Contributors:  ET. Carboni (UKRI-STFC RAL Space), G.E. Thomas (UKRI-STFC RAL SpaceUsedly (DWD)

Issued by: STFC RAL Space (UKRI-STFC) / Elisa CarboniDeutscher Wetterdienst / Tim Usedly

Date: 2231/07/20222024

Ref: C3S2_D312a_Lot1.1.3.1-v4.0_2022074_202407_PQAD_ECV_CCISurfaceRadiationBudgetSRB_SLSTR_v1.02

Official reference number service contract: 2021/C3S2_312a_Lot1_DWD/SC1

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List of datasets covered by this document

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Acronyms

Acronyms

List of tables

List of tables

List of figures

List of figures

General definitions

The “CCI product family” Climate Data Record (CDR) consists of two parts. The ATSR2-AATSR Surface Radiation Budget CDR is formed by a TCDR brokered from the ESA Cloud_cci project and an ICDR derived from the SLSTR on board of Sentinel-3. ICDR uses the same processing and infrastructure as the TCDR. Both TCDR and ICDR data have been produced by STFC RAL space.

These Surface Radiation Budget datasets from polar orbiting satellites consist of seven main variables: Surface Incoming Shortwave radiation (SIS), Surface Reflected Shortwave radiation (SRS), the Surface Net Shortwave radiation (SNS), the Surface Outgoing Longwave radiation (SOL), Surface Downwelling Longwave radiation (SDL), Surface Net Longwave radiation (SNL), and the Surface Radiation Budget (SRB).

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b=\frac{\sum_{i=1}^N (p_i - r_i)}{N} \ \ (Eq. 1)

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generaldefinitions generaldefinitions

General definitions

Table 1: Summary of variables and definitions

Table 2: Definition of processing levels

Table 3: Definition of various technical terms used in the document

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bc- RMSE=\sqrt{\frac{\sum_{i=1}^N ((p-b)-r)^2}{N}} \ \ (Eq. 2)

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Stability: The variation of the bias over a multi-annual time period

Table 1: Summary of variables and definitions

Table 2: Definition of processing levels

Table 3: Definition of various technical terms used in the document

Scope of the document

This document provides a description of the product validation methodology for the Essential Climate Variable (ECV) Surface Radiation Budget. This CDR comprises inputs from two sources: (i) brokered products from the Cloud Climate Change Initiative (ESA’s Cloud_cci), namely those coming from processing of the Advanced Along-Track Scanning Radiometer (A)ATSR) data  and (ii) those produced under this contract fore, specifically those coming from processing of the Sea and Land Surface Temperature Radiometers (SLSTR).

The Thematic Climate Data Record (TCDR) is the product brokered from the European Space Agency Cloud Climate Change Initiative (ESA’s Cloud_cci) ATSR2-AATSR version 3.0 (Level-3C) dataset. This is produced by STFC RAL Space from the second Along-Track Scanning Radiometer (ATSR-2) on board the second European Remote Sensing Satellite (ERS-2) spanning the period 1995-2003, the Advanced ATSR (AATSR) on board ENVISAT spanning the period 2002-2012.

In addition, the Interim Climate Data Record (ICDR) is the product derived from the SLSTR on board of Sentinel-3 and spans the period from 2017 to present.

Validation of ATSR2, AATSR and SLSTR derived products for the period from January 2017 to December 2021 are described in this document. It summarizes and refers to the methodology presented in the Cloud_cci Product Validation and Intercomparison Report [D1], used in the validation of the TCDR product. The same methodology is applied to the ICDR dataset.

Executive Summary

The ESA Climate Change Initiative (CCI) Surface Radiation Budget Climate Data Record (CDR) is a brokered product from the ESA Cloud_cci project, while the extension Interim CDR (ICDR) produced from the Sea and Land Surface Temperature Radiometer (SLSTR) is produced specifically for C3S. The product is generated by STFC RAL Space, using the Community Cloud for Climate (CC4CL) processor, based on the Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm. The Surface Radiation Budget is a product of the Broadband Radiative Flux Retrieval (BRFR) module of CC4CL, which uses the cloud properties produced by ORAC to compute broadband radiative flux values.

The Cloud_cci record comprises 17 years (1995-2012) of satellite-based measurements derived from the Along Track Scanning Radiometers (ATSR-2 and AATSR) onboard the ESA second European Research Satellite (ERS-2) and ENVISAT satellites. This CDR is partnered with the ICDR produced from the Sentinel-3A SLSTR, beginning in 2017, and Sentinel-3B SLSTR beginning in October 2018. In addition to individual products from each Sentinel-3 platform, a combined product that averages data from both SLSTR instruments into single daily and monthly means will also be provided.

