Contributors: Karl-Göran Karlsson (SMHI), Nicolas Clerbaux (RMIB), Almudena Velazquez Blazquez (RMIB), Edward Baudrez (RMIB), Gareth Thomas (STFC-RAL)

Issued by: SMHI/Karl-Göran Karlsson

Date: 07/08/2024

Ref: C3S2_D312a_Lot1.3.1.1-2023_TRGAD-ERB_v1.1

Official reference number service contract: 2021/C3S2_312a_Lot1_DWD/SC1

Document citation

Karlsson, K.-G., et al., (2024): C3S Earth Radiation Budget CDRs releases until March 2024: Target Requirements and Gap Analysis Document. Copernicus Climate Change Service. Document reference C3S2_D312a_Lot1.3.1.1-2023_TRGAD-ERB_v1.1. Last accessed on dd/mm/yyyy

Table of Contents

History of modifications

Version

Date

Description of modification

Chapters / Sections

V1.0

30/04/2024

Original version covering all deliveries between start of Phase II until March 2024

All

V1.1

03/06/2024

Document revised following feedback from independent review

All

Related documents

Reference ID

Document

D1

Loeb, N. G., Doelling, D. R., Wang, H., Su, W., Nguyen, C., Corbett, J. G., ... & Kato, S. (2018). Clouds and the earth’s radiant energy system (CERES) energy balanced and filled (EBAF) top-of-atmosphere (TOA) edition-4.0 data product. Journal of Climate, 31(2), 895-918, DOI: https://doi.org/10.1175/JCLI-D-17-0208.1  

D2

CERES_EBAF_Ed4.2 Data Quality Summary (Feb. 1, 2024). Available at:

https://ceres.larc.nasa.gov/documents/DQ_summaries/CERES_EBAF_Ed4.2_DQS.pdf

D3

Meirink, J.F. (KNMI) et al (2022) C3S Service: Key Performance Indicators (KPIs), Copernicus Climate Change Service, Document ref. C3S_D312b_Lot1.0.4.8_201903_UpdatedKPIs_v1.0

https://confluence.ecmwf.int/x/AM_BEQ

Last accessed on 07/08/2024

D4

Velazquez Blazquez A., Clerbaux N., Baudrez E. (RMIB) (2021), C3S Earth Radiation Budget NOAA/NCEI HIRS, Service: Product Quality Assurance Document (PQAD), Copernicus Climate Change Service, Document ref. C3S_D312b_Lot1.2.5.5-v1.2_202103_PQAD_ECVEarthRadiationBudget_v1.2

https://confluence.ecmwf.int/x/8lIiEg

Last accessed on 07/08/2024

D5

Climate Algorithm Theoretical Basis Document (C-ATBD) for Monthly OLR CDR v02r07

http://olr.umd.edu/References/CDRP-ATBD-0097%20Rev%204%20Outgoing%20Longwave%20Radiation%20-%20Monthly%20(01B-06)%20(DSR-1210)%20Final.pdf

D6

Scientific Validation Report for the CM SAF Top of Atmosphere Radiation SEVIRI/GERB Data Records, CM-Product identifier: CM-21301, CM-21321, CM-21331, CM-21351

SAF/CM/RMIB/VAL/GERB, Version 1.1, Date: 13.12.2016.

D7

Lee, H.-T., 2018: Quality Assurance Summary and Results for Monthly and Daily OLR CDR (rev.20180831).

http://olr.umd.edu/References/QA_Summary_OLR-Monthly_and_Daily_CDR_20180831.pdf

D8

[GCOS-107] Systematic Observation Requirements for Satellite-based Products for Climate, 2006

https://library.wmo.int/doc_num.php?explnum_id=3813

D9

[GCOS-154] Systematic Observation Requirements for Satellite-based Products for Climate Supplemental details to the satellite-based component of the Implementation Plan for the Global Observing System for Climate in Support of the UNFCCC, 2011 Update, December 2011. World Meteorological Organization, Geneva, Switzerland. Available from

https://library.wmo.int/doc_num.php?explnum_id=3710

D10

[GCOS-200] Global Climate Observing System, Implementation Plan, 2016. World Meteorological Organization, Geneva, Switzerland. Available from

https://library.wmo.int/doc_num.php?explnum_id=3417

D11

Sentinel-3 SLSTR User Guide, ESA.

https://sentinel.esa.int/web/sentinel/user-guides/sentinel-3-slstr

Last accessed on 07/08/2024

D12

ESA Cloud CCI Algorithm Theoretical Basis Document, v.6.2, 14.10.2019. Available from:

https://climate.esa.int/media/documents/Cloud_Algorithm-Theoretical-Baseline-Document-ATBD_v6.2.pdf
Last accessed on 07/08/2024

D13

ESA Cloud CCI Algorithm Theoretical Basis Document: Community Cloud retrieval for Climate (CC4Cl), v.6.2, 18.10.2019. Available from:

https://climate.esa.int/media/documents/Cloud_Algorithm-Theoretical-Baseline-Document-ATBD-CC4CL_v6.2.pdf
Last accessed on 07/08/2024

D14

ESA Cloud CCI Validation Report for MODIS multi-layer clouds, v1.1, 30.04.2018. Available from:

https://climate.esa.int/media/documents/Cloud_Validation-Report-CC4CL-MLEV_v1.1.pdf
Last accessed on 07/08/2024

D15

Validation Report CM SAF Cloud, Albedo, Radiation data record, AVHRR-based, Edition 3 (CLARA-A3) Top-of-Atmosphere Radiation. Versions 1.1. Available from:

https://www.cmsaf.eu/EN/Documentation/Documentation/Documentation_node.html
Last accessed on 07/08/2024

D16

C3S Target Requirements and Gap Analysis Document (TRGAD) for Cloud product family. Available at:

https://confluence.ecmwf.int/display/CKB/CP%3A+Target+Requirements+and+Gap+Analysis+Document
Last accessed on 07/08/2024

Acronyms

Acronym

Definition

(A)ATSR

(Advanced) Along-Track Scanning Radiometer

ABI

Advanced Baseline Imager

ACRIM

Active Cavity Radiometer Irradiance Monitor

ADM

Angular Dependency Model

AHI

Advanced Himawari Imager

ASCII

American Standard Code for Information Interchange

ATBD

Algorithm Theoretical Basis Document

ATLAS

Atmospheric Laboratory for Applications and Science

AU

Astronomical Unit

AVHRR

Advanced Very High-Resolution Radiometer

BBR

BroadBand Radiometer

BRDF

Bidirectional Reflectance Distribution Function

Cal/Val

Calibration and Validation

C3S

Copernicus Climate Change Service

CC4Cl

Community Cloud for Climate

CCI

Climate Change Initiative (ESA)

CDOP

Continuous Development and Operation Phase

CDR

Climate Data Record

CDS

Climate Data Store

CEDA

Centre for Environmental Data Analysis

CERES

Cloud and Earth Radiant Energy System

CF

Climate and Forecast

CIMSS

Cooperative Institute for Meteorological Satellite Studies

CLARA

Compact Lightweight Absolute Radiometer

CLARA

CM SAF’s Cloud, Radiation and Surface Albedo

CM SAF

Climate Monitoring Satellite Application Facility

CrIS

Cross-track Infrared Sounder

cRMSD

Centered RMSD (equal to bias-corrected RMSD)

DARA

Davos Absolute Radiometer

DIARAD

Differential Absolute Radiometer

DOI

Digital Object Identifier

DQS

Data Quality Summary

EarthCARE

Earth Cloud Aerosol Radiation Explorer

EBAF

Energy Balanced And Filled

ECMWF

European Center for Medium range Weather Forecast

ECT

Equator Crossing Time

ECV

Essential Climate Variable

EEI

Earth Energy Imbalance

ENVISAT

ENVIronment SATellite

EOS

Earth Observing System

EPS-SG

EUMETSAT Polar System-Second Generation

ERA5

5th ECMWF ReAnalysis

ERB

Earth Radiation Budget

ERBE

Earth Radiation Budget Experiment

ERBS

Earth Radiation Budget Satellite

ERM

Earth Radiation Measurement (on Chinese FY-3 satellites)

ERS

European Research Satellite

ESA

European Space Agency

ESSIC

Earth System Science Interdisciplinary Center

EURECA

European Retrievable Carrier

EVC

Earth venture Continuity

FCDR

Fundamental Climate Data Record

FCI

Flexible Combined Imager

FIDUCEO

Fidelity and uncertainty in climate data records from Earth Observations

FOV

Field of View

FORUM

Far-infrared Outgoing Radiation Understanding and Monitoring

FY

Feng-Yun satellites (China)

FMx

Flight Model x

FY

Feng Yung

GCOS

Global Climate Observing System

GEO

Geostationary Orbit

GEOS

Goddard Earth Observing System

GERB

Geostationary Earth Radiation Budget

GMAO

Global Modeling and Assimilation Office

GOES

Geostationary Operational Environmental Satellite

GSIP

GOES Surface and Insolation Products

HIRS

High Resolution Infrared Radiation Sounder

IASI

Infrared Atmospheric Sounding Interferometer

IASI-NG

Infrared Atmospheric Sounding Interferometer – New Generation

ICDR

Interim Climate Data Record

IR

InfraRed

ISCCP(-NG)

International Satellite Cloud Climatology Project (-Next Generation)

ISP-2

Solar Constant Gauge (instrument on Meteor 3 satellite)

ISS

International Space Station

JPSS

Joint Polar Satellite System (cooperation between NOAA and EUMETSAT)

KPI

Key Performance Index

LaRC

Langley Research Center

LEO

Low Earth Orbit

LTDN

Local Time at Descending Node

LW

LongWave

Metop(-SG)

EUMETSAT’s polar orbiting satellites (-Second Generation)

3MI

Multi-viewing, Multi-channel, Multi-polarisation Imaging

MJO

Madden-Julian Oscillation

MODIS

Moderate Resolution Imaging Spectroradiometer

NASA

National Aeronautics and Space Administration

NCEI

National Centers for Environmental Information

NEODC

NERC Earth Observation Data Centre

NERC

Natural Environment Research Council

NESDIS

National Environmental Satellite, Data, and Information Service

NetCDF

Network Common Data Form

NISE

Near-real-time Ice and Snow Extent

NOAA

National Oceanic and Atmospheric Administration

NPP

NPOESS Preparatory Project

NRLTSI

Naval Research Laboratory Total Solar Irradiance

NTC

Non Time Critical

NWP

Numerical Weather Prediction

OpenDAP

Open-source project for a network Data Access Protocol

Obs4MIPS

Observations for climate Model Intercomparison Projects

OLCI

Ocean and Land Colour instrument (Sentinel-3 satellite)

OLR

Outgoing Longwave Radiation

OPeNDAP

Open-source Project for a Network Data Access Protocol

ORAC

Optimal Retrieval of Aerosol and Cloud

OSCAR

Observing Systems Capability Analysis and Review

OSI SAF

Ocean and Sea Ice Satellite Application Facility

PFM

Proto-Flight Model

PI

Principal Investigator

PMO

Physikalisches und Meteorologisches Observatorium

PREMOS

Precision Monitor Sensor

RBI

Radiation Budget Instrument

RMIB

Royal Meteorological Institute of Belgium

RMSD

Root Mean Squared Deviation

RSF

Reflected Shortwave Flux

RTTOV

Radiative Transfer for the Television and Infrared Observation Satellite Operational Vertical Sounder

SATIRE

Spectral And Total Irradiance REconstructions

ScaRab

Scanner for Radiation budget

SEVIRI

Spinning Enhances Visible InfraRed Imager

SIM

Solar Irradiance Monitor

SLSTR

Sea and Land Surface Temperature Radiometer

SMM

Solar Maximum Mission

SOHO

Solar and Heliospheric Observatory

SOLCON

Solar Constant

SORCE

Solar Radiation and Climate Experiment

SOVA

Solar Variability

SOVIM

Solar Variability Irradiance Monitor

SSI

Solar Spectral Irradiance

SW

ShortWave

TC

Triple Collocation

TCDR

Thematic Climate Data Record

TCFM

Temperature Control Flux Monitor

TCTE

Total Solar Irradiance Calibration Transfer Experiment

TIM

Total Irradiance Monitoring

TISA

Time Interpolation and Spatial Averaging

TOA

Top Of Atmosphere

TOT

TOTal wave

TRGAD

Target Requirements and Gap Analysis Document

TRMM

Tropical Rainfall Measuring Mission

TRUTHS

Traceable Radiometry Underpinning Terrestrial- and Helio- Studies mission (ESA Earthwatch mission)

TSI

Total Solar Irradiance

TSIS

Total and Spectral Solar Irradiance Sensor

UARS

Upper Atmosphere Research Satellite

UMD

University of Maryland

USGS

U.S. Geological Survey

VIRGO

Variability of Irradiance and Gravity Oscillations

WMO

World Meteorological Organization

General definitions

Climate data records

Climate data compilations from observations are most often referred to as Climate Data Records (CDRs). However, the data records from satellites may consist of different types of quantities, from original radiances to derived products. Radiance data of climate quality are defined as Fundamental Climate Data records (FCDRs) while data records consisting of satellite-derived geophysical products are defined as Thematic Climate Data Records (TCDRs). In the ideal case the TCDRs should be derived by methods using FCDRs as input. However, if standards for the used radiances have not fulfilled the strict requirements for being classified as FCDRs, these radiances may be denoted Fundamental Data Records (FDRs). Note that TCDRs can currently be based on either FCDRs or FDRs.

