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NASA NTRS2013

The GLAS Standard Data Products Specification-Data Dictionary, Version 1.0

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 contains the data dictionary for the GLAS standard data products. It details the parameters present on GLAS standard data products. Each parameter is defined with a short name, a long name, units on product, type of variable, a long description and products that contain it. The term standard data products refers to those EOS instrument data that are routinely generated for public distribution. These products are distributed by the National Snow and Ice Data Center (NSDIC).

Lee, Jeffrey E.↗
NASA NTRS2013

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.↗
NASA NTRS2013

The GLAS Science Algorithm Software (GSAS) User's Guide Version 7

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 is the final version of the GLAS Science Algorithm Software Users Guide document. It contains the instructions to install the GLAS Science Algorithm Software (GSAS) in the production environment that was used to create the standard data products. It also describes the usage of each GSAS program in that environment with their required inputs and outputs. Included are a number of utility programs that are used to create ancillary data files that are used in the processing but generally are not distributed to the public as data products. Of importance is the values for the large number of constants used in the GSAS algorithm during processing are provided in an appendix.

Lee, Jeffrey E.↗
NASA NTRS2014

Novel Epoxy Particulate Composites for Mitigation of Insect Residue Adhesion on Future Aircraft Surfaces

Drag is reduced significantly for airflow over surfaces when laminar flow can be maintained over greater chord lengths, the distance from the leading edge of an airfoil.1 However, surface imperfections, such as chipped paint, scratches, and events that change topography on a microscopic scale can introduce airflow instabilities resulting in premature transition to turbulent flow.1 Although many of these surface imperfections can be avoided with proper maintenance, advanced materials, and advanced manufacturing practices, topographical surface anomalies arising during flight from insect impacts cannot be controlled and can influence laminar flow stability. Practical solutions to this operational challenge need to be developed for future aircraft to have full advantage of laminar flow designs that improve fuel efficiency.2 Researchers have investigated various methods to mitigate insect residue adhesion for decades.3 Although several techniques have demonstrated efficacy including mechanical scrapers, active liquid discharge systems, and sacrificial paper coatings, they have not been commercially implemented due to increased manufacturing and operational complexity, environmental impact, and weight penalties. Coatings offer a simple route for passive insect residue adhesion prevention without many of the challenges associated with maintenance of laminar flow.4 In our previous work, we determined that most commercially available materials were not effective at insect residue adhesion.5 We also identified improvements when both surface energy could be controlled by surface modifying agents and the topography could be altered through the use of micron-sized and nanometer-sized filler materials.6 In this work, these general principles were applied to an epoxy system to evaluate the behavior of the surface modifying agent, a fluorinated alkyl ether oligomer, on surface energy and insect residue adhesion properties.

Wohl, Christopher J.↗
NASA NTRS2011

High Frequency PIN-Diode Switches for Radiometer Applications

Internally calibrated radiometers are needed for ocean topography and other missions. Typically internal calibration is achieved with Dicke switching as one of the techniques. We have developed high frequency single-pole double-throw (SPDT) switches in the form of monolithic microwave integrated circuits (MMIC) that can be easily integrated into Dicke switched radiometers that utilize microstrip technology. In particular, the switches we developed can be used for a radiometer such as the one proposed for the Surface Water and Ocean Topography (SWOT) Satellite Mission whose three channels at 92, 130, and 166 GHz would allow for wet-tropospheric path delay correction near coastal zones and over land. This feat is not possible with the current Jason-class radiometers due to their lower frequency signal measurement and thus lower resolution. The MMIC chips were fabricated at NGST using their InP PIN diode process and measured at JPL using high frequency test equipment. Measurement and simulation results will be presented.

