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NASA NTRS2020

Wildfire Smoke Particle Properties and Evolution, from Space-Based Multi-Angle Imaging

Emitted smoke composition is determined by properties of the biomass burning source and ambient ecosystem. However, conditions that mediate the partitioning of black carbon (BC) and brown carbon (BrC) formation, as well as the spatial and temporal factors that drive particle evolution, are not understood adequately for many climate and air-quality related modeling applications. In situ observations provide considerable detail about aerosol microphysical and chemical properties, although sampling is extremely limited. Satellites offer the frequent global coverage that would allow for statistical characterization of emitted and evolved smoke, but generally lack microphysical detail. However, once properly validated, data from the National Aeronautics and Space Administration (NASA) Earth Observing System’s Multi-Angle Imaging Spectroradiometer (MISR) instrument can create at least a partial picture of smoke particle properties and plume evolution. We use in situ data from the Department of Energy’s Biomass Burning Observation Project (BBOP) field campaign to assess the strengths and limitations of smoke particle retrieval results from the MISR Research Aerosol (RA) retrieval algorithm. We then use MISR to characterize wildfire smoke particle properties and to identify the relevant aging factors in several cases, to the extent possible. The RA successfully maps qualitative changes in effective particle size, light absorption, and its spectral dependence, when compared to in situ observations. By observing the entire plume uniformly, the satellite data can be interpreted in terms of smoke plume evolution, including size-selective deposition, new-particle formation, and locations within the plume where BC or BrC dominates.

Noyes, Katherine Junghenn↗

DOE OSTI2026

Data from: "Towards CONUS-Wide ML-Augmented Conceptually-Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics"

This data package was generated to support the manuscript “Towards CONUS-Wide Machine Learning-Augmented Conceptually Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics.” It provides input files, model outputs, plotting data, scripts, notebooks, and documentation used to develop, evaluate, and reproduce Mass-Conserving Perceptron (MCP)-based hydrologic modeling experiments across 513 selected Catchment Attributes and Meteorology for Large-sample Studies in the United States (CAMELS-US) basins. The files are organized by modeling component and analysis purpose, including rainfall–runoff experiments, snow module experiments, coupled hydrologic-snow experiments, Long Short-Term Memory (LSTM) benchmark results, model skill metrics, initialization and epoch records, cell-state normalization files, Akaike Information Criterion (AIC)-based model comparison files, and data used to generate manuscript figures. Tabular files can be opened using standard spreadsheet software or Python/R data-analysis tools. Python scripts, Jupyter notebooks, and selected MATLAB scripts are included for model execution, postprocessing, plotting, and statistical analysis. Quality assurance and quality control were conducted through the source-data selection and modeling workflow. Meteorological forcing, streamflow, and static catchment attributes were derived from the CAMELS-US dataset, and snow water equivalent data were derived from the University of Arizona (UA) Snow Water Equivalent dataset. Selected basins and time periods were screened during the associated research workflow to avoid missing observations or poor-quality cases. Static geospatial features were processed primarily using Quantum Geographic Information System (QGIS) and Geospatial Data Abstraction Library (GDAL) workflows. Additional details are provided in the associated manuscript and documentation.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗

NASA NTRS2017

The 2013 FLEX-US Airborne Campaign at the Parker Tract Loblolly Pine Plantation in North Carolina, USA

