2012, Keys, P.W., van der Ent, R.J., Gordon, L.J., Hoff, H., Nikoli, R., Savenije, H.H.G.

It is well known that rivers connect upstream and downstream ecosystems within watersheds. Here we describe the concept of precipitationsheds to show how upwind terrestrial evaporation source areas contribute moisture for precipitation to downwind sink regions. We illustrate the importance of upwind land cover in precipitationsheds to sustain precipitation in critically water stressed downwind areas, specifically dryland agricultural areas. We first identify seven regions where rainfed agriculture is particularly vulnerable to reductions in precipitation, and then map their precipitationsheds. We then develop a framework for qualitatively assessing the vulnerability of precipitation for these seven agricultural regions. We illustrate that the sink regions have varying degrees of vulnerability to changes in upwind evaporation rates depending on the extent of the precipitationshed, source region land use intensity and expected land cover changes in the source region.

2015, Rolinski, S., Rammig, A., Walz, A., von Bloh, W., van Oijen, M., Thonicke, K.

Extreme weather events are likely to occur more often under climate change and the resulting effects on ecosystems could lead to a further acceleration of climate change. But not all extreme weather events lead to extreme ecosystem response. Here, we focus on hazardous ecosystem behaviour and identify coinciding weather conditions. We use a simple probabilistic risk assessment based on time series of ecosystem behaviour and climate conditions. Given the risk assessment terminology, vulnerability and risk for the previously defined hazard are estimated on the basis of observed hazardous ecosystem behaviour. We apply this approach to extreme responses of terrestrial ecosystems to drought, defining the hazard as a negative net biome productivity over a 12-month period. We show an application for two selected sites using data for 1981–2010 and then apply the method to the pan-European scale for the same period, based on numerical modelling results (LPJmL for ecosystem behaviour; ERA-Interim data for climate). Our site-specific results demonstrate the applicability of the proposed method, using the SPEI to describe the climate condition. The site in Spain provides an example of vulnerability to drought because the expected value of the SPEI is 0.4 lower for hazardous than for non-hazardous ecosystem behaviour. In northern Germany, on the contrary, the site is not vulnerable to drought because the SPEI expectation values imply wetter conditions in the hazard case than in the non-hazard case. At the pan-European scale, ecosystem vulnerability to drought is calculated in the Mediterranean and temperate region, whereas Scandinavian ecosystems are vulnerable under conditions without water shortages. These first model-based applications indicate the conceptual advantages of the proposed method by focusing on the identification of critical weather conditions for which we observe hazardous ecosystem behaviour in the analysed data set. Application of the method to empirical time series and to future climate would be important next steps to test the approach.

2016, Bren d'Amour, Christopher, Wenz, Leonie, Kalkuhl, Matthias, Steckel, Jan Christoph, Creutzig, Felix

The 2008–2010 food crisis might have been a harbinger of fundamental climate-induced food crises with geopolitical implications. Heat-wave-induced yield losses in Russia and resulting export restrictions led to increases in market prices for wheat across the Middle East, likely contributing to the Arab Spring. With ongoing climate change, temperatures and temperature variability will rise, leading to higher uncertainty in yields for major nutritional crops. Here we investigate which countries are most vulnerable to teleconnected supply-shocks, i.e. where diets strongly rely on the import of wheat, maize, or rice, and where a large share of the population is living in poverty. We find that the Middle East is most sensitive to teleconnected supply shocks in wheat, Central America to supply shocks in maize, and Western Africa to supply shocks in rice. Weighing with poverty levels, Sub-Saharan Africa is most affected. Altogether, a simultaneous 10% reduction in exports of wheat, rice, and maize would reduce caloric intake of 55 million people living in poverty by about 5%. Export bans in major producing regions would put up to 200 million people below the poverty line at risk, 90% of which live in Sub-Saharan Africa. Our results suggest that a region-specific combination of national increases in agricultural productivity and diversification of trade partners and diets can effectively decrease future food security risks.

