Озоновый слой и погодные аномалии осени 2013 г. : аномально холодный и мокрый сентябрь в Восточной Европе; наводнение на Амуре; природные пожары в Австралии; аномально теплый ноябрь в России
Bibliographic record
Abstract
Monitoring of natural anomalies in real-time mode and an explanation of observed phenomena are an important scientific and social problem. I compare world meteorological information (from official and public Internet sources) with data derived from the Canadian Brewer network (open access information from ozonesondes of ARQX & Canadian Upper Air Network (Select and Ultraviolet Research and Environment Canada's World Wide Web Site. Green LaneTM. Web. ). As a result, I explain the origin of weather anomalies based on Earth Degassing Theory and Degassing Level Conception. From that point of view, the main cause of weather (climate) anomalies is total ozone fluctuations in atmosphere. These fluctuations are caused by the emission of the deep, ozone-depleting gases (hydrogen and methane) and variations of the geomagnetic field, which increase the concentration of ozone. positive ozone anomalies cool the troposphere and form anti-cyclones (dry, heavy and slow moving air masses). negative anomalies warm up the air and form cyclonic masses with law pressure. closest anticyclones could move to that area bringing with them the anomalous temperatures, sometimes very high and sometimes very law. From this perspective, in this article I have explained the anomalous September weather in and Eastern Europe, the catastrophic flood in Amur River region, wildfires in Australia in October and a hurricane in the Chukotka region in early November. weather (climate) anomaly; ozone anomalies; ozone layer; deep degassing; hydrogen; anomalous September weather in and Eastern Europe; catastrophic flood in Amur River Region; wildfires in Australia; hurricane in Chukotka Region 2013 China–Russia Floods. Wikipedia, the Free Encyclopedia. Wikimedia Foundation, Inc., Sept. 2013. Web. . (In Russian). Australia Has Declared a State of Emergency Because of the Unprecedented Forest Fires Threaten to the East of the Country. NEWSru.com. In the World. N.p., 20 Oct. 2013. Web. . (In Russian). Hydrometeorological Centre of The Main Weather and Climatic Features in September 2013 in the Northern Hemisphere. Hydrometeorological Centre of Federal Service for Hydrometeorology and Environmental Monitoring, Sep. 2013. Web. .(In Russian). Liu X., Bhartia P.K., Chance K, Froidevaux L, Spurr R.J.D., Kurosu T.P. Validation of Monitoring Instrument (OMI) Profiles and Stratospheric Columns with Microwave Limb Sounder (MLS) Measurements, Atmos. Chem. Phys. 10 (2010): 2539–2549. Liu X., Bhartia P.K., Chance K., Spurr R.J.D., Kurosu T.P. Ozone Profile Retrievals from the Monitoring Instrument. Atmos. Chem. Phys. 10 (2010): 2521–2537. Lovejoy S., Tuck A.F., Hovde S.J., Schertzer D. Do Stable Atmospheric Layers Exist?. Geophys. Res. Lett. 35 (2008): L01802. DOI: 10.1029/2007GL032122. Maduro R. Gaping Holes Open up in the Depletion Theory. Executive Intelligence Review 18.16 (1991): 15–31. Maduro R. Scientific Evidence Proves Depletion Theory False. Ecology: Myths & Frauds. Argentinean Foundation for a Scientific Ecology, English Version. FAEC, n.d. Web. . Nikolaeva T. Hurricane Raging In Kamchatka and Chukotka. Free Press. Autonomous Nonprofit Organization “InPress”, 7 Nov. 2013. Web. . (In Russian). On Weather Maps, Asian Anticyclone Was Disappeared. Gismeteo News. N.p., 29 Sep. 2013. Web. .(In Russian). Select Maps. and Ultraviolet Research and Monitoring. Environment Canada's World Wide Web Site. Green LaneTM, Web. . Syvorotkin V.L. Degassing and Global Disasters. Moscow: Geoinformmark Publisher, 2002. 250 p. (In Russian). Syvorotkin V.L. Deep Degassing of the Earth and Geo-Ecological Problems in Frontier Areas of Russia. Electronic Scientific Edition Almanac Space and Time 3.1 (2013). PDF-file. . (In Russian). Syvorotkin V.L. Deep Degassing, Layer and Weather Anomalies in Northern Hemisphere in Summer 2013: Heat in May and Cold in July in Central Russia, Floods in June and Heat in July in Europe, Heat in Greenland. Space and Time 3 (2013): 163–171. (In Russian). Syvorotkin V.L. Deep Degassing, Layer and Wildfires in European Russia in Summer 2010. Space and Time 2 (2010): 175–182. (In Russian). Syvorotkin V.L. Hydrogen Degassing of the Earth: Natural Disasters and the Biosphere. Man and the Geosphere. Ed. I.V. Florinsky. New York: Nova Science Publishers, 2010, pp. 307–347. The Air Temperature in the Capital Is Breaking All Records. Gismeteo News. N.p., 6 Nov. 2013. Web. .(In Russian). The Flood Chronicle: How It Was. First Channel. Open Joint Stock Company “First Channel”, Closed Joint Stock Company “National Media Group”, 29 Sep. 2013. Web. . (In Russian). Vyskrebentseva E., Glebova M., Ushakov I., Komarov A. Moscow Is Supposed to 40 Rainy Days. TV Center. OJSC “TV Tsentr”, 29 Sep. 2013. Web. . (In Russian). Syvorotkin, V. L. Ozone Layer and Weather Anomalies in the Fall of 2013: Anomalously Cold and Wet September in Eastern Europe, a Flood on Amur River; Wildfires in Australia; Anomalously Warm November in Russia. Space and Time 4 (2013): 201–207. (In Russian).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 0.015 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".