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At least 127 records · Page 7

Variability in equatorial Pacific sea surface topography during the verification phase of the TOPEX/POSEIDON mission

As part of the verification phase of the TOPEX/POSEIDON mission, 10-day gridded fields of altimeter data derived from TOPEX geophysical data records are compared with 10-day gridded fields of dynamic height derived from more than 60 moorings of the Tropical Ocean and Global Atmosphere-Tropical Atmosphere Ocean (TOGA-TAO) array in the equatorial Pacific Ocean. Access to TAO data in real time permits the first 500 days of the TOPEX/POSEIDON mission to be placed in the context of complementary, in-situ measurements of surface winds, sea surface temperatures, and upper ocean thermal structure, as well as the time history of these variables prior to launch. Analysis of the space-time structure in the TOPEX and TAO surface topography data increases sea level variability primarily due to equatorial Kelvin wave activity generated by intense wind bursts west of the date line in association with the 1991-1993 El Nino. Cross correlations between the two data sets are generally greater than 0.7, with root mean square (RMS) differences less than 4 cm. However, for reasons not fully understood, correlations drop to less than 0.5 in certain regions off the equator in the eastern Pacific and RMS differences can be greater than 5 cm north of the equator in the central and eastern Pacific.

Busalacchi, Antonio J.↗

Geostationary Imaging FTS (GIFTS) Data Processing: Measurement Simulation and Compression

GIFTS (Geostationary Imaging Fourier Transform Spectrometer), a forerunner of next generation geostationary satellite weather observing systems, will be built to fly on the NASA EO-3 geostationary orbit mission in 2004 to demonstrate the use of large area detector arrays and readouts. Timely high spatial resolution images and quantitative soundings of clouds, water vapor, temperature, and pollutants of the atmosphere for weather prediction and air quality monitoring will be achieved. GIFTS is novel in terms of providing many scientific returns that traditionally can only be achieved by separate advanced imaging and sounding systems. GIFTS' ability to obtain half-hourly high vertical density wind over the full earth disk is revolutionary. However, these new technologies bring forth many challenges for data transmission, archiving, and geophysical data processing. In this paper, we will focus on the aspect of data volume and downlink issues by conducting a GIFTS data compression experiment. We will discuss the scenario of using principal component analysis as a foundation for atmospheric data retrieval and compression of uncalibrated and un-normalized interferograms. The effects of compression on the degradation of the signal and noise reduction in interferogram and spectral domains will be highlighted. A simulation system developed to model the GIFTS instrument measurements is described in detail.

Huang, Hung-Lung↗

The Miniature Radio Frequency Instruments (Mini-RF) Global Observations of Earth's Moon

Radar provides a unique means to analyze the surface and subsurface physical properties of geologic deposits, including their wavelength-scale roughness, the relative depth of the deposits, and some limited compositional information. The NASA Lunar Reconnaissance Orbiter's (LRO) Miniature Radio Frequency (Mini-RF) instrument has enabled these analyses on the Moon at a global scale. Mini-RF has accumulated 67% coverage of the lunar surface in S-band (12.6 cm) radar with a resolution of 30 m/pixel. Here we present new Mini-RF global orthorectified uncontrolled S-band maps of the Moon and use them for analysis of lunar surface physical properties. Reported here are readily apparent global- and regional-scale differences in lunar surface physical properties that suggest three distinct terranes, namely: a (1) Nearside Radar Dark Region; (2) Orientale basin and continuous ejecta; and the (3) Highlands Radar Bright Region. Integrating these observations with new data from LRO's Diviner Radiometer rock abundance maps, as well Clementine and Lunar Prospector derived compositional values show multiple distinct lunar surface terranes and sub-terranes based upon both physical and compositional surface properties. Previous geochemical investigations of the Moon suggested its crust is best divided into three to four basic crustal provinces or terranes (Feldspathic Highlands Terrane (-An and -Outer), Procellarum KREEP Terrane, and South Pole Aitken Terrane) that are distinct from one another. However, integration of these geochemical data sets with new geophysical data sets allows us to refine these terranes. The result shows a more complex view of these same crustal provinces and provides valuable scientific and hazard perspectives for future targeted human and robotic exploration.

