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Preparing for Lunar Exploration: Geology and Field Training for Astronauts

NASA astronauts will soon return to the Moon, this time to the lunar south pole. Astronauts will perform traverses, make geologic observations, and collect samples to return to Earth. Lessons from Apollo show that science returns were optimized because crews were well-trained in both spacewalk operations and field geology. In that spirit, our team of geologists introduced a revised geologic training program for in-coming NASA astronauts that includes classroom activities and fieldwork and is split over 2 years. Year 1 focuses on an introduction to geologic concepts capped by a field exercise. Year two focuses on climate change, the Moon, other planets, and additional fieldwork. Our geology curriculum supports astronaut observations from the ISS and is the foundation for future Artemis geology training, which will include lunar science and increasingly complex field training in planetary-relevant locations. A final piece of our training program provides geology and field mapping experiences for NASA engineers, flight controllers, and managers, to help them understand the principles of fieldwork and relevance to lunar exploration. The Year 1 geology training must be an effective introduction for astronauts who have little or no background in geology. We focus the training around a narrowly defined field problem and use a week of classroom training to prepare the astronauts with the specific skills and background they need to carry out a field exercise on volcanic features, structures, and landforms of the Taos Plateau, New Mexico. Classroom modules are hands-on, using satellite imagery, maps, analog models, and samples, and provide the astronauts with specific and relevant experience in how to make observations and describe what they see, recognize, and interpret patterns, infer processes from products, and analyze relationships to build a story based on evidence from a variety of data sources. At the end of each classroom day, astronauts work in teams to build a preliminary geologic map of the field area, adding new observations and interpretations as they learn about topics in the classroom. Each team’s bucket list of target areas to visit helps shape their investigations during their week in the field. On the final day in the field, each astronaut team presents a geologic map, cross section, and geologic interpretation

Geology↗

Sage III/ISS Stratospheric Aerosols and Gas Experiment An Earth Science Mission on the International Space Station

Stratospheric aerosols play key roles in the chemistry and radiation balance of the atmosphere and are a key input parameter for global chemistry and climate models. The degree to which aerosols impact chemistry and radiation balance depends primarily on the relative abundance of different sized particles within the sample volume, often referred to as the particle size distribution (PSD). If the PSD is accurately known then other key modeling parameters (e.g., surface area density and effective radius) can be derived. Historically, occultation observations from orbital instruments such as SAGE III/ISS have been used to infer these PSD parameters by inverting the extinction coefficient spectra. However, past efforts routinely failed to account for measurement uncertainty and lacked a rigorous estimate of the inferred PSD uncertainty. We developed a PSD solution algorithm that infers single mode and bimodal distribution parameters and applied this algorithm to the SAGE II and SAGE III/ISS data record. Herein we describe the algorithm, evaluate its performance, and show results from the 2022 Hunga Tonga eruption.

Travis N. Knepp↗

Extending the Utility of Space-Borne Snow Water Equivalent Observations Over Vegetated Areas With Data Assimilation

Snow is a vital component of the earth system, yet no snow-focused satellite remote sensing platform currently exists. In this study, we investigate how synthetic observations of snow water equivalent (SWE) representative of a synthetic aperture radar remote sensing platform could improve spatiotemporal estimates of snowpack. We use a fraternal twin observing system simulation experiment, specifically investigating how much snow simulated using widely used models and forcing data could be improved by assimilating synthetic observations of SWE. We focus this study across a 24° x 37° domain in the western USA and Canada, simulating snow at 250 m resolution and hourly time steps in water year 2019. We perform two data assimilation experiments, including (1) a simulation excluding synthetic observations in forests where canopies obstruct remote sensing retrievals and (2) a simulation inferring snow distribution in forested grid cells using synthetic observations from nearby canopy-free grid cells. Results found that, relative to a nature run, or assumed true simulation of snow evolution, assimilating synthetic SWE observations improved average SWE biases at maximum snowpack timing in shrub, grass, crop, bare-ground, and wetland land cover types from 14 %, to within 1 %. However, forested grid cells contained a disproportionate amount of SWE volume. In forests, SWE mean absolute errors at the time of maximum snow volume were 111 mm and average SWE biases were on the order of 150 %. Here the data assimilation approach that estimated forest SWE using observations from the nearest canopy-free grid cells substantially improved these SWE biases (18 %) and the SWE mean absolute error (27 mm). Simulations employing data assimilation also improved estimates of the temporal evolution of both SWE and runoff, even in spring snowmelt periods when melting snow and high snow liquid water content prevented synthetic SWE retrievals. In fact, in the Upper Colorado River region, melt-season SWE biases were improved from 63 % to within 1 %, and the Nash–Sutcliffe efficiency of runoff improved from −2.59 to 0.22. These results demonstrate the value of data assimilation and a snow-focused globally relevant remote sensing platform for improving the characterization of SWE and associated water availability.

