Last modified on Jun 01, 2022 11:16

Contributors: G.E. Thomas (UKRI-STFC RAL Space)

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Scope of the document

This Algorithm Theoretical Basis Document (ATBD) describes the generation of the Climate Data Record (CDR) on cloud properties brokered from ESA's Cloud_cci programme and its extension with an interim-CDR (ICDR) derived from the Sea and Land Surface Temperature Radiometer (SLSTR) on the Sentinel-3 platform. This extension of the ESA Cloud_cci dataset is generated specifically for C3S by RAL Space, but is derived using the same algorithm and processing chain. Therefore, this document refers to several Cloud_cci documents (see _Related documents), namely the ESA Cloud_cci ATBDs [D1, D2], the ESA Cloud_cci Product User Guide (PUG) [D3], and the ESA Cloud_cci Error characterization report [D4]. These documents describe the data processing chain and the algorithms used to generate the cloud property products. The assessment described in this document is carried out within the scope of C3S and the intellectual property rights of the products themselves remain with the Cloud_cci, in the case of the CDR, or lie with STFC RAL Space, in the case of the ICDR. This document is not part of the official Cloud_cci documentation but produced solely in the scope of the brokering to the CDS.

Executive summary

The CDR on cloud properties is a product of the CC4CL dataset produced by ESA's Cloud_cci project and brokered to C3S, and the SLSTR ICDR is an extension to the brokered product. Accordingly, this document largely refers to the ESA Cloud_cci documentation.

The Cloud_cci record contains 17 years (1995-2012) of satellite-borne observations derived from measurements of the ATSR series of satellites on board the ESA ERS-2 and ENVISAT satellites. The CDR provided to C3S comprises daily (0.1° x 0.1° resolution), and monthly (0.5° x 0.5° resolution) means of cloud properties on a regular global latitude-longitude grid. The SLSTR ICDR continues this record, with a 5-year gap, with version v3.x providing cloud products from SLSTR from 2017 on.

The provided cloud products are cloud fractional cover, cloud top level (consisting of cloud top temperature, pressure, and height), and cloud physical properties (consisting of cloud optical thickness, effective radius, and water path for both the liquid and the ice phase). Note that the brokered service within Copernicus provides only a subset of the original CCI cloud properties dataset, thus the mentioned products do not cover the entire range on cloud products contained in the original dataset provided by Cloud_cci.

1. Instruments

The brokered Cloud_cci cloud dataset is derived from the ATSR-2 and AATSR instruments, which are described in Cloud_cci ATBD [D1], Section 2.2.

ICDR data is derived from the Sea and Land Surface Temperature Radiometer (SLSTR), flown on board the Copernicus Sentinel-3 platform. The SLSTR is an improved version of the ATSR instruments, providing additional spectral channels, improved spatial resolution for the visible and shortwave-infrared channels and a considerably wider swath (1,400 km nadir swath, compared to 512 km for AATSR). As part of the Copernicus operational observation system, two SLSTR instruments are kept operational, with a backup instrument also to be in orbit (although not yet launched). The two operational instruments were launched on Sentinel-3A on 16^th February 2016 and Sentinel-3B on 25^th April 2018. The two platforms fly in identical, interleaved sun-synchronous orbits, such that the two SLSTR instruments provide nearly global coverage twice daily (with one day and one night overpass). Orbital characteristics of Sentinel-3A are summarised in Table 1‑1.

Table 1‑1: The orbital characteristics of the Sentinel-3 satellites. Note that these characteristics are very similar to the ERS-2 and ENVISAT platforms which carried the preceding ATSR instruments.

The SLSTR instrument is described in detail by the Sentinel-3 SLSTR User Guide [D10], but an overview of its specifications is given in Table 1‑2.

Table 1‑2: The specifications of the SLSTR instruments (taken from the SLSTR User Guide [D10]).

2. Input and auxiliary data

This section summarises the required input data used in the retrieval algorithms.

