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- ItemLong-term studies of mesosphere and lower-thermosphere summer length definitions based on mean zonal wind features observed for more than one solar cycle at middle and high latitudes in the Northern Hemisphere(Katlenburg, Lindau : Copernicus, 2022) Jaen, Juliana; Renkwitz, Toralf; Chau, Jorge L.; He, Maosheng; Hoffmann, Peter; Yamazaki, Yosuke; Jacobi, Christoph; Tsutsumi, Masaki; Matthias, Vivien; Hall, ChrisSpecular meteor radars (SMRs) and partial reflection radars (PRRs) have been observing mesospheric winds for more than a solar cycle over Germany (g1/4g54g gN) and northern Norway (g1/4g69g gN). This work investigates the mesospheric mean zonal wind and the zonal mean geostrophic zonal wind from the Microwave Limb Sounder (MLS) over these two regions between 2004 and 2020. Our study focuses on the summer when strong planetary waves are absent and the stratospheric and tropospheric conditions are relatively stable. We establish two definitions of the summer length according to the zonal wind reversals: (1) the mesosphere and lower-thermosphere summer length (MLT-SL) using SMR and PRR winds and (2) the mesosphere summer length (M-SL) using the PRR and MLS. Under both definitions, the summer begins around April and ends around middle September. The largest year-to-year variability is found in the summer beginning in both definitions, particularly at high latitudes, possibly due to the influence of the polar vortex. At high latitudes, the year 2004 has a longer summer length compared to the mean value for MLT-SL as well as 2012 for both definitions. The M-SL exhibits an increasing trend over the years, while MLT-SL does not have a well-defined trend. We explore a possible influence of solar activity as well as large-scale atmospheric influences (e.g., quasi-biennial oscillation (QBO), El Niño-Southern Oscillation (ENSO), major sudden stratospheric warming events). We complement our work with an extended time series of 31 years at middle latitudes using only PRR winds. In this case, the summer length shows a breakpoint, suggesting a non-uniform trend, and periods similar to those known for ENSO and QBO.
- ItemLong-term in situ observations of biomass burning aerosol at a high altitude station in Venezuela – Sources, impacts and interannual variability(München : European Geopyhsical Union, 2013) Hamburger, T.; Matisāns, M.; Tunved, P.; Ström, J.; Calderon, S.; Hoffmann, P.; Hochschild, G.; Gross, J.; Schmeissner, T.; Wiedensohler, A.; Krejci, R.First long-term observations of South American biomass burning aerosol within the tropical lower free troposphere are presented. The observations were conducted between 2007 and 2009 at a high altitude station (4765 m a.s.l.) on the Pico Espejo, Venezuela. Sub-micron particle volume, number concentrations of primary particles and particle absorption were observed. Orographic lifting and shallow convection leads to a distinct diurnal cycle at the station. It enables measurements within the lower free troposphere during night-time and observations of boundary layer air masses during daytime and at their transitional regions. The seasonal cycle is defined by a wet rainy season and a dry biomass burning season. The particle load of biomass burning aerosol is dominated by fires in the Venezuelan savannah. Increases of aerosol concentrations could not be linked to long-range transport of biomass burning plumes from the Amazon basin or Africa due to effective wet scavenging of particles. Highest particle concentrations were observed within boundary layer air masses during the dry season. Ambient sub-micron particle volume reached 1.4±1.3 μm3 cm−3, refractory particle number concentrations (at 300 °C) 510±420 cm−3 and the absorption coefficient 0.91±1.2 Mm−1. The respective concentrations were lowest within the lower free troposphere during the wet season and averaged at 0.19±0.25 μm3 cm−3, 150±94 cm−3 and 0.15±0.26 Mm−1. A decrease of particle concentrations during the dry seasons from 2007–2009 could be connected to a decrease in fire activity in the wider region of Venezuela using MODIS satellite observations. The variability of biomass burning is most likely linked to the El Niño–Southern Oscillation (ENSO). Low biomass burning activity in the Venezuelan savannah was observed to follow La Niña conditions, high biomass burning activity followed El Niño conditions.
- ItemOrbital insolation variations, intrinsic climate variability, and Quaternary glaciations(Katlenburg-Lindau : Copernicus Ges., 2022) Riechers, Keno; Mitsui, Takahito; Boers, Niklas; Ghil, MichaelThe relative role of external forcing and of intrinsic variability is a key question of climate variability in general and of our planet's paleoclimatic past in particular. Over the last 100 years since Milankovic's contributions, the importance of orbital forcing has been established for the period covering the last 2.6gMyr and the Quaternary glaciation cycles that took place during that time. A convincing case has also been made for the role of several internal mechanisms that are active on timescales both shorter and longer than the orbital ones. Such mechanisms clearly have a causal role in Dansgaard-Oeschger and Heinrich events, as well as in the mid-Pleistocene transition. We introduce herein a unified framework for the understanding of the orbital forcing's effects on the climate system's internal variability on timescales from thousands to millions of years. This framework relies on the fairly recent theory of non-autonomous and random dynamical systems, and it has so far been successfully applied in the climate sciences for problems like the El Niño-Southern Oscillation, the oceans' wind-driven circulation, and other problems on interannual to interdecadal timescales. Finally, we provide further examples of climate applications and present preliminary results of interest for the Quaternary glaciation cycles in general and the mid-Pleistocene transition in particular.
