Description: Numerical simulations employing prognostic stable water isotopes can not only facilitate our understanding of hydrological processes and climate change but also allow for a direct comparison between isotope signals obtained from models and various archives. In the current work, we describe the performance and explore the potential of a new version of the Earth system model AWI-ESM (Alfred Wegener Institute Earth System Model), labeled AWI-ESM-2.1-wiso, in which we incorporated three isotope tracers into all relevant components of the water cycle. We present here the results of pre-industrial (PI) and mid-Holocene (MH) simulations. The model reproduces the observed PI isotope compositions in both precipitation and seawater well and captures their major differences from the MH conditions. The simulated relationship between the isotope composition in precipitation (δ18Op) and surface air temperature is very similar between the PI and MH conditions, and it is largely consistent with modern observations despite some regional model biases. The ratio of the MH–PI difference in δ18Op to the MH–PI difference in surface air temperature is comparable to proxy records over Greenland and Antarctica only when summertime air temperature is considered. An amount effect is evident over the North African monsoon domain, where a negative correlation between δ18Op and the amount of precipitation is simulated. As an example of model applications, we studied the onset and withdrawal date of the MH West African summer monsoon (WASM) using daily variables. We find that defining the WASM onset based on precipitation alone may yield erroneous results due to the substantial daily variations in precipitation, which may obscure the distinction between pre-monsoon and monsoon seasons. Combining precipitation and isotope indicators, we suggest in this work a novel method for identifying the commencement of the WASM. Moreover, we do not find an obvious difference between the MH and PI periods in terms of the mean onset of the WASM. However, an advancement in the WASM withdrawal is found in the MH compared to the PI period due to an earlier decline in insolation over the northern location of Intertropical Convergence Zone (ITCZ).

Description: 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 forcings.

Description: The Pliocene Model Intercomparison Project is the first coordinated climate model comparison for a warmer palaeoclimate with atmospheric CO2 significantly higher than pre-industrial concentrations. The simulations of the mid-Pliocene warm period show global warming of between 1.8 and 3.6 °C above pre-industrial surface air temperatures, with significant polar amplification. Here we perform energy balance calculations on all eight of the coupled ocean–atmosphere simulations within PlioMIP Experiment 2 to evaluate the causes of the increased temperatures and differences between the models. In the tropics simulated warming is dominated by greenhouse gas increases, with cloud albedo feedbacks enhancing the warming in most of the models, but by widely varying amounts. The responses to mid-Pliocene climate forcing in the Northern Hemisphere mid-latitudes are substantially different between the climate models, with the only consistent response being a warming due to increased greenhouse gases. In the high latitudes all the energy balance components become important, but the dominant warming influence comes from the clear sky albedo. This demonstrates the importance of specified ice sheet and high latitude vegetation boundary conditions and simulated sea ice and snow albedo feedbacks. The largest components in the overall uncertainty are associated with cloud albedo feedbacks in the tropics and polar clear sky albedo, particularly in sea ice regions. These simulations show that high latitude albedo feedbacks provide the most significant enhancements to Pliocene greenhouse warming.

Description: Based on simulations with 15 climate models in the Pliocene Model Intercomparison Project (PlioMIP), the regional climate of East Asia (focusing on China) during the mid-Pliocene is investigated in this study. Compared to the pre-industrial, the multi-model ensemble mean (MMM) of all models shows the East Asian summer winds (EASWs) largely strengthen in monsoon China, and the East Asian winter winds (EAWWs) strengthen in south monsoon China but slightly weaken in north monsoon China in the mid-Pliocene. The MMM of all models also illustrates a warmer and wetter mid-Pliocene climate in China. The simulated weakened mid-Pliocene EAWWs in north monsoon China and intensified EASWs in monsoon China agree well with geological reconstructions. However, there is a large model–model discrepancy in simulating mid-Pliocene EAWW, which should be further addressed in the future work of PlioMIP.

Description: The last interglaciation (~130 to 116 ka) is a time period with a strong astronomically induced seasonal forcing of insolation compared to the present. Proxy records indicate a significantly different climate to that of the modern, in particular Arctic summer warming and higher eustatic sea level. Because the forcings are relatively well constrained, it provides an opportunity to test numerical models which are used for future climate prediction. In this paper we compile a set of climate model simulations of the early last interglaciation (130 to 125 ka), encompassing a range of model complexities. We compare the simulations to each other and to a recently published compilation of last interglacial temperature estimates. We show that the annual mean response of the models is rather small, with no clear signal in many regions. However, the seasonal response is more robust, and there is significant agreement amongst models as to the regions of warming vs cooling. However, the quantitative agreement of the model simulations with data is poor, with the models in general underestimating the magnitude of response seen in the proxies. Taking possible seasonal biases in the proxies into account improves the agreement, but only marginally. However, a lack of uncertainty estimates in the data does not allow us to draw firm conclusions. Instead, this paper points to several ways in which both modelling and data could be improved, to allow a more robust model–data comparison.

