Estimation of Titan Atmosphere Density by Cassini SCO AACS Operations Team
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reconstruction↗
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Reconstructed Historical Land Cover and Biophysical Parameters for Studies of Land-Atmosphere Interactions within the Eastern United States
The local environment where we live within the Earth's biosphere is often taken for granted. This environment can vary depending on whether the land cover is a forest, grassland, wetland, water body, bare soil, pastureland, agricultural field, village, residential suburb, or an urban complex with concrete, asphalt, and large buildings. In general, the type and characteristics of land cover influence surface temperatures, sunlight exposure and duration, relative humidity, wind speed and direction, soil moisture amount, plant life, birds, and other wildlife in our backyards. The physical and biological properties (biophysical characteristics) of land cover help to determine our surface environment because they directly affect surface radiation, heat, and soil moisture processes, and also feedback to regional weather and climate. Depending on the spatial scale and land use intensity, land cover changes can have profound impacts on our local and regional environment. Over the past 350 years, the eastern half of the United States, an area extending from the grassland prairies of the Great Plains to the Gulf and Atlantic coasts, has experienced extensive land cover and land use changes that began with land clearing in the 1600s, led to extensive deforestation and intensive land use practices by 1920, and then evolved to the present-day landscape. Determining the consequences of such land cover changes on regional and global climate is a major research issue. Such research requires detailed historical land cover data and modeling experiments simulating historical climates. Given the need to understand the effects of historical land cover changes in the eastern United States, some questions include: - What were the most important land cover transformations and how did they alter biophysical characteristics of the land cover at key points in time since the mid-1600s? - How have land cover and land use changes over the past 350 years affected the land surface environment including surface weather, hydrologic, and climatic variability? - How do the potential effects of regional human-induced land cover change on the environment compare to similar changes that are caused by the natural variations of the Earth's climate system? To help answer these questions, we reconstructed a fractional land cover and biophysical parameter dataset for the eastern United States at 1650, 1850, 1920, and 1992 time-slices. Each land cover fraction is associated with a biophysical parameter class, a suite of parameters defining the biophysical characteristics of that kind of land cover. This new dataset is designed for use in computer models of land-atmosphere interactions, to understand and quantify the effects of historical land cover changes on the water, energy, and carbon cycles
Steyaert, Louis T.↗
Sensitivity of the GAPS experiment to low-energy cosmic-ray antiprotons
The General Antiparticle Spectrometer (GAPS) is an upcoming balloon mission to measure low-energy cosmic-ray antinuclei during at least three ~35-day Antarctic flights. With its large geometric acceptance and novel exotic atom-based particle identification, GAPS will detect ~500 cosmic antiprotons per flight and produce a precision cosmic antiproton spectrum in the kinetic energy range of ~0.07–0.21 GeV/n at the top of the atmosphere. With these high statistics extending to lower energies than any previous experiment, and with complementary sources of experimental uncertainty compared to traditional magnetic spectrometers, the GAPS antiproton measurement will be sensitive to dark matter, primordial black holes, and cosmic ray propagation. The antiproton measurement will also validate the GAPS antinucleus identification technique for the antideuteron and antihelium rare-event searches. Finally, this analysis demonstrates the GAPS sensitivity to cosmic-ray antiprotons using a full instrument simulation and event reconstruction, and including solar and atmospheric effects.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Using Onboard Telemetry for MAVEN Orbit Determination
Determination of the spacecraft state has been traditional done using radiometric tracking data before and after the atmosphere drag pass. This paper describes our approach and results to include onboard telemetry measurements in addition to radiometric observables to refine the reconstructed trajectory estimate for the Mars Atmosphere and Volatile Evolution Mission (MAVEN). Uncertainties in the Mars atmosphere models, combined with non-continuous tracking degrade navigation accuracy, making MAVEN a key candidate for using onboard telemetry data to help complement its orbit determination process.
