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NASA NTRS2016

Multi-Disciplinary, Multi-Fidelity Discrete Data Transfer Using Degenerate Geometry Forms

In a typical multi-fidelity design process, different levels of geometric abstraction are used for different analysis methods, and transitioning from one phase of design to the next often requires a complete re-creation of the geometry. To maintain consistency between lower-order and higher-order analysis results, Vehicle Sketch Pad (OpenVSP) recently introduced the ability to generate and export several degenerate forms of the geometry, representing the type of abstraction required to perform low- to medium-order analysis for a range of aeronautical disciplines. In this research, the functionality of these degenerate models was extended, so that in addition to serving as repositories for the geometric information that is required as input to an analysis, the degenerate models can also store the results of that analysis mapped back onto the geometric nodes. At the same time, the results are also mapped indirectly onto the nodes of lower-order degenerate models using a process called aggregation, and onto higher-order models using a process called disaggregation. The mapped analysis results are available for use by any subsequent analysis in an integrated design and analysis process. A simple multi-fidelity analysis process for a single-aisle subsonic transport aircraft is used as an example case to demonstrate the value of the approach.

Olson, Erik D.↗

NASA NTRS2016

Sublimation as a Landform-Shaping Process on Pluto

Several icy-world surfaces in the solar system exhibit sublimation-driven landform modification erosion, condensation, and mass wasting [1]. In addition to the obvious role of gravity, mass wasting can work in conjunction with internal disaggregation of a landform's relief-supporting material through the loss (or deteriorating alteration) of its cohesive matrix. To give a conspicuous example, Callisto's landscape exhibits widespread erosion from sublimation erosion of slopes, which results in smooth, undulating, low albedo plains composed of lag deposits, with isolated high albedo pinnacles perched on remnants of crater rims due to the re-precipitation of ice on local cold traps [2, 3, 4]. Sublimation-driven mass wasting was anticipated on Pluto prior to the encounter (see refs in [5]). Here we report on several landscapes on Pluto we interpret to be formed, or at least heavily modified, by sublimation erosion.

Properties of Ice at Pluto↗

NASA NTRS2014

Comparison Of Downscaled CMIP5 Precipitation Datasets For Projecting Changes In Extreme Precipitation In The San Francisco Bay Area.

Water resource managers planning for the adaptation to future events of extreme precipitation now have access to high resolution downscaled daily projections derived from statistical bias correction and constructed analogs. We also show that along the Pacific Coast the Northern Oscillation Index (NOI) is a reliable predictor of storm likelihood, and therefore a predictor of seasonal precipitation totals and likelihood of extremely intense precipitation. Such time series can be used to project intensity duration curves into the future or input into stormwater models. However, few climate projection studies have explored the impact of the type of downscaling method used on the range and uncertainty of predictions for local flood protection studies. Here we present a study of the future climate flood risk at NASA Ames Research Center, located in South Bay Area, by comparing the range of predictions in extreme precipitation events calculated from three sets of time series downscaled from CMIP5 data: 1) the Bias Correction Constructed Analogs method dataset downscaled to a 1/8 degree grid (12km); 2) the Bias Correction Spatial Disaggregation method downscaled to a 1km grid; 3) a statistical model of extreme daily precipitation events and projected NOI from CMIP5 models. In addition, predicted years of extreme precipitation are used to estimate the risk of overtopping of the retention pond located on the site through simulations of the EPA SWMM hydrologic model. Preliminary results indicate that the intensity of extreme precipitation events is expected to increase and flood the NASA Ames retention pond. The results from these estimations will assist flood protection managers in planning for infrastructure adaptations.

