My laboratory is developing an accelerometer. However, if you do not install the dedicated software, you can not browse the data. In addition, since it is necessary to go to the site on a semi-annual basis and collect data due to capacity problems, the current operation is burdened. In order to solve these problems, we devised WebGL that enables high-speed drawing when processing a large amount of data such as Big Data, and a Web application that uses server that can transmit, save, and download acquired data. In this application, an accelerometer and a raspberry pie are connected, and the raspberry pie receives data obtained from the accelerometer and sends the data to a server installed in a laboratory by SCP file transfer at regular intervals. These data specify the location and date from the client side through the Internet browser, download the data using the download function of the browser, read this data on the application and draw the waveform. The data obtained from the accelerometer in the development to date is converted into a CSV file and transferred to the server. These data can be downloaded and displayed on the web application. For the google map displayed on the right side of the screen, it is to make the application more useful by registering the location where the accelerometer was set in the future.

It was investigated that the reproducibility of surface wind and tracer transport simulations over complex terrain in wintertime using high-resolution (5-km, 3-km, and 1-km grid) weather and transport models, in which radioactive cesium (Cs-137) emitted from the Fukushima nuclear power plant was used as a tracer. Fukushima has complex terrain, such as mountains and valleys. The model results were validated by observations collected from the national networks of the automated meteorological data acquisition system and the hourly air pollution sampling system. The reproducibility depended on the model resolution, topographic complexity, and synoptic weather conditions. Higher model resolution led to higher reproducibility of surface winds, especially in mountainous areas when the Siberian winter monsoon was disturbed. In contrast, the model improvement was negligible or nonexistent over plain/coastal areas when the synoptic field was steady. The statistical scores of the tracer transport simulations often deteriorated due to small errors in the plume locations. However, the higher-resolution models advantageously performed better transport simulations in the mountainous areas because of the lower numerical diffusion and higher reproducibility of the mass flux. The reproducibility of the tracer distribution in the valley of the Fukushima mountainous region was dramatically improved with increasing model resolution. In conclusion, a higher-resolution model is definitely recommended for tracer transport simulations over mountainous terrain at least in the range of mesoscale model resolutions (commonly 1~10 km grids).

We consider the statistical properties of solutions of the stochastic fractional relaxation equation that has been proposed as a model for the earth’s energy balance. In thisequation, the (scaling) fractional derivative term modelsenergy storage processes that occur over a wide range of space and time scales. Up until now, stochastic fractionalrelaxation processes have only been considered withRiemann-Liouville fractional derivatives in the context of random walk processes where it yields highlynonstationary behaviour. For our purposes we require the stationary processes that are the solutions of the Weyl fractional relaxation equations whose domain is −∞ to t rather than 0 to t. We develop a framework for handling fractional equationsdriven by white noise forcings. To avoid divergences, wefollow the approach used in fractional Brownian motion(fBm). The resulting fractional relaxation motions (fRm) and fractional relaxation noises (fRn) generalize the more familiar fBm and fGn (fractional Gaussian noise). Weanalytically determine both the small and large scale limitsand show extensive analytic and numerical results on the autocorrelation functions, Haar fluctuations and spectra. We display sample realizations. Finally, we discuss the prediction of fRn, fRm which – due to long memories - is a past value problem, not an initial value problem. We develop an analytic formula for the fRnforecast skill and compare it to fGn. Although the large scale limit is an (unpredictable) white noise that is attainedin a slow power law manner, when the temporal resolutionof the series is small compared to the relaxation time, fRncan mimick a long memory process with a wide range of exponents ranging from fGn to fBm and beyond. Wediscuss the implications for monthly, seasonal, annualforecasts of the earth’s temperature.

