Tomography of Plage and Network Magnetic Fields from Hinode and CLASP2 Observations
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R Ishikawa↗
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Mars planetary geodesy using earth-based observations of Mars landers
The potential for earth-based radiometric observations of a network of Mars surface landers to provide accurate determination of the Mars rotational orientation in inertial space is investigated. An error budget is presented for the carrier phase data type and related to system requirements for the surface landers. Differencing the carrier phase observations for a pair of Mars landers can provide extremely high precision due to common-mode error cancellation. Results of a covariance analysis are presented which show that Mars orientation can be determined to better than 10 milliarcsec, corresponding to decimeter distances at the planet surface. Recommendations on how to incorporate these concepts into future Mars missions, such as the Mars Environmental Survey, are discussed.
Edwards, C. D., Jr.↗
Improvement of VLBI EOP Accuracy and Precision
In the CORE program, EOP measurements will be made with several different networks, each operating on a different day. It is essential that systematic differences between EOP derived by the different networks be minimized. Observed biases between the simultaneous CORE-A and NEOS-A sessions are about 60-130 micro(as) for PM, UT1 and nutation parameters. After removing biases, the observed rms differences are consistent with an increase in the formal precision of the measurements by factors ranging from 1.05 to 1.4. We discuss the possible sources of unmodeled error that account for these factors and the biases and the sensitivities of the network differences to modeling errors. We also discuss differences between VLBI and GPS PM measurements.
MacMillan, Daniel↗
K-12 Students as Ground Observers of Contrails in Support of Scientific Research
Scientists are very interested in the formation of contrails, both the type and the coverage. To be detected by a satellite-born instrument, the contrail must be of a certain size, which means that some contrails go undetected. The K-12 education community is assisting with the study of contrails by participating in a network of student observers. To provide a venue for student contrail observations, the GLOBE Contrails protocol was developed as part of the GLOBE Atmospheric Science protocols. The first year of observations has provided a rich resource for researcher.
Chambers, Lin H.↗
Tracking seasonal variability in plant traits from spaceborne PRISMA and NEON AOP across forest types and ecoregions
Plant traits serve as critical indicators of how plants adapt to environmental changes and influence ecosystem functions. While airborne hyperspectral remote sensing effectively maps plant traits through detailed reflectance properties, it is limited by cost and scale, making large-scale and temporal studies challenging. The recently launched spaceborne hyperspectral imager, PRecursore IperSpettrale della Missione Applicativa (PRISMA), offers frequent, large scale and high-fidelity observations on a spatial resolution of 30 m and a revisit time of around 29 days, making it suitable for large-scale seasonal trait mapping. However, their potential remains largely unexplored. This study developed a multi-stage framework by leveraging the PRISMA spaceborne hyperspectral data and National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) hyperspectral data to investigate the seasonal dynamics of four key plant traits — chlorophyll content, carotenoid content, equivalent water thickness, and nitrogen content — across eleven NEON sites representing diverse forest types and ecoregions in the contiguous U.S. Our results demonstrated that PRISMA hyperspectral data can reliably track seasonal variability in plant traits, achieving overall R 2 values ranging from 0.78 to 0.88 and normalized root mean square error (NRMSE) values ranging from 5.4% to 8.4% for the four traits. Seasonal patterns revealed bell-shaped trajectories for chlorophyll and carotenoids, while equivalent water thickness decreased steadily across most sites, driven by structural changes during leaf maturation and senescence. Nitrogen content exhibited less pronounced seasonal variation but followed expected nutrient resorption patterns. Analysis of environmental drivers showed that seasonal variability is primarily controlled by solar radiation and day length in northern sites, vapor pressure in semi-arid regions, and temperature in mid-southeastern sites. Spatial variability, meanwhile, was primarily driven by soil properties, particularly during the peak growing season. However, the influence of soil variables slightly declines toward the end of the season at several sites, as climatic factors become more prominent. This study highlights the capability of PRISMA, and potentially other similar spaceborne hyperspectral data for large-scale, time-series plant trait mapping and provides valuable insights into the interactions between plant traits and environmental factors. In conclusion, these findings contribute to advancing our understanding of plant functional ecology and improving predictions of ecosystem responses to environmental changes.
Environmental drivers↗
Improving the Representation of Land Surface Processes Using the Data Assimilation Research Testbed (DART)
The land surface is a critical part of the earth system as processes related to water, carbon, energy and nitrogen cycling have important implications for climate forcing, air quality, water availability and seasonal atmospheric forecasting. Despite advances in land surface modeling, land surface model performance is often limited because of errors related to initial and boundary conditions, model structure, and parameters. Data assimilation (DA) techniques combined with an expanding network of earth system observations present an opportunity to reduce these errors and improve simulations. Here, we emphasize the implementation of tools and approaches to overcome challenges related to land DA to constrain carbon and water cycling. In particular, we discuss the implementation of adaptive inflation to modify ensemble spread in response to time-varying networks of gridded observations. We also discuss methods to generate ensemble spread through boundary condition (meteorology) forcing that can be applied to site-level applications. Next, we describe the application of vertical localization upon surface soil moisture observations, and forward operators specifically designed for the assimilation of snow and solar-induced fluorescence observations. Finally, we discuss the potential benefit of a quantile conserving filter used to update bounded quantities (state or parameter values).
