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MME forecast wind and rainfall valid for 17-23 October 2011: (a) days 5-11 forecast wind based on 13 Oct. (b) days 12-18 forecast wind based on 06 Oct. (c) and (d), same as 'a' and 'b' but for rainfall anomaly.
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Over the North Indian Ocean (NIO), the months of October-December are known to produce tropical cyclones (TCs) of severe intensity in the Bay of Bengal, which after crossing the coast cause damages to life and property over many countries surrounding the Bay of Bengal. The strong winds, heavy rains and large storm surges associated with TCs are the...
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Context 1
... depression over Bay of Bengal which crossed Myanmar coast on 20 th October, 2011 is very well captured in the weekly MME forecast mean wind valid for the period 17-23 October, 2011 based on initial condition of 13 October (days 5-11 forecast) (Fig. 2a) and based on initial condition of 06 th October (days 12-18 forecast) (Fig. 2b). There is fairly good indication of closed cyclonic circulation in the MME forecast valid for days 5-11 and days 12-18. Thus, even two weeks in advance the formation and likely movement was well anticipated in the MME forecast. The forecast rainfall anomaly ...
Context 2
... depression over Bay of Bengal which crossed Myanmar coast on 20 th October, 2011 is very well captured in the weekly MME forecast mean wind valid for the period 17-23 October, 2011 based on initial condition of 13 October (days 5-11 forecast) (Fig. 2a) and based on initial condition of 06 th October (days 12-18 forecast) (Fig. 2b). There is fairly good indication of closed cyclonic circulation in the MME forecast valid for days 5-11 and days 12-18. Thus, even two weeks in advance the formation and likely movement was well anticipated in the MME forecast. The forecast rainfall anomaly based on 13 Oct and 06 Oct initial conditions also indicated active convection ...
Context 3
... in the MME forecast valid for days 5-11 and days 12-18. Thus, even two weeks in advance the formation and likely movement was well anticipated in the MME forecast. The forecast rainfall anomaly based on 13 Oct and 06 Oct initial conditions also indicated active convection leading to rainfall over the Bay of Bengal in the rainfall anomaly ( Fig. 2c-2d), which indicated rainfall over the Myanmar coast consistent with the location of formation of the ...
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Citations
... Using the latest generation global numerical weather prediction models there have been some efforts to study the predictability of TCs of the North Indian Ocean. Pattanaik et al. (2013b) and Pattanaik and Mohapatra (2014) in their recent studies have demonstrated that the prediction of genesis of TCs in extended range time scale using present generation coupled models has got useful skill over the north Indian Ocean. The current ERF system is also being used for cyclogenesis potential probability operationally Over the Bay of Bengal the Super Cyclonic Storm (SuCS) "AMPHAN" initially formed as a low-pressure area over southeast Bay of Bengal and adjoining south Andaman Sea, in the morning of 13 May 2020. ...
Monsoon rainfall over India during June to September shows intra-seasonal variability with spells of above-normal rainfall (active) and subdued rainfall (break) cycles. India Meteorological Department (IMD) with the support from other sister’s organizations of the Ministry of Earth Sciences (MoES) has implemented the operational extended range forecast (ERF) system based on the Climate Forecast System (CFS) version 2 coupled model for extended range forecasts valid up to 3–4 weeks. The operational ERF of rainfall during southwest and northeast monsoon season, maximum and minimum temperature, cyclogenesis potential, etc. has demonstrated useful skill. The ERF for the southwest monsoon season clearly captured the intra-seasonal variability of monsoon including delay/early onset of monsoon, active/break spells of monsoon, and also withdrawal of monsoon at least 2 weeks in advance. The forecast at met-subdivision level is being used for application in Agriculture. Similarly, the cyclogenesis potential in case of Super Cyclone AMPHAN also captured very well 2 weeks in advance, which has the potential application in the disaster management sector. In addition to the regular ERF products for application in agriculture, additional products are being prepared, viz., (i) active phase of monsoon rainfall having potential of heavy rainfall events; (ii) land-surface hydrology products like soil moisture and runoff; (iii) heat wave/cold wave; (iv) transmission window products for vector-borne diseases, etc. for applications in disaster management, hydrology, energy, and health sectors, respectively.KeywordsCoupled modelExtended range forecastIndian monsoonCFSv2Sectoral applications
... Using the latest generation global numerical weather prediction models there have been some efforts to study the predictability of TCs of the North Indian Ocean. Pattanaik et al. (2013b) and Pattanaik and Mohapatra (2014) in their recent studies have demonstrated that the prediction of genesis of TCs in extended range time scale using present generation coupled models has got useful skill over the north Indian Ocean. The current ERF system is also being used for cyclogenesis potential probability operationally Over the Bay of Bengal the Super Cyclonic Storm (SuCS) "AMPHAN" initially formed as a low-pressure area over southeast Bay of Bengal and adjoining south Andaman Sea, in the morning of 13 May 2020. ...
