@article{HierroBurgosFonsecaRamezaniZiaranietal.2019, author = {Hierro, Rodrigo and Burgos Fonseca, Y. and Ramezani Ziarani, Maryam and Llamedo, P. and Schmidt, Torsten and de la Torre, Alejandro and Alexander, P.}, title = {On the behavior of rainfall maxima at the eastern Andes}, series = {Atmospheric Research}, volume = {234}, journal = {Atmospheric Research}, publisher = {Elsevier}, address = {Amsterdam [u.a.]}, issn = {0169-8095}, doi = {10.1016/j.atmosres.2019.104792}, year = {2019}, abstract = {In this study, we detect high percentile rainfall events in the eastern central Andes, based on Tropical Rainfall Measuring Mission (TRMM) with a spatial resolution of 0.25 × 0.25°, a temporal resolution of 3 h, and for the duration from 2001 to 2018. We identify three areas with high mean accumulated rainfall and analyze their atmospheric behaviour and rainfall characteristics with specific focus on extreme events. Extreme events are defined by events above the 95th percentile of their daily mean accumulated rainfall. Austral summer (DJF) is the period of the year presenting the most frequent extreme events over these three regions. Daily statistics show that the spatial maxima, as well as their associated extreme events, are produced during the night. For the considered period, ERA-Interim reanalysis data, provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) with 0.75° x0.75° spatial and 6-hourly temporal resolutions, were used for the analysis of the meso- and synoptic-scale atmospheric patterns. Night- and day-time differences indicate a nocturnal overload of northerly and northeasterly low-level humidity flows arriving from tropical South America. Under these conditions, cooling descending air from the mountains may find unstable air at the surface, giving place to the development of strong local convection. Another possible mechanism is presented here: a forced ascent of the low-level flow due to the mountains, disrupting the atmospheric stratification and generating vertical displacement of air trajectories. A Principal Component Analysis (PCA) in T-mode is applied to day- and night-time data during the maximum and extreme events. The results show strong correlation areas over each subregion under study during night-time, whereas during day-time no defined patterns are found. This confirms the observed nocturnal behavior of rainfall within these three hotspots.}, language = {en} } @article{SpiekermannHarderGilmoreetal.2019, author = {Spiekermann, Georg and Harder, M. and Gilmore, Keith and Zalden, Peter and Sahle, Christoph J. and Petitgirard, Sylvain and Wilke, Max and Biedermann, Nicole and Weis, Thomas and Morgenroth, Wolfgang and Tse, John S. and Kulik, E. and Nishiyama, Norimasa and Yava{\c{s}}, Hasan and Sternemann, Christian}, title = {Persistent Octahedral Coordination in Amorphous GeO₂ Up to 100 GPa by Kβ'' X-Ray Emission Spectroscopy}, series = {Physical Review X}, volume = {9}, journal = {Physical Review X}, number = {1}, publisher = {American Physical Society by the American Institute of Physics}, address = {Melville, NY}, issn = {2469-9926}, doi = {10.1103/PhysRevX.9.011025}, pages = {10}, year = {2019}, abstract = {We measure valence-to-core x-ray emission spectra of compressed crystalline GeO₂ up to 56 GPa and of amorphous GeO₂ up to 100 GPa. In a novel approach, we extract the Ge coordination number and mean Ge-O distances from the emission energy and the intensity of the Kβ'' emission line. The spectra of high-pressure polymorphs are calculated using the Bethe-Salpeter equation. Trends observed in the experimental and calculated spectra are found to match only when utilizing an octahedral model. The results reveal persistent octahedral Ge coordination with increasing distortion, similar to the compaction mechanism in the sequence of octahedrally coordinated crystalline GeO₂ high-pressure polymorphs.}, language = {en} } @article{PickEffenbergerZhelavskayaetal.2019, author = {Pick, Leonie and Effenberger, Frederic and Zhelavskaya, Irina and Korte, Monika}, title = {A Statistical Classifier for Historical Geomagnetic Storm Drivers Derived Solely From Ground-Based Magnetic Field Measurements}, series = {Earth and Space Science}, volume = {6}, journal = {Earth and Space Science}, publisher = {American Geophysical Union}, address = {Malden, Mass.}, issn = {2333-5084}, doi = {10.1029/2019EA000726}, pages = {2000 -- 2015}, year = {2019}, abstract = {Solar wind observations show that geomagnetic storms are mainly driven by interplanetary coronal mass ejections (ICMEs) and corotating or stream interaction regions (C/SIRs). We present a binary classifier that assigns one of these drivers to 7,546 storms between 1930 and 2015 using ground-based geomagnetic field observations only. The input data consists of the long-term stable Hourly Magnetospheric Currents index alongside the corresponding midlatitude geomagnetic observatory time series. This data set provides comprehensive information on the global storm time magnetic disturbance field, particularly its spatial variability, over eight solar cycles. For the first time, we use this information statistically with regard to an automated storm driver identification. Our supervised classification model significantly outperforms unskilled baseline models (78\% accuracy with 26[19]\% misidentified interplanetary coronal mass ejections [corotating or stream interaction regions]) and delivers plausible driver occurrences with regard to storm intensity and solar cycle phase. Our results can readily be used to advance related studies fundamental to space weather research, for example, studies connecting galactic cosmic ray modulation and geomagnetic disturbances. They are fully reproducible by means of the underlying open-source software (Pick, 2019, http://doi.org/10.5880/GFZ.2.3.2019.003)}, language = {en} } @article{ZhuChenLiuetal.2019, author = {Zhu, Hui and Chen, Lunjin and Liu, Xu and Shprits, Yuri Y.