# Cloud Radiative Feedbacks during the ENSO Cycle Simulated by CAMS-CSM

• Corresponding author: Lijuan HUA, hualj@cma.gov.cn
• Funds:

Supported by the National Key Research and Development Program (2018YFC1506002); National Natural Science Foundation of China (41606011, 41705059, 41630423, and 41420104002); Basic Scientific Research and Operation Foundation of Chinese Academy of Meteorological Sciences (2017Y007); National Science Foundation AGS-1565653; National (Key) Basic Research and Development (973) Program of China (2015CB453200); Startup Foundation for Introducing Talent of NUIST, LASG Open Project; open fund of State Key Laboratory of Loess and Quartary Geology (SKLLQG1802), and NUIST Excellent Bachelor Dissertation Funding (1241591901003). This is the Earth System Modeling Center (ESMC) contribution (No. 247)

• doi: 10.1007/s13351-019-8104-3
• This study evaluated the simulated cloud radiative feedbacks (CRF) during the El Niño–Southern Oscillation (ENSO) cycle in the latest version of the Chinese Academy of Meteorological Sciences climate system model (CAMS-CSM). We conducted two experimental model simulations: the Atmospheric Model Intercomparison Project (AMIP), forced by the observed sea surface temperature (SST); and the preindustrial control (PIcontrol), a coupled run without flux correction. We found that both the experiments generally reproduced the observed features of the shortwave and longwave cloud radiative forcing (SWCRF and LWCRF) feedbacks. The AMIP run exhibited better simulation performance in the magnitude and spatial distribution than the PIcontrol run. Furthermore, the simulation biases in SWCRF and LWCRF feedbacks were linked to the biases in the representation of the corresponding total cloud cover and precipitation feedbacks. It is interesting to further find that the simulation bias originating in the atmospheric component was amplified in the PIcontrol run, indicating that the coupling aggravated the simulation bias. Since the PIcontrol run exhibited an apparent mean SST cold bias over the cold tongue, the precipitation response to the SST anomaly (SSTA) changes during the ENSO cycle occurred towards the relatively warmer western equatorial Pacific. Thus, the corresponding cloud cover and CRF shifted westward and showed a weaker magnitude in the PIcontrol run versus observational data. In contrast, the AMIP run was forced by the observational SST, hence representing a more realistic CRF. Our results demonstrate the challenges of simulating CRF in coupled models. This study also underscores the necessity of realistically representing the climatological mean state when simulating CRF during the ENSO cycle.
• Fig. 1.  The response of SWCRF to SSTA changes (W m−2 K−1) during the ENSO cycle for the (a) observation, (b) AMIP run, and (c) PIcontrol run. Spatial pattern correlation coefficients between the two simulations and observational data are shown in Figs. 1b, c.

Fig. 2.  As in Fig. 1, but for the response of LWCRF to SSTA changes (W m−2 K−1) during the ENSO cycle.

Fig. 3.  From left to right, bars show the SWsfc feedback (${\alpha _{{\rm{SW}}}}$; m−2 K−1), DYF, RHF, and LWPF from the reanalyses (green bars), AMIP run (blue), and PIcontrol run (red). Note that the feedbacks shown here were calculated by using only the positive Niño 3 SSTAs (SSTA > 0 K).

Fig. 4.  As in Fig. 1, but for the response of CLD to SSTA changes (% K−1) during the ENSO cycle.

Fig. 5.  The cloud fraction response to SSTA changes (% K−1) during the ENSO cycle along the equator (averaged between 5°S and 5°N) for (a) AMIP and (b) PIcontrol runs.

Fig. 6.  As in Fig. 1, but for the response of precipitation to SSTA changes (mm day−1 K−1) during the ENSO cycle.

Fig. 7.  The vertical velocity response to SSTA changes (hPa day−1 K−1) during the ENSO cycle along the equator (averaged between 5°S and 5°N) for the (a) observation, (b) AMIP run, and (c) PIcontrol run.

Fig. 8.  Climatological SST (°C) for the (a) observational data and (b) PIcontrol run. (c) The climatological SST profile along the equator (averaged between 5°S and 5°N), and the y-axis denotes the unit of temperature (°C).

###### 通讯作者: 陈斌, bchen63@163.com
• 1.

沈阳化工大学材料科学与工程学院 沈阳 110142

## Cloud Radiative Feedbacks during the ENSO Cycle Simulated by CAMS-CSM

###### Corresponding author: Lijuan HUA, hualj@cma.gov.cn;
• 1. Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environmental Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology (NUIST), Nanjing 210044
• 2. State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029
• 3. State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi’an 710061
• 4. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, China Meteorological Administration, Beijing 100081
Funds: Supported by the National Key Research and Development Program (2018YFC1506002); National Natural Science Foundation of China (41606011, 41705059, 41630423, and 41420104002); Basic Scientific Research and Operation Foundation of Chinese Academy of Meteorological Sciences (2017Y007); National Science Foundation AGS-1565653; National (Key) Basic Research and Development (973) Program of China (2015CB453200); Startup Foundation for Introducing Talent of NUIST, LASG Open Project; open fund of State Key Laboratory of Loess and Quartary Geology (SKLLQG1802), and NUIST Excellent Bachelor Dissertation Funding (1241591901003). This is the Earth System Modeling Center (ESMC) contribution (No. 247)

Abstract: This study evaluated the simulated cloud radiative feedbacks (CRF) during the El Niño–Southern Oscillation (ENSO) cycle in the latest version of the Chinese Academy of Meteorological Sciences climate system model (CAMS-CSM). We conducted two experimental model simulations: the Atmospheric Model Intercomparison Project (AMIP), forced by the observed sea surface temperature (SST); and the preindustrial control (PIcontrol), a coupled run without flux correction. We found that both the experiments generally reproduced the observed features of the shortwave and longwave cloud radiative forcing (SWCRF and LWCRF) feedbacks. The AMIP run exhibited better simulation performance in the magnitude and spatial distribution than the PIcontrol run. Furthermore, the simulation biases in SWCRF and LWCRF feedbacks were linked to the biases in the representation of the corresponding total cloud cover and precipitation feedbacks. It is interesting to further find that the simulation bias originating in the atmospheric component was amplified in the PIcontrol run, indicating that the coupling aggravated the simulation bias. Since the PIcontrol run exhibited an apparent mean SST cold bias over the cold tongue, the precipitation response to the SST anomaly (SSTA) changes during the ENSO cycle occurred towards the relatively warmer western equatorial Pacific. Thus, the corresponding cloud cover and CRF shifted westward and showed a weaker magnitude in the PIcontrol run versus observational data. In contrast, the AMIP run was forced by the observational SST, hence representing a more realistic CRF. Our results demonstrate the challenges of simulating CRF in coupled models. This study also underscores the necessity of realistically representing the climatological mean state when simulating CRF during the ENSO cycle.

Reference (55)

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