Dear Sabyasachi,

There is no particular reason to compute climate statistics on the basis of a 30-year period, other than tradition: one could have chosen 25, or 29, or 32 just as well. Initially, the logic was to select a period long enough that individual weather events would not skew the results one way or another. On the other hand, adopting much longer periods would have prevented many weather stations to contribute climate statistics.

Remember also that the climate is actually varying on a wide range of temporal scales, with inter-annual fluctuations, El-Niño events, oscillations, etc., up to well-documented ice ages on the time scales of tens of thousands of years. And, as you correctly point out, mean global temperature is itself evolving rather quickly lately, in comparison to what happened during the last 100,000 years, for instance.

So there is really no magic in that number: it is just a convenient convention. I hope this helps. Michel.

Dear Sabyasachi,

There is no particular reason to compute climate statistics on the basis of a 30-year period, other than tradition: one could have chosen 25, or 29, or 32 just as well. Initially, the logic was to select a period long enough that individual weather events would not skew the results one way or another. On the other hand, adopting much longer periods would have prevented many weather stations to contribute climate statistics.

Remember also that the climate is actually varying on a wide range of temporal scales, with inter-annual fluctuations, El-Niño events, oscillations, etc., up to well-documented ice ages on the time scales of tens of thousands of years. And, as you correctly point out, mean global temperature is itself evolving rather quickly lately, in comparison to what happened during the last 100,000 years, for instance.

So there is really no magic in that number: it is just a convenient convention. I hope this helps. Michel.

@Michel Sir and @ Kenneth M Towe Sir, thank you so much for such explanatory responses.

@Kenneth M Towe Sir,

I didn't get your last sentence i.e.

"Also, Frank is not correct that temperatures have been "evolving" rather quickly lately. Their rate of growth is very slow."

Who is Frank? Evolution of temperature? Can you please provide a better insight to it. It seems very interesting!

@Gregor Sir, thanks for your answer. The paper is indeed useful.

@Kenneth M Towe Sir, thanks for clarifying in such a lucid and interesting way. You even have all the comments related to a particular field in your mind, you can give so many quotes (relevant comments of different persons even years ago) in an answer. That is amazing and very much inspiring. Thanks a million sir!

climate is a micro variable whereas climate change is macro. so we need to study a long period of time to assess the climate change and its conveniently taken as 30 years or so

@ Sachin,

thanks for your answer. But, how you said "climate is a micro variable whereas climate change is macro". Even climate is a very long term phenomena. I have read several books or papers, where it is mentioned that, climate is the average weather for a longer periods, typically 30 years or more. So, can you please elaborate, why and how climate is a micro variable whereas its changes becomes macro?

@sabyasachi

I just try to point out  that when compared to climate change climate is micro 

more people means getting higher chance of using somethings causing heat. CO content becomes higher and higher because of human activity. Actually in a geologic time, we are now in the interglacial period so the temperatures are gradually decreasing bit by bit.

From the young 

Exposing kids to nature is a crucial step to getting kids to care about environmental issues, the poll finds. Those with personal, positive experiences with nature were twice as likely to view themselves as strong environmentalists and were significantly more likely to express concern about water issues, air pollution, climate change and the overall condition of the environment.

http://www.nature.org/newsfeatures/kids-in-nature/kids-in-nature-poll.xml

Dear Sabyasachi Swain,

The main reason by why we can't predict the climate in a short interval is mainly due to chaotic nature. If you are familiar with the butterfly effect you would be aware that even deterministic systems can become unpredictable. Take a look at Lyapunov time scale too. As beyond this scale, predictions are impossible.

Hope this helps

Hari

Thanks @Punya Charusiri, @ Krishnan Umachandran and @Harisankar Krishnadas for your answers.

@Punya Charusiri, "temperatures are gradually decreasing bit by bit". But your explanation is contrasting this last sentence of your comment.

Moreover, How can we draw a line of 30 years for climate change then? Because the rate of increase in population or CO is not constant.

Climatic data are usually expressed in terms of an individual calendar months or season and are determined over a period , usually about 30 years, long enough ti ensure that representative values for the month or season are obtained.

See: http://library.wur.nl/WebQuery/clc/155885,

For thirty years air temperatures are the minimum set of data or time series with which the standard deviation between the data tends to stabilize.

Thank you Giorgio Russo for your answer.

This is a great question, one that could lead to development of a research program.

