Some of the classical models of tropical cyclone intensification predict tropical cyclones to intensify up to a steady intensity, which depends on surface fluxes only, without any relevant role played by convective motions in the troposphere, typically assumed to have a moist adiabatic lapse rate. Simulations performed using the non-hydrostatic, high-resolution model SAM in idealized settings (rotating radiative-convective equilibrium on a doubly-periodic domain) show early intensification consistent with these theoretical expectations, but different intensity evolution, with the cyclone undergoing an oscillation in wind speed. This oscillation can be linked to feedbacks between the cyclone intensity and air buoyancy: convective heating, radiative heating, and mixing with warm low stratospheric air warm the mid and upper troposphere of the cyclone stabilizing the air column and thus reducing its intensity. After the intensity decay phase, mid and upper tropospheric cooling, mostly through cold advection from the surroundings, cooled by radiation, rebuilds CAPE and triggers a new intensification. These idealized simulations thus highlight the potentially important interactions between a tropical cyclone, its environment and radiation.

Training data: 1.6 million 2x8x8 patches of SAR data randomly sampled from 105 bursts of OPERA RTC-S1; 30m resolution, with two channels: VV (Vertical transmit and Vertical receive) and VH (Vertical transmit and Horizontal receive). Validation Sites: On May 24, 2024, a large landslide in Papua New Guinea buried a village and killed between 650 and 2,000 people. In February 2024, a series of wildfires broke out in the Valparaiso region of Chile. At least 137 people were killed and over 23,000 hectares were burned.

We describe CATKE, a parameterization for fluxes associated with small-scale or “microscale’ ocean turbulent mixing on scales between 1 and 100 meters. CATKE uses a downgradient formulation that depends on a prognostic turbulent kinetic energy (TKE) variable and a diagnostic mixing length scale that includes a dynamic convective adjustment (CA) component. With its dynamic convective mixing length, CATKE predicts not just the depth spanned by convective plumes but also the characteristic convective mixing timescale, an important aspect of turbulent convection not captured by simpler static convective adjustment schemes. As a result, CATKE can describe the competition between convection and other processes such as shear-driven mixing and baroclinic restratification. To calibrate CATKE, we use Ensemble Kalman Inversion to minimize the error between 21~large eddy simulations (LES) and predictions of the LES data by CATKE-parameterized single column simulations at three different vertical resolutions. We find that CATKE makes accurate predictions of both idealized and realistic LES compared to microscale turbulence parameterizations commonly used in climate models.

The use of spherical modes offers an efficient solution for storing embedded element patterns with significant angular structure for large scale arrays, such as the Square Kilometre Array (SKA)-Low radio telescope. These patterns are required for calibration of the numerous stations comprising the telescope, each containing several hundred elements, and operating over a 7:1 bandwidth. However, implementation is significantly complicated by the many differences in the notation used in the literature for the Legendre special functions. The differing phasor conventions used in electrical engineering and physics further complicate this. This paper synthesises much of the existing literature on this topic, paying special attention to these issues. Mathematical implementation issues are also addressed. A number of suitable tests using canonical dipole radiators to verify correct implementation are outlined. The paper concludes with tests on an individual SKALA4 antenna and a full-scale SKA-Low prototype station comprising 256 of these antennas. The storage saving afforded is some three orders of magnitude; this is very significant for a full SKA-Low station. Supporting material addresses some mathematical issues, outlines industry-standard storage schemes and summarises differing conventions encountered in the literature.

