Forzieri, Giovanni; Bianchi, Alessandra; Feyen, Luc; Silva, Filipe Batista e.; Marin, Mario; Lavalle, Carlo; Leblois, Antoine
The projected increases in exposure to multiple climate hazards in many regions of Europe, emphasize the relevance of a multi-hazard risk assessment to comprehensively quantify potential impacts of climate change and develop suitable adaptation strategies. In this context, quantifying the future impacts of climatic extremes on critical infrastructures is crucial due to their key role for human wellbeing and their effects on the overall economy. Critical infrastructures describe the existing assets and systems that are essential for the maintenance of vital societal functions, health, safety, security, economic or social well-being of people, and the disruption or destruction of which would have a significant impact as a result of the failure to maintain those functions. We assess the direct damages of heat and cold waves, river and coastal flooding, droughts, wildfires and windstorms to energy, transport, industry and social infrastructures in Europe along the 21st century. The methodology integrates in a coherent framework climate hazard, exposure and vulnerability components. Overall damage is expected to rise up to 38 billion €/yr, ten time-folds the current climate damage, with drastic variations in risk scenarios. Exemplificative are drought and heat-related damages that could represent 70% of the overall climate damage in 2080s versus the current 12%. Many regions, prominently Southern Europe, will likely suffer multiple stresses and systematic infrastructure failures due to climate extremes if no suitable adaptation measures will be taken.
Nissen, Katrin; Ulbrich, Uwe
An event based detection algorithm for extreme precipitation is applied to a multi-model ensemble of regional climate model simulations. The algorithm determines extent, location, duration and severity of extreme precipitation events. We assume that precipitation in excess of the local present-day 10-year return value will potentially exceed the capacity of the drainage systems that protect critical infrastructure elements. This assumption is based on legislation for the design of drainage systems which is in place in many European countries. Thus, events exceeding the local 10-year return value are detected. In this study we distinguish between sub-daily events (3 hourly) with high precipitation intensities and long-duration events (1-3 days) with high precipitation amounts. The climate change simulations investigated here were conducted within the EURO-CORDEX framework and exhibit a horizontal resolution of approximately 12.5 km. The period between 1971-2100 forced with observed and scenario (RCP 8.5 and RCP 4.5) greenhouse gas concentrations was analysed. Examined are changes in event frequency, event duration and size. The simulations show an increase in the number of extreme precipitation events for the future climate period over most of the area, which is strongest in Northern Europe. Strength and statistical significance of the signal increase with increasing greenhouse gas concentrations. This work has been conducted within the EU project RAIN (Risk Analysis of Infrastructure Networks in response to extreme weather).
SU Sheng; LI YinHong; DUAN XianZhong
This paper analyzes the statistics of faults in a transmission and distribution networks in central China, unveils long-term autocorrelation and power law distribution of power system faults, which indicates that power system fault has self-organized criticality (SOC) feature. The conclusion is consistent with the power systems data in 2008 with ice storm present. Since power systems cover large areas, climate is the key factor to its safety and stability. In-depth analysis shows that the SOC of atmosphere system contributes much to that of power system faults. Extreme climate will be more intense and frequent with global warming, it will have more and more impact upon power systems. The SOC feature of power system faults is utilized to develop approaches to facilitate power systems adaptation to climate varia-tion in an economical and efficient way.
In October 2005, as the United States still was reeling from Hurricane Katrina in August and as the alphabet was too short to contain all of that year's named Atlantic tropical storms (Hurricane Wilma was forming near Jamaica), a timely workshop in Bermuda focused on climate extremes and society (see Eos, 87(3), 25, 17 January 2006). This edited volume, which corresponds roughly to the presentations given at that workshop, offers a fascinating look at the critically important intersection of acute climate stress and human vulnerabilities. A changing climate affects humans and other living things not through the variable that most robustly demonstrates the role of rising greenhouse gases—globally averaged temperature—but through local changes, especially changes in extremes. The first part of this book, “Defining and modeling the nature of weather and climate extremes,” focuses on natural science. The second part, “Impacts of weather and climate extremes,” focuses on societal impacts and responses, emphasizing an insurance industry perspective because a primary sponsor of the workshop was the Risk Prediction Initiative, whose aim is to “support scientific research on topics of interest to its sponsors” (p. 320).
O'Gorman, Paul A
The response of precipitation extremes to climate change is considered using results from theory, modeling, and observations, with a focus on the physical factors that control the response. Observations and simulations with climate models show that precipitation extremes intensify in response to a warming climate. However, the sensitivity of precipitation extremes to warming remains uncertain when convection is important, and it may be higher in the tropics than the extratropics. Several physical contributions govern the response of precipitation extremes. The thermodynamic contribution is robust and well understood, but theoretical understanding of the microphysical and dynamical contributions is still being developed. Orographic precipitation extremes and snowfall extremes respond differently from other precipitation extremes and require particular attention. Outstanding research challenges include the influence of mesoscale convective organization, the dependence on the duration considered, and the need to...
We analyse some climate dynamics from a complex network approach. This leads to an inverse problem: Is there a backbone-like structure underlying the climate system? For this we propose a method to reconstruct and analyze a complex network from data generated by a spatio-temporal dynamical system. This approach enables us to uncover relations to global circulation patterns in oceans and atmosphere. The global scale view on climate networks offers promising new perspectives for detecting dynamical structures based on nonlinear physical processes in the climate system. Moreover, we evaluate different regional climate models from this aspect. This concept is also applied to Monsoon data in order to characterize the regional occurrence of extreme rain events and its impact on predictability. Changing climatic conditions have led to a significant increase in magnitude and frequency of spatially extensive extreme rainfall events in the eastern Central Andes of South America. These events impose substantial natural hazards for population, economy, and ecology by floods and landslides. For example, heavy floods in Bolivia in early 2007 affected more than 133.000 households and produced estimated costs of 443 Mio. USD. Here, we develop a general framework to predict extreme events by combining a non-linear synchronization technique with complex networks. We apply our method to real-time satellite-derived rainfall data and are able to predict a large amount of extreme rainfall events. Our study reveals a linkage between polar and subtropical regimes as responsible mechanism: Extreme rainfall in the eastern Central Andes is caused by the interplay of northward migrating frontal systems and a low-level wind channel from the western Amazon to the subtropics, providing additional moisture. Frontal systems from the Antarctic thus play a key role for sub-seasonal variability of the South American Monsoon System.
Canada's natural environment and built infrastructure are affected significantly by extreme weather events, with repercussions such as economic losses. The purpose of this presentation was to research whether these losses are due to greater societal vulnerability or climatic extremes or both, and to determine whether engineering design codes and standards need to be changed to ensure that infrastructure, such as dams, can withstand future climatic extremes. Environment Canada maintains long term climate and water observing networks and uses climate data in the development of building codes and engineering design standards and practices. Because of the variable nature of precipitation, the range of spatial scales, climate system influences and the importance of local topography on precipitation occurrence and amount, analyzing historical trends and making future projections for precipitation, particularly extremes, are challenging. This presentation discussed historical climate trends and future projections with reference to changes temperature, precipitation and precipitation extremes. In addition, extreme weather events and recent trends were discussed together with human influence on trends and projections. The presentation demonstrated how the climate in Canada has varied during the period of instrumental records. Future predictions for precipitation extremes were developed using climate models and statistical downscaling. The presentation also highlighted atmospheric hazards information under development for emergency preparedness and disaster management planning. It was concluded that future climate changes are inevitable and will likely affect the frequency of heavy precipitation events. 14 refs., 1 tab., 19 figs
Hoang, L. P.; Lauri, H.; Kummu, M.; Koponen, J.; van Vliet, M. T. H.; Supit, I.; Leemans, R.; Kabat, P.; Ludwig, F.
Climate change poses critical threats to water related safety and sustainability in the Mekong River basin. Hydrological impact signals derived from CMIP3 climate change scenarios, however, are highly uncertain and largely ignore hydrological extremes. This paper provides one of the first hydrological impact assessments using the most recent CMIP5 climate change scenarios. Furthermore, we model and analyse changes in river flow regimes and hydrological extremes (i.e. high flow and low flow conditions). Similar to earlier CMIP3-based assessments, the hydrological cycle also intensifies in the CMIP5 climate change scenarios. The scenarios ensemble mean shows increases in both seasonal and annual river discharges (annual change between +5 and +16 %, depending on location). Despite the overall increasing trend, the individual scenarios show differences in the magnitude of discharge changes and, to a lesser extent, contrasting directional changes. We further found that extremely high flow events increase in both magnitude and frequency. Extremely low flows, on the other hand, are projected to occur less often under climate change. Higher low flows can help reducing dry season water shortage and controlling salinization in the downstream Mekong Delta. However, higher and more frequent peak discharges will exacerbate flood risk in the basin. The implications of climate change induced hydrological changes are critical and thus require special attention in climate change adaptation and disaster-risk reduction.
Tan, X.; Gan, T. Y.
When will the signal of obvious changes in extreme climate emerge over climate variability (Time of Emergence, ToE) is a key question for planning and implementing measures to mitigate the potential impact of climate change to natural and human systems that are generally adapted to potential changes from current variability. We estimated ToEs for the magnitude, duration and frequency of global extreme climate represented by 24 extreme climate indices (16 for temperature and 8 for precipitation) with different thresholds of the signal-to-noise (S/N) ratio based on projections of CMIP5 global climate models under RCP8.5 and RCP4.5 for the 21st century. The uncertainty of ToE is assessed by using 3 different methods to calculate S/N for each extreme index. Results show that ToEs of the projected extreme climate indices based on the RCP4.5 climate scenarios are generally projected to happen about 20 years later than that for the RCP8.5 climate scenarios. Under RCP8.5, the projected magnitude, duration and frequency of extreme temperature on Earth will all exceed 2 standard deviations by 2100, and the empirical 50th percentile of the global ToE for the frequency and magnitude of hot (cold) extreme are about 2040 and 2054 (2064 and 2054) for S/N > 2, respectively. The 50th percentile of global ToE for the intensity of extreme precipitation is about 2030 and 2058 for S/N >0.5 and S/N >1, respectively. We further evaluated the exposure of ecosystems and human societies to the pace of extreme climate change by determining the year of ToE for various extreme climate indices projected to occur over terrestrial biomes, marine realms and major urban areas with large populations. This was done by overlaying terrestrial, ecoregions and population maps with maps of ToE derived, to extract ToEs for these regions. Possible relationships between GDP per person and ToE are also investigated by relating the mean ToE for each country and its average value of GDP per person.
While the commercial and banking centre Dubai finds itself dealing with the aftermath of the economic crisis, the conservative neighbour Abu Dhabi is already pursuing ambitious targets - but the climate conditions in the desert states are not always ideal for the utilization of renewable energies. (orig.)
Thiery, Wim; Davin, Edouard L.; Lawrence, Dave; Hauser, Mathias; Seneviratne, Sonia I.
Land irrigation is an essential practice sustaining global food production and many regional economies. During the last decades, irrigation amounts have been growing rapidly. Emerging scientific evidence indicates that land irrigation substantially affects mean climate conditions in different regions of the world. However, a thorough understanding of the impact of irrigation on extreme climatic conditions, such as heat waves, droughts or intense precipitation, is currently still lacking. In this context, we aim to assess the historical influence of irrigation on the occurrence of climate extremes. To this end, two simulations are conducted over the period 1910-2010 with a state-of-the-art global climate model (the Community Earth System Model, CESM): a control simulation including all major anthropogenic and natural external forcings except for irrigation and a second experiment with transient irrigation enabled. The two simulations are evaluated for their ability to represent (i) hot, dry and wet extremes using the HadEX2 and ERA-Interim datasets as a reference, and (ii) latent heat fluxes using LandFlux-EVAL. Assuming a linear combination of climatic responses to different forcings, the difference between both experiments approximates the influence of irrigation. We will analyse the impact of irrigation on a number of climate indices reflecting the intensity and duration of heat waves. Thereby, particular attention is given to the role of soil moisture changes in modulating climate extremes. Furthermore, the contribution of individual biogeophysical processes to the total impact of irrigation on hot extremes is quantified by application of a surface energy balance decomposition technique to the 90th and 99th percentile surface temperature changes.
Frédéric JIGUET, Lluis BROTONS, Vincent DEVICTOR
Full Text Available Species assemblages and natural communities are increasingly impacted by changes in the frequency and severity of extreme climatic events. Here we propose a brief overview of expected and demonstrated direct and indirect impacts of extreme events on animal communities. We show that differential impacts on basic biological parameters of individual species can lead to strong changes in community composition and structure with the potential to considerably modify the functional traits of the community. Sudden disequilibria have even been shown to induce irreversible shifts in marine ecosystems, while cascade effects on various taxonomic groups have been highlighted in Mediterranean forests. Indirect effects of extreme climatic events are expected when event-induced habitat changes (e.g. soil stability, vegetation composition, water flows altered by droughts, floods or hurricanes have differential consequences on species assembled within the communities. Moreover, in increasing the amplitude of trophic mismatches, extreme events are likely to turn many systems into ecological traps under climate change. Finally, we propose a focus on the potential impacts of an extreme heat wave on local assemblages as an empirical case study, analysing monitoring data on breeding birds collected in France. In this example, we show that despite specific populations were differently affected by local temperature anomalies, communities seem to be unaffected by a sudden heat wave. These results suggest that communities are tracking climate change at the highest possible rate [Current Zoology 57 (3: 406–413, 2011].
Frédéric JIGUET; Lluis BROTONS; Vincent DEVICTOR
Species assemblages and natural communities are increasingly impacted by changes in the frequency and severity of extreme climatic events. Here we propose a brief overview of expected and demonstrated direct and indirect impacts of extreme events on animal communities. We show that differential impacts on basic biological parameters of individual species can lead to strong changes in community composition and structure with the potential to considerably modify the functional traits of the community. Sudden disequilibria have even been shown to induce irreversible shifts in marine ecosystems, while cascade effects on various taxonomic groups have been highlighted in Mediterranean forests. Indirect effects of extreme climatic events are expected when event-induced habitat changes (e.g. Soil stability, vegetation composition, water flows altered by droughts, floods or hurricanes) have differential consequences on species assembled within the communities. Moreover, in increasing the amplitude of trophic mismatches, extreme events are likely to turn many systems into ecological traps under climate change. Finally, we propose a focus on the potential impacts of an extreme heat wave on local assemblages as an empirical case study, analysing monitoring data on breeding birds collected in France. In this example, we show that despite specific populations were differently affected by local temperature anomalies, communities seem to be unaffected by a sudden heat wave. These results suggest that communities are tracking climate change at the highest possible rate.
Reichstein, Markus; Bahn, Michael; Ciais, Philippe; Vicca, Sara; et al.
Abstract: The terrestrial biosphere is a key component of the global carbon cycle and its carbon balance is strongly influenced by climate. Continuing environmental changes are thought to increase global terrestrial carbon uptake. But evidence is mounting that climate extremes such as droughts or storms can lead to a decrease in regional ecosystem carbon stocks and therefore have the potential to negate an expected increase in terrestrial carbon uptake. Here we explore the mechanisms and impa...
Diez, Jeffrey M; D'Antonio, Carla M; Dukes, Jeffrey S; Grosholz, Edwin D.; Olden, Julian D.; Sorte, Cascade JB; Dana M. Blumenthal; Bradley, Bethany A; Early, Regan; Ibáñez, Inés; Jones, Sierra J; Lawler, Joshua J.; Miller, Luke P.
Extreme climatic events (ECEs) – such as unusual heat waves, hurricanes, floods, and droughts – can dramatically affect ecological and evolutionary processes, and these events are projected to become more frequent and more intense with ongoing climate change. However, the implications of ECEs for biological invasions remain poorly understood. Using concepts and empirical evidence from invasion ecology, we identify mechanisms by which ECEs may influence the invasion process, from initial intro...
Mastrandrea, M. D.; Tebaldi, C.; Snyder, C.; Schneider, S. H.
In the next few decades, it is likely that California must face the challenge of coping with increased impacts from extreme events such as heatwaves, wildfires, droughts, and floods. Such events can cause significant damages, and are responsible for a large fraction of near-term climate-related impacts every year. Some extreme events have already very likely changed in frequency and intensity over the past several decades, and these changes are expected to continue with relatively small changes in average conditions. We synthesize existing research to characterize current understanding of the direct impacts of extreme events across sectors, as well as the interactions between sectors as they are affected by extreme events. We also produce new projections of changes in the frequency and intensity of extreme events in the future across climate models, emissions scenarios, and downscaling methods for producing regional climate information, for each county in California. We evaluate historical and projected changes for a suite of temperature and precipitation-based climate indicators, and we conduct a return level analysis to investigate projected changes in extreme temperatures. Finally, we include an analysis of the future likelihood of events similar in magnitude to specific historical events, such as the July 2006 heat wave. Consistent with other studies, we find significant increases in the frequency and magnitude of both maximum and minimum temperature extremes in many areas, with the magnitude of change dependent on the magnitude of projected emissions and overall temperature increase. For example, in many regions of California, at least a ten-fold increase in frequency is projected for extreme temperatures currently estimated to occur once every 100 years, even under a moderate emissions scenario (SRES B1). Under a higher emissions scenario (SRES A2), these temperatures are projected to occur close to annually in most regions. Also consistent with other studies
Wuebbles, D. J.
It is a real honor for me to get the opportunity to pay homage to Steve Schneider and his extensive accomplishments. I also treasured his friendship. Steve was known for being a great communicator and for his expertise in climate policy and solutions, along with being an outstanding scientist with many contributions to understanding the Earth's climate system. One of the major challenges today to all of these areas is the changing trends in extreme weather under a changing climate. My focus in this presentation is to examine these issues by drawing on new research from my own team at Illinois. For example, climate change amplification in the Arctic has raised questions regarding its potential effects on extreme weather at mid-latitudes, especially the United States. In our studies, we find a statistically significant relationship between summer sea ice north of Alaska and geopotential height anomalies in the north Pacific during subsequent winter and spring months. The frequency of these semi-persistent height anomalies exhibits a long-term upward trend that amplify the jet stream off the West Coast of the U.S., driving more persistent precipitation patterns over certain regions of the United States, specifically in the West and Midwest parts of the country. Our results suggest that as sea ice in the Arctic north of Alaska continues to decrease, a more persistent ridge will form in areas adjacent to this location and affect storm tracks over the continental United States. In other studies, we are examining the effects of the changing climate on trends in extreme events throughout the continental U.S. We are also investigating changes in historical severe convective weather over the United States using reanalysis data, the NEXRAD/in situ gauge Climate Data Record (CDR) data set, and storm reports. After analyzing the ability of global climate models to represent the observed trends in severe-thunderstorm environments, projected future trends are also to be analyzed.
Full Text Available Humankind has been exposed to climate extremes from the very beginning of its existence. Today, prevention and mitigation of natural catastrophes have become a priority for International Union and World Meteorological Organization. Atmospheric electrical discharges and thunders represent an event characteristic of our part of the world in the warm half of a year. This climate event pose a danger to human life and material goods, so this work discusses approximate number of days with thunder and the absolutely highest number of days with thunder in Serbia in the period from 1995 to 2005.
An overview of the expected change of climate extremes during this century due to greenhouse gases and aerosol anthropogenic emissions is presented. The most commonly used methodologies rely on the dynamical or statistical down-scaling of climate projections, performed with coupled atmosphere-ocean general circulation models. Either of dynamical or of statistical type, down-scaling methods present strengths and weaknesses, but neither their validation on present climate conditions, nor their potential ability to project the impact of climate change on extreme event statistics allows one to give a specific advantage to one of the two types. The results synthesized in the last IPCC report and more recent studies underline a convergence for a very likely increase in heat wave episodes over land surfaces, linked to the mean warming and the increase in temperature variability. In addition, the number of days of frost should decrease and the growing season length should increase. The projected increase in heavy precipitation events appears also as very likely over most areas and also seems linked to a change in the shape of the precipitation intensity distribution. The global trends for drought duration are less consistent between models and down-scaling methodologies, due to their regional variability. The change of wind-related extremes is also regionally dependent, and associated to a poleward displacement of the mid-latitude storm tracks. The specific study of extreme events over France reveals the high sensitivity of some statistics of climate extremes at the decadal time scale as a consequence of regional climate internal variability. (authors)
monsoon and b) tropical cyclones. Basically the climate of India is domi- nated by the south west monsoon season which accounts for about 75% of the annual rainfall. The extreme weather events occur over India are: Floods, Droughts, Tropical Cyclones..., 52, 35, 092 people in 4962 villages were af- fected. Standing crops in 2,13,184 hectares of land were badly affected. Of all the major natural disasters, droughts account for significant damages even though the number of deaths is insignificant...
Kyselý, Jan; Gaál, Ladislav; Beranová, Romana; Plavcová, Eva
Patras: University of Patras, 2010 - (Argiriou, A.; Kazantzidis, A.), s. 833-838 ISBN 978-960-99254-0-2. [International Conference of Meteorology, Climatology and Atmospheric Physics (COMECAP2010) /10./. Patras (GR), 25.05.2010-28.05.2010] R&D Projects: GA AV ČR KJB300420801 Grant ostatní: ENSEMBLES(XE) 505539 Institutional research plan: CEZ:AV0Z30420517 Keywords : precipitation extremes * region-of-influence method * regional climate models Subject RIV: DG - Athmosphere Sciences, Meteorology
Montanari, Alberto; Papalexiou, Simon Michael
The title of the present contribution is a relevant question that is frequently posed to scientists, technicians and managers of local authorities. Although several research efforts were recently dedicated to rainfall observation, analysis and modelling, the above question remains essentially unanswered. The question comes from the awareness that the frequency of floods and the related socio-economic impacts are increasing in many countries, and climate change is deemed to be the main trigger. Indeed, identifying the real reasons for the observed increase of flood risk is necessary in order to plan effective mitigation and adaptation strategies. While mitigation of climate change is an extremely important issue at the global level, at small spatial scales several other triggers may interact with it, therefore requiring different mitigation strategies. Similarly, the responsibilities of administrators are radically different at local and global scales. This talk aims to provide insights and information to address the question expressed by its title. High resolution and long term rainfall data will be presented, as well as an analysis of the frequency of their extremes and its progress in time. The results will provide pragmatic indications for the sake of better planning flood risk mitigation policies.
Trenberth, Kevin E.; Fasullo, John T.
A global perspective is developed on a number of high impact climate extremes in 2010 through diagnostic studies of the anomalies, diabatic heating, and global energy and water cycles that demonstrate relationships among variables and across events. Natural variability, especially ENSO, and global warming from human influences together resulted in very high sea surface temperatures (SSTs) in several places that played a vital role in subsequent developments. Record high SSTs in the Northern Indian Ocean in May 2010, the Gulf of Mexico in August 2010, the Caribbean in September 2010, and north of Australia in December 2010 provided a source of unusually abundant atmospheric moisture for nearby monsoon rains and flooding in Pakistan, Colombia, and Queensland. The resulting anomalous diabatic heating in the northern Indian and tropical Atlantic Oceans altered the atmospheric circulation by forcing quasi-stationary Rossby waves and altering monsoons. The anomalous monsoonal circulations had direct links to higher latitudes: from Southeast Asia to southern Russia, and from Colombia to Brazil. Strong convection in the tropical Atlantic in northern summer 2010 was associated with a Rossby wave train that extended into Europe creating anomalous cyclonic conditions over the Mediterranean area while normal anticyclonic conditions shifted downstream where they likely interacted with an anomalously strong monsoon circulation, helping to support the persistent atmospheric anticyclonic regime over Russia. This set the stage for the "blocking" anticyclone and associated Russian heat wave and wild fires. Attribution is limited by shortcomings in models in replicating monsoons, teleconnections and blocking.
Climate extremes are rarely occurring natural phenomena in the climate system. They often pose one of the greatest environmental threats to human and natural systems. Statistical methods are commonly used to investigate characteristics of climate extremes. The fitted statistical properties are often
Sunyer Pinya, Maria Antonia
The latest report from the Intergovernmental Panel on Climate Change (IPCC) states that it is unequivocal that climate change is occurring. One of the largest impacts of climate change is anticipated to be an increase in the severity of extreme events, such as extreme precipitation. Floods caused...... by extreme precipitation pose a threat to human life and cause high economic losses for society. Thus, strategies to adapt to changes in extreme precipitation are currently being developed and established worldwide. Information on the expected changes in extreme precipitation is required for the...... development of adaptation strategies, but these changes are subject to uncertainties. The focus of this PhD thesis is the quantification of uncertainties in changes in extreme precipitation. It addresses two of the main sources of uncertainty in climate change impact studies: regional climate models (RCMs...
The author discusses some reasons to be sceptical about the media-supported idea of an actual climate change, and more particularly about the critical role assigned to carbon dioxide in global warming, about the ability to make the distinction between natural and man-induced climate variations, about the quality of models and simulations, about the knowledge on climate physics, about the interpretation of the recently observed warming (since 1997)
Müller, Miloslav; Kašpar, Marek
Roč. 1, 06 Sep (2013), s. 4481-4510. ISSN 2195-9269 R&D Projects: GA ČR(CZ) GAP209/11/1990 Institutional support: RVO:68378289 Keywords : weather extreme * climate extreme * extremity evaluation * return period * generalized extreme value distribution * region of influence Subject RIV: DG - Athmosphere Sciences, Meteorology http://www.nat-hazards-earth-syst-sci-discuss.net/1/4481/2013/nhessd-1-4481-2013.pdf
Müller, Miloslav; Kašpar, Marek
Roč. 14, č. 2 (2014), s. 473-483. ISSN 1561-8633 R&D Projects: GA ČR(CZ) GAP209/11/1990 Institutional support: RVO:68378289 Keywords : weather extreme * climate extreme * extremity evaluation * return period * generalized extreme value distribution * region of influence Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.735, year: 2014 http://www.nat-hazards-earth-syst-sci.net/14/473/2014/nhess-14-473-2014.pdf
This PhD thesis presents the development of a methodology that analyzes potential climate change impacts on hydrological extremes along rivers in Flanders (Belgium).The main objective of this study is to show whether hydrological modelling techniques driven by climate modelling techniques and climate change scenarios enable a prediction of the long-term evolution of the hydrological system of the studied area.The climate change impact analysis is based on a continuous simulation approach: The...
Dettinger, M. D.
Projections of climate change are typically made with global models of the climate system responding to future greenhouse-gas emissions. The resolution of the models is currently about 50-200 km over the US, with outputs available at 6-hourly or longer steps. These resolutions are not suitable for direct evaluation of changes in hydrometeorological extremes. Furthermore, the skill with which the projections represent storm extremes has not been documented for the most part. Nonetheless, extremes are so important that management communities already urgently need assessments. Examples of several approaches in use in California will be outlined. For the Central Valley Flood Protection Plan, a threshold approach is attempting to identify "breaking points" in flood-management systems beyond which unacceptable failures occur. Where breaking points can be identified, the question to climate scientists becomes "are the meteorological conditions causing these breaking points likely to be surpassed under even projected conditions?" Most resource and hazards management systems have faced extreme events in the past, and designs to accommodate similar events in the future commonly exist. The threshold analysis is sharpening thinking about those historically based "design events" in the new context of climate change. Once the mechanisms for the most extreme (historical) hydrometeorological challenges have been identified, climate models and their projections can be evaluated with a focus on the large-scale meteorological conditions that led to the critical storm types. If GCM-scale indicators of those storm types are represented adequately, then projections can be evaluated directly to estimate changes in frequency, intensity, timing, and location of the critical-storms, as illustrated with landfalling atmospheric-river storms. Detection of such changes can then inform threshold approaches outlined above and allow construction of entirely new design scenarios. Finally, most
Kuchar, Leszek; Kosierb, Ryszard; Iwański, Sławomir; Jelonek, Leszek
-80 years. The probability distribution of the extreme river flow gives detailed information on the moment characteristics, confidence intervals and critical values. It is an important tool for a decision support system. In case of extreme daily flow in the Kaczawa River, the catchment shows significant changes depending on the climate change scenario and time to lead. REFERENCES Iwanski, S. and L. Kuchar (2003). Spatial generation of daily meteorological data. Acta Scientiarum Polonorum - Formatio Circumiectu, 2(1): 113-121 (in Polish). Katz, R.W. (1996). Use of conditional stochastic models to generate climate change scenarios. Clim. Change, 35: 397-414. Walpole R.E., Myers R.H., Myers S.L. and K. Ye (2002). Probability and statistics for engineers and scientists. Prentice Hall, 7th Ed., New Jersey.
Fokko Hattermann, Fred; Huang, Shaochun; Kundzewicz, Zbigniew W.; Hoffmann, Peter
An increase of hydro-climatic extremes can be observed worldwide and is challenging national and regional risk management and adaptation plans. Our study presents and discusses possible trends in climate drivers and hydro-climatic extremes in Europe observed and under future climate conditions. In a case study for Germany, impacts of different regional climate scenario ensembles are compared. To this end, a hydrological model was applied to transform the scenarios data into river runoff for more than 5000 river reaches in Germany. Extreme Value Distributions have been fitted to the hydrographs of the river reaches to derive the basic flood statistics. The results for each river reach have been linked to related damage functions as provided by the German Insurance Association considering damages on buildings and small enterprises. The robust result is that under scenario conditions a significant increase in flood related losses can be expected in Germany, while also the number of low flow events may rise.
Several lines of evidence suggest that the warming climate plays a vital role in driving certain types of extreme weather. The impact of warming and of extreme weather on forest carbon assimilation capacity is poorly known. Filling this knowledge gap is critical towards understanding the amount of carbon that forests can hold. Here, we used a perfect-deficit approach to identify forest canopy photosynthetic capacity (CPC) deficits and analyze how they correlate to climate extremes, based on observational data measured by the eddy covariance method at 27 forest sites over 146 site-years. We found that droughts severely affect the carbon assimilation capacities of evergreen broadleaf forest (EBF) and deciduous broadleaf forest. The carbon assimilation capacities of Mediterranean forests were highly sensitive to climate extremes, while marine forest climates tended to be insensitive to climate extremes. Our estimates suggest an average global reduction of forest CPC due to unfavorable climate extremes of 6.3 Pg C (∼5.2% of global gross primary production) per growing season over 2001–2010, with EBFs contributing 52% of the total reduction
Williams, C.; Kniveton, D.; Layberry, R.
It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable extreme events, due to a number of factors including extensive poverty, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of a state-of-the-art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. Once the model's ability to reproduce extremes has been assessed, idealised regions of SST anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, results from sensitivity testing of the UK Meteorological Office Hadley Centre's climate model's domain size are firstly presented. Then simulations of current climate from the model, operating in both regional and global mode, are compared to the MIRA dataset at daily timescales. Thirdly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset. Finally, the results from the idealised SST experiments are briefly presented, suggesting associations between rainfall extremes and both local and remote SST anomalies.
Zickgraf, Caroline; Perrin, Nathalie; Gemenne, François
With the target of limiting global warming to 2ºC becoming increasingly difficult to achieve, policymakers, businesses and other decision-makers need to begin to plan ahead for adaptation to changes in climate associated with higher levels of global warming. Alongside this, ongoing international negotiations on limiting global warming require clear information on the demographic consequences of different levels of climate change. The HELIX project (High-End cLimate Impacts and eXtremes), and ...
Bailey, Liam; Van de Pol, M.
Summary Extreme climatic events (ECEs) are predicted to become more frequent as the climate changes. A rapidly increasing number of studies – though few on animals – suggest that the biological consequences of ECEs can be severe. However, ecological research on the impacts of ECEs has been limited b
Full text: Full text: Assessments of the impact of climate change on extreme sea levels along parts of the Victorian coast will be presented. The method involves identifying a large population of storm surge events in tide gauge records along the stretch of coastline of interest and modelling each event with a hydrodynamic model. Conditions under future climate regimes are considered by perturbing the atmospheric boundary conditions of the model in accordance with wind speed projections from climate models. Extreme value analysis is applied to the output of the hydrodynamic model to generate probabilities and return periods for storm surge heights. A Monte-Carlo approach is used to combine these heights with tide heights. Finally estimates of future mean sea level rise from the Intergovernmental Panel on Climate Change are added in. Initial work on the possible impact of changes in extreme sea levels on the risk of inundation of low lying coastal land will also be presented
Anushiya, j.; Andimuthu, R.
