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The Zebiak and Cane (1987) model is used in its uncoupled mode.
The two MarCO “cubesat” spacecraft were launched alongside NASA’s InSight in May 2018, operating primarily as a technology demonstrator for small satellites in deep space, with a nominal (but experimental) mission to provide relay support for the primary spacecraft during entry, descent, and landing at Mars. Due to their small size and experimental nature, extensive use of telemetry beyond that commonly used by deep space missions was necessary to complete adequate orbit determination. In particular, telemetry was valuable in two areas: use of wheel speeds during thruster calibrations to improve knowledge of individual thruster force levels, and the use of propellant temperature and pressure data to correctly model small thrusting events on board the vehicle.
The envisioned future of Advanced Air Mobility involves low-altitude operation of a new class of air vehicles. The low altitudes of the flight paths would have these vehicles spending most of their operation in conditions where unpredictable wind and turbulence effects may occur. Wind measurements will hence be critical to ensure safe and efficient operations for AAM. Such wind measurement could be used as a monitoring system for warning of hazardous wind events, as data input to forecasting models, or as a research tool to understand wind effects in complex environments. To meet this need NASA is evaluating wind sensing technologies with a capability to probe the atmospheric boundary layer. Doppler lidar is a leading candidate ground-based sensor, as shown by the decades-long history of being an effective tool for many wind studies. However, there is a need to re-assess the Doppler wind lidars for the AAM application which involves evaluating wind effects as vehicles operate in and out of vertiports, notably regarding spatial resolution. Meeting the needs for spatial resolution may involve the use of dual-Doppler techniques, rather than just single Doppler lidar. The study was furthermore motivated by looking toward the future of AAM, in which the air vehicles involved can also provide wind measurements. Airborne wind measurements, obtained directly from vehicle-mounted anemometers or indirectly from vehicle navigation data, offer a means to compare remotely sensed wind lidar with in-situ measurements. The following sections report on results of wind measurements obtained using lidar and the small uninhabited aircraft systems (sUAS’s) operating in the same volume of air.
In this paper, we examine the conditions under which the Cane and Zebiak's model can be run so that the simulated anomalies of wind and SST agree better with the observations.
We have analyzed calibration data acquired during the Orbital Activation and Checkout (OAC) phase of the Chandra X-ray Observatory (CXO) mission in order to characterize the background of the Advanced CCD Imaging Spectrometer (ACIS) produced by charged particles and non-cosmic X-rays. The ACIS instrument contains 8 Front-Illuminated (FI) CCDs and 2 Back-Illuminated (BI) CCDs. The FI and BI CCD)s exhibit dramatically different responses to enhancements in the particle flux. The F1 CCDs show relatively little increase in the overall count rate, typical increases are 1 - 3 counts/s; the BI CCDs show large excursions to as high as 100 counts/s. The duration of these intervals of enhanced background are highly variable ranging from 100 s to 5000 s. The spatial distribution of these background events is relatively flat across the power-law. The events produce morphologies which are similar to cosmic X-ray events, so that morphology alone cannot be used as a rejection criterion. We explore the correlation of these times of high background with the data from Chandra's on-board radiation monitor, the EPHIN (Electron, Proton, Helium Instrument particle detector) instrument and archival data from the Advanced Composition Explorer (ACE) satellite. We discuss strategies for observers to identify and exclude times of high background and to model and subtract the background events from their data.
We have analyzed calibration data acquired during the Orbital Activation and Checkout (OAC) phase of the Chandra X-ray Observatory (CXO) mission in order to characterize the background of the Advanced CCD Imaging Spectrometer (ACIS) produced by charged particles and non-cosmic x-rays. The ACIS instrument contains eight Front-Illuminated (FI) CCDs and two Back-Illuminated (BI) CCDs. The FI and BI CCDs exhibit dramatically different responses to enhancements in the particle flux. The FI CCDs show relatively little increase in the overall count rate, typical increases are 1-3 counts/s; the BI CCDs show large excursions to as high as 100 counts/s. The directions of these intervals of enhanced background are highly variable ranging from 100 s to 5000 s. The spatial distribution of these background events is relatively flat across the detectors. The spectral distribution can be characterized by a simple power law. The events produce morphologies which are similar to cosmic x-ray events, so that morphology alone cannot be used as a rejection criterion. We explore the correlation of these times of high background with the data from Chandra's on-board radiation monitor, the EPHIN (Electron, Proton, Helium Instrument particle detector) instrument and archival data from the Advanced Composition Explorer (ACE) satellite. We discuss strategies for observers to identify and exclude times of high background and to model and subtract the background events from their data.
