EconPapers    
Economics at your fingertips  
 

Impact of Kalpana-1 retrieved multispectral AMVs on Mahasen tropical cyclone forecast

Inderpreet Kaur, Prashant Kumar (), S. Deb, C. Kishtawal, P. Pal and Raj Kumar

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2015, vol. 77, issue 1, 205-222

Abstract: The atmospheric motion vectors (AMVs) retrieved from geostationary satellites are recognized as one of the important inputs for numerical weather prediction models to improve the tropical cyclone (TC) forecast. In this study, the weather research and forecasting (WRF) model, WRF three-dimensional variational (3D-Var) data assimilation system and WRF tangent linear and adjoint model are used to investigate the impact of multispectral Kalpana-1 AMVs on the simulation of Mahasen tropical cyclone (now known as cyclonic storm Viyaru) over the Indian Ocean. Three different sets of experiments are performed to evaluate the impact of Kalpana-1 AMVs. First, the impacts of Kalpana-1 AMVs are evaluated for different forecast lengths. The assimilation of Kalpana-1 AMVs improves the cyclone track prediction compared to control experiment. However, all the experiments are unable to capture the deep re-curvature of the TC. The next set of experiments is performed to evaluate the impact of Kalpana-1 AMVs derived from different multispectral channels (viz. visible, infrared and water vapor channels). More improvement is observed in TC track forecast when AMVs from water vapor channel are used for assimilation compared to infrared channel. Results also show degradation in short-range forecast when less-strict quality control is used for AMVs assimilation, but a considerable improvement is observed in long-range forecasts. Finally, the WRF tangent linear and adjoint model is used to compute the forecast sensitivity to Kalpana-1 AMVs observations. Upper- and lower-level circulation information provided by the Kalpana-1 AMVs influences the TC steering flow, and a positive impact on the track prediction is observed. Copyright Springer Science+Business Media Dordrecht 2015

Keywords: Atmospheric motion vectors; Data assimilation; Forecast sensitivity; Tropical cyclone (search for similar items in EconPapers)
Date: 2015
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1007/s11069-015-1591-3 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:77:y:2015:i:1:p:205-222

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-015-1591-3

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:nathaz:v:77:y:2015:i:1:p:205-222