ALBERT

Description: Amorphous metal-oxide semiconductors have emerged as potential replacements for organic and silicon materials in thin-film electronics. The high carrier mobility in the amorphous state, and excellent large-area uniformity, have extended their applications to active-matrix electronics, including displays, sensor arrays and X-ray detectors. Moreover, their solution processability and optical transparency have opened new horizons for low-cost printable and transparent electronics on plastic substrates. But metal-oxide formation by the sol-gel route requires an annealing step at relatively high temperature, which has prevented the incorporation of these materials with the polymer substrates used in high-performance flexible electronics. Here we report a general method for forming high-performance and operationally stable metal-oxide semiconductors at room temperature, by deep-ultraviolet photochemical activation of sol-gel films. Deep-ultraviolet irradiation induces efficient condensation and densification of oxide semiconducting films by photochemical activation at low temperature. This photochemical activation is applicable to numerous metal-oxide semiconductors, and the performance (in terms of transistor mobility and operational stability) of thin-film transistors fabricated by this route compares favourably with that of thin-film transistors based on thermally annealed materials. The field-effect mobilities of the photo-activated metal-oxide semiconductors are as high as 14 and 7 cm(2) V(-1) s(-1) (with an Al(2)O(3) gate insulator) on glass and polymer substrates, respectively; and seven-stage ring oscillators fabricated on polymer substrates operate with an oscillation frequency of more than 340 kHz, corresponding to a propagation delay of less than 210 nanoseconds per stage.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Kim, Yong-Hoon -- Heo, Jae-Sang -- Kim, Tae-Hyeong -- Park, Sungjun -- Yoon, Myung-Han -- Kim, Jiwan -- Oh, Min Suk -- Yi, Gi-Ra -- Noh, Yong-Young -- Park, Sung Kyu -- England -- Nature. 2012 Sep 6;489(7414):128-32. doi: 10.1038/nature11434.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Flexible Display Research Center, Korea Electronics Technology Institute, Seongnam 463-816, Korea.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/22955624" target="_blank"〉PubMed〈/a〉

Description: Alzheimer's disease is the most common form of dementia, characterized by two pathological hallmarks: amyloid-beta plaques and neurofibrillary tangles. The amyloid hypothesis of Alzheimer's disease posits that the excessive accumulation of amyloid-beta peptide leads to neurofibrillary tangles composed of aggregated hyperphosphorylated tau. However, to date, no single disease model has serially linked these two pathological events using human neuronal cells. Mouse models with familial Alzheimer's disease (FAD) mutations exhibit amyloid-beta-induced synaptic and memory deficits but they do not fully recapitulate other key pathological events of Alzheimer's disease, including distinct neurofibrillary tangle pathology. Human neurons derived from Alzheimer's disease patients have shown elevated levels of toxic amyloid-beta species and phosphorylated tau but did not demonstrate amyloid-beta plaques or neurofibrillary tangles. Here we report that FAD mutations in beta-amyloid precursor protein and presenilin 1 are able to induce robust extracellular deposition of amyloid-beta, including amyloid-beta plaques, in a human neural stem-cell-derived three-dimensional (3D) culture system. More importantly, the 3D-differentiated neuronal cells expressing FAD mutations exhibited high levels of detergent-resistant, silver-positive aggregates of phosphorylated tau in the soma and neurites, as well as filamentous tau, as detected by immunoelectron microscopy. Inhibition of amyloid-beta generation with beta- or gamma-secretase inhibitors not only decreased amyloid-beta pathology, but also attenuated tauopathy. We also found that glycogen synthase kinase 3 (GSK3) regulated amyloid-beta-mediated tau phosphorylation. We have successfully recapitulated amyloid-beta and tau pathology in a single 3D human neural cell culture system. Our unique strategy for recapitulating Alzheimer's disease pathology in a 3D neural cell culture model should also serve to facilitate the development of more precise human neural cell models of other neurodegenerative disorders.