Disease in a more variable and unpredictable climate

NASA Astrophysics Data System (ADS)

McMahon, T. A.; Raffel, T.; Rohr, J. R.; Halstead, N.; Venesky, M.; Romansic, J.

2014-12-01

Global climate change is shifting the dynamics of infectious diseases of humans and wildlife with potential adverse consequences for disease control. Despite this, the role of global climate change in the decline of biodiversity and the emergence of infectious diseases remains controversial. Climate change is expected to increase climate variability in addition to increasing mean temperatures, making climate less predictable. However, few empirical or theoretical studies have considered the effects of climate variability or predictability on disease, despite it being likely that hosts and parasites will have differential responses to climatic shifts. Here we present a theoretical framework for how temperature variation and its predictability influence disease risk by affecting host and parasite acclimation responses. Laboratory experiments and field data on disease-associated frog declines in Latin America support this framework and provide evidence that unpredictable temperature fluctuations, on both monthly and diurnal timescales, decrease frog resistance to the pathogenic chytrid fungus Batrachochytrium dendrobatidis (Bd). Furthermore, the pattern of temperature-dependent growth of the fungus on frogs was inconsistent with the pattern of Bd growth in culture, emphasizing the importance of accounting for the host-parasite interaction when predicting climate-dependent disease dynamics. Consistent with our laboratory experiments, increased regional temperature variability associated with global El Niño climatic events was the best predictor of widespread amphibian losses in the genus Atelopus. Thus, incorporating the effects of small-scale temporal variability in climate can greatly improve our ability to predict the effects of climate change on disease.

Impact of anthropogenic climate change on wildfire across western US forests.

PubMed

Abatzoglou, John T; Williams, A Park

2016-10-18

Increased forest fire activity across the western continental United States (US) in recent decades has likely been enabled by a number of factors, including the legacy of fire suppression and human settlement, natural climate variability, and human-caused climate change. We use modeled climate projections to estimate the contribution of anthropogenic climate change to observed increases in eight fuel aridity metrics and forest fire area across the western United States. Anthropogenic increases in temperature and vapor pressure deficit significantly enhanced fuel aridity across western US forests over the past several decades and, during 2000-2015, contributed to 75% more forested area experiencing high (>1 σ) fire-season fuel aridity and an average of nine additional days per year of high fire potential. Anthropogenic climate change accounted for ∼55% of observed increases in fuel aridity from 1979 to 2015 across western US forests, highlighting both anthropogenic climate change and natural climate variability as important contributors to increased wildfire potential in recent decades. We estimate that human-caused climate change contributed to an additional 4.2 million ha of forest fire area during 1984-2015, nearly doubling the forest fire area expected in its absence. Natural climate variability will continue to alternate between modulating and compounding anthropogenic increases in fuel aridity, but anthropogenic climate change has emerged as a driver of increased forest fire activity and should continue to do so while fuels are not limiting.

Impact of anthropogenic climate change on wildfire across western US forests

NASA Astrophysics Data System (ADS)

Abatzoglou, John T.; Park Williams, A.

2016-10-01

Increased forest fire activity across the western continental United States (US) in recent decades has likely been enabled by a number of factors, including the legacy of fire suppression and human settlement, natural climate variability, and human-caused climate change. We use modeled climate projections to estimate the contribution of anthropogenic climate change to observed increases in eight fuel aridity metrics and forest fire area across the western United States. Anthropogenic increases in temperature and vapor pressure deficit significantly enhanced fuel aridity across western US forests over the past several decades and, during 2000-2015, contributed to 75% more forested area experiencing high (>1 σ) fire-season fuel aridity and an average of nine additional days per year of high fire potential. Anthropogenic climate change accounted for ˜55% of observed increases in fuel aridity from 1979 to 2015 across western US forests, highlighting both anthropogenic climate change and natural climate variability as important contributors to increased wildfire potential in recent decades. We estimate that human-caused climate change contributed to an additional 4.2 million ha of forest fire area during 1984-2015, nearly doubling the forest fire area expected in its absence. Natural climate variability will continue to alternate between modulating and compounding anthropogenic increases in fuel aridity, but anthropogenic climate change has emerged as a driver of increased forest fire activity and should continue to do so while fuels are not limiting.

Climatic extremes improve predictions of spatial patterns of tree species

USGS Publications Warehouse

Zimmermann, N.E.; Yoccoz, N.G.; Edwards, T.C.; Meier, E.S.; Thuiller, W.; Guisan, Antoine; Schmatz, D.R.; Pearman, P.B.

2009-01-01

Understanding niche evolution, dynamics, and the response of species to climate change requires knowledge of the determinants of the environmental niche and species range limits. Mean values of climatic variables are often used in such analyses. In contrast, the increasing frequency of climate extremes suggests the importance of understanding their additional influence on range limits. Here, we assess how measures representing climate extremes (i.e., interannual variability in climate parameters) explain and predict spatial patterns of 11 tree species in Switzerland. We find clear, although comparably small, improvement (+20% in adjusted D2, +8% and +3% in cross-validated True Skill Statistic and area under the receiver operating characteristics curve values) in models that use measures of extremes in addition to means. The primary effect of including information on climate extremes is a correction of local overprediction and underprediction. Our results demonstrate that measures of climate extremes are important for understanding the climatic limits of tree species and assessing species niche characteristics. The inclusion of climate variability likely will improve models of species range limits under future conditions, where changes in mean climate and increased variability are expected.

Climate variability has a stabilizing effect on the coexistence of prairie grasses

PubMed Central

Adler, Peter B.; HilleRisLambers, Janneke; Kyriakidis, Phaedon C.; Guan, Qingfeng; Levine, Jonathan M.

2006-01-01

How expected increases in climate variability will affect species diversity depends on the role of such variability in regulating the coexistence of competing species. Despite theory linking temporal environmental fluctuations with the maintenance of diversity, the importance of climate variability for stabilizing coexistence remains unknown because of a lack of appropriate long-term observations. Here, we analyze three decades of demographic data from a Kansas prairie to demonstrate that interannual climate variability promotes the coexistence of three common grass species. Specifically, we show that (i) the dynamics of the three species satisfy all requirements of “storage effect” theory based on recruitment variability with overlapping generations, (ii) climate variables are correlated with interannual variation in species performance, and (iii) temporal variability increases low-density growth rates, buffering these species against competitive exclusion. Given that environmental fluctuations are ubiquitous in natural systems, our results suggest that coexistence based on the storage effect may be underappreciated and could provide an important alternative to recent neutral theories of diversity. Field evidence for positive effects of variability on coexistence also emphasizes the need to consider changes in both climate means and variances when forecasting the effects of global change on species diversity. PMID:16908862

Quantifying the increasing sensitivity of power systems to climate variability

NASA Astrophysics Data System (ADS)

Bloomfield, H. C.; Brayshaw, D. J.; Shaffrey, L. C.; Coker, P. J.; Thornton, H. E.

2016-12-01

Large quantities of weather-dependent renewable energy generation are expected in power systems under climate change mitigation policies, yet little attention has been given to the impact of long term climate variability. By combining state-of-the-art multi-decadal meteorological records with a parsimonious representation of a power system, this study characterises the impact of year-to-year climate variability on multiple aspects of the power system of Great Britain (including coal, gas and nuclear generation), demonstrating why multi-decadal approaches are necessary. All aspects of the example system are impacted by inter-annual climate variability, with the impacts being most pronounced for baseload generation. The impacts of inter-annual climate variability increase in a 2025 wind-power scenario, with a 4-fold increase in the inter-annual range of operating hours for baseload such as nuclear. The impacts on peak load and peaking-plant are comparably small. Less than 10 years of power supply and demand data are shown to be insufficient for providing robust power system planning guidance. This suggests renewable integration studies—widely used in policy, investment and system design—should adopt a more robust approach to climate characterisation.

Correlative and multivariate analysis of increased radon concentration in underground laboratory.

PubMed

Maletić, Dimitrije M; Udovičić, Vladimir I; Banjanac, Radomir M; Joković, Dejan R; Dragić, Aleksandar L; Veselinović, Nikola B; Filipović, Jelena

2014-11-01

The results of analysis using correlative and multivariate methods, as developed for data analysis in high-energy physics and implemented in the Toolkit for Multivariate Analysis software package, of the relations of the variation of increased radon concentration with climate variables in shallow underground laboratory is presented. Multivariate regression analysis identified a number of multivariate methods which can give a good evaluation of increased radon concentrations based on climate variables. The use of the multivariate regression methods will enable the investigation of the relations of specific climate variable with increased radon concentrations by analysis of regression methods resulting in 'mapped' underlying functional behaviour of radon concentrations depending on a wide spectrum of climate variables. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A virtual water network of the Roman world

NASA Astrophysics Data System (ADS)

Dermody, B. J.; van Beek, R. P. H.; Meeks, E.; Klein Goldewijk, K.; Scheidel, W.; van der Velde, Y.; Bierkens, M. F. P.; Wassen, M. J.; Dekker, S. C.

2014-12-01

The Romans were perhaps the most impressive exponents of water resource management in preindustrial times with irrigation and virtual water trade facilitating unprecedented urbanization and socioeconomic stability for hundreds of years in a region of highly variable climate. To understand Roman water resource management in response to urbanization and climate variability, a Virtual Water Network of the Roman World was developed. Using this network we find that irrigation and virtual water trade increased Roman resilience to interannual climate variability. However, urbanization arising from virtual water trade likely pushed the Empire closer to the boundary of its water resources, led to an increase in import costs, and eroded its resilience to climate variability in the long term. In addition to improving our understanding of Roman water resource management, our cost-distance-based analysis illuminates how increases in import costs arising from climatic and population pressures are likely to be distributed in the future global virtual water network.

A virtual water network of the Roman world

NASA Astrophysics Data System (ADS)

Dermody, B. J.; van Beek, R. P. H.; Meeks, E.; Klein Goldewijk, K.; Scheidel, W.; van der Velde, Y.; Bierkens, M. F. P.; Wassen, M. J.; Dekker, S. C.

2014-06-01

The Romans were perhaps the most impressive exponents of water resource management in preindustrial times with irrigation and virtual water trade facilitating unprecedented urbanisation and socioeconomic stability for hundreds of years in a region of highly variable climate. To understand Roman water resource management in response to urbanisation and climate variability, a Virtual Water Network of the Roman World was developed. Using this network we find that irrigation and virtual water trade increased Roman resilience to climate variability in the short term. However, urbanisation arising from virtual water trade likely pushed the Empire closer to the boundary of its water resources, led to an increase in import costs, and reduced its resilience to climate variability in the long-term. In addition to improving our understanding of Roman water resource management, our cost-distance based analysis illuminates how increases in import costs arising from climatic and population pressures are likely to be distributed in the future global virtual water network.

Impacts of climate change and variability on transportation systems and infrastructure : Gulf Coast study, phase 2 : task 2 : climate variability and change in Mobile, Alabama.

DOT National Transportation Integrated Search

2012-09-01

Despite increasing confidence in global climate change projections in recent years, projections of : climate effects at local scales remains scarce. Location-specific risks to transportation systems : imposed by changes in climate are not yet well kn...

Impact of anthropogenic climate change on wildfire across western US forests

PubMed Central

Williams, A. Park

2016-01-01

Increased forest fire activity across the western continental United States (US) in recent decades has likely been enabled by a number of factors, including the legacy of fire suppression and human settlement, natural climate variability, and human-caused climate change. We use modeled climate projections to estimate the contribution of anthropogenic climate change to observed increases in eight fuel aridity metrics and forest fire area across the western United States. Anthropogenic increases in temperature and vapor pressure deficit significantly enhanced fuel aridity across western US forests over the past several decades and, during 2000–2015, contributed to 75% more forested area experiencing high (>1 σ) fire-season fuel aridity and an average of nine additional days per year of high fire potential. Anthropogenic climate change accounted for ∼55% of observed increases in fuel aridity from 1979 to 2015 across western US forests, highlighting both anthropogenic climate change and natural climate variability as important contributors to increased wildfire potential in recent decades. We estimate that human-caused climate change contributed to an additional 4.2 million ha of forest fire area during 1984–2015, nearly doubling the forest fire area expected in its absence. Natural climate variability will continue to alternate between modulating and compounding anthropogenic increases in fuel aridity, but anthropogenic climate change has emerged as a driver of increased forest fire activity and should continue to do so while fuels are not limiting. PMID:27791053

Alternating high and low climate variability: The context of natural selection and speciation in Plio-Pleistocene hominin evolution.

PubMed

Potts, Richard; Faith, J Tyler

2015-10-01

Interaction of orbital insolation cycles defines a predictive model of alternating phases of high- and low-climate variability for tropical East Africa over the past 5 million years. This model, which is described in terms of climate variability stages, implies repeated increases in landscape/resource instability and intervening periods of stability in East Africa. It predicts eight prolonged (>192 kyr) eras of intensified habitat instability (high variability stages) in which hominin evolutionary innovations are likely to have occurred, potentially by variability selection. The prediction that repeated shifts toward high climate variability affected paleoenvironments and evolution is tested in three ways. In the first test, deep-sea records of northeast African terrigenous dust flux (Sites 721/722) and eastern Mediterranean sapropels (Site 967A) show increased and decreased variability in concert with predicted shifts in climate variability. These regional measurements of climate dynamics are complemented by stratigraphic observations in five basins with lengthy stratigraphic and paleoenvironmental records: the mid-Pleistocene Olorgesailie Basin, the Plio-Pleistocene Turkana and Olduvai Basins, and the Pliocene Tugen Hills sequence and Hadar Basin--all of which show that highly variable landscapes inhabited by hominin populations were indeed concentrated in predicted stages of prolonged high climate variability. Second, stringent null-model tests demonstrate a significant association of currently known first and last appearance datums (FADs and LADs) of the major hominin lineages, suites of technological behaviors, and dispersal events with the predicted intervals of prolonged high climate variability. Palynological study in the Nihewan Basin, China, provides a third test, which shows the occupation of highly diverse habitats in eastern Asia, consistent with the predicted increase in adaptability in dispersing Oldowan hominins. Integration of fossil, archeological, sedimentary, and paleolandscape evidence illustrates the potential influence of prolonged high variability on the origin and spread of critical adaptations and lineages in the evolution of Homo. The growing body of data concerning environmental dynamics supports the idea that the evolution of adaptability in response to climate and overall ecological instability represents a unifying theme in hominin evolutionary history. Published by Elsevier Ltd.

Solar radiation increases suicide rate after adjusting for other climate factors in South Korea.

PubMed

Jee, Hee-Jung; Cho, Chul-Hyun; Lee, Yu Jin; Choi, Nari; An, Hyonggin; Lee, Heon-Jeong

2017-03-01

Previous studies have indicated that suicide rates have significant seasonal variations. There is seasonal discordance between temperature and solar radiation due to the monsoon season in South Korea. We investigated the seasonality of suicide and assessed its association with climate variables in South Korea. Suicide rates were obtained from the National Statistical Office of South Korea, and climatic data were obtained from the Korea Meteorological Administration for the period of 1992-2010. We conducted analyses using a generalized additive model (GAM). First, we explored the seasonality of suicide and climate variables such as mean temperature, daily temperature range, solar radiation, and relative humidity. Next, we identified confounding climate variables associated with suicide rate. To estimate the adjusted effect of solar radiation on the suicide rate, we investigated the confounding variables using a multivariable GAM. Suicide rate showed seasonality with a pattern similar to that of solar radiation. We found that the suicide rate increased 1.008 times when solar radiation increased by 1 MJ/m 2 after adjusting for other confounding climate factors (P < 0.001). Solar radiation has a significant linear relationship with suicide after adjusting for region, other climate variables, and time trends. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Effects of climate change and variability on population dynamics in a long-lived shorebird.

PubMed

van de Pol, Martijn; Vindenes, Yngvild; Saether, Bernt-Erik; Engen, Steinar; Ens, Bruno J; Oosterbeek, Kees; Tinbergen, Joost M

2010-04-01

Climate change affects both the mean and variability of climatic variables, but their relative impact on the dynamics of populations is still largely unexplored. Based on a long-term study of the demography of a declining Eurasian Oystercatcher (Haematopus ostralegus) population, we quantify the effect of changes in mean and variance of winter temperature on different vital rates across the life cycle. Subsequently, we quantify, using stochastic stage-structured models, how changes in the mean and variance of this environmental variable affect important characteristics of the future population dynamics, such as the time to extinction. Local mean winter temperature is predicted to strongly increase, and we show that this is likely to increase the population's persistence time via its positive effects on adult survival that outweigh the negative effects that higher temperatures have on fecundity. Interannual variation in winter temperature is predicted to decrease, which is also likely to increase persistence time via its positive effects on adult survival that outweigh the negative effects that lower temperature variability has on fecundity. Overall, a 0.1 degrees C change in mean temperature is predicted to alter median time to extinction by 1.5 times as many years as would a 0.1 degrees C change in the standard deviation in temperature, suggesting that the dynamics of oystercatchers are more sensitive to changes in the mean than in the interannual variability of this climatic variable. Moreover, as climate models predict larger changes in the mean than in the standard deviation of local winter temperature, the effects of future climatic variability on this population's time to extinction are expected to be overwhelmed by the effects of changes in climatic means. We discuss the mechanisms by which climatic variability can either increase or decrease population viability and how this might depend both on species' life histories and on the vital rates affected. This study illustrates that, for making reliable inferences about population consequences in species in which life history changes with age or stage, it is crucial to investigate the impact of climate change on vital rates across the entire life cycle. Disturbingly, such data are unavailable for most species of conservation concern.

Extinction risk and eco-evolutionary dynamics in a variable environment with increasing frequency of extreme events

PubMed Central

Vincenzi, Simone

2014-01-01

One of the most dramatic consequences of climate change will be the intensification and increased frequency of extreme events. I used numerical simulations to understand and predict the consequences of directional trend (i.e. mean state) and increased variability of a climate variable (e.g. temperature), increased probability of occurrence of point extreme events (e.g. floods), selection pressure and effect size of mutations on a quantitative trait determining individual fitness, as well as the their effects on the population and genetic dynamics of a population of moderate size. The interaction among climate trend, variability and probability of point extremes had a minor effect on risk of extinction, time to extinction and distribution of the trait after accounting for their independent effects. The survival chances of a population strongly and linearly decreased with increasing strength of selection, as well as with increasing climate trend and variability. Mutation amplitude had no effects on extinction risk, time to extinction or genetic adaptation to the new climate. Climate trend and strength of selection largely determined the shift of the mean phenotype in the population. The extinction or persistence of the populations in an ‘extinction window’ of 10 years was well predicted by a simple model including mean population size and mean genetic variance over a 10-year time frame preceding the ‘extinction window’, although genetic variance had a smaller role than population size in predicting contemporary risk of extinction. PMID:24920116

Effect of climatic variability on malaria trends in Baringo County, Kenya.

PubMed

Kipruto, Edwin K; Ochieng, Alfred O; Anyona, Douglas N; Mbalanya, Macrae; Mutua, Edna N; Onguru, Daniel; Nyamongo, Isaac K; Estambale, Benson B A

2017-05-25

Malaria transmission in arid and semi-arid regions of Kenya such as Baringo County, is seasonal and often influenced by climatic factors. Unravelling the relationship between climate variables and malaria transmission dynamics is therefore instrumental in developing effective malaria control strategies. The main aim of this study was to describe the effects of variability of rainfall, maximum temperature and vegetation indices on seasonal trends of malaria in selected health facilities within Baringo County, Kenya. Climate variables sourced from the International Research Institute (IRI)/Lamont-Doherty Earth Observatory (LDEO) climate database and malaria cases reported in 10 health facilities spread across four ecological zones (riverine, lowland, mid-altitude and highland) between 2004 and 2014 were subjected to a time series analysis. A negative binomial regression model with lagged climate variables was used to model long-term monthly malaria cases. The seasonal Mann-Kendall trend test was then used to detect overall monotonic trends in malaria cases. Malaria cases increased significantly in the highland and midland zones over the study period. Changes in malaria prevalence corresponded to variations in rainfall and maximum temperature. Rainfall at a time lag of 2 months resulted in an increase in malaria transmission across the four zones while an increase in temperature at time lags of 0 and 1 month resulted in an increase in malaria cases in the riverine and highland zones, respectively. Given the existence of a time lag between climatic variables more so rainfall and peak malaria transmission, appropriate control measures can be initiated at the onset of short and after long rains seasons.

Climate change and occurrence of diarrheal diseases: evolving facts from Nepal.

PubMed

Bhandari, G P; Gurung, S; Dhimal, M; Bhusal, C L

2012-09-01

Climate change is becoming huge threat to health especially for those from developing countries. Diarrhea as one of the major diseases linked with changing climate. This study has been carried out to assess the relationship between climatic variables, and malaria and to find out the range of non-climatic factors that can confound the relationship of climate change and human health. It is a Retrospective study where data of past ten years relating to climate and disease (diarrhea) variable were analyzed. The study conducted trend analysis based on correlation. The climate related data were obtained from Department of Hydrology and Meteorology. Time Series analysis was also being conducted. The trend of number of yearly cases of diarrhea has been increasing from 1998 to 2001 after which the cases remain constant till 2006.The climate types in Jhapa vary from humid to per-humid based on the moisture index and Mega-thermal based on thermal efficiency. The mean annual temperature is increasing at an average of 0.04 °C/year with maximum temperature increasing faster than the minimum temperature. The annual total rainfall of Jhapa is decreasing at an average rate of -7.1 mm/year. Statistically significant correlation between diarrheal cases occurrence and temperature and rainfall has been observed. However, climate variables were not the significant predictors of diarrheal occurrence. The association among climate variables and diarrheal disease occurrence cannot be neglected which has been showed by this study. Further prospective longitudinal study adjusting influence of non-climatic factors is recommended.

The impact of anthropogenic climate change on wildfire across western US forests

NASA Astrophysics Data System (ADS)

Williams, P.; Abatzoglou, J. T.

2016-12-01

Increased forest fire activity across the western United States (US) in recent decades has contributed to widespread forest mortality, carbon emissions, periods of degraded air quality, and substantial fire suppression expenditures. The increase in forest fire activity has likely been enabled by a number of factors including the legacy of fire suppression and human settlement, changes in suppression policies, natural climate variability, and human-caused climate change. We use modeled climate projections to estimate the contribution of anthropogenic climate change to observed increases in eight fuel aridity metrics and forest fire area across the western US. Anthropogenic increases in temperature and vapor pressure deficit have significantly enhanced fuel aridity across western US forests over the past several decades. Comparing observational climate records to records recalculated after removal of modeled anthropogenic trends, we find that anthropogenic climate change accounted for approximately 55% of observed increases in the eight-metric mean fuel aridity during 1979-2015 across western US forests. This implicates anthropogenic climate change as an important driver of observed increases in fuel aridity, and also highlights the importance of natural multi-decadal climate variability in influencing trends in forest fire potential on the timescales of human lives. Based on a very strong (R2 = 0.76) and mechanistically reasonable relationship between interannual variability in the eight-metric mean fuel aridity and forest-fire area in the western US, we estimate that anthropogenic increases in fuel aridity contributed to an additional 4.2 million ha (95% confidence range: 2.7-6.5 million ha) of forest fire area during 1984-2015, nearly doubling the total forest fire area expected in the absence of anthropogenic climate change. The relationship between annual forest fire area and fuel aridity is exponential and the proportion of total forest area burned in a given year has grown rapidly over the past 32 years. Natural climate variability will continue to alternate between modulating and compounding anthropogenic increases in fuel aridity, but anthropogenic climate change has emerged as a chronic driver of increased forest fire activity and should continue to do so where fuels are not limiting.

Population viability of Pediocactus bradyi (Cactaceae) in a changing climate.

PubMed

Shryock, Daniel F; Esque, Todd C; Hughes, Lee

2014-11-01

A key question concerns the vulnerability of desert species adapted to harsh, variable climates to future climate change. Evaluating this requires coupling long-term demographic models with information on past and projected future climates. We investigated climatic drivers of population growth using a 22-yr demographic model for Pediocactus bradyi, an endangered cactus in northern Arizona. We used a matrix model to calculate stochastic population growth rates (λs) and the relative influences of life-cycle transitions on population growth. Regression models linked population growth with climatic variability, while stochastic simulations were used to (1) understand how predicted increases in drought frequency and extreme precipitation would affect λs, and (2) quantify variability in λs based on temporal replication of data. Overall λs was below unity (0.961). Population growth was equally influenced by fecundity and survival and significantly correlated with increased annual precipitation and higher winter temperatures. Stochastic simulations increasing the probability of drought and extreme precipitation reduced λs, but less than simulations increasing the probability of drought alone. Simulations varying the temporal replication of data suggested 14 yr were required for accurate λs estimates. Pediocactus bradyi may be vulnerable to increases in the frequency and intensity of extreme climatic events, particularly drought. Biotic interactions resulting in low survival during drought years outweighed increased seedling establishment following heavy precipitation. Climatic extremes beyond historical ranges of variability may threaten rare desert species with low population growth rates and therefore high susceptibility to stochastic events. © 2014 Botanical Society of America, Inc.

Climate-mediated spatiotemporal variability in the terrestrial productivity across Europe

NASA Astrophysics Data System (ADS)

Wu, X.; Mahecha, M. D.; Reichstein, M.; Ciais, P.; Wattenbach, M.; Babst, F.; Frank, D.; Zang, C.

2013-11-01

Quantifying the interannual variability (IAV) of the terrestrial productivity and its sensitivity to climate is crucial for improving carbon budget predictions. However, the influence of climate and other mechanisms underlying the spatiotemporal patterns of IAV of productivity are not well understood. In this study we investigated the spatiotemporal patterns of IAV of historical observations of crop yields, tree ring width, remote sensing retrievals of FAPAR and NDVI, and other variables relevant to the terrestrial productivity in Europe in tandem with a set of climate variables. Our results reveal distinct spatial patterns in the IAV of most variables linked to terrestrial productivity. In particular, we find higher IAV in water-limited regions of Europe (Mediterranean and temperate continental Europe) compared to other regions. Our results further indicate that variations in the water balance during active growing season exert a more pronounced and direct effect than variations of temperature on explaining the spatial patterns in IAV of productivity related variables in temperate Europe. We also observe a~temporally increasing trend in the IAV of terrestrial productivity and an increasing sensitivity of productivity to water availability in dry regions of Europe, which is likely attributable to the recently increased IAV of water availability in these regions. These findings suggest nonlinear responses of carbon fluxes to climate variability in Europe and that the IAV of terrestrial productivity has become more sensitive and more vulnerable to changes in water availability in the dry regions in Europe. The changing climate sensitivity of terrestrial productivity accompanied by the changing IAV of climate could impact carbon stocks and the net carbon balance of European ecosystems.

Spatial Models for Prediction and Early Warning of Aedes aegypti Proliferation from Data on Climate Change and Variability in Cuba.

PubMed

Ortiz, Paulo L; Rivero, Alina; Linares, Yzenia; Pérez, Alina; Vázquez, Juan R

2015-04-01

Climate variability, the primary expression of climate change, is one of the most important environmental problems affecting human health, particularly vector-borne diseases. Despite research efforts worldwide, there are few studies addressing the use of information on climate variability for prevention and early warning of vector-borne infectious diseases. Show the utility of climate information for vector surveillance by developing spatial models using an entomological indicator and information on predicted climate variability in Cuba to provide early warning of danger of increased risk of dengue transmission. An ecological study was carried out using retrospective and prospective analyses of time series combined with spatial statistics. Several entomological and climatic indicators were considered using complex Bultó indices -1 and -2. Moran's I spatial autocorrelation coefficient specified for a matrix of neighbors with a radius of 20 km, was used to identify the spatial structure. Spatial structure simulation was based on simultaneous autoregressive and conditional autoregressive models; agreement between predicted and observed values for number of Aedes aegypti foci was determined by the concordance index Di and skill factor Bi. Spatial and temporal distributions of populations of Aedes aegypti were obtained. Models for describing, simulating and predicting spatial patterns of Aedes aegypti populations associated with climate variability patterns were put forward. The ranges of climate variability affecting Aedes aegypti populations were identified. Forecast maps were generated for the municipal level. Using the Bultó indices of climate variability, it is possible to construct spatial models for predicting increased Aedes aegypti populations in Cuba. At 20 x 20 km resolution, the models are able to provide warning of potential changes in vector populations in rainy and dry seasons and by month, thus demonstrating the usefulness of climate information for epidemiological surveillance.

Taking the pulse of mountains: Ecosystem responses to climatic variability

USGS Publications Warehouse

Fagre, Daniel B.; Peterson, David L.; Hessl, Amy E.

2003-01-01

An integrated program of ecosystem modeling and field studies in the mountains of the Pacific Northwest (U.S.A.) has quantified many of the ecological processes affected by climatic variability. Paleoecological and contemporary ecological data in forest ecosystems provided model parameterization and validation at broad spatial and temporal scales for tree growth, tree regeneration and treeline movement. For subalpine tree species, winter precipitation has a strong negative correlation with growth; this relationship is stronger at higher elevations and west-side sites (which have more precipitation). Temperature affects tree growth at some locations with respect to length of growing season (spring) and severity of drought at drier sites (summer). Furthermore, variable but predictable climate-growth relationships across elevation gradients suggest that tree species respond differently to climate at different locations, making a uniform response of these species to future climatic change unlikely. Multi-decadal variability in climate also affects ecosystem processes. Mountain hemlock growth at high-elevation sites is negatively correlated with winter snow depth and positively correlated with the winter Pacific Decadal Oscillation (PDO) index. At low elevations, the reverse is true. Glacier mass balance and fire severity are also linked to PDO. Rapid establishment of trees in subalpine ecosystems during this century is increasing forest cover and reducing meadow cover at many subalpine locations in the western U.S.A. and precipitation (snow depth) is a critical variable regulating conifer expansion. Lastly, modeling potential future ecosystem conditions suggests that increased climatic variability will result in increasing forest fire size and frequency, and reduced net primary productivity in drier, east-side forest ecosystems. As additional empirical data and modeling output become available, we will improve our ability to predict the effects of climatic change across a broad range of climates and mountain ecosystems in the northwestern U.S.A.

Does internal climate variability overwhelm climate change signals in streamflow? The upper Po and Rhone basin case studies.

PubMed

Fatichi, S; Rimkus, S; Burlando, P; Bordoy, R

2014-09-15

Projections of climate change effects in streamflow are increasingly required to plan water management strategies. These projections are however largely uncertain due to the spread among climate model realizations, internal climate variability, and difficulties in transferring climate model results at the spatial and temporal scales required by catchment hydrology. A combination of a stochastic downscaling methodology and distributed hydrological modeling was used in the ACQWA project to provide projections of future streamflow (up to year 2050) for the upper Po and Rhone basins, respectively located in northern Italy and south-western Switzerland. Results suggest that internal (stochastic) climate variability is a fundamental source of uncertainty, typically comparable or larger than the projected climate change signal. Therefore, climate change effects in streamflow mean, frequency, and seasonality can be masked by natural climatic fluctuations in large parts of the analyzed regions. An exception to the overwhelming role of stochastic variability is represented by high elevation catchments fed by glaciers where streamflow is expected to be considerably reduced due to glacier retreat, with consequences appreciable in the main downstream rivers in August and September. Simulations also identify regions (west upper Rhone and Toce, Ticino river basins) where a strong precipitation increase in the February to April period projects streamflow beyond the range of natural climate variability during the melting season. This study emphasizes the importance of including internal climate variability in climate change analyses, especially when compared to the limited uncertainty that would be accounted for by few deterministic projections. The presented results could be useful in guiding more specific impact studies, although design or management decisions should be better based on reliability and vulnerability criteria as suggested by recent literature. Copyright © 2013 Elsevier B.V. All rights reserved.

Extinction risk and eco-evolutionary dynamics in a variable environment with increasing frequency of extreme events.

PubMed

Vincenzi, Simone

2014-08-06

One of the most dramatic consequences of climate change will be the intensification and increased frequency of extreme events. I used numerical simulations to understand and predict the consequences of directional trend (i.e. mean state) and increased variability of a climate variable (e.g. temperature), increased probability of occurrence of point extreme events (e.g. floods), selection pressure and effect size of mutations on a quantitative trait determining individual fitness, as well as the their effects on the population and genetic dynamics of a population of moderate size. The interaction among climate trend, variability and probability of point extremes had a minor effect on risk of extinction, time to extinction and distribution of the trait after accounting for their independent effects. The survival chances of a population strongly and linearly decreased with increasing strength of selection, as well as with increasing climate trend and variability. Mutation amplitude had no effects on extinction risk, time to extinction or genetic adaptation to the new climate. Climate trend and strength of selection largely determined the shift of the mean phenotype in the population. The extinction or persistence of the populations in an 'extinction window' of 10 years was well predicted by a simple model including mean population size and mean genetic variance over a 10-year time frame preceding the 'extinction window', although genetic variance had a smaller role than population size in predicting contemporary risk of extinction. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Virtual water trade in the Roman Mediterranean

NASA Astrophysics Data System (ADS)

Dermody, Brian; van Beek, Rens; Meeks, Elijah; Klein Goldewijk, Kees; Scheidel, Walter; van der Velde, Ype; Bierkens, Marc; Wassen, Martin; Dekker, Stefan

2015-04-01

The Romans were perhaps the most impressive exponents of water resource management in pre-industrial times with irrigation and virtual water trade facilitating unprecedented urbanisation and socio-economic stability for hundreds of years in a region of highly variable climate. To understand Roman water resource management in response to urbanisation and climate variability, a Virtual Water Network of the Roman World was developed. Using this network we found that irrigation and virtual water trade increased Roman resilience to inter-annual climate variability. However, urbanisation and population growth arising from virtual water trade likely pushed the Empire closer to the boundary of its water resources, led to an increase in import costs, and eroded its resilience to climate variability in the long term. Our newest findings also assess the impact that persistent climate change associated with Holocene climate anomalies had on Roman water resource management. Specifically we assess the impact of the change in climate from the Roman Warm Period to the Dark Ages Cold Period on the Roman food supply and whether it could have contributed to the fall of the Western Roman Empire.

Recent changes in county-level corn yield variability in the United States from observations and crop models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leng, Guoyong

The United States is responsible for 35% and 60% of global corn supply and exports. Enhanced supply stability through a reduction in the year-to-year variability of US corn yield would greatly benefit global food security. Important in this regard is to understand how corn yield variability has evolved geographically in the history and how it relates to climatic and non-climatic factors. Results showed that year-to-year variation of US corn yield has decreased significantly during 1980-2010, mainly in Midwest Corn Belt, Nebraska and western arid regions. Despite the country-scale decreasing variability, corn yield variability exhibited an increasing trend in South Dakota,more » Texas and Southeast growing regions, indicating the importance of considering spatial scales in estimating yield variability. The observed pattern is partly reproduced by process-based crop models, simulating larger areas experiencing increasing variability and underestimating the magnitude of decreasing variability. And 3 out of 11 models even produced a differing sign of change from observations. Hence, statistical model which produces closer agreement with observations is used to explore the contribution of climatic and non-climatic factors to the changes in yield variability. It is found that climate variability dominate the change trends of corn yield variability in the Midwest Corn Belt, while the ability of climate variability in controlling yield variability is low in southeastern and western arid regions. Irrigation has largely reduced the corn yield variability in regions (e.g. Nebraska) where separate estimates of irrigated and rain-fed corn yield exist, demonstrating the importance of non-climatic factors in governing the changes in corn yield variability. The results highlight the distinct spatial patterns of corn yield variability change as well as its influencing factors at the county scale. I also caution the use of process-based crop models, which have substantially underestimated the change trend of corn yield variability, in projecting its future changes.« less

Compound extremes of summer temperature and precipitation leading to intensified departures from natural variability.

NASA Astrophysics Data System (ADS)

Mahony, C. R.; Cannon, A. J.

2017-12-01

Climate change can drive local climates outside the range of their historical year-to-year variability, straining the adaptive capacity of ecological and human communities. We demonstrate that interactions between climate variables can produce larger and earlier departures from natural variability than is detectable in individual variables. For example, summer temperature (Tx) and precipitation (Pr) are negatively correlated in most terrestrial regions, such that interannual variability lies along an axis from warm-and-dry to cool-and-wet conditions. A climate change trend perpendicular to this axis, towards warmer-wetter conditions, can depart more quickly from the range of natural variability than a warmer-drier trend. This multivariate "departure intensification" effect is evident in all six CMIP5 models that we examined: 23% (9-34%) of the land area of each model exhibits a pronounced increase in 2σ extremesin the Tx-Pr regime relative to Tx or Pr alone. Observational data suggest that Tx-Pr correlations are sufficient to produce departure intensification in distinct regions on all continents. Departures from the historical Tx-Pr regime may produce ecological disruptions, such as in plant-pathogen interactions and human diseases, that could offset the drought mitigation benefits of increased precipitation. Our study alerts researchers and adaptation practitioners to the presence of multivariate climate change signals and compound extremes that are not detectable in individual climate variables.

Disease and thermal acclimation in a more variable and unpredictable climate

NASA Astrophysics Data System (ADS)

Raffel, Thomas R.; Romansic, John M.; Halstead, Neal T.; McMahon, Taegan A.; Venesky, Matthew D.; Rohr, Jason R.

2013-02-01

Global climate change is shifting the distribution of infectious diseases of humans and wildlife with potential adverse consequences for disease control. As well as increasing mean temperatures, climate change is expected to increase climate variability, making climate less predictable. However, few empirical or theoretical studies have considered the effects of climate variability or predictability on disease, despite it being likely that hosts and parasites will have differential responses to climatic shifts. Here we present a theoretical framework for how temperature variation and its predictability influence disease risk by affecting host and parasite acclimation responses. Laboratory experiments conducted in 80 independent incubators, and field data on disease-associated frog declines in Latin America, support the framework and provide evidence that unpredictable temperature fluctuations, on both monthly and diurnal timescales, decrease frog resistance to the pathogenic chytrid fungus Batrachochytrium dendrobatidis. Furthermore, the pattern of temperature-dependent growth of the fungus on frogs was opposite to the pattern of growth in culture, emphasizing the importance of accounting for the host-parasite interaction when predicting climate-dependent disease dynamics. If similar acclimation responses influence other host-parasite systems, as seems likely, then present models, which generally ignore small-scale temporal variability in climate, might provide poor predictions for climate effects on disease.

High-resolution projections of 21st century climate over the Athabasca River Basin through an integrated evaluation-classification-downscaling-based climate projection framework

NASA Astrophysics Data System (ADS)

Cheng, Guanhui; Huang, Guohe; Dong, Cong; Zhu, Jinxin; Zhou, Xiong; Yao, Y.

2017-03-01

An evaluation-classification-downscaling-based climate projection (ECDoCP) framework is developed to fill a methodological gap of general circulation models (GCMs)-driven statistical-downscaling-based climate projections. ECDoCP includes four interconnected modules: GCM evaluation, climate classification, statistical downscaling, and climate projection. Monthly averages of daily minimum (Tmin) and maximum (Tmax) temperature and daily cumulative precipitation (Prec) over the Athabasca River Basin (ARB) at a 10 km resolution in the 21st century under four Representative Concentration Pathways (RCPs) are projected through ECDoCP. At the octodecadal scale, temperature and precipitation would increase; after bias correction, temperature would increase with a decreased increment, while precipitation would increase only under RCP 8.5. Interannual variability of climate anomalies would increase from RCPs 4.5, 2.6, 6.0 to 8.5 for temperature and from RCPs 2.6, 4.5, 6.0 to 8.5 for precipitation. Bidecadal averaged climate anomalies would decrease from December-January-February (DJF), March-April-May (MAM), September-October-November (SON) to June-July-August (JJA) for Tmin, from DJF, SON, MAM to JJA for Tmax, and from JJA, MAM, SON to DJF for Prec. Climate projection uncertainties would decrease in May to September for temperature and in November to April for precipitation. Spatial climatic variability would not obviously change with RCPs; climatic anomalies are highly correlated with climate-variable magnitudes. Climate anomalies would decrease from upstream to downstream for temperature, and precipitation would follow an opposite pattern. The north end and the other zones would have colder and warmer days, respectively; precipitation would decrease in the upstream and increase in the remaining region. Climate changes might lead to issues, e.g., accelerated glacier/snow melting, deserving attentions of researchers and the public.

Historical Compilation and Georeferencing of Dengue and Chikungunya outbreak data for Disease Modeling

USDA-ARS?s Scientific Manuscript database

The risk of vector-borne disease spread is increasing due to significant changes and variability in the global climate and increasing global travel and trade. Understanding the relationships between climate variability and disease outbreak patterns are critical to the design and construction of pred...

Climate-driven vital rates do not always mean climate-driven population.

PubMed

Tavecchia, Giacomo; Tenan, Simone; Pradel, Roger; Igual, José-Manuel; Genovart, Meritxell; Oro, Daniel

2016-12-01

Current climatic changes have increased the need to forecast population responses to climate variability. A common approach to address this question is through models that project current population state using the functional relationship between demographic rates and climatic variables. We argue that this approach can lead to erroneous conclusions when interpopulation dispersal is not considered. We found that immigration can release the population from climate-driven trajectories even when local vital rates are climate dependent. We illustrated this using individual-based data on a trans-equatorial migratory seabird, the Scopoli's shearwater Calonectris diomedea, in which the variation of vital rates has been associated with large-scale climatic indices. We compared the population annual growth rate λ i , estimated using local climate-driven parameters with ρ i , a population growth rate directly estimated from individual information and that accounts for immigration. While λ i varied as a function of climatic variables, reflecting the climate-dependent parameters, ρ i did not, indicating that dispersal decouples the relationship between population growth and climate variables from that between climatic variables and vital rates. Our results suggest caution when assessing demographic effects of climatic variability especially in open populations for very mobile organisms such as fish, marine mammals, bats, or birds. When a population model cannot be validated or it is not detailed enough, ignoring immigration might lead to misleading climate-driven projections. © 2016 John Wiley & Sons Ltd.

Impacts of Climate Change and Variability on Water Resources in the Southeast USA

Treesearch

Ge Sun; Peter V. Caldwell; Steven G. McNulty; Aris P. Georgakakos; Sankar Arumugam; James Cruise; Richard T. McNider; Adam Terando; Paul A. Conrads; John Feldt; Vasu Misra; Luigi Romolo; Todd C. Rasmussen; Daniel A. Marion

2013-01-01

Key FindingsClimate change is affecting the southeastern USA, particularly increases in rainfall variability and air temperature, which have resulted in more frequent hydrologic extremes, such as high‐intensity storms (tropical storms and hurricanes), flooding, and drought events.Future climate warming likely will...

Impacts of climate variability and future climate change on harmful algal blooms and human health.

PubMed

Moore, Stephanie K; Trainer, Vera L; Mantua, Nathan J; Parker, Micaela S; Laws, Edward A; Backer, Lorraine C; Fleming, Lora E

2008-11-07

Anthropogenically-derived increases in atmospheric greenhouse gas concentrations have been implicated in recent climate change, and are projected to substantially impact the climate on a global scale in the future. For marine and freshwater systems, increasing concentrations of greenhouse gases are expected to increase surface temperatures, lower pH, and cause changes to vertical mixing, upwelling, precipitation, and evaporation patterns. The potential consequences of these changes for harmful algal blooms (HABs) have received relatively little attention and are not well understood. Given the apparent increase in HABs around the world and the potential for greater problems as a result of climate change and ocean acidification, substantial research is needed to evaluate the direct and indirect associations between HABs, climate change, ocean acidification, and human health. This research will require a multidisciplinary approach utilizing expertise in climatology, oceanography, biology, epidemiology, and other disciplines. We review the interactions between selected patterns of large-scale climate variability and climate change, oceanic conditions, and harmful algae.

Impacts of climate variability and future climate change on harmful algal blooms and human health

PubMed Central

Moore, Stephanie K; Trainer, Vera L; Mantua, Nathan J; Parker, Micaela S; Laws, Edward A; Backer, Lorraine C; Fleming, Lora E

2008-01-01

Anthropogenically-derived increases in atmospheric greenhouse gas concentrations have been implicated in recent climate change, and are projected to substantially impact the climate on a global scale in the future. For marine and freshwater systems, increasing concentrations of greenhouse gases are expected to increase surface temperatures, lower pH, and cause changes to vertical mixing, upwelling, precipitation, and evaporation patterns. The potential consequences of these changes for harmful algal blooms (HABs) have received relatively little attention and are not well understood. Given the apparent increase in HABs around the world and the potential for greater problems as a result of climate change and ocean acidification, substantial research is needed to evaluate the direct and indirect associations between HABs, climate change, ocean acidification, and human health. This research will require a multidisciplinary approach utilizing expertise in climatology, oceanography, biology, epidemiology, and other disciplines. We review the interactions between selected patterns of large-scale climate variability and climate change, oceanic conditions, and harmful algae. PMID:19025675

Climate-Driven Crop Yield and Yield Variability and Climate Change Impacts on the U.S. Great Plains Agricultural Production.

PubMed

Kukal, Meetpal S; Irmak, Suat

2018-02-22

Climate variability and trends affect global crop yields and are characterized as highly dependent on location, crop type, and irrigation. U.S. Great Plains, due to its significance in national food production, evident climate variability, and extensive irrigation is an ideal region of investigation for climate impacts on food production. This paper evaluates climate impacts on maize, sorghum, and soybean yields and effect of irrigation for individual counties in this region by employing extensive crop yield and climate datasets from 1968-2013. Variability in crop yields was a quarter of the regional average yields, with a quarter of this variability explained by climate variability, and temperature and precipitation explained these in singularity or combination at different locations. Observed temperature trend was beneficial for maize yields, but detrimental for sorghum and soybean yields, whereas observed precipitation trend was beneficial for all three crops. Irrigated yields demonstrated increased robustness and an effective mitigation strategy against climate impacts than their non-irrigated counterparts by a considerable fraction. The information, data, and maps provided can serve as an assessment guide for planners, managers, and policy- and decision makers to prioritize agricultural resilience efforts and resource allocation or re-allocation in the regions that exhibit risk from climate variability.

Sources and Impacts of Modeled and Observed Low-Frequency Climate Variability

NASA Astrophysics Data System (ADS)

Parsons, Luke Alexander

Here we analyze climate variability using instrumental, paleoclimate (proxy), and the latest climate model data to understand more about the sources and impacts of low-frequency climate variability. Understanding the drivers of climate variability at interannual to century timescales is important for studies of climate change, including analyses of detection and attribution of climate change impacts. Additionally, correctly modeling the sources and impacts of variability is key to the simulation of abrupt change (Alley et al., 2003) and extended drought (Seager et al., 2005; Pelletier and Turcotte, 1997; Ault et al., 2014). In Appendix A, we employ an Earth system model (GFDL-ESM2M) simulation to study the impacts of a weakening of the Atlantic meridional overturning circulation (AMOC) on the climate of the American Tropics. The AMOC drives some degree of local and global internal low-frequency climate variability (Manabe and Stouffer, 1995; Thornalley et al., 2009) and helps control the position of the tropical rainfall belt (Zhang and Delworth, 2005). We find that a major weakening of the AMOC can cause large-scale temperature, precipitation, and carbon storage changes in Central and South America. Our results suggest that possible future changes in AMOC strength alone will not be sufficient to drive a large-scale dieback of the Amazonian forest, but this key natural ecosystem is sensitive to dry-season length and timing of rainfall (Parsons et al., 2014). In Appendix B, we compare a paleoclimate record of precipitation variability in the Peruvian Amazon to climate model precipitation variability. The paleoclimate (Lake Limon) record indicates that precipitation variability in western Amazonia is 'red' (i.e., increasing variability with timescale). By contrast, most state-of-the-art climate models indicate precipitation variability in this region is nearly 'white' (i.e., equally variability across timescales). This paleo-model disagreement in the overall structure of the variance spectrum has important consequences for the probability of multi-year drought. Our lake record suggests there is a significant background threat of multi-year, and even decade-length, drought in western Amazonia, whereas climate model simulations indicate most droughts likely last no longer than one to three years. These findings suggest climate models may underestimate the future risk of extended drought in this important region. In Appendix C, we expand our analysis of climate variability beyond South America. We use observations, well-constrained tropical paleoclimate, and Earth system model data to examine the overall shape of the climate spectrum across interannual to century frequencies. We find a general agreement among observations and models that temperature variability increases with timescale across most of the globe outside the tropics. However, as compared to paleoclimate records, climate models generate too little low-frequency variability in the tropics (e.g., Laepple and Huybers, 2014). When we compare the shape of the simulated climate spectrum to the spectrum of a simple autoregressive process, we find much of the modeled surface temperature variability in the tropics could be explained by ocean smoothing of weather noise. Importantly, modeled precipitation tends to be similar to white noise across much of the globe. By contrast, paleoclimate records of various types from around the globe indicate that both temperature and precipitation variability should experience much more low-frequency variability than a simple autoregressive or white-noise process. In summary, state-of-the-art climate models generate some degree of dynamically driven low-frequency climate variability, especially at high latitudes. However, the latest climate models, observations, and paleoclimate data provide us with drastically different pictures of the background climate system and its associated risks. This research has important consequences for improving how we simulate climate extremes as we enter a warmer (and often drier) world in the coming centuries; if climate models underestimate low-frequency variability, we will underestimate the risk of future abrupt change and extreme events, such as megadroughts.

Climate reddening increases the chance of critical transitions

NASA Astrophysics Data System (ADS)

van der Bolt, Bregje; van Nes, Egbert H.; Bathiany, Sebastian; Vollebregt, Marlies E.; Scheffer, Marten

2018-06-01

Climate change research often focuses on trends in the mean and variance. However, analyses of palaeoclimatic and contemporary dynamics reveal that climate memory — as measured for instance by temporal autocorrelation — may also change substantially over time. Here, we show that elevated temporal autocorrelation in climatic variables should be expected to increase the chance of critical transitions in climate-sensitive systems with tipping points. We demonstrate that this prediction is consistent with evidence from forests, coral reefs, poverty traps, violent conflict and ice sheet instability. In each example, the duration of anomalous dry or warm events elevates chances of invoking a critical transition. Understanding the effects of climate variability thus requires research not only on variance, but also on climate memory.

Quantifying the effects of climate variability and human activities on runoff for Kaidu River Basin in arid region of northwest China

NASA Astrophysics Data System (ADS)

Chen, Zhongsheng; Chen, Yaning; Li, Baofu

2013-02-01

Much attention has recently been focused on the effects that climate variability and human activities have had on runoff. In this study, data from the Kaidu River Basin in the arid region of northwest China were analyzed to investigate changes in annual runoff during the period of 1960-2009. The nonparametric Mann-Kendall test and the Mann-Kendall-Sneyers test were used to identify trend and step change point in the annual runoff. It was found that the basin had a significant increasing trend in annual runoff. Step change point in annual runoff was identified in the basin, which occurred in the year around 1993 dividing the long-term runoff series into a natural period (1960-1993) and a human-induced period (1994-2009). Then, the hydrologic sensitivity analysis method was employed to evaluate the effects of climate variability and human activities on mean annual runoff for the human-induced period based on precipitation and potential evapotranspiration. In 1994-2009, climate variability was the main factor that increased runoff with contribution of 90.5 %, while the increasing percentage due to human activities only accounted for 9.5 %, showing that runoff in the Kaidu River Basin is more sensitive to climate variability than human activities. This study quantitatively distinguishes the effects between climate variability and human activities on runoff, which can do duty for a reference for regional water resources assessment and management.

Southern Hemisphere climate variability forced by Northern Hemisphere ice-sheet topography

NASA Astrophysics Data System (ADS)

Jones, T. R.; Roberts, W. H. G.; Steig, E. J.; Cuffey, K. M.; Markle, B. R.; White, J. W. C.

2018-02-01

The presence of large Northern Hemisphere ice sheets and reduced greenhouse gas concentrations during the Last Glacial Maximum fundamentally altered global ocean-atmosphere climate dynamics. Model simulations and palaeoclimate records suggest that glacial boundary conditions affected the El Niño-Southern Oscillation, a dominant source of short-term global climate variability. Yet little is known about changes in short-term climate variability at mid- to high latitudes. Here we use a high-resolution water isotope record from West Antarctica to demonstrate that interannual to decadal climate variability at high southern latitudes was almost twice as large at the Last Glacial Maximum as during the ensuing Holocene epoch (the past 11,700 years). Climate model simulations indicate that this increased variability reflects an increase in the teleconnection strength between the tropical Pacific and West Antarctica, owing to a shift in the mean location of tropical convection. This shift, in turn, can be attributed to the influence of topography and albedo of the North American ice sheets on atmospheric circulation. As the planet deglaciated, the largest and most abrupt decline in teleconnection strength occurred between approximately 16,000 years and 15,000 years ago, followed by a slower decline into the early Holocene.

Temperature variability is a key component in accurately forecasting the effects of climate change on pest phenology.

PubMed

Merrill, Scott C; Peairs, Frank B

2017-02-01

Models describing the effects of climate change on arthropod pest ecology are needed to help mitigate and adapt to forthcoming changes. Challenges arise because climate data are at resolutions that do not readily synchronize with arthropod biology. Here we explain how multiple sources of climate and weather data can be synthesized to quantify the effects of climate change on pest phenology. Predictions of phenological events differ substantially between models that incorporate scale-appropriate temperature variability and models that do not. As an illustrative example, we predicted adult emergence of a pest of sunflower, the sunflower stem weevil Cylindrocopturus adspersus (LeConte). Predictions of the timing of phenological events differed by an average of 11 days between models with different temperature variability inputs. Moreover, as temperature variability increases, developmental rates accelerate. Our work details a phenological modeling approach intended to help develop tools to plan for and mitigate the effects of climate change. Results show that selection of scale-appropriate temperature data is of more importance than selecting a climate change emission scenario. Predictions derived without appropriate temperature variability inputs will likely result in substantial phenological event miscalculations. Additionally, results suggest that increased temperature instability will lead to accelerated pest development. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Two centuries of observed atmospheric variability and change over the North Sea region

NASA Astrophysics Data System (ADS)

Stendel, Martin; van den Besselaar, Else; Hannachi, Abdel; Kent, Elizabeth; Lefebvre, Christiana; van Oldenborgh, Geert Jan; Rosenhagen, Gudrun; Schenk, Frederik; van der Schrier, Gerard

2015-04-01

Situated in northwestern Europe, the North Sea region is under influence of air masses from subtropical to arctic origin, and thus exhibits significant natural climate variability. As the land areas surrounding the North Sea are densely populated, climate change is an important issue in terms of e.g. coastal protection, fishery and trade. This study is part of the NOSCCA initiative (North Sea Region Climate Change Assessment) and presents observed variability and changes in atmospheric parameters during the last roughly 200 years. Circulation patterns show considerable decadal variability. In recent decades, a northward shift of storm tracks and increased cyclonic activity has been observed. There is also an indication of increased persistence of weather types. The wind climate is dominated by large multidecadal variability, and no robust long-term trends can be identified in the available datasets. There is a clear positive trend in near-surface temperatures, in particular during spring and winter. Over the region as a whole, no clear long-term precipitation trends are visible, although regional indications exist for an increased risk of extreme precipitation events.

Impacts of climate variability and future climate change on harmful algal blooms and human health

Treesearch

Stephanie K. Moore; Vera L. Trainer; Nathan J. Mantua; Micaela S. Parker; Edward A. Laws; Lorraine C. Backer; Lora E. Fleming

2008-01-01

Anthropogenically-derived increases in atmospheric greenhouse gas concentrations have been implicated in recent climate change, and are projected to substantially impact the climate on a global scale in the future. For marine and freshwater systems, increasing concentrations of greenhouse gases are expected to increase surface temperatures, lower pH, and cause changes...

Statistical structure of intrinsic climate variability under global warming

NASA Astrophysics Data System (ADS)

Zhu, Xiuhua; Bye, John; Fraedrich, Klaus

2017-04-01

Climate variability is often studied in terms of fluctuations with respect to the mean state, whereas the dependence between the mean and variability is rarely discussed. We propose a new climate metric to measure the relationship between means and standard deviations of annual surface temperature computed over non-overlapping 100-year segments. This metric is analyzed based on equilibrium simulations of the Max Planck Institute-Earth System Model (MPI-ESM): the last millennium climate (800-1799), the future climate projection following the A1B scenario (2100-2199), and the 3100-year unforced control simulation. A linear relationship is globally observed in the control simulation and thus termed intrinsic climate variability, which is most pronounced in the tropical region with negative regression slopes over the Pacific warm pool and positive slopes in the eastern tropical Pacific. It relates to asymmetric changes in temperature extremes and associates fluctuating climate means with increase or decrease in intensity and occurrence of both El Niño and La Niña events. In the future scenario period, the linear regression slopes largely retain their spatial structure with appreciable changes in intensity and geographical locations. Since intrinsic climate variability describes the internal rhythm of the climate system, it may serve as guidance for interpreting climate variability and climate change signals in the past and the future.

Examining for any impact of climate change on the association between seasonality and hospitalization for mania.

PubMed

Parker, Gordon B; Hadzi-Pavlovic, Dusan; Graham, Rebecca K

2017-01-15

Studies have established higher rates of hospitalization for mania in spring and summer and posit various explanatory climatic variables. As the earth's climate is changing, we pursue whether this is reflected in the yearly seasonal variation in hospitalizations for mania. This would be indicated by the presence of secular changes in both the hospitalization seasonal pattern and climatic variables, and associations between both variable sets. Data were obtained for 21,882 individuals hospitalized to psychiatric hospitals in the Australian state of New South Wales (NSW) over a 14-year period (2000-2014) with ICD-diagnosed mania - and with NSW population figures and salient climatic variables collected for the same period. Regression analyses were conducted to examine the predictive value of climate variables on hospital admissions. Data quantified a peak for manic admissions in spring of the southern hemisphere, in the months of October and November. There was a significant linear increase in manic admissions (0.5%/year) over the 14-year time period, with significant variation across years. In terms of climatic variables, there was a significant linear trend over the interval for solar radiation, although the trend indicated a decrease rather than an increase. Seasonal variation in admissions was most closely associated with two climate variables - evaporation in the current month and temperature in the previous month. Hospitalization rates do not necessarily provide an accurate estimate of the onset of manic episodes and findings may be limited to the southern hemisphere, or New South Wales. While overall findings do not support the hypothesis that climate change is leading to a higher seasonal impact for manic hospital admissions in the southern hemisphere, analyses identified two climate/weather variables - evaporation and temperature - that may account for the yearly spring excess. Copyright © 2016 Elsevier B.V. All rights reserved.

A system's approach to assess the exposure of agricultural production to climate change and variability

USDA-ARS?s Scientific Manuscript database

Estimating the exposure of agriculture to climate variability and change can help us to understand the key vulnerability as well as improve the adaptive capacity which is important for increasing food production to feed the world’s increasing population. A number of indices are available in literat...

Does climatic variability influence agricultural land prices under differing uses? The Texas High Plains case

USDA-ARS?s Scientific Manuscript database

The Texas High Plains faces projections of increasing temperature and declining precipitation in the future on account of its semi-arid climate. This research evaluated the impact of climatic variability on agricultural land prices under different land uses in the Texas High Plains, employing the Ri...

Exploring the Climate Change, Migration and Conflict Nexus.

PubMed

Burrows, Kate; Kinney, Patrick L

2016-04-22

The potential link between climate change, migration, and conflict has been widely discussed and is increasingly viewed by policy makers as a security issue. However, considerable uncertainty remains regarding the role that climate variability and change play among the many drivers of migration and conflict. The overall objective of this paper is to explore the potential pathways linking climate change, migration and increased risk of conflict. We review the existing literature surrounding this issue and break the problem into two components: the links between climate change and migration, and those between migration and conflict. We found a large range of views regarding the importance of climate change as a driver for increasing rates of migration and subsequently of conflict. We argue that future research should focus not only on the climate-migration-conflict pathway but also work to understand the other pathways by which climate variability and change might exacerbate conflict. We conclude by proposing five questions to help guide future research on the link between climate change, migration, and conflict.

Exploring the Climate Change, Migration and Conflict Nexus

PubMed Central

Burrows, Kate; Kinney, Patrick L.

2016-01-01

The potential link between climate change, migration, and conflict has been widely discussed and is increasingly viewed by policy makers as a security issue. However, considerable uncertainty remains regarding the role that climate variability and change play among the many drivers of migration and conflict. The overall objective of this paper is to explore the potential pathways linking climate change, migration and increased risk of conflict. We review the existing literature surrounding this issue and break the problem into two components: the links between climate change and migration, and those between migration and conflict. We found a large range of views regarding the importance of climate change as a driver for increasing rates of migration and subsequently of conflict. We argue that future research should focus not only on the climate-migration-conflict pathway but also work to understand the other pathways by which climate variability and change might exacerbate conflict. We conclude by proposing five questions to help guide future research on the link between climate change, migration, and conflict. PMID:27110806

Aboriginal hunting buffers climate-driven fire-size variability in Australia's spinifex grasslands.

PubMed

Bliege Bird, Rebecca; Codding, Brian F; Kauhanen, Peter G; Bird, Douglas W

2012-06-26

Across diverse ecosystems, greater climatic variability tends to increase wildfire size, particularly in Australia, where alternating wet-dry cycles increase vegetation growth, only to leave a dry overgrown landscape highly susceptible to fire spread. Aboriginal Australian hunting fires have been hypothesized to buffer such variability, mitigating mortality on small-mammal populations, which have suffered declines and extinctions in the arid zone coincident with Aboriginal depopulation. We test the hypothesis that the relationship between climate and fire size is buffered through the maintenance of an anthropogenic, fine-grained fire regime by comparing the effect of climatic variability on landscapes dominated by Martu Aboriginal hunting fires with those dominated by lightning fires. We show that Aboriginal fires are smaller, more tightly clustered, and remain small even when climate variation causes huge fires in the lightning region. As these effects likely benefit threatened small-mammal species, Aboriginal hunters should be considered trophic facilitators, and policies aimed at reducing the risk of large fires should promote land-management strategies consistent with Aboriginal burning regimes.

Means and extremes: building variability into community-level climate change experiments.

PubMed

Thompson, Ross M; Beardall, John; Beringer, Jason; Grace, Mike; Sardina, Paula

2013-06-01

Experimental studies assessing climatic effects on ecological communities have typically applied static warming treatments. Although these studies have been informative, they have usually failed to incorporate either current or predicted future, patterns of variability. Future climates are likely to include extreme events which have greater impacts on ecological systems than changes in means alone. Here, we review the studies which have used experiments to assess impacts of temperature on marine, freshwater and terrestrial communities, and classify them into a set of 'generations' based on how they incorporate variability. The majority of studies have failed to incorporate extreme events. In terrestrial ecosystems in particular, experimental treatments have reduced temperature variability, when most climate models predict increased variability. Marine studies have tended to not concentrate on changes in variability, likely in part because the thermal mass of oceans will moderate variation. In freshwaters, climate change experiments have a much shorter history than in the other ecosystems, and have tended to take a relatively simple approach. We propose a new 'generation' of climate change experiments using down-scaled climate models which incorporate predicted changes in climatic variability, and describe a process for generating data which can be applied as experimental climate change treatments. © 2013 John Wiley & Sons Ltd/CNRS.

Changes in rainfed and irrigated crop yield response to climate in the western US

NASA Astrophysics Data System (ADS)

Li, X.; Troy, T. J.

2018-06-01

As the global population increases and the climate changes, ensuring a secure food supply is increasingly important. One strategy is irrigation, which allows for crops to be grown outside their optimal climate growing regions and which buffers against climate variability. Although irrigation is a positive climate adaptation mechanism for agriculture, it has a potentially negative effect on water resources as it can lead to groundwater depletion and diminished surface water supplies. This study quantifies how crop yields are affected by climate variability and extremes and the impact of irrigation on crop yield increases under various growing-season climate conditions. To do this, we use historical climate data and county-level rainfed and irrigated crop yields for maize, soybean, winter and spring wheat over the US to analyze the relationship between climate, crop yields, and irrigation. We find that there are optimal climates, specific to each crop, where irrigation provides a benefit and other conditions where irrigation proves to have marginal, if any, benefits. Furthermore, the relationship between crop yields and climate has changed over the last decades, with a changing sensitivity in the relationship of soybean and winter wheat yields to certain climate variables, like crop reference evapotranspiration. These two conclusions have important implications for agricultural and water resource system planning, as it implies there are more optimal climate conditions where irrigation is particularly productive and regions where irrigation should be reconsidered as there is not a significant agricultural benefit and the water could be used more productively.

Net primary productivity of subalpine meadows in Yosemite National Park in relation to climate variability

USGS Publications Warehouse

Moore, Peggy E.; Van Wagtendonk, Jan W.; Yee, Julie L.; McClaran, Mitchel P.; Cole, David N.; McDougald, Neil K.; Brooks, Matthew L.

