Find research datasets worth reusing

opencc-by-4.0Nov 2023View details →

JasonAlongTrack: A reformatted version of the Integrated Multi-Mission Ocean Altimeter Data for Climate Research Version 5.1

JasonAlongTrack contains geo-registered along-track sea surface height anomalies with respect to the DTU15 mean sea surface at 1-second intervals from Jason-class altimeters, reformatted for convenience into a 3D array with dimensions of along-track direction by geographically sorted track number by cycle.This is a reformatted version of Beckley et al.'s Integrated Multi-Mission Ocean Altimeter Data for Climate Research complete time series Version 5.1 dataset, available from <a href="https://podaac.jpl.nasa.gov/dataset/MERGED_TP_J1_OSTM_OST_ALL_V51">https://podaac.jpl.nasa.gov/dataset/MERGED_TP_J1_OSTM_OST_ALL_V51</a>.   The changes are as follows. Altimeter passes are sorted according to their initial longitude, then split into descending and ascending potions with all descending tracks preceding all ascending tracks. Descending tracks are then flipped so that latitude increases in the alongtrack direction for all tracks. This leads to a 3373 x 254 matrix of observational locations, with the first dimension being the along-track location and the second dimension being the track index. Sea surface height anomaly, time, and flag values are then placed into their correct locations within this matrix, such that these three variables are all of size 3373 x 254 x K where K is the number of cycles, currently 1087. A very good approximation to the time at each of the 3373 x 254 x K observation points is constructed with a length K array of cycles times together with a 3373 x 254 array of time offsets. A median-based editing criterion in introduced to identify a small number of suspect data points.  These are set to a value of NaN in sla, but their positions and values are recorded in rejected_index and rejected_values, respectively.  The DTU15 mean dynamic topography (mdt) is included, in addition to the mean sea surface field already provided, interpolated onto the track locations using bicubic interpolation.  Finally, an estimate of the small-scale noise level, sigma, is produced using a wavelet transform filter.

opencc-by-4.0Aug 2020View details →

Reconstructed high-rate SEIS data recorded during HP3 hammering from the NASA InSight mission to Mars

The NASA InSight lander successfully placed a seismometer on the surface of Mars. Alongside, a hammering device was deployed that penetrated into the ground to attempt the first measurements of the planetary heat flow of Mars. The hammering of the heat probe generated repeated seismic signals that were registered by the seismometer. However, the broad frequency content of the seismic signals generated by the hammering extends beyond the Nyquist frequency governed by the seismometer's sampling rate of 100 samples per second. Here, we provide data that was reconstructed at a higher sampling rate of 2000 samples per second using a dedicated de-aliasing algorithm described in the accompanying article. This archive will be updated regularly with new data acquired on Mars.  For a detailed data description and instructions on how to cite this dataset, please refer to the README file.

opencc-by-4.0Dec 2022View details →

Spectral reflectance data of Mercury's surface collected by the Mercury Atmospheric and Surface Composition Spectrometer (MASCS) instrument during orbital observations of the NASA MESSENGER mission between 2011 and 2015 resampled to a [55399 × 396] tabular data format.

MASCS is a three sensor point spectrometer with a spectral coverage from 200 nm to 1450 nm. Single spectra are resamples in to steps to a format useful for our ML application : a datacube with ~400 spectral channel covering the whole surface of Mercury. The final dataset has dimension [N×M] where N is the number of grid cells (360 × 180 = 64, 800) and M is the number of spectral features (396). Due to the incomplete coverage and data filtering, some grid cells are empty. After removing these empty cells, the size of the dataset is [55399 × 396]. This specific product is stored as a gzip compressed json, where each element is a grid cell. We are in the process to publish a complete pipeline to produce this product from RAW data on https://github.com/epn-ml/MESSENGER-Mercury-Surface-Cassification-Unsupervised_DLR/ . Spectral reflectance data of Mercury’s surface collected by the Mercury Atmospheric and Surface Composition Spectrometer (MASCS) instrument during orbital observations of the NASA MESSENGER mission between 2011 and 2015. MASCS is a three sensor point spectrometer with a spectral coverage from 200 nm to 1450 nm. Single spectra are resamples in to steps to a format useful for our ML application : a datacube with ~400 spectral channel covering the whole surface of Mercury. The final dataset has dimension [N×M] where N is the number of grid cells (360 × 180 = 64, 800) and M is the number of spectral features (396). Due to the incomplete coverage and data filtering, some grid cells are empty. After removing these empty cells, the size of the dataset is [55399 × 396]. 0. Pre-filtering We used the most recent dataset that had large-scale photometric corrections and thus was almost free from observation geometry effects. However, extreme geometry are still present and are typically associated with high noise and some residual instrumental effects. Based on our empirical tests, we filtered out observations with an emission/incidence angle ≥80∘. We also calculated the median value per wavelength and per cell grid when constructing the global hyperspectral data cube and filtered out observations falling under the 2nd percentile and above 99.9th percentile to clean some residual geometry effects. With this approach we create an effective noise filter while retaining enough observations to be able to analyse the entirety of the surface of the planet. 1. Spectral resmpling Unprocessed MASCS spectra could have 512 or 256 channes, depending on binning. We resampled the data in the spectral dimension to a common wavelength range from 260 nm to 1052 nm with a  4 nm resolution (2 nm spectral sampling), resulting in 396 spectral channels. This approach slightly oversamples the original 4.77 nm spectral resolution and removes some points from the original 200-1050 nm range. The resulting data matrix is expressed in tabular form, with each row representing a single grid cell or pixel on the surface. The elements of each row are the spectral reflectance values from the VIS instrument at 396 (resampled) wavelengths. 2. Spatial resmpling The whole dataset of &sim; 5 million spectra is resampled to a planet-wide rectangular grid of 1×1deg in the latitudinal band between ± 80. The cell longitudinal size varies between &sim; 40 km at the equator to a minimum of &sim; 10 km at ±80∘. Thus, the area spanned by each grid cell depends on the latitude. However, the same is true for the acquisition process, where higher spatial resolution is reached near the equator and lower resolution at the poles.