... After the initial few years during 2008 and 2009, the improved dynamical models like the ECMWF monthly forecast systems, NCEP CFSv2 climate model, and the JMA Ensemble Prediction System (EPS) are used for the preparation of real-time MME-based ERF during the period from 2010 to 2016. The intra-seasonal monsoon forecast during the drought year of 2009 and other recent years showed useful skill in MME (Tyagi and Pattanaik 2010;Pattanaik et al. 2013a;Pattanaik 2014). The MMEERF products are also prepared on smaller spatial domains (4 homogeneous regions of India and 36 met-subdivisions) during the southwest monsoon season from June to September for the preparation of Agro-met advisory(Pattanaik 2014). ...
... The intra-seasonal monsoon forecast during the drought year of 2009 and other recent years showed useful skill in MME (Tyagi and Pattanaik 2010;Pattanaik et al. 2013a;Pattanaik 2014). The MMEERF products are also prepared on smaller spatial domains (4 homogeneous regions of India and 36 met-subdivisions) during the southwest monsoon season from June to September for the preparation of Agro-met advisory(Pattanaik 2014). ...
Forecasting severe weather events is of immense value since it can help alleviate (if not mitigate) the disastrous impacts to a certain extent. While accurate and precise forecasting is a great challenge, the advances in recent decades in the NWP in India have shown improved accuracy and reliability in the forecasting capabilities, especially for severe weather events. Improved observations, monitoring, modelling and forecasting capabilities in recent years in India have helped in early detection and warning for severe weather events. This Chapter documents the recent developments in India, and NCMRWF in particular, in forecasting (i) Heavy Rainfall (ii) Tropical Cyclones (iii) Thunderstorms and Hailstorms (iv) Heat and Cold Waves (v) Fog and Visibility.
... With the genesis of a depression IMD begins issuing TC forecast advisories for valid for 72 hrs (IMD, 2003). The forecasting of genesis of tropical cyclone and associated rainfall in the extended range time scale (about 2 weeks in advance) is also very useful for applications in disaster risk reduction (Pattanaik et al., 2013;Pattanaik & Mohapatra, 2014). IMD has started using the dynamical models outputs for forecast of cyclogenesis in the extended range time scale since 2010 (Pattanaik et al., 2013b;Pattanaik & Mohapatra, 2014). ...
... The forecasting of genesis of tropical cyclone and associated rainfall in the extended range time scale (about 2 weeks in advance) is also very useful for applications in disaster risk reduction (Pattanaik et al., 2013;Pattanaik & Mohapatra, 2014). IMD has started using the dynamical models outputs for forecast of cyclogenesis in the extended range time scale since 2010 (Pattanaik et al., 2013b;Pattanaik & Mohapatra, 2014). With operational implementation of coupled modeling system for ERF the genesis forecast of tropical cyclone has also improved over the time. ...
... Based on the available dynamical models outputs the forecasting of genesis of tropical cyclone and associated rainfall in the extended range time scale (about 2 weeks in advance) for applications in disaster risk reduction had a modest beginning in IMD in 2010, where it started using the dynamical models outputs from various models for forecast of cyclogenesis in the extended range time scale (Pattanaik et al., 2013;Pattanaik & Mohapatra, 2014). As shown in Fig. 2(a) obtained from the cyclone e-Atlas (IMD, 2012) the severe cyclonic storm (SCS) "Jal" during 1 st week of November, 2010 was first observed as a low pressure area over the south Andaman Sea and neighbourhood on 2 nd November, gradually intensified into a SCS on 6 th November and crossed north Tamil Nadusouth Andhra Pradesh coasts on 7 th November and caused lot of damage in Tamil Nadu and south Andhra Pradesh coast associated with not only strong wind but also due to heavy rainfall due to the cyclone. ...
The post monsoon seasons (October-December; OND) are known to produce tropical cyclones (TCs) of severe intensity over the North Indian Ocean (NIO) and particularly over the Bay of Bengal (BoB). The
evolution of operational extended range forecast (ERF) of cyclogenesis probability during 2010 to 2020 based on dynamical models have been discussed. The ERF of cyclogenesis probability based on ECMWF and CFSv1 dynamical models had a modest beginning in 2010 with reasonable performance in case of severe cyclonic storm ‘Jal’ formed during the first week of November. The 2015 cyclone season with active Arabian Sea and inactive BoB was also very well captured in the real time ERF.
IMD implemented CFSv2 coupled model for operational ERF in 2017 and based on it the Genesis Potential Parameter (GPP) is calculated for four weeks by using the dynamical variables like vorticity, divergence, vertical wind shear & mid-level relative humidity and was tested for the ‘Ockhi’ cyclone of 24-30 November, 2017. The GPP in case of ‘Ockhi’ cyclone was well predicted in the ERF, however, with a lead time of only one week.