Justin Pflug↗

Remote sensing of seasonal distribution of precipitable water vapor over the oceans and inference of boundary layer structure

Over the ocean satellite infrared spectral measurements in the 18 micrometer water vapor band and the 11 micrometer window region were used to derive precipitable water vapor, w, in the atmosphere and the sea surface temperature, SST. Seasonal maps of w on the oceans derived from these data reveal the dynamical influence of the large scale atmospheric circulation. With the help of a model for the vertical distribution of water vapor, the configuration of the atmospheric boundary layer over the oceans can be inferred from w when the information of SST is combined. The gross seasonal mean structure of the boundary layer inferred in this fashion reveals the broad areas of the trade wind inversion and the convectively active areas such as the intertropical convergence zones.

Prabhakara, C.↗

Remote Sensing of Crystal Shapes in Ice Clouds

Ice crystals in clouds exist in a virtually limitless variation of geometries. The most basic shapes of ice crystals are columnar or plate-like hexagonal prisms with aspect ratios determined by relative humidity and temperature. However, crystals in ice clouds generally display more complex structures owing to aggregation, riming and growth histories through varying temperature and humidity regimes. Crystal shape is relevant for cloud evolution as it affects microphysical properties such as fall speeds and aggregation efficiency. Furthermore, the scattering properties of ice crystals are affected by their general shape, as well as by microscopic features such as surface roughness, impurities and internal structure. To improve the representation of ice clouds in climate models, increased understanding of the global variation of crystal shape and how it relates to, e.g., location, cloud temperature and atmospheric state is crucial. Here, the remote sensing of ice crystal macroscale and microscale structure from airborne and space-based lidar depolarization observations and multi-directional measurements of total and polarized reflectances is reviewed. In addition, a brief overview is given of in situ and laboratory observations of ice crystal shape as well as the optical properties of ice crystals that serve as foundations for the remote sensing approaches. Lidar depolarization is generally found to increase with increasing cloud height and to vary with latitude. Although this variation is generally linked to the variation of ice crystal shape, the interpretation of the depolarization remains largely qualitative and more research is needed before quantitative conclusions about ice shape can be deduced. The angular variation of total and polarized reflectances of ice clouds has been analyzed by numerous studies in order to infer information about ice crystal shapes from them. From these studies it is apparent that pristine crystals with smooth surfaces are generally inconsistent with the data and thus crystal impurity, distortion or surface roughness is prevalent. However, conclusions about the dominating ice shapes are often inconclusive and contradictory and are highly dependent on the limited selection of shapes included in the investigations. Since ice crystal optical properties are mostly determined by the aspect ratios of the crystal components and their microscale structure, it is advised that remote sensing applications focus on the variation of these ice shape characteristics, rather than on the macroscale shape or habit. Recent studies use databases with nearly continuous ranges of crystal component aspect ratio and-or roughness levels to infer the variation of ice crystal shape from satellite and airborne remote sensing measurements. Here, the rationale and results of varying strategies for the remote sensing of ice crystal shape are reviewed. Observed systematic variations of ice crystal geometry with location, cloud height and atmospheric state suggested by the data are discussed. Finally, a prospective is given on the future of the remote sensing of ice cloud particle shapes.

