Abstract:

The results presented are from the NOAA EPPCSC NERTO graduate internship project conducted under the mentorship of Dr. Menghua Wang and co-mentor Dr. Jianwei Wei, Marine Ecosystems and Coastal Branch, NOAA/NESDIS/STAR. This NERTO experience aligns with the NOAA Cooperative Science Center in CESSRST-II, supporting the Center’s goal to understand and predict changes in oceans and coasts through science. This project, titled “Remote Sensing of Suspended Particulate Matter in Coastal Alaska with Ocean Color” addresses the performance and uncertainty of suspended particulate matter (SPM) retrieval algorithms in the complex and challenging coastal Arctic Alaska region.

Satellite ocean color remote sensing of suspended particulate matter (SPM) provides valuable spatial and temporal coverage for the study of coastal systems, including water clarity, riverine exports, and erosion. Satellite remote sensing retrievals of water quality parameters are critical in Arctic Alaska due to the expansive spatial extent and challenging sampling logistics in remote regions. The NOAA NESDIS STAR Ocean Color Science Team developed an algorithm for global SPM retrieval using the NIR-RGB (near infrared, red, green, and blue) bands of the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor. However, the study noted the need for additional evaluation in high latitude regions such as Arctic Alaska due to remote sensing reflectance (R_rs) uncertainties. This project compiled an expanded validation data set for Arctic Alaska with in situ SPM and R_rs samples, and granules from the NOAA VIIRS-SNPP (Suomi National Polar Orbiting Partnership) satellite sensor.

The NIR-RGB algorithm predicted SPM using in situ R_rs with strong agreement with in situ SPM samples based on fit statistics including the coefficient of determination (R²), bias, and median absolute percent difference (MAPD). Using VIIRS-SNPP R_rs for SPM prediction, R²was lower but bias and MAPD were consistent. The R_rs validation showed high alignment for the R_rs(671)/R_rs(551) band ratio, which is the most important for SPM retrieval in turbid waters, but weaker performance for the R_rs(551)/R_rs(443) band ratio used for SPM retrieval in clear waters, potentially indicating a driver of the lower fit for satellite SPM retrievals. As a case study, the project developed a spatial climatology and time series of SPM from 2012-2025in the Colville River Delta region of the Beaufort Sea using the NIR-RGB algorithm.

The work provides value to the scientific community and program stakeholders by assessing the uncertainty of the NIR-RGB suspended particulate matter (SPM) retrieval algorithm, indicating the suitability of theLevel-2 VIIRS SPM product available in NOAA Coast Watch and OC View for fisheries and coastal management applications in the coastal Arctic Alaska region. Through this internship, the student deepened their understanding of NOAA mission areas and gained skills in satellite remote sensing ocean color calibration and validation