The North Atlantic subpolar gyre is a key region for the North Atlantic phytoplankton bloom (NAB), the foundation of the regional foodweb. The NAB is dependent on nutrients seasonally introduced into the surface ocean by deep winter convection. Under climate change, this pattern is threatened by increasing water column stratification, and the NAB may “collapse” as a result, representing a potential “tipping point” in the Earth system. We investigate change in winter mixing and the impacts on the SPG and the broader northern North Atlantic using 1. a spread of future projections from a low-resolution Earth system model (UKESM) and 2. a single, high-warming projection of a high-resolution ocean-only configuration of the same model (NEMO-MEDUSA). For both models we find significant declines in the strength of the NAB during the 21st century. In UKESM, this occurred across all projections, but with low spatiotemporal coherence. In NEMO-MEDUSA, changes in upper mixed layer depth, surface nutrients and chlorophyll concentrations were noticeably abrupt and more highly spatiotemporally-correlated. We also find a large (>30 day) phenological shift in the peak of the bloom aligned with the timing of this change, which may affect foodweb dynamics. Overall, defining “collapse” as a halving of surface chlorophyll, we find that the NAB collapses by the end of the century regardless of future projection. However, the timing, abruptness and coherence of this collapse differs in high and low resolution models, suggesting the need for higher resolution for prediction of abrupt and irreversible changes, especially those involving ecosystem dynamics.

In global applications and data sparse regions, which comprise most of the earth, hydrologic model-based flood monitoring relies on precipitation data from satellite multisensor precipitation products or numerical weather forecasts. However, these products often exhibit substantial errors during the meteorological conditions that lead to flooding, including extreme rainfall. The propagation of precipitation forcing errors to predicted runoff and streamflow is scale-dependent and requires an understanding of the autocorrelation structure of precipitation errors, since error autocorrelation impacts the accumulation of precipitation errors over space and time in hydrologic models. Previous efforts to account for satellite precipitation uncertainty in hydrologic models have demonstrated the potential for improving streamflow estimates; however, these efforts use satellite precipitation error models that rely heavily on ground reference data such as rain gages or weather radar and do not characterize the nonstationarity of precipitation error autocorrelation structures. This work evaluates a new method, the Space-Time Rainfall Error and Autocorrelation Model (STREAM), which stochastically generates possible true precipitation fields, as input to the Hillslope Link Model to generate ensemble streamflow estimates. Unlike previous error models, STREAM represents the nonstationary and anisotropic autocorrelation structure of satellite 2 precipitation error and does not use any ground reference to do so. Ensemble streamflow predictions are compared with streamflow generated using satellite precipitation fields as well as a radar-gage precipitation dataset during peak flow events. Results demonstrate that this approach to accounting for precipitation uncertainty effectively characterizes the uncertainty in streamflow estimates and reduces the error of predicted streamflow. Streamflow ensembles forced by STREAM improve streamflow prediction nearly to the level obtained using ground-reference forcing data across basin sizes.

We compute stress drops for earthquakes in Northern Chile recorded between 2007to 2021. By applying two different analysis techniques, (1) the spectral ratio (SR) method and (2) the spectral decomposition (SDC) method, a stress drop map for the subduction zone consisting of 51,510 stress drop values is produced. We build an extended set of empirical Green’s function (EGF) events for the SR method by systematic template matching. Outputs are used to compare with results from the SDC approach, where we apply cell-wise obtained global EGF’s to compensate for the structural heterogeneity of the subduction zone. We find a good consistency of results of the two methods. The increased spatial coverage and quantity of stress drop estimates from the SDC method facilitate a consistent stress drop mapping of the different seismo-tectonic domains. Albeit differences of median stress drops are relatively small, strike-perpendicular depth sections clearly reveal systematic variations, with earthquakes within the upper plate, along the interface and at intermediate depth exhibiting distinct values. In particular, interface seismicity is characterized by the lowest observed median value, whereas upper plate earthquakes show noticeably higher stress drop values. Intermediate depth earthquakes show comparatively high average stress drop and a rather strong depth-dependent in-crease of median stress drop.  Additionally, we observe spatio-temporal variability of stress drops related to the occurrence of the two megathrust earthquakes in the study region. The here presented study is the first coherent large scale 3D stress drop mapping of the Northern Chilean subduction zone. It provides an important component for further detailed analysis of the physics of earthquake ruptures.

