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Sökning: WFRF:(Vinther Bo M.) > (2020)

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1.
  • Sjolte, Jesper, et al. (författare)
  • Seasonal reconstructions coupling ice core data and an isotope-enabled climate model - Methodological implications of seasonality, climate modes and selection of proxy data
  • 2020
  • Ingår i: Climate of the Past. - : Copernicus GmbH. - 1814-9324 .- 1814-9332. ; 16:5, s. 1737-1758
  • Tidskriftsartikel (refereegranskat)abstract
    • The research area of climate field reconstructions has developed strongly during the past 20 years, motivated by the need to understand the complex dynamics of the earth system in a changing climate. Climate field reconstructions aim to build a consistent gridded climate reconstruction of different variables, often from a range of climate proxies, using either statistical tools or a climate model to fill the gaps between the locations of the proxy data. Commonly, large-scale climate field reconstructions covering more than 500 years are of annual resolution. In this method study, we investigate the potential of seasonally resolved climate field reconstructions based on oxygen isotope records from Greenland ice cores and an isotope-enabled climate model. Our analogue-type method matches modeled isotope patterns in Greenland precipitation to the patterns of ice core data from up to 14 ice core sites. In a second step, the climate variables of the best-matching model years are extracted, with the mean of the best-matching years comprising the reconstruction. We test a range of climate reconstructions, varying the definition of the seasons and the number of ice cores used. Our findings show that the optimal definition of the seasons depends on the variability in the target season. For winter, the vigorous variability is best captured when defining the season as December-February due to the dominance of large-scale patterns. For summer, which has weaker variability, albeit more persistent in time, the variability is better captured using a longer season of May-October. Motivated by the scarcity of seasonal data, we also test the use of annual data where the year is divided during summer, that is, not following the calendar year. This means that the winter variability is not split and that the annual data then can be used to reconstruct the winter variability. In particularly when reconstructing the sea level pressure and the corresponding main modes of variability, it is important to take seasonality into account, because of changes in the spatial patterns of the modes throughout the year. Targeting the annual mean sea level pressure for the reconstruction lowers the skill simply due to the seasonal geographical shift of the circulation modes. Our reconstructions based on ice core data also show skill for the North Atlantic sea surface temperatures, in particularly during winter for latitudes higher than 50 N. In addition, the main modes of the sea surface temperature variability are qualitatively captured by the reconstructions. When testing the skill of the reconstructions using 19 ice cores compared to the ones using eight ice cores, we do not find a clear advantage of using a larger data set. This could be due to a more even spatial distribution of the eight ice cores. However, including European tree-ring data to further constrain the summer temperature reconstruction clearly improves the skill for this season, which otherwise is more difficult to capture than the winter season.
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2.
  • Svensson, Anders, et al. (författare)
  • Bipolar volcanic synchronization of abrupt climate change in Greenland and Antarctic ice cores during the last glacial period
  • 2020
  • Ingår i: Climate of the Past. - : Copernicus GmbH. - 1814-9324 .- 1814-9332. ; 16:4, s. 1565-1580
  • Tidskriftsartikel (refereegranskat)abstract
    • The last glacial period is characterized by a number of millennial climate events that have been identified in both Greenland and Antarctic ice cores and that are abrupt in Greenland climate records. The mechanisms governing this climate variability remain a puzzle that requires a precise synchronization of ice cores from the two hemispheres to be resolved. Previously, Greenland and Antarctic ice cores have been synchronized primarily via their common records of gas concentrations or isotopes from the trapped air and via cosmogenic isotopes measured on the ice. In this work, we apply ice core volcanic proxies and annual layer counting to identify large volcanic eruptions that have left a signature in both Greenland and Antarctica. Generally, no tephra is associated with those eruptions in the ice cores, so the source of the eruptions cannot be identified. Instead, we identify and match sequences of volcanic eruptions with bipolar distribution of sulfate, i.e. unique patterns of volcanic events separated by the same number of years at the two poles. Using this approach, we pinpoint 82 large bipolar volcanic eruptions throughout the second half of the last glacial period (12-60ka). This improved ice core synchronization is applied to determine the bipolar phasing of abrupt climate change events at decadal-scale precision. In response to Greenland abrupt climatic transitions, we find a response in the Antarctic water isotope signals (δ18O and deuterium excess) that is both more immediate and more abrupt than that found with previous gas-based interpolar synchronizations, providing additional support for our volcanic framework. On average, the Antarctic bipolar seesaw climate response lags the midpoint of Greenland abrupt δ18O transitions by 122±24 years. The time difference between Antarctic signals in deuterium excess and δ18O, which likewise informs the time needed to propagate the signal as described by the theory of the bipolar seesaw but is less sensitive to synchronization errors, suggests an Antarctic δ18O lag behind Greenland of 152±37 years. These estimates are shorter than the 200 years suggested by earlier gas-based synchronizations. As before, we find variations in the timing and duration between the response at different sites and for different events suggesting an interaction of oceanic and atmospheric teleconnection patterns as well as internal climate variability.
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