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At least 163 records · Page 9

Time-Domain Astronomy with the Fermi GBM

The Fermi Gamma-ray Burst Monitor (GBM) is an all-sky monitoring instrument sensitive to energies from 8 keV to 40 MeV. Over the past 8 years of operation, the GBM has detected over 240 gamma-ray bursts per year and provided timely GCN notices with localization to few-degree accuracy for follow-up observations. In addition to GRBs, Galactic transients, solar flares, and terrestrial gamma-ray flashes have also been observed. In recent years we have also been searching the continuous GBM data for electromagnetic counterpart to astrophysical neutrinos and gravitational wave events, as these are believed to be associated with gamma-ray bursts. With continuous data downlink every few hours and a temporal resolution of 2 microseconds, GBM is well suited for observing transients and supporting EM follow-up in the era of multi-messenger astronomy.

gamma-ray burst↗

Time-Domain Astronomy with the Fermi GBM

The Fermi Gamma-ray Burst Monitor (GBM) is an all-sky monitoring instrument sensitive to energies from 8 kiloelectronvolts to 40 megaelectronvolts. Over the past 8 years of operation, the GBM has detected over 240 gamma-ray bursts per year and provided timely GCN (Gamma-ray Coordinates Network) notices with localization to few-degree accuracy for follow-up observations. In addition to GRBs, galactic transients, solar flares, and terrestrial gamma-ray flashes have also been observed. In recent years we have also been searching the continuous GBM data for electromagnetic counterpart to astrophysical neutrinos and gravitational wave events, as these are believed to be associated with gamma-ray bursts. With continuous data downlink every few hours and a temporal resolution of 2 microseconds, GBM is well suited for observing transients and supporting EM followup in the era of multi-messenger astronomy.

gamma-ray burst↗

Altimetry for the Future: Building on 25 Years of Progress

In 2018 we celebrated 25 years of development of radar altimetry, and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences. Many symbolic major events have celebrated these developments, e.g., in Venice, Italy, the 15th (2006) and 20th (2012) years of progress and more recently, in 2018, in Ponta Delgada, Portugal, 25 Years of Progress in Radar Altimetry. On this latter occasion it was decided to collect contributions of scientists, engineers and managers involved in the worldwide altimetry community to depict the state of altimetry and propose recommendations for the altimetry of the future. This paper summarizes contributions and recommendations that were collected and provides guidance for future mission design, research activities, and sustainable operational radar altimetry data exploitation. Recommendations provided are fundamental for optimizing further scientific and operational advances of oceanographic observations by altimetry, including requirements for spatial and temporal resolution of altimetric measurements, their accuracy and continuity. There are also new challenges and new openings mentioned in the paper that are particularly crucial for observations at higher latitudes, for coastal oceanography, for cryospheric studies and for hydrology. The paper starts with a general introduction followed by a section on Earth System Science including Ocean Dynamics, Sea Level, the Coastal Ocean, Hydrology, the Cryosphere and Polar Oceans and the ‘‘Green” Ocean, extending the frontier from biogeochemistry to marine ecology. Applications are described in a subsequent section, which covers Operational Oceanography, Weather, Hurricane Wave and Wind Forecasting, Climate projection. Instruments’ development and satellite missions’ evolutions are described in a fourth section. A fifth section covers the key observations that altimeters provide and their potential complements, from other Earth observation measurements to in situ data. Section 6 identifies the data and methods and provides some accuracy and resolution requirements for the wet tropospheric correction, the orbit and other geodetic requirements, the Mean Sea Surface, Geoid and Mean Dynamic Topography, Calibration and Validation, data accuracy, data access and handling (including the DUACS system). Section 7 brings a transversal view on scales, integration, artificial intelligence, and capacity building (education and training). Section 8 reviews the programmatic issues followed by a conclusion.

