adsabs/AstroCLIMB huggingface dataset:
Paper: A Multiannual Record of Convective Instability in Mars’s Middle Atmosphere from the Mars Climate Sounder
Authors: Nicholas G. Heavens, Alexey Pankine, J. Michael Battalio, Corwin Wright, David M. Kass, Armin Kleinböhl
Figure caption: Mean probability of convective instability, MY 29–33, MY 35–36 for the labeled time of day, L  s  range, and pressure level. Binning resolution in latitude and longitude is 2°.
Paper: A Multiannual Record of Convective Instability in Mars’s Middle Atmosphere from the Mars Climate Sounder
Authors: Nicholas G. Heavens, Alexey Pankine, J. Michael Battalio, Corwin Wright, David M. Kass, Armin Kleinböhl
Figure caption: The mean probability of convective instability on the dayside (%) for a vertical cross section averaged over 15° S–15° N. The average is weighted by the cosine of the latitude. Red letters mark the estimated peak of activity for the major dust event compilation described in Section 2.3. Binning resolution in L  s  is 2°. Zonal averages are only shown when data is available in all 12 of the 30° bins in longitude.
Paper: A Multiannual Record of Convective Instability in Mars’s Middle Atmosphere from the Mars Climate Sounder
Authors: Nicholas G. Heavens, Alexey Pankine, J. Michael Battalio, Corwin Wright, David M. Kass, Armin Kleinböhl
Figure caption: The mean probability of convective instability (%) on the nightside for a vertical cross section averaged over 90°–45° S. The average is weighted by the cosine of the latitude. Red letters mark the estimated peak of activity for the major dust event compilation described in Section 2.3. Binning resolution in L  s  is 2°. Zonal averages are only shown when data is available in all 12 of the 30° bins in longitude.
Paper: A Multiannual Record of Convective Instability in Mars’s Middle Atmosphere from the Mars Climate Sounder
Authors: Nicholas G. Heavens, Alexey Pankine, J. Michael Battalio, Corwin Wright, David M. Kass, Armin Kleinböhl
Figure caption: The mean probability of convective instability on the dayside (%) for a vertical cross section averaged over 90°–45° S. The average is weighted by the cosine of the latitude. Red letters mark the estimated peak of activity for the major dust event compilation described in Section 2.3. Binning resolution in L  s  is 2°. Zonal averages are only shown when data is available in all 12 of the 30° bins in longitude.
Paper: A Multiannual Record of Convective Instability in Mars’s Middle Atmosphere from the Mars Climate Sounder
Authors: Nicholas G. Heavens, Alexey Pankine, J. Michael Battalio, Corwin Wright, David M. Kass, Armin Kleinböhl
Figure caption: The mean probability of convective instability on the nightside (%) for a vertical cross section averaged over 60°–90° N. The average is weighted by the cosine of the latitude. Red letters mark the estimated peak of activity for the major dust event compilation described in Section 2.3. Binning resolution in L  s  is 2°. Values less than 1% are shown in the deepest purple color. Zonal average required to sample all 12 of the 30° bins in the longitude to be shown.
Paper: A Multiannual Record of Convective Instability in Mars’s Middle Atmosphere from the Mars Climate Sounder
Authors: Nicholas G. Heavens, Alexey Pankine, J. Michael Battalio, Corwin Wright, David M. Kass, Armin Kleinböhl
Figure caption: Mean probability of convective instability on the nightside at 2.8 Pa from 0° to 30° N for the Mars years labeled. The top panel shows the analysis during 34P, while the bottom panel shows a climatology that excludes planetary-scale and Z dust events. Binning resolution in longitude is 10° and 2° in L  s . Values less than 1% are shown in the deepest purple color. Missing data is in white.
Paper: A Multiannual Record of Convective Instability in Mars’s Middle Atmosphere from the Mars Climate Sounder
Authors: Nicholas G. Heavens, Alexey Pankine, J. Michael Battalio, Corwin Wright, David M. Kass, Armin Kleinböhl
Figure caption: Mean nightside (2–4 AM LST) temperature (K) averaged over 0°–10° N, 60°–90° W from MRO-MCS temperature profiles for the labeled Mars Years. Binning is by 1° of L  s . The axes, labels, and color scale approximate that used in Figure 2 of Steele et al. (2021a).
Paper: A Multiannual Record of Convective Instability in Mars’s Middle Atmosphere from the Mars Climate Sounder
Authors: Nicholas G. Heavens, Alexey Pankine, J. Michael Battalio, Corwin Wright, David M. Kass, Armin Kleinböhl
Figure caption: Zonal mean probability of convective instability on the nightside for the Mars years and L  s  bins labeled. The top row of panels shows 28P, while the bottom row of panels shows a climatology of years without planet-encircling dust events. Binning resolution in latitude is 2°.