The first European Space Agency (ESA) and NASA collaboration in an airborne campaign to support ESA's FLuorescence EXplorer (FLEX) mission was conducted in North Carolina, USA during September-October 2013 (FLEX-US 2013) at the Parker Tract Loblolly Pine (LP) Plantation (Plymouth, NC, USA). This campaign combined two unique airborne instrument packages to obtain simultaneous observations of solar-induced fluorescence (SIF), LiDAR-based canopy structural information, visible through shortwave infrared (VSWIR) reflectance spectra, and surface temperature, to advance vegetation studies of carbon cycle dynamics and ecosystem health. We obtained statistically significant results for fluorescence, canopy temperature, and tower fluxes from data collected at four times of day over two consecutive autumn days across an age class chronosequence. Both the red fluorescence (F685) and far-red fluorescence (F740) radiances had highest values at mid-day, but their fluorescence yields exhibited different diurnal responses across LP age classes. The diurnal trends for F685 varied with forest canopy temperature difference (canopy minus air), having a stronger daily amplitude change for young vs. old canopies. The Photochemical Reflectance Index (PRI) was positively correlated with this temperature variable over the diurnal cycle. Tower measurements from mature loblolly stand showed the red/far-red fluorescence ratio was linearly related to canopy light use efficiency (LUE) over the diurnal cycle, but performed even better for the combined morning/afternoon (without midday) observations. This study demonstrates the importance of diurnal observations for interpretation of fluorescence dynamics, the need for red fluorescence to understand canopy physiological processes, and the benefits of combining fluorescence, reflectance, and structure information to clarify canopy function versus structure characteristics for a coniferous forest.

chlorophyll fluorescence; diurnal responses; red S↗

DOE OSTI2026

Reassessing Hybrid Vigor or Hybrid Dysfunction Using Physiological Trade-Offs in an Endangered Salamander System

Fitness of interspecific hybrids can be higher or lower than that of their parental genotypes, with major ramifications for evolution and conservation. A recent study found that hybrid tiger salamanders had higher metabolic rates than their parental forms. Specifically, the ratio of resting metabolic rate to water loss, which was used as a measure of performance, was greater in hybrids. Recent genetic research showed that over half of the experimental subjects in that study were genetically pure California tiger salamanders (Ambystoma californiense) misclassified as hybrids. We reanalyzed the data using the corrected identification of hybrids and parentals. As expected, updating the classification revealed even stronger evidence for differences between hybrids and parentals. Hybrids had higher resting metabolic rates and greater water loss than parentals. The ratio of resting metabolic rate to water loss was also higher in hybrids. However, we suggest that this ratio might not be a positive measure of salamander performance. Higher metabolic rate means higher energy expenditure, and higher water loss suggests increased risk of desiccation. Both are major challenges for terrestrial amphibians, especially salamanders, which are hypothesized to be low-energy, low-water-loss specialists. Under this hypothesis, the ratio of energy expenditure to water loss is a ratio of two costs rather than a ratio of benefit to cost. While our analyses corroborate and strengthen the previous statistical results, we suggest that high resting metabolic rate is better interpreted as hybrid dysfunction, not vigor. Here, both hypotheses are speculative, and specific research on the fitness effects of these physiological differences is needed to resolve this important ecological question.

Ambystoma californiense↗

NASA NTRS2016

Polarbrdf: A General Purpose Python Package for Visualization Quantitative Analysis of Multi-Angular Remote Sensing Measurements

The Bidirectional Reflectance Distribution Function (BRDF) is a fundamental concept for characterizing the reflectance property of a surface, and helps in the analysis of remote sensing data from satellite, airborne and surface platforms. Multi-angular remote sensing measurements are required for the development and evaluation of BRDF models for improved characterization of surface properties. However, multi-angular data and the associated BRDF models are typically multidimensional involving multi-angular and multi-wavelength information. Effective visualization of such complex multidimensional measurements for different wavelength combinations is presently somewhat lacking in the literature, and could serve as a potentially useful research and teaching tool in aiding both interpretation and analysis of BRDF measurements. This article describes a newly developed software package in Python (PolarBRDF) to help visualize and analyze multi-angular data in polar and False Color Composite (FCC) forms. PolarBRDF also includes functionalities for computing important multi-angular reflectance/albedo parameters including spectral albedo, principal plane reflectance and spectral reflectance slope. Application of PolarBRDF is demonstrated using various case studies obtained from airborne multi-angular remote sensing measurements using NASA's Cloud Absorption Radiometer (CAR). Our visualization program also provides functionalities for untangling complex surface/atmosphere features embedded in pixel-based remote sensing measurements, such as the FCC imagery generation of BRDF measurements of grasslands in the presence of wild fire smoke and clouds. Furthermore, PolarBRDF also provides quantitative information of the angular distribution of scattered surface/atmosphere radiation, in the form of relevant BRDF variables such as sunglint, hotspot and scattering statistics.

