Climatic Change

Climatic variations within the dry valleys in southwestern China and the influences of artificial reservoirs Abstract Climatic variation within a typical dry-valley area located in the southern Hengduan Mountains of China is studied, and the potential regional climate influences of large reservoirs in the area are discussed. Six meteorological stations near a reservoir are identified and classified into two categories (dry and non-dry valleys) to compare their level of climate change. Temperatures tended to increase since 1990 with a precipitation shift toward the dry season in both dry and non-dry valleys. Wavelet analysis shows that temperature and precipitation have significant variation with periods of 3.6 and 16.5 years, respectively. The standardized precipitation evapotranspiration index (SPEI) shows that dry valleys have multiple drought trends. Temperature in non-dry valleys changed more than that in dry valleys, but the variations of other indices in the two categories of valleys are not statistically different. The climatic variation of one station is in accordance with the reservoir filling, which is related to the orientation of the reservoir in the prevailing wind direction especially during summer. This study provides a profile of the climate change of dry valleys and documents the influence of large artificial reservoirs on regional climate.

Addressing ambiguity in probabilistic assessments of future coastal flooding using possibility distributions Abstract Decision-making in the area of coastal adaptation is facing major challenges due to ambiguity (i.e., deep uncertainty) pertaining to the selection of a probability model for sea level rise (SLR) projections. Possibility distributions are mathematical tools that address this type of uncertainty since they bound all the plausible probability models that are consistent with the available data. In the present study, SLR uncertainties are represented by a possibility distribution constrained by likely ranges provided in the IPCC Fifth Assessment Report and by a review of high-end scenarios. On this basis, we propose a framework combining probabilities and possibilities to evaluate how SLR uncertainties accumulate with other sources of uncertainties, such as future greenhouse gas emissions, upper bounds of future sea level changes, the regional variability of sea level changes, the vertical ground motion, and the contributions of extremes and wave effects. We apply the framework to evaluate the probability of coastal flooding by the year 2100 at a local, low-lying coastal French urban area on the Mediterranean coast. We show that when adaptation is limited to maintaining current defenses, the level of ambiguity is too large to precisely assign a probability model to future flooding. Raising the coastal walls by 85 cm creates a safety margin that may not be considered sufficient by local stakeholders. A sensitivity analysis highlights the key role of deep uncertainties pertaining to global SLR and of the statistical uncertainty related to extremes. The ranking of uncertainties strongly depends on the decision-maker's attitude to risk (e.g., neutral, averse), which highlights the need for research combining advanced mathematical theories of uncertainties with decision analytics and social science.

Impacts of climate warming, cultivar shifts, and phenological dates on rice growth period length in China after correction for seasonal shift effects Abstract Crop phenology changes are important indicators of climate change. Climate change impacts on crop phenology are generally investigated through statistical analysis of the relationship between growth period length and growth period mean temperature. However, growth periods may be either earlier or later in a given year; hence, changes in mean temperature indicate both the effects of climate change and those attributable to seasonal temperature differences. Failure to consider temperature change resulting from seasonal shifts can lead to biased estimation of warming trends and their corresponding impact on phenology. We evaluated this potential bias in rice phenology change in 892 phenology series from China by applying time series regression control for phenological dates. The results indicate that the true magnitudes of climate change for early rice, late rice, and single rice are 0.20–0.56, 0.23–0.86, and 0.28–0.38 K/decade, after correction for the effects of seasonal shifts. The effects of seasonal shifts of growth periods led to underestimates of the magnitude of climate change by 0.16–0.22 and 0.05–0.08 K/decade for early rice and single rice, respectively, and an overestimate of the effect for late rice of 0.02–0.06 K/decade. Correspondingly, the net warming impacts on growth period length after correcting for the effects of seasonal shifts were − 2.7 d/K for early rice, − 4.8 d/K for late rice, and − 3.1 d/K for single rice, which were weaker for early and single rice, but stronger for late rice, relative to previous reports. Changes in growth period length were most closely associated with variation in phenological dates, while their relationship with climate change was less pronounced. Our results indicate that earlier phenological dates and prolonged-duration cultivars have been adopted to offset the impact of climate change, providing further evidence of active adaptation of rice cultivation practice to climate change in China.