This paper describes and evaluates novel parameterizations for accounting for the effect of rooftop mitigation strategies on the urban environment, in the context of the mesoscale model Weather Research and Forecasting (WRF), coupled with a urban canopy parameterization and a building energy model (BEP+BEM). Through the new implementation, the sensitivity of near-surface air temperature and building energy consumption to different rooftop mitigation strategies is evaluated by means of numerical simulations in idealized urban areas, for typical summer and winter conditions. Rooftop mitigation strategies considered include cool roofs, green roofs and rooftop photovoltaic panels. Results indicate that near-surface air temperature is reduced by all the RMSs during the summer period: cool roofs are the most efficient in decreasing air temperature (up to 1 °C on average), followed by green roofs and photovoltaic panels. Green roofs reveal to be the most efficient strategy in reducing the energy consumption by air conditioning systems, up to 45%, while electricity produced by photovoltaic panels overcomes energy demand by air conditioning systems. During wintertime, green roofs maintain a higher near-surface air temperature than standard roofs. On the other hand, photovoltaic panels and cool roofs reduce near-surface air temperature, resulting in a reduced thermal comfort. The results presented here show that the novel parameterization schemes implemented in the WRF model can be a valuable tool to evaluate the effects of mitigation strategies in the urban environment. The new model is available as part of the public release of WRF in version 4.3.

Terrestrial hot springs have existed throughout Earth’s history and house some of the most ancient evidence of life on our planet. These settings are known for their high habitability and preservation potential, and are extensively studied as analog environments since hot spring deposits are thought to exist on the surface of Mars. Hot spring water commonly precipitates silica that coats microbial life dwelling in the hot spring outflow streams. This process can entomb microorganisms and preserve microbial remains over long timescales and with high morphological fidelity. Here we present research carried out on modern and sub-recent remains of microbial filaments from amorphous (unaltered) silica deposits in Yellowstone National Park. This work suggests that various elements sequestered by hot spring-dwelling organisms during life are preserved in microbial remains and persist over > 10,000 years. We also present findings from microfossils preserved in mid-Paleozoic terrestrial hot spring deposits which also show sequestrations of select elements in microfossil remains, suggesting that certain elements may persist even after several hundred million years and substantial host rock alteration. These elemental concentrations may be indicative of metabolic functioning during life and have application as biosignatures. Recent developments in analytical instrumentation now allow for even extremely low trace elemental abundances to be detected and mapped, regardless of sample complexity. This work is especially relevant to the search for life on Mars, as evidence of impact-induced hydrothermal activity may exist near the rim of Jezero Crater and may be sampled by the Perseverance rover. As a primary objective of the Mars 2020 mission is to search for evidence of past life on Mars, we suggest the application of this analytical technique to be valuable for potential samples returned to Earth by future Mars Sample Return missions. Distribution Statement A. Approved for public release: distribution unlimited.

River flow to the Arctic Ocean plays a significant role in the oceanic freshwater budget accounting for about 2/3 of the total freshwater flux to the Arctic Ocean. Ocean salinity and sea ice formation are critically affected by river input and changes in the freshwater and heat fluxes to the ocean can exert significant control over global ocean circulation via the North Atlantic deep water formation. There are mounting evidences that hydrological regime across the pan-Arctic is experiencing an unprecedented degree of change. However, the exact causes of such change are not immediately apparent, as they constitute a complex interplay between climate- and human-induced drivers. We used a new version of University of New Hampshire Water Balance Model (WBM) to quantify major sources of changes in river flux to the Arctic Ocean from Eurasian drainage basin. WBM is a grid based model which simulates the vertical water exchange between the land surface and the atmosphere and the horizontal water transport along a prescribed river networks for both natural and anthropogenic systems. The model accounts for sub-pixel land cover types, glacier and snow-pack accumulation/melt across sub-pixel elevation bands, permafrost dynamics, anthropogenic water use (e.g. domestic and industrial consumption, and irrigation for most of existing crop types), hydro-infrastructure for inter-basin water transfer and reservoir/dam regulations. To identify and quantify contributions of individual drivers/factors to river flow we used a new water source tracking capability recently developed in WBM. It allows “fingerprinting” of water at all steps in the water cycle such as in soils, groundwater pools, lakes, reservoirs, and fluxes such as originated from snowmelt, rain, glacier runoff, and baseflow. By comparing the difference in water component fractions in water storages and fluxes resulting from multiple historical runs we were able to quantify responses of each water source to the changes in climatic drivers and to characterize causes of observed changes in river flow to the Arctic Ocean. This work was mainly supported by Russian Foundation for Basic Research, grants: 18-05-60192 and 18-05-60240.