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4366007/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4366007/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Choi, Se Hoon -- Kim, Young Hye -- Hebisch, Matthias -- Sliwinski, Christopher -- Lee, Seungkyu -- D'Avanzo, Carla -- Chen, Hechao -- Hooli, Basavaraj -- Asselin, Caroline -- Muffat, Julien -- Klee, Justin B -- Zhang, Can -- Wainger, Brian J -- Peitz, Michael -- Kovacs, Dora M -- Woolf, Clifford J -- Wagner, Steven L -- Tanzi, Rudolph E -- Kim, Doo Yeon -- 5P01AG15379/AG/NIA NIH HHS/ -- 5R37MH060009/MH/NIMH NIH HHS/ -- P01 AG004953/AG/NIA NIH HHS/ -- P01 AG015379/AG/NIA NIH HHS/ -- P30 HD018655/HD/NICHD NIH HHS/ -- P30 NS045776/NS/NINDS NIH HHS/ -- P50 AG005134/AG/NIA NIH HHS/ -- R01 AG014713/AG/NIA NIH HHS/ -- R01 NS045860/NS/NINDS NIH HHS/ -- R21 AG031483/AG/NIA NIH HHS/ -- RF1 AG048080/AG/NIA NIH HHS/ -- England -- Nature. 2014 Nov 13;515(7526):274-8. doi: 10.1038/nature13800. Epub 2014 Oct 12.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉1] Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts 02129, USA [2]. ; 1] Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts 02129, USA [2] Division of Mass Spectrometry Research, Korea Basic Science Institute, Cheongju-si, Chungbuk 363-883, South Korea [3]. ; 1] Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts 02129, USA [2] Institute of Reconstructive Neurobiology, Life and Brain Center, University of Bonn and Hertie Foundation, 53127 Bonn, Germany. ; Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts 02129, USA. ; FM Kirby Neurobiology Center, Boston Children's Hospital and Harvard Stem Cell Institute, Boston, Massachusetts 02115, USA. ; The Whitehead Institute for Biomedical Research, Cambridge, Massachusetts 02142, USA. ; Institute of Reconstructive Neurobiology, Life and Brain Center, University of Bonn and Hertie Foundation, 53127 Bonn, Germany. ; Department of Neurosciences, University of California, San Diego, La Jolla, California 92093, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25307057" target="_blank"〉PubMed〈/a〉

Description: We have sequenced the genomes of 110 small cell lung cancers (SCLC), one of the deadliest human cancers. In nearly all the tumours analysed we found bi-allelic inactivation of TP53 and RB1, sometimes by complex genomic rearrangements. Two tumours with wild-type RB1 had evidence of chromothripsis leading to overexpression of cyclin D1 (encoded by the CCND1 gene), revealing an alternative mechanism of Rb1 deregulation. Thus, loss of the tumour suppressors TP53 and RB1 is obligatory in SCLC. We discovered somatic genomic rearrangements of TP73 that create an oncogenic version of this gene, TP73Deltaex2/3. In rare cases, SCLC tumours exhibited kinase gene mutations, providing a possible therapeutic opportunity for individual patients. Finally, we observed inactivating mutations in NOTCH family genes in 25% of human SCLC. Accordingly, activation of Notch signalling in a pre-clinical SCLC mouse model strikingly reduced the number of tumours and extended the survival of the mutant mice. Furthermore, neuroendocrine gene expression was abrogated by Notch activity in SCLC cells. This first comprehensive study of somatic genome alterations in SCLC uncovers several key biological processes and identifies candidate therapeutic targets in this highly lethal form of cancer.