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NASA NTRS2010

Sonic Booms on Big Structures (SonicBOBS) Phase I Database; NASA Dryden Sensors

This DVD contains 13 channels of microphone and up to 22 channels of pressure transducer data collected in September, 2009 around several buildings located at Edwards Air Force Base. These data were recorded by NASA Dryden. Not included are data taken by NASA Langley and Gulfstream. Each day's data is in a separate folder and each pass is in a file beginning with "SonicBOBS_" (for microphone data) or "SonicBOBSBB_" (for BADS and BASS data) followed by the month, day, year as two digits each, followed by the hour, minute, sec after midnight GMT. The filename time given is for the END time of the raw recording file. In the case of the microphone data, this time may be several minutes after the sonic boom, and is according to the PC's uncalibrated clock. The Matlab data files have the actual time as provided by a GPS-based IRIG-B signal recorded concurrently with the data. Microphone data is given for 5 seconds prior to 20 seconds after the sonic boom. BADS and BASS data is given for the full recording, 6 seconds for the BADS and 10 seconds for the BASS. As an example of the naming convention, file "SonicBOBS_091209154618.mat" is from September 12, 2009 at 15:46:18 GMT. Note that data taken on September 12, 2009 prior to 01:00:00 GMT was of the Space Shuttle Discovery (a sonic boom of opportunity), which was on September 11, 2009 in local Pacific Daylight Time.

Haering, Edward A., Jr.↗

NASA NTRS2010

X/Ka Celestial Frame Improvements: Vision to Reality

In order to extend the International Celestial Reference Frame from its S/X-band (2.3/8.4 GHz) basis to a complementary frame at X/Ka-band (8.4/32 GHz), we began in mid-2005 an ongoing series of X/Ka observations using NASA s Deep Space Network (DSN) radio telescopes. Over the course of 47 sessions, we have detected 351 extra-galactic radio sources covering the full 24 hours of right ascension and declinations down to -45 degrees. Angular source position accuracy is at the part-per-billion level. We developed an error budget which shows that the main errors arise from limited sensitivity, mismodeling of the troposphere, uncalibrated instrumental effects, and the lack of a southern baseline. Recent work has improved sensitivity by improving pointing calibrations and by increasing the data rate four-fold. Troposphere calibration has been demonstrated at the mm-level. Construction of instrumental phase calibrators and new digital baseband filtering electronics began in recent months. We will discuss the expected effect of these improvements on the X/Ka frame.

Jacobs, C. S.↗

NASA NTRS2006

Tracking the Martian CO2 Polar Ice Caps in Infrared Images

Researchers at NASA s Jet Propulsion Laboratory have developed a method for automatically tracking the polar caps on Mars as they advance and recede each year (see figure). The seasonal Mars polar caps are composed mainly of CO2 ice and are therefore cold enough to stand out clearly in infrared data collected by the Thermal Emission Imaging System (THEMIS) onboard the Mars Odyssey spacecraft. The Bimodal Image Temperature (BIT) histogram analysis algorithm analyzes raw, uncalibrated data to identify images that contain both "cold" ("polar cap") and "warm" ("not polar cap") pixels. The algorithm dynamically identifies the temperature that separates these two regions. This flexibility is critical, because in the absence of any calibration, the threshold temperature can vary significantly from image to image. Using the identified threshold, the algorithm classifies each pixel in the image as "polar cap" or "not polar cap," then identifies the image row that contains the spatial transition from "polar cap" to "not polar cap." While this method is useful for analyzing data that has already been returned by THEMIS, it has even more significance with respect to data that has not yet been collected. Instead of seeking the polar cap only in specific, targeted images, the simplicity and efficiency of this method makes it feasible for direct, onboard use. That is, THEMIS could continuously monitor its observations for any detections of the polar-cap edge, producing detections over a wide range of spatial and temporal conditions. This effort can greatly contribute to our understanding of long-term climatic change on Mars.