Brett Raczka↗
Evaluation of IEEE 802.11g and 802.16 for Lunar Surface Exploration Missions Using MACHETE Simulations
In this paper, we investigated the suitability of terrestrial wireless networking technologies for lunar surface exploration missions. Specifically, the scenario we considered consisted of two teams of collaborating astronauts, one base station and one rover, where the base station and the rover have the capability of acting as relays. We focused on the evaluation of IEEE 802.11g and IEEE 802.16 protocols, simulating homogeneous 802.11g network, homogeneous 802.16 network, and heterogeneous network using both 802.11g and 802.16. A mix of traffic flows were simulated, including telemetry, caution and warning, voice, command and file transfer. Each traffic type had its own distribution profile, data volume, and priority. We analyzed the loss and delay trade-offs of these wireless protocols with various link-layer options. We observed that 802.16 network managed the channel better than an 802.11g network due to controlled infrastructure and centralized scheduling. However, due to the centralized scheduling, 802.16 also had a longer delay. The heterogeneous (hybrid) of 802.11/802.16 achieved a better balance of performance in terms of data loss and delay compared to using 802.11 or 802.16 alone.
Segui, John↗
Current-Sensitive Path Planning for an Underactuated Free-Floating Ocean Sensorweb
This work investigates multi-agent path planning in strong, dynamic currents using thousands of highly under-actuated vehicles. We address the specific task of path planning for a global network of ocean-observing floats. These submersibles are typified by the Argo global network consisting of over 3000 sensor platforms. They can control their buoyancy to float at depth for data collection or rise to the surface for satellite communications. Currently, floats drift at a constant depth regardless of the local currents. However, accurate current forecasts have become available which present the possibility of intentionally controlling floats' motion by dynamically commanding them to linger at different depths. This project explores the use of these current predictions to direct float networks to some desired final formation or position. It presents multiple algorithms for such path optimization and demonstrates their advantage over the standard approach of constant-depth drifting.
oceanography↗
Comparison of column water vapor measurements using downward-looking near-infrared and infrared imaging systems and upward-looking microwave radiometers
Remote soundings of precipitable water vapor from three systems are compared with each other and with ground truth from radiosondes. Ancillary data from a mesoscale network of surface observing stations and from wind-profiling radars are also used in the analysis. The three remote-sounding techniques are: (a) a reflectance technique using spectral data collected by the Airborne Visible-Infrared Imaging Spectrometer; (b) an emission technique using Visible-Infrared Spin Scan Radiometer Atmospheric Sounder (VAS) data acquired from the NOAA's GOES; and (c) a microwave technique using data from a limited network of three ground-based dual-channel microwave radiometers. The data were taken over the Front Range of eastern Colorado on 22-23 March 1990. The generally small differences between the three types of remote-sounding measurements are consistent with the horizontal and temporal resolutions of the instruments. The microwave and optical reflectance measurements agreed to within 0.1 cm; comparisons of the microwave data with radiosondes were also either as good or explainable. The largest differences between the VAS and the microwave radiometer at Elbert were between 0.4 and 0.5 cm and appear to be due to variable terrain within the satellite footprint.
Gao, Bo-Cai↗
Distributed state-space generation of discrete-state stochastic models
High-level formalisms such as stochastic Petri nets can be used to model complex systems. Analysis of logical and numerical properties of these models of ten requires the generation and storage of the entire underlying state space. This imposes practical limitations on the types of systems which can be modeled. Because of the vast amount of memory consumed, we investigate distributed algorithms for the generation of state space graphs. The distributed construction allows us to take advantage of the combined memory readily available on a network of workstations. The key technical problem is to find effective methods for on-the-fly partitioning, so that the state space is evenly distributed among processors. In this paper we report on the implementation of a distributed state-space generator that may be linked to a number of existing system modeling tools. We discuss partitioning strategies in the context of Petri net models, and report on performance observed on a network of workstations, as well as on a distributed memory multi-computer.
