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Drylands are highly vulnerable to climate change due to their fragile ecosystems and limited ability to adapt. In contrast to the global drying after tropical volcanic eruptions shown previously, we demonstrate that large tropical volcanic eruptions can induce significant two-year hydroclimatic wetting over drylands by employing the last millennium simulations. During this wetting period, which extends from the first to the third boreal winter after the eruption, several hydroclimatic indicators, such as self-calibrating Palmer Drought Severity Index based on the Penman-Monteith equation for potential evapotranspiration (scPDSIpm), standard precipitation evapotranspiration index (SPEI), aridity index (AI), top-10cm soil moisture (SM_10cm), and leaf area index (LAI), show significant positive anomalies over most drylands. The primary contribution to the wetting response is the potential evapotranspiration (PET) reduction resulting from dryland surface cooling and reduced solar radiation, as well as a weak contribution from increased precipitation. The latter is due to the wind convergence into drylands caused by slower tropical cooling compared to drylands. The wetting response of drylands to volcanic eruptions also demonstrates some benefits over the global hydrological slowdown resulting from stratospheric aerosol injection, which replicates the cooling effects of volcanic eruptions to address global warming.

Multidecadal sea surface temperature (SST) variations in the tropical western Pacific (TWP) have been attributed to nonlinear external forcing and remote influences from the Atlantic Multidecadal Variability (AMV). However, the AMV resulted from both internal variability (IV) and external forcing. Thus, the origins of the TWP SST variations are not well understood. By analyzing observations and model simulations, we show that more than half of the decadal to multidecadal SST variations in TWP during 1920–2020 resulted from external forcing with the forced component correlated with AMV, while the internal component is unrelated to AMV. Furthermore, about 43%–49% of the forced AMV‐like SST variations in TWP result from remote influences of the forced AMV in the Atlantic via atmospheric teleconnection over the North Pacific, with the rest from other remote or local processes.

Arctic warming has significant environmental and social impacts. Arctic long‐term warming trend is modulated by decadal‐to‐multidecadal variations. Improved understanding of how different external forcings and internal variability affect Arctic surface air temperature (SAT) is crucial for explaining and predicting Arctic climate changes. We analyze multiple observational data sets and large ensembles of climate model simulations to quantify the contributions of specific external forcings and various modes of internal variability to Arctic SAT changes during 1900–2021. We find that the long‐term trend and total variance in Arctic‐mean SAT since 1900 are largely forced responses, including warming due to greenhouse gases and natural forcings and cooling due to anthropogenic aerosols. In contrast, internal variability dominates the early 20th century Arctic warming and mid‐20th century Arctic cooling. Internal variability also explains ∼40% of the recent Arctic warming from 1979 to 2021. Unforced changes in Arctic SAT are largely attributed to two leading modes. The first is pan‐Arctic warming with stronger loading over the Eurasian sector, accounting for 70% of the unforced variance and closely related to the positive phase of the unforced Atlantic Multidecadal Oscillation (AMO). The second mode exhibits relatively weak warming averaged over the entire Arctic with warming over the North American‐Pacific sector and cooling over the Atlantic sector, explaining 10% of the unforced variance and likely caused by the positive phase of the unforced Interdecadal Pacific Oscillation (IPO). The AMO‐related changes dominate the unforced Arctic warming since 1979, while the IPO‐related changes contribute to the decadal SAT changes over the North American‐Pacific Arctic.

The dynamic and thermodynamic mechanisms that link retreating sea ice to increased Arctic cloud amount and cloud water content are unclear. Using the fifth generation of the ECMWF Reanalysis (ERA5), the long-term changes between years 1950–79 and 1990–2019 in Arctic clouds are estimated along with their relationship to sea ice loss. A comparison of ERA5 to CERES satellite cloud fractions reveals that ERA5 simulates the seasonal cycle, variations, and changes of cloud fraction well over water surfaces during 2001–20. This suggests that ERA5 may reliably represent the cloud response to sea ice loss because melting sea ice exposes more water surfaces in the Arctic. Increases in ERA5 Arctic cloud fraction and water content are largest during October–March from ∼950 to 700 hPa over areas with significant (≥15%) sea ice loss. Further, regions with significant sea ice loss experience higher convective available potential energy (∼2–2.75 J kg⁻¹), planetary boundary layer height (∼120–200 m), and near-surface specific humidity (∼0.25–0.40 g kg⁻¹) and a greater reduction of the lower-tropospheric temperature inversion (∼3°–4°C) than regions with small (<15%) sea ice loss in autumn and winter. Areas with significant sea ice loss also show strengthened upward motion between 1000 and 700 hPa, enhanced horizontal convergence (divergence) of air, and decreased (increased) relative humidity from 1000 to 950 hPa (950–700 hPa) during the cold season. Analyses of moisture divergence, evaporation minus precipitation, and meridional moisture flux fields suggest that increased local surface water fluxes, rather than atmospheric motions, provide a key source of moisture for increased Arctic clouds over newly exposed water surfaces during October–March.

