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NASA NTRS2004

The Forced Annual Wobble in Earth's Polar Motion

The annual wobble in Earth's polar motion is a forced motion, as opposed to an excited natural oscillation which is the Chandler wobble in the case of polar motion. It is forced by the combination of many angular momentum variations in the geophysical fluids that exchange these variations with the solid Earth, hence changing its rotation. Among all forcing sources of the annual wobble the geophysical fluid that has the dominant contribution is the atmosphere, while the oceans and the land hydrology make up the remaining budget together with tidal influences. The latter include that from the solid Earth deformation and that from the ocean tides at the annual period. The combined forcing produces both prograde and retrograde wobbles; the prograde wobble gets magnified substantially by the near-by presence of the natural Chandler wobble resonance. On the other hand, the closeness of the prograde annual forcing power to the Chandler period is an indication that some of the power leakage into the Chandler period band becomes the main excitation source for the Chandler wobble. In this paper we will review our knowledge about annual wobble and show the status in the effort of closing the budget with the annual angular momentum variations from the various geophysical fluids.

Chao, Benjamin F.↗

NASA NTRS1989

The historic biogeography of India: isolation or contact?

Geophysical maps depicting continental movement have consistently shown India, as it moved northward, to be located far out in the Tethys Sea. India split off from the African east coast about 148 m.y.a. From that time onward, according to almost all geophysical accounts, India was isolated from all of other continents until the early Miocene when it made contact with Eurasia. But the biological data, both fossil and Recent, indicate that this concept cannot be correct. If India had really existed as an isolated, oceanic continent for about 100 m.y., it should have developed a peculiar biota with many endemic genera and families in its terrestrial and shallow marine habitats. But there are virtually no remains of organisms indicating that India was isolated for any substantial time (millions of years). Instead, we find that almost all Indian taxa were possessed in common with other continents. As time went on, the northern relationships became stronger and the southern ones weaker. Most of the recent geophysical accounts show India not making contact with Eurasia until the early Miocene, but fossil materials show that this event must have taken place by the early Eocene. It has been postulated that, as India moved northward, it created a biogeographic barrier that separated marine fish populations and resulted in the east-west provinces that are now apparent in the Indian Ocean. At the same time, the barrier effect was supposed to have resulted in the formation of sister species that are now located far apart. Information currently available indicates that most living, tropical marine species are probably not over 3 m.y. old. Consequently, the northward movement of India, which took place primarily between 148 and 50 m.y.a., could have no bearing on the relationships of modern species.

NASA Discipline Exobiology↗

NASA NTRS2004

Magnetohydrodynamic Convection in the Outer Core and its Geodynamic Consequences

The Earth's fluid outer core is in vigorous convection through much of the Earth's history. In addition to generating and maintaining Earth s time-varying magnetic field (geodynamo), the core convection also generates mass redistribution in the core and a dynamical pressure field on the core-mantle boundary (CMB). All these shall result in various core-mantle interactions, and contribute to surface geodynamic observables. For example, electromagnetic core-mantle coupling arises from finite electrically conducting lower mantle; gravitational interaction occurs between the cores and the heterogeneous mantle; mechanical coupling may also occur when the CMB topography is aspherical. Besides changing the mantle rotation via the coupling torques, the mass-redistribution in the core shall produce a spatial-temporal gravity anomaly. Numerical modeling of the core dynamical processes contributes in several geophysical disciplines. It helps explain the physical causes of surface geodynamic observables via space geodetic techniques and other means, e.g. Earth's rotation variation on decadal time scales, and secular time-variable gravity. Conversely, identification of the sources of the observables can provide additional insights on the dynamics of the fluid core, leading to better constraints on the physics in the numerical modeling. In the past few years, our core dynamics modeling efforts, with respect to our MoSST model, have made significant progress in understanding individual geophysical consequences. However, integrated studies are desirable, not only because of more mature numerical core dynamics models, but also because of inter-correlation among the geophysical phenomena, e.g. mass redistribution in the outer core produces not only time-variable gravity, but also gravitational core-mantle coupling and thus the Earth's rotation variation. They are expected to further facilitate multidisciplinary studies of core dynamics and interactions of the core with other components of the Earth.

