Description: A recent temperature reconstruction of global annual temperature shows Early Holocene warmth followed by a cooling trend through the Middle to Late Holocene [Marcott SA, et al., 2013, Science 339(6124):1198–1201]. This global cooling is puzzling because it is opposite from the expected and simulated global warming trend due to the retreating ice sheets and rising atmospheric greenhouse gases. Our critical reexamination of this contradiction between the reconstructed cooling and the simulated warming points to potentially significant biases in both the seasonality of the proxy reconstruction and the climate sensitivity of current climate models.

Description: The Last Glacial Maximum (LGM, ∼ 21 000 years ago) has been a major focus for evaluating how well state-of-the-art climate models simulate climate changes as large as those expected in the future using paleoclimate reconstructions. A new generation of climate models has been used to generate LGM simulations as part of the Paleoclimate Modelling Intercomparison Project (PMIP) contribution to the Coupled Model Intercomparison Project (CMIP). Here, we provide a preliminary analysis and evaluation of the results of these LGM experiments (PMIP4, most of which are PMIP4-CMIP6) and compare them with the previous generation of simulations (PMIP3, most of which are PMIP3-CMIP5). We show that the global averages of the PMIP4 simulations span a larger range in terms of mean annual surface air temperature and mean annual precipitation compared to the PMIP3-CMIP5 simulations, with some PMIP4 simulations reaching a globally colder and drier state. However, the multi-model global cooling average is similar for the PMIP4 and PMIP3 ensembles, while the multi-model PMIP4 mean annual precipitation average is drier than the PMIP3 one. There are important differences in both atmospheric and oceanic circulations between the two sets of experiments, with the northern and southern jet streams being more poleward and the changes in the Atlantic Meridional Overturning Circulation being less pronounced in the PMIP4-CMIP6 simulations than in the PMIP3-CMIP5 simulations. Changes in simulated precipitation patterns are influenced by both temperature and circulation changes. Differences in simulated climate between individual models remain large. Therefore, although there are differences in the average behaviour across the two ensembles, the new simulation results are not fundamentally different from the PMIP3-CMIP5 results. Evaluation of large-scale climate features, such as land–sea contrast and polar amplification, confirms that the models capture these well and within the uncertainty of the paleoclimate reconstructions. Nevertheless, regional climate changes are less well simulated: the models underestimate extratropical cooling, particularly in winter, and precipitation changes. These results point to the utility of using paleoclimate simulations to understand the mechanisms of climate change and evaluate model performance.

Description: We present results from an ensemble of eight climate models, each of which has carried out simulations of the early Eocene climate optimum (EECO, ∼ 50 million years ago). These simulations have been carried out in the framework of the Deep-Time Model Intercomparison Project (DeepMIP; http://www.deepmip.org, last access: 10 January 2021); thus, all models have been configured with the same paleogeographic and vegetation boundary conditions. The results indicate that these non-CO2 boundary conditions contribute between 3 and 5 ∘C to Eocene warmth. Compared with results from previous studies, the DeepMIP simulations generally show a reduced spread of the global mean surface temperature response across the ensemble for a given atmospheric CO2 concentration as well as an increased climate sensitivity on average. An energy balance analysis of the model ensemble indicates that global mean warming in the Eocene compared with the preindustrial period mostly arises from decreases in emissivity due to the elevated CO2 concentration (and associated water vapour and long-wave cloud feedbacks), whereas the reduction in the Eocene in terms of the meridional temperature gradient is primarily due to emissivity and albedo changes owing to the non-CO2 boundary conditions (i.e. the removal of the Antarctic ice sheet and changes in vegetation). Three of the models (the Community Earth System Model, CESM; the Geophysical Fluid Dynamics Laboratory, GFDL, model; and the Norwegian Earth System Model, NorESM) show results that are consistent with the proxies in terms of the global mean temperature, meridional SST gradient, and CO2, without prescribing changes to model parameters. In addition, many of the models agree well with the first-order spatial patterns in the SST proxies. However, at a more regional scale, the models lack skill. In particular, the modelled anomalies are substantially lower than those indicated by the proxies in the southwest Pacific; here, modelled continental surface air temperature anomalies are more consistent with surface air temperature proxies, implying a possible inconsistency between marine and terrestrial temperatures in either the proxies or models in this region. Our aim is that the documentation of the large-scale features and model–data comparison presented herein will pave the way to further studies that explore aspects of the model simulations in more detail, for example the ocean circulation, hydrological cycle, and modes of variability, and encourage sensitivity studies to aspects such as paleogeography, orbital configuration, and aerosols.

