Beschreibung: We present here the first results, for the preindustrial and mid-Holocene climatological periods, of the newly developed isotope-enhanced version of the fully coupled Earth system model MPI-ESM, called hereafter MPI-ESM-wiso. The water stable isotopes H162O, H182O and HDO have been implemented into all components of the coupled model setup. The mid-Holocene provides the opportunity to evaluate the model response to changes in the seasonal and latitudinal distribution of insolation induced by different orbital forcing conditions. The results of our equilibrium simulations allow us to evaluate the performance of the isotopic model in simulating the spatial and temporal variations of water isotopes in the different compartments of the hydrological system for warm climates. For the preindustrial climate, MPI-ESM-wiso reproduces very well the observed spatial distribution of the isotopic content in precipitation linked to the spatial variations in temperature and precipitation rate. We also find a good model–data agreement with the observed distribution of isotopic composition in surface seawater but a bias with the presence of surface seawater that is too 18O-depleted in the Arctic Ocean. All these results are improved compared to the previous model version ECHAM5/MPIOM. The spatial relationships of water isotopic composition with temperature, precipitation rate and salinity are consistent with observational data. For the preindustrial climate, the interannual relationships of water isotopes with temperature and salinity are globally lower than the spatial ones, consistent with previous studies. Simulated results under mid-Holocene conditions are in fair agreement with the isotopic measurements from ice cores and continental speleothems. MPI-ESM-wiso simulates a decrease in the isotopic composition of precipitation from North Africa to the Tibetan Plateau via India due to the enhanced monsoons during the mid-Holocene. Over Greenland, our simulation indicates a higher isotopic composition of precipitation linked to higher summer temperature and a reduction in sea ice, shown by positive isotope–temperature gradient. For the Antarctic continent, the model simulates lower isotopic values over the East Antarctic plateau, linked to the lower temperatures during the mid-Holocene period, while similar or higher isotopic values are modeled over the rest of the continent. While variations of isotopic contents in precipitation over West Antarctica between mid-Holocene and preindustrial periods are partly controlled by changes in temperature, the transport of relatively 18O-rich water vapor near the coast to the western ice core sites could play a role in the final isotopic composition. So, more caution has to be taken about the reconstruction of past temperature variations during warm periods over this area. The coupling of such a model with an ice sheet model or the use of a zoomed grid centered on this region could help to better describe the role of the water vapor transport and sea ice around West Antarctica. The reconstruction of past salinity through isotopic content in sea surface waters can be complicated for regions with strong ocean dynamics, variations in sea ice regimes or significant changes in freshwater budget, giving an extremely variable relationship between the isotopic content and salinity of ocean surface waters over small spatial scales. These complicating factors demonstrate the complexity of interpreting water isotopes as past climate signals of warm periods like the mid-Holocene. A systematic isotope model intercomparison study for further insights on the model dependency of these results would be beneficial.

Beschreibung: Mineral dust aerosol constitutes an important component of the Earth's climate system, not only on short timescales due to direct and indirect influences on the radiation budget but also on long timescales by acting as a fertilizer for the biosphere and thus affecting the global carbon cycle. For a quantitative assessment of its impact on the global climate, state-of-the-art atmospheric and aerosol models can be utilized. In this study, we use the ECHAM6.3-HAM2.3 model to perform global simulations of the mineral dust cycle for present-day (PD), pre-industrial (PI), and last glacial maximum (LGM) climate conditions. The intercomparison with marine sediment and ice core data, as well as other modeling studies, shows that the obtained annual dust emissions of 1221, 923, and 5159 Tg for PD, PI, and LGM, respectively, generally agree well with previous findings. Our analyses focusing on the Southern Hemisphere suggest that over 90 % of the mineral dust deposited over Antarctica are of Australian or South American origin during both PI and LGM. However, contrary to previous studies, we find that Australia contributes a higher proportion during the LGM, which is mainly caused by changes in the precipitation patterns. Obtained increased particle radii during the LGM can be traced back to increased sulfate condensation on the particle surfaces as a consequence of longer particle lifetimes. The meridional transport of mineral dust from its source regions to the South Pole takes place at different altitudes depending on the grain size of the dust particles. We find a trend of generally lower transport heights during the LGM compared to PI as a consequence of reduced convection due to colder surfaces, indicating a vertically less extensive Polar cell.