Kuang, Weijia↗

NASA NTRS2005

International VLBI Service for Geodesy and Astrometry 2004 Annual Report

Contents include the following: Combination Studies using the Cont02 Campaign. Coordinating Center report. Analysis coordinator report. Network coordinator report. IVS Technology coordinator report. Algonquin Radio observatory. Fortaleza Station report for 2004. Gilmore Creek Geophysical Observatory. Goddard Geophysical and Astronomical observatory. Hartebeesthoek Radio Astronomy Observatory (HartRAO). Hbart, Mt Pleasant, station report for 2004. Kashima 34m Radio Telescope. Kashima and Koganei 11-m VLBI Stations. Kokee Park Geophysical Observatory. Matera GGS VLBI Station. The Medicina Station status report. Report of the Mizusawa 10m Telescope. Noto Station Activity. NYAL Ny-Alesund 20 metre Antenna. German Antarctic receiving Station (GARS) O'higgins. The IVS network station Onsala space Observatory. Sheshan VLBI Station report for 2004. 10 Years of Geodetic Experiments at the Simeiz VLBI Station. Svetloe RAdio Astronomical Observatory. JARE Syowa Station 11-m Antenna, Antarctica. Geodetic Observatory TIGO in Concepcion. Tsukuba 32-m VLBI Station. Nanshan VLBI Station Report. Westford Antenna. Fundamental-station Wettzell 20m Radiotelescope. Observatorio Astroonomico Nacional Yebes. Yellowknife Observatory. The Bonn Geodetic VLBI Operation Center. CORE Operation Center Report. U.S. Naval Observatory Operation Center. The Bonn Astro/Geo Mark IV Correlator.

Behrend, Dirk↗

NASA NTRS2006

Improved Soundings and Error Estimates using AIRS/AMSU Data

AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of 1 K, and layer precipitable water with an rms error of 20 percent, in cases with up to 80 percent effective cloud cover. The basic theory used to analyze AIRS/AMSU/HSB data in the presence of clouds, called the at-launch algorithm, and a post-launch algorithm which differed only in the minor details from the at-launch algorithm, have been described previously. The post-launch algorithm, referred to as AIRS Version 4.0, has been used by the Goddard DAAC to analyze and distribute AIRS retrieval products. In this paper we show progress made toward the AIRS Version 5.0 algorithm which will be used by the Goddard DAAC starting late in 2006. A new methodology has been developed to provide accurate case by case error estimates for retrieved geophysical parameters and for the channel by channel cloud cleared radiances used to derive the geophysical parameters from the AIRS/AMSU observations. These error estimates are in turn used for quality control of the derived geophysical parameters and clear column radiances. Improvements made to the retrieval algorithm since Version 4.0 are described as well as results comparing Version 5.0 retrieval accuracy and spatial coverage with those obtained using Version 4.0.

Susskind, Joel↗

NASA NTRS2007

Production and Distribution of NASA MODIS Remote Sensing Products

The two Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on-board NASA's Earth Observing System (EOS) Terra and Aqua satellites make key measurements for understanding the Earth's terrestrial ecosystems. Global time-series of terrestrial geophysical parameters have been produced from MODIS/Terra for over 7 years and for MODIS/Aqua for more than 4 1/2 years. These well calibrated instruments, a team of scientists and a large data production, archive and distribution systems have allowed for the development of a new suite of high quality product variables at spatial resolutions as fine as 250m in support of global change research and natural resource applications. This talk describes the MODIS Science team's products, with a focus on the terrestrial (land) products, the data processing approach and the process for monitoring and improving the product quality. The original MODIS science team was formed in 1989. The team's primary role is the development and implementation of the geophysical algorithms. In addition, the team provided feedback on the design and pre-launch testing of the instrument and helped guide the development of the data processing system. The key challenges the science team dealt with before launch were the development of algorithms for a new instrument and provide guidance of the large and complex multi-discipline processing system. Land, Ocean and Atmosphere discipline teams drove the processing system requirements, particularly in the area of the processing loads and volumes needed to daily produce geophysical maps of the Earth at resolutions as fine as 250 m. The processing system had to handle a large number of data products, large data volumes and processing loads, and complex processing requirements. Prior to MODIS, daily global maps from heritage instruments, such as Advanced Very High Resolution Radiometer (AVHRR), were not produced at resolutions finer than 5 km. The processing solution evolved into a combination of processing the lower level (Level 1) products and the higher level discipline specific Land and Atmosphere products in the MODIS Science Investigator Lead Processing System (SIPS), the MODIS Adaptive Processing System (MODAPS), and archive and distribution of the Land products to the user community by two of NASA s EOS Distributed Active Archive Centers (DAACs). Recently, a part of MODAPS, the Level 1 and Atmosphere Archive and Distribution System (LAADS), took over the role of archiving and distributing the Level 1 and Atmosphere products to the user community.