Wagstaff, Kiri L.↗

NASA NTRS2012

Restoration and Reexamination of Apollo Lunar Dust Detector Data from Original Telemetry Files

We are recovering the original telemetry (Figure I) from the Apollo Dust, Thermal, Radiation Environment Monitor (DTREM) experiment, more commonly known as the Dust Detector, and producing full time resolution (54 second) data sets for release through the Planetary Data System (PDS). The primary objective of the experiment was to evaluate the effect of dust deposition, temperature, and radiation damage on solar cells on the lunar surface. The monitor was a small box consisting of three solar cells and thermistors mounted on the ALSEP (Apollo Lunar Surface Experiments Package) central station. The Dust Detector was carried on Apollo's 11, 12, 14 and 15. The Apollo 11 DTREM was powered by solar cells and only operated for a few months as planned. The Apollo 12, 14, and 15 detectors operated for 5 to 7 years, returning data every 54 seconds, consisting of voltage outputs from the three solar cells and temperatures measured by the three thermistors. The telemetry was received at ground stations and held on the Apollo Housekeeping (known as "Word 33") tapes. made available to the National Space Science Data Center (NSSDC) by Yosio Nakamura (University of Texas Institute for Geophysics). We have converted selected parts of the telemetry into uncalibrated and calibrated output voltages and temperatures.

McBride, M. J.↗

NASA NTRS2012

Distributed Assimilation of Satellite-based Snow Extent for Improving Simulated Streamflow in Mountainous, Dense Forests: An Example Over the DMIP2 Western Basins

Snow cover area affects snowmelt, soil moisture, evapotranspiration, and ultimately streamflow. For the Distributed Model Intercomparison Project - Phase 2 Western basins, we assimilate satellite-based fractional snow cover area (fSCA) from the Moderate Resolution Imaging Spectroradiometer, or MODIS, into the National Weather Service (NWS) SNOW-17 model. This model is coupled with the NWS Sacramento Heat Transfer (SAC-HT) model inside the National Aeronautics and Space Administration's (NASA) Land Information System. SNOW-17 computes fSCA from snow water equivalent (SWE) values using an areal depletion curve. Using a direct insertion, we assimilate fSCAs in two fully distributed ways: 1) we update the curve by attempting SWE preservation, and 2) we reconstruct SWEs using the curve. The preceding are refinements of an existing simple, conceptually-guided NWS algorithm. Satellite fSCA over dense forests inadequately accounts for below-canopy snow, degrading simulated streamflow upon assimilation during snowmelt. Accordingly, we implement a below-canopy allowance during assimilation. This simplistic allowance and direct insertion are found to be inadequate for improving calibrated results, still degrading them as mentioned above. However, for streamflow volume for the uncalibrated runs, we obtain: (1) substantial to major improvements (64-81 %) as a percentage of the control run residuals (or distance from observations), and (2) minor improvements (16-22 %) as a percentage of observed values. We highlight the need for detailed representations of canopy-snow optical radiative transfer processes in mountainous, dense forest regions if assimilation-based improvements are to be seen in calibrated runs over these areas.

Yatheendradas, Soni↗

NASA NTRS2012

Earth Radiation Imbalance from a Constellation of 66 Iridium Satellites: Climate Science Aspects

The "global warming hiatus" since the 1998 El Nino, highlighted by Meehl et al., and the resulting "missing energy" problem highlighted by Trenberth et al., has opened the door to a more fundamental view of climate change than mere surface air temperature. That new view is based on two variables which are strongly correlated: the rate of change of ocean heat content d(OHC)/dt; and Earth Radiation Imbalance (ERI) at the top of the atmosphere, whose guesstimated range is 0.4 to 0.9 Watts per square meters (this imbalance being mainly due to increasing CO2). The Argo float array is making better and better measurements of OHC. But existing satellite systems cannot measure ERI to even one significant digit. So, climate model predictions of ERI are used in place of real measurements of it, and the satellite data are tuned to the climate model predictions. Some oceanographers say "just depend on Argo for understanding the global warming hiatus and the missing energy", but we don't think this is a good idea because d(OHC)/dt and ERI have different time scales and are never perfectly correlated. We think the ERB community needs to step up to measuring ERI correctly, just as oceanographers have deployed Argo to measure OHC correctly. This talk will overview a proposed constellation of 66 Earth radiation budget instruments, hosted on Iridium satellites, that will actually be able to measure ERI to at least one significant digit, thus enabling a crucial test of climate models. This constellation will also be able to provide ERI at two-hourly time scales and 500-km spatial scales without extrapolations from uncalibrated narrowband geostationary instruments, using the highly successful methods of GRACE to obtain spatial resolution. This high time resolution would make ERI a synoptic variable like temperature, and allow studies of ERI's response to fast-evolving phenomena like dust storms and hurricanes and even brief excursions of Total Solar Irradiance. Time permitting, we will also discuss the emerging view of clear vs. cloudy and its implications for the traditional ERB approach.

