Ensemble Kalman Filters (EnKFs), which assimilate observations based on statistics derived from samples of ocean states called ensemble, have become the norm for ocean data assimilation (DA) and forecasting. These schemes are commonly implemented with inflation and localization techniques to increase their ensemble spread and to filter out spurious long-range correlations resulting from the limited-size ensembles imposed by computational burden constraints. Such ad hoc methods were found not necessary in ensemble DA experiments with simplified ocean/atmospheric models and large ensembles. Here, we conduct a series of 1-year-long ensemble experiments with a fully realistic EnKF-DA system in the Red Sea using tens-to-thousands of ensemble members. The system assimilates satellite and in-situ observations and accounts for model uncertainties by integrating a 4km-resolution ocean model with ECMWF atmospheric ensemble fields, perturbed internal physics and initial conditions for forecasting. Our results indicate that accounting for model uncertainties is more beneficial than simply increasing the ensemble size, with the improvements due to large ensemble leveling off at about 250 members. Besides, and in contrast to what is commonly observed with simplified models, the investigated ensemble DA system still required localization even when implemented with thousands of members. These findings are explained by (i) amplified spurious long-range correlations produced by the low-rank nature of the ECMWF atmospheric forcing ensemble, and (ii) non-Gaussianity generated by the perturbed internal physical parameterization schemes. Large ensemble forcing fields and non-Gaussian DA methods might be needed to take full benefits from large ensembles in ocean DA.

Rapidly changing climate is disrupting the High Arctic’s natural water systems. This disruption demands high quality monitoring of Arctic hydrology to better reconstruct past changes, track ongoing transformations, and assess future environmental threats. Water isotopes are valuable tracers of hydrological processes, but logistical challenges limit the length and scope of isotopic monitoring in High Arctic landscapes. Here, we present a comprehensive isotopic survey of 535 water samples taken in 2018–2019 of the lakes, streams, and other surface waters of the periglacial Pituffik Peninsula in far northwest Greenland. The δ18O, δ2H, and deuterium-excess values of these samples, representing 196 unique sites, grant us unprecedented insight into the environmental drivers of the region’s hydrology and water isotopic variability. We find that the spatial and temporal variability of lake isotopes is dominated by evaporation and connectivity to summer meltwater sources, while evaporation determines interannual isotopic changes. Stream isotopic compositions vary in both space and time based on the relative source balance of tundra snowpack meltwater versus surface melt from the nearby Greenland Ice Sheet. Overall, our survey highlights the diversity of isotopic composition and evolution in Pituffik surface waters, and our complete isotopic and geospatial database provides a strong foundation for future researchers to study hydrological changes at Pituffik and across the Arctic. Water isotope samples taken at individual times or sites in similar periglacial landscapes likely have limited regional representativeness, and increasing the spatiotemporal extent of isotopic sampling is critical to producing accurate and informative High Arctic paleoclimate reconstructions.

The reality of living on Mars is closer than ever before. For years science fiction writers and movie producers have presumed powerful Martian dust storms capable of catastrophic events. In the movie, The Martian (2015), a powerful dust storm rips an antenna off its base and in the movie Martian Land (2015), an astronaut is blown away and carried off by a dust storm. In reality, some of the dust storms are large enough to be visible by telescopes on earth. In this article, the force impact of a Martian dust storm is evaluated. Wind speed data from Viking 1 and Viking 2 Lander in 1976, the Phoenix Lander in 2008, Mars Curiosity Rover in 2011, InSight mission Lander in 2018, and Mars 2020 mission Perseverance Rover are used for this study. Modifying Bernoulli’s Equation based on Martian atmospheric density to determine the wind velocity pressure in pounds per square foot. The stability of a male and female astronaut in an EVA(Extravehicular Activity) space suit is evaluated during the highest wind speed of a Martian dust storm.

