Effect of Clouds on the Diurnal Evolution of the Atmospheric Boundary-Layer Height Over a Tropical Coastal Station

Davis, Edwin V.; Rajeev, K.; Mishra, Manoj Kumar

doi:10.1007/s10546-019-00497-6

Cited by 18 publications

(21 citation statements)

References 42 publications

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“…The outflow of warm continental air masses leads to the dissipation of cloud (Painemal et al, 2014). Our findings of higher means and high variability in BLHs (RN) under clear sky conditions between April and August, were in good agreement with the results of Davis et al, (2020). Based on these findings, we can conclude that the variability in the BLH (RN) over Walvis Bay is a function of the origin and direction of airflow, and surface heating that, in combination with macroscale circulation, is also linked to the frequency of occurrence and variability in cloud fractions.…”

Section: Cloud Fractionsupporting

confidence: 91%

“…During these times, we found the steepest zonal gradients in low-level inversion strengths, with strengths decreasing towards the subcontinent (Figure 10 and Figure 12). Sea-breezes have been found to inhibit the noontime convective development of the coastal BLH (Davis et al, 2020), but we could not detect this in our once daily, morning measurements. This effect is also not apparent in the MG height (Figure 8), but it may be responsible for maintaining low noontime low-level inversion heights (Figure 11).…”

Section: Differential Heatingcontrasting

confidence: 56%

“…Differential heating across the cold ocean and coastal margin, and the mainly arid landscapes across the subcontinent, results in the formation of steep temperature and pressure gradients across the region on diurnal and seasonal scales (Markowski and Richardson, 2010;Tyson and Preston-Whyte, 2014). The resultant winds that form between the marine and continental atmospheres are a significant modulator of the BLH along the coastal margin (Davis et al, 2020). Land breezes and berg winds are known to enhance stability and typically form at night and in the winter near the surface and at the BL top (Ao et al, 2012;Davis et al, 2020;Tlhalerwa et al, 2005).…”

Section: Differential Heatingmentioning

confidence: 99%

“…The resultant winds that form between the marine and continental atmospheres are a significant modulator of the BLH along the coastal margin (Davis et al, 2020). Land breezes and berg winds are known to enhance stability and typically form at night and in the winter near the surface and at the BL top (Ao et al, 2012;Davis et al, 2020;Tlhalerwa et al, 2005). Evidence of this is seen in the high BLHs (RN) and high variability in winter (Figure 4), which coincides with the increased frequency of occurrence in local easterly wind components below 500 m (Figure 5).…”

Section: Differential Heatingmentioning

confidence: 99%

“…The lifetime and fraction of low-cloud cover is a known modulator of the BLH over tropical coasts (Davis et al, 2020). In the presence of clouds, some of the incoming solar radiation is intercepted at cloud top, limiting the convective heating at the surface, and resulting in an overall lower BLH as compared to clear sky conditions (Davis et al, 2020), as seen in our low BLHs (RN) between October and March, when cloud fractions over the area are higher than for the rest of the year (Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), available at: https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/; last accessed: 24/03/2021: Gelaro et al, 2017). The outflow of warm continental air masses leads to the dissipation of cloud (Painemal et al, 2014).…”

Section: Cloud Fractionmentioning

confidence: 99%

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Atmospheric stratification over Namibia and the southeast Atlantic Ocean

Klopper

Burger

Dirkse

et al. 2021

Preprint

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Abstract. We currently have a limited understanding of the spatial and temporal variability in vertically stratified atmospheric layers over Namibia and the southeast Atlantic (SEA) Ocean. Stratified layers are relevant to the transport and dilution of local and long-range transported atmospheric constituents. This study used eleven years of global positioning system radio occultation (GPS-RO) signal refractivity data (2007–2017) over Namibia and the adjacent ocean surfaces, and three years of radiosonde data from Walvis Bay, Namibia, to study the character and variability in stratified layers. From the GPS-RO data and up to a height of 10 km, we studied the spatial and temporal variability in the point of minimum gradient in refractivity, and the temperature inversion height, depth and strength. We also present the temporal variability of temperature inversions and the boundary layer height (BLH) from radiosondes. The BLH was estimated by the parcel method, the top of a surface-based inversion, the top of a stable layer identified by the bulk Richardson number (RN), and the point of minimum gradient in the refractivity (for comparison with GPS-RO data). A comparison between co-located GPS-RO to radiosonde temperature profiles found good agreement between the two, and an average underestimation of GPS-RO to radiosonde temperatures of −0.45 ± 1.25 °C, with smaller differences further from the surface and with decreasing atmospheric moisture content. The minimum gradient (MG) of refractivity, calculated from these two datasets were generally in good agreement (230 ± 180 m), with an exeption of a few cases when differences exceeded 1000 m. The surface of MG across the region of interest was largely affected by macroscale circulation and changes in atmospheric moisture and cloud, and was not consistent with BLH(RN). We found correlations in the character of low-level inversions with macroscale circulation, radiation interactions with the surface, cloud cover over the ocean and the seasonal maximum in biomass burning over southern Africa. Radiative cooling on diurnal scales also affected elevated inversions between 2.5 and 10 km, with more co-occurring inversions observed at night and in the morning. Elevated inversions formed most frequently over the subcontinent and under subsidence by high-pressure systems in the colder months. Despite this macroscale influence peaking in the winter, the springtime inversions, like those at low levels, were strongest.

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Section: Cloud Fractionsupporting

confidence: 91%

Section: Differential Heatingcontrasting

confidence: 56%