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1. A Simple Model for Predicting the Tropical Cyclone Radius of Maximum Wind from Outer Size

   https://doi.org/10.1175/WAF-D-21-0103.1  

   Chavas, Daniel R. ; Knaff, John A. ( May 2022 , Weather and Forecasting)

   The radius of maximum wind (R_max) in a tropical cyclone governs the footprint of hazards, including damaging wind, surge, and rainfall. However,R_maxis an inconstant quantity that is difficult to observe directly and is poorly resolved in reanalyses and climate models. In contrast, outer wind radii are much less sensitive to such issues. Here we present a simple empirical model for predictingR_maxfrom the radius of 34-kt (1 kt ≈ 0.51 m s⁻¹) wind (R_17.5 ms). The model only requires as input quantities that are routinely estimated operationally: maximum wind speed,R_17.5 ms, and latitude. The form of the empirical model takes advantage of our physical understanding of tropical cyclone radial structure and is trained on the Extended Best Track database from the North Atlantic 2004–20. Results are similar for the TC-OBS database. The physics reduces the relationship between the two radii to a dependence on two physical parameters, while the observational data enables an optimal estimate of the quantitative dependence on those parameters. The model performs substantially better than existing operational methods for estimatingR_max. The model reproduces the observed statistical increase inR_maxwith latitude and demonstrates that this increase is driven by the increase inR_17.5 mswith latitude. Overall, the model offers a simple and fast first-order prediction ofR_maxthat can be used operationally and in risk models.

   If we can better predict the area of strong winds in a tropical cyclone, we can better prepare for its potential impacts. This work develops a simple model to predict the radius where the strongest winds in a tropical cyclone are located. The model is simple and fast and more accurate than existing models, and it also helps us to understand what causes this radius to vary in time, from storm to storm, and at different latitudes. It can be used in both operational forecasting and models of tropical cyclone hazard risk.

    

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2. Assessing the utility of SoilGrids250 for biogeographic inference of plant populations

   https://doi.org/10.1002/ece3.10986  

   Miller, Tony ; Blackwood, Christopher B. ; Case, Andrea L. ( March 2024 , Ecology and Evolution)

   Inclusion of edaphic conditions in biogeographical studies typically provides a better fit and deeper understanding of plant distributions. Increased reliance on soil data calls for easily accessible data layers providing continuous soil predictions worldwide. Although SoilGrids provides a potentially useful source of predicted soil data for biogeographic applications, its accuracy for estimating the soil characteristics experienced by individuals in small‐scale populations is unclear. We used a biogeographic sampling approach to obtain soil samples from 212 sites across the midwestern and eastern United States, sampling only at sites where there was a population of one of the 22 species inLobeliasect.Lobelia. We analyzed six physical and chemical characteristics in our samples and compared them with predicted values from SoilGrids. Across all sites and species, soil texture variables (clay, silt, sand) were better predicted by SoilGrids (R²: .25–.46) than were soil chemistry variables (carbon and nitrogen,R² ≤ .01; pH,R²: .19). While SoilGrids predictions rarely matched actual field values for any variable, we were able to recover qualitative patterns relating species means and population‐level plant characteristics to soil texture and pH. Rank order of species mean values from SoilGrids and direct measures were much more consistent for soil texture (Spearmanr_S = .74–.84; allp < .0001) and pH (r_S = .61,p = .002) than for carbon and nitrogen (p > .35). Within the speciesL. siphilitica, a significant association, known from field measurements, between soil texture and population sex ratios could be detected using SoilGrids data, but only with large numbers of sites. Our results suggest that modeled soil texture values can be used with caution in biogeographic applications, such as species distribution modeling, but that soil carbon and nitrogen contents are currently unreliable, at least in the region studied here.

    

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3. A Model for the Tropical Cyclone Wind Field Response to Idealized Landfall

   https://doi.org/10.1175/JAS-D-22-0156.1  

   Chen, Jie ; Chavas, Daniel R. ( April 2023 , Journal of the Atmospheric Sciences)

   The impacts of a tropical cyclone after landfall depend not only on storm intensity but also on the size and structure of the wind field. Hence, a simple predictive model for the wind field after landfall has significant potential value. This work tests existing theory for wind structure and size over the ocean against idealized axisymmetric landfall experiments in which the surface beneath a mature storm is instantaneously dried and roughened individually or simultaneously. Structure theory captures the response of the low-level wind field to different types of idealized landfalls, given the intensity and size response. Storm size, modeled to follow the ratio of simulated time-dependent storm intensity to the Coriolis parameter, can generally predict the transient response of the storm gale wind radiir_34ktto inland surface forcings, particularly for at least moderate surface roughening regardless of the level of drying. Given knowledge of the intensity evolution, the above results combine to yield a theoretical model that can predict the full tangential wind field response to idealized landfalls.

