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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: 2631/0107/20232024
Ref: C3S2_D312a_Lot1.1.2.3-v4.0_2023018_202407_PQAD_CCIEarthRadiationBudgetECV_ERB_SLSTR_v1.12
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
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title | Click here to expand the list of acronyms |
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Acronym
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Definition
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AATSR
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Advanced Along-Track Scanning Radiometer
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ATBD
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Algorithm Theoretical Basis Document
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ATSR
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Along-Track Scanning Radiometer
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C3S
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Copernicus Climate Change Service
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CCI
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Climate Change Initiative
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CERES
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Clouds and Earth Radiation Energy System
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CDR
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Climate Data Record
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CDS
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Climate Data Store
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ENVISAT
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Environmental Satellite
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ERS
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European Research Satellite
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ESA
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European Space Agency
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ICDR
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Interim Climate Data Record
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OLR
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Outgoing Longwave Radiation
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RAL
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Rutherford Appleton Laboratory
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RSF
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Reflected Solar radiation Flux
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SLSTR
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Sea and Land Surface Temperature Radiometers
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STFC
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Science and Technology Facilities Council
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TCDR
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Thematic Climate Data Record
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TOA
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Top Of the Atmosphere
List of tables
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Table 1-1: Summary of the TCDR and preliminary assessment of ICDR accuracy of the Earth Radiation Budget dataset |
List of figures
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Figure 4-1: RSF and OLR from SLSTR (ICDR dataset) for March 2017. Figure 4-2: RSF and OLR from CERES dataset for March 2017. |
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 Earth Radiation Budget datasets from polar orbiting satellites consist of two main variables: Outgoing Longwave Radiation (OLR): The outgoing longwave flux, measured at the top of the atmosphere.
Reflected Solar Radiation (RSR): The reflected solar flux, measured at the top of the atmosphere.
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b=\frac{\sum_{i=1}^N (p_i - r_i)}{N} \ \ (Eq. 1) |
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Acronyms
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List of tables
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Table 2-1: Datasets and information used for validation of SLSTR data Table 3-1: Summary of requirements for OLR and RSF based on GCOS [D6] Table 4-1: Results of evaluation against GCOS requirements for SLSTR OLR Table 4-2: Results of evaluation against GCOS requirements for SLSTR RSF |
List of figures
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Figure 1-1: Overview of data producers, satellites, time coverages and grids for the ICDRs. Figure 4-1: Global mean flux of monthly SLSTR OLR and reference datasets from 01/2017 – 12/2023 Figure 4-2: Global mean flux of monthly SLSTR RSF and reference datasets from 01/2017 – 12/2023 |
General definitions
Table 1: Summary of variables and definitions
Variables | Abbreviation | Definition |
Outgoing Longwave Radiation | OLR | Net total thermal radiation emitted by the Earth, as measured at the top of atmosphere. |
Reflected Solar Flux | RSF | Net total outgoing shortwave (UV, visible, near-IR) radiation at the top of atmosphere. This is dominated by reflected and scattered solar radiation. |
Table 2: Definition of various technical terms used in the document
Jargon | Definition |
TCDR | A Thematic Climate Data Record is a consistently processed time series of a geophysical variable. The time series should be of sufficient length and quality. |
ICDR | An Interim Climate Data Record (ICDR) denotes an extension of TCDR, processed with a processing system as consistent as possible to the generation of TCDR. |
GCOS requirement | GCOS defines three requirements depending on user’s 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 |
