Search NASA⌕ Search

SEARCH · Search NASA

Results for “Great Lakes”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Development of Hyperspectral Remote Sensing Capability For the Early Detection and Monitoring of Harmful Algal Blooms (HABs) in the Great Lakes

Hyperspectral imagers have significant capability for detecting and classifying waterborne constituents. One particularly appropriate application of such instruments in the Great Lakes is to detect and monitor the development of potentially Harmful Algal Blooms (HABs). Two generations of small hyperspectral imagers have been built and tested for aircraft based monitoring of harmful algal blooms. In this paper a discussion of the two instruments as well as field studies conducted using these instruments will be presented. During the second field study, in situ reflectance data was obtained from the Research Vessel Lake Guardian in conjunction with reflectance data obtained with the hyperspectral imager from overflights of the same locations. A comparison of these two data sets shows that the airborne hyperspectral imager closely matches measurements obtained from instruments on the lake surface and thus positively supports its utilization for detecting and monitoring HABs.

Lekki, John↗
NASA NTRS1980

Coordinated aircraft and ship surveys for determining impact of river inputs on great lakes waters. Remote sensing results

The remote sensing results of aircraft and ship surveys for determining the impact of river effluents on Great Lakes waters are presented. Aircraft multi-spectral scanner data were acquired throughout the spring and early summer of 1976 at five locations: the West Basin of Lake Erie, Genesee River - Lake Ontario, Menomonee River - Lake Michigan, Grand River - Lake Michigan, and Nemadji River - Lake Superior. Multispectral scanner data and ship surface sample data are correlated resulting in 40 contour plots showing large-scale distributions of parameters such as total suspended solids, turbidity, Secchi depth, nutrients, salts, and dissolved oxygen. The imagery and data analysis are used to determine the transport and dispersion of materials from the river discharges, especially during spring runoff events, and to evaluate the relative effects of river input, resuspension, and shore erosion. Twenty-five LANDSAT satellite images of the study sites are also included in the analysis. Examples of the use of remote sensing data in quantitatively estimating total particulate loading in determining water types, in assessing transport across international boundaries, and in supporting numerical current modeling are included. The importance of coordination of aircraft and ship lake surveys is discussed, including the use of telefacsimile for the transmission of imagery.

Raquet, C. A.↗
NASA NTRS1994

Evaluation of the TOPEX/POSEIDON altimeter system over the Great Lakes

The TOPEX/POSEIDON altimeter measurment system is evaluated for the first 46 repeat cycles (September 23, 1992-December 23, 1992) using tracks over the Great Lakes. The temporal variations in lake level are removed from the altimeter measurements using in-situ lake level measurements, thus permitting the performance of the altimeter system to be assessed. For the NASA altimeter, the root-mean-square (RMS) scatter of the residuals is 3.95 cm using all the tracks over the lakes. However, some of the scatter in this result is probably due to lake tides or seiche, which can amount to a few centimeters amplitude near the ends of the lakes. When the seven best tracks are used, which cross the center of the lakes where tides/seiche effects are minimal, the RMS error is included to either 2.9 or 3.0 cm, depending on whether the Centre National d'Etudes Spatiales (CNES) or NASA orbit is used. This places an upper limit on the error budget of the altimeter system, excluding ocean tides and inverse barometer effect. There are several short-period variations in the residuals. The most pronounced is a 55-day period, with a 1-cm amplitude, which we believe is (at least in part) due to orbit error. When the model-derived wet tropospheric correction is substituted for the TOPEX microwave radiometer correction, the RMS error increases significantly, possibly resulting in an annual cycle of a few centimeters. Evaluation of the ionospheric correction indicates that the dual-frequency correction provides an average improvement of 0.85 cm over the Doppler orbitography and radiopositioning integrated by satellite (DORIS) correction. Although there are insufficient data to directly assess the CNES altimeter, the relative bias between the altimeters is estimated to be either -14.3 or -15.6 cm (NASA altimeter measuring short), depending on whether the DORIS or dual-frequency ionospheric correction is applied to the NASA altimeter.

Morris, Charles S.↗
DOE OSTI2025

An Extension Industrial Assessment Center in Eastern Great Lakes Region

The extension IAC at CWRU is funded for 3 years to conduct 10 assessments of small and medium-sized manufacturing facilities each year in Eastern Great Lakes region. Total 30 assessments was proposed in the SOPO but due to the Covid-19 pandemic, the IAC program was suspended for 1.5 years. A total of 20 assessments was contracted to the extension IAC at CWRU which have been successfully accomplished. In the proposal, we proposed to train 18 students in the extension IAC program, and actually we selected and trained 19 students even though the IAC project was suspended during half of its project period.

