Simulation characteristics of planetary boundary layer parameterizations: A case study in Xinjiang during summer
Received date: 2020-03-10
Revised date: 2020-06-04
Online published: 2021-03-05
Planetary boundary layer (PBL) parameterization has significant impacts on the simulation and prediction of climate, weather, and environmental air quality. Here, ideal experiments were conducted using the single-column model to study the response characteristics of specific humidity and potential temperatures on soil moisture under different PBL parameterizations. A heavy precipitation synoptic process in Xinjiang from 15th-18th August 2019 was simulated and verified with six PBL parameterizations, including YSU, ACM2, BOULAC, GBM, MYJ, and QNSE. As the soil moisture increases, the simulated atmospheric boundary layer presents significant characteristics, namely, increasing specific humidity, decreasing potential temperatures, and decreasing boundary layer height. In GBM and ACM2 cases, the vertical water vapor transport efficiency was low, atmospheric specific humidity was also low, the potential temperature was high, eddy action scope was large, and precipitation was underestimated. In QNSE and MYJ cases, the vertical water vapor transport efficiency was high, atmospheric specific humidity was high, the potential temperature was low, eddy action scope was small, and precipitation was overestimated. The maximum 2 m specific humidity was achieved using QNSE and MYJ, while the minimum 2 m specific humidity was by ACM2. The lowest 2 m temperature was achieved at nighttime using QNSE, while the highest 2 m temperature was at daytime using MYJ. The highest 10 m wind speed was achieved using QNSE and MYJ. These simulating characters are closely related to the differences in the vertical water vapor transport efficiency of the different PBL parameterizations.
ZHANG Hailiang,LI Huoqing,Ali Mamtimin . Simulation characteristics of planetary boundary layer parameterizations: A case study in Xinjiang during summer[J]. Arid Zone Research, 2021 , 38(1) : 154 -162 . DOI: 10.13866/j.azr.2021.01.17
[1] | Stull R B. An Introduction to Boundary Layer Meteorology[M]. Netherlands: Springer, 1988. |
[2] | Smith R K, Thomsen G L. Dependence of tropical-cyclone intensification on the boundary-layer representation in a numerical model[J]. Quarterly Journal of the Royal Meteorological Society, 2010,136(652):1671-1685. |
[3] | Shin H H, Hong S Y. Intercomparison of planetary boundary-layer parametrizations in the WRF model for a single day from CASES-99[J]. Boundary-Layer Meteorology, 2011,139(2):261-281. |
[4] | Cheng F Y, Chin S C, Liu T H. The role of boundary layer schemes in meteorological and air quality simulations of the Taiwan area[J]. Atmospheric Environment, 2012,54(7):714-727. |
[5] | Xie B, Fung J C H, Chan A, et al. Evaluation of nonlocal and local planetary boundary layer schemes in the WRF model[J]. Journal of Geophysical Research Atmospheres, 2012,117(D12). |
[6] | Huang W, Shen X, Wang W, et al. Comparison of the thermal and dynamic structural characteristics in boundary layer with different boundary layer parameterizations[J]. Chinese Journal of Geophysics, 2014,57(4):543-562. |
[7] | Cohen A E, Cavallo S M, Coniglio M C, et al. A review of planetary boundary layer parameterization schemes and their sensitivity in simulating southeastern US cold season severe weather environmens[J]. Weather and Forecasting, 2015,30(3):591-612. |
[8] | 王建捷, 周斌, 郭肖容. 不同对流参数化方案试验中凝结加热的特征及对暴雨中尺度模拟结果的影响[J]. 气象学报, 2005,63(4):405-417. |
[8] | [ Wang Jianjie, Zhou bin, Guo Xiaorong. Numerical study on characteristics of condensational heating rates and their impacts on mesoscale structure of torrential rain simulation[J]. Acta Meteorologica Sinica, 2005,63(4):405-417. ] |
[9] | 孙建华, 赵思雄. 一次罕见的华南大暴雨过程的诊断与数值模拟研究[J]. 大气科学, 2000,24(3):381-392. |
[9] | [ Sun Jianhua, Zhao Sixiong. A diagnosis and simulation study of a strong heavy rainfall in south China[J]. Chinese Journal of Atmospheric Sciences, 2000,24(3):381-392. ] |
[10] | 陈静, 薛纪善, 颜宏. 物理过程参数化方案对中尺度暴雨数值模拟影响的研究[J]. 气象学报, 2003,61(2):203-218. |