Atmospheric instability affects the formation of convective storms, but how it has changed during recent decades is unknown. Here we analyze the occurrence frequency of stable and unstable atmospheric conditions over land using homogenized radiosonde data from 1979 to 2020. We show that atmospheric stable (unstable) conditions have decreased (increased) significantly by ∼8%–32% (of time) from 1979 to 2020 over most land areas. In boreal summer, the mean positive buoyancy (i.e., convective available potential energy [CAPE]) also increases over East Asia while mean negative buoyancy (i.e., convective inhibition [CIN]) strengthens over Europe and North America from midnight‐dawn for unstable cases. The increased unstable cases and mean CAPE result from increased low‐level specific humidity and air temperature, which increase the buoyancy of a lifted parcel. The stronger CIN results from decreased near‐surface relatively humidity and decreased lapse rate in the lower troposphere. Our results suggest that the atmosphere has become increasingly unstable, which could lead to more convective storms.

Recent satellite and in-situ measurements show that forests can influence regional and global cloud cover through biophysical processes. However, forest’s possible local and non-local impacts on clouds remain unclear. By analyzing the model simulations from the Coupled Model Intercomparison Project Phase 6, here we show that deforestation-induced cloud cover changes have a strong latitudinal dependence, with decreased cloudiness in the tropics but increased cloudiness in the temperate and boreal regions. We further disentangle the local and non-local effects in influencing the cloudiness changes in model simulations. Results show that deforestation leads to a local cloud reduction in the tropics and a non-local cloud enhancement in the temperate and boreal regions. We demonstrate that the relationship between changes in cloud cover and deforestation would be misinterpreted without considering the non-local signals. Furthermore, our modeling results are inconsistent with recent observational studies, with enhanced clouds in model simulations but reduced clouds in observations in the temperate and boreal regions. Further efforts to explore the non-local effect and to reduce the model uncertainty could help advance our understanding of the biophysical effects of deforestation.

Summer heatwaves over Europe, which can cause many deaths and severe damage, have become increasingly frequent over central and eastern Europe and western Russia in recent decades. In this paper, we estimate the contributions of the warming due to increased greenhouse gases (GHG) and nonlinear variations correlated with the Atlantic Multidecadal Oscillation (AMO) to the observed heatwave trend over Europe during 1980–2021, when the GHG‐induced warming over Europe exhibits a linear trend. It is found that GHG‐induced warming contributes to ∼57% of the European heatwave trend over 1980–2021, while the cold‐to‐warm phase shift of the AMO‐like variations accounts for ∼43% of the trend via the intensification of midlatitude North Atlantic jet. The recent trend of heatwaves over western and northern Europe is mainly due to GHG‐induced warming, while that over central and eastern Europe and western Russia is primarily related to the combined effect of the AMO‐like variations and GHG‐induced warming. To some extent, GHG‐induced warming is an amplifier of the increasing trend of recent AMO‐related European heatwaves. Moreover, European blocking (Ural blocking, UB) is shown to contribute to 55% (42%) of the AMO‐related heatwave trend via the influence of midlatitude North Atlantic jet. In the presence of a strong North Atlantic jet during the recent warm AMO phase, UB events concurrent with positive‐phase North Atlantic Oscillation can cause intense, persistent and widespread heatwaves over Europe such as that observed in the summer of 2022.

The 2022 heatwave in China featured record‐shattering high temperatures, raising questions about its origin and possible link to global warming. Here we show that the maximum temperature anomalies over Central China reached 13.1°C in the summer of 2022, which is ∼4.2σ above the 1981–2010 mean with a return period of tens of thousands of years. Our results suggested that the persistent high‐pressure anomaly and associated extreme heatwave likely resulted mainly from internal variability, although anthropogenic warming has increased the probability of such extreme heatwaves. We also estimate that the 2022‐like heatwave becomes six to seven times more likely under persistent high‐pressure conditions when compared to stochastic circulation states. Due to a shift toward warmer mean temperatures and a flattening of the probability distribution function, such rare extreme heatwaves are projected to become much more common at a global warming level of 4°C, occurring once about every 8.5 years.

Radiative climate feedbacks in the Arctic have been extensively studied, but their spatial and seasonal variations have not been thoroughly examined. Using ERA5 reanalysis data, we examine seasonal variations in Arctic climate feedbacks and their relationship to sea‐ice loss based on changes from 1950–1979 to 1990–2019. The spring and summer seasons experienced large sea‐ice loss, strong surface albedo feedback, and large oceanic heat uptake. Arctic clouds exerted small net cooling in May‐June‐July but moderate warming during the cold season, especially over areas with large sea‐ice loss where cloud liquid and ice water content increased. Arctic water vapor feedback peaked in summer but was weak and uncorrelated with sea‐ice loss. Arctic positive lapse rate feedback (LRF) was strongest in winter over areas with large sea‐ice loss and weak inversion but uncorrelated with atmospheric stability, suggesting that oceanic heating from sea‐ice loss led to enhanced surface warming and the positive LRF.

Winter surface air temperature (Tas) over the Barents–Kara Seas (BKS) and other Arctic regions has experienced rapid warming since the late 1990s that has been linked to the concurring cooling over Eurasia, and these multidecadal trends are attributed partly to internal variability. However, how such variability is generated is unclear. Through analyses of observations and model simulations, we show that sea ice–air two-way interactions amplify multidecadal variability in sea-ice cover, sea surface temperatures (SST) and Tas from the North Atlantic to BKS, and the Atlantic Meridional Overturning Circulation (AMOC) mainly through variations in surface fluxes. When sea ice is fixed in flux calculations, multidecadal variations are reduced substantially (by 20–50%) not only in Arctic Tas, but also in North Atlantic SST and AMOC. The results suggest that sea ice–air interactions are crucial for multidecadal climate variability in both the Arctic and North Atlantic, similar to air-sea interactions for tropical climate.