The question of what drives tectonic plates has been revitalized by seismic observations that cannot be explained by conventional plate-driving forces. The observations, designed to constrain flow in the asthenosphere, are consistent with the asthenosphere locally flowing faster than the plate above and in a direction offset from plate motion. These inferences are not consistent with plates being driven exclusively by slab-pull and/or ridge-push forces. Mantle convection models were put forth to argue that pressure-driven flow, interacting with a non-Newtonian upper mantle viscosity, could explain these observations. To test the robustness of those results, we expand the models to allow for the development of weak plate margins and associated plate-like behavior. We find that with weak margins, the overall component of slab-driven flow becomes stronger while pressure driven asthenosphere flow remains active. Locally, the asthenosphere can lead plates and there are rotations in the direction of asthenosphere flow with depth. The balance of plate driving forces (i.e., the ratio of slab-pull to asthenosphere flow) is found to depend on plate margin strength. The models also indicate that a non-Newtonian upper mantle allows for a hysteresis effect such that, depending on initial conditions, single-plate and plate-tectonic modes can exist at the same parameter conditions.

High-speed data transfer and high-performance imaging can be realized by using radio-waves in high-frequency bands, such as millimeter-waves and THz-waves, where wide frequency bands are available. However, the cell size would be smaller than a few hundred meters, due to large free space propagation loss and large atmospheric attenuation. Thus, many base stations, which are connected by networks, are required to offer nation-wide or global network services by such high-frequency radio-bands. The networks would be constructed by various transmission media including optical fibers and fixed wireless links, where many media converters are required. This paper reviews various technologies for seamless bridges between radio and optical links. For the time being, congestion of radio spectrum in THz bands is not significant. However, if we look at the history of radio-wave technologies, spectral congestion has been high even in newly developed high frequency bands. Even in active radio services in millimeter-wave or THz-wave bands, interference mitigation with passive services such as radio astronomy and Earth observation satellites is an important issue, as of now. This paper describes research trends of THz-wave technologies from the point of view of a figure of merit defined by a product of the carrier frequency and spectral efficiency, to discuss the significance of spectral efficiency enhancement in the high-frequency region. Analysis of power consumption of short distance radio systems is also shown to discuss expected performance of THz-wave links.

Subtropical anticyclones and midlatitude storm tracks are key components of the large-scale atmospheric circulation. Focusing on the southern hemisphere, the seasonality of the three dominant subtropical anticyclones, situated over the South Pacific, South Atlantic and South Indian Ocean basins, has a large influence on local weather and climate within South America, Southern Africa and Australasia, respectively. Generally speaking, sea level pressure within the southern hemisphere subtropics reaches its seasonal maximum during the winter season when the southern hemisphere Hadley Cell is at its strongest. One exception to this is the seasonal evolution of the South Pacific subtropical anticyclone. While winter maxima are seen in the South Atlantic and South Indian subtropical anticyclones, the South Pacific subtropical anticyclone reaches its seasonal maximum during local spring with elevated values extending into summer. In this study we investigate the hypothesis that strength of the austral summer South Pacific subtropical anticyclone is largely due to heating over the South Pacific Convergence Zone. Using reanalysis data, and AGCM added cooling and heating experiments to artificially change the strength of diabatic heating over the South Pacific Convergence Zone, our results show that increased heating triggers a Rossby wave train over the Southern Hemisphere mid-latitudes by increasing upper-level divergence. The propagating Rossby wave train creates a high-low sea level pressure pattern that projects onto the center of the South Pacific Subtropical Anticyclone to intensify its area and strength. The southern hemisphere storm tracks also shift poleward due to increased heating over the South Pacific Convergence Zone.

The historical record of rainfall observation rarely provides sufficient record length and resolution required in many applications. The work described here presents a stochastic framework for long-term simulations of non-tropical storms at high spatial and temporal resolution. The framework adopts optimal estimation for spatio-temporal modeling of rain fields. A non-parametric approach featuring K-Nearest Neighbor Resampling (KNNR) plus the Genetic Algorithm (GA) mixing process is utilized for generating parameters in the long-term simulation. A case study is conducted in Dallas-Fort-Worth metroplex as the simulation domain. Ensemble parameters are generated using the KNNR+GA method from adjacent homogeneous areas and 10 years of radar rainfall observation. One hundred most rainy days in the 10 years are simulated at the resolutions of 4 × 4 km and 1 hour for 50 ensemble members. The simulated rainfall is thoroughly evaluated against the observed radar rainfall with respects to statistical moments, spatio-temporal structure, and frequency distribution of rainfall at both near-point scale and domain scale. The results indicate that ensemble simulations successfully reproduce key statistical properties of the observed rainfall. In addition, the approach is also effective and flexible in capturing heavy rainfall values, which is important for many hydrologic/hydraulic practices. As essentially a downscaling tool, this stochastic rainfall generator can have many applications where rainfall needs to be represented at finer spatiotemporal resolution.

