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X-ORIGINAL-URL:https://www.cessrst.org
X-WR-CALDESC:Events for NOAA Center for Earth System Sciences and Remote Sensing Technologies
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250322T153000
DTEND;TZID=America/New_York:20250322T170000
DTSTAMP:20260404T051814
CREATED:20250310T171531Z
LAST-MODIFIED:20250710T171650Z
UID:5512-1742657400-1742662800@www.cessrst.org
SUMMARY:Seminar: Data Science Techniques and Climate Science
DESCRIPTION:Seminar: Data Science Techniques and Climate Science\n\nDate: March 22\, 2025 at 3pm\nBy:  Douglas Rao\, PhD \nNorth Carolina State University\nCooperative Institute for Satellite Earth System Studies (CISESS)\nNOAA National Centers for Environmental Information\n\n\nMicrosoft Teams Need help?\n\nJoin the meeting now\nMeeting ID: 297 638 988 331\nPasscode: Xf2L3U5T
URL:https://www.cessrst.org/event/seminar-data-science-techniques-and-climate-science/
CATEGORIES:Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250401T150000
DTEND;TZID=America/New_York:20250401T170000
DTSTAMP:20260404T051814
CREATED:20250321T120726Z
LAST-MODIFIED:20250328T145614Z
UID:5433-1743519600-1743526800@www.cessrst.org
SUMMARY:Seminar on Air Quality Modeling & Role of Clouds in Atmospheric Composition
DESCRIPTION:Seminar on Air Quality Modeling and Forecasting & Role Clouds play in Affecting Atmospheric Composition \nDownload Flyer \nDate: April 1\, 2025 from 3pm – 5pm \nPresenter(s):  Rajesh Kumar\,  Deputy Director\, Research Application Lab\, NSF NCAR and  Mary Barth \, Senior Scientist\, NSF NCAR \nZoom: https://ccny.zoom.us/j/84211573613?pwd=oKXF3GDMatUta9weRD3zTkKXLRjWqH.1 \nAbstracts: \nAir Quality Modeling and Forecasting \nAir quality science emerged out of the societal need to mitigate health effects of deadly smog events that occurred in North America and\nEurope around the middle of 20th century. In the past 70 years\, atmospheric chemistry has advanced so much that we are now capable of\npredicting air quality in both the short-term (1-3 days) and long-term (climate time scales) and assessing the implications of air pollution for\npublic health and food security. Dr. Kumar will provide a very high-level historical overview of air quality research followed by fundamentals of\nair quality modeling\, development of an air quality forecasting system for New Delhi\, and conclude with the future of atmospheric\nchemistry modeling at NSF NCAR \nRole Clouds play in Affecting Atmospheric Composition \nThe Earth’s atmosphere is composed of gases and aerosol particles that affect air quality\, atmospheric radiation\, and cloud properties\, impacting climate and weather. Clouds\, which cover ~60% of the globe at any given time\, affect the concentrations of trace gases and aerosols within the atmosphere in many ways\, including vertical transport to higher altitudes\, removal via precipitation\, and cloud chemistry. This talk will review our current understanding of how clouds affect trace gas and aerosol concentrations using data collected in and near thunderstorms during two aircraft field campaigns. The presentation illustrates the value of combining atmospheric chemistry models with observations to advance our understanding of the atmosphere \n 
URL:https://www.cessrst.org/event/seminar-on-air-quality-modeling-role-of-clouds-in-atmospheric-composition/
LOCATION:Grove School of Engineering\, 160 Convent Avenue\, New York\, NY\, 10031\, United States
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=image/png:https://www.cessrst.org/wp-content/uploads/2025/03/NCAR-Seminar-04-01-2025.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250408T043000
DTEND;TZID=America/New_York:20250410T133000
DTSTAMP:20260404T051814
CREATED:20250320T135208Z
LAST-MODIFIED:20250320T135208Z
UID:5417-1744086600-1744291800@www.cessrst.org
SUMMARY:Third CESSRST II Annual Meeting
DESCRIPTION:Third Annual CESSRST-II Meeting \nDate: April 8-10\, 2025 \nTime: 8:30AM ET \nVenue: NOAA/NCWCP\, College Park\, MD \nMeeting Objects and Expected Outcomes \n\nTo share the Center’s 5 year plan and year 3 updates\nTo create better collaborations and connection between CESSRST Scientist and NOAA Collaborators and Subject Matter Experts (SMEs)
URL:https://www.cessrst.org/event/third-cessrst-ii-annual-meeting/
LOCATION:NOAA Center for Weather and Climate Prediction (NCWCP)\, 5830 University Research Ct\, College Park\, MD\, 20740\, United States
CATEGORIES:Conference/Symposium
ATTACH;FMTTYPE=image/png:https://www.cessrst.org/wp-content/uploads/2023/02/logo-htext-sm.png
ORGANIZER;CN="Center for Earth System Sciences and Remote Sensing Technologies (CESSRST)":MAILTO:cessrst@ccny.cuny.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250422T150000
DTEND;TZID=America/New_York:20250422T170000
DTSTAMP:20260404T051814
CREATED:20250410T171301Z
LAST-MODIFIED:20250710T171746Z
UID:5510-1745334000-1745341200@www.cessrst.org
SUMMARY:Seminar: AI Weather Prediction Models Developed in the Private Sector and explored at NOAA
DESCRIPTION:Seminar:  AI Weather Prediction Models Developed in the Private Sector and explored at NOAA\n\nDate: April 22\, 2025 at 3pm\n\nBy:  Jacob Radford\, PhD \nResearch Scientist\nCooperative Institute for Research in the Atmosphere\n\nJoin the meeting now\n\n\nMeeting ID: 297 638 988 331 \n\n\nPasscode: Xf2L3U5T \n\n\n\n\n\n\n\nDial in by phone \n\n\n+1 206-785-9984\,\,783676980# United States\, Seattle \n\n\nFind a local number \n\n\nPhone conference ID: 783 676 980#
URL:https://www.cessrst.org/event/seminar-ai-weather-prediction-models-developed-in-the-private-sector-and-explored-at-noaa/
CATEGORIES:Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250425T133000
DTEND;TZID=America/New_York:20250425T163000
DTSTAMP:20260404T051814
CREATED:20250403T131421Z
LAST-MODIFIED:20250603T131651Z
UID:5489-1745587800-1745598600@www.cessrst.org
SUMMARY:Seminar: Economics Applications and the NOAA Mission Enterprise
DESCRIPTION:Join us for one of our social science seminars: Economics in the NOAA Mission Enterprise\, \, featuring CESSRST-II Faculty Member\, Dr. Yusuke Kuwayama (UMBC) and Senior Economist at NOAA\, Joe Conran.  \nThis seminar will take place on Friday\, April 25th\, 2025 from 1:30-4pm EST- REGISTRATION REQUIRED.
