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Extreme rainfall events are becoming increasingly severe under a warming climate. North China has experienced several catastrophic rainfall events, of which the rainstorm in 2023 was particularly severe inducing unprecedented damage. Since 1980, the neighboring Mongolian Plateau (MP) has been warming at a rate three times the global average, faster than the surrounding regions. Whether a link exists between extreme rainfall in North China and the fast MP warming is unknown. Here, using global variable‐resolution atmospheric model with convection‐permitting capability over North China, we find the rapid warming trends, particularly over the MP, are highly conducive to extreme rainfall over North China. In the 2023 case, the fast MP warming induced an anomalous terrestrial high, which in the Western North Pacific Subtropical High created a strong high‐pressure system over North China. This system obstructed northeastward movement of Typhoon Doksuri, concentrating moisture supply which prolonged and intensified the extreme. Plain Language Summary The devastating “23.7” rainstorm that struck North China in 2023 broke multiple rainfall records and caused unprecedented damage. Using an advanced atmospheric model, we discover that unusually rapid warming over the Mongolian Plateau—a region warming three times faster than the global average—played a crucial role in making this rainstorm so extreme. The intense warming induced a strong and unusual high‐pressure system that, when combined with the Western North Pacific Subtropical High, acted like a barrier. This barrier trapped the northeastward movement of Typhoon Doksuri over North China, leading to concentrated and prolonged extreme rainfall. Our findings reveal a surprising connection: rapid warming in one region can trigger extreme rainfall events in distant areas through its effects on atmospheric circulation. This discovery has important implications for predicting and preparing for future extreme events as different regions continue to warm at different rates under climate change. The study also demonstrates why we need to look at weather extremes from a global perspective rather than focusing only on local conditions. Key Points Mongolian Plateau warming intensified an extreme rainstorm over North China, as demonstrated by global variable‐resolution forecast Anomalous high‐pressure system induced by fast warming created a barrier, obstructing typhoon northward and prolonging rainfall The rapid warming disrupted the balance, concentrating the rainstorm within a smaller region and resulting in record‐breaking rainfall

Key questions remain about the atmospheric response to variability in the oceanic western boundary currents (WBCs). Here we exploit a unique high‐resolution slab‐ocean coupled climate model to investigate how ocean heat transport (OHT) anomalies in the major WBCs of both hemispheres affect the atmospheric circulation. Prescribed OHT anomalies lead to robust changes in convective precipitation anomalies equatorward of the maximum surface warming. The response is deepest and most pronounced over the Northern Hemisphere (NH) WBCs, where it is associated with significant changes in upper tropospheric vertical motion, condensational heating and geopotential heights. The response is relatively shallow over the Southern Hemisphere (SH) WBCs. The findings reveal the robustness of the atmospheric response to OHT anomalies and highlight key hemispheric differences: in the NH, OHT anomalies are balanced by deep atmospheric vertical motion; in the SH, they are balanced primarily by shallow horizontal temperature advection. Plain Language Summary We study how ocean heat transport (OHT) influences the atmospheric circulation in the major western boundary currents (WBCs) of both hemispheres, including the Gulf Stream, Kuroshio‐Oyashio Extension, Brazil‐Malvinas Confluence, and Agulhas Currents. We find that the heating due to anomalous ocean heat transport causes air to rise on the equatorward side of the largest surface heating in all WBC regions. The regions of rising air are also associated with more intense convective precipitation. The effect is strongest in the Northern Hemisphere (NH) where the atmospheric response extends to the upper troposphere, leading to significant heating and atmospheric circulation anomalies aloft. The findings highlight the robustness of the atmospheric response to ocean dynamical processes in the western boundary currents, although differences in the hemispheric responses are noteworthy. In the NH WBCs, the atmospheric response to OHT anomalies is balanced primarily through vertical air movement, whereas in the Southern Hemisphere, the response is balanced primarily by low‐level horizontal temperature advection. Key Points The atmospheric response to ocean heat transport (OHT) anomalies in the western boundary currents (WBC) is examined Anomalous OHT drives robust changes in the atmospheric circulation and convective precipitation over the WBCs of both hemispheres The Northern Hemisphere responses extend to the upper troposphere; the Southern Hemisphere responses are limited to the lower troposphere

