ALBERT

Description: We evaluated how ranges of four endemic and non-endemic aquatic ostracode species changed in response to long-term (glacial–interglacial cycles) and abrupt climate fluctuations during the last 155 kyr in the northern Neotropical region. We employed two complementary approaches, fossil records and species distribution models (SDMs). Fossil assemblages were obtained from sediment cores PI-1, PI-2, PI-6 and Petén-Itzá 22-VIII-99 from the Petén Itzá Scientific Drilling Project, Lake Petén Itzá, Guatemala. To obtain a spatially resolved pattern of (past) species distribution, a downscaling cascade is employed. SDMs were reconstructed for the last interglacial (∼120 ka), the last glacial maximum (∼22 ka) and the middle Holocene (∼6 ka). During glacial and interglacial cycles and marine isotope stages (MISs), modelled paleo-distributions and paleo-records show the nearly continuous presence of endemic and non-endemic species in the region, suggesting negligible effects of long-term climate variations on aquatic niche stability. During periods of abrupt ecological disruption such as Heinrich Stadial 1 (HS1), endemic species were resilient, remaining within their current areas of distribution. Non-endemic species, however, proved to be more sensitive. Modelled paleo-distributions suggest that the geographic range of non-endemic species changed, moving southward into Central America. Due to the uncertainties involved in the downscaling from the global numerical to the highly resolved regional geospatial statistical modelling, results can be seen as a benchmark for future studies using similar approaches. Given relatively moderate temperature decreases in Lake Petén Itzá waters (∼5 ∘C) and the persistence of some aquatic ecosystems even during periods of severe drying in HS1, our data suggest (1) the existence of micro-refugia and/or (2) continuous interaction between central metapopulations and surrounding populations, enabling aquatic taxa to survive climate fluctuations in the northern Neotropical region.

Description: Two statistical methods are tested to reconstruct the interannual variations in past sea surface temperatures (SSTs) of the North Atlantic (NA) Ocean over the past millennium based on annually resolved and absolutely dated marine proxy records of the bivalve mollusk Arctica islandica. The methods are tested in a pseudo-proxy experiment (PPE) setup using state-of-the-art climate models (CMIP5 Earth system models) and reanalysis data from the COBE2 SST data set. The methods were applied in the virtual reality provided by global climate simulations and reanalysis data to reconstruct the past NA SSTs using pseudo-proxy records that mimic the statistical characteristics and network of Arctica islandica. The multivariate linear regression methods evaluated here are principal component regression and canonical correlation analysis. Differences in the skill of the climate field reconstruction (CFR) are assessed according to different calibration periods and different proxy locations within the NA basin. The choice of the climate model used as a surrogate reality in the PPE has a more profound effect on the CFR skill than the calibration period and the statistical reconstruction method. The differences between the two methods are clearer for the MPI-ESM model due to its higher spatial resolution in the NA basin. The pseudo-proxy results of the CCSM4 model are closer to the pseudo-proxy results based on the reanalysis data set COBE2. Conducting PPEs using noise-contaminated pseudo-proxies instead of noise-free pseudo-proxies is important for the evaluation of the methods, as more spatial differences in the reconstruction skill are revealed. Both methods are appropriate for the reconstruction of the temporal evolution of the NA SSTs, even though they lead to a great loss of variance away from the proxy sites. Under reasonable assumptions about the characteristics of the non-climate noise in the proxy records, our results show that the marine network of Arctica islandica can be used to skillfully reconstruct the spatial patterns of SSTs at the eastern NA basin.

