@article{MaheswaranAgarwalSivakumaretal.2019,
  author    = {Maheswaran, Rathinasamy and Agarwal, Ankit and Sivakumar, Bellie and Marwan, Norbert and Kurths, J{\"u}rgen},
  title     = {Wavelet analysis of precipitation extremes over India and teleconnections to climate indices},
  series = {Stochastic Environmental Research and Risk Assessment},
  volume    = {33},
  journal   = {Stochastic Environmental Research and Risk Assessment},
  number    = {11-12},
  publisher = {Springer},
  address   = {New York},
  issn      = {1436-3240},
  doi       = {10.1007/s00477-019-01738-3},
  pages     = {2053 -- 2069},
  year      = {2019},
  abstract  = {Precipitation patterns and extremes are significantly influenced by various climatic factors and large-scale atmospheric circulation patterns. This study uses wavelet coherence analysis to detect significant interannual and interdecadal oscillations in monthly precipitation extremes across India and their teleconnections to three prominent climate indices, namely, Nino 3.4, Pacific Decadal Oscillation, and Indian Ocean Dipole (IOD). Further, partial wavelet coherence analysis is used to estimate the standalone relationship between the climate indices and precipitation after removing the effect of interdependency. The wavelet analysis of monthly precipitation extremes at 30 different locations across India reveals that (a) interannual (2-8 years) and interdecadal (8-32 years) oscillations are statistically significant, and (b) the oscillations vary in both time and space. The results from the partial wavelet coherence analysis reveal that Nino 3.4 and IOD are the significant drivers of Indian precipitation at interannual and interdecadal scales. Intriguingly, the study also confirms that the strength of influence of large-scale atmospheric circulation patterns on Indian precipitation extremes varies with spatial physiography of the region.},
  language  = {en}
}
@article{KurthsAgarwalShuklaetal.2019,
  author    = {Kurths, J{\"u}rgen and Agarwal, Ankit and Shukla, Roopam and Marwan, Norbert and Maheswaran, Rathinasamy and Caesar, Levke and Krishnan, Raghavan and Merz, Bruno},
  title     = {Unravelling the spatial diversity of Indian precipitation teleconnections via a non-linear multi-scale approach},
  series = {Nonlinear processes in geophysics},
  volume    = {26},
  journal   = {Nonlinear processes in geophysics},
  number    = {3},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {1023-5809},
  doi       = {10.5194/npg-26-251-2019},
  pages     = {251 -- 266},
  year      = {2019},
  abstract  = {A better understanding of precipitation dynamics in the Indian subcontinent is required since India's society depends heavily on reliable monsoon forecasts. We introduce a non-linear, multiscale approach, based on wavelets and event synchronization, for unravelling teleconnection influences on precipitation. We consider those climate patterns with the highest relevance for Indian precipitation. Our results suggest significant influences which are not well captured by only the wavelet coherence analysis, the state-of-the-art method in understanding linkages at multiple timescales. We find substantial variation across India and across timescales. In particular, El Ni{\~n}o-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) mainly influence precipitation in the south-east at interannual and decadal scales, respectively, whereas the North Atlantic Oscillation (NAO) has a strong connection to precipitation, particularly in the northern regions. The effect of the Pacific Decadal Oscillation (PDO) stretches across the whole country, whereas the Atlantic Multidecadal Oscillation (AMO) influences precipitation particularly in the central arid and semi-arid regions. The proposed method provides a powerful approach for capturing the dynamics of precipitation and, hence, helps improve precipitation forecasting.},
  language  = {en}
}
@article{CiemerBoersHirotaetal.2019,
  author    = {Ciemer, Catrin and Boers, Niklas and Hirota, Marina and Kurths, J{\"u}rgen and M{\"u}ller-Hansen, Finn and Oliveira, Rafael S. and Winkelmann, Ricarda},
  title     = {Higher resilience to climatic disturbances in tropical vegetation exposed to more variable rainfall},
  series = {Nature geoscience},
  volume    = {12},
  journal   = {Nature geoscience},
  number    = {3},
  publisher = {Nature Publ. Group},
  address   = {New York},
  issn      = {1752-0894},
  doi       = {10.1038/s41561-019-0312-z},
  pages     = {174 -- 179},
  year      = {2019},
  abstract  = {With ongoing global warming, the amount and frequency of precipitation in the tropics is projected to change substantially. While it has been shown that tropical forests and savannahs are sustained within the same intermediate mean annual precipitation range, the mechanisms that lead to the resilience of these ecosystems are still not fully understood. In particular, the long-term impact of rainfall variability on resilience is as yet unclear. Here we present observational evidence that both tropical forest and savannah exposed to a higher rainfall variability-in particular on interannual scales-during their long-term past are overall more resilient against climatic disturbances. Based on precipitation and tree cover data in the Brazilian Amazon basin, we constructed potential landscapes that enable us to systematically measure the resilience of the different ecosystems. Additionally, we infer that shifts from forest to savannah due to decreasing precipitation in the future are more likely to occur in regions with a precursory lower rainfall variability. Long-term rainfall variability thus needs to be taken into account in resilience analyses and projections of vegetation response to climate change.},
  language  = {en}
}