CAR↗

NASA NTRS1973

Variations of the occurrence rate of discontinuities in the interplanetary magnetic field

A statistical study of magnetic field discontinuities for the interval from February to October 1968 using data from the NASA Goddard Space Flight Center/University of Rome experiment on Pioneer 8 has been conducted. High-resolution data (10-sec averages) have been employed, stringent criteria being utilized to select more than 16,000 events, about 50 per cent being identified as disturbances that are probably tangential discontinuities (TD). Near 1 AU the average occurrence rate of discontinuities is about 3.6/hr, whereas that of tangential-like discontinuities is about 1.6/hr. The rate of occurrence of discontinuities is found to be correlated with the directional change of the field across the discontinuity surface. The normal to the TD discontinuity plane is most often perpendicular to the Archimedean spiral field configuration. A decrease in the rate of occurrence of TD is found with increasing heliocentric distance and/or with decreasing heliocentric latitude. Possible interpretations of the effect are discussed.

Mariani, F.↗

NASA NTRS2005

Scanning Backscatter Lidar Observations for Characterizing 4-D Cloud and Aerosol Fields to Improve Radiative Transfer Parameterizations

Clouds have a powerful influence on atmospheric radiative transfer and hence are crucial to understanding and interpreting the exchange of radiation between the Earth's surface, the atmosphere, and space. Because clouds are highly variable in space, time and physical makeup, it is important to be able to observe them in three dimensions (3-D) with sufficient resolution that the data can be used to generate and validate parameterizations of cloud fields at the resolution scale of global climate models (GCMs). Simulation of photon transport in three dimensionally inhomogeneous cloud fields show that spatial inhomogeneities tend to decrease cloud reflection and absorption and increase direct and diffuse transmission, Therefore it is an important task to characterize cloud spatial structures in three dimensions on the scale of GCM grid elements. In order to validate cloud parameterizations that represent the ensemble, or mean and variance of cloud properties within a GCM grid element, measurements of the parameters must be obtained on a much finer scale so that the statistics on those measurements are truly representative. High spatial sampling resolution is required, on the order of 1 km or less. Since the radiation fields respond almost instantaneously to changes in the cloud field, and clouds changes occur on scales of seconds and less when viewed on scales of approximately 100m, the temporal resolution of cloud properties should be measured and characterized on second time scales. GCM time steps are typically on the order of an hour, but in order to obtain sufficient statistical representations of cloud properties in the parameterizations that are used as model inputs, averaged values of cloud properties should be calculated on time scales on the order of 10-100 s. The Holographic Airborne Rotating Lidar Instrument Experiment (HARLIE) provides exceptional temporal (100 ms) and spatial (30 m) resolution measurements of aerosol and cloud backscatter in three dimensions. HARLIE was used in a ground-based configuration in several recent field campaigns. Principal data products include aerosol backscatter profiles, boundary layer heights, entrainment zone thickness, cloud fraction as a function of altitude and horizontal wind vector profiles based on correlating the motions of clouds and aerosol structures across portions of the scan. Comparisons will be made between various cloud detecting instruments to develop a baseline performance metric.

Schwemmer, Geary K.↗

NASA NTRS2022

A Modular Framework for Integrating and Visualizing Telemetry for Mars 2020 Rover Mechanism Operations

The analysis of mechanism telemetry requires a wide variety of tools to quickly and effectively assess spacecraft state, capture long-term trends in system performance, and identify and track anomalous events. Such analysis often requires spacecraft telemetry to first be transformed into derived fields and aggregated statistics before operators can begin their analysis. In past missions, aspects of this process have been automated, but operators were expected to use their own tools and procedures to understand and visualize the data, which led to redundant and inconsistent tools and processes. The Mech Data Tools Python library (MDT) was developed to provide a flexible, unified tool set for operators to extract and analyze mechanism telemetry over the life of the Mars 2020 surface mission. MDT consists of a set of configurable components that implement standard interfaces for ingesting input and producing output. Components can be chained together to form a data processing pipeline. Data are ingested from several sources within the greater Mars 2020 cloud infrastructure and stored in pandas DataFrames, which allows users to leverage the data manipulation capabilities present within the widely-used pandas library. Visualization capabilities are provided through the Plotly library, which generates interactive plots for users to interpret. Following the beginning of Mars 2020 surface operations, usage of MDT has spread to all mechanism-focused subsystems and has demonstrated great utility in analyzing early surface activities. This paper describes MDT’s evolution from heritage mechanism telemetry tools, the critical architecture decisions and challenges faced over MDT’s two years of development, and current applications of MDT in support of mechanism operations.

