Global storm-resolving model (GSRM) simulations (kilometer-scale horizontal resolution) of the atmosphere can capture the interaction between the scales of deep cumulus convection and the large-scale dynamics and thermodynamic properties of the atmosphere. Here, we assess the vertical structure of tropical temperature change in the GSRM X-SHiELD, developed by the Geophysical Fluid Dynamics Laboratory, perturbed by a uniform sea surface temperature (SST) warming and/or increased CO2 concentration. The simulated response to SST warming shows weakly amplified warming from the surface through the mid-troposphere before increasing to a factor of about 2.5 near the tropopause. This combination of muted warming in the mid-troposphere and amplified warming aloft is within the range of CMIP6 models at individual pressure levels but, taken together, is distinctive behavior. The response to CO2 increase with unchanged SST is an approximately vertically uniform warming, comparable to CMIP6 models, and is linearly additive with the SST-induced warming in X-SHiELD.

Recent advances have allowed for integration of global storm resolving models (GSRMs) to a timescale of several years. These short simulations are sufficient for studying characteristics and statistics of short- and small-scale phenomena; however, it is questionable what we can learn from these integrations about the large-scale climate response to perturbations. To address this question, we use the response of X-SHiELD (a GSRM) to uniform SST warming and CO$_2$ increase in a two-year integration and compare it to similar CMIP6 experiments. Specifically, we assess the statistical meaning of having two years in one model outside the spread of another model or model ensemble. This is of particular interest because X-SHiELD shows a distinct response of the global mean precipitation to uniform warming, and the northern hemisphere jet shift response to isolated CO$_2$ increase. We use the CMIP6 models to estimate the probability of two years in one model being more than one standard deviation away from another model (ensemble) mean, knowing the mean of two models. For example, if two years in one model are more than one standard deviation away from the other model’s mean, we find that the chances for these models’ means to be within one standard deviation are $\sim 25\%$. We find that for some large-scale metrics, there is an important base-state dependence that, when taken into account, can qualitatively change the interpretation of the results. We note that a year-to-year comparison is physically meaningful due to the use of prescribed sea-surface-temperature simulations.

We present the System for High-resolution prediction on Earth-to-Local Domains (SHiELD), an atmosphere model 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 (S2S) prediction, global-to-regional convective-scale hurricane and contiguous US precipitation forecasts, and global cloud-resolving modeling. Advances within SHiELD can be seamlessly transitioned into other Unified Forecast System (UFS) or FV3-based models, including operational implementations of the UFS. 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) shows significant improvement in hurricane structure from a new tracer advection scheme and promise for medium-range prediction of convective storms, respectively.

Intense convection (updrafts exceeding 10 m∙s-1) plays an essential role in severe weather and Earth’s energy balance. Despite its importance, how the global pattern of intense convection changes in response to warmed climates remains unclear, as simulations from traditional climate models are too coarse to simulate intense convection. Here we take advantage of a kilometer-scale global storm resolving model and conduct year-long simulations of a control run, forced by analyzed sea surface temperature (SST), and one with a 4-K increase in SST for comparison. Comparisons show that the increased SST enhances the frequency of intense convection globally with large spatial and seasonal variations. Increases in the intense convection frequency do not necessarily reflect increases in convective available potential energy (CAPE). Results are also compared with traditional climate model projections. Changes in the spatial pattern of intense convection are associated with changes in planetary circulation.

The 13 km SHiELD (System for High-resolution prediction on Earth-to-Local Domains) global model that is under development at the Geophysical Fluid Dynamics Laboratory (GFDL) and runs in near real time, produced outstanding tropical cyclone track forecasts during the 2021 Atlantic hurricane season, compared to both the upgraded National Weather Service Global Forecast System (GFSv16), the Hurricane Weather Research and Forecasting (HWRF) model and the European Centre for Medium-Range Weather Forecast Integrated Forecasting System (IFS). SHiELD’s average track forecast errors were 10% and 15% less than the GFSv16 and HWRF, respectively, for the 3-5 day forecast lead times. SHiELD’s track forecast skill was comparable to the National Hurricane Center’s official forecast at several forecast lead times, and approached 70% skill relative to the Climatology and Persistence Model (CLIPER) at 3 and 4 days. Similar improvements were found in the western Pacific basin in 2021, with improvements also seen in the eastern Pacific at days 4 and 5. Improved performance was also found in the 2019 Atlantic hurricane season, with neutral performance in 2020, when SHiELD was run retrospectively from the GFSv16 initial conditions. Distribution of the spatial errors and biases showed that in both the 2021 Atlantic hurricane season and the previous two years, the largest track forecast errors from both SHiELD and GFSv16 occurred in the subtropical eastern Atlantic, associated with a distinct northeast bias. Analysis indicated that some of the excessive north bias in the GFSv16 is associated with lower geopotential height fields compared to those in SHiELD.

We present the characteristics of rotating convective updrafts in the 2021 version of GFDL’s Experimental System for High-resolution prediction on Earth-to-Local Domains (X-SHiELD), a kilometer scale global storm resolving model (GSRM). Rotation is quantified using 2–5 km Updraft Helicity (UH) in a year-long integration forced by analyzed SSTs. Updrafts with UH magnitudes above 50 m2/s2; are common over the mid-latitude continents, especially in the warm seasons where they are associated with severe weather but are also common over most tropical ocean basins. In nearly all areas cyclonically rotating convection dominates, with larger UH values increasingly preferring cyclonic rotation. The ratio of cyclonic to anticyclonic updrafts is largest in the subtropical and mid-latitude oceans and is slightly lower over mid-latitude continents. The ratio of cyclonic to anticyclonic updrafts can be substantively explained by the mean storm-relative helicity (SRH) in convective regions, indicating the importance for environmental controls on the sense of storm rotation, although internal storm dynamics also plays a role in the generation of anticyclonic updrafts.