Primitive achondrites like the acapulcoites-lodranites (AL) clan are meteorites that formed on bodies in the process of forming a metallic core, providing a unique window into how early solar system processes transformed unmelted material into differentiated bodies. However, the size and structure of the parent body of ALs and other primitive achondrites are largely unknown. Paleomagnetism can establish the presence or absence of a metallic core by looking for evidence of a dynamo magnetic field. We conducted a magnetic study of the Acapulco acapulcoite to determine its ferromagnetic minerals and their recording properties. This is the first detailed rock magnetic and first paleomagnetic study of a primitive achondrite group. We determined that metal inclusions located inside silicate grains consist of two magnetic minerals, kamacite and tetrataenite, which have robust recording properties. However, the mechanisms and timing by which these minerals acquired any natural remanent magnetization are unknown. Despite this, Acapulco has not been substantially remagnetized since arriving on Earth and therefore should retain a record dating to 4.55 billion years ago. Future studies could characterize this record by using high resolution magnetometry measurements of individual grains and developing an understanding of how and when they became magnetized. Our discovery of tetrataenite in ALs provides the first mineralogical evidence for slow cooling (~5 x 103 °C Ma-1) of the AL parent body at low temperatures (~320°C). Its presence means that the AL parent body is unlikely to have been catastrophically disrupted at AL peak temperatures (~1200°C) without subsequent reaccretion.

The arid region of Northwest China and Mongolia (NCM) receives most of the precipitation in the summer. The need for a better understanding of the synoptic-scale mechanism responsible for precipitation formation is accentuated by the recent wetting trend and its implications for future hydroclimate change. By conducting a hierarchical clustering analysis on an observationally-based daily precipitation dataset, we show that there are three distinct precipitation patterns over NCM, one of which is associated with strong precipitation over the western part of the region and another over the eastern part. The corresponding large-scale circulation anomalies indicate that these strong precipitation events are triggered by the upper-tropospheric disturbances in the form of transient Rossby wave packets. Furthermore, the wetting trend is linked to more frequent strong precipitation events over the eastern NCM, suggesting that it may have been induced remotely by atmospheric circulation perturbations.

Given the possibility of irreversible, anthropogenic changes in the climate system, technologies such as solar radiation management (SRM) are sometimes framed as possible emergency interventions. However, little knowledge exists on the efficacy of such  deployments. To fill in this gap, we perform Community Earth System Model 2 (CESM 2) simulations of an intense warming scenario on which we impose gradual early-century SRM or rapid late-century cooling (an emergency intervention), both realised via stratospheric aerosol injection (SAI). While both scenarios cool Earth's surface, ocean responses differ drastically. Rapid cooling fails to release deep ocean heat content or restore an ailing North Atlantic deep convection but partially stabilizes the Atlantic meridional overturning circulation. In contrast, the early intervention effectively mitigates changes in all of these features. Our results suggest that slow ocean timescales impair the efficacy of some SAI emergency interventions.

Large reductions in anthropogenic emissions of particulate matter and its precursor emissions have occurred since the enactment of the Clean Air Act Amendments of 1990. The Interagency Monitoring of Protected Visual Environments (IMPROVE) network has measured PM2.5 gravimetric mass (mass of particles with aerodynamic diameters less than 2.5 µm, also referred to here as fine mass, “FM”) and speciated PM2.5 aerosol composition at remote sites since 1988. Measured species include inorganic anions such as sulfate, nitrate, and chloride, carbonaceous aerosols such as organic (OC) and elemental carbon (EC), and elemental concentrations used to derive fine dust (FD). Trend analyses of seasonal and annual mean mass concentrations were calculated from 2000 through 2021, a period that includes the largest reductions in emissions. On average, annual mean FM at remote sites in the continental United States has decreased at a rate of -1.8% yr-1. This reduction is largely due to annual mean trends in sulfate (-6.1% yr-1), nitrate (-2.7% yr-1), EC (-2.2% yr-1), FD (-1.3% yr-1), and OC (-0.9% yr-1), although the OC annual mean trend was insignificant. Seasonal and regional FM trends varied significantly, with strong reductions in the East in all seasons due to sulfate reductions, and flat and insignificant trends in summer and fall in the West due to the impacts of biomass burning emissions on OC trends. Evaluating regional and seasonal trends in aerosol composition helps identify sources that continue to adversely impact air quality and hinder progress in FM reductions due to successful regulatory activity.

