Abstract
This study evaluates the performance of a dynamically downscaled Weather Research and Forecasting (WRF) model by capturing the characteristics of the interseasonal variability in terms of active and break spells of the Indian summer monsoon during the period 1980–2014. We identify the active and break days based on the standard criteria of previous studies. Further, the composite means in the rainfall and different rainfall events, along with the thermal and dynamical features associated with active and break spells, are analyzed and discussed. Our results clearly show that the WRF model reproduces the observed features of monsoon circulation in active spells such as the wider and intensified lower tropospheric winds, the presence of mid-tropospheric cyclonic circulation, and the dominance of strong upper-level tropical easterlies along with the high influx of moisture towards the Indian subcontinent. Even in the break spells, the WRF model effectively simulates the observed features of the ERA, such as weaker monsoon winds at both low and upper levels and decreased strength of northwesterly winds of Shamal, the presence of a strong thermal inversion over the northwestern part of the Arabian Sea, and a significant increase in the African easterly jet. Moreover, our rainfall analysis during active and break spells reveals that the WRF model accurately reproduces the observed characteristics of the regional-scale precipitation. The results also reveal that the spatial distributions of moderate, heavy, and very heavy rainfall events over the monsoon core region are well captured by the WRF model, with only slight intensity variations compared to the observed distributions.
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00024-021-02837-5/MediaObjects/24_2021_2837_Fig1_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00024-021-02837-5/MediaObjects/24_2021_2837_Fig2_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00024-021-02837-5/MediaObjects/24_2021_2837_Fig3_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00024-021-02837-5/MediaObjects/24_2021_2837_Fig4_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00024-021-02837-5/MediaObjects/24_2021_2837_Fig5_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00024-021-02837-5/MediaObjects/24_2021_2837_Fig6_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00024-021-02837-5/MediaObjects/24_2021_2837_Fig7_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00024-021-02837-5/MediaObjects/24_2021_2837_Fig8_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00024-021-02837-5/MediaObjects/24_2021_2837_Fig9_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00024-021-02837-5/MediaObjects/24_2021_2837_Fig10_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00024-021-02837-5/MediaObjects/24_2021_2837_Fig11_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00024-021-02837-5/MediaObjects/24_2021_2837_Fig12_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00024-021-02837-5/MediaObjects/24_2021_2837_Fig13_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00024-021-02837-5/MediaObjects/24_2021_2837_Fig14_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00024-021-02837-5/MediaObjects/24_2021_2837_Fig15_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00024-021-02837-5/MediaObjects/24_2021_2837_Fig16_HTML.png)
Similar content being viewed by others
Availability of data and material
Observational data was collected from IMD and ERA5 which are publicly available. Downscaled WRF data was generated in-house and occupies large storage (400TB). The data will be shared for specific cases or as composite means based on the request.
Code availability
The rainfall events and grads scripting codes are self-written codes.
References
Attada, R., Dasari, H. P., Chowdary, J. S., Yadav, R. K., Knio, O., & Hoteit, I. (2018). Surface air temperature variability over the Arabian Peninsula and its links to circulation patterns. International Journal of Climatology. https://doi.org/10.1002/joc.5821.
Bhatla, R., Mohanty, U. C., Raju, P. V. S., & Madan, O. P. (2004). A study on dynamic and thermodynamic aspects of breaks in the summer monsoon over India. International Journal of Climatology, 24(3), 341–360.
Caldwell, P., Chin, H. N. S., Bader, D. C., & Bala, G. (2009). Evaluation of a WRF dynamical downscaling simulation over California. Climate Change, 95, 499–521.
Chen, F., & Dudhia, J. (2001). Coupling an advanced land surface-hydrology model with the Penn State–NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Monthly Weather Review, 129, 569–585.
Das, P. K. (2002). The Monsoons, Nation Book Trust, New Delhi, India, ISBN 978-81-237-1123-2, pp. 193.
Dasari, H. P., Pozo, I., Ferri-Yáñez, F., & Araújo, M. B. (2014a). A regional climate study of heatwaves over the Iberian Peninsula. Atmospheric and Climate Sciences, 4, 841–853.
