Quantitative precipitation forecasting over Narmada Catchment

Quantitative precipitation forecasting (QPF) has been attempted over the Narmada Catchment following a statistical approach. The catchment has been divided into five sub-regions for the development of QPF models with a maximum lead-time of 24 hours. For this purpose the data of daily rainfall from 56 raingauge stations, twice daily observations on different surface meteorological parameters from 28 meteorological observatories and upper air data from 11 aerological stations for the nine monsoon seasons of 1972-1980 have been utilized. The horizontal divergence, relative vorticity, vertical velocity and moisture divergence are computed using the kinematic method at different pressure levels and used as independent variables along with the rainfall and surface meteorological parameters. Multiple linear regression equations have been developed using the stepwise procedure separately with actual and square root and log-transformed rainfall using 8-year data (1972-1979). When these equations were verified with an independent data for the monsoon season of 1980, it was found that the transformed rainfall equations fared much better compared to the actual rainfall equations. The performance of the forecasts of QPF model compared to the climatological and persistence forecasts has been assessed by computing the verification scores using the forecasts for the monsoon season of 1980

Statistical distribution of daily rainfall and its association with the coefficient of variation of rainfall series

The study focuses attention on the normalized rainfall curve (NRC) depicting the association between cumulated percentage rain amount (x) and cumulated percentage number of rain days (y) of the rainfall series. It is shown that the NRC is uniquely determined by the coefficient of variation (CV) of the rainfall series. There is no universal NRC that can represent all rainfall regimes. The equation x=y exp-b(100-y)c, where b and c are two empirical constants, gives a good analytical representation of the NRCs over a wide range of CV values of the rainfall series. This analytical equation is able to account for the occurrence of high rainfall intensities towards the upper extremity of the NRC for rainfall series with high values of CV

The onset of the southwest monsoon in 1990

statistics relating to the date of onset of the southwest monsoon over kerala for the 100 year period 1891-1990 reveal that the mean and median dates of onset for south kerala are 31 May and 1 June with standard deviation of 8.5 day

Some aspects of daily rainfall distribution over India during the south-west monsoon season

This paper presents the results of an analysis of the daily rainfall at 365 Indian stations for the 80-year period, 1901-1980. The rainfall data relate to the south-west monsoon season June to September (122 days), which accounts for the major part of the annual rainfall over most parts of the country. The coefficient of variation (CV) of the daily rainfall series varies between 100 and 230 at individual stations, with nearly half the number of stations having CV values in the range 130-150. The number of days of significant rainfall (days with rainfall greater than the mean intensity per rain-day) constitute about 30 of the total number of rain-days and account for about 75 of the seasonal rainfall at almost all the stations

The onset of the southwest monsoon over Kerala: 1901-1980

Utilising daily mean rainfall from dense rain gauge networks, the dates of onset of the southwest monsoon over south and north Kerala have been derived on the basis of objective criteria for the years 1901 to 1980. These dates have been compared with the onset dates as per records of the India Meteorological Department. Statistics of the onset dates are presented. The mean onset date for south Kerala is found to be 30 May and for north Kerala 1 June with a standard deviation of about 9 days in both cases. The sharp increase in rainfall that heralds the onset of the monsoon is highlighted by superposed epoch analysis. The prevailing notion that rainfall from pre-monsoon thunderstorms progressively increases and merges with the monsoon rainfall is shown to be not valid

Evaluation of equivalent potential temperature (EPT) from radiosonde data

The pseudo-equivalent potential temperature of sample of air is the temperature it would attain by ascending pseduo-adiabatically till all the water vapour in it has been condense

Onset dates of the south-west monsoon over Kerala for the period 1870-1900

This communication presents the dates on onset of the south-west monsoon over south Kerala for the period 1890-1900 and over north Kerala for the period 1870-1900

Indian summer monsoon onset forecast skill in the UK Met Office initialized coupled seasonal forecasting system (GloSea5-GC2)

Accurate and precise forecasting of the Indian monsoon is important for the socio-economic security of India, with improvements in agriculture and associated sectors from prediction of the monsoon onset. In this study we establish the skill of the UK Met Office coupled initialized global seasonal forecasting system, GloSea5-GC2, in forecasting Indian monsoon onset. We build on previous work that has demonstrated the good skill of GloSea5 at forecasting interannual variations of the seasonal mean Indian monsoon using measures of large-scale circulation and local precipitation. We analyze the summer hindcasts from a set of three springtime start-dates in late April/early May for the 20-year hindcast period (1992-2011). The hindcast set features at least fifteen ensemble members for each year and is analyzed using five different objective monsoon indices. These indices are designed to examine large and local-scale measures of the monsoon circulation, hydrological changes, tropospheric temperature gradient, or rainfall for single value (area-averaged) or grid-point measures of the Indian monsoon onset. There is significant correlation between onset dates in the model and those found in reanalysis. Indices based on large-scale dynamic and thermodynamic indices are better at estimating monsoon onset in the model rather than local-scale dynamical and hydrological indices. This can be attributed to the model's better representation of large-scale dynamics compared to local-scale features. GloSea5 may not be able to predict the exact date of monsoon onset over India, but this study shows that the model has a good ability at predicting category-wise monsoon onset, using early, normal or late tercile categories. Using a grid-point local rainfall onset index, we note that the forecast skill is highest over parts of central India, the Gangetic plains, and parts of coastal India - all zones of extensive agriculture in India. El Niño Southern Oscillation (ENSO) forcing in the model improves the forecast skill of monsoon onset when using a large-scale circulation index, with late monsoon onset coinciding with El Niño conditions and early monsoon onset more common in La Niña years. The results of this study suggest that GloSea5's ensemble-mean forecast may be used for reliable Indian monsoon onset prediction a month in advance despite systematic model errors