Wolsieffer, Ben↗

NASA NTRS1994

Assessment of climate variability of the Greenland Ice Sheet: Integration of in situ and satellite data

The proposed research involves the application of multispectral satellite data in combination with ground truth measurements to monitor surface properties of the Greenland Ice Sheet which are essential for describing the energy and mass of the ice sheet. Several key components of the energy balance are parameterized using satellite data and in situ measurements. The analysis will be done for a ten year time period in order to get statistics on the seasonal and interannual variations of the surface processes and the climatology. Our goal is to investigate to what accuracy and over what geographic areas large scale snow properties and radiative fluxes can be derived based upon a combination of available remote sensing and meteorological data sets. Operational satellite sensors are calibrated based on ground measurements and atmospheric modeling prior to large scale analysis to ensure the quality of the satellite data. Further, several satellite sensors of different spatial and spectral resolution are intercompared to access the parameter accuracy. Proposed parameterization schemes to derive key component of the energy balance from satellite data are validated. For the understanding of the surface processes a field program was designed to collect information on spectral albedo, specular reflectance, soot content, grain size and the physical properties of different snow types. Further, the radiative and turbulent fluxes at the ice/snow surface are monitored for the parameterization and interpretation of the satellite data. The expected results include several baseline data sets of albedo, surface temperature, radiative fluxes, and different snow types of the entire Greenland Ice Sheet. These climatological data sets will be of potential use for climate sensitivity studies in the context of future climate change.

Steffen, K.↗

DOE OSTI2025

Predicting weather impacts on corn production in a data-limited region using a transfer learning approach

The stability of food supply and prices may depend more on annual changes in yields from year-to-year variability in weather than on longer-term average changes from changing climatic conditions. However, the absence of high-quality data on crop yields at fine spatial resolutions in many regions of the world makes it challenging to statistically model their response to interannual variability in weather patterns. Therefore, there is a need for empirical methods that can project annual crop yield changes even in limited data regions. Here, we propose a transfer learning algorithm that uses high spatial resolution data from one region to project yields in another region with more limited data. The goal of our work is to understand what data types can be beneficial for transferring learning from a source region to a very different target region with more limited data. We utilize Long Short-Term Memory to develop a transfer learning model that is trained on historical county-level corn yield in the United States and predicts district-level corn yield variations in India. Even using smaller amounts of data in India, simulating a data-scarce region, we achieve an average root mean square error of 0.48 bu acre−1 in predicting interannual yield variations. Using Shapley values to interpret results, we explore the contribution of the different weather parameters to interannual yield variability and find a larger influence of precipitation-related variables. Our study demonstrates the usefulness of this method for transferring models of weather impacts on crop yields trained on a data-rich country to one with more limited data. It suggests the potential of applying the transfer learning model to mitigate the need for extensive raw data globally.

Vishwakarma, Srishti [ORNL] (ORCID:000000031674419↗

DOE OSTI2025

Discovery and Spectroscopic Confirmation of Aquarius III: A Low-mass Milky Way Satellite Galaxy