URL:https://www.cessrst.org/event/seminar-economics-applications-and-the-noaa-mission-enterprise/
CATEGORIES:Seminar Series,Workshop
ATTACH;FMTTYPE=image/jpeg:https://www.cessrst.org/wp-content/uploads/2025/06/Economics-Workshop-042025.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250501T150000
DTEND;TZID=America/New_York:20250501T170000
DTSTAMP:20260404T051814
CREATED:20250410T170922Z
LAST-MODIFIED:20250710T171215Z
UID:5508-1746111600-1746118800@www.cessrst.org
SUMMARY:Seminar: Statistical Methods used in Social Sciences
DESCRIPTION:Seminar: Statistical Methods used in Social Sciences\n\nDate: May 1\, 2025 at 3pm\nBy: Cassandra Shivers-Williams\, PhD\nSocial Science Deputy Program Manager\nNOAA Weather Program Office\n\nMicrosoft Teams Need help?\nJoin the meeting now\nMeeting ID: 297 638 988 331\nPasscode: Xf2L3U5T\n\n\n\nDial in by phone\n+1 206-785-9984\,\,783676980# United States\, Seattle\nFind a local number\nPhone conference ID: 783 676 980#\nJoin on a video conferencing device\nTenant key: howard@m.webex.com\nVideo ID: 115 646 114 7\nMore info
URL:https://www.cessrst.org/event/seminar-statistical-methods-used-in-social-sciences/
CATEGORIES:Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250516T130000
DTEND;TZID=America/New_York:20250516T150000
DTSTAMP:20260404T051814
CREATED:20250503T131934Z
LAST-MODIFIED:20250603T133153Z
UID:5492-1747400400-1747407600@www.cessrst.org
SUMMARY:Seminar: Data Science and Stewardship at NOAA’s National Centers for Environmental Information (NCEI)
DESCRIPTION:Data Science and Stewardship at NOAA’s National Centers for Environmental Information (NCEI) Seminar. \n Description: This seminar will highlight how NOAA’s NCEI applies data science to safeguard and make environmental data accessible. You will explore how technologies like cloud storage\, smart search systems\, and organized data management empower researchers and the public to utilize environmental data for research and decision-making. See flyer for other details. \nREGISTER 
URL:https://www.cessrst.org/event/seminar-data-science-and-stewardship-at-noaas-national-centers-for-environmental-information-ncei/
CATEGORIES:Seminar Series,Workshop
ATTACH;FMTTYPE=image/jpeg:https://www.cessrst.org/wp-content/uploads/2025/06/Data-Stewardship-Seminar.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20250601
DTEND;VALUE=DATE:20250607
DTSTAMP:20260404T051814
CREATED:20250123T134555Z
LAST-MODIFIED:20250130T135616Z
UID:5332-1748736000-1749254399@www.cessrst.org
SUMMARY:2025 AMS Science Policy Colloquium
DESCRIPTION:The registration is open for the 2025 Science Policy Colloquium (www.ametsoc.org/spc)\, which will occur from June 1-6\, 2025 in Washington\, DC.  \nThe Colloquium is a career-shaping experience. Alumni have gone on to serve in crucial roles for the nation and the scientific community such as working in congress and at the highest levels of leadership in the National Weather Service\, the Office of Science and Technology Policy (OSTP)\, the National Science Foundation\, the U.S. Global Change Research Program (USGCRP)\, and the American Meteorological Society\, to name only a few. \n\n\n\nThe Science Policy Colloquium is an intensive immersion in policy for Earth and environmental system scientists and professionals. Registration is open to all (see details here) but will be limited to no more than 45 individuals and will be based on the order received. \nA limited amount of funding is available to support\, through a national competition\, participation of graduate students\, postdocs\, and early-career faculty. Applications for support are due March 1\, 2025.
URL:https://www.cessrst.org/event/2025-ams-science-policy-colloquium/
CATEGORIES:Conference/Symposium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250710T120000
DTEND;TZID=America/New_York:20250710T130000
DTSTAMP:20260404T051814
CREATED:20250701T132522Z
LAST-MODIFIED:20251117T142606Z
UID:5672-1752148800-1752152400@www.cessrst.org
SUMMARY:Social Science Community of Practice Meeting  (CoP)
DESCRIPTION:[vc_row][vc_column][vc_column_text css=””]CESSRT-II Social Science Meeting:  Student Cohort Community of Practice Meeting \nSocial science community of practice meeting. \nDate:  July 10\, 2025  at 12p\,[/vc_column_text][/vc_column][/vc_row]
URL:https://www.cessrst.org/event/social-science-community-of-practice-meeting-cop-3/
CATEGORIES:Informational Webinar
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20250729
DTEND;VALUE=DATE:20250802
DTSTAMP:20260404T051814
CREATED:20250630T201308Z
LAST-MODIFIED:20250728T124029Z
UID:5499-1753747200-1754092799@www.cessrst.org
SUMMARY:Third Annual CESSRST-II Symposium
DESCRIPTION:The Symposium provides a forum for students\, faculty\, and the community to discuss cutting edge remote sensing research  topics and to examine the connection between research and education. \n\nDownload Symposium Program\n\nThis year's symposium will feature \n- Workshop on Generative AI\,  Prompt Engineering and research\n-  Introduction to ArcGIS \n- Citizen Science day\n- Annual Cohort Experience\n\n\nDates:  Monday\, July 29 – Thursday\, August 1\, 2025 \n\n 
URL:https://www.cessrst.org/event/third-annual-cessrst-ii-symposium/
CATEGORIES:Conference/Symposium
ORGANIZER;CN="Center for Earth System Sciences and Remote Sensing Technologies (CESSRST)":MAILTO:cessrst@ccny.cuny.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250811T150000
DTEND;TZID=America/New_York:20250811T160000
DTSTAMP:20260404T051814
CREATED:20250801T160221Z
LAST-MODIFIED:20250807T160452Z
UID:5548-1754924400-1754928000@www.cessrst.org
SUMMARY:NOAA Seminar Series: Mapping Cumulative Impacts of Essential Fish Habitat Consultations in the Pacific Islands Region
DESCRIPTION:Title: Mapping Cumulative Impacts of Essential Fish Habitat Consultations in the Pacific Islands Region\n \nPresenter(s):  Amy Carrillo \nDate: 11 August 2025\, 3:00 pm – 4:00 pm ET\n \nRemote Access: Google Meet joining info \nVideo call link: https://meet.google.com/prg-psrb-moa \nAbout Speaker:  Amy Carrillo \nAbstract: 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.
URL:https://www.cessrst.org/event/noaa-seminar-series-mapping-cumulative-impacts-of-essential-fish-habitat-consultations-in-the-pacific-islands-region/
CATEGORIES:NOAA Seminar Series,Seminar Series
ORGANIZER;CN="Center for Earth System Sciences and Remote Sensing Technologies (CESSRST)":MAILTO:cessrst@ccny.cuny.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250820T100000
DTEND;TZID=America/New_York:20250820T110000
DTSTAMP:20260404T051814
CREATED:20250801T160655Z
LAST-MODIFIED:20250807T160844Z
UID:5550-1755684000-1755687600@www.cessrst.org
SUMMARY:NOAA Seminar Series: Marine Heatwaves in the Tropical Atlantic: Detection\, Characteristics\, and Trends in a Warming Ocean.
DESCRIPTION:Title: Marine Heatwaves in the Tropical Atlantic: Detection\, Characteristics\, and Trends in a Warming Ocean.\n \nDate:  August 20\, 2025\, 10:00 am – 11:00 am ET\n \nPresenter(s): Keneshia Hibbert\, CESSRST-II Graduate Fellow\n\nRemote Access: : https://meet.google.com/jyf-ojbj-wzn\n\nAbstract: 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.
URL:https://www.cessrst.org/event/noaa-seminar-series-marine-heatwaves-in-the-tropical-atlantic-detection-characteristics-and-trends-in-a-warming-ocean/
CATEGORIES:NOAA Seminar Series,Seminar Series
ORGANIZER;CN="Center for Earth System Sciences and Remote Sensing Technologies (CESSRST)":MAILTO:cessrst@ccny.cuny.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250828T130000
DTEND;TZID=America/New_York:20250828T140000
DTSTAMP:20260404T051814
CREATED:20250807T162057Z
LAST-MODIFIED:20250807T162057Z
UID:5552-1756386000-1756389600@www.cessrst.org
SUMMARY:NOAA Seminar Series: Spatial Resolution Impacts on Remotely Sensed Product Uncertainty and Representativeness
DESCRIPTION:Title: Spatial Resolution Impacts on Remotely Sensed Product Uncertainty and Representativeness \nPresenter(s): Biajani Gonzalez\, CESSRST II Graduate Fellow  \nGoogle Meet :  https://meet.google.com/ugm-keyg-pgr\n\nAbstract: 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. 
