Top PDF Impacts of +2°C global warming on winter tourism demand in Europe

Impacts of +2°C global warming on winter tourism demand in Europe

Impacts of +2°C global warming on winter tourism demand in Europe

Tourism is one of the most weather-sensitive sectors. Hence, a deep understanding of the impacts and risks that weather variabil- ity poses to this sector is important for the effective design of con- temporary economic policies and risk management strategies, as well as for the assessment of potential economic impacts of future climate change (Prettenthaler et al., 2016). With ‘Weather Value at Risk’ or just ‘Weather-VaR’, Toeglhofer et al. (2012) introduced a simple concept for measuring economic risks related to weather fluctuations. Prettenthaler et al. (2016) extended the concept of Weather-VaR to describe and compare sectoral income risks from climate change, using the examples of wheat cultivation and sum- mer tourism in (parts of) Sardinia. In this study, we apply the Weather-VaR concept for the first time at the international level, using the example of alpine winter tourism. Considering major ski- ing intensive tourism regions in Europe, we compare the weather- induced risk of losses in overnight stays and potential changes under 2 °C global warming. Using time series regression models, we estimate the sensitivity of winter overnight stays towards snow conditions on a monthly basis and at the NUTS-3 level. Taking the regression model results and the distribution of historical and pro- jected snow data stemming from the hydrological model VIC (Liang et al., 1994), we quantify the risk of tourism demand losses due to weather variability and assess the potential impacts of cli- mate change. As the concept of Weather-VaR is capable of captur- ing both a climate-induced change in the mean and in the variability of tourism demand, this indicator could help businesses to adequately quantify their weather risks and provides an appro- priate decision criterion for climate proof investments.
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Projections of future floods and hydrological droughts in Europe under a +2°C global warming

Projections of future floods and hydrological droughts in Europe under a +2°C global warming

516 Figure 5: summary of the impacts of extreme discharge (return period is 10 years) under a +2C warming. Green area means 517 that (i) QRP10 change < -5%, (ii) QRPlow10 change> +5% and (iii) QRPlow10 duration change <-5%. We show here only pixels

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Climate change alters low flows in Europe under global warming of 1 5, 2, and 3 °C

Climate change alters low flows in Europe under global warming of 1 5, 2, and 3 °C

for the Mediterranean ( − 16 %). Overall, half of the simu- lations show robust changes over Europe with large regional differences. Likely changes are found in the south-west of Europe, northern Norway, and the Balkans. It is worth em- phasizing that the differences between global warming of 2 and 3 K in low flows are substantial. These changes are on top of those projected between 1971 and 2000 and a 2 K warming, where already 70 % of the simulations show sig- nificant changes (Fig. 5d). As a result, the increase in low flows in the Alpine and Northern regions could, in combina- tion with increased future annual precipitation in the GCMs (see Fig. 4), lead to higher hydropower potential. Conversely, a further decrease in available water (in low flows as well as annual precipitation) in the Mediterranean may pose addi- tional water stress in that area. Although human influences such as reservoir management and human water demand are not considered in this study, different regional adaptation op- tions should be considered depending on whether the world warms 2 or 3 K. This also holds true for the more pronounced warming between 1.5 and 3 K (Fig. 5e and f), where the re- gional changes in low flows as well as the robustness amplify compared to 2 and 3 K warming. These results also highlight the non-linear sensitivity of changes in low flows to different levels of global warming. For example with long-lasting in- frastructure or long planning horizons, adaptation strategies should be put in place now whether or not the 3 K level is reached.
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Euro-Atlantic winter storminess and precipitation extremes under 1.5 °C vs. 2 °C warming scenarios

Euro-Atlantic winter storminess and precipitation extremes under 1.5 °C vs. 2 °C warming scenarios

