Marine dissolved organic carbon (DOC) is a major carbon reservoir influencing climate, but is poorly quantified. The lack of a comprehensive DOC climatology hinders model validation, estimation of the modern DOC inventory, and understanding of DOC’s role in the carbon cycle and climate. To address this problem, we used boosted regression trees to relate a compilation of DOC observations to different environmental climatologies, and extrapolated these inferred relationships to the entire ocean to compute annual layer-wise DOC climatologies with uncertainties. Prediction performance was satisfactory, with R² values within 0.6 - 0.8 for all layers and prediction error comparable to within-pixel measurement variability. DOC was mainly predicted by dissolved oxygen in the bathypelagic layer, and by nutrients in other layers. We estimate the total oceanic DOC inventory to be around 690 Pg C. Our results exemplify that machine learning is a powerful tool for constructing climatologies from limited observations.

Recoil leaders develop in lightning flash decayed channels. The propagation of a recoil leader depends on its intensity and on the conductivity of the decayed channel. When the recoil leader is strong enough to propagate over the entire channel, a subsequent return stroke happens. When the recoil leader is not intense enough, only a partial reconstruction of the channel occurs, that is, only part of the decayed channel is reionized. The present work aims to analyze the herein named secondary recoil leader that originates near a previously formed recoil leader. When these secondary recoil leaders develop and connect to previous recoil leaders, they provide enough energy for the recoil leader to reionize the whole decayed channel of the lightning flash. High-speed videos analysis of upward lightning flashes shows that secondary recoil leaders play an important role on the formation and progression of dart leaders/subsequent return strokes.

In this study, 42 years of tidal records and landfall TC best tracks in Japan were used to demonstrate that TC pre-landfall forward speed is significantly correlated with maximum storm surge height. Coastal morphology was the determining factor for the correlation between storm surge and TC forward speed. Fast-moving TCs tended to amplify the storm surge along open coastlines (Pearson correlation coefficient, R = 0.62), but reduce it in semi-enclosed bays (R = -0.52). The negative correlation contrasts with the general perception that the coincidence of TC wind speed and forward speed vectors generates a larger storm surge. The influence of coastal morphology was most prominent for TCs with a central pressure lower than 956 hPa. Tropical cyclone (TC) operational forecasts are continuously improving; however, there is still scope to improve the precision of storm surge predictions. These findings could contribute to the improvement of storm surge forecasting and provide emergency management personnel with more precise early warnings of dangerous storm surges.

We report on three classes of terrestrial gamma-ray flashes (TGFs) from the Reuven Ramaty High-Energy Solar Spectroscopic Imager (RHESSI) satellite. The first class drives the detectors into paralysis, being observed usually through a few counts on the rising edge and the later tail of Comptonized photons. These events – and any bright TGF – reveal their true luminosity more clearly via their Compton tail than via the main peak, since the former is unaffected by the unknown beaming pattern of the unscattered radiation, and Comptonization mostly isotropizes the flux. This technique could be applied to TGFs from any mission. The second class is more than usually bright and long in duration. When the magnetic field at the conjugate point is stronger than at the nearby footpoint, we find that 4 out of 11 such events show a significant signal at the time expected for a relativistic electron beam to make a round trip to the opposite footpoint and back. We conclude that a large fraction of TGFs lasting more than a few hundred microseconds may include counts due to the upward-moving secondary particle beam ejected from the atmosphere. Finally, using a new search algorithm to find short TGFs in RHESSI, we see that these tend to occur more often over the oceans than land, relative to longer-duration events. In the feedback model of TGF production, this suggests a higher thunderstorm potential, since more feedback per avalanche implies fewer “generations” of avalanches needed to complete the TGF discharge.

Lake Powell is a major reservoir responsible for providing water resources throughout the Colorado River Basin. Here we develop a hybrid model to perform 1-4 month forecasts of the inflow to Lake Powell. First, observational data are used in early December for a binary prediction of high- or low-flow based on peak monthly inflow or April-July inflow, and our prediction is much better than the Colorado Basin River Forecast Center (CBRFC)’s forecasts for the 1982-2016 study period. Second, we calibrate the NCEP Climate Forecast System seasonal forecasts of temperature, precipitation, and snow mass, and use them to perform 1-4 month inflow prediction through a regression equation, with the coefficients determined for the high- and low-flow years separately. Our early April forecasts for the critical April-July inflow are better than those of the CBRFC from 1982-2016. Sensitivity tests have also demonstrated the value of including snow mass in our prediction.

