卢冰, 王薇, 杨扬, 仲跻芹, 陈敏. 2019: WRF中土壤图及参数表的更新对华北夏季预报的影响研究. 气象学报, 77(6): 1028-1040. DOI: 10.11676/qxxb2019.066
引用本文: 卢冰, 王薇, 杨扬, 仲跻芹, 陈敏. 2019: WRF中土壤图及参数表的更新对华北夏季预报的影响研究. 气象学报, 77(6): 1028-1040. DOI: 10.11676/qxxb2019.066
Bing LU, Wei WANG, Yang YANG, Jiqin ZHONG, Min CHEN. 2019: Updated soil map and soil hydrologic parameters for WRF and their influences over North China during the warm season. Acta Meteorologica Sinica, 77(6): 1028-1040. DOI: 10.11676/qxxb2019.066
Citation: Bing LU, Wei WANG, Yang YANG, Jiqin ZHONG, Min CHEN. 2019: Updated soil map and soil hydrologic parameters for WRF and their influences over North China during the warm season. Acta Meteorologica Sinica, 77(6): 1028-1040. DOI: 10.11676/qxxb2019.066

WRF中土壤图及参数表的更新对华北夏季预报的影响研究

Updated soil map and soil hydrologic parameters for WRF and their influences over North China during the warm season

  • 摘要: 土壤质地及其物理性质的参数化对陆面过程模拟具有明显的影响。研究了土壤质地和土壤水文参数表的更新对WRF(Weather Research and Forecasting)模拟性能的影响。使用北京师范大学土壤属性数据集和修正后的土壤水文参数表替换WRF默认数据,对2017年6—8月华北地区开展数值模拟试验和评估验证。结果表明,模拟结果对土壤类型数据集和水文参数表的更新较为敏感,对地面要素预报有正效果。WRF默认土壤数据集中,中国东部以粘壤土为主,而在北京师范大学土壤数据集里则以壤土为主;修正后的土壤水文参数在Noah陆面过程中增强了裸土潜热蒸发能力。数值模拟试验表明,土壤输入数据和土壤水文参数的更新能够增强陆面向大气的潜热同时减弱感热输送,致使大气底层温度降低而湿度增大。利用华北区域748个地面气象观测站的2 m温度和2 m湿度对2017年夏季的模拟结果进行验证,结果显示更新试验对地面要素的预报偏差有较好的修正作用,能够将2 m温、湿度的预报技巧分别提高3.4%和2.9%。

     

    Abstract: In meteorological models, land surface processes are crucial for simulating accurate numerical patterns. The land surface can be determined by physical properties of soil and soil state variables. The purpose of the present study is to implement a new soil map generated by Beijing Normal University (BNU) in China and revised hydrologic soil parameters different to defaults in the Weather Research and Forecasting model (WRF), and value their influences on the forecast skill over North China during the warm season using the Noah land surface model. A three months (from 1 June to 31 August 2017) simulation by the WRF model shows that the BNU soil map and the revised hydrologic soil parameters can obviously improve the simulation of ground meteorological elements. Loamy soil is the dominant soil type over eastern China based on the BNU soil dataset, whereas clay loam is the dominant one in WRF default soil dataset. Soil water content at field capacity is greater in the revised soil parameters dataset than that in the WRF default, which results in enhanced direct evaporation from the top shallow soil layer. Colder 2 m temperature and wetter 2 m humidity are found in the simulation with updated soil parameters because of reduced heat flux and enhanced latent heat flux from surface to the atmosphere. Evaluation against observations at 748 surface meteorological stations shows that the root mean square errors are reduced by 3.4% and 2.9% for 2 m temperature and 2 m humidity respectively with updated soil texture and soil parameters.

     

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