orbit determination↗
Reconstruction of Thermal Protection System Aeroheating using a Green’s Function Approach
Inverse heat transfer (IHT) techniques are often used to reconstruct the surface heating conditions on spacecraft thermal protection systems (TPS) during atmospheric entry. Current IHT techniques for entry spacecraft applications, however, demand substantial computational resources, and are impractical for analyses such as uncertainty quantification and real-time health monitoring. In this paper, a Green’s function sensor fusion approach is used to reconstruct the TPS surface aeroheating conditions on experimental spaceflight and ground test systems from collocated temperature and heat flux sensors embedded in the TPS. The algorithm leverages Green’s functions to model the heat conduction within the spacecraft TPS and stabilizes the recovery of the surface heating condition using the direct heat flux sensor measurement. The algorithm is validated using arc-jet ground test data and applied to the reconstruction of the Mars 2020 backshell heating during Martian atmospheric entry. The performance of the algorithm is benchmarked against a current state-of-the-art IHT framework, FIAT_Opt. The Green’s function-based reconstruction algorithm recovers the net hot-wall heat flux absorbed by the TPS and the incident heat flux from the atmospheric entry environment in close agreement with FIAT_Opt. Notably, computation of the surface heating condition is completed in three orders of magnitude less time with the Green’s function sensor fusion approach using a consumer-grade PC, versus with FIAT_Opt running on a high performance computer cluster. The efficiency of the algorithm is leveraged to compute the uncertainty contributions of input parameters to the total uncertainty in reconstructed Mars 2020 backshell heating for the full atmospheric entry heat pulse. The sensitivity analysis uncovers that, at different times throughout the entry heat pulse, uncertainties in the TPS specific heat, thermal conductivity, and emissivity are all dominant drivers of the reconstruction uncertainty. These results demonstrate Green’s functions and sensor-fusion techniques as promising IHT approaches to reconstruct atmospheric entry environments from TPS-embedded measurements, and highlight how these techniques may give access to post-flight analyses previously hindered by the prohibitive cost of current methods.
Kenneth McAfee↗
Reconstruction of Thermal Protection System Aeroheating using a Green’s Function Approach
Inverse heat transfer (IHT) techniques are often used to reconstruct the surface heating conditions on spacecraft thermal protection systems (TPS) during atmospheric entry. Current IHT techniques for entry spacecraft applications, however, demand substantial computational resources, and are impractical for analyses such as uncertainty quantification and real-time health monitoring. In this paper, a Green’s function sensor fusion approach is used to reconstruct the TPS surface aeroheating conditions on experimental spaceflight and ground test systems from collocated temperature and heat flux sensors embedded in the TPS. The algorithm leverages Green’s functions to model the heat conduction within the spacecraft TPS and stabilizes the recovery of the surface heating condition using the direct heat flux sensor measurement. The algorithm is validated using arc-jet ground test data and applied to the reconstruction of the Mars 2020 backshell heating during Martian atmospheric entry. The performance of the algorithm is benchmarked against a current state-of-the-art IHT framework, FIAT_Opt. The Green’s function-based reconstruction algorithm recovers the net hot-wall heat flux absorbed by the TPS and the incident heat flux from the atmospheric entry environment in close agreement with FIAT_Opt. Notably, computation of the surface heating condition is completed in three orders of magnitude less time with the Green’s function sensor fusion approach using a consumer-grade PC, versus with FIAT_Opt running on a high performance computer cluster. The efficiency of the algorithm is leveraged to compute the uncertainty contributions of input parameters to the total uncertainty in reconstructed Mars 2020 backshell heating for the full atmospheric entry heat pulse. The sensitivity analysis uncovers that, at different times throughout the entry heat pulse, uncertainties in the TPS specific heat, thermal conductivity, and emissivity are all dominant drivers of the reconstruction uncertainty. These results demonstrate Green’s functions and sensor-fusion techniques as promising IHT approaches to reconstruct atmospheric entry environments from TPS-embedded measurements, and highlight how these techniques may give access to post-flight analyses previously hindered by the prohibitive cost of current methods.