At some submarine volcanoes, the influx and output of magma vary over time producing years-to-decades-long cycles of inflation and deflation, which in turn cause pronounced physical changes in the overlying oceanic crust and the hydrothermal circulation hosted within. Permeability within the oceanic crust exerts primary control on seafloor fluid circulation and hence has important influences on the heat and chemical exchange between the earth's lithosphere and oceanic hydrosphere, as well as surface and subsurface biological communities. Despite its importance, permeability is one of the most poorly constrained hydrologic properties for most of the mid-ocean ridge system. In this study, harmonic analysis of a high-resolution, long-term time series of effluent temperature measured at a high-temperature hydrothermal vent on Axial Seamount yields time-varying estimates of the effective permeability within the hydrothermal upflow zone. Comparing the records of permeability and volcanic deformation during and after the April-May 2015 eruption at Axial suggests a decrease in upflow-zone permeability during co-eruptive deflation and an increase in permeability during post-eruption re-inflation from July 2015 to June 2019. Modeling of the three-dimensional strain field suggests that the temporal variations in effective upflow-zone permeability can be explained by closing and opening of hydrothermal pathways that accompany crustal compression and extension in relation to the volcano's deformation cycle.

Different timescales of the daily amplitude of the geomagnetic Y component during quiet period (Sq(Y)) over several solar cycles at 25 mid-low latitudes observatories were analyzed. The annual mean (Sq0), annual (Sq1) and semiannual (Sq2) components were separated from Sq(Y) by means of Fourier analysis method. No obvious distinction is found for the morphology of the spatial distribution of these Sq(Y) components during solar quiet and active periods, except that they are more intense in high solar activity. Sq1(Y) exhibits a remarkable longitudinal inequality, which is much stronger around Eurasia and Australia anomaly zones and weaker around South Atlantic Ocean anomaly zones. The positive correlation between Sq0(Y) and geomagnetic vertical component Z suggests that the convection electric fields in the dynamo region play a key role in controlling annual mean (Sq0). On the other hand, the Sq1(Y) exhibits a positive correlation with geomagnetic horizontal component H, implying the inter-hemispheric field-aligned currents (IHFACs) may contribute to difference of the annual variation amplitude at different observatories. The Sq2(Y) is most prominent in the South Atlantic Ocean anomaly (SAO) region. It is possible the stronger ionospheric conductivity in the dynamo region contribute to the remarkable semiannual variation at SAO region.

Tomographic imaging based on long-term ambient seismic noise measurements, mainly the phase information from surface waves, has been shown to be a powerful tool for geothermal reservoir imaging and monitoring. In this study, we utilize seismic noise data from a dense nodal array (192 3C nodes within 20km2) over a ultra-short observation period (4.7 days) to reconstruct surface waves and determine the high-resolution (0.2km) three-dimensional (3-D) S wave velocity structure beneath a rural town in Zhejiang, China. We report the advantage of cross-coherence over cross-correlation in suppressing pseudo-arrivals caused by persistent sources. We use ambient noise interferometry to retrieve high quality Rayleigh waves and Love waves. Body waves are also observed on the R-R component interferograms. We apply phase velocity dispersion measurements on both Rayleigh waves and Love waves and automatically pick more than 23,000 dispersion curves by using a Machine Learning technique. 3-D surface wave tomographic results after depth inversion indicate low-velocity anomalies (between -1% and -4%) from the surface to 2km depth in the central area. Combined with the conductive characteristics observed on resistivity profile, the low-velocity anomalies are inferred to be a fluid saturated zone of highly fractured rock. Joint interpretation based on HVSR measurements, and existing temperature and fluid resistivity records observed in a nearby well, suggests the existence of the high-temperature geothermal field through the fracture channel. Strong correlation between HVSR measurements and S wave velocity model sheds light on the potential of extraction of both amplitude and phase information from ambient noise.

