博碩士論文 101621024 詳細資訊




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姓名 林梓舜(Tzu-shun Lin)  查詢紙本館藏   畢業系所 大氣物理研究所
論文名稱 地表水文循環過程與大氣耦合作用對土壤溼度以及氣象模擬的影響
(Effects of land surface hydrological processes on soil moisture and coupled impact on the meteorological characteristics)
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摘要(中) 隨著科技及電腦運算資源快速的進展,大氣及水文模式已能夠模擬更高解析度的現象,更突顯出地表特性的重要性如:地形、土地利用形態、植被覆蓋率及土壤質地等,地表可藉由能量及水文的循環和儲存影響短期天氣的事件及長期氣候的變異。土壤中的水分改變地表能量的收支,並影響著數值天氣預報的表現,土壤濕度與地表水文過程息息相關,並受到地形、土地利用及土壤質地空間異質性的分佈而有所改變。因此在時間及空間上對於土壤濕度的觀測及模擬,具有很高的挑戰性。此篇研究主要目的,在於瞭解地表水文過程對土壤溼度及大氣模擬的影響,並改善模式土壤初始化、土壤形態及次網格解析度的物理水文過程。
本研究使用WRF氣象模式,探討次網格水文過程及土壤濕度與大氣間的交互作用,並主要對於2013年8月29日至9月11日的個案進行討論。首先為了解並改善土壤初始場, 使用全球地表同化系統(Global Land Data Assimilation System, GLDAS) 0.25度的土壤溫度及土壤濕度來取代原先提供自再分析場的資料做為初始值。GLDAS相較於再分析場的資料提供了較乾的土濕,也與觀測值較為接近,透過近地表潛熱與可感熱的重新分配,進而影響溫度變化、邊界層、低層雲的發展,並調節了區域風場的結構。模擬的土壤濕度空間分佈也與給定的土壤質地形態的相關土壤參數有關,因此進一步針對台灣土壤質地分類進行更新,藉由野外實地的調查資料,呈現出更為接近真實的土壤形態空間分佈,結果顯示土壤濕度在空間上因土壤粒徑大小及水分傳導速率的不同而有所變化。
另外,目前WRF-Noah模式的架構下,有以下幾項缺點:(1)土壤水分只考慮了垂直的輸送作用;(2)地表逕流只考量了超入滲過程,缺乏過飽和逕流的演算機制、地表積水的再入滲過程,並且未考量飽和地下水的土壤結構。對於台灣陡峭的地形而言,大部份降雨沿山區流入平地,在高解析度的模擬下,由地形產生水平方向水分的交換,在局部水文收支平衡中,是不可忽視的。因此,我們建置WRF大氣-地表-水文雙向耦合模式系統,以改進模式次網格解析度的逕流過程,以及近地表水文過程。由於側向水的流動,土壤水分在山區減少,平地則有所增加,並進而改變地表與低層大氣間的反饋作用。本研究闡明地表水文過程和土壤濕度的重要性及其對大氣的交互作用。
摘要(英) Heat and water storages of soil conditions memorize the signals of atmospheric information including short-term weather events and long-term climate anomalies. The amount of soil water is critical in determining the performance of numerical weather predictions, and affects the surface energy budgets. The spatial patterns of soil moisture are not only the results of land surface hydrological processes including precipitation, evapotranspiration, groundwater, and surface and subsurface runoff processes, but also are affected by the heterogeneity of topography, soil properties, and land cover characteristics as well.
In order to present the effects of land surface hydrological processes on soil moisture and its feedback on the meteorological characteristics, the two-way coupled WRF-Hydro modeling system is applied from 29 August to 11 September 2013. Due to the topography-induced lateral transport of overland flow and saturated subsurface flow, the results from WRF-Hydro model show the increase of soil moisture content in the low-lying areas, while the soil moisture content is reduced over the mountainous regions, and consequently inducing hydrometeorological responses. In addition, the better initial soil states from Global Land Data Assimilation System (GLDAS) and updated soil textures based on field investigations over the Taiwan areas are used to improve the simulations and explore the effects of the GLDAS analysis on the atmospheric model prediction. The soil initialization from GLDAS products can better reproduce the amplitude of temporal variations with observations. Simulated results reveal the spatial distribution of soil moisture is extremely relevant to the soil properties of soil types prescribed in WRF model and surface water budget is analyzed to understand the physical processes. These results show the improvement and heterogeneity of simulated soil moisture though the better representation of initial soil states, soil physical and hydraulic properties, and sub-grid scale hydrological responses. This study sheds light on the importance of fine-scale hydrological processes on soil moisture and its subsequent impact on the coupling of soil moisture-atmosphere interactions in Taiwan.