Low-cost air quality monitors (LCAQMs) are promising supplements to regulatory monitors for PM2.5 exposure assessment. However, the application of LCAQM in spatially extensive exposure modeling is hindered by the difficulty in performing calibration at large spatial scales and the adverse influence of LCAQM residual uncertainty after calibration. We aimed to develop an efficient spatially scalable calibration method for LCAQM and design a residual uncertainty-derived down-weighting strategy to optimize the use of LCAQM data with regulatory monitoring data in PM2.5 modeling. In California, for each monitor from PurpleAir, a global LCAQM network, we identified a station within a 500-m radius from the Air Quality System (AQS), a U.S. regulatory monitoring network. Regional calibration of PurpleAir to AQS was performed at the hourly level with Geographically Weighted Regression (GWR). The calibrated PurpleAir measurements were down-weighted according to their residual uncertainty and then incorporated into a Random Forest (RF) prediction model as a dependent variable to generate 1-km daily PM2.5 exposure estimates. The state-level PurpleAir calibration reduced the systematic bias to ~0 ug/m3 and decreased the random error by 38%. The considerably large samples also enabled quantitative analyses regarding potential factors related to the PurpleAir bias. The RF-based model with both AQS and down-weighted PurpleAir data outperformed the RF model based solely on AQS with an improved CV R2 of 0.86, an improved spatial CV R2 of 0.81, and a lower prediction error of 5.40 ug/m3. The down-weighting allowed the prediction model to show more spatial details of PM2.5 and to better detect pollution hot-spots. Our spatially scalable calibration and down-weighting strategies, for the first time, allowed an effective application of a state-level LCAQM network in high-resolution PM2.5 exposure modeling. The proposed framework can be generalized to regions worldwide for advancing the evaluation of heavy PM2.5 episodes and health-related applications.

In this presentation, we will describe the [Pangeo Project](http://pangeo.io), a coordinated community effort with support from NASA, NSF, AWS, Microsoft Azure and Google Cloud, to develop interactive and reproducible open source workflows for discovery, visualization, and quantitative analysis of large datasets used for research in the Earth Sciences. The Pangeo computational platform is based on JupyterHub and deployed wherever the data is stored. Python libraries such as Xarray, Rasterio, and Dask enable distributed parallel computations on HPC and Kubernetes clusters. We will discuss the design concepts central to the Pangeo platform and highlight specific applications using NASA satellite data archives on AWS. We will discuss recent progress in the integration of data discovery tools (e.g. STAC, CMR, Intake) with cloud-native storage formats for multidimensional data types (Cloud-Optimized Geotiff, Zarr, etc.) and highlight how they can be used to construct elegant, robust and reproducible scientific workflows. Finally, we will discuss performance, security, transferability across public cloud platforms, cost to operate, and approaches to encourage a cultural shift in scientific computation through educational events.

Solar geoengineering has been suggested as a potential approach to counteract the anthropogenic global warming. Major volcanic eruptions have been used as natural analogues to large-scale deployments of stratospheric aerosol geoengineering, yet difference in climate responses to these forcings remains unclear. Among many factors characterizing the difference between the two, durations of the additional aerosol layer in the stratosphere differ substantially between volcanic eruptions and the SAI geoengineering. Sulfate aerosols from volcanic eruptions typically stay in the stratosphere for one to two years. Stratospheric aerosol geoengineering, however, if used to counteract anthropogenic warming, would need to be deployed quasi-continuously and thus the additional aerosols would stay in the stratosphere persistently. Using the NCAR CESM model, we compare the climate response to two highly idealized stratospheric aerosol forcings that have different durations: a short-term pulse representative of volcanic eruptions and a long-term sustained forcing representative of geoengineering. For the same amount of global mean cooling, the pulse case causes much larger reductions in surface temperature over land relative to the sustained case. This greater cooling over land leads to a larger decrease in the vertical motion of air over land in lower atmosphere, and reduces water vapor transport from the ocean to land. For similar amounts of global cooling, the decrease in land runoff caused by a short-term pulse aerosol forcing is about twice as large as that caused by a sustained aerosol forcing. Our results clearly demonstrate difference in the climate response to volcanic-like and geoengineering-like stratospheric aerosol forcings, and suggest that caution should be exercised when extrapolating results from volcanic eruptions to the SAI geoengineering deployments. However, observations and simulations of climate impacts from volcanic eruptions test many of the same physical mechanisms that would come into play in a stratospheric aerosol geoengineering scenario, and thus major volcanic eruptions remain as valuable analogues for solar geoengineering deployment.