Projected climate change impacts on the mean climate state and on extreme weather are investigated based on model simulations with CAM5.1.2 (hereafter CAM5.1.2_0.25) at the highest available ∼ 0.25 ◦ horizontal resolution. The sim- ulations are part of the HAPPI experiment (Mitchell et al., 2017). The project is designed to provide model output data describing climate and weather changes under 1.5 and 2C levels of global warming, as compared to preindus- trial conditions (1861–1880). The design of HAPPI (Mitchell et al., 2017) provides three time slice experiments, using atmosphere-only models, to create large ensembles of 10- year simulations for the present climate (2006–2015) and potential future climate under 1.5 and 2C levels of warm- ing (2106–2115). The two future run ensembles will here- after be referred to + 1.5 and + 2C, respectively. Observed forcing conditions include SSTs and sea ice (Taylor et al., 2012). SSTs in future scenarios are prescribed by summation of the observed 2006–2015 SSTs and an offset estimated be- tween decadal averages of the 2006–2015 period and the pro- jected warmer global conditions for the 2091–2100 period. The 2006–2015 runs use 2006–2015 values for all forcings (GHGs, nonvolcanic aerosols, ozone, volcanic aerosol, so- lar), except land cover (set at 1850). Representative Concen- tration Pathway 2.6 (RCP2.6, year 2095) is used to provide the model boundary conditions, including atmospheric GHG concentrations, aerosols, ozone, land use and land cover for the 1.5 ◦ C scenario. For the 2C scenario these conditions are the same, except the CO 2 concentration, which is set to a
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Projections of global warming-induced impacts on winter storm losses in the German private household sector

Projections of global warming-induced impacts on winter storm losses in the German private household sector

1 Introduction Winter storms represent one of the major natural hazards. Based on three decades of data (1982–2011) from the EM-DAT 1 database (e.g. Guha-Sapir et al. 2012 ) extratropical storms account for a world-wide average of annual economic loss of USD 10.7 bn in 2011 prices. According to Kron et al. ( 2012 ), the cumulative world-wide losses 1980–2012 amount for USD 178 bn (2012 prices). For Europe, current estimates for a single 10-year event reach USD 7 bn (2006 prices), increasing up to USD 30 bn for events with a return level of once per 100 years (Schwierz et al. 2010 ). Changes in winter storm statistics related to global warming have been studied in several investigations, in particular referring to the Euro-Atlantic area (e.g. Ulbrich et al. 2009 ). Additionally, several studies indicate that losses from winter storms may increase in future decades over Western Europe (e.g. Donat et al. 2011a ; Leckebusch et al. 2007 ; Pinto et al. 2012 ; Schwierz et al. 2010 ). Hence, winter storms clearly have the potential for a relevant global warming impact category. Further, the international debate on an adequate climate policy is shifting from a mitigation-oriented focus towards a broader perspective including more of the impact and adaptation side. 2 With this aim, we suggest a new methodological
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Differential impacts of ocean acidification and warming on winter and summer progeny of a coastal squid (Loligo vulgaris)

Differential impacts of ocean acidification and warming on winter and summer progeny of a coastal squid (Loligo vulgaris)

effects on the survival, growth, calcification and physiology of cephalopods (Gutowska et al., 2008; Hu et al., 2011; Kaplan et al., 2013; Rosa and Seibel, 2008; Rosa et al., 2013c). Concomitantly, average global sea surface temperatures are expected to increase by up to 3°C by 2100 (Meehl et al., 2007), a scenario that will likely drive profound impacts on the ecophysiology (Donelson et al., 2011; Munday et al., 2009; Pörtner and Knust, 2007; Rosa and Seibel, 2008) and, consequently, the biogeography of marine biota (Perry et al., 2005; Somero, 2005). Coastal marine ecosystems are warming at a higher rate than most other ecosystems (MacKenzie and Schiedek, 2007). As several coastal organisms already live close to their thermal tolerance limits (Helmuth et al., 2006; Stillman and Somero, 2000), ocean warming is expected to negatively impact their performance and survival. The metabolism of marine ectotherms is constrained by oxygen supply at high (and low) temperatures with a progressive transition to an anaerobic mode of energy production [the ‘oxygen and capacity limitation of thermal tolerance’ concept (Pörtner and Knust, 2007)]. The reduction in aerobic scope is not caused by lower levels of ambient oxygen but rather through the limited capacity of oxygen supply mechanisms (ventilatory and circulatory systems) to meet an animal’s temperature-dependent oxygen demand. These patterns may be influenced by rising CO 2 levels. In fact, hypercapnia is known to
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Global warming and windstorm impacts in the EU