關鍵字(中) ★ 地表水文過程
★ 地表模式
★ 土壤濕度
★ 大氣水文耦合
★ 土壤質地
★ 土壤初始化
★ 陸氣交互作用
★ 逕流
★ 地表特性
關鍵字(英) ★ Land surface hydrological processes
★ Land surface model
★ WRF-Hydro modeling system
★ Soil moisture
★ Soil temperature
★ Soil textures
★ Land-Atmosphere interactions
★ Global Land Data Assimilation System (GLDAS
★ Runoff
★ Mosaic
★ Land surface characteristics
論文目次 摘要 i
Abstract iii
致謝 v
Table of Contents vi
List of Tables ix
List of Figures x
Chapter 1 Introductions 1
1.1 Background 1
1.2 Literature reviews 3
1.2.1 Soil initialization and spin-up process 3
1.2.2 Land surface characteristics 6
1.2.3 Land surface hydrological processes 8
1.2.4 Relevant studies in Taiwan 12
1.3 Objectives and novelties 14
1.4 Framework 14
Chapter 2 Methodology and datasets 15
2.1 Datasets 15
2.1.1 GLDAS-1 products 15
2.1.2 Soil textures datasets 17
2.1.3 Observations 19
2.2 Models 19
2.2.1 Atmospheric model - WRF 19
2.2.2 Land surface model – Noah 21
2.2.3 Hydrologic model – WRF-Hydro 24
2.3 Numerical experiment designs 27
2.4 Simulation episodes 27
Chapter 3 Results and Discussions 29
3.1 Overall model simulations 29
3.2 Effects of soil moisture initialization process (WRF-GLDAS) 32
3.2.1 Analysis of spatial results 32
3.2.2 Time series comparisons 35
3.2.3 Surface water budgets 36
3.2.4 Diurnal cycle changes 37
3.3 Impact of updated soil textures (WRF-GSoil) 40
3.3.1 Analysis of spatial distributions 40
3.3.2 Time series comparisons 41
3.3.3 Surface water budgets 43
3.4 Effects of hydrologic processes (WRF-GHydro) 44
3.4.1 Analysis of spatial distributions 44
3.4.2 Time series comparison 46
3.4.3 100-meter results 47
Chapter 4 Discussions 49
4.1 Role of soil moisture 49
4.1.1 Scatter plots of daily results 49
4.1.2 Scatter plots of 20 CWB stations 49
4.1.3 Scatter plots of observations at Lien Hua Chih flux tower 50
4.2 Impact of land surface characteristics 51
Chapter 5 Conclusions and future works 54
References 58
Tables 68
Figures 75
參考文獻 蘇倫平、吳家蓁、吳竹政、湯桂香、郭鴻裕,台灣山地土壤調查,行政院農業委員會農業試驗所主管農業發展計畫99年度計畫結束報告表,西元2010年。
宋馥淇,「地表特性對台灣及鄰近地區氣候影響之模擬研究」,國立中央大學,碩士論文,西元2006年。
曹嘉宏,「台灣土地利用型態對MM5模擬局部環流之影響」,國立中央大學,碩士論文,西元2007年。
許志禎,「台灣土地利用型態對於局部環流與降雨模擬之影響」,國立中央大學,碩士論文,西元2009年。
Cai, X., Z.-L. Yang, C. H. David, G.-Y. Niu, and M. Rodell, 2014: Hydrological evaluation of the Noah-MP land surface model for the Mississippi River Basin. J. Geophys. Res., 119(1), 23-38, doi:10.1002/2013JD020792.
Chen, F., K. Mitchell, J. Schaake, Y. Xue, H. Pan, V. Koren, Q. Y. Duan, M. Ek, and A. Betts, 1996: Modeling of land surface evaporation by four schemes and comparison with FIFE observations. J. Geophys. Res., 101(D3), 7251 – 7268, doi:10.1029/95JD02165.
Chen, F., and J. Dudhia, 2001: Coupling an advanced land-surface hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon. Weather Rev., 129, 569–585.