We describe the main differences in simulations of stratospheric climate and variability by models within the fifth Coupled Model Intercomparison Project (CMIP5) that have a model top above the stratopause and relatively fine stratospheric vertical resolution (high-top), and those that have a model top below the stratopause (low-top). Although the simulation of mean stratospheric climate by the two model ensembles is similar, the low-top model ensemble has very weak stratospheric variability on daily and interannual time scales. The frequency of major sudden stratospheric warming events is strongly underestimated by the low-top models with less than half the frequency of events observed in the reanalysis data and high-top models. The lack of stratospheric variability in the low-top models affects their stratosphere-troposphere coupling, resulting in short-lived anomalies in the Northern Annular Mode, which do not produce long-lasting tropospheric impacts, as seen in observations. The lack of stratospheric variability, however, does not appear to have any impact on the ability of the low-top models to reproduce past stratospheric temperature trends. We find little improvement in the simulation of decadal variability for the high-top models compared to the low-top, which is likely related to the fact that neither ensemble produces a realistic dynamical response to volcanic eruptions.
Satellite data acquired and processed in real time now have the potential to provide the spacetime information on rainfall needed to monitor flood and landslide events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models and landslide algorithms. Progress in using the TRMM Multi-satellite Precipitation Analysis (TMPA) as input to flood and landslide forecasts is outlined, with a focus on understanding limitations of the rainfall data and impacts of those limitations on flood/landslide analyses. Case studies of both successes and failures will be shown, as well as comparison with ground comparison data sets both in terms of rainfall and in terms of flood/landslide events. In addition to potential uses in real-time, the nearly ten years of TMPA data allow retrospective running of the models to examine variations in extreme events. The flood determination algorithm consists of four major components: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM (Shuttle Radar Terrain Mission), topography-derived hydrologic parameters such as flow direction, flow accumulation, basin, and river network etc.; 3) a hydrological model to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay the input data to the models and display the flood inundation results to potential users and decision-makers. In terms of landslides, the satellite rainfall information is combined with a global landslide susceptibility map, derived from a combination of global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a weighted linear combination approach. In those areas identified as "susceptible" (based on the surface characteristics), landslides are forecast where and when a rainfall intensity/duration threshold is exceeded. Results are described indicating general agreement with landslide occurrences. However, difficulties in comparing landslide event information (mostly from news reports) with the satellite-based forecasts are analyzed.
A global time-dependent model is presented for the coronal and interplanetary shock acceleration and propagation of energetic solar flare particles. The calculations are carried out to help prove that coronal shock acceleration of solar flare particles is responsible for energetic solar flare event data gathered in interplanetary space. The model is based on the theory of diffusive shock acceleration, and requires particle speeds to be much greater than bulk velocities. Also, sufficient scattering must occur upstream and downstream of the shock for the particle scattering mean free path to be smaller than the characteristic scale lengths, which causes the same particles to encounter the shock repeatedly. A spherically symmetric shock wave is assumed, which leads to the same emission configuration for impulsively and monoenergetically emitted particles. Consideration is given to acceleration by compression at the shock front, adiabatic deceleration in the divergent downstream flow, the temporal evolution of the shock and the three-dimensional geometry of the corona. The model is used to generate normalized proton omnidirectional distributions at 1 AU and at the shock front. The spectral exhibit trends similar to those in observational data, especially proton acceleration times and the proton distribution profiles at 1 AU.
Satellite data acquired and processed in real time now have the potential to provide the spacetime information on rainfall needed to monitor flood and landslide events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models and landslide algorithms. Progress in using the TRMM Multi-satellite Precipitation Analysis (TMPA) as input to flood and landslide forecasts is outlined, with a focus on understanding limitations of the rainfall data and impacts of those limitations on flood/landslide analyses. Case studies of both successes and failures will be shown, as well as comparison with ground comparison data sets-- both in terms of rainfall and in terms of flood/landslide events. In addition to potential uses in real-time, the nearly ten years of TMPA data allow retrospective running of the models to examine variations in extreme events. The flood determination algorithm consists of four major components: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM (Shuttle Radar Terrain Mission), topography-derived hydrologic parameters such as flow direction, flow accumulation, basin, and river network etc.; 3) a hydrological model to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay the input data to the models and display the flood inundation results to potential users and decision-makers, In terms of landslides, the satellite rainfall information is combined with a global landslide susceptibility map, derived from a combination of global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a weighted linear combination approach. In those areas identified as "susceptible" (based on the surface characteristics), landslides are forecast where and when a rainfall intensity/duration threshold is exceeded. Results are described indicating general agreement with landslide occurrences.
