<p>I downloaded an edmo dataset of 1 ensemble of the cera-20c model. I want to convert these data, which are in [m], to mm/month. Further specifications: 0.125/0.125 grid, -29/30/-30/31 area. Example of the data (see picture) of total precipitation January 1980:</p>

<p><a href="https://i.sstatic.net/FdqHM.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/FdqHM.png" alt="the month January of 1980 of the dataset"></a></p>

<p>My method: Taking the average of these numbers multiplying by 31 (days in January) and 1000 (from m to mm) gives me 299 mm for January. But this does not seem right. It seems overestimated. I hope you can help me with the right answer. I read something about multiplying by the scale factor and adding the add_offset. But the scale factor is so small (10E-7) that all numbers approximately similar.  </p>

<p>Thanks a lot in advance for any ideas.
Louwrens Timmer</p>

CC BY-SA 4.0
2019-01-14T01:21:04.183Z
Retrieving the necessary values should be straightforward, but a few additional details are needed to answer this. Presumably these are the values for some subset of the lat/lon grid? Also, you mention the scale factor, but what is the add_offset? This is a pretty common method of storing meteorological data, but is there any other documentation listed describing the scaling or data structure?
dplmmr
CC BY-SA 4.0
2019-01-14T03:31:13.193Z
May be helpful to both future searchers and to anyone trying to help with the question if you provide a direct link to the dataset you're using to aid with clarity? :-)
JeopardyTempest
CC BY-SA 4.0
2019-01-14T08:29:39.620Z
@JeopardyTempest How can I add in the dataset in the attachment?
L. Timmer
CC BY-SA 4.0
2019-01-14T08:37:00.270Z
A more or less similar question was asked earlier: https://earthscience.stackexchange.com/questions/7055/era-interim-how-to-handle-total-precipitation
L. Timmer
CC BY-SA 4.0
2019-01-14T09:29:16.367Z
Sorry, poor wording on my part... I meant to link to the site you get the dataset from, not the actual dataset itself (the word "direct" thus wasn't a good choice!)  I wasn't as familiar with the acronym CERA-20C as I was with the bit more generic ERA, so it seemed some exotic format (not that I've done much with either).  If there happens to be useful documentation page on the ECMWF page, that'd always help, but certainly already cleared it up some for me, thanks :)
JeopardyTempest
CC BY-SA 4.0
2019-01-14T09:35:04.077Z
@JeopardyTempest https://www.ecmwf.int/en/forecasts/datasets/archive-datasets/reanalysis-datasets/cera-20c this is the link to the documentation page of the CERA-20C.
L. Timmer
CC BY-SA 4.0
2019-01-14T09:35:57.327Z
Thanks a lot, helpful for all trying to offer input :-)
JeopardyTempest
CC BY-SA 4.0
2019-01-14T11:40:46.457Z
@dplmmr The dataset is downloaded as a netcdf file. But I extracted the data in an excel file format to see how the data is structured and to make the first calculations. Further describing documentation: dimensions:
    longitude = 9;
    latitude = 9;
    time = UNLIMITED
  variables:
    double tp(time=12, latitude=9, longitude=9);
      :scale_factor = 2.0893531189079316E-7; // double
      :add_offset = 0.006947661364936322; // double
      :_FillValue = -32767S; // short
      :missing_value = -32767S; // short
      :units = "m";
      :long_name = "Total precipitation";
L. Timmer
CC BY-SA 4.0
2019-01-14T20:41:36.870Z
Following that, the listed values are multiplied by the scale factor, then the offset value is added. But as you allude to, this gives similar quantities - only varying at the 6th decimal place after converting to mm. Multiplying those values by 31 gives a lower (but still large and suspiciously unvarying) ~215 mm.
Computationally that makes sense, but it's as far as I can get without finding more specifics on other details/steps for this dataset. Unless there are more details specific to it, the question seems covered by the one you linked (which I missed, searching only for CERA questions).
dplmmr
CC BY-SA 4.0
2019-01-15T08:47:25.617Z
@dplmmr Yes that was what I also found out after researching the web for scale factor and offset. To my knowledge there are no more details or steps. all information has been posted above. However, I have been struggling with this dataset for quite a while now. And I need reanalysis rainfall data for the period 1900-2010. Do you guys have any advice? Try ERA-20C or another database?
L. Timmer
CC BY-SA 4.0
2019-01-15T09:00:11.223Z
@dplmmr The problem with the scale factor is indeed that the number only varies at 6th decimal. But using this method every month gets the same amount of rainfall...
L. Timmer
CC BY-SA 4.0
2019-01-15T16:54:49.757Z
I don't have personal familiarity with the European reanalyses, I've only directly worked with forecast and reanalysis datasets maintained by NOAA in the US so I'm a bit more familiar with their files and documentation. Unfortunately that's not possible to check at the moment as the archival websites are inoperative during the US government shutdown.
dplmmr
CC BY-SA 4.0
2019-01-20T16:56:53.947Z
I solved the problem. The method of multiplying the average of the grid by 31 (for days) and 1000 (m to mm conversion was the correct. However these values were only one of the ten ensembles the model produced. It was probably a very wet year and/or a extreme model 'run'. Thanks again everyone
L. Timmer
<meteorology><atmosphere><precipitation><climate-models><reanalysis>
How can I convert a CERA-20C total precipitation dataset of "monthly means of daily means' (edmo) to mm/month?
L. Timmer
# How can I convert a CERA-20C total precipitation dataset of "monthly means of daily means' (edmo) to mm/month?

