Search Results

You are looking at 11 - 13 of 13 items for

  • Author or Editor: D. A. Mooley x
  • Refine by Access: All Content x
Clear All Modify Search
D. A. Mooley
,
B. Parthasarathy
, and
G. B. Pant

Abstract

Banerjee et al. showed for the first time that the number of Indian subdivisions with normal or above-normal monsoon rainfall is related to the location of the April 500-mb ridge along 75°E. Thapliyal brought out the relationship between monsoon rainfall of peninsular India and this ridge.

A detailed investigation of the relationship between all-India (India taken as one unit) monsoon rainfall, as well as monsoon rainfall of the subdivisions of India, and the location of the April 500-mb ridge along 75°E, and of the stability and consistency of the relationship has been made in this study, which is based on data for 1939–84. The relationship between all-India monsoon rainfall and the ridge location is positive (correlation coefficient = 0.71) and is significant at the 0.1% level and that between the subdivisional monsoon rainfall and the ridge is significant at 5% or above for all the subdivisions lying west of 84°E and north of 12°N. During the years when all-India monsoon rainfall is deficient, the ridge position is south of its normal position and the contribution by these years to the covariance is very high.

The stability and consistency of the relationship between all-India rainfall and the ridge location have been examined over sliding 10-, 15-, and 20-year periods, and it is found that the relationship is significant at the 1% level for all 20-yeat periods. Thus the relationship is characterized by high stability and consistency for periods of 20 years or more.

The contingency table for the two parameters shows that when the ridge is south of the mean position by more than one standard deviation, all-India rainfall is deficient on 80% of such occasions and that when the ridge is similarly located to the north of the mean, all-India rainfall is excessive on two-thirds of such occasions. The regression equation between all-India monsoon rainfall (y, in cm) and the ridge location (x, in degrees), based on data for the period 1939–80, is y = 38.02 + 3.10x. This relationship explains about 53% of the total variance. So far, the ridge location appears to be the only single parameter that explains such a high percentage of the variance of all-India monsoon rainfall. Estimates from this relationship for the independent years 1981–84 are found to be quite good, except for 1983, the year of excessive rainfall.

The southernmost ridge location was 11°N and the northernmost, about 18°N. It is intriguing to find that a variation of 7° in the latitude of the ridge location over western peninsular India during April makes a large difference in all-India monsoon rainfall (from deficient to excessive). Possibly, the ridge locations with relatively high departures from the normal in April have a tendency to persist, resulting in early or delayed transition to the tropospheric conditions from premonsoon season to the monsoon season.

Full access
H. N. Bhalme
,
D. A. Mooley
, and
S. K. Jadhav

Abstract

An objective numerical drought/flood index has been used to obtain, on the dryness side, the Drought Area Index (DAI) and on the wetness side, the Flood Area Index (FAI) for India for the period 1891–1979. The DAI for a given year is the percentage area of India corresponding to a mean monsoon index with drought intensity ≤ −2 (moderate drought or worse). Likewise, on the wetness side, the Flood Area Index (FAI) for the given year is the percentage area of India corresponding to a mean monsoon index with flood intensity ⩾ +2 (moderate flood or worse), where the mean monsoon index of an area is the mean drought/flood index for the four monsoon months (June-September). A year with DAI/FAI ⩾ 25, i.e., 25% of the country area, is identified as a large-scale drought/good year, respectively. The magnitude 25 used in identifying large-scale drought/flood corresponds approximately to twice the standard deviation of the DAI/FAI series.

The large-scale April Pressure Index (PI) of the Southern Oscillation has been devised with the combination of surface pressure of stations from Australia, India, Indonesia and South America. The fluctuations of PI covering a period of 89 years (1891–1979) and its relation to the DAI and FAI have been examined. The study indicates a significant inverse relationship between the PI and DAI series. This implies that the 1arge negative PI value, significant weakening of the southeast trades over the Indo-Pacific region tends to coincide with a large DAI value, meaning a 1arge area affected by drought during the subsequent monsoon and vice versa. The PI and FAI am significantly positively correlated. This implies that a large positive value of PI, signifying strengthening of the southeast trades tends to correspond to a large value of FAI, meaning a large area affected by flood during the monsoon and vice versa. The spectrum and cross-spectrum analysis of the PI and DAI series suggest that significant correlation between the PI and DAI is mostly due to the oscillations in the range of 3–6 years. The maximum coherence falls over a period of about 3 years. Furthermore, an oscillation of ∼3 years in a climatic element such as DAI arises primarily as a result of the Southern 0scillation. The Southern Oscillation appears to be one possible causal climatic phenomenon for introducing a most common period of anything from 3 to 6 years for the recurrence of tame-scale droughts over India.

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