The dataset encompasses level-3 data (monthly means) on a regular global latitude-longitude grid (with a resolution of 0.5°´ 0.5°) and includes these products: the Surface Incoming and Reflected Shortwave radiation (SIS and SRS respectively), the Surface Downwelling and Outgoing Longwave radiation (SDL and SOL respectively), the Surface Net Shortwave and Longwave radiation (SNS and SNL), and the total Surface Radiation Budget (SRB).

This document is divided into different sections:

• the first section presents a brief description of the  surface radiation CDR products together with reference for further information;
• the second section presents the datasets used to estimate the accuracy of the CDR surface radiation dataset;
• the third section presents the methodology used for the validation and is divided in different subsections that describe: the validation with ground measurements, the comparison with Clouds and Earth Radiation Energy System (CERES) surface data and the uncertainty propagation used to estimate the accuracy of the other parameters.

1. Validated products

The ATSR2-AATSR Surface Radiation Budget CDR is formed by a TCDR brokered from the ESA Cloud_cci project and an ICDR derived from the SLSTR on board of Sentinel-3. Both TCDR and ICDR data have been produced by STFC RAL space.

The SLSTR ICDR, both from the individual instruments (version 3.0) and combining both in a single product (version 4.0), is supplied to the CDS via the same route and uses the same processing software and infrastructure as the TCDR. The retrieval algorithm is  described in detail in [D2].

These Surface Radiation Budget datasets from polar orbiting satellites consist of: Surface Incoming Shortwave radiation (SIS), Surface Reflected Shortwave radiation (SRS), the Surface Net Shortwave radiation (SNS), the Surface Outgoing Longwave radiation (SOL), Surface Downwelling Longwave radiation (SDL), Surface Net Longwave radiation (SNL), and the Surface Radiation Budget (SRB).

The datasets cover the period from June 1995 to April 2012 (TCDR), using satellite-based measurements derived from ATSR2 and AATSR onboard the polar orbiting ERS-2 and ENVISAT respectively, and the period from January 2017 onwards using the SLSTR measurements (ICDR). These are level 3 products (monthly means) on a regular global latitude-longitude grid (with 0.5° x 0.5° resolution). Cloud properties from the ESA Cloud_cci dataset version 3 (TCDR) are used for the estimation of the Surface Radiation Budget¹. The Cloud_cci dataset can be downloaded here: https://climate.esa.int/en/projects/cloud/data/. The SLSTR based ICDR extends the coverage, with a five year gap, from 2017 onwards and is only available through the Copernicus Climate Data Store (CDS). Table 1-1 reports the values from the PQAR[D4]

The TCDR dataset that includes Surface Radiation Budget products as well as Cloud Properties and Earth Radiation Budget products are described by Poulsen et al. (2019) [D3].

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Table 4: Definition of statistical measures used in the document

B=\frac{1}{n}*\sum_{i=1}^n (y_i - o_i)

MAD=\frac{1}{n}*\sum_{i=1}^n |y_i - o_i|

SD=\sqrt{\frac{1}{n-1}*\sum_{i=1}^n ((y_i-o_i)-(\bar{y}-\bar{o}))^2}

FRAC=100\frac{\sum_{i=1}^n f_i}{n} \text{with} \begin{cases} f_i=1, & \text{if} & y_i \gt T \\ f_i=0, & \text{if} & y_i \le T \end{cases}

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) Surface Radiation Budget (SRB).

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 measurements from ground stations from the Baseline Surface Radiation Network (BSRN). Depending on the temporal availability and variable up to 37 stations were used to provide best possible global coverage (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 from 07/2022 to 12/2023 and also validated against the same reference dataset as the equal angle version of SLSTR.

A nearest neighbor technique is used to compare gridded satellite data (the points closest to ground stations) with ground stations. Amongst others the uncertainty metrics Bias and Absolute Bias are calculated and further evaluated against requirements defined by the Global Climate Observing System (GCOS) (see chapter 3).

