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Lunar soil evolution processes and Apollo 16 core 60013/60014

Soils of the 62-cm deep Apollo 16 double drive tube 60013/14 are mature at the top and submature at the bottom. Modal analyses of 5529 grains from the 90-150 micrometers and the 500-1000 micrometers fractions from 12 levels of the core show that, in general, agglutinate abundance increases somewhat monotonically to the top and mimics the Is/FeO profile. There is a general decrease in the modal abundance of monomineralic fragments towards the top, suggesting that agglutinates were formed in part at the expense of monomineralic grains, especially feldspars, which are by far the most abundant mineral in these soils. In detail, the top 27 cm of the core differs from the bottom 21 cm, and the middle 14 cm is intermediate in its properties. In the upper segment, variations in the abundances of feldspars correspond with those of feldspathic fragmental breccias and cataclastic anorthosites; in the bottom segment, a similar but weak correspondence between feldspars and crystalline matrix breccias is observed. Mixing of the comminuted products of these three rock types likely produced the bulk of the core material. Many single feldspars in all size fractions are remarkably fresh, show no damage from shock, and are similar in appearance to the large feldspars in anorthosites and feldspathic fragmental breccias, which we consider to be the primary sources of single feldspars in this core. Major (Na, Al, Si, K, Ca) and minor (Fe, Ba) element analyses of 198 single feldspar grains indicate the presence of only one population of feldspars, which is consistent with our interpretation of feldspar provenance. Classification of 890 monomineralic feldspar, olivine, pyroxene, and glass spherules on the basis of the presence or absence of thin brownish coating--related to reworking at the surface--shows that coated grains are much more abundant in the top segment than in the bottom segment. A comparison with the mixing and maturation model (McKay et al., 1977) of soils in the core 60009/10, some 60 m away from 60013/14, shows that mixtures of an immature, nearly pure plagioclase soil (dominant in 60009/10) and another immature, crystalline breccia-rich soil (dominant in 60013/14) may have matured through in situ reworking to produce the soils under investigation. We conclude that the soils in this core are products of mixing along soil evolution Path 2 of McKay et al. (1974). Superimposed on that soil column is the reworking of the upper part, which has evolved more recently along Path 1. This core thus represents a consanguineous column of the lunar regolith with an upper reworked segment.

short duration↗

Field Observations of Soil Moisture Variability across Scales

In this study, over 36,000 ground-based soil moisture measurements collected during the SGP97, SGP99, SMEX02, and SMEX03 field campaigns were analyzed to characterize the behavior of soil moisture variability across scales. The field campaigns were conducted in Oklahoma and Iowa in the central USA. The Oklahoma study region is sub-humid with moderately rolling topography, while the Iowa study region is humid with low-relief topography. The relationship of soil moisture standard deviation, skewness and the coefficient of variation versus mean moisture content was explored at six distinct extent scales, ranging from 2.5 m to 50 km. Results showed that variability generally increases with extent scale. The standard deviation increased from 0.036 cm3/cm3 at the 2.5-m scale to 0.071 cm3/cm3 at the 50-km scale. The log standard deviation of soil moisture increased linearly with the log extent scale, from 16 m to 1.6 km, indicative of fractal scaling. The soil moisture standard deviation versus mean moisture content exhibited a convex upward relationship at the 800-m and 50-km scales, with maximum values at mean moisture contents of roughly 0.17 cm3/cm3 and 0.19 cm3/cm3, respectively. An empirical model derived from the observed behavior of soil moisture variability was used to estimate uncertainty in the mean moisture content for a fixed number of samples at the 800-m and 50-km scales, as well as the number of ground-truth samples needed to achieve 0.05 cm3/cm3 and 0.03 cm3/cm3 accuracies. The empirical relationships can also be used to parameterize surface soil moisture variations in land surface and hydrological models across a range of scales. To our knowledge, this is the first study to document the behavior of soil moisture variability over this range of extent scales using ground-based measurements. Our results will contribute not only to efficient and reliable satellite validation, but also to better utilization of remotely sensed soil moisture products for enhanced modeling and prediction.