A wide range of observational studies are carried out to improve our understanding of the bodies of the outer solar system. Using the 200-inch Hale telescope, near-infrared observations are made of Uranus, Neptune, and the Pluto-Charon system. High time resolution occultation observations of the Uranus Ring system are used to study in detail the dynamics of this system. Occultation studies of Neptune are probing this intriguing ring-arc system. Occulation observations of the Pluto-Charon system probe the surface properties of these distant bodies. In addition, the plate material of the PSSII servey is being used to search for new comets and asteroids. Researchers observed one Neptune stellar occultation in July 1987 and completed the analysis of a series of seven separate Neptune occultation observations in conjunction with Nicholson et al., of Cornell. The analysis has shown that minimum of three ring arcs, at radii ranging from 54,000 km - 67,000 km are required to account for the high quality ring events. Current theoretical models can account for these data. Of two observations scheduled of Pluto-Charon mutual occulations scheduled for the 200-inch, the Charon eclipse event was successfully observed (the other was clouded out).
A comprehensive understanding of the meteorological and microphysical nature of Mediterranean storms requires a combination of in situ data analysis, radar data analysis, and satellite data analysis, effectively integrated with numerical modeling studies at various scales. An important aspect of understanding microphysical controls of severe storms, is first understanding the meteorological controls under which a storm has evolved, and then using that information to help characterize the dominant microphysical processes. For hazardous Mediterranean storms, highlighted by the October 5-6, 1998 Friuli flood event in northern Italy, a comprehensive microphysical interpretation requires an understanding of the multiple phases of storm evolution. This involves intense convective development, Sratiform decay, orographic lifting, and sloped frontal lifting processes, as well as the associated vertical motions and thermodynamical instabilities governing physical processes that effect details of the size distributions and fall rates of the various types of hydrometeors found within the storm environment. This talk overviews the microphysical elements of a severe Mediterranean storm in such a context, investigated with the aid of TRMM satellite and other remote sensing measurements, but guided by a nonhydrostatic mesoscale model simulation of the Friuli flood event. The data analysis for this paper was conducted by my research groups at the Global Hydrology and Climate Center in Huntsville, AL and Florida State University in Tallahassee, and in collaboration with Dr. Alberto Mugnai's research group at the Institute of Atmospheric Physics in Rome. The numerical modeling was conducted by Professor Oreg Tripoli and Ms. Giulia Panegrossi at the University of Wisconsin in Madison, using Professor Tripoli's nonhydrostatic modeling system (NMS). This is a scalable, fully nested mesoscale model capable of resolving nonhydrostatic circulations from regional scale down to cloud scale and below.
Proton data from the GOES 6 and 7 satellites and heavy ion data from the IMP-8 satellite have been compared to the expected results of Nymmik's new model for solar particle event fluences. This model calculates the energy spectra of Ions for protons through nickel for solar particle events, based upon the observed proton integral fluence above 30 MeV. Based upon 27 observed proton events of solar cycle 22, and three large historical events, with integral fluences above 30 MeV of greater than 106 particles/cm2, a reasonable agreement with model predictions is seen for more than half of the events. However, several events show a marked departure from the model predictions, leading to the conclusion that there may exist more than a single class of event, or that it may be necessary to include additional parameters within the model, such as solar disk position of the source flare, or height of disturbance in the solar corona. Data for heavy Ions, (oxygen and iron), were limited to a total of six solar particle events, of which only two occurred in solar cycle 22. The agreement between data and the model predictions appeared to be quite good, however this agreement was sensitively dependent upon the value taken for the proton fluence above 30 MeV.
Short-term air pollution episodes motivate improved understanding of the association between air pollution and acute morbidity and mortality episodes, and triggers required mitigation plans. A variety of methods have been employed to estimate exposure to air pollution episodes, including GIS-based dispersion models, interpolation between sparse monitoring sites, land-use regression models, optimization models, line- or area-dispersion plume models, and models using information from imaging satellites, often including land-use and meteorological variables. There has been increasing use of satellite-borne aerosol products for assessing short-term air quality events. They provide better spatial coverage, but currently at the price of low temporal coverage and rather crude spatial resolution. This brief review of using satellite data for modeling short-term air quality and pollution events. The review can be pursued as a practical guide for modeling air quality with satellite-based products, as it includes important questions that should be considered in both the study design as well as the model development stages. Progress in this field is detailed and includes published models and their use in environmental and health studies. Both current and future satellite-borne capabilities are covered. It also provides links to access and download relevant datasets and some R code for data processing and modeling.