We present a reinterpretation of a geological section in the Tampico-Misantla oil province made with the purpose of selecting and evaluating possible sites to implement a Geological CO2 Storage (GCS) in the Jurassic sedimentary units. Specific parameters of the reservoir such as porosity, permeability, fluid content, temperature, and overburden pressure were estimated from a database of drilled oil wells, core descriptions, laboratory tests, and analogue outcrop descriptions. Previous data indicated porosity values ranging from 6% to 12%, and relatively low permeability values <0.001 mD for calcareous sand and clay-silty bearing layers. Reinterpretation of a geological section involving the main lithostratigraphic units, from Cenozoic sediments to Jurassic metamorphic rocks, was made based on geological maps, geological contacts, and seismic data. Petrophysical properties were obtained from well logs available (Neutron, DTCO, Gamma Ray, Resistivity) and compared with laboratory measurements in cores from wells and outcrops. A model of regional petrophysical facies for the reservoir and seal units was developed by using selected physical properties in relation with the regional geological context. Five petrophysical facies distributed across the study area were identified in the reservoir including calcareous sands, quartz bearing sandstone and quartz bearing conglomerates for the reservoir, and bituminous shales and limestone for the shale units covering the reservoir. Permeability and porosity values at the reservoir scale were estimated from well logs using methods available in the literature and then compared with the laboratory tests. Two porosity estimations were computed from well logs: Neutron porosity (NPHI) and Sonic Porosity (PHITS) with results ranging from 0.1 % to 16%. Estimated permeability yielded a range of 0.001 mD to 15 mD. The results suggest that the Jurassic units are a suitable reservoir since geological traps and specific depositional facies distributed in the basin have the required porosity and permeability values suggested for efficient CO2 storage.

A sediment core taken proximal to a large sunken ship in the north channel of the Yangtze delta suggests a dramatic change in sedimentation that is coincident with the sinking of the ship. We conducted AMS 14C and OSL dating and analysed the lithology, grain size, magnetic susceptibility and organic elemental geochemistry and combined these data with historical marine charts and historical data. A notable change in sedimentary environments implies a dramatic change to the geomorphological evolution of the environment at the location of the shipwreck. The sediments below the shipwreck layers suggest that the shipwreck occurred in a sheltered tidal channel developed at the north margin of the Tongsha Shoal of the Yangtze River mouth. The shipwreck layer containing the wood pieces of the sunken ship is composed of structureless silts and underlain by homogeneous mud separated by an erosional contact. The ship/storm layer is overlain by sandy facies reflecting a change to more open marine channel conditions. The sedimentary data implies that a large historical typhoon possibly on July 31, 1879 sunk several ships and caused significant geomorphological change to the Yangtze delta.

Solar flare, as a typical large temporal-spatial turbulent magnetic reconnection (LTSTMR, the ratio of observed current sheets thickness to electron characteristic length, electron Larmor radius for low-β and electron inertial length for high-β, is on the order of 10E10–10E11; the ratio of observed evolution time to electron gyroperiod is on the order of 10E7–10E9) explosion in the solar atmosphere activities, involving sudden bursts of particle acceleration that from sudden release of magnetic energy in a few minutes to a few tens of minutes. The X rays and gamma rays are believed to result from the interactions of the high energy electrons energized and nuclear interaction of the high energy protons and other heavier ions, respectively. While many particle acceleration models consider turbulence acceleration as an effective way of generating energetic electrons, the precise turbulence roles during acceleration and heating of electrons still remain unclear. Here we show from 3D relativistic hybrid particle-in-cell and lattice Boltzmann method (RHPIC-LBM) simulation that interaction of helical magnetic structure that leads to efficient energization of electrons. By following the trajectories of the most energetic electrons, we found the strong Langmuir turbulence acceleration (LTA) through wave-wave, wave-particle interaction in the diffusion region of the flare, which can accelerate electrons effectively. and discuss the turbulence acceleration by strong Langmuir wave. The simulation of LTA is not only similar to the shock wave acceleration, but more efficient than that of the shock wave acceleration. The energy spectrum of hot electrons undergoing LTA can be studied the X ray and gamma ray production in flare. We anticipate our results to be a key point for understanding the relationship between particle acceleration mechanism and explosive energetic electrons observed in the solar flares during MHD Alfven turbulence translate into Kinetic Alfven turbulence progress.