Saleh Abdalla↗

Comparison of Dust Optical Depth From Multi-Sensor Products and MONARCH (Multiscale Online Non-hydrostatic AtmospheRe CHemistry) Dust Reanalysis Over North Africa, the Middle East, and Europe

Aerosol reanalysis datasets are model-based, observationally constrained, continuous 3D aerosol fields with a relatively high temporal frequency that can be used to assess aerosol variations and trends, climate effects, and impacts on socioeconomic sectors, such as health. Here we compare and assess the recently published MONARCH (Multiscale Online Non-hydrostatic AtmospheRe CHemistry) high-resolution regional desert dust reanalysis over northern Africa, the Middle East, and Europe (NAMEE) with a combination of ground-based observations and space-based dust retrievals and products. In particular, we compare the total and coarse dust optical depth (DOD) from the new reanalysis with DOD products derived from MODIS (MODerate resolution Imaging Spectroradiometer), MISR (Multi-angle Imaging SpectroRadiometer), and IASI (Infrared Atmospheric Sounding Interferometer) spaceborne instruments. Despite the larger uncertainties, satellite-based datasets provide a better geographical coverage than ground-based observations, and the use of different retrievals and products allows at least partially overcoming some single-product weaknesses in the comparison. Nevertheless, limitations and uncertainties due to the type of sensor, its operating principle, its sensitivity, its temporal and spatial resolution, and the methodology for retrieving or further deriving dust products are factors that bias the reanalysis assessment. We, therefore, also use ground-based DOD observations provided by 238 stations of the AERONET (AErosol RObotic NETwork) located within the NAMEE region as a reference evaluation dataset. In particular, prior to the reanalysis assessment, the satellite datasets were evaluated against AERONET, showing moderate underestimations in the vicinities of dust sources and downwind regions, whereas small or significant overestimations, depending on the dataset, can be found in the remote regions. Taking these results into consideration, the MONARCH reanalysis assessment shows that total and coarse-DOD simulations are consistent with satellite- and ground-based data, qualitatively capturing the major dust sources in the area in addition to the dust transport patterns. Moreover, the MONARCH reanalysis reproduces the seasonal dust cycle, identifying the increased dust activity that occurred in the NAMEE region during spring and summer. The quantitative comparison between the MONARCH reanalysis DOD and satellite multi-sensor products shows that the reanalysis tends to slightly overestimate the desert dust that is emitted from the source regions and underestimate the transported dust over the outflow regions, implying that the model's removal of dust particles from the atmosphere, through deposition processes, is too effective. More specifically, small positive biases are found over the Sahara desert (0.04) and negative biases over the Atlantic Ocean and the Arabian Sea (−0.04), which constitute the main pathways of the long-range dust transport. Considering the DOD values recorded on average there, such discrepancies can be considered low, as the low relative bias in the Sahara desert (< 50 %) and over the adjacent maritime regions (< 100 %) certifies. Similarly, over areas with intense dust activity, the linear correlation coefficient between the MONARCH reanalysis simulations and the ensemble of the satellite products is significantly high for both total and coarse DOD, reaching 0.8 over the Middle East, the Atlantic Ocean, and the Arabian Sea and exceeding it over the African continent. Moreover, the low relative biases and high correlations are associated with regions for which large numbers of observations are available, thus allowing for robust reanalysis assessment.

Michail Mytilinaios↗

Mapping National Forest Aboveground Biomass in Mexico By Integrating GEDI and Landsat Times Series Data

Mexico is one of the countries with great potential for the UN's Reducing Emissions from Deforestation and Forest Degradation (REDD+) program, a key nature-based solution for the forest sector. To monitor carbon stock changes, there is a growing demand for unbiased Monitoring Reporting Verification (MRV) systems to facilitate effective forest management and climate change mitigation strategies. Remote sensing-based national aboveground biomass density (AGBD) estimation over Mexico is scarce and often limited to one-time static mapping, leading to spatiotemporal inconsistency in inputs. As an effort under NASA's Carbon Monitoring System (CMS) program, we have developed a remote sensing-based approach to create consistent historical AGBD maps of Mexico using multi-stream remote sensing data, including spaceborne lidar GEDI and long-term Landsat time series, as well as topographic information. We employ the continuous change detection and classification (CCDC) algorithm for temporal modeling of Landsat surface reflectance, followed by the inference of forest AGBD using a random forest machine learning algorithm with the temporal information of land surface dynamics extracted by the CCDC as input. GEDI provides unprecedented forest structure and AGBD sampling datasets for model training and validation practices. In this presentation, we share the progress made in developing a spatially explicit mapping of historical AGBD changes associated with land surface changes and post-disturbance landscapes.