 A special case of TCDRs are data records produced with short latency (e.g., shortly after the end of a month). These are called Interim Climate Data Records (ICDRs). The word Interim means that the data record has a higher uncertainty than the original TCDR since it has not been possible to use exactly the same input data as for the TCDR due to the short latency. Interim also means that a user may have to wait for the next edition of the TCDR to get a fully consistent and homogenous climate data record that includes data from the period with ICDR data. Normally ICDRs behave very similar to TCDRs but continuous monitoring of their quality is recommended.

 Note that since ICDRs are continuous extensions of the TCDR they are also delivered at subsequent times in separate batches (numbered 1,2,3, etc.) where each one covers a certain time period (e.g. a number of months). Thus, when formally describing the full ICDR in the text (i.e., using the name specified in the delivery list), the ICDR version number is given but the batch number is written in generic form using letter x, for example ICDR v1.x. This is just to indicate that the batch number is only describing a temporal increment of the product and not any change of the product.


Uncertainty parameters

The meaning of the terms uncertainty, accuracy and error is often difficult to interpret and may be treated differently in various referred documents. In this document, we adopt the following interpretation:

The accuracy, uncertainty or error of an estimated ECV is described by three differently contributing components:

  1. The systematic error
  2. The random error
  3. The time-dependent error

The systematic error is commonly the mean error or the Bias. For non-Gaussian distributions of the error, the median or the mean absolute error can be a more useful quantity.

The random error is commonly the root-mean-squared deviation RMSD. Sometimes, the Bias is subtracted yielding the centred root-mean-squared deviation cRMSD. Note that if the Bias is zero, the two mentioned quantities are equal and may be interpreted as the standard deviation of the error (often denoted standard error).

The time-dependent error is commonly the change in Bias over time (for ECVs over decades). We call this parameter stability

More details on the estimation of these parameters are given in the Report on Updated KPIs (D3).


Testing the quality and consistency of TCDRs and ICDRs

This C3S project also deals with extensions of TCDRs, i.e. products derived from continued processing of the CDRs using the same methods and algorithms as originally used for TCDR production. We denote these CDRs Intermediate Climate Data Records, ICDRs. To evaluate the ICDR compliance with original TCDRs, a different approach in terms of defined requirements is followed. The ICDR is assessed on the basis of the TCDR distribution with respect to a reference validation source. After calculation of this distribution of differences, the ICDR is evaluated against the same reference and a binomial test is applied to verify that 95 % of the difference values lie within the upper and lower bounds of the TCDR difference distribution. The lower and upper bounds of the difference distribution is defined as the 2.5th and 97.5th percentiles of the difference distribution.

For further clarity, a binomial test is a way to test the statistical significance of deviations by referring to a theoretically expected distribution of observations. In this case, we use the theoretically expected distribution of observation differences which is estimated from the difference between TCDR results and corresponding results from a validation source. We now want to test if a corresponding but restricted, i.e., based on a shorter time series of ICDR results, difference distribution is similar in its shape to the original TCDR difference distribution. This can be tested by selecting one upper and one lower percentile in the original distribution (here, the 2.5th and 97.5th percentiles) and check how many samples will fall within or outside this restricted distribution if randomly extracting a number of samples. The resulting distribution of yes and no answers as a function of the number of samples can be described by the binomial distribution (see statistical standard literature for its definition). Consequently, this sample-based difference distribution from the ICDR can then be numerically compared with what could be expected from the reference distribution based on the TCDR. Based on this, one can judge whether the ICDR results are representative or not for the TCDR results. Deviations here would then indicate particular problems for the ICDR products (assuming that the character of reference observations does not change).

More details on the estimation of errors and uncertainty parameters are given in the Report on Updated KPIs (D3). 


Product requirements

Depending on the data record producer, different product requirements may be applied and they are used to evaluate validation results. An often-used way to handle this is to define several levels of requirements where each level is linked to specific needs or priorities. A three-level approach like the following is rather common:

Requirement

Description

Threshold requirement:

A product should at least fulfill this level to be considered useful at all. Sometimes the term ‘Breakthrough” is used instead.

Target requirement:

This is the main quality goal for a product. It should reach this level based on the current knowledge on what is reasonable to achieve.

Optimal requirement:

This is a level where a product is considered to perform much better than expected given the current knowledge.


Satellite product levels

Satellite-based products are often described as belonging to the following condensed description of processing levels, each one with different complexity and information content:

Level

Description

Level-0:

Raw data coming directly from satellite sensors, often described as sensor counts.

Level-1:

Data being enhanced with information on calibration and geolocation.
Three sub-levels are often referred to:

Level-1a: Data with attached calibration and geolocation information

Level-1b: Data with applied calibration and attached geolocation information

Level-1c: Data with applied calibration and additional layers of geolocation, satellite viewing and solar angle information

Level-2:

Derived geophysical variables at the same resolution and location as L1 source data.

An often-used Level-2 variety is the following:

Level-2b: Globally resampled images, two per day per satellite, describing both ascending (passing equator from south) and descending (passing equator from north) nodes. Resampling is based on the principle that the value for the pixel with the lowest satellite zenith angle is chosen in case two or several swaths are overlapping.

Level-3:

Gridded data with results accumulated over time (e.g., monthly means).

A more comprehensive definition of all processing levels is given here:

https://www.earthdata.nasa.gov/engage/open-data-services-and-software/data-information-policy/data-levels.


Radiation terms

Since satellite measurements are primarily about radiation measurements in different parts of the spectrum, some definitions or synonyms need to be explained. Roughly, the spectrum is usually sub-divided into one part where solar radiation dominates and one part where radiation emitted by the Earth and the atmosphere dominates.

The solar part is usually referred to as “visible (VIS)” radiation and covers approximately wavelengths smaller than 1 µm. Two sub-regions are often referred to, namely “ultraviolet (UV)” for radiation below approximately 0.38 µm, and “near-infrared (NIR)” for radiation between 0.78 µm and 1 µm (but sometimes claimed to continue up to 2.8 µm).

The part dominated by emitted radiation from the Earth is often referred to as “thermal” radiation. Common synonyms used are “infrared (IR)” or “terrestrial” radiation. Also here, we have several sub-regions defined. The “short-wave infrared (SWIR)” region is approximately defined by wavelengths between 1 µm and 2.5 µm. The “medium-wave infrared (MWIR)” region is approximately defined by wavelengths between 2.5 µm and 5 µm. The “long-wave” region, often simply referred to as just “infrared” to represent the bulk majority of radiation emitted by the Earth, defines radiation from approximately 5 µm up to about 1 mm. Radiation above 1 mm up to 10 cm is denoted “microwave (MW)” radiation.


Special terms

The term “AVHRR-heritage” is frequently used in the TRGAD documents. By this is meant spectral channels of other sensors than the AVHRR which show a close similarity (or heritage) to the AVHRR channels, i.e., having almost the same spectral characteristics.

A product is said to be “brokered” when an existing data record from an external source (i.e., not produced exclusively within this C3S project) is handled. This also means that target requirements for these products are set to their achieved validation results since the product was not developed and validated in the C3S project.

We can get a better idea of how accurate the final product values are by using the method of “error propagation”. It means that the retrieval method is capable of accounting for errors or uncertainties in the measurements or products used to derive the final product, e.g., radiances, input or ancillary data. In this way, the uncertainty of the final products can be estimated.

Radiation fluxes for radiation budget estimations are sometimes described as being “balanced”. It comes from the fact that instrument uncertainties for radiation budget measurements are often too high to be capable of providing accurate estimations of the net radiation fluxes at the top of atmosphere. Thus, balancing is a form of bias correction based on investigations of energy balance from other observations and model studies.

Calibration of radiances are sometimes described as based on “vicarious” methods. This indicates that there is no on-board mechanism on the satellite that provides the necessary calibration information. Consequently, parameters used in calibration equations have to be estimated retrospectively from historic data by use of additional references. For example, Earth surfaces which are considered to be invariant or stable are often used as reference targets for calibration of visible radiances.

An “OPeNDAP” server is an advanced software solution for remote data retrieval (see https://www.opendap.org/).

“Triple Collocation (TC)” is a large-scale validation technique by which error variances and data-truth correlation coefficients of three independent datasets can be estimated without a specific reference observation. For further details, see Stoffelen (1998).

List of figures

List of tables

Table 1‑1: Matching between internal C3S versions and official CERES versions

Table 1‑2: Content of the CERES EBAF file that is brokered in the C3S CDS

Table 1‑3: CERES instrument history. Instruments and platforms used here are marked in green

Table 1‑4: Main input and auxiliary data used in processing the CERES EBAF edition 4 CDR

Table 1‑5: Characteristics of the monthly and daily means HIRS OLR CDRs

Table 1‑6: Characteristics of the Cloud_cci ERB TCDR and SLSTR ICDR

Table 1‑7: Characteristics of the CLARA-A3 ERB products

Table 1‑8: Total Solar Irradiance space instruments (see acronym list for full explanation of acronyms) 

Table 1‑9: Characteristics of the C3S TSI product (v3.x)

Table 2‑1: Key Performance Indicators (KPIs) or target requirements (i.e., fulfilled requirements by the CERES Team) for OLR and RSF products from the CERES EBAF RSF and OLR products

Table 2‑2: KPI percentile requirements (2.5 % and 97.5 %) for the ICDR RSF and OLR differences against ERA5 fluxes

Table 2‑3: GCOS requirements for OLR and RSF (GCOS-154 and GCOS-200)

Table 2‑4: GCOS requirements for OLR (GCOS-154 and GCOS-200) compared with HIRS OLR TCDR achievements

Table 2‑5: Target requirements for Top-of-atmosphere Earth Radiation Budget components as defined by GCOS-154 ([D9])

Table 2‑6: Key Performance Indicators (KPIs) or target requirements (i.e., fulfilled requirements by the ESA-CCI-CLOUDS project) for OLR and RSF products from the ESA_CCI_AATSR TCDR v3.0

Table 2‑7: Key performance indicators (KPIs) for the Cloud_cci SRB record, to be applied to the SLSTR ICDR data

Table 2‑8: Target requirements for CM SAF CLARA-A3 OLR and RSF TCDR products

Table 2‑9: KPI percentile requirements (2.5 % and 97.5 %) for the CLARA A3 ICDR (v3.x)

Table 2‑10: Key Performance Indicators (KPIs) or target requirements for TSI TOA TCDR products

Table 2‑11: KPI percentile requirements (2.5 % and 97.5 %) for the TSI ICDR (v3.x)

Table 2‑12: GCOS requirements (from [D10]) concerning the total and spectral solar irradiance (TSI and SSI)

Table 3‑1: HIRS (-like) instrument version per satellite


Scope of the document

This document provides relevant information on requirements and gaps for the Earth Radiation Budget (ERB) Essential Climate Variable (ECV).

The document is divided into three parts. Part 1 describes products the present document refers to. Part 2 provides target requirements for the products. Part 3 provides a past, present, and future gap analysis for the products and covers both gaps in the data availability and scientific gaps that could be addressed by further research activities (outside C3S).

Executive summary

The Earth Radiation Budget (ERB) describes the radiation conditions and energy exchanges at the top of the atmosphere (TOA). From this information it is theoretically possible to estimate the Earth Energy Imbalance (EEI) which is the fundamental driver of climate change on Earth. Thus, the ERB products are central for all climate change studies.

ERB products are primarily dealing with the estimation of outgoing radiation fluxes at the top of atmosphere since this is what satellite sensors generally measure. However, even if the incoming fluxes can be reasonably estimated using the present knowledge of the Total Solar Irradiance (TSI), one has to realize that even the TSI is varying. Thus, some data records falling under the ERB portfolio also deal with measurements of the incoming fluxes. This is necessary since the estimation of EEI is calculated as a subtraction of two large quantities (i.e., incoming minus outgoing fluxes) which results in a very small quantity. Thus, any small variation in the TSI as well as small biases in the fluxes must be estimated and considered.

All ERB data records provided in this C3S project are based on measurements from polar orbiting satellites in a Low Earth Orbit (LEO) since the requirement to have similar measurements from a chain of satellites in the Geostationary Orbit (GEO) is presently not fulfilled. The sensors used for estimating ERB regarding the outgoing fluxes are the following:

  • CERES: Cloud and Earth Radiant Energy System
  • MODIS: Moderate Resolution Imaging Spectroradiometer
  • AVHRR: Advanced Very High Resolution Radiometer
  • HIRS: High Resolution Infrared Radiation Sounder
  • (A)ATSR: (Advanced) Along-Track Scanning Radiometer
  • SLSTR: Sea and Land Surface Radiometer

More details on these instruments can be found at the World Meteorological Organization (WMO) Observing Systems Capability Analysis and Review (OSCAR) site (https://space.oscar.wmo.int/).
For the incoming fluxes (i.e., incoming solar radiation or the Total Solar Irradiance), measurements from a suite of several satellite missions for research in the period 1979 until present have been used.