opencc-by-4.0Feb 2023View details →

Dataset for paper "Target selection for Near-Earth Asteroids in-orbit sample collection missions"

This dataset can be used to reproduce the results of the paper titled "Target selection for Near-Earth Asteroids in-orbit sample collection missions." The "results" folder contains the data to reproduce the maps and the rankings of the target asteroids. The "trajectories" folder contains the propagation of the sample trajectories used to obtain the grids.

opencc-by-4.0Sep 2016View details →

A multi-resolution, multi-epoch low Radio Frequency Survey of the Kepler K2 Mission Campaign 1 Field

Data abstract: Contained within are the MWA images used as input data for this study. The production and analysis of these images are described in the linked paper. The final catalogues and light curves are available from VizieR (http://vizier.cfa.harvard.edu/viz-bin/VizieR?-source=J/AJ/152/82). Paper abstract: We present the first dedicated radio continuum survey of a Kepler K2 mission field, Field 1, covering the North Galactic Cap. The survey is wide field, contemporaneous, multi-epoch, and multi-resolution in nature and was conducted at low radio frequencies between 140 and 200 MHz. The multi-epoch and ultra wide field (but relatively low resolution) part of the survey was provided by 15 nights of observation using the Murchison Widefield Array (MWA) over a period of approximately a month, contemporaneous with K2 observations of the field. The multi-resolution aspect of the survey was provided by the low resolution (4‧) MWA imaging, complemented by non-contemporaneous but much higher resolution (20″) observations using the Giant Metrewave Radio Telescope (GMRT). The survey is, therefore, sensitive to the details of radio structures across a wide range of angular scales. Consistent with other recent low radio frequency surveys, no significant radio transients or variables were detected in the survey. The resulting source catalogs consist of 1085 and 1468 detections in the two MWA observation bands (centered at 154 and 185 MHz, respectively) and 7445 detections in the GMRT observation band (centered at 148 MHz), over 314 square degrees. The survey is presented as a significant resource for multi-wavelength investigations of the more than 21,000 target objects in the K2 field. We briefly examine our survey data against K2 target lists for dwarf star types (stellar types M and L) that have been known to produce radio flares.

opencc-by-4.0Apr 2023View details →

Lunar Missions Database (MoonDB)

The MoonDB is a database of past and present spacecraft in cislunar space, compiled through publicly available sources. It was designed to better understand the rationale behind missions, focusing on their final results, current status, funding agencies and nations. Particular attention has also been given to the surface of the Moon, where landing sites have been identified. The database is mainly based on data collected by NASA in the Master Catalogue of the NASA Space Science Data Coordinated Archive (NSSDCA) [1]. Other sources are also considered, such as the Satellite Catalog (SATCAT) from the Space-Track project [2], created by the US Combined Force Space Component Command (CFSCC). The work by McDowell (2020) [3] has also been considered an inspiration for this work, although the primary source of information has remained the NASA catalogue. Some structural and logical changes have been introduced to follow the needs of this research project. Following a list provided by the NSSDCA, a certain number of tentative USSR missions were added to the statistics [4]. Most spacecraft were destroyed due to a launch failure and were not disclosed to the public: the available information results from an investigation. Additional information and a version changelog are provided in the readme file.

opencc-by-4.0Jul 2022View details →

Dataset generated to evaluate in situ sampling strategies to reconstruct fine-scale ocean currents in the context of SWOT satellite mission (H2020 EuroSea project)