Radar observations↗

How Long Is Too Long? Variogram Analysis of AERONET Data to Aid Aerosol Validation and Intercomparison Studies

Geophysical data sets derived from satellite sensors, ground/airborne instrumentation, and computational models are often compared against each other. A common example is the validation of satellite aerosol optical depth (AOD) retrievals against measurements from Aerosol Robotic Network (AERONET) Sun photometers. Spatiotemporal mismatch between data set sampling means that uncaptured variation in the underlying geophysical field introduces apparent disagreement into such comparisons, known as representation or collocation matchup uncertainty. This study uses variogram analysis of AERONET data to estimate temporal mismatch uncertainties and decorrelation time scales for the global AERONET record. As well as total AOD, the fine‐ and coarse‐mode AODs, Ångström Exponent (AE), and fine‐mode fraction (FMF) of AOD are analyzed. Globally, a time difference of 30 min typically induces from 0.011–0.035 variation in AOD. For total, fine, and coarse AODs the typical time to decorrelation is around 2–10 days. For AE and FMF it is 3–33 days; that is, aerosol systems often persist significantly longer than individual events in them. Biomass burning regions tend to show the largest and fastest subdaily AOD variability and also longest times to decorrelation. Some sites show significant season‐to‐season variations in behavior. These results can be used to inform site‐specific time collocation thresholds for aerosol validation analyses and account for temporal variation when estimating data set uncertainty. They also have implications for comparisons between different satellite products or models, data aggregation, and time series analyses. Results are provided on a site‐by‐site basis to facilitate use by other researchers.

satellite↗

Advancing Geophysical Techniques to Image a Stratigraphic Hydrothermal Resource

Sedimentary-hosted geothermal energy systems are permeable structural, structural-stratigraphic, and/or stratigraphic horizons with sufficient temperature for direct use and/or electricity generation. Sedimentary-hosted (i.e., stratigraphic) geothermal reservoirs may be present in multiple locations across the central and eastern Great Basin of the USA, thereby constituting a potentially large base of untapped, economically accessible energy resources. Sandia National Laboratories has partnered with a multi disciplinary group of collaborators to evaluate a stratigraphic system in Steptoe Valley, Nevada using both established and novel geophysical imaging techniques. The goal of this study is to inform an optimized strategy for subsequent exploration and development of this resource and analogous ones. Building from prior Nevada Play Fairway Analysis (PFA), this team is primarily 1) collecting additional geophysical data, 2) employing novel joint geophysical inversion/modeling techniques to update existing 3D geologic models, and 3) integrating the geophysical results to produce a working, geologically constrained thermo-hydrological reservoir model. Prior PFA work highlights Steptoe Valley as a favorable resource basin that likely has both sedimentary and hydrothermal characteristics. However, there remains significant uncertainty on the nature and architecture of the resource(s) at depth, which increases the risk in exploratory drilling. Newly acquired gravity, magnetic, magnetotelluric, and controlled-source electromagnetic data products, in conjunction with new and preexisting geoscientific measurements and observations, are being integrated and evaluated for efficacy in understanding stratigraphic geothermal resources and mitigating exploration risk. Furthermore, the influence of hydrothermal activity on sedimentary-hosted reservoirs in favorable structural settings, and whether fault-controlled systems may locally enhance temperature and permeability in some deep stratigraphic reservoirs, will also be evaluated.

Geothermal, Sedimentary Heat, Geophysics, Seismic,↗

Deep learning multiphysics network for imaging CO 2 saturation and estimating uncertainty in geological carbon storage

Multiphysics inversion exploits different types of geophysical data that often complement each other and aims to improve overall imaging resolution and reduce uncertainties in geophysical interpretation. Despite the advantages, traditional multiphysics inversion is challenging because it requires a large amount of computational time and intensive human interactions for preprocessing data and finding trade-off parameters. These issues make it nearly impossible for traditional multiphysics inversion to be applied as a real-time monitoring tool for geological carbon storage. In this paper, we present a deep learning (DL) multiphysics network for imaging CO 2 saturation in real time. The multiphysics network consists of three encoders for analysing seismic, electromagnetic and gravity data and shares one decoder for combining imaging capabilities of the different geophysical data for better predicting CO 2 saturation. The network is trained on pairs of CO 2 label models and multiphysics data so that it can directly image CO 2 saturation. Here we use the bootstrap aggregating method to enhance the imaging accuracy and estimate uncertainties associated with CO 2 saturation images. Using realistic CO 2 label models and multiphysics data derived from the Kimberlina CO 2 storage model, we evaluate the performance of the deep learning multiphysics network and compare its imaging results to those from the deep learning single-physics networks. Our modelling experiments show that the deep learning multiphysics network for seismic, electromagnetic, and gravity data not only improves the imaging accuracy but also reduces uncertainties associated with CO 2 saturation images. Our results also suggest that the deep learning multiphysics network for the non-seismic data (i.e., electromagnetic and gravity) can be used as an effective low-cost monitoring tool in between regular seismic monitoring.