Paper: A Multiannual Record of Convective Instability in Mars’s Middle Atmosphere from the Mars Climate Sounder
Authors: Nicholas G. Heavens, Alexey Pankine, J. Michael Battalio, Corwin Wright, David M. Kass, Armin Kleinböhl
Figure caption: Zonal mean probability of convective instability on the nightside for the Mars years and L  s  bins labeled. The top row of panels shows 34P, while the bottom row of panels shows a climatology of years without planetary-scale and Z dust events. Binning resolution in latitude is 2°.
Paper: A Multiannual Record of Convective Instability in Mars’s Middle Atmosphere from the Mars Climate Sounder
Authors: Nicholas G. Heavens, Alexey Pankine, J. Michael Battalio, Corwin Wright, David M. Kass, Armin Kleinböhl
Figure caption: Zonal mean probability of convective instability on the dayside for the Mars years and L  s  bins labeled. The top row of panels shows 28P, while the bottom row of panels shows a climatology of years without planetary-scale dust events. Binning resolution in latitude is 2°.
Paper: A Multiannual Record of Convective Instability in Mars’s Middle Atmosphere from the Mars Climate Sounder
Authors: Nicholas G. Heavens, Alexey Pankine, J. Michael Battalio, Corwin Wright, David M. Kass, Armin Kleinböhl
Figure caption: Zonal mean probability of convective instability on the dayside for the Mars years and L  s  bins labeled. The top row of panels shows 34P, while the bottom row of panels shows a climatology of years without planetary-scale and Z dust events. Binning resolution in latitude is 2°.
Paper: Formation, Structure, and Detectability of the Geminids Meteoroid Stream
Authors: W. Z. Cukier, J. R. Szalay
Figure caption: Number column density of the Geminids stream in the x–y plane as described by the Basic Model (left), Violent Creation Model (middle), and Cometary Creation Model (right) during the last two years of simulation. Densities are normalized to 1 in each panel independently. The green ellipse is the orbit of (3200) Phaethon; the orange curve is the orbit of PSP during the anomalous spike in dust flux. All panels are in ecliptic J2000 coordinates. Note that particles with a semimajor axis of a < 0.2 were removed from the simulations, leading to the discontinuity in density near the Sun in the Cometary Creation Model. The top panels show “large particles,” which are defined as particles with m > 10−5 g, which are the particles that we consider at Earth in Section 3.2. The bottom panels show ”small particles,” which are defined as particles with m < 10−7 g.
Paper: Formation, Structure, and Detectability of the Geminids Meteoroid Stream
Authors: W. Z. Cukier, J. R. Szalay
Figure caption: Top: plots of number column density in the plane of the orbit of (3200) Phaethon for the Basic Model (left), Violent Creation Model (middle), and Cometary Creation Model (right) during the last two years of simulation. Superposed on these plots is the orbit of (3200) Phaethon (yellow solid line) and the fitted core of the modeled stream (dashed green line). Bottom: the relative number of particles at each signed offset from the orbit of (3200) Phaethon as a function of mean anomaly. Cyan and dark green points in the bottom panels show the center of the radial bins of maximum density for each mean anomaly bin. The dashed line is a parabolic fit to those points and is taken to represent the core of the stream. Coefficients of the parabolic fit can be found in Table 2.
Paper: Formation, Structure, and Detectability of the Geminids Meteoroid Stream
Authors: W. Z. Cukier, J. R. Szalay
Figure caption: Plot of the normalized impactor flux upon Earth as predicted during the last two years of simulation by the Basic Model (blue dashed line), the Violent Creation Model (orange dotted line), and the Cometary Creation Model (green dotted–dashed line) compared to observational data taken from CMOR (solid red line; Jones et al. 2005).
Paper: Formation, Structure, and Detectability of the Geminids Meteoroid Stream
Authors: W. Z. Cukier, J. R. Szalay
Figure caption: The relative number of particles located at each point around the “unwrapped” orbit of (3200) Phaethon for the Basic Model (left), Violent Creation Model (middle), and the Cometary Creation Model (right) during the last two years of simulation. To create this figure each particle was radially projected onto the orbit of (3200) Phaethon and then the distance between that point and the particle was calculated. The white area in the rightmost panel represents locations where no particles exist and is caused by some combination of the removal of particles that are too close to the Sun and the fact that few or no particles exist outside the orbit of (3200) Phaethon in the Cometary Model.
