The simultaneous effect of NAO and SO on the monsoon activity over India

North Atlantic Oscillation (NAO) and Southern Oscillation (SO) are two large-scale atmospheric oscillations in northern and southern hemisphere respectively. These two oscillations are known to affect Indian summer monsoon (June-September) rainfall (ISMR). It is logical to expect the combined effect of these two oscillations on monsoon rainfall over Indian subcontinent. In the present paper this combined effect of NAO and SO on Indian summer monsoon rainfall is studied. North Atlantic Oscillation (NAO) index in the month of April is showing an inverse and statistically significant relationship with Indian summer monsoon rainfall (ISMR). Southern oscillation (SO) indices from April through December show direct association with ISMR. The present study deals with the simultaneous effect of NAO and SO on monsoon rainfall over India. The effective strength index is newly defined to quantify the simultaneous effect of NAO and SO and its relationship with ISMR is investigated. For this purpose 40 years data (1951-90) has been used. The study emphasizes an important role of interaction between NAO and SO in the month of April. It also emphasizes that monsoon activity over India depends upon the strength of both the oscillations namely NAO and SO. The analysis suggests that the effective strength index can be used as a pre-cursor to understand the extreme monsoon events. The analysis also suggests an inverse association of ISMR with the effective strength index from April through December with statistically significant relationship in the months of April, October, November and December

Prediction of Indian summer monsoon rainfall using surface temperature and sea-level pressure cluster parameters

The scientific community has been putting in continuous efforts to improve long-range forecast of Indian summer monsoon rainfall (ISMR). In this study we try to search for new predictors which may improve the prediction of ISMR. The shared nearest neighbour technique has been applied to surface temperature (ST) and sea-level pressure (SLP) to obtain the clusters in pre-monsoon months (January through May) and seasons (winter, spring). The powers of time series averaged over the clusters are used as parameters for predicting ISMR. Instead of a single prediction equation, two separate equations are developed based on the positive and negative phase of effective strength index (ESI) tendency. Simple multiple regression equations are developed using these cluster parameters for predicting ISMR during the contrasting phases of ESI tendency. During positive (negative) phase of ESI tendency, the SLP (ST) cluster parameters can predict ISMR. The prediction of ISMR is improved if we use the prediction equation depending upon the phase of ESI tendency

Indian monsoon variability in relation to Regional Pressure Index

In this paper Regional Pressure Index (RPI) over the Indian region (20°N-40°N and 70°E-85°E) has been constructed for 101 years (1899-1999) on a monthly scale. The relationship of these indices was carried out with the Indian Summer Monsoon Rainfall (June-September) (ISMR) over the various homogeneous regions, for all the time scales. From the analysis it has been seen that RPI in the month of May is significantly associated with ISMR over various regions on all the scales. The relationship is statistically significant at 1 level. The study reveals that RPI in the month of May and January will be a new precursor for the long range forecasting of ISMR on the smaller spatial scale. On the decadal and climatological scale, winter and spring time RPI show a significant inverse relationship with the rainfall over the regions Peninsular India (PI) and North West India (NWI), while the association is direct with Central North East India (CNEI) and North East India (NEI). The relationship is significant at 0.1 and 1 level respectively

The changing relationship between surface temperatures and Indian monsoon rainfall with the phase of ESI tendency

ffective Strength Index (ESI) is the relative strength of NAO and SO. ESI tendency is the algebraic difference between April-ESI and January-ESI and it represents the simultaneous evolution of NAO and SO from winter to spring. During positive (negative) phase of ESI tendency, NAO restores positive (negative) phase and SO restores negative (positive) phase before the beginning of summer season. Thus during contrasting phases (positive and negative) of ESI tendency, the evolution of NAO and SO is out of phase. In this paper we have studied the spatial and temporal variability of winter-time temperature field over Europe, Arabian Sea and Bay of Bengal during contrasting phases of ESI tendency. The study reveals that during positive (negative) ESI tendency, smaller (larger) region of Europe is showing significant winter-time cooling (warming) at surface. The relationship between winter-time surface temperature over above regions and Indian summer monsoon rainfall (ISMR) also shows spatial and temporal variability. The probable explanation for this change in the relationship is discussed in the paper. Two sets of temperature parameters for two different phases of ESI tendency are found out. Multiple regression equations are developed for the prediction of ISMR in each phase of ESI tendency. The performance of these equations is also discussed in this paper

