The 50 most-cited articles in Geophysical Research Letters, 2023

Abstract The 2022 Compound Drought and Heatwave (CDHW) caused widespread crop damage, water shortages, and wildfires across Europe. Our study analyzed this event’s severity and return period (RP) and compared it with past mega CDHWs in Europe. The hardest‐hit areas were Iberian Peninsula, France, and Italy, where temperatures exceeded 2.5°C above normal, and severe droughts persisted from May to August. Using a Bayesian approach, we estimated the RP for the 2022 CDHW event, which was unprecedented in Northern Italy, Iberian Peninsula, and western parts of France, with RPs of 354, 420, and 280 years, respectively. The reduced soil moisture due to precipitation deficits and high temperatures contributed to the persistence and severity of drought, creating a positive feedback loop where dry soils led to even drier conditions. In light of our findings, it is evident that global warming poses increased risks of severe CDHW events, which are likely to increase.

Abstract The impacts of hot, dry, and compound hot‐dry extremes are significant for societies, economies, and ecosystems worldwide. Such events therefore need to be assessed in the light of anthropogenic climate change so that suitable adaptation measures can be implemented by governments and stakeholders. Here we show a comprehensive analysis of hot, dry, and compound hot‐dry extremes over global land regions using 25 Coupled Model Intercomparison Project Phase 6 models and four future emissions scenarios from 1950 to 2100. Hot, dry, and compound hot‐dry extremes are projected to increase over large parts of the globe by the end of the 21st century. Hot and compound hot‐dry extremes show the most widespread increases and dry extreme changes are sensitive to the index used. Many regional changes depend on the strength of greenhouse‐gas forcing, which highlights the potential to limit the changes with strong mitigation efforts.

Abstract A devastating doublet of earthquakes with moment magnitude M W 7.9 and M W 7.6 earthquakes contiguously occurred in SE Türkiye near the NW border of Syria. Here we perform a potency‐density tensor inversion to simultaneously estimate rupture evolution and fault geometry for the doublet. We find the initial M W 7.9 earthquake involved discrete episodes of supershear rupture and back‐rupture propagation, and was triggered by initial rupture along a bifurcated splay of the East Anatolian Fault. The second M W 7.6 event was triggered by the earlier M W 7.9 event, and it involved more extensive supershear rupture along a favorably curved fault, and was likely stopped by geometric barriers at the fault ends. Our results highlight the multi‐scale cascading rupture growth across the complex fault network that affects the diverse rupture geometries of the 2023 Türkiye earthquake doublet, contributing to the strong ground shaking and associated devastation.

Abstract This paper evaluates sea surface temperature (SST) biases of coupled models participating in Coupled Model Intercomparison Project Phase 5 (CMIP5) and CMIP6. Overall, CMIP6 models perform better than CMIP5 ones in reproducing SST climatology, with lower multi‐model ensemble mean (MME) globally averaged absolute bias (1.17 vs. 1.31 K). MME bias in global mean annual SST shifts from cooling (−0.09 ± 0.52 K) to warming (0.23 ± 0.60 K). Regionally, in CMIP6 cooling biases over the Northwest Pacific and North Atlantic are reduced by 20% and 18%, while warming biases over the Northeast Pacific, Southeast Atlantic and Southern Ocean are increased by 25%, 16% and 107% respectively. These changes are mainly attributed to the combined effects from aggravated positive (or alleviated negative) bias in clear‐sky surface downward longwave radiation, and alleviated negative bias in cloud radiative effect, partially reduced by enhanced cooling bias in clear‐sky surface downward shortwave radiation.

Abstract This study examines the deep convection populations and mesoscale convective systems (MCSs) simulated in the DYAMOND (DYnamics of the atmospheric general circulation modeled on non‐hydrostatic domains) winter project. A storm tracking algorithm is applied to six DYAMOND simulations and a global high‐resolution satellite cloud and precipitation data set for comparison. The simulated frequencies of tropical deep convection and organized convective systems vary widely among models and regions, although robust MCSs are generally underestimated. The diurnal cycles of MCS initiation and mature stages are well simulated, but the amplitudes are exaggerated over land. Most models capture the observed MCS lifetime, cloud shield area, rainfall volume and movement speed. However, cloud‐top height and convective rainfall intensity are consistently overestimated, and stratiform rainfall area and amount are consistently underestimated. Possible causes for the model differences compared to observations and implications for future model developments are discussed.

Abstract We considered various non‐uniformities such as branch faults, rotation of stress field directions, and changes in tectonic environments to simulate the dynamic rupture process of the 6 February 2023 Mw 7.8 Kahramanmaraş earthquake in SE Türkiye. We utilized near‐fault waveform data, GNSS static displacements, and surface rupture to constrain the dynamic model. The results indicate that the high initial stress accumulated in the Kahramanmaraş‐Çelikhan seismic gap leads to the successful triggering of the East Anatolian Fault (EAF) and the supershear rupture in the northeast segment. Due to the complexity of fault geometry, the rupture speed along the southeastern segment of the EAF varied repeatedly between supershear and subshear, which contributed to the unexpectedly strong ground motion. Furthermore, the triggering of the EAF reminds us to be aware of the risk of seismic gaps on major faults being triggered by secondary faults, which is crucial to prevent significant disasters.

