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There is major concern for the fate of Amazonia over the coming century in the face of anthropogenic climate change. A key area of uncertainty is the scale of rainforest die-back to be expected under a future, drier climate. In this study, we use the middle Holocene (ca. 6,000 years before present) as an approximate analogue for a drier future, given that palaeoclimate data show much of Amazonia was significantly drier than present at this time. Here, we use an ensemble of climate and vegetation models to explore the sensitivity of Amazonian biomes to mid-Holocene climate change. For this we employ three dynamic vegetation models (JULES, IBIS, and SDGVM) forced by the bias-corrected mid-Holocene climate simulations from seven models that participated in the Paleoclimate Modelling Intercomparison Project 3 (PMIP3). These model outputs are compared with a multi-proxy palaeoecological dataset to gain a better understanding of where in Amazonia we have most confidence in the mid-Holocene vegetation simulations. A robust feature of all simulations and palaeodata is that the central Amazonian rainforest biome is unaffected by mid-Holocene drought. Greater divergence in mid-Holocene simulations exists in ecotonal eastern and southern Amazonia. Vegetation models driven with climate models that simulate a drier mid Holocene (100-150 mm per year decrease) better capture the observed (palaeodata) tropical forest die-back in these areas. Based on the relationship between simulated rainfall decrease and vegetation change, we find indications that in southern Amazonia the rate of tropical forest die-back was ~125,000 km2 per 100 mm rainfall decrease in the mid Holocene. This provides a baseline sensitivity of tropical forests to drought for this region (without human-driven changes to greenhouse gases, fire, and deforestation). We highlight the need for more palaeoecological and palaeoclimate data across lowland Amazonia to constrain model responses.

The Caspian Sea (CS) delivers considerable ecosystem services to millions of people. It experienced water level variations of 3 m during the 20th century alone. Robust scenarios of future CS level are vital to inform environmental risk management and water-use planning. In this study we investigated the water budget variation in the CS drainage basin and its potential impact on CS level during the 21st century using projected climate from selected climate change scenarios of shared socioeconomic pathways (SSPs) and representative concentration pathways (RCPs), and explored the impact of human extractions. We show that the size of the CS prescribed in climate models determines the modelled water budgets for both historical and future projections. Most future projections show drying over the 21st century. The moisture deficits are more pronounced for extreme radiative forcing scenarios (RCP8.5/SSP585) and for models where a larger CS is prescribed. By 2100, up to 8 (10) m decrease in CS level is found using RCP4.5 (RCP8.5) models, and up to 20 (30) m for SSP245 (SSP585) scenario models. Water extraction rates are as important as climate in controlling future CS level, with potentially up to 7 m further decline, leading to desiccation of the shallow northern CS. This will have wide-ranging implications for the livelihoods of the surrounding communities; increasing vulnerability to freshwater scarcity, transforming ecosystems, as well as impacting the climate system. Caution should be exercised when using individual models to inform policy as projected CS level is so variable between models. We identify that many climate models either ignore, or do not properly prescribe, CS area. No future climate projections include any changes in CS surface area, even when the catchment is projected to be considerably drier. Coupling between atmosphere and lakes within climate models would be a significant advance to capture crucial two-way feedbacks.

The latitude of the tropical rainbelt oscillates seasonally but has also varied on millennial time-scales in response to changes in the seasonal distribution of insolation due to Earth’s orbital configuration, as well as climate change initiated at high latitudes. Interpretations of palaeoclimate proxy archives often suggest hemispherically coherent variations, some proposing meridional shifts in global rainbelt position and the ‘global monsoon’, while others propose interhemispherically symmetric expansion and contraction. Here, we use a unique set of climate model simulations of the last glacial cycle (120 kyr), that compares well against a compilation of precipitation proxy data, to demonstrate that while asymmetric extratropical forcings (icesheets, freshwater hosing) generally produce meridional shifts in the zonal mean rainbelt, orbital variations produce expansion/contractions in terms of the global zonal mean. This is primarily a dynamic response of the rainbelt over the oceans to regional interhemispheric temperature gradients, which is opposite to the largely local thermodynamic terrestrial response to insolation. The mode of rainbelt variation is regionally variable, depending on surface type (land or ocean) and surrounding continental configuration. This makes interpretation of precipitation-proxy records as large-scale rainbelt movement challenging, requiring regional or global data syntheses.

