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NASA NTRS2015

Multi-Model Ensemble Wake Vortex Prediction

Several multi-model ensemble methods are investigated for predicting wake vortex transport and decay. This study is a joint effort between National Aeronautics and Space Administration and Deutsches Zentrum fuer Luft- und Raumfahrt to develop a multi-model ensemble capability using their wake models. An overview of different multi-model ensemble methods and their feasibility for wake applications is presented. The methods include Reliability Ensemble Averaging, Bayesian Model Averaging, and Monte Carlo Simulations. The methodologies are evaluated using data from wake vortex field experiments.

Koerner, Stephan↗

NASA NTRS2015

Multi-Model Ensemble Wake Vortex Prediction

Koerner, Stephan↗

NASA NTRS2016

Retrievals of Cloud Droplet Size from the RSP Data: Validation Using in Situ Measurements

We present comparisons of cloud droplet size distributions retrieved from the Research Scanning Polarimeter (RSP) data with correlative in situ measurements made during the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). This field experiment was based at St. Johns airport, Newfoundland, Canada with the latest deployment in May - June 2016. RSP was onboard the NASA C-130 aircraft together with an array of in situ and other remote sensing instrumentation. The RSP is an along-track scanner measuring polarized and total reflectances in9 spectral channels. Its unique high angular resolution allows for characterization of liquid water droplet size using the rainbow structure observed in the polarized reflectances in the scattering angle range between 135 and 165 degrees. A parametric fitting algorithm applied to the polarized reflectances provides retrievals of the droplet effective radius and variance assuming a prescribed size distribution shape (gamma distribution). In addition to this, we use a non-parametric method, Rainbow Fourier Transform (RFT), which allows us to retrieve the droplet size distribution (DSD) itself. The latter is important in the case of clouds with complex structure, which results in multi-modal DSDs. During NAAMES the aircraft performed a number of flight patterns specifically designed for comparison of remote sensing retrievals and in situ measurements. These patterns consisted of two flight segments above the same straight ground track. One of these segments was flown above clouds allowing for remote sensing measurements, while the other was at the cloud top where cloud droplets were sampled. We compare the DSDs retrieved from the RSP data with in situ measurements made by the Cloud Droplet Probe (CDP). The comparisons show generally good agreement with deviations explainable by the position of the aircraft within cloud and by presence of additional cloud layers in RSP view that do not contribute to the in situ DSDs. In the latter case the distributions retrieved from the RSP data were consistent with the multi-layer cloud structures observed in the correlative High Spectral Resolution Lidar (HSRL) profiles. The comparison results provide a rare validation of polarimetric droplet size retrieval techniques, which can be used for analysis of satellite data on global scale.

cloud droplets↗

NASA NTRS2016

NASA AVOSS Fast-Time Models for Aircraft Wake Prediction: User's Guide (APA3.8 and TDP2.1)

NASA's current distribution of fast-time wake vortex decay and transport models includes APA (Version 3.8) and TDP (Version 2.1). This User's Guide provides detailed information on the model inputs, file formats, and model outputs. A brief description of the Memphis 1995, Dallas/Fort Worth 1997, and the Denver 2003 wake vortex datasets is given along with the evaluation of models. A detailed bibliography is provided which includes publications on model development, wake field experiment descriptions, and applications of the fast-time wake vortex models.

Ahmad, Nash'at N.↗

NASA NTRS2016

Validating MODIS Above-Cloud Aerosol Optical Depth Retrieved from Color Ratio Algorithm Using Direct Measurements Made by NASA's Airborne AATS and 4STAR Sensors

We present the validation analysis of above-cloud aerosol optical depth (ACAOD) retrieved from the color ratio method applied to MODIS cloudy-sky reflectance measurements using the limited direct measurements made by NASAs airborne Ames Airborne Tracking Sunphotometer (AATS) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) sensors. A thorough search of the airborne database collection revealed a total of five significant events in which an airborne sun photometer, coincident with the MODIS overpass, observed partially absorbing aerosols emitted from agricultural biomass burning, dust, and wildfires over a low-level cloud deck during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS 2013 campaigns, respectively. The co-located satellite-airborne match ups revealed a good agreement (root-mean-square difference less than 0.1), with most match ups falling within the estimated uncertainties associated with the MODIS retrievals (about -10 to +50 ). The co-retrieved cloud optical depth was comparable to that of the MODIS operational cloud product for ACE-ASIA and SEAC4RS, however, higher by 30-50% for the SAFARI-2000 case study. The reason for this discrepancy could be attributed to the distinct aerosol optical properties encountered during respective campaigns. A brief discussion on the sources of uncertainty in the satellite-based ACAOD retrieval and co-location procedure is presented. Field experiments dedicated to making direct measurements of aerosols above cloud are needed for the extensive validation of satellite based retrievals.