Abstract The Mj6.5 (Mw6.2) event that occurred on 5 May 2023 near the northern shoreline of the northeastern tip of the Noto Peninsula, central Japan, is the largest event to date in a long‐lasting, intense earthquake swarm. Here we have created a more precise aftershock catalog associated with the 2023 Mj6.5 and the second‐largest 2022 Mj5.4 sequence to understand the rupture process of this largest earthquake. Most of the aftershocks are aligned along a ∼45° SE‐dipping plane. The mainshock initially ruptured the same deep section of the fault zone that had been ruptured by the 2022 Mj5.4 event, before propagating rapidly to shallow depths and to offshore along the ruptured fault plane. The aftershock front migrated at a speed of ∼20 km/hr. This rapid upward migration of the immediate aftershocks might be driven by upwelling of crustal fluids along the intensely fractured and permeable fault zone via mainshock dynamic rupture.

Abstract Yangtze River basin (YZB) experienced record‐breaking heat in the summer of 2022. Here, we focused on daytime‐nighttime compound heat waves, and used the magnitude index that considers both duration and intensity to investigate the risk of the 2022 extreme heat. The magnitude of heatwaves in 2022 was much larger than the historical average level, which was estimated as a 1‐in‐64‐year event over 1979–2014 climate. Without mitigation efforts (SSP585), the record‐breaking heat would emerge as normal during 2050s, and would affect ∼70% of land and projected population in the basin before global mean temperature change reaches 3°C. Such an emergence could be progressively delayed and impacts could be reduced under lower warming levels. The affected area would be 60% lesser at 2°C warming, and the emergence could be avoided by limiting warming to 1.5°C. Our results call for urgent mitigation efforts for reducing the risk of compound heat extremes.

Abstract Underground hydrogen storage is a long‐duration energy storage option for a low‐carbon economy. Although research into the technical feasibility of underground hydrogen storage is ongoing, existing underground gas storage (UGS) facilities are appealing candidates for the technology because of their ability to store and deliver natural gas. We estimate that UGS facilities in the United States (U.S.) can store 327 TWh (9.8 MMT) of pure hydrogen. A complete transition to hydrogen storage would reduce the collective working‐gas energy of UGS facilities by ∼75%; however, most (73.2%) UGS facilities could maintain current energy demand using a 20% hydrogen‐natural gas blend. U.S. UGS facilities can buffer 23.9%–44.6% of the high and low hydrogen demand projected for 2050, respectively, which exceeds the current percentage of natural gas demand buffered by storage. Thus, transitioning UGS infrastructure to hydrogen could substantially reduce the number of new hydrogen storage facilities needed to support a hydrogen economy.

Abstract Since the early 1990s the Pacific Walker circulation shows a multi‐decadal strengthening, which contradicts future model projections. Whether this trend, evident in many climate indices especially before the 2015 El Niño, reflects the coupled ocean‐atmosphere response to global warming or the negative phase of the Pacific Decadal Oscillation (PDO) remains debated. Here we show that sea surface temperature trends during 1980–2020 are dominated by three signals: a spatially uniform warming trend, a negative PDO pattern, and a Northern Hemisphere‐Indo‐West Pacific warming pattern. The latter pattern, which closely resembles the transient ocean thermostat‐like response to global warming emerging in a subset of CMIP6 models, shows cooling in the central‐eastern equatorial Pacific but warming in the western Pacific and tropical Indian Ocean. Together with the PDO, this pattern drives the Walker circulation strengthening in the equatorial band. Historical simulations appear to underestimate this pattern, contributing to the models' inability to replicate the Walker cell…

Abstract Attenuation of ocean waves by ice is a crucial process of the interaction between waves and sea ice in marginal ice zone (MIZ), while such interaction can contribute to the retreating of sea ice in the Arctic. Based on the retrieved two‐dimensional ocean wave spectra by spaceborne Synthetic Aperture Radar, we investigated the attenuation of ocean waves in the MIZ in Svalbard and Greenland. The results show that the energy attenuation rate ranges from 0.126 × 10 −4 /m to 0.618 × 10 −4 /m. Quantitative analysis suggests that the attenuation rate is significantly related to wave height and peak wave period of coming waves. It is further found that the waves decay faster in the area with ice thickness exceeding 0.5 m. We compared the derived wave attenuation rates in the present study with those in previous studies based on in situ measurements, which reveals that waves are becoming less attenuated by sea ice in the Arctic.

Abstract 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.

Abstract In weather and climate applications, a wide range of commonly employed heatwave intensity indices relies either on cumulative or averaged values of temperature‐based variables. In this study, by comparing four different heatwave intensity indices applied to reanalysis data we show that metrics based on cumulative or averaged values lead to important differences in the detection of the most intense events of the period 1950–2021. This suggests that particular attention is needed when using the two families of metrics for assessing heatwave intensity. Indices based on cumulative values should be preferred over the ones relying on temporal averages, better allowing for the comparison of events of different length. Under these considerations, one of the considered cumulative indices is used for characterizing heatwaves of the period 1950–2021, showing that heatwaves that were unlikely before 1986 have become almost 10 times more frequent and up to three times more intense during recent times.