Wiscombe, W.↗

NASA NTRS2012

Earth Radiation Imbalance from a Constellation of 66 Iridium Satellites: Technological Aspects

Iridium Communications Inc. is launching a new generation of polar orbiting communication satellites in 2015-2017. Iridium will provide a hosted payload bay on each of the 66 satellites (plus 6 in-space spares). This offers the potential for a paradigm shift in the way we measure Earth radiation imbalance from space, as well as massive cost savings. Because the constellation provides 24/7 global coverage, there is no need to account for diurnal cycle via extrapolations from uncalibrated narrowband geostationary imagers. And the spares can be rolled over to view the Sun and deep space, then transfer their calibration to the other members of the constellation during the frequent cross-overs. In part using simulations of the constellation viewing realistic Earth scenes, this presentation will address the technological aspects of such a constellation: (1) the calibration strategy; (2) the highly-accurate and stable radiometers for measuring outgoing flux; and (3) the GRACE-inspired algorithms for representing the outgoing flux field in spherical harmonics and thus achieving rv500-km spatial resolution and two-hour temporal resolution.

Wiscombe, W.↗

NASA NTRS2012

Laser Mode Behavior of the Cassini CIRS Fourier Transform Spectrometer at Saturn

The CIRS Fourier transform spectrometer aboard the NASA/ESA/ASI Cassini orbiter has been acquiring spectra of the Saturnian system since 2004. The CIRS reference interferometer employs a laser diode to trigger the interferogram sampling. Although the control of laser diode drive current and operating temperature are stringent enough to restrict laser wavelength variation to a small fraction of CIRS finest resolution element, the CIRS instrument does need to be restarted every year or two, at which time it may start in a new laser mode. By monitoring the Mylar absorption features in uncalibrated spectra due to the beam splitter Mylar substrate, it can be shown that these jumps are to adjacent modes and that most of the eight-year operation so far is restricted to three adjacent modes. For a given mode, the wavelength stability appears consistent with the stability of the laser diode drive curren.t and operating temperature.

Brasunas, John C.↗

NASA NTRS2013

KINEROS2-AGWA: Model Use, Calibration, and Validation

KINEROS (KINematic runoff and EROSion) originated in the 1960s as a distributed event-based model that conceptualizes a watershed as a cascade of overland flow model elements that flow into trapezoidal channel model elements. KINEROS was one of the first widely available watershed models that interactively coupled a finite difference approximation of the kinematic overland flow equations to a physically based infiltration model. Development and improvement of KINEROS continued from the 1960s on a variety of projects for a range of purposes, which has resulted in a suite of KINEROS-based modeling tools. This article focuses on KINEROS2 (K2), a spatially distributed, event-based watershed rainfall-runoff and erosion model, and the companion ArcGIS-based Automated Geospatial Watershed Assessment (AGWA) tool. AGWA automates the time-consuming tasks of watershed delineation into distributed model elements and initial parameterization of these elements using commonly available, national GIS data layers. A variety of approaches have been used to calibrate and validate K2 successfully across a relatively broad range of applications (e.g., urbanization, pre- and post-fire, hillslope erosion, erosion from roads, runoff and recharge, and manure transport). The case studies presented in this article (1) compare lumped to stepwise calibration and validation of runoff and sediment at plot, hillslope, and small watershed scales; and (2) demonstrate an uncalibrated application to address relative change in watershed response to wildfire.

