Abstract

The objective of this study is to compare and validate low and high resolution versions of sea surface temperature (SST) from NASA’s Multiscale Ultrahigh Resolution (MUR) L4 analysis. Statistical differences between buoys and satellites were calculated for ocean regions surrounding North America. In addition, yearly and seasonal SST biases and standard deviations were plotted and mapped. Special attention was given to the California Coast and Gulf Stream; one region is a major center of ocean upwelling and the other is the world’s fastest moving ocean current. The study is part of an international effort to develop high resolution SST data for seasonal forecasting, ocean modeling and forecasting, numerical weather prediction, and the research of climate variability and change. Previous studies have analyzed how resolution affects the quality of SST datasets, such as Pathfinder, but no published study has analyzed the resolution of MUR data, one of NASA’s newest SST products. Preliminary findings show that both low and high resolution datasets display similar SST biases and standard deviation as defined by satellite minus buoy. The higher resolution data display larger biases in the Gulf Stream, but lower biases off the coast of California. Results show that higher resolution SST data sets are critical for understanding the oceans in coastal regions and strong currents.

Mentor

Dr. Jorge Vazquez

Lab site

NASA Jet Propulsion Laboratory (JPL)

Funding Acknowledgement

This material is based upon work supported by the S.D. Bechtel, Jr. Foundation and by the National Science Foundation under Grant No. 0952013. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the S.D. Bechtel, Jr. Foundation or the National Science Foundation.

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URL: https://digitalcommons.calpoly.edu/star/97

 

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