PIN-diode↗
NASA NTRS2012

Low Noise Amplifiers and Receivers for Remote Sensing

The study of atmospheric dynamics and climatology depend on accurate and frequent measurements of temperature and humidity profiles of the atmosphere. These measurements furthermore enable highly accurate measurements of ocean topography by providing total column water vapour data for radar path delay correction. The atmospheric temperature profile is characterized at the oxygen molecule absorption frequencies (60 and 118 GHz) and the humidity profile at the water molecule absorption frequencies (23 and 183 GHz). Total column measurements can be achieved by comparing measured radiometric temperatures at atmospheric window channels, such as 90, 130, and 166 GHz. The standard receiver technology for these frequencies was diode mixers with MMIC LNAs being applied at the lower frequencies. The sensitivity of millimeter wave receivers improved significantly with the introduction of the low noise 35 nm gate length InP MMIC amplifiers. We currently achieve 3 dB noise figure at 180 GHz and 2 dB noise figure at 90 GHz with our MMIC low noise amplifiers (LNAs) in room temperature. These amplifiers and the receivers we have built using them made it possible to conduct highly accurate airborne measurements campaigns from the Global Hawk unmanned aerial vehicle, develop millimeter wave internally calibrated radiometers for altimeter radar path delay correction, and build prototypes of large arrays of millimeter receivers for a geostationary interferometric sounder. We use the developed millimeter wave receivers to measure temperature and humidity profiles in the atmosphere and in hurricanes as well as to characterize the path delay error in ocean topography alitmetery.

low noise temperature↗
NASA NTRS2011

Low Noise Amplifiers and Receivers for Remote Sensing

The study of atmospheric dynamics and climatology depend on accurate and frequent measurements of temperature and humidity profiles of the atmosphere. These measurements furthermore enable highly accurate measurements of ocean topography by providing total column water vapour data for radar path delay correction. The atmospheric temperature profile is characterised at the oxygen molecule absorption frequencies (60 and 118 GHz) and the humidity profile at the water molecule absorption frequencies (23 and 183 GHz). Total column measurements can be achieved by comparing measured radiometric temperatures at atmospheric window channels, such as 90, 130 and 166 GHz. The standard receiver technology for these frequencies was diode mixers with MMIC LNAs being applied at the lower frequencies. The sensitivity of millimetre wave receivers improved significantly with the introduction of the low noise 35 nm gate length InP MMIC amplifiers. We currently achieve 3 dB noise figure at 180 GHz and 2 dB noise figure at 90 GHz with our MMIC low noise amplifiers (LNAs) in room temperature. These amplifiers and the receivers we have built using them made it possible to conduct highly accurate airborne measurement campaigns from the Global Hawk unmanned aerial vehicle, develop millimeter wave internally calibrated radiometers for altimeter radar path delay correction, and build prototypes of large arrays of millimeter receivers for a geostationary interferometric sounder. We use the developed millimeter wave receivers to measure temperature and humidity profiles in the atmosphere and in hurricanes as well as to characterize the path delay error in ocean topography altimetry.

low noise amplifier↗
NASA NTRS2014

Global Distribution of Lunar Impact Melt Flows

In this study, we analyzed the distribution and properties of 146 craters with impact melt deposits exterior to their rims. Many of these craters were only recently discovered due to their unusual radar properties in the near-global Mini-RF data set. We find that most craters with exterior deposits of impact melt are small, less than 20 kilometers, and that the smallest craters have the longest melt flows relative to their size. In addition, exterior deposits of impact melt are more common in the highlands than the mare. This may be the result of differing target properties in the highlands and mare, the difference in titanium content, or the greater variation of topography in the highlands. We find that 80 percent of complex craters and 60 percent of simple craters have melt directions that are coincident or nearly coincident with the lowest point in their rim, implying that pre-existing topography plays a dominant role in melt emplacement. This is likely due to movement during crater modification (complex craters) or breached crater rims (simple craters). We also find that impact melt flows have very high circular polarization ratios compared to other features on the Moon. This suggests that their surfaces are some of the roughest material on the Moon at the centimeter to decimeter scale, even though they appear smooth at the meter scale.

Cratering↗
NASA NTRS2014

Validation of TRMM Multi-Satellite Precipitation Analysis (TMPA) Products in the Peruvian Andes

The relevance of accurate and timely rainfall estimates cannot be overstated. The rainfall gauge network is still insufficient across significant areas worldwide. Rainfall estimates fromspaceborne sensors present an opportunity to supplement the existing network and enable the development of critical, near real time applications. However, the societal benefits of such systems can only be realized if the estimates are properly validated and the performance of existing products accurately described. In this study, two products generated by the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) are validated for the Peruvian Andes. This is a region of complex topography that poses significant challenges to the retrieval of rainfall values fromspace. The TMPA products, both research grade (3B42V7) and near real time (3B42RT), are compared against in situ data. Different observation lengths are studied and the results are analyzed in light of geographic, topographic and climatic constraints. The Time Series of the science grade product were also studied under Dynamic TimeWarping and Hierarchical Clustering to streamline intertile comparisons. The TMPA products showa good agreementwith the gauge values, especially formore prolonged observation periods (over 8 days). The validation results display a strong regional dependence as a consequence of differences in the climate and topography. This region-specific performance calls for additional, detailed case studies and localized validation efforts. Overall the TMPAwas found to performadequately and provide quality information for a number of applications requiring timely estimates in convenient formats.