Famiglietti, James S.↗

Constitutive Soil Properties for Unwashed Sand and Kennedy Space Center

Accurate soil models are required for numerical simulations of land landings for the Orion Crew Exploration Vehicle. This report provides constitutive material models for one soil, unwashed sand, from NASA Langley's gantry drop test facility and three soils from Kennedy Space Center (KSC). The four soil models are based on mechanical and compressive behavior observed during geotechnical laboratory testing of remolded soil samples. The test specimens were reconstituted to measured in situ density and moisture content. Tests included: triaxial compression, hydrostatic compression, and uniaxial strain. A fit to the triaxial test results defines the strength envelope. Hydrostatic and uniaxial tests define the compressibility. The constitutive properties are presented in the format of LS-DYNA Material Model 5: Soil and Foam. However, the laboratory test data provided can be used to construct other material models. The four soil models are intended to be specific to the soil conditions discussed in the report. The unwashed sand model represents clayey sand at high density. The KSC models represent three distinct coastal sand conditions: low density dry sand, high density in-situ moisture sand, and high density flooded sand. It is possible to approximate other sands with these models, but the results would be unverified without geotechnical tests to confirm similar soil behavior.

Thomas, Michael A.↗

Constitutive Soil Properties for Cuddeback Lake, California and Carson Sink, Nevada

Accurate soil models are required for numerical simulations of land landings for the Orion Crew Exploration Vehicle. This report provides constitutive material modeling properties for four soil models from two dry lakebeds in the western United States. The four soil models are based on mechanical and compressive behavior observed during geotechnical laboratory testing of remolded soil samples from the lakebeds. The test specimens were reconstituted to measured in situ density and moisture content. Tests included: triaxial compression, hydrostatic compression, and uniaxial strain. A fit to the triaxial test results defines the strength envelope. Hydrostatic and uniaxial tests define the compressibility. The constitutive properties are presented in the format of LS-DYNA Material Model 5: Soil and Foam. However, the laboratory test data provided can be used to construct other material models. The four soil models are intended to be specific only to the two lakebeds discussed in the report. The Cuddeback A and B models represent the softest and hardest soils at Cuddeback Lake. The Carson Sink Wet and Dry models represent different seasonal conditions. It is possible to approximate other clay soils with these models, but the results would be unverified without geotechnical tests to confirm similar soil behavior.

Thomas, Michael A.↗

Temporal Stability of Surface Roughness Effects on Radar Based Soil Moisture Retrieval During the Corn Growth Cycle

A representative soil surface roughness parameterization needed for the retrieval of soil moisture from active microwave satellite observation is difficult to obtain through either in-situ measurements or remote sensing-based inversion techniques. Typically, for the retrieval of soil moisture, temporal variations in surface roughness are assumed to be negligible. Although previous investigations have suggested that this assumption might be reasonable for natural vegetation covers (Moran et al. 2002, Thoma et al. 2006), insitu measurements over plowed agricultural fields (Callens et al. 2006) have shown that the soil surface roughness can change considerably over time. This paper reports on the temporal stability of surface roughness effects on radar observations and soil moisture retrieved from these radar observations collected once a week during a corn growth cycle (May 10th - October 2002). The data set employed was collected during the Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) field campaign covering this 2002 corn growth cycle and consists of dual-polarized (HH and VV) L-band (1.6 GHz) acquired at view angles of 15, 35, and 55 degrees. Cross-polarized L baud radar data were also collected as part of this experiment, but are not used in the analysis reported on here. After accounting for vegetation effects on radar observations, time-invariant optimum roughness parameters were determined using the Integral Equation Method (IEM) and radar observations acquired over bare soil and cropped conditions (the complete radar data set includes entire corn growth cycle). The optimum roughness parameters, soil moisture retrieval uncertainty, temporal distribution of retrieval errors and its relationship with the weather conditions (e.g. rainfall and wind speed) have been analyzed. It is shown that over the corn growth cycle, temporal roughness variations due to weathering by rain are responsible for almost 50% of soil moisture retrieval uncertainty depending on the sensing configuration. The effects of surface roughness variations are found to be smallest for observations acquired at a view angle of 55 degrees and HH polarization. A possible explanation for this result is that at 55 degrees and HH polarization the effect of vertical surface height changes on the observed radar response are limited because the microwaves travel parallel to the incident plane and as a result will not interact directly with vertically oriented soil structures.