airborne sun photometer↗

NASA NTRS2016

Evaluating Multispectral Snowpack Reflectivity With Changing Snow Correlation Lengths

This study investigates the sensitivity of multispectral reflectivity to changing snow correlation lengths. Matzler's ice-lamellae radiative transfer model was implemented and tested to evaluate the reflectivity of snow correlation lengths at multiple frequencies from the ultraviolet (UV) to the microwave bands. The model reveals that, in the UV to infrared (IR) frequency range, the reflectivity and correlation length are inversely related, whereas reflectivity increases with snow correlation length in the microwave frequency range. The model further shows that the reflectivity behavior can be mainly attributed to scattering rather than absorption for shallow snowpacks. The largest scattering coefficients and reflectivity occur at very small correlation lengths (approximately 10(exp -5 m) for frequencies higher than the IR band. In the microwave range, the largest scattering coefficients are found at millimeter wavelengths. For validation purposes, the ice-lamella model is coupled with a multilayer snow physics model to characterize the reflectivity response of realistic snow hydrological processes. The evolution of the coupled model simulated reflectivities in both the visible and the microwave bands is consistent with satellite-based reflectivity observations in the same frequencies. The model results are also compared with colocated in situ snow correlation length measurements (Cold Land Processes Field Experiment 2002-2003). The analysis and evaluation of model results indicate that the coupled multifrequency radiative transfer and snow hydrology modeling system can be used as a forward operator in a data-assimilation framework to predict the status of snow physical properties, including snow correlation length.

Kang, Do Hyuk↗

NASA NTRS2016

2016 International Land Model Benchmarking (ILAMB) Workshop Report

As earth system models (ESMs) become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of terrestrial biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistryclimate feedbacks and ecosystem processes in these models are essential for reducing the acknowledged substantial uncertainties in 21st century climate change projections.

earth system models (ESMs)↗

NASA NTRS2017

Soil Moisture Retrieval with Airborne PALS Instrument over Agricultural Areas in SMAPVEX16

NASA's SMAP (Soil Moisture Active Passive) calibration and validation program revealed that the soil moisture products are experiencing difficulties in meeting the mission requirements in certain agricultural areas. Therefore, the mission organized airborne field experiments at two core validation sites to investigate these anomalies. The SMAP Validation Experiment 2016 included airborne observations with the PALS (Passive Active L-band Sensor) instrument and intensive ground sampling. The goal of the PALS measurements are to investigate the soil moisture retrieval algorithm formulation and parameterization under the varying (spatially and temporally) conditions of the agricultural domains and to obtain high resolution soil moisture maps within the SMAP pixels. In this paper the soil moisture retrieval using the PALS brightness temperature observations in SMAPVEX16 is presented.

SMAPVEX15↗

NASA NTRS2018

Retrievals of Cloud Droplet Size from the Research Scanning Polarimeter Data: Validation Using In Situ Measurements

We present comparisons of cloud droplet size distributions (DSDs) retrieved from the research scanning polarimeter (RSP) data with correlative in situ measurements made during the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). The airborne portion of this field experiment was based out of St. John's airport, Newfoundland, Canada with the focus of this paper being on the deployment in May - June 2016. RSP was onboard the NASA C-130 aircraft together with an array of in situ and other remote sensing instrumentation. The RSP is an along-track scanner measuring the polarized and total reflectance in 9 spectral channels. Its uniquely high angular resolution allows for characterization of liquid water droplet sizes using the rainbow structure observed in the polarized reflectance over the scattering angle range from 135 to 165.degrees The rainbow is dominated by single scattering of light by cloud droplets, so its structure is characteristic specifically of the droplet sizes at cloud top (within unit optical depth into the cloud, equivalent to approximately 50m). A parametric fitting algorithm applied to the polarized reflectance provides retrievals of the droplet effective radius and variance assuming a prescribed size distribution shape (gamma distribution). In addition to this, we use a non-parametric method, the Rainbow Fourier Transform (RFT), which allows us to retrieve the droplet size distribution itself. The latter is important in the case of clouds with complex microphysical structure, or multiple layers of cloud, which result in multi-modal DSDs. During NAAMES the aircraft performed a number of flight patterns specifically designed for comparisons between remote sensing retrievals and in situ measurements. These patterns consisted of two flight segments above the same straight ground track. One of these segments was flown above clouds allowing for remote sensing measurements, while the other was near the cloud top where cloud droplets were sampled. We compare the DSDs retrieved from the RSP data with in situ measurements made by the Cloud Droplet Probe (CDP). The comparisons generally show good agreement (better than 1 micron for effective radius and in most cases better than 0.02 for effective variance) with deviations explainable by the position of the aircraft within the cloud, or by the presence of additional cloud layers between the cloud being sampled by the in situ instrumentation and the altitude of the remote sensing segment. In the latter case, the multi-modal DSDs retrieved from the RSP data were consistent with the multi-layer cloud structures observed in the correlative High Spectral Resolution Lidar (HSRL) profiles. The results of these comparisons provide a rare validation of polarimetric droplet size retrieval techniques, demonstrating their accuracy and robustness and the potential of satellite data of this kind on a global scale.

