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USGS · 70236098

SPEAR: The next generation GFDL modeling system for seasonal to multidecadal prediction and projection

Abstract

We document the development and simulation characteristics of the next generation modeling system for seasonal to decadal prediction and projection at the Geophysical Fluid Dynamics Laboratory (GFDL). SPEAR ( S eamless System for P rediction and EA rth System R esearch) is built from component models recently developed at GFDL—the AM4 atmosphere model, MOM6 ocean code, LM4 land model, and SIS2 sea ice model. The SPEAR models are specifically designed with attributes needed for a prediction model for seasonal to decadal time scales, including the ability to run large ensembles of simulations with available computational resources. For computational speed SPEAR uses a coarse ocean resolution of approximately 1.0° (with tropical refinement). SPEAR can use differing atmospheric horizontal resolutions ranging from 1° to 0.25°. The higher atmospheric resolution facilitates improved simulation of regional climate and extremes. SPEAR is built from the same components as the GFDL CM4 and ESM4 models but with design choices geared toward seasonal to multidecadal physical climate prediction and projection. We document simulation characteristics for the time mean climate, aspects of internal variability, and the response to both idealized and realistic radiative forcing change. We describe in greater detail one focus of the model development process that was motivated by the importance of the Southern Ocean to the global climate system. We present sensitivity tests that document the influence of the Antarctic surface heat budget on Southern Ocean ventilation and deep global ocean circulation. These findings were also useful in the development processes for the GFDL CM4 and ESM4 models.

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BibTeXRIS

Thomas L. Delworth, William F. Cooke, Alistair A. Adcroft, Mitchell Bushuk, Jan-Huey Chen, Krista A. Dunne, Paul Ginoux, Richard Gudgel, Lucas Harris, Matthew J. Harrison, Robert W. Hallberg, Nathaniel Johnson, Sarah B. Kapnick, Shian-Jian Lin, Feiyu Lu, Sergey Malyshev, Paul C. D. Milly, Hiroyuki Murakami, Vaishali Naik, Salvatore Pascale, David Paynter, Anthony Rosati, M. D. Schwarzkopf, Elena Shevliakova, Seth Underwood, Andrew T. Wittenberg, Baoqiang Xiang, Xiaosong Yang, Fanrong Zeng, Honghai Zhang, Liping Zhang, Ming Zhao. 2020-03-11. SPEAR: The next generation GFDL modeling system for seasonal to multidecadal prediction and projection. https://doi.org/10.1029/2019ms001895

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