Classification of cyclone hazard prone districts of India

Mohapatra, M.; Mandal, G. S.; Bandyopadhyay, B. K.; Tyagi, Ajit; Mohanty, U. C.

doi:10.1007/s11069-011-9891-8

Cited by 101 publications

(36 citation statements)

References 4 publications

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“…Looking at the impact from the spatial context, it has been observed that at least 15 districts were affected 10 times by cyclones and floods during 1995-2010 (GoO 2011). Mohapatra et al (2012) find that 14 districts of Odisha are prone to cyclonic storms, which include six coastal districts, namely, Balasore, Bhadrak, Kendrapada, Jagatsinghpur, Puri and Ganjam, and eight noncoastal districts (e.g. Khordha, Mayurbhanj, Jajpur, Keonjhar, Dhenkanal, Cuttack, Nayagarh and Gajapati).…”

Section: The Study Areamentioning

confidence: 97%

The damages from climatic extremes in India: do disaster-specific and generic adaptation measures matter?

Bahinipati

Patnaik

2014

Environ Econ Policy Stud

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The damages due to climatic extremes have gone up over the years, particularly in developing nations like India. Disaster-specific risk reduction measures have been adopted at both individual and policy levels to reduce potential impacts. At the same time, a variety of generic adaptation activities have also been undertaken. However, there is inconclusive empirical evidence on the effectiveness of these interventions in reducing damages from climatic extremes, especially for the developing nations. This study, therefore, examines the influence of disasterspecific and generic adaptation measures in reducing the damages resulting from the climate extremes like cyclones and floods in India. A district-level analysis was carried out for the state of Odisha, India from 1999 to 2008 using fixed effects for OLS and negative binomial models. Controlling for the influence of exposure and population, three major findings emerge: (1) households and policy makers have learned from the previous disaster experiences, i.e. there is a 'learning effect', (2) the disaster risk management programme undertaken by the government has reduced the damages from climate extremes, and (3) generic adaptation interventions are helpful. Since the frequency and intensity of these events are likely to increase because of climate change, these results have policy implications in the context of reducing potential impacts now and in the foreseeable future.Electronic supplementary material The online version of this article (

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Section: The Study Areamentioning

confidence: 97%

The damages from climatic extremes in India: do disaster-specific and generic adaptation measures matter?

Bahinipati

Patnaik

2014

Environ Econ Policy Stud

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“…A major component of tropical cyclone (TC) motion forecasting is the routine preparation of best tracks and detailed forecast performance statistics at the end of each season. Its importance further increases, when we consider the landfalling TCs over the North Indian Ocean (NIO) and prediction of their landfall point and time due to TC hazard proneness of the region (Mohapatra et al 2012a). Though this is a time-consuming task, it provides invaluable information on overall forecast performance and the relative performance of individual techniques.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of official tropical cyclone landfall forecast issued by India Meteorological Department

et al. 2015

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India Meteorological Department (IMD) introduced the objective tropical cyclone (TC) track forecast valid for next 24 hrs over the North Indian Ocean (NIO) in 2003. It further extended the validity period up to 72 hrs in 2009. Here an attempt is made to evaluate the TC landfall forecast issued by IMD during 2003-2013 (11 years) by calculating the landfall point forecast error (LPE) and landfall time forecast error (LTE). The average LPE is about 67, 95, and 124 km and LTE is about 4, 7, and 2 hrs, respectively for 24, 48, and 72-hr forecasts over the NIO as a whole during 2009-2013. The accuracy of TC landfall forecast has been analysed with respect to basin of formation (Bay of Bengal, Arabian Sea, and NIO as a whole), specific regions of landfall, season of formation (pre-monsoon and post-monsoon seasons), intensity of TCs (cyclonic storm (CS), and severe cyclonic storm (SCS) or higher intensities) at the time of initiation of forecast and type of track of TCs (climatological/straight moving and recurving/looping type). The LPE is less over the BOB than over the AS for all forecast lengths up to 72 hrs. Similarly, the LPE is less during the post-monsoon season than during pre-monsoon season. The LPEs are less for climatologically moving/straight moving TCs than for the recurving/looping TCs. The LPE over the NIO has decreased at the rate of about 14.5 km/year during 2003-2013 for 24-hr forecasts. The LTE does not show any significant improvement for 24-hr forecast during the same period. There is significant decrease in LPE and LTE during 2009-2013 compared to 2003-2008 due to the modernisation programme of IMD. The 24-hr LPE and LTE have decreased from 157.5 to 66.5 km and 7.8 to 4.1 hrs, respectively. However, there is still scope for further reduction in 48 and 72-hr forecast errors over the NIO to about 50 and 100 km respectively based on the latest technology including aircraft reconnaissance, deployment of buoys, and assimilation of more observational data from satellite and Doppler weather radars, etc., in the numerical weather prediction (NWP) models during the next five years.

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“…This may be due to the fact that the predictability of TCs over the ARS is less than that over BOB according, to Mohapatra et al (2013a, b). The genesis characteristics of TCs are also different for BOB and ARS (Mohapatra et al 2012a(Mohapatra et al , 2013a(Mohapatra et al , b, 2014(Mohapatra et al , 2015 due to different dynamical and thermodynamical properties over these basins. However, the bias/error in the satellite estimation of sea surface winds through Oceansat-II and QuickSCAT needs to be investigated with respect to BOB and ARS.…”

Section: Resultsmentioning

confidence: 98%

“…When they cross the coast, torrential rain, high wind speed and storm surge cause havoc in terms of loss of life and properties. Entire east and west coast districts of India are prone to TC activity, though the proneness varies from district to district depending upon the frequency and intensity of the TC crossing the district and the associated heavy rains, winds and storm surges over the district (Mohapatra et al 2012a;Mohapatra 2015). Hence, the early detection and prediction of cyclogenesis over the north Indian Ocean (NIO) can provide more lead time and also accurate early warning of TCs.…”

Section: Introductionmentioning

confidence: 99%

Validation of a satellite-based cyclogenesis technique over the North Indian Ocean

et al. 2016

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Indian region is severely affected by the tropical cyclones (TCs) due to the long coast line of about 7500 km. Hence, whenever any low level circulation (LLC) forms over the Indian Seas, the prediction of its intensification into a TC is very essential for the management of TC disaster. Satellite Application Centre (SAC) of Indian Space Research Organization (ISRO), Ahmedabad, has developed a technique to predict TCs based on scatterometer-derived winds from the polar orbiting satellite, QuikSCAT and Oceansat-II. The India Meteorological Department (IMD) has acquired the technique and verified it for the years 2010-2013 for operational use. The model is based on the concept of analogs of the sea surface wind distribution at the stage of LLC or vortex (T1.0) as per Dvorak's classifications, which eventually leads to cyclogenesis (T2.5). The results indicate that the developed model could predict cyclogenesis with a probability of detection of 61% and critical success index of 0.29. However, it shows high overprediction of the model is better over the Bay of Bengal than over Arabian Sea and during post-monsoon season (September-December) than in pre-monsoon season (March-June).

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Classification of cyclone hazard prone districts of India

Cited by 101 publications

References 4 publications

The damages from climatic extremes in India: do disaster-specific and generic adaptation measures matter?

The damages from climatic extremes in India: do disaster-specific and generic adaptation measures matter?

Evaluation of official tropical cyclone landfall forecast issued by India Meteorological Department

Validation of a satellite-based cyclogenesis technique over the North Indian Ocean

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