NOAA Seminar Series: Phytoplankton monitoring and mapping using NOAA OAR/AOML satellite data products for urban waters ecosystems.
2024-10-21 14:00 - 14:35 (America/New_York)
Title: Phytoplankton monitoring and mapping using NOAA OAR/AOML satellite data products for urban waters ecosystems.

Presenter(s): Carolina Perez
Date: 21 October 2024 2:05 pm – 2:35 pm ET

Remote Access: Google Meet joining info
Video call link: https://meet.google.com/yjc-yvec-nkm
Or dial: (US) +1 929-269-1887 PIN: 429 915 143#
More phone numbers: https://tel.meet/yjc-yvec-nkm?pin=1379180679958
About Speaker: Carolina Perez
Abstract: Harmful Algal Blooms (HABs) significantly threaten coastal communities and public health, impacting marine ecosystems and local economies. These blooms indicate potentially toxic phytoplankton and reflect broader environmental issues such as eutrophication, runoff, and the effects of weather events on coastal areas. My research focuses on the monitoring of HABs in New York City waterbodies, specifically Randall’s Island and the Gowanus Canal, in collaboration with NOAA’s National Centers for Coastal Ocean Science (NCCOS)and the National Phytoplankton Monitoring Network (PMN). The Gowanus Canal, a notable study area, was designated a Superfund site by the EPA in 2010 due to its severe contamination from runoff and combined sewage overflow.During my time at AOML, as part of my NERTO research project, I helped develop a research technique by combining satellite data and ground-based data to develop interactive web tools to enhance the real-time monitoring of marine ecosystems. While a NOAA AOML NERTO Intern, I contributed to enhancing sustainability and resilience for marine ecosystems and coastal communities. AOML’s Ocean Chemistry and Ecosystem Dynamics (OCED) branch employs satellite observations to analyze sea surface temperature (SST) and chlorophyll-a (CHL) levels in water bodies. Using the Environmental Research Division’s Data Access Program (ERDDAP), data on SST and CHL I was able to generate detailed maps of these parameters using MATLAB. Integrating satellite-based data with in-situ measurements offers a powerful approach to understanding the health of both open ocean and coastal ecosystems. Combining these data sources, the research aims to create synthesis products that examine algal blooms and their dynamics.The results are from the NOAA EPP/MSI CSC NERTO graduate internship project that was conducted with NOAA mentors Dr. Chris Kelble and Dr. Enrique Montes of the NOAA Atlantic Oceanographic and Meteorological Laboratory, Ocean Chemistry and Ecosystem Dynamics (OCED) branch. This NERTO aligns with NOAA CSC’s goal of Resilient Coastal Communities and Economies through the theme of Oceans and Coasts. The NERTO deepened the intern’s understanding of NOAA’s research practices by giving me firsthand experience with the teamwork and dedication of a NOAA research team.

NOAA Seminar Series: Societal Data Insights: Data Integration for Inland Flooding.
2024-10-24 14:00 - 14:30
Title:Societal Data Insights: Data Integration for Inland Flooding.

Presenter(s): Isabel Lopez
Date: 24 October 2024 2:00 pm – 2:30 pm ET

Remote Access: Google Meet joining info
Video call link: https://meet.google.com/xsy-nupc-von
Or dial: (US) +1 234-276-0398PIN: 436 710 044#
More phone numbers: https://tel.meet/xsy-nupc-von?pin=2132911046548
About Speaker: Isabel Lopez
Abstract: Urban recurrent flooding presents a complex challenge distinct from nuisance flooding, typically associated with coastal areas. Unlike nuisance flooding, which is often predictable and localized, urban recurrent flooding involves adynamic interplay of factors such as dense infrastructure, varied land use, and heterogeneous topography. These elements contribute to unpredictable flood patterns that are more difficult to model and manage. The complexity of urban environments amplifies the challenges in assessing flood risks and potential impacts, necessitating a more sophisticated analytical approach. This research adapts the Topographic Wetness Index (TWI) to highlight areas prone to flooding based on flow direction and water accumulation. Additionally, it incorporates the Curve Number (CN) method to estimate runoff volumes from precipitation events, providing refined tools for measuring surface runoff and predicting flooding potential. Recognizing that urban flooding significantly impacts communities, this study integrates social data to capture the broader societal effects, particularly on vulnerable populations. The proposed framework is designed for flexibility, allowing its application across diverse urban areas with varying geographic and social characteristics. By combining geospatial analysis with social data, this research offers a comprehensive approach to flood risk assessment, providing valuable insights for policymakers and urban planners.The results are from the NOAA EPP/MSI CSC NERTO graduate internship project that was conducted with NOAA mentors Dr. Jonathon Mote and Dr. Kyle Metta of the Weather ProgramOffice (WPO) in Silver Spring, MD. The NERTO aligns with NOAA CSC CESSRST-II’s goal to understand changes in climate and weather and to share that knowledge and information with others. The NERTO project enhanced the intern’s ability to integrate social data with physical data, providing deeper insights into developing methods that combine social, weather, and climate data for more comprehensive analyses.