Abstract We investigate error growth from small‐amplitude initial condition perturbations, simulated with a recent artificial intelligence‐based weather prediction model. From past simulations with standard physically‐based numerical models as well as from theoretical considerations it is expected that such small‐amplitude initial condition perturbations would grow very fast initially. This fast growth then sets a fixed and fundamental limit to the predictability of weather, a phenomenon known as the butterfly effect. We find however, that the AI‐based model completely fails to reproduce the rapid initial growth rates and hence would incorrectly suggest an unlimited predictability of the atmosphere. In contrast, if the initial perturbations are large and comparable to current uncertainties in the estimation of the initial state, the AI‐based model basically agrees with physically‐based simulations, although some deficits are still present.

Abstract We use high‐resolution three‐dimensional X‐ray imaging to study hydrogen injection and withdrawal in the pore space of Bentheimer sandstone. The results are compared with a replicate experiment using nitrogen. We observe less trapping with hydrogen because the initial saturation after drainage is lower due to channeling. Remarkably we observe that after imbibition, if the sample is imaged again after 12 hr, there is a significant rearrangement of the trapped hydrogen. Many smaller ganglia disappear while the larger ganglia swell, with no detectable change in overall gas volume. For nitrogen, the fluid configuration is largely unchanged. This rearrangement is facilitated by concentration gradients of dissolved gas in the aqueous phase—Ostwald ripening, We estimate the time‐scales for this effect to be significant, consistent with the experimental observations. The swelling of larger ganglia potentially increases the gas connectivity, leading to less hysteresis and more efficient withdrawal.

Abstract The factors controlling earthquake swarm duration are remain unclear, especially in the long‐living ones. A severe earthquake swarm struck the tip of the Noto peninsula, Japan. Ten M > 4.0 earthquakes occurred, and the sequence has continued more than 4 years. We investigated the spatiotemporal characteristics of the swarm using relocated hypocenters to elucidate the factors causing this long duration. The swarm consists of four seismic clusters—northern, northeastern, western, and southern—the latter of which began first. Diffusive hypocenter migrations were observed in the western, northern, and northeastern clusters with moderate to low diffusivities, implying a low‐permeability environment. Rapid diffusive migration associated with intermittent seismicity deep within the southern cluster suggests the presence of a highly pressurized fluid supply. We conclude that the nature of this fluid supply combined with intermittent seismicity from the southern cluster and a low‐permeability environment are the key causes of this long‐living swarm.

Abstract The Yangtze River Basin experienced one of the worst flash droughts on record during 2022 summer, but the relative contributions of precipitation deficit and high temperature to drought onset speed and intensity are difficult to separate due to the compounding feature of hot and dry extremes caused by persistent high‐pressure anomalies. Based on high‐resolution land surface model ensemble simulations with specified meteorological conditions that reproduce precipitation deficit and/or high temperature anomalies during 2022, we find the precipitation deficit is the dominant factor for triggering the flash drought. Meanwhile, high temperature further accelerates the decrease of soil moisture and intensifies drought condition by increasing evapotranspiration, which contributes 37% ± 14% (31% ± 15%) and 36% ± 11% (30% ± 15%) of the drought onset speed and intensity over upper reach (middle and lower reaches). Our study reveals the nontrivial role of high temperature in intensifying the 2022 Yangtze flash drought, which might be more significant in the warmer future.

Abstract We derive the ALOS‐2 coseismic interferograms, pixel‐offsets and Sentinel‐2 sub‐pixel offsets of the 2023 M w 7.8 and M w 7.7 Kahramanmaras, Turkey earthquake sequence. Offset maps show that the sequence ruptured ∼300 km along the East Anatolian Fault (EAF) and ∼180 km along the secondary Cardak and Dogansehir faults. We infer the coseismic slip distribution and interseismic fault motion by inverting the co‐ and inter‐seismic observations. Inversion results show that the coseismic slip (∼8.0 m) and interseismic strike‐slip rate (∼4.6 mm/yr) on the main rupture of the M w 7.8 event are basically consistent with the ∼8.4 m and ∼3.9 mm/yr of the M w 7.7 event. Most coseismic slips of the M w 7.8 and M w 7.7 events occur within 10 and 12 km at depth, respectively, in keeping with the interseismic locking depth of 10.4 ± 3.3 km and 11.1 ± 3.1 km. This implies that the coseismic rupture kinematics correlate with the interseismic strain accumulation. Moreover, static stress changes show that the M w 7.7 event is likely promoted by ∼2 bar stress increase from the M w 7.8 event on…