}, title = {Modulation of locally generated equatorial noise by ULF wave}, series = {Journal of geophysical research : Space physics}, volume = {124}, journal = {Journal of geophysical research : Space physics}, number = {4}, publisher = {American Geophysical Union}, address = {Washington}, issn = {2169-9380}, doi = {10.1029/2018JA026199}, pages = {2779 -- 2787}, year = {2019}, abstract = {In this paper we report a rare and fortunate event of fast magnetosonic (MS, also called equatorial noise) waves modulated by compressional ultralow frequency (ULF) waves measured by Van Allen Probes. The characteristics of MS waves, ULF waves, proton distribution, and their potential correlations are analyzed. The results show that ULF waves can modulate the energetic ring proton distribution and in turn modulate the MS generation. Furthermore, the variation of MS intensities is attributed to not only ULF wave activities but also the variation of background parameters, for example, number density. The results confirm the opinion that MS waves are generated by proton ring distribution and propose a new modulation phenomenon.}, language = {en} } @article{RamachandranRupakhetiCherianetal.2022, author = {Ramachandran, Srikanthan and Rupakheti, Maheswar and Cherian, R. and Lawrence, Mark}, title = {Climate Benefits of Cleaner Energy Transitions in East and South Asia Through Black Carbon Reduction}, series = {Frontiers in environmental science}, volume = {10}, journal = {Frontiers in environmental science}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {2296-665X}, doi = {10.3389/fenvs.2022.842319}, pages = {16}, year = {2022}, abstract = {The state of air pollution has historically been tightly linked to how we produce and use energy. Air pollutant emissions over Asia are now changing rapidly due to cleaner energy transitions; however, magnitudes of benefits for climate and air quality remain poorly quantified. The associated risks involve adverse health impacts, reduced agricultural yields, reduced freshwater availability, contributions to climate change, and economic costs. We focus particularly on climate benefits of energy transitions by making first-time use of two decades of high quality observations of atmospheric loading of light-absorbing black carbon (BC) over Kanpur (South Asia) and Beijing (East Asia) and relating these observations to changing energy, emissions, and economic trends in India and China. Our analysis reveals that absorption aerosol optical depth (AAOD) due to BC has decreased substantially, by 40\% over Kanpur and 60\% over Beijing between 2001 and 2017, and thus became decoupled from regional economic growth. Furthermore, the resultant decrease in BC emissions and BC AAOD over Asia is regionally coherent and occurs primarily due to transitions into cleaner energies (both renewables and fossil fuels) and not due to the decrease in primary energy supply or decrease in use of fossil use and biofuels and waste. Model simulations show that BC aerosols alone contribute about half of the surface temperature change (warming) of the total forcing due to greenhouse gases, natural and internal variability, and aerosols, thus clearly revealing the climate benefits due to a reduction in BC emissions, which would significantly reduce global warming. However, this modeling study excludes responses from natural variability, circulation, and sea ice responses, which cause relatively strong temperature fluctuations that may mask signals from BC aerosols. Our findings show additional benefits for climate (beyond benefits of CO2 reduction) and for several other issues of sustainability over South and East Asia, provide motivation for ongoing cleaner energy production, and consumption transitions, especially when they are associated with reduced emissions of air pollutants. Such an analysis connecting the trends in energy transitions and aerosol absorption loading, unavailable so far, is crucial for simulating the aerosol climate impacts over Asia which is quite uncertain.}, language = {en} } @article{AgarwalGuntuBanerjeeetal.2022, author = {Agarwal, Ankit and Guntu, Ravikumar and Banerjee, Abhirup and Gadhawe, Mayuri Ashokrao and Marwan, Norbert}, title = {A complex network approach to study the extreme precipitation patterns in a river basin}, series = {Chaos : an interdisciplinary journal of nonlinear science}, volume = {32}, journal = {Chaos : an interdisciplinary journal of nonlinear science}, number = {1}, publisher = {American Institute of Physics}, address = {Woodbury, NY}, issn = {1054-1500}, doi = {10.1063/5.0072520}, pages = {12}, year = {2022}, abstract = {The quantification of spatial propagation of extreme precipitation events is vital in water resources planning and disaster mitigation. However, quantifying these extreme events has always been challenging as many traditional methods are insufficient to capture the nonlinear interrelationships between extreme event time series. Therefore, it is crucial to develop suitable methods for analyzing the dynamics of extreme events over a river basin with a diverse climate and complicated topography. Over the last decade, complex network analysis emerged as a powerful tool to study the intricate spatiotemporal relationship between many variables in a compact way. In this study, we employ two nonlinear concepts of event synchronization and edit distance to investigate the extreme precipitation pattern in the Ganga river basin. We use the network degree to understand the spatial synchronization pattern of extreme rainfall and identify essential sites in the river basin with respect to potential prediction skills. The study also attempts to quantify the influence of precipitation seasonality and topography on extreme events. The findings of the study reveal that (1) the network degree is decreased in the southwest to northwest direction, (2) the timing of 50th percentile precipitation within a year influences the spatial distribution of degree, (3) the timing is inversely related to elevation, and (4) the lower elevation greatly influences connectivity of the sites. The study highlights that edit distance could be a promising alternative to analyze event-like data by incorporating event time and amplitude and constructing complex networks of climate extremes.}, language = {en} }