clouds↗

GEDI Launches a New Era of Biomass Inference from Space

Accurate estimation of aboveground forest biomass stocks is required to assess the impacts of land use changes such as deforestation and subsequent regrowth on concentrations of atmospheric CO 2 . The Global Ecosystem Dynamics Investigation (GEDI) is a lidar mission launched by NASA to the International Space Station in 2018. GEDI was specifically designed to retrieve vegetation structure within a novel, theoretical sampling design that explicitly quantifies biomass and its uncertainty across a variety of spatial scales. In this paper we provide the estimates of pan-tropical and temperate biomass derived from two years of GEDI observations. We present estimates of mean biomass densities at 1 km resolution, as well as estimates aggregated to the national level for every country GEDI observes, and at the sub-national level for the United States. For all estimates we provide the standard error of the mean biomass. These data serve as a baseline for current biomass stocks and their future changes, and the mission’s integrated use of formal statistical inference points the way towards the possibility of a new generation of powerful monitoring tools from space.

Ralph Dubayah↗

The Induced Magnetic Field of the Moon: Conductivity Profiles and Inferred Temperature

Electromagnetic induction in the moon driven by fluctuations of the interplanetary magnetic field is used to determine the lunar bulk electrical conductivity. The present data clearly show the north-south and east-west transfer function difference as well as high frequency rollover. The difference is shown to be compatible over the mid-frequency range with a noise source associated with the compression of the local remanent field by solar wind dynamic pressure fluctuations. Models for two, three, and four layer; current layer, double current layer, and core plus current layer moons are generated by inversion of the data using a theory which incorporates higher order multipoles. Core radii conductivities generally are in the range 1200 to 1300 km and 0.001 to 0.003 mhos/m; and for the conducting shell 1500 to 1700 km with 0.0001 to 0.0007 mhos/m with an outer layer taken as nonconducting. Core temperature based on available olivine data is 700 to 1000 C.

Sonett, C. P.↗

The induced magnetic field of the moon - Conductivity profiles and inferred temperature.

Electromagnetic induction in the moon driven by fluctuations of the interplanetary magnetic field is used to determine the lunar bulk electrical conductivity. The earlier data are now augmented by an order of magnitude. The present data clearly show the north-south and east-west transfer function difference as well as the high-frequency rollover suggested earlier. The difference is shown to be compatible over the midfrequency range (0.001 to 0.01 Hz) with a noise source associated with the compression of the local remanent field by solar wind dynamic pressure fluctuations. The rollover of the transfer functions is shown to result from higher order magnetic multipole radiation; electric multipoles appear supressed, although a vestigial TM interaction may still be present. Models for two, three, and four layer; current layer, double current layer, and core plus current layer moons are generated by inversion of the data, using a theory that incorporates higher-order multipoles.

Sonett, C. P.↗

Sea ice motions in the central arctic ice central arctic pack ice as inferred from AVHRR imagery

Synoptic observations of ice motion in the Arctic Basin are currently limited to those acquired by drifting buoys and, more recently, radar data from ERS-1. Buoys are not uniformly distributed throughout the Arctic, and SAR coverage is limited regionally and temporally due to the data volume, swath width, processing requirements, and power needs of the SAR. Additional ice-motion observations that can map ice responses simultaneously over large portions of the Arctic on daily to weekly time intervals are thus needed to augment the SAR and buoy data and to provide an intermediate-scale measure of ice drift suitable for climatological analyses and ice modeling. Merging the remotely-sensed ice motions with SAR, AVHRR, OLS, and SSM/I imagery permits studies of ice processes over a range of space and time scales. A medium-resolution passive microwave sensor might be ideal for this purpose, but no such satellite will be available in the near future. Combinations of existing data types are thus likely to be our best bet for generating motion fields with a coverage and resolution best suited to climate studies. Principal objectives of this project are to: (1) demonstrate whether sufficient ice features and ice motion existed within the consolidated ice pack to permit motion tracking using AVHRR imagery; (2) determine the limits imposed on AVHRR mapping by cloud cover; and (3) test the applicability of AVHRR-derived motions in studies of ice-atmosphere interactions.

