RESEARCH Themes

The Northern Gulf Institute (NGI) has four scientific research themes:

Climate Change and Climate Variability Effects on Regional Ecosystems

This research theme focuses on the effects of climate change and climate variability on marine ecosystems, adjacent watersheds, and the socioeconomic well-being of the region. It also addresses how the ecosystem affects climate processes.

Coastal Hazards

This research theme encompasses the physical and biological systems as well as the biological and socio-economic dimensions associated with coastal hazards, such as population increases, that are of concern to agencies responsible for the public good of coastal regions and for a sustainable Gulf of Mexico.

Ecosystem Management

This research theme promotes sustainable coastal development, facilitating community resiliency, and enabling an ecosystem-based approach to management, including fisheries management. Enhanced scientific understanding of the interconnections between the marine ecosystem and the adjacent watershed including their resource stewardship implications drive the focus of these efforts.

Effective and Efficient Data Management Systems Supporting a Data-driven Economy

This research theme investigates, develops, and tests innovative data stewardship solutions. The research addresses gaps in data management capacity resulting from the development of new environmental data sensors and platforms, larger data volumes, and increased public demand for information. These efforts enhance NOAA’s data management, visualization, and dissemination capabilities.

Research Projects

Active Research Projects

This page contains summaries of active projects organized by funding source. The first few words of each summary are bolded so readers can see the topic that a project addresses or a key component (e.g., technology or method) that it employs.For more information, go to Projects & Publications Search (under the Research Tab).

PIs/Co-PIs: If your project summary needs correction, please send an email to maggied@ngi.msstate.edu.

Funding Sources:

Oceanic and Atmospheric Research (OAR)

1.Wind speed at the ocean’s surface influences hurricane forecasts by the National Hurricane Center (NHC). Researchers are improving estimates of surface wind speed by evaluating the Stepped-Frequency Microwave Radiometer (SFMR) flown on hurricane hunter aircraft that is used in gathering data that factors into wind speed calculations. The need for improvement was realized after they found greater variability between the SFMR estimates and those from other sources, such as dropsonde data and adjusted flight-level winds. The researchers are improving the detection of radio frequency interference (RFI) that the SFMR uses to estimate surface wind speed by updating it with a more robust technique using reflectivity data from the tail-Doppler radars (TDR) on hurricane hunter aircraft to correct for rain impacts. Data collected during the 2021 and beginning of the 2022 hurricane seasons will serve as an independent dataset to test the updated SFMR algorithm, which will be provided to NOAA and Air Force hurricane hunters for consideration to implement operationally.

Title, NGI Number: Improvements to Surface Wind Speed Estimates in Tropical Cyclones, 21-NGI4-03 and 20-NGI3-113
Performance Period: 09/01/2020 to 09/30/2022
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Heather Holbach, Florida State University
NGI Theme(s): Coastal Hazards
Collaborators/Partners: NOAA National Weather Service (NWS), National Centers for Environmental Prediction (NCEP) National Hurricane Center (NHC), Office of Marine and Aviation Operations (OMAO) Aircraft Operations Center (AOC), and AOML/Hurricane Research Division (HRD); University of Miami/Cooperative Institute for Marine and Atmospheric Studies (CIMAS); the National Center for Atmospheric Research (NCAR); and ProSensing Inc.


2.The tail-Doppler radars (TDR) on NOAA hurricane hunter aircraft collect data, specifically spatial coverage of the surface wind field, that has the potential to improve forecasts by the National Hurricane Center (NHC). Forecasters rely on data provided by satellites and hurricane hunter aircraft; however, the spatial coverage of the aircraft-based surface wind speed estimates are limited to being along the flight track or point measurements, leading to an under-sampling problem in which the peak intensity and desired wind radii are unlikely to be observed on any given flight. Collaborating with TDR experts at the NOAA Hurricane Research Division researchers are developing a method to reduce the lower-level TDR winds to the surface which would provide swaths of data as opposed to a track or single point of data. To do so, they are comparing the TDR wind field from the swath analysis at 1 km altitude (and adjacent levels) to wind surface speeds from dropsonde and Stepped-Frequency Microwave Radiometer (SFMR). This analysis will be performed using data collected since the late 1990s when the TDR fore-aft scanning technique was first employed.  

Title, NGI Number: TDR Surface Wind Reduction, 21-NGI3-127
Performance Period: 06/01/2021 to 07/31/2022
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Heather Holbach, Florida State University
NGI Theme(s): Coastal Hazards
Collaborators/Partners: NOAA/AOML Hurricane Research Division (HRD)


3.Hurricane predictions typically utilize statistical methods, but researchers are investigating the use of physical mechanismsin prediction models. Specifically, they are looking at mechanisms that control the influence of the Atlantic Warm Pool (AWP) on tropical cyclone steering flow that drives landfall. To do so, they are using retrospective forecast data from the National Multi-Model Ensemble Phase-2 to quantify the seasonal predictability of the AWP and its modulation on the steering flow as well as associated atmospheric states conducive to tropical cyclone landfall. This involves analysis of climate model simulations (using the Community Earth System Model) for the AWP modulation up to 6 months before the beginning of the Atlantic hurricane season.They will also development a beta advection model to quantify the propagation associated with the AWP modulations. A seasonal outlook for landfalling Atlantic hurricanes will be developed based on these modeled frameworks. This method could also influence the predictability of other seasonal phenomena besides tropical cyclones.

Title, NGI Number: Enhanced Seasonal Landfalling Hurricane Outlook, 19-NGI3-77
Performance Period: 10/01/2019 to 09/30/2022
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Andrew Mercer, Mississippi State University
NGI Theme(s): Coastal Hazards
Collaborators/Partners: National Center for Atmospheric Research


4.Air-sea interactions with fluxes of heat, moisture, and momentum serve as indicators of change in regional climate and weather patterns and, at smaller scales, may be linked to drought, floods, and storm intensity and track. Flux-related variables are used in forcing ocean models and testing coupled ocean/atmospheric models. To improve the quality of wind and flux products, researchers are developing a global (over water) multi-satellite wind product and a satellite-based flux product that assimilates satellite and in situ data. The new gridding technique combines the strengths of satellite observations and numerical weather prediction analyses through a planetary boundary-layer model to produce a higher resolution surface vector wind data set. Earlier efforts resulted in the delayed-mode objective 1˚ FSU3 wind and flux product, monthly wind products, the quick-look 1˚ Legler Indian Ocean (currently not being produced) and the 2˚ Tropical Pacific pseudo-wind stress, which contributes to the NOAA Climate Diagnostics Bulletin. The wind products are available at https://mdc.coaps.fsu.edu/data, which is accessed by ~170 registered users representing academic institutions, governmental agencies, and public/non-profit entities from 16 countries.

Title, NGI Number: Climate Variability in Ocean Surface Turbulent Fluxes, 21-NGI4-04
Performance Period: 10/01/2016 to 09/30/2022
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Climate Program Office (CPO)
PI/Co-PI: Mark Bourassa/Shawn Smith, Florida State University

NGI Themes: Climate Change and Climate Variability Effects on Regional Ecosystems, Coastal Hazards
Collaborators/Partners: NOAA National Centers for Environmental Information (NCEI), National Centers for Environmental Prediction (NCEP), Observing System Monitoring Center (OSMC), Climate Prediction Center (CPC), and Atlantic Oceanographic and Meteorological Laboratory (AOML) Hurricane Research Division (HRD) and Physical Oceanography Division (PHOD); SeaFlux Project, NASA NEWS, Ocean Heat Flux Project, Southern Ocean Observing System (SOOS), NASA Ocean Vector Winds Science Team, International Ocean Vector Winds Science Team, and satellite science community


5.Accurately predicting tropical cyclone (TC) intensity  is challenging, and a contributing factor is the poor understanding and modeling of boundary layer turbulent processes in high-wind conditions.These processes have scarce observations, and existing planetary boundary layer (PBL) parameterizations in models are generally designed for low-wind conditions, pointing to the need for continuous development of PBL parameterizations for hurricane forecast models. Researchers are building up their recent development of a modeling framework that combines a small-domain large eddy simulation (LES) and dropsonde thermodynamic data (collected in mature hurricanes by NOAA aircraft) to study the turbulence characteristics in the TC boundary layer. This framework pioneers the way to evaluate and improve the PBL schemes in hurricane conditions, and it was used to evaluate and improve the PBL scheme from NOAA’s Global Forecast System (GFS) and Hurricane Analysis and Forecast System (HAFS) models. Hindcasts of the 2021 hurricane season demonstrated that the improved PBL schemes improves both intensity and structure forecasts. To transition their research to operations (R2O), they are incorporating the improved PBL scheme into the new version of HAFS, and the 2022 real-time HAFS forecasts will be available at https://storm.aoml.noaa.gov/viewer/. They will also use the improved PBL scheme to assess the role of PBL parameterizations for Hurricane Michael (2018), which was stronger than projected. As their recent findings highlight the role of turbulence-kinetic-energy (TKE) in TC intensity and structure, they recommend TKE-based PBL schemes for TC simulations.

Title, NGI Number: Toward Improved Understanding and Modeling of Boundary Layer Processes in Tropical Cyclones Using Large-Eddy Simulation, 21-NGI4-01
Performance Period: 10/01/2021 to 09/30/2023
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Xiaomin Chen/Robert Moorhead, Mississippi State University
NGI Theme(s): Coastal Hazards

Collaborators/Partners: Texas A&M University, National Center for Atmospheric Research (NCAR), University of Miami/Cooperative Institute for Marine and Atmospheric Studies (CIMAS), NOAA AOML/Hurricane Research Division (HRD)


6.The investigation of tornado formation includes analysis of storms that spawn unusual or unexpected tornados. From January to April 2021, researchers deployed mobile facilities to collect data on atmospheric boundary layer evolution and cloud characteristics that preceded thunderstorms that formed along or ahead of cold fronts (known as Quasi-Linear Convective Systems, QLCS). They are conducting quality control of and analyzing the data acquired and will also analyze pre-storm conditions for 40 cold season events from 2005 to 2021. Case studies will be used to examine the internal structure of two severe QLCSs (11/18/2017 and 02/12/2020), including the 03/03/2020 tornadic storm that devastated central Tennessee. Additionally, they are conducting inter-comparisons of wind profiles derived from various systems (radar wind profilers, Doppler lidar, Doppler sodar, and scanning Doppler radars). Each case will include analyses of dual Doppler radar data, environmental data from profiling systems and balloon soundings, and the kinematics of QLCS updrafts and downdrafts using vertically pointing Doppler radar data.

Title, NGI Number: Improved Understanding of the Kinematic and Thermodynamic Characteristics of Cold Season, Non-Classical Tornadic Storms, 20-NGI3-109
Performance Period: 08/01/2020 to 05/31/2022
Funding Source: NOAA Oceanic and Atmospheric Research (OAR)
PI/Co-PI: Kevin Knupp, University of Alabama at Huntsville
NGI Theme(s): Coastal Hazards
Collaborators/Partners: NOAA Earth System Research Laboratory (ESRL)


7.Meteorological data from U.S. research vessels are being collected and monitored for quality control and disseminated through the Shipboard Automated Meteorological and Oceanographic System Data Assembly Center (SAMOS DAC) https://samos.coaps.fsu.edu/html/, which supports the NOAA Global Ocean Monitoring and Observing mission. Recent efforts have included a review and update of components of the data processing systems and a development of procedures for the automated intake of instrument metadata. To date, observation data has been archived for 1,329 ship days from 16 NOAA and four other research vessels. These observations contribute to several marine products, including the International Comprehensive Ocean-Atmosphere Data Set and the Surface Underway Marine Database Portal.

Title, NGI Number: U.S. Research Vessel Surface Meteorology Data Assembly Center, 21-NGI4-07
Performance Period: 10/01/2016 to 09/30/2022
Funding Source: NOAA Oceanic and Atmospheric Research (OAR)
PI/Co-PI: Shawn Smith/Mark Bourassa, Florida State University
NGI Theme(s): Data Management
Collaborators/Partners: NOAA National Centers for Environmental Information (NCEI), NOAA Office of Marine and Aviation Operations (OMAO), NOAA Earth Systems Research Laboratory Physical Science Division (ESRL/PSD), and the NSF Rolling Deck to Repository Project (R2R).