42 ENGINEERING↗
NASA NTRS1974

Selected satellite data on snow and ice in the Great Lakes basin 1972-73 /IFYGL/

Three snow-extent maps of the Lake Ontario drainage basin were prepared from NOAA-2 satellite visible band images during the International Field Year for the Great Lakes. These maps are discussed and the satellite data are evaluated for snow-extent mapping. The value of ERTS-1 imagery and digital data is also discussed in relation to the Lake Ontario basin studies. ERTS-1 MSS data are excellent for ice identification and analysis but are not useful for forecasting where timely receipt of data is imperative. NOAA-2 VHRR data are timely but the lower resolution of the VHRR makes identification of certain ice features difficult. NOAA-2 VHRR is well suited for snow-extent maps and thermal maps of large areas such as the 19,000 sq-km Lake Ontario basin.

Wiesnet, D. R.↗
NASA NTRS1975

Great Lakes all-weather ice information system

The all-weather ice information system described uses the X-band side-looking airborne radar to determine the aerial distribution, location, and type of ice cover in the Great Lakes and an airborne S-band short-pulse radar to determine the ice thickness. Results from the 1974-1975 winter season demonstrated the ability of the system to provide all-weather ice information to shippers at the required time.

Schertler, R. J.↗
NASA NTRS2007

Preliminary Validation of the AFWA-NASA Blended Snowcover Product Over the Lower Great Lakes region

A new snow product created using the standard Moderate-Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer for EOS (AMSR-E) snow cover and snow-water equivalent products has been evaluated for the Lower Great Lakes region during the winter of 2002- 03. National Weather Service Co-Operative Observing Network stations and student-acquired snow data were used as ground truth. An interpolation scheme was used to map snow cover on the ground from the station measurements for each day of the study period. It is concluded that this technique does not represent the actual ground conditions adequately to permit evaluation of the new snow product in an absolute sense. However, use of the new product was found to improve the mapping of snow cover as compared to using either the MODIS or AMSR-E product, alone. Plans for further analysis are discussed.

Hall, D. K.↗
NASA NTRS1975

Microwave properties of ice from The Great Lakes

The increasing use of radar systems as remote sensors of ice thickness has revealed a lack of basic data on the microwave properties of fresh-water ice. A program, in which the complex dielectric constant was measured for a series of ice samples taken from the Great Lakes, is described. The measurements were taken at temperatures of -5, -10, and -15 C. It is noted that the ice has considerable internal layered structure, and the effects of the layering are examined. Values of 3.0 to 3.2 are reported for the real part of the dielectric constant, with an error bar of + or - 0.01.

Vickers, R. S.↗
NASA NTRS2021

Snowfall in the Northern Great Lakes: Lessons Learned from a Multisensor Observatory

A multisensor snowfall observational suite has been deployed at the Marquette, Michigan, National Weather Service Weather Forecast Office (KMQT) since 2014. Micro Rain Radar (MRR; profiling radar), Precipitation Imaging Package (PIP; snow particle imager), and ancillary ground-based meteorological observations illustrate the unique capabilities of these combined instruments to document radar and concomitant microphysical properties associated with northern Great Lakes snowfall regimes. Lake-effect, lake-orographic, and transition event case studies are presented that illustrate the variety of snowfall events that occur at KMQT. Case studies and multiyear analyses reveal the ubiquity of snowfall produced by shallow events. These shallow snowfall features and their distinctive microphysical fingerprints are often difficult to discern with conventional remote sensing instruments, thus highlighting the scientific and potential operational value of MRR and PIP observations. The importance of near-surface lake-orographic snowfall enhancement processes in extreme snowfall events and regime-dependent snow particle microphysical variability controlled by regime and environmental factors are also highlighted.

Lake effects↗
DOE OSTI2022

Intercomparison of Dynamically and Statistically Downscaled Climate Change Projections over the Midwest and Great Lakes Region

Downscaling of global climate model (GCMs) simulations is a key element of regional-to-local-scale climate change projections that can inform impact assessments, long-term planning, and resource management in different sectors. Here, we conduct an intercomparison between statistically and dynamically downscaled GCMs simulations using the hybrid delta (HD) and the Weather Research and Forecast (WRF) Model, respectively, over the Midwest and Great Lakes region to 1) validate their performance in reproducing extreme daily precipitation (P) and daily maximum temperature (T max ) for summer and winter and 2) evaluate projections of extremes in the future. Our results show the HD statistical downscaling approach, which includes large-scale bias correction of GCM inputs, can reproduce observed extreme P and T max reasonably well for both summer and winter. However, raw historical WRF simulations show significant bias in both extreme P and T max for both seasons. Interestingly, the convection-permitting WRF simulation at 4-km grid spacing does not produce better results for seasonal extremes than the WRF simulation at 12 km using a parameterized convection scheme. Despite a broad similarity for winter extreme P projections, the projected changes in the future summer storms are quite different between downscaling methods; WRF simulations show substantial increases in summer extreme precipitation, while the changes projected by the HD approach exhibit moderate decreases overall. The WRF simulations at 4 km also show a pronounced decoupling effect between seasonal totals and extreme daily P for summer, which suggests that there could be more intense summer extremes at two different time scales, with more severe individual convective storms combined with longer summer droughts at the end of the twenty-first century.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1973

