Open Access
Subscription Access
INSAT-3DR-Rapid Scan Operations for Weather Monitoring Over India
In order to observe severe weather conditions during cyclones, thunderstorms, etc., IMAGER instruments on-board INSAT3D/3DR have been built with a flexible scanning feature known as ‘rapid scan mode’. Using this feature, the number of scan lines over a given coverage region and the number of repetitions of the selected region can be programmed for scanning. Therefore, to understand the physical processes involved in convective clouds associated with severe weather phenomena, rapid scan of INSAT3DR mode is attempted. It has very high temporal resolution of approximately 4 min and 30 sec. The present study will help in better understanding of the physical processes of severe weather phenomena and in nowcasting. It will also help to improve the accuracy in the NWP model forecast through assimilation of radiances and atmospheric motion wind determined using rapid scan mode.
Keywords
Nowcasting, Physical Processes, Rapid Scan Operations, Severe Weather Conditions, Weather Monitoring.
User
Font Size
Information
- IMD, A technical report ‘INSAT-3D Data Products Catalog’, India Meteorological Department, New Delhi, January 2014.
- EUMETSAT, Meteosat-9 takes over rapid scanning service, 9 April 2013; http://www.eumetsat.int/Home/Main/News/Press_ Releases/831419?l=en
- Schmit, T. J. et al., Geostationary operational environmental satellite (GOES)-14 super rapid scan operations to prepare for GOES-R. J. Appl. Remote Sensing, 2013, 7(1), 073462.
- Bessho, K. et al., An introduction to Himawari‐8/9 – Japan’s new‐generation geostationary meteorological satellites. J. Meteorol. Soc. Jpn., 2016, 94(2), 151–183; https://doi.org/10.2151/ jmsj.2016‐009.
- Sawada, Y., Okamoto, K., Kunii, M. and Miyoshi, T., Assimilating every-10-minute Himawari‐8 infrared radiances to improve convective predictability. J. Geophys. Res.: Atmos., 2019, 124, 2546–2561; https://doi.org/10.1029/2018JD029643.
- Dvorak, V., Tropical cyclone intensity analysis and forecasting from satellite imagery. Mon. Weather Rev., 1975, 103(5), 420– 430.
- Dvorak, V., Tropical cyclone intensity analysis using satellite data. NOAA Tech. Rep. 1984, 11, 45; NOAA/NESDIS, Washington, DC, USA, 1984, p. 45.
- Ribeiro, B. Z., Machado, L. A. T., Huamán, Ch. J. H., Biscaro, T. S., Freitas, E. D., Goodman, S. J. and Mozer, K. W., An evaluation of the GOES-16 rapid scan for nowcasting in Southeastern Brazil: analysis of a severe hailstorm case. Weather Forecast., 2019, 34(6).
- Gairola, R. M, Mishra, A., Prakash, S. and Mahesh, C., Development of INSAT multi-spectral rainfall algorithm (IMSRA) for monitoring rainfall events over India using Kalpana-IR and TRMM-precipitation radar observations. Scientific Report, SAC/EPSA/AOSG/INSAT/SR-39/2010, 2010, p. 22.
- Karagiannidis, A., Lagouvardos, K., Kotroni, V. and Mazarakis, N., Investigation of isolated thunderstorms lightning activity over eastern Mediterranean using Meteosat rapid scan infrared imagery. Int. J. Remote Sensing, 2016, 37(20), 5001–5020; doi:10.1080/ 01431161.2016.12260000.
- RSMC, Report on cyclonic disturbances over North Indian Ocean during 2018. No. ESSO/IMD/CWD Report No-01 (2019)/09. India Meteorological Department, New Delhi and World Meteorological Organization, 2019.
- Goodman, S. J., Blakeslee, R. J., Koshak, W. J., Mach, D., Bailey, J. and Buechler, D. L., The GOES-R geostationary lightning Mapper (GLM). Atmos. Res., 2013, 125–126, 34–49.
- Velden, C. et al., Recent innovations in deriving tropospheric winds from meteorological satellites. Bull. Am. Meteorol. Soc., 2005, 86, 205–223.
- Gallucci, D. et al., Convective initiation proxies for nowcasting precipitation severity using the MSG-SEVIRI rapid scan. Remote Sensing, 2020, 12, 2562.
- Langland, R. H., Velden, C., Pauley, P. M. and Berger, H., Impact of satellite-derived rapid-scan wind observations on numerical model forecasts of Hurricane Katrina. Mon. Weather Rev., 2009, 137, 1615–1622; https://doi.org/10.1175/2008MWR2627.1.
- Li, J., Li, J., Velden, C., Wang, P., Schmit, T. J. and Sippel, J., Impact of rapid‐scan‐based dynamical information from GOES‐16 on HWRF hurricane forecasts. J. Geophys. Res.: Atmos., 2020, 125, e2019JD031647; https://doi.org/10.1029/2019JD031647.
Abstract Views: 412
PDF Views: 190