Earth Science India Vol.1 (IV), October, 2008, pp.302-312

http://www.earthscienceindia.info/

Use of interaction between NAO and   MJO for the prediction of dry and wet spell in monsoon season
           
S.S. Dugam
Indian Institute of Tropical Meteorology, Pune-411008

Abstract:The Indian summer monsoon exhibits prominent 30-40 day fluctuations with “active” periods of heavy rain interrupted by dry periods i.e. “Breaks”. The circulation anomalies associated with active/break monsoon cover the entire Indian Ocean remote tropics and North Pacific Ocean. A prolonged dry/wet period will result in severe drought/flooding, which have profound influences on the south Asia water cycle, agriculture and societal activity of more than one billion people. The atmospheric general circulation models have great difficulty in simulating the Intra-seasonal oscillation (ISO). Therefore, it is necessary to study the empirical relationship between various atmospheric processes, which are responsible for the ISO. In this paper, the analysis of North Atlantic Oscillation Index (NAOI) and Madden Julian Oscillation Index (MJOI) on daily scale is carried out in relation to daily Indian summer monsoon rainfall (June-September). The analysis is carried out for the period 1979-2001.  Since the potential predictability limit for monsoon break is about 20 days, the 20 days running lag/lead correlation analysis between the NAOI and MJOI is found out for each year. It is observed that 20-day lag relationship between NAO and MJO is inverse and significant (0.1 level) and this relationship remains negative throughout the break monsoon period and in active phase it reverses. This twenty days lag relationship between NAO and MJO is potential predictor for break/ active monsoon conditions over the Indian region. The analysis is verified for major drought year 2002.

              In spite of governing industrialization, Indian economy still depends up on the rain-fed agricultural production. Moreover, the summer monsoon rainfall is also important for hydroelectric power generation and achieving drinking water requirements. Therefore, performance of the southwest monsoon over India plays a very crucial role in affecting the quality of life in Indian sub-continent. The southwest monsoon season (June-September) accounts for 80%-90% of the annual rainfall of the country, out of these four months, more than 60% of the seasonal rainfall occurs during July and August, but if  during this period the frequency of  dry/wet spell  prolonged  it affects the agriculture production and create drought/floods situations. In 2002 July and 2004 monsoon season the prolonged dry spells affect the entire monsoon seasonal rainfall.  Therefore, rainfall during the months of July and August; particularly in months of July (since more than 60% of seasonal rainfall occurs during July and August) which is the rainiest month has a decisive role in determining the over all performance of the southwest monsoon and its subsequent impacts.  Most of the operational and experimental forecasts based on statistical and dynamical models (Rajeavan, 2001) are unable to predict such a large-scale deficiency in July 2002.   It has opened new challenges for forecasters/ researchers to examine the monsoon verifiability with new precursors and techniques for the prediction of dry/wet spells in monsoon. However, the state of art atmospheric general circulation models has great difficulty in simulating the monsoon cycle (Waliser et al., 2003).

            The daily monsoon rainfall has high temporal and spatial variability. This daily variability is due to synoptic events. Hence, predictability of daily rainfall is limited due to the predictability of synoptic events. Therefore, the prediction of daily rainfall more than 3-5 days in advance is difficult. However, monsoon rainfall and circulation have low frequency intraseasonal oscillation (ISO) with dominant periods between 10-20days and 30-40 days. This quasi-periodic nature may render enhanced potential predictability of the monsoon ISO. Prince K Xavier and Goswami (2004) have shown that the transitions from break to active conditions are much more chaotic than those from active to break and makes monsoon breaks more predictable than active monsoon condition. The potential predictability limit for monsoon break is about 20 days while that for active conditions is about 10 days.

             Active and break episodes, characteristics of sub- seasonal variation of the Indian summer monsoon are associated with increased ( Decreased) rainfall over central and western India and decreased ( Increased) rainfall over southern peninsula and eastern India (Singh et al. 1992 ; Krishnamurthy and Shukla 2000).  The intraseasonal variations of rainfall (active-break cycle) are strongly coupled to ISO (Hartmann and Michelson, 1989; Webster et al., 1998; Sperber et al., 2000; Goswami and Ajaya Mohan, 2001).

             The Indian summer monsoon exhibits prominent 30-40 days fluctuations with active periods of heavy rain interrupted by dry “breaks” (Gadgil, 2003; Krishnamurti and Bhalme, 1976). The circulation anomalies associated with active/ break monsoons cover up the entire Indian Ocean and influence remote tropics and North Pacific Ocean (Webster et al. 1998).

             Previous  studies have established that the active/ break monsoons are triggered by organized northward propagation of heavy  precipitating or cloud free zones from the equatorial region towards the continental landmass (Yasunari, 1979; Sikka and Gadgil, 1980). However, a question arises of some consequences i.e. where and how the convective anomalies bring active and break cycles?  There is some support for the idea that the upper-level divergent waves associated with Madden and jullian (1971) Oscillation (MJO) that circumnavigate the globe, could re-initiate convective anomalies over the Indian Ocean (Lorenc, 1984, Lau and Chan, 1986). However, Salby and Hendon (1994) show that the decorrelation time of MJO is less than 1 cycle. Hence, one event tends not to follow another. During boreal summer the equatorial eastward propagating MJO weakens substantially (Hendon and Salby 1994) and some northward propagating episodes are independent of MJO (Wang and Rai, 1990).Whether we could get signal from NAO about the weaking of the eastward propagating MJO over the Indian Ocean remains to be examined to predict active/break cycle in monsoon season.

            Matthews and Kiladis (1999) have proposed tropical-extra tropical interaction as a possible mechanism for the initiation of the convective cycle of MJO in the Indian Ocean. Propagation of extra tropical waves in to the tropical Indian Ocean region has been shown to initiate the MJO in case studies (Hsu et al., 1990) and simple modeling studies (Blade and Hartmann, 1993).

