首页 | 本学科首页   官方微博 | 高级检索  
     检索      


An Indian monsoon intraseasonal oscillations (MISO) index for real time monitoring and forecast verification
Authors:E Suhas  J M Neena  B N Goswami
Institution:1. Scripps Institution of Oceanography, University of California San Diego, 9500 Gilman Drive, La Jolla, California, 92093, USA
2. Joint Institute for Regional Earth System Science and Engineering, University of California Los Angeles, Los Angeles, California, 90095, USA
3. Indian Institute of Tropical Meteorology, Dr. Homi Bhaba Road, Pashan, Pune, 411008, India
Abstract:The wet/dry spells of the Indian summer monsoon (ISM) rainfall are governed by northward propagating boreal summer monsoon intraseasonal oscillations (MISO). Unlike for the Madden Julian Oscillation (e.g. RMM indices, Wheeler and Hendon in Mon Weather Rev 132:1917–1932, 2004), a low dimensional real-time monitoring and forecast verification metric for the MISO is not currently available. Here, for the first time, we present a real time monitoring index developed for identifying the amplitude and phase of the MISO over the ISM domain. The index is constructed by applying extended empirical orthogonal function (EEOF) analysis on daily unfiltered rainfall anomalies averaged over the longitudinal domain 60.5°E–95.5°E. The gravest two modes of the EEOFs together explain about 23 % of the total variance, similar to the variance explained by MISO in observation. The pair of first two principal components (PCs) of the EEOFs is named as MISO1 and MISO2 indices which together represent the evolution of the MISOs in a low dimensional phase space. Power spectral analysis reveals that the MISO indices neatly isolate the MISO signal from the higher frequency noise. It is found that the current amplitude and phase of the MISO can be estimated by preserving a memory of at least 15 days. Composite pictures of the spatio-temporal evolution of the MISOs over the ISM domain are brought out using the MISO indices. It is further demonstrated that the MISO indices can be used in the quantification of skill of extended range forecasts of MISOs. Since the MISO index does not rely on any sort of time filtering, it has great potential for real time monitoring of the MISO and may be useful in developing some prediction scheme.
Keywords:
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号