臺灣博碩士論文加值系統

全球環流模式在解析度逐漸提升的過程中，所使用的對流積雲參數化也必須隨之相應的減少其作用，才能在解析度提升至雲解析模式時，自動將參數化之功能解除。為了發展出整合性參數化方法，Arakawa and Wu (2013) 使用GATE個案在VVM當中的模擬，並以不同次網域大小作平均，將之視為不同解析度下的全球環流模式網格資料，再去分析其中的次網格對流強度隨解析度之關係。他們提出對流覆蓋率是整合不同解析度模式的適當參數選項，並用此參數推導出整合性參數化方法，當次網格對流覆蓋率接近網格尺度時，藉由此參數來調降參數化之強度，避免重複計算。本研究旨在推廣此一參數化方法在不同對流強度之適用性，及配合現有之積雲參數化來進行整合性參數化試驗。我們所用的個案為對流強度變化較GATE個案多的DYNAMO實驗，也將DYNAMO實驗依照降水強度分成四類，並沿用Arakawa and Wu (2013) 的實驗方法進行分析，結果顯示在DYNAMO整體及不同強度降水的次網格對流中，其對流覆蓋率關係是類似的，因此使用對流覆蓋率作為參數之整合性參數化在不同對流強度下也適用。我們也首度將整合性參數化結合Zhang-McFarlane積雲參數化以及兩種不同的對流垂直速度參數化方法，並用來計算DYNAMO實驗中的次網格對流強度。整合性參數化結果顯示所得到的對流覆蓋率有偏低且偏離實際對流網格的情形，其主要原因為診斷之垂直速度過大及積雲參數化對流為垂直發展之限制。在整體參數化對流強度方面，傳統和整合性之結果差異不大，主要原因為對流覆蓋率過小，而原本與對流覆蓋率無關係之傳統參數化對流，則藉由此參數化方法調整至較接近雲解析模式之結果。

Statistics of convective updraft fraction (σ) dependence, using the analysis methods in Arakawa and Wu (2013) (AW13), in a 15 days period of time-variant thermodynamic forcing case (DYNAMO), and the offline test of unified parameterization (UP) closure combined with Zhang-McFarlane parameterization scheme (ZM) are presented in this work. The similar result of σ dependence within DYNAMO and GATE (used in AW13), and of the four different strength categories of precipitation in DYNAMO explain that the σ dependence is more appropriate than resolution dependence for unified-parameterizing multi-phase convection. The UP closure proposed by AW13 uses σ as the tuning parameter to adjust the conventional parameterized convection, which lacks of consciousness of sub-grid scale convection coverage. The results of inputting DYNAMO forcing into the ZM, combined with UP and vertical velocity parameterization scheme, which is for diagnosing unknown σ in the closure, shows the underestimation of the σ values and the shift of convective areas away from the cloud resolving model (CRM) simulation, causing the problem of tuning down the parameterized mass fluxes at incorrect places. This can be improved by revising the closure that decides the place of convection and tuning the in-cloud vertical velocities to a more reasonable scale. The purpose of UP scheme is to adjust the sub-grid scale convection by regarding its parameterized σ, so even the ensemble average of convection fluxes doesn’t significantly changed after applying UP scheme, the σ dependence of unified parameterized convection fluxes still better fit the σ dependence in the convection of CRM.

口試委員會審定書………………………………………………………………… i
致謝………………………………………………………………………………… ii
中文摘要………………………………………..…………………………………. iii
Abstract……………………………………………………………………………. iv
1. Introduction……………………………………………………………………. 1
2. Dependence of sub-grid scale convective updraft in DYNAMO……………… 6
3. The derivation of unified parameterization scheme…………………………… 23
3.1 The revision of conventional closure to unified closure………………….. 23
3.2 Parameterize σ from boundary convection scheme………………………. 28
3.3 Combination with Zhang-McFarlane Scheme……………………………. 31
4. Analysis of unified parameterized convection……………………………….. 33
5. Conclusion and future work…………………………………………………... 47
References………………………………………………………………………… 51
Appendix……………………………………………………………….................. 54