Erosion↗

NASA NTRS2018

Satellite Remote Sensing Estimation of River Discharge: Application to the Yukon River Alaska

A methodology based on general hydraulic relations for rivers has been developed to estimate the discharge (flow rate) of rivers using satellite remote sensing observations. The estimates of discharge, flow depth, and flow velocity are derived from remotely observed water surface area, water surface slope, and water surface height, and demonstrated for two reaches of the Yukon River in Alaska, at Eagle (reach length 34.7 km) and near Stevens Village (reach length 38.3 km). The method is based on fundamental equations of hydraulic flow resistance in rivers, including the Manning equation and the Prandtl-von Karman universal velocity distribution equation. The method employs some new hydraulic relations to help define flow resistance and height of the zero flow boundary in the channel. Estimates are made both with and without calibration. The water surface area of the river reach is measured by using a provisional version of the U.S. Geological Survey (USGS) Landsat based product named Dynamic Surface Water Extent (DSWE). The water surface height and slope measurements require a self-consistent datum, and are derived from observations from the Jason-2 satellite altimeter mission. At both reach locations, the Jason-2 radar altimeter non-winter heights consistently tracked the stage recorded at USGS streamgages with a standard deviation of differences (error) during the non-winter periods of less than 7%. Part of the error may be due to differences in the gage and altimeter crossing locations with respect to the range of stage change and the response to changes in discharge at the upstream and downstream locations. For the non-winter periods, the radar derived slope estimates (mean = 0.0003) were constant over the mission lifetime, and in agreement with previously measured USGS water surface slopes and slopes determined from USGS topographic maps. The accuracy of the mean of the uncalibrated daily estimates of discharge varied between reaches, ranging from 13% near Stevens Village (N = 90) to −21% at Eagle (N = 246) based on the absolute error, and 5% to −6% based on the error of the log of the estimates. Calibrating to the mean of USGS daily discharge estimates from the streamflow rating for the same period of record at each streamgage resulted in mean absolute errors ranging from 1% to 2%, and log errors ranging from 1% or less. The error pattern of the estimates shows that without calibration, even though the mean is well simulated, the high and low end values over the range of estimates may have significant bias.

Bjerklie, David M.↗

NASA NTRS2019

Creating Calibration Curves to Determine Shock Pressure in Clinopyroxene

Impact cratering is an important geological process that occurs on every rocky body in the solar system. It alters the texture and mineralogy of rocks via shock metamorphism. The peak shock pressures experienced by a rock are traditionally evaluated using qualitative optical methods however, quantitative methods do exist. One such method was developed by Uchizono et al., who used X-ray Diffraction (XRD) to measure lattice strain (ε) in several artificially shocked olivine grains using XRD peak broadening as a function of tan θ, where θ is the diffraction angle. They plotted the ε values against the known peak shock pressures experienced by the olivine grains. Using this calibration curve, the precise shock pressure experienced by a grain of olivine can be determined using its measured ε value. Another method was developed by McCausland et al. and Izawa et al., who used in situ XRD to measure strain-related mosaicity (SRM) of olivine in several ordinary chondrites and enstatite in enstatite chondrites, respectively. They plotted these results against the shock stage estimates for these meteorites. Using these plots, meteorites can be assigned to shock stage bins by measuring the SRM of olivine and/or enstatite. Both methods are useful for evaluating shock metamorphism, however, they have limitations. Uchizono et al.’s calibration curve has been successfully applied to martian meteorites, however it can only be applied to olivine-bearing rocks. McCausland et al.’s and Izawa et al.’s SRM method is uncalibrated and is limited to binning meteorites by shock stage. This work aims to expand on both methods by creating calibration curves for clinopyroxene (CPX): one for ε, similar to Uchizono et al.’s calibration curve for olivine, and one for SRM. This will extend the application of shock calibration methods to a greater variety of rock types. Preliminary results are presented herein.