Analyses of observed climate throughout world revealed some significant changes in the extremes. Any change in the frequency or severity of extreme climate events would have profound impacts on the resilience of nature and society. It is thus very important to analyze extreme events to reliably monitor and detect climate change. Chennai is the fourth largest metropolis in India and one of the fastest growing economic and Industrial growth centers in South Asia. Population has grown rapidly in the last 20 years due to its major industrialization and tremendous growth. Already Chennai's day and night time Temperature shows an increasing trend. The past incidence of catastrophic flooding was observed in the city due to heavy rains associated with depressions and cyclonic storm lead floods in major rivers. After 2000, the incidents were reported repeatedly. The effort has made in this study to find the observed climate extremities over the past years and in the future. For observed changes, IMD gridded data set, and station data are used. Future high resolution climate scenarios (0.220x0.220) are developed through RCM using PRECIS. The boundary data have provided by the UK Met office. The selected members are simulated under the A1B scenario (a mid range emission scenario) for a continuous run till 2100. Climate indices listed by Expert Team (ET) on Climate Change Detection and Indices (ETCCDI) by the CLIVAR are considered in this study. The indices were obtained using the software package RClimDex. Kendall's tau based slope estimator has been used to find the significance lavel. The results shows the significant increasing tendency of warm days (TX90P) in the past and in future. The trends in extreme wet days (R99P) are also increased. The growth in population, urban and industrial area, economic activities, depletion of natural resources along with changing climate are forced to develop the infrastructure includes climate friendly policies to adopt and to ensure the
Wang, Hui-Jun; Sun, Jian-Qi; Chen, Huo-Po; Zhu, Ya-Li; Zhang, Ying; Jiang, Da-Bang; Lang, Xian-Mei; Fan, Ke; Yu, En-Tao [Chinese Academy of Sciences, Beijing (China). Inst. of Atmospheric Physics; Yang, Song [NOAA Climate Prediction Center, Camp Springs, MD (United States)
In this paper, studies on extreme climate in China including extreme temperature and precipitation, dust weather activity, tropical cyclone activity, intense snowfall and cold surge activity, floods, and droughts are reviewed based on the peer-reviewed publications in recent decades. The review is focused first on the climatological features, variability, and trends in the past half century and then on simulations and projections based on global and regional climate models. As the annual mean surface air temperature (SAT) increased throughout China, heat wave intensity and frequency overall increased in the past half century, with a large rate after the 1980s. The daily or yearly minimum SAT increased more significantly than the mean or maximum SAT. The long-term change in precipitation is predominantly characterized by the so-called southern flood and northern drought pattern in eastern China and by the overall increase over Northwest China. The interdecadal variation of monsoon, represented by the monsoon weakening in the end of 1970s, is largely responsible for this change in mean precipitation. Precipitation-related extreme events (e.g., heavy rainfall and intense snowfall) have become more frequent and intense generally over China in the recent years, with large spatial features. Dust weather activity, however, has become less frequent over northern China in the recent years, as result of weakened cold surge activity, reinforced precipitation, and improved vegetation condition. State-of-the-art climate models are capable of reproducing some features of the mean climate and extreme climate events. However, discrepancies among models in simulating and projecting the mean and extreme climate are also demonstrated by many recent studies. Regional models with higher resolutions often perform better than global models. To predict and project climate variations and extremes, many new approaches and schemes based on dynamical models, statistical methods, or their
Smith, R. L.; Wehner, M. F.
The increasing frequency of extreme weather events raises the question of to what extent such events can be attributed to human causes. Within the climate literature, an approach has been developed based on a quantity known as the fraction of attributable risk, or FAR. The essence of this approach is to estimate the probability of the extreme event of interest from parallel runs of climate models under either anthropogenic or natural conditions; the two probabilities are then combined to produce the FAR. However, a number of existing approaches either make questionable assumptions about estimating extreme event probabilites (e.g. inappropriate assumption of the normal distribution) or ignore the differences between climate models and observational data. Here, we propose an approach based on extreme value theory, incorporated into a hierarchical model to account for differences among climate models. A related technique, based on the same modeling approach, leads to quantitative estimates of how the probability of an extreme event will change under future projected climate change. We illustrate the method with examples related to the European heatwave of 2003, the Russian heatwave of 2010, and the Texas/Oklahoma heatwave and drought of 2011.
Mohammad Badrul Masud; Peeyush Soni; Sangam Shrestha; Tripathi, Nitin K.
This study analyzes 24 climate extreme indices over North Thailand using observed data for daily maximum and minimum temperatures and total daily rainfall for the 1960–2010 period, and HadCM3 Global Climate Model (GCM) and PRECIS Regional Climate Model simulated data for the 1960–2100 period. A statistical downscaling tool is employed to downscale GCM outputs. Variations in and trends of historical and future climates are identified using the nonparametric Mann-Kendall trend test and Sen’s sl...
Veland, S.; Lynch, A. H.
Human societies have become a geologic agent of change, and with this is an increasing awareness of the environment risks that confront human activities and values. More frequent and extreme hydroclimate events, anomalous tropical cyclone seasons, heat waves and droughts have all been documented, and many rigorously attributed to fossil fuel emissions (e.g. DeGaetano 2009; Hoyos et al. 2006). These extremes, however, do not register themselves in the abstract - they occur in particular places, affecting particular populations and ecosystems (Turner et al. 2003). This can be considered to present a policy window to decrease vulnerability and enhance emergency management. However, the asymmetrical character of these events may lead some to treat remote areas or disenfranchised populations as capable of absorbing the environmental damage attributable to the collective behavior of those residing in wealthy, populous, industrialized societies (Young 1989). Sound policies for adaptation to changing extremes must take into account the multiple interests and resource constraints for the populations affected and their broader contexts. Minimizing vulnerability to weather extremes is only one of many interests in human societies, and as noted, this interest competes with the others for limited time, attention, funds and other resources. Progress in reducing vulnerability also depends on policy that integrates the best available local and scientific knowledge and experience elsewhere. This improves the chance that each policy will succeed, but there are no guarantees. Each policy must be recognized as a matter of trial and error to some extent; surprises are inevitable. Thus each policy should be designed to fail gracefully if it fails, to learn from the experience, and to leave resources sufficient to implement the lessons learned. Overall policy processes must be quasi-evolutionary, avoiding replication without modification of failed policies and building on the successes
Ruane, Alexander C.; McDermid, Sonali; Mavromatis, Theodoros; Hudson, Nicholas; Morales, Monica; Simmons, John; Prabodha, Agalawatte; Ahmad, Ashfaq; Ahmad, Shakeel; Ahuja, Laj R.
Recognizing that climate change will affect agricultural systems both through mean changes and through shifts in climate variability and associated extreme events, we present preliminary analyses of climate impacts from a network of 1137 crop modeling sites contributed to the AgMIP Coordinated Climate-Crop Modeling Project (C3MP). At each site sensitivity tests were run according to a common protocol, which enables the fitting of crop model emulators across a range of carbon dioxide, temperature, and water (CTW) changes. C3MP can elucidate several aspects of these changes and quantify crop responses across a wide diversity of farming systems. Here we test the hypothesis that climate change and variability interact in three main ways. First, mean climate changes can affect yields across an entire time period. Second, extreme events (when they do occur) may be more sensitive to climate changes than a year with normal climate. Third, mean climate changes can alter the likelihood of climate extremes, leading to more frequent seasons with anomalies outside of the expected conditions for which management was designed. In this way, shifts in climate variability can result in an increase or reduction of mean yield, as extreme climate events tend to have lower yield than years with normal climate.C3MP maize simulations across 126 farms reveal a clear indication and quantification (as response functions) of mean climate impacts on mean yield and clearly show that mean climate changes will directly affect the variability of yield. Yield reductions from increased climate variability are not as clear as crop models tend to be less sensitive to dangers on the cool and wet extremes of climate variability, likely underestimating losses from water-logging, floods, and frosts.
A, A.; Mishra, V.
Climate change is likely to affect food and water security in India. India has witnessed tremendous growth in its food production after the green revolution. However, during the recent decades the food grain yields were significantly affected by the extreme climate and weather events. Air temperature and associated extreme events (number of hot days and hot nights, heat waves) increased significantly during the last 50 years in the majority of India. More remarkably, a substantial increase in mean and extreme temperatures was observed during the winter season in India. On the other hand, India witnessed extreme flood and drought events that have become frequent during the past few decades. Extreme rainfall during the non-monsoon season adversely affected the food grain yields and results in tremendous losses in several parts of the country. Here we evaluate the changes in hydroclimatic extremes and its linkage with the food grain production in India. We use observed food grain yield data for the period of 1980-2012 at district level. We understand the linkages between food grain yield and crop phenology obtained from the high resolution leaf area index and NDVI datasets from satellites. We used long-term observed data of daily precipitation and maximum and minimum temperatures to evaluate changes in the extreme events. We use statistical models to develop relationships between crop yields, mean and extreme temperatures for various crops to understand the sensitivity of these crops towards changing climatic conditions. We find that some of the major crop types and predominant crop growing areas have shown a significant sensitivity towards changes in extreme climatic conditions in India.
Extremes in climate have significant impacts on ecosystems and are expected to increase under future climate change. Extremes in vegetation could capture such impacts and indicate the vulnerability of ecosystems, but currently have not received a global long-term assessment. In this study, a robust method has been developed to detect significant extremes (low values) in biweekly time series of global normalized difference vegetation index (NDVI) from 1982 to 2006 and thus to acquire a global pattern of vegetation extreme frequency. This pattern coincides with vegetation vulnerability patterns suggested by earlier studies using different methods over different time spans, indicating a consistent mechanism of regulation. Vegetation extremes were found to aggregate in Amazonia and in the semi-arid and semi-humid regions in low and middle latitudes, while they seldom occurred in high latitudes. Among the environmental variables studied, extreme low precipitation has the highest slope against extreme vegetation. For the eight biomes analyzed, these slopes are highest in temperate broadleaf forest and temperate grassland, suggesting a higher sensitivity in these environments. The results presented here contradict the hypothesis that vegetation in water-limited semi-arid and semi-humid regions might be adapted to drought and suggest that vegetation in these regions (especially temperate broadleaf forest and temperate grassland) is highly prone to vegetation extreme events under more severe precipitation extremes. It is also suggested here that more attention be paid to precipitation-induced vegetation changes than to temperature-induced events. (letter)
Climate extremes have profound implications for urban infrastructure and human society, but studies of observed changes in climate extremes over the global urban areas are few, even though more than half of the global population now resides in urban areas. Here, using observed station data for 217 urban areas across the globe, we show that these urban areas have experienced significant increases (p-value <0.05) in the number of heat waves during the period 1973–2012, while the frequency of cold waves has declined. Almost half of the urban areas experienced significant increases in the number of extreme hot days, while almost 2/3 showed significant increases in the frequency of extreme hot nights. Extreme windy days declined substantially during the last four decades with statistically significant declines in about 60% in the urban areas. Significant increases (p-value <0.05) in the frequency of daily precipitation extremes and in annual maximum precipitation occurred at smaller fractions (17 and 10% respectively) of the total urban areas, with about half as many urban areas showing statistically significant downtrends as uptrends. Changes in temperature and wind extremes, estimated as the result of a 40 year linear trend, differed for urban and non-urban pairs, while changes in indices of extreme precipitation showed no clear differentiation for urban and selected non-urban stations. (letter)
Prabhat, Mr; Ruebel, Oliver; Byna, Surendra; Wu, Kesheng; Li, Fuyu; Wehner, Michael; Bethel, E. Wes
We present TECA, a parallel toolkit for detecting extreme events in large climate datasets. Modern climate datasets expose parallelism across a number of dimensions: spatial locations, timesteps and ensemble members. We design TECA to exploit these modes of parallelism and demonstrate a prototype implementation for detecting and tracking three classes of extreme events: tropical cyclones, extra-tropical cyclones and atmospheric rivers. We process a modern TB-sized CAM5 simulation dataset with TECA, and demonstrate good runtime performance for the three case studies.
Kundzewicz, Z. W.; Giannakopoulos, C.; Schwarb, M.; Stjernquist, I.; Schlyter, P.; Szwed, M.; Palutikof, J.
Significant changes in the climatic system have been observed, which may be attributed to human-enhanced greenhouse effect. Even stronger changes are projected for the future, impacting in an increasing way on human activity sectors. The present contribution, prepared in the framework of the MICE (Modelling the Impact of Climate Extremes) Project of the European Union, reviews how climate change may impact on winter tourism in the Alpine region, intense precipitation and flood potential in central Europe, forest damage in Scandinavia and beach holidays in the Mediterranean coast. Impacts are likely to be serious and largely adverse. Due to a lack of adequate information and lack of broadly accepted and reliable mathematical models describing the impact of changes in climate extremes on these activity sectors, it has been found useful to use expert judgement based impact assessment. Accordingly, regional mini-workshops were organized serving as platforms for communication between scientists and stakeholders, vehicles for dissemination of the state-of-the-art of the scientific understanding and for learning stakeholders’ view on extreme events, their impacts and the preparedness system. Stakeholders had the opportunity to react to the scientific results and to reflect on their perception of the likely impacts of projected changes in extremes on relevant activity sectors and the potential to adapt and avert adverse consequences. The results reported in this paper present the stakeholders’ suggestions for essential information on different extreme event impacts and their needs from science.
Isbell, Forest; Craven, Dylan; Connolly, John; Loreau, Michel; Schmid, Bernhard; Beierkuhnlein, Carl; Bezemer, T. Martijn; Bonin, Catherine; Bruelheide, Helge; de Luca, Enrica; Ebeling, Anne; Griffin, John N.; Guo, Qinfeng; Hautier, Yann; Hector, Andy; Jentsch, Anke; Kreyling, Jürgen; Lanta, Vojtěch; Manning, Pete; Meyer, Sebastian T.; Mori, Akira S.; Naeem, Shahid; Niklaus, Pascal A.; Polley, H. Wayne; Reich, Peter B.; Roscher, Christiane; Seabloom, Eric W.; Smith, Melinda D.; Thakur, Madhav P.; Tilman, David; Tracy, Benjamin F.; van der Putten, Wim H.; van Ruijven, Jasper; Weigelt, Alexandra; Weisser, Wolfgang W.; Wilsey, Brian; Eisenhauer, Nico
It remains unclear whether biodiversity buffers ecosystems against climate extremes, which are becoming increasingly frequent worldwide. Early results suggested that the ecosystem productivity of diverse grassland plant communities was more resistant, changing less during drought, and more resilient, recovering more quickly after drought, than that of depauperate communities. However, subsequent experimental tests produced mixed results. Here we use data from 46 experiments that manipulated grassland plant diversity to test whether biodiversity provides resistance during and resilience after climate events. We show that biodiversity increased ecosystem resistance for a broad range of climate events, including wet or dry, moderate or extreme, and brief or prolonged events. Across all studies and climate events, the productivity of low-diversity communities with one or two species changed by approximately 50% during climate events, whereas that of high-diversity communities with 16-32 species was more resistant, changing by only approximately 25%. By a year after each climate event, ecosystem productivity had often fully recovered, or overshot, normal levels of productivity in both high- and low-diversity communities, leading to no detectable dependence of ecosystem resilience on biodiversity. Our results suggest that biodiversity mainly stabilizes ecosystem productivity, and productivity-dependent ecosystem services, by increasing resistance to climate events. Anthropogenic environmental changes that drive biodiversity loss thus seem likely to decrease ecosystem stability, and restoration of biodiversity to increase it, mainly by changing the resistance of ecosystem productivity to climate events.
Williams, C. J. R.; Kniveton, D. R.; Layberry, R.
It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will
Casati, B.; Lefaivre, L.
Extreme weather events can cause large damages and losses, and have high societal and economical impacts. Climate model integrations predict increases in both frequency and intensity of extreme events under enhanced greenhouse conditions. Better understanding of the capabilities of climate models in representing the present climate extremes, joint with the analysis of the future climate projections for extreme events, can help to forewarn society from future high-impact events, and possibly better develop adaptation strategies. Extreme Value Theory (EVT) provides a well established and robust framework to analyse the behaviour of extreme weather events for the present climate and future projections. In this study a non-stationary model for Generalised Extreme Value (GEV) distributions is used to analyse the trend of the distributions of extreme precipitation and temperatures, in the context of a changing climate. The analysis is performed for the climate projections of the Canadian Regional Climate Model (CRCM), under a SRES A2 emission scenario, for annual, seasonal and monthly extremes, for 12 regions characterised by different climatologies over the North American domain. Significant positive trends for the location of the distributions are found in most regions, indicating an expected increase in extreme value intensities, whereas the scale (variability) and shape (tail values) of the extreme distributions seem not to vary significantly. Extreme events, such as intense convective precipitation, are often associated to small-scale features. The enhanced resolution of Regional Climate Models enables to better represent such extreme events, with respect to Global Climate Models. However the resolution of these models is sometimes still too coarse to reproduce realistic extremes. To address this representativeness issue, statistical downscaling of the CRCM projections is performed. The downscaling relation is obtained by comparing the GEV distributions for the CRCM
Turp, M. Tufan; Collu, Kamil; Deler, F. Busra; Ozturk, Tugba; Kurnaz, M. Levent
The Middle East is one of the most vulnerable regions to the impacts of climate change. Because of the importance of the region and its vulnerability to global climate change, the studies including the investigation of projected changes in the climate of the Middle East play a crucial role in order to struggle with the negative effects of climate change. This research points out the relationship between the climate change and climate extremes indices in the Middle East and it investigates the changes in the number of extreme events as described by the joint CCl/CLIVAR/JCOMM Expert Team (ET) on Climate Change Detection and Indices (ETCCDI). As part of the study, the regional climate model (RegCM4.4) of the Abdus Salam International Centre for Theoretical Physics (ICTP) is run to obtain future projection data. This research has been supported by Boǧaziçi University Research Fund Grant Number 10421.
Full Text Available In this paper, we study extreme values of non-stationary climatic phenomena. In the usually considered stationary case, the modelling of extremes is only based on the behaviour of the tails of the distribution of the remainder of the data set. In the non-stationary case though, it seems reasonable to assume that the temporal dynamics of the entire data set and that of extremes are closely related and thus all the available information about this link should be used in statistical studies of these events. We try to study how centered and normalized data which are closer to stationary data than the observation allows easier statistical analysis and to understand if we are very far from a hypothesis stating that the extreme events of centered and normed data follow a stationary distribution. The location and scale parameters used for this transformation (the central field, as well as extreme parameters obtained for the transformed data enable us to retrieve the trends in extreme events of the initial data set. Through non-parametric statistical methods, we thus compare a model directly built on the extreme events and a model reconstructed from estimations of the trends of the location and scale parameters of the entire data set and stationary extremes obtained from the centered and normed data set. In case of a correct reconstruction, we can clearly state that variations of the characteristics of extremes are well explained by the central field. Through these analyses we bring arguments to choose constant shape parameters of extreme distributions. We show that for the frequency of the moments of high threshold excesses (or for the mean of annual extremes, the general dynamics explains a large part of the trends on frequency of extreme events. The conclusion is less obvious for the amplitudes of threshold exceedances (or the variance of annual extremes – especially for cold temperatures, partly justified by the statistical tools used, which
van den Hurk, Bart; Wijngaard, Janet; Pappenberger, Florian; Bouwer, Laurens; Weerts, Albrecht; Buontempo, Carlo; Doescher, Ralf; Manez, Maria; Ramos, Maria-Helena; Hananel, Cedric; Ercin, Ertug; Hunink, Johannes; Klein, Bastian; Pouget, Laurent; Ward, Philip
The EU Roadmap on Climate Services can be seen as a result of convergence between the society's call for "actionable research", and the climate research community providing tailored data, information and knowledge. However, although weather and climate have clearly distinct definitions, a strong link between weather and climate services exists that is not explored extensively. Stakeholders being interviewed in the context of the Roadmap consider climate as a far distant long term feature that is difficult to consider in present-day decision taking, which is dominated by daily experience with handling extreme events. It is argued that this experience is a rich source of inspiration to increase society's resilience to an unknown future. A newly started European research project, IMPREX, is built on the notion that "experience in managing current day weather extremes is the best learning school to anticipate consequences of future climate". This paper illustrates possible ways to increase the link between information and services addressing weather and climate time scales by discussing the underlying concepts of IMPREX and its expected outcome.
Imole Ezekiel Gbode
Full Text Available Observed rainfall and temperature data for the period 1960–2007 were used to examine recent changes of extreme climate over Kano, located in the Sahelian region of Nigeria. The RClimDex software package was employed to generate nine important climate indices as defined by the Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI. For the entire period, the results show a warming trend, an increased number of cool nights, more warm days, and a strong increase in the number of warm spells. The rainfall indices show a slight increase in annual total rainfall, a decrease in the maximum number of consecutive wet days, and a significant increase in the number of extremely wet days. Such changes in climate may result in an increasing demand for domestic energy for cooling and a higher evaporation rate from water bodies and irrigated crop. These findings may give some guidance to politicians and planners in how to best cope with these extreme weather and climate events.
Thibault, Katherine M.; Brown, James H.
Extreme climatic events are predicted to increase in frequency and magnitude, but their ecological impacts are poorly understood. Such events are large, infrequent, stochastic perturbations that can change the outcome of entrained ecological processes. Here we show how an extreme flood event affected a desert rodent community that has been monitored for 30 years. The flood (i) caused catastrophic, species-specific mortality; (ii) eliminated the incumbency advantage of previously dominant species; (iii) reset long-term population and community trends; (iv) interacted with competitive and metapopulation dynamics; and (v) resulted in rapid, wholesale reorganization of the community. This and a previous extreme rainfall event were punctuational perturbations—they caused large, rapid population- and community-level changes that were superimposed on a background of more gradual trends driven by climate and vegetation change. Captured by chance through long-term monitoring, the impacts of such large, infrequent events provide unique insights into the processes that structure ecological communities. PMID:18303115
This paper focuses a synthesis of the works led within the framework of the French project ANR/Extraflo on the evolution of the daily (and infra daily) extreme rainfall in France. An important dataset of more than 900 series was used. It was shown that a majority of series presented a not significant upward trend in particular in Mediterranean area, in relation with various recent exceptional extreme events. An interesting way to characterize this evolution consists in identifying climatic co-variables associated to heavy rainfall events (weather patterns, average temperatures, flow of humidity) and in taking into account them with a non stationary POT model. The application of this method with climatic projections under scenario A2 from IPCC could lead to a possible increase on extreme precipitation quantiles on the horizon 2070. (authors)
van Eck, Christel Melissa; Waegeman, Willem; Papagiannopoulou, Christina; Verhoest, Niko; Depoorter, Mathieu; Regnier, Pierre; Friedlingstein, Pierre; Dolman, A. Johannes; de Jeu, Richard; Dorigo, Wouter; Miralles, Diego G.
Global warming is expected to increase the frequency and severity of droughts, extreme precipitation events and heatwaves. Recent studies have underlined the critical impacts of these extremes on the terrestrial carbon cycle, particularly on the dynamics of vegetation. Yet, the latest IPCC report reveals large uncertainties in extremes trends and biomass impacts. Conversely, new advances in satellite Earth observation have led to the recent development of consistent global historical records of crucial environmental and climatic variables - like surface soil moisture, soil water storage, terrestrial evaporation or vegetation water content. These datasets provide alternative means to unravel the processes driving past climate extremes, uncover the spatiotemporal scales at which these extremes operate and understand their impact on terrestrial biomass. The SAT-EX project (funded by BELSPO) recently raised with the purpose of exploring the potential of the state-of-art remote sensing datasets to study the causes and consequences of the spatiotemporal changes in wet, dry and warm spells over the past three decades. Core methodologies involve the analysis of satellite-based climate extreme indices and vegetation characteristics through a novel combination of machine learning methods, fingerprint identification approaches, and spatio-temporal clustering. First results will show how droughts, heatwaves and extreme rain events have changed in frequency and intensity since the '80s, and attribute these changes to on-going processes like the widening of the tropical belt, ocean-atmospheric teleconnections, the intensification of land-atmospheric feedbacks or the overall rise in greenhouse gasses (and expected acceleration of the hydrological cycle). A specific focus will be given on large-scale vegetation response to climate extremes throughout our analyses. Further phases in the project will involve the evaluation of IPCC Earth System Models on the basis of their skill to
Planton, S.; Deque, M.; Chauvin, F. [Meteo-France, Centre National de Recherches Meteorologiques/groupe d' Etude de l' Atmosphere Meteorologique (CNRM/GAME), 31 - Toulouse (France); Terray, L. [Centre Europeen de Recherches Avancees en Calcul Scientifique, 31 - Toulouse (France)
An overview of the expected change of climate extremes during this century due to greenhouse gases and aerosol anthropogenic emissions is presented. The most commonly used methodologies rely on the dynamical or statistical down-scaling of climate projections, performed with coupled atmosphere-ocean general circulation models. Either of dynamical or of statistical type, down-scaling methods present strengths and weaknesses, but neither their validation on present climate conditions, nor their potential ability to project the impact of climate change on extreme event statistics allows one to give a specific advantage to one of the two types. The results synthesized in the last IPCC report and more recent studies underline a convergence for a very likely increase in heat wave episodes over land surfaces, linked to the mean warming and the increase in temperature variability. In addition, the number of days of frost should decrease and the growing season length should increase. The projected increase in heavy precipitation events appears also as very likely over most areas and also seems linked to a change in the shape of the precipitation intensity distribution. The global trends for drought duration are less consistent between models and down-scaling methodologies, due to their regional variability. The change of wind-related extremes is also regionally dependent, and associated to a poleward displacement of the mid-latitude storm tracks. The specific study of extreme events over France reveals the high sensitivity of some statistics of climate extremes at the decadal time scale as a consequence of regional climate internal variability. (authors)
J. MARTINEZ; S. MERINO
The effect that climatic changes can exert on parasitic interactions represents a multifactor problem whose results are difficult to predict. The actual impact of changes will depend on their magnitude and the physiological tolerance of affected organisms. When the change is considered extreme (I.e. Unusual weather events that are at the extremes of the historical distribution for a given area), the probability of an alteration in an organisms' homeostasis increases dramatically. However, factors determining the altered dynamics of host-parasite interactions due to an extreme change are the same as those acting in response to changes of lower magnitude. Only a deep knowledge of these factors will help to produce more accurate predictive models for the effects of extreme changes on parasitic interactions. Extreme environmental conditions may affect pathogens directly when they include free-living stages in their life-cycles and indirectly through reduced resource availability for hosts and thus reduced ability to produce efficient anti-parasite defenses, or by effects on host density affecting transmission dynamics of diseases or the frequency of intraspecific contact. What are the consequences for host-parasite interactions? Here we summarize the present knowledge on three principal factors in determining host-parasite associations; biodiversity, population density and immunocompetence. In addition, we analyzed examples of the effects of environmental alteration of anthropogenic origin on parasitic systems because the effects are analogous to that exerted by an extreme climatic change.
Chen, Gang [Cornell Univ., Ithaca, NY (United States)
Mid-latitude extreme weather events are responsible for a large part of climate-related damage. Yet large uncertainties remain in climate model projections of heat waves, droughts, and heavy rain/snow events on regional scales, limiting our ability to effectively use these projections for climate adaptation and mitigation. These uncertainties can be attributed to both the lack of spatial resolution in the models, and to the lack of a dynamical understanding of these extremes. The approach of this project is to relate the fine-scale features to the large scales in current climate simulations, seasonal re-forecasts, and climate change projections in a very wide range of models, including the atmospheric and coupled models of ECMWF over a range of horizontal resolutions (125 to 10 km), aqua-planet configuration of the Model for Prediction Across Scales and High Order Method Modeling Environments (resolutions ranging from 240 km – 7.5 km) with various physics suites, and selected CMIP5 model simulations. The large scale circulation will be quantified both on the basis of the well tested preferred circulation regime approach, and very recently developed measures, the finite amplitude Wave Activity (FAWA) and its spectrum. The fine scale structures related to extremes will be diagnosed following the latest approaches in the literature. The goal is to use the large scale measures as indicators of the probability of occurrence of the finer scale structures, and hence extreme events. These indicators will then be applied to the CMIP5 models and time-slice projections of a future climate.
Europe witnessed a spate of record-breaking warm seasons during the 2000's. As illustrated by the devastating heat-wave of the summer 2003, these episodes induced strong societal and environmental impacts. Such occurrence of exceptional events over a relatively short time period raised up many questionings in the present context of climate change. In particular, can recent temperature extremes be considered as 'previews' of future climate conditions? Do they result from an increasing temperature variability? These questions constitute the main motivations of this thesis. Thus, our work aims to contribute to the understanding of physical mechanisms responsible for seasonal temperature extremes in Europe, in order to anticipate their future statistical characteristics. Involved processes are assessed by both statistical data-analysis of observations and climate projections and regional modeling experiments. First we show that while the inter-annual European temperature variability appears driven by disturbances in the North-Atlantic dynamics, the recent warming is likely to be dissociated with potential circulation changes. This inconsistency climaxes during the exceptionally mild autumn of 2006, whose temperature anomaly is only half explained by the atmospheric flow. Recent warm surface conditions in the North-Atlantic ocean seem to substantially contribute to the European warming in autumn-winter, through the establishment of advective and radiative processes. In spring-summer, since both advection by the westerlies and Atlantic warming are reduced, more local processes appear predominant (e.g. soil moisture, clouds, aerosols). Then the issue of future evolution of the relationship between North-Atlantic dynamics and European temperatures is addressed, based on climate projections of the International Panel on Climate Change. Multi-model analysis, using both flow-analogues and weather regimes methods, show that the inconsistency noticed over recent decades is
Timofeyeva, M. M.; Hollingshead, A.; Hilderbrand, D.; Mayes, B.; Hartley, T.; Kempf McGavock, N. M.; Lau, E.; Olenic, E. A.; Motta, B.; Bunge, R.; Brown, L. E.; Fritsch, F.
tornadoes, flash floods, storminess, extreme weather events, etc. LCAT will expand the suite of NWS climate products. The LCAT development utilizes NWS Operations and Services Improvement Process (OSIP) to document the field and user requirements, develop solutions, and prioritize resources. OSIP is a five work-stage process separated by four gate reviews. LCAT is currently at work-stage three: Research Demonstration and Solution Analysis. Gate 1 and 2 reviews identified LCAT as a high strategic priority project with a very high operational need. The Integrated Working Team, consisting of NWS field representatives, assists in tool function design and identification of LCAT operational deployment support.
Ma, Xuanlong; Huete, Alfredo; Moran, Susan; Ponce-Campos, Guillermo; Eamus, Derek
Amplification of the hydrologic cycle as a consequence of global warming is predicted to increase climate variability and the frequency and severity of droughts. Recent large-scale drought and flooding over numerous continents provide unique opportunities to understand ecosystem responses to climatic extremes. In this study, we investigated the impacts of the early 21st century extreme hydroclimatic variations in southeastern Australia on phenology and vegetation productivity using Moderate Resolution Imaging Spectroradiometer Enhanced Vegetation Index and Standardized Precipitation-Evapotranspiration Index. Results revealed dramatic impacts of drought and wet extremes on vegetation dynamics, with abrupt between year changes in phenology. Drought resulted in widespread reductions or collapse in the normal patterns of seasonality such that in many cases there was no detectable phenological cycle during drought years. Across the full range of biomes examined, we found semiarid ecosystems to exhibit the largest sensitivity to hydroclimatic variations, exceeding that of arid and humid ecosystems. This result demonstrated the vulnerability of semiarid ecosystems to climatic extremes and potential loss of ecosystem resilience with future mega-drought events. A skewed distribution of hydroclimatic sensitivity with aridity is of global biogeochemical significance because it suggests that current drying trends in semiarid regions will reduce hydroclimatic sensitivity and suppress the large carbon sink that has been reported during recent wet periods (e.g., 2011 La Niña).
The evaluation of precipitation extremes is a paramount challenging issue in climate sciences and there is a need of both assessing changes in climate projections and comparing climate model simulations with observations. To address these needs, a non-parametric approach specifically designed for extremes is here proposed. The method is tested and applied to observations and CMIP5 historical simulations and future projections (under the high emission scenario RCP8.5) over the Euro-Mediterranean region. Results support the existence of a scaling relationship among models and between models and observations in terms of conditional mean of the extremes. However, the rescaled tails of models’ precipitation show significant differences when compared with observations. Concerning future projections, models show an intensification of heavy precipitation (especially at the end of the 21st century) linked to a change in the conditional mean of extremes. More complex changes in the upper tails are not identified at the mid-century, while a lack of model agreement prevents drawing definitive conclusions for the end of the century. (letter)
Various social and economic systems are at risk from variability in weather conditions. A realization of this fact has prompted endogenous adaptations to cope with weather variability. Climate change may overwhelm existing adaptive strategies. These systems would experience this change from the secular trends in first-order and higher order statistics of climate parameters (e.g., mean biotemperature, intensity, and inter-arrival times of extreme events). Historically, different human activities have formally or informally incorporated adaptation to climate conditions. Activities such as agriculture are influenced strongly by weather, yet through a variety of mechanisms, impacts are ameliorated. Taking agriculture as an example of a central and substantive system, the authors' study presents response strategies of oranges production -- a crop currently affected greatly by weather conditions. Understanding the adaptation mechanisms used today can be used to examine the cost and effectiveness of adaptive actions to future climate change
Full Text Available Climate signal maps can be used to identify regions where robust climate changes can be derived from an ensemble of climate change simulations. Here, robustness is defined as a combination of model agreement and the significance of the individual model projections. Climate signal maps do not show all information available from the model ensemble, but give a condensed view in order to be useful for non-climate scientists who have to assess climate change impact during the course of their work. Three different ensembles of regional climate projections have been analyzed regarding changes of seasonal mean and extreme precipitation (defined as the number of days exceeding the 95th percentile threshold of daily precipitation for Germany, using climate signal maps. Although the models used and the scenario assumptions differ for the three ensembles (representative concentration pathway (RCP 4.5 vs. RCP8.5 vs. A1B, some similarities in the projections of future seasonal and extreme precipitation can be seen. For the winter season, both mean and extreme precipitation are projected to increase. The strength, robustness and regional pattern of this increase, however, depends on the ensemble. For summer, a robust decrease of mean precipitation can be detected only for small regions in southwestern Germany and only from two of the three ensembles, whereas none of them projects a robust increase of summer extreme precipitation.
