2019 Summer Fellows Position Descriptions

Operational atmospheric models are increasingly being employed as forcing factors to drive lake models. However, the accuracy of over-lake meteorological model products has not been sufficiently investigated. The NOAA High-Resolution Rapid Refresh (HRRR) operational atmospheric model is being used to drive hydrodynamic model FVCOM in the NOAA Great Lakes Coastal Forecasting System (GLCFS), a set of real-time hydrodynamic models that simulate nowcast and forecast predictions of the physical environment of the Great Lakes. In 2017, FVCOM exhibited warm temperature bias in the upper layer of Lake Erie which is likely caused by errors in HRRR predictions. In this project we will test the accuracy of HRRR (air temperature, wind speed and cloud cover) by comparing model predictions with observations of several meteorological variables over the lake that impact surface heat balance. This work will advance nearshore capability of hydrodynamic models, particularly in Lake Erie where harmful algal blooms and hypoxia are common, as well as aid in the development of the NOAA GLCFS.

Research Question: What is the accuracy of over-lake atmospheric forcing and its potential impact on surface heat balance and lake temperature predictions?

Project Activities: Extract modeled meteorological variables driving FVCOM and compare with archived over-lake observations:

• Validate modeled lake surface temperature with NOAA buoy observations
• Validate modeled air temperature with NOAA buoy and ship observations
• Validate modeled wind with NOAA buoy observations
• Validate modeled cloud cover with airport observations

Required & Desired Skills: Candidates should have strong scientific and computing skills and experience with data analysis (e.g., using Python, R, IDL). Knowledge of the UNIX/LINUX environment and basic physical oceanography/ limnology would be a plus.

Location: NOAA Great Lakes Environmental Research Laboratory, Ann Arbor, Michigan

Storm surges are a hazardous phenomenon along Alaska’s western coast. Regional forecasters and the communities they serve have limited ability to assess threats from storm events, and have no basis to determine risk, the potential impacts of storms, or to evaluate safe evacuation routes and locations. Sea ice plays a key role in altering the intensity of storm surges by amplifying or dampening waves and surges, yet due to its complex physics, the overall impacts in the region are unknown. To address this gap, the project aims to develop a physical model system where interactions among sea ice, waves, and ocean currents are enabled. The developed model system will be experimentally implemented in an operational forecast framework to provide forecast guidance of storm surges to the western Alaska region.

Research Question: What are the impacts of landfast ice and partial and free-drifting sea ice on storm surges?

Project Activities: The fellow will help analyze simulation results from sea ice, wave, and storm surge models by comparing them with available observations. The analyses will focus on selected historical storm events.

• Compare sea ice model simulations with satellite-based observations.
• Collect landfast ice datasets along Western Alaska
• Analyze meteorological and ocean current model results in comparison with in situ and other observational datasets.

Required & Desired Skills: Basic knowledge in oceanography or a related field is required. Familiarity with the UNIX/Linux environment and computer programming languages (e.g. Fortran, Python) is preferred.

Location: NOAA Great Lakes Environmental Research Laboratory, Ann Arbor, Michigan

The seasonal development of hypoxia in Lake Erie poses serious challenges for water treatment plants when wind-driven movement within the lake brings hypoxic water closer to intake pipes located near the shore. Among the risks posed by hypoxia is contamination by manganese, a naturally occurring heavy metal that is released from sediments during hypoxia, and if not removed during treatment, turns drinking water yellow and potentially toxic. Recent work has shown that Lake Erie sediments have the potential for rapid release of dissolved manganese during, but it remains unknown which factors control the oxidation of manganese from the dissolved form, which is more hazardous, into particulate forms that are more effectively removed during the water treatment process.

 

Research Question: Is oxidation of manganese (Mn) in Lake Erie controlled by the biological production of superoxide, and not directly by bacterial metabolism or abiotic reactions (i.e., exposure to dissolved oxygen)? Since these controls operate at very different timescales and in response to distinct drivers, it is critical to determine which mechanism is relevant for understanding and modeling the fate of Mn in Lake Erie.

Project Activities: The fellow will perform field work and laboratory experiments linking manganese biogeochemistry to the problem of seasonal hypoxia in Lake Erie. Specifically, the fellow will perform experiments to determine which factors control the oxidation of manganese and to measure the rate of oxidation under the conditions present in the lake.