Global warming and windstorm impacts in the EU

baseline (1981-2010) climate with those under global warming levels (GWLs) of 1.5, 2 and 3°C above preindustrial levels. We evaluated wind impacts under GWLs on today’s society (static economic analysis) as well as on Europe in 2050 and 2100 for the EU Reference economic scenario (2015 Ageing Report projections. This allows understanding windstorm risk if climate conditions under different levels of warming would be imposed on today’s society, without any assumptions on socioeconomic developments over long time spans. In addition, we also assess the impacts at different warming levels on society in 2050 and 2100 for the EU Reference socioeconomic scenario (2015 Ageing Report projections). Comparison of the static and dynamic economic analyses allows disentangling the effects of climate and socioeconomic changes. The vulnerability derived from recent windstorm events is assumed constant in the projections, hence the results presented do not include any additional adaptation of sectors to changing maximum wind speed conditions. Our hazard analysis includes all EU member states plus a number of neighbouring countries (Iceland, Norway, and Switzerland and Balkan countries). Economic impacts are presented for EU countries and the UK. More details on the methodology can be found in Annex 1.
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The impacts of sea-level rise on European coasts in a 2°C world. Results and analysis of task 6.5 prepared as part of IMPACT2C: quantifying project impacts under 2°C warming

The impacts of sea-level rise on European coasts in a 2°C world. Results and analysis of task 6.5 prepared as part of IMPACT2C: quantifying project impacts under 2°C warming

Impacts also depend on the level of adaptation. Many European countries are aware of the impacts of coastal climate change (e.g. Tol et al. 2008; Eurobarometer 2009), so engineer and adapt their shorelines. Due to data resolution and computation power, it is not possible to model all types of coastal adaptation. DIVA evaluates the building of sea and river dikes to reduce the risk of flooding (following Hoozemans et al. 1993) and beach/shore nourishment to reduce erosion (Hinkel et al. 2013). For the former, as there is no empirical data on actual dike heights available at a global level, a demand for safety is computed and assumed to be provided by dikes (Tol, 2006; Tol and Yohe, 2007), which changes as sea-levels rise. As a full cost-benefit is computationally too expensive, a demand for safety function was developed, where, as population density increases there is a greater level or protection. There are no dikes where there is very low population density (< 1 person/km 2 ). Half of the demand for safety is applied at a population density of 20 persons/km 2 , and 90% at a population density of 200 persons/km 2 . This is akin to providing isolated dikes around individual settlements at lower population densities, to more continuous dikes at higher population densities. Maintenance costs of sea dikes are projected at 1% of their capital costs (Nicholls et al. 2010). In beach nourishment, the sand is placed directly on the intertidal beach, while in shore nourishment the sand is placed below low tide where the sand will progressively feed onshore due to wave action, following current Dutch practice (van Koningsveld et al., 2008). Shore nourishment is substantially cheaper than beach nourishment, but the benefits are not felt immediately.
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Assessing the impacts of 1.5 °C global warming – simulation protocol of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b)

