AI Summary & Key Takeaways
AI InsightBesides the linear relationships, nonlinear relationships are also studied using the Generalized, Unbiased, Interaction Detection and Estimation (GUIDE) algorithm, the results confirming similar predictions of Caspian Sea SST.
📌 3 Key Takeaways
Abstract
The relationship between climate indices and the Caspian Sea Surface Temperature (SST) are investigated, making use of the satellite measured SST during 1985-2005. North Sea Caspian Pattern (NCP) and NINO 3.4 index are shown to have a strong influence on the SST among the studied indices, in the studied February to May period. High correlation of SST with the climate indices suggests prompt response of the surface oceanic variables to the atmospheric forcing. Besides the linear relationships, nonlinear relationships are also studied using the Generalized, Unbiased, Interaction Detection and Estimation (GUIDE) algorithm, the results confirming similar predictions of Caspian Sea SST.
Özet
The relationship between climate indices and the Caspian Sea Surface Temperature (SST) are investigated, making use of the satellite measured SST during 1985-2005. North Sea Caspian Pattern (NCP) and NINO 3.4 index are shown to have a strong influence on the SST among the studied indices, in the studied February to May period. High correlation of SST with the climate indices suggests prompt response of the surface oceanic variables to the atmospheric forcing. Besides the linear relationships, nonlinear relationships are also studied using the Generalized, Unbiased, Interaction Detection and Estimation (GUIDE) algorithm, the results confirming similar predictions of Caspian Sea SST.