NOAA Seminar Series: Historical Data Reconstruction for the California Coastal Currents using 3D Empirical Orthogonal Functions and Multivariate Regression
2024-10-24 14:35 - 15:05
Title: Historical Data Reconstruction for the California Coastal Currents using 3D Empirical Orthogonal Functions and Multivariate Regression

Presenter(s): Danielle Lafarga,
Date: 24 October 2024 2:35 pm – 3:05 pm ET

Remote Access: Google Meet joining info
Video call link: https://meet.google.com/new-qbkh-azj
Or dial: (US) +1 440-482-5511 PIN: 303 375 204#
More phone numbers: https://tel.meet/new-qbkh-azj?pin=5643412593662
About Speaker: Danielle Lafarga,
Abstract: Many studies analyze ocean temperature variance, computing empirical orthogonal functions (EOFs) one layer at a time(2D). However, surface phenomena like El Nio extend into deeper layers, exemplifying how crucial it is to examine their three-dimensional structure to fully understand their impact. This research aims to compute 3D EOFs for different areas of the Pacific Ocean to answer how much and what variability can be explored across ocean layers using ahigh-resolution, eddy-resolving model known as the Global Ocean Physics Reanalysis (GLORYS). The model’s fine resolution allows for detailed analysis of smaller-scale dynamics, such as those along the coasts of California, Oaxaca, and Costa Rica. Nevertheless, the volume of data presents a memory challenge for 3D calculations. To address this, we propose an algorithm that enables 3D EOF computation on computers with limited memory (16GB RAM), making high-resolution analysis feasible.Computing 3D EOFs is crucial for understanding our oceans and how ocean dynamics can extend through multiple layers. This research aligns with NOAA’s mission to understand and predict changes in climate, weather, oceans, and coasts. By providing a more comprehensive view of ocean variability, the results also contribute valuable insights into the habitats of fish species protected by NOAA Fisheries, aiding in the preservation and management of marine ecosystems.The results are from the NOAA EPP/MSI CSC NERTO graduate internship project that was conducted with NOAA mentor, Dr. Michael Jacox of NOAA SWFSC Environmental Research Division, and NOAA collaborator Dr. Michael Alexander of NOAA Atmosphere Ocean Processes and Predictability (AOPP) Division. The NERTO aligns NOAA CSCCESSRST-II’s goal of to understand and predict changes in climate and weather. The NERTO project deepened the intern’s understanding of remote sensing technology, big data computing, and participation in NOAA mission-aligned activities through extensive collaborations with NOAA employees.

NOAA Seminar Series: Identifying local and synoptic-scale meteorological and land cover conditions favorable for the occurrence of large fires in California
2024-10-24 15:15 - 15:45
Title: Identifying local and synoptic-scale meteorological and land cover conditions favorable for the occurrence of large fires in California

