Last modified on May 30, 2025 17:03

Contributors: T. Usedly (DWD)

Issued by: Deutscher Wetterdienst / Tim Usedly

Date: 31/07/2024

Ref: C3S2_D312a_Lot1.1.2.8_202407_PQAD_ECV_ERB_SLSTR_v1.2

Official reference number service contract: 2021/C3S2_312a_Lot1_DWD/SC1

History of modifications

List of datasets covered by this document

Related documents

Acronyms

List of tables

List of figures

General definitions

Table 1: Summary of variables and definitions

Table 2: Definition of various technical terms used in the document

Table 3: Definition of processing levels

Table 4: Definition of statistical measures used in the document

Scope of the document

This document provides a description of the product validation methodology for the Sea and Land Surface Temperature Radiometer (SLSTR) v4.0 based Interim Climate Data Record (ICDR) of the Essential Climate Variable (ECV) Earth Radiation Budget (ERB).

The dataset produced by RAL Space and Brockmann Consult (BC) under the Copernicus Climate Change Service (C3S) program ranges from January 2017 to December 2023 and provides an Interim Climate Data Record (ICDR) to the brokered Thematic Climate Data Record (TCDR) from the European Space Agency Cloud Climate Change Initiative (ESA’s Cloud_cci).

The TCDR is a brokered product based on processing of the (Advanced) Along-Track Scanning Radiometer ((A)TSR) onboard ERS-2 and Envisat that was produced by RAL Space for the ESA Cloud_cci program and ranges from June 1995 to April 2012. Detailed validation methodology and results are presented in the Cloud_cci Product Validation and Intercomparison Report [D1].

The ICDR is derived with a five-year gap from SLSTR onboard the Sentinel-3A and -3B satellites covering 01/2017 – 12/2023. Detailed results are presented in the corresponding Product Quality Assessment Report (PQAR) [D2].

Executive summary

The Sea and Land Surface Temperature Radiometer onboard Sentinel-3A provides data from 01/2017 on. With the launch of Sentinel-3B in 10/2018 not just individual data but also a merged version of Sentinel-3A/3B is provided (see chapter 1). The merged version (until 12/2023) is validated against the following satellite-based datasets: CERES EBAF Ed. 4.2, CERES SYN1deg Ed. 4.1, HIRS OLR daily v1.2, CLARA-A3, as well as ECMWF’s Reanalysis product ERA5 (see chapter 2). In addition to the merged SLSTR version, a second version on a different grid (equal area in addition to equal angle) is provided for the period from 07/2022 to 12/2023 and also validated against the same reference datasets as the equal angle version of SLSTR.

All datasets are (if necessary) remapped to a 1°x1° grid and the following uncertainty metrics between datasets and reference calculated: Bias, Mean Bias and Mean Absolute Bias. The Mean Absolute Bias is then evaluated against requirements defined by the Global Climate Observing System (GCOS) (see chapter 3).

Overall the SLSTR data does not fulfill the requirements by GCOS; the values of the mean absolute bias that vary between 4-5 W/m² for Outgoing Longwave Radiation (OLR), and between 10-15 W/m² for Reflected Shortwave Flux (RSF), depending on the reference, are much higher than the threshold requirement (1 W/m²) (see chapter 4).

1. Validated products

The SLSTR-based dataset provides monthly means on a regular global latitude-longitude grid with 0.5°x0.5° spatial resolution for two variables of the Essential Climate Variable Earth Radiation Budget (ERB): Outgoing Longwave Radiation (OLR) and Reflected Shortwave Flux (RSF).

The record is generated by RAL Space (data from 01/2017 – 06/2022) and Brockmann Consult (07/2022 – 12/2023) solely for the Climate Data Store (CDS) from the Copernicus Climate Change Service (C3S). The Data are provided for each individual satellite: For Sentinel-3A (S3A) from January 2017 to June 2022 and for Sentinel-3B (S3B) from October 2018 to June 2022. In addition, a merged version is provided from 10/2018 on, when S3B was launched. From 07/2022, Brockmann Consult provides a continuation of the merged version until 12/2023. BC provides data for the merged product for two different grids: (1) regular equal angle global latitude-longitude grid (continuation of previous data) and (2) regular equal area global latitude-longitude grid. The equal area projection uses a sinusoidal raster as aggregation raster for the binning process. A final transformation step maps the monthly aggregates into the plate-carree projection. During this projection, data of the sinusoidal raster close to the poles is repeatedly mapped to several plate-carree cells until the angle extension matches the ground extension in kilometers; the measurement data are not altered in this case.

