Results 171 to 174 of about 382 (174)

Retrieving riming in arctic mixed phase clouds from collocated remote sensing and in situ aircraft measurements during ACLOUD 

2022
<p>Ice crystal formation and growth processes in mixed-phase clouds (MPCs) are not sufficiently understood. This leads to uncertainties of atmospheric models in representing MPCs. This presentation is centered around riming, which occurs when liquid water droplets freeze onto ice crystals.
Nina Maherndl, Maximilian Maahn, Frederic Tridon, Regis Dupuy   +3 more
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Triple collocation-based estimation of spatially correlated observation error covariance in remote sensing soil moisture data assimilation

Journal of Applied Remote Sensing, 2018
Spatially correlated errors are typically ignored in data assimilation, thus degenerating the observation error covariance R to a diagonal matrix. We argue that a nondiagonal R carries more observation information making assimilation results more accurate.
Zhenhang Jiao, Lei Nie, Hong Shu, Kai Wu
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Dynamic collocation between satellite and in-situ measurements in wave remote sensing

The validation and error analysis of remote sensing data are important for their application. Currently, due to the relative scarcity of in-situ observations in the ocean, the accumulation of collocations between remote sensing and in-situ data is slow. This study proposes an engineering trick to address this issue: using the output of numerical models
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Estimation of the Errors of Remote Sensing and Hydrological Model-Based Soil Moisture Values Using Triple Collocation

2017
Only limited studies in Turkey have focused their attention on soil moisture even though it has a key role in climate, flood, drought and agricultural yield related studies. Estimation of soil moisture product obtained via merging of hydrological model- and remote sensing-based soil moisture data sets is only possible if the errors of the merged ...
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