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At least 271 records · Page 15

Automated Grouping of Opportunity Rover Alpha Particle X-Ray Spectrometer Compositional Data

The Alpha Particle X-ray Spectrometer (APXS) conducts high-precision in situ measurements of rocks and soils on both active NASA Mars rovers. Since 2004 the rover Opportunity has acquired around 440 unique APXS measurements, including a wide variety of compositions, during its 42+ kilometers traverse across several geological formations. Here we discuss an analytical comparison algorithm providing a means to cluster samples due to compositional similarity and the resulting automated classification scheme. Due to the inherent variance of elements in the APXS data set, each element has an associated weight that is inversely proportional to the variance. Thus, the more consistent the abundance of an element in the data set, the more it contributes to the classification. All 16 elements standard to the APXS data set are considered. Careful attention is also given to the errors associated with the composition measured by the APXS - larger uncertainties reduce the weighting of the element accordingly. The comparison of two targets, i and j, generates a similarity score, S(sub ij). This score is immediately comparable to an average ratio across all elements if one assumes standard weighted uncertainty. The algorithm facilitates the classification of APXS targets by chemistry alone - independent of target appearance and geological context which can be added later as a consistency check. For the N targets considered, a N by N hollow matrix, S, is generated where S = S(sup T). The average relation score, S(sub av), for target N(sub i) is simply the average of column i of S. A large S(sub av) is indicative of a unique sample. In such an instance any targets with a low comparison score can be classified alike. The threshold between classes requires careful consideration. Applying the algorithm to recent Marathon Valley targets indicates similarities with Burns formation and average-Mars-like rocks encountered earlier at Endeavour Crater as well as a new class of felsic rocks.

VanBommel, S. J.↗

Scale Dependence of Cirrus Horizontal Heterogeneity Effects on TOA Measurements: MODIS Brightness Temperatures in the Thermal Infrared - Part I

This paper presents a study on the impact of cirrus cloud heterogeneities on MODIS simulated thermal infrared (TIR) brightness temperatures (BTs) at the top of the atmosphere (TOA) as a function of spatial resolution from 50 meters to 10 kilometers. A realistic 3-D (three-dimensional) cirrus field is generated by the 3DCLOUD model (average optical thickness of 1.4, cloudtop and base altitudes at 10 and 12 kilometers, respectively, consisting of aggregate column crystals of D (sub eff) equals 20 microns), and 3-D thermal infrared radiative transfer (RT) is simulated with the 3DMCPOL (3-D Monte Carlo Polarized) code. According to previous studies, differences between 3-D BT computed from a heterogenous pixel and 1-D (one-dimensional) RT computed from a homogeneous pixel are considered dependent at nadir on two effects: (i) the optical thickness horizontal heterogeneity leading to the plane-parallel homogeneous bias (PPHB); and the (ii) horizontal radiative transport (HRT) leading to the independent pixel approximation error (IPAE). A single but realistic cirrus case is simulated and, as expected, the PPHB mainly impacts the low-spatial resolution results (above approximately 250 meters), with averaged values of up to 5-7 K (thousand), while the IPAE mainly impacts the high-spatial resolution results (below approximately 250 meters) with average values of up to 1-2 K (thousand). A sensitivity study has been performed in order to extend these results to various cirrus optical thicknesses and heterogeneities by sampling the cirrus in several ranges of parameters. For four optical thickness classes and four optical heterogeneity classes, we have found that, for nadir observations, the spatial resolution at which the combination of PPHB and HRT effects is the smallest, falls between 100 and 250 meters. These spatial resolutions thus appear to be the best choice to retrieve cirrus optical properties with the smallest cloud heterogeneity-related total bias in the thermal infrared. For off-nadir observations, the average total effect is increased and the minimum is shifted to coarser spatial resolutions.