- ItemA multi-model analysis of teleconnected crop yield variability in a range of cropping systems(Göttingen : Copernicus Publ., 2020) Heino, Matias; Guillaume, Joseph H.A.; Müller, Christoph; Iizumi, Toshichika; Kummu, MattiClimate oscillations are periodically fluctuating oceanic and atmospheric phenomena, which are related to variations in weather patterns and crop yields worldwide. In terms of crop production, the most widespread impacts have been observed for the El Niño-Southern Oscillation (ENSO), which has been found to impact crop yields on all continents that produce crops, while two other climate oscillations - the Indian Ocean Dipole (IOD) and the North Atlantic Oscillation (NAO) - have been shown to especially impact crop production in Australia and Europe, respectively. In this study, we analyse the impacts of ENSO, IOD, and NAO on the growing conditions of maize, rice, soybean, and wheat at the global scale by utilising crop yield data from an ensemble of global gridded crop models simulated for a range of crop management scenarios. Our results show that, while accounting for their potential co-variation, climate oscillations are correlated with simulated crop yield variability to a wide extent (half of all maize and wheat harvested areas for ENSO) and in several important crop-producing areas, e.g. in North America (ENSO, wheat), Australia (IOD and ENSO, wheat), and northern South America (ENSO, soybean). Further, our analyses show that higher sensitivity to these oscillations can be observed for rainfed and fully fertilised scenarios, while the sensitivity tends to be lower if crops were to be fully irrigated. Since the development of ENSO, IOD, and NAO can potentially be forecasted well in advance, a better understanding about the relationship between crop production and these climate oscillations can improve the resilience of the global food system to climate-related shocks. © 2020 American Institute of Physics Inc.. All rights reserved.
- ItemAbrupt transitions in time series with uncertainties(London : Nature Publishing Group, 2018) Goswami, B.; Boers, N.; Rheinwalt, A.; Marwan, N.; Heitzig, J.; Breitenbach, S.F.M.; Kurths, J.Identifying abrupt transitions is a key question in various disciplines. Existing transition detection methods, however, do not rigorously account for time series uncertainties, often neglecting them altogether or assuming them to be independent and qualitatively similar. Here, we introduce a novel approach suited to handle uncertainties by representing the time series as a time-ordered sequence of probability density functions. We show how to detect abrupt transitions in such a sequence using the community structure of networks representing probabilities of recurrence. Using our approach, we detect transitions in global stock indices related to well-known periods of politico-economic volatility. We further uncover transitions in the El Niño-Southern Oscillation which coincide with periods of phase locking with the Pacific Decadal Oscillation. Finally, we provide for the first time an 'uncertainty-aware' framework which validates the hypothesis that ice-rafting events in the North Atlantic during the Holocene were synchronous with a weakened Asian summer monsoon.
- ItemComparing climate projections to observations up to 2011(Bristol : IOP Publishing, 2012) Rahmstorf, Stefan; Foster, Grant; Cazenave, AnnyWe analyse global temperature and sea-level data for the past few decades and compare them to projections published in the third and fourth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). The results show that global temperature continues to increase in good agreement with the best estimates of the IPCC, especially if we account for the effects of short-term variability due to the El Niño/Southern Oscillation, volcanic activity and solar variability. The rate of sea-level rise of the past few decades, on the other hand, is greater than projected by the IPCC models. This suggests that IPCC sea-level projections for the future may also be biased low.
- ItemUnravelling the spatial diversity of Indian precipitation teleconnections via a non-linear multi-scale approach(Katlenburg-Lindau : European Geophysical Society, 2019) Kurths, Jürgen; Agarwal, Ankit; Shukla, Roopam; Marwan, Norbert; Rathinasamy, Maheswaran; Caesar, Levke; Krishnan, Raghavan; Merz, BrunoA 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 Niño-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. © 2019 Author(s).
- ItemA propagation-separation approach to estimate the autocorrelation in a time-series(Göttingen : Copernicus, 2008) Divine, D.V.; Polzehl, J.; Godtliebsen, F.The paper presents an approach to estimate parameters of a local stationary AR(1) time series model by maximization of a local likelihood function. The method is based on a propagation-separation procedure that leads to data dependent weights defining the local model. Using free propagation of weights under homogeneity, the method is capable of separating the time series into intervals of approximate local stationarity. Parameters in different regions will be significantly different. Therefore the method also serves as a test for a stationary AR(1) model. The performance of the method is illustrated by applications to both synthetic data and real time-series of reconstructed NAO and ENSO indices and GRIP stable isotopes.