Dasari, H. P., Salgado, R., Perdigao, J., & Srinivas, C. V. (2014b). A regional climate simulation study using WRFARW model over Europe and evaluation for extreme temperature weather events. International Journal of Atmospheric Sciences. https://doi.org/10.1155/2014/704079.
Dasari, H. P., Srinivas, D., Sabique, S., Langodan, R. A., Ravi, K. K., Viswanadhapalli, Y., Omar, K., & Ibrahim, H. (2019a). High-resolution assessment of solar energy resources over the Arabian Peninsula. Applied Energy, 248, 354–371. https://doi.org/10.1016/j.apenergy.2019.04.105.
Dasari, H. P., Srinivas, D., Sabique, L., Raju, A., Yesubabu, V., Ravikumar, K., & Hoteit, I. (2019b). Assessment of solar radiation resources and its variability over Arabian Peninsula. Applied Energy, 248, 354–371.
Dasari, H.P., Srinivas, D., Sabique, L., Viswanadhapalli, Y., & Ibrahim, H. (2021). Analysis of outdoor thermal discomfort over the Kingdom of Saudi Arabia. GeoHealth, [In Press reference no# 2020GH000370R].
De, U. S., Lele, R. R., & Natu, J.C. (1998). Breaks in southwest monsoon. India Meteorological Department, Report no 1998/3.
Ding, Q., & Wang, B. (2007). Intraseasonal teleconnection between the Eurasian wavetrain and Indian summer monsoon. Journal of Climate, 20, 3751–3767.
Dwivedi, S., Yesubabu, V., Ratnam, M. V., et al. (2020). Variability of monsoon inversion over the Arabian Sea and its impact on rainfall. International Journal of Climatology, 1, 21. https://doi.org/10.1002/joc.6896.
Feng, J., & Fu, C. (2006). Inter-comparison of 10-year precipitation simulated by several RCMs for Asia. Advances in Atmospheric Sciences, 23, 531–542.
Gadgil, S., & Joseph, P. V. (2003). On breaks of the Indian monsoon. Journal of Earth System Science, 112, 529–558.
Gandham, H., Dasari, H. P., Sabique, L., Karumuri, R. K., & Hoteit, I. (2020). Major changes in extreme dust events dynamics over the arabian peninsula during 2003–2017 driven by atmospheric conditions. Journal of Geophysical Research. https://doi.org/10.1029/2020JD032931.
Ghosh, S. K., Pant, M. C., & Dewan, B. N. (1978). Influence of Arabian Sea on the Indian summer monsoon. Tellus, 30, 117–125.
Goswami, B. N., & Ajayamohan, R. S. (2001). Intraseasonal oscillations and interannual variability of the Indian summer monsoon. Journal of Climate, 14, 1180–1198.
Goswami, B. N., & Xavier, P. (2003). Potential predictability and extended range prediction of Indian summer monsoon breaks. Geophysical Research Letters, 30, 1966.
Hariprasad, D., Venkata Srinivas, C., Venkata Bhaskar, R. D., & Anjaneyulu, Y. (2011). Simulation of Indian monsoon extreme rainfall events during the decadal period 2000–2009 using a high resolution mesoscale model. Advances in Geosciences, A6, 31–48.
Hima Bindu, H., Venkat Ratnam, M., Viswanadhapalli, Y., & Hari, P. D. (2018). Medium frequency gravity wave characteristics obtained using Weather Research and Forecasting (WRF) model simulations. Journal of Atmospheric and Solar-Terrestrial Physics, , 119–129. https://doi.org/10.1016/j.jastp.2018.11.013182.
Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S. A., & Collins, W. D. (2008). Radiative forcing by longlived greenhouse gases: calculations with the AER radiative transfer models. Journal of Geophysical Research, 113, D13103. https://doi.org/10.1029/2008JD009944.
Jacob, D., et al. (2014). EURO-CORDEX: New high-resolution climate change projections for European impact research. Regional Environmental Change, 14(2), 563–578. https://doi.org/10.1007/s10113-013-0499-2.