We reprocessed and interpreted Chang’E-4 Lunar Penetrating Radar (LPR) data collected until 14th February 2023, exploiting a new Deep Learning-based algorithm to automatically extract reflectors from a processed radar dataset. The results are in terms of horizon probability and have been interpreted by integrating signal attribute analysis with orbital imagery. The approach provides more objective results by minimizing the subjectivity of data interpretation allowing to link radar reflectors to their geological context and surface structures. For the first time, we imaged dipping layers and at least 20 shallow buried crateriform structures within the regolith using LPR data. We further recognized four deeper structures similar to craters, locating ejecta deposits related to a crater rim crossed by the rover path and visible in satellite image data.

Understanding and predicting sea ice dynamics and ice-ocean feedback processes requires accurate descriptions of momentum fluxes across the ice-ocean interface. In this study, we present observations from an array of moorings in the Beaufort Sea. Using a force-balance approach, we determine ice-ocean drag coefficient values over an annual cycle and a range of ice conditions. Statistics from high resolution ice draft measurements are used to calculate expected drag coefficient values from morphology-based parameterization schemes. With both approaches, drag coefficient values ranged from approximately 1-10×10^-3, with a minimum in fall and a maximum at the end of spring, consistent with previous observations. The parameterizations do a reasonable job of predicting the observed drag values if the under ice geometry is known, and reveal that keel drag is the primary contributor to the total ice-ocean drag coefficient. When translations of bulk model outputs to ice geometry are included in the parameterizations, they overpredict drag on floe edges, leading to the inverted seasonal cycle seen in prior models. Using these results to investigate the efficiency of total momentum flux across the atmosphere-ice-ocean interface suggests an inter-annual trend of increasing coupling between the atmosphere and the ocean.

Submesoscale currents, comprising fronts and mixed-layer eddies, exhibit a dual cascade of kinetic energy: a forward cascade to dissipation scales at fronts and an inverse cascade from mixed-layer eddies to mesoscale eddies. Within a coarse-graining framework using both spatial and temporal filters, we show that this dual cascade can be captured in simple mathematical form obtained by writing the cross-scale energy flux in the local principal strain coordinate system, wherein the flux reduces to the the sum of two terms, one proportional to the convergence and the other proportional to the strain. The strain term is found to cause the inverse energy flux to larger scales while an approximate equipartition of the convergent and strain terms capture the forward energy flux, demonstrated through model-based analysis and asymptotic theory. A consequence of this equipartition is that the frontal forward energy flux is simply proportional to the frontal convergence. In a recent study, it was shown that the Lagrangian rate of change of quantities like the divergence, vorticity and horizontal buoyancy gradient are proportional to convergence at fronts implying that horizontal convergence drives frontogenesis. We show that these two results imply that the primary mechanism for the forward energy flux at fronts is frontogenesis. We also analyze the energy flux through a Helmholtz decomposition and show that the rotational components are primarily responsible for the inverse cascade while a mix of the divergent and rotational components cause the forward cascade, consistent with our asymptotic analysis based on the principal strain framework.

The Glass Window Bridge Located in Eleuthera, The Bahamas, is the only bridge connecting Eleuthera’s northern and southern mainland, facing the Atlantic Ocean to the east and the Great Bahama Bank to the west. This bridge is under constant threat from hurricanes and large swells in the Atlantic Ocean. The existing bridge has been subject to severe damage arising from wave impact forces since its construction. In addition, severe overtopping of the cliffs near the Glass Window Bridge causes damage to the roads and severe erosion, that over the years has created unique geologic features. As the global climate warms and sea level rises (SLR), coastal areas will be subject to more extreme flooding and intense hurricanes. Therefore, assessing the impact of potential SLR on the GW bridge and guiding bridge wave mitigation measures are of crucial need. A 3D Digital Terrain Model (DTM) of the bridge site and adjacent ocean bathymetry is constructed from satellite data. This study develops a multiphase computational fluid dynamics (CFD) model based on the DTM to study the impact of wave-breaking for three major historical storm events, and for three different estimates of SLR for the year 2100. Our results suggest that, due to SLR, the islands are subjected to increased overtopping, which occurs even during normal wave conditions. Notably, nonlinear increases in wave splash extent and wave-induced bridge loads are observed as SLR increases. Our results indicate that SLR additionally magnifies the erosional energy, accelerating further changes in the geological features of the island.

