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Optical air data systems and methods

Systems and methods for sensing air includes at least one, and in some embodiments three, transceivers for projecting the laser energy as laser radiation to the air. The transceivers are scanned or aligned along several different axes. Each transceiver receives laser energy as it is backscattered from the air. A computer processes signals from the transceivers to distinguish molecular scattered laser radiation from aerosol scattered laser radiation and determines air temperatures, wind speeds, and wind directions based on the scattered laser radiation. Applications of the system to wind power site evaluation, wind turbine control, traffic safety, general meteorological monitoring and airport safety are presented.

Caldwell, Loren M.↗

Vehicle Assembly Building Fire Mishap Investigation Report. Volume I of V

On January 13, 2005, at approximately 1355, smoke was noticed on the 4th floor of D Tower in the Vehicle Assembly Building (VAB). Subsequently, a 911 call was made, a fire alarm pull station was activated, and the VAB was evacuated. The source of the smoke was determined to be a fire on the Low Bay M/N section roof near the Launch Control Center (LCC) Crossover. Due to the high visibility of the mishap, the KSC Center Director appointed a Mishap Investigation Board. Damage to government property was limited to the roof and a small number of ceiling tiles that were damaged by the fire fighters during the response. At the time of the mishap, there were hazardous commodities in the VAB including Solid Rocket Motors (SRMs) with open grain due to Solid Rocket Booster (SRB) igniter inspections. The Board agrees with the SGS Fire Services' theory that large amounts of smoke concentrated in the VAB D Tower and moved downward into the cable tunnel. The Board determined the proximate cause of this incident to be torching. HRI was installing a torch applied roof membrane which resulted in the ignition of combustible materials under the membrane near a wooden roof expansion joint. The torch applied roofing method is a universally accepted safe industry practice when applied to non-combustible surfaces. The combination of an open flame torch and combustible materiaLs presents an increased level of risk even with skilled applicators. The addition of high winds to this combination results in a risk the Board thinks can not be adequately mitigated. An appropriate risk assessment and analysis must be performed on the proposed roofing method to be used on high visibility facilities which represent unique national assets even when using common industry practices for repair and modification. The Board identified three root causes which contributed to or created the proximate cause and, if eliminated or modified, would have prevented the mishap: 1. Combustible materials in existing roof system 2. Wind speed and direction 3. Inadequate fire watch technique. Two contributing factors were identified which may have contributed to the occurrence but, if eliminated or modified, would not have prevented the occurrence: 1. HRI rushed to dry in and seal the roof on January 13 because heavy rain was predicted for the next day 2. No guidance on torching in windy conditions A total of 17 significant observations were noted during this investigation, which could lead to another mishap, or increase the severity of a mishap, but were not contributing factors in this mishap.

Kight, Ira↗

Displaying Composite and Archived Soundings in the Advanced Weather Interactive Processing System