Storm↗

NASA NTRS2016

NASA Soil Moisture Active Passive Mission Status and Science Performance

The Soil Moisture Active Passive (SMAP) observatory was launched January 31, 2015, and its L-band radiometer and radar instruments became operational since mid-April 2015. The SMAP radiometer has been operating flawlessly, but the radar transmitter ceased operation on July 7. This paper provides a status summary of the calibration and validation of the SMAP instruments and the quality assessment of its soil moisture and freeze/thaw products. Since the loss of the radar in July, the SMAP project has been conducting two parallel activities to enhance the resolution of soil moisture products. One of them explores the Backus Gilbert optimum interpolation and de-convolution techniques based on the oversampling characteristics of the SMAP radiometer. The other investigates the disaggregation of the SMAP radiometer data using the European Space Agency's Sentinel-1 C-band synthetic radar data to obtain soil moisture products at about 1 to 3 kilometers resolution. In addition, SMAP's L-band data have found many new applications, including vegetation opacity, ocean surface salinity and hurricane ocean surface wind mapping. Highlights of these new applications will be provided.

hydroclimatology↗

NASA NTRS2016

Gridded National Inventory of U.S. Methane Emissions

We present a gridded inventory of US anthropogenic methane emissions with 0.1 deg x 0.1 deg spatial resolution, monthly temporal resolution, and detailed scale dependent error characterization. The inventory is designed to be onsistent with the 2016 US Environmental Protection Agency (EPA) Inventory of US Greenhouse Gas Emissionsand Sinks (GHGI) for 2012. The EPA inventory is available only as national totals for different source types. We use a widerange of databases at the state, county, local, and point source level to disaggregate the inventory and allocate the spatial and temporal distribution of emissions for individual source types. Results show large differences with the EDGAR v4.2 global gridded inventory commonly used as a priori estimate in inversions of atmospheric methane observations. We derive grid-dependent error statistics for individual source types from comparison with the Environmental Defense Fund (EDF) regional inventory for Northeast Texas. These error statistics are independently verified by comparison with the California Greenhouse Gas Emissions Measurement (CALGEM) grid-resolved emission inventory. Our gridded, time-resolved inventory provides an improved basis for inversion of atmospheric methane observations to estimate US methane emissions and interpret the results in terms of the underlying processes.

Methane↗

NASA NTRS2017

NASA Soil Moisture Active Passive Mission Status and Science Highlights

The Soil Moisture Active Passive (SMAP) observatory was launched January 31, 2015, and its L-band radiometer and radar instruments became operational during April 2015. This paper provides a summary of the quality assessment of its baseline soil moisture and freeze/thaw products as well as an overview of new products. The first new product explores the Backus Gilbert optimum interpolation based on the oversampling characteristics of the SMAP radiometer. The second one investigates the disaggregation of the SMAP radiometer data using the European Space Agency's Sentinel-1 C-band synthetic aperture radar (SAR) data to obtain soil moisture products at about 1 to 3 km resolution. In addition, SMAPs L-band data have been found useful for many scientific applications, including depictions of water cycles, vegetation opacity, ocean surface salinity and hurricane ocean surface wind mapping. Highlights of these new applications will be provided.The SMAP soil moisture, freeze/taw state and SSSprovide a synergistic view of water cycle. For example, Fig.7 illustrates the transition of freeze/thaw state, change of soilmoisture near the pole and SSS in the Arctic Ocean fromApril to October in 2015 and 2016. In April, most parts ofAlaska, Canada, and Siberia remained frozen. Melt onsetstarted in May. Alaska, Canada, and a big part of Siberia havebecome thawed at the end of May; some freshwater dischargecould be found near the mouth of Mackenzie in 2016, but notin 2015. The soil moisture appeared to be higher in the Oband Yenisei river basins in Siberia in 2015. As a result,freshwater discharge was more widespread in the Kara Seanear the mouths of both rivers in June 2015 than in 2016. TheNorth America and Siberia have become completely thawedin July. After June, the freshwater discharge from other riversinto the Arctic, indicated by blue, also became visible. Thefreeze-up started in September and the high latitude regionsin North America and Eurasia became frozen. Comparing thespread of freshwater in August 2015 and 2016 suggests thatthere was more discharge from Ob and Yenisei in 2015,which appeared to correspond to a higher soil moisturecontent in the Ob and Yenisei basins. In contrast, Mackenzieappeared to have more discharge in September 2016.

soil moisture↗

NASA NTRS2017

Validation and Scaling of Soil Moisture in a Semi-Arid Environment: SMAP Validation Experiment 2015 (SMAPVEX15)

