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These files contain 24 hour periods of data collected from the CLAMPS1 Halo Streamline Doppler lidar. While not conducting other scans, the lidar directs the beam to zenith, allowing for the measurement of vertical velocity. These data were collected during the TRACER project.
These files contain 24 hour periods of data collected from the CLAMPS2 Halo Streamline XR+ Doppler lidar. While not conducting other scans, the lidar directs the beam to zenith, allowing for the measurement of vertical velocity. These data were collected during the TRACER project.
These files contain 24 hour periods of data collected from the SPARC Halo Streamline XR+ Doppler lidar. While not conducting other scans, the lidar directs the beam to zenith, allowing for the measurement of vertical velocity. These data were collected during the TRACER project.
The Thermal Emission Spectrometer (TES) on the Mars Global Surveyor has made extensive observations of the Martian atmospheric water vapor column since the beginning of its mapping mission in early 1999. The results show broad agreement with the earlier Viking Mars Atmospheric Water Detector (MAWD) results (though column amounts in southern summer are higher, perhaps due to dust obscuration during the Viking mission). General circulation model (GCM) simulations of the annual Martian water cycle also show broad agreement with the TES observations. Details of the simulations depend on cloud and boundary layer parameterizations and on the adsorbing properties of the regolith. In order to make quantitative assessments of this agreement and to obtain observational values for the required physical parameters, a tracer transport data assimilation model has been developed. Model winds are derived from both tracer measurements and retrieved atmospheric temperature structures, providing a useful check of the underlying dynamical core of the GCM. By allowing detailed intercomparison between spacecraft and ground-based observations of Martian water vapor, the model should also contribute significantly to our understanding of the diurnal water cycle.
This dataset includes observations collected using the University of Colorado RAAVEN small Uncrewed Aircraft System (sUAS) during the TRACER Intensive Operations Period. These observations include flights conducted at two primary locations, including an area near the Brazoria National Wildlife Refuge and the University of Houston Coastal Center. Flights were conducted for approximately two weeks per month between June and the end of September, and include two primary flight modes. The first mode is a spiraling profile between the surface and 600 m above ground level, and the second mode includes flight conducted in a series of stepped altitudes between 600 and 20 m above ground level.
Hyporheic exchange in streams is critical to ecosystem functions such as nutrient cycling along river corridors, especially for slowly moving or small stream systems. The transient storage model (TSM) has been widely used for modeling of hyporheic exchange. TSM calibration, for hyporheic exchange, is typically used to estimate four parameters, including the mass exchange rate coefficient, the dispersion coefficient, stream cross-sectional area, and hyporheic zone cross-sectional area. Prior studies have raised concerns regarding the non-uniqueness of the inverse problem for the TSM, that is, the occurrence of different parameter vectors resulting in TSM solution that reproduces the observed in-stream tracer break through curve (BTC) with the same error. This leads to practical non-identifiability in determining the unknown parameter vector values even when global-optimal values exist, and the parameter optimization becomes practically non-unique. To address this problem, we applied the simulated annealing method to calibrate the TSM to BTCs, because it is less susceptible to local minima-induced non-identifiability. A hypothetical (or synthetic) tracer test data set with known parameters was developed to demonstrate the capability of the simulated annealing method to find the global minimum parameter vector, and it identified the “hypothetically-true” global minimum parameter vector even with input data that were modified with up to 10% noise without increasing the number of iterations required for convergence. The simulated annealing TSM was then calibrated using two in-stream tracer tests conducted in East Fork Poplar Creek, Tennessee. In conclusion, simulated annealing was determined to be appropriate for quantifying the TSM parameter vector because of its search capability for the global minimum parameter vector.
