A convolution process on a directed network provides a covariance model for SST that respects physical barriers and currents, used to identify thermal hot spots via Monte Carlo RCP projections.
The European Physical Journal Special Topics 174(1):157--179
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Wet-season rainfall over southeast India is increasing in amount and variability but shows potential predictability up to 10 months ahead from tropical sea surface temperature networks.
citing papers explorer
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A Convolution Process for Sea Surface Temperature Hot-Spot Identification in the Mediterranean Sea
A convolution process on a directed network provides a covariance model for SST that respects physical barriers and currents, used to identify thermal hot spots via Monte Carlo RCP projections.
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Prediction and Predictability of the Wet-Season Rainfall over Southeast India
Wet-season rainfall over southeast India is increasing in amount and variability but shows potential predictability up to 10 months ahead from tropical sea surface temperature networks.