"Low-level stratiform clouds remain one of the wildcards in future climate simulations. Despite their important role in the earth's radiation budget and the large number of dedicated field campaigns, several cloud-scale processes in marine stratocumulus clouds remain misrepresented. The 19-month-long deployment of the Atmospheric Radiation Measurement Program Mobile Facility in the Azores provided the longest and most comprehensive ground-based observational dataset of marine boundary layer clouds to date. The first objective of this project was the documentation of the frequency of occurrence of different cloud and precipitation systems in the Azores using a combination of passive and active measurements. The analysis indicates that, even though clouds were often observed (close to 80 % of the time), especially in the boundary layer (~50 %), a single-layer stratocumulus coverage rarely persisted more than a day. In fact, many stratocumulus clouds were observed to have cumulus clouds underneath them. This is linked to the nearly constant decoupled state of the boundary layer in the Azores, contrary to what has been observed in the Pacific decks. 35 cases of mostly single-layer persisting stratocumulus coverage were selected for further analysis. Results include similarities with other studies (e.g., maximum coverage at night, thicker clouds needed to drizzle, and importance of cloud-top radiative cooling at night), as well as differences (e.g., coherent structures account for a smaller fraction of the updraft mass flux). The second objective of this project was to revisit the detection of drizzle-size particles in stratocumulus clouds using radar observations. First, the cloud and drizzle size distributions are related theoretically to the radar measurements, including the effects of the dynamics. Then, a forward radar Doppler spectra model was developed to test the sensitivity of the radar measurements to modifications of the drizzle contribution. Finally, a simple 1-D steady-state model was exploited to simulate drizzle growth as it falls in a cloud, using the forward model to link the output back to the radar observations. Using that combination of models, some observed features of the drizzle evolution inside continental and maritime stratocumulus clouds were successfully investigated. Overall, it was found that the skewness of a radar Doppler spectrum is a good indicator of the presence of early drizzle droplets, while a reflectivity or Doppler velocity threshold indicates the change in dominance in the Doppler spectrum occurring when drizzle is well developed. The third and final objective of this project was to revisit another long-standing challenge: the retrieval of cloud microphysical properties using a combination of radar-radiometer measurements. A new technique was developed to retrieve the cloud particle size distribution in stratocumulus clouds, adding a microphysical condensational model under steady-state supersaturation conditions to a common retrieval method. The results appear reasonable in two nondrizzling marine stratocumulus clouds, and the derived cloud optical depth compares well with the one derived independently with another instrument. The errors of the retrievals were also estimated, demonstrating the added value of the new technique." --

Marine stratocumulus clouds (Sc) cover large areas of the Earth and have a substantial impact on the Earth's radiative balance by reflecting copious amounts of sunlight away from the Earth and emitting longwave radiation at a temperature close to surface. Cloud and precipitation (drizzle) liquid water content (hereafter CLWC and PLWC) are two of the most important microphysical properties of Sc which directly affect radiative transfer and the hydrological cycle, as well as play a critical role in many microphysical and planetary boundary layer processes. It is thus crucial to determine CLWC and PLWC accurately. Sc in many global climate models (GCMs) are found to precipitate too frequently and too lightly which is likely due in part to the lack of information on the subgrid variability in CLWC and PLWC in the calculation of autoconversion and accretion rates. In most GCMs, the effects of subgrid variability have been either completely ignored or incorporated by multiplying the autoconversion and accretion rates (based on grid-mean values) by an enhancement factor to account for the subgrid variability. This dissertation aims to retrieve CLWC and PLWC jointly for Sc based on a millimeter wavelength radar, and to examine the nature of spatial variability in CLWC and PLWC and its impact on the autoconversion and accretion rates. In particular, we derive enhancement factors for autoconversion and accretion rates based on the radar observations, and examine how the enhancement factors change with different factors such as the length scale (size of a GCM grid) and the frequency of below-cloud precipitation. In the first part of the dissertation (Chapter 2), the CLWC and PLWC are retrieved based on a combination of retrieval techniques including a novel Doppler spectra decomposition method that separates Doppler spectra into a cloud and a precipitation component. The radar Doppler spectra data from a vertically pointing Ka-band cloud radar, along with total liquid water path from a three-channel microwave radiometer (MWR) and radiosonde measurements are used in the retrievals. These observational data in this study were collected at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Eastern North Atlantic (ENA) site. At the scale of a single radar volume, the uncertainty of our retrieved PLWC is about an order of magnitude. By comparing to in-situ aircraft observations, we find on average they are in a good agreement. On the scale of one day, the uncertainty in the mean CLWC is estimated to be within 30% and the systematic errors in the mean PLWC are estimated to be less than 75%. In the second part of the dissertation (Chapter 3), the variability in CLWC and PLWC and its effects on the grid-mean autoconversion and accretion rates are examined, specifically enhancement factors for autoconversion rate (E[subscript]auto) and accretion rate (E[subscript]accr). In many studies (and model implementations) enhancement factors are formulated under the assumption that variability in cloud and precipitation mixing ratio (water content divided by the air density) can be represented by a bivariate lognormal distribution with three key parameters: (i) the fractional standard deviation of the cloud-water mixing ratio, (ii) the fractional standard deviation of precipitating water mixing ratio, and (iii) the (cross) correlation coefficient (between cloud and precipitation mixing ratio). Therefore, both the enhancement factors and these three parameters are evaluated. Overall, we find that while our retrieved joint distribution is not truly a bivariate lognormal, this framework nonetheless works well given the correct values for the three key parameters. In general, we find that E[subscript]auto and E[subscript]accr increase with grid size and have a maximum when precipitation fraction is about 0.4 - 0.6 (depending somewhat on how precipitation occurrence is defined and grid size). E[subscript]auto stays relatively unchanged due to the assumption made in the retrievals that CLWC increases linearly with height in the cloud. E[subscript]accr generally decreases from cloud base to cloud top although an increase in correlation of q[subscript]c and q[subscript]p and a decrease in the magnitude of the subgrid variability of q[subscript]p have some offsetting effects. In addition, we find that E[subscript]auto and E[subscript]accr have little if any correlations with relative humidity (RH), lower tropospheric stability (LTS), and mean liquid water path (LWP) or mean cloud thickness. However, they are highly correlated with variability in of LWP, cloud thickness and cloud base, suggesting that any knowledge in subgrid variability might be useful in predicting E[subscript]auto and E[subscript]accr.

An attempt is made to examine the credibility and explore the implications of the reports of convective clouds to extreme heights which have been indicated by radar in recent years. The extreme cases have not been verified by independent observations and it is shown that inherent limitations in radar observations of convective cloud heights are such as to raise serious doubts in regard to the accuracy of many of the extreme echo heights which have been reported. (Author).

Understanding the onset of coalescence in warm clouds is key in our effort to improve cloud representation in numerical models. Coalescence acts at small scales, and its study requires detailed high-resolution dynamical and microphysical measurements from a comprehensive suite of instruments over a wide range of environmental conditions (e.g., aerosol loading). The first AMF is currently in its second year of a two-year deployment at Graciosa Island in the Azores, offering the opportunity to collect a long data set from a stable land-based platform in a marine stratocumulus regime. In this study, recorded WACR Doppler spectra are used to characterize the properties of Doppler spectra from warm clouds with and without drizzle, and from drizzle only, in an effort to observe the transition (onset) to precipitation in clouds. A retrieval technique that decomposes observed Doppler spectra into their cloud and/or drizzle components is applied in order to quantify drizzle growth.