Minor constituents play an important role in atmospheric chemistry and serve as tracers in transport and mixing studies in tropospheric-stratospheric exchange processes. Measurements of trace gases are essential to an understanding of the mechanisms by which minor constituents originating in the troposphere, both naturally occurring and anthropogenic, reach the stratosphere. Many of these gases are sources of species directly involved in the chemistry of ozone depletion in the stratosphere and ozone generation in the troposphere. Some contribute to the warming of the atmosphere. Data on tracer distributions are important in the development of models for predicting photochemical effects in the stratosphere and troposphere. Data on atmospheric dynamics are important for the development of models for predicting the transport of photochemical species and for characterizing the nature of stratospheric motions.
This model-data archive pertains to a study aimed at the numerical evaluation of the photosensitive tracers as a potential strategy for separating the effects of surface and hyporheic storage zones (SSZs and HSZs, respectively). Separating effects of SSZ and HSZ are important for accurately representing stream function as HSZs and SSZs expose solutes to significantly different biogeochemical conditions. We perform numerical experiments using a multiscale reactive transport model for stream corridors implemented in ATS code, which allows for representing multiple storage zones with their respective travel time distributions and biogeochemistry. For each of the numerical experiment, we provide in this model-data archive python wrapper to drive ATS (forward_model.py), synthetic observation (synthetic_btc.py, BTC_observed.csv), forward model files including ATS input (multiscale_transport.tpl), PFLOTRAN inputs (reactions_channel.tpl, reactions_hz.tpl, reactions_sz.tpl), MCMC (mcmc_run.py), predictive uncertainty (pred_uncert.py, BTCs_simulated_day.csv, BTCs_simulated_night.csv), MCMC outputs (tracer_test_GR.npy, tracer_test_logps.npy, tracer_test_parameters.npy) and Jupyter notebook for post-processing and visualization (post-processing.ipynb). For the denitrification application, ATS input file (denitrification_multisubgrid.tpl), PFLOTRAN input files (denitrification_channel.in, denitrification_hz.in), predictive uncertainty (pred_uncert_denitrification.py, BTCs_simulated_DO.csv, BTCs_simulated_DOC.csv, BTCs_simulated_Nitrate.csv).
A method is presented of computing the dayside global earth magnetic field which is in equilibrium with the plasma pressure, based on satellite observations at a local region of the magnetosphere. The method, which utilizes a perturbation around a dipole magnetic field, involves computation of the global plasma pressure profile based on the equatorial (anisotropic) pressure data, derivation of the current profile which satisfies the equilibrium condition, and computation of the magnetic field using the current profile and the boundary current produced by the solar wind. The method is applied for the Active Magnetospheric Particle Tracer Explorers data, and the result of the computation is found to compare reasonably well with the observed magnetic field profile near the geomagnetic equator.
Minor constituents play an important role in upper atmospheric photochemistry and serve as tracers in transport and mixing studies in tropospheric stratospheric exchange processes. Measurements of trace gases are essential to an understanding of the mechanisms by which minor constituents originating in the troposphere, both naturally occurring and anthropogenic, reach the stratosphere; data on tracer distributions thus acquired are important in the development of models for predicting photochemical effects in the stratosphere.
Modelling the chemistry of molecular clouds is critical to accurately simulating their evolution. To reduce computational cost, 3D simulations generally restrict their chemistry to species with strong heating and cooling effects. Time-dependent information about the evolution of other species is therefore often neglected. We address this gap by post-processing tracer particles in the SILCC-Zoom molecular cloud simulations. Using a chemical network of 39 species and 301 reactions (including freeze-out of CO and H 2 O) and a novel algorithm to reconstruct a density grid from sparse tracer particle data, we produce time-dependent density distributions for various species. We focus upon the evolution of HCO + , which is a critical formation reactant of CO but is not typically modelled on the fly. We find that ∼ 90 per cent of the HCO + content of the cold molecular gas forms in situ around n HCO + ∼ 10 3 –10 4 cm −3 , over a time-scale of approximately 1 Myr. The remaining ∼ 10 per cent forms at high extinction sites, with minimal turbulent mixing out into the less dense gas. We further show that the dominant HCO + formation pathway is dependent on the visual extinction, with the reaction H 3 + + CO contributing 90 per cent of the total HCO + production above A V, 3D = 3. We produce the very first maps of the HCO + column density, N(HCO + ), and show that it reaches values as high as 10 15 cm −2 . We find that 50 per cent of the HCO + mass is located within AV ∼ 10–30 in a density range of 10 3.5 –10 4.5 cm −3 . Our maps of N(HCO + ) are shown to be in good agreement with recent observations of the W49A star-forming region.