Abstract We present the discovery of Aquarius III, an ultra-faint Milky Way satellite galaxy identified in the second data release of the DECam Local Volume Exploration survey. Based on deeper follow-up imaging with DECam, we find that Aquarius III is a low-luminosity ( M V = − 2.5 − 0.5 + 0.3 ; L V = 850 − 260 + 380 L ⊙ ), extended ( r 1 / 2 = 41 − 8 + 9 pc) stellar system located in the outer halo ( D ⊙ = 85 ± 4 kpc). From medium-resolution Keck/DEIMOS spectroscopy, we identify 11 member stars and measure a mean heliocentric radial velocity of v sys = − 13.1 − 0.9 + 1.0 km s − 1 for the system and place an upper limit of σ v < 3.5 km s −1 ( σ v < 1.6 km s −1 ) on its velocity dispersion at the 95% (68%) credible level. Based on calcium-triplet metallicities of the six brightest red giant members, we find that Aquarius III is very metal-poor ([Fe/H]= − 2.61 ± 0.21) with a statistically significant metallicity spread ( σ [ Fe / H ] = 0.46 − 0.14 + 0.26 dex). We interpret this metallicity spread as strong evidence that the system is a dwarf galaxy as opposed to a star cluster. Combining our velocity measurement with Gaia proper motions, we find that Aquarius III is currently situated near its orbital pericenter in the outer halo ( r peri = 78 ± 7 kpc) and that it is plausibly on first infall onto the Milky Way. This orbital history likely precludes significant tidal disruption from the Galactic disk, notably unlike other satellites with comparably low velocity dispersion limits in the literature. Thus, if further velocity measurements confirm that its velocity dispersion is truly below σ v ≲ 2 km s −1 , Aquarius III may serve as a useful laboratory for probing galaxy formation physics in low-mass halos.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2014

The Bombardment History of 4 Vesta as Told by Sample Geochronology

The Dawn mission showed asteroid 4 Vesta to be an extensively cratered body, ancient in age, with craters in a variety of morphologies and preservation states [1-3]. Tying Vesta's relative crater ages to an absolute impact history can be accomplished through investigations of the HED (howardite, eucrite, diogenite) meteorites. Eucrites are crustal basalts and gabbros, diogenites are mostly orthopyroxenites representing lower crust or upper mantle materials, and howardites are mixed breccias containing both lithologies. Eucrite 53Mn-53Cr systematics show that the HED parent body globally differentiated by ~4.56 Ga and fully crystallized soon afterwards [4]. Much later, many eucrites were brecciated and heated by large impacts into the parent body surface. Disturbance ages in eucrites show that multiple large impacts occurred within 1 Gyr after crystallization, showing a history that largely resembles that of the Moon [5-7]. Dawn images also showed that Vesta is covered with a well-developed regolith that is spectrally similar to howardite meteorites [8]. Howardites are polymict regolith breccias made up mostly of clasts of eucrites and diogenites, but which also contain clasts formed by melting of the regolith by relatively large, energetic impact events. Impact-melt clast ages from howardites extend our knowledge of the impact history of Vesta, expanding on eucrite disturbance ages and helping give absolute age context to the observed crater-counts produced using Dawn data. The distribution of 40Ar-39Ar ages of impact-melt clasts in howardites shows that they formed within the time period 3.3-3.8 Ga [9]. These, and other impact-melted HED materials, have distinct age and compositional characteristics that suggest they formed in discrete impact events. In order to create these crystalline impact-melt products on the surface of Vesta, the impacts during this time period must have had velocities much higher than 5 km/s, the main belt average [10]. This is inconsistent with formation by a normal distribution of impact velocities and points instead to a unique period where high-velocity collisions were more frequent than currently observed. Until now, impact-reset ages in the HED meteorites have been be interpreted under the umbrella of the canonical lunar cataclysm where an increase in the absolute number of bombarding objects is responsible for creating larger absolute amounts of impact-affected and impact-melted rocks, statistically increasing their chances of being found on Earth and dated. However, the distribution of age among the howardite impact-melt clasts may not necessarily result from an increased number of impacts, but rather result from impacts of higher velocity. The changeover from a typical main belt velocity profile to this regime of increased velocity population at Vesta occurs contemporaneously with a similar transition at the Moon, indicating that howardite impact-melt clast ages reinforce the notion of a dynamically unusual episode of bombardment in the inner solar system beginning at around 4.0 Ga.

