更改

Simple box models, i.e. box model with a small number of boxes whose properties (e.g. their volume) do not change with time, are often useful to derive analytical formulas describing the dynamics and steady-state abundance of a species. More complex box models are usually solved using numerical techniques.

Simple box models, i.e. box model with a small number of boxes whose properties (e.g. their volume) do not change with time, are often useful to derive analytical formulas describing the dynamics and steady-state abundance of a species. More complex box models are usually solved using numerical techniques.

简单的盒子模型，例如。盒子模型，有少量的盒子，它们的属性(例如:。它们的体积)不随时间变化，通常用于推导描述物种的动态和稳态丰度的解析公式。更复杂的箱模型通常用数值方法求解。

简单的盒子模型，例如。盒子模型有少量的盒子，它们的属性(例如:它们的体积)不随时间变化，通常用于推导描述物种的动态和稳态丰富度的解析公式。更复杂的箱模型通常用数值方法求解。

Box models are used extensively to model environmental systems or ecosystems and in studies of [[ocean circulation]] and the [[carbon cycle]].<ref name=Sarmiento1984>{{cite journal

Box models are used extensively to model environmental systems or ecosystems and in studies of [[ocean circulation]] and the [[carbon cycle]].<ref name=Sarmiento1984>{{cite journal

  | issue=5960

  | issue=5960

  |bibcode = 1984Natur.308..621S |s2cid=4312683

  |bibcode = 1984Natur.308..621S |s2cid=4312683

  }}</ref>

  }}</ref>They are instances of a [[multi-compartment model]].

They are instances of a [[multi-compartment model]].

 

They are instances of a multi-compartment model.

箱模型被广泛用于模拟环境系统或生态系统以及海洋环流和碳循环的研究。它们是多室模型的实例。

箱模型被广泛用于模拟环境系统或生态系统以及海洋环流和碳循环的研究。它们是多室模型的实例。

Solving for the temperature,

Solving for the temperature,

:<nowiki>T = \sqrt[4]{ \frac{(1-a)S}{4 \epsilon \sigma}}</nowiki>

:<nowiki>T = \sqrt[4]{ \frac{(1-a)S}{4 \epsilon \sigma}}</nowiki>

:This yields an apparent effective average earth temperature of Convert.<ref>[http://eospso.gsfc.nasa.gov/ftp_docs/lithographs/CERES_litho.pdf]  {{webarchive |url=https://web.archive.org/web/20130218204711/http://eospso.gsfc.nasa.gov/ftp_docs/lithographs/CERES_litho.pdf |date=18 February 2013 }}</ref> This is because the above equation represents the effective ''radiative'' temperature of the Earth (including the clouds and atmosphere).

:This yields an apparent effective average earth temperature of .<ref>[http://eospso.gsfc.nasa.gov/ftp_docs/lithographs/CERES_litho.pdf]  {{webarchive |url=https://web.archive.org/web/20130218204711/http://eospso.gsfc.nasa.gov/ftp_docs/lithographs/CERES_litho.pdf |date=18 February 2013 }}</ref> This is because the above equation represents the effective ''radiative'' temperature of the Earth (including the clouds and atmosphere).

:一个非常简单的地球辐射平衡模型是：

:一个非常简单的地球辐射平衡模型是：

:(1-a)S/pi*r² =4/pi*r²/epsilon/sigma*T⁴

:(1-a)S/pi*r² =4/pi*r²/epsilon/sigma*T⁴

:* S是太阳常数，即单位面积内的入射太阳辐射约1367 W·m⁻²

:* S是太阳常数，即单位面积内的入射太阳辐射约1367 W·m⁻²

:* a 是地球的平均反照率，测量值为0.3；

:* a 是地球的平均反照率，测量值为0.3；

:* r 为地球半径ー大约6.371 × 106m；

:* r 为地球半径，大约6.371 × 106m；

:* π 为数学常数(3.141...)；

:* π 为数学常数(3.141...)；

:* σ 为斯蒂芬-玻尔兹曼常数ー大约5.67 × 10^-8jk^-4m^-2s^-1

:* σ 为斯蒂芬-玻尔兹曼常数，大约5.67 × 10^-8jk^-4m^-2s^-1

:* ε 为地球的有效发射率，大约0.612；

:* ε 为地球的有效反射率，大约0.612；

::常数πr²可以分解出来，给出求解温度 :

