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1. Asymmetric Rainband Processes Leading to Secondary Eyewall Formation in a Model Simulation of Hurricane Matthew (2016)

   https://doi.org/10.1175/JAS-D-20-0061.1  

   Yu, Chau-Lam; Didlake, Anthony C.; Zhang, Fuqing; Nystrom, Robert G. (January 2021, Journal of the Atmospheric Sciences)

   Abstract The dynamics of an asymmetric rainband complex leading into secondary eyewall formation (SEF) are examined in a simulation of Hurricane Matthew (2016), with particular focus on the tangential wind field evolution. Prior to SEF, the storm experiences an axisymmetric broadening of the tangential wind field as a stationary rainband complex in the downshear quadrants intensifies. The axisymmetric acceleration pattern that causes this broadening is an inward-descending structure of positive acceleration nearly 100 km wide in radial extent and maximizes in the low levels near 50 km radius. Vertical advection from convective updrafts in the downshear-right quadrant largely contributes to the low-level acceleration maximum, while the broader inward-descending pattern is due to horizontal advection within stratiform precipitation in the downshear-left quadrant. This broad slantwise pattern of positive acceleration is due to a mesoscale descending inflow (MDI) that is driven by midlevel cooling within the stratiform regions and draws absolute angular momentum inward. The MDI is further revealed by examining the irrotational component of the radial velocity, which shows the MDI extending downwind into the upshear-left quadrant. Here, the MDI connects with the boundary layer, where new convective updrafts are triggered along its inner edge; these new upshear-left updrafts are found to be important to the subsequent axisymmetrization of the low-level tangential wind maximum within the incipient secondary eyewall. 

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2. Features of Magnetic Field Switchbacks in Relation to the Local-field Geometry of Large-amplitude Alfvénic Oscillations: Wind and PSP Observations

   https://doi.org/10.3847/2041-8213/ac67d9  

   Bourouaine, Sofiane; Perez, Jean C.; Raouafi, Nour E.; Chandran, Benjamin D.; Bale, Stuart D.; Velli, Marco (June 2022, The Astrophysical Journal Letters)

   Abstract In this Letter, we report observations of magnetic switchback (SB) features near 1 au using data from the Wind spacecraft. These features appear to be strikingly similar to the ones observed by the Parker Solar Probe mission closer to the Sun: namely, one-sided spikes (or enhancements) in the solar-wind bulk speed V that correlate/anticorrelate with the spikes seen in the radial-field component B R . In the solar-wind streams that we analyzed, these specific SB features near 1 au are associated with large-amplitude Alfvénic oscillations that propagate outward from the Sun along a local background (prevalent) magnetic field B 0 that is nearly radial. We also show that, when B 0 is nearly perpendicular to the radial direction, the large-amplitude Alfvénic oscillations display variations in V that are two sided (i.e., V alternately increases and decreases depending on the vector Δ B = B − B 0 ). As a consequence, SBs may not always appear as one-sided spikes in V , especially at larger heliocentric distances where the local background field statistically departs from the radial direction. We suggest that SBs can be well described by large-amplitude Alfvénic fluctuations if the field rotation is computed with respect to a well-determined local background field that, in some cases, may deviate from the large-scale Parker field. 

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3. Arctic Amplification Weakens the Variability of Daily Temperatures over Northern Middle-High Latitudes

   https://doi.org/10.1175/JCLI-D-20-0514.1  

   Dai, Aiguo; Deng, Jiechun (April 2021, Journal of Climate)

   null (Ed.)