Abstract The amount, frequency and intensity of extreme precipitation over Xinjiang have increased dramatically under the wetting trend in Northwest China, but long‐term trends in the precipitation‐recycling process remain largely unexplored. Based on dynamic recycling model and MERRA2 reanalysis, we revealed a mean recycling ratio for extreme precipitation in Xinjiang of 42.3% with a growth rate of 2.3% decade −1 during 1982–2019. The increasing trend of extreme precipitation was almost equally attributed to increased recycling precipitation (49%) and external precipitation (51%). The extreme precipitation in Xinjiang exhibited two peak centers, the Tianshan Mountains region (TS) and Kunlun Mountains region (KL), highlighting variations in the water cycle. Specifically, the external cycle predominated the increased extreme precipitation in TS (61%), while the recycling process mainly influenced the increase in KL (67%) due to markedly enhanced evapotranspiration. Moisture source attribution further proved the crucial role of evapotranspiration from Xinjiang and its vicinity in…

Abstract Compound drought‐heatwave (CDHW) events threaten ecosystem productivity and are often characterized by low soil moisture (SM) and high vapor pressure deficit (VPD). However, the relative roles of SM and VPD in constraining forest productivity during CDHWs remain controversial. In the summer of 2022, China experienced a record‐breaking CDHW event (DH2022). Here, we applied satellite remote‐sensing data and meteorological data, and machine‐learning techniques to quantify the individual contributions of SM and VPD to forest productivity variations and investigate their interactions during the development of DH2022. The results reveal that SM, rather than VPD, dominates the forest productivity decline during DH2022. We identified a possible critical tipping point of SM below which forest productivity would quickly decline with the decreasing SM. Furthermore, we illuminated the evolution of SM, VPD, evapotranspiration, forest productivity, and their interactions throughout DH2022. Our findings broaden the understanding of forest response to extreme CDHWs at the ecosystem scale.

Abstract An Mw 6.2 earthquake occurred in Suzu, northeastern Noto Peninsula, Japan, on 5 May 2023, followed by many aftershocks. Before this mainshock‐aftershock sequence, an intense earthquake swarm lasted in the vicinity for 2.5 years. Here, we estimated the rupture process of the Mw 6.2 mainshock and relocated >20,000 surrounding small earthquakes. The results show that systematic upward migration occurred via a complex network of faults in the preceding swarm period and that the mainshock rupture was initiated near the shallow end of the swarm earthquakes. The mainshock rupture propagated farther updip, followed by many aftershocks in the shallow extension. Upward fluid movement likely caused systematic upward earthquake migration from a depth of 18–5 km. The present results indicate the importance of monitoring swarm events since large (M > 6) and dangerous earthquakes can occur during such swarms.

Abstract Geological CO 2 storage is an emerging topic in energy and environmental community, which is, as a commonly accepted sense, considered as the most promising and powerful approach to mitigate the global carbon emissions during the transition to net‐zero. Of the geological media which initially considered cover the saline aquifers, oil and gas reservoirs, coal beds, and potentially basalts, up to now only the first two choices have been proven to be the most capable storage sites and successfully implemented at pilot/commercial scales. Here, two tandem papers propose novel strategies for the first time, by synthesizing and utilizing new high‐dryness CO 2 foam, to enhance geological CO 2 storage capacity in saline aquifer and oil and gas reservoirs. In this paper, a new high‐dryness CO 2 foam is synthesized and injected into the saline aquifers to explore the storage capacity enhancement, with the unique foam‐induced advantages of sweep area expansion and storage efficiency improvement. Such a new idea is specifically evaluated and validated through a series of static…

Abstract Streamflow droughts are governed by different hydro‐meteorological processes, whose relative importance may change over time, with potential impacts on drought severity. Here, we assess changes in the importance of different hydrological drought generation processes in the European Alps by applying a standardized drought type classification scheme to two time periods—one in the distant (1970–1993) and one in the recent past (1994–2017). Our findings show that changes in the relative importance of different drought generation processes are stronger in high‐elevation catchments, where we detect clear changes in drought seasonality, than in low‐elevation catchments. Furthermore, they suggest that changes in drought severity and generation processes are related because increasingly frequent snowmelt‐deficit droughts in high‐elevation catchments have larger deficits than droughts caused by decreasingly frequent cold temperatures. These changes might persist into the future, because of continuing decreases in snow cover and increases in evapotranspiration, with potential…

Abstract Small water bodies (i.e., ponds; <0.01 km 2 ) play an important role in Earth System processes, including carbon cycling and emissions of methane. Detection and monitoring of ponds using satellite imagery has been extremely difficult and many water maps are biased toward lakes (>0.01 km 2 ). We leverage high‐resolution (3 m) optical satellite imagery from Planet Labs and deep learning methods to map seasonal changes in pond and lake areal extent across four regions in Alaska. Our water maps indicate that changes in open water extent over the snow‐free season are especially pronounced in ponds. To investigate potential impacts of seasonal changes in pond area on carbon emissions, we provide a case study of open water methane emission budgets using the new water maps. Our approach has widespread applications for water resources, habitat and land cover change assessments, wildlife management, risk assessments, and other biogeochemical modeling efforts.

