Abstract
The northern Bay of Bengal (BoB) has been traditionally understudied and undersampled. Satellite and modeling products could compensate for the scarcity of in situ measurements, but this requires evaluating the accuracy of satellite and modeling products first. We present a comparison of sea surface temperature (SST) and sea surface salinity (SSS) products (satellite and model output) with 46 in situ observations in the northern BoB. We used satellite and modeled SST (daily) and SSS (weekly and daily) in this comparison. The results are as follows. (1) Both model and satellite-derived SSTs agreed well with in situ observations and with each other, with small biases (<1 ° C) and large correlation coefficients (r > 0.77). (2) Neither model nor satellite SSSs agreed well with in situ observations (biases > 0.5 PSU, r < 0.54). (3) Calculations of the d-index support the argument that model and satellite SSTs agreed well with in situ observations (d-index values of 0.68 and 0.65, respectively), while the model and satellite SSSs did not agree well with observations (d-index values of 0.31 and 0.40, respectively). The results suggest that additional work is needed to improve both model prediction and satellite retrieval algorithms for SSS in the northern BoB.
Highlights
Accurate and timely remote measurements of ocean temperature and salinity are essential for numerical prediction models[1] to forecast the ocean and atmosphere dynamics
For SSTsat, the standard deviation (SD) of bias was larger (1.06°C) than it was for SSTmod, even though the mean bias decreased to 0.09°C
This study presents evidence that in the data-poor region of the northern Bay of Bengal (BoB), satellite observations and model analyses compare well with in situ measurements of sea surface temperature (SST) but poorly with in situ measurements of sea surface salinity (SSS)
Summary
Accurate and timely remote measurements of ocean temperature and salinity are essential for numerical prediction models[1] to forecast the ocean and atmosphere dynamics. Brown et al.[2] analyzed calibration methods of the U.S National Oceanographic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR), by deriving accurate SST fields from satellite infrared (IR) observations, based on vacuum test datasets. Kumar et al.[3] explicitly examined the global Pathfinder algorithm’s performance in regional conditions, by comparing satellite data to buoy data. They concluded that a variation of ∼5°C existed between these two sources. Among the six different Group for High Resolution Sea Surface Temperature (GHRSST) Level[4] SST and Level-2 SSS products, they found good agreement with satellite-derived SST and less correlation to the SSS datasets
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