Planetary boundary layer (PBL) modeling is a primary contributor to uncertainties in a numerical weather prediction model due to difficulties in modeling the turbulent transport of surface fluxes. The Weather Research and Forecasting model (WRF) has included many PBL schemes which may feature a non-local transport component driven by super-grid eddies or a one-and-half order turbulence closure model. In the present study, a turbulent kinetic energy (TKE)-based turbulence closure model is integrated into the non-local Asymmetric Convective Model version 2 (ACM2) PBL scheme and implemented in WRF. Non-local transport is modeled the same as ACM2 using the transilient matrix method. The new TKE-ACM2 PBL scheme is evaluated by comparing it with high spatiotemporal Doppler LiDAR observations in Hong Kong over 30 days each for summer and winter seasons to examine its capability in predicting the vertical structures of winds. Scatter plots of measured versus simulated instantaneous wind speeds show that TKE-ACM2 is able to reduce the root mean square error and mean bias and improve the index of agreement, especially at the urban observational site. The diurnal evolution of monthly averaged wind profiles suggests TKE-ACM2 can better match both the magnitudes and vertical gradients, revealing its superiority compared to ACM2 at stable atmospheric conditions. Other meteorological parameters including the potential temperature profiles, PBL heights, and surface wind speeds have also been investigated with references to various sources of observations.

Coarse-grid weather and climate models rely particularly on parameterizations of cloud fields, and coarse-grained cloud fields from a fine-grid reference model are a natural target for a machine-learned parameterization. We machine-learn the coarsened-fine cloud properties as a function of coarse-grid model state in each grid cell of NOAA’s FV3GFS global atmosphere model with 200 km grid spacing, trained using a 3 km fine-grid reference simulation with a modified version of FV3GFS. The ML outputs are coarsened fine fractional cloud cover and liquid and ice cloud condensate mixing ratios, and the inputs are coarse model temperature, pressure, relative humidity, and ice cloud condensate. The predicted fields are skillful and unbiased, but somewhat under-dispersed, resulting in too many partially-cloudy model columns. When the predicted fields are applied diagnostically (offline) in FV3GFS’s radiation scheme, they lead to small biases in global-mean top-of-atmosphere (TOA) and surface radiative fluxes. An unbiased global mean TOA net radiative flux is obtained by setting to zero any predicted cloud with grid cell mean cloud fraction less than a threshold of 6.5%; this does not significantly degrade the ML prediction of cloud properties. The diagnostic, ML-derived radiative fluxes are  far more accurate than those obtained with the existing cloud parameterization in the nudged coarse-grid model, as they leverage the accuracy of the fine-grid reference simulation’s cloud properties. 

Tropical high cloud cover decreases with surface warming in most general circulation models. This reduction, according to the “stability-iris” hypothesis, is thermodynamically controlled and linked to a decrease in the radiatively-driven clear-sky convergence, when the peak anvil clouds rise because of the rising isotherms. The influence of the large-scale dynamical changes on the tropical high cloud fraction remains difficult to disentangle from the local thermodynamic influence, given that the mean meridional circulation remains inextricably tied to the local thermodynamic structure of the atmosphere. However, using idealized general circulation model (GCM) simulations, we propose a novel method to segregate the dynamical impact from the thermodynamic impact on the tropical high cloud fraction. To this end, our investigation primarily focuses on the mechanisms underpinning changes in the high cloud cover in the deep tropics in response to extratropical surface warming, when tropical sea surface temperatures remain invariant. We find that the relative importance of the net convective detrainment of ice cloud condensates to the cloud microphysical processes, such as the net depositional growth of ice aggregates, in controlling the tropical high cloud fraction is altitude-dependent.

High temperature extremes accompanied by drought have led to serious ramifications for environmental and socio-economic systems. Thus, improving the predictability of heat-wave events is a high priority. One key to achieving this is to better understand land-atmosphere interactions. Recent studies have documented a hypersensitive regime in the soil moisture-temperature relationship when soil dries below a critical low threshold, air temperatures increase at a greater rate as soil moisture declines. In this study, we explore the mechanisms linking low soil moisture to high air temperatures. From in-situ observations, we confirm that the hypersensitive regime acts throughout the chain of energy processes from land to atmosphere. A simple energy-balance model indicates that the cause of the hypersensitive regime is the dramatic drop in evaporative cooling that occurs when soil moisture dries to the permanent wilting point, below which latent heat flux almost ceases. Precisely how a model represents the relationship between evapotranspiration and soil moisture is found to be essential to describe the occurrence of hypersensitive regime. Thus, we advocate that climate models should ensure a realistic representation of land-atmosphere interactions to obtain reliable forecasts of extremes and climate projections, aiding the assessment of climate vulnerability and adaptation.

