Media attention for climate change around the world: A comparative analysis of newspaper coverage in 27 countries

Climate change is a global phenomenon, and its outcomes affect societies around the world. So far, however, studies on media representations of climate change have mostly concentrated on Western societies. This paper goes beyond this limited geographical scope by presenting a comparative analysis of issue attention in 27 countries. The sample includes, among others, countries that have committed themselves to greenhouse gas emission reductions under the Kyoto Protocol such as Germany as well as countries that are strongly affected by the consequences of climate change like India. In a first step, it describes the development of media attention for climate change in these countries from 1996 to 2010. Second, it compares the amount of media attention and explores whether it corresponds with indicators measuring the relevance of climate change and climate policies for a country. The analyses show that climate change coverage has increased in all countries. Still, overall media attention levels, as well as the extent of growth over time, differ strongly between countries. Media attention is especially high in carbon dependent countries with commitments under the Kyoto Protocol.     

Flow over Hills: A Large-Eddy Simulation of the Bolund Case

Simulation of local atmospheric flows around complex topography is important for several applications in wind energy (short-term wind forecasting and turbine siting and control), local weather prediction in mountainous regions and avalanche risk assessment. However, atmospheric simulation around steep mountain topography remains challenging, and a number of different approaches are used to represent such topography in numerical models. The immersed boundary method (IBM) is particularly well-suited for efficient and numerically stable simulation of flow around steep terrain. It uses a homogenous grid and permits a fast meshing of the topography. Here, we use the IBM in conjunction with a large-eddy simulation (LES) and test it against two unique datasets. In the first comparison, the LES is used to reproduce experimental results from a wind-tunnel study of a smooth three-dimensional hill. In the second comparison, we simulate the wind field around the Bolund Hill, Denmark, and make direct comparisons with field measurements. Both cases show good agreement between the simulation results and the experimental data, with the largest disagreement observed near the surface. The source of error is investigated by performing additional simulations with a variety of spatial resolutions and surface roughness properties.     

Tracking suitable habitat for tree populations under climate change in western North America

An important criticism of bioclimate envelope models is that many wide-ranging species consist of locally adapted populations that may all lag behind their optimal climate habitat under climate change, and thus should be modeled separately. Here, we apply a bioclimate envelope model that tracks habitat of individual populations to estimate adaptational lags for 15 wide-ranging forest tree species in western North America. An ensemble classifier modeling approach (RandomForest) was used to spatially project the climate space of tree populations under observed climate trends (1970s to 2000s) and multi-model projections for the 2020s, 2050s and 2080s. We find that, on average, populations already lag behind their optimal climate niche by approximately 130 km in latitude, or 60 m in elevation. For the 2020s we expect an average lag of approximately 310 km in latitude or 140 m in elevation, with the most pronounced geographic lags in the Rocky Mountains and the boreal forest. We show that our results could in principle be applied to guide assisted migration of planting stock in reforestation programs using a general formula where 100 km north shift is equivalent to approximately 44 m upward shift in elevation. However, additional non-climatic factors should be considered when matching reforestation stock to suitable planting environments.     

Effects of climate change on oceanic fisheries in the tropical Pacific: implications for economic development and food security

The four species of tuna that underpin oceanic fisheries in the tropical Pacific (skipjack, yellowfin, bigeye and albacore tuna) deliver great economic and social benefits to Pacific Island countries and territories (PICTs). Domestic tuna fleets and local fish processing operations contribute 3–20 % to gross domestic product in four PICTs and licence fees from foreign fleets provide an average of 3–40 % of government revenue for seven PICTs. More than 12,000 people are employed in tuna processing facilities and on tuna fishing vessels. Fish is a cornerstone of food security for many PICTs and provides 50–90 % of dietary animal protein in rural areas. Several PICTs have plans to (1) increase the benefits they receive from oceanic fisheries by increasing the amount of tuna processed locally, and (2) allocate more tuna for the food security of their rapidly growing populations. The projected effects of climate change on the distribution of tuna in the tropical Pacific Ocean, due to increases in sea surface temperature, changes in velocity of major currents and decreases in nutrient supply to the photic zone from greater stratification, are likely to affect these plans. PICTs in the east of the region with a high dependence on licence fees for government revenue are expected to receive more revenue as tuna catches increase in their exclusive economic zones. On the other hand, countries in the west may encounter problems securing enough fish for their canneries as tuna are redistributed progressively to the east. Changes in the distribution of tuna will also affect the proportions of national tuna catches required for food security. We present priority adaptations to reduce the threats to oceanic fisheries posed by climate change and to capitalise on opportunities.     

