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US plant and radiation dosimetry experiments flown on the Soviet satellite Cosmos 1129

Experiments included: 30 young male Wistar SPF rats used for wide range physiological studies; experiments with plants, fungi, insects, and mammalian tissue cultures; radiation physics experiments; a heat convection study; a rat embryology experiment in which an attempt was made to breed 2 male and 5 female rats during the flight; and fertile quail eggs used to determine the effects of spaceflight on avian embryogenesis. Specimens for US experiments were initially prepared at the recovery site or in Moscow and transferred to US laboratories for complete analyses. An overview of the mission focusing on preflight, on orbit, and postflight activities pertinent to the fourteen US experiments aboard Cosmos 1129 is presented.

Heinrich, M. R.↗

OCTS and SeaWiFS Bio-Optical Algorithm and Product Validation and Intercomparison in US Coastal Waters

Monitoring the health of US coastal waters is an important goal of the National Oceanic and Atmospheric Administration (NOAA). Satellite sensors are capable of providing daily synoptic data of large expanses of the US coast. Ocean color sensors, in particular, can be used to monitor the water quality of coastal waters on an operational basis. To appraise the validity of satellite-derived measurements, such as chlorophyll concentration, the bio-optical algorithms used to derive them must be evaluated in coastal environments. Towards this purpose, over 21 cruises in diverse US coastal waters have been conducted. Of these 21 cruises, 12 have been performed in conjunction with and under the auspices of the NASA/Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project. The primary goal of these cruises has been to obtain in-situ measurements of downwelling irradiance, upwelling radiance, and chlorophyll concentrations in order to evaluate bio-optical algorithms that estimate chlorophyll concentration. In this Technical Memorandum, we evaluate the ability of five bio-optical algorithms, including the current Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) algorithm, to estimate chlorophyll concentration in surface waters of the South Atlantic Bight (SAB). The SAB consists of a variety of environments including coastal and continental shelf regimes, Gulf Stream waters, and the Sargasso Sea. The biological and optical characteristics of the region is complicated by temporal and spatial variability in phytoplankton composition, primary productivity, and the concentrations of colored dissolved organic matter (CDOM) and suspended sediment. As such, the SAB is an ideal location to test the robustness of algorithms for coastal use.

Brown, Christopher W.↗

Ensemble Cannonical Correlation Prediction of Seasonal Precipitation Over the US

This paper presents preliminary results of an ensemble cannonical correlation (ECC) prediction scheme developed at the Climate and Radiation Branch, NASA/Goddard Space Flight Center for determining the potential predictability of regional precipitation, and for climate downscaling studies. The scheme is tested on seasonal hindcasts of anomalous precipitation over the continental United States using global sea surface temperature (SST) for 1951-2000. To maximize the forecast skill derived from SST, the world ocean is divided into nonoverlapping sectors. The cannonical SST modes for each sector are used as the predictor for the ensemble hindcasts. Results show that the ECC yields a substantial (10-25%) increase in prediction skills for all regions of the US and for all seasonal compared to traditional CCA prediction schemes. For the boreal winter, the tropical Pacific contributes the largest potential predictability to precipitation in the southwestern and southeastern regions, while the North Pacific and the North Atlantic are responsible for enhanced forecast skills in the Pacific Northwest, the northern Great Plains and Ohio Valley. Most importantly, the ECC increases skill for summertime precipitation prediction and substantially reduced the spring predictability barrier over all regions of the US continent. Besides SST, the ECC is designed with the flexibility to include any number of predictor fields, such as soil moisture, snow cover and regional regional data. Moreover, the ECC forecasts can be applied to other climate subsystems and, in conjunction with further diagnostic or model studies will enables a better understanding of the dynamic links between climate variations and precipitation, not only for the US, but also for other regions of the world.

Lau, William K. M.↗

Hyperspectral Technology Transfer to the US Department of Interior: Summary of Results of the NASA/DOI Hyperspectral Technology Transfer Project

In 1997 the Office of Biological Informatics and Outreach (OBIO), Biological Resources Division, US Geological Survey and NASA, Office of Earth Science (OES), initiated a coordinated effort for applying Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) data and analysis, as a technology transfer project, to critical DOI environmental issues in four study sites throughout the United States. This work was accomplished by four US Department of the Interior (DOI) study teams with support from NASA/OES principal investigators and the Office of Earth Science programs. The studies, including personnel, objectives, background, project plans, and milestones were documented in a project website at . This report summarizes the final outcomes of the project, detailing accomplishments, lessons learned, and benefits realized to NASA, the US Geological Survey, and the participating DOI bureaus.