Deep earthquakes in the lower continental lithosphere - the lower crust and uppermost mantle - are frequently too poorly located in depth to be definitively labelled as having occurred above or below the Mohorovičić discontinuity (Moho; base of the crust). Our Sn/Lg methodology utilizes two regional seismic waves to determine the depth of an earthquake relative to the Moho: Sn and Lg waves, which are phases that propagate through reflections in the mantle lid and the crust, respectively. Therefore, an analysis of Sn and Lg waves can provide a robust understanding of an earthquake’s depth relative to the Moho. We present our Sn/Lg analysis through reduced-velocity record sections, which show Sn and Lg energy in the waveform, allowing measurements of RMS amplitudes, and maps of ray-paths and Sn/Lg amplitude ratios which allow us to visualize the propagation of Sn and Lg in all directions. We demonstrate the efficacy of our approach by applying it to a well-known upper-mantle earthquake in Wyoming and a shallow earthquake with a similar epicenter. We then use our method to study other deep-crustal/upper-mantle earthquakes in North America. A cluster of earthquakes with reported depths from 10–50 km ± ~10 km, spans the border between Alberta, Canada and Montana, U.S.A. where the crustal thickness increases from ~30 km in the SW to ~45km in the NE. For an earthquake occurring in the crust-mantle transition zone, the dipping Moho should tend to block Sn (decrease the Sn/Lg ratio) in the direction of crustal thickening, and tend to block Lg (increase the Sn/Lg ratio) in the direction of crustal thinning. We studied seven earthquakes of magnitude>2.5. A m=2.7 earthquake, previously reported (USGS PDE) to be at 50±10 km where CRUST 1.0 shows a 49 km Moho depth, and a m=3.5 reported at 38 km depth above a nominal 43 km Moho, both show much stronger Sn/Lg ratios than earthquakes with nearby epicenters at nominal dots of 15 and 21 km. Hence the “50-km” and the “38-km” earthquakes must occur in the upper mantle, or so close to the upper mantle as to preferentially excite Sn. The better-recorded of these earthquakes also shows clear evidence of Sn enhancement along azimuths into regions of thinner crust.

We present a study analyzing relativistic and ultra relativistic electron energization and the evolution of pitch angle distributions using data from the Van Allen Probes. We study the connection between energization and isotropization to determine if there is a coherence across storms and across energies. Pitch angle distributions are fit with a Jsinθ function, and the variable ‘n’ is characterized as the pitch angle index and tracked over time. Our results show that, consistently across all storms with ultra relativistic electron energization, electrons become most anisotropic within around a day of Dst and relax down to prestorm isotropization levels in the following week. In addition, each consecutively higher energy channel is associated with higher anisotropy after storm main phase. Changes in the pitch angle index are reflected in each energy channel; when 1.8 MeV electrons increase (or decrease) in pitch angle index, so do all the other energy channels. In a superposed epoch study, we show that the peak anisotropies differ between CME- and CIR- driven storms and measure the relaxation rate as the anisotropy falls after the storm. The relaxation rate in pitch angle index for CME-driven storms is -0.14+/-0.023 at 1.8 MeV, -0.28+/-0.01 at 3.4 MeV, and -0.36±0.02 at 5.2 MeV. For CIR-driven storms, the relaxation rates are -0.09±0.01 for 1.8 MeV, -0.12±0.02 for 3.4 MeV, and -0.11±0.02 for 5.2 MeV. This study shows that there is a global coherence across energies and that storm type may play a role in the evolution of electron pitch angle distributions.