::常数πr²可以分解出来，给出求解温度 :

::<nowiki>T = sqrt [4]{ frac {(1-a) s }{4 epsilon sigma }}</nowiki>  

::                                                     <nowiki>T = sqrt [4]{ frac {(1-a) s }{4 epsilon sigma }}</nowiki>

::这样得到转换的表观有效地球平均温度。这是因为上面的方程代表了地球的有效辐射温度(包括云和大气)。

::这样得到明显有效的地球平均温度。这是因为上面的方程代表了地球的有效辐射温度(包括云和大气)。

::This very simple model is quite instructive. For example, it easily determines the effect on average earth temperature of changes in solar constant or change of albedo or effective earth emissivity.

::This very simple model is quite instructive. For example, it easily determines the effect on average earth temperature of changes in solar constant or change of albedo or effective earth emissivity.

::这个非常简单的模型很有启发性。例如，它很容易确定太阳常数的变化或反照率或有效地球发射率的变化对平均地球温度的影响。

::这个非常简单的模型很有启发性。例如，它很容易确定太阳常数、反照率或有效地球发射率的变化对平均地球温度的影响。

::The average emissivity of the earth is readily estimated from available data. The emissivities of terrestrial surfaces are all in the range of 0.96 to 0.99<ref>{{cite web|url=http://www.icess.ucsb.edu/modis/EMIS/html/seawater.html|title=Seawater Samples - Emissivities|work=ucsb.edu}}</ref><ref>{{cite journal |doi=10.1175/JCLI3720.1 |vauthors=Jin M, Liang S |title=An Improved Land Surface Emissivity Parameter for Land Surface Models Using Global Remote Sensing Observations |journal=J. Climate |volume=19 |issue=12 |pages=2867–81 |date=15 June 2006 |url=http://www.glue.umd.edu/~sliang/papers/Jin2006.emissivity.pdf|bibcode = 2006JCli...19.2867J }}</ref> (except for some small desert areas which may be as low as 0.7). Clouds, however, which cover about half of the earth's surface, have an average emissivity of about 0.5<ref>{{cite conference |author1=T.R. Shippert |author2=S.A. Clough |author3=P.D. Brown |author4=W.L. Smith |author5=R.O. Knuteson |author6=S.A. Ackerman |title=Spectral Cloud Emissivities from LBLRTM/AERI QME  |book-title=Proceedings of the Eighth Atmospheric Radiation Measurement (ARM) Science Team Meeting March 1998 Tucson, Arizona |url=http://www.arm.gov/publications/proceedings/conf08/extended_abs/shippert_tr.pdf }}</ref> (which must be reduced by the fourth power of the ratio of cloud absolute temperature to average earth absolute temperature) and an average cloud temperature of about {{convert|258|K|abbr=on}}.<ref>{{cite conference |author1=A.G. Gorelik |author2=V. Sterljadkin |author3=E. Kadygrov |author4=A. Koldaev |title=Microwave and IR Radiometry for Estimation of Atmospheric Radiation Balance and Sea Ice Formation |book-title=Proceedings of the Eleventh Atmospheric Radiation Measurement (ARM) Science Team Meeting March 2001 Atlanta, Georgia |url=http://www.arm.gov/publications/proceedings/conf11/extended_abs/gorelik_ag.pdf }}</ref> Taking all this properly into account results in an effective earth emissivity of about 0.64 (earth average temperature {{convert|285|K|abbr=on}}). 地球的平均比辐射率很容易从现有数据中估计出来。陆地表面的放射系数均在0.96ー0.99之间(除少数小沙漠地区可能低至0.7)。然而，覆盖地球表面大约一半的云层，其平均发射率约为0.5(必须用云的绝对温度与地球平均绝对温度之比的四次方减少) ，而云的平均温度约为0.5。适当地考虑这些因素，得到的有效地球发射率约为0.64(地球平均温度)。