Chen, F., and Coauthors, 2007: Description and evaluation of the characteristics of the NCAR high-resolution data assimilation system. J. Appl. Meteor. Climatol., 46, 694–713, doi:10.1175/JAM2463.1.
Chen, Y. Y., and M. H. Li, 2013: Determining adequate averaging periods and reference coordinates for eddy covariance measurements of surface heat and water vapor fluxes over mountainous terrain. Terr. Atmos. Ocean. Sci., 24, doi:10.3319/TAO.2012.05.02.01(Hy).
Cheng, F. Y., Y. C. Hsu, P. L. Lin, and T. H. Lin, 2013: Investigation of the effects of different land use and land cover patterns on mesoscale meteorological simulations in the Taiwan area. J. Appl. Meteor. Climatol., 52, 570–587.
Cheng, F. Y., S. P. Jian, B. J. Tsuang, and M. C. Yen, 2014: Impact of regional climate changes on variations of meteorological characteristics in Taiwan. Submitted.
Chow, F. K., A. P. Weigel, R. L. Street, M. W. Rotach, and M. Xue, 2006: High-resolution large-eddy simulations of flow in a steep Alpine Valley. Part I: Methodology, verification, and sensitivity experiments. J. Appl. Meteor. Climatol., 45, 63–86.
Cosby, B. J., G. M. Hornberger, R. B. Clapp, and T. R. Ginn, 1984: A statistical exploration of the relationships of soil moisture characteristics to the physical properties of soils. Water Resour. Res., 20, 682–690
Decharme, B., 2007: Influence of runoff parameterization on continental hydrology: Comparison between the Noah and the ISBA land surface models. J. Geophys. Res., 112, D19108, doi:10.1029/2007JD008463.
Decharme, B., C. Ottlé, S. Saux-Picart, N. Boulain, B. Cappelaere, D. Ramier, and M. Zribi, 2009: A new land surface hydrology within the Noah-WRF land-atmosphere mesoscale model applied to semiarid environment: Evaluation over the Dantiandou Kori (Niger). Adv. Meteor., 2009, 731874, doi:10.1155/2009/731874.
Gao, Y., F. Chen, M. Barlage, W. Liu, Y. Ran, H. Li, H. Peng, and M. Ma, 2008: Enhancement of land surface information and its impact on atmospheric modeling in the Heihe River basin, northwest China. J. Geophys. Res., 113, D20S90, doi:10.1029/2008JD010359.
Gochis, D. J., and F. Chen, 2003: Hydrological enhancements to the community Noah land surface model. NCAR Technical Note, NCAR/TN-454+STR, 68 pgs.
Gochis, D. J., W. Yu, and D. N. Yates, 2013: The WRF-Hydro model technical description and user′s guide, version 1.0. NCAR Technical Document, 120 pages. Available online at: http://www.ral.ucar.edu/projects/wrf_hydro/
Hagos, S., L. R Leung, Y. Xue, A. Boone, F. de Sales, N. Neupane, M. Huang, and J.-H. Yoon, 2014: Assessment of uncertainties in the uesponse of the African Monsoon precipitation to land use change simulated by a regional model. Climate Dynamics, doi: 10.1007/s00382-014-2092-x.
Hong, S. B., V. Lakshmi, E. E. Small, F. Chen, M. Tewari, and K. W. Manning, 2009: Effects of vegetation and soil moisture on the simulated land surface processes from the coupled WRF/Noah model. J. Geophys. Res., 114, D18118, doi:10.1029/2008JD011249.
Hong, S.-Y., J. Dudhia, and S.-H. Chen, 2004: A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon. Wea. Rev., 132, 103–120.
Hong, S.-Y., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 2318–2341.
Hung, Y.-C., J.-S. Hong, C.-L. Tsay, M. Barlage, F. Chen, 2014: Evaluation of the High Resolution Land Data Assimilation System. Atmospheric Sciences, 42(1), 29-47. (in Chinese)
Husain, S. Z., S. Bélair, and S. Leroyer, 2014: Influence of soil moisture on urban microclimate and surface-layer meteorology in Oklahoma City. J. Appl. Meteor. Climatol., 53, 83–98.
Iacono, M. J., J. S. Delamere, E. J. Mlawer, M. W. Shephard, S. A. Clough, and W. D. Collins, 2008: Radiative forcing by long–lived greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res., 113, D13103.