URL:https://www.cessrst.org/event/noaa-seminar-series-spatial-resolution-impacts-on-remotely-sensed-product-uncertainty-and-representativeness/
CATEGORIES:NOAA Seminar Series,Seminar Series
ORGANIZER;CN="Center for Earth System Sciences and Remote Sensing Technologies (CESSRST)":MAILTO:cessrst@ccny.cuny.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250916T090000
DTEND;TZID=America/New_York:20250917T163000
DTSTAMP:20260404T051814
CREATED:20250711T143524Z
LAST-MODIFIED:20250911T143752Z
UID:5576-1758013200-1758126600@www.cessrst.org
SUMMARY:7th NOAA AI Workshop
DESCRIPTION:[vc_row][vc_column][vc_column_text css=””]\n\n\n\n\n7th NOAA AI Hybrid Workshop – Generative AI for Earth and Space Science Applications\n\n\n\n\n\n\n\n\n\n\n\nThe hybrid workshop will take place from September 16-17\, 2025 at UCAR/NCAR Center Green Campus with virtual connection via Zoom. See below for the workshop agenda. \nTo Register\, please visit the events page \n\n\n\n\n\n\n\n[/vc_column_text][/vc_column][/vc_row]
URL:https://www.cessrst.org/event/7th-noaa-ai-workshop/
CATEGORIES:Workshop
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250926T120000
DTEND;TZID=America/New_York:20250926T130000
DTSTAMP:20260404T051814
CREATED:20250916T202547Z
LAST-MODIFIED:20250916T210643Z
UID:5584-1758888000-1758891600@www.cessrst.org
SUMMARY:Seminar on the 2025 Joint Center Research and Development Project (JCRDP)
DESCRIPTION:[vc_row][vc_column][vc_column_text css=””]Seminar on The 2025 Joint Center Research and Development Project (JCRDP) – Training\, Dry Run & Intensive Observation Period \nDownload Flyer \nDate: September 26\, 2025 from 12pm \nPresenter(s): Dr.  Sen Chiao\, Director of the NOAA Cooperative Science Center in Atmospheric Sciences and Meteorology (NCAS-M) and a Professor of Interdisciplinary Studies at Howard University \nZoom: https://ccny.zoom.us/j/84211573613?pwd=oKXF3GDMatUta9weRD3zTkKXLRjWqH.1 \nAbstract: \nUrban boundary layer dynamics and composition research is an area of overlapping capability and expertise for the two Cooperative Science Centers (CSCs)\, NOAA Center for Earth System Sciences and Remote Sensing Technologies (CESSRST) and NOAA\nCenter for Atmospheric Sciences and Meteorology (NCAS-M). The two Centers have engaged with NOAA NESDIS and NWS\, as well as NOAA Research (NOAA/OAR)\, to design a joint Collaborative Research and Development Project JCRDP with a focus on\ninterdisciplinary research and training on urban meteorology\, air quality\, urban ecosystems\, and communities. This effort brings together the two Centers’ expertise in analysis\, modeling\, and observation capabilities to build a framework to study air\npollution causes and impact in the northeast corridor. \nAbout Presenter: \nSen Chiao is the Director of the NOAA Cooperative Science Center in Atmospheric Sciences and Meteorology (NCAS-M) and a Professor of Interdisciplinary Studies at Howard University. NCAS-M is a research-through-education enterprise led by Howard University and includes seven partner institutions. Before coming to Howard University\, Sen served as the Meteorology and Climate Science department chair at San Jose State University.  His current research work and interests include data analysis and numerical modeling\, with emphasis on mesoscale modeling.[/vc_column_text][/vc_column][/vc_row]
URL:https://www.cessrst.org/event/seminar-on-the-2025-joint-center-research-and-development-project-jcrdp/
LOCATION:Grove School of Engineering\, 160 Convent Avenue\, New York\, NY\, 10031\, United States
CATEGORIES:Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250926T143000
DTEND;TZID=America/New_York:20250926T150000
DTSTAMP:20260404T051814
CREATED:20250816T130848Z
LAST-MODIFIED:20250918T203051Z
UID:5580-1758897000-1758898800@www.cessrst.org
SUMMARY:NOAA Seminar Series: Quantifying the accuracy of satellite-observed sea surface salinity against in situ observations by saildrones
DESCRIPTION:[vc_row][vc_column][vc_column_text css=””]\n\n\nTitle: Quantifying the accuracy of satellite-observed sea surface salinity against in situ observations by saildrones \nPresenter(s): Andrew Dixon\, CESSRST II Graduate Fellow  \nGoogle Meet : https://meet.google.com/rxj-wgmk-day \nOr dial: ‪(US) +1 318-367-3080 PIN: ‪865 081 511# \n\nAbstract:  \nSea 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. \nThe 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. \n\n\n[/vc_column_text][/vc_column][/vc_row]
URL:https://www.cessrst.org/event/noaa-seminar-series-quantifying-the-accuracy-of-satellite-observed-sea-surface-salinity-against-in-situ-observations-by-saildrones/
CATEGORIES:NOAA Seminar Series,Seminar Series
ORGANIZER;CN="Center for Earth System Sciences and Remote Sensing Technologies (CESSRST)":MAILTO:cessrst@ccny.cuny.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251003T120000
DTEND;TZID=America/New_York:20251003T130000
DTSTAMP:20260404T051814
CREATED:20250917T131958Z
LAST-MODIFIED:20251117T142202Z
UID:5668-1759492800-1759496400@www.cessrst.org
SUMMARY:Social Science Community of Practice Meeting  (CoP)
DESCRIPTION:[vc_row][vc_column][vc_column_text css=””]CESSRT-II Social Science Meeting:  Student Cohort Community of Practice Meeting \nSocial science community of practice meeting. \nDate:  October 3\, 2025  at 2pm\, \nDownoad Flyer[/vc_column_text][/vc_column][/vc_row]
URL:https://www.cessrst.org/event/social-science-community-of-practice-meeting-cop-2/
CATEGORIES:Informational Webinar
ATTACH;FMTTYPE=image/jpeg:https://www.cessrst.org/wp-content/uploads/2025/11/Cop-10-21-2025.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251023T133000
DTEND;TZID=America/New_York:20251023T143000
DTSTAMP:20260404T051814
CREATED:20251001T130024Z
LAST-MODIFIED:20251117T141329Z
UID:5656-1761226200-1761229800@www.cessrst.org
SUMMARY:CSC Education Experts’ Seminar Series: Alumni Career Panel
DESCRIPTION:[vc_row][vc_column][vc_column_text css=””]\nPlease join the Education Experts’ Seminar Series on Thursday\, October 23\, 2024\, for a NOAA EPP/MSI Cooperative Science Center (CSC) Alumni Career Panel (flyer is attached). The purpose of this panel is to showcase career pathways that align with NOAA’s mission\, beyond traditional NOAA federal employment. Panelists who are alumni from CSCs\, including CESSRST\, will discuss: \n\nTheir career journey since completing the EPP/MSI CSC program\nHow their current role contributes to NOAA’s mission\nInsights into navigating career decisions and building professional networks\nAdvice for Fellows exploring non-federal career options\n\n Please be sure to engage with your questions. Also\, please remember to: \n\nAppropriately introduce yourself before engaging verbally or in the chat (Name\, Identify yourself as a CESSRST-II fellow\, Identify your cohort number\, and your institution)\nUse the CESSRST-II Virtual Background (You may download the background appropriate to your institution from this folder)\n\nMeeting details: \nhttps://ccny.zoom.us/j/88623680869?pwd=uT3NCkeqB2jPwZzxMGbknPa61wBkpu.1 \nMeeting ID: 886 2368 0869 \nPasscode: 196466[/vc_column_text][/vc_column][/vc_row]
URL:https://www.cessrst.org/event/csc-education-experts-seminar-series-aluni-career-panel/
CATEGORIES:Informational Webinar,Seminar Series
ATTACH;FMTTYPE=image/png:https://www.cessrst.org/wp-content/uploads/2025/11/EESS_Fall-2025-ALUMNI-CAREER-PANEL.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251024T130000
DTEND;TZID=America/New_York:20251024T143000
DTSTAMP:20260404T051814
CREATED:20251005T130602Z
LAST-MODIFIED:20251117T140802Z
UID:5660-1761310800-1761316200@www.cessrst.org
SUMMARY:Write it Right Workshop: Using MS Word Strategically for CESSRST-II Reporting
