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At least 523 records · Page 29

The ERTS-1 investigation (ER-600). Volume 6: ERTS-1 signature extension analysis, July 1972 - June 1973

Feature classification, spatially and temporally, was extended over the Houston test site area. The Earth Resources Technology Satellite (ERTS-1) multispectral scanner data from August, September, and October 1972, of five widely separated lakes were used as statistical training fields and test sites. Short term temporal (same day to 36 days) and moderately long term spatial (within and between three ERTS multispectral scanner frames) signature extensions have been verified with respect to large relatively homogeneous features. The most significant feature dependent variable affecting spatial and short term extension was water turbidity. Long term signature extension will require a model to compensate or modify the ERTS-1 multispectral scanner data for significant sun angle changes. The presence of atmospheric haze changed the absolute signature but always by approximately the same amount so that the measured water signature was always the same. The normally occurring variations in atmospheric haze conditions had no major effect on the water signatures in this study.

Erb, R. B.↗

Passive microwave studies of frozen lakes

Lakes of various sizes, depths and ice thicknesses in Alaska, Utah and Colorado were overflown with passive microwave sensors providing observations at several wavelengths. A layer model is used to calculate the microwave brightness temperature, T sub B (a function of the emissivity and physical temperatures of the object), of snowcovered ice underlain with water. Calculated T sub B's are comparable to measured T sub B's. At short wavelengths, e.g., 0.8 cm, T sub B data provide information on the near surface properties of ice covered lakes where the long wavelength, 21.0 cm, observations sense the entire thickness of ice including underlying water. Additionally, T sub B is found to increase with ice thickness. 1.55 cm observations on Chandalar Lake in Alaska show a T sub B increase of 38 K with an approximate 124 cm increase in ice thickness.

Hall, D. K.↗

First results from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)

After engineering flights aboard the NASA U-2 research aircraft in the winter of 1986 to 1987 and spring of 1987, extensive data collection across the United States was begun with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) in the summer of 1987 in support of a NASA data evaluation and technology assessment program. This paper presents some of the first results obtained from AVIRIS. Examples of spectral imagery acquired over Mountain View and Mono Lake, California, and the Cuprite Mining District in western Nevada are presented. Sensor performance and data quality are described, and in the final section of this paper, plans for the future are discussed.

Vane, Gregg↗

First results from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)

After engineering flights aboard the NASA U-2 research aircraft in the winter of 1986 to 1987 and spring of 1987, extensive data collection across the United States was begun with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) in the summer of 1987 in support of a NASA data evaluation and technology assessment program. This paper presents some of the first results obtained from AVIRIS. Examples of spectral imagery acquired over Mountain View and Mono Lake, California, and the Cuprite Mining District in western Nevada are presented. Sensor performance and data quality are described, and in the final section of this paper, plans for the future are discussed.

Vane, Gregg↗

AmeriFlux CA-GL4 Nine Mile Lighthouse

This is the AmeriFlux version of the carbon flux data for the site CA-GL4 Nine Mile Lighthouse. Site Description - Nine Mile Lighthouse is located at the south end of Simcoe Island on Lake Ontario. The eddy covariance instrumentation is located on the historic lighthouse, built in 1833, and instrumented with eddy covariance data in 2016 by a network of scientists from both US and Canada (eventually to be called the Great Lakes Evaporation Network (GLEN)). The intent of GLEN has been to provide observations of over-lake meteorology and evaporation, improve forecasting of Great Lakes water levels, and support a wide variety of stakeholders, including the National Weather Service (NWS), Environment and Climate Change Canada, National Oceanic and Atmospheric Administration, U.S. Coast Guard, recreational boaters and commercial shipping, emergency management officials, and the Great Lakes research community.

