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The northeastern depressed region of Bangladesh is highly susceptible to recurrent flash flooding due to excessive rainfall over these areas and in the upstream hilly regions. Two such severe pre-monsoon flash flood events occurred in 2016 and 2017. This research attempts to forecast both flash flood events using a coupled atmospheric-hydrological numerical weather prediction (NWP) model, namely the weather research and forecasting (WRF) model. The ARW (Advanced Research WRF) model is able to predict the rainfall over these areas with a lead time of 91 h. However, the discharge and water level are overestimated by the WRF-Hydro model. The model predicts a flash flood with a lag of approximately 12 h with respect to the highest amount of rainfall. The overall performances of the models were satisfactory. The two parameters, rainfall and subsequent discharge, which are required for delineation of lag time, were almost precisely simulated. Simulated values also had fewer errors, justified by the root mean squared error (RMSE) and mean absolute error values. The Nash–Sutcliffe efficiency criterion scores for model-derived discharge were close to 1.0, and the RMSE-observation standard deviation ratio scores were less than 0.5. This finding proves that the NWP models could be considered for forecasting flash flood events over selected areas of Bangladesh.

The physical and dynamical characteristics of pre-monsoon (March–May) thunderstorms (TS) are investigated over Bangladesh using the Weather Research and Forecasting (WRF) model. The model was run for 24-h using 6-hourly data sets as initial and lateral boundary conditions. The Milbrandt cloud microphysics scheme, Krain–Fritsch cumulus scheme, and Yonsei University planetary boundary layer are found to be the best combination by comparing the root mean square error of rainfall from 18 sensitivity experiments. The synoptic condition and atmospheric instability associated with three TS cases have been analyzed based on mean sea level pressure, convective available potential energy (CAPE), and thermodynamic indices. CAPE is found between 500 and 2700 J kg−1 at 0000 UTC for the TS cases. The presence of low-level southerly wind from the Bay of Bengal and upper-level westerly or north-westerly wind with speeds ranging from 5 to 30 m s−1 is found during the storms. The cloud characteristics and intensity were investigated based on Doppler Weather Radar and INSAT 3DR satellite observations. Cloud micro-physical hydrometeors and other composite features (e.g., cloud top and core precipitation altitude, length of squall line) were also studied by the model and then compared with available observed values. For 24-h rainfall, 2 × 2 contingency tables are computed using Model Evaluation Tools. Categorical skill scores such as proportion correct, frequency bias index, probability of false detection, false alarm ratio, and Gilbert skill score were calculated to evaluate the model's performance. The forecast goodness is found to be reasonably satisfactory after analyzing the significance of the skill scores.

An attempt is made to determine skill of a mesoscale model through calculation of distance, intensity and time errors with respect to observed maximum reflectivity data (maxdBZ) of Doppler Weather Radar (DWR). A new approach is adopted to calculate distance, intensity and time errors of the model simulated thunderstorm events. Five cases of pre-monsoon thunderstorms over the eastern part of India are simulated by Advanced Research WRF (ARW) model and the model simulated maxdBZ is validated against DWR data. In all the cases the model is run from two different initial conditions. The global model forecast of National Centre for Medium Range Weather Forecasting (NCMRWF), India is directly used as the initial condition for the control run (Exp1) while in the other run (Exp2) initial condition is prepared by assimilating local synoptic data with 6 h model forecast taken as background. The spatial distributions of model simulated and observed maxdBZ show that the newly adopted method is capable of capturing the model skill through computation of distance error. This newly adopted method is used to investigate whether the model simulation with data assimilation is more skillful in determining distance, intensity and time errors. In all the cases, except one, experiments with data assimilations have shown comparatively less distance error than control experiments in the initial hours of the days of the events. Intensity errors of experiments with data assimilations are marginally better than those of control experiment for two cases. Experiments with data assimilation show less time errors than that of control experiment in some cases but it is not always true.

Heavy rainfall events frequently occur over the western and central Himalayas during the monsoon season causing losses of lives and damages to properties over the fragile mountain environment. A heavy rainfall event that occurred over Uttarkashi (30.73°N, 78.45°E) in the Western Himalayas on 3rd August 2012 is investigated. The formation of the storm, its evolution and the initial physical mechanisms responsible for this event are analyzed by using a double nested Weather Research and Forecasting (WRF) model. The model skill is evaluated against available observations and analysis fields. The impact of assimilation of Global Telecommunication System (GTS) data in the model initial condition is also studied. The model simulated rainfall is compared with daily rainfall data from satellite-gauge merged rainfall and 3 hourly Tropical Rainfall Measuring Mission (TRMM) estimated rainfall. The double nested configuration of the model successfully simulates this heavy rainfall event. 3DVAR assimilation of GTS data in the model initial condition improves prediction of precipitation amount and location of heavy rainfall. The results of double nested WRF model simulation with GTS data assimilation are compared with the results of global model forecasts of National Centre for Medium Range Weather Forecasting (NCMRWF), India. Forecast skill of the model with and without data assimilation is computed with respect to TRMM estimated daily rainfall.

