Land use and climate change impacts on soil organic carbon stocks in semi-arid Spain

Purpose The sensitivity of soil organic carbon to global change drivers, according to the depth profile, is receiving increasing attention because of its importance in the global carbon cycle and its potential feedback to climate change. A better knowledge of the vertical distribution of SOC and its controlling factors—the aim of this study—will help scientists predict the consequences of global change. Materials and methods The study area was the Murcia Province (S.E. Spain) under semiarid Mediterranean conditions. The database used consists of 312 soil profiles collected in a systematic grid, each 12 km2 covering a total area of 11,004 km2. Statistical analysis to study the relationships between SOC concentration and control factors in different soil use scenarios was conducted at fixed depths of 0–20, 20–40, 40–60, and 60–100 cm. Results and discussion SOC concentration in the top 40 cm ranged between 6.1 and 31.5 g kg−1, with significant differences according to land use, soil type and lithology, while below this depth, no differences were observed (SOC concentration 2.1–6.8 g kg−1). The ANOVA showed that land use was the most important factor controlling SOC concentration in the 0–40 cm depth. Significant differences were found in the relative importance of environmental and textural factors according to land use and soil depth. In forestland, mean annual precipitation and texture were the main predictors of SOC, while in cropland and shrubland, the main predictors were mean annual temperature and lithology. Total SOC stored in the top 1 m in the region was about 79 Tg with a low mean density of 7.18 kg Cm−3. The vertical distribution of SOC was shallower in forestland and deeper in cropland. A reduction in rainfall would lead to SOC decrease in forestland and shrubland, and an increase of mean annual temperature would adversely affect SOC in croplands and shrubland. With increasing depth, the relative importance of climatic factors decreases and texture becomes more important in controlling SOC in all land uses. Conclusions Due to climate change, impacts will be much greater in surface SOC, the strategies for C sequestration should be focused on subsoil sequestration, which was hindered in forestland due to bedrock limitations to soil depth. In these conditions, sequestration in cropland through appropriate management practices is recommended.

Animal infectious disease and climate change: a selected review

It is indisputable that climate is an important factor in many livestock diseases. Nevertheless, our knowledge of the impact of climate change on livestock infectious diseases is much less certain. Therefore, the aim of the article is to conduct a systematic review of the literature on the topic utilizing available retrospective data and information. Across a corpus of 175 formal publications, limited empirical evidence was offered to underpin many of the main arguments. The literature reviewed was highly polarized and often inconsistent regarding what the future may hold. Historical explorations were rare. However, identifying past drivers to livestock disease may not fully capture the extent that new and unknown drivers will influence future change. As such, our current predictive capacity is low. We offer a number of recommendations to strengthen this capacity in the coming years. We conclude that our current approach to research on the topic is limiting and unlikely to yield sufficient, actionable evidence to inform future praxis. Therefore, we argue for the creation of a reflexive, knowledge-based system, underpinned by a collective intelligence framework to support the drawing of inferences across the literature.

Statistical-dynamical downscaling for wind energy potentials: evaluation and applications to decadal hindcasts and climate change projections

A statistical–dynamical downscaling (SDD) approach for the regionalization of wind energy output (Eout) over Europe with special focus on Germany is proposed. SDD uses an extended circulation weather type (CWT) analysis on global daily mean sea level pressure fields with the central point being located over Germany. Seventy-seven weather classes based on the associated CWT and the intensity of the geostrophic flow are identified. Representatives of these classes are dynamically downscaled with the regional climate model COSMO-CLM. By using weather class frequencies of different data sets, the simulated representatives are recombined to probability density functions (PDFs) of near-surface wind speed and finally to Eout of a sample wind turbine for present and future climate. This is performed for reanalysis, decadal hindcasts and long-term future projections. For evaluation purposes, results of SDD are compared to wind observations and to simulated Eout of purely dynamical downscaling (DD) methods. For the present climate, SDD is able to simulate realistic PDFs of 10-m wind speed for most stations in Germany. The resulting spatial Eout patterns are similar to DD-simulated Eout. In terms of decadal hindcasts, results of SDD are similar to DD-simulated Eout over Germany, Poland, Czech Republic, and Benelux, for which high correlations between annual Eout time series of SDD and DD are detected for selected hindcasts. Lower correlation is found for other European countries. It is demonstrated that SDD can be used to downscale the full ensemble of the Earth System Model of the Max Planck Institute (MPI-ESM) decadal prediction system. Long-term climate change projections in Special Report on Emission Scenarios of ECHAM5/MPI-OM as obtained by SDD agree well to the results of other studies using DD methods, with increasing Eout over northern Europe and a negative trend over southern Europe. Despite some biases, it is concluded that SDD is an adequate tool to assess regional wind energy changes in large model ensembles.