Assessing the impacts of 1.5 °C global warming – simulation protocol of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b)

the pre-industrial period. This severely restricts the opportu- nities to gain a better understanding of climate-change im- pacts already unfolding and the options to address ques- tions associated with the “detection and attribution” of his- torical impacts in the context of the “loss and damage” de- bate (James et al., 2014). In the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5), an entire chapter is dedicated to the detection and attribution of observed climate-change impacts (Cramer et al., 2014). However, the conclusions that can be drawn are limited by (1) the lack of long-term and homogeneous ob- servational data, and (2) the confounding influence of other drivers such as population growth and management changes (e.g. expansion of agriculture in response to growing food demand, changes in irrigation water withdrawal, building of dams and reservoirs, changes in fertilizer input, and switch- ing to other crop varieties) on climate-impact indicators such as river discharge, crop yields, and energy demand, etc. For the historical period these other influences may also com- prise known natural disturbances such as wildfires, outbreaks of diseases, and pests, etc. that could be considered as ex- ternal drivers in part of the models. However, for simplicity we refer to the entire group of external drivers as “socio- economic conditions” throughout the paper. Over the his- torical period, these influences have evolved simultaneously with climate, rendering the quantification of the pure climate- change signal difficult. Model simulations could help to fill these gaps and could become essential tools to sep- arate the effects of climate change from other historical drivers. To address these challenges, the ISIMIP2b protocol includes (1) a multi-centennial pre-industrial reference sim- ulation (picontrol + fixed pre-industrial socio-economic con- ditions (1860soc), 1660–1860), (2) historical simulations ac- counting for varying
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Mean and extreme climate in Europe under 1.5, 2, and 3°C global warming

Mean and extreme climate in Europe under 1.5, 2, and 3°C global warming

3.2 Indices of extreme temperature Under global warming, the temperature Probability Distribution Function (PDF) of temperature is expected to change, with an increase of the mean value and broadening of its width (increase of variability). This results in an increased probability of extreme events (Fischer & Schär, 2010; Schär et al., 2004). However, the tail of the PDF (i.e., hot and cold extremes) can change, at increasing levels of warming, differently than the mean value. Figure 4 shows the change of selected temperature indices under different warming levels; Figure 5 shows the fraction of land where this change is either robust or non-significant, for NEU and SEU in both winter and summer. TXx, TXn, TNx, and TNn are a measure of hot and cold extreme temperature events, whereas the number of frost days and tropical nights are examples of threshold-based indices that may be relevant for impact assessment studies.
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Assessing the impacts of 1 5 °C global warming–simulation protocol of the Inter Sectoral Impact Model Intercomparison Project (ISIMIP2b)

Assessing the impacts of 1 5 °C global warming–simulation protocol of the Inter Sectoral Impact Model Intercomparison Project (ISIMIP2b)

the pre-industrial period. This severely restricts the opportu- nities to gain a better understanding of climate-change im- pacts already unfolding and the options to address ques- tions associated with the “detection and attribution” of his- torical impacts in the context of the “loss and damage” de- bate (James et al., 2014). In the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5), an entire chapter is dedicated to the detection and attribution of observed climate-change impacts (Cramer et al., 2014). However, the conclusions that can be drawn are limited by (1) the lack of long-term and homogeneous ob- servational data, and (2) the confounding influence of other drivers such as population growth and management changes (e.g. expansion of agriculture in response to growing food demand, changes in irrigation water withdrawal, building of dams and reservoirs, changes in fertilizer input, and switch- ing to other crop varieties) on climate-impact indicators such as river discharge, crop yields, and energy demand, etc. For the historical period these other influences may also com- prise known natural disturbances such as wildfires, outbreaks of diseases, and pests, etc. that could be considered as ex- ternal drivers in part of the models. However, for simplicity we refer to the entire group of external drivers as “socio- economic conditions” throughout the paper. Over the his- torical period, these influences have evolved simultaneously with climate, rendering the quantification of the pure climate- change signal difficult. Model simulations could help to fill these gaps and could become essential tools to sep- arate the effects of climate change from other historical drivers. To address these challenges, the ISIMIP2b protocol includes (1) a multi-centennial pre-industrial reference sim- ulation (picontrol + fixed pre-industrial socio-economic con- ditions (1860soc), 1660–1860), (2) historical simulations ac- counting for varying
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International tourism demand to Finnish Lapland in the early winter season

