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  • 2020-2023  (3)
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  • 1
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    Probing the timescale dependency of local and global variations in surface air temperature from climate simulations and reconstructions of the last millennia (2021)
    American Physical Society
    In:  Physical Review E, 104 (6). Art.Nr. 064136.
    Details
    Publication Date: 2022-01-17
    Description: Earth's climate can be understood as a dynamical system that changes due to external forcing and internal couplings. Essential climate variables, such as surface air temperature, describe this dynamics. Our current interglacial, the Holocene (11 700 yr ago to today), has been characterized by small variations in global mean temperature prior to anthropogenic warming. However, the mechanisms and spatiotemporal patterns of fluctuations around this mean, called temperature variability, are poorly understood despite their socioeconomic relevance for climate change mitigation and adaptation. Here we examine discrepancies between temperature variability from model simulations and paleoclimate reconstructions by categorizing the scaling behavior of local and global surface air temperature on the timescale of years to centuries. To this end, we contrast power spectral densities (PSD) and their power-law scaling using simulated and observation-based temperature series of the last 6000 yr. We further introduce the spectral gain to disentangle the externally forced and internally generated variability as a function of timescale. It is based on our estimate of the joint PSD of radiative forcing, which exhibits a scale break around the period of 7 yr. We find that local temperature series from paleoclimate reconstructions show a different scaling behavior than simulated ones, with a tendency towards stronger persistence (i.e., correlation between successive values within a time series) on periods of 10 to 200 yr. Conversely, the PSD and spectral gain of global mean temperature are consistent across data sets. Our results point to the limitation of climate models to fully represent local temperature statistics over decades to centuries. By highlighting the key characteristics of temperature variability, we pave a way to better constrain possible changes in temperature variability with global warming and assess future climate risks.
    Type: Article , PeerReviewed
    Format: text
    DOI: 10.1103/PhysRevE.104.064136
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 2
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    Identifying Global‐Scale Patterns of Vegetation Change During the Last Deglaciation From Paleoclimate Networks (2021)
    Details
    Publication Date: 2022-03-29
    Description: During the last deglaciation (∼19–11 ka before present), the global mean temperature increased by 3–8 K. The concurrent hydroclimate and land cover changes are not well constrained. Here, we use a pollen database to quantify global‐scale vegetation changes during this transitional period at orbital (∼104 years) and millennial timescales (∼103 years). We focus on the proportion of tree and shrub pollen, the arboreal pollen (AP) fraction. Temporal similarities over long distances are identified by a paleoclimate network approach. At the orbital scale, we find coherent AP variations in the low and mid‐latitudes which we attribute to the global climate forcing. While AP fractions predominantly increased through the deglaciation, we identify regions where AP fractions decreased. For millennial timescales, we do not observe spatially coherent similarity structures. We compare our results with networks computed from three deglacial climate simulations with the CCSM3, HadCM3, and LOVECLIM models. Networks based on simulated precipitation patterns reproduce the characteristics of the AP network. Sensitivity experiments with statistical emulators indicate that, indeed, precipitation variations explain the diagnosed patterns of vegetation change better than temperature and CO2 variations. Our findings support previous interpretations of deglacial forest evolution in the mid‐latitudes being the result of atmospheric circulation changes. The network analysis identifies differences in the vegetation‐climate‐CO2 relationship simulated by CCSM3 and HadCM3. We conclude that network analyses are a promising tool to benchmark transient climate simulations with dynamical vegetation changes. This may result in stronger constraints of future hydroclimate and land cover changes.
    Description: Plain Language Summary: We do not understand changes in rainfall and plant cover since the last ice age as good as temperature changes. Pollen is widely used to study which plants grew under which climate in the past. We check how many tree and shrub pollen, versus how many from herbs and grasses can be found in many locations. This shows how similar plant cover changes were in different regions. We find that plant cover changed similarly across all continents from the last ice age to the current warm period. During this transition, tree and shrub pollen increased while herbs and grasses decreased. However, we identify distinct regions where the change is the other way around. To understand this better, we use data from three climate models. The vegetation components of the climate models calculate how Earth's plant cover changed. By comparing the model results to pollen data, we find that the tree and shrub cover changes since the last ice age are better explained by rainfall than by temperature and carbon dioxide in the low and mid‐latitudes. Comparing the pollen data and model results in this way can help us to understand how well climate models simulate plant cover and rainfall changes.
    Description: Key Points: An analysis of arboreal pollen networks shows largely coherent vegetation changes in the low and mid‐latitudes during the last deglaciation. A comparison with climate simulations suggests that hydroclimate changes explain regionally anti‐correlated vegetation variations best. Our work is a promising step toward process‐based benchmarking of vegetation and hydroclimate in transient simulations of the deglaciation.
    Description: Deutsche Forschungsgemeinschaft (DFG) http://dx.doi.org/10.13039/501100001659
    Description: Bundesministerium für Bildung und Forschung (BMBF) http://dx.doi.org/10.13039/501100002347
    Keywords: ddc:561.1
    Language: English
    Type: doc-type:article
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  • 3
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    Contrasting State‐Dependent Effects of Natural Forcing on Global and Local Climate Variability (2022)
    Details
    Publication Date: 2022-10-04
    Description: Natural forcing from solar and volcanic activity contributes significantly to climate variability. The post‐eruption cooling of strong volcanic eruptions was hypothesized to have led to millennial‐scale variability during Glacials. Cooling induced by volcanic eruption is potentially weaker in the warmer climate. The underlying question is whether the climatic response to natural forcing is state‐dependent. Here, we quantify the response to natural forcing under Last Glacial and Pre‐Industrial conditions in an ensemble of climate model simulations. We evaluate internal and forced variability on annual to multicentennial scales. The global temperature response reveals no state dependency. Small local differences result mainly from state‐dependent sea ice changes. Variability in forced simulations matches paleoclimate reconstructions significantly better than in unforced scenarios. Considering natural forcing is therefore important for model‐data comparison and future projections.
    Description: Plain Language Summary: Climate variability describes the spatial and temporal variations of Earth's climate. Understanding these variations is important for estimating the occurrence of extreme climate events such as droughts. Yet, it is unclear whether climate variability depends on the mean surface temperature of the Earth or not. Here, we investigate the effects of natural forcing from volcanic eruptions and solar activity changes on climate variability. We compare simulations of a past (cold) and present (warm) climate with and without volcanism and solar changes. We find that overall, the climate system responds similarly to natural forcing in the cold and warm state. Small local differences mainly occur where ice can form. To evaluate the simulated variability, we use data from paleoclimate archives, including trees, ice‐cores, and marine sediments. Climate variability from forced simulations agrees better with the temperature variability obtained from data. Natural forcing is therefore critical for reliable simulation of variability in past and future climates.
    Description: Key Points: We present Glacial/Interglacial climate simulations and quantify effects of time‐varying volcanic and solar forcing on climate variability. The mean global and local response to these forcings is similar in Glacial and Interglacial climate, suggesting low state dependency. In both climate states, modeled temperature variance agrees better with palaeoclimate data when volcanic and solar forcing is included.
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Description: Heinrich Böll Stiftung (Heinrich Böll Foundation) http://dx.doi.org/10.13039/100009379
    Description: Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347
    Description: https://doi.org/10.5281/zenodo.6074747
    Description: https://github.com/paleovar/StateDependency
    Description: https://doi.org/10.5281/zenodo.6474769
    Keywords: ddc:551.6
    Language: English
    Type: doc-type:article
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    CITATION GEO-LEO
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