Gaál, Ľ.; Beranová, R.; Hlavčová, K.; Kyselý, Jan
Roč. 2014, č. 943487 (2014), s. 1-14. ISSN 1687-9309 Institutional support: RVO:67179843 ; RVO:68378289 Keywords : precipitation extremes * regional climate models * climate change Subject RIV: EH - Ecology, Behaviour Impact factor: 0.946, year: 2014
Sørensen, Carlo Sass; Knudsen, Per; Broge, Niels;
We investigate effects of sea level rise and a change in precipitation pattern on coastal flooding hazards. Historic and present in situ and satellite data of water and groundwater levels, precipitation, vertical ground motion, geology,and geotechnical soil properties are combined with flood...... protection measures, topography, and infrastructure to provide a more complete picture of the water-related impact from climate change at an exposed coastal location. Results show that future sea extremes evaluated from extreme value statistics may, indeed, have a large impact. The integrated effects from...
Miller, N.L.; Hayhoe, K.; Jin, J.; Auffhammer, M.
Climate projections from three atmosphere-ocean climate models with a range of low to mid-high temperature sensitivity forced by the Intergovernmental Panel for Climate Change SRES higher, middle, and lower emission scenarios indicate that, over the 21st century, extreme heat events for major cities in heavily air-conditioned California will increase rapidly. These increases in temperature extremes are projected to exceed the rate of increase in mean temperature, along with increased variance. Extreme heat is defined here as the 90 percent exceedance probability (T90) of the local warmest summer days under the current climate. The number of extreme heat days in Los Angeles, where T90 is currently 95 F (32 C), may increase from 12 days to as many as 96 days per year by 2100, implying current-day heat wave conditions may last for the entire summer, with earlier onset. Overall, projected increases in extreme heat under the higher A1fi emission scenario by 2070-2099 tend to be 20-30 percent higher than those projected under the lower B1 emission scenario, ranging from approximately double the historical number of days for inland California cities (e.g. Sacramento and Fresno), up to four times for previously temperate coastal cities (e.g. Los Angeles, San Diego). These findings, combined with observed relationships between high temperature and electricity demand for air-conditioned regions, suggest potential shortfalls in transmission and supply during T90 peak electricity demand periods. When the projected extreme heat and peak demand for electricity are mapped onto current availability, maintaining technology and population constant only for demand side calculations, we find the potential for electricity deficits as high as 17 percent. Similar increases in extreme heat days are suggested for other locations across the U.S. southwest, as well as for developing nations with rapidly increasing electricity demands. Electricity response to recent extreme heat events, such
Full Text Available Regional decadal predictions have emerged in the past few years as a research field with high application potential, especially for extremes like heat and drought periods. However, up to now the prediction skill of decadal hindcasts, as evaluated with standard methods is moderate, and for extreme values even rarely investigated. In this study, we use hindcast data from a regional climate model (CCLM for 8 regions in Europe to construct time evolving climate networks and use the network correlation threshold (link strength as a predictor for heat periods. We show that the skill of the network measure to predict the low frequency dynamics of heat periods is similar to the one of the standard approach, with the potential of being even better in some regions.
Leonard, Michael; Westra, Seth; Phatak, Aloke; Lambert, Martin; van den Hurk, Bart; McInness, Kathleen; Risby, James; Schuster, Sandra; Jakob, Doerte; Stafford-Smith, Mark
Climate variables give rise to hazards such as cyclones, floods and fires where an extreme impact is the result of a combination of variables rather than any one variable being in an extreme state in isolation. The combination of variables is termed a compound event and the nature of any given compound event will depend upon the variety of physical variables, the range of spatial and temporal scales over which they are linked, the strength of dependence between processes, and the interest of the stakeholder in defining the impact. Modelling compound events is a large, complex and inter-disciplinary undertaking and to facilitate this task influence diagrams are proposed for better defining, mapping, analysing, modelling and communicating the behaviour of the compound event. Ultimately, the greater appreciation of compound events will lead to greater insight and a changed perspective on how impact risks are associated with climate related hazards.
Siegmund, J. F.; Wiedermann, M.; Donges, J. F.; Donner, R. V.
Ongoing climate change is known to cause an increase in the frequency and amplitude of local temperature and precipitation extremes in many regions of the Earth. While gradual changes in the climatological conditions are known to strongly influence plant flowering dates, the question arises if and how extremes specifically impact the timing of this important phenological phase. In this study, we systematically quantify simultaneities between meteorological extremes and the timing of flowering of four shrub species across Germany by means of event coincidence analysis, a novel statistical tool that allows assessing whether or not two types of events exhibit similar sequences of occurrences. Our systematic investigation supports previous findings of experimental studies by highlighting the impact of early spring temperatures on the flowering of wildlife plants. In addition, we find statistically significant indications for some long-term relations reaching back to the previous year.
Anttila-Hughes, J. K.
A variety of recent extreme climatic events are considered to be strong evidence that the climate is warming, but these incremental advances in certainty often seem ignored by non-scientists. I identify two unusual types of events that are considered to be evidence of climate change, announcements by NASA that the global annual average temperature has set a new record, and the sudden collapse of major polar ice shelves, and then conduct an event study to test whether news of these events changes investors' valuation of energy companies, a subset of firms whose future performance is closely tied to climate change. I find evidence that both classes of events have influenced energy stock prices since the 1990s, with record temperature announcements on average associated with negative returns and ice shelf collapses associated with positive returns. I identify a variety of plausible mechanisms that may be driving these differential responses, discuss implications for energy markets' views on long-term regulatory risk, and conclude that investors not only pay attention to scientifically significant climate events, but discriminate between signals carrying different information about the nature of climatic change.
Champion, Adrian; Hodges, Kevin; Bengtsson, Lennart
Extreme precipitation events have the potential of causing widespread damage and are a common issue to address for insurance companies. There are many challenges facing the prediction of extreme precipitation events, including the ability to forecast the intensity of the events with high-resolution forecast models and to determine the projected change in these events is in a warmer climate. This talk examines these two challenges from a storm's perspective. The floods during the summer of 2007 in the UK were caused by the presence of a persistent upper-level cut-off low providing a continuous moisture supply over the UK. This allowed the development of a series of convective systems embedded within the synoptic system, causing persistent extreme rainfall for several hours. A 12km and a 4km UK Met Office Limited Area Model (LAM) with ECMWF re-analysis boundary conditions was run to investigate whether the LAM was able to predict the intensities and distribution observed through raingauge and radar data. The results suggest that whilst the large-scale distribution of the rainfall is similar to that observed by the radar, the intensity of the rainfall does not equate to the raingauge observations. This intensity error is not reduced at the higher resolution, however the distribution is improved. The effect on the precipitation of synoptic scale events in a warmer climate has also been investigated. The TRACK software was used to track storms in the ECHAM5 T319 Global Climate Model (GCM) to determine whether the intensity and frequency of such events will change under the IPCC A1B warming scenario. These results were compared to the results from the T213 resolution run presented in Bengtsson et al (2009). The effect of a warming climate is for the number of extreme events to increase, and for the intensity, for the precipitation and vorticity fields, to increase. These are the same conclusions as for the T213 run. The effect of a warmer climate has a consistent
Frank, Dorothea; Reichstein, Markus; Bahn, Michael;
Extreme droughts, heat waves, frosts, precipitation, wind storms and other climate extremes may impact the structure, composition and functioning of terrestrial ecosystems, and thus carbon cycling and its feedbacks to the climate system. Yet, the interconnected avenues through which climate extre...... remote sensing vs. ground‐based observational case studies reveals that many regions in the (sub‐)tropics are understudied. Hence, regional investigations are needed to allow a global upscaling of the impacts of climate extremes on global carbon–climate feedbacks....
Bellprat, Omar; Doblas-Reyes, Francisco
Event attribution aims to estimate the role of an external driver after the occurrence of an extreme weather and climate event by comparing the probability that the event occurs in two counterfactual worlds. These probabilities are typically computed using ensembles of climate simulations whose simulated probabilities are known to be imperfect. The implications of using imperfect models in this context are largely unknown, limited by the number of observed extreme events in the past to conduct a robust evaluation. Using an idealized framework, this model limitation is studied by generating large number of simulations with variable reliability in simulated probability. The framework illustrates that unreliable climate simulations are prone to overestimate the attributable risk to climate change. Climate model ensembles tend to be overconfident in their representation of the climate variability which leads to systematic increase in the attributable risk to an extreme event. Our results suggest that event attribution approaches comprising of a single climate model would benefit from ensemble calibration in order to account for model inadequacies similarly as operational forecasting systems.
Prabhat, M.; Byna, S.; Paciorek, C.; Weber, G.; Wu, K.; Yopes, T.; Wehner, M. F.; Ostrouchov, G.; Pugmire, D.; Strelitz, R.; Collins, W.; Bethel, W.
We consider several challenging problems in climate that require quantitative analysis of very large data volumes generated by modern climate simulations. We demonstrate new software capable of addressing these challenges that is designed to exploit petascale platforms using state-of-the-art methods in high performance computing. Atmospheric rivers and Hurricanes are important classes of extreme weather phenomena. Developing analysis tools that can automatically detect these events in large climate datasets can provide us with invaluable information about the frequency of these events. Application of these tools to different climate model outputs can provide us with quality metrics that evaluate whether models produce this important class of phenomena and how the statistics of these events will likely vary in the future. In this work, we present an automatic technique for detecting atmospheric rivers. We use techniques from image processing and topological analysis to extract these features. We implement this technique in a massively parallel fashion on modern supercomputing platforms, and apply the resulting software to both observational data and various models from the CMIP-3 archive. We have successfully completed atmospheric river detections on 1TB of data on 10000 hopper cores in 10 seconds. For hurricane tracking, we have adapted code from GFDL to run in parallel on large datasets. We present results from the application of this code to some recent high resolution CAM5 simulations. Our code is capable of processing 1TB of data in 10 seconds. Extreme value analysis involves statistical techniques for estimating the probability of extreme events and variations in the probabilities over time and space. Because of their rarity, there is a high degree of uncertainty when estimating the behavior of extremes from data at any one location. We are developing a local likelihood approach to borrow strength from multiple locations, with uncertainty estimated using the
Ganguly, A. R.; Kodra, E. A.; Agrawal, A.; Banerjee, A.; Boriah, S.; Chatterjee, Sn.; Chatterjee, So.; Choudhary, A.; Das, D.; Faghmous, J.; Ganguli, P.; Ghosh, S.; Hayhoe, K.; Hays, C.; Hendrix, W.; Fu, Q.; Kawale, J.; Kumar, D.; Kumar, V.; Liao, W.; Liess, S.; Mawalagedara, R.; Mithal, V.; Oglesby, R.; Salvi, K.; Snyder, P. K.; Steinhaeuser, K.; Wang, D.; Wuebbles, D.
Extreme events such as heat waves, cold spells, floods, droughts, tropical cyclones, and tornadoes have potentially devastating impacts on natural and engineered systems and human communities worldwide. Stakeholder decisions about critical infrastructures, natural resources, emergency preparedness and humanitarian aid typically need to be made at local to regional scales over seasonal to decadal planning horizons. However, credible climate change attribution and reliable projections at more localized and shorter time scales remain grand challenges. Long-standing gaps include inadequate understanding of processes such as cloud physics and ocean-land-atmosphere interactions, limitations of physics-based computer models, and the importance of intrinsic climate system variability at decadal horizons. Meanwhile, the growing size and complexity of climate data from model simulations and remote sensors increases opportunities to address these scientific gaps. This perspectives article explores the possibility that physically cognizant mining of massive climate data may lead to significant advances in generating credible predictive insights about climate extremes and in turn translating them to actionable metrics and information for adaptation and policy. Specifically, we propose that data mining techniques geared towards extremes can help tackle the grand challenges in the development of interpretable climate projections, predictability, and uncertainty assessments. To be successful, scalable methods will need to handle what has been called "big data" to tease out elusive but robust statistics of extremes and change from what is ultimately small data. Physically based relationships (where available) and conceptual understanding (where appropriate) are needed to guide methods development and interpretation of results. Such approaches may be especially relevant in situations where computer models may not be able to fully encapsulate current process understanding, yet the
Dreesen, F. E.; Boeck, H. J. de; I. A. Janssens; Nijs, I.
The probability that plant communities undergo successive climate extremes increases under climate change. Exposure to an extreme event might elicit acclimatory responses and thereby greater resistance to a subsequent event, but might also reduce resistance if the recovery period is too short or resilience too low. Using experimental plant assemblages, we compared the effects of two successive extremes (either two drought extremes, two heat extremes or two drought + heat extremes) to those of...
S. D. Outten
Full Text Available Extreme winds cause vast amounts of damage every year and represent a major concern for numerous industries including construction, afforestation, wind energy and many others. Under a changing climate, the intensity and frequency of extreme events are expected to change, and accurate projections of these changes will be invaluable to decision makers and society as a whole. This work examines four regional climate model downscalings over Europe following the SRES A1B scenario from the "ENSEMBLE-based Predictions of Climate Changes and their Impacts" project (ENSEMBLES. It investigates the projected changes in the 50 yr return wind speeds and the associated uncertainties. This is accomplished by employing the peaks-over-threshold method with the use of the generalised Pareto distribution. The models show that, for much of Europe, the 50 yr return wind is projected to change by less than 2 m s−1, while the uncertainties associated with the statistical estimates are larger than this. In keeping with previous works in this field, the largest source of uncertainty is found to be the inter-model spread, with some locations showing differences in the 50 yr return wind of over 20 m s−1 between two different downscalings.
Beniston, Martin; Stephenson, David B.; Christensen, Ole B.; Ferro, Christopher A. T.; Frei, Christoph; Goyette, Stéphane; Halsnaes, Kirsten; Holt, Tom; Jylhä, Kirsti; Koffi, Brigitte; Palutikof, Jean; Schöll, Regina; Semmler, Tido; Woth, Katja
This paper presents an overview of changes in the extreme events that are most likely to affect Europe in forthcoming decades. A variety of diagnostic methods are used to determine how heat waves, heavy precipitation, drought, wind storms, and storm surges change between present (1961–90) and future (2071–2100) climate on the basis of regional climate model simulations produced by the PRUDENCE project. A summary of the main results follows. Heat waves – Regional surface warming causes the fre...
Schatz, Jason; Kucharik, Christopher J.
As climate change increases the frequency and intensity of extreme heat, cities and their urban heat island (UHI) effects are growing, as are the urban populations encountering them. These mutually reinforcing trends present a growing risk for urban populations. However, we have limited understanding of urban climates during extreme temperature episodes, when additional heat from the UHI may be most consequential. We observed a historically hot summer and historically cold winter using an array of up to 150 temperature and relative humidity sensors in and around Madison, Wisconsin, an urban area of population 402 000 surrounded by lakes and a rural landscape of agriculture, forests, wetlands, and grasslands. In the summer of 2012 (third hottest since 1869), Madison’s urban areas experienced up to twice as many hours ⩾32.2 °C (90 °F), mean July TMAX up to 1.8 °C higher, and mean July TMIN up to 5.3 °C higher than rural areas. During a record setting heat wave, dense urban areas spent over four consecutive nights above the National Weather Service nighttime heat stress threshold of 26.7 °C (80 °F), while rural areas fell below 26.7 °C nearly every night. In the winter of 2013-14 (coldest in 35 years), Madison’s most densely built urban areas experienced up to 40% fewer hours ⩽-17.8 °C (0 °F), mean January TMAX up to 1 °C higher, and mean January TMIN up to 3 °C higher than rural areas. Spatially, the UHI tended to be most intense in areas with higher population densities. Temporally, both daytime and nighttime UHIs tended to be slightly more intense during more-extreme heat days compared to average summer days. These results help us understand the climates for which cities must prepare in a warming, urbanizing world.
Samuels, R.; Smiatek, G.; Krichak, S.; Kunstmann, H.; Alpert, P.
Understanding changing trends and frequency of extreme rainfall and temperature events is extremely important for optimal planning in many sectors, including agriculture, water resource management, health, and even economics. For people living in the Jordan River region of the Middle East such changes can have immediate devastating impacts as water resources are already scarce and overexploited and summer temperatures in the desert regions can reach 45°C or higher. Understanding shifts in frequency and intensity of extreme events can provide crucial information for planning and adaptation. In this paper we present results from regional climate model simulations with RegCM3 and MM5 centered on the eastern Mediterranean region. Our analysis focuses on changes in extreme temperature and rainfall events. We show that maximum daily summer temperature is expected to increase by between 2.5°C and 3°C, with an increase in warm spell length. Precipitation extremes are expected to increase with longer dry spells, shorter wet spells, and increases in heavy rainfall. Model agreement for the control period 1961-1990 is higher in the southern region than in the north, perhaps because of the complex topography, suggesting that even small differences in spatial scale play an important role. In addition, we notice that the chosen global model plays an important role in determining future temperature trends, while the choice of regional climate model is critical for understanding how precipitation is expected to evolve.
Ying Zhang; Jincui Wang; Jihong Jing; Jichao Sun
The North China Plain (NCP) is one of the water shortage areas of China. Lack of water resources restricted the economic and social development of North China area and resulted in deterio-ration of ecosystem and natural environment. Influenced by the climate change and human activities, the water circulation of NCP was largely changed and the crisis of water resources was aggravated. Therefore, it is important to study the features of the extreme climate and the response mechanism of groundwater to climate change. We analyzed the trend of climate change and extreme climate features in the past 60 years based on the monitoring data of meteorological stations. And then the response characteristics of groundwater to climate change were discussed. The average temperature of NCP was in an obviously upward trend. The overall precipitation variation was in a downward trend. The cli-mate change in this area showed a warming-drying trend. The intensity of extreme precipitation dis-played a trend of declining and then increasing from north to south as well as declining from eastern coastal plain to the piedmont plain. Grey correlation degree analysis indicated that groundwater depth had a close relationship with precipitation and human activities in NCP. The response of groundwater level to precipitation differed from the piedmont alluvial-pluvial plain to the coastal plain. The response was more obvious in the coastal plain than the piedmont alluvial-pluvial plain and the middle plain. The precipitation influenced the groundwater depth both directly and indirectly. Under the condition of extreme precipitation, the impact would aggravate, in the forms of rapid or lag raise of groundwater levels.
Konstantinov, Pavel; Akhmetova, Alina
Urban Heat Island (UHI) phenomenon is well known in scientific literature since first half of the 19th century . By now a wide number of world capitals is described from climatological point of view, especially in mid-latitudes. In beginning of XXI century new studies focus on heat island of tropical cities. However dynamics UHI in extreme continental climates is insufficiently investigated, due to the fact that there isn't large cities in Europe and Northern America within that climate type. In this paper we investigate seasonal and diurnal dynamics UHI intensity for Astana, capital city of Kazakhstan (population larger than 835 000 within the city) including UHI intensity changes on different time scales. Now (since 1998) Astana is the second coldest capital city in the world after Ulaanbaatar, Mongolia  For this study we use the UHI investigation technology, described in . According to this paper, we selected three stations: one located into city in high and midrise buildings area (including extensive lowrise and high-energy industrial - LCZ classification) and two others located in rural site (sparsely built or open-set and lightweight lowrise according LCZ classification). Also these stations must be close by distance (less than 100 km) and altitude. Therefore, first for Astana city were obtained numerical evaluations for UHI climate dynamics, UHI dependence of synoptic situations and total UHI climatology on monthly and daily averages. References: 1.Howard, L. (1833) The Climate of London, Deduced from Meteorological Observations. Volume 2, London. 2.Kukanova E.A., Konstantinov P.I. An urban heat islands climatology in Russia and linkages to the climate change In Geophysical Research Abstracts, volume 16 of EGU General Assembly, pages EGU2014-10833-1, Germany, 2014. Germany. 3.www.pogoda.ru.net
Design of urban drainage structures should include the climatic changes anticipated over the technical lifetime of the system. In Northern Europe climate changes implies increasing occurrences of extreme rainfall. Three approaches to quantify the impact of climate changes on extreme rainfall are ...
Erkaev, N V; Odert, P; Kulikov, Yu N; Kislyakova, K G
By considering martian-like planetary embryos inside the habitable zone of solar-like stars we study the behavior of the hydrodynamic atmospheric escape of hydrogen for small values of the Jeans escape parameter $\\beta < 3$, near the base of the thermosphere, that is defined as a ratio of the gravitational and thermal energy. Our study is based on a 1-D hydrodynamic upper atmosphere model that calculates the volume heating rate in a hydrogen dominated thermosphere due to the absorption of the stellar soft X-ray and extreme ultraviolet (XUV) flux. We find that when the $\\beta$ value near the mesopause/homopause level exceeds a critical value of $\\sim$2.5, there exists a steady hydrodynamic solution with a smooth transition from subsonic to supersonic flow. For a fixed XUV flux, the escape rate of the upper atmosphere is an increasing function of the temperature at the lower boundary. Our model results indicate a crucial enhancement of the atmospheric escape rate, when the Jeans escape parameter $\\beta$ decr...
Chu, Pao-Shin; Zhao, Xin
This article reviews Bayesian analysis methods applied to extreme climatic data. We particularly focus on applications to three different problems related to extreme climatic events including detection of abrupt regime shifts, clustering tropical cyclone tracks, and statistical forecasting for seasonal tropical cyclone activity. For identifying potential change points in an extreme event count series, a hierarchical Bayesian framework involving three layers - data, parameter, and hypothesis - is formulated to demonstrate the posterior probability of the shifts throughout the time. For the data layer, a Poisson process with a gamma distributed rate is presumed. For the hypothesis layer, multiple candidate hypotheses with different change-points are considered. To calculate the posterior probability for each hypothesis and its associated parameters we developed an exact analytical formula, a Markov Chain Monte Carlo (MCMC) algorithm, and a more sophisticated reversible jump Markov Chain Monte Carlo (RJMCMC) algorithm. The algorithms are applied to several rare event series: the annual tropical cyclone or typhoon counts over the central, eastern, and western North Pacific; the annual extremely heavy rainfall event counts at Manoa, Hawaii; and the annual heat wave frequency in France. Using an Expectation-Maximization (EM) algorithm, a Bayesian clustering method built on a mixture Gaussian model is applied to objectively classify historical, spaghetti-like tropical cyclone tracks (1945-2007) over the western North Pacific and the South China Sea into eight distinct track types. A regression based approach to forecasting seasonal tropical cyclone frequency in a region is developed. Specifically, by adopting large-scale environmental conditions prior to the tropical cyclone season, a Poisson regression model is built for predicting seasonal tropical cyclone counts, and a probit regression model is alternatively developed toward a binary classification problem. With a non
Ionita-Scholz, Monica; Grosfeld, Klaus; Lohmann, Gerrit; Scholz, Patrick
The potential increase of temperature extremes under climate change is a major threat to society, as temperature extremes have a deep impact on environment, hydrology, agriculture, society and economy. Hence, the analysis of the mechanisms underlying their occurrence, including their relationships with the large-scale atmospheric circulation and sea ice concentration, is of major importance. At the same time, the decline in Arctic sea ice cover during the last 30 years has been widely documented and it is clear that this change is having profound impacts at regional as well as planetary scale. As such, this study aims to investigate the relation between the autumn regional sea ice concentration variability and cold winters in Europe, as identified by the numbers of cold nights (TN10p), cold days (TX10p), ice days (ID) and consecutive frost days (CFD). We analyze the relationship between Arctic sea ice variation in autumn (September-October-November) averaged over eight different Arctic regions (Barents/Kara Seas, Beaufort Sea, Chukchi/Bering Seas, Central Arctic, Greenland Sea, Labrador Sea/Baffin Bay, Laptev/East Siberian Seas and Northern Hemisphere) and variations in atmospheric circulation and climate extreme indices in the following winter season over Europe using composite map analysis. Based on the composite map analysis it is shown that the response of the winter extreme temperatures over Europe is highly correlated/connected to changes in Arctic sea ice variability. However, this signal is not symmetrical for the case of high and low sea ice years. Moreover, the response of temperatures extreme over Europe to sea ice variability over the different Arctic regions differs substantially. The regions which have the strongest impact on the extreme winter temperature over Europe are: Barents/Kara Seas, Beaufort Sea, Central Arctic and the Northern Hemisphere. For the years of high sea ice concentration in the Barents/Kara Seas there is a reduction in the number
Min, Seung-Ki; Son, Seok-Woo; Seo, Kyong-Hwan; Kug, Jong-Seong; An, Soon-Il; Choi, Yong-Sang; Jeong, Jee-Hoon; Kim, Baek-Min; Kim, Ji-Won; Kim, Yeon-Hee; Lee, June-Yi; Lee, Myong-In
Weather and climate extremes exert devastating influence on human society and ecosystem around the world. Recent observations show increase in frequency and intensity of climate extremes around the world including East Asia. In order to assess current status of the observed changes in weather and climate extremes and discuss possible mechanisms, this study provides an overview of recent analyses on such extremes over Korea and East Asia. It is found that the temperature extremes over the Korean Peninsula exhibit long-term warming trends with more frequent hot events and less frequent cold events, along with sizeable interannual and decadal variabilities. The comprehensive review on the previous literature further suggests that the weather and climate extremes over East Asia can be affected by several climate factors of external and internal origins. It has been assessed that greenhouse warming leads to increase in warm extremes and decrease in cold extremes over East Asia, but recent Arctic sea-ice melting and associated warming tends to bring cold snaps to East Asia during winter. Internal climate variability such as tropical intraseasonal oscillation and El Niño-Southern Oscillation can also exert considerable impacts on weather and climate extremes over Korea and East Asia. It is, however, noted that our current understanding is far behind to estimate the effect of these climate factors on local weather and climate extremes in a quantitative sense.
The economy of climate policy is characterized by notions as cost-benefit analysis, optimal policy and optimal timing. It is argued that the use of such notions reflects an unjustified optimism with respect to the contribution of economic science to the discussion on climate policy. The complexity of the biosphere and the uncertainty about climatic change, as well as their socio-economic consequences, are extensive. Another economic approach of the climate problem is suggested, based on complexity and historical justice. 12 refs
Schubert, Siegfried D.; Lim, Young-Kwon
basic mechanisms by which extremes vary is incomplete. As noted in IPCC (2007), Incomplete global data sets and remaining model uncertainties still restrict understanding of changes in extremes and attribution of changes to causes, although understanding of changes in the intensity, frequency and risk of extremes has improved. Separating decadal and other shorter-term variability from climate change impacts on extremes requires a better understanding of the processes responsible for the changes. In particular, the physical processes linking sea surface temperature changes to regional climate changes, and a basic understanding of the inherent variability in weather extremes and how that is impacted by atmospheric circulation changes at subseasonal to decadal and longer time scales, are still inadequately understood. Given the fundamental limitations in the time span and quality of global observations, substantial progress on these issues will rely increasingly on improvements in models, with observations continuing to play a critical role, though less as a detection tool, and more as a tool for addressing physical processes, and to insure the quality of the climate models and the verisimilitude of the simulations (CCSP SAP 1.3, 2008).
Kyselý, Jan; Gaál, Ladislav; Beranová, Romana; Plavcová, Eva
Roč. 104, 3-4 (2011), s. 529-542. ISSN 0177-798X R&D Projects: GA ČR GAP209/10/2265 Grant ostatní: European Commission(XE) 505539 Institutional research plan: CEZ:AV0Z30420517 Keywords : precipitation extremes * regional climate models * ENSEMBLES * climate change * region-of-influence method Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.942, year: 2011 http://www.springerlink.com/content/95wj1140307nu5k7/fulltext.pdf
Fonseca, P. A. M.
Bacterial diarrheal diseases have a high incidence rate during and after flooding episodes. In the Brazilian Amazon, flood extreme events have become more frequent, leading to high incidence rates for infant diarrhea. In this study we aimed to find a statistical association between rainfall, river levels and diarrheal diseases in children under 5, in the river Acre basin, in the State of Acre (Brazil). We also aimed to identify the time-lag and annual season of extreme rainfall and flooding in different cities in the water basin. The results using Tropical Rainfall Measuring Mission (TRMM) Satellite rainfall data show robustness of these estimates against observational stations on-ground. The Pearson coefficient correlation results (highest 0.35) indicate a time-lag, up to 4 days in three of the cities in the water-basin. In addition, a correlation was also tested between monthly accumulated rainfall and the diarrheal incidence during the rainy season (DJF). Correlation results were higher, especially in Acrelândia (0.7) and Brasiléia and Epitaciolândia (0.5). The correlation between water level monthly averages and diarrheal diseases incidence was 0.3 and 0.5 in Brasiléia and Epitaciolândia. The time-lag evidence found in this paper is critical to inform stakeholders, local populations and civil defense authorities about the time available for preventive and adaptation measures between extreme rainfall and flooding events in vulnerable cities. This study was part of a pilot application in the state of Acre of the PULSE-Brazil project (http://www.pulse-brasil.org/tool/), an interface of climate, environmental and health data to support climate adaptation. The next step of this research is to expand the analysis to other climate variables on diarrheal diseases across the whole Brazilian Amazon Basin and estimate the relative risk (RR) of a child getting sick. A statistical model will estimate RR based on the observed values and seasonal forecasts (higher
Sorensen, Carlo; Knudsen, Per; Broge, Niels; Molgaard, Mads; Andersen, Ole
We investigate effects of sea level rise and a change in precipitation pattern on coastal flooding hazards. Historic and present in situ and satellite data of water and groundwater levels, precipitation, vertical ground motion, geology, and geotechnical soil properties are combined with flood protection measures, topography, and infrastructure to provide a more complete picture of the water-related impact from climate change at an exposed coastal location. Results show that future sea extremes evaluated from extreme value statistics may, indeed, have a large impact. The integrated effects from future storm surges and other geo- and hydro-parameters need to be considered in order to provide for the best protection and mitigation efforts, however. Based on the results we present and discuss a simple conceptual model setup that can e.g. be used for 'translation' of regional sea level rise evidence and projections to concrete impact measures. This may be used by potentially affected stakeholders -often working in different sectors and across levels of governance, in a common appraisal of the challenges faced ahead. The model may also enter dynamic tools to evaluate local impact as sea level research advances and projections for the future are updated.
Frank, Dorothea; Reichstein, Markus; Bahn, Michael; Thonicke, Kirsten; Frank, David; Mahecha, Miguel D; Smith, Pete; van der Velde, Marijn; Vicca, Sara; Babst, Flurin; Beer, Christian; Buchmann, Nina; Canadell, Josep G; Ciais, Philippe; Cramer, Wolfgang; Ibrom, Andreas; Miglietta, Franco; Poulter, Ben; Rammig, Anja; Seneviratne, Sonia I; Walz, Ariane; Wattenbach, Martin; Zavala, Miguel A; Zscheischler, Jakob
Extreme droughts, heat waves, frosts, precipitation, wind storms and other climate extremes may impact the structure, composition and functioning of terrestrial ecosystems, and thus carbon cycling and its feedbacks to the climate system. Yet, the interconnected avenues through which climate extremes drive ecological and physiological processes and alter the carbon balance are poorly understood. Here, we review the literature on carbon cycle relevant responses of ecosystems to extreme climatic events. Given that impacts of climate extremes are considered disturbances, we assume the respective general disturbance-induced mechanisms and processes to also operate in an extreme context. The paucity of well-defined studies currently renders a quantitative meta-analysis impossible, but permits us to develop a deductive framework for identifying the main mechanisms (and coupling thereof) through which climate extremes may act on the carbon cycle. We find that ecosystem responses can exceed the duration of the climate impacts via lagged effects on the carbon cycle. The expected regional impacts of future climate extremes will depend on changes in the probability and severity of their occurrence, on the compound effects and timing of different climate extremes, and on the vulnerability of each land-cover type modulated by management. Although processes and sensitivities differ among biomes, based on expert opinion, we expect forests to exhibit the largest net effect of extremes due to their large carbon pools and fluxes, potentially large indirect and lagged impacts, and long recovery time to regain previous stocks. At the global scale, we presume that droughts have the strongest and most widespread effects on terrestrial carbon cycling. Comparing impacts of climate extremes identified via remote sensing vs. ground-based observational case studies reveals that many regions in the (sub-)tropics are understudied. Hence, regional investigations are needed to allow a global
Sima, Mihaela; Micu, Dana; Dragota, Carmen-Sofia; Mihalache, Sorin
The Baia Mare Urban System is located in the north-western part of Romania, with around 200,000 inhabitants and represents one of the most important former mining areas in the country, whose socioeconomic profile and environmental conditions have greatly changed over the last 20 years during the transition and post-transition period. Currently the mining is closed in the area, but the historical legacy of this activity has implications in terms of economic growth, social and cultural developments and environmental quality. Baia Mare city lies in an extended depression, particularly sheltered by the mountain and hilly regions located in the north and respectively, in the south-south-eastern part of it, which explains the high frequency of calm conditions and low airstream channeling occurrences. This urban system has a typically moderate temperate-continental climate, subject to frequent westerly airflows (moist), which moderate the thermal regime (without depicting severe extremes, both positive and negative) and enhance the precipitation one (entailing a greater frequency of wet extremes). During the reference period (1971-2000), the climate change signal in the area is rather weak and not statistically significant. However, since the mid 1980s, the warming signal became more evident from the observational data (Baia Mare station), showing a higher frequency of dry spells and positive extremes. The modelling experiments covering the 2021-2050 time horizon using regional (RM5.1/HadRM3Q0/RCA3) and global (ARPEGE/HadCM3Q0/BCM/ECHAM5) circulation models carried out within the ECLISE FP7 project suggest an ongoing temperature rise, associated to an intensification of temperature and precipitation extremes. In this context, the aim of this study was to evaluate how the local authorities consider and include climate change in their activity, as well as in the development plans (e.g. territorial, economic and social development plans). Individual interviews have been
Martel, Jean-Luc; Brissette, François; Chen, Jie
Frequency analysis has been widely used for the inference of flood magnitude and rainfall intensity required in engineering design. However, this inference is based on the concept of stationarity. How accurate is it when taking into account climate variability (i.e. both internal- and externally-forced variabilities)? Even in the absence of human-induced climate change, the short temporal horizon of the historical records renders this task extremely difficult to accomplish. To overcome this situation, large ensembles of simulations from a single climate model can be used to assess the impact of climate variability on precipitation and streamflow extremes. Thus, the objective of this project is to determine the reliability of return period estimates using the CanESM2 large ensemble. The spring flood annual maxima metric over snowmelt-dominated watersheds was selected to take into account the limits of global circulation models to properly simulate convective precipitation. The GR4J hydrological model coupled with the CemaNeige snow model was selected and calibrated using gridded observation datasets on snowmelt-dominated watersheds in Quebec, Canada. Using the hydrological model, streamflows were simulated using bias corrected precipitation and temperature data from the 50 members of CanESM2. Flood frequency analyses on the spring flood annual maxima were then computed using the Gumbel distribution with a 90% confidence interval. The 20-year return period estimates were then compared to assess the impact of natural climate variability over the 1971-2000 return period. To assess the impact of global warming, this methodology was then repeated for three time slices: reference period (1971-2000), near future (2036-2065) and far future (2071-2100). Over the reference period results indicate that the relative error between the return period estimates of two members can be up to 25%. Regarding the near future and far future periods, natural climate variability of extreme
Puma, Michael J.; Cook, Benjamin I.; Krakauer, Nir; Gentine, Pierre; Nazarenka, Larissa; Kelly, Maxwell; Wada, Yoshihide
Widespread irrigation alters regional climate through changes to the energy and water budgets of the land surface. Within general circulation models, simulation studies have revealed significant changes in temperature, precipitation, and other climate variables. Here we investigate the feedbacks of irrigation with a focus on daily extremes at the global scale. We simulate global climate for the year 2000 with and without irrigation to understand irrigation-induced changes. Our simulations reveal shifts in key climate-extreme metrics. These findings indicate that land cover and land use change may be an important contributor to climate extremes both locally and in remote regions including the low-latitudes.