Subglacial models represent moulins as cylinders or cones, but field observations suggest the upper part of moulins in the Greenland Ice Sheet have more complex shapes. These more complex shapes should cause englacial water storage within moulins to vary as a function of depth, a relationship not currently accounted for in models. Here, we use a coupled englacial--subglacial conduit model to explore how moulin shape affects depth-dependent moulin water storage and water pressure dynamics within a subglacial channel. We simulate seven different moulin shapes across a range of moulin sizes. We find that the englacial storage capacity at the water level is the main control over the daily water level oscillation range and that depth-varying changes in englacial water storage control the temporal shape of this oscillation. Further, the cross-sectional area of the moulin within the daily oscillation range, but not above or below this range, controls pressures within the connected subglacial channel. Specifically, large cross-sectional areas can dampen daily to weekly oscillations that occur in the surface meltwater supply. Our findings suggest that further knowledge of the shape of moulins around the equilibrium water level would improve englacial storage parameterization in subglacial hydrological models and aid predictions of hydro-dynamic coupling.

The Arctic Ocean receives a large supply of dissolved organic matter (DOM) from its catchment and shelf sediments, which can be traced across much of the basin’s upper waters. This signature can potentially be used as a tracer. On the shelf, the combination of river discharge and sea-ice formation, modifies water densities and mixing considerably. These waters are a source of the halocline layer that covers much of the Arctic Ocean, but also contain elevated levels of DOM. Here we demonstrate how this can be used as a supplementary tracer and contribute to evaluating ocean circulation in the Arctic. A fraction of the organic compounds that DOM consists of fluoresce and can be measured using in-situ fluorometers. When deployed on autonomous platforms these provide high temporal and spatial resolution measurements over long periods. The results of an analysis of data derived from several Ice Tethered Profilers (ITPs) offer a unique spatial coverage of the distribution of DOM in the surface 800m below Arctic sea-ice. Water mass analysis using temperature, salinity and DOM fluorescence, can clearly distinguish between the contribution of Siberian terrestrial DOM and marine DOM from the Chukchi shelf to the waters of the halocline. The findings offer a new approach to trace the distribution of Pacific waters and its export from the Arctic Ocean. Our results indicate the potential to extend the approach to separate freshwater contributions from, sea-ice melt, riverine discharge and the Pacific Ocean.

Clouds over tropical oceans are an important factor in Earth’s response to increased greenhouse gas concentrations, but their representation in climate models is challenging due to the small-scale nature of the involved convective processes. We perform two 4-year-long simulations at kilometer-resolution (3.3 km horizontal grid spacing) with the limited-area model COSMO over the tropical Atlantic on a 9000x7000 km2 domain: A control simulation under current climate conditions driven by the ERA5 reanalysis, and a climate change scenario simulation using the Pseudo-Global Warming (PGW) approach. We compare these results to the changes projected in the CMIP6 scenario ensemble. We find a good representation of the annual cycle of albedo, in particular for trade-wind clouds, even compared to the ERA5 reanalysis. Also, the vertical structure and annual cycle of the marine intertropical convergence zone (ITCZ) is accurately simulated, and the simulation does not suffer from the double ITCZ problem commonly present in global climate models (GCMs). The ITCZ responds to warming through a vertical extension and intensification primarily at high levels, as well as a slight southward extension of the annual mean ITCZ, while the narrowing typically seen in GCMs is not visible.

We examine the wave coupling efficiency of solar wind to magnetospheric fluctuations in the ULF frequency range using an advanced full-wave simulation code, Petra-M. Earth’s magnetic field is tilted to the ecliptic plane; thus, compressional wave sources can be incident over a wide range of magnetic latitudes. When compressional waves are incident at a low latitude, very little wave power can reach the inner magnetosphere. On the other hand, waves incident from a high latitude source can propagate efficiently into the inner magnetosphere and reach the ground near the cusp region. The mode-conversion and polarization reversal at the crossover plays a critical role in compressional wave propagation. The mode-converted linearly polarized electromagnetic ion cyclotron waves also occur at the Alfvén and ion-ion hybrid resonances. Therefore, the results suggest that solar wind compression can drive the linearly polarized EMIC waves, and the wave occurrence can have seasonal and diurnal dependence.

The 13 km SHiELD (System for High-resolution prediction on Earth-to-Local Domains) global model that is under development at the Geophysical Fluid Dynamics Laboratory (GFDL) and runs in near real time, produced outstanding tropical cyclone track forecasts during the 2021 Atlantic hurricane season, compared to both the upgraded National Weather Service Global Forecast System (GFSv16), the Hurricane Weather Research and Forecasting (HWRF) model and the European Centre for Medium-Range Weather Forecast Integrated Forecasting System (IFS). SHiELD’s average track forecast errors were 10% and 15% less than the GFSv16 and HWRF, respectively, for the 3-5 day forecast lead times. SHiELD’s track forecast skill was comparable to the National Hurricane Center’s official forecast at several forecast lead times, and approached 70% skill relative to the Climatology and Persistence Model (CLIPER) at 3 and 4 days. Similar improvements were found in the western Pacific basin in 2021, with improvements also seen in the eastern Pacific at days 4 and 5. Improved performance was also found in the 2019 Atlantic hurricane season, with neutral performance in 2020, when SHiELD was run retrospectively from the GFSv16 initial conditions. Distribution of the spatial errors and biases showed that in both the 2021 Atlantic hurricane season and the previous two years, the largest track forecast errors from both SHiELD and GFSv16 occurred in the subtropical eastern Atlantic, associated with a distinct northeast bias. Analysis indicated that some of the excessive north bias in the GFSv16 is associated with lower geopotential height fields compared to those in SHiELD.

