Contributors: T.Usedly (DWD)
Issued by: Deutscher Wetterdienst / Tim Usedly
Date: 01/08/2024
Ref: C3S2_D312a_Lot1.2.3.7_202408_PQAR_ECV_SRB_SLSTR_v1.2
Official reference number service contract: 2021/C3S2_312a_Lot1_DWD/SC1
History of modifications
List of datasets covered by this document
Related documents
Acronyms
List of tables
List of figures
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 results 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) programme ranges from 01/2017 – 12/2023 and provides an Interim Climate Data Record (ICDR) to the brokered Thematic Climate Data Record (TCDR) from 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 by RAL Space for the ESA Cloud_cci programme and ranges from 06/1995 – 04/2012. 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 spanning from 01/2017 – 12/2023
Executive Summary
The Sea and Land Surface Temperature Radiometer onboard Sentinel-3A has provided data since January 2017. The launch of Sentinel-3B in October 2018 makes it possible to deliver not only individual data from both satellites but also a merged Sentinel-3A/3B product. 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 specific variable up to 37 stations were used to provide the best possible global coverage. In addition to the merged SLSTR version, a second version on a different grid (equal area in addition to equal angle) is provided for the period from 07/2022 to 12/2023 and also validated against the same reference dataset as the equal angle version of SLSTR.
Validation to these SLSTR derived products is described in the following chapters of this document: Chapter 1 provides a summary of the product validation methodology while chapter 2 presents the validation results. A detailed validation methodology can be found in the Product Quality Assurance Document (PQAD) [D2]. Chapters 3 and 4 discuss possible application specific assessments and compliances with user requirements respectively.
Overall the SLSTR data meets the breakthrough/target GCOS requirement for the horizontal and temporal resolution. However, all variables do not meet the threshold GCOS requirements in terms of accuracy (Table 1-1); 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.
1. Product validation methodology
Detailed information about the validation methodology can be found in the corresponding PQAD [D2], section 3. The validation process is separated into three parts: Data preparation (section 1.1), validation (section 1.2) and evaluation (1.3).
1.1 Data preparation
SLSTR data is provided at a regular latitude-longitude grid with 0.5°x0.5° spatial resolution and monthly means. The validation is based on the comparison with monthly means of available ground station measurements of the BSRN (Ohmura, 1998). A nearest neighbor technique is used for a comparison, using the ground stations coordinates to extract the nearest grid point of the gridded dataset to calculate the bias and further statistical measures.
1.2 Validation
Validation is done by calculating each station’s mean bias and absolute bias as well as a correlation of all available station-months. In addition, Standard deviation and Fraction of months outside the validation target values are calculated.
1.3 Evaluation
The previously calculated 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]. They are summarized in table 1-1.Comparison with CERES satellite data
Table 1-1: Summary of requirements for Surface Radiation Parameters: 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 |
2. Validation results
Sections 2.1 – 2.4 show the validation results for the four variables: (i) Surface Incoming Shortwave Radiation (SIS), (ii) Surface Reflected Shortwave Radiation (SRS), (iii) Surface Downwelling Longwave Radiation (SDL) and (iv) Surface Outgoing Longwave Radiation (SOL).
2.1 Surface Incoming Shortwave Radiation
Figure 2-1: Plot (a, left) shows bias (black dots) and absolute bias (white triangle) for the comparison of SLSTR SIS and BSRN ground stations. Green shaded area marks the 10 W/m² threshold requirement by GCOS. Plot (b, right) shows the number of available months per station
Figure 2-1 shows bias and absolute bias for the SLSTR SIS compared to measurements from 37 stations. Most of the absolute biases are within the ± 10W/m² area with an overall small positive bias (1.82 W/m²). Four stations show a significant positive bias: Boulder (1689 m, east end of the Rocky Mountains), Darwin Met Office (North coast of Australia), Lanyu Island (Island close to Taiwan) and Reunion Island (Island east of Madagascar). A negative bias is seen in Izana (2373 m, central Spain). What all of these stations have in common is that they are either located at high altitude/topographic terrain or small islands/coastal areas and are questionable in terms of representativeness. In addition, Boulder and Darwin Met Office only rely on 19 and 17 months, respectively. Figure 2-2 indicates that almost all stations with absolute biases >10 W/m² are at high altitudes, islands/coasts or at high latitude (see Antarctica).
Figure 2-2: Temporal average of SIS from SLSTR and stations from the BSRN. Green dots indicate surface stations where the SLSTR SIS data meets the target accuracy (absolute bias less than 10W/m²), black triangles correspond to surface stations, where the SLSTR data does not meet the target accuracy
The correlation of all available 1706 station-months shows good agreement with a correlation of 0.97 and a small positive bias (red line slightly below the blue line) (figure 2-3).