Wolfe, Robert↗

NASA NTRS2010

A Methodology to Assess the Impact of Optical and Electronic Crosstalk in a New Generation of Sensors Using Heritage Sensors

Electronic and optical crosstalk are radiometric challenges that often exist in the focal plane design in many sensors Such as MODIS. A methodology is described to assess the impact due to optical and electronic crosstalk on the measured radiance, and thereafter, the retrieval of geophysical products using MODIS Level I data sets. Based on a postulated set of electronic and optical crosstalk coefficients, and a set of MODIS scenes, we have simulated a system signal contamination on any detector on a focal plane when another detector on that focal plane is stimulated with a geophysical signal. The original MODIS scenes and the crosstalk impacted scenes can be used with validated geophysical algorithms to derive the final data products. Products contaminated with crosstalk are then compared to those without contamination to assess the impact magnitude and location, and will allow us to separate Out-Of-Band (OOB) leaks from hand-to-hand optical crosstalk, and identify potential failures to meet climate research requirements.

Oudrari, Hassan↗

NASA NTRS2008

Proceedings of the 39th Lunar and Planetary Science Conference

Sessions with oral presentations include: A SPECIAL SESSION: MESSENGER at Mercury, Mars: Pingos, Polygons, and Other Puzzles, Solar Wind and Genesis: Measurements and Interpretation, Asteroids, Comets, and Small Bodies, Mars: Ice On the Ground and In the Ground, SPECIAL SESSION: Results from Kaguya (SELENE) Mission to the Moon, Outer Planet Satellites: Not Titan, Not Enceladus, SPECIAL SESSION: Lunar Science: Past, Present, and Future, Mars: North Pole, South Pole - Structure and Evolution, Refractory Inclusions, Impact Events: Modeling, Experiments, and Observations, Mars Sedimentary Processes from Victoria Crater to the Columbia Hills, Formation and Alteration of Carbonaceous Chondrites, New Achondrite GRA 06128/GRA 06129 - Origins Unknown, The Science Behind Lunar Missions, Mars Volcanics and Tectonics, From Dust to Planets (Planetary Formation and Planetesimals):When, Where, and Kaboom! Astrobiology: Biosignatures, Impacts, Habitability, Excavating a Comet, Mars Interior Dynamics to Exterior Impacts, Achondrites, Lunar Remote Sensing, Mars Aeolian Processes and Gully Formation Mechanisms, Solar Nebula Shake and Bake: Mixing and Isotopes, Lunar Geophysics, Meteorites from Mars: Shergottite and Nakhlite Invasion, Mars Fluvial Geomorphology, Chondrules and Chondrule Formation, Lunar Samples: Chronology, Geochemistry, and Petrology, Enceladus, Venus: Resurfacing and Topography (with Pancakes!), Overview of the Lunar Reconnaissance Orbiter Mission, Mars Sulfates, Phyllosilicates, and Their Aqueous Sources, Ordinary and Enstatite Chondrites, Impact Calibration and Effects, Comparative Planetology, Analogs: Environments and Materials, Mars: The Orbital View of Sediments and Aqueous Mineralogy, Planetary Differentiation, Titan, Presolar Grains: Still More Isotopes Out of This World, Poster sessions include: Education and Public Outreach Programs, Early Solar System and Planet Formation, Solar Wind and Genesis, Asteroids, Comets, and Small Bodies, Carbonaceous Chondrites, Chondrules and Chondrule Formation, Chondrites, Refractory Inclusions, Organics in Chondrites, Meteorites: Techniques, Experiments, and Physical Properties, MESSENGER and Mercury, Lunar Science Present: Kaguya (SELENE) Results, Lunar Remote Sensing: Basins and Mapping of Geology and Geochemistry, Lunar Science: Dust and Ice, Lunar Science: Missions and Planning, Mars: Layered, Icy, and Polygonal, Mars Stratigraphy and Sedimentology, Mars (Peri)Glacial, Mars Polar (and Vast), Mars, You are Here: Landing Sites and Imagery, Mars Volcanics and Magmas, Mars Atmosphere, Impact Events: Modeling, Experiments, and Observation, Ice is Nice: Mostly Outer Planet Satellites, Galilean Satellites, The Big Giant Planets, Astrobiology, In Situ Instrumentation, Rocket Scientist's Toolbox: Mission Science and Operations, Spacecraft Missions, Presolar Grains, Micrometeorites, Condensation-Evaporation: Stardust Ties, Comet Dust, Comparative Planetology, Planetary Differentiation, Lunar Meteorites, Nonchondritic Meteorites, Martian Meteorites, Apollo Samples and Lunar Interior, Lunar Geophysics, Lunar Science: Geophysics, Surface Science, and Extralunar Components, Mars, Remotely, Mars Orbital Data - Methods and Interpretation, Mars Tectonics and Dynamics, Mars Craters: Tiny to Humongous, Mars Sedimentary Mineralogy, Martian Gullies and Slope Streaks, Mars Fluvial Geomorphology, Mars Aeolian Processes, Mars Data and Mission,s Venus Mapping, Modeling, and Data Analysis, Titan, Icy Dwarf Satellites, Rocket Scientist's Toolbox: In Situ Analysis, Remote Sensing Approaches, Advances, and Applications, Analogs: Sulfates - Earth and Lab to Mars, Analogs: Remote Sensing and Spectroscopy, Analogs: Methods and Instruments, Analogs: Weird Places!. Print Only Early Solar System, Solar Wind, IDPs, Presolar/Solar Grains, Stardust, Comets, Asteroids, and Phobos, Venus, Mercury, Moon, Meteorites, Mars, Astrobiology, Impacts, Outer Planets, Satellites, and Rings, Support for Mission Operations, Analog Education and Public Outreach.