Thirty years was the period adopted officially by the WMO around 1940.

http://journals.ametsoc.org/doi/pdf/10.1175/2010BAMS2955.1

In 1940, most academics were teaching that global climate had been stable for 5,000 years, since the hypsithermal.

But a few prehistorians and archaeologists had anticipated the research of Hubert Lamb in claiming that climate had fluctuated sufficiently to have been a factor in the rise and fall of prehistoric societies and of civilizations.

In retrospect, it seems there was not much scientific justification for adopting a 30-year period. Nevertheless, bureaucrats and scientists still use 30 years.

A recent paper compared the first and last 30 years of the 20th century and found little difference in regional climate boundaries when assessed by Koppen-Trewartha criteria.

The precipitation data they used has since been corrected for wet bias. Thus, the small changes they reported would be smaller if they were to use the new datasets.

Climate classification revisited from Köppen to Trewartha, Belda, M. et al, Climate Research, 2014

http://www.int-res.com/articles/cr_oa/c059p001.pdf

Oceanic oscillations (PDO, NAO, AMO, etc) have been implicated in multi-decadal fluctuations in climate with quasi-cyclical periods as long as 60 years.

This longer-period fluctuation could be seen almost 30 years ago in the graphs presented by Stanley Grotch of the Lawrence Livermore Labs. Until 1980, his graph showed long-period climate fluctuations within the "normal" range observed since the 19th century.

Grotch, S. L. (1987). Some considerations relevant to computing average hemispheric temperature anomalies. Monthly weather review, 115(7), 1305-1317.

http://journals.ametsoc.org/doi/abs/10.1175/1520-0493(1987)1152.0.CO%3B2

Between around 1975 to 2005 global temperature and precipitation were slightly higher than between 1900 to 1930 or so. And between those two periods, global temperature declined.

In my opinion, an important scientific question is the degree to which past fluctuations in temperature were driven by oceanic oscillations.

This would include the increase in global temperature between 1975 to 2005 and what may still turn out to be a topping out since then, depending on the strength of the developing La Nina and what happens later.

That question would lead to the further question: what drives the oceanic oscillations?

And to the further question: which drives which? 

Does the climate system work the way it does because the atmosphere drives the oceans or because the oceans drive the atmosphere?

To what extent are the atmosphere and oceans coupled, such as by wind and by convection?

Before embarking on a research program, I suggest obtaining data on the 30 or so GCM (models) presented in IPCC reports.

http://www.ipcc-data.org/sim/gcm_monthly/AR5/index.html

Look for the average of the ensemble of the models, the heavy red line in the graphic on page 959, AR5 Climate Change 2013: The Physical Science Basis, Chapter 11, Near-term Climate Change:

Projections and Predictability.

http://www.ipcc.ch/pdf/assessment-report/ar5/wg1/WG1AR5_Chapter11_FINAL.pdf

Look also for the projected CO2 equivalent of GHG used in the models.

Plot temperature as the dependent variable and CO2-equivalent as the independent variable. (You cannot use past observations for this because the models have been tuned to the past.)

Judge for yourself to what extent the GCMs have produced a result not contained in the AGW assumption that atmospheric CO2 drives the climate system. 

Environmental Research Letters declined to publish a paper by Lennart Bengtsson.

The reviewer stated that IPCC ranges in AR4 and AR5 are "...not directly comparable to observation based intervals.... One cannot and should not simply interpret the IPCCs ranges for AR4 or 5 as confidence intervals or pdfs and hence they are not directly comparable to observation based intervals (as e.g. in Otto et al)..... I have rated the potential impact in the field as high, but I have to emphasise that this would be a strongly negative impact, as it does not clarify anything but puts up the (false) claim of some big inconsistency, where no consistency was to be expected in the first place."

http://ioppublishing.org/news/statement-from-iop-publishing-on-story-in-the-times/

In my opinion, this confirms that both the average of the ensemble of GCMs and the models themselves are merely scenarios with no predictive value beyond what could be generated by a one-page spreadsheet.

And if the correlation between projected CO2 and projected temperature is as high as I have seen reported I have doubts about the degree of coupling in the models between atmosphere and oceans.

So my advice to you as a researcher is not to allow yourself to be intimidated by the vastness of the literature or the grant budgets that support it. 

Just continue to ask good questions and design your own approach to exploring answers. 

Thank you @Frederick Colbourne for your insightful explanations and advice...

Kenneth, thanks for these graphics.