Presenter(s): E’lysha Guerrero
Date: 24 October 2024 3:15 pm – 3:45 pm ET

Remote Access: Google Meet joining info
Video call link: https://meet.google.com/dft-obqy-fhb
Or dial: (US) +1 650-535-0909PIN: 928 542 289#
More phone numbers: https://tel.meet/dft-obqy-fhb?pin=5001908281383
About Speaker: E’lysha Guerrero,
Abstract: Whilst global warming projections lead to continuous warming trends and California wildfire activity is expected to increase, the state of wildfire predictions will need to be enhanced to keep up with the ever-changing climate conditions. This research project aims to characterize meteorological and land conditions related to large wildfires in California and identify their connection to predictable climate patterns, potentially enhancing future wildfire predictions. We utilize historical wildfire perimeter data (2000 “2022) and apply the K-means Clustering Algorithm on localized meteorological variables to group wildfires based on similar conditions. Larger-scale synoptic meteorology is analyzed to identify potential predictors for future wildfire occurrences. The research questions addressed during the NERTO are: (a) What are the local regional and seasonal characteristics of California’s historically larger wildfires from 2000 – 2022? and (b) What are the typical large-scale circulation patterns associated with each California clustered group?The value of this research lies in its contribution to NOAA’s mission to understand and predict climate and weather changes, specifically through advancing wildfire prediction capabilities. The insights gained can improve both prediction models and wildfire management strategies, supporting NOAA’s broader goal of mitigating the impacts of extreme weather and natural hazards. Additionally, the use of machine learning techniques, like K-means clustering, fosters innovation in predictive skills, aligning with the NOAA Physical Sciences Laboratory’s mission to develop new knowledge and tools for forecasting extreme events such as wildfires. The results are from the NOAA EPP/MSI CSC NERTO graduate internship project that was conducted with NOAA mentor Dr. Andrew Hoell, Dr. Rochelle Worsnop, and Dr. Melissa Breeden of NOAA Physical Sciences Laboratory, Boulder, CO. The NERTO aligns with NOAA CSC CESSRST-II’s goal to understand and predict changes in climate and weather. The NERTO project deepened the intern’s understanding and increased the research skill sets of data acquisition, preprocessing, analyses, and validation techniques required for earth system science research.

NOAA Seminar Series: Remote sensing of extreme weather events on CDOM in Long Island Sound
2024-10-25 13:30 - 14:00
Title: Remote sensing of extreme weather events on CDOM in Long Island Sound

Presenter(s): Charlotte Rhoads
Date: 25 October 2024 1:30 pm – 2:00 pm ET

Remote Access: Google Meet joining info
Video call link: https://meet.google.com/gnq-msir-wvj
Or dial: (US) +1 267-553-4621 PIN: 434 202 737#
More phone numbers: https://tel.meet/gnq-msir-wvj?pin=9872489736362

About Speaker: Charlotte Rhoads
Abstract: Coastal areas are critical in global carbon cycling, particularly as climate change alters carbon fluxes through rising temperatures, shifting precipitation patterns, and sea-level rise. These changes affect microbial activity, carbon remineralization, and transportation pathways, influencing the fate of carbon in coastal environments. Dissolved organic matter (DOM), sourced from land and sea, regulates ecosystem functioning, while colored dissolved organic matter (CDOM) acts as an optical proxy for tracking DOM dynamics. Extreme weather events modify DOM quantity and quality, impacting harmful algal blooms (HABs). In Long Island Sound (LIS), a eutrophic estuary, high-resolution satellite remote sensing, and regionally optimized algorithms enable monitoring of DOM and its response to extreme precipitation events. By analyzing CDOM’s optical properties, such as aCDOM(300),DOC, S275″295, and SR, changes in DOM can be linked to carbon cycling and water quality. Increased DOM flux during heavy rains drives dinoflagellate blooms, posing threats to water quality and aquaculture. Identifying CDOM optical signatures of harmful dinoflagellates like Prorocentrumcordatum and Margalefidinium polykrikoides may allow for monitoring via remote sensing. The results are from the NOAA EPP/MSI CSC NERTO graduate internship project that was conducted with NOAA mentors Veronica Lance and Jonathan Sherman of NESDIS and Gary Wilkfors and Lisa Guy of NOAA Fisheries. The NERTO aligns with NOAACSC CESSRST-II’s goal of providing actionable remote sensing-based research to stakeholders. The NERTO deepened the intern’s understanding of NOAA’s mission of managing and protecting coastal ecosystems and resources.

Climate Seminar Series: The Expanding Reach of Ocean Acidification
2024-11-14 12:00 - 13:00
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Event: NOAA EPP/MSI CSC Climate Change Seminar Series
Title: THE EXPANDING REACH OF OCEAN ACIDIFICATION
Presenter: Andrea Fassbender, OAR Pacific Marine Environment Lab (Hosted by CCME)
Date: November 14, 2024
Time: 12:00pm-1:00 PM
Register: Click here to register
After registering, you will receive a confirmation email with details to join the event
About the Seminar Series.
Join NOAA’s EPP/MSI Cooperative Science Centers for this lecture series featuring scientists from NOAA Fisheries and NOAA Research. These monthly seminars will be hosted by the lead institution, virtually or hybrid throughout the 2025-2025 academic year. For more information, please visit, https://research.noaa.gov/noaa-csc-24-25/

