Spatio-temporal variations in global surface soil moisture based on multiple datasets: intercomparison and climate drivers

Accurate soil moisture datasets are essential to understand the impacts of climate change. However, few studies have evaluated the consistency and drivers of long-term trends in soil moisture among different dataset types (satellite, assimilation, reanalysis, and climate model) at the global scale. Here we analyze the spatio-temporal variations of global surface soil moisture and associated climate dynamics over 1980–2020 using multiple soil moisture datasets, i.e., multi-satellite assimilated remote sensing datasets (ESA CCI), simulated soil moisture based on LSMs (GLDAS, GLEAM, CMIP6), and reanalysis (ECMWF ERA5, MERRA2, CRA-Land). Most of these datasets indicate pervasive drying of global surface soil moisture over the last four decades. Prominent soil moisture drying is detected in North America, Europe, northeastern Asia, North Africa, and the Arabian Peninsula. The cross-correlations among the five synthetic soil moisture datasets are the highest between GLEAM and the reanalysis datasets. Using the Aridity Index (AI, the ratio between annual total precipitation and potential evapotranspiration), we find that soil moisture drying is the most intensive in the humid-arid transitional regions with AI ranging 0.8–1.2. Surface soil moisture drying is primarily driven by increases in temperature, followed by ENSO, as indicated by Maximum Covariance Analysis (MCA). However, the significance of the impact of ENSO on soil moisture variability is sensitive to the choice of soil moisture dataset used in the MCA

Contribution of anthropogenic activities to the intensification of heat index-based spatiotemporally contiguous heatwave events in China

In this study, we identified heat index (HI)-based spatiotemporally contiguous heatwaves (HI-STHWs) in China based on meteorological observations and CMIP6 global climate model simulations. We analyzed the spatiotemporal patterns of changes in HI-STHWs in the past and future and quantitatively attributed these changes to anthropogenic activities. The results show that the duration, severity, average, maximum, and total impacted area of the annual strongest HI-STHWs during the present period of 1991–2014 are 1.77, 2.0, 1.05, 1.14, and 1.89 times the historical period of 1961–1990, respectively. In the fingerprint results, the anthropogenic greenhouse gases (GHG) signal is significantly detected, while the aerosol (AER) and natural (NAT) signals are not. GHG is the primary factor driving the intensification of HI-STHWs, which alone explains about 130%, 122%, 112%, 111%, and 114% of the above changes. The reason for GHG contribution exceeding 100% is that AER might have a negative contribution although nonsignificant. In the future warming climate, anthropogenic activities are projected to lead to more unprecedented HI-STHWs. Under the high emissions scenario of SSP585, by 2100, the annual strongest HI-STHW in China is projected to last almost the whole year and influence 96% regions of China in the most serious day. Meanwhile, its duration and total impacted area are 24.5 [17.2, 31.6] (90% confidence interval) and 107.2 [70, 129.9] times the preindustrial period. However, if the warming level could be limited to 2/1.5 °C, those values would be 3.4/5.4 and 8.2/16.2 times smaller than that under the SSP585 scenario by 2100

Phase shifts of the PDO and AMO alter the translation distance of global tropical cyclones

Recent decadal changes in tropical cyclone (TC) frequency since the mid-1990s have been widely reported; however, it is unclear whether there have also been any changes in TC translation distance. Here, we show that long-term decrease in global TC translation distance during 1975–2020 is caused by an abrupt change point around the year 1997. This change point marks a switch between an increasing translation distance during 1975–1997 and decreasing translation distance during 1998–2020. The shift in TC translation distance is attributed to changes in the distance between the location of TC genesis and land, and the percentage of landfalling TCs to all TCs, which is driven by the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) phase switch in the mid-1990s. In the last 20 years, the cool, La Niña-like sea surface temperatures (SST) during the PDO negative phase and the warm SST pattern during the AMO positive phase have enhanced the genesis potential index and the potential intensity in offshore areas, resulting in greater TC genesis landward. Phase shifts of PDO and AMO modulate environmental conditions, regulating TC genesis location and landfall frequency, and their combined effects on the translation distance of Pacific TCs. The warm SST anomalies during the AMO positive phase enhance these circulation patterns in two possible ways: via the Indian Ocean and the subtropical eastern Pacific relaying effects at a multidecadal timescale. Our findings suggest that the PDO and AMO act as key pacemakers for decadal changes in global TC translation distance