   A theoretical model that can predict the time-dependent wind field structure of landfalling tropical cyclones (TCs) with a small number of physical, observable input parameters is essential for mitigating hazards and allocating public resources. This work provides a first-order prediction of storm size and structure after landfall, which can be combined with existing intensity predictions to form a simple model describing the inland wind field evolution. Results show its potential utility for modeling idealized inland TC wind fields.

    

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4. The Ionization and Dynamics of the Makani Galactic Wind

   https://doi.org/10.3847/1538-4357/acbfae  

   Rupke, David S. ; Coil, Alison L. ; Perrotta, Serena ; Davis, Julie D. ; Diamond-Stanic, Aleksandar M. ; Geach, James E. ; Hickox, Ryan C. ; Moustakas, John ; Petter, Grayson C. ; Rudnick, Gregory H. ; et al ( April 2023 , The Astrophysical Journal)

   The Makani galaxy hosts the poster child of a galactic wind on scales of the circumgalactic medium. It consists of a two-episode wind in which the slow, outer wind originated 400 Myr ago (Episode I;R_I= 20 − 50 kpc) and the fast, inner wind is 7 Myr old (Episode II;R_II= 0 − 20 kpc). While this wind contains ionized, neutral, and molecular gas, the physical state and mass of the most extended phase—the warm, ionized gas—are unknown. Here we present Keck optical spectra of the Makani outflow. These allow us to detect hydrogen lines out tor= 30–40 kpc and thus constrain the mass, momentum, and energy in the wind. Many collisionally excited lines are detected throughout the wind, and their line ratios are consistent with 200–400 km s⁻¹shocks that power the ionized gas, withv_shock=σ_wind. Combining shock models, density-sensitive line ratios, and mass and velocity measurements, we estimate that the ionized mass and outflow rate in the Episode II wind could be as high as those of the molecular gas:$M_{\mathrm{II}}^{\mathrm{H}\mathrm{II}}\sim M_{\mathrm{II}}^{{\mathrm{H}}_2}=(1-2)\times {10}^9{M}_{\odot }$and$\mathit{dM}/{\mathit{dt}}_{\mathrm{II}}^{\mathrm{H}\mathrm{II}}\sim \mathit{dM}/{\mathit{dt}}_{\mathrm{II}}^{{\mathrm{H}}_2}=170-250M_{\odot }$yr⁻¹. The outer wind has slowed, so that$\mathit{dM}/{\mathit{dt}}_{\mathrm{I}}^{\mathrm{H}\mathrm{II}}\sim 10M_{\odot }$yr⁻¹, but it contains more ionized gas,$M_{\mathrm{I}}^{\mathrm{H}\mathrm{II}}=5\times {10}^9$M_⊙. The momentum and energy in the recent Episode II wind imply a momentum-driven flow (p“boost” ∼7) driven by the hot ejecta and radiation pressure from the Eddington-limited, compact starburst. Much of the energy and momentum in the older Episode I wind may reside in a hotter phase, or lie further into the circumgalactic medium.

    

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5. Capturing Uncertainty in Magnetospheric Ultralow Frequency Wave Models

   https://doi.org/10.1029/2018SW002102  

   Bentley, S. N. ; Watt, Clare E. J. ; Rae, I. J. ; Owens, M. J. ; Murphy, K. ; Lockwood, M. ; Sandhu, J. K. ( April 2019 , Space Weather)

   We develop and test an empirical model predicting ground‐based observations of ultralow frequency (ULF, 1–20 mHz) wave power across a range of frequencies, latitudes, and MLT sectors. This is parameterized by instantaneous solar wind speedv_sw, variance in proton number density var(Np), and interplanetary southward magnetic fieldB_z. A probabilistic model of ULF wave power will allow us to address uncertainty in radial diffusion coefficients and therefore improve diffusion modeling of radial transport in Earth's outer radiation belt. Our model can be used in two ways to reproduce wave power: by sampling from conditional probability distribution functions and by using the mean (expectation) values. We derive a method for testing the quality of the parameterization and test the ability of the model to reproduce ULF wave power time series. Sampling is a better method for reproducing power over an extended time period as it retains the same overall distribution, while mean values are better for predicting the power in a time series. The model predicts each hour in a time series better than the assumption that power persists from the preceding hour. Finally, we review other sources of diffusion coefficient uncertainty. Although this wave model is designed principally for the goal of improved radial diffusion coefficients to include in outer radiation belt diffusion‐based modeling, we anticipate that our model can also be used to investigate the occurrence of ULF waves throughout the magnetosphere and hence the physics of ULF wave generation and propagation.

    

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