Joseph, A.T.↗

Orion Landing Simulation Eight Soil Model Comparison

LS-DYNA finite element simulations of a rigid Orion Crew Module (CM) were used to investigate the CM impact behavior on eight different soil models. Ten different landing conditions, characterized by the combination of CM vertical and horizontal velocity, hang angle, and roll angle were simulated on the eight different soils. The CM center of gravity accelerations, pitch angle, kinetic energy, and soil contact forces were the outputs of interest. The simulation results are presented, with comparisons of the CM behavior on the different soils. The soils analyzed in this study can be roughly categorized as soft, medium, or hard, according to the CM accelerations that occur when landing on them. The soft group is comprised of the Carson Sink Wet soil and the Kennedy Space Center (KSC) Low Density Dry Sand. The medium group includes Carson Sink Dry, the KSC High Density In-Situ Moisture Sand and High Density Flooded Sand, and Cuddeback B. The hard soils are Cuddeback A and the Gantry Unwashed Sand. The softer soils were found to produce lower peak accelerations, have more stable pitch behavior, and to be less sensitive to the landing conditions. This investigation found that the Cuddeback A soil produced the highest peak accelerations and worst stability conditions, and that the best landing performance was achieved on the KSC Low Density Dry Sand.

Mark, Stephen D.↗

Evaluating the Utility of Remotely-Sensed Soil Moisture Retrievals for Operational Agricultural Drought Monitoring

Soil moisture is a fundamental data source used by the United States Department of Agriculture (USDA) International Production Assessment Division (IPAD) to monitor crop growth stage and condition and subsequently, globally forecast agricultural yields. Currently, the USDA IPAD estimates surface and root-zone soil moisture using a two-layer modified Palmer soil moisture model forced by global precipitation and temperature measurements. However, this approach suffers from well-known errors arising from uncertainty in model forcing data and highly simplified model physics. Here we attempt to correct for these errors by designing and applying an Ensemble Kalman filter (EnKF) data assimilation system to integrate surface soil moisture retrievals from the NASA Advanced Microwave Scanning Radiometer (AMSR-E) into the USDA modified Palmer soil moisture model. An assessment of soil moisture analysis products produced from this assimilation has been completed for a five-year (2002 to 2007) period over the North American continent between 23degN - 50degN and 128degW - 65degW. In particular, a data denial experimental approach is utilized to isolate the added utility of integrating remotely-sensed soil moisture by comparing EnKF soil moisture results obtained using (relatively) low-quality precipitation products obtained from real-time satellite imagery to baseline Palmer model runs forced with higher quality rainfall. An analysis of root-zone anomalies for each model simulation suggests that the assimilation of AMSR-E surface soil moisture retrievals can add significant value to USDA root-zone predictions derived from real-time satellite precipitation products.

Bolten, John D.↗

The Biotoxicity of Mars Soils

Recent evidence from the Opportunity and Spirit rovers suggests that the soils on Mars might be very high in biotoxic materials induding sulfate salts, chlorides, and acidifying agents. Yet, very little is known about how the chemistries of Mars soils might affect the survival and growth of terrestrial microorganisms. The primary objectives of the proposed research will be to: (1) prepare and characterize Mars analog soils amended with potential biotoxic levels of sulfates, chlorides, and acidifying minerals; (2) use the stimulants to conduct a series of toxicology assays to determine if terrestrial microorganisms from spacecraft or extreme environments can survive direct exposure to the biotoxic soils, and (3) mix soils from extreme environments on Earth into Mars analog soils to determine if terrestrial microorganisms can grow and replicate under Martian conditions. The Mars analog soils will be thoroughly characterized by a wide diversity of soil chemistry assays to determine the exact nature of the soluble biotoxic components following hydration. The microbial experiments will be designed to test the effects of Mars stimulants on microbial survival, growth and replication during direct challenge experiments. Toxicology experiments will be designed to mimic terrestrial microbes coming into contact with biotoxic soils with and without liquid water. Results are expected to help" ... characterize the limits of life in ... planetary environments ... " and may help constrain the search for life on Mars.