Kenneth McAfee↗
Cosmogenic 10Be constraints on deglacial snowline rise in the Southern Alps, New Zealand
We report geochronological dating of glacial landforms, such as terminal and lateral moraines, is useful for determining the extent and timing of past glaciation and for reconstructing the magnitude and rate of past climate changes. In the Southern Alps of New Zealand, well-dated glacial geomorphological records constrain the last glacial cycle across much of the Waitaki River basin (e.g. Ōhau, Pukaki, Tekapo) but its southern sector such as the Ahuriri River valley remains comparatively unconstrained. Recently, there has been debate on the scale and rapidity of mountain glacier retreat during the last glacial termination, particularly the 20–17 ka period in New Zealand. Missing from this debate is well-constrained equilibrium-line altitude (ELA) and associated temperature reconstructions, particularly over the period around 17 ka, which can help us to develop a more complete picture of how past temperature changes drove glacier retreat. Here we report the first glacial chronology dataset from the Last Glacial Maximum (LGM) and subsequent deglaciation from the Ahuriri River valley, Southern Alps, New Zealand (44°23'54"S, 169°39'48"E) based on 38 beryllium-10 ( 10 Be) surface-exposure ages from terminal moraine systems and glaciated bedrock situated at the lower and middle sections of the valley. Our results show that the former Ahuriri Glacier reached its maximum extent at 19.8 ± 0.3 ka, which coincides with the global Last Glacial Maximum. By 16.7 ± 0.3 ka, the glacier had retreat ~18 km up-valley suggesting at least ~43% glacier-length loss relative to its full LGM extent. This deglaciation was accompanied by the formation of a shallow proglacial lake. Using the accumulation area ratio (AAR) method, we estimate that the ELA was lower than present by ~880 m (~1120 m a.s.l.) at 19.8 ± 0.3 ka, and ~770 m lower (~1230 m a.s.l.) at 16.7 ± 0.3 ka. Applying an estimate for temperature lapse rate, this ELA anomaly implies that local air temperature was 5 ± 1 °C colder than present (1981–2010) at 19.8 ± 0.3 ka, while it was 4.4 ± 0.9 °C colder at 16.7 ± 0.3 ka, assuming no change in precipitation. The substantial glacier retreat in response to a relatively small accompanying increases in ELA (110 m) and temperature (0.6 °C) may have been a result of the high glacier-length sensitivity of this glacier system due to its low gradient of former ice surface. Our low warming estimate differs markedly from other deglaciation studies, specifically from Rakaia River valley, which reports a much larger temperature increase at the onset of the last deglaciation. This precisely-dated moraine record along with reconstructed ELA as proxies for atmospheric conditions, provides new insight into post LGM glacier behaviour and climate conditions in New Zealand.
58 GEOSCIENCES↗
Wind tunnels
Supersonic wind tunnel test data, angle of attack envelope computations, and accelerometer package for reconstructing density profile of unknown atmosphere
ACCELEROMETER↗
Analytical inversions in remote sensing of particle size distributions. I - Multispectral extinctions in the anomalous diffraction approximation. II Angular and spectral scattering in diffraction approximations
Consideration is given to analytical inversions in the remote sensing of particle size distributions, noting multispectral extinctions in anomalous diffraction approximation and angular and spectral scattering in diffraction approximation. A closed-form analytical inverse solution is derived in order to reconstruct the size distribution of atmospheric aerosols. The anomalous diffraction approximation to Mie's solution is used to describe the particles. Experimental data yield the geometrical area of aerosol polydispersion. Size distribution is thus found from a set of multispectral extinction measurements. In terms of the angular and spectral scattering of light in a narrow forward cone, it is shown that an analytical inverse solution may also be found for the Fraunhofer approximation to the Kirchhoff diffraction, and for an improved expression of this approximation due to Penndorf (1962) and Shifrin-Punina (1968).
Fymat, A. L.↗
Remote sensing of environmental particulate pollutants - Optical methods for determinations of size distribution and complex refractive index
A unifying approach, based on a generalization of Pearson's differential equation of statistical theory, is proposed for both the representation of particulate size distribution and the interpretation of radiometric measurements in terms of this parameter. A single-parameter gamma-type distribution is introduced, and it is shown that inversion can only provide the dimensionless parameter, r/ab (where r = particle radius, a = effective radius, b = effective variance), at least when the distribution vanishes at both ends. The basic inversion problem in reconstructing the particle size distribution is analyzed, and the existing methods are reviewed (with emphasis on their capabilities) and classified. A two-step strategy is proposed for simultaneously determining the complex refractive index and reconstructing the size distribution of atmospheric particulates.
Fymat, A. L.↗
Data recording and processing for speckle image reconstruction
Image reconstruction from astronomical speckle data using the Knox-Thompson algorithm has now been extensively demonstrated as feasible through analysis and computer simulations. Experimental verification of the technique and its implementation for astronomy places stringent constraints on the recording system and requires complex processing algorithms to handle the many experimental details. In this paper we describe a video recording system specifically designed for the requirements of speckle imaging. This system has been built and tested, yielding high quality image reconstructions from a laboratory-atmospheric simulator for a wide range of input light levels and test objects.
