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NASA NTRS2011

Magnetic Clouds at/near the 2007 - 2009 Solar Minimum: Frequency of Occurrence and Some Unusual Properties

Magnetic clouds (MCs) have been identified for the period 2007 2009 (at/near the recent solar minimum) from Wind data, then confirmed through MC parameter fitting using a force-free model. A dramatic increase in the frequency of occurrence of these events took place from the two early years of 2007 (with five MCs) and 2008 (one MC) compared to 2009 (12 MCs). This pattern approximately mirrors the occurrence-frequency profile that was observed over a three-year interval 12 years earlier, with eight events in 1995, four in 1996, and 17 in 1997, but decreased overall by a factor of 0.62 in number. However, the average estimated axial field strength taken over all of the 18 events of 2007 - 2009 (called the "recent period" here) was only 11.0 nT, whereas |BO| for the 29 events of 1995 - 1997 (called the "earlier period" ) was 16.5 nT. This 33% average drop in |BO| is more or less consistent with the decreased three-year average interplanetary magnetic field intensity between these two periods, which shows a 23% drop. In the earlier period, the MCs were clearly of mixed types but predominantly of the South-to-North type, whereas those in the recent period are almost exclusively the North-to-South type; this change is consistent with global solar field changes predicted by Bothmer and Rust (Geophys. Monogr. Ser. 99, 139, 1997). As we have argued in earlier work (Lepping and Wu, J. Geophys. Res. 112, A10103, 2007), this change should make it possible to carry out (accurate short-term) magnetic storm forecasting by predicting the latter part of an MC from the earlier part, using a good MC parameter-fitting model with real-time data from a spacecraft at L1, for example. The recent set s average duration is 15.2 hours, which is a 27% decrease compared to that of the earlier set, which had an average duration of 20.9 hours. In fact, all physical aspects of the recent MC set are shown to drop with respect to the earlier set; e.g., as well as the average internal magnetic field drop, the recent set had a somewhat low average speed of 379 km/s (5% drop), and the average diameter had a 24% drop. Hence, compared to the earlier set, the recent set consists of events that are smaller, slightly slower, and weaker in every respect (and fewer in number), but in a relative sense the two three-year sets have similar frequency-of-occurrence profiles. It is also interesting that the two sets have almost the same average axial inclinations, i.e., axial latitude approx. = 31deg (in GSE). These MC characteristics are compared to relevant solar features and their changes. A preliminary assessment of the statistics on possible shocks and pressure pulses upstream of these recent MCs yields the following: About 28% of the MCs, at most, had shocks, and 33% had shocks and/or pressure pulses. These are low values, since typically the percentage of cases with shocks is about 50%, and the percentage with shocks and/or pressure pulses is usually about 75%.

Lepping. R. P.↗

NASA NTRS2017

Comparing Proxy and Model Estimates of Hydroclimate Variability and Change over the Common Era

Water availability is fundamental to societies and ecosystems, but our understanding of variations in hydroclimate (including extreme events, flooding, and decadal periods of drought) is limited because of a paucity of modern instrumental observations that are distributed unevenly across the globe and only span parts of the 20th and 21st centuries. Such data coverage is insufficient for characterizing hydroclimate and its associated dynamics because of its multidecadal to centennial variability and highly regionalized spatial signature. High-resolution (seasonal to decadal) hydroclimatic proxies that span all or parts of the Common Era (CE) and paleoclimate simulations from climate models are therefore important tools for augmenting our understanding of hydroclimate variability. In particular, the comparison of the two sources of information is critical for addressing the uncertainties and limitations of both while enriching each of their interpretations. We review the principal proxy data available for hydroclimatic reconstructions over the CE and highlight the contemporary understanding of how these proxies are interpreted as hydroclimate indicators. We also review the available last-millennium simulations from fully coupled climate models and discuss several outstanding challenges associated with simulating hydroclimate variability and change over the CE. A specific review of simulated hydroclimatic changes forced by volcanic events is provided, as is a discussion of expected improvements in estimated radiative forcings, models, and their implementation in the future. Our review of hydroclimatic proxies and last-millennium model simulations is used as the basis for articulating a variety of considerations and best practices for how to perform proxy-model comparisons of CE hydroclimate. This discussion provides a framework for how best to evaluate hydroclimate variability and its associated dynamics using these comparisons and how they can better inform interpretations of both proxy data and model simulations.We subsequently explore means of using proxy-model comparisons to better constrain and characterize future hydroclimate risks. This is explored specifically in the context of several examples that demonstrate how proxy-model comparisons can be used to quantitatively constrain future hydroclimatic risks as estimated from climate model projections.