The Improved GPP (IGPP) is used since 2019, which can be applied both over the Ocean and the land region. In the case of IGPP the vorticity and middle tropospheric humidity terms of GPP have been retained but the thermodynamic term is modified as the scaled and averaged equivalent potential temperature (θe) between 1000 and 500 hPa. The vertical shear between 850 and 200 hPa is scaled and averaged over an annular region between 100 and 200 km radii for
each grid point. In case of Super cyclone “Amphan” it indicated the genesis of the system in “Week 1” and “Week 2” forecast and also its re-curvature northeastward like the observed track. The cyclone “Nisarga” over the Arabian Sea and its track towards western coast of India was well captured in week 1 forecast based on Initial Condition of 27 May, 2020. The IGPP also showed reasonable skill in ERF in predicting the genesis of three intense cyclones viz., „Gati‟ during
21-24 November, „Nivar‟ during 22-26 November and „Burehi‟ during 30 November to 5 December and the two depressions of October, 2020. Considering the significant role of Madden Julian Oscillation (MJO) in BoB TC genesis, IMD is making use of the operational IGPP along with other parameters like current and forecast MJO, Tropical Cyclone Heat Potential etc and the value-added cyclogenesis probability outlook is being issued for two weeks on every Thursday.
... In addition, the world's highest population density coupled with low socioeconomic conditions in the region has resulted in several land-falling TCs becoming devastating natural disasters. The forecasting of genesis of tropical cyclone and associated rainfall in the extended range time scale (about 2 weeks in advance) is also very useful for applications in disaster risk reduction (Pattanaik et al., 2013b;Pattanaik & Mohapatra, 2014). The post-monsoon cyclone season during OND is also known as the northeast monsoon season. ...
... Some earlier studies Kotal et al., 2009) have also discussed the genesis parameters of formations of TCs over North Indian Ocean (NIO) based on dynamical variables in the medium range time scales. Also, there have been some efforts to forecast the genesis of TCs over the Bay of Bengal (BoB) in the extended range time scale (2-3 weeks) using latest generation coupled model outputs (Belanger et al., 2010;Pattanaik et al., 2013b;Pattanaik and Mohapatra, 2014) over the NIO. IMD has started to use the real time ERF for converting into cyclogenesis potential based on Kotal et al. (2009). ...
The evolution of operational extended range forecast (ERF) system of IMD starting from use of empirical models, dynamic models and the Multi-model Ensemble (MME) from 2009 to 2016 till the operational implementation of fully coupled model in 2016 is discussed. The coupled model implemented in IMD is the Climate Forecast System version 2 (CFSv2). The performance of ERF for southwest monsoon, northeast monsoon, cyclogenesis over the Bay of Bengal (BoB) and maximum and minimum temperature during the period from 2009 to 2018 have been discussed along with its prospects of its application in different sectors like, agriculture, hydrology, health, power etc. are also analysed. The performance of extended range forecasts for the southwest monsoon seasons clearly captured the intra-seasonal variability of monsoon including delay/early onset of monsoon, active/break spells of monsoon and also withdrawal of monsoon in the real time in providing guidance for various applications. The MME based ERF also provides encouraging results to provide useful guidance upto 2/3 weeks about northeast monsoon and cyclogenesis potential during October to December (OND) over the north Indian Ocean, heat wave, cold wave during summer and winter with statistically significant correlation coefficient (CC) upto two weeks. For applications in agriculture sector meteorological subdivision level forecasts are prepared for two weeks for the purpose of agro advisory. 234 MAUSAM, 70, 2 (April 2019) In addition to the regular ERF products for application in agriculture and hydrology, additional products are being prepared like, Standarised Precipitation Index (SPI), land-surface hydrology products like soil moisture and runoff change, transmission windows products for vector borne diseases etc for applications in agriculture, hydrology and health sectors.
... Extended range prediction of CS using multi-model ensembles (MME) have been a major breakthrough in the recent years with many studies proving that over NIO, probabilistic prediction of CS possesses improved skill over single dynamical and statistical prediction tools (Majumdar and Finocchio 2010;Pattanaik et al. 2013;Jaiswal et al. 2016). Pattanaik and Mohapatra (2014) studied the MME-based extended range forecast for TC genesis over NIO and found that the present generation general circulation models (GCMs) are capable of providing useful guidance in TC prediction on extended range. Using European Centre for Medium-Range Weather Forecasts (ECMWF) Variable EPS (VarEPS), Belanger et al. (2012) showed that probabilistic prediction of cyclogenesis over NIO is skilful through 2-week period. ...