Description: 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 impact of changes in large-scale ocean circulation on summer sea-ice within a single model is smaller than the natural range of summer sea-ice cover across the models considered here. This indicates that care must be taken when using a single model to reconstruct past climate regimes.

Description: Neoproterozoic igneous rocks along the northern Yangtze Block are closely related to the evolution of the Rodinia supercontinent. This paper presents zircon U–Pb dating, whole-rock geochemistry and Sr-Nd isotopes of the gabbro–granite association from the Micangshan area, northern Yangtze Block. Zircon LA-ICP MS U–Pb dating indicates that the tonalite and monzogranite from the Pinghe display identical ages of 869 ± 4 Ma (MSWD = 1.3, 2σ) and 859 ± 8 Ma (MSWD = 1.9, 2σ), respectively. According to the regional geology, the gabbro may be younger. The monzogranite and tonalite display almost identical geochemical features, both of them have high Na 2 O/K 2 O ratios, with insignificant negative Eu anomalies, relatively juvenile Sr-Nd isotopic compositions. The monzogranite has initial ( 87 Sr/ 86 Sr)i ratios of 0.703403 to 0.705218, and positive ɛNd( t ) values of +1.23 to +2.98. The tonalite have ( 87 Sr/ 86 Sr)i ratios of 0.700387 to 0.706222, positive ɛNd( t ) values of +1.98 to +7.79, indicating that they were derived from juvenile source. The 860 Ma monzogranite–tonalite association suggests crustal growth event in an active continental margin. The gabbro has low (La/Yb) N ratios (1.80 to 7.61) and total rare earth element contents (∑REE = 44.95 to 83.92 ppm), they have initial ( 87 Sr/ 86 Sr)i ratios of 0.701913 to 0.704815, positive ɛNd( t ) values of +0.65 to +5.73, indicating an island-arc affinity. In combination with the other Neoproterozoic igneous rocks along the western and northern margin of the Yangtze Block, we propose that the gabbro and granitoid association from the Micangshan area represent two stage crustal growth events in the active continental margin setting, and these results imply that the Neoproterozoic crustal growth events in the Yangtze Block may be controlled by subduction.

Description: Long non-coding RNAs (lncRNAs) participate in the development of breast cancer. Genetic variants in lncRNAs may be involved in their abnormal expressions and associated with cancer risk. In the present study, we performed RNA sequencing on five paired breast cancer tumor and adjacent non-cancerous tissues to obtain differentially expressed lncRNAs. We systematically selected potential regulatory variants of these lncRNAs and investigated the associations between these variants and breast cancer susceptibility in 1,486 breast cancer cases and 1,519 cancer-free controls in a Chinese population. Eleven lncRNAs were significantly differentially expressed between breast cancer tumor and normal tissues (false discovery rate (FDR) 〈 0.05 and fold-change 〉 2), including two known lncRNAs HOTAIR and UCA1 . We subsequently genotyped 20 variants located on these lncRNAs and identified two variants (rs11471161 in AC104135.3 and rs3751232 in RP11-1060J15.4 ) associated with breast cancer risk. Logistic regression analysis indicated that the variant allele of rs11471161 was significantly associated with a decreased breast cancer risk (additive model: OR = 0.84, 95%CI = 0.74–0.94, P = 0.004), while the variant allele of rs3751232 showed an increased risk of breast cancer (additive model: OR = 1.20, 95%CI = 1.02–1.40, P = 0.027). Further co-expression analysis indicated that AC104135.3 associated with ERBB2 , which promotes the development and progression of breast cancer through overexpression. Together, these results suggest that genetic variants rs11471161 and rs3751232 in AC104135.3 and RP11 - 1060J15.4 , respectively, may influence the susceptibility to breast cancer in the Chinese population. Further functional evaluations and larger studies are warranted to validate these findings. This article is protected by copyright. All rights reserved