They found that the rate of precursor upstream rapid cyclogenesis was related to a peak in IRE near block onset followed by a peak in block intensity. Finally, examined the relationship between block intensity and IRE during block onset. The model had difficulty with the timing of block termination as well. Additionally, the GEFS model could not sustain the blocking event for as long as they were observed to exist. However, the block intensity was not forecasted well by the GEFS model. Then demonstrated that the timing of onset and the location for blocking was forecast well by the GEFS ensemble mean fields. They found that as expected, individual ensemble members performed better than the control or the ensemble mean, but that the IE was forecast reasonably. The work of used IE to study the performance of the Global Ensemble Forecast System (GEFS) in simulating the dynamic behavior of two blocking events. They found that differences in forecasts using parameterization schemes within a model were smaller than those using two different models. The study of examined the development of a cold-season mid-latitude cyclone over the southeast United States using two different models and varying the different boundary layer physics and convective precipitation parameterizations. Recent studies used the quantity Integrated Regional Enstrophy (IRE) to examine predictability within mid-latitude events such as synoptic-scale cyclones and blocking events. Then, showed that if a large region of the NH was used to calculate IE, the regional estimate and its change with time was similar to the hemispheric value. The quantity integrated enstrophy (IE) was first proposed by and they demonstrated that in a barotropic atmosphere, IE is proportional to the system stability and predictability. Such conditions indicate that, in some cases, predictability of certain phenomena at some time scales is nearly impossible given our current understanding of fluid dynamics. They demonstrated that the predictability of a rapidly developing tropical cyclone (Hurricane Patricia-October 2015) was associated with dynamics consistent with violent turbulence, or rough dependence on the initial conditions (RDIC). Hurricane track prediction has improved substantially in recent years, but models often fail to capture the intensity of very strong tropical cyclones. While the track of Florence was well-forecast by operational numerical models, the rapid loss in intensity as the storm approached the coast as well as the amount of rain produced by the storm was not well forecast. However, the storm made landfall as a category one storm on 14 September after it was anticipated to make landfall as a major hurricane. By 11 September, Florence was classified as a major hurricane (category four) on the Saffir-Simpson Scale with maximum sustained winds of more than 70 m∙s −1 (140 mph). Hurricane Florence began as a tropical depression over the eastern tropical Atlantic on 31 August 2018. The storm was associated with at least one report of more than 75 cm of rain over the four-day period, see the Community Collaborative Rain Hail and Snow network (CoCoRaHS- ). Hurricane Florence made landfall in the southeast United States during 14-17 September 2018 resulting in more than 15 deaths and causing over one billion dollars in damage. The results also showed that when the boundary layer, convective, and cloud microphysical schemes of the model were varied, the areal coverage of heavy precipitation of Florence was under-forecast by approximately 10% or more, and the heaviest amounts were under-forecast by an average of about 20%. The results demonstrated that the sign of the local IRE tendency was similar to that of the Northern Hemisphere Integrated Enstrophy. In order to measure the predictability of a system, we will use different convective and boundary layer schemes initialized from the same conditions. The large-scale analysis showed that a change in the Northern Hemisphere flow regime, especially the flow in the western part of the Northern Hemisphere may have contributed partly to the reduced forward speed of the tropical cyclone. The WRF ARW core resolution used here was the 27-km grid spacing chosen to in order to balance finer resolution against in house processing time and storage. This was performed over the period from 0000 UTC 13 September 2018 through 0000 UTC 18 September 2018. The overall purpose of this paper is to post-evaluate the predictability of Hurricane Florence using the Advanced Research Weather Research Forecast (WRF) (ARW) version of a mesoscale model.
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