Observed rapid Arctic warming and sea-ice loss are likely to continue in the future, unless and after greenhouse gas emissions are reduced to net-zero. Here, we examine the possible effects of future sea-ice loss at 2°C global warming above pre-industrial levels on winter temperature extremes across the Northern Hemisphere, using coordinated experiments from the Polar Amplification Model Intercomparison Project. 1-in-20-year cold extremes are simulated to become less severe at high- and mid-latitudes in response to Arctic sea-ice loss. 1-in-20-year winter warm extremes become warmer at northern high latitudes due to sea-ice loss, but warm by less than cold extremes. We compare the response to sea-ice loss to that from global SST change also at 2°C global warming. SST change causes less severe cold extremes and more severe warm extremes globally. Except northern high latitudes, the response to SST change is of larger magnitude than that to Arctic sea-ice loss.

Soil moisture influences near-surface air temperature by partitioning downwelling radiation into latent and sensible heat fluxes, through which dry soils generally lead to higher temperatures. The strength of this coupled soil moisture-temperature (SM-T) relationship is not spatially uniform, and numerous methods have been developed to assess SM-T coupling strength across the globe. These methods tend to involve either idealized climate-model experiments or linear statistical methods which cannot fully capture nonlinear SM-T coupling. In this study, we propose a nonlinear machine learning-based approach for analyzing SM-T coupling and apply this method to various mid-latitude regions using historical reanalysis datasets. We first train convolutional neural networks (CNNs) to predict daily maximum near-surface air temperature (TMAX) given daily SM and geopotential height fields. We then use partial dependence analysis to isolate the average sensitivity of each CNN’s TMAX prediction to the SM input under daily atmospheric conditions. The resulting SM-T relationships broadly agree with previous assessments of SM-T coupling strength. Over many regions, we find nonlinear relationships between the CNN’s TMAX prediction and the SM input map. These nonlinearities suggest that the coupled interactions governing SM-T relationships vary under different SM conditions, but these variations are regionally dependent. We also apply this method to test the influence of SM memory on SM-T coupling and find that our results are consistent with previous studies. Although our study focuses specifically on local SM-T coupling, our machine learning-based method can be extended to investigate other coupled interactions within the climate system using observed or model-derived datasets.

Numerical wave models have been developed to reproduce the evolution of waves generated in all directions and over a wide range of wavelengths. The amount of wave energy in the different directions and wavelength is the result of a number of physical processes that are not well understood and that may not be represented in parameterizations. Models have generally been tuned to reproduce dominant wave properties: significant wave height, mean direction, dominant wavelengths. A recent update in wave dissipation parameterizations has shown that it can produce realistic energy levels and directional distribution for shorter waves too. Here we show that this new formulation of the wave energy sink can reproduce the variability of measured infrasound power below a frequency of 2 Hz, associated with a large energy level of waves propagating perpendicular to the wind, for waves with frequencies up to at least 1 Hz. The details are sensitive to the balance between the non-linear transfer of energy away from the wind direction, and the influence of dominant and relatively long waves on the dissipation of shorter waves in other directions.

Continent-scale observations of seismic phenomena have provided multi-scale constraints of the Earth’s interior. Of those analysed, array-based observations of slowness vector properties (backazimuth and horizontal slowness) and multipathing have yet to be made on a continental scale. Slowness vector measurements give inferences on mantle heterogeneity properties such as velocity perturbation, velocity gradient strength and quantify their effect on the wavefield. Multipathing is a consequence of waves interacting with strong velocity gradients resulting in two arrivals that arrive with different slowness vector properties and times. The mantle structure beneath the contiguous Unites States has been thoroughly analysed by seismic studies and is data-rich, making it an excellent testing ground to analyse mantle structure with our approach and compare with other techniques. We apply an automated array-analysis technique to an SKS dataset to create the first continent-scale dataset of multipathing and slowness vector measurements. We analyse the divergence of the slowness vector deviation field to highlight seismically slow and fast regions in our data. Our results resolve several slow mantle anomalies beneath Yellowstone, the Appalachian mountains and fast anomalies throughout the mantle. Many of the anomalies cause multipathing in frequency bands 0.15–0.30 and 0.20–0.40 Hz which suggests velocity transitions over at most 500 km exist. Comparing our observations to synthetics created from tomography models, we find model NA13 \citeA{bedle_continental_2021} fits our data best but differences still remain. We therefore suggest slowness vector measurements should be used as an additional constraint in tomographic inversions and will lead to better-resolved models of the mantle.