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉George, Julie -- Lim, Jing Shan -- Jang, Se Jin -- Cun, Yupeng -- Ozretic, Luka -- Kong, Gu -- Leenders, Frauke -- Lu, Xin -- Fernandez-Cuesta, Lynnette -- Bosco, Graziella -- Muller, Christian -- Dahmen, Ilona -- Jahchan, Nadine S -- Park, Kwon-Sik -- Yang, Dian -- Karnezis, Anthony N -- Vaka, Dedeepya -- Torres, Angela -- Wang, Maia Segura -- Korbel, Jan O -- Menon, Roopika -- Chun, Sung-Min -- Kim, Deokhoon -- Wilkerson, Matt -- Hayes, Neil -- Engelmann, David -- Putzer, Brigitte -- Bos, Marc -- Michels, Sebastian -- Vlasic, Ignacija -- Seidel, Danila -- Pinther, Berit -- Schaub, Philipp -- Becker, Christian -- Altmuller, Janine -- Yokota, Jun -- Kohno, Takashi -- Iwakawa, Reika -- Tsuta, Koji -- Noguchi, Masayuki -- Muley, Thomas -- Hoffmann, Hans -- Schnabel, Philipp A -- Petersen, Iver -- Chen, Yuan -- Soltermann, Alex -- Tischler, Verena -- Choi, Chang-min -- Kim, Yong-Hee -- Massion, Pierre P -- Zou, Yong -- Jovanovic, Dragana -- Kontic, Milica -- Wright, Gavin M -- Russell, Prudence A -- Solomon, Benjamin -- Koch, Ina -- Lindner, Michael -- Muscarella, Lucia A -- la Torre, Annamaria -- Field, John K -- Jakopovic, Marko -- Knezevic, Jelena -- Castanos-Velez, Esmeralda -- Roz, Luca -- Pastorino, Ugo -- Brustugun, Odd-Terje -- Lund-Iversen, Marius -- Thunnissen, Erik -- Kohler, Jens -- Schuler, Martin -- Botling, Johan -- Sandelin, Martin -- Sanchez-Cespedes, Montserrat -- Salvesen, Helga B -- Achter, Viktor -- Lang, Ulrich -- Bogus, Magdalena -- Schneider, Peter M -- Zander, Thomas -- Ansen, Sascha -- Hallek, Michael -- Wolf, Jurgen -- Vingron, Martin -- Yatabe, Yasushi -- Travis, William D -- Nurnberg, Peter -- Reinhardt, Christian -- Perner, Sven -- Heukamp, Lukas -- Buttner, Reinhard -- Haas, Stefan A -- Brambilla, Elisabeth -- Peifer, Martin -- Sage, Julien -- Thomas, Roman K -- 5R01CA114102-08/CA/NCI NIH HHS/ -- England -- Nature. 2015 Aug 6;524(7563):47-53. doi: 10.1038/nature14664. Epub 2015 Jul 13.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Translational Genomics, Center of Integrated Oncology Cologne-Bonn, Medical Faculty, University of Cologne, 50931 Cologne, Germany. ; Departments of Pediatrics and Genetics, Stanford University, Stanford, California 94305, USA. ; Department of Pathology and Center for Cancer Genome Discovery, University of Ulsan College of Medicine, Asan Medical Center 88, Olympic-ro 43-gil, Songpa-gu, Seoul 138-736, Korea. ; Department of Pathology, University Hospital Cologne, 50937 Cologne, Germany. ; Department of Pathology, College of Medicine, Hanyang University. 222 Wangsimniro, Seongdong-gu, Seoul 133-791, Korea. ; Vancouver General Hospital, Terry Fox laboratory, Vancouver, British Columbia V5Z 1L3, Canada. ; European Molecular Biology Laboratory, Genome Biology Unit, 69117 Heidelberg, Germany. ; Institute of Pathology, Center of Integrated Oncology Cologne-Bonn, University Hospital of Bonn, 53127 Bonn, Germany. ; Center for Cancer Genome Discovery, University of Ulsan College of Medicine, Asan Medical Center 88, Olympic-ro 43-gil, Songpa-gu, Seoul 138-736, Korea. ; Department of Genetics, Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, North Carolina 27599-7295, USA. ; UNC Lineberger Comprehensive Cancer Center School of Medicine, University of North Carolina at Chapel Hill, North Carolina 27599-7295, USA. ; Institute of Experimental Gene Therapy and Cancer Research, Rostock University Medical Center, 18057 Rostock, Germany. ; Department I of Internal Medicine, Center of Integrated Oncology Cologne-Bonn, University Hospital Cologne, 50937 Cologne, Germany. ; Department of Internal Medicine, University Hospital of Cologne, 50931 Cologne, Germany. ; Cologne Center for Genomics (CCG), University of Cologne, 50931 Cologne, Germany. ; 1] Cologne Center for Genomics (CCG), University of Cologne, 