            For explanation of this tropical extra tropical interaction we analyzed the daily NCEP/NCAR data. The OLR data for the period 1958-2003 and NAO correlation analysis shown in figure-1 (a) and divergence at 200 hPa level Figure-2 (b). From this, it seen that during the positive phase of NAO upper level divergence at 200hPa over Indian land/ ocean region is negatively correlated.  This means that when the NAO is stronger than the upper level divergence field is weak that affects the convention in Indian Ocean and near by region. This is also observed in figure-1 (a) between OLR and NAO.

Figure 1(a) Association of 20-day lag-lead relationship between NAO and MJO with 20-day mean rainfall in monsoon season for drought year 1987

 Figure1(b): Association of 20-day lag-lead relationship between NAO and MJO with 20-day mean rainfall in monsoon season for  normal monsoon year 1982.

Figure1(c ): Association of 20-day lag-lead relationship between NAO and MJO with 20-day mean rainfall in monsoon season for  good monsoon year 1988

              As it is known that the tropical-extra tropical interaction through NAO and Pacific North American (PNA) pattern and coupling between the NAO and MJO through the upper level divergent wave that circumnavigate the globe, which could re-initiate convective anomalies over Indian Ocean (Wang et al.,2000). This divergent wave may be perturbed by large-scale mid-latitude oscillation like NAO, NPA and North Pacific Oscillation (NPO). To see the effect of NAO on the divergence at 200 hPa over the Indian region the NCEP/NCAR Reanalysis data at 200 h Pa grid point is correlated with the monthly NAO index. The lag-lead relationship between NAO and divergence at 200 h Pa is calculated for the 38 years (1958-1997) figure-1(b) and it is seen that the over Indian region the relationship is inverse it means when NAO is stronger  than normal then next phase followed a negative divergence and hence the suppressed convention and subsequently sub due rainfall activity.

Data details

                 The daily Madden Julian Oscillation index time series for the period 1979 to 2001 is taken from the Eric Maloney of Oregon Sate University. He constructed these indices from the  first 2 principal components of the band pass filtered 30-90 days 850 h Pa 5°N-5°s zonal wind from the National centers for Atmospheric Research reanalysis. Daily North Atlantic Oscillation index data have been taken from the web site   http://www.cpc.ncep.noaa.gov/ for the same period. Daily NCEP/NCAR reanalyzed Out going Long Radiation (OLR) and divergence at 200 hPa level data for 1958-2003 and 1958-1996 (figure A&B) have been taken for the analysis (Kalnay et al., 1996). We used the daily rainfall data at 1°by 1° resolution from the India Meteorological Department (IMD), based on 1803 stations (Rajeevan et al., 2006) for the period 1951-2000.

                  we have computed the lag-lead correlation between daily NAO and MJO index data for the monsoon period. The analysis of North Atlantic Oscillation Index (NAOI) and Madden Julian Oscillation Index (MJOI) on daily scale is carried out in relation to daily Indian summer monsoon rainfall (June-September). Figure 1(a, b, c,) shows the 20 days lag-lead relationship between NAO and MJO and it association with the 20 days mean rainfall anomalies for the drought (1987), Normal (1997) and flood (1988). From the figure it is observed that prior to the break/ active spell of monsoon rainfall the combined relationship between NAO and MJO is negative/ positive respectively. The composite analysis for all droughts and flood years also shown in figure 2(a, b). It seen that lag-lead relationship between NAO, MJO, and 20 days mean rainfall anomalies is going hand in hand. The analysis is carried out for period 1979-2001.  Since the potential predictability limit for monsoon break is about 20 days, the 20 days running lag/lead correlation analysis between the NAOI and MJOI is found out for each year. It is observed that 20-day lag relationship between NAO and MJO is inverse and significant (0.1 level) and this relationship remains negative throughout the break monsoon period and in active phase it reverses. This twenty days lag relationship between NAO and MJO is potential predictor for break/ active monsoon condition over Indian region. The analysis is verified for major drought year 2002.

  Figure (B): The lag- leads relationship between NAO and divergence at 200hPa during  monsoon season for period 1958-2003

                    Probable physical linkage for using this relationship for predicting the dry/wet spell in monsoons period could be like this, previous studies have established that the active/break monsoon are triggered by organized northward propagation of heavy precipitating or cloud free zones from the equatorial regions towards the continental land mass. This northward propagating mode (NPM) over the Indian monsoon region was weaker (stronger) during drought (flood). It is also known that the MJO interacts with the NPM in the Indian monsoon region; it is plausible that the different phases of NAO modulate the temperature gradients cold/warm in upper troposphere. Hence, it might be responsible for the increase in the period of the NPM. A longer period NPM could possibly lead to longer monsoon break periods causing the major drought condition and vise versa.

Acknowledgment:The authors are grateful to Prof. B.N. Goswami Director, I.I.T.M. for providing necessary facilities for completing this study and to Dr. P. N. Mahajan, Head, Forecasting Research Division, for his encouragement and valuable suggestions. Thanks are due to the NOAA/ESRL Physical Sciences Division, Boulder Colorado for their Web site at http://www.cdc.noaa.gov/. and India Meteorology Department for providing the rainfall data.

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About the Author

Dugam Surendra Sidram is a scientist of Indian Institute of Tropical Meteorology, Pune. He has over 30 years experience in LRF study. He has successfully completed study on ‘Monsoon variability in relation to NAO and ENSO and its use for predicting monsoon rainfall over smaller spatial and temporal scale’. He has over 50 research papers to his cradit and guided several students for M.Sc. project.