This presentation talks about the effect of portable ground control points (GCPs) on the accuracy of unmanned aerial vehicle (UAV)-based remote sensing data in predicting plant health. 6 GCPs equipped with GPS receivers were spaced around the experimental plots of citrus and strawberry. UAVs equipped with multispectral sensors were then used to collect the remote sensing data of citrus and strawberry plants. The remote sensing data was used to calculate various vegetation indices including normalized difference vegetation index (NDVI), Green NDVI, and soil adjusted vegetation indices (SAVI). These indices were compared with the data obtained from proximal sensors that include Handheld Spectroradiometer and Chlorophyll Meter. Correlation between various vegetation indices, chlorophyll content, and spectroradiometer data will be shown and discussed. A significantly higher correlation coefficients were obtained between the remote sensing and proximal sensor data when the GCPs were used. Increased accuracy of remote sensing data is important for the widespread adoption of UAV-based remote sensing technology for precision agriculture so that the technology can be used for site-specific input management by taking into account the infield variability.

Reflection profiles generated using PKPdf as a virtual source show laterally continuous reflections from structures at depths less than 1 km to roughly 200 km beneath the southern Appalachian orogen and Atlantic Coastal Plain. Arrivals interpreted as reflections from the Moho increase in time from ~10 s beneath the Coastal Plain to 17.4 s (~57 km) beneath the Blue Ridge Mountains, providing additional evidence that the southern Appalachians are in rough isostatic equilibrium. Reflections at 32-36 s (120-135 km) are consistent with the depth to the base of the lithosphere found in recent inversions of Ps arrivals and surface waves. Alternatively, these and later reflections at times up to 58 s (~224 km) may be due to layering associated with drag-induced flow in the asthenosphere, suggesting largely horizontal rather than vertical flow for depths less than 225 km beneath the Georgia coastal plain.

Estimates of net primary (NPP) and ecosystem production (NEP) are needed for tropical savanna, which is structurally diverse but understudied compared to tropical rainforest. Estimates of NPP and NEP are available from eddy covariance and inventory methods, but both approaches have errors and uncertainties. We used both methods to estimate carbon (C) fluxes for an upland mixed grassland and a seasonally flooded forest to determine the correspondence in C cycling components derived from these methods and assess the contribution of the various C cycling components to the overall NEP. Both techniques provided similar estimates of NPP, NEP, and gross primary production (GPP). Belowground NPP accounted for 49-53% of the total NPP for both ecosystems, followed by aboveground litter (26-27%) and wood (16-17%) production. Increases in water availability increased the potential for C storage, but the mechanism was different in the savanna types with an increase in soil moisture causing higher NPP in the mixed grassland but lower ecosystem respiration (Reco) in the Cerrado forest. Compared to other savanna ecosystems, the mixed grassland had a similar rate of Reco but lower productivity and C use efficiency (CUE = NPP/GPP = 0.28). The Cerrado forest had a high CUE (0.58) and similar C flux rates to other tropical savanna forests and woodlands. While our measurements are spatially and temporally limited, the agreement in C fluxes estimated using inventory and eddy covariance methods suggest that the C cycle estimates for these savanna ecosystems are robust.

Multiphase fluid flow in porous media has been extensively studied for its applications in carbon capture and storage, hydrocarbon recovery, aquifer contamination, soil hydrology and subsurface energy resources. Fluid displacement in porous media can be investigated using highly time-resolved synchrotron X-ray microtomography. One consequence of extremely fast imaging can be compromised image quality, including noise and decreased contrast, which makes the images hard to be segmented. We trained an established convolutional neural network (CNN) architecture (U-Net) with 18,072 images from multiphase flow experiments generated by synchrotron μCT. The trained neural network can segment synchrotron μCT images of core-flooding experiments rapidly and accurately without any pre-processing of the raw image. Segmenting one μCT scan volume of size 1004x496x496 takes 5.6 minutes on an Nvidia Quadro K5200 GPU, while a conventional segmentation pipeline using CPU for the same size data takes 50.2 minutes. On the test dataset, the AUC-ROC score of individual class reached above 0.99 and the mean accuracy of the three segmentation classes reached 99%. The average IoU of the three classes is 0.98. The accuracy of the CNN segmentation is of the same order as conventional methods but it is significantly faster.