Dataset generated in Subtask 2.3.1 of the H2020 EuroSea project. <ul> <li> H2020 EuroSea project: The H2020 EuroSea project aims at improving and integrating the European Ocean Observing and Forecasting System (see official website: <a href="https://eurosea.eu/">https://eurosea.eu/</a>). It has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 862626). </li> <li> Task 2.3: Task 2.3 has the objective to improve the design of multi-platform experiments aimed to validate the Surface Water and Ocean Topography (SWOT) satellite observations with the goal to optimize the utility of these observing platforms. Observing System Simulation Experiments (OSSEs) have been conducted to evaluate different configurations of the in situ observing system, including rosette and underway CTD, gliders, conventional satellite nadir altimetry and velocities from drifters. High-resolution models have been used to simulate the observations and to represent the “ocean truth”. Several methods of reconstruction have been tested: spatio-temporal optimal interpolation, machine-learning techniques, model data assimilation and the MIOST tool. The planned OSSEs are detailed in this public report <a href="https://doi.org/10.3289/eurosea_d2.1">Barceló-Llull et al. (2020)</a> and the complete analysis is available here <a href="https://doi.org/10.3289/eurosea_d2.3">Barceló-Llull et al. (2022)</a>. Contributors to Task 2.3 are CSIC (Spain), CLS (France), SOCIB (Spain), IMT-Atlantique (France) and Ocean-Next (France). </li> <li> Subtask 2.3.1: Subtask 2.3.1 aims to evaluate different in situ sampling strategies to reconstruct fine-scale ocean currents (~20 km) in the context of SWOT. An advanced version of the classic optimal interpolation used in field experiments, which considers the spatial and temporal variability of the observations, has been applied to reconstruct different configurations with the objective to evaluate the best sampling strategy to validate SWOT. </li> <li> Where? The analysis focuses on two regions of interest: (i) the western Mediterranean Sea and (ii) the Subpolar North West Atlantic. In the western Mediterranean Sea, the target area is located within a swath of SWOT, while in the North West Atlantic the region of study includes a crossover of SWOT during the fast-sampling phase. </li> </ul> Report with the full analysis The complete analysis can be found in this report: <a href="https://doi.org/10.3289/eurosea_d2.3">Barceló-Llull et al. (2022)</a>. Codes for the analysis The codes generated to develop Subtask 2.3.1 can be found on GitHub: <a href="https://github.com/bbarcelollull/EuroSea_subTask_2.3.1">https://github.com/bbarcelollull/EuroSea_subTask_2.3.1</a> The dataset The dataset includes: 1) Model outputs used to simulate the observations in different configurations in both regions of study. The folder "2D_model_outputs" contains 2D data used to simulate SSH observations for the analysis of the temporal correlation scale (<a href="https://doi.org/10.3289/eurosea_d2.3">Barceló-Llull et al., 2022</a>, p. 28-42). The folder "3D_model_outputs" contains 3D model outputs used to simulate observations of temperature and salinity. Note that eNATL60 outputs have been interpolated onto a new regular grid.   2) Simulated configurations (or sampling strategies) in each region (PKL file format). 3) Observations simulated in each configuration in both regions of study. The observations simulated are temperature and salinity. ADCP horizontal velocities are also simulated, however for eNATL60 they will be corrected in the future to account for the rotated original axes. File format: region_configuration_period_model.nc. The folder "SSH" includes the simulated SSH observations for the analysis of the temporal correlation scale (<a href="https://doi.org/10.3289/eurosea_d2.3">Barceló-Llull et al., 2022</a>, p. 28-42). 4) Reconstructed fields with the spatio-temporal optimal interpolation. File format: region_configuration_period_model_stOI_Lx_Lt_cd_YYYYMMDDhhmm_var.nc (stOI = spatio-temporal optimal interpolation, Lx = spatial correlation scale, Lt = temporal correlation scale, cd = map on the central date of the sampling, YYYYMMDDhhmm = date and time of the map, var = variable interpolated (temperature and salinity) or the derived variables (dynamic height, geostrophic velocities and the Rossby number)). 5) Compared fields (ocean truth from model outputs vs. reconstructed fields) for each region and model (PKL file format).

opencc-by-4.0Feb 2023View details →

Predicted times of bow Shock crossings at Venus from the ESA/Venus Express mission, using spacecraft ephemerides and magnetic field data, with a predictor-corrector algorithm