Emery, William↗

Sea ice motions in the Central Arctic pack ice as inferred from AVHRR imagery

Synoptic observations of ice motion in the Arctic Basin are currently limited to those acquired by drifting buoys and, more recently, radar data from ERS-1. Buoys are not uniformly distributed throughout the Arctic, and SAR coverage is currently limited regionally and temporally due to the data volume, swath width, processing requirements, and power needs of the SAR. Additional ice-motion observations that can map ice responses simultaneously over large portions of the Arctic on daily to weekly time intervals are thus needed to augment the SAR and buoys data and to provide an intermediate-scale measure of ice drift suitable for climatological analyses and ice modeling. Principal objectives of this project were to: (1) demonstrate whether sufficient ice features and ice motion existed within the consolidated ice pack to permit motion tracking using AVHRR imagery; (2) determine the limits imposed on AVHRR mapping by cloud cover; and (3) test the applicability of AVHRR-derived motions in studies of ice-atmosphere interactions. Each of these main objectives was addressed. We conclude that AVHRR data, particularly when blended with other available observations, provide a valuable data set for studying sea ice processes. In a follow-on project, we are now extending this work to cover larger areas and to address science questions in more detail.

Emery, William↗

Aerosol Retrievals Using Channel 1 and 2 AVHRR Data

The effect of tropospheric aerosols on global climate via the direct and indirect radiative forcings is one of the largest remaining uncertainties in climate change studies. Current assessments of the direct aerosol radiative effect mainly focus on sulfate aerosols. It has become clear, however, that other aerosol types like soil dust and smoke from biomass burning are also likely to be important climate forcing factors. The magnitude and even the sign of the climate forcing caused by these aerosol types is still unknown. General circulation models (GCMs) can be used to estimate the climatic effect of the direct radiative forcing by tropospheric and stratospheric aerosols. Aerosol optical properties are already parameterized in the Goddard Institute for Space Studies GCM. Once the global distribution of aerosol properties (optical thickness, size distribution, and chemical composition) is available, the calculation of the direct aerosol forcing is rather straighfforward. However, estimates of the indirect aerosol effect require additional knowledge of the physics and chemistry of aerosol-cloud interactions which are still poorly understood. One of the main objectives of the Global Aerosol Climatology Project, established in 1998 as a joint initiative of NASA's Radiation Science Program and GEWEX, is to infer the global distribution of aerosols, their properties, and their seasonal and interannual variations for the full period of available satellite data. This will be accomplished primarily through a systematic application of multichannel aerosol retrieval algorithms to existing satellite data and advanced 3-dimensional aerosol chemistry/transport models. In this paper we outline the methodology of analyzing channel 1 and 2 AVHRR radiance data over the oceans and describe preliminary retrieval results.

Mishchenko, Michael I.↗

The interpretation of remotely sensed cloud properties from a model paramterization perspective

A study has been made of the relationship between mean cloud radiative properties and cloud fraction in stratocumulus cloud systems. The analysis is of several Land Resources Satellite System (LANDSAT) images and three hourly International Satellite Cloud Climatology Project (ISCCP) C-1 data during daylight hours for two grid boxes covering an area typical of a general circulation model (GCM) grid increment. Cloud properties were inferred from the LANDSAT images using two thresholds and several pixel resolutions ranging from roughly 0.0625 km to 8 km. At the finest resolution, the analysis shows that mean cloud optical depth (or liquid water path) increases somewhat with increasing cloud fraction up to 20% cloud coverage. More striking, however, is the lack of correlation between the two quantities for cloud fractions between roughly 0.2 and 0.8. When the scene is essentially overcast, the mean cloud optical tends to be higher. Coarse resolution LANDSAT analysis and the ISCCP 8-km data show lack of correlation between mean cloud optical depth and cloud fraction for coverage less than about 90%. This study shows that there is perhaps a local mean liquid water path (LWP) associated with partly cloudy areas of stratocumulus clouds. A method has been suggested to use this property to construct the cloud fraction paramterization in a GCM when the model computes a grid-box-mean LWP.

