我现在在大学读环境科学,在一次关于古气候的讲座中,我们的教授展示了一些全新世和更新世时期的气候图表(如下所示),然后说全新世的温度比更新世稳定得多,然后就没有详细说明了。
我们知道为什么会这样吗?有没有研究试图找出这是为什么?< / p >
试图理解这个问题,一位大学讲师发给我:
“中世纪气候异常在区域尺度上的主导气候和强迫机制方面是独特的。”
用案例研究来批判性地评价这一评论,以支持你的答案
这一陈述是说MCA仅仅是由区域范围内的现行气候和机制引起的吗?如果是这样,有什么区域尺度强迫机制的例子?< / p >
Perhaps this is more of a pure physics question than an applied physics, Earth-science one, but I am very curious....
CO2吸收大约15微米波长或波数650,并在相同但也更宽的范围内辐射。
然而,海洋的顶层似乎也转换了光谱范围。根据一篇论文,我发现在650波数附近,水中的红外线吸收率有所增加。< / p >
http://www.acamedia.info/sciences/J_G/envrad/microwaves/Water_absorption_spectrum.pdf
Can it in a substantial way contribute to a conversion of that spectrum range to other spectra?
Added text for asked clarification.
We know co2 radiation is somewhat wider than absorption. I am asking if that is the same in the first few microns depth in water (few molecules of the top layer). Absorption of infrared in water does the same? And the total (combined with co2) is substantial enough to explain the missing gap around 15 microns wavelenght in the outgoing radiation of the earth?
水在不同压力和温度下的相变化告诉我们,在没有大气压的情况下,200开尔文(- 73摄氏度)足以将冰直接转化为蒸汽
这难道不表明,在地球到太阳的距离上,太阳的日照加热势足以将假设的冰行星启动为一个有大气的水世界吗?即使是平均白天/晚上?< / p >
这一过程的最终结果是一份详尽全面的“已发表的气候学家”名单。
导出这两个关键术语的定义以最大限度地提高其规范的合理性的最佳过程是什么?
我正在拍摄,实际上直接询问世界上所有出版的气候学家,使用一个非常高质量的(与盖洛普民意调查相当)调查,只有对/错或多项选择答案。
(1)他们必须至少有一篇与气候变化直接相关的已发表论文。
(2)这必须发表在同行评议的与气候学或气象学直接相关的学术期刊上。
(3)具有气候学或气象学博士学位。
这将筛选出许多非常合格的人,因为我们不能让任何不合格的人出现在这个集合中。< / p >
(1)实现特定目标(如2C)所需的温室气体减排目标。第一个估计值似乎是到2050年净排放量为零。在我们真正拥有完全可扩展的碳减排技术之前,我们必须假设零排放。江南登录网址app下载
(2)超过2摄氏度目标对人类社会和地球上其他生物的影响。IPCC对作物产量的估计影响似乎相当显著。
(3)对反馈回路的不可逆转点(引爆点)的估计:
在永久冻土融化等事件使减缓气候变化的行动变得不可行之前,我们还要等多久才开始采取减缓气候变化的行动?
(1)如果达成共识,我们必须在2050年之前实现温室气体零排放,这精确地量化了紧迫性的一个关键方面。
(2)如果人们一致认为,80年的商业活动可能会导致全球升温5摄氏度,这是另一个量化的紧迫性衡量标准。
(3)如果人们达成共识,认为全球升温5摄氏度很可能会导致作物生产等事物的风险显著增加,这是另一个量化的紧迫性衡量标准。
(4)如果我们距离一个关键的临界点反馈回路50 PPM的二氧化碳使永久冻土的融化无法停止,这将提供另一种量化的紧迫性措施。< / p >
I appreciate your help.
Thank you!
我对可视化整个美国的气候数据感兴趣,以确定我有兴趣居住的地区。目前为止,我调出了NOAA的数据,我已经:
首先,这些似乎是“足够好”的近似值,但我发现这种方法有些不充分,因为它是:
我最初试图发现平均温度高的地区,每年和每天的温度变化小,降雨量少。我可以使用哪些指标来改进这项调查?谢谢!< / p >
我目前正在开发一些云掩蔽软件,到目前为止,我只使用了最近春天(北半球)的卫星数据。然而,我想知道云的覆盖或形成是否在不同的季节有明显的变化?< / p >
我们没有找到任何文档来解释这个事实。你能解释一下平均和时间戳背后的原理吗?参考资料会很有帮助的。
称它们为热点正确吗?< / p >
I hear the claim a lot that the recent cold weather extremes (such as the polar vortex affecting the US) are caused by global warming, but haven't seen many scientific papers supporting it. I'm not sure if I just haven't come across more. And, I'm not sure if the ones that exist are even considered compelling by climatologists.