8.Drought conditions and their frequency in the southeast U.S. are modulated by complex interactions of large-scale climate variations. To better understand the underlying mechanisms behind this relationship, researchers are employing reanalysis products to study drought conditions stemming from weather and climate variations over the past 50-100 years and performing fully coupled global simulations using the Community Earth System Model (CESM). Specifically, they are exploring the impacts of interdecadal Pacific oscillation and Atlantic multidecadal oscillation and the associated activity of El Niño–Southern Oscillation (ENSO) on drought. They will also consider how future changes in the state of the Pacific and Atlantic oceans might impact drought conditions and incorporate machine learning techniques to validate and test for projections of drought conditions. This model is a first attempt at predicting southeast U.S. drought exclusively through utilizing multidecadal teleconnection patterns with ENSO phase.

Title, NGI Number: Asymmetric Influences of the Pacific and Atlantic Oceans on the Decadal Drought Frequency in the Southern U.S., 21-NGI4-15
Performance Period: 10/01/2021 to 09/30/2023
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Andrew Mercer, Mississippi State University
NGI Theme(s): Climate Change and Climate Variability Effects on Regional Ecosystems; Coastal Hazards
Collaborators: NOAA AOML Physical Oceanography Division


9.Uncrewed Aircraft Systems (UAS) are helping provide rapid response during and after flooding events with near real-time imagery of flooded areas, enabling the production of inundation maps and more accurate forecasts and warnings. Researchers have executed multiple missions with UAS. The mission around Greenwood, MS documented one of the highest floods ever recorded in the area and provided forecast imagery, as opposed to just written descriptions, that showed the impact of future floods. The mission in late 2020 flew a 500# UAS in the aftermath of Hurricane Delta and collected data along the main stem of the Mississippi River south of Greenville, MS. Collaboration between UAS operators and users of UAS data has helped each to understand the other’s needs and identifed ways to improve the capture, transmission, and display of real-time imagery. This work has helped advance proof that the UAS can operate safely beyond a visible line of sight with a human on the aircraft and can quickly document and track changes in river channels (such as structure, morphology, and presence of debris) and provide details on levee breaches and inundation (location, width, depth).

Title, NGI Number: SHOUT4Rivers, 19-NGI3-84
Performance Period: 10/01/2017 to 09/30/2022
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Uncrewed Systems Research Transition Office (UxSRTO)
PI/Co-PI: Robert Moorhead/Jamie Dyer, Mississippi State University
NGI Theme(s): Coastal Hazards
Collaborators/Partners: NOAA Office of Water Prediction (OWP); and NOAA NWS Southern Region, Lower Mississippi River Forecast Center (LMRFC), West Gulf River Forecast Center (WGRFC), and Southeast River Forecast Center (SERFC)


10.The ocean’s biological carbon pump (BCP) helps modulate the Earth’s climate. To understand the biodiversity and variability of the BCP and its relation to carbon cycling, experts in ‘omics, biogeochemistry, and paleoceanography are combining eDNA with emergent observing technologies (such as BGC-Argo) and paleoclimate archives. Leveraging NOAA and UNOLS cruises, they will deploy moored sediment traps at the base of the euphotic zone in the northern Gulf of Mexico to collect particulate fluxes and analyze for biodiversity and contributions to the BCP. They will perform amplicon metabarcoding of specific gene regions for a range of organisms (e.g., 18S rRNA for plankton and 16S rRna for bacteria) to link carbon export processes with taxonomic groups across multiple trophic levels. Additionally, they will compare the results of a traditional analysis of foraminifera with a targeted eDNA study of foraminiferal biodiversity. This effort will establish and facilitate future best practices for eDNA sampling and may contribute to modeling carbon and nutrient export and cycling as well as developing biological proxies to characterize the strength and efficiency of the BCP.

Title, NGI Number: Characterizing the Biodiversity and Variability of the Biological Carbon Pump in the Northern Gulf of Mexico, 21-NGI4-06
Performance Period: 10/01/2021 to 09/30/2026
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Luke Thompson, Mississippi State University
NGI Theme(s): Climate Change and Climate Variability Effects on Regional Ecosystems, Ecosystem Management, Data Management
Collaborators: University of South Carolina, US Geological Survey


11.Biogeochemical fluxes in the ocean are linked to microbial diversity, and researchers are seeking to better understand that relationship by collaborating with the Global Ocean Ship-based Hydrographic Investigations Program (GO-SHIP). GO-SHIP is an ocean and climate observing system aimed at producing a high-resolution picture of ocean conditions and quantifying ocean and climate dynamics. They will provide support for the 2022 GO-SHIP cruise P02; following the cruise, they will perform analyses on the collected DNA (from plankton, microorganisms, metazoans, and fish), including DNA metabarcoding to sequence bacteria and protists (16S and18S rRNA genes) and fish environmental DNA (mitochondrial 12S rRNA gene). After metabarcoding and sequencing are completed, they will analyze sequence data in combination with the metagenomic, physical, and chemical data from the GO-SHIP collaborators.

Title, NGI Number: Bringing Environmental Monitoring to the Global Ocean Ship-Based Hydrographic Investigations Program (GO-SHIP), 21-NGI4-02
Performance Period: 10/01/2021 to 09/30/2022
Funding Source: NOAA Oceanic and Atmospheric Research (OAR)/Global Ocean Monitoring and Observing (GOMO)
PI/Co-PI: Luck Thompson, Mississippi State University
NGI Themes: Climate Change and Climate Variability Effects on Regional Ecosystems
Collaborators/Partners: Michigan State University Research Technology Support Facility


12.The biological effects of ocean acidification (OA) remain unclear; however, recent efforts to monitor OA via the Gulf of Mexico Ecosystems and Carbon Cycle (GOMECC) cruises have revealed spatial differences in OA parameters (e.g., pH and CO2). To better understand the biological response to OA, researchers will collect water samples from CTD casts and surface waters during the GOMECC-4 cruise and sequence and analyze environmental DNA or eDNA for the presence of species in coastal and open-ocean sites. The eDNA sampling will be coordinated with biological measurements (plankton counts, grazing, calcification), OA parameters (total alkalinity, pH, carbonate, dissolved inorganic carbon), and other physicochemical parameters (oxygen, salinity, temperature). The sequence data will be analyzed bioinformatically to reveal patterns in biodiversity and composition among populations of bacteria, plankton, and fish. These data, combined with physical and chemical parameters, will help develop models of ecosystem biodiversity (a multi-trophic level model of biodiversity and a predictive model of harmful algal bloom responses to environmental conditions) and identify potential indicator species of OA. Information gained will advance eDNA metabarcoding as a standard tool for biological ocean research, biodiversity assessments, and ecosystem management.

Title, NGI Number: Assessing Ecosystem Responses of Gulf of Mexico Communities to OA using Environmental DNA , 21-NGI3-132
Performance Period: 07/01/2021 to 09/30/2022
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Luke Thompson, Mississippi State University
NGI Theme(s): Climate Change and Climate Variability Effects on Regional Ecosystems
Collaborators/Partners: Cooperative Institute for Marine and Atmospheric Studies (CIMAS)


13.Increases in ocean acidification (OA) contribute to changing physicochemical conditions, which can affect processes that drive productivity, biodiversity, and food web dynamics. During the NOAA Gulf of Mexico Ecosystems and Carbon Cycle 3 (GOMECC-3) cruise, the first biologically relevant sampling and rate measurements with relationship to OA were conducted, with initial data suggesting a strong link between OA, hypoxia, and eutrophication. To provide an integrated view of these conditions and their ecosystem impacts, researchers are analyzing datasets collected during GOMECC-3 and will collect and analyze marine samples on the GOMECC-4 cruise. They will characterize plankton communities and quantify changes in carbon flow to higher trophic levels by conducting onboard microzooplankton and copepod grazing experiments using traditional and ‘omics approaches. They will also identify indicator species/assemblages that are most impacted by environmental stressors for continued tracking and collect larval fish and analyze their distribution, abundance, diet, growth, condition, and evidence of microplastic ingestion for tracking OA impacts on food web dynamics. This project includes hosting/mentoring a Research Experience for Undergraduate (REU) intern.

Title, NGI Number: USM REU: Evaluation of OA Impacts to Plankton and Fish Distributions in the Gulf of Mexico during GOMECC-4 with a focus on HAP-Interactions (BIO-GOMECC-4) Years 2 & 3, 21-NGI4-05
Performance Period: 10/01/2021 to 09/30/2023
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Frank Hernandez, University of Southern Mississippi
NGI Theme(s): Ecosystem Management, Climate Change and Climate Variability Effects on Regional Ecosystems
Collaborators: NOAA Southeast Fisheries Science Center (SEFSC) Pascagoula Laboratory, Gulf Coast Research Lab, North Carolina State University, and University of Louisiana at Lafayette


14.An ocean biogeochemical model is being configured to improve our understanding about potential large-scale climate drivers of shifts in plankton biomass and range for a suite of coastal pelagic species in the Gulf of Mexico and South Atlantic Bight. Researchers have configured a Modular Ocean Model – Tracers Of Phytoplankton with Allometric Zooplankton (MOM5-TOPAZ) model for the north Atlantic for the time period of 1958 to 2019 using a new atmospheric dataset for driving ocean-sea-ice models (JRA55-DO) as surface forcing. This test model has a one-quarter degree resolution, which is a necessary first step before increasing model resolution to 10 km. Model outputs are available in the Network Common Data Form (NetCDF) format on the NOAA OAR/AOML server.

Title, NGI Number: Ocean Biogeochemical Modeling of the U.S. Gulf and East Coasts, 20-NGI3-118
Performance Period: 10/01/2020 to 09/30/2022
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Fabian Gomez, Mississippi State University
NGI Theme(s): Climate Change and Climate Variability Effects on Regional Ecosystems
Collaborators/Partners: NOAA AOML Physical Oceanography Division


15.Declines in coastal pelagic species abundance along the U.S. Gulf Coast and South Atlantic Bight prompted researchers to examine changes in the food chain and physical ocean mechanisms that might be driving declines. Using prey field data from the Southeast Area Monitoring and Assessment Program (SEAMAP), they quantified basin-wide productivity for mesozooplankton secondary production estimates from 1993 to 2012 in Gulf of Mexico fishing regions. They analyzed long-term landing and survey data for King Mackerel, Spanish Mackerel, and Cobia. Results showed significant decreases in King Mackerel growth and similar decreases in secondary production. By demonstrating that secondary production has a significant impact on growth rates of King Mackerel, the researchers highlighted the importance of an ecosystem-based management approach. The 20-year secondary production estimates can be used to investigate the link between lower trophic level productivity and the productivity or recruitment of other species.

Title, NGI Number: Recent Declines in Coastal Pelagic Species along the U.S. Gulf and South Atlantic Bight and the Potential Impact of Large-Scale Ocean Circulation Changes, 19-NGI3-73
Performance Period: 10/01/2019 to 07/31/2022
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Frank Hernandez, University of Southern Mississippi
NGI Theme(s): Ecosystem Management
Collaborators/Partners: NOAA AOML Physical Oceanography Division, NOAA Southeast Fisheries Science Center (SEFSC) Sustainable Fisheries Division in the Gulf of Mexico Branch, and Cooperative Institute for Marine and Atmospheric Studies (CIMAS)


16.Cetaceans (whales, dolphins, and porpoises) are targets of conservation efforts. In the Gulf of Mexico, the endangered Bryde’s whale population has approximately 33 individuals and Bottlenose dolphins were affected by the Deepwater Horizon oil spill. Understanding the ecology and feeding behavior of Bryde’s whales and oil spill impacts on dolphins are priorities of NOAA Fisheries. Researchers are applying their expertise in ’omics and using cutting-edge DNA analysis facilities and bioinformatics capacity to support conservation research at the Southeast Fisheries Science Center (SEFSC). Using samples collected by SEFSC scientists of both fish and eDNA from deep waters where Bryde’s whales had just been observed, researchers will identify potential prey species. Using samples collected by SEFSC scientists of skin microbiome from dolphins in Barataria Bay and from those near the spill site before and shortly after the spill as well as several years later, they will identify a baseline skin microbiome and possible effects on it from the oil spill. Researchers will perform DNA metabarcoding analyses and analyze the DNA sequence results to find the taxonomic compositions of the samples.