• Field Work Activities: Participate in at least two research cruises aboard vessels on Lake Erie; collect water samples from the hypolimnion and surface mixed layer; initiate incubation experiments; process samples for biological and chemical parameters (e.g. manganese, nutrients, chlorophyll).
• Experimental Activities: (1) Test the hypothesis that manganese oxidation is biologically-mediated and that abiotically-mediated oxidation cannot explain observed rates in the lake and (2) Quantify the potential oxidation rate and distribution of manganese under the conditions present in different areas of the lake.
• Quantitative Laboratory Analyses: spectrophotometric measurement of total and dissolved manganese; leucoberbelin blue assay to measure production manganese (III, IV) oxides; and measurement of dissolved oxygen using luminescence sensors and Winkler titrations.

Required & Desired Skills: We are seeking a student with coursework experience in limnology, microbial ecology, or biogeochemistry. Experience performing quantitative laboratory chemistry is desired, but not essential.

Location: NOAA Great Lakes Environmental Research Laboratory, Ann Arbor, Michigan, is the primary work location, but some travel is required to Central Michigan University (Mount Pleasant, MI) to use specific equipment and facilities in the laboratory of Deric Learman.

The HAB-tracker model in Lake Erie, initialized from satellite-derived cyanobacterial harmful algal bloom (CHAB) concentration, uses the predicted currents from a numerical hydrodynamic model and a particle tracking model to produce a 5-day forecast of harmful algal blooms (HABs) in western Lake Erie. The model provides real-time and future information on the extent of HAB horizontal and vertical distribution and physical transport of cyanobacteria for public water systems management as well as recreational users of Lake Erie. From 2011 to 2018, different satellites, including MERIS, MODIS and OLCI, have been used. The different satellites have different performance in HABs detection and affect the model skill. Therefore, it is necessary to assess the accuracy of the models based on different satellites through hindcast skill assessment.

Research Question: This project will evaluate the skill of HABs forecast in 2017 and 2018, and investigate how the utilization of different satellites affects the HAB tracker model’s skill.

Project Activities

• HABs hindcast in 2017 and 2018;
• Skill assessment of HAB tracker in 2017 and 2018;
• Comparisons of model skills using different satellites.

Required & Desired Skills: Candidates should have a strong background in natural sciences or engineering and some experience with scripting-based data analysis (for example, R, Python, Matlab, or IDL).

Location: NOAA Great Lakes Environmental Research Laboratory, Ann Arbor, Michigan

Mysis are a key component to the Great Lakes ecosystem, providing an energy rich packet to the upper food web. However, knowledge on fine-scale changes in distribution and size structure are limited due to current sampling technologies and gear avoidance. Such information is essential for determining how changes in Mysis size structure and biomass will impact the upper food web (fishes). Here we build on past results of Mysis research and use a new technology in the Great Lakes (Multiple Opening and Closing Net and Environmental Sensing System- MOCNES) to measure the fine-scale vertical distribution, size structure, and biomass of Mysis in Lake Michigan.

Research Questions: The following research questions will be directly and indirectly addressed by this project. Indirect contribution to questions will help inform ongoing CIGLR and GLERL research programs. Contributions are indicated for each research question.

• How does the size structure of Mysis differ between seasons, vertical depth and years? (Direct result of the fellow’s project)
• Does a fraction of the Mysis population occupy the water column during the day?
• (Direct result of the fellow project)
• What is the catchability of Mysis using the MOCNESS? (Direct result of the fellow’s project)
• How does the biomass size spectrum change with respect to spatial and temporal observations (inshore vs. offshore; across seasons and years) (Indirect application of results to support ongoing CIGLR supported project)
• Can fisheries acoustics be used to quantify the biomass and changes in biomass of Mysis across space and time? (Indirect application of the results of the fellow’s project. Note this has been an ongoing interest of Drs. Lars Rudstam, Doran Mason and Edward Rutherford where Dr. Rudstam has been working on this question for better than a decade).

Project Activities: The fellow will participate in data processing of previously collected samples, statistical analysis, and one MOCNESS summer cruise. The fellow will also interact closely with a CIGLR funded Post-Doc to inform a CIGLR funded project to quantify the biomass size structure of Great Lakes pelagic communities.

Required & desired skills: The fellow is expected to have background in statistics and using R statistical programming language for the analysis of data and generating graphics. In addition, we are looking for a student that has a keen interest in participating in the collection of Mysis samples using the MOCNESS.

Location: NOAA Great Lakes Environmental Research Laboratory, Ann Arbor, Michigan

Profiling gliders, or AUVs, are autonomous, underwater vehicles used to collect data throughout the entire water column via multiple onboard sensors. CIGLR and NOAA GLERL have deployed gliders in Lakes Michigan, Huron, and Ontario since 2012 collecting environmental data throughout the water column on conductivity, temperature, depth, chlorophyll, dissolved organic matter, and other parameters. A workflow is needed to processes raw data from the sensors into the Integrated Ocean Observing System (IOOS) National Glider Data Assembly Center (NGDAC) NetCDF format, which can then be easily used by collaborators within our organizations and with stakeholders across the Great Lakes basin. These data can then be used to validate hydrodynamic models and build visualizations to aid our understanding of the physical and chemical variations in the water column.  Once the data are processed into a standardized format, visualization methods need to be explored including static graphics, and potentially, interactive visualization applications.   The visualizations can be used to engage the general public and stakeholders through our website and presentation materials, as well as supporting information for internal research.