Megacities and climate change: a brief overview

Cities have developed into the hotspots of human economic activity. From the appearance of the first cities in the Neolithic to 21st century metropolis their impact on the environment has always been apparent. With more people living in cities than in rural environments now it becomes crucial to understand these environmental impacts. With the immergence of megacities in the 20th century and their continued growth in both, population and economic power, the environmental impact has reached the global scale. In this paper we examine megacity impacts on atmospheric composition and climate. We present basic concepts, discuss various definitions of footprints, summarize research on megacity impacts and assess the impact of megacity emissions on air quality and on the climate at the regional to global scale. The intention and ambition of this paper is to give a comprehensive but brief overview of the science with regard to megacities and the environment.

Hurricanes and climate: the U.S. CLIVAR working group on hurricanes

While a quantitative climate theory of tropical cyclone formation remains elusive, considerable progress has been made recently in our ability to simulate tropical cyclone climatologies and understand the relationship between climate and tropical cyclone formation. Climate models are now able to simulate a realistic rate of global tropical cyclone formation, although simulation of the Atlantic tropical cyclone climatology remains challenging unless horizontal resolutions finer than 50 km are employed. This article summarizes published research from the idealized experiments of the Hurricane Working Group of U.S. CLIVAR (CLImate VARiability and predictability of the ocean-atmosphere system). This work, combined with results from other model simulations, has strengthened relationships between tropical cyclone formation rates and climate variables such as mid-tropospheric vertical velocity, with decreased climatological vertical velocities leading to decreased tropical cyclone formation. Systematic differences are shown between experiments in which only sea surface temperature is increased versus experiments where only atmospheric carbon dioxide is increased, with the carbon dioxide experiments more likely to demonstrate the decrease in tropical cyclone numbers previously shown to be a common response of climate models in a warmer climate. Experiments where the two effects are combined also show decreases in numbers, but these tend to be less for models that demonstrate a strong tropical cyclone response to increased sea surface temperatures. Further experiments are proposed that may improve our understanding of the relationship between climate and tropical cyclone formation, including experiments with two-way interaction between the ocean and the atmosphere and variations in atmospheric aerosols.

Basic concepts for convection parameterization in weather forecast and climate models: COST Action ES0905 final report

The research network “Basic Concepts for Convection Parameterization in Weather Forecast and Climate Models” was organized with European funding (COST Action ES0905) for the period of 2010–2014. Its extensive brainstorming suggests how the subgrid-scale parameterization problem in atmospheric modeling, especially for convection, can be examined and developed from the point of view of a robust theoretical basis. Our main cautions are current emphasis on massive observational data analyses and process studies. The closure and the entrainment–detrainment problems are identified as the two highest priorities for convection parameterization under the mass–flux formulation. The need for a drastic change of the current European research culture as concerns policies and funding in order not to further deplete the visions of the European researchers focusing on those basic issues is emphasized.

Observed relationships between maize yield and climate in Sri Lanka

The present study evaluated the effects of climate variability on maize (Zea mays L.) yield in Sri Lanka at different spatial scales. Biophysical data from the Department of Agriculture (DOA) in Sri Lanka for six major maize-growing districts (Ampara, Anuradhapura, Badulla, Hambantota, Moneragala, and Kurunegala) from 1990 to 2010 were analyzed. Simple linear regression models were fitted to observed climate data and detrended maize yield to identify significant correlations. The correlation between first differences of maize yield and climate (r) was further investigated at 0.50° grid scale using interpolated climate data. After 2003, significantly positive (p < 0.01) yield trends varied from 154 kg ha–1 yr–1 to 360 kg ha–1 yr–1. The correlations between maize yield and climate reported that five out of six districts were significant at 10% level. Rainfall had a consistent significant (p < 0.10) positive impact on maize yield in Anuradhapura, Hambantota, and Moneragala, where seasonal total rainfall together with high temperature (“hot-dry”) are the key limitations. Further, the seasonal mean temperature had a negative impact on maize yield in Moneragala (“hot-dry”), the only district that showed high temperatures. Badulla district (“cold-dry”) reported a significant (r = 0.38) positive correlation with mean seasonal temperature, indicating higher potential toward increasing temperatures. Each 1°C rise in seasonal mean temperature reduced maize yield by about 5% from 1990 to 2010. Overall, there was a reasonable correlation between district maize yield and seasonal climate in most of the districts within the maize belt of Sri Lanka.