Title, NGI Number: Applying Omics Technologies to Support Cetacean Conservation in the Gulf of Mexico, 21-NGI3-131
Performance Period: 07/01/2021 to 09/30/2022
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)

PI/Co-PI: Luke Thompson, Mississippi State University
NGI Theme(s): Climate Change and Climate Variability Effects on Regional Ecosystems
Collaborators/Partners: NOAA Southeast Fisheries Science Center (SEFSC)


17.Five turtle species live in the Gulf of Mexico, with one listed as threatened (loggerheads) and four as endangered (leatherback, green, Kemp’s Ridley, and hawksbill). The Gulf of Mexico Sea Turtle Early Restoration Project aims to restore sea turtle populations affected by the Deepwater Horizon oil spill. Researchers with the NOAA and Northern Gulf Institute are collaborating to better understand sea turtle strandings by implementing and testing two analytical and mapping tools. One is the Backcasting Analysis and Mortality Mapping (BAMM) tool that provides a backcast prediction of the origin of strandings; the other is the Beaching Probability Index (Beaching Index) that evaluates the probability and location of strandings. They will also design and implement a web interface to access results from the Beaching Index. Estimates of origin for stranded sea turtles and predictions of the influence of environmental conditions on animal drift and dispersal will provide valuable insight on turtle strandings and mortality for resource managers and facilitate better response and planning for sea turtle stranding emergencies.

Title, NGI Number: Coastal Science Research, Data Development, and Information Services (NRDA Turtle Project), NA18OAR4170438
Performance Period: 09/01/2018 to 08/31/2022
Funding Source: Mississippi-Alabama Sea Grant Consortium (MASGC) via NOAA Oceanic and Atmospheric Research (OAR) via National Centers for Environmental Information (NCEI)
PI/Co-PI: Just Cebrian/Zhankun Wang, Mississippi State University
NGI Theme(s): Ecosystem Management
Collaborators/Partners: NOAA Southeast Fisheries Science Center (SEFSC) in Mississippi, Office of Protected Resources (OPR), Restoration Center (RC), and National Centers for Environmental Information (NCEI)


18.Electronic monitoring (EM) as a sampling technology is being developed to help NOAA fisheries efficiently collect information on fish species, size, and catch events. Researchers are using EM hardware and software to improve the NOAA electronic logbook (eLog). They built several hardware test structures, developed and analyzed subject area specific machine learning algorithms, prototyped EM hardware, and evaluated EM software systems. They supplied information to NOAA NMFS on data requirements for use of the Google Cloud Platform and the NMFS National Image Library Initiative. The prototype hardware (cameras, computers, etc.) will be installed on a NOAA survey vessel, after which data will be collected and annotated. They are also working with Mote Marine Laboratory on a shark species identification pilot project.

Title, NGI Number: Develop Innovative Sampling Technologies, 21-NGI4-13

Performance Period: 10/01/2020 to 09/30/2022
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI:John Ball/Robert Moorhead, Mississippi State University
NGI Theme(s): Data Management, Ecosystem Management
Collaborators/Partners: NOAA NMFS SEFSC and Alaska Fisheries Science Center (AFSC), Mote Marine Laboratory, CVisionAI, and Saltwater Inc.


19.Building bioinformatics capacity is critical to address threats on ecosystem services, especially as genome-based techniques (termed ‘omics) are now the gold-standard for biological measurement. However, bioinformatics expertise has not kept pace with the generation of sequence data, creating created a data backlog and hindering the transition of data to actionable information. This project supports on-going efforts to develop 'omics-derived ecosystem indices for incorporation into models and a trained workforce that can use computational tools to analyze genomic databases. This includes analysis of the global Ocean Sampling Day dataset using bioinformatic tools in support of the Earth Microbiome Project, collaboration with international partners for publications, and getting back-logged data into the public domain. Additionally, there is analysis of ocean and animal microbiome (existing DNA sequences from Gulf of Mexico samples) and evaluation of a prototype autonomous underwater vehicle that can collect samples for 'omics analysis. The transfer of bioinformatics knowledge to students and workers is being done through presentations, workshops, and university courses (e.g., Applications of Biotechnology in Marine Biology).

Title, NGI Number: Bioinformatics to Aid Ecosystem Understanding, Research Transition, and Development of a Next-Gen Workforce, 17-NGI3-33

Performance Period: 10/01/2017 to 06/30/2022
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI:Shiao Wang, University of Southern Mississippi
NGI Theme(s): Climate Change and Climate Variability Effects on Regional Ecosystems, Coastal Hazards, Ecosystem Management, Data Management
Collaborators/Partners:

20.Building bioinformatics capacity infrastructure supports 'omics observations and characterizations of sites and microbiomes important to the sustainable use of ocean resources. This includes bioinformatic analysis to characterize microbial communities collected from the Gulf of Mexico, (rich in oil and natural gas) and from the Great Lakes (economic resource and source of drinking water), both of which are threatened by harmful algal blooms. Such characterizations will be integrated into a global database to extend the ability to classify microbial genomes from individual samples, such as microbes associated with energy reserves. Completed were the development and assessment of bioinformatics workflows (Tourmaline, an amplicon sequence processing workflow that uses QIIME 2 and Snakemake https://github.com/NOAA-AOML/tourmaline) and the application of workflows to characterize microbial communities in the Gulf of Mexico, the Red Sea, and the Great Lakes. Also developed were training and resources for bioinformatics expertise (workshops, updated university course Applications of Biotechnology in Marine Biology, and development of course on data science using Python available on GitHub and YouTube). Engagement with academic and governmental groups was done to develop and promote metadata and data standards and the development of a user-friendly visual interface to allow assignment of individual microbial genomes to sample type.

Title, NGI Number: Bioinformatics to Support Ecosystem Fisheries and Blue Economy ‘Omics Applications, 19-NGI3-71
Performance Period: 10/01/2018 to 09/30/2022
Funding support: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Shiao Wang, University of Southern Mississippi
NGI Theme(s): Climate Change and Climate Variability Effects on Regional Ecosystems, Ecosystem Management, Data Management
Collaborators/Partners:University of California San Diego, Harvard University, Broad Institute of Harvard and MIT, University of Oulu (Finland), University of South Carolina, University of Florida, King Abdullah University of Science and Technology (Saudi Arabia), Bangor University (UK), Northern Arizona University, Leibniz Institute (Germany), New York University Abu Dhabi (UAE)


21.Building ‘omics and bioinformatics capacity for reproducible and efficient analysis of environmental samples requires a data framework with metadata standards and a metadata quality control workflow, a sequence data quality control workflow, expanded amplicon reference sequence databases, and an improved amplicon processing workflow. This project produced a draft OAR 'Omics Data Management Plan to be published as a NOAA Technical Report and produced data and metadata standards (https://microbiomedata.org/) and a Tourmaline amplicon sequence analysis workflow version 2 (https://github.com/aomlomics/tourmaline). Two different magnetic bead DNA extraction protocols were developed and run on the KingFisher Flex bead-handling robot. PCR preparation, PCR cleanup, DNA dilution, and extraction prep protocols were developed and run on the Opentrons liquid handling robot. The 'omics lab at AOML was modernized, including the integration of the two robots for sample processing.

Title, NGI Number: Building NOAA ‘Omics and Bioinformatics Capacity for Reproducible and Efficient Analysis of Environmental Samples, 19-NGI3-78
Performance Period: 10/01/2019 to 09/30/2022
Funding support: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Luke Thompson, University of Southern Mississippi
NGI Theme(s): Ecosystem Management, Data Management
Collaborators/Partners:NOAA Great Lakes Environmental Research Laboratory, Pacific Marine Environmental Laboratory, Northwest Fisheries Science Center, Southeast Fisheries Science Center


22.‘Omics and bioinformatics tools support marine systems studies, NOAA missions, and the sustainable use of ocean resources. Scientists with expertise in these areas are building a foundation of infrastructure (adapting traditional and cloud HPC systems for bioinformatics), competence (cultivating bioinformatics skills in scientists), capacity (high-throughput analysis and improved standards, workflows, and databases), and application (analysis of ‘omics datasets). Infrastructure includes cloud computing strategy documentation, genomic databases, and repositories for bioinformatics code and ‘omics protocols. Workforce includes ‘omics meetings on topics of broad interest, technical workshops (Python, QIIME 2, metagenomics); and bioinformatics tutorials. Capacity includes reference databases and software to query them, environmental DNA (eDNA) metadata standards, quality control workflows, workflows for amplicon and shotgun sequence data, and a cloud-based eDNA and omics analysis platform. Application includes collection and analysis of fish eDNA datasets and eDNA data from the mesopelagic zone; analysis of harmful algal bloom datasets; and analysis of microbial communities from pelagic (metagenomes for hydrocarbon degradation potential) and benthic (gut microbiomes from methane ice worms) environments. Products include an OAR ‘Omics Data Management Plan, data and metadata standards (https://microbiomedata.org/),  data analysis tutorials (https://github.com/aomlomics/tutorials), and an updated Tourmaline amplicon DNA sequence analysis workflow (https://github.com/aomlomics/tourmaline).

Title, NGI Number : Advancing Bioinformatics Infrastructure with Standards, Workflows, and Databases, 20-NGI3-112
Performance Period: 10/01/2020 to 09/30/2022
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Paul Luke Thompson/Paul Mickle, Mississippi State University
NGI Theme(s) : Ecosystem Management, Data Management
Collaborators/Partners: Atlantic Oceanographic and Meteorological Laboratory (AOML)


23.Water quality assessments for Biscayne Bay, FL are being facilitated by improved understanding of nutrient concentrations and the addition of water quality data to hydrodynamic models. Analysis of field samples is helping researchers gain a better understanding of sources for and the spatial distribution of nutrient concentrations in the Coral Gables Waterway, a sub-watershed to Biscayne Bay. A Soil and Water Assessment Tool (SWAT), a watershed model that incorporates Artificial Neural Network Modeling, is being developed. Additionally, researchers develop recommendations for continued partner collaboration and resource management and provide information about processes associated with nutrient inputs to inform additional watershed studies. The Best Management Practices that the researchers created will allow for prioritization of municipal infrastructure projects.

Title, NGI Number: AOML-NGI South Florida Water Quality Analyses, 21-NGI4-16
Performance Period: 10/01/2016 to 09/30/2026
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Paul Mickle, Mississippi State University
NGI Theme(s): Ecosystem Management, Coastal Hazards, Climate Change and Climate Variability Effects on Regional Ecosystems
Collaborators/Partners: NOAA Ecosystem Assessment and Modeling Laboratory within the Ocean Chemistry and Ecosystems Division at AOML and CIMAS

24.The Gulf Coast Ecosystem Restoration Council (GCERC) funds projects and activities aimed at restoring the ecosystem and economy of the region following the Deepwater Horizon oil spill. To meet their RESTORE Act requirements, the GCERC is developing a metadata tool for their grant recipients and produces publications and communication materials for the science community and public audiences. Staff with expertise in scientific data stewardship, metadata requirements, and graphics design and development at the Northern Gulf Institute will collaborate with the NOAA National Centers for Environmental Information (NCEI) to support the GCERC efforts. They will assist in the development of metadata tools, templates, and standards and provide online training and support for their use by the GCERC and GCERC-funded grant recipients. They will also develop 508 compliant materials and graphics for scientific and technical publications and presentations and public outreach and engagement.

Title, NGI Number: Public Engagement Support and Metadata Tool and Training for the Gulf Coast Ecosystem Restoration Council (GCERC), NA18OAR4170438
Performance Period: 09/01/2018 to 08/31/2022
Funding Source: Mississippi-Alabama Sea Grant Consortium (MASGC) via NOAA Oceanic and Atmospheric Research (OAR) via National Centers for Environmental Information (NCEI)
PI/Co-PI: Paul Mickle, Mississippi State University
NGI Theme(s): Data Management, Ecosystem Management
Collaborators/Partners: NOAA National Centers for Environmental Information (NCEI)


25.Enhanced data stewardship, products, and services for NOAA programs that help link science to application is the goal of collaborative efforts of the Northern Gulf Institute and the National Centers for Environmental Information (NCEI). This involves the development and stewardship (including quality control and documentation review) of the long-term coastal data record and support for coastal science products, services, and activities. They will provide scientific and infrastructure support to facilitate environmental investigations, analyses, and predictions for the Gulf of Mexico ecosystem, focusing on habitat characterization, water quality, living marine resources, and coastal hazards and mitigation. They will also provide support for workforce training, updating computer systems, and data management optimization such as the development of reference environmental data records and techniques to synthesize and visualize data, disparate data for product generation, and enhance data discovery. Additionally, they will support extension and outreach of products and information services for federal and state coastal programs and formulation of public policy related to regional restoration activities. The Coastal Ecosystem Data Assembly Center (CEDAC), a tool under development, will be utilized to provide a unified public interface for timely, easy, and convenient public access to the data collections resulting from the Gulf recovery and restoration activities.

