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Osuri K.K.,Indian Institute of Technology Bhubaneswar | Mohanty U.C.,Indian Institute of Technology Bhubaneswar | Routray A.,National Center for Medium Range Weather Forecasting | Niyogi D.,Purdue University
Monthly Weather Review | Year: 2015

The impact on tropical cyclone (TC) prediction from assimilating Doppler weather radar (DWR) observations obtained from the TC inner core and environment over the Bay of Bengal (BoB) is studied. A set of three operationally relevant numerical experiments were conducted for 24 forecast cases involving 5 unique severe/very severe BoB cyclones: Sidr (2007), Aila (2009), Laila (2010), Jal (2010), and Thane (2011). The first experiment (CNTL) used the NCEP FNL analyses for model initial and boundary conditions. In the second experiment [Global Telecommunication System (GTS)], the GTS observations were assimilated into the model initial condition while the third experiment (DWR) used DWR with GTS observations. Assimilation of the TC environment from DWR improved track prediction by 32%-53% for the 12-72-h forecast over the CNTL run and by 5%-25% over GTS and was consistently skillful. More gains were seen in intensity, track, and structure by assimilating inner-core DWR observations as they provided more realistic initial organization/asymmetry and strength of the TC vortex. Additional experiments were conducted to assess the role of warmrain and ice-phase microphysics to assimilate DWR reflectivity observations. Results indicate that the icephase microphysics has a dominant impact on inner-core reflectivity assimilation and in modifying the intensity evolution, hydrometeors, and warm core structure, leading to improved rainfall prediction. This study helps provide a baseline for the credibility of an observational network and assist with the transfer of research to operations over the India monsoon region. © 2015 American Meteorological Society.

Litta A.J.,Cochin University of Science and Technology | Mohanty U.C.,Indian Institute of Technology Delhi | Das S.,National Center for Medium Range Weather Forecasting | Mary Idicula S.,Cochin University of Science and Technology
Atmospheric Research | Year: 2012

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. © 2012 Elsevier B.V.

Kar S.C.,National Center for Medium Range Weather Forecasting | Acharya N.,Indian Institute of Technology Delhi | Mohanty U.C.,Indian Institute of Technology Delhi | Kulkarni M.A.,Indian Institute of Technology Delhi
International Journal of Climatology | Year: 2012

Rainfall in the month of July in India is decided by large-scale monsoon pattern in seasonal to interannual timescales as well as intraseasonal oscillations. India receives maximum rainfall during July and August. Global dynamic models (either atmosphere only or coupled models) have varying skills in predicting the monthly rainfall over India during July. Multi-model ensemble (MME) methods have been utilized to evaluate the skills of five global model predictions for 1982-2004. The objective has been to develop a prediction system to be used in real time to derive the mean of the forecast distribution of monthly rainfall. It has been found that the weighted multi-model ensemble (MME) schemes have higher skill in predicting July rainfall compared to individual models. Through the MME methods, skill of rainfall predictions improved significantly over eastern parts of India. However, there is a region over India where none of the models or the MME scheme has any useful skill. Similarly, there are few typical years in which the mean distribution of July rainfall cannot be predicted with higher skill using the available statistical post-processing methods. A simple MME probabilistic scheme has been utilized to show that skill of probabilistic predictions improved when the representation of mean of forecast distribution has better skill. © 2011 Royal Meteorological Society.

Sinha P.,Indian Institute of Technology Delhi | Mohanty U.C.,Indian Institute of Technology Delhi | Kar S.C.,National Center for Medium Range Weather Forecasting | Kumari S.,Indian Institute of Technology Delhi
Pure and Applied Geophysics | Year: 2014

In this study, sensitivity of the Indian summer monsoon simulation to the Himalayan orography representation in a regional climate model (RegCM) is examined. The prescribed height of the Himalayan orography is less in the RegCM model than the actual height of the Himalayas. Therefore, in order to understand the impact of the Himalayan orography representation on the Indian summer monsoon, the height of the Himalayan orography is increased (decreased) by 10 % from its control height in the RegCM model. Three distinct monsoon years such as deficit (1987), excess (1988) and normal rainfall years are considered for this study. The performance of the RegCM model is tested with the use of a driving force from the reanalysis data and a global model output. IMD gridded rainfall and the reanalysis-2 data are used as verification analysis to validate the model results. The RegCM model has the potential to represent mean rainfall distribution over India as well as the upper air circulation patterns and some of the semi-permanent features during the Indian summer monsoon season. The skill of RegCM is reasonable in representing the variation in circulation and precipitation pattern and intensity during two contrasting rainfall years. The simulated seasonal mean rainfall over many parts of India especially, the foothills of the Himalaya, west coast of India and over the north east India along with the whole of India are more when the orography height is increased. The low level southwesterly wind including the Somali jet stream as well as upper air circulation associated with the tropical easterly jet stream become stronger with the enhancement of the Himalayan orography. Statistical analysis suggests that the distribution and intensity of rainfall is represented better with the increased orography of RegCM by 10 % from its control height. Thus, representation of the Himalayan orography in the model is close to actual and may enhance the skill in seasonal scale simulation of the Indian summer monsoon. © 2013 Springer Basel.

Acharya N.,Indian Institute of Technology Delhi | Kar S.C.,National Center for Medium Range Weather Forecasting | Mohanty U.C.,Indian Institute of Technology Delhi | Kulkarni M.A.,Indian Institute of Technology Delhi | Dash S.K.,Indian Institute of Technology Delhi
Theoretical and Applied Climatology | Year: 2011

The 2009 drought in India was one of the major droughts that the country faced in the last 100 years. This study describes the anomalous features of 2009 summer monsoon and examines real-time seasonal predictions made using six general circulation models (GCMs). El Niño conditions evolved in the Pacific Ocean, and sea surface temperatures (SSTs) over the Indian Ocean were warmer than normal during monsoon 2009. The observed circulation patterns indicate a weaker monsoon in that year over India with weaker than normal convection over the Bay of Bengal and Indian landmass. Skill of the GCMs during hindcast period shows that neither these models simulate the observed interannual variability nor their multi-model ensemble (MME) significantly improves the skill of monsoon rainfall predictions. Except for one model used in this study, the real-time predictions with longer lead (2- and 1-month lead) made for the 2009 monsoon season did not provide any indication of a highly anomalous monsoon. However, with less lead time (zero lead), most of the models as well as the MME had provided predictions of below normal rainfall for that monsoon season. This study indicates that the models could not predict the 2009 drought over India due to the use of less warm SST anomalies over the Pacific in the longer lead runs. Hence, it is proposed that the uncertainties in SST predictions (the lower boundary condition) have to be represented in the model predictions of summer monsoon rainfall over India. © 2011 Springer-Verlag.

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