Quality control methods for KOOS operational sea surface temperature products

Sea surface temperature SST obtained from the initial version of the Korea Operational Oceanographic System（KOOS） SST satellite have low accuracy during summer and daytime. This is attributed to the diurnal warming effect. Error estimation of SST data must be carried out to use the real-time forecasting numerical model of the KOOS. This study suggests two quality control methods for the KOOS SST system. To minimize the diurnal warming effect, SSTs of areas where wind speed is higher than 5 m/s were used. Depending on the wind threshold value, KOOS SST data for August 2014 were reduced by 0.15°C. Errors in SST data are considered to be a combination of random, sampling, and bias errors. To estimate bias error, the standard deviation of bias between KOOS SSTs and climatology SSTs were used. KOOS SST data yielded an analysis error standard deviation value similar to OSTIA and NOAA NCDC（OISST） data. The KOOS SST shows lower random and sampling errors with increasing number of observations using six satellite datasets. In further studies, the proposed quality control methods for the KOOS SST system will be applied through more long-term case studies and comparisons with other SST systems.

The 2020–2021 prolonged La Niña evolution in the tropical Pacific

The evolution of sea surface temperature(SST)in the tropical Pacific during 2020–2021 indicates a second-year cooling in late 2021 again,following the 2020 La Niña event.Its physical explanations are still lacking,and there is a clear need to understand the underlying processes involved.Observational data and reanalysis products are used to describe the characteristics and spatiotemporal evolution of upper-ocean thermal anomalies;an intermediate coupled model(ICM)is also used to perform numerical experiments to confirm these observation-based inferences.The evolution of subsurface thermal anomalies is critically important to that of SST in the central-eastern equatorial Pacific;the effects of the former on the latter can be well represented by the temperature of subsurface waters entrained into the mixed layer(Te),a field that reflects a subsurface forcing on SST.The SST evolution is sensitively dependent on the intensities of the local effect associated with Te anomalies in the eastern equatorial Pacific and the remote effect associated with subsurface anomalies from the western Pacific.During early-and mid-2021,a competition was present between these local and remote effects associated with Te anomalies.When the remote warming effect dominates the local cooling effect,the cold SST condition in the east is likely to turn into neutral and warm conditions;otherwise,it tends to continue.In addition,the negative Te anomalies were sustained and enhanced by off-equatorial processes due to equatorial wave reflections at the eastern boundary associated with the 2020 La Niña event.The SST evolution in mid-2021 corresponded to a situation in which the warming effect associated with positive subsurface thermal anomalies from the west were not strong enough to counteract the local cooling effect associated with negative anomalies in the east.In due course,cold SST anomalies in the east developed again and the second-year cooling reoccurred in late 2021,with a turning point in June 2021.Modeling experiments support these arguments and indicate that the intensity of subsurface thermal effect on SST,as represented by Te anomalies,needs to be adequately depicted for coupled models to capture the 2021 second-year cooling conditions in the tropical Pacific.