Description: Two statistical methods are tested to reconstruct the inter-annual variations of past sea surface temperatures (SSTs) of the North Atlantic (NA) Ocean over the past millennium, based on annually resolved and absolutely dated marine proxy records of the bivalve mollusk Arctica islandica. The methods are tested in a pseudo-proxy experiment (PPE) set-up using state-of-the-art climate models (CMIP5 Earth System Models) and reanalysis data from the COBE2 SST data set. The methods were applied in the virtual reality provided by global climate simulations and reanalysis data to reconstruct the past NA SSTs, using pseudoproxy records that mimic the statistical characteristics and network of Arctica islandica. The multivariate linear regression methods evaluated here are Principal Component Regression and Canonical Correlation Analysis. Differences in the skill of the Climate Field Reconstruction (CFR) are assessed according to different calibration periods and different proxy locations within the NA basin. The choice of the climate model used as surrogate reality in the PPE has a more profound effect on the CFR skill than the calibration period and the statistical reconstruction method. The differences between the two methods are clearer for the MPI-ESM model, due to its higher spatial resolution in the NA basin. The pseudo-proxy results of the CCSM4 model are closer to the pseudo-proxy results based on the reanalysis data set COBE2. The addition of noise in the pseudo-proxies is important for the evaluation of the methods, as more spatial differences in the reconstruction skill are revealed. More profound differences between methods are obtained when the number of proxy records is smaller than five, making the Principal Component Regression a more appropriate method in this case. Despite the differences, the results show that the marine network of Arctica islandica can be used to skilfully reconstruct the spatial patterns of SSTs at the eastern NA basin.

Description: The pre-industrial millennium is among the periods selected by the Paleoclimate Model Intercomparison Project (PMIP) for experiments contributing to the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and the fourth phase of the PMIP (PMIP4). The past1000 transient simulations serve to investigate the response to (mainly) natural forcing under background conditions not too different from today, and to discriminate between forced and internally generated variability on interannual to centennial timescales. This paper describes the motivation and the experimental set-ups for the PMIP4-CMIP6 past1000 simulations, and discusses the forcing agents orbital, solar, volcanic, and land use/land cover changes, and variations in greenhouse gas concentrations. The past1000 simulations covering the pre-industrial millennium from 850 Common Era (CE) to 1849 CE have to be complemented by historical simulations (1850 to 2014 CE) following the CMIP6 protocol. The external forcings for the past1000 experiments have been adapted to provide a seamless transition across these time periods. Protocols for the past1000 simulations have been divided into three tiers. A default forcing data set has been defined for the Tier 1 (the CMIP6 past1000) experiment. However, the PMIP community has maintained the flexibility to conduct coordinated sensitivity experiments to explore uncertainty in forcing reconstructions as well as parameter uncertainty in dedicated Tier 2 simulations. Additional experiments (Tier 3) are defined to foster collaborative model experiments focusing on the early instrumental period and to extend the temporal range and the scope of the simulations. This paper outlines current and future research foci and common analyses for collaborative work between the PMIP and the observational communities (reconstructions, instrumental data).

Description: We evaluated how ranges of four endemic and non-endemic aquatic ostracode species changed in response to long-term (glacial-interglacial cycles) and abrupt climate fluctuations during the last 155 ka in the northern Neotropical region. We employed two complementary approaches, fossil records and species distribution modeling (SDM). Fossil assemblages were obtained from sediment cores PI-1, PI-2, PI-6 and Petén-Itzá 22-VIII-99 from Petén Itzá Scientific Drilling Project, Lake Petén Itzá, Guatemala. To obtain a spatially resolved pattern of (past) species distribution, a downscaling cascade is employed. SDM's were reconstructed for the Last Interglacial (~ 120 ka BP), the Last Glacial Maximum (~ 22 ka BP) and the middle Holocene (~ 6 ka BP). During glacial/interglacial cycles and Marine Isotope Stages, modeled paleo-distributions and paleo-records show nearly continuous presence of endemic and non-endemic species in the region, suggesting negligible effects of long-term climate variations on aquatic niche stability. During periods of abrupt ecological disruption such as Heinrich Stadial 1 (HS1), endemic species were resilient, remaining within their current areas of distribution. Non-endemic species, however, proved to be more sensitive. Modeled paleo-distributions suggest that the geographic range of non-endemic species changed, moving southward into Central America. Due to the uncertainties involved in the downscaling from the global numerical to the highly resolved regional geospatial statistical modelling, results can be seen as benchmark for future studies using similar approaches. Given relatively moderate temperature decreases in Lake Petén Itzá waters (~ 5 ºC) and persistence of some aquatic ecosystems even during periods of severe drying in HS1, our data suggest 1) existence of micro-refugia and/or 2) continuous interaction between central metapopulations and surrounding populations, enabling aquatic taxa to survive climate fluctuations in the northern Neotropical region.

