<p>The most common period to use is 30-years, which comes from the idea of <a href="https://en.wikipedia.org/wiki/Climatological_normal" rel="noreferrer">climate normals</a> used in NWP.  Using only 10 years even global mean temperature will see the influence of a single large El Nino or prolonged La Nina events, which probably isn't what you're after.  If you were writing a paper that used 30-years means, the reviewer probably wouldn't question it; if you used 20-year means they might ask you to justify it; if you used 10-year means you'd probably be criticized for it.</p>
<p>Regardless of what period you pick, it's always a good idea to also calculate confidence intervals for your means, which can give you a sanity check on whether differences between periods are really notable.  That's sort of one step short of doing formal statistical hypothesis testing.</p>
<p>From the IPCC AR6 glossary, for reference:</p>
<blockquote>
<p><em>Climate</em>: Climate in a narrow sense is usually defined as the average weather, or more rigorously, as the statistical description in terms of the mean and variability of relevant quantities over a period of time ranging from months to thousands or millions of years. The classical period for averaging these variables is <strong>30 years</strong>, as defined by the World Meteorological Organization (WMO). The relevant quantities are most often surface variables such as temperature, precipitation and wind. Climate in a wider sense is the state, including a statistical description, of the climate system.</p>
</blockquote>
<p>and,</p>
<blockquote>
<p><em>Global warming</em>: Global warming refers to the increase in global surface temperature relative to a baseline reference period, averaging over a period sufficient to remove interannual variations (e.g., <strong>20 or 30 years</strong>). A common choice for the baseline is 1850-1900 (the earliest period of reliable observations with sufficient geographic coverage), with more modern baselines used depending upon the application.</p>
</blockquote>

CC BY-SA 4.0
2022-06-28T09:15:17.930Z
2022-06-28T09:15:17.930Z
Deditos
<p>I would like to show the change in temperatures since 1960 until today. I have thought about creating two time blocks, e.g. from 1960-1970 and from 2010-2020! Then I want to average the data of these two time blocks (i.e. the data from 1960-1970 and from 2010-2020) and then calculate the difference between the two time blocks. Now I wonder if there are rules in the geosciences about how large the time periods should be, because I simply assumed the 10 years. The question for me is what period can be assumed as the minimum to prevent extreme years (either extremely hot or extremely cold) from having a major influence?</p>

CC BY-SA 4.0
2022-06-27T20:52:44.693Z
Generally climate sets use 30 year averages in atmospheric sciences to reduce the impact of extreme years/shortterm fluctuations.  That's the standard the NWS uses to calculate longterm means, updating each 10 years.
JeopardyTempest
CC BY-SA 4.0
2022-06-28T08:18:30.147Z
@JeopardyTempest thank you very much!
Weiss
CC BY-SA 4.0
2022-06-28T09:37:52.937Z
Does your title refer to Milankovich cycles? If that is the case I'd like to give a warning. Whatever you will find it won't  show any trend induced by the periodic changes of earth relative to the sun.
Joscha Fregin
CC BY-SA 4.0
2022-06-28T09:39:06.947Z
Oh I think it is called this way! Is there a nouther way to call this type of time seperated analysis!
Weiss
<climate-change><models>
Milancovich analysis
Weiss
# Milancovich analysis

(Asked by: username_0 on 2022-06-27)

I would like to show the change in temperatures since 1960 until today. I have thought about creating two time blocks, e.g. from 1960-1970 and from 2010-2020! Then I want to average the data of these two time blocks (i.e. the data from 1960-1970 and from 2010-2020) and then calculate the difference between the two time blocks. Now I wonder if there are rules in the geosciences about how large the time periods should be, because I simply assumed the 10 years. The question for me is what period can be assumed as the minimum to prevent extreme years (either extremely hot or extremely cold) from having a major influence?

**Tags:** climate-change, models

> **Comments:**
> **username_1**: Generally climate sets use 30 year averages in atmospheric sciences to reduce the impact of extreme years/shortterm fluctuations.  That's the standard the NWS uses to calculate longterm means, updating each 10 years.  
> **username_0**: @username_1 thank you very much!  
> **username_2**: Does your title refer to Milankovich cycles? If that is the case I'd like to give a warning. Whatever you will find it won't  show any trend induced by the periodic changes of earth relative to the sun.  
> **username_0**: Oh I think it is called this way! Is there a nouther way to call this type of time seperated analysis!  

---

## 1 answers

### Answer by username_3 on 2022-06-28. Score: 6 | Accepted answer

The most common period to use is 30-years, which comes from the idea of [climate normals](https://en.wikipedia.org/wiki/Climatological_normal) used in NWP. Using only 10 years even global mean temperature will see the influence of a single large El Nino or prolonged La Nina events, which probably isn't what you're after. If you were writing a paper that used 30-years means, the reviewer probably wouldn't question it; if you used 20-year means they might ask you to justify it; if you used 10-year means you'd probably be criticized for it.

Regardless of what period you pick, it's always a good idea to also calculate confidence intervals for your means, which can give you a sanity check on whether differences between periods are really notable. That's sort of one step short of doing formal statistical hypothesis testing.

From the IPCC AR6 glossary, for reference:

> *Climate*: Climate in a narrow sense is usually defined as the average weather, or more rigorously, as the statistical description in terms of the mean and variability of relevant quantities over a period of time ranging from months to thousands or millions of years. The classical period for averaging these variables is **30 years**, as defined by the World Meteorological Organization (WMO). The relevant quantities are most often surface variables such as temperature, precipitation and wind. Climate in a wider sense is the state, including a statistical description, of the climate system.

and,

> *Global warming*: Global warming refers to the increase in global surface temperature relative to a baseline reference period, averaging over a period sufficient to remove interannual variations (e.g., **20 or 30 years**). A common choice for the baseline is 1850-1900 (the earliest period of reliable observations with sufficient geographic coverage), with more modern baselines used depending upon the application.


---