Five different ERB data records are provided. These are

  1. Earth Radiation Budget CERES EBAF Ed4.2

  2. The HIRS OLR daily v01r02 and monthly v02r07

  3. Earth Radiation Budget ESA_CCI_AATSR TCDR v3.0 + SLSTR-based ICDR v3.1.1 + v4.0

  4. Earth Radiation Budget TCDR and ICDR AVHRR CLARA v3.0 (CLARA-A3)

  5. Earth Radiation Budget TSI TOA TCDR v3.0 + ICDR v3.x

The TCDR notation describes measurements over a long period while the ICDR notation describes continuous extensions of the same data record produced in near real time (see General definitions for a more detailed explanation of TCDR and ICDR).

The first dataset above is based on combined measurements from the CERES and MODIS instruments, the second on HIRS measurements, the third on measurements from the (A)ATSR and SLSTR instruments, the fourth on measurements from the AVHRR instrument and the fifth on various experimental and research instruments measuring the Total Solar Irradiance (TSI).

The target requirements for the ERB product from CERES (first in the list above) are expressed as the Root Mean Squared Difference (RMSD) to the validation reference for both longwave and shortwave upward fluxes and it is set to 2.5 W m-2. The stability requirements for longwave fluxes are set to 0.2 W m-2 decade-1 and to 0.3 W m-2 decade-1 for shortwave fluxes. The ICDR requirements are set to ensure that ICDR results are not deviating significantly from TCDR results (full details are given in specific User Requirement sub-sections). The CERES EBAF Ed4.2 data coverage spans the period 2000-present and is secured for the next 10-15 years (including the follow-up instrument called Libera). The use and definition of ERB parameters are partly dependent on non-measurable quantities like ocean heat uptake and is therefore vulnerable to changes in the assessment of these quantities. A need to improve angular dependency models for some instruments has been identified. Since in the future the CERES EBAF product will be based on only broadband observation done during the afternoon, it is suggested to develop ERB products for EUMETSAT Polar System-Second Generation (EPS-SG) satellites. An opportunity to better characterize the error in CERES level 2 products is foreseen after the launch of the EarthCARE satellite (currently foreseen end of May 2024).

Due to the long period coverage, from 1979 onward, the HIRS Outgoing Longwave Radiation (OLR) TCDR (i.e., the second data record in the list above), maintained by NOAA as part of its CDR program, is also delivered in this C3S project. Target requirements are similar to the previously described data record. The data coverage of the delivered data record runs from 1979 to the present. The HIRS instrument is not present on current Metop-C and NOAA-20 and following satellites. Therefore, HIRS-like data are generated from the Infrared Atmospheric Sounding Interferometer (IASI) and the Cross-track Infrared Sounder (CrIS) instruments on current and future satellites. Thus, continuation of the HIRS OLR record is secured.

ERB estimates of outgoing fluxes derived from (A)ATSR are also provided from the ESA Cloud_cci project (i.e., the third data record in the list above). This data record is also being extended with the same analysis applied to the SLSTR instruments aboard the Sentinel-3 satellite (i.e., the SLSTR ICDR). These products differ from the others, as they are derived through radiative transfer calculations from cloud and aerosol retrieval output, along with surface radiation budget (described in the TRGAD documents for Cloud products [D16] and for Surface Radiation products). Target requirements are generally set to the WMO Global Climate Observing Systems (GCOS) requirements of a mean absolute bias (MAB) of 1 Wm-2. Data coverage runs from mid-1995 to early 2012 for the (A)ATSR TCDR, with the SLSTR ICDR running from January 2017 to the present. Regarding the future availability of SLSTR data, a measurement prolongation beyond the current Sentinel-3A and Sentinal-3B satellites is planned for with two more satellites (Sentinel 3C and Sentinel 3D, which are scheduled for launch in 2024 and 2028, respectively).

Recently, ERB estimates from the AVHRR instrument are provide in the CM SAF CLARA-A3 data record. The record combines a long coverage (1979 onward) and a fine spatial resolution (0.25°x 0.25°). Target requirements are set to 4 Wm-2 for both shortwave and longwave fluxes and with a stability requirement of 1 Wm-2decade-1. The ICDR requirements are set to ensure that ICDR results are not deviating significantly from TCDR results (full details are given in specific User Requirement sub-sections).

Finally, a composite CDR of daily Total Solar Irradiance (TSI) from a large set of space instruments, is also delivered in this C3S project (i.e., data record number 5 in the list above). This data record provides measurement of the variation in the solar constant since 1979 until present date (i.e., latest ICDR delivery covers until end of 2023). Target requirements for this data record are given by GCOS requirements and are set to a relative accuracy of 0.04 % and a stability of 0.01 % per decade. The ICDR requirements are set to ensure that ICDR results are not deviating significantly from TCDR results (full details are given in specific User Requirement sub-sections). Although a couple of new sensors have been put in orbit (e.g. CLARA, DARA), the operational availability of TSI measurements is rather uncertain in the future, especially at the end of the Solar and Heliospheric Observatory (SOHO) mission. Possibly, there will only be measurements from the United States Total Irradiance Monitor (TIM) instruments in the future.

1. Product description

The Earth Radiation Budget products describe the radiation conditions and energy exchanges at the top of the atmosphere (TOA). From this information it is theoretically possible to estimate the Earth Energy Imbalance (EEI) which is the fundamental driver of climate change on Earth. Thus, the ERB products are central for all climate change studies.

For estimation of EEI, three components must first be estimated, namely the reflected solar radiation (or the Reflected Solar Flux, RSF), the Outgoing Longwave Radiation (OLR) and the incoming solar radiation, linked to the Total Solar Irradiance (TSI). In the following, five ERB data records are described where four of them estimate the outgoing fluxes (RSF, OLR) and one the incoming flux (TSI). For estimating the outgoing fluxes, measurements from the Cloud and Earth Radiant Energy System (CERES) sensor, the High-Resolution Infrared Radiation Sounder (HIRS), the combined (Advanced) Along-Track Scanning Radiometer ((A)ATSR) and Sea and Land Surface Radiometer (SLSTR) sensors, and the Advanced Very High-Resolution Radiometer (AVHRR) are used. For TSI estimations, sensors on a number of experimental and research satellites are used. 

1.1 Earth Radiation Budget CERES TCDR v1.0 + TCDR v2.0 + ICDR v2.x (OLR, RSF)

Table 1‑1 shows the matching between the (internal) C3S version and the official CERES versioning. From April 2022 onward, the near real time EBAF production (ICDR) is only done as Ed 4.2 following the drift of Aqua orbit that makes it unsuitable for the EBAF.

Table 1‑1Matching between internal C3S versions and official CERES versions.

C3S internal version (not to be shown to CDS users)

CERES edition

Input data (FM = Flight Model)

v1.0

Ed 4.1

  • Mar 2000 to June 2002: Terra only (FM1, FM2)

  • July 2002 to Mar 2022: Terra (FM1,FM2) + Aqua (FM3,FM4)

v2.0

v2.x (ICDR)

Ed 4.2

  • Mar 2000 to June 2002: Terra only (FM1, FM2)

  • July 2002 to Mar 2022: Terra (FM1,FM2) + Aqua (FM3,FM4)

  • Apr 2022 onward: Terra (FM1,FM2) + NOAA-20 (FM6)

1.1.1 The CERES EBAF CDR

The CERES Energy Balanced and Filled (EBAF) data is “brokered” in the Copernicus Climate Data Store (CDS). The EBAF product is based on the data acquired by the Cloud and Earth’s Radiant Energy System (CERES) instruments (Figure 1-1). The CERES instruments are broadband radiometers developed as part of the NASA's Earth Observing System (EOS) program. Wielicki et al. (1996) provide a description of the CERES instrument as well as of the CERES mission.


Figure 1‑1: CERES instrument (left) and program logo (right).

The Top-of-Atmosphere (TOA) EBAF file provides a total of 14 parameters which are given in Table 1-2. Among those, only the shortwave and longwave fluxes in all-sky condition are accessible via the CDS. The incoming solar flux is also available via the CDS but as an ancillary field of the RSF. It is worth mentioning that these fluxes are provided at a reference level of 20km, to ease the comparison with climate/NWP models (see Loeb et al, 2002).


Table 1‑2: Content of the CERES EBAF file.

Variable

Long name

Units

Brokered in CDS

toa_sw_all_mon

Top of The Atmosphere Shortwave Flux, Monthly Means, All-Sky conditions

W/m²

yes

toa_lw_all_mon

Top of The Atmosphere Longwave Flux, Monthly Means, All-Sky conditions

W/m²

yes

solar_mon

Incoming Solar Flux, Monthly Means

W/m²

yes

1.1.2 Input data

Table 1‑3 details the instrument names and platforms on which the 7 CERES instruments have been launched. The CERES EBAF edition 4.1 relies on the FM1 to FM4 instruments from the EOS Terra and Aqua satellites. The edition 4.2 adds data from FM6 on NOAA-20.

Table 1‑3: CERES instrument history. Instruments and platforms used in the C3S project are marked in green.

Instrument

Platform

Operation period

Used in EBAF edition 4.1

Used in EBAF edition 4.2

PFM

TRMM

Jan. to Aug. 1998

(+limited oper. in 1999 and 2000)

no

no

FM1

Terra

Mar. 2000 onward

yes

yes

FM2

Terra

Mar. 2000 onward

yes

yes

FM3

Aqua

Jul. 2002 onward

yes

yes

FM4

Aqua

Jul. 2002 onward

yes

yes

FM5

NPP Suomi

Feb. 2012 onward

no

no

FM6

NOAA-20

Jan. 2018 onward

no

yes

A brief summary of the input data is given in Table 1‑4, while a comprehensive description is provided by Loeb et al. (2018) [D1].

Table 1‑4: Main input and auxiliary data used in processing the CERES EBAF edition 4 CDR.

Input and auxiliary data used in processing the CERES EBAF edition 4

CERES

The CERES shortwave (SW) and total wave (TOT) filtered radiances are the main input of the processing. By subtraction, the longwave (LW) radiance can be estimated. The SW and LW radiance are then “unfiltered” to account for some spectral variation of the instrument sensitivity. Then, empirical Angular Dependency Models (ADM) are used to estimate the hemispheric fluxes. Starting from the instantaneous fluxes, the Time Interpolation and Spatial Averaging (TISA, Doelling et al., 2013 and 2016) is used to estimate daily and monthly means values of the flux. This processing makes used of data from geostationary satellites (GEO hereafter). Finally, the fluxes are “balanced” to create the EBAF CDR (Loeb et al., 2009).

MODIS

The MODIS observations are processed by the CERES team to estimate cloud properties in each CERES footprint. This is an important input to apply ADM. The CERES cloud processing is described in various papers (e.g. Minnis et al., 2011).

GEO

The geostationary data are used in the TISA subsystem to improve the diurnal cycle modelling, especially in regions that exhibit diurnal cycles of cloud properties (e.g., convection).  

Meteorological

data

Meteorological data are used in different parts of the processing. For CERES EBAF, the GEOS 5.4.1, a CERES-restricted effort of the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center, is used.

1.1.3 Algorithm name and version, bias correction

The data comes from EBAF Edition 4.1 (DOI : 10.5067/TERRA+AQUA/CERES/EBAF-TOA_L3B004.1) and Edition 4.2 . However, as the data is fetched directly from NASA’s OPeNDAP servers, the version that is offered through CDS in the future may be more recent. For CERES EBAF, the ICDR has the same characteristics as the TCDR described in the previous sections. There is no change of input data or algorithm. The CERES team regularly adds new data in the EBAF record but does not make a formal difference between “validated” TCDR and “interim” ICDR. The TCDR/ICDR distinction is done in C3S to indicate difference in the level of validation.

The TOA fluxes have been “balanced” in the EBAF. This consists of a kind of bias correction to make the data compliant with the best estimate of the Earth Energy Imbalance (EEI, see Loeb et al, 2018; [D1]).

1.2 Earth Radiation Budget HIRS OLR monthly v02r07 and daily v01r02

1.2.1 The HIRS OLR TCDR

The HIRS OLR product is based on the data acquired by the High Resolution Infrared Radiation Sounder (HIRS) instruments (Figure 1‑2) measuring radiances in the infrared (IR).

Figure 1‑2:  HIRS instrument (left) and NOAA logo (right)

The HIRS OLR CDR is widely used by the climate community as an important component of the ERB (Schreck et al., 2018). The OLR can also be used as an accurate indicator of the convection and useful to diagnose major tropical circulation patterns and its temporal and spatial features (e.g., the Madden-Julian Oscillation, MJO). OLR is also used for climate model evaluation. It is worth mentioning that the HIRS OLR CDR is, along with the CERES products, the only data currently published in Obs4MIPS (Observations for Model Intercomparison Projects, https://esgf-node.llnl.gov/projects/obs4mips/) concerning the ERB. An example of a product is given in Figure 1‑3.

Figure 1‑3: Illustration of the monthly mean HIRS OLR v02r07 (unit is W/m²).