[10] | [ Chen Jing, Xue Jishan, Yan Hong. The impact of physics parameterization schemes on mesoscale heavy rainfall simulation[J]. Acta Meteorologica Sinica, 2003,61(2):203-218. ] |
[11] | 孙文奇, 李昌义. 数值模式中的大气边界层参数化方案综述[J]. 海洋气象学报, 2018,38(3):11-19. |
[11] | [ Sun Wenqi, Li Changyi. A review of atmospheric boundary layer parameterization schemes in numerical models[J]. Journal of Marine Meteorology, 2018,38(3):11-19. ] |
[12] | Sukoriansky S, Galperin B, Perov V. Application of a new spectral theory of stably stratified turbulence to the atmospheric boundary layer over sea ice[J]. Boundary-Layer Meteorology, 2005,117(2):231-257. |
[13] | Gibbs J A, Fedorovich E. Comparison of convective boundary layer velocity spectra retrieved from large-eddy-simulation and Weather Research and Forecasting model data[J]. Journal of Applied Meteorology and Climatology, 2014,53(2):77-394. |
[14] | LeMone M A, Tewari M, Chen F, et al. Objectively determined fair-weather CBL depths in the ARW-WRF model and their comparison to CASES-97 observations[J]. Monthly Weather Review, 2013,141(1):30-54. |
[15] | Banks R F, Tiana-Alsina J, Baldasano, J M, et al. Sensitivity of boundary-layer variables to PBL schemes in the WRF model based on surface meteorological observations, lidar, radiosondes during the HygrA-CD campaign[J]. Atmospheric Research, 2016, 176-177:185-201. |
[16] | 张小培, 银燕. 复杂地形地区WRF模式四种边界层参数化方案的评估[J]. 大气科学学报, 2013,36(1):68-76. |
[16] | [ Zhang Xiaopei, Yin Yan. Evaluation of the four PBL schemes in WRF model over complex topographic areas[J]. Transactions of Atmospheric Sciences, 2013,36(1):68-76. ] |
[17] | 王颖, 张镭, 胡菊, 等. WRF模式对山谷城市边界层模拟能力的检验及地面气象特征分析[J]. 高原气象, 2010,29(6):1397-1407. |
[17] | [ Wang Ying, Zhang Lei, Hu Ju, et al. Verification of WRF simulation capacity on PBL characteristic and analysis of surface meteorological characteristic over complex terrain[J]. Plateau Meteorology, 2010,29(6):1397-1407. ] |
[18] | 陈淑莹, 胡琪, 张弛, 等. WRF模式在天山地区模拟能力的敏感性评估[J]. 干旱区研究, 2019,36(1):196-206. |
[18] | [ Chen Shuying, Hu Qi, Zhang Chi, et al. Evaluation on the sensitivity of WRF model in the Tianshan Mountains[J]. Arid Zone Research, 2019,36(1):196-206. ] |
[19] | 黄文彦, 沈新勇, 王卫国, 等. 边界层参数化方案对边界层热力和动力结构特征影响的比较[J]. 地球物理学报, 2014,57(5):1399-1414. |
[19] | [ Huang Wenyan, Shen Xinyong, Wang Weiguo, et al. Comparison of the thermal and dynamic structural characteristics in boundary layer with different boundary layer parameterizations[J]. Chinese Journal of Geophysics, 2014,57(5):1399-1414. ] |
[20] | Hu X M, Nielsen-Gammon J W, Zhang F. Evaluation of three planetary boundary layer schemes in the WRF model[J]. Journal of Applied Meteorology & Climatology, 2010,49(9):1831-1844. |
[21] | Wang W, Shen X, Huang W. A comparison of boundary-layer characteristics simulated using different parametrization schemes[J]. Boundary-Layer Meteorology, 2016,161(2):375-403. |
[22] | Cuxart J, Holtslag A A M, Beare R J, et al. Single-column model intercomparison for a stably stratified atmospheric boundary layer[J]. Boundary-Layer Meteorology, 2006,118(2):273-303. |
[23] | Ayotte K W, Sullivan P P, Anders Andrén, et al. An evaluation of neutral and convective planetary boundary-layer parameterizations relative to large eddy simulations[J]. Boundary-Layer Meteorology, 1996,79(1-2):131-175. |
[24] | Pleim J E. A combined local and nonlocal closure model for the atmospheric boundary layer. Part I: model description and testing[J]. Journal of Applied Meteorology & Climatology, 2007,46(9):1383-1395. |
[25] | Angevine W M, Jiang H, Mauritsen T. Performance of an eddy diffusivity-mass flux scheme for shallow cumulus boundary layers[J]. Monthly Weather Review, 2010,138(7):2895-2912. |
[26] | 赵建华, 张峰, 梁芸, 等. 大气边界层湍流相干结构研究进展[J]. 干旱区研究, 2019,36(6):1419-1430. |
[26] | [ Zhao Jianhua, Zhang Feng, Liang Yun, et al. Research progress on turbulent coherent structure in atmospheric boundary layer[J]. Arid Zone Research, 2019,36(6):1419-1430. ] |
[27] | Zhang H, Liu J, Li H, et al. The impacts of soil moisture initialization on the forecasts of Weather Research and Forecasting model: A case study in Xinjiang, China[J]. Water, 2020,12(7):1892. |
/
〈 | 〉 |