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Improving our understanding of the controls on Antarctic precipitation is critical for gaining insights into past and future polar and global environmental changes. Here we develop innovative water tracing diagnostics in the atmospheric general circulation model ECHAM6. These tracers provide new detailed information on moisture source locations and properties of Antarctic precipitation. In the preindustrial simulation, annual mean Antarctic precipitation originating from the open ocean has a source latitude range of 49–35∘ S, a source sea surface temperature range of 9.8–16.3 ∘C, a source 2 m relative humidity range of 75.6 %–83.3 %, and a source 10 m wind velocity (vel10) range of 10.1 to 11.3 m s−1. These results are consistent with estimates from existing literature. Central Antarctic precipitation is sourced from more equatorward (distant) sources via elevated transport pathways compared to coastal Antarctic precipitation. This has been attributed to a moist isentropic framework; i.e. poleward vapour transport tends to follow constant equivalent potential temperature. However, we find notable deviations from this tendency especially in the lower troposphere, likely due to radiative cooling. Heavy precipitation is sourced by longer-range moisture transport: it comes from 2.9∘ (300 km, averaged over Antarctica) more equatorward (distant) sources compared to the rest of precipitation. Precipitation during negative phases of the Southern Annular Mode (SAM) also comes from more equatorward moisture sources (by 2.4∘, averaged over Antarctica) compared to precipitation during positive SAM phases, likely due to amplified planetary waves during negative SAM phases. Moreover, source vel10 of annual mean precipitation is on average 2.1 m s−1 higher than annual mean vel10 at moisture source locations from which the precipitation originates. This shows that the evaporation of moisture driving Antarctic precipitation occurs under windier conditions than average. We quantified

The Atlantic Meridional Overturning Circulation (AMOC) is a key feature of the North Atlantic with global ocean impacts. The AMOC's response to past changes in forcings during the Holocene provides important context for the coming centuries. Here, we investigate AMOC trends using an emerging set of transient simulations using multiple global climate models for the past 6,000 years. Although some models show changes, no consistent trend in overall AMOC strength during the mid-to-late Holocene emerges from the ensemble. We interpret this result to suggest no overall change in AMOC, which fits with our assessment of available proxy reconstructions. The decadal variability of the AMOC does not change in ensemble during the mid- and late-Holocene. There are interesting AMOC changes seen in the early Holocene, but their nature depends a lot on which inputs are used to drive the experiment.

In order to quantify the relative importance of individual boundary conditions and forcings, including greenhouse gases, ice sheets, and Earth's orbital parameters, on determining Last Glacial Maximum (LGM) climate, we have performed a series of LGM experiments using a state-of-the-art climate model AWI-ESM, in which different combinations of boundary conditions and forcings have been applied following the protocol of Paleoclimate Modelling Intercomparison Project phase 4 (PMIP4). In good agreement with observational proxy records, a general colder and drier climate is simulated in our full-forced LGM experiment as compared to the present-day simulation. Our simulated results from non-full-forced sensitivity simulations reveal that both the greenhouse gases and ice sheets play a major role in defining the anomalous LGM surface temperature compared to today. Decreased greenhouse gases in LGM as compared to present day leads to a non-uniform global cooling with polar amplification effect. The presence of LGM ice sheets favors a warming over the Arctic and northern Atlantic oceans in boreal winter, as well as a cooling over regions with the presence of ice sheets. The former is induced by a strengthening in the Atlantic meridional overturning circulation (AMOC) transporting more heat to high latitudes, whilst the latter is due to the increased surface albedo and elevation of ice sheets. We find that the Northern Hemisphere monsoon precipitation is influenced by the opposing effects of LGM greenhouse gases and ice sheets. Specifically, the presence of ice sheets leads to significant drying in the Northern Hemisphere monsoon regions, while a reduction in greenhouse gases results in increased monsoon rainfall. Based on our model results, continental ice sheets exert a major control on atmospheric dynamics and the variability of El Niño–Southern Oscillation (ENSO). Moreover, our analysis also implies a nonlinearity in climate response to LGM boundary conditions and forcing

