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1.
Sci Rep ; 11(1): 15443, 2021 07 29.
Artículo en Inglés | MEDLINE | ID: mdl-34326427

RESUMEN

Milky seas are a rare form of marine bioluminescence where the nocturnal ocean surface produces a widespread, uniform and steady whitish glow. Mariners have compared their appearance to a daylit snowfield that extends to all horizons. Encountered most often in remote waters of the northwest Indian Ocean and the Maritime Continent, milky seas have eluded rigorous scientific inquiry, and thus little is known about their composition, formation mechanism, and role within the marine ecosystem. The Day/Night Band (DNB), a new-generation spaceborne low-light imager, holds potential to detect milky seas, but the capability has yet to be demonstrated. Here, we show initial examples of DNB-detected milky seas based on a multi-year (2012-2021) search. The massive bodies of glowing ocean, sometimes exceeding 100,000 km2 in size, persist for days to weeks, drift within doldrums amidst the prevailing sea surface currents, and align with narrow ranges of sea surface temperature and biomass in a way that suggests water mass isolation. These findings show how spaceborne assets can now help guide research vessels toward active milky seas to learn more about them.

2.
Sensors (Basel) ; 10(1): 913-32, 2010.
Artículo en Inglés | MEDLINE | ID: mdl-22315576

RESUMEN

Spatial and temporal soil moisture dynamics are critically needed to improve the parameterization for hydrological and meteorological modeling processes. This study evaluates the statistical spatial structure of large-scale observed and simulated estimates of soil moisture under pre- and post-precipitation event conditions. This large scale variability is a crucial in calibration and validation of large-scale satellite based data assimilation systems. Spatial analysis using geostatistical approaches was used to validate modeled soil moisture by the Agriculture Meteorological (AGRMET) model using in situ measurements of soil moisture from a state-wide environmental monitoring network (Oklahoma Mesonet). The results show that AGRMET data produces larger spatial decorrelation compared to in situ based soil moisture data. The precipitation storms drive the soil moisture spatial structures at large scale, found smaller decorrelation length after precipitation. This study also evaluates the geostatistical approach for mitigation for quality control issues within in situ soil moisture network to estimates at soil moisture at unsampled stations.


Asunto(s)
Monitoreo del Ambiente/métodos , Modelos Estadísticos , Suelo/análisis , Suelo/química , Agua/análisis , Simulación por Computador
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