1.2.2 Input data

The CDR compiles data from 4 successive versions of the HIRS instrument: HIRS/2, HIRS/2I, HIRS/3 and HIRS/4. They have been launched on the NOAA and Metop satellites. The HIRS instrument series is now discontinued and there is no HIRS on Metop-C or on NOAA-20 and onward. Significantly improved performances are obtained by incorporating data from the Cross-track Infrared Sounder (CrIS, on satellites Suomi-NPP, NOAA-20 and NOAA-21) and the Infrared Atmospheric Sounding Interferometer (IASI, on all Metop satellites). Data from these instruments are included in this product.

1.2.3 General characteristics of the product

The general characteristics of the monthly and daily mean HIRS OLR CDRs are given in Table 1‑5.

Table 1‑6: Characteristics of the monthly mean HIRS OLR CDR.

                                                                                                                     General characteristics of monthly and daily mean HIRS OLR

NOAA version

V02r07

V01r02

Spatial resolution

2.5° x 2.5°

1° x 1°

Grid

Regular lat-lon

Regular lat-lon

Temporal resolution

Monthly mean

Daily mean

Time period

January 1979 to present (note that new months
are added with a latency of +/- 1 months).

January 1979 to present (note that new days
are added with a latency of +/- 10 days).

Format

NetCDF version 4, CF compliant

Reference level for the fluxes

20km above mean sea level (see Loeb et al, 2002)

Geophysical quantity

Outgoing Longwave Radiation (OLR), also known as “longwave flux” or “thermal flux”

1.3 Earth Radiation Budget ESA_CCI_AATSR TCDR v3.0 + SLSTR-based ICDR v3.1.1 and v4.0 (OLR, RSF)

 1.3.1 The Cloud_cci ERB CDR and ICDR

This section describes the ERB products of the Cloud_cci (A)ATSR v3.0 data record, which we will refer to as Cloud_cci v3, and its extension with the same retrieval scheme applied to the Sea and Land Surface Radiometer (SLSTR), which is produced specifically for C3S. The Cloud_cci v3 record is based on Along-Track Scanning Radiometer 2 (ATSR-2) and Advanced Along-Track Scanning Radiometer (AATSR) observations onboard the ESA 2nd European Research Satellite (ERS-2) and ENVISAT satellites. Together, the data record provided by these two instruments is often abbreviated to (A)ATSR. The SLSTR instrument, which is the successor to (A)ATSR, is on board the Copernicus Sentinel-3 platform [D11].

Observations are available on a 1x1 km grid, which closely matches the true instrument spatial resolution globally and the final CDR is compiled in a regular global grid with 0.5° latitude-longitude resolution for monthly averages. The covered time period of the Cloud_cci data record ranges from June 1995 to April 2012 (with a 6-month gap from January – June 1996) and the SLSTR extension provides coverage from January 2017 to June 2022 at the time of writing. SLSTR data for 2021 will be delivered shortly, with the coverage then extending on a six-monthly basis.

The SLSTR instrument was designed as the operational successor to the (A)ATSR instruments, using the same measurement principles and techniques, improving them based on the experience gained with the (A)ATSRs, and continuing the 17-year data record provided by ATSR-2 and AATSR (21 years if ATSR-1 is included). Unfortunately, the development time of the Copernicus Sentinel satellites and the demise of ENVISAT in 2012, broke the continuity of this dataset, with an almost five-year gap between the end of the AATSR record and the availability of SLSTR. Despite this, SLSTR products can be considered an ICDR extension of the (A)ATSR TCDR, for the following reasons:

  1. The (A)ATSR and SLSTR instruments were conceived with the goal of creating long-term data records for climate monitoring. Consistency and stability are at the core of their design.

  2. The instruments are very similar – SLSTR provides a wider swath, some additional channels, increases the spatial resolution of the shortwave channels and alters the viewing geometry compared to (A)ATSR. But the differences in the instrument and orbital characteristics between AATSR and SLSTR are comparable to those between ATSR-2 and AATSR.

The product was produced using the Community Cloud for Climate (CC4Cl) processing chain, which is based around the Optimal Retrieval of Aerosol and Cloud (ORAC) retrieval scheme, both of which are described in detail in [D12, D13] and by Sus et al. (2018) and McGarragh et al. (2018). The primary product of this retrieval chain are cloud properties, but these are used, in conjunction with aerosol properties also derived from (A)ATSR or SLSTR using the ORAC retrieval, as inputs to the Bugsrad radiative transfer scheme (described by Stephens et al., 2001) to derive broadband radiative fluxes at both the surface and TOA. The two values provided to the CDS in the Cloud_cci v3 ERB product are the Reflected Solar Flux (RSF) and Outgoing Longwave Radiation (OLR).

1.3.2 Input data

The Cloud_cci TCDR products were based on the third reprocessing of the AATSR-multimission archive, which included vicarious calibration of the shortwave channels over the entire data record to correct for long-term calibration drift (Smith, 2012). SLSTR ICDR products are based on collection 3 of the “non-time critical (NTC)” SLSTR level 1 archive. NTC products are products delivered with a latency of 1 month or longer. In addition, the CC4Cl processing chain makes use of the following auxiliary datasets:

  • USGS Digital Elevation Map (USGS, 1996, described by https://doi.org/10.5066/F7GB230D)

  • ERA-Interim surface and atmospheric profile temperatures and pressure (Dee et al., 2011)

  • ERA-Interim profiles of moisture content and Ozone concentrations (Dee et al., 2011)

  • ERA-Interim snow depth and albedo (Dee et al., 2011)

  • National Snow and Ice Data Center Near-real-time Ice and Snow Extent (NISE) sea ice concentration (Brodzik and Stewart, 2016).

  • ERA-Interim 10 m u and v wind components (Dee et al., 2011).

  • MODIS-based land surface bidirectional reflectance distribution function (BRDF) data (MCD43C1 Collection 6, (Schaaf and Wang, 2015)).

  • Land surface emissivity from the Cooperative Institute for Meteorological Satellite Studies (CIMSS) “Baseline Fit” database.

  • Solar and Heliospheric Observatory (SOHO) and Solar Radiation and Climate Experiment (SORCE) incoming total solar irradiance.

For Level-1 data outside the temporal coverage of these datasets (for example, ATSR-2 data prior to the 1999 launch of MODIS products), climatologies based on these data are used. In the case of the SLSTR ICDR, ERA-5 data is used rather than ERA-Interim (for details, see [D12]).

1.3.3 General characteristics of the product

The general characteristics of the product are given by .

Table 1‑6: Characteristics of the Cloud_cci ERB TCDR and SLSTR ICDR

General characteristics of monthly mean ERB


Spatial resolution

1 × 1°

Grid

Regular latitude-longitude grid

Temporal resolution

Monthly mean

Time period

TCDR: 1st Jun. 1995 to 8th Apr. 2012 (with 6-month gap from 22nd Dec. 1995 to 1st Jul. 1996)

ICDR: 1st January 2017 to 31th June 2022 (v3.1 and v4.0)

Format

NetCDF v4, CF compliant

Reference level for the fluxes

NA

Geophysical quantity

Reflectance Solar Flux (RSF) at TOA

Outgoing Longwave Radiation (OLR) at TOA

Units

W/m²

1.4 Earth Radiation Budget TCDR and ICDR AVHRR CLARA v3.0 (CLARA-A3)

 1.4.1 The Cloud, Albedo and Radiation (CLARA) dataset

We refer to the Cloud TRGAD [D16] for a general description of the CLARA-A3 data record. The Earth Radiation Budget products, i.e. the Reflected Solar Flux (RSF) and Outgoing Longwave Radiation (OLR), are new products introduced in the third edition (A3) of the CLARA portfolio.

 1.4.2 Input data

For the RSF product, the main input data are the reflectances in the channels 1 and 2 of the AVHRR instrument. The OLR product is based on the brightness temperatures in the channels 4 and 5. The processing also exploits the CLARA-A3 cloud products and some ancillary information from ERA5 (and ERA5T for the ICDR) and sea ice information from OSI SAF.

 1.4.3 General characteristics of the product

The general characteristics of the CLARA-A3 Earth Radiation Budget (ERB) products are given in Table 1-7.

Table 1‑7: Characteristics of the CLARA-A3 ERB products

General characteristics of the CLARA-A3 ERB products


Spatial resolution

0.25° × 0.25°

Grid

Regular latitude-longitude grid

Temporal resolution

  • Monthly mean

  • Daily mean

Time period

  • TCDR: 1st Jan. 1979 to 31st Dec. 2020.

  • ICDR: 1st January 2021 to present

Format

NetCDF v4, CF compliant

Reference level for the fluxes

Top Of Atmosphere (TOA)

Geophysical quantity

Reflectance Solar Flux (RSF) at TOA

Outgoing Longwave Radiation (OLR) at TOA

Units

W/m²

1.5 Earth Radiation Budget TSI TOA TCDR v3.0+ ICDR v3.x

 1.5.1The C3S Total Solar Irradiance CDR

The Total Solar Irradiance (TSI) quantifies the amount of solar energy that reaches the Earth per unit surface perpendicular to the Sun–Earth direction at the mean Sun–Earth distance (i.e. at 1 astronomical unit, AU). It is a fundamental variable governing the climate system, and is recognized as an ECV by the GCOS. Within the C3S, a long composite CDR is constructed from TSI measurements from an ensemble of space instruments. The measurements of the individual instruments are first put on a common absolute scale, and their quality is assessed by intercomparison. Then, the composite time series is the average of all available measurements, on a daily basis. Figure 1‑4 shows the daily values of the TSI (grey) as well as a rolling mean (black). The 11-years cycle of solar activity is clearly visible.

Figure 1‑4: Time series of daily C3S TSI (grey) and rolling mean calculated over periods of 121 days (black). The graph also shows the rolling mean for the NRLTSI2 (green) and SATIRE (red) models, and the community Consensus TSI (blue).

1.5.2 Input data

Table 1‑8 lists the main platforms and instruments for TSI measurement and indicates those used to construct the C3S composite (green-marked rows). 

Table 1-9: Total Solar Irradiance space instruments (see acronym list for full explanation of acronyms). The instruments used in v3.x are highlighted in green.

 Instrument

 Platform(s)

Used

In C3S

Operation period(s)

TCFM


Mariner-6

Mariner-7

No

1969

ERB

Nimbus 6

No

1975

Nimbus 7

Yes

1978

ACRIM 1

SMM

Yes

1980-1989

Solcon 1

Spacelab 1

No

1983

ERBE

ERBS

Yes

1984-2003

NOAA-9

No

1985-1989

ACRIM 2

UARS

Yes

1991-2001

SOLCON 2

Atlas 1

No

1992

SOVA 1

Eureca

No

1992-1993

SOVA 2

Eureca

No

1992-1993

ISP-2

Meteor-3 7

No

1994

DIARAD/VIRGO

SOHO

Yes

1996-present

PMO06V-A/VIRGO

SOHO

Yes

1996-present

ACRIM 3

ACRIMSAT

Yes

2000-2014

TIM

SORCE

Yes

2003-2020

DIARAD/SOVIM

ISS

No

2008

SIM

FY 3A

No

2008-2015

SOVA

Picard

Yes

2010-2014

PREMOS

Picard

Yes

2010-2014

SIM

FY 3B

No

2011-present

TIM

TCTE

Yes

2013-2019

SIM

FY 3C

No

2013-present

TIM

TSIS-1

Yes

2018 - present

1.5.3 General characteristics of the product

The general characteristics of the product are given in Table 1‑9.

Table 1‑9: Characteristics of the C3S TSI product (v2.x and v3.x).

General characteristics of daily mean C3S TSI

Spatial resolution

NA

Grid

NA

Temporal resolution

Daily mean

Time period

  • TCDR v3.0: 1st Jan. 1979 to 31st Dec. 2020

  • ICDR v3.1: 1st Jan. 2021 to 6th June 2023

  • ICDR v3.2: 1st Jan. 2021 to 31st Dec 2023

ICDR v3.latest  latency

about 10 days

Format

ASCII file

Reference level for the fluxes

NA

Geophysical quantity

Total Solar Irradiance (TSI) also known as “solar constant”
at 1 astronomical unit for the Earth-Sun distance.

Units

W/m²

2. User Requirements

This section describes the requirements which have been set to be achieved by the described products. Requirements can be set at different levels (as explained in the section with General definitions) but here we will focus on what is called the Target Requirements. These requirements define the main goals for data producers which have to be fulfilled by their products. Requirements are specified by the use of various accuracy parameters which are also listed in the section with General definitions. Observe that for brokered products the target requirements are set to the achieved validation results since these products are not developed and tested within the C3S project.

Concerning products to be used in climate monitoring, requirements for what should be achievable through Earth Observation systems are generally defined by the World Meteorological Organisation (WMO) Global Climate Observation System (GCOS) expert panel. However, these requirements are generally oriented towards the capability and resolution of climate models with a rather course spatial resolution while many products listed here are focusing more on the monitoring of local and regional scale conditions. Also, they are often not attainable using existing or historical observing systems. Thus, GCOS requirements are not always identical to the requirements listed here since also other user groups than the climate modelling community have contributed in setting the requirements. However, the relation to GCOS requirements are discussed below for each individual product.