Spence, Chris [Environment and Climate Change Cana↗

Cosmogenic Production of Be-7 and Be-10 in Water Targets

We have measured Be-10(t(sub 1/2) = 1.5 x 10(exp 6) years) and Be-7 (t(sub 1/2) = 53.28 days) concentrations in water targets exposed for 1 to 2 years at Echo Lake, Colorado (elevation = 3246 m) and at La Jolla, California (140 m). Neutron monitor data were used to normalize the measured concentrations in order to calculate production rates equivalent to the cosmic ray flux averaged over four solar cycles (43 years). The Be-7 production rates thus obtained correspond to 6.03 +/- 0.07 x 10(exp -6) atom/g.O/s at Echo Lake and 5.06 +/- 0.20 x 10(exp -7) atom/g.O/ s at La Jolla. The Be-10 production rates correspond to 3.14 +/- 0.18 x 10(exp -6) atom/g.O/s at Echo Lake and 2.68 +/- 0.47 x 10(exp -7) atom/g.O/s at La Jolla. When compared with Be-10 production rates determined in Be-10-saturated rocks from the Antarctic and with theoretical calculations based on meteorite and lunar sample data, we find that the million-year average production rate is about 14 - 17% greater than the present production rate averaged over the last four solar cycles. Comparison with production rates determined by measuring glacially polished rocks from the Sierra Nevada in California indicates that average production (based on a revised 13,000-year deglaciation age and a geographic latitude correction) is a about 11% greater than the average over the last four solar cycles. The measured Be-10/Be-7 production ratio in oxygen is 0.52 +/- 0.03 at Echo Lake and 0.55 +/- 0.07 at La Jolla.

Nishiizumi, K.↗

Lake Anna Water Resources: Using NASA Earth Observations to Identify Algal Event Risk Factors in Lake Anna and Help Inform Future Management Practices

Lake Anna is a man-made reservoir and popular recreation destination that spans over 13,000 acres-9,600 public and 3,400 private-in the Piedmont region of Virginia. The Lake has recently seen a rise in documented harmful algal blooms (HABs), which pose a variety of community and ecological concerns and are often exacerbated by anthropogenic factors, such as excess nutrient loads from agricultural runoff. NASA DEVELOP has partnered with the Virginia Department of Environmental Quality (DEQ) to help monitor cyanobacteria and nutrient pollution indicators across Lake Anna. The team utilized Earth observations (EO) and in situ ancillary data to identify and monitor algal bloom trends. The team used Landsat 8 Operational Land Imager (OLI), Landsat 9 OLI-2, Sentinel-2 Multispectral Instrument (MSI), and Sentinel-3 Ocean and Land Color Instrument (OLCI) to analyze water quality variables such as chlorophyll-a, turbidity, surface temperature, and cyanobacteria. Due to the lack of comprehensive in situ data and historic HAB event records, our ability to compare and validate EOs was limited. Additionally, deficient spatial resolutions, along with a geographically complicated shoreline, accentuated the spatial constraints we faced in our analysis. After examining EOs, our results indicated conditions conducive to the formation of HABs within the upper reaches of Lake Anna. Yet, spatially dependent limiting factors may have also influenced where these phenomena developed. When used in concert with existing in situ datasets, NASA EOs provide relevant stakeholders with more comprehensive analyses with which to engage in enhanced monitoring and watershed management.

cyanobacteria↗

Linking Spatiotemporal Biological Data to Predict Harmful Algal Blooms

Cyanobacterial Harmful Algal Blooms (cHABs) have significant impacts on an affected region’s economy, ecology, and human health. The blooms can release toxins that kill fish and poison water for people and animals. The global adverse effects of cHABs are exacerbated by the consequences of climate change and increased pollution. Though the phenomena are well documented, scientists’ efforts to mitigate the damage are hampered by insufficient predictive models and incomplete granular knowledge of cHAB community structure. With a goal of leveraging bioinformatics and machine learning tools to better understand and predict cHABs, we are first exploring water sample data sets. Using nearly four thousand samples from the National Center for Biotechnology Information Sequence Read Archive (NCBI-SRA) across 16 years with latitude and longitude embedded in the metadata, we mapped the location of the samples onto a Lake Erie shape file. We combined information about location, date, and community taxa in the NCBI samples to discover factors that determine cHAB features. The data are separated into three distinct zones, with the majority pooled at the southwest end of the lake and occurring in 2017. The samples are rich in biological data; our next steps are to carry out whole genome sequence analysis and use the community profiles as part of our predictive machine learning model.

59 BASIC BIOLOGICAL SCIENCES↗

Separability of boreal forest species in the Lake Jennette area, Minnesota

In order to exploit the use of thematic mapper (TM) data to obtain vegetation and net primary productivity maps in the boreal forest, three aircraft flights were undertaken over the area near Ely, MN, with the NS 001 Thematic Mapper Simulator. Attention is presently given to an analysis of these 1983 data, which attempted to separate coniferous trees from deciduous ones. Canopy reflectance models and measured optical properties of the scattering elements have been used to deepen understanding of this separability, and to relate the ratio of nadir view reflectances in TM bands 4 and 3 to the overstory leaf area index. A map that is proportional to the leaf area index for deciduous species is presented.