Title, NGI Number: Coastal Science Research, Data Development, and Information Services (Base Award), NA18OAR4170438
Performance Period: 09/01/2018 to 08/31/2022
Funding Source: Mississippi-Alabama Sea Grant Consortium (MASGC) via NOAA Oceanic and Atmospheric Research (OAR) via National Centers for Environmental Information (NCEI)
PI/Co-PI: Robert Moorhead/Paul Mickle, Mississippi State University
NGI Theme(s): Data Management, Ecosystem Management
Collaborators/Partners: NOAA National Centers for Coastal and Ocean Science (NCCOS), Natural Resource Damage Assessment (NRDA), National Marine Fisheries Service (NMFS), and Exploration and Research (OER)


26.High performance computing (HPC) supports NOAA missions, including environmental modeling that results in products and services upon which the public depends. The HPC system Orion at Mississippi State University is providing increased computational capability for NOAA research activities and supports 59 unique NOAA projects that involve 524 users who consume approximately 50 million wallclock-hours of CPU time per month. The system is a Dell C6420 cluster containing 1,800 nodes with a total of 3,600 Intel Xeon Gold 6148 processors (72,000 compute cores in aggregate) and 345 terabytes of RAM, a 10 petabyte high performance data storage system, and a Mellanox HDR InfiniBand interconnect. The system ranked as the 60th fastest system in the world in the TOP500 Supercomputer Sites November 2019 list and has a peak performance of 5.5 PetaFLOPS

Title, NGI Number: HPC Support for OAR, NA190OAR4590410
Performance Period: 10/01/2017 to 09/30/2023
Funding Support: NOAA Oceanic and Atmospheric Research (OAR)
PI/Co-PI: Trey Breckenridge, Mississippi State University
NGI Theme(s): Data Management

National Ocean Service (NOS)


27.Underwater gliders  are increasingly involved in routine, innovative, and emergency marine data collection to support operations and research and development efforts. Operating this glider technology requires specialized training. To meet that need, researchers are developing the curricula for a next-level Operator's Certificate (Tier 2) focused on underwater gliders. The certificate course is offered by the University of Southern Mississippi Uncrewed Marine Systems Program. The curricula, which are based on syllabi developed by the university and Perspecta with input from the U.S. Navy and NOAA, support three training courses (each worth three credits) for buoyancy glider operations. The inaugural training program (October 2021) incorporated the new curricula and associated materials, which included a recently acquired Hydroid 1000 m SeaGlider. Current plans include expanding the planning and navigation tools available as the course moves forward.

Title, NGI Number: Underwater Glider Operations and Science in the Gulf of Mexico: A Public-Private Partnership, 19-NGI3-93
Performance Period: 09/01/2018 to 07/31/2022
Funding Source: NOAA National Ocean Service (NOS)
PI/Co-PI: Steven Howden, University of Southern Mississippi
NGI Theme(s): Ecosystem Management
Collaborators/Partners: The Command Naval Meteorology and Oceanography Command and subcommand of the Naval Oceanographic Office, the Naval Undersea Warfare Center of the Naval Sea Systems Command, the Gulf of Mexico Coastal Ocean Observing System, and Perspecta 


28.Uncrewed Surface Vessels (USVs) provide a safe and efficient method for data collection that support hydrographic and oceanographic survey operations. Researchers acquired a CWorker 5 USV Sea Eagle, which was demonstrated at several events and research cruises. The Saildrone USV Surveyor was outfitted with a shallow water multibeam system and Inertial Navigation System and collected high resolution bathymetric data. The Saildrone USV Profiler was outfitted with a sound velocity profiler on a winch system, showing good potential for use in remote areas. A Seafloor Systems Echoboat USV was gifted to the center and outfitted with a multibeam sonar and batteries to match systems used by NOAA’s Navigation Response Teams and is being used as an experimentation and troubleshooting platform. Research continues into use of a multi-Global Navigation Satellite System (GNSS) for precise positioning. Lessons learned related to USV use are being developed for inclusion in Standard Operating Procedures. Also being developed are a local sub-net of GNSS receivers to compare with GCGC Real-Time Network.

Title, NGI Number: University of Southern Mississippi Mapping Center, 18-NGI3-58
Performance Period: 10/01/2016 to 07/31/2022
Funding Source: NOAA National Ocean Service (NOS)
PI/Co-PI: Brian Connon, University of Southern Mississippi
NGI Themes: Ecosystem Management, Coastal Hazards
Collaborators/Partners: NOAA Office of Coastal Survey (OCS), Gulf Coast Geospatial Center, ASV-L3 ASV Global, Kongsberg, R2Sonic, Saildrone, and Norbit


29.Ecosystem-based management (EBM) is an approach that resource managers have growing confidence in as well as the capacity to apply it. Scientific publications describe EBM application and supporting practices; however, there is little understanding for how EBM is used and understood in practice by resource managers in the U.S. Gulf of Mexico region. Researchers are addressing this knowledge gap by developing baseline data and information regarding if and how resource managers in the region actually use and understand EBM. They will interview and survey resource managers and develop case studies of when science has been created, used, and applied directly for EBM practices. Resource managers and case studies will include ecosystem-based fisheries management projects, marine ecosystem planning, watershed management and planning, and more general resource management projects. This work will provide a comprehensive understanding of the state of EBM practices and identify specific findings, insights, and generalizations about EBM.

Title, NGI Number: Assessing Ecosystem-Based Management Practices and Science-Informed Decision-Making in the Gulf of Mexico, 21-NGI3-135

Performance Period: 08/01/2021 to 05/31/2022
Funding Source: NOAA National Ocean Service (NOS)
PI/Co-PI: Kathleen Ernst, Florida State University
NGI Themes: Ecosystem Management, Effective and Efficient Data Management Systems Supporting a Data-Driven Economy
Collaborators/Partners: NOAA Resources and Ecosystems Sustainability, Tourist Opportunities, and Revived Economies (RESTORE) Science Program


30.Monitoring the Gulf of Mexico hypoxic zone helps advance the science that underpins its management by scientists, modelers, resource managers, and other stakeholders. To measure progress toward achieving nutrient management goals set out in the Gulf Action Plan, researchers conduct regular field verification of the hypoxic zone both east and west of the Mississippi River, collecting data during annual research cruises and information about watershed activities that affect downstream water quality and habitats. Those data are used to develop models that inform the Hypoxia Task Force goals for nutrient reduction to conduct forecasts and hindcasts with enhanced biogeochemical and hydrodynamic models. Recently, standard operating procedures were finalized for conducting the annual monitoring cruise and information was made available to resource managers who can provide guidance for restoration projects. Efforts continue to foster communication and coordination among working groups focused on nutrients in the Mississippi River, the Cooperative Hypoxia Assessment and Monitoring Program (CHAMP), partners, and stakeholders.

Title, NGI Number: Hypoxia National Office Technical Assistance, Observations, Monitoring, and Coordination, 21-NGI4-09
Performance Period: 10/01/2016 to 09/30/2022
Funding Source: NOAA National Ocean Service (NOS)
PI/Co-PI: Paul Mickle, Mississippi State University
NGI Theme(s): Ecosystem Management, Coastal Hazards
Collaborators/Partners: Louisiana office of Coastal Protection and Restoration; Mississippi Department of Marine Resources; Mississippi Department of Environmental Quality; NOAA NCCOS, NWS, and NMFS; Louisiana Sea Grant; Minnesota Sea Grant; Louisiana Universities Marine Consortium (LUMCON); Lake Pontchartrain Basin Foundation; the University of Southern Mississippi; and Dauphin Island Sea Laboratory


31.The promotion of geospatial technology to improve coastal communities is the goal of researchers involved with workforce training for technical and nontechnical users in geographic information systems (GIS), development of web-based geospatial tools for enhanced visualization and data dissemination, and creation of geospatial data. This effort serves the Mississippi Department of Environmental Quality (MDEQ) with development of high-resolution hydrography datasets. Two mobile classrooms offer workshops with both commercial and open source software covering topics from introductory GIS to multi-user database systems (https://www.gri.msstate.edu/GEO/). GeoCoast 3D Coastal Inundation Visualization application evaluates impacts of sea level rise on traffic patterns and infrastructure accessibility (https://geoproject.hpc.msstate.edu/GeoCoast3D/). A web-based GIS application for public use is compatible with all operating systems and provides tools to create data and text overlays as well as upload spatial datasets from GPS units (https://geoproject.hpc.msstate.edu/GeoDawg). Current application development efforts are focused on augmented reality for GeoCoast and multi-criteria decision analysis for coastal watershed erosion.

Title, NGI Number: Regional Geospatial Modeling, and NA19NOS4730207
Performance Period: 10/01/2016 to 09/30/2024
Funding Source: NOAA National Ocean Service (NOS)
PI/Co-PI: John Cartwright, Mississippi State University
NGI Themes: Coastal Hazards, Ecosystem Management
Collaborators/Partners: Coastal Conservation and Restoration Program, and the Marine Fisheries Ecology Program at the Mississippi State Coastal Research and Extension Center

National Environmental Satellite, Data, and Information Service (NESDIS)


32.Satellite products for improved thunderstorm predictions that provide advanced notice of heavy rain, high winds, and lightening is the goal of researchers making advancements to NOAA GOES-R Convective Initiation (CI) products that the National Weather Service (NWS) forecasts use. The “R” series of Geostationary Operational Environmental Satellite (GOES-R) provides real-time, high-resolution imagery and atmospheric measurements of Earth’s weather, oceans and environment, and monitoring of solar activity and space weather. Researchers maintain and improve the 0-1 hour GOES-R CI algorithm, provide product fields to government users of CI nowcast products, and maintain data feeds to NASA and NOAA. Updates and improvements allow the CI algorithm to work on mobile devices, make imagery more viewer friendly, identify potential false signals due to snow cover, and resolve issues related to domain changes and data ingestion. The unique nature of the algorithm to identify, track, and predict cloud growth across a satellite image has been enhanced. Under development is script to download data from Amazon Web Services for CI Product to run at night. This effort includes coordination with NASA’s Short-term Prediction Research and Transition (SPoRT) Center to facilitate transfer of CI-related products to end users.

Title, NGI Number: GOES-R Convective Initiation Product Support, 20-NGI3-129
Performance Period: 08/01/2020 to 07/31/2022
Funding Source: NOAA National Environmental Satellite, Data, and Information Service (NESDIS)
PI-Co-PI: John Mecikalski, University of Alabama Huntsville
NGI Themes: Coastal Hazards
Collaborators/Partners: NOAA Cooperative Institute for Research in the Atmosphere (CIRA) and NASA Short-term Prediction Research and Transition (SPoRT) Center


33.The Deep-Sea Coral Research and Technology Program (DSCRTP) collects, analyzes, and makes publicly available coral and sponge occurrence data and related physical/biological data; the program also develops products using those data such as predictive model outputs and publications. Scientists with the Northern Gulf Insitute and National Centers for Environmental Information (NCEI) are collaborating with DSCRTP scientists to develop a comprehensive end-to-end data management system that will identify, inventory, and provide stewardship of program-generated data from collection to long-term preservation. This effort involves development of the NOAA National Database for Deep Sea Corals and Sponges and innovative enhancements to its public interface for effective access to web mapping applications, search tools, and datasets (including photographic and video imagery and program activities). Additionally, code that are developed as well as tutorials associated with database features will be published. Data and graphical representation or analyses will be provided to support DSCRTP reports, publications, and to respond to external user requests (e.g., Fisheries Management Councils).

Title, NGI Number : Support to the Mission, Growth, and Impact of the Deep-Sea Coral Research and Technology Program (DSCRTP), 21-NGI4-14
Performance Period: 10/01/2021 to 09/30/2026
Funding Source:NOAA National Environmental Satellite, Data, and Information Service (NESDIS)
PI/Co-PI: Just Cebrian/Paul Mickle, Mississippi State University
NGI Theme(s): Data Management, Ecosystem Management
Collaborators: NOAA National Marine Fisheries, Ocean Exploration and Research Program


34.Exploring the deep ocean for national benefit is the mission of the NOAA Ocean Exploration (OER) program. Researchers with the Northern Gulf Institute are collaborating with the National Centers for Environmental Information (NCEI) to provide subject matter expertise for the development, enhancement, maintenance, and public availability of OER oceanographic data and video collections (Digital Atlas, Okeanos Explorer Atlas, Video Portal, ROV/Cruise Landing Pages, Benthic Animal Guide, and GIS services). They will provide stewardship for the storage, tracking, use, and policy-compliance of its collections working with the NCEI Cruise Information Management System (CIMS), Video Information Management Systems (VIMS), and Sampling Operations Database Application (SODA). This effort will report on and support field campaigns, data acquisition, and disposition; make recommendations for data management and use; assure quality of and archive incoming data; support development of new archive pipelines; and deliver data for custom requests. It will also generate annotated metadata records to increase data discoverability and reusability, present results and products to the ocean science community, and coordinate outreach activities through the Stennis Exploration Command Center.