In a previous task, the Applied Meteorology Unit (AMU) developed spatial and temporal climatologies of lightning occurrence based on eight atmospheric flow regimes. The AMU created climatological, or composite, soundings of wind speed and direction, temperature, and dew point temperature at four rawinsonde observation stations at Jacksonville, Tampa, Miami, and Cape Canaveral Air Force Station, for each of the eight flow regimes. The composite soundings were delivered to the National Weather Service (NWS) Melbourne (MLB) office for display using the National version of the Skew-T Hodograph analysis and Research Program (NSHARP) software program. The NWS MLB requested the AMU make the composite soundings available for display in the Advanced Weather Interactive Processing System (AWIPS), so they could be overlaid on current observed soundings. This will allow the forecasters to compare the current state of the atmosphere with climatology. This presentation describes how the AMU converted the composite soundings from NSHARP Archive format to Network Common Data Form (NetCDF) format, so that the soundings could be displayed in AWl PS. The NetCDF is a set of data formats, programming interfaces, and software libraries used to read and write scientific data files. In AWIPS, each meteorological data type, such as soundings or surface observations, has a unique NetCDF format. Each format is described by a NetCDF template file. Although NetCDF files are in binary format, they can be converted to a text format called network Common data form Description Language (CDL). A software utility called ncgen is used to create a NetCDF file from a CDL file, while the ncdump utility is used to create a CDL file from a NetCDF file. An AWIPS receives soundings in Binary Universal Form for the Representation of Meteorological data (BUFR) format (http://dss.ucar.edu/docs/formats/bufr/), and then decodes them into NetCDF format. Only two sounding files are generated in AWIPS per day. One file contains all of the soundings received worldwide between 0000 UTC and 1200 UTC, and the other includes all soundings between 1200 UTC and 0000 UTC. In order to add the composite soundings into AWIPS, a procedure was created to configure, or localize, AWIPS. This involved modifying and creating several configuration text files. A unique fourcharacter site identifier was created for each of the 32 soundings so each could be viewed separately. The first three characters were based on the site identifier of the observed sounding, while the last character was based on the flow regime. While researching the localization process for soundings, the AMU discovered a method of archiving soundings so old soundings would not get purged automatically by AWl PS. This method could provide an alternative way of localizing AWl PS for composite soundings. In addition, this would allow forecasters to use archived soundings in AWIPS for case studies. A test sounding file in NetCDF format was written in order to verify the correct format for soundings in AWIPS. After the file was viewed successfully in AWIPS, the AMU wrote a software program in the Tool Command Language/Tool Kit (Tcl/Tk) language to convert the 32 composite soundings from NSHARP Archive to CDL format. The ncgen utility was then used to convert the CDL file to a NetCDF file. The NetCDF file could then be read and displayed in AWIPS.

Barrett, Joe H., III↗

A Preliminary Interpretation of the First Results from the REMS Surface Pressure Measurements of the MSL Mission

The Rover Environmental Monitoring Station (REMS) on the Mars Science Laboratory (MSL) Curiosity rover consists of a suite of meteorological instruments that measure pressure, temperature (air and ground), wind (speed and direction), relative humidity, and the UV flux. A description of the instruments is described elsewhere.. Here we focus on interpreting the first 90 sols of REMS operations with a particular emphasis on the pressure data.

Haberle, Robert M.↗

Applied Meteorology Unit (AMU)

Develop climatologies of gridded CG lightning densities and frequencies of occurrence for the Melbourne, FL National Weather Service (NWS MLB) county warning area. These grids are used to create a first-guess field for the lightning threat index map that is available on the NWS MLB NASA KSCIKT website. Forecasters previously created this map from scratch. Having the climatologies as a background field will increase consistency between forecasters and decrease their workload. Delivered all files containing the lightning climatologies, the data, and the code used to create the climatologies to NWS MLB. Completed and distributed a final memorandum describing how the climatologies were created. All the files were installed on the NWS MLB computer system, and then the code was compiled and tested to ensure that it worked properly on their operating system. The climatologies and their descriptions are posted on the NWS MLB website. Forecasting Low-Level Convergent Bands Under Southeast Flow Provide guidance to operational personnel that will help improve their forecasts of cloud bands under large-scale southeast flow. When these bands occur, they can lead to cloud, rain, and thunderstorm occurrences that adversely affect launch, landing, and ground operations at Kennedy Space Center/Cape Canaveral Air Force Station (KSC/CCAFS). Completed the first draft of the final report. The conclusions from this task indicated low-level wind speed and direction, low-level high pressure ridge position, east coast sea breeze front activity and upper-level jet streak position have the greatest influence on convergent band formation and movement during southeasterly flow.

Bauman, William↗

The Present Habitability Potential of Gale Crater: What We Have Learned So Far From Mars Science Laboratory

The Mars Science Laboratory mission has comprehensively interrogated the surface environment of Mars as it explores Gale Crater. Both chemical and physical attributes of the present environment have been measured over the course of the mission, enabling us to compare the present state of the martian surface with the environmental requirements of prokaryotic microbes. While this approach does not exclude the possibility of martian life that may have evolved to adapt to the present conditions, it is advantageous in that it allows us to evaluate environmental requirements of known life and also provide insight into the likelihood of forward contamination by Earth organisms with the comparison of their environmental requirements with the measured attributes of the environment at Gale Crater. We have already modeled a paleoenvironment with high habitability potential (HP) based upon chemistry, mineralogy and other geological evidence such as sedimentary structures and larger scale geomorphology [1]. In this report, we turn our attention to the present HP of the Yellowknife Bay area, including the importance of the physical environmental metrics such as atmospheric pressure, air and ground temperature, ionizing radiation, wind speed and direction, slope, etc.

