Practical Application of NASA-Langley Advanced Satellite Products to In-Flight Icing Nowcasts

Experimental satellite-based icing products developed by the NASA Langley Research Center provide new tools to identify the locations of icing and its intensity. Since 1997, research forecasters at the National Center for Atmospheric Research (NCAR) have been helping to guide the NASA Glenn Research Center's Twin Otter aircraft into and out of clouds and precipitation for the purpose of characterizing in-flight icing conditions, including supercooled large drops, the accretions that result from such encounters and their effect on aircraft performance. Since the winter of 2003-04, the NASA Langley satellite products have been evaluated as part of this process, and are being considered as an input to NCAR s automated Current Icing Potential (CIP) products. This has already been accomplished for a relatively straightforward icing event, but many icing events have much more complex characteristics, providing additional challenges to all icing diagnosis tools. In this paper, four icing events with a variety of characteristics will be examined, with a focus on the NASA Langley satellite retrievals that were available in real time and their implications for icing nowcasting and potential applications in CIP

Comparison of In-Situ, Model and Ground Based In-Flight Icing Severity

As an aircraft flies through supercooled liquid water, the liquid freezes instantaneously to the airframe thus altering its lift, drag, and weight characteristics. In-flight icing is a contributing factor to many aviation accidents, and the reliable detection of this hazard is a fundamental concern to aviation safety. The scientific community has recently developed products to provide in-flight icing warnings. NASA's Icing Remote Sensing System (NIRSS) deploys a vertically--pointing Ka--band radar, a laser ceilometer, and a profiling multi-channel microwave radiometer for the diagnosis of terminal area in-flight icing hazards with high spatial and temporal resolution. NCAR s Current Icing Product (CIP) combines several meteorological inputs to produce a gridded, three-dimensional depiction of icing severity on an hourly basis. Pilot reports are the best and only source of information on in-situ icing conditions encountered by an aircraft. The goal of this analysis was to ascertain how the testbed NIRSS icing severity product and the operational CIP severity product compare to pilot reports of icing severity, and how NIRSS and CIP compare to each other. This study revealed that the icing severity product from the ground-based NASA testbed system compared very favorably with the operational model-based product and pilot reported in-situ icing

Tropospheric Airborne Meteorological Data and Reporting (TAMDAR) Icing Sensor Performance during the 2003/2004 Alliance Icing Research Study (AIRS II)

NASA Langley Research Center and its research partners from the University of North Dakota (UND) and the National Center for Atmospheric Research (NCAR) participated in the AIRS II campaign from November 17 to December 17, 2003. AIRS II provided the opportunity to compare TAMDAR in situ in-flight icing condition assessments with in situ data from the UND Citation II aircraft's Rosemont system. TAMDAR is designed to provide a general warning of ice accretion and to report it directly into the Meteorological Data Communications and Reporting System (MDCRS). In addition to evaluating TAMDAR with microphysical data obtained by the Citation II, this study also compares these data to the NWS operational in-flight icing Current Icing Potential (CIP) graphic product and with the NASA Advanced Satellite Aviation-weather Products (ASAP) Icing Severity product. The CIP and ASAP graphics are also examined in this study to provide a context for the Citation II's sorties in AIRS II

Topology optimization for human proximal femur considering bi-modulus behavior of cortical bones

© Springer International Publishing Switzerland 2015. The material in the human proximal femur is considered as bi-modulus material and the density distribution is predicted by topology optimization method. To reduce the computational cost, the bi-modulus material is replaced with two isotropic materials in simulation. The selection of local material modulus is determined by the previous local stress state. Compared with density prediction results by traditional isotropic material in proximal femur, the bi-modulus material layouts are different obviously. The results also demonstrate that the bi-modulus material model is better than the isotropic material model in simulation of density prediction in femur bone

The Critical Role of Notch Ligand Delta-like 1 in the Pathogenesis of Influenza A Virus (H1N1) Infection