This study explores the relationship between dinoflagellate cyst (dinocyst) assemblages and the mixed layer depth (MLD) using canonical correspondence analyses. Our results demonstrate that wintertime deepening of MLD, in response to deep convection events, can influence dinocyst assemblages and especially the relative abundance of Nematosphaeropsis labyrinthus, which can thus be used as a proxy of MLD and the associated deep convection intensity. The analysis of Holocene N. labyrinthus percentage records in the subpolar North Atlantic, along with quantitative reconstructions of MLD from dinocyst assemblages, further reveals a westward migration of potential deep convection region around 6 ka BP, from the Nordic Seas and eastern subpolar gyre (SPG) during the Early Holocene, to the western to central SPG during the Middle and Late Holocene. The intensification of deep convection in the Labrador Sea towards a modern-like situation started during the Late Holocene, one or two thousand years later than the major transition around 6 ka BP in other parts of the subpolar North Atlantic. These results strengthen the hypothesis of reduced deep-water formation in the eastern North Atlantic from the early to late Holocene.

Airglow originating from metastable helium He(2^3S) at 1083 nm has been used to study the upper thermosphere since its discovery in 1959, yielding insights into e.g. solar EUV intensities and thermospheric photoelectron densities. However, passive airglow measurements are fundamentally limited, because they represent a vertical integration of the entire He(2^3S) layer, spanning 100s of km, and because they rely on solar illumination of the He(2^3S) layer, so temporal changes are difficult to distinguish from vertical variations. Recently, the first height-resolved measurements of He(2^3S) density were made by fluorescence lidar, opening a new window for studying the upper thermosphere. We report on a series of 51 measurements by this instrument spanning an entire winter season and extending to an altitude of 1000 km, revealing a broad He(2^3S) layer that extends to, and peaks at, higher altitudes than previously expected.