Root, Ralph↗

Wind-US Flow Calculations for the M2129 S-Duct Using Structured and Unstructured Grids

Computational Fluid Dynamics (CFD) flow solutions for the M2129 diffusing S-duct with and without vane effectors were computed by the Wind-US flow solver. Both structured and unstructured 3-D grids were used. Without vane effectors, the duct exhibited massive flow separation in both experiment and CFD. With vane effectors installed, the flow remained attached and aerodynamic losses were reduced. Total pressure recovery and distortion near the duct outlet were computed from the solutions and compared favorably to experimental values. These calculations are part of a validation effort for the Wind-US code. They also provide an example case to aid engineers in learning to use the Wind-US software.

Mohler, Stanley R., Jr.↗

A Tamarisk Habitat Suitability Map for the Continental US

This paper presents a national-scale map of habitat suitability for a high-priority invasive species, Tamarisk (Tamarisk spp., salt cedar). We successfully integrate satellite data and tens of thousands of field sampling points through logistic regression modeling to create a habitat suitability map that is 90% accurate. This interagency effort uses field data collected and coordinated through the US Geological Survey and nation-wide environmental data layers derived from NASA s MODerate Resolution Imaging Spectroradiometer (MODIS). We demonstrate the utilization of the map by ranking the lower 48 US states (and the District of Columbia) based upon their absolute, as well as proportional, areas of highly likely and moderately likely habitat for Tamarisk. The interagency effort and modeling approach presented here could be applied to map other harmful species in the US and globally.

Morisette, Jeffrey T.↗

Applications of OMI Tropospheric NO(Sub 2) Data: Air Quality Trends in the US and Lightning NO(x) Source Strength

This talk will be presented in two parts: 1) an analysis of tropospheric column NO2 trends in the eastern half of the United States over the period 2005 to 2009 and 2) estimation of lightning NO(x) production rates based on OMI observations and lightning flash rate data. The air quality trends in the eastern US will be determined for specific subregions using tropospheric column NO2 data from OMI for 2005 through 2008 and from GOME-2 for 2007 through 2009. This period is characterized by significant NO(x) emission reductions at power plants within most of this region. The air quality trends will be compared with those estimated from continuous emission monitoring data from the power plants compiled by the US Environmental Protection Agency. OMI NO2 data have also been used to estimate lightning NOx production per flash in selected storms near Costa Rica and Panama during the 2007 NASA TC4 field campaign and over the continental US, Gulf of Mexico, and western Atlantic during the summers of 2005 and 2006. The lightning signal is extracted from the OMI data through a custom retrieval in which an NO2 profile representative of convective outflow is used in the airmass factor calculation and the background NO2 column is subtracted from the tropospheric column. When combined with NO(x)/NO2 ratios from the NASA GMT model and observed flash rates, the resulting estimates of NO(x) production per flash are comparable to those estimated obtained from analyses of aircraft data and cloud-resolving modeling.