Ciardo, Gianfranco↗
Auroral kilometric radiation/aurora correlation
Auroral kilometric radiation (AKR) observations from the ISIS 1 topside sounder receiver were compared with visual auroral observations from the network of Alaskan all-sky camera stations. The goal was to relate AKR source region encounters to specific auroral forms on the same magnetic field line. Thirty-eight simultaneous data sets were identified and analyzed. In general, intense AKR was associated with bright auroral arcs and conditions of weak or no AKR corresponded to times when either no aurora or only a faint arc or weak diffuse aurora were observed. Five cases, when both intense AKR and bright visual aurora were present, were analyzed in detail. Complete electron density N sub e contours, from the satellite altitude down to the F region ionization peak, were obtained along N-S traversals of the AKR source region. In addition, the ISIS 1 orbital tracks were projected down the magnetic field lines to the auroral altitude and compared to auroral features on a map derived from the all sky camera images. Density cavities (regions where N sub e 100/cu cm) were encountered on each of these passes.
Benson, R. F.↗
Auroral kilometric radiation/aurora correlation
Auroral kilometric radiation (AKR) observations from the ISIS 1 topside sounder receiver were compared with visual auroral observations from the network of Alaskan all-sky camera stations. The goal was to relate AKR source region encounters to specific auroral forms on the same magnetic field line. Thirty-eight simultaneous data sets were identified and analyzed. In general, intense AKR was associated with bright auroral arcs and conditions of weak or no AKR corresponded to times when either no aurora or only a faint arc or weak diffuse aurora were observed. Five cases, when both intense AKR and bright visual aurora were present, were analyzed in detail. Complete electron density N sub e contours, from the satellite altitude down to the F region ionization peak, were obtained along N-S traversals of the AKR source region. In addition, the ISIS 1 orbital tracks were projected down the magnetic field lines to the auroral altitude and compared to auroral features on a map derived from the all sky camera images. Density cavities (regions where N sub e 100/cu cm) were encountered on each of these passes. Previously announced in STAR as N83-27516
Benson, R. F.↗
Recent studies of magnetic canopies
Two current studies are described which stem from Giovanelli's seminal studies of the spreading of chromospheric fields near active regions and active-region network. First, improved observational techniques are described for obtaining magnetograms in the Ca II 8542 A, Fe I 8688 A, and C I 9111 A lines which at least in principle allow for more accurate treatment of instrumental noise and allow better inference of field orientation. Second, a generalized response function is developed for calculating theoretical magnetograph signals from arbitrary line-of-sight variations of magnetic field, and initial applications to two-dimensional, potential-field models of network fields are described. Preliminary indications are that potential-field models can better explain the presence of low-lying, diffuse horizontal fields than can thin flux-tube models, but fail to predict a differential response between the different lines.
Jones, H. P.↗
Geometric adjustment of the South American satellite densification (PC-1000) network
Reduced normal equations were computed from observation data and combined with reduced normal equations of other satellite networks to provide station coordinates from a single least square adjustment. Terrestrial data, which include base-lines, heights, and survey coordinates, provide the necessary relative position constraints between collocated stations of two satellite networks. Survey information regarding the observation stations is summarized, and constraints used in the solution are given. Geoidal undulations are computed by using the formula and constants shown.
Mueller, I. I.↗
Collaborative Clustering for Sensor Networks
Traditionally, nodes in a sensor network simply collect data and then pass it on to a centralized node that archives, distributes, and possibly analyzes the data. However, analysis at the individual nodes could enable faster detection of anomalies or other interesting events, as well as faster responses such as sending out alerts or increasing the data collection rate. There is an additional opportunity for increased performance if individual nodes can communicate directly with their neighbors. Previously, a method was developed by which machine learning classification algorithms could collaborate to achieve high performance autonomously (without requiring human intervention). This method worked for supervised learning algorithms, in which labeled data is used to train models. The learners collaborated by exchanging labels describing the data. The new advance enables clustering algorithms, which do not use labeled data, to also collaborate. This is achieved by defining a new language for collaboration that uses pair-wise constraints to encode useful information for other learners. These constraints specify that two items must, or cannot, be placed into the same cluster. Previous work has shown that clustering with these constraints (in isolation) already improves performance. In the problem formulation, each learner resides at a different node in the sensor network and makes observations (collects data) independently of the other learners. Each learner clusters its data and then selects a pair of items about which it is uncertain and uses them to query its neighbors. The resulting feedback (a must and cannot constraint from each neighbor) is combined by the learner into a consensus constraint, and it then reclusters its data while incorporating the new constraint. A strategy was also proposed for cleaning the resulting constraint sets, which may contain conflicting constraints; this improves performance significantly. This approach has been applied to collaborative clustering of seismic and infrasonic data collected by the Mount Erebus Volcano Observatory in Antarctica. Previous approaches to distributed clustering cannot readily be applied in a sensor network setting, because they assume that each node has the same view of the data set. A view is the set of features used to represent each object. When a single data set is partitioned across several computational nodes, distributed clustering works; all objects have the same view. But when the data is collected from different locations, using different sensors, a more flexible approach is needed. This approach instead operates in situations where the data collected at each node has a different view (e.g., seismic vs. infrasonic sensors), but they observe the same events. This enables them to exchange information about the likely cluster membership relations between objects, even if they do not use the same features to represent the objects.
