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1. Observed Bulk Hook Echo Drop Size Distribution Evolution in Supercell Tornadogenesis and Tornadogenesis Failure

   https://doi.org/10.1175/MWR-D-20-0353.1  

   Tuftedal, Kristofer S. ; French, Michael M. ; Kingfield, Darrel M. ; Snyder, Jeffrey C. ( June 2021 , Monthly Weather Review)

   null (Ed.)

   Abstract The time preceding supercell tornadogenesis and tornadogenesis “failure” has been studied extensively to identify differing attributes related to tornado production or lack thereof. Studies from the Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX) found that air in the rear-flank downdraft (RFD) regions of non- and weakly tornadic supercells had different near-surface thermodynamic characteristics than that in strongly tornadic supercells. Subsequently, it was proposed that microphysical processes are likely to have an impact on the resulting thermodynamics of the near-surface RFD region. One way to view proxies to microphysical features, namely drop size distributions (DSDs), is through use of polarimetric radar data. Studies from the second VORTEX used data from dual-polarization radars to provide evidence of different DSDs in the hook echoes of tornadic and non-tornadic supercells. However, radar-based studies during these projects were limited to a small number of cases preventing result generalizations. This study compiles 68 tornadic and 62 non-tornadic supercells using Weather Surveillance Radar–1988 Doppler (WSR-88D) data to analyze changes in polarimetric radar variables leading up to, and at, tornadogenesis and tornadogenesis failure. Case types generally did not show notable hook echo differences in variables between sets, but did show spatial hook echo quadrant DSD differences. Consistent with past studies, differential radar reflectivity factor (Z DR ) generally decreased leading up to tornadogenesis and tornadogenesis failure; in both sets, estimated total number concentration increased during the same times. Relationships between DSDs and the near-storm environment, and implications of results for nowcasting tornadogenesis, also are discussed. 

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2. Polarimetric Observations and Simulations of Sublimating Snow: Implications for Nowcasting

   https://doi.org/10.1175/JAMC-D-21-0038.1  

   Carlin, Jacob T. ; Reeves, Heather D. ; Ryzhkov, Alexander V. ( July 2021 , Journal of Applied Meteorology and Climatology)

   Abstract Snow sublimating in dry air is a forecasting challenge and can delay the onset of surface snowfall and affect storm-total accumulations. Despite this, it remains comparatively less studied than other microphysical processes. Herein, the characteristics of sublimating snow and the potential for nowcasting snowfall reaching the surface are explored through the use of dual-polarization radar. Twelve cases featuring prolific sublimation were analyzed using range-defined quasi-vertical profiles (RDQVPs) and compared with environmental model analyses. Overall, reflectivity Z significantly decreases, differential reflectivity Z DR slightly decreases, and copolar-correlation coefficient ρ hv remains nearly constant through the sublimation layer. Regions of enhanced specific differential phase K dp were frequently observed in the sublimation layer and are believed to be polarimetric evidence of secondary ice production via sublimation. A 1D bin model was initialized using particle size distributions retrieved from the RDQVPs using numerous novel polarimetric snowretrieval relations for a wide range of forecast lead times, with the model environment evolving in response to sublimation. It was found that the model was largely able to predict the snowfall start time up to six hours in advance, with a 6-h median bias of just -18.5 minutes. A more detailed case study of the 08 December 2013 snowstorm in the Philadelphia region was also performed, demonstrating good correspondence with observations and examples of model fields (e.g., cooling rate) hypothetically available from such a tool. The proof-of-concept results herein demonstrate the potential benefits of incorporating spatially averaged radar data in conjunction with simple 1D models into the nowcasting process. 