Kerney, Krystal↗

Calculating Soil Wetness, Evapotranspiration and Carbon Cycle Processes Over Large Grid Areas Using a New Scaling Technique

Soil wetness typically shows great spatial variability over the length scales of general circulation model (GCM) grid areas (approx 100 km ), and the functions relating evapotranspiration and photosynthetic rate to local-scale (approx 1 m) soil wetness are highly non-linear. Soil respiration is also highly dependent on very small-scale variations in soil wetness. We therefore expect significant inaccuracies whenever we insert a single grid area-average soil wetness value into a function to calculate any of these rates for the grid area. For the particular case of evapotranspiration., this method - use of a grid-averaged soil wetness value - can also provoke severe oscillations in the evapotranspiration rate and soil wetness under some conditions. A method is presented whereby the probability distribution timction(pdf) for soil wetness within a grid area is represented by binning. and numerical integration of the binned pdf is performed to provide a spatially-integrated wetness stress term for the whole grid area, which then permits calculation of grid area fluxes in a single operation. The method is very accurate when 10 or more bins are used, can deal realistically with spatially variable precipitation, conserves moisture exactly and allows for precise modification of the soil wetness pdf after every time step. The method could also be applied to other ecological problems where small-scale processes must be area-integrated, or upscaled, to estimate fluxes over large areas, for example in treatments of the terrestrial carbon budget or trace gas generation.

Sellers, Piers↗

The NASA Soil Moisture Active Passive (SMAP) Mission - Science and Data Product Development Status

The Soil Moisture Active Passive (SMAP) mission, planned for launch in late 2014, has the objective of frequent, global mapping of near-surface soil moisture and its freeze-thaw state. The SMAP measurement system utilizes an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna. The instruments will operate on a spacecraft in a 685 km polar orbit with 6am/6pm nodal crossings, viewing the surface at a constant 40-degree incidence angle with a 1000-km swath width, providing 3-day global coverage. Data from the instruments will yield global maps of soil moisture and freeze/thaw state at 10 km and 3 km resolutions, respectively, every two to three days. The 10-km soil moisture product will be generated using a combined radar and radiometer retrieval algorithm. SMAP will also provide a radiometer-only soil moisture product at 40-km spatial resolution and a radar-only soil moisture product at 3-km resolution. The relative accuracies of these products will vary regionally and will depend on surface characteristics such as vegetation water content, vegetation type, surface roughness, and landscape heterogeneity. The SMAP soil moisture and freeze/thaw measurements will enable significantly improved estimates of the fluxes of water, energy and carbon between the land and atmosphere. Soil moisture and freeze/thaw controls of these fluxes are key factors in the performance of models used for weather and climate predictions and for quantifYing the global carbon balance. Soil moisture measurements are also of importance in modeling and predicting extreme events such as floods and droughts. The algorithms and data products for SMAP are being developed in the SMAP Science Data System (SDS) Testbed. In the Testbed algorithms are developed and evaluated using simulated SMAP observations as well as observational data from current airborne and spaceborne L-band sensors including data from the SMOS and Aquarius missions. We report here on the development status of the SMAP data products. The Testbed simulations are designed to capture various sources of errors in the products including environment effects, instrument effects (nonideal aspects of the measurement system), and retrieval algorithm errors. The SMAP project has developed a Calibration and Validation (Cal/Val) Plan that is designed to support algorithm development (pre-launch) and data product validation (post-launch). A key component of the Cal/Val Plan is the identification, characterization, and instrumentation of sites that can be used to calibrate and validate the sensor data (Level l) and derived geophysical products (Level 2 and higher).

