Using Climate Forecast System Reanalysis (CFSR) data and numerical simulations, the impacts of the multi-scale sea surface temperature (SST) anomalies in the North Pacific on the boreal winter atmospheric circulations are investigated. The basin-scale SST anomaly as the Pacific Decadal Oscillation (PDO) pattern, a narrow meridional band of frontal-scale smoothed SST anomaly in the subtropical front zone (STFZ) and the spatial dispersed eddy-scale SST anomalies within the STFZ are the three types of forcings. The results of Liang-Kleeman information flow method find that all three oceanic forcings may correspond to the winter North Pacific jet changing with the similar pattern. Furthermore, several simulations are used to reveal the differences and detail processes of the three forcings. The basin-scale cold PDO-pattern SST anomaly first causes negative turbulent heat flux anomalies, atmospheric cooling, and wind deceleration in the lower atmosphere. Subsequently, the cooling temperature with an amplified southern lower temperature gradient and baroclinity brings a lagging middle warming because of the enhanced atmospheric eddy heat transport. The poleward and upward development of baroclinic fluctuations eventually causes the acceleration of the upper jet. The smoothed frontal- and eddy-scale SST anomalies in the STFZ cause comparable anomalous jet as the basin-scale by changing the upward baroclinic energy and E-P fluxes. The forcing effects of multi-scale SST anomalies coexist simultaneously in the mid-latitude North Pacific, which can cause similar anomalous upper atmospheric circulations. This is probably why it is tricky to define the certain oceanic forcing that leads to specific atmospheric circulation variation in observations

We developed a storm surge Ensemble Prediction System (EPS) for the Goro lagoon (GOLFEM-EPS) in the Northern Adriatic Sea. The lagoon is threatened every year by storm surge events with consequent risks for human life and economic losses. We show the advantages and limitations of an EPS with 45 members, using a very high-resolution unstructured grid finite element model. For five recent storm surge events, the EPS generally improves the forecast skill on the third forecast day compared to just one deterministic forecast, while they are similar in the first two days. A weighting system is implemented to compute an improved ensemble mean. The uncertainties regarding sea level due to meteorological forcing, river run-off, initial and lateral boundaries are evaluated, and the different forecasts are used to compose the EPS members. We conclude that the largest uncertainty is in the initial and lateral boundary fields at different time and space scales, including the tidal components.

In this paper we analyze electric-field and current measurements of competing upward leaders induced by a downward negative lightning flash that struck a residential building. The attachment process was recorded by two high-speed cameras running at 37,800 and 70,000 images per second and the current measured in two lightning rods. Differently from previous works, here we show, for the first time, the behavior of multiple upward leaders that after initiation compete to connect the negative downward moving leader. At the beginning of the propagation of the leaders that initiate on the instrumented lightning rods, current pulses appear superimposed to a steadily increasing DC current. The upward leader current pulses increase with the approach of the downward leader and are not synchronized but present an alternating pattern. All leader speeds are constant. The upward leaders are slower than the downward leader speed. The average time interval between current pulses in upward leaders is close to the interstep time interval found by optical or electric field sensors for negative cloud-to-ground stepped leaders. The upward leaders respond to different downward propagating branches and, as the branches alternate in propagation and intensity, so do the leaders accordingly. Right before the attachment process the alternating pattern of the leaders ceases, all downward leader branches intensify, and consequently upward leaders synchronize and pulse together. The average linear densities for upward leaders (49 and 82 µC/m) were obtained for the first time for natural lightning.

This paper is a contribution to the exploration of the parametric Kalman filter (PKF), which is an approximation of the Kalman filter, where the error covariance are approximated by a covariance model. Here we focus on the covariance model parameterized from the variance and the anisotropy of the local correlations, and whose parameters dynamics provides a proxy for the full error-covariance dynamics. For this covariance mode, we aim to provide the boundary condition to specify in the prediction of PKF for bounded domains, focusing on Dirichlet and Neumann conditions when they are prescribed for the physical dynamics. An ensemble validation is proposed for the transport equation and for the heterogeneous diffusion equations over a bounded 1D domain. This ensemble validation requires to specify the auto-correlation time-scale needed to populate boundary perturbation that leads to prescribed uncertainty characteristics. The numerical simulations show that the PKF is able to reproduce the uncertainty diagnosed from the ensemble of forecast appropriately perturbed on the boundaries, which show the ability of the PKF to handle boundaries in the prediction of the uncertainties. It results that Dirichlet condition on the physical dynamics implies Dirichlet condition on the variance and on the anisotropy.