TOA↗

Sensitivity Analysis of Drivers Water Shortage in the Los Angeles Region During Drought

The code and detailed step-by-step instructions for generating the model output data, processing results, and analysis and plotting are provided at https://github.com/IMMM-SFA/Ferencz_et_al_2026_ER_Water. The PyArtes model is a python adaptation of the Artes model. PyArtes uses many of the same input data and optimization model architecture as Artes. Documentation for the PyArtes model is provided in the Supplement to the paper. The primary data product are simulated monthly water shortages for indoor and outdoor demand under a large ensemble of drought scenarios (>13,000). The droughts are hypothetical and are not based on historical time series data of supply sources - though historical data did help inform ranges explored for supply parameters. Demands are informed by recent 2017-2021 water supply data. Demands used for the model can be accessed at https://github.com/IMMM-SFA/Ferencz_et_al_2026_ER_Water. Simulations resolve demand for over 90 water providers in the study region. The results report 36 months of water shortage data for each indoor and outdoor demand node. The study also developed a multilayer perceptron (MLP) neural network trained on a subset of the simulated shortage ensemble to emulate worst annual water shortage for a given set of parameter multipliers -- provided the parameter values fall within the ranges sampled in the ensemble. Emulated water shortages for synthetic ensembles are in the MLP-generated shortages folder. The MLP model was used to generate larger ensembles to support Sobol analysis that would have been extremely computationally expensive to simulate. Datasets provided in this repository*: Simulated shortages. These results are used for the analysis for Figures 5, 8, and 9 in the paper, and also to train the MLP emulator. .zip file containing outputs for the 13,312 scenario ensemble. Separate .csv files for indoor and outdoor shortage for each scenario. Rows = demand ids (~100), Columns = months (36) Units = acre-feet/month of shortage (shortage = monthly demand - supply). 1 acft = 1233.48 m^3 .csv files of aggregated shortages derived from the 13,312 ensemble Rows = scenarios (13,312), Columns = demand ids (~100) Units = acre-feet/year (either worst annual shortage or total shortage over the 3-year drought) .csv file of the parameter multipliers scenarios for the ensemble .csv file of the parameter ranges and baseline values the multipliers were applied to MLP-generated shortages. These results are used for Figures 4, 6, and 7 in the paper. mwd higher folder: scenario ensembles, emulated worst year total shortages (acft), and Sobol results Emulated shortages. Rows = scenarios, columns = demand ids, units acft Sobol results. Rows = demand ids, columns Sobol (S1, ST, or 95% confidence interval) value for each parameter mwd lower folder: scenario ensembles, emulated worst year total shortages (acft), and Sobol results same organization as mwd higher MLP performance: performance metrics (R^2, RMSE, BIAS, MAPE) for the testing subset (20% or 2,662 scenarios) and simulated vs emulated worst year shortage (acre-feet/year) for every demand node, MWD wholesale regions, and the entire study region (LAC). Supporting data for figures. Figure plotting scripts in the associated GitHub repo. These files support analysis and visualization. Geospatial Data used for plotting simulated water shortages and Sobol results. Dictionary of full names for demand nodes in the model and estimates of water supply by source type informed by Artes input files and California Urban Water Management Planning data: https://water.ca.gov/Programs/Water-Use-And-Efficiency/Urban-Water-Use-Efficiency/Urban-Water-Management-Plans *Readme files provided for each folder.

drought↗

Bipartisan Infrastructure Law (BIL) – Illinois Rare Earth Novel Extraction and Supply (IRENES) - Report on Technology Down Select No. 1 - Acid Baking vs. Heap Leaching

An essential step for recovering rare earth and critical minerals from coal mine waste is one that achieves adequate dissolution of the target elements into a pregnant leachate solution. The simplest technical approach was thought to be heap-leaching that could proceed using mild acid dosing or naturally generated acid from biological activity. For this reason, the University of Kentucky at Lexington (UKY) undertook two efforts to evaluate feasibility, including a laboratory column leaching evaluation and a pilot heap-leaching demonstration. Later, the UK evaluated a pyrometallurgical approach using roasting combined with acid baking and tank leaching at elevated temperatures to improve extraction efficiencies. This report surveys the previously reported leaching yields and calculates the gross value of rare earth oxides as a basket in the pregnant leachate solution.