The NASA SMAP (Soil Moisture Active Passive) mission conducted the SMAP Validation Experiment 2015 (SMAPVEX15) in order to support the calibration and validation activities of SMAP soil moisture data products. The main goals of the experiment were to address issues regarding the spatial disaggregation methodologies for improvement of soil moisture products and validation of the in situ measurement upscaling techniques. To support these objectives high-resolution soil moisture maps were acquired with the airborne PALS (Passive Active L-band Sensor) instrument over an area in southeast Arizona that includes the Walnut Gulch Experimental Watershed (WGEW), and intensive ground sampling was carried out to augment the permanent in situ instrumentation. The objective of the paper was to establish the correspondence and relationship between the highly heterogeneous spatial distribution of soil moisture on the ground and the coarse resolution radiometer-based soil moisture retrievals of SMAP. The high-resolution mapping conducted with PALS provided the required connection between the in situ measurements and SMAP retrievals. The in situ measurements were used to validate the PALS soil moisture acquired at 1-km resolution. Based on the information from a dense network of rain gauges in the study area, the in situ soil moisture measurements did not capture all the precipitation events accurately. That is, the PALS and SMAP soil moisture estimates responded to precipitation events detected by rain gauges, which were in some cases not detected by the in situ soil moisture sensors. It was also concluded that the spatial distribution of the soil moisture resulted from the relatively small spatial extents of the typical convective storms in this region was not completely captured with the in situ stations. After removing those cases (approximately10 of the observations) the following metrics were obtained: RMSD (root mean square difference) of0.016m3m3 and correlation of 0.83. The PALS soil moisture was also compared to SMAP and in situ soil moisture at the 36-km scale, which is the SMAP grid size for the standard product. PALS and SMAP soil moistures were found to be very similar owing to the close match of the brightness temperature measurements and the use of a common soil moisture retrieval algorithm. Spatial heterogeneity, which was identified using the high-resolution PALS soil moisture and the intensive ground sampling, also contributed to differences between the soil moisture estimates. In general, discrepancies found between the L-band soil moisture estimates and the 5-cm depth in situ measurements require methodologies to mitigate the impact on their interpretations in soil moisture validation and algorithm development. Specifically, the metrics computed for the SMAP radiometer-based soil moisture product over WGEW will include errors resulting from rainfall, particularly during the monsoon season when the spatial distribution of soil moisture is especially heterogeneous.

SMAPVEX15↗

NASA NTRS2018

Next-Generation NASA Earth-Orbiting Relay Satellites: Fusing Microwave and Optical Communications

NASA is currently considering architectures and concepts for the generation of relay satellites that will replace the Tracking and Data Relay Satellite (TDRS) constellation, which has been flying since 1983. TDRS-M, the last of the second TDRS generation, launched in August 2017, extending the life of the TDRS constellation beyond 2030. However, opportunities exist to re-engineer the concepts of geosynchronous Earth relay satellites. The needs of the relay satellite customers have changed dramatically over the last 34 years since the first TDRS launch. There is a demand for greater bandwidth as the availability of the traditional RF spectrum for space communications diminishes and the demand for ground station access grows. The next generation of NASA relay satellites will provide for operations that have factored in these new constraints. In this paper, we describe a heterogeneous constellation of geosynchronous relay satellites employing optical and RF communications. The new constellation will enable new optical communications services formed by user-to-space relay, space relay-to-space relay and space relay-to-ground links. It will build upon the experience from the Lunar Laser Communications Demonstration from 2013 and the Laser Communications Relay Demonstration to be launched in 2019.Simultaneous to establishment of the optical communications space segment, spacecraft in the TDRS constellation will be replaced with RF relay satellites with targeted subsets of the TDRS capabilities. This disaggregation of the TDRS service model will allow for flexibility in replenishing the needs of legacy users as well as addition of new capabilities for future users. It will also permit the U.S. government access to launch capabilities such as rideshare and to hosted payloads that were not previously available. In this paper, we also explore how the next generation of Earth relay satellites provides a significant boost in the opportunities for commercial providers to the communications space segment. For optical communications, the backbone of this effort is adoption of commercial technologies from the terrestrial high-bandwidth telecommunications industry into optical payloads. For RF communications, the explosion of software-defined radio, high-speed digital signal processing technologies and networking from areas such as 5G multicarrier will be important. Future commercial providers will not be limited to a small set of large aerospace companies. Ultimately, entirely government-owned and -operated satellite communications will phase out and make way for commercial business models that satisfy NASAs satellite communications requirements. The competition being provided by new entrants in the space communications business may result in a future in which all NASA communications needs can be satisfied commercially.

