schmidt is a climate scientist at Columbia University's Earth Institute and is Deputy Chief at the NASA Goddard Institute for Space Studies. He works on understanding past, present and future climate change, using ever-more refined models and data sets to explore how the planet's climate behaves over time.
 
Schmidt is also deeply committed to communicating science to the general public. As a contributing editor at RealClimate.org, he helps make sure general readers have access to the basics of climate science, and works to bring the newest data and models into the public discussion around one of the most pressing issues of our time. He has worked with the American Museum of Natural History and the New York Academy of Sciences on education and public outreach, and he is the author of Climate Change: Picturing the Science, with Josh Wolfe.
More profile about the speaker
Gavin Schmidt | Speaker | TED.com

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