01 COAL, LIGNITE, AND PEAT↗

Nature of the gases released from lunar rocks and soils upon crushing

Qualitative and quantitative analyses of inorganic gases released from lunar basalts, breccias and soils by crushing have been performed in an apparatus which consists of a piston operating in a stream of purified He and a dual-column gas chromatograph equipped with He-ionization detectors. The apparatus eliminates the problem of adsorption of the released gases by fresh sample surfaces generated by crushing. Upper concentration levels for nitrogen, H2, CH4, O2 and other gases released from crushed basalts are reported. A direct correlation is established between the amount of nitrogen released from lunar soils by crushing and the lunar soil maturity indicator proposed by Morris (1976).

Gibson, E. K., Jr.↗

Technologies for antenna shape and vibration control

This paper describes the application of advanced control methods and techniques to the second- and third-generation mobile satellite (MSAT) configurations having wrap-rib offset feed construction. The technologies are generically applicable to other designs such as hoop-column and other elastically deformable non-rigid structures. The focus of the discussion is on reflector shape determination and control, dynamics identification, and pointing jitter suppression.

Mettler, Edward↗

Stable isotopic biogeochemistry of carbon and nitrogen in a perennially ice-covered Antarctic lake

Lake Hoare (77 degrees 38' S, 162 degrees 53' E) is an amictic, oligotrophic, 34-m-deep, closed-basin lake in Taylor Valley, Antarctica. Its perennial ice cover minimizes wind-generated currents and reduces light penetration, as well as restricts sediment deposition into the lake and the exchange of atmospheric gases between the water column and the atmosphere. The biological community of Lake Hoare consists solely of microorganisms -- both planktonic populations and benthic microbial mats. Lake Hoare is one of several perennially ice-covered lakes in the McMurdo Dry Valleys that represent the end-member conditions of cold desert and saline lakes. The dry valley lakes provide a unique opportunity to examine lacustrine processes that operate at all latitudes, but under an extreme set of environmental conditions. The dry valley lakes may also offer a valuable record of catchment and global changes in the past and present. Furthermore, these lakes are modern-day equivalents of periglacial lakes that are likely to have been common during periods of glacial maxima at temperate latitudes. We have analyzed the dissolved inorganic carbon (DIC) of Lake Hoare for delta 13C and the organic matter of the sediments and sediment-trap material for delta 13C and delta 15N. The delta 13C of the DIC indicates that 12C is differentially removed in the shallow, oxic portions of the lake via photosynthesis. In the anoxic portions of the lake (27-34 m) a net addition of 12C to the DIC pool occurs via organic matter decomposition. The dissolution of CaCO3 at depth also contributes to the DIC pool. Except near the Canada Glacier where a substantial amount of allochthonous organic matter enters the lake, the organic carbon being deposited on the lake bottom at different sites is isotopically similar, suggesting an autochthonous source for the organic carbon. Preliminary inorganic carbon flux calculations suggest that a high percentage of the organic carbon fixed in the water column is remineralized as it falls through the water column. At nearby Lake Fryxell, the substantial (relative to Lake Hoare) glacial meltstream input overprints Fryxell's shallow-water biological delta 13C signal with delta 13C-depleted DIC. In contrast, Lake Hoare is not significantly affected by surface-water input and mixing, and therefore the delta 13C patterns observed arise primarily from biological dynamics within the lake. Organic matter in Lake Hoare is depleted in 15N, which we suggest is partially the result of the addition of relatively light inorganic nitrogen into the lake system from terrestrial sources.