Title, NGI Number: Support to the Mission, Growth, and Impact of the Ocean Exploration and Research Program, 21-NGI4-10
Performance Period: 10/01/2021 to 09/30/2026
Funding Source: NOAA National Environmental Satellite, Data, and Information Service (NESDIS)
PI/Co-PI: Just Cebrian/Paul Mickle, Mississippi State University
NGI Theme(s):Data Management, Climate Change and Climate Variability Effects on Regional Ecosystems; Ecosystem Management
Collaborators: NOAA National Centers for Environmental Information (NCEI)


35.The Coastal Ecosystem Data Assembly Center (CEDAC) is being developed as a resource for scientific data exchange that serves the needs of both data providers and users, including access to data management tools and training and a portal to upload data for archive staging. This effort will involve stewardship of the long-term coastal data record and its continued development to support Gulf of Mexico ecosystem research. The CEDAC will also provide a unified interface for timely, easy, and convenient public access to data collections resulting from recovery and restoration activities that followed the Deepwater Horizon oil spill. Innovative data stewardship solutions to enhance NOAA capabilities with data management, visualization, and dissemination will be developed as well as methods and tools to improve data discovery and access. Sea Grant extension specialists will conduct needs assessments with end users before product and services are developed and again afterwards to gain insights into making them more useful and user friendly. Sea Grant will also host trainings and workshops to increase awareness and use of CEDAC products and information services.

Title, NGI Number: Enhanced Coastal Data Development and Information Services: CEDAC, 17-NGI3-35
Performance Period: 07/01/2017 to 06/30/2022
Funding Source: NOAA National Environmental Satellite, Data, and Information Service (NESDIS)
PI/Co-PI: Robert Moorhead/Paul Mickle, Mississippi State University
NGI Theme(s): Data Management, Ecosystem Management
Collaborators/Partners: NOAA NCEI Oceanographic and Geophysical Science and Services Division (OGSSD) and the Mississippi-Alabama Sea Grant Consortium

National Marine Fisheries Service (NMFS)


36.The endangered smalltooth sawfish (Pristis pectinate) and the reduction or prevention of their mortality is the top action in the National Marine Fisheries Service Recovery Plan. Sawfishes are large shark-like rays with an elongated blade-like snout that can become entangled in gillnets and trawls, a leading cause of their population decline. To address NOAA recovery actions, researchers conduct sampling trips to attach SPOT satellite tags on adult smalltooth sawfish and collect life history information. The data will improve understanding about the population and reproductive status of adult sawfish, the habitats they frequent, and if these areas meet criteria for Critical Habitat listing. The data may reveal spatial and temporal distribution patterns, including mating sites and long-term residency and migration patterns, and if these occur in areas of commercial trawling and longlining. Knowing these connections can provide guidance on actions to reduce bycatch mortality, such as seasonally limiting access to specific areas and habitats. This effort includes the data collection on scalloped hammerhead sharks for ongoing federal stock assessments and conservation awareness through education and outreach. 

Title, NGI Number: Determination of Movement patterns and Reproductive Status of Adult Smalltooth Sawfish (and Scalloped Hammerhead Sharks), 21-NGI4-08
Performance Period: 10/01/2016 to 09/30/22
Funding Source: NOAA National Marine Fisheries Service (NMFS)
PI/Co-PI: Dean Grubbs, Florida State University

NGI Themes: Ecosystem Management, Climate Change and Climate Variability Effects on Regional Ecosystems
Collaborators/Partners: NOAA Office of Protected Resources (OPR), NOAA Fisheries, Bimini Biological Field Station, Disney Conservation Fund, Havenworth Coastal Conservation, and University of North Florida


37.Artificial Intelligence (AI) applied to fisheries digital media collected for assessments is making the data more assessable and usable. Researchers are organizing the media, which are housed at various NOAA NMFS laboratories and partnering agencies in the southeast US, and using AI to automate the detection and identification of fish species from video. They are compiling and archiving image libraries and associated manual annotations, collecting and digitizing historic video, and comparing human-based annotations with those generated by Video Image Analytics for the Marine Environment (VIAME) algorithms, which speeds up video processing time and quality control procedures. The annotation library and model iterations for fish detection and identification are available for viewing and use on Kitware’s VIAME web application. The researchers share results with NOAA fisheries labs to demonstrate how to use the fish tracking models and the VIAME applications for their project needs. The model’s ability to classify and track reef fish has improved, especially for high priority species such as snappers and groupers.

Title, NGI Number: Video and Imagery Data Management for Fisheries Assessments, 21-NGI4-11
Performance Period: 08/01/2020 to 09/30/2022
Funding Source: NOAA National Marine Fisheries Services (NMFS)
PI/Co-PI: Paul Mickle/Jack Prior, Mississippi State University
NGI Theme(s): Data Management
Collaborators/Partners: NOAA NMFS


38.The archival and storage of plankton samples for the Southeast Area Monitoring and Assessment Program (SEAMAP) is a continuing service provided by the University of Southern Mississippi at their NASA Stennis Space Center facility. The facility also stores samples collected during the NOAA Natural Resource Damage Assessment (NRDA) effort following the Deepwater Horizon oil spill. The Stennis facility provides a safe and secure archive for the plankton samples, which comprise the longest plankton time series for the Gulf of Mexico. Samples are available for loan to researchers upon request.

Title, NGI Number: Continuation of Secure Archival Storage for NOAA/NMFS Preserved Specimens at USM's Plankton Archival Facilities, 20-NGI3-130
Performance Period: 04/01/2017 to 07/31/2022
Funding Source: NOAA National Marine Fisheries Service (NMFS)
PI/Co-PI: Frank Hernandez, University of Southern Mississippi
NGI Theme(s): Data Management, Ecosystem Management
Collaborators/Partners: Southeast Area Monitoring and Assessment Program (SEAMAP) and NOAA Natural Resource Damage Assessment (NRDA)

National Weather Service


39.Improving tornado detection is the goal of researchers who are examining the effectiveness of infrasound, sound at wave frequencies beyond what humans can hear, to detect tornadoes. They are analyzing past tornadic storms to determine if attributes such as lightning and airflow can provide infrasound sources. After analyzing the 3-D airflow of the March 19, 2018 supercell storm and 60 km EF-2 tornado that passed within 10-30 km of three National Center for Physical Acoustics (NCPA) infrasound detector arrays, they found that the entire tornadic phase was detectable by ARMOR radar (University of Alabama at Huntsville), SR3 radar (University of Oklahoma), and the WSR-88D KHTX radar (National Weather Service). Once the dual Doppler analysis is complete, they will analyze lightning characteristics and integrate their findings with available data from wind profiling systems and radiosondes to develop a larger representation of the storm and its environment. 

Title, NGI Number: Evaluation and Improvements of Tornado Detection Using Infrasound Remote Sensing: Comparative Analysis of Infrasound, Radar, Profiler, and Meteorological Data Sets, and Potential Impacts on NOAA/NWS, 18-NGI3-59
Performance Period: 10/01/2018 to 07/31/2022
Funding Source: NOAA National Weather Service (NWS)
PI/Co-PI: Kevin Knupp, University of Alabama at Huntsville
NGI Theme(s): Coastal Hazards
Collaborators/Partners: University of Mississippi NCPA


40.Atmospheric River Reconnaissance (AR Recon) missions provide data, visualization, and web support to the NOAA Environmental Modeling Center (EMC) for their weather, water, and climate predictions. AR are weather phenomena that drive heavy rain events that often cause floods. Researchers completed a successful AR Recon mission using sensitivity tools to identify potential flight paths and developed several data impact evaluation tools based on AR analysis, including the first version of a new high resolution regional model called the Atmospheric River Analysis and Forecast System (AR-AFS). Data impact evaluation is done by comparing module runs of the Global Forecast System for control (with AR Recon data) and denial (without AR Recon data), and an AR analysis is done using data from the Global Ensemble Forecast System.

Title, NGI Number: Operational Data Impact Assessment and Support for Atmosphere River Reconnaissance, 21-NGI4-12
Performance Period: 10/01/2020 to 09/30/2022
Funding Source: NOAA National Weather Service (NWS), National Centers for Environmental Prediction (NCEP), and Environmental Monitoring Center (EMC)
PI/Co-PI: Keqin Wu, Mississippi State University
NGI Theme(s): Climate Change and Climate Variability Effects on Regional Ecosystems, Coastal Hazards
Collaborators/Partners: Center for Western Weather and Water Extremes (CW3E) and University of California San Diego

Recently Completed Projects

This page provides summaries of projects completed in the last three years (2021, 2020, 2019), organized by funding source. The first few words of each project summary are bolded so readers can see the issue or topic that a project addressed or a key component (e.g., technology or method) that it employed. Projects completed in years prior are available in the Projects & Publications Search (under the Research Tab).

PIs/Co-PIs: If your project summary needs correction, please send an email to maggied@ngi.msstate.edu.

Funding Sources:

Oceanic and Atmospheric Research (OAR)


1.A biophysical ocean modeling framework has been developed to increase our understanding of the impacts of climate variability on mortality of larvae of several coastal pelagic fishes. Researchers adapted the NEMURO (North Pacific Ecosystem Model for Understanding Regional Oceanography) for the Gulf of Mexico, coupled it with the Massachusetts Institute of Technology General Circulation Model (MITgcm), and validated it using zooplankton data and satellite-derived sea-surface chlorophyl. They also developed a Food Limitation Index (FLI) to quantitatively compare food availability and food requirement experienced by fish larvae. Simulations for past and present climate conditions help improve understanding of the variability of food-limiting conditions and the impact on fish larvae mortality. Results from the biophysical model developed are novel in that no lower trophic level ecosystem modeling studies have validated against a multi-decadal zooplankton dataset because zooplankton concentrations have not been quantified past isolated sampling events and biogeochemical models are often designed with only one or sometimes two zooplankton state variables. This work will facilitate better estimates of recruitment for fisheries that can also form the basis for applications in other management regions, and an improved understanding of the marine ecosystem and fishery response to climate variability and change.

Title, Number: Modeling Climate Impacts on Fish Larvae Mortality in the Gulf of Mexico, 18-NGI3-41
Performance Period: 07/01/2017 to 06/30/2020
Funding Source:  NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Steve Morey, Florida State University
NGI Themes:Climate Change and Climate Variability Effects on Regional Ecosystems
Collaborators/Partners: NOAA Southeast Fisheries Science Center (SEFSC), Consortium for Simulation of Oil-Microbial Interactions in the Ocean (CSOMIO), NASA


2.Estimates of fish abundance from age 0 through larval stage have been associated with a high degree of uncertainty. Researchers developed a simulation approach using a biogeochemical model for the Gulf of Mexico to estimate abundance and better understand environmental factors that influence larval abundance and mortality. The model uses new techniques to determine food limitation and starvation for larvae and impacts of climate change on larval survival, including hydrodynamic data from a 20-year reanalysis. While the model is based on the North Pacific Ecosystem Model for Understanding Regional Oceanography (NEMURO), researchers modified it for application to the Gulf of Mexico, based in part on recent shipboard observations, and an individual-based model (IBM) was incorporated to simulate the transport of fish larvae. An objective assessment found that this new biogeochemical model performs better than any other published to date. Results have been published on model simulations of variability and ecosystem and Atlantic Bluefin Tuna Larvae advection with mortality computed based on starvation, predation, and analyses of spawning and predation patterns.  This modeling approach is applied to evaluate the interannual variability in larval mortality and to estimate changes in abundance under future climate scenarios.