Brokered product | The C3S Climate Data Store (CDS) provides both data produced specifically for C3S and so-called brokered products. The latter are existing products produced under an independent programme or project which are made available through the CDS. |
Climate Data Store (CDS) | The front-end and delivery mechanism for data made available through C3S. It is a platform that provides access to a wide range of climate data, including satellite and in-situ observations, reanalysis and other relevant datasets. |
Retrieval | A numerical data analysis scheme which uses some form of mathematical inversion to derive physical properties from some form of measurement. In this case, the derivation of cloud properties from satellite measured radiances. |
Forward model | A deterministic model which predicts the measurements made of a system, given its physical properties. The forward model is the function which is mathematically inverted by a retrieval scheme. In this case, the forward model predicts the radiances measured by a satellite instrument as a function of atmospheric and surface state, and cloud properties. |
Remapping | Interpolation of horizontal fields to a new, predefined grid. All datasets are remapped to the same grid (1°x1°, latitude from -90° to 90°, longitude from -180° to 180°) to make them comparable. The remap is done with bilateral interpolation. |
Collocation | A collocation consists in filtering nan values of different datasets in the same grid to make them uniform. This is necessary to compare e.g. the global average of two datasets. |
Cosine weighted averaging | Consideration of different grid box areas. Grid boxes on usual equal angle grid boxes have a different area depending on the latitude (with larger areas towards the equator). Towards the poles the same number of boxes covers a smaller area; therefore, a correction factor is needed to achieve equal area grid boxes. This factor is the cosine of the latitude. The method is applied for calculation of global averages. |
Table 3: Definition of processing levels
Processing level | Definition |
Level-1b | The full-resolution geolocated radiometric measurements (for each view and each channel), rebinned onto a regular spatial grid. |
Level-2 (L2) | Retrieved cloud variables at full input data resolution, thus with the same resolution and location as the sensor measurements (Level-1b). |
Level-3C (L3C) | Cloud properties of Level-2 orbits of one single sensor combined (averaged) on a global spatial grid. Both daily and monthly products provided through C3S are Level-3C. |
Table 4: Definition of statistical measures used in the document
Statistical measures | Definition | ||
Bias (B) | Difference for each grid box (i,j) and time step between the dataset and reference dataset. Defined as:
with B the Bias, i, j grid box indices and F the dataset and reference dataset. | ||
Mean Bias (MB) | Mean Bias is defined as the overall bias between a dataset and reference dataset. Based on the calculated bias (resulting in a map) the global spatial and weighted average is calculated resulting in the mean bias:
with MB the Mean Bias, n and m the number of grid boxes for latitude (180) and longitude (360), w the latitude dependent factor for the cosine-weighted averaging and B the predefined Bias. | ||
Mean Absolute Bias (MAB) | Mean Absolute Bias is defined as subtracting the predefined Mean Bias from every grid box and time steps bias to remove the general bias. On a next step, the global spatial and weighted average is calculated:
with MAB the Mean Absolute Bias, n and m the number of grid boxes for latitude and longitude, w the latitude dependent factor for cosine-weighted averaging, B the predefined Bias and MB as the predefined Mean Bias. |
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).
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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. Anchor figure1_1 figure1_1
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.
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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 Anchor table2_1 table2_1
Dataset | Variables | Time | Temporal resolution | Spatial resolution | Chapter |
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CERES EBAF Ed. 4.2 | OLR and RSF | 01/2017 – 12/2023 | monthly | 1°x1° | See 2.1 |
CERES SYN1deg Ed. 4.1 | OLR and RSF | 01/2017 – 12/2023 | monthly | 1°x1° | See 2.2 |
HIRS v1.2 | OLR | 01/2017 – 12/2023 | daily (monthly mean created via cdo) | 1°x1° | See 2.3 |
ERA5 | OLR and RSF | 01/2017 – 12/2023 | monthly | 0.25°x0.25° (remapped to 1°x1°) | See 2.4 |
CLARA-A3 | OLR and RSF | 01/2017 – 12/2023 | monthly | 0.25°x0.25° (remapped to 1°x1°) | See 2.5 |
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
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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:
Individual SLSTR onboard Sentinel-3A: | 01/2017 – 06/2022 (not validated) |
Individual SLSTR onboard Sentinel-3B: | 10/2018 – 06/2022 (not validated) |
Merged SLSTR product: | 10/2018 – 12/2023 |
Merged SLSTR product on equal area grid: | 07/2022 – 12/2023 |
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.
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1 See [D5] for cdo manual |
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:
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o(t,x)=mean (i(tx),t_1<t \le t_n) (1) |
with
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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:
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B_{i,j}=F_{Data,i,j}-F_{Ref,i,j} (2) |
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.