NASA Program Exobiology↗

Paleolimnology of the McMurdo Dry Valleys, Antarctica

The McMurdo Dry Valleys presently contain more than 20 permanent lakes and ponds, which vary markedly in character. All, with the exception of a hypersaline pond, have a perennial ice-cover. The dry valley lakes, and lakes in other ice-free regions of continental Antarctica, are unique on this planet in that they consistently maintain a thick year-round ice cover (2.8-6.0 m) over liquid water. The persistent ice covers minimize wind-generated currents and reduce light penetration, as well as restricting sediment deposition into a lake and the exchange of atmospheric gases between the water column and the atmosphere. From a paleolimnological perspective, the dry valley lakes offer an important record of catchment and environmental changes. These lakes are also modern-day equivalents of periglacial lakes that were common during glacial periods at temperate latitudes. The present lakes are mostly remnants of larger glacial lakes that occupied the valleys in the past, perhaps up to 4.6 Ma ago. Two of the valleys contain evidence of being filled with large glacial lakes within the last 10000 years. Repeated drying and filling events since then have left a characteristic impression on the salt profiles of some lakes creating a unique paleo-indicator within the water column. These events are also marked in the sediments by the concentration and dilution of certain chemical constituents, particularly salts, and are also corroborated by carbonate speciation and oxygen isotope analysis. Stratigraphic analysis of dry valley lake sediments is made difficult by the occurrence of an 'old carbon' reservoir creating spurious radiocarbon dates, and by the high degree of spatial variability in lake sedimentation. From a biological perspective, the lakes are relatively simple, containing various taxa of planktonic and benthic microorganisms, but no higher forms of life, which is an advantage to paleolimnologists because there is no bioturbation in the sediments. Useful biological paleo-indicators found in the sediments include cyanobacterial filament sheaths, diatom frustules and other eukaryotic algal cells, protozoan cysts, photosynthetic pigments, and minerals (e.g. carbonates) associated with microbial activity. Future work will benefit from fully characterizing the connection between the ice covers, environmental conditions, and paleo-indicators, thereby allowing refinement of inferences made concerning the paleoenvironment. New dating techniques need to be tested in this environment to overcome the problems associated with radiocarbon dating. The establishment of a detailed and focused paleolimnological campaign is proposed.

Non-NASA Center↗

Short-range precipitation forecasts using assimilation of simulated satellite water vapor profiles and column cloud liquid water amounts

These observing system simulation experiments investigate the assimilation of satellite-observed water vapor and cloud liquid water data in the initialization of a limited-area primitive equations model with the goal of improving short-range precipitation forecasts. The assimilation procedure presented includes two aspects: specification of an initial cloud liquid water vertical distribution and diabatic initialization. The satellite data is simulated for the next generation of polar-orbiting satellite instruments, the Advanced Microwave Sounding Unit (AMSU) and the High-Resolution Infrared Sounder (HIRS), which are scheduled to be launched on the NOAA-K satellite in the mid-1990s. Based on cloud-top height and total column cloud liquid water amounts simulated for satellite data a diagnostic method is used to specify an initial cloud water vertical distribution and to modify the initial moisture distribution in cloudy areas. Using a diabatic initialization procedure, the associated latent heating profiles are directly assimilated into the numerical model. The initial heating is estimated by time averaging the latent heat release from convective and large-scale condensation during the early forecast stage after insertion of satellite-observed temperature, water vapor, and cloud water formation. The assimilation of satellite-observed moisture and cloud water, together withy three-mode diabatic initialization, significantly alleviates the model precipitation spinup problem, especially in the first 3 h of the forecast. Experimental forecasts indicate that the impact of satellite-observed temperature and water vapor profiles and cloud water alone in the initialization procedure shortens the spinup time for precipitation rates by 1-2 h and for regeneration of the areal coverage by 3 h. The diabatic initialization further reduces the precipitation spinup time (compared to adiabatic initialization) by 1 h.

Wu, Xiaohua↗

Ice Nucleation in Deep Convection

The processes controlling production of ice crystals in deep, rapidly ascending convective columns are poorly understood due to the difficulties involved with either modeling or in situ sampling of these violent clouds. A large number of ice crystals are no doubt generated when droplets freeze at about -40 C. However, at higher levels, these crystals are likely depleted due to precipitation and detrainment. As the ice surface area decreases, the relative humidity can increase well above ice saturation, resulting in bursts of ice nucleation. We will present simulations of these processes using a large-eddy simulation model with detailed microphysics. Size bins are included for aerosols, liquid droplets, ice crystals, and mixed-phase (ice/liquid) hydrometers. Microphysical processes simulated include droplet activation, freezing, melting, homogeneous freezing of sulfate aerosols, and heterogeneous ice nucleation. We are focusing on the importance of ice nucleation events in the upper part of the cloud at temperatures below -40 C. We will show that the ultimate evolution of the cloud in this region (and the anvil produced by the convection) is sensitive to these ice nucleation events, and hence to the composition of upper tropospheric aerosols that get entrained into the convective column.