Park, Changyong; Min, Seung-Ki; Lee, Donghyun; Cha, Dong-Hyun; Suh, Myoung-Seok; Kang, Hyun-Suk; Hong, Song-You; Lee, Dong-Kyou; Baek, Hee-Jeong; Boo, Kyung-On; Kwon, Won-Tae
In this study, five regional climate models (RCMs) participating in the CORDEX-East Asia project (HadGEM3-RA, RegCM4, SNU-MM5, SNU-WRF, and YSU-RSM) are evaluated in terms of their performances in simulating the climatology of summer extremes in East Asia. Seasonal maxima of daily mean temperature and precipitation are analyzed using the generalized extreme value method. RCMs show systematic bias patterns in both seasonal means and extremes. A cold bias is located along the coast, whereas a warm bias occurs in northern China. Overall, wet bias occurs in East Asia, but with a substantial dry bias centered in South Korea. This dry bias appears to be related to the colder ocean surface around South Korea, positioning the monsoonal front further south compared to observations. Taylor diagram analyses reveal that the models simulate temperature means more accurately compared to extremes because of the higher spatial correlation, whereas precipitation extremes are simulated better than their means because of the higher spatial variability. The latter implies that extreme rainfall events can be captured more accurately by RCMs compared to the driving GCM despite poorer simulation of mean rainfall. Inter-RCM analysis indicates a close relationship between the means and extremes in terms of model skills, but it does not show a clear relationship between temperature and precipitation. Sub-regional analysis largely supports the mean-extreme skill relationship. Analyses of frequency and intensity distributions of daily data for three selected sub-regions suggest that overall shifts of temperature distribution and biases in moderate-heavy precipitations contribute importantly to the seasonal mean biases.
Several issues relating to insurance and the damage costs of climate change are discussed. It is argued that the option of insuring climate change is severely limited because the associated damages are hardly quantifiable and little diversifiable; in addition, binding contracts are a problem on long time scales and in an international context. Hedging, consumption smoothing over time, precautionary investments and liability are not to be presented under the heading of insurance, not only because this unnecessarily and confusingly expands the traditional definition of insurance, but also because this could create a false sense of security. The impact of climate change on the profitability of the commercial insurance sector is not likely to be severe, as the insurance companies are capable of shifting changed risks to the insured, provided that they are properly and timely informed on the consequences of climate change. (author)
Extreme heat stress during the crop reproductive period can be critical for crop productivity. Projected changes in the frequency and severity of extreme climatic events are expected to negatively impact crop yields and global food production. This study applies the global crop model PEGASUS to quantify, for the first time at the global scale, impacts of extreme heat stress on maize, spring wheat and soybean yields resulting from 72 climate change scenarios for the 21st century. Our results project maize to face progressively worse impacts under a range of RCPs but spring wheat and soybean to improve globally through to the 2080s due to CO2 fertilization effects, even though parts of the tropic and sub-tropic regions could face substantial yield declines. We find extreme heat stress at anthesis (HSA) by the 2080s (relative to the 1980s) under RCP 8.5, taking into account CO2 fertilization effects, could double global losses of maize yield (ΔY = −12.8 ± 6.7% versus − 7.0 ± 5.3% without HSA), reduce projected gains in spring wheat yield by half (ΔY = 34.3 ± 13.5% versus 72.0 ± 10.9% without HSA) and in soybean yield by a quarter (ΔY = 15.3 ± 26.5% versus 20.4 ± 22.1% without HSA). The range reflects uncertainty due to differences between climate model scenarios; soybean exhibits both positive and negative impacts, maize is generally negative and spring wheat generally positive. Furthermore, when assuming CO2 fertilization effects to be negligible, we observe drastic climate mitigation policy as in RCP 2.6 could avoid more than 80% of the global average yield losses otherwise expected by the 2080s under RCP 8.5. We show large disparities in climate impacts across regions and find extreme heat stress adversely affects major producing regions and lower income countries. (paper)
The Earth has to face more and more devastating extreme events. Between 1970 and 2009, at the worldwide scale, the 25 most costly catastrophes all took place after 1987, and for more than half of them after 2001. Among these 25 catastrophes, 23 were linked to climate conditions. France was not spared: the December 1999 storms led to 88 deaths, deprived 3.5 million households of electricity and costed more than 9 billion euros. The 2003 heat wave led to about 15000 supernumerary deaths between August 1 and August 20. The recent Xynthia storm, with its flood barrier ruptures, provoked 53 deaths in addition to many other tragedies that took place in areas liable to flooding. In the present day context of climate change, we know that we must be prepared to even more dangerous events, sometimes unexpected before. These events can have amplified effects because of the urban development, the overpopulation of coastal areas and the anthropization of natural environments. They represent real 'poverty traps' for the poorest countries of the Earth. The anticipation need is real but is our country ready to answer it? Does it have a sufficient contribution to international actions aiming at reducing risks? Is his scientific information suitable? France is not less vulnerable than other countries. It must reinforce its prevention, its response and resilience capacities in the framework of integrated policies of catastrophes risk management as well as in the framework of climate change adaptation plans. This reinforcement supposes the development of vigilance systems with a better risk coverage and benefiting by the advances gained in the meteorology and health domains. It supposes a town and country planning allowing to improve the viability of ecological and social systems - in particular by protecting their diversity. Finally, this reinforcement requires inciting financial coverage solutions for catastrophes prevention and for their management once they have taken place. A
Hauber, Eva K.; Donner, Reik V.
In the context of ongoing climate change, extremes are likely to increase in magnitude and frequency. One of the most important consequences of these changes is that the associated ecological risks and impacts are potentially rising as well. In order to better anticipate and understand these impacts, it therefore becomes more and more crucial to understand the general connection between climate extremes and the response and functionality of ecosystems. Among other region of the world, Europe presents an excellent test case for studies concerning the interaction between climate and biosphere, since it lies in the transition region between cold polar and warm tropical air masses and thus covers a great variety of different climatic zones and associated terrestrial ecosystems. The large temperature differences across the continent make this region particularly interesting for investigating the effects of climate change on biosphere-climate interactions. However, previously used methods for defining an extreme event typically disregard the necessity of taking seasonality as well as seasonal variance appropriately into account. Furthermore, most studies have focused on the impacts of individual extreme events instead of considering a whole inventory of extremes with their respective spatio-temporal extents. In order to overcome the aforementioned research gaps, this work introduces a new approach to studying climate-biosphere interactions associated with extreme events, which comprises three consecutive steps: (1) Since Europe exhibits climatic conditions characterized by marked seasonality, a novel method is developed to define extreme events taking into account the seasonality in all quantiles of the probability distribution of the respective variable of interest. This is achieved by considering kernel density estimates individually for each observation date during the year, including the properly weighted information from adjacent dates. By this procedure, we obtain
Steed, Chad A [ORNL; Evans, Katherine J [ORNL; Harney, John F [ORNL; Jewell, Brian C [ORNL; Shipman, Galen M [ORNL; Smith, Brian E [ORNL; Thornton, Peter E [ORNL; Williams, Dean N. [Lawrence Livermore National Laboratory (LLNL)
In this paper, we introduce a Web-based visual analytics framework for democratizing advanced visualization and analysis capabilities pertinent to large-scale earth system simulations. We address significant limitations of present climate data analysis tools such as tightly coupled dependencies, ineffi- cient data movements, complex user interfaces, and static visualizations. Our Web-based visual analytics framework removes critical barriers to the widespread accessibility and adoption of advanced scientific techniques. Using distributed connections to back-end diagnostics, we minimize data movements and leverage HPC platforms. We also mitigate system dependency issues by employing a RESTful interface. Our framework embraces the visual analytics paradigm via new visual navigation techniques for hierarchical parameter spaces, multi-scale representations, and interactive spatio-temporal data mining methods that retain details. Although generalizable to other science domains, the current work focuses on improving exploratory analysis of large-scale Community Land Model (CLM) and Community Atmosphere Model (CAM) simulations.
Cho, K.; Park, B. K.; E-hyung, P.; Gong, Y.; Kim, H. K.; Park, S.; Min, S. K.; Yoo, H. D.
Recently, extreme weather/climate events such as heat waves, flooding/droughts etc. have been increasing in frequency and intensity under climate change over the world. Also, they can have substantial impacts on ecosystem and human society (agriculture, health, and economy) of the affected regions. According to future projections of climate, extreme weather and climate events in Korea are expected to occure more frequently with stronger intensity over the 21st century. For the better long range forecast, it is also fundamentally ruquired to develop a supporting system in terms of extreme weather and climate events including forequency and trend. In this context, the KMA (Korea Meteorological Administration) has recently initiated a development of the extreme climate monintoring and early warning system for long range forecast, which consists of three sub-system components; (1) Real-time climate monitoring system, (2) Ensemble prediction system, and (3) Mechanism analysis and display system for climate extremes. As a first step, a pilot system has been designed focusing on temperature extremes such heat waves and cold snaps using daily, monthly and seasonal observations and model prediction output on the global, regional and national levels. In parallel, the skills of the KMA long range prediction system are being evaluated comprehensively for weather and climate extremes, for which varous case studies are conducted to better understand the observed variations of extrem climates and responsible mechanisms and also to assess predictability of the ensemble prediction system for extremes. Details in the KMA extreme climate monitoring and early warning system will be intorduced and some preliminary results will be discussed for heat/cold waves in Korea.
Willems, P.; Olsson, J.; Arnbjerg-Nielsen, Karsten;
Impacts of Climate Change on Rainfall Extremes and Urban Drainage Systems provides a state-of-the-art overview of existing methodologies and relevant results related to the assessment of the climate change impacts on urban rainfall extremes as well as on urban hydrology and hydraulics. This overv...
Gregersen, Ida Bülow; Sunyer Pinya, Maria Antonia; Madsen, Henrik;
considered effects of anthropogenic climate change. The increase in precipitation extremes has led to inundations in most of the larger cities during the last 10 years. To establish cities that are resilient to pluvial floods, robust projections of the frequency and intensity of extreme precipitation events...... climate model (RCM) simulations shows that anthropogenic activity very likely will contribute to a significant increase in extreme precipitation amount and occurrence in Denmark. It is argued that climate models are incapable of simulating extreme precipitation at the temporal scales relevant for...
McCalla, M. R.
The 2002 Office of the Federal Coordinator for Meteorological Services and Supporting Research (OFCM1)-sponsored report, Weather Information for Surface Transportation: National Needs Assessment Report, addressed meteorological needs for six core modes of surface transportation: roadway, railway, transit, marine transportation/operations, pipeline, and airport ground operations. The report's goal was to articulate the weather information needs and attendant surface transportation weather products and services for those entities that use, operate, and manage America's surface transportation infrastructure. The report documented weather thresholds and associated impacts which are critical for decision-making in surface transportation. More recently, the 2008 Climate Change Science Program's (CCSP) Synthesis and Assessment Product (SAP) 4.7 entitled, Impacts of Climate Change and Variability on Transportation Systems and Infrastructure: Gulf Coast Study, Phase I, included many of the impacts from the OFCM- sponsored report in Table 1.1 of this SAP.2 The Intergovernmental Panel on Climate Change (IPCC) reported that since 1950, there has been an increase in the number of heat waves, heavy precipitation events, and areas of drought. Moreover, the IPCC indicated that greater wind speeds could accompany more severe tropical cyclones.3 Taken together, the OFCM, CCSP, and IPCC reports indicate not only the significance of extreme events, but also the potential increasing significance of many of the weather thresholds and associated impacts which are critical for decision-making in surface transportation. Accordingly, there is a real and urgent need to understand what climate products and services are available now to address the weather thresholds within the surface transportation arena. It is equally urgent to understand what new climate products and services are needed to address these weather thresholds, and articulate what can be done to fill the gap between the
Beniston, M.; Stephenson, D.B.; Christensen, O.B.;
regions of Holland, Germany and Denmark, in particular. These results are found to depend to different degrees on model formulation. While the responses of heat waves are robust to model formulation, the magnitudes of changes in precipitation and wind speed are sensitive to the choice of regional model......This paper presents an overview of changes in the extreme events that are most likely to affect Europe in forthcoming decades. A variety of diagnostic methods are used to determine how heat waves, heavy precipitation, drought, wind storms, and storm surges change between present (1961......-90) and future (2071-2 100) climate on the basis of regional climate model simulations produced by the PRUDENCE project. A summary of the main results follows. Heat waves - Regional surface warming causes the frequency, intensity and duration of heat waves to increase over Europe. By the end of the twenty first...
Bruyere, C. L.; Tye, M. R.; Holland, G. J.; Done, J.
Graceful failure acknowledges that all systems will fail at some level and incorporates the potential for failure as a key component of engineering design, community planning, and the associated research and development. This is a fundamental component of the ECEP, an interdisciplinary partnership bringing together scientific, engineering, cultural, business and government expertise to develop robust, well-communicated predictions and advice on the impacts of weather and climate extremes in support of decision-making. A feature of the partnership is the manner in which basic and applied research and development is conducted in direct collaboration with the end user. A major ECEP focus is the Global Risk and Resilience Toolbox (GRRT) that is aimed at developing public-domain, risk-modeling and response data and planning system in support of engineering design, and community planning and adaptation activities. In this presentation I will outline the overall ECEP and GRIP activities, and expand on the 'graceful failure' concept. Specific examples for direct assessment and prediction of hurricane impacts and damage potential will be included.
Williams, Charles Jonathan Roger; Kniveton, Dominic; Layberry, Russell
Changes in climate variability and, in particular, changes in extreme climate events are likely to be of far more significance for environmentally vulnerable regions than changes in the mean state. It is generally accepted that sea-surface temperatures (SSTs) play an important role in modulating rainfall variability. Consequently, SSTs can be prescribed in global and regional climate modelling in order to study the physical mechanisms behind rainfall and its extremes. Using a satellite-based ...
Full Text Available Exploring changes of building energy consumption and its relationships with climate can provide basis for energy-saving and carbon emission reduction. Heating and cooling energy consumption of different types of buildings during 1981-2010 in Tianjin city, was simulated by using TRNSYS software. Daily or hourly extreme energy consumption was determined by percentile methods, and the climate impact on extreme energy consumption was analyzed. The results showed that days of extreme heating consumption showed apparent decrease during the recent 30 years for residential and large venue buildings, whereas days of extreme cooling consumption increased in large venue building. No significant variations were found for the days of extreme energy consumption for commercial building, although a decreasing trend in extreme heating energy consumption. Daily extreme energy consumption for large venue building had no relationship with climate parameters, whereas extreme energy consumption for commercial and residential buildings was related to various climate parameters. Further multiple regression analysis suggested heating energy consumption for commercial building was affected by maximum temperature, dry bulb temperature, solar radiation and minimum temperature, which together can explain 71.5 % of the variation of the daily extreme heating energy consumption. The daily extreme cooling energy consumption for commercial building was only related to the wet bulb temperature (R2= 0.382. The daily extreme heating energy consumption for residential building was affected by 4 climate parameters, but the dry bulb temperature had the main impact. The impacts of climate on hourly extreme heating energy consumption has a 1-3 hour delay in all three types of buildings, but no delay was found in the impacts of climate on hourly extreme cooling energy consumption for the selected buildings.
Li, Mingcai; Shi, Jun; Guo, Jun; Cao, Jingfu; Niu, Jide; Xiong, Mingming
Exploring changes of building energy consumption and its relationships with climate can provide basis for energy-saving and carbon emission reduction. Heating and cooling energy consumption of different types of buildings during 1981-2010 in Tianjin city, was simulated by using TRNSYS software. Daily or hourly extreme energy consumption was determined by percentile methods, and the climate impact on extreme energy consumption was analyzed. The results showed that days of extreme heating consumption showed apparent decrease during the recent 30 years for residential and large venue buildings, whereas days of extreme cooling consumption increased in large venue building. No significant variations were found for the days of extreme energy consumption for commercial building, although a decreasing trend in extreme heating energy consumption. Daily extreme energy consumption for large venue building had no relationship with climate parameters, whereas extreme energy consumption for commercial and residential buildings was related to various climate parameters. Further multiple regression analysis suggested heating energy consumption for commercial building was affected by maximum temperature, dry bulb temperature, solar radiation and minimum temperature, which together can explain 71.5 % of the variation of the daily extreme heating energy consumption. The daily extreme cooling energy consumption for commercial building was only related to the wet bulb temperature (R2= 0.382). The daily extreme heating energy consumption for residential building was affected by 4 climate parameters, but the dry bulb temperature had the main impact. The impacts of climate on hourly extreme heating energy consumption has a 1-3 hour delay in all three types of buildings, but no delay was found in the impacts of climate on hourly extreme cooling energy consumption for the selected buildings. PMID:25923205
Kuleshov, Y.; Jones, D.; Spillman, C. M.
Climate change and climate extremes have a major impact on Australia and Pacific Island countries. Of particular concern are tropical cyclones and extreme ocean temperatures, the first being the most destructive events for terrestrial systems, while the latter has the potential to devastate ocean ecosystems through coral bleaching. As a practical response to climate change, under the Pacific-Australia Climate Change Science and Adaptation Planning program (PACCSAP), we are developing enhanced web-based information tools for providing seasonal forecasts for climatic extremes in the Western Pacific. Tropical cyclones are the most destructive weather systems that impact on coastal areas. Interannual variability in the intensity and distribution of tropical cyclones is large, and presently greater than any trends that are ascribable to climate change. In the warming environment, predicting tropical cyclone occurrence based on historical relationships, with predictors such as sea surface temperatures (SSTs) now frequently lying outside of the range of past variability meaning that it is not possible to find historical analogues for the seasonal conditions often faced by Pacific countries. Elevated SSTs are the primary trigger for mass coral bleaching events, which can lead to widespread damage and mortality on reef systems. Degraded coral reefs present many problems, including long-term loss of tourism and potential loss or degradation of fisheries. The monitoring and prediction of thermal stress events enables the support of a range of adaptive and management activities that could improve reef resilience to extreme conditions. Using the climate model POAMA (Predictive Ocean-Atmosphere Model for Australia), we aim to improve accuracy of seasonal forecasts of tropical cyclone activity and extreme SSTs for the regions of Western Pacific. Improved knowledge of extreme climatic events, with the assistance of tailored forecast tools, will help enhance the resilience and
Extreme climatic events have a major role in the structuring of biological communities, and their occurrence is expected to increase due to climate change. Here I use a manipulative approach to test the effects of extreme storm events on rocky mid-shore assemblages. This study shows that an extreme storm can cause more negative effects than several mild storms, primarily by bringing the biological assemblages towards early stages of succession. This finding contrasts with the effects of clustering of climatic events due to climate change, which are expected to mitigate its ecological impacts. Thus, the ecological consequences of climatic events that are influenced by climate change may have contrasting effects depending on the features that are considered. These results have relevant implications in the forecasting of the ecological consequences of climate change and should be considered when designing measures to mitigate its effects. PMID:27527612
Brunsell, Nathaniel [University of Kansas; Mechem, David [University of Kansas; Ma, Chunsheng [Wichita State University
Recent studies have suggested that low-frequency modes of climate variability can significantly influence regional climate. The climatology associated with extreme events has been shown to be particularly sensitive. This has profound implications for droughts, heat waves, and food production. We propose to examine regional climate simulations conducted over the continental United States by applying a recently developed technique which combines wavelet multi–resolution analysis with information theory metrics. This research is motivated by two fundamental questions concerning the spatial and temporal structure of extreme events. These questions are 1) what temporal scales of the extreme value distributions are most sensitive to alteration by low-frequency climate forcings and 2) what is the nature of the spatial structure of variation in these timescales? The primary objective is to assess to what extent information theory metrics can be useful in characterizing the nature of extreme weather phenomena. Specifically, we hypothesize that (1) changes in the nature of extreme events will impact the temporal probability density functions and that information theory metrics will be sensitive these changes and (2) via a wavelet multi–resolution analysis, we will be able to characterize the relative contribution of different timescales on the stochastic nature of extreme events. In order to address these hypotheses, we propose a unique combination of an established regional climate modeling approach and advanced statistical techniques to assess the effects of low-frequency modes on climate extremes over North America. The behavior of climate extremes in RCM simulations for the 20th century will be compared with statistics calculated from the United States Historical Climatology Network (USHCN) and simulations from the North American Regional Climate Change Assessment Program (NARCCAP). This effort will serve to establish the baseline behavior of climate extremes, the
Rita, Angelo; Borghetti, Marco; Todaro, Luigi; Saracino, Antonio
In the Mediterranean region, the widely predicted rise in temperature, change in the precipitation pattern, and increase in the frequency of extreme climatic events are expected to alter the shape of ecological communities and to affect plant physiological processes that regulate ecosystem functioning. Although change in the mean values are important, there is increasing evidence that plant distribution, survival, and productivity respond to extremes rather than to the average climatic condition. The present study aims to assess the effects of both mean and extreme climatic conditions on radial growth and functional anatomical traits using long-term tree-ring time series of two co-existing Quercus spp. from a drought-prone site in Southern Italy. In particular, this is the first attempt to apply the Generalized Additive Model for Location, Scale, and Shape (GAMLSS) technique and Bayesian modeling procedures to xylem traits data set, with the aim of (i) detecting non-linear long-term responses to climate and (ii) exploring relationships between climate extreme and xylem traits variability in terms of probability of occurrence. This study demonstrates the usefulness of long-term xylem trait chronologies as records of environmental conditions at annual resolution. Statistical analyses revealed that most of the variability in tree-ring width and specific hydraulic conductivity might be explained by cambial age. Additionally, results highlighted appreciable relationships between xylem traits and climate variability more than tree-ring width, supporting also the evidence that the plant hydraulic traits are closely linked to local climate extremes rather than average climatic conditions. We reported that the probability of extreme departure in specific hydraulic conductivity (Ks) rises at extreme values of Standardized Precipitation Index (SPI). Therefore, changing frequency or intensity of extreme events might overcome the adaptive limits of vascular transport, resulting
Caldeira, Maria C.; Lecomte, Xavier; David, Teresa S.; Pinto, Joaquim G.; Bugalho, Miguel N.; Werner, Christiane
Extreme drought events and plant invasions are major drivers of global change that can critically affect ecosystem functioning and alter ecosystem-atmosphere exchange. Invaders are expanding worldwide and extreme drought events are projected to increase in frequency and intensity. However, very little is known on how these drivers may interact to affect the functioning and resilience of ecosystems to extreme events. Using a manipulative shrub removal experiment and the co-occurrence of an extreme drought event (2011/2012) in a Mediterranean woodland, we show that native shrub invasion and extreme drought synergistically reduced ecosystem transpiration and the resilience of key-stone oak tree species. Ecosystem transpiration was dominated by the water use of the invasive shrub Cistus ladanifer, which further increased after the extreme drought event. Meanwhile, the transpiration of key-stone tree species decreased, indicating a competitive advantage in favour of the invader. Our results suggest that in Mediterranean-type climates the invasion of water spending species and projected recurrent extreme drought events may synergistically cause critical drought tolerance thresholds of key-stone tree species to be surpassed, corroborating observed higher tree mortality in the invaded ecosystems. Ultimately, this may shift seasonally water limited ecosystems into less desirable alternative states dominated by water spending invasive shrubs.
Huang, Whitney K.; Stein, Michael L.; McInerney, David J.; Sun, Shanshan; Moyer, Elisabeth J.
Changes in extreme weather may produce some of the largest societal impacts of anthropogenic climate change. However, it is intrinsically difficult to estimate changes in extreme events from the short observational record. In this work we use millennial runs from the Community Climate System Model version 3 (CCSM3) in equilibrated pre-industrial and possible future (700 and 1400 ppm CO2) conditions to examine both how extremes change in this model and how well these changes can be estimated as a function of run length. We estimate changes to distributions of future temperature extremes (annual minima and annual maxima) in the contiguous United States by fitting generalized extreme value (GEV) distributions. Using 1000-year pre-industrial and future time series, we show that warm extremes largely change in accordance with mean shifts in the distribution of summertime temperatures. Cold extremes warm more than mean shifts in the distribution of wintertime temperatures, but changes in GEV location parameters are generally well explained by the combination of mean shifts and reduced wintertime temperature variability. For cold extremes at inland locations, return levels at long recurrence intervals show additional effects related to changes in the spread and shape of GEV distributions. We then examine uncertainties that result from using shorter model runs. In theory, the GEV distribution can allow prediction of infrequent events using time series shorter than the recurrence interval of those events. To investigate how well this approach works in practice, we estimate 20-, 50-, and 100-year extreme events using segments of varying lengths. We find that even using GEV distributions, time series of comparable or shorter length than the return period of interest can lead to very poor estimates. These results suggest caution when attempting to use short observational time series or model runs to infer infrequent extremes.
Arnbjerg-Nielsen, Karsten; Funder, S. G.; Madsen, H.
change over time. The study focuses on assessing climate analogues for Denmark based on current climate data set (E-OBS) observations as well as the ENSEMBLES database of future climates with the aim of projecting future precipitation extremes. The local present precipitation extremes are assessed......Climate analogues, also denoted Space-For-Time, may be used to identify regions where the present climatic conditions resemble conditions of a past or future state of another location or region based on robust climate variable statistics in combination with projections of how these statistics...... by means of intensity-duration-frequency curves for urban drainage design for the relevant locations being France, the Netherlands, Belgium, Germany, the United Kingdom, and Denmark. Based on this approach projected increases of extreme precipitation by 2100 of 9 and 21% are expected for 2 and 10 year...
Climate extremes have been suggested to increase significantly in intensity and frequency in the coming decades, and may influence ecosystem processes and the carbon cycle more profoundly than gradual climate warming. While there is a growing understanding of plant-soil interactions in extreme environments and from lab experiments, we still know very little about how such interactions affect soil carbon dynamics in real-world ecosystems exposed to climate extremes. In this talk I will give a brief overview of the topic and will present evidence from in-situ experiments on plant-soil interactions and their consequences for soil carbon dynamics under severe drought.
Cheng, L.; AghaKouchak, A.; Gilleland, E.
Numerous studies show that climatic extremes have increased substantially in the second half of the 20th century. For this reason, analysis of extremes under a nonstationary assumption has received a great deal of attention. This paper presents a software package developed for estimation of return levels, return periods, and risks of climatic extremes in a changing climate. This MATLAB software package offers tools for analysis of climate extremes under both stationary and non-stationary assumptions. The Nonstationary Extreme Value Analysis (hereafter, NEVA) provides an efficient and generalized framework for analyzing extremes using Bayesian inference. NEVA estimates the extreme value parameters using a Differential Evolution Markov Chain (DE-MC) which utilizes the genetic algorithm Differential Evolution (DE) for global optimization over the real parameter space with the Markov Chain Monte Carlo (MCMC) approach and has the advantage of simplicity, speed of calculation and convergence over conventional MCMC. NEVA also offers the confidence interval and uncertainty bounds of estimated return levels based on the sampled parameters. NEVA integrates extreme value design concepts, data analysis tools, optimization and visualization, explicitly designed to facilitate analysis extremes in geosciences. The generalized input and output files of this software package make it attractive for users from across different fields. Both stationary and nonstationary components of the package are validated for a number of case studies using empirical return levels. The results show that NEVA reliably describes extremes and their return levels.
Gaál, Ladislav; Beranová, Romana; Hlavčová, K.; Kyselý, Jan
Roč. 2014, č. 943487 (2014), s. 1-14. ISSN 1687-9309 R&D Projects: GA ČR(CZ) GA14-18675S Institutional support: RVO:68378289 Keywords : precipitation extremes * regional climate models * climate change Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 0.946, year: 2014 http://www.hindawi.com/journals/amete/2014/943487/
Climate change will increase the recurrence of extreme weather events such as drought and heavy rainfall. Evidence suggests that modifications in extreme weather events pose stronger threats to ecosystem functioning than global trends and shifts in average conditions. As ecosystem functioning is connected with ecological services, this has far-reaching effects on societies in the 21. century. Here, we: (i) present the rationale for the increasing frequency and magnitude of extreme weather events in the near future; (ii) discuss recent findings on meteorological extremes and summarize their effects on ecosystems and (iii) identify gaps in current ecological climate change research. (authors)
Coniglio, Nicola D.; Pesce, Giovanni
"Climate change and international migration flows are phenomena which attract a great deal of attention from policymakers, researchers and the general public around the globe. Are these two phenomena related? Is migration an adaptation strategy to sudden or gradual changes in climate? In this paper our aim is to investigate whether countries that are affected by climatic anomalies with respect to long-term mean experience, ceteris paribus, larger outmigration flows toward rich OECD countries ...
Ionel NĂFTĂNĂILĂ; Ivona ORZEA
Extreme Programming represents a modern Project Management methodology, being a part of AGILE methodologies. The present paper has the purpose of making a critical analysis of the Extreme Programming (XP) from the point of view of advantages and disadvantages that it implies, both from a theoretical and practical approach. From the theoretical point of view the paper will present the main contributions in the Extreme Programming literature, analyzing in the same time the main characteristics ...
Full Text Available Climatic extreme events can cause the shift or disruption of plant-insect interactions due to altered plant quality, e.g. leaf carbon to nitrogen ratios, and phenology. However, the response of plant-herbivore interactions to extreme events and climatic gradients has been rarely studied, although climatic extremes will increase in frequency and intensity in the future and insect herbivores represent a highly diverse and functionally important group. We set up a replicated climate change experiment along elevational gradients in the German Alps to study the responses of three plant guilds and their herbivory by insects to extreme events (extreme drought, advanced and delayed snowmelt versus control plots under different climatic conditions on 15 grassland sites. Our results indicate that elevational shifts in CN (carbon to nitrogen ratios and herbivory depend on plant guild and season. CN ratios increased with altitude for grasses, but decreased for legumes and other forbs. In contrast to our hypotheses, extreme climatic events did not significantly affect CN ratios and herbivory. Thus, our study indicates that nutritional quality of plants and antagonistic interactions with insect herbivores are robust against seasonal climatic extremes. Across the three functional plant guilds, herbivory increased with nitrogen concentrations. Further, increased CN ratios indicate a reduction in nutritional plant quality with advancing season. Although our results revealed no direct effects of extreme climatic events, the opposing responses of plant guilds along elevation imply that competitive interactions within plant communities might change under future climates, with unknown consequences for plant-herbivore interactions and plant community composition.
Benito, G.; Macklin, M.G.; Cohen, K.M.; Herget, J.
