Contributors: T. Usedly (DWD)

Issued by: Deutscher Wetterdienst / Tim Usedly

Date: 31/07/2024

Ref: C3S2_D312a_Lot1.1.3.4_202407_PQAD_ECV_SRB_SLSTR_v1.2

Official reference number service contract: 2021/C3S2_312a_Lot1_DWD/SC1

History of modifications


Version

Date

Description of modification

Chapters / Sections

V1.0

30/06/2024

Initial version

All

V1.1

30/07/2024

Implementation of the comments from the review team

All

V1.2

31/07/2024

Implementation of the comments from the review team and finalization for publication

All


List of datasets covered by this document


Deliverable ID

Product title

Product type (CDR, ICDR)

Version number

Delivery date

D2.1.3 P1

ECV Surface Radiation Budget derived from SLSTR

ICDR

V4.0

03/05/2023

D2.9.1

ECV Surface Radiation Budget derived from SLSTR extension

ICDR

V4.0

31/05/2024


Related documents


Reference ID

Document

D1

Product Validation and Intercomparison Report (PVIR), v6.1. ESA Cloud_cci.

https://climate.esa.int/media/documents/Cloud_Product-Validation-and-Intercomparison-Report-PVIR_v6.0.pdf

Last accessed on 07/01/2025

D2

Usedly, T. (DWD), 2024, C3S Surface Radiation Budget,

Service: Product Quality Assessment Report. Copernicus Climate Change Service,

Document ref. C3S2_D312a_Lot1.2.3.7_202406_PQAR_ECV_SRB_SLSTR_v1.0

Not yet published

Last accessed on xx/xx/xxxx

D3

The 2022 GCOS ECV’s Requirements

WMO, 2022, GCOS-245

https://library.wmo.int/viewer/58111/download?file=GCOS-245_2022_GCOS_ECVs_Requirements.pdf&type=pdf&navigator=1

Last accessed on 07/01/2025

D4

Thomas, G. (STFC-RAL), 2023, C3S Surface Radiation Budget

Service: Algorithm Theoretical Basis Document. Copernicus Climate Change Service,

Document ref. C3S2_D312a_Lot1.2.3.3-v4.0_202301_ATBD_CCISurfaceRadiationBudget_v1.2

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

Last accessed on 07/01/2025


Acronyms


Acronym

Definition

ATBD

Algorithm Theoretical Basis Document

BC

Brockmann Consult

BSRN

Baseline Surface Radiation Network

C3S

Copernicus Climate Change Service

CDR

Climate Data Record

CDS

Climate Data Store

Cloud_cci

Cloud Climate Change Initiative

DWD

Deutscher Wetterdienst

EBAF

Energy Balanced and Filled

ECMWF

European Centre for Medium-Range Weather Forecasts

ECV

Essential Climate Variable

ENVISAT

Environmental Satellite

ESA

European Space Agency

GCOS

Global Climate Observing System

ICDR

Interim Climate Data Record

MB

Mean Bias

PQAD

Product Quality Assurance Document

PQAR

Product Quality Assessment Report

RAL

Rutherford Appleton Laboratory

SD

Standard Deviation

SDL

Surface Downwelling Longwave Radiation

SIS

Surface Incoming Shortwave Radiation

SLSTR

Sea and Land Surface Temperature Radiometer

SNL

Surface Net Longwave Radiation

SNS

Surface Net Shortwave Radiation

SOL

Surface Outgoing Longwave Radiation

SRB

Surface Radiation Budget

SRS

Surface Reflected Shortwave Radiation

STFC

Science and Technology Facilities Council

TCDR

Thematic Climate Data Record

WMO

World Meteorological Organization

WRMC

World Radiation Monitoring Center


List of tables

Table 2-1: List of station from the BSRN used for the validation with information on latitude, longitude, altitude and temporal availability

Table 3-1: Summary of requirements for SIS, SDL and SOL based on GCOS [D3]

Table 4-1: Summary of evaluation results for each variable compared to BSRN station data and GCOS requirements

List of figures

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

Figure 2-1: Location of all used BSRN ground stations

Figure 4-1: Bias (black) and absolute bias (white) for SIS between satellite-based SLSTR data and ground stations of the BSRN

Figure 4-2: Bias (black) and absolute bias (white) for SRS between satellite-based SLSTR data and ground stations of the BSRN

Figure 4-3: Bias (black) and absolute bias (white) for SDL between satellite-based SLSTR data and ground stations of the BSRN

Figure 4-4: Bias (black) and absolute bias (white) for SOL between satellite-based SLSTR data and ground stations of the BSRN

General definitions

Table 1: Summary of variables and definitions

Variables

Abbreviation

Definition

Surface Incoming Shortwave Radiation

SIS

Amount of shortwave radiation energy reaching the lower boundary of the atmosphere per unit of time and area from the above.