Jensen, Eric↗

PDF Entity Annotation Tool (PEAT)

While different text mining approaches – including the use of Artificial Intelligence (AI) and other machine based methods - continue to expand at a rapid pace, the tools used by researchers to create the labeled datasets required for training, modeling, and evaluation remain rudimentary. Labeled datasets contain the target attributes the machine is going to learn; for example, training an algorithm to delineate between images of a car or truck would generally require a set of images with a quantitative description of the underlying features of each vehicle type. Development of labeled textual data that can be used to build natural language machine learning models for scientific literature is not currently integrated into existing manual workflows used by domain experts. Published literature is rich with important information, such as different types of embedded text, plots, and tables that can all be used as inputs to train ML/natural language processing (NLP) models, when extracted and prepared in machine readable formats. Currently, both normalized data extraction of use to domain experts and extraction to support development of ML/NLP models are labor intensive and cumbersome manual processes. Automatic extraction of data and information from formats such as PDFs that are optimized for layout and human readability, not machine readability. The PDF (Portable Document Format) Entity Annotation Tool (PEAT) was developed with the goal of allowing users to annotate publications within their current print format, while also allowing those annotations to be captured in a machine-readable format. One of the main issues with traditional annotation tools is that they require transforming the PDF into plain text to facilitate the annotation process. While doing so lessens the technical challenges of annotating data, the user loses all structure and provenance that was inherent in the underlying PDF. Also, textual data extraction from PDFs can be an error prone process. Challenges include identifying sequential blocks of text and a multitude of document formats (multiple columns, font encodings, etc.). As a result of these challenges, using existing tools for development of NLP/ML models directly from PDFs is difficult because the generated outputs are not interoperable. We created a system that allows annotations to be completed on the original PDF document structure, with no plain text extraction. The result is an application that allows for easier and more accurate annotations. In addition, by including a feature that grants the user the ability to easily create a schema, we have developed a system that can be used to annotate text for different domain-centric schemas of relevance to subject matter experts. Different knowledge domains require distinct schemas and annotation tags to support machine learning.

97 MATHEMATICS AND COMPUTING↗

Integrating Reanalysis and Satellite Cloud Information to Estimate Surface Downward Long-Wave Radiation

The estimation of downward long-wave radiation (DLR) at the surface is very important for the understanding of the Earth’s radiative budget with implications in surface–atmosphere exchanges, climate variability, and global warming. Theoretical radiative transfer and observationally based studies identify the crucial role of clouds in modulating the temporal and spatial variability of DLR. In this study, a new machine learning algorithm that uses multivariate adaptive regression splines (MARS) and the combination of near-surface meteorological data with satellite cloud information is proposed. The new algorithm is compared with the current operational formulation used by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Land Surface Analysis (LSA-SAF). Both algorithms use near-surface temperature and dewpoint temperature along with total column water vapor from the latest European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis ERA5 and satellite cloud information from the Meteosat Second Generation. The algorithms are trained and validated using both ECMWF-ERA5 and DLR acquired from 23 ground stations as part of the Baseline Surface Radiation Network (BSRN) and the Atmospheric Radiation Measurement (ARM) user facility. Results show that the MARS algorithm generally improves DLR estimation in comparison with other model estimates, particularly when trained with observations. When considering all the validation data, root mean square errors (RMSEs) of 18.76, 23.55, and 22.08 W·m –2 are obtained for MARS, operational LSA-SAF, and ERA5, respectively. The added value of using the satellite cloud information is accessed by comparing with estimates driven by ERA5 total cloud cover, showing an increase of 17% of the RMSE. The consistency of MARS estimate is also tested against an independent dataset of 52 ground stations (from FLUXNET2015), further supporting the good performance of the proposed model.

54 ENVIRONMENTAL SCIENCES↗

Solidus and liquidus temperatures and mineralogies for anhydrous garnet-lherzolite to 15 GPa

Strong convergence is noted, in experimental data for systems pertaining to anhydrous fertile garnet-lherzolite in the 6.5-15 GPa range, either to a common temperature or to temperatures differing by only about 100 C. The major element composition of magmas generated by even minor degrees of partial melting may be similar to the composition of the primordial, bulk silicate earth in an upper mantle stratigraphic column more than 160 km deep. Whether or not the solidus and liquidus intersect, the liquidus mineralogy for undepleted garnet-lherzolite compositions is found to change from olivine, at low pressures, to pyroxene, garnet, or a solid solution of both, at pressures greater than 10-15 GPa.

