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1. Laboratory Wave and Stress Measurements Quantify the Aerodynamic Sheltering in Extreme Winds

   https://doi.org/10.1029/2022JC019505  

   Tan, Peisen ; Smith, Andrew W. ; Curcic, Milan ; Haus, Brian K. ( April 2023 , Journal of Geophysical Research: Oceans)

   In strong winds, air flow detaches from the ocean surface in the lee of wave crests and creates a low‐pressure zone on the wave’s leeward face. The pressure difference between the wave’s rear and front face modulates the momentum input from wind to waves. Numerical wave models parameterize this effect using a so‐called sheltering coefficient. However, its value and dependence on wind speed are not well understood, particularly with background swell waves. To bridge this gap, we conducted laboratory experiments with winds up to Category 4 hurricane force blown over various mechanically generated wave conditions (pure wind sea, mixed waves with directional spreading, and monochromatic unidirectional waves) and measured the wind, waves, and stress at a sufficient frequency to resolve wind‐wave variability over the long‐wave phase. We analyze the results in the context of Jeffreys’s sheltering theory and find two regimes: (a) from low‐to‐moderate wind forcing (10 m s⁻¹ < U₁₀ < 33 m s⁻¹), the aerodynamic sheltering increases with wind speed, consistent with previous studies; (b) in hurricane conditions (U₁₀ > 33 m s⁻¹), the aerodynamic sheltering decreases with wind at a rate depending on wave state. Further, we isolate the short wind waves from the longer paddle waves and find that the aerodynamic sheltering by longer waves leads to a phase‐dependent variability of the short wind‐waves’ local steepness, which is evidenced by the sheltering coefficient’s value derived from wind and wave measurements. Our results emphasize the need for further measurements of aerodynamic sheltering and improving its representation in models.

    

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2. Wind Stress, Wind Stress Curl, and Upwelling Velocities in the Northwest Atlantic (80-45W, 30-45N) during 1980-2019

   https://doi.org/10.5281/zenodo.8200832  

   Gifford, Ian ; Gangopadhyay, Avijit ; Andres, Magdalena ; Gawarkiewicz, Glen ; Oliver, Hilde ; Silver, Adrienne ( January 2023 , Zenodo)

   This dataset contains three netcdf files that pertain to monthly, seasonal, and annual fields of surface wind stress, wind stress curl, and curl-derived upwelling velocities over the Northwest Atlantic (80-45W, 30-45N) covering a forty year period from 1980 to 2019. Six-hourly surface (10 m) wind speed components from the Japanese 55-year reanalysis (JRA-55; Kobayashi et al., 2015) were processed from 1980 to 2019 over a larger North Atlantic domain of 100W to 10E and 10N to 80N. Wind stress was computed using a modified step-wise formulation, originally based on (Gill, 1982) and a non-linear drag coefficient (Large and Pond, 1981), and later modified for low speeds (Trenberth et al., 1989). See Gifford (2023) for more details.   

   After the six-hourly zonal and meridional wind stresses were calculated, the zonal change in meridional stress (curlx) and the negative meridional change in zonal stress (curly) were found using NumPy’s gradient function in Python (Harris et al., 2020) over the larger North Atlantic domain (100W-10E, 10-80N). The curl (curlx + curly) over the study domain (80-45W, 10-80N) is then extracted, which maintain a constant order of computational accuracy in the interior and along the boundaries for the smaller domain in a centered-difference gradient calculation. 

   The monthly averages of the 6-hour daily stresses and curls were then computed using the command line suite climate data operators (CDO, Schulzweida, 2022) monmean function. The seasonal (3-month average) and annual averages (12-month average) were calculated in Python using the monthly fields with NumPy (NumPy, Harris et al., 2020). 

   Corresponding upwelling velocities at different time-scales were obtained from the respective curl fields and zonal wind stress by using the Ekman pumping equation of the study by Risien and Chelton (2008; page 2393). Please see Gifford (2023) for more details.   

   The files each contain nine variables that include longitude, latitude, time, zonal wind stress, meridional wind stress, zonal change in meridional wind stress (curlx), the negative meridional change in zonal wind stress (curly), total curl, and upwelling. Units of time begin in 1980 and are months, seasons (JFM etc.), and years to 2019. The longitude variable extends from 80W to 45W and latitude is 30N to 45N with uniform 1.25 degree resolution.  