Climate Seminar Series: An overview of the Tropospheric Ozone Pollution Project
2024-12-05 12:00 - 13:00
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Event: NOAA EPP/MSI CSC Climate Change Seminar Series
Title: AN OVERVIEW OF THE TROPOSPHERIC OZONE POLLUTION PROJECT – USING BALLOON SONDES TO UNDERSTAND INFLUENCES ON AIR QUALITY
Presenter: Gary Morris, OAR Global Monitoring Lab (Hosted by CESSRST-II)
Date: December 5, 2024
Time: 12:00pm-1:00 PM
Register: Click here to register
After registering, you will receive a confirmation email with details to join the event
About the Seminar Series.
Join NOAA’s EPP/MSI Cooperative Science Centers for this lecture series featuring scientists from NOAA Fisheries and NOAA Research. These monthly seminars will be hosted by the lead institution, virtually or hybrid throughout the 2025-2025 academic year. For more information, please visit, https://research.noaa.gov/noaa-csc-24-25/

Climate Seminar Series: Sub seasonal to Seasonal Prediction of Extreme Events
2025-02-13 12:00 - 13:00
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Event: NOAA EPP/MSI CSC Climate Change Seminar Series
Title: SUBSEASONAL TO SEASONAL PREDICTION OF EXTREME EVENTS: ADVANCES AND CHALLENGES
Presenter: Mark Olsen, OAR Weather Program Office (Hosted by NCAS-M)
Date: February 13, 2025
Time: 12:00pm-1:00 PM
Register: Click here to register
After registering, you will receive a confirmation email with details to join the event
About the Seminar Series.
Join NOAA’s EPP/MSI Cooperative Science Centers for this lecture series featuring scientists from NOAA Fisheries and NOAA Research. These monthly seminars will be hosted by the lead institution, virtually or hybrid throughout the 2025-2025 academic year. For more information, please visit, https://research.noaa.gov/noaa-csc-24-25/

NOAA Seminar Series: Mapping Cumulative Impacts of Essential Fish Habitat Consultations in the Pacific Islands Region
2025-08-11 15:00 - 16:00
Title: Mapping Cumulative Impacts of Essential Fish Habitat Consultations in the Pacific Islands Region

Presenter(s): Amy Carrillo
Date: 11 August 2025, 3:00 pm – 4:00 pm ET

Remote Access: Google Meet joining info
Video call link: https://meet.google.com/prg-psrb-moa
About Speaker: Amy Carrillo
Abstract: The cumulative impacts of federally funded projects, reviewed by the Essential Fish Habitat (EFH) team, on EFH in the Pacific Islands region were visualized and evaluated. Using data from the Environmental Consultation Organizer (ECO), covering projects from 2017 to the present, interactive dashboards and a story map were created to visualize the spatial distribution and intensity of these projects across the region. Three tools were created, first a dashboard that displays all the EFH consultations as points covering the Pacific Island region to allow for visualization of project locations. Second, on Oahu, where each consultation action area is mapped as polygons, scored for adverse impacts on EFH, and supplemented with detailed information on the type of activity, impact level, and other relevant data. Finally, on Honolulu Harbor, presenting a story map of one of Oahu’s most heavily impacted and managed areas, which also hosts a large coral nursery. By processing over 500 project records and creating these tools, the project provides a comprehensive overview of the scale and impact of federal activities on EFH. The dashboards and story maps are designed to support decision-making by offering accessible tools for conservation efforts and the EFH team’s effective coastal resource management.

NOAA Seminar Series: Marine Heatwaves in the Tropical Atlantic: Detection, Characteristics, and Trends in a Warming Ocean.
2025-08-20 10:00 - 11:00
Title: Marine Heatwaves in the Tropical Atlantic: Detection, Characteristics, and Trends in a Warming Ocean.

