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杨洪卿, 范可, 田宝强, 等. 2021. 为什么NCEP-CFSv2模式对11月西伯利亚高压强度的预测性能较好[J]. 大气科学, 45(4): 697−712. doi: 10.3878/j.issn.1006-9895.2009.20106
引用本文: 杨洪卿, 范可, 田宝强, 等. 2021. 为什么NCEP-CFSv2模式对11月西伯利亚高压强度的预测性能较好[J]. 大气科学, 45(4): 697−712. doi: 10.3878/j.issn.1006-9895.2009.20106
YANG Hongqing, FAN Ke, TIAN Baoqiang, et al. 2021. Why is the November Siberian High Intensity More Predictable by NCEP-CFSv2 Model? [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 45(4): 697−712. doi: 10.3878/j.issn.1006-9895.2009.20106
Citation: YANG Hongqing, FAN Ke, TIAN Baoqiang, et al. 2021. Why is the November Siberian High Intensity More Predictable by NCEP-CFSv2 Model? [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 45(4): 697−712. doi: 10.3878/j.issn.1006-9895.2009.20106

为什么NCEP-CFSv2模式对11月西伯利亚高压强度的预测性能较好

Why is the November Siberian High Intensity More Predictable by NCEP-CFSv2 Model?

  • 摘要: 作为东亚冬季风的关键系统,西伯利亚高压的变化对欧亚大陆冬季天气及气候异常产生重要影响。本文系统地评估了美国国家环境预测中心第二代气候预测系统(NCEP-CFSv2,National Center for Environment Prediction-Climate Forecast System, version 2)对冬半年(11~2月)及逐月西伯利亚高压强度的预测效能。结果表明,NCEP-CFSv2模式仅对11月西伯利亚高压强度的预测效能较好,研究其成因发现11月西伯利亚高压强度主要受该地区热力、动力过程以及西伯利亚地区积雪状况的影响。在热力过程方面,NCEP-CFSv2模式可以较好地再现11月西伯利亚高压强度及其相联的该地区表层土壤温度、对外长波辐射等热力因素;在动力过程方面,模式能较好地再现11月西伯利亚高压强度及其相联的该地区对流层低层辐散环流、中高层下沉运动;同时,模式也能较好地再现11月西伯利亚高压强度与该地区积雪覆盖率之间的相互作用。因此,与11月西伯利亚高压相联的热力、动力过程和该地区积雪状况可能是11月西伯利亚高压强度的可预测来源,且NCEP-CFSv2模式能较好地再现这些可预测来源。

     

    Abstract: As a critical system of the East Asian winter monsoon, the Siberian high has an important impact on the winter weather and climate anomalies in Eurasia. Using the National Center for Environment Prediction-Climate Forecast System version 2 (NCEP-CFSv2), this study comprehensively evaluates the seasonal and monthly prediction of the Siberian high intensity during the winter time (November to February). Results show that the NCEP-CFSv2 model can skillfully predict the Siberian high intensity only in November, the reasons for which are that the local thermal process, dynamic process, and Siberian snow cover extent mainly affect the Siberian high intensity in November. In terms of the thermal process, the NCEP-CFSv2 can better reproduce the Siberian high intensity in November and its related surface soil temperature, upward long-wave radiation, and other thermal factors in Siberia. In terms of the dynamic process, the NCEP-CFSv2 can better reproduce the Siberian high strength in November, which is associated with the low-level tropospheric divergent circulation and the sinking movement of the upper and middle layers in the Siberian area. The model also reproduces the relationship between the snow cover extent over Siberia and the Siberian high intensity in November. The thermodynamic process of the Siberian high and snow cover extent in the area are predictability sources of the Siberian High intensity in November, and the NCEP-CFSv2 can reasonably reproduce these predictability sources in November.

     

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