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Rajagopal, E. N.
- Improved Prediction of Cyclone Phailin (9-12 October 2013) with 4DVAR Assimilation
Abstract Views :297 |
PDF Views:79
Authors
Gopal Iyengar
1,
Raghavendra Ashrit
1,
Amit Ashish
1,
Kuldeep Sharma
1,
Munmun Das Gupta
2,
E. N. Rajagopal
1,
Swati Basu
1
Affiliations
1 National Centre for Medium Range Weather Forecasting, A-50, Sec-62, Noida 201 307, IN
2 National Centre for Medium Range Weather Forecasting, A-50, Sec-62, Noida 201 307, HT
1 National Centre for Medium Range Weather Forecasting, A-50, Sec-62, Noida 201 307, IN
2 National Centre for Medium Range Weather Forecasting, A-50, Sec-62, Noida 201 307, HT
Source
Current Science, Vol 107, No 6 (2014), Pagination: 952-954Abstract
No Abstract.Full Text
- Global Retrospective Analysis Using NGFS for the Period 2000-2011
Abstract Views :217 |
PDF Views:86
Authors
Affiliations
1 National Centre for Medium Range Weather Forecasting, A-50 Secto-62, Institutional Area, Noida 201 309, IN
1 National Centre for Medium Range Weather Forecasting, A-50 Secto-62, Institutional Area, Noida 201 309, IN
Source
Current Science, Vol 112, No 02 (2017), Pagination: 370-377Abstract
The National Centre for Medium Range Weather Forecasting (NCMRWF) conducted its first global data retrospective analysis (reanalysis) for the period 1 January 2000-31 March 2011 using its GFS based system (NGFS). This reanalysis is called NGFS-R and the main objectives of this effort are to address issues for studying decadal variability of the Indian summer monsoon, high-resolution global analysis fields to study the Indian monsoon and to provide short-term mean fields for its seasonal/long-term forecasts by ensemble methods. NGFS-R has been conducted with the T574L64 version of the Global Data Assimilation and Forecasting System of NCMRWF that is operational as of May 2015, and using CFS-reanalysis data dump. With this effort, a high-resolution global data analysis at 6 h intervals is made available for about 16 years (2000-2015) for various uses and applications.Keywords
Global Data Assimilation and Forecasting, Monsoon Season, Numerical Weather Prediction Models, Retrospective Analysis.Full Text
- Impact of Cartosat-1 Orography in 330 M Unified Model Forecast
Abstract Views :225 |
PDF Views:77
Authors
Affiliations
1 National Centre for Medium Range Weather Forecasting, Ministry of Earth Sciences, Government of India, A-50, Sector 62, Noida 201 309, IN
1 National Centre for Medium Range Weather Forecasting, Ministry of Earth Sciences, Government of India, A-50, Sector 62, Noida 201 309, IN
Source
Current Science, Vol 116, No 5 (2019), Pagination: 816-822Abstract
The newly introduced high-resolution (330 m) regional model, Delhi Model (DM), at the National Centre for Medium Range Weather Forecasting targets winter time fog/visibility forecast over Delhi, India. The pre-sent study focuses on the benefits of enhanced oro-graphic features in DM, through a new data set deve-loped using the Indian Space Research Organisation Cartosat-1 orography (Cartosat-run), against those from the NASA Shuttle Radar Topography Mission Digital Elevation Model employed previously (SRTM-run). The early morning visibilities from the Cartosat-runs were lower compared to the SRTM-runs, which could be linked to an enhanced downdraft (negative vertical velocity) in the former, helping form a shallow and stratified boundary layer. The evolution and vari-ability of ‘ventilation index’ in the model domain is regulated by the local wind circulation changes within the shallow boundary layer which in turn is modulat-ed by the orography representation. The DM forecast-ed ventilation index has been projected to be a potential indicator of the atmosphere dispersion of airborne pollutants over Delhi.Keywords
Cartosat, Fog, Orography, Visibility.Full Text
References
- Ghude, S. D., Bhat, G. S., Prabhakaran, T., Jenamani, R. K., Chate, D. M., Safai, P. D. and Rajeevan, M., Winter fog experiment over the Indo-Gangetic plains of India. Curr. Sci., 2017, 112, 767–784.
- Gautam, R. and Singh, M. K., Urban Heat Island over Delhi punches holes in widespread fog in the Indo-Gangetic Plains. Geophys. Res. Lett., 2018, 45; https://doi.org/10.1002/2017GL076794.
- Boutle, I. A., Price, J., Kudzotsa, I., Kokkola, H. and Romakkanie-mi, S., Aerosol–fog interaction and the transition to well-mixed radiation fog, Atmos. Chem. Phys., 2018, 18, 7827–7840; https://doi. org/10.5194/acp-2017-765.
- Jayakumar, A., Rajagopal, E. N., Boutle, I. A., George, J. P., Mohandas, S., Webster, S. and Aditi, S., An operational fog predic-tion system for Delhi using the 330 m Unified Model. Atmos. Sci. Lett., 2018, 19, e796; doi:10.1002/asl.796.
- Patel, A., Katiyar, S. K., and Prasad, V., Performances evaluation of different open source DEM using differential global positioning sys-tem (DGPS). Egypt. J. Remote Sensing Space Sci., 2016, 19, 7–16; doi: http://dx.doi.org/10.1016/j.ejrs.2015.12.004.
- Sethunadh, J., Jayakumar, A., Mohandas, S. A., Rajagopal, E. N. and Nagulu, A. S., Impact of Cartosat-1 orography on weather pre-diction in the high resolution NCMRWF Unified Model. J. Earth Syst. Sci., 2018 (accepted).
- Nakoudi, K., Giannakaki E., Dandou, A., Tombrou, M. and Komp-pula, M., Planetary boundary Layer variability over New Delhi, India, during EUCAARI project, J. Atmos. Meas. Tech. (under review); doi: https://doi.org/10.5194/amt-2018-342.
- Ferguson, A. S., Smoke dispersion prediction systems. In Smoke Management Guide (eds Hardy, C. et al.), National Wildlife Coor-dination Group, 2001, pp. 163–176.