Cloud Radar Observations of Diurnal and Seasonal Cloudiness over Reunion Island

Jonathan Durand,Julien Delanoë,Edouard Lees,Olivier Bousquet,François Bonnardot

doi:10.3390/atmos12070868

Abstract

In November 2016, a 95 GHz cloud radar was permanently deployed in Reunion Island to investigate the vertical distribution of tropical clouds and monitor the temporal variability of cloudiness in the frame of the pan-European research infrastructure Aerosol, Clouds and Trace gases Research InfraStructure (ACTRIS). In the present study, reflectivity observations collected during the two first years of operation (2016–2018) of this vertically pointing cloud radar are relied upon to investigate the diurnal and seasonal cycle of cloudiness in the northern part of this island. During the wet season (December–March), cloudiness is particularly pronounced between 1–3 km above sea level (with a frequency of cloud occurrence of 45% between 12:00–19:00 LST) and 8–12 km (with a frequency of cloud occurrence of 15% between 14:00–19:00 LST). During the dry season (June–September), this bimodal vertical mode is no longer observed and the vertical cloud extension is essentially limited to a height of 3 km due to both the drop-in humidity resulting from the northward migration of the ITCZ and the capping effect of the trade winds inversion. The frequency of cloud occurrence is at its maximum between 13:00–18:00 LST, with a probability of 35% at 15 LST near an altitude of 2 km. The analysis of global navigation satellite system (GNSS)-derived weather data also shows that the diurnal cycle of low- (1–3 km) and mid-to-high level (5–10 km) clouds is strongly correlated with the diurnal evolution of tropospheric humidity, suggesting that additional moisture is advected towards the island by the sea breeze regime. The detailed analysis of cloudiness observations collected during the four seasons sampled in 2017 and 2018 also shows substantial differences between the two years, possibly associated with a strong positive Indian Ocean Southern Dipole (IOSD) event extending throughout the year 2017.

Highlights

Because cloudiness plays a major role in distributing the radiative energy available in the atmosphere [1,2], knowledge of cloud properties is crucial for anticipating the impacts of cloud cover and, in particular, low-level cloud feedbacks in climate change projections [3]
If one except a few studies conducted from the Atmospheric Radiation Measurement (ARM) Tropical Western Pacific (TWP) sites [14,15,16], the latter were essentially conducted in the northern hemisphere due to the overall lack of observation facilities available south of the equator
The permanent deployment, in 2016, of a 95 GHz vertically pointing cloud radar BASTA in Reunion Island is an important achievement in order to reinforce cloud observations and atmospheric science research capabilities in the Southwest Indian Ocean (SWIO)

Summary

Introduction

Because cloudiness plays a major role in distributing the radiative energy available in the atmosphere [1,2], knowledge of cloud properties is crucial for anticipating the impacts of cloud cover and, in particular, low-level cloud feedbacks in climate change projections [3]. This new observation facility, located on the northern coast of the island at Saint-Denis de La Réunion (Figure 1), was notably equipped, in 2016, with a 95 GHz radar BASTA (Bistatic rAdar SysTem for Atmospheric Studies; [24]) to collect cloud observations at high spatial and temporal resolutions This new site is, in particular, well-adapted to investigate coastal tropical clouds, which are known to occur over different mid-tropospheric conditions than over the open ocean and continental areas due to the combined effects of land–sea breeze interactions [25]. Reflectivity observations collected during the two first years of operation of the cloud radar BASTA are used to investigate the characteristics of cloudiness in Reunion Island as well as its relationship with local and regional tropospheric humidity patterns inferred from radiosounding, Global Navigation Satellite System (GNSS) and high-resolution reanalysis data. Analysis of Local and Large‐Scale Environmental Conditions Prevailing in 2017 and 2018

IOSD Patterns

Large Scale Anomalies

Local Observations

Findings

Discussion and Conclusions