An overview of the various data producers, satellites, grids and time coverages for the ICDRs is shown in Figure 1-1.

Figure 1-1: Overview of data producers, satellites, time coverages and grids for the ICDRs. Products above/below the black line are produced by RAL Space/Brockmann Consult (BC); the data generated from 07/2022 on are provided in two different grids.

The retrieval algorithm is described in detail in [D7].

The PQAD and PQAR cover the merged product for the time periods 10/2018 – 12/2023 on the equal angle grid and 07/2022 – 12/2023 on the equal area grid respectively.

2. Description of validating datasets

The SLSTR ICDR is validated against a wide range of datasets (Table 2-1). Chapters 2.1 – 2.5 provide a brief introduction to the respective datasets. All datasets provide a global coverage with a regular latitude-longitude grid with resolutions of 1°x1° or higher. Datasets with higher spatial resolution are remapped to 1° resolution (see Chapter 3). HIRS monthly data is only available with 2.5° resolution, therefore HIRS daily data (0.25° resolution) is used and remapped as well as monthly means based on the daily means calculated.

Table 2-1: Datasets and information used for validation of SLSTR data

 2.1 CERES EBAF Ed. 4.2

The Cloud and Earth’s Radiant Energy System (CERES) Energy Balanced And Filled (EBAF) Edition 4.2 provides monthly mean data of OLR and RSF with 1°x1° spatial resolution from 03/2000 on. The dataset is produced by NASA based on the CERES instruments onboard polar orbiting Aqua, Terra and NOAA-20 platforms.

Terra is the only satellite in descending sun-synchronous orbit, while Aqua and NOAA-20 are in ascending sun-synchronous orbits. CERES instruments are broadband radiometers on each satellite and detect radiances in three different spectral domains: the Shortwave (0.3 μm - 5 μm), total (0.3 μm - 200 μm) and window (8 μm – 12 μm) regions. The radiances are subsequently converted by empirical angular distribution models to Top of Atmosphere (TOA) fluxes (Loeb, 2018).

Data is downloaded via the CERES Ordering Tool: https://ceres-tool.larc.nasa.gov/ord-tool/

 2.2 CERES SYN1deg Ed. 4.1

The Cloud and Earth’s Radiant Energy System (CERES) SYN1deg Edition 4.1 provides monthly mean data of OLR and RSF with 1°x1° spatial resolution from 03/2000 on and is also produced by NASA.

Unlike CERES EBAF, the product merges data from five geostationary satellites (60°S – 60°N) and from the two sun-synchronous polar orbiting platforms Aqua and Terra. As the orbits of Aqua and Terra provide observations only twice per day, the additional data from geostationary satellites improve monitoring of the diurnal variability (Doelling et al, 2013) [D3].

Data is downloaded via the CERES Ordering Tool: https://ceres-tool.larc.nasa.gov/ord-tool/

 2.3 HIRS OLR Daily v1.2

The High-Resolution Infrared Radiation (HIRS) dataset is produced by the NOAA National Centers for Environmental Information (NCEI) and based on the HIRS instruments onboard NOAA and MetOp satellites. The dataset provides daily means (1°x1° spatial resolution) as well as monthly means (2.5° x 2.5°) from 01/1979 to present only for Outgoing Longwave Radiation. Due to the advantage of the better resolution, daily means are used and monthly means calculated based on them.

The HIRS instruments measure radiances in the Infrared (IR) spectrum, which is why only OLR is provided. For the relevant period of 2018 to 2023, the fourth version of the HIRS instrument is onboard polar orbiting satellites NOAA-18, NOAA-19, MetOp-A and MetOp-B.