Abstract A comprehensive comparison of the trends and drivers of global surface and canopy urban heat islands (termed I s and I c trends, respectively) is critical for better designing urban heat mitigation strategies. However, such a global comparison remains largely absent. Using spatially continuous land surface temperatures and surface air temperatures (2003–2020), here we find that the magnitude of the global mean I s trend (0.19 ± 0.006°C/decade, mean ± SE) for 5,643 cities worldwide is nearly six‐times the corresponding I c trend (0.03 ± 0.002°C/decade) during the day, while the former (0.06 ± 0.004°C/decade) is double the latter (0.03 ± 0.002°C/decade) at night. Variable importance scores indicate that global daytime I s trend is slightly more controlled by surface property, while background climate plays a more dominant role in regulating global daytime I c trend. At night, both global I s and I c trends are mainly controlled by background climate.

Abstract Distributed Acoustic Sensing (DAS) is a promising technique to improve the rapid detection and characterization of earthquakes. Previous DAS studies mainly focus on the phase information but less on the amplitude information. In this study, we compile earthquake data from two DAS arrays in California, USA, and one submarine array in Sanriku, Japan. We develop a data‐driven method to obtain the first scaling relation between DAS amplitude and earthquake magnitude. Our results reveal that the earthquake amplitudes recorded by DAS in different regions follow a similar scaling relation. The scaling relation can provide a rapid earthquake magnitude estimation and effectively avoid uncertainties caused by the conversion to ground motions. Our results show that the scaling relation appears transferable to new regions with calibrations. The scaling relation highlights the great potential of DAS in earthquake source characterization and early warning.

Abstract The reliable Subseasonal‐to‐Seasonal (S2S) forecast of precipitation, particularly extreme precipitation, is critical for disaster prevention and mitigation, which however remains a great challenge for mission agencies and research communities. In this study, a deep learning method based on U‐Net with additional atmospheric factor forecasts included is proposed to improve S2S quantitative forecasts of summer precipitation over Southern China. The weighted loss function integrated by mean square error and threat score is introduced to capture extreme precipitation more precisely. Generally, the U‐Net model shows promising results in both general statistics and extreme events. Predictor importance analyses show that the U‐Net forecast skills at the 1‐week lead time mainly arise from synchronous precipitation forecasts, but the contributions made by atmospheric factor forecasts rise rapidly with increasing lead times. Therefore, the channel combining numerical weather prediction model and deep learning framework is demonstrated promising in S2S precipitation forecasts.

Abstract Using multi‐satellite observations, the cloud dynamic and microphysical characteristics were revealed during the rapid intensification (RI) of super‐typhoon Nanmadol (2022). As the storm intensifies, the eyewall contracts, the upper‐level divergence strengthens, and the cirrus cloud increases, leading to stronger upper‐level radial outflow and the vertical updraft. Meanwhile, it is found that there exists a dynamically attractive area in the outer rainbands, where particles grow effectively and form “a small amount of large particles” around 300 km from the eye. A theory of cloud dynamics‐microphysics interaction, called “tunnel theory,” is further proposed to explain the generation, accumulation, and concentrated downflow of large particles in the outer rainbands during RI. Results suggest the unique feature of particle distribution in the outer rainbands could be a potential indicator for RI.

Abstract Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common data set consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection.

Abstract Large wildfires are increasing across numerous regions of the globe. While the West has remained a primary focus of wildfire research and resources in the U.S., recent signals suggest that wildfire risk is increasing in the eastern U.S. as well. We conducted an in‐depth assessment of large (>200 ha) wildfire regime characteristics (size, number, total hectares burned, seasonality, probability of occurrence, and ignition source) over a 36‐year period across the Eastern Temperate Forests of the U.S. to quantify geographic patterns in large‐wildfire regime and identify changing spatio‐temporal large wildfire patterns. We found increases in large wildfire size, occurrence, number, and total hectares burned in the southern and eastern regions of the Eastern Temperate Forests. In contrast, large wildfires declined or were minimal in northern ecoregions. We demonstrate increasing large wildfires across some of the most populated regions of the United States.

Abstract Extreme events have become more frequent in the Northern Hemisphere mid‐latitudes in recent decades, hugely impacting the ecosystem and society. The quasi‐resonance amplification (QRA) of planetary waves is considered one of the dynamic mechanisms leading to extreme weather. However, the specific impact of resonant waves caused by QRA on surface heat extremes is still an open issue. Here we show that the QRA of planetary waves leading to heat extremes is closely related to double jets, accompanied by the enhancement of atmospheric blocking and the weakening of planetary wave escaping into the stratosphere. Our results illustrate the important role of mid‐latitude planetary waves with zonal wavenumber m = 6–8 caused by QRA in the increasingly frequent heat waves in recent years, as it can increase the coverage area and occurrence frequency of heat extremes in mid‐latitudes and show a significant impact on preferred regions, especially in Eurasia.

