Probabilistic high‐impact rainfall forecasts from landfalling tropical cyclones using Warn‐on‐Forecast system

Abstract

Intense rainfall and flash flooding from landfalling tropical cyclones (LTC) can have devastating impacts on human life and property in coastal areas. The years 2017 and 2018 are examples of how the North Atlantic LTCs can create widespread destruction in the United States. Better preparedness is needed to mitigate the impact from the violent LTCs and can be achieved by improving the accuracy of forecasts and increased lead‐time of guidance products. However, predicting the fine‐scale details of rain bands in LTC is very challenging. This study attempts to elucidate the potential of National Severe Storms Laboratory's convective‐scale ensemble analysis and prediction system, known as the Warn‐on‐Forecast System (WoFS), in improving 0–6 hr probabilistic intense rainfall forecasts from three recent LTCs in the United States. Results indicate that the frequent 15 min assimilation cycling can accurately analyse the small‐scale details from the LTC rain bands in the WoFS analyses. The WoFS 0–6 hr ensemble forecasts initialized from those analyses represent the location, intensity and spatial distribution of intense rainfall (with the potential to cause flash flooding) as well as low‐level rotation with reasonably good accuracy. The continuous flow of the frequently updated WoFS rainfall guidance has the potential to aid operational forecasters in issuing watches, warnings, and short‐term forecast products of life‐threatening LTC with higher spatial and temporal specificity.

Assessing the Fidelity of Landfalling Tropical Cyclone Convective‐Scale Environments in the Warn‐On‐Forecast System Using Radiosondes

“…The 2020 version of WoFS uses a custom version of the Advanced Research Weather Research and Forecasting model (WRF‐ARW version 3.9.1; Developmental Testbed Center, 2008) together with an Ensemble Kalman filter (EnKF; Houtekamer et al., 2005; Whitaker et al., 2008) from the Community Gridpoint Statistical Interpolation (GSI‐EnKF; Kleist et al., 2009). The current configuration of WoFS in this study uses 18 ensemble members with a 3‐km horizontal grid spacing, containing 300 × 300 grid points with 51 hybrid sigma‐pressure vertical levels, using a vertical grid spacing of ≤100 m near the surface that decreases to ≥1 km at the model top (Wheatley et al., 2015; Yussouf et al., 2020). Each ensemble member uses initial and boundary conditions from 1‐hr experimental, 18‐member High‐Resolution Rapid Refresh Ensemble forecasts (HRRRE; Dowell et al., 2016).…”

“…Jones et al, 2016;Skinner et al, 2018). uses 18 ensemble members with a 3-km horizontal grid spacing, containing 300 × 300 grid points with 51 hybrid sigma-pressure vertical levels, using a vertical grid spacing of ≤100 m near the surface that decreases to ≥1 km at the model top (Wheatley et al, 2015;Yussouf et al, 2020). Each ensemble member uses initial and boundary conditions from 1-hr experimental, 18member High-Resolution Rapid Refresh Ensemble forecasts (HRRRE; Dowell et al, 2016).…”

A Method for Assimilating Pseudo Dewpoint Temperature as a Function of GLM Flash Extent Density in GSI‐Based EnKF Data Assimilation System—A Proof of Concept Study

“…The WoFS system is an on‐demand ensemble DA and forecasting system designed to provide guidance of hazardous weather events, such as tornadoes, damaging winds, large hail, and flash flooding. The current WoFS uses a customized Advanced Research Weather Research and Forecasting Model (WRF‐ARW) based on version 3.8.1 (Skamarock et al., 2008), coupled with the GSI‐based EnKF system (Jones et al., 2016, 2020; Yussouf & Knopfmeier, 2019; Yussouf et al., 2020). The GSI‐EnKF system assimilates radar radial velocity and reflectivity data (Johnson et al., 2015; Wang & Wang, 2017), satellite cloud water path (CWP, Jones et al., 2013) and GOES‐16 ABI radiance (Jones et al., 2020).…”

A Method for Assimilating Pseudo Dewpoint Temperature as a Function of GLM Flash Extent Density in GSI-Based EnKF Data Assimilation System - A Proof of Concept study

“…The WoFS system is an on-demand ensemble DA and forecasting system designed to provide guidance of hazardous weather events, such as tornadoes, damaging winds, large hail, and flash flooding. The current WoFS uses a customized Advanced Research Weather Research and Forecasting Model (WRF-ARW) based on version 3.8.1 (Skamarock et al, 2008), coupled with the GSI-based EnKF system (Jones et al, 2016(Jones et al, , 2020Yussouf et al, 2020). The GSI-EnKF system assimilates radar radial velocity and reflectivity data (Johnson et al, 2015;Wang & Wang, 2017), satellite cloud water path (CWP, Jones et al, 2013) and GOES-16 ABI radiance (Jones et al, 2020).…”