2.1 Fundamental climate data record

The input data for the Cloud_cci dataset is the so-called AATSR-multi-mission level 1b data record, and this forms the fundamental climate data record for this product. The processing of measured radiances to level 1b is described in the ESA AATSR Detailed Processing Model Level 1b [D8] and ENVISAT-style products for ATSR-1 and ATSR-2 data [D9] documents.

The input data for the SLSTR ICDR is the (non near-real-time) ESA Observation mode SLSTR level-1 archive, hosted by the Centre for Environmental Data Analysis (CEDA). At time of writing, no reprocessing of the SLSTR level-1 archive has been undertaken, and improvements in instrument calibration, pixel colocation/geolocation and minor product details have continued to evolve throughout the lifetime of the mission. It is likely that some variation in cloud product quality will be attributable to this inconsistency in the level-1 input data.

SLSTR level-1 data is provided in NetCDF-4 formatted files, which are segregated into 3-minute frames. The level-1 data provide TOA reflectance (for visible and SWIR channels) and brightness temperature (for TIR channels), pixel viewing geometry, measurement time and geolocation, as well as other auxiliary information (see the SLSTR User Guide [D10] for further details).

2.2 Specific input and auxiliary data

The specific spectral channels used in producing the (A)ASTR and SLSTR cloud properties datasets are detailed in Table 2-1, which were chosen to match the so-called heritage-channels provided by the long-running AVHRR instrument series. The cloud retrieval only makes use of the nadir view of the (A)ATSR and SLSTR instruments.

Table 2-1: (A)ATSR and SLSTR channels used to produce the Cloud_cci cloud properties v3.0 TCDR and SLSTR v3.x ICDR

In addition to (A)ATSR or SLSTR level 1 data, the CC4CL retrieval scheme also relies on a range of auxiliary datasets, which are detailed in Table 2-2.

Table 2-2: Auxiliary data used in generating the Cloud_cci TCDR and SLSTR ICDR cloud properties products.

Further details of the input and auxiliary data used are provided in the Cloud_cci CC4CL ATBD [D2], Section 3.

3. Algorithms

This section describes the algorithms used to derive the final cloud properties products.

3.1 Retrieval of swath-based cloud properties (level-2 data)

3.1.1 Cloud fractional cover

The algorithm used to retrieve the level-2 data on the cloud fractional cover is briefly summarised in Cloud_cci ATBD [D1] Section 3.1 and the CC4CL ATBD [D2] Section 2.1. A comprehensive description can be found in Sus et al. 2017 [D6].

3.1.2 Cloud physical properties

The algorithm used to retrieve the level-2 data on the cloud physical properties is briefly summarised in Cloud_cci ATBD [D1], Section 3.3. Detailed descriptions can be found in the CC4CL ATBD [D2] and McGarragh et al 2017 [D7].

3.2 Error budget estimates

3.2.1 Cloud fractional cover

Error budget estimates of cloud fractional cover as well as assumptions and limitations associated with the retrieval algorithms are found in the Cloud_cci Comprehensive Error Characterisation Report [D4].

3.2.2 Cloud physical properties

Error budget estimates of cloud physical properties as well as assumptions and limitations associated with the retrieval algorithms are found in the Cloud_cci CC4CL ATBD [D2] Section 2 and the Comprehensive Error Characterisation Report [D4].

3.3 Generation of final products (level-3 data)

The generation of the final level-3 products (the daily and monthly means) is outlined in Cloud_cci ATBD [D1], Section 4. Note that within the scope of this project, the provided dataset constitutes only a subset of the original Cloud_cci cloud properties dataset. The Cloud_cci PUG [D3] Annex C and the Cloud_cci Comprehensive Error Characterisation Report [D4] Section 6.1 describe the propagation of uncertainty into L3 products.

3.3.1 Cloud fractional cover

Details on the level-3 cloud fractional cover retrieval are given in Cloud_cci ATBD [D1] Section 4.2.1.

