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Finger‐like km‐scale features have been observed along the inner‐edge of the eyewall of intense hurricanes. But due to the limited availability of observations, many important aspects of these features remain unknown. In this study, we aim to offer insights on the nature of these phenomena based on a four‐day‐duration O(100 m) grid spacing simulation that covers the inner‐core region of an idealized hurricane. The simulation successfully captured the finger‐like features, which closely resemble observed ones. We propose that these features are formed due to the shear instability associated with vertical distribution of the tangential wind in the inner‐core region. This proposed mechanism offers insights on several key characteristics of the features of interest, including their emergence time, frequency, radial location and vertical extent. Our study also demonstrates the feasibility of using multi‐level nesting for O(100 m) grid spacing hurricane simulations and predictions, aligning with the goals for next generation hurricane models. Plain Language Summary The inner core region of hurricanes harbors complex dynamical features, including small‐scale clouds characterized by finger‐like appearances pointing toward the hurricane eye. These features have been frequently observed in intense hurricanes. However, many basic aspects of these features remain unknown, particularly regarding what controls their occurrence and location. We conduct a numerical simulation with a very fine (about 100 m) horizontal grid spacing to investigate the nature of these features. Our proposed mechanism explains several key characteristics of these features. Key Points We conduct a O(100 m) grid spacing simulation that captures the finger‐like features along the inner edge of the hurricane eyewall We propose a mechanism that links the finger cloud formation and hurricane‐scale dynamics This proposed mechanism explains the emergence time, frequency, radial location and vertical extent of the finger features

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. Key Points A unified “one code, one executable, one workflow” global prediction modeling system is presented SHiELD's multiple configurations show prediction skill and simulation fidelity matching or exceeding those of existing U.S. models The FV3 Dynamical Core provides a powerful foundation for unified prediction modeling

High‐resolution atmospheric models are powerful tools for hurricane track and intensity predictions. Although using high resolution contributes to better representation of hurricane structure and intensity, its value in the prediction of steering flow and storm tracks is uncertain. Here we present experiments suggesting that biases in the predicted North Atlantic hurricane tracks in a high‐resolution (approximately 3 km grid‐spacing) model originates from the model's explicit simulation of deep convection. Differing behavior of explicit convection leads to changes in the synoptic‐scale pattern and thereby to the steering flow. Our results suggest that optimizing small‐scale convection activity, for example, through the model's horizontal advection scheme, can lead to significantly improved hurricane track prediction (∼10% reduction of mean track error) at lead times beyond 72 hr. This work calls attention to the behavior of explicit convection in high‐resolution models, and its often overlooked role in affecting larger‐scale circulations and hurricane track prediction. Plain Language Summary High‐resolution models (approximately 3 km grid spacing or finer) covering a large domain are emerging powerful tools for hurricane prediction. However, the use of high resolution in the model can be a double‐edged sword—while it helps improve hurricane intensity prediction, it can also make the model more prone to develop errors in the prediction of steering flow and hurricane tracks due to the possible impact of prevalent small‐scale features resolved by the model. Our results suggest that regulating small‐scale convection activity in a high‐resolution model can significantly improve hurricane track predictions at days 4 and 5. Key Points Better regulation of explicit convection reduces North Atlantic hurricane track errors in a high‐resolution model by 10% at days 4 and 5 Improved track forecasts are related to a more realistic representation of the North Atlantic subtropical ridge Explicit convection is modulated by implicit diffusivity in the model's advection scheme

Capabilities to directly assimilate radar data are implemented within the local ensemble transform Kalman filter (LETKF) and the gain‐form LETKF (LGETKF) algorithms of the Joint Effort for Data assimilation Integration (JEDI) system. The capabilities are evaluated for the analysis and forecast of a severe convection case of 20 May 2019 in the Southern Great Plains using the limited area model version of the FV3 dynamical core (FV3‐LAM) from a recent release for Short‐Range Weather Application (SRW App). The LETKF and LGETKF implementations are shown to produce analyses and short‐range forecasts comparable to those using the ensemble square‐root Kalman Filter (EnSRF) within the Gridpoint Statistical Interpolation (GSI) framework used by current NCEP operational models. In addition, LGETKF retaining only 60% variances for model‐space vertical localization performs similarly to LGETKF retaining 99% of variance and LETKF using observation error‐based vertical localization. JEDI LETKF shows better parallel scalability than LGETKF and GSI EnSRF. Plain Language Summary The JEDI data assimilation (DA) framework under development will be used by all operational forecasting systems of the U.S. National Weather Service, including the Rapid Refresh Forecast System based on FV3, a dynamic core chosen for next‐generation NWS forecasting systems. In this study, we implemented radar DA capabilities into the JEDI with two local ensemble transform Kalman filter (LETKF) algorithms coupled with limited‐area FV3. Analyses and forecasts with radar DA better match radar reflectivity and radial velocity observations than forecasts without radar DA during the assimilation period. Three‐hour forecasts of precipitation, reflectivity, and updraft rotation show skills comparable to a DA experiment using the ensemble square‐root Kalman filter within the more mature GSI DA system. In addition, the new gain‐form LETKF, which has not been applied to radar DA before, performs quite well, although it is computationally more expensive than the regular LETKF. This work paves the way for using JEDI to assimilate radar data in operational forecasting systems. Key Points Radar data assimilation capabilities are implemented and tested in Joint Effort for Data assimilation Integration (JEDI), a future data assimilation infrastructure for Unified Forecast System applications Local ensemble transform Kalman filter (LETKF) algorithm with gain‐form vertical localization is tested for radar data assimilation and is found to perform similarly as LETKF The enhanced gain‐form LETKF and LETKF in JEDI perform similarly as ensemble square‐root Kalman Filter within Gridpoint Statistical Interpolation for radar data assimilation