Pickering, Kenneth↗

Shoulder Injuries in US Astronauts Related to EVA Suit Design

Introduction: For every one hour spent performing extravehicular activity (EVA) in space, astronauts in the US space program spend approximately six to ten hours training in the EVA spacesuit at NASA-Johnson Space Center's Neutral Buoyancy Lab (NBL). In 1997, NASA introduced the planar hard upper torso (HUT) EVA spacesuit which subsequently replaced the existing pivoted HUT. An extra joint in the pivoted shoulder allows increased mobility but also increased complexity. Over the next decade a number of astronauts developed shoulder problems requiring surgical intervention, many of whom performed EVA training in the NBL. This study investigated whether changing HUT designs led to shoulder injuries requiring surgical repair. Methods: US astronaut EVA training data and spacesuit design employed were analyzed from the NBL data. Shoulder surgery data was acquired from the medical record database, and causal mechanisms were obtained from personal interviews Analysis of the individual HUT designs was performed as it related to normal shoulder biomechanics. Results: To date, 23 US astronauts have required 25 shoulder surgeries. Approximately 48% (11/23) directly attributed their injury to training in the planar HUT, whereas none attributed their injury to training in the pivoted HUT. The planar HUT design limits shoulder abduction to 90 degrees compared to approximately 120 degrees in the pivoted HUT. The planar HUT also forces the shoulder into a forward flexed position requiring active retraction and extension to increase abduction beyond 90 degrees. Discussion: Multiple factors are associated with mechanisms leading to shoulder injury requiring surgical repair. Limitations to normal shoulder mechanics, suit fit, donning/doffing, body position, pre-existing injury, tool weight and configuration, age, in-suit activity, and HUT design have all been identified as potential sources of injury. Conclusion: Crewmembers with pre-existing or current shoulder injuries or certain anthropometric body types should conduct NBL EVA training in the pivoted HUT.

Scheuring, R. A.↗

Monitoring Regional Forest Disturbances across the US with near Real Time MODIS NDVI Products Resident to the ForWarn Forest Threat Early Warning System

Forest threats across the US have become increasingly evident in recent years. Sometimes these have resulted in regionally evident disturbance progressions (e.g., from drought, bark beetle outbreaks, and wildfires) that can occur across multiyear durations and have resulted in extensive forest overstory mortality. In addition to stand replacement disturbances, other forests are subject to ephemeral, sometimes yearly defoliation from various insects and varying types and intensities of ephemeral damage from storms. Sometimes, after prolonged severe disturbance, signs of recovery in terms of Normalized Difference Vegetation Index (NDVI) can occur. The growing prominence and threat of forest disturbances in part have led to the formation and implementation of the 2003 Healthy Forest Restoration Act which mandated that national forest threat early warning system be developed and deployed. In response, the US Forest Service collaborated with NASA, DOE Oakridge National Laboratory, and the USGS Eros Data Center to build and roll-out the near real time ForWarn early warning system for monitoring regionally evident forest disturbances. Given the diversity of disturbance types, severities, and durations, ForWarn employs multiple historical baselines that are used with current NDVI to derive a suite of six forest change products that are refreshed every 8 days. ForWarn employs daily quarter kilometer MODIS NDVI data from the Aqua and Terra satellites, including MOD13 data for deriving historical baseline NDVIs and eMODIS 7 NDVI for compiling current NDVI. In doing so, the Time Series Product Tool and the Phenological Parameters Estimation Tool are used to temporally de-noise, fuse, and aggregate current and historical MODIS NDVIs into 24 day composites refreshed every 8 days with 46 dates of products per year. The 24 day compositing interval enables disturbances to be detected, while minimizing the frequency of residual atmospheric contamination. Forest change products are computed versus the previous 1, previous 3, and all previous years in the MODIS record for a given 24 day interval. Other "weekly" forest change products include one computed using an adaptive length compositing method for quicker detection of disturbances, two others that adjust for seasonal fluctuations in normal vegetation phenology (e.g., early versus late springs). This overall approach enables forest disturbance dynamics from a variety of regionally evident biotic and abiotic forest disturbances to be viewed and assessed through the calendar year. The change products are also being utilized for forest change trend analysis and for developing regional forest overstory mortality products. ForWarn's forest change products are used to alert forest health specialists about new forest disturbances. Such alerts are also typically based on available Landsat, aerial, and ground data as well as communications with forest health specialists and previous experience. ForWarn products have been used to detect and track many types of regional disturbances to multiple forest types, including defoliation from caterpillars and severe storms, as well as mortality from both biotic and abiotic agents (e.g., bark beetles, drought, fire, anthropogenic clearing). ForWarn offers products that could be combined with other geospatial data on forest biomass to assess forest disturbance carbon impacts within the conterminous US.

