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At least 19 records

Evaluation Analysis of NASA SMAP L3 and L4 and SPoRT-LIS Soil Moisture Data in the United States

Soil moisture has a critical role in the development, frequency and persistence of climatic and hydrologic extremes such as drought, heat wave and flooding events. In situ soil moisture data are uneven and sparse in time and space. This highlights the need to utilize other soil moisture sources to fill this spatiotemporal gap. The goal of this study is to validate one satellite-based and two model-based soil moisture datasets with in situ data across the United States. Soil moisture information from the Soil Moisture Active Passive (SMAP) enhanced level 3 (L3) (SMAP L3) and modeled level 4 (L4) (SMAP L4) data at 9-km resolution and Short-term Prediction Research and Transition-Land Information System (SPoRT-LIS) modeled at 3-km resolution were selected for evaluation. SPoRT-LIS is a near real-time, high resolution operational land analysis data. Ground-based data were obtained from the North American Soil Moisture Database (NASMD) for 362 stations. Seven statistical indicators including anomaly, Spearman, and Pearson correlation coefficients, the systematic error (Bias), root mean square error (RMSE), unbiased root mean square error (ubRMSE), and normalized standard deviation (SDV) were used to evaluate the satellite- and model-derived soil moisture data. In addition, the triple collocation (TC) error model was used to measure the error among SMAP L4, SPoRT-LIS and ground-based data. This study assesses which satellite or modeled dataset is most appropriate for specific times and locations to use as a surrogate for in situ observations. Temporal and spatial analysis demonstrated that, overall, SMAP L4 performed better than SMAP L3 and SPoRT-LIS. Strong agreement was observed between SMAP L4 and in situ observations (ρ = 0.53, Bias = −0.006) in all seasons and most regions with various land covers, especially in winter and in the central regions of the United States. For croplands, SMAP L4 presented the best agreement with in situ data, analyzing all period (ρ = 0.60) and non-winter period (ρ = 0.61) separately.

Tavakol, Ameneh↗

T2M Forecasts at Subseasonal Leads: Do Different Soil Moisture Initial States Have Different Impacts?

Soil moisture (W) helps control evapotranspiration (ET), and ET variations can in turn have a distinct impact on 2-m air temperature (T2M), given that increases in evaporative cooling encourage reduced temperatures. Soil moisture is accordingly linked to T2M, and realistic soil moisture initialization has, in previous studies, been shown to improve the skill of subseasonal T2M forecasts. The relationship between soil moisture and evapotranspiration, however, is distinctly nonlinear, with ET tending to increase with soil moisture in drier conditions and to be insensitive to soil moisture variations in wetter conditions. Here, through an extensive analysis of subseasonal forecasts produced with a state-of-the-art seasonal forecast system, this nonlinearity is shown to imprint itself on T2M forecast error in the conterminous United States in two unique ways: (i) the T2M forecast bias (relative to independent observations) induced by a negative precipitation bias tends to be larger for dry initializations, and (ii) on average, the unbiased root-mean-square error (ubRMSE) tends to be larger for dry initializations. Such findings can aid in the identification of forecasts of opportunity; taken a step further, they suggest a pathway for improving bias correction and uncertainty estimation in subseasonal T2M forecasts by conditioning each on initial soil moisture state.