Warmer than present Antarctic and Southern Ocean temperatures during the last interglacial, approximately 128,000 years ago, have been attributed to changes in north-south ocean heat transport, causing opposing hemispheric temperature anomalies. We investigate the magnitude of Antarctic warming and Antarctic ice core isotopic enrichment in response to Northern Hemisphere meltwater input during the early last interglacial. A 1,600 year HadCM3 simulation driven by 0.25 Sv of meltwater input reproduces 50-60 % of the peak Southern Ocean summer sea surface temperature anomaly, sea ice retreat and ice core isotope enrichment. We also find a robust increase in the proportion of cold season precipitation during the last interglacial, leading to lower isotopic values at the Antarctic ice core sites. These results suggest that a HadCM3 simulation including 0.25 Sv for 3,000-4,000 years would reconcile the last interglacial observations, providing a potential solution for the last interglacial 'missing heat' problem.

Human induced land-use change (LUC) alters the biogeophysical characteristics of the land surface influencing the surface energy balance. The level of atmospheric CO2 is expected to increase in the coming century and beyond, modifying temperature and precipitation patterns and altering the distribution and physiology of natural vegetation. It is important to constrain how CO2-induced climate and vegetation change may influence the regional extent to which LUC alters climate. This sensitivity study uses the HadCM3 coupled climate model under a range of equilibrium forcings to show that the impact of LUC declines under increasing atmospheric CO2, specifically in temperate and boreal regions. A surface energy balance analysis is used to diagnose how these changes occur. In Northern Hemisphere winter this pattern is attributed in part to the decline in winter snow cover and in the summer due to a reduction in latent cooling with higher levels of CO2. The CO2-induced change in natural vegetation distribution is also shown to play a significant role. Simulations run at elevated CO2 yet present day vegetation show a significantly increased sensitivity to LUC, driven in part by an increase in latent cooling. This study shows that modelling the impact of LUC needs to accurately simulate CO2 driven changes in precipitation and snowfall, and incorporate accurate, dynamic vegetation distribution.

Centennial-scale records of sea-surface temperature and opal composition spanning the Last Glacial Maximum and Termination 1 (circa 25-6 ka) are presented here from Guaymas Basin in the Gulf of California. Through the application of two organic geochemistry proxies, the U-37(K') index and the TEX86H index, we present evidence for rapid, stepped changes in temperatures during deglaciation. These occur in both temperature proxies at 13 ka (similar to 3 degrees C increase in 270 years), 10.0 ka (similar to 2 degrees C decrease over similar to 250 years) and at 8.2 ka (3 degrees C increase in

Several continuous observational datasets of Artic sea-ice concentration are currently available that cover the period since the advent of routine satellite observations. We report on a comparison of three sea-ice concentration datasets. These are the National Ice Center charts, and two passive microwave radiometer datasets derived using different approaches: the NASA team and Bootstrap algorithms. Empirical orthogonal function (EOF) analyses were employed to compare modes of variability and their consistency between the datasets. The analysis was motivated by the need for a reliable, realistic sea ice climatology for use in climate model simulations, for which both the variability and absolute values of extent and concentration are important. We found that, while there are significant discrepancies in absolute concentrations, the major modes of variability derived from all records were essentially the same.

The global distribution of language diversity mirrors that of several variables related to ecosystem productivity. It has been argued that this is driven by the size of social networks, which tend to be larger in harsher climates to ensure food security, leading to reduced language divergence. Is this pattern purely synchronic, or is there also a quantifiable relationship between environmental conditions and language diversification over time? We used a spatio-temporal phylogeny of the Bantu language family to estimate local diversification rates at the times and locations of language divergence. We compared these data against spatially-explicit reconstructions of several palaeoclimate and palaeovegetation variables (mean annual temperature and the temperature of the coldest and warmest quarter, annual precipitation and the precipitation of the wettest and driest quarter, growing degree days, the length of the growing season, and net primary production), to investigate a potential link between local environmental factors and diversification rates in the Bantu languages. A regression analysis does not suggest a statistically significant relationship between climatic or ecological variables and linguistic diversification over time. We find a strong positive correlation between pairwise linguistic and geographic distances in the Bantu languages, arguing for a dominant role of isolation as a result of the rapid Bantu expansion that might have overwhelmed any potential influence of local environmental factors.