Urban vulnerability and adaptation to heatwaves: a case study of Graz (Austria)

The increasing frequency of heatwaves, particularly in urban contexts, is one of the perceptible consequences of climate change. A city’s vulnerability to these heatwaves must be determined to develop proper adaptation measures. This article addresses the vulnerability of a medium-sized city in Central Europe, Graz, to heatwaves. Based on secondary data and primary data gathered from expert interviews, we identified certain determinants of vulnerability for the city: temperature, proportion of open and green spaces to developed areas, construction period of buildings, distribution of age and poverty risk, adaptation strategies used, and risk perception levels assessed for decision makers in the city administration. Certain city districts can be classified as particularly vulnerable. A high level of risk perception was detected among all decision makers and some adaptation measures have already been enacted. In particular, inter-organizational collaboration in adaptation networks works effectively. A deficit in efficient communication between researchers, policy makers, and members of the public was perceived to be the main barrier. This case study exemplifies the assessment of a city’s vulnerability to heatwaves on the basis of particular determinants and can be applied to many other cities.

Policy relevance

The method applied revealed potential improvements and opportunities on the policy level. Strong networks for climate change adaptation are most effective if regular meetings take place, allowing trust and friendship to grow between decision makers. More target-group-oriented information is needed. Emergency organizations, in particular, need more information, because the perception of heatwave risks has only been based thus far on personal experiences. By establishing a central authority, more information could be provided on heatwaves in cities. The need to raise the perception of members of the population and motivate them to take personal responsibility during disasters was emphasized by interviewed decision makers. This can be supported by providing advice during heatwaves through newspapers, TV, and radio. People in risk groups and their relatives could be trained in workshops. City areas that are at high risk should be marked on maps to make relevant information more tangible for decision makers.     

Seychelles coral record of changes in sea surface temperature bimodality in the western Indian Ocean from the Mid-Holocene to the present

We report fossil coral records from the Seychelles comprising individual time slices of 14–20 sclerochronological years between 2 and 6.2 kyr BP to reconstruct changes in the seasonal cycle of western Indian Ocean sea surface temperature (SST) compared to the present (1990–2003). These reconstructions allowed us to link changes in the SST bimodality to orbital changes, which were causing a reorganization of the seasonal insolation pattern. Our results reveal the lowest seasonal SST range in the Mid-Holocene (6.2–5.2 kyr BP) and around 2 kyr BP, while the highest range is observed around 4.6 kyr BP and between 1990 and 2003. The season of maximum temperature shifts from austral spring (September to November) to austral autumn (March to May), following changes in seasonal insolation over the past 6 kyr. However, the changes in SST bimodality do not linearly follow the insolation seasonality. For example, the 5.2 and 6.2 kyr BP corals show only subtle SST differences in austral spring and autumn. We use paleoclimate simulations of a fully coupled atmosphere–ocean general circulation model to compare with proxy data for the Mid-Holocene around 6 kyr BP. The model results show that in the Mid-Holocene the austral winter and spring seasons in the western Indian Ocean were warmer while austral summer was cooler. This is qualitatively consistent with the coral data from 6.2 to 5.2 kyr BP, which shows a similar reduction in the seasonal amplitude compared to the present day. However, the pattern of the seasonal SST cycle in the model appears to follow the changes in insolation more directly than indicated by the corals. Our results highlight the importance of ocean–atmosphere interactions for Indian Ocean SST seasonality throughout the Holocene. In order to understand Holocene climate variability in the countries surrounding the Indian Ocean, we need a much more comprehensive analysis of seasonally resolved archives from the tropical Indian Ocean. Insolation data alone only provides an incomplete picture.     

US agricultural sector analysis on pesticide externalities – the impact of climate change and a Pigovian tax

Residuals from agricultural pesticides threaten the environment and human health. Climate change alters these externalities because it affects pest pressure and pesticide application rates. This study examines damages from pesticide externalities in US agriculture under different climate projections and the effects of alternative regulations. We find divergent impacts of externality regulation and climate change on agricultural production in the US. A Pigovian tax on pesticide externalities generally increases crop production cost, but farm revenue improves because of increased commodity prices. Climate change generally decreases US farm revenue because production increases and prices fall. Results also show a heterogeneous effect of climate change on pest management intensities across major crops.     

Quantitative assessment of the climate components driving the pacific decadal oscillation in climate models

The Pacific decadal oscillation (PDO) is defined as the first empirical orthogonal function (EOF) mode of the North Pacific sea surface temperature anomalies. In this study, we reconstructed the PDO using the first-order autoregressive model from various climate indices representing the El Niño-Southern oscillation (ENSO), Aleutian Low (AL), sea surface height (SSH), and thermocline depth over the Kuroshio–Oyashio extension (KOE) region. The climate indices were obtained from observation and twentieth-century simulations of the eight coupled general circulation models (CGCMs) participating in the Climate Model Intercomparison Project Phase III (CMIP3). In this manner, we quantitatively assessed the major climate components generating the PDO using observation and models. Based on observations, the PDO pattern in the central to eastern North Pacific was accurately reconstructed by the AL and ENSO indices, and that in the western North Pacific was best reconstructed by the SSH and thermocline indices. In the CMIP3 CGCMs, the relative contribution of each component to the generation of the PDO varied greatly from model to model, and observations, although the PDO patterns from most of the models were similar to the pattern observed. In the models, the PDO pattern in the eastern and western North Pacific were well reconstructed using the AL and SSH indices, respectively. However, the PDO pattern reconstructed by the ENSO index was quite different from the observed pattern, which was possibly due to the model's common deficiency in simulating the amplitude and location of the ENSO. Furthermore, the differences in the contribution of the KOE thermocline index between the observed pattern and most of the models indicated that the PDO pattern associated with ocean wave dynamics is not properly simulated by most models. Therefore, the virtually well simulated PDO pattern by models is a result of physically inconsistent processes.     

Climate sensitivity estimated from ensemble simulations of glacial climate

The concentration of greenhouse gases (GHGs) in the atmosphere continues to rise, hence estimating the climate system’s sensitivity to changes in GHG concentration is of vital importance. Uncertainty in climate sensitivity is a main source of uncertainty in projections of future climate change. Here we present a new approach for constraining this key uncertainty by combining ensemble simulations of the last glacial maximum (LGM) with paleo-data. For this purpose we used a climate model of intermediate complexity to perform a large set of equilibrium runs for (1) pre-industrial boundary conditions, (2) doubled CO₂ concentrations, and (3) a complete set of glacial forcings (including dust and vegetation changes). Using proxy-data from the LGM at low and high latitudes we constrain the set of realistic model versions and thus climate sensitivity. We show that irrespective of uncertainties in model parameters and feedback strengths, in our model a close link exists between the simulated warming due to a doubling of CO₂, and the cooling obtained for the LGM. Our results agree with recent studies that annual mean data-constraints from present day climate prove to not rule out climate sensitivities above the widely assumed sensitivity range of 1.5–4.5°C (Houghton et al. 2001). Based on our inferred close relationship between past and future temperature evolution, our study suggests that paleo-climatic data can help to reduce uncertainty in future climate projections. Our inferred uncertainty range for climate sensitivity, constrained by paleo-data, is 1.2–4.3°C and thus almost identical to the IPCC estimate. When additionally accounting for potential structural uncertainties inferred from other models the upper limit increases by about 1°C.