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MB=\frac{1}{m*n}*\sum_{i=1}^m \sum_{j=1}^n w_j(B_{i,j}) (3) |
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.
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MAB=\frac{1}{m*n}*\sum_{i=1}^m \sum_{j=1}^n w_j*|B_{i,j}-MB| (4) |
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]
Products | Requirement | Surface Incoming Shortwave Radiation | Surface Downwelling Longwave Radiation |
Horizontal Resolution | G | 10 km | 10 km |
B | 50 km | 50 km | |
T | 100 km | 100 km | |
Temporal Resolution | G | 1 h | 1 h |
B | 24 h | 24 h | |
T | 720 h | 720 h | |
Accuracy | G | 0.2 W/m² | 0.2 W/m² |
B | 0.5 W/m² | 0.5 W/m² | |
T | 1 W/m² | 1 W/m² |
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 Anchor figure4_1 figure4_1
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 Anchor table4_1 table4_1
Products | Requirement | Values | Outgoing Longwave Radiation | |
Horizontal Resolution | G | 10 km | Roughly 55 km at the equator | |
B | 50 km | |||
T | 100 km | |||
Temporal Resolution | G | 1 h | Monthly mean (720h) | |
B | 24 h | |||
T | 720 h | |||
Accuracy | G | 0.2 W/m² | Merged SLSTR product vs. reference datasets (10/2018 – 12/2023): CERES EBAF: 4.64 W/m² CERES SYN: 4.60 W/m² HIRS: 4.46 W/m² ERA5: 5.00 W/m² CLARA-A3: 4.65 W/m² | Equal area SLSTR product vs. reference datasets (07/2022 – 12/2023): SLSTR equal angle: 0.00 W/m² CERES EBAF: 5.14 W/m² CERES SYN: 5.02 W/m² HIRS: 4.86 W/m² ERA5: 5.40 W/m² CLARA-A3: 5.00 W/m² |
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 Anchor figure4_2 figure4_2
Table 4-2: Results of evaluation against GCOS requirements for SLSTR RSF Anchor table4_2 table4_2
Products | Requirement | Values | Reflected Shortwave Radiation | |
Horizontal Resolution | G | 10 km | Roughly 55 km at the equator | |
B | 50 km | |||
T | 100 km | |||
Temporal Resolution | G | 1 h | Monthly mean (720h) | |
B | 24 h | |||
T | 720 h | |||
Accuracy | G | 0.2 W/m² | Merged SLSTR product vs. reference datasets (10/2018 – 12/2023): CERES EBAF: 10.08 W/m² CERES SYN: 10.40 W/m² ERA5: 13.90 W/m² CLARA-A3: 10.03 W/m² | Equal area SLSTR product vs. reference datasets (07/2022 – 12/2023): SLSTR equal angle: 00.00 W/m² CERES EBAF: 10.84 W/m² CERES SYN: 11.00 W/m² ERA5: 14.40 W/m² CLARA-A3: 10.27 W/m² |
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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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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
Variables | Abbreviation | Definition |
Outgoing longwave radiation | OLR | Net total thermal radiation emitted by the Earth, as measured at the top of atmosphere. |
Reflected solar flux | RSF | Net total outgoing shortwave (UV, visible, near-IR) radiation at the top of atmosphere. This is dominated by reflected and scattered solar radiation. |
Table 2: Definition of processing levels
Processing level | Definition |
Level-1b | The full-resolution geolocated radiometric measurements (for each view and each channel), rebinned onto a regular spatial grid. |
Level-2 (L2) | Retrieved cloud variables at full input data resolution, thus with the same resolution and location as the sensor measurements (Level-1b). |
Level-3C (L3C) | Cloud properties of Level-2 orbits of one single sensor combined (averaged) on a global spatial grid. Both daily and monthly products provided through C3S are Level-3C. |
Table 3: Definition of various technical terms used in the document
Jargon | Definition |
Brokered product | The C3S Climate Data Store (CDS) provides both data produced specifically for C3S and so-called brokered products. The latter are existing products produced under an independent programme or project which are made available through the CDS. |
Climate Data Store (CDS) | The front-end and delivery mechanism for data made available through C3S. |
Retrieval | A numerical data analysis scheme which uses some form of mathematical inversion to derive physical properties from some form of measurement. In this case, the derivation of cloud properties from satellite measured radiances. |
Forward model | A deterministic model which predicts the measurements made of a system, given its physical properties. The forward model is the function which is mathematically inverted by a retrieval scheme. In this case, the forward model predicts the radiances measured by a satellite instrument as a function of atmospheric and surface state, and cloud properties. |