Conrad, P. G.↗

Airborne Wind Profiling Algorithm for Doppler Wind LIDAR

Systems, methods, and devices of the present invention enable airborne Doppler Wind LIDAR system measurements and INS/GPS measurements to be combined to estimate wind parameters and compensate for instrument misalignment. In a further embodiment, the wind speed and wind direction may be computed based on two orthogonal line-of-sight LIDAR returns.

Beyon, Jeffrey Y.↗

The Quality Control Algorithms Used in the Creation of NASA Kennedy Space Center Lightning Protection System Towers Meteorological Database

An accurate database of meteorological data is essential for designing any aerospace vehicle and for preparing launch commit criteria. Meteorological instrumentation were recently placed on the three Lightning Protection System (LPS) towers at Kennedy Space Center (KSC) launch complex 39B (LC-39B), which provide a unique meteorological dataset existing at the launch complex over an extensive altitude range. Data records of temperature, dew point, relative humidity, wind speed, and wind direction are produced at 40, 78, 116, and 139 m at each tower. The Marshall Space Flight Center Natural Environments Branch (EV44) received an archive that consists of one-minute averaged measurements for the period of record of January 2011 - April 2015. However, before the received database could be used EV44 needed to remove any erroneous data from within the database through a comprehensive quality control (QC) process. The QC process applied to the LPS towers' meteorological data is similar to other QC processes developed by EV44, which were used in the creation of meteorological databases for other towers at KSC. The QC process utilized in this study has been modified specifically for use with the LPS tower database. The QC process first includes a check of each individual sensor. This check includes removing any unrealistic data and checking the temporal consistency of each variable. Next, data from all three sensors at each height are checked against each other, checked against climatology, and checked for sensors that erroneously report a constant value. Then, a vertical consistency check of each variable at each tower is completed. Last, the upwind sensor at each level is selected to minimize the influence of the towers and other structures at LC-39B on the measurements. The selection process for the upwind sensor implemented a study of tower-induced turbulence. This paper describes in detail the QC process, QC results, and the attributes of the LPS towers meteorological database.

Orcutt, John M.↗

The Modern Near-Surface Martian Climate: A Review of In-Situ Meteorological Data from Viking to Curiosity

We analyze the complete set of in-situ meteorological data obtained from the Viking landers in the 1970s to todays Curiosity rover to review our understanding of the modern near-surface climate of Mars, with focus on the dust, CO2 and H2O cycles and their impact on the radiative and thermodynamic conditions near the surface. In particular, we provide values of the highest confidence possible for atmospheric opacity, atmospheric pressure, near-surface air temperature, ground temperature, near-surface wind speed and direction, and near-surface air relative humidity and water vapor content. Then, we study the diurnal, seasonal and interannual variability of these quantities over a span of more than twenty Martian years. Finally, we propose measurements to improve our understanding of the Martian dust and H2O cycles, and discuss the potential for liquid water formation under Mars present day conditions and its implications for future Mars missions.

Martinez, G. M.↗

Seasonal Impact of Regional Outdoor Biomass Burning on Air Pollution in Three Indian Cities: Delhi, Bengaluru, and Pune