Jacquemin, B., and J. Noilhan, 1990: Sensitivity study and validation of a land surface parameterization using the HAPEX-MOBILHY data set. Bound.-Layer Meteor., 52, 93–134.
Jiménez, P. A., J. Dudhia, J. F. González-Rouco, J. Navarro, J. P. Montávez, and E. García-Bustamante, 2012: A revised scheme for the WRF surface layer formulation. Mon. Wea. Rev., 140, 898–918.
Kain, J. S., Fritsch, J. M., 1993. Convective parameterization for mesoscale models: The Kain-Fritsch scheme. The representation of cumulus convection in numerical models. Meteorol. Monogr. Ser., Am. Meteorol. Soc., 24, 165-170.
Kain, J. S., 2004: The Kain–Fritsch convective parameterization: An update. J. Appl. Meteor., 43, 170–181.
Kim, Y., and G. Wang, 2007: Impact of initial soil moisture anomalies on subsequent precipitation over North America in the coupled land–atmosphere model CAM3–CLM3. J. Hydrometeor., 8, 513–533.
Koster, R. D., and M. J. Suarez, 2001: Soil moisture memory in climate models. J. Hydrometeor., 2, 558–570.
Koster, R. D., and Coauthors, 2004: Regions of strong coupling between soil moisture and precipitation. Science, 305, 1138–1140, doi:10.1126/science.1100217.
Koster, R. D., and Coauthors, 2006: GLACE: The Global Land–Atmosphere Coupling Experiment. Part I: Overview. J. Hydrometeor., 7,590–610.
Kumar, S. V., and Coauthors, 2006: Land Information System—An interoperable framework for high resolution land surface modeling. Environ. Modell. Software, 21, 1402–1415.
Lai, Y.-S., 2009: The impact of land surface initialization on regional climate in Taiwan. Master’s thesis, National Central University.
LeMone, M. A., F. Chen, J. G. Alfieri, M. Tewari, B. Geerts, Q. Miao, R. L. Grossman, and R. L. Coulter, 2007: Influence of land cover, soil moisture, and terrain on the horizontal distribution of sensible and latent heat fluxes and boundary layer structure in southeast Kansas during IHOP_2002 and CASES-97. J. Hydrometeor., 8, 68–87.
Leng, G., M. Huang, Q. Tang, W. J. Sacks, H. Lei, and L. R. Leung, 2013: Modeling the effects of irrigation on land surface fluxes and states over the conterminous United States: Sensitivity to input data and model parameters. J. Geophys. Res. Atmos., 118, 9789–9803, doi:10.1002/jgrd.50792.
Leung, K.-W., and T.-T. Chen, 1957: Soils of Taiwan. Journal of the Agricultural Association of China New Series, 20, 1-25.
Li, D., E. Bou-Zeid, M. L. Baeck, S. Jessup, and J. A. Smith, 2013a: Modeling land surface processes and heavy rainfall in urban environments: Sensitivity to urban surface representations. J. Hydrometeorol., 14(4), 1098–1118, doi:10.1175/jhm-d-12-0154.1.
Li, D., E. Bou-Zeid, M. Barlage, F. Chen, and J. A. Smith, 2013b: Development and Evaluation of a Mosaic Approach in the WRF-Noah Framework. J. Geophys. Res. Atmos., 118,11,918-11,935, doi: 10.1002/2013JD02065.
Lim, Y. J., J. Hong, and T. Y. Lee, 2012: Spin-up behavior of soil moisture in a land surface model for East Asia. Meteorol. Atmos. Phys., 118, 151–161.
Lin, C.-F., 2013: Update the land surface parameters for Taiwan’s meteorological simulation. Master’s thesis, National Central University.
Liu, D., G. Wang, R. Mei, Z. Yu, and M. Yu, 2014: Impact of initial soil moisture anomalies on climate mean and extremes over Asia. J. Geophys. Res., 119(2), 529-545.
Lo, M.-H., and J. S. Famiglietti, 2011: Precipitation response to land subsurface hydrologic processes in atmospheric general circulation models. J. Geophys. Res., 116, D05107, doi:10.1029/2010JD015134.
Lo, M.-H., and J. S. Famiglietti, 2013: Irrigation in California’s Central Valley strengthens the southwestern U.S. water cycle. Geophys. Res. Lett.,40, 301–306, doi:10.1002/grl.50108.