Global warming to increase flood risk on European railways Abstract For effective disaster risk management and adaptation planning, a good understanding of current and projected flood risk is required. Recent advances in quantifying flood risk at the regional and global scale have largely neglected critical infrastructure, or addressed this important sector with insufficient detail. Here, we present the first European-wide assessment of current and future flood risk to railway tracks for different global warming scenarios using an infrastructure-specific damage model. We find that the present risk, measured as expected annual damage, to railway networks in Europe is approx. €581 million per year, with the highest risk relative to the length of the network in North Macedonia, Croatia, Norway, Portugal, and Germany. Based on an ensemble of climate projections for RCP8.5, we show that current risk to railway networks is projected to increase by 255% under a 1.5 °C, by 281% under a 2 °C, and by 310% under a 3 °C warming scenario. The largest increases in risk under a 3 °C scenario are projected for Slovakia, Austria, Slovenia, and Belgium. Our advances in the projection of flood risk to railway infrastructure are important given their criticality, and because losses to public infrastructure are usually not insured or even uninsurable in the private market. To cover the risk increase due to climate change, European member states would need to increase expenditure in transport by €1.22 billion annually under a 3 °C warming scenario without further adaptation. Limiting global warming to the 1.5 °C goal of the Paris Agreement would result in avoided losses of €317 million annually.

Substantial increase in minimum lake surface temperatures under climate change Abstract The annual minimum of lake surface water temperature influences ecological and biogeochemical processes, but variability and change in this extreme have not been investigated. Here, we analysed observational data from eight European lakes and investigated the changes in annual minimum surface water temperature. We found that between 1973 and 2014, the annual minimum lake surface temperature has increased at an average rate of + 0.35 °C decade−1, comparable to the rate of summer average lake surface temperature change during the same period (+ 0.32 °C decade−1). Coherent responses to climatic warming are observed between the increase in annual minimum lake surface temperature and the increase in winter air temperature variations. As a result of the rapid warming of annual minimum lake surface temperatures, some of the studied lakes no longer reach important minimum surface temperature thresholds that occur in winter, with complex and significant potential implications for lakes and the ecosystem services that they provide.

A multi-temporal analysis of streamflow using multiple CMIP5 GCMs in the Upper Ayerawaddy Basin, Myanmar Abstract In this study, bias-corrected daily rainfall data of eight global climate models (GCMs) was used as input for a hydrologic model (Hydrological Engineering Center - Hydrological Modeling System (HEC-HMS)) to simulate daily streamflow in the Upper Ayerawaddy River basin (UARB), Myanmar. Monthly, seasonal, annual, and decadal mean flows, calculated for the baseline (1975–2014), were compared with projections for future periods (2040s: 2021–2060 and 2080s: 2061–2100) under two Representative Concentration Pathways (RCP 4.5 and RCP 8.5). The spread of low flows (10th and 25th percentile of daily flows) and high flows (75th, 90th, and 100th percentiles) were analyzed for each period. The ensemble of GCMs indicates an increase in mean monthly (except in October and November), seasonal (except post-monsoon), annual, and decadal rainfalls and corresponding flows in the UARB. Future low flows are expected to have high variability while high flows are expected to have higher means than that of baseline. The density distribution analysis of baseline and future flows reveals that future periods are likely to experience an increase in the magnitude of mean flows but a decrease in variability. Rainfall extremes indicated by 1-day maximum rainfall, 5-day consecutive maximum rainfall, and the number of extreme rainfall days reveals frequent wetter extremes in the UARB under future climate conditions. Extreme floods, as estimated by the frequency analysis of daily flows, are also expected to become more frequent during the future periods. These changes in flows can be attributed solely to climate change since the analyses did not account impacts of possible land use change and water resources development in the UARB. This study is a good starting point to assess future flows, and further research is recommended to address the limitations of this study for improved understanding and assessments that will prove useful for planning purposes in the study area.

Beliefs about climate change in the aftermath of extreme flooding Abstract When faced with natural disasters, communities respond in diverse ways, with processes that reflect their cultures, needs, and the extent of damage incurred by the community. Because of their potentially recurring nature, floods offer an opportunity for communities to learn from and adapt to these experiences with the goal of increasing resiliency through reflection, modification of former policies, and adoption of new policies. A key component of a community's ability to learn from disaster is how community members perceive the causes of extreme flood events and whether there is risk of future similar events. Perceptions of causes of flooding, including climate change, may be influenced by experiencing a flood event, along with individual preferences for various policies put in place to help a community recover. Using data collected from two rounds of public surveys (n = 903) across six Colorado communities flooded in 2013, we investigate whether there is variation across causal understanding of flooding, and whether this variation can be linked to differences in proximity of damages experienced (personal property, neighborhood, or community). By analyzing these variables, along with other variables (time since flood, political affiliation, and worldview), this study improves our understanding of the factors that drive our beliefs about potential causes of floods, focusing on climate change. The findings suggest that the extent of damage experienced at the neighborhood and community levels can have a significant effect on the perceptions of climate change held by the public. In turn, these beliefs about climate change are positively associated with perceptions of risks of future flooding.