58 GEOSCIENCES↗

Superposed Epoch Analysis of Ring Current Geoeffectiveness Related to Solar Wind and Plasma Sheet Drivers

The goal of that proposal was to examine the relationship between solar wind drivers and ring current dynamics through data analysis and numerical simulations. The data analysis study was a statistical examination (via superposed epoch analyses) of a solar cycle's worth of storm data. Solar wind data, geophysical indices, and geosynchronous plasma data were collected for every time period with Dst< -50 nT from 1989 through 2002, and the storm list now exceeds 400 entries. This work was first conducted by a summer undergraduate student, Mr. John Vann (University of Kansas), with funding from the NSF Research Experience for Undergraduates program. It was then continued by a University of Michigan graduate student, Mr. Jichun Zhang. Mr. Zhang is now in his fourth year at U-M and is progressing very well toward a PhD in space science. His dissertation will be based on his data analysis and modeling efforts using this geomagnetic storm database. The results of the data analysis study have been the focus of several conference presentations, and the first manuscript has just been published. Two additional papers are presently being prepared, one on average (superposed) solar wind features for various storm subsets (e.g., intense storms at solar maximum), and another on geosynchronous plasma features for these same storm subsets. The latter result was highlighted by the TR&T program director in his presentation at the COSPAR meeting this summer.

Liemohm, M. W.↗

Three-dimensional cooperative inversion of airborne magnetic and gravity gradient data using deep-learning techniques

Using multiple geophysical methods has become a prevailing approach in numerous geophysical applications to investigate subsurface structures and parameters. These multimethod-based exploration strategies have the potential to greatly diminish uncertainties and ambiguities encountered during geophysical data analysis and interpretation. One of the applications is the cooperative inversion of airborne magnetic and gravity gradient data for the interpretation of data obtained in mineral, oil and gas, and geothermal explorations. In this paper, a unified cooperative inversion framework is designed by combining the standard separate inversions with a deep neural network (DNN), which serves as the link between different types of data. A well-trained DNN takes the separately inverted susceptibility and density models as the inputs and provides improved models that will be used as the initial models of deterministic inversions. A two-round iteration strategy is adopted to guarantee the reasonability of the recovered models and overall efficiency of the inversion. In addition, this deep-learning (DL)-based framework demonstrates excellent generalization abilities when tested on models that are entirely distinct from the training data sets. The framework can easily incorporate multiphysics without necessitating any structural changes to the network. Synthetic experiments validate that our DL-based method outperforms conventional separate inversions and cross-gradient-based joint inversion in view of the accuracy of the recovered models and inversion efficiency. Successful application to field data further verifies the effectiveness of our DL-based method.

Geochemistry & Geophysics↗

Suppression of the unwanted variations in data

The removal of unwanted frequency components in geophysical data may be accomplished by filtering. The filtering procedure described in this paper consists of estimating the undesirable component by using a narrow-band delay filter and subtracting the estimate from the data. Suppression of strong solar components in the presence of weak lunar components is considered in detail.