2.1 Earth Radiation Budget CERES EBAF Ed4.2 (OLR, RSF)

 2.1.1Summary of target requirements (KPIs)

The accuracy and stability requirements (here only expressed as the random component RMSD) for the CERES TCDR are given in Table 2‑1. The CERES team has demonstrated that the fluxes in EBAF edition 4 CDR meet these accuracy and stability requirements [D2]. These values have been adopted as KPIs for the OLR and RSF TCDR [D3].

Table 2‑1: Key Performance Indicators (KPIs) or target requirements (i.e., fulfilled requirements by the CERES Team) for OLR and RSF products from the CERES EBAF RSF and OLR products. 

Variable

KPI: accuracy (Bias)

Fulfilled by CERES CDRs

KPI: decadal stability

Fulfilled by CERES CDRs

RSF

2.5 Wm-2

0.3 Wm-2decade-1

OLR

2.5 Wm-2

0.2 Wm-2decade-1

For the ICDR period, the C3S approach (where ICDR products are evaluated using binomial tests based on data from an external reference) is followed, using ERA5 fluxes as the external reference. Resulting KPIs are given in Table 2‑2.

Table 2‑2: KPI percentile requirements (2.5 % and 97.5 %) for the ICDR RSF and OLR differences against ERA5 fluxes.

Variable

KPI: lower percentile

(2.5 %)

KPI: higher percentile

(97.5 %)

RSF

0.4 Wm-2

2.3 Wm-2

OLR

-2.4 Wm-2

-1.3 Wm-2

2.1.2 Discussion of requirements with respect to GCOS and other requirements

The target requirements are only partly in line with the GCOS requirements (GCOS-154 [D9] and GCOS-200 [D10]) (see Table 2‑3) for the ECV Earth Radiation Budget [D4] in terms of accuracy and stability. Indeed, while the stability KPIs are fully consistent with GCOS, the accuracy KPI for the C3S product (2.5 Wm-2) is less strict that that of GCOS (1 Wm-2). It should be noted that, in the previous release of the GCOS requirements (GCOS-107, [D8]), the accuracy requirement for OLR and RSF was set at 5.0 Wm-2. The applied target requirements here for accuracy are therefore in-between the requirements of GCOS-107 and GCOS-154.

Table 2‑3: GCOS requirements for OLR and RSF (GCOS-154 and GCOS-200).

Requirements

GCOS (Target)

CERES TCDR v1.0 + ICDR v1.x

Spatial resolution

100km

100km

Temporal resolution

Monthly (resolving diurnal cycle)

Monthly (resolving diurnal cycle)

Accuracy

1 Wm-2

2.5 Wm-2 for the Terra + Aqua period. Slightly less (~ 3.5 Wm-2)
before July 2002 (Terra only) and after April 2022 (NOAA-20 only).

Stability

OLR: 0.2 Wm-2decade-1

RSF: 0.3 Wm-2decade-1

OLR: 0.2 Wm-2decade-1

RSF: 0.3 Wm-2decade-1

2.1.3 Data format and content issues

The EBAF data are available at NASA as NetCDF CF, through an OPeNDAP server. There are no known issues with the data format or content of the files. Due to technical limitations, the OPeNDAP features offered by NASA, such as subsetting or reprojection, are not yet available to CDS users.

2.2 Earth Radiation Budget HIRS OLR monthly v02r07 and daily v01r02

2.2.1 Summary of target requirements (KPIs)

As for CERES EBAF, the Key Performance Indicator for accuracy is set to 2.5 Wm-2 for the HIRS monthly mean OLR CDR. In terms of stability, the KPI is set to 0.2 Wm-2 decade-1 (i.e., same values as in Table 2‑1).

2.2.2 Discussion of requirements with respect to GCOS and other requirements

Table 2‑4 provides the GCOS-154 ([13]) requirement for OLR where also the used target requirements for the HIRS-based product is given.

As for CERES, the target requirements are only partly compliant with GCOS as the accuracy requirement is less strict that that of GCOS. Thus, it has been changed from 1 Wm-2 to 2.5 Wm-2. In v02r07, the spatial resolution of the monthly mean HIRS OLR CDR is 2.5° x 2.5°, therefore not strictly compliant with the 100 km (approx. 1°) recommended by GCOS. The user who requires finer spatial resolution can consider downloading the daily mean HIRS OLR product which is provided at a 1° x 1° spatial resolution, but this product is not part of the CDS and must be downloaded from the NOAA servers.

Table 2‑4: GCOS requirements for OLR (GCOS-154 and GCOS-200) compared with HIRS OLR TCDR achievements.

Requirements

GCOS (Target)

HIRS OLR TCDR V1.0

NOAA version v02r07

HIRS OLR TCDR v2.0

NOAA version v01r02

Spatial resolution

100km

2.5°x2.5°

1°x1°

Temporal resolution

Monthly (resolving diurnal cycle)

Monthly mean

Daily mean

Accuracy

1 W/m²

2.5 W/m²

2.8 W/m²

Stability

0.2 W/m²/decade

0.2 W/m²/decade

0.2 W/m²/decade

In terms of temporal resolution, only monthly mean is provided, without attempting to resolve the diurnal cycle.

2.2.3 Data format and content issues

The HIRS OLR TCDR data is produced at the National Centers for Environmental Information (NCEI) of the U.S. National Oceanic and Atmospheric Administration (NOAA). The data is provided as a NetCDF CF file, through an OPeNDAP server. There are no known issues with the data format or content of the files. Due to technical limitations, the OPeNDAP features offered by NOAA/NCEI, such as subsetting or reprojection, are not yet available to CDS users. The HIRS OLR TCDR ATBD [D8] contains a detailed description of the product format and content. The “landing page” for the HIRS OLR TCDR is https://doi.org/10.7289/V5222RQP.

2.3 Earth Radiation Budget ESA_CCI_AATSR TCDR v3.0 + SLSTR-based ICDR v3.1.1+v4.0 (OLR, RSF)

2.4.1 Summary of target requirements (KPIs) - TCDR

The target requirements for the Cloud_cci TCDR are identical to the requirements defined by the GCOS initiative ([D9]) and they are listed in Table 2‑5.

Table 2‑5: Target requirements for Top-of-atmosphere Earth Radiation Budget components as defined by GCOS-154 ([D9]).

GCOS quantity

Corresponding Cloud_cci variable

GCOS targets

Top-of-atmosphere ERB longwave

Outgoing longwave radiation (OLR)

  • Frequency: Monthly (resolving diurnal cycle)
  • Resolution: 100 km
  • Measurement uncertainty: 1 Wm-2 on global mean
  • Stability: 0.2 Wm-2dec-1

Top-of-atmosphere ERB shortwave

Reflected solar radiation (rsf)

  • Frequency: Monthly (resolving diurnal cycle)
  • Resolution: 100 km
  • Measurement uncertainty: 1 Wm-2 on global mean
  • Stability: 0.3 Wm-2dec-1

The Cloud_cci product, and the SLSTR extension (further dealt with in the next section), achieve or exceed the frequency and resolution requirements (however, they do not resolve the diurnal cycle, as this is not possible with a single low-Earth-orbit platform).

2.4.2 Summary of target requirements (KPIs) - ICDR

The Cloud_cci (A)ATSR products are brokered from the ESA CCI programme and cannot be altered within the scope of C3S_312b_Lot1. Therefore, target requirements are in this case set identical to the achieved results in previous validation efforts (Table 2‑6).

Table 2‑6: Key Performance Indicators (KPIs) or target requirements (i.e., fulfilled requirements by the ESA-CCI-CLOUDS project) for OLR and RSF products from the ESA_CCI_AATSR TCDR v3.0. 

Variable

KPI: accuracy (Bias)

Fulfilled by ESA-CLOUD-CCI

KPI: decadal stability

Fulfilled by ESA-CLOUD-CCI

RSF

5.72 Wm-2

-0.15 Wm-2decade-1

OLR

1.72 Wm-2

 0.52 Wm-2decade-1

The ESA_CCI_AATSR TCDR v3.0 dataset forms the basis of the KPIs for the SLSTR based ICDR. The KPIs for the ERB product are based on comparison against the NASA Clouds and the Earth's Radiant Energy System (CERES) instruments. These comparisons are represented as the 2.5 and 97.5 percentiles of the distribution of differences between (A)ATSR or SLSTR monthly-mean values and the corresponding CERES values (corrected for the mean seasonal cycle). These values, calculated from the 12-year (A)ATSR CDR are summarized in Table 2‑7.

Table 2‑7: Key performance indicators (KPIs) for the Cloud_cci SRB record, to be applied to the SLSTR ICDR data.

Variable

KPI: lower percentile

(2.5 %), W/m2

KPI: higher percentile

(97.5 %), W/m2

OLR Monthly mean

-1.17

0.898

RSF Monthly mean

-1.36

1.15

2.4.3 Discussion of requirements with respect to GCOS and other requirements

Requirements are consistent with GCOS. See Section 2.4.1.

2.4.4 Data format and content issues

The Cloud_cci v3 cloud property products are defined using standard data formats (netCDF) and map projections (regular latitude/longitude grids). Meta data definitions follow the Climate & Forecast conventions (http://cfconventions.org/).

 2.4 Earth Radiation Budget TCDR and ICDR AVHRR CLARA v3.0 (CLARA-A3)

 2.4.1 Summary of target requirements (KPIs) - ICDR

The CLARA-A3 products are brokered from CM SAF and the target requirements for these products have been set as part of CM SAF requirement review process. They are summarized in Table 2-8.

Table 2-8: Target requirements for CM SAF CLARA-A3 OLR and RSF TCDR products.

Variable

Accuracy (Bias)

Decadal stability


RSF

4.0 Wm-2

1 Wm-2decade-1

OLR

4.0 Wm-2

1 Wm-2decade-1

For the ICDR period, the C3S approach is followed, using modeled RSF and OLR from ERA5 reanalysis. Results are presented in Table 2-9. The anomalies of fluxes with respect to ERA5 should remain within the 2.5% and 97.5% percentiles of the anomalies observed during the TCDR periods (1st Jan. 1979 to 31st Dec. 2020 for CLARA-A3).

Table 2‑9: KPI percentile requirements (2.5 % and 97.5 %) for the CLARA A3 ICDR (v3.x).

Variable

KPI: lower percentile

(2.5 %)


KPI: higher percentile

(97.5 %)

RSF v3.x

-2.39 Wm-2

3.55 Wm-2

OLR v3.x

-2.70 Wm-2

1.55 Wm-2

2.4.2Discussion of requirements with respect to GCOS and other requirements

The spatial and temporal resolution agree well with the latest GCOS requirements, with however the exception that the diurnal cycle is not resolved in CLARA-A3. Concerning the accuracy and stability, the dataset complies with the CM SAF requirements (Table 2-8) but not the GCOS ones.


2.5 Earth Radiation Budget TSI TOA TCDR v3.0 + ICDR v3.x

2.5.1 Summary of target requirements (KPIs)

The Key Performance Indicators for the TCDR are shown in Table 2‑10 below. As there is no “ground truth” for these KPIs, their fulfillment is assessed indirectly through intercomparison with other datasets and models (see details in the corresponding TSI v3.0 PQAR report):

Table 2‑10: Key Performance Indicators (KPIs) or target requirements for TSI TOA TCDR products.

Variable

KPI: accuracy (RMSD)

KPI: decadal stability

TSI

1 Wm-2

0.3 Wm-2decade-1

For the ICDR period, the C3S approach is followed, using modeled TSI from proxy data (the NRLTSI2 CDR) and results are presented in Table 2‑11. The anomalies of TSI with respect to the model should remain within the 2.5% and 97.5% percentiles of the anomalies observed during the TCDR periods (1st Jan. 1979 to 31st Dec. 2020 for v3.0).

Table 2‑11: KPI percentile requirements (2.5 % and 97.5 %) for the TSI ICDR (v2.x and v3.x).

Variable

KPI: lower percentile

(2.5 %)

KPI: higher percentile

(97.5 %)

TSI v2.x

0.869 Wm-2

1.829 Wm-2

TSI v3.x

0.130 Wm-2

0.562 Wm-2

2.3.2 Discussion of requirements with respect to GCOS and other requirements

Concerning the solar irradiance, the GCOS considers 2 products as essential for the global climate: The Total Solar Irradiance (TSI) and the Solar Spectral Irradiance (SSI). The TSI is defined as the “Flux density of solar radiation at TOA (Wm-2)” while the SSI is defined as “the solar irradiance measured as a function of wavelength (Wm-2μm-1)”. The GCOS requirements are given in Table 2‑12. Currently, the CDS only provides TSI data.


Concerning the incoming solar energy, the GCOS considers 2 products as essential for the global climate: the Total Solar Irradiance (TSI) and the Solar Spectral Irradiance (SSI). The TSI is defined as the “Flux density of solar radiation at TOA (Wm-2)” while the SSI is defined as “the solar irradiance measured as a function of wavelength (Wm-2μm-1)”. The GCOS requirements are given in . Currently, the CDS only provides TSI data.

Table 2‑12: GCOS requirements ([D10]) concerning the total and spectral solar irradiance (TSI and SSI).

