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At least 19 records

SPRUCE: Carbon Dioxide and Methane Soil Flux Measurements at High Temporal Resolution, Beginning in 2022

This data set contains high temporal resolution measurements of greenhouse gas flux (CO2 and CH4) from the SPRUCE (Spruce and Peatland Responses Under Changing Environments) experiment (Hanson et al. 2017) over the growing seasons in 2022 (30-minute resolution) and 2023 (15-minute resolution). Additional data will be appended to this dataset periodically until the close out of the SPRUCE experiment in 2025. This dataset contains two data files in comma-separate (*.csv) format. ABB GLA131-GGA CO2/CH4 gas analyzers, each paired with an Eosense eosMX multiplexer and 2 eosAC-LT automated flux chambers, were deployed from during the 2022 and 2023 growing seasons (2022-06-06 – 2023-10-26). Each SPRUCE experimental enclosure included two Eosense 50 cm diameter flux chambers with 40 cm tall stainless steel collars embedded approximately 15 cm into the peat soil, to measure soil gas flux of peatland ecosystem moss-shrub communities. . Measurements were taken for three minutes, alternating between the flux chambers, with each Eosense flux chamber sampling gas fluxes four times per hour in 2023 and twice per hour for 2022. In addition, time-series environmental data measured at the flux chamber are included: Photosynthetically active radiation (PAR), soil temperature, soil volumetric water content (at 10 cm depth), air temperature, soil temperature (0-200 cm depth), and volumetric water at 20 cm depth.

Spruce and Peatland Responses Under Changing Envir↗

Estimating soybean yields from high-temporal-resolution multi-source data using deep learning

Accurate and timely crop yield prediction is crucial for ensuring food security and maintaining stable agricultural markets. In recent years, there has been a surge in interest in leveraging high-temporal-resolution, multi-source data for effective crop growth monitoring and yield estimation. A notable challenge arises from the difficulty in capturing the intricate interactions between variables across different time steps within these high-temporal-resolution time series datasets. This complexity hinders the reliable extraction of yield information from voluminous and often noisy datasets, especially during periods of extreme weather events. Here, in this study, we propose an Attention and Graph Isomorphism Network-enhanced Bi-directional Long Short-Term Memory network (AGB-LSTM) for estimating county-level soybean yield in the United States. This model integrates a diverse set of remote sensing data, including Near-Infrared Reflectance of Vegetation (NIRv), Sun-Induced chlorophyll Fluorescence (SIF), and Gross Primary Productivity (GPP), along with environmental covariates. The AGB-LSTM effectively leverages information related to crop yield from high-temporal-resolution time series data (5-days), achieving an accuracy of R²= 0.67 and rRMSE = 14.46%. This approach significantly outperforms traditional machine learning methods such as Random Forest (RF) (R²= 0.52, rRMSE = 17.36%) and Bi-LSTM (R²= 0.58, rRMSE = 16.17%). Sensitivity experiments with different time steps and ranges demonstrated that our model could accurately and stably predict yields 1 to 2 months before harvest. Moreover, data with a finer temporal resolution consistently improved prediction performance, resulting in an approximately 20% increase in and an approximately 20% decrease in rRMSE compared to using monthly composites. We also evaluated the robustness of the model under extreme climate events and observed strong performance (R²= 0.50, rRMSE = 21.32%). Finally, yield mapping for major soybean-producing regions in North America in 2023 revealed spatial patterns that closely matched USDA yield reports. Our findings suggest that the AGB-LSTM model is a promising and effective method for estimating yield and has notable potential for global crop yield forecasting.

Deep learning↗

Technical Note: High temporal resolution characterization of gating response time

Purpose: Low temporal latency between a gating ON/OFF signal and the LINAC beam ON/OFF during respiratory gating is critical for patient safety. Here the authors describe a novel method to precisely measure gating lag times at high temporal resolutions. Methods: A respiratory gating simulator with an oscillating platform was modified to include a linear potentiometer for position measurement. A photon diode was placed at linear accelerator isocenter for beam output measurement. The output signals of the potentiometer and diode were recorded simultaneously at 2500 Hz with an analog to digital converter for four different commercial respiratory gating systems. The ON and OFF of the beam signal were located and compared to the expected gating window for both phase and position based gating and the temporal lag times extracted. Results: For phase based gating, a real-time position management (RPM) infrared marker tracking system with a single camera and a RPM system with a stereoscopic camera were measured to have mean gate ON/OFF lag times of 98/90 and 86/44 ms, respectively. For position based gating, an AlignRT 3D surface system and a Calypso magnetic fiducial tracking system were measured to have mean gate ON/OFF lag times of 356/529 and 209/60 ms, respectively. Conclusions: Temporal resolution of the method was high enough to allow characterization of individual gate cycles and was primary limited by the sampling speed of the data recording device. Significant variation of mean gate ON/OFF lag time was found between different gating systems. For certain gating devices, individual gating cycle lag times can vary significantly.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Reconstruction of high temporal resolution Thomson scattering data during a modulated electron cyclotron resonance heating using conditional averaging