Figure 2-3: Correlation between SLSTR SIS and BSRN ground stations. Blue line defines a perfect correlation (45°), the red line marks the slope
2.1.1 Surface Incoming Shortwave Radiation (equal area grid)
Figure 2-4: Plot (a, left) shows the bias (black dots) and absolute bias (white triangle) for the comparison of SLSTR SIS (equal area grid) and BSRN ground stations. Green shaded area marks the 10 W/m² threshold requirement by GCOS. Plot (b, right) shows the number of available months per station
The reduced validation period (07/2022 – 12/2023) for the SLSTR SIS version on the equal area grid shows generally the same pattern (Figures 2-4 to 2-6). Stations in Izana and Reunion Island are the biggest outliers, while most of the stations´ biases are slightly positive but within the 10 W/m² area. The overall bias is higher compared to the SLSTR SIS on the equal angle grid (4.81 W/m²) but this might be related to a reduced number of months (312) and a different selection of stations. In addition to the previously mentioned outliers, Ny Alesund, another outlier, is located at Spitzbergen, Norway at a very high latitude of 78.93 °N.
Figure 2-5: Temporal average of SIS (equal area grid) from SLSTR and stations from the BSRN. Green dots indicate surface stations where the SLSTR SIS data meets the target accuracy (absolute bias > 10W/m²), black triangles correspond to surface stations, where the SLSTR data does not meet the target accuracy
Figure 2-6: Correlation between SLSTR SIS (equal area grid) and BSRN ground stations. Blue line defines a perfect correlation (45°), the red line marks the slope
2.2 Surface Reflected Shortwave Radiation
Figure 2-7: (a) Bias (black dots) and absolute bias (white triangle) for the comparison of SLSTR SRS and BSRN ground stations. Green shaded area marks the 10 W/m² threshold requirement by GCOS. (b) Number of available months per station
Figures 2-7 to 2-9 show the bias and absolute bias for the SLSTR SRS data. For the outgoing radiations (SRS and SOL) a reduced number of stations is available for the period from 10/2018 on. The majority of stations show a negative bias (-5.22 W/m² on average). Outliers are again noticed for Izana (negative bias) and Boulder (positive bias). Stations south of 60°S latitude show generally a negative bias (Concordia Station, Georg von Neumayer Station and Syowa – all located on the Antarctica continent) and absolute biases are higher than 10 W/m². Other outliers are seen for the high-latitude stations Barrows and Ny-Alesund as well as the high altitude station of Izana. Stations with higher values tend to have a negative bias (see Figure 2-9), while satellite data with generally low values show good agreement with BSRN data.
Figure 2-8: Temporal average of SRS from SLSTR and stations from the BSRN. Green dots indicate surface stations where the SLSTR SRS data meets the target accuracy (absolute bias less than 10W/m²), black triangles correspond to surface stations, where the SLSTR data does not meet the target accuracy
Figure 2-9: Correlation between SLSTR SRS and BSRN ground stations. Blue line defines a perfect correlation (45°), the red line marks the slope
2.2.1 Surface Reflected Shortwave Radiation (equal area grid)
Figure 2-10: (a) Bias (black dots) and absolute bias (white triangle) for the comparison of SLSTR SRS (equal area grid) and BSRN ground stations. Green shaded area marks the 10 W/m² threshold requirement by GCOS. (b) Number of available months per station
Comparison of SLSTR SRS data on the equal area grid shows the same pattern with an overall negative bias (-8.99 W/m²). Stations with absolute biases outside of 10 W/m² are generally the same as those mentioned previously while European continental stations (Budapest-Lorinc, Hungary and Payerne, Switzerland) meet the target accuracy requirements for SLSTR (see Figure 2-11). Correlation shows a slight negative bias with a correlation of 0.93.
Figure 2-11: Temporal average of SRS (equal area grid) from SLSTR and stations from the BSRN. Green dots indicate surface stations where the SLSTR SRS data meets the target accuracy (absolute bias less than 10W/m²), black triangles correspond to surface stations, where the SLSTR data does not meet the target accuracy
Figure 2-12: Correlation between SLSTR SRS (equal area grid) and BSRN ground stations. Blue line defines a perfect correlation (45°), the red line marks the slope
2.3 Surface Downwelling Longwave Radiation
Figure 2-13: Plot (a, left) shows the bias (black dots) and absolute bias (white triangle) for the comparison of SLSTR SDL and BSRN ground stations. Green shaded area marks the 10 W/m² threshold requirement by GCOS. Plot (b, right) shows the number of available months per station
Compared with the previous variables, in the case of SDL most of the stations´ biases are positive (31/37) with more significant outliers for the high-altitude stations of Izana (2373 m), Sonnblick (3109 m) and Yushan (3858 m). Those three stations are clearly visible in figure 2-15 in a pronounced cloud of data points situated separately below the 1-1 line. The majority of the 1701 months shows a slight positive bias for values from 200 W/m² upwards, while generally lower values (<200 W/m²) are underestimated by SLSTR (majority of points belongs to Concordia Station, Antarctica. 26/37 stations have higher absolute bias than 10 W/m² (figure 2-14).