Mahanama, S. P. P., R. D. Koster, R. H. Reichle, and L. Zubair, 2008: The role of soil moisture initialization in subseasonal and seasonal streamflow predictability: A case study in Sri Lanka. Adv. Water Resour., 31, 1333–1343, doi:10.1016/j.advwatres.2008.06.004.
Mahrt, L., and K. Ek, 1984a: The influence of atmospheric stability on potential evaporation. J. Appl. Meteorol., 23, 222 – 234, doi:10.1175/1520-0450(1984)023<0222:TIOASO>2.0.CO;2.
Mahrt, L., and H. L. Pan, 1984b: A two-layer model of soil hydrology. Boundary Layer Meteorol., 29, 1 – 20, doi:10.1007/BF00119116.
Maxwell, R. M., F. K. Chow, and S. J. Kollet, 2007: The groundwater-land-surface-atmosphere connection: Soil moisture effects on the atmospheric boundary layer in fully-coupled simulations. Adv. Water Resour., 30, 2447–2466.
Maxwell, R. M., J. K. Lundquist, J. D. Mirocha, S. G. Smith, C. S. Woodward, and A. F. B. Tompson, 2011: Development of a coupled groundwater–atmospheric model. Mon. Wea. Rev., 139, 96–116.
Meng, L., and Y. J. Shen, 2014a: On the relationship of soil moisture and extreme temperatures in East China. Earth Interact., 18, 1–20.
Meng, L., D. Long, S. M. Quiring, and Y. J. Shen, 2014b: Statistical analysis of the relationship between spring soil moisture and summer precipitation in East China. Int. J. Climatol., 34(5), 1511-1523, doi:10.1002/joc.3780.
Miller, D. A., and R. A. White, 1998: A conterminous United States multilayer soil characteristics data set for regional climate and hydrology modeling. Earth Interact., 2, 1–26, doi:10.1175/1087-3562(1998)002<0002:CUSMS>2.0.CO;2.
Mitchell, K. E., and Coauthors, 2004: The multi-institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system. J. Geophys. Res., 109, D07S90, doi:10.1029/2003JD003823.
Mitchell, K.E., 2005: The community Noah land-surface model user’s guide, public release version 2.7.1. 26 pages. Available online at http://www.ral.ucar.edu/research/land/technology/lsm.php
Niu, G. Y., Z. L. Yang, R. E. Dickinson, and L. E. Gulden, 2005: A simple TOPMODEL-based runoff parameterization (SIMTOP) for use in global climate models. J. Geophys. Res., 110, D21106, doi:10.1029/2005JD006111.
Niu, G. Y., Z. L. Yang, R. E. Dickinson, L. E. Gulden, and H. Su, 2007: Development of a simple groundwater model for use in climate models and evaluation with Gravity Recovery and Climate Experiment data. J. Geophys. Res., 112, D07103, doi:10.1029/2006JD007522.
Niu, G.-Y., and Coauthors, 2011: The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements. J. Geophys. Res., 116, D12109, doi:10.1029/2010JD015139.
Noilhan, J., and S. Planton, 1989: A simple parameterization of land surface processes for meteorological models. Mon. Wea. Rev., 117, 536–549.
Pan, H. L., and L. Mahrt, 1987: Interaction between soil hydrology and boundary-layer development. Boundary Layer Meteorol., 38, 185 – 202, doi:10.1007/BF00121563.
Qian, Y., M. Huang, B. Yang, and L. K. Berg, 2013: A modeling study of irrigation effects on surface fluxes and land–air–cloud interactions in the southern Great Plains. J. Hydrometeor.,14, 700–721, doi:10.1175/JHM-D-12-0134.1.
Rodell, M., P.R. Houser, U. Jambor, J. Gottschalck, K. Mitchell, C.-J. Meng, K. Arsenault, B. Cosgrove, J. Radakovich, M. Bosilovich, J.K. Entin, J.P. Walker, D. Lohmann, and D. Toll, 2004: The Global Land Data Assimilation System. Bull. Amer. Meteor. Soc., 85(3), 381-394.
Rodell, M., P. R. Houser, A. A. Berg, and J. S. Famiglietti, 2005: Evaluation of 10 methods for initializing a land surface model. J. Hydrometeorol., 6, 146–155, doi:10.1175/JHM414.1.