Paper: Formation, Structure, and Detectability of the Geminids Meteoroid Stream
Authors: W. Z. Cukier, J. R. Szalay
Figure caption: Number column density of the Geminids stream in the x–y (top) and y–z (bottom) planes as described by the Basic Model (left), Violent Creation Model (middle), and Cometary Creation Model (right) during the last two years of simulation. Densities are normalized to 1 in each panel independently. The green ellipse is the orbit of (3200) Phaethon; the orange curve is the orbit of PSP during the anomalous spike in dust flux. All panels are in ecliptic J2000 coordinates. Note that particles with a semimajor axis of a < 0.2 were removed from the simulations, leading to the discontinuity in density near the Sun in the Cometary Creation Model.
Paper: Formation, Structure, and Detectability of the Geminids Meteoroid Stream
Authors: W. Z. Cukier, J. R. Szalay
Figure caption: Dust flux incident on the Parker Solar Probe from the Geminids stream around perihelion of orbit 4 of PSP as predicted during the last two years of simulation by the various models and compared with the observed dust flux showing the post-perihelion enhancement. Dust flux was modeled using the density of meteoroids within 0.05 au of PSP. PSP impact rates are from previously published observations (Szalay et al. 2021).
Paper: Formation, Structure, and Detectability of the Geminids Meteoroid Stream
Authors: W. Z. Cukier, J. R. Szalay
Figure caption: Time evolution of the orbital elements of the average particle in the primary stream (m > 10−8 g) from the model variants and for (3200) Phaethon. All elements are measured in the ecliptic J2000 frame. Top left: semimajor axis. Top right: eccentricity. Middle left: inclination (deg). Middle right: argument of pericenter (deg). Bottom: longitude of ascending node (deg).
Paper: Constraining the Limitations of NEATM-like Models: A Case Study with Near-Earth Asteroid (285263) 1998 QE2
Authors: Samuel A. Myers, Ellen S. Howell, Christopher Magri, Ronald J. Vervack, Yanga R. Fernández, Sean E. Marshall, Patrick A. Taylor
Figure caption: Processed LXD data sets for each night of observations with SpeX and NEOWISE. (a–f) SpeX data for each of the six nights. The different letters within each panel indicate different data sets collected each night (Table 1). The y-axis is normalized flux, normalized to 1.6 μm. (Note that there is no significant thermal contamination at this wavelength.) (g) NEOWISE data in absolute flux density. Note that the NEOWISE data are plotted over a different wavelength range. We plot both the 1σ and 3σ uncertainties. (h) The “A“ data set for each night of SpeX data. These spectra highlight how different viewing geometries across the different nights produce a range of spectral slopes. We see that changes in viewing geometry produce changes in the spectra shape both within nights and across all nights of observations. Modeling these differences allows us to place tighter constraints on NEA properties.
Paper: Constraining the Limitations of NEATM-like Models: A Case Study with Near-Earth Asteroid (285263) 1998 QE2
Authors: Samuel A. Myers, Ellen S. Howell, Christopher Magri, Ronald J. Vervack, Yanga R. Fernández, Sean E. Marshall, Patrick A. Taylor
Figure caption: Sub-Earth locations on QE2 during observations as determined by a radar shape model (Springmann et al. 2014). (a) The pole solution with the “bumpy” topography in the northern hemisphere. (b) The pole solution with the topography partially in the southern hemisphere (Section 2.3). The range of sub-Earth locations observed indicates that QE2 was observed across multiple different viewing geometries. This range of observations is key for constraining QE2's parameters using our NEATM-like model.
Paper: Constraining the Limitations of NEATM-like Models: A Case Study with Near-Earth Asteroid (285263) 1998 QE2
Authors: Samuel A. Myers, Ellen S. Howell, Christopher Magri, Ronald J. Vervack, Yanga R. Fernández, Sean E. Marshall, Patrick A. Taylor
Figure caption: Plot of fitted beaming parameters as a function of solar phase angle adjusted so that 0° corresponds to QE2's minimum phase angle during its close approach to Earth. We also compare our beaming parameters to those found by Moskovitz et al. (2017). Note the introduction of negative phase angles to differentiate between observations taken before (positive values) and after (negative values) opposition. The error bars represent the range of beaming parameters. The range is calculated by identifying models that fit the data with fixed albedo and thermal inertia (Section 4). Moskovitz et al. (2017) values are taken from their Figure 3. We see that our data exhibit roughly the same trend where the data overlap, but that our beaming values are significantly offset from the Moskovitz et al. (2017) values.