Research Questions: Can we use profiling glider data to improve the numerical model predictions of lake dynamics, including temperature, currents, and primary productivity? Can we use historical glider data to better inform our future field sampling and experiment designs? How can we best visualize the data to better understand the water column of the Great Lakes?

Project Activities: The summer fellow will develop a workflow taking profiling glider data from raw sensor output to IOOS standardized format and archiving the data at the NOAA data centers. The summer fellow will also have an opportunity to go out in the field for the deployment and retrieval of a profiling glider. Specifically, the fellow will:

• Develop a workflow to process raw glider profiles to the IOOS NGDAC NetCDF format using community developed tools in MatLab and
• Participate in at least one deployment and retrieval of a profiling glider on the Great
• Document data according to ISO metadata standards and setup automatic archiving of glider data with the NOAA National Centers for Environmental
• Develop visualization of glider profile data using standard methods (e.g., contours) and research new visualization methods to be used for public presentations, on the CIGLR and GLERL websites, and on social Visualizations could include the development of applications using platforms, such as RStudio ShinyApps, so the spatial, temporal, and parameter dimensions of the data may be explored interactively by users.  The summer fellow will be expected to provided visualization examples and recommendations to the project team.
• Review and summarize existing literature about profiling gliders in oceanographic settings.
• Work with hydrodynamic modelers at GLERL to compare profiling glider data with FVCOM hydrodynamic model output and assimilate glider data in FVCOM model(s).  Develop recommendations on how future glider deployments could be designed to close data gaps in FVCOM models.

Required & Desired Skills: A qualified candidate will have experience processing and visualizing time-series data using Matlab, Python or R with a background in engineering, limnology, or oceanographic sciences. Previous experience with R and RStudio ShinyApps desired.

Location: NOAA Great Lakes Environmental Research Laboratory, Ann Arbor, Michigan

When invasive species colonize new habitats, they typically experience selection pressure that differs from their home environments. Understanding how populations rapidly respond to changes in selection pressure can help us explore why invasives are so successful in their new environments.  In their native region, male round gobies display different alternative reproductive tactics during mating. These typically include a territorial tactic, where larger males defend territories used for attracting females, and a sneaker tactic, where smaller males sneak fertilizations from territorial males. The success of these multiple mating tactics can increase overall genetic diversity in the population. The proportion of these tactics within a population can vary and is thought to be influenced by environmental factors, but what drives those changes is currently unclear. It is also unclear whether all round goby populations maintain these alternative reproductive tactics once they have invaded new environments.

Research Questions:

• Do invasive populations of round gobies in Michigan display alternative reproductive tactics?
• If alternative reproductive tactics exist, do the proportions of these tactics within a population change across environments with differing anthropogenic influences?

Project Activities: The main activities of this project will include bi-monthly sampling of round gobies from different drowned-river mouth lakes along the eastern side of Lake Michigan that represent a range of anthropogenic influence to determine the proportion of alternative reproductive tactics for each location and the influence of anthropogenic disturbance. Specific tasks include:

• Bi-monthly collecting of round gobies using minnow traps from drowned-river mouth lakes
• Water sampling for each lake using a YSI to obtain standard environmental characteristics (water pH, salinity, conductivity, temperature, DO, etc.)
• Collecting data on testes weight, seminal vesicle weight, total weight, and body morphometrics for round gobies to characterize alternative reproductive tactics. These characteristics significantly differ between territorial and sneaker tactics and will be used to classify individuals.
• Determining the proportion of each alternative reproductive tactic for each lake sampled
• Examining whether the variation in the proportion of alternative reproductive tactics is associated with environmental characteristics collected from each lake and/or level of anthropogenic disturbance

Required & Desired Skills: Candidates should have a strong interest and some background in aquatic ecology as well as a demonstrated ability to work as part of a team. Prior experience working on a research project is preferred.  Previous experience with fish dissections would be desired but is not a requirement.