Chronological control of Late Pleistocene and Holocene fluvial archives has much improved during the past decades, and this is renewing their use in order to improve records of extreme hydrological events worldwide. A extreme hydrological event is here defined in the sense given by Gregroy et al., (
Kim, Soyoun; Ryu, Youngryel; Jiang, Chongya
Climate extreme events have made significant impacts on terrestrial carbon cycles. Recent studies on detection and attribution of climate extreme events and their impact on carbon cycles used coarse spatial resolution data such as 0.5 degree. The coarse resolution data might miss important climate extremes and their impacts on GPP. To fill this research gap, we use a new global GPP product derived from a process-based model, the Breathing Earth System Simulator (BESS). The BESS takes full advantages of MODIS/AVHRR land and atmosphere products, providing global GPP product in 1 km resolution from 2000 to 2015 and 1/12 degree resolution from 1982 to 1999. We first integrate the BESS GPP products to 0.5 degree (1982-2015) and apply the method of Zscheischler et al. (2013). To test the impacts of spatial resolutions on detecting extreme events, we enhance spatial resolutions of the BESS GPP from 0.5 degree to 0.25, 0.125, and 1/12 degrees and quantify the variations of areas which experienced climate extremes. We subsequently investigate hotspot regions where the extremes occur using fine resolution GPP data at 1/12 degree (1982-2015), then analyze the causes of the extreme events that substantially decreased GPP by using precipitation, air temperature, and frost. This study could improve the understanding of the relationship between climate extremes and the carbon cycle at multiple spatial scales.
Collet, Lila; Beevers, Lindsay; Prudhomme, Christel
Floods are the most common and widely distributed natural risk to life and property worldwide, causing over £6B worth of damage to the UK since 2000. Climate projections are predicted to result in the increase of UK properties at risk from flooding. It thus becomes urgent to assess the possible impact of these changes on extreme high flows in particular, and evaluate the uncertainties related to these projections. This paper aims to assess the changes in extreme runoff for the 1:100 year return period event across Great Britain as a result of climate change. It is based on the Future Flow database and analyses daily runoff over 1961-2098 for 281 gauging stations. The Generalized Extreme Value (GEV) and Generalized Pareto (GP) distribution functions are automatically fitted for 11 climate-change ensembles over the baseline (1961-1990) and the 2080s (2069-2098) for each gauging station. The analysis evaluates the uncertainty related to the Extreme Value (EV) distributions, and the uncertainty related to the climate model parameterization. Then it assesses return levels with combined uncertainties across Great Britain for both EV distributions. Ultimately, this work gives a national picture of extreme flows assessed by the two methods and allows a direct comparison between them. Results show that the GP distribution computes higher runoff estimates than the GEV distribution. Generally, the uncertainties associated with both distributions are similar, but the GP computes significantly higher uncertainties for stations in the south and southeast of England. From the baseline to the 2080s horizon, the GEV distribution shows variable runoff trends across Great Britain, while the GP distribution shows an increasing trend of return level estimate and uncertainties, especially in the northeast and southeast of England. The lowest climate model and extreme value uncertainty is generally seen across the west coast of Great Britain. In terms of uncertainty, with the GEV
Full Text Available Variations in extreme precipitation can be described by various indices. In order to evaluate a climate model's ability to simulate extreme precipitation, gridded extreme precipitation indices from observations are needed. There are two ways to obtain gridded extreme precipitation indices from station-based observations: either through interpolation of station-based extreme indices (EISTA or estimated from gridded precipitation datasets (EIGRID. In this work, we evaluated these two methods and compared observational extreme precipitation indices in China to those obtained from a set of widely used global climate models. Results show that the difference between the two methods is quite large; and in some cases it is even larger than the difference between model simulations and observed gridded EISTA. Based on the sensitivity of the indices to horizontal resolution, it was suggested that EIGRID is more appropriate for evaluating extreme indices simulated by models. Subsequently, historic simulations of extreme precipitation from 21 CMIP5 (Coupled Model Intercomparison Project Phase 5 global climate models were evaluated against two reanalysis datasets during 1961–2000. It was found that most models overestimate extreme precipitation in the mountain regions in western China and northern China and underestimate extreme precipitation in southern China. In eastern China, these models simulate mean extreme precipitation fairly well. Despite this bias, the temporal trend in extreme precipitation for western China is well captured by most models. However, in eastern China, the trend of extreme precipitation is poorly captured by most models, especially for the so-called southern flood and northern drought pattern. Overall, our results suggest that the dynamics of inter-decadal summer monsoon variability should be improved for better prediction of extreme precipitation by the global climate models.
McDonald, Daniel; Ackermann, Gail; Khailova, Ludmila; Baird, Christine; Heyland, Daren; Kozar, Rosemary; Lemieux, Margot; Derenski, Karrie; King, Judy; Vis-Kampen, Christine; Knight, Rob; Wischmeyer, Paul E
Critical illness is hypothesized to associate with loss of "health-promoting" commensal microbes and overgrowth of pathogenic bacteria (dysbiosis). This dysbiosis is believed to increase susceptibility to nosocomial infections, sepsis, and organ failure. A trial with prospective monitoring of the intensive care unit (ICU) patient microbiome using culture-independent techniques to confirm and characterize this dysbiosis is thus urgently needed. Characterizing ICU patient microbiome changes may provide first steps toward the development of diagnostic and therapeutic interventions using microbiome signatures. To characterize the ICU patient microbiome, we collected fecal, oral, and skin samples from 115 mixed ICU patients across four centers in the United States and Canada. Samples were collected at two time points: within 48 h of ICU admission, and at ICU discharge or on ICU day 10. Sample collection and processing were performed according to Earth Microbiome Project protocols. We applied SourceTracker to assess the source composition of ICU patient samples by using Qiita, including samples from the American Gut Project (AGP), mammalian corpse decomposition samples, childhood (Global Gut study), and house surfaces. Our results demonstrate that critical illness leads to significant and rapid dysbiosis. Many taxons significantly depleted from ICU patients versus AGP healthy controls are key "health-promoting" organisms, and overgrowth of known pathogens was frequent. Source compositions of ICU patient samples are largely uncharacteristic of the expected community type. Between time points and within a patient, the source composition changed dramatically. Our initial results show great promise for microbiome signatures as diagnostic markers and guides to therapeutic interventions in the ICU to repopulate the normal, "health-promoting" microbiome and thereby improve patient outcomes. IMPORTANCE Critical illness may be associated with the loss of normal, "health
Full Text Available It is thought that direct personal experience of extreme weather events could result in greater public engagement and policy response to climate change. Based on this premise, we present a set of future climate scenarios for Ireland communicated in the context of recent, observed extremes. Specifically, we examine the changing likelihood of extreme seasonal conditions in the long-term observational record, and explore how frequently such extremes might occur in a changed Irish climate according to the latest model projections. Over the period (1900–2014 records suggest a greater than 50-fold increase in the likelihood of the warmest recorded summer (1995, whilst the likelihood of the wettest winter (1994/95 and driest summer (1995 has respectively doubled since 1850. The most severe end-of-century climate model projections suggest that summers as cool as 1995 may only occur once every ∼7 years, whilst winters as wet as 1994/95 and summers as dry as 1995 may increase by factors of ∼8 and ∼10 respectively. Contrary to previous research, we find no evidence for increased wintertime storminess as the Irish climate warms, but caution that this conclusion may be an artefact of the metric employed. It is hoped that framing future climate scenarios in the context of extremes from living memory will help communicate the scale of the challenge climate change presents, and in so doing bridge the gap between climate scientists and wider society.
The author discusses some reasons to be sceptical about the media-supported idea of an actual climate change, and more particularly about the critical role assigned to carbon dioxide in global warming, about the ability to make the distinction between natural and man-induced climate variations, about the quality of models and simulations, about the knowledge on climate physics, about the interpretation of the recently observed warming (since 1997)
This talk will describe how evidence has grown in recent years for a human influence on climate and explain how the Fifth Assessment Report of the Intergovernmental Panel on Climate Change concluded that it is extremely likely (>95% probability) that human influence on climate has been the dominant cause of the observed global-mean warming since the mid-20th century. The fingerprint of human activities has also been detected in warming of the ocean, in changes in the global water cycle, in reductions in snow and ice, and in changes in some climate extremes. The strengthening of evidence for the effects of human influence on climate extremes is in line with long-held basic understanding of the consequences of mean warming for temperature extremes and for atmospheric moisture. Despite such compelling evidence this does not mean that every instance of high impact weather can be attributed to anthropogenic climate change, because climate variability is often a major factor in many locations, especially for rain...
Hiles, Laura A; Donoviel, Dorit B; Bershad, Eric M
Our ability to monitor the brain physiology is advancing; however, most of the technology is bulky, expensive, and designed for traditional clinical settings. With long-duration space exploration, there is a need for developing medical technologies that are reliable, low energy, portable, and semiautonomous. Our aim was to review the state of the art for noninvasive technologies capable of monitoring brain physiology in diverse settings. A literature review of PubMed and the Texas Medical Center library sites was performed using prespecified search criteria to identify portable technologies for monitoring physiological aspects of the brain physiology. Most brain-monitoring technologies require a moderate to high degree of operator skill. Some are low energy, but many require a constant external power supply. Most of the technologies lack the accuracy seen in gold standard measures, due to the need for calibration, but may be useful for screening or monitoring relative changes in a parameter. Most of the technologies use ultrasound or electromagnetic radiation as energy sources. There is an important need for further development of portable technologies that can be operated in a variety of extreme environments to monitor brain health. PMID:25811362
Babst, Flurin; Carrer, Marco; Poulter, Benjamin; Urbinati, Carlo; Neuwirth, Burkhard; Frank, David
Climatic extreme events strongly affect forest growth and thus significantly influence the inter-annual terrestrial carbon balance. As we are facing an increase in frequency and intensity of climate extremes, extensive empirical archives are required to assess continental scale impacts of temperature and precipitation anomalies. Here we divide a tree-ring network of approximately 1000 sites into fifteen groups of similar high-frequency growth variability to reconstruct regional positive and n...
Andrello, Marco; Bizoux, Jean-Philippe; BARBET-MASSIN, morgane; Gaudeul, Myriam; Nicolè, Florence; Till-Bottraud, Irène
Extreme climatic events like the 2003 summer heatwave and inappropriate land management can threaten the existence of rare plants. We studied the response of Eryngium alpinum, a vulnerable species, to this extreme climatic event and different agricultural practices. A demographic study was conducted in seven field sites between 2001 and 2010. Stage-specific vital rates were used to parameterize matrix population models and perform stochastic projections to calculate population growth rates an...
The impacts of historical droughts and heat-waves on ecosystems are often considered indicative of future global warming impacts, under the assumption that water stress sets in above a fixed high temperature threshold. Historical and future (RCP8.5) Earth system model (ESM) climate projections were analyzed in this study to illustrate changes in the temperatures for onset of water stress under global warming. The ESMs examined here predict sharp declines in gross primary production (GPP) at warm temperature extremes in historical climates, similar to the observed correlations between GPP and temperature during historical heat-waves and droughts. However, soil moisture increases at the warm end of the temperature range, and the temperature at which soil moisture declines with temperature shifts to a higher temperature. The temperature for onset of water stress thus increases under global warming and is associated with a shift in the temperature for maximum GPP to warmer temperatures. Despite the shift in this local temperature optimum, the impacts of warm extremes on GPP are approximately invariant when extremes are defined relative to the optimal temperature within each climate period. The GPP sensitivity to these relative temperature extremes therefore remains similar between future and present climates, suggesting that the heat- and drought-induced GPP reductions seen recently can be expected to be similar in the future, and may be underestimates of future impacts given model projections of increased frequency and persistence of heat-waves and droughts. The local temperature optimum can be understood as the temperature at which the combination of water stress and light limitations is minimized, and this concept gives insights into how GPP responds to climate extremes in both historical and future climate periods. Both cold (temperature and light-limited) and warm (water-limited) relative temperature extremes become more persistent in future climate projections
Alatalo, Juha M.; Jägerbrand, Annika K.; Molau, Ulf
Climate variability is expected to increase in future but there exist very few experimental studies that apply different warming regimes on plant communities over several years. We studied an alpine meadow community under three warming regimes over three years. Treatments consisted of (a) a constant level of warming with open-top chambers (ca. 1.9 °C above ambient), (b) yearly stepwise increases in warming (increases of ca. 1.0, 1.9 and 3.5 °C), and (c) pulse warming, a single first-year pulse event of warming (increase of ca. 3.5 °C). Pulse warming and stepwise warming was hypothesised to cause distinct first-year and third-year effects, respectively. We found support for both hypotheses; however, the responses varied among measurement levels (whole community, canopy, bottom layer, and plant functional groups), treatments, and time. Our study revealed complex responses of the alpine plant community to the different experimentally imposed climate warming regimes. Plant cover, height and biomass frequently responded distinctly to the constant level of warming, the stepwise increase in warming and the extreme pulse-warming event. Notably, we found that stepwise warming had an accumulating effect on biomass, the responses to the different warming regimes varied among functional groups, and the short-term perturbations had negative effect on species richness and diversity
G. Benito; Macklin, M. G.; Cohen, K.M.; J. Herget
Chronological control of Late Pleistocene and Holocene fluvial archives has much improved during the past decades, and this is renewing their use in order to improve records of extreme hydrological events worldwide. A extreme hydrological event is here defined in the sense given by Gregroy et al., (2006), meaning any past process or phenomena related to the hydrological cycle (e.g. rainfall, runoff, snowmelt, flood, water recharge) with a magnitude higher/lower than the mean and probably abov...
Rueda, A.; Camus, P.; Tomás, A.; Vitousek, S.; Méndez, F. J.
Coastal floods often coincide with large waves, storm surge and tides. Thus, joint probability methods are needed to properly characterize extreme sea levels. This work introduces a statistical downscaling framework for multivariate extremes that relates the non-stationary behavior of coastal flooding events to the occurrence probability of daily weather patterns. The proposed method is based on recently-developed weather-type methods to predict extreme events (e.g., significant wave height, mean wave period, surge level) from large-scale sea-level pressure fields. For each weather type, variables of interest are modeled using Generalized Extreme Value (GEV) distributions and a Gaussian copula for modelling the interdependence between variables. The statistical dependence between consecutive days is addressed by defining a climate-based extremal index for each weather type. This work allows attribution of extreme events to specific weather conditions, enhancing the knowledge of climate-driven coastal flooding.
Kyselý, Jan; Rulfová, Zuzana; Farda, A.; Hanel, M.
Cantabria: Environmental Hydraulics Institute Cantabria, 2015. [International Conference on Advances in Extreme Value Analysis and Application to Natural Hazards (EVAN2015) /2./. 16.09.2015–18.09.2015, Santander] Institutional support: RVO:68378289 Keywords : precipitation extremes * climate models * convective precipitation Subject RIV: DG - Athmosphere Sciences, Meteorology
Sylvester, L.; Allen, M. R.; Wilbanks, T. J.
Built infrastructure consists of a series of interconnected networks with many coupled interdependencies. Traditionally, risk and vulnerability assessments are conducted one infrastructure at a time, considering only direct impacts on built and planned assets. However, extreme events caused by climate change affect local communities in different respects and stress vital interconnected infrastructures in complex ways that cannot be captured with traditional risk assessment methodologies. We employ a combination of high-performance computing, geographical information science, and imaging methods to examine the impacts of climate change on infrastructure for cities in two different climate regions: Chicago, Illinois in the Midwest and Portland, Maine (and Casco Bay area) in the Northeast. In Illinois, we evaluate effects of changes in regional temperature and precipitation, informed by an extreme climate change projection, population growth and migration, water supply, and technological development, on electricity generation and consumption. In Maine, we determine the aggregate effects of sea level rise, changing precipitation patterns, and population shifts on the depth of the freshwater-saltwater interface in coastal aquifers and the implications of these changes for water supply in general. The purpose of these efforts is to develop a multi-model framework for investigating potential climate change impacts on interdependent critical infrastructure assessing both vulnerabilities and alternative adaptive measures.
Gregersen, Ida Bülow; Madsen, H.; Arnbjerg-Nielsen, Karsten
The application of climate factors has become more common in urban drainage design. The climate factor accounts for the expected increase in the magnitude of the extreme rainfall events during the technical lifetime of the drainage system. The present practice in Denmark is the application of cli...
Gaál, Ladislav; Beranová, Romana; Kyselý, Jan
Phoenix: American Meteorological Society, 2015. s. 64. [AMS Annual Meeting /95./ and Conference on Climate Variability and Change /27./. 04.01.2015–08.01.2015, Phoenix] Institutional support: RVO:68378289 Keywords : precipitation extremes * regional climate model simulations Subject RIV: DG - Athmosphere Sciences, Meteorology https://ams.confex.com/ams/95Annual/webprogram/Paper257799.html
Woods, M.; Cullen, H. M.
Local television weathercasters, in their role as Station Scientists, are often called upon to educate viewers about the science and impacts of climate change. Climate Central supports these efforts through its Climate Matters program. Launched in 2010 with support from the National Science Foundation, the program has grown into a network that includes more than 245 weathercasters from across the country and provides localized information on climate and ready-to-use, broadcast quality graphics and analyses in both English and Spanish. This presentation will focus on discussing best practices for integrating climate science into the local weather forecast as well as advances in the science of extreme event attribution. The Chief Meteorologist at News10 (Sacramento, CA) will discuss local news coverage of the ongoing California drought, extreme weather and climate literacy.
Phillips, Colin B.; Jerolmack, Douglas J.
Spatial and temporal variations in rainfall are hypothesized to influence landscape evolution through erosion and sediment transport by rivers. However, determining the relation between rainfall and river dynamics requires a greater understanding of the feedbacks between flooding and a river’s capacity to transport sediment. We analyzed channel geometry and stream-flow records from 186 coarse-grained rivers across the United States. We found that channels adjust their shape so that floods slightly exceed the critical shear velocity needed to transport bed sediment, independently of climatic, tectonic, and bedrock controls. The distribution of fluid shear velocity associated with floods is universal, indicating that self-organization of near-critical channels filters the climate signal evident in discharge. This effect blunts the impact of extreme rainfall events on landscape evolution.
Middleton, R. S.; Brown, M.; Coon, E.; Linn, R.; McDowell, N. G.; Painter, S. L.; Xu, C.
Climate change, extreme climate events, and climate-induced disturbances will have a substantial and detrimental impact on terrestrial ecosystems. How ecosystems respond to these impacts will, in turn, have a significant effect on the quantity, quality, and timing of water supply for energy security, agriculture, industry, and municipal use. As a community, we lack sufficient quantitative and mechanistic understanding of the complex interplay between climate extremes (e.g., drought, floods), ecosystem dynamics (e.g., vegetation succession), and disruptive events (e.g., wildfire) to assess ecosystem vulnerabilities and to design mitigation strategies that minimize or prevent catastrophic ecosystem impacts. Through a combination of experimental and observational science and modeling, we are developing a unique multi-physics ecohydrologic framework for understanding and quantifying feedbacks between novel climate and extremes, surface and subsurface hydrology, ecosystem dynamics, and disruptive events in critical watersheds. The simulation capability integrates and advances coupled surface-subsurface hydrology from the Advanced Terrestrial Simulator (ATS), dynamic vegetation succession from the Ecosystem Demography (ED) model, and QUICFIRE, a novel wildfire behavior model developed from the FIRETEC platform. These advances are expected to make extensive contributions to the literature and to earth system modeling. The framework is designed to predict, quantify, and mitigate the impacts of climate change on vulnerable watersheds, with a focus on the US Mountain West and the energy-water nexus. This emerging capability is used to identify tipping points in watershed ecosystems, quantify impacts on downstream users, and formally evaluate mitigation efforts including forest (e.g., thinning, prescribed burns) and watershed (e.g., slope stabilization). The framework is being trained, validated, and demonstrated using field observations and remote data collections in the
A. P. Mφller
Behavioral responses to environmental change are the mechanisms that allow for rapid phenotypic change preventing temporary or permanent damage and hence preventing reductions in fitness. Extreme climatic events are by definition rare, although they are predicted to increase in amplitude and frequency in the coming years. However, our current knowledge about behavioral responses to such extreme events is scarce. Here I analyze two examples of the effects of extreme weather events on behavior and life history: (1) A comparison of behavior and life history during extremely warm and extremely cold years relative to normal years; and (2) a comparison of behavior before and after the extremely early snowfall in fall 1974 when numerous birds died in the Alps during September-October. Behavioral and life history responses of barn swallows Hirundo rustica to extremely cold and extremely warm years were positively correlated, with particularly large effect sizes in cold years. Extreme mortality in barn swallows during fall migration 1974 in the Alps eliminated more than 40％ of the breeding population across large areas in Central and Northern Europe, and this affected first arrival date, changes in timing and extent of reproduction and changes in degree of breeding sociality supposedly as a consequence of correlated responses to selection. Finally, I provide directions for research that will allow us to better understand behavior and life history changes in response to extreme climate change [Current Zoology 57 (3): 351-362,2011].
A. P. Møller
Full Text Available Behavioral responses to environmental change are the mechanisms that allow for rapid phenotypic change preventing temporary or permanent damage and hence preventing reductions in fitness. Extreme climatic events are by definition rare, although they are predicted to increase in amplitude and frequency in the coming years. However, our current knowledge about behavioral responses to such extreme events is scarce. Here I analyze two examples of the effects of extreme weather events on behavior and life history: (1 A comparison of behavior and life history during extremely warm and extremely cold years relative to normal years; and (2 a comparison of behavior before and after the extremely early snowfall in fall 1974 when numerous birds died in the Alps during September-October. Behavioral and life history responses of barn swallows Hirundo rustica to extremely cold and extremely warm years were positively correlated, with particularly large effect sizes in cold years. Extreme mortality in barn swallows during fall migration 1974 in the Alps eliminated more than 40% of the breeding population across large areas in Central and Northern Europe, and this affected first arrival date, changes in timing and extent of reproduction and changes in degree of breeding sociality supposedly as a consequence of correlated responses to selection. Finally, I provide directions for research that will allow us to better understand behavior and life history changes in response to extreme climate change [Current Zoology 57 (3: 351–362, 2011].
Holmgren, M.; Stapp, P.; Dickman, C.; Gracia, C.; Graham, S.
Climatic changes associated with the El Nino Southern Oscillation (ENSO) can have a dramatic impact on terrestrial ecosystems worldwide, but especially on arid and semiarid systems, where productivity is strongly limited by precipitation. Nearly two decades of research, including both short-term exp
Abiodun, Babatunde J.; Salami, Ayobami T.; Matthew, Olaniran J.; Odedokun, Sola
Afforestation is usually thought as a good approach to mitigate impacts of warming over a region. This study presents an argument that afforestation may have bigger impacts than originally thought by previous studies. The study investigates the impacts of afforestation on future climate and extreme events in Nigeria, using a regional climate model (RegCM3), forced with global climate model simulations. The impacts of seven afforestation options on the near future (2031-2050, under A1B scenario) climate and the extreme events are investigated. RegCM3 replicates essential features in the present-day (1981-2000) climate and the associated extreme events, and adequately simulates the seasonal variations over the ecological zones in the country. However, the model simulates the seasonal climate better over the northern ecological zones than over the southern ecological zones. The simulated spatial distribution of the extreme events agrees well with the observation, though the magnitude of the simulated events is smaller than the observed. The study shows that afforestation in Nigeria could have both positive and negative future impacts on the climate change and extreme events in the country. While afforestation reduces the projected global warming and enhances rainfall over the afforested area (and over coastal zones), it enhances the warming and reduces the rainfall over the north-eastern part of the country. In addition, the afforestation induces more frequent occurrence of extreme rainfall events (flooding) over the coastal region and more frequent occurrence of heat waves and droughts over the semi-arid region. The positive and negative impacts of the afforestation are not limited to Nigeria; they extend to the neighboring countries. While afforestation lowers the warming and enhances rainfall over Benin Republic, it increases the warming and lowers the rainfall over Niger, Chad and Cameroon. The result of the study has important implication for the ongoing climate
Some events are difficult to avoid and gives considerable influence to humans and the environment is extreme weather and climate change. Many of the problems that require knowledge about the behavior of extreme values and one of the methods used are the Extreme Value Theory (EVT). EVT used to draw up reliable systems in a variety of conditions, so as to minimize the risk of a major disaster. There are two methods for identifying extreme value, Block Maxima with Generalized Extreme Value (GEV) distribution approach and Peaks over Threshold (POT) with Generalized Pareto Distribution (GPD) approach. This research in Indramayu with January 1961-December 2003 period, the method used is Block Maxima with GEV distribution approach. The result showed that there is no climate change in Indramayu with January 1961-December 2003 period.
Arnbjerg-Nielsen, Karsten; Gregersen, Ida Bülow; Sunyer Pinya, Maria Antonia;
During the past 30 years rather dramatic changes in extreme precipitation has been observed in Denmark. The changes have mainly been observed in the frequency of extreme events, but also a tendency towards more severe events is occurring. The increase in precipitation extremes have led to...... precipitation extremes. The objective is to establish cities that are resilient to pluvial floods by means of a gradual upgrading of the drainage capacity in combination with a structured risk management approach. Using the regional climate model (RCM) data repositories from PRUDENCE and ENSEMBLES, estimates of...... climate change impacts from anthropogenic effects can be established based on projections of daily precipitation. These estimates have then been further downscaled to enable urban pluvial inundation calculations using different statistical downscaling and extreme value analysis techniques. . From the...
Full Text Available Weather and climate extremes in light of the IPCC SREX (2011 and beyond. The recent IPCC Special Report (IPCC SREX, 2011 provides a comprehensive overview of meteorological (i.e. weather and climate extremes and their various aspects. The present paper reflects the core concepts of the Report, clarifying the relations of the natural and anthropogenic factors causing meteorological extremes, as well, as condition determining the risks and general ways of response by the society. The paper can only add some recent statistics to this scheme on various aspects of meteorological and non-meteorological reasons of natural disasters. The paper argues, however, the still unclear definition of the extremes and their classification as weather and climate extremes. We also dedicate a sub-Section to the statistical and physical considerations on how the extremes may change parallel to the global warming. Another sub-Section refers to further difficulties that hamper the empirical establishment of the trends in the meteorological extremes. Finally we overview the IPCC AR4 (2007 conclusions on some meteorological extremes, since the detailed Chapters of the IPCC SREX (2011 Report were not available by the time of writing the paper, but from its SPM no difference in the statements and even its uncertainties can be established since the AR4.
Caldeira, Maria; Lecomte, Xavier; David, Teresa; Pinto, Joaquim; Bugalho, Miguel; Werner, Christiane
Extreme droughts and plant invasions are major drivers of global change that can critically affect ecosystem functioning. Shrub encroachment is increasing in many regions worldwide and extreme events are projected to increase in frequency and intensity, namely in the Mediterranean region. Nevertheless, little is known about how these drivers may interact and affect ecosystem functioning and resilience to extreme droughts. Using a manipulative shrub removal experiment and the co-occurrence of an extreme drought event (2011/2012) in a Mediterranean woodland, we show that the native shrub invasion and extreme drought combined to reduce ecosystem transpiration and the resilience of the key-stone oak tree species. We established six 25 x 25 m paired plots in a shrub (Cistus ladanifer L.) encroached Mediterranean cork-oak (Quercus suber L.) woodland. We measured sapflow and pre-dawn leaf water potential of trees and shrubs and soil water content in all plots during three years. We determined the resilience of tree transpiration to evaluate to what extent trees recovered from the extreme drought event. From February to November 2011 we conducted baseline measurements for plot comparison. In November 2011 all the shrubs from one of all the paired plots were cut and removed. Ecosystem transpiration was dominated by the water use of the invasive shrub, which further increased after the extreme drought. Simultaneously, tree transpiration in invaded plots declined much stronger (67 ± 13 %) than in plots cleared from shrubs (31 ± 11%) relative to the pre-drought year. Trees in invaded plots were not able to recover in the following wetter year showing lower resilience to the extreme drought event. Our results imply that in Mediterranean-type of climates invasion by water spending species can combine with projected recurrent extreme droughts causing critical drought tolerance thresholds of trees to be overcome increasing the probability of tree mortality (Caldeira et.al. 2015
Attia, Shady; Duchhart, Ingrid
In the desert the role of bioclimatic landscape design is to consider three major environmental factors, solar radiation, evaporation, wind and air flows. Therefore the landscape architect should be prepared with a group of design principals and design guidelines that can help him to improve the micro-climate and conserve energy. This paper presents a group of passive design strategies for bioclimatic landscape architecture in the desert. In this study, a bioclimatic landscape design strategy...
Climatic extreme events strongly affect forest growth and thus significantly influence the inter-annual terrestrial carbon balance. As we are facing an increase in frequency and intensity of climate extremes, extensive empirical archives are required to assess continental scale impacts of temperature and precipitation anomalies. Here we divide a tree-ring network of approximately 1000 sites into fifteen groups of similar high-frequency growth variability to reconstruct regional positive and negative extreme events in different parts of Europe between 1500 and 2008. Synchronized growth maxima or minima within and among regions indicate eighteen years in the pre-instrumental period and two events in the 20th century (1948, 1976) with extensive radial growth fluctuations. Comparisons with instrumental data showed that the European tree-ring network mirrors the spatial extent of temperature and precipitation extremes, but the interpretation of pre-instrumental events is challenged by lagged responses to off-growing season climate extremes. We were able to attribute growth minima in subsequent years to unfavourable August–October conditions and to mild climate during winter months associated with respiratory carbon losses. Our results emphasize the importance of carry-over effects and species-specific growth characteristics for forest productivity. Furthermore, they promote the use of regional tree-ring chronologies in research related to climate variability and terrestrial carbon sink dynamics. (letter)
PaiMazumder, Debasish; Done, James M.
The suitability of dynamical downscaling in producing high-resolution climate scenarios for impact assessments is limited by the quality of the driving data and regional climate model (RCM) error. Multiple RCMs driven by a single global climate model simulation of current climate show a reduction in bias compared to the driving data, and the remaining bias motivates exploration of bias correction and higher RCM resolution. The merits of bias correcting the mean climate of the driving data (boundary bias correction) versus bias correcting the mean of the RCM output data are explored and compared to model resolution sensitivity. This analysis focuses on the simulation of summer temperature and precipitation extremes using a single RCM, the Nested Regional Climate Model (NRCM). The NRCM has a general cool bias for hot and cold extremes, a wet bias for wet extremes and a dry bias for dry extremes. Both bias corrections generally reduced the bias and overall error with some indication that boundary bias correction provided greater benefits than bias correcting the mean of the RCM output data, particularly for precipitation. High resolution tended not to lead to further improvements, though further work is needed using multiple resolution evaluation datasets and convection permitting resolution simulations to comprehensively assess the value of high resolution.
Kara, Fatih; Yucel, Ismail
This study investigates the climate change impact on the changes of mean and extreme flows under current and future climate conditions in the Omerli Basin of Istanbul, Turkey. The 15 regional climate model output from the EU-ENSEMBLES project and a downscaling method based on local implications from geophysical variables were used for the comparative analyses. Automated calibration algorithm is used to optimize the parameters of Hydrologiska Byråns Vattenbalansavdel-ning (HBV) model for the study catchment using observed daily temperature and precipitation. The calibrated HBV model was implemented to simulate daily flows using precipitation and temperature data from climate models with and without downscaling method for reference (1960-1990) and scenario (2071-2100) periods. Flood indices were derived from daily flows, and their changes throughout the four seasons and year were evaluated by comparing their values derived from simulations corresponding to the current and future climate. All climate models strongly underestimate precipitation while downscaling improves their underestimation feature particularly for extreme events. Depending on precipitation input from climate models with and without downscaling the HBV also significantly underestimates daily mean and extreme flows through all seasons. However, this underestimation feature is importantly improved for all seasons especially for spring and winter through the use of downscaled inputs. Changes in extreme flows from reference to future increased for the winter and spring and decreased for the fall and summer seasons. These changes were more significant with downscaling inputs. With respect to current time, higher flow magnitudes for given return periods will be experienced in the future and hence, in the planning of the Omerli reservoir, the effective storage and water use should be sustained. PMID:26293893
Kristie L. Ebi
Full Text Available Current public health strategies, policies, and measures are being modified to enhance current health protection to climate-sensitive health outcomes. These modifications are critical to decrease vulnerability to climate variability, but do not necessarily increase resilience to future (and different weather patterns. Communities resilient to the health risks of climate change anticipate risks; reduce vulnerability to those risks; prepare for and respond quickly and effectively to threats; and recover faster, with increased capacity to prepare for and respond to the next threat. Increasing resilience includes top-down (e.g., strengthening and maintaining disaster risk management programs and bottom-up (e.g., increasing social capital measures, and focuses not only on the risks presented by climate change but also on the underlying socioeconomic, geographic, and other vulnerabilities that affect the extent and magnitude of impacts. Three examples are discussed of public health programs designed for other purposes that provide opportunities for increasing the capacity of communities to avoid, prepare for, and effectively respond to the health risks of extreme weather and climate events. Incorporating elements of adaptive management into public health practice, including a strong and explicit focus on iteratively managing risks, will increase effective management of climate change risks.
