National Centre for Medium Range Weather Forecasting

About: National Centre for Medium Range Weather Forecasting is a government organization based out in Noida, India. It is known for research contribution in the topics: Monsoon & Weather Research and Forecasting Model. The organization has 176 authors who have published 368 publications receiving 4749 citations.

Modulation of low frequency intraseasonal oscillations of northern summer monsoon by El Nino and Southern Oscillation (ENSO)

Abstract: In order to improve our understanding of the interannual variability of the 30–50 day oscillations of the northern summer monsoon, we have performed numerical experiments using a 5-level global spectral model (GSM). By intercomparing the GSM simulations of a control summer experiment (E1) and a warm ENSO experiment (E2) we have examined the sensitivity of the low frequency intraseasonal monsoonal modes to changes in the planetary scale component of the monsoon induced by anomalous heating in the equatorial eastern Pacific during a warm ENSO phase. It is found that the anomalous heating in the equatorial eastern Pacific induces circulation changes which correspond to weakening of the time-mean divergent planetary scale circulation in the equatorial western Pacific, weakening of the east-west Walker cell over the western Pacific ocean, weakening of the time-mean Reverse Hadley circulation (RHC) over the summer monsoon region and strengthening of the time-mean divergent circulation and the subtropical jet stream over the eastern Pacific and Atlantic oceans. These changes in the large scale basic flow induced by the anomalous heat source are found to significantly affect the propagation characteristics of the 30–50 day oscillations. It is noticed that the reduction (increase) in the intensity of the time-mean divergent circulation in the equatorial western (eastern) Pacific sectors produces weaker (stronger) low-level convergence as a result of which the amplitude of the eastward propagating 30–50 day divergent wave decreases (increases) in the western (eastern) Pacific sectors in E2. One of the striking aspects is that the eastward propagating equatorial wave arrives over the Indian longitudes more regularly in the warm ENSO experiment (E2). The GSM simulations reveal several small scale east-west cells in the longitudinal belt between 0–130°E in the E1 experiment. On the other hand the intraseasonal oscillations in E2 show fewer east-west cells having longer zonal scales. The stronger suppression of small scale east-west cells in E2 probably accounts for the greater regularity of the 30–50 day oscillations over the Indian longitudes in this case. The interaction between the monsoon RHC and the equatorial 30–50 day waves leads to excitation of northward propagating modes over the Indian subcontinent in both cases. It is found that the zonal wind perturbations migrate northward at a rate of about 0.8° latitude per day in E1 while they have a slightly faster propagation speed of about 1° latitude per day in E2. The low frequency monsoonal modes have smaller amplitude but possess greater regularity in E2 relative to E1. As the wavelet trains of low latitude anomalies progress northward it is found that the giant meridional monsoonal circulation (RHC) undergoes well-defined intraseasonal oscillations. The amplitude of the monsoon RHC oscillations are significantly weaker in E2 as compared to E1. But what is more important is that the RHC is found to oscillate rapidly with a period of 40 days in E1 while it executes slower oscillations of 55 days period in E2. These results support the observational findings of Yasunari (1980) who showed that the cloudiness fluctuations on the 30–60 day time scale over the Indian summer monsoon region are associated with longer periods during El Nino years. The oscillations of the monsoon RHC show an enhancement of the larger scale meridional cells and also a stronger suppression of the smaller scale cells in E2 relative to E1 which seems to account for the slower fluctuations of the monsoon RHC in the warm ENSO experiment. It is also proposed that the periodic arrival of the eastward propagating equatorial wave over the Indian longitudes followed by a stronger inhibition of the smaller meridional scales happen to be the two primary mechanisms that favour steady and regular northward propagation of intraseasonal transients over the Indian subcontinent in the warm ENSO experiment (E2). This study clearly demonstrates that the presence of E1 Nino related summertime SST anomalies and associated convection anomalies in the tropical central and eastern Pacific are favourable criteria for the detection and prediction of low frequency monsoonal modes over India.

Bias correction of maximum temperature forecasts over India during March-May 2017

Abstract: In recent times, instances of intense heat waves have increased over the Indian subcontinent. This increase in temperature has an adverse effect on human health and the economy. Over India, such high temperatures are usually seen during the months of March–May (summer). For weather forecasters, it is a challenging job to accurately predict the timing and intensity of this anomalous high temperature. The difficulty in the accurate prediction of weather is increased because of the presence of systematic biases in the models. These biases are present because of improper parameterizations or model physics. For increasing the reliability or accuracy of a forecast it is essential to remove these biases by using a process called post-processing. In this study the biases in the surface temperature maximum are corrected using two methods, namely, the moving average and the decaying average. One of the main advantages of both the methods is that they do not require a large amount of past data for calibration and they take into account the most recent behaviour of the forecasting system. Verification, for maximum surface temperature during March–May 2017, was carried out in order to decide upon the method giving the best temperature forecast. It was found that both the bias correction methods lead to a decrease in the mean error in maximum surface temperature (Tmax). However, the decaying average method showed a higher decrease in the mean error. Scores obtained from a contingency table like POD, FAR and PSS, showed that for Tmax, the decaying average method outperforms the forecasts, i.e., raw and moving average in terms of having high POD and PSS and a low FAR.

Operational mesoscale atmospheric dispersion prediction using a parallel computing cluster

Abstract: An operational atmospheric dispersion prediction system is implemented on a cluster supercomputer for Online Emergency Response at the Kalpakkam nuclear site. This numerical system constitutes a parallel version of a nested grid meso-scale meteorological model MM5 coupled to a random walk particle dispersion model FLEXPART. The system provides 48-hour forecast of the local weather and radioactive plume dispersion due to hypothetical airborne releases in a range of 100 km around the site. The parallel code was implemented on different cluster configurations like distributed and shared memory systems. A 16-node dual Xeon distributed memory gigabit ethernet cluster has been found sufficient for operational applications. The runtime of a triple nested domain MM5 is about 4 h for a 24 h forecast. The system had been operated continuously for a few months and results were ported on the IMSc home page. Initial and periodic boundary condition data for MM5 are provided by NCMRWF, New Delhi. An alternative source is found to be NCEP, USA. These two sources provide the input data to the operational models at different spatial and temporal resolutions using different assimilation methods. A comparative study on the results of forecast is presented using these two data sources for present operational use. Improvement is noticed in rainfall forecasts that used NCEP data, probably because of its high spatial and temporal resolution

Simulation of heavy rainfall event along east coast of India using WRF modeling system: impact of 3DVAR data assimilation

Abstract: The study is evaluated the impact of WRF three dimensional Variational (3DVAR) data assimilation for simulation of a heavy rainfall event due to the presence of the monsoon depression (MD) along the east coast of India. In this purpose, two numerical experiments are carried out such as CNTL (without data assimilation) and 3DV (with assimilation of observations from Global Telecommunication System) for simulation of the heavy rainfall event occurred during 16–21 August 2016 over Indian region. The model is integrated upto 120 h starting at 00 UTC of 16th August 2016 in both the experiments. The results demonstrate that the model with resulting high-resolution reanalyses from 3DV produced reasonably well simulated the location and intensity of rainfall due to the presence of the MD. The model simulated mean sea level pressure (MSLP), vertical structure, track and direct position errors (DPEs) of the MD reasonably well represented in the assimilation experiment (3DV). The statistical skill scores viz. Equitable Thereat Score (ETS) and bias with various thresholds of the rainfall are improved in the 3DV experiment as compared to the CNTL experiment. The present study clearly suggested that the data assimilation (3DVAR) has a positive impact on the simulation of the heavy rainfall event.