Someshwar Das

Simulation of a Himalayan cloudburst event

Intense rainfall often leads to floods and landslides in the Himalayan region even with rainfall amounts that are considered comparatively moderate over the plains; for example, ‘cloudbursts’, which are devastating convective phenomena producing sudden high-intensity rainfall (∼10 cm per hour) over a small area. Early prediction and warning of such severe local weather systems is crucial to mitigate societal impact arising from the accompanying flash floods. We examine a cloudburst event in the Himalayan region at Shillagarh village in the early hours of 16 July 2003. The storm lasted for less than half an hour, followed by flash floods that affected hundreds of people. We examine the fidelity of MM5 configured with multiple-nested domains (81, 27, 9 and 3 km grid-resolution) for predicting a cloudburst event with attention to horizontal resolution and the cloud microphysics parameterization. The MM5 model predicts the rainfall amount 24 hours in advance. However, the location of the cloudburst is displaced by tens of kilometers

Calibration of TRMM Derived Rainfall Over Nepal During 1998-2007

In this study rainfall is calculated from Tropical Rainfall Measuring Mission (TRMM) Version 6 (V6) 3B42 datasets and calibrated with reference to the observed daily rainfall by rain-gauge collected at 15 locations over Nepal during 1998-2007. In monthly, seasonal and annual scales TRMM estimated rainfalls follow the similar distribution of historical patterns obtained from the rain-gauge data. Rainfall is large in the Southern parts of the country, especially in the Central Nepal. Day-to-day rainfall comparison shows that TRMM derived trend is very similar to the observed data but TRMM usually underestimates rainfall on many days with some exceptions of overestimation on some days. The correlation coefficient of rainfalls between TRMM and rain-gauge data is obtained about 0.71. TRMM can measure about 65.39% of surface rainfall in Nepal. After using calibration factors obtained through regression expression the TRMM estimated rainfall over Nepal becomes about 99.91% of observed data. TRMM detection of rainy days is poor over Nepal; it can approximately detect, under-detect and over-detect by 19%, 72% and 9% of stations respectively. False alarm rate, probability of detection, threat score and skill score are calculated as 0.30, 0.68, 0.53 and 0.55 respectively. Finally, TRMM data can be utilized in measuring mountainous rainfall over Nepal but exact amount of rainfall has to be calculated with the help of adjustment factors obtained through calibration procedure. This preliminary work is the preparation of utilization of Global Precipitation Measurement (GPM) data to be commencing in 2013.

MESOSCALE MODELING FOR MOUNTAIN WEATHER FORECASTING OVER THE HIMALAYAS

Severe weather has a more calamitous effect in the mountainous region because the terrain is complex and the economy is poorly developed and fragile. Such weather systems occurring on a small spatiotemporal scale invite application of models with fine-grid resolution and observations from radars and satellites besides the conventional observations for forecasting and disaster mitigation.

Circulation characteristics of a monsoon depression during BOBMEX-99 using high-resolution analysis

The skill and efficiency of a numerical model mostly varies with the quality of initial values, accuracy on parameterization of physical processes and horizontal and vertical resolution of the model. Commonly used low-resolution reanalyses are hardly able to capture the prominent features associated with organized convective processes in a monsoon depression. The objective is to prepare improved high-resolution analysis by the use of MM5 modelling system developed by the Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR). It requires the objective comparison of high and low-resolution analysis datasets in assessing the specific convective features of a monsoon depression. For this purpose, reanalysis datasets of NCAR/NCEP (National Center for Atmospheric Research/National Centers for Environmental Prediction) at a horizontal resolution of 2.5‡ (latitude/longitude) have been used as first guess in the objective analysis scheme. The additional asynoptic datasets obtained during BOBMEX-99 are utilized within the assimilation process. Cloud Motion Wind (CMW) data of METEOSAT satellite and SSM/I surface wind data are included for the improvement of derived analysis. The multiquadric (MQD) interpolation technique is selected and applied for meteorological objective analysis at a horizontal resolution of 30 km. After a successful inclusion of additional data, the resulting reanalysis is able to produce the structure of convective organization as well as prominent synoptic features associated with monsoon depression. Comparison and error verifications have been done with the help of available upper-air station data. The objective verification reveals the efficiency of the analysis scheme.