2013-01-01

Subalpine meadows are some of the most ecologically important components of mountain landscapes, and primary productivity is important to the maintenance of meadow functions. Understanding how changes in primary productivity are associated with variability in moisture and temperature will become increasingly important with current and anticipated changes in climate. Our objective was to describe patterns and variability in aboveground live vascular plant biomass in relation to climatic factors. We harvested aboveground biomass at peak growth from four 64-m2 plots each in xeric, mesic, and hydric meadows annually from 1994 to 2000. Data from nearby weather stations provided independent variables of spring snow water content, snow-free date, and thawing degree days for a cumulative index of available energy. We assembled these climatic variables into a set of mixed effects analysis of covariance models to evaluate their relationships with annual aboveground net primary productivity (ANPP), and we used an information theoretic approach to compare the quality of fit among candidate models. ANPP in the xeric meadow was negatively related to snow water content and thawing degree days and in the mesic meadow was negatively related to snow water content. Relationships between ANPP and these 2 covariates in the hydric meadow were not significant. Increasing snow water content may limit ANPP in these meadows if anaerobic conditions delay microbial activity and nutrient availability. Increased thawing degree days may limit ANPP in xeric meadows by prematurely depleting soil moisture. Large within-year variation of ANPP in the hydric meadow limited sensitivity to the climatic variables. These relationships suggest that, under projected warmer and drier conditions, ANPP will increase in mesic meadows but remain unchanged in xeric meadows because declines associated with increased temperatures would offset the increases from decreased snow water content.

Climate change and associated spatial heterogeneity of Pakistan: Empirical evidence using multidisciplinary approach.

PubMed

Ali, Ghaffar

2018-09-01

Climate change is a multidimensional phenomenon, which has various implications for the environment and socio-economic conditions of the people. Its effects are deeper in an agrarian economy which is susceptible to the vagaries of nature. Therefore, climate change directly impacts the society in different ways, and society must pay the cost. Focusing on this truth, the main objective of this research was to investigate the empirical changes and spatial heterogeneity in the climate of Pakistan in real terms using time series data. Climate change and variability in Pakistan, over time, were estimated from 1961 to 2014 using all the climate variables for the very first time. Several studies were available on climate change impacts, mitigation, and adaptation; however, it was difficult to observe exactly how much change occurred in which province and when. A multidisciplinary approach was utilized to estimate the absolute change through a combination of environmental, econometric, and remote sensing methods. Moreover, the Autoregressive Distributed Lag (ARDL) model was used to ascertain the extent of variability in climate change and information was digitalized through ground truthing. Results showed that the average temperature of Pakistan increased by 2°C between 1960 and 1987 and 4°C between 1988 and 2014, and R 2 was 0.978. The rate of temperature increased 0.09°C between 1960 and 2014. The mean annual precipitation of Pakistan increased by 478mm, and its R 2 were 0.34-0.64. The mean annual humidity of Pakistan increased by 2.94%, and the rate of humidity has been increased by 0.97% from 1988 to 2014. Notably, Sindh and Balochistan provinces have shown a significant spatial heterogeneity regarding the increase in precipitation. Statistically all variables are significant. This would serve as a baseline information for climate change-related studies in Pakistan and its application in different sectors. This would also serve the plant breeders and policymakers of the country. Copyright © 2018 Elsevier B.V. All rights reserved.

Relationships between northern Adriatic Sea mucilage events and climate variability.

PubMed

Deserti, Marco; Cacciamani, Carlo; Chiggiato, Jacopo; Rinaldi, Attilio; Ferrari, Carla R

2005-12-15

A long term analysis (1865-2002) of meteorological data collected in the Po Valley and Northern Adriatic Basin have been analysed to find possible links between variability in the climatic parameters and the phenomenon of mucilage. Seasonal anomalies of temperature, calculated as spatial mean over the Po Valley area, and anomalies of North Atlantic Oscillation were compared with the historical record of mucilage episodes. Both climatic indices were found to be positively correlated with mucilage events, suggesting a possible relationship between climatic variability and the increased appearance of mucilage aggregates.

Climate and Southern Africa's Water-Energy-Food Nexus

NASA Astrophysics Data System (ADS)

Conway, D.; Osborn, T.; Dorling, S.; Ringler, C.; Lankford, B.; Dalin, C.; Thurlow, J.; Zhu, T.; Deryng, D.; Landman, W.; Archer van Garderen, E.; Krueger, T.; Lebek, K.

2014-12-01

Numerous challenges coalesce to make Southern Africa emblematic of the connections between climate and the water-energy-food nexus. Rainfall and river flows in the region show high levels of variability across a range of spatial and temporal scales. Physical and socioeconomic exposure to climate variability and change is high, for example, the contribution of electricity produced from hydroelectric sources is over 30% in Madagascar and Zimbabwe and almost 100% in the DRC, Lesotho, Malawi, and Zambia. The region's economy is closely linked with that of the rest of the African continent and climate-sensitive food products are an important item of trade. Southern Africa's population is concentrated in regions exposed to high levels of hydro-meteorological variability, and will increase rapidly over the next four decades. The capacity to manage the effects of climate variability tends, however, to be low. Moreover, with climate change annual precipitation levels, soil moisture and runoff are likely to decrease and rising temperatures will increase evaporative demand. Despite high levels of hydro-meteorological variability, the sectoral and cross-sectoral water-energy-food linkages with climate in Southern Africa have not been considered in detail. Lack of data and questionable reliability are compounded by complex dynamic relationships. We review the role of climate in Southern Africa's nexus, complemented by empirical analysis of national level data on climate, water resources, crop and energy production, and economic activity. Our aim is to examine the role of climate variability as a driver of production fluctuations in the nexus, and to improve understanding of the magnitude and temporal dimensions of their interactions. We first consider national level exposure of food, water and energy production to climate in aggregate economic terms and then examine the linkages between interannual and multi-year climate variability and economic activity, focusing on food and hydropower production. We then review the potential for connecting areas with robust seasonal climate forecasting skill with key precursors of economic output and conclude by identifying knowledge gaps in our understanding of regional and national economic linkages in the climate and water-energy-food nexus.

Climate change and water availability for vulnerable agriculture

NASA Astrophysics Data System (ADS)

Dalezios, Nicolas; Tarquis, Ana Maria

2017-04-01

Climatic projections for the Mediterranean basin indicate that the area will suffer a decrease in water resources due to climate change. The key climatic trends identified for the Mediterranean region are continuous temperature increase, further drying with precipitation decrease and the accentuation of climate extremes, such as droughts, heat waves and/or forest fires, which are expected to have a profound effect on agriculture. Indeed, the impact of climate variability on agricultural production is important at local, regional, national, as well as global scales. Agriculture of any kind is strongly influenced by the availability of water. Climate change will modify rainfall, evaporation, runoff, and soil moisture storage patterns. Changes in total seasonal precipitation or in its pattern of variability are both important. Similarly, with higher temperatures, the water-holding capacity of the atmosphere and evaporation into the atmosphere increase, and this favors increased climate variability, with more intense precipitation and more droughts. As a result, crop yields are affected by variations in climatic factors, such as air temperature and precipitation, and the frequency and severity of the above mentioned extreme events. The aim of this work is to briefly present the main effects of climate change and variability on water resources with respect to water availability for vulnerable agriculture, namely in the Mediterranean region. Results of undertaken studies in Greece on precipitation patterns and drought assessment using historical data records are presented. Based on precipitation frequency analysis, evidence of precipitation reductions is shown. Drought is assessed through an agricultural drought index, namely the Vegetation Health Index (VHI), in Thessaly, a drought-prone region in central Greece. The results justify the importance of water availability for vulnerable agriculture and the need for drought monitoring in the Mediterranean basin as part of an integrated climate adaptation strategy.

Climate Factors as Important Determinants of Dengue Incidence in Curaçao.

PubMed

Limper, M; Thai, K T D; Gerstenbluth, I; Osterhaus, A D M E; Duits, A J; van Gorp, E C M

2016-03-01

Macro- and microclimates may have variable impact on dengue incidence in different settings. We estimated the short-term impact and delayed effects of climate variables on dengue morbidity in Curaçao. Monthly dengue incidence data from 1999 to 2009 were included to estimate the short-term influences of climate variables by employing wavelet analysis, generalized additive models (GAM) and distributed lag nonlinear models (DLNM) on rainfall, temperature and relative humidity in relation to dengue incidence. Dengue incidence showed a significant irregular 4-year multi-annual cycle associated with climate variables. Based on GAM, temperature showed a U-shape, while humidity and rainfall exhibited a dome-shaped association, suggesting that deviation from mean temperature increases and deviation from mean humidity and rainfall decreases dengue incidence, respectively. Rainfall was associated with an immediate increase in dengue incidence of 4.1% (95% CI: 2.2-8.1%) after a 10-mm increase, with a maximum increase of 6.5% (95% CI: 3.2-10.0%) after 1.5 month lag. A 1 °C decrease of mean temperature was associated with a RR of 17.4% (95% CI: 11.2-27.0%); the effect was inversed for a 1°C increase of mean temperature (RR= 0.457, 95% CI: 0.278-0.752). Climate variables are important determinants of dengue incidence and provide insight into its short-term effects. An increase in mean temperature was associated with lower dengue incidence, whereas lower temperatures were associated with higher dengue incidence. © 2015 Blackwell Verlag GmbH.

Atmospheric Teleconnection and Climate Variability: Affecting Rice Productivity of Bihar, India

NASA Astrophysics Data System (ADS)

Saini, A.

2017-12-01

Climate variability brought various negative results to the environment around us and area under rice crop in Bihar has also faced a lot of negative impacts due to variability in temperature and rainfall. Location of Bihar in Northern Plain of India automatically makes it prime location for agriculture and therefore variability in climatic variables brings highly sensitive results to the agricultural production (especially rice). In this study, rainfall and temperature variables are taken into consideration to investigate the impact on rice cultivated area. Change in climate variable with the passage of time is prevailing since the start of geological time scale, how the variability in climate variables has affected the major crops. Climate index of Pacific Ocean and Indian Ocean influences the seasonal weather in Bihar and therefore role of ENSO and IOD is an interesting point of inquiry. Does there exists direct relation between climate variability and area under agricultural crops? How many important variables directly signals towards the change in area under agriculture production? These entire questions are answered with respect to change in area under rice cultivation of Bihar State of India. Temperature, rainfall and ENSO are a good indicator with respect to rice cultivation in Indian subcontinent. Impact on the area under rice has been signaled through ONI, Niño3 and DMI. Increasing range of temperature in the rice productivity declining years is observed since 1990.

New Perspectives on the Role of Internal Variability in Regional Climate Change and Climate Model Evaluation

NASA Astrophysics Data System (ADS)

Deser, C.

2017-12-01

Natural climate variability occurs over a wide range of time and space scales as a result of processes intrinsic to the atmosphere, the ocean, and their coupled interactions. Such internally generated climate fluctuations pose significant challenges for the identification of externally forced climate signals such as those driven by volcanic eruptions or anthropogenic increases in greenhouse gases. This challenge is exacerbated for regional climate responses evaluated from short (< 50 years) data records. The limited duration of the observations also places strong constraints on how well the spatial and temporal characteristics of natural climate variability are known, especially on multi-decadal time scales. The observational constraints, in turn, pose challenges for evaluation of climate models, including their representation of internal variability and assessing the accuracy of their responses to natural and anthropogenic radiative forcings. A promising new approach to climate model assessment is the advent of large (10-100 member) "initial-condition" ensembles of climate change simulations with individual models. Such ensembles allow for accurate determination, and straightforward separation, of externally forced climate signals and internal climate variability on regional scales. The range of climate trajectories in a given model ensemble results from the fact that each simulation represents a particular sequence of internal variability superimposed upon a common forced response. This makes clear that nature's single realization is only one of many that could have unfolded. This perspective leads to a rethinking of approaches to climate model evaluation that incorporate observational uncertainty due to limited sampling of internal variability. Illustrative examples across a range of well-known climate phenomena including ENSO, volcanic eruptions, and anthropogenic climate change will be discussed.

The devil is in the details: An investigation of the relationships between conflict, food price and climate across Africa.

PubMed

Raleigh, Clionadh; Choi, Hyun Jin; Kniveton, Dominic

2015-05-01

This study investigates the relationship between violent conflict, food price, and climate variability at the subnational level. Using disaggregated data on 113 African markets from January 1997 to April 2010, interrelationships between the three variables are analyzed in simultaneous equation models. We find that: (i) a positive feedback exists between food price and violence - higher food prices increase conflict rates within markets and conflict increases food prices; (ii) anomalously dry conditions are associated with increased frequencies of conflict; and (iii) decreased rainfall exerts an indirect effect on conflict through its impact on food prices. These findings suggest that the negative effects of climate variability on conflict can be mitigated by interventions and effective price management in local markets. Creating environments in which food prices are stable and reliable, and markets are accessible and safe, can lower the impacts of both climate change and conflict feedbacks.

Contributions of meteorology to the phenology of cyanobacterial blooms: implications for future climate change.

PubMed

Zhang, Min; Duan, Hongtao; Shi, Xiaoli; Yu, Yang; Kong, Fanxiang

2012-02-01

Cyanobacterial blooms are often a result of eutrophication. Recently, however, their expansion has also been found to be associated with changes in climate. To elucidate the effects of climatic variables on the expansion of cyanobacterial blooms in Taihu, China, we analyzed the relationships between climatic variables and bloom events which were retrieved by satellite images. We then assessed the contribution of each climate variable to the phenology of blooms using multiple regression models. Our study demonstrates that retrieving ecological information from satellite images is meritorious for large-scale and long-term ecological research in freshwater ecosystems. Our results show that the phenological changes of blooms at an inter-annual scale are strongly linked to climate in Taihu during the past 23 yr. Cyanobacterial blooms occur earlier and last longer with the increase of temperature, sunshine hours, and global radiation and the decrease of wind speed. Furthermore, the duration increases when the daily averages of maximum, mean, and minimum temperature each exceed 20.3 °C, 16.7 °C, and 13.7 °C, respectively. Among these factors, sunshine hours and wind speed are the primary contributors to the onset of the blooms, explaining 84.6% of their variability over the past 23 yr. These factors are also good predictors of the variability in the duration of annual blooms and determined 58.9% of the variability in this parameter. Our results indicate that when nutrients are in sufficiently high quantities to sustain the formation of cyanobacterial blooms, climatic variables become crucial in predicting cyanobacterial bloom events. Climate changes should be considered when we evaluate how much the amount of nutrients should be reduced in Taihu for lake management. Copyright © 2011 Elsevier Ltd. All rights reserved.

The perils of climate change: In utero exposure to temperature variability and birth outcomes in the Andean region.

PubMed

Molina, Oswaldo; Saldarriaga, Victor

2017-02-01

The discussion on the effects of climate change on human activity has primarily focused on how increasing temperature levels can impair human health. However, less attention has been paid to the effect of increased climate variability on health. We investigate how in utero exposure to temperature variability, measured as the fluctuations relative to the historical local temperature mean, affects birth outcomes in the Andean region. Our results suggest that exposure to a temperate one standard deviation relative to the municipality's long-term temperature mean during pregnancy reduces birth weight by 20g. and increases the probability a child is born with low birth weight by a 0.7 percentage point. We also explore potential channels driving our results and find some evidence that increased temperature variability can lead to a decrease in health care and increased food insecurity during pregnancy. Copyright © 2016 Elsevier B.V. All rights reserved.

Enhanced future variability during India's rainy season

NASA Astrophysics Data System (ADS)

Menon, Arathy; Levermann, Anders; Schewe, Jacob

2013-06-01

The Indian summer monsoon shapes the livelihood of a large share of the world's population. About 80% of annual precipitation over India occurs during the monsoon season from June through September. Next to its seasonal mean rainfall, the day-to-day variability is crucial for the risk of flooding, national water supply, and agricultural productivity. Here we show that the latest ensemble of climate model simulations, prepared for the AR-5 of the Intergovernmental Panel on Climate Change, consistently projects significant increases in day-to-day rainfall variability under unmitigated climate change. The relative increase by the period 2071-2100 with respect to the control period 1871-1900 ranges from 13% to 50% under the strongest scenario (Representative Concentration Pathways, RCP-8.5), in the 10 models with the most realistic monsoon climatology; and 13% to 85% when all the 20 models are considered. The spread across models reduces when variability increase per degree of global warming is considered, which is independent of the scenario in most models, and is 8% ± 4%/K on average. This consistent projection across 20 comprehensive climate models provides confidence in the results and suggests the necessity of profound adaptation measures in the case of unmitigated climate change.

Assessment of impact of climate change and adaptation strategies on maize production in Uganda

NASA Astrophysics Data System (ADS)

Kikoyo, Duncan A.; Nobert, Joel

2016-06-01

Globally, various climatic studies have estimated a reduction of crop yields due to changes in surface temperature and precipitation especially for the developing countries which is heavily dependent on agriculture and lacks resources to counter the negative effects of climate change. Uganda's economy and the wellbeing of its populace depend on rain-fed agriculture which is susceptible to climate change. This study quantified the impacts of climate change and variability in Uganda and how coping strategies can enhance crop production against climate change and/or variability. The study used statistical methods to establish various climate change and variability indicators across the country, and uses the FAO AquaCrop model to simulate yields under possible future climate scenarios with and without adaptation strategies. Maize, the most widely grown crop was used for the study. Meteorological, soil and crop data were collected for various districts representing the maize growing ecological zones in the country. Based on this study, it was found that temperatures have increased by up to 1 °C across much of Uganda since the 1970s, with rates of warming around 0.3 °C per decade across the country. High altitude, low rainfall regions experience the highest level of warming, with over 0.5 °C/decade recorded in Kasese. Rainfall is variable and does not follow a specific significant increasing or decreasing trend. For both future climate scenarios, Maize yields will reduce in excess of 4.7% for the fast warming-low rainfall climates but increase on average by 3.5% for slow warming-high rainfall regions, by 2050. Improved soil fertility can improve yields by over 50% while mulching and use of surface water management practices improve yields by single digit percentages. The use of fertilizer application needs to go hand in hand with other water management strategies since more yields as a result of the improved soil fertility leads to increased water stress, especially for the dry climates.

Transferability of optimally-selected climate models in the quantification of climate change impacts on hydrology

NASA Astrophysics Data System (ADS)

Chen, Jie; Brissette, François P.; Lucas-Picher, Philippe

2016-11-01

Given the ever increasing number of climate change simulations being carried out, it has become impractical to use all of them to cover the uncertainty of climate change impacts. Various methods have been proposed to optimally select subsets of a large ensemble of climate simulations for impact studies. However, the behaviour of optimally-selected subsets of climate simulations for climate change impacts is unknown, since the transfer process from climate projections to the impact study world is usually highly non-linear. Consequently, this study investigates the transferability of optimally-selected subsets of climate simulations in the case of hydrological impacts. Two different methods were used for the optimal selection of subsets of climate scenarios, and both were found to be capable of adequately representing the spread of selected climate model variables contained in the original large ensemble. However, in both cases, the optimal subsets had limited transferability to hydrological impacts. To capture a similar variability in the impact model world, many more simulations have to be used than those that are needed to simply cover variability from the climate model variables' perspective. Overall, both optimal subset selection methods were better than random selection when small subsets were selected from a large ensemble for impact studies. However, as the number of selected simulations increased, random selection often performed better than the two optimal methods. To ensure adequate uncertainty coverage, the results of this study imply that selecting as many climate change simulations as possible is the best avenue. Where this was not possible, the two optimal methods were found to perform adequately.

Land Use and Climate Variability Amplify Contaminant Pulses

EPA Science Inventory

Converting land to human-dominated uses has increased contaminant loads in streams and rivers and vastly transformed hydrological cycles (Vitousek et al. 1997). More recently, climate change has further altered hydrologic cycles and variability of precipitation (IPCC 2007). Toge...

Variability in climate change simulations affects needed long-term riverine nutrient reductions for the Baltic Sea.

PubMed

Bring, Arvid; Rogberg, Peter; Destouni, Georgia

2015-06-01

Changes to runoff due to climate change may influence management of nutrient loading to the sea. Assuming unchanged river nutrient concentrations, we evaluate the effects of changing runoff on commitments to nutrient reductions under the Baltic Sea Action Plan. For several countries, climate projections point to large variability in load changes in relation to reduction targets. These changes either increase loads, making the target more difficult to reach, or decrease them, leading instead to a full achievement of the target. The impact of variability in climate projections varies with the size of the reduction target and is larger for countries with more limited commitments. In the end, a number of focused actions are needed to manage the effects of climate change on nutrient loads: reducing uncertainty in climate projections, deciding on frameworks to identify best performing models with respect to land surface hydrology, and increasing efforts at sustained monitoring of water flow changes.

Variability in climate change simulations affects needed long-term riverine nutrient reductions for the Baltic Sea

DOE PAGES

Bring, Arvid; Rogberg, Peter; Destouni, Georgia

2015-05-28

Changes to runoff due to climate change may influence management of nutrient loading to the sea. Assuming unchanged river nutrient concentrations, we evaluate the effects of changing runoff on commitments to nutrient reductions under the Baltic Sea Action Plan. For several countries, climate projections point to large variability in load changes in relation to reduction targets. These changes either increase loads, making the target more difficult to reach, or decrease them, leading instead to a full achievement of the target. The impact of variability in climate projections varies with the size of the reduction target and is larger for countriesmore » with more limited commitments. Finally, in the end, a number of focused actions are needed to manage the effects of climate change on nutrient loads: reducing uncertainty in climate projections, deciding on frameworks to identify best performing models with respect to land surface hydrology, and increasing efforts at sustained monitoring of water flow changes.« less

Variability in climate change simulations affects needed long-term riverine nutrient reductions for the Baltic Sea

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bring, Arvid; Rogberg, Peter; Destouni, Georgia

Changes to runoff due to climate change may influence management of nutrient loading to the sea. Assuming unchanged river nutrient concentrations, we evaluate the effects of changing runoff on commitments to nutrient reductions under the Baltic Sea Action Plan. For several countries, climate projections point to large variability in load changes in relation to reduction targets. These changes either increase loads, making the target more difficult to reach, or decrease them, leading instead to a full achievement of the target. The impact of variability in climate projections varies with the size of the reduction target and is larger for countriesmore » with more limited commitments. Finally, in the end, a number of focused actions are needed to manage the effects of climate change on nutrient loads: reducing uncertainty in climate projections, deciding on frameworks to identify best performing models with respect to land surface hydrology, and increasing efforts at sustained monitoring of water flow changes.« less

[Modelling the effect of local climatic variability on dengue transmission in Medellin (Colombia) by means of time series analysis].

PubMed

Rúa-Uribe, Guillermo L; Suárez-Acosta, Carolina; Chauca, José; Ventosilla, Palmira; Almanza, Rita

2013-09-01

Dengue fever is a major impact on public health vector-borne disease, and its transmission is influenced by entomological, sociocultural and economic factors. Additionally, climate variability plays an important role in the transmission dynamics. A large scientific consensus has indicated that the strong association between climatic variables and disease could be used to develop models to explain the incidence of the disease. To develop a model that provides a better understanding of dengue transmission dynamics in Medellin and predicts increases in the incidence of the disease. The incidence of dengue fever was used as dependent variable, and weekly climatic factors (maximum, mean and minimum temperature, relative humidity and precipitation) as independent variables. Expert Modeler was used to develop a model to better explain the behavior of the disease. Climatic variables with significant association to the dependent variable were selected through ARIMA models. The model explains 34% of observed variability. Precipitation was the climatic variable showing statistically significant association with the incidence of dengue fever, but with a 20 weeks delay. In Medellin, the transmission of dengue fever was influenced by climate variability, especially precipitation. The strong association dengue fever/precipitation allowed the construction of a model to help understand dengue transmission dynamics. This information will be useful to develop appropriate and timely strategies for dengue control.

Enhanced future variability during India's rainy season

NASA Astrophysics Data System (ADS)

Menon, Arathy; Levermann, Anders; Schewe, Jacob

2013-04-01

The Indian summer monsoon shapes the livelihood of a large share of the world's population. About 80% of annual precipitation over India occurs during the monsoon season from June through September. Next to its seasonal mean rainfall the day-to-day variability is crucial for the risk of flooding, national water supply and agricultural productivity. Here we show that the latest ensemble of climate model simulations, prepared for the IPCC's AR-5, consistently projects significant increases in day-to-day rainfall variability under unmitigated climate change. While all models show an increase in day-to-day variability, some models are more realistic in capturing the observed seasonal mean rainfall over India than others. While no model's monsoon rainfall exceeds the observed value by more than two standard deviations, half of the models simulate a significantly weaker monsoon than observed. The relative increase in day-to-day variability by the year 2100 ranges from 15% to 48% under the strongest scenario (RCP-8.5), in the ten models which capture seasonal mean rainfall closest to observations. The variability increase per degree of global warming is independent of the scenario in most models, and is 8% +/- 4% per K on average. This consistent projection across 20 comprehensive climate models provides confidence in the results and suggests the necessity of profound adaptation measures in the case of unmitigated climate change.

[Impact of changes in land use and climate on the runoff in Liuxihe Watershed based on SWAT model].

PubMed

Yuan, Yu-zhi; Zhang, Zheng-dong; Meng, Jin-hua

2015-04-01

SWAT model, an extensively used distributed hydrological model, was used to quantitatively analyze the influences of changes in land use and climate on the runoff at watershed scale. Liuxihe Watershed' s SWAT model was established and three scenarios were set. The calibration and validation at three hydrological stations of Wenquan, Taipingchang and Nangang showed that the three factors of Wenquan station just only reached the standard in validated period, and the other two stations had relative error (RE) < 15%, correlation coefficient (R2) > 0.8 and Nash-Sutcliffe efficiency valve (Ens) > 0.75, suggesting that SWAT model was appropriate for simulating runoff response to land use change and climate variability in Liuxihe watershed. According to the integrated scenario simulation, the annual runoff increased by 11.23 m3 x s(-1) from 2001 to 2010 compared with the baseline period from 1991 to 2000, among which, the land use change caused an annual runoff reduction of 0.62 m3 x s(-1), whereas climate variability caused an annual runoff increase of 11.85 m3 x s(-1). Apparently, the impact of climate variability was stronger than that of land use change. On the other hand, the scenario simulation of extreme land use showed that compared with the land use in 2000, the annual runoff of the farmland scenario and the grassland scenario increased by 2.7% and 0.5% respectively, while that of the forest land scenario were reduced by 0.7%, which suggested that forest land had an ability of diversion closure. Furthermore, the scenario simulation of climatic variability indicated that the change of river runoff correlated positively with precipitation change (increase of 11.6% in annual runoff with increase of 10% in annual precipitation) , but negatively with air temperature change (reduction of 0.8% in annual runoff with increase of 1 degrees C in annual mean air temperature), which showed that the impact of precipitation variability was stronger than that of air temperature change. Therefore, in face of climate variability, we need to pay attention to strong rainfall forecasts, optimization of land use structure and spatial distribution, which could reduce the negative hydrological effects (such as floods) induced by climate change.

Building Climate Resilience in the Blue Nile/Abay Highlands: A Role for Earth System Sciences

PubMed Central

Zaitchik, Benjamin F.; Simane, Belay; Habib, Shahid; Anderson, Martha C.; Ozdogan, Mutlu; Foltz, Jeremy D.

2012-01-01

The Blue Nile (Abay) Highlands of Ethiopia are characterized by significant interannual climate variability, complex topography and associated local climate contrasts, erosive rains and erodible soils, and intense land pressure due to an increasing population and an economy that is almost entirely dependent on smallholder, low-input agriculture. As a result, these highland zones are highly vulnerable to negative impacts of climate variability. As patterns of variability and precipitation intensity alter under anthropogenic climate change, there is concern that this vulnerability will increase, threatening economic development and food security in the region. In order to overcome these challenges and to enhance sustainable development in the context of climate change, it is necessary to establish climate resilient development strategies that are informed by best-available Earth System Science (ESS) information. This requirement is complicated by the fact that climate projections for the Abay Highlands contain significant and perhaps irreducible uncertainties. A critical challenge for ESS, then, is to generate and to communicate meaningful information for climate resilient development in the context of a highly uncertain climate forecast. Here we report on a framework for applying ESS to climate resilient development in the Abay Highlands, with a focus on the challenge of reducing land degradation. PMID:22470302

Response of water temperatures and stratification to changing climate in three lakes with different morphometry

NASA Astrophysics Data System (ADS)

Magee, Madeline R.; Wu, Chin H.

2017-12-01

Water temperatures and stratification are important drivers for ecological and water quality processes within lake systems, and changes in these with increases in air temperature and changes to wind speeds may have significant ecological consequences. To properly manage these systems under changing climate, it is important to understand the effects of increasing air temperatures and wind speed changes in lakes of different depths and surface areas. In this study, we simulate three lakes that vary in depth and surface area to elucidate the effects of the observed increasing air temperatures and decreasing wind speeds on lake thermal variables (water temperature, stratification dates, strength of stratification, and surface heat fluxes) over a century (1911-2014). For all three lakes, simulations showed that epilimnetic temperatures increased, hypolimnetic temperatures decreased, the length of the stratified season increased due to earlier stratification onset and later fall overturn, stability increased, and longwave and sensible heat fluxes at the surface increased. Overall, lake depth influences the presence of stratification, Schmidt stability, and differences in surface heat flux, while lake surface area influences differences in hypolimnion temperature, hypolimnetic heating, variability of Schmidt stability, and stratification onset and fall overturn dates. Larger surface area lakes have greater wind mixing due to increased surface momentum. Climate perturbations indicate that our larger study lakes have more variability in temperature and stratification variables than the smaller lakes, and this variability increases with larger wind speeds. For all study lakes, Pearson correlations and climate perturbation scenarios indicate that wind speed has a large effect on temperature and stratification variables, sometimes greater than changes in air temperature, and wind can act to either amplify or mitigate the effect of warmer air temperatures on lake thermal structure depending on the direction of local wind speed changes.

Climate change is likely to worsen the public health threat of diarrheal disease in Botswana.

PubMed

Alexander, Kathleen A; Carzolio, Marcos; Goodin, Douglas; Vance, Eric

2013-03-26

Diarrheal disease is an important health challenge, accounting for the majority of childhood deaths globally. Climate change is expected to increase the global burden of diarrheal disease but little is known regarding climate drivers, particularly in Africa. Using health data from Botswana spanning a 30-year period (1974-2003), we evaluated monthly reports of diarrheal disease among patients presenting to Botswana health facilities and compared this to climatic variables. Diarrheal case incidence presents with a bimodal cyclical pattern with peaks in March (ANOVA p < 0.001) and October (ANOVA p < 0.001) in the wet and dry season, respectively. There is a strong positive autocorrelation (p < 0.001) in the number of reported diarrhea cases at the one-month lag level. Climatic variables (rainfall, minimum temperature, and vapor pressure) predicted seasonal diarrheal with a one-month lag in variables (p < 0.001). Diarrheal case incidence was highest in the dry season after accounting for other variables, exhibiting on average a 20% increase over the yearly mean (p < 0.001). Our analysis suggests that forecasted climate change increases in temperature and decreases in precipitation may increase dry season diarrheal disease incidence with hot, dry conditions starting earlier and lasting longer. Diarrheal disease incidence in the wet season is likely to decline. Our results identify significant health-climate interactions, highlighting the need for an escalated public health focus on controlling diarrheal disease in Botswana. Study findings have application to other arid countries in Africa where diarrheal disease is a persistent public health problem.

Climate Change is Likely to Worsen the Public Health Threat of Diarrheal Disease in Botswana

PubMed Central

Alexander, Kathleen A.; Carzolio, Marcos; Goodin, Douglas; Vance, Eric

2013-01-01

Diarrheal disease is an important health challenge, accounting for the majority of childhood deaths globally. Climate change is expected to increase the global burden of diarrheal disease but little is known regarding climate drivers, particularly in Africa. Using health data from Botswana spanning a 30-year period (1974–2003), we evaluated monthly reports of diarrheal disease among patients presenting to Botswana health facilities and compared this to climatic variables. Diarrheal case incidence presents with a bimodal cyclical pattern with peaks in March (ANOVA p < 0.001) and October (ANOVA p < 0.001) in the wet and dry season, respectively. There is a strong positive autocorrelation (p < 0.001) in the number of reported diarrhea cases at the one-month lag level. Climatic variables (rainfall, minimum temperature, and vapor pressure) predicted seasonal diarrheal with a one-month lag in variables (p < 0.001). Diarrheal case incidence was highest in the dry season after accounting for other variables, exhibiting on average a 20% increase over the yearly mean (p < 0.001). Our analysis suggests that forecasted climate change increases in temperature and decreases in precipitation may increase dry season diarrheal disease incidence with hot, dry conditions starting earlier and lasting longer. Diarrheal disease incidence in the wet season is likely to decline. Our results identify significant health-climate interactions, highlighting the need for an escalated public health focus on controlling diarrheal disease in Botswana. Study findings have application to other arid countries in Africa where diarrheal disease is a persistent public health problem. PMID:23531489

Climate Variability and Phytoplankton in the Pacific Ocean

NASA Technical Reports Server (NTRS)

Rousseaux, Cecile

2012-01-01

The effect of climate variability on phytoplankton communities was assessed for the tropical and sub-tropical Pacific Ocean between 1998 and 2005 using an established biogeochemical assimilation model. The phytoplankton communities exhibited wide range of responses to climate variability, from radical shifts in the Equatorial Pacific, to changes of only a couple of phytoplankton groups in the North Central Pacific, to no significant changes in the South Pacific. In the Equatorial Pacific, climate variability dominated the variability of phytoplankton. Here, nitrate, chlorophyll and all but one of the 4 phytoplankton types (diatoms, cyanobacteria and coccolithophores) were strongly correlated (p<0.01) with the Multivariate El Nino Southern Oscillation Index (MEI). In the North Central Pacific, MEI and chlorophyll were significantly (p<0.01) correlated along with two of the phytoplankton groups (chlorophytes and coccolithophores). Ocean biology in the South Pacific was not significantly correlated with MEI. During La Nina events, diatoms increased and expanded westward along the cold tongue (correlation with MEI, r=-0.81), while cyanobacteria concentrations decreased significantly (r=0.78). El Nino produced the reverse pattern, with cyanobacteria populations increasing while diatoms plummeted. The diverse response of phytoplankton in the different major basins of the Pacific suggests the different roles climate variability can play in ocean biology.

Climate Projections and Uncertainty Communication.

PubMed

Joslyn, Susan L; LeClerc, Jared E

2016-01-01

Lingering skepticism about climate change might be due in part to the way climate projections are perceived by members of the public. Variability between scientists' estimates might give the impression that scientists disagree about the fact of climate change rather than about details concerning the extent or timing. Providing uncertainty estimates might clarify that the variability is due in part to quantifiable uncertainty inherent in the prediction process, thereby increasing people's trust in climate projections. This hypothesis was tested in two experiments. Results suggest that including uncertainty estimates along with climate projections leads to an increase in participants' trust in the information. Analyses explored the roles of time, place, demographic differences (e.g., age, gender, education level, political party affiliation), and initial belief in climate change. Implications are discussed in terms of the potential benefit of adding uncertainty estimates to public climate projections. Copyright © 2015 Cognitive Science Society, Inc.

Application of a stochastic weather generator to assess climate change impacts in a semi-arid climate: The Upper Indus Basin

NASA Astrophysics Data System (ADS)

Forsythe, N.; Fowler, H. J.; Blenkinsop, S.; Burton, A.; Kilsby, C. G.; Archer, D. R.; Harpham, C.; Hashmi, M. Z.

2014-09-01

Assessing local climate change impacts requires downscaling from Global Climate Model simulations. Here, a stochastic rainfall model (RainSim) combined with a rainfall conditioned weather generator (CRU WG) have been successfully applied in a semi-arid mountain climate, for part of the Upper Indus Basin (UIB), for point stations at a daily time-step to explore climate change impacts. Validation of the simulated time-series against observations (1961-1990) demonstrated the models' skill in reproducing climatological means of core variables with monthly RMSE of <2.0 mm for precipitation and ⩽0.4 °C for mean temperature and daily temperature range. This level of performance is impressive given complexity of climate processes operating in this mountainous context at the boundary between monsoonal and mid-latitude (westerly) weather systems. Of equal importance the model captures well the observed interannual variability as quantified by the first and last decile of 30-year climatic periods. Differences between a control (1961-1990) and future (2071-2100) regional climate model (RCM) time-slice experiment were then used to provide change factors which could be applied within the rainfall and weather models to produce perturbed ‘future' weather time-series. These project year-round increases in precipitation (maximum seasonal mean change:+27%, annual mean change: +18%) with increased intensity in the wettest months (February, March, April) and year-round increases in mean temperature (annual mean +4.8 °C). Climatic constraints on the productivity of natural resource-dependent systems were also assessed using relevant indices from the European Climate Assessment (ECA) and indicate potential future risk to water resources and local agriculture. However, the uniformity of projected temperature increases is in stark contrast to recent seasonally asymmetrical trends in observations, so an alternative scenario of extrapolated trends was also explored. We conclude that interannual variability in climate will continue to have the dominant impact on water resources management whichever trajectory is followed. This demonstrates the need for sophisticated downscaling methods which can evaluate changes in variability and sequencing of events to explore climate change impacts in this region.

Slowing down of North Pacific climate variability and its implications for abrupt ecosystem change.

PubMed

Boulton, Chris A; Lenton, Timothy M

2015-09-15

Marine ecosystems are sensitive to stochastic environmental variability, with higher-amplitude, lower-frequency--i.e., "redder"--variability posing a greater threat of triggering large ecosystem changes. Here we show that fluctuations in the Pacific Decadal Oscillation (PDO) index have slowed down markedly over the observational record (1900-present), as indicated by a robust increase in autocorrelation. This "reddening" of the spectrum of climate variability is also found in regionally averaged North Pacific sea surface temperatures (SSTs), and can be at least partly explained by observed deepening of the ocean mixed layer. The progressive reddening of North Pacific climate variability has important implications for marine ecosystems. Ecosystem variables that respond linearly to climate forcing will have become prone to much larger variations over the observational record, whereas ecosystem variables that respond nonlinearly to climate forcing will have become prone to more frequent "regime shifts." Thus, slowing down of North Pacific climate variability can help explain the large magnitude and potentially the quick succession of well-known abrupt changes in North Pacific ecosystems in 1977 and 1989. When looking ahead, despite model limitations in simulating mixed layer depth (MLD) in the North Pacific, global warming is robustly expected to decrease MLD. This could potentially reverse the observed trend of slowing down of North Pacific climate variability and its effects on marine ecosystems.

Aboriginal hunting buffers climate-driven fire-size variability in Australia’s spinifex grasslands

PubMed Central

Bliege Bird, Rebecca; Codding, Brian F.; Kauhanen, Peter G.

2012-01-01

Across diverse ecosystems, greater climatic variability tends to increase wildfire size, particularly in Australia, where alternating wet–dry cycles increase vegetation growth, only to leave a dry overgrown landscape highly susceptible to fire spread. Aboriginal Australian hunting fires have been hypothesized to buffer such variability, mitigating mortality on small-mammal populations, which have suffered declines and extinctions in the arid zone coincident with Aboriginal depopulation. We test the hypothesis that the relationship between climate and fire size is buffered through the maintenance of an anthropogenic, fine-grained fire regime by comparing the effect of climatic variability on landscapes dominated by Martu Aboriginal hunting fires with those dominated by lightning fires. We show that Aboriginal fires are smaller, more tightly clustered, and remain small even when climate variation causes huge fires in the lightning region. As these effects likely benefit threatened small-mammal species, Aboriginal hunters should be considered trophic facilitators, and policies aimed at reducing the risk of large fires should promote land-management strategies consistent with Aboriginal burning regimes. PMID:22689979

Climate change hampers endangered species through intensified moisture-related plant stresses (Invited)

NASA Astrophysics Data System (ADS)

Bartholomeus, R.; Witte, J.; van Bodegom, P.; Dam, J. V.; Aerts, R.

2010-12-01

With recent climate change, extremes in meteorological conditions are forecast and observed to increase globally, and to affect vegetation composition. More prolonged dry periods will alternate with more intensive rainfall events, both within and between years, which will change soil moisture dynamics. In temperate climates, soil moisture, in concert with nutrient availability and soil acidity, is the most important environmental filter in determining local plant species composition, as it determines the availability of both oxygen and water to plant roots. These resources are indispensable for meeting the physiological demands of plants. The consequences of climate change for our natural environment are among the most pressing issues of our time. The international research community is beginning to realise that climate extremes may be more powerful drivers of vegetation change and species extinctions than slow-and-steady climatic changes, but the causal mechanisms of such changes are presently unknown. The roles of amplitudes in water availability as drivers of vegetation change have been particularly elusive owing to the lack of integration of the key variables involved. Here we show that the combined effect of increased rainfall variability, temperature and atmospheric CO2-concentration will lead to an increased variability in both wet and dry extremes in stresses faced by plants (oxygen and water stress, respectively). We simulated these plant stresses with a novel, process-based approach, incorporating in detail the interacting processes in the soil-plant-atmosphere interface. In order to quantify oxygen and water stress with causal measures, we focused on interacting meteorological, soil physical, microbial, and plant physiological processes in the soil-plant-atmosphere system. As both the supply and demand of oxygen and water depend strongly on the prevailing meteorological conditions, both oxygen and water stress were calculated dynamically in time to capture climate change effects. We demonstrate that increased rainfall variability in interaction with predicted changes in temperature and CO2, affects soil moisture conditions and plant oxygen and water demands such, that both oxygen stress and water stress will intensify due to climate change. Moreover, these stresses will increasingly coincide, causing variable stress conditions. These variable stress conditions were found to decrease future habitat suitability, especially for plant species that are presently endangered. The future existence of such species is thus at risk by climate change, which has direct implications for policies to maintain endangered species, as applied by international nature management organisations (e.g. IUCN). Our integrated mechanistic analysis of two stresses combined, which has never been done so far, reveals large impacts of climate change on species extinctions and thereby on biodiversity.

Possible effects of anthropogenically-increased CO[sub 2] on the dynamics of climate: Implications for ice age cycles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saltzman, B.; Maasch, K.A.; Verbitsky, M.Ya.

1993-06-07

The authors look at the impact of an antropogenic step increase in atmospheric carbon dioxide content on a dynamic model designed to look at long-term variations in climate. The model is one developed by Saltzman and Maasch, and Saltzman and Verbitsky, where four slow responding variables are considered to carry the climatic change information over the past 5 My. One of these variables is the carbon dioxide concentration in the atmosphere. If this step increase is maintained over a long period of time, what impact does this have of the present unstable regime where climate oscillates through ice age periodsmore » Indications are that the climate shifts to a regime where the oscillations are much weaker than those which prevailed during the Pleistocene.« less

Investigating the Contribution of Climate Variables to Estimates of Net Primary Productivity in a Tropical Ecosystem in India

NASA Astrophysics Data System (ADS)

Tripathi, P.; Behera, M. D.; Behera, S. K.; Sahu, N.

2016-12-01

Investigating the impact of climate variables on net primary productivity is crucial to evaluate the ecosystem health and the status of forest type response to climate change. The objective of this paper is (1) to analyze the spatio-temporal pattern of net primary productivity (NPP) in a tropical forest ecosystem situated along the Himalayan foothills in India and (2) to investigate the continuous and delayed effects of climatic variables. Weapplied simple Monteith equation based Light use efficiency model for two dominant plant functional types; sal (Shorea robusta) forest and teak (Tectona grandis) plantation to estimate the NPP for a decadal period from 2001 to 2010. The impact of climate variables on NPP for these 10 years was seen by applying two correlation analyses; generalized linear modelling (GLM) and time lag correlation approach.The impact of different climate variables was observed to vary throughout the study period.A decline in mean NPP during 2002-2003, 2005 and 2008 to 2010 could be attributed to drought, increased vapour pressure deficit, and decreased humidity and solar radiation. In time lag correlation analysis, precipitation and humidity were observed to be the major variables affecting NPP; whereas combination of temperature, humidity and VPD showed dominant effect on NPP in GLM. Shorea robusta forest showed slightly higher NPP than that of Tectona grandis plantation throughout the study period. Highest decrease in NPP was observed during 2010,pertaining to lower solar radiation, humidity and precipitation along with increased VPD.Higher gains in NPP by sal during all years indicates their better adaptability to climate compared to teak. Contribution of different climatic variables through some link process is revealed in statistical analysis clearly indicates the co-dominance of all the variables in explaining NPP. Lacking of site specific meteorological observations and microclimate put constraint on broad level analyses.

Climate change and adverse health events: community perceptions from the Tanahu district of Nepal

NASA Astrophysics Data System (ADS)

Mishra, Shiva Raj; Mani Bhandari, Parash; Issa, Rita; Neupane, Dinesh; Gurung, Swadesh; Khanal, Vishnu

2015-03-01

Nepal is a country economically dependent on climate-sensitive industries. It is highly vulnerable to the environmental, social, economic and health impacts of climate change. The objective of this study is to explore community perceptions of climate variability and human health risks. In this letter, we present a cross sectional study conducted between August 2013 and July 2014 in the Tanahu district of Nepal. Our analysis is based on 258 face-to-face interviews with household heads utilizing structured questionnaires. Over half of the respondents (54.7%) had perceived a change in climate, 53.9% had perceived an increase in temperature in the summer and 49.2% had perceived an increase in rainfall during the rainy season. Half of the respondents perceived an increase in the number of diseases during the summer, 46.5% perceived an increase during the rainy season and 48.8% during winter. Only 8.9% of the respondents felt that the government was doing enough to prevent climate change and its impact on their community. Belonging to the Janajati (indigenous) ethnic group, living in a pakki, super-pakki house and belonging to poor or mid-level income were related to higher odds of perceiving climate variability. Illiterates were less likely to perceive climate variability. Respondents living in a pakki house, super-pakki, or those who were poor were more likely to perceive health risks. Illiterates were less likely to perceive health risks.

Climate Informed Economic Instruments to Enhance Urban Water Supply Resilience to Hydroclimatological Variability and Change

NASA Astrophysics Data System (ADS)

Brown, C.; Carriquiry, M.; Souza Filho, F. A.

2006-12-01

Hydroclimatological variability presents acute challenges to urban water supply providers. The impact is often most severe in developing nations where hydrologic and climate variability can be very high, water demand is unmet and increasing, and the financial resources to mitigate the social effects of that variability are limited. Furthermore, existing urban water systems face a reduced solution space, constrained by competing and conflicting interests, such as irrigation demand, recreation and hydropower production, and new (relative to system design) demands to satisfy environmental flow requirements. These constraints magnify the impacts of hydroclimatic variability and increase the vulnerability of urban areas to climate change. The high economic and social costs of structural responses to hydrologic variability, such as groundwater utilization and the construction or expansion of dams, create a need for innovative alternatives. Advances in hydrologic and climate forecasting, and the increasing sophistication and acceptance of incentive-based mechanisms for achieving economically efficient water allocation offer potential for improving the resilience of existing water systems to the challenge of variable supply. This presentation will explore the performance of a system of climate informed economic instruments designed to facilitate the reduction of hydroclimatologic variability-induced impacts on water-sensitive stakeholders. The system is comprised of bulk water option contracts between urban water suppliers and agricultural users and insurance indexed on reservoir inflows designed to cover the financial needs of the water supplier in situations where the option is likely to be exercised. Contract and insurance parameters are linked to forecasts and the evolution of seasonal precipitation and streamflow and designed for financial and political viability. A simulation of system performance is presented based on ongoing work in Metro Manila, Philippines. The system is further evaluated as an alternative strategy to infrastructure expansion for climate change adaptation in the water resources sector.

Resilience, rapid transitions and regime shifts: fingerprinting the responses of Lake Żabińskie (NE Poland) to climate variability and human disturbance since 1000 AD

NASA Astrophysics Data System (ADS)

Tylmann, Wojciech; Hernández-Almeida, Iván; Grosjean, Martin; José Gómez Navarro, Juan; Larocque-Tobler, Isabelle; Bonk, Alicja; Enters, Dirk; Ustrzycka, Alicja; Piotrowska, Natalia; Przybylak, Rajmund; Wacnik, Agnieszka; Witak, Małgorzata

2016-04-01

Rapid ecosystem transitions and adverse effects on ecosystem services as responses to combined climate and human impacts are of major concern. Yet few quantitative observational data exist, particularly for ecosystems that have a long history of human intervention. Here, we combine quantitative summer and winter climate reconstructions, climate model simulations and proxies for three major environmental pressures (land use, nutrients and erosion) to explore the system dynamics, resilience, and the role of disturbance regimes in varved eutrophic Lake Żabińskie since AD 1000. Comparison between regional and global climate simulations and quantitative climate reconstructions indicate that proxy data capture noticeably natural forced climate variability, while internal variability appears as the dominant source of climate variability in the climate model simulations during most parts of the last millennium. Using different multivariate analyses and change point detection techniques, we identify ecosystem changes through time and shifts between rather stable states and highly variable ones, as expressed by the proxies for land-use, erosion and productivity in the lake. Prior to AD 1600, the lake ecosystem was characterized by a high stability and resilience against considerable observed natural climate variability. In contrast, lake-ecosystem conditions started to fluctuate at high frequency across a broad range of states after AD 1600. The period AD 1748-1868 represents the phase with the strongest human disturbance of the ecosystem. Analyses of the frequency of change points in the multi-proxy dataset suggests that the last 400 years were highly variable and flickering with increasing vulnerability of the ecosystem to the combined effects of climate variability and anthropogenic disturbances. This led to significant rapid ecosystem transformations.

Impact of Climate Change on Food Security in Kenya

NASA Astrophysics Data System (ADS)

Yator, J. J.

2016-12-01

This study sought to address the existing gap on the impact of climate change on food security in support of policy measures to avert famine catastrophes. Fixed and random effects regressions for crop food security were estimated. The study simulated the expected impact of future climate change on food insecurity based on the Representative Concentration Pathways scenario (RCPs). The study makes use of county-level yields estimates (beans, maize, millet and sorghum) and daily climate data (1971 to 2010). Climate variability affects food security irrespective of how food security is defined. Rainfall during October-November-December (OND), as well as during March-April-May (MAM) exhibit an inverted U-shaped relationship with most food crops; the effects are most pronounced for maize and sorghum. Beans and Millet are found to be largely unresponsive to climate variability and also to time-invariant factors. OND rains and fall and summer temperature exhibit a U-shaped relationship with yields for most crops, while MAM rains temperature exhibits an inverted U-shaped relationship. However, winter temperatures exhibit a hill-shaped relationship with most crops. Project future climate change scenarios on crop productivity show that climate change will adversely affect food security, with up to 69% decline in yields by the year 2100. Climate variables have a non-linear relationship with food insecurity. Temperature exhibits an inverted U-shaped relationship with food insecurity, suggesting that increased temperatures will increase crop food insecurity. However, maize and millet, benefit from increased summer and winter temperatures. The simulated effects of different climate change scenarios on food insecurity suggest that adverse climate change will increase food insecurity in Kenya. The largest increases in food insecurity are predicted for the RCP 8.5Wm2, compared to RCP 4.5Wm2. Climate change is likely to have the greatest effects on maize insecurity, which is likely to increase by between 8.56% and 21% by the year 2100. There exists a need for policies that safeguard agriculture against the adverse effects of climate change to alleviate food insecurity in Kenya. Therefore, it is important that climate change mitigation is given much more priority in policy planning and also implementation.

Annual trend patterns of phytoplankton species abundance belie homogeneous taxonomical group responses to climate in the NE Atlantic upwelling.

PubMed

Bode, Antonio; Estévez, M Graciela; Varela, Manuel; Vilar, José A

2015-09-01

Phytoplankton is a sentinel of marine ecosystem change. Composed by many species with different life-history strategies, it rapidly responds to environment changes. An analysis of the abundance of 54 phytoplankton species in Galicia (NW Spain) between 1989 and 2008 to determine the main components of temporal variability in relation to climate and upwelling showed that most of this variability was stochastic, as seasonality and long term trends contributed to relatively small fractions of the series. In general, trends appeared as non linear, and species clustered in 4 groups according to the trend pattern but there was no defined pattern for diatoms, dinoflagellates or other groups. While, in general, total abundance increased, no clear trend was found for 23 species, 14 species decreased, 4 species increased during the early 1990s, and only 13 species showed a general increase through the series. In contrast, series of local environmental conditions (temperature, stratification, nutrients) and climate-related variables (atmospheric pressure indices, upwelling winds) showed a high fraction of their variability in deterministic seasonality and trends. As a result, each species responded independently to environmental and climate variability, measured by generalized additive models. Most species showed a positive relationship with nutrient concentrations but only a few showed a direct relationship with stratification and upwelling. Climate variables had only measurable effects on some species but no common response emerged. Because its adaptation to frequent disturbances, phytoplankton communities in upwelling ecosystems appear less sensitive to changes in regional climate than other communities characterized by short and well defined productive periods. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Relationship between Climate Variability, Wildfire Risk, and Wildfire Occurrence in Wildland-Urban Interface of the Southwestern United States

NASA Astrophysics Data System (ADS)

Kafatos, M.; Kim, S. H.; Jia, S.; Nghiem, S. V.

2017-12-01

As housing units in or near wildlands have grown, the wildland-urban interface (WUI) contain at present approximately one-third of all housing in the contiguous US. Wildfires are a part of the natural cycle in the Southwestern United States (SWUS) but the increasing trend of WUI has made wildfires a serious high-risk hazard. The expansion of WUI has elevated wildfire risks by increasing the chance of human caused ignitions and past fire suppression in the area. Previous studies on climate variability have shown that the SWUS region is prone to frequent droughts and has suffered from severe wildfires in the recent decade. Therefore, assessing the increased vulnerability to the wildfire in WUI is crucial for proactive adaptation under climate change. Our previous study has shown that a strong correlation between North Atlantic Oscillation (NAO) and temperature was found during March-June in the SWUS. The abnormally warm and dry spring conditions, combined with suppression of winter precipitation, can cause an early start of a fire season and high fire risk throughout the summer and fall. Therefore, it is crucial to investigate the connections between climate variability and wildfire danger characteristics. This study aims to identify climate variability using multiple climate indices such as NAO, El Niño-Southern Oscillation and the Pacific Decadal Oscillation closely related with droughts in the SWUS region. Correlation between the variability and fire frequency and severity in WUI were examined. Also, we investigated climate variability and its relationship on local wildfire potential using both Keetch-Byram Drought Index (KBDI) and Fire Weather Index (FWI) which have been used to assessing wildfire potential in the U.S.A and Canada, respectively. We examined the long-term variability of the fire potential indices and relationships between the indices and historical occurrence in WUI using multi-decadal reanalysis data sets. Following our analysis, we investigated joint impacts of multiple climate indices on droughts and human activities in the WUI for regional wildfire potential.

Adapting to climate variability and change: experiences from cereal-based farming in the central rift and Kobo Valleys, Ethiopia.

PubMed

Kassie, Belay Tseganeh; Hengsdijk, Huib; Rötter, Reimund; Kahiluoto, Helena; Asseng, Senthold; Van Ittersum, Martin

2013-11-01

Small-holder farmers in Ethiopia are facing several climate related hazards, in particular highly variable rainfall with severe droughts which can have devastating effects on their livelihoods. Projected changes in climate are expected to aggravate the existing challenges. This study examines farmer perceptions on current climate variability and long-term changes, current adaptive strategies, and potential barriers for successful further adaptation in two case study regions-the Central Rift Valley (CRV) and Kobo Valley. The study was based on a household questionnaire, interviews with key stakeholders, and focus group discussions. The result revealed that about 99 % of the respondents at the CRV and 96 % at the Kobo Valley perceived an increase in temperature and 94 % at CRV and 91 % at the Kobo Valley perceived a decrease in rainfall over the last 20-30 years. Inter-annual and intraseasonal rainfall variability also has increased according to the farmers. The observed climate data (1977-2009) also showed an increasing trend in temperature and high inter-annual and intra-seasonal rainfall variability. In contrast to farmers' perceptions of a decrease in rainfall totals, observed rainfall data showed no statistically significant decline. The interaction among various bio-physical and socio-economic factors, changes in rainfall intensity and reduced water available to crops due to increased hot spells, may have influenced the perception of farmers with respect to rainfall trends. In recent decades, farmers in both the CRV and Kobo have changed farming practices to adapt to perceived climate change and variability, for example, through crop and variety choice, adjustment of cropping calendar, and in situ moisture conservation. These relatively low-cost changes in farm practices were within the limited adaptation capacity of farmers, which may be insufficient to deal with the impacts of future climate change. Anticipated climate change is expected to impose new risks outside the range of current experiences. To enable farmers to adapt to these impacts critical technological, institutional, and market-access constraints need to be removed. Inconsistencies between farmers' perceptions and observed climate trends (e.g., decrease in annual rainfall) could lead to sub-optimal or counterproductive adaptations, and therefore must be removed by better communication and capacity building, for example through Climate Field Schools. Enabling strategies, which are among others targeted at agricultural inputs, credit supply, market access, and strengthening of local knowledge and information services need to become integral part of government policies to assist farmers to adapt to the impacts of current and future climate change.

Adapting to Climate Variability and Change: Experiences from Cereal-Based Farming in the Central Rift and Kobo Valleys, Ethiopia

NASA Astrophysics Data System (ADS)

Kassie, Belay Tseganeh; Hengsdijk, Huib; Rötter, Reimund; Kahiluoto, Helena; Asseng, Senthold; Van Ittersum, Martin

2013-11-01

Small-holder farmers in Ethiopia are facing several climate related hazards, in particular highly variable rainfall with severe droughts which can have devastating effects on their livelihoods. Projected changes in climate are expected to aggravate the existing challenges. This study examines farmer perceptions on current climate variability and long-term changes, current adaptive strategies, and potential barriers for successful further adaptation in two case study regions—the Central Rift Valley (CRV) and Kobo Valley. The study was based on a household questionnaire, interviews with key stakeholders, and focus group discussions. The result revealed that about 99 % of the respondents at the CRV and 96 % at the Kobo Valley perceived an increase in temperature and 94 % at CRV and 91 % at the Kobo Valley perceived a decrease in rainfall over the last 20-30 years. Inter-annual and intraseasonal rainfall variability also has increased according to the farmers. The observed climate data (1977-2009) also showed an increasing trend in temperature and high inter-annual and intra-seasonal rainfall variability. In contrast to farmers’ perceptions of a decrease in rainfall totals, observed rainfall data showed no statistically significant decline. The interaction among various bio-physical and socio-economic factors, changes in rainfall intensity and reduced water available to crops due to increased hot spells, may have influenced the perception of farmers with respect to rainfall trends. In recent decades, farmers in both the CRV and Kobo have changed farming practices to adapt to perceived climate change and variability, for example, through crop and variety choice, adjustment of cropping calendar, and in situ moisture conservation. These relatively low-cost changes in farm practices were within the limited adaptation capacity of farmers, which may be insufficient to deal with the impacts of future climate change. Anticipated climate change is expected to impose new risks outside the range of current experiences. To enable farmers to adapt to these impacts critical technological, institutional, and market-access constraints need to be removed. Inconsistencies between farmers’ perceptions and observed climate trends (e.g., decrease in annual rainfall) could lead to sub-optimal or counterproductive adaptations, and therefore must be removed by better communication and capacity building, for example through Climate Field Schools. Enabling strategies, which are among others targeted at agricultural inputs, credit supply, market access, and strengthening of local knowledge and information services need to become integral part of government policies to assist farmers to adapt to the impacts of current and future climate change.

Climate variability and extremes, interacting with nitrogen storage, amplify eutrophication risk

USGS Publications Warehouse

Lee, Minjin; Shevliakova, Elena; Malyshev, Sergey; Milly, P.C.D.; Jaffe, Peter R.

2016-01-01

Despite 30 years of basin-wide nutrient-reduction efforts, severe hypoxia continues to be observed in the Chesapeake Bay. Here we demonstrate the critical influence of climate variability, interacting with accumulated nitrogen (N) over multidecades, on Susquehanna River dissolved nitrogen (DN) loads, known precursors of the hypoxia in the Bay. We used the process model LM3-TAN (Terrestrial and Aquatic Nitrogen), which is capable of capturing both seasonal and decadal-to-century changes in vegetation-soil-river N storage, and produced nine scenarios of DN-load distributions under different short-term scenarios of climate variability and extremes. We illustrate that after 1 to 3 yearlong dry spells, the likelihood of exceeding a threshold DN load (56 kt yr−1) increases by 40 to 65% due to flushing of N accumulated throughout the dry spells and altered microbial processes. Our analyses suggest that possible future increases in climate variability/extremes—specifically, high precipitation occurring after multiyear dry spells—could likely lead to high DN-load anomalies and hypoxia.

Contrasting growth forecasts across the geographical range of Scots pine due to altitudinal and latitudinal differences in climatic sensitivity.

PubMed

Matías, Luis; Linares, Juan C; Sánchez-Miranda, Ángela; Jump, Alistair S

2017-10-01

Ongoing changes in global climate are altering ecological conditions for many species. The consequences of such changes are typically most evident at the edge of a species' geographical distribution, where differences in growth or population dynamics may result in range expansions or contractions. Understanding population responses to different climatic drivers along wide latitudinal and altitudinal gradients is necessary in order to gain a better understanding of plant responses to ongoing increases in global temperature and drought severity. We selected Scots pine (Pinus sylvestris L.) as a model species to explore growth responses to climatic variability (seasonal temperature and precipitation) over the last century through dendrochronological methods. We developed linear models based on age, climate and previous growth to forecast growth trends up to year 2100 using climatic predictions. Populations were located at the treeline across a latitudinal gradient covering the northern, central and southernmost populations and across an altitudinal gradient at the southern edge of the distribution (treeline, medium and lower elevations). Radial growth was maximal at medium altitude and treeline of the southernmost populations. Temperature was the main factor controlling growth variability along the gradients, although the timing and strength of climatic variables affecting growth shifted with latitude and altitude. Predictive models forecast a general increase in Scots pine growth at treeline across the latitudinal distribution, with southern populations increasing growth up to year 2050, when it stabilizes. The highest responsiveness appeared at central latitude, and moderate growth increase is projected at the northern limit. Contrastingly, the model forecasted growth declines at lowland-southern populations, suggesting an upslope range displacement over the coming decades. Our results give insight into the geographical responses of tree species to climate change and demonstrate the importance of incorporating biogeographical variability into predictive models for an accurate prediction of species dynamics as climate changes. © 2017 John Wiley & Sons Ltd.

Implementation of a Time Series Analysis for the Assessment of the Role of Climate Variability in a Post-Disturbance Savanna System

NASA Astrophysics Data System (ADS)

Gibbes, C.; Southworth, J.; Waylen, P. R.

2013-05-01

How do climate variability and climate change influence vegetation cover and vegetation change in savannas? A landscape scale investigation of the effect of changes in precipitation on vegetation is undertaken through the employment of a time series analysis. The multi-national study region is located within the Kavango-Zambezi region, and is delineated by the Okavango, Kwando, and Zambezi watersheds. A mean-variance time-series analysis quantifies vegetation dynamics and characterizes vegetation response to climate. The spatially explicit approach used to quantify the persistence of vegetation productivity permits the extraction of information regarding long term climate-landscape dynamics. Results show a pattern of reduced mean annual precipitation and increased precipitation variability across key social and ecological areas within the study region. Despite decreased mean annual precipitation since the mid to late 1970's vegetation trends predominantly indicate increasing biomass. The limited areas which have diminished vegetative cover relate to specific vegetation types, and are associated with declines in precipitation variability. Results indicate that in addition to short term changes in vegetation cover, long term trends in productive biomass are apparent, relate to spatial differences in precipitation variability, and potentially represent shifts vegetation composition. This work highlights the importance of time-series analyses for examining climate-vegetation linkages in a spatially explicit manner within a highly vulnerable region of the world.

Socio-ecological Typologies for Understanding Adaptive Capacity of a Region to Natural Disasters

NASA Astrophysics Data System (ADS)

Surendran Nair, S.; Preston, B. L.; King, A. W.; Mei, R.