Ebi, Kristie L
Current public health strategies, policies, and measures are being modified to enhance current health protection to climate-sensitive health outcomes. These modifications are critical to decrease vulnerability to climate variability, but do not necessarily increase resilience to future (and different) weather patterns. Communities resilient to the health risks of climate change anticipate risks; reduce vulnerability to those risks; prepare for and respond quickly and effectively to threats; and recover faster, with increased capacity to prepare for and respond to the next threat. Increasing resilience includes top-down (e.g., strengthening and maintaining disaster risk management programs) and bottom-up (e.g., increasing social capital) measures, and focuses not only on the risks presented by climate change but also on the underlying socioeconomic, geographic, and other vulnerabilities that affect the extent and magnitude of impacts. Three examples are discussed of public health programs designed for other purposes that provide opportunities for increasing the capacity of communities to avoid, prepare for, and effectively respond to the health risks of extreme weather and climate events. Incorporating elements of adaptive management into public health practice, including a strong and explicit focus on iteratively managing risks, will increase effective management of climate change risks. PMID:22408590
Rimbu, Norel; Ionita, Monica; Lohmann, Gerrit
Interannual to millennial time scale variability of precipitation (R20mm, Rx5day, R95pTOT), cold (TN10p, CSDI and CFD), heat (TX90p and WSDI) and drought (CDD) extreme climate indices is investigated using long-term observational and proxy records. We detect significant correlations between these indices and various high resolution proxy records like lake sediments from southern Germany, stable oxygen isotopes from Greenland ice cores and stable oxygen isotopes from Red Sea corals during observational period. The analysis of long-term reanalysis data in combination with extreme climate indices and proxy data reveals that distinct atmospheric circulation patterns explain most of the identified relationships. In particular, we show that a sediment record from southern Germany (lake Ammersee), which records flood frequency of River Ammer during the last 5500 years, is related to a wave-train atmospheric circulation pattern with a pronounced negative center over western Europe. We show that high frequency of River Ammer floods is related not only to high frequency of extreme precipitation events (R95p) in the Ammer region but also with significant positive anomalies of various extreme temperature indices (TX90p and TXx) over northeastern Europe. Such extreme temperatures are forced by cloudiness anomaly pattern associated with flood related atmospheric circulation pattern. Based on this record we discuss possible interannual to millennial scale variations of extreme precipitation and temperature indices over Europe during the last 5500 years. Coherent variations of extreme precipitation and temperature indices over Europe and stable oxygen isotopes from Greenland ice cores and northern Red Sea corals during observational period are related to atmospheric blocking variability in the North Atlantic region. Possible variations of climate extreme indices during different time slices of the Holocene period and their implications for future extreme climate variability are
Alfieri, Silvia Maria; De Lorenzi, Francesca; Basile, Angelo; Bonfante, Antonello; Missere, Daniele; Menenti, Massimo
Climate change in Mediterranean area is likely to reduce precipitation amounts and to increase temperature thus affecting the timing of development stages and the productivity of crops. Further, extreme weather events are expected to increase in the future leading to significant increase in agricultural risk. Some strategies for effectively managing risks and adapting to climate change involve adjustments to irrigation management and use of different varieties. We quantified the risk on Peach production in an irrigated area of "Emilia Romagna" region ( Italy) taking into account the impact on crop yield due to climate change and variability and to extreme weather events as well as the ability of the agricultural system to modulate this impact (adaptive capacity) through changes in water and crop management. We have focused on climatic events causing insufficient water supply to crops, while taking into account the effect of climate on the duration and timing of phenological stages. Further, extreme maximum and minimum temperature events causing significant reduction of crop yield have been considered using phase-specific critical temperatures. In our study risk was assessed as the product of the probability of a damaging event (hazard), such as drought or extreme temperatures, and the estimated impact of such an event (vulnerability). To estimate vulnerability we took into account the possible options to reduce risk, by combining estimates of the sensitivity of the system (negative impact on crop yield) and its adaptive capacity. The latter was evaluated as the relative improvement due to alternate management options: the use of alternate varieties or the changes in irrigation management. Vulnerability was quantified using cultivar-specific thermal and hydrologic requirements of a set of cultivars determined by experimental data and from scientific literature. Critical temperatures determining a certain reduction of crop yield have been estimated and used to assess
Gregersen, Ida Bülow; Sørup, Hjalte Jomo Danielsen; Madsen, Henrik;
Climate change is expected to influence the occurrence and magnitude of rainfall extremes and hence the flood risks in cities. Major impacts of an increased pluvial flood risk are expected to occur at hourly and sub-hourly resolutions. This makes convective storms the dominant rainfall type in...... relation to urban flooding. The present study focuses on high-resolution regional climate model (RCM) skill in simulating sub-daily rainfall extremes. Temporal and spatial characteristics of output from three different RCM simulations with 25 km resolution are compared to point rainfall extremes estimated...... from observed data. The applied RCM data sets represent two different models and two different types of forcing. Temporal changes in observed extreme point rainfall are partly reproduced by the RCM RACMO when forced by ERA40 re-analysis data. Two ECHAM forced simulations show similar increases in the...
Thonicke, Kirsten; Rolinski, Susanne; Walz, Ariane; von Bloh, Werner; van Oijen, Marcel; Davin, Edouard; Vieli, Barla; Kato, Tomomichi; Beer, Christian
Extremes of meteorological events may but do not have to cause damages in ecosystems. Climate change is expected to have a strong impact on the resilience and stability of ecosystems worldwide. So far, the impacts of trends and extremes of physical drivers on ecosystems have generally been studied regardless of the extremeness of the ecosystem response. We base our analysis on a Probabilistic Risk Assessment concept of Van Oijen et al. (2013) quantifying the vulnerability of vegetation dynamics in relation to the extremeness of meteorological drivers such as temperature, precipitation or drought indices. Here, the definition of extreme, hazardous weather conditions is based on the ecosystem response. Instead of searching for extreme meteorological events, we define extreme ecosystem responses in terms of threshold levels of carbon uptake, and search for the meteorological conditions which are responsible. Having defined hazardous events in this way, we quantify the vulnerability or resilience of ecosystems to such hazards. We apply this approach on results of different vegetation models (such as LPJmL, Orchidee, JSBACH or CLM4) and the forest model BASFOR using climatic input for Europe from the WATCH-ERAI-REMO climate dataset with the SRES A1B emission scenario. Our results show that under current climatic conditions, the southern part of Europe already suffers severe heat and drought stress which is reflected in our approach by vulnerability values being high for precipitation, relatively high for the SPEI index, moderately high for temperature and quite high for the consecutive dry days. Thus, hazard occurrence is frequent enough to determine ecosystem vulnerability but this depends on the definition of the threshold of hazardous ecosystem responses. Vulnerability values in the Mediterranean increase towards the end of the 21st century for all models indicating that a tipping point towards drought damages has been reached for the chosen climate scenario.
Thibeault, J. M.; Seth, A.
Extreme climate events are known to have severe impacts on human and natural systems. As greenhouse warming progresses, a major concern is the potential for an increase in the frequency and intensity of extreme events. The Northeast (defined as the Northeast US, southern Quebec, and southeastern Ontario) is sensitive to climate extremes. The region is prone to flooding and drought, which poses challenges for infrastructure and water resource management, and increases risks to agriculture and forests. Extreme heat can be dangerous to human health, especially in the large urban centers of the Northeast. Annual average temperatures have steadily increased since the 1970s, accompanied by more frequent extremely hot weather, a longer growing season, and fewer frost days. Heavy precipitation events have become more frequent in recent decades. This research examines multi-model projections of annual and monthly extreme indices for the Northeast, using extreme indices computed by the Expert Team on Climate Change Detection and Indices (ETCCDI) for twenty-three global climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) for the 20th century historical and RCP8.5 experiments. Model simulations are compared to HadEX2 and ERA-interim gridded observations. CMIP5 simulations are consistent with observations - conditions in the Northeast are already becoming warmer and wetter. Projections indicate significant shifts toward warmer and wetter conditions by the middle century (2041-2070). Most indices are projected to be largely outside their late 20th century ranges by the late century (2071-2099). These results provide important information to stakeholders developing plans to lessen the adverse impacts of a warmer and wetter climate in the Northeast.
Sunyer Pinya, Maria Antonia; Sørup, Hjalte Jomo Danielsen; Christensen, Ole Bøssing;
In recent years, there has been an increase in the number of climate studies addressing changes in extreme precipitation. A common step in these studies involves the assessment of the climate model performance. This is often measured by comparing climate model output with observational data. In the...... majority of such studies the characteristics and uncertainties of the observational data are neglected. This study addresses the influence of using different observational datasets to assess the climate model performance. Four different datasets covering Denmark using different gauge systems and comprising...... datasets, the RCMs are ranked according to their performance using two different metrics. These are based on the error in representing the indices and the spatial correlation. In comparison to the mean, extreme precipitation indices are highly dependent on the spatial resolution of the observations. The...
Kyselý, Jan; Picek, J.; Beranová, Romana
Istambul: The Scientific and Technological Research Council of Turkey, 2008 - (Dincer, I.; Karakoc, T.; Hepbasli, A.; Midilli, A.; Colpan, C.; Gündüz, S.), s. 465-473 ISBN 978-605-89885-0-7. [ Global Conference on Global Warming 2008. Istambul (TR), 06.07.2008-10.07.2008] R&D Projects: GA ČR GA205/06/1535 Institutional research plan: CEZ:AV0Z30420517 Keywords : extreme value analysis * Global Climate Models * climate change * peaks-over-threshold * Poisson process * extreme temperatures Subject RIV: DG - Athmosphere Sciences, Meteorology
This paper focuses upon topics related to current and possible future extreme weather events in order to highlight the links between climatic change and its economic impacts. Most of the examples given here are drawn from observations in Switzerland and the Alpine region that have a wealth of climatic, environmental and socio-economic data. These enable detailed studies to be undertaken on trends in mean and extreme climates and their impacts. Model simulations for a ''greenhouse climate'' suggest that risks associated with various forms of extreme events that affect the Alps may increase in the future, which could lead to high damage costs. In addition to the direct impacts of extremes, it is also necessary to take into account the increasing economic value of infrastructure located in zones potentially at risk. The final part of the paper addresses some of the issues that are related to fully integrated modeling approaches that are aimed at assessing the costs of damage in the wake of an extreme event. (author)
This paper focuses upon topics related to current and possible future extreme weather events in order to highlight the links between climatic change and its economic impacts. Most of the examples given here are drawn from observations in Switzerland and the Alpine region that have a wealth of climatic, environmental and socio-economic data. These enable detailed studies to be undertaken on trends in mean and extreme climates and their impacts. Model simulations for a 'greenhouse climate' suggest that risks associated with various forms of extreme events that affect the Alps may increase in the future, which could lead to high damage costs. In addition to the direct impacts of extremes, it is also necessary to take into account the increasing economic value of infrastructure located in zones potentially at risk. The final part of the paper addresses some of the issues that are related to fully integrated modeling approaches that are aimed at assessing the costs of damage in the wake of an extreme event
Hoover, David L.; Knapp, Alan K.; Smith, Melinda D.
The predicted increase in the frequency and intensity of climate extremes is expected to impact terrestrial carbon fluxes to the atmosphere, potentially changing ecosystems from carbon sinks to sources, with positive feedbacks to climate change. As the second largest terrestrial carbon flux, soil CO2 efflux or soil respiration (Rs) is strongly influenced by soil temperature and moisture. Thus, climate extremes such as heat waves and extreme drought should have substantial impacts on Rs. We investigated the effects of such climate extremes on growing season Rs in a mesic grassland by experimentally imposing 2 years of extreme drought combined with midsummer heat waves. After this 2 year period, we continued to measure Rs during a recovery year. Two consecutive drought years reduced Rs by about 25% each growing season; however, when normal rainfall returned during the recovery year, formerly droughted plots had higher rates of Rs than control plots (up to +17%). The heat wave treatments had no effect on Rs, alone or when combined with drought, and during the growing season, soil moisture was the primary driver of Rs with little evidence for Rs temperature sensitivity. When compared to aboveground net primary production, growing season Rs was much less sensitive to drought but was more responsive postdrought. These results are consistent with the hypothesis that ecosystems become sources of CO2 during drought because carbon inputs (production) are decreased relatively more than outputs (respiration). Moreover, stimulation of Rs postdrought may lengthen the time required for net carbon exchange to return to predrought levels.
Williams, C. J. R.; Kniveton, D. R.; Layberry, R.
It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with
Full Text Available Drylands cover about 40% of the terrestrial land surface and account for approximately 40% of global net primary productivity. Water is fundamental to the biophysical processes that sustain ecosystem function and food production, particularly in drylands, where a tight coupling exists between water resource availability and ecosystem productivity, surface energy balance, and biogeochemical cycles. Currently, drylands support at least 2 billion people and comprise both natural and managed ecosystems. In this synthesis, we identify some current critical issues in the understanding of dryland systems and discuss how arid and semiarid environments are responding to the changes in climate and land use. Specifically, we focus on dryland agriculture and food security, dryland population growth, desertification, shrub encroachment and dryland development issues as factors of change requiring increased understanding and management. We also review recent technical advances in the quantitative assessment of human versus climate change related drivers of desertification, evapotranspiration partitioning using field deployable stable water isotope systems and the remote sensing of key ecohydrological processes. These technological advances provide new tools that assist in addressing major critical issues in dryland ecohydrology under climate change
I. Climate change comprises average temperatures rise, changes in the distribution of precipitation and an increased amount and intensity of extreme climatic events in the last decades. Considering these serious changes in the abiotic environment it seems obvious that ecosystems also change. Flora and fauna have to adapt to the fast changing conditions, migrate or go extinct. This might result in shifts in biodiversity, species composition, species interactions and in ecosystem functioning an...
Willems, Patrick; Olsson, Jonas; Arnbjerg-Nielsen, Karsten; Beecham, Simon; Pathirana, Assela; Bülow Gregersen, Ida; Madsen, Henrik; Nguyen, Van-Thanh-Van
Under the umbrella of the IWA/IAHR Joint Committee on Urban Drainage, the International Working Group on Urban Rainfall (IGUR) has reviewed existing methodologies for the analysis of long-term historical and future trends in urban rainfall extremes and their effects on urban drainage systems, due to anthropogenic climate change. Current practises have several limitations and pitfalls, which are important to be considered by trend or climate change impact modellers and users of trend/impact re...
Wen-Cheng Huang; Yi-Ying Lee
Extreme weather caused by global climate change affects slope-land in Taiwan, causing soil loss, floods, and sediment hazards. Although Taiwan is a small island, the population density is ranked second highest worldwide. With three-fourths of the island area being slope-land, soil and water conservation (SWC) is crucial. Therefore, because of the impact of climate and social change, the means of maintaining sustainable development of slope-land and the safety of the living environment in Taiw...
Willems, Patrick; Olsson, Jonas; Arnbjerg-Nielsen, Karsten; Beecham, Simon; Pathirana, Assela; Gregersen, Ida Bülow; Madsen, Henrik; Nguyen, Van-Thanh-Van
Under the umbrella of the IWA/IAHR Joint Committee on Urban Drainage, the International Working Group on Urban Rainfall (IGUR) has reviewed existing methodologies for the analysis of long-term historical and future trends in urban rainfall extremes and their effects on urban drainage systems, due to anthropogenic climate change. Current practises have several limitations and pitfalls, which are important to be considered by trend or climate change impact modellers and users of trend/impact re...
Leckebusch, Gregor C.; Befort, Daniel J.; Hodges, Kevin I.
Suitable adaptation strategies or the timely initiation of related mitigation efforts in East Asia will strongly depend on robust and comprehensive information about future near-term as well as long-term potential changes in the climate system. Therefore, understanding the driving mechanisms associated with the East Asian climate is of major importance. The FOREX project (Fostering Regional Decision Making by the Assessment of Uncertainties of Future Regional Extremes and their Linkage to Global Climate System Variability for China and East Asia) focuses on the investigation of extreme wind and rainfall related events over Eastern Asia and their possible future changes. Here, analyses focus on the link between local extreme events and their driving weather systems. This includes the coupling between local rainfall extremes and tropical cyclones, the Meiyu frontal system, extra-tropical teleconnections and monsoonal activity. Furthermore, the relation between these driving weather systems and large-scale variability modes, e.g. NAO, PDO, ENSO is analysed. Thus, beside analysing future changes of local extreme events, the temporal variability of their driving weather systems and related large-scale variability modes will be assessed in current CMIP5 global model simulations to obtain more robust results. Beyond an overview of FOREX itself, first results regarding the link between local extremes and their steering weather systems based on observational and reanalysis data are shown. Special focus is laid on the contribution of monsoonal activity, tropical cyclones and the Meiyu frontal system on the inter-annual variability of the East Asian summer rainfall.
A method of validating climate models in climate research with a view to extreme events; Eine Methode zur Validierung von Klimamodellen fuer die Klimawirkungsforschung hinsichtlich der Wiedergabe extremer Ereignisse
A method is presented to validate climate models with respect to extreme events which are suitable for risk assessment in impact modeling. The algorithm is intended to complement conventional techniques. These procedures mainly compare simulation results with reference data based on single or only a few climatic variables at the same time under the aspect how well a model performs in reproducing the known physical processes of the atmosphere. Such investigations are often based on seasonal or annual mean values. For impact research, however, extreme climatic conditions with shorter typical time scales are generally more interesting. Furthermore, such extreme events are frequently characterized by combinations of individual extremes which require a multivariate approach. The validation method presented here basically consists of a combination of several well-known statistical techniques, completed by a newly developed diagnosis module to quantify model deficiencies. First of all, critical threshold values of key climatic variables for impact research have to be derived serving as criteria to define extreme conditions for a specific activity. Unlike in other techniques, the simulation results to be validated are interpolated to the reference data sampling points in the initial step of this new technique. Besides that fact that the same spatial representation is provided in this way in both data sets for the next diagnostic steps, this procedure also enables to leave the reference basis unchanged for any type of model output and to perform the validation on a real orography. To simultaneously identify the spatial characteristics of a given situation regarding all considered extreme value criteria, a multivariate cluster analysis method for pattern recognition is separately applied to both simulation results and reference data. Afterwards, various distribution-free statistical tests are applied depending on the specific situation to detect statistical significant
Full Text Available Drylands cover about 40% of the terrestrial land surface and account for approximately 40% of global net primary productivity. Water is fundamental to the biophysical processes that sustain ecosystem function and food production, particularly in drylands where a tight coupling exists between ecosystem productivity, surface energy balance, biogeochemical cycles, and water resource availability. Currently, drylands support at least 2 billion people and comprise both natural and managed ecosystems. In this synthesis, we identify some current critical issues in the understanding of dryland systems and discuss how arid and semiarid environments are responding to the changes in climate and land use. The issues range from societal aspects such as rapid population growth, the resulting food and water security, and development issues, to natural aspects such as ecohydrological consequences of bush encroachment and the causes of desertification. To improve current understanding and inform upon the needed research efforts to address these critical issues, we identify some recent technical advances in terms of monitoring dryland water dynamics, water budget and vegetation water use, with a focus on the use of stable isotopes and remote sensing. These technological advances provide new tools that assist in addressing critical issues in dryland ecohydrology under climate change.
Wang, L.; D'Odorico, P.; Evans, J. P.; Eldridge, D. J.; McCabe, M. F.; Caylor, K. K.; King, E. G.
Drylands cover about 40% of the terrestrial land surface and account for approximately 40% of global net primary productivity. Water is fundamental to the biophysical processes that sustain ecosystem function and food production, particularly in drylands where a tight coupling exists between ecosystem productivity, surface energy balance, biogeochemical cycles, and water resource availability. Currently, drylands support at least 2 billion people and comprise both natural and managed ecosystems. In this synthesis, we identify some current critical issues in the understanding of dryland systems and discuss how arid and semiarid environments are responding to the changes in climate and land use. The issues range from societal aspects such as rapid population growth, the resulting food and water security, and development issues, to natural aspects such as ecohydrological consequences of bush encroachment and the causes of desertification. To improve current understanding and inform upon the needed research efforts to address these critical issues, we identify some recent technical advances in terms of monitoring dryland water dynamics, water budget and vegetation water use, with a focus on the use of stable isotopes and remote sensing. These technological advances provide new tools that assist in addressing critical issues in dryland ecohydrology under climate change.
Bernhard M Riegl
Full Text Available Climate change scenarios suggest an increase in tropical ocean temperature by 1-3°C by 2099, potentially killing many coral reefs. But Arabian/Persian Gulf corals already exist in this future thermal environment predicted for most tropical reefs and survived severe bleaching in 2010, one of the hottest years on record. Exposure to 33-35°C was on average twice as long as in non-bleaching years. Gulf corals bleached after exposure to temperatures above 34°C for a total of 8 weeks of which 3 weeks were above 35°C. This is more heat than any other corals can survive, providing an insight into the present limits of holobiont adaptation. We show that average temperatures as well as heat-waves in the Gulf have been increasing, that coral population levels will fluctuate strongly, and reef-building capability will be compromised. This, in combination with ocean acidification and significant local threats posed by rampant coastal development puts even these most heat-adapted corals at risk. WWF considers the Gulf ecoregion as "critically endangered". We argue here that Gulf corals should be considered for assisted migration to the tropical Indo-Pacific. This would have the double benefit of avoiding local extinction of the world's most heat-adapted holobionts while at the same time introducing their genetic information to populations naïve to such extremes, potentially assisting their survival. Thus, the heat-adaptation acquired by Gulf corals over 6 k, could benefit tropical Indo-Pacific corals who have <100 y until they will experience a similarly harsh climate. Population models suggest that the heat-adapted corals could become dominant on tropical reefs within ∼20 years.
Yamagata, Yoshiki; Murakami, Daisuke; Peters, Gareth W.; Matsui, Tomoko
Real-time urban climate monitoring provides useful information that can be utilized to help monitor and adapt to extreme events, including urban heatwaves. Typical approaches to the monitoring of climate data include weather station monitoring and remote sensing. However, climate monitoring stations are very often distributed spatially in a sparse manner, and consequently, this has a significant impact on the ability to reveal exposure risks due to extreme climates at an intra-urban scale. Ad...
Mitchell, Daniel; Heaviside, Clare; Vardoulakis, Sotiris; Huntingford, Chris; Masato, Giacomo; Guillod, Benoit P.; Frumhoff, Peter; Bowery, Andy; Wallom, David; Allen, Myles
It has been argued that climate change is the biggest global health threat of the 21st century. The extreme high temperatures of the summer of 2003 were associated with up to seventy thousand excess deaths across Europe. Previous studies have attributed the meteorological event to the human influence on climate, or examined the role of heat waves on human health. Here, for the first time, we explicitly quantify the role of human activity on climate and heat-related mortality in an event attribution framework, analysing both the Europe-wide temperature response in 2003, and localised responses over London and Paris. Using publicly-donated computing, we perform many thousands of climate simulations of a high-resolution regional climate model. This allows generation of a comprehensive statistical description of the 2003 event and the role of human influence within it, using the results as input to a health impact assessment model of human mortality. We find large-scale dynamical modes of atmospheric variability remain largely unchanged under anthropogenic climate change, and hence the direct thermodynamical response is mainly responsible for the increased mortality. In summer 2003, anthropogenic climate change increased the risk of heat-related mortality in Central Paris by ∼70% and by ∼20% in London, which experienced lower extreme heat. Out of the estimated ∼315 and ∼735 summer deaths attributed to the heatwave event in Greater London and Central Paris, respectively, 64 (±3) deaths were attributable to anthropogenic climate change in London, and 506 (±51) in Paris. Such an ability to robustly attribute specific damages to anthropogenic drivers of increased extreme heat can inform societal responses to, and responsibilities for, climate change.
Full Text Available Various types of slope processes, mainly landslides and avalanches (snow, rock, clay and debris pose together with floods the main geohazards in Norway. Landslides and avalanches have caused more than 2000 casualties and considerable damage to infrastructure over the last 150 years. The interdisciplinary research project "GeoExtreme" focuses on investigating the coupling between meteorological factors and landslides and avalanches, extrapolating this into the near future with a changing climate and estimating the socioeconomic implications. The main objective of the project is to predict future geohazard changes in a changing climate. A database consisting of more than 20 000 recorded historical events have been coupled with a meteorological database to assess the predictability of landslides and avalanches caused by meteorological conditions. Present day climate and near future climate scenarios are modelled with a global climate model on a stretched grid, focusing on extreme weather events in Norway. The effects of climate change on landslides and avalanche activity are studied in four selected areas covering the most important climatic regions in Norway. The statistical analysis of historical landslide and avalanche events versus weather observations shows strong regional differences in the country. Avalanches show the best correlation with weather events while landslides and rockfalls are less correlated. The new climate modelling approach applying spectral nudging to achieve a regional downscaling for Norway proves to reproduce extreme events of precipitation much better than conventional modelling approaches. Detailed studies of slope stabilities in one of the selected study area show a high sensitivity of slope stability in a changed precipitation regime. The value of elements at risk was estimated in one study area using a GIS based approach that includes an estimation of the values within given present state hazard zones. The ongoing
Ashraf Vaghefi, Saeid; Abbaspour, Karim C.
Estimating magnitude and occurrence frequency of extreme hydrological events is required for taking preventive remedial actions against the impact of climate change on the management of water resources. Examples include: characterization of extreme rainfall events to predict urban runoff, determination of river flows, and the likely severity of drought events during the design life of a water project. In recent years California has experienced its most severe drought in recorded history, causing water stress, economic loss, and an increase in wildfires. In this paper we describe development of a Climate Change Toolkit (CCT) and demonstrate its use in the analysis of dry and wet periods in California for the years 2020-2050 and compare the results with the historic period 1975-2005. CCT provides four modules to: i) manage big databases such as those of Global Climate Models (GCMs), ii) make bias correction using observed local climate data , iii) interpolate gridded climate data to finer resolution, and iv) calculate continuous dry- and wet-day periods based on rainfall, temperature, and soil moisture for analysis of drought and flooding risks. We used bias-corrected meteorological data of five GCMs for extreme CO2 emission scenario rcp8.5 for California to analyze the trend of extreme hydrological events. The findings indicate that frequency of dry period will increase in center and southern parts of California. The assessment of the number of wet days and the frequency of wet periods suggests an increased risk of flooding in north and north-western part of California, especially in the coastal strip. Keywords: Climate Change Toolkit (CCT), Extreme Hydrological Events, California
Casola, J. H.; Huber, D.
Many media, academic, government, and advocacy organizations have achieved sophistication in developing effective messages based on scientific information, and can quickly translate salient aspects of emerging climate research and evolving observations. However, there are several ways in which valid messages can be misconstrued by decision makers, leading them to inaccurate conclusions about the risks associated with climate impacts. Three cases will be discussed: 1) Issues of spatial scale in interpreting climate observations: Local climate observations may contradict summary statements about the effects of climate change on larger regional or global spatial scales. Effectively addressing these differences often requires communicators to understand local and regional climate drivers, and the distinction between a 'signal' associated with climate change and local climate 'noise.' Hydrological statistics in Missouri and California are shown to illustrate this case. 2) Issues of complexity related to extreme events: Climate change is typically invoked following a wide range of damaging meteorological events (e.g., heat waves, landfalling hurricanes, tornadoes), regardless of the strength of the relationship between anthropogenic climate change and the frequency or severity of that type of event. Examples are drawn from media coverage of several recent events, contrasting useful and potentially confusing word choices and frames. 3) Issues revolving around climate sensitivity: The so-called 'pause' or 'hiatus' in global warming has reverberated strongly through political and business discussions of climate change. Addressing the recent slowdown in warming yields an important opportunity to raise climate literacy in these communities. Attempts to use recent observations as a wedge between climate 'believers' and 'deniers' is likely to be counterproductive. Examples are drawn from Congressional testimony and media stories. All three cases illustrate ways that decision
Willems, P.; Olsson, J.; Arnbjerg-Nielsen, Karsten;
Under the umbrella of the IWA/IAHR Joint Committee on Urban Drainage, the International Working Group on Urban Rainfall (IGUR) has reviewed existing methodologies for the analysis of long-term historical and future trends in urban rainfall extremes and their effects on urban drainage systems, due...... to anthropogenic climate change. Current practices have several limitations and pitfalls, which are important to be considered by trend or climate change impact modellers and users of trend/impact results. Climate change may well be the driver that ensures that changes in urban drainage paradigms are...
Sunyer Pinya, Maria Antonia; Madsen, H.; Rosbjerg, Dan; Arnbjerg-Nielsen, Karsten
Climate Models (RCMs) and General Circulation Models (GCMs). These multi-model ensembles provide the information needed to estimate probabilistic climate change projections. Several probabilistic methods have been suggested. One common assumption in most of these methods is that the climate models are...... independent. The effects of this assumption on the uncertainty quantification of extreme rainfall projections are addressed in this study. First, the interdependency of the 95% quantile of wet days in the ENSEMBLES RCMs is estimated. For this statistic and the region studied, the RCMs cannot be assumed...
Tao, F.; Rötter, R.
Many studies on global climate report that climate variability is increasing with more frequent and intense extreme events1. There are quite large uncertainties from both the plot- and regional-scale models in simulating impacts of climate variability and extremes on crop development, growth and productivity2,3. One key to reducing the uncertainties is better exploitation of experimental data to eliminate crop model deficiencies and develop better algorithms that more adequately capture the impacts of extreme events, such as high temperature and drought, on crop performance4,5. In the present study, in a first step, the inter-annual variability in wheat yield and climate from 1971 to 2012 in Finland was investigated. Using statistical approaches the impacts of climate variability and extremes on wheat growth and productivity were quantified. In a second step, a plot-scale model, WOFOST6, and a regional-scale crop model, MCWLA7, were calibrated and validated, and applied to simulate wheat growth and yield variability from 1971-2012. Next, the estimated impacts of high temperature stress, cold damage, and drought stress on crop growth and productivity based on the statistical approaches, and on crop simulation models WOFOST and MCWLA were compared. Then, the impact mechanisms of climate extremes on crop growth and productivity in the WOFOST model and MCWLA model were identified, and subsequently, the various algorithm and impact functions were fitted against the long-term crop trial data. Finally, the impact mechanisms, algorithms and functions in WOFOST model and MCWLA model were improved to better simulate the impacts of climate variability and extremes, particularly high temperature stress, cold damage and drought stress for location-specific and large area climate impact assessments. Our studies provide a good example of how to improve, in parallel, the plot- and regional-scale models for simulating impacts of climate variability and extremes, as needed for
Arnbjerg-Nielsen, Karsten; Willems, P.; Olsson, J.;
A review is made of current methods for assessing future changes in urban rainfall extremes and their effects on urban drainage systems, due to anthropogenic-induced climate change. The review concludes that in spite of significant advances there are still many limitations in our understanding of...
Furger, M.; Rogiers, N.; Eugster, W. [University of Bern and ETH Zurich (Switzerland)
The summer of 2003 was the hottest summer in Switzerland on record. Field campaigns performed during such extreme events may yield exceptional results that are difficult to generalize. But they also give a flavour of how a warmer climate could affect the vegetation in mountainous areas. (author)
Kundeti, K.; Kanikicharla, K. K.; Al sulaiti, M.; Khulaifi, M.; Alboinin, N.; Kito, A.
The climate of the State of Qatar and the adjacent region is dominated by subtropical dry, hot desert climate with low annual rainfall, very high temperatures in summer and a big difference between maximum and minimum temperatures, especially in the inland areas. The coastal areas are influenced by the Arabian Gulf, and have lower maximum, but higher minimum temperatures and a higher moisture percentage in the air. The global warming can have profound impact on the mean climate as well as extreme weather events over the Arabian Peninsula that may affect both natural and human systems significantly. Therefore, it is important to assess the future changes in the seasonal/annual mean of temperature and precipitation and also the extremes in temperature and wind events for a country like Qatar. This study assesses the performance of the Coupled Model Inter comparison Project Phase 5 (CMIP5) simulations in present and develops future climate scenarios. The changes in climate extremes are assessed for three future periods 2016-2035, 2046-2065 and 2080-2099 with respect to 1986-2005 (base line) under two RCPs (Representative Concentrate Pathways) - RCP4.5 and RCP8.5. We analyzed the projected changes in temperature and precipitation extremes using several indices including those that capture heat stress. The observations show an increase in warm extremes over many parts in this region that are generally well captured by the models. The results indicate a significant change in frequency and intensity of both temperature and precipitation extremes over many parts of this region which may have serious implications on human health, water resources and the onshore/offshore infrastructure in this region. Data from a high-resolution (20km) AGCM simulation from Meteorological Research Institute of Japan Meteorological Agency for the present (1979-2003) and a future time slice (2075-2099) corresponding to RCP8.5 have also been utilized to assess the impact of climate change on
Jones, B.; O'Neill, B. C.; Tebaldi, C.; Oleson, K. W.