Common Era↗

NASA NTRS2004

Sensor Web Dynamic Measurement Techniques and Adaptive Observing Strategies

Sensor Web observing systems may have the potential to significantly improve our ability to monitor, understand, and predict the evolution of rapidly evolving, transient, or variable environmental features and events. This improvement will come about by integrating novel data collection techniques, new or improved instruments, emerging communications technologies and protocols, sensor mark-up languages, and interoperable planning and scheduling systems. In contrast to today's observing systems, "event-driven" sensor webs will synthesize real- or near-real time measurements and information from other platforms and then react by reconfiguring the platforms and instruments to invoke new measurement modes and adaptive observation strategies. Similarly, "model-driven" sensor webs will utilize environmental prediction models to initiate targeted sensor measurements or to use a new observing strategy. The sensor web concept contrasts with today's data collection techniques and observing system operations concepts where independent measurements are made by remote sensing and in situ platforms that do not share, and therefore cannot act upon, potentially useful complementary sensor measurement data and platform state information. This presentation describes NASA's view of event-driven and model-driven Sensor Webs and highlights several research and development activities at the Goddard Space Flight Center.

Talabac, Stephen J.↗

NASA NTRS1991

A nuclear fragmentation energy deposition model

A formalism for target fragment transport is presented with application to energy loss spectra in thin silicon devices. A nuclear data base is recommended that agrees well with the measurements of McNulty et al. using surface barrier detectors. High-energy events observed by McNulty et al., which are not predicted by intranuclear cascade models, are well represented by the present work.

NASA Discipline Number 04-10↗

NASA NTRS2013

Downscaling MODIS Land Surface Temperature for Urban Public Health Applications

This study is part of a project funded by the NASA Applied Sciences Public Health Program, which focuses on Earth science applications of remote sensing data for enhancing public health decision-making. Heat related death is currently the number one weather-related killer in the United States. Mortality from these events is expected to increase as a function of climate change. This activity sought to augment current Heat Watch/Warning Systems (HWWS) with NASA remotely sensed data, and models used in conjunction with socioeconomic and heatrelated mortality data. The current HWWS do not take into account intra-urban spatial variation in risk assessment. The purpose of this effort is to evaluate a potential method to improve spatial delineation of risk from extreme heat events in urban environments by integrating sociodemographic risk factors with estimates of land surface temperature (LST) derived from thermal remote sensing data. In order to further improve the consideration of intra-urban variations in risk from extreme heat, we also developed and evaluated a number of spatial statistical techniques for downscaling the 1-km daily MODerate-resolution Imaging Spectroradiometer (MODIS) LST data to 60 m using Landsat-derived LST data, which have finer spatial but coarser temporal resolution than MODIS. In this paper, we will present these techniques, which have been demonstrated and validated for Phoenix, AZ using data from the summers of 2000-2006.

Al-Hamdan, Mohammad↗

NASA NTRS2013

Downscaling MODIS Land Surface Temperature for Urban Public Health Applications

Al-Hamdan, Mohammad↗

NASA NTRS1993

(abstract) Monitoring Seasonal State and Mapping Species in Alaskan Taiga Using Imaging Radar as Input to CO(sub 2) Flux Models

