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26 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Warming, Increase in Precipitation, and Irrigation Enhance Greening in High Mountain Asia

High-Mountain Asia (HMA) exhibits one of the highest increases in vegetation greenness on Earth, subsequently influencing the exchange of water and energy between the land surface and the atmosphere. Given the strong interactions between the hydrosphere, the biosphere, and the cryosphere, understanding the drivers of greening in this highly complex region with significant land cover heterogeneity is essential to assess the changes in the regional water budget. Here we perform a holistic multivariate remote sensing analysis to simultaneously examine the primary components of the terrestrial water cycle from 2003 to 2020 and decipher the principal drivers of greening in HMA. We identified three drivers of greening: (1) precipitation drives greening in mid and low elevation areas covered by evergreen and mixed forests (e.g., Irrawaddy basin), (2) decreases in snow enhance greening in most of the hydrologic basins, and (3) irrigation induces greening in irrigated lands (Ganges-Brahmaputra and Indus).

Fadji Zaouna Maina↗
NASA NTRS2022

Evaluation of High Mountain Asia-Land Data Assimilation System (version 1) from 2003 to 2016: 2. The impact of assimilating satellite-based snow cover and freeze/thaw observations into a land surface model

This second paper of the two-part series focuses on demonstrating the impact of assimilating satellite-based snow cover and freeze/thaw observations into the hyper-resolution, offline terrestrial modeling system used for the High Mountain Asia (HMA) region from 2003 to 2016. To this end, this study systematically evaluates a total of six sets of 0.01° (∼1 km) model simulations forced by different precipitation forcings, with and without the dual assimilation scheme enabled, at point-scale, basin-scale, and domain-scale. The key variables of interest include surface net shortwave radiation, surface net longwave radiation, skin temperature, near-surface soil temperature, snow depth, snow water equivalent (SWE), and total runoff. First, the point-scale assessment is mainly conducted via evaluating against ground-based measurements. In general, the assimilation enabled estimates are better than no-assimilation counterparts. Second, the basin-scale runoff assessment demonstrates that across three snow-dominated basins, the assimilation enabled experiment yields systematic improvements in all goodness-of-fit statistics through mitigating the negative effects brought by the fixed long-term precipitation correction factors. For example, when forced by the bias-corrected precipitation, the assimilation-enabled experiment improves the bias by 69%, the root-mean-squared error by 30%, and the unbiased root-mean-squared error by 18% (relative to the no-assimilation counterpart). Finally, the domainscale assessment is conducted via evaluating against satellite-based SWE and skin temperature products. Both sets of domain-scale analysis further corroborate the findings in the point-scale evaluations. Overall, this study suggests the benefits of the proposed multi-variate assimilation system in improving the cryospherichydrological process within a land surface model for use in HMA.

Yuan Xue↗
NASA NTRS2022

Evaluation of High Mountain Asia-Land Data Assimilation System (version 1) from 2003 to 2016: 2. The impact of assimilating satellite-based snow cover and freeze/thaw observations into a land surface model

This second paper of the two-part series focuses on demonstrating the impact of assimilating satellite-based snow cover and freeze/thaw observations into the hyper-resolution, offline terrestrial modeling system used for the High Mountain Asia (HMA) region from 2003 to 2016. To this end, this study systematically evaluates a total of six sets of 0.01° (∼1 km) model simulations forced by different precipitation forcings, with and without the dual assimilation scheme enabled, at point-scale, basin-scale, and domain-scale. The key variables of interest include surface net shortwave radiation, surface net longwave radiation, skin temperature, near-surface soil temperature, snow depth, snow water equivalent (SWE), and total runoff. First, the point-scale assessment is mainly conducted via evaluating against ground-based measurements. In general, the assimilation enabled estimates are better than no-assimilation counterparts. Second, the basin-scale runoff assessment demonstrates that across three snow-dominated basins, the assimilation enabled experiment yields systematic improvements in all goodness-of-fit statistics through mitigating the negative effects brought by the fixed long-term precipitation correction factors. For example, when forced by the bias-corrected precipitation, the assimilation-enabled experiment improves the bias by 69%, the root-mean-squared error by 30%, and the unbiased root-mean-squared error by 18% (relative to the no-assimilation counterpart). Finally, the domain-scale assessment is conducted via evaluating against satellite-based SWE and skin temperature products. Both sets of domain-scale analysis further corroborate the findings in the point-scale evaluations. Overall, this study suggests the benefits of the proposed multi-variate assimilation system in improving the cryospheric-hydrological process within a land surface model for use in HMA.

Yuan Xue↗
NASA NTRS2024

Anthropogenic Influences Alter the Response and Seasonality of Evapotranspiration: A Case Study Over Two High Mountain Asia Basins

Earth's vegetation has been increasing over the past decades, altering water and energy cycles by changing evapotranspiration (ET). Greening, caused by climatic and anthropogenic factors, has high rates in High Mountain Asia (HMA). Here we focus on two HMA basins (the Yangtze and the Ganges-Brahmaputra) to contrast the impacts of climate- and human-induced greening on ET. Though the rate of greening is similar in both basins, anthropogenic influences lead to dissimilar responses in ET. In the Yangtze, climate-induced greening increases ET, with the increase in moisture being high enough to meet the ET demand. In the Ganges-Brahmaputra, irrigation-induced greening does not alter annual ET, only pre-monsoon ET increases. The dry season declines in water storage due to pumping decrease ET, while laboriously meeting the demand. This study provides a representative example of the contrasting influences of climate induced and anthropogenic driven processes on the seasonality of ET.