Influenza A viral infections have been identified as the etiologic agents for historic pandemics, and contribute to the annual mortality associated with acute viral pneumonia. While both innate and acquired immunity are important in combating influenza virus infection, the mechanism connecting these arms of the immune system remains unknown. Recent data have indicated that the Notch system is an important bridge between antigen-presenting cells (APCs) and T cell communication circuits and plays a central role in driving the immune system to overcome disease. In the present study, we examine the role of Notch signaling during influenza H1N1 virus infection, focusing on APCs. We demonstrate here that macrophages, but not dendritic cells (DCs), increased Notch ligand Delta-like 1 (Dll1) expression following influenza virus challenge. Dll1 expression on macrophages was dependent on retinoic acid-inducible gene-I (RIG-I) induced type-I IFN pathway, and not on the TLR3-TRIF pathway. We also found that IFNα-Receptor knockout mice failed to induce Dll1 expression on lung macrophages and had enhanced mortality during influenza virus infection. Our results further showed that specific neutralization of Dll1 during influenza virus challenge induced higher mortality, impaired viral clearance, and decreased levels of IFN-γ. In addition, we blocked Notch signaling by using γ-secretase inhibitor (GSI), a Notch signaling inhibitor. Intranasal administration of GSI during influenza infection also led to higher mortality, and higher virus load with excessive inflammation and an impaired production of IFN-γ in lungs. Moreover, Dll1 expression on macrophages specifically regulates IFN-γ levels from CD4+and CD8+T cells, which are important for anti-viral immunity. Together, the results of this study show that Dll1 positively influences the development of anti-viral immunity, and may provide mechanistic approaches for modifying and controlling the immune response against influenza H1N1 virus infection

Near-real time cloud properties and aircraft icing indices from GEO and LEO satellites

Imagers on many of the current and future operational meteorological satellites in geostationary Earth orbit (GEO) and lower Earth orbit (LEO) have enough spectral channels to derive cloud microphysical properties useful for a variety of applications. The products include cloud amount, phase, optical depth, temperature, height and pressure, thickness, effective particle size, and ice or liquid water path, shortwave albedo, and outgoing longwave radiation for each imager pixel. Because aircraft icing depends on cloud temperature, droplet size, and liquid water content as well as aircraft variables, it is possible to estimate the potential icing conditions from the cloud phase, temperature, effective droplet size, and liquid water path. A prototype icing index is currently being derived over the contiguous USA in near-real time from Geostationary Operational Environmental Satellite (GOES-10 and 12) data on a half-hourly basis and from NOAA-16 Advanced Very High Resolution (AVHRR) data when available. Because the threshold-based algorithm is sensitiv

The Secondary Production of Ice in Cumulus Experiment (SPICULE)

The secondary ice process (SIP) is a major microphysical process, which can result in rapid enhancement of ice particle concentration in the presence of preexisting ice. SPICULE was conducted to further investigate the effect of collision–coalescence on the rate of the fragmentation of freezing drop (FFD) SIP mechanism in cumulus congestus clouds. Measurements were conducted over the Great Plains and central United States from two coordinated aircraft, the NSF Gulfstream V (GV) and SPEC Learjet 35A, both equipped with state-of-the-art microphysical instrumentation and vertically pointing W- and Ka-band radars, respectively. The GV primarily targeted measurements of subcloud aerosols with subsequent sampling in warm cloud. Simultaneously, the Learjet performed multiple penetrations of the ascending cumulus congestus (CuCg) cloud top. First primary ice was typically detected at temperatures colder than −10°C, consistent with measured ice nucleating particles. Subsequent production of ice via FFD SIP was strongly related to the concentration of supercooled large drops (SLDs), with diameters from about 0.2 to a few millimeters. The concentration of SLDs is directly linked to the rate of collision–coalescence, which depends primarily on the subcloud aerosol size distribution and cloud-base temperature. SPICULE supports previous observational results showing that FFD SIP efficiency could be deduced from the product of cloud-base temperature and maximum diameter of drops measured ~300 m above cloud base. However, new measurements with higher concentrations of aerosol and total cloud-base drop concentrations show an attenuating effect on the rate of coalescence. The SPICULE dataset provides rich material for validation of numerical schemes of collision–coalescence and SIP to improve weather prediction simulations