Changes in the seasonal CO(sub 2) flux of the boreal forests may result from increased atmospheric CO(sub 2) concentrations and associated atmospheric warming. To monitor this potential change, a combination of remote sensing information and ecophysiological models are required. In this paper we address the use of synthetic aperture radar (SAR) data to provide some of the input to the ecophysiological models: forest type, freeze/thaw state which limits the growing season for conifers, and leaf on/off state which limits the growing season for deciduous species. AIRSAR data collected in March 1988 during an early thaw event and May 1991 during spring breakup are used to generate species maps and to determine the sensitivity of SAR to canopy freeze/thaw transitions. These data are also used to validate a microwave scattering model which is then used to determine the sensitivity of SAR to leaf on/off and soil freeze/thaw transitions. Finally, a CO(sub 2) flux algorithm which utilizes SAR data and an ecophysiological model to estimate CO(sub 2) flux is presented. CO(sub 2) flux maps are generated from which areal estimates of CO(sub 2) flux are derived.

leaf cover boreal forests radar backscatter↗

NASA NTRS2001

Tropical Ocean Evaporation/SST Sensitivity and It's Link to Water and Energy Budget Variations During ENSO

The continuing debate over feedback mechanisms governing tropical sea surface temperatures (SSTs) and tropical climate in general has highlighted the diversity of potential checks and balances within the climate system. Competing feedbacks due to changes in surface evaporation, water vapor, and cloud long- and shortwave radiative properties each may serve critical roles in stabilizing or destabilizing the climate system. It is also intriguing that even those climate variations having origins internal to the climate system - changes in ocean heat transport for example, apparently require complementary equilibrating effects by changes in atmospheric energy fluxes. Perhaps the best observational evidence of this is the relatively invariant nature of tropically averaged net radiation exiting the top-of-atmosphere (TOA) as measured by broadband satellite sensors over the past two decades. Thus, analyzing how these feedback mechanisms are operating within the context of current interannual variability may offer considerable insight for anticipating future climate change. In this paper we focus primarily on interannual variations of ocean evaporative fluxes and their significance for coupled water and energy cycles within the tropical climate system. In particular, we use both the da Silva estimates of surface fluxes (based on the Comprehensive Ocean Atmosphere Data Set, COADS) and numerical simulations from several global climate models to examine evaporation sensitivity to perturbations in SST associated with warm and cold ENSO events. The specific questions we address are as follows: (1) What recurring patterns of surface wind and humidity anomalies are present during ENSO and how do they combine to yield systematic evaporation anomalies?, (2) What is the resulting tropical ocean mean evaporation-SST sensitivity associated with this climate perturbation?, and (3) What role does this evaporation play in tropical heat and water balance over tropical oceanic regions? We use the da Silva ocean flux data to identify composite structure of departures of latent heat flux from climatology. We also show how these patterns arise out of associated wind and humidity anomaly distributions. Our preliminary work shows that evaporation sensitivity estimates from the da Silva / COADS data, computed for the tropical oceans (30 degrees N/S) are in the neighborhood of 5 to 6 W/square m K. Model estimates are also quite close to this figure. This rate is only slightly less than a rate corresponding to constant relative humidity; however, substantial regional departures from constant relative humidity are present. These patterns are robust and we relate the associated wind and humidity fluctuations noted in previous investigations to the derived evaporation anomalies. Finally, these results are interpreted with other data from the Earth radiation Budget Experiment (ERBE), Global Precipitation Climatology Project (GPCP) and NASA's Surface Radiation Budget (SRB) data set to characterize the tropical energetics of ENSO-related climate variability.

Robertson, Franklin R.↗

NASA NTRS1987

Cluster analysis of multiple planetary flow regimes

A modified cluster analysis method was developed to identify spatial patterns of planetary flow regimes, and to study transitions between them. This method was applied first to a simple deterministic model and second to Northern Hemisphere (NH) 500 mb data. The dynamical model is governed by the fully-nonlinear, equivalent-barotropic vorticity equation on the sphere. Clusters of point in the model's phase space are associated with either a few persistent or with many transient events. Two stationary clusters have patterns similar to unstable stationary model solutions, zonal, or blocked. Transient clusters of wave trains serve as way stations between the stationary ones. For the NH data, cluster analysis was performed in the subspace of the first seven empirical orthogonal functions (EOFs). Stationary clusters are found in the low-frequency band of more than 10 days, and transient clusters in the bandpass frequency window between 2.5 and 6 days. In the low-frequency band three pairs of clusters determine, respectively, EOFs 1, 2, and 3. They exhibit well-known regional features, such as blocking, the Pacific/North American (PNA) pattern and wave trains. Both model and low-pass data show strong bimodality. Clusters in the bandpass window show wave-train patterns in the two jet exit regions. They are related, as in the model, to transitions between stationary clusters.