DESCRIPTION:[vc_row][vc_column][vc_column_text css=””]Description: Effective use of Microsoft Word is essential for producing professional-quality reports\, manuscripts\, and academic documents. In addition to your academic work\, your CESSRST-II fellowship requires several types reports that need to meet professional standards. This workshop will provide a practical guide on leveraging MS Word’s advanced features to enhance the clarity\, consistency\, and impact of written work. Fellows will learn how to organize documents using structured headings\, apply automatic formatting styles\, and create well-formatted tables with appropriate captions and cross-references for figures and tables. This workshop will focus on reporting for the post NOAA Experiential Research and Training Opportunities (NERTO) report that is required by the NOAA EPP/MSI Program. It will review crafting clear and concise abstracts\, and managing citations and references using Word’s built-in tools and external citation managers such as Mendeley. Emphasis will be placed on maintaining uniform document styles\, integrating visuals effectively\, and adhering to academic writing conventions.  By the end of this session\, attendees will be equipped with the knowledge and skills to efficiently draft\, format\, and finalize the post NERTO report. \n Who should attend? \n\nFellows who have recently completed a NERTO and are in the feedback phase with the Center before making the finalized submission\, and\nFellows who plan to complete a NERTO or NOAA Undergraduate Research Internship (NURI) by August 2026\n\n Facilitators: Dr. Tarendra Lakhankar\, Center Research Coordinator  \nFormat: https://ccny.zoom.us/j/83921420413?pwd=cLp9Qit6AAbV4nFQwRjOEpwmDafctd.1 \nMeeting ID: 839 2142 0413 \nPasscode: 840266 \n [/vc_column_text][/vc_column][/vc_row]
URL:https://www.cessrst.org/event/write-it-right-workshop-using-ms-word-strategically-for-cessrst-ii-reporting/
LOCATION:City College of New York\, 160 Convent Avenue\, New York\, 10031
CATEGORIES:Informational Webinar,Workshop
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251028T123000
DTEND;TZID=America/New_York:20251028T133000
DTSTAMP:20260404T051814
CREATED:20251017T164144Z
LAST-MODIFIED:20251020T173707Z
UID:5630-1761654600-1761658200@www.cessrst.org
SUMMARY:Seminar on Characterizing the Dust Storm: An Integrated Ground-Based\, Satellite\, and Model Study
DESCRIPTION:[vc_row][vc_column width=”5/6″][vc_column_text css=””]Seminar on Characterizing the ‘Godzilla’ Dust Storm: An Integrated Ground-Based\, Satellite\, and Model Study to Advance our Understanding of the Impact of African Dust on the Tropical Western Hemisphere \nDownload Flyer \nDate: October 28\, 2025 from 12:30pm \nLocation: Exhibit Room\, Steinman Hall\, Grove School of Engineering \nPresenter(s): Dr.  Olga L. Mayo-Bracero\, Atmospheric Scientist\, Brookhaven National Laboratory \nZoom: https://ccny.zoom.us/j/85976950243?pwd=D8N0Lyv26rAwLTzcKWeBHfXNeEk1Zw.1[/vc_column_text][/vc_column][vc_column width=”1/6″][vc_single_image image=”5635″ css=””][/vc_column][/vc_row][vc_row][vc_column][vc_column_text css=””]Abstract: \nAfrican dust transport across the Atlantic significantly impacts air quality\, weather\, and climate in the Caribbean and surrounding regions. However\, gaps remain in understanding the intensity\, variability\, and health effects of these huge aerosol events. Addressing these uncertainties requires a comprehensive approach that combines multiple observational and modeling techniques to track dust movement and assess its impacts effectively. Long-term research and monitoring efforts in the Caribbean have been instrumental in improving our understanding of African dust transport and its regional consequences. \nThe unprecedented June 2020 “Godzilla” African dust event provided a unique opportunity to evaluate the effectiveness of an integrated approach using ground-based aerosol measurements\, satellite observations\, and forecast models. The NASA-funded CALIMA campaign built on prior research efforts\, integrating data from nine Caribbean locations\, satellite sensors (CALIOP\, MODIS\, MISR)\, and dust forecast models (NASA GEOS\, WRF-Chem) to characterize dust transport and its impact on air quality. Surface and columnar measurements revealed severe air quality degradation across the Caribbean\, southern United States\, northern South America\, and Central America\, posing significant public health risks. Model evaluations exposed substantial discrepancies in dust forecasts\, highlighting the need for improved prediction capabilities. \nThis study demonstrates the value of combining observational networks with satellite remote sensing and modeling to characterize the spatial and temporal variability of African dust transport to the western hemisphere. Strengthening such coordinated efforts is essential to refine forecasts\, mitigate health and environmental risks\, and better understand how transatlantic dust transport may evolve under a changing climate. \nAbout Presenter: \nDr. Olga L. Mayol-Bracero is an atmospheric scientist and the Lead of the Aerosol Observations Group in the Environmental Science and Technologies Department at Brookhaven National Laboratory (BNL)\, where she also serves as the Director of the Center for Aerosol Measurement Science (CAMS). She is the Lead Mentor of the Aerosol Observing Systems (AOS) of the DOE Atmospheric Radiation Measurement (ARM) User Facility and a participant in the DOE Atmospheric System Research (ASR) program. She joined BNL in August 2021.   Before joining BNL\, Dr. Mayol-Bracero was a Full Professor in the Department of Environmental Science at the University of Puerto Rico–Río Piedras (UPR-RP). There\, she directed the Atmospheric Chemistry and Aerosols Research Group and led both the Cape San Juan Atmospheric Observatory—a site that is part of NOAA ESRL’s aerosol network\, NASA’s AERONET\, Pandora\, and MPLNET networks\, and a WMO GAW regional station—and the Pico del Este Cloud Forest Station. \nDr. Mayol-Bracero’s research focuses on the temporal and spatial variability of atmospheric aerosols\, including the characterization of African dust\, biomass burning\, marine\, urban\, and biogenic aerosols\, with particular emphasis on tropical regions. Her expertise spans size-resolved aerosol composition and sources\, carbonaceous aerosols (organic and black carbon)\, aerosol–cloud–precipitation interactions\, and air quality. \nShe has extensive experience leading aerosol field projects and managing field atmospheric observatories\, participating in numerous ground-based and airborne field campaigns across diverse environments\, including the Maldives\, the Amazon Basin\, and the Caribbean region. Dr. Mayol-Bracero also holds several international leadership roles\, serving as a member of the International Commission on Atmospheric Chemistry and Global Pollution (iCACGP)\, the World Meteorological Organization’s Scientific Advisory Group on Aerosols\, and the Americas Working Group of the International Global Atmospheric Chemistry (IGAC) project. She is the author of more than 60 peer-reviewed publications\, one book chapter\, and over 300 presentations at national and international conferences. Dr. Mayol-Bracero earned her B.S. and M.S. in Chemistry and her Ph.D. in Chemistry from the University of Puerto Rico–Río Piedras and the Lawrence Berkeley National Laboratory. She completed her postdoctoral fellowship at the Max Planck Institute for Chemistry in Mainz\, Germany.[/vc_column_text][/vc_column][/vc_row]
URL:https://www.cessrst.org/event/seminar-on-characterizing-the-dust-storm-an-integrated-ground-based-satellite-and-model-study-to-advance-our-understanding-of-the-impact-of-african-dust-on-the-tropical-western-hemisphere/
LOCATION:Grove School of Engineering\, 160 Convent Avenue\, New York\, NY\, 10031\, United States
CATEGORIES:Seminar Series
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251119T130000
DTEND;TZID=America/New_York:20251119T143000
DTSTAMP:20260404T051814
CREATED:20251101T131344Z
LAST-MODIFIED:20251117T141715Z