Fadji Z Maina↗
NASA NTRS2024

Synergy of Urban Heat, Pollution, and Social 1 Vulnerability in One of America’s Most Rapidly 2 Growing Cities: Houston, We Have a Problem

During the first two decades of the twenty-first century, we analyze the expansion of 23urban land cover, urban heat island (UHI), and urban pollution island (UPI) in the Houston 24Metropolitan Area (HMA) using land cover classifications derived from Landsat and land/aerosol 25products from NASA's Moderate Resolution Imaging Spectroradiometer. Our approach involves 26both direct utilization and fusion with in situobservations for a comprehensive characterization.27We also examined how social vulnerability within the HMA changed during the study period and 28whether the synergy of UHI, UPI,and social vulnerability enhances environmental inequalities.

Andrew Blackford↗
NASA NTRSDate not supplied

NASA’s Exploration and In-Space Services (NExIS) Division OSAM-1 Propellant Transfer Subsystem Progress through FY 2024

The National Aeronautics and Space Administration (NASA) Exploration and In-Space Services (NExIS) Division of Goddard Space Flight Center (GSFC) has been developing technology to robotically refuel both heritage and recently developed satellites on-orbit funded through NASA’s Space Technology Mission Directorate (STMD). The On-orbit Servicing, Assembly, and Manufacturing 1 (OSAM-1) mission, formerly known as Restore-L, developed a system to refuel a satellite in space and assemble a communications antenna. By demonstrating these capabilities, the mission would advance never-before tested technologies for use in future missions (by NASA, other government organizations, and private industries). The purpose of this paper is to capture the lessons learned from the hardware development of the OSAM-1 Propellant Transfer System (PTS) that are highly relevant for the ISAM community. This paper covers a review of in-space servicing extensibility and critical technologies that were being developed within NExIS, focusing on the fluid transfer refueling technology within the framework of the OSAM-1 PTS. An overview of the technology demonstration servicing mission via the OSAM-1 Space Vehicle is provided as an extension of the technology development progress reported in 2018, 2019 and 2020. The general objectives, challenges, and key technologies are presented as an introduction to the context of the OSAM-1 mission, and a precursor to the OSAM-1 PTS specific development status. Final assembly, qualification, and functional tests along with installation and acceptance testing of the Hose Management Assembly (HMA) and Propellant Transfer Assembly (PTA) are discussed. Technology development, challenges, lessons learned, along with installation and testing results are discussed, with particular focus on the OSAM-1 assemblies including the PTA and HMA. In addition, testing utilizing the integrated flight simulator test setups will be summarized. The OSAM-1 PTS made great strides in advancing in-space refueling technology; however, there are unfinished development efforts remaining. This paper concludes with a brief summary of the technology shortfalls (gaps) that remain in the key areas of in-space fluid transfer.

ISAM↗
NASA NTRS2008

Launch Pad 39 Hail Monitor Array System

Weather conditions at Kennedy Space Center are extremely dynamic, and they greatly affect the safety of the Space Shuttles sitting on the launch pads. For example, on May 13, 1999, the foam on the External Tank (ET) of STS-96 was significantly damaged by hail at the launch pad, requiring rollback to the Vehicle Assembly Building. The loss of ET foam on STS-114 in 2005 intensified interest in monitoring and measuring damage to ET foam, especially from hail. But hail can be difficult to detect and monitor because it is often localized and obscured by heavy rain. Furthermore, the hot Florida climate usually melts the hail even before the rainfall subsides. In response, the hail monitor array (HMA) system, a joint effort of the Applied Physics Laboratory operated by NASA and ASRC Aerospace at KSC, was deployed for operational testing in the fall of 2006. Volunteers from the Community Collaborative Rain, Hail, and Snow (CoCoRaHS) network, in conjunction with Colorado State University, continue to test duplicate hail monitor systems deployed in the high plains of Colorado.

Source record↗
NASA NTRS2021

Evaluation of High Mountain Asia-Land Data Assimilation System (Version 1) from 2003 to 2016, Part I: A Hyper-Resolution Terrestrial Modeling System

This first paper of the two-part series focuses on demonstrating the accuracy of a hyper-resolution, offline terrestrial modeling system used for the High Mountain Asia (HMA) region. To this end, this study systematically evaluates four sets of model simulations at point scale, basin scale, and domain scale obtained from different spatial resolutions including 0.01° (∼1-km) and 0.25° (∼25-km). The assessment is conducted via comparisons against ground-based observations and satellite-derived reference products. The key variables of interest include surface net shortwave radiation, surface net longwave radiation, skin temperature, near-surface soil temperature, snow depth, snow water equivalent, and total runoff. In the evaluation against ground-based measurements, the superiority of the 0.01° estimates are mostly demonstrated across relatively complex terrain. Specifically, hyper-resolution modeling improves the skill in meteorological forcing estimates (except precipitation) by 9% relative to coarse-resolution estimates. The model forced by downscaled forcings in its entirety yields the highest skill in model output states as well as precipitation, which improves the skill obtained by coarse-resolution estimates by 7%. These findings, on one hand, corroborate the importance of employing the hyper-resolution versus coarse-resolution modeling in areas characterized by complex terrain. On the other hand, by evaluating four sets of model simulations forced with different precipitation products, this study emphasizes the importance of accurate hyper-resolution precipitation products to drive model simulations.

Yuan Xue↗