satellites↗
NASA NTRS2015

Airborne Lidar-Based Estimates of Tropical Forest Structure in Complex Terrain: Opportunities and Trade-Offs for REDD+

Background: Carbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas with complex topography present a challenge for lidar remote sensing. Results: We compared digital terrain models (DTM) derived from airborne lidar data from a mountainous region of the Atlantic Forest in Brazil to 35 ground control points measured with survey grade GNSS receivers. The terrain model generated from full-density (approx. 20 returns/sq m) data was highly accurate (mean signed error of 0.19 +/-0.97 m), while those derived from reduced-density datasets (8/sq m, 4/sq m, 2/sq m and 1/sq m) were increasingly less accurate. Canopy heights calculated from reduced-density lidar data declined as data density decreased due to the inability to accurately model the terrain surface. For lidar return densities below 4/sq m, the bias in height estimates translated into errors of 80-125 Mg/ha in predicted aboveground biomass. Conclusions: Given the growing emphasis on the use of airborne lidar for forest management, carbon monitoring, and conservation efforts, the results of this study highlight the importance of careful survey planning and consistent sampling for accurate quantification of aboveground biomass stocks and dynamics. Approaches that rely primarily on canopy height to estimate aboveground biomass are sensitive to DTM errors from variability in lidar sampling density.

Airborne lidar↗
NASA NTRS2015

Stratigraphy of the Caloris Basin, Mercury: Implications for Volcanic History and Basin Impact Melt

Caloris basin, Mercury's youngest large impact basin, is filled by volcanic plains that are spectrally distinct from surrounding material. Post-plains impact craters of a variety of sizes populate the basin interior, and the spectra of the material they have excavated enable the thickness of the volcanic fill to be estimated and reveal the nature of the subsurface. The thickness of the interior volcanic plains is consistently at least 2.5 km, reaching 3.5 km in places, with thinner fill toward the edge of the basin. No systematic variations in fill thickness are observed with long-wavelength topography or azimuth. The lack of correlation between plains thickness and variations in elevation at large horizontal scales within the basin indicates that plains emplacement must have predated most, if not all, of the changes in long-wavelength topography that affected the basin. There are no embayed or unambiguously buried (ghost) craters with diameters greater than 10 km in the Caloris interior plains. The absence of such ghost craters indicates that one or more of the following scenarios must hold: the plains are sufficiently thick to have buried all evidence of craters that formed between the Caloris impact event and the emplacement of the plains; the plains were emplaced soon after basin formation; or the complex tectonic deformation of the basin interior has disguised wrinkle-ridge rings localized by buried craters. That low-reflectance material (LRM) was exposed by every impact that penetrated through the surface volcanic plains provides a means to explore near-surface stratigraphy. If all occurrences of LRM are derived from a single layer, the subsurface LRM deposit is at least 7.5-8.5 km thick and its top likely once made up the Caloris basin floor. The Caloris-forming impact would have generated a layer of impact melt 3-15 km thick; such a layer could account for the entire thickness of LRM. This material would have been derived from a combination of lower crust and upper mantle.