Space Communications↗

NASA NTRS2018

Next-Generation NASA Earth-Orbiting Relay Satellites: Fusing Optical and Microwave Communications

NASA is currently considering architectures and concepts for the generation of relay satellites that will replace the Tracking and Data Relay Satellite (TDRS) constellation, which has been flying since 1983. TDRS-M, the last of the second TDRS generation, launched in August 2017, extending the life of the TDRS constellation beyond 2030. However, opportunities exist to re-engineer the concepts of geosynchronous Earth relay satellites. The needs of the relay satellite customers have changed dramatically over the last 34 years since the first TDRS launch. There is a demand for greater bandwidth as the availability of the traditional RF spectrum for space communications diminishes and the demand for ground station access grows. The next generation of NASA relay satellites will provide for operations that have factored in these new constraints. In this paper, we describe a heterogeneous constellation of geosynchronous relay satellites employing optical and RF communications. The new constellation will enable new optical communications services formed by user-to-space relay, space relay-to-space relay and space relay-to-ground links. It will build upon the experience from the Lunar Laser Communications Demonstration from 2013 and the Laser Communications Relay Demonstration to be launched in 2019.Simultaneous to establishment of the optical communications space segment, spacecraft in the TDRS constellation will be replaced with RF relay satellites with targeted subsets of the TDRS capabilities. This disaggregation of the TDRS service model will allow for flexibility in replenishing the needs of legacy users as well as addition of new capabilities for future users. It will also permit the U.S. government access to launch capabilities such as rideshare and to hosted payloads that were not previously available.In this paper, we also explore how the next generation of Earth relay satellites provides a significant boost in the opportunities for commercial providers to the communications space segment. For optical communications, the backbone of this effort is adoption of commercial technologies from the terrestrial high-bandwidth telecommunications industry into optical payloads. For RF communications, the explosion of software-defined radio, high-speed digital signal processing technologies and networking from areas such as 5G multicarrier will be important. Future commercial providers will not be limited to a small set of large aerospace companies. Ultimately, entirely government-owned and -operated satellite communications will phase out and make way for commercial business models that satisfy NASA's satellite communications requirements. The competition being provided by new entrants in the space communications business may result in a future in which all NASA communications needs can be satisfied commercially.

Space Communications↗

NASA NTRS2018

A Method for Mapping Future Urbanization in the United States

Cities are poised to absorb additional people. Their sustainability, or ability to accommodate a population increase without depleting resources or compromising future growth, depends on whether they harness the efficiency gains from urban land management. Population is often projected as a bulk national number without details about spatial distribution. We use Landsat and population data in a methodology to project and map U.S. urbanization for the year 2020 and document its spatial pattern. This methodology is important to spatially disaggregate projected population and assist land managers to monitor land use, assess infrastructure and distribute resources. We found the U.S. west coast urban areas to have the fastest population growth with relatively small land consumption resulting in future decrease in per capita land use. Except for Miami (FL), most other U.S. large urban areas, especially in the Midwest, are growing spatially faster than their population and inadvertently consuming land needed for ecosystem services. In large cities, such as New York, Chicago, Houston and Miami, land development is expected more in suburban zones than urban cores. In contrast, in Los Angeles land development within the city core is greater than in its suburbs.