Source record↗

NASA NTRS2012

My IGY in Antarctica

Dr Charles Bentley is the A.P. Crary Professor Emeritus of Geophysics, Department of Geology and Geophysics, University of Wisconsin-Madison. Dr. Bentley joined the Arctic Institute of North America in 1956 to participate in International Geophysical Year (IGY)-related activities in the Antarctic. He wintered over consecutively in 1957 and 1958 at Byrd Station, a station in the interior of West Antarctica that housed 24 men each winter - 12 Navy support people and 12 civilian scientists/technicians. During the austral summers, he also participated in over-snow traverses, first as co-leader, then leader (the other coleader went home after the first year). These traverses consisted of six men and three vehicles, and lasted several months. These traverses covered more than 1609 kilometers (1000 miles) of largely unmapped and unphotographed terrain. During these traverses, connections to Byrd Station were by radio (daily, when the transmission conditions were good enough) and roughly every 2 weeks by resupply flight.

Bentley, Charles↗

NASA NTRS2013

Error Consistency Analysis Scheme for Infrared Ultraspectral Sounding Retrieval Error Budget Estimation

Great effort has been devoted towards validating geophysical parameters retrieved from ultraspectral infrared radiances obtained from satellite remote sensors. An error consistency analysis scheme (ECAS), utilizing fast radiative transfer model (RTM) forward and inverse calculations, has been developed to estimate the error budget in terms of mean difference and standard deviation of error in both spectral radiance and retrieval domains. The retrieval error is assessed through ECAS without relying on other independent measurements such as radiosonde data. ECAS establishes a link between the accuracies of radiances and retrieved geophysical parameters. ECAS can be applied to measurements from any ultraspectral instrument and any retrieval scheme with its associated RTM. In this manuscript, ECAS is described and demonstrated with measurements from the MetOp-A satellite Infrared Atmospheric Sounding Interferometer (IASI). This scheme can be used together with other validation methodologies to give a more definitive characterization of the error and/or uncertainty of geophysical parameters retrieved from ultraspectral radiances observed from current and future satellite remote sensors such as IASI, the Atmospheric Infrared Sounder (AIRS), and the Cross-track Infrared Sounder (CrIS).

Zhou, Daniel K.↗

NASA NTRS2013

Spatial Statistical Data Fusion (SSDF)

As remote sensing for scientific purposes has transitioned from an experimental technology to an operational one, the selection of instruments has become more coordinated, so that the scientific community can exploit complementary measurements. However, tech nological and scientific heterogeneity across devices means that the statistical characteristics of the data they collect are different. The challenge addressed here is how to combine heterogeneous remote sensing data sets in a way that yields optimal statistical estimates of the underlying geophysical field, and provides rigorous uncertainty measures for those estimates. Different remote sensing data sets may have different spatial resolutions, different measurement error biases and variances, and other disparate characteristics. A state-of-the-art spatial statistical model was used to relate the true, but not directly observed, geophysical field to noisy, spatial aggregates observed by remote sensing instruments. The spatial covariances of the true field and the covariances of the true field with the observations were modeled. The observations are spatial averages of the true field values, over pixels, with different measurement noise superimposed. A kriging framework is used to infer optimal (minimum mean squared error and unbiased) estimates of the true field at point locations from pixel-level, noisy observations. A key feature of the spatial statistical model is the spatial mixed effects model that underlies it. The approach models the spatial covariance function of the underlying field using linear combinations of basis functions of fixed size. Approaches based on kriging require the inversion of very large spatial covariance matrices, and this is usually done by making simplifying assumptions about spatial covariance structure that simply do not hold for geophysical variables. In contrast, this method does not require these assumptions, and is also computationally much faster. This method is fundamentally different than other approaches to data fusion for remote sensing data because it is inferential rather than merely descriptive. All approaches combine data in a way that minimizes some specified loss function. Most of these are more or less ad hoc criteria based on what looks good to the eye, or some criteria that relate only to the data at hand.