The Central Highlands of Vietnam is the biggest Robusta coffee (Coffea canephora Pierre ex A.Froehner) growing region in the world. This study aims to identify the most important climatic variables that determine the current distribution of coffee in the Central Highlands and build a “coffee suitability” model to assess changes in this distribution due to climate change scenarios. A suitability model based on neural networks was trained on coffee occurrence data derived from national statistics on coffee-growing areas. Bias-corrected regional climate models were used for two climate change scenarios (RCP8.5 and RCP2.6) to assess changes in suitability for three future time periods (i.e., 2038-2048, 2059-2069, 2060-2070) relative to the 2009-2019 baseline. Average expected losses in suitable areas were 62% and 27% for RCP8.5 and RCP2.6, respectively. The loss in suitability due to RCP8.5 is particularly pronounced after 2060. Increasing mean minimum temperature during harvest (October-November) and growing season (March-September) and decreasing precipitation during late growing season (July-September) mainly determined the loss in suitable areas. If the policy commitments made at the Paris agreement are met, the loss in coffee suitability could potentially be compensated by climate change adaptation measures such as making use of shade trees and adapted clones.

Self-organizing diffusion-reaction systems naturally form complex patterns under far from equilibrium conditions. A representative example is the rhythmic concentration pattern of Fe-oxides in Zebra rocks; these patterns include reddish-brown stripes, rounded rods, and elliptical spots. Similar patterns are observed in the banded iron formations which are presumed to have formed in the early earth under global glaciation. We propose that such patterns can be used directly (e.g., by computer-vision-analysis) to infer basic quantities relevant to their formation giving information on generalized chemical gradients. Here we present a phase-field model that quantitatively captures the distinct Zebra rock patterns based on the concept of phase separation that describes the process forming Liesegang stripes. We find that diffusive coefficients (i.e., the bulk self-diffusivities and the diffusive mobility of Cahn-Hilliard dynamics) play an essential role in controlling the appearance of regular stripe patterns as well as the transition from stripes to spots. The numerical results are carefully benchmarked with the well-established empirical spacing law, width law, timing law and the Matalon-Packter law. Using this model, we invert for the important process parameters that originate from the intrinsic material properties, the self-diffusivity ratio and the diffusive mobility of Fe-oxides, with a series of Zebra rock samples. This study allows a quantitative prediction of the generalized chemical gradients in mineralized source rocks without intrusive measurements, providing a better intuition for the mineral exploration space.

Water quality in rivers is influenced by natural factors and human activities that interact in complex and nonlinear ways, which make water quality modelling a challenging task. The concepts of complex networks (CN), a recent development in network theory, seem to provide new avenues to unravel the connections and dynamics of water quality phenomenon, including clandestine teleconnections. This study aims to explore the spatial patterns of water quality using the CN concepts, at both catchment scale and larger national scale. Three major water quality parameters, i.e. dissolved oxygen (DO), permanganate index (COD Mn), and ammonia nitrogen (NH 3-N) are considered for analysis. Weekly data over a period of 12 years (since 2006) from 91 monitoring stations across China are analysed. Degree centrality and clustering coefficient methods are employed. The results show that the degree centrality and clustering coefficients values for water quality indicators is DO > NH 3-N > COD Mn at both basin scale and national scale. Since COD Mn is more sensitive to the upstream point source pollution, as it depends upon the locality and human activities, it leads to a higher heterogeneity of CN indexes even among spatially closer stations. NH 3-N comes next due to the identical pollution level and degradation process in a certain spatial extension. Meanwhile, DO shows good regional connectivity in line with the strong diffusivity. However, the CN characteristic is relatively inconspicuous in large basins and nationwide scale, which indicates the regional impact on water quality fluctuation and CN analysis. These original findings boost a comprehensive understanding of water quality dynamics and enlighten novel methods for environment system analysis and watershed management.