Description: Several proxy-based and modeling studies have investigated long-term changes in Caribbean climate during the Holocene, however, very little is known on its variability on short timescales. Here we reconstruct seasonality and interannual to multidecadal variability of sea surface hydrology of the southern Caribbean Sea by applying paired coral Sr/Ca and δ18O measurements on fossil annually banded Diploria strigosa corals from Bonaire. This allows for better understanding of seasonal to multidecadal variability of the Caribbean hydrological cycle during the mid- to late Holocene. The monthly resolved coral Δδ18O records are used as a proxy for the oxygen isotopic composition of seawater (δ18Osw) of the southern Caribbean Sea. Consistent with modern day conditions, annual δ18Osw cycles reconstructed from three modern corals reveal that freshwater budget at the study site is influenced by both net precipitation and advection of tropical freshwater brought by wind-driven surface currents. In contrast, the annual δ18Osw cycle reconstructed from a mid-Holocene coral indicates a sharp peak towards more negative values in summer, suggesting intense summer precipitation at 6 ka BP (before present). In line with this, our model simulations indicate that increased seasonality of the hydrological cycle at 6 ka BP results from enhanced precipitation in summertime. On interannual to multidecadal timescales, the systematic positive correlation observed between reconstructed sea surface temperature and salinity suggests that freshwater discharged from the Orinoco and Amazon rivers and transported into the Caribbean by wind-driven surface currents is a critical component influencing sea surface hydrology on these timescales.

Description: The equilibrium climate sensitivity (ECS) of climate models is calculated as the equilibrium global mean surface air warming resulting from a simulated doubling of the atmospheric CO2 concentration. In these simulations, long-term processes in the climate system, such as land ice changes, are not incorporated. Hence, climate sensitivity derived from paleodata has to be compensated for these processes, when comparing it to the ECS of climate models. Several recent studies found that the impact these long-term processes have on global temperature cannot be quantified directly through the global radiative forcing they induce. This renders the prevailing approach of deconvoluting paleotemperatures through a partitioning based on radiative forcings inaccurate. Here, we therefore implement an efficacy factor ε[LI] that relates the impact of land ice changes on global temperature to that of CO2 changes in our calculation of climate sensitivity from paleodata. We apply our refined approach to a proxy-inferred paleoclimate dataset, using ε[LI]=0.45+0.34−0.20 based on a multi-model assemblage of simulated relative influences of land ice changes on the Last Glacial Maximum temperature anomaly. The implemented ε[LI] is smaller than unity, meaning that per unit of radiative, forcing the impact on global temperature is less strong for land ice changes than for CO2 changes. Consequently, our obtained ECS estimate of 5.8±1.3 K, where the uncertainty reflects the implemented range in ε[LI], is ∼50 % higher than when differences in efficacy are not considered.

Description: Rapid monsoon changes since the last deglaciation remain poorly constrained due to the scarcity of geological archives. Here we present a high-resolution scanning X-ray fluorescence (XRF) analysis of a 13.5 m terrace succession on the western Chinese Loess Plateau (CLP) to infer rapid monsoon changes since the last deglaciation. Our results indicate that Rb∕Sr and Zr∕Rb are sensitive indicators of chemical weathering and wind sorting, respectively, which are further linked to the strength of the East Asian summer monsoon (EASM) and the East Asian winter monsoon (EAWM). During the last deglaciation, two cold intervals of the Heinrich event 1 and Younger Dryas were characterized by intensified winter monsoon and weakened summer monsoon. The EAWM gradually weakened at the beginning of the Holocene, while the EASM remained steady till 9.9 ka and then grew stronger. Both the EASM and EAWM intensities were relatively weak during the Middle Holocene, indicating a mid-Holocene climatic optimum. Rb∕Sr and Zr∕Rb exhibit an antiphase relationship between the summer and winter monsoon changes on a centennial timescale during 16–1 ka. Comparison of these monsoon changes with solar activity and North Atlantic cooling events reveals that both factors can lead to abrupt changes on a centennial timescale in the Early Holocene. During the Late Holocene, North Atlantic cooling became the major forcing of centennial monsoon events.

Description: 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.

Description: In this paper we introduce a Bayesian framework, which is explicit about prior assumptions, for using model ensembles and observations together to constrain future climate change. The emergent constraint approach has seen broad application in recent years, including studies constraining the equilibrium climate sensitivity (ECS) using the Last Glacial Maximum (LGM) and the mid-Pliocene Warm Period (mPWP). Most of these studies were based on ordinary least squares (OLS) fits between a variable of the climate state, such as tropical temperature, and climate sensitivity. Using our Bayesian method, and considering the LGM and mPWP separately, we obtain values of ECS of 2.7 K (0.6–5.2, 5th–95th percentiles) using the PMIP2, PMIP3, and PMIP4 datasets for the LGM and 2.3 K (0.5–4.4) with the PlioMIP1 and PlioMIP2 datasets for the mPWP. Restricting the ensembles to include only the most recent version of each model, we obtain 2.7 K (0.7–5.2) using the LGM and 2.3 K (0.4–4.5) using the mPWP. An advantage of the Bayesian framework is that it is possible to combine the two periods assuming they are independent, whereby we obtain a tighter constraint of 2.5 K (0.8–4.0) using the restricted ensemble. We have explored the sensitivity to our assumptions in the method, including considering structural uncertainty, and in the choice of models, and this leads to 95 % probability of climate sensitivity mostly below 5 K and only exceeding 6 K in a single and most uncertain case assuming a large structural uncertainty. The approach is compared with other approaches based on OLS, a Kalman filter method, and an alternative Bayesian method. An interesting implication of this work is that OLS-based emergent constraints on ECS generate tighter uncertainty estimates, in particular at the lower end, an artefact due to a flatter regression line in the case of lack of correlation. Although some fundamental challenges related to the use of emergent constraints remain, this paper provides a step towards a better foundation for their potential use in future probabilistic estimations of climate sensitivity.