Azad, S. and Rajeevan, M.: Possible shift in the ENSO-Indian monsoon rainfall relationship under future global warming, Sci. Rep.-UK, 6, 20145, https://doi.org/10.1038/srep20145, 2016.
GCOS: Download Climate Timeseries, GCOS [data set],
https://psl.noaa.gov/gcos_wgsp/Timeseries/ (last access: 3 February 2021), 2020.
Grinsted, A., Moore, J. C., and Jevrejeva, S.: Application of the cross wavelet transform and wavelet coherence to geophysical time series, Nonlin. Processes Geophys., 11, 561–566, https://doi.org/10.5194/npg-11-561-2004, 2004.
Hu, W. and Si, B. C.: Technical note: Multiple wavelet coherence for untangling scale-specific and localized multivariate relationships in geosciences, Hydrol. Earth Syst. Sci., 20, 3183–3191, https://doi.org/10.5194/hess-20-3183-2016, 2016.
India-WRIS: India Water Resources Information System, India-WRIS [data set],
https://indiawris.gov.in/wris, last access: 3 February 2021.
Kendall, M. G.: Rank Correlation Methods, 4th edn., Charles Griffin, London, 1975.
Khaliq, M. N., Ouarda, T. B. M. J., Ondo, J. C., Gachon, P., and Bobée, B.: Frequency analysis of a sequence of dependent and/or non-stationary hydro-meteorological observations: a review, J. Hydrol., 329, 534–552, 2006.
Krishnan, R. and Sugi, M.: Pacific decadal oscillation and variability of the Indian summer monsoon rainfall, Clim. Dynam., 21, 233–242, 2003.
Kumar, P., Kaur, S., Weller, E., and Min, S. K.: Influence of natural climate variability on the extreme ocean surface wave heights over the Indian Ocean, J. Geophys. Res.-Oceans, 124, 6176–6199, https://doi.org/10.1029/2019JC015391, 2019.
Kwiatkowski, D., Phillips, P. C. B., Schmidt, P., and Shin, Y.: Testing the null hypothesis of stationarity against the alternative of a unit root how sure are we that economic time series have a unit root?, J. Econ., 54, 159–178, 1992.
Li, Q. and Chen, J.: Teleconnection between ENSO and climate in South China, Stoch. Environ. Res. Risk. Assess., 28, 927–941, 2014.
Mann, H. B.: Non-parametric tests against trend, Econometrica, 13, 163–171, 1945.
Mokhov, II., Smirnov, D. A., Nakonechny, P. I., Kozlenko, S. S., and Kurths, J.: Relationship between El-Ninño/Southern oscillation and the Indian monsoon, Izv. Atmos. Ocean Phys., 48, 47–56, https://doi.org/10.1134/S0001433812010082, 2012.
Nourani, V., Hosseini Baghanam, A., Adamowski, J., and Kisi, O.: Applications of hybrid wavelet – Artificial Intelligence models in hydrology: A review, J. Hydrol., 514, 358–377, 2014.
Pai, D. S., Latha, S., Rajeevan, M., Sreejith, O. P., Satbhai, N. S., and Mukhopadhyay, B.: Development of a new high spatial resolution (0.25°
× 0.25°) 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, https://doi.org/10.54302/mausam.v65i1.851, 2014.
Pettitt, A. N.: A non-parametric approach to the change-point problem, Appl. Stat., 28, 126–135, 1979.
Rathinasamy, M., Agarwal, A., Sivakumar, B., Marwan, N., and Kurths, J.: Wavelet analysis of precipitation extremes over India and teleconnections to climate indices, Stoch. Environ. Res. Risk Assess., 33, 2053–2069, https://doi.org/10.1007/s00477-019-01738-3, 2019.
Sang, Y. F.: A review on the applications of wavelet transform in hydrology time series analysis, Atmos. Res., 122, 8–15, 2013.
Sen, P. K.: Estimates of the regression coefficient based on Kendall's tau, J. Am. Stat. Assoc., 63, 1379–1389, 1968.
Song, X., Zhang, C., Zhang, J., Zou, X., Mo, Y., and Tian, Y.: Potential linkages of precipitation extremes in Beijing-Tianjin-Hebei region, China, with large-scale climate patterns using wavelet-based approaches, Theor. Appl. Climatol., 141, 1251–1269, 2020.
Srivastava, A. K., Rajeevan, M., and Kshirsagar, S. R.: Development of High Resolution Daily Gridded Temperature Data Se
t (1969–2005) for the Indian Region, Atmos. Sci. Lett., 10, 249–254, https://doi.org/10.1002/asl.232, 2009.
Villarini, G., Smith, J. A., Serinaldi, F., Bales, J., Bates, P. D., Krajewski, W. F.: Flood frequency analysis for nonstationary annual peak records in an urban drainage basin, Adv. Water Resour., 32, 1255–1266, 2009.
Yeditha, P. K., Pant, T., Rathinasamy, M., and Agarwal, A.: Multi-scale investigation on streamflow temporal variability and its connection to global climate indices for unregulated rivers in India, J. Wat. Clim. Change, 13, 735–757, 2022.