Cratering↗
NASA NTRS2017

Small-Scale Density Variations in the Lunar Crust Revealed by GRAIL

Data from the Gravity Recovery and Interior Laboratory (GRAIL) mission have revealed that approximately 98 percent of the power of the gravity signal of the Moon at high spherical harmonic degrees correlates with the topography. The remaining 2 percent of the signal, which cannot be explained by topography, contains information about density variations within the crust. These high-degree Bouguer gravity anomalies are likely caused by small-scale (10's of km) shallow density variations. Here we use gravity inversions to model the small-scale three-dimensional variations in the density of the lunar crust. Inversion results from three non-descript areas yield shallow density variations in the range of 100-200 kg/m3. Three end-member scenarios of variations in porosity, intrusions into the crust, and variations in bulk crustal composition were tested as possible sources of the density variations. We find that the density anomalies can be caused entirely by changes in porosity. Characteristics of density anomalies in the South Pole-Aitken basin also support porosity as a primary source of these variations. Mafic intrusions into the crust could explain many, but not all of the anomalies. Additionally, variations in crustal composition revealed by spectral data could only explain a small fraction of the density anomalies. Nevertheless, all three sources of density variations likely contribute. Collectively, results from this study of GRAIL gravity data, combined with other studies of remote sensing data and lunar samples, show that the lunar crust exhibits variations in density by plus or minus 10 percent over scales ranging from centimeters to 100’s of kilometers.

J C Jansen↗
NASA NTRS2017

The Climatology of Carbon Monoxide and Water Vapor on Mars as Observed by CRISM and Modeled by the GEM-Mars General Circulation Model

Radiative transfer modeling of near-infrared spectra taken by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) instrument onboard Mars Reconnaissance Orbiter (MRO) enables the column-integrated abundance of carbon monoxide (CO) and water vapor (H 2 O) to be retrieved. These results provide a detailed global description of the seasonal and spatial distribution of CO in the Mars atmosphere and new information about the interannual variability of H2O. The CRISM retrievals show the seasonally and globally averaged carbon monoxide mixing ratio to be near 800 parts per million, but with strong seasonal variations, especially at high latitudes. At low latitudes, the carbon monoxide mixing ratio varies in response to the mean seasonal cycle of surface pressure and shows little variation with topography. At high latitudes, carbon monoxide is depleted in the summer hemisphere by a factor of two or more, while in the winter hemisphere there is relatively higher mixing ratio in regions with low-lying topography. Water vapor shows only modest interannual variations, with the largest observed difference being unusually dry conditions in the wake of the Mars Year 28 global dust storm. Modeling results from the GEM (Global Environmental Multiscale) - Mars general circulation model generally reproduce the observed seasonal and spatial trends and provide insight into the underlying physical processes.

Smith, Michael D.↗
NASA NTRS2018

Improving the SMAP Level-4 Soil Moisture Product

The NASA Soil Moisture Active Passive (SMAP) mission generates, among other data sets, the Level 4 Soil Moisture (L4 SM) product. The L4 SM algorithm is based on the assimilation of SMAP radiometer brightness temperature observations into the NASA Catchment land surface model using a spatially distributed ensemble Kalman filter. The L4 SM data are published with a mean latency of approx. 2.5 days from the time of observation and provide global, three-hourly, 9 km resolution estimates of surface and root-zone soil moisture and related land surface states and fluxes. In 2018, the product was upgraded from Version 3 to Version 4. Underlying the new version is a revised modeling system that includes improved input parameter datasets for land cover, topography, and vegetation height that are based on recent, high quality space-borne remote sensing observations. Land cover inputs were updated to the GlobCover2009 product, which is based on satellite observations from the Medium Resolution Imaging Spectrometer. Topographic statistics now rely on observations from the Shuttle Radar Topography Mission. Finally, vegetation height inputs are derived from space-borne Lidar measurements. Additionally, SMAP Level-2 soil moisture retrievals and in situ soil moisture measurements were used to calibrate a particular Catchment model parameter that governs the recharge of soil moisture from the models root-zone excess reservoir into the surface excess reservoir. Specifically, the replenishment of soil moisture near the surface from below under non-equilibrium conditions was substantially reduced, which brings the models surface soil moisture more in line with the SMAP Level 2 and in situ soil moisture. Finally, the calibration of the assimilated SMAP brightness temperatures changed substantially from Version 3 to Version 4. Considerable effort went into the version upgrade, creating an expectation that the new version is improved over the old version. Indeed, some aspects of the new version are clearly better. However, other aspects are not, and on balance, the overall improvement is modest at best. In this presentation we summarize the skill of the new and old versions vs. independent in situ measurements and in terms of data assimilation diagnostics, including, for example, the statistics of the (soil moisture) analysis increments and the observation minus forecast (brightness temperatures) residuals. We share our experience with trying to improve to the L4 SM product and the lessons learned from the effort.