Bernhardt, P. A.↗

Deposition, Diagenesis, and Sequence Stratigraphy of the Pennsylvanian Morrowan and Atokan Intervals at Farnsworth Unit

Farnsworth Field Unit (FWU), a mature oilfield currently undergoing CO2-enhanced oil recovery (EOR) in the northeastern Texas panhandle, is the study area for an extensive project undertaken by the Southwest Regional Partnership on Carbon Sequestration (SWP). SWP is characterizing the field and monitoring and modeling injection and fluid flow processes with the intent of verifying storage of CO2 in a timeframe of 100–1000 years. Collection of a large set of data including logs, core, and 3D geophysical data has allowed us to build a detailed reservoir model that is well-grounded in observations from the field. This paper presents a geological description of the rocks comprising the reservoir that is a target for both oil production and CO2 storage, as well as the overlying units that make up the primary and secondary seals. Core descriptions and petrographic analyses were used to determine depositional setting, general lithofacies, and a diagenetic sequence for reservoir and caprock at FWU. The reservoir is in the Pennsylvanian-aged Morrow B sandstone, an incised valley fluvial deposit that is encased within marine shales. The Morrow B exhibits several lithofacies with distinct appearance as well as petrophysical characteristics. The lithofacies are typical of incised valley fluvial sequences and vary from a relatively coarse conglomerate base to an upper fine sandstone that grades into the overlying marine-dominated shales and mudstone/limestone cyclical sequences of the Thirteen Finger limestone. Observations ranging from field scale (seismic surveys, well logs) to microscopic (mercury porosimetry, petrographic microscopy, microprobe and isotope data) provide a rich set of data on which we have built our geological and reservoir models.

04 OIL SHALES AND TAR SANDS↗

Use of MAGSAT anomaly data for crustal structure and mineral resources in the US midcontinent

Magnetic fields were measured from October 1979 until June 1980 using the satellite. The processed magnetic data yield long wavelength anomalies that arise from crustal and upper mantle sources. Analysis techniques are being developed to help interpret the structure and character of the lithosphere in central North America. The region includes the Midcontinent Gravity Anomaly peleorift zone and the New Madrid rift/seismic zone, both of which are of plaeotectonic and neotectonic interest. Preliminary analysis of the initial MAGSAT data combined with correlative geological and geophysical data shows the utility of the satellite data for regional crustal and basement study.

Carmichael, R. S.↗

Reduction of Marine Magnetic Data for Modeling the Main Field of the Earth

The marine data set archived at the National Geophysical Data Center (NGDC) consists of shipborne surveys conducted by various institutes worldwide. This data set spans four decades (1953, 1958, 1960-1987), and contains almost 13 million total intensity observations. These are often less than 1 km apart. These typically measure seafloor spreading anomalies with amplitudes of several hundred nanotesla (nT) which, since they originate in the crust, interfere with main field modeling. The source for these short wavelength features are confined within the magnetic crust (i.e., sources above the Curie isotherm). The main field, on the other hand, is of much longer wavelengths and originates within the earth's core. It is desirable to extract the long wavelength information from the marine data set for use in modeling the main field. This can be accomplished by averaging the data along the track. In addition, those data which are measured during periods of magnetic disturbance can be identified and eliminated. Thus, it should be possible to create a data set which has worldwide data distribution, spans several decades, is not contaminated with short wavelengths of the crustal field or with magnetic storm noise, and which is limited enough in size to be manageable for the main field modeling. The along track filtering described above has proved to be an effective means of condensing large numbers of shipborne magnetic data into a manageable and meaningful data set for main field modeling. Its simplicity and ability to adequately handle varying spatial and sampling constraints has outweighed consideration of more sophisticated approaches. This filtering technique also provides the benefits of smoothing out short wavelength crustal anomalies, discarding data recorded during magnetically noisy periods, and assigning reasonable error estimates to be used in the least square modeling. A useful data set now exists which spans 1953-1987.

Baldwin, R. T.↗

Cross-calibration survey (VISNIR)

Included in the summary of the VISNIR survey is (1) a statement of the preferred cross-calibration approach, as endorsed by select members of the VISNIR group, (2) two viewgraphs which summarize the wavelength and fields-of-view of the various instruments, and (3) a listing of these same data, as given by the respective calibration representatives in the survey responses. The Earth Observing System (EOS) Project is fundamentally committed to the acquisition of data which can be reduced to geophysical data products of high and known accuracy. One possible method of insuring the primary data products are of known accuracy is to use the instruments themselves against the same sources to provide an independent check that a common understanding of accuracy exists. The goal then of the radiometric 'Cross-Calibration' at the integrator facility (GE) would be to convincingly establish as late as feasible in the Integration and Test (I&T) cycle that, when stimulated with common sources, the appropriate EOS instrument measurements agree within their previously established accuracy estimates across a useful radiance range, accounting for the additional uncertainty associated with the unique properties of the test set-up itself.