Multi-variable error correction of regional climate models

Climate change impact research needs regional climate scenarios of multiple meteorological variables. Those variables are available from regional climate models (RCMs), but affected by considerable biases. We evaluate the application of an empirical-statistical error correction method, quantile mapping (QM), for a small ensemble of RCMs and six meteorological variables. Annual and monthly biases are reduced to close to zero by QM for all variables in most cases. Exceptions are found, if non-stationarity of the model’s error characteristics occur. Even in the worst cases of non-stationarity, QM clearly improves the biases of raw RCMs. In addition, QM successfully adjusts the distributions of the analysed variables. To approach the question whether time series and inter-variable relationships are still plausible after correction, we evaluate the root-mean-square error (RMSE), autocorrelation and inter-variable correlation. We found improvement or no clear effect in RMSE and autocorrelation, and no clear effect on the correlation between meteorological variables. These results demonstrate that QM retains the quality of the temporal structure in time series and the inter-variable dependencies of RCMs. It has to be emphasised that this cannot be interpreted as an improvement and that deficiencies of the RCMs in those features are retained as well. Our results give some indication for the performance of QM applied to future scenarios, since our evaluation relies on independent calibration and evaluation periods, which are affected by climate variability and change. The effect of non-stationarity, however, can be expected to be larger in far future. We demonstrate the retainment of the RCM’s temporal structure and inter-variable dependencies, and large improvements in biases. This qualifies QM as a valuable, though not perfect, method in the interface between climate models and climate change impact research. Nonetheless, in case of no correlation between re-analysis driven RCM and observation, one should consider that QM does not correct this correlation.     

Mechanism development and modelling of tropospheric multiphase halogen chemistry: The CAPRAM Halogen Module 2.0 (HM2)

A new detailed multiphase halogen mechanism, the CAPRAM Halogen Module 2.0 (HM2), has been developed and coupled to the multiphase chemistry mechanism RACM-MIM2ext/CAPRAM 3.0n. The overall mechanism comprises 1,705 reactions including 595 reactions of the HM2. Halogen chemistry box model studies have been, for the first time, performed with a non-permanent cloud scenario for pristine open ocean regions in mid-latitudes. Moreover, detailed time-resolved reaction flux analysis has been used to investigate the multiphase halogen reaction cycles in more detail. Clouds significantly change the multiphase halogen chemical system and new reaction cycles are proposed for in-cloud conditions. While most gas phase concentrations are decreased for chlorine and iodine species, they are increased for bromine. Flux analyses determined the relative contributions of the methylene dihalides CH₂IX (X = Cl, Br, I) as the main I atom source with a contribution of about 80 % to the total iodocarbon sources. Furthermore, HOI was confirmed to be important for chlorine activation. It is shown that 25 % of the ozone loss can be attributed to halogens. VOC oxidation by halogens is important as halogens account for about 20 % of the methane oxidation and up to 80 % of the oxidation of other VOCs. In other cases, enhanced VOC and VOC oxidation product concentration levels were found. For example, 15 % of the methyl peroxyl radicals are formed after the reaction of chlorine atoms with methane or methyl hydroperoxide. In the aqueous phase, changes in the oxidation of organics do only occur for highly oxidised organics without a C-H bond. For example, over 80 % of oxalic acid are oxidised by electron transfer with Cl₂ ^? in deliquescent particles during non-cloud periods.     

Basic analysis of climate and urban bioclimate of Dar es Salaam, Tanzania

Better understanding of urban microclimate and bioclimate of any city is imperative today when the world is constrained by both urbanisation and global climate change. Urbanisation generally triggers changes in land cover and hence influencing the urban local climate. Dar es Salaam city in Tanzania is one of the fast growing cities. Assessment of its urban climate and the human biometeorological conditions was done using the easily available synoptic meteorological data covering the period 2001–2011. In particular, the physiologically equivalent temperature (PET) was calculated using the RayMan software and results reveal that the afternoon period from December to February (DJF season) is relatively the most thermal stressful period to human beings in Dar es Salaam where PET values of above 35 °C were found. Additionally, the diurnal cycle of the individual meteorological elements that influence the PET index were analysed and found that air temperature of 30–35 °C dominate the afternoon period from 12:00 to 15:00 hours local standard time at about 60 % of occurrence. The current results, though considered as preliminary to the ongoing urban climate study in the city, provide an insight on how urban climate research is of significant importance in providing useful climatic information for ensuring quality of life and wellbeing of city dwellers.     