The development of a limited area model (LAM) capability for the nonhydrostatic Finite‐Volume Cubed‐Sphere (FV3) dynamical core is described and compared with a globally nested approach featuring two‐way feedback. Comparisons of the computational performance of the LAM relative to the two‐way nest reveal that the LAM configuration exhibits considerable improvement in efficiency. High‐resolution (i.e., 3‐km) LAM and nest configuration forecasts covering a 1‐month period show statistically comparable results for most parameters. Forecast differences between the two configurations primarily arise in the upper air temperature and height fields, which show a statistically significant increase in the magnitude of negative biases in geopotential height and upper‐air temperature using the LAM configuration relative to the nest at forecast lead times >24‐h. Precipitation forecasts over the full 60‐h forecast period are also evaluated and depict no statistically significant differences between the two configurations, with the nest configuration exhibiting slightly improved scores. Overall results suggest that while the FV3 LAM approach can introduce degradations into the forecast relative to the two‐way interactive nest at lead times >24‐h, these errors are generally small in magnitude and are accompanied by considerable improvement in computational efficiency. Plain Language Summary In this study, we describe and evaluate a new limited area model (LAM) capability for the Finite‐Volume Cubed‐Sphere dynamical core. This capability provides a way to run the dynamical core over any region without the need for simultaneous integration of a global model counterpart, thus saving considerable computational resources. However, this framework is susceptible to errors from lateral boundaries, which are provided by an external model at a coarse temporal frequency compared to a global model employing a nest with two‐way feedback. Short range forecasts at 3‐km grid spacing over the contiguous United States show generally similar performance between the limited area and nest configurations for a month‐long period in 2019, with the nest showing slightly better forecast scores near the end of the studied forecast length of 60 h. These results suggest that use of the LAM performs similarly to the more sophisticated, and computationally expensive, two‐way nest configuration for convection‐allowing, short range forecasts to 60 h. Key Points A limited area modeling capability has been developed for the Finite‐Volume Cubed‐Sphere dynamical core This capability was evaluated for a month‐long period against a similarly configured two‐way nest driven by a global model The limited area model is statistically comparable to the two‐way nest for the first 24 h, with minor degradation by 48–60 h

Ranaviruses have been involved in amphibian mass mortality events worldwide. Effective screening to control this pathogen is essential; however, current sampling methods are unsuitable for the detection of subclinical infections. Non-lethal screening is needed to prevent both further spread of ranavirus and losses of at-risk species. To assess non-lethal sampling methods, we conducted two experiments: bath exposing common frogs to RUK13 ranavirus at three concentrations, and exposing common toads to RUK13 or PDE18. Non-lethal sampling included buccal, digit, body and tank swabs, along with toe clips and stool taken across three time-points post-exposure. The presence/load of ranavirus was examined using quantitative PCR in 11 different tissues obtained from the same euthanised animals (incl. liver, gastro-intestinal tract and kidney). Buccal swab screening had the highest virus detection rate in both species (62% frogs; 71% toads) and produced consistently high virus levels compared to other non-lethal assays. The buccal swab was effective across multiple stages of infection and differing infection intensities, though low levels of infection were more difficult to detect. Buccal swab assays competed with, and even outperformed, lethal sampling in frogs and toads, respectively. Successful virus detection in the absence of clinical signs was observed (33% frogs; 50% toads); we found no difference in detectability for RUK13 and PDE18. Our results suggest that buccal swabbing could replace lethal sampling for screening and be introduced as standard practice for ranavirus surveillance.