Bounoua, Lahouari↗

NASA NTRS2018

Toward Landsat and Sentinel-2 BRDF Normalization and Albedo Estimation: A Case Study in the Peruvian Amazon Forest

The Amazon forest has been the focus of study by the science community during the last few decades. Remote sensing data analysis is the only way to study such a large geographical extent during an extended period of time. Since the launch in 2015 of Sentinel 2 and its increase in temporal resolution through the combination with Landsat sensors, a strong emphasis has been put on exploiting these data. Though these satellites provide near nadir observations, surface reflectance time series are affected by illumination variability throughout the year. These effects can be corrected using a Bidirectional Reflectance Distribution Function (BRDF) model. Franch et al. (2014a) developed a methodology to derive Landsat surface albedo and BRDF. It is based on the BRDF parameters from the MODerate Resolution Imaging Spectroradiometer (MODIS) which are disaggregated at Landsat spatial resolution (30 m). In this work, we apply the Franch et al. (2014a) method to normalize the surface reflectance for BRDF effects using the NASA's Harmonized Landsat Sentinel-2 (HLS) product. We apply this method to the Tambopata region in Peru from 2013 to 2017 and validate it using ground-based albedometer measurements. The results show that the near infrared reflectance can increase up to 0.06 (20%) for low solar angles while the impact on the red range and the NDVI is minor (<0.01). The evaluation of the surface albedo against field measurements shows an error of 0.01.

Landsat 8↗

NASA NTRS2020

Modeling Uncertainty in Large Natural Resource Allocation Problems

The productivity of the world's natural resources is critically dependent on a variety of highly uncertain factors, which obscure individual investors and governments that seek to make long-term, sometimes irreversible investments in their exploration and utilization. These dynamic considerations are poorly represented in disaggregated resource models, as incorporating uncertainty into large-dimensional problems presents a challenging computational task. This study introduces a novel numerical method to solve large-scale dynamic stochastic natural resource allocation problems that cannot be addressed by conventional methods. The method is illustrated with an application focusing on the allocation of global land resource use under stochastic crop yields due to adverse climate impacts and limits on further technological progress. For the same model parameters, the range of land conversion is considerably smaller for the dynamic stochastic model as compared to deterministic scenario analysis. The scenario analysis can thus significantly overstate the magnitude of expected land conversion under uncertain crop yields.

Cai, Yongyang↗

NASA NTRSDate not supplied

Retrospective Observations of the Solar System Planets with Interstellar Probe

Retrospective Observations of the Solar System Planets with Interstellar Probe The Interstellar Probe (ISP) mission concept could simultaneously explore a number of long-standing solar system and exoplanetary science objectives. ISP’s long mission lifetime, in combination with the large separations from the solar system objects it could observe (Fig. 1), affords a truly unique dataset. This data could be leveraged to validate models of solar system and extrasolar planets and would be directly analogous to observations we can expect to make for exoplanets. Taken together, these opportunities suggest that ISP’s mission is a critical and necessary component for future planetary science endeavors. This abstract aims to address some of the clear synergies between ISP’s mission profile and the gaps in solar system science that are necessarily gaps in our ability to wholly bound our expectations for exoplanet observations (partly discussed in several white papers, including Zemcov et al., 2019; Harman et al., 2020). Notably, no single platform has yet returned near-complete phase curves for the majority of solar system planets. This is partly due to observational constraints (e.g., ground-based observatories can observe a maximum phase angle of Jupiter, Saturn, Uranus, and Neptune of 12º, 6º, 3º, and 2º, respectively; Mallama and Hilton, 2018), but also because of the sparse nature of observations captured by spacecraft over the last 40 years (e.g., Pollack et al., 1986). Additionally, these observations come from disparate instruments that have their own biases and limitations, whereas observations by ISP’s instrumentation would provide almost uniform measurements of nearly every solar system object, removing much of the uncertainty when it comes to data intercomparisons. The biggest hurdles for making these measurements from ISP are likely to be the tight mass and energy limitations, as well as the technical challenge of looking as close as possible to the Sun without peering directly at it. This is potentially complicated by the nature of the larger astrophysical mission requirements, including whether the spacecraft is spinning, but integrating observations on board before returning them to Earth serves to both partly mitigate both the possibility of a spinning spacecraft and the downlink volumes for lookback data (although it may make data disaggregation more technically challenging). Ultimately, ISP could return truly innovative observational data of our solar system, in furtherance of a number of planetary and solar system science goals.

