Anthropogenic activities are altering flood frequency-magnitude distributions along many of the world’s large rivers, yet isolating the impact of any single factor amongst the multitudes of competing anthropogenic drivers is a persistent, yet important challenge if we are to mitigate their negative consequences. The Usumacinta River in southeastern Mexico provides an ideal opportunity to study an anthropogenic driver in isolation: tropical forest conversion. This article employs a novel approach to disentangle the anthropogenic signal from climate variability, and provides valuable insights into the impact of forest conversion on flood severity. Here we analyse continuous daily time series of precipitation, temperature, and discharge to identify long-term trends, and compare ratios of catchment-wide precipitation totals to daily discharges in order to account for climatic variability. We also identify an anthropogenic signature of tropical forest conversion at the intra-annual scale, successfully reproduce this signal using a distributed hydrological model (VMOD), and demonstrate that the continued conversion of tropical forest to agricultural land use will further exacerbate large-scale flooding. We find statistically significant increasing trends in annual minimum, mean, and maximum discharges that are not evident in either precipitation or temperature records. We also find that mean monthly discharges have increased between 7% and 75% in the past decade, in contrast to mean monthly precipitation, which shows no statistically significant trend. Model results demonstrate that forest cover loss is responsible for raising the 10-year return peak discharge by 25%, while the total conversion of forest to agricultural use would result in an additional 18% rise. These findings highlight the need for a holistic approach to catchment-wide land management in tropical regions that weights the benefits of agricultural expansion against the consequences of increased flood prevalence, and the economic and social costs that they incur.

Next to precipitation, secondary water sources emerging from shallow groundwater and lateral redistribution of soil moisture, together with soil properties modulating their accessibility are highly important in water-limited ecosystems. However, effects of these land-associated secondary inputs are not well known over large domains given the mismatch of spatial scales of processes. Here, we quantify the role of land properties on the spatial variations of seasonal decay rate of vegetation cover over water-limited regions of Africa, using machine learning. Over the study domain, 17 % of these variations are directly attributed to land properties, and 16 % are attributed to interaction effects of land properties with climate and vegetation. Locally, total land attributed variations account for more than 60 % in hotspots with different land properties like shallow groundwater, complex topography, and favourable soil properties. Our findings lend empirical evidence for the importance of local-scale secondary water inputs over large domains.

Deep-sea polymetallic sulfides formed by hydrothermal activity are considered a potential resource for economically valuable base and precious metals. The Southwest Indian Ridge (SWIR, Indian Ocean) hosts active and inactive hydrothermal systems. Inactive hydrothermal fields are more abundant but difficult to characterize. We report a self-potential investigation to locate inactive ore deposits at the Yuhuang hydrothermal field on the ultraslow-spreading SWIR. A horizontal array of 6 AgCl electrodes were attached to a dual towed transient electromagnetic system to record the electrical field at a height of 40 m above the seafloor. The observed electrical field strength near the known sulfide drills reaches 0.5 mV/m. Negative self-potential anomalies (~ -25 mV, obtained by integrating the electrical field) were observed. High electrical conductivities (up to 12 S/m) of sulfide samples measured in the laboratory and the oxidize sulfides recovered at the outcrop of the deposit suggest that the self-potential anomalies are due to sulfides mineralization and corrosion of the polymetallic sulfides. Tomography of the self-potential anomalies reveals a localized current source distribution with a thickness of ~65 m. Our field data demonstrate that the self-potential method is a useful exploration method to characterize seafloor sulfides localized in inactive hydrothermal fields at mid-ocean ridges.

Snow algae are found from spring to summer on snowfields and glaciers throughout the world. Their blooming darkens snow surfaces, reducing snow surface albedo and accelerating melting. Uncertainties remain, however, regarding the blooming season and global distribution of these algae. To reproduce snow algal bloom temporal and spatial variability, we improved an existing snow algae model using a land surface model calibrated with a global atmospheric reanalysis dataset. Snowfall and daylight length data for selected model locations were also incorporated. To evaluate its performance, we used in situ observational data from 15 polar to alpine area sites. The improvements made in this study allowed the reconstruction of detailed snow algal blooming reports from various locations worldwide, and the results suggested that the major factors affecting the appearance of snow algal blooming were the snow melting period duration and algal growth interruption by new snow cover. We then incorporated the updated snow algae model into a land surface model and performed a global simulation. In this case, our simulation suggested that red snow could appear on snowfields during the melting season but only in the absence of frequent new snow falls, and if the snow cover persists long enough to allow prolonged algal growth.