Remotely sensed evapotranspiration (ETRS) is increasingly used for streamflow estimation. Earlier reports are conflicting as to whether ETRS is useful in improving streamflow estimation skills. We believe that it is because earlier works used calibrated models and explored only small subspaces of the complex relationship between model skills for streamflow (Q) and ET. To shed some light on this complex relationship, we design a novel randomized, large sample experiment to explore the full ET-Q skill space, using seven catchments in Vietnam and four global ETRS products. For each catchment and each ETRS product, we employ 10,000 SWAT (Soil and Water Assessment Tool) model runs whose parameters are randomly generated via Latin Hypercube sampling. We then assess the full joint distribution of streamflow and ET skills using all model simulations. Results show that the relationship between ET and streamflow skills varies with regions, ETRS products, and the selected performance indices. This relationship even changes with different ranges of ET skills. Parameter sensitivity analysis indicates that the most sensitive parameters could have opposite contributions to ET and streamflow skills. Conditional probability assessment reveals that with certain ETRS products, the probabilities of having good streamflow skills are high and increase with better ET skills, but for other ETRS products, good model skills for streamflow are only achievable with certain intermediate ranges of ET skills, not the best ones. Overall, our study provides a useful approach for evaluating the value of ETRS for streamflow estimation.

Recent studies have demonstrated that it is possible to combine machine learning with data assimilation to reconstruct the dynamics of a physical model partially and imperfectly observed. The surrogate model can be defined as an hybrid combination where a physical model based on prior knowledge is enhanced with a statistical model estimated by a neural network. The training of the neural network is typically done offline, once a large enough dataset of model state estimates is available. By contrast, with online approaches the surrogate model is improved each time a new system state estimate is computed. Online approaches naturally fit the sequential framework encountered in geosciences where new observations become available with time. In a recent methodology paper, we have developed a new weak-constraint 4D-Var formulation which can be used to train a neural network for online model error correction. In the present article, we develop a simplified version of that method, in the incremental 4D-Var framework adopted by most operational weather centres. The simplified method is implemented in the ECMWF Object-Oriented Prediction System, with the help of a newly developed Fortran neural network library, and tested with a two-layer two-dimensional quasi geostrophic model. The results confirm that online learning is effective and yields a more accurate model error correction than offline learning. Finally, the simplified method is compatible with future applications to state-of-the-art models such as the ECMWF Integrated Forecasting System.

Rock glaciers manifest the creep of mountain permafrost occurring in the past or at present. Their presence and dynamics are indicators of permafrost distribution and changes in response to climate forcing. Knowledge of rock glaciers is completely lacking in the West Kunlun, one of the driest mountain ranges in Asia, where widespread permafrost is rapidly warming. In this study, we first mapped and quantified the kinematics of active rock glaciers based on satellite Interferometric Synthetic Aperture Radar (InSAR) and Google Earth images. Then we trained DeepLabv3+, a deep learning network for semantic image segmentation, to automate the mapping task. The well-trained model was applied for a region-wide, extensive delineation of rock glaciers from Sentinel-2 images to map the landforms that were previously missed due to the limitations of the InSAR-based identification. Finally, we mapped 413 rock glaciers across the West Kunlun: 290 of them were active rock glaciers mapped manually based on InSAR and 123 of them were newly identified and outlined by deep learning. The rock glaciers are categorized by their spatial connection to the upslope geomorphic units. All the rock glaciers are located at altitudes between 3,389 m and 5,541 m with an average size of 0.26 km2 and a mean slope angle of 17°. The mean and maximum surface downslope velocities of the active ones are 24 cm yr-1 and 127 cm yr-1, respectively. Characteristics of the rock glaciers of different categories hold implications on the interactions between glacial and periglacial processes in the West Kunlun.

The polar cap can become teardrop shaped through the poleward expansion of the dusk and dawn sectors of the auroral oval, to form what is called horse collar aurora (HCA). The formation of HCA has been linked to dual-lobe reconnection (DLR) where magnetic flux is closed at the dayside magnetopause. A prolonged period of northward IMF is required for the formation of HCA. HCA have previously been identified in UV images captured by the Special Sensor Ultraviolet Spectrographic Imager (SSUSI) instrument on-board the Defense Meteorological Satellite Program (DMSP) spacecraft F16, F17 and F18. Events that have concurrent 630.0 nm all-sky camera (ASC) data from the Redline Geospace Observatory (REGO) Resolute Bay site are now studied in more detail, making use of the higher cadence of the ASC images compared to DMSP/SSUSI. 11 HCA events are studied and classified based on the IMF conditions at the end of the event. Five of the events were found to end via a southward turning of the IMF, two end with positive By dominated IMF and four with negative By dominance. Under positive (negative) By the arcs move duskward (dawnward) in the northern hemisphere with the opposite true in the southern hemisphere. Under a southward turning the arcs move equatorward. One event is of particular interest as it occurred while there was a transpolar arc (TPA) also present. Understanding the evolution of HCA will allow DLR to be studied in more detail.

