Artificial selection

Targeted artificial ocean cooling to weaken tropical cyclones would be futile

  • Moore, JC et al. Atlantic hurricane surge response to geoengineering. proc. Natl Acad. Science. UNITED STATES 11213794–13799 (2015).

    CASE
    Article

    Google Scholar

  • Jones, AC et al. Impacts of hemispherical solar geoengineering on the frequency of tropical cyclones. Nat. Common. 8, https://doi.org/10.1038/s41467-017-01606-0 (2017).

  • Jones, AC et al. Regional climate impacts of stabilizing global warming at 1.5 K using solar geoengineering. future of earth 6230-251 (2018).

    Article

    Google Scholar

  • Irvine, P. et al. Halving warming through idealized solar geoengineering mitigates key climate risks. Nat. Climate change 9295-299 (2019).

    Article

    Google Scholar

  • Latham, J. et al. Clearing of sea clouds. Philos. Trans. R. Soc. A 3704217–4262 (2012).

    Article

    Google Scholar

  • Ahlm, L. et al. Clearing of marine clouds – also effective without clouds. atmosphere. Chem. Phys. 1713071–13087 (2017).

    CASE
    Article

    Google Scholar

  • Willoughby, HE, Jorgensen, DP, Black, RA & Rosenthal, SL Project STORMFURY: A Science Chronicle 1962-1983. Bull. A m. Meteorol. Soc. 66505–514 (1985).

    Article

    Google Scholar

  • Robock, A., Bunzl, M., Kravitz, B. & Stenchikov, GL A test for geoengineering? Science 327530-531 (2010).

    CASE
    Article

    Google Scholar

  • Robock, A., MacMartin, DG, Duren, R. & Christensen, MW Studying geoengineering with natural and anthropogenic analogues. Air conditioning To change 121445–458 (2013).

    Article

    Google Scholar

  • Latham, J. et al. Brightening of marine clouds: regional applications. Philos. Trans. R. Soc. A 372 1–11 (2014).

  • MacCracken, MC The rationale for accelerating region-focused climate intervention research. future of earth 4649-657 (2016).

    Article

    Google Scholar

  • Uram, H. United States Patent Application Publication No. 0008155A1. https://patents.google.com/patent/US20020008155A1/en?inventor=herbert+uram&oq=herbert+uram (2002).

  • Kitamura, K. United States Patent Application Publication No. 7832657B2. https://patents.google.com/patent/US7832657B2/en?oq=7%2C832%2C657 (2010).

  • Gradle, R. United States Patent Application Publication No. 8148840B2. https://patents.google.com/patent/US7832657B2/en?oq=7%2C832%2C657 (2012).

  • Tawil, JJ U.S. Patent Application Publication No. 0038063A1. https://patents.google.com/patent/US20130038063A1/en?assignee=jack+joseph+tawil&oq=jack+joseph+tawil (2013).

  • Bowers, JA et al. United States Patent Application Publication No. 8685254B2. https://patents.google.com/patent/US8685254B2/en?oq=8685254 (2014).

  • OceanTherm: https://www.oceantherm.no/ (2021).

  • Emanuel, KA A theory of air-sea interaction for tropical cyclones. Part I: steady state maintenance. J. Atmos. Science. 43585–605 (1986).

  • Emanuel, KA Maximum hurricane intensity. J.Atmos. Science. 451143–1155 (1988).

    Article

    Google Scholar

  • Miller, BI A study of Hurricane Donna’s (1960) infill on land. Mon Weather Rev. 92389–406 (1964).

    Article

    Google Scholar

  • Tuleya, RE Development and decay of tropical storms: sensitivity to surface boundary conditions. Mon Weather Rev. 122291–304 (1994).

    Article

    Google Scholar

  • DeMaria, M., Mainelli, M., Shay, LK, Knaff, JA, and Kaplan, J. Further enhancements to the Statistical Hurricane Intensity Forecasting System (SHIPS). Weather forecast. 20531–543 (2005).

    Article

    Google Scholar

  • Hlywiak, J. & Nolan, DS The response of the near-surface tropical cyclone wind field to the length of inner surface roughness and soil moisture content during and after landfall. J.Atmos. Science. 78983-1000 (2021).

  • Cione, JJ & Uhlhorn, EW Sea surface temperature variability in hurricanes: implications for intensity change. Mon Weather Rev. 1311783–1796 (2003).

    Article

    Google Scholar

  • D’Asaro, EA, Sanford, TB, Niiler, PP & Terrill, EJ Cold wake of Hurricane Frances. Geophys. Res. Lett. 342–7 (2007).

    Google Scholar

  • Chen, S., Elsberry, RL & Harr, PA Modeling the interaction of a tropical cyclone with its cold wake. J. Atmos. Science. 743981–4001 (2017).

    Article

    Google Scholar

  • Guo, T., Sun, Y., Liu, L. & Zhong, Z. The impact of storm-induced SST cooling on storm size and destructiveness: results from coupled atmosphere-ocean simulations. J. Meteol. Res. 341068-1081 (2020).

    Article

    Google Scholar

  • Shay, LK, Goni, GJ & Black, PG Effects of a warm ocean feature on Hurricane Opal. Mon Weather Rev. 1281366-1383 (2000).

    Article

    Google Scholar

  • Mainelli, MM, DeMaria, M., Shay, LK & Goni, G. Application of ocean heat content estimation to operational forecasting of recent Atlantic Category 5 hurricanes. Weather forecast. 233–16 (2008).

