Atmospheric Seasonal Predictability Experiments by the JMA AGCM
Atmospheric Seasonal Predictability Experiments by the JMA AGCM
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JMA AGCM 的大气季节可预测性实验
DOI：
10.2151/jmsj.79.1183
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发表时间：
2001
影响因子：
3.1
通讯作者：
K. Takano
中科院分区：
文献类型：
--
作者：
S. Kusunoki;M. Sugi;A. Kitoh;C. Kobayashi;K. Takano
利用日本气象厅（JMA）的大气环流模式（AGCM）研究了大气的季节可预测性，该模式是一种T63分辨率的全球光谱模式，用于以前的业务一个月预报。从目标季节前连续9天的初始条件开始进行为期4个月的整体集成。选取1979 - 1993年15年间的四个季节作为目标季节。在时间积分期间，模式被观测到的海表温度（SST）强迫。通过季节平均500 hPa高度的异常相关性验证如下：(1)就15年平均值而言，整体平均预报的技巧往往高于个别预报、持续预报和全球气候预报的技巧。(2)北半球春冬季技能高，夏秋季技能低。(3)东亚和北美地区的技能水平高于欧洲和大西洋地区。在冬季，东亚和北美地区相对较高的技能可归因于模式对西太平洋（WP）和太平洋/北美（PNA）遥相关模式的合理再现。(4)更大的集合规模提高了模式在温带和热带地区以及所有四季的技能。(5)各地区、各季节，1个月提前期预测技能均低于无提前期预测技能。在北半球，相对于提前期而言，相对较大的技能退化在春季尤为明显，这表明该模型对春季初始条件的敏感性高于夏季和秋季。(6)强厄尔尼诺和南方涛动（ENSO）年的技能增强在全球范围内普遍明显，但在北半球不那么明显。在ENSO年份，北美的技能增加，但在欧洲和大西洋地区没有明显的技能增加。该模式重现降水年际变率的能力也进行了研究。观测降水与模式集合平均预报降水的年际时间相关系数的地理分布表明，在所有季节，热带地区的相关性普遍高于温带地区。在热带地区，赤道东太平洋的技能相对较高，而印度则较低。该模式在模拟印度夏季风季和东亚夏季雨季降水的年际变化方面存在困难，这可能是由于该模式在这些地区夏季的气候学较差。
Atmospheric seasonal predictability is investigated using the Japan Meteorological Agency (JMA) Atmospheric General Circulation Model (AGCM) which is a global spectral model of T63 resolution used for former operational one-month farecasts. Four-month ensemble integrations were performed from nine consecutive days of initial condition preceding the target season. All four seasons in the 15-year period from 1979 to 1993 are chosen as the target seasons. The model was forced with observed sea surface temperature (SST) during the time integrations. Verification by the anomaly correlation of seasonal averaged 500 hPa height are summarized as follows. (1) In terms of a 15-year mean, ensmble average forecasts tend to have higher skill than means of individual forecasts, persistence forecasts and climatological forecasts over the whole globe. (2) In the Northern Hemisphere, skill is high in spring and winter, and low in summer and autumn. (3) Skill is higher over East Asia and North America, than over Europe and Atlantic regions. In winter, the relatively higher skill over East Asia and North America can be attributed to reasonable reproducibility of Western Pacific (WP) and Pacific/North American (PNA) teleconnection patterns by the model. (4) A larger ensemble size improves the skill of the model both for extratropical regions and the tropics, and for all four seasons. (5) The skill of one-month lead time forecasts is lower than that of no lead time forecasts for all regions and all seasons. Focusing on the Northern Hemisphere, the relatively large skill degradation with respect to lead time is striking in spring, which suggests that the model is more sensitive to initial conditions in spring than in summer and autumn. (6) Skill enhancement for strong El Nino and the Southern Oscillation (ENSO) years is generally evident over the whole globe, but is not so striking in the Northern Hemisphere. Skill over North America increases for ENSO years, but there is no clear skill enhancement over the Europe and Atlantic regions. The model’s ability to reproduce the interannual variability of precipitation was also investigated. Geographycal distributions of interannual temporal correlation coefficients between observed precipitation, and model ensemble average forecast precipitation show that correlations are generally higher in the tropics than in the extratropics for all seasons. In the tropics, skill is relatively higher in the equatorial eastern Pacific ocean and lower over India. The model has difficulty in simulating the interannual variability of precipitation for the Indian summer monsoon season and for the East Asian rainy season in summer, which may originate from the model’s poor climatology over these regions in summer.