Freeboardelevation of a structure above the base flood elevation (BFE)is a critical component in mitigating or avoiding flood losses. However, the unrevealed benefits and savings of freeboard installation have prevented communities from adopting this approach. To improve decision-making for flood-vulnerable communities and enhance flood risk mitigation strategies, this study presents the methodology underlying a new webtool, FloodSafeHome, that estimates comprehensively the economic benefits and savings of freeboard installation for new construction of residential buildings. Specifically, the proposed evaluation framework has been designed to calculate monthly savings for individual buildings by assessing freeboard cost, insurance savings per year, and expected annual flood loss. This new evaluation method is built into a web-based, decision-making tool for use by the public and community leaders in three southeastern Louisiana parishes, to identify expected future benefits of building residences with freeboard and enhance their decision-making processes with interactive risk/benefit analysis features. For example, results indicate the levels of freeboard that optimize the costbenefit ratio for flood-insured homes in the study area. This approach is expected to improve long-term flood resilience and provide cost-efficient flood mitigation strategies particularly in disaster vulnerable regions.

Manganese (Mn) is an essential element for photosynthetic life, yet concentrations in Southern Ocean open waters are very low, resulting from biological uptake along with limited external inputs. At southern latitudes, waters overlying the Antarctic shelf are expected to have much higher Mn concentrations due to their proximity to external sources such as sediment and sea ice. In this study, we investigated the potential export of Mn-rich Antarctic shelf waters toward depleted open Southern Ocean waters. Our results showed that while high Mn concentrations were observed over the shelf, strong biological uptake decreased dissolved Mn concentrations in surface waters north of the Southern Antarctic Circumpolar Current Front (< 0.1 nM), limiting export of shelf Mn to the open Southern Ocean. Conversely, in bottom waters, mixing between Mn-rich Antarctic Bottom Waters and Mn-depleted Low Circumpolar Deep Waters combined with scavenging processes led to a decrease in dissolved Mn concentrations with distance from the coast. Subsurface dissolved Mn maxima represented a potential reservoir for surface waters (0.3 – 0.6 nM). However, these high subsurface values decreased with distance from the coast, suggesting these features may result from external sources near the shelf in addition to particle remineralization. Overall, these results imply that the lower-than-expected lateral export of trace metal-enriched waters contributes to the extremely low (< 0.1 nM) and potentially co-limiting Mn concentrations previously reported further north in this Southern Ocean region.

The geometry of the Antarctic-Phoenix Plate system, with the Antarctic Plate forming both the overriding plate and the conjugate to the subducting oceanic plate, allows quantification of slab age and convergence rate back to the Paleocene and direct comparison with the associated magmatic arc. New Ar-Ar data from Cape Melville (South Shetland Islands, SSI) and collated geochronology shows Antarctic arc magmatism ceased at ~19 Ma. Since the Cretaceous, the arc front remained ~100 km from the trench whilst its rear migrated trenchward at 6 km/Myr. South of the SSI, arc magmatism ceased ~8–5 Myr prior to each ridge-trench collision, whilst on the SSI (where no collision occurred) the end of arc magmatism predates the end of subduction by ~16 Myr. Despite the narrowing and successive cessation of the arc, geochemical and dyke orientation data shows the arc remained in a consistently transitional state of compressional continental arc and extensional backarc tectonics. Numerically relating slab age, convergence rate, and slab dip to the Antarctic-Phoenix Plate system, we conclude that the narrowing of the arc and the cessation of magmatism south of the South Shetland Islands was primarily in response to the subduction of progressively younger oceanic crust, and secondarily to the decreasing convergence rate. Increased slab dip beneath the SSI migrated the final magmatism offshore. Comparable changes in the geometry and composition are observed on the Andean arc, suggesting slab age and convergence rate may affect magmatic arc geometry and composition in settings currently attributed to slab dip variation.