Nloku, E.↗

Numerical Simulation of Rocket Exhaust Interaction with Lunar Soil

This technology development originated from the need to assess the debris threat resulting from soil material erosion induced by landing spacecraft rocket plume impingement on extraterrestrial planetary surfaces. The impact of soil debris was observed to be highly detrimental during NASA s Apollo lunar missions and will pose a threat for any future landings on the Moon, Mars, and other exploration targets. The innovation developed under this program provides a simulation tool that combines modeling of the diverse disciplines of rocket plume impingement gas dynamics, granular soil material liberation, and soil debris particle kinetics into one unified simulation system. The Unified Flow Solver (UFS) developed by CFDRC enabled the efficient, seamless simulation of mixed continuum and rarefied rocket plume flow utilizing a novel direct numerical simulation technique of the Boltzmann gas dynamics equation. The characteristics of the soil granular material response and modeling of the erosion and liberation processes were enabled through novel first principle-based granular mechanics models developed by the University of Florida specifically for the highly irregularly shaped and cohesive lunar regolith material. These tools were integrated into a unique simulation system that accounts for all relevant physics aspects: (1) Modeling of spacecraft rocket plume impingement flow under lunar vacuum environment resulting in a mixed continuum and rarefied flow; (2) Modeling of lunar soil characteristics to capture soil-specific effects of particle size and shape composition, soil layer cohesion and granular flow physics; and (3) Accurate tracking of soil-borne debris particles beginning with aerodynamically driven motion inside the plume to purely ballistic motion in lunar far field conditions. In the earlier project phase of this innovation, the capabilities of the UFS for mixed continuum and rarefied flow situations were validated and demonstrated for lunar lander rocket plume flow impingement under lunar vacuum conditions. Applications and improvements to the granular flow simulation tools contributed by the University of Florida were tested against Earth environment experimental results. Requirements for developing, validating, and demonstrating this solution environment were clearly identified, and an effective second phase execution plan was devised. In this phase, the physics models were refined and fully integrated into a production-oriented simulation tool set. Three-dimensional simulations of Apollo Lunar Excursion Module (LEM) and Altair landers (including full-scale lander geometry) established the practical applicability of the UFS simulation approach and its advanced performance level for large-scale realistic problems.

Liever, Peter↗

Preservation of Lipid Biomarkers Under Prolonged and Extreme Hyperaridity in Atacama Desert Soils

Molecular biomarkers are the most direct biosignatures of life on early Earth and a key target in the search for life on Mars. Lipid biomarkers are of particular interest given their ability to survive oxidative degradation and record microbial presence and activity of microorganisms that occurred billions of years ago (Eigenbrode, 2008). Environmental conditions that suspend biotic and abiotic degradative processes prior to lithification can lead to enhanced biomolecular preservation over geological time-scales. The hyperarid core of the Atacama Desert in northern Chile offers a unique environment to investigate lipid biomarker taphonomy under extreme and prolonged dryness. We investigated the accumulation and degree of preservation of lipid biomarkers in million-year-old hyperarid soils where primarily abiotic conditions influence their taphonomy. Soils were extracted and free and membrane bound lipids were analyzed across a vertical profile of 2.5 meters in the Yungay hyper-arid core of the Atacama Desert. Due to the extremely low inventory of biomass in Atacama soils, samples were collected by scientists wearing cleanroom suits to minimize anthropogenic contamination during sampling. Fatty acids were found to be well preserved in Yungay soils, and were most abundant in the clay-rich soils at approx.2 m depth (approx.750 ng of fatty acid methyl ester/g of soil). These buried clays layers were fluvially deposited approximately 2 million years ago, and have been excluded from exposure to rainwater and modern surficial processes since their emplacement (Ewing et al., 2008). Monocarboxylic fatty acid, monohydroxy fatty acid, glycerol tetraether, and n-alkane hydrocarbon content was found to change with depth. Lipid biomarker content in deeper soil layers is suggestive of soils having been formed at a time when environmental conditions were capable of supporting active microbial communities and plants. In short, total lipid extracts reveal a remarkable degree of lipid biomarker preservation even in the oldest soils analyzed (ca. 2 Myr) indicating that typical diagenetic processes of lipid destruction are arrested under extreme dryness. This result has implications for the search for molecular biomarkers on Mars, which could have experienced millions to billions of years of extreme hyperaridity.

Lipid Biomarkers↗

Global Assessment of the SMAP Level-4 Soil Moisture Product Using Assimilation Diagnostics

The Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture and related land surface variables from 31 March 2015 to present with approx. 2.5-day latency. The ensemble-based L4_SM algorithm assimilates SMAP brightness temperature (Tb) observations into the Catchment land surface model. This study describes the spatially distributed L4_SM analysis and assesses the observation-minus-forecast (O-F) Tb residuals and the soil moisture and temperature analysis increments. Owing to the climatological rescaling of the Tb observations prior to assimilation, the analysis is essentially unbiased, with global mean values of approx. 0.37 K for the O-F Tb residuals and practically zero for the soil moisture and temperature increments. There are, however, modest regional (absolute) biases in the O-F residuals (under approx. 3 K), the soil moisture increments (under approx. 0.01 cu m/cu m), and the surface soil temperature increments (under approx. 1 K). Typical instantaneous values are approx. 6 K for O-F residuals, approx. 0.01 (approx. 0.003) cu m/cu m for surface (root-zone) soil moisture increments, and approx. 0.6 K for surface soil temperature increments. The O-F diagnostics indicate that the actual errors in the system are overestimated in deserts and densely vegetated regions and underestimated in agricultural regions and transition zones between dry and wet climates. The O-F auto-correlations suggest that the SMAP observations are used efficiently in western North America, the Sahel, and Australia, but not in many forested regions and the high northern latitudes. A case study in Australia demonstrates that assimilating SMAP observations successfully corrects short-term errors in the L4_SM rainfall forcing.

Reichle, Rolf↗

Using Data Assimilation Diagnostics to Assess the SMAP Level-4 Soil Moisture Product

The Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture and related land surface variables from 31 March 2015 to present with approx.2.5-day latency. The ensemble-based L4_SM algorithm assimilates SMAP brightness temperature (Tb) observations into the Catchment land surface model. This study describes the spatially distributed L4_SM analysis and assesses the observation-minus-forecast (O-F) Tb residuals and the soil moisture and temperature analysis increments. Owing to the climatological rescaling of the Tb observations prior to assimilation, the analysis is essentially unbiased, with global mean values of approx. 0.37 K for the O-F Tb residuals and practically zero for the soil moisture and temperature increments. There are, however, modest regional (absolute) biases in the O-F residuals (under approx. 3 K), the soil moisture increments (under approx. 0.01 cu m/cu m), and the surface soil temperature increments (under approx. 1 K). Typical instantaneous values are approx. 6 K for O-F residuals, approx. 0.01 (approx. 0.003) cu m/cu m for surface (root-zone) soil moisture increments, and approx. 0.6 K for surface soil temperature increments. The O-F diagnostics indicate that the actual errors in the system are overestimated in deserts and densely vegetated regions and underestimated in agricultural regions and transition zones between dry and wet climates. The O-F auto-correlations suggest that the SMAP observations are used efficiently in western North America, the Sahel, and Australia, but not in many forested regions and the high northern latitudes. A case study in Australia demonstrates that assimilating SMAP observations successfully corrects short-term errors in the L4_SM rainfall forcing.

SMAP↗

Global-scale Evaluation of SMAP, SMOS and ASCAT Soil Moisture Products Using Triple Collocation

Global-scale surface soil moisture products are currently available from multiple remote sensing platforms. Footprint-scale assessments of these products are generally restricted to limited number of densely-instrumented validation sites. However, by taking active and passive soil moisture products together with a third independent soil moisture estimates via land surface modeling, triple collocation (TC) can be applied to estimate the correlation metric of satellite soil moisture products (versus an unknown ground truth) over a quasi-global domain. Here, an assessment of Soil Moisture Active Passive (SMAP), Soil Moisture Ocean Salinity (SMOS) and Advanced SCATterometer (ASCAT) surface soil moisture retrievals via TC is presented. Considering the potential violation of TC error assumptions, the impact of active-passive and satellite-model error cross correlations on the TC-derived inter-comparison results is examined at in situ sites using quadruple collocation analysis. In addition, confidence intervals for the TC-estimated correlation metric are constructed from moving-block bootstrap sampling designed to preserve the temporal persistence of the original (unevenly-sampled) soil moisture time-series. This study is the first to apply TC to obtain a robust global-scale cross-assessment of SMAP, SMOS and ASCAT soil moisture retrieval accuracy in terms of anomaly temporal correlation. Our results confirm the overall advantage of SMAP (with a global average anomaly correlation of 0.76) over SMOS (0.66) and ASCAT (0.63) that has been established in several recent regional, ground-based studies. SMAP is also the best-performing product over the majority of applicable land pixels (52%), although SMOS and ASCAT each shows advantage in distinct geographic regions.