Pigmentary hematite carries important signals in paleomagnetic and paleoenvironmental studies. However, weak magnetism and the assumption that it has high magnetic coercivity prevents prevents routine identification of the size distribution of pigmentary hematite, especially for fine particle sizes. We present a strategy for estimating joint hematite particle volume and microcoercivity (f (V, Hk0)) distributions from low-temperature demagnetization curves and thermal fluctuation tomography (TFT) of pigmentary hematite in bulk samples of Triassic-Jurassic Inuyama red chert, Japan. The coercivity of the pigmentary hematite increases exponentially with decreasing temperature, following a modified Kneller’s law, where microcoercivity has a wide but approximately symmetric distribution in logarithmic space from ~1 tesla to tens of tesla. All of the red chert samples contain stable single domain (SSD) hematite with 35 - 160 nm diameter; a significant superparamagnetic (SP) hematite population with sizes down to several nanometers also occurs in Jurassic samples. The SP/SSD threshold size is estimated to be 8 - 18 nm in these samples. The fine particle size of the pigmentary hematite is evident in its low median unblocking temperature (194 °C to 529 °C) and, thus, this hematite may contribute to all four paleomagnetic components identified in published thermal magnetization studies of the Inuyama red chert. In this work, uniaxial anisotropy and magnetization switching via coherent rotation are assumed. Uniaxial anisotropy is often dominant in fine-grained hematite, although the dominant anisotropy type should be evaluated before using TFT. This approach is applicable to studies that require knowledge of coercivity and size distributions of hematite pigments.

The Moho is the interface between crust and mantle, and accurate location of the Moho is important for both resource exploration and deep earth condition and structural change investigations. The Parker-Oldenburg (P-O) method, is simple and efficient and thus has been extensively applied in the frequency domain and for Moho depth inversion. However, Moho fluctuation simulations using the P-O method are not reliable because of the lack of field geographic data constraints during the inversion process and excessively smoothing of data details caused by using a filter to correct the source data signals. To solve those problems, we propose an improved iteration P-O method with variable density, the iterative process is constrained by geological data in the inversion parameters, and the variable depth of the gravity interface is iterated using an equivalent form of upward continuation in the Fourier domain, which is more stable and convergent than downward continuation term in original P-O method. Synthetic experiments indicate that improved method has the better consistency among the simulations than original method, and our improved method has the smallest RMS of 0.59 km. In a real case, we employed the improved method to invert the Moho depth of the South China Sea, and the RMS between our Moho model and the seismological data is the smallest value of 3.87 km. The synthetic experiments and application of the model to the SCS further prove that our method is practical and efficient.

Parameterizations for bottom shear stress are required to predict sediment resuspension from field observations and within numerical models that do not resolve flow within the viscous sublayer. This study assessed three observation-based bottom shear stress (τb) parameterizations, including (1) the sum of surface wave stress and mean current (quadratic) stress (τb= τw +τc); (2) the log-law (τb= τL); and (3) the turbulent kinetic energy (τb= τTKE); using two years of observations from a large shallow lake. For this system, the parameterization τb= τw +τc was sufficient to qualitatively predict resuspension, since bottom currents and surface wave orbitals were the two major processes found to resuspend bottom sediments. However, the τL and τTKE parameterizations also captured the development of a nepheloid layer within the hypolimnion associated with high-frequency internal waves. Reynolds-averaged Navier-Stokes (RANS) equation models parameterize τb as the summation of modeled current-induced bottom stress (τc,m) and modelled surface wave-induced bottom stress (τw,m). The performance of different parameterizations for τc,m and τw,m in RANS models was assessed against the observations. The optimal parameterizations yielded root-mean-square errors of 0.031 and 0.025 Pa, respectively, when τc,m, and τw,m were set using a constant canonical drag coefficient. A RANS-based τL parameterization was developed; however, the grid-averaged modelled dissipation did not always match local observations, leading to O(10) errors in prediction of bottom stress. Turbulence-based parameterizations should be further developed for application to flows with mean shear-free boundary turbulence.

