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The TCDR is a brokered version of ESA’s Cloud_cci ATSR2-AATSR version 3.0 (Level-3C) dataset, produced by RAL from the second Along-Track Scanning Radiometer (ATSR-2) on board the second European Remote Sensing Satellite (ERS-2) spanned 1995-2003 and the Advanced ATSR (AATSR) on board ENVISAT spanned 2002-2012. In addition, the Sea and Land Surface Temperature Radiometer (SLSTR) on board of Sentinel-3 spans from 2017 to present and forms the ICDR. The validation for the ICDR is over the period from January 2017 to December 2018. The retrieval algorithm is presented in [D2] and the validation methodology refers to the Cloud_cci Product Validation and Intercomparison Report [D1]. The same methodology is applied to SLSTR dataset.
Poulsen et al. (2019) [D3] is the paper describing the dataset that includes cloud properties as well as Surface Radiation Budget and Earth Radiation Budget products. This document will mainly refer to the Cloud_cci Product Validation and Intercomparison Report [D1].
Executive Summary
The ESA Climate Change Initiative (CCI) Cloud Properties Climate Data Record (CDR) is a brokered product from the ESA Cloud_cci project, while the extension Interim CDR (ICDR) produced from the Sea and Land Surface Temperature Radiometer (SLSTR) is produced specifically for C3S. The product is generated by STFC RAL Space, using the Community Cloud for Climate (CC4CL) processor, based on the Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm.
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Table 1: provides a summary of the estimated accuracies of the TCDR together with the GCOS requirements. The validation results are provided in [D1] section 7-2, with a recommendation for use.Anchor table1 table1
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1 Value obtained from the difference between CDR LWP trend (0.99g/m2/decade) and MODIS LWP trend (8.06g/m2/decade) divided by mean MODIS C6.1 LWP (123g/m²). 2 Value obtained from the difference between CDR IWP trend (-2.27g/m2/decade) and MODIS IWP trend (7.82g/m2/decade) divided by mean MODIS C6.1 IWP (208g/m²). |
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1. Product validation methodology
The validation methodology is described in section 2.4 of [D1]. In summary, we use the bias (mean difference) between CDR and reference data as the metric for accuracy. The bias corrected root mean squared error (bc-RMSE) is used to express the precision of CDR compared to a reference data record, which is also known as the standard deviation about the mean. Stability is calculated as the variation of the bias over a multi-annual time period.
2. Validation results
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2.1 Validation results for the TCDR
The validation results for TCDR products are provided in [D1], section 3 and 4. The evaluation is divided in validation against high quality and satellite-based reference observations (CALIOP, AMSR-E and DARDAR) and an intercomparison to well-established, satellite-based cloud datasets of similar kind (e.g. MODIS Collection 6.1). Table 1 in the Executive summary provides a summary of the resulting TCDR accuracies.
2.1.1 Cloud Fractional Cover (CFC)
Cloud Fractional Cover (CFC) is validated against CALIOP in [D1], section 3.1.1 and compared with MODIS in [D1], section 4.1.1.
A slight underestimation of cloud occurrences is found in the Cloud_cci data compared to CALIOP, which is primarily due to a lack of sensitivity of passive imager data with respect to optically very thin clouds.
2.1.2 Cloud Top Height (CTH)
Cloud Top Height is validated against CALIOP in [D1] section 3.1.3.
For liquid clouds only very small biases (0.12km) and bc-RMSE (0.97km) are found.
For ice clouds, the strong underestimation of cloud top height is evident and a common feature for all three Cloud_cci datasets, and mainly caused by high-level, optically thin clouds. Biases are around -3.5 km and bc-RMSE around 2.3 km. Removing the optically very thin cloud layers at the top of the CALIOP profiles, improves the agreement between Cloud_cci and CALIOP significantly.
2.1.3 Cloud Top Pressure (CTP), Cloud Optical Thickness (COT) and Cloud Effective Radius (CER)
These parameters are compared against MODIS in the following sections of [D1]: Cloud Top Pressure (CTP) is compared in section 4.1.2. Cloud Effective Radius (CER) is compared in section 4.1.5 and 4.1.6. Cloud Optical Thickness (COT) is compared in section 4.1.3 and 4.1.4 for liquid and ice cloud.
2.1.4 Liquid Water Path (LWP) and Ice Water Path (IWP)
Liquid Water Path (LWP) is validated in [D1] section 3.1.4 against AMSR-E products and compared with MODIS in [D1] section 4.1.7.
Ice Water Path (IWP) is validated against DARDAR IWP product in [D1] section 3.1.5 and compared with MODIS in section 4.1.8.
Validating liquid water path over ocean against AMSR-E gives very convincing results for CDR dataset, with bc-RMSE values of 25 g/m², only small biases (-1.44 g/m²) and high correlations (0.76). Validating ice water path against the combined CALIPSO-CloudSat product DARDAR shows good agreement with correlations of 0.45. There is a general underestimation of IWP by Cloud_cci which in terms of relative bias partly exceeds 50%.
2.2 ICDR comparison with MODIS
The first 24 months of SLSTR products have been compared against MODIS (Collection 6.1 Terra) following the same methodology described in [D1] section 4.1. We estimate the bias, i.e. mean differences, and the monthly mean global average of C3S and the MODIS data. To compute the monthly mean global average of both datasets we considered only the valid data between -60 and +60 latitude.
Table 2 shows the bias results from this comparison for both TCDR data (from D1) and for ICDR.
Of the cloud properties considered only the IWP has higher bias against MODIS for the ICDR.
Figure 1 and 2 show show an example of ICDR monthly products for March 2017 and the equivalent monthly product from MODIS.
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Parameters | TCDR (2003-2011) bias | ICDR (2017-2018) bias |
CFC |
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CTP | -25 hPa | -15 hPa |
LWP | -17.3 g/m2 | -16.0 g/m2 |
IWP | -28.8 g/m2 | -34 g/m2 |
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Figure 1: CFC, CTP, LWP and IWP from SLSTR (ICDR dataset) for March 2017.
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Figure 2. CFC, CTP, LWP and IWP from MODIS dataset for March 2017
3. Application(s) specific assessment
N/A
4. Compliance with user requirements
The main validation results are summarized in [D1], Section 7, including a comparison with GCOS requirements in table 7.2. We report here a summary.
Table 1 provides an overview of the GCOS requirements for the Cloud Properties and the values achieved by TCDR. It should be noted that GCOS requirements are targets and are often not attainable using existing or historical observing systems. The Cloud_cci doesn’t meet the frequency requirement (3h) due to the nature of the satellite observations, but exceeds the spatial resolution (50 km GCOS target). ICDR accuracies (estimate with the first 24 months only) are consistent with TCDR accuracies apart from IWP where we find slightly higher bias in comparison with MODIS (section 2.2).
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Recommendation on the usage and know limitations (from [D1] table 7.1):
Cloud Fractional Cover (CFC)
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