Sonny Harman↗

NASA NTRS2021

A Method for Landsat and Sentinel 2 (HLS) BRDF Normalization

The Harmonized Landsat/Sentinel-2 (HLS) project aims to generate a seamless surface reflectance product by combining observations from USGS/NASA Landsat-8 and ESA Sentinel-2 remote sensing satellites. These satellites’ sampling characteristics provide nearly constant observation geometry and low illumination variation through the scene. However, the illumination variation throughout the year impacts the surface reflectance by producing higher values for low solar zenith angles and lower reflectance for large zenith angles. In this work, we present a model to derive the bidirectional reflectance distribution function (BRDF) normalization and apply it to the HLS product at 30m spatial resolution. It is based on the BRDF parameters estimated from the MODerate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product (M{O,Y}D09) at 1 km spatial resolution using the VJB method (Vermote et al., 2009). Unsupervised classification (segmentation) of HLS images is used to disaggregate the BRDF parameters to the HLS spatial resolution and to build a BRDF parameters database at HLS scale. We first test the proposed BRDF normalization for different solar zenith angles over two homogeneous sites, in particular one desert and one Peruvian Amazon forest. The proposed method reduces both the correlation with the solar zenith angle and the coefficient of variation (CV) of the reflectance time series in the red and near infrared bands to 4% in forest and keeps a low CV of 3% to 4% for the deserts. Additionally, we assess the impact of the view zenith angle (VZA) in an area of the Brazilian Amazon forest close to the equator, where impact of the angular variation is stronger because it occurs in the principal plane. The directional reflectance shows a strong dependency with the VZA. The current HLS BRDF correction reduces this dependency but still shows an under-correction, especially in the near infrared, while the proposed method shows no dependency with the view angles. We also evaluate the BRDF parameters using field surface albedo measurements as a reference over seven different sites of the US surface radiation budget observing network (SURFRAD) and five sites of the Australian OzFlux network.

Belen Franch↗

NASA NTRS2019

Exploiting OMI NO2 Satellite Observations to Infer Fossil-fuel CO2 Emissions from U.S. Megacities

Fossil-fuel CO2 emissions and their trends in eight U.S. megacities during 2006–2017 are inferred by combining satellite-derived NOX emissions with bottom-up city-specific NOX-to-CO2 emission ratios. A statistical model is fit to a collection NO2 plumes observed from the Ozone Monitoring Instrument (OMI), and is used to calculate top-down NOX emissions. Decreases in OMI-derived NOX emissions are observed across the eight cities from 2006 to 2017 (−17% in Miami to −58% in Los Angeles), and are generally consistent with long-term trends of bottom-up inventories (−25% in Miami to −49% in Los Angeles), but there are some interannual discrepancies. City-specific NOX-to-CO2 emission ratios, used to calculate inferred CO2, are estimated through annual bottom-up inventories of NOX and CO2 emissions disaggregated to 1 × 1 km2 resolution. Over the study period, NOX-to-CO2 emission ratios have decreased by ~40% nationwide (−24% to −51% for our studied cities), which is attributed to a faster reduction in NOX when compared to CO2 due to policy regulations and fuel type shifts. Combining top-down NOX emissions and bottom-up NOX-to-CO2 emission ratios, annual fossil-fuel CO2 emissions are derived. Inferred OMI-based top-down CO2 emissions trends vary between +7% in Dallas to −31% in Phoenix. For 2017, we report annual fossil-fuel CO2 emissions to be: Los Angeles 113 ± 49 Tg/yr; New York City 144 ± 62 Tg/yr; and Chicago 55 ± 24 Tg/yr. A study in the Los Angeles area, using independent methods, reported a 2013–2016 average CO2 emissions rate of 104 Tg/yr and 120 Tg/yr, which suggests that the CO2 emissions from our method are in good agreement with other studies' top-down estimates. We anticipate future remote sensing instruments – with better spatial and temporal resolution – will better constrain the NOX-to-CO2 ratio and reduce the uncertainty in our method.