GCOS Target requirements Total Solar Irradiance (TSI)

 TSI TOA ICDR v2.x + TCDR v3.0

Spatial resolution

NA

NA

Temporal resolution

Daily

Daily

Accuracy

0.04% (i.e.  0.54 W/m² 

1 Wm-2

Stability

0.01%/decade (i.e.  0.14 W/m²/decade) 

0.3 Wm-2 decade-1

GCOS Target requirements Spectral Solar Irradiance (SSI)

 Not delivered to C3S

Spatial resolution

NA

NA

Temporal resolution

Daily

NA

Spectral resolution

1 nm < 290 nm;

2 nm 290-1000 nm;

5 nm 1000-1600 nm;

10 nm 1600-3200 nm;

20 nm 3200-6400 nm;

40 nm 6400-10020 nm;

20000 nm spacing up to 160000 nm

NA

Accuracy

0.3% (200-2400nm)

NA

Stability

1%/decade (200-2400nm)

NA

2.3.3 Data format and content issues

Following the standard practice in the community, the TSI time series is released as a simple ASCII file. The current format provides TSI values as a function of the day, and in addition, many additional fields, including the original time series of the various instruments used to construct the composite.


3. Gap Analysis

3.1 Description of past, current and future satellite coverage

Quantification of the Earth Radiation Budget with broadband radiometers already has a long history. The design of the instruments included narrow (scanning) and wide (non-scanning) Field of View (FOV), and instruments have been flown on both Low Earth Orbit (LEO) and geostationary (GEO) satellites. A review of available data is provided by Dewitte and Clerbaux (2017).

3.1.1 Earth Radiation Budget CERES EBAF Ed4.2 (OLR, RSF)

CERES EBAF incorporates uninterrupted observations provided by the CERES instruments on EOS satellites since 2000 (for Terra), 2002 (for Aqua) and 2022 (for NOAA-20). Since measurements from polar orbiting satellites are not capable of describing the full diurnal cycles of various ECVs due to poor temporal sampling, the data are combined with geostationary observations to mitigate the error. It is expected that this approach, combining one or several CERES or CERES-like broadband radiometers (i.e. Libera) in LEO with GEO data of the latest generation, will continue during the next 10 to 15 years.

To maintain continuity, NASA has issued a call for Earth Venture Continuity (EVC) for the procurement, within a limited cost envelop of 150 M$, of an instrument sharing many aspects of the CERES instrument. The instrument’s data shall be processed with the existing CERES ground segment. The proposal’s evaluation was completed in early 2020 and the selected mission is called Libera (in the Roman mythology Libera is the daughter of Ceres, the goddess of agriculture). The first Libera instrument will fly on the fourth Joint Polar Satellite System (JPSS-4) satellite, in late 2027. The afternoon observation is therefore safeguarded.

The CERES team has estimated that if either S-NPP or NOAA-20 are terminated prior to Libera, there is a 1 in 3 chance of a data gap in the ERB record [Norman Loeb, CERES Science Team meeting Oct. 2023].

As the Terra mission has lasted well past its design lifetime and the NASA EVC only considers the afternoon orbit, there will be a data gap in the morning observations, at end of the Terra mission (probably end 2026 or beginning of 2027).


3.1.2 Earth Radiation Budget OLR_HIRS TCDR v1.0 (monthly mean) and v2.0 (daily mean)

High-resolution Infra-Red Sounder (HIRS) instruments have been flown on a total of 18 satellites, as detailed in Table 1‑5 and Table 3‑1. The sounding mission is now carried out with advanced hyperspectral sounders like CrIS and IASI, as the HIRS instrument is not on-board NOAA-20 (and following) and Metop-C. The CrIS and IASI data have been incorporated in the record on 1st November 2023 and the period from 2007 onward has been reprocessed.

Table 3-1: HIRS (-like) instrument version per satellite.

HIRS instrument version

 Satellites

HIRS

Nimbus-6

HIRS/2

TIROS-N, NOAA-6, NOAA-7, …  until NOAA-14

HIRS/3

NOAA-15, NOAA-16, NOAA-17

HIRS/4

NOAA-18, NOAA-19, Metop-A, Metop-B

CrIS

S-NPP, NOAA-20, NOAA-21

IASI

Metop-A, Metop -B, Metop -C

Currently, data are acquired from the NOAA-18 and -19 (afternoon) and Metop-A and –B (morning). Although noise levels in some of the HIRS channels do not meet requirements, it has not affected the generation of the CDR. The main problem to monitor in the coming years will be the drift in Equator Crossing Time (ECT) for those 4 satellites. For C3S, the monitoring is done through the KPI. On longer timescales, HIRS-like data from CrIS and IASI (and successors as IASI-NG) will be considered for inclusion in the CDR.

3.1.3 Earth Radiation Budget ESA_CCI_AATSR TCDR v3.0 + SLSTR based ICDR v3.1.1+v4.0 (OLR, RSF)

The Cloud_cci v3 dataset is based on radiances provided by the ATSR series of sensors. These instruments flew on sun-synchronous polar orbiting satellites with daytime equatorial crossing times in the mid-morning: 10:30 Local Time on Descending Node (LTDN) for ATSR-2 and 10:00 LTDN for ENVISAT, with both satellites sharing the same ground track. There were 14.3 orbits per day, meaning 28 equatorial overpasses per-day, with measurements covering a total of 18% of equatorial circumference of the Earth (with equally spaced 512 km swaths). The observation frequency increased at higher latitudes (with a maximum of 14 observations per day at the poles) due to increasing overlaps between the satellite swaths. Both sensors provided the same seven channels (and used the same conical dual-viewing geometry), but not all channels were provided at all times, or at full digitization rate from ATSR-2, due to limitations of the data bandwidth provided by the ERS-2 platform. Over ocean regions, ATRS visible channels were often only provided in a 256 pixel “narrow-swath” mode. The channels provided by both instruments were centered at 0.55, 0.67, 0.87, 1.6, 3.7, 10.8, 12.0 mm and the filter band passes were very similar between instruments. Despite the low-data rate modes of ATSR-2, the combination of the very similar instrument specifications, very close orbital parameters and the lack of any significant orbital drift in the ERS-2 and ENVISAT satellites mean that ATSR-2 and AATSR provide a highly consistent data record.

The TCDR from Cloud_cci v3.0 begins with the launch of ERS-2 in mid-1995 and continued until the failure of ENVISAT in April 2012. Due to instrument problems, there is a six-month data gap in the ATSR-2 record from January to June 1996.

There is an overlap of 1 year of data between the ATSR-2 and AATSR platforms, between mid-2002 (when ENVISAT was launched) and mid-2003 (when the onboard data storage on ERS-2 failed). There is additional ATSR-2 data available up-to 2009, but this is not global as data could only be collected when the satellite was within line-of-sight with a ground receiving station, and has not been included in the TCDR. There is some scope to push the coverage of the ATSR cloud record back to 1991, by using the ATSR-1 instrument (onboard ERS-1), which also flew in a similar orbit to its successors. However, ATSR-1 lacked the shortwave channels (apart from the 1.6 mm) channel, which would reduce the information available in daylight retrievals, as well as the estimation of shortwave radiative fluxes, and would represent a significant inhomogeneity in the TCDR.

The extension of the ATSR TCDR makes use of SLSTR sensors onboard the Sentinel-3 platform. SLSTR represents a significant upgrade over (A)ATSR, providing a wider swath, two satellites within interleaved orbit swaths, additional channels and an operational system for near realtime acquisition of data. The Sentinel-3s have a very similar orbit to ENVISAT and the ERS satellites, with a sun-synchronous orbit with an LTDN of 10:00, and 14.3 orbits per-day. However, there is slightly longer than a 4-year gap between the end of the (A)ATSR record and the first SLSTR data. There are several options available to fill this gap, as ORAC can be applied to most radiometers with similar channels to those provided by ATSR. Indeed, cloud CDRs of ORAC applied to both MODIS and AVHRR already exist, having been produced in the Cloud_cci program, but have not been brokered to the CDS.

We suggest that addressing the (A)ATSR/SLSTR data gap, by linking the two datasets with a third source of data which overlaps with each should be a priority for Copernicus, and would likely be readily achievable given the necessary support. There are several datasets which provide similar measurements to the (A)ATSR/SLSTR ERB dataset (including the other C3S products discussed in this report) and which overlap both (A)ATSR and SLSTR temporally. Such data could be used to assess the consistency of the (A)ATSR TCDRs and SLSTR ICDRs, but this remains to be done for the ERB dataset.

It should also be noted that ORAC could be applied to the VIIRS and MetImage instruments, which could complement the SLSTR ICDR.

Regarding the future availability of SLSTR data, a measurement prolongation beyond the current Sentinel-3A and Sentinal-3B satellites is planned for with two more satellites (Sentinel 3C and Sentinel 3D, which are scheduled for launch in 2024 and 2028, respectively).

3.1.4Earth Radiation Budget TCDR and ICDR AVHRR CLARA v3.0 (CLARA-A3)

The description of the past, current and future satellite coverages used as input of the CM SAF CLARA dataset is provided in the Cloud TRGAD document [D16]. The analysis is not repeated here.

3.1.5 Earth Radiation Budget TSI TOA TCDR V3.0+ ICDR v3.x

Table 1‑8 lists the main space-borne instruments for TSI observation and indicates the ones used to construct the C3S composite CDR.

Concerning the new ICDR, the v3.x (from 1st January 2021 onward), solar irradiance data are acquired from 2 instruments on the SOHO satellite (DIARAD/VIRGO and PMO6) and the TIM instruments on TSIS-1 (on the ISS) missions. The SIM instruments on FY-3B and FY-3C are not (yet) validated enough for inclusion in the composite. It is the same for the Compact Lightweight Absolute Radiometer (CLARA) instrument. Also, long-term data provision has still to be secured before inclusion of these data in an operational ICDR. The European instruments on SOHO (launched in Dec. 1995!) are still used in v3.x, but they are well beyond their expected lifetime and are expected to be discontinued soon. So, there is a significant probability that TSI observations will be provided only by the U.S. TIM (or TIM-like) instruments in the future. This could limit our capacity to detect instrument degradation and to assess the CDR stability.


3.2 Development of processing algorithms

3.2.1 Earth Radiation Budget CERES EBAF Ed4.2 (OLR, RSF)

Generally speaking, the processing of CERES data in the EBAF CDR is of excellent quality, and, in recent editions, fully exploits the advanced angular sampling capabilities of the instrument. The quality of the fluxes in some particular regions and/or conditions could benefit from further improvements; e.g., cloud retrieval over Polar Regions. Efforts are being made in this direction and improvements in the CERES data processing can be expected in the coming years (e.g. in Edition 5). The record will also benefit from improved ancillary data (in particular the NWP fields from the latest reanalysis), the homogeneity of the MODIS radiance used for the cloud retrieval, and use of the Fundamental Climate Data Record (FCDR) from GEO satellite observations needed for the TISA.

In EBAF, the closure of the Earth radiative budget depends on an assessment of ocean heat content. Given recent developments in this field, consolidation of the ocean heat content (and trend) is to be expected in the coming years, with a direct bearing on the top-of-atmosphere fluxes.

3.2.2 Earth Radiation Budget HIRS OLR monthly v02r07 and daily v01r02

Due to discontinuation of the HIRS instruments from NOAA-20 and Metop-C onward, developments have been made to incorporate HIRS-like data from the Infrared Atmospheric Sounding Interferometer (IASI) and Cross-track Infrared Sounder (CrIS) instruments. These developments led to a first reprocessed version of the datasets from 2007 onward (called v02r07-reprocessed and v01r02-reprocessed in the CDS). The inclusion of CrIS and IASI will be fully described in the next version of the datasets (v02r08 for monthly and v01r03 for daily), to be released soon.

The first brokered OLR products from HIRS were the monthly mean produced by NCEI/NOAA at a spatial resolution of 2.5°x2.5°. This (coarse) spatial resolution seems to be motivated by continuation of the OLR operational record that started a long time ago and is widely used. Since several years, daily mean OLR from HIRS are also available at a finer resolution of 1°x1°. These data are now also brokered in the CDS. It is straightforward to aggregate the daily data to provide monthly mean data at 1°x1° resolution, consistently with the CERES EBAF record.


3.2.4 Earth Radiation Budget ESA_CCI_AATSR TCDR v3.0 and SLSTR-based ICDR v3.1.1 + v4.0 (OLR,RSF)

The stability and quality of the input data is the key parameter which influences the reliability of the Cloud_cci v3 CDRs. The (A)ATSR TCDR is based on version 3 of the “AATSR multimission archive” maintained by CEDA and the UK National Earth Observation Data Centre (NEODC). This record incorporates the latest calibration corrections (including long-term drift corrections from vicarious calibration) and represents the most consistent and accurate record of radiances from the (A)ATSR record. A future update to this record would make a reprocessing of the Cloud_cci TCDR possible.

In the case of the SLSTR ICDR, the status of the level 1 radiances is considerably less stable. Data from early in the SLSTR record has considerably worse calibration and geolocation than more recent data. When a fully reprocessed version of the data record becomes available in the future, regeneration of the cloud ICDR would be possible.

EUMETSAT has provided updated calibration corrections to SLSTR shortwave channels, communicated through the Sentinel-3 Scientific Validation Team (S3VT), which have been applied retrospectively. However, there is not yet any information on the stability of the SLSTR calibration over time.