2-meter Temperature↗

Three Paradigms of Lunar Regolith Evolution

Integration of diverse datasets on the Moon may render some paradigms of lunar science either better-defended or vulnerable. We will consider three paradigms commonly used for understanding the processes of lunar regolith evolution in light of new and accumulated data. Our premise is that all data-sets should converge to a single interpretation if a concept or model is to be accepted as a paradigm. If a convergence is lacking, the paradigm needs fresh scrutiny. SteadyState: Lunar regolith evolution is currently understood in terms of comminution, agglutination, and replenishment as described by McKay and coworkers). Briefly, the model envisages continued micrometeoritic bombardment to comminute exposed soil particles to finer sizes while continued agglutination consumes finer sizes to produce larger constructional particles. Eventually, a balance between these two opposing processes achieves a steady state; soils at steady state maintain their mean grain size (M(sub z)). Episodic higher-energy impacts excavate fresh coarse material from below the soil cover, disturb the steady state, and restart the process to achieve a new steady state. It follows that the thickness of the regolith at any site would control the frequency of replenishment; indeed, the thickness of the regolith at Apollo landing sites was predicted by McKay et al. from the average M(sub z) of local soils. However, replenishment may come also from disintegrating boulders and cobbles at the lunar surface, and rates of comminution and agglutination may depend on the properties of target material. Regression between M(sub z) and I(sub s)/Fe(sup 0) (a measure of maturity or total surface exposure) of Apollo soils at different sites shows the following relations and estimated M(sub z) at a high maturity of I(sub s)/Fe(sup 0)= 100. It is possible that Apollo 12 and 15 sites have the thickest regolith and the Apollo 16 site has the thinnest. It is also possible that Apollo 12 and 15 basalts are comminuted faster than Apollo 16 highland rocks and Apollo 14 and 17 soils are products of mixed parentage. If a soil becomes continually finer as it matures until agglutination catches up, and if comminution is differential-dependent on the physical properties of the constituents, then the composition of the bulk soil has to match the composition of some "fulcrum" grain size fraction, say X Grain size fractions >X and <X will complement each other; their mass balance is the bulk soil. It appears that the 10-20-micron size fraction may be the fulcrum. In general, trace-element chemistry and IR reflectance spectra of this size fraction are closest to that of the bulk soil, regardless of maturity that is surprising. Disaggregated products of regolith breccias may also show similar relationships. If the 10-20 gm is the fulcrum (i.e., X as above) for many soil properties (e.g., major element composition, FMR, solar-wind-implanted elements), then this may be the ultimate mean grain size of lunar soils at steady state. However, different properties of soils may find steady states at different grain size fractions. The steady state of solar-wind-implanted elements, on the other hand, will climb up the grain-size scale as agglutinates transfer surface-correlated components into volume correlated components until a saturation level is reached or the rates of replenishment and implantation become equal. The same will be the case with vapor-deposited reduced metals as they too are incorporated inside constructional particles. Properties that are directly affected by soil-maturation processes will thus have different pathways of achieving steady states. Maturity, i.e., cumulative surface exposure, of lunar soils is best quantified by the amount of nanophase superparamagnetic Fe(sup 0) (np-Fe(sup 0)) normalized to Fe content (=I(sub s)/Fe(sup 0). The majority consensus (paradigm?) for the production of np-Fe(sup 0) is associated with the production of agglutinates. Because large doses of solar-wind H are implanted in all lunar soils upon exposure, any melting (e.g., during agglutinate production) triggers a chemical reduction of Fe-bearing minerals resulting in np-Fe(sup 0) production. The quantity of np-Fe(sup 0) is thus dependent on melting events, (i.e., exposure), and limited by the Fe content of the soil. All freshly produced np-Fe(sup 0) resides in agglutinitic glass, as new TEM images show. Apparently, the correction procedure developed by Lucey et al. to estimate the Fe content of the lunar surface from IR-reflectance spectra depends on accepting the above. However, the process of producing np-Fe(sup 0) may be physical rather than chemical. All np-Fe(sup 0) could be deposits from a vapor produced by micrometeoritic impact on lunar soils. If metal-O bonds in target phases are broken, O being "most volatile" will escape leaving an O-deficient vapor to facilitate the production of np-Fe(sup 0). If so, the quantity of np-Fe(sup 0) is dependent on the vaporizing events, (i.e., exposure), and limited by the efficiency of breaking metal-O bonds and the escape of 0. To the extent that strengths of metal-O bonds are dependent on the local crystal field, production of np-Fe(sup 0) may be limited by the mineral composition of target soils and not by their total Fe content. According to this model, vapor-deposited np-Fe(sup 0) should be found at any retentive sites on lunar soil grains. Indeed, TEM images show np-Fe(sup 0) on plagioclase and ilmenite. Incorporation of such pre-irradiated np-Fe(sup 0)-bearing grains into agglutinates may account for eventual increased emplacement of np-Fe(sup 0) in agglutinates. Such a paradigm shift in understanding the origin of np-Fe(sup 0) will raise questions ranging from the unquestionable use of Is/FeO as the universal maturity parameter of lunar soils to global elemental maps of the Moon from remote-sensing data. Additional information is contained in the original.