Joseph, S., Sahai, A. K., & Goswami, B. N. (2009). Eastward propagating MJO during boreal summer and Indian monsoon droughts. Climate Dynamics, 32(7–8), 1139–1153.
Kaskaoutis, D. G., Rashki, A., Houssos, E. E., Mofidi, A., Goto, D., Bartzokas, A., Francois, P., & Legrand, M. (2015). Meteorological aspects associated with dust storms in the Sistan region, southeastern Iran. Climate Dynamics, 45(1–2), 407–424.
Keshavamurty, R. N., & Awade, S. T. (1974). Dynamical abnormalities associated with drought in the Asiatic summer monsoon. Indian Journal of Meteorology & Geophysics, 25, 257–266.
Khain, A., & Lynn, B. (2009). Simulation of a super cell storm in clean and dirty atmosphere using Weather research and forecast model with spectral bin microphysics. Journal of Geophysical Research, 114, D19209. https://doi.org/10.1029/2009JD011827.
Kim, M. K., Lau, W. K. M., Kim, K. M., Sang, J., Kim, Y. H., & Lee, W. S. (2015). Amplification of ENSO effects on Indian summer monsoon by absorbing aerosols. Climate Dynamics, 46(7–8), 2657–2671. https://doi.org/10.1007/s00382-015-2722-y.
Krishnamurthy, V., & Shukla, J. (2008). Seasonal persistence and propagation of intraseasonal patterns over the Indian summer monsoon region. Climate Dynamics, 30, 353–369.
Krishnan, R., Zhang, C., & Sugi, M. (2000). Dynamics of breaks in the Indian summer monsoon. Journal of Atmospheric Science, 57, 1354–1372.
Kulkarni, A., Sabade, S. S., & Kripalani, R. H. (2009). Spatial variability of intra-seasonal oscillations during extreme Indian monsoons. International Journal of Climatology, 29, 1945–1955.
Kunchala, R. K., Raju, A., Hari, D. P., Ramesh, K. V., Yasser, O. A., Karumuri, A., & Ibrahim, I. (2019). On the recent amplification of dust over the arabian peninsula during 2002–2012. Journal of Geophysical Research. https://doi.org/10.1029/2019JD030695.
Langodan, S., Yesubabu, V., Hariprasad, D., & Omar, K. (2016). A high-resolution assessment of wind and wave energy potentials in the Red Sea. Applied Energy, 181, 244–255.
Langodan, S., Cavaleri, L., Yesubabu, V., Pomaro, A., Bertotti, L., & Hoteit, I. (2017). The climatology of the Red Sea—part 1: The wind. International Journal of Climatology. https://doi.org/10.1002/joc.5103.
Lo, J. C. F., Yang, Z. L., & Pielke, R. A., Sr. (2008). Assessment of three dynamical climate downscaling methods using the weather research and forecasting (WRF) model. Journal of Geophysical Research, 113, D09112. https://doi.org/10.1029/2007JD00921.
Lucas-Picher, P., Christensen, J. H., Saeed, F., Kumar, P., Asharaf, S., Ahrens, B., Wiltshire, A., Jacob, D., & Hagemann, S. (2011). Can regional climate models represent the Indian monsoon? Journal of Hydrometeorology. https://doi.org/10.1175/2011JHM1327.1mm.
Lucas-Picher, P., Boberg, F., Christensen, J. H., & Peter, B. (2013). Dynamical downscaling with reinitializations: A method to generate fine scale climate datasets suitable for impact studies. Journal of Hydrometeorology, 14, 1159–1174. https://doi.org/10.1175/JHMD-12-063.1.
Muraleedharan, P. M., Mohankumar, K., & Sivakumar, K. U. (2013). A study on the characteristics of temperature inversions in active and break phases of Indian summer monsoon. Journal of Atmospheric and Solar-Terrestrial Physics, 93, 11–20.
Nakanishi, M., & Niino, H. (2006). An improved Mellor-Yamada level-3 model: Its numerical stability and application to a regional prediction of advection fog. Boundary-Layer Meteorol., 119, 397–407.