Reichle, Rolf↗
NASA NTRS2018

Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the GMAO S2S Forecast System

El Nino/Southern Oscillation (ENSO) has far reaching global climatic impacts and so extending useful ENSO forecasts would be of great benefit for society. However, one key variable that has yet to be fully exploited within coupled forecast systems is accurate estimation of near-surface ocean density. Satellite Sea Surface Salinity (SSS), combined with temperature, help to identify ocean density changes and associated mixing near the ocean surface. We assess the impact of satellite SSS observations for improving near-surface dynamics within ocean analyses and how these impact dynamical ENSO forecasts using the NASA GMAO (Global Modeling and Assimilation Office) Sub-seasonal to Seasonal (S2S_v2.1) coupled forecast system (Molod et al. 2018 - i.e. NASA's contribution to the NMME (National Multi-Model Ensemble) project). For all initialization experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF ( Local Ensemble Transform Kalman Filter) scheme similar to Penny et al., 2013. A separate reanalysis additionally assimilates Aquarius V5 (September 2011 to June 2015) and SMAP (Soil Moisture Active Passive) V4 (March 2015 to present) along-track data.We highlight the impact of satellite SSS on ocean reanalyses by comparing validation statistics of experiments that assimilate SSS versus our current prediction system that withholds SSS. We find that near-surface validation versus observed statistics for salinity are slightly degraded when assimilating SSS. This is an expected result due to known biases between SSS (measured by the satellite at approximately 1 centimeter) and in situ measurements (typically measured by Argo floats at 3 meters). On the other hand, a very encouraging result is that both temperature, absolute dynamic topography, and mixed layer statistics are improved with SSS assimilation. Previous work has shown that correcting near-surface density structure via gridded SSS assimilation can improve coupled forecasts. Here we present results of coupled forecasts that are initialized from the GMAO S2S reanalyses that assimilates/withholds along-track (L2) SSS. In particular, we contrast forecasts of the overestimated 2014 El Nino, the big 2015 El Nino, and the minor 2016 La Nina. For each of these ENSO scenarios, assimilation of satellite SSS improves the forecast validation. Improved SSS and density upgrades the mixed layer depth leading to more accurate coupled air/sea interaction.

Hackert, E.↗
NASA NTRS2019

SPARROW: Steam Propelled Autonomous Retrieval Robot for Ocean Worlds

The Steam Propelled Autonomous Retrieval Robot (SPARROW) for Ocean Worlds was a Phase I mission concept study funded under the NASA NIAC program. This report represents the findings of that study and recommendations for future work. SPARROW, envisioned as a soccer ball-sized payload to a primary lander mission, is a propulsively hopping robot for the exploration of Europa's rugged, icy surface. A multi-thruster, passively gimballed robot within a protective, spherical shell, SPARROW is able to freely rotate, self-right, and tumble over chaotic terrains. Europa's abundant surface ice would be harvested as an in situ propellant source. The principal objective of SPARROW is to increase the science return of a Europa landed asset by enabling access to distal, spatially distributed geologic units. The design of mobility systems for Europa is challenging, due in part to its almost entirely unconstrained surface topography and strength. Images returned by Voyager and Galileo yielded resolutions on the order of hundreds of meters per pixel, with localized regions reaching 6 meters per pixel—still far larger than a typical rover. A key benefit of SPARROW's hopping, impact-tolerant design, is that it eliminates the need for a priori information regarding terrain topography and surface strength; no surface reaction forces are required for motion. In this context, SPARROW is believed to be entirely terrain agnostic. In this report we detail the results of three study objectives: i) to quantify the energy required to collect surface ice, change its phase, and maintain propellant temperature, ii) to identify control and estimation strategies that enable SPARROW to successfully reach, and return from, regions of scientific interest, and iii) to characterize the impact of SPARROW's range on likely science return. Five water-based propellant architectures are presented alongside their mass, power, and volume requirements. Monte Carlo simulations of SPARROW hopping and tumbling over 1 km of glacial ice are summarized, characterizing SPARROW's sensitivity to uncertainty in: initial pose, thrust profile, and vehicle-terrain interaction. A science traceability matrix is presented, which details the effect of sortie range on three science goals: constraining Europa's evolutionary morphology, assessing sub-surface ocean habitability, and searching for life and/or biosignatures.