2016, Geiger, Tobias, Frieler, Katja, Levermann, Anders

Damage due to tropical cyclones accounts for more than 50% of all meteorologically-induced economic losses worldwide. Their nominal impact is projected to increase substantially as the exposed population grows, per capita income increases, and anthropogenic climate change manifests. So far, historical losses due to tropical cyclones have been found to increase less than linearly with a nation's affected gross domestic product (GDP). Here we show that for the United States this scaling is caused by a sub-linear increase with affected population while relative losses scale super-linearly with per capita income. The finding is robust across a multitude of empirically derived damage models that link the storm's wind speed, exposed population, and per capita GDP to reported losses. The separation of both socio-economic predictors strongly affects the projection of potential future hurricane losses. Separating the effects of growth in population and per-capita income, per hurricane losses with respect to national GDP are projected to triple by the end of the century under unmitigated climate change, while they are estimated to decrease slightly without the separation.

2012, Schneider von Deimling, T., Meinshausen, M., Levermann, A., Huber, V., Frieler, K., Lawrence, D.M., Brovkin, V.

Thawing of permafrost and the associated release of carbon constitutes a positive feedback in the climate system, elevating the effect of anthropogenic GHG emissions on global-mean temperatures. Multiple factors have hindered the quantification of this feedback, which was not included in climate carbon-cycle models which participated in recent model intercomparisons (such as the Coupled Carbon Cycle Climate Model Intercomparison Project – C4MIP) . There are considerable uncertainties in the rate and extent of permafrost thaw, the hydrological and vegetation response to permafrost thaw, the decomposition timescales of freshly thawed organic material, the proportion of soil carbon that might be emitted as carbon dioxide via aerobic decomposition or as methane via anaerobic decomposition, and in the magnitude of the high latitude amplification of global warming that will drive permafrost degradation. Additionally, there are extensive and poorly characterized regional heterogeneities in soil properties, carbon content, and hydrology. Here, we couple a new permafrost module to a reduced complexity carbon-cycle climate model, which allows us to perform a large ensemble of simulations. The ensemble is designed to span the uncertainties listed above and thereby the results provide an estimate of the potential strength of the feedback from newly thawed permafrost carbon. For the high CO2 concentration scenario (RCP8.5), 33–114 GtC (giga tons of Carbon) are released by 2100 (68 % uncertainty range). This leads to an additional warming of 0.04–0.23 °C. Though projected 21st century permafrost carbon emissions are relatively modest, ongoing permafrost thaw and slow but steady soil carbon decomposition means that, by 2300, about half of the potentially vulnerable permafrost carbon stock in the upper 3 m of soil layer (600–1000 GtC) could be released as CO2, with an extra 1–4 % being released as methane. Our results also suggest that mitigation action in line with the lower scenario RCP3-PD could contain Arctic temperature increase sufficiently that thawing of the permafrost area is limited to 9–23 % and the permafrost-carbon induced temperature increase does not exceed 0.04–0.16 °C by 2300.

2016, Ruane, Alex C., Teichmann, Claas, Arnell, Nigel W., Carter, Timothy R., Ebi, Kristie L., Frieler, Katja, Goodess, Clare M., Hewitson, Bruce, Horton, Radley, Kovats, R. Sari, Lotze, Heike K., Mearns, Linda O., Navarra, Antonio, Ojima, Dennis S., Riahi, Keywan, Rosenzweig, Cynthia, Themessl, Matthias, Vincent, Katharine

This paper describes the motivation for the creation of the Vulnerability, Impacts, Adaptation and Climate Services (VIACS) Advisory Board for the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), its initial activities, and its plans to serve as a bridge between climate change applications experts and climate modelers. The climate change application community comprises researchers and other specialists who use climate information (alongside socioeconomic and other environmental information) to analyze vulnerability, impacts, and adaptation of natural systems and society in relation to past, ongoing, and projected future climate change. Much of this activity is directed toward the co-development of information needed by decision-makers for managing projected risks. CMIP6 provides a unique opportunity to facilitate a two-way dialog between climate modelers and VIACS experts who are looking to apply CMIP6 results for a wide array of research and climate services objectives. The VIACS Advisory Board convenes leaders of major impact sectors, international programs, and climate services to solicit community feedback that increases the applications relevance of the CMIP6-Endorsed Model Intercomparison Projects (MIPs). As an illustration of its potential, the VIACS community provided CMIP6 leadership with a list of prioritized climate model variables and MIP experiments of the greatest interest to the climate model applications community, indicating the applicability and societal relevance of climate model simulation outputs. The VIACS Advisory Board also recommended an impacts version of Obs4MIPs and indicated user needs for the gridding and processing of model output.