TCDR | It is a consistently-processed time series of a geophysical variable of sufficient length and quality. |
ICDR | An Interim Climate Data Record (ICDR) denotes an extension of TCDR, processed with a processing system as consistent as possible to the generation of TCDR. |
CDR | A Climate Data Record (CDR) is defined as a time series of measurements with sufficient length, consistency, and continuity to determine climate variability and change. |
Scope of the document
This document provides a description of the product validation methodology for the Climate Data record (CDR) of the Essential Climate Variable (ECV) Earth 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 for the Climate Data Store, 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 the Science and Technology Facilities Council (STFC), RAL Space from the second Along-Track Scanning Radiometer (ATSR-2) on board the second European Remote Sensing Satellite (ERS-2) which spanned the period 1995-2003 and the Advanced ATSR (AATSR) on board ENVISAT which spanned the period 2002-2012.
The Interim Climate Data Record (ICDR) is the product derived from SLSTR on board of Sentinel-3 and spans the period from January 2017 to present. Validation of this SLSTR derived product for the period from January 2017 to December 2021 is described in this document.
This document summarizes and refers to the methodology presented in the Cloud_cci Product Validation and Intercomparison Report [D1], used for the validation of the TCDR product. The same methodology is applied to the ICDR dataset.
Executive Summary
The ESA Climate Change Initiative (CCI) Earth Radiation Budget Data Record (TCDR) 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 Cloud_cci dataset 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. This TCDR 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 monthly means will also be provided.
The TCDR and ICDR provide level-3 data (monthly means) on a regular global latitude-longitude grid (with a resolution of 0.5°´ 0.5°) and include these products: Outgoing Longwave Radiation (OLR) and Reflected Solar radiation Flux (RSF) at TOA.
This document is divided in different sessions:
- the first section presents a brief description of the Earth 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 with Clouds and Earth Radiation Energy System (CERES) top of atmosphere data.
1. Validated products
The Earth Radiation Budget dataset from polar orbiting satellites consists of: Outgoing Longwave Radiation (OLR) and Reflected Solar radiation Flux (RSF).
The Cloud_cci Earth Radiation Budget CDR is formed by a TCDR, derived from ATSR2-AATSR, brokered from the ESA Cloud_cci project and an ICDR derived from the SLSTR on board of Sentinel-3.
The SLSTR ICDR, both from the individual instruments (version 3.0 and 3.1) 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].
The datasets cover the period from June 1995 to April 2012 (TCDR) of 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), with Sentinel-3b and combined data becoming available from October 2018. These are level 3 products (monthly means) on a regular global latitude-longitude grid (0.5° x 0.5° resolution). Table 1-1 report the values from [D4]
ESA’s Cloud_cci dataset version 3 on clouds is the Climate Data Record used for the estimation of the Earth Radiation Budget1.
The SLSTR based ICDR extends the coverage, with a five year gap, from 2017 onwards and is only available through Copernicus Climate Data Store (CDS).
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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Product name | Accuracy [W/m2] | Accuracy for the ICDR – SLSTR-A [W/m2] | Accuracy for the ICDR – SLSTR-B [W/m2] |
Outgoing Longwave Radiation (OLR) | 1.72 | -1.7 | -1.7 |
Reflected Solar radiation Flux (RSF) | 5.72 | 4.9 | 3.2 |
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1 https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003 |
2. Description of validating datasets
The Earth Radiation Budget TCDR and ICDR datasets are compared against Clouds and Earth Radiation Energy System (CERES) Energy Balanced and Filled (EBAF) fluxes Edition 4.1 Top of atmosphere (TOA) fluxes Edition (Loeb et al., 2018)2.