Paper: Constraining the Limitations of NEATM-like Models: A Case Study with Near-Earth Asteroid (285263) 1998 QE2
Authors: Samuel A. Myers, Ellen S. Howell, Christopher Magri, Ronald J. Vervack, Yanga R. Fernández, Sean E. Marshall, Patrick A. Taylor
Figure caption: Final best-fit space for the visible geometric albedo and thermal inertia for QE2 using our simple, NEATM-like model. The color of the points represents the number of data sets that are fit by the associated parameter values. A cooler color means that the given parameters are consistent with more data sets. White indicates models consistent with ≤ 2 data sets. The black line outlines the region of best fit. This region corresponds to the region of overlap between all the individual model ranges found to fit each individual data set (Section 4). There is a correlation such that higher thermal inertias require lower albedos. All models were run with the same fixed model inputs listed in Section 3 and using ephemeris inputs listed in Table 1. This figure is generated using the results from the 1σ uncertainties on the NEOWISE data.
Paper: Constraining the Limitations of NEATM-like Models: A Case Study with Near-Earth Asteroid (285263) 1998 QE2
Authors: Samuel A. Myers, Ellen S. Howell, Christopher Magri, Ronald J. Vervack, Yanga R. Fernández, Sean E. Marshall, Patrick A. Taylor
Figure caption: The variation in NEATM-like models that were accepted to fit the data for each data set. Any models within the shaded region are considered to fit the data. All other models for the given data set are discarded, as they are poor fits to the data. An objective function is used to identify which models fall within the shown region (Section 4). (a–f) SpeX data. The y-axis is normalized flux. The spectra are offset for clarity. (g) NEOWISE data in absolute flux density. Note that the NEOWISE data are plotted over a different wavelength range. For the NEOWISE data we examine models that fit within both the 1σ and 3σ uncertainties. Both regions are shown.
Paper: Constraining the Limitations of NEATM-like Models: A Case Study with Near-Earth Asteroid (285263) 1998 QE2
Authors: Samuel A. Myers, Ellen S. Howell, Christopher Magri, Ronald J. Vervack, Yanga R. Fernández, Sean E. Marshall, Patrick A. Taylor
Figure caption: A range of NEATM-like models compared to one of our SpeX data sets. As either the albedo or thermal inertia changes monotonically, the models correspondingly change monotonically across the data. This property allows us to identify a range of models that fit the data and is typical to all of our data sets. All models that fall within the 1σ error bars of the data would be considered good fits to the data. As such, in this case only the p  V  = 0.06 and Γ = 100 TIU model would be considered a good fit. Models shown here all have η = 0.86. Changes in beaming parameter can also monotonically affect how the models fit to the data.
Paper: Constraining the Limitations of NEATM-like Models: A Case Study with Near-Earth Asteroid (285263) 1998 QE2
Authors: Samuel A. Myers, Ellen S. Howell, Christopher Magri, Ronald J. Vervack, Yanga R. Fernández, Sean E. Marshall, Patrick A. Taylor
Figure caption: Reduced χ 2 maps for each of the spectra as fit by our simple, NEATM-like model. Warmer colors mean higher values (worse fits), and cooler colors mean lower values (better fits). Note that different max values are used for different spectra, as the reduced χ 2 are not directly comparable across different spectra (Section 4). Each χ 2 map is equivalent to showing the range of models that fit a given data set. The fit space of the NEOWISE data corresponds to the 1σ uncertainties
Paper: Constraining the Limitations of NEATM-like Models: A Case Study with Near-Earth Asteroid (285263) 1998 QE2
Authors: Samuel A. Myers, Ellen S. Howell, Christopher Magri, Ronald J. Vervack, Yanga R. Fernández, Sean E. Marshall, Patrick A. Taylor
Figure caption: Radar image of QE2 taken by the Arecibo Telescope on 2013 June 10. The vertical extent of the image shows distance from the observer to the terminator of the object. The horizontal extent shows Doppler shift, with blueshift to redshift going left to right. The resolution of the pixels, combined with knowledge of the speed of light, directly gives the object’s radius. In this image, QE2 covers 210 pixels in the vertical extent at 7.5 m pixel−1, giving an apparent radius of 1575 m or a diameter of 3.15 km.
Paper: Constraining the Limitations of NEATM-like Models: A Case Study with Near-Earth Asteroid (285263) 1998 QE2
Authors: Samuel A. Myers, Ellen S. Howell, Christopher Magri, Ronald J. Vervack, Yanga R. Fernández, Sean E. Marshall, Patrick A. Taylor
Figure caption: Sky views of QE2 on 2013 July 10 that show the radar shape model from Springmann et al. (2014). The arrows indicate the pole and spin direction. Left: the A solution with a pole position of λ = 119° and β = 55°. Right: the B solution with a pole position of λ = 158° and β = 41°.