The main input data for the daily OLR product is the HIRS Level-1b all-sky data. Based on the Level-1 data, the data record is produced including OLR regression and inter-satellite bias correction. Observations from imagers onboard geostationary satellites are used to improve the representation of the diurnal variability. HIRS-based observations are added to cover the regions outside 60°S-60°N.

Data is downloaded via the “Earth's radiation budget from 1979 to present derived from satellite observations” landing page of the Climate Data Store.

 2.4 ERA5

ERA5 is the fifth generation of atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) (Hersbach et al.,2020). Data is available with a spatial resolution of 0.25°x0.25° and monthly means from 1940 to present.

Reanalysis is a combination (data assimilation) of model data with observations and provides a globally complete and consistent dataset for several decades. In the case of ECMWF, a model trajectory of the previous forecast is fitted to the available observations in a 12 hour window to achieve the best estimate of the true atmospheric development.

Data is downloaded via the “ERA5 monthly averaged data on single levels from 1940 to present” landing page of the Climate Data Store. The variable “Top net longwave radiation” is used as OLR (with the assumption of no downwelling longwave radiation at the top of the atmosphere), while RSF is calculated as the difference of “Total incident solar radiation” and “Top net shortwave radiation).

 2.5 CLARA-A3

CM SAF cLoud, Albedo and surface RAdiation dataset from AVHRR data - Edition 3 (CLARA-A3), produced by EUMETSAT’s Satellite Application Facility on Climate Monitoring (CM SAF), provides data from 01/1979 on for OLR and RSF on a regular latitude-longitude grid with 0.25°x0.25° resolution and monthly means.

CLARA-A3 products are derived from Advanced Very High-Resolution Radiometers (AVHRR) onboard polar orbiting NOAA and MetOp satellites to derive spatio-temporal averaged datasets. The detailed description of the algorithm used to generate the TOA radiation CDR is given in the CM SAF Algorithm Theoretical Basis Document [D4].

Data is downloaded via the CM SAF Web User Interface (WUI):

https://wui.cmsaf.eu/safira/action/viewHome

3. Description of product validation methodology

The validation methodology is separated into three parts: Data preparation (section 3.1) to make the SLSTR dataset as well as the five reference datasets comparable, Validation (section 3.2) against several satellite-based reference datasets and Evaluation (section 3.3) against several requirements defined by Global Climate Observing System (GCOS) and the CM SAF Product Requirements Document.

3.1 Data preparation

Datasets are prepared before the validation and modified towards a 1°x1° target grid with -90° to 90° latitude and -180° to 180° longitude. The validation is also based on monthly means, which requires to calculate monthly means based on daily means (HIRS). All five reference datasets are available from 01/2017 to 12/2023, while the SLSTR data start at different times:

 3.1.1 Remapping

All datasets need to be on the same grid to make them comparable (e.g. difference of two maps). Therefore, a spatial resolution of 1°x1° is defined as the target grid for all datasets. CERES EBAF, CERES SYN, and HIRS are already available with a 1° resolution, while CLARA-A3, ERA5 and SLSTR need a remapping to meet the 1° grid. The remapping is done by a bilinear interpolation with the climate data operator (cdo¹) function named remapbil.

3.1.2 Monthly mean

The cdo function monmean is used to calculate monthly means based on daily means. This is necessary for the HIRS data only.

Calculation is done by: 

with \( t_1-t_n \) the timesteps of the same month, o as output file, i as input file(s) and x as grid point.

 3.2 Validation

The following uncertainty metrics are calculated: Bias, Mean Bias and Mean Absolute Bias.

Bias is the difference between the (validated) dataset and the reference dataset for each month and grid box:

with B the Bias, F the validated/reference datasets, and i, j the indices. Prior to the bias calculation, the datasets are collocated and only grid points considered, where all datasets have valid values (not 

nan). This means, if grid points with nan values appear in at least one dataset, the corresponding grid points for all the datasets are set to nan and filtered out. This method can be applied on two or more datasets depending on what is compared. The bias is used for calculation of further uncertainty metrics.