    Article

    Google Scholar

  • Balaguru, K. et al. Effect of ocean barrier layers on the intensification of tropical cyclones. proc. Natl Acad. Science. UNITED STATES 10914343–14347 (2012).

    CASE
    Article

    Google Scholar

  • Hlywiak, J. & Nolan, D. The influence of ocean barrier layers on tropical cyclone intensity as determined by idealized coupled numerical simulations. J.Phys. Oceanogr. 491723-1745 (2019).

  • Rudzin, JE, Shay, LK & Cruz, BJDL The impact of the Amazon-Orinoco River plume on enthalpy flux and air-sea interaction in tropical cyclones in the Caribbean Sea. Mon Weather Rev. 147931–950 (2019).

    Article

    Google Scholar

  • Powell, M. & Reinhold, T. Destructive potential of tropical cyclones by integrated kinetic energy. Bull. A m. Meteorol. Soc. 88513-526 (2007).

    Article

    Google Scholar

  • Klotzbach, PJ et al. Surface pressure is a more adept predictor of normalized hurricane damage than maximum sustained wind. Bull. A m. Meteorol. Soc. 101E830–E846 (2020).

    Article

    Google Scholar

  • Miyamoto, Y., Bryan, GH & Rotunno, R. An analytical model of maximum potential intensity for tropical cyclones incorporating the effect of ocean mixing. Geophys. Res. Lett. 445826–5835 (2017).

    Article

    Google Scholar

  • US Energy Information Administration. Monthly energy balance for April 2022. Technical Report 4 (US Energy Information Administration, 2022).

  • Ma, Z., Fei, J., Liu, L., Huang, X. & Li, Y. An investigation of the influences of mesoscale ocean eddies on tropical cyclone intensities. Mon Weather Rev. 1451181-1201 (2017).

    Article

    Google Scholar

  • Yablonsky, RM & Ginis, I. Impact of warm ocean gyre circulation on hurricane-induced sea surface cooling with implications for hurricane intensity. Mon Weather Rev. 141997-1021 (2013).

    Article

    Google Scholar

  • Feng, EY, Su, B. & Oschlies, A. Geoengineered vertical ocean water exchange may accelerate global deoxygenation. Geophys. Res. Lett. 47e2020GL088263 (2020).

  • Gray, WM Global view of the origin of tropical disturbances and storms. Mon Weather Rev. 96669–700 (1968).

    Article

    Google Scholar

  • DeMaria, M., Mainelli, M., Shay, LK, Knaff, JA, and Kaplan, J. Further enhancements to the Statistical Hurricane Intensity Forecasting System (SHIPS). Weather forecast. 20531–543 (2005).

    Article

    Google Scholar

  • Kaplan, J. et al. Assessing environmental impacts on the predictability of rapidly intensifying tropical cyclones using statistical models. Weather forecast. 301374-1396 (2015).

    Article

    Google Scholar

  • Foltz, GR, Balaguru, K. & Hagos, S. Interbasin differences in the relationship between SST and tropical cyclone intensification. Mon Weather Rev. 146853–870 (2018).

  • Wadler, JB, Zhang, JA, Rogers, RF, Jaimes, B. & Shay, LK The Rapidly Intensifying Hurricane Michael (2018): Storm Structure and Relationship to Environmental and Air-Sea Interactions. Mon Weather Rev. 149245-267 (2021).

    Article

    Google Scholar

  • Gilford, D. dgilford/pyPI: pyPI v1.3 (initial package release). https://zenodo.org/record/3985975 (2020).

  • Gilford, DM PyPI (v1.3): calculations of the potential intensity of tropical cyclones in python. Geosci. Model Dev. 142351-2369 (2021).

    Article

    Google Scholar

  • Hersbach, H. et al. Monthly average of ERA5 data on pressure levels from 1979 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). https://doi.org/10.24381/cds.6860a573 (2019).

  • Nolan, DS Assessing environmental suitability for tropical cyclone development with the point downscaling method. J. Adv. Model. System Ground 31–28 (2011).

  • Onderlinde, MJ & Nolan, DS The response of tropical cyclones to changing wind shear using the time-varying point downscaling method. J. Adv. Model. System Ground 9908–931 (2017).

    Article

    Google Scholar

  • Lim, JOJ & Hong, SY Effects of bulk ice microphysics on simulated monsoon precipitation over East Asia. J. Geophys. Res. atmosphere. 1101–16 (2005).

    Article

    Google Scholar

  • Zhang, C., Wang, Y. & Hamilton, K. Improved representation of boundary layer clouds over the Southeast Pacific in ARW-WRF using a cumulus parameterization scheme Modified Tietke. Mon Weather Rev. 1393489–3513 (2011).

    Article

    Google Scholar

  • Janjic, Z. Non-singular implementation of the Level 2.5 Mellor-Yamada scheme in the NCEP Meso model. Note from the NCEP office 43761 (2002).

    Google Scholar

  • Edson, JB et al. On the momentum exchange above the open ocean. J.Phys. Oceanogr. 431589-1610 (2013).

    Article

    Google Scholar

  • Chen, F. & Dudhia, J. Coupling an Advanced Land Surface Hydrological Model with the Penn State-NCAR MM5 Modeling System. Part I: model implementation and sensitivity. Mon Weather Rev. 129569–585 (2001).

    Article

    Google Scholar

  • Pollard, RT, Rhines, PB & Thompson, RO Deepening of the wind mixed layer. Geophys. Astrophysic. Dynamic fluid. 4381–404 (1972).

    Article

    Google Scholar