Paper: Constraining the Limitations of NEATM-like Models: A Case Study with Near-Earth Asteroid (285263) 1998 QE2
Authors: Samuel A. Myers, Ellen S. Howell, Christopher Magri, Ronald J. Vervack, Yanga R. Fernández, Sean E. Marshall, Patrick A. Taylor
Figure caption: Plot of predicted apparent magnitudes for QE2 compared to all magnitudes reported to the MPC. All observations are from 2013 during QE2's close approach to Earth. The predicted apparent magnitudes were calculated using ephemeris from JPL Horizons at 1-day intervals throughout 2013. We used H = 16.0 (a value from our modeled H-magnitude range) and H = 17.3 (the H-magnitude from Moskovitz et al. 2017), as well as a range of G values. We see that a lower H-magnitude, more consistent with our modeled range, agrees with the data for low G values.
Paper: Constraining the Limitations of NEATM-like Models: A Case Study with Near-Earth Asteroid (285263) 1998 QE2
Authors: Samuel A. Myers, Ellen S. Howell, Christopher Magri, Ronald J. Vervack, Yanga R. Fernández, Sean E. Marshall, Patrick A. Taylor
Figure caption: Plot of NEATM-like models with varying visual geometric albedos across a selected range of dates. The data sets shown for May 30 and June 15 are the “A” data sets. All models shown have thermal inertia and beaming parameters that are within the best-fit ranges for the given date. Each row is a different data set. The left panels show the tail region, and the right panels show the thermally dominated region. We see that for July 10 A the models that fit the thermally dominated region do not fit the tail region and vice versa. An increase in albedo of ∼0.02 is required to fit the tail region for July 10 A. This is indicative of some kind of surface inhomogeneity.
Paper: Constraining the Limitations of NEATM-like Models: A Case Study with Near-Earth Asteroid (285263) 1998 QE2
Authors: Samuel A. Myers, Ellen S. Howell, Christopher Magri, Ronald J. Vervack, Yanga R. Fernández, Sean E. Marshall, Patrick A. Taylor
Figure caption: Plot of best-fit models from Moskovitz et al. (2017) compared to our longer-wavelength data. These models are generated using our simple, NEATM-like model. All data sets shown are the “A” data set for the given date. All models shown have zero thermal inertia and albedos of 0.03, as per the Moskovitz et al. (2017) fits. The shown η values correspond to the ranges reported for each date by Moskovitz et al. (2017). The left panels show the tail region, and the right panels show the thermally dominated region. We see that the models fit the tail region well, as expected. However, we note that these models do not fit the thermally dominated region. This discrepancy may explain why we find different modeled beaming parameters than Moskovitz et al. (2017).
Paper: Constraining the Limitations of NEATM-like Models: A Case Study with Near-Earth Asteroid (285263) 1998 QE2
Authors: Samuel A. Myers, Ellen S. Howell, Christopher Magri, Ronald J. Vervack, Yanga R. Fernández, Sean E. Marshall, Patrick A. Taylor
Figure caption: SHERMAN model results for June 8 and July 10 using both the A and B pole solutions. All models have a visual geometric albedo of 0.053, thermal inertia of 200 TIU, and crater fraction of 70%. We see a clear preference for the B pole solution in the June 8 data and a slight preference for the B pole solution in the July 10 data. Thus, we see that QE2's topography may be playing a role in shaping its thermal emission. We also note that the albedo and thermal inertia are consistent with our NEATM-like model.
Paper: Outgassing Composition of the Murchison Meteorite: Implications for Volatile Depletion of Planetesimals and Interior-atmosphere Connections for Terrestrial Exoplanets
Authors: Maggie A. Thompson, Myriam Telus, Graham Harper Edwards, Laura Schaefer, Jasmeet Dhaliwal, Brian Dreyer, Jonathan J. Fortney, Kyle Kim
Figure caption: Average normalized intensities from the unheated Murchison samples and the 						set of stepped-heating experiments performed in a high-vacuum environment 							(∼10−4Pa/10−9 bar). (a) Intensities normalized to 						V; (b) intensities normalized to V and the average of the two unheated 						Murchison samples. The analytical uncertainties in panels (a) and (b) are 						the 1σ standard deviations for the normalized 						data propagated from the RSD uncertainties of Table 9. In panel (a), the uncertainties are smaller 						than the data points. In panel (b), the red vertical line represents the 						reproducibility between the V-normalized intensities of the two unheated 						Murchison samples, expressed as the maximum relative difference calculated 						using Equation (1). 						The x-axes are the same as in Figure 2.