Nisenson, P.↗
Use of Forecast Atmosphere for Earth Entry, Descent, and Landing Modeling
Flight mechanics simulations are used to characterize the performance of Earth entry, descent, and landing vehicles. Atmospheric prediction models are often a key component of these simulations. Global atmospheric models are used for both engineering design due to their ability to define atmospheric properties over a large swath of locations and times as well as used for the availability of atmospheric uncertainties in the models that can be used in statistical performance analysis. However for day-of-flight operations, the use of forecast atmospheres based on more current measurements are beneficial to the accuracy of the performance prediction, including landing locations. Reanalysis of these forecasts can also be used for post-flight analysis, including trajectory reconstruction. This paper describes how forecast atmospheres can be beneficial for Earth entry, descent, and landing analysis and ways these models can be implemented in simulations.
Soumyo Dutta↗
Mars Science Laboratory (MSL) Entry, Descent, and Landing Instrumentation (MEDLI): Complete Flight Data Set
The Mars Science Laboratory (MSL) entry vehicle (EV) successfully entered the Mars atmosphere and landed the Curiosity rover safely on the surface of the planet in Gale crater on August 6, 2012. MSL carried the MSL Entry, Descent, and Landing (EDL) Instrumentation (MEDLI). MEDLI delivered the first in-depth understanding of the Mars entry environments and the response of the entry vehicle to those environments. MEDLI was comprised of three major subsystems: the Mars Entry Atmospheric Data System (MEADS), the MEDLI Integrated Sensor Plugs (MISP), and the Sensor Support Electronics (SSE). Ultimately, the entire MEDLI sensor suite consisting of both MEADS and MISP provided measurements that were used for trajectory reconstruction and engineering validation of aerodynamic, atmospheric, and thermal protection system (TPS) models in addition to Earth-based systems testing procedures. This report contains in-depth hardware descriptions, performance evaluation, and data information of the three MEDLI subsystems.
Cheatwood, F. McNeil↗
TPSAS-NF1676L-20351-DND
Characterization of atmospheric variability is crucial to the design of the Entry, Descent, and Landing (EDL) activities at Mars. The distribution of dust in the Martian atmosphere has a significant impact on the atmospheric structure and variability. Information obtained through reconstruction of EDL data from past missions can be used in studying the performance of a model used in preflight atmospheric characterization for future missions. We use the Mars Weather Research and Forecasting (MarsWRF) General Circulation Model to simulate the atmospheric temperature during the landing time periods of Mars Exploration Rovers MER-A and MER-B in 2004. The multi-scale capability of MarsWRF is useful for conducting high- resolution nested simulation centered at the landing site. This version of MarsWRF includes a high spectral accuracy k-distribution radiative transfer model. We use the IR dust opacity profile data from the Thermal Emission spectrometer (TES) limb scan data as well as the TES Nadir data to prescribe the dust opacity distribution. Data from MY 26, which corresponds to the year of MER landing, and data from a climatology based on the median of 4 years (MY24 to MY27) of TES data are used. Model temperature profiles are compared with the reconstructions from EDL data and TES observations. Sensitivity of the model simulation to variations in the input opacity data are shown.