This research targets disentangling shallow causes of anthropogenically-induced subsidence in a reclaimed and urbanized coastal plain. The study area is around the city of Almere, in the South Flevoland polder, the Netherlands, which is among the countries’ fastest subsiding areas. The procedure consists of integrating synthetic Interferometric Synthetic Aperture Radar (InSAR) data with high-resolution phreatic groundwater and lithoclass models, and a database containing construction details. The two main parts of the workflow are isolation of the InSAR points of structures without a pile foundation and a data assimilation procedure by Ensemble Smoothing with Multiple Data Assimilation. The shrinkage of surficial clay beds by phreatic groundwater level lowering is identified to be the main cause of shallow subsidence in the area, with an average contribution of 6 mm/year. The history-matched physics-based model predicts that one meter drop in phreatic groundwater level now translates into 10 millimeter of subsidence in the next five years. Also, this study showed that a groundwater deficiency due to severe dry periods should be considered as an accelerator of subsidence in both the short- and long-term planning. To ensure a robust network to estimate future subsidence, we advise on a consistent monitoring strategy of the phreatic groundwater level.

This paper describes the development of the fluxgate magnetometer on the Fengyun-4B satellite. The Fengyun-4 is the second generation of China’s geostationary orbit satellite with the function of monitoring the space environment in GEO orbit. A fluxgate magnetometer (FGM) is deployed on this satellite to observe the magnetic field as a necessary input to space weather forecasting. This payload adopts three 3-axis fluxgate sensors to obtain space magnetic field data by excluding the satellite’s interference. Each three-axis fluxgate sensor has an independent signal processing circuit. FGM uses digital signal processing technology to acquire magnetic field signals. First, the analog signal is oversampled using a high-speed ADC, then digital signal processing, such as phase-sensitive demodulation, integration, and filtering, is performed inside the FPGA, and the feedback signal is output to the feedback coil through the DAC. This signal processing loop constitutes an ADC system, and the quantization accuracy of the output digital quantity can reach 18 bits. the FGM performs in-orbit calibration during satellite rotation maneuver and Alfven wave events. Comparison with the GOES-16 satellite and Tsyganenko magnetic field model proves FGM to be effective in monitoring the magnetic field of the space environment. Through joint observations with GOES-16 satellite and geomagnetic stations, FY-4B describes the development of a typical magnetic storm on November 4, 2021. The Ground calibration and in-orbit preliminary results show the FY-4B satellite magnetometer outputs 20 bits of digital resolution data at a 30 Hz sampling rate, with the noise lower than 3×10-4nT2/Hz@1Hz in the ±600nT range.

Eyewall replacements occur in 70% of major tropical cyclones (TCs), and are associated with rapid changes in storm intensity and rapid broadening of strong winds. In this study, we present to use the radial gradient of absolute angular momentum with Holland’s wind profile as a simple diagnostic for eyewall replacement as internal variability of the storm. The diagnostic is solely dependent on the maximum wind speed, the radius of maximum wind, and the latitude and found to coincident with 70% of satellite observed concentric eyewalls for 1991-2020. The diagnostic can be expressed as a latitude-irrelevant Rossby Number of primary eyewall, varying with the peakedness of wind. It highlights the importance of pressure-wind relationship in eyewall replacement and provides a valuable tool to improve the understanding, modeling and risk assessment of storms with eyewall replacements.

Winter cold spells over North America have been correlated with European wind extremes, but the physical mechanisms behind such “pan-Atlantic” compound extremes have not been clarified yet. In this study, we propose that pan–Atlantic cold and windy extremes occur following two possible dynamical pathways. The first one involves the propagation of a Rossby wave train from the Pacific Ocean, associated with windstorms over north-western Europe in the 5-10 days after the cold spell peak. The second is associated with a high-latitude anticyclone over the North Atlantic and an equatorward-shifted jet, leading to windstorms over south-western Europe already in the days preceding the cold spell peak. European windstorms are thus consistently tied to North American cold spells according to the different flow configuration. The analysis underscores that seemingly similar surface extremes may be driven by different processes, and that overlooking these subtleties and conflating them together could lead to misleading conclusions.

