CLARA-A3: The third edition of the AVHRR-based CM SAF climate data record on clouds, radiation and surface albedo covering the period 1979 to 2023

Abstract

Abstract. This paper presents the third edition of The Satellite Application Facility on Climate Monitoring's (CM SAF) cloud, albedo, and surface radiation dataset from advanced very-high-resolution radiometer (AVHRR) data, CLARA-A3. The content of earlier CLARA editions, namely cloud, surface albedo, and surface radiation products, has been extended with two additional surface albedo products (blue- and white-sky albedo), three additional surface radiation products (net shortwave and longwave radiation, and surface radiation budget), and two top of atmosphere radiation budget products (reflected solar flux and outgoing longwave radiation). The record length is extended to 42 years (1979–2020) by also incorporating results from the first version of the advanced very high resolution radiometer imager (AVHRR/1). A continuous extension of the climate data record (CDR) has also been implemented by processing an interim climate data record (ICDR) based on the same set of algorithms but with slightly changed ancillary input data. All products are briefly described together with validation results and intercomparisons with currently existing similar CDRs. The extension of the product portfolio and the temporal coverage of the data record, together with product improvements, is expected to enlarge the potential of using CLARA-A3 for climate change studies and, in particular, studies of potential feedback effects between clouds, surface albedo, and radiation. The CLARA-A3 data record is hosted by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) CM SAF and is freely available at https://doi.org/10.5676/EUM_SAF_CM/CLARA_AVHRR/V003 (Karlsson et al., 2023b).

Difference between WMO Climate Normal and Climatology: Insights from a Satellite-Based Global Cloud and Radiation Climate Data Record

“…The differences between CN_WMO and Clim40 shown in Figures 1 and 3 for the total and low cloud fraction, respectively, are noteworthy. Previous studies have shown that the global cloud cover is generally decreasing when the trends are computed over the last forty years [21,23,25,26,48]. The decrease has mainly occurred over the sub-tropical to mid-latitudes in both hemispheres.…”

“…In this study, we use the data from the third edition of the CM SAF cLoud, Albedo and surface RAdiation dataset from AVHRR data, CLARA-A3 [21]. This climate data record has a rich history of dedicated, continuous developments and improvements dating back to its beginning 25 years ago in the framework of EUMETSAT's Satellite Application Facility on Climate Monitoring [46].…”

“…It employs cloud probabilistic detection based on the Naïve Bayesian theory, while the cloud top property algorithms employ artificial neural networks. A number of recent studies have documented the theoretical basis, validations, and improvements in the CLARA-A3 climate data record [21,26,[47][48][49].…”

“…Similar to the results shown for total cloud fraction before, The situation over the Antarctic and Greenland is even more interesting. Here, the data gaps in climate normals are not just due to the prevailing clear sky conditions, but also due to the fact that the cloud detection algorithm in CLARA-A3 may miss clouds over the bright and cold polar regions, especially in cases of extremely cold surface temperatures [21,48], and then no other cloud properties are retrieved downstream. This shows that the cloud detection sensitivity of climate data records could also play an important role while computing the climate normals.…”

“…The satellite sensors now provide information on more than two-thirds of all ECVs, and many of them do cover the entire 1991-2020 period [14,15]. Furthermore, there have been stratospheric improvements in the retrievals of ECVs in the recent decades, uplifting their quality and maturity to a level where climate data records of ECVs are being provided [16][17][18][19][20][21][22][23][24][25][26][27].…”