Organisms leave traces of DNA as they move through their environments. The extraction of these DNA traces is known as environmental DNA (eDNA). eDNA provides scientists and researchers a non-invasive, rapid, cost-effective and sensitive way to detect and quantify species. Traditional eDNA sampling consists of manually filtering water, which is labor and cost-intensive for remote locations. Furthermore, commercialized solutions are expensive and require a field operator. This eDNA sampler project aims to provide an affordable, open-sourced, remotely deployable, fully automated, and customizable alternative. The PolyWAG (Water Acquired Genomics) system can run up to 24 inline filter units with support for different conditions including pressure, time and volume limit. The pumps deliver maximum 400mL/min with solenoid valves separating each inline filter to minimize cross-contamination. At the end of each sample, the desired stabilizing solution can be injected to fully submerge the filter for preservation. An optional river depth sensor can provide a proxy for flow to correct eDNA concentrations to allow for improved quantification of organisms. Data acquired during operation including water depth, pressure, temperature, and flow rate will be stored on microSD card in CSV format, which allows easier data export and analysis. A web application provides an intuitive UI for in-field programming, real-time sensor updates, scheduling tasks, and manual operations. We present data from multiple tests showing the length of the preservation period and the contamination level between samples. The PolyWAG system is estimated to be $3000 each, with add-on river depth sensor and 10ah 12V battery.

Variation of the surface coastal current in the marginal sea off the west coast of Sumatra during the Pre-YMC and YMC periods was investigated by the R/V “Mirai” cruises (Pre-YMC [Years of the Maritime Continent]: MR15-04 and YMC: MR17-08). One of the major differences between the cruises of MR15-04 and MR17-08 was the direction of the surface coastal current. According to the LADCP observation, the southeastward current along the coast was continuously dominant under the forcing of a weak easterly winds in the MR15-04, whereas in the MR17-08, the current direction was rotated counterclockwise around 10 days under the strong westerly wind forcing after the passage of the MJO, suggesting the passage of meso-vortices. The difference was confirmed by the oceanic reanalysis of the ECCO2, and it was confirmed that the meso-vortex was slowly moved along the coast (about 300 km / 10 days). It was suggested that the presence or absence of the meso-vortex formation caused a large difference in not only the horizontal advection but also the up or down welling in the mixed layer. The meso-vortex was also accompanied by a clear maximum of the sea surface height, and a large vertical motion in the mixed layer is estimated in ECCO2. The coastal meso-vortex was gradually formed and developed under the continuous westerly wind forcing more than 10 days after the MJO passage.

Fast solar wind streams are known to be dominated by Alfvenic turbulence, i.e. large amplitude magnetic field and quasi-incompressible velocity fluctuations with a correlation corresponding to waves propagating away from the Sun. At the same time the Ulysses spacecraft showed That microstreams, persistent long period (1/2-2 days) fluctuations in the radial velocity field, are ubiquitous in the fast wind. This contribution explores the possible causal relation between microstreams and Alfvenic turbulence. We carry out a parametric study of the stability of the microstream jets to Kelvin-Helmholtz (KH) instabilities: starting from the profiles of density, radial speed and magnetic field observed in the solar wind, we investigate both at what distance from the Sun KH instabilities may be triggered and the ensuing nonlinear dynamics.

To close the water use budget in irrigated agricultural fields in flood plains with substantial riparian corridors, it is necessary to understand groundwater usage by dominant phreatophyte vegetation, particularly when the primary source of the water for irrigation comes from groundwater abstraction. We report here results of measurements of sap flow in phreatophyte vegetation in a riparian corridor, which is part of a watershed located along the coast in Santa Cruz County, California. The riparian corridor is within a study area of 75 to 140 meters wide in the lower portion of Scotts Creek watershed, which is bounded to the west by the Pacific Ocean. Canopy cover in the study area often approaches 100 percent, with dominant trees being red alder (Alnus rubra), arroyo willow (Salix lasiolepis), and pacific willow (Salix lasiandra var. lasiandra). Other trees include boxelder (Acer negundo), big leaf maple (Acer macrophyllum), and California bay laurel (Umbellularia californica). Common understory vegetation includes California blackberry (Rubus ursinus), stinging nettle (Urtica dioica subsp. gracilis), poison hemlock (Conium maculatum), Cape ivy (Delairea odorata), and Italian thistle (Carduus pycnocephalus). For the study reported here, only the two most dominant phreatophyte species, namely red alders and arroyo willows, were instrumented with sap flow sensors. In addition to diurnal fluctuations, sap flow data collected hitherto also shows expected seasonal variation with summer maxima and winter minima, with transition fall and spring periods. Sap flow measurements from the study area are projected across the entire riparian forest using sampled tree sapwood area and used to estimate forest evapotranspiration (ET). The ET is then used in a groundwater flow model to more accurately predict observed groundwater fluctuations and usage by riparian vegetation.