Chloride salt-bearing deposits are widely distributed across the southern highlands of Mars. Because chloride salts are highly water-soluble, these deposits may be representative of the last significant period of stable liquid water at the Martian surface. Therefore, these deposits are key to understanding the fate and evolution of surface waters on Mars. Yet, little consensus exists about the formation conditions of these deposits, and their origins remain enigmatic. This is due in part because remote spectroscopic detection and quantification of many chlorides is hampered by a lack of easily discernible diagnostic absorption features. To address this issue, we present a novel Hapke radiative transfer model (RTM)-based method to estimate hydration states and salt abundances of Martian chloride salt-bearing deposits using visible/near-infrared (VNIR) reflectance spectra. VNIR laboratory spectra are used to derive water abundances of analog chloride-bearing materials, establishing an experimental basis for application of these methods to Mars. These methods are then applied to orbital Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) data to create maps of hydration state and modeled salt abundance of chloride-bearing deposits. When overlain onto high resolution 3D digital terrain models (DTMs), these methods produce the highest resolution, site-specific salt abundance maps currently available, enabling new discoveries and understanding of geologic context. As an example, deposits in the Terra Sirenum region are observed to have higher estimated salt abundances than previously recognized, exhibiting spatial variations in both abundance and surface morphology.

Cooling magma plutons and intrusions are the heat sources for hydrothermal systems in volcanic settings. To explain system longevity and observed heat transfer at rates higher than those explained by pure conduction, the concept of fluid convection in fractures that deepen because of thermal rock contraction has been proposed as a heat-source mechanism. While recent numerical studies have supported this half a century old hypothesis, understanding of the various regimes where convective downward migration of fractures can be an effective mechanism for heat transfer is lacking. Using a numerical model for fluid flow and fracture propagation in thermo-poroelastic media, we investigate scenarios for which convective downward migration of fractures may occur. Our results support convective downward migration of fractures as a possible mechanism for development of hydrothermal systems, both for settings within active zones of volcanism and spreading and, under favorable conditions, in older crust away from such zones.

A particular strength of lightning remote sensing is the variety of lightning types observed, each with a unique occurrence context and characteristically different emission. Distinct energetic intra-cloud (EIC) lightning discharges – compact intra-cloud lightning discharges (CIDs) and energetic intra-cloud pulses (EIPs) – produce intense RF radiation, suggesting large currents inside the cloud, and they also have different production mechanisms and occurrence contexts. A Low-Frequency (LF) lightning remote sensing instrument array was deployed during the RELAMPAGO field campaign in west central Argentina, designed to investigate convective storms that produce high-impact weather. LF data from the campaign can provide a valuable dataset for researching the lightning context of EICs in a variety of sub-tropical convective storms. This paper describes the production of an LF-CID dataset in RELAMPAGO, and includes a preliminary analysis of CID prevalence. Geolocated lightning events and their corresponding observed waveforms from the RELAMPAGO LF dataset are used in the classification of EICs. Height estimates based on skywave reflections are computed, where pre-fit residual data editing is used to improve robustness against outliers. Even if EIPs occurred within the network, given the low number of very high peak current events and receiver saturation, automatic classification of EIPs may not be feasible using this dataset. The classification of CIDs, on the other hand, is straightforward and their properties, for both positive and negative polarity, are investigated. A few RELAMPAGO case studies are also presented, where high variability of CID prevalence in ordinary storms and high-altitude positive CIDs, possibly in overshooting tops, are observed.

The spatiotemporal scale used to calculate extreme precipitation intensities can introduce strong biases when investigating their physical origin, impacts, and sensitivity to climate. Besides, the contribution of Mesoscale Convective Systems (MCSs) to tropical precipitation extremes remains loosely quantified on various scales, in particular on kilometer scales. Here we analyze the co-occurrence of extreme precipitation at convective and mesoscale levels to compare their properties in terms of precipitation morphology and regional predominance. Using a storm tracking algorithm, we contrast the occurrence and rain statistics for various types of convective systems across ten global storm-resolving models and one geostationary satellite product. We find a large statistical independence between rain extremes on these two scales, as they occur in distinct regions. Heavy km-scale events occur mostly over continents, over margins of convective zones, 40\% of which are produced by MCSs in observations. Their intensity is independent from the area of rain features. Conversely, heavy mesoscale rain intensities scale with the area of rain features, occur more frequently over oceans and a third of these events are produced by MCSs. More generally, a continuum between these extremes emerges from the wider variety of convective systems, quantified here as deep, very-deep and mesoscale convective systems. Compared to observations, models consistently underestimate the precipitating surface and show high variability in the contribution of convective systems to precipitation extremes at each scale. This diagnostic can serve as an evaluation criterion for the ability of GSRMs to represent how individual convective systems produce realistic heavy rain distributions.