Both, TCDR and ICDR from SLSTR instruments, are validated with the Clouds and Earth Radiation Energy System (CERES) Energy Balanced and Filled (EBAF) fluxes Edition 4.1 Top of atmosphere (TOA) 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 are based upon daily samples over the entire globe.
More detail on the datasets used for the validation are described in [D1] section 2.4.2 and Annex A.6.
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2 Data available here: https://ceres.larc.nasa.gov/data/ 3 Data available here: https://ceres.larc.nasa.gov/data/ |
3. Description of product validation methodology
The evaluation strategy applied to the TCDR is described in [D1] section 2.4.
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 the reference data record, this is also referred to as standard deviation about the mean.
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).
The Product Validation and Intercomparison Report [D1] is the document that includes validation and intercomparison of the TCDR versus the CERES satellite dataset.
3.1 Comparison with CERES satellite data
TCDR and reference datasets are compared by calculation of multi-annual mean and standard deviation for a common time period (2003-2011). The same methodology is applied to ICDR data, covering the period from January 2017 to December 2021.
Global maps of monthly Outgoing Longwave Radiation (OLR) and Reflected Solar radiation Flux (RSF) are computed for the TCDR, ICDR and the reference dataset. The scores (bias and bc-RMSE) are calculated by including all valid data points pairwise in the CERES and the TCDR/ICDR datasets.
The validation methodology for Outgoing Longwave Radiation (OLR) and Reflected Solar radiation Flux (RSF) at the TOA with the CERES dataset is described in section 3.3.1, 5.1 and 5.2 of [D1].
The stability of the TCDR dataset is defined as the variation of the bias over a multi-annual time period. It is obtained by calculating the linear trend of the bias between the TCDR and reference dataset (in this case CERES dataset).
4. Summary of validation results
The validation results for the TCDR are provided in [D1], sections 3.3.1, 5.1 and 5.2. Section 7 of [D1] provides a summary of the validation results together with recommendations for use. Validation of Cloud_cci (TCDR) radiation products with CERES present a bias of 5.72 W/m² and a standard deviation of 1.64 W/m² for RSF, Bias of 1.72 W/m² and standard deviation of 1.12 W/m² for OLR. The TCDR RSF presents a stability of -0.15 W/m²/decade and +0.52 W/m²/decade for OLR.
Figure 4-1 and 4-2 (from [D4]) show an example of the ICDR monthly products for March 2017 and the equivalent monthly product from CERES.
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Figure 4-2. RSF and OLR from CERES dataset for March 2017.
Preliminary validation (using the monthly mean data from January 2017 to December 2021) of ICDR products with CERES present biases consistent with values found through the TCDR validation (4.9 W/m² for RSF and -1.7 W/m² for OLR).
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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.
Poulsen, C. A., McGarragh, G. R., Thomas, G. E., Stengel, M., Christensen, M. W., Povey, A. C., Proud, S. R., Carboni, E., Hollmann, R., and Grainger, R. G.: Cloud_cci ATSR-2 and AATSR data set version 3: a 17-year climatology of global cloud and radiation properties, Earth Syst. Sci. Data, 12, 2121–2135, 2020. https://doi.org/10.5194/essd-12-2121-2020
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This document has been produced in the context of the Copernicus Climate Change Service (C3S). The activities leading to these results have been contracted by the European Centre for Medium-Range Weather Forecasts, operator of C3S on behalf of the European Union (Delegation Agreement signed on 11/11/2014 and Contribution Agreement signed on 22/07/2021). All information in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose. The users thereof use the information at their sole risk and liability. For the avoidance of all doubt , the European Commission and the European Centre for Medium - Range Weather Forecasts have no liability in respect of this document, which is merely representing the author's view. |
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