This study evaluates high-latitude stratiform mixed-phase clouds (SMPC) in the atmosphere model of the newly released Energy Exascale Earth System Model version 2 (EAMv2) by utilizing one-year-long ground-based remote sensing measurements from the U.S. Department of Energy Atmospheric Radiation and Measurement (ARM) Program. A nudging approach is applied to model simulations for a better comparison with the ARM observations. Observed and modeled SMPCs are collocated to evaluate their macro- and microphysical properties at the ARM North Slope of Alaska (NSA) site in the Arctic and the McMurdo (AWR) site in the Antarctic. We found that EAMv2 overestimates (underestimates) SMPC frequency of occurrence at the NSA (AWR) site nearly all year round. However, the model captures the observed larger cloud frequency of occurrence at the NSA site. For collocated SMPCs, the annual statistics of observed cloud macrophysics are generally reproduced at the NSA site, while at the AWR site, there are larger biases. Compared to the AWR site, the lower cloud boundaries and the warmer cloud top temperature observed at NSA are well simulated. On the other hand, simulated cloud phases are substantially biased at each location. The model largely overestimates liquid water path at NSA, whereas it is frequently underestimated at AWR. Meanwhile, the simulated ice water path is underestimated at NSA, but at AWR, it is comparable to observations. As a result, the observed hemispheric difference in cloud phase partitioning is misrepresented in EAMv2. This study implies that continuous improvement in cloud microphysics is needed for high-latitude mixed-phase clouds.

The lower cell of the meridional overturning circulation (MOC) is sourced by dense Antarctic Bottom Water (AABW), which forms and sinks around Antarctica and subsequently fills the abyssal ocean. For the MOC to ‘overturn’, these dense waters must upwell through mixing with lighter waters above. Here, we investigate the processes underpinning such mixing, and the resulting water mass transformation, using an observationally forced, high-resolution numerical model of the Drake Passage in the Southern Ocean. In the Drake Passage, the mixing of dense AABW formed in the Weddell Sea with lighter deep waters transported from the Pacific Ocean by the Antarctic Circumpolar Current is catalysed by energetic flows impinging on rough topography. We find that multiple topographic interaction processes act to facilitate mixing of the two water masses, ultimately resulting in upwelling of waters with neutral density greater 28.19 kg m-3, and downwelling of the lighter waters above. In particular, we identify the role of sharp density interfaces between AABW and overlying waters, and find that the dynamics of the interfaces’ interaction with topography can enhance mixing. Such sharp interfaces between water masses have been observed in several parts of the global ocean, but are unresolved and unrepresented in ocean and climate models. We suggest that they are likely to play an important role in abyssal dynamics and mixing, and therefore require further exploration.

Polynyas play an important role in climate change with an efficient exchange of heat and matter between the atmosphere and the ocean in polar regions. This study investigated the influence of strong tides and atmospheric forcing on the Amundsen Sea Polynya, especially focusing on large-area polynya events from 2002 to 2020. We found that the geographical locations of the polynyas are closely related to the underwater ridge, where tidal currents are relatively strong. More importantly, strong cross-ridge winds are the “triggers” above the sea surface for the initial formation of the Amundsen Sea Polynya, while strong tides under the sea surface tend to create large-area polynya. Four of the five largest polynya events occurred mainly during spring tides. Only the 2016 event occurred during the normal tide period, which was atmosphere-dominated. Strong tides significantly affect the evolution of polynyas by strengthening the vertical mixing of seawater. Given that ocean in Antarctica might become warmer, tidal mixing might enhance the mixing in the future climate.

Long-term atmospheric water vapor hydrogen (δ2H), oxygen (δ18O), and deuterium excess (d-excess) can provide unique insights into the land-atmosphere coupling processes. The in-situ measurements of atmospheric water vapor δ2H, δ18O, and d-excess were conducted above a reed wetland of Liaodong Bay (2019-2020). We found significant inter-annual variations in atmospheric water vapor isotopes between the two growing (May-September) seasons. The δ2H, δ18O, and d-excess of atmospheric water vapor exhibited different seasonal and diurnal cycles respect to the vertical (i.e., 1 m, 3 m, and 5 m) measurement heights, especially in 2019. The isotopic differences of atmospheric water vapor among vertical measurement heights were more evident in the daytime (8:00-20:00 LST) than at night (20:00-8:00 LST). Rainfall events had a direct impact on the diurnal patterns of water vapor isotopes, and the influences depended on rainfall intensities. However, only week correlations existed between water vapor isotopes and local meteorological factors (R2 = 0.01-0.16, P < 0.001), such as water vapor concentration (w), relative humidity (RH), and surface air temperature (Ta). Based on the back-air trajectory analyses, the spatial-temporal dynamics of atmospheric water vapor isotopes highly synchronized with monsoon activities. The dominant air masses in this region mainly arose from ocean sources, which contributed to 62.1 ± 12.2% (49.4-84.5%) of the total air moisture. High d-excess consistently followed the strong monsoon activities, suggesting predominating impacts of ocean air masses from the East Asian monsoon region. High-resolution measurements of atmospheric water vapor isotopes will improve our understanding of the hydrological cycles in coastal areas.