The question of what drives tectonic plates has been revitalized by seismic observations that cannot be explained by conventional plate-driving forces. The observations, designed to constrain flow in the asthenosphere, are consistent with the asthenosphere locally flowing faster than the plate above and in a direction offset from plate motion. These inferences are not consistent with plates being driven exclusively by slab-pull and/or ridge-push forces. Mantle convection models were put forth to argue that pressure-driven flow, interacting with a non-Newtonian upper mantle viscosity, could explain these observations. To test the robustness of those results, we expand the models to allow for the development of weak plate margins and associated plate-like behavior. We find that with weak margins, the overall component of slab-driven flow becomes stronger while pressure driven asthenosphere flow remains active. Locally, the asthenosphere can lead plates and there are rotations in the direction of asthenosphere flow with depth. The balance of plate driving forces (i.e., the ratio of slab-pull to asthenosphere flow) is found to depend on plate margin strength. The models also indicate that a non-Newtonian upper mantle allows for a hysteresis effect such that, depending on initial conditions, single-plate and plate-tectonic modes can exist at the same parameter conditions.

Mantle convection is driven by the transport of heat from a planetary interior. This heat may come from the internal energy of the mantle or may come from the core beneath and in general there will be contributions from both. Past investigations of mixed-mode heating have revealed unusual behavior that confounds our intuition based on boundary layer theory applied to end-member cases. In particular, increased internal heating can cause a decrease in convective velocity despite an increase in surface heat flow. We investigate this behavior using numerical experiments and develop a scaling for velocity in the mixed-heating case. We identify a planform transition that impacts both heat flux and convective velocities. More significantly, we demonstrate that increased internal heating leads not only to a decrease in internal velocities but also a decrease in the velocity of the upper thermal boundary layer (a model analog of the Earth’s lithosphere). This behavior is connected to boundary layer interactions and is independent of any partic- ular rheological assumptions. In simulations with a temperature-dependent viscosity and a finite yield stress, increased internal heating does not cause an absolute decrease in surface velocity but does cause a decrease in sur- face velocity relative to the purely bottom or internally heated cases as well as a transition to rigid-lid behavior at high heating rates. The differences between a mixed system and end-member cases have implications for under- standing the connection between plate tectonics and mantle convection and for planetary thermal history modeling.

The projected response of the atmospheric circulation to changes driven by increasing greenhouse gas concentrations is highly uncertain. One of the primary reasons for this is that the state-of-the-art models we employ to investigate these responses struggle to represent basic features of the midlatitude circulation such as storm tracks, jets and blocking. Biases also have detrimental effects on predictive skill for dynamically driven fields at climate prediction time scales of seasons to decades. Despite this, physical understanding of the controls on these features and the drivers of their biases is still limited. Here we investigate a hierarchy of large ensemble climate reanalysis and hindcast simulations performed by the Norwegian Earth System Model (NorESM). Each ensemble is 30 members and was run from 1985-2010. For the reanalysis runs various data-assimilation strategies were employed. These are: SST only, SST plus hydrographic profiles, SST plus hydrographic profiles plus sea-ice concentration. The assimilation was performed monthly after which the model runs freely. These are compared to both free runs and AMIP-style simulations with ERA-Interim serving as ground truth. We evaluate the North Pacific and North Atlantic jets in winter and summer. We also identify where the observations lie within the predictive distribution of the ensemble. Results show that the North Atlantic jet is too zonal, extends too far into Europe and is shifted northwards. Virtually the entire North Atlantic sector lies outside the predictive distribution of the ensemble and performance actually degrades in the simulations with tighter constraints on the assimilation. By contrast the North Pacific jet is rather better represented in all aspects both with respect to pattern as well as magnitude of the biases. This is likely due to the better-represented teleconnections between the tropical and extratropical Pacific. Comparison of these ensembles with AMIP simulations suggests that the errors in the midlatitude circulation reside in the atmospheric component of the model. We also present results from hindcast simulations where NorCPM was initialized at different times of the year and then run forward 12 months. Implications and causes of the varying behavior among the ensembles are discussed as well as prospects for the future.

Machine learning has been widely applied in numerical weather prediction, but the incorporation of new observational sites into models trained on stations with long historical records remains a challenge. Here we propose a post-processing framework consisting of three machine learning methods: station clustering with K-means, temperature prediction based on decision trees, and transfer learning for newly-built stations. We apply this framework to post-processing forecasts of surface air temperature at 301 weather stations in China. The results show significant reductions (as much as 39.4%~20.0%) in the root-mean-square error of operational forecasts at lead times as long as 7 days. Moreover, the use of transfer learning to incorporate new stations improves forecasts at the new site by 36.4% after only one year of data collection. These results demonstrate the potential for clustering and transfer learning to boost existing applications of machine learning techniques in weather forecasting.