2015-12-01

It is expected that the frequency and magnitude of extreme climatic events will increase in coming decades with an anticipated increase in losses from climate hazards. In the Gulf Coastal region of the United States, climate hazards/disasters are common including hurricanes, drought and flooding. However, the capacity to adapt to extreme climatic events varies across the region. This adaptive capacity is linked to the magnitude of the extreme event, exposed infrastructure, and the socio-economic conditions across the region. This study uses hierarchical clustering to quantitatively integrates regional socioeconomic and biophysical factors and develop socio-ecological typologies (SET). The biophysical factors include climatic and topographic variables, and the socio-economic variables include human capital, social capital and man-made resources (infrastructure) of the region. The types of the SET are independent variables in a statistical model of a regional variable of interest. The methodology was applied to US Gulf States to evaluate the social and biophysical determinants of the regional variation in social vulnerability and economic loss to climate hazards. The results show that the SET explains much of the regional variation in social vulnerability, effectively capturing its determinants. In addition, the SET also explains of the variability in economic loss to hazards across of the region. The approach can thus be used to prioritize adaptation strategies to reduce vulnerability and loss across the region.

Hydropower plans in eastern and southern Africa increase risk of concurrent climate-related electricity supply disruption

NASA Astrophysics Data System (ADS)

Conway, Declan; Dalin, Carole; Landman, Willem A.; Osborn, Timothy J.

2017-12-01

Hydropower comprises a significant and rapidly expanding proportion of electricity production in eastern and southern Africa. In both regions, hydropower is exposed to high levels of climate variability and regional climate linkages are strong, yet an understanding of spatial interdependences is lacking. Here we consider river basin configuration and define regions of coherent rainfall variability using cluster analysis to illustrate exposure to the risk of hydropower supply disruption of current (2015) and planned (2030) hydropower sites. Assuming completion of the dams planned, hydropower will become increasingly concentrated in the Nile (from 62% to 82% of total regional capacity) and Zambezi (from 73% to 85%) basins. By 2030, 70% and 59% of total hydropower capacity will be located in one cluster of rainfall variability in eastern and southern Africa, respectively, increasing the risk of concurrent climate-related electricity supply disruption in each region. Linking of nascent regional electricity sharing mechanisms could mitigate intraregional risk, although these mechanisms face considerable political and infrastructural challenges.

Climate variability slows evolutionary responses of Colias butterflies to recent climate change.

PubMed

Kingsolver, Joel G; Buckley, Lauren B

2015-03-07

How does recent climate warming and climate variability alter fitness, phenotypic selection and evolution in natural populations? We combine biophysical, demographic and evolutionary models with recent climate data to address this question for the subalpine and alpine butterfly, Colias meadii, in the southern Rocky Mountains. We focus on predicting patterns of selection and evolution for a key thermoregulatory trait, melanin (solar absorptivity) on the posterior ventral hindwings, which affects patterns of body temperature, flight activity, adult and egg survival, and reproductive success in Colias. Both mean annual summer temperatures and thermal variability within summers have increased during the past 60 years at subalpine and alpine sites. At the subalpine site, predicted directional selection on wing absorptivity has shifted from generally positive (favouring increased wing melanin) to generally negative during the past 60 years, but there is substantial variation among years in the predicted magnitude and direction of selection and the optimal absorptivity. The predicted magnitude of directional selection at the alpine site declined during the past 60 years and varies substantially among years, but selection has generally been positive at this site. Predicted evolutionary responses to mean climate warming at the subalpine site since 1980 is small, because of the variability in selection and asymmetry of the fitness function. At both sites, the predicted effects of adaptive evolution on mean population fitness are much smaller than the fluctuations in mean fitness due to climate variability among years. Our analyses suggest that variation in climate within and among years may strongly limit evolutionary responses of ectotherms to mean climate warming in these habitats. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Current temporal trends in moth abundance are counter to predicted effects of climate change in an assemblage of subarctic forest moths.

PubMed

Hunter, Mark D; Kozlov, Mikhail V; Itämies, Juhani; Pulliainen, Erkki; Bäck, Jaana; Kyrö, Ella-Maria; Niemelä, Pekka

2014-06-01

Changes in climate are influencing the distribution and abundance of the world's biota, with significant consequences for biological diversity and ecosystem processes. Recent work has raised concern that populations of moths and butterflies (Lepidoptera) may be particularly susceptible to population declines under environmental change. Moreover, effects of climate change may be especially pronounced in high latitude ecosystems. Here, we examine population dynamics in an assemblage of subarctic forest moths in Finnish Lapland to assess current trajectories of population change. Moth counts were made continuously over a period of 32 years using light traps. From 456 species recorded, 80 were sufficiently abundant for detailed analyses of their population dynamics. Climate records indicated rapid increases in temperature and winter precipitation at our study site during the sampling period. However, 90% of moth populations were stable (57%) or increasing (33%) over the same period of study. Nonetheless, current population trends do not appear to reflect positive responses to climate change. Rather, time-series models illustrated that the per capita rates of change of moth species were more frequently associated negatively than positively with climate change variables, even as their populations were increasing. For example, the per capita rates of change of 35% of microlepidoptera were associated negatively with climate change variables. Moth life-history traits were not generally strong predictors of current population change or associations with climate change variables. However, 60% of moth species that fed as larvae on resources other than living vascular plants (e.g. litter, lichen, mosses) were associated negatively with climate change variables in time-series models, suggesting that such species may be particularly vulnerable to climate change. Overall, populations of subarctic forest moths in Finland are performing better than expected, and their populations appear buffered at present from potential deleterious effects of climate change by other ecological forces. © 2014 John Wiley & Sons Ltd.

Compounding nonlinearities in the climate and wildfire system contribute to high uncertainty in estimates of future burned area in the western United State

NASA Astrophysics Data System (ADS)

Williams, P.

2015-12-01

Ecological studies are increasingly recognizing the importance of atmospheric vapor-pressure deficit (VPD) as a driver of forest drought stress and disturbance processes such as wildfire. Because of the nonlinear Clausius-Clapeyron relationship between temperature and saturation vapor pressure, small variations in temperature can have large impacts on VPD, and therefore drought, particularly in warm, dry areas and particularly during the warm season. It is also clear that VPD and drought affect forest fire nonlinearly, as incremental drying leads to increasingly large burned areas. Forest fire is also affected by fuel amount and connectivity, which are promoted by vegetation growth in previous years, which is in turn promoted by lack of drought, highlighting the importance of nuances in the sequencing of natural interannual climate variations in modulating the impacts of drought on wildfire. The many factors affecting forest fire, and the nonlinearities embedded within the climate and wildfire systems, cause interannual variability in forest-fire area and frequency to be wildly variable and strongly affected by internal climate variability. In addition, warming over the past century has produced a background increase in forest fire frequency and area in many regions. In this talk I focus on the western United States and will explore whether the relationships between internal climate variability on forest fire area have been amplified by the effects of warming as a result of the compounding nonlinearities described above. I will then explore what this means for future burned area in the western United States and make the case that uncertainties in the future global greenhouse gas emissions trajectory, model projections of mean temperatures, model projections of precipitation, and model projections of natural climate variability translate to very large uncertainties in the effects of future climate variability on forest fire area in the United States and globally.

Water management to cope with and adapt to climate variability and change.

NASA Astrophysics Data System (ADS)

Hamdy, A.; Trisorio-Liuzzi, G.

2009-04-01

In many parts of the world, variability in climatic conditions is already resulting in major impacts. These impacts are wide ranging and the link to water management problems is obvious and profound. The know-how and the available information undoubtedly indicate that climate change will lead to an intensification of the global hydrological cycle and can have major impacts on regional water resources, affecting both ground and surface water supply for sectorial water uses and, in particular, the irrigation field imposing notable negative effects on food security and poverty alleviation programs in most arid and semi-arid developing countries. At the United Nations Millennium Summit, in September 2000, world leaders adopted the Millennium Development Declaration. From this declaration, the IWRM was recognised as the key concept the water sector should be using for water related development and measures and, hence, for achieving the water related MDG's. However, the potential impacts of climate change and increasing climate variability are not sufficiently addressed in the IWRM plans. Indeed, only a very limited IWRM national plans have been prepared, coping with climate variability and changes. This is mainly due to the lack of operational instruments to deal with climate change and climate variability issues. This is particularly true in developing countries where the financial, human and ecological impacts are potentially greatest and where water resources may be already highly stressed, but the capacity to cope and adapt is weakest. Climate change has now brought realities including mainly rising temperatures and increasing frequency of floods and droughts that present new challenges to be addressed by the IWRM practice. There are already several regional and international initiatives underway that focus on various aspects of water resources management those to be linked with climate changes and vulnerability issues. This is the way where the water resources management and climate scientist communities are engaged in a process for building confidence and understanding, identifying options and defining the water resources management strategies which to cope with impacts of climate variability and change.

Smallholder agriculture in India and adaptation to current and future climate variability and climate change

NASA Astrophysics Data System (ADS)

Murari, K. K.; Jayaraman, T.

2014-12-01

Modeling studies have indicated that global warming, in many regions, will increase the exposure of major crops to rainfall and temperature stress, leading to lower crop yields. Climate variability alone has a potential to decrease yield to an extent comparable to or greater than yield reductions expected due to rising temperature. For India, where agriculture is important, both in terms of food security as well as a source of livelihoods to a majority of its population, climate variability and climate change are subjects of serious concern. There is however a need to distinguish the impact of current climate variability and climate change on Indian agriculture, especially in relation to their socioeconomic impact. This differentiation is difficult to determine due to the secular trend of increasing production and yield of the past several decades. The current research in this aspect is in an initial stage and requires a multi-disciplinary effort. In this study, we assess the potential differential impacts of environmental stress and shock across different socioeconomic strata of the rural population, using village level survey data. The survey data from eight selected villages, based on the Project on Agrarian Relations in India conducted by the Foundation for Agrarian Studies, indicated that income from crop production of the top 20 households (based on the extent of operational land holding, employment of hired labour and asset holdings) is a multiple of the mean income of the village. In sharp contrast, the income of the bottom 20 households is a fraction of the mean and sometimes negative, indicating a net loss from crop production. The considerable differentials in output and incomes suggest that small and marginal farmers are far more susceptible to climate variability and climate change than the other sections. Climate change is effectively an immediate threat to small and marginal farmers, which is driven essentially by socioeconomic conditions. The impact of climate variability on smallholder agriculture in the present can therefore provide important insights into the nature of its vulnerability to future climate change.

Influence of climate variability on acute myocardial infarction mortality in Havana, 2001-2012.

PubMed

Rivero, Alina; Bolufé, Javier; Ortiz, Paulo L; Rodríguez, Yunisleydi; Reyes, María C

2015-04-01

Death from acute myocardial infarction is due to many factors; influences on risk to the individual include habits, lifestyle and behavior, as well as weather, climate and other environmental components. Changing climate patterns make it especially important to understand how climatic variability may influence acute myocardial infarction mortality. Describe the relationship between climate variability and acute myocardial infarction mortality during the period 2001-2012 in Havana. An ecological time-series study was conducted. The universe comprised 23,744 deaths from acute myocardial infarction (ICD-10: I21-I22) in Havana residents from 2001 to 2012. Climate variability and seasonal anomalies were described using the Bultó-1 bioclimatic index (comprising variables of temperature, humidity, precipitation, and atmospheric pressure), along with series analysis to determine different seasonal-to-interannual climate variation signals. The role played by climate variables in acute myocardial infarction mortality was determined using factor analysis. The Mann-Kendall and Pettitt statistical tests were used for trend analysis with a significance level of 5%. The strong association between climate variability conditions described using the Bultó-1 bioclimatic index and acute myocardial infarctions accounts for the marked seasonal pattern in AMI mortality. The highest mortality rate occurred during the dry season, i.e., the winter months in Cuba (November-April), with peak numbers in January, December and March. The lowest mortality coincided with the rainy season, i.e., the summer months (May-October). A downward trend in total number of deaths can be seen starting with the change point in April 2009. Climate variability is inversely associated with an increase in acute myocardial infarction mortality as is shown by the Bultó-1 index. This inverse relationship accounts for acute myocardial infarction mortality's seasonal pattern.

Temperature and aridity regulate spatial variability of soil multifunctionality in drylands across the globe.

PubMed

Durán, Jorge; Delgado-Baquerizo, Manuel; Dougill, Andrew J; Guuroh, Reginald T; Linstädter, Anja; Thomas, Andrew D; Maestre, Fernando T

2018-05-01

The relationship between the spatial variability of soil multifunctionality (i.e., the capacity of soils to conduct multiple functions; SVM) and major climatic drivers, such as temperature and aridity, has never been assessed globally in terrestrial ecosystems. We surveyed 236 dryland ecosystems from six continents to evaluate the relative importance of aridity and mean annual temperature, and of other abiotic (e.g., texture) and biotic (e.g., plant cover) variables as drivers of SVM, calculated as the averaged coefficient of variation for multiple soil variables linked to nutrient stocks and cycling. We found that increases in temperature and aridity were globally correlated to increases in SVM. Some of these climatic effects on SVM were direct, but others were indirectly driven through reductions in the number of vegetation patches and increases in soil sand content. The predictive capacity of our structural equation modelling was clearly higher for the spatial variability of N- than for C- and P-related soil variables. In the case of N cycling, the effects of temperature and aridity were both direct and indirect via changes in soil properties. For C and P, the effect of climate was mainly indirect via changes in plant attributes. These results suggest that future changes in climate may decouple the spatial availability of these elements for plants and microbes in dryland soils. Our findings significantly advance our understanding of the patterns and mechanisms driving SVM in drylands across the globe, which is critical for predicting changes in ecosystem functioning in response to climate change. © 2018 by the Ecological Society of America.

Precision diet formulation to improve performance and profitability across various climates: Modeling the implications of increasing the formulation frequency of dairy cattle diets.

PubMed

White, Robin R; Capper, Judith L

2014-03-01

The objective of this study was to use a precision nutrition model to simulate the relationship between diet formulation frequency and dairy cattle performance across various climates. Agricultural Modeling and Training Systems (AMTS) CattlePro diet-balancing software (Cornell Research Foundation, Ithaca, NY) was used to compare 3 diet formulation frequencies (weekly, monthly, or seasonal) and 3 levels of climate variability (hot, cold, or variable). Predicted daily milk yield (MY), metabolizable energy (ME) balance, and dry matter intake (DMI) were recorded for each frequency-variability combination. Economic analysis was conducted to calculate the predicted revenue over feed and labor costs. Diet formulation frequency affected ME balance and MY but did not affect DMI. Climate variability affected ME balance and DMI but not MY. The interaction between climate variability and formulation frequency did not affect ME balance, MY, or DMI. Formulating diets more frequently increased MY, DMI, and ME balance. Economic analysis showed that formulating diets weekly rather than seasonally could improve returns over variable costs by $25,000 per year for a moderate-sized (300-cow) operation. To achieve this increase in returns, an entire feeding system margin of error of <1% was required. Formulating monthly, rather than seasonally, may be a more feasible alternative as this requires a margin of error of only 2.5% for the entire feeding system. Feeding systems with a low margin of error must be developed to better take advantage of the benefits of precision nutrition. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Is temperature the main cause of dengue rise in non-endemic countries? The case of Argentina

PubMed Central

2012-01-01

Background Dengue cases have increased during the last decades, particularly in non-endemic areas, and Argentina was no exception in the southern transmission fringe. Although temperature rise has been blamed for this, human population growth, increased travel and inefficient vector control may also be implicated. The relative contribution of geographic, demographic and climatic of variables on the occurrence of dengue cases was evaluated. Methods According to dengue history in the country, the study was divided in two decades, a first decade corresponding to the reemergence of the disease and the second including several epidemics. Annual dengue risk was modeled by a temperature-based mechanistic model as annual days of possible transmission. The spatial distribution of dengue occurrence was modeled as a function of the output of the mechanistic model, climatic, geographic and demographic variables for both decades. Results According to the temperature-based model dengue risk increased between the two decades, and epidemics of the last decade coincided with high annual risk. Dengue spatial occurrence was best modeled by a combination of climatic, demographic and geographic variables and province as a grouping factor. It was positively associated with days of possible transmission, human population number, population fall and distance to water bodies. When considered separately, the classification performance of demographic variables was higher than that of climatic and geographic variables. Conclusions Temperature, though useful to estimate annual transmission risk, does not fully describe the distribution of dengue occurrence at the country scale. Indeed, when taken separately, climatic variables performed worse than geographic or demographic variables. A combination of the three types was best for this task. PMID:22768874

Regional changes in extreme monsoon rainfall deficit and excess in India

NASA Astrophysics Data System (ADS)

Pal, Indrani; Al-Tabbaa, Abir

2010-04-01

With increasing concerns about climate change, the need to understand the nature and variability of monsoon climatic conditions and to evaluate possible future changes becomes increasingly important. This paper deals with the changes in frequency and magnitudes of extreme monsoon rainfall deficiency and excess in India from 1871 to 2005. Five regions across India comprising variable climates were selected for the study. Apart from changes in individual regions, changing tendencies in extreme monsoon rainfall deficit and excess were also determined for the Indian region as a whole. The trends and their significance were assessed using non-parametric Mann-Kendall technique. The results show that intra-region variability for extreme monsoon seasonal precipitation is large and mostly exhibited a negative tendency leading to increasing frequency and magnitude of monsoon rainfall deficit and decreasing frequency and magnitude of monsoon rainfall excess.

Climate-growth relationships for yellow-poplar across structural and site quality gradients in the southern Appalachian Mountains

Treesearch

Tara L. Keyser; Peter M. Brown

2014-01-01

Forecasted changes in climate across the southeastern US include an increase in temperature along with more variable precipitation patterns, including an increase in the severity and frequency of drought events. As such, the management of forests for increased resistance or resilience to the direct and indirect effects of climate change, including decreased tree- and...

Variability of precipitation in Poland under climate change

NASA Astrophysics Data System (ADS)

Szwed, Małgorzata

2018-02-01

The surface warming has been widespread over the entire globe. Central Europe, including Poland, is not an exception. Global temperature increases are accompanied by changes in other climatic variables. Climate change in Poland manifests itself also as change in annual sums of precipitation. They have been slightly growing but, what is more important, seasonal and monthly distributions of precipitation have been also changing. The most visible increases have been observed during colder half-year, especially in March. A decreasing contribution of summer precipitation total (June-August) to the annual total is observed. Climate projections for Poland predict further warming and continuation of already observed changes in the quantity of precipitation as well as its spatial and seasonal distribution.

Evaluating climate change impacts on streamflow variability based on a multisite multivariate GCM downscaling method in the Jing River of China

NASA Astrophysics Data System (ADS)

Li, Zhi; Jin, Jiming

2017-11-01

Projected hydrological variability is important for future resource and hazard management of water supplies because changes in hydrological variability can cause more disasters than changes in the mean state. However, climate change scenarios downscaled from Earth System Models (ESMs) at single sites cannot meet the requirements of distributed hydrologic models for simulating hydrological variability. This study developed multisite multivariate climate change scenarios via three steps: (i) spatial downscaling of ESMs using a transfer function method, (ii) temporal downscaling of ESMs using a single-site weather generator, and (iii) reconstruction of spatiotemporal correlations using a distribution-free shuffle procedure. Multisite precipitation and temperature change scenarios for 2011-2040 were generated from five ESMs under four representative concentration pathways to project changes in streamflow variability using the Soil and Water Assessment Tool (SWAT) for the Jing River, China. The correlation reconstruction method performed realistically for intersite and intervariable correlation reproduction and hydrological modeling. The SWAT model was found to be well calibrated with monthly streamflow with a model efficiency coefficient of 0.78. It was projected that the annual mean precipitation would not change, while the mean maximum and minimum temperatures would increase significantly by 1.6 ± 0.3 and 1.3 ± 0.2 °C; the variance ratios of 2011-2040 to 1961-2005 were 1.15 ± 0.13 for precipitation, 1.15 ± 0.14 for mean maximum temperature, and 1.04 ± 0.10 for mean minimum temperature. A warmer climate was predicted for the flood season, while the dry season was projected to become wetter and warmer; the findings indicated that the intra-annual and interannual variations in the future climate would be greater than in the current climate. The total annual streamflow was found to change insignificantly but its variance ratios of 2011-2040 to 1961-2005 increased by 1.25 ± 0.55. Streamflow variability was predicted to become greater over most months on the seasonal scale because of the increased monthly maximum streamflow and decreased monthly minimum streamflow. The increase in streamflow variability was attributed mainly to larger positive contributions from increased precipitation variances rather than negative contributions from increased mean temperatures.

The Relative Importance of Spatial and Local Environmental Factors in Determining Beetle Assemblages in the Inner Mongolia Grassland.

PubMed

Yu, Xiao-Dong; Lü, Liang; Wang, Feng-Yan; Luo, Tian-Hong; Zou, Si-Si; Wang, Cheng-Bin; Song, Ting-Ting; Zhou, Hong-Zhang

2016-01-01

The aim of this paper is to increase understanding of the relative importance of the input of geographic and local environmental factors on richness and composition of epigaeic steppe beetles (Coleoptera: Carabidae and Tenebrionidae) along a geographic (longitudinal/precipitation) gradient in the Inner Mongolia grassland. Specifically, we evaluate the associations of environmental variables representing climate and environmental heterogeneity with beetle assemblages. Beetles were sampled using pitfall traps at 25 sites scattered across the full geographic extent of the study biome in 2011-2012. We used variance partitioning techniques and multi-model selection based on the Akaike information criterion to assess the relative importance of the spatial and environmental variables on beetle assemblages. Species richness and abundance showed unimodal patterns along the geographic gradient. Together with space, climate variables associated with precipitation, water-energy balance and harshness of climate had strong explanatory power in richness pattern. Abundance pattern showed strongest association with variation in temperature and environmental heterogeneity. Climatic factors associated with temperature and precipitation variables and the interaction between climate with space were able to explain a substantial amount of variation in community structure. In addition, the turnover of species increased significantly as geographic distances increased. We confirmed that spatial and local environmental factors worked together to shape epigaeic beetle communities along the geographic gradient in the Inner Mongolia grassland. Moreover, the climate features, especially precipitation, water-energy balance and temperature, and the interaction between climate with space and environmental heterogeneity appeared to play important roles on controlling richness and abundance, and species compositions of epigaeic beetles.

Crop responses to climatic variation

PubMed Central

Porter, John R; Semenov, Mikhail A

2005-01-01

The yield and quality of food crops is central to the well being of humans and is directly affected by climate and weather. Initial studies of climate change on crops focussed on effects of increased carbon dioxide (CO2) level and/or global mean temperature and/or rainfall and nutrition on crop production. However, crops can respond nonlinearly to changes in their growing conditions, exhibit threshold responses and are subject to combinations of stress factors that affect their growth, development and yield. Thus, climate variability and changes in the frequency of extreme events are important for yield, its stability and quality. In this context, threshold temperatures for crop processes are found not to differ greatly for different crops and are important to define for the major food crops, to assist climate modellers predict the occurrence of crop critical temperatures and their temporal resolution. This paper demonstrates the impacts of climate variability for crop production in a number of crops. Increasing temperature and precipitation variability increases the risks to yield, as shown via computer simulation and experimental studies. The issue of food quality has not been given sufficient importance when assessing the impact of climate change for food and this is addressed. Using simulation models of wheat, the concentration of grain protein is shown to respond to changes in the mean and variability of temperature and precipitation events. The paper concludes with discussion of adaptation possibilities for crops in response to drought and argues that characters that enable better exploration of the soil and slower leaf canopy expansion could lead to crop higher transpiration efficiency. PMID:16433091

Decoding the spatial signatures of multi-scale climate variability - a climate network perspective

NASA Astrophysics Data System (ADS)

Donner, R. V.; Jajcay, N.; Wiedermann, M.; Ekhtiari, N.; Palus, M.

2017-12-01

During the last years, the application of complex networks as a versatile tool for analyzing complex spatio-temporal data has gained increasing interest. Establishing this approach as a new paradigm in climatology has already provided valuable insights into key spatio-temporal climate variability patterns across scales, including novel perspectives on the dynamics of the El Nino Southern Oscillation or the emergence of extreme precipitation patterns in monsoonal regions. In this work, we report first attempts to employ network analysis for disentangling multi-scale climate variability. Specifically, we introduce the concept of scale-specific climate networks, which comprises a sequence of networks representing the statistical association structure between variations at distinct time scales. For this purpose, we consider global surface air temperature reanalysis data and subject the corresponding time series at each grid point to a complex-valued continuous wavelet transform. From this time-scale decomposition, we obtain three types of signals per grid point and scale - amplitude, phase and reconstructed signal, the statistical similarity of which is then represented by three complex networks associated with each scale. We provide a detailed analysis of the resulting connectivity patterns reflecting the spatial organization of climate variability at each chosen time-scale. Global network characteristics like transitivity or network entropy are shown to provide a new view on the (global average) relevance of different time scales in climate dynamics. Beyond expected trends originating from the increasing smoothness of fluctuations at longer scales, network-based statistics reveal different degrees of fragmentation of spatial co-variability patterns at different scales and zonal shifts among the key players of climate variability from tropically to extra-tropically dominated patterns when moving from inter-annual to decadal scales and beyond. The obtained results demonstrate the potential usefulness of systematically exploiting scale-specific climate networks, whose general patterns are in line with existing climatological knowledge, but provide vast opportunities for further quantifications at local, regional and global scales that are yet to be explored.

Quantitative approaches in climate change ecology

PubMed Central

Brown, Christopher J; Schoeman, David S; Sydeman, William J; Brander, Keith; Buckley, Lauren B; Burrows, Michael; Duarte, Carlos M; Moore, Pippa J; Pandolfi, John M; Poloczanska, Elvira; Venables, William; Richardson, Anthony J

2011-01-01

Contemporary impacts of anthropogenic climate change on ecosystems are increasingly being recognized. Documenting the extent of these impacts requires quantitative tools for analyses of ecological observations to distinguish climate impacts in noisy data and to understand interactions between climate variability and other drivers of change. To assist the development of reliable statistical approaches, we review the marine climate change literature and provide suggestions for quantitative approaches in climate change ecology. We compiled 267 peer-reviewed articles that examined relationships between climate change and marine ecological variables. Of the articles with time series data (n = 186), 75% used statistics to test for a dependency of ecological variables on climate variables. We identified several common weaknesses in statistical approaches, including marginalizing other important non-climate drivers of change, ignoring temporal and spatial autocorrelation, averaging across spatial patterns and not reporting key metrics. We provide a list of issues that need to be addressed to make inferences more defensible, including the consideration of (i) data limitations and the comparability of data sets; (ii) alternative mechanisms for change; (iii) appropriate response variables; (iv) a suitable model for the process under study; (v) temporal autocorrelation; (vi) spatial autocorrelation and patterns; and (vii) the reporting of rates of change. While the focus of our review was marine studies, these suggestions are equally applicable to terrestrial studies. Consideration of these suggestions will help advance global knowledge of climate impacts and understanding of the processes driving ecological change.

Hydrological Impacts of Land Use Change and Climate Variability in the Headwater Region of the Heihe River Basin, Northwest China

PubMed Central

Zhang, Ling; Nan, Zhuotong; Xu, Yi; Li, Shuo

2016-01-01

Land use change and climate variability are two key factors impacting watershed hydrology, which is strongly related to the availability of water resources and the sustainability of local ecosystems. This study assessed separate and combined hydrological impacts of land use change and climate variability in the headwater region of a typical arid inland river basin, known as the Heihe River Basin, northwest China, in the recent past (1995–2014) and near future (2015–2024), by combining two land use models (i.e., Markov chain model and Dyna-CLUE) with a hydrological model (i.e., SWAT). The potential impacts in the near future were explored using projected land use patterns and hypothetical climate scenarios established on the basis of analyzing long-term climatic observations. Land use changes in the recent past are dominated by the expansion of grassland and a decrease in farmland; meanwhile the climate develops with a wetting and warming trend. Land use changes in this period induce slight reductions in surface runoff, groundwater discharge and streamflow whereas climate changes produce pronounced increases in them. The joint hydrological impacts are similar to those solely induced by climate changes. Spatially, both the effects of land use change and climate variability vary with the sub-basin. The influences of land use changes are more identifiable in some sub-basins, compared with the basin-wide impacts. In the near future, climate changes tend to affect the hydrological regimes much more prominently than land use changes, leading to significant increases in all hydrological components. Nevertheless, the role of land use change should not be overlooked, especially if the climate becomes drier in the future, as in this case it may magnify the hydrological responses. PMID:27348224

Hydrological Impacts of Land Use Change and Climate Variability in the Headwater Region of the Heihe River Basin, Northwest China.

PubMed

Zhang, Ling; Nan, Zhuotong; Xu, Yi; Li, Shuo

2016-01-01

Land use change and climate variability are two key factors impacting watershed hydrology, which is strongly related to the availability of water resources and the sustainability of local ecosystems. This study assessed separate and combined hydrological impacts of land use change and climate variability in the headwater region of a typical arid inland river basin, known as the Heihe River Basin, northwest China, in the recent past (1995-2014) and near future (2015-2024), by combining two land use models (i.e., Markov chain model and Dyna-CLUE) with a hydrological model (i.e., SWAT). The potential impacts in the near future were explored using projected land use patterns and hypothetical climate scenarios established on the basis of analyzing long-term climatic observations. Land use changes in the recent past are dominated by the expansion of grassland and a decrease in farmland; meanwhile the climate develops with a wetting and warming trend. Land use changes in this period induce slight reductions in surface runoff, groundwater discharge and streamflow whereas climate changes produce pronounced increases in them. The joint hydrological impacts are similar to those solely induced by climate changes. Spatially, both the effects of land use change and climate variability vary with the sub-basin. The influences of land use changes are more identifiable in some sub-basins, compared with the basin-wide impacts. In the near future, climate changes tend to affect the hydrological regimes much more prominently than land use changes, leading to significant increases in all hydrological components. Nevertheless, the role of land use change should not be overlooked, especially if the climate becomes drier in the future, as in this case it may magnify the hydrological responses.

Evaluation of climate variability on drought occurrence in an agricultural watershed

USDA-ARS?s Scientific Manuscript database

Changes in the future hydrologic cycle due to changes in precipitation and temperature are likely to be associated with increases in hydrologic extremes. This study evaluates the impacts of climate variability on drought using the Soil and Water Assessment Tool (SWAT) in the Goodwater Creek Experim...

Predicting drought in an agricultural watershed given climate variability

USDA-ARS?s Scientific Manuscript database

Changes in the future hydrologic cycle due to changes in temperature (T) and precipitation (P) are likely to be associated with increases in hydrologic extremes. This study evaluates the impacts of climate variability on drought using the Soil and Water Assessment Tool (SWAT) in Goodwater Creek Expe...

Meridional Modes and Increasing Pacific Decadal Variability Under Anthropogenic Forcing

NASA Astrophysics Data System (ADS)

Liguori, Giovanni; Di Lorenzo, Emanuele

2018-01-01

Pacific decadal variability has strong impacts on the statistics of weather, atmosphere extremes, droughts, hurricanes, marine heatwaves, and marine ecosystems. Sea surface temperature (SST) observations show that the variance of the El Niño-like decadal variability has increased by 30% (1920-2015) with a stronger coupling between the major Pacific climate modes. Although we cannot attribute these trends to global climate change, the examination of 30 members of the Community Earth System Model Large Ensemble (LENS) forced with the RCP8.5 radiative forcing scenario (1920-2100) suggests that significant anthropogenic trends in Pacific decadal variance will emerge by 2020 in response to a more energetic North Pacific Meridional Mode (PMM)—a well-known El Niño precursor. The PMM is a key mechanism for energizing and coupling tropical and extratropical decadal variability. In the LENS, the increase in PMM variance is consistent with an intensification of the winds-evaporation-SST thermodynamic feedback that results from a warmer mean climate.

Predicting ecological responses in a changing ocean: the effects of future climate uncertainty.

PubMed

Freer, Jennifer J; Partridge, Julian C; Tarling, Geraint A; Collins, Martin A; Genner, Martin J

2018-01-01

Predicting how species will respond to climate change is a growing field in marine ecology, yet knowledge of how to incorporate the uncertainty from future climate data into these predictions remains a significant challenge. To help overcome it, this review separates climate uncertainty into its three components (scenario uncertainty, model uncertainty, and internal model variability) and identifies four criteria that constitute a thorough interpretation of an ecological response to climate change in relation to these parts (awareness, access, incorporation, communication). Through a literature review, the extent to which the marine ecology community has addressed these criteria in their predictions was assessed. Despite a high awareness of climate uncertainty, articles favoured the most severe emission scenario, and only a subset of climate models were used as input into ecological analyses. In the case of sea surface temperature, these models can have projections unrepresentative against a larger ensemble mean. Moreover, 91% of studies failed to incorporate the internal variability of a climate model into results. We explored the influence that the choice of emission scenario, climate model, and model realisation can have when predicting the future distribution of the pelagic fish, Electrona antarctica . Future distributions were highly influenced by the choice of climate model, and in some cases, internal variability was important in determining the direction and severity of the distribution change. Increased clarity and availability of processed climate data would facilitate more comprehensive explorations of climate uncertainty, and increase in the quality and standard of marine prediction studies.

Faithful or not: direct and indirect effects of climate on extra-pair paternities in a population of Alpine marmots

PubMed Central

Allainé, Dominique; Sauzet, Sandrine; Cohas, Aurélie

2016-01-01

Despite being identified an area that is poorly understood regarding the effects of climate change, behavioural responses to climatic variability are seldom explored. Climatic variability is likely to cause large inter-annual variation in the frequency of extra-pair litters produced, a widespread alternative mating tactic to help prevent, correct or minimize the negative consequences of sub-optimal mate choice. In this study, we investigated how climatic variability affects the inter-annual variation in the proportion of extra-pair litters in a wild population of Alpine marmots. During 22 years of monitoring, the annual proportion of extra-pair litters directly increased with the onset of earlier springs and indirectly with increased snow in winters. Snowier winters resulted in a higher proportion of families with sexually mature male subordinates and thus, created a social context within which extra-pair paternity was favoured. Earlier spring snowmelt could create this pattern by relaxing energetic, movement and time constraints. Further, deeper snow in winter could also contribute by increasing litter size and juvenile survival. Optimal mate choice is particularly relevant to generate adaptive genetic diversity. Understanding the influence of environmental conditions and the capacity of the individuals to cope with them is crucial within the context of rapid climate change. PMID:28003452

Faithful or not: direct and indirect effects of climate on extra-pair paternities in a population of Alpine marmots.

PubMed

Bichet, Coraline; Allainé, Dominique; Sauzet, Sandrine; Cohas, Aurélie

2016-12-28

Despite being identified an area that is poorly understood regarding the effects of climate change, behavioural responses to climatic variability are seldom explored. Climatic variability is likely to cause large inter-annual variation in the frequency of extra-pair litters produced, a widespread alternative mating tactic to help prevent, correct or minimize the negative consequences of sub-optimal mate choice. In this study, we investigated how climatic variability affects the inter-annual variation in the proportion of extra-pair litters in a wild population of Alpine marmots. During 22 years of monitoring, the annual proportion of extra-pair litters directly increased with the onset of earlier springs and indirectly with increased snow in winters. Snowier winters resulted in a higher proportion of families with sexually mature male subordinates and thus, created a social context within which extra-pair paternity was favoured. Earlier spring snowmelt could create this pattern by relaxing energetic, movement and time constraints. Further, deeper snow in winter could also contribute by increasing litter size and juvenile survival. Optimal mate choice is particularly relevant to generate adaptive genetic diversity. Understanding the influence of environmental conditions and the capacity of the individuals to cope with them is crucial within the context of rapid climate change. © 2016 The Author(s).

Unlocking the climate riddle in forested ecosystems

Treesearch

Greg C. Liknes; Christopher W. Woodall; Brian F. Walters; Sara A. Goeking

2012-01-01

Climate information is often used as a predictor in ecological studies, where temporal averages are typically based on climate normals (30-year means) or seasonal averages. While ensemble projections of future climate forecast a higher global average annual temperature, they also predict increased climate variability. It remains to be seen whether forest ecosystems...

Climate induced changes in biome distribution, NPP and hydrology for potential vegetation of the Upper Midwest U.S

NASA Astrophysics Data System (ADS)

Motew, M.; Kucharik, C. J.

2011-12-01

While much attention is focused on future impacts of climate change on ecosystems, much can be learned about the previous interactions of ecosystems with recent climate change. In this study, we investigated the impacts of climate change on potential vegetation distributions (i.e. grasses, trees, and shrubs) and carbon and water cycling across the Upper Midwest USA from 1948-2007 using the Agro-IBIS dynamic vegetation model. We drove the model using a historical, gridded daily climate data set (temperature, precipitation, humidity, solar radiation, and wind speed) at a spatial resolution of 5 min x 5 min. While trends in climate variables exhibited heterogeneous spatial patterns over the study period, the overall impact of climate change on vegetation productivity was positive. We observed total increases in net primary productivity (NPP) ranging from 20-150 g C m-2, based on linear regression analysis. We determined that increased summer relative humidity, increased annual precipitation and decreased mean maximum summer temperatures were key variables contributing to these positive trends, likely through a reduction in soil moisture stress (e.g., increased available water) and heat stress. Model simulations also illustrated an increase in annual drainage throughout the region of 20-140 mm yr-1, driven by substantial increases in annual precipitation. Evapotranspiration had a highly variable spatial trend over the 60-year period, with total change over the study period ranging between -100 and +100 mm yr-1. We also analyzed potential changes in plant functional type (PFT) distributions at the biome level, but hypothesize that the model may be unable to adequately capture competitive interactions among PFTs as well as the dynamics between upper and lower canopies consisting of trees, grasses and shrubs. An analysis of the bioclimatic envelopes for PFTs common to the region revealed no significant change to the boreal conifer tree climatic domain over the study period, yet did reveal a slightly expanded domain for temperate deciduous broadleaf trees. The location of the Tension Zone, a broad ecotone dividing mixed forests in the north and southern hardwood forests and prairies in the south, was not observed to shift using analyses of both meteorological variables and through the results of simulated vegetation distributions. In general, our results supported the idea that climate change is spatially variable in nature, having significant effects on ecosystem structure and function. Our analysis also revealed interesting relationships among the key climatic quantities driving plant productivity and hydrology in the region. Most notably, while the model suggested that potential biome and PFT distributions have not likely shifted significantly in the past 60 years, climate change has contributed to substantial changes in coupled carbon, water, and energy exchange in natural ecosystems of the Upper Midwest US. We conclude that incorporating recent, high-resolution climate records into ecological studies offers valuable insight into the heterogeneous nature of climate change and its impacts on ecosystems at the local level.

Centennial-scale Holocene climate variations amplified by Antarctic Ice Sheet discharge

NASA Astrophysics Data System (ADS)

Bakker, Pepijn; Clark, Peter U.; Golledge, Nicholas R.; Schmittner, Andreas; Weber, Michael E.

2017-01-01

Proxy-based indicators of past climate change show that current global climate models systematically underestimate Holocene-epoch climate variability on centennial to multi-millennial timescales, with the mismatch increasing for longer periods. Proposed explanations for the discrepancy include ocean-atmosphere coupling that is too weak in models, insufficient energy cascades from smaller to larger spatial and temporal scales, or that global climate models do not consider slow climate feedbacks related to the carbon cycle or interactions between ice sheets and climate. Such interactions, however, are known to have strongly affected centennial- to orbital-scale climate variability during past glaciations, and are likely to be important in future climate change. Here we show that fluctuations in Antarctic Ice Sheet discharge caused by relatively small changes in subsurface ocean temperature can amplify multi-centennial climate variability regionally and globally, suggesting that a dynamic Antarctic Ice Sheet may have driven climate fluctuations during the Holocene. We analysed high-temporal-resolution records of iceberg-rafted debris derived from the Antarctic Ice Sheet, and performed both high-spatial-resolution ice-sheet modelling of the Antarctic Ice Sheet and multi-millennial global climate model simulations. Ice-sheet responses to decadal-scale ocean forcing appear to be less important, possibly indicating that the future response of the Antarctic Ice Sheet will be governed more by long-term anthropogenic warming combined with multi-centennial natural variability than by annual or decadal climate oscillations.

The scaling of population persistence with carrying capacity does not asymptote in populations of a fish experiencing extreme climate variability.

PubMed

White, Richard S A; Wintle, Brendan A; McHugh, Peter A; Booker, Douglas J; McIntosh, Angus R

2017-06-14

Despite growing concerns regarding increasing frequency of extreme climate events and declining population sizes, the influence of environmental stochasticity on the relationship between population carrying capacity and time-to-extinction has received little empirical attention. While time-to-extinction increases exponentially with carrying capacity in constant environments, theoretical models suggest increasing environmental stochasticity causes asymptotic scaling, thus making minimum viable carrying capacity vastly uncertain in variable environments. Using empirical estimates of environmental stochasticity in fish metapopulations, we showed that increasing environmental stochasticity resulting from extreme droughts was insufficient to create asymptotic scaling of time-to-extinction with carrying capacity in local populations as predicted by theory. Local time-to-extinction increased with carrying capacity due to declining sensitivity to demographic stochasticity, and the slope of this relationship declined significantly as environmental stochasticity increased. However, recent 1 in 25 yr extreme droughts were insufficient to extirpate populations with large carrying capacity. Consequently, large populations may be more resilient to environmental stochasticity than previously thought. The lack of carrying capacity-related asymptotes in persistence under extreme climate variability reveals how small populations affected by habitat loss or overharvesting, may be disproportionately threatened by increases in extreme climate events with global warming. © 2017 The Author(s).

Impact of climate variability and anthropogenic activity on streamflow in the Three Rivers Headwater Region, Tibetan Plateau, China

NASA Astrophysics Data System (ADS)

Jiang, Chong; Li, Daiqing; Gao, Yanni; Liu, Wenfeng; Zhang, Linbo

2017-07-01

Under the impacts of climate variability and human activities, there is violent fluctuation for streamflow in the large basins in China. Therefore, it is crucial to separate the impacts of climate variability and human activities on streamflow fluctuation for better water resources planning and management. In this study, the Three Rivers Headwater Region (TRHR) was chosen as the study area. Long-term hydrological data for the TRHR were collected in order to investigate the changes in annual runoff during the period of 1956-2012. The nonparametric Mann-Kendall test, moving t test, Pettitt test, Mann-Kendall-Sneyers test, and the cumulative anomaly curve were used to identify trends and change points in the hydro-meteorological variables. Change point in runoff was identified in the three basins, which respectively occurred around the years 1989 and 1993, dividing the long-term runoff series into a natural period and a human-induced period. Then, the hydrologic sensitivity analysis method was employed to evaluate the effects of climate variability and human activities on mean annual runoff for the human-induced period based on precipitation and potential evapotranspiration. In the human-induced period, climate variability was the main factor that increased (reduced) runoff in LRB and YARB (YRB) with contribution of more than 90 %, while the increasing (decreasing) percentage due to human activities only accounted for less than 10 %, showing that runoff in the TRHR is more sensitive to climate variability than human activities. The intra-annual distribution of runoff shifted gradually from a double peak pattern to a single peak pattern, which was mainly influenced by atmospheric circulation in the summer and autumn. The inter-annual variation in runoff was jointly controlled by the East Asian monsoon, the westerly, and Tibetan Plateau monsoons.

Large-scale climatic phenomena drive fluctuations in macroinvertebrate assemblages in lowland tropical streams, Costa Rica: The importance of ENSO events in determining long-term (15y) patterns

PubMed Central

Ramírez, Alonso; Pringle, Catherine M.

2018-01-01

Understanding how environmental variables influence the distribution and density of organisms over relatively long temporal scales is a central question in ecology given increased climatic variability (e.g., precipitation, ENSO events). The primary goal of our study was to evaluate long-term (15y time span) patterns of climate, as well as environmental parameters in two Neotropical streams in lowland Costa Rica, to assess potential effects on aquatic macroinvertebrates. We also examined the relative effects of an 8y whole-stream P-enrichment experiment on macroinvertebrate assemblages against the backdrop of this long-term study. Climate, environmental variables and macroinvertebrate samples were measured monthly for 7y and then quarterly for an additional 8y in each stream. Temporal patterns in climatic and environmental variables showed high variability over time, without clear inter-annual or intra-annual patterns. Macroinvertebrate richness and abundance decreased with increasing discharge and was positively related to the number of days since the last high discharge event. Findings show that fluctuations in stream physicochemistry and macroinvertebrate assemblage structure are ultimately the result of large-scale climatic phenomena, such as ENSO events, while the 8y P-enrichment did not appear to affect macroinvertebrates. Our study demonstrates that Neotropical lowland streams are highly dynamic and not as stable as is commonly presumed, with high intra- and inter-annual variability in environmental parameters that change the structure and composition of freshwater macroinvertebrate assemblages. PMID:29420548

The cumulative effects of forest disturbance and climate variability on baseflow in a large forested watershed

NASA Astrophysics Data System (ADS)

Li, Q.; Wei, A.; Giles-Hansen, K.; Zhang, M.; Liu, W.

2016-12-01

Assessing how forest disturbance and climate change affect baseflow or groundwater discharge is critical for understanding water resource supply and protecting aquatic functions. Previous studies have mainly evaluated the effects of forest disturbance on streamflow, with rare attention on baseflow, particularly in large watersheds. However, studying this topic is challenging as it requires explicit inclusion of climate into assessment due to their interactions at any large watersheds. In this study, we used Upper Similkameen River watershed (USR) (1810 km2), located in the southern interior of British Columbia, Canada to examine how forest disturbance and climate variability affect baseflow. The conductivity mass balance method was first used for baseflow separation, and the modified double mass curves were then employed to quantitatively separate the relative contributions of forest disturbance and climate variability to annual baseflow. Our results showed that average annual baseflow and baseflow index (baseflow/streamflow) were about 85.2 ± 21.5 mm year-1 and 0.22 ± 0.05 for the study period of 1954-2013, respectively. The forest disturbance increased the annual baseflow of 18.4 mm, while climate variability decreased 19.4 mm. In addition, forest disturbance also shifted the baseflow regime with increasing of the spring baseflow and decreasing of the summer baseflow. We conclude that forest disturbance significantly altered the baseflow magnitudes and patterns, and its role in annual baseflow was equal to that caused by climate variability in the study watershed despite their opposite changing directions. The implications of our results are discussed in the context of future forest disturbance (or land cover changes) and climate changes.

Climate science and famine early warning

USGS Publications Warehouse

Verdin, James P.; Funk, Chris; Senay, Gabriel B.; Choularton, R.

2005-01-01

Food security assessment in sub-Saharan Africa requires simultaneous consideration of multiple socio-economic and environmental variables. Early identification of populations at risk enables timely and appropriate action. Since large and widely dispersed populations depend on rainfed agriculture and pastoralism, climate monitoring and forecasting are important inputs to food security analysis. Satellite rainfall estimates (RFE) fill in gaps in station observations, and serve as input to drought index maps and crop water balance models. Gridded rainfall time-series give historical context, and provide a basis for quantitative interpretation of seasonal precipitation forecasts. RFE are also used to characterize flood hazards, in both simple indices and stream flow models. In the future, many African countries are likely to see negative impacts on subsistence agriculture due to the effects of global warming. Increased climate variability is forecast, with more frequent extreme events. Ethiopia requires special attention. Already facing a food security emergency, troubling persistent dryness has been observed in some areas, associated with a positive trend in Indian Ocean sea surface temperatures. Increased African capacity for rainfall observation, forecasting, data management and modelling applications is urgently needed. Managing climate change and increased climate variability require these fundamental technical capacities if creative coping strategies are to be devised.

Climate science and famine early warning.

PubMed

Verdin, James; Funk, Chris; Senay, Gabriel; Choularton, Richard

2005-11-29

Food security assessment in sub-Saharan Africa requires simultaneous consideration of multiple socio-economic and environmental variables. Early identification of populations at risk enables timely and appropriate action. Since large and widely dispersed populations depend on rainfed agriculture and pastoralism, climate monitoring and forecasting are important inputs to food security analysis. Satellite rainfall estimates (RFE) fill in gaps in station observations, and serve as input to drought index maps and crop water balance models. Gridded rainfall time-series give historical context, and provide a basis for quantitative interpretation of seasonal precipitation forecasts. RFE are also used to characterize flood hazards, in both simple indices and stream flow models. In the future, many African countries are likely to see negative impacts on subsistence agriculture due to the effects of global warming. Increased climate variability is forecast, with more frequent extreme events. Ethiopia requires special attention. Already facing a food security emergency, troubling persistent dryness has been observed in some areas, associated with a positive trend in Indian Ocean sea surface temperatures. Increased African capacity for rainfall observation, forecasting, data management and modelling applications is urgently needed. Managing climate change and increased climate variability require these fundamental technical capacities if creative coping strategies are to be devised.

Climate science and famine early warning

PubMed Central

Verdin, James; Funk, Chris; Senay, Gabriel; Choularton, Richard

2005-01-01

Food security assessment in sub-Saharan Africa requires simultaneous consideration of multiple socio-economic and environmental variables. Early identification of populations at risk enables timely and appropriate action. Since large and widely dispersed populations depend on rainfed agriculture and pastoralism, climate monitoring and forecasting are important inputs to food security analysis. Satellite rainfall estimates (RFE) fill in gaps in station observations, and serve as input to drought index maps and crop water balance models. Gridded rainfall time-series give historical context, and provide a basis for quantitative interpretation of seasonal precipitation forecasts. RFE are also used to characterize flood hazards, in both simple indices and stream flow models. In the future, many African countries are likely to see negative impacts on subsistence agriculture due to the effects of global warming. Increased climate variability is forecast, with more frequent extreme events. Ethiopia requires special attention. Already facing a food security emergency, troubling persistent dryness has been observed in some areas, associated with a positive trend in Indian Ocean sea surface temperatures. Increased African capacity for rainfall observation, forecasting, data management and modelling applications is urgently needed. Managing climate change and increased climate variability require these fundamental technical capacities if creative coping strategies are to be devised. PMID:16433101

Impacts of Changing Climate on Agricultural Variability: Implications for Smallholder Farmers in India

NASA Astrophysics Data System (ADS)

Mondal, P.; Jain, M.; DeFries, R. S.; Galford, G. L.; Small, C.

2013-12-01

Agriculture is the largest employment sector in India, where food productivity, and thus food security, is highly dependent on seasonal rainfall and temperature. Projected increase in temperature, along with less frequent but intense rainfall events, will have a negative impact on crop productivity in India in the coming decades. These changes, along with continued ground water depletion, could have serious implications for Indian smallholder farmers, who are among some of the most vulnerable communities to climatic and economic changes. Hence baseline information on agricultural sensitivity to climate variability is important for strategies and policies that promote adaptation to climate variability. This study examines how cropping patterns in different agro-ecological zones in India respond to variations in precipitation and temperature. We specifically examine: a) which climate variables most influence crop cover for monsoon and winter crops? and b) how does the sensitivity of crop cover to climate variability vary in different agro-ecological regions with diverse socio-economic factors? We use remote sensing data (2000-01 - 2012-13) for cropping patterns (developed using MODIS satellite data), climate parameters (derived from MODIS and TRMM satellite data) and agricultural census data. We initially assessed the importance of these climate variables in two agro-ecoregions: a predominantly groundwater irrigated, cash crop region in western India, and a region in central India primarily comprised of rain-fed or surface water irrigated subsistence crops. Seasonal crop cover anomaly varied between -25% and 25% of the 13-year mean in these two regions. Predominantly climate-dependent region in central India showed high anomalies up to 200% of the 13-year crop cover mean, especially during winter season. Winter daytime mean temperature is overwhelmingly the most important climate variable for winter crops irrespective of the varied biophysical and socio-economic conditions across the study regions. Despite access to groundwater irrigation, crop cover in the western Indian study region showed substantial fluctuations during monsoon, probably due to changing planting strategies. This region is less sensitive to precipitation compared to the central Indian study region with predominantly climate-dependent irrigation from surface water. In western Indian study region a greater number of rainy days, increased intensity of rainfall, and cooler daytime and nighttime temperatures lead to increased crop cover during monsoon season, compared to in the central Indian study region where monsoon timing and amount of total rainfall are the most important factors of crop cover. Our findings indicate that different regions respond differently to climate, since socio-economic factors, such as irrigation access, market influences, demography, and policies play critical role in agricultural production. In the wake of projected precipitation and temperature changes, better access to irrigation and heat-tolerant high-yielding crop varieties will be crucial for future food production.

Vulnerability of breeding waterbirds to climate change in the Prairie Pothole Region, U.S.A.

PubMed

Steen, Valerie; Skagen, Susan K; Noon, Barry R

2014-01-01

The Prairie Pothole Region (PPR) of the north-central U.S. and south-central Canada contains millions of small prairie wetlands that provide critical habitat to many migrating and breeding waterbirds. Due to their small size and the relatively dry climate of the region, these wetlands are considered at high risk for negative climate change effects as temperatures increase. To estimate the potential impacts of climate change on breeding waterbirds, we predicted current and future distributions of species common in the PPR using species distribution models (SDMs). We created regional-scale SDMs for the U.S. PPR using Breeding Bird Survey occurrence records for 1971-2011 and wetland, upland, and climate variables. For each species, we predicted current distribution based on climate records for 1981-2000 and projected future distributions to climate scenarios for 2040-2049. Species were projected to, on average, lose almost half their current habitat (-46%). However, individual species projections varied widely, from +8% (Upland Sandpiper) to -100% (Wilson's Snipe). Variable importance ranks indicated that land cover (wetland and upland) variables were generally more important than climate variables in predicting species distributions. However, climate variables were relatively more important during a drought period. Projected distributions of species responses to climate change contracted within current areas of distribution rather than shifting. Given the large variation in species-level impacts, we suggest that climate change mitigation efforts focus on species projected to be the most vulnerable by enacting targeted wetland management, easement acquisition, and restoration efforts.

Climate-mediated spatiotemporal variability in terrestrial productivity across Europe

NASA Astrophysics Data System (ADS)

Wu, X.; Babst, F.; Ciais, P.; Frank, D.; Reichstein, M.; Wattenbach, M.; Zang, C.; Mahecha, M. D.

2014-06-01

Quantifying the interannual variability (IAV) of the terrestrial ecosystem productivity and its sensitivity to climate is crucial for improving carbon budget predictions. In this context it is necessary to disentangle the influence of climate from impacts of other mechanisms underlying the spatiotemporal patterns of IAV of the ecosystem productivity. In this study we investigated the spatiotemporal patterns of IAV of historical observations of European crop yields in tandem with a set of climate variables. We further evaluated if relevant remote-sensing retrievals of NDVI (normalized difference vegetation index) and FAPAR (fraction of absorbed photosynthetically active radiation) depict a similar behaviour. Our results reveal distinct spatial patterns in the IAV of the analysed proxies linked to terrestrial productivity. In particular, we find higher IAV in water-limited regions of Europe (Mediterranean and temperate continental Europe) compared to other regions in both crop yield and remote-sensing observations. Our results further indicate that variations in the water balance during the active growing season exert a more pronounced and direct effect than variations of temperature on explaining the spatial patterns in IAV of productivity-related variables in temperate Europe. Overall, we observe a temporally increasing trend in the IAV of terrestrial productivity and an increasing sensitivity of productivity to water availability in dry regions of Europe during the 1975-2009 period. In the same regions, a simultaneous increase in the IAV of water availability was detected. These findings suggest intricate responses of carbon fluxes to climate variability in Europe and that the IAV of terrestrial productivity has become potentially more sensitive to changes in water availability in the dry regions in Europe. The changing sensitivity of terrestrial productivity accompanied by the changing IAV of climate is expected to impact carbon stocks and the net carbon balance of European ecosystems.

Abrupt shifts in phenology and vegetation productivity under climate extremes

USDA-ARS?s Scientific Manuscript database

Amplification of the hydrologic cycle as a consequence of global warming is predicted to increase climate variability and the frequency and severity of droughts. Predicting how ecosystems will be affected by climate change requires not only reliable forecasts of future climate, but also observationa...

Conveying the Science of Climate Change: Explaining Natural Variability

NASA Astrophysics Data System (ADS)

Chanton, J.

2011-12-01

One of the main problems in climate change education is reconciling the role of humans and natural variability. The climate is always changing, so how can humans have a role in causing change? How do we reconcile and differentiate the anthropogenic effect from natural variability? This talk will offer several approaches that have been successful for the author. First, the context of climate change during the Pleistocene must be addressed. Second, is the role of the industrial revolution in significantly altering Pleistocene cycles, and introduction of the concept of the Anthropocene. Finally the positive feedbacks between climatic nudging due to increased insolation and greenhouse gas forcing can be likened to a rock rolling down a hill, without a leading cause. This approach has proven successful in presentations to undergraduates to state agencies.

Climate change impacts on faecal indicator and waterborne pathogen concentrations and disease

NASA Astrophysics Data System (ADS)

Hofstra, Nynke; Vermeulen, Lucie C.; Wondmagegn, Berhanu Y.

2013-04-01

Changes in temperature and precipitation patterns may impact on the concentrations of the faecal indicator E. coli and waterborne pathogens, such as Cryptosporidium, in the surface water, and consequently - through drinking water, recreational water or consumption of irrigated vegetables - on the risk of waterborne disease. Although an increased temperature would generally increase the decline of pathogens and therefore decrease the surface water concentrations, increased precipitation and an increased incidence of extreme precipitation may increase surface water concentrations through increased (sub-)surface runoff and an increased risk of sewer overflows. And while the diluting effect of increased precipitation decreases the surface water concentration, decreased precipitation increases the percentage of sewage in the surface water and therefore increases the concentration. Moreover, (extreme) precipitation after drought may also increase the concentration. Changes in behaviour, such as increased recreation and irrigation with higher temperatures may impact on the disease risk. What the balance is between these positive and negative impacts of climate change on faecal indicator and waterborne pathogen concentrations and disease is not well known yet. A lack of available statistical or process-based models and suitable scenarios prevents quantitative analyses. We will present two examples of recent studies that aim to assess the impact of climate change on faecal indicator concentrations and waterborne disease. The first is a study on the relationship between climate variables and E. coli concentrations in the water of river systems in the Netherlands for the period 1985 - 2010. This study shows that each of the variables water temperature (negatively), precipitation and discharge (both positively) are significantly correlated with E. coli concentrations for most measurement locations. We will also present a linear regression model, including all of these variables. In the second example we assess the relationship between the weather variables precipitation and minimum and maximum temperature and the number of diarrhoeal cases in Ethiopia. We have digitised data from the Ethiopian health service and hospitals on the number of diarrhoeal cases for the period 2005 - 2010 and used meteorological data from their weather service. Very strong correlations can be found between the monthly weather variables and the number of diarrhoeal cases and a linear regression model including all variables explains a large part of the variability of the data. The studies indicate that climate change may increase the waterborne pathogen concentration in surface water and disease risk and should therefore not be ignored as a threat to microbial water quality.

The response of the southwest Western Australian wave climate to Indian Ocean climate variability

NASA Astrophysics Data System (ADS)

Wandres, Moritz; Pattiaratchi, Charitha; Hetzel, Yasha; Wijeratne, E. M. S.

2018-03-01

Knowledge of regional wave climates is critical for coastal planning, management, and protection. In order to develop a regional wave climate, it is important to understand the atmospheric systems responsible for wave generation. This study examines the variability of the southwest Western Australian (SWWA) shelf and nearshore wind wave climate and its relationship to southern hemisphere climate variability represented by various atmospheric indices: the southern oscillation index (SOI), the Southern Annular Mode (SAM), the Indian Ocean Dipole Mode Index (DMI), the Indian Ocean Subtropical Dipole (IOSD), the latitudinal position of the subtropical high-pressure ridge (STRP), and the corresponding intensity of the subtropical ridge (STRI). A 21-year wave hindcast (1994-2014) of the SWWA continental shelf was created using the third generation wave model Simulating WAves Nearshore (SWAN), to analyse the seasonal and inter-annual wave climate variability and its relationship to the atmospheric regime. Strong relationships between wave heights and the STRP and the STRI, a moderate correlation between the wave climate and the SAM, and no significant correlation between SOI, DMI, and IOSD and the wave climate were found. Strong spatial, seasonal, and inter-annual variability, as well as seasonal longer-term trends in the mean wave climate were studied and linked to the latitudinal changes in the subtropical high-pressure ridge and the Southern Ocean storm belt. As the Southern Ocean storm belt and the subtropical high-pressure ridge shifted southward (northward) wave heights on the SWWA shelf region decreased (increased). The wave height anomalies appear to be driven by the same atmospheric conditions that influence rainfall variability in SWWA.

Spatial variability of climate change impacts on yield of rice and wheat in the Indian Ganga Basin.

PubMed

Mishra, Ashok; Singh, R; Raghuwanshi, N S; Chatterjee, C; Froebrich, Jochen

2013-12-01

Indian Ganga Basin (IGB), one of the most densely populated areas in the world, is facing a significant threat to food grain production, besides increased yield gap between actual and potential production, due to climate change. We have analyzed the spatial variability of climate change impacts on rice and wheat yields at three different locations representing the upper, middle and lower IGB. The DSSAT model is used to simulate the effects of climate variability and climate change on rice and wheat yields by analyzing: (i) spatial crop yield response to current climate, and (ii) impact of a changing climate as projected by two regional climate models, REMO and HadRM3, based on SRES A1B emission scenarios for the period 2011-2040. Results for current climate demonstrate a significant gap between actual and potential yield for upper, middle and lower IGB stations. The analysis based on RCM projections shows that during 2011-2040, the largest reduction in rice and wheat yields will occur in the upper IGB (reduction of potential rice and wheat yield respectively by 43.2% and 20.9% by REMO, and 24.8% and 17.2% by HadRM3). In the lower IGB, however, contrasting results are obtained, with HadRM3 based projections showing an increase in the potential rice and wheat yields, whereas, REMO based projections show decreased potential yields. We discuss the influence of agro-climatic factors; variation in temperature, length of maturity period and leaf area index which are responsible for modeled spatial variability in crop yield response within the IGB. Copyright © 2013 Elsevier B.V. All rights reserved.

Forecasting Glacier Evolution and Hindcasting Paleoclimates In Light of Mass Balance Nonlinearities

NASA Astrophysics Data System (ADS)

Malone, A.; Doughty, A. M.; MacAyeal, D. R.

2016-12-01

Glaciers are commonly used barometers of present and past climate change, with their variations often being linked to shifts in the mean climate. Climate variability within a unchanging mean state, however, can produce short term mass balance and glacier length anomalies, complicating this linkage. Also, the mass balance response to this variability can be nonlinear, possibly impacting the longer term state of the glacier. We propose a conceptual model to understand these nonlinearities and quantify their impacts on the longer term mass balance and glacier length. The relationship between mass balance and elevation, i.e. the vertical balance profile (VBP), illuminates these nonlinearities (Figure A). The VBP, given here for a wet tropical glacier, is piecewise, which can lead to different mass balance responses to climate anomalies of similar magnitude but opposite sign. We simulate the mass balance response to climate variability by vertically (temperature anomalies) and horizontally (precipitation anomalies) transposing the VBP for the mean climate (Figure A). The resulting anomalous VBP is the superposition of the two translations. We drive a 1-D flowline model with 10,000 years of anomalous VBPs. The aggregate VBP for the mean climate including variability differs from the VBP for the mean climate excluding variability, having a higher equilibrium line altitude (ELA) and a negative mass balance (Figure B). Accordingly, the glacier retreats, and the equilibrium glacier length for the aggregate VBP is the same as the mean length from the 10,000 year flowline simulation (Figure C). The magnitude of the VBP shift and glacier retreat increases with greater temperature variability and larger discontinuities in the VBP slope. These results highlight the importance of both the climate mean and variability in determining the longer term state of the glacier. Thus, forecasting glacier evolution or hindcasting past climates should also include representation of climate variability.

The influence of climate variables on dengue in Singapore.

PubMed

Pinto, Edna; Coelho, Micheline; Oliver, Leuda; Massad, Eduardo

2011-12-01

In this work we correlated dengue cases with climatic variables for the city of Singapore. This was done through a Poisson Regression Model (PRM) that considers dengue cases as the dependent variable and the climatic variables (rainfall, maximum and minimum temperature and relative humidity) as independent variables. We also used Principal Components Analysis (PCA) to choose the variables that influence in the increase of the number of dengue cases in Singapore, where PC₁ (Principal component 1) is represented by temperature and rainfall and PC₂ (Principal component 2) is represented by relative humidity. We calculated the probability of occurrence of new cases of dengue and the relative risk of occurrence of dengue cases influenced by climatic variable. The months from July to September showed the highest probabilities of the occurrence of new cases of the disease throughout the year. This was based on an analysis of time series of maximum and minimum temperature. An interesting result was that for every 2-10°C of variation of the maximum temperature, there was an average increase of 22.2-184.6% in the number of dengue cases. For the minimum temperature, we observed that for the same variation, there was an average increase of 26.1-230.3% in the number of the dengue cases from April to August. The precipitation and the relative humidity, after analysis of correlation, were discarded in the use of Poisson Regression Model because they did not present good correlation with the dengue cases. Additionally, the relative risk of the occurrence of the cases of the disease under the influence of the variation of temperature was from 1.2-2.8 for maximum temperature and increased from 1.3-3.3 for minimum temperature. Therefore, the variable temperature (maximum and minimum) was the best predictor for the increased number of dengue cases in Singapore.