Abstract Clear‐air turbulence (CAT) is hazardous to aircraft and is projected to intensify in response to future climate change. However, our understanding of past CAT trends is currently limited, being derived largely from outdated reanalysis data. Here we analyze CAT trends globally during 1979–2020 in a modern reanalysis data set using 21 diagnostics. We find clear evidence of large increases around the midlatitudes at aircraft cruising altitudes. For example, at an average point over the North Atlantic, the total annual duration of light‐or‐greater CAT increased by 17% from 466.5 hr in 1979 to 546.8 hr in 2020, with even larger relative changes for moderate‐or greater CAT (increasing by 37% from 70.0 to 96.1 hr) and severe‐or‐greater CAT (increasing by 55% from 17.7 to 27.4 hr). Similar increases are also found over the continental USA. Our study represents the best evidence yet that CAT has increased over the past four decades.

Abstract The Loess Plateau of China has witnessed a remarkable greening trend due to vegetation restoration in recent decades. However, the precipitation response to greening remains unclear, and the hydrological effect of greening is controversial. Here, we revisited biophysical effects of greening on precipitation over the plateau during 2002–2015 using the state‐of‐the‐art water vapor tracer embedded in a regional coupled model. We find that greening can promote the growing season precipitation (0.45 mm·day −1 ), with 15% and 85% of the precipitation increment resulting from increases in the local evapotranspiration and the water vapor inflow from outside the plateau, respectively. As a consequence, the enhanced precipitation can compensate for the terrestrial water loss driven by the increased evapotranspiration, leading to a slight increase in the water yield. This study highlights the dominant role of the nonlocal effect in precipitation responses to greening in this region.

Abstract We study hysteresis properties of the Atlantic Meridional Overturning Circulation (AMOC) under a slowly‐varying North Atlantic (20°N–50°N) freshwater flux forcing in state‐of‐the‐art global climate model (GCM), the Community Earth System Model. Results are presented of a full hysteresis simulation (4,400 model years) and show that there is a hysteresis width of about 0.4 Sv. This demonstrates that an AMOC collapse and recovery do not only occur in conceptual and idealized climate models, but also in a state‐of‐the‐art GCM. The AMOC recovery is about a factor six faster than the AMOC collapse and this asymmetry is due to the major effect of the North Atlantic sea‐ice distribution on the AMOC recovery. The results have implications for projections of possible future AMOC behavior and for explaining relatively rapid climate transitions in the geological past.

Abstract A purely data‐driven and transformer‐based model with a novel self‐attention mechanism (3D‐Geoformer) is used to make predictions by adopting a rolling predictive manner similar to that in dynamical coupled models. The 3D‐Geoformer yields a successful prediction of the 2021 second‐year cooling conditions that followed the 2020 La Niña event, including covarying anomalies of surface wind stress and three‐dimensional (3D) upper‐ocean temperature, the reoccurrence of negative subsurface temperature anomalies in the eastern equatorial Pacific and a corresponding turning point of sea surface temperature (SST) evolution in mid‐2021. The reasons for the successful prediction with interpretability are explored comprehensively by performing sensitivity experiments with modulating effects on SST due to wind and subsurface thermal forcings being separately considered in the input predictors for prediction. A comparison is also conducted with physics‐based modeling, illustrating the suitability and effectiveness of 3D‐Geoformer as a new platform for El Niño and Southern Oscillation…

Abstract Heatwaves lead to catastrophic consequences on public health and the economy. Accurate and timely predictions of regional heatwaves can improve climate preparedness and foster decision‐making to alleviate the burdens due to climate change. In this paper, we propose a heatwave prediction algorithm based on a novel deep learning model, that is, Graph Neural Network (GNN). This new GNN framework can provide real time warnings of the sudden occurrence of regional heatwaves with high accuracy at lower costs of computation and data collection. In addition, its interpretable structure unravels the spatiotemporal patterns of regional heatwaves and helps to enrich our understanding of the general climate dynamics and the causal influences between locations. The proposed GNN framework can be applied for the detection and prediction of other extreme or compound climate events, which calls for future studies.

Abstract Seismic wave arrival time measurements form the basis for numerous downstream applications. State‐of‐the‐art approaches for phase picking use deep neural networks to annotate seismograms at each station independently, yet human experts annotate seismic data by examining the whole network jointly. Here, we introduce a general‐purpose network‐wide phase picking algorithm based on a recently developed machine learning paradigm called Neural Operator. Our model, called Phase Neural Operator, leverages the spatio‐temporal contextual information to pick phases simultaneously for any seismic network geometry. This results in superior performance over leading baseline algorithms by detecting many more earthquakes, picking more phase arrivals, while also greatly improving measurement accuracy. Following similar trends being seen across the domains of artificial intelligence, our approach provides but a glimpse of the potential gains from fully‐utilizing the massive seismic data sets being collected worldwide.

Abstract A tectonic Plate Motion Model (PMM) is essential for geodetic applications, while contributing to the understanding of geodynamic processes affecting the Earth's surface. We introduce a PMM derived from the horizontal velocities of 518 sites extracted from the ITRF2020 solution. These sites were chosen away from plate boundaries, Glacial Isostatic Adjustment regions, and other deforming zones. Unlike the ITRF2014‐PMM, which showed no significant Origin Rate Bias (ORB), velocities used to determine the ITRF2020‐PMM exhibit a statistically significant ORB (0.74 ± 0.09 mm/yr along the Z‐component). Users are advised to add the estimated ORB to the horizontal velocities predicted by the ITRF2020‐PMM rotation poles for full consistency with the ITRF2020. However, the predicted vertical velocities resulting from the addition of the ORB should be discarded. The overall precision with which the ITRF2020 velocity field is represented by the rigid ITRF2020‐PMM is at the level of 0.25 mm/yr WRMS.