::The average emissivity of the earth is readily estimated from available data. The emissivities of terrestrial surfaces are all in the range of 0.96 to 0.99<ref name=":1">{{cite web|url=http://www.icess.ucsb.edu/modis/EMIS/html/seawater.html|title=Seawater Samples - Emissivities|work=ucsb.edu}}</ref><ref name=":2">{{cite journal |doi=10.1175/JCLI3720.1 |vauthors=Jin M, Liang S |title=An Improved Land Surface Emissivity Parameter for Land Surface Models Using Global Remote Sensing Observations |journal=J. Climate |volume=19 |issue=12 |pages=2867–81 |date=15 June 2006 |url=http://www.glue.umd.edu/~sliang/papers/Jin2006.emissivity.pdf|bibcode = 2006JCli...19.2867J }}</ref> (except for some small desert areas which may be as low as 0.7). Clouds, however, which cover about half of the earth's surface, have an average emissivity of about 0.5<ref>{{cite conference |author1=T.R. Shippert |author2=S.A. Clough |author3=P.D. Brown |author4=W.L. Smith |author5=R.O. Knuteson |author6=S.A. Ackerman |title=Spectral Cloud Emissivities from LBLRTM/AERI QME  |book-title=Proceedings of the Eighth Atmospheric Radiation Measurement (ARM) Science Team Meeting March 1998 Tucson, Arizona |url=http://www.arm.gov/publications/proceedings/conf08/extended_abs/shippert_tr.pdf }}</ref> (which must be reduced by the fourth power of the ratio of cloud absolute temperature to average earth absolute temperature) and an average cloud temperature of about 0.5.<ref>{{cite conference |author1=A.G. Gorelik |author2=V. Sterljadkin |author3=E. Kadygrov |author4=A. Koldaev |title=Microwave and IR Radiometry for Estimation of Atmospheric Radiation Balance and Sea Ice Formation |book-title=Proceedings of the Eleventh Atmospheric Radiation Measurement (ARM) Science Team Meeting March 2001 Atlanta, Georgia |url=http://www.arm.gov/publications/proceedings/conf11/extended_abs/gorelik_ag.pdf }}</ref> Taking all this properly into account results in an effective earth emissivity of about 0.64 (earth average temperature).

:This simple model readily determines the effect of changes in solar output or change of earth albedo or effective earth emissivity on average earth temperature. It says nothing, however about what might cause these things to change. Zero-dimensional models do not address the temperature distribution on the earth or the factors that move energy about the earth.

::地球的平均比辐射率很容易从现有数据中估计出来。陆地表面的放射系数均在0.96ー0.99之间<ref name=":1" /><ref name=":2" /> (除少数小沙漠地区可能低至0.7)。然而，覆盖地球表面大约一半的云层，其平均反射率约为0.5(必须用云的绝对温度与地球平均绝对温度之比的四次方减少) ，而云的平均温度约为0.5。适当地考虑这些因素，得到有效地球反射率约为0.64(地球平均温度)。

:这个简单的模型很容易确定太阳输出量的变化或地球反照率或有效地球发射率的变化对地球平均温度的影响。然而，它没有提到是什么可能导致这些事情发生改变。零维模型不能解释地球上的温度分布或者地球周围移动能量的因素。

::This simple model readily determines the effect of changes in solar output or change of earth albedo or effective earth emissivity on average earth temperature. It says nothing, however about what might cause these things to change. Zero-dimensional models do not address the temperature distribution on the earth or the factors that move energy about the earth.

::这个简单的模型很容易确定太阳输出量的变化或地球反照率的变化或有效地球反射率的变化对地球平均温度的影响。然而，它没有提到是什么可能导致这些事情发生改变。零维模型不能解释地球上的温度分布或者导致地球能量移动的因素。

== Radiative-convective models= = 辐射-对流模式 = ==

== Radiative-convective models= = 辐射-对流模式 = ==

* upward transport of heat by convection (especially important in the lower [[troposphere]]).

* upward transport of heat by convection (especially important in the lower [[troposphere]]).

上述零维模型利用太阳常数和给定的地球平均温度，确定了向空间发射的长波辐射的有效地球发射率。这可以在垂直于一维辐射对流模式的方向上加以改进，该模式考虑两个能量输送过程:

上述零维模型利用太阳常数和给定的地球平均温度，确定了向空间发射的长波辐射的有效地球反射率。这可以在垂直于一维辐射对流模式的方向上加以改进，该模式考虑两个能量输送过程:

* 通过大气层的上升流和下降辐射转移，这些大气层通过对流层吸收和释放红外线

* 通过大气层的上升流和下降辐射转移，这些大气层通过对流层吸收和释放红外线

The radiative-convective models have advantages over the simple model: they can determine the effects of varying [[greenhouse gas]] concentrations on effective emissivity and therefore the surface temperature. But added parameters are needed to determine local emissivity and albedo and address the factors that move energy about the earth.

