Last modified on Jan 17, 2024 20:08

Contributors: O. Bobryshev (Deutscher Wetterdienst)

Issued by: Deutscher Wetterdienst (DWD) / Oleksandr Bobryshev

Date: 14/11/2023

Ref: C3S2_D312a_Lot1.1.2.6-v3.0_202311_PQAD_ECVEarthRadiationBudget_v1.2

Official reference number service contract: 2021/C3S2_312a_Lot1_DWD/SC1

History of Modification

List of datasets covered by this document

Related documents

Acronyms

List of figures

List of tables

General definitions

Scope of the document

This Product Quality Assurance Document (PQAD) provides a description of the product validation methodology for the Top-Of-Atmosphere (TOA) radiation products of the Climate Data Record (CDR) CM SAF Cloud, Albedo, Radiation data record, AVHRR-based, Edition 3 (CLARA-A3), which is a brokered service from EUMETSAT's CM SAF, and its extension with an Interim Climate Data Record (ICDR) derived from the Advanced Very High Resolution Radiometer (AVHRR).

This document mostly refers to the original Satellite Application Facilities on Climate Monitoring (CM SAF) Validation Report [D1] that encompasses an extensive evaluation of the Top-Of-Atmosphere (TOA) radiation Thematic Climate Data Record (TCDR) version 3 product. The ICDR extension of the EUMETSAT CM SAF CLARA-A3 dataset is derived using the same algorithm and processing chain. Additionally, this document refers to the CM SAF Validation Report [D1] with a specific section for the ICDR evaluation.

This document is not part of the official CM SAF documentation but produced solely in the scope of data brokering to the Climate Data Store (CDS).

Executive summary

The TCDR on the Essential Climate Variable (ECV) Earth Radiation Budget is a brokered product of the CLARA-A3 dataset produced by EUMETSAT's CM SAF. The extending ICDR is also a brokered product of EUMETSAT's CLARA-A3 ICDR, also produced by EUMETSAT's CM SAF. Accordingly, this document largely refers to the corresponding EUMETSAT CM SAF original documentation [D1,D3].

The brokering service of the CLARA-A3 data products includes 42 years (1979-2020) of level-3 data (monthly and daily means) on a regular global latitude-longitude grid (with 0.25° x 0.25° resolution), merged from various polar orbiting satellites. It includes two products: the TOA Reflected Solar Flux and the TOA Outgoing Longwave Radiation (OLR). This CDR is brokered from EUMETSAT’s CM SAF. Therefore, this document only refers to the validation results from the original EUMETSAT CM SAF Validation Report [D1]. A brief summary of the validation products (CLARA-A3 in section 1 and reference datasets in section 2) can be found in the following sections.

Section 3 contains a description of the validation methodology, while section 4 gives a brief summary of the validation results.

1. Validated products

The validated dataset is the CLARA-A3 dataset produced by EUMETSAT's CM SAF and brokered to the Climate Data Store (CDS).

The data products brokered from CM SAF CLARA-A3 are:

• the Reflected Solar Flux (RSF),

• the Outgoing Longwave Radiation (OLR).

The CM SAF CLARA TOA radiation data record is derived from successive AVHRR sensors onboard dedicated polar orbiting platforms, including TIROS-N, NOAA, and Metop satellites. AVHRR observations are used to derive spatio-temporal averaged data sets. The final product is available as monthly and daily averages on a regular latitude-longitude grid with a spatial resolution of 0.25° × 0.25° degrees. The TCDR comprises 42 years of data ranging from January 1979 to December 2020. Main characteristics of the CDR are summarized in Table 1-1. The detailed description of the algorithm used to generate the TOA radiation CDR is given in the CM SAF Algorithm Theoretical Basis Document [D3].

Table 1-1: General characteristics of the brokered CLARA-A3 TOA radiation products

2. Description of validating datasets

The validation for the TCDR is based on a set of satellite-based reference data records. They are CERES EBAF Ed. 4.1, CERES SYN1deg, HIRS OLR Daily v01r02, HIRS OLR Monthly v02r07, ERA5 (reanalysis), ISCCP FH MPF ¹ and Cloud_cci v3.0. These are described in detail in the CM SAF Validation Report [D1], Section 4 and are summarized in the following.