Abstract The detection of GW170817/AT2017gfo inaugurated an era of multimessenger astrophysics, in which gravitational-wave and multiwavelength photon observations complement one another to provide unique insight into astrophysical systems. A broad theoretical consensus exists, in which the photon phenomenology of neutron star mergers largely rests upon the evolution of the small amount of matter left on bound orbits around the black hole or massive neutron star remaining after the merger. Because this accretion disk is far from inflow equilibrium, its subsequent evolution depends very strongly on its initial state, yet very little is known about how this state is determined. Using both snapshot and tracer particle data from a numerical relativity/MHD simulation of an equal-mass neutron star merger that collapses to a black hole, we show how gravitational forces arising in a nonaxisymmetric, dynamical spacetime supplement hydrodynamical effects in shaping the initial structure of the bound debris disk. The work done by hydrodynamical forces is ∼10 times greater than that due to time-dependent gravity. Although gravitational torques prior to remnant relaxation are an order of magnitude larger than hydrodynamical torques, their intrinsic sign symmetry leads to strong cancellation; as a result, hydrodynamical and gravitational torques have a comparable effect. We also show that the debris disk’s initial specific angular momentum distribution is sharply peaked at roughly the specific angular momentum of the merged neutron star’s outer layers, a fewr g c, and identify the regulating mechanism.
During the courses of a day, the Mars Observer spacecraft will acquire globally distributed profiles of the martian atmosphere. It is highly desirable that this data be assembled into synoptic weather maps (complete specifications of the atmospheric pressure, temperature, and winds at a given time), which can in turn be used as starting points in the study of many meteorological phenomena. Unfortunately, the special nature of the Mars Observer data presents several challenges above and beyond the usual difficult problem of data initialization. Mars Observer atmospheric data will consist almost exclusively of asynoptic vertical profiles of temperatures (or radiances) and pressures, whereas winds are generally in balance with horizontal gradients of these quantities (which will not be observed). It will therefore be necessary to resort to dynamical models to analyze the wind fields. As a rule, data assimilation into atmospheric models can result in the generation of spurious gravity waves, so special steps must be taken to suppress these. In addition, the asynoptic nature of the data will require a four-dimensional (space and time) data assimilation scheme. The problem is to find a full set of meteorological fields (winds and temperatures) such that, when marched forward in time in the model, they achieve a best fit (in the weighted least-squares sense) to the data. The proposed solution is to develop a model especially for the Mars Observer data assimilation problem. Gravity waves are filtered from the model by eliminating all divergence terms from the prognostic divergence equation. This leaves a diagnostic gradient wind relation between the rotational wind and the temperature field. The divergent wind is diagnosed as the wind required to maintain the gradient wind balance in the presence of the diabatic heating. The primitive equations of atmospheric dynamics (with three principal dependent variables) are thus reduced to a simpler system with a single prognostic equation for temperature - the variable that will be best observed. (This balance system was apparently first derived by Charney as a first-order Rossby number expansion of the equations of motion). Experience with a full primitive equation model of the martian atmosphere indicates that a further simplification is possible: at least for short-term integrations, the model can be linearized about the zonally symmetric basic state.
