Based on a long-term simulation of an ocean-biogeochemical coupled model, we investigate the biogeochemical response to the two types of El Niño events, a Cold Tongue (CT)-El Niño and a Warm Pool (WP)-El Niño, in which a local maximum of anomalous sea surface temperature (SST) is located in the eastern and central tropical Pacific. Our model is able to reasonably simulate the characteristics of the biological variables in a way comparable to the observations. During the developing period, anomalous low chlorophyll appears in the eastern Pacific, while it appears in the central Pacific in the WP-El Niño. The difference in the spatial-temporal response of chlorophyll for the two types of El Niño events is mainly due to the eastward zonal advection of upper ocean currents, which plays a role in bringing nutrient-poor water from the western Pacific. During the decaying period of the WP-El Niño, anomalous high chlorophyll appears concurrently with anomalous low SST in the eastern Pacific. Conversely, anomalous high chlorophyll appears in the central Pacific prior to the decaying period of the CT-El Niño. In particular, the anomalous low sea level from the northwestern Pacific shifts to the southern equatorial region during the decaying period of the CT-El Niño. This drives anticyclonic boundary currents which enhance the Equatorial Undercurrent, playing a role in the supply of nutrients to the central equatorial Pacific, resulting in an increase in chlorophyll concentration in the same region.

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  The Korea Meteorological Administration(KMA) is producing an impact-based forecast data based on both the deterministic forecast and ensemble forecast for heat waves (HW) and cold waves (CW). Ensemble prediction system for impact-based forecast is Multi-Model ensemble system which integrates UM(global, global ensemble, local, and local ensemble models), ECMWF(global and global ensemble models) and KIM(Korean Integrated Model) global model(Hereafter, impact-based forecast  based on the deterministic forecast and Multi-Model ensemble system are called `IMPC` and ‘MEPS’, respectively.). MEPS determine the risk level by using the probability of occurrence of abnormal temperatures on the Korean Peninsula. Once maximum perceived temperature(HW) or lowest temperature(CW) from all 93 Multi-Model Ensemble members were extracted, their probability distribution was determined by using a Generalized Extreme Value (GEV) distribution.  The performance of MEPS for HW was compared with IMPC for July and August 2022. Verification was conducted by evaluating how well impact-based forecast level(safe, concern, caution, warning, alarm) was matched to the observed risk level in 175 regions.   As a result of verification it was found that IMPC forecasts ‘concern’ more frequently and MEPS forecasts ‘caution’ more frequently. In July, IMPC's prediction performance is excellent for ‘safe’ and ‘concern’ level and MEPS is excellent at a ‘caution’ and ‘warning’. IMPC underestimates ‘caution’ and ‘warning’ while MEPS tends to overestimate ‘safe’ and ‘concern’. In August, ETS score of MEPS is excellent for ‘safe’ levels as well as ‘caution’ and ‘warning’ levels. In case studies, there is many cases in which MEPS detected HW better than IMPC when a high-level heat wave was observed on the Korean Peninsula. Overall, MEPS is expected to be a good reference data in the impact-based forecast where predictive ability for high risk levels is important.   The MEPS guidance uses only daily temperatures, but according to KMA’s forecast guideline, HW is defined a phenomenon in which a high temperature lasts for more than 2 days. By reflecting these conditions, future guidance needs to be improved. In the HW guidance, the risk level re-established by considering whether the risk level lasts longer tha two days improved the predictive performance of ‘safe’ and ‘concern’, and the CSI (Critical Success Index) and ETS increased at all risk level.