Title, Number: NOAA Fisheries and the Environment (FATE): Development of Environmentally Driven Larval Mortality and Age-0 Abundance Indices for a Suite of Coastal Pelagic Species in the Gulf of Mexico, 18-NGI3-52
Performance Period: 07/01/2019 to 06/30/2021
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Steve Morey, Florida State University
NGI Themes: Climate Change and Climate Variability Effects on Regional Ecosystems, Ecosystem Management
Collaborators/Partners: NOAA AOML, NOAA SEFSC, Florida A&M University, the University of Maryland Center for Environmental Science, Scripps Institution of Oceanography, and the University of Southern Mississippi


3.The Stepped-Frequency Microwave Radiometer Surface (SFMR) is the primary tool used for collecting aircraft-based estimates of the surface wind speed in tropical cyclones (TCs), which are used as input to numerical models and by National Hurricane Center TC forecasts. To further improve the accuracy of the SFMR algorithm, researchers collected additional measurements from hurricane reconnaissance flights and looked at variables that the algorithm was dependent upon to identify error sources. They identified a dependency of the SFMR algorithm accuracy on environmental (mid-latitude vs tropical) characteristics (SST, ambient air temperature). Analysis of thousands of dropsondes showed that the WL150 surface reduction factor for eyewall dropsondes and outer vortex dropsondes are different and that the relationships between upper-level winds and surface winds needed to be updated. They collected SFMR data during the 2018 hurricane season to begin analyzing the pitch dependency of the SFMR and found that significantly more data needs to be collected to quantify the relationship. The results of this study will be implemented in the 2020 operational SFMR algorithm update. 

Title, Number: Further Refinements to Stepped-Frequency Microwave Radiometer Surface Wind Measurements in Hurricanes, 17-NGI3-32
Performance Period: 10/01/2016 to 09/30/2019
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Mark Bourassa, Florida State University
NGI Themes: Climate Change and Climate Variability Effects on Regional Ecosystems, Coastal Hazards
Collaborators/Partners: NOAA/AOML Hurricane Research Division (HRD)


4.The Stepped-Frequency Microwave Radiometer (SFMR) collects aircraft-based estimates of the surface wind speed in tropical cyclones for use in National Hurricane Center forecasts. Areas for improvement to the accuracy of its observations have been identified, some of which this project addressed. Completed were the development of new guidance for the SFMR on the impacts of aircraft angle with respect to the surface; identification of rain-related aspects that were being attributed to wind speed, which were previously unknown; and comparisons of SFMR data to surface wind speed measurements from other instruments (dropsondes and aircraft-based radar systems), which revealed much larger variability in techniques than had been previously understood. The radars also depicted several features in the TCs that may explain discrepancies between the SFMR and wind speed data collected at the height of the aircraft. These findings provided forecasters at the National Hurricane Center with additional guidance for interpreting the SFMR surface wind speed and will be incorporated into an upcoming update to the SFMR observation processing to further increase the accuracy of the observations. 

Title, Number: Hurricane 3-D Wind Structure Analysis Using Stepped-Frequency Microwave Radiometer Surface Wind Measurements, 18-NGI3-53
Performance Period: 10/01/2018 to 09/30/2020
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Mark Bourassa, Florida State University
NGI Themes: Climate Change and Climate Variability Effects on Regional Ecosystems, Coastal Hazards
Collaborators/Partners: NOAA National Hurricane Center (NHC)


5.The planetary boundary layer (PBL) is the lowest level of the atmosphere with conditions that frequently and rapidly change in response to the Earth’s surface fluxes. These rapidly changing conditions are parameterized in the NOAA hurricane forecasting modeling system. Researchers are seeking to improve the NOAA modeling system and its products by identifying error sources, conducting validations, and analyzing case studies. This project will improve parametric formulations of the surface tropical cyclone winds equation to better represent wind decay after a hurricane reaches land. Currently, the extrapolation of parametric wind equations (20- to 34-knot winds) in the tropical cyclone outer-core contain a positive bias, resulting in over-specified surge inundation and wind gust impacts. New empirical equations are being developed for tropical cyclone wind profiles extending past the radius of 34-knot winds using surface sustained winds extracted from a University Corporation for Atmospheric Research (UCAR) hurricane reconnaissance flight dataset from 1997 to 2019. They developed a new evaluation framework to isolate error sources caused by PBL variations.  

Title, NGI Number: Examination of Hurricane Weather Research and Forecasting (HWRF) System at the Land and Ocean Interface, 19-NGI3-72
Performance Period: 10/1/2019 to 12/31/2021
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Xiaomin Chen, Mississippi State University
NGI Themes: Coastal Hazards
Collaborators/Partners: NOAA OAR/AOML Hurricane Research Division (HRD) and National Weather Service (NWS), Cooperative Institute for Marine and Atmospheric Studies (CIMAS), National Center for Atmospheric Research (NCAR), University Corporation for Atmospheric Research (UCAR), Cooperative Institute for Research in the Atmosphere (CIRA), University of North Carolina, Department of Homeland Security, Texas A&M University-Corpus Christi, and University of Oklahoma


6.The conditions that contribute to dangerous tornadoes are what meteorologists and social scientists collaboratively researched in the VORTEX-SE (Verification of the Origins of Rotation in Tornadoes EXperiment-Southeast) project. Activities included analysis of existing data, collection of field data pre- and post-tornados during the spring of 2017, and quality control of data. Field measurements were acquired from the Mobile Alabama X-band (MAX) radar, Mobile Integrated Profiling System (MIPS), Mobile Doppler Lidar and Sounding System (MoDLS), Rapidly Deployable Atmospheric Profiling System (RaDAPS), and balloon soundings on events of interest. Profiler and radar data were analyzed to document the variability in low-level clouds, thermodynamics, and wind shear for cold-season tornado events.

Title, Number: Core Infrastructure Enhancements, Operations, and Preliminary Research Activities Supporting VORTEX-SE 2017 Field Campaign Activities - Phase 2: Operations and research supporting the VORTEX-SE 2017 field campaign, 16-NGI3-11
Performance Period: 10/01/2016 to 09/30/2018
Funding Source: NOAA Oceanic and Atmospheric Research (OAR)
PI/Co-PI: Kevin Knupp, University of Alabama Huntsville
NGI Themes: Climate Change and Climate Variability Effects on Regional Ecosystems, Coastal Hazards
Collaborators/Partners: NOAA National Severe Storms Laboratory (NSSL)


7.Factors that contribute to tornado formation were investigated by researchers who conducted field observations over northern Alabama from November 2017 to May 2018, followed by initial analysis and quality control. They examined horizontal shearing instability with tornadic quasi-linear convective systems (QLCSs) and of stratocumulus cloud behavior and their interaction with the boundary layer during cold season tornado events. They also completed analysis of data collected during previous VORTEX-SE field campaigns in 2016 and 2017, including analysis of wind profiler and balloon sounding data sets collected during a violent tornado over Sand Mountain. Completed work included an initial examination of horizontal shearing instability (HIS) within QLCSs, characterization of stratocumulus clouds during cool season tornado events, and evaluation (risk reduction) of observational strategies for a future experiment. This effort supported the development of a preliminary hypotheses regarding the propagation characteristics, internal structure and dynamical behavior, and development of mesovortices within high-shear, low-cape (HSLC) QLCSs.

Title, Number: VORTEX-SE 2018 Field Campaign Activities: High-CAPE, Low-Shear Emphasis, 17-NGI3-31
Performance Period: 08/01/2017 to 07/31/2019
Funding Source: NOAA Oceanic and Atmospheric Research (OAR)
PI/Co-PI: Kevin Knupp, University of Alabama Huntsville
NGI Themes: Climate Change and Climate Variability Effects on Regional Ecosystems, Coastal Hazards
Collaborators/Partners: N/A


8.The processes that fuel thunderstorm growth were investigated by researchers who conducted twelve field campaigns from December 2019 to April 2020. Their goal was to document mesoscale variability of convective available potential energy (CAPE) and wind shear, particularly with the atmospheric boundary layer, and to analyze data acquired in previous. The field work included radiosonde balloon launches, deployment of the Mobile Alabama X-band radar and mobile atmospheric profiling systems, (including the Rapidly Deployable Atmospheric Profiling System and Mobile Doppler Lidar and Sounding System), and the Mobile Meteorological Measurement Vehicle. Analysis continued for two datasets acquired earlier in 2019 and were started for several of the newly acquired data. A unique data set showing relationships between Doppler radar measurements at very close range and tree damage (via ground and aerial surveys) was acquired, with further analysis to follow to establish a relationship between wind speed and degrees of damage to trees.

Title, Number: VORTEX-SE 2019 Field Campaign Activities: Mesoscale Variability of CAPE, SHEAR, and PBL Characteristics, 18-NGI3-40
Performance Period: 09/01/2018 to 08/31/2020
Funding Source:  NOAA Oceanic and Atmospheric Research (OAR)
PI/Co-PI: Kevin Knupp, University of Alabama Huntsville
NGI Themes: Climate Change and Climate Variability Effects on Regional Ecosystems, Coastal Hazards
Collaborators/Partners: NOAA Earth System Research Laboratory


9.Understanding the potential for severe storms in the Southeast, Midwest, and Great Plains is what researchers investigating Quasi-Linear Convective Systems (QLCSs) aimed to improve. This was done through the development of methodologies or use of new data sets to advance understanding of mesoscale variability (MV) and boundary layer variability (BLV) associated with these systems, specifically the Afternoon to Evening Transition (AET) process. A real-time prototype high-resolution Velocity Azimuth Display (HR-VAD) wind product was developed (https://www.nsstc.uah.edu/armor/webimage/viewer.html), and wind profiles obtained from it were compared with wind profiles from wind profiling systems nearby, with very good correlation between the two measurements. This preliminary research shows promise in advancing knowledge of boundary layer structure and processes in advance of severe QLCSs.  A related effort was to characterize the spatial variability in the atmospheric boundary layer (ABL) and lower atmosphere produced by cooling from shading by low-level clouds and by evaporation from rain showers in the vicinity of potential tornadic storms, and the impact of this evaporational cooling.

Title, Number: Advancing Meteorological and Operational Detection of Mesoscale Kinematic and Thermodynamic Variability, 18-NGI3-49
Performance Period: 09/01/2018 to 08/31/2020
Funding Source: NOAA Oceanic and Atmospheric Research (OAR)
PI/Co-PI: Kevin Knupp, University of Alabama Huntsville
NGI Themes: Climate Change and Climate Variability Effects on Regional Ecosystems, Coastal Hazards
Collaborators/Partners: NOAA Physical Sciences Laboratory (PSL)


10.Investigating tornado formation includes analysis of storms that spawn unusual or unexpected tornados. From January to April 2021, researchers deployed mobile facilities to collect data on atmospheric boundary layer evolution, cloud characteristics, and kinematic structure and evolution that preceded thunderstorms that formed along or ahead of cold fronts (known as Quasi-Linear Convective Systems, QLCS). They also analyzed pre-storm conditions for 40 cold season events from 2005 to 2021 and initiated case studies to examine the internal structure of two severe QLCSs (11/18/2017 and 02/12/2020). Included in their studies is the 03/03/2020 tornadic storm that devastated central Tennessee. Additionally, they conducted inter-comparisons of wind profiles derived from various systems (radar wind profilers, Doppler lidar, Doppler sodar, and scanning Doppler radars). Each case included analyses of dual Doppler radar data, environmental data from profiling systems and balloon soundings, and the kinematics of QLCS updrafts and downdrafts using vertically pointing Doppler radar data. 

Title, Number: VORTEX-SE 2020 Field Campaign Activities: Observations of the Environment and Evolution of Non-Classical Tornadic Storms, 19-NGI3-88
Performance Period: 09/01/2019 to 08/31/2021
Funding Source: NOAA OAR
PI/Co-PI: Kevin Knupp, University of Alabama at Huntsville
NGI Themes: Climate Change and Climate Variability Effects on Regional Ecosystems, Coastal Hazards
Collaborators/Partners: NOAA Earth System Research Laboratory (ESRL)


11.A machine learning-based forecast for tropical cyclone rapid intensification (RI) was built as a first effort at implementation in an operational RI forecast task. This novel unsupervised learning technique employed Global Forecast System analyses to identify features that are most helpful in discriminating RI and non-RI environments. To develop a new classification predictor set, researchers identified predictors to emphasize outer band structures versus inner-core structures of tropical cyclones, and then they retained and added the optimal discriminating fields to the existing SHIPS-RII predictors (currently used operationally to make RI forecasts). A fully cross-validated support vector machine (SVM) classifier was built from these predictors to predict Atlantic RI on 3,605 tropical cyclone timesteps. They tested this scheme in the Joint Hurricane Testbed experiments at the National Hurricane Center, with results indicating skill improvements of up to 18% better than climatology (roughly a 20% improvement over the performance baseline seen in the SHIPS-RII). Afterwards, the classifier was tested on 2017-2019 Atlantic Hurricane season cases to identify its performance in true forecast mode. Testing and evaluation will continue. .