A significant stress drop characterizes sometimes earthquakes induced by injection or extraction of fluids in rocks. Moreover, long-term fluid operations in underground reservoirs can impact a seismogenic reaction of the rocks per a unit volume of the involved fluid. The seismogenic index is a quantitative characteristic of such a reaction. We derive a relationship between the seismogenic index and the stress drop. We propose a simple and rather general phenomenological model of the stress drop of induced events in various faulting regimes. Our results suggest that high stress drops of some earthquakes induced by long-term underground fluid operations may be controlled by drops of cohesion of more cohesive faults getting seismically activated due to gradually increasing with time differential stresses. On the one hand, this effect can result in an increase of seismogenic index with production time. On the other hand, a production-caused depleting of the pore pressure can also cause a systematic increase of the stress drop. This provides an additional contribution to the growth of seismogenic index with production time at such reservoirs.

Based on satellites monitoring of the X-Rays Precipitations (Solar Flares), Solar Proton Precipitations (Solar Proton Events), and Riometer absorption in association with F region plasma patches formed in the cusp and propagating into the polar cap, we estimate ionospheric D-Layer ionization caused by energetic electrons precipitations based on our Computational Model of D-Region Ion Production. Knowing D-Layer ionization mechanisms will allow us to monitor precipitating electron source rates based on routine ionospheric absorption measurements by the Canadian Geospace Observatory Riometer Network (GO-RIO).

In this paper we will propose a possible solution for the density parameter of dark energy. From the dimensionless unification of the fundamental interactions will be presended the formulas for the density parameter of dark energy. Also we will show the geometric representation of the density parameter for dark energy and the geometric representation of the relationship between the de Sitter radius and the Hubble length.

The Mercury’s magnetic fields are known to be weaker than that predicted by conventional dynamo models. In order to explain the Mercury’s weak magnetic field, several models are proposed (Stanley and Glatzmaier, 2010). One of them is the thermoelectric dynamo, which drive the dynamo via the thermoelectric force (Stevenson, 1987). The field strength is proportional to the relative Seebeck coefficient between the core and the mantle. Because the Seebeck coefficient of insulators is more than one order larger than that of metals, the Seebeck coefficient of Mercury’s mantle is the central parameter. Therefore, we investigated the Seebeck coefficient of mantle minerals from the first-principles calculations. The structure relaxation and band structure calculations were conducted by using the Quantum ESPRESSO package. The bandgap energy was calibrated by means of the quasiparticles self-consistent GW (QSGW) approximation adopted in the ecalj package. The Seebeck coefficient was calculated via the Boltzmann equation implemented in the BoltzTraP package. The results indicate that the Seebeck coefficient of forsterite with a small amount of dopant exhibit comparable to that previously thought (|S| ~ 1000 μV/K). This value may constrain the upper limit. The Mercury’s mantle may contain ~3wt% FeO (Robinson and Taylor, 2001). The Fe substitution and O vacancy act as donor, which is predicted to reduce the Seebeck coefficient, significantly. The field strength also depends on the electrical conductivity of the mangle. Recent high pressure experiments suggest that the electrical conductivity of the Earth’s mantle is ~ 10^-2 Sm. Considering the both of the Seebeck coefficient and the electrical conductivity of mantle material, the field strength is calculated to be ~ 0.1 nT, which is significantly weaker than the observed value of 300 nT. Therefore, we conclude that the thermoelectric dynamo cannot generate the Mercury’s magnetic fields.

The spatial patterns of earthquake ground motion amplitudes are commonly represented using a double couple model that corresponds to shear slip on a planar fault. While this framework has proven successful in explaining low-frequency seismic recordings, at higher frequencies the wavefield becomes more azimuthally isotropic for reasons that are not yet well understood. Here we use a dense array of nodal seismometers in Oklahoma to study the radiation patterns of earthquakes in the near-source region where wavefield scattering effects are limited. At these close distances, the radiation pattern is predominantly double couple at low frequencies (<15Hz). At higher frequencies, the recorded wavefield contains significant isotropic and residual components that cannot be explained as path or site effects, implying complexity in the rupture process or local fault zone structure. These findings demonstrate that earthquake source complexity can drive variability in the ground motions that control seismic hazard.

