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Abstract The diurnal cycle of precipitation plays a crucial role in regulating Earth's water cycle, energy balance, and regional climate patterns. However, the diurnal precipitation across mainland Southeast Asia (MSEA) and the factors influencing its spatial variations are not fully understood. In this study, we investigated diurnal precipitation patterns in summertime (June–August) from 2002 to 2005 over MSEA using ground‐based observations, satellite products, the global ERA5 reanalysis, and high‐resolution simulations from the Weather Research and Forecasting (WRF) Model at 9‐ and 3‐km grid spacing forced by ERA5 hourly data on ∼0.25° grids. Various observation‐based data sets including GHCN‐Daily, Multi‐Source Weighted‐Ensemble Precipitation (MSWEP), Asian Precipitation ‐ Highly‐Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), and Integrated Multi‐satellite Retrievals for Global Precipitation Measurement (IMERG) were used. In evaluating daily precipitation over MSEA, MSWEP, and APHRODITE data sets show similar patterns in precipitation amount, frequency, and intensity, while IMERG tends to produce higher amounts but with less frequency. ERA5 overestimates light precipitation compared to the other data sets. The WRF simulations generally produce heavier but less frequent light precipitation, with the 3‐km simulation producing less intense precipitation than the 9‐km simulation. A k‐means classification of IMERG data revealed five distinct spatial regimes with varying diurnal precipitation cycles. The WRF simulations closely match these regimes, capturing key diurnal cycles missed by ERA5 over mountainous regions and coastlines. Additionally, convective activities and near‐surface winds influence these cycles, with WRF simulations better representing coastal and mountain precipitation patterns than ERA5. High‐resolution WRF simulations, especially the 3‐km simulation, capture diurnal precipitation more accurately than ERA5, highlighting the importance of employing convection‐permitting models to simulate precipitation diurnal cycles over complex terrain. 

Abstract 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. 

Abstract On 8 April 2024, a rare total solar eclipse (TSE) passed over western New York State (NYS), the first since 1925 and the last one until 2079. The NYS Mesonet (NYSM) consisting of 126 weather stations with 55 on the totality path provides unprecedented surface, profile, and flux data and camera images during the TSE. Here we use NYSM observations to characterize the TSE's impacts at the surface, in the planetary boundary layer (PBL), and on surface fluxes and CO₂concentrations. The TSE‐induced peak surface cooling occurs 17 min after the totality and is 2.8°C on average with a maximum of 6.8°C. It results in night‐like surface inversion, calm winds, and reduced vertical motion and mixing, leading to the shallowing of the PBL and its moistening. Surface sensible, latent and ground heat fluxes all decrease whereas near‐surface CO₂concentration rises as photosynthesis slows down. 

Abstract 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. 

Abstract The Atlantic multidecadal variability (AMV) and Pacific multidecadal variability (PMV) can influence Arctic sea ice and modulate its trend, but to what extent the AMV and PMV can affect Arctic sea ice and which processes are dominant are not well understood. Here, we analyze the Community Earth System Model, version 1, idealized and time-varying pacemaker ensemble simulations to investigate these issues. These experiments show that the sea ice concentration varies mainly over the marginal Arctic Ocean, while the sea ice thickness variations occur over the entire Arctic Ocean. The internal components of AMV and PMV can enhance or weaken the decadal sea ice loss rates over the marginal Arctic Ocean by more than 50%. The AMV- or PMV-induced anomalous atmospheric energy transport and downward longwave radiation related to low clouds (thermodynamical processes) and sea ice motion (dynamical processes) contribute to the Arctic surface air temperature and sea ice concentration and thickness changes. Anomalous oceanic heat flux is mainly a response to rather than a cause of sea ice variations. The dynamic processes contribute to the winter Arctic sea ice variations as much as the thermodynamic processes, but they contribute less (more) to the summer Arctic sea ice variability than the thermodynamic processes over the marginal Arctic Ocean (parts of the central Arctic Ocean). Sea ice loss enhances air–sea heat fluxes, which cause oceanic heat convergence and warm near-surface air and the lower troposphere, which in turn melt more sea ice. 

Abstract 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. 

Abstract 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. Significance StatementSea ice loss has been shown to be a primary contributor to Arctic warming. Despite the evidence linking large sea ice retreat to Arctic warming, some studies have suggested that enhanced downwelling longwave radiation associated with increased clouds and water vapor is the primary reason for Arctic amplification. However, it is unclear how sea ice loss is linked to changes in clouds and water vapor in the Arctic. Here, we investigate the relationship between Arctic sea ice loss and changes in clouds using the ERA5 dataset. Improved knowledge of the relationship between Arctic sea ice loss and changes in clouds will help further our understanding of the role of the cloud feedback in Arctic warming. 

Abstract 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. 

Abstract 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. 

Abstract 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.