This paper provides a software application of the sampling scope concept for fusion research. The time evolution of Thomson scattering data is reconstructed with a high temporal resolution during a modulated electron cyclotron resonance heating (MECH) phase. The amplitude profile and the delay time profile of the heat pulse propagation are obtained from the reconstructed signal for discharges having on-axis and off-axis MECH depositions. The results are found to be consistent with the MECH deposition.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

High Temporal Resolution Tropospheric Wind Profile Observations at NASA Kennedy Space Center During Hurricane Irma

The NASA Kennedy Space Center (KSC) operates a 48-MHz Tropospheric/Stratospheric Doppler Radar Wind Profiler (TDRWP) on a continual basis generating wind profiles between 2-19 km in the support of space launch vehicle operations. A benefit of the continual operability of the system is the ability to provide unique observations of severe weather events such as hurricanes. Over the past two Atlantic Hurricane seasons the TDRWP has made high temporal resolution wind profile observations of Hurricane Irma in 2017 and Hurricane Matthew in 2016. Hurricane Irma was responsible for power outages to approximately 2/3 of Florida's population during its movement over the state(Stein,2017). An overview of the TDRWP system configuration, brief summary of Hurricanes Irma and Matthew storm track in proximity to KSC, characteristics of the tropospheric wind observations from the TDRWP during both events, and discussion of the dissemination of TDRWP data during the event will be presented.

Decker, Ryan K.↗

Capillary absorption spectroscopy for high temporal resolution measurements of stable carbon isotopes in soil and plant-based systems

Capillary Absorption Spectroscopy (CAS) is a relatively new analytical technique for performing stable isotope analysis. Here, we demonstrate the utility of CAS by recording and quantifying variation in 13C in controlled and biologically relevant applications. We calibrated CAS system response to increased 13CO2, with an observed ~4‰ increase in measured Δ13C for each 0.03 ppm shift in 13CO2 concentration. We leveraged this calibration to quantify rates of biogeochemical processes using a 13C tracer. For example, we monitored microbial respiration of 13C-glucose within an agricultural soil at 10 s quantification intervals and results demonstrated 8.6% ± 0.4 of added glucose was converted to 13CO2 within 1.5 h of incubation. We expanded the demonstration by adapting a rhizobox to permit continuous monitoring of 13CO2 in a soil (as distinct from plant) headspace to track the timing and quantify respiration rates of fresh plant photosynthate and observed a 3.5 h delay between plant exposure to a13CO2 tracer and the first signs of respiration by soil biota. These experiments highlight CAS is effective in producing high temporal resolution quantification of 13CO2 and demonstrate potential applications.

13CO2↗

Rhythmic Mechanisms Governing CAM Photosynthesis in Kalanchoe fedtschenkoi : High-Resolution Temporal Transcriptomics

Crassulacean acid metabolism (CAM) is a specialized photosynthetic pathway that enhances water-use efficiency by temporally separating nocturnal CO 2 uptake from daytime decarboxylation and carbon fixation. To uncover the regulatory mechanisms coordinating these temporal dynamics, we generated high-resolution, 48 h time-course transcriptomes for the CAM model Kalanchoe fedtschenkoi under both 12 h/12 h light/dark (LD) cycles and continuous light (LL). A rhythmicity analysis revealed that diel light cues are the dominant driver of transcript oscillations: 16,810 genes (54.3% of annotated genes) exhibited rhythmic expression only under LD, whereas just 399 genes (1.3%) remained rhythmic under LL. A smaller set of 3009 genes (9.7%) oscillated in both conditions, indicating that the intrinsic circadian clock sustains rhythmicity for a limited subset of the transcriptome. A gene co-expression network analysis revealed extensive integration between circadian clock components, core CAM pathway enzymes, and stomatal regulators, defining regulatory modules that coordinate metabolic and physiological timing. Notably, key hub genes associated with post-translational and post-transcriptional regulation, including the E3 ubiquitin ligase HUB2 and several pentatricopeptide repeat (PPR) proteins, act as central nodes in CAM-associated networks. This discovery implicates epigenetic and organellar regulation as previously unrecognized critical tiers of control in CAM. Together, our results support a regulatory model in which CAM rhythmicity is governed by both external light/dark cues and the endogenous circadian clock through multi-level control spanning transcriptional and protein-level regulation. To support community exploration, we also provide an interactive eFP (electronic Fluorescent Pictograph) browser for visualizing time-resolved gene expression profiles.

