Climatology of Low-Level Clouds over Western Equatorial Africa Based on Ground Observations and Satellites

Abstract

The tropical cloud forest ecosystem in Western Equatorial Africa (WEA) is known to be sensitive to the presence of an extensive and persistent low-level stratiform cloud deck during the long dry season from June to September (JJAS). Here we present a new climatology of the diurnal cycle of the low-level cloud cover from surface synoptic stations over WEA during JJAS 1971–2019. For the period JJAS 2008–2019, we also utilized estimates of cloudiness from four satellite products, namely the Satellite Application Facility on Support to Nowcasting and Very Short Range Forecasting (SAFNWC) cloud classification, the Day and Night Microphysical Schemes (DMS/NMS) and cross-sections from CALIPSO and CloudSat (2B-GEOPROF-LIDAR). A comparison with surface stations reveals that the NMS at night together with SAFNWC at daytime yield the smallest biases. The climatological analysis reveals that low-level clouds persist during the day over the coastal plains and windward side of the low mountain ranges. Conversely, on their leeward sides, i.e. over the plateaus, a decrease of the low-level cloud frequency is observed in the afternoon, together with a change from stratocumulus to cumulus. At night, the low-level cloud deck reforms over this region with the largest cloud occurrence frequencies in the morning. Vertical profiles from 2B-GEOPROF-LIDAR reveal cloud tops below 3000 m even at daytime. The station data and the suitable satellite products form the basis to better understand the physical processes controlling the clouds and to evaluated cloudiness from reanalyses and models.

Diurnal to interannual variability of low‐level cloud cover over western equatorial Africa in May–October

“…LCF (in oktas) and LCG (the nine low cloud genera defined by the WMO standards plus two extra categories [#10: “sky obscured by fog” and #11: “cumulonimbus with thunderstorm”]) as well as many meteorological characteristics over 85 synoptic stations in the 1971–2009 period. This primary EECRA dataset has been completed by various sources, detailed in Champagne et al (2023), leading to a consistent quality‐controlled database of 3‐hourly LCF and LCG observed at 88 stations (Figure 1) in the May to October 1971–2019 period (Aellig et al, 2022). Three stations unavailable in EECRA have also been added.…”

“…Topography (grey shadings in meter asl) and location of the 26 stations (named black dots) used in most of the analyses. The stations of the original data set (Aellig et al, 2022; Champagne et al, 2023) used for climatology only (Figure 3) are plotted as unnamed red dots [Colour figure can be viewed at wileyonlinelibrary.com]…”

“…The analysis of interannual variations is not as trivial as the one of diurnal and seasonal cycles, which are very strong in amplitude and well sampled. There are three main issues; (1) the amount of missing entries in the observed dataset (Champagne et al, 2023); (2) the relatively small amount of variance beyond the diurnal and seasonal cycles; (3) the large time and spatial heterogeneities in the sampling.…”

“…To overcome some of the above issues, a k ‐means cluster analysis is applied to unfiltered diurnal LCF variations (i.e., variations within 1 day) (Figure 5). The clustering enables classifying all days at all available stations into basic diurnal types (DTs, see section 3.3), portraying typical variations of low cloud cover relative to the mean diurnal cycle, which usually peaks in late night and morning and decreases during the afternoon (Champagne et al, 2023; Dommo et al, 2022). The methodology, detailed in Figure 5, allows the optimization of the available data by following two different paths: (1) Using first the small set of complete daily records to define the DTs as centroids of the clusters of diurnal 3‐hourly LCF (upper part of Figure 5) and (2) then projecting the remaining incomplete days (and ERA5), sampling at least the LCF around its usual highest and lowest daily intensity (lower part of Figure 5).…”

“…In this subsection, we analyse the space–time interannual variations of low‐level cloud cover during the core of the cloudy season of JJAS (Figures 3 and 7), as in Champagne et al (2023) and Camberlin et al (2023). Classical EOF analysis is applied to the frequencies of the three DTs.…”