Overall the SLSTR data mostly do not fulfill the requirements by GCOS (table 1); the values of the absolute bias are 13.05 W/m² (13.60 W/m²) for Surface Incoming Shortwave radiation (SIS) for equal angle grid (equal area grid), 13.36 W/m² (15.73 W/m²) for Surface Outgoing Longwave Radiation and do meet the threshold requirement (10 W/m²). Biases for Surface Reflected Shortwave Radiation (SRS) are 14.65 W/m² (14.00 W/m²) and Surface Downwelling Longwave Radiation (SDL) also do not meet the requirement due to a bias of 20.56 W/m² (18.40 W/m²). Comparison with the most continental and representative stations meet the threshold requirement by GCOS, outliers are mainly due the stations at high altitudes, high latitudes or Islands (see chapter 4).

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section1 section1

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 seven variables of the Essential Climate Variable Surface Radiation Budget (SRB): Surface Incoming Shortwave Radiation (SIS), Surface Reflected Shortwave Radiation (SRS), Surface Outgoing Longwave Radiation (SOL), Surface Downwelling Longwave Radiation (SDL) as well as the Net Fluxes (Surface Net Shortwave (SNS) and Surface Net Longwave Radiation(SNL)) and the overall net Radiation named Surface Radiation Budget (SRB).

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.

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The retrieval algorithm is described in detail in [D4].

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.

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section2 section2

2. Description of validating datasets

The SLSTR ICDR is validated for SIS, SRS, SOL and SDL against a wide range of measurements from ground stations of the Baseline Surface Radiation Network (BSRN). The World Radiation Monitoring Center (WRMC) is the central archive of the BSRN aiming to provide data on short- and longwave radiation fluxes, to e.g. monitor radiative components and their changes, and validate/evaluate satellite-based data. The BSRN provides quality-controlled surface radiation measurements at globally distributed ground stations available in, amongst others, monthly means (Ohmura et al., 1998). A list of stations with geographical information is provided Table 2-1. A global distribution of the stations is provided in Figure 2-1.

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Data is downloaded at the WRMC-BSRN website: https://bsrn.awi.de/

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section3 section3

3. Description of product validation methodology

The validation methodology is separated into three parts: Data preparation and application of methodology to compare a gridded satellite base dataset with ground stations (section 3.1), Validation (section 3.2) against available ground stations and Evaluation (section 3.3) against requirements defined by Global Climate Observing System (GCOS).

3.1 Data preparation

SLSTR data is provided at a regular latitude-longitude grid with 0.5°x0.5° spatial resolution and monthly means, and the validation is based on the comparison with monthly means of available surface measurements. A nearest neighbor technique is used forthe comparison, using the ground stations coordinates to extract the nearest grid point of the gridded dataset to calculate the bias and further statistical measures.

The maximum available number of months per stations for the SLSTR data is 63 (10/2018 – 12/2023) and 18 (07/2022 – 12/2023) on the equal angle and on the equal area grid respectively. A criteria is defined that at least 15 months should be available of the BSRN data for comparison with the equal angle grid version.

3.2 Validation

he following uncertainty metrics are calculated: Bias, Mean Absolute Difference (also called absolute bias), Standard Deviation and Fraction of months outside the validation target values (see definitions in General definitions section).

The corresponding Product Quality Assessment Report (PQAR) [D2] provides results on bias and absolute bias for each variable and station as well as maps with stations in green/red whether they meet/don’t meet the threshold requirement by GCOS. In addition, a correlation of SLSTR and BSRN data for all months is provided with metrics on correlation coefficient.

3.3 Evaluation

The 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) [D3].

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 should be mentioned, that these requirements are rather intended towards potentials and resolutions of climate models. Thus, GOCS 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 for SIS, SDL and SOL

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section4 section4

4. Summary of validation results

A brief summary of the validation results is provided in sections 4.1 to 4.4. Figures 4-1 to 4-4 show bias and absolute bias for each station and variable. Section 4.5 shows the evaluation results compared to the GCOS requirements. Detailed results can be found in the corresponding Product Quality Assessment Report (PQAR) [D2].

4.1 Surface Incoming Shortwave Radiation

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Figure 4-1 shows bias (black dots) and absolute bias (white triangle) for SLSTR data compared to every available ground station. Most of the station’s biases are within the threshold requirement (10 W/m²). Outliers are due to stations with high altitude (Boulder, Izana, Sonnblick, Yushan) or stations on islands (Lanyu Island).

4.2 Surface Reflected Shortwave Radiation

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Figure 4-2 shows proportion wise more outliers for SRS compared to SIS considering the number of available stations. On average a small negative is seen with the same stations outside the 10 W/m² threshold requirement. The proportion of negative values for the bias is higher compared with SIS.