Mesoscale sea surface temperature (SST) variability influences the marine atmosphere boundary layer (MABL), affecting near‐surface winds and turbulent heat fluxes. This study examines precipitation response to mesoscale SST forcing using satellite observations, ERA5 reanalysis, and high‐ and low‐resolution climate models. The results show that high‐resolution models produce a precipitation response to mesoscale SST consistent with satellite observations and ERA5. However, partitioning ERA5 and model precipitation into resolved and parameterized convective components reveals that even in high‐resolution models, the simulated mesoscale SST‐precipitation relationship is shaped by the characteristics of convective parameterization. Further, the precipitation response to SST is strongly dependent on the background SST and SST variability in coupled models. Further analysis of ERA5 and high‐resolution simulations shows a vertical velocity response extending to 500 hPa. However, the reliance on convective parameterizations introduces uncertainties about whether high‐resolution models accurately capture these effects.

This study focuses on projecting future changes in mean and extreme precipitation in Asia, and discusses their uncertainties. Time‐slice experiments using a 20‐km‐mesh atmospheric general circulation (AGCM) were performed both in the present‐day (1979–2003) and the future (2075–2099). To assess the uncertainty of the projections, 12 ensemble projections (i.e., combination of 3 different cumulus schemes and 4 different sea surface temperature (SST) change patterns) were conducted using 60‐km‐mesh AGCMs. For the present‐day simulations, the models successfully reproduced the pattern and amount of mean and extreme precipitation, although the model with the Arakawa–Schubert (AS) cumulus scheme underestimated the amount of extreme precipitation. For the future climate simulations, in South Asia and Southeast Asia, mean and extreme precipitation generally increase, but their changes show marked differences among the projections, suggesting some uncertainty in their changes over these regions. In East Asia, northwestern China and Bangladesh, in contrast, mean and extreme precipitation show consistent increases among the projections, suggesting their increases are reliable for this model framework. Further investigation by analysis of variance (ANOVA) revealed that the uncertainty in the precipitation changes in South Asia and Southeast Asia are derived mainly from differences in the cumulus schemes, with an exception in the Maritime Continent where the uncertainty originates mainly from the differences in the SST pattern. Key Points Precipitation increases consistently in East Asia and Bangladesh Precipitation changes in South Asia and Southeast Asia have large uncertainty The uncertainty comes from variation of cumulus schemes rather than SST patterns

Convective available potential energy (CAPE), a metric associated with severe weather, is expected to increase with warming, but we have lacked a framework that describes its changes in the populated midlatitudes. In the tropics, theory suggests mean CAPE should rise following the Clausius–Clapeyron (C–C) relationship at ∼6%/K. In the heterogeneous midlatitudes, where the mean change is less relevant, we show that CAPE changes are larger and can be well‐described by a simple framework based on moist static energy surplus, which is robust across climate states. This effect is highly general and holds across both high‐resolution nudged regional simulations and free‐running global climate models. The simplicity of this framework means that complex distributional changes in future CAPE can be well‐captured by a simple scaling of present‐day data using only three parameters. Plain Language Summary Severe thunderstorms cause substantial damage and may become more destructive in the future. Because these events are associated with conditions of high “Convective Available Potential Energy” (CAPE), it is important to understand how CAPE might increase in a future warmer climate. However, existing theories designed for the tropics are not suitable for the U.S. and similar areas. We find that future changes in CAPE are complex and cannot be predicted based on surface temperature alone, but can be explained using three factors: temperature and moisture at the surface and temperature at a higher level. A single simple framework is therefore able to explain CAPE differences between present and future climates, warm and cold regions, and daytime and nighttime. Key Points Convective available potential energy (CAPE) shows a strong dependence on “moist static energy surplus” and this dependence holds across climate states. These results are robust across models Shifts in CAPE contours under climate change mean that hotter and/or wetter conditions are required to produce a given CAPE Distributional shifts in future midlatitudes CAPE can be well‐captured given 3 regional mean changes: surface T and RH, and upper‐level T