Air pollution in many of India's cities exceeds national and international standards, and effective pollution control strategies require knowledge of the sources that contribute to air pollution and their spatiotemporal variability. In this study, we examine the influence of a single pollution source, outdoor biomass burning, on particulate matter (PM) concentrations, surface visibility, and aerosol optical depth (AOD) from 2007 to 2013 in three of the most populous Indian cities. We define the upwind regions, or "airsheds," for the cities by using atmospheric back trajectories from the HYSPLIT model. Using satellite fire radiative power (FRP) observations as a measure of fire activity, we target pre-monsoon and post-monsoon fires upwind of the Delhi National Capital Region and pre-monsoon fires surrounding Bengaluru and Pune. We find varying contributions of outdoor fires to different air quality metrics. For the post-monsoon burning season, we find that a subset of local meteorological variables (air temperature, humidity, sea level pressure, wind speed and direction) and FRP as the only pollution source explained 39% of variance in Delhi station PM(sub 10) anomalies, 77% in visibility, and 30% in satellite AOD; additionally, per unit increase in FRP within the daily airshed (1000 MW), PM(sub 10) increases by 16.34 micrograms per cubic meter, visibility decreases by 0.097 km, and satellite AOD increases by 0.07. In contrast, for the pre-monsoon burning season, we find less significant contributions from FRP to air quality in all three cities. Further, we attribute 99% of FRP from post-monsoon outdoor fires within Delhi's average airshed to agricultural burning. Our work suggests that although outdoor fires are not the dominant air pollution source in India throughout the year, post-monsoon fires contribute substantially to regional air pollution and high levels of population exposure around Delhi. During 3-day blocks of extreme PM(sub 2.5) in the 2013 post-monsoon burning season, which coincided with statistically significant high fire activity, concentrations in Delhi averaged 304 micrograms per cubic meter, or more than 1000% above the 24-h PM(sub 2.5) guideline (25 micrograms per cubic meter) of the World Health Organization. These results suggest that providing viable alternatives to agricultural residue burning could help improve post-monsoon air quality for a growing population of 63 million (39% in urban areas) within Delhi's airshed.

Air quality; Outdoor fires; Crop residue burning; ↗

SAEVe: A Long Duration Small Sat Class Venus Lander - Seismic and Atmospheric Exploration of Venus

NASA's science mission directorate has put increasing emphasis on innovative, smaller, and lower cost missions to achieve their science objectives. One example of this was the recent call by the Planetary Science Division for cube and small satellite concepts expected to cost $100M or less, not including launch and weighing less than 180kg. Over 100 proposals were submitted suggesting that indeed this is a size of mission worthy of being considered in future planning. Nineteen missions were selected for study, one being a long-lived Venus mission called SAEVe, for Seismic and Atmospheric Exploration of Venus. The science objectives and relevance of SAEVe include: Is Venus seismically active? What can we learn about its crust (thickness and composition) and its interior (lithosphere, mantle, and core)? What can be learned about its evolutionary history or about the planet / atmosphere interactions? SAEVe begins to address these science questions with simple, but capable, instrumented probes that can survive on the surface of Venus and take temporal measurements over months something never attempted before. The data returned will further our understanding of the solar system and Earth, and aid in meeting the NASA Science Plan goal to ascertain the content, origin, and evolution of the solar system and the chemical and physical processes in our solar system. SAEVe is delivered to Venus as a ride-along on another mission to Venus. Its two small probes are placed into the Venus atmosphere via a single Stardust-like entry capsule, are ejected at different times, free fall, and decelerate in the thickening atmosphere to touchdown under 8 m/s2 or less. The probes will begin taking measurements and transmitting important parameters at or near the surface and will focus on measurements like seismic activity, heat flux, wind speed and direction, basic chemical abundances, temperature, and pressure. At preset intervals, the probes acquire the science measurements and beam the data to the orbiting host spacecraft. SAEVe will serve as a highly capable precursor and pave the way for larger and more complex lander missions to explore Venus.

lander↗

The Impact of MISR-Derived Injection Height Initialization on Wildfire and Volcanic Plume Dispersion in the HYSPLIT Model

The dispersion of particles from wildfires, volcanic eruptions, dust storms, and other aerosol sources can affect air quality and other environmental factors downwind. Aerosol injection height is one source attribute that mediates downwind dispersion, as wind speed and direction can vary dramatically with elevation. Using plume heights derived from space-based, multi-angle imaging, we examine the impact of initializing plumes with satellite-measured vs. nominal (model-calculated or VAAC observations) injection height on the simulated dispersion of six large aerosol plumes. When there are significant differences in nominal vs. satellite-derived particle injection heights, or if one injection height is within the planetary boundary layer (PBL) and the other is above the PBL, differences in simulation results can arise. In the cases studied with significant nominal vs. satellite-derived injection height differences, the NOAA Air Resources Laboratory's Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model tends to represent plume evolution better if the injection height in the model is constrained by hyper-stereo satellite retrievals.

