In this document
You'll learn how to run the Solar radiation data QC tool (requires time reference checks to be completed first): opening it via Quality/Solar radiation, running automatic checks that validate and cross-reference solar parameters using test groups (close-proximity instrument comparisons configured in the Metadata editor), and examining results through the Heatmap flag plot, Time series flag plot, Consistency plots (available with 3+ solar radiation parameters), and the Quality control summary.
Prerequisites
An active Solargis Analyst account.
Installed an Analyst desktop application.
One or more datasets with available solar data in the Solargis Analyst application.
Finished time reference quality control check.
Solar radiation data QC
Solar radiation data quality check (QC) must be performed to ensure the integrity and reliability of the measured solar irradiance data. Without these checks, issues such as sensor faults, shading, miscalibration, or data anomalies may remain undetected, leading to misleading results in downstream energy yield assessments and performance analyses. This quality control step ensures the dataset accurately reflects site conditions and meets data validation standards before further processing.
Key points to remember:
Correct time reference checks must be done first to ensure there are no time shifts left in the dataset.
This check utilises test groups usually defined in the Metadata editor, but you can still create and edit them in the solar radiation data check window.
The solar radiation data QC may take some time depending on the size of the tested dataset.
A flag column for each parameter will be added to the dataset upon this check to store the flags.
Flags are numbered, each representing different data issue, and these numbers are added to the flag columns when flagging the data. Zooming the chart also considers the selected height as well. You can use this advantage when selecting data range with low values which would otherwise appear close to zero in the chart.
Solar radiation data QC tool
You can open the solar radiation data check tool from the main menu via Quality/Solar radiation or by using the 
quick access icon located below the main menu. The window interface offers the following (after the check has been performed):
Run automatic checks: Execute the solar radiation data quality checks. The results will be displayed in the plot section and suspicious data flagged.
Visualization and summary tabs: Toggle between different visualizations to examine the flagged data or view the quality control summary.
Data visualization: Provides visual insights into where the data inconsistencies happen and what the detected issue was. The flags legend is located above the charts.
Test groups: These are used to group measurements from instruments in close proximity where values are expected to correlate. Test groups and how to work with them are described here.
Plot settings and parameter selector: Select which parameter to display for examination and set how to visualize the data.
Executing the solar radiation data quality check
When you open the solar radiation data QC tool, its interface may be empty, containing no visualizations. You must run the tests first to display the test results in the interface. To do this, click the “Run” button at the bottom-right of the window.
Important: This test will add new flag columns to the dataset for each solar parameter. These columns serve to add flags to particular values in the dataset.
Test groups
The solar radiation data QC works with test groups that help it to compare and evaluate related parameters for better accuracy. We recommend ensuring that the test groups are configured properly before proceeding to solar radiation checks.
Test groups are usually created automatically in the metadata editor, but you can edit and change them here in the solar radiation QC tool. You can learn how to work with the test groups here.
Analyst maintains the default test groups automatically:
When the primary parameter of a group is a GTI parameter, a default supporting GHI parameter is added to the group automatically.
Empty test groups are detected and removed.
If the same parameter is primary in two groups, it stays primary in the first group only.
Automatic tests and settings
The solar radiation QC runs a set of automatic tests against every solar parameter in each test group. Each test corresponds to a flag, so the flag you see in the heatmap tells you which test caught the value. The full flag list is available in the Application settings article.
Flags that the automatic tests detect are listed in the table.
Flag | Test | What it detects |
|---|---|---|
-1 | Invalid values | Records that are not valid numeric measurements. |
0 | Sun below horizon | Night-time records, where irradiance is expected to be zero. Shown in grey rather than treated as an error. |
2 | Below physical minimum | Values falling under the acceptable minimum for the parameter type. |
3 | Above physical maximum | Values exceeding the physically plausible maximum for the parameter type. |
4 | Consecutive static values | Runs of near-identical values that indicate a frozen sensor or a stuck data logger. |
5 | Consistency | Values where the physical relationship between irradiance components breaks down — GHI, DNI and DIF against each other, and GTI fix against GHI, DNI and DIF. |
6 | Two-component tests | Pairwise checks between two parameters, including GHI against DIF and GHI against GTI. |
22 | Tracker issue | Records affected by a sun-tracking mechanism that is not operating correctly. |
24 | Logger issue | Records affected by a data logger that is not recording or transmitting correctly — for example corrupted, misaligned or incomplete entries caused by logger or communication faults. |
Testing methodology
Two methodologies are available, selected in the application's Quality control settings:
Solargis (default) — the more precise option, supporting the full test set and all solar parameter types. Solargis derived this methodology from BSRN and extended it.
BSRN — supports GHI, DNI and DIF only, with lower minimum limits.
