Storm-Scale Predictability and Analysis of the 13 April 2020 Central Savannah River Area Tornado Outbreak

Abstract An early morning tornado outbreak occurred on 13 April 2020 in the Central Savannah River Area. Multiple significant tornadoes were reported, resulting in fatalities and injuries. While the operational tornado warnings had positive lead times, the convective mode (quasi-linear convective system) increased the warning decision complexity. The timing of the event [0500–0600 local time (LT)] also made NWS-to-public communication difficult. The experimental NSSL Warn-on-Forecast System (WoFS) was run retrospectively for this case. The WoFS consists of 3–6-h ensemble forecasts initialized every 30 min, and the goals of the system are to bridge the gap between severe weather watches and warnings and to increase warning lead times. Multiple WoFS forecasts were initialized leading up to the first tornado report; those initialized prior to tornado warning issuance have high ensemble probabilities of low-level rotation in the appropriate areas based on subsequent tornado reports. This case highlights another example of the usefulness of WoFS before its eventual transition to operations. Using the WoFS forecasts, kinematic and thermodynamic storm–environment relationships are analyzed using ensemble sensitivity analysis (ESA). The analyses suggest variations in the mesoscale environmental vertical wind profile are not as influential on mesovortex intensity as variations in the thermodynamic environment. Surface observations recorded prior to the tornado outbreak reveal subtle temperature and moisture gradients that may be the impetus for mesovortex intensification and tornadogenesis.</jats:p

A CLIMATOLOGY BASED FORECAST TOOL FOR COASTAL FLOODING IN THE LOWCOUNTRY

AbstractCoastal nuisance flooding has increased by an order of magnitude over the past half century, but the National Weather Service has a limited suite of statistical tools to forecast them. Such a tool was developed using coastal flood events from 1996—2014 in Charleston, South Carolina, which were identified and classified by prevailing synoptic conditions based on composite mean sea level pressure anomalies. The synoptic climatology indicated low level northeasterly winds dominated the forcing in anticyclonic and cyclonic events, while a southeasterly surge was the main forcing component for frontal events. Tidal anomalies between flood events and previous low tides were used to create linear regression models for each composite classification studied for forecasting levels of coastal flood magnitude. Beta tests using data from 2018—2019 confirmed the effectiveness of the models with RMSE values less than 0.3 ft and MAE values less than 0.25 ft for each event type. The veracity of the methods was further verified by a multiple day case study from November 2018, where the model was tested against both statistically predicted heights and heights based on ETSS Model (v2.2). The RMSE and MAE for the statical model were 0.18 and 0.15 respectively, while the same values for the ETSS model were 0.28 and 0.23 respectively.</jats:p

Development of a methodology for energy supply transformation strategies to support net-zero production

Transformation concepts for factories are an integral aspect of the ongoing global energy transition. Identifying emission sources and substituting them with green energy solutions remains a complex task. While regulatory pressure urges compliance with climate goals, investment decisions require satisfactory financial returns to be realized. This paper introduces a five-step brownfield methodology addressing transformation of energy supply systems to support net-zero production. It focuses on selecting potential transformation scenarios based on supplementary solution modules and further environmental and economic criteria, using the solution modules to assist transformation planning. The methodology is applied to an exemplary use-case