暴雨類型 的英文怎麼說

中文拼音 [bàoyǔlèixíng]
暴雨類型 英文
storm pattern
  • 暴 : Ⅰ形容詞1 （突然而且猛烈） sudden and violent 2 （兇狠; 殘酷） harsh and tyrannical; cruel; fierce...
  • 雨 : 雨名詞（從雲層中降向地面的水） rain
  • 類 : Ⅰ名1 （許多相似或相同的事物的綜合; 種類） class; category; kind; type 2 （姓氏） a surname Ⅱ動詞...
  • 暴雨 : torrential rain; rainstorm; hard rain; intense fall; squall; downpour; gush暴雨放大 storm maximiz...
  • 類型 : type; mold; form; cut類型論 theory of types; 類型語句 [計算機] type statements
  1. The initial state of the consolidated specimens can be classified into dilative and contractive in the light of the soil state relative to the critical state line. the failure mechanisms of both dilative and contractive soils under the penetration of rainfall are analyzed

    根據斜坡土體狀態在臨界狀態線的相對位置將土體分為剪脹和剪縮兩種類型，並對這兩種土體在暴雨條件下的破壞機理和破壞過程進行了分析。
  2. 8 disaster factors of soil erosion have been defined : surface material, landform and slope gradient, cover - degree, topographic, 30min rainfall intensity, engineering measure grade of conservation of water - soil, irregular subsidence and volume weight

    確定了土壤水性的8個致災因子: 30而n暴雨強度、地表物質、地形坡度、植被搜蓋度、植被類型、工程水土保持措施等級、容重和非均勻沉降
  3. These works include the cloud system families of the meiyu heavy rainfall and their interactions, the structure, precipitation characteristics and microphysical features of the mesoscale convective complexes ( mcc ), the favorable genesis and evolution settings for mcs, the different environments between mcc and meso - p - scale convective system, the relationship between the tropical water vapor plume ( wvp ) and mcs, and what characteristics of the wvp

    先後分析了梅雨暴雨系統的雲系成員及其相互作用；中尺度對流復合體（ mcc ）的結構、降雨特徵、微物理特徵及其形成和發展的有利環境條件；不同類型中尺度對流系統（ mcs ）形成與發展的環境條件差異；熱帶水汽羽和暴雨雲團的關系，水汽羽的動力和熱力特徵。
  4. In this paper we studied the textural features extraction, remote sensing images classification and bp neural network techniques and their applications in the meteorological problems such as recognition of the cloud cluster feature, cloud - drift wind retrieval and heavy rain process analysis etc. to the question of the low precise recognition of satellite images by using spectral features, the proposed approach assumes to perform a multiple analysis based on an advisable decision - making model by first developing a mixed pixel model which was based on the textural features of images, and then improving the recognition intelligence

    本文對模式識別領域中的圖像紋理特徵提取、遙感圖像分類、 bp神經網路與紋理特徵組合分類等方法，以及它們在雲團屬性識別、雲跡風反演和暴雨過程分析等氣象問題中的應用作了研究。針對過去利用圖像光譜亮度特徵進行識別分析氣象衛星圖像準確度不高的問題，本文提出了發展混合像元的分解模型，以圖像的紋理特徵為基礎，提高圖像識別的智能水平，以實現在分析決策模型的支持下，快速準確的復合分析的解決方案。
  5. By examining on the rainstorm process happened during the period of july 4th - 5, 2003, the rationality of using textural feature as the whole decision - making model ' s foundation was successfully testified. furthermore, the improved cloud - drift wind retrieval t echnique which based on this decision - making model also showed a remarkable performance in analyzing a meso - scale weather system

    通過對2003年7月4 ? 5日暴雨過程的試驗分析發現，使用紋理特徵作為整個分析決策模型的基礎是十分合理的，另外改進的基於紋理分類的雲跡風反演技術，由於精度的提高，使診斷水平有了很大的改善。
  6. The assimilation experimentation results indicate that after assimilating radar wind field of small spatial scale, mesoscale and small - scale precipitation prediction can be improved and mesoscale and small - scale information which ca n ' t appear by tradition datum can be gained, which is valuable to analyze the mesoscale and small - scale system structure ; the effect assimilating radar humidity field is n ' t obvious, which is perhaps correlation with precipitation types and assimilating time. the results also show that adding radar humidity field to initial condition at initial time can supply the gap of the regular data in reflecting the mesoscale and small - scale systems, strengthen the humidity in the initial field, and eventually help to improve precipitation. the experiment of assimilating radar wind field and radar humility field at the same time shows that vapor transportation and local vapor divergence play more significant role in causing excessively heavy rain than only high wet center

    同化試驗結果表明：同化空間解析度很高的雷達風場后，能改善中小尺度降水的預報效果，並且能夠得到常規觀測資料所不能得到的中小尺度信息，對分析中小尺度系統結構具有重要意義；同化雷達濕度場效果不明顯，可能與降水類型和同化時刻有關；而直接在初始時刻加入雷達濕度場，補充了常規資料在反映中小尺度系統方面的不足，增強了初始場中的水汽，有利於降水量的增加；同時同化雷達風場和雷達濕度場的試驗表明，水汽的輸送和局地的水汽輻合對于產生特大暴雨的貢獻遠大於僅有高濕中心的貢獻。
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