Remote Sensing↗

NASA NTRS2018

Aerosols in Atmospheric Chemistry and Biogeochemical Cycles of Nutrients

Atmospheric aerosols have complex and variable compositions and properties.While scientific interest is centered on the health and climatic effects of atmospheric aerosols, insufficient attention is given to their involvement in multiphase chemistry that alters their contribution as carriers of nutrients in ecosystems. However, there is experimental proof that the nutrient equilibria of both land and marine ecosystems have been disturbed during the Anthropocene period. This review study first summarizes our current understanding of aerosol chemical processing in the atmosphere as relevant to biogeochemical cycles. Then it binds together results of recent modeling studies based on laboratory and field experiments, focusing on the organic and dust components of aerosols that account for multiphase chemistry, aerosol ageing in the atmosphere, nutrient (N, P, Fe) emissions, atmospheric transport, transformation and deposition. The human-driven contribution to atmospheric deposition of these nutrients, derived by global simulations using past and future anthropogenic emissions of pollutants, is put into perspective with regard to potential changes in nutrient limitations and biodiversity. Atmospheric deposition of nutrients has been suggested to result in human-induced ecosystem limitations with regard to specific nutrients. Such modifications favor the development of certain species against others and affect the overall functioning of ecosystems. Organic forms of nutrients are found to contribute to the atmospheric deposition of the nutrients N, P and Fe by 20%-40%, 35%-45% and 7%-18%, respectively. These have the potential to be key components of the biogeochemical cycles since there is initial proof of their bioavailability to ecosystems. Bioaerosols have been found to make a significant contribution to atmospheric sources of N and P, indicating potentially significant interactions between terrestrial and marine ecosystems. These results deserve further experimental and modeling studies to reduce uncertainties and understand the feedbacks induced by atmospheric deposition of nutrients to ecosystems.

dust↗

NASA NTRS2016

Spaceborne Remote Sensing of Aerosol Type: Global Distribution, Model Evaluation and Translation into Chemical Speciation

It is essential to evaluate and refine aerosol classification methods applied to passive satellite remote sensing. We have developed an aerosol classification algorithm (called Specified Clustering and Mahalanobis Classification, SCMC) that assigns an aerosol type to multi-parameter retrievals by spaceborne, airborne or ground-based passive remote sensing instruments [1]. The aerosol types identified by our scheme are pure dust, polluted dust, urban-industrialdeveloped economy, urban-industrialdeveloping economy, dark biomass smoke, light biomass smoke and pure marine. We apply the SCMC method to inversions from the ground-based AErosol RObotic NETwork (AERONET [2]) and retrievals from the space-borne Polarization and Directionality of Earths Reflectances instrument (POLDER, [3]). The POLDER retrievals that we use differ from the standard POLDER retrievals [4] as they make full use of multi-angle, multispectral polarimetric data [5]. We analyze agreement in the aerosol types inferred from both AERONET and POLDER and evaluate GEOS-Chem [6] simulations over the globe. Finally, we use in-situ observations from the SEAC4RS airborne field experiment to bridge the gap between remote sensing-inferred qualitative SCMC aerosol types and their corresponding quantitative chemical speciation. We apply the SCMC method to airborne in-situ observations from the NASA Langley Aerosol Research Group Experiment (LARGE, [7]) and the Differential Aerosol Sizing and Hygroscopicity Spectrometer Probe (DASH-SP, [8]) instruments; we then relate each coarsely defined SCMC type to a sum of percentage of individual aerosol species, using in-situ observations from the Particle Analysis by Laser Mass Spectrometry (PALMS, [9]), the Soluble Acidic Gases and Aerosol (SAGA, [10]), and the High - Resolution Time - of - Flight Aerosol Mass Spectrometer (HR ToF AMS, [11]).

airborne↗

NASA NTRS2014

Integrated Diagnostics and Prognostics for the Electrical Power System of a Planetary Rover

For electric vehicles, technology for monitoring, diagnosis, and prognosis of the electrical power system (EPS) becomes essential for safe and efficient operation. To this end, we develop a general system-level integrated diagnosis and prognosis framework, which detects, isolates, and identifies EPS faults, and predicts when the EPS will fail to deliver sufficient power. The approach takes advantage of recent work in structural model decomposition in order to distribute the global diagnosis and prognosis problems into local subproblems that can be solved in parallel, thus enabling implementation on distributed computational platforms. The framework is applied to the EPS of a planetary rover testbed, and is demonstrated using data from field experiments.