Title, Number: Transition of Machine-Learning Based Rapid Intensification Forecasts to Operations, NA17OAR4590140
Performance Period: 07/01/2017 to 06/30/2020
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Andrew Mercer, Mississippi State University    
NGI Themes: Coastal Hazards
Collaborators/Partners: NOAA National Hurricane Center (NHC)


12.A digitized ranking index to assess tropical cyclone forecast products has been developed to facilitate decision-making on allocating resources. The validation technique makes the tedious task of product validation easier and increases model assessment efficiency. The 15 metrics used are a blend of relative scale, absolute scale, similarity measurement, and outlier characteristics which capture a range of unique error attributes. This method can also assess track error by vector direction and magnitude, isolating ambiguous model deficiencies based on the traditional absolute error distance calculation. During this process, an improved Kurihara vortex filter (required for shear calculations) was developed for higher-resolution models. Validation and case study analyses were performed on NOAA Hurricane Weather Research and Forecasting (HWRF) model products and experimental products (e.g., HWRF-HYCOM, HEDAS, and basin-scale HWRFT).

Title, Number: Examination and Validation of Reconnaissance Field Program Data in Multiple HWRF Framework, 18-NGI3-57
Performance Period: 10/01/2016 to 09/30/2019
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Pat Fitzpatrick, Mississippi State University
NGI Themes: Coastal Hazards, Data Management
Collaborators/Partners: NOAA OAR/AOML Hurricane Research Division (HRD), National Weather Service (NWS) National Centers for Environmental Prediction (NCEP) Environmental Modeling Center (EMC), and Climate Prediction Center (CPC)


13.New capabilities for the National Water Model (NWM) were made possible by the implementation of the model within the Unified Forecast System (UFS) and development of applications to water-related issues across the Southeast US. Researchers implemented and tested the NWM over sub-domains within this region focus on data flow and coupling methods, calibration of model parameters, and assessment of output accuracy and precision in short-range (hours to days) and medium-range (days to ~two weeks) simulations. This effort included hydrologic simulations at these time scales to provide water-related quality and quantity information. Evaluations were conducted on the NWM’s ability to address extreme conditions such as flood and drought and to address data needs for simulating a variety of hydrologic conditions, including groundwater withdrawals for municipal and agricultural uses, land use, leaf area index, and soil moisture values and their influence on the precision and accuracy of NWM output. A parallel version of the WRF-Hydro model with the same configuration and parameterization as the medium-range NWM operational framework was compiled and tested; the sensitivity of near-surface temperature and moisture patterns over the Southeast US was quantified within the WRF-Hydro model framework; and historical NWM output compared against observed recorded data during low flow events.

Title, Number: Developing New Capabilities and Research Applications for the National Water Model Over the Southeastern US, NA19OAR4590411
Performance Period: 09/01/2019 to 08/31/2021
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Jamie Dyer/Andrew Mercer, Mississippi State University
NGI Themes:Climate Change and Climate Variability Effects on Regional Ecosystems, Coastal Hazards
Collaborators/Partners: NOAA National Centers for Environmental Prediction (NCEP) Environmental Modeling Center (EMC)


14.High-resolution modeling of Ocean Acidification for the Gulf of Mexico and North Atlantic using a 13-component biogeochemical model was modified to include an additional carbon module that simulated dissolved inorganic carbon and total alkalinity. Using the expanded model with the carbon module, researchers described surface inorganic carbon system variables and sea–air CO2 fluxes in coastal and ocean domains of the Gulf of Mexico. Model results indicated that seasonal changes in surface pCO2 are strongly controlled by temperature across most of the Gulf of Mexico, except in the vicinity of the Mississippi–Atchafalaya River system delta, where runoff largely controls changes in dissolved inorganic carbon and total alkalinity. Further, the model results also showed that seasonal patterns of surface aragonite saturation state are driven by seasonal changes in dissolved inorganic carbon and total alkalinity, and reinforced by the seasonal changes in temperature. This model provides a tool to address questions related to ocean acidification and other processes that may impact the Gulf of Mexico and its natural resources.

Title, Number: High-Resolution Modeling of the Ocean Acidification in the East and Gulf Coasts of the U.S., 18-NGI3-43
Performance Period: 03/01/2018 to 07/31/2019
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Frank Hernandez, University of Southern Mississippi
NGI Themes: Climate Change and Climate Variability Effects on Regional Ecosystems
Collaborators/Partners: NOAA Southeast Fisheries Science Center (SEFSC)


15.To improve communication of tornado warnings to deaf, blind, or deaf and blind people, researchers conducted interviews with these populations. Findings from blind participants are discussed in a webinar hosted by the Centre for Crisis Studies and Mitigation at the University of Manchester (https://www.youtube.com/watch?v=lHIFh7sZPbQ) and included a desire for more geographic description in tornado warnings with information that is neighborhood specific with details on trajectory (where the tornado will be and when). The lack of audio for warnings that scroll at the bottom of television programs posed a barrier to some. Some reported not having shelter or a lack of transportation to get to a shelter since they could not drive themselves. Also discussed were preferences for methods to receive warnings (phone, television, text) and the amount of detail in warnings. Findings from deaf and hard-of-hearing participants are discussed in a webinar hosted by the National Weather Association (https://www.youtube.com/watch?v=FORkpRPXklk) and included issues related to insufficient closed captioning causing some to use a variety of other sources to alleviate confusion. Suggestions to improve tornado warnings involved the use of an ASL interpreter live for local television coverage.

Title, Number: Improving Accessibility and Comprehension of Tornado Warnings in the Southeast for the Dead, Blind, and Deaf-Blind, NA17OAR4590198
Performance Period: 09/01/2017 to 08/31/2020
Funding Source: NOAA Oceanic and Atmospheric Research (OAR) Atlantic Oceanographic and Meteorological Laboratory (AOML)
PI/Co-PI: Kathleen Sherman-Morris, Mississippi State University
NGI Themes: Coastal Hazards
Collaborators/Partners:

National Ocean Service (NOS)

No projects completed in 2021, 2020, 2019

National Environmental Satellite, Data, and Information Service (NESDIS)


16.Video data of the Gulf of Mexico seafloor are collected by NOAA using the remotely operated vehicle (ROV) Deep Discover aboard the Okeanos Explorer, and researchers have enhanced access to and usability of this data. They generated and tested Python scripts that created maps of the seafloor viewshed and the seafloor substrate distribution along the full extent of the ROV dives. The scrips extracted ROV navigation and video annotation data from NOAA datasets and yield GIS digital maps that comply with the Coastal and Marine Ecological Classification Standard (CMECS). The researchers also generated standard operating procedures for the Python scripts that automate the generation of color-coded seafloor substrate maps and resultant GIS polygon files from ROV and shipboard data and will make all project code available through a GitHub public repository. The ROV video data provided the base for a model of comprehensive digital mapping of seafloor environmental parameters, including ecological observations.

Title, Number: Geospatial Analysis of Deep-Sea Environments using ROV Video Data with the Coastal and Marine Ecological Classification Standard (CMECS), 19-NGI3-79
Performance Period:09/01/2019 to 08/31/2021
Funding Source: NOAA National Environmental Satellite, Data, and Information Service (NESDIS) National Centers for Environmental Information (NCEI)
PI/Co-PI: Adam Skarke/Jacob Freemen, Mississippi State University
NGI Themes: Data Management
Collaborators/Partners: NOAA NCEI, National Centers of Coastal Ocean Science (NCCOS), Office of Ocean Exploration and Research (OER), and the Deep-Sea Coral Research and Technology Program (DSCRTP)


17.Calculations for tropical cyclone intensification was sought by researchers using a product that merges Geostationary Lightning Mapper (GLM) data with ground-based observations in a Bayesian manner for a ratio of intracloud flashes to cloud to ground flashes. They trained and validated a random forest model to estimate the probability a flash is intracloud, based on optical attributes, and applied the model to tropical cyclone case studies for 2019 and 2020 to investigate its relationship to tropical cyclone intensification. An analysis of the case studies followed along with the development of a GLM beta data set with near real time capabilities that contain the probability a flash is intracloud. Their work suggests there is a signal in the cloud flash fraction that relates to tropical cyclone intensification. The cloud flash fraction (CFF) product will be developed further into the operational environment, including the exploration of suitable time steps in which to display the product to forecasters.

Title, Number: Bayesian Merging of GLM Data with Ground-Based Networks, 19-NGI3-85
Performance Period:08/01/2017 to 07/31/2020
Funding Source:  NOAA National Environmental Satellite, Data, and Information Service (NESDIS)
PI/Co-PI: Phillip Bitzer, University of Alabama Huntsville
NGI Themes: Climate Change and Climate Variability Effects on Regional Ecosystems, Coastal Hazards
Collaborators/Partners: NOAA National Weather Service (NWS)


18.The on-orbit calibration and validation of satellite ocean products was established for the VIIRS (Visible Infrared Imaging Radiometer Suite) on the NOAA Suomi National Polar–Orbiting Preparatory Project (SNPP) satellite. This effort supported the improvement of ocean color products (water leaving radiance, chlorophyll, and bio-optical properties) that enhance the monitoring of coastal and open waters. As members of the NOAA Joint Polar Satellite System (JPSS) calibration and validation (calval) team, this project team coordinated the calibration of ocean satellite products and tracking the stability of the VIIRS sensor and satellite products. They investigated the sensor characterization and processing software used to derive ocean products and to evaluate the long-term trends of the sensor calibration for processing software. They collected measurements for several cruises; maintained a data stream on the wave-current information system (WavCIS) for NOAA, NASA, and others; and provided calibration data sets for validation of ocean color products for the NOAA VIIRS sensor. The WavCis platform was updated to sensor SN638 and matchup of VIIRS inherent optical properties with cruise flowthrough data for the Bonnie Carrier cruise (Feb 2016) and other cruises that year and in 2017. The calval team participated in the Okeanos Explorer 2018 cruise and collected in situ data for VIIRS calibration and validation followed by data analysis with NOAA team cruise members.  

Title, Number: Calibration and Validation of NOAA VIIRS Ocean Products for Monitoring Oceans, 18-NGI3-51
Performance Period: 10/01/2019 to 12/31/2019
Funding Source: NOAA National Environmental Satellite, Data, and Information Service (NESDIS)
PI/Co-PI: Bob Arnone, University of Southern Mississippi
NGI Themes: Data Management, Ecosystem Management
Collaborators/Partners: NOAA-STAR Center for Satellite Applications and Research, NASA Goddard, Naval Research Laboratory, Louisiana State University, City College of New York, National Institutes for Standards and Technology, University of Southern Florida, UMB- University of Mass Boston, University of Miami, Oregon State University, Columbian University (LAMONT), Joint Research Council (Italy), Gulf of Mexico Research Initiative USM CONCORDE project, NOAA National Marine Fishers Service, and Naval Research Laboratory


19.Scientific support for partner agencies was provided by the Northern Gulf Institute (NGI) through expertise in data management and stewardship and development of products and services for coastal ecological and observational data and information. The NGI provided data management expertise for the National Marine Fisheries Service Deep Sea Coral Research and Technology Program (DSCRTP), National Centers for Coastal and Ocean Science, the Office of Response and Restoration working with the Natural Resources Damage Assessment, and the Ocean Exploration and Research Program. The NGI reviewed and updated the Data Management Best Practices document for the National Centers for Environmental Information (NCEI) Coastal Data Development (CDD) Program to support the long-term coastal data record and coordinated data management and visualization activities across Ocean Exploration and Research (OER) Divisions. 

Title, Number: Enhanced Coastal Data Development and Information Services: Scientific Support for Partner Agencies, 17-NGI3-38
Performance Period: 07/01/2017 to 09/30/2019
Funding Source:  NOAA National Environmental Satellite, Data, and Information Service (NESDIS)
PI/Co-PI: Steve Ashby, Mississippi State University
NGI Themes: Data Management, Ecosystem Management
Collaborators/Partners: NOAA RESTORE Science Program; RESTORE Council; National Academies of Science Gulf Research Program; MS/AL Sea Grant Consortium; the Damage Assessment, Remediation, and Restoration Program (DARRP); Naval Oceanographic Office; Leidos for Advanced Naval Technology Exercise; Florida Fish and Wildlife Research Institute; Alabama Department of Public Health; Mississippi Department of Marine Resources; Texas Parks and Wildlife Department; Gulf of Mexico Alliance; and Gulf of Mexico Research Initiative and GRIIDC.