Wagstaff. Loro :/↗
Imprint of Anthropogenic Sources and Soil Removal on the Surface Concentration of H2 in the Contiguous US
Hydrogen (H2) is experiencing renewed interest throughout the world as a low carbon fuel alternative or complement to fossil fuels. Significant uncertainties remain regarding the environmental impact of increasing H2 usage, in part due to gaps in our understanding of the H2 atmospheric budget, including the H2 release from industrial activities and the H2 soil removal, the most important sink of H2. This study focuses on H2 dry air mole fractions measured by the NOAA Global Monitoring Laboratory in discrete ambient air samples collected every few days at sites located in the contiguous United States between 2010 and 2022. We take advantage of the long-term observations from this network to study the regional distribution of H2 sources using the potential source contribution function (PSCF). We find that H2 PSCF is consistent with a large anthropogenic source of atmospheric H2 from the incomplete combustion of fossil fuel. However, episodic air masses with high H2 dry air mole fractions (>700 ppb) recorded at some sampling locations in the Western and Southeastern US are not associated with elevated CO, suggesting significant noncombustion anthropogenic or geological sources of H2. Air masses depleted in H2 are recorded in rural or remote continental sites. Our analysis of observations from a tall tower in NE Colorado suggests that the degree of H2 depletion not only reflects differences in soil exposure but also the regional inhibition of the soil sink under arid conditions.
Paulot, Fabien↗
The Connection between Model Performance on the CCMVal Transport Diagnostics and Simulated Sensitivity of Ozone to Chlorine Change
The chemistry climate models that contributed simulations for past and future ozone evolution to the 2010 Scientific Assessment of Ozone Depletion were subject to extensive evaluation by the SPARC (Stratospheric Processes and their Role in Climate) CCMVal (Chemistry-Climate Model Validation) activity. The sensitivity of ozone to changes in composition and climate varies among the models, but the relationship between these variations and the model evaluations of CCMVal is not obvious. We have learned that the transport evaluation can be used to interpret the comparisons between observed and simulated columns of chlorine reservoirs, hydrochloric acid (HCl) and chlorine nitrate (ClONO2); these comparisons were part of the CCMVal evaluation of chemistry. The simulations with best performance on the transport diagnostics most faithfully reproduce the evolution and seasonal variation of the chlorine reservoirs as observed at NDACC (Network for Detection of Atmospheric Composition Change) stations (NyAlesund 78.9N, Kiruna 67.8N, Harestua 60.2N, Jungfraujoch 46.6N, Toronto 43.6N, Kitt Peak 31.9N, Izana 28.3N, Mauna Loa 19.5N, Lauder 45S and Arrival Heights 77.8S). In the simulations, the HCl in the lower stratosphere depends on total inorganic chlorine (Cly) and partitioning between HCl and ClON02. Total inorganic chlorine depends on the fractional release of chlorine from source gases, and ratio of ClON02 to HCl is inversely dependent on methane and varies quadratically with ozone. Simulated HCl from various models may agree with observations even though Cly is in error, partitioning is in error, or both. Simulated ozone sensitivity to chlorine is shown to be greater for models that produce larger values of chlorine nitrate for background chlorine levels, and vice versa. Comparisons with the NDACC data show why the models with 'best' transport have similar sensitivity to chlorine change. The realistic evolution of the simulated HCl and ClONO2 columns suggests realistic levels of Cly in the lower atmosphere. In addition, the wide range values for the sensitivity of ozone to chlorine obtained from the CCMVal simulations is explained by the wide range in lower atmospheric columns of ClONO2 and the concomitant wide range of levels for chlorine monoxide.
Douglass, Anne↗
Synoptic conditions producing cirrus during the FIRE cirrus IFO
Although direct observations of cirrus clouds by the FIRE research aircraft were usually confined to the area of Intensive Field Observation (IFO) surface network, these cirrus were generally part of a more extensive zone of upper level cloudiness. It is these large scale patterns of cirriform cloud and their relationship to the corresponding synoptic environment which are the prime focus. Three conceptual models are presented and each of the individual cases are classified into one of these categories. Although the cases manifest significant differences in intensity and small scale structure, it is believed that they are best viewed in this unified context. The descriptions given are mostly qualitative, however, quantitative descriptions of the synoptic control and its relationship to cloud structure for all the IFO cases are summarized. The synoptic situations in which extensive cirriform clouds were observed are classified into three basic types: warm front cases, cold front cases, and closed low aloft cases. A simplified summary of each type of situation is presented.
Starr, David OC.↗