Figure 2-14: Temporal average of SDL from SLSTR and stations from the BSRN. Green dots indicate surface stations where the SLSTR SDL data meets the target accuracy (absolute bias > 10W/m²), black triangles correspond to surface stations, where the SLSTR data does not meet the target accuracy
Figure 2-15: Correlation between SLSTR SDL and BSRN ground stations. Blue line defines a perfect correlation (45°), the red line marks the slope. The pronounced cloud of data below the 1-1 line are the outliers for the high-altitude stations of Izana (2373 m), Sonnblick (3109 m) and Yushan (3858 m).
2.3.1 Surface Downwelling Longwave Radiation (equal area grid)
Figure 2-16: (a) Bias (black dots) and absolute bias (white triangle) for the comparison of SLSTR SDL (equal area grid) and BSRN ground stations. Green shaded area marks the 10 W/m² threshold requirement by GCOS. (b) Number of available months per station
Figures 2-16 to 2-18 show the same patterns for the SLSTR SDL equal area grid version with reduced months/stations availability. 312 station-months (compared to 1701) result in similar correlation coefficients (0.89 and 0.88 for equal area grid). However, it is worth mentioning that the selection of stations differs for the two comparisons and the absence of the Concordia Station removes parts of the negative bias.
Figure 2-17: Temporal average of SDL (equal area grid) from SLSTR and stations from the BSRN. Green dots indicate surface stations where the SLSTR SDL data meets the target accuracy (absolute bias > 10W/m²), black triangles correspond to surface stations, where the SLSTR data does not meet the target accuracy
Figure 2-18: Correlation between SLSTR SDL (equal area grid) and BSRN ground stations. Blue line defines a perfect correlation (45°), the red line marks the slope. The pronounced cloud of data below the 1-1 line are the outliers for the high-altitude stations of Izana (2373 m), Sonnblick (3109 m)
2.4 Surface Outgoing Longwave Radiation
Figure 2-19: (a) Bias (black dots) and absolute bias (white triangle) for the comparison of SLSTR SOL and BSRN ground stations. Green shaded area marks the 10 W/m² threshold requirement by GCOS. (b) Number of available months per station
The SLSTR SOL product exhibits the smallest bias (0.08 W/m²) compared to the other variables. This minimal bias arises because there is no overall trend, as observed with variables like SDL; instead, there is a balanced distribution (see figure 2-19). Correlation between SLSTR and BSRN is 0.97 while 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 (see figure 2-21).
Figure 2-20: Temporal average of SOL from SLSTR and stations from the BSRN. Green dots indicate surface stations where the SLSTR SOL data meets the target accuracy (absolute bias > 10W/m²), black triangles correspond to surface stations, where the SLSTR data does not meet the target accuracy
Figure 2-21: Correlation between SLSTR SOL and BSRN ground stations. Blue line defines a perfect correlation (45°), the red line marks the slope
2.4.1 Surface Outgoing Longwave Radiation (equal area grid)
Figure 2-22: (a) Bias (black dots) and absolute bias (white triangle) for the comparison of SLSTR SOL (equal area grid) and BSRN ground stations. Green shaded area marks the 10 W/m² threshold requirement by GCOS. (b) Number of available months per station
Validation for the SLSTR SOL product on the equal area grid for the period from 07/2022 – 12/2023 is limited to eight available stations (and five for the whole time period) and should therefore be treated with caution. Overall bias is -2.63 W/m² and absolute bias 15.73 W/m² which is mainly due to the Station at Izana, which has a larger impact due to the small number of stations (Figures 2-22 to 2-24).
Figure 2-23: Temporal average of SOL (equal area grid) from SLSTR and stations from the BSRN. Green dots indicate surface stations where the SLSTR SOL data meets the target accuracy (absolute bias > 10W/m²), black triangles correspond to surface stations, where the SLSTR data does not meet the target accuracy
Figure 2-24: Correlation between SLSTR SOL (equal area grid) and BSRN ground stations. Blue line defines a perfect correlation (45°), the red line marks the slope
3. Application(s) specific assessments
This section is not applicable. There are no additional application specific assessments known since the dataset has just been published.
4.Compliance with user requirements
The GCOS requirements [D3] for the ECV Surface Radiation Budget are used to evaluate the compliance for different users needs. Tables 4-1 and 4-2 show the requirements as well as the results.