Surface Reflected Shortwave Radiation

SRS

Amount of shortwave radiation energy reaching the lower boundary of the atmosphere per unit of time and area from below.

Surface Outgoing Longwave Radiation

SOL

Amount of longwave radiation energy reaching the lower boundary of the atmosphere per unit of time and area from below.

Surface Downwelling Longwave Radiation

SDL

Amount of longwave radiation energy reaching the lower boundary of the atmosphere per unit of time and area from the above.

Surface Net Shortwave Radiation

SNS

Difference between the amount of shortwave radiation energy reaching the lower boundary of the atmosphere from below (upwelling) and the amount from above (downwelling). Values are provided per unit of time and area.

Surface Net Longwave Radiation

SNL

Difference between the amount of longwave radiation energy reaching the lower boundary of the atmosphere from below (upwelling) and the amount from above (downwelling). Values are provided per unit of time and area.

Surface Radiation Budget

SRB

Difference between the amount of radiation energy reaching the lower boundary of the atmosphere from below (upwelling) and the amount from above (downwelling). Values are provided per unit of time and area.

Table 2: Definition of processing levels

Processing level

Definition

Level-1b

The full-resolution geolocated radiometric measurements (for each view and each channel), rebinned onto a regular spatial grid.

Level-2 (L2)

Retrieved cloud variables at full input data resolution, thus with the same resolution and location as the sensor measurements (Level-1b).

Level-3C (L3C)

Cloud properties of Level-2 orbits of one single sensor combined (averaged) on a global spatial grid. Both daily and monthly products are provided through C3S are Level-3C.

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

Jargon

Definition

TCDR

A Thematic Climate Data Record is a consistently processed time series of a geophysical variable. The time series should be of sufficient length and quality.

ICDR

An Interim Climate Data Record (ICDR) denotes an extension of TCDR, processed with a processing system as consistent as possible to the generation of TCDR.

Brokered product

The C3S Climate Data Store (CDS) provides both data produced specifically for C3S and so-called brokered products. The latter are existing products produced under an independent program or project which are made available through the CDS.

Climate Data Store (CDS)

The front-end and delivery mechanism for data made available through C3S. It is a platform that provides access to a wide range of climate data, including satellite and in-situ observations, reanalysis and other relevant datasets.

Retrieval

A numerical data analysis scheme which uses some form of mathematical inversion to derive physical properties from some form of measurement. In this case, the derivation of cloud properties from satellite measured radiances.

Forward model

A deterministic model which predicts the measurements made of a system, given its physical properties. The forward model is the function which is mathematically inverted by a retrieval scheme. In this case, the forward model predicts the radiances measured by a satellite instrument as a function of atmospheric and surface state, and cloud properties.

Remapping

Interpolation of horizontal fields to a new, predefined grid. All datasets are remapped to the same grid (1°x1°, latitude from -90° to 90°, longitude from -180° to 180°) to make them comparable. The remap is done with bilateral interpolation.

Collocation

A collocation consists in filtering nan values of different datasets in the same grid to make them uniform. This is necessary to compare e.g. the global average of two datasets.

Cosine weighted averaging

Consideration of different grid box areas. Grid boxes on usual equal angle grid boxes have a different area depending on the latitude (with larger areas towards the equator). Towards the poles the same number of boxes covers a smaller area; therefore, a correction factor is needed to achieve equal area grid boxes. This factor is the cosine of the latitude. The method is applied for calculation of global averages.

Nearest neighbor

Technique used for a comparison of gridded, satellite-based data and ground station. Ground stations coordinates are used to extract the nearest grid point of the gridded dataset to calculate bias and further statistical measures.

Plate Carree projection

Cylindrical projection of a map with meridians and parallels build equally spaced grids.

Table 4: Definition of statistical measures used in the document

Statistical measures

Definition

Bias

Mean difference between two datasets. In this case, a comparison between a gridded dataset and ground stations reference data, it is simply the arithmetic mean of the difference of all months for the nearest grid point in the datasets based on the location of the ground station. It is defined as:

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

 with B the Bias, n as the number of months, y the dataset and o as the reference dataset.