Towards a comprehensive characterization of evidence in synthesis assessments: the climate change impacts on the Brazilian water resources Abstract The Intergovernmental Panel on Climate Change (IPCC) has put a lot of efforts to describe uncertainties and to judge the confidence level of its major conclusions. Despite a guidance to communicate uncertainty, the assignment of confidence is not sufficiently clear and, thus, hard to be reproduced by the extern community. By conducting a synthesis assessment about the impacts of climate change on the Brazilian water resources, we identified an opportunity to illustrate the characterization of evidence as adopted in IPCC reports. We propose a method to describe the evidence from model outputs wherein the quality and amount of studies, as well as the consistency among their conclusions, are subject of a transparent rating procedure. In summary, the more comprehensive the study in sampling uncertainties, the higher its quality. Likewise, the amount and consistencyamong conclusions is assigned in a systematic way. The method is applied for synthesizing a collection of 42 peer-reviewed articles. It reveals important aspects about the evidence of the potential impacts of climate change in the Brazilian water resources, such as changes into a drier hydrological regime. However, the use of multi-model ensemble, the evaluation of models, and the observational data is limited. The proposed method enables consistent communication of the degree of evidence in a transparent, traceable, and comprehensive fashion. The method can be used as a tool to support experts on their judgment. The approach is reproducible and can guide synthesis work not only in Brazil but anywhere else.

Global and regional impacts of climate change at different levels of global temperature increase Abstract The assessment of the impacts of climate change at different levels of global warming helps inform national and international policy discussion around mitigation targets. This paper provides consistent estimates of global and regional impacts and risks at increases in global mean temperature up to 5 °C above pre-industrial levels, for over 30 indicators representing temperature extremes and heatwaves, hydrological change, floods and droughts and proxies for impacts on crop yields. At the global scale, all the impacts that could plausibly be either adverse or beneficial are adverse, and impacts and risks increase with temperature change. For example, the global average chance of a major heatwave increases from 5% in 1981–2010 to 28% at 1.5 °C and 92% at 4 °C, of an agricultural drought increases from 9 to 24% at 1.5 °C and 61% at 4 °C, and of the 50-year return period river flood increases from 2 to 2.4% at 1.5 °C and 5.4% at 4 °C. The chance of a damaging hot spell for maize increases from 5 to 50% at 4 °C, whilst the chance for rice rises from 27 to 46%. There is considerable uncertainty around these central estimates, and impacts and risks vary between regions. Some impacts—for example heatwaves—increase rapidly as temperature increases, whilst others show more linear responses. The paper presents estimates of the risk of impacts exceeding specific targets and demonstrates that these estimates are sensitive to the thresholds used.

Changes in vegetation and surface water balance at basin-scale in Central China with rising atmospheric CO 2 Abstract Elevated atmospheric CO2 concentration alters vegetation growth and composition, increases plant water use efficiency (WUE), and changes surface water balance. These changes and their differences between wet and dry climate are studied at a mid-latitude experiment site in the Loess Plateau of China. The study site, the Jinghe River basin (JRB), covers an area of 43,216 km2 and has a semiarid climate in the north and a semi-humid climate in the south. Two simulations from 1965 to 2012 are made using a site-calibrated Lund–Potsdam–Jena dynamic global vegetation model: one with the observed rise of the atmospheric CO2 from 319.7–391.2 ppmv, and the other with a fixed CO2 at the level of 1964 (318.9 ppmv). Analyses of the model results show that the elevated atmospheric CO2 promotes growth of woody vegetation (trees) and causes a 6.0% increase in basin-wide net primary production (NPP). The NPP increase uses little extra water however because of higher WUE. Further examination of the surface water budget reveals opposite CO2 effects between semiarid and semi-humid climates in the JRB. In the semiarid climate, plants sustain growth in higher CO2 because of the higher level of intracellular CO2 and therefore WUE, thus consuming more water and causing a greater decrease of surface runoff than in the fixed-lower CO2 case. In the semi-humid climate, NPP also increases but by a smaller amount than in the semiarid climate. Plant transpiration (ET) and total evapotranspiration (E) decrease in the elevated CO2 environment, yielding the increase of runoff. This asymmetry of the effects of elevated atmospheric CO2 exacerbates drying in the semiarid climate and enhances wetness in the semi-humid climate. Furthermore, plant WUE (=NPP/ET) is found to be nearly invariant to climate but primarily a function of the atmospheric CO2 concentration, a result suggesting a strong constraint of atmospheric CO2 on biophysical properties of the Earth system.

Alexandros Sfakianakis
Anapafseos 5 . Agios Nikolaos
Crete.Greece.72100
2841026182

6948891480

alsfakia@gmail.com