Extreme heat events are projected to increase in frequency and intensity in the coming decades . The physical effects of extreme heat on human populations are well-documented, and anticipating changes in future exposure to extreme heat is a key component of adequate planning/mitigation [2, 3]. Exposure to extreme heat depends not only on changing climate, but also on changes in the size and spatial distribution of the human population. Here we focus on systematically quantifying exposure to extreme heat as a function of both climate and population change. We compare exposure outcomes across multiple global climate and spatial population scenarios, and characterize the relative contributions of each to population exposure to extreme heat. We consider a 2 x 2 matrix of climate and population output, using projections of heat extremes corresponding to RCP 4.5 and RCP 8.5 from the NCAR community land model, and spatial population projections for SSP 3 and SSP 5 from the NCAR spatial population downscaling model. Our primary comparison is across RCPs - exposure outcomes from RCP 4.5 versus RCP 8.5 - paying particular attention to how variation depends on the choice of SSP in terms of aggregate global and regional exposure, as well as the spatial distribution of exposure. We assess how aggregate exposure changes based on the choice of SSP, and which driver is more important, population or climate change (i.e. does that outcome vary more as a result of RCP or SSP). We further decompose the population component to analyze the contributions of total population change, migration, and changes in local spatial structure. Preliminary results from a similar study of the US suggests a four-to-six fold increase in total exposure by the latter half of the 21st century. Changes in population are as important as changes in climate in driving this outcome, and there is regional variation in the relative importance of each. Aggregate population growth, as well as redistribution of
Laux, Patrick; Dang, Thinh; Kunstmann, Harald
We investigate possible impacts of climate change on future floods in the VuGia-ThuBon river basin, central Vietnam using a multi-model climate ensemble. An ensemble of regional climate projections (SRES) derived from different combinations of global and regional climate models in combination with different emission scenarios are used. In order to correct for the biases between the modelled climate variables and the observations, different bias correction techniques such as linear scaling, local intensity scaling, and quantile mapping are applied to the RCM outputs. Bias-corrected and raw climate data are then used as input for the fully distributed hydrological water balance model WaSIM-ETH to reproduce discharge data at NongSon station. Annual maximum discharges are extracted from the modeled daily series from the control period (1980-1999) and the future periods 2011-2030, 2031-2050, and 2080-2099 for subsequent extreme frequency analyses. To derive flood frequency curves for the four time periods, the generalized extreme value probability distribution is fitted to the data. Our analysis shows that actually none of the bias correction approaches applied to the control runs of simulated precipitation data can satisfactorily correct their distributions towards those of the observations. Therefore, this study builds further on the delta change approach, which adjusts the observed extreme values by the derived signals from the hydrological simulations fed by raw future climate projections. Adjusted return periods of e.g. HQ100 values are calculated based on the delta change method. The results inhibit a remarkable variation among the different climate scenarios in representing extreme values. Results show that MRI-MRI, ECHAM3-REMO, HadCMQ10-HadRM3P and HadCMQ13-HadRM3P models always exhibit a positive signal for all considered time slices and climate change scenarios. On the other hand, CCSM-MM5 frequently shows a negative signal for all time slices. On average, an
Willems, Patrick; Olsson, Jonas; Arnbjerg-Nielsen, Karsten; Beecham, Simon; Pathirana, Assela; Bülow Gregersen, Ida; Madsen, Henrik; Nguyen, Van-Thanh-Van
Under the umbrella of the IWA/IAHR Joint Committee on Urban Drainage, the International Working Group on Urban Rainfall (IGUR) has reviewed existing methodologies for the analysis of long-term historical and future trends in urban rainfall extremes and their effects on urban drainage systems, due to anthropogenic climate change. Current practises have several limitations and pitfalls, which are important to be considered by trend or climate change impact modellers and users of trend/impact results. The review considers the following aspects: Analysis of long-term historical trends due to anthropogenic climate change: influence of data limitation, instrumental or environmental changes, interannual variations and longer term climate oscillations on trend testing results. Analysis of long-term future trends due to anthropogenic climate change: by complementing empirical historical data with the results from physically-based climate models, dynamic downscaling to the urban scale by means of Limited Area Models (LAMs) including explicitly small-scale cloud processes; validation of RCM/GCM results for local conditions accounting for natural variability, limited length of the available time series, difference in spatial scales, and influence of climate oscillations; statistical downscaling methods combined with bias correction; uncertainties associated with the climate forcing scenarios, the climate models, the initial states and the statistical downscaling step; uncertainties in the impact models (e.g. runoff peak flows, flood or surcharge frequencies, and CSO frequencies and volumes), including the impacts of more extreme conditions than considered during impact model calibration and validation. Implications for urban drainage infrastructure design and management: upgrading of the urban drainage system as part of a program of routine and scheduled replacement and renewal of aging infrastructure; how to account for the uncertainties; flexible and sustainable solutions
Full Text Available The Peruvian anchovy fishery is the largest worldwide in terms of catches. The fishery started during the mid 1950s, and since then it has been highly dependent on natural stock fluctuations, due to the sensitivity of anchovy stocks to ocean-climate variability. The main driver of anchovy stock variability is the El Niño Southern Oscillation (ENSO, and three extreme ENSO warm events were recorded in 1972–1973, 1983–1984 and 1997–1998. This study investigates the evolution of coping strategies developed by the anchovy fisheries to deal with climate variability and extreme ENSO events. Results showed eight coping strategies to reduce impacts on the fishery. These included: decentralized installation of anchovy processing factories; simultaneous ownership of fishing fleet and processing factories; use of low-cost unloading facilities; opportunistic utilization of invading fish populations; low cost intensive monitoring; rapid flexible management; reduction of fishmeal price uncertainty through controlled production based on market demand; and decoupling of fishmeal prices from those of other protein-rich feed substitutes like soybean. This research shows that there are concrete lessons to be learned from successful adaptations to cope with climate change-related extreme climatic events that impact the supply of natural resources. The lessons can contribute to improved policies for coping with climate change in the commercial fishery sector.
Heimbach, Patrick [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
A main research objectives of PISCEES is the development of formal methods for quantifying uncertainties in ice sheet modeling. Uncertainties in simulating and projecting mass loss from the polar ice sheets arise primarily from initial conditions, surface and basal boundary conditions, and model parameters. In general terms, two main chains of uncertainty propagation may be identified: 1. inverse propagation of observation and/or prior onto posterior control variable uncertainties; 2. forward propagation of prior or posterior control variable uncertainties onto those of target output quantities of interest (e.g., climate indices or ice sheet mass loss). A related goal is the development of computationally efficient methods for producing initial conditions for an ice sheet that are close to available present-day observations and essentially free of artificial model drift, which is required in order to be useful for model projections (“initialization problem”). To be of maximum value, such optimal initial states should be accompanied by “useful” uncertainty estimates that account for the different sources of uncerainties, as well as the degree to which the optimum state is constrained by available observations. The PISCEES proposal outlined two approaches for quantifying uncertainties. The first targets the full exploration of the uncertainty in model projections with sampling-based methods and a workflow managed by DAKOTA (the main delivery vehicle for software developed under QUEST). This is feasible for low-dimensional problems, e.g., those with a handful of global parameters to be inferred. This approach can benefit from derivative/adjoint information, but it is not necessary, which is why it often referred to as “non-intrusive”. The second approach makes heavy use of derivative information from model adjoints to address quantifying uncertainty in high-dimensions (e.g., basal boundary conditions in ice sheet models). The use of local gradient, or
Lajeunesse, E.; Delacourt, C.; Allemand, P.; Limare, A.; Dessert, C.; Ammann, J.; Grandjean, P.
A series of recent works have underlined that the flux of material exported outside of a watershed is dramatically increased during extreme climatic events, such as storms, tropical cyclones and hurricanes [Dadson et al., 2003 and 2004; Hilton et al., 2008]. Indeed the exceptionally high rainfall rates reached during these events trigger runoff and landsliding which destabilize slopes and accumulate a significant amount of sediments in flooded rivers. This observation raises the question of the control that extreme climatic events might exert on the denudation rate and the morphology of watersheds. Addressing this questions requires to measure sediment transport in flooded rivers. However most conventional sediment monitoring technics rely on manned operated measurements which cannot be performed during extreme climatic events. Monitoring riverine sediment transport during extreme climatic events remains therefore a challenging issue because of the lack of instruments and methodologies adapted to such extreme conditions. In this paper, we present a new methodology aimed at estimating the impact of extreme events on sediment transport in rivers. Our approach relies on the development of two instruments. The first one is an in-situ optical instrument, based on a LISST-25X sensor, capable of measuring both the water level and the concentration of suspended matter in rivers with a time step going from one measurement every hour at low flow to one measurement every 2 minutes during a flood. The second instrument is a remote controlled drone helicopter used to acquire high resolution stereophotogrammetric images of river beds used to compute DEMs and to estimate how flash floods impact the granulometry and the morphology of the river. These two instruments were developed and tested during a 1.5 years field survey performed from june 2007 to january 2009 on the Capesterre river located on Basse-Terre island (Guadeloupe archipelago, Lesser Antilles Arc).
Lenaerts, J.T.M.; van den Broeke, M.R.; van Wessem, J.M.; van de Berg, W.J.; van Meijgaard, E.; van Ulft, L.H.; Schaefer, M.
This study uses output of a high-resolution (5.5 km) regional atmospheric climate model to describe the present-day (1979–2012) climate of Patagonia, with a particular focus on the surface mass balance (SMB) of the Patagonian ice fields. Through a comparison with available in situ observations, it i
Full Text Available In this study, past (1970-2005 as well as future long term (2011-2099 trends in various extreme events of temperature and precipitation have been investigated over selected hydro-meteorological stations in the Sutlej river basin. The ensembles of two Coupled Model Intercomparison Project (CMIP3 models: third generation Canadian Coupled Global Climate Model and Hadley Centre Coupled Model have been used for simulation of future daily time series of temperature (maximum and minimum and precipitation under A2 emission scenario. Large scale atmospheric variables of both models and National Centre for Environmental Prediction/National Centre for Atmospheric Research reanalysis data sets have been downscaled using statistical downscaling technique at individual stations. A total number of 25 extreme indices of temperature (14 and precipitation (11 as specified by the Expert Team of the World Meteorological Organization and Climate Variability and Predictability are derived for the past and future periods. Trends in extreme indices are detected over time using the modified Mann-Kendall test method. The stations which have shown either decrease or no change in hot extreme events (i.e., maximum TMax, warm days, warm nights, maximum TMin, tropical nights, summer days and warm spell duration indicators for 1970–2005 and increase in cold extreme events (cool days, cool nights, frost days and cold spell duration indicators are predicted to increase and decrease respectively in the future. In addition, an increase in frequency and intensity of extreme precipitation events is also predicted.
Extreme events are often defined as rare events, for example floods or heavy precipitation events. Then very extreme events cannot be counted any more, and the use of a theoretical distribution to extrapolate to yet not observed quantiles is a general approach. Extreme value theory (EVT) deals with the specific characteristics of extreme values, for example their asymmetric distribution, and provides according theoretical distributions. In hydrology, the use of EVT has a long tradition. A prominent example is the estimation of 100-year flood return levels for water management purposes. It is likely that changes to hydrological extremes due to climate change will have a great impact on human society in the future: Temperature increase might amplify the occurrence of heavy precipitation events due to an increased water-holding capacity of the atmosphere. On the other hand, regions, which are already vulnerable to water stress, might have to cope with an intensification of droughts. The adequate description of the characteristics of extreme hydrological events and their changes is thus a core element of risk assessment and water management. In this talk, examples of the use of EVT to assess hydrological extremes are given. Results for flood occurrence in Southern Germany and droughts in Central Spain will be presented. A focus will be set on the treatment of temporal or spatial evolving extremes, and the assessment of future changes.
Foulon, E.; Gagnon, P.; Rousseau, A. N.
Extreme flow conditions such as droughts and floods are in general the direct consequences of short- to long-term weather/climate anomalies. For example, in southern Quebec, Canada, winter and summer 7-day low flows are due to summer and fall precipitations. Which prompts the question: is it possible to assess future extreme flow conditions from meteorological/climate indices or should we rely on the classical approach of using outputs of climate models as input to a hydrological model? The objective of this study is to assess six hydrological indices describing extreme flows at the watershed scale (Qmax, Qmin;7d, Qmin;30d for two seasons: winter and summer) using local climate indices without relying on the aforementioned classical approach. To establish the relationship between climate and hydrological indices, daily precipitations, minimum and maximum temperatures from 89 climate projections are used as inputs to a distributed hydrological model. River flows are simulated at the outlet of the Yamaska and Bécancour watersheds in Québec for the 1961-2100 periods. To identify the best predictors, hydrological indices are extracted from the flow series, and climate indices are computed for different time intervals (from a day up to four years). The difference between four-month, cumulative, climatic demand (P-ETP) explains 69% of the 7-day summer low flow during the calibration process. For both watersheds, preliminary findings indicate that the selected indices explain, on average, 38 and 60% of the variability of high- and low-flow indices, respectively. Overall, the results clearly illustrate that the change in the hydrological indices can be detected through the concurrent trends in the climate indices. The use of many climate projections ensures the relationships are not simulation-dependent and shows summer events are particularly at risk with increasing high flows and decreasing low flows. The development of a simple predictive tool to assess the impact of
Lee, K.; Gao, H.; Huang, M.; Sheffield, J.
With the changing climate, hydrologic extremes (such as floods, droughts, and heat waves) are becoming more frequent and intensified. Such changes in extreme events are expected to affect agricultural production and food supplies. This study focuses on the State of Texas, which has the largest farm area and the highest value of livestock production in the U.S. The objectives are two-fold: First, to investigate the climatic impact on the occurrence of future hydrologic extreme events; and second, to evaluate the effects of the future extremes on agricultural production. The Variable Infiltration Capacity (VIC) model, which is calibrated and validated over Texas river basins during the historical period, is employed for this study. The VIC model is forced by the statistically downscaled climate projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) model ensembles at a spatial resolution of 1/8°. The CMIP5 projections contain four different scenarios in terms of Representative Concentration Pathway (RCP) (i.e. 2.6, 4.5, 6.0 and 8.5 w/m2). To carry out the analysis, VIC outputs forced by the CMIP5 model scenarios over three 30-year periods (1970-1999, 2020-2049 and 2070-2099) are first evaluated to identify how the frequency and the extent of the extreme events will be altered in the ten Texas major river basins. The results suggest that a significant increase in the number of extreme events will occur starting in the first half of the 21st century in Texas. Then, the effects of the predicted hydrologic extreme events on the irrigation water demand are investigated. It is found that future changes in water demand vary by crop type and location, with an east-to-west gradient. The results are expected to contribute to future water management and planning in Texas.
McCarthy, M.; Kenneston, A.; Wall, T. U.; Brown, T. J.; Redmond, K. T.
Effective climate resiliency planning at the regional level requires extensive interactive dialogue among climate scientists, emergency managers, public health officials, urban planners, social scientists, and policy makers. Engaging federal, tribal, state, local governments and private sector business and infrastructure owners/operators in defining, assessing and characterizing the impacts of extreme events allows communities to understand how different events "break the system" forcing local communities to seek support and resources from state/federal governments and/or the private sector and what actions can be taken proactively to mitigate consequences and accelerate recovery. The Washoe County Regional Resiliency Study was prepared in response to potential climate variability related impacts specific to the Northern Nevada Region. The last several decades have seen dramatic growth in the region, coupled with increased resource demands that have forced local governments to consider how those impacts will affect the region and may, in turn, impact the region's ability to provide essential services. The Western Regional Climate Center of the Desert Research Institute provided a synthesis of climate studies with predictions regarding plausible changes in the local climate of Northern California and Nevada for the next 50 years. In general, these predictions indicate that the region's climate is undergoing a gradual shift, which will primarily affect the frequency, amount, and form of precipitation in the Sierra Nevada and Great Basin. Changes in water availability and other extreme events may have serious and long lasting effects in the Northern Nevada Region, and create a variety of social, environmental and economic concerns. A range of extreme events were considered including Adverse Air Quality, Droughts, Floods, Heat Waves, High Wind, Structure Fires, Wildland Fires, and Major Winter Storms. Due to the complexity of our climate systems, and the difficulty in
Liu, Yupeng; Yu, Deyong; Su, Yun; Hao, Ruifang
Climate change comprises three fractions of trend, fluctuation, and extreme event. Assessing the effect of climate change on terrestrial ecosystem requires an understanding of the action mechanism of these fractions, respectively. This study examined 11 years of remotely sensed-derived net primary productivity (NPP) to identify the impacts of the trend and fluctuation of climate change as well as extremely low temperatures caused by a freezing disaster on ecosystem productivity in Hunan province, China. The partial least squares regression model was used to evaluate the contributions of temperature, precipitation, and photosynthetically active radiation (PAR) to NPP variation. A climatic signal decomposition and contribution assessment model was proposed to decompose climate factors into trend and fluctuation components. Then, we quantitatively evaluated the contributions of each component of climatic factors to NPP variation. The results indicated that the total contribution of the temperature, precipitation, and PAR to NPP variation from 2001 to 2011 in Hunan province is 85 %, and individual contributions of the temperature, precipitation, and PAR to NPP variation are 44 % (including 34 % trend contribution and 10 % fluctuation contribution), 5 % (including 4 % trend contribution and 1 % fluctuation contribution), and 36 % (including 30 % trend contribution and 6 % fluctuation contribution), respectively. The contributions of temperature fluctuation-driven NPP were higher in the north and lower in the south, and the contributions of precipitation trend-driven NPP and PAR fluctuation-driven NPP are higher in the west and lower in the east. As an instance of occasionally triggered disturbance in 2008, extremely low temperatures and a freezing disaster produced an abrupt decrease of NPP in forest and grass ecosystems. These results prove that the climatic trend change brought about great impacts on ecosystem productivity and that climatic fluctuations and
Munevar, A.; Das, T.
Current evaluations of Central Valley, California flood control improvements are based on climate and hydrologic conditions that occurred over the past 100 years. This historical period includes significant flood events caused by intense precipitation, rapid snowmelt, and watershed conditions that, in combination, result in the hydrologic conditions that have shaped the current flood infrastructure and management. Future climate projections indicate the potential for increased flood peak flows and flood volumes in the Central Valley that will likely exceed the current capacity of existing flood control systems. Preliminary estimates of potential changes in flood flows have been developed for all the major watersheds in the Central Valley through the use of regionally downscaled climate projections and hydrologic modeling. Results suggest increasing flood risks that are dependent on spatial climate change patterns, individual watershed characteristics, and existing infrastructure investments. In many areas, the increasing flood risks cannot be managed through traditional flood infrastructure alone, and more adaptive measures are needed to improve resilience under climate extremes. Planning approaches are being applied to consider the full range of flood risks, and include tiered interventions for events beyond the floods-of-record. The on-going flood risk planning efforts demonstrate new, and sensible approaches toward improving resilience for uncertain and evolving climate extremes.
Full Text Available The objective of this study was to estimate the potential sediment yield distribution in Japan attributed to extreme-rainfall-induced slope failures in the future. For this purpose, a regression relationship between the slope failure probability and the subsequent sediment yield was developed by using sediment yield observations from 59 dams throughout Japan. The slope failure probability accounts for the effects of topography (as relief energy, geology and hydro-climate variations (hydraulic gradient changes due to extreme rainfall variations and determines the potential slope failure occurrence with a 1-km resolution. The applicability of the developed relationship was then validated by comparing the simulated and observed sediment yields in another 43 dams. To incorporate the effects of a changing climate, extreme rainfall variations were estimated by using two climate change scenarios (the MRI-RCM20 Ver.2 model A2 scenario and the MIROC A1B scenario for the future and by accounting for the slope failure probability through the effect of extreme rainfall on the hydraulic gradient. Finally, the developed slope failure hazard-sediment yield relationship was employed to estimate the potential sediment yield distribution under a changing climate in Japan.
Time series analyses of annual sediment yields covering 15–20 years in 59 dams reveal that extreme sedimentation events have a high probability of occurring on average every 5–7 years. Therefore, the extreme-rainfall-induced slope failure probability with a five-year return period has a statistically robust relationship with specific sediment yield observations (with r2 = 0.65. The verification demonstrated that the model is effective for use in simulating specific sediment yields with r2 = 0.74. The results of the GCM scenarios suggest that the sediment yield issue will be critical in Japan in the future. When the spatially averaged sediment
Full Text Available The effect of climate change on population-weighted concentrations of particulate matter (PM during extreme events was studied using the Parallel Climate Model (PCM, the Weather Research and Forecasting (WRF model and the UCD/CIT 3-D photochemical air quality model. A "business as usual" (B06.44 global emissions scenario was dynamically downscaled for the entire state of California between the years 2000–2006 and 2047–2053. Air quality simulations were carried out for 1008 days in each of the present-day and future climate conditions using year-2000 emissions. Population-weighted concentrations of PM0.1, PM2.5, and PM10 total mass, components species, and primary source contributions were calculated for California and three air basins: the Sacramento Valley air basin (SV, the San Joaquin Valley air basin (SJV and the South Coast Air Basin (SoCAB. Results over annual-average periods were contrasted with extreme events.
Climate change between 2000 vs. 2050 did not cause a statistically significant change in annual-average population-weighted PM2.5 mass concentrations within any major sub-region of California in the current study. Climate change did alter the annual-average composition of the airborne particles in the SoCAB, with notable reductions of elemental carbon (EC; −3% and organic carbon (OC; −3% due to increased annual-average wind speeds that diluted primary concentrations from gasoline combustion (−3% and food cooking (−4%. In contrast, climate change caused significant increases in population-weighted PM2.5 mass concentrations in central California during extreme events. The maximum 24-h average PM2.5 concentration experienced by an average person during a ten-year period in the SJV increased by 21% due to enhanced production of secondary particulate matter (manifested as NH4NO3. In general, climate change caused increased
Identification of 'critical thresholds' of temperature increase is an essential task for inform policy decisions on establishing greenhouse gas (GHG) emission targets. We use the A2 (medium-high GHG emission pathway) and B2 (medium-low) climate change scenarios produced by the Regional Climate Model PRECIS, the crop model - CERES, and socio-economic scenarios described by IPCC SRES, to simulate the average yield changes per hectare of three main grain crops (rice, wheat, and maize) at 50 km x 50 km scale. The threshold of food production to temperature increases was analyzed based on the relationship between yield changes and temperature rise, and then food security was discussed corresponding to each IPCC SRES scenario. The results show that without the CO2 fertilization effect in the analysis, the yield per hectare for the three crops would fall consistently as temperature rises beyond 2.5C; when the CO2 fertilization effect was included in the simulation, there were no adverse impacts on China's food production under the projected range of temperature rise (0.9-3.9C). A critical threshold of temperature increase was not found for food production. When the socio-economic scenarios, agricultural technology development and international trade were incorporated in the analysis, China's internal food production would meet a critical threshold of basic demand (300 kg/capita) while it would not under A2 (no CO2 fertilization); whereas basic food demand would be satisfied under both A2 and B2, and would even meet a higher food demand threshold required to sustain economic growth (400 kg/capita) under B2, when CO2 fertilization was considered
Huqiang ZHANG; LI Yaohui; GAO Xuejie
This study aims at exploring potential impacts of land-use vegetation change (LUC) on regional climate variability and extremes.Results from a pair of Australian Bureau of Meteorology Research Centre (BMRC)climate model 54-yr (1949-2002) integrations have been analysed.In the model experiments,two vegetation datasets are used,with one representing current vegetation coverage in China and the other approximating its potential coverage without human intervention.The model results show potential impacts of LUC on climate variability and extremes.There are statistically significant changes of surface interannual climate variability simulated by the model.Using different vegetation datasets,significant changes in correlation coefficients between tropical Pacific Nifio3.4 SST and precipitation and surface temperature over East Asia are identified,which indicate that changes in vegetation coverage may alter ENSO impacts on regional climate variability.Because of the lack of slowly varying surface processes when forests are removed and less rainfall is received following LUC,the ENSO signal simulated by the model becomes stronger.Results furthermore show that land-use could modulate characteristics of decadal variations in this region.When using current vegetation coverage,the model gives better simulation of observed climate variations in the region than the case using potential vegetation coverage.In addition,results suggest that land-use could be a potential factor contributing to the prolonged drought in central-west China.Changes in local climate extremes,including precipitation and surface temperature maxima and minima,are also identified.Overall,this study has illustrated the importance of further investigation of such important issues in future land-use studies.
P Guhathakurta; O P Sreejith; P A Menon
The occurrence of exceptionally heavy rainfall events and associated flash floods in many areas during recent years motivate us to study long-term changes in extreme rainfall over India. The analysis of the frequency of rainy days, rain days and heavy rainfall days as well as one-day extreme rainfall and return period has been carried out in this study to observe the impact of climate change on extreme rainfall events and flood risk in India. The frequency of heavy rainfall events are decreasing in major parts of central and north India while they are increasing in peninsular, east and north east India. The study tries to bring out some of the interesting findings which are very useful for hydrological planning and disaster managements. Extreme rainfall and flood risk are increasing significantly in the country except some parts of central India.
Sanchez, E.; Zaninelli, P.; Carril, A.; Menendez, C.; Dominguez, M.
An ensemble of seven regional climate models (RCM) included in the European CLARIS-LPB project (A Europe-South America Network for Climate Change Assessment and Impact Studies in La Plata Basin) are used to study how some features related to climatic extremes are projected to be changed by the end of XXIst century. These RCMs are forced by different IPCC-AR4 global climate models (IPSL, ECHAM5 and HadCM3), covering three different 30-year periods: present (1960-1990), near future (2010-2040) and distant future (2070-2100), with 50km of horizontal resolution. These regional climate models have previously been forced with ERA-Interim reanalysis, in a consistent procedure with CORDEX (A COordinated Regional climate Downscaling EXperiment) initiative for the South-America domain. The analysis shows a good agreement among them and the available observational databases to describe the main features of the mean climate of the continent. Here we focus our analysis on some topics of interest related to extreme events, such as the development of diagnostics related to dry-spells length, the structure of the frequency distribution functions over several subregions defined by more or less homogeneous climatic conditions (four sub-basins over the La Plata Basin, the southern part of the Amazon basin, Northeast Brazil, and the South Atlantic Convergence Zone (SACZ)), the structure of the annual cycle and their main features and relation with the length of the seasons, or the frequency of anomalous hot or cold events. One shortcoming that must be considered is the lack of observational databases with both time and spatial frequency to validate model outputs. At the same time, one challenging issue of this study is the regional modelling description of a continent where a huge variety of climates are present, from desert to mountain conditions, and from tropical to subtropical regimes. Another basic objective of this preliminary work is also to obtain a measure of the spread among
Patt, A.; Nussbaumer, P.
Extreme climate and weather events such as droughts, floods, and tropical cyclones account for over 60% of the loss of life, and over 90% of total impacts, from natural disasters. Both observed trends and global climate models (GCMs) suggest that the frequency and intensity of extreme events is increasing, and will continue to increase as a result of climate change. Among planners and policy-makers at both national and international levels there is thus concern that this rise in extreme events will lead to greater losses in the future. Since low levels of development are associated with greater numbers of people killed and needing emergency assistance from natural disasters, the concern is most pronounced for least developed countries. If, however, these countries make substantial improvements in their levels of human development, as leading forecasters suggest may be the case over the coming decades, then their vulnerability to extreme events may fall. In this study, we examine the potential combined effects of increased extreme event frequency and improved levels of human development, to generate scenarios of risk levels into the second half of the century. It is the African continent for which these results may be the most relevant, since it is widely viewed as most vulnerable to increased risks from climate change; we focus on the particular country of Mozambique, which has experienced high losses from droughts, floods, and tropical cyclones in recent decades, and stands out as being among the most vulnerable in Africa. To assess the change in risk levels from the present until 2060, we pull together three pieces of analysis. The first is a statistical analysis of the losses from 1990-2007 from climate-related disasters, using national level data from the Centre for Research on the Epidemiology of Disasters (CRED) and the United Nations. From this analysis, we establish statistical relationships between several drivers of vulnerability—including country size
The paper presents the dynamics, circulation and radiation conditions of climatic water balances KWB in Wroclaw-Swojec (Poland) in the years 1891-03. Monthly sums and the 2-, 3-, 4-, 6-, 12-months sequences of extremes have been analysed. Also, 2-, 3-, 7-, 11-years and other consecutive sums of the parameters have been studied. Climatic water balances of the vegetation season have been coupled with those in preceding periods, especially in the autumn and winter-early spring months, to underline the importance of ground water resources for the summer water regime in agroecosystems. The results demonstrated fluctuating character of the long-term dynamics of the extremes. There was a tendency of concentrating the anomalies in certain decades and their lack in others. The character of variations was strongly associated with changes of the North Atlantic Oscillation (NAO) epochs and probably with the secular rhythm of solar activity. Analyses of the long-term variability of the extremes in climatic water balances (the difference between precipitation P and reference evaporation Eo) and their determinants allowed for better understanding the problems of droughts and extremely wet years in the regional scale
Collins, W.; Wehner, M. F.; O'Brien, T. A.; Paciorek, C. J.; Krishnan, H.; Johnson, J. N.; Prabhat, M.
The potential for increasing frequency and intensity of extremephenomena including downpours, heat waves, and tropical cyclonesconstitutes one of the primary risks of climate change for society andthe environment. The challenge of characterizing these risks is thatextremes represent the "tails" of distributions of atmosphericphenomena and are, by definition, highly localized and typicallyrelatively transient. Therefore very large volumes of observationaldata and projections of future climate are required to quantify theirproperties in a robust manner. Massive data analytics are required inorder to detect individual extremes, accumulate statistics on theirproperties, quantify how these statistics are changing with time, andattribute the effects of anthropogenic global warming on thesestatistics. We describe examples of the suite of techniques the climate communityis developing to address these analytical challenges. The techniquesinclude massively parallel methods for detecting and trackingatmospheric rivers and cyclones; data-intensive extensions togeneralized extreme value theory to summarize the properties ofextremes; and multi-model ensembles of hindcasts to quantify theattributable risk of anthropogenic influence on individual extremes.We conclude by highlighting examples of these methods developed by ourCASCADE (Calibrated and Systematic Characterization, Attribution, andDetection of Extremes) project.
Full Text Available In the context of predicted alteration of sea ice cover and increased frequency of extreme events, it is especially timely to investigate plasticity within Antarctic species responding to a key environmental aspect of their ecology: sea ice variability. Using 13 years of longitudinal data, we investigated the effect of sea ice concentration (SIC on the foraging efficiency of Adélie penguins (Pygoscelis adeliae breeding in the Ross Sea. A 'natural experiment' brought by the exceptional presence of giant icebergs during 5 consecutive years provided unprecedented habitat variation for testing the effects of extreme events on the relationship between SIC and foraging efficiency in this sea-ice dependent species. Significant levels of phenotypic plasticity were evident in response to changes in SIC in normal environmental conditions. Maximum foraging efficiency occurred at relatively low SIC, peaking at 6.1% and decreasing with higher SIC. The 'natural experiment' uncoupled efficiency levels from SIC variations. Our study suggests that lower summer SIC than currently observed would benefit the foraging performance of Adélie penguins in their southernmost breeding area. Importantly, it also provides evidence that extreme climatic events can disrupt response plasticity in a wild seabird population. This questions the predictive power of relationships built on past observations, when not only the average climatic conditions are changing but the frequency of extreme climatic anomalies is also on the rise.
Haustein, Karsten; Otto, Friederike; Uhe, Peter; Allen, Myles; Cullen, Heidi
Extreme weather detection and attribution analysis has emerged as a core theme in climate science over the last decade or so. By using a combination of observational data and climate models it is possible to identify the role of climate change in certain types of extreme weather events such as sea level rise and its contribution to storm surges, extreme heat events and droughts or heavy rainfall and flood events. These analyses are usually carried out after an extreme event has occurred when reanalysis and observational data become available. The Climate Central WWA project will exploit the increasing forecast skill of seasonal forecast prediction systems such as the UK MetOffice GloSea5 (Global seasonal forecasting system) ensemble forecasting method. This way, the current weather can be fed into climate models to simulate large ensembles of possible weather scenarios before an event has fully emerged yet. This effort runs along parallel and intersecting tracks of science and communications that involve research, message development and testing, staged socialization of attribution science with key audiences, and dissemination. The method we employ uses a very large ensemble of simulations of regional climate models to run two different analyses: one to represent the current climate as it was observed, and one to represent the same events in the world that might have been without human-induced climate change. For the weather "as observed" experiment, the atmospheric model uses observed sea surface temperature (SST) data from GloSea5 (currently) and present-day atmospheric gas concentrations to simulate weather events that are possible given the observed climate conditions. The weather in the "world that might have been" experiments is obtained by removing the anthropogenic forcing from the observed SSTs, thereby simulating a counterfactual world without human activity. The anthropogenic forcing is obtained by comparing the CMIP5 historical and natural simulations
Forestieri, Angelo; Fowler, Hayley; Lo Conti, Francesco; Noto, Leonardo
In this study possible effects of the climate change on the extreme precipitation events have been analyzed by means of the CORDEX (Coordinated Regional climate Downscaling Experiment) data, a WCRP-sponsored program for the study of climate change effects at regional scales. In particular, some models runs from the EURO-CORDEX and the MED-CORDEX, i.e., two branch of the main project, have been exploited for the analysis of possible effects on extreme rainfall for the area of Sicily (Italy). In order to improve the reliability of reference data retrieved from the CORDEX datasets, a bias correction procedure based on hystorical measurements has been designed. Moreover, a simple cascade temporal downscaling procedure, has been applied for the derivation of sub-daily data. Results highlight that mean annual precipitation for the period 2006-2050 shows a reduction of the average total precipitation for both scenarios, rcp8.5 more than rcp4.5. The precipitation for the shorter durations has shown an increase respect to higher durations. This behaviour is confirmed by many works of the scientific community, which underline this trend. Therefore, results report the indications that in this area the up to date climate predictions are congruent with future scenarios characterized by a decrease of the total amount of precipitation with an increase of the extreme rainfall events.