This dataset contains tracer test results from stimulation and circulation experiments conducted on the Utah FORGE wells 16A(78)-32 and 16B(78)-32 during 2024. The data was collected by RESMAN Energy Technology and includes detailed tracer analysis from flowback, short- and extended-duration circulation tests, and reinjection sampling. Sampling included analysis of tracers during different stages of testing in April, August, and September 2024. The dataset is accompanied by an interpretation report and contains time-series tracer concentration data with identification of test phases and sampling conditions. It includes results for flowback from well 16A, commingling effects with water from well 16B, tracer data from short and extended circulation tests, and reinjection tracer corrections for the August/September test. Users should be aware that proprietary tracer methodologies were applied, and they should consult the interpretation report for insights into experimental procedures and data contextualization.
Multiple sets of tracer tests were conducted at the EGS Collab Testbed 2 on the 4100 L at the Sanford Underground Research Facility (SURF), Lead, SD. The enclosed data package includes: tracer recovery results, water balance calculations and rationales, water flow measurement for north ditch, (manual) water flow measurements at different production points, and a tracer-interpretation paper presented at the Stanford Geothermal Workshop, 2023.
The distribution and variation of oxygen isotopes in seawater are calculated using the Goddard Institute for Space Studies global ocean model. Simple ecological models are used to estimate the planktonic foraminiferal abundance as a function of depth, column temperature, season, light intensity, and density stratification. These models are combined to forward model isotopic signals recorded in calcareous ocean sediment. The sensitivity of the results to the changes in foraminiferal ecology, secondary calcification, and dissolution are also examined. Simulated present-day isotopic values for ecology relevant for multiple species compare well with core-top data. Hindcasts of sea surface temperature and salinity are made from time series of the modeled carbonate isotope values as the model climate changes. Paleoclimatic inferences from these carbonate isotope records are strongly affected by erroneous assumptions concerning the covariations of temperature, salinity, and delta (sup 18)O(sub w). Habitat-imposed biases are less important, although errors due to temperature-dependent abundances can be significant.
Time-lapse electrical resistivity tomography (ERT) measurements provide indirect observations of hydrological processes in the Earth's shallow subsurface at high spatial and temporal resolution. ERT has been used in the past decades to detect leaks and monitor the evolution of associated contaminant plumes. Specifically, inverted resistivity images allow visualization of the dynamic changes in the structure of the plume. However, existing methods do not allow the direct estimation of leak parameters (e.g. leak rate, location, etc.) and their uncertainties. We propose an ensemble-based data assimilation framework that evaluates proposed hydrological models against observed time-lapse ERT measurements without directly inverting for the resistivities. Each proposed hydrological model is run through the parallel coupled hydro-geophysical simulation code PFLOTRAN-E4D to obtain simulated ERT measurements. The ensemble of model proposals is then updated using an iterative ensemble smoother. In this paper, we demonstrate the proposed framework on synthetic and field ERT data from controlled tracer injection experiments. Our results show that the approach allows joint identification of contaminant source location, initial release time, and solute loading from the cross-borehole time-lapse ERT data, alongside with an assessment of uncertainties in these estimates. We demonstrate a reduction in site-wide uncertainty by comparing the prior and posterior plume mass discharges at a selected image plane. This framework is particularly attractive to sites that have previously undergone extensive geological investigation (e.g., nuclear sites). It is well suited to complement ERT imaging and we discuss practical issues in its application to field problems.
The use of model-assimilated meteorological observations for stratospheric research has become routine since the late 1980's. The first stratospheric assimilation systems were straightforward extensions of systems developed for tropospheric weather forecasting. During the 1990's systems were developed that more directly addressed the specifics of stratospheric applications. These developments include better treatment of the satellite observations and improved models that better represent the residual circulation in the assimilated data sets. This talk will review the evolution of stratospheric data assimilation and its application, especially to problems of tracer transport. The new data assimilation currently under validation at NASA will be described in some detail, and results from the validation exercise will be presented. This data assimilation system sits at the foundation of a proposed stratospheric reanalysis that covers the era of the Upper Atmosphere Research Satellite (UARS).