This is a comment on the Boone et al. (2022) article. The authors analyzed spaceborne observations of stratospheric aerosol in 2019-2020 . They concluded, the dominating aerosol type was volcanic sulfate aerosol. They critisized Raman lidar observations of Ohneiser et al. (2021) and Ansmann et al. (2021). These authors classified the aerosol as wildfire smoke. Boone et al. (2022) stated that this classification is wrong. In this article, we clearly show that the dominant aerosol type was wildfire smoke.

Process-based land surface models are important tools for estimating global wetland methane (CH4) emissions and projecting their behavior across space and time. So far there are no performance assessments of model responses to drivers at multiple time scales. In this study, we apply wavelet analysis to identify the dominant time scales contributing to model uncertainty in the frequency domain. We evaluate seven wetland models at 23 eddy covariance tower sites. Our study first characterizes site-level patterns of freshwater wetland CH4 fluxes (FCH4) at different time scales. A Monte Carlo approach has been developed to incorporate flux observation error to avoid misidentification of the time scales that dominate model error. Our results suggest that 1) significant model-observation disagreements are mainly at short- to intermediate time scales (< 15 days); 2) most of the models can capture the CH4 variability at long time scales (> 32 days) for the boreal and Arctic tundra wetland sites but have limited performance for temperate and tropical/subtropical sites; 3) model error approximates pink noise patterns, indicating that biases at short time scales (< 5 days) could contribute to persistent systematic biases on longer time scales; and 4) differences in error pattern are related to model structure (e.g. proxy of CH4 production). Our evaluation suggests the need to accurately replicate FCH4 variability in future wetland CH4 model developments.

In-situ measurements of the trade cumulus boundary layer turbulence structure are compared across large-scale circulation conditions and cloud horizontal organizations during the EUREC4A-ATOMIC campaign. The vertical structure of turbulent (e.g. vertical velocity variance, total kinetic energy) and flux (e.g. sensible, latent, and buoyancy) quantities are derived and investigated using the WP-3D aircraft stacked level legs (cloud modules).The 16 cloud modules aboard the P-3 were split into three groups according to cloud top height and column-integrated TKE and vertical velocity variance. These groups map onto qualitative cloud features related to object size and clustering over a scale of 100 km. This grouping also correlates to the large scale forcings of surface windspeed and low-level divergence on the scale of a few hundred km. The ratio cloud top to trade inversion base height is consistent across the groups at around 1.18. The altitude of maximum turbulence is 0.75-0.85 of cloud top height. The consistency of these ratios across the groups may point to the underlying coupling between convection, dissipation, and boundary layer thermodynamic structure. The following picture of turbulence and cloud organization is proposed: (1) light surface winds and turbulence which decreases from the sub-cloud mixed layer (ML) with height generates clouds with generally uniform spacing and smaller features, then (2) as the surface winds increase, convective aggregation occurs, and finally (3), if surface convergence occurs, convection and turbulence reach higher altitudes, producing higher clouds which may precipitate and create colds pools. Observations are compared to a CAM simulation is run over the study period, nudged by ERA5 winds and surface pressure. CAM produces higher column integrated turbulent kinetic energy and larger maximum values on the days where higher cloud tops are observed from the aircraft, which is likely a factor that influences the development of deeper clouds in the model. However, CAM places the peak turbulence 500 m lower than observed, suggesting there may be a bias in CAM representation of turbulence and moisture transport. CAM also does not capture the large LHFs seen for two of the days in which lower cloud tops are observed, which could result in insufficient lower free tropospheric moistening in the model during this type of cloud organization. A large and consistent bias between the model and observations for all cloud groups is the negative SHFs produced in CAM near 1500 m. This is not observed in the measurements. This leads to a net negative buoyancy flux not observed and provides evidence of a specific shortcoming that can be addressed as part of the needed improvement in the representation of clouds by large-scale models.

The effect of climate change on precipitation intensity is well documented. However, findings regarding changes in spatial extent of extreme precipitation events are still ambiguous as previous studies focused on particular regions and time domains. This study addresses this ambiguity by investigating the pattern of changes in the spatial extent of short duration extreme precipitation events globally. A grid-based indicator termed Spatial-Homogeneity (SH) is proposed and used to assess the changes of spatial extent in Global Precipitation Measurement (GPM) records. This study shows that i) rising temperature causes significant shrinking of precipitation extent in tropics, but an expansion of precipitation extent in arid regions, ii) storms with higher precipitation intensity show a faster decrease in spatial extent, iii) larger spatial extent storms are associated with higher total precipitable water. Results imply that in a warming climate, tropics may experience severe floods as storms may become more intense and spatially concentrated.