Braverman, Amy J.↗

NASA NTRS2018

Modeling the Distribution and Type of High-Latitude Natural Wetlands for Methane Studies

High latitude (>50N) natural wetlands emit a substantial amount of methane to the atmosphere, and are located in a region of amplified warming. Northern hemisphere high latitudes are characterized by cold climates, extensive permafrost, poor drainage, short growing seasons, and slow decay rates. Under these conditions, organic carbon accumulates in the soil, sequestering CO2 from the atmosphere. Methanogens produce methane from this carbon reservoir, converting stored carbon into a powerful greenhouse gas. Methane emission from wetland ecosystems depends on vegetation type, climate characteristics (e.g, precipitation amount and seasonality, temperature, snow cover, etc.), and geophysical variables (e.g., permafrost, soil type, and landscape slope). To understand how wetland methane dynamics in this critical region will respond to climate change, we have to first understand how wetlands themselves will change and therefore, what the primary controllers of wetland distribution and type are. Understanding these relationships permits data-anchored, physically-based modeling of wetland distribution and type in other climate scenarios, such as paleoclimates or future climates, a necessary first step toward modeling wetland methane emissions in these scenarios. We investigate techniques and datasets for predicting the distribution and type of high latitude (>50N) natural wetlands from a suite of geophysical and climate predictors. Hierarchical clustering is used to derive an empirical methane-centric wetland model. The model is applied in a multistep process first to predict the distribution of wetlands from relevant geophysical parameters, and then, given the predicted wetland distribution, to classify the wetlands into methane-relevant types using an expanded suite of climate and biogeophysical variables. As the optimum set of predictor variables is not known a priori, the model is applied iteratively, and each simulation is evaluated with respect to observed high-latitude wetlands.

Romanski, Joy↗

NASA NTRS2019

Analyzing Machine Learning Predictions of Passive Microwave Brightness Temperature Spectral Difference Over Snow-Covered Terrain in High Mountain Asia

Snow is an important component of the terrestrial freshwater budget in high mountainAsia (HMA) and contributes to the runoff in Himalayan rivers through snowmelt. Despitethe importance of snow in HMA, considerable spatiotemporal uncertainty exists across the different estimates of snow water equivalent for this region. In order to better estimate snow water equivalent, radiative transfer models are often used in conjunction with microwave brightness temperature measurements. In this study, the efficacy of support vector machines (SVMs), a machine learning technique, to predict passive microwave brightness temperature spectral difference (1Tb) as a function of geophysical variables (snow water equivalent, snow depth, snow temperature, and snow density) is explored through a sensitivity analysis. The use of machine learning (as opposed to radiative transfer models) is a relatively new and novel approach for improving snow water equivalent estimates. The Noah-MP land surface model within the NASALand Information System framework is used to simulate the hydrologic cycle over HMA and model geophysical variables that are then used for SVM training. The SVMsserve as a nonlinear map between the geophysical space (modeled in Noah-MP) andthe observation space (1Tb as measured by the radiometer). Advanced MicrowaveScanning Radiometer-Earth Observing System measured passive microwave brightness temperatures over snow-covered locations in the HMA region are used as training data during the SVM training phase. Sensitivity of well-trained SVMs to each Noah-MP modeled state variable is assessed by computing normalized sensitivity coefficients. Sensitivity analysis results generally conform with the known first-order physics. Input states that increase volume scattering of microwave radiation, such as snow density and snow water equivalent, exhibit a plurality of positive normalized sensitivity coefficients. In general, snow temperature was the most sensitive input to the SVM predictions. The sensitivity of each state is location and time dependent. The signs of normalized sensitivity coefficients that indicate physical irrationality are ascribed to significant cross-correlation between Noah-MP simulated states and decreased SVM prediction capability at specific locations due to insufficient training data. SVM prediction pitfalls do exist that serve to highlight the limitations of this particular machine learning algorithm.

high mountain Asia↗

NASA NTRS2020

Global Estimates and Long-Term Trends of Fine Particulate Matter Concentrations (1998-2018)

