M. Mohapatra, Anshul Chauhan, Avnish Varshney, Suman Gurjar, M. Bushair, M. Sharma, RK Jenamani, K. Srivastava, P. Guhathakurta, R. Chattopadhyay, Mamta Yadav, Radheshyam Sharma, AK Mitra, Ananda KumarDas, S. Nath, Naresh Kumar, S. Senroy, T. Arulalan, Amit Bharadwaj, D. Pattanaik, BP Yadav, R. Saxena, Ashok KumarDas, Asok Raja, B. Hemlata, Kvh Arun, S. Nitha, Atul KSingh, Shobhit Katiyar, K. Mishra, Surendra PratapSingh, Shashikant Mishra, A. Srivastava, B. Geetha, M. Rahul, K. Nagaratna, H. Biswas, M. Mohanty, R. Thapliyal, Shivinder Singh, S. Lotus, Sandeep KumarSharma, V. Mini, S. Das, Gk Das, A. Anand, Gayatri KVani
{"title":"Short to medium range impact based forecasting of heavy rainfall in India","authors":"M. Mohapatra, Anshul Chauhan, Avnish Varshney, Suman Gurjar, M. Bushair, M. Sharma, RK Jenamani, K. Srivastava, P. Guhathakurta, R. Chattopadhyay, Mamta Yadav, Radheshyam Sharma, AK Mitra, Ananda KumarDas, S. Nath, Naresh Kumar, S. Senroy, T. Arulalan, Amit Bharadwaj, D. Pattanaik, BP Yadav, R. Saxena, Ashok KumarDas, Asok Raja, B. Hemlata, Kvh Arun, S. Nitha, Atul KSingh, Shobhit Katiyar, K. Mishra, Surendra PratapSingh, Shashikant Mishra, A. Srivastava, B. Geetha, M. Rahul, K. Nagaratna, H. Biswas, M. Mohanty, R. Thapliyal, Shivinder Singh, S. Lotus, Sandeep KumarSharma, V. Mini, S. Das, Gk Das, A. Anand, Gayatri KVani","doi":"10.54302/mausam.v74i2.6180","DOIUrl":null,"url":null,"abstract":"There have been major advances in the last few decades in our understanding of heavy rainfall during monsoon season due to substantial progress in both observation and numerical modelling of monsoon. All these resulted in more accurate forecast of heavy rainfall in short to medium range, (upto five days) with 40% improvement in accuracy of heavy rainfall forecast in recent five years (2018-2022) as compared to previous five years. However, improvement of forecast and warning skill is not sufficient to minimize damage to lives and property. It is essential to extend to hazard forecast systems (hazard models) and then to impact and risk assessment with stakeholder interaction for risk based warning (RBW) and response action to protect lives and livelihoods\n \nConsidering all these, India Meteorological Department (IMD) has introduced impact based forecast (IBF) for heavy rainfall at meteorological sub-division level since July 2013 and at district and city scale in August, 2019 in its short to medium range forecasts and nowcasts indicating the likely impact of the heavy rainfall in different sectors and required response actions. Thereafter the IBF of heavy rainfall has undergone several changes over the years. Currently, the IBF being implemented by IMD includes all the four components, viz., (i) meteorological hazards, (ii) geophysical hazards, (iii) geospatial applications and (iv) socio-economic conditions and it utilises a web-GIS based decision support system (DSS). In this study we have reviewed various approaches and stages of development of IBF of heavy rainfall in India. The success of IBF of heavy rainfall will enhance the management of critical resources like agriculture, water & power and support urban and disaster management sectors among others while reducing loss of life and property.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"MAUSAM","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.54302/mausam.v74i2.6180","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
There have been major advances in the last few decades in our understanding of heavy rainfall during monsoon season due to substantial progress in both observation and numerical modelling of monsoon. All these resulted in more accurate forecast of heavy rainfall in short to medium range, (upto five days) with 40% improvement in accuracy of heavy rainfall forecast in recent five years (2018-2022) as compared to previous five years. However, improvement of forecast and warning skill is not sufficient to minimize damage to lives and property. It is essential to extend to hazard forecast systems (hazard models) and then to impact and risk assessment with stakeholder interaction for risk based warning (RBW) and response action to protect lives and livelihoods
Considering all these, India Meteorological Department (IMD) has introduced impact based forecast (IBF) for heavy rainfall at meteorological sub-division level since July 2013 and at district and city scale in August, 2019 in its short to medium range forecasts and nowcasts indicating the likely impact of the heavy rainfall in different sectors and required response actions. Thereafter the IBF of heavy rainfall has undergone several changes over the years. Currently, the IBF being implemented by IMD includes all the four components, viz., (i) meteorological hazards, (ii) geophysical hazards, (iii) geospatial applications and (iv) socio-economic conditions and it utilises a web-GIS based decision support system (DSS). In this study we have reviewed various approaches and stages of development of IBF of heavy rainfall in India. The success of IBF of heavy rainfall will enhance the management of critical resources like agriculture, water & power and support urban and disaster management sectors among others while reducing loss of life and property.
期刊介绍:
MAUSAM (Formerly Indian Journal of Meteorology, Hydrology & Geophysics), established in January 1950, is the quarterly research
journal brought out by the India Meteorological Department (IMD). MAUSAM is a medium for publication of original scientific
research work. MAUSAM is a premier scientific research journal published in this part of the world in the fields of Meteorology,
Hydrology & Geophysics. The four issues appear in January, April, July & October.