Incorporating Future Climate Scenarios in Oil Industry’s Risk Assessment: A Greek Refinery Case Study

The impacts of climate change are anticipated to become stronger in the future, leading to higher costs and more severe accidents in the oil industry’s facilities and surrounding communities. Motivated by this, the main objective of this paper is to develop, for the oil industry, a risk assessment methodology that considers future climate projections. In the context of an action research effort, carried out in a refinery in Greece, we adapted the organization’s extant risk management approach based on the Risk Assessment Matrix (RAM) and suggested a risk quantification process that incorporates future climate projections. The Climate Risk Assessment Matrix (CRAM) was developed to be used to assess the exposure of the facility’s assets, including human resources, to future climate risks. To evaluate CRAM, a comparison with RAM for the specific organization for the period 1980–2004 was made. Next, the application of CRAM for the period 2025–2049 indicated that, even though the resilience of the operations of the company to extreme conditions seems adequate at present, increased attention should be paid in the future to the resilience of refinery processes, the cooling system, and human resources. Beyond the specific case, the paper provides lessons for similar organizations and infrastructures located elsewhere.

Future Projections of Heat Mortality Risk for Major European Cities

Over the last few decades heat waves have intensified and have led to excess mortality. While the probability of being affected by heat stress has significantly increased, the risk of heat mortality is rarely quantified. This quantification of heat mortality risk is necessary for systematic adaptation measures. Furthermore, heat mortality records are sparse and short, which presents a challenge for assessing heat mortality risk for future climate projections. It is therefore crucial to derive indicators for a systematic heat mortality risk assessment. Here, risk indicators based on temperature and mortality data are developed and applied to major cities in Germany, France and Spain, using regional climate model simulations. Bias-corrected daily maximum, minimum and wet-bulb temperatures show increasing trends in future climate projections for most considered cities. Additionally, we derive a relationship between daily maximum temperatures and mortality for producing future projections of heat mortality risk due to extreme temperatures based on low (Representative Concentration Pathway; RCP2.6) and high (RCP8.5) emission scenario future climate projections. Our results illustrate that heat mortality increases by about 0.9%/decade in Germany, 1.7%/decade in France and 7.9%/decade in Spain for RCP8.5 by 2050. The future climate projections also show that wet-bulb temperatures above 30°C will be reached regularly with maxima above 40°C likely by 2050. Our results suggest a significant increase of heat mortality in the future, especially in Spain. On average, our results indicate that the mortality risk trend is almost twice as high in all three countries for the RCP8.5 scenario compared to RCP2.6.

Climate change projections of maximum temperature in the pre-monsoon season in Bangladesh using statistical downscaling of global climate models

The climate of Bangladesh is very likely to be influenced by global climate change. To quantify the influence on the climate of Bangladesh, Global Climate Models were downscaled statistically to produce future climate projections of maximum temperature during the pre-monsoon season (March–May) for the 21st century for Bangladesh. The future climate projections are generated based on three emission scenarios (RCP2.6, RCP4.5 and RCP8.5) provided by the fifth Coupled Model Intercomparison Project. The downscaling process is undertaken by relating the large-scale seasonal mean temperature, taken from the ERA5 reanalysis data set, to the leading principal components of the observed maximum temperature at stations under Bangladesh Meteorological Department in Bangladesh, and applying the relationship to the GCM ensemble. The in-situ temperature data has only recently been digitised, and this is the first time they have been used in statistical downscaling of local climate projections for Bangladesh. This analysis also provides an evaluation of the local data, and the local temperatures in Bangladesh show a close match with the ERA5 reanalysis. Compared to the reference period of 1981–2010, the projected maximum pre-monsoon temperature in Bangladesh indicate an increase by 0.7/0.7/0.7 ∘C in the near future (2021–2050) and 2.2/1.2/0.8 ∘C in the far future (2071–2100) assuming the RCP8.5/RCP4.5/RCP2.6 scenario, respectively.

Communicating future climate projections of precipitation change

Understanding how precipitation may change in the future is important for guiding climate change adaptation. Climate models are the primary tools for providing information on future precipitation change, though communicating and interpreting results of different model simulations is challenging. Using an online survey, completed by producers and users of climate model information, we compare and evaluate interpretations of different approaches used to summarise and visualise future climate projections. Results reveal large differences in interpretations of precipitation change arising from choices made in summarising and visualising the data. Respondents interpret significantly smaller ranges of future precipitation change when provided with the multi-model ensemble mean or percentile information, which are commonly used to summarise climate model projections, compared to information about the full ensemble. The ensemble mean is found to be particularly misleading, even when used with information to show model agreement in the sign of change. We conclude that these approaches can lead to distorted interpretations which may impact on adaptation policy and decision-making. To help improve the interpretation and use of climate projections in decision-making, regular testing of visualisations and sustained engagement with target audiences is required to determine the most effective and appropriate visualisation approaches.

Incorporating missing volcanic impacts into future climate impact assessments

<div> <div> <div> <p>Future climate projections for the 21st century generally do not include the effects of volcanic eruptions. While some attempt has been made to account for the integrated effect of multiple eruptions by incorporating a small continuous volcanic forcing, a recent study (http://nature.com/articles/doi:10.1038/nclimate3394) has already shown that this approach is insufficient to resolve the increased climate variance caused by individual eruptions, especially on decadal timescales. Increased climate variance exerts stresses on ecosystems and society, thus resolving the impacts of plausible future volcanic eruptions is of importance for certain adaptation and mitigation decisions.</p> <p>While previous work has used a modelling approach to address this problem, in this talk we demonstrate a computationally inexpensive method to incorporate the effects of plausible volcanic eruptions into future climate projections. This method uses stochastic volcanic emulators based on 2,500 years of past volcanic activity and the characterization of the response of the climate system to individual eruptions. We will demonstrate not only this methodology, but also describe the requirements and potential for its application to the wider future projections of CMIP6.</p> </div> </div> </div>