CHARACTERISTICS Planet: Venus Radius: RV = 6051.8 km (volumetric mean planetary radius) Spacecraft: ESA/Venus Express Spacecraft coordinates system: Venus Solar Orbital (VSO) equivalent to Sun-State coordinate system: <ul> <li>+XVSO points towards the Sun from the planet’s centre,</li> <li>+ZVSO towards Venus’ North pole and perpendicular to the orbital plane defined as the XVSO–YVSO plane passing through the centre of Venus,</li> <li>YVSO completes the orthogonal system.</li> </ul> Time span: 01/04/2006 to 25/11/2014 Total number N of candidate bow shock crossings in the database: N = 4950 Number of quasi-parallel bow shock crossings: N|| = 844 Number of quasi-perpendicular bow shock crossings: N$\perp$ = 4106 ORIGINAL DATASETS USED The original Venus Express/MAG data repository on which these algorithms were applied is available on ESA's Planetary Science Archive system (PSA) at: https://archives.esac.esa.int/psa/ftp/VENUS-EXPRESS/MAG/. For this study, 1-Hz magnetic field data was used. METHOD To construct this database from the original datasets above, the predictor and predictor-corrector algorithms used are described for the Mars case in: Simon Wedlund, C., Volwerk, M., Beth, A., Mazelle, C., Möstl, C., Halekas, J., Gruesbeck, J. and Rojas-Castillo, D., (2021), A Fast Bow Shock Location Predictor-Estimator From 2D and 3D Analytical Models: Application to Mars and the MAVEN mission, Journal of Geophysical Research, 127, e2021JA029942. <a href="https://doi.org/10.1029/2021JA029942">https://doi.org/10.1029/2021JA029942</a> They consist of two consecutive steps:  <ol> <li>Predictor geometric algorithm based on 2D or 3D existing fits for prediction of the Venus bow shock position. The original fits were taken from 2D conic fits in the plane $\left(X_\text{VSO}, \sqrt{Y_\text{VSO}^2+Z_\text{VSO}^2}\right)$performed on the datasets of Persson et al. (2023), Venusian bow shock crossings manually identified from measurements by the ASPERA-4 and MAG instruments onboard Venus Express, Zenodo (<a href="http://doi.org/10.5281/zenodo.7679677">https://doi.org/10.5281/zenodo.7679677</a>).</li> <li>Corrector algorithm based on magnetic field measurements.</li> </ol> We also provide the angle between the average Interplanetary Magnetic Field (IMF) vector upstream of the shock and the shock normal, noted θBn (ThetaBn). Assuming a locally smooth shock surface, this gives a first indication of the geometry of the shock, so that: <ul> <li>45∘<θBn<135∘: quasi-perpendicular shock condition</li> <li>θBn≤45∘ and θBn$\geq$135∘: quasi-parallel shock condition</li> </ul> Uncertainty on these angles is estimated to be ± 5º.  For details, see Simon Wedlund et al. (2022) above, §2.3 pp. 10-12. VARIABLES DESCRIPTION This database contains the following ASCII variables: <ul> <li>Bow shock times in Venus Express' database (1-s resolution): Tbs</li> <li>Venus Solar Orbital coordinates of the shock, in units of Venus radius RV (RV = 6051.8 km): XVSO, YVSO, ZVSO and Euclidean distance $R_{VSO} = \sqrt{X_{VSO}^2 + Y_{VSO}^2 + Z_{VSO}^2}$ (in RV)</li> <li>Solar Zenith angle in degrees: SZA = $\tan^{-1}{Y_{VSO}^2+Z_{VSO}^2 \over X_{VSO}^2}$ (in º) </li> <li>Angle between average B-field direction and shock normal assuming a smooth shock surface $\theta_{Bn}$ (ThetaBn, in º, calculated with atan2(norm(cross(B,ñ),dot(B,ñ)), with B the magnetic field vector and ñ the vector normal to the shock surface): <ul> <li>45 < ThetaBn <  135 deg: quasi-$\perp$ shock</li> <li>ThetaBn $\leq$ 45 deg & ThetaBn $\geq$ 135 deg: quasi-|| shock</li> </ul> </li> <li>Interplanetary Magnetic Field (IMF) upstream average vector in VSO coordinates, Bx, By, Bz (in nT).</li> <li>Flag for direction of crossing: <ul> <li>flag = 0: magnetosheath $\longrightarrow$ solar wind (2447 events)</li> <li>flag = 1: solar wind $\longrightarrow$ magnetosheath (2503 events)</li> </ul> </li> </ul> WARNING <ol> <li>This version of the database is currently in a preliminary stage of application and, as such, is not fully tested. Solar wind upstream magnetic field values (IMF) are given only as a first approximation for each orbit segment. See point 2 for caveats. For carefully manually picked shock crossings, the user is referred to the database of: Persson et al. (2023), Venusian bow shock crossings manually identified from measurements by the ASPERA-4 and MAG instruments onboard Venus Express, Zenodo (<a href="http://doi.org/10.5281/zenodo.7679677">https://doi.org/10.5281/zenodo.7679677</a>)</li> <li>This database is based on an automatic statistical geometrical estimate, further refined by constraints on magnetic fields. This is aimed at giving a first approximation of the shock area times in the Venus Express data. It is particularly suited to statistical studies and region identification in the Venus Express datasets. As such, this database should be used as a first indicator of the shock location, and with caution: it CANNOT, and WILL NOT substitute, especially in case studies, for a careful analysis of the full magnetometer and plasma bow shock signatures. Moreover, the algorithm is optimised for detecting the first disturbance observed in the magnetic field immediately ahead of the shock's foot (in the foreshock area), and not for the detection of other structures in the shock, such as the shock ramp. The "shock" location is therefore given here with typical uncertainties of about 0.040 RV (with RV = 6051.8 km, i.e., about 250 km in the radial direction). Finally, for multiple shock crossings, the algorithm chooses the first occurrence of the shock starting from the undisturbed solar wind.</li> </ol> Current formatting optimised for MATLAB. ACKNOWLEDGEMENTS C. Simon Wedlund and M. Volwerk thank the Austrian Science Fund (FWF) project P32035-N36.     LICENSE AND RIGHTS This database is shared under a Creative Commons CC-BY-4.0 license. Version 1 (c) Cyril Simon Wedlund @ Space Research Institute of Graz (IWF),                                                              Austrian Academy of Sciences, 2022-10-05 Contact email:        cyril.simon.wedlund@gmail.com

