Open AccessThe Impacts of Bias in Cloud‐Radiation‐Dynamics Interactions on Central Pacific Seasonal and El Niño Simulations in Contemporary GCMs
Author(s) -
Li J.L. F.,
Suhas E.,
Richardson Mark,
Lee WeiLiang,
Wang YiHui,
Yu JiaYuh,
Lee Tong,
Fetzer Eric,
Stephens Graeme,
Shen MinHua
Publication year - 2018
Publication title -
earth and space science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.843
H-Index - 23
ISSN - 2333-5084
DOI - 10.1002/2017ea000304
Subject(s) - climatology , radiative transfer , convection , environmental science , coupled model intercomparison project , atmospheric sciences , climate model , sea surface temperature , atmosphere (unit) , geology , meteorology , climate change , oceanography , geography , physics , quantum mechanics
Most of the global climate models (GCMs) in the Coupled Model Intercomparison Project, phase 5 do not include precipitating ice (aka falling snow) in their radiation calculations. We examine the importance of the radiative effects of precipitating ice on simulated surface wind stress and sea surface temperatures (SSTs) in terms of seasonal variation and in the evolution of central Pacific El Niño (CP‐El Niño) events. Using controlled simulations with the CESM1 model, we show that the exclusion of precipitating ice radiative effects generates a persistent excessive upper‐level radiative cooling and an increasingly unstable atmosphere over convective regions such as the western Pacific and tropical convergence zones. The invigorated convection leads to persistent anomalous low‐level outflows which weaken the easterly trade winds, reducing upper‐ocean mixing and leading to a positive SST bias in the model mean state. In CP‐El Niño events, this means that outflow from the modeled convection in the central Pacific reduces winds to the east, allowing unrealistic eastward propagation of warm SST anomalies following the peak in CP‐El Niño activity. Including the radiative effects of precipitating ice reduces these model biases and improves the simulated life cycle of the CP‐El Niño. Improved simulations of present‐day tropical seasonal variations and CP‐El Niño events would increase the confidence in simulating their future behavior.