Heavier precipitation in response to longer-lasting tropical cyclones and rapid urbanization over the Yangtze River Delta of eastern China

Precipitation induced by tropical cyclones (TCs) over cities is associated with both TC duration and urbanization; however, observational evidence of the impacts of TC duration and urbanization on precipitation in megalopolises is limited. In this study, the Yangtze River Delta (YRD) of eastern China is taken as a typical region because this region has been experiencing both rapid urbanization processes and frequent TC attacks. During 1979–2018, we find reduced translation speed and increased meandering of TCs over the YRD, resulting in increased TC duration and the proportion of TC stalling in this region. The correlation between TC duration and TC-induced precipitation amount is significant across the YRD region but is relatively weak in areas with faster urbanization expansion rates. Long-term increases in TC-induced precipitation are found in both rural and urban areas but are larger for urban areas. Urbanization plays an important role in enhancing TC-induced precipitation over urban areas of the YRD region. Areas with faster urbanization expansion rates and longer TC durations have larger TC-induced precipitation, suggesting that urban expansion and TC duration jointly amplify TC-induced precipitation. Our findings suggest that urban planners, in areas potentially affected by TCs, should consider adaptation measures to mitigate the impacts of urban rainstorms amplified by the combined effects of TCs and urbanization

Increase in ocean-onto-land droughts and their drivers under anthropogenic climate change

Ocean-onto-land droughts (OTLDs)—i.e., droughts originating over the oceans and migrating onto land—are a recently identified phenomenon with severe natural and human impacts. However, the influence of anthropogenic emissions on past and future changes in OTLDs and their underlying mechanisms remain unclear. Here, using precipitation-minus-evaporation deficits to identify global OTLDs, we find OTLDs have intensified due to anthropogenic climate change during the past 60 years. Under a future high-emissions scenario, the OTLDs would become more frequent (+39.68%), persistent (+54.25%), widespread (+448.92%), and severe (+612.78%) globally. Intensified OTLDs are associated with reduced moisture transport driven by subtropical anticyclones in the northern hemisphere and complex circulation patterns in the southern hemisphere. The reduction in moisture transport during OTLDs is mainly caused by the atmospheric thermodynamic responses to human-induced global warming. Our results underscore the importance of improving understanding of this type of drought and adopting climate mitigation measures

Human-induced intensification of terrestrial water cycle in dry regions of the globe

Anthropogenic climate change (ACC) strengthens the global terrestrial water cycle (TWC) through increases in annual total precipitation (PRCPTOT) over global land. While the increase in the average global terrestrial PRCPTOT has been attributed to ACC, it is unclear whether this is equally true in dry and wet regions, given the difference in PRCPTOT changes between the two climatic regions. Here, we show the increase in PRCPTOT in dry regions is twice as fast as in wet regions of the globe during 1961–2018 in both observations and simulations. This faster increase is projected to grow with future warming, with an intensified human-induced TWC in the driest regions of the globe. We show this phenomenon can be explained by the faster warming and precipitation response rates as well as the stronger moisture transport in dry regions under ACC. Quantitative detection and attribution results show that the global increase in PRCPTOT can no longer be attributed to ACC if dry regions are excluded. From 1961–2018, the observed PRCPTOT increased by 5.63%~7.39% (2.44%~2.80%) over dry (wet) regions, and as much as 89% (as little as 5%) can be attributed to ACC. The faster ACC-induced TWC in dry regions is likely to have both beneficial and detrimental effects on dry regions of the globe, simultaneously alleviating water scarcity while increasing the risk of major flooding

Machine learning-constrained projection of bivariate hydrological drought magnitudes and socioeconomic risks over China