West African Monsoon dynamics in idealized simulations: the competitive roles of SST warming and CO2

NASA Astrophysics Data System (ADS)

Gaetani, Marco; Flamant, Cyrille; Hourdin, Frederic; Bastin, Sophie; Braconnot, Pascale; Bony, Sandrine

2015-04-01

The West African Monsoon (WAM) is affected by large climate variability at different timescales, from interannual to multidecadal, with strong environmental and socio-economic impacts associated to climate-related rainfall variability, especially in the Sahelian belt. State-of-the-art coupled climate models still show poor ability in correctly simulating the WAM past variability and also a large spread is observed in future climate projections. In this work, the July-to-September (JAS) WAM variability in the period 1979-2008 is studied in AMIP-like simulations (SST-forced) from CMIP5. The individual roles of global SST warming and CO2 concentration increasing are investigated through idealized experiments simulating a 4K warmer SST and a 4x CO2 concentration, respectively. Results show a dry response in Sahel to SST warming, with dryer conditions over western Sahel. On the contrary, wet conditions are observed when CO2 is increased, with the strongest response over central-eastern Sahel. The precipitation changes are associated to modifications in the regional atmospheric circulation: dry (wet) conditions are associated with reduced (increased) convergence in the lower troposphere, a southward (northward) shift of the African Easterly Jet, and a weaker (stronger) Tropical Easterly Jet. The co-variability between global SST and WAM precipitation is also investigated, highlighting a reorganization of the main co-variability modes. Namely, in the 4xCO2 simulation the influence of Tropical Pacific is dominant, while it is reduced in the 4K simulation, which also shows an increased coupling with the eastern Pacific and the Indian Ocean. The above results suggest a competitive action of SST warming and CO2 increasing on the WAM climate variability, with opposite effects on precipitation. The combination of the observed positive and negative response in precipitation, with wet conditions in central-eastern Sahel and dry conditions in western Sahel, is consistent with the future precipitation trends over West Africa resulting from CMIP5 coupled simulations. It is argued that the large spread in CMIP5 future projections may be related to the weight given to SST warming and direct CO2 effect by individual models. The capability of climate models in reproducing the SST-precipitation relationship appears to be crucial in this respect.

Impacts of Climate Trends and Variability on Livestock Production in Brazil

NASA Astrophysics Data System (ADS)

Cohn, A.; Munger, J.; Gibbs, H.

2015-12-01

Cattle systems of Brazil are of major economic and environmental importance. They occupy ¼ of the land surface of the country, account for over 15 billion USD of annual revenue through the sale of beef, leather, and milk, are closely associated with deforestation, and have been projected to substantially grow in the coming decades. Sustainable intensification of production in the sector could help to limit environmental harm from increased production, but productivity growth could be inhibited by climate change. Gauging the potential future impacts of climate change on the Brazilian livestock sector can be aided by examining past evidence of the link between climate and cattle production and productivity. We use statistical techniques to investigate the contribution of climate variability and climate change to variability in cattle system output in Brazil's municipalities over the period 1974 to 2013. We find significant impacts of both temperature and precipitation variability and temperature trends on municipality-level exports and the production of both milk and beef. Pasture productivity, represented by a vegetation index, also varies significantly with climate shocks. In some regions, losses from exposure to climate trends were of comparable magnitude to technology and/or market-driven productivity gains over the study period.

Predicting the unpredictable: potential climate change impacts on vegetation in the Pacific Northwest

Treesearch

Marie Oliver; David W. Peterson; Becky Kerns

2016-01-01

Earth's climate is changing, as evidenced by warming temperatures, increased temperature variability, fluctuating precipitation patterns, and climate-related environmental disturbances. And with considerable uncertainty about the future, Forest Service land managers are now considering climate change adaptation in their planning efforts. They want practical...

The subtle role of climate change on population genetic structure in Canada lynx.

PubMed

Row, Jeffrey R; Wilson, Paul J; Gomez, Celine; Koen, Erin L; Bowman, Jeff; Thornton, Daniel; Murray, Dennis L

2014-07-01

Anthropogenically driven climatic change is expected to reshape global patterns of species distribution and abundance. Given recent links between genetic variation and environmental patterns, climate change may similarly impact genetic population structure, but we lack information on the spatial and mechanistic underpinnings of genetic-climate associations. Here, we show that current genetic variability of Canada lynx (Lynx canadensis) is strongly correlated with a winter climate gradient (i.e. increasing snow depth and winter precipitation from west-to-east) across the Pacific-North American (PNO) to North Atlantic Oscillation (NAO) climatic systems. This relationship was stronger than isolation by distance and not explained by landscape variables or changes in abundance. Thus, these patterns suggest that individuals restricted dispersal across the climate boundary, likely in the absence of changes in habitat quality. We propose habitat imprinting on snow conditions as one possible explanation for this unusual phenomenon. Coupling historical climate data with future projections, we also found increasingly diverging snow conditions between the two climate systems. Based on genetic simulations using projected climate data (2041-2070), we predicted that this divergence could lead to a threefold increase in genetic differentiation, potentially leading to isolated east-west populations of lynx in North America. Our results imply that subtle genetic structure can be governed by current climate and that substantive genetic differentiation and related ecological divergence may arise from changing climate patterns. © 2014 John Wiley & Sons Ltd.

Robust signals of future projections of Indian summer monsoon rainfall by IPCC AR5 climate models: Role of seasonal cycle and interannual variability

NASA Astrophysics Data System (ADS)

Jayasankar, C. B.; Surendran, Sajani; Rajendran, Kavirajan

2015-05-01

Coupled Model Intercomparison Project phase 5 (Fifth Assessment Report of Intergovernmental Panel on Climate Change) coupled global climate model Representative Concentration Pathway 8.5 simulations are analyzed to derive robust signals of projected changes in Indian summer monsoon rainfall (ISMR) and its variability. Models project clear future temperature increase but diverse changes in ISMR with substantial intermodel spread. Objective measures of interannual variability (IAV) yields nearly equal chance for future increase or decrease. This leads to discrepancy in quantifying changes in ISMR and variability. However, based primarily on the physical association between mean changes in ISMR and its IAV, and objective methods such as k-means clustering with Dunn's validity index, mean seasonal cycle, and reliability ensemble averaging, projections fall into distinct groups. Physically consistent groups of models with the highest reliability project future reduction in the frequency of light rainfall but increase in high to extreme rainfall and thereby future increase in ISMR by 0.74 ± 0.36 mm d-1, along with increased future IAV. These robust estimates of future changes are important for useful impact assessments.

The sensitivity of terrestrial carbon storage to historical climate variability and atmospheric CO2 in the United States

USGS Publications Warehouse

Tian, H.; Melillo, J.M.; Kicklighter, D.W.; McGuire, A.D.; Helfrich, J.

1999-01-01

We use the Terrestrial Ecosystem Model (TEM, Version 4.1) and the land cover data set of the international geosphere-biosphere program to investigate how increasing atmospheric CO2 concentration and climate variability during 1900-1994 affect the carbon storage of terrestrial ecosystems in the conterminous USA, and how carbon storage has been affected by land-use change. The estimates of TEM indicate that over the past 95 years a combination of increasing atmospheric CO2 with historical temperature and precipitation variability causes a 4.2% (4.3 Pg C) decrease in total carbon storage of potential vegetation in the conterminous US, with vegetation carbon decreasing by 7.2% (3.2 Pg C) and soil organic carbon decreasing by 1.9% (1.1 Pg C). Several dry periods including the 1930s and 1950s are responsible for the loss of carbon storage. Our factorial experiments indicate that precipitation variability alone decreases total carbon storage by 9.5%. Temperature variability alone does not significantly affect carbon storage. The effect of CO2 fertilization alone increases total carbon storage by 4.4%. The effects of increasing atmospheric CO2 and climate variability are not additive. Interactions among CO2, temperature and precipitation increase total carbon storage by 1.1%. Our study also shows substantial year-to-year variations in net carbon exchange between the atmosphere and terrestrial ecosystems due to climate variability. Since the 1960s, we estimate these terrestrial ecosystems have acted primarily as a sink of atmospheric CO2 as a result of wetter weather and higher atmospheric CO2 concentrations. For the 1980s, we estimate the natural terrestrial ecosystems, excluding cropland and urban areas, of the conterminous US have accumulated 78.2 Tg C yr-1 because of the combined effect of increasing atmospheric CO2 and climate variability. For the conterminous US, we estimate that the conversion of natural ecosystems to cropland and urban areas has caused a 18.2% (17.7 Pg C) reduction in total carbon storage from that estimated for potential vegetation. The carbon sink capacity of natural terrestrial ecosystems in the conterminous US is about 69% of that estimated for potential vegetation.

Impact of climate variability on the transmission risk of malaria in northern Côte d'Ivoire.

PubMed

M'Bra, Richard K; Kone, Brama; Soro, Dramane P; N'krumah, Raymond T A S; Soro, Nagnin; Ndione, Jacques A; Sy, Ibrahima; Ceccato, Pietro; Ebi, Kristie L; Utzinger, Jürg; Schindler, Christian; Cissé, Guéladio

2018-01-01

Since the 1970s, the northern part of Côte d'Ivoire has experienced considerable fluctuation in its meteorology including a general decrease of rainfall and increase of temperature from 1970 to 2000, a slight increase of rainfall since 2000, a severe drought in 2004-2005 and flooding in 2006-2007. Such changing climate patterns might affect the transmission of malaria. The purpose of this study was to analyze climate and environmental parameters associated with malaria transmission in Korhogo, a city in northern Côte d'Ivoire. All data were collected over a 10-year period (2004-2013). Rainfall, temperature and Normalized Difference Vegetation Index (NDVI) were the climate and environmental variables considered. Association between these variables and clinical malaria data was determined, using negative binomial regression models. From 2004 to 2013, there was an increase in the annual average precipitation (1100.3-1376.5 mm) and the average temperature (27.2°C-27.5°C). The NDVI decreased from 0.42 to 0.40. We observed a strong seasonality in these climatic variables, which resembled the seasonality in clinical malaria. An incremental increase of 10 mm of monthly precipitation was, on average, associated with a 1% (95% Confidence interval (CI): 0.7 to 1.2%) and a 1.2% (95% CI: 0.9 to 1.5%) increase in the number of clinical malaria episodes one and two months later respectively. A 1°C increase in average monthly temperature was, on average, associated with a decline of a 3.5% (95% CI: 0.1 to 6.7%) in clinical malaria episodes. A 0.1 unit increase in monthly NDVI was associated with a 7.3% (95% CI: 0.8 to 14.1%) increase in the monthly malaria count. There was a similar increase for the preceding-month lag (6.7% (95% CI: 2.3% to 11.2%)). The study results can be used to establish a malaria early warning system in Korhogo to prepare for outbreaks of malaria, which would increase community resilience no matter the magnitude and pattern of climate change.

Development and application of downscaled hydroclimatic predictor variables for use in climate vulnerability and assessment studies

USGS Publications Warehouse

Thorne, James; Boynton, Ryan; Flint, Lorraine; Flint, Alan; N'goc Le, Thuy

2012-01-01

This paper outlines the production of 270-meter grid-scale maps for 14 climate and derivative hydrologic variables for a region that encompasses the State of California and all the streams that flow into it. The paper describes the Basin Characterization Model (BCM), a map-based, mechanistic model used to process the hydrological variables. Three historic and three future time periods of 30 years (1911–1940, 1941–1970, 1971–2000, 2010–2039, 2040–2069, and 2070–2099) were developed that summarize 180 years of monthly historic and future climate values. These comprise a standardized set of fine-scale climate data that were shared with 14 research groups, including the U.S. National Park Service and several University of California groups as part of this project. We present three analyses done with the outputs from the Basin Characterization Model: trends in hydrologic variables over baseline, the most recent 30-year period; a calibration and validation effort that uses measured discharge values from 139 streamgages and compares those to Basin Characterization Model-derived projections of discharge for the same basins; and an assessment of the trends of specific hydrological variables that links historical trend to projected future change under four future climate projections. Overall, increases in potential evapotranspiration dominate other influences in future hydrologic cycles. Increased potential evapotranspiration drives decreasing runoff even under forecasts with increased precipitation, and drives increased climatic water deficit, which may lead to conversion of dominant vegetation types across large parts of the study region as well as have implications for rain-fed agriculture. The potential evapotranspiration is driven by air temperatures, and the Basin Characterization Model permits it to be integrated with a water balance model that can be derived for landscapes and summarized by watershed. These results show the utility of using a process-based model with modules representing different hydrological pathways that can be inter-linked.

Variable climatic conditions dominate recent phytoplankton dynamics in Chesapeake Bay

NASA Astrophysics Data System (ADS)

Harding, Lawrence W., Jr.; Mallonee, Michael E.; Perry, Elgin S.; Miller, W. David; Adolf, Jason E.; Gallegos, Charles L.; Paerl, Hans W.

2016-03-01

Variable climatic conditions strongly influence phytoplankton dynamics in estuaries globally. Our study area is Chesapeake Bay, a highly productive ecosystem providing natural resources, transportation, and recreation for nearly 16 million people inhabiting a 165,000-km2 watershed. Since World War II, nutrient over-enrichment has led to multiple ecosystem impairments caused by increased phytoplankton biomass as chlorophyll-a (chl-a). Doubled nitrogen (N) loadings from 1945-1980 led to increased chl-a, reduced water clarity, and low dissolved oxygen (DO), while decreased N loadings from 1981-2012 suggest modest improvement. The recent 30+ years are characterized by high inter-annual variability of chl-a, coinciding with irregular dry and wet periods, complicating the detection of long-term trends. Here, we synthesize time-series data for historical and recent N loadings (TN, NO2 + NO3), chl-a, floral composition, and net primary productivity (NPP) to distinguish secular changes caused by nutrient over-enrichment from spatio-temporal variability imposed by climatic conditions. Wet years showed higher chl-a, higher diatom abundance, and increased NPP, while dry years showed lower chl-a, lower diatom abundance, and decreased NPP. Our findings support a conceptual model wherein variable climatic conditions dominate recent phytoplankton dynamics against a backdrop of nutrient over-enrichment, emphasizing the need to separate these effects to gauge progress toward improving water quality in estuaries.

Variable climatic conditions dominate recent phytoplankton dynamics in Chesapeake Bay.

PubMed

Harding, Lawrence W; Mallonee, Michael E; Perry, Elgin S; Miller, W David; Adolf, Jason E; Gallegos, Charles L; Paerl, Hans W

2016-03-30

Variable climatic conditions strongly influence phytoplankton dynamics in estuaries globally. Our study area is Chesapeake Bay, a highly productive ecosystem providing natural resources, transportation, and recreation for nearly 16 million people inhabiting a 165,000-km(2) watershed. Since World War II, nutrient over-enrichment has led to multiple ecosystem impairments caused by increased phytoplankton biomass as chlorophyll-a (chl-a). Doubled nitrogen (N) loadings from 1945-1980 led to increased chl-a, reduced water clarity, and low dissolved oxygen (DO), while decreased N loadings from 1981-2012 suggest modest improvement. The recent 30+ years are characterized by high inter-annual variability of chl-a, coinciding with irregular dry and wet periods, complicating the detection of long-term trends. Here, we synthesize time-series data for historical and recent N loadings (TN, NO2 + NO3), chl-a, floral composition, and net primary productivity (NPP) to distinguish secular changes caused by nutrient over-enrichment from spatio-temporal variability imposed by climatic conditions. Wet years showed higher chl-a, higher diatom abundance, and increased NPP, while dry years showed lower chl-a, lower diatom abundance, and decreased NPP. Our findings support a conceptual model wherein variable climatic conditions dominate recent phytoplankton dynamics against a backdrop of nutrient over-enrichment, emphasizing the need to separate these effects to gauge progress toward improving water quality in estuaries.

Variable climatic conditions dominate recent phytoplankton dynamics in Chesapeake Bay

PubMed Central

Harding, Jr., Lawrence W.; Mallonee, Michael E.; Perry, Elgin S.; Miller, W. David; Adolf, Jason E.; Gallegos, Charles L.; Paerl, Hans W.

2016-01-01

Variable climatic conditions strongly influence phytoplankton dynamics in estuaries globally. Our study area is Chesapeake Bay, a highly productive ecosystem providing natural resources, transportation, and recreation for nearly 16 million people inhabiting a 165,000-km2 watershed. Since World War II, nutrient over-enrichment has led to multiple ecosystem impairments caused by increased phytoplankton biomass as chlorophyll-a (chl-a). Doubled nitrogen (N) loadings from 1945–1980 led to increased chl-a, reduced water clarity, and low dissolved oxygen (DO), while decreased N loadings from 1981–2012 suggest modest improvement. The recent 30+ years are characterized by high inter-annual variability of chl-a, coinciding with irregular dry and wet periods, complicating the detection of long-term trends. Here, we synthesize time-series data for historical and recent N loadings (TN, NO2 + NO3), chl-a, floral composition, and net primary productivity (NPP) to distinguish secular changes caused by nutrient over-enrichment from spatio-temporal variability imposed by climatic conditions. Wet years showed higher chl-a, higher diatom abundance, and increased NPP, while dry years showed lower chl-a, lower diatom abundance, and decreased NPP. Our findings support a conceptual model wherein variable climatic conditions dominate recent phytoplankton dynamics against a backdrop of nutrient over-enrichment, emphasizing the need to separate these effects to gauge progress toward improving water quality in estuaries. PMID:27026279

Adaptation of rainfed agriculture to climatic variability in the Mixteca Alta Region of Oaxaca, Mexico

NASA Astrophysics Data System (ADS)

Rogé, P.; Friedman, A. R.; Astier, M.; Altieri, M.

2015-12-01

The traditional management systems of the Mixteca Alta Region of Oaxaca, Mexico offer historical lessons about resilience to climatic variability. We interviewed small farmers to inquire about the dynamics of abandonment and persistence of a traditional management systems. We interpret farmers' narratives from a perspective of general agroecological resilience. In addition, we facilitated workshops in small farmers described their adaptation to past climate challenges and identified 14 indicators that they subsequently used to evaluate the condition of their agroecosystems. The most recent years presented increasingly extreme climatic and socioeconomic hardships: increased temperatures, delayed rainy seasons, reduced capacity of soils to retain soil moisture, changing cultural norms, and reduced rural labor. Farmers reported that their cropping systems were changing for multiple reasons: more drought, later rainfall onset, decreased rural labor, and introduced labor-saving technologies. Examination of climate data found that farmers' climate narratives were largely consistent with the observational record. There have been increases in temperature and rainfall intensity, and an increase in rainfall seasonality that may be perceived as later rainfall onset. Farmers ranked landscape-scale indicators as more marginal than farmer management or soil quality indicators. From this analysis, farmers proposed strategies to improve the ability of their agroecosystems to cope with climatic variability. Notably, they recognized that social organizing and education are required for landscape-level indicators to be improved. Transformative change is required to develop novel cropping systems and complementary activities to agriculture that will allow for farming to be sustained in the face of these challenges. Climate change adaptation by small farmers involves much more than just a set of farming practices, but also community action to tackle collective problems.

Ground Water and Climate Change

NASA Technical Reports Server (NTRS)

Taylor, Richard G.; Scanlon, Bridget; Doell, Petra; Rodell, Matt; van Beek, Rens; Wada, Yoshihide; Longuevergne, Laurent; Leblanc, Marc; Famiglietti, James S.; Edmunds, Mike;

Ground water and climate change

USGS Publications Warehouse

Taylor, Richard G.; Scanlon, Bridget R.; Döll, Petra; Rodell, Matt; van Beek, Rens; Wada, Yoshihide; Longuevergne, Laurent; Leblanc, Marc; Famiglietti, James S.; Edmunds, Mike; Konikow, Leonard F.; Green, Timothy R.; Chen, Jianyao; Taniguchi, Makoto; Bierkens, Marc F.P.; MacDonald, Alan; Fan, Ying; Maxwell, Reed M.; Yechieli, Yossi; Gurdak, Jason J.; Allen, Diana M.; Shamsudduha, Mohammad; Hiscock, Kevin; Yeh, Pat J.-F.; Holman, Ian; Treidel, Holger

2012-01-01

As the world's largest distributed store of fresh water, ground water plays a central part in sustaining ecosystems and enabling human adaptation to climate variability and change. The strategic importance of ground water for global water and food security will probably intensify under climate change as more frequent and intense climate extremes (droughts and floods) increase variability in precipitation, soil moisture and surface water. Here we critically review recent research assessing the impacts of climate on ground water through natural and human-induced processes as well as through groundwater-driven feedbacks on the climate system. Furthermore, we examine the possible opportunities and challenges of using and sustaining groundwater resources in climate adaptation strategies, and highlight the lack of groundwater observations, which, at present, limits our understanding of the dynamic relationship between ground water and climate.

Combining landscape variables and species traits can improve the utility of climate change vulnerability assessments

USGS Publications Warehouse

Nadeau, Christopher P.; Fuller, Angela K.

2016-01-01

Conservation organizations worldwide are investing in climate change vulnerability assessments. Most vulnerability assessment methods focus on either landscape features or species traits that can affect a species vulnerability to climate change. However, landscape features and species traits likely interact to affect vulnerability. We compare a landscape-based assessment, a trait-based assessment, and an assessment that combines landscape variables and species traits for 113 species of birds, herpetofauna, and mammals in the northeastern United States. Our aim is to better understand which species traits and landscape variables have the largest influence on assessment results and which types of vulnerability assessments are most useful for different objectives. Species traits were most important for determining which species will be most vulnerable to climate change. The sensitivity of species to dispersal barriers and the species average natal dispersal distance were the most important traits. Landscape features were most important for determining where species will be most vulnerable because species were most vulnerable in areas where multiple landscape features combined to increase vulnerability, regardless of species traits. The interaction between landscape variables and species traits was important when determining how to reduce climate change vulnerability. For example, an assessment that combines information on landscape connectivity, climate change velocity, and natal dispersal distance suggests that increasing landscape connectivity may not reduce the vulnerability of many species. Assessments that include landscape features and species traits will likely be most useful in guiding conservation under climate change.

Topography alters tree growth–climate relationships in a semi-arid forested catchment

DOE PAGES

Adams, Hallie R.; Barnard, Holly R.; Loomis, Alexander K.

2014-11-26

Topography and climate play an integral role in the spatial variability and annual dynamics of aboveground carbon sequestration. Despite knowledge of vegetation–climate–topography relationships on the landscape and hillslope scales, little is known about the influence of complex terrain coupled with hydrologic and topoclimatic variation on tree growth and physiology at the catchment scale. Climate change predictions for the semi-arid, western United States include increased temperatures, more frequent and extreme drought events, and decreases in snowpack, all of which put forests at risk of drought induced mortality and enhanced susceptibility to disturbance events. In this study, we determine how species-specific treemore » growth patterns and water use efficiency respond to interannual climate variability and how this response varies with topographic position. We found that Pinus contorta and Pinus ponderosa both show significant decreases in growth with water-limiting climate conditions, but complex terrain mediates this response by controlling moisture conditions in variable topoclimates. Foliar carbon isotope analyses show increased water use efficiency during drought for Pinus contorta, but indicate no significant difference in water use efficiency of Pinus ponderosa between a drought year and a non-drought year. The responses of the two pine species to climate indicate that semi-arid forests are especially susceptible to changes and risks posed by climate change and that topographic variability will likely play a significant role in determining the future vegetation patterns of semi-arid systems.« less

Relationship of suicide rates with climate and economic variables in Europe during 2000-2012.

PubMed

Fountoulakis, Konstantinos N; Chatzikosta, Isaia; Pastiadis, Konstantinos; Zanis, Prodromos; Kawohl, Wolfram; Kerkhof, Ad J F M; Navickas, Alvydas; Höschl, Cyril; Lecic-Tosevski, Dusica; Sorel, Eliot; Rancans, Elmars; Palova, Eva; Juckel, Georg; Isacsson, Goran; Jagodic, Helena Korosec; Botezat-Antonescu, Ileana; Rybakowski, Janusz; Azorin, Jean Michel; Cookson, John; Waddington, John; Pregelj, Peter; Demyttenaere, Koen; Hranov, Luchezar G; Stevovic, Lidija Injac; Pezawas, Lucas; Adida, Marc; Figuera, Maria Luisa; Jakovljević, Miro; Vichi, Monica; Perugi, Giulio; Andreassen, Ole A; Vukovic, Olivera; Mavrogiorgou, Paraskevi; Varnik, Peeter; Dome, Peter; Winkler, Petr; Salokangas, Raimo K R; From, Tiina; Danileviciute, Vita; Gonda, Xenia; Rihmer, Zoltan; Forsman, Jonas; Grady, Anne; Hyphantis, Thomas; Dieset, Ingrid; Soendergaard, Susan; Pompili, Maurizio; Bech, Per

2016-01-01

It is well known that suicidal rates vary considerably among European countries and the reasons for this are unknown, although several theories have been proposed. The effect of economic variables has been extensively studied but not that of climate. Data from 29 European countries covering the years 2000-2012 and concerning male and female standardized suicidal rates (according to WHO), economic variables (according World Bank) and climate variables were gathered. The statistical analysis included cluster and principal component analysis and categorical regression. The derived models explained 62.4 % of the variability of male suicidal rates. Economic variables alone explained 26.9 % and climate variables 37.6 %. For females, the respective figures were 41.7, 11.5 and 28.1 %. Male suicides correlated with high unemployment rate in the frame of high growth rate and high inflation and low GDP per capita, while female suicides correlated negatively with inflation. Both male and female suicides correlated with low temperature. The current study reports that the climatic effect (cold climate) is stronger than the economic one, but both are present. It seems that in Europe suicidality follows the climate/temperature cline which interestingly is not from south to north but from south to north-east. This raises concerns that climate change could lead to an increase in suicide rates. The current study is essentially the first successful attempt to explain the differences across countries in Europe; however, it is an observational analysis based on aggregate data and thus there is a lack of control for confounders.

Using MERRA, AMIP II, CMIP5 Outputs to Assess Actual and Potential Building Climate Zone Change and Variability From the Last 30 Years Through 2100

NASA Astrophysics Data System (ADS)

Stackhouse, P. W.; Westberg, D. J.; Hoell, J. M., Jr.; Chandler, W.; Zhang, T.

2014-12-01

In the US, residential and commercial building infrastructure combined consumes about 40% of total energy usage and emits about 39% of total CO2emission (DOE/EIA "Annual Energy Outlook 2013"). Thus, increasing the energy efficiency of buildings is paramount to reducing energy costs and emissions. Building codes, as used by local and state enforcement entities are typically tied to the dominant climate within an enforcement jurisdiction classified according to various climate zones. These climates zones are based upon a 30-year average of local surface observations and are developed by DOE and ASHRAE (formerly known as the American Society of Hearting, Refrigeration and Air-Conditioning Engineers). A significant shortcoming of the methodology used in constructing such maps is the use of surface observations (located mainly near airports) that are unequally distributed and frequently have periods of missing data that need to be filled by various approximation schemes. This paper demonstrates the usefulness of using NASA's Modern Era Retrospective-analysis for Research and Applications (MERRA) atmospheric data assimilation to derive the ASHRAE climate zone maps and then using MERRA to define the last 30 years of variability in climate zones. These results show that there is a statistically significant increase in the area covered by warmer climate zones and some tendency for a reduction of area in colder climate zones that require longer time series to confirm. Using the uncertainties of the basic surface temperature and precipitation parameters from MERRA as determined by comparison to surface measurements, we first compare patterns and variability of ASHRAE climate zones from MERRA relative to present day climate model runs from AMIP simulations to establish baseline sensitivity. Based upon these results, we assess the variability of the ASHRAE climate zones according to CMIP runs through 2100 using an ensemble analysis that classifies model output changes by percentiles. Estimates of statistical significance are then compared to original model variability during the AMIP period. This work quantifies and tests for significance the changes seen in the various US regions that represent a potential contribution by NASA to the ongoing National Climate Assessment.

Climate and Vegetation Effects on Temperate Mountain Forest Evapotranspiration

EPA Science Inventory

Current forest composition may be resilient to typical climatic variability; however, climate trends, combined with projected changes in species composition, may increase tree vulnerability to water stress. A shift in forest composition toward tree species with higher water use h...

Evaluating historical climate and hydrologic trends in the Central Appalachian region of the United States

NASA Astrophysics Data System (ADS)

Gaertner, B. A.; Zegre, N.

2015-12-01

Climate change is surfacing as one of the most important environmental and social issues of the 21st century. Over the last 100 years, observations show increasing trends in global temperatures and intensity and frequency of precipitation events such as flooding, drought, and extreme storms. Global circulation models (GCM) show similar trends for historic and future climate indicators, albeit with geographic and topographic variability at regional and local scale. In order to assess the utility of GCM projections for hydrologic modeling, it is important to quantify how robust GCM outputs are compared to robust historical observations at finer spatial scales. Previous research in the United States has primarily focused on the Western and Northeastern regions due to dominance of snow melt for runoff and aquifer recharge but the impact of climate warming in the mountainous central Appalachian Region is poorly understood. In this research, we assess the performance of GCM-generated historical climate compared to historical observations primarily in the context of forcing data for macro-scale hydrologic modeling. Our results show significant spatial heterogeneity of modeled climate indices when compared to observational trends at the watershed scale. Observational data is showing considerable variability within maximum temperature and precipitation trends, with consistent increases in minimum temperature. The geographic, temperature, and complex topographic gradient throughout the central Appalachian region is likely the contributing factor in temperature and precipitation variability. Variable climate changes are leading to more severe and frequent climate events such as temperature extremes and storm events, which can have significant impacts on our drinking water supply, infrastructure, and health of all downstream communities.

Climate variability drives recent tree mortality in Europe.

PubMed

Neumann, Mathias; Mues, Volker; Moreno, Adam; Hasenauer, Hubert; Seidl, Rupert

2017-11-01

Tree mortality is an important process in forest ecosystems, frequently hypothesized to be highly climate sensitive. Yet, tree death remains one of the least understood processes of forest dynamics. Recently, changes in tree mortality have been observed in forests around the globe, which could profoundly affect ecosystem functioning and services provisioning to society. We describe continental-scale patterns of recent tree mortality from the only consistent pan-European forest monitoring network, identifying recent mortality hotspots in southern and northern Europe. Analyzing 925,462 annual observations of 235,895 trees between 2000 and 2012, we determine the influence of climate variability and tree age on interannual variation in tree mortality using Cox proportional hazard models. Warm summers as well as high seasonal variability in precipitation increased the likelihood of tree death. However, our data also suggest that reduced cold-induced mortality could compensate increased mortality related to peak temperatures in a warming climate. Besides climate variability, age was an important driver of tree mortality, with individual mortality probability decreasing with age over the first century of a trees life. A considerable portion of the observed variation in tree mortality could be explained by satellite-derived net primary productivity, suggesting that widely available remote sensing products can be used as an early warning indicator of widespread tree mortality. Our findings advance the understanding of patterns of large-scale tree mortality by demonstrating the influence of seasonal and diurnal climate variation, and highlight the potential of state-of-the-art remote sensing to anticipate an increased likelihood of tree mortality in space and time. © 2017 John Wiley & Sons Ltd.

The relative impacts of climate and land-use change on conterminous United States bird species from 2001 to 2075

USGS Publications Warehouse

Sohl, Terry L.

2014-01-01

Species distribution models often use climate data to assess contemporary and/or future ranges for animal or plant species. Land use and land cover (LULC) data are important predictor variables for determining species range, yet are rarely used when modeling future distributions. In this study, maximum entropy modeling was used to construct species distribution maps for 50 North American bird species to determine relative contributions of climate and LULC for contemporary (2001) and future (2075) time periods. Species presence data were used as a dependent variable, while climate, LULC, and topographic data were used as predictor variables. Results varied by species, but in general, measures of model fit for 2001 indicated significantly poorer fit when either climate or LULC data were excluded from model simulations. Climate covariates provided a higher contribution to 2001 model results than did LULC variables, although both categories of variables strongly contributed. The area deemed to be "suitable" for 2001 species presence was strongly affected by the choice of model covariates, with significantly larger ranges predicted when LULC was excluded as a covariate. Changes in species ranges for 2075 indicate much larger overall range changes due to projected climate change than due to projected LULC change. However, the choice of study area impacted results for both current and projected model applications, with truncation of actual species ranges resulting in lower model fit scores and increased difficulty in interpreting covariate impacts on species range. Results indicate species-specific response to climate and LULC variables; however, both climate and LULC variables clearly are important for modeling both contemporary and potential future species ranges.

The Relative Impacts of Climate and Land-Use Change on Conterminous United States Bird Species from 2001 to 2075

PubMed Central

Sohl, Terry L.

2014-01-01

Species distribution models often use climate data to assess contemporary and/or future ranges for animal or plant species. Land use and land cover (LULC) data are important predictor variables for determining species range, yet are rarely used when modeling future distributions. In this study, maximum entropy modeling was used to construct species distribution maps for 50 North American bird species to determine relative contributions of climate and LULC for contemporary (2001) and future (2075) time periods. Species presence data were used as a dependent variable, while climate, LULC, and topographic data were used as predictor variables. Results varied by species, but in general, measures of model fit for 2001 indicated significantly poorer fit when either climate or LULC data were excluded from model simulations. Climate covariates provided a higher contribution to 2001 model results than did LULC variables, although both categories of variables strongly contributed. The area deemed to be “suitable” for 2001 species presence was strongly affected by the choice of model covariates, with significantly larger ranges predicted when LULC was excluded as a covariate. Changes in species ranges for 2075 indicate much larger overall range changes due to projected climate change than due to projected LULC change. However, the choice of study area impacted results for both current and projected model applications, with truncation of actual species ranges resulting in lower model fit scores and increased difficulty in interpreting covariate impacts on species range. Results indicate species-specific response to climate and LULC variables; however, both climate and LULC variables clearly are important for modeling both contemporary and potential future species ranges. PMID:25372571

Precipitation variability on global pasturelands may affect food security in livestock-dependent regions

NASA Astrophysics Data System (ADS)

Sloat, L.; Gerber, J. S.; Samberg, L. H.; Smith, W. K.; West, P. C.; Herrero, M.; Brendan, P.; Cecile, G.; Katharina, W.; Smith, W. K.

2016-12-01

The need to feed an increasing number of people while maintaining biodiversity and ecosystem services is one of the key challenges currently facing humanity. Livestock systems are likely to be a crucial piece of this puzzle, as urbanization and changing diets in much of the world lead to increases in global meat consumption. This predicted increase in global demand for livestock products will challenge the ability of pastures and rangelands to maintain or increase their productivity. The majority of people that depend on animal production for food security do so through grazing and herding on natural rangelands, and these systems make a significant contribution to global production of meat and milk. The vegetation dynamics of natural forage are highly dependent on climate, and subject to disruption with changes in climate and climate variability. Precipitation heterogeneity has been linked to the ecosystem dynamics of grazing lands through impacts on livestock carrying capacity and grassland degradation potential. Additionally, changes in precipitation variability are linked to the increased incidence of extreme events (e.g. droughts, floods) that negatively impact food production and food security. Here, we use the inter-annual coefficient of variation (CV) of precipitation as a metric to assess climate risk on global pastures. Comparisons of global satellite measures of vegetation greenness to climate reveal that the CV of precipitation is negatively related to mean annual NDVI, such that areas with low year-to-year precipitation variability have the highest measures of vegetation greenness, and vice versa. Furthermore, areas with high CV of precipitation support lower livestock densities and produce less meat. A sliding window analysis of changes in CV of precipitation over the last century shows that, overall, precipitation variability is increasing in global pasture areas, although global maps reveal a patchwork of both positive and negative changes. We use this information to identify regions in which changes in the variability of precipitation may already be affecting the ability of grazing systems to support intensified livestock production, and assess the potential impacts of those changes on pasture productivity.

Sensitivity of ring growth and carbon allocation to climatic variation vary within ponderosa pine trees.

PubMed

Kerhoulas, Lucy P; Kane, Jeffrey M

2012-01-01

Most dendrochronological studies focus on cores sampled from standard positions (main stem, breast height), yet vertical gradients in hydraulic constraints and priorities for carbon allocation may contribute to different growth sensitivities with position. Using cores taken from five positions (coarse roots, breast height, base of live crown, mid-crown branch and treetop), we investigated how radial growth sensitivity to climate over the period of 1895-2008 varies by position within 36 large ponderosa pines (Pinus ponderosa Dougl.) in northern Arizona. The climate parameters investigated were Palmer Drought Severity Index, water year and monsoon precipitation, maximum annual temperature, minimum annual temperature and average annual temperature. For each study tree, we generated Pearson correlation coefficients between ring width indices from each position and six climate parameters. We also investigated whether the number of missing rings differed among positions and bole heights. We found that tree density did not significantly influence climatic sensitivity to any of the climate parameters investigated at any of the sample positions. Results from three types of analyses suggest that climatic sensitivity of tree growth varied with position height: (i) correlations of radial growth and climate variables consistently increased with height; (ii) model strength based on Akaike's information criterion increased with height, where treetop growth consistently had the highest sensitivity and coarse roots the lowest sensitivity to each climatic parameter; and (iii) the correlation between bole ring width indices decreased with distance between positions. We speculate that increased sensitivity to climate at higher positions is related to hydraulic limitation because higher positions experience greater xylem tensions due to gravitational effects that render these positions more sensitive to climatic stresses. The low sensitivity of root growth to all climatic variables measured suggests that tree carbon allocation to coarse roots is independent of annual climate variability. The greater number of missing rings in branches highlights the fact that canopy development is a low priority for carbon allocation during poor growing conditions.

Future projection of Indian summer monsoon variability under climate change scenario: An assessment from CMIP5 climate models

NASA Astrophysics Data System (ADS)

Sharmila, S.; Joseph, S.; Sahai, A. K.; Abhilash, S.; Chattopadhyay, R.

2015-01-01

In this study, the impact of enhanced anthropogenic greenhouse gas emissions on the possible future changes in different aspects of daily-to-interannual variability of Indian summer monsoon (ISM) is systematically assessed using 20 coupled models participated in the Coupled Model Inter-comparison Project Phase 5. The historical (1951-1999) and future (2051-2099) simulations under the strongest Representative Concentration Pathway have been analyzed for this purpose. A few reliable models are selected based on their competence in simulating the basic features of present-climate ISM variability. The robust and consistent projections across the selected models suggest substantial changes in the ISM variability by the end of 21st century indicating strong sensitivity of ISM to global warming. On the seasonal scale, the all-India summer monsoon mean rainfall is likely to increase moderately in future, primarily governed by enhanced thermodynamic conditions due to atmospheric warming, but slightly offset by weakened large scale monsoon circulation. It is projected that the rainfall magnitude will increase over core monsoon zone in future climate, along with lengthening of the season due to late withdrawal. On interannual timescales, it is speculated that severity and frequency of both strong monsoon (SM) and weak monsoon (WM) might increase noticeably in future climate. Substantial changes in the daily variability of ISM are also projected, which are largely associated with the increase in heavy rainfall events and decrease in both low rain-rate and number of wet days during future monsoon. On the subseasonal scale, the model projections depict considerable amplification of higher frequency (below 30 day mode) components; although the dominant northward propagating 30-70 day mode of monsoon intraseasonal oscillations may not change appreciably in a warmer climate. It is speculated that the enhanced high frequency mode of monsoon ISOs due to increased GHG induced warming may notably modulate the ISM rainfall in future climate. Both extreme wet and dry episodes are likely to intensify and regionally extend in future climate with enhanced propensity of short active and long break spells. The SM (WM) could also be more wet (dry) in future due to the increment in longer active (break) spells. However, future changes in the spatial pattern during active/break phase of SM and WM are geographically inconsistent among the models. The results point out the growing climate-related vulnerability over Indian subcontinent, and further suggest the requisite of profound adaptation measures and better policy making in future.

Exploring consensus in 21st century projections of climatically suitable areas for African vertebrates

PubMed Central

Garcia, Raquel A; Burgess, Neil D; Cabeza, Mar; Rahbek, Carsten; Araújo, Miguel B

2012-01-01

Africa is predicted to be highly vulnerable to 21st century climatic changes. Assessing the impacts of these changes on Africa's biodiversity is, however, plagued by uncertainties, and markedly different results can be obtained from alternative bioclimatic envelope models or future climate projections. Using an ensemble forecasting framework, we examine projections of future shifts in climatic suitability, and their methodological uncertainties, for over 2500 species of mammals, birds, amphibians and snakes in sub-Saharan Africa. To summarize a priori the variability in the ensemble of 17 general circulation models, we introduce a consensus methodology that combines co-varying models. Thus, we quantify and map the relative contribution to uncertainty of seven bioclimatic envelope models, three multi-model climate projections and three emissions scenarios, and explore the resulting variability in species turnover estimates. We show that bioclimatic envelope models contribute most to variability, particularly in projected novel climatic conditions over Sahelian and southern Saharan Africa. To summarize agreements among projections from the bioclimatic envelope models we compare five consensus methodologies, which generally increase or retain projection accuracy and provide consistent estimates of species turnover. Variability from emissions scenarios increases towards late-century and affects southern regions of high species turnover centred in arid Namibia. Twofold differences in median species turnover across the study area emerge among alternative climate projections and emissions scenarios. Our ensemble of projections underscores the potential bias when using a single algorithm or climate projection for Africa, and provides a cautious first approximation of the potential exposure of sub-Saharan African vertebrates to climatic changes. The future use and further development of bioclimatic envelope modelling will hinge on the interpretation of results in the light of methodological as well as biological uncertainties. Here, we provide a framework to address methodological uncertainties and contextualize results.

Vulnerability of Breeding Waterbirds to Climate Change in the Prairie Pothole Region, U.S.A

PubMed Central

Steen, Valerie; Skagen, Susan K.; Noon, Barry R.

2014-01-01

The Prairie Pothole Region (PPR) of the north-central U.S. and south-central Canada contains millions of small prairie wetlands that provide critical habitat to many migrating and breeding waterbirds. Due to their small size and the relatively dry climate of the region, these wetlands are considered at high risk for negative climate change effects as temperatures increase. To estimate the potential impacts of climate change on breeding waterbirds, we predicted current and future distributions of species common in the PPR using species distribution models (SDMs). We created regional-scale SDMs for the U.S. PPR using Breeding Bird Survey occurrence records for 1971–2011 and wetland, upland, and climate variables. For each species, we predicted current distribution based on climate records for 1981–2000 and projected future distributions to climate scenarios for 2040–2049. Species were projected to, on average, lose almost half their current habitat (-46%). However, individual species projections varied widely, from +8% (Upland Sandpiper) to -100% (Wilson's Snipe). Variable importance ranks indicated that land cover (wetland and upland) variables were generally more important than climate variables in predicting species distributions. However, climate variables were relatively more important during a drought period. Projected distributions of species responses to climate change contracted within current areas of distribution rather than shifting. Given the large variation in species-level impacts, we suggest that climate change mitigation efforts focus on species projected to be the most vulnerable by enacting targeted wetland management, easement acquisition, and restoration efforts. PMID:24927165

Vulnerability of breeding waterbirds to climate change in the Prairie Pothole Region, U.S.A.

USGS Publications Warehouse

Steen, Valerie; Skagen, Susan K.; Noon, Barry R.

2014-01-01

The Prairie Pothole Region (PPR) of the north-central U.S. and south-central Canada contains millions of small prairie wetlands that provide critical habitat to many migrating and breeding waterbirds. Due to their small size and the relatively dry climate of the region, these wetlands are considered at high risk for negative climate change effects as temperatures increase. To estimate the potential impacts of climate change on breeding waterbirds, we predicted current and future distributions of species common in the PPR using species distribution models (SDMs). We created regional-scale SDMs for the U.S. PPR using Breeding Bird Survey occurrence records for 1971–2011 and wetland, upland, and climate variables. For each species, we predicted current distribution based on climate records for 1981–2000 and projected future distributions to climate scenarios for 2040–2049. Species were projected to, on average, lose almost half their current habitat (-46%). However, individual species projections varied widely, from +8% (Upland Sandpiper) to -100% (Wilson's Snipe). Variable importance ranks indicated that land cover (wetland and upland) variables were generally more important than climate variables in predicting species distributions. However, climate variables were relatively more important during a drought period. Projected distributions of species responses to climate change contracted within current areas of distribution rather than shifting. Given the large variation in species-level impacts, we suggest that climate change mitigation efforts focus on species projected to be the most vulnerable by enacting targeted wetland management, easement acquisition, and restoration efforts.

The Women's Role in the Adaptation to Climate Variability and Climate Change: Its Contribution to the Risk Management

NASA Astrophysics Data System (ADS)

Quintero Angel, M.; Carvajal Escobar, Y.; Garcia Vargas, M.

2007-05-01

Recently, there is evidence of an increase in the amount of severity in extreme events associated with the climate variability or climate change; which demonstrates that climate in this planet is changing. There is an observation of increasing damages, and of social economical cost associated with these phenomena's, mostly do to more people are living in hazard vulnerable conditions. The victims of natural disasters have increase from 147 to 211 million between 1991 and 2000. In same way more than 665.000 people have died in 2557 natural disasters, which 90% are associated with water and climate. (UNESCO & WWAP, 2003). The actual tendency and the introduction of new factors of risk, suggest lost increase in the future, obligating actions to manage and reduce risk of disaster. Bind work, health, poverty, education, water, climate, and disasters is not an error, is an obligation. Vulnerability of society to natural hazards and to poverty are bond, to reduce the risk of disasters is frequently united with the reduction of poverty and in the other way too (Sen, 2000). In this context, extreme events impact societies in all the world, affecting differently men and women, do to the different roles they play in the society, the different access in the control of resources, the few participation that women have in taking decisions with preparedness, mitigation, rehabilitation of disasters, impacting more women in developing countries. Although, women understand better the causes and local consequences in changes of climate conditions. They have a pile of knowledge and abilities for guiding adaptation, playing a very important role in vulnerable communities. This work shows how these topics connect with the millennium development goals; particularly how it affects its accomplishment. It also describes the impact of climate variability and climate change in developing countries. Analyzing adaptation responses that are emerging; especially from women initiation.

Climate change and the impact of increased rainfall variability on sediment transport and catchment scale water quality

NASA Astrophysics Data System (ADS)

Hancock, G. R.; Willgoose, G. R.; Cohen, S.

2009-12-01

Recently there has been recognition that changing climate will affect rainfall and storm patterns with research directed to examine how the global hydrological cycle will respond to climate change. This study investigates the effect of different rainfall patterns on erosion and resultant water quality for a well studied tropical monsoonal catchment that is undisturbed by Europeans in the Northern Territory, Australia. Water quality has a large affect on a range of aquatic flora and fauna and a significant change in sediment could have impacts on the aquatic ecosystems. There have been several studies of the effect of climate change on rainfall patterns in the study area with projections indicating a significant increase in storm activity. Therefore it is important that the impact of this variability be assessed in terms of catchment hydrology, sediment transport and water quality. Here a numerical model of erosion and hydrology (CAESAR) is used to assess several different rainfall scenarios over a 1000 year modelled period. The results show that that increased rainfall amount and intensity increases sediment transport rates but predicted water quality was variable and non-linear but within the range of measured field data for the catchment and region. Therefore an assessment of sediment transport and water quality is a significant and complex issue that requires further understandings of the role of biophysical feedbacks such as vegetation as well as the role of humans in managing landscapes (i.e. controlled and uncontrolled fire). The study provides a robust methodology for assessing the impact of enhanced climate variability on sediment transport and water quality.

Variability in soybean yield in Brazil stemming from the interaction of heterogeneous management and climate variability

NASA Astrophysics Data System (ADS)

Cohn, A.; Bragança, A.; Jeffries, G. R.

2017-12-01

An increasing share of global agricultural production can be found in the humid tropics. Therefore, an improved understanding of the mechanisms governing variability in the output of tropical agricultural systems is of increasing importance for food security including through climate change adaptation. Yet, the long window over which many tropical crops can be sown, the diversity of crop varieties and management practices combine to challenge inference into climate risk to cropping output in analyses of tropical crop-climate sensitivity employing administrative data. In this paper, we leverage a newly developed spatially explicit dataset of soybean yields in Brazil to combat this problem. The dataset was built by training a model of remotely-sensed vegetation index data and land cover classification data using a rich in situ dataset of soybean yield and management variables collected over the period 2006 to 2016. The dataset contains soybean yields by plant date, cropping frequency, and maturity group for each 5km grid cell in Brazil. We model variation in these yields using an approach enabling the estimation of the influence of management factors on the sensitivity of soybean yields to variability in: cumulative solar radiation, extreme degree days, growing degree days, flooding rain in the harvest period, and dry spells in the rainy season. We find strong variation in climate sensitivity by management class. Planting date and maturity group each explained a great deal more variation in yield sensitivity than did cropping frequency. Brazil collects comparatively fine spatial resolution yield data. But, our attempt to replicate our results using administrative soy yield data revealed substantially lesser crop-climate sensitivity; suggesting that previous analyses employing administrative data may have underestimated climate risk to tropical soy production.

Uncertainty in Arctic climate projections traced to variability of downwelling longwave radiation

NASA Astrophysics Data System (ADS)

Krikken, Folmer; Bintanja, Richard; Hazeleger, WIlco; van Heerwaarden, Chiel

2017-04-01

The Arctic region has warmed rapidly over the last decades, and this warming is projected to increase. The uncertainty in these projections, i.e. intermodel spread, is however very large and a clear understanding of the sources behind the spread is so far still lacking. Here we use 31 state-of-the-art global climate models to show that variability of May downwelling radiation (DLR) in the models' control climate, primarily located at the land surrounding the Arctic ocean, explains 2/3 of the intermodel spread in projected Arctic warming under the RPC85 scenario. This variability is related to the combined radiative effect of the cloud radiative forcing (CRF) and the albedo response due to snowfall, which varies strongly between the models in these regions. This mechanism dampens or enhances yearly variability of DLR in the control climate but also dampens or enhances the climate response of DLR, sea ice cover and near surface temperature.

Comparison of winter wheat yield sensitivity to climate variables under irrigated and rain-fed conditions

NASA Astrophysics Data System (ADS)

Xiao, Dengpan; Shen, Yanjun; Zhang, He; Moiwo, Juana P.; Qi, Yongqing; Wang, Rende; Pei, Hongwei; Zhang, Yucui; Shen, Huitao

2016-09-01

Crop simulation models provide alternative, less time-consuming, and cost-effective means of determining the sensitivity of crop yield to climate change. In this study, two dynamic mechanistic models, CERES (Crop Environment Resource Synthesis) and APSIM (Agricultural Production Systems Simulator), were used to simulate the yield of wheat ( Triticum aestivum L.) under well irrigated (CFG) and rain-fed (YY) conditions in relation to different climate variables in the North China Plain (NCP). The study tested winter wheat yield sensitivity to different levels of temperature, radiation, precipitation, and atmospheric carbon dioxide (CO2) concentration under CFG and YY conditions at Luancheng Agro-ecosystem Experimental Stations in the NCP. The results from the CERES and APSIM wheat crop models were largely consistent and suggested that changes in climate variables influenced wheat grain yield in the NCP. There was also significant variation in the sensitivity of winter wheat yield to climate variables under different water (CFG and YY) conditions. While a temperature increase of 2°C was the threshold beyond which temperature negatively influenced wheat yield under CFG, a temperature rise exceeding 1°C decreased winter wheat grain yield under YY. A decrease in solar radiation decreased wheat grain yield under both CFG and YY conditions. Although the sensitivity of winter wheat yield to precipitation was small under the CFG, yield decreased significantly with decreasing precipitation under the rainfed YY treatment. The results also suggest that wheat yield under CFG linearly increased by ≈3.5% per 60 ppm (parts per million) increase in CO2 concentration from 380 to 560 ppm, and yield under YY increased linearly by ≈7.0% for the same increase in CO2 concentration.

Net primary productivity of subalpine meadows in Yosemite National Park in relation to climate variability

Treesearch

Peggy E. Moore; Jan W. van Wagtendonk; Julie L. Yee; Mitchel P. McClaran; David N. Cole; Neil K. McDougald; Matthew L. Brooks

2013-01-01

Subalpine meadows are some of the most ecologically important components of mountain landscapes, and primary productivity is important to the maintenance of meadow functions. Understanding how changes in primary productivity are associated with variability in moisture and temperature will become increasingly important with current and anticipated changes in climate....

Climate change enhances interannual variability of the Nile river flow

NASA Astrophysics Data System (ADS)

Siam, Mohamed S.; Eltahir, Elfatih A. B.

2017-04-01

The human population living in the Nile basin countries is projected to double by 2050, approaching one billion. The increase in water demand associated with this burgeoning population will put significant stress on the available water resources. Potential changes in the flow of the Nile River as a result of climate change may further strain this critical situation. Here, we present empirical evidence from observations and consistent projections from climate model simulations suggesting that the standard deviation describing interannual variability of total Nile flow could increase by 50% (+/-35%) (multi-model ensemble mean +/- 1 standard deviation) in the twenty-first century compared to the twentieth century. We attribute the relatively large change in interannual variability of the Nile flow to projected increases in future occurrences of El Niño and La Niña events and to observed teleconnection between the El Niño-Southern Oscillation and Nile River flow. Adequacy of current water storage capacity and plans for additional storage capacity in the basin will need to be re-evaluated given the projected enhancement of interannual variability in the future flow of the Nile river.

Natural Variability and Anthropogenic Trends in the Ocean Carbon Sink

NASA Astrophysics Data System (ADS)

McKinley, Galen A.; Fay, Amanda R.; Lovenduski, Nicole S.; Pilcher, Darren J.

2017-01-01

Since preindustrial times, the ocean has removed from the atmosphere 41% of the carbon emitted by human industrial activities. Despite significant uncertainties, the balance of evidence indicates that the globally integrated rate of ocean carbon uptake is increasing in response to increasing atmospheric CO2 concentrations. The El Niño-Southern Oscillation in the equatorial Pacific dominates interannual variability of the globally integrated sink. Modes of climate variability in high latitudes are correlated with variability in regional carbon sinks, but mechanistic understanding is incomplete. Regional sink variability, combined with sparse sampling, means that the growing oceanic sink cannot yet be directly detected from available surface data. Accurate and precise shipboard observations need to be continued and increasingly complemented with autonomous observations. These data, together with a variety of mechanistic and diagnostic models, are needed for better understanding, long-term monitoring, and future projections of this critical climate regulation service.

Quantification of spatial temporal variability of snow cover and hydro-climatic variables based on multi-source remote sensing data in the Swat watershed, Hindukush Mountains, Pakistan

NASA Astrophysics Data System (ADS)

Anjum, Muhammad Naveed; Ding, Yongjian; Shangguan, Donghui; Liu, Junguo; Ahmad, Ijaz; Ijaz, Muhammad Wajid; Khan, Muhammad Imran

2018-02-01

The northern part of Hindukush Mountains has a perplexing environment due to the influence of adjacent mountains of Himalaya, Karakoram, and Tibetan Plateau. Although reliable evidences of climate change are available; however, a clear knowledge of snow cover dynamics in the context of climate change is missing for this region. In this study, we used various remotely sensed (TRMM precipitation product, while MODIS temperature and snow cover products) and gauge-based datasets to quantify the spatiotemporal variability of climatic variables and their turn effects over the snow cover area (SCA) and river discharge in the Swat watershed, northern Hindukush Mountains, Pakistan. The Mann-Kendall method and Sen's slope estimator were used to estimate the trends in SCA and hydro-climatic variables, at 5% significant level (P = 0.05). Results show that the winter and springs temperatures have increased (at the rate of 0.079 and 0.059 °C year-1, respectively), while decreasing in the summer and autumn (at the rate of 0.049 and 0.070 °C year-1, respectively). Basin-wide increasing tendency of precipitation was identified with a highest increasing rate of 3.563 mm year-1 in the spring season. A decreasing trend in the winter SCA (at the rate of -0.275% year-1) and increasing trends in other seasons were identified. An increasing tendency of river discharge on annual and seasonal scales was also witnessed. The seasonal variations in discharge showed significant positive and negative relationships with temperature and SCA, respectively. We conclude that the future variations in the temperature and SCA in the higher altitudes of the Swat watershed could substantially affect the seasonality of the river discharge. Moreover, it implies that the effect of ongoing global warming on the SCA in the snowmelt-dominated river basins needs to be considered for sustainable regional planning and management of water resources, hydropower production, and downstream irrigation scheduling.

Climate change threatens endangered plant species by stronger and interacting water-related stresses

NASA Astrophysics Data System (ADS)

Bartholomeus, Ruud P.; Witte, Jan-Philip M.; van Bodegom, Peter M.; van Dam, Jos C.; Aerts, Rien

2011-12-01

Atmospheric CO2-concentration, temperature and rainfall variability are all expected to increase in the near future. The resulting increased dynamics of soil moisture contents, together with increased plant physiological demands for both oxygen and water, will lead to an increased occurrence of wet and dry extremes of plant stresses, i.e., of oxygen and drought stress, respectively, alone and in interaction. The use of indirect environmental variables in previous studies and a focus on individual stresses rather than their combined effects has hampered understanding of the causal impact of climate change on plant species composition through changes in abiotic site conditions. Here, we use process-based simulations of oxygen and drought stresses in conjunction with a downscaled national version of IPCC scenarios in order to show that these stresses will increase (on average by ˜20% at sites where both stresses occur) in a warmer and more variable future (2050) climate. These two types of stresses will increasingly coincide, i.e. both stresses will occur more often (but not at the same time) within a single vegetation plot. We further show that this increased coincidence of water-related stresses will negatively affect the future occurrence of currently endangered plant species (causing a reduction of ˜16%), while apparently no such decrease will occur among common species. Individual stresses did not appear to affect the occurrence of endangered plant species. Consequently, our study demonstrates that species that are already threatened under the current climate will suffer most from the effects of climate change.

The rogue nature of hiatuses in a global warming climate

NASA Astrophysics Data System (ADS)

Sévellec, F.; Sinha, B.; Skliris, N.

2016-08-01

The nature of rogue events is their unlikelihood and the recent unpredicted decade-long slowdown in surface warming, the so-called hiatus, may be such an event. However, given decadal variability in climate, global surface temperatures were never expected to increase monotonically with increasing radiative forcing. Here surface air temperature from 20 climate models is analyzed to estimate the historical and future likelihood of hiatuses and "surges" (faster than expected warming), showing that the global hiatus of the early 21st century was extremely unlikely. A novel analysis of future climate scenarios suggests that hiatuses will almost vanish and surges will strongly intensify by 2100 under a "business as usual" scenario. For "CO2 stabilisation" scenarios, hiatus, and surge characteristics revert to typical 1940s values. These results suggest to study the hiatus of the early 21st century and future reoccurrences as rogue events, at the limit of the variability of current climate modelling capability.

The essential interactions between understanding climate variability and climate change

NASA Astrophysics Data System (ADS)

Neelin, J. D.

2017-12-01

Global change is sometimes perceived as a field separate from other aspects of atmospheric and oceanic sciences. Despite the long history of communication between the scientific communities studying global change and those studying interannual variability and weather, increasing specialization and conflicting societal demands on the fields can put these interactions at risk. At the same time, current trajectories for greenhouse gas emissions imply substantial adaptation to climate change will be necessary. Instead of simply projecting effects to be avoided, the field is increasingly being asked to provide regional-level information for specific adaptation strategies—with associated requirements for increased precision on projections. For extreme events, challenges include validating models for rare events, especially for events that are unprecedented in the historical record. These factors will be illustrated with examples of information transfer to climate change from work on fundamental climate processes aimed originally at timescales from hours to interannual. Work to understand the effects that control probability distributions of moisture, temperature and precipitation in historical weather can yield new factors to examine for the changes in the extremes of these distributions under climate change. Surprisingly simple process models can give insights into the behavior of vastly more complex climate models. Observation systems and model ensembles aimed at weather and interannual variations prove valuable for global change and vice versa. Work on teleconnections in the climate system, such as the remote impacts of El Niño, is informing analysis of projected regional rainfall change over California. Young scientists need to prepare to work across the full spectrum of climate variability and change, and to communicate their findings, as they and our society head for future that is more interesting than optimal.

The environmental context for the origins of modern human diversity: a synthesis of regional variability in African climate 150,000-30,000 years ago.

PubMed

Blome, Margaret Whiting; Cohen, Andrew S; Tryon, Christian A; Brooks, Alison S; Russell, Joellen

2012-05-01

We synthesize African paleoclimate from 150 to 30 ka (thousand years ago) using 85 diverse datasets at a regional scale, testing for coherence with North Atlantic glacial/interglacial phases and northern and southern hemisphere insolation cycles. Two major determinants of circum-African climate variability over this time period are supported by principal components analysis: North Atlantic sea surface temperature (SST) variations and local insolation maxima. North Atlantic SSTs correlated with the variability found in most circum-African SST records, whereas the variability of the majority of terrestrial temperature and precipitation records is explained by local insolation maxima, particularly at times when solar radiation was intense and highly variable (e.g., 150-75 ka). We demonstrate that climates varied with latitude, such that periods of relatively increased aridity or humidity were asynchronous across the northern, eastern, tropical and southern portions of Africa. Comparisons of the archaeological, fossil, or genetic records with generalized patterns of environmental change based solely on northern hemisphere glacial/interglacial cycles are therefore imprecise. We compare our refined climatic framework to a database of 64 radiometrically-dated paleoanthropological sites to test hypotheses of demographic response to climatic change among African hominin populations during the 150-30 ka interval. We argue that at a continental scale, population and climate changes were asynchronous and likely occurred under different regimes of climate forcing, creating alternating opportunities for migration into adjacent regions. Our results suggest little relation between large scale demographic and climate change in southern Africa during this time span, but strongly support the hypothesis of hominin occupation of the Sahara during discrete humid intervals ~135-115 ka and 105-75 ka. Hominin populations in equatorial and eastern Africa may have been buffered from the extremes of climate change by locally steep altitudinal and rainfall gradients and the complex and variable effects of increased aridity on human habitat suitability in the tropics. Our data are consistent with hominin migrations out of Africa through varying exit points from ~140-80 ka. Copyright © 2012 Elsevier Ltd. All rights reserved.

ENSO in a warming world: interannual climate variability in the early Miocene Southern Hemisphere

NASA Astrophysics Data System (ADS)

Fox, Bethany; Wilson, Gary; Lee, Daphne

2016-04-01

The El Niño - Southern Oscillation (ENSO) is the dominant source of interannual variability in the modern-day climate system. ENSO is a quasi-periodic cycle with a recurrence interval of 2-8 years. A major question in modern climatology is how ENSO will respond to increased climatic warmth. ENSO-like (2-8 year) cycles have been detected in many palaeoclimate records for the Holocene. However, the temporal resolution of pre-Quaternary palaeoclimate archives is generally too coarse to investigate ENSO-scale variability. We present a 100-kyr record of ENSO-like variability during the second half of the Oligocene/Miocene Mi-1 event, a period of increasing global temperatures and Antarctic deglaciation (~23.032-2.93 Ma). This record is drawn from an annually laminated lacustrine diatomite from southern New Zealand, a region strongly affected by ENSO in the present day. The diatomite consists of seasonal alternations of light (diatom bloom) and dark (low diatom productivity) layers. Each light-dark couplet represents one year's sedimentation. Light-dark couplet thickness is characterised by ENSO-scale variability. We use high-resolution (sub-annual) measurements of colour spectra to detect couplet thickness variability. Wavelet analysis indicates that absolute values are modulated by orbital cycles. However, when orbital effects are taken into account, ENSO-like variability occurs throughout the entire depositional period, with no clear increase or reduction in relation to Antarctic deglaciation and increasing global warmth.

Ecosystem response to climatic variables - air temperature and precipitation: How can these variables alter plant productions in C4-grass dominant ecosystem?

NASA Astrophysics Data System (ADS)

Jung, C. G.; Jiang, L.; Luo, Y.

