博碩士論文 996201020 完整後設資料紀錄

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DC.contributor大氣物理研究所zh_TW
DC.creator張楚珺zh_TW
DC.creatorChu-Chun Changen_US
dc.date.accessioned2013-3-13T07:39:07Z
dc.date.available2013-3-13T07:39:07Z
dc.date.issued2013
dc.identifier.urihttp://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=996201020
dc.contributor.department大氣物理研究所zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract在大氣化學模擬中,如何定量描述化學物質之地表通量乃一重要的課題。過去許多研究藉由同化化學物之觀測估計其未知的地表通量。然而這些研究大多使用全球模式或額外的大氣傳輸模式。為進一步探討於區域模式中,同化大氣化學物質與地表通量估計之影響,本研究使用區域大氣化學模式WRFChemT以及局地系集轉換卡爾曼濾波器(LETKF)進行OSSE實驗。 OSSE實驗設定上,以總排放量5.3×108 g/s積分之長時間模擬作為真實場,並分為(1)定量排放與(2)具有日夜變化之排放兩種情境假設。同化系統分別由大氣及化學同化子系統耦合而成,並分別同化氣象探空資料與化學複合物混合比。 研究結果顯示,在定量排放情境下,同化化學場觀測可成功估計無直接觀測資訊之地表通量,並改善化學場的分佈。然而在具日夜變化排放的情境下,受到模式誤差參數的影響,會使地表通量估計變得更加困難。為減小模式誤差對地表通量估計之影響,我們藉由模式化學場濃度變化資訊,反推地表通量隨時間變化之趨勢。研究結果顯示,嵌入地表通量時間變化之趨勢,可有效改善地表通量估計,並間接降低化學場誤差。我們也發現在日夜變化的情境假設下,系統對於初始場較敏感。因此,對於估計具日夜變化之排放源,初始系集化學場及地表通量的選取會是重要的關鍵。zh_TW
dc.description.abstractTo constrain the sources and sinks of the chemical compounds of interest at surface from limited observations, a chemical assimilation with the Local Ensemble Transform Kalman Filter (LETKF) has been developed and implemented to the WRF-Chem model. In this study, a two-tier method is used to update the meteorological and chemical states updated separately and simultaneously. To investigate the capability of the WRF-Chem/LETKF system, experiments are carried out under an observation simulation system experiments (OSSE) framework. Two scenarios of localized emissions are tested: constant emission and emission with diurnal cycle. Results indicate that the system can successfully provide reasonable estimate for the constant forcing case and improve the distribution of the chemicals. Strategies need to be applied for retrieving the time-varying emission.en_US
DC.subject系集轉換卡爾曼濾波器zh_TW
DC.subject變數局地化zh_TW
DC.subjectLETKFen_US
DC.subjectVariable localizationen_US
DC.title利用系集資料同化系統估算區域大氣化學耦合模式中trace物種之排放與吸收:以CO2為例zh_TW
dc.language.isozh-TWzh-TW
DC.titleConstraining sources and sinks for trace species under an ensemble-based data assimilation framework with a regional chemical transport model: CO2 as an exampleen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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