Seagrass meadows are effective carbon sinks due to their high primary production and sequestration in sediments. However, methane (CH4) fluxes can partially counteract their carbon sink capacity. Here, we measured diffusive sediment-water and air-sea CO2 and CH4 fluxes in a coastal embayment dominated by Posidonia oceanica in the Mediterranean Sea. High resolution timeseries observations revealed large spatial and temporal variability in CH4 concentrations (2 to 36 nM). Higher emissions were observed in an area with dense seagrass meadows. A 6 − 40% decrease of CH4 concentration in the surface water around noon indicates that photosynthesis likely limits CH4 fluxes. Sediments were the major CH4 source as implied from radon (a natural porewater tracer) observations and evidence for methanogenesis in deeper sediments. CH4 sediment-water fluxes (0.1 ± 0.1 − 0.4 ± 0.1 µmol m-2 d-1) were higher than average water-air CH4 emissions (0.12 ± 0.10 µmol m-2 d-1), suggesting that dilution and CH4 oxidation in the water column could reduce net CH4 fluxes into the atmosphere. Overall, relatively low air-sea CH4 fluxes at this likely represent net emissions from subtidal seagrass habitats sites, which are not influenced by nearby allochthonous CH4 sources. The local CH4 emissions in P. oceanica offset less than 1% of the carbon burial in sediments (142 ± 69 g CO2eq m-2 yr-1). Combining our results with earlier observations in other seagrass meadows worldwide reveals that global CH4 emissions within seagrass meadows only offset a small fraction (<2%) of carbon sequestration in sediments.

Negative abnormal changes of atmospheric electric field have been monitored many times before earthquakes, especially before large earthquakes. However, its mechanism has not been clearly concluded yet. Based on the comparative analysis of the positive anomaly characteristics of atmospheric electric field before lightning and geoelectric field before earthquakes in earthquake areas, this paper concludes that the negative anomalies of atmospheric electric field before earthquakes are caused by the rise of the geoelectric potential in earthquake areas, and the areas with the abnormal rise of the geoelectric potential are potential earthquake areas. Based on the inference above , this paper further proposes a comprehensive earthquake early warning method with station network layout by geoelectric field instruments in combination with the atmospheric electric field data monitored by Electric Field Mills (EFMs). The research results will provide a possible reference for exploring the mechanism of earthquake generation, and will be help to explore earthquake early warning.

Tectonic tremors occurring on subducting plate boundaries are known to migrate at various timescales and migration speeds. Spatiotemporal patterns of tremor migration are key to investigating the rupture growth of slow earthquakes. However, spatiotemporal patterns are not sufficiently simple to visually define tremor migrations. This study developed a space-time Hough transform to objectively extract tremor migrations. The space-time Hough transform enables the extraction of multiple tremor migrations with various durations, migration directions, and migration speeds. We applied this method to a catalog of tremors for the period from 2012 to 2014, which was determined from the data analysis of a dense seismic array deployed in the Kii Peninsula, Southwest Japan. We successfully extracted 1,010 tremor migrations with durations ranging from 10 min to 24 h. Along-strike migrations propagating southwestward were predominant in the northeastern part of the Kii Peninsula, whereas those propagating northeastward were principal in the southwestern part. Regarding the along-dip direction, tremor migrations propagating in the up-dip directions were predominant in the deep part, and those propagating in the down-dip directions were principal in the shallow part. The patterns of along-strike migrations were related to the distribution of tremor energies, suggesting that tremor migrations may be controlled by heterogeneous structures of frictional properties on the plate interface. We further found that the migration speed is proportional to the inverse of the square root of the duration. This relation implies that a diffusion process controls the growth of fault ruptures behind tremor migrations.