2017, Geiger, Tobias, Frieler, Katja, Levermann, Anders

Recently a multitude of empirically derived damage models have been applied to project future tropical cyclone (TC) losses for the United States. In their study (Geiger et al 2016 Environ. Res. Lett. 11 084012) compared two approaches that differ in the scaling of losses with socio-economic drivers: the commonly-used approach resulting in a sub-linear scaling of historical TC losses with a nation's affected gross domestic product (GDP), and the disentangled approach that shows a sub-linear increase with affected population and a super-linear scaling of relative losses with per capita income. Statistics cannot determine which approach is preferable but since process understanding demands that there is a dependence of the loss on both GDP per capita and population, an approach that accounts for both separately is preferable to one which assumes a specific relation between the two dependencies. In the accompanying comment, Rybski et al argued that there is no rigorous evidence to reach the conclusion that high-income does not protect against hurricane losses. Here we affirm that our conclusion is drawn correctly and reply to further remarks raised in the comment, highlighting the adequateness of our approach but also the potential for future extension of our research.

2017, Baumbach, Lukas, Siegmund, Jonatan F., Mittermeier, Magdalena, Donner, Reik V.

Temperature is a key factor controlling plant growth and vitality in the temperate climates of the mid-latitudes like in vast parts of the European continent. Beyond the effect of average conditions, the timings and magnitudes of temperature extremes play a particularly crucial role, which needs to be better understood in the context of projected future rises in the frequency and/or intensity of such events. In this work, we employ event coincidence analysis (ECA) to quantify the likelihood of simultaneous occurrences of extremes in daytime land surface temperature anomalies (LSTAD) and the normalized difference vegetation index (NDVI). We perform this analysis for entire Europe based upon remote sensing data, differentiating between three periods corresponding to different stages of plant development during the growing season. In addition, we analyze the typical elevation and land cover type of the regions showing significantly large event coincidences rates to identify the most severely affected vegetation types. Our results reveal distinct spatio-temporal impact patterns in terms of extraordinarily large co-occurrence rates between several combinations of temperature and NDVI extremes. Croplands are among the most frequently affected land cover types, while elevation is found to have only a minor effect on the spatial distribution of corresponding extreme weather impacts. These findings provide important insights into the vulnerability of European terrestrial ecosystems to extreme temperature events and demonstrate how event-based statistics like ECA can provide a valuable perspective on environmental nexuses.

2013, Werg, J., Grothmann, T., Schmidt, P.

People are unequally affected by extreme weather events in terms of mortality, morbidity and financial losses; this is the case not only for developing, but also for industrialized countries. Previous research has established indicators for identifying who is particularly vulnerable and why, focusing on socio-demographic factors such as income, age, gender, health and minority status. However, these factors can only partly explain the large disparities in the extent to which people are affected by natural hazards. Moreover, these factors are usually not alterable in the short to medium term, which limits their usefulness for strategies of reducing social vulnerability and building social capacity. Based on a literature review and an expert survey, we propose an approach for refining assessments of social vulnerability and building social capacity by integrating psychological and governance factors.

2013, van Oijen, Marcel, Beer, Christian, Cramer, Wolfgang, Rammig, Anja, Reichstein, Markus, Rolinski, Susanne, Soussana, Jean-Francois

We present a simple method of probabilistic risk analysis for ecosystems. The only requirements are time series—modelled or measured—of environment and ecosystem variables. Risk is defined as the product of hazard probability and ecosystem vulnerability. Vulnerability is the expected difference in ecosystem performance between years with and without hazardous conditions. We show an application to drought risk for net primary productivity of coniferous forests across Europe, for both recent and future climatic conditions.