Nakanishi, M., & Niino, H. (2009). Development of an improved turbulence closure model for the atmosphericboundary layer. Journal of the Meteorological Society of Japan, 87, 895–912.
Narayanan, M. S., & Rao, B. M. (1981). Detection of monsoon inversion by TIROS-N satellite. Nature, 294, 546–548.
Pai, D. S., Bhate, J., Sreejith, O. P., & Hatwar, H. R. (2011). Impact of MJO on the intraseasonal variation of summer monsoon rainfall over India. Climate Dynamics, 36, 41–55.
Pai, D. S., Sridhar, L., Rajeevan, M., Sreejith, O. P., Satbhai, N. S., & Mukhopadhyay, B. (2014). Development of a new high spatial resolution (0.250×0.250) long period (1901–2010) daily gridded rainfall data set over India and its comparison with existing data sets over the region. Mausam, 65, 1–18.
Pai, D. S., Sridhar, L., & Ramesh, K. M. R. (2016). Active and break events of indian summer monsoon during 1901–2014. Climate Dynamics, 46(11), 3921–3939.
Pathak, A., Ghosh, S., Kumar, P., & Murtugudde, R. (2017). Role of oceanic and terrestrial atmospheric moisture sources in intraseasonal variability of indian summer monsoon rainfall. Science and Reports, 7, 12729. https://doi.org/10.1038/s41598-017-13115-7.
Prathipati, V. K., Naidu, C. V., & Konatham, P. (2019). Inconsistency in the frequency of rainfall events in the Indian summer monsoon season. International Journal of Climatology. https://doi.org/10.1002/joc.6113.
Prathipati, V. K., Naidu, C. V., & Konatham, P. (2020). Recent unprecedented weakening of Indian summer monsoon in warming environment. Theoretical and Applied Climatology. https://doi.org/10.1007/s00704-019-03087-1.
Rajeevan, M., Gadgil, S., & Bhate, J. (2010). Active and break spells of the Indian summer monsoon. Journal of Earth System Science, 119(3), 229–247.
Raju, A., Parekh, A., Chowdary, J. S., & Gnanaseelan, C. (2014). Assessment of the Indian summer monsoon in the WRF regional climate model. Climate Dynamics, 44(11–12), 3077–3100. https://doi.org/10.1007/s00382-014-2295-1.
Raju, A., Parekh, A., Chowdary, J. S., & Gnanaseelan, C. (2017). Reanalysis of the Indian summer monsoon: Four dimensional data assimilation of AIRS retrievals in a regional data assimilation and modeling framework. Climate Dynamics, 4, 4. https://doi.org/10.1007/s00382-017-3781-z.
Ramakrishna, S. S. V. S., Brahmananda-Rao, V., Srinivasa-Rao, B. R., et al. (2017). A study of 2014 record drought in India with CFSv2 model: Role of water vapor transport. Climate Dynamics, 49(1–2), 297–312. https://doi.org/10.1007/s00382-016-3343-9.
Ramamurthy, K. (1969). Some aspects of the “break” in the Indian southwest monsoon during July and August. Forecasting Manual, Rep. IV-18.3, India Meteorological Department, p. 29.
Raman, C. R. V., & Rao, Y. P. (1981). Blocking highs over Asia and monsoon droughts over India. Nature, 289, 221–223.
Ramaswamy, C. (1962). Breaks in the India summer monsoon as a phenomenon of interaction between easterly and the subtropical westerly jet streams. Tellus, 14, 337–349.
Ramaswamy, V., Muraleedharan, P. M., & Babu, C. P. (2017). Midtroposphere transport of middle-east dust over the Arabian Sea and its effect on rainwater composition and sensitive ecosystems over India. Scientific Reports, 7(1), 1–8.
Rao, Y. P. (1976). Southwest Monsoons. Meteor. Monogr., No. 1, India Meteorological Department, pp. 1–367.
Rao, T. N., Uma, K. N., Satyanarayana, T. M., & Rao, D. N. (2009). Differences in draft core statistics from the wet spell to dry spell over Gandaki, India (1358N, 7928E). Monthly Weather Review, 2009, 4293–4306.