Recent increasing wildfire activities in California have raised widespread public concerns. This raises a question as to whether the increase of of fire weather this year and in recent decades is mainly due to weather pattern change dominated by natural variability or anthropogenic warming. We observed that vapor pressure deficit (VPD), an important fire weather risk index, in the warm season (May to September) of California, has increased significantly since 1979, with a positive trend of 0.70 hPa or 0.50 σ per decade, and this trend is also significant for VPD in large fire days; trend analysis of saturated and actual vapor pressure suggests that direct warming and drying contributes to about 70% and 30%, respectively, to the positive VPD trend. This increase of VPD and warming for such a short period cannot be simply linked to anthropogenic factors as it can also be affected by circulation changes. Our self-organizing maps analysis reveals the close relationship between VPD and circulation. Using a flow analogue approach, we estimated circulation changes contribute to about half (54%) of the observed VPD trend. Since circulation changes represent the upper limit of internal variability of the climate system because both the internal climate variability and anthropogenic forcings can contribute to such a change, our results suggest that anthropogenic warming must explain at least the other half of the observed VPD trend.

Electric field measurements are necessary to understand thunderstorm evolution and lightning initiation. However, most existing measurements are made with single instruments carried by weather balloons. It is difficult to interpret such data since a change in observed electric field could be due either to motion of the instrument or charging/discharging currents. In order to decouple these behaviors, it is necessary to make simultaneous measurements at multiple locations. To avoid the complexity of multiple balloon launches, we describe a single balloon instrument with multiple, independent dropsondes to be released at desired time intervals. The dropsondes are designed to rotate and be self stabilizing, enabling them to measure electric fields as they fall. The dropsondes are lightweight, robust, and low-cost, and include a preamplifier, GPS receiver, search coil and accelerometer for orientation sensing, microcontroller, and a telemetry system to transmit data to a ground station. Prototype instruments have been drop-tested to demonstrate aerodynamic stability and rotation and have been calibrated for electric field measurement. A balloon payload set to release a set of such dropsondes via hot-wire release mechanisms can thus accomplish the goal of multi-point measurements of thunderstorm electrical structures.

A document by Tae Kim. Click on the document to view its contents.

A drift-diffusion model is used to simulate the low-altitude electron distribution, accounting for azimuthal drift, pitch angle diffusion, and atmospheric backscattering effects during a rapid electron dropout event on August 21st, 2013, at L=4.5. Additional external loss effects are introduced during times when the low-altitude electron distribution cannot be reproduced by diffusion alone. The model utilizes low-altitude electron count rate data from five POES/MetOp satellites to quantify pitch angle diffusion rates. Low-altitude data provides critical constraint on the model because it includes the drift loss cone region where the electron distribution in longitude is highly dependent on the balance between azimuthal drift and pitch angle diffusion. Furthermore, a newly derived angular response function for the detectors onboard POES/MetOp is employed to accurately incorporate the bounce loss cone measurements, which have been previously contaminated by electrons from outside the nominal field-of-view. While constrained by low-altitude data, the model also shows reasonable agreement with high-altitude data. Pitch angle diffusion rates during the event are quantified and are faster at lower energies. Precipitation is determined to account for all of the total loss observed for 350 keV electrons, 76% for 600 keV and 45% for 900 keV. Predictions made in the MeV range are deemed unreliable as the integral energy channels E3 and P6 fail to provide the necessary constraint at relativistic energies.

Snow distribution is a function of interactions among static variables, such as terrain, vegetation, and soil properties, and dynamic meteorological variables, such as wind speed and direction, solar radiation, and soil moisture that occur over a range of spatial scales. However, identifying the dominant physical drivers responsible for spatial patterns of the snowpack, particularly for ephemeral, shallow snowpacks, has been challenged due to the lack of the high-resolution snowpack and physical variables with high vertical accuracy as well as inherent limitations in traditional approaches. This study uses an Unpiloted Aerial System (UAS) lidar-based snow depth and static variables (1-m spatial resolution) to analyze field-scale spatial structures of snow depth and apply the Maximum Entropy (MaxEnt) framework to identify primary controls over open terrain and forests at the Thompson Farm Research Observatory, New Hampshire, United States. We found that, among nine topographic and soil variables, plant functional type and terrain roughness contribute up to 80% and 76% of relative importance in MaxEnt to predicting locations of deeper or shallower snowpacks, respectively, across the landscape. Soil variables, such as organic matter and saturated hydraulic conductivity, were also important controls (up to 70% and 81%) on snow depth spatial variations for both open and forested landscapes suggesting spatial variations in soil variables under snow can control thermal transfer among soil, snowpack, and surface-atmosphere. This work contributes to improving land surface and snow models by informing parameterization of the sub-grid scale snow depths, downscaling remotely sensed snow products, and understanding field scale snow states.