Functional Magnetic Resonance Imaging (fMRI) is a primary modality for studying brain activity. Modeling spatial dependence of imaging data at different spatial scales is one of the main challenges of contemporary neuroimaging, and it could allow for accurate testing for significance in neural activity. The high dimensionality of this type of data (on the order of hundreds of thousands of voxels) poses serious modeling challenges and considerable computational constraints. For the sake of feasibility, standard models typically reduce dimensionality by modeling covariance among regions of interest (ROIs)—coarser or larger spatial units—rather than among voxels. However, ignoring spatial dependence at different scales could drastically reduce our ability to detect activation patterns in the brain and hence produce misleading results. We introduce a multi-resolution spatio-temporal model and a computationally efficient methodology to estimate cognitive control related activation and whole-brain connectivity. The proposed model allows for testing voxel-specific activation while accounting for non-stationary local spatial dependence within anatomically defined ROIs, as well as regional dependence (between-ROIs). The model is used in a motor-task fMRI study to investigate brain activation and connectivity patterns aimed at identifying associations between these patterns and regaining motor functionality following a stroke.

Lightning is one of the most hazardous natural phenomena, causing significant damage to life and property. In India, lightning activity peaks during pre‐monsoon and monsoon seasons. In 2022, 36% of the deaths from natural disasters were attributed to lightning. Accurate forecasting is critical for preparedness and mitigation, but complex convection processes often lead to spatial mismatches in forecasts. Spatial verification methods offer valuable insights into the accuracy of modeling systems. This study evaluates the performance of a high‐resolution (4 km) regional model, operational at the National Centre for Medium Range Weather Forecasting (NCMRWF), that is, NCUMR (NCMRWF Regional Model), in predicting lightning strikes over India during pre‐monsoon and monsoon seasons from 2021 to 2024. The Method for Object‐Based Diagnostic Evaluation (MODE) was applied to assess the model's ability to predict lightning‐prone regions. The primary objectives of this study are (i) to analyze the performance of the NCUMR model in predicting regions affected by lightning and (ii) to determine whether MODE can be used as an effective tool for forecasting lightning‐prone areas. Results demonstrate that the NCUMR model is capable of forecasting the spatial structure and distribution of lightning events with reasonable accuracy up to 3 days in advance. On Day 1, more than 88% of lightning objects for thresholds above 5 strikes/day show boundary overlap with observations, with centroid distances for 50% of matched objects remaining below 55 km. For Day 2 lead time, 83%–85% of objects show boundary overlap. On Day 3, although displacement errors increase slightly, over 85% of objects still exhibit zero boundary distance at lower thresholds, and centroid distances remain within 1°–1.5°. For all lead times, 75% of the forecasted objects have area ratios exceeding 0.7, and complexity ratios consistently above 0.7, indicating good structural agreement. While intensity is generally under‐forecasted, 90th percentile intensity ratios exceed 0.5 in most cases. The model performs better for lower thresholds and shows improved object correspondence during the monsoon season compared to pre‐monsoon. These results confirm the utility of object‐based verification using MODE in capturing spatial aspects of lightning forecasts and highlight its potential application for real‐time impact‐based forecasting and early warning systems. This study evaluates a high‐resolution (4 km) regional model's performance in forecasting lightning over India (2021–2024) using the MODE tool. Results show reliable predictions of spatial extent, intensity, and shape, with better performance during the monsoon season. MODE effectively identifies high‐risk regions, supporting 3‐day advance impact‐based forecasts for lightning‐prone areas.

We explore long-term sea-level variability along the coast of Japan during the 20th century, using a 1/10 ∘ ocean general circulation model driven by two 20th century atmospheric reanalysis data. The modeled sea level anomalies along the coast of Japan (JPN-SLAs) show a consistent upward trend throughout the 20th century, which is comparable to global-mean sea-level rise, whereas no trend is obvious for the observed JPN-SLAs based on tide gauge data carefully selected by the Japan Meteorological Agency (JMA). We point out that the major difference between the model results and the tide gauge data may be due to the vertical land movements (VLMs) at the tide gauge stations, despite the JMA’s assumption that the VLMs are relatively small there. If this is correct, the estimates from our model combined with the barystatic component by a recent study would yield a linear trend of 1.79 [0.89 ∼ 2.28] mm yr - 1 for JPN-SLAs without VLMs from 1900 to 2010, which is close to the global average SLAs estimated in recent studies. The empirical orthogonal function (EOF) analysis shows that the first mode of the modeled JPN-SLAs is almost spatially uniform with a peak in the 1950s. The peak is created by coastal trapped waves (CTWs), which are excited when positive sea level anomalies produced by change in wind stress, propagate westward as baroclinic Rossby waves and reach Japan. From idealized experiments, we find that the first EOF mode is well reproduced by the CTWs excited east of Hokkaido.

