NOAA EPP Cooperative Science Centers

Distinguishing diatom and dinoflagellate blooms in Chesapeake Bay is difficult because its waters are optically complex and field observations rarely coincide with satellite measurements. This project combines historical phytoplankton observations, NOAA satellite bloom products, geospatial processing and ecological information in a reproducible workflow. Quality control addresses mixed pixels, land contamination, cloud, missing observations, saturation and inconsistent coordinates. Of 31,531 field-to-satellite records, 860 initially pass validation; neighbouring pixels offer further recoverable data. A preliminary Mini U-Net illustrates segmentation feasibility but exposes weak automatic labels, motivating interactive expert validation and masking. Seasonal phenology and environmental variables are evaluated as features for future multimodal models. The NOAA NERTO project was mentored by Michelle Tomlinson and Sachidananda Mishra at NCCOS.

This project tests whether nearby National Weather Service METAR observations can fill missing pressure and temperature records at California's Sky Oaks Field Station, where measurements support carbon-cycle research. Linear mixed-effects models and inverse-distance interpolation combine archived observations from the Iowa Environmental Mesonet with USGS elevation data. The pressure model is statistically significant but its 1.21-millibar mean absolute error exceeds the one-millibar target. The temperature model finds no significant correlation and has a 2.60°F mean absolute error. An eddy-covariance tower was also restored to collect meteorological and gas-flux data. The work was completed through a NOAA NERTO internship mentored by Ivory Small and demonstrates both the potential and limitations of reconstructing local environmental observations.

Fixed-rate drone soundings can miss thin inversions, humidity transitions and wind shifts important to severe-weather forecasting. This project tests adaptive sampling by matching partial atmospheric profiles to seasonally stratified historical IGRA2 radiosondes. K-medoids clustering and a two-of-three point-of-interest voting method are integrated with the BLISS CopterSonde and LAAIRS ground-control system. Correcting a temperature convention reduces matching errors from approximately 18°C to 0.4–1.6°C; gains level off beyond about 15–20 medoids. Field validation places transition zones at 800–1,100 metres above ground, and the matching method operates end to end in LAAIRS. The NOAA NERTO work, mentored by Elizabeth Smith at the National Severe Storms Laboratory, examines a hardware-independent route to more efficient atmospheric sampling.

NOAA's Mussel Watch records are examined as a unified framework for coastal contamination. The study combines sediment chemistry, toxicity, benthic condition and tissue measurements, using AMBI and M-AMBI scores at 732 national assessment sites and 33 Hudson–Raritan stations. Random-forest and Bayesian models associate urbanization with benthic condition in the New York region (ρ=0.62), but not nationally (ρ=0.05). A Delft3D estuary model reproduces observed tides and predicts increased deep-channel bed shear under sea-level rise. The work asks whether sediment contaminants mediate urbanization impacts and whether legacy cleanup remains effective as sea level changes. It was conducted through a NOAA NERTO graduate internship with Kimani Kimbrough and Erik Davenport at NCCOS.