2017-12-01

Understanding net primary production (NPP) response to the key climatic variables, temperature and precipitation, is essential since the response could be represented by one of future consequences from ecosystem responses. Under future climatic warming, fluctuating precipitation is expected. In addition, NPP solely could not explain whole ecosystem response; therefore, not only NPP, but also above- and below-ground NPP (ANPP and BNPP, respectively) need to be examined. This examination needs to include how the plant productions response along temperature and precipitation gradients. Several studies have examined the response of NPP against each of single climatic variable, but understanding the response of ANPP and BNPP to the multiple variables is notably poor. In this study, we used the plant productions data (NPP, ANPP, and BNPP) with climatic variables, i.e., air temperature and precipitation, from 1999 to 2015 under warming and clipping treatments (mimicking hay-harvesting) in C4-grass dominant ecosystem located in central Oklahoma, United States. Firstly, we examined the nonlinear relationships with the climatic variables for NPP, ANPP and BNPP; and then predicted possible responses in the temperature - precipitation space by using a linear mixed effect model. Nonlinearities of NPP, ANPP and BNPP to the climatic variables have been found to show unimodal curves, and nonlinear models have better goodness of fit as shown lower Akaike information criterion (AIC) than linear models. Optimum condition for NPP is represented at high temperature and precipitation level whereas BNPP is maximized at moderate precipitation levels while ANPP has same range of NPP's optimum condition. Clipping significantly reduced ANPP while there was no clipping effect on NPP and BNPP. Furthermore, inclining NPP and ANPP have shown in a range from moderate to high precipitation level with increasing temperature while inclining pattern for BNPP was observed in moderate precipitation level. Overall, the C4-grass dominant ecosystem has a potential for considerable increases in NPP in hotter and wetter conditions as shown a range from moderate to high temperature and precipitation levels; ANPP has peaked at the high temperature and precipitation level, but maximum BNPP needs moderate precipitation level and high temperature.

An Assessment of Actual and Potential Building Climate Zone Change and Variability From the Last 30 Years Through 2100 Using NASA's MERRA and CMIP5 Simulations

NASA Technical Reports Server (NTRS)

Stackhouse, Paul W., Jr.; Chandler, William S.; Hoell, James M.; Westberg, David; Zhang, Taiping

2015-01-01

Background: In the US, residential and commercial building infrastructure combined consumes about 40% of total energy usage and emits about 39% of total CO2 emission (DOE/EIA "Annual Energy Outlook 2013"). Building codes, as used by local and state enforcement entities are typically tied to the dominant climate within an enforcement jurisdiction classified according to various climate zones. These climate zones are based upon a 30-year average of local surface observations and are developed by DOE and ASHRAE. Establishing the current variability and potential changes to future building climate zones is very important for increasing the energy efficiency of buildings and reducing energy costs and emissions in the future. Objectives: This paper demonstrates the usefulness of using NASA's Modern Era Retrospective-analysis for Research and Applications (MERRA) atmospheric data assimilation to derive the DOE/ASHRAE building climate zone maps and then using MERRA to define the last 30 years of variability in climate zones for the Continental US. An atmospheric assimilation is a global atmospheric model optimized to satellite, atmospheric and surface in situ measurements. Using MERRA as a baseline, we then evaluate the latest Climate Model Inter-comparison Project (CMIP) climate model Version 5 runs to assess potential variability in future climate zones under various assumptions. Methods: We derive DOE/ASHRAE building climate zones using surface and temperature data products from MERRA. We assess these zones using the uncertainties derived by comparison to surface measurements. Using statistical tests, we evaluate variability of the climate zones in time and assess areas in the continental US for statistically significant trends by region. CMIP 5 produced a data base of over two dozen detailed climate model runs under various greenhouse gas forcing assumptions. We evaluate the variation in building climate zones for 3 different decades using an ensemble and quartile statistics to provide an assessment of potential building climate zone changes relative to the uncertainties demonstrated using MERRA. Findings and Conclusions: These results show that there is a statistically significant increase in the area covered by warmer climate zones and a tendency for a reduction of area in colder climate zones in some limited regions. The CMIP analysis shows that models vary from relatively little building climate zone change for the least sensitive and conservation assumptions to a warming of at most 3 zones for certain areas, particularly the north central US by the end of the 21st century.

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD

PubMed Central

Lorenz, David J.; Nieto-Lugilde, Diego; Blois, Jessica L.; Fitzpatrick, Matthew C.; Williams, John W.

2016-01-01

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950–2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850–2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity. PMID:27377537

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD.

PubMed

Lorenz, David J; Nieto-Lugilde, Diego; Blois, Jessica L; Fitzpatrick, Matthew C; Williams, John W

2016-07-05

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950-2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850-2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity.

Forced Atlantic Multidecadal Variability Over the Past Millennium

NASA Astrophysics Data System (ADS)

Halloran, P. R.; Reynolds, D.; Scourse, J. D.; Hall, I. R.

2016-02-01

Paul R. Halloran, David J. Reynolds, Ian R. Hall and James D. Scourse Multidecadal variability in Atlantic sea surface temperatures (SSTs) plays a first order role in determining regional atmospheric circulation and moisture transport, with major climatic consequences. These regional climate impacts range from drought in the Sahel and South America, though increased hurricane activity and temperature extremes, to modified monsoonal rainfall. Multidecadal Atlantic SST variability could arise through internal variability in the Atlantic Meridional Overturning Circulation (AMOC) (e.g., Knight et al., 2006), or through externally forced change (e.g. Booth et al., 2012). It is critical that we know whether internal or external forcing dominates if we are to provide useful near-term climate projections in the Atlantic region. A persuasive argument that internal variability plays an important role in Atlantic Multidecadal Variability is that periodic SST variability has been observed throughout much of the last millennium (Mann et al., 2009), and the hypothesized external forcing of historical Atlantic Multidecadal Variability (Booth et al., 2012) is largely anthropogenic in origin. Here we combine the first annually-resolved millennial marine reconstruction with multi-model analysis, to show that the Atlantic SST variability of the last millennium can be explained by a combination of direct volcanic forcing, and indirect, forced, AMOC variability. Our results indicate that whilst climate models capture the timing of both the directly forced SST and forced AMOC-mediated SST variability, the models fail to capture the magnitude of the forced AMOC change. Does this mean that models underestimate the 21st century reduction in AMOC strength? J. Knight, C. Folland and A. Scaife., Climate impacts of the Atlantic Multidecadal Oscillation, GRL, 2006 B.B.B Booth, N. Dunstone, P.R. Halloran et al., Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability, Nature, 2012 M.E. Mann, Z. Zhang, S. Rutherford et al., Global Signatures and Dynamical Origins of the Little Ice Age and Medieval Climate Anomaly, Science, 2009

Increasing ENSO-Driven Drought and Wildfire Risks in a Warming Climate

NASA Astrophysics Data System (ADS)

Fasullo, J.; Otto-Bliesner, B. L.; Stevenson, S.

2015-12-01

ENSO-related teleconnections occurring in the transient climate states of the 20th and 21st centuries are examined using the NCAR CESM1-CAM5 Large Ensemble (LE). A focus is given to quantifying the changing nature of related variability in a warming climate, the statistical robustness of which is enhanced by the numerous members of the LE (presently ~40). It is found that while the dynamical components of ENSO's teleconnections weaken considerably in a warming world, associated variability over land is in many cases sustained by changes in the background state, such as for rainfall due to the background rise in specific humidity. In some fields, particularly those associated with associated with thermal stress (e.g. drought and wildfire), ENSO-related variance increases dramatically. This, combined with the fact that ENSO variance itself increases in a warming climate in the LE, contributes to dramatic projected increases in ENSO-driven drought and wildfire risks in a warming world.

Unstable relationships between tree ring δ18O and climate variables over southwestern China: possible impacts from increasing central Pacific SSTs

NASA Astrophysics Data System (ADS)

An, Wenling; Liu, Xiaohong; Hou, Shugui; Zeng, Xiaomin; Sun, Weizhen; Wang, Wenzhi; Wang, Yu; Xu, Guobao; Ren, Jiawen

2018-05-01

In this study, we investigated the potential influence of central and eastern Pacific sea surface temperatures (SSTs) on the unstable relationship between earlywood δ18O and climatic factors in the southwestern China from 1902 to 2005. The results show that the strength of the climate signals recorded in the earlywood δ18O series has declined since the late 1970s. This reduction in signal strength may have been caused by the changes in the local hydroclimate, which is associated with the increasing SSTs in the central Pacific Ocean over recent decades. Alongside these increasing SSTs in the central Pacific, southwestern China has experienced more droughts, as well as more severe droughts through the late spring and early summer during the central Pacific (CP) El Niño years than during the eastern Pacific (EP) El Niño years in recent decades. This increased drought frequency may have weakened the response of earlywood δ18O to climate variables.

Projected Changes in Mean and Interannual Variability of Surface Water over Continental China

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leng, Guoyong; Tang, Qiuhong; Huang, Maoyi

Five General Circulation Model (GCM) climate projections under the RCP8.5 emission scenario were used to drive the Variable Infiltration Capacity (VIC) hydrologic model to investigate the impacts of climate change on hydrologic cycle over continental China in the 21st century. The bias-corrected climatic variables were generated for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5) by the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). Results showed much larger fractional changes of annual mean Evaportranspiration (ET) per unit warming than the corresponding fractional changes of Precipitation (P) per unit warming across the country especially for South China,more » which led to notable decrease of surface water variability (P-E). Specifically, negative trends for annual mean runoff up to -0.33%/decade and soil moisture trends varying between -0.02 to -0.13%/decade were found for most river basins across China. Coincidentally, interannual variability for both runoff and soil moisture exhibited significant positive trends for almost all river basins across China, implying an increase in extremes relative to the mean conditions. Noticeably, the largest positive trends for runoff variability and soil moisture variability, which were up to 38 0.41%/decade and 0.90%/decade, both occurred in Southwest China. In addition to the regional contrast, intra-seasonal variation was also large for the runoff mean and runoff variability changes, but small for the soil moisture mean and variability changes. Our results suggest that future climate change could further exacerbate existing water-related risks (e.g. floods and droughts) across China as indicated by the marked decrease of surface water amounts combined with steady increase of interannual variability throughout the 21st century. This study highlights the regional contrast and intra-seasonal variations for the projected hydrologic changes and could provide muti-scale guidance for assessing effective adaptation strategies for the country on a river basin, regional, or as whole.« less

The Effect of ENSO on Phytoplankton Composition in the Pacific Ocean

NASA Technical Reports Server (NTRS)

Rousseaux, Cecile

2012-01-01

The effect of climate variability on phytoplankton communities was assessed for the tropical and sub-tropical Pacific Ocean between 1998 and 2005 using an established biogeochemical assimilation model. The phytoplankton communities exhibited wide range of responses to climate variability, from radical shifts in the Equatorial Pacific, to changes of only a couple of phytoplankton groups in the North Central Pacific, to no significant changes in the South Pacific. In the Equatorial Pacific, climate variability dominated the variability of phytoplankton. Here, nitrate, chlorophyll and all but one of the 4 phytoplankton types (diatoms, cyanobacteria and coccolithophores) were strongly correlated (p less than 0.01) with the Multivariate El Nino Southern Oscillation Index (MEI). In the North Central Pacific, MEI and chlorophyll were significantly (p<0.01) correlated along with two of the phytoplankton groups (chlorophytes and coccolithophores). Ocean biology in the South Pacific was not significantly correlated with MEI. During La Ni a events, diatoms increased and expanded westward along the cold tongue (correlation with MEI, r=-0.81), while cyanobacteria concentrations decreased significantly (r=0.78). El Nino produced the reverse pattern, with cyanobacteria populations increasing while diatoms plummeted. The diverse response of phytoplankton in the different major basins of the Pacific suggests the different roles climate variability can play in ocean biology.

Climate Change Amplifications of Climate-Fire Teleconnections in the Southern Hemisphere

NASA Astrophysics Data System (ADS)

Mariani, Michela; Holz, Andrés.; Veblen, Thomas T.; Williamson, Grant; Fletcher, Michael-Shawn; Bowman, David M. J. S.

2018-05-01

Recent changes in trend and variability of the main Southern Hemisphere climate modes are driven by a variety of factors, including increasing atmospheric greenhouse gases, changes in tropical sea surface temperature, and stratospheric ozone depletion and recovery. One of the most important implications for climatic change is its effect via climate teleconnections on natural ecosystems, water security, and fire variability in proximity to populated areas, thus threatening human lives and properties. Only sparse and fragmentary knowledge of relationships between teleconnections, lightning strikes, and fire is available during the observed record within the Southern Hemisphere. This constitutes a major knowledge gap for undertaking suitable management and conservation plans. Our analysis of documentary fire records from Mediterranean and temperate regions across the Southern Hemisphere reveals a critical increased strength of climate-fire teleconnections during the onset of the 21st century including a tight coupling between lightning-ignited fire occurrences, the upward trend in the Southern Annular Mode, and rising temperatures across the Southern Hemisphere.

Characterizing hydroclimatic variability in tributaries of the Upper Colorado River Basin—WY1911-2001

NASA Astrophysics Data System (ADS)

Matter, Margaret A.; Garcia, Luis A.; Fontane, Darrell G.; Bledsoe, Brian

2010-01-01

SummaryMountain snowpack is the main source of water in the semi-arid Colorado River Basin (CRB), and while the demands for water are increasing, competing and often conflicting, the supply is limited and has become increasingly variable over the 20th Century. Greater variability is believed to contribute to lower accuracy in water supply forecasts, plus greater variability violates the assumption of stationarity, a fundamental assumption of many methods used in water resources engineering planning, design and management. Thus, it is essential to understand the underpinnings of hydroclimatic variability in order to accurately predict effects of climate changes and effectively meet future water supply challenges. A new methodology was applied to characterized time series of temperature, precipitation, and streamflow (i.e., historic and reconstructed undepleted flows) according to the three climate regimes that occurred in CRB during the 20th Century. Results for two tributaries in the Upper CRB show that hydroclimatic variability is more deterministic than previously thought because it entails complementary temperature and precipitation patterns associated with wetter or drier conditions on climate regime and annual scales. Complementary temperature and precipitation patterns characterize climate regime type (e.g., cool/wet and warm/dry), and the patterns entail increasing or decreasing temperatures and changes in magnitude and timing of precipitation according to the climate regime type. Accompanying each climate regime on annual scales are complementary temperature ( T) and precipitation ( P) patterns that are associated with upcoming precipitation and annual basin yield (i.e., total annual flow volume at a streamflow gauge). Annual complementary T and P patterns establish by fall, are detectable as early as September, persist to early spring, are related to the relative magnitude of upcoming precipitation and annual basin yield, are unique to climate regime type, and are specific to each river basin. Thus, while most of the water supply in the Upper CRB originates from winter snowpack, statistically significant indictors of relative magnitude of upcoming precipitation and runoff are evident in the fall, well before appreciable snow accumulation. Results of this study suggest strategies that may integrated into existing forecast methods to potentially improve forecast accuracy and advance lead time by as much as six months (i.e., from April 1 to October 1 of the previous year). These techniques also have applications in downscaling climate models and in river restoration and management.

Adaptation with climate uncertainty: An examination of agricultural land use in the United States

USGS Publications Warehouse

Mu, Jianhong E.; McCarl, Bruce A.; Sleeter, Benjamin M.; Abatzoglou, John T.; Zhang, Hongliang

2018-01-01

This paper examines adaptation responses to climate change through adjustment of agricultural land use. The climate drivers we examine are changes in long-term climate normals (e.g., 10-year moving averages) and changes in inter-annual climate variability. Using US county level data over 1982 to 2012 from Census of Agriculture, we find that impacts of long-term climate normals are as important as that of inter-annual climate variability. Projecting into the future, we find projected climate change will lead to an expansion in crop land share across the northern and interior western United States with decreases in the south. We also find that grazing land share increases in southern regions and Inland Pacific Northwest and declines in the northern areas. However, the extent to which the adaptation potential would be is dependent on the climate model, emission scenario and time horizon under consideration.

Population viability of Pediocactus brady (Cactaceae) in a changing climate

USGS Publications Warehouse

Shryock, Daniel F.; Esque, Todd C.; Huges, Lee

2014-01-01

• Conclusions: Pediocactus bradyi may be vulnerable to increases in the frequency and intensity of extreme climatic events, particularly drought. Biotic interactions resulting in low survival during drought years outweighed increased seedling establishment following heavy precipitation. Climatic extremes beyond historical ranges of variability may threaten rare desert species with low population growth rates and therefore high susceptibility to stochastic events.

Vegetation change, malnutrition and violence in the Horn of Africa

NASA Astrophysics Data System (ADS)

Rowhani, P.; Degomme, O.; Linderman, M.; Guha-Sapir, D.; Lambin, E.

2008-12-01

In certain circumstances, climate change in association with a broad range of social factors may increase the risk of famines and subsequently, violent conflict. The impacts of climate change on society will be experienced both through changes in mean conditions over long time periods and through increases in extreme events. Recent studies have shown the historical effects of long term climate change on societies and the importance of short term climatic triggers on armed conflict. However, most of these studies are at the state level ignoring local conditions. Here we use detailed information extracted from wide-swath satellite data (MODIS) to analyze the impact of climate variability change on malnutrition and violent conflict. More specifically, we perform multivariate logistic regression analysis in order to explain the geographical distribution of malnutrition and conflict in the Horn of Africa on a sub-national level. This region, constituted by several unstable and poor states, has been affected by droughts, floods, famines, and violence in the past few years. Three commonly used nutrition and mortality indicators are used to characterize the health situation (CE-DAT database). To map violence we use the georeferenced Armed Conflicts dataset developed by the Center for the Study of Civil War. Explanatory variables include several socio-economic variables and environmental variables characterizing land degradation, vegetation activity, and interannual variability in land-surface conditions. First results show that interannual variability in land-surface conditions is associated with malnutrition but not with armed conflict. Furthermore, land degradation seems not to be associated with either malnutrition or armed conflict.

Utilizing Satellite Precipitation Products to Understand the Link Between Climate Variability and Malaria

NASA Astrophysics Data System (ADS)

Maggioni, V.; Mousam, A.; Delamater, P. L.; Cash, B. A.; Quispe, A.

2015-12-01

Malaria is a public health threat to people globally leading to 198 million cases and 584,000 deaths annually. Outbreaks of vector borne diseases such as malaria can be significantly impacted by climate variables such as precipitation. For example, an increase in rainfall has the potential to create pools of water that can serve as breeding locations for mosquitos. Peru is a country that is currently controlling malaria, but has not been able to completely eliminate the disease. Despite the various initiatives in order to control malaria - including regional efforts to improve surveillance, early detection, prompt treatment, and vector management - malaria cases in Peru have risen between 2011 and 2014. The purpose of this study is to test the hypothesis that climate variability plays a fundamental role in malaria occurrence over a 12-year period (2003-2014) in Peru. When analyzing climate variability, it is important to obtain high-quality, high-resolution data for a time series long enough to draw conclusion about how climate variables have been and are changing. Remote sensing is a powerful tool for measuring and monitoring climate variables continuously in time and space. A widely used satellite-based precipitation product, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), available globally since 1998, was used to obtain 3-hourly data with a spatial resolution of 0.25° x 0.25°. The precipitation data was linked to weekly (2003-2014) malaria cases collected by health centers and available at a district level all over Peru to investigate the relationship between precipitation and the seasonal and annual variations in malaria incidence. Further studies will incorporate additional climate variables such as temperature, humidity, soil moisture, and surface pressure from remote sensing data products and climate models. Ultimately, this research will help us to understand if climate variability impacts malaria incidence rates and to determine which regions of the country are most affected.

Vulnerability to climate variability and change in East Timor.

PubMed

Barnett, Jon; Dessai, Suraje; Jones, Roger N

2007-07-01

This paper presents the results of a preliminary study of climate vulnerability in East Timor. It shows the results of projections of climate change in East Timor. The country's climate may become hotter, drier, and increasingly variable. Sea levels are likely to rise. The paper then considers the implications of these changes on three natural resources--water, soils, and the coastal zone--and finds all to be sensitive to changes in climate and sea level. Changes in the abundance and distribution of these resources is likely to cause a reduction in agricultural production and food security, and sea-level rise is likely to damage coastal areas, including Dili, the capital city.

The Impact of Climate Change on the Potential Distribution of Agricultural Pests: The Case of the Coffee White Stem Borer (Monochamus leuconotus P.) in Zimbabwe

PubMed Central

Kutywayo, Dumisani; Chemura, Abel; Kusena, Winmore; Chidoko, Pardon; Mahoya, Caleb

2013-01-01

The production of agricultural commodities faces increased risk of pests, diseases and other stresses due to climate change and variability. This study assesses the potential distribution of agricultural pests under projected climatic scenarios using evidence from the African coffee white stem borer (CWB), Monochamus leuconotus (Pascoe) (Coleoptera: Cerambycidae), an important pest of coffee in Zimbabwe. A species distribution modeling approach utilising Boosted Regression Trees (BRT) and Generalized Linear Models (GLM) was applied on current and projected climate data obtained from the WorldClim database and occurrence data (presence and absence) collected through on-farm biological surveys in Chipinge, Chimanimani, Mutare and Mutasa districts in Zimbabwe. Results from both the BRT and GLM indicate that precipitation-related variables are more important in determining species range for the CWB than temperature related variables. The CWB has extensive potential habitats in all coffee areas with Mutasa district having the largest model average area suitable for CWB under current and projected climatic conditions. Habitat ranges for CWB will increase under future climate scenarios for Chipinge, Chimanimani and Mutare districts while it will decrease in Mutasa district. The highest percentage change in area suitable for the CWB was for Chimanimani district with a model average of 49.1% (3 906 ha) increase in CWB range by 2080. The BRT and GLM predictions gave similar predicted ranges for Chipinge, Chimanimani and Mutasa districts compared to the high variation in current and projected habitat area for CWB in Mutare district. The study concludes that suitable area for CWB will increase significantly in Zimbabwe due to climate change and there is need to develop adaptation mechanisms. PMID:24014222

Interannual variability and climatic noise in satellite-observed outgoing longwave radiation

NASA Technical Reports Server (NTRS)

Short, D. A.; Cahalan, R. F.

1983-01-01

Upwelling-IR observations of the North Pacific by polar orbiters NOAA 3, 4, 5, and 6 and TIROS-N from 1974 to 1981 are analyzed statistically in terms of interannual variability (IAV) in monthly averages and climatic noise due to short-term weather fluctuations. It is found that although the daily variance in the observations is the same in summer and winter months, and although IAV in winter is smaller than that in summer, the climatic noise in winter is so much smaller that a greater fraction of winter anomalies are statistically significant. The smaller winter climatic noise level is shown to be due to shorter autocorrelation times. It is demonstrated that increasing averaging area does not reduce the climatic noise level, suggesting that continuing collection of high-resolution satellite IR data on a global basis is necessary if better models of short-term variability are to be constructed.

Climate variability, social and environmental factors, and ross river virus transmission: research development and future research needs.

PubMed

Tong, Shilu; Dale, Pat; Nicholls, Neville; Mackenzie, John S; Wolff, Rodney; McMichael, Anthony J

2008-12-01

Arbovirus diseases have emerged as a global public health concern. However, the impact of climatic, social, and environmental variability on the transmission of arbovirus diseases remains to be determined. Our goal for this study was to provide an overview of research development and future research directions about the interrelationship between climate variability, social and environmental factors, and the transmission of Ross River virus (RRV), the most common and widespread arbovirus disease in Australia. We conducted a systematic literature search on climatic, social, and environmental factors and RRV disease. Potentially relevant studies were identified from a series of electronic searches. The body of evidence revealed that the transmission cycles of RRV disease appear to be sensitive to climate and tidal variability. Rainfall, temperature, and high tides were among major determinants of the transmission of RRV disease at the macro level. However, the nature and magnitude of the interrelationship between climate variability, mosquito density, and the transmission of RRV disease varied with geographic area and socioenvironmental condition. Projected anthropogenic global climatic change may result in an increase in RRV infections, and the key determinants of RRV transmission we have identified here may be useful in the development of an early warning system. The analysis indicates that there is a complex relationship between climate variability, social and environmental factors, and RRV transmission. Different strategies may be needed for the control and prevention of RRV disease at different levels. These research findings could be used as an additional tool to support decision making in disease control/surveillance and risk management.

Climate variability risks for electricity supply

NASA Astrophysics Data System (ADS)

Kling, Harald

2017-12-01

Hydropower represents about 20% of sub-Saharan electricity, and expansion is underway. Rainfall varies year-to-year in geographical clusters, increasing the risk of climate-related electricity supply disruption in dry years.

Contingency in the Direction and Mechanics of Soil Organic Matter Responses to Increased Rainfall

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berhe, Asmeret A.; Suttle, K. Blake; Burton, Sarah D.

2012-09-03

Shifts in regional precipitation patterns will be a major component of global climate change. Rainfall will show greater and more variable changes in response to rising earth surface temperatures than most other climatic variables, and will be a major driver of ecosystem change. We studied the consequences of predicted changes in California’s rainy season for storage and stabilization mechanisms of soil organic matter (SOM). In a controlled and replicated experiment, we amended rainfall over large plots of natural grassland in accordance with alternative scenarios of future climate change. Results show that increases in annual rainfall have important consequences for soilmore » C storage, but that the strength and even direction of these effects depend entirely on seasonal timing. Rainfall increases during the winter rainy season led to pronounced C loss from soil while rainfall increases after the typical rainy season increased soil C stocks. Analysis of mineral-OM associations reveals a powerful mechanism underlying this difference: increased winter rainfall vastly diminished the role of Fe and Al oxides in SOM stabilization. Dithionite extractable crystalline Fe oxides explained more than 35 percent of the variability in C storage in ambient control and spring-addition treatments, compared to less than 0.01 percent in the winter-addition treatment. Likewise, poorly crystalline Fe and Al oxides explained more than 25 and 40 percent of the variability in C storage, respectively, in the control and spring-addition treatments compared to less than 5 percent in the -winter-addition treatment. Increases in annual precipitation identical in amount but at three-month offsets produced opposite effects on soil C storage. These results highlight the complexity inherent in biospheric feedbacks to the climate system, and the way that careful experimentation can penetrate that complexity to improve predictions of ecosystem and climatic change.« less

Identifying the interferences of irrigation on evapotranspiration variability over the Northern High Plains

NASA Astrophysics Data System (ADS)

Zeng, R.; Cai, X.

2016-12-01

Irrigation has considerably interfered with hydrological processes in arid and semi-arid areas with heavy irrigated agriculture. With the increasing demand for food production and evaporative demand due to climate change, irrigation water consumption is expected to increase, which would aggravate the interferences to hydrologic processes. Current studies focus on the impact of irrigation on the mean value of evapotranspiration (ET) at either local or regional scale, however, how irrigation changes the variability of ET has not been well understood. This study analyzes the impact of extensive irrigation on ET variability in the Northern High Plains. We apply an ET variance decomposition framework developed from our previous work to quantify the effects of both climate and irrigation on ET variance in the Northern High Plains watersheds. Based on climate and water table observations, we assess the monthly ET variance and its components for two periods: 1930s-1960s with less irrigation development 970s-2010s with more development. It is found that irrigation not only caused the well-recognized groundwater drawdown and stream depletion problems in the region, but also buffered ET variance from climatic fluctuations. In addition to increasing food productivity, irrigation also stabilizes crop yield by mitigating the impact of hydroclimatic variability. With complementary water supply from irrigation, ET often approaches to the potential ET, and thus the observed ET variance is more attributed to climatic variables especially temperature; meanwhile irrigation causes significant seasonal fluctuations to groundwater storage. For sustainable water resources management in the Northern High Plains, we argue that both the mean value and the variance of ET should be considered together for the regulation of irrigation in this region.

Semi-arid vegetation response to antecedent climate and water balance windows

USGS Publications Warehouse

Thoma, David P.; Munson, Seth M.; Irvine, Kathryn M.; Witwicki, Dana L.; Bunting, Erin

2016-01-01

Questions Can we improve understanding of vegetation response to water availability on monthly time scales in semi-arid environments using remote sensing methods? What climatic or water balance variables and antecedent windows of time associated with these variables best relate to the condition of vegetation? Can we develop credible near-term forecasts from climate data that can be used to prepare for future climate change effects on vegetation? Location Semi-arid grasslands in Capitol Reef National Park, Utah, USA. Methods We built vegetation response models by relating the normalized difference vegetation index (NDVI) from MODIS imagery in Mar–Nov 2000–2013 to antecedent climate and water balance variables preceding the monthly NDVI observations. We compared how climate and water balance variables explained vegetation greenness and then used a multi-model ensemble of climate and water balance models to forecast monthly NDVI for three holdout years. Results Water balance variables explained vegetation greenness to a greater degree than climate variables for most growing season months. Seasonally important variables included measures of antecedent water input and storage in spring, switching to indicators of drought, input or use in summer, followed by antecedent moisture availability in autumn. In spite of similar climates, there was evidence the grazed grassland showed a response to drying conditions 1 mo sooner than the ungrazed grassland. Lead times were generally short early in the growing season and antecedent window durations increased from 3 mo early in the growing season to 1 yr or more as the growing season progressed. Forecast accuracy for three holdout years using a multi-model ensemble of climate and water balance variables outperformed forecasts made with a naïve NDVI climatology. Conclusions We determined the influence of climate and water balance on vegetation at a fine temporal scale, which presents an opportunity to forecast vegetation response with short lead times. This understanding was obtained through high-frequency vegetation monitoring using remote sensing, which reduces the costs and time necessary for field measurements and can lead to more rapid detection of vegetation changes that could help managers take appropriate actions.

Selecting Populations for Non-Analogous Climate Conditions Using Universal Response Functions: The Case of Douglas-Fir in Central Europe.

PubMed

Chakraborty, Debojyoti; Wang, Tongli; Andre, Konrad; Konnert, Monika; Lexer, Manfred J; Matulla, Christoph; Schueler, Silvio

2015-01-01

Identifying populations within tree species potentially adapted to future climatic conditions is an important requirement for reforestation and assisted migration programmes. Such populations can be identified either by empirical response functions based on correlations of quantitative traits with climate variables or by climate envelope models that compare the climate of seed sources and potential growing areas. In the present study, we analyzed the intraspecific variation in climate growth response of Douglas-fir planted within the non-analogous climate conditions of Central and continental Europe. With data from 50 common garden trials, we developed Universal Response Functions (URF) for tree height and mean basal area and compared the growth performance of the selected best performing populations with that of populations identified through a climate envelope approach. Climate variables of the trial location were found to be stronger predictors of growth performance than climate variables of the population origin. Although the precipitation regime of the population sources varied strongly none of the precipitation related climate variables of population origin was found to be significant within the models. Overall, the URFs explained more than 88% of variation in growth performance. Populations identified by the URF models originate from western Cascades and coastal areas of Washington and Oregon and show significantly higher growth performance than populations identified by the climate envelope approach under both current and climate change scenarios. The URFs predict decreasing growth performance at low and middle elevations of the case study area, but increasing growth performance on high elevation sites. Our analysis suggests that population recommendations based on empirical approaches should be preferred and population selections by climate envelope models without considering climatic constrains of growth performance should be carefully appraised before transferring populations to planting locations with novel or dissimilar climate.

Impacts of temperature and its variability on mortality in New England

NASA Astrophysics Data System (ADS)

Shi, Liuhua; Kloog, Itai; Zanobetti, Antonella; Liu, Pengfei; Schwartz, Joel D.

2015-11-01

Rapid build-up of greenhouse gases is expected to increase Earth’s mean surface temperature, with unclear effects on temperature variability. This makes understanding the direct effects of a changing climate on human health more urgent. However, the effects of prolonged exposures to variable temperatures, which are important for understanding the public health burden, are unclear. Here we demonstrate that long-term survival was significantly associated with both seasonal mean values and standard deviations of temperature among the Medicare population (aged 65+) in New England, and break that down into long-term contrasts between ZIP codes and annual anomalies. A rise in summer mean temperature of 1 °C was associated with a 1.0% higher death rate, whereas an increase in winter mean temperature corresponded to a 0.6% decrease in mortality. Increases in standard deviations of temperature for both summer and winter were harmful. The increased mortality in warmer summers was entirely due to anomalies, whereas it was long-term average differences in the standard deviation of summer temperatures across ZIP codes that drove the increased risk. For future climate scenarios, seasonal mean temperatures may in part account for the public health burden, but the excess public health risk of climate change may also stem from changes of within-season temperature variability.

Nitrate and dissolved organic carbon mobilization in response to soil freezing variability

Treesearch

Colin B. Fuss; Charles T. Driscoll; Peter M. Groffman; John L. Campbell; Lynn M. Christenson; Timothy J. Fahey; Melany C. Fisk; Myron J. Mitchell; Pamela H. Templer; Jorge Durán; Jennifer L. Morse

2016-01-01

Reduced snowpack and associated increases in soil freezing severity resulting from winter climate change have the potential to disrupt carbon (C) and nitrogen (N) cycling in soils. We used a natural winter climate gradient based on elevation and aspect in a northern hardwood forest to examine the effects of variability in soil freezing depth, duration, and frequency on...

Using an improved understanding of current climate variability to develop increased drought resilience in UK irrigated agriculture

NASA Astrophysics Data System (ADS)

Holman, I.; Rey Vicario, D.

2016-12-01

Improving community preparedness for climate change can be supported by developing resilience to past events, focused on those changes of particular relevance (such as floods and droughts). However, communities' perceptions of impacts and risk can be influenced by an incomplete appreciation of historical baseline climate variability. This can arise from a number of factors including individual's age, access to long term data records and availability of local knowledge. For example, the most significant recent drought in the UK occurred in 1976/77 but does it represent the worst drought that did occur (or could have occurred) without climate change? We focus on the east of England where most irrigated agriculture is located and where many local farmers interviewed were either not in business then or have an incomplete memory of the impacts of the drought. This paper describes a comparison of an annual agroclimatic indicator closely linked to irrigation demand (maximum Potential Soil Moisture Deficit) calculated from three sources of long term observational and simulated historical weather data with recent data. These long term datasets include gridded measured / calculated datasets of precipitation and reference evapotranspiration; a dynamically downscaled 20th Century Re-analysis dataset, and two Regional Climate Model ensemble datasets (FutureFlows and the MaRIUS event set) which each provide between 110 and 3000 years of baseline weather. The comparison shows that the long term datasets provide a wider characterisation of current climate variability and affect the perception of current drought frequency and severity. The paper will show that using a more comprehensive understanding of current climate variability and drought risk as a basis for adapting irrigated systems to droughts can provide substantial increased resilience to (uncertain) climate change.

2500 Years of European Climate Variability and Human Susceptibility

NASA Astrophysics Data System (ADS)

Büntgen, Ulf; Tegel, Willy; Nicolussi, Kurt; McCormick, Michael; Frank, David; Trouet, Valerie; Kaplan, Jed O.; Herzig, Franz; Heussner, Karl-Uwe; Wanner, Heinz; Luterbacher, Jürg; Esper, Jan

2011-02-01

Climate variations influenced the agricultural productivity, health risk, and conflict level of preindustrial societies. Discrimination between environmental and anthropogenic impacts on past civilizations, however, remains difficult because of the paucity of high-resolution paleoclimatic evidence. We present tree ring-based reconstructions of central European summer precipitation and temperature variability over the past 2500 years. Recent warming is unprecedented, but modern hydroclimatic variations may have at times been exceeded in magnitude and duration. Wet and warm summers occurred during periods of Roman and medieval prosperity. Increased climate variability from ~250 to 600 C.E. coincided with the demise of the western Roman Empire and the turmoil of the Migration Period. Such historical data may provide a basis for counteracting the recent political and fiscal reluctance to mitigate projected climate change.

Using non-systematic surveys to investigate effects of regional climate variability on Australasian gannets in the Hauraki Gulf, New Zealand

NASA Astrophysics Data System (ADS)

Srinivasan, Mridula; Dassis, Mariela; Benn, Emily; Stockin, Karen A.; Martinez, Emmanuelle; Machovsky-Capuska, Gabriel E.

2015-05-01

Few studies have investigated regional and natural climate variability on seabird populations using ocean reanalysis datasets (e.g. Simple Ocean Data Assimilation (SODA)) that integrate atmospheric information to supplement ocean observations and provide improved estimates of ocean conditions. Herein we use a non-systematic dataset on Australasian gannets (Morus serrator) from 2001 to 2009 to identify potential connections between Gannet Sightings Per Unit Effort (GSPUE) and climate and oceanographic variability in a region of known importance for breeding seabirds, the Hauraki Gulf (HG), New Zealand. While no statistically significant relationships between GSPUE and global climate indices were determined, there was a significant correlation between GSPUE and regional SST anomaly for HG. Also, there appears to be a strong link between global climate indices and regional climate in the HG. Further, based on cross-correlation function coefficients and lagged multiple regression models, we identified potential leading and lagging climate variables, and climate variables but with limited predictive capacity in forecasting future GSPUE. Despite significant inter-annual variability and marginally cooler SSTs since 2001, gannet sightings appear to be increasing. We hypothesize that at present underlying physical changes in the marine ecosystem may be insufficient to affect supply of preferred gannet main prey (pilchard Sardinops spp.), which tolerate a wide thermal range. Our study showcases the potential scientific value of lengthy non-systematic data streams and when designed properly (i.e., contain abundance, flock size, and spatial data), can yield useful information in climate impact studies on seabirds and other marine fauna. Such information can be invaluable for enhancing conservation measures for protected species in fiscally constrained research environments.

Incorporating abundance information and guiding variable selection for climate-based ensemble forecasting of species' distributional shifts.

PubMed

Tanner, Evan P; Papeş, Monica; Elmore, R Dwayne; Fuhlendorf, Samuel D; Davis, Craig A

2017-01-01

Ecological niche models (ENMs) have increasingly been used to estimate the potential effects of climate change on species' distributions worldwide. Recently, predictions of species abundance have also been obtained with such models, though knowledge about the climatic variables affecting species abundance is often lacking. To address this, we used a well-studied guild (temperate North American quail) and the Maxent modeling algorithm to compare model performance of three variable selection approaches: correlation/variable contribution (CVC), biological (i.e., variables known to affect species abundance), and random. We then applied the best approach to forecast potential distributions, under future climatic conditions, and analyze future potential distributions in light of available abundance data and presence-only occurrence data. To estimate species' distributional shifts we generated ensemble forecasts using four global circulation models, four representative concentration pathways, and two time periods (2050 and 2070). Furthermore, we present distributional shifts where 75%, 90%, and 100% of our ensemble models agreed. The CVC variable selection approach outperformed our biological approach for four of the six species. Model projections indicated species-specific effects of climate change on future distributions of temperate North American quail. The Gambel's quail (Callipepla gambelii) was the only species predicted to gain area in climatic suitability across all three scenarios of ensemble model agreement. Conversely, the scaled quail (Callipepla squamata) was the only species predicted to lose area in climatic suitability across all three scenarios of ensemble model agreement. Our models projected future loss of areas for the northern bobwhite (Colinus virginianus) and scaled quail in portions of their distributions which are currently areas of high abundance. Climatic variables that influence local abundance may not always scale up to influence species' distributions. Special attention should be given to selecting variables for ENMs, and tests of model performance should be used to validate the choice of variables.

Global variation in thermal tolerances and vulnerability of endotherms to climate change

PubMed Central

Khaliq, Imran; Hof, Christian; Prinzinger, Roland; Böhning-Gaese, Katrin; Pfenninger, Markus

2014-01-01

The relationships among species' physiological capacities and the geographical variation of ambient climate are of key importance to understanding the distribution of life on the Earth. Furthermore, predictions of how species will respond to climate change will profit from the explicit consideration of their physiological tolerances. The climatic variability hypothesis, which predicts that climatic tolerances are broader in more variable climates, provides an analytical framework for studying these relationships between physiology and biogeography. However, direct empirical support for the hypothesis is mostly lacking for endotherms, and few studies have tried to integrate physiological data into assessments of species' climatic vulnerability at the global scale. Here, we test the climatic variability hypothesis for endotherms, with a comprehensive dataset on thermal tolerances derived from physiological experiments, and use these data to assess the vulnerability of species to projected climate change. We find the expected relationship between thermal tolerance and ambient climatic variability in birds, but not in mammals—a contrast possibly resulting from different adaptation strategies to ambient climate via behaviour, morphology or physiology. We show that currently most of the species are experiencing ambient temperatures well within their tolerance limits and that in the future many species may be able to tolerate projected temperature increases across significant proportions of their distributions. However, our findings also underline the high vulnerability of tropical regions to changes in temperature and other threats of anthropogenic global changes. Our study demonstrates that a better understanding of the interplay among species' physiology and the geography of climate change will advance assessments of species' vulnerability to climate change. PMID:25009066

Towards multi-resolution global climate modeling with ECHAM6-FESOM. Part II: climate variability

NASA Astrophysics Data System (ADS)

Rackow, T.; Goessling, H. F.; Jung, T.; Sidorenko, D.; Semmler, T.; Barbi, D.; Handorf, D.

2018-04-01

This study forms part II of two papers describing ECHAM6-FESOM, a newly established global climate model with a unique multi-resolution sea ice-ocean component. While part I deals with the model description and the mean climate state, here we examine the internal climate variability of the model under constant present-day (1990) conditions. We (1) assess the internal variations in the model in terms of objective variability performance indices, (2) analyze variations in global mean surface temperature and put them in context to variations in the observed record, with particular emphasis on the recent warming slowdown, (3) analyze and validate the most common atmospheric and oceanic variability patterns, (4) diagnose the potential predictability of various climate indices, and (5) put the multi-resolution approach to the test by comparing two setups that differ only in oceanic resolution in the equatorial belt, where one ocean mesh keeps the coarse 1° resolution applied in the adjacent open-ocean regions and the other mesh is gradually refined to 0.25°. Objective variability performance indices show that, in the considered setups, ECHAM6-FESOM performs overall favourably compared to five well-established climate models. Internal variations of the global mean surface temperature in the model are consistent with observed fluctuations and suggest that the recent warming slowdown can be explained as a once-in-one-hundred-years event caused by internal climate variability; periods of strong cooling in the model (`hiatus' analogs) are mainly associated with ENSO-related variability and to a lesser degree also to PDO shifts, with the AMO playing a minor role. Common atmospheric and oceanic variability patterns are simulated largely consistent with their real counterparts. Typical deficits also found in other models at similar resolutions remain, in particular too weak non-seasonal variability of SSTs over large parts of the ocean and episodic periods of almost absent deep-water formation in the Labrador Sea, resulting in overestimated North Atlantic SST variability. Concerning the influence of locally (isotropically) increased resolution, the ENSO pattern and index statistics improve significantly with higher resolution around the equator, illustrating the potential of the novel unstructured-mesh method for global climate modeling.

Using physiology to understand climate-driven changes in disease and their implications for conservation.

PubMed

Rohr, Jason R; Raffel, Thomas R; Blaustein, Andrew R; Johnson, Pieter T J; Paull, Sara H; Young, Suzanne

2013-01-01

Controversy persists regarding the contributions of climate change to biodiversity losses, through its effects on the spread and emergence of infectious diseases. One of the reasons for this controversy is that there are few mechanistic studies that explore the links among climate change, infectious disease, and declines of host populations. Given that host-parasite interactions are generally mediated by physiological responses, we submit that physiological models could facilitate the prediction of how host-parasite interactions will respond to climate change, and might offer theoretical and terminological cohesion that has been lacking in the climate change-disease literature. We stress that much of the work on how climate influences host-parasite interactions has emphasized changes in climatic means, despite a hallmark of climate change being changes in climatic variability and extremes. Owing to this gap, we highlight how temporal variability in weather, coupled with non-linearities in responses to mean climate, can be used to predict the effects of climate on host-parasite interactions. We also discuss the climate variability hypothesis for disease-related declines, which posits that increased unpredictable temperature variability might provide a temporary advantage to pathogens because they are smaller and have faster metabolisms than their hosts, allowing more rapid acclimatization following a temperature shift. In support of these hypotheses, we provide case studies on the role of climatic variability in host population declines associated with the emergence of the infectious diseases chytridiomycosis, withering syndrome, and malaria. Finally, we present a mathematical model that provides the scaffolding to integrate metabolic theory, physiological mechanisms, and large-scale spatiotemporal processes to predict how simultaneous changes in climatic means, variances, and extremes will affect host-parasite interactions. However, several outstanding questions remain to be answered before investigators can accurately predict how changes in climatic means and variances will affect infectious diseases and the conservation status of host populations.

Using physiology to understand climate-driven changes in disease and their implications for conservation

PubMed Central

Rohr, Jason R.; Raffel, Thomas R.; Blaustein, Andrew R.; Johnson, Pieter T. J.; Paull, Sara H.; Young, Suzanne

2013-01-01

Controversy persists regarding the contributions of climate change to biodiversity losses, through its effects on the spread and emergence of infectious diseases. One of the reasons for this controversy is that there are few mechanistic studies that explore the links among climate change, infectious disease, and declines of host populations. Given that host–parasite interactions are generally mediated by physiological responses, we submit that physiological models could facilitate the prediction of how host–parasite interactions will respond to climate change, and might offer theoretical and terminological cohesion that has been lacking in the climate change–disease literature. We stress that much of the work on how climate influences host–parasite interactions has emphasized changes in climatic means, despite a hallmark of climate change being changes in climatic variability and extremes. Owing to this gap, we highlight how temporal variability in weather, coupled with non-linearities in responses to mean climate, can be used to predict the effects of climate on host–parasite interactions. We also discuss the climate variability hypothesis for disease-related declines, which posits that increased unpredictable temperature variability might provide a temporary advantage to pathogens because they are smaller and have faster metabolisms than their hosts, allowing more rapid acclimatization following a temperature shift. In support of these hypotheses, we provide case studies on the role of climatic variability in host population declines associated with the emergence of the infectious diseases chytridiomycosis, withering syndrome, and malaria. Finally, we present a mathematical model that provides the scaffolding to integrate metabolic theory, physiological mechanisms, and large-scale spatiotemporal processes to predict how simultaneous changes in climatic means, variances, and extremes will affect host–parasite interactions. However, several outstanding questions remain to be answered before investigators can accurately predict how changes in climatic means and variances will affect infectious diseases and the conservation status of host populations. PMID:27293606

Evidence for lower plasticity in CTMAX at warmer developmental temperatures.

PubMed

Kellermann, Vanessa; Sgrò, Carla M

2018-06-07

Understanding the capacity for different species to reduce their susceptibility to climate change via phenotypic plasticity is essential for accurately predicting species extinction risk. The climatic variability hypothesis suggests that spatial and temporal variation in climatic variables should select for more plastic phenotypes. However, empirical support for this hypothesis is limited. Here, we examine the capacity for ten Drosophila species to increase their critical thermal maxima (CT MAX ) through developmental acclimation and/or adult heat hardening. Using four fluctuating developmental temperature regimes, ranging from 13 to 33 °C, we find that most species can increase their CT MAX via developmental acclimation and adult hardening, but found no relationship between climatic variables and absolute measures of plasticity. However, when plasticity was dissected across developmental temperatures, a positive association between plasticity and one measure of climatic variability (temperature seasonality) was found when development took place between 26 and 28 °C, whereas a negative relationship was found when development took place between 20 and 23 °C. In addition, a decline in CT MAX and egg-to-adult viability, a proxy for fitness, was observed in tropical species at the warmer developmental temperatures (26-28 °C); this suggests that tropical species may be at even greater risk from climate change than currently predicted. The combined effects of developmental acclimation and adult hardening on CT MAX were small, contributing to a <0.60 °C shift in CT MAX . Although small shifts in CT MAX may increase population persistence in the shorter term, the degree to which they can contribute to meaningful responses in the long term is unclear. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches

PubMed Central

Delerce, Sylvain; Dorado, Hugo; Grillon, Alexandre; Rebolledo, Maria Camila; Prager, Steven D.; Patiño, Victor Hugo; Garcés Varón, Gabriel; Jiménez, Daniel

2016-01-01

Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily weather series. Using Conditional Inference Forest and clustering techniques, we assessed the relationships between climatic factors and crop yield variability at the local scale for specific cultivars and growth stages. The analysis showed clear relationships in the various location-cultivar combinations, with climatic factors explaining 6 to 46% of spatiotemporal variability in yield, and with crop responses to weather being non-linear and cultivar-specific. Climatic factors affected cultivars differently during each stage of development. For instance, one cultivar was affected by high nighttime temperatures in the reproductive stage but responded positively to accumulated solar radiation during the ripening stage. Another was affected by high nighttime temperatures during both the vegetative and reproductive stages. Clustering of the weather patterns corresponding to individual cropping events revealed different groups of weather patterns for irrigated and rainfed systems with contrasting yield levels. Best-suited cultivars were identified for some weather patterns, making weather-site-specific recommendations possible. This study illustrates the potential of data mining for adding value to existing observational data in agriculture by allowing embedded knowledge to be quickly leveraged. It generates site-specific information on cultivar response to climatic factors and supports on-farm management decisions for adaptation to climate variability. PMID:27560980

Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches.

PubMed

Delerce, Sylvain; Dorado, Hugo; Grillon, Alexandre; Rebolledo, Maria Camila; Prager, Steven D; Patiño, Victor Hugo; Garcés Varón, Gabriel; Jiménez, Daniel

2016-01-01

Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily weather series. Using Conditional Inference Forest and clustering techniques, we assessed the relationships between climatic factors and crop yield variability at the local scale for specific cultivars and growth stages. The analysis showed clear relationships in the various location-cultivar combinations, with climatic factors explaining 6 to 46% of spatiotemporal variability in yield, and with crop responses to weather being non-linear and cultivar-specific. Climatic factors affected cultivars differently during each stage of development. For instance, one cultivar was affected by high nighttime temperatures in the reproductive stage but responded positively to accumulated solar radiation during the ripening stage. Another was affected by high nighttime temperatures during both the vegetative and reproductive stages. Clustering of the weather patterns corresponding to individual cropping events revealed different groups of weather patterns for irrigated and rainfed systems with contrasting yield levels. Best-suited cultivars were identified for some weather patterns, making weather-site-specific recommendations possible. This study illustrates the potential of data mining for adding value to existing observational data in agriculture by allowing embedded knowledge to be quickly leveraged. It generates site-specific information on cultivar response to climatic factors and supports on-farm management decisions for adaptation to climate variability.

Changes in field workability and drought risk from projected climate change drive spatially variable risks in Illinois cropping systems.

PubMed

Tomasek, Bradley J; Williams, Martin M; Davis, Adam S

2017-01-01

As weather patterns become more volatile and extreme, risks introduced by weather variability will become more critical to agricultural production. The availability of days suitable for field work is driven by soil temperature and moisture, both of which may be altered by climate change. We projected changes in Illinois season length, spring field workability, and summer drought risk under three different emissions scenarios (B1, A1B, and A2) down to the crop district scale. Across all scenarios, thermal time units increased in parallel with a longer frost-free season. An increase in late March and Early April field workability was consistent across scenarios, but a decline in overall April through May workable days was observed for many cases. In addition, summer drought metrics were projected to increase for most scenarios. These results highlight how the spatial and temporal variability in climate change may present unique challenges to mitigation and adaptation efforts.

Climate, water use, and land surface transformation in an irrigation intensive watershed - streamflow responses from 1950 through 2010

USGS Publications Warehouse

Dale, Joseph; Zou, Chris B.; Andrews, William J.; Long, James M.; Liang, Ye; Qiao, Lei

2015-01-01

Climatic variability and land surface change have a wide range of effects on streamflow and are often difficult to separate. We analyzed long-term records of climate, land use and land cover, and re-constructed the water budget based on precipitation, groundwater levels, and water use from 1950 through 2010 in the Cimarron–Skeleton watershed and a portion of the Cimarron–Eagle Chief watershed in Oklahoma, an irrigation-intensive agricultural watershed in the Southern Great Plains, USA. Our results show that intensive irrigation through alluvial aquifer withdrawal modifies climatic feedback and alters streamflow response to precipitation. Increase in consumptive water use was associated with decreases in annual streamflow, while returning croplands to non-irrigated grasslands was associated with increases in streamflow. Along with groundwater withdrawal, anthropogenic-induced factors and activities contributed nearly half to the observed variability of annual streamflow. Streamflow was more responsive to precipitation during the period of intensive irrigation between 1965 and 1984 than the period of relatively lower water use between 1985 and 2010. The Cimarron River is transitioning from a historically flashy river to one that is more stable with a lower frequency of both high and low flow pulses, a higher baseflow, and an increased median flow due in part to the return of cropland to grassland. These results demonstrated the interrelationship among climate, land use, groundwater withdrawal and streamflow regime and the potential to design agricultural production systems and adjust irrigation to mitigate impact of increasing climate variability on streamflow in irrigation intensive agricultural watershed.

Climate SPHINX: High-resolution present-day and future climate simulations with an improved representation of small-scale variability

NASA Astrophysics Data System (ADS)

Davini, Paolo; von Hardenberg, Jost; Corti, Susanna; Subramanian, Aneesh; Weisheimer, Antje; Christensen, Hannah; Juricke, Stephan; Palmer, Tim

2016-04-01

The PRACE Climate SPHINX project investigates the sensitivity of climate simulations to model resolution and stochastic parameterization. The EC-Earth Earth-System Model is used to explore the impact of stochastic physics in 30-years climate integrations as a function of model resolution (from 80km up to 16km for the atmosphere). The experiments include more than 70 simulations in both a historical scenario (1979-2008) and a climate change projection (2039-2068), using RCP8.5 CMIP5 forcing. A total amount of 20 million core hours will be used at end of the project (March 2016) and about 150 TBytes of post-processed data will be available to the climate community. Preliminary results show a clear improvement in the representation of climate variability over the Euro-Atlantic following resolution increase. More specifically, the well-known atmospheric blocking negative bias over Europe is definitely resolved. High resolution runs also show improved fidelity in representation of tropical variability - such as the MJO and its propagation - over the low resolution simulations. It is shown that including stochastic parameterization in the low resolution runs help to improve some of the aspects of the MJO propagation further. These findings show the importance of representing the impact of small scale processes on the large scale climate variability either explicitly (with high resolution simulations) or stochastically (in low resolution simulations).

Potential Impact of North Atlantic Climate Variability on Ocean Biogeochemical Processes

NASA Astrophysics Data System (ADS)

Liu, Y.; Muhling, B.; Lee, S. K.; Muller-Karger, F. E.; Enfield, D. B.; Lamkin, J. T.; Roffer, M. A.

2016-02-01

Previous studies have shown that upper ocean circulations largely determine primary production in the euphotic layers, here the global ocean model with biogeochemistry (GFDL's Modular Ocean Model with TOPAZ biogeochemistry) forced with the ERA-Interim is used to simulate the natural variability of biogeochemical processes in global ocean during 1979-present. Preliminary results show that the surface chlorophyll is overall underestimated in MOM-TOPAZ, but its spatial pattern is fairly realistic. Relatively high chlorophyll variability is shown in the subpolar North Atlantic, northeastern tropical Atlantic, and equatorial Atlantic. Further analysis suggests that the chlorophyll variability in the North Atlantic Ocean is affected by long-term climate variability. For the subpolar North Atlantic region, the chlorophyll variability is light-limited and is significantly correlated with North Atlantic Oscillation. A dipole pattern of chlorophyll variability is found between the northeastern tropical Atlantic and equatorial Atlantic. For the northeastern North Atlantic, the chlorophyll variability is significantly correlated with Atlantic Meridional Mode (AMM) and Atlantic Multidecadal Oscillation (AMO). During the negative phase of AMM and AMO, the increased trade wind in the northeast North Atlantic can lead to increased upwelling of nutrients. In the equatorial Atlantic region, the chlorophyll variability is largely link to Atlantic-Niño and associated equatorial upwelling of nutrients. The potential impact of climate variability on the distribution of pelagic fishes (i.e. yellowfin tuna) are discussed.

New climate change scenarios for the Netherlands.

PubMed

van den Hurk, B; Tank, A K; Lenderink, G; Ulden, A van; Oldenborgh, G J van; Katsman, C; Brink, H van den; Keller, F; Bessembinder, J; Burgers, G; Komen, G; Hazeleger, W; Drijfhout, S

2007-01-01

A new set of climate change scenarios for 2050 for the Netherlands was produced recently. The scenarios span a wide range of possible future climate conditions, and include climate variables that are of interest to a broad user community. The scenario values are constructed by combining output from an ensemble of recent General Climate Model (GCM) simulations, Regional Climate Model (RCM) output, meteorological observations and a touch of expert judgment. For temperature, precipitation, potential evaporation and wind four scenarios are constructed, encompassing ranges of both global mean temperature rise in 2050 and the strength of the response of the dominant atmospheric circulation in the area of interest to global warming. For this particular area, wintertime precipitation is seen to increase between 3.5 and 7% per degree global warming, but mean summertime precipitation shows opposite signs depending on the assumed response of the circulation regime. Annual maximum daily mean wind speed shows small changes compared to the observed (natural) variability of this variable. Sea level rise in the North Sea in 2100 ranges between 35 and 85 cm. Preliminary assessment of the impact of the new scenarios on water management and coastal defence policies indicate that particularly dry summer scenarios and increased intensity of extreme daily precipitation deserves additional attention in the near future.

Sometimes processes don't matter: the general effect of short term climate variability on erosional systems.

NASA Astrophysics Data System (ADS)

Deal, Eric; Braun, Jean

2017-04-01

Climatic forcing undoubtedly plays an important role in shaping the Earth's surface. However, precisely how climate affects erosion rates, landscape morphology and the sedimentary record is highly debated. Recently there has been a focus on the influence of short-term variability in rainfall and river discharge on the relationship between climate and erosion rates. Here, we present a simple probabilistic argument, backed by modelling, that demonstrates that the way the Earth's surface responds to short-term climatic forcing variability is primarily determined by the existence and magnitude of erosional thresholds. We find that it is the ratio between the threshold magnitude and the mean magnitude of climatic forcing that determines whether variability matters or not and in which way. This is a fundamental result that applies regardless of the nature of the erosional process. This means, for example, that we can understand the role that discharge variability plays in determining fluvial erosion efficiency despite doubts about the processes involved in fluvial erosion. We can use this finding to reproduce the main conclusions of previous studies on the role of discharge variability in determining long-term fluvial erosion efficiency. Many aspects of the landscape known to influence discharge variability are affected by human activity, such as land use and river damming. Another important control on discharge variability, rainfall intensity, is also expected to increase with warmer temperatures. Among many other implications, our findings help provide a general framework to understand and predict the response of the Earth's surface to changes in mean and variability of rainfall and river discharge associated with the anthropogenic activity. In addition, the process independent nature of our findings suggest that previous work on river discharge variability and erosion thresholds can be applied to other erosional systems.

Climate Variability and Oceanographic Settings Associated with Interannual Variability in the Initiation of Dinophysis acuminata Blooms

PubMed Central

Díaz, Patricio A.; Reguera, Beatriz; Ruiz-Villarreal, Manuel; Pazos, Yolanda; Velo-Suárez, Lourdes; Berger, Henrick; Sourisseau, Marc

2013-01-01

In 2012, there were exceptional blooms of D. acuminata in early spring in what appeared to be a mesoscale event affecting Western Iberia and the Bay of Biscay. The objective of this work was to identify common climatic patterns to explain the observed anomalies in two important aquaculture sites, the Galician Rías Baixas (NW Spain) and Arcachon Bay (SW France). Here, we examine climate variability through physical-biological couplings, Sea Surface Temperature (SST) anomalies and time of initiation of the upwelling season and its intensity over several decades. In 2012, the mesoscale features common to the two sites were positive anomalies in SST and unusual wind patterns. These led to an atypical predominance of upwelling in winter in the Galician Rías, and increased haline stratification associated with a southward advection of the Gironde plume in Arcachon Bay. Both scenarios promoted an early phytoplankton growth season and increased stability that enhanced D. acuminata growth. Therefore, a common climate anomaly caused exceptional blooms of D. acuminata in two distant regions through different triggering mechanisms. These results increase our capability to predict intense diarrhetic shellfish poisoning outbreaks in the early spring from observations in the preceding winter. PMID:23959151

Modelling spatial and temporal vegetation variability with the Climate Constrained Vegetation Index: evidence of CO2 fertilisation and of water stress in continental interiors

NASA Astrophysics Data System (ADS)

Los, S. O.

2015-06-01

A model was developed to simulate spatial, seasonal and interannual variations in vegetation in response to temperature, precipitation and atmospheric CO2 concentrations; the model addresses shortcomings in current implementations. The model uses the minimum of 12 temperature and precipitation constraint functions to simulate NDVI. Functions vary based on the Köppen-Trewartha climate classification to take adaptations of vegetation to climate into account. The simulated NDVI, referred to as the climate constrained vegetation index (CCVI), captured the spatial variability (0.82 < r <0.87), seasonal variability (median r = 0.83) and interannual variability (median global r = 0.24) in NDVI. The CCVI simulated the effects of adverse climate on vegetation during the 1984 drought in the Sahel and during dust bowls of the 1930s and 1950s in the Great Plains in North America. A global CO2 fertilisation effect was found in NDVI data, similar in magnitude to that of earlier estimates (8 % for the 20th century). This effect increased linearly with simple ratio, a transformation of the NDVI. Three CCVI scenarios, based on climate simulations using the representative concentration pathway RCP4.5, showed a greater sensitivity of vegetation towards precipitation in Northern Hemisphere mid latitudes than is currently implemented in climate models. This higher sensitivity is of importance to assess the impact of climate variability on vegetation, in particular on agricultural productivity.

Simulation of climate change in San Francisco Bay Basins, California: Case studies in the Russian River Valley and Santa Cruz Mountains

USGS Publications Warehouse

Flint, Lorraine E.; Flint, Alan L.

2012-01-01

As a result of ongoing changes in climate, hydrologic and ecologic effects are being seen across the western United States. A regional study of how climate change affects water resources and habitats in the San Francisco Bay area relied on historical climate data and future projections of climate, which were downscaled to fine spatial scales for application to a regional water-balance model. Changes in climate, potential evapotranspiration, recharge, runoff, and climatic water deficit were modeled for the Bay Area. In addition, detailed studies in the Russian River Valley and Santa Cruz Mountains, which are on the northern and southern extremes of the Bay Area, respectively, were carried out in collaboration with local water agencies. Resource managers depend on science-based projections to inform planning exercises that result in competent adaptation to ongoing and future changes in water supply and environmental conditions. Results indicated large spatial variability in climate change and the hydrologic response across the region; although there is warming under all projections, potential change in precipitation by the end of the 21st century differed according to model. Hydrologic models predicted reduced early and late wet season runoff for the end of the century for both wetter and drier future climate projections, which could result in an extended dry season. In fact, summers are projected to be longer and drier in the future than in the past regardless of precipitation trends. While water supply could be subject to increased variability (that is, reduced reliability) due to greater variability in precipitation, water demand is likely to steadily increase because of increased evapotranspiration rates and climatic water deficit during the extended summers. Extended dry season conditions and the potential for drought, combined with unprecedented increases in precipitation, could serve as additional stressors on water quality and habitat. By focusing on the relationship between soil moisture storage and evapotranspiration pressures, climatic water deficit integrates the effects of increasing temperature and varying precipitation on basin conditions. At the fine-scale used for these analyses, this variable is an effective indicator of the areas in the landscape that are the most resilient or vulnerable to projected changes. These analyses have shown that regardless of the direction of precipitation change, climatic water deficit is projected to increase, which implies greater water demand to maintain current agricultural resources or land cover. Fine-scale modeling provides a spatially distributed view of locations in the landscape that could prove to be resilient to climatic changes in contrast to locations where vegetation is currently living on the edge of its present-day bioclimatic distribution and, therefore, is more likely to perish or shift to other dominant species under future warming. This type of modeling and the associated analyses provide a useful means for greater understanding of water and land resources, which can lead to better resource management and planning.

­Weather and climate change drivers of agricultural pesticide use in the US

NASA Astrophysics Data System (ADS)

Larsen, A.; Deschenes, O.

2016-12-01

Agricultural pesticides have numerous negative consequences for human and environmental health due to direct exposure, and associated air pollution, water contamination and biodiversity losses. As such, understanding the abiotic and biotic drivers of pesticide variability is a scientific and policy priority. Temperature is a direct determinant of insect pest development rates, and as such, it is anticipated that insect pest damage and insecticide use will increase in a warmer climate. Yet, the complexity of plant-insect interactions, diversity of crop growing regions, and uncertainty of climate forecasts have hampered predictions regarding where and to what degree climate change may alter insecticide use. Here we use a county-level, panel data set including the USDA Census of Agriculture and the National Climatic Data Center (NCDC) Global Historical Climatology Network-Daily (GHCN-Daily) for 1987-2012 to statistically evaluate how a rich set of weather variables (e.g. degree days, frosts, precipitation) affect current insecticide use patterns in the continental US. Using climate predictions from National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM) we then estimate how different climate change emissions scenarios (i.e. A2, B1) are likely to impact insecticide use in different agricultural regions of the US. We find an increase in growing season temperature (degree days) leads to an increase in insecticides on average, and in most regions of the US. However, our results indicate that the effect of a warm year is heterogeneous in time with, for example, a warm January leading to a more consistent increase in insecticides than a warm July. Therefore, we estimate that while future climate change will lead to an overall increase in insecticide use, the degree to which that increase materializes will depend on how warming manifests during the year.

