著者
下條 太貴 廣瀬 等 Shimojo Taiki Hirose Hitoshi
出版者
琉球大学教育学部附属教育実践総合センター
雑誌
琉球大学教育学部教育実践総合センター紀要 (ISSN:13466038)
巻号頁・発行日
no.22, pp.117-138, 2015

本研究は,児童の規範意識の発達について,学校・家庭・地域での活動が規範意識に及ぼす影響を明らかにすることを目的とした。調査では,小学生5ー6年生を対象とし,規範についてはTurielの領域特殊理論に基づき,規範を「道徳」「社会的慣習」「個人」の3領域に分けて詳細に検討した。下條・廣瀬(2015) の結果に基づき,その結果を実践的な場面において検討するため,家庭や地域が関わる,小学校における行事(運動会)を取り上げた。そして,家庭や学校,地域での活動の影響により,児童の規範意識の高まりの結果としての規範行動が行事(運動会)の前後でどのように変化するかを明らかにし,小学校における行事(運動会(5学年については組み体操, 6学年についてはエイサー))に関わる学校や家庭,地域での活動が規範行動に与える効果を検討し,明らかにした。
著者
HIROSE Hitoshi SHIGE Shoichi YAMAMOTO Munehisa K. HIGUCHI Atsushi
出版者
Meteorological Society of Japan
雑誌
気象集誌. 第2輯 (ISSN:00261165)
巻号頁・発行日
pp.2019-040, (Released:2019-03-15)
被引用文献数
23

We introduce a novel rainfall estimation algorithm with a random-forest machine-learning method only from Infrared (IR) observations. As training data, we use nine-band brightness temperature (BT) observations obtained from IR radiometers on the third-generation geostationary meteorological satellite (GEO) Himawari-8 and precipitation radar observations from the Global Precipitation Measurement core observatory. The Himawari-8 Rainfall estimation Algorithm (HRA) enables us to estimate rain rate with high spatial and temporal resolution (i.e., 0.04° every 10 min), covering the entire Himawari-8 observation area (i.e., 85°E–155°W, 60°S–60°N) based solely on satellite observations. We conducted a case analysis of the Kanto–Tohoku heavy rainfall event to compare rainfall estimation results of HRA and the near-real-time version of the Global Satellite Mapping of Precipitation (GSMaP_NRT), which combines global rainfall estimation products with microwave and IR BT observations obtained from satellites. In this case, HRA could estimate heavy rainfall from warm-type precipitating clouds, although GSMaP_NRT could not estimate heavy rainfall when the microwave satellites were unavailable. Further, a statistical analysis showed that the warm-type heavy rain seen in the Asian monsoon region occurred frequently when the BT differences between the 6.9-μm and 7.3-μm of water vapor (WV) bands (ΔT6.9–7.3) were small. Himawari-8 is the first GEO to include the 6.9-μm band which is sensitive to middle-to-upper tropospheric WV. An analysis for the weighting functions of the WV multibands revealed that ΔT6.9–7.3 became small as WV amount in the middle-to-upper troposphere was small and there were optically thick cloud with the cloud top near the middle troposphere. Statistical analyses during boreal summer (August and September 2015 and July 2016) and boreal winter (December 2015 and January and February 2016) indicate that HRA has higher estimation accuracy for heavy rain from warm-type precipitating clouds than a conventional rain estimation method based on only one IR band.