09 BIOMASS FUELS↗

Analysing the Advantages of High Temporal Resolution Geostationary MSG SEVIRI Data Compared to Polar Operational Environmental Satellite Data for Land Surface Monitoring in Africa

Since 1972, satellite remote sensing of the environment has been dominated by polar-orbiting sensors providing useful data for monitoring the earth s natural resources. However their observation and monitoring capacity are inhibited by daily to monthly looks for any given ground surface which often is obscured by frequent and persistent cloud cover creating large gaps in time series measurements. The launch of the Meteosat Second Generation (MSG) satellite into geostationary orbit has opened new opportunities for land surface monitoring. The Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on-board MSG with an imaging capability every 15 minutes which is substantially greater than any temporal resolution that can be obtained from existing polar operational environmental satellites (POES) systems currently in use for environmental monitoring. Different areas of the African continent were affected by droughts and floods in 2008 caused by periods of abnormally low and high rainfall, respectively. Based on the effectiveness of monitoring these events from Earth Observation (EO) data the current analyses show that the new generation of geostationary remote sensing data can provide higher temporal resolution cloud-free (less than 5 days) measurements of the environment as compared to existing POES systems. SEVIRI MSG 5-day continental scale composites will enable rapid assessment of environmental conditions and improved early warning of disasters for the African continent such as flooding or droughts. The high temporal resolution geostationary data will complement existing higher spatial resolution polar-orbiting satellite data for various dynamic environmental and natural resource applications of terrestrial ecosystems.

Fensholt, R.↗

Understanding Growth Dynamics and Yield Prediction of Sorghum Using High Temporal Resolution UAV Imagery Time Series and Machine Learning

Unmanned aerial vehicles (UAV) carrying multispectral cameras are increasingly being used for high-throughput phenotyping (HTP) of above-ground traits of crops to study genetic diversity, resource use efficiency and responses to abiotic or biotic stresses. There is significant unexplored potential for repeated data collection through a field season to reveal information on the rates of growth and provide predictions of the final yield. Generating such information early in the season would create opportunities for more efficient in-depth phenotyping and germplasm selection. This study tested the use of high-resolution time-series imagery (5 or 10 sampling dates) to understand the relationships between growth dynamics, temporal resolution and end-of-season above-ground biomass (AGB) in 869 diverse accessions of highly productive (mean AGB = 23.4 Mg/Ha), photoperiod sensitive sorghum. Canopy surface height (CSM), ground cover (GC), and five common spectral indices were considered as features of the crop phenotype. Spline curve fitting was used to integrate data from single flights into continuous time courses. Random Forest was used to predict end-of-season AGB from aerial imagery, and to identify the most informative variables driving predictions. Improved prediction of end-of-season AGB (RMSE reduction of 0.24 Mg/Ha) was achieved earlier in the growing season (10 to 20 days) by leveraging early- and mid-season measurement of the rate of change of geometric and spectral features. Early in the season, dynamic traits describing the rates of change of CSM and GC predicted end-of-season AGB best. Late in the season, CSM on a given date was the most influential predictor of end-of-season AGB. The power to predict end-of-season AGB was greatest at 50 days after planting, accounting for 63% of variance across this very diverse germplasm collection with modest error (RMSE 1.8 Mg/ha). End-of-season AGB could be predicted equally well when spline fitting was performed on data collected from five flights versus 10 flights over the growing season. This demonstrates a more valuable and efficient approach to using UAVs for HTP, while also proposing strategies to add further value.

54 ENVIRONMENTAL SCIENCES↗

High temporal resolution observations of electron heating at the bow shock

Results deduced from highly time-resolved electron plasma profiles of earth's bow shock obtained with fast-plasma-experiment instrumentation on ISEE 1 and 2 are presented. Emphasis is placed on those bow-shock crossings that occurred during periods of high-data-rate transmission, so that the detailed structure of the bow-shock transition for electrons is discerned. The measurements indicate that electron thermalization and density compression are generally synchronized, although exceptions to this rule occur. In a few examples where direct comparison with magnetic-field measurements is possible, the electron-temperature and density profiles at the bow shock are found to be nearly identical to that of the field intensity. The measurements also reveal an interesting feature of the bow-shock profile, viz., an electron-pressure overshoot lasting several tens of seconds and generally followed by an undershoot, which gives the shock profile the appearance of a damped wave.

