The role of aerosols and clouds is one of the largest sources of uncertainty in understanding climate change. The primary scientific goal of this thesis is to improve the understanding of cloud-aerosol interactions by applying inverse modeling using Markov Chain Monte Carlo (MCMC) simulation. Through a set of synthetic tests using a pseudo-adiabatic cloud parcel model, it is shown that a self adaptive MCMC algorithm can efficiently find the correct optimal values of meteorological and aerosol physiochemical parameters for a specified droplet size distribution and determine the global sensitivity of these parameters. For an updraft velocity of 0.3 m s-1, a shift towards an increase in the relative importance of chemistry compared to the accumulation mode number concentration is shown to exist somewhere between marine (~75 cm-3) and rural continental (~450 cm-3) aerosol regimes. Examination of in-situ measurements from the Marine Stratus/Stratocumulus Experiment (MASE II) shows that for air masses with higher number concentrations of accumulation mode (Dp = 60-120 nm) particles (~450 cm-3), an accurate simulation of the measured droplet size distribution requires an accurate representation of the particle chemistry. The chemistry is relatively more important than the accumulation mode particle number concentration, and similar in importance to the particle mean radius. This result is somewhat at odds with current theory that suggests chemistry can be ignored in all except for the most polluted environments. Under anthropogenic influence, we must consider particle chemistry also in marine environments that may be deemed relatively clean. The MCMC algorithm can successfully reproduce the observed marine stratocumulus droplet size distributions. However, optimising towards the broadness of the measured droplet size distribution resulted in a discrepancy between the updraft velocity, and mean radius/geometric standard deviation of the accumulation mode. This suggests that we are missing a dynamical process in the pseudo-adiabatic cloud parcel model. / At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Submitted. Paper 4: Manuscript.

A detailed understanding of cloud microphysical processes is crucial for a large range of scientific disciplines that require knowledge of cloud particles for accurate climate and weather prediction. This thesis focuses on 3 measurement campaigns, encompassing both airborne and ground based measurements of the microphysical structures observed in cold, warm and occluded frontal systems around the United Kingdom, stratocumulus clouds in the Arctic and many different clouds observed over a 6 week period at a high-alpine site in the Swiss Alps. Particular attention was paid to the origin and distribution of both primary and secondary ice and the dominant features associated with ice phase processes. During investigation of cold, warm and occluded frontal systems associated with mid-latitude cyclones around the U.K., secondary ice was often found to dominate the number and mass concentrations of ice particles in all systems. The presence of large liquid droplets was sometimes observed in close proximity to regions of secondary ice production. The existence of these provides a possible mechanism by which rime-splintering is greatly enhanced through the creation of instant rimers as the large drops freeze. In-situ measurements during the cold frontal case were used to calculate rates of diabatic heating during a comparison between bin-resolved and bulk microphysics schemes. Observations in arctic stratocumulus clouds during spring and summer seasons revealed higher ice concentrations in the summer cases when compared to the spring season. This is attributed to secondary ice production actively enhancing ice concentrations in the summer, due to the higher temperature range the clouds spanned. At Jungfraujoch in the Swiss Alps, ground based measurements allowed us to obtain high spatial scale resolution measurements of cloud microphysics and we found transitions between high and low ice mass fractions that took place on differing temporal scales spanning seconds to hours. During the campaign measurements of aerosol properties at an out of cloud site, Schilthorn, were made. When analysing a Saharan Dust Event that took place a possible link between the number of U.V. fluorescent particles and the number of ice particles was found in the temperature range around -10 ºC.

The Swedish Armed Forces setup of the Weather Research and Forecasting Model (WRF) has problems to forecast low clouds in stably stratified conditions when the ground is covered by snow. The aim of this thesis is to understand what causes this deficit. Simulations during January and February 2018 are here compared with observations from Sodankylä in northern Finland. It is revealed that neither type of planetary boundary layer parameterization chosen nor vertical or horizontal interpolation are responsible for the deficiency. Instead, our experiments show that, to first order, poor initialization of Stratocumulus (Sc) clouds from the host model, Atmospheric Model High Resolution (HRES), of the Integrated Forecast System (IFS) is the missing link. In situations when Sc clouds are missing in the IFS analysis, although they exist in reality, we use information from vertical soundings from Sodankylä. In the initialization process we used the fact that liquid potential temperature is constant in a well-mixed cloud. Initializing cloud water and cloud ice from IFS HRES and from soundings with different methods improves the model performance and the formation of very low artificial clouds at the first model level is prohibited.

Representations of Boundary Layer Cloudiness and Surface Wind Probability Distributions in Subtropical Marine Stratus and Stratocumulus Regions Yanping He 153 pages Directed by Dr. Robert E. Dickinson A simple low cloud cover scheme is developed for the subtropical marine stratus and stratocumulus (MSC) regions. It is based on a modified CIN concept named the Lower Troposphere Available Dry Inhibition Energy (ADIN). The e-folder time for the local change of ADIN is found to be approximately 6 to 7 hours. On monthly and longer timescales, local productions of ADIN are balanced by local destructions of ADIN within lower troposphere. Dynamical transport of environmental dry static energy and surface evaporation lead to the variations of cloud top radiative cooling, which is a linear function of low cloud cover. Data analysis suggests that total ADIN dynamical transport plays the most important role in determining the seasonal variations and spatial variations of low cloud amounts¡£ The new scheme produces realistic seasonal and spatial variations of both EECRA ship observation and satellite observations in all MSC regions. It explains 25% more covariance than that using Klein-Hartmann (KH) scheme for monthly ISCCP low cloud amount near the Peruvian and Canarian region during the period from 1985 to 1997£¬it better represents the relationship between ENSO index and low cloud cover variations near the Peruvian region. When implemented into NCAR CAM3.1, it systematically reduces the model biases in the summertime spatial variations of low cloud amount and downward solar radiation in the Peruvian, California, and Canarian regions. Model simulated summertime cloud liquid water path, large scale precipitation, and surface fluxes are also significantly changed. A single predictor named Lower troposphere available thermal inhibition energy (ATIN) is also shown to be more skillful than the lower tropospheric stability in diagnosing low cloud stratiform clouds in the monthly and seasonal timescales. On synoptic timescale, dynamical transport of available dry inhibition energy and surface evaporation are better correlated with marine low cloud amount variations than ATIN and lower troposphere stability. The influence of boundary layer clouds, ocean surface SST, and large scale divergence on the stochastic dynamics of local ocean surface winds are addressed using QuikSCAT and AIRS satellite observations and a simple conceptual model in the southeast Pacific. The ocean surface pressure gradient depends on both the boundary layer height and temperature inversion strength. Marine boundary clouds are diagnosed using the cloud cover scheme developed in Chapter 2. The model successfully reproduces the observed mean state, the standard deviation, and skewness of local surface wind speeds in the southeast Pacific.