Spruce, Joseph P.↗

Simulated Transmission of the Dengue Virus Across the US-Mexico Border Using Remotely Sensed and Ground Based Weather Data

Incidence of dengue fever, caused by a mosquito transmitted virus, have increased in the Americas during recent decades. In the US, local transmission has been reported in southern Texas and Florida. However, despite its close proximity to dengue endemic areas in Mexico and the presence of a primary mosquito vector, there are no reports of local transmission in Arizona. Many studies have demonstrated that weather influences dengue virus transmission by regulating vector development rates, vector habitat availability, and the duration of the virus extrinsic incubation period (EIP). The EIP, the period between mosquito infection and the ability for it to retransmit the virus, is especially important given its high sensitivity to temperature and the short lifespan of mosquitoes. Other studies, however, have suggested that human related factors such as socioeconomic status and herd immunity may explain much of the disparity in dengue incidence in the US‐Mexico border region. Using a meteorologically driven model of vector population dynamics and virus transmission we compare simulations of dengue fever cases in southern Arizona and northern Mexico. A Monte Carlo approach is employed to select parameter values by evaluating simulations in Hermosillo Mexico with reported dengue fever case data. Simulations that replicate the case data best are retained and rerun using remotely sensed climate data from other Arizona and Mexico locations to determine the relative influence of weather on virus transmission. Although human and environmental factors undoubtedly influence dengue transmission in the US‐Mexico border regions, weather is a major facilitator of the transmission process.

Dengue↗

An Evaluation of MODIS-Retrieved Aerosol Optical Depth over a Mountainous AERONET Site in the Southeastern US

The literature shows that aerosol optical depth (AOD) derived from the MODIS Collection 5 (C5) dark target algorithm has been extensively validated by spatiotemporal collocation with AERONET sites on both global and regional scales.Although generally comparing well over the eastern US region, poor performance over mountains in other regions indicate the need to evaluate the MODIS product over a mountain site. This study compares MODIS C5 AOD at 550nm to AOD measured at the Appalachian State University AERONET site in Boone, NC over 30 months between August 2010 and September 2013. For the combined Aqua and Terra datasets, although more than 70% of the 500 MODIS AOD measurements agree with collocated AERONET AOD to within error envelope of +/- (0.05 + 15%), MODIS tends to have a low bias (0.02-0.03). The agreement between MODIS and AERONET AOD does not depend on MODIS quality assurance confidence (QAC) value. However, when stratified by satellite, MODIS-Terra data does not perform as well as Aqua, with especially poor correlation (r = 0.39) for low aerosol loading conditions (AERONET AOD less than 0.15).Linear regressions between Terra and AERONET possess statistically-different slopes for AOD < 0.15 and AOD > or = 0.15. AERONET AOD measured only during MODIS overpass hours is highly correlated with daily-averaged AERONET AOD. MODIS monthly-averaged AOD also tracks that of AERONET over the study period. These results indicate that MODIS is sensitive to the day-to-day variability, as well as the annual cycle of AOD over the Appalachian State AERONET site. The complex topography and high seasonality in AOD and vegetation indices allow us to specifically evaluate MODIS dark target algorithm surface albedo and aerosol model assumptions at a regionally-representative SE US mountain site.

air quality↗

Characterizing Agricultural Impacts of Recent Large-Scale US Droughts and Changing Technology and Management

Process-based agricultural models, applied in novel ways, can reproduce historical crop yield anomalies in the US, with median absolute deviation from observations of 6.7% at national-level and 11% at state-level. In seasons for which drought is the overriding factor, performance is further improved. Historical counterfactual scenarios for the 1988 and 2012 droughts show that changes in agricultural technologies and management have reduced system-level drought sensitivity in US maize production by about 25% in the intervening years. Finally, we estimate the economic costs of the two droughts in terms of insured and uninsured crop losses in each US county (for a total, adjusted for inflation, of $9 billion in 1988 and $21.6 billion in 2012). We compare these with cost estimates from the counterfactual scenarios and with crop indemnity data where available. Model based measures are capable of accurately reproducing the direct agro-economic losses associated with extreme drought and can be used to characterize and compare events that occurred under very different conditions. This work suggests new approaches to modeling, monitoring, forecasting, and evaluating drought impacts on agriculture, as well as evaluating technological changes to inform adaptation strategies for future climate change and extreme events.

