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引用本文:王丹丹,王伟,刘寿东,邱新法,穆俊宇,莫华阳,崔丛欣,陶潘虹,阙宇杰,俞乐,陈泓宇,薛舒航.太湖小时尺度水面蒸发特征及3种模型模拟效果对比.湖泊科学,2017,29(6):1538-1550. DOI:10.18307/2017.0626
WANG Dandan,WANG Wei,LIU Shoudong,QIU Xinfa,MU Junyu,MO Huayang,CUI Congxin,TAO Panhong,QUE Yujie,YU Le,CHEN Hongyu,XUE Shuhang.Characteristics of modelling hourly water surface evaporation in Lake Taihu and comparison of simulation results by three models. J. Lake Sci.2017,29(6):1538-1550. DOI:10.18307/2017.0626
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太湖小时尺度水面蒸发特征及3种模型模拟效果对比
王丹丹1,2, 王伟1,2, 刘寿东1,2, 邱新法2, 穆俊宇2, 莫华阳2, 崔丛欣2, 陶潘虹2, 阙宇杰2, 俞乐2, 陈泓宇2, 薛舒航3
1.耶鲁大学-南京信息工程大学大气环境中心, 南京 210044;2.南京信息工程大学应用气象学院, 南京 210044;3.南京信息工程大学大气科学学院, 南京 210044
摘要:
小时尺度水面蒸发可影响水面大气边界层热力和动力结构,分析湖泊小时尺度水面蒸发主要影响因素,选取准确模拟其特征的蒸发模型,将有助于改善流域天气预报和空气质量预报.基于太湖避风港站2012-2013年通量、辐射和气象观测数据,分析太湖小时尺度水面蒸发主要影响因子和3个模型(传统质量传输模型、Granger and Hedstrom经验模型、DYRESM模型)的模拟效果.结果表明:影响太湖小时尺度水面蒸发的主要因子为水气界面水汽压差和风速的乘积,而非净辐射.传统质量传输模型、Granger and Hedstrom经验模型、DYRESM模型模拟值与全年实测值的一致性系数分别为0.92、0.87和0.89,均方根误差分别为28.35、41.58和38.26 W/m2.传统质量传输模型对太湖小时尺度水面蒸发的日变化和季节动态模拟效果最佳,其夜间模拟相对误差小于3%,除秋季外,其他季节的模拟绝对误差均小于4 W/m2.Granger and Hedstrom经验模型系统性地高估太湖潜热通量,在大气较为稳定的午后(高估22~32 W/m2)和冬季(高估72%)高估最为明显,模拟效果最差.DYRESM模型也系统地高估太湖潜热通量,模拟效果居中.考虑水汽交换系数随风速的变化特征将有助于改善传统质量传输模型和DYRESM模型对太湖小时尺度水面蒸发的模拟精度.
关键词:  太湖  潜热通量  水面蒸发模拟  小时尺度  传统质量传输模型  Granger and Hedstrom经验模型  DYRESM模型
DOI:10.18307/2017.0626
分类号:
基金项目:国家自然科学基金青年项目(41505005)、江苏省自然科学基金青年项目(BK20150900)、国家自然科学基金项目(41475141,41575147)、南京信息工程大学人才启动经费项目(2014r046)和南京信息工程大学2015年度大学生实践创新训练计划项目(201510300023)联合资助.
Characteristics of modelling hourly water surface evaporation in Lake Taihu and comparison of simulation results by three models
WANG Dandan1,2, WANG Wei1,2, LIU Shoudong1,2, QIU Xinfa2, MU Junyu2, MO Huayang2, CUI Congxin2, TAO Panhong2, QUE Yujie2, YU Le2, CHEN Hongyu2, XUE Shuhang3
1.Yale-NUIST Center on Atmospheric Environment, Nanjing University of Information Science and Technology, Nanjing 210044, P. R. China;2.College of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, P. R. China;3.College of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing 210044, P. R. China
Abstract:
Water surface evaporation on hourly timescale can affect the thermal and dynamic structure of the aloft atmospheric boundary layers. Understanding the main drivers of hourly evaporation and accurate evaporation model can improve weather forecast and air quality prediction in catchment. Based on half-hour flux, radiation and micrometeorological observations at the Bifenggang site in Lake Taihu in 2012 and 2013, the main drivers of Lake Taihu hourly evaporation were investigated. Then the performance of three models (traditional mass transfer model, Granger and Hedstrom model and DYRESM model) was evaluated against latent heat flux measured by eddy covariance. The results showed that the main driver for Taihu hourly evaporation was the product of the water vapor pressure difference at water-atmosphere interface and wind speed, rather than the expected net radiation. The Willmott index of agreement between simulated values and measured values were 0.92, 0.87, 0.89 for traditional mass transfer model, Granger and Hedstrom model and DYRESM model, respectively, with the corresponding root mean square error of 28.35 W/m2, 38.26 W/m2 and 41.58 W/m2. The traditional mass transfer model showed the best performance on the diurnal time scale, especially at night when the simulation relative error was less than 3%. Except autumn, the absolute errors of traditional mass transfer model were less than 4 W/m2. Granger and Hedstrom model performed worst and systematically overestimated the latent heat flux at Lake Taihu, particularly in the afternoon (overestimate of 22-32 W/m2) and winter (overestimate of 72%) when the atmospheric boundary layer was stable. Although with overestimation, DYRESM model still performed considerably better than Granger and Hedstrom model and ranked middle. The parameterization of transfer coefficient for water vapor with wind speed can improve the hourly evaporation simulation at Lake Taihu by traditional mass transfer model and DYRESM model.
Key words:  Lake Taihu  latent heat flux  modelling water surface evaporation  hourly time scale  traditional mass transfer model  Granger and Hedstrom model  DYRESM model
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