Date: August 20, 2025, 10:00 am – 11:00 am ET

Presenter(s): Keneshia Hibbert, CESSRST-II Graduate Fellow

Remote Access: : https://meet.google.com/jyf-ojbj-wzn

Abstract: Marine heatwaves (MHWs) are prolonged periods of anomalously warm sea surface temperatures (SSTs) that can have profound ecological and climatic consequences. This study presents a comprehensive assessment of MHW characteristics across the tropical Atlantic Ocean from 1982to 2024, employing a consistent methodology based on the framework established by Hobday et al. (2016). Daily SST data were analyzed against a seasonally varying climatological 90th percentile threshold to detect MHW events and quantify key metrics, including event frequency, duration, and spatial extent. Our domain-level approach identifies and tracks contiguous periods of elevated SSTs across the entire basin, applying strict temporal criteria to ensure scientific robustness. Results reveal distinct seasonal and interannual variability in MHW occurrence, with several multi-week events observed during the boreal summer and fall months. The spatial extent of MHWs was found to fluctuate considerably over time, occasionally covering large portions of the tropical Atlantic Basin. These findings provide a critical foundation for understanding the temporal evolution and physical characteristics of marine heatwaves in a region of high climate sensitivity. This work lays the groundwork for future efforts to investigate the role of large-scale climate modes and anthropogenic warming in shaping the dynamics of MHW in the tropical Atlantic.

NOAA Seminar Series: Spatial Resolution Impacts on Remotely Sensed Product Uncertainty and Representativeness
2025-08-28 13:00 - 14:00
Title: Spatial Resolution Impacts on Remotely Sensed Product Uncertainty and Representativeness
Presenter(s): Biajani Gonzalez, CESSRST II Graduate Fellow
Google Meet : https://meet.google.com/ugm-keyg-pgr

Abstract: Satellite remote sensing, while providing broad geographic coverage, faces limitations in spatial resolution for detailed benthic mapping, particularly in coastal regions such as Puerto Rico. Small unmanned aerial systems (UAS) offer a promising solution due to their ability to capture high-resolution imagery with flexibility. This study examines the impact of spatial resolution and classifier training strategies on the accuracy and consistency of benthic habitat classifications derived from drone-based imagery. It determines the optimal airborne sampling parameters ” balancing effective spatial resolution and flight parameters ” when using UAS for marine habitat mapping. Using high-resolution RGB orthomosaics (0.036 m/pixel) collected via UAS and upscaled to coarser resolutions (0.5 m to 10 m), we assessed the classification performance of coral, sand, seagrass, and substrate using Support Vector Machine (SVM) classifiers under four case-study scenarios. Spatial metrics (total area, patch count) and accuracy assessment indicators (self-transition and Critical Success Index) were applied to quantify classification degradation across scales and scenes. Results show fine-scale features, especially coral and seagrass, rapidly degrade beyond 1 meter, while more homogeneous classes, such as sand and substrate, remain relatively stable.

NOAA Seminar Series: Quantifying the accuracy of satellite-observed sea surface salinity against in situ observations by saildrones
2025-09-26 14:30 - 15:00
Title: Quantifying the accuracy of satellite-observed sea surface salinity against in situ observations by saildrones
Presenter(s): Andrew Dixon, CESSRST II Graduate Fellow
Google Meet : https://meet.google.com/rxj-wgmk-day
Or dial: ‪(US) +1 318-367-3080 PIN: ‪865 081 511#

Abstract:
Sea surface salinity (SSS) regulates upper-ocean stratification, influencing vertical mixing and the heat exchange critical to the development of tropical cyclones. Satellite salinity observations from NASA’s SMAP observatory offer global coverage and have been validated for general conditions in certain areas, but benefit from validation under storm conditions. This study uses NOAA Saildrones (uncrewed surface vehicles), capable of targeting specific storms and collecting near-continuous data, to compare in situ SSS with two SMAP products. Results show strong agreement with the 8-day averaged dataset and moderate but positive agreement with the near-real-time product. Collocations during storm encounters indicate that SMAP could be useful in tropical cyclone forecasting. By validating satellite data with uncrewed systems, this work advances NOAA’s mission of enabling a weather-ready nation through expanded hurricane predictions and fostering collaborations for future satellite data validation projects.
The results are from the NOAA EPP/MSI CSCNERTO graduate internship project that was conducted with NOAA mentor, Dr. Chidong Zhang of NOAA Research’s Pacific Marine Environmental Laboratory. The NERTO aligns with NOAA CSC CESSRST-II’s goal of conducting NOAA mission-aligned collaborative research to understand and predict changes in climate, weather, oceans, and coasts. The NERTO “Quantifying the accuracy of satellite observed sea surface salinity against in situ observations by Saildrones” also deepened the intern’s understanding of NOAA’s databases and development steps toward further use of uncrewed systems.