3.2.4.1 Adaptions of the ORAC scheme to better exploit SLSTR

As mentioned above, SLSTR provides some additional channels over the earlier AATSR instruments. Of particular note is the new 1.3 mm channel, which, due to its location in a water-vapour absorption feature, it particularly sensitive to the presence of high-altitude clouds. Utilizing this channel in the retrieval scheme itself is unlikely to be beneficial, as accurate knowledge of the water vapour profile is needed to accurately model the radiances. However, the use of this channel in prior cloud-detection and characterization has been studied under the Cloud_cci+ project and an assessment of its impact on the quality of ORAC cloud retrievals is underway.

3.2.4.2 Forward model improvements

Further improvements to the forward modelling of clouds for the ORAC retrieval scheme are also underway. In particular:

  • The SLSTR ICDR makes use of ERA-5, rather than the ERA-Interim used for the TCDR.
  • The spectral dependence of cloud scattering and absorption will be modelled across the bandpass of the instrument channels (rather than at the channel centre as previously).
  • At present cloud is modelled as an infinitesimally thin layer within an atmosphere modelled by RTTOV. The modelling of cloud geometric thickness effects will also be investigated in the upcoming Cloud_cci+ project.
  • The use of new ice cloud optical properties will also be investigated, as these become available.

Improvements in the propagation of uncertainty from L2 products to gridded L3 products is also under investigation.

 3.2.4 Earth Radiation Budget TCDR and ICDR AVHRR CLARA v3.0 (CLARA-A3)

Several improvements of the CM SAF CLARA processing algorithms are foreseen in view of the generation of the CLARA-A3.5 and CLARA-A4 editions. The Cloud TRGAD document [D16] discusses the developments of the processing algorithms which are common to the different CLARA products, e.g. the improvement of the FCDR record.

3.2.5 Earth Radiation Budget TSI TOA TCDR v3.0 and ICDR v3.x

Currently, there are concerns about the instruments aging more rapidly than implied by the stated stability. For instance, Dewitte and Nevens (2016) suspected some drift in the TIM/SORCE time series. When compared with NRLTSI2, the ACRIM3 timeseries also shows some kind of temporal change. If this is confirmed, better accounting for aging should be implemented in future releases of the CDR. The difficulty here is obviously to find a good reference to assess the aging. Having an instrument on the ISS (e.g. TIM on TSIS-1) provides the opportunity for instrument ground recalibration at the end of the operational mission.

More specifically, since 2010 the DIARAD/VIRGO timeseries exhibits a kind of annual cycle when compared to other TSI instruments and models (SATIRE, NRLTSI2). This is likely a thermal effect that could be corrected using housekeeping data (such as shutter temperature). The DIARAD/VIRGO team is aware of this.

3.3 Methods for estimating uncertainties

3.3.1 Earth Radiation Budget CERES TCDR v1.0 + v2.0 and ICDR v2.x (OLR, RSF)

The CERES team has invested a considerable effort in the validation of the EBAF record. A summary of the findings is in the Data Quality Summary (DQS) for EBAF edition 4 [D2]. Overall, the stability of the CERES EBAF product complies with the GCOS requirements. In terms of accuracy, uncertainties are 2.5 W m-2 for SW and LW for the monthly mean product at 1°x1° resolution.

3.3.2 Earth Radiation Budget HIRS OLR TCDR v1.0 (monthly mean) and v2.0 (daily mean)

The product has been intensively evaluated by Dr. Hai-Tien Lee from University of Maryland (UMD), the PI of the HIRS OLR product. The results are summarized in the “Quality Assurance Results and Summary” document [D7], available at:

http://olr.umd.edu/References/QA_Summary_OLR-Monthly_and_Daily_CDR_20180831.pdf

The best reference datasets for the validation of the HIRS OLR CDR are the CERES EBAF and CERES SYN1deg-month products. The validation is then restricted to the 2000-onward period (with slightly lower quality before the inclusion of CERES Aqua in 2002). 

Efforts to validate the CDR accuracy and stability in the pre-CERES era remain very relevant. Stability might have been affected by HIRS instrument degradation but also from the significant changes in the ECT of the NOAA satellites. Intercomparisons with atmospheric reanalysis provide some insight on the CDR stability. Such intercomparisons could be a piece of the puzzle but, alone, are not accurate enough to address the stability at the 0.2 W m-2 decade-1 level.

In [D6], an intercomparison is performed between HIRS OLR, CERES EBAF and the CM SAF GERB/SEVIRI data records following the Triple Collocation (TC) methodology. Assuming that the errors affecting those 3 records are uncorrelated, it is possible to estimate the individual error for the 3 CDRs. Further assessment on the applicability of the TC methodology to ERB datasets would be highly beneficial to narrow the uncertainty estimate.

3.3.3 Earth Radiation Budget ESA_CCI_AATSR TCDR v3.0 + SLSTR-based ICDR v3.1.1 + v4.0 (OLR,RSF)

The ORAC retrieval scheme provides propagated uncertainties on the retrieved cloud parameters, but these are not propagated through the broadband flux calculations at present. Thus, no uncertainty estimates are provided in the (A)ATSR TCDR or SLSTR ICDR products, aside from the standard deviation of the level-2 pixels included in each monthly-mean grid box. Thus, uncertainty information is only available through validation activities.

 3.3.4 Earth Radiation Budget TCDR and ICDR AVHRR CLARA v3.0 (CLARA-A3)

The uncertainties of the TOA radiation products (RSF, OLR) in the CLARA-A3 TCDR have been quantified by intercomparison with different reference datasets as described in the CM SAF validation report [D15].

For the ICDR, a routine monitoring is performed as part of the C3S project. The monitoring is based on the global RSF and OLR biases with respect to ERA5. These biases are expected to remain between the 2.5% and 97.5% percentiles determined during the CLARA-A3 TCDR period (see Table 2-9).

3.3.5 Earth Radiation Budget TSI TOA TCDR v3.0 and ICDR v3.x

A first indicator of the uncertainty is the comparison of the individual TSI time series, before they are combined in the composite TSI time series. This is done routinely, as part of the CDR generation. These intercomparisons permit the identification of periods of lower quality (e.g. drift) for some of the individual TSI instruments. These periods have been discarded from the final C3S composite (Dewitte and Nevens, 2016).   

Uncertainty and stability can also be assessed, to a certain level, using a proxy for the TSI like the number of Sun spots or indices extracted from magnetograms (for example, see http://solar-center.stanford.edu/solar-images/magnetograms.html). Efforts in this direction will not only narrow the uncertainty estimate for the TSI CDR, but also permit extension back in time the CDR in the pre-satellite era.


3.4 Opportunities to improve quality and fitness-for-purpose of the CDRs

3.4.1 Earth Radiation Budget CERES EBAF Ed4.2 (OLR, RSF)

Currently there is no indication of significant limitations with the data that would call for a reprocessing of the EBAF record in the coming months. C3S keeps in touch with the CERES Science Team through attendance to the bi-annual science team meetings, where the Edition 5 of the data will be decided. CERES Edition 5 is not expected to either drastically improve the current EBAF record nor to enhance significantly its fitness-for-purpose.

3.4.2 Earth Radiation Budget HIRS OLR monthly v02r07 and daily v01r02

The current version of the CDR is based on 4 HIRS channels and on the geostationary IR observations via GridSat (Knapp et al., 2011). Several opportunities have been identified for improvement of the record as detailed in [D5]. Here, the following opportunities for European contributions can be considered:

  • Use true FCDR for the HIRS radiances, e.g. the FCDR developed in the framework of the Fidelity and uncertainty in climate data records from Earth Observations (FIDUCEO) Horizon 2020 project (see https://research.reading.ac.uk/fiduceo/).

  • Merge with high spatial resolution data from AVHRR, e.g. also based on an FCDR of AVHRR channel 4 and 5 observations from FIDUCEO or the FDR record developed by EUMETSAT.

  • Another potential European contribution could be a merging of the HIRS OLR CDR with the CLARA-A3 OLR.

3.4.3 Earth Radiation Budget ESA_CCI_AATSR TCDR v3.0 + SLSTR-based ICDR v3.1.1 + v4.0 (OLR,RSF)

Most potential improvements to ORAC radiative flux products stem from improvements to the underlying cloud retrieval scheme, which are discussed below.

The planned development of the ORAC retrieval scheme, as applied to (A)ATSR and SLSTR, has already been described in section 3.2.3. ORAC is under active development, both through the ESA CCI+ program and through national UK funding (in particular, under the National Centre for Earth Observation). New improvements of the scheme, where applicable, will be fed through to the production of improved CDR products from SLSTR.

It is also worth noting that the ORAC scheme is not specifically designed for application to (A)ATSR or SLSTR. CDRs have already been produced using the scheme for the AVHRR and MODIS instruments, under previous iterations of the CCI program. The scheme has also been applied to geo-stationary sensors (SEVIRI, GOES and Himawari-AHI), and improved application of the scheme to SEVIRI in particular (making use of the water-vapor sounding channels provided by the instrument) is being undertaken in CCI+.

The code includes the ability to utilize sounding channels (CO2 slicing and water-vapor absorption), as well as a multi-layer cloud retrieval mode ([D14]), which greatly improve on the shortcomings of the existing “heritage channel” (AVHRR-like) CDRs produced in CCI, and retrieves the properties of dual-layer cloud scenes. Thus, the scheme provides the scope for the production of cutting-edge CDRs from a wide range of instruments, all with a consistent retrieval approach.

 3.4.4 Earth Radiation Budget TCDR and ICDR AVHRR CLARA v3.0 (CLARA-A3)

Concerning the CLARA-A3 TOA radiation CDR, several opportunities to improve the quality and the fitness-for-purpose of the CDR have been identified by the development team at CM SAF. Some are being implemented in the upcoming edition A3.5 and edition A4.

The edition A3.5 will incorporate AVHRR-like data from the VIIRS instrument on S-NPP and NOAA satellites. This is expected to significantly improve the quality of the record from 2016 onward. Indeed, from that time the afternoon NOAA satellites with AVHRR instrument are drifting to late afternoon/evening and the peaks of RSF and OLR radiation (in early afternoon) are not directly observed.

The development of the edition A4 will be based on comments received by the users of the editions A3 and A3.5. An interesting addition in A4 could be the clear sky fluxes as this would allow estimation of the cloud radiative effect. Also, the addition of incoming solar flux, to allow conversion of the RSF to planetary albedo, would increase the fitness-for-purpose.

3.4.5 Earth Radiation Budget TSI TOA TCDR v3.0 and ICDR v3.x

The question of the absolute level of the TSI time series is still partly unresolved. Different instruments have shown differences that exceeded the sum of their stated individual accuracies. Solving this problem would require an even more comprehensive and accurate instrument ground characterization, fully linked to international metrology standards, and, if possible, on re-characterization at the end of the mission (e.g. for instrument on the ISS or space shuttles). On ground intercomparison campaigns of space instruments, such as the one organized by the World Radiation Center at PMO/Davos (https://www.pmodwrc.ch/), also help to understand remaining differences in absolute level.

Additionally, the TSI record could be complemented by high quality CDR about the Solar Spectral Irradiance, as recommended by the GCOS [D10].

3.5 Scientific Research needs

3.5.1 Earth Radiation Budget CERES EBAF Ed4.2 (OLR, RSF)

In view of a likely gap in the morning broadband observation at the end of the Terra mission, it is recommended that European players (from instance EUMETSAT, or the GERB and ScaRaB teams) develop ERB products for the Metop satellites. In particular, Metop-SG will host the Multi-viewing, -channel, -polarisation Imaging (3MI) instrument that could be valuable for the shortwave flux estimation. The development of TOA radiation fluxes for the METimage instruments is also very relevant at this level, especially for the RSF.

3.5.2 Earth Radiation Budget HIRS OLR monthly v02r07 and daily v01r02

As already stated, the main effort should be on the generation of a high-quality FCDR for the HIRS observation record (e.g. through the FIDUCEO project).

New reanalysis systems, incorporating the radiative effect of the main volcanic eruptions, could be used to assess the uncertainty of the HIRS OLR CDR during the pre-CERES era. This would provide further evidence that the effect of ECT drift of the NOAA satellites (and also of the Metop satellites toward end of life) is accurately compensated for in the processing. For example, a difference in global mean OLR between the HIRS OLR CDR and the OLR in the ERA5 reanalysis has been found. Also, variation of the bias appears to be larger in the first half of the record with respect to the second half.

Further research in applicability of the Triple Collocation (TC) methodology to ERB datasets is also needed to better understand the uncertainties in the daily and monthly mean product at regional scale.

3.5.3 Earth Radiation Budget ESA_CCI_AATSR TCDR v3.0 + SLSTR-based ICDR v3.1.1 + v4.0 (OLR, RSF)

As mentioned above, most improvements to ORAC radiative products will come from improvements in the underlying cloud retrieval performance. One of the largest sources of uncertainty in cloud (and aerosol) products has always been and continues to be the problem of “scene identification”; i.e. distinguishing cloud from clear-sky or elevated aerosol loading over all surface types, as well as identifying cloud type (liquid, ice, multi-layer, etc.). Areas known to be particularly problematic include identifying cloud over ice/snow surfaces, dealing with the so-called twilight zone between cloudy and clear pixels and the correct identification and classification of extreme aerosol events (such as dust storms, smoke plumes and volcanic ash). Much work is ongoing, particularly in the field of machine learning, on addressing this area.