Plume heights↗

Testing and Improving a UAV-Based System Designed for Wetland Methane Source Measurements

Wetlands are the single highest emitting methane source category, but the magnitude of wetland fluxes remains difficult to fully characterize due to their large spatial extent and heterogeneity. Fluxes can vary with land surface conditions, vegetation type, and seasonal changes in environmental conditions. Unmanned aerial vehicles (UAVs) are an emerging platform to better characterize spatial variability in these natural ecosystems. While presenting some advantages over traditional techniques like towers and flux chambers, in that they are mobile vertically and horizontally, their use is still challenging, requiring continued improvement in sensor technology and field measurement approaches. In this work, we employ a small, fast response laser spectrometer on a Matrice 600 hexacopter. The system was previously deployed successfully for 40 flights conducted in a four-day period in 2018 near Fairbanks, Alaska. These flights revealed several potential areas for improvement, including: vertical positioning accuracy, the need for sensor health indicators, and approaches to deal with low wind speeds. An additional set of flights was conducted this year near Antioch in California. Flights were conducted several meters above ground up to 15-25 m in a curtain pattern. These curtains were flown both upwind and downwind of a tower site, allowing us to calculate a mass balance methane flux estimate that can be compared to eddy covariance fluxes from the tower. Testing will better characterize the extent to which altitude drifts in-flight and how GPS values compare with measurements from the onboard LIDAR, as well as the agreement between two-dimensional wind speed and direction on the ground versus measured onboard the UAV. Hardware improvements to the sensor and GPS are being considered to help reduce these sources of uncertainty. Results of this testing and how system performance relates to needs for quantifying wetland fluxes, will be presented.

Golston, Levi↗

Maximum entropy modeling to identify physical drivers of shallow snowpack heterogeneity using unpiloted aerial system (UAS) lidar

Understanding the spatial variability of the snowpack is valuable for hydrologists and ecologists seeking to predict hydrological processes in a cold region. Snow distribution is a function of interactions among static variables, such as terrain, vegetation, and soil properties, and dynamic meteorological variables, such as solar radiation, wind speed and direction, and soil moisture. However, identifying the dominant physical drivers responsible for spatial patterns of the snowpack, particularly for ephemeral, shallow snowpacks, has been challenging due to the lack of the high-resolution snowpack and physical variables with high vertical accuracy as well as inherent limitations in traditional approaches. This study uses an Unpiloted Aerial System (UAS) lidar-based snow depth and static variables (1-m spatial resolution) to analyze field-scale spatial structures of snow depth and apply the Maximum Entropy (MaxEnt) model to identify primary controls over open terrain and forests at the University of New Hampshire Thompson Farm Research Observatory, New Hampshire, United States. We found that, among nine topographic and soil variables, plant functional type and terrain roughness contribute up to 80% and 76% of relative importance in the MaxEnt framework to predict locations of deeper or shallower snowpacks, respectively, across a mixed temperate forested and field landscape. Soil variables, such as organic matter and saturated hydraulic conductivity, were also important controls (up to 70% and 81%) on snow depth spatial variations for both open and forested landscapes suggesting spatial variations in soil variables under snow can control thermal transfer among soil, snowpack, and surface-atmosphere. This work contributes to improving land surface and snow models by informing parameterization of the sub-grid scale snow depths, down-scaling remotely sensed snow products, and understanding field scale snow states.

