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Coupling an Advanced Land Surface-Hydrology Model with the Penn State-NCAR MM5 Modeling System. Part Ⅰ :Model Implementation and Sensitivity. Fei Chen and Jimy Dudhia (April 2001) 報告:陳心穎. 動機. 因為 地表物理過程 嚴重影響邊界層結構〈例如,受到地表 的強迫會引局部中尺度環流〉,也關係著雲和降水過程,
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Coupling an Advanced Land Surface-Hydrology Model with the Penn State-NCAR MM5 Modeling System. PartⅠ :Model Implementation and Sensitivity Fei Chen and Jimy Dudhia (April 2001) 報告:陳心穎
動機 因為地表物理過程嚴重影響邊界層結構〈例如,受到地表 的強迫會引局部中尺度環流〉,也關係著雲和降水過程, 所以研究主要是增加更好的空間及時間解析度和改善PBL 的參數化。然而當中尺度解析度持續提高時,而實際觀測 網的密度無法配合取得小尺度的資料,因此,比較重要的 是先做資料的初始化。再取得地表受自由大氣及邊界層作 用的中尺度結構。 近來,MM5模式及資料同化系統為了即時天氣預報將網格 解析增加到1km了,所以地表作用〈明顯〉會導致局部中 尺度環流,而修正地表模式更加重要。
LSM (The simple land surface model)是概念的 ground heat budget model,Grell et al 1994 將LSM跟MM5 結合,但是與其他的物理過程不相容 1.土壤水分只有方程式的變換,也就是只有季節性的 值而沒有隨模擬而有所改變〈下雨也沒有改變其水分〉 2.缺乏覆雪的預報 3.使用粗糙的陸地解析度 4.沒有植物的蒸發散及逕流過程 p.s逕流─〈雨〉水未被土地吸收而在地表流動 目標 1.修改MM5系統,讓它可以輕鬆的駕馭LSMs系統 2.利用已實行的LSM去改善地表熱通量及邊界層和降水過程 的模擬
地表模式的選擇 • They extended the Oregon State University LSM(OSULSM) • ,which originally developed by Pan and Mahrt (1987),to include an explicit canopy resistance formulation and a surface runoff scheme.
Brief description of the LSM • A brief description of the soil thermodynamics and soil hydrology in the OSULSM • Has one canopy layer • Prognostic variables:soil temperature and moisture in the soil layers,water stored on the canopy,and snow stored on the ground. • Have 4 soil layers,and the root zone in the upper 1 m of soil. • For the soil model to capture the daily,weekly,and seasonal evolution of soil moisture and also to mitigate the possible truncation error in discretization. 0.1m 0.3m 0.6m 1m
Modelthermodynamics 地表熱通量 T:土壤溫度 :volumetric heat capacity :thermal conductivity :volumetric soil water content Maximum soil moisture
maximum soil moisture (porosity) saturated soil potential (suction) depend on soil texture
The layer-integrated from of Eq.(1) for th soil layer is : The prediction of Ti is performed using the Crank-Nicholson scheme.
Model hydrology Volumetric soil Moisture Content soil water diffusivity hydraulic conductivity are function of Represent sources and sinks soil water tension function 曲線配套参數 Saturated soil potential depend on soil type
R=Pd-Imax runoff 最大滲透量 未被攔截的降水 置換成為一天的值 :saturated hydraulic conductivity depend on soil texture =3.0 , =2*10-6m s-1
:直接蒸發 :被植披攔截蒸發 :經由根部及葉的發散量 潛在蒸發 field capacity wilting point Green vegetation fraction Chosen n=0.5 Maximum canopy capacity Intercepted canopy Water content If ,the excess precipitation or drip Input total precipitation
Canopy evapo- transpiration :與飽和比濕曲線的 斜率有關 :空氣的T和P的函數 :熱量和水汽的交換 係數 Function of canopy resistance canopy resistance 太陽輻射效率 水汽壓不足效應 氣溫效應 土壤水分效應
Snow and sea-ice model “skin” temperature temperature in the first soil layer snow heat flux physical snow depth Thermal diffusivity for snow depend on porosity of snow it is set to be Compared to the original OSULSM,a new procedure has been represent the snow evaporation/sublimation and melting process
:skin temperature (set to the snow surface temperature of the previous time set) 代入 給定:the snow evaporate/sublimate 而 :effective skin temperature 可解出 ,snow will not melt ,evaporation/sublimation and melting will coexist
is the snow temperature 當融雪量 大於已融所剩的覆雪,便定義 而新的地表溫度Ts則可以由下面的地表能量平衡式決定
雖然有很大的改進,但還是有一些缺點: • 均勻的雪覆在固定的網格中 • 只有一層雪 • 雪的熱力擴散係數是常數 • 沒有考慮雪的生命期及雪的多孔的特性 • Koren et al (1999)extended this LSM to include a physically based • parameterization of frozen soil and a new snow accumulation/ • ablation scheme .this new scheme is able to simulate the total • ice content of each soil layer. • Sea-ice model Change:1.heat capacity, 2.thermal conductivity, 3.the temperature at the sea surface below sea-ice pack is assumed to de -2ºC
Land surface characteristic fields and parameter specification There are two primary variables upon which other secondary parameters (such as minimal canopy resistance and soil hydraulic properties) are determined . 1. vegetation type 2. soil texture
For vegetation classification,we utilize the 1-km resolution U.S. Geological Survey’s(USGS) SiB model vegetation categorization,which has 16 land cover classes. This land cover bataset is derived from the 1-km satellite Advanced Very High Resolution Radiometer(AVHRR) 粗糙長度 氣孔 可見太陽通量