(Asked by: username_0 on 2019-01-11)

I downloaded an edmo dataset of 1 ensemble of the cera-20c model. I want to convert these data, which are in [m], to mm/month. Further specifications: 0.125/0.125 grid, -29/30/-30/31 area. Example of the data (see picture) of total precipitation January 1980:

[![the month January of 1980 of the dataset](https://i.sstatic.net/FdqHM.png)](https://i.sstatic.net/FdqHM.png)

My method: Taking the average of these numbers multiplying by 31 (days in January) and 1000 (from m to mm) gives me 299 mm for January. But this does not seem right. It seems overestimated. I hope you can help me with the right answer. I read something about multiplying by the scale factor and adding the add\_offset. But the scale factor is so small (10E-7) that all numbers approximately similar.

Thanks a lot in advance for any ideas.
Louwrens username_0

**Tags:** meteorology, atmosphere, precipitation, climate-models, reanalysis

> **Comments:**
> **username_1**: Retrieving the necessary values should be straightforward, but a few additional details are needed to answer this. Presumably these are the values for some subset of the lat/lon grid? Also, you mention the scale factor, but what is the add_offset? This is a pretty common method of storing meteorological data, but is there any other documentation listed describing the scaling or data structure?  
> **username_2**: May be helpful to both future searchers and to anyone trying to help with the question if you provide a direct link to the dataset you're using to aid with clarity? :-)  
> **username_0**: @username_2 How can I add in the dataset in the attachment?  
> **username_0**: A more or less similar question was asked earlier: https://earthscience.stackexchange.com/questions/7055/era-interim-how-to-handle-total-precipitation  
> **username_2**: Sorry, poor wording on my part... I meant to link to the site you get the dataset from, not the actual dataset itself (the word "direct" thus wasn't a good choice!)  I wasn't as familiar with the acronym CERA-20C as I was with the bit more generic ERA, so it seemed some exotic format (not that I've done much with either).  If there happens to be useful documentation page on the ECMWF page, that'd always help, but certainly already cleared it up some for me, thanks :)  
> **username_0**: @username_2 https://www.ecmwf.int/en/forecasts/datasets/archive-datasets/reanalysis-datasets/cera-20c this is the link to the documentation page of the CERA-20C.  
> **username_2**: Thanks a lot, helpful for all trying to offer input :-)  
> **username_0**: @username_1 The dataset is downloaded as a netcdf file. But I extracted the data in an excel file format to see how the data is structured and to make the first calculations. Further describing documentation: dimensions:     longitude = 9;     latitude = 9;     time = UNLIMITED   variables:     double tp(time=12, latitude=9, longitude=9);       :scale_factor = 2.0893531189079316E-7; // double       :add_offset = 0.006947661364936322; // double       :_FillValue = -32767S; // short       :missing_value = -32767S; // short       :units = "m";       :long_name = "Total precipitation";  
> **username_1**: Following that, the listed values are multiplied by the scale factor, then the offset value is added. But as you allude to, this gives similar quantities - only varying at the 6th decimal place after converting to mm. Multiplying those values by 31 gives a lower (but still large and suspiciously unvarying) ~215 mm. Computationally that makes sense, but it's as far as I can get without finding more specifics on other details/steps for this dataset. Unless there are more details specific to it, the question seems covered by the one you linked (which I missed, searching only for CERA questions).  
> **username_0**: @username_1 Yes that was what I also found out after researching the web for scale factor and offset. To my knowledge there are no more details or steps. all information has been posted above. However, I have been struggling with this dataset for quite a while now. And I need reanalysis rainfall data for the period 1900-2010. Do you guys have any advice? Try ERA-20C or another database?  
> **username_0**: @username_1 The problem with the scale factor is indeed that the number only varies at 6th decimal. But using this method every month gets the same amount of rainfall...  
> **username_1**: I don't have personal familiarity with the European reanalyses, I've only directly worked with forecast and reanalysis datasets maintained by NOAA in the US so I'm a bit more familiar with their files and documentation. Unfortunately that's not possible to check at the moment as the archival websites are inoperative during the US government shutdown.  
> **username_0**: I solved the problem. The method of multiplying the average of the grid by 31 (for days) and 1000 (m to mm conversion was the correct. However these values were only one of the ten ensembles the model produced. It was probably a very wet year and/or a extreme model 'run'. Thanks again everyone  

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## 0 answers

