Climatology of morphology and cloud-radiative properties of marine low-level mixed-phase clouds
Marine stratocumuli cover about 40 - 60% of the ocean surface. They self-organize into different morphological regimes. The two organized cellular regimes are called open and closed mesoscale-cellular convective (MCC) clouds. In mid-to-high latitudes, open and closed cells are the two most frequent...
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| Format: | Doctoral or Postdoctoral Thesis |
| Language: | English |
| Published: |
2023
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| Online Access: | http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/79980 https://nbn-resolving.org/urn:nbn:de:hebis:30:3-799808 https://doi.org/10.21248/gups.79980 http://publikationen.ub.uni-frankfurt.de/files/79980/Dissertation_Jessica_Danker_CC.pdf |
| Summary: | Marine stratocumuli cover about 40 - 60% of the ocean surface. They self-organize into different morphological regimes. The two organized cellular regimes are called open and closed mesoscale-cellular convective (MCC) clouds. In mid-to-high latitudes, open and closed cells are the two most frequent types of MCC clouds. In particular, many MCC clouds consist of a mixture of vapor, liquid droplets, and ice particles, referred to as mixed-phase clouds (MPCs). Even for the same cloud fraction, the albedo of open cells is, on average, lower than that of closed MCC clouds. Cloud phase and morphology individually influence the cloud radiative effect. Thus, this thesis investigates the relationships between the cloud phase, MCC organization, cell size, and differences regarding the cloud-radiative effect. This thesis focuses on space-borne retrievals to achieve extensive temporal and spatial coverage. The liDAR-raDAR (DARDAR) version 2 product collocates two active and one passive satellite: CloudSat, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and Moderate Resolution Imaging Spectroradiometer (MODIS). The cloud phase of DARDAR is vertically integrated to establish a single cloud phase at each data point. The MCC classification data set based on the liquid water path (LWP) of MODIS scenes is collocated with the DARDAR product to determine the MCC organization. Cell-size statistics of both MCC clouds are obtained using a marker-based image segmentation method on MODIS reflectance scenes. In addition, based on MODIS reflectance scenes, a convolutional neural network (CNN) is developed to classify open and closed MCC scenes to avoid missing mature MPCs with a low LWP. The first part of this thesis explores the relationships between cloud phase, morphology, and cloud albedo in the Southern Ocean (SO). At a given cloud-top temperature (CTT), seasonal changes in the mixed-phase fraction, defined as the number of MPCs divided by the sum of MPC and supercooled liquid cloud (SLC) pixels, are ... |
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