Application of SLAR for monitoring Great Lakes total ice cover

A series of X-band SLAR images is presented showing the development and disintegration of the entire ice cover on Lake Erie during the winter of 1972-1973. Simultaneous ground truth observations and ERTS-1 photography establish accurate correlations of radar responses with ice conditions. The all-weather, broad areal mapping capability of SLAR is seen to be the means for obtaining the repeated coverage needed for winter navigation on the Great Lakes.

Jirberg, R. J.↗
NASA NTRS1973

Application of SLAR for monitoring Great Lakes total ice cover

A series of X-band SLAR images is presented showing the development and disintegration of the entire ice cover on Lake Erie during the winter of 1972-1973. Simultaneous ground truth observations and ERTS-1 photography establish accurate correlations of radar responses with ice conditions. The all-weather, broad areal mapping capability of SLAR is seen to be the means for obtaining the repeated coverage needed for winter navigation on the Great Lakes.

Jirberg, R. J.↗
NASA NTRS2009

Preliminary Evaluation of the AFWA-NASA (ANSA) Blended Snow-Cover Product over the Lower Great Lakes Region

The Air Force Weather Agency (AFWA) - NASA (ANSA) blended-snow product utilizes EOS standard snow products from the Moderate-Resolution Imaging Spectroradiometer (MODIS) and the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) to map daily snow cover and snow-water equivalent (SWE) globally. We have compared ANSA-derived SWE. with SWE values calculated from snow depths reported at approx.1500 National Climatic Data Center (NCDC) coop stations in the Lower Great Lakes basin. Our preliminary results show that conversion of snow depth to SWE is very sensitive to the choice of snow density (we used either 0.2 or 03 as conversion factors). We found overall better agreement between the ANSA-derived SWE and the co-op station data when we use a snow density of 0.3 to convert the snow depths to SWE. In addition, we show that the ANSA underestimates SWE in densely-forested areas, using January and February 2008 ANSA and co-op data. Furthermore, apparent large SWE changes from one day to the next may be caused by thaw-re-freeze events, and do not always represent a real change in SWE. In the near future we will continue the analysis in the 2006-07 and 2007-08 snow seasons.

Hall, Dorothy K.↗
NASA NTRS1981

Data use investigations for applications Explorer Mission A (Heat Capacity Mapping Mission): HCMM's role in studies of the urban heat island, Great Lakes thermal phenomena and radiometric calibration of satellite data

The utility of data from NASA'a heat capacity mapping mission satellite for studies of the urban heat island, thermal phenomena in large lakes and radiometric calibration of satellite sensors was assessed. The data were found to be of significant value in all cases. Using HCMM data, the existence and microstructure of the heat island can be observed and associated with land cover within the urban complex. The formation and development of the thermal bar in the Great Lakes can be observed and quantitatively mapped using HCMM data. In addition, the thermal patterns observed can be associated with water quality variations observed both from other remote sensing platforms and in situ. The imaging radiometer on-board the HCMM satellite is shown to be calibratible to within about 1.1 C of actual surface temperatures. These findings, as well as the analytical procedures used in studying the HCMM data, are included.

Schott, J. R.↗
NASA NTRS1973

Application of thermal imagery to the development of a Great Lakes ice information system

Recent measurements and analysis have shown that thermal infrared imagery can be employed to delineate the relative thicknesses of various regions of freshwater ice and to differentiate new ice from both open water areas and thicker (young) ice. Thermal imagery was observed to be generally superior to visual (0.4 - 0.7 micron) and SLAR (3.3 cm) imagery for estimating relative ice thicknesses and delineating open water from new ice growth. In a real-time Great Lakes ice information system, thermal imagery can not only provide supplementary imagery but can also aid in developing interpretative methods for all-weather SLAR imagery.