Bame, S. J.↗

High temporal resolution energetic particle soundings at the magnetopause on November 8, 1977, using ISEE 2

An inbound crossing of the magnetopause on November 8, 1977, was analyzed using the greater spatial resolution obtained by the ISEE 2 instrument at high bit rate. A technique is described, which was used to obtain trapping boundary parameters for five energy channels in the energy range from 24-70 keV, and the location of the trapping boundary with respect to the boundary layer plasma is identified in addition to the waves on the trapping boundary consistent with the soundings in all energy channels. It is found that the trapping boundary for energetic ions is sharp and well defined for about 35 keV ions, corresponding most of the time to the earthward edge of the plasma boundary layer. Magnetosheath-like plasma is sometimes observed up to 800 km inside the trapping boundary, and it is argued that the wave nature of the trapping boundary is the cause of the slight difference between the higher and lower energy ion trapping boundary locations.

Fritz, T. A.↗

Bench testing of a heterodyne CO 2 laser dispersion interferometer for high temporal resolution plasma density measurements

Here, a heterodyne detection scheme is combined with a 10.59 μm CO 2 laser dispersion interferometer for the first time to allow large bandwidth measurements in the 10-100 MHz range. The approach employed utilizes a 40 MHz acousto-optic cell operating on the frequency doubled CO 2 beam which is obtained using a high 2nd harmonic conversion efficiency orientation patterned gallium arsenide crystal. The measured standard deviation of the line integrated electron density equivalent phase resolution obtained with digital phase demodulation technique, is 4 × 10 17 m –2 . Air flow was found to significantly affect the baseline of the phase signal, which an optical table cover was able to reduce considerably. The heterodyne dispersion interferometer (DI) approach is found to be robustly insensitive to motion, with measured phase shifts below baseline drifts even in the presence of several centimeters of retroreflector induced path length variations. Plasma induced dispersion was simulated with a wedged ZnSe plate and the measured DI phase shifts are consistent with expectations.

47 OTHER INSTRUMENTATION↗

High temporal resolution velocity estimates from the NASA 50 MHz wind profiler

A three-point medium filter for wind profiling radar has been found which, when applied to successive spectral data, effectively eliminates most spurious echoes from the data while improving SNRs. When combined with velocity calculations using a first guess, the result is a robust system that can extract high-quality wind profiles at three-minute intervals. The velocity computation methodology is described and its performance is illustrated using two sample data sets taken during very different synoptic regimes. Operational considerations are discussed.

Wilfong, Timothy L.↗

High Resolution Temporal and Spectral Monitoring of Eta Carinae's X-Ray Emission the June Eclipse

The supermassive and luminous star Eta Carinae undergoes strong X-ray variations every 5.5 years when its 2-10 keV X-ray emission brightens rapidly with wild fluctuations before dropping by a factor of 100 to a minimum lasting 3 months. The most recent X-ray "eclipse" began in June 2003 and during this time Eta Carinae was intensely observed throughout the electromagnetic spectrum. Here we report the first results of frequent monitoring of the 2-10 keV band X-ray emission by the Rossi X-ray Timing Explorer along wit high resolution X-ray spectra obtained with the transmission gratings on the Chandra X-ray Observatory. We compare these observations to those results obtained during the previous X-ray eclipse in 1998, and interpret the variations in the X-ray brightness, in the amount of absorption, in the X-ray emission measure and in the K-shell emission lines in terms of a colliding wind binary model.

Corcoran, M. F.↗

Stormtime Particle Energization with High Temporal Resolution AMIE Potentials

Simulations were conducted to investigate the influence of rapid electric field fluctuations on electron energization in the inner magnetosphere based on the assimilative mapping of ionospheric electrodynamics (AMIE) technique. Simulations for four different magnetic storms were run, namely those that occurred on May 15, 1997, May 4, 1998, September 25, 1998, and October 19, 1998. Here, we have examined the formation of high energy (10-1000 keV) electrons in the inner magnetosphere during these storm events with our recently-developed relativistic radiation belt transport code. The point of this numerical experiment is to show that a simulation of a real event must have the high time resolution electric field input files in order to produce the seed population for the radiation belts, which are often observed to increase in the days following a magnetic storm. Specifically, a cadence of the global electric field pattern of 5 minutes or less produces inner magnetospheric fluxes that are larger (by up to several orders of magnitude) than fluxes produced with a longer cadence. Differences were particularly large relative to simulation results with a 3-hour time cadence, analogous to a Kp-driven electric field model.

