Japan Geoscience Union Meeting 2021

Presentation information

[J] Oral

A (Atmospheric and Hydrospheric Sciences ) » A-AS Atmospheric Sciences, Meteorology & Atmospheric Environment

[A-AS07] Weather, Climate, and Environmental Science Studies using High-Performance Computing

Fri. Jun 4, 2021 9:00 AM - 10:30 AM Ch.07 (Zoom Room 07)

convener:Hisashi Yashiro(National Institute for Environmental Studies), Takuya Kawabata(Meteorological Research Institute), Tomoki Miyakawa(Atmosphere and Ocean Research Institute, The University of Tokyo), Koji Terasaki(RIKEN Center for Computational Science), Chairperson:Hisashi Yashiro(National Institute for Environmental Studies)

9:45 AM - 10:00 AM

[AAS07-04] Progress in Tropical Weather and Climate Prediction with Global Storm-Resolving Models

★Invited Papers

*Falko Judt1 (1.National Center for Atmospheric Research )

Keywords:Tropical meteorology, Tropical cyclones, Global storm-resolving model, High-resolution model, Global cloud-resolving model

Despite advances in many areas, current-generation global weather and climate models struggle with simulating the tropical atmosphere. For example, current models have difficulties with capturing the extreme winds of tropical cyclones, and they are unable to properly simulate equatorial waves and tropical rainfall variability. It has long been hypothesized that these shortcomings are the consequence of inadequate model resolution and the need to parameterize deep convection. Unfortunately, a thorough assessment of this hypothesis has not been possible because of the tremendous computing resources required to run and analyze global models with horizontal resolution < 5 km (i.e., the resolution that is necessary to explicitly simulate convective storms). Yet as computing power has been increasing, limitations are easing, and it is now possible to produce global storm-resolving simulations and assess their benefits. Here we demonstrate that global storm-resolving models are indeed a game changer in simulating the tropical atmosphere. For example, global storm-resolving models capture the intensity of tropical cyclones, and they produce realistic equatorial waves. Nonetheless, a model intercomparison indicates that global storm-resolving models have unique biases, and further improvement is necessary to unleash the models' full potential.