The ERA5's diurnal cycle of low-level clouds over Western Central Africa during June–September: Dynamic and thermodynamic processes

Dommo, A.; Vondou, Derbetini A.; Philippon, Nathalie; Eastman, Ryan; Moron, Vincent; Aloysius, N.

doi:10.1016/j.atmosres.2022.106426

Cited by 10 publications

(11 citation statements)

References 60 publications

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“…Afternoon low‐level clouds are thus the most sensitive part of the diurnal cycle at the interannual time scale. This sensitivity fits well with the mean diurnal cycle in JJAS, which shows minimal LCF during the afternoon and early night (Champagne et al, 2023; Dommo et al, 2022). While the agreement between station diurnal types and their corresponding ERA5 grid‐points is only moderate at daily time scale, the interannual variations are very similar over the cloudiest area of Gabon and southwestern RC represented by the leading JJAS principal component of the anomalous frequencies of the diurnal types.…”

Section: Summary and Concluding Remarkssupporting

confidence: 77%

“…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).…”

Section: Space–time Variations Of the Stratiform Cloud Deckmentioning

confidence: 99%

“…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:…”

Section: Definition Of Low-level Cloud Cover Diurnal Typesmentioning

confidence: 99%

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

Moron

Camberlin

Aellig

et al. 2023

Intl Journal of Climatology

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This study examines the diurnal to interannual variations of the stratiform cloud cover in May–October (1971–2019) from a 3‐hourly station database and from ERA5 reanalyses over western equatorial Africa (WEA). The main diurnal variations of the local‐scale fraction and genus of stratiform clouds are synthesized into three canonical diurnal types (i.e., “clear,” “clear afternoon,” “cloudy” days). The interannual variations of frequencies of the three diurnal types during the cloudiest months (JJAS) are mostly associated with two main mechanisms: a meridional shallow overturning cell associating more “cloudy” and less “clear” and “clear afternoon” days to anomalous southerlies below 900 hPa over and around WEA, anomalous ascent around 5°–7°N, anomalous northerlies between 875 and 700 hPa, and anomalous subsidence over the equatorial Atlantic. This circulation is strongly related to interannual variations of the equatorial Atlantic upwelling (i.e., more clouds when the upwelling is strong) associated with a meridional shift of the Intertropical Convergence Zone over the Tropical Atlantic and adjacent continents. The second mechanism operates mostly in the zonal direction and involves again the coupled ocean–atmosphere system over the equatorial Atlantic, but also the remote El Niño–Southern Oscillation (ENSO). An anomalously cold equatorial Atlantic drives increased low‐level westerlies toward the Congo Basin. Warm ENSO events promote broad warm and easterly anomalies in the middle and upper troposphere, which increase the local static stability, and thus the local stratiform cloud cover over WEA. The present study suggests new mechanisms responsible for interannual variations of stratiform clouds in WEA, thus providing avenues of future research regarding the stability of the stratiform cloud deck under the ongoing differential warming of tropical ocean and land masses.

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Section: Summary and Concluding Remarkssupporting

confidence: 77%

Section: Space–time Variations Of the Stratiform Cloud Deckmentioning

confidence: 99%

Section: Definition Of Low-level Cloud Cover Diurnal Typesmentioning

confidence: 99%

See 1 more Smart Citation

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

Moron

Camberlin

Aellig

et al. 2023

Intl Journal of Climatology

Self Cite

View full text Add to dashboard Cite

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“…It was found temporally consistent with Moderate Resolution Imaging Spectroradiometer (MODIS) data. The diurnal cycle of LCF from ERA5 also matches with the Extended Edited Synoptic Cloud Reports Archive (EECRA) data(Dommo et al 2022).…”

supporting

confidence: 60%

Contrasting temporal trends in low-level clouds and mid- and high-level clouds over the Indian Ocean in the last four decades (1979–2018)

Moher,

Dutta,

Pant

et al. 2024

Environ. Res. Commun.

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Understanding the climatic trends in cloud fraction (fc) and its drivers is critical in climate science. Here, we analyzed 40 years (1979-2018) of hourly fc data at 0.25°×0.25° spatial scale from ERA5 to examine the trends in the 3-D distribution of fc over the oceanic region adjacent to the Indian Subcontinent in view of its drivers. We found that the mid-level fc (MCF) and high-level fc (HCF) have increased by 0.05 and 0.05-0.12 fraction in the last four decades in this region. On the contrary, the low-level fc (LCF) decreased by 0.04 fraction, resulting in a net marginal increase in total fc. The observed contrasting trends in LCF, MCF and HCF are manifestations of the changes in sea surface temperature and meteorological conditions. Although LCF showed a regionally averaged declining trend, it has increased over the south-southwestern part of the domain. The increasing trend of MCF and HCF can be attributed to the increase in natural convection due to surface warming. Our results suggest that the observed contrasting trends might have resulted in positive radiative feedback on the Indian Ocean warming.

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“…With a 0.25 • horizontal grid, ERA5 can provide hourly horizontal wind, air temperature and humidity data, and it has 37 pressure levels below 1 hPa [48]. Because of its great geographical and temporal resolution, ERA5 has been frequently employed in studies on air pollution [49], clouds [50] and heavy rainfall [51]. In this study, ERA5 was used from 2016 to 2021, and the high spatiotemporal resolutions of the ERA5 dataset can meet the criteria of vertical structure analysis [52][53][54].…”

Section: Era5 Reanalysis Datamentioning

confidence: 99%

The Effects of Planetary Boundary Layer Features on Air Pollution Based on ERA5 Data in East China

et al. 2023

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The planetary boundary layer (PBL) structure and its evolution can significantly affect air pollution. Here, the PBL’s characteristics and their association with air pollution were analyzed in Hefei, east China, using ERA5 reanalysis data, weather observations and air pollutant measurements from 2016 to 2021. In the near-surface level, air pollution was directly influenced by ground meteorological conditions, and high PM2.5 was normally related to weak wind speed, northwest wind anomalies, low temperature and high relative humidity. Moreover, in the trajectory analysis, air masses from the north and the northwest with short length played an important role in the high PM2.5 with pollutant transport within the PBL. Furthermore, high PM2.5 showed a tight dependence on PBL stratification. There was high temperature and relative humidity and low wind speed and PBL height within all PBL altitudes in the polluted condition. Notably, vertical wind shear (VWS) and temperature gradient tended to be much weaker below 900 hPa, which created a deeply stable stratification that acted as a cap to upward-moving air. Such a PBL structure facilitated more stable stratification and enhanced the generation of air pollution. Finally, the stable stratification in the PBL was related to the special synoptic configuration for the high PM2.5 conditions, which included the block situation at the high level, the southerly wind anomalies at the middle level and the wild range of the uniform pressure field at the near-ground level. Therefore, air pollutant concentrations were regulated by ground factors, PBL structure and the synoptic situation. Our results provide a precise understanding of the role of PBL features in air pollution, which contributes to improving the assimilation method of the atmospheric chemistry model in east China.

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The ERA5's diurnal cycle of low-level clouds over Western Central Africa during June–September: Dynamic and thermodynamic processes

Cited by 10 publications

References 60 publications

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

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

Contrasting temporal trends in low-level clouds and mid- and high-level clouds over the Indian Ocean in the last four decades (1979–2018)

The Effects of Planetary Boundary Layer Features on Air Pollution Based on ERA5 Data in East China

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