Using transient climate forcing based on simulations from the Alfred Wegener Institute Earth System Model (AWI-ESM), we simulate the evolution of the Greenland Ice Sheet (GrIS) from the last interglacial (125 ka, kiloyear before present) to 2100 AD with the Parallel Ice Sheet Model (PISM). The impact of paleoclimate, especially Holocene climate, on the present and future evolution of the GrIS is explored. Our simulations of the past show close agreement with reconstructions with respect to the recent timing of the peaks in ice volume and the climate of Greenland. The maximum and minimum ice volume at around 18–17 ka and 6–5 ka lag the respective extremes in climate by several thousand years, implying that the ice volume response of the GrIS strongly lags climatic changes. Given that Greenland’s climate was getting colder from the Holocene Thermal Maximum (i.e., 8 ka) to the Pre-Industrial era, our simulation implies that the GrIS experienced growth from the mid-Holocene to the industrial era. Due to this background trend, the GrIS still gains mass until the second half of the 20th century, even though anthropogenic warming begins around 1850 AD. This is also in agreement with observational evidence showing mass loss of the GrIS does not begin earlier than the late 20th century. Our results highlight that the present evolution of the GrIS is not only controlled by the recent climate changes, but is also affected by paleoclimate, especially the relatively warm Holocene climate. We propose that the GrIS was not in equilibrium throughout the entire Holocene and that the slow response to Holocene climate needs to be represented in ice sheet simulations in order to predict ice mass loss, and therefore sea level rise, accurately.

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 f

Variability on centennial to multi-centennial timescales is mentioned as a feature in reconstructions of the Holocene climate. As more long transient model simulations with complex climate models become available and efforts have been made to compile large proxy databases, there is now a unique opportunity to study multi-centennial variability with greater detail and a large amount of data than earlier. This paper presents a spectral analysis of transient Holocene simulations from 9 models and 120 proxy records to find the common signals related to oscillation periods and geographic dependencies and discuss the implications for the potential driving mechanisms. Multi-centennial variability is significant in most proxy records, with the dominant oscillation periods around 120–130 years and an average of 240 years. Spectra of model-based global mean temperature (GMT) agree well with proxy evidence with significant multi-centennial variability in all simulations with the dominant oscillation periods around 120–150 years. It indicates a comparatively good agreement between model and proxy data. A lack of latitudinal dependencies in terms of oscillation period is found in both the model and proxy data. However, all model simulations have the highest spectral density distributed over the Northern hemisphere high latitudes, which could indicate a particular variability sensitivity or potential driving mechanisms in this region. Five models also have differentiated forcings simulations with various combinations of forcing agents. Significant multi-centennial variability with oscillation periods between 100 and 200 years is found in all forcing scenarios, including those with only orbital forcing. The different forcings induce some variability in the system. Yet, none appear to be the predominant driver based on the spectral analysis. Solar irradiance has long been hypothesized to be a primary driver of multi-centennial variability. However, all the simulations without this

Variability on centennial to multi-centennial timescales is mentioned as a feature in reconstructions of the Holocene climate. As more long transient model simulations with complex climate models become available and efforts have been made to compile large proxy databases, there is now a unique opportunity to study multi-centennial variability with greater detail and a large amount of data than earlier. This paper presents a spectral analysis of transient Holocene simulations from 9 models and 120 proxy records to find the common signals related to oscillation periods and geographic dependencies and discuss the implications for the potential driving mechanisms. Multi-centennial variability is significant in most proxy records, with the dominant oscillation periods around 120–130 years and an average of 240 years. Spectra of model-based global mean temperature (GMT) agree well with proxy evidence with significant multi-centennial variability in all simulations with the dominant oscillation periods around 120–150 years. It indicates a comparatively good agreement between model and proxy data. A lack of latitudinal dependencies in terms of oscillation period is found in both the model and proxy data. However, all model simulations have the highest spectral density distributed over the Northern hemisphere high latitudes, which could indicate a particular variability sensitivity or potential driving mechanisms in this region. Five models also have differentiated forcings simulations with various combinations of forcing agents. Significant multi-centennial variability with oscillation periods between 100 and 200 years is found in all forcing scenarios, including those with only orbital forcing. The different forcings induce some variability in the system. Yet, none appear to be the predominant driver based on the spectral analysis. Solar irradiance has long been hypothesized to be a primary driver of multi-centennial variability. However, all the simulations without this