The simulation of European heat waves from an ensemble of regional climate models within the EURO-CORDEX project

The ability of a large ensemble of regional climate models to accurately simulate heat waves at the regional scale of Europe was evaluated. Within the EURO-CORDEX project, several state-of-the art models, including non-hydrostatic meso-scale models, were run for an extended time period (20 years) at high resolution (12 km), over a large domain allowing for the first time the simultaneous representation of atmospheric phenomena over a large range of spatial scales. Eight models were run in this configuration, and thirteen models were run at a classical resolution of 50 km. The models were driven with the same boundary conditions, the ERA-Interim re-analysis, and except for one simulation, no observations were assimilated in the inner domain. Results, which are compared with daily temperature and precipitation observations (ECA&D and E-OBS data sets) show that, even forced by the same re-analysis, the ensemble exhibits a large spread. A preliminary analysis of the sources of spread, using in particular simulations of the same model with different parameterizations, shows that the simulation of hot temperature is primarily sensitive to the convection and the microphysics schemes, which affect incoming energy and the Bowen ratio. Further, most models exhibit an overestimation of summertime temperature extremes in Mediterranean regions and an underestimation over Scandinavia. Even after bias removal, the simulated heat wave events were found to be too persistent, but a higher resolution reduced this deficiency. The amplitude of events as well as the variability beyond the 90th percentile threshold were found to be too strong in almost all simulations and increasing resolution did not generally improve this deficiency. Resolution increase was also shown to induce large-scale 90th percentile warming or cooling for some models, with beneficial or detrimental effects on the overall biases. Even though full causality cannot be established on the basis of this evaluation work, the drivers of such regional differences were shown to be linked to changes in precipitation due to resolution changes, affecting the energy partitioning. Finally, the inter-annual sequence of hot summers over central/southern Europe was found to be fairly well simulated in most experiments despite an overestimation of the number of hot days and of the variability. The accurate simulation of inter-annual variability for a few models is independent of the model bias. This indicates that internal variability of high summer temperatures should not play a major role in controlling inter-annual variability. Despite some improvements, especially along coastlines, the analyses conducted here did not allow us to generally conclude that a higher resolution is clearly beneficial for a correct representation of heat waves by regional climate models. Even though local-scale feedbacks should be better represented at high resolution, combinations of parameterizations have to be improved or adapted accordingly.     

Depositional rates and dating techniques of modern deposits in the Brno reservoir (Czech Republic) during the last 70 years

Facies analysis, magnetic susceptibility, and analysis of grain size, TOC content and isotopes (¹³⁷Cs, ²¹⁰Pb, ²²⁶Ra, ²²⁸Ra, and ²³⁸U concentrations) were used to determine the history of the modern deposits of the Brno reservoir. The sedimentary succession can be subdivided into two main units. The lower unit is formed predominantly by medium- to coarse-grained silty sands and is interpreted as a fluvial succession deposited before the Svratka River was dammed. The upper unit consists of brownish planar laminated silts and rarely of clayey or sandy silts and is interpreted as a product of the reservoir deposition. The concentrations of ²³⁸U reflect the history of uranium mining in the upper part of the Svratka River catchment. As a consequence, ²¹⁰Pb radionuclide concentrations cannot be used for establishing a sediment chronology. Concentrations of ¹³⁷Cs show two marked peaks, the upper of which is attributed to the Chernobyl reactor accident in 1986, and the lower one is attributed to the maximum rate of atomic weapons testing in 1963. From these peaks, mean depositional rates of 3.2 cm year⁻¹ for the time period of 1986–2007 and of 3.4 cm year⁻¹ between 1963 and 1986 are calculated. Based on the known age of the reservoir, which was constructed in 1939, we can also calculate mean depositional rate for the time period of 1939–1963, which is 3.1 cm year⁻¹.