Interactive access and management for four-dimensional environmental data sets using McIDAS

Significant accomplishments in the past year are presented and include the following: (1) enhancements to VIS-5D; (2) Implementation of the VIS AD System; and (3) numerical modeling applications. Focus of current research and plans for next year in the following areas are briefly discussed: (1) continued development and application of the VIS-AD system; (2) further enhancements to VIS-5D; and (3) plans for modeling applications

An Objective Analysis Technique for Constructing Three-Dimensional Urban-Scale Wind Fields

An objective analysis procedure for generating mass-consistent, urban-scale three-dimensional wind fields is presented together with a comparison against existing techniques. The algorithm employs terrain following coordinates and variable vertical grid spacing. Initial estimates of the velocity field are developed by interpolating surface and upper level wind measurements. A local terrain adjustment technique, involving solution of the Poisson equation, is used to establish the horizontal components of the surface field. Vertical velocities are developed from successive solutions of the continuity equation followed by an iterative procedure which reduces anomalous divergence in the complete field. Major advantages of the procedure are that it is computationally efficient and allows boundary values to adjust in response to changes in the interior flow. The method has been successfully tested using field measurements and problems with known analytic solutions

Machine learning tools for pattern recognition in polar climate science

This thesis explores the application of two novel machine learning approaches to the study of polar climate, with particular focus on Arctic sea ice. The first technique, complex networks, is based on an unsupervised learning approach which is able to exploit spatio-temporal patterns of variability within geospatial time series data sets. The second, Gaussian Process Regression (GPR), is a supervised learning Bayesian inference approach which establishes a principled framework for learning functional relationships between pairs of observation points, through updating prior uncertainty in the presence of new information. These methods are applied to a variety of problems facing the polar climate community at present, although each problem can be considered as an individual component of the wider problem relating to Arctic sea ice predictability. In the first instance, the complex networks methodology is combined with GPR in order to produce skilful seasonal forecasts of pan-Arctic and regional September sea ice extents, with up to 3 months lead time. De-trended forecast skills of 0.53, 0.62, and 0.81 are achieved at 3-, 2- and 1-month lead time respectively, as well as generally highest regional predictive skill ($> 0.30$) in the Pacific sectors of the Arctic, although the ability to skilfully predict many of these regions may be changing over time. Subsequently, the GPR approach is used to combine observations from CryoSat-2, Sentinel-3A and Sentinel-3B satellite radar altimeters, in order to produce daily pan-Arctic estimates of radar freeboard, as well as uncertainty, across the 2018--2019 winter season. The empirical Bayes numerical optimisation technique is also used to derive auxiliary properties relating to the radar freeboard, including its spatial and temporal (de-)correlation length scales, allowing daily pan-Arctic maps of these fields to be generated as well. The estimated daily freeboards are consistent to CryoSat-2 and Sentinel-3 to within $< 1$ mm (standard deviations $< 6$ cm) across the 2018--2019 season, and furthermore, cross-validation experiments show that prediction errors are generally $\leq 4$ mm across the same period. Finally, the complex networks approach is used to evaluate the presence of the winter Arctic Oscillation (AO) to summer sea ice teleconnection within 31 coupled climate models participating in phase 6 of the World Climate Research Programme Coupled Model Intercomparison Project (CMIP6). Two global metrics are used to compare patterns of variability between observations and models: the Adjusted Rand Index and a network distance metric. CMIP6 models generally over-estimate the magnitude of sea-level pressure variability over the north-western Pacific Ocean, and under-estimate the variability over the north Africa and southern Europe, while they also under-estimate the importance of regions such as the Beaufort, East Siberian and Laptev seas in explaining pan-Arctic summer sea ice area variability. They also under-estimate the degree of covariance between the winter AO and summer sea ice in key regions such as the East Siberian Sea and Canada basin, which may hinder their ability to make skilful seasonal to inter-annual predictions of summer sea ice

Acute Jaundice in a Six-year-old: An Unusual Presentation of Atypical Kawasaki Disease

Kawasaki disease (KD) is a rare vasculitis of childhood that is critical to recognize and treat due to associated morbidity and mortality. A six-year-old male presented to our emergency department (ED) afebrile but with reported recent fevers. Exam revealed jaundice and erythematous tongue with papules, and laboratory studies indicated a direct hyperbilirubinemia. Admitted for evaluation, he developed continuous fever, increasing maculopapular rash, and subsequent desquamation of hands and feet. He ultimately met criteria for incomplete KD, was treated with intravenous immunoglobulin, and avoided cardiac complications. This presentation of incomplete KD with hyperbilirubinemia is rare because the patient was afebrile at ED presentation

Gamma radiation background measurements from Spacelab 2

A Nuclear Radiation Monitor incorporating a NaI(Tl) scintillation detector was flown as part of the verification flight instrumentation on the Spacelab 2 mission, July 29 to August 6, 1985. Gamma-ray spectra were measured with better than 20 s resolution throughout most of the mission in the energy range 0.1 to 30 MeV. Knowledge of the decay characteristics and the geomagnetic dependence of the counting rates enable measurement of the various components of the Spacelab gamma-ray background: prompt secondary radiation, Earth albedo, and delayed induced radioactivity. The status of the data analysis and present relevant examples of typical background behavior are covered

Using Moored Arrays and Hyperspectral Aerial Imagery to Develop Nutrient Criteria for New Hampshire\u27s Estuaries

