Zobrazeno 1 - 10
of 46
pro vyhledávání: '"Bedartha Goswami"'
Publikováno v:
Geophysical Research Letters, Vol 51, Iss 16, Pp n/a-n/a (2024)
Abstract The frequency change of 100‐year flood events is often determined by fitting extreme value distributions to annual maximum discharge from a historical base period. This study demonstrates that this approach may significantly bias the compu
Externí odkaz:
https://doaj.org/article/bcc41948dce2446abdbea328a7fc6dde
Publikováno v:
Geophysical Research Letters, Vol 51, Iss 14, Pp n/a-n/a (2024)
Abstract El Niño Southern Oscillation (ENSO) diversity is characterized based on the longitudinal location of maximum sea surface temperature anomalies (SSTA) and amplitude in the tropical Pacific, as Central Pacific events are typically weaker than
Externí odkaz:
https://doaj.org/article/2ceca7b7a3b2427aa913313e4dd3a53c
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-16 (2023)
Abstract Intraseasonal variation of rainfall extremes within boreal summer in the Indo-Pacific region is driven by the Boreal Summer Intraseasonal Oscillation (BSISO), a quasi-periodic north-eastward movement of convective precipitation from the Indi
Externí odkaz:
https://doaj.org/article/16b3043d121d47c58af41e9d28e2f4ab
Publikováno v:
Geophysical Research Letters, Vol 49, Iss 17, Pp n/a-n/a (2022)
Abstract The diversity of El Niño events is commonly described by two distinct flavors, the Eastern Pacific (EP) and Central Pacific (CP) type. While the remote impacts, that is, teleconnections, of EP and CP events have been studied for different r
Externí odkaz:
https://doaj.org/article/f9906f05664c43debaa41abcfe1ac7b9
Autor:
Bedartha Goswami, Niklas Boers, Aljoscha Rheinwalt, Norbert Marwan, Jobst Heitzig, Sebastian F. M. Breitenbach, Jürgen Kurths
Publikováno v:
Nature Communications, Vol 9, Iss 1, Pp 1-10 (2018)
Most time series techniques tend to ignore data uncertainties, which results in inaccurate conclusions. Here, Goswami et al. represent time series as a sequence of probability density functions, and reliably detect abrupt transitions by identifying c
Externí odkaz:
https://doaj.org/article/0e3d61b1efc947cfb08752dc628291d8
Autor:
Abhirup Banerjee, Matthias Kemter, Bedartha Goswami, Bruno Merz, Jürgen Kurths, Norbert Marwan
Publikováno v:
Theoretical and Applied Climatology
Extreme precipitation events have a significant impact on life and property. The U.S. experiences huge economic losses due to severe floods caused by extreme precipitation. With the complex terrain of the region, it becomes increasingly important to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f3b893f3a2bfd73f868b261fd73752a2
https://doi.org/10.1007/s00704-023-04393-5
https://doi.org/10.1007/s00704-023-04393-5
Sea surface temperature anomalies (SSTA) associated with the El-Niño Southern Oscillation (ENSO) show strong event-to-event variability, known as ENSO diversity. El Niño and La Niña events are typically divided into Eastern Pacific (EP) and Centra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e5a08f91e63ab3cc3d2153ba00aa8c2c
https://doi.org/10.5194/egusphere-egu23-2136
https://doi.org/10.5194/egusphere-egu23-2136
Recent years have seen substantial performance-improvements of deep-learning-basedweather prediction models (DLWPs). These models cover a large range of temporal andspatial resolutions—from nowcasting to seasonal forecasting and on scales ranging f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bdbf02715439a05a328ba4158412dc2e
https://doi.org/10.5194/egusphere-egu23-16186
https://doi.org/10.5194/egusphere-egu23-16186
Intraseasonal variability of extreme rainfall events (EREs) during the South Asian Summer Monsoon season is dominated by the Boreal Summer Intraseasonal Oscillation (BSISO). However, deviations from its canonical north-eastward propagation are poorly
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3553d89eda4667f48f325e8f4eeff61d
https://doi.org/10.5194/egusphere-egu23-6671
https://doi.org/10.5194/egusphere-egu23-6671
Climate networks have become a popular tool for detecting complex structures in spatio-temporal data. However, they require to estimate correlation values on many edges based on limited and noisy time series. Consequently any constructed network like
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c6f5e3952308832eedb83e301ae1f184
https://doi.org/10.5194/egusphere-egu23-13601
https://doi.org/10.5194/egusphere-egu23-13601