Experimental bacteriophage addition to soil depresses bacterial respiration and alters nitrogen transformationsBenjamin D. Duval1*, Kurt E. Williamson2, Anika Baloun1, Linda C. DeVeaux11Biology Department, New Mexico Institute of Mining and Technology, Socorro, New Mexico, USA 878012Biology Department, The College of William and Mary, Williamsburg, Virginia, USA 23185*corresponding author:[email protected] ID: 0000-0001-7692-4400CRediT contributor roles:BDD: conceptualization, data curation, formal analysis, methodology, project administration, supervision, writing (draft), writing (editing)KEW: conceptualization, writing (draft), writing (review & editing)AB: investigation, writing (review & editing)LCD: methodology, resources, supervision, writing (review & editing)ABSTRACTSoil heterogeneity and complex host-phage relationships impede understanding phage influence on terrestrial nutrient cycles. We performed laboratory experiments quantifying phage effects on bacterial respiration and inorganic soil N and P changes. Soil microcosms under reducing conditions were inoculated with a single bacterial host (Gordonia rubripertincta ) or with the host + phage (φ Apollonia6). Respiration declined immediately following phage introduction, and was lower in the presence of phage through time. Phage additions increased variance in N transforms. NH4+ decline did not match NO3- gain, suggesting microbial immobilization in +phage microcosms. Net NO3- accumulation was observed with phage, suggesting viral interruption of bacterial NO3- reduction. Phosphate pools declined in both treatments, likely due to cell uptake and incorporation into phage. This single host-phage system highlights phage depression of bacterial respiration and altered nutrient transformation, and can be the basis for further investigations into phage-bacteria soil interactions and their impacts on terrestrial nutrient cycling.Keywords: Ammonium uptake, bacteriophage, biogeochemistry, Gordonia rubripertincta, nitrate reduction, respiration, soilINTRODUCTIONViruses that infect bacteria (bacteriophage or phage), are ubiquitous and numerous in soil systems, with abundances as high as reported for forest soils (1). There is a presumption of biogeochemical importance with such abundances, and phage are increasingly recognized as having a regulatory role within bacteria-driven portions of carbon (C), nitrogen (N) and phosphorus (P) cycles (2–4). However, there is tremendous uncertainty about the magnitude and direction of phage effects on most terrestrial biogeochemical processes, due to the physical and chemical complexity of soils, and the numerous types of potential phage-bacteria interactions in soil (5).Kuzyakov and Mason-Jones’ (2018) review of phage influence on soil processes arrives at two important conclusions: 1) soil bacterial mortality is principally caused by phage, and 2) nucleotide metabolism involved in phage genome replication creates high N and P demand which alters the stoichiometry of necromass relative to living biomass. Thus, phage-induced mortality is expected to release qualitatively different resources into the soil system than other mechanisms of bacterial mortality, e.g., protozoan grazing or from soil perturbations such as freeze-thaw cycles (7). However, variation in phage infection outcomes (e.g., lysis, lysogeny or chronic infection), from a population level, may also produce very different biogeochemical results with respect to both bacterial mortality and nutrient demands.Phage-induced mortality could simply lower host bacterial population activity and the rate and net products of any processes performed by that population (i.e., microbial N immobilization or NO3- reduction). This could be characterized as “kill the host, kill the process”. However, bacterial mortality also liberates cell components that are subsequently recycled as C and N sources promoting growth and activity in living microbial biomass (i.e., “eat the dead, change the product”). These possibilities, coupled with observations that phage lysate typically has higher C:N and lower phosphorus (P) than living biomass, suggest that phage mortality creates an intermediate biogeochemical scenario between process interruption from host death and process enhancement from necromass nutrient fertilization (6–8). Furthermore, a significant fraction of soil phages at any given time are likely lysogenic, and infect bacteria without immediately causing cell death via lysis (9,10). Physiological stress may skew temperate phages toward lysogenic replication, in which the phage genome takes up stable residence inside of its host cell instead of generating progeny particles and inducing cell lysis (11), and we expect those lysogenized cells to continue elemental uptake and transformation. It is unclear if element processing rates would be negatively impacted by the presence of a prophage, but prophage could slow bacterial element processing by reducing bacterial metabolism, and lysogeny prevalence can correlate with sub-optimal host conditions (12,13).Given the range of potential phage impacts on bacterial functional roles, microcosm experiments are well-suited to answer questions related to mortality effects and quantifying elemental flux changes as a result of single host-phage interactions in soil. To do so, we selected a heterotrophic (organic C processing) host bacterial strainGordonia rubritincta, that has known roles in organic compound degradation and synthesis (14,15), NO3- reduction, and has substantial P demand (16). Our group has recently isolated several phages from natural and anthropogenically influenced soils that infect Gordonia (17). From that group, we selected the phage φApollonia6 for its consistent infection rate in our lab trials (Duval and DeVeaux, pre-experimental observations). The influence of this phage on Gordonia functional ecology was quantified for two key ecosystem processes, organic C mineralization/respiration and inorganic nutrient (N and P) transformation. Microcosms were designed to promote NO3- reduction by this bacterial strain (high H2O/low O2) during a medium duration (~1 month) incubation experiment.We predict that sterile soils inoculated with Gordonia would have relatively high rates of CO2 respiration compared to soils that also had phage additions; these soils are also predicted to yield lower final pools of NO3- due to denitrification. Phage additions will result in lower CO2 fluxes due to cell mortality, and as a result, NO3- pools increase due to denitrification interruption due to phage. Because virion production is implicitly P limited, we expect greater reductions of inorganic P pools (as a result of P uptake and synthesis into organic structures) in soils with phage addition (16). Alternatively, a dip in respiration from mortality may be followed by a pulse of activity from cells utilizing lysis products as energy sources and possibly nutrients (7). In that instance, we expect higher rates of CO2 emissions and lower NO3- pools with phage addition compared to bacteria-only soils. Regardless of outcome, this experiment contributes to the growing literature of phage-influenced soil N and P transformations.METHODS

A document by Mike Coughlan. Click on the document to view its contents.