The next generation Hurricane Analysis and Forecast System (HAFS) has been developed recently in the National Oceanic and Atmospheric Administration (NOAA) to accelerate the improvement of tropical cyclone (TC) forecasts within the Unified Forecast System (UFS) framework. The finite-volume cubed sphere (FV3) based convection-allowing HAFS Stand-Alone Regional model (HAFS-SAR) was successfully implemented during Hurricane Forecast Improvement Project (HFIP) real-time experiments for the 2019 Atlantic TC season. HAFS-SAR has a single large 3-km horizontal resolution regional domain covering the North Atlantic basin. A total of 273 cases during the 2019 TC season are systematically evaluated against the best track and compared with three operational forecasting systems: Global Forecast System (GFS), Hurricane Weather Research and Forecasting model (HWRF), and Hurricanes in a Multi-scale Ocean-coupled Non-hydrostatic model (HMON). HAFS-SAR has the best performance in track forecasts among the models presented in this study. The intensity forecasts are improved over GFS, but show less skill compared to HWRF and HMON. The radius of gale force wind is over-predicted in HAFS-SAR, while the hurricane force wind radius has lower error than other models.

The glutamic acid-leucine-arginine (ELR) motif is a hallmark feature shared by mammalian inflammatory CXC chemokines such the granulocyte chemo-attractant CXCL8 (interleukin-8, IL-8). By contrast, most teleost fish inflammatory chemokines lack this motif. Interestingly, the amphibian encodes multiple isoforms of CXCL8, one of which (CXCL8a) possesses an ELR motif, while another (CXCL8b) does not. These CXCL8 isoforms exhibit distinct expression patterns during frog development and following immune challenge of animals and primary myeloid cultures. To define potential functional differences between these CXCL8 chemokines, we produced them in recombinant form (rCXCL8a and rCXCL8b) and performed dose-response chemotaxis assays. Our results indicate that compared to rCXCL8b, rCXCL8a is a significantly more potent chemo-attractant of -derived tadpole granulocytes and of -differentiated frog bone marrow granulocytes. The mammalian CXCL8 mediates its effects through two distinct chemokine receptors, CXCR1 and CXCR2 and our pharmacological inhibition of these receptors in frog granulocytes indicates that the CXCL8a and CXCL8b both chemoattract tadpole and adult frog granulocytes by engaging CXCR1 and CXCR2. To delineate which frog cells are recruited by CXCL8a and CXCL8b , we injected tadpoles and adult frogs intraperitoneally with rCXCL8a or rCXCL8b and recovered the accumulated cells by lavage. Our transcriptional and cytological analyses of these tadpole and adult frog peritoneal exudates indicate that they are comprised predominantly of granulocytes. Interestingly, the granulocytes recruited into the tadpole, but not adult frog peritonea by rCXCL8b, express significantly greater levels of several pan immunosuppressive genes.

Viruses are obligate intracellular parasites that alter host metabolic machinery to obtain energy and macromolecules that are pivotal for replication. Ranavirus, including the type species of the genus frog virus 3 (FV3), represent an ecologically important group of viruses that infect fish, amphibians, and reptiles. It was established that fatty acid synthesis, glucose, and glutamine metabolism exert roles during iridovirus infections; however, no information exists regarding the role of purine metabolism. In this study, we assessed the impact of exogenously applied purines adenine, adenosine, adenosine 5′-monophosphate (AMP), inosine 5′-monophosphate (IMP), inosine, S-adenosyl-L-homocysteine (SAH), and S-adenosyl-L-methionine (SAM) on FV3 replication. We found that all compounds except for SAH increased FV3 replication in a dose-dependent manner. Of the purines investigated, adenine and adenosine produced the most robust response, increasing FV3 replication by 58% and 51%, respectively. While all compounds except SAH increased FV3 replication, only adenine increased plaque area. This suggests that the stimulatory effect of adenine on FV3 replication is mediated by a mechanism that is at least in part independent from the other compounds investigated. Our results are the first to report a response to exogenously applied purines and may provide insight into the importance of purine metabolism during iridoviral infection.

Using a nonhydrostatic model based on a version of Geophysical Fluid Dynamics Laboratory's FV3 dynamical core at a cloud‐resolving resolution in radiative‐convective equilibrium (RCE) configuration, the sensitivity of the mean RCE climate to the magnitude and scale‐selectivity of the divergence damping is explored. Divergence damping is used to reduce small‐scale noise in more realistic configurations of this model. This sensitivity is tied to the strength (and width) of the convective updrafts, which decreases (increases) with increased damping and acts to organize the convection, dramatically drying out the troposphere and increasing the outgoing longwave radiation. Increased damping also results in a much‐broadened precipitation probability distribution and larger extreme values, as well as reduction in cloud fraction, which correspondingly decreases the magnitude of shortwave and longwave cloud radiative effects. Solutions exhibit a monotonic dependence on the strength of the damping and asymptotically converge to the inviscid limit. While the potential dependence of RCE simulations on resolution and microphysical assumptions are generally appreciated, these results highlight the potential significance of the choice of subgrid numerical diffusion in the dynamical core. Key Points RCE simulations by the GFDL FV3 CRM exhibit remarkable sensitivity to the divergence damping Divergence damping, while acting to smooth out small‐scale noise, modifies the strength and width of convective updraft velocity Changes in the updraft vertical velocity in the model have strong influence on the simulated climate, that is, relative humidity, convective organization, and cloud radiative forcing