Clouds, circulation and climate sensitivity

Fundamental puzzles of climate science remain unsolved because of our limited understanding of how clouds, circulation and climate interact. One example is our inability to provide robust assessments of future global and regional climate changes. However, ongoing advances in our capacity to observe, simulate and conceptualize the climate system now make it possible to fill gaps in our knowledge. We argue that progress can be accelerated by focusing research on a handful of important scientific questions that have become tractable as a result of recent advances. We propose four such questions below; they involve understanding the role of cloud feedbacks and convective organization in climate, and the factors that control the position, the strength and the variability of the tropical rain belts and the extratropical storm tracks.

Radiative forcing and climate metrics for ozone precursor emissions: the impact of multi-model averaging

Multi-model ensembles are frequently used to assess understanding of the response of ozone and methane lifetime to changes in emissions of ozone precursors such as NOx, VOCs (volatile organic compounds) and CO. When these ozone changes are used to calculate radiative forcing (RF) (and climate metrics such as the global warming potential (GWP) and global temperature-change potential (GTP)) there is a methodological choice, determined partly by the available computing resources, as to whether the mean ozone (and methane) concentration changes are input to the radiation code, or whether each model's ozone and methane changes are used as input, with the average RF computed from the individual model RFs. We use data from the Task Force on Hemispheric Transport of Air Pollution source–receptor global chemical transport model ensemble to assess the impact of this choice for emission changes in four regions (East Asia, Europe, North America and South Asia). We conclude that using the multi-model mean ozone and methane responses is accurate for calculating the mean RF, with differences up to 0.6% for CO, 0.7% for VOCs and 2% for NOx. Differences of up to 60% for NOx 7% for VOCs and 3% for CO are introduced into the 20 year GWP. The differences for the 20 year GTP are smaller than for the GWP for NOx, and similar for the other species. However, estimates of the standard deviation calculated from the ensemble-mean input fields (where the standard deviation at each point on the model grid is added to or subtracted from the mean field) are almost always substantially larger in RF, GWP and GTP metrics than the true standard deviation, and can be larger than the model range for short-lived ozone RF, and for the 20 and 100 year GWP and 100 year GTP. The order of averaging has most impact on the metrics for NOx, as the net values for these quantities is the residual of the sum of terms of opposing signs. For example, the standard deviation for the 20 year GWP is 2–3 times larger using the ensemble-mean fields than using the individual models to calculate the RF. The source of this effect is largely due to the construction of the input ozone fields, which overestimate the true ensemble spread. Hence, while the average of multi-model fields are normally appropriate for calculating mean RF, GWP and GTP, they are not a reliable method for calculating the uncertainty in these fields, and in general overestimate the uncertainty.

Two fast radiative transfer methods to improve the temporal sampling of clouds in numerical weather prediction and climate models

The high computational cost of calculating the radiative heating rates in numerical weather prediction (NWP) and climate models requires that calculations are made infrequently, leading to poor sampling of the fast-changing cloud field and a poor representation of the feedback that would occur. This paper presents two related schemes for improving the temporal sampling of the cloud field. Firstly, the ‘split time-stepping’ scheme takes advantage of the independent nature of the monochromatic calculations of the ‘correlated-k’ method to split the calculation into gaseous absorption terms that are highly dependent on changes in cloud (the optically thin terms) and those that are not (optically thick). The small number of optically thin terms can then be calculated more often to capture changes in the grey absorption and scattering associated with cloud droplets and ice crystals. Secondly, the ‘incremental time-stepping’ scheme uses a simple radiative transfer calculation using only one or two monochromatic calculations representing the optically thin part of the atmospheric spectrum. These are found to be sufficient to represent the heating rate increments caused by changes in the cloud field, which can then be added to the last full calculation of the radiation code. We test these schemes in an operational forecast model configuration and find a significant improvement is achieved, for a small computational cost, over the current scheme employed at the Met Office. The ‘incremental time-stepping’ scheme is recommended for operational use, along with a new scheme to correct the surface fluxes for the change in solar zenith angle between radiation calculations.