UID:5662-1763557200-1763562600@www.cessrst.org
SUMMARY:CSC Education Experts’ Seminar Series: Connecting Minds - AI insights for CSC Fellows
DESCRIPTION:[vc_row][vc_column][vc_column_text css=””]\nPlease join next week’s Education Experts’ Seminar Series (EESS) session titled “Connecting Minds – AI insights for CSC Fellows” with presentations from Dr. Luke Madaus (Research Science\, RWE AI Lab) and Dr.  David Die\, (DRS at LMRCSC) \nDownload Flyer for Speaker information. \n Meeting Information: \n\nZoom Link\nMeeting ID: 867 5670 9117\nPasscode: 348968\n\n[/vc_column_text][/vc_column][/vc_row]
URL:https://www.cessrst.org/event/csc-education-experts-seminar-series-connecting-minds-ai-insights-for-csc-fellows/
CATEGORIES:Informational Webinar,Seminar Series
ATTACH;FMTTYPE=image/jpeg:https://www.cessrst.org/wp-content/uploads/2025/11/EE-Seminar-Nov-19.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251121T140000
DTEND;TZID=America/New_York:20251121T143000
DTSTAMP:20260404T051814
CREATED:20251118T221001Z
LAST-MODIFIED:20251119T221323Z
UID:5689-1763733600-1763735400@www.cessrst.org
SUMMARY:NOAA Seminar Series: Species distribution models of deep-sea coral and sponge(DSCS)species of the northeast continental shelf (USA)
DESCRIPTION:[vc_row][vc_column][vc_column_text css=””]\n\nTitle:  Species distribution models of deep-sea coral and sponge(DSCS)species of the northeast continental shelf (USA) \nPresenter(s): James Herlan\, CESSRST II Graduate Fellow  \nRemote Access: Video call link: https://meet.google.com/wde-shmw-vcw\nOr dial: (US)+1 435-562-1268 PIN: 906485 620\n\n#More phone numbers: https://tel.meet/wde-shmw-vcw?pin=3526342705011 \nAbstract: Deep-sea coral distributions in the Northwest Atlantic remain poorly characterized due to sampling limitations. We developed species distribution models (SDMs) for the cold-water coral Desmophyllum dianthus using generalized additive models (GAMs) to identify key environmental drivers and predict suitable habitat. We analyzed 81\,112 presence-absence records from multiple research cruises\, evaluating 28 environmental predictors through variance inflation factor (VIF) screening and univariate assessment. The final model incorporated depth\, rugosity index (rie)\, slope (qslp)\, and bottom total alkalinity (btm_talk_ann) as smoothed terms\, with and without spatial coordinates. Model performance was strong (AUC = 0.878 with location\, 0.849without)\, with 26.0% deviance explained. D. dianthus showed a unimodal depth response peaking at 500 ” 700 m\, positive associations with seafloor rugosity and slope\, and a narrow alkalinity optimum (2.400 ” 2.405 mol m-3). Spatial structure accounted for 18.5% of explained deviance\, suggesting unmeasured environmental gradients or dispersal limitations contribute moderately to distribution patterns. The 4.8 percentage point deviance improvement and 0.029AUC increase when including spatial terms demonstrates the value of incorporating geographic structure in deep-sea SDMs\, though environmental predictors remain primary drivers. Our results provide critical baseline information for conservation planning and highlight the importance of topographic complexity and oceanographic conditions in determining cold-water coral distributions. The results are from the NOAA EPP/MSI CSC NERTO graduate internship project\, which was conducted under the guidance of NOAA mentor James Vasslides of James J. Howard Marine Sciences Laboratory at Sandy Hook. The NERTO aligns with NOAA CSC Center for Earth System Sciences and Remote Sensing Technologies (CESSRST-II) award’s goal of becoming a scientist. The NERTO also deepened the intern’s understanding of multiple modeling approaches that include generalized linear models (GLMs)\, generalized additive models(GAMs)\, boosted regression trees (BRTs)\, and random forest models (RFs)\, using has been collected as part of the larger Northeast Deep Sea Coral Initiative\, he will interact with scientists from other parts of NOAA Fisheries\, NCCOS\, and international collaborators. \n  \n\n\n[/vc_column_text][/vc_column][/vc_row]
URL:https://www.cessrst.org/event/noaa-seminar-series-species-distribution-models-of-deep-sea-coral-and-spongedscsspecies-of-the-northeast-continental-shelf-usa/
CATEGORIES:NOAA Seminar Series,Seminar Series
ORGANIZER;CN="Center for Earth System Sciences and Remote Sensing Technologies (CESSRST)":MAILTO:cessrst@ccny.cuny.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251203T103000
DTEND;TZID=America/New_York:20251203T110000
DTSTAMP:20260404T051814
CREATED:20251120T215646Z
LAST-MODIFIED:20251120T220006Z
UID:5691-1764757800-1764759600@www.cessrst.org
SUMMARY:NOAA Seminar Series: Assessment of High-Resolution Rapid Refresh (HRRR) Precipitation Forecasts for Urban Coastal Areas: New York City Testbed
DESCRIPTION:[vc_row][vc_column][vc_column_text css=””]\n\nTitle: Assessment of High-Resolution Rapid Refresh (HRRR) Precipitation Forecasts for Urban Coastal Areas: New York City Testbed \nPresenter(s): Sebastian Makrides\, CESSRST II Graduate Fellow  \nRemote Access: Video call link: https://meet.google.com/fnt-grnx-fdd\n\nAbstract: Accurate precipitation forecasting is critical for managing flood risks in New York City (NYC). NYC’s approximately 72% impervious surface area often routes runoff directly to sewer systems with limited capacity (~ 44.45 mm/hr). NOAA’s High-Resolution Rapid Refresh (HRRR) model\, a3-km grid spacing hourly-updating convection-allowing forecast system\, provides quantitative precipitation forecasts (QPF) alongside other predicted variables for the continental United States. While the HRRR’s QPF performance has been evaluated over broad regions\, assessments over small-scale urban coastal environments like NYC remain limited. Therefore\, this research assesses HRRR performance in predicting where\, when\, and how much precipitation reaches NYC. This study evaluates HRRR QPF by comparing it with the gridded Analysis of Record for Calibration (AORC) dataset. Multi-year precipitation data are extracted\, temporally and spatially aligned\, and assessed via statistical and numerical analysis to evaluate HRRR’s accuracy in predicting timing\, intensity\, and spatial placement of rainfall. Additionally\, the use of self-organizing maps is explored for the spatial verification of extreme events based on shared seasonal behavior\, facilitating analysis despite their rarity and localized nature. The results expected from such methods will provide insight into potential systematic biases and spatial inaccuracies that may limit the HRRR’s performance for NYC\, where limited drainage infrastructure and vulnerable populations heighten the need for more accurate precipitation forecasts. Understanding HRRR performance for urban hydrometeorology and its associated forecasting strengths and limitations will support improved flood preparedness\, aid in future model developments\, and drive enhancements in verification techniques for the HRRR and other numerical weather prediction models alike. The results are from the NOAA EPP/MSI CSC NERTO graduate internship project that was conducted with NOAA mentors\, Dave Turner and Kelly Mahoney of Earth System Research Laboratories (ESRL)\, Oceanic and Atmospheric Research (OAR). The NERTO aligns with NOAA CESSRST’s goal to conduct NOAA mission-aligned collaborative research. The NERTO Assessment of High-Resolution Rapid Refresh (HRRR) Precipitation Forecasts for Urban Coastal Areas: New York City Testbed also deepened the intern’s understanding of NOAA’s operational forecasting systems\, data assimilation techniques\, and model verification processes\, while enhancing competencies in statistical analysis\, geospatial data integration\, and the interpretation of high-resolution numerical weather prediction outputs for urban hydrometeorological applications.\n \n  \n\n\n[/vc_column_text][/vc_column][/vc_row]