Description: The large variety of atmospheric circulation systems affecting the East Asian climate is reflected by the complex Asian vegetation distribution. Particularly in the transition zones of these circulation systems, vegetation is supposed to be very sensitive to climate change. Since proxy records are scarce, hitherto a mechanistic understanding of the past spatio-temporal climate-vegetation relationship is lacking. To assess the Holocene vegetation change and to obtain an ensemble of potential mid-Holocene biome distributions for Eastern Asia, we forced the diagnostic biome model BIOME4 with climate anomalies of different transient Holocene climate simulations performed in coupled atmosphere-ocean(-vegetation) models. The simulated biome changes are compared with pollen-based biome records for different key regions. In all simulations, substantial biome shifts during the Holocene are confined to the high-northern latitudes and the Monsoon-Westerlies transition zone, but the temporal evolution and amplitude of change strongly depends on the climate forcing. Large parts of the southern tundra are replaced by taiga during the mid-Holocene due to a warmer growing season and the boreal treeline in northern Asia is shifted northward by approx. 4° in the ensemble mean, ranging from 1.5° to 6° in the individual simulations, respectively. This simulated treeline shift is in agreement with pollen-based reconstructions from northern Siberia. The desert fraction in the transition zone is reduced by 21 % during the mid-Holocene compared to pre-industrial due to enhanced precipitation. The desert- steppe margin is shifted westward by 5° (1°–9° in the individual simulations). The forest biomes are expanded north-westward by 2° ranging from 0°–4° in the single simulations. These results corroborate pollen-based reconstructions indicating an extended forest area in north Central China during the mid-Holocene. According to the model, the forest-to-non-forest and steppe-to-desert changes in the climate transition zones are spatially not uniform and not linear during the Holocene.

Description: We analyse the variability of the probability distribution of daily wind speed in wintertime over Northern and Central Europe in a series of global and regional climate simulations covering the last centuries, and in reanalysis products covering approximately the last 60 years. The focus of the study lies on identifying the link of the variations in the wind speed distribution to the regional near-surface temperature, to the meridional temperature gradient and to the North Atlantic Oscillation. Our main result is that the link between the daily wind distribution and the regional climate drivers is strongly model dependent. The global models tend to behave similarly, although they show some discrepancies. The two regional models also tend to behave similarly to each other, but surprisingly the results derived from each regional model strongly deviates from the results derived from its driving global model. In addition, considering multi-centennial timescales, we find in two global simulations a long-term tendency for the probability distribution of daily wind speed to widen through the last centuries. The cause for this widening is likely the effect of the deforestation prescribed in these simulations. We conclude that no clear systematic relationship between the mean temperature, the temperature gradient and/or the North Atlantic Oscillation, with the daily wind speed statistics can be inferred from these simulations. The understanding of past and future changes in the distribution of wind speeds, and thus of wind speed extremes, will require a detailed analysis of the representation of the interaction between large-scale and small-scale dynamics.