Each parameter type has a configurable acceptable minimum, and the defaults differ by methodology:
Parameter | Solargis minimum | BSRN minimum |
|---|---|---|
GHI | 0.0 | -4 |
DIF | 0.0 | -4 |
DNI | -2.5 | -4 |
GTI | 0.0 | 0 |
ALB | 0.02 | 0.02 |
RHI | 0 | 0 |
Important: New tests are added to the Solargis methodology only. If you select BSRN, the newer tests and the additional parameter types are not applied. We recommend keeping the Solargis methodology unless you specifically need BSRN-comparable results.
Dataset requirements for automatic tests
The automatic QC will not run unless the dataset meets these conditions:
Units — solar radiation parameters must be in W/m² or Wh/m².
Time step — hourly or sub-hourly data only. Coarser time steps are not supported.
No duplicate timestamps — remove duplicated records before running the check.
Measured data — the check does not apply to model-only or TMY datasets.
Time reference — the QC assumes the dataset is already shifted to UTC±0. If no time reference check status is present, a warning appears when you open the window; you can acknowledge it and continue, but we strongly recommend completing the time reference check first.
Advanced settings
Open the solar radiation QC settings using the 
icon in the window. Here you can configure the methodology, choose which tests to run, and set the limits applied during the check.
Test selection: Enable or disable individual tests with a checkbox in the List of tests.
Acceptable minima: Set the minimum per parameter type (GHI, DIF, DNI, GTI, ALB, RHI).
Logger issues: Specify the acceptable range of consecutive static values.
Exclude periods: Exclude defined periods from consistency testing for GHI, DNI and DIF. This is useful when something happened to the instrument for a known stretch of time, for example if it was physically moved. You can add, remove, or clear all excluded periods.
Copy flags (ALB): When the dataset contains an ALB parameter, copy flags from the source parameters to the calculated ones. The option is disabled when no ALB column is present.
Flags to update after QC: Choose which existing flags the automatic QC may overwrite. By default, all flags with a value below 7 are overwritten, which preserves manually assigned flags with higher values.
Examining the solar radiation data QC results
You can examine the results and view the flags added to the dataset once the system finishes the checks. There are several visualizations at hand to help you analyze the datasets and flagged data, and you can navigate them using the top navigation menu:
Heatmap flag plot: View the flags in a timeline chart. The correct data are displayed in green, night values (zero) are shown in grey, and the visualizations are separated by year.
Time series flag plot: Lets you view the flags in two charts: time series and the percentage of data points per month.
Consistency plots: Consistency plots require the dataset to contain GHI, DNI and DIF, and all three must belong to the same test group. They are then compared against calculated values to determine data accuracy.
Quality control summary: Provides a summary of the checks performed in the dataset, separated by test groups.
Records where the calculation produces no result — typically at very low irradiance — are omitted along with their measured counterparts, since the plot needs valid pairs. A systematic problem shows up as the whole scatter shifting away from the ideal 45° line.
Tip: Use the toolbar controls to work with the charts and examine the flags closely.
Heatmap flag plot
The heatmap flag plot is the default tab you will see after the solar radiation QC finishes. It gives you a first look at the data and flags that have been automatically added to the identified values. It can help you quickly evaluate the data quality.
Heatmap: Shows the color-coded data and flags in a timeline. The Y axis represents 24-hour cycle, and X axis represents the timeline of the dataset. One heatmap contains one year of data by default. Green color represents correct values, grey night values, and various color points depict the flags in the timeline.
Identified flags: Flags that have been identified for the selected parameter, their respective color in the heatmap, and what they represent.
Parameter selector: Select the parameter you want to display in the heatmap flag plot.
Time series flag plot
The time series flag plot tab lets you examine the flags in two ways - in a time series chart, where you can zoom and see particular flags, and in a QC results monthly statistics chart, where you can visually compare amounts of different flags.
Flaged data: Color-coded flagged data.
Flags list: A color-coded list of flags that were identified in the dataset for the selected parameter. The same applies to the second chart.
Monthly statistics visualization: Each color represents a single flag. The amount of each flag is depicted in percent. This can help you quickly spot how much good data (green) is available for each month.
Parameter selector: Select the parameter you want to display in the charts.
Consistency plots
Consistency plots work only if there are at least three of the following parameters: GHI, DNI, DIF, and GTI. They are then compared and evaluated by calculations to determine the data accuracy. Each of the available parameters is displayed in a separate chart per testing group.
Consistency chart: Displays the data consistency for the given parameter. Color-coded points show passed vs values flagged with the consistency flag. Other flags are hidden in this case.
Test group selector: Select any test group to view the consistency charts for its parameters.
Quality control summary
The quality control summary tab provides a comprehensive breakdown of all solar radiation quality checks that have been carried out per test group.
Finishing solar radiation data check
Once you are done with the solar radiation data checks, use the “Save flags” button to apply the changes and add solar radiation QC status to the dataset.