As with most products centered on Earth radiative processing, improvements in the knowledge of, and updates to databases of surface properties, particularly land-surface reflectance and emissivity are key.

 3.5.4 Earth Radiation Budget TCDR and ICDR AVHRR CLARA v3.0 (CLARA-A3)

The generation of AVHRR-like data from VIIRS and METimage would necessitate (limited) scientific research needs, which are currently provided by CM SAF. Improving the representation of the diurnal cycles of the radiation in the CLARA record is another domain requiring scientific research. Efforts in the direction of a high-quality “GeoRing” FCDR are performed at international level, by EUMETSAT, NOAA and JAXA, as well as in some projects like SCOPE-CM, CM SAF, ISCCP and ISCCP-NG.

3.5.5 Earth Radiation Budget TSI TOA TCDR v3.0 and ICDR v3.x

Scientific research should focus on a better exploitation of proxy data for solar activity (sun spot number, magnetic indices, etc.). Improved proxy data would permit a better detection of instrumental aging and detection of erroneous data, leading to improved TSI composites.

3.6 Opportunities from exploiting the Sentinels and any other relevant satellite

EarthCARE, the 6th ESA Earth Explorer mission, is now planned for launch on 25th – 31st May 2024 with a Falcon-9 launcher. The mission includes a 3-views Broadband Radiometer (BBR) that will provide TOA shortwave and longwave fluxes with an unprecedented instantaneous accuracy (requirement < 10 W/m²). The EarthCARE data are not aimed to be directly ingested in the generation of global CDR (the BBR swath is limited to 18km while the orbits are separated by 2,574 km at the Equator). However, EarthCARE BBR data presents many opportunities for improving CDR of TOA Earth Radiation Budget. In particular, the BBR will complement future GeoRing TOA radiation products based on the latest generation of geostationary imagers (i.e. GOES ABI, Himawari AHI, and Meteosat FCI). With respect to the previous generation, these new imagers provide extended spectral coverage in the 0.4µm-0.6µm region where aerosol scattering and absorption directly affect the ERB. The EarthCARE BBR fluxes will be valuable to characterize the accuracy of these new GEO products, while the EarthCARE radiances will be valuable to homogenize the flux products coming from the different imagers in the GeoRing (calibration transfer).

3.6.1 Earth Radiation Budget CERES EBAF Ed4.2 (OLR, RSF)

EarthCARE will be an opportunity to better characterize the error in the CERES level 2 products. Some matches can be expected between the 14:00 descending orbit of EarthCARE and the 13:30 ascending orbit of the EOS Aqua satellite. This is foreseen in two calibration and validation (Cal/Val) research activities selected by ESA. The first Cal/Val activity will be done by the CERES team at NASA Langley Research Center (LaRC), while a second activity will be conducted by a consortium including RMIB, Imperial College London and NASA LaRC.

Implementation of TOA radiation products from the improved geostationary imagers (GOES ABI, Himawari AHI, MTG/FCI) presents also many opportunities of synergy with the CERES CDR. Activities toward ERB GeoRing are foreseen in the Continuous Development and Operation Phase 4 (CDOP 4) of CM SAF (2022-2027) as part of support activity for ISCCP-NG.

In the more distant future, measurements of reflected shortwave flux (from CERES or other missions) are expected to benefit from metrology missions like the Traceable Radiometry Underpinning Terrestrial- and Helio- Studies (TRUTHS). This mission was selected in November 2019 for funding within the Earth Observation Earth Watch program. It will provide state of the art and fully SI-traceable measurements of the incoming and outgoing solar radiation, with an unprecedented accuracy thanks to innovative calibration devices. The mission, led by the National Physical Laboratory in the UK, is currently in phase A/B.

3.6.2 Earth Radiation Budget HIRS OLR monthly v02r07 and daily v01r02

The Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) mission has been selected for implementation as the 9th ESA Earth Explorer. FORUM will sample the infrared spectrum from 100 cm-1 to 1600 cm-1 (100 µm to 6.25 µm) with a spectral resolution of 0.5 cm-1. Combined with IASI-NG, this mission will provide accurate spectral measurements of the full infra-red spectrum. This kind of spectrum would be interesting to understand the limits of the HIRS channels for OLR estimation through narrowband-to-broadband conversion.

3.6.3 Earth Radiation Budget ESA_CCI_AATSR TCDR v3.0 + SLSTR-based ICDR v3.1.1 + v4.0 (OLR, RSF)

The ESA SLSTR v3.x ICDR directly exploits data from the Sentinel-3 platform. There have been examples shown of utilizing Sentinel-3 OLCI-like measurements (mainly using MERIS on ENVISAT) for cloud retrieval in conjunction with (A)ATSR or SLSTR (Carbajal Henken et al. 2014), but difficulties in cross-calibration and co-registration of the different instruments have meant these products have not shown improved performance over the (A)ATSR/SLSTR only algorithms. The availability of a well co-located and calibrated joint SLSTR-OLCI L1 product, could resurrect this approach to further improve cloud products derived from Sentinel-3 (and the preceding ENVISAT).

As discussed in section 3.1.3, the ORAC retrieval scheme can be, and has been, applied to a wide range of satellite visible-IR imaging radiometers. A particular instrument, of direct relevance to the Sentinel satellite program is the Flexible Combined Imager (FCI) to fly on MeteoSat Third Generation/Sentinel-4. This instrument is essentially a replacement for the SEVIRI sensors on MSG, with capabilities similar to those provided by Himawari-AHI and GOES-ABI imagers (which ORAC has already been applied to).

 3.6.4 Earth Radiation Budget TCDR and ICDR AVHRR CLARA v3.0 (CLARA-A3)

With respect to other CDRs, the main advantage of the CLARA CDR is the very long duration back in time, to 01.01.1979. For this reason, new satellite missions and the Sentinels are not expected to provide direct opportunities to improve the record.

3.6.5 Earth Radiation Budget TSI_TOA TCDR v3.0 and ICDR v3.x

The TSIS-1 mission includes a TIM instrument on the International Space Station (ISS). A second instrument is foreseen as a TSIS-2 mission, on a free flying spacecraft, which is currently planned for launch in May 2025.


References

Brodzik, M. J. and J. S. Stewart. 2016: Near-Real-Time SSM/I-SSMIS EASE-Grid Daily Global Ice Concentration and Snow Extent, Version 5. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. DOI: https://doi.org/10.5067/3KB2JPLFPK3R.

Carbajal Henken, C.K., R. Lindstrot, R. Preusker and J. Fischer, 2014: FAME-C: cloud property retrieval using synergistic AATSR and MERIS observations. Atmos. Meas. Tech., 7, 3873–3890, DOI: https://doi.org/10.5194/amt-7-3873-2014.

Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., Vitart, F., 2011: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Quarterly Journal of the Royal Meteorological Society, 137, 656, 553—597, DOI: https://doi.org/10.1002/qj.828

Dewitte, S. and S. Nevens, 2016: The total solar irradiance climate data record. The Astrophysical Journal, 830(1), p.25, DOI: https://doi.org/10.3847/0004-637X/830/1/25

Dewitte S. and N. Clerbaux, 2017: Measurement of the Earth Radiation Budget at the Top of the Atmosphere — A Review, Remote Sensing, 9, 1143; doi: https://doi.org/10.3390/rs9111143.

Dewitte, S., N. Clerbaux, N. and J. Cornelis, 2019: Decadal Changes of the Reflected Solar Radiation and the Earth Energy Imbalance. Remote Sensing, 11(6), p.663, doi: https://doi.org/10.3390/rs11060663

Doelling, D. R. et al., 2013: Geostationary enhanced temporal interpolation for CERES flux products. Journal of Atmospheric and Oceanic Technology, 30(6), 1072-1090, doi: https://doi.org/10.1175/JTECH-D-12-00136.1

Doelling, D.R., et al., 2016. Advances in geostationary-derived longwave fluxes for the CERES synoptic (SYN1deg) product. Journal of Atmospheric and Oceanic Technology, 33(3), pp.503-521, doi: https://doi.org/10.1175/JTECH-D-15-0147.1

Knapp, K.R., et al., 2011: Globally gridded satellite observations for climate studies. Bulletin of the American Meteorological Society, 92(7), pp.893-907, doi: https://doi.org/10.1175/2011BAMS3039.1

Lee, H.-T., 2014: Daily OLR CDR – Development and Evaluation. CERES Science Team Meeting, Apr 2014.

Lee, H.-T., 2014: Daily OLR Climate Data Record. EGU General Assembly, Apr 2014.

Lee, H.-T., C. J. Schreck, and K. R. Knapp, 2014: Generation of Daily OLR CDR. Eumetsat Meteorological Satellite Conference, Sep 2014.

Lee, H.-T., 2018: Quality Assurance Summary and Results for Monthly and Daily OLR CDR (rev.20180831).

Lee, H.-T., A. Gruber, R. G. Ellingson and I. Laszlo, 2007: Development of the HIRS Outgoing Longwave Radiation climate data set. J. Atmos. Ocean. Tech., 24, 2029–2047, doi: https://doi.org/10.1175/2007JTECHA989.1

Loeb, N. G., S. Kato, and B. A. Wielicki, 2002: Defining top-of-atmosphere flux reference level for Earth Radiation Budget studies. Journal of Climate, 15, 3301-3309, doi: https://doi.org/10.1175/1520-0442(2002)015%3C3301:DTOTAF%3E2.0.CO;2

Loeb, N. G., et al., 2009: Toward optimal closure of the Earth's top-of-atmosphere radiation budget. Journal of Climate, 22(3), 748-766, doi: https://doi.org/10.1175/2008JCLI2637.1

Loeb, N. G., et al., 2018: Clouds and the earth’s radiant energy system (CERES) energy balanced and filled (EBAF) top-of-atmosphere (TOA) edition-4.0 data product. Journal of Climate, 31(2), 895-918, doi: https://doi.org/10.1175/JCLI-D-17-0208.1

McGarragh, G. R., Poulsen, C. A., Thomas, G. E., Povey, A. C., Sus, O., Stapelberg, S., Schlundt, C., Proud, S., Christensen, M. W., Stengel, M., Hollmann, R., and Grainger, R. G., 2018: The Community Cloud retrieval for CLimate (CC4CL) – Part 2: The optimal estimation approach, Atmos. Meas. Tech., 11, 3397–3431, https://doi.org/10.5194/amt-11-3397-2018.

Minnis P., et al., 2011: CERES Edition-2 cloud property retrievals using TRMM VIRS and Terra and Aqua MODIS data--Part I: Algorithms. IEEE Trans. Geosci. Remote Sens., 49, 4374-4400, doi: https://doi.org/10.1109/TGRS.2011.2144601

Schaaf, C. and Wang, Z., 2015: MCD43C1 MODIS/Terra+Aqua BRDF/AlbedoModel Parameters Daily L3 Global 0.05Deg CMG V006, NASA EOSDIS Land Processes DAAC, https://doi.org/10.5067/MODIS/MCD43C1.006.

Schreck, C. J., H.-T. Lee and K. Knapp, 2018: HIRS Outgoing Longwave Radiation—Daily Climate Data Record: Application toward Identifying Tropical Subseasonal Variability. Remote Sens. 2018, 10, 1325, doi: https://doi.org/10.3390/rs10091325

Smith, D., C. Mutlow, J. Delderfield, B. Watkins and G. Mason, 2012: ATSR infrared radiometric calibration and in-orbit performance. Remote Sens. Environ., 116, 4-16, DOI: 10.1016/j.rse.2011.01.027.

Stephens, G. L., Gabriel, P. M., and Partain, P. T., 2001: Parameterization of Atmospheric Radiative Transfer. Part I: Validity of Simple Models. Journal of the Atmospheric Sciences, 58(22):3391–3409, DOI: https://doi.org/10.1175/1520-0469(2001)058<3391:POARTP>2.0.CO;2

Stoffelen, A., 1998: Towards the true near-surface wind speed: Error modeling and calibration using triple collocation. J. Geophys. Res. 103C3, 7755-7766, doi: https://doi.org/10.1029/97JC03180

Sus, O., Stengel, M., Stapelberg, S., McGarragh, G., Poulsen, C., Povey, A. C., Schlundt, C., Thomas, G., Christensen, M., Proud, S., Jerg, M., Grainger, R., and Hollmann, R., 2018: The Community Cloud retrieval for CLimate (CC4CL) – Part 1: A framework applied to multiple satellite imaging sensors, Atmos. Meas. Tech., 11, 3373–3396, DOI: https://doi.org/10.5194/amt-11-3373-2018.

Wielicki, B. A., Barkstrom, B. R., Harrison, E. F., Lee III, R. B., Smith, G. L., & Cooper, J. E., 1996: Clouds and the Earth's Radiant Energy System (CERES): An earth observing system experiment. Bulletin of the American Meteorological Society, 77(5), 853-868, DOI: https://doi.org/10.1175/2009JTECHA1281.1.


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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.

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