Arakawa, A. 2004. The cumulus parameterization problem: Past, present, and future. Journal of Climate, 17(13), 2493-2525.
――, J. H. Jung, and C. M. Wu, 2011. Toward unification of the multiscale modeling of the atmosphere. Atmospheric Chemistry and Physics, 11(8), 3731-3742.
――, and W. H. Schubert, 1974. Interaction of a cumulus cloud ensemble with the large-scale environment, Part I. Journal of the Atmospheric Sciences, 31(3), 674-701.
――, and C. M. Wu, 2013. A unified representation of deep moist convection in numerical modeling of the atmosphere. Part I. Journal of the Atmospheric Sciences, 70(7), 1977-1992.
Collins, W. D., P. J. Rasch, B. A. Boville, J. J. Hack, J. R. McCaa, D. L. Williamson, J. T. Kiehl, B. Briegleb, C. Bitz, S. J. Lin, and M. Zhang, 2004. Description of the NCAR community atmosphere model (CAM 3.0). NCAR Tech. Note NCAR/TN-464+ STR, 226.
de Roode, S. R., A. P. Siebesma, H. J. Jonker, and Y. de Voogd, 2012. Parameterization of the vertical velocity equation for shallow cumulus clouds. Monthly Weather Review, 140(8), 2424-2436.
Fan, J., Y. C. Liu, K. M. Xu, K. North, S. Collis, X. Dong, G. J. Zhang, Q. Chen, P. Kollias, and S. J. Ghan, 2015. Improving representation of convective transport for scale‐aware parameterization: 1. Convection and cloud properties simulated with spectral bin and bulk microphysics. Journal of Geophysical Research: Atmospheres, 120(8), 3485-3509.
Jung, J. H., and A. Arakawa, 2004. The resolution dependence of model physics: Illustrations from nonhydrostatic model experiments. Journal of the atmospheric sciences, 61(1), 88-102.
――, and ――, 2008. A three-dimensional anelastic model based on the vorticity equation. Monthly Weather Review, 136(1), 276-294.
Kim, D., and I. S. Kang, 2012. A bulk mass flux convection scheme for climate model: description and moisture sensitivity. Climate dynamics, 38(1-2), 411-429.
Kim, S. Y., and M. I. Lee, 2014, Evaluations of the Cloud-resolving Model in Representing Convective Precipitation Process. 2014 년도 한국기상학회 가을학술대회 프로그램집, 235-236.
Liu, Y. C., J. Fan, G. J. Zhang, K. M. Xu, and S. J. Ghan, 2015. Improving representation of convective transport for scale‐aware parameterization: 2. Analysis of cloud‐resolving model simulations. Journal of Geophysical Research: Atmospheres, 120(8), 3510-3532.
Lappen, C. L., and D. A. Randall, 2001a. Toward a unified parameterization of the boundary layer and moist convection. Part I: A new type of mass-flux model. Journal of the atmospheric sciences, 58(15), 2021-2036.
――, and ――, 2001b. Toward a unified parameterization of the boundary layer and moist convection. Part II: Lateral mass exchanges and subplume-scale fluxes. Journal of the atmospheric sciences, 58(15), 2037-2051.
――, and ――, 2001c. Toward a unified parameterization of the boundary layer and moist convection. Part III: Simulations of clear and cloudy convection. Journal of the atmospheric sciences, 58(15), 2052-2072.
Wu, C. M., and A. Arakawa, 2014. A unified representation of deep moist convection in numerical modeling of the atmosphere. Part II. Journal of the Atmospheric Sciences, 71(6), 2089-2103.
Xiao, H., W. I. Gustafson, S. M. Hagos, C. M. Wu, and H. Wan, 2015. Resolution‐dependent behavior of subgrid‐scale vertical transport in the Zhang‐McFarlane convection parameterization. Journal of Advances in Modeling Earth Systems, 7(2), 537-550.
Zhang, G. J., and N. A. McFarlane, 1995. Sensitivity of climate simulations to the parameterization of cumulus convection in the Canadian Climate Centre general circulation model. Atmosphere-ocean, 33(3), 407-446.