50931 Cologne, Germany. [2] Institute of Human Genetics, University Hospital Cologne, 50931 Cologne, Germany. ; 1] Division of Genome Biology, National Cancer Center Research Institute, Chuo-ku, Tokyo 1040045, Japan. [2] Genomics and Epigenomics of Cancer Prediction Program, Institute of Predictive and Personalized Medicine of Cancer (IMPPC), Barcelona 08916, Spain. ; Division of Genome Biology, National Cancer Center Research Institute, Chuo-ku, Tokyo 1040045, Japan. ; Department of Pathology and Clinical Laboratories, National Cancer Center Hospital Chuo-ku, Tokyo 1040045, Japan. ; Department of Pathology, Faculty of Medicine, University of Tsukuba, Ibaraki 305-8575, Japan. ; 1] Thoraxklinik at University Hospital Heidelberg, Amalienstrasse 5, 69126 Heidelberg, Germany. [2] Translational Lung Research Center Heidelberg (TLRC-H), Member of German Center for Lung Research (DZL), Amalienstrasse 5, 69126 Heidelberg, Germany. ; Thoraxklinik at University Hospital Heidelberg, Amalienstrasse 5, 69126 Heidelberg, Germany. ; 1] Translational Lung Research Center Heidelberg (TLRC-H), Member of German Center for Lung Research (DZL), Amalienstrasse 5, 69126 Heidelberg, Germany. [2] Institute of Pathology, University of Heidelberg, Im Neuenheimer Feld 220, 69120 Heidelberg, Germany. ; Institute of Pathology, Jena University Hospital, Friedrich-Schiller-University, 07743 Jena, Germany. ; Institute of Surgical Pathology, University Hospital Zurich, 8091 Zurich, Switzerland. ; Department of Oncology, University of Ulsan College of Medicine, Asan Medical Center, 88, Olympic-ro 43-gil, Songpa-gu, Seoul 138-736, Korea. ; Department of Thoracic and Cardiovascular Surgery, University of Ulsan College of Medicine, Asan Medical Center, 88, Olympic-ro 43-gil, Songpa-gu, Seoul 138-736, Korea. ; Thoracic Program, Vanderbilt-Ingram Cancer Center PRB 640, 2220 Pierce Avenue, Nashville, Tennessee 37232, USA. ; University Hospital of Pulmonology, Clinical Center of Serbia, Medical School, University of Belgrade, 11000 Belgrade, Serbia. ; Department of Surgery, St. Vincent's Hospital, Peter MacCallum Cancer Centre, 3065 Melbourne, Victoria, Australia. ; Department of Pathology, St. Vincent's Hospital, Peter MacCallum Cancer Centre, 3065 Melbourne, Victoria, Australia. ; Department of Haematology and Medical Oncology, Peter MacCallum Cancer Centre, 3065 Melbourne, Victoria, Australia. ; Asklepios Biobank fur Lungenerkrankungen, Comprehensive Pneumology Center Munich, Member of the German Center for Lung Research (DZL), Asklepios Fachkliniken Munchen-Gauting 82131, Germany. ; Laboratory of Oncology, IRCCS Casa Sollievo della Sofferenza, Viale Cappuccini, 71013 San Giovanni, Rotondo, Italy. ; Roy Castle Lung Cancer Research Programme, Department of Molecular and Clinical Cancer Medicine, Institute of Translational Medicine, The University of Liverpool Cancer Research Centre, 200 London Road, L69 3GA Liverpool, UK. ; University of Zagreb, School of Medicine, Department for Respiratory Diseases Jordanovac, University Hospital Center Zagreb, 10000 Zagreb, Croatia. ; Laboratory for Translational Medicine, Rudjer Boskovic Institute, 10000 Zagreb, Croatia. ; Charite Comprehensive Cancer Center, Charite Campus Mitte, 10115 Berlin, Germany. ; Tumor Genomics Unit, Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS - Istituto Nazionale Tumori, Via Venezian 1, 20133 Milan, Italy. ; Thoracic Surgery Unit, Department of Surgery, Fondazione IRCCS Istituto Nazionale Tumori, 20133 Milan, Italy. ; 1] Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, N-0424 Oslo, Norway. [2] Department of Oncology, Norwegian Radium Hospital, Oslo University Hospital, N-0310 Oslo, Norway. ; Department of Pathology, Norwegian Radium Hospital, Oslo University Hospital, N-0310 Oslo, Norway. ; Department of Pathology, VU University Medical Center, 1007 MB Amsterdam, The Netherlands. ; 1] West German