Impervious surfaces (IS) are a key indicator of environmental quality, and mapping of urban IS is important for a wide range of applications including hydrological modelling, water management, urban ...and environmental planning and urban climate studies. This paper addresses the accuracy and applicability of vegetation indices (VI), from Landsat imagery, to estimate IS fractions for European cities. The accuracy of three different measures of vegetation cover is examined for eight urban areas at different locations in Europe. The Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) are converted to IS fractions using a regression modelling approach. Also, NDVI is used to estimate fractional vegetation cover (FR), and consequently IS fractions. All three indices provide fairly accurate estimates (MAEs alomst equal to 10%, MBE's < 2%) of sub-pixel imperviousness, and are found to be applicable for cities with dissimilar climatic and vegetative conditions. The VI/IS relationship across cities is examined by quantifying the MAEs and MBEs between all combinations of models and urban areas. Also, regional regression models are developed by compiling data from multiple cities to examine the potential for developing and applying a single regression model to estimate IS fractions for numerous urban areas without reducing the accuracy considerably. Our findings indicate that the models can be applied broadly for multiple urban areas, and that the accuracy is reduced only marginally by applying the regional models. SAVI is identified as a superior index for the development of regional quantification models. The findings of this study highlight that IS fractions, and spatiotemporal changes herein, can be mapped by use of simple regression models based on VIs from remote sensors, and that the method presented enables simple, accurate and resource efficient quantification of IS.
Risk assessments of flooding in urban areas during extreme precipitation for use in, for example, decision-making regarding climate adaptation, are surrounded by great uncertainties stemming from ...climate model projections, methods of downscaling and the assumptions of socioeconomic impact models. The multidisciplinary character of such risk assessments also requires that research groups and experts from different scientific disciplines combine knowledge and share model outputs. This paper describes an integrated framework and tool, the Danish Integrated Assessment System (DIAS), which has been designed to address the complex linkages between the different kinds of data required in assessing climate adaptation. It emphasizes that the availability of spatially explicit data can reduce the overall uncertainty of the risk assessment and assist in identifying key vulnerable assets. The usefulness of such a framework is demonstrated by means of a risk assessment of flooding from extreme precipitation for the city of Odense, Denmark. A sensitivity analysis shows how the presence of particularly important assets, such as cultural and historical heritage, may be addressed in assessing such risks. The output of the risk assessment for Odense indicates that highly detailed geographical data reduce the overall uncertainty and assist climate adaptation decision-makers in focusing on protecting those assets that are considered to be relevant in the given context. Also, using an integrated framework such as DIAS enables the relative importance of the different factors (i.e. degree of climate change, assets value, discount rate etc.) to be determined, thus influencing the overall output of the assessment.
To limit global warming to less than 2 °C requires a low-carbon transition with very large shares of renewables. Options such as wind, solar and hydro are influenced by both short and longer-term ...weather and climate variability. While still subject to natural and anthropogenic climate forcing and fluctuating energy prices, water reservoirs can dually operate as storage and production facilities and serve to balance the more volatile production capacity from solar and wind. This paper assesses the dynamics and demands of the hydro-dominated Nordic electricity system and market and identifies untapped potential for climate services based on a combination of literature-based research, documented stakeholder needs and data sources on historical and future conditions. A critical need for both improving the appropriateness and reliability of existing climate services and for developing new tailored solutions for a broader group of stakeholders from the renewable energy sector in the Nordics is observed. The quantification of uncertainties related to short-term weather forecasts and longer-term climate predictions is also found to be important for minimizing the financial risk in relation to systems management and to overall investments in renewable energy.