Jenkins, Laura E.↗

NASA NTRS2017

Juno Gravity Science: Preparing for Data Collection at Jupiter

One of the primary goals of the Juno mission is to investigate Jupiter’s interior by mapping its gravitational field with the gravity science instrument. The Juno spacecraft has two radio science components that comprise the gravity science instrument: the X-band telecommunications system for a X-up/X-down link and a Ka-band Translator for a Ka-up/Ka-down link. The Deep Space Network’s DSS-25 beam waveguide antenna at the Goldstone Deep Space Communications Complex in California provides the X- and Ka-band uplink alongside an Advanced Water Vapor Radiometer to calibrate tropospheric effects. X-band and Ka-band downlink data are collected with both open-loop and closed-loop receivers located at the complex. Utilization of Ka-band provides scientific benefit to the Doppler measurements, but also adds operational challenges. Pointing of the uplink and downlink Ka-band signals requires additional systems to be calibrated and operated by the Deep Space Network; and the higher frequency of Ka-band means the signal dynamics are increased by a factor of four over X-band signals. Due to the spacecraft’s elliptical orbit and 4000 kilometer perijove altitude, it accelerates at an extreme rate as it approaches Jupiter, inducing large dynamic ranges in Doppler range of approximately 6 MHz over 3 hours at Ka-band. After the installation of a new Ka-band transmitter at DSS-25 for Juno was completed in 2015, end-to-end testing was conducted to ensure readiness for operations at Jupiter and provide an initial assessment of the performance. Cruise testing was conducted in the same operational configuration that the system will be used in during perijove passes. Processed open-loop data yielded uncalibrated Doppler residuals of 1.9 mHz at X-band and 6.0 mHz at Ka-band with 5-second compression time. Conduction of these tests has prepared the instrument and the operations team for science data collection during the science phase of the mission.

Buccino, Dustin↗

NASA NTRS1993

Instrumental Biases in Ionospheric Measurement Derived from GPS Data

Line-of-sight ionosphere measurements derived from differencing dual frequency GPS range data are corrupted by instrumental biases in both receiver and GPS satellite transmitters due to hardware delays in the L1 and L2 signal paths. Using a global ionospheric shell model to fit GPS based ionospheric delay data from a world wide network of 30 to 40 receivers, we can estimate, with a single fit, satellite biases for the entire GPS constellation and receiver biases for all the uncalibrated receivers.

GPS↗

NASA NTRS2021

Status of the Moderate-resolution Imaging Spectroradiometer Level 1B Algorithm

The Moderate-resolution Imaging Spectroradiometer (MODIS) instruments are on-board the Aqua and Terra spacecraft, launched in 2002 and 1999, respectively. Since beginning operation, they have continued to collect valuable remote sensing data of the Earth in 36 spectral bands ranging in wavelengths from 0.41 to 14.5 μm. The Level 1B (L1B) algorithm produces calibrated top of the atmosphere (TOA) radiances for each Earth-view (EV) pixel and calibrated TOA reflectances for the reflective solar bands using geo-located, uncalibrated instrument data and calibration look up tables (LUTs) produced regularly by the MODIS Characterization Support Team (MCST). The L1B algorithm also calculates an uncertainty value for each EV pixel. The calibrated radiance and reflectance products are used to generate higher-level science products. A separate L1B code version is maintained for both MODIS instruments so that sensor specific issues can be handled individually. The current L1B algorithm version produces the Collection 6.1 (C6.1) products and was released in 2017. An overview of the C6.1 algorithm is provided together with improvements made since its release. Also discussed briefly are the planned improvements in the Collection 7 L1B algorithm.

MODIS↗

NASA NTRS2022

Terra and Aqua MODIS Collection 7 Level 1B Algorithm

MODIS continues to be an important instrument for NASA’s Earth Observing System (EOS). Terra and Aqua MODIS have produced more than 22 and 20 years of global datasets that have significantly helped scientists better understand the Earth’s systems respectively. The MODIS Level-1B (L1B) algorithms use the uncalibrated, geolocated Earth scene observations as input and convert the instrument response into calibrated reflectance and radiance, which are used to generate the downstream science products. The sustained calibration and characterization activities undertaken by the MODIS Characterization Support Team have resulted in several upgrades to the L1B algorithms in order to maintain accurate calibration in the data products. In this paper, we present an overview of the L1B algorithm designated as Collection 7. Various algorithm enhancements both in the reflective bands and thermal bands characterization, are currently under science testing and evaluation. Once applied in data processing (projected in early 2023), they are expected to manifest in improved science products, both in terms of radiometric accuracy and long-term stability.