Cancer Center, Department of Medical Oncology, University Hospital Essen, 45147 Essen, Germany. [2] German Cancer Consortium (DKTK), 69120 Heidelberg, Germany. ; Departments of Immunology, Genetics and Pathology, and Medical Sciences, Respiratory, Allergy and Sleep Research, Uppsala University, 75185 Uppsala, Sweden. ; Genes and Cancer Group, Cancer Epigenetics and Biology Program (PEBC), Bellvitge Biomedical Research Institute (IDIBELL), 08908 Hospitalet de Llobregat, Barcelona, Spain. ; 1] Department of Clinical Science, Center for Cancer Biomarkers, University of Bergen, N-5058 Bergen, Norway. [2] Department of Gynecology and Obstetrics, Haukeland University Hospital, N-5058 Bergen, Norway. ; Computing Center, University of Cologne, 50931 Cologne, Germany. ; 1] Computing Center, University of Cologne, 50931 Cologne, Germany. [2] Department of Informatics, University of Cologne, 50931 Cologne, Germany. ; Institute of Legal Medicine, University of Cologne, 50823 Cologne, Germany. ; Gastrointestinal Cancer Group Cologne, Center of Integrated Oncology Cologne-Bonn, Department I for Internal Medicine, University Hospital of Cologne, 50937 Cologne, Germany. ; 1] Department I of Internal Medicine, Center of Integrated Oncology Cologne-Bonn, University Hospital Cologne, 50937 Cologne, Germany. [2] Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, 50931 Cologne, Germany. ; Computational Molecular Biology Group, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany. ; Department of Pathology and Molecular Diagnostics, Aichi Cancer Center, 464-8681 Nagoya, Japan. ; Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York 10065, USA. ; 1] Cologne Center for Genomics (CCG), University of Cologne, 50931 Cologne, Germany. [2] Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, 50931 Cologne, Germany. [3] Center for Molecular Medicine Cologne (CMMC), University of Cologne, 50931 Cologne, Germany. ; Department of Pathology, CHU Grenoble INSERM U823, University Joseph Fourier, Institute Albert Bonniot 38043, CS10217 Grenoble, France. ; 1] Department of Translational Genomics, Center of Integrated Oncology Cologne-Bonn, Medical Faculty, University of Cologne, 50931 Cologne, Germany. [2] Center for Molecular Medicine Cologne (CMMC), University of Cologne, 50931 Cologne, Germany. ; 1] Department of Translational Genomics, Center of Integrated Oncology Cologne-Bonn, Medical Faculty, University of Cologne, 50931 Cologne, Germany. [2] Department of Pathology, University Hospital Cologne, 50937 Cologne, Germany.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/26168399" target="_blank"〉PubMed〈/a〉

Description: The ground-based microwave sounding radiometers installed at 9 weather stations of Korea Meteorological Administration alongside with the wind profilers have been operated for more than 4 years. Here we introduce a process to assess the characteristics of the instrument calibration by comparing the measured brightness temperature (Tb) with the theoretical reference data, which are prepared by the radiative transfer simulation with the temperature and humidity profiles from the numerical weather prediction model. Based on the three years of data, from 2010 to 2012, we were able to characterize the effects of the absolute calibration, the thick clouds, and the frequency calibration to the quality of the measured Tb. When the three effects are properly considered, including the frequency adjustment which is estimated using the simulated Tb, the measured and simulated Tb show an excellent agreement. The regression coefficients are better than 0.97 along with the bias value of better than 0.5 K. However, the variability given as the SD of difference between the measured and simulated Tb, show a relatively large value at the lower observation frequencies, as large as 2.6 K at the 51.28 GHz channel, while they improve with the increasing frequency.