2.1 CERES SYN1deg and CERES EBAF Ed 4.1

A brief description of the dataset can be found in [D1], Section 3.1 and 3.2.

Two CDR’s CERES SYN1deg and CERES EBAF Ed4.1 provide level 3 TOA Reflected Solar Flux (RSF) and Outgoing Longwave Radiation (OLR) in all sky and clear sky conditions. Both datasets comprise 22 years (March 2000 – March 2022) of satellite-based measurements derived from the Clouds and the Earth’s Radiant Energy System (CERES) instruments onboard the polar orbiting Terra and Aqua NASA EOS satellites. The CERES instruments are broadband radiometers developed as part of the NASA's Earth Observing System (EOS) program.

The CERES SYN1deg CDR provides estimates of the daily and monthly RSF and OLR fluxes on a 1°x1° nested grid. The CDR uses CERES-observed measurements, enhanced by geostationary observations ² .

The CERES EBAF Ed 4.1 CDR provides estimates of the monthly RSF and OLR fluxes at 1° x 1° regular latitude-longitude grid. This CDR uses improved algorithm of ingesting the geostationary observations. A one-time adjustment to RSF and OLR fluxes within their ranges of uncertainty is made to remove the inconsistency between average global net TOA flux and heat storage in the Earth-atmosphere system.

2.2 HIRS OLR Daily v01r02 and Monthly v02r07

A brief description of the dataset can be found in [D1], Sections 4.3 and 4.4.

The HIRS OLR product is based on the data acquired by the High Resolution Infrared Radiation Sounder (HIRS) instruments measuring radiances in the infrared (IR). The instruments used for this CDR come from four successive versions of the instrument: HIRS/2, HIRS/2I, HIRS/3 and HIRS/4. They are installed onboard the NOAA and MetOp satellites. At the time of writing, the dataset comprises more than 43 years (January 1979 onward).

The version v01r02 of the HIRS OLR CDR provides daily mean Outgoing Longwave Radiation (OLR) in all sky conditions. The OLR estimates from geostationary observations (Geostationary Operational Environmental Satellites (GOES) series of satellites and Meteosat series of satellites) are used to allow accurate temporal integration of the daily mean OLR. This CDR is a level 3 product (daily means) on a regular global latitude-longitude grid with 1° x 1° resolution.

The version v02r07 of the HIRS OLR CDR provides monthly daily mean Outgoing Longwave Radiation (OLR) in all sky conditions. In contrast to HIRS daily CDR, this CDR doesn’t use information from the geostationary satellites. The spatial resolution of the monthly mean HIRS OLR CDR is 2.5° x 2.5°.

2.3 ERA5

A brief description of the dataset can be found in [D1], Section 4.5.

ERA5 is the fifth generation ECMWF reanalysis for the global climate and weather for the past 8 decades. The model is the Integrated Forecasting System (IFS) cycle 41r2 with a 4-D variational analysis (4DVAR) assimilation system. The temporal resolution is 1 hour, and output data are interpolated on a regular latitude-longitude grid of 0.25°x0.25°. The ERA5’s radiation scheme is described in (Hogan, et al. 2018)

2.4 ISCCP-FH

A brief description can be found in [D1], Section 4.6.1.

The International Satellite Cloud Climatology Project (ISCCP-FH) is a third generation, high resolution version of the ISCCP radiative flux products. It includes all upwelling and downwelling, shortwave and longwave radiative fluxes at the top of the atmosphere (TOA), at three levels in the atmosphere, and at the surface using aradiative transfer model RadH-PRD [D4]. The H series ³ CDR covers the period from July 1983 through June 2017 on a regular latitude-longitude grid with 1°x1° resolution.

2.5 Cloud_cci

A brief description can be found in [D1], section 8.5.

European Space Agency’s (ESA's) Cloud Climate Change Initiative (Cloud_cci) provides the Cloud_cci AVHRR-PM version 3.0 dataset based on the afternoon orbit NOAA-satellites. TOA fluxes are calculated using a radiative transfer model (BUGSrad ⁴ ). The Level-3 monthly mean data are provided on a regular latitude-longitude grid of 0.5°x0.5° for the period of 1982-2018.