Shen, S. S.↗

Energy budget measurements using eddy correlation and Bowen ratio techniques at the Kinosheo Lake tower site during the Northern Wetlands Study

Fluxes of heat and water vapor were measured on a 20-m tower at Kinosheo Lake in the Hudson Bay lowlands using eddy correlation and Bowen ratio energy balance techniques. The study period was June 25 to July 28, 1990. Measurements were made over a peat bog consisting of a mixture of sphagnum moss and lichen hummocks and black pools. About 200 m west of the tower were several shallow ponds. The hummocks had a dry, insulating surface and were underlain by an ice layer near 50 cm depth until mid-July. At the beginning of the period the black pools were covered with water, and although the free water gradually disappeared over the study period, they remained saturated to the end of July. The depth of peat near the tower was about 3 m. Despite the ice layer under the hummocks, their daytime surface temperatures were high, near 35 C, and after the middle of July, above 40 C. Inspection of temperature, precipitation, and radiation data showed that the midsummer period of 1990 was warmer, drier, and sunnier than usual at Moosonee and so by influence at Lake Kinosheo. When all the data were combined to yield average diurnal energy balance components, the eddy correlation fluxes accounted for 90% of the available energy. Latent heat flux averaged 46% of the total available energy and the sensible heat flux averaged 34%. Daytime Bowen ratios were near 1 for the experimental period, suggesting that the bog behaved more like a dryland than a wetland. Eddy correlation measurements of sensible heat and latent heat flux were less than those measured using the Bowen ratio energy balance technique, the average ratios being 0.81 and 0.86 respectively. These differences were possibly due to the difficulty in measuring energy balance components of net radiation and ground heat flux over the mosaic surface.

Den Hartog, G.↗

The PRISM4 (mid-Piacenzian) Palaeoenvironmental Reconstruction

The mid-Piacenzian is known as a period of relative warmth when compared to the present day. A comprehensive understanding of conditions during the Piacenzian serves as both a conceptual model and a source for boundary conditions as well as means of verification of global climate model experiments. In this paper we present the PRISM4 reconstruction, a paleoenvironmental reconstruction of the mid-Piacenzian (approximately 3 Ma) containing data for paleogeography, land and sea ice, sea-surface temperature, vegetation, soils, and lakes. Our retrodicted paleogeography takes into account glacial isostatic adjustments and changes in dynamic topography. Soils and lakes, both significant as land surface features, are introduced to the PRISM reconstruction for the first time. Sea-surface temperature and vegetation reconstructions are unchanged but now have confidence assessments. The PRISM4 reconstruction is being used as boundary condition data for the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2) experiments.

soils↗

Evaluation of computer-aided procedure for detecting surface water

Results from an evaluation of a computer-aided procedure for processing ERTS-1 data to detect and locate surface water are presented. The procedure was evaluated using data from a study area in the vicinity of the Lake Somerville area in Washington County, Texas. The procedure consisted of (1) selecting water training fields, (2) aggregating the training samples together and clustering them into unimodal clusters, (3) computing the mean vector and covariance matrix for each cluster, (4) classifying all of the study area into classes corresponding to the clusters using the maximum likelihood classifier, and (5) thresholding out the nonwater pixels.

Source record↗

Part 2: Sedimentary geology of the Valles, Marineris, Mars and Antarctic dry valley lakes

Detailed mapping of the layered deposits in the Valles Marineris, Mars from high-resolution Viking orbiter images revealed that they from plateaus of rhythmically layered material whose bases are in the lowest elevations of the canyon floors, and whose tops are within a few hundred meters in elevation of the surrounding plateaus. Four hypotheses for the origin of the layered deposits were considered: that they are eolian deposits; that they are remnants of the same material as the canyon walls; that they are explosive volcanic deposits; or that they were deposited in standing bodies of water. There are serious morphologic objections to each of the first three. The deposition of the layered deposits in standing bodies of water best explains their lateral continuity, horizontality, great thickness, rhythmic nature, and stratigraphic relationships with other units within the canyons. The Martian climatic history indicated that any ancient lakes were ice covered. Two methods for transporting sediment through a cover of ice on a martian lake appear to be feasible. Based on the presently available data, along with the theoretical calculations presented, it appears most likely that the layered deposits in the Valles Marineris were laid down in standing bodies of water.