Basu, A.↗

Lunar soil grain size distribution

A comprehensive review has been made of the currently available data for lunar grain size distributions. It has been concluded that there is little or no statistical difference among the large majority of the soil samples from the Apollo 11, 12, 14, and 15 missions. The grain size distribution for these soils has reached a steady state in which the comminution processes are balanced by the aggregation processes. The median particle size for the steady-state soil is 40 to 130 microns. The predictions of lunar grain size distributions based on the Surveyor television photographs have been found to be quantitatively in error and qualitatively misleading.

Carrier, W. D., III↗

Assessing Disaggregated SMAP Soil Moisture Products in the United States

A soil moisture (SM) disaggregation algorithm based on thermal inertia (TI) theory was implemented to downscale the Soil Moisture Active Passive (SMAP) Enhanced product(SPL2SMPE) from 9 km to 1 km over the continental United States. The algorithm applies land surface temperature and normalized difference vegetation index from Moderate Resolution Imaging Spectroradiometer (MODIS) at higher spatial resolution to estimate relative soil wetness within a coarse SMAP grid -this MODIS-derived relative wetness is then used to produce the downscaled SMAP SM. Results from the algorithm were evaluated in terms of their spatiotemporal coverage and accuracy using in situ measurements from SMAP Core Validation Sites (CVS), the US Department of Agriculture Soil Climate Analysis Network (USDA-SCAN), and the National Oceanic and Atmospheric Administration Climate Reference Network(NOAA-CRN). Results were also compared with the baselineSPL2SMPE and the SMAP/Sentinel-1 (SPL2SMAPS) 1kmproduct. Overall, the unbiased root mean square error (ubRMSE)of the disaggregated SM at the CVS using the TI approach is approximately 0.04 m3=m3, which is the SMAP mission requirement for the baseline products. The TI approach out performs the SMAP/Sentinel SL2SMAPS 1km product by approximately0.02 m3=m3. Over the agriculture/crop areas from SCAN and CRN sparse network stations, the TI approach exhibits better ubRMSE compared to SPL2SMPE andSPL2SMAPS byabout0.01 and 0.02 m3=m3, indicating its advantage in these areas. However, a drawback of this approach is that there are data gaps due to cloud cover as optical sensors cannot have a clear view of the land surface.

Soil moisture↗

Grain size and the evolution of lunar soils

Grain-size data are presented for Apollo-17 soils, and the relationship is considered between grain-size distribution and the processes which pulverize the soil, reconstitute it as agglutinates, and replenish it with fresh material. It is shown that a strong inverse correlation exists between mean grain size and standard deviation and that there is a correlation between grain size and agglutinate content whereby the finest samples have the highest agglutinate content. Two evolutionary sequences are described for the soils in which (1) reworking by micrometeorites predominates over mixing with other soils and (2) mixing predominates over reworking. It is shown that the final result of soil evolution may be a steady-state soil where pulverization by micrometeorites is balanced by agglutination and replenishment of coarser grains. A model is presented for such a soil, and it is argued that its grain-size distribution may depend on regolith thickness.-

Mckay, D. S.↗

Illinois Disasters: Utilizing NASA Earth Observations to Enhance Drought Monitoring in Illinois

Drought and flooding in Illinois have severe impacts on the communities and ecosystems of the state. Soil moisture is a valuable indicator of drought and flood vulnerability but can be difficult to measure since in situ monitoring is limited to discrete stations throughout the state. The team created a framework to compare in situ, modeled, and NASA satellite soil moisture measurements to increase the spatial coverage of soil moisture monitoring. The team partnered with the Illinois State Weather Survey, USDA Midwest Climate Hub, NOAA Regional Climate Services of the Central Region, NOAA National Integrated Drought Information System’s Midwest Drought Early Warning System, and the NOAA North Central River ForecastCenter. The team standardized and compared soil moisture data from NASA’s Soil Moisture Active Passive (SMAP) mission, modeled soil moisture outputs from NASA’s SPoRT Land Information System (SPoRT-LIS), and in situ measurements from the Illinois State Weather Survey’s Water and Atmospheric Resources Monitoring (WARM) program. Compared to the WARM data, the satellite and modeled data showed seasonally variable differences and bias. The difference was highest in the winter months and lowest in the late summer and early fall months for the SMAP and SPoRT-LIS data products. SPoRT-LIS produced lower seasonal variability and SMAP demonstrated higher correlation values and lower differences. These analyses suggest that both SMAP and SPoRT-LIS products offer unique strengths and limitations when used for soil moisture monitoring