σf (green vegetation fraction),defined as the grid-cell fraction for which midday downward solar insolation is intercepted by photosynthetically active green canopy.In the current coupled MM5-LSM, σf is assigned by monthly 5-yr climatology of green vegetation cover data with 0.15° resolution derived from AVHRR
Soil texture 多孔性 飽和土壤吸水力飽和水力傳導係數 田間含水量凋萎點
Field capacity :也就是田間含水量,當內部排水終止時稱之 沒有標準的方法去定量或計算,有些學者定義為當最大土壤溼度 為75%或當水壓係數k=0.1時的土壤溼度值。 It is important parameter in the LSM formulation (11)and (16),which determine the evaporation rate. Wilting point : defined as the critical soil moisture at which the evaporation process ceases. In MM5-LSM ,we simply increase(decrease) the value of field capacity (wilting point) to save computational time.
Annual mean air temperature of 1987-88 adopted to the MM5 topography.
Initialization of soil moisture In the current MM5-LSM model,the initial soil moisture can be obtained from two forecast/analysis systems. 1.the NCEP regional operational Eta model and its companion data assimilation system(EDAS). *has relatively high resolution(run at 32 km),over the North America region. 2.the NCEP-NCAR reanalysis system can be used retrospective applications and the NCEP global data assimilation system (GDAS) can be used for real- time applications for region outside of North America and for historical cases going back 40 yr.
Some studies point out that the reanalysis tends to very wet soil moisture due to a model positive precipitation bias .It may be necessary to adjust to initialize the soil moisture in the initialization procedure. (apply climatological soil moisture damping field and depends on season) when using the reanalysis-GDAS soil moisture to initialize the MM5 for January through June, Soil moisture from the reanalysis-GDAS and for July through December, Initial soil Moisture in the MM5
To demonstrate the sensitivity of the coupling MM5-LSM model to initial soil • moisture field,the MM5 model to set up 48-h simulations(starting at 4 Jun 1987) • This period is chosen because of the existence of clear-sky condition over • most of the United States. • The horizontal gird increments are 90,30,10 km • The initial soil moisture and temperature condition in the MM5 are obtained • from the NCER-NCAR reanalysis. • Two set of simulation conducted • 1. The soil moisture is changed (increased and deceased) by 10% • 2. The soil moisture is changed (increased and deceased) by 0.1 in terms of • absolute volumetric values,representing a large change. • The surface heat fluxes at four grid points are studied. • 1. 35.01°N, 109.09 °W, near the New Mexico and Arizona border for the 10% • change experiment.(dry) • 2. 35.01 °N, 115.0 °W ,near Lake Havasu City ,Arizona border for the 0.1 • change experiment.(dry) • 3. 34.11 °N, 97.99 °W, near Oklahoma City, Oklahoma. (semidry) • 4. 34.11 °N, 84.0 °W, near Atlanta,Georgia.(wet) • for both experiment experiment
Initial soil moisture,interpolated from the reanalysis,for the four soil layers at four points. Note that the reanalysis volumetric soil moisture field are for two soil layers ,0~0.1 m and 0.1~2 m,and are interpolated to the four soil moisture layers.
Dry point Upper is 10% changed ,the other is 0.1 changed Sensible heat flux Latent heat flux
Semidry point Upper is 10% changed ,the other is 0.1 changed Latent heat flux Sensible heat flux
Surface layer parameterization and PBL scheme A surface layer parameterization should provide the surface (bulk) exchange coefficients for momentum,heat,and water vapor used to determine the flux of these quantities between the land surface and the atmosphere. The exchange coefficients is passed to the LSM from the PBL scheme.
Currently,in MM5,the surface exchange coefficient for heat and moisture is formulated as wind speed at the lowest layer Stability-dependent function for momentum and heat The roughness lengths for momentum and heat :friction velocity molecular diffusivity ( ) 0.01m k=0.4 von Kármán constant
F.Chen et al. test two approaches to specify the thermal roughness length: 1.assume the roughness length for heat is a fixed ratio of the roughness length for momentum 2.relate this ratio to the roughness Reynolds number as proposed by Zilitinkevich (1995).C=0.1 A long-term test with the NCEP mesoscale Eta Model indicated that this approach can also reduce forecast precipitation bias. Without sublayer parameterization Z.scheme With sublayer parameterization Latent heat