The radiative-convective models have advantages over the simple model: they can determine the effects of varying [[greenhouse gas]] concentrations on effective emissivity and therefore the surface temperature. But added parameters are needed to determine local emissivity and albedo and address the factors that move energy about the earth.

辐射-对流模式比简单模式有优点: 它们可以确定不同温室气体浓度对有效发射率的影响，因此也可以确定地表温度。但是需要增加参数来确定局部辐射系数和反照率，并解决地球周围能量移动的因素。

辐射-对流模式比简单模式有优点: 它们可以确定不同温室气体浓度对有效反射率的影响，因此也可以确定地表温度。但是需要增加参数来确定局部辐射系数和反照率，并解释导致地球上能量移动的因子。

Effect of ice-albedo feedback on global sensitivity in a one-dimensional radiative-convective climate model.<ref>{{cite web|url=http://pubs.giss.nasa.gov/cgi-bin/abstract.cgi?id=wa03100m|archive-url=https://archive.today/20120730021359/http://pubs.giss.nasa.gov/cgi-bin/abstract.cgi?id=wa03100m|url-status=dead|archive-date=2012-07-30|title=Pubs.GISS: Wang and Stone 1980: Effect of ice-albedo feedback on global sensitivity in a one-dimensional...|work=nasa.gov}}</ref><ref>{{Cite journal

Effect of ice-albedo feedback on global sensitivity in a one-dimensional radiative-convective climate model.<ref>{{cite web|url=http://pubs.giss.nasa.gov/cgi-bin/abstract.cgi?id=wa03100m|archive-url=https://archive.today/20120730021359/http://pubs.giss.nasa.gov/cgi-bin/abstract.cgi?id=wa03100m|url-status=dead|archive-date=2012-07-30|title=Pubs.GISS: Wang and Stone 1980: Effect of ice-albedo feedback on global sensitivity in a one-dimensional...|work=nasa.gov}}</ref><ref>{{Cite journal

冰反照率反馈对一维辐射对流气候模式全球敏感性的影响。

冰反照率反馈对一维辐射对流气候模式全球敏感性的影响。

== Higher-dimension models= = 高维模型 = = ==

== Higher-dimension models = 高维模型 = ==

The zero-dimensional model may be expanded to consider the energy transported horizontally in the atmosphere. This kind of model may well be [[Zonal and meridional|zonally]] averaged. This model has the advantage of allowing a rational dependence of local albedo and emissivity on temperature – the poles can be allowed to be icy and the equator warm – but the lack of true dynamics means that horizontal transports have to be specified.<ref>{{cite web|url=http://www.shodor.org/master/environmental/general/energy/application.html|title=Energy Balance Models|work=shodor.org}}</ref>

The zero-dimensional model may be expanded to consider the energy transported horizontally in the atmosphere. This kind of model may well be [[Zonal and meridional|zonally]] averaged. This model has the advantage of allowing a rational dependence of local albedo and emissivity on temperature – the poles can be allowed to be icy and the equator warm – but the lack of true dynamics means that horizontal transports have to be specified.<ref>{{cite web|url=http://www.shodor.org/master/environmental/general/energy/application.html|title=Energy Balance Models|work=shodor.org}}</ref>

== EMICs (Earth-system models of intermediate complexity) ==

== EMICs (Earth-system models of intermediate complexity) ==

大气环流模式(GCMs)离散了流体运动和能量传递的方程，并随着时间的推移积分这些方程。与较简单的模型不同，大气环流模型将大气和/或海洋划分为代表计算单位的离散“单元”网格。与作出混合假设的简单模型不同，单元内部的过程(例如对流)在尺度太小而无法直接解决的情况下在单元层面上被参数化，而其他功能则控制单元之间的界面。