Location: GVSU Annis Water Resources Institute in Muskegon, Michigan

The declining productivity of Great Lakes food webs is thought to affect reproductive success of prey fish that support valuable fisheries. Survival and potential recruitment (numbers of young adults) of fish often is determined during the egg and larval stages. Recent studies in Lake Michigan indicate larval fish growth rates, condition, and their zooplankton prey densities have declined since invasive quagga mussels irrupted in the early 2000s. Analysis of fish larvae diets suggests that Dreissena mussel veligers have replaced native copepods as prey, and may have caused the decline in fish larvae growth rate. Energy density of veligers and its relative importance to fish larvae growth and survival is unknown.

Research Questions:

• What is the relative importance of Dreissena mussel veligers in the diets of larval fishes?
• Can a diet of veligers support the historic growth and production of larval fishes in the Great Lakes?

Project Activities: The fellow will help conduct surveys and laboratory analysis to learn how density, availability and energetic content of Dreissena veligers affect diet and growth of larval fish (yellow perch, alewife). The fellow will supplement data analysis of new samples collected during diel surveys in Lake Michigan in 2019 with analysis of prior plankton collections in Lake Michigan in 2018.

Required & Desired Skills: Candidates should have a strong background in freshwater or marine science, have taken an introductory statistics course, and be experienced working on boats in variable weather conditions.

Location: NOAA Great Lakes Environmental Research Laboratory, Ann Arbor, Michigan

Great Lakes ecosystems are controlled by processes occurring within the lakes, and by external physical and environmental forcings.  Ecosystems respond to a combination of these factors, which are often difficult to separate. In this project, in-depth research will look for links between climate teleconnection patterns (such as North Atlantic Oscillation, ENSO, Atlantic Multi-decadal Oscillation, and Pacific Decadal Oscillation) to the Great Lakes climate, ice cover, and water quality such as hypoxia in Lake Erie.

Research Questions:

• In addition to water temperature and wind forcing, is Lake Erie hypoxia correlated to teleconnection patterns or ice cover? If so, how strong are these correlations and are they linear or non-linear?
• Can we hindcast and predict biological parameters using physical forcings?

Project Activities: The fellow will develop regression models in R for predicting ice cover and hypoxia using climate teleconnection indices and physical forcings. Tools for data analyses include time series analysis, correlation, and/or empirical orthogonal function analysis and regression analysis. The project is part of the prediction of ice cover and ecological change in response to a changing climate on seasonal, interannual, and decadal time scales.

Required & Desired Skills: Qualifications include programming in R-software, Fortran, Python, and/or other programming skills. Data analyses and statistics background are desired.

Location: NOAA Great Lakes Environmental Research Laboratory, Ann Arbor, Michigan

The rapid pace and global scale of environmental change has necessitated new strategies to study the Great Lakes. A key component of these efforts is the use of in situ instruments that provide continuous and realtime data. The Realtime Aquatic Ecosystem Observation Network (RAEON), a $15-million Canadian investment in instruments and equipment at the University of Windsor, begins in 2019 with a collaboration with NOAA GLERL and CIGLR. RAEON will be deploying four realtime sensor arrays in the western basin of Lake Erie in May 2019 to provide fine-scale data to validate and check dissolved oxygen and temperature models developed by GLERL. These arrays will also support UWindsor research on nutrient transport mechanisms and associated lake biogeochemical responses to improve our knowledge of threshold drivers of harmful algal blooms. The fellow will work closely with Crossman and Rowe to develop parameters of the data collection and presentation on the RAEON website for the science objectives of the project. On a day-to-day basis, they will work closely with RAEON field and data technicians (Todd Leadley, field; and Katelynn Johnson, data), as well as graduate students in the Crossman and Fisk labs, for field work in Lake Erie and data management of incoming realtime data.

Research Questions: What is the variation in environmental data (temperature, oxygen, nutrients, chlorophyll) at small and large spatial and temporal scales in western basin of Lake Erie? What resolution is needed to collect sufficient data for models, research and public outreach?

Project Activities: The summer fellow will provide support in gathering and interpreting the realtime data that are collected, including helping to fine-tune strategies and methods. The student will also prepare a plan for outreach and communications to share ongoing results with the public and other audiences. Specifically, the student will be involved in:

i) assisting with the servicing of the sensory array in Lake Erie by UWindsor RAEON technicians, ii) collecting, archiving, monitoring and organizing realtime data collected by the sensor array, and iii) analyzing and summarizing realtime data for presentation on RAEON website for public outreach.

Required & Desired Skills: Applicant must be enrolled fulltime in a biology, chemistry or environmental science undergraduate program at a university, with at least one introductory statistical course. Students with experience working or volunteering with a state or federal science agency, such as USGS or NOAA, are preferred.

Location: The fellow will be based at the University of Windsor but will spend at least 1 day every two weeks at GLERL, in addition to participating in all CIGLR summer fellow training, seminars, and workshops.