Mo, Kingtse↗

NASA NTRS2013

Skipped Stage Modeling and Testing of the CPAS Main Parachutes

The Capsule Parachute Assembly System (CPAS) has undergone the transition from modeling a skipped stage event using a simulation that treats a cluster of parachutes as a single composite canopy to the capability of simulating each parachute individually. This capability along with data obtained from skipped stage flight tests has been crucial in modeling the behavior of a skipping canopy as well as the crowding effect on non-skipping ("lagging") neighbors. For the finite mass inflation of CPAS Main parachutes, the cluster is assumed to inflate nominally through the nominal fill time, at which point the skipping parachute continues inflating. This sub-phase modeling method was used to reconstruct three flight tests involving skipped stages. Best fit inflation parameters were determined for both the skipping and lagging canopies.

Varela, Jose G.↗

NASA NTRS2016

Kepler Data Validation Time Series File: Description of File Format and Content

The Kepler space mission searches its time series data for periodic, transit-like signatures. The ephemerides of these events, called Threshold Crossing Events (TCEs), are reported in the TCE tables at the NASA Exoplanet Archive (NExScI). Those TCEs are then further evaluated to create planet candidates and populate the Kepler Objects of Interest (KOI) table, also hosted at the Exoplanet Archive. The search, evaluation and export of TCEs is performed by two pipeline modules, TPS (Transit Planet Search) and DV (Data Validation). TPS searches for the strongest, believable signal and then sends that information to DV to fit a transit model, compute various statistics, and remove the transit events so that the light curve can be searched for other TCEs. More on how this search is done and on the creation of the TCE table can be found in Tenenbaum et al. (2012), Seader et al. (2015), Jenkins (2002). For each star with at least one TCE, the pipeline exports a file that contains the light curves used by TPS and DV to find and evaluate the TCE(s). This document describes the content of these DV time series files, and this introduction provides a bit of context for how the data in these files are used by the pipeline.

DV Time Series↗

NASA NTRS2016

Predicting Real-Time Safety of the National Airspace System

To gain the situational awareness necessary for informed decision making regarding avoidance of airspace hazards, each operator must consolidate operations-relevant information from disparate sources and apply extensive domain knowledge to correctly interpret not just the current state of the NAS but forecast its (combined) evolution over the duration of the operation. This time- and workload-intensive process is periodically repeated throughout the operation so that changes can be managed in a timely manner.The imprecision, inaccuracies, inconsistency, and incompleteness of the incoming data further challenges the process. To facilitate informed decision making, this paper presents a model-based framework for the textitautomated real-time monitoring and prediction of possible effects of airspace hazards on the safety of the National Airspace System (NAS). First, hazards to flight are identified and transformed into sms, that is, quantities of interest that could be evaluated based on available data and are predictive of an unsafe event. The sms and associated thresholds that specify when an event transitions from emphsafe to emphunsafe are combined with models of airspace operations and aircraft dynamics. The framework can include any hazard to flight that can be modeled quantitatively. Models can be detailed and complex, or they can be considerably simplifed, as appropriate to the application. Real-time NAS safety monitoring and prediction begins with an estimate of the state of the NAS using the dynamic models. Given the state estimate and a probability distribution of future inputs to the NAS, we can then predict the evolution of the NAS - the future state - and the occurrence of hazards and unsafe events. The entire probability distribution of airspace sms is computed, not just point estimates, without significant assumptions regarding the distribution type andor parameters. We demonstrate our overall approach through a simulated scenario in which we predict the occurrence of some unsafe events and show how these predictions evolve in time as flight operations progress. Predictions accounting for common sources of uncertainty are included and it is shown how the predictions improve in time, become more confident, and change dynamically as new information is made available to the prediction algorithm.