Extreme heat waves beset western North America during 2021, including a 46.7°C (116°F) observation in Portland, Oregon, an astonishing 5°C above the previous record. Using Portland as an example we provide evidence for a latent risk of extreme heat waves in the Pacific Northwest (PNW) and along the west coast of the United States where a maritime climate and its intrinsic variations yield a positive skewness in summertime daily maximum temperatures. A generalized Pareto extreme value analysis yields a heavy tailed distribution with a return period of 300-1000 years, indicating that, while rare, the event was possible, contrary to prior claims that the event was “virtually impossible”. We demonstrate that the extreme temperatures can be explained by the coincident extreme values of geopotential heights, and that the relationship between heights and extreme temperatures has not materially changed over the observational record. The dynamical nature of the event along with recent developments in stochastic theory justifies the use of skewed and heavy-tailed distributions which may provide the basis for a more proactive approach to managing the risk of future events.

One of the most prominent plate tectonic processes is seafloor spreading. But its formation processes are poorly understood. In this study, we thoroughly address how the brittle-ductile weakening process affects the formation and development of tectonic patterns at spreading centers using 3D magmatic-thermomechanical numerical models. Grain size evolution and brittle/plastic strain weakening are fully coupled into the model. A spectrum of tectonic patterns, from asymmetric long-lived detachment faults in rolling-hinge mode, short-lived detachment faults in flip-flop mode, to symmetric conjugate faults in flip-flop mode are documented in our models. Systematic numerical results indicate that fault strength reduction and axial brittle layer thickness are two pivotal factors in controlling the faulting patterns and spreading modes. Strain weakening induced by localized hydrothermal alteration can lead to the variation of the fault strength reduction. Strong strain weakening with large fault strength reduction results in very asymmetric detachment faults developing in rolling-hinge mode, while weak strain weakening leads to small fault strength reduction, forming conjugate faults. Moreover, the thermal structure beneath the ridge is influenced by spreading rates, hydrothermal circulation, and mantle potential temperature, which in turn controls the thickness of the axial brittle layer and results in variation in tectonic patterns. Further, in order to test a damage mechanism with a physical basis, we investigate grain size reduction at the root of detachment faults. We found that its effect in the formation of detachment faults appears to play a subordinate role compared to brittle/plastic strain weakening of faults.

Heatwaves occurred frequently in summers, severely harming natural environment and human society. While a few long-term spatiotemporal heatwave studies have been conducted in China at the grid scale, their shortcomings involve discrete distribution and poor spatiotemporal continuity. We used daily data of 691 meteorological stations to obtain torridity index (TI) and heatwave index (HWI) datasets (0.01°), to evaluate the spatiotemporal distribution of heatwaves in Chinese mainland for 1990-2019. The results were as follows: (1) TI rose but with fluctuations. The largest increase occurred in North China in July. Areas with hazard levels of medium and above accounted for 22.16%, mainly in the eastern and southern provinces of China, South Tibet, East and South Xinjiang, and Chongqing. The hazard indicators in Chongqing and central Zhejiang were at especially high levels, which is concerning. (2) Average heatwave frequency, intensity, and duration reached relatively high levels of 6-8, 20-25, and 11-16, respectively, in East and South Xinjiang and Southeast Tibet. (3) The study areas were divided into four categories according to the spatiotemporal distribution of hazards. The “high hazard and rapidly increasing” and “low hazard and keep increasing” areas accounted for 8.71% and 41.33%, respectively. (4) The proportions of units with significantly increased average hazard (AH) at city and county levels were 57% and 68%, respectively. Jinhua, Zhengzhou, Nanchang, Wuhan, Shaoxing, Changsha, Shijiazhuang, Nanjing, Wuxi, and Changzhou accounted for the top 10 AH among the 49 first-tier, new first-tier, and second-tier cities. “Ten Furnaces” at the top of the provincial capitals were Zhengzhou, Nanchang, Wuhan, Changsha, Shijiazhuang, Nanjing, Hangzhou, Haikou, Chongqing, and Hefei. Suzhou’s AH rose the fastest. While the strategy of west development and of revitalizing northeast China progressed, and the urbanization level and population aging of developed areas were further developed, the continuously increasing heatwave hazard should be fully considered.