This paper describes magnetospheric waves of very long wavelength in thin magnetic filaments. We consider an average magnetospheric configuration with zero ionospheric conductance and calculate waves using two different formulations: classic interchange theory and ideal MHD. Classic interchange theory, which is developed in detail in this paper, is basically analytic and is relatively straightforward to determine computationally, but it can’t offer very high accuracy.The two formalisms agree well for the plasma sheet and also for the inner magnetosphere. The eigenfrequencies range over about a factor of seven, but the formulations generally agree with a root-mean-square difference of the $log_{10}$ of the ratio of the interchange to MHD frequencies to be $\sim 0.054$. The pressure perturbations in the classic interchange theory are assumed constant along each field line, but the MHD computed pressure perturbations along the field line vary in a range $\sim 30 \%$ in the plasma sheet but are larger in the inner magnetosphere. The parallel and perpendicular displacements, which are very different in the plasma sheet and inner magnetosphere, show good qualitative agreement between the two approaches. In the plasma sheet, the perpendicular displacements are strongly concentrated in the equatorial plane, whereas the parallel displacements are spread through most of the plasma sheet away from the equatorial plane; and can be regarded as buoyancy waves. In the inner magnetosphere, the displacements are more sinusoidal and are more like conventional slow modes. The different forms of the waves are best characterized by the flux tube entropy $PV^\gamma$.

The lunar polar regions offer permanently shadowed regions (PSRs) representing the only regions which are cold enough for water ice to accumulate on the surface. The Lunar Exploration Neutron Detector (LEND) aboard the Lunar Reconnaissance Orbiter (LRO) has mapped the polar regions for their hydrogen abundance which possibly resides there in the form of water ice. Neutron Suppression Regions (NSRs) are regions of excessive hydrogen concentrations and were previously identified using LEND data. At each pole we applied thermal modeling at three NSRs and one unclassified region to evaluate the correlation between hydrogen concentrations and temperatures. Our thermal model delivers temperature estimates for the surface and for 29 layers in the sub-surface down to 2 m depth. As anticipated, we find the three south polar NSRs which are coincident with PSRs in agreement with locations of hydrogen abundance and their respective (near-)surface temperatures. Water ice is suspected to be present in the upper ≈19 cm layer of regolith. The three north polar NSRs however lie in non-PSR areas and are counter-intuitive as such that most surfaces reach temperatures that are too high for water ice to exist. However, we found that these areas offer ideal conditions for ice pumping and suggest water ice to depths down to ≈35-65 cm. These depths are observable by LEND and can, at least in part, explain the existence and shape of the observed hydrogen signal. Although we can substantiate the anticipated correlation between hydrogen abundance and temperature the converse argument cannot be made.

In this study, we use a parametrized model of ionospheric electrodynamics to investigate the effect of Region 2 currents’ location on the development and dynamics of the auroral electrojet (AE), using real cases data as input parameters for our simulations. We calculated the maps of equivalent ionospheric currents reproducing the events of interest, analyzed the results and compared with SuperMAG observations. The simulations have shown that strong R2 currents provide a robust closure for the ionospheric currents flowing from R1 via auroral zone ionosphere. We found that the highest magnitude westward auroral electrojet is in the day-to-dawn sector, while the equivalent ionospheric currents on the night-side have much lower magnitude. We suggest that the location of the R2 currents affects the entire distribution of ionospheric currents, changing the MLT location and magnitude of the maximum auroral electrojet. As the distance between the location of the maxima for the R1 and R2 current systems increases, the magnitude of the ionospheric currents decreases because the ionospheric currents spread over larger regions at low latitudes. When R2 currents cannot provide the proper closure, the ionospheric currents flow from the dawn to dusk over the night-side ionosphere, leading to the westward auroral electrojet development in the night region of the auroral zone. We analyzed features and magnitude of these currents and compared with observations.

