During marine cold-air outbreaks (MCAOs), when cold polar air moves over warmer ocean, a well-recognized cloud pattern develops, with open or closed mesoscale cellular convection (MCC) at larger fetch over open water. The Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) provided a comprehensive set of ground-based in-situ and remote sensing observations of MCAOs at a coastal location in northern Norway. We determine MCAO periods that unambiguously exhibit open or closed MCC. Individual cells observed with a profiling Ka-band radar are identified using a water segmentation method. Using self-organizing maps (SOMs), these cells are then objectively classified based on the variability in their vertical structure. The SOM-based classification shows that comparatively intense convection occurs only in open MCC. This convection undergoes an apparent lifecycle. Developing cells are associated with stronger updrafts, large spectral width, larger amounts of liquid water, lower precipitation rates, and lower cloud tops than mature and weakening cells. The weakening of these cells is associated with the development of precipitation-induced cold pools. The SOM classification also reveals less intense convection, with a similar lifecycle. Such convection, when weakening, becomes virtually indistinguishable from the more intense stratiform precipitation cores in closed MCC. Non-precipitating stratiform cores have weak vertical drafts and are almost exclusively found during closed MCC periods. Convection is observed only occasionally in the closed MCC environment.

Timothy W Juliano

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Marine cold-air outbreaks, or CAOs, are airmass transformations whereby relatively cold boundary layer (BL) air is transported over relatively warm water. Such convectively-driven conditions are rather ubiquitous in the high-latitudes, occurring most frequently during the winter and spring. To more deeply understand BL and cloud properties during CAO conditions, the Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) took place from late 2019 into early 2020. During COMBLE, the U.S. Department of Energy (DOE) first Atmospheric Radiation Measurement Mobile Facility (AMF1) was deployed to Andenes, Norway, far downstream (~1000 km) from the Arctic pack ice. This study examines the two most intense CAOs sampled at the AMF1 site. The observed BL structures are open cellular in nature with high (~3-5 km) and cold (-30 to -50 oC) cloud tops, and they often have pockets of high liquid water paths (LWPs; up to ~1000 g m-2) associated with strong updrafts and enhanced turbulence. We use a high-resolution mesoscale model to explore how well four different turbulence closure methods represent open cellular cloud properties. After applying a radar simulator to the model outputs for direct evaluation, we show that cloud top properties agree well with AMF1 observations (within ~10%), but radar reflectivity and LWP agreement is more variable. The eddy-diffusivity/mass-flux approach produces the deepest cloud layer and therefore the largest and most coherent cellular structures. Our results suggest that the turbulent Prandtl number may play an important role for the simulated BL and cloud properties.

LIGIA BERNARDET

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To support the development of the Global Forecast System (GFS) physics suite and identify opportunities for improving the model physics in the UFS, the Developmental Testbed Center (DTC) conducted an array of analyses for evaluating the operational GFSv15 forecasts and the experimental forecasts using the GFSv16beta physics suite distributed with the UFS Medium-Range Weather Application v1.0 public release. Five-day GFSv16beta forecasts for one boreal winter season were generated using the operational GFS analyses as initial conditions. The evaluation metrics included tools from Model Evaluation Tools (MET) and in-house process-oriented diagnostics. The evaluations focused on the perpetuating GFS forecast errors pertaining to the planetary boundary layer (PBL), land-surface, cumulus, radiation, and cloud processes. The runs using GFSv16beta outperformed the operational GFSv15 with respect to the root-mean-square errors of large-scale environmental variables and the anomaly correlation coefficient for 500 hPa geopotential height. Nevertheless, larger biases associated with key physical processes were identified in the GFSv16beta forecasts. For example, the global precipitation forecast skill degrades and a dry bias remains in the tropics, suggesting a persistent problem in the cumulus scheme. The near-surface and boundary-layer cold biases are larger over most continents and polar regions, which is partly related to the systematic negative temperature errors in the GFS analysis. The overestimated near-surface wind speed particularly at night in the northeastern U.S. implies that the surface drag may be underrepresented. Excessive short-wave radiation reaching the ground in the high-latitudes of the summer hemisphere appears to be related to low cloud liquid and ice water path. These and other results will be described in this presentation.