KM2112 SCOPE-PARAGON cruise, Seaglider 513, Mission 11

The 2021 SCOPE-PARAGON research expedition is a coordinated effort to characterize particle dynamics and remineralization in the upper 500 m of the North Pacific Subtropical Gyre. Despite the importance of particles as key sites of biological activity in an otherwise dilute seawater medium, there remain major gaps in our understanding of the specific processes and organisms controlling particle transformations. The 2021 SCOPE-PARAGON cruise will be directed towards understanding the processes and rates of biological particulate matter transformations (e.g., production, decomposition, sinking) as well as the ecological interactions that occur in association with suspended and sinking particles. These targeted studies of particle dynamics at Station ALOHA will leverage ongoing ecological and biogeochemical modeling efforts in SCOPE.

KM2209 SCOPE-PARAGON 2 cruise, Seaglider 513, Mission 13

The 2022 SCOPE-PARAGON II research expedition is a coordinated effort to characterize particle dynamics and remineralization in the upper 500 m of the North Pacific Subtropical Gyre. Despite the importance of particles as key sites of biological activity in an otherwise dilute seawater medium, there remain major gaps in our understanding of the specific processes and organisms controlling particle transformations. The 2022 SCOPE-PARAGON II cruise will be directed towards understanding the processes and rates of biological particulate matter transformations (e.g., production, decomposition, sinking) as well as the ecological interactions that occur in association with suspended and sinking particles. These targeted studies of particle dynamics at Station ALOHA will leverage ongoing ecological and biogeochemical modeling efforts in SCOPE.

KM2112 SCOPE-PARAGON cruise, Seaglider 626, Mission 3

KM2112 SCOPE-PARAGON cruise, Seaglider 511, Mission 20

openCC (other)Oct 2022View details →

edi48/100

SBC LTER: Land: Hydrology: Stream discharge and associated parameters at Mission Creek at Rocky Nook, USGS 11119745 (MC06)

Stream Discharge and water temperature were collected with a Solinst Model 3001 LT Levelogger at Mission Creek at Rocky Nook, USGS 11119745 in the Santa Barbara coastal area (site ID: MC06). Data are reported hourly. Stage values were converted to discharge using a rating curve developed with stream channel cross-sections, roughness estimates and the HEC-RAS model.

opencc-zeroApr 2024View details →

Coefficients for a Proxy Long-Wavelength Correction for the SWOT 1-Day Repeat Mission

This archive contains NetCDF-formatted files containing the weighting coefficients which define the proxy long-wavelength correction (LWC) described in a manuscript submitted to AGU Earth and Space Science,  "The Significance of the Long-Wavelength Correction for Studies of Baroclinic Tides with SWOT".

opencc-by-4.0Nov 2021View details →

Predicted times, spatial coordinates of bow shock crossings and shock geometry at Mars from the NASA/MAVEN mission, using spacecraft ephemerides and magnetic field data, with a predictor-corrector algorithm