Schaake, J. C., V. I. Koren, Q. Y. Duan, K. Mitchell, and F. Chen, 1996: A simple water balance model (SWB) for estimating runoff at different spatial and temporal scales. J. Geophys. Res.,101, 7461–7475.
Seneviratne, S. I., and Coauthors, 2006: Soil moisture memory in AGCM simulations: Analysis of Global Land–Atmosphere Coupling Experiment (GLACE) data. J. Hydrometeor., 7, 1090–1112.
Seneviratne S.I., T. Corti, E.L. Davin, M. Hirschi, E. Jaeger, I. Lehner, B. Orlowsky, and A.J. Teuling, 2010: Investigating soil moisture-climate interactions in a changing climate: A review. Earth Sci. Rev., 99, 125–161
Seuffert, G., P. Gross, C. Simmer, and E. Wood, 2002: The influence of hydrologic modelling on the predicted local weather: Two-way coupling of a mesoscale weather prediction model and a land surface hydrologic model. J. Hydrometeor., 3, 505–523.
Shi, X., 2011: Numerical study of initial soil moisture impacts on regional surface climate. Atmospheric and Climate Sciences, 1(4), 172-185, doi: 10.4236/acs.2011.14019.
Strahler, A. N., 1952: Hypsometric (area-altitude) analysis of erosional topology. Geological Society of America Bulletin 63 (11), 1117–1142, doi:10.1130/0016-7606(1952)63[1117:HAAOET]2.0.CO;2
Su, S.-K., 2008: Evaluation simulated hydrological processes of NOAH land surface model applied to Shi-Men reservoir watershed. Master’s thesis, National Central University.
Tian, W., X. Li, G. D. Cheng, X. S. Wang, and B. X. Hu, 2012: Coupling a groundwater model with a land surface model to improve the water and energy cycle simulation. Hydrol. Earth Syst. Sci., 16, 4707–4723.
Trier, S. B., F. Chen, K. W. Manning, M. A. LeMone, and C. A. Davis, 2008: Sensitivity of the PBL and precipitation in 12-day simulations of warm-season convection using different land surface models and soil wetness conditions. Mon. Wea. Rev., 136, 2321–2343.
Vivoni, E. R., K. Tai, and D. J. Gohis, 2009: Effects of the initial soil moisture on rainfall generation and subsequent hydrologic response during the North American monsoon. J. Hydrometeor., 10, 644–664.
Warrach-Sagi, K., V. Wulfmeyer, R. Grasselt, F. Ament, and C. Simmer, 2008: Streamflow simulations reveal the impact of the soil parameterization. Meteor. Z., 17, 751–762, doi:10.1127/0941-2948/2008/0343.
Wood, E. F., and Coauthors, 1998: The project for intercomparison of land-surface parameterization schemes (PILPS) phase-2c Red-Arkansas River Basin experiment—I: experiment description and summary intercomparison. Global and Planetary Change, 19, 115–135.
Wu, Y.-S., 2010: The Impact of Land-Use Change on the Watershed Runoff:Lan-Yang River Catchment as an Example. Master’s thesis, National Central University.
Yang, Y., M. Uddstrom, M. Revell, P. Andrews, H. Oliver, R. Turner, and T. Carey-Smith, 2011a: Numerical simulations of effects of soil moisture and modification by mountains over New Zealand in summer. Mon. Wea. Rev., 139, 494–510.
Yang, Y., M. Uddstrom, M. Duncan, 2011b: Effects of short spin-up periods on soil moisture simulation and the causes over New Zealand. J. Geophys. Res. 116: D24108, doi: 10.1029/2011JD016121.
Yang, Z.-L., R. E. Dickinson, A. Henderson-Sellers, and A. J. Pitman, 1995: Preliminary study of spin-up processes in land surface models with the first stage data of Project for Intercomparison of Land Surface Parameterization Schemes Phase 1(a). J. Geophys. Res., 100, 16,553–16,578, doi:10.1029/95JD01076.
Zhang, J., L. Wu, and W. Dong, 2011: Land–atmosphere coupling and summer climate variability over East Asia. J. Geophys. Res., 116, D05117, doi:10.1029/2010JD014714.
Zhang, C., Y. Wang, A. Lauer, and K. Hamilton, 2012: Configuration and evaluation of the WRF model for the study of Hawaiian regional climate. Mon. Wea. Rev., 140, 3259–3277.
指導教授 鄭芳怡(Fang-yi Cheng) 審核日期 2014-8-28
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