The effects of sphericity are regularly neglected in numerical and laboratory studies that examine the factors controlling subduction dynamics. Most existing studies have been executed in a Cartesian domain, with the small number of simulations undertaken in a spherical shell incorporating plates with an oversimplified rheology, limiting their applicability. Here, we simulate free-subduction of composite visco-plastic plates in 3-D Cartesian and spherical shell domains, to examine the role of sphericity in dictating the dynamics of subduction, and highlight the limitations of Cartesian models. We identify two irreconcilable differences between Cartesian and spherical models, which limit the suitability of Cartesian-based studies: (i) the presence of sidewall boundaries in Cartesian models, which modify the flow regime; and (ii) the reduction of space with depth in spherical shells, alongside the radial gravity direction, which cannot be captured in Cartesian domains. Although Cartesian models generally predict comparable subduction regimes and slab morphologies to their spherical counterparts, there are significant quantitative discrepancies. We find that simulations in Cartesian domains that exceed Earth’s dimensions overestimate trench retreat. Conversely, due to boundary effects, simulations in smaller Cartesian domains overestimate the variation of trench curvature driven by plate width. Importantly, spherical models consistently predict higher sinking velocities and a reduction in slab width with depth, particularly for wider subduction systems, enhancing along-strike slab buckling and trench curvature. Results imply that sphericity must be considered when simulating Earth’s subduction systems, and that it is essential for accurately predicting the dynamics of subduction zones of width ~2400 km or more.

The distribution of a mosaic of biological soil crusts (BSCs) and shrubs is a common landscape surface feature in temperate deserts. With the continued climatic change, the desert shrub experiences varying rates of mortality which has serious negative impacts on soil structure and functions. However, it is not clear whether BSCs, which develop extensively in areas under shrub canopies, can mitigate the effects of shrub mortality on soil nutrient multifunctionality. Therefore, in this study, the Gurbantungut Desert, a typical temperate desert in northern China, was selected as the study area, and the dominant shrubs, Ephedra przewalskii shrub, and the moss crust were used as the study objects. Soil samples were collected from the bare sand and moss crusts under the living shrub and the dead shrub and analyzed to determine their carbon, nitrogen, phosphorus, and potassium contents. The results showed that the shrub mortality reduced the soil moisture content, pH, electric conductivity, and carbon, nitrogen, phosphorus, and potassium contents in the bare sand compared with the bare sand under the living shrub. The presence of the moss crust greatly mitigated the negative impacts of shrub mortality on soil carbon, nitrogen, phosphorus, and potassium contents, and the nutrient multifunctionality of the moss crust was only reduced by 4.01% compared with the reduction by bare sand (67.42%) after shrub mortality. The results of SEM analysis showed that with the coexistence of shrubs and crust, the effect of shrubs on soil multifunctionality was much stronger than that of the moss crust; compared with available nutrients, the total nutrient content was the most important factor driving changes in soil nutrient multifunctionality. In conclusion, in desert ecosystems with degraded shrubs, moss crusts can mitigate the reduction in soil nutrient contents caused by shrub degradation and, therefore, maintain the soil stability and nutrient multifunctionality as a “substitute”.

We built an integrated nonlinear analysis software -INA- designed to study space plasma turbulence and intermittency. The MATLAB programming environment was used for the algorithmic development and implementation of methods for spectral analysis, multiscale fluctuations and multifractal analysis. The performance of INA is demonstrated using magnetic field measurements from the Cluster 3 spacecraft during an inbound pass through the Earth’s magnetosheath region. We show how specific features of the power spectral density (PSD) can be mapped to localised time-frequency regions in the spectrogram representation, and identify multiple intermittent events using the wavelet-based local intermittency measure (LIM). Multiscale probability density functions (PDFs) showed clear departures from Gaussianity, signifying the presence of intermittency. Structure functions (SFs) and rank-ordered multifractal analysis (ROMA) revealed the multifractal nature of the analysed signal. INA is freely distributed as a standalone executable file to any interested user, and provides an integrated, interactive, and user-friendly environment in which one can import a dataset, customize key analysis parameters, apply multiple methods on the same signal and then export high-quality, publication-ready figures. These are only a few of the many distinguishing features of INA.