CHARACTERISTICS Planet: Mars Radius: RM = 3389.5 km (volumetric mean planetary radius) Spacecraft: NASA/Mars Atmosphere and Volatile Evolution (MAVEN) Spacecraft coordinates system: Mars Solar Orbital (MSO) equivalent to Sun-State coordinate system: <ul> <li>+XMSO points towards the Sun from the planet’s centre,</li> <li>+ZMSO towards Mars’ North pole and perpendicular to the orbital plane defined as the XMSO–YMSO plane passing through the centre of Mars,</li> <li>YMSO completes the orthogonal system.</li> </ul> Time span: 01/11/2014 to 30/04/2024 (Mars Years MY32 to MY36 included, part of MY37). Total number N of candidate bow shock crossings in the database: N = 20107 ORIGINAL DATASETS USED The original MAVEN/MAG data repository on which these algorithms were applied is available on NASA's Planetary Data System (PDS) at <a href="https://doi.org/10.17189/1414178">https://doi.org/10.17189/1414178</a>. For this study, 1-Hz magnetic field data was used. METHOD To construct this database from the original datasets above, the predictor and predictor-corrector algorithms used are described in: Simon Wedlund, C., Volwerk, M., Beth, A., Mazelle, C., Möstl, C., Halekas, J., Gruesbeck, J. and Rojas-Castillo, D., (2022), A Fast Bow Shock Location Predictor-Estimator From 2D and 3D Analytical Models: Application to Mars and the MAVEN mission, Journal of Geophysical Research, 127, 1-33, e2021JA029942, <a href="https://doi. org/10.1029/2021JA029942">https://doi. org/10.1029/2021JA029942</a>.  Also available at: <a href="https://doi.org/10.1002/essoar.10507942.1">https://doi.org/10.1002/essoar.10507942.1 </a> and as arXiv e-print: <a href="https://doi.org/10.48550/arXiv.2109.04366">https://doi.org/10.48550/arXiv.2109.04366</a> These algorithms consist of two consecutive steps:  <ol> <li>Predictor geometric algorithm based on J. Gruesbeck's 3D model (<a href="https://doi.org/10.1029/2018JA025366">Gruesbeck et al. 2018</a>) for prediction of Mars bow shock position</li> <li>Corrector algorithm based on magnetic field measurements (magnitude and fluctuations).</li> </ol> REMARK ON VERSIONS From Version 3 onwards, we also provide the angle between the average Interplanetary Magnetic Field (IMF) vector upstream of the shock and the shock normal, noted $\theta_{Bn}$(ThetaBn). Assuming a smooth shock surface and the 3D model of Gruesbeck et al. (2018, all points), this gives a first indication of the geometry of the shock, so that: <ul> <li>45∘<θBn<135∘: quasi-perpendicular shock condition</li> <li>θBn≤45∘ and θBn≥135∘: quasi-parallel shock condition</li> </ul> Uncertainty on these angles is estimated to be ± 5º.  From Version 4 onwards, we also added the solar longitude Ls (in degrees). For details, see Simon Wedlund et al. (2022) above, §2.3 pp. 10-12. Note that due to minor adjustments in the code, some of the ThetaBn angles calculated here for the examples of Fig. 6 in Simon Wedlund et al. (2022) may slightly differ from the values quoted in the paper. VARIABLES DESCRIPTION This database contains the following ASCII variables: <ul> <li>Bow shock times in MAVEN's database (1-s resolution): Tbs</li> <li>Mars Solar Orbital coordinates of the shock, in units of Mars radius RM (RM = 3389.5 km): XMSO, YMSO, ZMSO and Euclidean distance $R_{MSO} = \sqrt{X_{MSO}^2 + Y_{MSO}^2 + Z_{MSO}^2}$ (in RM)</li> <li>Solar Zenith angle in degrees: SZA = $\tan^{-1}{Y_{MSO}^2+Z_{MSO}^2 \over X_{MSO}^2}$ (in º) </li> <li>Angle between average B-field direction and shock normal assuming a smooth shock surface $\theta_{Bn}$ (ThetaBn, in º) <ul> <li>45 < ThetaBn <  135 deg: quasi-&perp; shock</li> <li>ThetaBn ≤45 deg & ThetaBn ≥ 135 deg: quasi-|| shock</li> </ul> </li> <li>Solar longitude Ls, in degrees.</li> <li>Flag for crossing: <ul> <li>sheath $\longrightarrow$ solar wind, flag = 0.</li> <li>solar wind $\longrightarrow$ sheath, flag = 1.</li> </ul> </li> </ul> WARNING This database is based on an automatic statistical geometrical estimate, further refined by constraints on magnetic field. It is aimed at giving a first approximation of the shock area times in the MAVEN data. It is particularly suited to statistical studies and region identification in the MAVEN datasets. As such, this database should be used as a first indicator of the shock location, and with caution: it CANNOT, and WILL NOT substitute, especially in case studies, for a careful analysis of the full magnetometer and plasma suite bow shock signatures. Moreover, the algorithm is optimised for detecting the first disturbance observed in the magnetic field immediately ahead of the shock's foot (in the foreshock area), and not for the detection of other structures in the shock, such as the shock ramp. The "shock" location is therefore given here with typical uncertainties of about 0.075 RM (with RM = 3389.5 km, i.e., about 250 km in the radial direction). Finally, for multiple shock crossings, the algorithm chooses the first occurrence of the shock starting from the undisturbed solar wind. Current formatting optimised for MATLAB. ACKNOWLEDGEMENTS C. Simon Wedlund and M. Volwerk thank the Austrian Science Fund (FWF) project P32035-N36. C. Möstl thanks the Austrian Science Fund FWF projects P31659-N27, P31521-N27. A. Beth thanks the Swedish National Space Agency (SNSA) and its support with the grant 108/18. This database was notably used to add to the Helio4Cast database which monitors solar wind parameters in the solar system (<a href="https://doi.org/10.6084/m9.figshare.6356420">https://doi.org/10.6084/m9.figshare.6356420</a>). Helio4Cast is available at <a href="http://www.helioforecast.space/icmecat">www.helioforecast.space/icmeca</a>t and <a href="http://www.helioforecast.space/sircat">www.helioforecast.space/sircat</a>.      LICENSE AND RIGHTS This database is shared under a Creative Commons CC-BY-4.0 license. Version 1 (c) Cyril Simon Wedlund @ Space Research Institute of Graz (IWF),                                                              Austrian Academy of Sciences (ÖAW), 2021-09-08 Version 2 (c) CSW @ ÖAW/IWF, 2021-11-30 -- Addition of R_MSO and SZA Version 3 (c) CSW @ ÖAW/IWF, 2022-02-09 -- Addition of ThetaBn Version 4 (c) CSW @ ÖAW/IWF, 2025-03-20 -- Addition of Ls, Bx, By, Bz and Bt.   Contact email:        cyril.simon.wedlund@gmail.com

