The evolution of past global ice sheets is highly uncertain. One example is the missing ice problem during the Last Glacial Maximum (LGM, 26 000-19 000 years before present) - an apparent 8-28 m ...discrepancy between far-field sea level indicators and modelled sea level from ice sheet reconstructions. In the absence of ice sheet reconstructions, researchers often use marine δ
O proxy records to infer ice volume prior to the LGM. We present a global ice sheet reconstruction for the past 80 000 years, called PaleoMIST 1.0, constructed independently of far-field sea level and δ
O proxy records. Our reconstruction is compatible with LGM far-field sea-level records without requiring extra ice volume, thus solving the missing ice problem. However, for Marine Isotope Stage 3 (57 000-29 000 years before present) - a pre-LGM period - our reconstruction does not match proxy-based sea level reconstructions, indicating the relationship between marine δ
O and sea level may be more complex than assumed.
Arctic temperature is one of the most uncertain aspects of mid‐Holocene (MH) climate change modeling, usually attributed to the different responses of different models to external forcing. However, ...in this study, we find that significant discrepancies (i.e., the noise is close to the signal in term of climate change) in the MH Arctic temperature changes can occur within the same model and for identical external forcing due to initial ocean condition perturbations. It is shown that initial ocean perturbations can affect the surface energy budget change through the uncertain cloud effect on shortwave radiation in boreal summer. The resulted uncertain change in summer surface heat flux alters the subsequent autumn and winter sea ice and contributes to significant differences in Arctic temperature via sea ice‐albedo feedback. This study suggests that internal uncertainty of an individual model is a non‐negligible source of overall uncertainty in simulating the MH Arctic temperature change.
Plain Language Summary
Proxies suggest that during the mid‐Holocene (MH) (∼6,000 years ago), the climate was warmer than in the preindustrial period. However, climate models generally suggested a colder MH climate. This discrepancy between data and model results could be attributed to either the biased interpretation of proxy records or the models' unrealistic response to external forcings. From the modeling perspective, the Arctic temperature change is one of the most uncertain aspects of MH simulation, which can hinder our understanding of MH climate change and the comparison with proxy data. Generally, the uncertainty in modeling Arctic temperatures is attributed to variations in the response to external forcings among different models. However, we have uncovered that this uncertainty also exists within a single model. The responses of Arctic temperatures differ significantly in identical experiments when different initial ocean states are used. Specifically, the influence of clouds on the climate is highly sensitive to the initial ocean conditions, leading to various effects on solar radiation, which in turn affects changes in Arctic sea ice to varying degrees, ultimately resulting in distinct Arctic temperature changes during the MH. This study underscores the importance of addressing internal uncertainties within individual climate models when simulating changes in Arctic temperatures.
Key Points
The Arctic temperature changes in the mid‐Holocene (MH) exhibit considerable discrepancy among the experiments with initial ocean perturbation
The summer cloud effect on solar insolation plays a crucial role in modifying the Arctic sea ice change and hence the temperature response
The internal uncertainty within a single model is non‐negligible in simulating the MH Arctic temperature change
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Abstract Drought frequency and severity are projected to increase in the future, but the changes are expected to be unevenly distributed across the globe. Based on multi-model simulations under three ...different future emissions and shared socioeconomic pathways, we show that a significant drought intensification is expected in dry regions, whereby the severity depends on greenhouse gas emissions and development pathways. The drought hotspots are located in the sub-tropical regions where a moderate to extreme summer drought in today’s climate is expected to become a new normal by the end of the 21 st century under the warmest scenario. On average, under the warmest future scenario, the drought occurrence rate is projected to be 100% higher than that of the low emission scenario. Further, for the regions which are currently less affected by long-lasting droughts, such as the European continent, climate models indicate a significant increase in drought occurrence probability under the warmest future scenario.
The Atlantic multidecadal oscillation (AMO) and its possible change during the Holocene are examined in this study, using long-term simulations of the earth system model Community Earth System Models ...(COSMOS). A quasi-persistent ∼55–80-yr cycle characterizing in the North Atlantic sea surface temperature is highly associated with the multidecadal variability of the Atlantic meridional overturning circulation (AMOC) during the Holocene. This mode can be found throughout the Holocene, indicating that the AMO is dominated by internal climate variability. Stronger-than-normal AMOC results in warmer-than-normal surface temperature spreading over almost the whole North Hemisphere, in particular the North Atlantic Ocean. During the warm phase of the AMO, more precipitation is detected in the North Atlantic low and high latitudes. It also generates a dipolar seesaw pattern in the sea ice anomaly. The results reveal that the influence of the AMO can be amplified by a more vigorous AMOC variability during the early Holocene in the presence of a remnant of the Laurentide Ice Sheet and when freshwater entered the North Atlantic Ocean. This conclusion could have potential application for the past AMO reconstruction and the future AMO estimation.