Exposure to outdoor fine particulate matter (PM2.5) is a leading risk factor for mortality. We develop global estimates of annual PM2.5 concentrations and trends for 1998–2018 using advances in satellite observations, chemical transport modeling, and ground-based monitoring. Aerosol optical depths (AODs) from advanced satellite products including finer resolution, increased global coverage, and improved long-term stability are combined and related to surface PM2.5 concentrations using geophysical relationships between surface PM2.5 and AOD simulated by the GEOS-Chem chemical transport model with updated algorithms. The resultant annual mean geophysical PM2.5 estimates are highly consistent with globally distributed ground monitors (R2 = 0.81; slope = 0.90). Geographically weighted regression is applied to the geophysical PM2.5 estimates to predict and account for the residual bias with PM2.5 monitors, yielding even higher cross validated agreement (R2 = 0.90–0.92; slope = 0.90–0.97) with ground monitors and improved agreement compared to all earlier global estimates. The consistent long-term satellite AOD and simulation enable trend assessment over a 21 year period, identifying significant trends for eastern North America (−0.28 ± 0.03 μg/m3/yr), Europe (−0.15 ± 0.03 μg/m3/yr), India (1.13 ± 0.15 μg/m3/yr), and globally (0.04 ± 0.02 μg/m3/yr). The positive trend (2.44 ± 0.44 μg/m3/yr) for India over 2005–2013 and the negative trend (−3.37 ± 0.38 μg/m3/yr) for China over 2011–2018 are remarkable, with implications for the health of billions of people.

Melanie S. Hammer↗

NASA NTRSDate not supplied

Lidar-Polarimeter Retrieval OSSEs using a Nature Run in Support of NASA's Aerosols, Clouds, Convection and Precipitation (ACCP) Study

The 2017 Decadal Survey (DS) highlighted Earth System Science themes, science and application questions, and several high priority objectives that have led to the inclusion of Aerosols (A) and Clouds-Convection-Precipitation (CCP) as Designated Observables (DOs). On June 1, 2018, several NASA centers (GSFC, LaRC, JPL, MSFC, GRC and ARC) submitted a joint Study Plan to the NASA Earth Science Division for the Aerosol (A) and Cloud, Convection, and Precipitation (CCP) Pre-formulation Study (ACCP). The DS and the ACCP team recognized the science merit in combining the A and CCP DOs for both enhancing the ability to address a number of science objectives and also to provide an expanded capability to address additional objectives beyond those addressed by individual DOs. A critical element of the ACCP observing strategy is to make extensive use of new passive and active sensors as well as of the so-called Program-of-Record (PoR), complemented by a fully integrated sub-orbital component. Central to this observing system design is the adoption of a Value Framework in which quantitative assessment of the science benefits of space- and air-borne assets is a key element. Given pre-defined ACCP science objectives and geophysical variables with desired accuracies, ACCP relies on a spectrum of Observing System Simulation Experiments (OSSEs) aimed at addressing pixel level retrieval uncertainties and sampling trade-offs. In this talk we will discuss a subset of Retrieval OSSEs being considered for ACCP, namely, synergistic lidar-polarimeter retrievals based on observation simulations from the GEOS-5 Nature Run (G5NR). Starting with aerosol states from the GEOS-5 Nature Run (G5NR) sampled along specific satellite orbits, we simulate polarized radiances at the desired polarimeter wavelengths with the Vector Linearized Direct Ordinate Radiative Transfer (VLIDORT) model, alongside the lidar signal for the relevant lidars with realistic error characterization. Next, inversions are performed with the Generalized Retrieval of Aerosol and Surface Properties (GRASP) system and the accuracy of the retrieved geophysical variables are assessed. In this presentation we will highlight results for key architectures being considered for ACCP with emphasis on geophysical variables of particular relevance to ACCP’s aerosol science objectives.