Ozone Monitoring Instrument (OMI)↗

NASA NTRS2020

Supporting Information for ”The 2019-2020 Australian Drought and Bushfires Altered the Partitioning of Hydrological Fluxes

The model configuration employs the modified International Geosphere Biosphere Programme (IGBP) MODIS 20 category landcover data, soil parameters derived from the International Soil Reference and Information Centre, and the Shuttle Radar Topography Mission based elevation, slope, and aspect data. Statistical downscaling approaches are used to transform the coarse resolution MERRA2 meteorological inputs to 1km. The input meteorological fields of air temperature, humidity, surface pressure, wind, downward shortwave radiation, and downward longwave radiation are downscaled to 1km by adjusting for terrain differences in elevation, slope, and aspect. The high resolution monthly precipitation climatology from WorldClim is used to spatially disaggregate input MERRA2 precipitation to 1km. The initial conditions for the model simulations are generated from a long spinup of NoahMP starting from year 2000. All model integrations and evaluations are conducted using the NASA Land Information System and the Land surface Verification Toolkit.

Sujay V Kumar↗

NASA NTRS2021

Optimizing GRACE/GRACE-FO Data and A priori Hydrological Knowledge for Improved Global Terrestial Water Storage Component Estimates

The comprehensive information of global terrestrial water storage (TWS) components (soil moisture, groundwater, snow, surface water) is essential for effective assessment of water resource availability, climate variation, and disaster mitigation measures. Observational data provided by the Gravity Recovery And Climate Experiment (GRACE) and GRACE Follow-On satellite missions offer global TWS variation (ΔTWS) in terms of an integrated water column. However, GRACE spatial resolution is relatively coarse (i.e., 3°), and the vertically integrated value cannot be separated into ΔTWS components directly. This study demonstrates the feasibility to estimate ΔTWS components at any desired spatial-vertical resolution by effectively maintaining the native resolution of the employed hydrological knowledge. It utilizes a least-squares with constraints (LSC) approach to rigorously incorporate GRACE and GRACE-FO data and a priori hydrological knowledge, with the aim to improve global ΔTWS components’ accuracy and spatial resolution. The 3°×3° GRACE mascon derived ΔTWS data is disaggregated into the 0.5°×0.5° anomalous soil moisture storage (ΔSMS), groundwater storage (ΔGWS), snow water equivalent (ΔSWE), and surface water storage (ΔSWS) based on the covariance information obtained from the Community Atmosphere Biosphere Land Exchange (CABLE) and the PCRaster Global Water Balance (PCR-GLOBWB) models. Evaluation with different ground measurements and satellite products between 2002 and 2019 exhibits significantly improved accuracy in all individual ΔTWS components. This improvement is of particular note in ΔGWS and ΔSWS, where the LSC approach increases the globally averaged correlation values by approximately 0.13 and 0.05, respectively. Reliable prior knowledge leads to a more accurate ΔTWS component estimate, and the use of ensemble-mean knowledge yields the best result.

GRACE↗

NASA NTRSDate not supplied

NASA’s Goddard Space Flight Center’s Distributed Systems Missions Architecture

Space and Earth Science are being transformed by applying a distributed approach to missions, where the fusion of data from components, systems, instruments, models, and observation locations works in concert with timely responses and feedback mechanisms to multiply the knowledge obtained. Additionally, a disaggregated approach allows for a distributed cost and schedule that can be shared across multiple organizations to enable the greater mission. With the advances in reduced size, weight, and power for space-worthy components leading to the revolution in smaller spacecraft, the cost and timeliness proposition for launching multiple space assets has also greatly improved. Thus, the aerospace industry is undergoing a paradigm shift toward a proliferation of small satellites as a networked approach to meet mission objectives. This paper will describe the impetus, goal, and path to provide an openly available framework as a unifying catalyst for broad-ranging Distributed Systems Missions (DSMs) contributors.

Distributed Systems↗