NASA NTRS · 20160014729
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Quick, Mason G., Blakeslee, Richard J., Christian, Hugh, Stewart, Mike, Podgorny, Scott, Corredor, David. 2016-12-12. Fly's Eye GLM Simulator. https://ntrs.nasa.gov/citations/20160014729
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Snow covers a maximum of 47 million km 2 of Earth's northern hemisphere each winter and is an important component of the planet's energy balance, hydrology cycles, and ecosystems. Monitoring regional and global snow cover has increased in urgency in recent years due to warming temperatures and declines in snow cover extent. Optical satellite instruments provide large-scale observations of snow cover, but cloud cover and dense forest canopy can reduce accuracy in mapping snow cover. Remote camera networks deployed for wildlife monitoring operate below cloud cover and in forests, representing a virtually untapped source of snow cover observations to supplement satellite observations. Using images from 1,181 wildlife cameras deployed by the Norwegian Institute for Nature Research (NINA), we compared snow cover extracted from camera images to Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover products during winter months of 2018–2020. Ordinal snow classifications (scale = 0–4) from cameras were closely related to normalized difference snow index (NDSI) values from the MODIS Terra Snow Cover Daily L3 Global 500m (MOD10A1) Collection 6 product (R 2 = 0.70). Tree canopy cover, the normalized difference vegetation index (NDVI), and image color mode influenced agreement between camera images and MOD10A1 NDSI values. For MOD10A1F, MOD10A1's corresponding cloud-gap filled product, agreement with cloud-gap filled values decreased from 78.5% to 56.4% in the first three days of cloudy periods and stabilized thereafter. Using our camera data as validation, we derived a threshold to create daily binary maps of snow cover from the MOD10A1 product. The threshold corresponding to snow presence was an NDSI value of 40.50, which closely matched a previously defined global binary threshold of 40 using the MOD10A2 8-day product. These analyses demonstrate the utility of camera trap networks for validation of snow cover products from satellite remote sensing, as well as their potential to identify sources of inaccuracy.
A rotating rake mode measurement system was designed to measure acoustic duct modes generated by a fan stage. After analysis of the measured data, the mode coefficient amplitudes and phases were quantified. Early studies using this system found that mode power levels computed from rotating rake measured data would agree with the far-field power levels. However, this agreement required that the sound from the noise sources within the duct propagated outward from the duct exit without reflection and previous studies suggested conditions could exist where significant reflections could occur. This paper shows that mounting a second rake to the rotating system, with an offset in both the axial and the azimuthal directions, measures the data necessary to determine the modes propagating in both directions within a duct. The rotating rake data analysis technique was extended to include the data measured by the second rake. The analysis resulted in a set of circumferential mode coefficients at each of the two rake microphone locations. Radial basis functions were then least-squares fit to this data to obtain the radial mode coefficients for the modes propagating in both directions within the duct while accounting for the presence of evanescent modes. The validation of the dual-rotating-rake measurements was conducted using data from a combination of experiments and numerical calculations to compute reflection coefficients and other mode coefficient ratios. Compared to results from analytical and numerical computations, the results from dual-rotating-rake measured data followed the expected trends when frequency, mode number, and duct termination geometry were changed.
Current performance and existing problems in SMAP radiometer L1B_TB version 3 data product are described. The post-launch calibration algorithm has been updated by calibrating the three calibration parameters (the equivalent noise temperature of the noise diode, the offset of the reference load, and the antenna gain) jointly by using the global ocean and CS with both 110o and 180o pitch maneuvers after the reflector emissivity is calibrated. The results show that both calibration drift during eclipse season and bias over CS are removed. The RMSDs of the calibration drift over both the global ocean and CS are less than 0.1 K, and the goals of the calibration algorithm upgrade are achieved for coming L1B_TB version 4 data release.