A tornado occurred at Brahmanbaria in Bangladesh in the afternoon of 22 March 2013. The tornado event has been studied based on tropical rainfall measuring mission (TRMM) data, radar observations and model simulations. The maximum reflectivity and the vertical extent of the system have been recorded to be about 54.7 dBZ and 15 km, respectively, by the Doppler weather radar (DWR) at Agartala, India. The event has been simulated by using the WRF model at 3- and 1-km horizontal resolution nested domains based on six hourly final (FNL) re-analysis data and boundary conditions of National Centers for Environmental Prediction (NCEP). Results show that, while there are differences of 40 minutes before the observed time of the storm, the distance between observed and simulated locations of the storms is 0.5°. The maximum amount of vorticity transferred by directional shear in the storm updraft (helicity) due to convective motion simulated by the model is found to be 1774 m2 s−2, and the highest value of bulk Richardson number shear that defines the region in which low-level mesocyclogenesis is more likely has been 457.3 m2 s−2, which is generally supposed to produce rotating storms according to the prescribed range. The highest vertical velocity simulated by the model is about −28 to 58 m s−1.

A recent heavy precipitation event on 13 September 2012 and the associated landslide on 14 September 2012 is one of the most severe calamities that occurred over the Rudraprayag region in Uttarakhand, India. This heavy precipitation event is also emblematic of the natural hazards occuring in the Himalayan region. Study objectives are to present dynamical fields associated with this event, and understand the processes related to the severe storm event, using the Weather Research and Forecasting (WRF ver 3.4) model. A triple-nested WRF model is configured over the Uttarakhand region centered over Ukhimath (30∘30′N; 79 ∘15′E), where the heavy precipitation event is reported. Model simulation of the intense storm on 13 September 2012 is with parameterized and then with explicit convection are examined for the 3 km grid spacing domain. The event was better simulated without the consideration of convection parameterization for the innermost domain. The role of steep orography forcings is notable in rapid dynamical lifting as revealed by the positive vorticity and high reflectivity values and the intensification of the monsoonal storm. Incursion of moist air, in the lower levels, converges at the foothills of the mountains and rise along the orography to form the updraft zone of the storm. Such rapid unstable ascent leads to deep convection and increases the condensation rate of the water vapour forming clouds at a swift rate. This culminates into high intensity precipitation which leads to high amount of surface runoff over regions of susceptible geomorphology causing the landslide. Even for this intense and potentially unsual rainfall event, the processes involved appear to be the ‘classic’ enhanced convective activity by orographic lifting of the moist air, as an important driver of the event.

The Nor'westers (severe thunderstorms) that form over northeast India and adjoining Bangladesh region during the pre-monsoon season of 2008 are studied employing observations from ground based radar, Tropical Rainfall Measuring Mission (TRMM) and synoptic stations. Subsequently, an attempt is made to simulate the storms using Weather Research and Forecasting (WRF) model at 9 km horizontal resolution, and 28 vertical levels. Analyses of Radar data for 15 cases out of 108 during the study period showed that the Nor'westers typically propagate in the form of squall lines (parallel bow shaped bands) having horizontal length of about 200 km, reaching more than 400 km on some occasions. They propagate at typical speeds of about 50 km h − 1 from northwest to southeast directions. The model underestimated the strength of the squall lines in terms of wind speed. The simulated results showed the presence of strong vertical wind shear and an advection of warm moist southerly wind from the Bay of Bengal during the formation of Nor'westers. Low level positive vorticity in combination with moist southerly wind from the Bay of Bengal and strong surface heating resulted in the formations of the Nor'westers in all the cases. Cloud tops reached as high as 18–20 km in some of the cases of the severe storms. The altitude of core of maximum precipitation was located between 3–5 km. Average cloud hydrometeor content of the Nor'westers was estimated to be about 3.5 g m − 3 .