safety↗

NASA NTRS1995

Spectral and Temporal Characteristics of X-Ray-Bright Stars in the Pleiades

We follow up our deep ROSAT imaging survey of the Pleiades (Stauffer et al. 1994) with an analysis of the spectral and temporal characteristics of the X-ray-bright stars in the Pleiades. Raymond & Smith (1977) one and two-temperature models have been used to fit the position-sensitive proportional counter (PSPC) pulse-height spectra of the dozen or so brightest sources associated with late-type Pleiades members. The best-fit temperatures suggest hot coronal temperatures for K, M, and rapidly rotating G stars, and cooler temperatures for F and slowly rotating G stars. In order to probe the many less X-ray-luminous stars, we have generated composite spectra by combining net counts from all Pleiades members according to spectral type and rotational velocity. Model fits to the composite spectra confirm the trend seen in the individual spectral fits. Particularly interesting is the apparent dependence of coronal temperature on L(sub x)/L(sub bol). A hardness-ratio analysis also confirms some of these trends. The PSPC data have also revealed a dozen or so strong X-ray flares with peak X-ray luminosities in excess of approx. 10(exp 30) ergs/sec. We have modeled the brightest of these flares with a simple quasi-static cooling loop model. The peak temperature and emission measure and the inferred electron density and plasma volume suggest a very large scale flaring event. The PSPC data were collected over a period of approx. 18 months, allowing us to search for source variability on timescales ranging from less than a day (in the case of flares) to more than a year between individual exposures. On approximately year-long timescales, roughly 25% of the late-type stars are variable. Since the Pleiades was also intensively monitored by the imaging instruments on the Einstein Observatory, we have examined X-ray luminosity variations on the 10 yr timescale between Einstein and ROSAT and find that up to 40% of the late-type stars are X-ray variable. Since there is only marginal evidence for increased variability on decade-long timescales, the variability observed on long and short timescales may have a common physical origin.

Gagne, Marc↗

NASA NTRS2019

Benchmarking CME Arrival Time and Impact: Progress on Metadata, Metrics, and Events

Accurate forecasting of the arrival time and subsequent geomagnetic impacts of coronal mass ejections (CMEs) at Earth is an important objective for space weather forecasting agencies. Recently, the CME Arrival and Impact working team has made significant progress toward defining communit yagreed metrics and validation methods to assess the current state of CME modeling capabilities. This will allow the community to quantify our current capabilities and track progress in models over time. First, it is crucial that the community focuses on the collection of the necessary metadata for transparency and reproducibility of results. Concerning CME arrival and impact we have identified six different metadata types: 3D CME measurement, model description, model input, CME (non)arrival observation, model output data, and metrics and validation methods. Second, the working team has also identified a validation time period, where all events within the following two periods will be considered: 1 January 2011 to 31 December 2012 and January 2015 to 31 December 2015. Those two periods amount to a total of about 100 hit events at Earth and a large amount of misses. Considering a time period will remove any bias in selecting events and the event set will represent a sample set that will not be biased by user selection. Lastly, we have defined the basic metrics and skill scores that the CME Arrival and Impact working team will focus on.

Verbeke, C.↗

NASA NTRS2015

An Empirical Non-TNT Approach to Launch Vehicle Explosion Modeling

In an effort to increase crew survivability from catastrophic explosions of Launch Vehicles (LV), a study was conducted to determine the best method for predicting LV explosion environments in the near field. After reviewing such methods as TNT equivalence, Vapor Cloud Explosion (VCE) theory, and Computational Fluid Dynamics (CFD), it was determined that the best approach for this study was to assemble all available empirical data from full scale launch vehicle explosion tests and accidents. Approximately 25 accidents or full-scale tests were found that had some amount of measured blast wave, thermal, or fragment explosion environment characteristics. Blast wave overpressure was found to be much lower in the near field than predicted by most TNT equivalence methods. Additionally, fragments tended to be larger, fewer, and slower than expected if the driving force was from a high explosive type event. In light of these discoveries, a simple model for cryogenic rocket explosions is presented. Predictions from this model encompass all known applicable full scale launch vehicle explosion data. Finally, a brief description of on-going analysis and testing to further refine the launch vehicle explosion environment is discussed.