Application of scenario-neutral methods to quantify impacts of climate change on water resources in East Africa

NASA Astrophysics Data System (ADS)

Ascott, M.; Macdonald, D.; Lapworth, D.; Tindimugaya, C.

2017-12-01

Quantification of the impact of climate change on water resources is essential for future resource planning. Unfortunately, climate change impact studies in African regions are often hindered by the extent in variability in future rainfall predictions, which also diverge from current drying trends. To overcome this limitation, "scenario-neutral" methods have been developed which stress a hydrological system using a wide range of climate futures to build a "climate response surface". We developed a hydrological model and scenario-neutral framework to quantify climate change impacts on river flows in the Katonga catchment, Uganda. Using the lumped catchment model GR4J, an acceptable calibration to historic daily flows (1966 - 2010, NSE = 0.69) was achieved. Using a delta change approach, we then systematically changed rainfall and PET inputs to develop response surfaces for key metrics, developed with Ugandan water resources planners (e.g. Q5, Q95). Scenarios from the CMIP5 models for 2030s and 2050s were then overlain on the response surface. The CMIP5 scenarios show consistent increases in temperature but large variability in rainfall increases, which results in substantial variability in increases in river flows. The developed response surface covers a wide range of climate futures beyond the CMIP5 projections, and can help water resources planners understand the sensitivity of water resource systems to future changes. When future climate scenarios are available, these can be directly overlain on the response surface without the need to re-run the hydrological model. Further work will consider using scenario-neutral approaches in more complex, semi-distributed models (e.g. SWAT), and will consider land use and socioeconomic change.

Climate change hampers endangered species through intensified moisture-related plant stresses

NASA Astrophysics Data System (ADS)

(Ruud) Bartholomeus, R. P.; (Flip) Witte, J. P. M.; (Peter) van Bodegom, P. M.; (Jos) van Dam, J. C.; (Rien) Aerts, R.

2010-05-01

With recent climate change, extremes in meteorological conditions are forecast and observed to increase globally, and to affect vegetation composition. More prolonged dry periods will alternate with more intensive rainfall events, both within and between years, which will change soil moisture dynamics. In temperate climates, soil moisture, in concert with nutrient availability and soil acidity, is the most important environmental filter in determining local plant species composition, as it determines the availability of both oxygen and water to plant roots. These resources are indispensable for meeting the physiological demands of plants. The consequences of climate change for our natural environment are among the most pressing issues of our time. The international research community is beginning to realise that climate extremes may be more powerful drivers of vegetation change and species extinctions than slow-and-steady climatic changes, but the causal mechanisms of such changes are presently unknown. The roles of amplitudes in water availability as drivers of vegetation change have been particularly elusive owing to the lack of integration of the key variables involved. Here we show that the combined effect of increased rainfall variability, temperature and atmospheric CO2-concentration will lead to an increased variability in both wet and dry extremes in stresses faced by plants (oxygen and water stress, respectively). We simulated these plant stresses with a novel, process-based approach, incorporating in detail the interacting processes in the soil-plant-atmosphere interface. In order to quantify oxygen and water stress with causal measures, we focused on interacting meteorological, soil physical, microbial, and plant physiological processes in the soil-plant-atmosphere system. The first physiological process inhibited at high soil moisture contents is plant root respiration, i.e. oxygen consumption in the roots, which responds to increased temperatures. High soil moisture contents hamper oxygen transport from the atmosphere, through the soil - where part of the oxygen additionally disappears by soil microbial oxygen consumption - and to the root cells. Reduced respiration negatively affects the energy supply to plant metabolism. Plant transpiration, which responds to increased temperatures and atmospheric CO2-concentrations, is the first physiological process that will be inhibited by low soil moisture contents, negatively affecting both photosynthesis and cooling. As both the supply and demand of oxygen and water depend strongly on the prevailing meteorological conditions, both oxygen and water stress were calculated dynamically in time to capture climate change effects. We demonstrate that increased rainfall variability in interaction with predicted changes in temperature and CO2, affects soil moisture conditions and plant oxygen and water demands such, that both oxygen stress and water stress will intensify due to climate change. Moreover, these stresses will increasingly coincide, causing variable stress conditions. These variable stress conditions were found to decrease future habitat suitability, especially for plant species that are presently endangered. The future existence of such species is thus at risk by climate change, which has direct implications for policies to maintain endangered species, as applied by international nature management organisations (e.g. IUCN). Our integrated mechanistic analysis of two stresses combined, which has never been done so far, reveals large impacts of climate change on species extinctions and thereby on biodiversity.

Temperate Mountain Forest Biodiversity under Climate Change: Compensating Negative Effects by Increasing Structural Complexity

PubMed Central

Braunisch, Veronika; Coppes, Joy; Arlettaz, Raphaël; Suchant, Rudi; Zellweger, Florian; Bollmann, Kurt

2014-01-01

Species adapted to cold-climatic mountain environments are expected to face a high risk of range contractions, if not local extinctions under climate change. Yet, the populations of many endothermic species may not be primarily affected by physiological constraints, but indirectly by climate-induced changes of habitat characteristics. In mountain forests, where vertebrate species largely depend on vegetation composition and structure, deteriorating habitat suitability may thus be mitigated or even compensated by habitat management aiming at compositional and structural enhancement. We tested this possibility using four cold-adapted bird species with complementary habitat requirements as model organisms. Based on species data and environmental information collected in 300 1-km2 grid cells distributed across four mountain ranges in central Europe, we investigated (1) how species’ occurrence is explained by climate, landscape, and vegetation, (2) to what extent climate change and climate-induced vegetation changes will affect habitat suitability, and (3) whether these changes could be compensated by adaptive habitat management. Species presence was modelled as a function of climate, landscape and vegetation variables under current climate; moreover, vegetation-climate relationships were assessed. The models were extrapolated to the climatic conditions of 2050, assuming the moderate IPCC-scenario A1B, and changes in species’ occurrence probability were quantified. Finally, we assessed the maximum increase in occurrence probability that could be achieved by modifying one or multiple vegetation variables under altered climate conditions. Climate variables contributed significantly to explaining species occurrence, and expected climatic changes, as well as climate-induced vegetation trends, decreased the occurrence probability of all four species, particularly at the low-altitudinal margins of their distribution. These effects could be partly compensated by modifying single vegetation factors, but full compensation would only be achieved if several factors were changed in concert. The results illustrate the possibilities and limitations of adaptive species conservation management under climate change. PMID:24823495

Temperate mountain forest biodiversity under climate change: compensating negative effects by increasing structural complexity.

PubMed

Braunisch, Veronika; Coppes, Joy; Arlettaz, Raphaël; Suchant, Rudi; Zellweger, Florian; Bollmann, Kurt

2014-01-01

Species adapted to cold-climatic mountain environments are expected to face a high risk of range contractions, if not local extinctions under climate change. Yet, the populations of many endothermic species may not be primarily affected by physiological constraints, but indirectly by climate-induced changes of habitat characteristics. In mountain forests, where vertebrate species largely depend on vegetation composition and structure, deteriorating habitat suitability may thus be mitigated or even compensated by habitat management aiming at compositional and structural enhancement. We tested this possibility using four cold-adapted bird species with complementary habitat requirements as model organisms. Based on species data and environmental information collected in 300 1-km2 grid cells distributed across four mountain ranges in central Europe, we investigated (1) how species' occurrence is explained by climate, landscape, and vegetation, (2) to what extent climate change and climate-induced vegetation changes will affect habitat suitability, and (3) whether these changes could be compensated by adaptive habitat management. Species presence was modelled as a function of climate, landscape and vegetation variables under current climate; moreover, vegetation-climate relationships were assessed. The models were extrapolated to the climatic conditions of 2050, assuming the moderate IPCC-scenario A1B, and changes in species' occurrence probability were quantified. Finally, we assessed the maximum increase in occurrence probability that could be achieved by modifying one or multiple vegetation variables under altered climate conditions. Climate variables contributed significantly to explaining species occurrence, and expected climatic changes, as well as climate-induced vegetation trends, decreased the occurrence probability of all four species, particularly at the low-altitudinal margins of their distribution. These effects could be partly compensated by modifying single vegetation factors, but full compensation would only be achieved if several factors were changed in concert. The results illustrate the possibilities and limitations of adaptive species conservation management under climate change.

Changes in Hydrological Extremes and its Relation to Climate Variability in Mountainous Watershed: A Case Study from Gandaki River Basin, Nepal

NASA Astrophysics Data System (ADS)

Shrestha, N. S.; Dahal, P.

2016-12-01

Changes in the hydrological extreme are expected due to climate variability and are needed to assess at local and regional scales since these changes are not uniform over the globe. This study analyses the changes in intensity, frequency and persistence hydrological extreme in Gandaki River Basin (GRB) Nepal over past and future and its relation to climate variability. Hydrological data of 12 different hydrological stations covering all the sub basins of Gandaki River Basin were analyzed. At least 1 hydrological station in each sub basin to the maximum of 3 was taken into consideration for this study. Results show that hydrological extreme have increased in intensity, frequency and persistence over recent year and are predicted to increase in future (2030-2060). The time-series analysis revealed an increase in the magnitude, frequency and duration of flood and drought. The instantaneous maximum flow, flood events and duration of flood events are found to have increasing trend. The minimum discharge was observed to be decreasing which entails that the water availability in the driest time is decreasing. Trend analysis of seasonal flow revealed an increase in monsoon flows and decreasing in post monsoon. Changes in climate variability over the same period shows higher anomalies in both temperature and precipitation in recent decades (1990s and 2000s) compared to the baseline period (1970-2000). Model suggests an increasing trend in annual flows with the increase more pronounced in 2060s. Significant increase in extreme flows and subsequent decrease in dependable flows suggest increase in frequency of isolated extreme flows followed by prolonged dry spells. Data also showed that the mean temperature will be increasing from 1.9 0C to 3.1 0C and precipitation will be changing by -8% to +12% in 2031-2060 compared to the baseline period. For long-term planning and management of water resources, current trend and future change in the pattern of water availability should be analysed well in advance. Climate change with intensifying extreme events will likely have serious consequences on the hydrological changes. Therefore, this study would be useful in understanding how the hydrological regime has been changing with climate change in mountainous watershed.

Quantitative Assessment of Antarctic Climate Variability and Change

NASA Astrophysics Data System (ADS)

Ordonez, A.; Schneider, D. P.

2013-12-01

The Antarctic climate is both extreme and highly variable, but there are indications it may be changing. As the climate in Antarctica can affect global sea level and ocean circulation, it is important to understand and monitor its behavior. Observational and model data have been used to study climate change in Antarctica and the Southern Ocean, though observational data is sparse and models have difficulty reproducing many observed climate features. For example, a leading hypothesis that ozone depletion has been responsible for sea ice trends is struggling with the inability of ozone-forced models to reproduce the observed sea ice increase. The extent to which this data-model disagreement represents inadequate observations versus model biases is unknown. This research assessed a variety of climate change indicators to present an overview of Antarctic climate that will allow scientists to easily access this data and compare indicators with other observational data and model output. Indicators were obtained from observational and reanalysis data for variables such as temperature, sea ice area, and zonal wind stress. Multiple datasets were used for key variables. Monthly and annual anomaly data from Antarctica and the Southern Ocean as well as tropical indices were plotted as time series on common axes for comparison. Trends and correlations were also computed. Zonal wind, surface temperature, and austral springtime sea ice had strong relationships and were further discussed in terms of how they may relate to climate variability and change in the Antarctic. This analysis will enable hypothesized mechanisms of Antarctic climate change to be critically evaluated.

High-resolution regional climate model evaluation using variable-resolution CESM over California

NASA Astrophysics Data System (ADS)

Huang, X.; Rhoades, A.; Ullrich, P. A.; Zarzycki, C. M.

2015-12-01

Understanding the effect of climate change at regional scales remains a topic of intensive research. Though computational constraints remain a problem, high horizontal resolution is needed to represent topographic forcing, which is a significant driver of local climate variability. Although regional climate models (RCMs) have traditionally been used at these scales, variable-resolution global climate models (VRGCMs) have recently arisen as an alternative for studying regional weather and climate allowing two-way interaction between these domains without the need for nudging. In this study, the recently developed variable-resolution option within the Community Earth System Model (CESM) is assessed for long-term regional climate modeling over California. Our variable-resolution simulations will focus on relatively high resolutions for climate assessment, namely 28km and 14km regional resolution, which are much more typical for dynamically downscaled studies. For comparison with the more widely used RCM method, the Weather Research and Forecasting (WRF) model will be used for simulations at 27km and 9km. All simulations use the AMIP (Atmospheric Model Intercomparison Project) protocols. The time period is from 1979-01-01 to 2005-12-31 (UTC), and year 1979 was discarded as spin up time. The mean climatology across California's diverse climate zones, including temperature and precipitation, is analyzed and contrasted with the Weather Research and Forcasting (WRF) model (as a traditional RCM), regional reanalysis, gridded observational datasets and uniform high-resolution CESM at 0.25 degree with the finite volume (FV) dynamical core. The results show that variable-resolution CESM is competitive in representing regional climatology on both annual and seasonal time scales. This assessment adds value to the use of VRGCMs for projecting climate change over the coming century and improve our understanding of both past and future regional climate related to fine-scale processes. This assessment is also relevant for addressing the scale limitation of current RCMs or VRGCMs when next-generation model resolution increases to ~10km and beyond.

Rainfall variability and extremes over southern Africa: assessment of a climate model to reproduce daily extremes

NASA Astrophysics Data System (ADS)

Williams, C.; Kniveton, D.; Layberry, R.

2009-04-01

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 be assessed, again by a comparison with extremes from the MIRA dataset.

Climate Change and Human Health Impacts in the United States: An Update on the Results of the U.S. National Assessment

PubMed Central

Ebi, Kristie L.; Mills, David M.; Smith, Joel B.; Grambsch, Anne

2006-01-01

The health sector component of the first U.S. National Assessment, published in 2000, synthesized the anticipated health impacts of climate variability and change for five categories of health outcomes: impacts attributable to temperature, extreme weather events (e.g., storms and floods), air pollution, water- and food-borne diseases, and vector- and rodent-borne diseases. The Health Sector Assessment (HSA) concluded that climate variability and change are likely to increase morbidity and mortality risks for several climate-sensitive health outcomes, with the net impact uncertain. The objective of this study was to update the first HSA based on recent publications that address the potential impacts of climate variability and change in the United States for the five health outcome categories. The literature published since the first HSA supports the initial conclusions, with new data refining quantitative exposure–response relationships for several health end points, particularly for extreme heat events and air pollution. The United States continues to have a very high capacity to plan for and respond to climate change, although relatively little progress has been noted in the literature on implementing adaptive strategies and measures. Large knowledge gaps remain, resulting in a substantial need for additional research to improve our understanding of how weather and climate, both directly and indirectly, can influence human health. Filling these knowledge gaps will help better define the potential health impacts of climate change and identify specific public health adaptations to increase resilience. PMID:16966082

Impacts of weather on long-term patterns of plant richness and diversity vary with location and management

USGS Publications Warehouse

Jonas, Jayne L.; Buhl, Deborah A.; Symstad, Amy J.

2015-01-01

Better understanding the influence of precipitation and temperature on plant assemblages is needed to predict the effects of climate change. Many studies have examined the relationship between plant productivity and weather (primarily precipitation), but few have directly assessed the relationship between plant richness or diversity and weather despite their increased use as metrics of ecosystem condition. We focus on the grasslands of central North America, which are characterized by high temporal climatic variability. Over the next 100 years, these grasslands are predicted to experience further increased variability in growing season precipitation, as well as increased temperatures, due to global climate change. We assess 1) the portion of interannual variability of richness and diversity explained by weather, 2) how relationships between these metrics and weather vary among plant assemblages, and 3) which aspects of weather best explain temporal variability. We used an information-theoretic approach to assess relationships between long-term plant richness and diversity patterns and a priori weather covariates using six datasets from four grasslands. Weather explained up to 49% and 63% of interannual variability in total plant species richness and diversity, respectively. However, richness and diversity responses to specific weather variables varied both among sites and among experimental treatments within sites. In general, we found many instances in which temperature was of equal or greater importance as precipitation, as well as evidence of the importance of lagged effects and precipitation or temperature variability. Although precipitation has been shown to be a key driver of productivity in grasslands, our results indicate that increasing temperatures alone, without substantial changes in precipitation patterns, could have measurable effects on Great Plains grassland plant assemblages and biodiversity metrics. Our results also suggest that richness and diversity will respond in unique ways to changing climate and management can affect these responses; additional research and monitoring will be essential for further understanding of these complex relationships.Read More: http://www.esajournals.org/doi/abs/10.1890/14-1989.1

Impacts of weather on long-term patterns of plant richness and diversity vary with location and management.

PubMed

Jonas, Jayne L; Buhl, Deborah A; Symstad, Amy J

2015-09-01

Better understanding the influence of precipitation and temperature on plant assemblages is needed to predict the effects of climate change. Many studies have examined the relationship between plant productivity and weather (primarily precipitation), but few have directly assessed the relationship between plant richness or diversity and weather despite their increased use as metrics of ecosystem condition. We focus on the grasslands of central North America, which are characterized by high temporal climatic variability. Over the next 100 years, these grasslands are predicted to experience further increased variability in growing season precipitation, as well as increased temperatures, due to global climate change. We assess the portion of interannual variability of richness and diversity explained by weather, how relationships between these metrics and weather vary among plant assemblages, and which aspects of weather best explain temporal variability. We used an information-theoretic approach to assess relationships between long-term plant richness and diversity patterns and a priori weather covariates using six data sets from four grasslands. Weather explained up to 49% and 63% of interannual variability in total plant species richness and diversity, respectively. However, richness and diversity responses to specific weather variables varied both among sites and among experimental treatments within sites. In general, we found many instances in which temperature was of equal or greater importance as precipitation, as well as evidence of the importance of lagged effects and precipitation or temperature variability. Although precipitation has been shown to be a key driver of productivity in grasslands, our results indicate that increasing temperatures alone, without substantial changes in precipitation patterns, could have measurable effects on Great Plains grassland plant assemblages and biodiversity metrics. Our results also suggest that richness and diversity will respond in unique ways to changing climate and management can affect these responses; additional research and monitoring will be essential for further understanding of these complex relationships.

Projected changes in crop yield mean and variability over West Africa in a world 1.5 K warmer than the pre-industrial era

NASA Astrophysics Data System (ADS)

Parkes, Ben; Defrance, Dimitri; Sultan, Benjamin; Ciais, Philippe; Wang, Xuhui

2018-02-01

The ability of a region to feed itself in the upcoming decades is an important issue. The West African population is expected to increase significantly in the next 30 years. The responses of crops to short-term climate change is critical to the population and the decision makers tasked with food security. This leads to three questions: how will crop yields change in the near future? What influence will climate change have on crop failures? Which adaptation methods should be employed to ameliorate undesirable changes? An ensemble of near-term climate projections are used to simulate maize, millet and sorghum in West Africa in the recent historic period (1986-2005) and a near-term future when global temperatures are 1.5 K above pre-industrial levels to assess the change in yield, yield variability and crop failure rate. Four crop models were used to simulate maize, millet and sorghum in West Africa in the historic and future climates. Across the majority of West Africa the maize, millet and sorghum yields are shown to fall. In the regions where yields increase, the variability also increases. This increase in variability increases the likelihood of crop failures, which are defined as yield negative anomalies beyond 1 standard deviation during the historic period. The increasing variability increases the frequency of crop failures across West Africa. The return time of crop failures falls from 8.8, 9.7 and 10.1 years to 5.2, 6.3 and 5.8 years for maize, millet and sorghum respectively. The adoption of heat-resistant cultivars and the use of captured rainwater have been investigated using one crop model as an idealized sensitivity test. The generalized doption of a cultivar resistant to high-temperature stress during flowering is shown to be more beneficial than using rainwater harvesting.

Some Spatial Aspects of Southeastern United States Climatology.

ERIC Educational Resources Information Center

Soule, Peter T.

1998-01-01

Focuses on the climatology of an eight-state region in the southern and southeastern United States. Discusses general controls of climate and spatial patterns of various climatic averages. Examines mapped extremes as a means of fostering increased awareness of the variability that exists for climatic conditions in the region. (CMK)

Global Climate Teleconnections to Forecast Increased Risk of Vector-Borne Animal and Human Disease Transmission

USDA-ARS?s Scientific Manuscript database

We willexamine how climate teleconnect ions and variability impact vector biology and vector borne disease ecology, and demonstrate that global climate monitoring can be used to anticipate and forecast epidemics and epizootics. In this context we willexamine significant worldwide weather anomalies t...

Monthly paleostreamflow reconstruction from annual tree-ring chronologies

Treesearch

J. H. Stagge; D. E. Rosenberg; R. J. DeRose; T. M. Rittenour

2018-01-01

Paleoclimate reconstructions are increasingly used to characterize annual climate variability prior to the instrumental record, to improve estimates of climate extremes, and to provide a baseline for climate change projections. To date, paleoclimate records have seen limited engineering use to estimate hydrologic risks because water systems models and managers usually...

Climate variability and nitrogen rate interactions affecting corn nitrogen use efficiency in Alabama

USDA-ARS?s Scientific Manuscript database

Nitrogen (N) fertilization is an important practice to increase yield; however, plant–soil interactions to in-season changes in climatic conditions result on site-specific responses of corn to nitrogen rates. The objective of this study was to evaluate the effect of different climatic conditions and...

Building climate resilience in the Blue Nile/Abay Highlands: Part II-arole for earth system sciences

USDA-ARS?s Scientific Manuscript database

The Blue Nile (Abay) Highlands of Ethiopia are characterized by significant interannual climate variability, dissected topography and associated local climate contrasts, erosive rains and erodible soils, and intense land pressure due to an increasing population and an economy that is almost entirely...

Direct and indirect climate controls predict heterogeneous early-mid 21st century wildfire burned area across western and boreal North America

PubMed Central

Falk, Donald A.; Westerling, Anthony L.; Swetnam, Thomas W.

2017-01-01

Predicting wildfire under future conditions is complicated by complex interrelated drivers operating across large spatial scales. Annual area burned (AAB) is a useful index of global wildfire activity. Current and antecedent seasonal climatic conditions, and the timing of snowpack melt, have been suggested as important drivers of AAB. As climate warms, seasonal climate and snowpack co-vary in intricate ways, influencing fire at continental and sub-continental scales. We used independent records of seasonal climate and snow cover duration (last date of permanent snowpack, LDPS) and cell-based Structural Equation Models (SEM) to separate direct (climatic) and indirect (snow cover) effects on relative changes in AAB under future climatic scenarios across western and boreal North America. To isolate seasonal climate variables with the greatest effect on AAB, we ran multiple regression models of log-transformed AAB on seasonal climate variables and LDPS. We used the results of multiple regressions to project future AAB using GCM ensemble climate variables and LDPS, and validated model predictions with recent AAB trends. Direct influences of spring and winter temperatures on AAB are larger and more widespread than the indirect effect mediated by changes in LDPS in most areas. Despite significant warming trends and reductions in snow cover duration, projected responses of AAB to early-mid 21st century are heterogeneous across the continent. Changes in AAB range from strongly increasing (one order of magnitude increases in AAB) to moderately decreasing (more than halving of baseline AAB). Annual wildfire area burned in coming decades is likely to be highly geographically heterogeneous, reflecting interacting regional and seasonal climate drivers of fire occurrence and spread. PMID:29244839

Association between climate factors and diarrhoea in a Mekong Delta area

NASA Astrophysics Data System (ADS)

Phung, Dung; Huang, Cunrui; Rutherford, Shannon; Chu, Cordia; Wang, Xiaoming; Nguyen, Minh; Nguyen, Nga Huy; Manh, Cuong Do; Nguyen, Trung Hieu

2015-09-01

The Mekong Delta is vulnerable to changes in climate and hydrological events which alter environmental conditions, resulting in increased risk of waterborne diseases. Research exploring the association between climate factors and diarrhoea, the most frequent waterborne disease in Mekong Delta region, is sparse. This study evaluated the climate-diarrhoea association in Can Tho city, a typical Mekong Delta area in Vietnam. Climate data (temperature, relative humidity, and rainfall) were obtained from the Southern Regional Hydro-Meteorological Centre, and weekly counts of diarrhoea visits were obtained from Can Tho Preventive Medicine Centre from 2004 to 2011. Analysis of climate and health variables was carried out using spline function to adjust for seasonal and long-term trends of variables. A distributed lag model was used to investigate possible delayed effects of climate variables on diarrhoea (considering 0-4 week lag periods), then the multivariate Poisson regression was used to examine any potential association between climate factors and diarrhoea. The results indicated that the diarrhoea incidence peaked within the period August-October annually. Significant positive associations were found between increased diarrhoea and high temperature at 4 weeks prior to the date of hospital visits (IRR = 1.07; 95 % CI = 1.04-1.08), high relative humidity (IRR = 1.13; 95 % CI = 1.12-1.15) and high (>90th percentile) cumulative rainfall (IRR = 1.05; 95 % CI = 1.05-1.08). The association between climate factors and diarrhoea was stronger in rural than urban areas. These findings in the context of the projected changes of climate conditions suggest that climate change will have important implications for residential health in Mekong Delta region.

Direct and indirect climate controls predict heterogeneous early-mid 21st century wildfire burned area across western and boreal North America.

PubMed

Kitzberger, Thomas; Falk, Donald A; Westerling, Anthony L; Swetnam, Thomas W

2017-01-01

Predicting wildfire under future conditions is complicated by complex interrelated drivers operating across large spatial scales. Annual area burned (AAB) is a useful index of global wildfire activity. Current and antecedent seasonal climatic conditions, and the timing of snowpack melt, have been suggested as important drivers of AAB. As climate warms, seasonal climate and snowpack co-vary in intricate ways, influencing fire at continental and sub-continental scales. We used independent records of seasonal climate and snow cover duration (last date of permanent snowpack, LDPS) and cell-based Structural Equation Models (SEM) to separate direct (climatic) and indirect (snow cover) effects on relative changes in AAB under future climatic scenarios across western and boreal North America. To isolate seasonal climate variables with the greatest effect on AAB, we ran multiple regression models of log-transformed AAB on seasonal climate variables and LDPS. We used the results of multiple regressions to project future AAB using GCM ensemble climate variables and LDPS, and validated model predictions with recent AAB trends. Direct influences of spring and winter temperatures on AAB are larger and more widespread than the indirect effect mediated by changes in LDPS in most areas. Despite significant warming trends and reductions in snow cover duration, projected responses of AAB to early-mid 21st century are heterogeneous across the continent. Changes in AAB range from strongly increasing (one order of magnitude increases in AAB) to moderately decreasing (more than halving of baseline AAB). Annual wildfire area burned in coming decades is likely to be highly geographically heterogeneous, reflecting interacting regional and seasonal climate drivers of fire occurrence and spread.

Evaluating the response of Lake Prespa (SW Balkan) to future climate change projections from a high-resolution model

NASA Astrophysics Data System (ADS)

van der Schriek, Tim; Varotsos, Konstantinos V.; Giannakopoulos, Christos

2017-04-01

The Mediterranean stands out globally due to its sensitivity to (future) climate change. Projections suggest that the Balkans will experience precipitation and runoff decreases of up to 30% by 2100. However, these projections show large regional spatial variability. Mediterranean lake-wetland systems are particularly threatened by projected climate changes that compound increasingly intensive human impacts (e.g. water extraction, drainage, pollution and dam-building). Protecting the remaining systems is extremely important for supporting global biodiversity. This protection should be based on a clear understanding of individual lake-wetland hydrological responses to future climate changes, which requires fine-resolution projections and a good understanding of the impact of hydro-climate variability on individual lakes. Climate change may directly affect lake level (variability), volume and water temperatures. In turn, these variables influence lake-ecology, habitats and water quality. Land-use intensification and water abstraction multiply these climate-driven changes. To date, there are no projections of future water level and -temperature of individual Mediterranean lakes under future climate scenarios. These are, however, of crucial importance to steer preservation strategies on the relevant catchment-scale. Here we present the first projections of water level and -temperature of the Prespa Lakes covering the period 2071-2100. These lakes are of global significance for biodiversity, and of great regional socio-economic importance as a water resource and tourist attraction. Impact projections are assessed by the Regional Climate Model RCA4 of the Swedish Meteorological and Hydrological Institute (SMHI) driven by the Max Planck Institute for Meteorology global climate model MPI-ESM-LR under two RCP future emissions scenarios, the RCP4.5 and the RCP8.5, with the simulations carried out in the framework of EURO-CORDEX. Temperature, evapo(transpi)ration and precipitation over the Prespa catchment were simulated with this high horizontal resolution (12 × 12 km) regional climate model. Lake temperatures were derived from surface temperatures based on physical models, while water levels were calculated with the lake water balance model. Climate simulations indicate that annual- and wet season catchment precipitation does not significantly change by the end of the century. The median precipitation decreases, while precipitation variability increases. The percentage of annual precipitation falling in the wet season increases by 5-10%, indicating a stronger seasonality in the precipitation regime. Summer (lake) temperatures and lake surface evaporation will rise significantly under both explored climate change scenarios. Lake impact projections indicate that evaporation changes will cause the water level of Lake Megali Prespa to fall by 5m to 840-839m. The increased precipitation variability will cause large inter-annual water level fluctuations. Average water level may fall even further if: (1) drier summers lead to more water abstraction for irrigation, and (2) there is a reduction in winter snowfall/accumulation and thus less discharge. These findings are of key importance for developing sustainable lake water resource management in a region that is highly vulnerable to future climate change and already experiences significant water stress. Research paves the way for innovative management adaptation strategies focussed on decreasing water abstraction, for example through introducing smart irrigation and selecting more water efficient crops.

The changing role of fire in conifer-dominated temperate rainforest through the last 14,000 years

NASA Astrophysics Data System (ADS)

Fletcher, M.-S.; Bowman, D. M. J. S.; Whitlock, C.; Mariani, M.; Stahle, L.

2018-02-01

Climate, fire and vegetation dynamics are often tightly coupled through time. Here, we use a 14 kyr sedimentary charcoal and pollen record from Lake Osborne, Tasmania, Australia, to explore how this relationship changes under varying climatic regimes within a temperate rainforest ecosystem. Superposed epoch analysis reveals a significant relationship between fire and vegetation change throughout the Holocene at our site. Our data indicates an initial resilience of the rainforest system to fire under a stable cool and humid climate regime between ca. 12-6 ka. In contrast, fires that occurred after 6 ka, under an increasingly variable climate regime wrought by the onset of the El Niño-Southern Oscillation (ENSO), resulted in a series of changes within the local rainforest vegetation that culminated in the replacement of rainforest by fire-promoted Eucalypt forest. We suggest that an increasingly variable ENSO-influenced climate regime inhibited rainforest recovery from fire because of slower growth, reduced fecundity and increased fire frequency, thus contributing to the eventual collapse of the rainforest system.

Future Warming Increases Global Maize Yield Variability with Implications for Food Markets

NASA Astrophysics Data System (ADS)

Tigchelaar, M.; Battisti, D. S.; Naylor, R. L.; Ray, D. K.

2017-12-01

If current trends in population growth and dietary shifts continue, the world will need to produce about 70% more food by 2050, while earth's climate is rapidly changing. Rising temperatures in particular are projected to negatively impact agricultural production, as the world's staple crops perform poorly in extreme heat. Theoretical models suggest that as temperatures rise above plants' optimal temperature for performance, not only will mean yields decline rapidly, but the variability of yields will increase, even as interannual variations in climate remain unchanged. Here we use global datasets of maize production and climate variability combined with CMIP5 temperature projections to quantify how yield variability will change in major maize producing countries under 2°C and 4°C of global warming. Maize is the world's most produced crop, and is linked to other staple crops through substitution in consumption and production. We find that in warmer climates - absent any breeding gains in heat tolerance - the Coefficient of Variation (CV) of maize yields increases almost everywhere, to values much larger than present-day. This increase in CV is due both to an increase in the standard deviation of yields, and a decrease in mean yields. In locations where crop failures become the norm under high (4°C) warming (mostly in tropical, low-yield environments), the standard deviation of yields ultimately decreases. The probability that in any given year the most productive areas in the top three maize producing countries (United States, China, Brazil) have simultaneous production losses greater than 10% is virtually zero under present-day climate conditions, but increases to 12% under 2°C warming, and 89% under 4°C warming. This has major implications for global food markets and staple crop prices, affecting especially the 2.5 billion people that comprise the world's poor, who already spend the majority of their disposable income on food and are particularly vulnerable to agricultural price spikes.

An observational and modeling study of the regional impacts of climate variability

NASA Astrophysics Data System (ADS)

Horton, Radley M.

Climate variability has large impacts on humans and their agricultural systems. Farmers are at the center of this agricultural network, but it is often agricultural planners---regional planners, extension agents, commodity groups and cooperatives---that translate climate information for users. Global climate models (GCMs) are a leading tool for understanding and predicting climate and climate change. Armed with climate projections and forecasts, agricultural planners adapt their decision-making to optimize outcomes. This thesis explores what GCMs can, and cannot, tell us about climate variability and change at regional scales. The question is important, since high-quality regional climate projections could assist farmers and regional planners in key management decisions, contributing to better agricultural outcomes. To answer these questions, climate variability and its regional impacts are explored in observations and models for the current and future climate. The goals are to identify impacts of observed variability, assess model simulation of variability, and explore how climate variability and its impacts may change under enhanced greenhouse warming. Chapter One explores how well Goddard Institute for Space Studies (GISS) atmospheric models, forced by historical sea surface temperatures (SST), simulate climatology and large-scale features during the exceptionally strong 1997--1999 El Nino Southern Oscillation (ENSO) cycle. Reasonable performance in this 'proof of concept' test is considered a minimum requirement for further study of variability in models. All model versions produce appropriate local changes with ENSO, indicating that with correct ocean temperatures these versions are capable of simulating the large-scale effects of ENSO around the globe. A high vertical resolution model (VHR) provides the best simulation. Evidence is also presented that SST anomalies outside the tropical Pacific may play a key role in generating remote teleconnections even during El Nino events. Based on the results from Chapter One, the analysis is expanded in several ways in Chapter Two. To gain a more complete and statistically meaningful understanding of ENSO, a 25 year time period is used instead of a single event. To gain a fuller understanding of climate variability, additional patterns are analyzed. Finally analysis is conducted at the regional scales that are of interest to farmers and agricultural planners. Key findings are that GISS ModelE can reproduce: (1) the spatial pattern associated with two additional related modes, the Arctic Oscillation (AO) and the North Atlantic Oscillation (NAO); (2) rainfall patterns in Indonesia; and (3) dynamical features such as sea level pressure (SLP) gradients and wind in the study regions. When run in coupled mode, the same model reproduces similar modes spatially but with reduced variance and weak teleconnections. Since Chapter Two identified Western Indonesia as the region where GCMs hold the most promise for agricultural applications, in Chapter Three a finer spatial and temporal scale analysis of ENSO's effects is presented. Agricultural decision-making is also linked to ENSO's climate effects. Early rainy season precipitation and circulation, and same-season planting and harvesting dates, are shown to be sensitive to ENSO. The locus of ENSO convergence and rainfall anomalies is shown to be near the axis of rainy season establishment, defined as the 6--8 mm/day isohyet, an approximate threshold for irrigated rice cultivation. As the axis tracks south and east between October and January, so do ENSO anomalies. Circulation anomalies associated with ENSO are shown to be similar to those associated with rainfall anomalies, suggesting that long lead-time ENSO forecasts may allow more adaptation than 'wait and see' methods, with little loss of forecast skill. Additional findings include: (1) rice and corn yields are lower (higher) during dry (wet) trimesters and El Nino (La Nina) years; and (2) a statistically significant negative relationship exists between malaria cases and ENSO. The final chapter adds climate change to the climate variability story. Under high CO2, the model able to capture ENSO dynamics---an atmospheric model coupled to the Cane-Zebiak ocean model ('C4' here)---generates more El Nino-like mean conditions in the tropical Pacific. These changes produce a 4x larger increase in maximum precipitation with warming in C4 than an atmospheric model with a slab ocean (Q4), dramatically enhancing the Pacific Hadley and Walker circulations, and through positive feedbacks, increasing the global temperature. Near Nordeste warming alone (Q4) produces added rainfall, which in C4 is partially cancelled out by El Nino-like changes in the Walker Cell. Both Q4 and C4 produce small changes in Indonesia, although C4 generates large circulation and precipitation anomalies over the Western Indian Ocean. C4 changes in the midlatitudes produce a very strong Pacific North American pattern (PNA) response that dominates a small positive AO change associated with Q4. These PNA changes produce increased rainfall over the Southeastern United States (SEUS) in C4. AO and NAO-like variability are also found to increase with enhanced CO2. This thesis highlights how climate variability influences regional climate variability, with an emphasis on four regions: Nordeste, Brazil, Western Indonesia, the Southeastern United States (SEUS), and the Mediterranean. It links El Nino-driven delay in the onset of rainy season drivers in Western Indonesia to decision-making about when to plant the year's largest crop. In a coupled configuration, the GISS GCM produces strong El Nino-like changes with global warming. This result suggests that the impacts---climatological and agricultural---of climate change may ultimately exceed the impacts of current variability. Somewhat paradoxically, these results indicate that one of the central manifestations of climate change is likely to be changes in patterns of climate variability and their regional impacts.

Attribution of maize yield increase in China to climate change and technological advancement between 1980 and 2010

NASA Astrophysics Data System (ADS)

Guo, Jianping; Zhao, Junfang; Wu, Dingrong; Mu, Jia; Xu, Yanhong

2014-12-01

Crop yields are affected by climate change and technological advancement. Objectively and quantitatively evaluating the attribution of crop yield change to climate change and technological advancement will ensure sustainable development of agriculture under climate change. In this study, daily climate variables obtained from 553 meteorological stations in China for the period 1961-2010, detailed observations of maize from 653 agricultural meteorological stations for the period 1981-2010, and results using an Agro-Ecological Zones (AEZ) model, are used to explore the attribution of maize (Zea mays L.) yield change to climate change and technological advancement. In the AEZ model, the climatic potential productivity is examined through three step-by-step levels: photosynthetic potential productivity, photosynthetic thermal potential productivity, and climatic potential productivity. The relative impacts of different climate variables on climatic potential productivity of maize from 1961 to 2010 in China are then evaluated. Combined with the observations of maize, the contributions of climate change and technological advancement to maize yield from 1981 to 2010 in China are separated. The results show that, from 1961 to 2010, climate change had a significant adverse impact on the climatic potential productivity of maize in China. Decreased radiation and increased temperature were the main factors leading to the decrease of climatic potential productivity. However, changes in precipitation had only a small effect. The maize yields of the 14 main planting provinces in China increased obviously over the past 30 years, which was opposite to the decreasing trends of climatic potential productivity. This suggests that technological advancement has offset the negative effects of climate change on maize yield. Technological advancement contributed to maize yield increases by 99.6%-141.6%, while climate change contribution was from -41.4% to 0.4%. In particular, the actual maize yields in Shandong, Henan, Jilin, and Inner Mongolia increased by 98.4, 90.4, 98.7, and 121.5 kg hm-2 yr-1 over the past 30 years, respectively. Correspondingly, the maize yields affected by technological advancement increased by 113.7, 97.9, 111.5, and 124.8 kg hm-2 yr-1, respectively. On the contrary, maize yields reduced markedly under climate change, with an average reduction of -9.0 kg hm-2 yr-1. Our findings highlight that agronomic technological advancement has contributed dominantly to maize yield increases in China in the past three decades.

Climate Penalty on Air Quality and Human Health in China and India

NASA Astrophysics Data System (ADS)

Li, M.; Zhang, S.; Garcia-Menendez, F.; Monier, E.; Selin, N. E.

2017-12-01

Climate change, favoring more heat waves and episodes of stagnant air, may deteriorate air quality by increasing ozone and fine particulate matter (PM2.5) concentrations and high pollution episodes. This effect, termed as "climate penalty", has been quantified and explained by many earlier studies in the U.S. and Europe, but research efforts in Asian countries are limited. We evaluate the impact of climate change on air quality and human health in China and India using a modeling framework that links the Massachusetts Institute of Technology Integrated Global System Model to the Community Atmosphere Model (MIT IGSM-CAM). Future climate fields are projected under three climate scenarios including a no-policy reference scenario and two climate stabilization scenarios with 2100 total radiative forcing targets of 9.7, 4.5 and 3.7 W m-2, respectively. Each climate scenario is run for five representations of climate variability to account for the role of natural variability. Thirty-year chemical transport simulations are conducted in 1981-2010 and 2086-2115 under the three climate scenarios with fixed anthropogenic emissions at year 2000 levels. We find that 2000—2100 climate change under the no-policy reference scenario would increase ozone concentrations in eastern China and northern India by up to 5 ppb through enhancing biogenic emissions and ozone production efficiency. Ozone extreme episodes also become more frequent in these regions, while climate policies can offset most of the increase in ozone episodes. Climate change between 2000 and 2100 would slightly increase anthropogenic PM2.5 concentrations in northern China and Sichuan province, but significantly reduce anthropogenic PM2.5 concentrations in southern China and northern India, primarily due to different chemical responses of sulfate-nitrate-ammonium aerosols to climate change in these regions. Our study also suggests that the mitigation costs of climate policies can be partially offset by health benefits from reduced climate-induced air pollution in China.

Seasonal and latitudinal acclimatization of cardiac transcriptome responses to thermal stress in porcelain crabs, Petrolisthes cinctipes.

PubMed

Stillman, Jonathon H; Tagmount, Abderrahmane

2009-10-01

Central predictions of climate warming models include increased climate variability and increased severity of heat waves. Physiological acclimatization in populations across large-scale ecological gradients in habitat temperature fluctuation is an important factor to consider in detecting responses to climate change related increases in thermal fluctuation. We measured in vivo cardiac thermal maxima and used microarrays to profile transcriptome heat and cold stress responses in cardiac tissue of intertidal zone porcelain crabs across biogeographic and seasonal gradients in habitat temperature fluctuation. We observed acclimatization dependent induction of heat shock proteins, as well as unknown genes with heat shock protein-like expression profiles. Thermal acclimatization had the largest effect on heat stress responses of extensin-like, beta tubulin, and unknown genes. For these genes, crabs acclimatized to thermally variable sites had higher constitutive expression than specimens from low variability sites, but heat stress dramatically induced expression in specimens from low variability sites and repressed expression in specimens from highly variable sites. Our application of ecological transcriptomics has yielded new biomarkers that may represent sensitive indicators of acclimatization to habitat temperature fluctuation. Our study also has identified novel genes whose further description may yield novel understanding of cellular responses to thermal acclimatization or thermal stress.

Assessing Lebanon's wildfire potential in association with current and future climatic conditions

Treesearch

George H. Mitri; Mireille G. Jazi; David McWethy

2015-01-01

The increasing occurrence and extent of large-scale wildfires in the Mediterranean have been linked to extended periods of warm and dry weather. We set out to assess Lebanon's wildfire potential in association with current and future climatic conditions. The Keetch-Byram Drought Index (KBDI) was the primary climate variable used in our evaluation of climate/fire...

Climate simulations and projections with a super-parameterized climate model

DOE PAGES

Stan, Cristiana; Xu, Li

2014-07-01

The mean climate and its variability are analyzed in a suite of numerical experiments with a fully coupled general circulation model in which subgrid-scale moist convection is explicitly represented through embedded 2D cloud-system resolving models. Control simulations forced by the present day, fixed atmospheric carbon dioxide concentration are conducted using two horizontal resolutions and validated against observations and reanalyses. The mean state simulated by the higher resolution configuration has smaller biases. Climate variability also shows some sensitivity to resolution but not as uniform as in the case of mean state. The interannual and seasonal variability are better represented in themore » simulation at lower resolution whereas the subseasonal variability is more accurate in the higher resolution simulation. The equilibrium climate sensitivity of the model is estimated from a simulation forced by an abrupt quadrupling of the atmospheric carbon dioxide concentration. The equilibrium climate sensitivity temperature of the model is 2.77 °C, and this value is slightly smaller than the mean value (3.37 °C) of contemporary models using conventional representation of cloud processes. As a result, the climate change simulation forced by the representative concentration pathway 8.5 scenario projects an increase in the frequency of severe droughts over most of the North America.« less

A hybrid model to assess the impact of climate variability on streamflow for an ungauged mountainous basin

NASA Astrophysics Data System (ADS)

Wang, Chong; Xu, Jianhua; Chen, Yaning; Bai, Ling; Chen, Zhongsheng

2018-04-01

To quantitatively assess the impact of climate variability on streamflow in an ungauged mountainous basin is a difficult and challenging work. In this study, a hybrid model combing downscaling method based on earth data products, back propagation artificial neural networks (BPANN) and weights connection method was developed to explore an approach for solving this problem. To validate the applicability of the hybrid model, the Kumarik River and Toshkan River, two headwaters of the Aksu River, were employed to assess the impact of climate variability on streamflow by using this hybrid model. The conclusion is that the hybrid model presented a good performance, and the quantitative assessment results for the two headwaters are: (1) the precipitation respectively increased by 48.5 and 41.0 mm in the Kumarik catchment and Toshkan catchment, and the average annual temperature both increased by 0.1 °C in the two catchments during each decade from 1980 to 2012; (2) with the warming and wetting climate, the streamflow respectively increased 1.5 × 108 and 3.3 × 108 m3 per decade in the Kumarik River and the Toshkan River; and (3) the contribution of the temperature and precipitation to the streamflow, which were 64.01 ± 7.34, 35.99 ± 7.34 and 47.72 ± 8.10, 52.26 ± 8.10%, respectively in the Kumarik catchment and Toshkan catchment. Our study introduced a feasible hybrid model for the assessment of the impact of climate variability on streamflow, which can be used in the ungauged mountainous basin of Northwest China.

Effects of climate on numbers of northern prairie wetlands

USGS Publications Warehouse

Larson, Diane L.

1995-01-01

The amount of water held in individual wetland basins depends not only on local climate patterns but also on groundwater flow regime, soil permeability, and basin size. Most wetland basins in the northern prairies hold water in some years and are dry in others. To assess the potential effect of climate change on the number of wetland basins holding water in a given year, one must first determine how much of the variability in number of wet basins is accounted for by climatic variables. I used multiple linear regression to examine the relationship between climate variables and percentage of wet basins throughout the Prairie Pothole Region of Canada and the United States. The region was divided into three areas: parkland, Canadian grassland, and United States grassland (i.e., North Dakota and South Dakota). The models - which included variables for spring and fall temperature, yearly precipitation, the previous year's count of wet basins, and for grassland areas, the previous fall precipitation - accounted for 63 to 65% of the variation in the number of wet basins. I then explored the sensitivities of the models to changes in temperature and precipitation, as might be associated with increased greenhouse gas concentrations. Parkland wetlands are shown to be much more vulnerable to increased temperatures than are wetlands in either Canadian or United States grasslands. Sensitivity to increased precipitation did not vary geographically. These results have implications for waterfowl and other wildlife populations that depend on availability of wetlands in the parklands for breeding or during periods of drought in the southern grasslands.

Validation of China-wide interpolated daily climate variables from 1960 to 2011

NASA Astrophysics Data System (ADS)

Yuan, Wenping; Xu, Bing; Chen, Zhuoqi; Xia, Jiangzhou; Xu, Wenfang; Chen, Yang; Wu, Xiaoxu; Fu, Yang

2015-02-01

Temporally and spatially continuous meteorological variables are increasingly in demand to support many different types of applications related to climate studies. Using measurements from 600 climate stations, a thin-plate spline method was applied to generate daily gridded climate datasets for mean air temperature, maximum temperature, minimum temperature, relative humidity, sunshine duration, wind speed, atmospheric pressure, and precipitation over China for the period 1961-2011. A comprehensive evaluation of interpolated climate was conducted at 150 independent validation sites. The results showed superior performance for most of the estimated variables. Except for wind speed, determination coefficients ( R 2) varied from 0.65 to 0.90, and interpolations showed high consistency with observations. Most of the estimated climate variables showed relatively consistent accuracy among all seasons according to the root mean square error, R 2, and relative predictive error. The interpolated data correctly predicted the occurrence of daily precipitation at validation sites with an accuracy of 83 %. Moreover, the interpolation data successfully explained the interannual variability trend for the eight meteorological variables at most validation sites. Consistent interannual variability trends were observed at 66-95 % of the sites for the eight meteorological variables. Accuracy in distinguishing extreme weather events differed substantially among the meteorological variables. The interpolated data identified extreme events for the three temperature variables, relative humidity, and sunshine duration with an accuracy ranging from 63 to 77 %. However, for wind speed, air pressure, and precipitation, the interpolation model correctly identified only 41, 48, and 58 % of extreme events, respectively. The validation indicates that the interpolations can be applied with high confidence for the three temperatures variables, as well as relative humidity and sunshine duration based on the performance of these variables in estimating daily variations, interannual variability, and extreme events. Although longitude, latitude, and elevation data are included in the model, additional information, such as topography and cloud cover, should be integrated into the interpolation algorithm to improve performance in estimating wind speed, atmospheric pressure, and precipitation.

Vegetation Interaction Enhances Interdecadal Climate Variability in the Sahel

NASA Technical Reports Server (NTRS)

Zeng, Ning; Neelin, J. David; Lau, William K.-M.

1999-01-01

The role of naturally varying vegetation in influencing the climate variability in the Sahel is explored in a coupled atmosphere-land-vegetation model. The Sahel rainfall variability is influenced by sea surface temperature (SST) variations in the oceans. Land-surface feedback is found to increase this variability both on interannual and interdecadal time scales. Interactive vegetation enhances the interdecadal variation significantly, but can reduce year to year variability due to a phase lag introduced by the relatively slow vegetation adjustment time. Variations in vegetation accompany the changes in rainfall, in particular, the multi-decadal drying trend from the 1950s to the 80s.

Impact of climate variability on runoff in the north-central United States

USGS Publications Warehouse

Ryberg, Karen R.; Lin, Wei; Vecchia, Aldo V.

2014-01-01

Large changes in runoff in the north-central United States have occurred during the past century, with larger floods and increases in runoff tending to occur from the 1970s to the present. The attribution of these changes is a subject of much interest. Long-term precipitation, temperature, and streamflow records were used to compare changes in precipitation and potential evapotranspiration (PET) to changes in runoff within 25 stream basins. The basins studied were organized into four groups, each one representing basins similar in topography, climate, and historic patterns of runoff. Precipitation, PET, and runoff data were adjusted for near-decadal scale variability to examine longer-term changes. A nonlinear water-balance analysis shows that changes in precipitation and PET explain the majority of multidecadal spatial/temporal variability of runoff and flood magnitudes, with precipitation being the dominant driver. Historical changes in climate and runoff in the region appear to be more consistent with complex transient shifts in seasonal climatic conditions than with gradual climate change. A portion of the unexplained variability likely stems from land-use change.

Evaluation of climatic changes in South-Asia

NASA Astrophysics Data System (ADS)

Kjellstrom, Erik; Rana, Arun; Grigory, Nikulin; Renate, Wilcke; Hansson, Ulf; Kolax, Michael

2016-04-01

Literature has sufficient evidences of climate change impact all over the world and its impact on various sectors. In light of new advancements made in climate modeling, availability of several climate downscaling approaches, the more robust bias correction methods with varying complexities and strengths, in the present study we performed a systematic evaluation of climate change impact over South-Asia region. We have used different Regional Climate Models (RCMs) (from CORDEX domain), (Global Climate Models GCMs) and gridded observations for the study area to evaluate the models in historical/control period (1980-2010) and changes in future period (2010-2099). Firstly, GCMs and RCMs are evaluated against the Gridded observational datasets in the area using precipitation and temperature as indicative variables. Observational dataset are also evaluated against the reliable set of observational dataset, as pointed in literature. Bias, Correlation, and changes (among other statistical measures) are calculated for the entire region and both the variables. Eventually, the region was sub-divided into various smaller domains based on homogenous precipitation zones to evaluate the average changes over time period. Spatial and temporal changes for the region are then finally calculated to evaluate the future changes in the region. Future changes are calculated for 2 Representative Concentration Pathways (RCPs), the middle emission (RCP4.5) and high emission (RCP8.5) and for both climatic variables, precipitation and temperature. Lastly, Evaluation of Extremes is performed based on precipitation and temperature based indices for whole region in future dataset. Results have indicated that the whole study region is under extreme stress in future climate scenarios for both climatic variables i.e. precipitation and temperature. Precipitation variability is dependent on the location in the area leading to droughts and floods in various regions in future. Temperature is hinting towards a constant increase throughout the region regardless of location.

Assessing effects of variation in global climate data sets on spatial predictions from climate envelope models

USGS Publications Warehouse

Romañach, Stephanie; Watling, James I.; Fletcher, Robert J.; Speroterra, Carolina; Bucklin, David N.; Brandt, Laura A.; Pearlstine, Leonard G.; Escribano, Yesenia; Mazzotti, Frank J.

2014-01-01

Climate change poses new challenges for natural resource managers. Predictive modeling of species–environment relationships using climate envelope models can enhance our understanding of climate change effects on biodiversity, assist in assessment of invasion risk by exotic organisms, and inform life-history understanding of individual species. While increasing interest has focused on the role of uncertainty in future conditions on model predictions, models also may be sensitive to the initial conditions on which they are trained. Although climate envelope models are usually trained using data on contemporary climate, we lack systematic comparisons of model performance and predictions across alternative climate data sets available for model training. Here, we seek to fill that gap by comparing variability in predictions between two contemporary climate data sets to variability in spatial predictions among three alternative projections of future climate. Overall, correlations between monthly temperature and precipitation variables were very high for both contemporary and future data. Model performance varied across algorithms, but not between two alternative contemporary climate data sets. Spatial predictions varied more among alternative general-circulation models describing future climate conditions than between contemporary climate data sets. However, we did find that climate envelope models with low Cohen's kappa scores made more discrepant spatial predictions between climate data sets for the contemporary period than did models with high Cohen's kappa scores. We suggest conservation planners evaluate multiple performance metrics and be aware of the importance of differences in initial conditions for spatial predictions from climate envelope models.

Integration of ENSO Signal Power Through Hydrological Processes in the Little River Watershed

NASA Astrophysics Data System (ADS)

Keener, V. W.; Jones, J. W.; Bosch, D. D.; Cho, J.

2011-12-01

The relationship of the El-Nino/Southern Oscillation (ENSO) to hydrology is typically discussed in terms of the ability to separate significantly different hydrologic variable responses versus the anomaly that has taken place. Most of the work relating ENSO trends to proxy variables had been done on precipitation records until the mid 1990s, at which point increasing numbers of studies started to focus on ENSO relationships with streamflow as well as other environmental variables. The signals in streamflow are typically complex, representing the integration of both climatic, landscape, and anthropological responses that are able to strengthen the inherent ENSO signal in chaotic regional precipitation data. There is a need to identify climate non-stationarities related to ENSO and their links to watershed-scale outcomes. For risk-management in particular, inter-annual modes of climate variability and their seasonal expression are of interest. In this study, we analyze 36 years of historical monthly streamflow data from the Little River Watershed (LWR), a coastal plain ecosystem in Georgia, in conjunction with wavelet spectral analysis and modeling via the Soil & Water Assessment Tool (SWAT). Using both spectral and physical models allows us to identify the mechanism by which the ENSO signal power in surface and simulated groundwater flow is strengthened as compared to precipitation. The clear increase in the power of the inter-annual climate signal is demonstrated by shared patterns in water budget and exceedance curves, as well as in high ENSO related energy in the 95% significant wavelet spectra for each variable and the NINO 3.4 index. In the LRW, the power of the ENSO teleconnection is increased in both the observed and simulated stream flow through the mechanisms of groundwater flow and interflow, through confinement by a geological layer, the Hawthorn Formation. This non-intuitive relationship between ENSO signal strength and streamflow could prove to be helpful for making seasonal climate predictions in a geographic area with a weaker than desirable ENSO signal, as a predictive relationship could be found between streamflow or other proxy hydro-climatic variables.

The relative contribution of climate variability and vector control coverage to changes in malaria parasite prevalence in Zambia 2006-2012.

PubMed

Bennett, Adam; Yukich, Josh; Miller, John M; Keating, Joseph; Moonga, Hawela; Hamainza, Busiku; Kamuliwo, Mulakwa; Andrade-Pacheco, Ricardo; Vounatsou, Penelope; Steketee, Richard W; Eisele, Thomas P

2016-08-05

Four malaria indicator surveys (MIS) were conducted in Zambia between 2006 and 2012 to evaluate malaria control scale-up. Nationally, coverage of insecticide-treated nets (ITNs) and indoor residual spraying (IRS) increased over this period, while parasite prevalence in children 1-59 months decreased dramatically between 2006 and 2008, but then increased from 2008 to 2010. We assessed the relative effects of vector control coverage and climate variability on malaria parasite prevalence over this period. Nationally-representative MISs were conducted in April-June of 2006, 2008, 2010 and 2012 to collect household-level information on malaria control interventions such as IRS, ITN ownership and use, and child parasite prevalence by microscopic examination of blood smears. We fitted Bayesian geostatistical models to assess the association between IRS and ITN coverage and climate variability and malaria parasite prevalence. We created predictions of the spatial distribution of malaria prevalence at each time point and compared results of varying IRS, ITN, and climate inputs to assess their relative contributions to changes in prevalence. Nationally, the proportion of households owning an ITN increased from 37.8 % in 2006 to 64.3 % in 2010 and 68.1 % in 2012, with substantial heterogeneity sub-nationally. The population-adjusted predicted child malaria parasite prevalence decreased from 19.6 % in 2006 to 10.4 % in 2008, but rose to 15.3 % in 2010 and 13.5 % in 2012. We estimated that the majority of this prevalence increase at the national level between 2008 and 2010 was due to climate effects on transmission, although there was substantial heterogeneity at the provincial level in the relative contribution of changing climate and ITN availability. We predict that if climate factors preceding the 2010 survey were the same as in 2008, the population-adjusted prevalence would have fallen to 9.9 % nationally. These results suggest that a combination of climate factors and reduced intervention coverage in parts of the country contributed to both the reduction and rebound in malaria parasite prevalence. Unusual rainfall patterns, perhaps related to moderate El Niño conditions, may have contributed to this variation. Zambia has demonstrated considerable success in scaling up vector control. This analysis highlights the importance of accounting for climate variability when using cross-sectional data for evaluation of malaria control efforts.

Interpreting the Climatic Effects on Xylem Functional Traits in Two Mediterranean Oak Species: The Role of Extreme Climatic Events.

PubMed

Rita, Angelo; Borghetti, Marco; Todaro, Luigi; Saracino, Antonio

2016-01-01

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 in substantial reduction of hydraulic functionality and, hence increased incidence of xylem dysfunctions.

Interpreting the Climatic Effects on Xylem Functional Traits in Two Mediterranean Oak Species: The Role of Extreme Climatic Events

PubMed Central

Rita, Angelo; Borghetti, Marco; Todaro, Luigi; Saracino, Antonio

2016-01-01

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 in substantial reduction of hydraulic functionality and, hence increased incidence of xylem dysfunctions. PMID:27532008

Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model

NASA Astrophysics Data System (ADS)

Lee, Sangchul; Yeo, In-Young; Sadeghi, Ali M.; McCarty, Gregory W.; Hively, Wells D.; Lang, Megan W.; Sharifi, Amir

2018-01-01

Water quality problems in the Chesapeake Bay Watershed (CBW) are expected to be exacerbated by climate variability and change. However, climate impacts on agricultural lands and resultant nutrient loads into surface water resources are largely unknown. This study evaluated the impacts of climate variability and change on two adjacent watersheds in the Coastal Plain of the CBW, using the Soil and Water Assessment Tool (SWAT) model. We prepared six climate sensitivity scenarios to assess the individual impacts of variations in CO2 concentration (590 and 850 ppm), precipitation increase (11 and 21 %), and temperature increase (2.9 and 5.0 °C), based on regional general circulation model (GCM) projections. Further, we considered the ensemble of five GCM projections (2085-2098) under the Representative Concentration Pathway (RCP) 8.5 scenario to evaluate simultaneous changes in CO2, precipitation, and temperature. Using SWAT model simulations from 2001 to 2014 as a baseline scenario, predicted hydrologic outputs (water and nitrate budgets) and crop growth were analyzed. Compared to the baseline scenario, a precipitation increase of 21 % and elevated CO2 concentration of 850 ppm significantly increased streamflow and nitrate loads by 50 and 52 %, respectively, while a temperature increase of 5.0 °C reduced streamflow and nitrate loads by 12 and 13 %, respectively. Crop biomass increased with elevated CO2 concentrations due to enhanced radiation- and water-use efficiency, while it decreased with precipitation and temperature increases. Over the GCM ensemble mean, annual streamflow and nitrate loads showed an increase of ˜ 70 % relative to the baseline scenario, due to elevated CO2 concentrations and precipitation increase. Different hydrological responses to climate change were observed from the two watersheds, due to contrasting land use and soil characteristics. The watershed with a larger percent of croplands demonstrated a greater increased rate of 5.2 kg N ha-1 in nitrate yield relative to the watershed with a lower percent of croplands as a result of increased export of nitrate derived from fertilizer. The watershed dominated by poorly drained soils showed increased nitrate removal due do enhanced denitrification compared to the watershed dominated by well-drained soils. Our findings suggest that increased implementation of conservation practices would be necessary for this region to mitigate increased nitrate loads associated with predicted changes in future climate.

Climate change and prairie pothole wetlands: mitigating water-level and hydroperiod effects through upland management

USGS Publications Warehouse

Renton, David A.; Mushet, David M.; DeKeyser, Edward S.

2015-01-01

Prairie pothole wetlands offer crucial habitat for North America’s waterfowl populations. The wetlands also support an abundance of other species and provide ecological services valued by society. The hydrology of prairie pothole wetlands is dependent on atmospheric interactions. Therefore, changes to the region’s climate can have profound effects on wetland hydrology. The relevant literature related to climate change and upland management effects on prairie pothole wetland water levels and hydroperiods was reviewed. Climate change is widely expected to affect water levels and hydroperiods of prairie pothole wetlands, as well as the biota and ecological services that the wetlands support. In general, hydrologic model projections that incorporate future climate change scenarios forecast lower water levels in prairie pothole wetlands and longer periods spent in a dry condition, despite potential increases in precipitation. However, the extreme natural variability in climate and hydrology of prairie pothole wetlands necessitates caution when interpreting model results. Recent changes in weather patterns throughout much of the Prairie Pothole Region have been in increased precipitation that results in increased water inputs to wetlands above losses associated with warmer temperatures. However, observed precipitation increases are within the range of natural climate variability and therefore, may not persist. Identifying management techniques with the potential to affect water inputs to prairie pothole wetlands would provide increased options for managers when dealing with the uncertainties associated with a changing climate. Several grassland management techniques (for example, grazing and burning) have the potential to affect water levels and hydroperiods of prairie pothole by affecting infiltration, evapotranspiration, and snow deposition.

Incorporating Anthropogenic Influences into Fire Probability Models: Effects of Human Activity and Climate Change on Fire Activity in California.

PubMed

Mann, Michael L; Batllori, Enric; Moritz, Max A; Waller, Eric K; Berck, Peter; Flint, Alan L; Flint, Lorraine E; Dolfi, Emmalee

2016-01-01

The costly interactions between humans and wildfires throughout California demonstrate the need to understand the relationships between them, especially in the face of a changing climate and expanding human communities. Although a number of statistical and process-based wildfire models exist for California, there is enormous uncertainty about the location and number of future fires, with previously published estimates of increases ranging from nine to fifty-three percent by the end of the century. Our goal is to assess the role of climate and anthropogenic influences on the state's fire regimes from 1975 to 2050. We develop an empirical model that integrates estimates of biophysical indicators relevant to plant communities and anthropogenic influences at each forecast time step. Historically, we find that anthropogenic influences account for up to fifty percent of explanatory power in the model. We also find that the total area burned is likely to increase, with burned area expected to increase by 2.2 and 5.0 percent by 2050 under climatic bookends (PCM and GFDL climate models, respectively). Our two climate models show considerable agreement, but due to potential shifts in rainfall patterns, substantial uncertainty remains for the semiarid inland deserts and coastal areas of the south. Given the strength of human-related variables in some regions, however, it is clear that comprehensive projections of future fire activity should include both anthropogenic and biophysical influences. Previous findings of substantially increased numbers of fires and burned area for California may be tied to omitted variable bias from the exclusion of human influences. The omission of anthropogenic variables in our model would overstate the importance of climatic ones by at least 24%. As such, the failure to include anthropogenic effects in many models likely overstates the response of wildfire to climatic change.