Hydrologic processes in snowmelt dominated systems are traditionally measured and understood at the point scale. However, snowmelt, sublimation, and snowfall rates exhibit significant spatial variability across larger landscapes. These variations are influenced by local atmospheric and terrain characteristics, which control the deviations between small-scale measurements and areally averaged responses to spatially heterogeneous mass and energy inputs. Appropriate upscaling relations are needed to translate small-scale descriptions of snow processes into constitutive relationships that are applicable at larger scales. As a proof of concept, this study examines the temporal and spatial variability of sublimation and snowmelt fluxes in a drainage basin in the Canadian Rockies using machine learning methods. Raven, a hydrological model, generates high-resolution fluxes and state variables used to train a random forest algorithm. The random forest (RF) algorithm is then applied to estimate coarse resolution fluxes. This study involves estimating spatially averaged results from discretized fine-scaled models without explicit knowledge of detailed local response, both with and without low-order statistics of state (e.g., the standard deviation of snow water equivalent). A series of experiments are used to verify that the upscaling methodology can successfully represent the impact of heterogeneity within the system. Spatially averaged forcing estimated from the scale-appropriate machine learning model is then incorporated into a mass balance equation at a coarse resolution to demonstrate the efficacy of this upscaling methodology.

For accurate and timely space weather forecasting, advanced knowledge of the ambient solar wind is required, both for its direct impact on the magnetosphere and for accurately forecasting the propagation of coronal mass ejections to Earth. Data assimilation (DA) combines model output and observations to form an optimum estimation of reality. Initial experiments with assimilation of in situ solar wind observations suggest the potential for significant improvement in the forecast skill of near-Earth solar wind conditions. However, these experiments have assimilated science-quality observations, rather than near-real-time (NRT) data that would be available to an operational forecast scheme. Here, we assimilate both NRT and science observations from the Solar Terrestrial Relations Observatory (STEREO) and near-Earth observations from the Advanced Composition Explorer (ACE) and Deep Space Climate Observatory (DSCOVR) spacecraft. We show that forecasts using NRT data are comparable to those based on science-level data. This suggests that an operational solar wind DA scheme would provide significant forecast improvement, with reduction in the mean absolute error (MAE) of solar wind speed around 45% over forecasts without DA. With a proposed space weather monitor planned for the L5 Lagrange point, we also quantify the solar wind forecast gain expected from L5 observations alongside existing observations from L1. This is achieved using particular configurations of the STEREO and L1 spacecraft. There is a 15.5% improvement for forecast lead times of less than 5 days when observations from L5 are assimilated alongside those from L1, compared to assimilation of L1 observations alone.

In this paper, a new path loss prediction model based on multi-modal sensory data is proposed to enhance the accuracy of path loss prediction in vehicular communication scenarios. Meanwhile, a new dataset under vehicular urban crossroads for intelligent multi-modal sensing-communication integration is constructed. Meanwhile, the mapping relationship between physical space and electromagnetic space is explored. Furthermore, path loss prediction is achieved with environmental information via multi-modal sensory data. Simulation results show that the proposed path loss prediction model is validated by the ground truth, which achieves a mean squared error (MSE) of 1.9283*10^{-6}. The proposed model improves the accuracy by 2 orders of magnitude over 3GPP TR 38.901 channel models. Compared to the artificial neural network (ANN), support vector regression (SVR), random forest (RF), and gradient tree boosting (GTB), the proposed model achieves the highest accuracy. Finally, the effectiveness of multi-modal sensory data fusion in path loss prediction for vehicular communication scenarios is validated, which shows a 19.8\% improvement in accuracy compared to predictions based on uni-modal data.

Previous work has pointed to the physical mechanisms behind the nocturnal offshore propagation of convection south-west of Sumatra. Low-level moisture flux convergence due to the land breeze front controls the progression of a squall line away from the coast overnight. However, the diurnal convection over the mountains occurs on only 57% of days in December-February (DJF) and propagates offshore on only 49% of those days. We investigate day-to-day variability in dynamical and thermodynamical conditions to explain the variability in diurnal convection and offshore propagation, using a convection-permitting simulation run for 900 DJF days. A convolutional neural network is used to identify regimes of diurnal cycle and offshore propagation behaviour. The diurnal cycle and offshore propagation are most likely to occur ahead of an active Madden-Julian Oscillation, or during El Niño or positive Indian Ocean Dipole; however, any regime can occur in any phase of these large-scale drivers, since the major control arises from the local scale. When the diurnal cycle of convection occurs, low-level wind is generally onshore, providing convergence over the mountains; and low-level humidity over the mountains is high enough to make the air column unstable for moist convection. When this convection propagates offshore, mid-level offshore winds provide a steering flow, combined with stronger convergence offshore due to the land breeze or convection-triggered cold pools. Low-level moisture around the coast also means that, as the convection propagates, the storm-relative inflow of air into the system adds greater instability than would be the case on other days.

