Search Results

You are looking at 1 - 10 of 15 items for

  • Author or Editor: S. V. Singh x
  • Refine by Access: All Content x
Clear All Modify Search
S. V. Singh and R. H. Kripalani

Abstract

The potential predictability of the lower tropospheric circulation and the rainfall over India during the peak summer monsoon season (July–August) is studied by analyzing the signal-to-noise ratio. Daily 700-mb heights, mean sea level pressure anomaly and rainfall at 220 stations for 21, 30 and 19 years, respectively, are used to represent the circulation and rainfall fields. The predictability of the circulation fields in general increases with decreasing latitude but is low over the area normally occupied by the monsoon trough. The potential predictability of rainfall is about 50% over the major parts of the country.

Full access
S. V. Singh and R. H. Kripalani

Abstract

No abstract available.

Full access
Ashok Kumar, Parvinder Maini, and S. V. Singh

Abstract

An operational system for forecasting probability of precipitation (PoP) and yes/no forecast over 10 stations during monsoon season is developed. A perfect prog method (PPM) approach is followed for statistical interpretation of numerical weather prediction products. PPM model equations are developed by using analysis data obtained from the European Centre for Medium-Range Weather Forecasts for a period of 6 yr (1985–90). PoP forecasts are obtained from these equations by using global T-80 model output, which was installed at the National Centre for Medium Range Weather Forecasting in 1993. Results of verification study conducted during the monsoon season of 1995 covering various aspects of forecast skill and quality are also described.

Full access
K. D. Prasad and S. V. Singh

Abstract

Three selected parameters have been analyzed for the spatial and temporal relationships with the Indian monsoon rainfall. These parameters are (i) the subtropical ridge position at 500 hPa over India in April, (ii) January–April Darwin surface pressure tendency, and (iii) January and February Northern Hemispheric surface air temperature. Multiple regression equations have been developed for forecasting monsoon rainfall on bimonthly to seasonal scales and on subdivisional to all-India scales. All equations have been verified by independent data.

We obtain positive skill in forecasting the seasonal rainfall of not only all of India but also of its three large subregions and meteorological subdivisions lying in west-central parts of the country. Also, the skill is generally better for the forecast of rainfall for the latter half of the monsoon season than the whole season.

Full access
S. V. Singh and R. H. Kripalani

Abstract

Extended empirical orthogonal function (EEOF) analysis has been employed to study linear relationships among the mean sea level pressure, 700 mb height and rainfall over India, and their low-frequency sequential evolution during the peak summer monsoon months. The interrelationships between these fields are strongest over central India and, while the rainfall activity is colocated with the corresponding changes in the 700 mb heights, it is displaced southward with respect to the pressure changes. The first two EEOF's of all the three fields (averaged over 5 or 7 days) show that the dominant low-frequency sequential evolution is associated with north and northeastward movement of the anomaly centers with a recurrence period of about 40 days. In addition, the presence of a westward moving wave in sea level pressure anomalies located roughly near 15°N latitude is revealed by the third EEOF.

Full access
Parvinder Maini, Ashok Kumar, L. S. Rathore, and S. V. Singh

Abstract

The inability of a general circulation model (GCM) to predict the surface weather parameters accurately necessitates statistical interpretation of numerical weather prediction (NWP) model output. Here a system for forecasting maximum and minimum temperatures has been developed and implemented for 12 locations in India based on the perfect prog method (PPM) approach. The analyzed data from the ECMWF for a period of 6 yr (1985–90) are used to develop PPM model equations. Daily forecasts for maximum and minimum temperatures are then obtained from these equations by using T-80 model output. In order to assess the skill and quality of the temperature forecasts, an attempt has been made to verify them by employing the conditional and marginal distribution of forecasts and observations using the data of four monsoon seasons from 1997 through 2000.

Full access
S. V. Singh, D. A. Mooley, and R. H. Kripalani

Abstract

The daily (mean of 0000 and 1200 GMT) 700 mb contour patterns over India are classified in five broad types for each summer monsoon month by using a chart-to-chart correlation method. Certain characteristics of these patterns, such as mutual transitions, persistence, preferred periods of occurrence and interrelationships are studied. Statistical probabilities of two threshold 24 h rainfall amounts (2.5 and 10 mm) being equated or exceeded for each type are computed for 107 stations, more or less uniformly distributed over India. This knowledge of the spatial distribution of precipitation probabilities associated with various circulation types can be used in forecasting probabilities of precipitation over the country if the circulation patterns can he forecast by numerical methods. These probabilities are then compared to the climatological and conditional probabilities of obtaining threshold rainfall amounts on different days of the subsequent 5-day period—given that the threshold rainfall occurred on the current day. The results, if averaged for all types and months, show that persistence is superior to the synoptic climatology developed in this study for forecasting precipitation probability for the next day over an regions and for forecasting precipitation probability up to 2–4 days—depending on region and threshold rainfall criteria. Synoptic climatology is superior to persistence as an aid for forecasting precipitation probability after 4 days over all the regions. Some shortcomings of the present study and future plans are described briefly.

Full access
S. V. Singh, R. H. Kripalani, and D. R. Sikka

Abstract

The Madden-Julian oscillations are quite prominent over the Indian monsoon region and they are related with the large-scale active-break phases of the monsoon. These oscillations, however, show considerable inter-annual variability in period and intensity. In this study interannual variability of these oscillations has been studied by using daily rainfall data of 365 stations for 80 years (1901–80). It is found that the intensity of these oscillations is not related with the overall performance of the monsoon and the El Niño–Southern Oscillation phenomenon.

Full access
Someshwar Das, S. V. Singh, E. N. Rajagopal, and Robert Gall

Severe weather has a more calamitous effect in the mountainous region because the terrain is complex and the economy is poorly developed and fragile. Such weather systems occurring on a small spatiotemporal scale invite application of models with fine-grid resolution and observations from radars and satellites besides the conventional observations for forecasting and disaster mitigation.

Full access
S. A. Saseendran, S. V. Singh, L. S. Rathore, and Someshwar Das

Abstract

Weekly cumulative rainfall forecasts were made for the meteorologically homogeneous areas of the Indian subcontinent, divided into meteorological subdivisions, by performing 7-day integrations of the operational Indian T80 Global Spectral Model every Wednesday during the six southwest monsoon seasons of 1994–99. Objective evaluations of the bias and accuracy of these forecasts during that 6-yr period are made through various forecast verification methods and are presented here. The skill or relative accuracy of the forecasts and some verification measures are quantified by computing the Heidke skill score (HSS), Hanssen–Kuipers discriminant (HKS), threat score (TS), hit rate (HR), probability of detection (POD), bias score, and false-alarm rate (FAR). The study revealed that the T80 model has a tendency to underpredict rainfall over most of the subdivisions falling on the windward side of the Western Ghats and sub-Himalayan areas. The model exhibited negative bias in rainfall simulations over the desert regions of Rajasthan and over the Arabian Sea and bay islands. There is a positive bias in the rainfall simulated over the subdivisions falling in the rain-shadow regions of the Western Ghats. The TS, POD, and FAR computations show that the predicted weekly rainfall over different subdivisions in the excess and scanty categories has more skill than those in the normal and deficient categories. The HR values range from 0.21 to 1 over different subdivisions. The HSS and HKS scores indicate better skill in rainfall forecast in the central belt of India where the orographic influence over rainfall distribution is comparatively less. Better correspondence between the magnitude of the predicted and observed rainfall is apparent in the all-India time series of weekly cumulative rainfall.

Full access