Blackwood, James M.↗

NASA NTRS2001

Monte Carlo track structure for radiation biology and space applications

Over the past two decades event by event Monte Carlo track structure codes have increasingly been used for biophysical modelling and radiotherapy. Advent of these codes has helped to shed light on many aspects of microdosimetry and mechanism of damage by ionising radiation in the cell. These codes have continuously been modified to include new improved cross sections and computational techniques. This paper provides a summary of input data for ionizations, excitations and elastic scattering cross sections for event by event Monte Carlo track structure simulations for electrons and ions in the form of parametric equations, which makes it easy to reproduce the data. Stopping power and radial distribution of dose are presented for ions and compared with experimental data. A model is described for simulation of full slowing down of proton tracks in water in the range 1 keV to 1 MeV. Modelling and calculations are presented for the response of a TEPC proportional counter irradiated with 5 MeV alpha-particles. Distributions are presented for the wall and wall-less counters. Data shows contribution of indirect effects to the lineal energy distribution for the wall counters responses even at such a low ion energy.

NASA Center JSC↗

NASA NTRS2009

Biophysics Representation of the Two-Hit Model of Alzheimer's Disease for the Exploration of Late CNS Risks from Space Radiation

A concern for long-term space travel outside the Earth s magnetic field is the late effects to the central nervous system (CNS) from galactic cosmic ray (GCR) or solar particle events (SPE). Human epidemiology data is severely limited for making CNS risk estimates and it is not clear such effects occur following low LET exposures. We are developing systems biology models based on biological information on specific diseases, and experimental data for proton and heavy ion radiation. A two-hit model of Alzheimer s disease (AD) has been proposed by Zhu et al.(1), which is the framework of our model. Of importance is that over 50% of the US population over the age of 75-y have mild to severe forms of AD. Therefore we recommend that risk assessment for a potential AD risk from space radiation should focus on the projection of an earlier age of onset of AD and the prevention of this possible acceleration through countermeasures. In the two-hit model, oxidative stress and aberrant cell cycle-related abnormalities leading to amyloid-beta plaques and neurofibrillary tangles are necessary and invariant steps in AD. We have formulated a stochastic cell kinetics model of the two-hit AD model. In our model a population of neuronal cells is allowed to undergo renewal through neurogenesis and is susceptible to oxidative stress or cell cycle abnormalities with age-specific accumulation of damage. Baseline rates are fitted to AD population data for specific ages, gender, and for persons with an apolipoprotein 4 allele. We then explore how low LET or heavy ions may increase either of the two-hits or neurogenesis either through persistent oxidative stress, direct mutation, or through changes to the micro-environment, and suggest possible ways to develop accurate quantitative estimates of these processes for predicting AD risks following long-term space travel.

Cucinotta, Francis A.↗

NASA NTRS2020

Uncertainty Quantification of Global Net Methane Emissions From Terrestrial Ecosystems Using a Mechanistically Based Biogeochemistry Model

Quantification of methane (CH4) emissions from wetlands and its sinks from uplands is still fraught with large uncertainties. Here, a methane biogeochemistry model was revised, parameterized, and verified for various wetland ecosystems across the globe. The model was then extrapolated to the global scale to quantify the uncertainty induced from four different types of uncertainty sources including parameterization, wetland type distribution, wetland area distribution, and meteorological input. We found that global wetland emissions are 212 ± 62 and 212 ± 32 Tg CH4 year−1 (1Tg = 1012 g) due to uncertain parameters and wetland type distribution, respectively, during 2000–2012. Using two wetland distribution data sets and three sets of climate data, the model simulations indicated that the global wetland emissions range from 186 to 212 CH4 year−1 for the same period. The parameters were the most significant uncertainty source. After combining the global methane consumption in the range of −34 to −46 Tg CH4 year−1, we estimated that the global net land methane emissions are 149–176 Tg CH4 year−1 due to uncertain wetland distribution and meteorological input. Spatially, the northeast United States and Amazon were two hotspots of methane emission, while consumption hotspots were in the Eastern United States and eastern China. During 1950–2016, both wetland emissions and upland consumption increased during El Niño events and decreased during La Niña events. This study highlights the need for more in situ methane flux data, more accurate wetland type, and area distribution information to better constrain the model uncertainty.

wetland methane emission↗