   Units of stress are in Pascals, units of curl are in Pascals per meter, and upwelling velocity is described by centimeters per day. The spatial grid is a 29 x 13 longitude x latitude array. 

   Filenames: 

   monthly_windstress_wsc_upwelling.nc: 480 time steps from 80W to 45W and 30N to 45N.

   seasonal_windstress_wsc_upwelling.nc: 160 time steps from 80W to 45W and 30N to 45N.

   annual_windstress_wsc_upwelling.nc: 40 time steps from 80W to 45W and 30N to 45N.

   Please contact igifford@earth.miami.edu for any queries. {"references": ["Gifford, I.H., 2023. The Synchronicity of the Gulf Stream Free Jet and the Wind Induced Cyclonic Vorticity Pool. MS Thesis, University of Massachusetts Dartmouth. 75pp.", "Gill, A. E. (1982). Atmosphere-ocean dynamics (Vol. 30). Academic Press.", "Harris, C.R., Millman, K.J., van der Walt, S.J. et al. Array programming with NumPy. Nature 585, 357\u2013362 (2020). DOI: 10.1038/s41586-020-2649-2.", "Japan Meteorological Agency/Japan (2013), JRA-55: Japanese 55-year Reanalysis, Daily 3-Hourly and 6-Hourly Data, https://doi.org/10.5065/D6HH6H41, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, Boulder, Colo. (Updated monthly.)", "Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi, K., Kamahori, H., Kobayashi, C., Endo, H. and Miyaoka, K., 2015. The JRA-55 reanalysis: General specifications and basic characteristics.\u202fJournal of the Meteorological Society of Japan. Ser. II,\u202f93(1), pp.5-48.", "Large, W.G. and Pond, S., 1981. Open ocean momentum flux measurements in moderate to strong winds.\u202fJournal of physical oceanography,\u202f11(3), pp.324-336.", "Risien, C.M. and Chelton, D.B., 2008. A global climatology of surface wind and wind stress fields from eight years of QuikSCAT scatterometer data.\u202fJournal of Physical Oceanography,\u202f38(11), pp.2379-2413.", "Schulzweida, Uwe. (2022). CDO User Guide (2.1.0). Zenodo. https://doi.org/10.5281/zenodo.7112925.", "Trenberth, K.E., Large, W.G. and Olson, J.G., 1989. The effective drag coefficient for evaluating wind stress over the oceans.\u202fJournal of Climate,\u202f2(12), pp.1507-1516."]} 

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3. Collapsar Gamma-Ray Bursts Grind Their Black Hole Spins to a Halt

   https://doi.org/10.3847/1538-4357/ad02f0  

   Jacquemin-Ide, Jonatan ; Gottlieb, Ore ; Lowell, Beverly ; Tchekhovskoy, Alexander ( January 2024 , The Astrophysical Journal)

   The spin of a newly formed black hole (BH) at the center of a massive star evolves from its natal value due to two competing processes: accretion of gas angular momentum that increases the spin and extraction of BH angular momentum by outflows that decreases the spin. Ultimately, the final, equilibrium spin is set by a balance between both processes. In order for the BH to launch relativistic jets and power aγ-ray burst (GRB), the BH magnetic field needs to be dynamically important. Thus, we consider the case of a magnetically arrested disk (MAD) driving the spin evolution of the BH. By applying the semianalytic MAD BH spin evolution model of Lowell et al. to collapsars, we show that if the BH accretes ∼20% of its initial mass, its dimensionless spin inevitably reaches small values,a≲ 0.2. For such spins, and for mass accretion rates inferred from collapsar simulations, we show that our semianalytic model reproduces the energetics of typical GRB jets,L_jet∼ 10⁵⁰erg s⁻¹. We show that our semianalytic model reproduces the nearly constant power of typical GRB jets. If the MAD onset is delayed, this allows powerful jets at the high end of the GRB luminosity distribution,L_jet∼ 10⁵²erg s⁻¹, but the final spin remains low,a≲ 0.3. These results are consistent with the low spins inferred from gravitational wave detections of binary BH mergers. In a companion paper by Gottlieb et al., we use GRB observations to constrain the natal BH spin to bea≃ 0.2.

