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.

Based on the 30-year global hourly sea surface temperature (SST) dataset (MLSST) produced by the National Marine Environmental Forecasting Center, Ministry of Natural Resources of China, we analyzed the variability of diurnal sea surface temperature amplitude (DSST) of the tropical Indian Ocean at multiple time scales, as well as its influencing factors. The results show that the DSST in the Arabian Sea, Bay of Bengal, and equatorial Indian Ocean exhibits a bimodal seasonal variation with a semi-annual cycle, while the DSST in the southern Indian Ocean shows an annual cycle. The seasonal variation of DSST is mainly influenced by factors such as sea surface wind speed, shortwave solar radiation, and precipitation. The DSST in the equatorial Indian Ocean is generally higher during El Niño years compared to La Niña years. At the intraseasonal scale, the large standard deviation of DSST in boreal winter is mainly distributed in the southern hemisphere, while the large standard deviation of DSST in boreal summer shifts northward. The intraseasonal variation amplitude of DSST in boreal winter of the tropical Indian Ocean is greater than that in boreal summer. The DSST in the tropical Indian Ocean exhibits significant variation characteristics at multi-time scales. This study provides reference for numerical simulation of air-sea interaction patterns in the tropical Indian Ocean, as well as improvement of short-term climate prediction.

The El Niño-Southern Oscillation (ENSO) has a significant impact on the global climate through atmospheric teleconnections. It is important to understand the stability of ENSO teleconnections, not only for future weather forecasting and climate projection, but also for ENSO reconstructions based on paleo-proxies. In this study, we investigate the decadal variations of ENSO teleconnections in global land surface temperature (LST) from 850 to 2005 AD using 13 ensemble members of the Community Earth System Model-Last Millennium Ensemble (CESM-LME). The CESM can simulate the main Eurasian cooling and Arctic warming, known as the warm Arctic-cold Eurasia (WACE) pattern, during the boreal winter of an El Niño. Furthermore, it can also capture the western Antarctic warming during the developing and decaying summers of an El Niño. There is a dominant decadal variation in the ENSO-LST teleconnections, expressed as anomalous LST patterns that closely resemble those seen in the WACE pattern during boreal winter and the western Antarctic warming pattern during summer. This decadal variation of ENSO-LST teleconnections is primarily due to the varying positions of Rossby wave sources associated with distinct ENSO patterns, which are located either to the west or to the east of Hawaii. The LST response to ENSO over South Siberia, as well as the associated precipitation response over North Eurasia, even show opposite patterns at different phases of the decadal variation. The decadal variation in CESM is found to be related to the interdecadal Pacific oscillation (IPO) and is likely attributed to internal variability rather than external forcing. Our findings suggest that the decadal variation in ENSO teleconnections should be considered when using proxies from Eurasian regions to reconstruct ENSO variability.