Abstract The El Niño‐Southern Oscillation (ENSO) influences climate variability across the globe. ENSO is highly predictable on seasonal timescales and therefore its teleconnections are a source of extratropical forecast skill. To fully harness this predictability, teleconnections must be represented accurately in seasonal forecasts. We find that a multimodel ensemble from five seasonal forecast systems can successfully capture the spatial structure of the late winter (JFM) El Niño teleconnection to the North Atlantic via North America, but the simulated amplitude is half of that observed. We find that weak amplitude teleconnections exist in all five models throughout the troposphere, and that the La Niña teleconnection is also weak. We find evidence that tropical forcing of the El Niño teleconnection is not underestimated and instead, deficiencies are likely to emerge in the extratropics. We investigate the impact of underestimated teleconnection strength on North Atlantic winter predictability, including its relevance to the signal‐to‐noise paradox.

Abstract Electromagnetic ion cyclotron (EMIC) waves can drive radiation belt depletion and Low‐Earth Orbit satellites can detect the resulting electron and proton precipitation. The ELFIN (Electron Losses and Fields InvestigatioN) CubeSats provide an excellent opportunity to study the properties of EMIC‐driven electron precipitation with much higher energy and pitch‐angle resolution than previously allowed. We collect EMIC‐driven electron precipitation events from ELFIN observations and use POES (Polar Orbiting Environmental Satellites) to search for 10s–100s keV proton precipitation nearby as a proxy of EMIC wave activity. Electron precipitation mainly occurs on localized radial scales (∼0.3 L), over 15–24 MLT and 5–8 L shells, stronger at ∼MeV energies and weaker down to ∼100–200 keV. Additionally, the observed loss cone pitch‐angle distribution agrees with quasilinear predictions at ≳250 keV (more filled loss cone with increasing energy), while additional mechanisms are needed to explain the observed low‐energy precipitation.

Abstract Predictions of thunderstorm‐related hazards are needed in several sectors, including first responders, infrastructure management and aviation. To address this need, we present a deep learning model that can be adapted to different hazard types. The model can utilize multiple data sources; we use data from weather radar, lightning detection, satellite visible/infrared imagery, numerical weather prediction and digital elevation models. We demonstrate the ability of the model to predict lightning, hail and heavy precipitation probabilistically on a 1 km resolution grid, with a temporal resolution of 5 min and lead times up to 60 min. Shapley values quantify the importance of the different data sources, showing that the weather radar products are the most important predictors for all three hazard types.

Abstract Accelerating ice loss from Thwaites Glacier is contributing approximately 5% of global sea‐level rise, and could add tens of centimeters to sea level over the coming centuries. We use an ocean model to calculate sub‐ice melting for a succession of Digital Elevation Models of the main trunk of Thwaites Glacier from 2011 to 2022. The ice evolution during this period induces a strong geometrical feedback onto melting. Ice thinning and retreat provides a larger melting area, thicker and better‐connected sub‐ice water column, and steeper ice base. This leads to stronger sub‐ice ocean currents, increasing melting by over 30% without any change in forcing from wider ocean conditions. This geometrical feedback over just 12 years is comparable to melting changes arising from plausible century‐scale changes in ocean conditions and subglacial meltwater inflow. These findings imply that ocean‐driven ice loss from Thwaites Glacier may only be weakly influenced by anthropogenic emissions mitigation.

Abstract Seismology is witnessing explosive growth in the diversity and scale of earthquake catalogs. A key motivation for this community effort is that more data should translate into better earthquake forecasts. Such improvements are yet to be seen. Here, we introduce the Recurrent Earthquake foreCAST (RECAST), a deep‐learning model based on recent developments in neural temporal point processes. The model enables access to a greater volume and diversity of earthquake observations, overcoming the theoretical and computational limitations of traditional approaches. We benchmark against a temporal Epidemic Type Aftershock Sequence model. Tests on synthetic data suggest that with a modest‐sized data set, RECAST accurately models earthquake‐like point processes directly from cataloged data. Tests on earthquake catalogs in Southern California indicate improved fit and forecast accuracy compared to our benchmark when the training set is sufficiently long (>10 4 events). The basic components in RECAST add flexibility and scalability for earthquake forecasting without sacrificing…

Abstract Climate model estimates show significant groundwater depletion during the 20th century, consistent with global mean sea level (GMSL) budget analysis. However, prior to the Argo float era, in the early 2000’s, there is little information about steric sea level contributions to GMSL, making the role of groundwater depletion in this period less certain. We show that a useful constraint is found in observed polar motion (PM). In the period 1993–2010, we find that predicted PM excitation trends estimated from various sources of surface mass loads and the estimated glacial isostatic adjustment agree very well with the observed. Among many contributors to the PM excitation trend, groundwater storage changes are estimated to be the second largest (4.36 cm/yr) toward 64.16°E. Neglecting groundwater effects, the predicted trend differs significantly from the observed. PM observations may also provide a tool for studying historical continental scale water storage variations.