   Abstract Arctic amplification (AA) reduces meridional temperature gradients ( dT / dy ) over the northern mid-high latitudes, which may weaken westerly winds. It is suggested that this may lead to wavier and more extreme weather in the midlatitudes. However, temperature variability is shown to decrease over the northern mid-high latitudes under increasing greenhouse gases due to reduced dT / dy . Here, through analyses of coupled model simulations and ERA5 reanalysis, it is shown that consistent with previous studies, cold-season surface and lower-mid troposphere temperature ( T ) variability decreases over northern mid-high latitudes even in simulations with suppressed AA and sea ice loss under increasing CO 2 ; however, AA and sea ice loss further reduce the T variability greatly, leading to a narrower probability distribution and weaker cold or warm extreme events relative to future mean climate. Increased CO 2 strengthens meridional wind ( υ ) with a wavenumber-4 pattern but weakens meridional thermal advection [− υ ( dT / dy )] over most northern mid-high latitudes, and AA weakens the climatological υ and − υ ( dT / dy ). The weakened thermal advection and its decreased variance are the primary causes of the T variability decrease, which is enlarged by a positive feedback between the variability of T and − υ ( dT / dy ). AA not only reduces dT / dy , but also its variance, which further decreases T variability through − υ ( dT / dy ). While the mean snow and ice cover decreases, its variability increases over many northern latitudes, and these changes do not weaken the T variability. Thus, AA’s influence on midlatitude temperature variability comes mainly from its impact on thermal advection, rather than on winds as previously thought. 

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4. Adaptive RKHS-based functional estimation of structurally perturbed second order infinite dimensional systems

   https://doi.org/10.1109/CDC51059.2022.9992577  

   Demetriou, Michael A. (December 2022, 2022 IEEE 61st Conference on Decision and Control (CDC))

   . (Ed.)

   This paper proposes a new approach for the adaptive functional estimation of second order infinite dimensional systems with structured perturbations. First, the proposed observer is formulated in the natural second order setting thus ensuring the time derivative of the estimated position is the estimated velocity, and therefore called natural adaptive observer. Assuming that the system does not yield a positive real system when placed in first order form, then the next step in deriving parameter adaptive laws is to assume a form of input-output collocation. Finally, to estimate structured perturbations taking the form of functions of the position and/or velocity outputs, the parameter space is not identified by a finite dimensional Euclidean space but instead is considered in a Reproducing Kernel Hilbert Space. Such a setting allows one not to be restricted by a priori assumptions on the dimension of the parameter spaces. Convergence of the position and velocity errors in their respective norms is established via the use of a parameter-dependent Lyapunov function, specifically formulated for second order infinite dimensional systems that include appropriately defined norms of the functional errors in the reproducing kernel Hilbert spaces. Boundedness of the functional estimates immediately follow and via an appropriate definition of a persistence of excitation condition for functional estimation, a functional convergence follows. When the system is governed by vector second order dynamics, all abstract spaces for the state evolution collapse to a Euclidean space and the natural adaptive observer results simplify. Numerical results of a second order PDE and a multi-degree of freedom finite dimensional mechanical system are presented. 

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5. Data from: Dynamics and scaling of a small river discharging into the surf zone

   https://doi.org/10.5061/dryad.2280gb608  

   Lou, Yingzhong; Horner-Devine, Alexander; Derakhti, Morteza; Giddings, Sarah; Spydell, Matthew; Rodriguez, Angelica; Simpson, Alexandra (January 2025, Dryad)