Aotearoa New Zealand’s marine environment is heavily impacted by El Niño Southern Oscillation (ENSO). Little is known about the effect of ENSO on oceanographic properties in the area or their consequences on the distribution of marine organisms. Here we characterise the spatio-temporal variability of fine-scale fronts (< 10 km) in the area of Tīpaka Moana Te Moana Nui a Toi Hauraki Gulf (HG) and investigate the impact of dominant wind direction, seasonality, and ENSO phase. We processed Ocean-Land Color Instrument (OLCI) images from satellites between 2016-2022 with a fit-for-purpose version of the Belkin and O’Reilly Algorithm, specifically for frontal detection. We find coherent shifts in the position of fine-scale features, with ENSO phases alternatively separate and connect different parts of the Gulf during El Niño and La Niña respectively. Overall, fronts tend to co-locate with the 70 m and 40 m isobaths in the outer and inner HG respectively and their locations shift close or away from shore in response to changes in dominant wind direction. Furthermore, offshore fronts occurrences increase during winter and spring, and nearshore ones increase during summer and autumn. Our results sketch a first assessment of the distribution of fine-scale features that are likely to impact the distribution of important areas for pollutants dispersion and feeding areas for marine megafauna.

The Carrascoy and Palomares faults are two major active faults of the Eastern Betic Shear Zone (SE Iberia), both controlling conspicuous mountain fronts. However, the area in between both faults, corresponding to the Mazarron Graben (MG), is a nearly flat plain bounded by a relief of smooth hills whose tectonic origin and evolution remains uncertain. By means of a morphotectonic analysis, geophysical survey and paleoseismological trenching we point out that this is area of distributed deformation controlled by folds of variable amplitude nucleated in high angle reverse faults with sinistral component without a well-defined deformation front. The MG developed a marine basin during the Upper Miocene evolving into an alluvial environment with calcrete pedogenic development through the Pleistocene, which formed a tableland landscape that favors the identification of tectonic structures. In this study we demonstrate how some of the ancient normal faults controlling the graben were reactivated as reverse during the late Middle Pleistocene within a regional frame of positive tectonic inversion. Such inversion is evidenced by several emblematic structures: (i) presence of harpoon folding, and (ii) newly formed high angle reverse faults, which dips increase and ruptures become younger backwards on the hanging wall. Based on the timing of the observed deformation, we also suggest that the onset of the regional tectonic inversion might be related to the tectonic evolution of the neighboring Carrascoy and Palomares faults, producing a local stress tensor varying dramatically from extension to compression within the neotectonic period in a regional convergence tectonic frame.

Antarctic ice core records suggest that atmospheric CO2 increased by 15 to 20 ppm during Heinrich stadials (HS). These periods of abrupt CO2 increase are associated with a significant weakening of the Atlantic meridional overturning circulation (AMOC), and a warming at high southern latitudes. As such, modelling studies have explored the link between changes in AMOC, high southern latitude climate and atmospheric CO2. While proxy records suggest that the aeolian iron input to the Southern Ocean decreased significantly during HS, the potential impact on CO2 of reduced iron input combined with oceanic circulation changes has not been studied in detail. Here, we quantify the respective and combined impacts of reduced iron fertilisation and AMOC weakening on CO2 by performing numerical experiments with an Earth system model under boundary conditions representing 40,000 years before present (ka). Our study indicates that reduced iron input can contribute up to 6 ppm rise in CO2 during an idealized Heinrich stadial. This is caused by a 5% reduction in nutrient utilisation in the Southern Ocean, leading to reduced export production and increased carbon outgassing from the Southern Ocean. An AMOC weakening under 40ka conditions and without changes in surface winds leads to a ~0.5 ppm CO2 increase. The combined impact of AMOC shutdown and weakened iron fertilisation is almost linear, leading to a total CO2 increase of 7 ppm. Therefore, this study highlights the need of including changes in aeolian iron input when studying the processes leading to changes in atmospheric CO2 concentration during HS.

With the rising air temperature and precipitation, water and sediment flux in the Source Region of the Yangtze River have increased significantly since 2000. Nonetheless, the response of braided river morphology to climate-driven water and sediment flux change is still unknown. Water bodies of nine large braided rivers from 1990 to 2020 were extracted based on Google Earth Engine platform, and impacts of climate change on activation indices of braided river morphology were quantified. The main results are presented that a new method of braided water body extraction by combining Lowpath algorithm and Local Otsu algorithm is firstly proposed, which reduces 59% of the root mean squared error of braiding intensity in comparison with the Global Otsu method. The braiding intensity has a parabolic variation trend with the water area ratio, and the average sandbar area ratio has a negative power law trend with the water area ratio. Intra-annual channel migration intensity has an obvious temporal scale effect, which increases rapidly when the time span is less than 5 years. The warming and wetting trend led to vegetation cover increasing significantly. With the increase of runoff, water area of each braided reach has increased in both flood and non-flood season. Intra-annual channel migration intensity shows three different trends of increasing, weakening, and unchanged over time. The response of migration intensity to climate warming can be classified into three patterns in the SRYR as follows: sediment increase constrained pattern, sediment increase dominated pattern, and runoff increase dominated pattern.

