In this study, a global-ocean-data-assimilation system based on the three-dimensional variational (3DVAR) scheme is built for operational oceanography. The available observations include satellite altimetry; the satellite-measured sea-surface temperature (SST); and T/S profiles from Argo floats, which are assimilated to provide the initial condition of the global-ocean forecasting. The statistical analysis methods are designed to assess the performance of the data-assimilation scheme, and the results show that the analysis SST fields agree well with OSTIA and MGDSST, and the corresponding root-mean-square errors are, respectively, 0.523 and 0.548 °C. Moreover, the analysis sea-surface-height fields are well represented at the middle and low latitudes and have a slightly greater difference in the regions with strong mesoscale eddies. The variations in the vertical distribution of the forecasting temperature profiles resemble those of the GTS buoy observation. The forecasting salinity profiles correspond well to GTS observations, except with a weaker cold bias between the depths 100 and 200 m (about 0.2 PSU) at buoy station 2901494. Overall, our 3DVAR assimilation system plays a significant role in improving the accuracy of analysis and forecasting fields for operational oceanography.

Marine heatwaves (MHWs) are changing global ecosystems and bearing profound socio-economic impacts, yet our understanding of the spatial features, temporal evolution characteristics, and regional differences in China’s marginal seas remains insufficient. In this study, the spatio-temporal variation characteristics of the frequency, mean intensity, maximum intensity, cumulative intensity, duration and total days of MHWs are systematically analyzed based on daily sea surface temperature data from Operational Sea Surface Temperature and Ice Analysis (OSTIA) for the period of 1983–2020. The results show the following: The annual mean frequency of MHWs in China’s coastal seas is 1.4–4.6 counts per year and increases gradually from north to south. The annual mean of mean intensity, maximum intensity and cumulative intensity are, respectively, in the ranges of 0.3–2.9 °C, 0.4–3.7 °C and 3.9–41.7 °C days, all of which show a significant decreasing trend from north to south. The annual mean of duration and total days of MHWs are in the respective ranges 8.7–19.7 and 18.9–69.1 days. The annual mean of frequency, cumulative intensity, duration and total days all show a clear increasing trend, with respective linear increases of 1.03 counts, 3.57 °C days, and 1.98 and 17.58 days per decade. The annual means of the mean intensity and maximum intensity have no obvious upward trend, with the exceptions of the Bohai and Yellow Seas. Finally, MHWs were divided into the four categories of moderate, strong, severe and extreme, with the results showing that moderate ones account for more than 70% of all heatwave events, while strong, severe and extreme ones, respectively, account for about 25%, 2% and 0.02%.

The ‘Two Oceans and One Sea’ area (West Pacific, Indian Ocean, and South China Sea; 15°S–60°N, 39°–178°E) is a core strategic area for the ‘21st Century Maritime Silk Road’ project, as well as national defense. With the increasing demand for disaster prevention and mitigation, the importance of 10–30-day extended range prediction, between the conventional short-term (around seven days) and the climate scale (longer than one month), is apparent. However, marine extended range prediction is still a ‘blank point’ in China, making the early warning of marine disasters almost impossible. Here, the authors introduce a recently launched Chinese national project on a numerical forecasting system for extended range prediction in the ‘Two Oceans and One Sea’ area based on a regional ultra-high resolution multi-layer coupled model, including the scientific aims, technical scheme, innovation, and expected achievements. The completion of this prediction system is of considerable significance for the economic development and national security of China. Graphical Abstract

In order to figure out the associated underlying dynamical processes of the 2014–2015 warming event, we used the ECCO (Estimating the Circulation and Climate of the Ocean) reanalysis from 1993 to 2016 and two combined scatterometers, QuikSCAT and ASCAT, to analysis hydrodynamic condition and ocean heat budget balance process in the equatorial tropical pacific. The spatiotemporal characteristics of that warming event were revealed by comparing the results with a composite El Niño. The results showed that the significant differences between the 2014 and 2015 warming periods were the magnitudes and positions of the equatorial easterly wind anomalies during the summer months. The abruptly easterly wind anomalies of 2014 that spread across the entire equatorial Pacific triggered the upwelling of the equatorial Kelvin waves and pushed the eastern edge of the warm pool back westward. These combined effects caused abrupt decreases in the sea surface temperatures (SST) and upper ocean heat content (OHC) and damped the 2014 warming process into an El Niño. In addition, the ocean budget of the upper 300 m of the El Niño 3.4 region showed that different dynamical processes were responsible for different warming phases. For example, at the beginning of 2014 and 2015, the U advection and subsurface processes played dominant roles in the positive ocean heat content tendency. During the easterly wind anomalies period of 2014, the U advection process mainly caused a negative tendency and halted the development of the warming phase. In regard to the easterly wind anomalies of 2015, the U advection and subsurface processes were weaker negatively when compared with that in 2014. However, the V advection processes were consistently positive, taking a leading role in the positive trends observed in the middle of 2015.

In recent years, global sea surface temperature (SST) has risen steadily, with 2023 and 2024 breaking successive historical observation records, thus rendering marine heatwaves (MHWs) an unignorable new marine disaster. To scientifically mitigate and assess the impacts of MHW disasters on China’s coastal waters, this study developed a monitoring and weekly forecast product for MHWs based on the OSTIA (Operational SST and Ice Analysis) SST observational fusion data and SST numerical forecast data. Evaluation shows the following: the quarterly average of the RMSE for the weekly MHWs intensity forecasts is 0.52 °C; and the quarterly average score for the weekly MHW’s category forecasts is 94.4. Characteristic analysis of 2024 MHWs reveals 93.7% of China’s coastal waters and adjacent areas experienced MHWs throughout the year, and the average monthly impact rate of MHWs is 43.8%. High-value areas of total days and cumulative intensity are concentrated in the central-eastern part of the Yellow Sea, which makes it the most severely affected area by MHW disasters in 2024. The weekly MHW’s forecast product developed in this study provides deterministic weekly forecasts of MHWs intensity and categories for China’s coastal waters. This product can serve as a guidance basis for MHW disaster prevention and mitigation, and help reduce losses caused by MHWs to the marine environment and marine economy.