Khazanov, George V.↗

Stormtime Particle Energization with High Temporal Resolution AMIE Potentials

Simulations were conducted to investigate the influence of rapid electric field fluctuations on electron energization in the inner magnetosphere based on the assimilative mapping of ionospheric electrodynamics (AMIE) technique. Simulations for four different magnetic storms were run, namely those that occurred on 15 May 1997, 4 May 1998, 25 September 1998, and 19 October 1998. Here we have examined the formation of high- energy (100-500 keV) electrons in the inner magnetosphere during these storm events with our recently developed relativistic radiation belt transport code. The point of this numerical experiment is to show that a simulation of a real event must have the high time resolution electric field input files in order to produce the seed population for the radiation belts, which are often observed to increase in the days following a magnetic storm. Specifically, a cadence of the global electric field pattern of 5 min or less produces inner magnetospheric fluxes that are larger (by up to several orders of magnitude) than fluxes produced with a longer cadence. Differences were particularly large relative to simulation results with a 3-hour time cadence, analogous to a Kpdriven electric field model.

Khazanov, George V.↗

Exploring electron-beam induced modifications of materials with machine-learning assisted high temporal resolution electron microscopy

Directed atomic fabrication using an aberration-corrected scanning transmission electron microscope (STEM) opens new pathways for atomic engineering of functional materials. In this approach, the electron beam is used to actively alter the atomic structure through electron beam induced irradiation processes. One of the impediments that has limited widespread use thus far has been the ability to understand the fundamental mechanisms of atomic transformation pathways at high spatiotemporal resolution. Here, we develop a workflow for obtaining and analyzing high-speed spiral scan STEM data, up to 100 fps, to track the atomic fabrication process during nanopore milling in monolayer MoS 2 . An automated feedback-controlled electron beam positioning system combined with deep convolution neural network (DCNN) was used to decipher fast but low signal-to-noise datasets and classify time-resolved atom positions and nature of their evolving atomic defect configurations. Through this automated decoding, the initial atomic disordering and reordering processes leading to nanopore formation was able to be studied across various timescales. Using these experimental workflows a greater degree of speed and information can be extracted from small datasets without compromising spatial resolution. This approach can be adapted to other 2D materials systems to gain further insights into the defect formation necessary to inform future automated fabrication techniques utilizing the STEM electron beam.

36 MATERIALS SCIENCE↗

High temporal resolution estimates of Arctic snowfall rates emphasizing gauge and radar-based retrievals from the MOSAiC expedition

This article presents the results of snowfall rate and accumulation estimates from a vertically pointing 35-GHz radar and other sensors deployed during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. The radar-based retrievals are the most consistent in terms of data availability and are largely immune to blowing snow. The total liquid-equivalent accumulation during the snow accumulation season is around 110 mm, with more abundant precipitation during spring months. About half of the total accumulation came from weak snowfall with rates less than approximately 0.2 mmh–1. The total snowfall estimates from a Vaisala optical sensor aboard the icebreaker are similar to those from radar retrievals, though their daily and monthly accumulations and instantaneous rates varied significantly. Compared to radar retrievals and the icebreaker optical sensor data, measurements from an identical optical sensor at an ice camp are biased high. Blowing snow effects, in part, explain differences. Weighing gauge measurements significantly overestimate snowfall during February–April 2020 as compared to other sensors and are not well suited for estimating instantaneous snowfall rates. The icebreaker optical disdrometer estimates of snowfall rates are, on average, relatively little biased compared to radar retrievals when raw particle counts are available and appropriate snowflake mass-size relations are used. These counts, however, are not available during periods that produced more than a third of the total snowfall. While there are uncertainties in the radar-based retrievals due to the choice of reflectivity-snowfall rate relations, the major error contributor is the uncertainty in the radar absolute calibration. The MOSAiC radar calibration is evaluated using comparisons with other radars and liquid water cloud–drizzle processes observed during summer. Overall, this study describes a consistent, radar-based snowfall rate product for MOSAiC that provides significant insight into Central Arctic snowfall and can be used for many other purposes.

54 ENVIRONMENTAL SCIENCES↗