An attempt has been made in this study to evaluate the performance of a multi-model ensemble prediction system (MMEPS) in the extended range prediction of genesis and track of cyclonic storms (CS) over North Indian Ocean (NIO) during the onset phase of Indian summer monsoon. The MMEPS comprises of National Centres for Environmental Prediction Climate Forecast System version 2 and its atmospheric component, Global Forecast System version 2, at two different resolutions. In this study, we analyse the performance of this MMEPS in the prediction of six CS cases formed around the onset phase of the Indian summer monsoon over NIO. Along with this, we evaluate the usefulness of the genesis potential parameter used by India Meteorological Department (IMD) for the real-time cyclogenesis prediction. ERA-Interim re-analysis data sets are used to compare MME predictions from two initial conditions (IC) close to the genesis date of each storm. Results show that genesis forecasts from nearest available IC is capturing the vorticity and associated features of the storm better than far-IC. A modified version of vortex tracking scheme developed by Geophysical Fluid Dynamics Laboratory is used to obtain the mean track positions from MME outputs and compare with IMD-best tracks. Track verification is done by calculating average direct position error, cross-track error and along-track error against corresponding IMD-best tracks. It is found that track predictions from both near and far ICs have lower average errors initially with near-IC having lesser errors as compared to far-IC. Along-track error for pre-genesis track prediction from far-IC implies that the predicted tracks remarkably lag behind observed tracks for most of the cases. These errors could be contributed from the inability of the models in realistically capturing the region of evolution and intensification of both thermodynamic and dynamic parameters with increasing lead time.
... Since then, several methodologies have been adopted for the seasonal TC activity forecast in different TC-prone areas of the world, such as Poisson regression models (Elsner and Schmertmann 1993;Kim et al. 2010), Bayesian regression models (Chu and Zhao 2007;Werner and Holbrook 2011) and projection pursuit regression (Chan and Liu 2001). Pattanaik and Mohapatra (2013) in their recent study demonstrating the skill in forecasting tropical cyclogenesis and associated rainfall in extended range time scale (1-2 week) over the NIO, based on multi-model ensemble system(MME) applied to ECMWF couple model, and the NCEP's climate forecast system (CFS) couple model. A detailed review of the seasonal tropical cyclone forecasts over the globe has been given by Camargo et al. (2007) and it is found that most of the forecast methods are focused on the statistical and dynamical method approach. ...
A neural network (NN) model is developed to predict the seasonal number of tropical cyclones (TCs) formed over the north Indian Ocean during the post-monsoon season (October, November, December). The frequency of TCs and the large scale climate variables derived from the NCEP/NCAR reanalysis dataset of resolution 2.5° × 2.5o have been analyzed for the period 1971-2013. Data for the years 1971-2002 have been used for the development of the model, which is tested with independent sample data for the years 2003-2013. Applying correlation analysis, five large-scale climate variables, namely geopotential height at 500 hPa, relative humidity at 500 hPa, sea level pressure, and zonal wind at 700 hPa and 200 hPa for the antecedent month September are selected as predictors. Based on some performance parameter statistics, the performance of the NN model is evaluated and the results are compared with the multiple linear regression (MLR) model. From the results it is inferred that the predicted tropical cyclone count by both models is very close to the actual counts for both periods. However, the NN model is found to be superior to the MLR model. This tropical cyclone prediction technique may be useful for operational prediction purposes.
Over the North Indian Ocean (NIO) and particularly over the Bay of Bengal (BoB), the post-monsoon season from October to December (OND) are known to produce tropical cyclones, which cause damage to life and property over India and many neighbouring countries. The variability of frequency of cyclonic disturbances (CDs) during OND season is found to be associated with variability of previous large-scale features during monsoon season from June to September, which is used to develop seasonal forecast model of CDs frequency over the BoB and NIO based on principal component regression (PCR). Six dynamical/thermodynamical parameters during previous June–August, viz., (i) sea surface temperature (SST) over the equatorial central Pacific, (ii) sea level pressure (SLP) over the southeastern equatorial Indian Ocean, (iii) meridional wind over the eastern equatorial Indian Ocean at 850 hPa, (iv) strength of upper level easterly, (v) strength of monsoon westerly over North Indian Ocean at 850 hPa, and (vi) SST over the northwest Pacific having significant and stable relationship with CDs over BoB in subsequent OND season are used in PCR model for a training period of 40 years (1971–2010) and the latest four years (2011–2014) are used for validation. The PCR model indicates highly significant correlation coefficient of 0.77 (0.76) between forecast and observed frequency of CD over the BoB (NIO) for the whole period of 44 years and is associated with the root mean square error and mean absolute error ≤ 1 CD. With respect to the category forecast of CD frequency over BoB and NIO, the Hit score is found to be about 63% and the Relative Operating Curves (ROC) for above and below normal forecast is found to be having much better forecast skill than the climatology. The PCR model performs very well, particularly for the above and below normal CD year over the BoB and the NIO, during the test period from 2011 to 2014.