Bruegge, Carol J.↗

Improvement of the photometric sunspot index and changes of the disk-integrated sunspot contrast with time

The photometric sunspot index (PSI) was developed to study the effects of sunspots on solar irradiance. It is calculated from the sunspot data published in the Solar-Geophysical Data catalog. It has been shown that the former PSI models overestimate the effect of dark sunspots on solar irradiance; furthermore results of direct sunspot photometry indicate that the contrast of spots depends on their area. An improved PSI calculation is presented; it takes into account the area dependence of the contrast and calculates `true' daily means for each observation using the differential rotation of the spots. Moreover, the observations are screened for outliers which improves the homogeneity of the data set substantially, at least for the period after December 1981 when NOAA started to report data from a few instead of one to two stations. A detailed description of the method is provided. The correlation between the newly calculated PSI and total solar irradiance is studied for different phases of the solar cycles 21 and 22 using bi-variate spectral analysis. The results can be used as a `calibration' of PSI in terms of gain, the factor by which PSI has to be multiplied to yield the observed irradiance change. The factor changes with time from about 0.6 in 1980 to 1.1 in 1990. This unexpected result cannot be interpreted by a change of the contrast relative to the quiet Sun (as it is normally defined and determined by direct photometry) but rather as a change of the contrast between the spots and their surrounding as seen in total irradiance (integrated over the solar disk). This may partly be explained by a change in the ratio between the areas of the spots and the surrounding faculae.

Froehlich, Claus↗

The GLAS Standard Data Products Specification--Level 2, Version 9

The Geoscience Laser Altimeter System (GLAS) is the primary instrument for the ICESat (Ice, Cloud and Land Elevation Satellite) laser altimetry mission. ICESat was the benchmark Earth Observing System (EOS) mission for measuring ice sheet mass balance, cloud and aerosol heights, as well as land topography and vegetation characteristics. From 2003 to 2009, the ICESat mission provided multi-year elevation data needed to determine ice sheet mass balance as well as cloud property information, especially for stratospheric clouds common over polar areas. It also provided topography and vegetation data around the globe, in addition to the polar-specific coverage over the Greenland and Antarctic ice sheets.This document defines the Level-2 GLAS standard data products. This document addresses the data flow, interfaces, record and data formats associated with the GLAS Level 2 standard data products. The term standard data products refers to those EOS instrument data that are routinely generated for public distribution. The National Snow and Ice Data Center (NSDIC) distribute these products. Each data product has a unique Product Identification code assigned by the Senior Project Scientist. The Level 2 Standard Data Products specifically include those derived geophysical data values (i.e., ice sheet elevation, cloud height, vegetation height, etc.). Additionally, the appropriate correction elements used to transform the Level 1A and Level 1B Data Products into Level 2 Data Products are included. The data are packaged with time tags, precision orbit location coordinates, and data quality and usage flags.

Lee, Jeffrey E.↗

The ICESat-2 Mission: Land, Ocean, and Inland Water Data Products for Middle and Low Latitude Science and Applications

NASA’s Ice, Cloud, and Land Elevation Satellite (ICESat-2) is a polar orbiting mission, launched on September 15, 2018, with over two years of nearly continuous observations. The sole instrument onboard is the Advanced Topographic Laser Altimeter System (ATLAS), a micropulse, high repetition rate, six-beam, 532 nm Lidar with photon-counting technology. Although designed primarily for detecting height changes in ice caps and sea ice in the high latitudes, it continuously observes all terrain in its track including middle and low latitude regions as well, during approximately 15 orbits per day. The official ICESat-2 products include not only cryosphere data but also global high resolution parameters associated with tree canopies, land surface, oceans, and over 1.5 million inland water bodies consisting of lakes, rivers and coastal waters. This presentation provides an overview and the status of the ICESat-2 mission including: i) a summary of the salient technological features and orbit design, ii) the official ICESat-2 science data products for ice, vegetation canopy, ocean sea level, and inland water including several examples in the middle and low latitudes, iii) a list of NASA sponsored software tools for globally browsing the two year archive and for processing both the raw data and the official ICESat-2 geophysical data products, and iv) avenues for interested users to connect with the ICESat-2 Applications Program for answering questions and assistance in possibly using ICESat-2 data in your particular science or application. The overall goal is to facilitate the use of ICESat-2 data not only for science investigations but also for improved decision support applications with societal benefit. Additional ICESat-2 information, documentation and data products are publicly available at https://nsidc.org/data/icesat-2