3.3.2 Cloud physical properties

Details on the level-3 cloud physical properties retrieval are given in Cloud_cci ATBD [D1] Section 4.2.2.

4. Output data

This section summarises information on the output files.

4.1 File format

Cloud_cci TCDR and SLSTR ICDR products are provided to the CDS in NetCDF (version 4), which are compliant with the conventions CF 1.8 and the NASA Global Change Master Directory (GCMD) Science Keywords vocabulary. Filenames follow the structure:

C3S-312bL1-L3C-MONTHLY-CLD-INSTORACPLATFORM{}YYYYMM{_}_fv3.0.nc,
or
C3S-312bL1-L3C-DAILY-CLD-INSTORACPLATFORM{}YYYYMMDD{_}_fv3.0.nc,

where INST and PLATFORM refer to the instrument and platform from which data originates (either ATSR2 and ERS2, or AATSR and ENVISAT for TCDR data, or SLSTR and Sentinel-3a or -3b for ICDR data), and YYYYMM or YYYYMMDD provide the year, month and (in the case of daily products) day covered by the mean product.

Data are provided as monthly and daily means of cloud properties, as described in Table 4-1 and 4-2, on a regular latitude-longitude grid. For monthly products this grid has a spacing of 0.5° in both dimensions (thus grid centres lie at -89.75°, -89.25°, -88.75°, …, 89.75° in latitude and -179.75°, -179.25°, -178.75°, …, 179.75° in longitude). Daily products have a grid spacing of 0.1° in both dimensions.

4.2 File contents

The data in the monthly cloud products are given in Table 4‑1, while those for the daily products are given in Table 4‑2. Most data fields have four related variables, which are the mean value of the data itself (for example, the mean cloud-top pressure is found in the ctp variable), followed by the standard deviation of the data, denoted by _std, the propagated uncertainty, denoted by _unc, and the spatially correlated uncertainty, denoted by _cor. The definition and details of the calculation of these terms is given in the Cloud_cci Comprehensive Error Characterisation Report [D4].

Both daily and monthly data files have common global attributes, which are defined in Table 4‑3. All data arrays (aside from the lat/lon arrays defining the geographic grid) in the monthly products are 720×360 element arrays, while those in the daily files are 3600×1800 elements. In the case of daily files, data are separated into daylight and night data, based on a solar zenith angle cut-off. This separation is done for two main reasons:

1. In locations where the daylight (descending half of the orbit) and night sections (ascending half of the orbit) overlap, data values separated in time by approximately 12 hours would be combined if a simple daily average was taken. Not only can such an average not be considered a valid daily mean, but will result in inconsistent results in adjacent sections of the orbit track which do and do-not overlap
2. Cloud optical depth and effective radius rely on information for the shortwave (A)ATSR or SLSTR channels, and thus are not retrieved for night pixels. Thus, in order to provide a consistent set of cloud properties for each retrieval, only daylight cloud top pressure, height and temperature as well as water path should be included in the averaging where effective radius and optical depth are present.

Table 4-1: The data variables included in the Cloud_cci TCDR and SLSTR ICDR monthly cloud properties files brokered to, or produced for, the CDS.

Table 4-2: The data variables included in the Cloud_cci TCDR and SLSTR ICDR daily cloud properties files brokered to, or produced for, the CDS.

Table 4-3: List of global attributes included in the Cloud_cci TCDR and SLSTR ICDR cloud properties files brokered to, or produced for, the CDS.

References

References are listed in ESA Cloud_cci ATBD [D1], Section 6; ESA Cloud_cci CC4CL ATBD [D2]; ESA Cloud_cci PUG [D3], Section 6; in ESA Cloud_cci CECR [D4], Section 11; in ESA Cloud_cci ATBD (MLEV) [D5], Section 4; in AATSR Level 1b Detailed Processing Model [D8], Section 3; in ENVISAT-style Products for ATSR-1 and ATSR-2 data [D9], Section 8; and Sus et al. 2017 and McGarragh et al. 2017 [D6, D7].

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