opencc-by-4.0Feb 2021View details →

Polar mesospheric clouds from the Balloon Lidar Experiment (BOLIDE) during the PMC Turbo balloon mission

This dataset contains BOLIDE lidar data obtained during the PMC Turbo balloon mission that was launched on 7 July 2018 from Esrange, Sweden and landed in Nunavut, Canada on 14 July 2018. The mission was designed to study small-scale atmospheric dynamics induced by breaking atmospheric gravity waves within the polar mesospheric cloud layer at ~82 km altitude. PMC Turbo floated at around 40 km altitude and carried seven digital cameras to image the polar mesospheric cloud layer and the first Rayleigh lidar to successfully operate from a balloon. The lidar data consists of volume backscatter coefficients of polar mesospheric clouds, available at 20 m vertical and 10 s temporal resolution, contained in a compressed netcdf file. The magnitude of volume backscatter coefficients scales with the brightness of clouds imaged by the PMC Turbo cameras. The netcdf file further includes floating altitude, rotator angle (azimuth) as well as latitude and longitude of the lidar beam at 82 km altitude. Users are encouraged to contact us for discussion when using BOLIDE data. Data contact: natalie.kaifler@dlr.de References: PMC Turbo camera videos: https://svs.gsfc.nasa.gov/13073 NASA Space Physics Data Facility: https://cdaweb.gsfc.nasa.gov/index.html/, select PMC Turbo DLR Institute mission database: https://halo-db.pa.op.dlr.de/mission/112 Kaifler, N., Kaifler, B., Rapp, M., Fritts, D.C. The polar mesospheric cloud dataset of the Balloon Lidar Experiment BOLIDE. Earth System Science Data. In preparation. Kaifler, B., Rempel, D., Roßi, P., Büdenbender, C., Kaifler, N., and Baturkin, V.: A technical description of the Balloon Lidar Experiment (BOLIDE), Atmos. Meas. Tech., 13, 5681–5695, https://doi.org/10.5194/amt-13-5681-2020, 2020. Fritts, D. C., Miller, A. D., Kjellstrand, C. B., Geach, C., Williams, B. P., Kaifler, B., et al. (2019). PMC Turbo: Studying gravity wave and instability dynamics in the summer mesosphere using polar mesospheric cloud imaging and profiling from a stratospheric balloon. Journal of Geophysical Research: Atmospheres, 124, 6423– 6443. https://doi.org/10.1029/2019JD030298

opencc-by-4.0Mar 2020View details →

Drone aerial imagery of a small island in Kobbefjord (SW Greenland) acquired during Mission Arctic 2017

<code>Aerial images of a small island in Kobbefjord (SW Greenland) were acquired on 5 July 2017 using a DJI Phantom 3 Standard drone during the <a href="https://www.frontiersin.org/articles/10.3389/fmars.2021.665582/full">Mission Arctic citizen science expedition</a>. Images were processed in Agisoft Metashape. A digital elevation model (DEM) and an orthomosaic were exported at 5 cm resolution. For details, see the readme and processing report that accompanies this dataset. </code>

opencc-by-4.0Sep 2022View details →

Drone aerial imagery of a headland in Nuup Kangerlua (Godthåbsfjord, SW Greenland) acquired during Mission Arctic 2017