URL:https://www.cessrst.org/event/noaa-seminar-series-assessment-of-high-resolution-rapid-refresh-hrrr-precipitation-forecasts-for-urban-coastal-areas-new-york-city-testbed/
CATEGORIES:NOAA Seminar Series,Seminar Series
ORGANIZER;CN="Center for Earth System Sciences and Remote Sensing Technologies (CESSRST)":MAILTO:cessrst@ccny.cuny.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251203T110000
DTEND;TZID=America/New_York:20251203T113000
DTSTAMP:20260404T051814
CREATED:20251120T215925Z
LAST-MODIFIED:20251120T215948Z
UID:5693-1764759600-1764761400@www.cessrst.org
SUMMARY:NOAA Seminar Series: Retrieving Humidity from Existing Wireless Transmissions
DESCRIPTION:[vc_row][vc_column][vc_column_text css=””]\n\nTitle: Retrieving Humidity from Existing Wireless Transmissions \nPresenter(s): Lasbati Djiwa CESSRST II Graduate Fellow  \nRemote Access: Video call link: https://meet.google.com/gxm-azan-dct\n\nAbstract: \n This graduate internship NERTO project addressed the research question: Can radio frequency (RF) phase shifts from existing wireless transmission systems be used to retrieve atmospheric humidity in real time? It has been previously demonstrated that the attenuation of signals such as cellular transmissions and wireless backhaul can be used to retrieve rainfall rates. This project aims to extend that concept to determine whether humidity can also be measured by monitoring the phase shifts of transmitted signals. The NERTO project involved designing and testing a 24.5 GHz experimental RF system to measure phase variations caused by humidity changes along a wireless path. Ground-truth humidity data from a commercial sensor were used for calibration. Linear regression and temperature-compensated models showed that RF-derived phase data can provide reasonable humidity estimates\, with improved accuracy when temperature effects are included. The results are from the NERTO graduate internship project that was conducted with the mentorship of J. Rafael Mendoza\, Cesar M Salazar Aquino\, and Gerald Kunkle at the National Severe Storms Laboratory in Norman\, Oklahoma. The NERTO aligns with NOAA CSC”CESSRST’s goal of advancing innovative environmental observations and developing next-generation atmospheric sensing technologies. The NERTO project also deepened the intern’s understanding of NOAA’s role in engineering-based environmental monitoring\, strengthened technical skills in RF systems and signal analysis\, and enhanced interdisciplinary collaboration with atmospheric scientists. This work adds value to NOAA’s mission and the broader science community by exploring a low-cost\, scalable approach to improve weather forecasting and climate monitoring capabilities. \n\n\n[/vc_column_text][/vc_column][/vc_row]
URL:https://www.cessrst.org/event/noaa-seminar-series-retrieving-humidity-from-existing-wireless-transmissions/
CATEGORIES:NOAA Seminar Series,Seminar Series
ORGANIZER;CN="Center for Earth System Sciences and Remote Sensing Technologies (CESSRST)":MAILTO:cessrst@ccny.cuny.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251203T113000
DTEND;TZID=America/New_York:20251203T120000
DTSTAMP:20260404T051814
CREATED:20251120T220245Z
LAST-MODIFIED:20251120T220245Z
UID:5695-1764761400-1764763200@www.cessrst.org
SUMMARY:NOAA Seminar Series: Detection of Seals and Polar Bears in Multispectral Aerial Imagery
DESCRIPTION:[vc_row][vc_column][vc_column_text css=””]\n\nTitle:  Detection of Seals and Polar Bears in Multispectral Aerial Imagery \nPresenter(s): Leah Porras\, CESSRST II Graduate Fellow  \nRemote Access: Video call link: https://meet.google.com/ias-uysw-ehc\n\nAbstract: \nIce seals (ribbon\, ringed\, spotted\, & bearded) use spring sea ice as a platform for pupping\, resting\, and their annual molt. Seals play vital roles in Arctic and subarctic marine ecosystems & are a resource for Alaska Native communities. To manage & conserve these species\, reliable population estimates and distribution maps are needed for management and understanding how they respond to climate change and other human impacts. The Polar Ecosystems Program at NOAA’s Alaska Fisheries Science Center conducts aerial surveys to estimate the abundance and distribution of ice-associated seals and polar bears in the Bering\, Chukchi\, and Beaufort seas. Millions of images are collected using color (RGB)\, thermal infrared (IR)\, & ultraviolet (UV) cameras. Current IR machine learning (ML)models struggle to detect rare animals\, including unattended white-coat seal pups\, because of their size\, and polar bears because of their variable thermal signatures. UV imagery has been introduced to address these challenges. This project seeks to enhance ML detection models by integrating UV\, RGB\, and IR imagery\, using annotated datasets developed by NOAA researchers for training and validation. The goal is to create a robust\, open-source model capable of detecting 80% known animals with fewer than 40%false positives. This system will improve survey efficiency & accuracy\, providing reliable population estimates & supporting conservation efforts. With the expected outcome of more precise abundance estimates for decision-making\, this project supports NOAA’s mission to understand and predict species distribution under changing sea ice conditions. The results are from the NOAA EPP/MSI CSC NERTO graduate internship project conducted with NOAA mentor Ms. Erin Moreland of the Alaska Fisheries Science Center\, Marine Mammal Laboratory\, Seattle\, WA. The NERTO aligns with NOAA CSC CESSRST-II’s goal for research on Coastal and Marine Habitat and Ecosystem Goods & Services. The research conducted supports NOAA’s mission by utilizing multidisciplinary tools to enhance the monitoring\, understanding\, and conservation of coastal and marine resources and habitats that are especially vulnerable to both natural and human-induced stressors. Through the NERTO Detection of Seals and Polar Bears in Multispectral Imagery project\, the intern advanced mission-aligned research skills at NOAA. She developed new competencies in artificial intelligence/machine learning for object detection and classification\, and employed remote sensing and computer vision methods to interrogate and validate multispectral datasets. \n\n\n[/vc_column_text][/vc_column][/vc_row]
URL:https://www.cessrst.org/event/noaa-seminar-series-detection-of-seals-and-polar-bears-in-multispectral-aerial-imagery/
CATEGORIES:NOAA Seminar Series,Seminar Series
ORGANIZER;CN="Center for Earth System Sciences and Remote Sensing Technologies (CESSRST)":MAILTO:cessrst@ccny.cuny.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251203T123000
DTEND;TZID=America/New_York:20251203T130000
DTSTAMP:20260404T051814
CREATED:20251125T181634Z
LAST-MODIFIED:20251125T181634Z
UID:5705-1764765000-1764766800@www.cessrst.org
SUMMARY:NOAA Seminar Series: Alaskan Arctic Patterns: Remote Sensing and Greenhouse Gas Emissions from Thermokarst Landscape
