Are the extreme marine heatwave events in the central-eastern tropical Pacific predictable 30–60 days in advance by NUIST CFS1.1 model?

• Published in: Atmospheric research 2023-07, Vol.289, p.106744, Article 106744
• Main Authors: Lin, Lin, Yu, Yueyue, Lu, Chuhan, Luo, Jingjia, Chen, Lin, Ma, Jing, Guan, Zhaoyong, Wu, Jiye
• Format: Article
• Language: English
• Subjects: Extreme marine heatwave; NUIST CFS1.1 model; Sub-seasonal forecasts; Tropical Pacific
• ISSN: 0169-8095; 1873-2895
• DOI: 10.1016/j.atmosres.2023.106744

The sub-seasonal predictability of extreme Marine Heat Wave events (MHWs) is still not clear despite of its importance for early warning systems and disaster prevention. This study focuses on the seven extreme MHW events in the central-eastern tropical Pacific from 1983 to 2020 and evaluates their sub-seasonal (30–60 day) forecast skills by the Nanjing University of Information Science and Technology Climate Forecast System (NUIST CFS1.1). It is found that among various indices of MHW, the areal intensity reaching the standard of moderate warming over the course of the MHW (denoted as the IS>1 index) is the most predictable while the index of grid cells experiencing extreme MHW is the least predictable. The start date of MHW always has a larger forecast error than the end date. The sub-seasonal forecasts of NUIST CFS1.1 is able to capture three out of seven MHW events. The sub-seasonal predictable MHW events are mainly characterized by peak IS>1 and IS>2 (same as IS>1, but reaching the standard of strong warming) near the super El Niño, larger area, stronger intensity, a longer duration, and smoother variations of IS>1 and IS>2. Contrarily, the MHW events with remarkable shorter-timescale fluctuations of IS>1 and IS>2 (particularly the later) or characterized by several rounds of local warming are less predictable. A further comparison among ensemble forecast members shows that the ensemble members using a fast sea surface temperature nudging scheme perform the best in predicting the IS>2, which could be an effective way to improve the sub-seasonal forecasts of MHW. •3/7extreme MHWs in central-eastern tropical Pacific are well performed 30–60d ahead.•The sub-seasonal predictability depends on timescale of areal intensity fluctuations.•The 30-60d forecast skill of areal intensity can be improved by fast nudging SST.