Outsize Influence of Central American Orography on Global Climate

被引:27
|
作者
Baldwin, Jane W. [1 ]
Atwood, Alyssa R. [2 ]
Vecchi, Gabriel A. [3 ,4 ]
Battisti, David S. [5 ]
机构
[1] Columbia Univ, Lamont Doherty Earth Observ, Palisades, NY 10964 USA
[2] Florida State Univ, Dept Earth Ocean Atmospher Sci, Tallahassee, FL USA
[3] Princeton Univ, Dept Geosci, Princeton, NJ USA
[4] Princeton Univ, High Meadows Environm Inst, Princeton, NJ USA
[5] Univ Washington, Dept Atmospher Sci, Seattle, WA 98195 USA
来源
AGU ADVANCES | 2021年 / 2卷 / 02期
基金
美国海洋和大气管理局; 美国国家科学基金会;
关键词
Atmosphere-ocean coupled; ENSO; global climate model; orography; precipitation bias; tropical Pacific; STOCHASTIC DYNAMICAL MODEL; SEA-SURFACE TEMPERATURE; TROPICAL PACIFIC; GAP WINDS; DECADAL VARIABILITY; TIBETAN PLATEAU; SYSTEM MODEL; ANNUAL CYCLE; EL-NINO; PART II;
D O I
10.1029/2020AV000343
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Global Climate Models (GCMs) exhibit substantial biases in their simulation of tropical climate. One particularly problematic bias exists in GCMs' simulation of the tropical rainband known as the Intertropical Convergence Zone (ITCZ). Much of the precipitation on Earth falls within the ITCZ, which plays a key role in setting Earth's temperature by affecting global energy transports, and partially dictates dynamics of the largest interannual mode of climate variability: The El Nino-Southern Oscillation (ENSO). Most GCMs fail to simulate the mean state of the ITCZ correctly, often exhibiting a "double ITCZ bias," with rainbands both north and south rather than just north of the equator. These tropical mean state biases limit confidence in climate models' simulation of projected future and paleoclimate states, and reduce the utility of these models for understanding present climate dynamics. Adjusting GCM parameterizations of cloud processes and atmospheric convection can reduce tropical biases, as can artificially correcting sea surface temperatures through modifications to air-sea fluxes (i.e., "flux adjustment"). Here, we argue that a significant portion of these rainfall and circulation biases are rooted in orographic height being biased low due to assumptions made in fitting observed orography onto GCM grids. We demonstrate that making different, and physically defensible, assumptions that raise the orographic height significantly improves model simulation of climatological features such as the ITCZ and North American rainfall as well as the simulation of ENSO. These findings suggest a simple, physically based, and computationally inexpensive method that can improve climate models and projections of future climate.
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页数:14
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