Eunsang Cho↗

Runway Configuration Management with Offline Reinforcement Learning

Runway configuration management (RCM) is a challenging task, and it affects the efficiency of the National Airspace System (NAS) and airport surface operations significantly. Each airport, depending on the geometry, capacity, local climate patterns, etc. has multiple configurations for the runway usage for arriving and departing flights. Many factors such as the incoming/outgoing traffic load, wind direction and speed, convective weather, cloud ceiling and other environmental factors might affect the choice of a runway configuration at any point in time. However, other factors such as safety measures and regulations, noise abatement, capacity of each configuration, and preference of the air traffic controllers (ATCs) can also play a significant role in selecting the configuration. A sub-optimal selection of the runway configuration, or delay in making configuration changes might result in significant increase in taxi times for aircraft on the surface of the airport, fuel and energy use of the aircraft, and maintenance costs. It can also lead to safety concerns, such as an aircraft performing one or more go-arounds before being able to land. All these factors make RCM an extremely important and challenging decision-making process for the ATCs. The current state of practice sets the runway configuration by the ATCs based on relevant information available at the time including weather, traffic, noise abatement, safety bounds, etc. This makes the decision-making process subjective based on the accuracy of the available information and the bias in human decision making. Unfortunately, this approach yields poor results (e.g., significant delays) if the predicted outcomes are uncertain and their relative impact is not well understood. This is especially evident when the uncertainty increases the size of possible predicted outcomes (combinatorial explosion in possible scenarios) that cannot be handled by human reasoning. On the other hand, an automated approach based on machine intelligence can make use of historical data and search through all (or significant amount of) possible scenarios under uncertainty and make well-informed decisions.

Milad Memarzadeh↗

Southern Rockies Western Slope Agriculture: Identifying Drivers of Rangeland Production for Drought Planning on the Western Slope of the Southern Rockies

Over the last decade, the southern Rocky Mountains of the United States have experienced increasingly severe and variable drought. Local ranchers and landowners have reported strain on their operations, citing decreasing forage production for their cattle and a need to adjust their business models, even considering abandoning their businesses altogether. The study identified Major Land Resource Area-48 (MLRA-48) and northwestern Colorado as the key region for analysis. NASA DEVELOP partnered with the BLM Colorado River Field Office, Colorado State University Extension, USDA Forest Service, and the National Drought Mitigation Center to address stakeholder concerns of the efficacy of existing remotely sensed rangeland production estimation platforms and explore possible early warning climatic indicators of drought. The study identified two key rangeland platforms, the Rangeland Production Monitoring Service (RPMS) and Rangeland Analysis Platform (RAP) and used in-situ data to statistically validate their efficacy. RAP outperformed RPMS in estimating in-situ biomass and was therefore used in our climate modeling. Our study performed a random forest analysis, sampling 1500 points across the study area, comparing monthly RAP biomass estimates to a variety of climatic variables, including mean precipitation, temperature, palmer drought severity index, snow water equivalent, wind speed and direction, and vapor pressure deficit. After analysis, our study determined that vapor pressure deficit is a key indicator in predicting forage production in MLRA-48. Our study recommends the use of RAP in estimating potential forage, with caution for its tendency to overestimate. Our climate analysis provided our partners with greater understanding of the influence of various climatic factors in determining forage production and allows them to assist landowners in planning for future drought.

Addie Gonzalez↗

Southern Rockies Western Slope Agriculture: Identifying Drivers of Rangeland Production for Drought Planning on the Western Slope of the Southern Rockies

Over the last decade, the southern Rocky Mountains of the United States experienced severe and variable drought. Local ranchers and landowners have reported strain on their operations, citing decreasing forage for their cattle and a need to adjust their business models. This study identified Major Land Resource Area-48 (MLRA-48) and northwestern Colorado as the key region for analysis. NASA DEVELOP partnered with the BLM Colorado River Field Office, Colorado State University Extension, USDA Forest Service, and the National Drought Mitigation Center to address concerns regarding the efficacy of remotely sensed rangeland production platforms and identify early warning climatic indicators of drought. The study identified two key platforms, The Rangeland Productivity Monitoring Service (RPMS) and Rangeland Analysis Platform (RAP), which use NASA Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI, and Landsat 9 OLI-2 to estimate rangeland biomass. We regressed these with in situ biomass data to validate their efficacy and found that RAP was more effective than RPMS in estimating rangeland biomass, though it presents a tendency to overestimate. Our study performed a random forest analysis, comparing monthly RAP biomass estimates to a variety of climate variables, including mean precipitation, temperature, Palmer Drought Severity Index, snow water equivalent, snow persistence from Terra MODIS, wind speed and direction, and vapor pressure deficit. We determined that vapor pressure deficit and precipitation are key indicators in predicting forage production in MLRA-48. Our climate analysis provided our partners with greater understanding of the influence of various climate variables in determining rangeland production and allows them to assist land managers in drought mitigation.

remote sensing↗