• Time-frequency analysis of the the total solar irradiance (TSI) dataset recoreded by the FY3E/JTSIM/DARA • DARA observations (in WRR scale) on average higher than measurements recorded with other instruments: ∼ 2.2 Wm −2 (VIRGO/PMO6), ∼ 1.2 Wm −2 (TIM/TSIS-1) and ∼ 1 Wm −2 (SIAR). • Analysis of the integration of the new JTSIM-DARA dataset into the 43 year long TSI composite time series

Predicting the relative susceptibility of reef areas to storm damage is important to stakeholders. Damage susceptibility depends primarily on exposure to waves and the fragility of the resident corals. Coral fragility is primarily related to shape and size which are related to species. Calculations based on colony measurements implies a large difference, O(10-100:1) between the fragility of massive and branching species. Here we estimate the relative fragility of various species using detailed damage survey data from 150 sites in Puerto Rico (PR) and 67 sites in Florida following the passage of hurricanes Irma and Maria in September of 2017. In PR both a transect and a roving survey were conducted near most sites. The damage measured in the two surveys near the same sites were not well correlated, making them relatively independent. We estimate species fragility as the average fraction damaged across all surveys of each type where that species was reported. Contrary to the same site damage results, the relative fragility between species was highly correlated across the different survey types. The difference between the measured fragility of branching and massive species was much smaller O(4:1) than the geometric calculations imply and there were variations within the massive species which were consistent and were significant when used in a simple reef damage model.

Sea surface salinity (SSS), an essential climate variable that is sensitive to changes in the global water cycle, varies seasonally in many places due to annual variations in rainfall and evaporation, as well as vertical mixing and advection. The seasonal variability of global mean SSS, with maximum/minimum SSS in March/September has been increasing in amplitude since the start of the satellite observation era in 2010. This variability, with a range of 0.03, implies approximately 2 cm of water leaving from and returning to the surface of the ocean over the course of the year, with its 0.01 increase in range since 2011, roughly equating to an additional 0.7 cm of water cycling out and returning to the ocean. This trend is consistent with predictions of an accelerating global water cycle on a warming planet.

A document by Ray Nassar. Click on the document to view its contents.

Magnetic reconnection, an essential mechanism in plasma physics that changes magnetic topology and energizes charged particles, plays a vital role in the dynamic processes of the Jovian magnetosphere. The traditional Vasyliūnas cycle only considers the effect of magnetic reconnection at the nightside magnetodisk. Recently, magnetic reconnection has been identified at the dayside magnetodisk in Saturn's magnetosphere and can impact dayside auroral processes. In this study, we provide the first evidence that the dayside magnetodisk reconnection can also occur at Jupiter. Using data from the Galileo and Voyager 2 spacecraft, we have identified 18 dayside reconnection events with radial distances in the range of 30–60 Jupiter radii (RJ). We analyzed the particle (electron and ion) flux, energy spectra, and characteristic energy of these dayside events and compared them to the nightside events. The statistical results show that the energy spectra and characteristic energy of electrons/ions in dayside and nightside magnetic reconnection events are comparable. On average, the characteristic energy of ions on the dayside is higher than that on the nightside. Based on the limited data set, we speculate that the occurrence rate of dayside magnetodisk reconnection should be significant. The dayside Jovian magnetodisk reconnection seems to have a comparable effect on providing energetic particles as that at nightside and to be one of the key processes driving dynamics within the Jovian magnetosphere.

A document by Kristian Strommen. Click on the document to view its contents.