Rainfall Estimation using Image Processing and Regression Model on DWR Rainfall Product for Delhi-NCR Region

Observed rainfall is a very essential parameter for the analysis of rainfall,day to day weather forecast and its validation.The observed rainfall data is only available from five observatories of IMD;while no rainfall data is available at various important locations in and around Delhi-NCR.However,the 24-hour rainfall data observed by Doppler Weather Radar(DWR)for entire Delhi and surrounding region(up to 150 km)is readily available in a pictorial form.In this paper,efforts have been made to derive/estimate the rainfall at desired locations using DWR hydrological products.Firstly,the rainfall at desired locations has been estimated from the precipitation accumulation product(PAC)of the DWR using image processing in Python language.After this,a linear regression model using the least square method has been developed in R language.Estimated and observed rainfall data of year 2018(July,August and September)was used to train the model.After this,the model was tested on rainfall data of year 2019(July,August and September)and validated.With the use of linear regression model,the error in mean rainfall estimation reduced by 46.58% and the error in max rainfall estimation reduced by 84.53% for the year 2019.The error in mean rainfall estimation reduced by 81.36% and the error in max rainfall estimation reduced by 33.81%for the year 2018.Thus,the rainfall can be estimated with a fair degree of accuracy at desired locations within the range of the Doppler Weather Radar using the radar rainfall products and the developed linear regression model.

Thumb Rule for Nowcast of Dust Storm and Strong Squally Winds over Delhi NCR using DWR Data

Squally winds are the natural hazards and are often associated with the severe thunderstorms(TS),which mostly affects plains of North West India during pre monsoon season(March to May).Squally winds of the order more than 60 kmph are very devastating.Under influence of these strong squally winds trees,electricity poles,advertisement sign boards fall,sometimes human life is also lost.The main objective of this study is to find out the thumb rule based on Doppler Weather Radar(DWR)Data to Nowcast the squally winds over a region.To detect thumb rule,five cases of thunder storm accompanied with squally winds ranging from(55 kmph to 110 kmph)are taken in to consideration.These TS’s occurred over Delhi NCR(National Capital Region)during May-June 2018.Maximum reflectivity(Max Z)data of Delhi DWR,Cloud Top Temperature(CTT)data from INSAT and squally winds along with other weather parameters observed at Safdarjung and Palam observatories are utilized to find out the Thumb Rule.Based on the analysis,it is concluded that presence of a western disturbance(WD),presence of East-West trough from North-west Rajasthan upto East UP through south Haryana and very high temperature of the order of 40 degree Celsius over the nearby area are very conducive for occurrence of squally winds accompanied with thunderstorms.Thumb rule find out in this study is that,squally winds of the order of 55 kmph or more will effect a station if a thunderstorm(having Max Z echo with vertical extension of cell>7 km,reflectivity>45 dBz and at a distance of more than 100 km from the station)moving towards station is present in one to two hour before images of Doppler Weather Radar.

Significant Improvement in Rainfall Forecast over Delhi:Annual and Seasonal Verification

Regional Weather Forecasting Centre(RWFC)New Delhi has the responsibility to issue and disseminate rainfall forecast for Delhi.So it is very important to scientifically verify the rainfall forecast issued by RWFC.In this study rainfall forecast verification of Delhi has been carried out annually and season wise for the period 2011 to 2021.Various statistical parameters such as Percentage Correct(PC),Probability of Detection(POD),Missing Ratio(MR),False Alarm Ratio(FAR),Critical Success Index(CSI),True Skill Statistics(TSS)and Heidke Skill Score(HSS)have been calculated for season wise and annually.A forecast is considered to be improved if PC,POD,CSI,TSS and HSS increase and FAR and MR decrease over a period of time.The author can conclude that annual accuracy of forecast has increased significantly over the period of time from 2011 to 2021,as PC,POD,CSI,TSS and HSS increase and FAR and MR decrease over a period of time.Maximum contribution in the improved forecast has observed in transition season(pre-monsoon season followed by post-monsoon,having rainfall activity mainly in association with thunderstorms),when FAR and MR have decreased drastically.