张录军, 王乐, 邢雯慧, 黄勇, 张雅琦, 刘树棣. 分辨率和陆面方案对长江流域短期气候预测影响[J]. 水科学进展, 2016, 27(6): 800-809. DOI: 10.14042/j.cnki.32.1309.2016.06.002
引用本文: 张录军, 王乐, 邢雯慧, 黄勇, 张雅琦, 刘树棣. 分辨率和陆面方案对长江流域短期气候预测影响[J]. 水科学进展, 2016, 27(6): 800-809. DOI: 10.14042/j.cnki.32.1309.2016.06.002
ZHANG Lujun, WANG Le, XING Wenhui, HUANG Yong, ZHANG Yaqi, LIU Shudi. Effect of different spatial resolutions and land surface parameterization schemes on the short-term climate prediction in the Yangtze River basin[J]. Advances in Water Science, 2016, 27(6): 800-809. DOI: 10.14042/j.cnki.32.1309.2016.06.002
Citation: ZHANG Lujun, WANG Le, XING Wenhui, HUANG Yong, ZHANG Yaqi, LIU Shudi. Effect of different spatial resolutions and land surface parameterization schemes on the short-term climate prediction in the Yangtze River basin[J]. Advances in Water Science, 2016, 27(6): 800-809. DOI: 10.14042/j.cnki.32.1309.2016.06.002

分辨率和陆面方案对长江流域短期气候预测影响

Effect of different spatial resolutions and land surface parameterization schemes on the short-term climate prediction in the Yangtze River basin

  • 摘要: 利用区域气候模式RegCM4.5,分别选取不同陆面参数化方案和空间分辨率,对5个长江流域降水异常年份进行短期气候回报试验,分析对气温和降水预测效果的影响及其最优组合。结果表明:空间分辨率的提高可以改善流域降水和气温的预测性能;而不同陆面方案引起的地表净辐射能量分布不同及其地表蒸散差异,最终导致流域内气温和降水预测效果不一致。RegCM(CLM4.5+30 km)对流域内小雨预测结果最好,而RegCM(BATS+30 km)预测流域内大雨和暴雨效果最优;RegCM(CLM3.5+30 km)对流域内气温预测能力最好。

     

    Abstract: In this paper, we predict the air temperature and precipitation of the Yangtze River basin in five years with abnormal precipitation by the Regional Climate Model (RegCM4.5). We compare the prediction results of air temperature and precipitation with three land surface parameterization schemes and two spatial resolutions. The results show that high spatial resolution can improve the accuracy of air temperature and precipitation prediction; Different land surface schemes can cause different temporal-spatial distribution of surface net flux and evapotranspiration, leading to uncertainty prediction performance of air temperature and precipitation in the Yangtze River basin. Through the comparative analysis, we found that CLM4.5 with 30 km resolution is the best combination of predicting light rain, and BATS with 30 km resolution is the optimal choice of predicting heavy rain. CLM3.5 with 30 km resolution gives the best performance for predicting air temperature in the Yangtze River basin.

     

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