Herzberg, C. T.↗

ROTA-CAP™: An Intensified Carbon Capture System Using Rotating Packed Beds (Final Scientific/Technical Report)

GTI Energy and Carbon Clean Solutions Limited successfully designed, constructed, and operated an integrated ROTA-CAP carbon capture skid. ROTA-CAP™ is a process intensification technology, applied for post-combustion carbon capture, which utilizes the centrifugal forces generated from rotation of rotating packed beds as well as advanced solvents to achieve increased mass transfer rates 1-2 orders of magnitude higher than conventional columns while substantially decreasing footprint. The test skid, which consisted of a dual stage RPB absorber with external interstage cooling and a single stage RPB regenerator, was operated at capacities up to 0.5 tonne/day of CO 2 capture with flue gas concentrations ranging from 4% to 22% CO 2 by vol. CO 2 removal rates greater than 95% were achieved, with CO 2 product purity also exceeding 95% by vol. Over 1,600 hours of operation were accumulated throughout the project, including over 1,000 hours of operation of the with real flue gas containing at least 9.8% CO 2 by vol. The skid was operated continuously for 24 hours per day and 7 days per week over the course of 7 long-term test campaigns, with the campaigns ranging from approximately 2-4 weeks per campaign. A techno-economic analysis was performed, and a cost of capture of $\$$41.18/tonne CO 2 was calculated for the ROTA-CAP process, compared to $\$$45.75/tonne for a Cansolv-based process. These results show a cost reduction of approximately 10% compared to the Cansolv-based process. Although this still exceeds the target cost of capture of $\$$30/tonne specified for this project, GTI expects that the cost of capture can be further reduced through further optimization of the design and technology. GTI also performed an engineering design review to determine the scale-up potential of the technology, with the results of the preliminary assessment indicating that it appears to be feasible to scale up the RPB technology to 4,000 TPD. It was also determined that both horizontal and vertical rotor orientations are feasible, though there are mechanical advantages to the vertical orientation.

20 FOSSIL-FUELED POWER PLANTS↗

Aprendizaje vertical

In the teaching and learning events of our life, there are characters who play key roles. Teachers, mentors, relatives, novels, songs, newspaper columns, often help us understand the questions in our heads. However, we often reject them because they are messages or attitudes from older people and the generation gap does not allow us to understand them well. The times of covid-19 have us locked up at home. They alert us that precisely “elderly people” are a vulnerable group. Also, we have been asked to take care of grandparents. If we are lucky enough to have an internet connection, it seems that we can learn anything we want with just one click. This could lead us to explore only what we find attractive, easy and comfortable. With this testimony, I invite you to acknowledge on the role of the elderly in the learning of entire generations. I call for openness towards diverse voices and for the understanding that we all play a role in moving towards a more mature society.

99 GENERAL AND MISCELLANEOUS↗

MPL-Net Measurements of Aerosol and Cloud Vertical Distributions at Co-Located AERONET Sites