The quantitative data from Doppler Weather Radar (DWR) such as the radial winds and reflectivity are useful for improving the numerical prediction of weather events like squalls. Mesoscale convective systems are responsible for majority of the squall and hail events and related natural hazards that occur over Bangladesh and surrounding region in pre-monsoon season. In this study, DWR observations (radial winds and reflectivity) of Bangladesh Meteorological Department are used for simulating the squall events during May 2011 with a view to update the initial and boundary conditions through three-dimensional variational assimilation technique within the Advanced Research Weather Research and Forecasting model. The simulated sea-level pressure, thermodynamic indices, wind fields at 850 hPa, and cloud hydrometeors from eight experiments are presented in this study for analyzing the observed and simulated features of the squall events which occurred in the month of May 2011. The model results are also compared with the Kalpana-1 satellite imagery and the observations of India Meteorological Department. Further, the intensity of the events generated from the simulations is also compared with the in situ meteorological observations in order to evaluate the model performance.

The Advanced Research WRF (ARW) model is used to simulate Very Severe Cyclonic Storms (VSCS) Hudhud (7–13 October, 2014), Phailin (8–14 October, 2013) and Lehar (24–29 November, 2013) to investigate the sensitivity to microphysical schemes on the skill of forecasting track and intensity of the tropical cyclones for high-resolution (9 and 3 km) 120-hr model integration. For cloud resolving grid scale (

A common feature of the weather during the pre-monsoon season (March–May) over the east and northeast India is the outburst of severe local storms which have significant socio-economic impact due to loss of lives and properties. Forecasting thunderstorms is one of the most difficult tasks in weather prediction, due to their rather small spatial and temporal scales and the inherent non-linearity of their dynamics and physics. In the present study, an attempt has been made to simulate severe local storms that occurred over east India during STORM field experiments 2007, 2009 and 2010, using Non-hydrostatic Mesoscale Model (NMM) and validate the model results with observation. This study shows that the NMM model holds better promise for prediction of thunderstorm with reasonable accuracy. The intensity of rainfall rates is in good agreement with the observation. The model has well captured the stability indices, which act as indicators of severe convective activity. The surface temperature and relative humidity over Kolkata are reasonably well simulated by the NMM model even though one hour time lag or lead exists. The model simulated well the updraft and downdraft over Kolkata, which is an important phenomenon related to thunderstorm life cycle. From the model simulated spatial plots of composite radar reflectivity and cloud top temperature, we can see that the model has also been able to capture the movement of thunder squall. The results of these analyses determined that the 3 km WRF-NMM model has good skill when it comes to the thunderstorm simulation.

In this paper the impact of Doppler weather radar (DWR) reflectivity and radial velocity observations for the short range forecasting of a tropical storm and associated rainfall event have been examined. Doppler radar observations of a tropical storm case that occurred during 29–30 October 2006 from SHARDWR (13.6° N, 80.2° E) are assimilated in the WRF 3DVAR system. The observation operator for radar reflectivity and radial velocity is included within latest version of WRF 3DVAR system. Keeping all model physics the same, three experiments were conducted at a horizontal resolution of 30 km. In the control experiment (CTRL), NCEP Final Analysis (FNL) interpolated to the model grid was used as the initial condition for 48-h free forecast. In the second experiment (NODWR), 6-h assimilation cycles have been carried out using all conventional (radiosonde and surface data) and non-conventional (satellite) observations from the Global Telecommunication System (GTS). The third experiment (DWR) is the same as the second, except Doppler radar radial velocity and reflectivity observations are also used in the assimilation cycle. Continuous 6-h assimilation cycle employed in the WRF-3DVAR system shows positive impact on the rainfall forecast. Assimilation of DWR data creates several small scale features near the storm centre. Additional sensitivity experiments were conducted to study the individual impact of reflectivity and radial velocity in the assimilation cycle. Radar data assimilation with reflectivity alone produced large analysis response on both thermodynamical and dynamical fields. However, radial velocity assimilation impacted only on dynamical fields. Analysis increments with radar reflectivity and radial velocity produce adjustments in both dynamical and thermodynamical fields. Verification of QPF skill shows that radar data assimilation has a considerable impact on the short range precipitation forecast. Improvement of the QPF skill with radar data assimilation is more clearly seen in the heavy rainfall (for thresholds >7 mm) event than light rainfall (for thresholds of 1 and 3 mm). The spatial pattern of rainfall is well simulated by the DWR experiment and is comparable to TRMM observations.

Performance of four mesoscale models namely, the MM5, ETA, RSM and WRF, run at NCMRWF for short range weather forecasting has been examined during monsoon-2006. Evaluation is carried out based upon comparisons between observations and day-1 and day-3 forecasts of wind, temperature, specific humidity, geopotential height, rainfall, systematic errors, root mean square errors and specific events like the monsoon depressions.