2.6 Reference datasets for the ICDR

The CLARA-A3 TOA radiation products TCDR used as a reference dataset is described in Section 1 and in [D1], Section 3.

3. Description of product validation methodology

The validation methodology is described in detail in [D1], Section 5 and summarized in the following.

Target requirements for the use of TOA radiation products are formulated in the CM SAF Product Requirement Document [D2]. They include ‘accuracy’ and stability requirements. The CLARA-A3 TOA radiation products cannot be considered independent of CERES products [D3]. The accuracy requirement thus is not “absolute radiometric error”, but an overall bias with respect to a reference data record. The stability is also defined as consistent temporally consistent bias to the reference dataset, over a period of 10 years (decade).

The TOA radiation products are provided at 0.25° x 0.25° spatial resolution, most of the validation is performed at a coarser spatial resolution of 1°x1° of CERES SYN1deg nested grid. Bias for a single grid box with indices (i,j) is calculated as:

\( B_{i,j}=F_{CLARA,i,j} - F_{REF,i,j} \ \ (Eq. 1) \)

, with  \( F_{CLARA} \) and  \( F_{REF} \) as Fluxes for respective datasets in W/m².

The global mean bias is calculated over all biases for a single grid box as follows:

\( MB = \frac{1}{m*n} \sum_{i=1}^m \sum_{j=1}^n w_j(B_{i,j}) = \frac{1}{m*n} \sum_{i=1}^m \sum_{j=1}^n w_j(F_{CLARA,i,j} - F_{REF,i,j}) \ \ (Eq. 2) \)

Where m and n are the number of grid boxes and  \( w_j \) is a meridionally varying weighting factor to correct the equal angle grid boxes to equal area grid boxes (to prevent an overrepresentation of the polar areas).

The global mean absolute bias (MAB), bias corrected is calculated as follows:

\( MAB = \frac{1}{m*n} \sum_{i=1}^m \sum_{j=1}^n w_j|B_{i,j} - MB| = \frac{1}{m*n} \sum_{i=1}^m \sum_{j=1}^n w_j |F_{CLARA,i,j} - F_{REF,i,j} - MB| \ \ (Eq. 3) \)

The MAB is used in the Validation Report [D1] to report the accuracy.

Spatially explicit validation, such as MAB, is sensitive for the spatial gaps. For the purposes of the validation, the spatial gaps in daily OLR and RSF are filled using daily mean ERA5 as ‘surrogate data record’.

CLARA-A3 TOA products ICDR is solely assessed based on how closely it resembles the CLARA-A3 TCDR despite the difference in the input data. TCDR and ICDR parts have the overlapping period of six months from 07/2020 to 12/2020.

4. Summary of validation results

Validation results of TCDR and ICDR are described in detail in [D1], Sections 6-7 and summarized briefly in the following.

The RSF and OLR data products are validated for accuracy and stability against satellite-based reference data records. The achieved accuracy is summarized in Table 4-1 below. Both products OLR and RSF fulfil the threshold requirements, as defined in the CM SAF Product Requirement Document [D2], on both time scales: monthly and daily.

Table 4-1: Summary of the achieved accuracy of the brokered CLARA-A3 TOA radiation products, [D1] Section 1 for RSF and OLR for TCDR and ICDR

4.1 Validation results for Reflected Solar Flux (RSF)

Validation results are described in detail in CM SAF Validation Report [D1], Section 6. The CLARA-A3 product on RSF meets optimal accuracy criterions, as specified in the [D2].

4.2 Validation results for Outgoing Longwave Radiation (OLR)

Validation results are described in detail in CM SAF Validation Report [D1], Section 7. The CLARA-A3 product on OLR meets optimal accuracy criterions, as specified in the [D2].

4.3 Validation results for ICDR products

Validation results are described in detail in CM SAF Validation Report [D1], Section 4.7.

Results of the comparison between the TCDR and ICDR products, show only very small differences, enough to demonstrate that the ICDR products meet all the requirements as the TCDR.

References

Hogan, R. J., & Bozzo, A. (2018). A flexible and efficient radiation scheme for the ECMWF model. Journal of Advances in Modeling Earth Systems, 10, 1990– 2008. doi: 10.1029/2018MS001364

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