   We use an idealized numerical model to investigate the dynamics and fate of a small river discharging into the surf zone. Our study reveals that the plume reaches a steady state, at which point the combined advective and diffusive freshwater fluxes from the surf zone to the inner shelf balance the river discharge. At a steady state, the surf zone is well-mixed vertically due to wave-enhanced vertical turbulent diffusion and has a strong cross-shore salinity gradient. The horizontal gradient drives a cross-shore buoyancy-driven circulation, directed offshore at the surface and onshore near the bottom, which opposes the wave-driven circulation. Using a scaling analysis based on momentum and freshwater budgets, we determine that the steady-state alongshore plume extent (Lp) and the fraction of river water trapped in the surf zone depend on the ratio of the near-field plume length to the surf zone width (Lnf/Lsz) across a wide range of discharge and wave conditions, and a limited set of tidal conditions. This scaling also allows us to predict the residence time and freshwater fraction (or dilution ratio) in the steady-state plume within the surf zone, which range from approximately 0.1 to 10 days and 0.1 to 0.3, respectively. Our findings establish the basic dynamics and scales of an idealized plume in the surf zone, as well as estimates of residence times and dilution rates that may provide guidance to coastal managers. # Data from: Dynamics and scaling of a small river discharging into the surf zone [https://doi.org/10.5061/dryad.2280gb608](https://doi.org/10.5061/dryad.2280gb608) The present dataset includes the [COAWST model](https://www.usgs.gov/centers/whcmsc/science/coawst-a-coupled-ocean-atmosphere-wave-sediment-transport-modeling-system) outputs used to describe the dynamics and scaling of a small river discharging into the surf zone. ## File structure The data are structured as follows: 1. plume_scale.mat - Data of plume scales of all the cases, where * Hs: significant wave height [m] * Q: river discharge [m^3 s^-1] * L_nf: near-field plume length [m] * L_p: alongshore plume extent [m] * h_sz: water depth at the surf zone edge [m] * x_sz: surf zone width [m] * S_in: inflow salinity [PSU] * g_p: reduced gravity at the river mouth [m s^-2] * g_p*_*0: reduced gravity at the river mouth calculated using the density difference between river inflow and ambient ocean water [m s^-2] * Eta_0: water surface elevation anomaly at the river mouth [m] * V_sz: total volume of freshwater trapped in the surf zone [m^3] * T: the time required for the plume to reach a steady state [day] * L_t: plume turning distance [m] * S_bar: averaged salinity in the plume [PSU] 2. DepthAveraged.mat - Depth-averaged flow fields. DepthAveraged_BaseCase.mat, DepthAveraged_Case1.mat, DepthAveraged_Case3.mat, DepthAveraged_Case4.mat, DepthAveraged_Case6.mat, DepthAveraged_Case7.mat, DepthAveraged_Case8.mat, DepthAveraged_Case9.mat, DepthAveraged_Case16.mat, DepthAveraged_Case17.mat, DepthAveraged_Case18.mat, DepthAveraged_Case19.mat includes the results of the base case, cases 1, 3, 4, 6-9, and 16-19, respectively. In these files: * Wetdry_mask: wet/dry mask on RHO-points [binary] * Wetdry_mask_u: wet/dry mask on U-points [binary] * Wetdry_mask_v: wet/dry mask on V-points [binary] * Z: free-surface [m] * S: surface salinity [PSU] * Hs: significant wave height [m] * U: vertically integrated u-momentum component [m s^-1] * U_st: vertically-integrated u-Stokes drift velocity [m s^-1] * V: vertically integrated v-momentum component [m s^-1] * V_st: vertically-integrated v-Stokes drift velocity [m s^-1] 3. FullField_BaseCase.mat - 3D flow fields for the base case, where * Z: free-surface [m] * S: salinity [PSU] * Hs: significant wave height [m] * Lw: mean wavelength [m] * U: u-momentum component [m s^-1] * U_st: u-Stokes drift velocity [m s^-1] * V: v-momentum component [m s^-1] * V_st: v-Stokes drift velocity [m s^-1] * W: w-momentum component [m s^-1] * W_st: w-Stokes drift velocity [m s^-1] * Aks: salinity vertical diffusion coefficient [m^2 s^-1] * Akv: vertical viscosity coefficient [m^2 s^-1] * Cs_r: S-coordinate stretching curves at RHO-points [-] * Cs_w: S-coordinate stretching curves at W-points [-] 4. FreshwaterTrace_BaseCase.mat - Time series of freshwater volume and fluxes for the base case, where * i_sz: XI-index of the location of the surf zone edge [-] * i_shore: XI-index of the location of the shoreline [-] * Vsz: volume of freshwater in the plume in the surf zone [m^3] * Vis: volume of freshwater in the plume in the inner shelf [m^3] * Vsz_total: total volume of freshwater in the surf zone [m^3] * Vis_total: total volume of freshwater in the inner shelf [m^3] * R2SZ_flux: freshwater flux discharging into the surf zone [m^3 s^-1] * Vchannel: volume of freshwater in the plume in the river channel [m^3] * Vchannel_total: volume of freshwater in the river channel [m^3] * SBoundary_flux_SZ: the freshwater fluxes through the southern domain boundaries of the surf zone [m^3 s^-1] * SBoundary_flux_IS: the freshwater fluxes through the southern domain boundaries of the inner shelf [m^3 s^-1] * NBoundary_flux_SZ: the freshwater fluxes through the northern domain boundaries of the surf zone [m^3 s^-1] * NBoundary_flux_IS: the freshwater fluxes through the northern domain boundaries of the inner shelf [m^3 s^-1] * WBoundary_flux: the freshwater fluxes through the westhern domain boundary [m^3 s^-1] 5. DepthAveraged_XDiagnostic.mat - Depth-averaged diagnostic output of cross-shore momentum terms. DepthAveraged_XDiagnostic_BaseCase.mat includes the results of the base case at the steady state, and DepthAveraged_XDiagnostic_0day_1mWave.mat includes those at the start of river flow. In these files: * ubar_xadv: time-averaged 2D u-momentum, horizontal XI-advection term [m s^-2] * ubar_yadv: time-averaged 2D u-momentum, horizontal ETA-advection term [m s^-2] * ubar_xvisc: time-averaged 2D u-momentum, horizontal XI-viscosity term [m s^-2] * ubar_yvisc: time-averaged 2D u-momentum, horizontal ETA-viscosity term [m s^-2] * ubar_prsgrd: time-averaged 2D u-momentum, pressure gradient term [m s^-2] * ubar_zqsp: time-averaged 2D u-momentum, quasi-static pressure [m s^-2] * ubar_zbeh: time-averaged 2D u-momentum, Bernoulli head [m s^-2] * ubar_bstr: time-averaged 2D u-momentum, bottom stress term [m s^-2] * ubar_wbrk: time-averaged 2D u-momentum, wave breaking term [m s^-2] 6. DepthAveraged_YDiagnostic_BaseCase.mat - Depth-averaged diagnostic output of alongshore momentum terms, where * vbar_xadv: time-averaged 2D v-momentum, horizontal XI-advection term [m s^-2] * vbar_yadv: time-averaged 2D v-momentum, horizontal ETA-advection term [m s^-2] * vbar_xvisc: time-averaged 2D v-momentum, horizontal XI-viscosity term [m s^-2] * vbar_yvisc: time-averaged 2D v-momentum, horizontal ETA-viscosity term [m s^-2] * vbar_prsgrd: time-averaged 2D v-momentum, pressure gradient term [m s^-2] * vbar_zqsp: time-averaged 2D v-momentum, quasi-static pressure [m s^-2] * vbar_zbeh: time-averaged 2D v-momentum, Bernoulli head [m s^-2] * vbar_bstr: time-averaged 2D v-momentum, bottom stress term [m s^-2] * vbar_wbrk: time-averaged 2D v-momentum, wave breaking term [m s^-2] 7. grid.zip - Model grid file. * This grid file is designed for use with [ROMS](https://www.myroms.org/index.php), the hydrodynamic module of the COAWST modeling system. A diagram illustrating how the variables are placed on the grid and where the boundaries lie relative to the grid is available on [WikiROMS](https://www.myroms.org/wiki/Grid_Generation). * This grid file is in NetCDF format, which can be opened and used by a wide range of application software such as MATLAB, Python, and Panoply. For more detailed information, please refer to its [official website](https://www.unidata.ucar.edu/software/netcdf/). ## Code/Software All the post-processing scripts and data are prepared by MATLAB. 

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