Constraining the properties of continental margin where dynamic interplay between the lithosphere and convective upper mantle actively occurs can provide implications to understand the evolution and modification process of cratonic lithosphere. Cratonic lithosphere in the eastern Eurasian plate has experienced multiple episodes of tectonic events at the continental margin during the Phanerozoic, which are characterized by collision and subduction of continental and oceanic plates with extensive magmatic intrusion, extension, and rifting. To better understand the complex tectonic processes and their influences on the continental lithosphere, we imaged upper mantle structure beneath the Archean-Proterozoic basement in the Korean Peninsula (KP) by seismic tomography. Our dataset is entirely based on relative arrival time of teleseismic body wave recorded by dense seismic array across the southern KP in order to extract velocity variations from the local area and reduce the effects from deeper upper mantle structures. The images show a sharp and large lateral velocity variation within a short distance (< 200 km) in KP, which indicates highly variable lithospheric structure. An anomalously thick high-velocity structure beneath the southwestern part suggests a fragment of a long-lasting cratonic lithosphere (~150 km) at the continental margin. The absence of deep lithosphere and mostly occupied by hot, buoyant, low-velocity upper mantle beneath the Gyeonggi massif, Gyeongsang continental arc-backarc system, and eastern continental margin of KP shows highly modified regions. In addition, there are clear spatial correlations of low-velocity upper mantle with partial melting zones and the localities of Cenozoic basalts, high surface heat flux, and high topography with recent uplift along the eastern mountain ranges. A strong variation in the upper mantle velocity structure without clear distinctions in surface geology across different massifs suggests heterogeneous modification of continental lithosphere by recent and transient processes, such as the opening of the East Sea (Sea of Japan) or a subduction of Philippine Sea Plate. Dynamic interaction of the prominent lithospheric structure and convective upper mantle has controlled reactivation and destabilization at the cratonic margin of KP.

In the context of climate change, a clear understanding of the processes and factors driving global warming is a major concern. During past geological times, Earth suffered several intervals of global warmth but the priming factors remain equivocal. Yet a careful appraisal of all processes being implied during those past events is essential to evaluate how they can inform future climates, in order to provide decision makers a clear understanding of the processes at play in a warmer world. In this context, the global warmth of the Cretaceous era, specifically during the Cenomanian-Turonian, is of particular interest. Here we use the IPSL-CM5A2 Earth System model to unravel the forcing parameters of the Cenomanian-Turonian greenhouse climate. We perform six simulations, from the preindustrial to the Cretaceous by implementing one additional boundary condition change at a time, i.e. (1) polar ice cap retreat, (2) pCO2 increase to 1120 ppm, (3) vegetation and soil parameters, (4) solar constant reduction (~ -1%) and (5) paleogeography (90Ma). Between the first preindustrial simulation and the last Cretaceous simulation, a global warming of more than 11°C is simulated. Most of this warming is driven by the increase in pCO2 to 1120 ppm. Paleogeographic changes represent the second major contributor to the warming while the solar constant reduction counteracts most of this geographically-driven warming. Finally, changes in vegetation and soil parameters as well as the retreat of polar ice caps have a minor impact at the global scale. A full assessment of the processes driving warming or cooling under each boundary condition change will be presented. Ultimately, our work supports the overarching influence of atmospheric carbon dioxide in driving the Earth’s global climate and global warming.