Taejin Park↗

Dual-Comb Spectroscopy to Tethered Balloon System (DCS to TBS) Field Campaign Report

There is a critical need for the ability to detect, quantify, and attribute sources and sinks of greenhouse gases (GHGs) with high temporal and spatial resolution. Current methods are typically based on continuously operating near-surface point sensors or intermittent aerial/satellite observations. Dual optical frequency comb spectroscopy (“dual-comb spectroscopy”; DCS) is a laser-based technique that can bridge this sensing gap by providing high-precision, high-accuracy, and high-temporal-resolution detection and quantification of trace gases over kilometer-length scales, connecting local and regional observations. A single DCS system can also provide spatial resolution for source/sink attribution with the addition of a few minor optical elements, enabling cross-validation of other observations (e.g., Total Carbon Column Observing Network [TCCON], Orbiting Carbon Observatory [OCO-2/3], Greenhouse Gases Observing Satellite [GOSAT-1/2][).

54 ENVIRONMENTAL SCIENCES↗

A Multi-Satellite Assimilation and Modeling Platform to Construct a Global and Complete view of the Hydrologic Cycle

What captivates me about the research field of satellite remote sensing of the earth system science is the opportunity to help human beings by addressing challenging questions related to the current and future availability of natural resources for domestic, agricultural, and industrial needs. For example, a continuously varying climate poses a threat to the water resource, not only in developing countries, but also in economically well-developed regions, creating the urgent need to characterize and predict its spatial and temporal availability. Specifically, my curiosity is driven by the challenge of merging cutting-edge space technology and earth observations (i.e., remote sensing) with state-of-the-art models for the purpose of improving our scientific knowledge about the variability and the change of the hydrologic cycle.The only practical way to observe the land surface processes (e.g., hydrologic cycle) on continental to global scales is via satellite remote sensing. Though remote sensing can make spatially comprehensive measurements of various components of the land surface system, it cannot provide direct information on the entire system, and the measurements represent only a snapshot in time. Physical based models may be used to continuously predict the temporal and spatial earth processes, but these predictions are often poor, due to model initialization, parameter and meteorological forcing errors, and inadequate model physics and/or resolution. Thus, an attractive prospect is to combine the strengths of land surface models and observations (and minimize the weaknesses of both) to provide a superior land surface state estimate. This is the goal of land surface data assimilation. Data assimilation provides a better estimate of the environmental states than either models or observations could individually do. The broad concept of data assimilation can be applied to various disciplines such as hydrology, ecology, environmental hazards, agriculture and economy.My research is targeted to integrating multiple satellite information having multi-sensor and multi-resolution assimilation within today's state-of-the-art hydrologic models. Multi-sensor and multi-resolution assimilation techniques represent a necessary milestone in future earth science applications because they offer the capability of comprehensively integrating disparate types of earth observations via deep-learning techniques. A multi-satellite assimilation and modeling platform will ultimately provide a robust and complete dataset to more fully understand earth's dynamics. In fact, the multi-satellite assimilation platforms build a comprehensive description of the earth processes that is geared toward accurately representing the complexity of natural and anthropogenic interactions in land surface processes. Most importantly, these platforms are suitable as decision support tools for applications across different aspects of earth system science.My recent work has focused on recent multi-sensor data assimilation techniques targeted at improving snow, soil moisture, groundwater, and terrestrial water storage hydrological states.

Girotto, Manuela↗

Unveiling Temporal Performance Deviation: Leveraging Clustering in Microservices Performance Analysis

As the market for cloud computing continues to grow, an increasing number of users are deploying applications as microservices. The shift introduces unique challenges in identifying and addressing performance issues, particularly within large and complex infrastructures. To address this challenge, we propose a methodology that unveils temporal performance deviations in microservices by clustering containers based on their performance characteristics at different time intervals. Showcasing our methodology on the Alibaba dataset, we found both stable and dynamic performance patterns, providing a valuable tool for enhancing overall performance and reliability in modern application landscapes.