DESCRIPTION:[vc_row][vc_column][vc_column_text css=””]\n\nTitle: Alaskan Arctic Patterns: Remote Sensing and Greenhouse Gas Emissions from Thermokarst Landscape \nPresenter(s): Francia Tenorio\, CESSRST II Graduate Fellow  \nRemote Access: Video call link: https://meet.google.com/emg-xjzf-phb\n\n\nAbstract: \nArctic soils are one of the largest terrestrial reservoirs of organic carbon. This carbon is climate-sensitive\, and much effort has been made to investigate its release by establishing baselines for monitoring carbon dioxide (CO2) and methane (CH4) emissions from polar regions. Nitrous oxide (N2O)\, an ozone-depleting greenhouse gas with a global warming potential of 273 times that of CO2\, has traditionally been considered negligible in Arctic ecosystems due to low nitrogen mineralization rates and intense competition for inorganic nitrogen. Recent studies suggest otherwise\, indicating that the Arctic can be a significant source of N2O emissions\, particularly in landforms resulting from permafrost thawing\, such as thermokarst-affected areas with unvegetated surfaces. However\, much remains unknown about these processes in polar regions. This NERTO project aims to investigate the spatial variability of greenhouse gas emissions (CO2\, CH4\, and N2O) from thermokarst-affected landscapes\, particularly retrogressive thaw slumps across the North Slope of Alaska\, via in situ measurements using interdisciplinary approaches. The results are from the NOAA EPP/MSI CSC NERTO graduate internship project\, conducted under the guidance of NOAA mentor Bryan Thomas\, Station Lead of NOAA’s Office of Oceanic and Atmospheric Research\, Global Monitoring Laboratory – Barrow Atmospheric Baseline Observatory. The NERTO program deepened the intern’s understanding of Arctic emissions and thermokarst processes while strengthening their research skills in a collaborative environment. Given the global warming potential of these potent greenhouse gases\, particularly N2O\, which has been overlooked in Arctic ecosystems\, and the vast amount of carbon stored in Arctic landforms\, the results from the NERTO provide valuable ground observations on the patterns and controls of emissions across the region’s landscape\, improving current models on the carbon budget and thereby contributing to climate resiliency\, mitigation\, and adaptation efforts\, aligning with NOAA’s mission of science\, service\, and stewardship.\n \n\n\n[/vc_column_text][/vc_column][/vc_row]
URL:https://www.cessrst.org/event/noaa-seminar-series-alaskan-arctic-patterns-remote-sensing-and-greenhouse-gas-emissions-from-thermokarst-landscape/
CATEGORIES:NOAA Seminar Series,Seminar Series
ORGANIZER;CN="Center for Earth System Sciences and Remote Sensing Technologies (CESSRST)":MAILTO:cessrst@ccny.cuny.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251203T130000
DTEND;TZID=America/New_York:20251203T133000
DTSTAMP:20260404T051814
CREATED:20251125T182444Z
LAST-MODIFIED:20251125T182444Z
UID:5709-1764766800-1764768600@www.cessrst.org
SUMMARY:NOAA Seminar Series: Leveraging Satellite Earth Observations to Understand Wetland Ecosystem Services for Coastal Resilience
DESCRIPTION:[vc_row][vc_column][vc_column_text css=””]\n\nTitle: Leveraging Satellite Earth Observations to Understand Wetland Ecosystem Services for Coastal Resilience\n \nPresenter(s): Nadia Samaroo\, CESSRST II Graduate Fellow  \nRemote Access: Video call link: https://meet.google.com/kim-pxkd-vwh\n\n\nAbstract: \nNew York City’s coastal wetlands “centered on Jamaica Bay’s tidal marshes” provide storm buffering\, carbon storage\, water filtration\, and habitat but have been degraded by relative sea-level rise\, sediment alteration\, eutrophication\, and urbanization. We test a reproducible\, multi-sensor workflow to map vegetation and track dynamics with two pipelines:(1) PlanetScope surface-reflectance imagery stacked with a USGS DEM and classified in R using a trained Random Forest to produce class and confidence GeoTIFFs; and (2) Sentinel-2 composites in Google Earth Engine generating seasonal NDVI (2016″2024) and annual NDWI (2016″2024) with robust cloud/cirrus masking. A Chesapeake Bay benchmark produced accurate five-class maps. In Jamaica Bay\, the model reliably separated open water from low marsh (Spartina alterniflora) but under-represented higher-elevation and edge communities\, indicating domain-shift and feature-set limits. NDVI showed strong seasonality (summer peaks\, winter minimal) and interannual variability consistent with restoration gains and edge erosion; NDWI captured dynamic wetness\, including expanding/contracting ponds and wave-washed fringes. The approach supports post-Sandy management by delivering repeatable indicators of marsh extent\, condition\, and hydrologic state. It highlights priorities for Jamaica Bay” specific retraining\, probability-aware mapping\, expanded predictors (texture\, tidal frequency\, LiDAR)\, and spatial cross-validation. The results are from the NOAA EPP/MSI CSC NERTO graduate internship project conducted with NOAA mentor Dr. Veronica Lance of the CoastWatch/OceanWatch/PolarWatch Program\, National Environmental Satellite\, Data\, and Information Service (NESDIS). The NERTO aligns with NOAA CSC CESSRST-II’s mission to advance earth system science\, remote sensing\, and data-driven environmental solutions\, in support of NOAA’s goals of a Weather-Ready Nation\, Resilient Coastal Communities\, and Climate Adaptation. The NERTO\, Leveraging Satellite Earth Observations to Understand Wetland Ecosystem Services for Coastal Resilience\, strengthened the intern’s skills by applying a multi-sensor workflow to map vegetation and track marsh dynamics in Jamaica Bay using PlanetScope classification in R andSentinel-2 NDVI/NDWI time series in Google Earth Engine. The project improved understanding of wetland change drivers and NOAA research practices while enhancing scientific communication\, technical reporting\, and collaborative analysis for coastal resilience.\n \n\n\n[/vc_column_text][/vc_column][/vc_row]
URL:https://www.cessrst.org/event/noaa-seminar-series-leveraging-satellite-earth-observations-to-understand-wetland-ecosystem-services-for-coastal-resilience/
CATEGORIES:NOAA Seminar Series,Seminar Series
ORGANIZER;CN="Center for Earth System Sciences and Remote Sensing Technologies (CESSRST)":MAILTO:cessrst@ccny.cuny.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251205T130000
DTEND;TZID=America/New_York:20251205T133000
DTSTAMP:20260404T051814
CREATED:20251125T181921Z
LAST-MODIFIED:20251125T181921Z
UID:5707-1764939600-1764941400@www.cessrst.org
SUMMARY:NOAA Seminar Series: Exploring sampling approaches for NSSL's UAS applications
DESCRIPTION:[vc_row][vc_column][vc_column_text css=””]\n\nTitle: Exploring sampling approaches for NSSL’s UAS applications\n \nPresenter(s): Alejandro Medina\, CESSRST II Graduate Fellow  \nRemote Access: Video call link: https://meet.google.com/jiv-gdsq-yqn\n\n\nAbstract: \nThis research\, conducted at NOAA’s National Severe Storms Laboratory (NSSL)\, developed a framework to close critical data gaps in boundary-layer observations\, a region essential for predicting severe weather. Traditional uncrewed aerial system (UAS) flights follow fixed paths\, limiting adaptability to evolving atmospheric conditions. To address this\, we introduced an unsupervised clustering algorithm trained on radiosonde data from the Integrated Global Radiosonde Archive (IGRA). The algorithm detects structural patterns in vertical temperature profiles and informs adaptive sampling strategies. The framework allows a UAS to first collect a baseline profile\, then compare new flight data against clustering results to determine which atmospheric layers are undersampled or highly variable. The UAS can then adjust its flight behavior\, spending more time in regions with sparse data rather than distributing measurements uniformly. Implementation combined Python-based preprocessing and clustering workflows with MATLAB and ArduPilot simulations\, integrating the approach into CopterSonde\, a boundary-layer UAS platform already used in NOAA OAR laboratories. Early tests show the feasibility of real-time adaptive sampling. This work paves the way for UAS operations that actively reduce data gaps\, sharpen the resolution of boundary-layer measurements\, and strengthen NOAA’s forecasting capabilities in support of the Weather-Ready Nation initiative. The results are from the NOAA EPP/MSI CSCNERTO graduate internship project conducted with NOAA mentor Dr. Elizabeth Smith of the Oceanic and Atmospheric Research\, National Severe Storms Laboratory. The NERTO aligns with NOAA CSC CESSRST-II’s mission to advance earth system science\, remote sensing\, and data-driven environmental solutions\, in support of NOAA’s goals of a Weather-Ready Nation\, Resilient Coastal Communities\, and Climate Adaptation. The NERTO Exploring sampling approaches for NSSL’s UAS applications also deepened the intern’s understanding of NOAA operational workflows\, scientific communication\, and collaborative research environments\, while strengthening professional skills such as technical reporting\, cross-disciplinary teamwork\, and real-time presentation of scientific results.\n \n\n\n[/vc_column_text][/vc_column][/vc_row]