International tourism demand to Finnish Lapland in the early winter season

3. Empirical model The tourism demand model predicts that the number of visitors depends positively on real income and negatively on prices (Lim, 1997; Song, Witt, & Li, 2009). Cortés-Jiménez and Blake (2011). Lim and Zhu (2017) suggest that the determinants of tourism demand vary widely by nationality, since different tourists from different visitor countries are expected to respond differently to changes in relative prices and real income. In addition to income of the visitor countries and relative prices, natural snow supply is generally considered as an important factor of winter tourism demand (Falk, 2010, 2013; Töglhofer et al., 2011; Damm et al., 2017). These studies find a positive relationship between snow conditions and overnight stays, although the magnitude of this relationship is rather low. A previous study on skiing demand for ski resorts in Finnish Lapland shows that skier visits depend on natural snow depth in the ski area (Falk & Vieru, 2017a). However, again the magnitude of the relationship is rather low. Few studies distinguish winter tourism demand by country of residence. An exception is Falk (2013), whose study is based on Austrian village data that finds that overnight stays of domestic visitors are sensitive to changes in snow conditions, whereas there is no relationship between foreign overnight stays and snow conditions.
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APPETITE FOR CHANGE GLOBAL WARMING IMPACTS ON FOOD AND FARMING REGIONS IN AUSTRALIA

APPETITE FOR CHANGE GLOBAL WARMING IMPACTS ON FOOD AND FARMING REGIONS IN AUSTRALIA

Maize, better known as corn, is one of the big three global cereal crops along with wheat and rice. Higher temperature may increase maize yields in temperate areas but reduce them in many tropical areas where temperatures exceed 35°C. In Australia more than half of total production comes from rain- fed agriculture, where yields are highly variable and increasingly affected by drought and extreme heat. Likewise, irrigated maize faces increasing competition for water. Further development of varieties and management techniques might help reduce future yield losses but only if they take into account likely future climate conditions.
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Global warming and ocean stratification: a potential result of large extraterrestrial impacts

Global warming and ocean stratification: a potential result of large extraterrestrial impacts

Over land, crocodylomorphs (a group including crocodilians), chelonians (the order containing turtles), and champsosaurs with representatives in shallow marine and freshwater habitats seem to have survived better than other large bodied fauna [Benton, 1993; MacLeod et al., 1997; Martin et al., 2014]. Large rivers might have been somewhat insulated from terrestrial temperature changes and fires, while estuarine areas might not Figure 3. (a) Minimum annually averaged temperature change over land (K), between years 0 and 10 after a simulated impact calculated using several hundred simulations of the EBM showing the combined effect of aerosol and SWV RF 8 . The abscissa shows the most negative aerosol RF (W m 2 ), and the ordinate shows the maximum value of SWV RF (W m 2 ), in each individual EBM run. (b) As in Figure 3a but for the maximum annually averaged ocean mixed layer temperature response (K). FAMOUS ensembles M2, M2D, M3, and M3D are marked in grey in positions corresponding to their initial radiative forcings for comparison.
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Impacts of Dams and Global Warming on Fish Biodiversity in the Indo-Burma Hotspot

Impacts of Dams and Global Warming on Fish Biodiversity in the Indo-Burma Hotspot

MAXENT version 3.3.3k was applied to occurrence data for each of the 365 fish species in the Indo-Burma Region that were included within our database. We trained species occurrence models using 14 layers of environmental factors anticipated to have a direct or indirect influ- ence on fishes ( Fig 2B–2O ). We then substituted them with layers that reflected changed condi- tions (e.g. higher annual mean temperatures) under different scenarios of dam construction and global warming in order to predict how species distributions would shift in response to future conditions. Of the 14 layers, altitude [ 41 ] and slope are basic topographic factors corre- lated with other environmental variables such as water temperature, water velocity, substrates size of stream beds, and discharge volume. The topographic wetness index is known to be accu- rate and correlated with floodplain extent [ 42 – 44 ], which constitutes important habitat for fishes [ 13 ], while distance from the sea was included to captures aspects of fish longitudinal zonation along rivers, especially the distribution of brackish species correlated with salinity [ 45 ]. The Global Human Influence Index v2 [ 46 ] was used as a composite measure of human impact. Ecoregional identity [ 47 – 48 ] was included to discriminate geographical assemblages of fishes. These six layers ( Fig 2B–2G ) were fixed in all projections made under different scenarios in MAXENT analysis. In contrast, layers related to dam construction–i.e. fragment areas (i.e. the extent of individual fragments within drainages upstream of each dam), and the number of ecoregions within each fragment [ 22 ]–changed under different dam and global warming pro-
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Impacts of climate change and climate extremes on major crops productivity in China at a global warming of 1.5 and 2.0 °C