大气环流模式(GCMs)离散了流体运动和能量传递的方程，并随着时间的推移积分这些方程。与较简单的模型不同，大气环流模型将大气和/或海洋划分为代表计算单位的离散“单元”网格。与作出混合假设的简单模型不同，单元内部的过程(例如对流)在尺度太小而无法直接解决的情况下在单元层面上被参数化，而其他功能则控制单元之间的界面。

Atmospheric GCMs (AGCMs) model the atmosphere and impose [[sea surface temperature]]s as boundary conditions. Coupled atmosphere-ocean GCMs (AOGCMs, e.g. [[HadCM3]], [[EdGCM]], [[GFDL CM2.X]], ARPEGE-Climat)<ref>[http://www.cnrm.meteo.fr/gmgec/site_engl/arpege/arpege_en.html ]  {{webarchive |url=https://web.archive.org/web/20070927215849/http://www.cnrm.meteo.fr/gmgec/site_engl/arpege/arpege_en.html |date=27 September 2007 }}</ref> combine the two models. The first general circulation climate model that combined both oceanic and atmospheric processes was developed in the late 1960s at the [[NOAA]] [[Geophysical Fluid Dynamics Laboratory]]<ref>{{cite web|url=http://celebrating200years.noaa.gov/breakthroughs/climate_model/welcome.html|title=NOAA 200th Top Tens: Breakthroughs: The First Climate Model|work=noaa.gov}}</ref> AOGCMs represent the pinnacle of complexity in climate models and internalise as many processes as possible. However, they are still under development and uncertainties remain.  They may be coupled to models of other processes, such as the [[carbon cycle]], so as to better model feedback effects. Such integrated multi-system models are sometimes referred to as either "earth system models" or "global climate models."

Atmospheric GCMs (AGCMs) model the atmosphere and impose [[sea surface temperature]]s as boundary conditions. Coupled atmosphere-ocean GCMs (AOGCMs, e.g. [[HadCM3]], [[EdGCM]], [[GFDL CM2.X]], ARPEGE-Climat)<ref>[http://www.cnrm.meteo.fr/gmgec/site_engl/arpege/arpege_en.html ]  {{webarchive |url=https://web.archive.org/web/20070927215849/http://www.cnrm.meteo.fr/gmgec/site_engl/arpege/arpege_en.html |date=27 September 2007 }}</ref> combine the two models. The first general circulation climate model that combined both oceanic and atmospheric processes was developed in the late 1960s at the [[NOAA]] [[Geophysical Fluid Dynamics Laboratory]]<ref>{{cite web|url=http://celebrating200years.noaa.gov/breakthroughs/climate_model/welcome.html|title=NOAA 200th Top Tens: Breakthroughs: The First Climate Model|work=noaa.gov}}</ref> AOGCMs represent the pinnacle of complexity in climate models and internalise as many processes as possible. However, they are still under development and uncertainties remain.  They may be coupled to models of other processes, such as the [[carbon cycle]], so as to better model feedback effects. Such integrated multi-system models are sometimes referred to as either “earth system models”or "global climate models."

大气层大气环流模式(AGCMs)模拟大气，并把海面温度作为边界条件。大气-海洋耦合大气环流模式。结合了这两个模型。第一个将海洋和大气过程结合在一起的大气环流气候模式是在20世纪60年代末由美国国家海洋和大气管理局的地球物理流体动力学实验室气候模式发展起来的，它代表了气候模式复杂性的顶峰，并且尽可能地内化了许多过程。然而，它们仍在发展之中，不确定性仍然存在。它们可以与碳循环等其他过程的模型耦合，以便更好地模拟反馈效应。这种综合的多系统模型有时被称为“地球系统模型”或“全球气候模型”

大气层大气环流模式(AGCMs)模拟大气，并把海面温度作为边界条件。大气-海洋耦合大气环流模式。结合了这两个模型。第一个将海洋和大气过程结合在一起的大气环流气候模式是在20世纪60年代末由美国国家海洋和大气管理局的地球物理流体动力学实验室气候模式发展起来的，它代表了气候模式复杂性的顶峰，并且尽可能地内化了许多过程。然而，它们仍在发展之中，不确定性仍然存在。它们可以与碳循环等其他过程的模型耦合，以便更好地模拟反馈效应。这种综合的多系统模型有时被称为“地球系统模型”或“全球气候模型”