Mean Absolute Difference (MAD)

The Mean Absolute Difference is the arithmetic mean of the absolute biases of all months. It is defined as:

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

with MAD as Mean Absolute Difference, n as the number of months, y as the dataset and o as the reference dataset.

Standard deviation

The standard deviation provides a quantification of the spread around the mean. It is defined as:

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

with SD as Standard Deviation, n as the number of months, y as the dataset and o as the reference dataset.

Frac

Fraction of months with bias above the validation target values. It is defined as:

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

 with n as the number of months, y as dataset and T as Target accuracy (10 W/m²)


Scope of the document

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

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

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

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

Executive Summary

The Sea and Land Surface Temperature Radiometer onboard Sentinel-3A provides data from 01/2017 on. With the launch of Sentinel-3B in 10/2018 not just individual data but also a merged version of Sentinel-3A/3B is provided (see chapter 1). The merged version (until 12/2023) is validated against measurements from ground stations from the Baseline Surface Radiation Network (BSRN). Depending on the temporal availability and variable up to 37 stations were used to provide best possible global coverage (see chapter 2). In addition to the merged SLSTR version, a second version on a different grid (equal area in addition to equal angle) is provided from 07/2022 to 12/2023 and also validated against the same reference dataset as the equal angle version of SLSTR.

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

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

1. Validated products

The SLSTR-based dataset provides monthly means on a regular global latitude-longitude grid with 0.5°x0.5° spatial resolution for seven variables of the Essential Climate Variable Surface Radiation Budget (SRB): Surface Incoming Shortwave Radiation (SIS), Surface Reflected Shortwave Radiation (SRS), Surface Outgoing Longwave Radiation (SOL), Surface Downwelling Longwave Radiation (SDL) as well as the Net Fluxes (Surface Net Shortwave (SNS) and Surface Net Longwave Radiation(SNL)) and the overall net Radiation named Surface Radiation Budget (SRB).

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

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

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


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

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


2. Description of validating datasets

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

Figure 2-1: Location of all used BSRN ground stations

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

Table 2-1: List of station from the BSRN used for the validation with information on latitude, longitude, altitude and temporal availability

Station

Shortname

Latitude

Longitude

Altitude

Timerange

Abashiri

abs

44.02

144.28

38

2021/03-2023/12

Alice Springs

asp

-23.80

134.89

547

2018/10-2020/06

Barrows

bar

71.32

-156.61

8

2018/10-2022/12

Bondville

bon

40.07

-88.37

213

2018/10-2022/12

Boulder

bos

40.13

-105.24

1689

2018/10-2020/04

Budapest-Lorinc

bud

47.43

19.18

139

2019/06-2023/09

Cabauw

cab

51.97

4.93

0

2018/10-2023/12

Cener

cnr

42.82

-1.60

471

2018/10-2023/12

CocosIsland

coc

-12.15

96.83

5

2018/10-2020/05

Concordia Station

dom

-75.1

123.28

3233

2018/10-2021/12

DesertRock

dra

36.63

-116.02

1007

2018/10-2022/12

Darwin Met Office

dwn

-12.43

130.89

32

2018/10-2020/06

Florinopolis

flo

-27.53

-48.52

11

2018/10-2022/12

Fort Peck

fpe

48.32

-105.10

634

2018/10-2022/12

Fukuoka

fua

33.58

130.38

3

2018/10-2023/12

Goodwin Creek

gcr

34.25

-89.87

98

2018/10-2020/04

Granite Island

gim

46.72

-87.41

208

2018/10-2023/12

Gobabeb

gob

-23.56

15.04

407

2018/10-2023/12

Georg von Neumayer

gvn

-70.65

-8.25

42

2018/10-2022/01

Magurele(MARS)