We report on the annual variation of quiet-time suprathermal ion composition and spectral properties for C-Fe using Advanced Composition Explorer (ACE)/Ultra-Low Energy Ion Spectrometer (ULEIS) over the energy range 0.3 MeV/nuc to 1.28 MeV/nuc from 1998 through 2020. This extends the work of Desai et al. (2006) and Dayeh et al. (2009, 2017) to cover Solar Cycle 23’s rising phase through Solar Cycle 24’s declining phase. With 5 additional years of data, we show that the number of quiet-time hours strongly anti-correlates with the Sunspot Number (SSN) at better than the -0.9 level. We also show (1) a clear ordering of the cross correlation between abundance (normalized to O) and SSN as a function of solar wind M/Q; (2) the slope of X/O’s abundance as a function of Fe/C decreases with increasing M/Q; and (3) discuss the trend of annual spectral indicies with respect to Oxygen’s spectral index as a function of solar cycle and M/Q. The contrast between our abundance and spectral index results suggests that the source from which suprathermal ions are drawn or accelerated varies with solar activity and is tied to each element’s chemistry, but he acceleration mechanism that governs the spectral shape does not.

The WIVERN (WInd VElocity Radar Nephoscope) mission, currently under the Phase-0 of the ESA Earth Explorer program, promises to provide new insight in the coupling between winds and microphysics by globally observing, for the first time, vertical profiles of horizontal winds in cloudy areas. The objective of this work is to explore the potential of the WIVERN conically scanning Doppler 94GHz radar for filling the wind observation gap inside tropical cyclones. To this aim, realistic WIVERN notional observations of TCs are produced by combining the CloudSat 94GHz radar reflectivity observations from 2007 to 2009 with ECMWF co-located winds. Despite the short wavelength of the radar (3mm), which causes strong attenuation in presence of large amount of liquid hydrometeors, the system can profile most of the tropical cyclones, particularly the cloudy areas above the freezing level and the precipitating stratiform regions. The statistical analysis of the results shows that, (i) because of its lower sensitivity, a nadir pointing WIVERN would detect 80% of the clouds (60% of winds with 3m/s accuracy) observed by CloudSat, (ii) but thanks to its scanning capability, WIVERN would actually provide 52 times more observations of clouds (40~times more observations of horizontal winds) than CloudSat in TCs, (iii) this corresponds to more than 400 (300) million observations of clouds (accurate winds) every year. Such observations could be used in data assimilation models in order to improve numerical weather prediction and by modellers in order to shed light on the physical processes underpinning the evolution of tropical cyclones.

A regional meteorology–chemistry model was used to assess the effects of passenger car conversion to battery electric vehicles (BEV) on summer O3 concentrations in Kanto (Japan’s most populous region). Four sensitivity experiments were conducted on different on-road and upstream (power plant and gas station) emission conditions. Daytime 8-h maximum O3 decreased by 3 ppb (5%) and 4 ppb (5%) in urban and inland suburbs, respectively. O3 levels decreased even in urban (VOC-limited regions) because exhaust and evaporative VOC emissions from vehicle and gas stations were reduced effectively (especially alkenes from gasoline evaporation; highly reactive in O3 formation). In the suburbs (NOx-limited regions), reduction of exhaust NOx by BEV shifting was significant, but in urban, even only evaporation measures induced almost the same O3 reduction effect as BEV shifting. The additional emissions from thermal power plants due to BEV night charging contributed little to the next day’s daytime O3 on a monthly average basis. However, on some days, pollutants were stored in the upper part of the stable nighttime boundary layer and could affect the surface O3 as the next day’s mixed layer development. Depending on the O3 sensitivity regime (NOx- or VOC-limited), additional NOx plumes from rural (urban) power plants tended to increase (decrease) the next day’s O3. However, the distribution of the regime changes temporally and spatially. The H2O2/HNO3 ratio was discovered to be a clear indicator for distinguishing regime boundaries and was effective in predicting positive or negative O3 sensitivity to the additional emissions from power plants.