Aerial images of a headland in Nuup Kangerlua (Godthåbsfjord, Greenland) were acquired on 11 July 2017 using a DJI Phantom 3 Standard drone during the <a href="https://www.frontiersin.org/articles/10.3389/fmars.2021.665582/full">Mission Arctic citizen science expedition</a>. Images were processed in Agisoft Metashape. A digital elevation model (DEM) and an orthomosaic were exported at 2.5 cm resolution. A 5 cm resolution orthomosaic is also included. For details, see the readme and processing report that accompanies this dataset.

opencc-by-4.0Sep 2022View details →

Mars Target Encyclopedia - Labeled LPSC abstracts for four Mars missions

This data set contains annotated text versions of 1635 two-page abstracts published at the Lunar and Planetary Science Conference from 1998 to 2020 of relevance to four Mars missions.  The annotations were generated using named entity recognition and relation extraction provided by the MTE processing pipeline (available at https://github.com/wkiri/MTE), followed by manual review.  Annotated entities include Element, Mineral, Property, and Target.  Annotated relations include Contains(Target, Element | Mineral) and HasProperty(Target, Property).  The extracted information (without full texts) is also available as a database (stored in .csv files) at https://pds-geosciences.wustl.edu/missions/mte/mte.htm . The complete annotated texts are provided here as a resource for further research and experimentation on information extraction methods.  For more information about the Mars Target Encyclopedia and these annotations, please see: <ul> <li>"<a href="https://www.hou.usra.edu/meetings/lpsc2022/pdf/1231.pdf">Targets from the Spirit Mars Exploration Rover in the Mars Target Encyclopedia</a>", Kiri L. Wagstaff, Raymond Francis, Matthew Golombek, Steven Lu, Ellen Riloff, Leslie Tamppari, Yuan Zhuang, and Thomas Stein. 53rd Lunar and Planetary Science Conference, Abstract #1231, March 2022.</li> <li>"<a href="https://www.hou.usra.edu/meetings/lpsc2021/pdf/1278.pdf">The Mars Target Encyclopedia Now Includes Mars Pathfinder and Mars Phoenix Targets</a>", Kiri L. Wagstaff, Raymond Francis, Matthew Golombek, Steven Lu, Ellen Riloff, Leslie Tamppari, and Thomas C. Stein. 52nd Lunar and Planetary Science Conference, Abstract #1278, March 2021.</li> </ul> The original PDF abstracts are available at:  <ul> <li>For years prior to 2000:  https://www.lpi.usra.edu/meetings/LPSC${two-digit-year}/pdf/${id}.pdf</li> <li>For year 2000:  https://www.lpi.usra.edu/meetings/LPSC${four-digit-year}/pdf/${id}.pdf</li> <li>For years 2001-2017 (note lower-case lpsc):  https://www.lpi.usra.edu/meetings/lpsc${four-digit-year}/pdf/${id}.pdf</li> <li>For years 2018-2020:  https://www.hou.usra.edu/meetings/lpsc${four-digit-year}/pdf/${id}.pdf</li> </ul> where ${id} is a four-digit abstract number, starting with 1001 (if available). The text files provided in this archive were extracted from the PDF files using the Apache Tika PDF parsing tool.  They are named as ${four-digit-year}_${id}.txt.  The text is provided here so that the annotations can be viewed in context.  The text content remains copyright of the original abstract authors. The annotations (entities and relations) are provided in the format used by the brat annotation tool.  They are named as ${four-digit-year}_${id}.ann. To view the annotations in a web-based graphical form, install the brat tool (http://brat.nlplab.org/).  These annotations were generated using brat v1.3.  The annotation files are also human-readable and can be parsed in to be used directly in code.  If the .ann file is empty, then there are no relevant annotations for the associated text file. Contents: <ul> <li>mpf.zip: 591 abstracts relating to the Mars Pathfinder mission (1998-2020)</li> <li>mer-a.zip: 397 abstracts relating to the MER-A (Spirit) rover mission (2004-2020)</li> <li>mer-b.zip: 256 abstracts relating to the MER-B (Opportunity) rover mission (2005-2020)</li> <li>phx.zip: 391 abstracts relating to the Mars Phoenix Lander mission (2009-2020)</li> </ul> Each directory contains a .txt and .ann file for each abstract.  The .ann file is in brat standoff format (http://brat.nlplab.org/standoff.html).  Additional .conf files are provided to generate color highlighting and keyboard shortcuts.  These are used by the brat tool. Note: the same abstract may appear in more than one mission directory, if it discusses targets from more than one mission.  It will have a different .ann file for each such appearance.  Within each directory, a "Target" annotation is understood to refer to a target of the relevant mission. Attribution: If you use this data set in your own work, please cite it as follows: Kiri L. Wagstaff, Raymond Francis, Matthew Golombek, Leslie Tamppari, and Steven Lu. (2022). Mars Target Encyclopedia - Labeled LPSC abstracts for four Mars missions (1.0.0.0) [Data set]. Zenodo. DOI: 10.5281/zenodo.7066107