GCOS defines three requirements depending on user’s needs:
Goal (G): The strictest requirement, indicating no further improvements necessary
Breakthrough (B): Intermediate level between threshold and goal. Breakthrough indicates that it is recommended for certain climate monitoring activities
Threshold (T): Minimum requirement
The SLSTR ICDR meets the breakthrough/target requirement (closely) for the horizontal/temporal resolution, respectively. However, all variables do not meet the requirements in terms of accuracy. Most of the continental stations are within the threshold requirement of 10 W/m², outliers stand out due to high altitudes, locations on islands or high latitude (e.g. Antarctica, Svalbard, Alaska)
It is worth mentioning that the GCOS requirements, defined by the World Meteorological Organisation (WMO), are not focused on satellite-based data records but also on climate models. Satellite-based data records, especially historical observing systems, are often not able to achieve the requirements.
Table 4-1: Results of evaluation against GCOS requirements for SLSTR SIS
Products | Requirement | Values | Surface Incoming Shortwave Radiation | |
Horizontal Resolution | G | 10 km | Roughly 55 km at the equator | |
B | 50 km | |||
T | 100 km | |||
Temporal Resolution | G | 1 h | Monthly mean (720h) | |
B | 24 h | |||
T | 720 h | |||
Accuracy | G | 1 W/m² | Merged SLSTR product vs. reference datasets (10/2018 – 12/2023): Bias: 1.82 W/m² Absolute Bias: 13.05 W/m² Standard Deviation: 15.97 W/m² Frac: 42.94% Available months: 1706 | Equal area SLSTR product vs. reference datasets (07/2022 – 12/2023): Bias: 4.81 W/m² Absolute Bias: 13.60 W/m² Standard Deviation: 14.91 W/m² Frac: 46.97 % Available months: 312 |
B | 5 W/m² | |||
T | 10 W/m² |
Table 4-2: Results of evaluation against GCOS requirements for SLSTR SRS
Products | Requirement | Values | Surface Incoming Shortwave Radiation | |
Horizontal Resolution | G | 10 km | Roughly 55 km at the equator | |
B | 50 km | |||
T | 100 km | |||
Temporal Resolution | G | 1 h | Monthly mean (720h) | |
B | 24 h | |||
T | 720 h | |||
Accuracy | G | 1 W/m² | Merged SLSTR product vs. reference datasets (10/2018 – 12/2023): Bias: -5.22 W/m² Absolute Bias: 14.65 W/m² Standard Deviation: 16.20 W/m² Frac: 49.15 % Available months: 782 | Equal area SLSTR product vs. reference datasets (07/2022 – 12/2023): Bias: -8.99 W/m² Absolute Bias: 14.00 W/m² Standard Deviation: 11.45 W/m² Frac: 50.67 % Available months: 132 |
B | 5 W/m² | |||
T | 10 W/m² |
Table 4-3: Results of evaluation against GCOS requirements for SLSTR SDL
Products | Requirement | Values | Surface Downwelling Longwave Radiation | |
Horizontal Resolution | G | 10 km | Roughly 55 km at the equator | |
B | 50 km | |||
T | 100 km | |||
Temporal Resolution | G | 1 h | Monthly mean (720h) | |
B | 24 h | |||
T | 720 h | |||
Accuracy | G | 1 W/m² | Merged SLSTR product vs. reference datasets (10/2018 – 12/2023): Bias: 16.90 W/m² Absolute Bias: 20.56 W/m² Standard Deviation: 9.49 W/m² Frac: 59.30 % Available months: 1701 | Equal area SLSTR product vs. reference datasets (07/2022 – 12/2023): Bias: 15.01 W/m² Absolute Bias: 18.40 W/m² Standard Deviation: 7.79 W/m² Frac: 54.04 % Available months: 312 |
B | 5 W/m² | |||
T | 10 W/m² |
Table 4-4: Results of evaluation against GCOS requirements for SLSTR SOL
Products | Requirement | Values | Surface Outwelling Longwave Radiation | |
Horizontal Resolution | G | 10 km | Roughly 55 km at the equator | |
B | 50 km | |||
T | 100 km | |||
Temporal Resolution | G | 1 h | Monthly mean (720h) | |
B | 24 h | |||
T | 720 h | |||
Accuracy | G | 1 W/m² | Merged SLSTR product vs. reference datasets (10/2018 – 12/2023): Bias: 0.08 W/m² Absolute Bias: 13.36 W/m² Standard Deviation: 13.57 W/m² Frac: 49.23 % Available months: 781 | Equal area SLSTR product vs. reference datasets (07/2022 – 12/2023): Bias: -2.63 W/m² Absolute Bias: 15.73 W/m² Standard Deviation: 14.62 W/m² Frac: 52.48 % Available months: 132 |
B | 5 W/m² | |||
T | 10 W/m² |
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