Beschreibung: We present a climatology of the near-sea-surface temperature (NSST) anomaly and the sea-ice extent during the Last Glacial Maximum (LGM, 23 000–19 000 years before present) mapped on a global regular 1∘×1∘ grid. It is an extension of the Glacial Atlantic Ocean Mapping (GLAMAP) reconstruction of the Atlantic NSST based on the faunal and floral assemblage data of the Multiproxy Approach for the Reconstruction of the Glacial Ocean Surface (MARGO) project and several recent estimates of the LGM sea-ice extent. Such a gridded climatology is highly useful for the visualization of the LGM climate, calculation of global and regional NSST averages, and estimation of the equilibrium climate sensitivity, as well as a boundary condition for atmospheric general circulation models. The gridding of the sparse NSST reconstruction was done in an optimal way using the Data-Interpolating Variational Analysis (DIVA) software, which takes into account the uncertainty in the reconstruction and includes the calculation of an error field. The resulting Glacial Ocean Map (GLOMAP) confirms the previous findings by the MARGO project regarding longitudinal and meridional NSST differences that were greater than today in all oceans. Taken at face value, the estimated global and tropical cooling would imply an equilibrium climate sensitivity at the lower end of the currently accepted range. However, because of anticipated changes in the seasonality and thermal structure of the upper ocean during the LGM as well as uneven spatial sampling, the estimated cooling and implied climate sensitivity are likely to be biased towards lower values.

Beschreibung: In order to investigate the impact of spatial resolution on the discrepancy between simulated δ18O and observed δ18O in Greenland ice cores, regional climate simulations are performed with the isotope-enabled regional climate model (RCM) COSMO_iso. For this purpose, isotope-enabled general circulation model (GCM) simulations with the ECHAM5-wiso general circulation model (GCM) under present-day conditions and the MPI-ESM-wiso GCM under mid-Holocene conditions are dynamically downscaled with COSMO_iso for the Arctic region. The capability of COSMO_iso to reproduce observed isotopic ratios in Greenland ice cores for these two periods is investigated by comparing the simulation results to measured δ18O ratios from snow pit samples, Global Network of Isotopes in Precipitation (GNIP) stations and ice cores. To our knowledge, this is the first time that a mid-Holocene isotope-enabled RCM simulation is performed for the Arctic region. Under present-day conditions, a dynamical downscaling of ECHAM5-wiso (1.1∘×1.1∘ ) with COSMO_iso to a spatial resolution of 50 km improves the agreement with the measured δ18O ratios for 14 of 19 observational data sets. A further increase in the spatial resolution to 7 km does not yield substantial improvements except for the coastal areas with its complex terrain. For the mid-Holocene, a fully coupled MPI-ESM-wiso time slice simulation is downscaled with COSMO_iso to a spatial resolution of 50 km. In the mid-Holocene, MPI-ESM-wiso already agrees well with observations in Greenland and a downscaling with COSMO_iso does not further improve the model–data agreement. Despite this lack of improvement in model biases, the study shows that in both periods, observed δ18O values at measurement sites constitute isotope ratios which are mainly within the subgrid-scale variability of the global ECHAM5-wiso and MPI-ESM-wiso simulation results. The correct δ18O ratios are consequently not resolved in the GCM simulation results and need to be extracted by a refinement with an RCM. In this context, the RCM simulations provide a spatial δ18O distribution by which the effects of local uncertainties can be taken into account in the comparison between point measurements and model outputs. Thus, an isotope-enabled GCM–RCM model chain with realistically implemented fractionating processes constitutes a useful supplement to reconstruct regional paleo-climate conditions during the mid-Holocene in Greenland. Such model chains might also be applied to reveal the full potential of GCMs in other regions and climate periods, in which large deviations relative to observed isotope ratios are simulated.