Impacts of climate change and climate extremes on major crops productivity in China at a global warming of 1.5 and 2.0 °C

In the past decades, global warming has markedly shifted the spatio-temporal patterns of temperature and precipitation (Gourdji et al., 2013; Liu and Allan, 2013). Moreover, the warming trend is expected to go on in the following decades with the increase in greenhouse gas emissions (Zhao et al., 2017), especially in cultivated areas (Lobell et al., 2011). The effects of climate changes and climate extreme on the growth and yields of crops have been of great concern (Porter et al., 2014; Asseng et al., 2015). Researchers have extensively demonstrated crop responses to climate factors through con- ducting environment-controlled experiments (e.g. Ottman et al., 2012; Chen et al., 2016), analysing historical records (e.g. Lobell et al., 2011; Tao et al., 2012, 2014) and carrying out crop model simulations (Porter et al., 2014; Asseng et al., 2015). These studies have documented that increasing tem- perature could shorten crop growth duration and reduce crop yields across a wide area (Porter et al., 2014). Meanwhile, with climate warming, the frequency and intensity of climate extreme events, for example heat stress, are projected to in- crease and substantially threaten crop growth and food se- curity, especially for some susceptible areas (Wahid et al., 2007; Asseng et al., 2011; Gourdji et al., 2013). Beside the negative impacts, the warmer environment could also im- prove crop production in some areas that suffer from a heat deficit (Tao et al., 2008a, 2012, 2014; Zhang et al., 2014). In addition, elevated CO 2 concentration could inhibit stom-
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What will global annual emissions of greenhouse gases be in 2030, and will they be consistent with avoiding global warming of more than 2 C?

What will global annual emissions of greenhouse gases be in 2030, and will they be consistent with avoiding global warming of more than 2 C?

international goal of limiting the rise in global mean surface temperature to no more than 2°C, even though they represent measurable progress, if delivered, relative to a ‘business as usual’ emissions pathway. Our preliminary analysis projects that the European Union, United States and China, together currently representing 2.2 billion of the global population of 7.2 billion, would collectively emit about 21 Gt CO 2 e in 2030, even if China succeeds in reaching a peak in emissions in 2025. Published model projections that are consistent with a 50-66% chance of limiting global warming to less than 2°C suggest that global annual emissions should be no more than 35 to 50 Gt CO 2 e in 2030, even assuming significant net negative carbon dioxide emissions from energy use during the 21 st century. Based on current and planned policies as of late 2014, the rest of the world would collectively emit 35.4 Gt CO 2 e in 2030, meaning global emissions would be 57 to 59 Gt CO 2 e in 2030. While it is hoped that countries will include more ambitious plans for emissions reductions in their submissions of INDCs to the UNFCCC secretariat, it seems likely that there will still be a significant gap between aggregate national intentions and a pathway that is consistent with avoiding global warming of more than 2°C. Indeed, there is likely to be a very significant gap between aggregate national intentions and the projected model pathways that are lowest risk (i.e. do not depend on net negative carbon dioxide emissions during the latter half of the 21 st century), which indicate that global annual emissions in 2030 would need to be between 32 and 44 Gt CO 2 e.
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A comparison of changes in river runoff from multiple global and catchment-scale hydrological models under global warming scenarios of 1 °C, 2 °C and 3 °C

A comparison of changes in river runoff from multiple global and catchment-scale hydrological models under global warming scenarios of 1 °C, 2 °C and 3 °C