Climate change influences the water cycle and alters the spatiotemporal distribution of hydrological variables, thus complicating the projection of future streamflow and hydrological droughts. Although machine learning is increasingly employed for hydrological simulations, few studies have used it to project hydrological droughts, not to mention bivariate risks (referring to drought duration and severity) as well as their socioeconomic effects under climate change. We developed a cascade modeling chain to project future bivariate hydrological drought characteristics in 179 catchments over China, using five bias-corrected global climate model (GCM) outputs under three shared socioeconomic pathways (SSPs), five hydrological models, and a deep-learning model. We quantified the contribution of various meteorological variables to daily streamflow by using a random forest model, and then we employed terrestrial water storage anomalies and a standardized runoff index to evaluate recent changes in hydrological drought. Subsequently, we constructed a bivariate framework to jointly model drought duration and severity by using copula functions and the most likely realization method. Finally, we used this framework to project future risks of hydrological droughts as well as the associated exposure of gross domestic product (GDP) and population. Results showed that our hybrid hydrological–deep-learning model achieved > 0.8 Kling–Gupta efficiency in 161 out of the 179 catchments. By the late 21st century, bivariate drought risk is projected to double over 60 % of the catchments mainly located in southwestern China under SSP5-85, which shows the increase in drought duration and severity. Our hybrid model also projected substantial GDP and population exposure by increasing bivariate drought risks, suggesting an urgent need to design climate mitigation strategies for a sustainable development pathway

Amplification of coupled hot-dry extremes over eastern monsoon China

High air temperatures and low atmospheric humidity can result in severe disasters such as flash droughts in regions characterized by high humidity (monsoon regions). However, it remains unclear whether responses of hot extremes to warming temperature are amplified on dry days as well as the response of dry extremes on hot days. Here, taking eastern monsoon China (EMC) as a typical monsoon region, we find a faster increase in air temperature on drier summer days, and a faster decrease in atmospheric humidity on hotter days, indicating “hotter days get drier” and “drier days get hotter” (i.e., coupling hotter and drier extremes), especially in southern EMC. The southern EMC is also a hotspot where the coupling hot-dry extremes has become significantly stronger during the past six decades. The stronger hot-dry coupling in southern EMC is associated with anomalies in large-scale circulations, such as reduced total cloud cover, abnormal anticyclones in the upper atmosphere, intense descending motion, and strong moisture divergence over this region. Land-atmosphere feedback enhance the hot-dry coupling in southern EMC by increasing land surface dryness (seen as a decrease in the evaporation fraction). The decreasing evaporation fraction is associated with drying surface soil moisture, controlled by decreases in pre-summer 1-m soil moisture and summer-mean precipitation. Given hot extremes are projected to increase and atmospheric humidity is predicted to decrease in the future, it is very likely that increasing hot-dry days and associated disasters will be witnessed in monsoon regions, which should be mitigated against by adopting adaptive measures

Slower-decaying tropical cyclones produce heavier precipitation over China

The post-landfall decay of tropical cyclones (TC) is often closely linked to the magnitude of damage to the environment, properties, and the loss of human lives. Despite growing interest in how climate change affects TC decay, data uncertainties still prevent a consensus on changes in TC decay rates and related precipitation. Here, after strict data-quality control, we show that the rate of decay of TCs after making landfall in China has significantly slowed down by 45% from 1967 to 2018. We find that, except the warmer sea surface temperature, the eastward shift of TC landfall locations also contributes to the slowdown of TC decay over China. That is TCs making landfall in eastern mainland China (EC) decay slower than that in southern mainland China (SC), and the eastward shift of TCs landfall locations causes more TCs landfalling in EC with slower decay rate. TCs making landfall in EC last longer at sea, carry more moisture upon landfall, and have more favorable dynamic and thermodynamic conditions sustaining them after landfall. Observational evidence shows that the decay of TC-induced precipitation amount and intensity within 48 h of landfall is positively related to the decay rate of landfalling TCs. The significant increase in TC-induced precipitation over the long term, due to the slower decay of landfalling TCs, increases flood risks in China’s coastal areas. Our results highlight evidence of a slowdown in TC decay rates at the regional scale. These findings provide scientific support for the need for better flood management and adaptation strategies in coastal areas under the threat of greater TC-induced precipitation