Southern hemispheric sea-ice impacts ocean circulation and the carbon exchange between the atmosphere and the ocean. Sea-ice is therefore one of the key processes in past and future climate change and variability. As climate models are the only tool available to project future climate change, it is important to assess their performance against observations for a range of different climate states. The Last Glacial Maximum (LGM, ∼21 000 years ago) represents an interesting target as it is a relatively well-documented period with climatic conditions very different from preindustrial conditions. Here, we analyze the LGM seasonal Southern Ocean sea-ice cover as simulated in numerical simulations as part of the Paleoclimate Modelling Intercomparison Project (PMIP) phases 3 and 4. We compare the model outputs to a recently updated compilation of LGM seasonal Southern Ocean sea-ice cover and summer sea surface temperature (SST) to assess the most likely LGM Southern Ocean state. Simulations and paleo-proxy records suggest a fairly well-constrained glacial winter sea-ice edge between 50.5 and 51∘ S. However, the spread in simulated glacial summer sea-ice is wide, ranging from almost ice-free conditions to a sea-ice edge reaching 53∘ S. Combining model outputs and proxy data, we estimate a likely LGM summer sea-ice edge between 61 and 62∘ S and a mean summer sea-ice extent of 14–15×106 km2, which is ∼20 %–30 % larger than previous estimates. These estimates point to a higher seasonality of southern hemispheric sea-ice during the LGM than today. We also analyze the main processes defining the summer sea-ice edge within each of the models. We find that summer sea-ice cover is mainly defined by thermodynamic effects in some models, while the sea-ice edge is defined by the position of Southern Ocean upwelling in others. For models included in both PMIP3 and PMIP4, this thermodynamic or dynamic control on sea-ice is consistent across both experiments. Finally, we find that the imp

Numerical simulations allow us to gain a comprehensive understanding of the underlying mechanisms of past, present, and future climate changes. The mid-Holocene (MH) and the last interglacial (LIG) were the two most recent warm episodes of Earth’s climate history and are the focus of paleoclimate research. Here, we present results of MH and LIG simulations with two versions of the state-of-the-art Earth system model AWI-ESM. Most of the climate changes in MH and LIG compared to the preindustrial era are agreed upon by the two model versions, including 1) enhanced seasonality in surface temperature that is driven by the redistribution of seasonal insolation; 2) a northward shift of the intertropical convergence zone (ITCZ) and tropical rain belt; 3) a reduction in annual mean Arctic sea ice concentration; 4) weakening and northward displacement of the Northern Hemisphere Hadley circulation, which is related to the decrease and poleward shift of the temperature gradient from the subtropical to the equator in the Northern Hemisphere; 5) a westward shift of the Indo-Pacific Walker circulation due to anomalous warming over the Eurasia and North Africa during boreal summer; and 6) an expansion and intensification of Northern Hemisphere summer monsoon rainfall, with the latter being dominated by the dynamic component of moisture budget (i.e., the strengthening of wind circulation). However, the simulated responses of the Atlantic meridional overturning circulation (AMOC) in the two models yield different results for both the LIG and the MH. AMOC anomalies between the warm interglacial and preindustrial periods are associated with changes in North Atlantic westerly winds and stratification of the water column at the North Atlantic due to changes in ocean temperature, salinity, and density.