Mean Bias (MB) describes the overall bias with respect to a reference dataset. It is defined as the bias of two gridded data records and a subsequently calculation of the global spatial average. This results in one value per month which can be averaged over the whole time period.

with MB the Mean Bias, i and j (m and n, respectively) the indices, w the cosine weighting factor and B the Bias.

The Mean Absolute Bias (MAB) is a bias corrected uncertainty metric calculated by subtracting the previously calculated MB from every grid box bias. Subsequently, the same steps as for the calculation of the mean bias are applied.

The PQAR contains collocated, globally averaged climatologies of all datasets as well as deseasonalized climatologies. Difference plots (climatology of mean bias) are provided together with climatologies of the mean absolute bias. In addition, bias maps for each year are produced.

3.3 Evaluation

The Mean Absolute Bias is used as evaluation against the requirements defined by the Global Climate Observing System (GCOS) in The 2022 GCOS ECVs Requirements (GCOS 245) [D6].

GCOS defines three requirements depending on users needs:

• Goal (G): The strictest requirement, indicating no further improvements necessary

• Breakthrough (B): Intermediate level between threshold and goal. Breakthrough indicates that it is recommended for certain climate monitoring activities

• Threshold (T): Minimum requirement

it is worth mentioning, that these requirements are rather intended towards potentials and resolutions of climate models. Thus, GCOS requirements are not identical to the users needs outside the climate modelling community. Also, they are often not attainable using existing or historical observing systems.

Table 3-1 names the requirements for horizontal and temporal resolution as well as accuracy and stability for OLR and RSF.

Table 3-1: Summary of requirements for OLR and RSF based on GCOS [D6]

4. Summary of validation results

A brief summary of the validation results is provided in sections 4.1 and 4.2. Figures 4-1 and 4-2 show the deseasonalized and globally averaged monthly mean fluxes of SLSTR OLR and SLSTR RSF as well as reference datasets. Also, an evaluation against GCOS requirements is presented. Detailed results can be found in the corresponding Product Quality Assessment Report (PQAR) [D2].

4.1 Outgoing Longwave Radiation

Figure 4-1: Global mean flux of monthly SLSTR OLR and reference datasets for 01/2017 – 12/2023

All five reference datasets appear to be stable within the short time period of seven years. A small positive trend from late 2022 on is visible for all datasets, also for the SLSTR products (purple). For most of the months of 2022 a positive anomaly is detected for the SLSTR data (S3A, S3B and therefore also the merged product). A map shows that the positive anomaly is seen in general over ocean area as well as land area below 30°N (especially over South East Asia). Generally, the accuracy requirements by GCOS are not fulfilled (table 4-1), due to the fact, that the requirements are not always appropriate for satellite-based data.

Table 4-1: Results of evaluation against GCOS requirements for SLSTR OLR

4.2 Reflected Shortwave Flux

Reference datasets CERES EBAF, CERES SYN, ERA5 and CLARA-A3 are relatively stable and similar to each other. In contrast to this a general bias to the SLSTR data is seen with higher values for the SLSTR instruments. In addition, the SLSTR dataset appears not to be stable within the short time range of seven years. This leads also to the GCOS requirements not being fulfilled (table 4-2).

Figure 4-2: Global mean flux of monthly SLSTR RSF and reference datasets for 01/2017 – 12/2023

Table 4-2: Results of evaluation against GCOS requirements for SLSTR RSF

References

Doelling, D. R., Loeb, N. G., Keyes, D. F., Nordeen, M. L., Morstad, D., Nguyen, C., ... & Sun, M. (2013).

Geostationary enhanced temporal interpolation for CERES flux products. Journal of Atmospheric and Oceanic Technology, 30(6), 1072-1090

Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz‐Sabater, J., ... & Thépaut, J. N. (2020). The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730), 1999-2049.

Loeb, N.G., Doelling, D.R., Wang, H., Su, W., Nguyen, C., Corbett, J.G., Liang, L., Mitrescu, C., Rose, F.G., and Kato, S.: Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Top-of-Atmosphere (TOA) Edition 4.0 Data Product, J. Climate, 31(2), 895–918, doi:10.1175/JCLI-D-17-0208.1, 2018.

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