Soil water repellency (SWR) is a temporary property of the soil that changes the functionality of the soil across a soil-specific range in soil moisture content (W). The severity and persistence of soil water repellency in agricultural soils is important in understanding and predicting its effects on the soil hydrological processes to optimize plant growth. Therefore, this study aimed at characterizing the persistence of SWR using Water Drop Penetration Time (WDPT) test; evaluating the SWR curve as a function of gravimetric water content from the WDPT results and finally developing relationships between SWR parameters (SWRAREA and Wc) and soil properties (TOC, Sand, Silt, Clay) to understand the persistence of SWR and its effect on water flow. The degree of SWR as a function of soil moisture content was measured and monitored from oven-dry conditions to the water content at which the soils turned hydrophilic (Wc). The total SWR (SWRAREA) was calculated as the trapezoidal area under the SWR-w curve. A total of 37% of the soils investigated were water repellent. The soils investigated had a wide range in clay (10-40%) and TOC (0.67-6.08%). The SWR-w curves were either single or double peaked. SWRAREA ranged from 8.38 second/%soil moisture content to 24.91 seconds/%soil moisture content. TOC was the most important soil property in explaining the total degree of SWR(SWRAREA) and Wc. Inclusion of Clay and silt in the Multiple Linear Regression (MLR) expression of SWRAREA significantly improved the prediction of SWRAREA to 85%. Further, an upper limit critical water content was derived from the simple relationship between the Wc and TOC, which could be applied to improve irrigation practices of agricultural soils of Murang’a County in Kenya. It is however advisable to develop soil type specific models for Wc as a function of TOC when more comprehensive data is available for each soil type.

Global average upper atmosphere temperature changes linked with the Hunga volcanic eruption (January 2022) are analyzed based on satellite measurements and compared with chemistry-climate model simulations. Results show stratospheric cooling of -0.5 to -1.0 K in the middle and upper stratosphere during 2022 through middle 2023, followed by stronger cooling (-1.0 to -2.0 K) in the mesosphere after middle 2023. The cooling patterns follow the upward propagating water vapor (H2O) anomalies from Hunga, and similar behavior is found between observations and model simulations. While the stratospheric cooling is mainly due to radiative cooling from enhanced H2O, the mesospheric temperature changes result from ozone losses in the mesosphere, which are in-turn driven by HOx radicals from Hunga H2O. Comparisons with the multi-decade climate record show that Hunga impacts on stratospheric temperatures have similar magnitude, but opposite sign, to temperature effects from the large El Chichón (1982) and Pinatubo (1991) volcanic eruptions.

The inevitable coarse pixels (~25 km) of satellite passive microwave images introduced large uncertainty to the surface melt area estimation on Antarctic ice margins. Our test showed that the melt index of the Austral year 2012-13 in the Antarctic Peninsula calculated from the high resolution product was 33% lower than the original Special Sensor Microwave/Imager (SSM/I) images. Therefore, by allowing for fractional melt estimation, a subpixel mapping method was adopted in this research to improve the accuracy and reliability of surface melt measurement from passive microwave images. This innovative method uses the least squares mixture analysis (LSMA) on the time series of daily passive microwave images by taking advantage of their high temporal resolution. The endmembers for the unmixing calculation were collected under the constraint of voronoi polygons. The fractional melt index of each pixel was calculated by multiplying its area with melt fraction. By using the high resolution passive microwave earth system data record (PMESDR) dataset as the reference, we found that compared with the original SSM/I images, the overestimation of surface melt was corrected by the unmixing analysis. A log-linear regression between melt fraction and elevation showed that the melt fraction is inversely correlated to the elevation, and the topography is the dominant factor for melt fraction distribution in high elevations. We recommend such a treatment of linear unmixing analysis on the passive microwave images to be used for future surface melt mapping in Antarctica and Greenland.