Schertler, R. J.↗
DOE OSTI2023

Comparative productivity of six bioenergy cropping systems on marginal lands in the Great Lakes Region, United States

Abstract Growing lignocellulosic crops on marginal lands is a promising solution for sustainable biofuel production. We evaluated the productivity of bioenergy cropping systems (switchgrass [ Panicum virgatum L., var. Cave‐In‐Rock], miscanthus [ Miscanthus × giganteus , ‘Illinois clone’], hybrid poplar [ Populus nigra × P. maximowiczii A. Henry ‘NM6’], native grasses [five species], early successional vegetation, and restored prairie vs. historical vegetation [as reference control]) with and without nitrogen fertilization on low‐fertility former cropland at five sites in the Great Lakes Region, United States. We reported biomass yields for the first 7 years after establishment. Switchgrass was most consistently productive across all sites but miscanthus was more productive at three of the five sites. When averaged across sites, years, and nitrogen (N) treatments, biomass yields followed the order miscanthus > switchgrass > hybrid poplar ≈ native grasses > restored prairie > early successional vegetation ≈ historical vegetation, but varied substantially by crop and site, with a significant crop by site interaction. Yields of miscanthus and switchgrass peaked after four–five growing seasons and declined thereafter, while yields of both native grasses and restored prairie increased throughout 6 years with no sign of follow‐on decline, suggesting that polycultures may outperform monocultures over the long term. Yields of early successional vegetation—similar in composition to historical vegetation at each site—did not improve with time. Nitrogen fertilization increased the yields of all cropping systems at all sites. Our results demonstrate the viability of low‐productivity former cropland for long‐term bioenergy production and suggest there is no single crop best suited for all low fertility soils.

Jayawardena, Dileepa M.↗
DOE OSTI2025

Rising Water Levels and Vegetation Shifts Drive Substantial Reductions in Methane Emissions and Carbon Dioxide Uptake in a Great Lakes Coastal Freshwater Wetland

ABSTRACT Coastal freshwater wetlands are critical ecosystems for both local and global carbon cycles, sequestering substantial carbon while also emitting methane (CH 4 ) due to anoxic conditions. Estuarine freshwater wetlands face unique challenges from fluctuating water levels, which influence water quality, vegetation, and carbon cycling. However, the response of CH 4 fluxes and their drivers to altered hydrology and vegetation remains unclear, hindering mechanistic modeling. To address these knowledge gaps, we studied an estuarine freshwater wetland in the Great Lakes region, where rising water levels led to a vegetation shift from emergent Typha dominance in 2015–2016 to floating‐leaved species in 2020–2022. Using eddy covariance flux measurements during the peak growing season (June–September) of both periods, we observed a 60% decrease in CH 4 emissions, from 81 ± 4 g C m −2 in 2015–2016 to 31 ± 3 g C m −2 in 2020–2022. This decline was driven by two main factors: (1) higher water levels, which suppressed ebullitive fluxes via increased hydrostatic pressure and extended CH 4 residence time, enhancing oxidation potential in the water column; and (2) reduced CH 4 conductance through plants. Net carbon dioxide (CO 2 ) uptake decreased by 90%, from −267 ± 26 g C m −2 in 2015–2016 to −27 ± 49 g C m −2 in 2020–2022. Additionally, diel CH 4 flux patterns shifted, with a distinct morning peak observed in 2015–2016 but absent in 2020–2022, suggesting changes in plant‐mediated transport and a potential decoupling from photosynthesis. The dominant factors influencing CH 4 fluxes shifted from water temperature and gross primary productivity in 2015–2016 to atmospheric pressure in 2020–2022, suggesting an increased role of ebullition as a primary transport pathway. Our results demonstrate that changes in water levels and vegetation can substantially alter CH 4 and CO 2 fluxes in coastal freshwater wetlands, underscoring the critical role of hydrological shifts in driving carbon dynamics in these ecosystems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

Improving the Accuracy of the AFWA-NASA (ANSA) Blended Snow-Cover Product over the Lower Great Lakes Region

The Air Force Weather Agency (AFWA) -- NASA blended snow-cover product, called ANSA, utilizes Earth Observing System standard snow products from the Moderate- Resolution Imaging Spectroradiometer (MODIS) and the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) to map daily snow cover and snow-water equivalent (SWE) globally. We have compared ANSA-derived SWE with SWE values calculated from snow depths reported at ~1500 National Climatic Data Center (NCDC) co-op stations in the Lower Great Lakes Basin. Compared to station data, the ANSA significantly underestimates SWE in densely-forested areas. We use two methods to remove some of the bias observed in forested areas to reduce the root-mean-square error (RMSE) between the ANSA- and station-derived SWE. First, we calculated a 5- year mean ANSA-derived SWE for the winters of 2005-06 through 2009-10, and developed a five-year mean bias-corrected SWE map for each month. For most of the months studied during the five-year period, the 5-year bias correction improved the agreement between the ANSA-derived and station-derived SWE. However, anomalous months such as when there was very little snow on the ground compared to the 5-year mean, or months in which the snow was much greater than the 5-year mean, showed poorer results (as expected). We also used a 7-day running mean (7DRM) bias correction method using days just prior to the day in question to correct the ANSA data. This method was more effective in reducing the RMSE between the ANSA- and co-op-derived SWE values, and in capturing the effects of anomalous snow conditions.

Hall, Dorothy K.↗