Beschreibung: Numerical modeling enables a comprehensive understanding not only of the Earth's system today, but also of the past. To date, a significant amount of time and effort has been devoted to paleoclimate modeling and analysis, which involves the latest and most advanced Paleoclimate Modelling Intercomparison Project phase 4 (PMIP4). The definition of seasonality, which is influenced by slow variations in the Earth's orbital parameters, plays a key role in determining the calculated seasonal cycle of the climate. In contrast to the classical calendar used today, where the lengths of the months and seasons are fixed, the angular calendar calculates the lengths of the months and seasons according to a fixed number of degrees along the Earth's orbit. When comparing simulation results for different time intervals, it is essential to account for the angular calendar to ensure that the data for comparison are from the same position along the Earth's orbit. Most models use the classical calendar, which can lead to strong distortions of the monthly and seasonal values, especially for the climate of the past. Here, by analyzing daily outputs from multiple PMIP4 model simulations, we examine calendar effects on surface air temperature and precipitation under mid-Holocene, Last Interglacial, and pre-industrial climate conditions. We came to the following conclusions. (a) The largest cooling bias occurs in boreal autumn when the classical calendar is applied for the mid-Holocene and Last Interglacial, due to the fact that the vernal equinox is fixed on 21 March. (b) The sign of the temperature anomalies between the Last Interglacial and pre-industrial in boreal autumn can be reversed after the switch from the classical to angular calendar, particularly over the Northern Hemisphere continents. (c) Precipitation over West Africa is overestimated in boreal summer and underestimated in boreal autumn when the classical seasonal cycle is applied. (d) Finally, month-length adjusted values for surface air temperature and precipitation are very similar to the day-length adjusted values, and therefore correcting the calendar based on the monthly model results can largely reduce the artificial bias. In addition, we examine the calendar effects in three transient simulations for 6–0 ka by AWI-ESM, MPI-ESM, and IPSL-CM. We find significant discrepancies between adjusted and unadjusted temperature values over continents for both hemispheres in boreal autumn, while for other seasons the deviations are relatively small. A drying bias can be found in the summer monsoon precipitation in Africa (in the classical calendar), whereby the magnitude of bias becomes smaller over time. Overall, our study underlines the importance of the application of calendar transformation in the analysis of climate simulations. Neglecting the calendar effects could lead to a profound artificial distortion of the calculated seasonal cycle of surface air temperature and precipitation.

Beschreibung: The incorporation of water isotopologues into the hydrology of general circulation models (GCMs) facilitates the comparison between modeled and measured proxy data in paleoclimate archives. However, the variability and drivers of measured and modeled water isotopologues, as well as the diversity of their representation in different models, are not well constrained. Improving our understanding of this variability in past and present climates will help to better constrain future climate change projections and decrease their range of uncertainty. Speleothems are a precisely datable terrestrial paleoclimate archives and provide well-preserved (semi-)continuous multivariate isotope time series in the lower latitudes and mid-latitudes and are therefore well suited to assess climate and isotope variability on decadal and longer timescales. However, the relationships of speleothem oxygen and carbon isotopes to climate variables are influenced by site-specific parameters, and their comparison to GCMs is not always straightforward. Here we compare speleothem oxygen and carbon isotopic signatures from the Speleothem Isotopes Synthesis and Analysis database version 2 (SISALv2) to the output of five different water-isotope-enabled GCMs (ECHAM5-wiso, GISS-E2-R, iCESM, iHadCM3, and isoGSM) over the last millennium (850–1850 CE). We systematically evaluate differences and commonalities between the standardized model simulation outputs. The goal is to distinguish climatic drivers of variability for modeled isotopes and compare them to those of measured isotopes. We find strong regional differences in the oxygen isotope signatures between models that can partly be attributed to differences in modeled surface temperature. At low latitudes, precipitation amount is the dominant driver for stable water isotope variability; however, at cave locations the agreement between modeled temperature variability is higher than for precipitation variability. While modeled isotopic signatures at cave locations exhibited extreme events coinciding with changes in volcanic and solar forcing, such fingerprints are not apparent in the speleothem isotopes. This may be attributed to the lower temporal resolution of speleothem records compared to the events that are to be detected. Using spectral analysis, we can show that all models underestimate decadal and longer variability compared to speleothems (albeit to varying extents). We found that no model excels in all analyzed comparisons, although some perform better than the others in either mean or variability. Therefore, we advise a multi-model approach whenever comparing proxy data to modeled data. Considering karst and cave internal processes, e.g., through isotope-enabled karst models, may alter the variability in speleothem isotopes and play an important role in determining the most appropriate model. By exploring new ways of analyzing the relationship between the oxygen and carbon isotopes, their variability, and co-variability across timescales, we provide methods that may serve as a baseline for future studies with different models using, e.g., different isotopes, different climate archives, or different time periods.