Abstract Increased wildfire activity in the western United States has exposed regional gaps in our understanding of postfire debris‐flow generation. To address this problem, we characterized flows in an unstudied area to test the rainfall intensity‐duration control of the hazard. Our rainfall measurements and field observations from the northern Sierra Nevada (California, USA) show that debris flows resulted from a short burst rainfall during a low‐accumulation storm. In contrast, a much higher accumulation storm (∼10 times more rainfall) with lower short‐duration rainfall rates only produced low‐hazard flooding. We conclude that total storm rainfall is not an ideal metric for identifying the rainfall conditions that initiate runoff‐generated debris flows in the first year after wildfire. Rather, a focus on short‐duration (<1 hr), high‐intensity rainfall that can occur during localized thunderstorms, or bands of intense rainfall during prolonged rainstorms, is more beneficial for the purposes of hazard assessment and warning.

Abstract The exceptionally violent eruption of the Hunga Tonga‐Hunga Ha'apai volcano (HTHH) of 15 January 2022, in the South Pacific, was associated with a powerful blast that injected gases, steam and aerosol to unprecedentedly high altitudes. This article details unique observations of the young volcanic plume from ground‐based lidars at Reunion (21°S, 55°E). Two lidars, operating at wavelengths of 355 and 532 nm, recorded the plume overhead from 19 January until 28 January providing the vertical structure and the optical properties of the plume. A series of thick stratospheric plumes between 36 and 18 km altitude have been characterized along time, with aerosol optical depth as high as 0.84 at 532 nm and negative Angström exponents for the main layers down to −0.8 ± 0.8. The diversity of plumes properties is explained by the injection heights of the volcanic material as well as stratospheric dynamics and chemistry.

Abstract The Tibetan Plateau (TP) has warmed at a rate twice the global average and presents unique warming patterns in surface temperature changes. However, key characteristics of glacier surface heatwave duration and intensity over the TP during the present extreme warming period are still unknown. In this study, we show that surface temperatures in glacial regions of the TP (0.37 ± 0.10°C per decade) have increased faster than those in non‐glacial areas (0.29 ± 0.05°C per decade) between 2001 and 2020. Moreover, the duration (5.3 ± 3.2 days per decade) and cumulative intensity (24.9 ± 16.3 days °C per decade) of glacier surface heatwaves have increased significantly during autumn. Our results demonstrate an elevation dependence to these key warming characteristics, which we also suggest are associated with extreme glacier mass loss. Here, we highlight potential threats to the sustainability of glacier water resources and increasing risk of glacier related hazards at the “roof of the world.”

Abstract Tropical convection tends to be more intense over land than ocean, but why? Numerous previous studies have investigated the causes of this difference. This paper revisits this question using CloudSat data and focuses on interconnecting various environmental parameters and cloud properties, which have often been examined in a piecemeal way in the past. Our analysis shows that if convection is treated as a process by which potential energy (convective available potential energy) is converted to kinetic energy (vertical velocity), then the conversion is more efficient over land than ocean. A key factor that affects this conversion efficiency is the lifting condensation level (LCL). Higher LCLs over land give rise to broader dry boundary layer thermals that transition to wider deep convective cores. Wider cores, in turn, are better protected from the dilution by entrainment, thus leading to stronger updrafts. This study highlights the importance of the dry stage of convection.

Abstract We report observations of Rayleigh waves that orbit around Mars up to three times following the S1222a marsquake. Averaging these signals, we find the largest amplitude signals at 30 and 85 s central period, propagating with distinctly different group velocities of 2.9 and 3.8 km/s, respectively. The group velocities constraining the average crustal thickness beneath the great circle path rule out the majority of previous crustal models of Mars that have a >200 kg/m 3 density contrast across the equatorial dichotomy between northern lowlands and southern highlands. We find that the thickness of the Martian crust is 42–56 km on average, and thus thicker than the crusts of the Earth and Moon. Considered with the context of thermal evolution models, a thick Martian crust suggests that the crust must contain 50%–70% of the total heat production to explain present‐day local melt zones in the interior of Mars.

Abstract The 2021 IPCC report found that most studies show declining trends for the global diurnal temperature range (DTR) since the 1950s, decreasing mainly during 1960–1980. This issue is revisited here using an up‐to‐date in‐situ data set, Hadley Center Integrated Surface Database, constrained by rigorous station selection conditions. The global observed DTR trend was found to reverse during 1980–2021, increasing significantly at a rate of 0.091 ± 0.008°C decade −1 . The trend was dominated by a faster rate of increasing daily maximum air temperature. This increasing observed trend in the past four decades was not fully captured in raw CMIP6 models, as models only partially capture the spatial patterns. With global CMIP6 outputs and regionally‐available observations, the global land DTR was then estimated, through emergent constraints, to be 0.063 ± 0.012°C decade −1 . The study raises concern for risks of increasing DTR globally and provides new insights into global DTR assessment.