Rao, T. N., Saikranthi, K., Radhakrishna, B., & Bhaskara Rao, S. V. (2016). Differences in the Climatological Characteristics of Precipitation between Active and Break Spells of the Indian Summer Monsoon. Journal of Climate, 29(21), 7797–7814. https://doi.org/10.1175/jcli-d-16-0028.1.
Reshmi Mohan, P., Srinivas, C. V., Yesubabu, V., Baskaran, R., & Venkatraman, B. (2018). Simulation of a heavy rainfall event over Chennai in Southeast India using WRF: Sensitivity to microphysics parameterization. Atmospheric Research, 210, 83–89. https://doi.org/10.1016/j.atmosres.2018.04.005.
Rosenfeld, D., Lohmann, U., Raga, G. B., O’Dowd, C. D., Kulmala, M., Fuzzi, S., Reissell, A., & Andreae, M. O. (2008). Flood or drought: how do aerosols affect precipitation? Science, 5321(5894), 1309–1313. https://doi.org/10.1126/science.1160606.
Saeed, F., Hagemann, S., & Jacob, D. (2012). A framework for the evaluation of the South Asian summer monsoon in a regional climate model applied to REMO. International Journal of Climatology, 32, 430–440.
Sahu, N., Panda, A., Nayak, S., Saini, A., Mishra, M., Sayama, T., Sahu, L., Duan, W., Avtar, R., & Behera, S. (2020). Impact of indo-pacific climate variability on high streamflow events in Mahanadi River Basin India. Water, 12, 7.
Sathiyamoorthy, V., Mahesh, C. K., Gopalan, S., Bipasha, P., Shukla, P., & Mathur, A. K. (2013). Characteristics of low clouds over the Arabian Sea. Journal of Geophysical Research: Atmospheres. https://doi.org/10.1002/2013JD020553.
Sikka, D. R., & Gadgil, S. (1980). On the maximum cloud zone and the ITCZ over Indian longitudes during the southwest monsoon. Monthly Weather Review, 108, 1840–1853.
Singh, N., & Ranade, A. (2010). The wet and dry spells across India during 1951–2007. Journal of Hydrometeorology, 11, 26–45.
Skamarock, W.C., Klemp, J.B., Dudhia, J., Gill, D.O., Barker, D.M., Duda, M. G., Huang, X.Y., Wang, W., & Powers, J.G. (2008). A description of the advanced research WRF version 3. NCAR Technical Note NCAR/TN475+STR 113.
Srinivas, C. V., Hariprasad, D., Bhaskar Rao, D. V., Anjaneyulu, Y., Baskaran, R., & Venkatraman, B. (2013). Simulation of the Indian summer monsoon regional climate using advanced research WRF model. International Journal of Climatology, 33, 1195–1210.
Srinivas, C. V., Hariprasad, D., Bhaskar Rao, D. V., Baskaran, B., & Venkatrman, B. (2015). Simulation of the Indian summer monsoon onset-phase rainfall using a regional model. Annales Geophysicae, 33, 1097–1115.
Srinivas, C. V., Yesubabu, V., Hari Prasad, D., Hari Prasad, K. B. R. R., Greeshma, M. M., Baskaran, R., & Venkatraman, B. (2018). Simulation of an extreme heavy rainfall event over Chennai, India using WRF: Sensitivity to grid resolution and boundary layer physics. Atmospheric Research, 210, 66–82.
Storch, V.H., Bruce, H., & Linda, O.M. (2000). Review of empirical downscaling techniques. Regional climate development under global warming, General Technical Report. 4.
Thomas, B., Yesubabu, V., Srinivas, C. V., Dasari, H. P., Raju, A., & Sabique, L. (2021). Cloud resolving simulation of extremely heavy rainfall event over Kerala in August 2018—sensitivity to microphysics and aerosol feedback. Atmospheric Research, 258(105613), 0169–8095. https://doi.org/10.1016/j.atmosres.2021.105613.
Thompson, G., Field, P. R., Rasmussen, R. M., & Hall, W. D. (2008). Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part II: Implementation of a new snow parameterization. American Meteorological Society, 136, 5095–5115.