Description: Elevated levels of formaldehyde (HCHO) along the ship corridors have been observed by satellite sensors, such as ESA/ERS-2 GOME (Global Ozone Monitoring Experiment), and were also simulated by global 3-D chemistry-transport models. In this study, three likely sources of the elevated HCHO levels in the ship plumes as well as their contributions to the elevated HCHO levels (budget) were investigated using a newly-developed ship-plume photochemical/dynamic model: (1) primary HCHO emission from ships; (2) secondary HCHO production via the atmospheric oxidation of non-methane volatile organic compounds (NMVOCs) emitted from ships; and (3) atmospheric oxidation of CH4 within the ship plumes. For this ship-plume modelling study, the ITCT 2K2 (Intercontinental Transport and Chemical Transformation 2002) ship-plume experiment, which was carried out about 100 km off the coast of California on 8 May 2002 (11:00 local standard time), was chosen as a base study case because it is the best defined in terms of (1) meteorological data, (2) in-plume chemical composition, and (3) background chemical composition. From multiple ship-plume model simulations for the ITCT 2K2 ship-plume experiment case, CH4 oxidation by elevated levels of in-plume OH radicals was found to be the main factor responsible for the elevated levels of HCHO in the ITCT 2K2 ship-plume. More than ~88% of the HCHO for the ITCT 2K2 ship-plume is produced by this atmospheric chemical process, except in the areas close to the ship stacks where the main source of the elevated HCHO levels would be primary HCHO from the ships (due to the deactivation of CH4 oxidation from the depletion of in-plume OH radicals). Because of active CH4 oxidation by OH radicals, the instantaneous chemical lifetime of CH4 (τCH4) decreased to ~0.45 yr inside the ship plume, which is in contrast to τCH4 of ~1.1 yr in the background (up to ~41% decrease) for the ITCT 2K2 ship-plume case. A variety of likely ship-plume situations at three different latitudinal locations within the global ship corridors was also studied to determine the enhancements in the HCHO levels in the marine boundary layer (MBL) influenced by ship emissions. It was found that the ship-plume HCHO levels could be 19.9–424.9 pptv higher than the background HCHO levels depending on the latitudinal locations of the ship plumes (i.e., intensity of solar radiation and temperature), MBL stability and NOx emission rates. On the other hand, NMVOC emissions from ships were not found to be a primary source of photochemical HCHO production inside ship plumes due to their rapid and individual dilution. However, the diluted NMVOCs would contribute to the HCHO productions in the background air.

Description: For a case study of Typhoon Ewiniar performed with a mesoscale model, we compare stratospheric gravity wave (GW) momentum flux determined from temperature variances by applying GW polarization relations and by assuming upward propagating waves, with GW momentum flux calculated from model winds which is considered as a reference. The temperature-based momentum-flux profile exhibits positive biases relative to the reference, which fluctuate significantly with altitude. The vertically-averaged magnitude of the positive biases is about 14% of the reference momentum flux. We found that this deviation from the reference stems from the interference between upward and downward propagating waves. The downward propagating GWs are due mainly to partial reflections of upward propagating waves at altitudes where the background wind and stability change with height. When the upward and downward propagating waves are decomposed and their momentum fluxes are calculated separately from temperature perturbations, the fraction of the momentum flux arising from the downward propagating waves is about 4.5–8.2% of that from the upward propagating waves. The net momentum flux of upward and downward propagating GWs agrees well with the reference from the model wind perturbations. The implications of this study for the GW momentum-flux observations from satellites are discussed.

