探討地表參數對台灣地區氣象模擬的影響

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姓名

林勤芳(Chin-fang Lin) 查詢紙本館藏

畢業系所

大氣物理研究所

論文名稱

探討地表參數對台灣地區氣象模擬的影響
(Update the land surface parameters for Taiwan’s meteorological simulation)

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摘要(中)

在數值模式中，地表過程主要在處理地表和大氣間的能量交換，目前
WRF 氣象模式在計算此能量的交換過程，主要是透過look-up
table 的方法，
也就是所有的地表參數皆與其相對應的土地利用型態(LU)有關，因此無法正
確反應出台灣地區之複雜地形地貌結構。本篇研究中，更新了台灣地區之
地表參數，包括土地利用型態、地形和粗糙長度(Z0)，並進行WRF 氣象模
擬，探討更新後的地表參數對台灣地區氣象模擬的影響。
更新後的LU 是使用2007 年MODIS 衛星影像資料，相較於WRF 原始
的USGS
(U.S.
Geological
Survey)資料，其將台灣分類為以灌溉地和森林為
主的土地利用形態，MODIS 主要將台灣分類為水田、旱田、都市和森林的
形態，正確的反應出現今的土地利用分布情形。地形資料來自於SRTM
(NASA
Shuttle
Radar
Topographic
Mission)的衛星影像資料。而Z0 為推估之
網格點資料，此資料提供自蔡等人(2010)。蔡等人(2010)將網格點中各種土
地利用所佔百分比，乘上其相對應的Z0。其中的都市以及灌溉地之Z0，為
經由觀測推估而來。
個案選取為2011 年10 月23 日-28 日，此段期間，在高雄附近有觀測到
高汙染事件，另外，在高雄潮寮國中也有密集的IOP 觀測計畫。目前先討
論更新地表參數後的氣象場結果，未來將對於污染和氣象場間的關聯進行
研究‧．模擬結果部份，使用新的土地利用資料在大部份地區會有溫度增加
和風速降低的情況，原因主要來自都市和森林區域的增加‧．更新地形資料
後，由於新的地形在山區的分布較內定值複雜，因此風速在山區有下降的
情形。此外，地形的增減也會直接反映在溫度變化上‧．而更新之後的粗糙
長度比原始模式內定資料約大一個數量級，較大的粗糙長度會增加地表與
大氣間的動量和可感熱通量交換，使溫度的日夜變化較明顯並減低風速。
將以上模擬結果與測站資料比較後也發現，更新地表參數資料對於溫度、
風速以及地表通量的模擬都有良好的修正‧．

摘要(英)

The accurate determination of the surface momentum, heat and moisture fluxes is strongly dependent on the accuracy of the land surface parameters. In this study, the mesoscale meteorological simulation using WRF is performed for the area in Taiwan by using the updated land use (LU) type, terrain height and roughness length (Z0). The updated LU
data were reclassified using the 2007 MODIS satellite image. The new LU data correctly represents Taiwan as mixtures of cropland, urban, and forestlands as well as the other land types. The elevation data is provided from NASA Shuttle Radar Topographic Mission (SRTM) satellite image. The Z0 is recalculated using the arithmetic mean of the fraction of each LU
type and the corresponded Z0.
Several WRF sensitivities are performed using the updated land surface parameters. The simulation using the updated LU data shows higher temperature and lower wind speed than the run using the default setup due to the increasement of the urban and forest areas. The simulation using the SRTM data improves the temperature biases particularly in the mountain area. The newer roughness length data was about an order higher than the default setup and the simulation result shows the enhancement of the temperature diurnal variation and
improves the wind speed.

關鍵字(中)

★ 地表參數
★ 粗糙長度

關鍵字(英)

★ land surface parameters
★ roughness length

論文目次

摘要
........................................................................................................................................................................
i
Abstract .................................................................................................................................... iii
Chapter 1 Introduction ................................................................................................................ 1
Chapter 2 Description of the land surface datasets ..................................................................... 4
2.1 Topographical data ............................................................................................... 4
2.2 LU data ................................................................................................................. 4
2.3 Aerodynamic roughness length data ..................................................................... 6
Chapter 3 Description of the simulation episode ...................................................................... 10
Chapter 4 Model configuration and experimental design ........................................................ 11
Chapter 5 Simulation results ..................................................................................................... 13
5.1 Sensitivity with updated elevation and LU data ................................................. 13
a. Analysis of spatial plot ................................................................................. 13
b. Time series comparison ................................................................................ 14
5.2 Sensitivity with updated Z0 data ........................................................................ 15
a. Analysis of spatial plot ................................................................................. 15
b. Time series comparison ................................................................................ 16
c. Vertical profile plot ....................................................................................... 17
d. Statistical analysis ......................................................................................... 19
Chapter 6 Conclusion and future work ..................................................................................... 20
References ............................................................................................................................... 22

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指導教授

鄭芳怡(Fang-yi Cheng)

審核日期

2013-1-24

推文