Nedell, Susan S.↗

Paleomagnetic and structural evidence for localized tectonic rotation associated with fault drag in the northeastern Mojave Desert: Implications for the late Cenozoic tectonic evolution of the Eastern California shear zone

Paleomagnetic data, coupled with detailed geological analysis of the southeastern Goldstone Lake region, indicate that lower Miocene volcanic and epiclastic rocks of the Pink Canyon area have been folded, faulted and tectonically rotated approximately 28.4 + or - 9.0 deg clockwise about a vertical axis. The Coyote Canyon Fault is locally folded about a vertical axis approximately 25 deg in a clockwise sense in the Pink Canyon area. Timing relationships indicate that rotation is post-early Miocene; regional relationships imply that deformation is late Miocene to Holocene in age. These relationships imply that tectonic rotation is local rather than regional in extent as proposed by some tectonic models. The results of this study are generally consistent with the Dokka and Travis model and the subsequently revised Dokka model of strain partitioning in the northeastern Mojave Desert block.

Macconnell, D. F.↗

The Transition of High-Resolution NASA MODIS Sea Surface Temperatures into the WRF Environmental Modeling System

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Moderate Resolution Imaging Spectroradiometer (MODIS) sea surface temperature (SST) composite at 2-km resolution that has been implemented in version 3 of the National Weather Service (NWS) Weather Research and Forecasting (WRF) Environmental Modeling System (EMS). The WRF EMS is a complete, full physics numerical weather prediction package that incorporates dynamical cores from both the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). The installation, configuration, and execution of either the ARW or NMM models is greatly simplified by the WRF EMS to encourage its use by NWS Weather Forecast Offices (WFOs) and the university community. The WRF EMS is easy to run on most Linux workstations and clusters without the need for compilers. Version 3 of the WRF EMS contains the most recent public release of the WRF-NMM and ARW modeling system (version 3 of the ARW is described in Skamarock et al. 2008), the WRF Pre-processing System (WPS) utilities, and the WRF Post-Processing program. The system is developed and maintained by the NWS National Science Operations Officer Science and Training Resource Coordinator. To initialize the WRF EMS with high-resolution MODIS SSTs, SPoRT developed the composite product consisting of MODIS SSTs over oceans and large lakes with the NCEP Real-Time Global (RTG) filling data over land points. Filling the land points is required due to minor inconsistencies between the WRF land-sea mask and that used to generate the MODIS SST composites. This methodology ensures a continuous field that adequately initializes all appropriate arrays in WRF. MODIS composites covering the Gulf of Mexico, western Atlantic Ocean and the Caribbean are generated daily at 0400, 0700, 1600, and 1900 UTC corresponding to overpass times of the NASA Aqua and Terra polar orbiting satellites. The MODIS SST product is output in gridded binary-1 (GRIB-1) data format for a seamless incorporation into WRF via the WPS utilities. The full-resolution, 1-km MODIS product is sub-sampled to 2-km grid spacing due to limitations in handling very large dimensions in the GRIB-1 data format. The GRIB-1 files are posted online at ftp://ftp.nsstc.org/sstcomp/WRF/, which is directly accessed by the WRF EMS scripts. The MODIS SST composites are also downloaded to the EMS data server, which is accessible by the WRF EMS users and NWS WFOs. The SPoRT MODIS SST composite provides the model with superior detail of the ocean gradients around Florida and surrounding waters, whereas the operational RTG SST typically depicts a relatively smooth field and is not able to capture sharp horizontal gradients in SST. Differences of 2-3 C are common over small horizontal distances, leading to enhanced SST gradients on either side of the Gulf Stream and along the edges of the cooler shelf waters. These sharper gradients can in turn produce atmospheric responses in simulated temperature and wind fields as depicted in LaCasse et al. Differences in atmospheric verification statistics over a several month study were generally small in the vicinity of south Florida; however, the validation of SSTs at specific buoy locations revealed important improvements in the biases and RMS errors, especially in the vicinity of the cooler shelf waters off the east-central Florida coast. A current weakness in the MODIS SST product is the occurrence of occasional discontinuities caused by high latency in SST coverage due to persistent cloud cover. An enhanced method developed by Jedlovec et al. (2009, GHRSST User Symposium) reduces the occurrence of these problems by adding Advanced Microwave Scanning Radiometer -- EOS (AMSR-E) SST data to the compositing process. Enhanced SST composites are produced over the ocean regions surrounding the Continental U.S. at four times each day corresponding to Terra and Aqua equator crossing times. For a given day and overpass time, both MODInd AMSR-E data from the previous seven days form a collection used in the compositing. At each MODIS pixel, cloud-free SST values from the collection are used to form a weighted average based on their latency (number of days from the current day). In this way, recent SST data are given more weight than older data. One of the primary issues involved in incorporating the AMSR-E microwave data in the composites is the tradeoff between the decreased spatial resolution of the AMSR-E data (25 km) and the increased coverage due to its near all-weather capability. Currently, the AMSR-E is given a weight of 20% compared to MODIS data, thereby preserving the spatial structure observed in the MODIS data. Day-time (night-time) AMSR-E SST data from Aqua are used with both Terra and Aqua MODIS day-time (night-time) SST data sets.

