<p>My professor gives the solution, as we can see at the site were the climatic variables came from <a href="http://www.worldclim.org/formats1" rel="nofollow noreferrer">http://www.worldclim.org/formats1</a>: </p>

<blockquote>
  <p>Please note that the temperature data are in °C * 10. This means that a value of 231 represents 23.1 °C. This does lead to some confusion, but it allows for much reduced file sizes which is important as for many downloading large files remains difficult. The unit used for the precipitation data is mm (millimeter).</p>
</blockquote>

<p>(Edited in by Gerrit): storing (climate) data with offsets and scale factors to reduce file size is common practice, as scaled integers can easily be less than half the size of floats.  When data are stored in standard formats sch as NetCDF or HDF-5, there is probably a variable attribute documenting this.  When data are stored in a homegrown format, check the documentation carefully for any mention of offsets and scale factors that need to be applied.</p>

CC BY-SA 3.0
2017-05-05T11:31:10.230Z
Finally somebody that can read metadata! Oh, the wonders of knowing how to read the metadata in a data file before overreacting!
arkaia
CC BY-SA 3.0
2017-05-05T12:22:12.730Z
@aretxabaleta [Déjà vu](https://earthscience.stackexchange.com/a/4657/94)...
Pont
CC BY-SA 3.0
2017-05-04T13:36:35.880Z
2017-05-05T11:27:29.440Z
2017-05-05T11:27:29.440Z
Emanuel
<p>I'm in doubt of some values for future scenarios of climate change that were downloaded from <a href="http://www.worldclim.org/version2" rel="nofollow noreferrer">http://www.worldclim.org/version2</a>. For example, the NCAR circulation model for <code>bio_5</code> variable at optimistic scenario (Max Temperature of Warmest Month) to 2050 is 335.33. </p>

<p>Other similar calculations with other scenarios, circulation models and another future year, returns values ranging from 55 to 103 for the max temperature of warmest month. This appears wrong. Am I reading the data correctly?</p>

CC BY-SA 3.0
2017-05-04T03:14:45.587Z
sure would be nice if you cited or linked to the source of information you are intrepreting.
f.thorpe
CC BY-SA 3.0
2017-05-04T04:17:01.190Z
Those numbers are impossible and I'm quite sure you're reading the data wrong.    Without source data, as @farrenthorpe points out, your question is meaningless.
userLTK
CC BY-SA 3.0
2017-05-04T06:21:09.390Z
Also, 335.33 as a temperature is far too specific.   No climate model is likely to predict temperature to 1/100th of a degree C for a specific year.   335.33 is likely a measurement of some kind, not a temperature prediction.
userLTK
CC BY-SA 3.0
2017-05-04T10:11:54.210Z
@userLTK I suspect that the OP is quoting raw numbers from CMIP5-like outputs, in which case the precision is just because they're stored as 32-bit floats.  They're also possibly quoting an individual daily max temperature from some grid box on some day, rather than a max monthly mean, so values > 50ºC are possible.  For example, a random dip into the CMIP5 data gives me 57ºC for CCSM3 and 95ºC for HadCM3 under RCP4.5.
Deditos
CC BY-SA 3.0
2017-05-05T10:54:14.263Z
@kingledion I think the question can be useful.  It is common for scientific values to be stored as scaled integers, in case of NetCDF with `scale_factor` defined as a variable attribute.  Emanuel is not the first and won't be the last with this problem.
gerrit
CC BY-SA 3.0
2017-05-05T11:10:53.507Z
@gerrit If you think the information is useful, I would suggest some edits to the question to make it more clear.
kingledion
CC BY-SA 3.0
2017-05-05T11:30:48.923Z
Oh, the wonders of knowing how to read the metadata in a data file before overreacting!
arkaia
CC BY-SA 3.0
2017-05-07T07:12:54.563Z
Voting to leave open, in the hope of an answer explaining the common problems in reading this type of data. @emanuel, it would be good if you could update to give more info on exactly where and how you are retrieving these high values.
Semidiurnal Simon
<climate-change><climate-models><data-formats>
Why do values stored in data files, such as climate model output, appear to be high?
Emanuel
# Why do values stored in data files, such as climate model output, appear to be high?

(Asked by: username_0 on 2017-05-03)

I'm in doubt of some values for future scenarios of climate change that were downloaded from <http://www.worldclim.org/version2>. For example, the NCAR circulation model for `bio_5` variable at optimistic scenario (Max Temperature of Warmest Month) to 2050 is 335.33.

Other similar calculations with other scenarios, circulation models and another future year, returns values ranging from 55 to 103 for the max temperature of warmest month. This appears wrong. Am I reading the data correctly?

**Tags:** climate-change, climate-models, data-formats

> **Comments:**
> **username_1**: sure would be nice if you cited or linked to the source of information you are intrepreting.  
> **username_2**: Those numbers are impossible and I'm quite sure you're reading the data wrong.    Without source data, as @farrenthorpe points out, your question is meaningless.  
> **username_2**: Also, 335.33 as a temperature is far too specific.   No climate model is likely to predict temperature to 1/100th of a degree C for a specific year.   335.33 is likely a measurement of some kind, not a temperature prediction.  
> **username_3**: @username_2 I suspect that the OP is quoting raw numbers from CMIP5-like outputs, in which case the precision is just because they're stored as 32-bit floats.  They're also possibly quoting an individual daily max temperature from some grid box on some day, rather than a max monthly mean, so values > 50ºC are possible.  For example, a random dip into the CMIP5 data gives me 57ºC for CCSM3 and 95ºC for HadCM3 under RCP4.5.  
> **username_4**: @username_5 I think the question can be useful.  It is common for scientific values to be stored as scaled integers, in case of NetCDF with `scale_factor` defined as a variable attribute.  username_0 is not the first and won't be the last with this problem.  
> **username_5**: @username_4 If you think the information is useful, I would suggest some edits to the question to make it more clear.  
> **username_6**: Oh, the wonders of knowing how to read the metadata in a data file before overreacting!  
> **username_7**: Voting to leave open, in the hope of an answer explaining the common problems in reading this type of data. @username_0, it would be good if you could update to give more info on exactly where and how you are retrieving these high values.  

---

## 1 answers

### Answer by username_0 on 2017-05-04. Score: 3 | Accepted answer

My professor gives the solution, as we can see at the site were the climatic variables came from <http://www.worldclim.org/formats1>:

> Please note that the temperature data are in °C \* 10. This means that a value of 231 represents 23.1 °C. This does lead to some confusion, but it allows for much reduced file sizes which is important as for many downloading large files remains difficult. The unit used for the precipitation data is mm (millimeter).

(Edited in by username_4): storing (climate) data with offsets and scale factors to reduce file size is common practice, as scaled integers can easily be less than half the size of floats. When data are stored in standard formats sch as NetCDF or HDF-5, there is probably a variable attribute documenting this. When data are stored in a homegrown format, check the documentation carefully for any mention of offsets and scale factors that need to be applied.

> **Comments:**
> **username_6**: Finally somebody that can read metadata! Oh, the wonders of knowing how to read the metadata in a data file before overreacting!  
> **username_8**: @aretxabaleta [Déjà vu](https://earthscience.stackexchange.com/a/4657/94)...  

---