Climate change risk assessments traditionally follow an analytical structure in which climate information is linked to impact models, and subsequently to damage models and decision-making tools. This ...structure generates a wide cascade of uncertainties that accumulate with each analytical step, consequently resulting in a wide range of risk estimates. This cascade of uncertainties can suggest that climate change risk assessments are not very useful in the context of decision-making regarding climate adaptation. However, many of the uncertainties revealed in traditionally structured climate risk assessments are not equally relevant to specific decisions, and presenting wide cascades of uncertainties can mask key decision-making parameters. In this paper, we show how the cascade of uncertainty relevant to decision-making can be reduced by applying an uncertainty decomposition approach, which, in study design, initially identifies the uncertainty cascade elements of particular relevance to the focal decision-making context. We compare the full cascade of uncertainties that emerge in a traditional risk assessment based on linked climate scenarios, impact modeling, and damage cost assessment with the uncertainty cascade generated by a detailed assessment of urban flooding risks where the focus is on key uncertainties in decision-making on climate change adaptation. A case study on flooding from extreme precipitation in the Danish city of Odense is used to decompose major sources of uncertainties in the climate modeling, the hydrological modeling, and the damage cost assessment. The decomposition approach reduces the focal range of damage cost estimates by 7–9 M EUR, which corresponds to a 20–24% reduction in the full uncertainty range without the application of the decomposition approach. Assuming that damage cost assessments can provide an indication of how much society should be willing to spend on climate adaptation, a decomposition approach as presented here could assist decision-makers in increasing the economic effectiveness when investing in protective measures.
Linear trend analysis and seasonal trend analysis are performed on gridded data of vegetation, rainfall, solar radiation flux, and air temperature, in order to examine the influence of the past three ...decades of climate variability and change on the Sahelian vegetation dynamics. Per-pixel correlation analyses are conducted on annual and monthly data, and analyses of change in the potential climatic constraints to the natural vegetation development from 1982–2007 are performed. The results reveal two distinct periods: (a) 1982–1994 marked by large increases in vegetation productivity and rainfall and little change in average air temperatures and solar radiation and (b) 1995–2007 characterized by no distinct trends in vegetation productivity and rainfall and increase in average air temperatures and decrease in solar radiation flux. Correlations between vegetation productivity and climatic constraints were found to be statistically significant only for rainfall explaining only a moderate degree of observed NDVI variation, indicating that nonclimatic factors are also important for the Sahelian vegetation dynamics.
Least developed countries are generally regarded as particularly sensitive to climate change due to among other vulnerable locations and low adaptation capabilities. In the present study, we address ...climate change hazards in least developed countries by presenting a methodological framework, which is suitable for the estimation damage costs as a function of risk aversion, equality, income distribution and climate scenario using state-of-the-art climate model projections. As a case study, the methodology is applied to study severe storms in Cambodia based on two future climate scenarios and data on historical damages from storm events, which are used as a proxy in performing a sensitivity analysis on all input parameters. For the assumptions and parameter ranges used here, the study shows a high sensitivity to the income distribution (reflected by discount rates) and risk aversion and smaller effects from equality measures and extreme wind climate scenario. We emphasize that the assumptions on risk aversion reflecting consumption smoothing possibilities of low-income households clearly depicts that climate risks can be particularly high as a consequence of poverty and therefore recommend that context-specific vulnerabilities and equity concerns in climate risk studies should be included when making assessments for least developed countries.
Wider applications of climate services within the management of climate risks face significant challenges. This paper presents a forecasting approach, to assess the development trends in climate ...service needs and thereby potential demand in key sectors that are essential to the green solution and will face a general growth in activity and key climate vulnerabilities towards 2050. These sectors are renewable energy, international climate finance, and cities. The geographical scope focuses on Europe, but global trends are included. We here suggest scenarios for growth in future climate services based on baseline development trends and policy scenarios reflecting future low-emission and SDG targets. Barriers and specific needs for climate service development within these sectors are discussed, and alignment of supply and demand within the climate service market is particularly emphasized. We find that several complexities influence the climate service market, including policy frameworks aimed at facilitating climate risk management as well as a lack of fit between the supply and demand sides of the market. Other barriers include uncertainties related to available climate information and socioeconomic climate risk information. Based on the forecasting, we find that substantial benefits can be seen with increased climate service development and deployment across the three sectors.
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