A study on the structure of the convective atmosphere over the Bay of Bengal during BOBMEX-99

Convective activity is one of the major processes in the atmosphere influencing the local and large-scale weather in the tropics. The latent heat released by the cumulus cloud is known to drive monsoon circulation, which on the other hand supplies the moisture that maintains the cumulus clouds. An investigation is carried out on the convective structure of the atmosphere during active and suppressed periods of convection using data sets obtained from the Bay of Bengal and Monsoon Experiment (BOBMEX). The cumulus convection though being a small-scale phenomenon, still influences its embedding environment by interaction through various scales. This study shows the variation in the kinematic and convective parameters during the transition from suppressed to active periods of convection. Convergence in the lower levels and strong upward vertical velocity, significant during active convection are associated with the formation of monsoon depressions. The apparent heat source due to latent heat release and the vertical transport of the eddy heat by cumulus convection, and the apparent moisture sink due to net condensation and vertical divergence of the eddy transport of moisture, are estimated through residuals of the thermodynamic equation and examined in relation to monsoon activity during BOBMEX.

Impact of downscaling on the simulation of seasonal monsoon rainfall over the Indian region using a global and mesoscale model.

A global model (T80L18; Triangular Truncation at wave number 80 with 18 vertical layers) and a mesoscale model MM5 (nested at 90 and 30 km resolutions) are integrated for 5 monsoon years 1998-2002. The impact of dynami- cal downscaling from global to mesoscale in the simulations of Indian summer monsoon rainfall is studied. Comparisons between the global and the mesoscale models show that, though the global model has an edge over the mesoscale model in simulating the all-India mean rainfall closer to the observation, the T80L18 model lacks in simulating the spatial variations in rainfall. The effect of downscaling is better represented in the rainfall variations produced by MM5 both quantitatively and qualitatively over the foothills of the Himalayas and along Nepal to North-eastern India. It is also seen that the mesoscale model is able to represent the dispersion (standard deviation) present in the observed rainfall over India. In the five monsoon seasons, RMSE of mean rainfall (monthly and seasonal) of T80L18 forecasts are mostly lower than that of MM5 forecasts. However, synoptic features like the Somali Jet and Tibetan anticyclone are better rep- resented by MM5. This model has also simulated the regions of convection better than the T80L18 model. However, the MM5 simulations produced an anomalous circulation over the Saudi Arabian region (15-20 0 N and 45-50 0 E) in many cases. The mesoscale model simulates better wind fields than the global model in general. Over peninsular India T80L18 model showed higher temperature gradient but, over Central India this model has better temperature field as compared to MM5. Over southern and north-eastern India, the temperature field of T80L18 and MM5 are very similar.

Study of cloud liquid water path and total precipitable water from irs-p4/msmr and numerical weather prediction model output

A global weather analysis-forecast system is used to produce six hourly analysis of meteorological fields at roughly 150 km × 150 km resolution at the National Center for Medium Range Weather Forecast (NCMRWF). In this paper, we have studied the Total Precipitable Water Content (TPWC) and Cloud Liquid Water Path (CLWP) derived from the Indian Remote Sensing (IRS-P4) Satellite over the Indian Ocean region in relation to operational numerical weather prediction (NWP) model analysis and short-range forecasts. An objective analysis was carried out by introducing the observations of CLWP, TPWC and their values (six hour forecasts) from the T80 model as the first guess, for a 20 days period of August 1999 using the standard Cressman’s technique. The reanalysis could capture the signature of TPWC and CLWP data from IRS-P4 satellite. In general the observed values of TPWC and CLWP from IRS-P4 have a positive bias compared to NCMRWF analysis over the region where the satellite passed. The CLWP values have been compared with Special Sensor Microwave/Imager (SSM/I) products from the Defense Meteorological Satellite Program (DMSP) satellites. Results indicate that the model derived CLWP values were within acceptable limits, whereas the observations from the Multi-channel Scanning Microwave Radiometer (MSMR) showed slightly larger values.

Numerical diagnosis of situations causing heavy rainfall over the Western Himalayas

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.

Simulation of Mesoscale Convective Systems Associated with Squalls Using 3DVAR Data Assimilation over Bangladesh

Thunderstorms of pre-monsoon season (March–May), locally known as “Kal Boishakhi” or nor’westers, develop from a variety of mesoscale convective structures as they mature to meso α scale (200–1,000 km) systems. These systems develop mainly due to merging of cold dry northwesterly winds aloft and southerly low level warm moist winds from the Bay of Bengal.