Autonomous↗
NASA NTRS2019

Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the GMAO Seasonal Forecast System

El Nino/Southern Oscillation (ENSO) has far reaching global climatic impacts and so extending useful ENSO forecasts would be of great benefit for society. However, one key variable that has yet to be fully exploited within coupled forecast systems is accurate estimation of near-surface ocean density. Satellite sea surface salinity (SSS), combined with temperature, help to identify ocean density changes and associated mixing near the ocean surface. We assess the impact of satellite SSS observations for improving near-surface dynamics within ocean analyses and how these impact dynamical ENSO forecasts using the NASA GMAO (Global Modeling and Assimilation Office) Sub-seasonal to Seasonal (S2S_v2.1) coupled forecast system (Molod et al. 2018 - i.e. NASA's contribution to the NMME (North American Multi-Model Ensemble) project). For all initialization experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF (Local Ensemble Transform Kalman Filter) scheme similar to Penny et al., 2013. A separate reanalysis additionally assimilates Aquarius V5 (September 2011 to June 2015) and SMAP (Soil Moisture Active Passive satellite) V4.1 (March 2015 to present) along-track data.We highlight the impact of satellite SSS on ocean reanalyses by comparing validation statistics of experiments that assimilate SSS versus our current prediction system that withholds SSS. We find that near-surface validation versus observed statistics for salinity are slightly degraded when assimilating SSS. This is an expected result due to known biases between SSS (measured by satellite at approximately 1-centimeter depth) and in situ measurements (typically measured by Argo floats at 3-meters depth). On the other hand, a very encouraging result is that both temperature, absolute dynamic topography, and mixed layer statistics are improved with SSS assimilation. Previous work has shown that correcting near-surface density structure via gridded SSS assimilation can improve coupled forecasts. Here we present results of coupled forecasts that are initialized from GMAO S2S spring reanalyses that assimilate/withhold along-track (L2) SSS. In particular, we contrast forecasts of the big 2015 El Nino, the 2017 La Nina and the 2018 weak El Nino. For each of these ENSO scenarios, assimilation of satellite SSS improves the forecast validation. Improved SSS and density upgrade the mixed layer depth leading to more accurate coupled air/sea interaction. From March to June 2015, the availability of two overlapping satellite SSS instruments, Aquarius and SMAP, allows a unique opportunity to compare and contrast forecasts initialized with the benefit of these two satellite SSS observation types. We assess the impact of gridded satellite sea surface salinity observations on dynamical ENSO forecasts for the big 2015 El Nino.

Hackert, E.↗
NASA NTRS2020

A Fresh Look at the Stratigraphy of Northern Australe

The roughly circular collection of mare deposits centered at ~38.9°S, 93°E is often re- ferred to as Mare Australe. It is located outside of the Procellarum KREEP Terrain. The circular arrangement of Australe’s mare patches has suggested an ancient, heavily degraded or relaxed impact basin roughly 900 km in diameter. The mare deposits are generally thought to have erupted into smaller post- basin craters. The type, volume, and distribution of mare eruptions potentially resembles the early stages of basin-filling mare events, but which are preserved in Australe and some farside locations. Gravity data suggest that if there was a basin, it is much smaller than originally proposed (now ~600 km) and located in the northern part of Mare Australe, between Humboldt, Milne, and Jenner craters. As a whole, Mare Australe lacks the topography typically associated with a basin; however, northern Australe has a slight topographic depression that roughly corresponds to the basin-like Bouguer gravity signature in the same area. The compositions exposed in Humboldt crater suggest that a preexisting basin might have excavated deeper crustal material. However, the underlying cause of the circularity of Mare Australe’s deposits, particularly those extending outside of the potential impact basin setting, is not yet understood. Thus, Australe may preserve fundamental information about mare volcanism potentially uncoupled from basin formation and structure. The objectives of this study are to use new high- resolution data (images, gravity, topography, and com- position) to reassess Australe’s mare deposits, deter- mine the timing and style of volcanism, identify discrete basalt deposits, and to further characterize the evolution of magmatism and subsurface structure in this area. Here, we focus on the northern Australe deposits (between Humboldt, Jenner, and Milne). As originally noted by Whitford-Stark (1979), Humboldt crater and its ejecta make an excellent stratigraphic marker that can be traced across much of the Australe region. The ejecta serves as a stratigraphic constraint for absolute model ages (AMAs) derived from crater size-frequency distributions (CSFDs).

Stopar, J. D.↗