ICESat-2↗

Geophysical and Environmental Monitoring Data, Lower Watershed, Teller Road Mile Marker 27, Seward Peninsula, Alaska, 2017-2019

This data set contains geophysical and environmental monitoring data acquired between September 2017 and 2019 at the lower Teller watershed, Seward Peninsula, Alaska. Geophysical data comprises processed resistivity data, acquired daily between Spring and Fall of 2018 and 2019, and a baseline measurement of Fall 2017. The environmental monitoring data comprises depth resolved, distributed soil moisture and soil temperature data. These measurements were obtained used Decagon 5TE sensors placed at 0.1 m, 0.2 m , 0.3 m, and 0.4 m depth. In addition, temperature data at 0.5 m, 1.0 m, and 1.5 m were acquired using Hobo temperature sensors. Data were collected to improve our understanding of the hydrological response of discontinuous permafrost systems, in particular focusing on multi-annual dynamics and short term disturbances, such as snowmelt or precipitation events. The electrical resistivity tomography (ERT) monitoring data are included as processed resistivity models, with model cells x dimension equal to the distance along the profile, and model z dimension being elevation. The start and end point of the transect are (UTM Zone 3N): E 454881.66 m, N 7178949.45 m, and E 454772.60, N 7178885.81. Locations of the soil moisture and temperature sensors are provided in the data package. This dataset is discussed in detail in the Uhlemann, S. et al 2021 paper listed in the references. This dataset includes one *.pdf user guide and 315 *.csv data files included within four zipped files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

The Thermal Evolution and Internal Structure of Saturn's Midsize Icy Satellites

The Cassini-Huygens mission is returning new geophysical data for the midsize, icy satellites of Saturn (i.e., satellites with radii between 100 and 1,000 km). These data have enabled a new generation of geophysical model studies for Phoebe, Iapetus, Rhea, Mimas, Tethys, Dione, as well as Enceladus (see Spencer et al. 2009). Here we consider the new model studies that have reported significant results elucidating the evolutionary histories and internal structures of these satellites. Those results have included their age, the development of their internal structures and mineralogies, which for greatest fidelity must be done concomitantly with coupled dynamical evolutions. Surface areas, volumes, bulk densities, spin rates, orbit inclinations, eccentricities, and distance from Saturn have changed as the satellites have aged. Heat is required to power the satellites evolution, but is not overly abundant for the midsized satellites. All sources of heat must be evaluated and taken into account. This includes their intensities and when they occur and are available to facilitate evolution, both internal and dynamical. The mechanisms of heat transport must also be included. However, to model these to high fidelity the material properties of the satellite interiors must be accurately known. This is not the case. Thus, we discuss what is known about these properties and how the uncertainties affect the estimation of heat sources, transport processes, and the consequential changes in composition and evolution. Phoebe has an oblate shape that may be in equilibrium with its spin period of ~9.3 h. Its orbital properties suggest that it is not one of the regular satellites, but is a captured body. Its density is higher than that of the other satellites, consistent with formation in the solar nebula rather than from material around Saturn. Oblate shape and high density are unusual for objects in this size range, and may indicate that Phoebe was heated by Al-26 decay soon after its formation, which is consistent with some models of the origin of Kuiper belt objects. Iapetus has the shape of a hydrostatic body with a rotation period near 16 h. It subsequently despun to its current synchronous rotation state, ~79 day period. These observations are sufficient to constrain the required heating in Iapetus early history, suggesting that it formed several My after CAI condensation. Because Saturn had to be present for Iapetus to form, this date also constrains the age of Saturn and how long it took to form. Both shape and gravitational data are available for Rhea. Gravity data were obtained from the single Cassini flyby during the prime mission and within the uncertainties cannot distinguish between hydrostatic and non-hydrostatic gravitational fields. Both Dione and Tethys display evidence of smooth terrains, with Dione's appearing considerably younger. Both are conceivably linked to tidal heating in the past, but the low rock abundance within Tethys and the lack of eccentricity excitation of Tethys orbit today make explaining this satellite's geology challenging.

Matson, Dennis L.↗