张利军,李建儒,王红光,等. 改进的蒸发波导RSHMU模型及预测性能分析[J]. 电波科学学报,2022,37(2):198-205. DOI: 10.12265/j.cjors.2021243
      引用本文: 张利军,李建儒,王红光,等. 改进的蒸发波导RSHMU模型及预测性能分析[J]. 电波科学学报,2022,37(2):198-205. DOI: 10.12265/j.cjors.2021243
      ZHANG L J, LI J R, WANG H G, et al. An improved evaporation duct RSHMU model and prediction performance analysis[J]. Chinese journal of radio science,2022,37(2):198-205. (in Chinese). DOI: 10.12265/j.cjors.2021243
      Citation: ZHANG L J, LI J R, WANG H G, et al. An improved evaporation duct RSHMU model and prediction performance analysis[J]. Chinese journal of radio science,2022,37(2):198-205. (in Chinese). DOI: 10.12265/j.cjors.2021243

      改进的蒸发波导RSHMU模型及预测性能分析

      An improved evaporation duct RSHMU model and prediction performance analysis

      • 摘要: 针对稳定条件下蒸发波导RSHMU模型过于敏感不便使用的问题,引入BH91关系式、CB05关系式和SHEBA07关系式给出了相关的改进方法,并对不同风速以及不同相对湿度的敏感性进行了分析. 结果发现引入稳定条件下的剖面稳定度函数对蒸发波导高度诊断的敏感性改善不大. 进一步地,借鉴Paulus给出的订正方法,给出了P-RSHMU蒸发波导模型改进预测方法,有效解决了已有模型稳定条件下的不合理诊断结果. 与渤海梯度塔实测数据对比分析表明:稳定条件下P-RSHMU蒸发波导模型预测蒸发波导高度的平均误差为−1.02 m,均方根误差为1.49 m,显著优于已有RSHMU模型.

         

        Abstract: Aiming the problem that the RSHMU evaporation duct model is too sensitive and can’t be used conveniently under the stable condition, some improved methods introduced BH91 expression, CB05 expression and SHEBA07 expression are given in this paper. The sensitivity analysis results under different wind speed and relative humitivity show that changing the profile function does not improve the sensitivity of evaporation duct height diagnosis. Based on the revised method given by Paulus, an improved prediction method called P-RSHMU evaporation duct model is presented which effectively solves the unreasonable diagnosis results under the stable condition compared with the original model. Compared with the measured data of gradient tower in Bohai sea, it is shown that the average error of the modified model is −1.02 m and the root mean square error is 1.49 m in stable conditions. The modified model performs better than the original RSHMU model significantly.

         

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