A Da Silva↗

NASA NTRSDate not supplied

VERNE: Revealing the Mysteries and Histories of Venus

Introduction: The three Venus missions that were recently selected for upcoming flight (VERITAS, DAVINCI+, and EnVision) will be incredibly valuable to our understanding of Venus’ history, geology, and atmosphere. However, even once completed, key gaps in our knowledge of Venus, and more generally the formation and active processes on rocky, Earth-like planets, will still persist. Remaining questions include 1) how global intrinsic magnetic fields might be maintained on rocky worlds, and how they could then go extinct, and 2) what role atmospheric sulfur chemistry plays in climates of Earth-like planets, which is an increasingly timely subject as Earth’s own atmospheric sulfur content is climbing due to human activity. These questions require in-situ observations from Venus’ cloud deck, at the altitudes at which the UV absorber exists. The Venus Environment Research and Novel Exploration (VERNE) mission will address these questions with an aerial platform that will drift around the equatorial region of the planet for 9 days. VERNE will collect data to determine the identity of the mysterious UV absorber, while also taking magnetic field measurements over the tesserae, the regions on Venus that are most likely to retain remanent crustal magnetization, in order to understand the potential role of a past intrinsically-generated global magnetic field on Venus. Mission Objectives: The two major science objectives that drive the VERNE mission are: 1) Determine the identity of the Venusian unknown ultraviolet absorber(s). First observed approximately a century ago [1], the composition of Venus’ ultraviolet (UV) absorber is one of the oldest mysteries in Venus atmospheric chemistry [2,3]. While several candidate UV absorbers (mostly sulfur species) have been proposed, no consensus has been reached on its composition and its specific interactions with the atmosphere. Determining the identity of the UV absorber will aid climate models by showing how and where incident solar energy is absorbed by the atmosphere and make progress towards understanding the chemical and energetic processes taking place above Venus’ upper cloud deck [4]. 2) Determine if Venus retains evidence of a past, internally-generated magnetic field. While Venus does not currently have an intrinsically-generated magnetic field, evidence for the existence of a past field on Venus and a timeline of its decay will fill in a more holistic picture of the evolution of Venus’ geological record and atmosphere. As the oldest geologic units on the surface, Venus’ tesserae may still have remanent crustal magnetization signatures within the rocky composition [5]. In any case, the signatures detected will provide insight into Venus’ past geological and core dynamo activity. Mission Summary: VERNE includes a 3-part flight system made up of 1) an entry system with a HEEET (Heatshield for Extreme Entry Environment Technology) aeroshell, 2) an orbiter for data relay, and 3) an in-situ balloon and gondola. After entry into Venus’ atmosphere, the balloon will be deployed within the upper cloud deck, at an altitude of 62 km, over a tesserae region. The in-situ data collection will last for the duration of 2 full circumnavigations of the planet, which will take ~9 days. Instrumentation Suite: The four instruments that comprise VERNE’s instrument payload will enable the identification of the unknown UV absorber and the detection of remanent crustal magnetization if it exists in the tesserae. The proposed instrument suite cycle during mission operations is shown in Fig. 1. The four instruments are described below: 1) Adams (ion neutral mass spectrometer) has a range of 18-257 AMU and will detect and distinguish the mixing ratios of O₂, H₂O, H₂SO₄, S, S₂, S₃, S₄, S₅, S₆, S₇, S₈, SO, SO₂, OSSO, SO₃, Cl₂, FeCl₃ and other trace sulfur and organic species. The spatial (longitudinal) and temporal (day/night) variations will be observed throughout 2 circumnavigations with a sample cadence of 12 minutes. 2) Shelley (nephelometer) will determine the size distribution of the aerosols (0.4 to 36 um) in the atmosphere. With a size resolution of <0.7 um, it can determine which mode of H2SO4 is present and characterize the large (>30 um) organic particles previously detected by the Venera and Galileo missions [6,7]. 3) Herbert (UV imager) will measure UV radiance at 283 nm (the wavelength of SO2 absorption) and 365 nm (the unknown part of the absorber). UV images will be taken concurrently with the INMS and nephelometer to correlate UV absorption with abundances of the UV absorber species. 4) Vonnegut (magnetometer) has a range of >600 nT and a precision and accuracy of 1 nT. If magnetized by a past field, the crust may have retained a magnetization of up to 3 A/m2 [5]. With a noise floor of 10 nT, the magnetometer will be able to detect RCM from an altitude of 62 km, even if the thickness of the magnetized crust is just 1 km (Fig. 2). Mission Concept Design: VERNE will be launched with a mass of 3300 kg in an intermediate-high performance class vehicle with a 4-m fairing. The 475-day mission includes 466 days for the cruise, coasting, and orbit initialization phases before entry, descent, and balloon deployment. During the 9-day science phase, the aerial platform will make 2 circumnavigations of the planet at an altitude of 62 km. The INMS and the nephelometer will acquire data for 2 hours during the daytime and nighttime during each circumnavigation, while the UV imager will be on for the duration of the daytime, and the magnetometer will be operational throughout the entirety of the science phase. Data will be stored and processed with the JPL-designed Sphinx command and data handling system. Data will be sent from the balloon to the orbiter using an S-band relay link, stored on the orbiter, and then forwarded to Earth where it will be received by the DSN. Conclusion: VERNE will fill key gaps in our understanding of the history and ongoing processes related to the geology and atmosphere of Venus and rocky worlds in general. Even with adequate flight system contingencies and expected costs below the $900M New Frontiers cost cap, VERNE is not without its risks and challenges. Further trade spaces to explore include 1) using solely battery power vs. including solar panels to increase the mission duration and 2) investigating the use of lightweight materials and 3D-printed structures to reduce the gondola mass, among others. Acknowledgments: We would like to thank the JPL Planetary Science Summer School, especially our mentors Troy Hudson, Karl Mitchell, and Leslie Lowes, as well as our Team-X study lead Al Nash and the members of Team-X. We’d additionally like to thank our review panel for asking insightful questions and providing valuable feedback. References: [1] Ross, F. E. (1928) Astrophysical J., 68, 57-92. [2] Rossow, W. B. et al. (1980) J. Geophysical Research, 85, 8107-8128. [3] Pinto, J. P. et al. (2021) Nature Communications, 12, 175. [4] Titov, D. V. et al. (2007) Cosmic Research, 21, 401. [5] O’Rourke, J. et al. (2019) Geophysical Research Lett., 46, 5768–5777. [6] Limaye, S. S. et al. (2018) Astrobiology, 18(9), 1181-1198. [7] Grinspoon, D. H. et al. (2013) Planetary and Space Sci., 41(7), 515-542. [8] Parker, R. L. (2003) J. Geophysical Research, 108, 5006. *The cost information contained in this document is of a budgetary and planning nature and is intended for informational purposes only. It does not constitute a commitment on the part of JPL and/or Caltech.