Daigle, Matthew↗

NASA NTRS2018

Development of a Mars Lidar (MARLI) for Measuring Wind and Aerosol Profiles from Orbit

Our understanding of the Mars atmosphere and the coupled atmospheric processes that drive its seasonal cycles is limited by a lack of observation data, particularly measurements that capture diurnal and seasonal variations on a global scale. As outlined in the 2011 Planetary Science Decadal Survey and the recent Mars Exploration Program Analysis Group(MEPAG) Goals Document, near-polar-orbital measurements of height-resolved aerosol backscatter and wind profiles area high-priority for the scientific community and would be valuable science products as part of a next-generation orbital science package. To address these needs, we have designed and tested a breadboard version of a direct detection atmospheric wind lidar for Mars orbit. It uses a single-frequency, seeded Nd:YAG laser ring oscillator operating at 1064nm (4 kHz repetition rate), with a 30-ns pulse duration amplified to 4 mJ pulse energy. The receiver uses a Fabry-Perotetalon as part of a dual-edge optical discrimination technique to isolate the Doppler-induced frequency shift of the back scattered photons. To detect weak aerosol backscatter profiles, the instrument uses a 4x4 photon-counting HgCdTeAPD detector with a 7 MHz bandwidth and < 0.4 fW/Hz(exp 1/2) noise equivalent power. With the MARLI lidar breadboard instrument, we were able to measure Doppler shifts continuously between 1 and 30 m/s by using a rotating chopper wheel to impart a Doppler shift to incident laser pulses. We then coupled the transmitter and receiver systems to a laser ranging telescope at the Goddard Geophysical and Astronomical Observatory (GGAO) to measure backscatter and Doppler wind profiles in the atmosphere from the ground. We measured a 5.3 ± 0.8 m/s wind speed from clouds in the planetary boundary layer at a range of 4 to 6 km. This measurement was confirmed with a range-over-time measurement to the same clouds as well as compared to EMC meteorological models. Here we describe the lidar approach and the breadboard instrument, and report some early results from ongoing field experiments.

Cremons, Daniel R.↗

NASA NTRS2018

Predicting the Operational Acceptance of Airborne Flight Reroute Requests Using Data Mining

For tools that generate more efficient flight routes or reroute advisories, it is important to ensure compatibility of automation and autonomy decisions with human objectives so as to ensure acceptability by the human operators. In this paper, the authors developed a proof of concept predictor of operational acceptability for route changes during a flight. Such a capability could have applications in automation tools that identify more efficient routes around airspace impacted by weather or congestion and that better meet airline preferences. The predictor is based on applying data mining techniques, including logistic regression, a decision tree, a support vector machine, a random forest and Adaptive Boost, to historical flight plan amendment data reported during operations and field experiments. Cross validation was used for model development, while nested cross validation was used to validate the models. The model found to have the best performance in predicting air traffic controller acceptance or rejection of a route change, using the available data from Fort Worth Air Traffic Control Center and its adjacent Centers, was the random forest, with an F-score of 0.77. This result indicates that the operational acceptance of reroute requests does indeed have some level of predictability, and that, with suitable data, models can be trained to predict the operational acceptability of reroute requests. Such models may ultimately be used to inform route selection by decision support tools, contributing to the development of increasingly autonomous systems that are capable of routing aircraft with less human input than is currently the case.

