Global Cloudiness and Cloud Top Information from AVHRR in the 42-Year CLARA-A3 Climate Data Record Covering the Period 1979–2020

Abstract

This paper investigates the quality of global cloud fraction and cloud-top height products provided by the third edition of the CM SAF cLoud, Albedo and surface RAdiation dataset from the AVHRR data (CLARA-A3) climate data record (CDR) produced by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF). Compared with with CALIPSO–CALIOP cloud lidar data and six other cloud CDRs, including the predecessor CLARA-A2, CLARA-A3 has improved cloud detection, especially over ocean surfaces, and improved geographical variation and cloud detection efficiency. In addition, CLARA-A3 exhibits remarkable improvements in the accuracy of its global cloud-top height measurements. For example, in tropical regions, previous underestimations for high-level clouds are reduced by more than 2 km. By taking advantage of more realistic descriptions of global cloudiness, this study attempted to estimate trends in the observable fraction of low-level clouds, acknowledging their importance in producing a net climate cooling effect. The results were generally inconclusive in the tropics, mainly due to the interference of El Nino modes during the period under study. However, the analysis found small negative trends over oceanic surfaces outside the core tropical region. Further studies are needed to verify the significance of these results.

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.…”

“…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.…”

Decadal Stability and Trends in the Global Cloud Amount and Cloud Top Temperature in the Satellite-Based Climate Data Records

“…The subplots in these figures show biases against MODIS-Aqua and the fitted trends therein. All four CDRs show seasonality in the cloud amount biases against MODIS (Figure 1), which can be explained by the different detection sensitivity of these CDRs and the seasonal differences in the monsoonal systems and inter-tropical convergence zones between the two hemispheres (see [45,46] for further details). It is to be noted that all AVHRR based CDRs (i.e.…”

Decadal Stability and Trends in the Global Cloud Amount and Cloud Top Temperature in the Satellite-Based Climate Data Records

“…All four CDRs show seasonality in the cloud amount biases against MODIS (Figure 1), which can be explained by the different detection sensitivity of these CDRs. The differences in detecting clouds over the monsoon regions, the inter-tropical convergence zone, and over the polar regions during respective polar winters can explain the observed seasonality in the biases (see [49,50] for further details). It is to be noted that all AVHRR-based CDRs (i.e., CLARA-A3, ESA Cloud CCI and PATMOS-x) satisfy even the strictest GCOS Goal requirements on the stability of derived cloud amounts.…”