We present the System for High-resolution prediction on Earth-to-Local Domains (SHiELD), an atmosphere model developed by the Geophysical Fluid Dynamics Laboratory (GFDL) coupling the nonhydrostatic FV3 Dynamical Core to a physics suite originally taken from the Global Forecast System. SHiELD is designed to demonstrate new capabilities within its components, explore new model applications, and to answer scientific questions through these new functionalities. A variety of configurations are presented, including short-to-medium-range and subseasonal-to-seasonal prediction, global-to-regional convective-scale hurricane and contiguous U.S. precipitation forecasts, and global cloud-resolving modeling. Advances within SHiELD can be seamlessly transitioned into other Unified Forecast System or FV3-based models, including operational implementations of the Unified Forecast System. Continued development of SHiELD has shown improvement upon existing models. The flagship 13-km SHiELD demonstrates steadily improved large-scale prediction skill and precipitation prediction skill. SHiELD and the coarser-resolution S-SHiELD demonstrate a superior diurnal cycle compared to existing climate models; the latter also demonstrates 28 days of useful prediction skill for the Madden-Julian Oscillation. The global-to-regional nested configurations T-SHiELD (tropical Atlantic) and C-SHiELD (contiguous United States) show significant improvement in hurricane structure from a new tracer advection scheme and promise for medium-range prediction of convective storms. Plain Language Summary At many weather forecasting centers where computer weather models are run, different models are run for different applications. However, each separate model multiplies the effort needed to maintain and upgrade each model and makes it difficult to move improvements between models. We present a new "unified" weather modeling system, System for High-resolution prediction on Earth-to-Local Domains, able to be configured for a variety of applications. This system uses a powerful computer code, FV3, to compute the fluid motion of the atmosphere at any scale and also able to zoom in on areas of interest to better "see" severe storms or intense hurricanes. We show how we started from a quickly assembled model for testing FV3 and then gradually improved the representation of different atmospheric processes and expanded into new uses for the system, including short-range severe thunderstorm prediction, hurricane forecasting, and forecasts out to as long as 6 weeks. We address some of the challenges that we faced and discuss prospects for future model improvements. Since many of the parts of System for High-resolution prediction on Earth-to-Local Domains are used by models being developed by the National Weather Service for use by weather forecasters, the advances described here can be rapidly introduced into those models, eventually improving official forecasts. 1. Unified Modeling at GFDL As computing power increases, global atmosphere models are now capable of regul...
In this study, the authors numerically simulate roll vortices (rolls) generated by the inflection-point instability in the hurricane boundary layer (HBL). The approach is based on embedding a two-dimensional high-resolution single-grid roll-resolving model (SRM) at selected horizontal grid points of an axisymmetric HBL model. The results from a set of idealized experiments indicate that the mixed-layer height is an important factor affecting the magnitude of the roll velocities and the structure of the internal waves triggered in the stably stratified layer above. This study reveals the important difference between the roll-induced cross-roll (nearly radial) and alongroll (nearly azimuthal) momentum fluxes: while the cross-roll momentum flux is well correlated to the cross-roll mean wind shear, the along-roll momentum flux is typically not correlated with the along-roll mean wind shear. Therefore, the commonly used K theory in the boundary layer parameterizations cannot reasonably capture the vertical distribution of the roll-induced along-roll momentum flux. Moreover, the authors find that the rolls induce more significant changes in the mean radial wind profile than in the mean azimuthal wind profile. Specifically, rolls reduce the inflow near surface, enhance the inflow at upper levels, and increase the inflow-layer height. Based on a linear dynamical HBL model, the authors find that the impact of rolls on the mean radial wind profile is essentially due to their redistribution effect on the mean azimuthal momentum in the HBL.
Horizontal roll vortices, or rolls, are frequently observed in the hurricane boundary layer (HBL). Previous studies suggest that these rolls can be generated by the inflection point instability of the HBL flow. In this study we investigate the formation of rolls due to this mechanism in the axisymmetric HBL using a numerical approach that explicitly resolves rolls. The effects of mean HBL wind and stratification distributions on rolls are evaluated. We identify two important factors of the mean HBL wind that affect the characteristics of rolls. The dynamical HBL height affects the wavelength of rolls, and the magnitude of the mean wind shear affects the growth rate of rolls. As a result, under neutrally stratified HBL, the wavelength of rolls increases with the radius (out of the radius of maximum wind), while the growth rate of rolls decreases. The stratification also plays an important role in the generation of rolls. The stable stratification suppresses the growth of rolls because of the negative work done by the buoyancy force. Nonuniform stratification with a mixed layer has less suppressing effect on rolls. Rolls can trigger internal waves in the stably stratified layer, which have both vertically propagating and decaying properties. We derive analytical solutions for the internal waves, which relate the properties of the internal waves to the boundary layer rolls. We find the properties of the internal waves are affected by the mixed-layer height.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.