Operational Acceptability↗

NASA NTRS2019

Bowles-Tatnall Wake Vortex Encounter Hazard Metric

Wake vortex spacing standards constrict the terminal area throughput and impose severe constraints on the overall capacity and efficiency of the National Airspace System. For more than two decades starting in the early 1990s, the National Aeronautics and Space Administration conducted extensive research on characterizing the formation and evolution of aircraft wakes. This multidisciplinary work included comprehensive field experiments (Pruis et al. 2016), flight tests (Vicroy et al. 1998), and wind tunnel tests (Rossow 1994; Chow et al. 1997). Parametric studies using large eddy simulations (Proctor 1998; Proctor et al. 2006) were conducted in order to develop fast-time models for the prediction of wake transport and decay (Ahmad et al. 2016). Substantial effort was spent on the formulation of acceptable vortex hazard metrics (Tatnall 1995; Hinton and Tatnall 1997). Several wake encounter severity metrics have been suggested in the past, which include the wake circulation strength, vortex-induced rolling moment coefficient (Clv), bank angle, and the roll control ratio (Tatnall 1995; Hinton and Tatnall 1997; Van der Geest 2012). The vortex-induced rolling moment coefficient introduced by Bowles and Tatnall (Tatnall 1995; Gloudemans et al. 2016) has been used extensively for risk and safety analysis of newly proposed air traffic management concepts and procedures. The original method of Bowles and Tatnall assumed a constant wing loading (the wing lift-curve slope, CL is constant), which resulted in an overestimation of the vortexinduced rolling moment coefficient. Bowles (2014) suggested a correction to the original method that provides more accurate values of Clv and which is also consistent with the underlying physics of the problem. The overestimation of Clv in the original method can be corrected by assuming an elliptical lift distribution. Figure 1.1 illustrates the correction in Clv achieved by the modified method.

Joel Malissa↗

NASA NTRSDate not supplied

TPSAS-NF1676L-32053-DND

The Atmospheric Science Data Center (ASDC) offers Earth Science data sets created from satellite measurements, modeling, and field experiments enabling scientists, educators, and the public to study earth and its atmosphere. NASA ESDIS is working towards making Earth Science data and tools cloud-ready. In an effort to align itself with these efforts, the ASDC is transitioning its existing web based services, tools and applications to RESTful APIs, containerized as microservices to leverage scalability and efficiency of an on-premise cloud environment.

Makhan L Virdi↗

NASA NTRSDate not supplied

TPSAS-NF1676L-11435-DND

Acoustical studies of atmospheric events like convective storms, shear-induced turbulence, acoustic gravity waves, microbursts, hurricanes, and clear air turbulence (CAT) over the past thirty years have established that these events are strong emitters of infrasound. Several mechanisms for the production of infrasound have been proposed, for example by the acceleration of vorticity or by space-time correlations of the turbulent Reynolds stresses (Lighthill theory). Electromagnetic (EM) sensors suffer two severe disadvantages in the detection of clear air turbulence and severe storms. The first is the inability to receive returns in clear air, where reflective targets (precipitation, particulate matter) are absent. The second disadvantage is that EM systems, being active, require scanning to locate an event, as opposed to a passive infrasonic array, which receives infrasonic radiation independently of event location. Further, EM systems, even weather radar ("NEXRAD"), do not have the extensive range (hundreds of miles) characteristic of infrasound. The leading laboratory for studies on atmospheric infrasound over the past thirty years has been the Environmental Technology Laboratory of the National Oceanic and Atmospheric Administration. This laboratory conducted measurements of infrasound from many sources, among which clear air turbulence was but a small part of the overall program. The summary of the results of this program suggests for development of a practical detection system. In other words, despite the progress made in this area, there does not exist today a National network of stations to monitor infrasound from turbulence. Under Innovative Partnership Program, Researchers at NASA Langley Research Center have been working to achieve that goal. As a first step, NASA Langley has designed and developed a portable infrasonic detection system which can be used to make useful infrasound measurements at a location where it was not possible previously. The design and results of the compact system, based upon laboratory and field experiments, will be presented.

Qamar Shams↗

NASA NTRSDate not supplied

Reconfiguring COSSIR for the Next Generation of Cloud and Precipitation Science

NASA originally developed the Compact Scanning Sub-millimeter Imaging Radiometer (CoSSIR) in the early 2000s, where it was own in the CRYSTAL-FACE and TC4 field experiments. With renewed interest in sub-millimeter remote sensing motivated by the upcoming launch of the EUMETSAT-sponsored Ice Cloud Imager (ICI), along with its potential for inclusion as part of the NASA Decadal Survey Aerosols, CLouds, Convection, and Precipitation (ACCP) observing architecture, CoSSIR is being refurbished to prepare for routine suborbital submillimeter measurements this decade. Upgrades include hardware (procurement of shared parts so that CoSMIR and CoSSIR can fly concurrently) and a change to the channels, with a focus on differential scattering and polarization at eight frequencies ranging from 170 to 640 GHz. As part of the refurbishment, the instrument name has been changed to Configurable Scanning Sub-millimeter Instrument/Radiometer, retaining the same acronym, in order to emphasize the science objectives that are enabled by CoSSIR's unique scanning geometry and channel set. These anticipated capabilities include two-dimensional pro ling of clouds and precipitation and characterization of the geometry (shape and orientation) of large cloud and precipitating ice particles.

Radiometry↗