URL:https://www.cessrst.org/event/noaa-seminar-series-exploring-sampling-approaches-for-nssls-uas-applications/
CATEGORIES:NOAA Seminar Series,Seminar Series
ORGANIZER;CN="Center for Earth System Sciences and Remote Sensing Technologies (CESSRST)":MAILTO:cessrst@ccny.cuny.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251222T110000
DTEND;TZID=America/New_York:20251222T113000
DTSTAMP:20260404T051814
CREATED:20251218T155802Z
LAST-MODIFIED:20251218T155802Z
UID:5731-1766401200-1766403000@www.cessrst.org
SUMMARY:NOAA Seminar Series: Short-Term Soil Moisture Dry-Down Prediction Using LSTM to Enhance Land-Surface Model Initialization and Verification
DESCRIPTION:[vc_row][vc_column][vc_column_text css=””]\n\nTitle: Short-Term Soil Moisture Dry-Down Prediction Using LSTM to Enhance Land-Surface Model Initialization and Verification\n \nPresenter(s): Stephanie Marquez\, CESSRST II Graduate Fellow  \nRemote Access: Video call link: https://meet.google.com/tin-sgmk-jpd\n\n\nAbstract: \nShort-term soil moisture prediction is essential for drought monitoring\, land “surface model initialization\, and improving the accuracy of NOAA’s environmental forecasting systems. This NERTO project was motivated by the operational need to better represent soil moisture dry-down behavior in NOAA models such as HRRR and Noah-MP\, which rely on accurate land-surface states but often lack sufficient observational constraints. The study focused on U.S. Climate Reference Network (USCRN) stations across the South west\, a region characterized by highly dynamic soil moisture conditions and strong land “atmosphere coupling\, making it an ideal domain for evaluating model skill. Using USCRN multi-depth soil moisture\, meteorological data\, and soil characteristics\, I developed a data-driven Long Short-Term Memory(LSTM) framework to forecast soil moisture recession at depths of 5″100 cm. The model used a 7-day lookback window to generate 1″30-day ahead predictions. Results show that the LSTM captures depth-dependent drying behavior\, achieving KGE values of 0.87″0.97 and RMSE values of 0.015″0.029\, with the highest skill in deeper soil layers where moisture changes more gradually. The model generalized well across stations and reproduced realistic dry-down trajectories\, revealing consistent patterns between soil depth\, atmospheric drivers\, and forecast skill. These findings demonstrate the value of machine-learning approaches for improving short-term soil moisture prediction and highlight their potential to support NOAA operations by enhancing land-surface model initialization\, bias detection\, and drought-related decision-making. The results presented are from the NOAA EPP/MSI CSC NERTO graduate internship project conducted under the mentorship of Dr. Dave Turner\, NOAA/OAR/Global Systems Laboratory\, and Dr. Michael Barlage\, NOAA/NWS/Environmental Modeling Center. This NERTO experience aligns with the NOAA Cooperative Science Center in CESSRST-II\, supporting the Center’s goal of conducting NOA A mission-aligned research to understand and predict changes in land and water systems. This project\, titled Short-Term Soil Moisture Dry-Down Prediction Using LSTM to Enhance Land-Surface Model Initialization and Verification\, addressed the research question: How accurately can an event-based\, multi-depth LSTM framework forecast soil moisture recession across USCRN sites\, and how can these predictions support NOAA land-surface modeling? The work provides value to the scientific community and program stakeholders by demonstrating a scalable\, data-driven approach for improving soil moisture representation in NOAA modeling systems\, supporting drought monitoring\, environmental prediction\, and land” atmosphere process understanding. \n\n\n[/vc_column_text][/vc_column][/vc_row]
URL:https://www.cessrst.org/event/noaa-seminar-series-short-term-soil-moisture-dry-down-prediction-using-lstm-to-enhance-land-surface-model-initialization-and-verification/
CATEGORIES:NOAA Seminar Series,Seminar Series
ORGANIZER;CN="Center for Earth System Sciences and Remote Sensing Technologies (CESSRST)":MAILTO:cessrst@ccny.cuny.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260108T110000
DTEND;TZID=America/New_York:20260108T113000
DTSTAMP:20260404T051814
CREATED:20251218T160238Z
LAST-MODIFIED:20251218T160238Z
UID:5733-1767870000-1767871800@www.cessrst.org
SUMMARY:NOAA Seminar Series: Machine Learning Techniques to Identify Solar Filaments
DESCRIPTION:[vc_row][vc_column][vc_column_text css=””]\n\nTitle:  Machine Learning Techniques to Identify Solar Filaments\n \nPresenter(s): Ryan Goldberg\, CESSRST II Graduate Fellow  \nRemote Access: Video call link: https://meet.google.com/npq-acov-qvq\n\n\nAbstract: \nSolar filaments are a regularly occurring feature of the solar atmosphere that provides crucial information on changes in solar activity and helps forecast solar weather. Most notably\, filaments can give rise to coronal mass ejections (CMEs)\, a large expulsion of plasma and magnetic field from the Sun’s corona that can heavily impact Earth’s magnetosphere. However\, filaments can be hard to detect across the entire solar disc\, and methods that rely on human annotations\, which are inherently costly and time-consuming\, can lead to inconsistent mapping of solar phenomena. This project uses imagery from the Global Oscillation Network Group (GONG)\, which observes the full solar disk in the H-alpha band where filaments are most prominent. The first step uses preprocessing techniques to highlight filament features\, along with the Segment Anything Model(SAM)\, to produce a first-pass filament segmentation. These SAM predictions are improved by incorporating physical constraints from known filament shapes\, often connecting closely but separately located prediction masks. The second step trains a U-Net model on the machine-generated pseudo-labels to produce refined filament predictions. This model is validated against existing human-annotated filament mapping of the GONG H-alpha solar images. This self-training pipeline offers a scalable alternative to human annotations for filament mapping and the creation of a consistent\, large-scale dataset. The dataset can serve as a new benchmark for solar filament detection models\, and the self-training model can be adapted for automated analysis. The results are from the NOAA EPP CSC NERTO (in-residence at NOAA graduate internship) project conducted with NOAA mentor Rob Redmon of the NOAA National Centers for Environmental Information (NCEI). The NERTO aligns with NOAA CSC CESSRST-II’s goal to advance environmental data science and develop innovative remote sensing and machine learning capabilities that support NOAA’s mission. The NERTO project\, A Self-Trained Deep-Learning Methodology for Automated Solar Filament Detection and Dataset Generation\, also deepened the intern’s understanding of NOAA’s data stewardship practices\, solar-terrestrial monitoring needs\, and the application of artificial intelligence to large-scale environmental information systems. \n\n\n[/vc_column_text][/vc_column][/vc_row]
URL:https://www.cessrst.org/event/noaa-seminar-series-machine-learning-techniques-to-identify-solar-filaments/
CATEGORIES:NOAA Seminar Series,Seminar Series
ORGANIZER;CN="Center for Earth System Sciences and Remote Sensing Technologies (CESSRST)":MAILTO:cessrst@ccny.cuny.edu
END:VEVENT
END:VCALENDAR