Joshua Green↗

Evaluation and Validation of a High Spatial Resolution Satellite Soil Moisture Product over the Continental United States

The soil moisture (SM) data retrieved from the Soil Moisture Active and Passive (SMAP) satellite are available at a 9 km grid spacing since April 2015. This product can provide valuable information for research and applications in hydrology and other related fields. However, the resolution may be too coarse for applications at catchment or field scale. In this study, an established downscaling methodology, which had a major modification regarding its application on the SMAP 33 km domain, was implemented to develop a 1 km soil moisture product based on the SMAP 9 km data. The algorithm proposed here is based on the thermal inertia principle and developed by modeling the relationship between surface temperature difference and SM for different Normalized Difference Vegetation Index (NDVI) classes. The model functions were established and tuned using data from the NASA’s Land Information System (LIS) North America Land Data Assimilation System (NLDAS) and remotely sensed VISible/InfRared (VIS/IR) reflectance data from Long Term Data Record (LTDR) AVHRR (Advanced Very High Resolution Radiometer) for the growing season months of April-September 1981–2018. These were then implemented using the MODIS (Moderate Resolution Imaging Spectroradiometer) data over the Continental United States (CONUS) domain. Validation activities were carried out using in situ measurements distributed through the International Soil Moisture Network (ISMN). The validation results computed using the 1 km SM data showed that the R2, unbiased RMSE (root mean square error) and bias were improved relative to the 9 km SMAP product by 0.045, 0.018m3/m3 and 0.001m3/m3, respectively. The 1 km SM also exhibited a strong time-series autocorrelation. Further accuracy assessment analyses indicated that precipitation might contribute to the uncertainties in both the 9 km SMAP and 1 km downscaled SMAP SM products.

SMAP↗

High Resolution Soil Water from Regional Databases and Satellite Images

This viewgraph presentation provides information on the ways in which plant growth can be inferred from satellite data and can then be used to infer soil water. There are several steps in this process, the first of which is the acquisition of data from satellite observations and relevant information databases such as the State Soil Geographic Database (STATSGO). Then probabilistic analysis and inversion with the Bayes' theorem reveals sources of uncertainty. The Markov chain Monte Carlo method is also used.

Morris, Robin D.↗

Analysis of Summertime Convective Initiation in Central Alabama Using the Land Information System

During the summer months in the southeastern United States, convective initiation presents a frequent challenge to operational forecasters. Thunderstorm development has traditionally been referred to as random due to their disorganized, sporadic appearance and lack of atmospheric forcing. Horizontal variations in land surface characteristics such as soil moisture, soil type, land and vegetation cover could possibly be a focus mechanism for afternoon convection during the summer months. The NASA Land Information System (LIS) provides a stand-alone land surface modeling framework that incorporates these varying soil and vegetation properties, antecedent precipitation, and atmospheric forcing to represent the soil state at high resolution. The use of LIS as a diagnostic tool may help forecasters to identify boundaries in land surface characteristics that could correlate to favored regions of convection initiation. The NASA Shortterm Prediction Research and Transition (SPoRT) team has been collaborating with the National Weather Service Office in Birmingham, AL to help incorporate LIS products into their operational forecasting methods. This paper highlights selected convective case dates from summer 2009 when synoptic forcing was weak, and identifies any boundaries in land surface characteristics that may have contributed to convective initiation. The LIS output depicts the effects of increased sensible heat flux from urban areas on the development of convection, as well as convection along gradients in land surface characteristics and surface sensible and latent heat fluxes. These features may promote mesoscale circulations and/or feedback processes that can either enhance or inhibit convection. With this output previously unavailable to operational forecasters, LIS provides a new tool to forecasters in order to help eliminate the randomness of summertime convective initiation.