Increasing nitrogen concentrations and declining eelgrass beds in Great Bay, NH are clear indicators of impending problems for the state’s estuaries. A workgroup established in 2005 by the NH Department of Environmental Services and the NH Estuaries Project (NHEP) adopted eelgrass survival as the water quality target for nutrient criteria development for NH’s estuaries. In 2007, the NHEP received a grant from the U.S. Environmental Protection Agency to collect water quality information including that from moored sensors and hyper-spectral imagery data of the Great Bay Estuary. Data from the Great Bay Coastal Buoy, part of the regional Integrated Ocean Observing System (IOOS), were used to derive a multivariate model of water clarity with phytoplankton, Colored Dissolved Organic Matter (CDOM), and non-algal particles. Non-algal particles include both inorganic and organic matter. Most of the temporal variability in the diffuse attenuation coefficient of Photosynthetically Available Radiation (PAR) was associated with non-algal particles. However, on a mean daily basis non-algal particles and CDOM contributed a similar fraction (~30 %) to the attenuation of light. The contribution of phytoplankton was about a third of the other two optically important constituents. CDOM concentrations varied with salinity and magnitude of riverine inputs demonstrating its terrestrial origin. Non-algal particle concentration also varied with river flow but also wind driven resuspension. Twelve of the NHEP estuarine assessment zones were observed with the hyperspectral aerial imagery on August 29 and October 17. A concurrent in situ effort included buoy measurements, continuous along-track sampling, discrete water grab samples, and vertical profiles of light attenuation. PAR effective attenuation coefficients retrieved from deep water regions in the imagery agreed well with in-situ observations. Water clarity was lower and optically important constituent concentrations were higher in the tributaries. Eelgrass survival depth, estimated as the depth at which 22% of surface light was available, ranged from less than half a meter to over two meters. The best water clarity was found in the Great Bay (GB), Little Bay (LB), and Lower Piscataqua River (LPR) assessment zones. Absence of eelgrass from these zones would indicate controlling factors other than water clarity

Effect of Optical Coating and Surface Treatments on Mechanical Loss in Fused Silica

We report on the mechanical loss in fused silica samples with various surface treatments and compare them with samples having an optical coating. Mild surface treatments such as washing in detergent or acetone were not found to affect the mechanical loss of flame-drawn fused silica fibers stored in air. However, mechanical contact (with steel calipers) significantly increased the loss. The application of a high-reflective optical coating of the type used for the LIGO test masses was found to greatly increase the mechanical loss of commercially polished fused silica microscope slides. We discuss the implications for the noise budget of interferometers.Comment: 7 pages, 2 figures. Accepted for publication in the Proceedings of the Third Eduardo Amaldi Conference on Gravitational Waves, July 12-16, 1999. Updated version contains a correction of Eq. 3 and an estimate for the loss angle of a LIGO coating. (Neither of these revisions are included in the version published in the conference proceedings.

Stellar Activity and its Implications for Exoplanet Detection on GJ 176

We present an in-depth analysis of stellar activity and its effects on radial velocity (RV) for the M2 dwarf GJ 176 based on spectra taken over 10 years from the High Resolution Spectrograph on the Hobby-Eberly Telescope. These data are supplemented with spectra from previous observations with the HIRES and HARPS spectrographs, and V- and R-band photometry taken over 6 years at the Dyer and Fairborn observatories. Previous studies of GJ 176 revealed a super-Earth exoplanet in an 8.8-day orbit. However, the velocities of this star are also known to be contaminated by activity, particularly at the 39-day stellar rotation period. We have examined the magnetic activity of GJ 176 using the sodium I D lines, which have been shown to be a sensitive activity tracer in cool stars. In addition to rotational modulation, we see evidence of a long-term trend in our Na I D index, which may be part of a long-period activity cycle. The sodium index is well correlated with our RVs, and we show that this activity trend drives a corresponding slope in RV. Interestingly, the rotation signal remains in phase in photometry, but not in the spectral activity indicators. We interpret this phenomenon as the result of one or more large spot complexes or active regions which dominate the photometric variability, while the spectral indices are driven by the overall magnetic activity across the stellar surface. In light of these results, we discuss the potential for correcting activity signals in the RVs of M dwarfs.Comment: Accepted for publication in Ap

Pilot Project Funding Opportunities

Learn about funding opportunities offered through the UMCCTS in the 2012-2013 academic year. Bill Thomas and Greg Babcock describe the resources available at MassBiologics and the new Next Hundred Million Pilot Program funding opportunity

Astrophysical Gyrokinetics: Basic Equations and Linear Theory

Magnetohydrodynamic (MHD) turbulence is encountered in a wide variety of astrophysical plasmas, including accretion disks, the solar wind, and the interstellar and intracluster medium. On small scales, this turbulence is often expected to consist of highly anisotropic fluctuations with frequencies small compared to the ion cyclotron frequency. For a number of applications, the small scales are also collisionless, so a kinetic treatment of the turbulence is necessary. We show that this anisotropic turbulence is well described by a low frequency expansion of the kinetic theory called gyrokinetics. This paper is the first in a series to examine turbulent astrophysical plasmas in the gyrokinetic limit. We derive and explain the nonlinear gyrokinetic equations and explore the linear properties of gyrokinetics as a prelude to nonlinear simulations. The linear dispersion relation for gyrokinetics is obtained and its solutions are compared to those of hot-plasma kinetic theory. These results are used to validate the performance of the gyrokinetic simulation code {\tt GS2} in the parameter regimes relevant for astrophysical plasmas. New results on global energy conservation in gyrokinetics are also derived. We briefly outline several of the problems to be addressed by future nonlinear simulations, including particle heating by turbulence in hot accretion flows and in the solar wind, the magnetic and electric field power spectra in the solar wind, and the origin of small-scale density fluctuations in the interstellar medium.Comment: emulateapj, 24 pages, 10 figures, revised submission to ApJ: references added, typos corrected, reorganized and streamline