itle：Climate change now detectable from any single day of weather at global scale

标题：现在可以从全球范围内任何一天的天气中检测到气候变化

作者：Sebastian Sippel?1,2,3*, Nicolai Meinshausen 2, Erich M. Fischer1, Enik? Székelyg1, and Reto Knutti1

1 Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland.

2Seminar for Statistics, ETH Zurich, Zurich, Switzerland.

3Norwegian Institute of Bioeconomy Research, ?s, Norway.

4Swiss Data Science Center, ETH Zurich and EPFL, Lausanne, Switzerland.

E-mail: sebastian.sippel@env.ethz.ch[1]

杂志：Nature Climate Change, volume 10, pages35–41(2020)

DOI： https://doi.org/10.1038/s41558-019-0666-7[2]

原文摘要

长此以往，气候科学家传递给公众的都是“天气不是气候”的观念，气候变化也被框定为天气分布的变化缓慢地出现于这数十年里主要的气候变率中1-7。然而，现阶段考虑全球性的天气则是一个未知的领域。在这里我们基于全球观测的单日温度和水汽来检测外部驱动气候变化的“指纹”所得到的结论是：地球作为一个整体正在变暖。我们的检测方法通过统计学习和气候模型模拟来封装每日温度和湿度的空间模式与关键的气候变化指标（例如，全球年平均温度或地球的能量失衡之间）之间的关系。观测数据投影到这种关系中来检测气候变化。根据一年的数据，从2012年初和1999年以来观测到的全球记录中的任何一天都可以检测到气候变化的“指纹”。即便是忽略长期全球变暖的趋势，检测的结果也是很稳健可靠的。这是对传统气候变化检测的补充，但也为区域天气事件的交流打开了更广阔的视野，改变了气候变化的叙述方式：尽管几十年来局地的天气变化正在出现，但现在就能即时检测到全球气候变化。

Abstract

For generations, climate scientists have educated the public that ‘weather is not climate’, and climate change has been framed as the change in the distribution of weather that slowly emerges from large variability over decades1-7. However, weather when considered globally is now in uncharted territory. Here we show that on the basis of a single day of globally observed temperature and moisture, we detect the fingerprint of externally driven climate change, and conclude that Earth as a whole is warming. Our detection approach invokes statistical learning and climate model simulations to encapsulate the relationship between spatial patterns of daily temperature and humidity, and key climate change metrics such as annual global mean temperature or Earth’s energy imbalance. Observations are projected onto this relationship to detect climate change. The fingerprint of climate change is detected from any single day in the observed global record since early 2012, and since 1999 on the basis of a year of data. Detection is robust even when ignoring the long-term global warming trend. This complements traditional climate change detection, but also opens broader perspectives for the communication of regional weather events, modifying the climate change narrative: while changes in weather locally are emerging over decades, global climate change is now detected instantaneously.

数据、代码

数据[3]

All original CMIP5 data, reanalyses and observations used in this study are publicly available under the following URLs.

CMIP5 model data: https://esgf-node.llnl.gov/projects/cmip5/;

reanalysis:

ERA-Interim (https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era-interim),

NCEP/NCAR Reanalysis 1 (https://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.html),

NCEP/NCAR Reanalysis 2 (https://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis2.html),

Twentieth Century Reanalysis (https://www.esrl.noaa.gov/psd/data/20thC_Rean/);

observations (monthly): GISTEMP temperature dataset, version 3 (https://data.giss.nasa.gov/gistemp/),

Cowtan and Way (2014) temperature dataset, version 2 (https://www-users.york.ac.uk/~kdc3/papers/coverage2013/series.html),

Berkeley Earth Monthly Land+Ocean temperature dataset (http://berkeleyearth.org/data/), Met Office gridded land surface humidity dataset (HadISDH),

version 4.0.0.2017f (https://www.metoffice.gov.uk/hadobs/hadisdh/);

observations (daily): Berkeley Earth Daily Land temperature dataset (Experimental, http://berkeleyearth.org/data/),

NOAA Optimum Interpolation Sea Surface Temperature (OISST), AVHRR-Only (https://www.ncdc.noaa.gov/oisst).