High-Intensity Long-Duration Continuous AE Activity (HILDCAA) intervals are driven by High Speed solar wind Streams (HSSs) during which the rapidly-varying interplanetary magnetic field (IMF) produces high but intermittent dayside reconnection rates. This results in several days of large, quasi-periodic enhancements in the auroral electrojet (AE) index. There has been debate over whether the enhancements in AE are produced by substorms or whether HILDCAAs represent a distinct class of magnetospheric dynamics. We investigate sixteen HILDCAA events using the expanding/contracting polar cap model as a framework to understand the magnetospheric dynamics occurring during HSSs. Each HILDCAA onset shows variations in open magnetic flux, dayside and nightside reconnection rates, the cross-polar cap potential, and AL that are characteristic of substorms. The enhancements in AE are produced by activity in the pre-midnight sector, which is the typical substorm onset region. The periodicities present in the intermittent IMF determine the exact nature of the activity, producing a range of behaviours from a sequence of isolated substorms, through substorms which merge into one-another, to almost continuous geomagnetic activity. The magnitude of magnetic fluctuations, $dB/dt$, in the pre-midnight sector during HSSs is sufficient to produce a significant risk of Geomagnetically Induced Currents, which can be detrimental to power-grids and pipelines.

The aurora often appears as an approximately oval shape surrounding the magnetic poles, and is a visible manifestation of the intricate coupling between the Earth’s upper atmosphere and the near-Earth space environment. While the average size of the auroral oval increases with geomagnetic activity, the instantaneous shape and size of the aurora is highly dynamic. The identification of auroral boundaries holds significant value in space physics, as it serves to define and differentiate regions within the magnetosphere connected to the aurora by magnetic field lines. In this work, we demonstrate a method to detect and model the poleward and equatorward boundaries in global UV images. Our methodology enables analysis of the spatiotemporal variation in auroral boundaries from 2.5 years of UV imagery from the IMAGE satellite. The resulting dataset reveals a root mean square boundary normal velocity of 149 m/s for the poleward boundary and 96 m/s for the equatorward boundary and the velocities are shown to be stronger on the nightside than on the dayside. Interestingly, our findings demonstrate an absence of correlation between the amount of open magnetic flux and the amount of flux enclosed within the auroral oval. Furthermore, we highlight the inadequacy of a simplistic generalization of the expanding-contracting polar cap paradigm in explaining temporal variations in the auroral oval area, underscoring the imperative for an enhanced understanding of equatorward boundary fluctuations.

Flood disasters are among the most devastating natural disasters worldwide. The occurrence of such disasters is often accompanied by strong precipitation and other weather factors, making it more difficult to identify the affected areas. Moreover, Synthetic Aperture Radar (SAR) technology can capture images in 24-hour window and penetrate through clouds and fog. The change detection technology, based on SAR images, is generally utilized to locate disaster-stricken areas by analyzing the differences between pre- and post-disaster images. However, this method mainly faces two challenges: the presence of speckle noise reduces the accuracy of the difference detection and the lack of a suitable SAR dataset for flood disaster change detection. Therefore, this research proposes a novel two-stage approach for locating the flood disaster area, named Denoising-Change Detection Approach (D-CDA). The first stage consists of a nine-layer denoising network with an encoder-decoder structure, called SAR Denoising Network (SDNet). It utilizes a multi-residual block and parallel convolutional block attention module to extract features during the encoding process to suppress the noise component. In the second stage, a novel convolution neural network is proposed to detect the changes between bitemporal SAR images, namely Coordinate Attention Fused Network (CAFNet), which combines the Siamese network and UNet++ as the backbone and fuses multi-coordinate attention modules to enhance the change features. Moreover, a change detection dataset (ZhengZhou Flood - ZZF-dataset) is constructed using Sentinel-1 SAR images based on the flood disaster in Zhengzhou of China in 2021. The simulations verify the effectiveness of the proposed method.