Krishnamurthy V
Center for Ocean-Land-Atmosphere Studies George Mason University Fairfax VA USA.
Earth Space Sci. 2019 Jul;6(7):1043-1056. doi: 10.1029/2019EA000586. Epub 2019 Jul 24.
The past developments in the predictability of weather and climate are discussed from the point of view of nonlinear dynamical systems. The problems ahead for long-range predictability extending into the climate time scale are also presented. The sensitive dependence of chaos on initial conditions and the imperfections in the models limit reliable predictability of the instantaneous state of the weather to less than 10 days in present-day operational forecasts. The existence of slowly varying components such as the sea surface temperature, soil moisture, snow cover, and sea ice may provide basis for predicting certain aspects of climate at long range. The regularly varying nonlinear oscillations, such as the Madden-Julian Oscillation, monsoon intraseasonal oscillations, and El Niño-Southern Oscillation, are also possible sources of extended-range predictability at the climate time scale. A prediction model based on phase space reconstruction has demonstrated that monsoon intraseasonal oscillation can be better predicted at long leads.
从非线性动力系统的角度讨论了过去天气和气候可预测性的发展情况。还介绍了延伸至气候时间尺度的长期可预测性面临的问题。在当今的业务预报中,混沌对初始条件的敏感依赖性以及模型的不完善性将天气瞬时状态的可靠可预测性限制在不到10天。诸如海面温度、土壤湿度、积雪和海冰等缓慢变化的成分的存在可能为长期预测气候的某些方面提供基础。规则变化的非线性振荡,如马登-朱利安振荡、季风季节内振荡和厄尔尼诺-南方涛动,也是气候时间尺度上延伸范围可预测性的可能来源。基于相空间重构的预测模型表明,季风季节内振荡在较长提前期时可以得到更好的预测。