ino

44.34

26.01

110

2021/05-2023/03

Ishigakijima

ish

24.34

124.16

6

2018/10-2023/12

Izana

iza

28.31

-16.50

2373

2018/10-2023/12

Lindenberg

lin

52.21

14.12

125

2018/10-2022/10

Langley Research

lrc

37.10

-76.39

3

2018/10-2023/12

Lanyu Island

lyu

22.04

121.56

324

2018/10-2021/12

Minamitorishima

mnm

24.29

153.98

7

2018/10-2023/12

Ny Alesund

nya

78.93

11.95

11

2018/10-2023/12

Palaiseu Cedex

pal

48.71

2.21

156

2018/10-2022/12

Payerne

pay

46.82

6.94

491

2018/10-2023/12

Reunion Island

run

-20.90

55.48

116

2019/06-2023/12

Sapporo

sap

43.06

141.33

17

2018/10-2020/11

Sonnblick

son

47.05

12.96

3109

2018/10-2023/12

Syowa

syo

-69.01

39.59

18

2018/10-2023/12

Tamanrasset

tam

22.79

5.53

1385

2018/10-2023/12

Tateno

tat

36.01

140.13

25

2018/10-2023/12

Toravere

tor

58.25

26.46

70

2018/10-2020/12

Yushan

yus

23.49

120.96

3858

2018/10-2022/12


3. Description of product validation methodology

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

3.1 Data preparation

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

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

3.2 Validation

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

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

3.3 Evaluation

The Absolute Bias is used as evaluation against the requirements defined by the Global Climate Observing System (GCOS) in The 2022 GCOS ECVs Requirements (GCOS 245) [D3].

GCOS defines three requirements depending on users needs:

It should be mentioned, that these requirements are rather intended towards potentials and resolutions of climate models. Thus, GOCS requirements are not identical to the users needs outside the climate modelling community. Also, they are often not attainable using existing or historical observing systems.

Table 3-1 names the requirements for horizontal and temporal resolution as well as accuracy for SIS, SDL and SOL

Table 3-1: Summary of requirements for SIS, SDL and SOL based on GCOS [D3]

Products

Requirement

Surface Incoming Shortwave Radiation

Surface Downwelling Longwave Radiation

Surface Outgoing Longwave Radiation

Horizontal Resolution

G

10 km

10 km

10 km

B

50 km

50 km

50 km

T

100 km

100 km

100 km






Temporal Resolution

G

1 h

1 h

1 h

B

24 h

24 h

24 h

T

720 h

720 h

720 h






Accuracy

G

1 W/m²

1 W/m²

1 W/m²

B

5 W/m²

5 W/m²

5 W/m²

T

10 W/m²

10 W/m²

10 W/m²

4. Summary of validation results

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

4.1 Surface Incoming Shortwave Radiation

Figure 4-1Bias (black) and absolute bias (white) for SIS between satellite-based SLSTR data and ground stations of the BSRN. The green area marks the threshold accuracy defined by GCOS.

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

4.2 Surface Reflected Shortwave Radiation

Figure 4-2: Bias (black) and absolute bias (white) for SRS between satellite-based SLSTR data and ground stations of the BSRN. The green area marks the threshold accuracy defined by GCOS.

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

4.3 Surface Downwelling Longwave Radiation

Figure 4-3: Bias (black) and absolute bias (white) for SDL between satellite-based SLSTR data and ground stations of the BSRN. The green area marks the threshold accuracy defined by GCOS.

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

4.4 Surface Outgoing Longwave Radiation

Figure 4-4: Bias (black) and absolute bias (white) for SOL between satellite-based SLSTR data and ground stations of the BSRN. The green area marks the threshold accuracy defined by GCOS.

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

4.5 Evaluation with GCOS requirements

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

Table 3-1Summary of requirements for SIS, SDL and SOL based on GCOS [D3]

Variable

Bias

Absolute Bias

Standard Deviation

Fraction of months
biases outside 10 Wm-2

Available months

Requirements:

G: 1 W/m²
B: 5 W/m²
T: 10 W/m²






SIS

1.82 W/m²

13.05 W/m²

15.97 W/m²

42.94 %

1706

SIS equal area grid

4.81 W/m²

13.60 W/m²

14.91 W/m²

46.97 %

312

SRS

-5.22 W/m²

14.65 W/m²

16.20 W/m²

49.15 %

782

SRS equal area grid

-8.99 W/m²

14.00 W/m²

11.45 W/m²

50.67 %

132

SDL

16.90 W/m²

20.56 W/m²

9.49 W/m²

59.30 %

1701

SDL equal area grid

15.01 W/m²

18.40 W/m²

7.79 W/m²

54.04 %

312

SOL

0.08 W/m²

13.36 W/m²

13.57 W/m²

49.23 %

781

SOL equal area grid

-2.63 W/m²

15.73 W/m²

14.62 W/m²

52.48 %

132



References

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


This document has been produced in the context of the Copernicus Climate Change Service (C3S).

The activities leading to these results have been contracted by the European Centre for Medium-Range Weather Forecasts, operator of C3S on behalf of the European Union (Delegation Agreement signed on 11/11/2014 and Contribution Agreement signed on 22/07/2021). All information in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose.

The users thereof use the information at their sole risk and liability. For the avoidance of all doubt , the European Commission and the European Centre for Medium - Range Weather Forecasts have no liability in respect of this document, which is merely representing the author's view.

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