James, Robert S.↗

Impact of Surface Roughness and Soil Texture on Mineral Dust Emission Fluxes Modeling

Dust production models (DPM) used to estimate vertical fluxes of mineral dust aerosols over arid regions need accurate data on soil and surface properties. The Laboratoire Inter-Universitaire des Systemes Atmospheriques (LISA) data set was developed for Northern Africa, the Middle East, and East Asia. This regional data set was built through dedicated field campaigns and include, among others, the aerodynamic roughness length, the smooth roughness length of the erodible fraction of the surface, and the dry (undisturbed) soil size distribution. Recently, satellite-derived roughness length and high-resolution soil texture data sets at the global scale have emerged and provide the opportunity for the use of advanced schemes in global models. This paper analyzes the behavior of the ERS satellite-derived global roughness length and the State Soil Geographic data base-Food and Agriculture Organization of the United Nations (STATSGO-FAO) soil texture data set (based on wet techniques) using an advanced DPM in comparison to the LISA data set over Northern Africa and the Middle East. We explore the sensitivity of the drag partition scheme (a critical component of the DPM) and of the dust vertical fluxes (intensity and spatial patterns) to the roughness length and soil texture data sets. We also compare the use of the drag partition scheme to a widely used preferential source approach in global models. Idealized experiments with prescribed wind speeds show that the ERS and STATSGO-FAO data sets provide realistic spatial patterns of dust emission and friction velocity thresholds in the region. Finally, we evaluate a dust transport model for the period of March to July 2011 with observed aerosol optical depths from Aerosol Robotic Network sites. Results show that ERS and STATSGO-FAO provide realistic simulations in the region.

textures↗

PowderSim: Lagrangian Discrete and Mesh-Free Continuum Simulation Code for Cohesive Soils

PowderSim is a calculation tool that combines a discrete-element method (DEM) module, including calibrated interparticle-interaction relationships, with a mesh-free, continuum, SPH (smoothed-particle hydrodynamics) based module that utilizes enhanced, calibrated, constitutive models capable of mimicking both large deformations and the flow behavior of regolith simulants and lunar regolith under conditions anticipated during in situ resource utilization (ISRU) operations. The major innovation introduced in PowderSim is to use a mesh-free method (SPH-based) with a calibrated and slightly modified critical-state soil mechanics constitutive model to extend the ability of the simulation tool to also address full-scale engineering systems in the continuum sense. The PowderSim software maintains the ability to address particle-scale problems, like size segregation, in selected regions with a traditional DEM module, which has improved contact physics and electrostatic interaction models.

Johnson, Scott↗

Lunar Polar Environmental Testing: Regolith Simulant Conditioning

As ISRU system development approaches flight fidelity, there is a need to test hardware in relevant environments. Extensive laboratory and field testing have involved relevant soil (lunar regolith simulants), but the current design iterations necessitate relevant pressure and temperature conditions. Including significant quantities of lunar regolith simulant in a thermal vacuum chamber poses unique challenges. These include facility operational challenges (dust tolerant hardware) and difficulty maintaining a pre-prepared soil state during pump down (consolidation state, moisture retention).For ISRU purposes, the regolith at the lunar poles will be of most interest due to the elevated water content. To test at polar conditions, the regolith simulant must be doped with water to an appropriate percentage and then chilled to cryogenic temperatures while exposed to vacuum conditions. A 1m tall, 28cm diameter bin of simulant was developed for testing these simulant preparation and drilling operations. The bin itself was wrapped with liquid nitrogen cooling loops (100K) so that the simulant bed reached an average temperature of 140K at vacuum. Post-test sampling was used to determine desiccation of the bed due to vacuum exposure. Depth dependent moisture data is presented from frozen and thawed soil samples.Following simulant only evacuation tests, drill hardware was incorporated into the vacuum chamber to test auguring techniques in the frozen soil at thermal vacuum conditions. The focus of this testing was to produce cuttings piles for a newly developed spectrometer to evaluate. This instrument, which is part of the RESOLVE program science hardware, detects water signatures from surface regolith. The drill performance, behavior of simulant during drilling, and characteristics of the cuttings piles will be offered.