Vijaya Kumari, K., Yesubabu, V., Karuna Sagar, S., Hari Prasad, D., & Rao, V. B. S. (2018). Role of planetary boundary layer processes on the simulation of tropical cyclones over Bay of Bengal. Pure and Applied Geophysics, 176(2), 951–977. https://doi.org/10.1007/s00024-018-2017-4.
Vinoj, V., Rasch, P. J., Wang, H., Yoon, J. H., Ma, P. L., & Landu, K. (2014). Short term modulation of Indian summer monsoon rainfall by West Asian dust. Nature Geoscience, 7, 308–313. https://doi.org/10.1038/ngeo2107.
Viswanadhapalli, Y., Dasari, H. P., Langodan, S., Challa, V. S., & Hoteit, I. (2017). Climatic features of the Red Sea from a regional assimilative model. International Journal of Climatology, 37, 2563–2581. https://doi.org/10.1002/joc.4865.
Viswanadhapalli, Y., Srinivas, C. V., Basha, G., Dasari, H. P., Langodan, S., Venkat-Ratnam, M., & Hoteit, I. (2019). A diagnostic study of extreme precipitation over Kerala during August 2018. Atmospheric Science Letters, 20, 12. https://doi.org/10.1002/asl.941.
Viswanadhapalli, Y., Dasari, H. P., Dwivedi, S., Madineni, V. R., Langodan, S., & Hoteit, I. (2020). Variability of monsoon low-level jet and associated rainfall over India. International Journal of Climatology, 40, 1067–1089. https://doi.org/10.1002/joc.6256.
Webster, P. J., Magaña, V. O., Palmer, T. N., Shukla, J., Tomas, R. A., Yanai, M., & Yasunari, T. (1998). Monsoons: Processes, predictability, and the prospects for prediction. Journal of Geophysical Research, 103(14), 451–510.
Wilks, D. S. (1995). Statistical Methods in the Atmospheric Sciences. Academic Press.
Xu, Z., & Yang, Z. L. (2015). A newdynamical downscaling approach withGCM bias corrections and spectralnudging. Journal of Geophysical Research: Atmospheres, 120, 3063–3084. https://doi.org/10.1002/2014JD022958.
Yu, Y., Notaro, M., Kalashnikova, O. V., & Garay, M. J. (2016). Climatology of summer Shamal wind in the Middle East. Journal of Geophysical Research: Atmospheres, 121, 289–305. https://doi.org/10.1002/2015JD024063.
Zheng, Y., Bourassa, M. A., Ali, M. M., & Krishnamurti, T. N. (2016). Distinctive features of rainfall over the Indian homogeneous rainfall regions between strong and weak Indian summer monsoons. Journal of Geophysical Research: Atmospheres, 121(10), 5631–5647.
Acknowledgements
The author, P. Vinay Kumar, wishes to thank the DST, Government of India, for providing research fellowships [DST/INSPIRE Fellowship/IF160113] and for providing the computational facility under the FIST programme at the Department of Meteorology and Oceanography, Andhra University, Visakhapatnam. The authors acknowledge the India Meteorological Department for providing the high-resolution gridded rainfall (0.25° × 0.25°) and ECMWF Copernicus Climate Change Service for providing the ERA5 data. This work is part of the PhD work of P. Vinay Kumar.
Funding
No funding available.
Author information
Authors and Affiliations
Contributions
All authors contributed to the study conception and design. Initial concept was planned by YV. Data collection and analysis were performed by YV and PVK. Code development and GrADS scripting were done by PVK. WRF data was prepared by YV and HPD. The first draft of the manuscript was written by PVK; corrections and valuable suggestions in improving the article quality were given by YV, CVN and HPD. All authors read and approved the final manuscript.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Prathipati, .K., Viswanadhapalli, Y., Chennu, .N. et al. Study of Active and Break Spell Phenomena of Indian Summer Monsoon Using WRF Downscaled Data. Pure Appl. Geophys. 178, 4195–4219 (2021). https://doi.org/10.1007/s00024-021-02837-5
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00024-021-02837-5