Beschreibung: Stable water isotopes in polar ice cores are widely used to reconstruct past temperature variations over several orbital climatic cycles. One way to calibrate the isotope–temperature relationship is to apply the present-day spatial relationship as a surrogate for the temporal one. However, this method leads to large uncertainties because several factors like the sea surface conditions or the origin and transport of water vapor influence the isotope–temperature temporal slope. In this study, we investigate how the sea surface temperature (SST), the sea ice extent, and the strength of the Atlantic Meridional Overturning Circulation (AMOC) affect these temporal slopes in Greenland and Antarctica for Last Glacial Maximum (LGM, ∼ 21 000 years ago) to preindustrial climate change. For that, we use the isotope-enabled atmosphere climate model ECHAM6-wiso, forced with a set of sea surface boundary condition datasets based on reconstructions (e.g., GLOMAP) or MIROC 4m simulation outputs. We found that the isotope–temperature temporal slopes in East Antarctic coastal areas are mainly controlled by the sea ice extent, while the sea surface temperature cooling affects the temporal slope values inland more. On the other hand, ECHAM6-wiso simulates the impact of sea ice extent on the EPICA Dome C (EDC) and Vostok sites through the contribution of water vapor from lower latitudes. Effects of sea surface boundary condition changes on modeled isotope–temperature temporal slopes are variable in West Antarctica. This is partly due to the transport of water vapor from the Southern Ocean to this area that can dampen the influence of local temperature on the changes in the isotopic composition of precipitation and snow. In the Greenland area, the isotope–temperature temporal slopes are influenced by the sea surface temperatures near the coasts of the continent. The greater the LGM cooling off the coast of southeastern Greenland, the greater the transport of water vapor from the North Atlantic, and the larger the temporal slopes. The presence or absence of sea ice very near the coast has a large influence in Baffin Bay and the Greenland Sea and influences the slopes at some inland ice core stations. The extent of the sea ice far south slightly influences the temporal slopes in Greenland through the transport of more depleted water vapor from lower latitudes to this area. The seasonal variations of sea ice distribution, especially its retreat in summer, influence the isotopic composition of the water vapor in this region and the modeled isotope–temperature temporal slopes in the eastern part of Greenland. A stronger LGM AMOC decreases LGM-to-preindustrial isotopic anomalies in precipitation in Greenland, degrading the isotopic model–data agreement. The AMOC strength modifies the temporal slopes over inner Greenland slightly and by a little on the coasts along the Greenland Sea where the changes in surface temperature and sea ice distribution due to the AMOC strength mainly occur.

Beschreibung: Global warming is associated with large increases in surface air temperature in Siberia. Here, we apply the isotope-enabled atmospheric general circulation model ECHAM5-wiso to explore the potential of water isotope measurements at a recently opened monitoring station in Kourovka (57.04° N, 59.55° E) in order to successfully trace climate change in western Siberia. Our model is constrained to atmospheric reanalysis fields for the period 1957–2013 to facilitate the comparison with observations of δD in total column water vapour from the GOSAT satellite, and with precipitation δ18O measurements from 15 Russian stations of the Global Network of Isotopes in Precipitation. The model captures the observed Russian climate within reasonable error margins, and displays the observed isotopic gradients associated with increasing continentality and decreasing meridional temperatures. The model also reproduces the observed seasonal cycle of δ18O, which parallels the seasonal cycle of temperature and ranges from −25 ‰ in winter to −5 ‰ in summer. Investigating West Siberian climate and precipitation δ18O variability during the last 50 years, we find long-term increasing trends in temperature and δ18O, while precipitation trends are uncertain. During the last 50 years, winter temperatures have increased by 1.7 °C. The simulated long-term increase of precipitation δ18O is at the detection limit (〈1 ‰ per 50 years) but significant. West Siberian climate is characterized by strong interannual variability, which in winter is strongly related to the North Atlantic Oscillation. In winter, regional temperature is the predominant factor controlling δ18O variations on interannual to decadal timescales with a slope of about 0.5 ‰ / °C. In summer, the interannual variability of δ18O can be attributed to short-term, regional-scale processes such as evaporation and convective precipitation. This finding suggests that precipitation δ18O has the potential to reveal hydrometeorological regime shifts in western Siberia which are otherwise difficult to identify. Focusing on Kourovka, the simulated evolution of temperature, δ18O and, to a smaller extent, precipitation during the last 50 years is synchronous with model results averaged over all of western Siberia, suggesting that this site will be representative to monitor future isotopic changes in the entire region.

Beschreibung: Water stable isotopologues provide integrated tracers of the atmospheric water cycle, affected by changes in air mass origin, non-convective and convective processes and continental recycling. Novel remote sensing and in situ measuring techniques have recently offered opportunities for monitoring atmospheric water vapour isotopic composition. Recently developed infrared laser spectrometers allow for continuous in situ measurements of surface water vapour δDv and δ18Ov. So far, very few intercomparisons of measurements conducted using different techniques have been achieved at a given location, due to difficulties intrinsic to the comparison of integrated with local measurements. Nudged simulations conducted with high-resolution isotopically enabled general circulation models (GCMs) provide a consistent framework for comparison with the different types of observations. Here, we compare simulations conducted with the ECHAM5-wiso model with two types of water vapour isotopic data obtained during summer 2012 at the forest site of Kourovka, western Siberia: hourly ground-based FTIR total atmospheric columnar δDv amounts, and in situ hourly Picarro δDv measurements. There is an excellent correlation between observed and predicted δDv at surface while the comparison between water column values derived from the model compares well with FTIR estimates.

Beschreibung: 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.