4.3 Surface Downwelling Longwave Radiation

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The comparison with SDL reveals a positive bias for most of the stations (31/37 stations). Most of the station’s biases are outside of 10 W/m² and there are three significant outliers in Izana (Spain, 2373 m), Sonnblick (Austria, 3109 m) and Yushan (Taiwan, 3858 m). These stations are located at higher altitudes compared to the other stations. Concordia Station (3233 m) has the highest negative bias.

4.4 Surface Outgoing Longwave Radiation

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Most of the months/stations tend to have a small negative bias which is compensated by measurements from Georg von Neumeyer and Izana Stations with positive biases.

4.5 Evaluation with GCOS requirements

Table 4-1 summarizes the uncertainty metrics for each variable. Absolute Bias is lowest for SIS, while SDL has the hightest. Most of the biases are positive, except for SRS and SOL on the equal area grid. Between 42-60% of the station months are outside the 10 W/m² threshold.

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references references

References

Ohmura, A., et al. (1998), Baseline Surface Radiation Network (BSRN/WCRP): New precision radiometry for climate research, Bulletin of the American Meteorological Society, 79(10), 2115-2136. DOI:https://doi.org/10.1175/1520-0477(1998)079<2115:BSRNBW>2.0.CO;2

2. Description of validating datasets

The Surface Radiation Budget TCDR dataset from the ATSR2 and AATSR instruments is compared against the ground measurements dataset: the central archive of the Baseline Surface Radiation Network (BSRN)².

BSRN stations measure direct, diffuse and global downwelling shortwave and longwave fluxes in 1 min temporal resolution. The manned stations are located at locations, which are representative of a relatively large surrounding area for the use in satellite and climate model validation. The quality controlled datasets are available for the years 1992 to 2017 in ASCII file format. Specially calculated monthly means of daily mean products have been used in TCDR validation [D1]

Both, TCDR and ICDR from SLSTR instruments, are compared with the Clouds and Earth Radiation Energy System (CERES) Energy Balanced and Filled (EBAF) fluxes Edition 4.1 Top of atmosphere (TOA) and Bottom of Atmosphere (BOA) fluxes Edition (Loeb et al., 2018)³.

The CERES product provides long-term shortwave (SW) and longwave (LW) TOA fluxes for all- and clear-sky conditions. The CERES instruments fly on the Terra and Aqua satellites and cover a period from March 2000 to June 2002 for Terra only, and cover combined Terra and Aqua observations from July 2002 to January 2017. The CERES instruments provide global coverage daily, and monthly mean regional fluxes and are based upon daily samples over the entire globe.

In addition to the TOA fluxes the CERES dataset provides EBAF Ed4.0 Surface Fluxes. EBAF Surface fluxes (used to compare with the CDR dataset) are derived using CERES TOA products and coincident imager data from the Moderate Resolution Imaging Spectrometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS).

3. Description of product validation methodology

The validation strategy is described in section 2.4 of [D1].

The methodology uses the bias between the Cloud_cci product and the reference data to estimate the accuracy of the dataset.

The bias corrected root mean squared error (bc-RMSE) is used to express the precision of CDR compared to a reference data record, which is also known as the standard deviation from the mean.

The SIS and SDL products of the TCDR dataset are validated against ground measurements and compared with the CERES satellite dataset in [D1].

The accuracy for SIS and SDL (TCDR) are estimated using  the ground measurements as reference because these are considered to be more accurate than satellite measurements.

The SIS and SDL products of the ICDR dataset are evaluated by a comparison with the CERES dataset and the evaluation is performed within the C3S project.

The SRS, SNS SNL and SRB accuracies for both TCDR and ICDR are estimated by uncertainty propagation as explained below (section 3.3 to 3.5). Table 3-1 summarizes the methodology used to estimate the accuracies for each product.

In all cases, the same validation approach will be applied to the combined SLSTR product (version 4.0) as is used for the individual platform SLSTR data (version 3.0 and 3.1).

