Quality check procedure

last update: Nov. 2015

    Quality Check - Temporal aggregation - FAQ - References

Prior to the comparison of a dataset to reference data (2)(5)(6), you need to be sure that these reference data are of sufficiently good quality to serve as reference.
This page aims at giving a large insight of the procedure adopted by MINES ParisTech and Transvalor in term of quality check of ground station measurements. In particular, the first section is dedicated to the quality control steps applied onto the 1 minute Baseline Surface Radiation Network station data (3)(4).

Quality Check (full description for sub-hourly values)

The quality check procedure is derived from the one published in the deliverable 3.2 on data harmonization provided within the framework of the European FP7 ENDORSE project. The table available page 60, also published in the poster(1), summarizes the quality check procedure for all the meteorological components. All the differences between our implementation and this document are highlighted in orange.

NB: This quality check procedure described below is for sub-hourly measurements, which is typically the procedure adopted onto the 1 min BSRN station data. If you need to handle ground measurements with other time steps (such as hourly, or daily values), you need to switch to the adequate column in the above p60 table.

Let's define GHIGRD, DHIGRD and BNIGRD respectively the sub-hourly GHI, DHI and BNI data for the ground station. SZA is the Solar Zénithal angle and SEA the Solar Elevation angle (please note that SEA=90°-SZA). Let's name GHITOA and BNITOA respectively the Global and the Direct component at the Top of Atmosphere.

Step Quality Check Equation
Step 1 - Night
  • Night values are set to 0
  • Sunrise and sunset: below 3° of sun elevation, if a value is negative, set it to 0
  • for SEA=0°, GHIGRD=0
  • for SEA≤3° & GHIGRD<0, GHIGRD=0
Step 2 - Missing values
  • Set the missing values to NaN
if GHIGRD is missing, GHIGRD=NaN
Step 3 - Outliers
  • Discard the values which exceed "Extremely Rare Limits (ERL)" and "Physical Possible Limits (PPL)" criteria.


NB: the maximum step for two following GHIGRD measures of 1000 Wm-2 hasn't been implemented.


  • ERL: 0.03 GHITOA < GHIGRD < min(1.2 BNITOA,1.5 BNITOA cos(SZA)1.2+100)
  • PPL: 0.03 GHITOA < GHIGRD < 1.2 BNITOA cos(SZA)1.2+50


  • PPL: 0 < BNIGRD < 0.95BNITOAcos(SZA)0.2+30


  • ERL: 0.03 GHITOA < DHIGRD < min(0.8 BNITOA,0.95 BNITOA cos(SZA)1.2+50)
  • PPL: 0.03 GHITOA < DHIGRD < 0.75 BNITOA cos(SZA)1.2+30
Step 4 - Consistency
  • If the ground station provides several components of radiation, apply the consistency checks (cross-comparisons)


NB: All the GHIGRD below 10 W/m² and all the BHIGRD below 4 W/m² are discarded(1) (2).

For 2 components (GHIGRD and DHIGRD)

For GHIGRD > 50 Wm-2

  • for SZA<75°, DHIGRD/GHIGRD < 1.05
  • for 75°<SZA<93°, DHIGRD/GHIGRD < 1.10

For 3 components (GHIGRD, DHIGRD and BNIGRD): compute first BHIGRD* from BNIGRD, and then compute GHIGRD*=BHIGRD*+DHIGRD and compare it to GHIGRD.

 For GHIGRD*> 50 Wm-2

  • for SZA<75°, DHIGRD/GHIGRD* ≤ 0.08
  • for 75°<SZA<93°, DHIGRD/GHIGRD* ≤ 0.15

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Temporal aggregation procedure

The below temporal aggregation procedure corresponds to the comparison of a HelioClim-3 (HC3) dataset against 1 min ground station measurements (typically BSRN).

