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Simple Multiple Regression Model for long range forecasting of Indian Summer Monsoon Rainfall

机译:简单多元回归模型对印度夏季风季风降水的长期预报

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The relationship between the Indian Ocean Sea-Surface Temperature Anomalies (SSTA) and the Indian Summer Monsoon Rainfall (ISMR) have been examined for the period, 1983–2006. High and positive correlation (0.51; significant at >99% level) is noticed between ISMR and SSTA over southeastern Arabian Sea (AS) in the preceding January. Significant and positive correlation (0.61: significant at >99% level) is also observed with the SSTA over northwest of Australia (NWA) in the preceding February. The combined SSTA index (AS + NWA) showed a very high correlation of 0.71 with the ISMR. The correlation between East Asia sea-level pressure (average during February and March in the region, 35° N–45° N; 120° E–130° E) and ISMR is found to be 0.62. The multiple correlation using the above two parameters is 0.85 which explains 72% variance in ISMR. Using the above two parameters a linear multiple regression model to predict ISMR is developed. Our results are comparable with those obtained from the power regression (developed with 16, 8 and 10 parameters) and ensemble models (using 3 to 6 parameters) of the Indian Meteorological Department (IMD) (Rajeevan et al. 2004; 2006). The rainfall during 2002 and 2004 could be predicted accurately from the present model. It is well known fact that most of the dynamical/statistical methods failed to predict the rainfall in 2002. However, as for associations between SST and ISMR, the index is quite susceptible to inter decadal fluctuations and markedly reduced skill is found in the decades preceding 1983. The RMS error for 24 years is 5.56 (% of long period average, LPA) and the correlation between the predicted and observed rainfall is 0.79.
机译:在1983-2006年期间,研究了印度洋海表温度距平(SSTA)和印度夏季风降水(ISMR)之间的关系。在上一月的东南阿拉伯海(AS)上,ISMR和SSTA之间发现了高度正相关(0.51;显着高于99%的水平)。在2月份,澳大利亚西北部(NWA)的SSTA也观察到显着正相关(0.61:在> 99%的水平上显着)。 SSTA组合指数(AS + NWA)与ISMR的相关性非常高,为0.71。发现东亚海平面压力(该地区2月和3月平均水平,北纬35°至45°;东经120°至130°)与ISMR之间的相关性为0.62。使用以上两个参数的多重相关为0.85,这说明ISMR中有72%的方差。利用以上两个参数,建立了线性多元回归模型来预测ISMR。我们的结果与印度气象部门(IMD)的幂回归(使用16、8和10参数开发)和集成模型(使用3至6参数)获得的结果相当(Rajeevan等人,2004; 2006)。根据目前的模型,可以准确预测2002年和2004年的降雨量。众所周知的事实是,大多数动力学/统计方法都无法预测2002年的降雨。但是,对于SST和ISMR之间的关联,该指数很容易受到年代际波动的影响,并且在此之前的几十年中,发现该技能的能力明显下降。 1983年。24年的RMS误差为5.56(长期平均值的百分比,LPA),并且预计和观测的降雨量之间的相关性是0.79。

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