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Product name

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Validation with BSRN

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Comparison with CERES

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Uncertainty propagation

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Surface Incoming Shortwave radiation (SIS)

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TCDR

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TCDR and ICDR

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Surface Reflected Shortwave radiation (SRS)

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ICDR

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TCDR and ICDR

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Surface Net Shortwave radiation (SNS)

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TCDR and ICDR

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Surface Outgoing Longwave radiation (SOL)

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TCDR and ICDR

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Surface Downwelling Longwave radiation (SDL)

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TCDR

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TCDR and ICDR

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Surface Net Longwave radiation (SNL)

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TCDR and ICDR

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Surface Radiation Budget (SRB)

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TCDR and ICDR

3.1 Validation with BSRN ground base radiative flux

BSRN stations measure direct, diffuse and global downwelling shortwave and longwave fluxes in 1 min temporal resolution. The 1-minute data were aggregated to monthly averages which were used as validation data. Using the TCDR and the reference datasets (in different locations around the world) we compute the bias and standard deviation.

The validation method for Surface Incoming Shortwave radiation (SIS) and Surface Downwelling Longwave radiation (SDL) with BSRN ground measurements is described in sections 2.4 and 3.3.2 of [D1].

3.2 Comparison with CERES satellite data

TCDR and reference datasets are compared by calculation of multi-annual mean (i.e., we produce a global map of one parameter averaged over multiple years, we calculate the mean of this global map and compare it with the equivalent mean from reference data) and standard deviation for the common time period (2003-2011). For the ICDR, we used the CERES dataset as a reference and compared the means of multi-monthly means (i.e., we compute the mean of the differences between CDR monthly mean global averages and reference data monthly mean global averages) as well as the standard deviation for the time period 2017-01 to 2021-12. Global maps of multiannual Surface Incoming Shortwave radiation (SIS) and Surface Downwelling Longwave radiation (SDL) are computed for the CDR and the reference dataset. The scores (bias and bc-RMSE) are calculated by including all valid data points pairwise in the CERES dataset and the CDR. The same methodology is applied for the TCDR in [D1] and ICDR within C3S.

The validation method for Surface Incoming Shortwave radiation (SIS) and Surface Downwelling Longwave radiation (SDL) with CERES is described in section 5.3 and 5.4 of [D1] as well as the results of the accuracy (bias) ΔSIS/ΔSDL. The same methodology will be used to estimate the accuracy of SOL in comparison with CERES.

3.3 Surface Reflected Shortwave Radiation (SRS)

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\Delta SRS= \frac{\delta SRS}{\delta SIS} \Delta SIS + \frac{\delta SRS}{\delta SAL} \Delta SAL = SAL \Delta SIS + SIS \Delta SAL, \quad \ \ (Eq. 3)

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\Delta SIS

comes from [D1] and

\Delta SAL

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SAL = SRS / SIS, \quad \ \ (Eq. 4)

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SNS = SIS - SRS, \quad \ \ (Eq. 5)

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\Delta SNS = \Delta SIS + \Delta SRS, \quad \ \ (Eq. 6)

3.5 Surface Net Longwave Radiation (SNL)

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SNL = SDL - SOL, \quad \ \ (Eq. 7)

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\Delta SNL

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\Delta SNL = \Delta SDL + \Delta SOL, \quad \ \ (Eq. 8)

3.6 Surface Radiation Budget (SRB)

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SRB = SNS + SNL, \quad \ \ (Eq. 9)

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\Delta SRB = \Delta SNS + \Delta SNL, \quad \ \ (Eq. 10)

4. Summary of validation results

The TCDR validation results are provided in [D1], section 3.3.2, 5.3 and 5.4.

As an example Figure 4-1 from [D1] shows the results of the TCDR comparison with the BSRN incoming shortwave (SIS) and longwave (SDL) radiation with scatter plots and global maps showing the bias for each station. A more detailed description and analysis of the results is available in the PQAR document [D4].

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Validation of BOA fluxes against BSRN stations present standard deviations of 24 W/m² and bias of 8.2 W/m² for Surface Incoming Shortwave radiation (SIS) and standard deviation of 14 W/m² and bias of 11.9 W/m² for Surface Downwelling Longwave radiation (SDL). The intercomparison of Cloud_cci radiation products with CERES present a bias of 1.53 W/m², standard deviation of 3.18 W/m² and stability of 0.97 W/m²/decade for SIS. Bias of 10.17 W/m², standard deviation of 1.2 W/m² and stability of 2.8 W/m²/decade for SDL. Intercomparison (using the monthly mean data from January 2017 to December 2021) of ICDR products with CERES showed biases (we report here the maximum between the values find for SLSTR-A and SLSTR-B) consistent with TCDR and are: 1.5 W/m² for SIS, 2.0 W/m² for SRS, 3.9 W/m² for SOL and 13 W/m² for SDL.

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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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