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3. Decomposing the Precipitation Response to Climate Change in Convection Allowing Simulations Over the Conterminous United States

   https://doi.org/10.1029/2023EA003094  

   Wallace, Brendan C. ; Haberlie, Alex M. ; Ashley, Walker S. ; Gensini, Vittorio A. ; Michaelis, Allison C. ( December 2023 , Earth and Space Science)

   Explicit representation of finer‐scale processes can affect the sign and magnitude of the precipitation response to climate change between convection‐permitting and convection‐parameterizing models. We compare precipitation across two 15‐year epochs, a historical (HIST) and an end‐of‐21st‐century (EoC85), between a set of dynamically downscaled regional climate simulations at 3.75 km grid spacing (WRF) and bias‐corrected Community Earth System Model (CESM) output used to initialize and force the lateral boundaries of the downscaled simulations. In the historical climate, the downscaled simulations demonstrate less overall error than CESM when compared to observations for most portions of the conterminous United States. Both sets of simulations overestimate the incidence of environments with moderate to high precipitable water while CESM generally simulates rainfall that is too frequent but less intense. Within both sets of simulations, EoC85 rainfall amounts decrease in low‐moisture environments due to reduced rainfall frequency and intensity while rainfall amounts increase in high‐moisture environments as they occur more often. Overall, reductions in rainfall are stronger in WRF than in CESM, particularly during the warm season. This reduced drying in CESM is attributed to relatively higher rainfall frequency in environments with high concentrations of precipitable water and weak vertical motion. As a result, an increase in the occurrence of high moisture environments in EoC85 naturally favors more rainfall in CESM than WRF. Our results present an in‐depth examination of the characteristics of changes in overall accumulated precipitation and highlight an extra dimension of uncertainty when comparing convection‐permitting models against convection‐parameterizing models.

    

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4. Hurricane Dorian Outer Rain Band Observations and 1D Particle Model Simulations: A Case Study.

   Bringi, V. ; Seifert, A. ; Wu, W. ; Thurai, M. ; Huang, G.-J. ; Siewert, C. ( August 2020 , Atmosphere)

   null (Ed.)

   The availability of high quality surface observations of precipitation and volume observations by polarimetric operational radars make it possible to constrain, evaluate, and validate numerical models with a wide variety of microphysical schemes. In this article, a novel particle-based Monte-Carlo microphysical model (called McSnow) is used to simulate the outer rain bands of Hurricane Dorian which traversed the densely instrumented precipitation research facility operated by NASA at Wallops Island, Virginia. The rain bands showed steady stratiform vertical profiles with radar signature of dendritic growth layers near −15 °C and peak reflectivity in the bright band of 55 dBZ along with polarimetric signatures of wet snow with sizes inferred to exceed 15 mm. A 2D-video disdrometer measured frequent occurrences of large drops >5 mm and combined with an optical array probe the drop size distribution was well-documented in spite of uncertainty for drops <0.5 mm due to high wind gusts and turbulence. The 1D McSnow control run and four numerical experiments were conducted and compared with observations. One of the main findings is that even at the moderate rain rate of 10 mm/h collisional breakup is essential for the shape of the drop size distribution 

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5. Hurricane Dorian Outer Rain Band Observations and 1D Particle Model Simulations: A Case Study

   https://doi.org/10.3390/atmos11080879  

   Bringi, Viswanathan ; Seifert, Axel ; Wu, Wei ; Thurai, Merhala ; Huang, Gwo-Jong ; Siewert, Christoph ( August 2020 , Atmosphere)

   null (Ed.)

   The availability of high quality surface observations of precipitation and volume observations by polarimetric operational radars make it possible to constrain, evaluate, and validate numerical models with a wide variety of microphysical schemes. In this article, a novel particle-based Monte-Carlo microphysical model (called McSnow) is used to simulate the outer rain bands of Hurricane Dorian which traversed the densely instrumented precipitation research facility operated by NASA at Wallops Island, Virginia. The rain bands showed steady stratiform vertical profiles with radar signature of dendritic growth layers near −15 °C and peak reflectivity in the bright band of 55 dBZ along with polarimetric signatures of wet snow with sizes inferred to exceed 15 mm. A 2D-video disdrometer measured frequent occurrences of large drops >5 mm and combined with an optical array probe the drop size distribution was well-documented in spite of uncertainty for drops <0.5 mm due to high wind gusts and turbulence. The 1D McSnow control run and four numerical experiments were conducted and compared with observations. One of the main findings is that even at the moderate rain rate of 10 mm/h collisional breakup is essential for the shape of the drop size distribution. 

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