For example, my geography textbook says that Atacama Desert is a desert where foggy weather is common, and it persists almost the whole year. Whereas every astronomer will say that it is the place with least clouds and fog, which is why it is one of the best places for astronomical observations beyond the dark sky.
So, which is true? And if one of them is not true, then how did it gain popularity at all?
These periods consist normally of 30 years of data. If you want to compare two normal periods with each other, let's say for example the periods 1951-1980 and 1981-2010.
Now if we take averages for all the seasons in the period 1951-1980, the last month is December in this period. If we regard December, January, and February as a complete season/winter, it means that we have an incomplete winter at the end of the period 1951-1980. Now taking December to represent a whole winter, would be inaccurate. The monthly variations of a climatic parameter can vary greatly, and multiplying the December values by 3 wouldn't yield a result based on actual observations. Also making December the whole winter of 1980, would underestimate the real winter average. This would in turn affect the overall 30-year mean, by lowering it and giving a wrong picture of the actual seasonal mean in that normal period.
Same goes for the beginning of the period 1981-2010, here we have January and February as an incomplete winter.
Now in order to get complete seasons in the intersections between the normal periods, wouldn't it be best to split the periods as follows: 1951-1980.11.30 and 1980.12.01-1990.
Also it would be best to cut out December completely at the end of the period: 1980.12.01-1990.
So that it becomes: 1980.12.01-1990.11.30.
The same goes for the last normal period: 1951-1980.11.30.
Where we would cut out January and February of 1951 so that we get: 1951.03.01-1980.11.30.
In this way we make sure we have complete seasons in both normal periods. So if we also do comparisons of monthly averages: JAN-FEB-MAR..., we would still split up the periods in the same manner, in order to use the exact same periods for exact comparison with the seasonal averages.
However when we have split up the periods as follows: 1951.03.01-1980.11.30 and 1980.12.01-1990.11.30. Is it still normal in academic papers to say that we are comparing the normal periods 1951-1980 and 1981-2010, when there is actually a small overlap in the last?
If this is not the normal procedure, what is the way to get around this? What do researchers normally do in this case?
In addition cutting of seasons/months in this manner yields an unequal number of months/seasons. The analysis might have data from a higher number of the month February compared to January. So the statistics from February are more reliable. Also a disadvantage of cutting out actual observation data, yields a loss of valuable observation data, which lowers the reliability of the statistics.
How they differ from RCPs? And how they are similar to Observed reanalysis data?
Thanks
对于撒哈拉以南非洲500mm和800mm降雨等雨量线之间的许多网格单元,我得到了每十年一次的降雨量(来自FEWS)。它们分布在整个大陆,而且有很多,所以它们会有不同的季节性,尽管它们应该都大致是单峰的(特别是考虑到我所处的纬度)。
我想定义一个算法来定义雨季的平均开始和结束时间。到目前为止,我想的是以下内容:
对于每个网格单元:
20%的数字似乎是任意的,尽管我不确定还能做什么。我并不是一个真正的气候科学家,不过也许我可以在电视上扮演一个。这里有公认的惯例吗? If not, any suggestions on improving my algorithm?
你能推荐一些关于气候/气候学的书吗?< / p >
显然,他认为戴维斯在提出他的(戴维斯)侵蚀正常循环时,把温带湿润条件假设为世界的“正常条件”是不正确的。
King接着建议,应该是“半干旱”的条件,而不是应该被假设为“正常条件”(代表世界气候),因此,他的(King’s)建议“侵蚀的正常循环”。< / p >
So my questions are:
P.S.: I suppose if a figure isn't available for Temperate/SemiArid climate, a figure for the 6 Temperate Biomes and the 3 SemiArid Biomes would also do the trick...
CRUTEM4中观测到的大部分陆地变暖是北半球的冬季月份造成的。从1850年到1990年,夏季(6月、7月、8月和9月)基本上没有任何变暖迹象。总的来说,北半球冬季的变暖程度大约是北半球夏季的两倍。< / p > < p >…同样的练习在南半球显示出非常小的差异,当然季节月份是颠倒的。
这个效应有一个合理的解释吗?比如,它在气候模型中重现了吗?< / p >