Clustering↗

Seasonal Monitoring of Melt and Accumulation Within the Deep Percolation Zone of the Greenland Ice Sheet and Comparison with Simulations of Regional Climate Modeling

Increasing melt over the Greenland Ice Sheet (GrIS) recorded over the past several years has resulted in significant changes of the percolation regime of the ice sheet. It remains unclear whether Greenland's percolation zone will act as a meltwater buffer in the near future through gradually filling all pore space or if near-surface refreezing causes the formation of impermeable layers, which provoke lateral runoff. Homogeneous ice layers within perennial firn, as well as near-surface ice layers of several meter thickness have been observed in firn cores. Because firn coring is a destructive method, deriving stratigraphic changes in firn and allocation of summer melt events is challenging. To overcome this deficit and provide continuous data for model evaluations on snow and firn density, temporal changes in liquid water content and depths of water infiltration, we installed an upward-looking radar system (upGPR) 3.4 m below the snow surface in May 2016 close to Camp Raven (66.4779 deg N, 46.2856 deg W) at 2120 m a.s.l. The radar is capable of quasi-continuously monitoring changes in snow and firn stratigraphy, which occur above the antennas. For summer 2016, we observed four major melt events, which routed liquid water into various depths beneath the surface. The last event in mid-August resulted in the deepest percolation down to about 2.3 m beneath the surface. Comparisons with simulations from the regional climate model MAR are in very good agreement in terms of seasonal changes in accumulation and timing of onset of melt. However, neither bulk density of near-surface layers nor the amounts of liquid water and percolation depths predicted by MAR correspond with upGPR data. Radar data and records of a nearby thermistor string, in contrast, matched very well for both timing and depth of temperature changes and observed water percolations. All four melt events transferred a cumulative mass of 56 kg/(sq. m) into firn beneath the summer surface of 2015. We find that continuous observations of liquid water content, percolation depths and rates for the seasonal mass fluxes are sufficiently accurate to provide valuable information for validation of model approaches and help to develop a better understanding of liquid water retention and percolation in perennial firn.

Heilig, Achim↗

Effect of GOES-R Image Navigation and Registration Errors on Atmospheric Motion Vectors

High temporal frequency imagery from geostationary satellites allows for the continuous monitoring of rapidly changing atmospheric constituents such as smoke, dust, water vapor and clouds. The image sequences are often used to quantify the displacement of image features such as water vapor and clouds to produce atmospheric motion vectors (AMVs) which are used as diagnostic tools and also assimilated into numerical weather forecast models. The basic principle behind the determination of AMVs is the calculation of the physical displacement of features from one image (time) to the next. This process assumes that the features being tracked do not change as a function of time, usually requiring the use of short time interval imagery to minimize substantial change in size and shape of the features being tracked. High spatial resolution imagery also is required for reliable feature identification. While these image resolution and temporal sampling requirements often provide major drivers for space-based instrument design requirements, accurate image navigation and registration, INn (between a sequence of images), is also critical to the derivation of useful AMVs. In this paper and poster to be presented at the conference, the image navigation and registration (INR) accuracy expected for the Advanced Baseline Imager (ABI) on the GOES-R series of satellites will be discussed in light of its impact on AMV accuracy. Significant satellite platform and modeling enhancements are planned which should significantly improve INn performance of the GOES-R instruments. Some of these improvements have been demonstrated for the GOES-13 satellite which was launched in summer of 2006. An analysis of GOES-13 INR data, from the special satellite check out period, will be used in the assessment.

