42 research outputs found
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Ocean dominated expansion and contraction of the late Quaternary tropical rainbelt
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
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EOF analysis of three records of sea-ice concentration spanning the last 30 years
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
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SHIMMER (1.0): a novel mathematical model for microbial and biogeochemical dynamics in glacier forefield ecosystems
SHIMMER (Soil biogeocHemIcal Model for Microbial Ecosystem Response) is a new numerical modelling framework designed to simulate microbial dynamics and biogeochemical cycling during initial ecosystem development in glacier forefield soils. However, it is also transferable to other extreme ecosystem types (such as desert soils or the surface of glaciers). The rationale for model development arises from decades of empirical observations in glacier forefields, and enables a quantitative and process focussed approach. Here, we provide a detailed description of SHIMMER, test its performance in two case study forefields: the Damma Glacier (Switzerland) and the Athabasca Glacier (Canada) and analyse sensitivity to identify the most sensitive and unconstrained model parameters. Results show that the accumulation of microbial biomass is highly dependent on variation in microbial growth and death rate constants, Q10 values, the active fraction of microbial biomass and the reactivity of organic matter. The model correctly predicts the rapid accumulation of microbial biomass observed during the initial stages of succession in the forefields of both the case study systems. Primary production is responsible for the initial build-up of labile substrate that subsequently supports heterotrophic growth. However, allochthonous contributions of organic matter, and nitrogen fixation, are important in sustaining this productivity. The development and application of SHIMMER also highlights aspects of these systems that require further empirical research: quantifying nutrient budgets and biogeochemical rates, exploring seasonality and microbial growth and cell death. This will lead to increased understanding of how glacier forefields contribute to global biogeochemical cycling and climate under future ice retreat
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Response of Amazonian forests to mid-Holocene drought: a model-data comparison
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
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The fate of the Caspian Sea under projected climate change and water extraction during the 21st century
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
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Environmental conditions do not predict diversification rates in the Bantu languages.
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
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Assessing the benefits of crop albedo bio-geoengineering
It has been proposed that growing crop varieties with higher canopy albedo would lower summer-time temperatures over North America and Eurasia and provide a partial mitigation of global warming ('bio-geoengineering') (Ridgwell et al 2009 Curr. Biol. 19 1–5). Here, we use a coupled ocean–atmosphere–vegetation model (HadCM3) with prescribed agricultural regions, to investigate to what extent the regional effectiveness of crop albedo bio-geoengineering might be influenced by a progressively warming climate as well as assessing the impacts on regional hydrological cycling and primary productivity. Consistent with previous analysis, we find that the averted warming due to increasing crop canopy albedo by 0.04 is regionally and seasonally specific, with the largest cooling of ~1 °C for Europe in summer whereas in the low latitude monsoonal SE Asian regions of high density cropland, the greatest cooling is experienced in winter. In this study we identify potentially important positive impacts of increasing crop canopy albedo on soil moisture and primary productivity in European cropland regions, due to seasonal increases in precipitation. We also find that the background climate state has an important influence on the predicted regional effectiveness of bio-geoengineering on societally-relevant timescales (ca 100 years). The degree of natural climate variability and its dependence on greenhouse forcing that are evident in our simulations highlights the difficulties faced in the detection and verification of climate mitigation in geoengineering schemes. However, despite the small global impact, regionally focused schemes such as crop albedo bio-geoengineering have detection advantages
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The Role of CO<sub>2</sub> and Dynamic Vegetation on the Impact of Temperate Land-Use Change in the HadCM3 Coupled Climate Model
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
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Twenty-first-century climate impacts from a declining Arctic sea ice cover
A steady decline in Arctic sea ice has been observed over recent decades. General circulation models predict further decreases under increasing greenhouse gas scenarios. Sea ice plays an important role in the climate system in that it influences ocean-to-atmosphere fluxes, surface albedo, and ocean buoyancy. The aim of this study is to isolate the climate impacts of a declining Arctic sea ice cover during the current century. The Hadley Centre Atmospheric Model (HadAM3) is forced with observed sea ice from 1980 to 2000 (obtained from satellite passive microwave radiometer data derived with the Bootstrap algorithm) and predicted sea ice reductions until 2100 under one moderate scenario and one severe scenario of ice decline, with a climatological SST field and increasing SSTs. Significant warming of the Arctic occurs during the twenty-first century (mean increase of between 1.6° and 3.9°C), with positive anomalies of up to 22°C locally. The majority of this is over ocean and limited to high latitudes, in contrast to recent observations of Northern Hemisphere warming. When a climatological SST field is used, statistically significant impacts on climate are only seen in winter, despite prescribing sea ice reductions in all months. When correspondingly increasing SSTs are incorporated, changes in climate are seen in both winter and summer, although the impacts in summer are much smaller. Alterations in atmospheric circulation and precipitation patterns are more widespread than temperature, extending down to midlatitude storm tracks. Results suggest that areas of Arctic land ice may even undergo net accumulation due to increased precipitation that results from loss of sea ice. Intensification of storm tracks implies that parts of Europe may experience higher precipitation rates
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Global biome patterns of the Middle and Late Pleistocene
Our primary aim was to assess the hypothesis that distinctive features of the patterns of vegetation change during successive Quaternary glacial–interglacial cycles reflect climatic differences arising from forcing differences. We addressed this hypothesis using 207 half-degree resolution global biome pattern simulations, for time slices between 800 and 2 ka, made using the LPJ-GUESS dynamic global vegetation model. Simulations were driven using ice-core atmospheric CO2 concentrations, Earth's obliquity, and outputs from a pre-industrial and 206 palaeoclimate experiments; four additional simulations were driven using projected future CO2 concentrations. Climate experiments were run using HadCM3. Using a rule-based approach, above-ground biomass and leaf area index of LPJ-GUESS plant functional types were used to infer each grid cell's biome. The hypothesis is supported by the palaeobiome simulations. To enable comparisons with the climatic forcing, multivariate analyses were performed of global vegetation pattern dissimilarities between simulations. Results showed generally similar responses to glacial–interglacial climatic variations during each cycle, although no two interglacials or glacials had identical biome patterns. Atmospheric CO2 concentration was the strongest driver of the dissimilarity patterns. Dissimilarities relative to the time slice with the lowest atmospheric CO2 concentration show the log-linear relationship to atmospheric CO2 concentration expected of an index of ecocarbon sensitivity. For each simulation, extent and total above-ground biomass of each biome were calculated globally and for three longitudinal segments corresponding to the major continental regions. Mean and minimum past extents of forest biomes, notably Temperate Summergreen Forest, in the three major continental regions strongly parallel relative tree diversities, hence supporting the hypothesis that past biome extents played an important role in determining present diversity. Albeit that they reflect the climatic consequences only of the faster Earth system components, simulated potential future biome patterns are unlike any during the past 800 ky, and likely will continue to change markedly for millennia if projected CO2 concentrations are realised