Murali Natarajan↗
Comparison of open‐source three‐dimensional reconstruction pipelines for maize‐root phenotyping
Abstract Understanding three‐dimensional (3D) root traits is essential to improve water uptake, increase nitrogen capture, and raise carbon sequestration from the atmosphere. However, quantifying 3D root traits by reconstructing 3D root models for deeper field‐grown roots remains a challenge due to the unknown tradeoff between 3D root‐model quality and 3D root‐trait accuracy. Therefore, we performed two computational experiments. We first compared the 3D model quality generated by five state‐of‐the‐art open‐source 3D model reconstruction pipelines on 12 contrasting genotypes of field‐grown maize roots. These pipelines included COLMAP, COLMAP+PMVS (Patch‐based Multi‐View Stereo), VisualSFM, Meshroom, and OpenMVG+MVE (Multi‐View Environment). The COLMAP pipeline achieved the best performance regarding 3D model quality versus computational time and image number needed. In the second test, we compared the accuracy of 3D root‐trait measurement generated by the Digital Imaging of Root Traits 3D pipeline (DIRT/3D) using COLMAP‐based 3D reconstruction with our current DIRT/3D pipeline that uses a VisualSFM‐based 3D reconstruction on the same dataset of 12 genotypes, with 5–10 replicates per genotype. The results revealed that (1) the average number of images needed to build a denser 3D model was reduced from 3000 to 3600 (DIRT/3D [VisualSFM‐based 3D reconstruction]) to around 360 for computational test 1, and around 600 for computational test 2 (DIRT/3D [COLMAP‐based 3D reconstruction]); (2) denser 3D models helped improve the accuracy of the 3D root‐trait measurement; (3) reducing the number of images can help resolve data storage problems. The updated DIRT/3D (COLMAP‐based 3D reconstruction) pipeline enables quicker image collection without compromising the accuracy of 3D root‐trait measurements.
09 BIOMASS FUELS↗
Remote probing of atmospheric particulates from radiation extinction experiments: A review of methods
The existing methodology for reconstructing the particle size distribution and inferring the refractive index of absorbing and scattering atmospheric particulates is critically reviewed. Emphasis is placed on method capabilities and shortcomings and, wherever possible, on achievable accuracy. The nature of the associated remote probing problem is analyzed with regard to the effects of the particulates on EM wave propagation in the atmosphere. The parameterization of size distribution is studied within the unifying framework of Pearson's distribution curves. The inversions of extinction measurements and their ratios are considered separately, and the potentialities of each type of measurement are identified. Work lacking in each of the methods reviewed is indicated. A method of determining both the effective complex refractive index and size distribution model parameters from the same data is also presented. Lastly, determination from extinction ratio data of the complex refractive index independent of size distribution is discussed and error analyzed.
Fymat, A. L.↗
Floods and Heavy Precipitation at the Global Scale: 100‐Year Analysis and 180‐Year Reconstruction
Floods and heavy precipitation have disruptive impacts worldwide, but their historical variability remains only partially understood at the global scale. This article aims at reducing this knowledge gap by jointly analyzing seasonal maxima of streamflow and precipitation at more than 3,000 stations over a 100‐year period. The analysis is based on Hidden Climate Indices (HCIs). Like standard climate indices (e.g., Nino 3.4, NAO), HCIs are used as covariates explaining the temporal variability of data, but unlike them, HCIs are estimated from the data. In this work, a distinction is made between common HCIs, that affect both heavy precipitation and floods, and specific HCIs, that exclusively affect one or the other. Overall, HCIs do not show noticeable autocorrelation, but some are affected by noticeable trends. In particular, strong and wide‐ranging trends are identified in precipitation‐specific HCIs, while trends affecting flood‐specific HCIs are weaker and have more localized effects. A probabilistic model is then derived to link HCIs and large‐scale atmospheric variables (pressure, wind, temperature) and to reconstruct HCIs since 1836 using the 20CRv3 reanalysis. In turn this allows estimating the probability of occurrence of floods and heavy precipitation at the global scale. This 180‐year reconstruction highlights flood hot‐spots and hot‐moments in the distant past, well before the establishment of perennial monitoring networks. Finally, the approach presented in this study is generic and paves the way for an improved characterization of historical variability by making a better use of long but highly irregular station data sets.
54 ENVIRONMENTAL SCIENCES↗
Comparison of Mars Atmospheric Density Estimates from Models to Measurements from Mars Global Surveyor (MGS) Data
A recent study (Desai, 2008) has shown that the actual landing sites of Mars Pathfinder, the Mars Exploration Rovers (Spirit and Opportunity) and the Phoenix Mars Lander have been further downrange than predicted by models prior to landing Desai's reconstruction of their entries into the Martian atmosphere showed that the models consistently predicted higher densities than those found upon entry, descent and landing. Desai's results have raised a question as to whether there is a systemic problem within Mars atmospheric models. Proposal is to compare Mars atmospheric density estimates from Mars atmospheric models to measurements made by Mars Global Surveyor (MGS). Comparison study requires the completion of several tasks that would result in a greater understanding of reasons behind the discrepancy found during recent landings on Mars and possible solutions to this problem.
Justh, Hilary L.↗