Tree-ring indicators of German summer drought over the last millennium

Büntgen, Ulf; Trouet, Valérie; Frank, David; Leuschner, Hanns Hubert; Friedrichs, Dagmar A.; Luterbacher, Jürg; Esper, Jan

doi:10.1016/j.quascirev.2010.01.003

Cited by 113 publications

(85 citation statements)

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“…These biases are generated when the samples originate from varying heights on the trees, and they are especially strong at the recent chronology end if old living trees are all sampled at the same height in contrast with what happens with subfossils. In the previous STREC reconstruction, living trees were standardized apart from subfossil stems in order to attenuate this sampling height problem; an approach also used elsewhere to combine heterogeneous subfossil and living tree datasets (Büntgen et al 2010(Büntgen et al , 2011. In the present study all ring width chronologies were standardized using the "pivot correction", a new variant of the RCS approach specifically designed to remove the sampling height bias in our material (Autin et al 2015).…”

Section: Proxy Interpretationmentioning

confidence: 99%

Bayesian multiproxy temperature reconstruction with black spruce ring widths and stable isotopes from the northern Quebec taiga

et al. 2017

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Section: Proxy Interpretationmentioning

confidence: 99%

Bayesian multiproxy temperature reconstruction with black spruce ring widths and stable isotopes from the northern Quebec taiga

et al. 2017

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“…Furthermore, long-term palaeoclimatic perspectives offer an excellent basis to improve predictive models . Past climate conditions have been reconstructed using various proxies, such as tree rings (Büntgen et al, 2011), lake sediments (Last and Smol, 2001), historical documents (Brázdil et al, 2005(Brázdil et al, , 2010, marine sediments (Abrantes et al, 2005), corals (Goodkin et al, 2008), speleothems (Proctor et al, 2002), and, ideally, a combination thereof (Jones et al, 2009).…”

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confidence: 99%

“…Unfavourable climate conditions during the LIA had also a considerable impact in European societies (Fagan, 2000). They likely contributed to the decline of health and economic wealth of medieval societies triggered by the Black Death (Büntgen et al, 2011), for instance, and led to the abandonment of different areas such as Norse settlements in Greenland (Patterson et al, 2010;D'Andrea et al, 2011). Despite the precise chronology, the spatial extent and mechanisms behind these climatic phases still remain a subject of debate (Paasche and Bakke, 2010).…”

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confidence: 99%

“…The impact of the LIA on Central European ecosystems and societies has been widely documented (Büntgen et al, 2011;Magny et al, 2011b;Denton and Broecker, 2008). However, environmental responses to the LIA in the Mediterranean region are not yet well understood (Touchan et al, 2011;Esper et al, 2007;Büntgen et al, 2008Büntgen et al, , 2010bLuterbacher et al, 2005).…”

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“…However, environmental responses to the LIA in the Mediterranean region are not yet well understood (Touchan et al, 2011;Esper et al, 2007;Büntgen et al, 2008Büntgen et al, , 2010bLuterbacher et al, 2005). Several studies have suggested that the hydrological impact of climate changes will dramatically affect snow-fed watersheds, such as the headwaters of many rivers located in the Pyrenees (Beniston, 2003;García-Ruiz et al, 2011).…”

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A multi-proxy perspective on millennium-long climate variability in the Southern Pyrenees

Morellón

Pérez-Sanz²,

Corella

et al. 2012

Clim. Past

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Abstract. This paper reviews multi-proxy paleoclimatic reconstructions with robust age-control derived from lacustrine, dendrochronological and geomorphological records and characterizes the main environmental changes that occurred in the Southern Pyrenees during the last millennium. Warmer and relatively arid conditions prevailed during the Medieval Climate Anomaly (MCA, ca. 900-1300 AD), with a significant development of xerophytes and Mediterranean vegetation and limited deciduous tree formations (mesophytes). The Little Ice Age (LIA, 1300-1800 AD) was generally colder and moister, with an expansion of deciduous taxa and cold-adapted montane conifers. Two major phases occurred within this period: (i) a transition MCA-LIA, characterized by fluctuating, moist conditions and relatively cold temperatures (ca. 1300 and 1600 AD); and (ii) a second period, characterized by the coldest and most humid conditions, coinciding with maximum (recent) glacier advances (ca. 1600-1800 AD). Glaciers retreated after the LIA when warmer and more arid conditions dominated, interrupted by a short-living cooling episode during the late 19th to early 20th centuries. Some records suggest a response to solar activity with colder and slightly moister conditions during solar minima. Centennial-scale hydrological fluctuations are in phase with reconstructions of NAO variability, which appears to be one of the main climate mechanisms influencing rainfall variations in the region during the last millennium.

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Using seasonal climate scenarios in the ForageAhead annual forage production model for early drought impact assessment

et al. 2023

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High interannual variability of forage production in semiarid grasslands leads to uncertainties when livestock producers make decisions, such as buying additional feed, relocating animals, or using flexible stocking. Within‐season predictions of annual forage production (i.e., yearly production) can provide specific boundaries for producers to make these decisions with more information and possibly with higher confidence. In this study, we use a recently developed forage production model, ForageAhead, that uses environmental and seasonal climate variables to estimate the annual forage production as approximated by remotely sensed vegetation data. Because, among other variables, this model uses observed summer climate data, the model output cannot be produced early enough in the year (e.g., spring months) to inform within‐season management decisions. To address this issue, we developed summer climate scenarios (e.g., extremely warm and dry and moderately cool and wet) that serve as an input in the model in combination with observed winter and spring climate data from a particular year. The summer climate scenarios used historical summer precipitation and temperature data (1950–2018) categorized into three, five, and seven percentile categories. These percentile values were then combined to represent summer climate scenarios, which were further used as the ForageAhead model input. We tested the optimal number of percentile categories to be used as the model input to obtain accurate prediction of forage production while also minimizing the number of possible temperature and precipitation combinations, which increases with the number of percentile categories. For the 19‐year period analysis (2000–2018), we also determined the most and least common scenarios that occurred in the western United States. When using five percentile categories for summer precipitation and temperature, we were able to capture the interannual variability in the spatial extent of abnormally low and high biomass production. The ForageAhead predictions captured similar spatial patterns of forage anomalies as another similar model (Grass‐Cast). This method can be made available in a user‐friendly automated system that can be used by livestock producers and rangeland managers to inform within‐season management decisions. This method can be especially valuable for flexible stocking as it provides a range of possible annual forage production scenarios by the end of May.

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Tree-ring indicators of German summer drought over the last millennium

Cited by 113 publications

References 68 publications

Bayesian multiproxy temperature reconstruction with black spruce ring widths and stable isotopes from the northern Quebec taiga

Bayesian multiproxy temperature reconstruction with black spruce ring widths and stable isotopes from the northern Quebec taiga

A multi-proxy perspective on millennium-long climate variability in the Southern Pyrenees

Using seasonal climate scenarios in the ForageAhead annual forage production model for early drought impact assessment

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