Jedlovec, Gary↗

All-fiber, discrete arbitrary picket-pulse shaping

Here, a novel all-fiber, hybrid pulse-shaping system based on the temporal stacking of discrete optical picket pulses combined with continuously shaped optical pulses provides 100-ps resolution with the high dynamic range and flexibility required for laser fusion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Microbial potentiometric sensor: A new approach to longstanding challenges

The underlying hypothesis of this study is that simple potentiometric measurements between sensing electrodes and a shared reference electrode - Microbial Potentiometric Sesnor (MPS) system - can be employed in a long-term, continuous mode of operation to resolve the spatial and temporal changes in environmental systems. To address the hypothesis, (1) a conceptual description of the MPS system and its postulated principle of operation are provided; (2) the MPS system performance is documented under controlled laboratory conditions; and (3) the capabilities of the MPS system are documented under quiescent and dynamic field condition. In a laboratory setting, the variability among different MPS signals was insignificant confirming the postulated high accuracy and reproducibility of the sensor performance. It also demonstrated statistically significant correlations with dissolved oxygen (DO) and oxidation-reduction potential (ORP) sensors, while showing capabilities of operating under anoxic and anaerobic conditions. Regardless of their locations in the model wetland system, three MPS sensors functioned without interruption and cleaning for a period >2 years, and thus demonstrating long-term durability of the MPS technology. In real batch-wastewater treatment facility, the deployed MPS system signals were able to describe the organic carbon trends and correlate with each treatment phase in a cycle. Data reproducibility and reliability exceeded the expectations better describing the carbon treatment levels than the DO and ORP sensors (p < 4.4 × 10 –162 vs phase adjusted p < 3.0 × 10 –58 ). While MPS signals correlate with specific parameters that describe the local process or environments, it is more prudent to employ both the magnitude and pattern of a composite signal like the MPS signal describe the change to reflect any shift in the local environment. Finally, when compared to a baseline pattern, this change in signal magnitude and pattern reveals important information that can be employed to tailor and optimize any condition or process which involves microorganisms.

47 OTHER INSTRUMENTATION↗

Terahertz Spectroscopy of Gas Mixtures with Dual Quantum Cascade Laser Frequency Combs

Terahertz laser frequency combs based on quantum cascade lasers provide coherent, broadband, electrically pumped, THz radiation sources for use in future spectroscopic applications. In this work, we explore the feasibility of such lasers in a dual-comb spectroscopy configuration for the detection of multiple molecular samples in the gas phase. The lasers span approximately 180 GHz of optical bandwidth, centered at 3.4 THz, with submilliwatt total optical power. One of the main advantages of dual-comb spectroscopy is its high speed, which opens up the possibility for direct observations of chemical reaction dynamics in the terahertz spectral region. As a proof-of-concept, we recorded continuously evolving spectra from gas mixtures with 1 ms temporal resolution.

42 ENGINEERING↗

Fermion-bag inspired Hamiltonian lattice field theory for fermionic quantum criticality

Motivated by the fermion-bag approach, in this work we construct a new class of Hamiltonian lattice field theories that can help us to study fermionic quantum critical points, particularly those with four-fermion interactions. Although these theories are constructed in discrete time with a finite temporal lattice spacing ϵ, when ϵ → 0, conventional continuous-time Hamiltonian lattice field theories are recovered. The fermion-bag algorithms run relatively faster when ϵ = 1 as compared to ϵ → 0 but still allow us to compute universal quantities near the quantum critical point even at such a large value of ϵ. As an example of this new approach, here we study the $N_f$ = 1 Gross-Neveu chiral-Ising universality class in 2 + 1 dimensions by calculating the critical scaling of the staggered mass order parameter. We show that we are able to study lattice sizes up to 100 2 sites when ϵ = 1, while with comparable resources we can reach lattice sizes of only up to 64 2 when ϵ → 0. The critical exponents obtained in both these studies match within errors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Joint physics-based and data-driven time-lapse seismic inversion: Mitigating data scarcity