Climate extremes; Drought impacts; Agriculture; Se↗

Effects of Resolution and Spectral Nudging in Simulation the Effects of Wintertime Atmospheric River Landfalls in the Western US

Landfalling atmospheric rivers (ARs) play a crucial role in the climate of the US Pacific coast region as they are frequently related with heavy precipitation and flash flooding events. Thus, the capability of climate models to accurately simulate AR landfalls and their key hydrologic effects is an important practical concern for WUS, from flood forecasting to future water resources projections. In order to examine the effects of model configuration, including the resolution and spectral nudging, in simulating the climatology of key weather events in the conterminous US, a NASA team has performed a hindcast experiment using the GEOS5 global and the NU-WRF regional models for Nov 1999 - Oct 2010. This study examines the skill of these hindcasts, with different models and their configurations, in simulating key footprints of landfalling ARs in the WUS region. Using an AR-landfall chronology based on the vertically-integrated water vapor flux calculated from the MERRA2 reanalysis, we have analyzed the observed and simulated precipitation and temperature anomalies associated with wintertime AR landfalls along the US Pacific coast. Model skill is measured using metrics including regional means, a skill score based on correlations and mean-square errors, and Taylor diagrams in four WUS Bukovsky regions. Results show that the AR-related anomalies of precipitation is more reliable than of surface temperatures. Model skill also varies according to regions. The AR temperature anomalies are well simulated in most of the WUS region except PNW. For precipitation, simulations with finer spatial resolution tend to generate larger spatial variability and agree better with the PRISM data in most regions. Such a resolution dependence of spatial variability is not found for temperatures; e.g., the MERRA2 reanalysis often outperforms, with similar spatial variability and higher pattern correlations with the PRISM data, finer-resolution NU-WRF runs in simulating temperature variations within subregions. Results from this study will be summarized to assist future (regional) climate experiments for climate change impact assessments and developing adaptationmitigation strategies, the key elements of the National Climate Assessment.

Simulation↗

Northeast US Ecological Forecasting: Modeling Invasive Plant Habitat Suitability to Support Management Efforts in the American Northeast

Invasive plant species threaten environmental and economic interests when they spread into new areas, outcompete native species, and disrupt ecosystem services. If the spread is not controlled early, species can become well-established and increasingly difficult to manage. The National Park Service (NPS) Invasive Plant Management Teams (IPMTs) strive for an “early detection, rapid response” approach to reducing invasive species spread. Management teams can better prioritize their work with the help of species distribution models (SDMs), which map habitat suitability by combining species occurrences with environmental predictor variables. Scarce invaded range data for newly arrived invasive species presents a particular challenge for producing accurate models. To improve future modeling efforts, this project compared SDM methods using different spatial scales to model two plant species invasive to the Northeast US: the well-established Japanese stiltgrass (Microstegium vimineum) and newer invasive species wavyleaf basketgrass (Oplismenus undulatifolius). The team used NASA Earth observations and climate datasets to model occurrence data and predictor layers at a US-specific extent (90m2 spatial resolution) and global extent (1 km2 spatial resolution). Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imager (OLI) provided data for US Normalized Difference Moisture Indices (NDMI), while global NDMI and topographic predictor layers were derived from Shuttle Radar Topography Mission (SRTM) and Terra Moderate Resolution Imaging Spectroradiometer (MODIS). The resulting models indicated important predictor variables for each species and explored the benefits and tradeoffs of using global data to model habitat suitability for new-arrival invasive species.

Rebecca Ohman↗

Extreme Precipitation in the Southern US Great Plains in the Spring of 2015: Mechanisms and Prediction

During May of 2015, the southern US Great Plains and adjacent Gulf Coast region experienced more than twice the long-term mean precipitation, making it the wettest May since 1895. We investigate the physical mechanisms associated with this event using a suite of large-ensemble regional replay AGCM simulations from the NASA-GEOS model. In these simulations, certain regions of the globe are constrained to closely follow observations while the remainder of the domain is free running, allowing for the isolation of the remote regions that were important for the event. Preliminary analysis provides evidence that the extreme southern US precipitation was linked in part to positive precipitation anomalies in the central and eastern tropical Pacific via a wave train, which ultimately caused anomalous moisture flux from the Gulf of Mexico. An analysis of Subseasonal Experiment (SubX) model output was conducted to explore the subseasonal prediction skill of the event. Several models are able the predict the presence of positive precipitation anomalies in or near the southern US at lead times exceeding 10 days, albeit with errors in the locations and magnitude of the heaviest precipitation anomalies. A more thorough investigation with version 2 of NASA’s GEOS-S2S model shows that the prediction skill stems from the model’s ability to reasonably predict the positive tropical Pacific precipitation anomalies and the initiation of the Rossby wave train that is believed to be linked to the event. The potential causes for limitations in the prediction skill of this event will be explored.

