Simulations of global hurricane climatology, interannual variability, and response to global warming using a 50-km resolution GCM.

By Ming Zhao, I. Held, Shian‐Jiann Lin, Gabriel Vecchi. 2009

706 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change, Oceanography

View Paper: https://www.semanticscholar.org/paper/90f710fb5af82d8345f2f8d568e27ffca075d95e

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Citations in the corpus

Statistical–Dynamical Predictions of Seasonal North Atlantic Hurricane Activity (2011, methodology): “We can use the correlation coefﬁcients and RMSEs from Zhao et al. (2009) and from applying the statistical hurricane emulator to observed SSTs ( r 5 0.78 and 0.76, and RMSE 5 1.91 and 1.99 hurricanes per year, respectively) as estimates of the explainable variance in hurricane counts from perfect kn”
The GFDL Global Atmosphere and Land Model AM4.0/LM4.0: 2. Model Description, Sensitivity Studies, and Tuning Strategies (2018, background): “1 (GFDL-GAMDT, 2004), AM3 (Donner et al., 2011), and HiRAM (Zhao et al., 2009).”
Global Warming Effects on U.S. Hurricane Damage (2011, background): “But even horizontal grid spacing as low as 20 km (Oouchi et al. 2006) cannot resolve the critical eyewall region of the cyclones, and invariably the maximum wind speed of simulated storms is truncated at relatively low values by the lack of horizontal resolution (Zhao et al. 2009).”
A Two-Way Nested Global-Regional Dynamical Core on the Cubed-Sphere Grid (2013, methodology): “Nearly any vertically monotonic quantity can be used as the base for the Eulerian coordinate; here, we use a 32-level hybrid s–p terrain-following vertical coordinate (Chen and Lin 2011; Zhao et al. 2009), in which for given constants ak, bk for each layer interface k 5 1, .”
Uncertainty in Model Climate Sensitivity Traced to Representations of Cumulus Precipitation Microphysics (2016, methodology): “Similarly to HiRAM, when the previous modified UWShCu convection (Zhao et al. 2009) was used in AM4 prototypes, we find the model produces highquality simulations of mean climate and tropical cyclone statistics when themodel is forced by the observed SSTs.”
The GFDL Global Atmosphere and Land Model AM4.0/LM4.0: 1. Simulation Characteristics With Prescribed SSTs (2018, methodology): “We mention but do not emphasize the various features that this model shares with previous GFDL models AM2 (GFDL-GAMDT, 2004), AM3 (Donner et al., 2011), HiRAM (Zhao et al., 2009), and LM3 (Milly et al., 2014).”
Skilful multi-year predictions of Atlantic hurricane frequency (2010, background): “Either way, hurricane frequency is potentially predictable, because climate models can directly simulate year-to-year variations in Atlantic tropical storm frequency, if forced by observed sea surface temperature”
Downscaling CMIP5 climate models shows increased tropical cyclone activity over the 21st century (2013, methodology): “An important limitation of this approach is that it severely underresolves tropical cyclones, resulting in a substantial truncation of the intensity spectrum of simulated storms, even at 50-km grid spacing (11), and usually produces fewer events than observed (12).”