Time step Steps
  1. Apply the Quality Check procedure (see above section)
from 1 to 15 min
  1. Generate the 15 min data if at least 85% of the 1 min slots are available, by applying an "intelligente interpolation" which takes into account the sun position at each instant.
15 MIN
  1. Set 15 min HC3 to NaN where 15 min GRD is NaN, and reverse.
  2. Compute the stats at 15 min
from 15 min to hourly data
  1. From now on, always perform partial sums. Generate hourly values by summing up the 15 min irradiation slots if at least 75% of the slots are available.
  1. Compute the stats at the hourly time step
from hourly to daily values
  1. Generate the partial daily values by summing up the 15 min values if at least 65% of the 15 min values are available.
  1. Compute the stats at the daily time step
from daily to monthly data
  1. Generate the partial monthly values by summing up the 15 min values if at least 50% of the of the 15 min values are available.
  1. Compute the stats at the monthly time step

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Discussion: If the time step of your ground station measurements or of your estimation is different, this procedure needs to be adapted.
For instance, if we collected hourly in-situ measurements to carry out a comparison with HC3, we must generate hourly HC3 values from the 15 min HC3 values using an intelligent interpolation like in step 2.
Another example: the first HC3 Similarity forecast datasets were generated with a hourly time step. We had to generate the hourly BSRN values from the 1 min data by using once more the step 2, if at least 85% of the 1 min slots are available in the hour.
Then follow the previous steps from step 7 to the end.


I_ "What are 'partial sums'? Why did you opt for partial sums instead of averages?"

If you apply any kind of averaging on measurements, you introduce an information which doesn't come from a real measurement. That is why we decided to avoid the distorsion of the values by summing up only the available values. This leads to partial sums for the day or the month. This means also that the resulting value is not representive of an actual daily or monthly value.

II_ "How did you choose the thresholds in your temporal aggregation procedure?"

Originally, we didn't set any threshold, and created aggregated values even if only one slot was available. Even if partial sums are not representative of, for instance, a daily or a monthly value, we decided that at least 75% of the 15 min slots were necessary to generate the hourly value, and 75% of the 15 min data to generate the daily or monthly value.

NB: discussion for the hour from 15 min slots: when the sun is rising, you could have less than 4 valid 15 min slots to generate the hourly value. As a consequence, the 75% threshold accepts 1 available slot over 1 valid slot, 2 over 2, 3 over 3 and 4 over 4, plus 3 over 4 valid slots. The first discarded is 2 available over 3 valid slots.

III_ "Why do you sum up 15 min slots to generate the daily and monthly values?"

After several tests trying to sum up the hourly values to generate the daily value, we realized that two many days were discarded. Summing up the 15 min slots returns more valid days for the comparisons.

IV_ "Why did you discard all the GHIGRD values below 50 Wm-2?"

This decision was motivated by the fact that most instruments present a high uncertainty in low radiation conditions. Moreover, as the consistency checks are not applied for values below this threshold, we finally decided to discard the values.

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(In alphabetic order)

(1) Espinar B., P. Blanc, L. Wald, C. Hoyer-Klick, M. Schroedter-Homscheidt, T. Wanderer, 2012. "Controlling the quality of measurements of meteorological variables and solar radiation. From sub-hourly to monthly average time periods", European Geosciences Union 2012, Vienna (Austria) 22–27 April 2012. Poster

(2) ISO Guide to the Expression of Uncertainty in Measurement: first edition, International Organization for Standardization, Geneva, Switzerland, 1995.

(3) Ohmura A., E. G. Dutton, B. Forgan, C. Fröhlich, H. Gilgen, H. Hegner, A. Heimo, G. König-Langlo, B. McArthur, G. Müller, R. Philipona, R. Pinker, C. H. Whitlock, K. Dehne, and . Wild, 1998. "Baseline Surface Radiation Network (BSRN/WCRP): New Precision Radiometry for Climate Research", Bulletin of the American Meteorological Society, vol. 79, N°10, pp. 2115-2136. Article

Content: Table 3 p 2119 gives the uncertainty on the GHI, DHI and BHI components measured by the BSRN stations: +/-5 W/m² for the GHI and the DHI components, and +/-2 W/m² for the BHI. This is why a threshold of respectively 10 W/m² and 4 W/m² is applied on the measurements in the adopted quality check procedure.

(4) Roesch, A., Wild, M., Ohmura, A., Dutton, E.G., Long, C.N., and Zhang, T.: Assessment of BSRN radiation records for the computation of monthly means, Atmos. Meas. Tech., 4, 339–354, doi:10.5194/amt-4-339-2011, 2011. Corrigendum, Atmos. Meas. Tech., 4, 973-973, doi:10.5194/amt-4-973-2011, 2011.

(5) WMO, 1981. Technical Note N° 172, WMO-No. 554, World Meteorological Organization, Geneva, Switzerland, pp. 121-123.

(6) WMO: Guide to meteorological instruments and methods of observation, World Meteorological Organization, WMO - No 8, 7th Edn., Geneva, Switzerland, 2008.

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