Research Project: Investigation and Forecast Improvements of Tornadoes in Landfalling Tropical Cyclones
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Tornadoes in recent landfalling tropical cyclones (TCs) in the United States underscore the threat these phenomena pose to society and the unique forecast challenge they present to operational forecasters. Despite a fairly robust body of research in this area, significant gaps in our knowledge remain regarding the tropical cyclone tornado (TCTOR) climatology, radar-based storm attributes, and near-cell environments of tornadic and nontornadic convective cells in TCs. Moreover, recent improvements in observational networks (e.g., nationwide dual-polarization radar) and high-resolution operational models afford opportunities to study these phenomena in greater detail.
Leveraging and expanding existing collaborations between the NWS and Texas A&M, this study seeks to advance our understanding of TCTOR cell attributes and environments, focusing on differences between verified tornado warnings and false alarms. The second major goal of this project is to improve the operational forecasting and warning decision process through integration of observed cell attributes and modeled near-cell environments. Specific objectives under these larger goals include:
O1: Build a database of all tornadoes and tornado warnings in TCs in the United States since the NEXRAD dual-polarization upgrade that includes radar-based storm attributes and near-storm environment information from model analyses.
O2: Assess the skill of high-resolution model analyses and forecasts in depicting 1) the low-level, near-cell environment for convective cells in TCs and 2) forecast proxies for low-level rotation (e.g., updraft helicity).
O3: Compare near-cell environment and storm attribute information between verified warnings and false alarms in the climatology to determine differences that may be leveraged to reduce false alarms.
O4: In partnership with NWS collaborators, assess the performance of current radar, high-resolution NWP, and storm-environment based TCTOR forecasting practices and heuristics.
O5: In partnership with NWS collaborators, improve and streamline TCTOR warning practices using information gained from this climatology, including development and evaluation of probabilistic hazard information (PHI) produced by a statistical model trained on data produced in our climatological database.
This proposed three-year project is relevant to the CSTAR program under the primary objective of engaging university researchers with operational NWS forecasters to improve basic understanding, forecasting, and warning accuracy for high impact weather events. Specifically, the proposed research addresses Program Priority 1b: “Improving application of Numerical Weather Prediction (NWP) information in the forecast and warning process at various time scales.” The proposed research also addresses Program Priority 1cii: through “developing Probabilistic Hazard Information (PHI).
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