HARSHVARDHAN↗

Remote sensing of seasonal distribution of precipitable water vapor over the oceans and the inference of boundary-layer structure

From the depth of the water vapor spectral lines in the 8-9 micron window region, measured by the Nimbus 4 Infrared Interferometer Spectrometer (IRIS) with a resolution of about 3/cm, the precipitable water vapor over the oceans is remotely sensed. In addition the IRIS spectral data in the 11-13 micron window region have been used to derive the sea surface temperature (SST). Seasonal maps of w on the oceans deduced from the spectral data reveal the dynamical influence of the large-scale atmospheric circulation. With the help of a model for the vertical distribution of water vapor, the configuration of the atmospheric boundary layer over the oceans can be inferred from these remotely sensed w and SST. The gross seasonal mean structure of the boundary layer inferred in this fashion reveals the broad areas of trade wind inversion and the convectively active areas such as the ITCZ. The derived information is in reasonable agreement with some observed climatological patterns over the oceans.

Prabhakara, C.↗

Precision Requirements for Space-based XCO2 Data

Precision requirements have been determined for the column-averaged CO2 dry air mole fraction (X(sub CO2)) data products to be delivered by the Orbiting Carbon Observatory (OCO). These requirements result from an assessment of the amplitude and spatial gradients in X(sub CO2), the relationship between X(sub CO2) precision and surface CO2 flux uncertainties calculated from inversions of the X(sub CO2) data, and the effects of X,,Z biases on CO2 flux inversions. Observing system simulation experiments and synthesis inversion modeling demonstrate that the OCO mission design and sampling strategy provide the means to achieve the X(sub CO2) precision requirements. The impact of X(sub CO2) biases on CO2 flux uncertainties depend on their spatial and temporal extent since CO2 sources and sinks are inferred from regional-scale X(sub CO2) gradients. Simulated OCO sampling of the TRACE-P CO2 fields shows the ability of X(sub CO2) data to constrain CO2 flux inversions over Asia and distinguish regional fluxes from India and China.

Miller, C. E.↗

Partitioning of ocean and land uptake of CO2 as inferred by delta C-13 measurements from the NOAA Climate Monitoring and Diagnostics Laboratory Global Air Sampling Network

Using delta C-13 measurements in atmospheric CO2 from a cooperative global air sampling network, we determined the partitioning of the net uptake of CO2 between ocean and land as a function of latitude and time. The majority of delta C-13 measurements were made at the Institute of Arctic and Alpine Research (INSTAAR) of the University of Colorado. We perform an inverse deconvolution of both CO2 and delta C-13 observations, using a two-dimensional model of atmospheric transport. Also, the discrimination against C-13 by plant photosynthesis, as a function of latitude and time, is calculated from global runs of the simple biosphere (SiB) model. Uncertainty due to the longitudinal structure of the data, which is not represented by the model, is studied through a bootstrap analysis by adding and omitting measurement sites. The resulting error estimates for our inferred sources and sinks are of the order of 1 GTC (1 GTC = 10(exp 15) gC). Such error bars do not reflect potential systematic errors arising from our estimates of the isotopic disequilibria between the atmosphere and the oceans and biosphere, which are estimated in a separate sensitivity analysis. With respect to global totals for 1992 we found that 3.2 GTC of carbon dissolved into the ocean and that 1.5 GTC were sequestered by land ecosystems. Northern hemisphere ocean gyres north of 15 deg N absorbed 2.7 GTC. The equatorial oceans between 10 deg S and 10 deg N were a net source to the atmosphere of 0.9 GTC. We obtained a sink of 1.6 GTC in southern ocean gyres south of 20 deg S, although the deconvolution is poorly constrained by sparse data coverage at high southern latitudes. The seasonal uptake of CO2 in the northern gyres appears to be correlated with a bloom of phytoplankton in surface waters. On land, northern temperate and boreal ecosystems between 35 deg N and 65 deg N were found to be a major sink of CO2 in 1992, as large as 3.5 GTC. Northern tropical ecosystems (equator-30 deg N) appear to be a net source to the source to the atmosphere of 2 GTC which could reflect biomass burning. A small sink, 0.3 GTC, was inferred for southern tropical ecosystems (30 deg S-equator).