H Alpert↗

NASA NTRSDate not supplied

Adding GPU Support to the Markov Chain Monte Carlo Code Catmip

In geophysics, we are confronted with many under-determined inverse problems. For example, all of our observations of earthquakes are made at the Earth’s surface. So, when we try to infer how slip during an earthquake evolves in space and time, we find that there are many potential slip histories that are consistent with our limited observations and our understanding of earthquake physics. One way to approach these problems is with Bayesian analysis which allows us to infer the ensemble of all potential slip models that satisfy the observations and our prior knowledge of earthquake physics. In Bayesian analysis, our prior knowledge is known as the prior probability density function or prior PDF, the fit to the data is known as the data likelihood, and the target PDF that satisfies both the prior PDF and data likelihood is known as the posterior PDF. However, simulating the posterior PDF typically requires using Markov Chain Monte Carlo (MCMC) to draw tens of billions of random realizations of earthquake slip models, which may not be computationally feasible. To make this and similar geophysical inversions computationally tractable, we developed the Cascading Adaptive Transitional Metropolis In Parallel (CATMIP) algorithm. CATMIP is an efficient parallel Markov Chain Monte Carlo (MCMC) sampler that is used for model fitting and uncertainty quantification in geophysics. Example use cases are earthquake rupture modeling, determining mineral composition on Mars, reconstructing the history of ocean salinity, and historical earthquake relocation. CATMIP employs many parallel instances of the Metropolis algorithm for sampling in a transitioning framework. Transitioning is a process in which a set of random samples at equilibrium with a known probability density function (PDF) are used as seeds for the Markov chains to sample successive target PDFs that incrementally move the distribution from the starting seeds to the final desired PDF that describes the relative plausibility of potential values for the model parameters. The algorithm is implemented as a Master-Worker model employing MPI for communication. The worker processes are loosely coupled with global parameters periodically optimized by the master process. This provides a very high amount of parallelism with little communication between updates. During the presentation we will discuss the history of the algorithm and elaborate the earthquake rupture modeling use case for the CATMIP package. Our first step toward GPU optimization was to optimize the code for the CPU. CPU profiling revealed that most of the compute time is spent in calls to level 2 BLAS routines and calls to GSL random number generators. We revised the algorithm to employ level 3 BLAS routines instead. In our presentation we will describe how this was accomplished. Adding GPU support to CATMIP consisted mostly of replacing the calls to GSL with calls to GPU vendor-provided library routines. A small number of loops were directly implemented in CUDA. In the presentation will provide implementation details. Finally, we will discuss methods for profiling and opportunities for further optimizing GPU execution. By creating a code with the flexibility to run on either a CPU or GPU architecture, CATMIP can be used on systems ranging from large CPU-based HPC environments to single servers with GPU acceleration and everything in between.

HECC↗

NASA NTRS1996

Ku-Band Ocean Backscatter Functions for Surface Wind Retrieval

The accuracy of wind measurements with scatterometer techniques depends on the particular geophysical model function used in the retrieval algorithm. The measured results are compared with calculated values to assess the existing geophysical model functions for applications to ocean surface wind retrieval.

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