Cohen, B. A.↗

NASA NTRS2013

Downscaling Satellite Precipitation with Emphasis on Extremes: A Variational 1-Norm Regularization in the Derivative Domain

The increasing availability of precipitation observations from space, e.g., from the Tropical Rainfall Measuring Mission (TRMM) and the forthcoming Global Precipitation Measuring (GPM) Mission, has fueled renewed interest in developing frameworks for downscaling and multi-sensor data fusion that can handle large data sets in computationally efficient ways while optimally reproducing desired properties of the underlying rainfall fields. Of special interest is the reproduction of extreme precipitation intensities and gradients, as these are directly relevant to hazard prediction. In this paper, we present a new formalism for downscaling satellite precipitation observations, which explicitly allows for the preservation of some key geometrical and statistical properties of spatial precipitation. These include sharp intensity gradients (due to high-intensity regions embedded within lower-intensity areas), coherent spatial structures (due to regions of slowly varying rainfall),and thicker-than-Gaussian tails of precipitation gradients and intensities. Specifically, we pose the downscaling problem as a discrete inverse problem and solve it via a regularized variational approach (variational downscaling) where the regularization term is selected to impose the desired smoothness in the solution while allowing for some steep gradients(called 1-norm or total variation regularization). We demonstrate the duality between this geometrically inspired solution and its Bayesian statistical interpretation, which is equivalent to assuming a Laplace prior distribution for the precipitation intensities in the derivative (wavelet) space. When the observation operator is not known, we discuss the effect of its misspecification and explore a previously proposed dictionary-based sparse inverse downscaling methodology to indirectly learn the observation operator from a database of coincidental high- and low-resolution observations. The proposed method and ideas are illustrated in case studies featuring the downscaling of a hurricane precipitation field.

Hurricanes↗

DOE OSTI2024

Study of e + e − → π + π − π 0 at s from 2.00 to 3.08 GeV at BESIII

With the data samples taken at center-of-mass energies from 2.00 to 3.08 GeV with the BESIII detector at the BEPCII collider, a partial wave analysis on the e + e − → π + π − π 0 process is performed. The Born cross sections for e + e − → π + π − π 0 and its intermediate processes e + e − → ρ π and ρ ( 1450 ) π are measured as functions of s . The results for e + e − → π + π − π 0 are consistent with previous results measured with the initial state radiation method within one standard deviation, and improve the uncertainty by a factor of ten. By fitting the line shapes of the Born cross sections for the e + e − → ρ π and e + e − → ρ ( 1450 ) π , a structure with mass M = 2119 ± 11 ± 15 MeV / c 2 and width Γ = 69 ± 30 ± 5 MeV is observed with a significance of 5.9 σ , where the first uncertainties are statistical and the second ones are systematic. This structure can be interpreted as an excited ω state. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

NASA NTRS1999

X-Ray Diffraction Techniques for a Field Instrument: Patterns of Lithologic Provences

Future exploration of Mars will attempt to shed light on the mineralogy of surface materials. Instruments deployed from remote platforms should have the capability to conduct both intensive analyses as well as rapid, reconnaissance surveys while they function in the martian environment as surrogate geologists. In order to accommodate the reconnaissance mode of analysis and to compensate for analytical limitations imposed by the space-flight conditions, data analysis methods are being developed that will permit interpretation of data by recognition of signatures or "fingerprints". Specifically, we are developing a technique which will allow interpretation of diffraction patterns by recognition of characteristic signatures of different lithologic provences. This technique allows a remote vehicle to function in a rapid-scan mode using the lithologic signature to determine where a more thorough analysis is needed. An x-ray diffraction pattern is characterized by the angular positions of diffracted x-rays, x-ray intensity levels and background radiation levels. These elements may be used to identify a generalized x-ray signature. Lithologic signatures are being developed in two ways. A signature is composed using the ideal powder diffraction indices from the mineral assembledge common to a specific lithologic provence. This is then confirmed using a laboratory diffraction pattern of a whole rock powder. Preliminary results comparing the diffraction signatures of the major mineral assembledges common to basalt, carbonate, and evaporite basin deposits indicate that lithologies are differentiable as a "fingerprint". Statistical analyses are being performed to establish the confidence levels of this technique.

