EGU22-10950, updated on 28 Mar 2022
https://doi.org/10.5194/egusphere-egu22-10950
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Asymmetry in the prediction skills of NMME models for springtime droughts and pluvials over East Asia

Byeong-Hee Kim and Jonghun Kam
Byeong-Hee Kim and Jonghun Kam
  • Pohang University of Science and Technology, Division of Environmental Science and Engineering, Korea, Republic of (kbhee87@postech.ac.kr)

Over East Asia, reliable forecasts of boreal spring droughts and pluvials can provide time window of opportunities to mitigate their adverse effects. Here, we aim to assess the seasonal prediction skill of boreal spring droughts and pluvials over East Asia (EA), using NMME and atmospheric-only global climate model (AGCM) simulations. Results show that NMME models show a better prediction skill of pluvials than that of droughts, indicating asymmetry in the prediction skill. This asymmetric tendency is also found in the prediction skill of sea surface temperature (SST) during the corresponding drought and pluvial years. Results from the AGCM simulations show asymmetry in the prediction skills of spring droughts and pluvials, indicating the limited predictability of SST-teleconnections in the model physics. The findings of this study prioritize a need to improve the representation of sea-air interactions during drought years in the current climate models.

How to cite: Kim, B.-H. and Kam, J.: Asymmetry in the prediction skills of NMME models for springtime droughts and pluvials over East Asia, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10950, https://doi.org/10.5194/egusphere-egu22-10950, 2022.

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