In this study, a global variable‐resolution modeling framework of atmospheric dust and its radiative feedback is established and evaluated. In this model, atmospheric dust is simulated simultaneously with meteorological fields, and dust‐radiation interactions are included. Five configurations of global mesh with refinement at different resolutions and over different regions are used to explore the impacts of regional refinement on modeling dust lifecycle at regional and global scales. The model reasonably produces the overall magnitudes and spatial variabilities of global dust metrics such as surface mass concentration, deposition, aerosol optical depth, and radiative forcing compared to observations and previous modeling results. Two global variable‐resolution simulations with mesh refinement over major deserts of North Africa (V16 km‐NA) and East Asia (V16 km‐EA) simulate less dust emissions and smaller dry deposition rates inside the refined regions due to the weakened near‐surface wind speed caused by better resolved topographic complexity at higher resolution. The dust mass loadings over North Africa are close to each other between V16 km‐NA and the quasi‐uniform resolution (∼120 km) (U120 km), while over East Asia, V16 km‐EA simulates higher dust mass loading. Over the non‐refined areas with the same resolution, the difference between global variable‐resolution and uniform‐resolution experiments also exists, which is partly related to their difference in dynamic time‐step and the coefficient for horizontal diffusion. Refinement at convection‐permitting resolution around the Tibetan Plateau (TP) simulates less dust due to its more efficient wet scavenging from resolved convective precipitation around the TP against coarse resolution. Plain Language Summary Mineral dust plays an important role in Earth's climate system. Numerical simulation of dust and its impacts on a regional scale still has large uncertainties, partly due to the relatively coarse horizontal resolution. Limited‐area simulation at relatively high resolution can generally better characterize dust and its impacts on a regional scale; however, lateral boundary conditions may introduce some numerical issues and constrain regional feedback, such as dust‐cloud and dust‐radiation interactions, to large‐scale circulation. In this study, a novel modeling framework of atmospheric dust and its climatic feedbacks with the capability of global variable‐resolution simulation is established and evaluated. The model produces reasonable global spatial distributions of dust compared to observations and previous studies. The difference between the simulations at global quasi‐uniform resolution and global variable resolution with regional refinement over East Asia and North Africa is significant, particularly with refinement at convection‐permitting resolution. This model may be used in the future to provide new insights into the impacts of dust on regional and global climate systems. Key Points A modeling framework of atmospheric dust with the capability of global variable‐resolution simulation is introduced and evaluated Experiments with regional refinement produce less dust emissions and mass loading and smaller dry deposition due to weaker surface wind Refinement at convection‐permitting resolution simulates stronger wet scavenging and less dust mass compared to coarse resolution

This study aims to analyze the forward/reverse causal relationships between belief (risk perception), attitude (judgment), and behavior (acceptance). A traditional view stresses forward causal relationships between the three variables. However, recently, several studies have reported the possibility of reverse causal relationships between them. Based on survey data collected from 1027 Korean/Japanese participants, here we test not only the forward or reverse relationships between these three variables, but also how such causal relationships depend on the trust and country contexts (Korea and Japan in this study). The results showed that, first, not only a general forward causal relationship but also reverse causal relationship exists between belief, attitude, and behavior. Second, there exist the moderated mediation and mediated moderation effect of trust in government and media across two countries. Third, the effects of trust in government and media work significantly overall. However, the patterns of interaction effects differ between two countries. The level of trust in the government influenced the belief and attitude of citizens in Japan more than in Korea. However, the level of trust in the media showed opposite results.