Case, Jonathan L.↗

Hyperspectral Imager for the Coastal Ocean (HICO): Overview, Operational Updates, and Coastal Ocean Applications

The Hyperspectral Imager for the Coastal Ocean (HICO) was built to measure in‐water properties of complex coastal regions. HICO enables synoptic coverage; 100‐meter spatial resolution for sampling the variability and spatial irregularity of coastal waters; and high spectral resolution to untangle the signals from chlorophyll, colored dissolved organic matter, suspended sediments and varying bottom types. HICO was built by the Naval Research Laboratory, installed on the International Space Station (ISS) in September 2009, and operated for ONR for the first three years. In 2013, NASA assumed sponsorship of operations in order to leverage HICO's ability to address their Earth monitoring mission. This has opened up access of HICO data to the broad research community. Over 8000 images are now available on NASA's Ocean Color Website (http://oceancolor.gsfc.nasa.gov/cgi/browse.pl?sen=hi). Oregon State University's HICO website (http://hico.coas.oregonstate.edu) remains the portal for researchers to request new collections and access their requested data. We will present updates on HICO's calibration and improvements in geolocation and show examples of the use of HICO data to address issues in the coastal ocean and Great Lakes.

Davis, Curtiss O.↗

Modeling and Observations of Outlet Canyons from Lake Overflow Floods on Early Mars

Numerous observations from both orbital remote sensing [1-3] and Mars Curiosity [4] suggest that lakes were once part of the martian landscape. From orbital data, one of the key lines of evidence for past paleolakes is the existence of several hundred valley network-fed basins – usually craters – that have outlet valleys that remain perched above their floors. The existence of outlets requires that water ponded to the point that it overflowed confining topography. Beyond recognizing these landforms, there has been only limited work reconstructing the morphometry, formative hydrology, and incision history for these outlets. Here, we describe our recently published observations of outlets and ongoing numerical modeling looking at these factors.

Fassett, Caleb I.↗

Integrating Deep Learning and Hydrodynamic Modeling to Improve the Great Lakes Forecast

The Laurentian Great Lakes, one of the world’s largest surface freshwater systems, pose a modeling challenge in seasonal forecast and climate projection. While physics-based hydrodynamic modeling is a fundamental approach, improving the forecast accuracy remains critical. In recent years, machine learning (ML) has quickly emerged in geoscience applications, but its application to the Great Lakes hydrodynamic prediction is still in its early stages. This work is the first one to explore a deep learning approach to predicting spatiotemporal distributions of the lake surface temperature (LST) in the Great Lakes. Our study shows that the Long Short-Term Memory (LSTM) neural network, trained with the limited data from hypothetical monitoring networks, can provide consistent and robust performance. The LSTM prediction captured the LST spatiotemporal variabilities across the five Great Lakes well, suggesting an effective and efficient way for monitoring network design in assisting the ML-based forecast. Furthermore, we employed an explainable artificial intelligence (XAI) technique named SHapley Additive exPlanations (SHAP) to uncover how the features impact the LSTM prediction. Our XAI analysis shows air temperature is the most influential feature for predicting LST in the trained LSTM. The relatively large bias in the LSTM prediction during the spring and fall was associated with substantial heterogeneity of air temperature during the two seasons. In contrast, the physics-based hydrodynamic model performed better in spring and fall yet exhibited relatively large biases during the summer stratification period. Finally, we developed a statistical integration of the hydrodynamic modeling and deep learning results based on the Best Linear Unbiased Estimator (BLUE). The integration further enhanced prediction accuracy, suggesting its potential for next-generation Great Lakes forecast systems.

Xue, Pengfei (ORCID:000000025702421X)↗