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Abstract

Precipitation is the result of a chain of meteorological processes ranging from the large- to the micro-scale. While the transport of moisture and lifting mechanisms leading to cloud formation are mostly governed by dynamical processes, the formation and growth of hydrometeors are ultimately determined by microphysical processes. A proper understanding of the complex interactions between atmospheric dynamics and microphysics is of paramount importance to accurately forecast precipitation. In particular, snowfall microphysics is greatly influenced by dynamical processes, such as turbulence and updraughts. Yet, the impact of atmospheric dynamics on snowfall microphysics remains poorly understood. In this thesis, meteorological radars and atmospheric models are combined to investigate how dynamical processes can influence snowfall microphysics. We exploit the synergies between measurements collected with an X-band polarimetric radar (named MXPol), a W-band Doppler radar, and a multi-angle snowflake camera (MASC). Hydrometeor classifications are used to identify the key microphysical processes at play. The objectives of this thesis are twofold: (i) collect data on clouds and precipitation during two field campaigns in South Korea and Antarctica, and (ii) leverage this data to investigate how dynamical processes influenced the microphysics of two snowfall events. First, a 4-month dataset of ground-based radar and in situ measurements collected in South Korea is presented. The dataset includes 9 precipitation events with a total accumulation of 195 mm of equivalent liquid precipitation. Second, measurements of clouds and precipitation during a 3-month campaign at Davis station, Antarctica are introduced. Altogether, both datasets collected during this thesis represent an opportunity to study snowfall microphysics thanks to the complementarity of Doppler radar data and snowflake photographs in two regions where such measurements were not available before. The second part of this thesis is devoted to case studies of two snowfall events. First, a case study of an intense precipitation event in South Korea reveals that a warm conveyor belt associated with a low pressure system provided ideal conditions for riming and aggregation through the generation of turbulence and SLW in the large-scale ascent. These processes led to enhanced precipitation rates of up to 12 mm/h and a total accumulation of 57 mm in 21 h. The second case study shows that orographic gravity waves (OGWs) determined the evolution and distribution of snowfall during an atmospheric river event over Davis in the Vestfold Hills, Antarctica. Despite the intense moisture advection by the atmospheric river, little precipitation was observed at Davis due to intense snowfall sublimation by foehn winds associated with the OGWs. We propose that this mechanism could contribute to the extremely dry climate of the Vestfold Hills, one of the rare ice-free regions of Antarctica. Altogether, this thesis offers two unique datasets which are available to the scientific community and can be used for future studies on snowfall microphysics. It also contributes to a better understanding of how atmospheric dynamics can influence snowfall microphysics. In particular, it illustrates how processes occurring at different spatial scales can determine the dominating snowfall microphysical processes.

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