Marshall, J.↗

NASA NTRS1997

A Statistical Study of the Global Structure of the Ring Current

In this paper we derive the average configuration of the ring current as a function of the state of the magnetosphere as indicated by the Dst index. We sort magnetic field data from the Combined Release and Radiation Effects Satellite (CRRES) by spatial location and by the Dst index in order to produce magnetic field maps. From these maps we calculate local current systems by taking the curl of the magnetic field. NN7e find both the westward (outer) and the eastward (inner) components of the ring current. We find that the ring current intensity varies linearly with D.St as expected, and that the ring current is asymmetric for all Dst values. The azimuthal peak of the ring current is located in the afternoon sector for quiet conditions, and near midnight for disturbed conditions. The ring current also moves closer to the Earth during disturbed conditions. We are able to recreate the Dst index by integrating the magnetic perturbations caused by the ring current. We find that we needed to apply a 20 nT offset to Dst, and assume a perfectly conducting Earth to obtain an optimal agreement between the computed and the observed Dst. We interpret the 20 nT offset as the magnetic field generated by the quiet time ring current used as baseline in computing Dst.

Jorgensen, A. M.↗

DOE OSTI2026

Historic climate, cosmogenic 10Be, denudation-rate, and geospatial datasets from the Pikes Peak region, Colorado, USA

This data package contains geographic information system (GIS) layers and tabular datasets associated with the study of elevation-dependent denudation rates on Pikes Peak in the Front Range of the Rocky Mountains, Colorado, USA. The package includes GIS layers used to produce the study-area map, including sample locations, sample watershed boundaries, the Pikes Peak batholith, Pleistocene glacier extent, weather station locations, and elevation and hillshade rasters, together with comma-separated value (CSV) tables and matching CSV data dictionaries. These mapped layers provide the geographic framework for interpreting denudation patterns across the Pikes Peak region and for relating sample locations to watershed geometry, bedrock setting, glacial history, and nearby climate stations. The first group of tables reports climate and geospatial context for the study area. These files include station-based temperature and precipitation data used to characterize elevational gradients in mean annual climate and monthly climate seasonality, sample locations, denudation-rate and topographic metrics, fixed frost-cracking model parameters, frost-cracking intensity and precipitation-frequency metrics, and stream-power inversion results. Together, these data provide the basis for evaluating how denudation varies with elevation, climate, and landscape form across sampled catchments on Pikes Peak. The second group of tables reports cosmogenic nuclide and erosion-model results used in the denudation analysis. Included files contain accelerator mass spectrometry (AMS) measurements for in situ-produced cosmogenic beryllium-10 (10Be), including sample identifiers, measured 10Be:9Be ratios, analytical uncertainties, carrier mass, quartz mass, blank corrections, blank-group statistics, and calculated 10Be concentrations and uncertainties. Additional tables summarize stream-power-law inversion results for sampled catchments, including optimized model parameters, predicted erosion rates, residual metrics, channel-pixel counts, and convergence status, as well as regression equations and summary statistics used to evaluate relationships among elevation, climate, frost cracking, precipitation forcing, and denudation rate. The package contains GIS files, comma-separated value files (.csv), Microsoft Excel files (.xlsx), CSV data dictionaries, a file-level metadata table, and a readme text file.

10Be cosmogenic nuclides↗

NASA NTRS2011

The RHESSI Microflare Height Distribution

We present the first in-depth statistical survey of flare source heights observed by RHESSI. Flares were found using a flare-finding algorithm designed to search the 6-10 keV count-rate when RHESSI's full sensitivity was available in order to find the smallest events (Christe et al., 2008). Between March 2002 and March 2007, a total of 25,006 events were found. Source locations were determined in the 4-10 keV, 10-15 keV, and 15-30 keV energy ranges for each event. In order to extract the height distribution from the observed projected source positions, a forward-fit model was developed with an assumed source height distribution where height is measured from the photosphere. We find that the best flare height distribution is given by g (h) oc exp(-h/lambda) where lambda = 6.1 plus or minus 0.3 Mm is the scale height. A power law height distribution with a negative power law index, gamma = 3.1 plus or minus 0.3 is also consistent with the data. Interpreted as thermal loop top sources, these heights are compared to loops generated by a potential field model (PFSS). The measured flare heights distribution are found to be much steeper than the potential field loop height distribution which may be a signature of the flare energization process.

Christe, P.↗