In the early 1990s, the first small, eye-safe, and autonomous lidar system was developed, the Micropulse Lidar (MPL). The MPL acquires signal profiles of backscattered laser light from aerosols and clouds. The signals are analyzed to yield multiple layer heights, optical depths of each layer, average extinction-to-backscatter ratios for each layer, and profiles of extinction in each layer. In 2000, several MPL sites were organized into a coordinated network, called MPL-Net, by the Cloud and Aerosol Lidar Group at NASA Goddard Space Flight Center (GSFC) using funding provided by the NASA Earth Observing System. tn addition to the funding provided by NASA EOS, the NASA CERES Ground Validation Group supplied four MPL systems to the project, and the NASA TOMS group contributed their MPL for work at GSFC. The Atmospheric Radiation Measurement Program (ARM) also agreed to make their data available to the MPL-Net project for processing. In addition to the initial NASA and ARM operated sites, several other independent research groups have also expressed interest in joining the network using their own instruments. Finally, a limited amount of EOS funding was set aside to participate in various field experiments each year. The NASA Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) project also provides funds to deploy their MPL during ocean research cruises. All together, the MPL-Net project has participated in four major field experiments since 2000. Most MPL-Net sites and field experiment locations are also co-located with sunphotometers in the NASA Aerosol Robotic Network. (AERONET). Therefore, at these locations data is collected on both aerosol and cloud vertical structure as well as column optical depth and sky radiance. Real-time data products are now available from most MPL-Net sites. Our real-time products are generated at times of AERONET aerosol optical depth (AOD) measurements. The AERONET AOD is used as input to our processing routines, which calculate the aerosol layer top height and extinction profile, and our MPL calibration value. A variety of other data products are available or under development. We present an overview of the MPL-Net project and discuss data products useful to the AERONET community. Results from several sites and field experiments will be presented.

Welton, Ellsworth J.↗

X-Ray Production by V1647 Ori During Optical Outbursts

The pre-main-sequence (PMS) star V1647 Ori has recently undergone two optical/near-infrared (OIR) outbursts that are associated with dramatic enhancements in the stellar accretion rate. Our intensive X-ray monitoring of this object affords the opportunity to investigate whether and how the intense X-ray emission is related to PMS accretion activity. Our analysis of all 14 Chandra X-Ray Observatory observations of V1647 Ori demonstrates that variations in the X-ray luminosity of V1647 Ori are correlated with similar changes in the OIR brightness of this source during both (2003-2005 and 2008) eruptions, strongly supporting the hypothesis that accretion is the primary generation mechanism for the X-ray outbursts. Furthermore, the Chandra monitoring demonstrates that the X-ray spectral properties of the second eruption were strikingly similar to those of the 2003 eruption. We find that X-ray spectra obtained immediately following the second outburstduring which V1647 Ori exhibited high X-ray luminosities, high hardness ratios, and strong X-ray variabilityare well modeled as a heavily absorbed (N H 4 1022cm2), single-component plasma with characteristic temperatures (kT X 2-6keV) that are consistently too high to be generated via accretion shocks but are in the range expected for plasma heated by magnetic reconnection events. We also find that the X-ray absorbing column has not changed significantly throughout the observing campaign. Since the OIR and X-ray changes are correlated, we hypothesize that these reconnection events either occur in the accretion stream connecting the circumstellar disk to the star or in accretion-enhanced protostellar coronal activity.

Teets, William↗

Data Processing of Miniaturized Laser Heterodyne Radiometer (mini-LHR) Ground Instrument Retrievals

The Miniaturized Laser Heterodyne Radiometer (mini-LHR) is a passive ground instrument that observes the mole fraction of carbon dioxide (CO) and methane (CH)in the atmospheric column by measuring their absorption of sunlight at 1.6 microns. A laser heterodyne radiometer is similar in design to the super heterodyne radio receiver that is well known by ham radio enthusiasts. While not previously a commercial technique, laser heterodyne radiometers have a history of measuring atmospheric trace gases that started in the 1960s. With the commercial availability of inexpensive, low-power, thumbnail-sized lasers developed for the telecommunications industry, it was possible to miniaturize this technique and ultimately commercialize it. The mini-LHR has been under development at NASA GSFC since 2009. During that time, in addition to signicant technical improvements, processing has also evolved and been streamlined. Here we present details of the processing approach for raw mini-LHR data to produce 30- and 60-minute data products of CH and CO column mole fractions. Processing occurs in two general stages: a python-based pre-processing of raw data, followed by ingestion into a Planetary Spectrum Generator (PSG) retrieval algorithm. Raw data processing involves removal of outliers, correcting for changes in air mass throughout the day, averaging scans, and ultimately converting averaged scans into transmittance vs. wavelength. The PSG retrieval simulates a spectra for the time/day/location of the scan with meteorological inputs from Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) data set and then perturbs the concentrations of CO and CH to obtain a t based on an iterative least-squares curve fitting procedure.

Giancarlo Roberto Zambrano↗