global-scale↗

Recent Updates in the SMAP Level-4 Soil Moisture Algorithm

The NASA Soil Moisture Active Passive (SMAP) mission generates, among other data sets, the Level-4 Soil Moisture (L4_SM) product. The L4_SM data are published with a mean latency of ~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. 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 (EnKF). In 2018, the L4_SM algorithm 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. 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 surface soil moisture from below under non-equilibrium conditions, which brings the model's surface soil moisture more in line with the SMAP Level-2 and in situ soil moisture. Moreover, the calibration of the assimilated SMAP brightness temperatures changed substantially from Version 3 to Version 4, and the "catchment deficit" model variable was removed from the EnKF state vector to avoid degrading the model's groundwater estimates.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. 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 H.↗

Assimilation of Satellite Soil Moisture for Improved Atmospheric Reanalyses

A newly developed, weakly coupled land and atmosphere data assimilation system for NASA’s Global Earth Observing System model is presented, and used to demonstrate the benefit of assimilating satellite soil moisture into an atmospheric reanalysis. Specifically, Advanced Scatterometer and Soil Moisture Ocean Salinity soil moisture retrievals are assimilated into a system that uses the same model, atmospheric assimilation system, and atmospheric observations as the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2). The atmosphere is sensitive to soil moisture only under certain conditions. Hence, while the globally averaged model improvements were small, regionally, the soil moisture assimilation induced some substantial improvements. For example, in a large region spanning from western Europe across southern Russia, the soil moisture assimilation decreased the RMSE against independent station observations of daily maximum 2-m temperature (T(sup 2m, sub max)) by up to 0.4 K, and of 2-m specific humidity (q(exp 2m)) by up to 0.5 g/kg. Over all available stations, the mean T(sup 2m, sub max) RMSE was reduced from 2.82 to 2.79 K, while the mean q(exp 2m) RMSE was reduced from 1.25 to 1.20 g/kg. The soil moisture assimilation also reduced the mean RMSE across 29 flux tower sites from 34.2 to 32.6 Wm(exp −2) for latent heating, and from 37.7 to 36.5 Wm(exp −2) for sensible heating. For all variables evaluated, the soil moisture assimilation improved the model at monthly to seasonal, rather than daily, time scales. Based on the above experiments, it is recommended that satellite soil moisture be assimilated into future reanalyses, including the follow-on to MERRA-2.

Clara Draper↗

Impact of Gauge-Based Precipitation Corrections on the Skill of SMAP Level-4 Soil Moisture Estimates

The NASA Soil Moisture Active Passive (SMAP) mission provides observations of L-band (1.4 GHz) passive microwave brightness temperature (Tb) observations at a resolution of ~40 km globally every 2-3 days. These observations are routinely assimilated into the NASA Catchment land surface model to generate the Level-4 Soil Moisture (L4_SM) product, which provides global estimates of surface and root-zone soil moisture, soil temperature, and surface fluxes (among others) at 9-km, 3-hourly resolution with ~2.5-day latency. The Catchment land surface model in the L4_SM algorithm is driven with 0.25°, hourly surface meteorological forcing data from the NASA Goddard Earth Observing System (GEOS) "forward-processing" product. Outside of Africa and the high latitudes, the GEOS precipitation forcing is corrected using the Climate Prediction Center Unified (CPCU) gauge-based, 0.5°, daily precipitation product.Soil moisture estimates from the L4_SM product were previously shown to improve over land model-only estimates that do not benefit from the assimilation of Tb observations, thereby demonstrating the value of assimilating SMAP observations for soil moisture estimation. In this presentation, we further isolate the contribution of the gauge-based precipitation corrections to the skill of the L4_SM soil moisture estimates. Specifically, we compare the skill of the L4_SM soil moisture to that of separate model-only and assimilation estimates obtained without the benefit of the gauge-based precipitation corrections.Preliminary results suggest that the soil moisture skill added by the CPCU-based precipitation corrections primarily depends on the quality of the CPCU precipitation product and is greatest in regions where the CPCU gauge network is dense and reliable. Conversely, in regions where the CPCU product is known to be of poor quality, for example in central Australia, the assimilation of SMAP Tb observations provides the most benefit. The presentation will provide an in-depth evaluation of the soil moisture skill of the model-only and assimilation estimates vs. independent in situ and satellite measurements.

Reichle, Rolf↗