All intermediate and derived data from these products (extracted CMIP5 fingerprints and daily/monthly time series of the test statistic (that is, obtained by projecting CMIP5 models, reanalyses and observations individually onto the fingerprints)) are available at https://data.iac.ethz.ch/Sippel_et_al_2019_DailyDetection/.

代码[4]

All computer code to reproduce the main results and all figures and Extended Data figures is available at https://data.iac.ethz.ch/Sippel_et_al_2019_DailyDetection/

图文

References

[1] sebastian.sippel@env.ethz.ch: mailto:sebastian.sippel@env.ethz.ch[2] https://doi.org/10.1038/s41558-019-0666-7: https://doi.org/10.1038/s41558-019-0666-7[3] 数据: https://www.nature.com/articles/s41558-019-0666-7#data-availability[4] 代码: https://data.iac.ethz.ch/Sippel_et_al_2019_DailyDetection/

开启WSL之旅》中，我们建立了windows10下的Ubuntu子系统，可以在Ubuntu与Windows系统间切换，毫无延迟感。本文介绍两种终端软件，MobaXterm与Xshell，与WSL中的Ubuntu建立SSH通道，本方案也适于windows访问独立的Linux主机。

准备工作：

• 1.获得Ubuntu系统的IP

【开始】中，启动Ubuntu18.04，在wsl窗口中，执行：

ifconfig

eth0:段中的inet后的 172.17.86.219 ，即为本机的IP地址（每次启动wsl，获得新地址，后面建立连接用到）

• 2.启动SSH 服务

wsl窗口中，执行：

sudo service ssh start

启动ssh server，如果出错或报没有此命令，则需安装SSH server，参考安装SSH。

sudo service ssh status (检查是否启动成功)

安装SSH

• 1.先更新系统包

sudo apt update

sudo apt upgrade

• 2.安装SSH服务

sudo apt remove openssh-server

sudo apt install openssh-server

• 3.修改配置文件

sudo vim /etc/ssh/sshd_config

主要改两项：

Port: 22 把前面的#注释去掉，紧接的几行也可以去掉#

PasswordAuthentication yes 把no改为yes

• 4.重新启动ssh

sudo service ssh restart

下载地址： https://mobaxterm.mobatek.net/download-home-edition.html

选择免安装版（Portable Edition）下载。

MobaXterm会自动检测到WSL环境，直接点击左侧图标，输入用户名、密码，即可快速连接。但下面介绍更一般的用法，手工建立会话连接，这也适用于连接其他计算机上的Linux系统。

如上图，点击左上角【Session】，打开如下界面

出现类似问题，可参考准备工作中的说明，检查一下ssh的启动状态。

选择【Yes】后，出现加密方式保存Ubuntu用户密码界面，加密密码至少为7位。

连接成功后，左侧为Ubuntu中的文件列表，可以在其中进行文件、目录操作。右侧为终端，可以在其中执行linux命令。

以后每次启动WSL，可以在建立的连接上，鼠标右键，【Edit session】，修改ip等参数。

• Xshell

下载地址： https://www.netsarang.com/en/free-for-home-school/

选择免费的个人版。

会发送两封邮件到你的邮箱，一个是Xshell的链接，另一个是Xftp的链接。Xftp为内嵌入Xshell中，用于文件传输，依次下载、安装。（因为下载的是个人免费版本，在首次启动Xshell后，会提问是否购买，【关闭】即可）。

【新建】会话

登录成功后，即可在右侧窗口执行linux命令，左侧会话列表中，选中一会话，鼠标右键【属性】中，可修改ip地址。如果要传输文件，可点击下图中图标，启动Xftp。

左侧为本地文件窗口，右侧为Ubuntu中文件操作窗口。鼠标右键，选择对应操作。

MobaXterm与Xshell对比

MobaXterm可以自动检测WSL，建立连接比较方便。Xshell中的Xftp，相当于一个ftp客户端，文件的操作能力强大。