data:solar_satire

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data:solar_satire [2016/08/09 14:16]
jypeter Added more details and python code to deal with the time axis 		data:solar_satire [2016/08/09 14:42]
jypeter python example to compute weighted time averages
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   * 14C data for the last 9000 years (6754.5 BC to December 2015)   * 14C data for the last 9000 years (6754.5 BC to December 2015)
   * 10Be data for the years 885 CE to December 2015   * 10Be data for the years 885 CE to December 2015
 +
 +  * In both cases, the data is daily, starting on January 1st 1850, and yearly before
  
 The **14C-based data set** scaled to the CMIP6 historical forcing is the **recommended forcing for the PMIP4-CMIP6 //tier-1// past1000 experiment**. The **14C-based data set** scaled to the CMIP6 historical forcing is the **recommended forcing for the PMIP4-CMIP6 //tier-1// past1000 experiment**.
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 >>> year_50_idx, year[year_50_idx] >>> year_50_idx, year[year_50_idx]
 (6805, 50.5)</code> (6805, 50.5)</code>
 +  * You can use the following if you want to do a weighted average over the time axis
 +    * <code python>>>> time_weights = np.ones((69235,))
 +>>> np.argwhere(year == 1850)
 +array([[8605]])
 +>>> tt[8605]
 +1850.0
 +>>> year[8604]
 +1849.5
 +# Note: it would be nicer to assign 366 to leap years below...
 +>>> time_weights[:8605] = 365 # Assign 365 to all time steps up to (but excluding) step 8605
 +>>> time_weights[8600:8620]
 +array([ 365.,  365.,  365.,  365.,  365.,    1.,    1.,    1.,    1.,
 +          1.,    1.,    1.,    1.,    1.,    1.,    1.,    1.,    1.,
 +          1.,    1.])
 +>>> ssi_average_weighted = np.average(ssi, axis=0, weights=time_weights)
 +</code>
  
 ===== References ===== ===== References =====
  • data/solar_satire.txt
  • Last modified: 2019/11/18 10:58
  • by jypeter