The properties of the inner core boundary (ICB) carry important information about the growth of the solid inner core and solidification of the liquid outer core. In this presentation, we study the ICB by analyzing the spectrum difference of PKiKP (a compressional wave reflected from the ICB) and PcP (a compressional wave reflected from the core-mantle boundary) phase pair. Our dataset includes the seismic data recorded by the Hi-net in Japan for two earthquakes occurring in Myanmar on 4th September 2009 and 4th February 2011, with their PKiKP waves sampling the ICB beneath mid-eastern China. Little waveform and spectrum differences are observed between PKiKP and PcP waves in the seismic data. By comparing spectrum shapes of the seismic data and the synthetics of models with various topographic fluctuations and transitional thicknesses of ICB, we conclude that the studied ICB region is flat and sharp. Within the resolvability of the seismic data, the ICB topographic fluctuation of the region is less than 200 m in height and the transition of the boundary is thinner than 100 m in thickness.

The timescale over which magma rises to the surface during a volcanic eruption is a critical parameter that controls eruption style but is challenging to determine. Melt embayments, which are pockets of magma trapped within crystals but are still open to the host magma, tend to develop volatile (e.g., H2O, CO2) concentration gradients during ascent through the process of diffusion. These gradients are increasingly used as output constraints for diffusion models to calculate total ascent time. However, there are two main assumptions associated with the method that have yet to be properly evaluated. First, the diffusion models tend to be carried out in 1D, which may be less accurate than 3D models if the embayment narrows near the opening. This geometry has more complicated volatile flux pathways that 1D models cannot account for. Second, the models typically assume that volatile contents follow equilibrium saturation trends defined by depth below the surface, which may not be accurate for high silica magmas. For these compositions, a significant supersaturation of volatiles may be needed for volatile exsolution to start, depending on the availability of suitable crystal phases for bubble nucleation. This nucleation lag delays the start of diffusion as well and could influence modeled timescales. We developed 3D diffusion models to evaluate the degree of inaccuracy in calculated timescales introduced by these assumptions for high silica magmas. We built synthetic embayments with variable 3D geometries and imposed both equilibrium and disequilibrium ascent conditions in our models. Our results indicate that the inaccuracy introduced by embayment geometry in 1D diffusion models increases as the diameter of the embayment opening decreases. This degree of inaccuracy is also tied to diffusion duration – as it increases, so does the relative error in timescales retrieved by 1D models fitting 3D-generated profiles. Once the diffusion front extends beyond the narrow, “necked” region of the embayment, relative error increases with increasing diffusion time. However, volatile disequilibrium behavior does not appear to significantly impact modeled timescales. These results indicate that embayment geometry is a critical variable that must be accounted for whereas delayed nucleation is of secondary influence.

The amount of aerosol is a key parameter modulating the cloud microphysics and its subsequent long-term impact on climate through Twomey (cloud albedo) effect and Albrecht (lifetime) effect. As the relative dispersion (ε; standard deviation divided by mean) of the cloud droplet size distribution is an important factor in controlling the droplet collision rate and precipitation, along with its relevance in cloud modeling, it would be valuable to study the influence of aerosol concentration (Na) on ε. The impact on ε from Na can be observed from two aspects: intra-cloud and inter-cloud correlation. The intra-cloud correlation may reveal the cloud microphysical processes that are affected by the local variability of aerosol concentration, whereas inter-cloud correlation sheds light onto how different background aerosol concentration affects the macrophysics of clouds under different meteorological settings. Past studies that investigated from these two aspects have shown inconsistent correlation between Na and ε. Hence, the objective of this study is to identify whether and how the Na affects ε, observed from these two aspects. In this study, to ensure statistical significance, we choose five in-situ campaign data sets that were collected in vastly different places around the world: VOCALS (Chilean west coast), MASE (California), POST (California, sampling emphasized near the cloud top), GoMACCS (Texas, emphasized on highly polluted areas), and ORACLES (Central African west coast). Surprisingly, we observe that both intra-cloud and inter-cloud Na-ε correlations are largely nonexistent, whether within individual campaigns or across campaigns. We also found that the intra-cloud correlation is instead pronounced only between cloud droplet concentration (Nd) and relative dispersion, suggesting that the cloud microphysics related to Nd and ε is not strongly influenced by Na but by other cloud processes. This strong (negative) correlation could also help models better predicting relative dispersion from droplet concentration to construct a more close-to-reality droplet size distribution.