Description: Climate reconstructions are means to extract the signal from uncertain paleo-observations, so-called proxies. It is essential to evaluate these reconstructions to understand and quantify their uncertainties. Similarly, comparing climate simulations and proxies requires approaches to bridge the temporal and spatial differences between both and to address their specific uncertainties. One way to achieve these two goals is so-called pseudoproxies. These are surrogate proxy records within the virtual reality of a climate simulation. They in turn depend on an understanding of the uncertainties of the real proxies including the noise characteristics disturbing the original environmental signal. Common pseudoproxy approaches so far concentrate on data with high temporal resolution over the last approximately 2000 years. Here we provide a simple but flexible noise model for potentially low-resolution sedimentary climate proxies for temperature on millennial timescales, the code for calculating a set of pseudoproxies from a simulation, and one example of pseudoproxies. The noise model considers the influence of other environmental variables, a dependence on the climate state, a bias due to changing seasonality, modifications of the archive (for example bioturbation), potential sampling variability, and a measurement error. Model, code, and data allow us to develop new ways of comparing simulation data with proxies on long timescales. Code and data are available at https://doi.org/10.17605/OSF.IO/ZBEHX (Bothe et al., 2018).

Description: The large variety of atmospheric circulation systems affecting the eastern Asian climate is reflected by the complex Asian vegetation distribution. Particularly in the transition zones of these circulation systems, vegetation is supposed to be very sensitive to climate change. Since proxy records are scarce, hitherto a mechanistic understanding of the past spatio-temporal climate–vegetation relationship is lacking. To assess the Holocene vegetation change and to obtain an ensemble of potential mid-Holocene biome distributions for eastern Asia, we forced the diagnostic biome model BIOME4 with climate anomalies of different transient Holocene climate simulations performed in coupled atmosphere–ocean(–vegetation) models. The simulated biome changes are compared with pollen-based biome records for different key regions.In all simulations, substantial biome shifts during the last 6000 years are confined to the high northern latitudes and the monsoon–westerly wind transition zone, but the temporal evolution and amplitude of change strongly depend on the climate forcing. Large parts of the southern tundra are replaced by taiga during the mid-Holocene due to a warmer growing season and the boreal treeline in northern Asia is shifted northward by approx. 4° in the ensemble mean, ranging from 1.5 to 6° in the individual simulations, respectively. This simulated treeline shift is in agreement with pollen-based reconstructions from northern Siberia. The desert fraction in the transition zone is reduced by 21 % during the mid-Holocene compared to pre-industrial due to enhanced precipitation. The desert–steppe margin is shifted westward by 5° (1–9° in the individual simulations). The forest biomes are expanded north-westward by 2°, ranging from 0 to 4° in the single simulations. These results corroborate pollen-based reconstructions indicating an extended forest area in north-central China during the mid-Holocene. According to the model, the forest-to-non-forest and steppe-to-desert changes in the climate transition zones are spatially not uniform and not linear since the mid-Holocene.

Description: Climate reconstructions are means to extract the signal from uncertain paleo-observations, i.e. proxies. It is essential to evaluate these to understand and quantify their uncertainties. Similarly, comparing climate simulations and proxies requires approaches to bridge the, e.g., temporal and spatial differences between both and address their specific uncertainties. One way to achieve these two goals are so called pseudoproxies. These are surrogate proxy records within, e.g., the virtual reality of a climate simulation. They in turn depend on an understanding of the uncertainties of the real proxies, i.e. the noise-characteristics disturbing the original environmental signal. Common pseudoproxy approaches so far concentrated on data with high temporal resolution from, e.g., tree-rings or ice-cores over the last approximately 2,000 years. Here we provide a simple but flexible noise model for potentially low-resolution sedimentary climate proxies for temperature on millennial time-scales, the code for calculating a set of pseudoproxies from a simulation and, for one simulation, the pseudoproxies themselves. The noise model considers the influence of other environmental variables, a dependence on the climate state, a bias due to changing seasonality, modifications of the archive (e.g., bioturbation), potential sampling variability, and a measurement error. Model, code, and data should allow to develop new ways of comparing simulation data with proxies on long time-scales. Code and data are available at https://doi.org/10.17605/OSF.IO/ZBEHX.