    

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4. Rest-frame UV Colors for Faint Galaxies at z ∼ 9–16 with the JWST NGDEEP Survey

   https://doi.org/10.3847/2041-8213/ad2de4  

   Morales, Alexa M. ; Finkelstein, Steven L. ; Leung, Gene C. K. ; Bagley, Micaela B. ; Cleri, Nikko J. ; Dave, Romeel ; Dickinson, Mark ; Ferguson, Henry C. ; Hathi, Nimish P. ; Jones, Ewan ; et al ( March 2024 , The Astrophysical Journal Letters)

   We present measurements of the rest-frame UV spectral slope,β, for a sample of 36 faint star-forming galaxies atz∼ 9–16 discovered in one of the deepest JWST NIRCam surveys to date, the Next Generation Deep Extragalactic Exploratory Public Survey. We use robust photometric measurements for UV-faint galaxies (down toM_UV∼ −16), originally published in Leung et al., and measure values of the UV spectral slope via photometric power-law fitting to both the observed photometry and stellar population models obtained through spectral energy distribution (SED) fitting withBagpipes. We obtain a median and 68% confidence interval forβfrom photometric power-law fitting of${\beta }_{\mathrm{PL}}=-{2.7}_{-0.5}^{+0.5}$and from SED fitting,${\beta }_{\mathrm{SED}}=-{2.3}_{-0.1}^{+0.2}$for the full sample. We show that when only two to three photometric detections are available, SED fitting has a lower scatter and reduced biases than photometric power-law fitting. We quantify this bias and find that after correction the median${\beta }_{\mathrm{SED},\mathrm{corr}}=-{2.5}_{-0.2}^{+0.2}$. We measure physical properties for our galaxies withBagpipesand find that our faint ($M_{\mathrm{UV}}=-{18.1}_{-0.9}^{+0.7}$) sample is low in mass ($\log [M_{*}/M_{\odot }]={7.7}_{-0.5}^{+0.5}$), fairly dust-poor ($A_{\mathrm{v}}={0.1}_{-0.1}^{+0.2}$mag), and modestly young ($\log [\mathrm{age}]={7.8}_{-0.8}^{+0.2}$yr) with a median star formation rate of$\log (\mathrm{SFR})=-{0.3}_{-0.4}^{+0.4}{M}_{\odot }{\mathrm{yr}}^{-1}$. We find no strong evidence for ultrablue UV spectral slopes (β∼ −3) within our sample, as would be expected for exotically metal-poor (Z/Z_⊙< 10⁻³) stellar populations with very high Lyman continuum escape fractions. Our observations are consistent with model predictions that galaxies of these stellar masses atz∼ 9–16 should have only modestly low metallicities (Z/Z_⊙∼ 0.1–0.2).

    

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5. Stability and Sea State as Limiting Conditions for TKE Dissipation and Dissipative Heating

   https://doi.org/10.1175/JAS-D-18-0142.1  

   Smith, Andrew W. ; Haus, Brian K. ; Zhang, Jun A. ( March 2019 , Journal of the Atmospheric Sciences)

   This study analyzes high-resolution ship data collected in the Gulf of Mexico during the Lagrangian Submesoscale Experiment (LASER) from January to February 2016 to produce the first reported measurements of dissipative heating in the explicitly nonhurricane atmospheric surface layer. Although typically computed from theory as a function of wind speed cubed, the dissipative heating directly estimated via the turbulent kinetic energy (TKE) dissipation rate is also presented. The dissipative heating magnitude agreed with a previous study that estimated the dissipative heating in the hurricane boundary layer using in situ aircraft data. Our observations that the 10-m neutral drag coefficient parameterized using TKE dissipation rate approaches zero slope as wind increases suggests that TKE dissipation and dissipative heating are constrained to a physical limit. Both surface-layer stability and sea state were observed to be important conditions influencing dissipative heating, with the stability determined via TKE budget terms and the sea state determined via wave steepness and age using direct shipboard measurements. Momentum and enthalpy fluxes used in the TKE budget are determined using the eddy-correlation method. It is found that the TKE dissipation rate and the dissipative heating are largest in a nonneutral atmospheric surface layer with a sea surface comprising steep wind sea and slow swell waves at a given surface wind speed, whereas the ratio of dissipative heating to enthalpy fluxes is largest in near-neutral stability where the turbulent vertical velocities are near zero.

    

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