Great Plains↗

Focus Group Study of US Pilots on Fatigue in Short-Haul Flight Operations

Introduction: There are few studies investigating the impact of fatigue in short-haul flight operations conducted under United States (US) Federal Aviation Regulations (FAR) Part 117 flight and duty limitations and rest requirements. In order to understand the fatigue factors unique to short-haul operations, we conducted a series of focus groups across four major commercial passenger airlines in the US. The outcomes of this study were intended to inform the scope of a larger study of fatigue in short-haul operations. Methods: Ninety short-haul pilots were recruited through emails distributed by airline safety teams and labor representatives. Fourteen focus groups were conducted via an online conferencing platform in which participants were asked to identify, specific to short-haul: a) schedules and operations that lead to elevated fatigue; b) schedules and operations that are not fatiguing, and c) important fatigue factors to study. Data were collected anonymously and coded using conventional qualitative content analysis, with axial coding and summative analysis used to identify main themes and over-arching categories. Results: Participants had an average of 12,348 (6,483) lifetime flying hours with 71 (14.5) hours of monthly flying. Forty-six percent of participants were captains. The six fatigue factor categories identified were: circadian disruption (e.g., circadian switches, redeyes), high workload (e.g., hassle factors, number of flights per duty), inadequate rest opportunity (e.g., minimum rest layovers, quality of rest facilities), schedule changes (e.g., unpredictability), regulation and policy issues (e.g., scheduling up to FAR 117 limits), and long sits (e.g., long wait times between flights). Discussion: A field study informed by these results and designed to investigate the prevalence and impact of these factors in US short-haul operations is currently underway.

aviation↗

High-Resolution Mapping of Nitrogen Oxide Emissions in Large US Cities From TROPOMI Retrievals of Tropospheric Nitrogen Dioxide Columns

Satellite-derived spatiotemporal patterns of nitrogen oxide (NO x ) emissions can improve accuracy of emission inventories to better support air quality and climate research and policy studies. In this study, we develop a new method by coupling the chemical transport Model-Independent SATellite-derived Emission estimation Algorithm for Mixed-sources (MISATEAM) with a divergence method to map high-resolution NO x emissions across US cities using TROPOspheric Monitoring Instrument (TROPOMI) tropospheric nitrogen dioxide (NO 2 ) retrievals. The accuracy of the coupled method is validated through application to synthetic NO 2 observations from the NASA-Unified Weather Research and Forecasting (NU-WRF) model, with a horizontal spatial resolution of 4 km × 4 km for 33 large and mid-size US cities. Validation reveals excellent agreement between inferred and NU-WRF-provided emission magnitudes (R= 0.99, normalized mean bias, NMB = −0.01) and a consistent spatial pattern when comparing emissions for individual grid cells (R=0.88 ± 0.06). We then develop a TROPOMI-based database reporting annual emissions for 39 US cities at a horizontal spatial resolution of 0.05° × 0.05° from 2018 to 2021. This database demonstrates a strong correlation (R= 0.90) with the National Emission Inventory (NEI) but reveals some bias (NMB = −0.24). There are noticeable differences in the spatial patterns of emissions in some cities. Our analysis suggests that uncertainties in TROPOMI-based emissions and potential misallocation of emissions and/or missing sources in bottom-up emission inventories both contribute to these differences.

NOx emissions↗

Identification of US 943 as a halo cataclysmic variable

US 943 has been shown to exhibit large (greater than about 5 mag) amplitude variations on time scales of one to two years. New time-resolved CCD photometry presented herein shows it also to be variable on time scales of 20 to 40 minutes with amplitude variation of up to 1 mag. Its membership as a cataclysmic variable is suggested. This assignment would place US 943 at a galactic distance of about 700 pc.

Howell, Steve B.↗