The Horn of Africa (HOA) is one of the most drought-prone regions in the world with many arid and semiarid areas, and even some extremely arid areas. Primarily affected by the marine continental climate systems, this zone is really sensitive to global warming. Drought is the main type of natural disaster affecting this region, which triggers famine, civil conflict, and even deterioration of food security. The present study examined changes in droughts in the HOA during 1979–2019 based on Standardized Precipitation Evapotranspiration Index (SPEI). Results show that frequency, duration, and intensity of droughts exhibited an increasing trend over the past decades. Moreover, in October to December (called locate “short rains”) 2016 and March to May (called locate “long rains”) 2017, the HOA experienced the most severe drought. Based on Generalized Extreme Value (GEV) fitting, the 2016/2017 SPEI index corresponds to a drought that occurs every 250 years in the observational records. However, considering the precipitation in short rains of 2016 (long rains of 2017) was only 27.1% (11.8%) less than normal, it is hard to explain the formation of this extreme drought only from precipitation anomalies. Further statistical result shows that the evaporation in 2016/2017 corresponds to a 1-in-131 years event in the observed records. The abnormally high temperature (1.02 °C higher than normal) as well as the greatest potential evaporation since 1979 are the more important causes for the formation of drought. Thus, the extreme drought in 2016/2017, probably caused by the combined effect of dry condition and high temperature simultaneously, and the latter, played a leading role. In other words, droughts can be exacerbated by the co-occurrence of extreme high temperature. With continuous warming caused by anthropogenic activities in the next decades, the Horn of Africa may be a hotspot of the compound droughts and, therefore, it is especially important to considering the combined impacts from less precipitation and high temperature when predicting the future drought trend and making adaptation measures.

Yunnan Province in Southwest China is vulnerable to droughts due to its distinctive topography and local climate. Spring drought in Yunnan (SDY), which accounts for 70% of all drought events, causes the most severe devastation. By examining the variation characteristics of droughts in Yunnan from 1961 to 2020 in terms of the standardized precipitation evapotranspiration index (SPEI), this present study shows that droughts in Yunnan have worsened in the past 60 years on different timescales. Especially, the SDY exhibits notable interannual and interdecadal variations, with no significant long-term trend, although the spring average regional temperatures have risen at a rate of 0.33 °C/10a since 1961. Here, in order to quantify the contribution of the precipitation and temperature, the two main meteorological impact factors, to the SDY under the exacerbation of climate warming, the statistical analyses reveal that precipitation plays a more crucial role than temperature in interannual and interdecadal SDY variations. Further, a diagnostic analysis of the moisture budget equation indicates that suppressed vertical moisture advection is the most important physical process affecting the reduced rainfall amount in spring, followed by the restricted horizontal water vapor transport. Meanwhile, the weak Bay of Bengal (BOB) summer monsoon, which is likely regulated by El Niño-like sea surface temperature anomalies (SSTAs) in spring, is closely linked with the SDY. This mechanism provides the possibility of SDY predictability on a seasonal scale.

A marine heatwave (MHW) can significantly harm marine ecosystems and fisheries. Based on a remotely sensed sea surface temperature (SST) product, this study investigated MHWs behaviors in the South China Sea (SCS) throughout the warm season (May to September) from 1982 to 2020. The distributions of the three MHW indices used in this study showed significant latitudinal variations: more frequent, longer, and more intense MHWs appear in the northern SCS, and less frequent, shorter, and weaker MHWs appear in the southern SCS. Using the empirical orthogonal function (EOF) method, we found that the first leading modes of the three MHW indices account for more than half of the total variance. The first leading modes reveal uniform anomalies throughout the SCS, with the maximum in the deep central portion and its surroundings. Their corresponding time series showed significant interdecadal variations, with a turning point around 2009. Since 2010, the SCS has seen an increase in the frequency, length, and severity of MHWs. The incidence of MHWs has been linked to the presence of stable near-surface anticyclonic anomalies, which reduced cloud cover and increased solar radiation. This abnormal pattern was usually accompanied by the intensification and westward shift of the western North Pacific subtropical high (WNPSH). The findings imply that MHWs in the SCS may be predictable on interannual and decadal scales.

Marine oil spill simulations typically employ the oil particle method to calculate particle trajectories, considering various factors such as wind, current, and turbulence. The wind drift factor (WDF), a random element determining the proportion of wind’s effect on oil particles, is often empirically set as a constant in traditional oil spill models, introducing limitations. This study proposes a support vector regression-based parameterization modeling (SVR-PM) for the WDF. Using extensive buoy data and ocean hydrodynamic reanalysis data, we trained an SVR model to compute the WDF in real-time based on real-time wind speed. The SVR-PM was integrated into an oil spill model to enhance the computation of the wind-induced velocity term. We validated the model using satellite images of two significant oil spills, resulting in an excellent average agreement. The SVR-PM’s advantage lies in enhancing the accuracy of wind-induced velocity term in oil spill simulations and demonstrating strong adaptability and generalizability over time and space. This advancement holds significant implications for maritime departments and emergency disaster response units.

Extreme sea surface temperatures (SSTs) attract much attention in recent years. However, the detailed spatial and temporal pattern of the extreme SSTs in China Seas has not been well understood. Using the daily SST data set of OISST v2 from January 1, 1982 to December 31, 2013, and based on four extreme SST indices, the frequency and intensity of SST extremes in the China Seas were examined. The analysis showed that the annual mean SST exhibited cooling trend, on pace with a trend of − 0.34 °C/decade during 1998–2013, confirming the previous studies that China Seas also experienced the recent global warming hiatus. But during this recent global warming hiatus, there was a notable asymmetric pattern of greater cooling trends in cold SSTs as compared to the hot SSTs in this region. During 1998–2013, the cold days (CDs) frequency increased significantly by 13 days per decade and cold SST extremes which were below the 10th percentile of each year (SST_10p) notably decreased by 0.4 °C per decade. Hot days (HD) and hot SST extremes which were above the 90th percentile of each year (SST_90p) slowed down, but without any distinct tendency. Meanwhile, the rates of SST_10p and CDs were highly heterogeneous in space. Cold extremes in the near-shore areas are much more sensitive to the global warming hiatus than these in the eastern of the Kuroshio Current. Importantly, hot extremes do not reveal any distinct cooling tendency during 1998–2013, there were more frequent hot days and more intense hot SSTs in this region comparing with 1982–1997. These hot extremes could push some marine organisms, fisheries and ecosystems beyond the limits of their resilience, with cascading impacts on economies and societies.

To estimate the changes in the annual mean sea level (MSL) and extreme sea levels (ESLs), the largest collection of tide gauge records from 10 tidal stations along the northern coast of the South China Sea (SCS) were analyzed in this study. Here, all the tide gauge records had been homogenized by a two-step process involving the detection of inhomogeneities, that is, breakpoints caused by non-climatic changes and the application of the adjustment. The study’s conclusions, based on the homogenized tide gauge records, can be summarized as follows: The instrument change and station relocation are the main causes for the identified inhomogeneities. From 1989 to 2018, the sea level along the SCS was at an average rate of 4.0 mm per year, as measured by the homogenized tide gauges. The ESLs from the nine tidal stations rose notably with interannual fluctuations, except for the XSA station. Additionally, the ESLs exhibited substantial decadal variations. The ESLs rose along the northern coast of the SCS and were accelerated at most stations throughout the whole study period, especially after the 1980s. There were significant positive correlations between the ESL and the annual MSL at most tide gauges. The MSL’s changes, especially long-term changes, play an important role in the change in ESLs.