lunar regolith↗

Lunar Polar Environmental Testing: Regolith Simulant Conditioning

As ISRU system development approaches flight fidelity, there is a need to test hardware in relevant environments. Extensive laboratory and field testing have involved relevant soil (lunar regolith simulants), but the current design iterations necessitate relevant pressure and temperature conditions. Including significant quantities of lunar regolith simulant in a thermal vacuum chamber poses unique challenges. These include facility operational challenges (dust tolerant hardware) and difficulty maintaining a pre-prepared soil state during pump down (consolidation state, moisture retention).For ISRU purposes, the regolith at the lunar poles will be of most interest due to the elevated water content. To test at polar conditions, the regolith simulant must be doped with water to an appropriate percentage and then chilled to cryogenic temperatures while exposed to vacuum conditions. A 1m tall, 28cm diameter bin of simulant was developed for testing these simulant preparation and drilling operations. The bin itself was wrapped with liquid nitrogen cooling loops (100K) so that the simulant bed reached an average temperature of 140K at vacuum. Post-test sampling was used to determine desiccation of the bed due to vacuum exposure. Depth dependent moisture data is presented from frozen and thawed soil samples.Following simulant only evacuation tests, drill hardware was incorporated into the vacuum chamber to test auguring techniques in the frozen soil at thermal vacuum conditions. The focus of this testing was to produce cuttings piles for a newly developed spectrometer to evaluate. This instrument, which is part of the RESOLVE program science hardware, detects water signatures from surface regolith. The drill performance, behavior of simulant during drilling, and characteristics of the cuttings piles will be offered.

in situ resource utilization↗

Comparative evaluation of ERTS imagery for resource inventory in land use planning

The author has identified the following significant results. Numerous previously unmapped faults in central Oregon have been distinguished on ERTS-1 imagery. Tectonic mapping of fault-controlled linears demonstrates the utility of ERTS-1 imagery as a mean of illustrating and studying the regional tectonics of the state. Soil colors observed on ERTS-1 frame 1075-18150-5 at the eastern end of the Columbia basin correlate very well with those from descriptions of soils from that area. Digital output from frame 1021-18151 has shown the enhanced ability to interpret such features as joint patterns, shadowed landslide blocks, bottomlands, and drainage patterns. Widespread use of wheat-fallow rotation in northern Umatilla County, Oregon, insures that nearly one-half of the cultivated soil is devoid of vegetation much of the time. On ERTS-1 imagery, fallow fields are only slightly darker than fields of wheat stubble at the western end of the transect. Similar climate-related contrasts in soil color are visible on ERTS-1 Imagery from several other portions of the Columbia Basin. Absence of steep topography in the area mentioned, however, minimizes the disturbing effect caused by shadows.

Simonson, G. H.↗

Radar spectral observations of snow

Radar remote sensing experiments have been conducted at test sites in Kansas, Colorado, and South Dakota over the last six years to examine backscatter coefficient response to snowcovered terrain. Truck-mounted 1-35 GHz scatterometers were employed in conjunction with detailed ground-truth measurements. From these experiments and associated modeling efforts, most of the fundamental questions concerning backscatter behavior in response to important snow parameters have been, at least qualitatively, answered. The optimum angular range seems to be between 20 and 50 deg and, for these angles, the results indicate that the radar backscatter generally: (1) increases with increasing water equivalent, (2) decreases with increasing liquid water, (3) increases with increasing crystal size, (4) is insensitive to surface roughness for dry snow conditions, and (5) can be sensitive to soil state if the snowcover is dry. This paper gives a summary of these results, along with empirical and theoretical models for describing the backscatter from snow.

Stiles, W. H.↗

Terrestrial Hydrological Data from NASA's Hydrology Data and Information Services Center (HDISC): Products, Services, and Applications

Terrestrial hydrological variables are important in global hydrology, climate, and carbon cycle studies. The North American and Global Land Data Assimilation Systems (NLDAS and GLDAS, respectively) have been generating a series of land surface states (soil moisture, snow, and temperature) and fluxes (evapotranspiration, radiation, and heat flux) variables. These data, hosted at and available from NASA s Hydrology Data and Information Services Center (HDISC), include the NLDAS hourly 1/8 degree products and the GLDAS 3-hourly 0.25 and 1.0 degree products. HDISC provides easy access and visualization and analysis capabilities for these products, thus reducing the time and resources spent by scientists on data management and facilitating hydrological research. Users can perform spatial and parameter subsetting, data format transformation, and data analysis operations without needing to first download the data. HDISC is continually being developed as a data and services portal that supports weather and climate forecasts, and water and energy cycle research.

Fang, Hongliang↗