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The earliest part of the Holocene, from 11.5k to 7k (k = 1000 years before present), is a critical transition period between the relatively cold last deglaciation and the warm middle Holocene. It is ...marked by more pronounced seasonality and reduced greenhouse gases (GHGs) than the present state, as well as by the presence of the Laurentide Ice Sheet (LIS) and glacial meltwater perturbation. This paper performs experiments under pre-industrial and different early-Holocene regimes with AWI-ESM (Alfred Wegener Institute–Earth System Model), a state-of-the-art climate model with unstructured mesh and varying resolutions, to examine the sensitivity of the simulated Atlantic meridional overturning circulation (AMOC) to early-Holocene insolation, GHGs, topography (including properties of the ice sheet), and glacial meltwater perturbation. In the experiments with early-Holocene Earth orbital parameters and GHGs applied, the AWI-ESM simulation shows a JJA (June–July–August) warming and DJF (December–January–February) cooling over the mid and high latitudes compared with pre-industrial conditions, with amplification over the continents. The presence of the LIS leads to an additional regional cooling over the North America. We also simulate the meltwater event around 8.2k. Big discrepancies are found in the oceanic responses to different locations and magnitudes of freshwater discharge. Our experiments, which compare the effects of freshwater release evenly across the Labrador Sea to a more precise injection along the western boundary of the North Atlantic (the coastal region of LIS), show significant differences in the ocean circulation response, as the former produces a major decline of the AMOC and the latter yields no obvious effect on the strength of the thermohaline circulation. Furthermore, proglacial drainage of Lakes Agassiz and Ojibway leads to a fast spin-down of the AMOC, followed, however, by a gradual recovery. Most hosing experiments lead to a warming over the Nordic Sea and Barents Sea of varying magnitudes, because of an enhanced inflow from lower latitudes and a northward displacement of the North Atlantic deep convection. These processes exist in both of our high- and low-resolution experiments, but with some local discrepancies such as (1) the hosing-induced subpolar warming is much less pronounced in the high-resolution simulations; (2) LIS coastal melting in the high-resolution model leads to a slight decrease in the AMOC; and (3) the convection formation site in the low- and high-resolution experiments differs, in the former mainly over northeastern North Atlantic Ocean, but in the latter over a very shallow subpolar region along the northern edge of the North Atlantic Ocean. In conclusion, we find that our simulations capture spatially heterogeneous responses of the early-Holocene climate.
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NUK, OILJ, SAZU, UKNU, UL, UM, UPUK
Coinciding with global warming, Arctic sea ice has rapidly decreased during the last four decades and climate scenarios suggest that sea ice may completely disappear during summer within the next ...about 50-100 years. Here we produce Arctic sea ice biomarker proxy records for the penultimate glacial (Marine Isotope Stage 6) and the subsequent last interglacial (Marine Isotope Stage 5e). The latter is a time interval when the high latitudes were significantly warmer than today. We document that even under such warmer climate conditions, sea ice existed in the central Arctic Ocean during summer, whereas sea ice was significantly reduced along the Barents Sea continental margin influenced by Atlantic Water inflow. Our proxy reconstruction of the last interglacial sea ice cover is supported by climate simulations, although some proxy data/model inconsistencies still exist. During late Marine Isotope Stage 6, polynya-type conditions occurred off the major ice sheets along the northern Barents and East Siberian continental margins, contradicting a giant Marine Isotope Stage 6 ice shelf that covered the entire Arctic Ocean.Coinciding with global warming, Arctic sea ice has rapidly decreased during the last four decades. Here, using biomarker records, the authors show that permanent sea ice was still present in the central Arctic Ocean during the last interglacial, when high latitudes were warmer than present.
We present a new approach to modeling the future development of extreme temperatures globally and on the time-scale of several centuries by using non-stationary generalized extreme value ...distributions in combination with logistic functions. The statistical models we propose are applied to annual maxima of daily temperature data from fully coupled climate models spanning the years 1850 through 2300. They enable us to investigate how extremes will change depending on the geographic location not only in terms of the magnitude, but also in terms of the timing of the changes. We find that in general, changes in extremes are stronger and more rapid over land masses than over oceans. In addition, our statistical models allow for changes in the different parameters of the fitted generalized extreme value distributions (a location, a scale and a shape parameter) to take place independently and at varying time periods. Different statistical models are presented and the Bayesian Information Criterion is used for model selection. It turns out that in most regions, changes in mean and variance take place simultaneously while the shape parameter of the distribution is predicted to stay constant. In the Arctic region, however, a different picture emerges: There, climate variability is predicted to increase rather quickly in the second half of the twenty-first century, probably due to the melting of ice, whereas changes in the mean values take longer and come into effect later.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Recent evidence shows that wind‐driven ocean currents, like the western boundary currents, are strongly affected by global warming. However, due to insufficient observations both on temporal and ...spatial scales, the impact of climate change on large‐scale ocean gyres is still not clear. Here, based on satellite observations of sea surface height and sea surface temperature, we find a consistent poleward shift of the major ocean gyres. Due to strong natural variability, most of the observed ocean gyre shifts are not statistically significant, implying that natural variations may contribute to the observed trends. However, climate model simulations forced with increasing greenhouse gases suggest that the observed shift is most likely to be a response of global warming. The displacement of ocean gyres, which is coupled with the poleward shift of extratropical atmospheric circulation, has broad impacts on ocean heat transport, regional sea level rise, and coastal ocean circulation.
Plain Language Summary
Ocean circulation plays a vital role in regulating the weather and climate and supporting marine life. Therefore, it is important to understand whether and how it responds to global warming. However, the available observations are currently sparse and short in duration, making it difficult to track the dynamic changes of large‐scale ocean circulation. Here, we show for the first time, independent satellite observational evidence demonstrating that the large‐scale ocean gyres are moving poleward during the past four decades. Further analysis based on climate models and various other data sets reveal that the poleward shifting of the ocean gyre circulation is most likely to be a consequence of global warming, which so far has not been well recognized by the public and the scientific community.
Key Points
Satellite observations show a consistent poleward shift of the major ocean gyres during the past four decades
Due to strong natural variability, most of the observed ocean gyre shifts are not statistically significant
Climate model simulations suggest that the observed shift is most likely to be a response to global warming
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
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