Romanowicz Renata J
Full Text Available This paper presents the background, objectives, and preliminary outcomes from the first year of activities of the Polish–Norwegian project CHIHE (Climate Change Impact on Hydrological Extremes. The project aims to estimate the influence of climate changes on extreme river flows (low and high and to evaluate the impact on the frequency of occurrence of hydrological extremes. Eight “twinned” catchments in Poland and Norway serve as case studies. We present the procedures of the catchment selection applied in Norway and Poland and a database consisting of near-natural ten Polish and eight Norwegian catchments constructed for the purpose of climate impact assessment. Climate projections for selected catchments are described and compared with observations of temperature and precipitation available for the reference period. Future changes based on those projections are analysed and assessed for two periods, the near future (2021–2050 and the far-future (2071–2100. The results indicate increases in precipitation and temperature in the periods and regions studied both in Poland and Norway.
Huang, Wen-Cheng; Lin, Cheng-Yu; Hsieh, Ting-Ju
Due to global climate change, the impact caused by extreme climate has become more and more compelling. In Taiwan, the total rainfall stays in the same level, but it brings along changes to rain types. The rainfall with high recurrence interval happens frequently, leading to soil loss of slope-land, and it may further result in flooding and sediment hazards. Although Taiwan is a small island, the population density is ranked at the second highest around the world. Moreover, third-fourth of Taiwan is slope-land, so the soil and water conservation is rather important. This study is based on the international trend analysis approach to review the related researches worldwide and 264 research projects in Taiwan. It indicates that under the pressure of extreme climate and social economic changes, it has higher possibility of slope-land to face the impacts from extreme rainfall events, and meanwhile, the carrying capacity of slope-land is decreasing. The experts' brainstorming meetings were held three times, and it concluded the current problems of soil and water conservation and the goal in 2025 for sustainable resources. Also, the 20-year weather data set was adopted to screen out 3 key watersheds with the potential of flooding (Puzih River Watershed), droughts (Xindian River Watershed), and sediment hazards (Chishan River Watershed) according to the moisture index, and further, to propose countermeasures in order to realize the goal in 2025, which is "regarding to climate and socioeconomic changes, it is based on multiple use to manage watershed resources for avoiding disasters and sustaining soil and water conservation." Keyword: Extreme climate, International trend analysis, Brainstorming, Key watershed
Raible, Christoph C.; Blumer, Sandro R.; Gomez-Navarro, Juan J.; Lehner, Flavio
Changes in the climate mean state are expected to influence society, but the socio-economic sensitivity to extreme events might be even more severe. Whether or not the current frequency and severity of extreme events is a unique characteristic of anthropogenic-driven climate change can be assessed by putting the observed changes in a long-term perspective. In doing so, early instrumental series and proxy archives are a rich source to investigate also extreme events, in particular during the last millennium, yet they suffer from spatial and temporal scarcity. Therefore, simulations with coupled general circulation models (GCMs) could fill such gaps and help in deepening our process understanding. In this study, an overview of past and current efforts as well as challenges in modelling paleo weather and extreme events is presented. Using simulations of the last millennium we investigate extreme midlatitude cyclone characteristics, precipitation, and their connection to large-scale atmospheric patterns in the North Atlantic European region. In cold climate states such as the Maunder Minimum, the North Atlantic Oscillation (NAO) is found to be predominantly in its negative phase. In this sense, simulations of different models agree with proxy findings for this period. However, some proxy data available for this period suggests an increase in storminess during this period, which could be interpreted as a positive phase of the NAO - a superficial contradiction. The simulated cyclones are partly reduced over Europe, which is consistent with the aforementioned negative phase of the NAO. However, as the meridional temperature gradient is increased during this period - which constitutes a source of low-level baroclincity - they also intensify. This example illustrates how model simulations could be used to improve our proxy interpretation and to gain additional process understanding. Nevertheless, there are also limitations associated with climate modeling efforts to
Future climate changes will place big challenges to the US agricultural system, among which increasing heat stress and precipitation variability were the two major concerns. Reliable prediction of crop productions in response to the increasingly frequent and severe extreme climate is a prerequisite for developing adaptive strategies on agricultural risk management. However, the progress has been slow on quantifying the uncertainty of computational predictions at high spatial resolutions. Here we assessed the risks of future climate extremes on the US corn and soybean production using the Agricultural Production System sIMulator (APSIM) model under different climate scenarios. To quantify the uncertainty due to conceptual representations of heat, drought and flooding stress in crop models, we proposed a new strategy of algorithm ensemble in which different methods for simulating crop responses to those extreme climatic events were incorporated into the APSIM. This strategy allowed us to isolate irrelevant structure differences among existing crop models but only focus on the process of interest. Future climate inputs were derived from high-spatial-resolution (12km × 12km) Weather Research and Forecasting (WRF) simulations under Representative Concentration Pathways 4.5 (RCP 4.5) and 8.5 (RCP 8.5). Based on crop model simulations, we analyzed the magnitude and frequency of heat, drought and flooding stress for the 21st century. We also evaluated the water use efficiency and water deficit on regional scales if farmers were to boost their yield by applying more fertilizers. Finally we proposed spatially explicit adaptation strategies of irrigation and fertilizing for different management zones.
Full Text Available We investigated the effect of changing the horizontal resolution of a regional climate model (RCM on the simulation of hydrological extremes. We employed the results of three experiments of the RCM HIRHAM using a grid size of approximately 12, 25 and 50 km. These simulations were used to drive the hydrological model LISFLOOD, developed for flood forecasting at European scale. The discharge simulations of LISFLOOD were compared with statistics of observed river runoff at 209 gauging stations across Europe. The largest discrepancies in peak flow occurred in climates with a seasonal snow cover, which may be explained by inaccuracies in the simulated precipitation that accumulate over winter. Although previous studies have found that high resolution climate simulations result in more realistic patterns of extreme precipitation, especially in mountainous regions, we did not find conclusive evidence that the 12-km HIRHAM run generally yields a better simulation of peak discharges. At some gauging stations the model performance is increasing with increasing horizontal resolution of the RCM, while at other stations it is decreasing. However, the differences between the three experiments become less important in larger river basins. Above about 30 000 km2 and 120 000 km2, respectively, the 25- and 50-km runs generally provided a good approximation of the simulations based on the 12-km climatology. Under the A2 scenario of climate change, the changes in extreme discharge levels were similar between the three experiments at continental scale. At the scale of individual river basins, however, there were occasionally important differences. If we assume the 12-km HIRHAM simulation to be more realistic, the use of lower-resolution climate simulations may lead to an underestimation of future flood hazard. This means that results obtained with lower-resolution RCM simulations should be interpreted with care, as the grid scale of the climate
Full Text Available Climate extremes can trigger exceptional responses in terrestrial ecosystems, for instance by altering growth or mortality rates. Effects of this kind are often manifested in reductions of the local net primary production (NPP. Investigating a set of European long-term data on annual radial tree growth confirms this pattern: we find that 53% of tree ring width (TRW indices are below one standard deviation, and up to 16% of the TRW values are below two standard deviations in years with extremely high temperatures and low precipitation. Based on these findings we investigate if climate driven patterns in long-term tree growth data may serve as benchmarks for state-of-the-art dynamic vegetation models such as LPJmL. The model simulates NPP but not explicitly the radial tree ring growth, hence requiring a generic method to ensure an objective comparison. Here we propose an analysis scheme that quantifies the coincidence rate of climate extremes with some biotic responses (here TRW or simulated NPP. We find that the reduction in tree-ring width during drought extremes is lower than the corresponding reduction of simulated NPP. We identify ten extreme years during the 20th century in which both, model and measurements indicate high coincidence rates across Europe. However, we detect substantial regional differences in simulated and observed responses to extreme events. One explanation for this discrepancy could be that the tree-ring data have preferentially been sampled at more climatically stressed sites. The model-data difference is amplified by the fact that dynamic vegetation models are designed to simulate mean ecosystem responses at landscape or regional scale. However, we find that both model-data and measurements display carry-over effects from the previous year. We conclude that using radial tree growth is a good basis for generic model-benchmarks if the data are analyzed by scale-free measures such as coincidence analysis. Our study shows
Park, Changyong; Min, Seung-Ki
The regional climate models (RCMs) have been widely used to generate more detailed information in space and time of climate patterns produced by the global climate models (GCMs). Recently the international collaborative effort has been set up as the CORDEX (Coordinated Regional Climate Downscaling Experiment) project which covers several regional domains including East Asia. In this study, five RCMs (HadGEM3-RA, RegCM4, SNU-MM5, SNU-WRF, and YSU-RSM) participating in the CORDEX-East Asia project are evaluated in terms of their skills at simulating climatology of summer extremes. We examine bias and RMSE and conduct a Taylor diagram analysis using seasonal maxima of daily mean temperature and daily precipitation amount over the East Asia land area from 'historical' experiments of individual RCMs and their multi-model ensemble means (MME). The APHRODITE (Asian Precipitation-Highly-Resolved Observational Data Integration Toward Evaluation) datasets on 0.5° x 0.5° grids are used as observations. Results show similar systematic bias patterns between seasonal means and extremes. A cold bias is found along the coast while a warm bias occurs in the northern China. Overall wet bias appears in East Asia but there is a substantial dry bias in South Korea. This dry bias appears related to be a cold SST (sea surface temperature) around South Korea, positioning the monsoonal front (Changma) further south than observations. Taylor diagram analyses show that temperature has better skill in means than in extremes because of higher spatial correlation whereas precipitation exhibits better skill in extremes than in means due to better spatial variability. The latter implies that extreme rainfall events may be better captured although seasonal mean precipitation tends to be overestimated by RCMs. The model performances between mean and extreme are found to be closely related, but not clearly between temperature and precipitation. Temperatures are always better simulated than
Arnbjerg-Nielsen, Karsten; Gregersen, Ida Bülow; Sunyer Pinya, Maria Antonia;
precipitation extremes has led to inundations in most of the larger cities during the last 10 years. The flood in Copenhagen in 2011 implied the second highest damage costs measured in Denmark during the last 100 years. To establish cities that are resilient to pluvial floods robust projections of the frequency...... climate models are incapable of simulating extreme precipitation at the temporal scales relevant for evaluation of the urban pluvial inundation risk. Hence statistical downscaling methods have been applied. Furthermore, the effect of the emission scenario, the spatial resolution of the RCM and the...
Munoz-Arriola, F.; Smith, K.; Corzo, G.; Chacon, J.; Carrillo-Cruz, C.
A major challenge for water, energy and food security relies on the capability of agroecosyststems and ecosystems to adapt to a changing climate and land use changes. The interdependency of these forcings, understood through our ability to monitor and model processes across scales, indicate the "depth" of their impact on agroecosystems and ecosystems, and consequently our ability to predict the system's ability to return to a "normal" state. We are particularly interested in explore two questions: (1) how hydrometeorological and climate extreme events (HCEs) affect sub-seasonal to interannual changes in evapotranspiration and soil moisture? And (2) how agroecosystems recover from the effect of such events. To address those questions we use the land surface hydrologic Variable Infiltration Capacity (VIC) model and the Moderate Resolution Imaging Spectrometer-Leaf Area Index (MODIS-LAI) over two time spans (1950-2013 using a seasonal fixed LAI cycle) and 2001-2013 (an 8-day MODIS-LAI). VIC is forced by daily/16th degree resolution precipitation, minimum and maximum temperature, and wind speed. In this large-scale experiment, resiliency is defined by the capacity of a particular agroecosystem, represented by a grid cell's ET, SM, and LAI to return to a historical average. This broad, yet simplistic definition will contribute to identify the possible components and their scales involved in agroecosystems and ecosystems capacity to adapt to the incidence of HCEs and technologies used to intensify agriculture and diversify their use for food and energy production. Preliminary results show that dynamical changes in land use, tracked by MODIS data, require larger time spans to address properly the influence of technologic improvements in crop production as well as the competition for land for biofuel vs. food production. On the other hand, fixed seasonal changes in land use allow us just to identify hydrologic changes mainly due to climate variability.
Full Text Available The carbon and water cycles for a southwestern Amazonian forest site were investigated using the longest time series of fluxes of CO2 and water vapor ever reported for this site. The period from 2004 to 2010 included two severe droughts (2005 and 2010 and a flooding year (2009. The effects of such climate extremes were detected in annual sums of fluxes as well as in other components of the carbon and water cycles, such as gross primary production and water use efficiency. Gap-filling and flux-partitioning were applied in order to fill gaps due to missing data, and errors analysis made it possible to infer the uncertainty on the carbon balance. Overall, the site was found to have a net carbon uptake of ≈5 t C ha(-1 year(-1, but the effects of the drought of 2005 were still noticed in 2006, when the climate disturbance caused the site to become a net source of carbon to the atmosphere. Different regions of the Amazon forest might respond differently to climate extremes due to differences in dry season length, annual precipitation, species compositions, albedo and soil type. Longer time series of fluxes measured over several locations are required to better characterize the effects of climate anomalies on the carbon and water balances for the whole Amazon region. Such valuable datasets can also be used to calibrate biogeochemical models and infer on future scenarios of the Amazon forest carbon balance under the influence of climate change.
Zeri, Marcelo; Sá, Leonardo D A; Manzi, Antônio O; Araújo, Alessandro C; Aguiar, Renata G; von Randow, Celso; Sampaio, Gilvan; Cardoso, Fernando L; Nobre, Carlos A
The carbon and water cycles for a southwestern Amazonian forest site were investigated using the longest time series of fluxes of CO2 and water vapor ever reported for this site. The period from 2004 to 2010 included two severe droughts (2005 and 2010) and a flooding year (2009). The effects of such climate extremes were detected in annual sums of fluxes as well as in other components of the carbon and water cycles, such as gross primary production and water use efficiency. Gap-filling and flux-partitioning were applied in order to fill gaps due to missing data, and errors analysis made it possible to infer the uncertainty on the carbon balance. Overall, the site was found to have a net carbon uptake of ≈5 t C ha(-1) year(-1), but the effects of the drought of 2005 were still noticed in 2006, when the climate disturbance caused the site to become a net source of carbon to the atmosphere. Different regions of the Amazon forest might respond differently to climate extremes due to differences in dry season length, annual precipitation, species compositions, albedo and soil type. Longer time series of fluxes measured over several locations are required to better characterize the effects of climate anomalies on the carbon and water balances for the whole Amazon region. Such valuable datasets can also be used to calibrate biogeochemical models and infer on future scenarios of the Amazon forest carbon balance under the influence of climate change. PMID:24558378
The laboratory replication of the greenhouse effect appears deceptively simple. Using a cubic box illuminated by an ordinary lamp, one may show some of the phenomena present in the climate system. It is nonetheless necessary to use a lot of physical ingenuity to understand the complex interaction of radiative and convective phenomena which characterizes such a simple system. In this paper we introduce a critical review of some experiments in the literature and suggest a new and original experimental set up using an unusual gas; in this way we overcome some of the limitations of the typical laboratory experiment, confirming the possibility of using it in educational physics laboratories without any lack of physical plausibility. (paper)
Willems, Patrick; Olsson, Jonas; Arnbjerg-Nielsen, Karsten;
Under the umbrella of the IWA/IAHR Joint Committee on Urban Drainage, the International Working Group on Urban Rainfall (IGUR) has reviewed existing methodologies for the analysis of long-term historical and future trends in urban rainfall extremes and their effects on urban drainage systems, due......-term historical trends due to anthropogenic climate change, analysis of long-term future trends due to anthropogenic climate change, and implications for urban drainage infrastructure design and management. A summary is provided in this paper....
The water resources of the Black Volta Basin in West Africa constitute a major resource for the four countries (Burkina Faso, Ghana, Côte d'Ivoire, Mali) that share it. For Burkina Faso and Ghana, the river is the main natural resource around which the development of the diverse sectors of the two economies is built. Whereas Ghana relies heavily on the river for energy, land-locked Burkina Faso continuously develops the water for agricultural purposes. Such important role of the river makes it an element around which there are potential conflicts: either among riparian countries or within the individual countries themselves. This study documents the changes in temperature and precipitation extremes in the Black Volta Basin region for the past (1981-2010) and makes projections for the mid-late 21st century (2051-2080) under two emission scenarios; RCP 2.6 and RCP 8.5. The Expert Team on Climate Change Detection and Indices (ETCCDI) temperature- and precipitation-based indices are computed with the RClimdex software. Observed daily records and downscaled CORDEX data of precipitation and maximum and minimum temperatures are used for historical and future trend analysis respectively. In general low emission scenarios show increases in the cold extremes. The region shows a consistent pattern of trends in hot extremes for the 1990's. An increasing trend in hot extremes is expected in the future under RCP 8.5 while RCP 2.5 shows reductions in hot extremes. Regardless of the emission scenario, projections show more frequent hot nights in the 21st century. Generally, the region shows variability in trends for future extreme precipitation indices with only a few of the trends being statistically significant (5% level). Results obtained provide a basic and first step to understanding how climatic extremes have been changing in the Volta Basin region and gives an idea of what to expect in the future. Such studies will also help in making informed decisions on water management
Soltani, M.; Laux, P.; Kunstmann, H.; Stan, K.; Sohrabi, M. M.; Molanejad, M.; Sabziparvar, A. A.; Ranjbar SaadatAbadi, A.; Ranjbar, F.; Rousta, I.; Zawar-Reza, P.; Khoshakhlagh, F.; Soltanzadeh, I.; Babu, C. A.; Azizi, G. H.; Martin, M. V.
In this study, changes in the spatial and temporal patterns of climate extreme indices were analyzed. Daily maximum and minimum air temperature, precipitation, and their association with climate change were used as the basis for tracking changes at 50 meteorological stations in Iran over the period 1975-2010. Sixteen indices of extreme temperature and 11 indices of extreme precipitation, which have been quality controlled and tested for homogeneity and missing data, are examined. Temperature extremes show a warming trend, with a large proportion of stations having statistically significant trends for all temperature indices. Over the last 15 years (1995-2010), the annual frequency of warm days and nights has increased by 12 and 14 days/decade, respectively. The number of cold days and nights has decreased by 4 and 3 days/decade, respectively. The annual mean maximum and minimum temperatures averaged across Iran both increased by 0.031 and 0.059 °C/decade. The probability of cold nights has gradually decreased from more than 20 % in 1975-1986 to less than 15 % in 1999-2010, whereas the mean frequency of warm days has increased abruptly between the first 12-year period (1975-1986) and the recent 12-year period (1999-2010) from 18 to 40 %, respectively. There are no systematic regional trends over the study period in total precipitation or in the frequency and duration of extreme precipitation events. Statistically significant trends in extreme precipitation events are observed at less than 15 % of all weather stations, with no spatially coherent pattern of change, whereas statistically significant changes in extreme temperature events have occurred at more than 85 % of all weather stations, forming strongly coherent spatial patterns.
Cavalcanti, I. F. A.; Carril, A. F.; Penalba, O. C.; Grimm, A. M.; Menéndez, C. G.; Sanchez, E.; Cherchi, A.; Sörensson, A.; Robledo, F.; Rivera, J.; Pántano, V.; Bettolli, L. M.; Zaninelli, P.; Zamboni, L.; Tedeschi, R. G.; Dominguez, M.; Ruscica, R.; Flach, R.
Monthly and daily precipitation extremes over La Plata Basin (LPB) are analyzed in the framework of the CLARIS-LPB Project. A review of the studies developed during the project and results of additional research are presented and discussed. Specific aspects of analysis are focused on large-scale versus local processes impacts on the intensity and frequency of precipitation extremes over LPB, and on the assessment of specific wet and dry spell indices and their changed characteristics in future climate scenarios. The analysis is shown for both available observations of precipitation in the region and ad-hoc global and regional models experiments. The Pacific, Indian and Atlantic Oceans can all impact precipitation intensity and frequency over LPB. In particular, considering the Pacific sector, different types of ENSO events (i.e. canonical vs Modoki or East vs Central) have different influences. Moreover, model projections indicate an increase in the frequency of precipitation extremes over LPB during El Niño and La Ninã events in future climate. Local forcings can also be important for precipitation extremes. Here, the feedbacks between soil moisture and extreme precipitation in LPB are discussed based on hydric conditions in the region and model sensitivity experiments. Concerning droughts, it was found that they were more frequent in the western than in the eastern sector of LPB during the period of 1962-2008. On the other hand, observations and model experiments agree in that the monthly wet extremes were more frequent than the dry extremes in the northern and southern LPB sectors during the period 1979-2001, with higher frequency in the south.
Serykh, Ilya; Kostianoy, Andrey
The Fourth (2007) and Fifth (2014) Assessment Reports on Climate Change of the Intergovernmental Panel on Climate Change (IPCC) state that in the XXI century, climate change will be accompanied by an increase in the frequency, intensity and duration of extreme nature events such as: extreme precipitation and extreme high and low air temperatures. All these will lead to floods, droughts, fires, shallowing of rivers, lakes and water reservoirs, desertification, dust storms, melting of glaciers and permafrost, algal bloom events in the seas, lakes and water reservoirs. In its turn, these events will lead to chemical and biological contamination of water, land and air. These events will result in a deterioration of quality of life, significant financial loss due to damage to the houses, businesses, roads, agriculture, forestry, tourism, and in many cases they end in loss of life. These predictions are confirmed by the results of the studies presented in the RosHydromet First (2008) and Second (2014) Assessment Reports on Climate Change and its Consequences in Russian Federation. Scientists predictions have been repeatedly confirmed in the last 15 years - floods in Novorossiysk (2002), Krymsk and Gelendzhik (2012), the Far East (2013), heat waves in 2010, unusually cold winter (February) of 2012 and unusually warm winter of 2013/2014 in the European territory of Russia. In this regard, analysis and forecasting of extreme climate events associated with climate change in the territory of Russia are an extremely important task. This task is complicated by the fact that modern atmospheric models used by IPCC and RosHydromet badly reproduce and predict the intensity of precipitation. We are analyzing meteorological reanalysis data (NCEP/NCAR, 20th Century Reanalysis, ERA-20C, JRA-55) and satellite data (NASA and AVISO) on air, water and land temperature, rainfall, wind speed and cloud cover, water levels in seas and lakes, index of vegetation over the past 30-60 years
The impacts of solar activity on climate are explored in this two-part study.Based on the principles of atmospheric dynamics,Part Ⅰ propose an amplifying mechanism of solar impacts on winter climate extremes through changing the atmospheric circulation patterns.This mechanism is supported by data analysis of the sunspot number up to the predicted Solar Cycle 24,the historical surface temperature data,and atmospheric variables of NCEP/NCAR Reanalysis up to the February 2011 for the Northern Hemisphere winters.For low solar activity,the thermal contrast between the low- and high-latitudes is enhanced,so as the mid-latitude baroclinic ultra-long wave activity.The land-ocean thermal contrast is also enhanced,which amplifies the topographic waves.The enhanced mid-latitude waves in turn enhance the meridional heat transport from the low to high latitudes,making the atmospheric “heat engine” more efficient than normal. The jets shift southward and the polar vortex is weakened.The Northern Annular Mode (NAM) index tends to be negative.The mid-latitude surface exhibits large-scale convergence and updrafts,which favor extreme weather/climate events to occur.The thermally driven Siberian high is enhanced,which enhances the East Asian winter monsoon (EAWM).For high solar activity,the mid-latitude circulation patterns are less wavy with less meridional transport.The NAM tends to be positive,and the Siberian high and the EAWM tend to be weaker than normal.Thus the extreme weather/climate events for high solar activity occur in different regions with different severity from those for low solar activity.The solar influence on the midto high-latitude surface temperature and circulations can stand out after renoving the influence from the El Ni(n)o-Southern Oscillation.The atmospheric amplifying mechanism indicates that the solar impacts on climate should not be simply estimated by the magnitude of the change in the solar radiation over solar cycles when it is compared with
Feller, Urs; Vaseva, Irina I
Climate models predict more frequent and more severe extreme events (e.g., heat waves, extended drought periods, flooding) in many regions for the next decades. The impact of adverse environmental conditions on crop plants is ecologically and economically relevant. This review is focused on drought and heat effects on physiological status and productivity of agronomically important plants. Stomatal opening represents an important regulatory mechanism during drought and heat stress since it in...
A. Loukas; Llasat, M.-C.; U. Ulbrich
This special issue of Natural Hazards and Earth System Sciences (NHESS) contains eight papers presented as oral or poster contributions in the Natural Hazards NH-1.2 session on"Extreme events induced by weather and climate change: evaluation, forecasting and proactive planning", held at the European Geosciences Union (EGU) General Assembly in Vienna, Austria, on 13-18 April 2008. The aim of the session was to provide an international forum for presenting new results and for discussing innovat...
Woodward, Guy; Bonada, Núria; Lee. E. Brown; Russell G. DEATH; Durance, Isabelle; Gray, Clare; Hladyz, Sally; Ledger, Mark E.; Milner, Alexander M.; Ormerod, Steve J.; Thompson, Ross M.; Pawar, Samraat
Most research on the effects of environmental change in freshwaters has focused on incremental changes in average conditions, rather than fluctuations or extreme events such as heatwaves, cold snaps, droughts, floods or wildfires, which may have even more profound consequences. Such events are commonly predicted to increase in frequency, intensity and duration with global climate change, with many systems being exposed to conditions with no recent historical precedent. We propose a mechanisti...
This dissertation examines the socio-spatial impacts of climate-related hazards and extreme weather events and associated responses in the Turtle Region of Trinidad & Tobago. The Turtle Region supports a growing eco-tourism industry centered on excursions to remote pristine beaches, hiking trails, waterfalls, and the annual migration of female Leatherback turtles to lay their eggs on natal beaches. The Turtle Region also experiences rapid rates of coastal erosion and severe weather related ev...
Gates, Joseph S.
Climatic extremes affect ground-water levels and quality in the basins of western Utah. The five droughts since 1930: 1930-36, 1953-65, 1974-78, 1988-93, and 1999-2004--resulted in much-less-than-average recharge, and the pronounced wet period of 1982-86 resulted in much-greater-than-average recharge. Decreased recharge lowered the ground-water level, and increased recharge raised it. These changes were largest in recharge areas-in discharge areas the water level is relatively constant and the primary effect is a change in the discharge area-smaller during a drought and larger during a pronounced wet period. The largest part of water-level change during climatic extremes, however, is not a result of changes in recharge but is related to changes in ground-water withdrawal. During a drought withdrawals increase to satisfy increased demand for ground water, especially in irrigated areas, and water levels decline. During a pronounced wet period, withdrawals decrease because of less demand and water levels rise. The amount of water-level change in representative observation wells in a basin is generally proportional to the basin's withdrawal. In undeveloped Tule Valley, water-level changes related to climatic extremes during 1981-2005 are less than 2 feet. In Snake Valley (small withdrawal), Tooele Valley (moderate withdrawal), and Pahvant Valley (large withdrawal), water-level declines in representative wells from 1985-86 to 2005 were 13.4, 23.8, and 63.8 feet, respectively. Ground-water quality is also affected by climatic extremes. In six irrigated areas in western Utah, water-level decline during drought has induced flow of water with large dissolved-solids concentrations toward areas of pumping, increasing the dissolved-solids concentrations in water sampled from observation wells. During the 1982-86 wet period, increased recharge resulted in a later decrease in dissolved-solids concentrations in three basins.
Laura Brimont; Driss Ezzine-de-Blas; Alain Karsenty; Angélique Toulon
Achieving forest conservation together with poverty alleviation and equity is an unending challenge in the tropics. The Makira REDD+ pilot project located in northeastern Madagascar is a well-suited case to explore this challenge in conditions of extreme poverty and climatic vulnerability. We assessed the potential effect of project siting on the livelihoods of the local population and which households would be the most strongly impacted by conservation measures. Farmers living in hilly areas...
Brown, Simon J.; Murphy, James M.; Sexton, David M. H.; Harris, Glen R.
A methodology is presented for providing projections of absolute future values of extreme weather events that takes into account key uncertainties in predicting future climate. This is achieved by characterising both observed and modelled extremes with a single form of non-stationary extreme value (EV) distribution that depends on global mean temperature and which includes terms that account for model bias. Such a distribution allows the prediction of future "observed" extremes for any period in the twenty-first century. Uncertainty in modelling future climate, arising from a wide range of atmospheric, oceanic, sulphur cycle and carbon cycle processes, is accounted for by using probabilistic distributions of future global temperature and EV parameters. These distributions are generated by Bayesian sampling of emulators with samples weighted by their likelihood with respect to a set of observational constraints. The emulators are trained on a large perturbed parameter ensemble of global simulations of the recent past, and the equilibrium response to doubled CO2. Emulated global EV parameters are converted to the relevant regional scale through downscaling relationships derived from a smaller perturbed parameter regional climate model ensemble. The simultaneous fitting of the EV model to regional model data and observations allows the characterisation of how observed extremes may change in the future irrespective of biases that may be present in the regional models simulation of the recent past climate. The clearest impact of a parameter perturbation in this ensemble was found to be the depth to which plants can access water. Members with shallow soils tend to be biased hot and dry in summer for the observational period. These biases also appear to have an impact on the potential future response for summer temperatures with some members with shallow soils having increases for extremes that reduce with extreme severity. We apply this methodology for London, using the
Decamps, H.; Amatore, C.; Bach, J.F.; Baccelli, F.; Balian, R.; Carpentier, A.; Charnay, P.; Cuzin, F.; Davier, M.; Dercourt, J.; Dumas, C.; Encrenaz, P.; Jeannerod, M.; Kahane, J.P.; Meunier, B.; Rebut, P.H.; Salencon, J.; Spitz, E.; Suquet, P.; Taquet, P.; Valleron, A.J.; Yoccoz, J.C.; Chapron, J.Y.; Fanon, J.; Andre, J.C.; Auger, P.; Bourrelier, P.H.; Combes, C.; Derrida, B.; Laubier, L.; Laval, K.; Le Maho, Y.; Marsily, G. De; Petit, M.; Schmidt-Laine, C.; Birot, Y.; Peyron, J.L.; Seguin, B.; Barles, S.; Besancenot, J.P.; Michel-Kerjan, E.; Hallegatte, S.; Dumas, P.; Ancey, V.; Requier-Desjardins, M.; Ducharnes, A.; Ciais, P.; Peylin, P.; Kaniewski, D.; Van Campo, E.; Planton, S.; Manuguerra, J.C.; Le Bars, Y.; Lagadec, P.; Kessler, D.; Pontikis, C.; Nussbaum, R.
The Earth has to face more and more devastating extreme events. Between 1970 and 2009, at the worldwide scale, the 25 most costly catastrophes all took place after 1987, and for more than half of them after 2001. Among these 25 catastrophes, 23 were linked to climate conditions. France was not spared: the December 1999 storms led to 88 deaths, deprived 3.5 million households of electricity and costed more than 9 billion euros. The 2003 heat wave led to about 15000 supernumerary deaths between August 1 and August 20. The recent Xynthia storm, with its flood barrier ruptures, provoked 53 deaths in addition to many other tragedies that took place in areas liable to flooding. In the present day context of climate change, we know that we must be prepared to even more dangerous events, sometimes unexpected before. These events can have amplified effects because of the urban development, the overpopulation of coastal areas and the anthropization of natural environments. They represent real 'poverty traps' for the poorest countries of the Earth. The anticipation need is real but is our country ready to answer it? Does it have a sufficient contribution to international actions aiming at reducing risks? Is his scientific information suitable? France is not less vulnerable than other countries. It must reinforce its prevention, its response and resilience capacities in the framework of integrated policies of catastrophes risk management as well as in the framework of climate change adaptation plans. This reinforcement supposes the development of vigilance systems with a better risk coverage and benefiting by the advances gained in the meteorology and health domains. It supposes a town and country planning allowing to improve the viability of ecological and social systems - in particular by protecting their diversity. Finally, this reinforcement requires inciting financial coverage solutions for catastrophes prevention and for their management once they have taken
Cortés-Hernández, Virginia Edith; Zheng, Feifei; Evans, Jason; Lambert, Martin; Sharma, Ashish; Westra, Seth
Sub-daily rainfall extremes are of significant societal interest, with implications for flash flooding and the design of urban stormwater systems. It is increasingly recognised that extreme subdaily rainfall will intensify as a result of global temperature increases, with regional climate models (RCMs) representing one of the principal lines of evidence on the likely magnitude and spatiotemporal characteristics of these changes. To evaluate the ability of RCMs to simulate subdaily extremes, it is common to compare the simulated statistical characteristics of the extreme rainfall events with those from observational records. While such analyses are important, they provide insufficient insight into whether the RCM reproduces the correct underlying physical processes; in other words, whether the model "gets the right answers for the right reasons". This paper develops a range of metrics to assess the performance of RCMs in capturing the physical mechanisms that produce extreme rainfall. These metrics include the diurnal and seasonal cycles, relationship between rainfall intensity and temperature, temporal scaling, and the spatial structure of extreme rainfall events. We evaluate a high resolution RCM—the Weather Research Forecasting model—over the Greater Sydney region, using three alternative parametrization schemes. The model shows consistency with the observations for most of the proposed metrics. Where differences exist, these are dependent on both the rainfall duration and model parameterization strategy. The use of physically meaningful performance metrics not only enhances the confidence in model simulations, but also provides better diagnostic power to assist with future model improvement.