Observations of sea-surface heights from satellite altimeters have been a major contributor to monitoring the evolution of the recent major El Nino event. Assimilating altimeter data directly into numerical models only takes advantage of the surface signature provided by the data. However, that surface signature is usually indicative of processes occurring at depth, especially in the equatorial Pacific. In order for assimilation schemes to make maximum use of surface data, it is helpful to have knowledge of how to best extend that data in the vertical to account for that variability. Toward that end, the vertical correlation structure between satellite-observed sea-surface heights and in situ temperature measurements is examined using TOPEX altimeter and TOGA TAO profile data for the period 1993-1998. This time period includes several states of the tropical Pacific, including a perturbed state from 1993-1994, a quiescent state encompassing 1995-1996, and the major ENSO event of 1997-1998. Analyses for each of these periods, as well as the total period will be presented. In addition to analyses at specific depth levels, analyses for particular density surfaces will also be presented.
Two laboratory-based impact tests have been conducted to develop and extend the capability of NASA satellite breakup models. The first experiment, the Satellite Orbital Debris Characterization Impact Test (SOCIT), was conducted by the U.S. Department of Defense and NASA in 1992. It employed a fully functional U.S. Navy Transit spacecraft, fabricated from materials commonly used in the 1960s. SOCIT fragmentation data formed the basis of the current NASA Standard Satellite Breakup Model (SSBM). A second experiment, DebriSat, was conducted in 2014 by the DebriSat consortium: the NASA Orbital Debris Program Office, the United States Space Force Space Systems Command, formerly the Air Force Space and Missile Systems Center, the Air Force Arnold Engineering Development Complex, and the University of Florida. This impact test was performed on a high-fidelity mock-up satellite assembled from modern components. Data from both experiments are expected to contribute to the next-generation models for on-orbit breakup analyses, long-term environment predictions, and debris risk assessment. This paper uses the direct statistical sampling of the SOCIT and DebriSat data ensembles to model an on-orbit breakup event, rather than the analytic expressions estimated from the samples in the SSBM and its predecessor. This direct method involves drawing fragments (i.e., sampling with replacement) from each fragmentation data-subset containing mass, shape category, material density, characteristic length, mass, and cross-sectional area. As part of the sampling process, the properties of sampled fragment data (e.g., area-to-mass ratios) are numerically checked to ensure they do not contain unrealistic quantities. The process to simulate a breakup cloud composed of fragments from SOCIT and DebriSat datasets is discussed. The methodology for ensuring that conservation of overall mass of the sampled fragment cloud under this sampling approach is highlighted. Finally, the results are compared with simulated clouds generated from SSBM for specific historical breakup events.
We take advantage of the May 1998 biomass burning event in Southern Mexico to test the global applicability of a smoke aerosol size model developed from data observed in South America. The Mexican event is an unique opportunity to observe well-aged, residual smoke. Observations of smoke aerosol size distribution made from vertical profiles of airborne in situ measurements show an inverse relationship between concentration and particle size that suggests the aging process continues more than a week after the smoke is separated from its fire sources. The ground-based radiometer retrievals show that the column-averaged, aged, Mexican smoke particles are larger (diameter = 0.28 - 0.33 micrometers) than the mean smoke particles in South America (diameter = 0.22 - 0.30 micrometers). However, the difference (delta - 0.06 micrometer) translates into differences in backscattering coefficient of only 4-7% and an increase of direct radiative forcing of only 10%.
The Community Coordinated Modeling Center (CCMC) hosts a set of state-of-the-art space science models ranging from the solar atmosphere to the Earth's upper atmosphere. CCMC provides a web-based Run-on-Request system, by which the interested scientist can request simulations for a broad range of space science problems. To allow the models to be driven by data relevant to particular events CCMC developed a tool that automatically downloads data from data archives and transform them to required formats. CCMC also provides a tailored web-based visualization interface for the model output, as well as the capability to download the simulation output in portable format. CCMC offers a variety of visualization and output analysis tools to aid scientists in interpretation of simulation results. During eight years since the Run-on-request system became available the CCMC archived the results of almost 3000 runs that are covering significant space weather events and time intervals of interest identified by the community. The simulation results archived at CCMC also include a library of general purpose runs with modeled conditions that are used for education and research. Archiving results of simulations performed in support of several Modeling Challenges helps to evaluate the progress in space weather modeling over time. We will highlight the scientific benefits of CCMC space science model archive and discuss plans for further development of advanced methods to interact with simulation results.