This study aims to quantify the impacts of ocean coupling on simulated and projected tropical cyclone (TC) precipitationin the Northern Hemisphere. We used global climate model (GCM) simulations over 1950-2050 from the High Resolution Model Intercomparison Project (HighResMIP) and compared its fully coupled atmosphere-ocean GCMs (AOGCMs) with atmosphere-only GCMs (AGCMs). We find that ocean coupling generally leads to decreased TC precipitation over ocean and land. Large-scale sea surface temperature (SST) biases are critical drivers of the precipitation difference, with secondary contributions from local TC-ocean feedbacks via SST cold wakes. The two driving factors, attributed to ocean coupling in the AOGCMs, influence TC precipitation in association with decreased TC intensity and specific humidity. The AOGCMs and AGCMs consistently project TC precipitation increases in 2015-2050 relative to 1950-2014 over ocean for all basins, and for landfalling TCs in the North Atlantic and western North Pacific.

As the COVID-19 virus spread over the world, governments restricted mobility to slow transmission. Public health measures had different intensities across European countries but all had significant impact on people’s daily lives and economic activities, causing a drop of CO2 emissions of about 10% for the whole year 2020. Here, we analyze changes in natural gas use in the industry and built environment sectors during the first half of year 2020 with daily gas flows data from pipeline and storage facilities in Europe. We find that reductions of industrial gas use reflect decreases in industrial production across most countries. Surprisingly, natural gas use in buildings also decreased despite most people being confined at home and cold spells in March 2020. Those reductions that we attribute to the impacts of COVID-19 remain of comparable magnitude to previous variations induced by cold or warm climate anomalies in the cold season. We conclude that climate variations played a larger role than COVID-19 induced stay-home orders in natural gas consumption across Europe.

The Middle–Upper Jurassic sedimentary strata in the southwestern Colorado Plateau recorded pervasive eolian to fluvio-lacustrine deposition in the Paradox Basin. While paleocurrents preserved in the Entrada Sandstone, an eolian deposition in the Middle Jurassic, has been well constrained and show a northwesterly to northeasterly migration of ergs from the south onto the Colorado Plateau, there is yet no clear resolution of the paleocurrents preserved in the Wanakah Formation and Tidwell Member of the Morrison Formation, both of which are important sedimentary sequences in the paleogeographic framework of the Colorado Plateau. New U–Pb detrital zircon geochronology of sandstones from these sequences suggests that an abrupt change in provenance occurred in the early Late Jurassic, with sediments largely sourced from eroding highlands in central Colorado. We measured the anisotropy of magnetic susceptibility (AMS) of sediments in oriented sandstone samples from these three successive sequences; first, to determine the paleocurrents from the orientations of the AMS fabrics in order to delineate the source area and sediments dispersal pattern and second, to determine the depositional mechanisms of the sediments. Preliminary AMS data from two study sites show consistency and clustering of the AMS axes in all the sedimentary sequences. The orientations of the Kmin – Kint planes in the Entrada Sandstone sample point to a NNE–NNW paleocurrent directions, which is in agreement with earlier studies. The orientations of the Kmin – Kint planes in the Wanakah Formation and Tidwell Member samples show W–SW trending paleocurrent directions, corroborating our hypothesis of a shift in provenance to the eroding Ancestral Front Range Mountain, located northeast of the Paradox Basin, during the Late Jurassic. Isothermal remanence magnetization (IRM) of the samples indicate that the primary AMS carriers are detrital, syndepositional ferromagnetic minerals. Thus, we contend that AMS can be successfully deployed in constraining paleocurrents in lacustrine sedimentary strata, which lacks traditional sedimentary structures for paleocurrent analyses.

• Nitrogen is the main component of the atmosphere, a key nutrient for organisms, and exerts con- trol over climate via direct warming, as N2O, and indirect effects, including pressure-broadening • Previous models linked N to C, and typically only considered biologic or geologic fluxes in detail, focusing on sedimentary rocks. These studies suggest atmospheric mass steady over Earth history, which does not match new geochemical and physical paleobarometers • New approach is to more completely include biologic and geologic fluxes, and link N behavior to PO4 and O2 abundance through time • This approach is consistent with large-scale changes in atmospheric mass through time, up to 3 present atmospheric masses of nitrogen (1 PAN = 4 × 10^18 kg N) supporting geochemical proxies that indicate atmospheric drawdown through time