Some catchments show a clear trend in their response to increases in global warming, with large differences between 2 and 3 °C that are consistent across both ensembles, as well as significant changes in hydrological indicators from present-day (assessed by a paired-samples t-test between the ensemble projections for each magnitude of global warming and the present- day simulations; Fig. 1 ). Examples include the Rhine, where there is an increased risk of decreases in low flows, with the median Q95 change escalating from around −11 % at 2 °C to −23 % at 3 °C (the change relative to present-day at 3 °C is statistically significant for both ensembles for Q95, p < 0.05). The risk of increases in high flows increases for the Lena, where the change in median Q5 intensifies from around +17 % (2 °C) to +26 % (3 °C), with a similar magnitude increase in MAR also (the changes are statistically significant for both ensembles at all magnitudes of global warming for all hydrological indicators, p < 0.05). The Tagus experiences declines in MAR and an enhanced risk of decreases in low flows, with changes in both MAR and Q95 of around −20 % at 2 °C, and then declining even further to around −40 % at 3 °C (the changes relative to present-day at 2 and 3 °C are statistically significant for both ensembles for MAR and Q95, p < 0.05). On the other hand, the Upper Mississippi and Upper Niger experience relatively small changes in the medians of hydrological indicators between 2 and 3 °C and the magnitude of changes relative to present are infrequently statistically significant.
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Climate Suitability and Vulnerability of Winter Wheat Planting in Gansu under the Background of Global Warming

Climate Suitability and Vulnerability of Winter Wheat Planting in Gansu under the Background of Global Warming

Applying the MaxEnt model to study the climate suitability of winter wheat planting distribution in Gansu, we must first test the applicability of the MaxEnt model. Here, the model input data includes two categories: one is the geograph- ical distribution data of the target, using the geographical distribution data of 40 winter wheat agrometeorological observation stations (showing in Figure 1) in the winter wheat growing area of Gansu; the second is the environmental varia- ble, according to the period from 1961 to 1990. Grid daily climate data (10 km resolution), calculated by Arcgis software to 6 climatic factors, including annual total radiation, annual precipitation, warmest monthly average temperature, coldest monthly average temperature, annual average temperature, annual ex- treme minimum temperature the 30-year average during the base period (1961-1990) was used as an environmental input variable for constructing a dis- tribution-climate relationship model for winter wheat planting. Import the two types of data into the MaxEnt model and set the relevant parameters to run.
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Global impacts of energy demand on the freshwater resources of nations

Global impacts of energy demand on the freshwater resources of nations

Findings in the present study can be placed within an emerging body of literature that suggests an imbalance in the use of natural resources (29, 30, 65–67) with exchanges between developed and less-developed countries having become increasingly ecologically unequal. The analysis of virtual freshwater transfers to affluent eastern provinces of China from other provinces in ref. 60 highlights that such an imbalance in resource use can also occur within countries. To address such transfers, ref. 60 suggests a number of policy mechanisms based on shared producer and consumer responsibility (68) that could be implemented and used to fund agricultural and industrial freshwater efficiency programs. In the context of findings in the present study, we would suggest that such mechanisms could also be used at the global level to ensure both the security of energy supply in areas where final demand lies and to address social, economic, and environmental issues where freshwater consumption to meet this demand originates. Ultimately, as argued by refs. 25 and 69, the analysis presented here provides information that can be used by policy makers to identify critical sectors and geographic regions at the water–energy nexus. When developing energy policy, deci- sions can then be made to invest in protecting these critical points to reduce social, environmental, and economic burdens. For ex- ample, in the 1970s, the government of Saudi Arabia identified threats to territorial freshwater resources as a major issue for the oil industry, such that the industry is now based almost entirely on the use of desalination technology and brackish water (70), a fact reflected in our analysis which finds comparatively low freshwater consumption in this region. Our analysis provides information that could enable transfer of resources between countries to en- able similar sectorial changes to protect freshwater resources and ensure security of the energy supply.
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