Radiative forcing and climate change

Aviation causes climate change as a result of its emissions of CO2, oxides of nitrogen, aerosols, and water vapor. One simple method of quantifying the climate impact of past emissions is radiative forcing. The radiative forcing due to changes in CO2 is best characterized, but there are formidable difficulties in estimating the non-CO2 forcings – this is particularly the case for possible aviation-induced changes in cloudiness (AIC). The most recent comprehensive assessment gave a best estimate of the 2005 total radiative forcing due to aviation of about 55–78 mW m−2 depending on whether AIC was included or not, with an uncertainty of at least a factor of 2. The aviation CO2 radiative forcing represents about 1.6% of the total CO2 forcing from all human activities. It is estimated that, including the non-CO2 effects, aviation contributes between 1.3 and 14% of the total radiative forcing due to all human activities. Alternative methods for comparing the future impact of present-day aviation emissions are presented – the perception of the relative importance of the non-CO2 emissions, relative to CO2, depends considerably on the chosen method and the parameters chosen within those methods.

Vegetation history, human impact and climate change during prehistory: an island perspective of the isles of Tiree, Coll and north-west Mull

Results of extensive site reconnaissance on the Isles of Tiree, Coll and north-west Mull, Inner Hebrides are presented. Pollen-stratigraphic records were compiled from a profile from Glen Aros, north-west Mull and from two profiles on Coll located at Loch an t-Sagairt and Caolas an Eilean. Quantification of microscopic charcoal provided records that were used to facilitate a preliminary evaluation of the causal driving mechanisms of vegetation change. Bayesian modelling of radiocarbon dates was used to construct preliminary chronological frameworks for these records. Basal sedimentary deposits at Glen Aros contain pollen records that correspond with vegetation succession typical of the early Holocene dating to c. 11,370 cal BP. Woodland development is a key feature of the pollen records dating to the early Holocene, while records from Loch an t-Sagairt show that blanket mire communities were widespread in north-west Coll by c. 9800 cal BP. The Corylus-rise is dated to c. 10,710 cal BP at Glen Aros and c. 9905 cal BP at Loch an t-Sagairt, with records indicating extensive cover of hazel woodland with birch. All of the major arboreal taxa were recorded, though Quercus and Ulmus were nowhere widespread. Analysis of wood charcoal remains from a Mesolithic site at Fiskary Bay, Coll indicate that Salix and Populus are likely to be under-represented in the pollen records. Reconstructed isopoll maps appear to underplay the importance of alder in western Scotland during the mid-Holocene. Alder-rise expansions in microscopic charcoal dating to c. 7300 cal BP at Glen Aros and c. 6510 to 5830 cal BP on Coll provide records of significance to the issue of human-induced burning related to the expansion of alder in Britain. Increasing frequencies in microscopic charcoal are correlated with mid-Holocene records of increasing aridity in western Scotland after c. 7490 cal BP at Glen Aros, 6760 cal BP at Loch an t-Sagairt and 6590 cal BP at Caolas an Eilean, while several phases of increasing bog surface wetness were detected in the Loch an t-Sagairt archive during the Holocene. At least five phases of small-scale woodland disturbance during the Mesolithic period were identified in the Glen Aros profile dating to c. 11,650 cal BP, 9300 cal BP, 7840 cal BP, 7040 cal BP and 6100 cal BP. The timing of the third phase is coincident with evidence of Mesolithic settlement at Creit Dhu, north-west Mull. Three phases of small-scale woodland disturbance were detected at Loch an t-Sagairt dating to c. 9270 cal BP, 8770 cal BP and 8270 cal BP, all of which overlap chronologically with evidence of Mesolithic activity at Fiskary Bay, Coll. A number of these episodes are aligned chronologically with phases of Holocene climate variability such as the 8.2 K event.