Description: The momentum forcing by equatorial waves to the QBO is estimated using recent reanalyses. Based on the estimation using the conventional pressure level datasets, the forcing by the Kelvin waves (3–9 m s−1 month−1) dominates the net forcing by all equatorial wave modes in the easterly-to-westerly transition phase at 30 hPa (3–11 m s−1 month−1). In the opposite phase, the net forcing by equatorial wave modes is small (1–5 m s−1 month−1). By comparing the results with those from the native model-level dataset of the ERA-Interim reanalysis, it is suggested that the use of conventional-level data causes the Kelvin wave forcing to be underestimated by 2–4 m s−1 month−1. The momentum forcing by mesoscale gravity waves, which are unresolved in the reanalyses, is deduced from the residual of the zonal wind tendency equation. In the easterly-to-westerly phase at 30 hPa, the mesoscale gravity wave forcing is found to be smaller than the resolved wave forcing, whereas the gravity wave forcing dominates over the resolved wave forcing in the opposite phase. Finally, we discuss the uncertainties in the wave forcing estimates using the reanalyses.

Description: For a case study of Typhoon Ewiniar performed with a mesoscale model, we compare stratospheric gravity wave (GW) momentum flux determined from temperature variances by applying GW polarization relations and by assuming upward propagating waves with GW momentum flux calculated from model winds, which is considered as a reference. The temperature-based momentum-flux profile exhibits positive biases which fluctuate with altitude and have peak values of 17–39% at 20–40 km. We found that this deviation stems from the interference between upward and downward propagating waves. The downward propagating GWs are due mainly to partial reflections of upward propagating waves at altitudes where the background wind and stability change with height. When the upward and downward propagating waves are decomposed and their momentum fluxes are calculated separately from temperature perturbations, the fraction of the momentum flux arising from the downward propagating waves is about 4.5–8.2%. The net momentum flux of upward and downward propagating GWs agrees well with the reference from the model wind perturbations. Global distributions of GW momentum flux can be deduced from satellite measurements of temperatures also employing GW polarization relations but using different analysis methods. The implications of this study for the GW momentum-flux observations from satellites are discussed.

Description: An idealized baroclinic instability case is simulated using a ~ 10 km resolution global model to investigate the characteristics of gravity waves (GWs) generated in the baroclinic life cycle. Three groups of GWs (W1–W3) appear around the high-latitude surface trough at the mature stage of the baroclinic wave. They have horizontal and vertical wavelengths of 40–400 and 2.9–9.8 km, respectively, in the upper troposphere. The two-dimensional phase-velocity spectrum of the waves is arc-shaped with a peak at 17 m s−1 eastward, which is difficult for the waves to propagate upward through the tropospheric westerly jet. At the breaking stage of the baroclinic wave, a midlatitude surface low is isolated from the higher-latitude trough, and two groups of quasi-stationary GWs (W4 and W5) appear near the surface low. These waves have horizontal and vertical wavelengths of 60–400 and 4.9–14 km, respectively, and are able to propagate vertically for long distances. The generation mechanism of the simulated GWs is discussed.

Description: Charging and coagulation influence one another and impact the particle charge and size distributions in the atmosphere. However, few investigations to date have focused on the coagulation kinetics of atmospheric particles accumulating charge. This study presents three approaches to include mutual effects of charging and coagulation on the microphysical evolution of atmospheric particles such as radioactive particles. The first approach employs ion balance, charge balance, and a bivariate population balance model (PBM) to comprehensively calculate both charge accumulation and coagulation rates of particles. The second approach involves a much simpler description of charging, and uses a monovariate PBM and subsequent effects of charge on particle coagulation. The third approach is further simplified assuming that particles instantaneously reach their steady-state charge distributions. It is found that compared to the other two approaches, the first approach can accurately predict time-dependent changes in the size and charge distributions of particles over a wide size range covering from the free molecule to continuum regimes. The other two approaches can reliably predict both charge accumulation and coagulation rates for particles larger than about 40 nm and atmospherically relevant conditions. These approaches are applied to investigate coagulation kinetics of particles accumulating charge in a radioactive neutralizer, the urban atmosphere, and a radioactive plume. Limitations of the approaches are discussed.