Sun–Jupiter decade-scale magnetic entanglement emerges from Wilcox Solar Observatory 1975-2021 N–S ≲150 μT mean-field data, as a global response of solar magnetic fields to the magnetar-type evolution of Jupiter ~2001–onward global magnetoactivity discovered recently in the 1–6 month (385.8–64.3 nHz) band of Rieger resonance. At extreme ≲20% field variance, the sudden Jovian deviation is so high it forced solar magnetoactivity devolution into inverse-matching response, at effectively moderate ≲1.5% mean-field variance. Thus as Jupiter magnetoactivity evolved sinusoidally, the Sun began mirror-compensating ~2002 (the epoch of Abbe number drop), reducing its magnetoactivity in decreasingly sinusoidal fashion to solar cycle 24 extreme minimum. For check, 2004-2021 WIND mission data revealed <0.5-var% (<5-dB) calm ≲50 nT interplanetary magnetic field at L1, slightly undulated by the Jupiter evolution impulse, thus excluding solar wind and Sun as impulse sources (confirmed by statistical fidelity waning down Jupiter–L1–Sun diffusion vector spaces, as 10^7–10^3–10^2). Magnetic tangling of stars and hot (<0.1 AU) Jupiters was blamed previously for observed star superflaring 10^2–10^7 times more energetic than the strongest solar flare. Accordingly, the Sun ante-impulse locking is a shock-absorbing mechanism — routine shutter-response to Jupiter recurrent phasing into the flare-brown-dwarf state — with which the Sun enters a grand minimum (sleep mode). As Jupiter intermittently becomes an indirect driver of Earth’s climate, the Sun prepares to discharge stored energy as a non-extinction ~10^32-erg superflare (currently overdue). The mechanism, in which warm/cold Jupiters too trigger (mild) superflares, possibly defends stars against incoming Jupiters.

An interplanetary shock can abruptly compress the magnetosphere, excite magnetospheric waves and field-aligned currents, and cause a ground magnetic response known as a sudden commencement (SC). However, the transient (<~1 min) response of the ionosphere-thermosphere system during an SC has been little studied due to limited temporal resolution in previous investigations. Here, we report observations of a global reversal of ionospheric vertical plasma motion during an SC on 24 October 2011 using ~6 s resolution SuperDARN ground scatter data. The dayside ionosphere suddenly moved downward during the magnetospheric compression due to the SC, lasting for only ~1 min before moving upward. By contrast, the post-midnight ionosphere briefly moved upward then moved downward during the SC. Simulations with a coupled geospace model suggest that the reversed E X B vertical drift is caused by a global reversal of ionospheric zonal electric field induced by magnetospheric compression during the SC.

A chain of magnetometers has been placed in Antartica for comparisons with magnetic field measurements taken in the northern hemisphere. The locations were chosen to be on magnetic field lines that connect to magnetometers on the western coast of Greenland, despite the difficulty of reaching and working at such remote locations. We report on some basic comparisons of the similarities and differences in the conjugate measurements. Our results presented here confirm that the conjugate sites do have very similar (symmetric) magnetic perturbations in a handful of cases, as expected. Sign reversals are required for two components in order to obtain this agreement, which is not commonly known. More frequently, a strong Y component of the Interplanetary Magnetic Field (IMF) breaks the symmetry, as well as the unequal conductivities in the opposite hemispheres, as shown in two examples. In one event the IMF Y component reversed signs twice within two hours, while the magnetometer chains were approaching local noon. This switch provided an opportunity to observe the effects at the conjugate locations and to measure time lags. It was found that the magnetic fields at the most poleward sites started to respond to the sudden IMF reversals 18 min after the IMF reaches the bow shock, a measure of the time it takes for the electromagnetic signal to travel to the magnetopause, and then along magnetic field lines to the polar ionospheres. An additional 9 to 14 min is required for the magnetic perturbations to complete their transition.

• Two fresh anomalies observed in the eastern subpolar North Atlantic upper ocean during 1992-2017 share similar spatial characteristics. • Salt budget analysis shows the 2012-2016 fresh anomaly in the upper 200 m occurs due to transport of anomalous salinity by mean currents. • In contrast, the fresh anomaly in the 1990s is due to anomalous circulation of the mean salinity field.