Ciais, Philippe↗

Chlorine Deactivation in the Lower Stratospheric Polar Regions during late Winter: Results from UARS

Recovery from enhanced chlorine conditions in the lower stratospheric polar regions of both hemispheres is investigated using data from the Upper Atmosphere Research Satellite (UARS). Microwave Limb Sounder (MLS) measurements of ClO within the polar vortices are used to infer ClO(sub x) (ClO + 2Cl202) abundances that are then correlated with simultaneous Cryogenic Limb Array Etalon Spectrometer (CLAES) measurements of ClON02 and Halogen Occultation Experiment (HALOE) measurements of HCl obtained starting within 5 days of the end of the MLS and CLAES high-latitude observing periods in each hemisphere. Time series of vortex-averaged mixing ratios are calculated on two potential temperature surfaces (585 K and 465 K) in the lower stratosphere for approximately month-long intervals during late winter: August 17 - September 17, 1992, in the southern hemisphere and February 12 - March 16, 1993, in the northern hemisphere. The observed mixing ratios are adjusted for the effects of vertical transport using diabatic vertical velocities estimated from CLAES tracer data. In the northern hemisphere, the decrease in ClO, is balanced on both surfaces by an increase in ClON02- In the southern hemisphere, continuing polar stratospheric cloud activity prevents ClO from undergoing sustained decline until about September 3. In contrast to the northern hemisphere, there is no significant chemical change in vortex-averaged ClON02 at 465 K, and there is an apparent decrease in ClON02 at 585 K, even after the enhanced ClO abundances have started to recede. Results from the SLIMCAT chemical transport model initialized with UARS data and run with OH + ClO yields HCl + 02 as an 8% channel suggest that the primary recovery product in the south during this time period is not ClON02, but HCl. HALOE HCl mixing ratios are extrapolated back to the time of the MLS and CLAES data. At 585 K, the chlorine budget can be made to balance by extrapolating HCl back to a value of 0.6 parts per billion by volume (ppbv) at the beginning of the study period; at 465 K, the contribution from extrapolated HCl is not sufficient to offset the loss in ClOx, and there is a slight imbalance between the decrease in reactive chlorine and the change in chlorine reservoirs. The difficulty in closing the chlorine budget in the southern hemisphere may arise from complications caused by ongoing activation, incomplete photochemical assumptions, and/or inadequate data quality.

Santee, M. L.↗

Measurements of the cosmic background radiation

Maps of the large scale structure (theta is greater than 6 deg) of the cosmic background radiation covering 90 percent of the sky are now available. The data show a very strong 50-100 sigma (statistical error) dipole component, interpreted as being due to our motion, with a direction of alpha = 11.5 + or - 0.15 hours, sigma = -5.6 + or - 2.0 deg. The inferred direction of the velocity of our galaxy relative to the cosmic background radiation is alpha = 10.6 + or - 0.3 hours, sigma = -2.3 + or - 5 deg. This is 44 deg from the center of the Virgo cluster. After removing the dipole component, the data show a galactic signature but no apparent residual structure. An autocorrelation of the residual data, after substraction of the galactic component from a combined Berkeley (3 mm) and Princeton (12 mm) data sets, show no apparent structure from 10 to 180 deg with a rms of 0.01 mK(sup 2). At 90 percent confidence level limit of .00007 is placed on a quadrupole component.

Lubin, P.↗