Spatial monsoon variability with respect to NAO and SO

In this paper, the simultaneous effect of North Atlantic Oscillation (NAO) and Southern Oscillation (SO) on monsoon rainfall over different homogeneous regions/subdivisions of India is studied. The simultaneous effect of both NAO and SO on Indian summer monsoon rainfall (ISMR) is more important than their individual impact because both the oscillations exist simultaneously throughout the year. To represent the simultaneous impact of NAO and SO, an index called effective strength index (ESI) has been defined on the basis of monthly NAO and SO indices. The variation in the tendency of ESI from January through April has been analyzed and reveals that when this tendency is decreasing, then the ESI value throughout the monsoon season (June-September) of the year remains negative and vice versa. This study further suggests that during the negative phase of ESI tendency, almost all subdivisions of India show above-normal rainfall and vice versa. The correlation analysis indicates that the ESI-tendency is showing an inverse and statistically significant relationship with rainfall over 14 subdivisions of India. Area wise, about 50 of the total area of India shows statistically significant association. Moreover, the ESI-tendency shows a significant relationship with rainfall over north west India, west central India, central north east India, peninsular India and India as a whole. Thus, ESI-tendency can be used as a precursor for the prediction of Indian summer monsoon rainfall on a smaller spatial scale

Pre-monsoon Zonal Wind Index over Tibetan Plateau and sub-seasonal Indian summer monsoon rainfall variability

In this paper, by using the Principal Component Analysis (PCA) technique monthly zonal wind indices over Tibetan Plateau (25°N-45°N, 75-105°E) (TP) at 200 hPa have been constructed for the period 1948-2006. These indices are referred as Tibetan Zonal Wind Index (TZWI). The relationship between the TZWI and Indian summer monsoon rainfall on monthly basis has been studied by the correlation analysis. From the analysis, it is observed that pre-monsoon months (April and May) of TZWI show the significant inverse relationship with June and July rainfall over India respectively. The study may be useful for forecasting rainfall activity in June and July months, which are crucial months from the agricultural point of view

Global temperature and monsoon activity

In this paper an attempt has been made to search a new parameter for the prediction of the Indian summer monsoon rainfall. For this purpose the relationship of the global surface-air temperature of four standard seasons viz., Winter (December-January-February), Spring (March-April-May), Summer (June-July-August), Autumn (September-October-November) with the Indian summer monsoon rainfall has been carried out. The same analysis is also carried out with surface-air temperature anomalies within the tropical belt (30°S to 30°N) and Indian summer monsoon rainfall. For the present study data for 30 years period from 1958 to 1988 have been used. The analysis reveals that there is a strong inverse relationship between the monsoon activity and the tropical belt temperature

Dopamine Increases a Value-Independent Gambling Propensity

Although the impact of dopamine on reward learning is well documented, its influence on other aspects of behavior remains the subject of much ongoing work. Dopaminergic drugs are known to increase risk-taking behavior, but the underlying mechanisms for this effect are not clear. We probed dopamine’s role by examining the effect of its precursor L-DOPA on the choices of healthy human participants in an experimental paradigm that allowed particular components of risk to be distinguished. We show that choice behavior depended on a baseline (ie, value-independent) gambling propensity, a gambling preference scaling with the amount/variance, and a value normalization factor. Boosting dopamine levels specifically increased just the value-independent baseline gambling propensity, leaving the other components unaffected. Our results indicate that the influence of dopamine on choice behavior involves a specific modulation of the attractiveness of risky options—a finding with implications for understanding a range of reward-related psychopathologies including addiction