In carbon capture and sequestration (CCS), developing rapid and effective imaging techniques is crucial for real-time monitoring of the spatial and temporal dynamics of CO 2 propagation during/after injection. With continuing improvements in computational power and data storage, data-driven techniques based on machine learning (ML) have been effectively applied to seismic inverse problems. In particular, ML helps alleviate the ill-posedness and high computational cost of full-waveform inversion (FWI). However, such data-driven inversion techniques require massive high-quality training data sets to ensure prediction accuracy, which hinders their application to time-lapse monitoring of CO 2 sequestration. We propose an efficient “hybrid” time-lapse workflow that combines physics-based FWI and data-driven ML inversion. The scarcity of the available training data is addressed by developing a new data-generation technique with physics constraints. The method is vali dated on a synthetic CO 2 -sequestration model based on the Kimberlina storage reservoir in California. The proposed approach is shown to synthesize a large volume of high-quality, physically realistic training data, which is critically important in accurately characterizing the CO 2 movement in the reservoir. In conclusion, the developed hybrid methodology can also simultaneously predict the variations in velocity and saturation and achieve high spatial resolution in the presence of realistic noise in the data.

58 GEOSCIENCES↗

Recent observations of cosmic gamma-ray bursts

The paper summarizes current knowledge of cosmic gamma ray bursts obtained from recent spaceborne observations. Three facts lie at the basis of interpreting gamma ray burst observations: (1) all measured event differential energy spectra appear to be alike, (2) there is no evidence that the event integral size spectrum departs from a -1.5 power law, and (3) the temporal structures of most events are consistent with a continuous flutter down to at least 30 msec throughout the event histories. Event-average spectra of 9 bursts observed with IMP-7 are presented, and the Vela size spectrum is compared with IMP-7 points, SAS-2 events, and balloon experiment limits.

Cline, T. L.↗

TRMM ground truth in a monsoon environment - Darwin, Australia

A ground truth station for the Tropical Rainfall Measuring Mission (TRMM) is described. The station is situated in Darwin, Australia in a monsoon environment typical for Southeast Asia. The climatological features of the site, and the Darwin observational program are examined. The instruments and operations at the station are discussed, including a Doppler radar making full upper tropospheric soundings every 12 hrs and wind soundings every 6 hrs, and a mesoscale raingauge and surface observing network operating continuously through the summer monsoon seasons. The spatial and temporal characteristics of rainfall in the area and an outline of the research objectives of the program are presented.

Keenan, T. D.↗

Meso-beta scale numerical simulation studies of terrain-induced jet streak mass and momentum perturbations

An in-depth analysis of observed gravity waves and their relationship to precipitation bands over the Montana mesonetwork during the 11-12 July 1981 CCOPE case study indicated two episodes of coherent waves. While geostrophic adjustment, shearing instability, and terrain were all implicated separately or in combination as possible wave generation mechanisms, the lack of upper-air data within the wave genesis region made it difficult to define the genesis processes from observations alone. The first part of this paper, 3D Numerical Modeling Studies of Terrain-Induced Mass/Momentum Perturbations, employs a mesoscale numerical model to help diagnose the intricate early wave generation mechanisms during the first observed gravity wave episode. The meso-beta scale numerical model is used to study various simulations of the role of multiple geostrophic adjustment processes in focusing a region for gravity wave genesis. The second part of this paper, Linear Theory and Theoretical Modeling, investigates the response of non-resting rotating homogeneous and continuously stratified Boussinesq models of the terrestrial atmosphere to temporally impulsive and uniformly propagating three-dimensional localized zonal momentum sources representative of midlatitude jet streaks. The methods of linear perturbation theory applied to the potential vorticity (PV) and wave field equations are used to study the geostrophic adjustment dynamics. The total zonal and meridional wind perturbations are separated into geostrophic and ageostrophic components in order to define and follow the evolution of both the primary and secondary mesocirculations accompanying midlatitude jetogenesis forced by geostrophic adjustment processes. This problem is addressed to help fill the gap in understanding the dynamics and structure of mesoscale inertia-gravity waves forced by geostrophic adjustment processes in simple two-dimensional quiescent current systems and those produced by mesoscale numerical models simulating the orographic and diabatic perturbation of three-dimensional quasi-geostrophically balanced synoptic scale jet streaks associated with complex baroclinic severe storm producing environments.

Lin, Yuh-Lang↗