National Marine Fisheries Service (NMFS)


20.Coastal hydrographic water column data are available as a continuous time series of temperature, salinity, depth, and current velocity collected from 2004 to the present from a small coastal ocean observing system (FOCAL WE-CP buoy) 20-25 kilometers southwest of Mobile Bay. This mooring operation represents the longest running time series of coastal hydrographic water column data in the Mississippi Bight and one of the longest in the entire Gulf of Mexico. However, data collection has typically been derived from process orientated studies, providing support for discrete periods of time, which has generated inconsistencies in data processing and organization. After several data management actions (organize the historic data collections from the mooring system and provide direct access to these historical data in conjunction with the real-time data from the FOCAL WE-CP buoy), the data are now available at https://accession.nodc.noaa.gov/0203749. The project increased the application of the historical data by new users from research institutions across the U.S. as well as by local and regional agencies to address issues related to ecosystem dynamics (e.g. fisheries populations, hypoxia) and extreme events (marine heatwaves, hurricanes). 

Title, Number: Improving Historical Data Access for Coastal Application, 18-NGI3-61

Performance Period: 10/01/2018 to 06/30/2020
Funding Source:  NOAA National Marine Fisheries Service (NMFS)
PI/Co-PI: Brian Dzwonkowski, Dauphin Island Sea Lab
NGI Themes: Data Management, Ecosystem Management
Collaborators/Partners: NOAA National Centers of Environmental Information (NCEI)
National Weather Service (NWS)


21.The NOAA National Data Buoy Center (NDBC) has an improved monthly data archiving process that now takes less time and has fewer errors. These improvements are the result of two new custom-made software packages (Java GUI applications using JavaFX and NetBeans) with python scripts, guides, and one-page summaries that are user-friendly, reliable, efficient, and sustainable. The software and scripts streamline the overall archiving process, generate missing sensor metadata, authenticate station location, visualize metadata and processed data, and perform quality control. The improvements allow NDBC to consistently disseminate high quality data collected by their C-MAN and Weather Buoy coastal ocean observing networks. Additionally, this effort added valuable sensor metadata and important station location authentication features.

Title, Number: Improvements to NDBC Weather Buoy/C-MAN archive process, 19-NGI3-75
Performance Period: 09/01/2019 to 02/28/2021
Funding Source: NOAA National Weather Service (NWS)
PI/Co-PI: Just Cebrian, Mississippi State University
NGI Themes: Data Management
Collaborators/Partners: NOAA NDBC
22.The Social Science Applications for Coastal Resiliency (SSACR) curriculum was developed and delivered as a week-long course to weather, water, environmental, and emergency management professionals working in various NOAA programs and offices. Participants learned about the structure and methodologies of applied social science research that complements the needs of the weather and water enterprises to incorporate human factors analysis. The course included readings followed by lectures and discussion about the nature of social science research, the ethics of such research, statistics used in data analysis, the tools and techniques used by social scientists, case examples, and how reliability and validity are addressed in various methods. Applied examples covered the societal understanding of water, heavy downpour events, mudslides, debris flows, droughts, and water quality. Preparing NOAA staff to think about how to pursue data and evidence about human behavior in the pursuit of their scientific duties in collaboration with social scientists will enhance their operations.

Title, Number: Social Science Applications for Coastal Resiliency (SSACR), 19-NGI3-74
Performance Period: 10/01/2019 to 12/31/2020
Funding Source:  NOAA National Weather Service (NWS)
PI/Co-PI: Laura Myers, Dauphin Island Sea Lab
NGI Themes: Coastal Hazards
Collaborators/Partners: Various NOAA programs


23.Understanding environments conducive to significant tornadoes was the goal of researchers assessing variability and the role of surface heterogeneity and mesoscale boundaries on the southeastern severe storm environment using mobile tropospheric soundings during the VORTEX-SE project. Completed were atmospheric profiles across a distinct agriculture / forest boundary where improvements in local environmental shear were noted over the agricultural region, likely due to a slightly less turbulent flow in the lower planetary boundary layer (PBL). However, surface instability across this boundary showed distinct changes where the agricultural region showed nearly twice the convective available potential energy when compared to the forested region. The greater instability was generated through slight increases in low-level atmospheric moisture over the agricultural landscape. While limited in scope, this suggests that updrafts rooted in the PBL may respond to sudden increases or decreases in instability which has been tied to tornado genesis.

Title, Number: Mesoscale Variability Experiment Using Full Tropospheric Soundings, 18-NGI3-50
Performance Period: 10/01/2018 to 09/30/2019
Funding Source: NOAA National Weather Service (NWS)
PI/Co-PI: Mike Brown, Mississippi State University
NGI Themes: Climate Change and Climate Variability Effects on Regional Ecosystems, Coastal Hazards
Collaborators/Partners:


25.Atmospheric River Reconnaissance (AR Recon) missions provide data, visualization, and web support to the NOAA Environmental Modeling Center (EMC) for their weather, water, and climate predictions. AR are weather phenomena that drive heavy rain events that often cause floods. Researchers completed a successful AR Recon mission using sensitivity tools to identify potential flight paths and developed several data impact evaluation tools based on AR analysis, including the first version of a new high resolution regional model called the Atmospheric River Analysis and Forecast System (AR-AFS). Data impact evaluation is done by comparing module runs of the Global Forecast System for control (with AR Recon data) and denial (without AR Recon data), and an AR analysis is done using data from the Global Ensemble Forecast System.

Title, NGI Number: Operational Data Impact Assessment and Support for Atmosphere River Reconnaissance, 20-NGI3-115
Performance Period: 10/01/2020 to 12/31/2021
Funding Source: NOAA National Weather Service (NWS), National Centers for Environmental Prediction (NCEP), and Environmental Monitoring Center (EMC)
PI/Co-PI: Robert Moorhead/Keqin Wu, Mississippi State University
NGI Theme(s): Climate Change and Climate Variability Effects on Regional Ecosystems, Coastal Hazards
Collaborators/Partners: Center for Western Weather and Water Extremes (CW3E) and University of California San Diego

Other-Funded Projects


25.Improved representation of mixing processes in oil plume dispersal models was sought by researchers who investigated linkages between the vertical distribution of turbulent mixing, bathymetry characteristics, and physical forcing phenomena of the northern Gulf of Mexico. Using gliders, a vertically-sampling turbulence profiler, a CTD Rosette, and moorings, field data were collected on ocean turbulence, velocity, and stratification from the surface to 1000 m water depth. The anticipated linkages were expected to show a quasi-stationary response to quasi-stationary flow over the steep and rough topography of the northern Gulf of Mexico. Instead, based upon moored time series observations, the response at the local diurnal (once a day) / inertial (once a pendulum day) time scale is fundamental. For the modeling community, this means that to get the instabilities right, the structure of the boundary layer must be right, and even ultra-high regional models lack this resolution. The turbulence and high frequency moored data enable a better understanding of the boundary layer structure in the northern Gulf of Mexico. This insight has been and is being communicated to the scientific community.
Title, Number: Understanding How the Complex Topography of the Deep-water Gulf of Mexico Influences Water-column Mixing Processes and the Vertical and Horizontal Distribution of Oil and Gas after a Blowout, 16561900/A101430
Performance Period: 01/01/2019 to 12/31/19    
Funding Source: Gulf of Mexico Research Initiative
PI/Co-PI: Zhankun Wang, Mississippi State University
NGI Themes: Coastal Hazards
Collaborators/Partners: Texas A&M University, Woods Hole Oceanographic Institution


26.The Gulf of Mexico Research Initiative (GoMRI) received administrative support from NGI staff with expertise in information systems design and management and science communication. They developed and managed the GoMRI Research Information System or RIS (https://research.gulfresearchinitiative.org) and the Education Website (https://education.gulfresearchinitiative.org/); produced a steady flow of vetted, original content for the GoMRI website (https://gulfresearchinitiative.org/); and provided communication and administrative support for the GoMRI Research Board and Chief Scientist. The RIS tracked programmatic data for all GoMRI funded research projects, personnel, and publications and presented that information in a public web portal. The Education Website houses resources for formal and informal education use that were developed through GoMRI-funded activities. The website articles provided content for other GoMRI outreach efforts, such as social media channels, quarterly newsletters, bi-weekly eNews, and presentations. Additionally, they co-authored several papers published in the 2021 Oceanography special issue featuring GoMRI (https://tos.org/oceanography/issue/volume-34-issue-01).

Title, Number: Gulf of Mexico Research Initiative Support Project, 231637-00
Performance Period:01/01/2017 to 12/31/2021
Funding Source: Gulf of Mexico Research Initiative via Gulf of Mexico Alliance
PI/Co-PI: Jay Ritchie/Maggie Dannreuther, Mississippi State University
NGI Themes: Climate Change and Climate Variability Effects on Regional Ecosystems, Coastal Hazards, Ecosystem Management, Data Management
Collaborators/Partners: American Institute of Biological Sciences, Consortium for Ocean Leadership, Sea Grant programs across the Gulf of Mexico region, and Texas A&M University Corpus Christy



Projects & Publications Search

Under Development!

The project and publications search tool is currently a beta version. For questions/concerns related to the functionality of this tool, please email Clay Hill (chill@hpc.msstate.edu).

Entries for projects and publications are currently being added, starting with most recent and working back. For content-related questions/concerns, please email Maggie Dannreuther (maggied@ngi.msstate.edu).

Proposal Development Guidance

A Principal Investigator wishing to submit a proposal through NGI should work with the sponsored programs office at his/her institution to submit the proposal package electronically to the Program Office. The complete proposal package should consist of the following:

  • Cover Sheet
  • Detailed Budget in Microsoft Excel format (template)
  • Detailed Budget Narrative (NOAA budget guidelines)
  • Project Narrative to include the following:
    • Description of Work - Research Plan
      1. Introduction/Narrative - Information contained in this section of the proposal should provide background information and significance of the proposed research.
      2. Specific aims/milestones - Information contained in this section of the proposal should provide the proposed goals and expected outcomes. It should also show when the researcher expects to reach the proposed goals and outcomes.
      3. Relationship to NOAA Goals - Information contained in this section of the proposal should show how the proposed research relates to the current NOAA Research Goals identified by the Cooperative Institute.
    • Description of project performance sites - List facilities that may be used outside of the Cooperative Institute where research will take place that is directly related to the proposed research - this would not include consortium members.
    • List of senior and key personnel - Describe their specific role as it relates to the specific aims/milestones.
    • Data Management Plan - Proposals must include a Data Management Plan (DMP) of up to two pages describing how these requirements will be satisfied. The DMP should be aligned with the Data Management Guidance provided by NOAA . The contents of the Data Management Plan (or absence thereof), and past performance regarding such plans, will be considered as part of proposal review. A typical plan should include descriptions of the types of environmental data and information expected to be created during the course of the project; the tentative date by which data will be shared; the standards to be used for data/metadata format and content; methods for providing data access; approximate total volume of data to be collected; and prior experience in making such data accessible. The costs of data preparation, accessibility, or archiving may be included in the proposal budget unless otherwise stated in the Guidance.

      Accepted submission of data to the NOAA National Centers for Environmental Information(NCEI) is one way to satisfy data sharing requirements; however, NCEI is not obligated to accept all submissions and may charge a fee, particularly for large or unusual datasets.

      Environmental data and information collected or created under NOAA grants or cooperative agreements must be made discoverable by and accessible to the general public, in a timely fashion (typically within two years), free of charge or at no more than the cost of reproduction, unless an exemption is granted by the NOAA Program. Data should be available in at least one machine-readable format, preferably a widely-used or open-standard format, and should also be accompanied by machine-readable documentation (metadata), preferably based on widely-used or international standards.

      Proposal submitters are hereby advised that the final pre-publication manuscripts of scholarly articles produced entirely or primarily with NOAA funding will be required to be submitted to NOAA Institutional Repository after acceptance, and no later than upon publication. Such manuscripts shall be made publicly available by NOAA one year after publication by the journal.

Questions related to the proposal submission process should be directed to Whitley Alford, NGI Program Administrator .


Funding Acknowledgement for Publications

Researchers who are preparing publications for work conducted with funding from NOAA through the Northern Gulf Institute (NGI) should use the following accreditation:

For work supported by funding awarded for the period 1 Oct 2016 through 30 Sept 2021: This work was supported by award NA16OAR4320199 to the Northern Gulf Institute from NOAA's Office of Oceanic and Atmospheric Research, U.S. Department of Commerce.

For work supported by funding awarded for the period 1 Oct 2021 through 30 Sept 2026: This work was supported by award NA21OAR4320190 to the Northern Gulf Institute from NOAA's Office of Oceanic and Atmospheric Research, U.S. Department of Commerce.