Improving the Understanding of Marine Boundary Layer Clouds

Abstract

Marine boundary layer clouds play a key role in the planetary radiation budget and are still a large source of uncertainty within global climate models. One of the main reasons for this uncertainty within global climate predictions is the interaction between aerosols, clouds, and meteorology, which is poorly represented within current global circulation models. This dissertation focuses on improving our understanding of marine boundary layer clouds by (1) re-evaluating two foundational relationships (i.e. lower tropospheric stability (LTS) and estimated inversion strength (EIS)) with marine boundary layer clouds, (2) assessing the performance of LTS and EIS as well as additional stability parameters (i.e. estimated cloud-top entrainment index (ECTEI) and cold-air outbreak index (CAO)) at different temporal resolutions using in-situ measurements, reanalysis data, and model output, and (3) creating gridded datasets from aircraft measurements from two aircraft in formation from the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) field campaigns to facilitate comparison of aerosol, cloud, and meteorology variables important to MBL cloud formation and aerosol-cloud-meteorology interactions. A foundation of our understanding of MBL clouds is the seasonal relationships between LTS (Klein and Hartmann, 1993) and EIS (Wood and Bretherton, 2006) with marine boundary layer clouds. In the first part of this dissertation, we re-evaluated the seasonal relationships between LTS and EIS with low cloud amount using three clouds data products. We found that (1) the relationship between LTS and low cloud amount was not consistent across the cloud datasets, (2) EIS does not estimate low cloud amount better than LTS in the midlatitudes, and (3) LTS and EIS are best at predicting stratocumulus clouds among all types of low-level clouds (stratus, stratocumulus, cumulus). These findings are crucial as the relationship with LTS and low-level clouds was used in early parameterizations of global circulation models. Additionally, the relationship with EIS and low cloud fraction is used to tune low level clouds in global circulation models. With these findings from the first part of this dissertation regarding the robustness of the LTS and EIS relationships with low-level clouds, the second part of this dissertation focuses on assessing the performance of LTS and EIS, in addition to other well-known stability parameters (i.e., ECTEI (Kawai et al., 2017) and CAO) with boundary layer clouds at different temporal scales. We found that CAO is the overall best predictor of low cloud fraction across all temporal scales and time periods evaluated in the western North Atlantic region. These findings are important because they demonstrate that the relationship with LTS/EIS and low-level clouds break down at smaller temporal scales. Additionally, the findings from this study improve our understanding of the relationship between marine boundary layer stability and marine boundary layer clouds and may inform future modeling studies as a result. The third part of this dissertation introduces a gridded data product using the two aircraft (King Air and HU-25 Falcon) flown during the ACTIVATE field campaigns from 2020-2022. These aircraft were spatially co-located, with the King Air flying at high altitudes (~9 km) and the Falcon flying at lower altitudes (0.15-3 km), closer to the ocean surface. The King Air launched dropsondes and carried remote sensors (i.e. High-Spectral Resolution LiDAR (HSRL-2) and Research Scanning Polarimeter (RSP)) while the Falcon performed in-situ measurements of trace gases, aerosol particles, clouds, and meteorology. A 0.25° grid resolution for the HSRL-2 and Falcon data was created. The King Air and Falcon datasets provide useful insights into aerosol-cloud-meteorology interactions on their own. However, ACTIVATE provides a unique opportunity to gain new and interesting insights into aerosol-cloud-meteorology interactions because of the two co-located aircraft. Gridding the two aircraft datasets will both allow for more streamlined and easier use of the co-located aircraft, allowing users to leverage the remote sensing data from the King Air and the in-situ measurements from the Falcon together. Additionally, the gridded data will help remove some of the barriers associated with using aircraft measurements for modelers and end users not familiar with the different file formats and caveats associated with using aircraft observations. The dataset will also provide a unique opportunity to gain valuable insights into aerosol-cloud-meteorology interactions for the western North Atlantic and inform future researchers in their development of new field campaigns.