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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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110 records · Page 7

Export of Ice Sheet Meltwater from Upernavik Fjord, West Greenland

Meltwater from Greenland is an important freshwater source for the North Atlantic Ocean, released into the ocean at the head of fjords in the form of runoff, submarine melt, and icebergs. The meltwater release gives rise to complex in-fjord transformations that result in its dilution through mixing with other water masses. The transformed waters, which contain the meltwater, are exported from the fjords as a new water mass Glacially Modified Water (GMW). Here we use summer hydrographic data collected from 2013 to 2019 in Upernavik, a major glacial fjord in northwest Greenland, to describe the water masses that flow into the fjord from the shelf and the exported GMWs. Using an optimum multi-parameter technique across multiple years we then show that GMW is composed of 57.8% ± 8.1% Atlantic Water (AW), 41.0% ± 8.3% Polar Water (PW), 1.0% ± 0.1% subglacial discharge, and 0.2% ± 0.2% submarine meltwater. We show that the GMW fractional composition cannot be described by buoyant plume theory alone since it includes lateral mixing within the upper layers of the fjord not accounted for by buoyant plume dynamics. Consistent with its composition, we find that changes in GMW properties reflect changes in the AW and PW source waters. Using the obtained dilution ratios, this study suggests that the exchange across the fjord mouth during summer is on the order of 50 mSv (1 Sv ≡ 10 6 m 3 s –1 ) (compared to a freshwater input of 0.5 mSv). This study provides a first-order parameterization for the exchange at the mouth of glacial fjords for large-scale ocean models.

58 GEOSCIENCES↗

The Global Spectra-Trait Initiative: A database of paired leaf spectroscopy and functional traits associated with leaf photosynthetic capacity (v1.0.0)

The Global Spectra-Trait Initiative (GSTI) aims to generate generalizable spectra trait models using reflectance data to predict leaf traits associated with the photosynthesis capacity of leaves. It comprises a synthesized dataset of leaf trait data, input datasets and code. Leaf traits include the maximum carboxylation rate of rubisco (Vcmax), the maximum electron transport rate (Jmax), the dark respiration, as well as the prediction of leaf nitrogen, leaf mass per area (LMA), and leaf water content (LWC). The dataset comprises >7500 paired observations from around 400 species from a broad range of biomes. This dataset comprises a zip file of the GSTI GitHub repository (https://github.com/plantphys/gsti), the synthesized database (.csv) and database metadata files. This dataset was updated on 2025-12-12 with minor edits to mirror the accepted manuscript version and GitHub release (Version 1.0.0 (ESSD accepted version)). Edits included minor changes to the project documentation on GitHub and removal of 12 duplicate entries from the database.

54 ENVIRONMENTAL SCIENCES↗