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在21世纪有自然驱动气候预测?

CMIP5提供natural-forcings-only模拟在1850 - 2005年,它允许与历史模拟,这允许我们显示人为人类行为如何影响气候。

CMIP5还提供预测在21世纪,一系列的rcp允许不同的排放场景。

然而,CMIP5不包括21世纪自然迫使相比较而言,尽管这将是有用的。这种模拟存在别的地方吗?

我意识到,这些不会是完全可能的,因为火山等自然营力的数据是不可用的。然而,这些可能是合理使用随机模型模拟。其他自然营力,如轨道营力,可以很容易地计算在下个世纪。太阳辐照度可能是在两者之间。

如果不存在这种模拟,会不合理使用1850 - 2005年的自然营力模拟作为21世纪的一个统计模型的基础吗?或者是一些自然营力可能大幅改变(如20世纪火山代表性的背景,或者是轨道迫使可能大幅改变在未来世纪?)。

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你是对的,没有未来的自然营力实验CMIP5协议中定义的。原因是简单,建模组认为其他实验更值得他们有限的计算时间。相比之下更呼吁historicalNat和historicalGHG实验,所需检测和归因研究。个人建模中心可能运行的未来自然营力实验,但这将打击和小姐,并没有一个实验名称提出CMIP5数据库中输出。顺便提一句,这种情况与RCP(所有营力)实验本身实际上是有点不完美,因为未来的实现自然营力的决策权交给每个建模组:> 5。…建议要么火山气溶胶应该完全省略了从控制和未来运行时,或者,或者,相同的背景气溶胶都应规定运行。> 6。建议的一些表示太阳活动周期被包括在20世纪和21世纪的模拟,尽管这是留给建模组的自由裁量权。> >来源:泰勒et al (2011)。CMIP5实验设计的总结。 ([pdf](https://cmip.llnl.gov/cmip5/docs/Taylor_CMIP5_design.pdf)) There was a further [recommendation](http://solarisheppa.geomar.de/cmip5) for how future solar irradiance forcing should be represented: > In CMIP5, climate projections were based on a stationary-Sun scenario, obtained by simply repeating solar cycle 23, which ran from April 1996 to June 2008 (Lean and Rind, 2009). > > Source: Matthes et al (2017). Solar forcing for CMIP6 (v3.2), Geosci. Model Dev., 10, 2247-2302, https://doi.org/10.5194/gmd-10-2247-2017 But, in practice, groups did slightly different things from each other, so you usually have to check the output file metadata and any associated journal papers for individual model runs to get an idea of the details. This is clearly not a crazy question though, because in CMIP6 some future natural forcings experiments have been defined, albeit in the lower priority tiers. Specifically, the Detection and Attribution MIP (DAMIP) includes [ssp245-GHG][1] and [ssp245-nat][2] experiments, and the volcano MIP ([VolMIP][5]) has the [volc-cluster-21C][3] experiment. If you dig down into those you’ll find that future solar variability is derived more or less the way you describe, i.e., projecting forward based on a set of statistical time series models trained on past variability. Note, however, that Matthes et al are careful to point out that this is a projection not a prediction: > As of today, predicting solar activity up to 2300 is very challenging, if not impossible… The unusually long solar cycle number 23 that ended in 2009, and the weak one (no. 24) that followed came as a surprise, and manifested our evident lack of understanding of the solar cycle. Conversely, future volcanic forcing in ssp245-nat will be prescribed as a near-constant background forcing: > Volcanic forcing will be ramped up from the value at the end of the historical simulation period (2015) over 10 years to the same constant value prescribed for the piControl simulations in the DECK, and then will be kept fixed. > > Source: O'Neill et al (2016). The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geosci. Model Dev., 9, 3461-3482, http://doi.org/10.5194/gmd-9-3461-2016 So why not a statistical model for volcanic emissions? This forcing is episodic rather than cyclic and is prescribed to the CMIP models as several variables on latitude-height-time grids. As you hint at in your question, this is too many degrees of freedom to pin down satisfactorily from just the 1850-2005 record. Even if it could be done, you then have the problem of how to use the statistical model, given that each climate model will only run a few realisations of a particular projection. Do you generate one scenario to be shared by all models, or do you let each group generate its own scenarios using the statistical model? Either way, you can’t explore enough of the parameter space to avoid ending up with a CMIP6 ensemble containing decadal variability that is strongly influenced by forcing scenarios that are extremely unlikely to happen. As I understand it, the current assumption is that volcanic forcing is stationary and, in the absence of knowing the future sequence of eruptions, its effect on slowly varying climate components like ocean heat content is best represented by a constant mean forcing. [1]: https://view.es-doc.org/?renderMethod=id&project=cmip6&id=f906e17f-1b29-40bc-9140-fbb035a2b8d9 "ssp245-GHG" [2]: https://view.es-doc.org/?renderMethod=id&project=cmip6&id=4966bb28-934e-40d5-a1bf-91a2827c4aa6 "ssp245-nat" [3]: https://view.es-doc.org/?renderMethod=id&project=cmip6&id=8dbad2a5-640b-4fb8-93d2-3fdeb0bd3ef9 "volc-cluster-21c" [5]: https://doi.org/10.5194/gmd-9-2701-2016 "VolMIP"

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\ begingroup美元固定的答案,谢谢。你的观点太大的自由度很多意义,尤其是这些天许多模型的高分辨率。我想会是一件很美好的事情很多的低分辨率模型尽可能广泛的样本输入的不确定性。但这真的是一个单独的问题我在问什么。 \ endgroup美元
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2019年1月29日,实在

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