MODIS↗

NASA NTRS2024

Effects of Water Limitation and Competition on Tree Carbon Allocation in an Earth System Modeling Framework

Earth system models (ESMs) have a limited capacity to represent plant functional diversity and shifts in trait distributions. Approaches to improving the representation of this complexity in ESMs include (i) optimality-based approaches that predict trait–environment responses and (ii) explicitly modelling coexistence and community assembly. These approaches are expected to converge only when optimality-based approaches identify competitively dominant strategies, which often differ from strategies that maximize ecosystem functioning or fitness components in monoculture. We used two models, LM3-PPA (a vegetation demographic model designed as an ESM component) and BiomeE (a computationally efficient analog for LM3-PPA), to explore how water limitation affects carbon allocation strategies of canopy trees. We compared competitive allocation strategies and those that maximize biomass or productivity in monoculture. We did not explicitly model coexistence or community assembly. Rather, we used model experiments to identify competitive and maximizing strategies in a two-dimensional trait space under different precipitation and mortality scenarios. At 10 eastern US locations, we simulated historical, wet and dry climate scenarios, novel drought and three different mortality scenarios (low, medium or high sensitivity to water deficit). For each site and scenario, we identified the competitive strategy and three maximizing strategies (maximum biomass, productivity or drought-tolerance). Root: leaf ratios tended to increase and leaf area tended to decrease with increasing water stress (increasing water limitation and its effects on mortality). However, relative to maximizing strategies, competitive strategies shifted towards greater allocation to roots and leaves with increasing water stress. Competitive overinvestments (greater allocation to roots and leaves by competitive strategies compared with maximizing strategies) were robust across different modelling contexts, including vegetation parameter sets (Acer vs. Populus), models (LM3-PPA vs. BiomeE) and uncalibrated vs. calibrated BiomeE versions. Synthesis: The theoretical prediction that competitive and maximizing allocation strategies differ under water limitation is confirmed for a demographic model designed as an ESM component. Optimality-based trait predictions can simplify representing trait diversity in ESMs but do not always correspond to competitive outcomes. Explicitly modelling coexistence and community assembly in ESMs is challenging but is likely the most general approach to representing trait diversity.

vegetation demographic model↗

DOE OSTI2020

Calibration and Uncertainty Estimation Using the Ensemble Kalman Filter with a Large Subsurface Flow and Transport Model - 20321

At routinely monitored groundwater contamination sites, periodically measured environmental conditions such as groundwater levels and contaminant concentrations are used to inform and confirm a conceptual site model (CSM) and guide the development and calibration of a numerical groundwater flow and transport model. The calibration of groundwater flow and transport models after each measurement (sampling) event can illuminate deficiencies in a CSM, identify areas where additional monitoring is warranted, and predict the behavior of the system to guide decision making. However, manual and automated (e.g. PEST) model calibration tools can be time-consuming and computationally expensive to implement after each sampling event. Perhaps as a result, such calibration tools generally utilize all available monitoring data simultaneously rather than sequentially assimilating monitoring data one sampling event at a time as the results from sampling become available. A more real-time data assimilation approach may reduce parameter uncertainty, quantify the value of additional monitoring data, and produce a usable model more quickly and with less effort. To mitigate the potential time-consuming aspects of manual and widely applied automated calibration techniques, a data assimilation algorithm called the ensemble Kalman filter (EnKF) was evaluated as a relatively efficient method of model calibration and uncertainty assessment via the sequential integration of monitoring data into a model. The EnKF was able to successfully and efficiently assimilate monitoring and modeling data to calibrate a complex flow and transport model at a real-world site with significant subsurface heterogeneity, uncertainty, and 12 years of monitoring data (over 4,000 individual measurements of groundwater levels and over 2,500 measurements of contaminant concentrations). Starting with an uncalibrated model data from annual sampling events were sequentially assimilated, and the resultant predication errors and estimated parameter uncertainties were tracked. After all monitoring data were assimilated, both flow and transport residuals at the end of the EnKF process were comparable to those produced via a concurrent PEST calibration effort but required fewer model simulations. Both uncertainty and prediction errors decreased over time. In a real-time application, the adequacy of the model could be assessed after each sampling event. The benefits of such a real-time approach to utilizing monitoring data include reduced costs (in the form of model updates or site characterization efforts), early flagging of possible errors in the CSM, and a reduced risk of overfitting and corresponding increased confidence in model predictions. This tool may be particularly useful compared to other calibration techniques (e.g. manual, PEST) when model runtimes are long, calibration parameters are many, or parameter uncertainty is large. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