Incorporating Anthropogenic Influences into Fire Probability Models: Effects of Human Activity and Climate Change on Fire Activity in California

PubMed Central

Batllori, Enric; Moritz, Max A.; Waller, Eric K.; Berck, Peter; Flint, Alan L.; Flint, Lorraine E.; Dolfi, Emmalee

2016-01-01

The costly interactions between humans and wildfires throughout California demonstrate the need to understand the relationships between them, especially in the face of a changing climate and expanding human communities. Although a number of statistical and process-based wildfire models exist for California, there is enormous uncertainty about the location and number of future fires, with previously published estimates of increases ranging from nine to fifty-three percent by the end of the century. Our goal is to assess the role of climate and anthropogenic influences on the state’s fire regimes from 1975 to 2050. We develop an empirical model that integrates estimates of biophysical indicators relevant to plant communities and anthropogenic influences at each forecast time step. Historically, we find that anthropogenic influences account for up to fifty percent of explanatory power in the model. We also find that the total area burned is likely to increase, with burned area expected to increase by 2.2 and 5.0 percent by 2050 under climatic bookends (PCM and GFDL climate models, respectively). Our two climate models show considerable agreement, but due to potential shifts in rainfall patterns, substantial uncertainty remains for the semiarid inland deserts and coastal areas of the south. Given the strength of human-related variables in some regions, however, it is clear that comprehensive projections of future fire activity should include both anthropogenic and biophysical influences. Previous findings of substantially increased numbers of fires and burned area for California may be tied to omitted variable bias from the exclusion of human influences. The omission of anthropogenic variables in our model would overstate the importance of climatic ones by at least 24%. As such, the failure to include anthropogenic effects in many models likely overstates the response of wildfire to climatic change. PMID:27124597

Climate Variability, Social and Environmental Factors, and Ross River Virus Transmission: Research Development and Future Research Needs

PubMed Central

Tong, Shilu; Dale, Pat; Nicholls, Neville; Mackenzie, John S.; Wolff, Rodney; McMichael, Anthony J.

2008-01-01

Background Arbovirus diseases have emerged as a global public health concern. However, the impact of climatic, social, and environmental variability on the transmission of arbovirus diseases remains to be determined. Objective Our goal for this study was to provide an overview of research development and future research directions about the interrelationship between climate variability, social and environmental factors, and the transmission of Ross River virus (RRV), the most common and widespread arbovirus disease in Australia. Methods We conducted a systematic literature search on climatic, social, and environmental factors and RRV disease. Potentially relevant studies were identified from a series of electronic searches. Results The body of evidence revealed that the transmission cycles of RRV disease appear to be sensitive to climate and tidal variability. Rainfall, temperature, and high tides were among major determinants of the transmission of RRV disease at the macro level. However, the nature and magnitude of the interrelationship between climate variability, mosquito density, and the transmission of RRV disease varied with geographic area and socioenvironmental condition. Projected anthropogenic global climatic change may result in an increase in RRV infections, and the key determinants of RRV transmission we have identified here may be useful in the development of an early warning system. Conclusions The analysis indicates that there is a complex relationship between climate variability, social and environmental factors, and RRV transmission. Different strategies may be needed for the control and prevention of RRV disease at different levels. These research findings could be used as an additional tool to support decision making in disease control/surveillance and risk management. PMID:19079707

Sensitivity of crop cover to climate variability: insights from two Indian agro-ecoregions.

PubMed

Mondal, Pinki; Jain, Meha; DeFries, Ruth S; Galford, Gillian L; Small, Christopher

2015-01-15

Crop productivity in India varies greatly with inter-annual climate variability and is highly dependent on monsoon rainfall and temperature. The sensitivity of yields to future climate variability varies with crop type, access to irrigation and other biophysical and socio-economic factors. To better understand sensitivities to future climate, this study focuses on agro-ecological subregions in Central and Western India that span a range of crops, irrigation, biophysical conditions and socioeconomic characteristics. Climate variability is derived from remotely-sensed data products, Tropical Rainfall Measuring Mission (TRMM - precipitation) and Moderate Resolution Imaging Spectroradiometer (MODIS - temperature). We examined green-leaf phenologies as proxy for crop productivity using the MODIS Enhanced Vegetation Index (EVI) from 2000 to 2012. Using both monsoon and winter growing seasons, we assessed phenological sensitivity to inter-annual variability in precipitation and temperature patterns. Inter-annual EVI phenology anomalies ranged from -25% to 25%, with some highly anomalous values up to 200%. Monsoon crop phenology in the Central India site is highly sensitive to climate, especially the timing of the start and end of the monsoon and intensity of precipitation. In the Western India site, monsoon crop phenology is less sensitive to precipitation variability, yet shows considerable fluctuations in monsoon crop productivity across the years. Temperature is critically important for winter productivity across a range of crop and management types, such that irrigation might not provide a sufficient buffer against projected temperature increases. Better access to weather information and usage of climate-resilient crop types would play pivotal role in maintaining future productivity. Effective strategies to adapt to projected climate changes in the coming decades would also need to be tailored to regional biophysical and socio-economic conditions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Uncertainties in Future Regional Sea Level Trends: How to Deal with the Internal Climate Variability?

NASA Astrophysics Data System (ADS)

Becker, M.; Karpytchev, M.; Hu, A.; Deser, C.; Lennartz-Sassinek, S.

2017-12-01

Today, the Climate models (CM) are the main tools for forecasting sea level rise (SLR) at global and regional scales. The CM forecasts are accompanied by inherent uncertainties. Understanding and reducing these uncertainties is becoming a matter of increasing urgency in order to provide robust estimates of SLR impact on coastal societies, which need sustainable choices of climate adaptation strategy. These CM uncertainties are linked to structural model formulation, initial conditions, emission scenario and internal variability. The internal variability is due to complex non-linear interactions within the Earth Climate System and can induce diverse quasi-periodic oscillatory modes and long-term persistences. To quantify the effects of internal variability, most studies used multi-model ensembles or sea level projections from a single model ran with perturbed initial conditions. However, large ensembles are not generally available, or too small, and computationally expensive. In this study, we use a power-law scaling of sea level fluctuations, as observed in many other geophysical signals and natural systems, which can be used to characterize the internal climate variability. From this specific statistical framework, we (1) use the pre-industrial control run of the National Center for Atmospheric Research Community Climate System Model (NCAR-CCSM) to test the robustness of the power-law scaling hypothesis; (2) employ the power-law statistics as a tool for assessing the spread of regional sea level projections due to the internal climate variability for the 21st century NCAR-CCSM; (3) compare the uncertainties in predicted sea level changes obtained from a NCAR-CCSM multi-member ensemble simulations with estimates derived for power-law processes, and (4) explore the sensitivity of spatial patterns of the internal variability and its effects on regional sea level projections.

Climate variability differentially impacts thermal fitness traits in three coprophagic beetle species.

PubMed

Nyamukondiwa, Casper; Chidawanyika, Frank; Machekano, Honest; Mutamiswa, Reyard; Sands, Bryony; Mgidiswa, Neludo; Wall, Richard

2018-01-01

While the impacts of extreme and rising mean temperatures are well documented, increased thermal variability associated with climate change may also threaten ectotherm fitness and survival, but remains poorly explored. Using three wild collected coprophagic species Copris elphenor, Metacatharsius opacus and Scarabaeus zambezianus, we explored the effects of thermal amplitude around the mean on thermal tolerance. Using standardized protocols, we measured traits of high- (critical thermal maxima [CTmax] and heat knockdown time [HKDT]) and -low temperature tolerance (critical thermal minima [CTmin], chill coma recovery time [CCRT] and supercooling points [SCPs]) following variable temperature pulses (δ0, δ3, δ6 and δ9°C) around the mean (27°C). Our results show that increased temperature variability may offset basal and plastic responses to temperature and differs across species and metrics tested. Furthermore, we also show differential effects of body mass, body water content (BWC) and body lipid content (BLC) on traits of thermal tolerance. For example, body mass significantly influenced C. elphenor and S. zambezianus CTmax and S. zambezianus HKDT but not CTmin and CCRT. BWC significantly affected M. opacus and C. elphenor CTmax and in only M. opacus HKDT, CTmin and CCRT. Similarly, BLC only had a significant effect for M opacus CTmin. These results suggest differential and species dependent effects of climate variability of thermal fitness traits. It is therefore likely that the ecological services provided by these species may be constrained in the face of climate change. This implies that, to develop more realistic predictions for the effects of climate change on insect biodiversity and ecosystem function, thermal variability is a significant determinant.

Effects of simulated daily precipitation patterns on annual plant populations depend on life stage and climatic region.

PubMed

Köchy, Martin

2008-03-27

To improve the understanding of consequences of climate change for annual plant communities, I used a detailed, grid-based model that simulates the effect of daily rainfall variability on individual plants in five climatic regions on a gradient from 100 to 800 mm mean annual precipitation (MAP). The model explicitly considers moisture storage in the soil. I manipulated daily rainfall variability by changing the daily mean rain (DMR, rain volume on rainy days averaged across years for each day of the year) by +/- 20%. At the same time I adjusted intervals appropriately between rainy days for keeping the mean annual volume constant. In factorial combination with changing DMR I also changed MAP by +/- 20%. Increasing MAP generally increased water availability, establishment, and peak shoot biomass. Increasing DMR increased the time that water was continuously available to plants in the upper 15 to 30 cm of the soil (longest wet period, LWP). The effect of DMR diminished with increasing humidity of the climate. An interaction between water availability and density-dependent germination increased the establishment of seedlings in the arid region, but in the more humid regions the establishment of seedlings decreased with increasing DMR. As plants matured, competition among individuals and their productivity increased, but the size of these effects decreased with the humidity of the regions. Therefore, peak shoot biomass generally increased with increasing DMR but the effect size diminished from the semiarid to the mesic Mediterranean region. Increasing DMR reduced via LWP the annual variability of biomass in the semiarid and dry Mediterranean regions. More rainstorms (greater DMR) increased the recharge of soil water reservoirs in more arid sites with consequences for germination, establishment, productivity, and population persistence. The order of magnitudes of DMR and MAP overlapped partially so that their combined effect is important for projections of climate change effects on annual vegetation.

Readings from Visibility Meters: Do They Really Mean the Maximum Distance of Observing A Black Object?

NASA Astrophysics Data System (ADS)

Li, M.; Zhang, S.; Garcia-Menendez, F.; Monier, E.; Selin, N. E.

2016-12-01

Climate change, favoring more heat waves and episodes of stagnant air, may deteriorate air quality by increasing ozone and fine particulate matter (PM2.5) concentrations and high pollution episodes. This effect, termed as "climate penalty", has been quantified and explained by many earlier studies in the U.S. and Europe, but research efforts in Asian countries are limited. We evaluate the impact of climate change on air quality and human health in China and India using a modeling framework that links the Massachusetts Institute of Technology Integrated Global System Model to the Community Atmosphere Model (MIT IGSM-CAM). Future climate fields are projected under three climate scenarios including a no-policy reference scenario and two climate stabilization scenarios with 2100 total radiative forcing targets of 9.7, 4.5 and 3.7 W m-2, respectively. Each climate scenario is run for five representations of climate variability to account for the role of natural variability. Thirty-year chemical transport simulations are conducted in 1981-2010 and 2086-2115 under the three climate scenarios with fixed anthropogenic emissions at year 2000 levels. We find that 2000—2100 climate change under the no-policy reference scenario would increase ozone concentrations in eastern China and northern India by up to 5 ppb through enhancing biogenic emissions and ozone production efficiency. Ozone extreme episodes also become more frequent in these regions, while climate policies can offset most of the increase in ozone episodes. Climate change between 2000 and 2100 would slightly increase anthropogenic PM2.5 concentrations in northern China and Sichuan province, but significantly reduce anthropogenic PM2.5 concentrations in southern China and northern India, primarily due to different chemical responses of sulfate-nitrate-ammonium aerosols to climate change in these regions. Our study also suggests that the mitigation costs of climate policies can be partially offset by health benefits from reduced climate-induced air pollution in China.

Oscillations and trends of river discharge in the southern Central Andes and linkages with climate variability

NASA Astrophysics Data System (ADS)

Castino, Fabiana; Bookhagen, Bodo; Strecker, Manfred R.

2017-12-01

This study analyzes the discharge variability of small to medium drainage basins (102-104 km2) in the southern Central Andes of NW Argentina. The Hilbert-Huang Transform (HHT) was applied to evaluate non-stationary oscillatory modes of variability and trends, based on four time series of monthly-normalized discharge anomaly between 1940 and 2015. Statistically significant trends reveal increasing discharge during the past decades and document an intensification of the hydrological cycle during this period. An Ensemble Empirical Mode Decomposition (EEMD) analysis revealed that discharge variability in this region can be best described by five quasi-periodic statistically significant oscillatory modes, with mean periods varying from 1 to ∼20 y. Moreover, we show that discharge variability is most likely linked to the phases of the Pacific Decadal Oscillation (PDO) at multi-decadal timescales (∼20 y) and, to a lesser degree, to the Tropical South Atlantic SST anomaly (TSA) variability at shorter timescales (∼2-5 y). Previous studies highlighted a rapid increase in discharge in the southern Central Andes during the 1970s, inferred to have been associated with the global 1976-77 climate shift. Our results suggest that the rapid discharge increase in the NW Argentine Andes coincides with the periodic enhancement of discharge, which is mainly linked to a negative to positive transition of the PDO phase and TSA variability associated with a long-term increasing trend. We therefore suggest that variations in discharge in this region are largely driven by both natural variability and the effects of global climate change. We furthermore posit that the links between atmospheric and hydrologic processes result from a combination of forcings that operate on different spatiotemporal scales.

Impacts of Climate Change/Variability and Human Activities on Contemporary Vegetation Productivity across Africa

NASA Astrophysics Data System (ADS)

Ugbaje, S. U.; Odeh, I. A.; Bishop, T.

2015-12-01

Vegetation productivity is increasingly being impacted upon by climate change/variability and anthropogenic activities, especially in developing countries, where many livelihoods depend on the natural resource base. Despite these impacts, the individual and combined roles of climate and anthropogenic factors on vegetation dynamics have rarely been quantified in many ecosystems and regions of the world. This paper analyzes recent trend in vegetation productivity across Africa and quantified the relative roles of climate change/variability and human activities in driving this trend over 2000-2014 using net primary productivity (NPP) as an indicator. The relative roles of these factors to vegetation productivity change were quantified by comparing the trend slope (p<0.1) and total change in interannual actual NPP (NPPA), potential NPP (NPPP), and human appropriated NPP (NPPH). NPP significantly increased across Africa relative to NPP decline, though the extent of NPP decline is also quite appreciable. Whereas estimated NPP declined by 207 Tg C over 140 X 104 km of land area, vegetation productivity was estimated to improve by 1415 Tg C over 786 X 104 km of land area. NPP improvement is largely concentrated in equatorial and northern hemispheric Africa, while subequatorial Africa exhibited the most NPP decline. Generally, anthropogenic activities dominated climate change/variability in improving or degrading vegetation productivity. Of the estimated total NPP gained over the study period, 32.6, 8.8, and 58.6 % were due to individual human, climate and combined impacts respectively. The contributions of the factors to NPP decline in the same order are: 50.7, 16.0 and 33.3 %. The Central Africa region is where human activities had the greatest impact on NPP improvement; whereas the Sahel and the coastlines of west northern Africa are areas associated with the greatest influence of climate-driven NPP gain. Areas with humans dominating NPP degradation include eastern Angola, western Zambia, and Liberia; whereas climate-driven NPP loss is pronounced in Zambia and Mozambique. Results from this study indicate that, compared to climate change/variability, contemporary anthropogenic activities are contributing more to the decline of Africa's vegetation productivity than to vegetation improvement.

Describing rainfall in northern Australia using multiple climate indices

NASA Astrophysics Data System (ADS)

Wilks Rogers, Cassandra Denise; Beringer, Jason

2017-02-01

Savanna landscapes are globally extensive and highly sensitive to climate change, yet the physical processes and climate phenomena which affect them remain poorly understood and therefore poorly represented in climate models. Both human populations and natural ecosystems are highly susceptible to precipitation variation in these regions due to the effects on water and food availability and atmosphere-biosphere energy fluxes. Here we quantify the relationship between climate phenomena and historical rainfall variability in Australian savannas and, in particular, how these relationships changed across a strong rainfall gradient, namely the North Australian Tropical Transect (NATT). Climate phenomena were described by 16 relevant climate indices and correlated against precipitation from 1900 to 2010 to determine the relative importance of each climate index on seasonal, annual and decadal timescales. Precipitation trends, climate index trends and wet season characteristics have also been investigated using linear statistical methods. In general, climate index-rainfall correlations were stronger in the north of the NATT where annual rainfall variability was lower and a high proportion of rainfall fell during the wet season. This is consistent with a decreased influence of the Indian-Australian monsoon from the north to the south. Seasonal variation was most strongly correlated with the Australian Monsoon Index, whereas yearly variability was related to a greater number of climate indices, predominately the Tasman Sea and Indonesian sea surface temperature indices (both of which experienced a linear increase over the duration of the study) and the El Niño-Southern Oscillation indices. These findings highlight the importance of understanding the climatic processes driving variability and, subsequently, the importance of understanding the relationships between rainfall and climatic phenomena in the Northern Territory in order to project future rainfall patterns in the region.

A Brazilian Vulnerability Index Towards Natural Disasters and Climatic Change - Flashfloods and Landslides.

NASA Astrophysics Data System (ADS)

Debortoli, N. S.; Camarinha, P. I., Sr.; Marengo, J. A.; Rodrigues, R.

2015-12-01

There are some evidences that hydrological climate extremes events have become more frequent an intense in the last decades due to climatic change. In Brazil, flashfloods and landslides were responsible for 74% of the deaths related to natural disasters in 1991-2010 period. In this sense, climate change could be considered a threat which can further increase these numbers, if actions of adaptation and reducing vulnerability are not taken. To evaluate Brazil's vulnerability hotspots to these disasters, two vulnerability indexes were developed using three sets of variables: (1) climate, with IPCC climate extreme indexes; (2) environmental, including land use, drainage systems, relief map, slope, road density and hydrography variables; (3) socioeconomic, including Gini coefficient, HDI (Human Development Index), housing conditions and poverty-related index. The variables were normalized on a scale between 0 to 1 and related using Map Algebra technique (ArcGIS). As part of the effort to contribute to the elaboration of the Third National Communication to the United Nations Framework Convention on Climate Change (UNFCCC), and to contribute to the assessment of impacts on strategic country's issues, simulations at higher resolution were carried out using Eta-20km RCM (Regional Climate Model) nested with two global climate models: HadGEM ES and MIROC 5 (INPE Brazilian National Institute for Space Research). For the baseline period of 1961-1990, the vulnerability indexes were adjusted by an iterative process, which was validated by comparing it to the Brazilian National Disasters Data. The same indexes found at baseline were used to estimate the vulnerability until the end of the XXI century, using the 4.5 and 8.5 IPCC/AR5 RCP (Representative Concentration Pathways) scenarios. The results indicate a large increase in Brazil's vulnerability to landslides mainly in coastal zone, southern states, high lands of southeast states, and along the Amazon River due to climatic aspects only, not considering other factors such as increase in population size, etc. Flashfloods vulnerability, on the other hand, increases mostly in the south/southeast regions, the northeast coastal zone and parts of the Amazon basin. Funded by: Ministry of Science and Technology of Brazil and the United Nations Development Program in Brazil.

Slope Controls Grain Yield and Climatic Yield in Mountainous Yunnan province, China

NASA Astrophysics Data System (ADS)

Duan, X.; Rong, L.; Gu, Z.; Feng, D.

2017-12-01

Mountainous regions are increasingly vulnerable to food insecurity because of limited arable land, growing population pressure, and climate change. Development of sustainable mountain agriculture will require an increased understanding of the effects of environmental factors on grain and climatic yields. The objective of this study was to explore the relationships between actual grain yield, climatic yield, and environmental factors in a mountainous region in China. We collected data on the average grain yield per unit area in 119 counties in Yunnan province from 1985 to 2012, and chose 17 environmental factors for the same period. Our results showed that actual grain yield ranged from 1.43 to 6.92 t·ha-1, and the climatic yield ranged from -0.15 to -0.01 t·ha-1. Lower climatic yield but higher grain yield was generally found in central areas and at lower slopes and elevations in the western and southwestern counties of Yunnan province. Higher climatic yield but lower grain yield were found in northwestern parts of Yunnan province on steep slopes. Annual precipation and temperature had a weak influence on the climatic yield. Slope explained 44.62 and 26.29% of the variation in grain yield and climatic yield. The effects of topography on grain and climatic yields were greater than climatic factors. Slope was the most important environmental variable for the variability in climatic and grain yields in the mountainous Yunnan province due to the highly heterogeneous topographic conditions. Conversion of slopes to terraces in areas with higher climatic yields is an effective way to maintain grain production in response to climate variability. Additionally, soil amendments and soil and water conservation measures should be considered to maintain soil fertility and aid in sustainable development in central areas, and in counties at lower slopes and elevations in western and southwestern Yunnan province.

Hurricanes and Climate: The U.S. CLIVAR Working Group on Hurricanes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walsh, Kevin J. E.; Camargo, Suzana J.; Vecchi, Gabriel A.

While a quantitative climate theory of tropical cyclone formation remains elusive, considerable progress has been made recently in our ability to simulate tropical cyclone climatologies and to understand the relationship between climate and tropical cyclone formation. Climate models are now able to simulate a realistic rate of global tropical cyclone formation, although simulation of the Atlantic tropical cyclone climatology remains challenging unless horizontal resolutions finer than 50 km are employed. This article summarizes published research from the idealized experiments of the Hurricane Working Group of U.S. Climate and Ocean: Variability, Predictability and Change (CLIVAR). This work, combined with results frommore » other model simulations, has strengthened relationships between tropical cyclone formation rates and climate variables such as midtropospheric vertical velocity, with decreased climatological vertical velocities leading to decreased tropical cyclone formation. Systematic differences are shown between experiments in which only sea surface temperature is increased compared with experiments where only atmospheric carbon dioxide is increased. Experiments where only carbon dioxide is increased are more likely to demonstrate a decrease in tropical cyclone numbers, similar to the decreases simulated by many climate models for a future, warmer climate. Experiments where the two effects are combined also show decreases in numbers, but these tend to be less for models that demonstrate a strong tropical cyclone response to increased sea surface temperatures. Lastly, further experiments are proposed that may improve our understanding of the relationship between climate and tropical cyclone formation, including experiments with two-way interaction between the ocean and the atmosphere and variations in atmospheric aerosols.« less

Hurricanes and Climate: The U.S. CLIVAR Working Group on Hurricanes

DOE PAGES

Walsh, Kevin J. E.; Camargo, Suzana J.; Vecchi, Gabriel A.; ...

2015-06-01

While a quantitative climate theory of tropical cyclone formation remains elusive, considerable progress has been made recently in our ability to simulate tropical cyclone climatologies and to understand the relationship between climate and tropical cyclone formation. Climate models are now able to simulate a realistic rate of global tropical cyclone formation, although simulation of the Atlantic tropical cyclone climatology remains challenging unless horizontal resolutions finer than 50 km are employed. This article summarizes published research from the idealized experiments of the Hurricane Working Group of U.S. Climate and Ocean: Variability, Predictability and Change (CLIVAR). This work, combined with results frommore » other model simulations, has strengthened relationships between tropical cyclone formation rates and climate variables such as midtropospheric vertical velocity, with decreased climatological vertical velocities leading to decreased tropical cyclone formation. Systematic differences are shown between experiments in which only sea surface temperature is increased compared with experiments where only atmospheric carbon dioxide is increased. Experiments where only carbon dioxide is increased are more likely to demonstrate a decrease in tropical cyclone numbers, similar to the decreases simulated by many climate models for a future, warmer climate. Experiments where the two effects are combined also show decreases in numbers, but these tend to be less for models that demonstrate a strong tropical cyclone response to increased sea surface temperatures. Lastly, further experiments are proposed that may improve our understanding of the relationship between climate and tropical cyclone formation, including experiments with two-way interaction between the ocean and the atmosphere and variations in atmospheric aerosols.« less

Effects of changing climate on European stream invertebrate communities: A long-term data analysis.

PubMed

Jourdan, Jonas; O'Hara, Robert B; Bottarin, Roberta; Huttunen, Kaisa-Leena; Kuemmerlen, Mathias; Monteith, Don; Muotka, Timo; Ozoliņš, Dāvis; Paavola, Riku; Pilotto, Francesca; Springe, Gunta; Skuja, Agnija; Sundermann, Andrea; Tonkin, Jonathan D; Haase, Peter

2018-04-15

Long-term observations on riverine benthic invertebrate communities enable assessments of the potential impacts of global change on stream ecosystems. Besides increasing average temperatures, many studies predict greater temperature extremes and intense precipitation events as a consequence of climate change. In this study we examined long-term observation data (10-32years) of 26 streams and rivers from four ecoregions in the European Long-Term Ecological Research (LTER) network, to investigate invertebrate community responses to changing climatic conditions. We used functional trait and multi-taxonomic analyses and combined examinations of general long-term changes in communities with detailed analyses of the impact of different climatic drivers (i.e., various temperature and precipitation variables) by focusing on the response of communities to climatic conditions of the previous year. Taxa and ecoregions differed substantially in their response to climate change conditions. We did not observe any trend of changes in total taxonomic richness or overall abundance over time or with increasing temperatures, which reflects a compensatory turnover in the composition of communities; sensitive Plecoptera decreased in response to warmer years and Ephemeroptera increased in northern regions. Invasive species increased with an increasing number of extreme days which also caused an apparent upstream community movement. The observed changes in functional feeding group diversity indicate that climate change may be associated with changes in trophic interactions within aquatic food webs. These findings highlight the vulnerability of riverine ecosystems to climate change and emphasize the need to further explore the interactive effects of climate change variables with other local stressors to develop appropriate conservation measures. Copyright © 2017 Elsevier B.V. All rights reserved.

Climate Change and Spatiotemporal Distributions of Vector-Borne Diseases in Nepal--A Systematic Synthesis of Literature.

PubMed

Dhimal, Meghnath; Ahrens, Bodo; Kuch, Ulrich

2015-01-01

Despite its largely mountainous terrain for which this Himalayan country is a popular tourist destination, Nepal is now endemic for five major vector-borne diseases (VBDs), namely malaria, lymphatic filariasis, Japanese encephalitis, visceral leishmaniasis and dengue fever. There is increasing evidence about the impacts of climate change on VBDs especially in tropical highlands and temperate regions. Our aim is to explore whether the observed spatiotemporal distributions of VBDs in Nepal can be related to climate change. A systematic literature search was performed and summarized information on climate change and the spatiotemporal distribution of VBDs in Nepal from the published literature until December 2014 following providing items for systematic review and meta-analysis (PRISMA) guidelines. We found 12 studies that analysed the trend of climatic data and are relevant for the study of VBDs, 38 studies that dealt with the spatial and temporal distribution of disease vectors and disease transmission. Among 38 studies, only eight studies assessed the association of VBDs with climatic variables. Our review highlights a pronounced warming in the mountains and an expansion of autochthonous cases of VBDs to non-endemic areas including mountain regions (i.e., at least 2,000 m above sea level). Furthermore, significant relationships between climatic variables and VBDs and their vectors are found in short-term studies. Taking into account the weak health care systems and difficult geographic terrain of Nepal, increasing trade and movements of people, a lack of vector control interventions, observed relationships between climatic variables and VBDs and their vectors and the establishment of relevant disease vectors already at least 2,000 m above sea level, we conclude that climate change can intensify the risk of VBD epidemics in the mountain regions of Nepal if other non-climatic drivers of VBDs remain constant.

US Power Production at Risk from Water Stress in a Changing Climate.

PubMed

Ganguli, Poulomi; Kumar, Devashish; Ganguly, Auroop R

2017-09-20

Thermoelectric power production in the United States primarily relies on wet-cooled plants, which in turn require water below prescribed design temperatures, both for cooling and operational efficiency. Thus, power production in US remains particularly vulnerable to water scarcity and rising stream temperatures under climate change and variability. Previous studies on the climate-water-energy nexus have primarily focused on mid- to end-century horizons and have not considered the full range of uncertainty in climate projections. Technology managers and energy policy makers are increasingly interested in the decadal time scales to understand adaptation challenges and investment strategies. Here we develop a new approach that relies on a novel multivariate water stress index, which considers the joint probability of warmer and scarcer water, and computes uncertainties arising from climate model imperfections and intrinsic variability. Our assessments over contiguous US suggest consistent increase in water stress for power production with about 27% of the production severely impacted by 2030s.

Ensemble Prediction of Tropical Cyclone Genesis

DTIC Science & Technology

2017-02-23

future changes in tropical cyclone (TC) activity around the Hawaiian Islands are investigated using the state-of-the-art climate models1–3. We find that...future warmer climate . This is in contrast to the NA, where BDI increases for all dynamic variables investigated while it shows little change for...Li, and A. Kitoh, 2013: Projected future increase in tropical cyclones near Hawaii. Nature Climate Change , 3, 749-754, doi:10.1038/nclimate1890

Increasing influence of heat stress on French maize yields from the 1960s to the 2030s

PubMed Central

Hawkins, Ed; Fricker, Thomas E; Challinor, Andrew J; Ferro, Christopher A T; Kit Ho, Chun; Osborne, Tom M

2013-01-01

Improved crop yield forecasts could enable more effective adaptation to climate variability and change. Here, we explore how to combine historical observations of crop yields and weather with climate model simulations to produce crop yield projections for decision relevant timescales. Firstly, the effects on historical crop yields of improved technology, precipitation and daily maximum temperatures are modelled empirically, accounting for a nonlinear technology trend and interactions between temperature and precipitation, and applied specifically for a case study of maize in France. The relative importance of precipitation variability for maize yields in France has decreased significantly since the 1960s, likely due to increased irrigation. In addition, heat stress is found to be as important for yield as precipitation since around 2000. A significant reduction in maize yield is found for each day with a maximum temperature above 32 °C, in broad agreement with previous estimates. The recent increase in such hot days has likely contributed to the observed yield stagnation. Furthermore, a general method for producing near-term crop yield projections, based on climate model simulations, is developed and utilized. We use projections of future daily maximum temperatures to assess the likely change in yields due to variations in climate. Importantly, we calibrate the climate model projections using observed data to ensure both reliable temperature mean and daily variability characteristics, and demonstrate that these methods work using retrospective predictions. We conclude that, to offset the projected increased daily maximum temperatures over France, improved technology will need to increase base level yields by 12% to be confident about maintaining current levels of yield for the period 2016–2035; the current rate of yield technology increase is not sufficient to meet this target. PMID:23504849

Water governance: learning by developing adaptive capacity to incorporate climate variability and change.

PubMed

Kashyap, A

2004-01-01

There is increasing evidence that global climate variability and change is affecting the quality and availability of water supplies. Integrated water resources development, use, and management strategies, represent an effective approach to achieve sustainable development of water resources in a changing environment with competing demands. It is also a key to achieving the Millennium Development Goals. It is critical that integrated water management strategies must incorporate the impacts of climate variability and change to reduce vulnerability of the poor, strengthen sustainable livelihoods and support national sustainable development. UNDP's strategy focuses on developing adaptation in the water governance sector as an entry point within the framework of poverty reduction and national sustainable development. This strategy aims to strengthen the capacity of governments and civil society organizations to have access to early warning systems, ability to assess the impact of climate variability and change on integrated water resources management, and developing adaptation intervention through hands-on learning by undertaking pilot activities.

Towards a More Biologically-meaningful Climate Characterization: Variability in Space and Time at Multiple Scales

NASA Astrophysics Data System (ADS)

Christianson, D. S.; Kaufman, C. G.; Kueppers, L. M.; Harte, J.

2013-12-01

Sampling limitations and current modeling capacity justify the common use of mean temperature values in summaries of historical climate and future projections. However, a monthly mean temperature representing a 1-km2 area on the landscape is often unable to capture the climate complexity driving organismal and ecological processes. Estimates of variability in addition to mean values are more biologically meaningful and have been shown to improve projections of range shifts for certain species. Historical analyses of variance and extreme events at coarse spatial scales, as well as coarse-scale projections, show increasing temporal variability in temperature with warmer means. Few studies have considered how spatial variance changes with warming, and analysis for both temporal and spatial variability across scales is lacking. It is unclear how the spatial variability of fine-scale conditions relevant to plant and animal individuals may change given warmer coarse-scale mean values. A change in spatial variability will affect the availability of suitable habitat on the landscape and thus, will influence future species ranges. By characterizing variability across both temporal and spatial scales, we can account for potential bias in species range projections that use coarse climate data and enable improvements to current models. In this study, we use temperature data at multiple spatial and temporal scales to characterize spatial and temporal variability under a warmer climate, i.e., increased mean temperatures. Observational data from the Sierra Nevada (California, USA), experimental climate manipulation data from the eastern and western slopes of the Rocky Mountains (Colorado, USA), projected CMIP5 data for California (USA) and observed PRISM data (USA) allow us to compare characteristics of a mean-variance relationship across spatial scales ranging from sub-meter2 to 10,000 km2 and across temporal scales ranging from hours to decades. Preliminary spatial analysis at fine-spatial scales (sub-meter to 10-meter) shows greater temperature variability with warmer mean temperatures. This is inconsistent with the inherent assumption made in current species distribution models that fine-scale variability is static, implying that current projections of future species ranges may be biased -- the direction and magnitude requiring further study. While we focus our findings on the cross-scaling characteristics of temporal and spatial variability, we also compare the mean-variance relationship between 1) experimental climate manipulations and observed conditions and 2) temporal versus spatial variance, i.e., variability in a time-series at one location vs. variability across a landscape at a single time. The former informs the rich debate concerning the ability to experimentally mimic a warmer future. The latter informs space-for-time study design and analyses, as well as species persistence via a combined spatiotemporal probability of suitable future habitat.

Climate Change Impacts on the Hydrology and Productivity of a Pine Plantation

Treesearch

Ge Sun; Devendra M. Amatya; Steven G. McNulty; R. Wayne Skaggs; Joseph H. Hughes

2000-01-01

There are increasing concerns in the forestry community about global climate change and variability associated with elevated atmospheric CO2. Changes in precipitation and increases in air temperature could impose additional stress on forests during the next century. For a study site in Carteret County, North Carolina, the General Circulation...

Assessing surface water availability considering human water use and projected climate variability

NASA Astrophysics Data System (ADS)

Ashraf, Batool; AghaKouchak, Amir; Mousavi-Baygi, Mohammd; Moftakhari, Hamed; Anjileli, Hassan

2017-04-01

Climate variability along with anthropogenic activities alter the hydrological cycle and local water availability. The overarching goal of this presentation is to demonstrate the compounding interactions between human water use/withdrawals and climate change and variability. We focus on Karkheh River basin and Urmia basin, in western Iran, that have high level of human activity and water use, and suffer from low water productivity. The future of these basins and their growth relies on sustainable water resources and hence, requires a holistic, basin-wide management to cope with water scarcity challenges. In this study, we investigate changes in the hydrology of the basin including human-induced alterations of the system, during the past three decades. Then, we investigate the individual and combined effects of climate variability and human water withdrawals on surface water storage in the 21st century. We use bias-corrected historical simulations and future projections from ensemble mean of eleven General Circulation Models (GCMs) under two climate change scenarios RCP4.5 and RCP8.5. The results show that, hydrology of the studied basins are significantly dominated by human activities over the baseline period (1976 - 2005). Results show that the increased anthropogenic water demand resulting from substantial socio-economic growth in the past three decades have put significant stress on water resources. We evaluate a number of future water demand scenarios and their interactions with future climate projections. Our results show that by the end of the 21st century, the compounding effects of increased irrigation water demand and precipitation variability may lead to severe local water scarcity in these basins. Our study highlights the necessity for understanding and considering the compounding effects of human water use and future climate projections. Such studies would be useful for improving water management and developing adaption plans in water scarce regions.

Climate change and wildfires

Treesearch

William J. De Groot; Michael D. Flannigan; Brian J. Stocks

2013-01-01

Wildland fire regimes are primarily driven by climate/weather, fuels and people. All of these factors are dynamic and their variable interactions create a mosaic of fire regimes around the world. Climate change will have a substantial impact on future fire regimes in many global regions. Current research suggests a general increase in area burned and fire occurrence...

Landscape, Climate and Hantavirus Cardiopulmonary Syndrome Outbreaks.

PubMed

Prist, Paula Ribeiro; D Andrea, Paulo Sérgio; Metzger, Jean Paul

2017-09-01

We performed a literature review in order to improve our understanding of how landscape and climate drivers affect HCPS outbreaks. Anthropogenic landscape changes such as forest loss, fragmentation and agricultural land uses are related with a boost in hantavirus reservoir species abundance and hantavirus prevalence in tropical areas, increasing HCPS risk. Additionally, higher precipitation, especially in arid regions, favors an increase in vegetational biomass, which augments the resources for reservoir rodents, also increasing HCPS risk. Although these relationships were observed, few studies described it so far, and the ones that did it are concentrated in few places. To guide future research on this issue, we build a conceptual model relating landscape and climate variables with HCPS outbreaks and identified research opportunities. We point out the need for studies addressing the effects of landscape configuration, temperature and the interaction between climate and landscape variables. Critical landscape thresholds are also highly relevant, once HCPS risk transmission can increase rapidly above a certain degree of landscape degradation. These studies could be relevant to implement preventive measures, creating landscapes that can mitigate disease spread risk.

ENSO activity during the last climate cycle using IFA

NASA Astrophysics Data System (ADS)

Leduc, Guillaume; Vidal, Laurence; Thirumalai, Kaustubh

2017-04-01

The El Niño / Southern Oscillation (ENSO) is the principal mode of interannual climate variability and affects key climate parameters such as low-latitude rainfall variability. Anticipating future ENSO variability under anthropogenic forcing is vital due to its profound socioeconomic impact. Fossil corals suggest that 20th century ENSO variance is particularly high as compared to other time periods of the Holocene (Cobb et al., 2013, Science), the Last Glacial Maximum (Ford et al., 2015, Science) and the last glacial period (Tudhope et al., 2001, Science). Yet, recent climate modeling experiments suggest an increase in the frequency of both El Niño (Cai et al., 2014, Nature Climate Change) and La Niña (Cai et al., 2015, Nature Climate Change) events. We have expanded an Individual Foraminifera Analysis (IFA) dataset using the thermocline-dwelling N. dutertrei on a marine core collected in the Panama Basin (Leduc et al., 2009, Paleoceanography), that has proven to be a skillful way to reconstruct the ENSO (Thirumalai et al., 2013, Paleoceanography). Our new IFA dataset comprehensively covers the Holocene, the last deglaciation and Termination II (MIS5/6) time windows. We will also use previously published data from the Marine Isotope Stage 3 (MIS3). Our dataset confirms variable ENSO intensity during the Holocene and weaker activity during LGM than during the Holocene. As a next step, ENSO activity will be discussed with respect to the contrasting climatic background of the analysed time windows (millenial-scale variability, Terminations).

To what extent does climate explain variations in reported malaria cases in early 20th century Uganda?

PubMed

Tompkins, Adrian M; Larsen, Laragh; McCreesh, Nicky; Taylor, David

2016-03-31

Malaria case statistics were analysed for the period 1926 to 1960 to identify inter-annual variations in malaria cases for the Uganda Protectorate. The analysis shows the mid-to-late 1930s to be a period of increased reported cases. After World War II, malaria cases trend down to a relative minimum in the early 1950s, before increasing rapidly after 1953 to the end of the decade. Data for the Western Province confirm these national trends, which at the time were attributed to a wide range of causes, including land development and management schemes, population mobility, interventions and misdiagnosis. Climate was occasionally proposed as a contributor to enhanced case numbers, and unusual precipitation patterns were held responsible; temperature was rarely, if ever, considered. In this study, a dynamical malaria model was driven with available precipitation and temperature data from the period for five stations located across a range of environments in Uganda. In line with the historical data, the simulations produced relatively enhanced transmission in the 1930s, although there is considerable variability between locations. In all locations, malaria transmission was low in the late 1940s and early 1950s, steeply increasing after 1954. Results indicate that past climate variability explains some of the variations in numbers of reported malaria cases. The impact of multiannual variability in temperature, while only on the order of 0.5°C, was sufficient to drive some of the trends observed in the statistics and thus the role of climate was likely underestimated in the contemporary reports. As the elimination campaigns of the 1960s followed this partly climate-driven increase in malaria, this emphasises the need to account for climate when planning and evaluating intervention strategies.

The influence of El Niño-Southern Oscillation regimes on eastern African vegetation and its future implications under the RCP8.5 warming scenario

NASA Astrophysics Data System (ADS)

Fer, Istem; Tietjen, Britta; Jeltsch, Florian; Wolff, Christian

2017-09-01

The El Niño-Southern Oscillation (ENSO) is the main driver of the interannual variability in eastern African rainfall, with a significant impact on vegetation and agriculture and dire consequences for food and social security. In this study, we identify and quantify the ENSO contribution to the eastern African rainfall variability to forecast future eastern African vegetation response to rainfall variability related to a predicted intensified ENSO. To differentiate the vegetation variability due to ENSO, we removed the ENSO signal from the climate data using empirical orthogonal teleconnection (EOT) analysis. Then, we simulated the ecosystem carbon and water fluxes under the historical climate without components related to ENSO teleconnections. We found ENSO-driven patterns in vegetation response and confirmed that EOT analysis can successfully produce coupled tropical Pacific sea surface temperature-eastern African rainfall teleconnection from observed datasets. We further simulated eastern African vegetation response under future climate change as it is projected by climate models and under future climate change combined with a predicted increased ENSO intensity. Our EOT analysis highlights that climate simulations are still not good at capturing rainfall variability due to ENSO, and as we show here the future vegetation would be different from what is simulated under these climate model outputs lacking accurate ENSO contribution. We simulated considerable differences in eastern African vegetation growth under the influence of an intensified ENSO regime which will bring further environmental stress to a region with a reduced capacity to adapt effects of global climate change and food security.

Elevated temperature is more effective than elevated [CO2 ] in exposing genotypic variation in Telopea speciosissima growth plasticity: implications for woody plant populations under climate change.

PubMed

Huang, Guomin; Rymer, Paul D; Duan, Honglang; Smith, Renee A; Tissue, David T

2015-10-01

Intraspecific variation in phenotypic plasticity is a critical determinant of plant species capacity to cope with climate change. A long-standing hypothesis states that greater levels of environmental variability will select for genotypes with greater phenotypic plasticity. However, few studies have examined how genotypes of woody species originating from contrasting environments respond to multiple climate change factors. Here, we investigated the main and interactive effects of elevated [CO2 ] (CE ) and elevated temperature (TE ) on growth and physiology of Coastal (warmer, less variable temperature environment) and Upland (cooler, more variable temperature environment) genotypes of an Australian woody species Telopea speciosissima. Both genotypes were positively responsive to CE (35% and 29% increase in whole-plant dry mass and leaf area, respectively), but only the Coastal genotype exhibited positive growth responses to TE . We found that the Coastal genotype exhibited greater growth response to TE (47% and 85% increase in whole-plant dry mass and leaf area, respectively) when compared with the Upland genotype (no change in dry mass or leaf area). No intraspecific variation in physiological plasticity was detected under CE or TE , and the interactive effects of CE and TE on intraspecific variation in phenotypic plasticity were also largely absent. Overall, TE was a more effective climate factor than CE in exposing genotypic variation in our woody species. Our results contradict the paradigm that genotypes from more variable climates will exhibit greater phenotypic plasticity in future climate regimes. © 2015 John Wiley & Sons Ltd.

Patterns of drought tolerance in major European temperate forest trees: climatic drivers and levels of variability.

PubMed

Zang, Christian; Hartl-Meier, Claudia; Dittmar, Christoph; Rothe, Andreas; Menzel, Annette

2014-12-01

The future performance of native tree species under climate change conditions is frequently discussed, since increasingly severe and more frequent drought events are expected to become a major risk for forest ecosystems. To improve our understanding of the drought tolerance of the three common European temperate forest tree species Norway spruce, silver fir and common beech, we tested the influence of climate and tree-specific traits on the inter and intrasite variability in drought responses of these species. Basal area increment data from a large tree-ring network in Southern Germany and Alpine Austria along a climatic cline from warm-dry to cool-wet conditions were used to calculate indices of tolerance to drought events and their variability at the level of individual trees and populations. General patterns of tolerance indicated a high vulnerability of Norway spruce in comparison to fir and beech and a strong influence of bioclimatic conditions on drought response for all species. On the level of individual trees, low-growth rates prior to drought events, high competitive status and low age favored resilience in growth response to drought. Consequently, drought events led to heterogeneous and variable response patterns in forests stands. These findings may support the idea of deliberately using spontaneous selection and adaption effects as a passive strategy of forest management under climate change conditions, especially a strong directional selection for more tolerant individuals when frequency and intensity of summer droughts will increase in the course of global climate change. © 2014 John Wiley & Sons Ltd.

Response Variability across Diverse Rice Accessions under Rising Temperature and Increasing Atmospheric Carbon Dioxide

USDA-ARS?s Scientific Manuscript database

Evaluating variability of rice response to concurrent increases in CO2 and temperature forecasted for future climates is a prerequisite step towards characterizing the genetic architecture underlying this response. Expanding on previous single cultivar studies, we evaluated eleven biogeographically ...

Assessing the impacts of climate and land use and land cover change on the freshwater availability in the Brahmaputra River basin

USGS Publications Warehouse

Pervez, Md Shahriar; Henebry, Geoffrey M.

2015-01-01

New hydrological insights for the region: Basin average annual ET was found to be sensitive to changes in CO2 concentration and temperature, while total water yield, streamflow, and groundwater recharge were sensitive to changes in precipitation. The basin hydrological components were predicted to increase with seasonal variability in response to climate and land use change scenarios. Strong increasing trends were predicted for total water yield, streamflow, and groundwater recharge, indicating exacerbation of flooding potential during August–October, but strong decreasing trends were predicted, indicating exacerbation of drought potential during May–July of the 21st century. The model has potential to facilitate strategic decision making through scenario generation integrating climate change adaptation and hazard mitigation policies to ensure optimized allocation of water resources under a variable and changing climate.

Impacts of climate change on the formation and stability of late Quaternary sand sheets and falling dunes, Black Mesa region, southern Colorado Plateau, USA

USGS Publications Warehouse

Ellwein, Amy L.; Mahan, Shannon; McFadden, Leslie D.

2015-01-01

Widely used predictive models of eolian system dynamics are typically based entirely on climatic variables and do not account for landscape complexity and geomorphic history. Climate-only assumptions fail to give accurate predictions of the dynamics of this and many other dune fields. A growing body of work suggests that eolian deposits in wind-driven semiarid climates may be more strongly related to increases in sediment supply than to increases in aridity.

Assessment of future impacts of potential climate change scenarios on aquifer recharge in continental Spain

NASA Astrophysics Data System (ADS)

Pulido-Velazquez, David; Collados-Lara, Antonio-Juan; Alcalá, Francisco J.

2017-04-01

This research proposes and applies a method to assess potential impacts of future climatic scenarios on aquifer rainfall recharge in wide and varied regions. The continental Spain territory was selected to show the application. The method requires to generate future series of climatic variables (precipitation, temperature) in the system to simulate them within a previously calibrated hydrological model for the historical data. In a previous work, Alcalá and Custodio (2014) used the atmospheric chloride mass balance (CMB) method for the spatial evaluation of average aquifer recharge by rainfall over the whole of continental Spain, by assuming long-term steady conditions of the balance variables. The distributed average CMB variables necessary to calculate recharge were estimated from available variable-length data series of variable quality and spatial coverage. The CMB variables were regionalized by ordinary kriging at the same 4976 nodes of a 10 km x 10 km grid. Two main sources of uncertainty affecting recharge estimates (given by the coefficient of variation, CV), induced by the inherent natural variability of the variables and from mapping were segregated. Based on these stationary results we define a simple empirical rainfall-recharge model. We consider that spatiotemporal variability of rainfall and temperature are the most important climatic feature and variables influencing potential aquifer recharge in natural regime. Changes in these variables can be important in the assessment of future potential impacts of climatic scenarios over spatiotemporal renewable groundwater resource. For instance, if temperature increases, actual evapotranspitration (EA) will increases reducing the available water for others groundwater balance components, including the recharge. For this reason, instead of defining an infiltration rate coefficient that relates precipitation (P) and recharge we propose to define a transformation function that allows estimating the spatial distribution of recharge (both average value and its uncertainty) from the difference in P and EA in each area. A complete analysis of potential short-term (2016-2045) future climate scenarios in continental Spain has been performed by considering different sources of uncertainty. It is based on the historical climatic data for the period 1976-2005 and the climatic models simulations (for the control [1976-2005] and future scenarios [2016-2045]) performed in the frame of the CORDEX EU project. The most pessimistic emission scenario (RCP8.5) has been considered. For the RCP8.5 scenario we have analyzed the time series generated by simulating with 5 Regional Climatic models (CCLM4-8-17, RCA4, HIRHAM5, RACMO22E, and WRF331F) nested to 4 different General Circulation Models (GCMs). Two different conceptual approaches (bias correction and delta change techniques) have been applied to generate potential future climate scenarios from these data. Different ensembles of obtained time series have been proposed to obtain more representative scenarios by considering all the simulations or only those providing better approximations to the historical statistics based on a multicriteria analysis. This was a step to analyze future potential impacts on the aquifer recharge by simulating them within a rainfall-recharge model. This research has been supported by the CGL2013-48424-C2-2-R (MINECO) and the PMAFI/06/14 (UCAM) projects.

Forest carbon changes of the United States in response to impacts of disturbances, succession, climate variability and atmospheric chemistry

Treesearch

Yude Pan; Richard Birdsey; Jing Chen; kevin McCullough

2008-01-01

U.S. forests and forest products currently offset about 20% of the nation's fossil fuel emissions. Two of the most significant recent scientific findings cast doubt on the sustainability of this offset. First, there are clear indications that the strength of the U.S. forest carbon offset is weakening due to increasing forest age, climate variability, and...

140-year subantarctic tree-ring temperature reconstruction reveals tropical forcing of increased Southern Ocean climate variability

NASA Astrophysics Data System (ADS)

Turney, C. S.; Fogwill, C. J.; Palmer, J. G.; VanSebille, E.; Thomas, Z.; McGlone, M.; Richardson, S.; Wilmshurst, J.; Fenwick, P.; Zunz, V.; Goosse, H.; Wilson, K. J.; Carter, L.; Lipson, M.; Jones, R. T.; Harsch, M.; Clark, G.; Marzinelli, E.; Rogers, T.; Rainsley, E.; Ciasto, L.; Waterman, S.; Thomas, E. R.; Visbeck, M.

2017-12-01

Occupying about 14 % of the world's surface, the Southern Ocean plays a fundamental role in ocean and atmosphere circulation, carbon cycling and Antarctic ice-sheet dynamics. Unfortunately, high interannual variability and a dearth of instrumental observations before the 1950s limits our understanding of how marine-atmosphere-ice domains interact on multi-decadal timescales and the impact of anthropogenic forcing. Here we integrate climate-sensitive tree growth with ocean and atmospheric observations on south-west Pacific subantarctic islands that lie at the boundary of polar and subtropical climates (52-54˚S). Our annually resolved temperature reconstruction captures regional change since the 1870s and demonstrates a significant increase in variability from the 1940s, a phenomenon predating the observational record, and coincident with major changes in mammalian and bird populations. Climate reanalysis and modelling show a parallel change in tropical Pacific sea surface temperatures that generate an atmospheric Rossby wave train which propagates across a large part of the Southern Hemisphere during the austral spring and summer. Our results suggest that modern observed high interannual variability was established across the mid-twentieth century, and that the influence of contemporary equatorial Pacific temperatures may now be a permanent feature across the mid- to high latitudes.

Sensitivity of ground - water recharge estimates to climate variability and change, Columbia Plateau, Washington

USGS Publications Warehouse

Vaccaro, John J.

1992-01-01

The sensitivity of groundwater recharge estimates was investigated for the semiarid Ellensburg basin, located on the Columbia Plateau, Washington, to historic and projected climatic regimes. Recharge was estimated for predevelopment and current (1980s) land use conditions using a daily energy-soil-water balance model. A synthetic daily weather generator was used to simulate lengthy sequences with parameters estimated from subsets of the historical record that were unusually wet and unusually dry. Comparison of recharge estimates corresponding to relatively wet and dry periods showed that recharge for predevelopment land use varies considerably within the range of climatic conditions observed in the 87-year historical observation period. Recharge variations for present land use conditions were less sensitive to the same range of historical climatic conditions because of irrigation. The estimated recharge based on the 87-year historical climatology was compared with adjustments to the historical precipitation and temperature records for the same record to reflect CO2-doubling climates as projected by general circulation models (GCMs). Two GCM scenarios were considered: an average of conditions for three different GCMs with CO2 doubling, and a most severe “maximum” case. For the average GCM scenario, predevelopment recharge increased, and current recharge decreased. Also considered was the sensitivity of recharge to the variability of climate within the historical and adjusted historical records. Predevelopment and current recharge were less and more sensitive, respectively, to the climate variability for the average GCM scenario as compared to the variability within the historical record. For the maximum GCM scenario, recharge for both predevelopment and current land use decreased, and the sensitivity to the CO2-related climate change was larger than sensitivity to the variability in the historical and adjusted historical climate records.

Vegetation coupling to global climate: Trajectories of vegetation change and phenology modeling from satellite observations

NASA Astrophysics Data System (ADS)

Fisher, Jeremy Isaac

Important systematic shifts in ecosystem function are often masked by natural variability. The rich legacy of over two decades of continuous satellite observations provides an important database for distinguishing climatological and anthropogenic ecosystem changes. Examples from semi-arid Sudanian West Africa and New England (USA) illustrate the response of vegetation to climate and land-use. In Burkina Faso, West Africa, pastoral and agricultural practices compete for land area, while degradation may follow intensification. The Nouhao Valley is a natural experiment in which pastoral and agricultural land uses were allocated separate, coherent reserves. Trajectories of annual net primary productivity were derived from 18 years of coarse-grain (AVHRR) satellite data. Trends suggested that pastoral lands had responded rigorously to increasing rainfall after the 1980's droughts. A detailed analysis at Landsat resolution (30m) indicated that the increased vegetative cover was concentrated in the river basins of the pastoral region, implying a riparian wood expansion. In comparison, riparian cover was reduced in agricultural regions. We suggest that broad-scale patterns of increasing semi-arid West African greenness may be indicative of climate variability, whereas local losses may be anthropogenic in nature. The contiguous deciduous forests, ocean proximity, topography, and dense urban developments of New England provide an ideal landscape to examine influences of climate variability and the impact of urban development vegetation response. Spatial and temporal patterns of interannual climate variability were examined via green leaf phenology. Phenology, or seasonal growth and senescence, is driven by deficits of light, temperature, and water. In temperate environments, phenology variability is driven by interannual temperature and precipitation shifts. Average and interannual phenology analyses across southern New England were conducted at resolutions of 30m (Landsat) and 500m Moderate Resolution Imaging Spectrometer (MODIS). A robust logistic-growth model of canopy cover was employed to determine phenological characteristics at each forest stand. The duel analyses revealed important findings: (a) local phenological gradients from microclimatic structures are highly influential in broad-scale phenological observations; (b) satellite observed phenology reflects observations of canopy growth from field studies; (c) phenological anomalies in urban areas which were previously attributed to urban heat may be a function of urban-specific land cover (i.e. green lawns); and (d) patterns of interannual variability in phenology at the regional scale have high spatial coherency and appear to be driven by broad-scale climatic change. Satellite-observed phenology may reflect temperatures during spring and provides a proxy of climate variability.

Little Ice Age climatic erraticism as an analogue for future enhanced hydroclimatic variability across the American Southwest

PubMed Central

Loisel, Julie; MacDonald, Glen M.; Thomson, Marcus J.

2017-01-01

The American Southwest has experienced a series of severe droughts interspersed with strong wet episodes over the past decades, prompting questions about future climate patterns and potential intensification of weather disruptions under warming conditions. Here we show that interannual hydroclimatic variability in this region has displayed a significant level of non-stationarity over the past millennium. Our tree ring-based analysis of past drought indicates that the Little Ice Age (LIA) experienced high interannual hydroclimatic variability, similar to projections for the 21st century. This is contrary to the Medieval Climate Anomaly (MCA), which had reduced variability and therefore may be misleading as an analog for 21st century warming, notwithstanding its warm (and arid) conditions. Given past non-stationarity, and particularly erratic LIA, a ‘warm LIA’ climate scenario for the coming century that combines high precipitation variability (similar to LIA conditions) with warm and dry conditions (similar to MCA conditions) represents a plausible situation that is supported by recent climate simulations. Our comparison of tree ring-based drought analysis and records from the tropical Pacific Ocean suggests that changing variability in El Niño Southern Oscillation (ENSO) explains much of the contrasting variances between the MCA and LIA conditions across the American Southwest. Greater ENSO variability for the 21st century could be induced by a decrease in meridional sea surface temperature gradient caused by increased greenhouse gas concentration, as shown by several recent climate modeling experiments. Overall, these results coupled with the paleo-record suggests that using the erratic LIA conditions as benchmarks for past hydroclimatic variability can be useful for developing future water-resource management and drought and flood hazard mitigation strategies in the Southwest. PMID:29036207

Climate change and dead zones.

PubMed

Altieri, Andrew H; Gedan, Keryn B

2015-04-01

Estuaries and coastal seas provide valuable ecosystem services but are particularly vulnerable to the co-occurring threats of climate change and oxygen-depleted dead zones. We analyzed the severity of climate change predicted for existing dead zones, and found that 94% of dead zones are in regions that will experience at least a 2 °C temperature increase by the end of the century. We then reviewed how climate change will exacerbate hypoxic conditions through oceanographic, ecological, and physiological processes. We found evidence that suggests numerous climate variables including temperature, ocean acidification, sea-level rise, precipitation, wind, and storm patterns will affect dead zones, and that each of those factors has the potential to act through multiple pathways on both oxygen availability and ecological responses to hypoxia. Given the variety and strength of the mechanisms by which climate change exacerbates hypoxia, and the rates at which climate is changing, we posit that climate change variables are contributing to the dead zone epidemic by acting synergistically with one another and with recognized anthropogenic triggers of hypoxia including eutrophication. This suggests that a multidisciplinary, integrated approach that considers the full range of climate variables is needed to track and potentially reverse the spread of dead zones. © 2014 John Wiley & Sons Ltd.

Signal to noise quantification of regional climate projections

NASA Astrophysics Data System (ADS)

Li, S.; Rupp, D. E.; Mote, P.

2016-12-01

One of the biggest challenges in interpreting climate model outputs for impacts studies and adaptation planning is understanding the sources of disagreement among models (which is often used imperfectly as a stand-in for system uncertainty). Internal variability is a primary source of uncertainty in climate projections, especially for precipitation, for which models disagree about even the sign of changes in large areas like the continental US. Taking advantage of a large initial-condition ensemble of regional climate simulations, this study quantifies the magnitude of changes forced by increasing greenhouse gas concentrations relative to internal variability. Results come from a large initial-condition ensemble of regional climate model simulations generated by weather@home, a citizen science computing platform, where the western United States climate was simulated for the recent past (1985-2014) and future (2030-2059) using a 25-km horizontal resolution regional climate model (HadRM3P) nested in global atmospheric model (HadAM3P). We quantify grid point level signal-to-noise not just in temperature and precipitation responses, but also the energy and moisture flux terms that are related to temperature and precipitation responses, to provide important insights regarding uncertainty in climate change projections at local and regional scales. These results will aid modelers in determining appropriate ensemble sizes for different climate variables and help users of climate model output with interpreting climate model projections.

Climate change. Six centuries of variability and extremes in a coupled marine-terrestrial ecosystem.

PubMed

Black, Bryan A; Sydeman, William J; Frank, David C; Griffin, Daniel; Stahle, David W; García-Reyes, Marisol; Rykaczewski, Ryan R; Bograd, Steven J; Peterson, William T

2014-09-19

Reported trends in the mean and variability of coastal upwelling in eastern boundary currents have raised concerns about the future of these highly productive and biodiverse marine ecosystems. However, the instrumental records on which these estimates are based are insufficiently long to determine whether such trends exceed preindustrial limits. In the California Current, a 576-year reconstruction of climate variables associated with winter upwelling indicates that variability increased over the latter 20th century to levels equaled only twice during the past 600 years. This modern trend in variance may be unique, because it appears to be driven by an unprecedented succession of extreme, downwelling-favorable, winter climate conditions that profoundly reduce productivity for marine predators of commercial and conservation interest. Copyright © 2014, American Association for the Advancement of Science.

Rainfall variability and extremes over southern Africa: Assessment of a climate model to reproduce daily extremes

NASA Astrophysics Data System (ADS)

Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

2009-04-01

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 be assessed, again by a comparison with extremes from the MIRA dataset. The paper will conclude by discussing the user needs of satellite rainfall retrievals from a climate change modelling prospective.

Tree Density and Species Decline in the African Sahel Attributable to Climate

NASA Technical Reports Server (NTRS)

Gonzalez, Patrick; Tucker, Compton J.; Sy, H.

2012-01-01

Increased aridity and human population have reduced tree cover in parts of the African Sahel and degraded resources for local people. Yet, tree cover trends and the relative importance of climate and population remain unresolved. From field measurements, aerial photos, and Ikonos satellite images, we detected significant 1954-2002 tree density declines in the western Sahel of 18 +/- 14% (P = 0.014, n = 204) and 17 +/- 13% (P = 0.0009, n = 187). From field observations, we detected a significant 1960-2000 species richness decline of 21 +/- 11% (P = 0.0028, n = 14) across the Sahel and a southward shift of the Sahel, Sudan, and Guinea zones. Multivariate analyses of climate, soil, and population showed that temperature most significantly (P < 0.001) explained tree cover changes. Multivariate and bivariate tests and field observations indicated the dominance of temperature and precipitation, supporting attribution of tree cover changes to climate variability. Climate change forcing of Sahel climate variability, particularly the significant (P < 0.05) 1901-2002 temperature increases and precipitation decreases in the research areas, connects Sahel tree cover changes to global climate change. This suggests roles for global action and local adaptation to address ecological change in the Sahel.

Dynamic response of airborne infections to climate change: predictions for varicella

NASA Astrophysics Data System (ADS)

Baker, R.; Mahmud, A. S.; Metcalf, C. J. E.

2017-12-01

Characterizing how climate change will alter the burden of infectious diseases has clear applications for public health policy. Despite our uniquely detailed understanding of the transmission process for directly transmitted infections, the impact of climate variables on these infections remains understudied. We develop a novel methodology for estimating the causal relationship between climate and directly transmitted infections, which combines an epidemiological model of disease transmission with panel regression techniques. Our method allows us to move beyond correlational approaches to studying the link between climate and infectious diseases. Further, we can generate semi-mechanistic projections of incidence across climate scenarios. We illustrate our approach using 30 years of reported cases of varicella, a common airborne childhood infection, across 32 states in Mexico. We find significantly increased varicella transmission in drier conditions. We use this to map potential changes in the magnitude and variability of varicella incidence in Mexico as a result of projected changes in future climate conditions. Our results indicate that the predicted decrease in humidity in Mexico towards the end of the century will increase incidence of varicella, all else equal, and that these changes in incidence will be non-uniform across the year.

Sensitivity of water resources in the Delaware River basin to climate variability and change

USGS Publications Warehouse

Ayers, Mark A.; Wolock, David M.; McCabe, Gregory J.; Hay, Lauren E.; Tasker, Gary D.

1994-01-01

Because of the greenhouse effect, projected increases in atmospheric carbon dioxide levels might cause global warming, which in turn could result in changes in precipitation patterns and evapotranspiration and in increases in sea level. This report describes the greenhouse effect; discusses the problems and uncertainties associated with the detection, prediction, and effects of climate change; and presents the results of sensitivity analyses of how climate change might affect water resources in the Delaware River basin. Sensitivity analyses suggest that potentially serious shortfalls of certain water resources in the basin could result if some scenarios for climate change come true . The results of model simulations of the basin streamflow demonstrate the difficulty in distinguishing the effects that climate change versus natural climate variability have on streamflow and water supply . The future direction of basin changes in most water resources, furthermore, cannot be precisely determined because of uncertainty in current projections of regional temperature and precipitation . This large uncertainty indicates that, for resource planning, information defining the sensitivities of water resources to a range of climate change is most relevant . The sensitivity analyses could be useful in developing contingency plans for evaluating and responding to changes, should they occur.

Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

NASA Astrophysics Data System (ADS)

Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

2010-01-01

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 extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is under-estimated (over-estimated) over wet (dry) regions of southern Africa.

Perspectives on Hydro-Climatic Change in Rivers Sourced From the Khangai Mountains, Mongolia

NASA Astrophysics Data System (ADS)

Venable, N. B.; Fassnacht, S. R.; Tumenjargal, S.; Batbuyan, B.; Odgarav, J.; Sukhbataar, J.; Fernandez-Gimenez, M.; Adyabadam, G.

2012-12-01

Patterns of pastoralism have shaped the Mongolian countryside throughout history. These patterns are largely dictated by seasonal and extreme climate and water conditions. While change has always been a part of the traditional herder lifestyle, the magnitude and variety of impacts imposed by natural and human-induced changes in the last few decades has increased, negatively affecting the coupled natural-human systems of Mongolia. Regional hydrologic impacts from increased mining, irrigation, urbanization, and climate change are challenging to measure and model due to sparse and relatively short meteorological and hydrological records. Characterization of the variability inherent in Mongolian hydrological systems in the international literature remains limited. To quantify recent changes to these systems, several river basins near the Khangai Mountains were analyzed. These basins adjoin and include community-based managed and non-managed grazing lands under study as part of an ongoing National Science Foundation Coupled Natural and Human Systems (NSF-CNH) project. Statistically significant increasing temperatures and decreasing streamflows in the study areas support herder's perceptions of hydro-climatic changes and variability. The results of basin characterization combined with water balance modeling and trend analyses illustrate the future potential for further change in these hydro-climatic systems. Alternate land-uses and herder lifestyle modifications may amplify impacts from climatic change. Recent fieldwork also revealed complex surface-groundwater interactions in some areas that may affect model outcomes. Future explorations of longer-term variability through the use of proxies and the development of hydrologic scenarios will place the current basin analyses in context to more fully assess possible impacts to the hydrologic-human systems of Mongolia.

Climate-driven shifts in continental net primary production implicated as a driver of a recent abrupt increase in the land carbon sink

NASA Astrophysics Data System (ADS)

Buermann, Wolfgang; Beaulieu, Claudie; Parida, Bikash; Medvigy, David; Collatz, George J.; Sheffield, Justin; Sarmiento, Jorge L.

2016-03-01

The world's ocean and land ecosystems act as sinks for anthropogenic CO2, and over the last half century their combined sink strength grew steadily with increasing CO2 emissions. Recent analyses of the global carbon budget, however, have uncovered an abrupt, substantial ( ˜ 1 PgC yr-1) and sustained increase in the land sink in the late 1980s whose origin remains unclear. In the absence of this prominent shift in the land sink, increases in atmospheric CO2 concentrations since the late 1980s would have been ˜ 30 % larger than observed (or ˜ 12 ppm above current levels). Global data analyses are limited in regards to attributing causes to changes in the land sink because different regions are likely responding to different drivers. Here, we address this challenge by using terrestrial biosphere models constrained by observations to determine if there is independent evidence for the abrupt strengthening of the land sink. We find that net primary production significantly increased in the late 1980s (more so than heterotrophic respiration), consistent with the inferred increase in the global land sink, and that large-scale climate anomalies are responsible for this shift. We identify two key regions in which climatic constraints on plant growth have eased: northern Eurasia experienced warming, and northern Africa received increased precipitation. Whether these changes in continental climates are connected is uncertain, but North Atlantic climate variability is important. Our findings suggest that improved understanding of climate variability in the North Atlantic may be essential for more credible projections of the land sink under climate change.

Climate variation explains a third of global crop yield variability

PubMed Central

Ray, Deepak K.; Gerber, James S.; MacDonald, Graham K.; West, Paul C.

2015-01-01

Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for ~13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, >60% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (~32–39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability. PMID:25609225

Variability in understory evapotranspiration with overstory density in Siberian larch forests

NASA Astrophysics Data System (ADS)

Tobio, A.; Loranty, M. M.; Kropp, H.; Pena, H., III; Alexander, H. D.; Natali, S.; Kholodov, A. L.

2016-12-01

Arctic ecosystems are changing rapidly in response to amplified rates of climate change. Increased vegetation productivity, altered ecosystem carbon and hydrologic cycling, and increased wildfire severity are among the key responses to changing permafrost and climate conditions. Boreal larch forests in northeastern Siberia are a critical but understudied ecosystem affected by these modifications. Understory vegetation in these ecosystems, which typically have low canopy cover, may account for half of all water fluxes. Despite the potential importance of the understory for ecosystem water exchange, there has been relatively little research examining variability in understory evapotranspiration in boreal larch forests. In particular, the water balance of understory shrubs and mosses is largely undefined and could provide insight on how understory vegetation and our changing climate interact. This is especially important because both observed increases in vegetation productivity and wildfire severity could lead to increases in forests density, altering the proportional contributions of over- and understory vegetation to whole ecosystem evapotranspiration. In order to better understand variability in understory evapotranspiration we measured in larch forests with differing overstory density and permafrost conditions that likely vary as a consequence of fire severity. We used the static chamber technique to measure fluxes across a range of understory vegetation types and environmental conditions. In general, we found that the understory vegetation in low density stands transpires more than that in high density stands. This tends to be correlated with a larger amount of aboveground biomass in the low density stands, and an increase in solar radiation, due to less shading by overstory trees. These results will help us to better understand water balances, evapotranspiration variability, and productivity changes associated with climate on understory vegetation. Additionally, our results will help understand how fire regime shifts may alter understory contributions to ecosystem evapotranspiration in Siberian larch forests.

Rising climate variability and synchrony in North Pacific ecosystems

NASA Astrophysics Data System (ADS)

Black, Bryan

2017-04-01

Rising climate variability and synchrony in North Pacific ecosystems Evidence is growing that climate variability of the northeast Pacific Ocean has increased over the last century, culminating in such events as the record-breaking El Niño years 1983, 1998, and 2016 and the unusually persistent 2014/15 North Pacific Ocean heat wave known as "The Blob." Of particular concern is that rising variability could increase synchrony within and among North Pacific ecosystems, which could reduce the diversity of biological responses to climate (i.e. the "portfolio effect"), diminish resilience, and leave populations more prone to extirpation. To test this phenomenon, we use a network of multidecadal fish otolith growth-increment chronologies that were strongly correlated to records of winter (Jan-Mar) sea level. These biological and physical datasets spanned the California Current through the Gulf of Alaska. Synchrony was quantified as directional changes in running (31-year window) mean pairwise correlation within sea level and then within otolith time series. Synchrony in winter sea level at the nine stations with the longest records has increased by more than 40% over the 1950-2015 interval. Likewise, synchrony among the eight longest otolith chronologies has increased more than 100% over a comparable time period. These directional changes in synchrony are highly unlikely due to chance alone, as confirmed by comparing trends in observed data to those in simulated data (n = 10,000 iterations) with time series of identical number, length, and autocorrelation. Ultimately, this trend in rising synchrony may be linked to increased impacts of the El Niño Southern Oscillation (ENSO) on mid-latitude ecosystems of North America, and may therefore reflect a much broader, global-scale signature.

Selecting Populations for Non-Analogous Climate Conditions Using Universal Response Functions: The Case of Douglas-Fir in Central Europe

PubMed Central

Chakraborty, Debojyoti; Wang, Tongli; Andre, Konrad; Konnert, Monika; Lexer, Manfred J.; Matulla, Christoph; Schueler, Silvio

2015-01-01

Identifying populations within tree species potentially adapted to future climatic conditions is an important requirement for reforestation and assisted migration programmes. Such populations can be identified either by empirical response functions based on correlations of quantitative traits with climate variables or by climate envelope models that compare the climate of seed sources and potential growing areas. In the present study, we analyzed the intraspecific variation in climate growth response of Douglas-fir planted within the non-analogous climate conditions of Central and continental Europe. With data from 50 common garden trials, we developed Universal Response Functions (URF) for tree height and mean basal area and compared the growth performance of the selected best performing populations with that of populations identified through a climate envelope approach. Climate variables of the trial location were found to be stronger predictors of growth performance than climate variables of the population origin. Although the precipitation regime of the population sources varied strongly none of the precipitation related climate variables of population origin was found to be significant within the models. Overall, the URFs explained more than 88% of variation in growth performance. Populations identified by the URF models originate from western Cascades and coastal areas of Washington and Oregon and show significantly higher growth performance than populations identified by the climate envelope approach under both current and climate change scenarios. The URFs predict decreasing growth performance at low and middle elevations of the case study area, but increasing growth performance on high elevation sites. Our analysis suggests that population recommendations based on empirical approaches should be preferred and population selections by climate envelope models without considering climatic constrains of growth performance should be carefully appraised before transferring populations to planting locations with novel or dissimilar climate. PMID:26288363

Can unforced radiative variability explain the "hiatus"?

NASA Astrophysics Data System (ADS)

Donohoe, A.

2016-02-01

The paradox of the "hiatus" is characterized as a decade long period over which global mean surface temperature remained relatively constant even though greenhouse forcing forcing is believed to have been positive and increasing. Explanations of the hiatus have focused on two primary lines of thought: 1. There was a net radiative imbalance at the top of atmosphere (TOA) but this energy input was stored in the ocean without increasing surface temperature or 2. There was no radiative imbalance at the TOA because the greenhouse forcing was offset by other climate forcings. Here, we explore a third hypothesis: that there was no TOA radiative imbalance over the decade due to unforced, natural modes of radiative variability that are unrelated to global mean temperature. Is it possible that the Earth could emit enough radiation to offset greenhouse forcing without increasing its temperature due to internal modes of climate variability? Global mean TOA energy imbalance is estimated to be 0.65 W m-2 as determined from the long term change in ocean heat content - where the majority of the energy imbalance is stored. Therefore, in order to offset this TOA energy imbalance natural modes of radiative variability with amplitudes of order 0.5 W m-2 at the decadal timescale are required. We demonstrate that unforced coupled climate models have global mean radiative variability of the required magnitude (2 standard deviations of 0.57 W m-2 in the inter-model mean) and that the vast majority (>90%) of this variability is unrelated to surface temperature radiative feedbacks. However, much of this variability is at shorter (monthly and annual) timescales and does not persist from year to year making the possibility of a decade long natural interruption of the energy accumulation in the climate system unlikely due to natural radiative variability alone given the magnitude of the greenhouse forcing on Earth. Comparison to observed satellite data suggest the models capture the magnitude (2 sigma = 0.61 W m-2) and mechanisms of internal radiative variability but we cannot exclude the possibility of low frequency modes of variability with significant magnitude given the limited length of the satellite record.

Climate Trends and Farmers' Perceptions of Climate Change in Zambia.

PubMed

Mulenga, Brian P; Wineman, Ayala; Sitko, Nicholas J

2017-02-01

A number of studies use meteorological records to analyze climate trends and assess the impact of climate change on agricultural yields. While these provide quantitative evidence on climate trends and the likely effects thereof, they incorporate limited qualitative analysis of farmers' perceptions of climate change and/or variability. The present study builds on the quantitative methods used elsewhere to analyze climate trends, and in addition compares local narratives of climate change with evidence found in meteorological records in Zambia. Farmers offer remarkably consistent reports of a rainy season that is growing shorter and less predictable. For some climate parameters-notably, rising average temperature-there is a clear overlap between farmers' observations and patterns found in the meteorological records. However, the data do not support the perception that the rainy season used to begin earlier, and we generally do not detect a reported increase in the frequency of dry spells. Several explanations for these discrepancies are offered. Further, we provide policy recommendations to help farmers adapt to climate change/variability, as well as suggestions to shape future climate change policies, programs, and research in developing countries.

The hydrologic and biogeochemical response of undisturbed mountain ecosystems in the Western United States to multiple stressors: Interactions between climate variability and atmospheric deposition of contaminants

NASA Astrophysics Data System (ADS)

Campbell, D. H.; Mast, M. A.; Clow, D. W.; Ingersoll, G. P.; Nanus, L.

2004-12-01

Wilderness areas and national parks of the West are largely protected from acute changes in land use such as urbanization and natural resource development. However, the ecosystems in these areas are sensitive to both climate variability and atmospheric deposition of acids, nitrogen (N), and toxic contaminants, and these stressors interact in ways that we are just beginning to understand. Here we examine some examples of the interactions between climate variability and nitrogen and mercury cycling in high elevation watersheds. During the recent drought, which began in 2000, streamwater nitrate concentrations nearly doubled in the Loch Vale watershed in Rocky Mountain National Park, exceeding 60 μ M during early snowmelt. Much of the elevated nitrate resulted from an increased percentage contribution to streamwater of nitrate-rich shallow groundwater. In a nearby pond used for breeding by a threatened amphibian species, nitrate concentrations were negligible but ammonium concentrations were extremely high (850 μ M) during the drought. In this case, organic N in pond sediments was likely mineralized and released during cycles of drying and rewetting of pond sediments. Even after 2 years of near-average precipitation, water levels remained below normal and ammonium concentrations remained elevated, indicating that the hydrologic response of this small system has a timescale of many years. Mercury (Hg) deposition at high elevations of the Rocky Mountains is comparable to that of the Midwest and Northeast, but the processes that control Hg cycling in alpine/subalpine ecosystems are not well understood. Methylation and bioaccumulation of Hg must occur before Hg reaches levels harmful to the ecosystem or human health, and both climate and nutrient cycling affect these processes. Fluctuating water levels caused by climate variability can mobilize Hg from lake and pond sediments, increasing reactivity and bioavailability of Hg in the ecosystem. Increased nutrient release from the terrestrial ecosystem (eg. from N saturation) may increase productivity and accumulation of organic matter, altering Hg cycling in the aquatic system. Long durations of ice cover and thick snowpacks are likely to cause elevated methyl Hg in aquatic ecosystems. Snow and ice cover on lakes promotes hypoxia in lake water, favoring production and accumulation of methyl Hg- the percentage of methyl-Hg in lake water under snow and ice was as much as 6 times greater than the percentage measured during late summer in a northwestern Colorado lake. Analysis of long-term trends indicates that climate variability is increasing in the Mountain West. Climatic extremes appear to exacerbate adverse impacts of atmospheric deposition, as well as stressing ecosystems directly. A better understanding of these interactions is needed in order to predict the response of mountain ecosystems to future changes in climate and atmospheric deposition.

Trends in Cold Extremes and Winter Weather for the SPTC Region

DOT National Transportation Integrated Search

2017-05-31

Extreme weather poses multifaceted hazards to transportation. There is now increased awareness of the threats of climate variability and change on transportation safety and state of good repair. In particular, a non-stationary climate will potentiall...

Fishing, fast growth and climate variability increase the risk of collapse

PubMed Central

Pinsky, Malin L.; Byler, David

2015-01-01

Species around the world have suffered collapses, and a key question is why some populations are more vulnerable than others. Traditional conservation biology and evidence from terrestrial species suggest that slow-growing populations are most at risk, but interactions between climate variability and harvest dynamics may alter or even reverse this pattern. Here, we test this hypothesis globally. We use boosted regression trees to analyse the influences of harvesting, species traits and climate variability on the risk of collapse (decline below a fixed threshold) across 154 marine fish populations around the world. The most important factor explaining collapses was the magnitude of overfishing, while the duration of overfishing best explained long-term depletion. However, fast growth was the next most important risk factor. Fast-growing populations and those in variable environments were especially sensitive to overfishing, and the risk of collapse was more than tripled for fast-growing when compared with slow-growing species that experienced overfishing. We found little evidence that, in the absence of overfishing, climate variability or fast growth rates alone drove population collapse over the last six decades. Expanding efforts to rapidly adjust harvest pressure to account for climate-driven lows in productivity could help to avoid future collapses, particularly among fast-growing species. PMID:26246548

Fishing, fast growth and climate variability increase the risk of collapse.

PubMed

Pinsky, Malin L; Byler, David

2015-08-22

Species around the world have suffered collapses, and a key question is why some populations are more vulnerable than others. Traditional conservation biology and evidence from terrestrial species suggest that slow-growing populations are most at risk, but interactions between climate variability and harvest dynamics may alter or even reverse this pattern. Here, we test this hypothesis globally. We use boosted regression trees to analyse the influences of harvesting, species traits and climate variability on the risk of collapse (decline below a fixed threshold) across 154 marine fish populations around the world. The most important factor explaining collapses was the magnitude of overfishing, while the duration of overfishing best explained long-term depletion. However, fast growth was the next most important risk factor. Fast-growing populations and those in variable environments were especially sensitive to overfishing, and the risk of collapse was more than tripled for fast-growing when compared with slow-growing species that experienced overfishing. We found little evidence that, in the absence of overfishing, climate variability or fast growth rates alone drove population collapse over the last six decades. Expanding efforts to rapidly adjust harvest pressure to account for climate-driven lows in productivity could help to avoid future collapses, particularly among fast-growing species. © 2015 The Author(s).

Flood Protection Decision Making Within a Coupled Human and Natural System

NASA Astrophysics Data System (ADS)

O'Donnell, Greg; O'Connell, Enda

2013-04-01

Due to the perceived threat from climate change, prediction under changing climatic and hydrological conditions has become a dominant theme of hydrological research. Much of this research has been climate model-centric, in which GCM/RCM climate projections have been used to drive hydrological system models to explore potential impacts that should inform adaptation decision-making. However, adaptation fundamentally involves how humans may respond to increasing flood and drought hazards by changing their strategies, activities and behaviours which are coupled in complex ways to the natural systems within which they live and work. Humans are major agents of change in hydrological systems, and representing human activities and behaviours in coupled human and natural hydrological system models is needed to gain insight into the complex interactions that take place, and to inform adaptation decision-making. Governments and their agencies are under pressure to make proactive investments to protect people living in floodplains from the perceived increasing flood hazard. However, adopting this as a universal strategy everywhere is not affordable, particularly in times of economic stringency and given uncertainty about future climatic conditions. It has been suggested that the assumption of stationarity, which has traditionally been invoked in making hydrological risk assessments, is no longer tenable. However, before the assumption of hydrologic nonstationarity is accepted, the ability to cope with the uncertain impacts of global warming on water management via the operational assumption of hydrologic stationarity should be carefully examined. Much can be learned by focussing on natural climate variability and its inherent changes in assessing alternative adaptation strategies. A stationary stochastic multisite flood hazard model has been developed that can exhibit increasing variability/persistence in annual maximum floods, starting with the traditional assumption of independence. This has been coupled to an agent based model of how various stakeholders interact in determining where and when flood protection investments are made in a hypothetical region with multiple sites at risk from flood hazard. Monte Carlo simulation is used to explore how government agencies with finite resources might best invest in flood protection infrastructure in a highly variable climate with a high degree of future uncertainty. Insight is provided into whether proactive or reactive strategies are to be preferred in an increasingly variable climate.

Climate change patterns in Amazonia and biodiversity.

PubMed

Cheng, Hai; Sinha, Ashish; Cruz, Francisco W; Wang, Xianfeng; Edwards, R Lawrence; d'Horta, Fernando M; Ribas, Camila C; Vuille, Mathias; Stott, Lowell D; Auler, Augusto S

2013-01-01

Precise characterization of hydroclimate variability in Amazonia on various timescales is critical to understanding the link between climate change and biodiversity. Here we present absolute-dated speleothem oxygen isotope records that characterize hydroclimate variation in western and eastern Amazonia over the past 250 and 20 ka, respectively. Although our records demonstrate the coherent millennial-scale precipitation variability across tropical-subtropical South America, the orbital-scale precipitation variability between western and eastern Amazonia exhibits a quasi-dipole pattern. During the last glacial period, our records imply a modest increase in precipitation amount in western Amazonia but a significant drying in eastern Amazonia, suggesting that higher biodiversity in western Amazonia, contrary to 'Refugia Hypothesis', is maintained under relatively stable climatic conditions. In contrast, the glacial-interglacial climatic perturbations might have been instances of loss rather than gain in biodiversity in eastern Amazonia, where forests may have been more susceptible to fragmentation in response to larger swings in hydroclimate.

Impacts of rainfall variability and expected rainfall changes on cost-effective adaptation of water systems to climate change.

PubMed

van der Pol, T D; van Ierland, E C; Gabbert, S; Weikard, H-P; Hendrix, E M T

2015-05-01

Stormwater drainage and other water systems are vulnerable to changes in rainfall and runoff and need to be adapted to climate change. This paper studies impacts of rainfall variability and changing return periods of rainfall extremes on cost-effective adaptation of water systems to climate change given a predefined system performance target, for example a flood risk standard. Rainfall variability causes system performance estimates to be volatile. These estimates may be used to recurrently evaluate system performance. This paper presents a model for this setting, and develops a solution method to identify cost-effective investments in stormwater drainage adaptations. Runoff and water levels are simulated with rainfall from stationary rainfall distributions, and time series of annual rainfall maxima are simulated for a climate scenario. Cost-effective investment strategies are determined by dynamic programming. The method is applied to study the choice of volume for a storage basin in a Dutch polder. We find that 'white noise', i.e. trend-free variability of rainfall, might cause earlier re-investment than expected under projected changes in rainfall. The risk of early re-investment may be reduced by increasing initial investment. This can be cost-effective if the investment involves fixed costs. Increasing initial investments, therefore, not only increases water system robustness to structural changes in rainfall, but could also offer insurance against additional costs that would occur if system performance is underestimated and re-investment becomes inevitable. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spatiotemporal patterns of evapotranspiration along the North American east coast as influenced by multiple environmental changes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Qichun; Tian, Hanqin; Li, Xia

The North American east coast has experienced significant land-use and climate changes since the beginning of the 20th century. In this study, using the Dynamic Land Ecosystem Model 2.0 driven by time-series input data of land use, climate and atmospheric CO 2, we examined how these driving forces have affected the spatiotemporal trends and variability of evapotranspiration (ET) in this region during 1901–2008. Annual ET in the North American east coast during this period was 648.3 ± 38.6 mm/year and demonstrated an increasing trend. Factorial model simulations indicated that climate variability explained 76% of the inter-annual ET variability. Although land-usemore » change only explained 16% of the ET temporal variability, afforestation induced the upward trend of ET and increased annual ET by 12.8 mm/year. Elevated atmospheric CO 2 reduced annual ET by 0.84 mm, and its potential impacts under future atmospheric CO 2 levels could be much larger than estimates for the historical 1901–2008 period. Climate change determined the spatial pattern of ET changes across the entire study area, whereas land-use changes dramatically affected ET in watersheds with significant land conversions. In spite of the multiple benefits from afforestation, its impacts on water resources should be considered in future land-use policy making. As a result, elevated ET may also affect fresh water availability for the increasing social and economic water demands.« less

Spatiotemporal patterns of evapotranspiration along the North American east coast as influenced by multiple environmental changes

DOE PAGES

Yang, Qichun; Tian, Hanqin; Li, Xia; ...

2014-08-08

The North American east coast has experienced significant land-use and climate changes since the beginning of the 20th century. In this study, using the Dynamic Land Ecosystem Model 2.0 driven by time-series input data of land use, climate and atmospheric CO 2, we examined how these driving forces have affected the spatiotemporal trends and variability of evapotranspiration (ET) in this region during 1901–2008. Annual ET in the North American east coast during this period was 648.3 ± 38.6 mm/year and demonstrated an increasing trend. Factorial model simulations indicated that climate variability explained 76% of the inter-annual ET variability. Although land-usemore » change only explained 16% of the ET temporal variability, afforestation induced the upward trend of ET and increased annual ET by 12.8 mm/year. Elevated atmospheric CO 2 reduced annual ET by 0.84 mm, and its potential impacts under future atmospheric CO 2 levels could be much larger than estimates for the historical 1901–2008 period. Climate change determined the spatial pattern of ET changes across the entire study area, whereas land-use changes dramatically affected ET in watersheds with significant land conversions. In spite of the multiple benefits from afforestation, its impacts on water resources should be considered in future land-use policy making. As a result, elevated ET may also affect fresh water availability for the increasing social and economic water demands.« less

Consequences of an uncertain mass mortality regime triggered by climate variability on giant clam population management in the Pacific Ocean.

PubMed

Van Wynsberge, Simon; Andréfouët, Serge; Gaertner-Mazouni, Nabila; Remoissenet, Georges

2018-02-01

Despite actions to manage sustainably tropical Pacific Ocean reef fisheries, managers have faced failures and frustrations because of unpredicted mass mortality events triggered by climate variability. The consequences of these events on the long-term population dynamics of living resources need to be better understood for better management decisions. Here, we use a giant clam (Tridacna maxima) spatially explicit population model to compare the efficiency of several management strategies under various scenarios of natural mortality, including mass mortality due to climatic anomalies. The model was parameterized by in situ estimations of growth and mortality and fishing effort, and was validated by historical and new in situ surveys of giant clam stocks in two French Polynesia lagoons. Projections on the long run (100 years) suggested that the best management strategy was a decrease of fishing pressure through quota implementation, regardless of the mortality regime considered. In contrast, increasing the minimum legal size of catch and closing areas to fishing were less efficient. When high mortality occurred due to climate variability, the efficiency of all management scenarios decreased markedly. Simulating El Niño Southern Oscillation event by adding temporal autocorrelation in natural mortality rates increased the natural variability of stocks, and also decreased the efficiency of management. These results highlight the difficulties that managers in small Pacific islands can expect in the future in the face of global warming, climate anomalies and new mass mortalities. Copyright © 2017 Elsevier Inc. All rights reserved.

Seasonal and interannual variability of climate and vegetation indices across the Amazon.

PubMed

Brando, Paulo M; Goetz, Scott J; Baccini, Alessandro; Nepstad, Daniel C; Beck, Pieter S A; Christman, Mary C

2010-08-17

Drought exerts a strong influence on tropical forest metabolism, carbon stocks, and ultimately the flux of carbon to the atmosphere. Satellite-based studies have suggested that Amazon forests green up during droughts because of increased sunlight, whereas field studies have reported increased tree mortality during severe droughts. In an effort to reconcile these apparently conflicting findings, we conducted an analysis of climate data, field measurements, and improved satellite-based measures of forest photosynthetic activity. Wet-season precipitation and plant-available water (PAW) decreased over the Amazon Basin from 1996-2005, and photosynthetically active radiation (PAR) and air dryness (expressed as vapor pressure deficit, VPD) increased from 2002-2005. Using improved enhanced vegetation index (EVI) measurements (2000-2008), we show that gross primary productivity (expressed as EVI) declined with VPD and PAW in regions of sparse canopy cover across a wide range of environments for each year of the study. In densely forested areas, no climatic variable adequately explained the Basin-wide interannual variability of EVI. Based on a site-specific study, we show that monthly EVI was relatively insensitive to leaf area index (LAI) but correlated positively with leaf flushing and PAR measured in the field. These findings suggest that production of new leaves, even when unaccompanied by associated changes in LAI, could play an important role in Basin-wide interannual EVI variability. Because EVI variability was greatest in regions of lower PAW, we hypothesize that drought could increase EVI by synchronizing leaf flushing via its effects on leaf bud development.

Interaction Between Ecohydrologic Dynamics and Microtopographic Variability Under Climate Change

NASA Astrophysics Data System (ADS)

Le, Phong V. V.; Kumar, Praveen

2017-10-01

Vegetation acclimation resulting from elevated atmospheric CO2 concentration, along with response to increased temperature and altered rainfall pattern, is expected to result in emergent behavior in ecologic and hydrologic functions. We hypothesize that microtopographic variability, which are landscape features typically of the length scale of the order of meters, such as topographic depressions, will play an important role in determining this dynamics by altering the persistence and variability of moisture. To investigate these emergent ecohydrologic dynamics, we develop a modeling framework, Dhara, which explicitly incorporates the control of microtopographic variability on vegetation, moisture, and energy dynamics. The intensive computational demand from such a modeling framework that allows coupling of multilayer modeling of the soil-vegetation continuum with 3-D surface-subsurface flow processes is addressed using hybrid CPU-GPU parallel computing framework. The study is performed for different climate change scenarios for an intensively managed agricultural landscape in central Illinois, USA, which is dominated by row-crop agriculture, primarily soybean (Glycine max) and maize (Zea mays). We show that rising CO2 concentration will decrease evapotranspiration, thus increasing soil moisture and surface water ponding in topographic depressions. However, increased atmospheric demand from higher air temperature overcomes this conservative behavior resulting in a net increase of evapotranspiration, leading to reduction in both soil moisture storage and persistence of ponding. These results shed light on the linkage between vegetation acclimation under climate change and microtopography variability controls on ecohydrologic processes.

Increased tree-ring network density reveals more precise estimations of sub-regional hydroclimate variability and climate dynamics in the Midwest, USA

NASA Astrophysics Data System (ADS)

Maxwell, Justin T.; Harley, Grant L.

2017-08-01

Understanding the historic variability in the hydroclimate provides important information on possible extreme dry or wet periods that in turn inform water management plans. Tree rings have long provided historical context of hydroclimate variability of the U.S. However, the tree-ring network used to create these countrywide gridded reconstructions is sparse in certain locations, such as the Midwest. Here, we increase ( n = 20) the spatial resolution of the tree-ring network in southern Indiana and compare a summer (June-August) Palmer Drought Severity Index (PDSI) reconstruction to existing gridded reconstructions of PDSI for this region. We find both droughts and pluvials that were previously unknown that rival the most intense PDSI values during the instrumental period. Additionally, historical drought occurred in Indiana that eclipsed instrumental conditions with regard to severity and duration. During the period 1962-2004 CE, we find that teleconnections of drought conditions through the Atlantic Meridional Overturning Circulation have a strong influence ( r = -0.60, p < 0.01) on secondary tree growth in this region for the late spring-early summer season. These findings highlight the importance of continuing to increase the spatial resolution of the tree-ring network used to infer past climate dynamics to capture the sub-regional spatial variability. Increasing the spatial resolution of the tree-ring network for a given region can better identify sub-regional variability, improve the accuracy of regional tree-ring PDSI reconstructions, and provide better information for climatic teleconnections.

The paradox of cooling streams in a warming world: Regional climate trends do not parallel variable local trends in stream temperature in the Pacific continental United States

USGS Publications Warehouse

Arismendi, Ivan; Johnson, Sherri; Dunham, Jason B.; Haggerty, Roy; Hockman-Wert, David

2012-01-01

Temperature is a fundamentally important driver of ecosystem processes in streams. Recent warming of terrestrial climates around the globe has motivated concern about consequent increases in stream temperature. More specifically, observed trends of increasing air temperature and declining stream flow are widely believed to result in corresponding increases in stream temperature. Here, we examined the evidence for this using long-term stream temperature data from minimally and highly human-impacted sites located across the Pacific continental United States. Based on hypothesized climate impacts, we predicted that we should find warming trends in the maximum, mean and minimum temperatures, as well as increasing variability over time. These predictions were not fully realized. Warming trends were most prevalent in a small subset of locations with longer time series beginning in the 1950s. More recent series of observations (1987-2009) exhibited fewer warming trends and more cooling trends in both minimally and highly human-influenced systems. Trends in variability were much less evident, regardless of the length of time series. Based on these findings, we conclude that our perspective of climate impacts on stream temperatures is clouded considerably by a lack of long-termdata on minimally impacted streams, and biased spatio-temporal representation of existing time series. Overall our results highlight the need to develop more mechanistic, process-based understanding of linkages between climate change, other human impacts and stream temperature, and to deploy sensor networks that will provide better information on trends in stream temperatures in the future.

A two-fold increase of carbon cycle sensitivity to tropical temperature variations.

PubMed

Wang, Xuhui; Piao, Shilong; Ciais, Philippe; Friedlingstein, Pierre; Myneni, Ranga B; Cox, Peter; Heimann, Martin; Miller, John; Peng, Shushi; Wang, Tao; Yang, Hui; Chen, Anping

2014-02-13

Earth system models project that the tropical land carbon sink will decrease in size in response to an increase in warming and drought during this century, probably causing a positive climate feedback. But available data are too limited at present to test the predicted changes in the tropical carbon balance in response to climate change. Long-term atmospheric carbon dioxide data provide a global record that integrates the interannual variability of the global carbon balance. Multiple lines of evidence demonstrate that most of this variability originates in the terrestrial biosphere. In particular, the year-to-year variations in the atmospheric carbon dioxide growth rate (CGR) are thought to be the result of fluctuations in the carbon fluxes of tropical land areas. Recently, the response of CGR to tropical climate interannual variability was used to put a constraint on the sensitivity of tropical land carbon to climate change. Here we use the long-term CGR record from Mauna Loa and the South Pole to show that the sensitivity of CGR to tropical temperature interannual variability has increased by a factor of 1.9 ± 0.3 in the past five decades. We find that this sensitivity was greater when tropical land regions experienced drier conditions. This suggests that the sensitivity of CGR to interannual temperature variations is regulated by moisture conditions, even though the direct correlation between CGR and tropical precipitation is weak. We also find that present terrestrial carbon cycle models do not capture the observed enhancement in CGR sensitivity in the past five decades. More realistic model predictions of future carbon cycle and climate feedbacks require a better understanding of the processes driving the response of tropical ecosystems to drought and warming.

Country-Specific Effects of Climate Variability on Human Migration.

PubMed

Gray, Clark; Wise, Erika

2016-04-01

Involuntary human migration is among the social outcomes of greatest concern in the current era of global climate change. Responding to this concern, a growing number of studies have investigated the consequences of short to medium-term climate variability for human migration using demographic and econometric approaches. These studies have provided important insights, but at the same time have been significantly limited by lack of expertise in the use of climate data, access to cross-national data on migration, and attention to model specification. To address these limitations, we link data on internal and international migration over a 6-year period from 9,812 origin households in Kenya, Uganda, Nigeria, Burkina Faso and Senegal to high-resolution gridded climate data from both station and satellite sources. Analyses of these data using several plausible specifications reveal that climate variability has country-specific effects on migration: Migration tends to increase with temperature anomalies in Uganda, tends to decrease with temperature anomalies in Kenya and Burkina Faso, and shows no consistent relationship with temperature in Nigeria and Senegal. Consistent with previous studies, precipitation shows weak and inconsistent relationships with migration across countries. These results challenge generalizing narratives that foresee a consistent migratory response to climate change across the globe.

Incorporating climate change and morphological uncertainty into coastal change hazard assessments

USGS Publications Warehouse

Baron, Heather M.; Ruggiero, Peter; Wood, Nathan J.; Harris, Erica L.; Allan, Jonathan; Komar, Paul D.; Corcoran, Patrick

2015-01-01

Documented and forecasted trends in rising sea levels and changes in storminess patterns have the potential to increase the frequency, magnitude, and spatial extent of coastal change hazards. To develop realistic adaptation strategies, coastal planners need information about coastal change hazards that recognizes the dynamic temporal and spatial scales of beach morphology, the climate controls on coastal change hazards, and the uncertainties surrounding the drivers and impacts of climate change. We present a probabilistic approach for quantifying and mapping coastal change hazards that incorporates the uncertainty associated with both climate change and morphological variability. To demonstrate the approach, coastal change hazard zones of arbitrary confidence levels are developed for the Tillamook County (State of Oregon, USA) coastline using a suite of simple models and a range of possible climate futures related to wave climate, sea-level rise projections, and the frequency of major El Niño events. Extreme total water levels are more influenced by wave height variability, whereas the magnitude of erosion is more influenced by sea-level rise scenarios. Morphological variability has a stronger influence on the width of coastal hazard zones than the uncertainty associated with the range of climate change scenarios.

Natural climate variability and teleconnections to precipitation over the Pacific-North American region in CMIP3 and CMIP5 models

NASA Astrophysics Data System (ADS)

Polade, Suraj D.; Gershunov, Alexander; Cayan, Daniel R.; Dettinger, Michael D.; Pierce, David W.

2013-05-01

climate variability will continue to be an important aspect of future regional climate even in the midst of long-term secular changes. Consequently, the ability of climate models to simulate major natural modes of variability and their teleconnections provides important context for the interpretation and use of climate change projections. Comparisons reported here indicate that the CMIP5 generation of global climate models shows significant improvements in simulations of key Pacific climate mode and their teleconnections to North America compared to earlier CMIP3 simulations. The performance of 14 models with simulations in both the CMIP3 and CMIP5 archives are assessed using singular value decomposition analysis of simulated and observed winter Pacific sea surface temperatures (SSTs) and concurrent precipitation over the contiguous United States and northwestern Mexico. Most of the models reproduce basic features of the key natural mode and their teleconnections, albeit with notable regional deviations from observations in both SST and precipitation. Increasing horizontal resolution in the CMIP5 simulations is an important, but not a necessary, factor in the improvement from CMIP3 to CMIP5.

Natural climate variability and teleconnections to precipitation over the Pacific-North American region in CMIP3 and CMIP5 models

USGS Publications Warehouse

Polade, Suraj D.; Gershunov, Alexander; Cayan, Daniel R.; Dettinger, Michael D.; Pierce, David W.

2013-01-01

Natural climate variability will continue to be an important aspect of future regional climate even in the midst of long-term secular changes. Consequently, the ability of climate models to simulate major natural modes of variability and their teleconnections provides important context for the interpretation and use of climate change projections. Comparisons reported here indicate that the CMIP5 generation of global climate models shows significant improvements in simulations of key Pacific climate mode and their teleconnections to North America compared to earlier CMIP3 simulations. The performance of 14 models with simulations in both the CMIP3 and CMIP5 archives are assessed using singular value decomposition analysis of simulated and observed winter Pacific sea surface temperatures (SSTs) and concurrent precipitation over the contiguous United States and northwestern Mexico. Most of the models reproduce basic features of the key natural mode and their teleconnections, albeit with notable regional deviations from observations in both SST and precipitation. Increasing horizontal resolution in the CMIP5 simulations is an important, but not a necessary, factor in the improvement from CMIP3 to CMIP5.

Modelling climate change and malaria transmission.

PubMed

Parham, Paul E; Michael, Edwin

2010-01-01

The impact of climate change on human health has received increasing attention in recent years, with potential impacts due to vector-borne diseases only now beginning to be understood. As the most severe vector-borne disease, with one million deaths globally in 2006, malaria is thought most likely to be affected by changes in climate variables due to the sensitivity of its transmission dynamics to environmental conditions. While considerable research has been carried out using statistical models to better assess the relationship between changes in environmental variables and malaria incidence, less progress has been made on developing process-based climate-driven mathematical models with greater explanatory power. Here, we develop a simple model of malaria transmission linked to climate which permits useful insights into the sensitivity of disease transmission to changes in rainfall and temperature variables. Both the impact of changes in the mean values of these key external variables and importantly temporal variation in these values are explored. We show that the development and analysis of such dynamic climate-driven transmission models will be crucial to understanding the rate at which P. falciparum and P. vivax may either infect, expand into or go extinct in populations as local environmental conditions change. Malaria becomes endemic in a population when the basic reproduction number R0 is greater than unity and we identify an optimum climate-driven transmission window for the disease, thus providing a useful indicator for determing how transmission risk may change as climate changes. Overall, our results indicate that considerable work is required to better understand ways in which global malaria incidence and distribution may alter with climate change. In particular, we show that the roles of seasonality, stochasticity and variability in environmental variables, as well as ultimately anthropogenic effects, require further study. The work presented here offers a theoretical framework upon which this future research may be developed.

Vulnerability of Agriculture to Climate Change as Revealed by Relationships between Simulated Crop Yield and Climate Change Indices

NASA Astrophysics Data System (ADS)

King, A. W.; Absar, S. M.; Nair, S.; Preston, B. L.

2012-12-01

The vulnerability of agriculture is among the leading concerns surrounding climate change. Agricultural production is influenced by drought and other extremes in weather and climate. In regions of subsistence farming, worst case reductions in yield lead to malnutrition and famine. Reduced surplus contributes to poverty in agrarian economies. In more economically diverse and industrialized regions, variations in agricultural yield can influence the regional economy through market mechanisms. The latter grows in importance as agriculture increasingly services the energy market in addition to markets for food and fiber. Agriculture is historically a highly adaptive enterprise and will respond to future changes in climate with a variety of adaptive mechanisms. Nonetheless, the risk, if not expectation, of increases in climate extremes and hazards exceeding historical experience motivates scientifically based anticipatory assessment of the vulnerability of agriculture to climate change. We investigate the sensitivity component of that vulnerability using EPIC, a well established field-scale model of cropping systems that includes the simulation of economic yield. The core of our analysis is the relationship between simulated yield and various indices of climate change, including the CCI/CLIVAR/JCOM ETCCDI indices, calculated from weather inputs to the model. We complement this core with analysis using the DSSAT cropping system model and exploration of relationships between historical yield statistics and climate indices calculated from weather records. Our analyses are for sites in the Southeast/Gulf Coast region of the United States. We do find "tight" monotonic relationships between annual yield and climate for some indices, especially those associated with available water. More commonly, however, we find an increase in the variability of yield as the index value becomes more extreme. Our findings contribute to understanding the sensitivity of crop yield as part of vulnerability analysis. They also contribute to considerations of adaptation, focusing attention on adapting to increased variability in yield rather than just reductions in yield. For example, in the face of increased variability or reduced reliability, hedging and risk spreading strategies may be more important than technological innovations such as drought-resistant crops or other optimization strategies. Our findings also have implications for the choice and application of climate extreme indices, demands on models used to project climate change and the development of next generation integrated assessment models (IAM) that incorporate the agricultural sector, and especially adaption within that sector, in energy and broader more general markets.

Optimal Interpolation scheme to generate reference crop evapotranspiration

NASA Astrophysics Data System (ADS)

Tomas-Burguera, Miquel; Beguería, Santiago; Vicente-Serrano, Sergio; Maneta, Marco

2018-05-01

We used an Optimal Interpolation (OI) scheme to generate a reference crop evapotranspiration (ETo) grid, forcing meteorological variables, and their respective error variance in the Iberian Peninsula for the period 1989-2011. To perform the OI we used observational data from the Spanish Meteorological Agency (AEMET) and outputs from a physically-based climate model. To compute ETo we used five OI schemes to generate grids for the five observed climate variables necessary to compute ETo using the FAO-recommended form of the Penman-Monteith equation (FAO-PM). The granularity of the resulting grids are less sensitive to variations in the density and distribution of the observational network than those generated by other interpolation methods. This is because our implementation of the OI method uses a physically-based climate model as prior background information about the spatial distribution of the climatic variables, which is critical for under-observed regions. This provides temporal consistency in the spatial variability of the climatic fields. We also show that increases in the density and improvements in the distribution of the observational network reduces substantially the uncertainty of the climatic and ETo estimates. Finally, a sensitivity analysis of observational uncertainties and network densification suggests the existence of a trade-off between quantity and quality of observations.

The Great Plains low-level jet in 1.5C and 2C HAPPI simulations: Implications for changes in extreme climate events

NASA Astrophysics Data System (ADS)

Weaver, S. J.; Barcikowska, M. J.

2017-12-01

Global temperature targets have become the cornerstone for global climate policy discussions. Given the goal of the Paris Accord to limit the rise in global mean temperature to well below 2.0oC above pre-industrial levels, and pursue efforts toward the more ambitious 1.5oC goal, there is increasing focus in the climate science community on what the relative changes in regional climate extremes may be for these two scenarios. Despite the successes of major climate science modeling efforts, there is still a significant information gap regarding the regional and seasonal changes in some climate extremes over the U.S. as a function of these global mean temperature targets.During the spring and summer, large amounts of heat and moisture are transported northward into the central and eastern U.S. by the Great Plains Low-Level Jet (GPLLJ) - an atmospheric river which dominates the subcontinental scale climate variability during the warm half of the year. Accordingly, the GPLLJ and its vast spatiotemporal variability is highly influential over several types of extreme climate anomalies east of the Rocky Mountains, including, drought and pluvial events, tornadic activity, and the evolution of central U.S warming hole. Changes in the GPLLJ and its variability are probed from the perspective of several hundred climate realizations afforded by the availability of climate model experiments from the Half a degree additional warming, Prognosis, and Projected Impacts (HAPPI) effort - a suite of multi-model ensemble AMIP simulations forced by 1.5oC and 2oC levels of global warming. The multimodel analysis focuses on the variable magnitude of the seasonal changes in the mean GPLLJ and shifts in the extremes of the prominent modes of GPLLJ variability - both of which have implications for the future shifts in extreme climate events over the Great Plains, Midwest, and southeast regions of the U.S.

Importance of climatological downscaling and plant phenology for red deer in heterogeneous landscapes

PubMed Central

Pettorelli, Nathalie; Mysterud, Atle; Yoccoz, Nigel G; Langvatn, Rolf; Stenseth, Nils Chr

2005-01-01

Understanding how climate influences ecosystems represents a challenge in ecology and natural resource management. Although we know that climate affects plant phenology and herbivore performances at any single site, no study has directly coupled the topography–climate interaction (i.e. the climatological downscaling process) with large-scale vegetation dynamics and animal performances. Here we show how climatic variability (measured by the North Atlantic oscillation ‘NAO’) interacts with local topography in determining the vegetative greenness (as measured by the normalized difference vegetation index ‘NDVI’) and the body masses and seasonal movements of red deer (Cervus elaphus) in Norway. Warm springs induced an earlier onset of vegetation, resulting in earlier migration and higher body masses. Increasing values of the winter-NAO corresponded to less snow at low altitude (warmer, more precipitation results in more rain), but more snow at high altitude (colder, more precipitation corresponds to more snow) relative to winters with low winter-NAO. An increasing NAO thus results in a spatially more variable phenology, offering migrating deer an extended period with access to high-quality forage leading to increased body mass. Our results emphasize the importance of incorporating spring as well as the interaction between winter climate and topography when aiming at understanding how plant and animal respond to climate change. PMID:16243701

Experimental Climate Change Modifies Degradative Succession in Boreal Peatland Fungal Communities.

PubMed

Asemaninejad, Asma; Thorn, R Greg; Lindo, Zoë

2017-04-01

Peatlands play an important role in global climate change through sequestration of atmospheric CO 2 . Climate-driven changes in the structure of fungal communities in boreal peatlands that favor saprotrophic fungi can substantially impact carbon dynamics and nutrient cycling in these crucial ecosystems. In a mesocosm study using a full factorial design, 100 intact peat monoliths, complete with living Sphagnum and above-ground vascular vegetation, were subjected to three climate change variables (increased temperature, reduced water table, and elevated CO 2 concentrations). Peat litterbags were placed in mesocosms, and fungal communities in litterbags were monitored over 12 months to assess the impacts of climate change variables on peat-inhabiting fungi. Changes in fungal richness, diversity, and community composition were assessed using Illumina MiSeq sequencing of ribosomal DNA (rDNA). While general fungal richness reduced under warming conditions, Ascomycota exhibited higher diversity under increased temperature treatments over the course of the experiment. Both increased temperature and lowered water table position drove shifts in fungal community composition with a strong positive effect on endophytic and mycorrhizal fungi (including one operational taxonomic unit (OTU) tentatively identified as Barrenia panicia) and different groups of saprotrophs identified as Mortierella, Galerina, and Mycena. These shifts were observed during a predicted degradative succession in the decomposer community as different carbon substrates became available. Since fungi play a central role in peatland communities, increased abundances of saprotrophic fungi under warming conditions, at the expense of reduced fungal richness overall, may increase decomposition rates under future climate scenarios and could potentially aggravate the impacts of climate change.

Role of the North Atlantic Ocean in Low Frequency Climate Variability

NASA Astrophysics Data System (ADS)

Danabasoglu, G.; Yeager, S. G.; Kim, W. M.; Castruccio, F. S.

2017-12-01

The Atlantic Ocean is a unique basin with its extensive, North - South overturning circulation, referred to as the Atlantic meridional overturning circulation (AMOC). AMOC is thought to represent the dynamical memory of the climate system, playing an important role in decadal and longer time scale climate variability as well as prediction of the earth's future climate on these time scales via its large heat and salt transports. This oceanic memory is communicated to the atmosphere primarily through the influence of persistent sea surface temperature (SST) variations. Indeed, many modeling studies suggest that ocean circulation, i.e., AMOC, is largely responsible for the creation of coherent SST variability in the North Atlantic, referred to as Atlantic Multidecadal Variability (AMV). AMV has been linked to many (multi)decadal climate variations in, e.g., Sahel and Brazilian rainfall, Atlantic hurricane activity, and Arctic sea-ice extent. In the absence of long, continuous observations, much of the evidence for the ocean's role in (multi)decadal variability comes from model simulations. Although models tend to agree on the role of the North Atlantic Oscillation in creating the density anomalies that proceed the changes in ocean circulation, model fidelity in representing variability characteristics, mechanisms, and air-sea interactions remains a serious concern. In particular, there is increasing evidence that models significantly underestimate low frequency variability in the North Atlantic compared to available observations. Such model deficiencies can amplify the relative influence of external or stochastic atmospheric forcing in generating (multi)decadal variability, i.e., AMV, at the expense of ocean dynamics. Here, a succinct overview of the current understanding of the (North) Atlantic Ocean's role on the regional and global climate, including some outstanding questions, will be presented. In addition, a few examples of the climate impacts of the AMV via atmospheric teleconnections from a set of coupled simulations, also considering the relative roles of its tropical and extratropical components, will be highlighted.

The Use of Expert Opinion to Assess the Risk of Emergence or Re-Emergence of Infectious Diseases in Canada Associated with Climate Change

PubMed Central

Cox, Ruth; Revie, Crawford W.; Sanchez, Javier

2012-01-01

Global climate change is predicted to lead to an increase in infectious disease outbreaks. Reliable surveillance for diseases that are most likely to emerge is required, and given limited resources, policy decision makers need rational methods with which to prioritise pathogen threats. Here expert opinion was collected to determine what criteria could be used to prioritise diseases according to the likelihood of emergence in response to climate change and according to their impact. We identified a total of 40 criteria that might be used for this purpose in the Canadian context. The opinion of 64 experts from academic, government and independent backgrounds was collected to determine the importance of the criteria. A weight was calculated for each criterion based on the expert opinion. The five that were considered most influential on disease emergence or impact were: potential economic impact, severity of disease in the general human population, human case fatality rate, the type of climate that the pathogen can tolerate and the current climatic conditions in Canada. There was effective consensus about the influence of some criteria among participants, while for others there was considerable variation. The specific climate criteria that were most likely to influence disease emergence were: an annual increase in temperature, an increase in summer temperature, an increase in summer precipitation and to a lesser extent an increase in winter temperature. These climate variables were considered to be most influential on vector-borne diseases and on food and water-borne diseases. Opinion about the influence of climate on air-borne diseases and diseases spread by direct/indirect contact were more variable. The impact of emerging diseases on the human population was deemed more important than the impact on animal populations. PMID:22848536

Implications of land use change in tropical West Africa under global warming

NASA Astrophysics Data System (ADS)

Brücher, Tim; Claussen, Martin

2015-04-01

Northern Africa, and the Sahel in particular, are highly vulnerable to climate change, due to strong exposure to increasing temperature, precipitation variability, and population growth. A major link between climate and humans in this region is land use and associated land cover change, mainly where subsistence farming prevails. But how strongly does climate change affect land use and how strongly does land use feeds back into climate change? To which extent may climate-induced water, food and wood shortages exacerbate conflict potential and lead changes in land use and to migration? Estimates of possible changes in African climate vary among the Earth System Models participating in the recent Coupled Model Intercomparison (CMIP5) exercise, except for the region adjacent to the Mediterranean Sea, where a significant decrease of precipitation emerges. While all models agree in a strong temperature increase, rainfall uncertainties for most parts of the Sahara, Sahel, and Sudan are higher. Here we present results of complementary experiments based on extreme and idealized land use change scenarios within a future climate.. We use the MPI-ESM forced with a strong green house gas scenario (RCP8.5) and apply an additional land use forcing by varying largely the intensity and kind of agricultural practice. By these transient experiments (until 2100) we elaborate the additional impact on climate due to strong land use forcing. However, the differences are mostly insignificant. The greenhouse gas caused temperature increase and the high variability in the West African Monsoon rainfall superposes the minor changes in climate due to land use. While simulated climate key variables like precipitation and temperature are not distinguishable from the CMIP5 RCP8.5 results, an additional greening is simulated, when crops are demanded. Crops have lower water usage than pastureland has. This benefits available soil water, which is taken up by the natural vegetation and makes it more productive. Given the limitations of an ESM, the findings of our study show that changes in the kind and intensity of land use have minor effects on the climate. Consequently, implications of extreme land use on e.g. human security, conflict or migration can be investigated in offline simulations.

Response of waves and coastline evolution to climate variability off the Niger Delta coast during the past 110 years

NASA Astrophysics Data System (ADS)

Dada, Olusegun A.; Li, Guangxue; Qiao, Lulu; Ma, Yanyan; Ding, Dong; Xu, Jishang; Li, Pin; Yang, Jichao

2016-08-01

River deltas, low-lying landforms that host critical economic infrastructures and diverse ecosystems as well as high concentrations of human population, are highly vulnerable to the effects of global climate change. In order to understand the wave climate, their potential changes and implication on coastline evolution for environment monitoring and sustainable management of the Niger Delta in the Gulf of Guinea, an investigation was carried out based on offshore wave statistics of an 110-year time series (1900-2010) dataset obtained from the ECMWF ERA-20C atmospheric reanalysis. Results of multivariate regression analyses indicate that interannual mean values of Hs and Tm trends tended to increase over time, especially in the western part of the delta coast, so that they are presently (1980 and 2010) up to 264 mm (300%) and 0.32 s (22%), respectively, higher than 80 years (1900-1930) ago. The maximum directions of the wave have become more westerly (southward) than southerly (westward) by up to 2° (33%) and the mean longshore sediment transport rate has increased by more than 8% over the last 80 years. The linear regression analysis for shoreline changes from 1987 to 2013 shows an erosional trend at the western part of the delta and accretional trends towards eastern part. The relationship between wave climate of the study area and atmospheric circulation using Pearson's correlation shows that the Atlantic Multidecadal Oscillation (AMO), North Atlantic Oscillation (NAO), East Atlantic pattern (EA) and El-Nino/Southern Oscillation (ENSO) Index explain significant proportion of the seasonal and annual wave variabilities compared to other indices. But it is most likely that the combination of these climatic indices acting together or separately constitutes a powerful and effective mechanism responsible for much of the variability of the offshore Niger Delta wave climate. The study concludes that changing wave climate off the Niger Delta has strong implications on the delta coastline changes. However, other processes (such as fluvial discharge variability due climatic variability and anthropogenic effect) may be acting concomitantly with changes in wave regime and associated littoral transport to influence shoreline evolution along the Niger Delta coast.

Agricultural Adaptations to Climate Changes in West Africa

NASA Astrophysics Data System (ADS)

Guan, K.; Sultan, B.; Lobell, D. B.; Biasutti, M.; Piani, C.; Hammer, G. L.; McLean, G.

2014-12-01

Agricultural production in West Africa is highly vulnerable to climate variability and change and a fast growing demand for food adds yet another challenge. Assessing possible adaptation strategies of crop production in West Africa under climate change is thus critical for ensuring regional food security and improving human welfare. Our previous efforts have identified as the main features of climate change in West Africa a robust increase in temperature and a complex shift in the rainfall pattern (i.e. seasonality delay and total amount change). Unaddressed, these robust climate changes would reduce regional crop production by up to 20%. In the current work, we use two well-validated crop models (APSIM and SARRA-H) to comprehensively assess different crop adaptation options under future climate scenarios. Particularly, we assess adaptations in both the choice of crop types and management strategies. The expected outcome of this study is to provide West Africa with region-specific adaptation recommendations that take into account both climate variability and climate change.

Farmers' Perceptions of Climate Variability and Factors Influencing Adaptation: Evidence from Anhui and Jiangsu, China

NASA Astrophysics Data System (ADS)

Kibue, Grace Wanjiru; Liu, Xiaoyu; Zheng, Jufeng; zhang, Xuhui; Pan, Genxing; Li, Lianqing; Han, Xiaojun

2016-05-01

Impacts of climate variability and climate change are on the rise in China posing great threat to agriculture and rural livelihoods. Consequently, China is undertaking research to find solutions of confronting climate change and variability. However, most studies of climate change and variability in China largely fail to address farmers' perceptions of climate variability and adaptation. Yet, without an understanding of farmers' perceptions, strategies are unlikely to be effective. We conducted questionnaire surveys of farmers in two farming regions, Yifeng, Jiangsu and Qinxi, Anhui achieving 280 and 293 responses, respectively. Additionally, we used climatological data to corroborate the farmers' perceptions of climate variability. We found that farmers' were aware of climate variability such that were consistent with climate records. However, perceived impacts of climate variability differed between the two regions and were influenced by farmers' characteristics. In addition, the vast majorities of farmers were yet to make adjustments in their farming practices as a result of numerous challenges. These challenges included socioeconomic and socio-cultural barriers. Results of logit modeling showed that farmers are more likely to adapt to climate variability if contact with extension services, frequency of seeking information, household heads' education, and climate variability perceptions are improved. These results suggest the need for policy makers to understand farmers' perceptions of climate variability and change in order to formulate policies that foster adaptation, and ultimately protect China's agricultural assets.

Farmers' Perceptions of Climate Variability and Factors Influencing Adaptation: Evidence from Anhui and Jiangsu, China.

PubMed

Kibue, Grace Wanjiru; Liu, Xiaoyu; Zheng, Jufeng; Zhang, Xuhui; Pan, Genxing; Li, Lianqing; Han, Xiaojun

2016-05-01

Impacts of climate variability and climate change are on the rise in China posing great threat to agriculture and rural livelihoods. Consequently, China is undertaking research to find solutions of confronting climate change and variability. However, most studies of climate change and variability in China largely fail to address farmers' perceptions of climate variability and adaptation. Yet, without an understanding of farmers' perceptions, strategies are unlikely to be effective. We conducted questionnaire surveys of farmers in two farming regions, Yifeng, Jiangsu and Qinxi, Anhui achieving 280 and 293 responses, respectively. Additionally, we used climatological data to corroborate the farmers' perceptions of climate variability. We found that farmers' were aware of climate variability such that were consistent with climate records. However, perceived impacts of climate variability differed between the two regions and were influenced by farmers' characteristics. In addition, the vast majorities of farmers were yet to make adjustments in their farming practices as a result of numerous challenges. These challenges included socioeconomic and socio-cultural barriers. Results of logit modeling showed that farmers are more likely to adapt to climate variability if contact with extension services, frequency of seeking information, household heads' education, and climate variability perceptions are improved. These results suggest the need for policy makers to understand farmers' perceptions of climate variability and change in order to formulate policies that foster adaptation, and ultimately protect China's agricultural assets.

Climate-growth relationships for largemouth bass (Micropterus salmoides) across three southeastern USA states

Treesearch

Andrew L. Rypel

2009-01-01

The role of climate variability in the ecology of freshwater fishes is of increasing interest. However, there are relatively few tools available for examining how freshwater fish populations respond to climate variations. Here, I apply tree-ring techniques to incremental growth patterns in largemouth bass (Micropterus salmoides Lacepe`de) otoliths to explore...

The influence of climate variability and change on the science and practice of restoration ecology

Treesearch

Donald A. Falk; Connie Millar

2016-01-01

Variation in Earth’s climate system has always been a primary driver of ecosystem processes and biological evolution. In recent decades, however, the prospect of anthropogenically driven change to the climate system has become an increasingly dominant concern for scientists and conservation biologists. Understanding how ecosystems may...

Modeling the influence of precipitation and nitrogen deposition on forest understory fuel connectivity in Sierra Nevada mixed-conifer forest

Treesearch

M. Hurteau; M. North; T. Foines

2009-01-01

Climate change models for California’s Sierra Nevada predict greater inter-annual variability in precipitation over the next 50 years. These increases in precipitation variability coupled with increases in nitrogen deposition fromfossil fuel consumption are likely to result in increased productivity levels and significant increases in...

Cholera and shigellosis: different epidemiology but similar responses to climate variability.

PubMed

Cash, Benjamin A; Rodó, Xavier; Emch, Michael; Yunus, Md; Faruque, Abu S G; Pascual, Mercedes

2014-01-01

Comparative studies of the associations between different infectious diseases and climate variability, such as the El Niño-Southern Oscillation, are lacking. Diarrheal illnesses, particularly cholera and shigellosis, provide an important opportunity to apply a comparative approach. Cholera and shigellosis have significant global mortality and morbidity burden, pronounced differences in transmission pathways and pathogen ecologies, and there is an established climate link with cholera. In particular, the specific ecology of Vibrio cholerae is often invoked to explain the sensitivity of that disease to climate. The extensive surveillance data of the International Center for Diarrheal Disease Research, Bangladesh are used here to revisit the known associations between cholera and climate, and to address their similarity to previously unexplored patterns for shigellosis. Monthly case data for both the city of Dhaka and a rural area known as Matlab are analyzed with respect to their association with El Niño and flooding. Linear correlations are examined between flooding and cumulative cases, as well as for flooding and El Niño. Rank-correlation maps are also computed between disease cases in the post-monsoon epidemic season and sea surface temperatures in the Pacific. Similar climate associations are found for both diseases and both locations. Increased cases follow increased monsoon flooding and increased sea surface temperatures in the preceding winter corresponding to an El Niño event. The similarity in association patterns suggests a systemic breakdown in population health with changing environmental conditions, in which climate variability acts primarily through increasing the exposure risk of the human population. We discuss these results in the context of the on-going debate on the relative importance of the environmental reservoir vs. secondary transmission, as well as the implications for the use of El Niño as an early indicator of flooding and enteric disease risk.

Cholera and Shigellosis: Different Epidemiology but Similar Responses to Climate Variability

PubMed Central

Cash, Benjamin A.; Rodó, Xavier; Emch, Michael; Yunus, Md.; Faruque, Abu S. G.; Pascual, Mercedes

2014-01-01

Background Comparative studies of the associations between different infectious diseases and climate variability, such as the El Niño-Southern Oscillation, are lacking. Diarrheal illnesses, particularly cholera and shigellosis, provide an important opportunity to apply a comparative approach. Cholera and shigellosis have significant global mortality and morbidity burden, pronounced differences in transmission pathways and pathogen ecologies, and there is an established climate link with cholera. In particular, the specific ecology of Vibrio cholerae is often invoked to explain the sensitivity of that disease to climate. Methods and Findings The extensive surveillance data of the International Center for Diarrheal Disease Research, Bangladesh are used here to revisit the known associations between cholera and climate, and to address their similarity to previously unexplored patterns for shigellosis. Monthly case data for both the city of Dhaka and a rural area known as Matlab are analyzed with respect to their association with El Niño and flooding. Linear correlations are examined between flooding and cumulative cases, as well as for flooding and El Niño. Rank-correlation maps are also computed between disease cases in the post-monsoon epidemic season and sea surface temperatures in the Pacific. Similar climate associations are found for both diseases and both locations. Increased cases follow increased monsoon flooding and increased sea surface temperatures in the preceding winter corresponding to an El Niño event. Conclusions The similarity in association patterns suggests a systemic breakdown in population health with changing environmental conditions, in which climate variability acts primarily through increasing the exposure risk of the human population. We discuss these results in the context of the on-going debate on the relative importance of the environmental reservoir vs. secondary transmission, as well as the implications for the use of El Niño as an early indicator of flooding and enteric disease risk. PMID:25229494

Mid-latitude shrub steppe plant communities: Climate change consequences for soil water resources

USGS Publications Warehouse

Palmquist, Kyle A.; Schlaepfer, Daniel R.; Bradford, John B.; Lauenroth, Willliam K.

2016-01-01

In the coming century, climate change is projected to impact precipitation and temperature regimes worldwide, with especially large effects in drylands. We use big sagebrush ecosystems as a model dryland ecosystem to explore the impacts of altered climate on ecohydrology and the implications of those changes for big sagebrush plant communities using output from 10 Global Circulation Models (GCMs) for two representative concentration pathways (RCPs). We ask: 1) What is the magnitude of variability in future temperature and precipitation regimes among GCMs and RCPs for big sagebrush ecosystems and 2) How will altered climate and uncertainty in climate forecasts influence key aspects of big sagebrush water balance? We explored these questions across 1980-2010, 2030-2060, and 2070-2100 to determine how changes in water balance might develop through the 21st century. We assessed ecohydrological variables at 898 sagebrush sites across the western US using a process-based soil water model, SOILWAT to model all components of daily water balance using site-specific vegetation parameters and site-specific soil properties for multiple soil layers. Our modeling approach allowed for changes in vegetation based on climate. Temperature increased across all GCMs and RCPs, while changes in precipitation were more variable across GCMs. Winter and spring precipitation was predicted to increase in the future (7% by 2030-2060, 12% by 2070-2100), resulting in slight increases in soil water potential (SWP) in winter. Despite wetter winter soil conditions, SWP decreased in late spring and summer due to increased evapotranspiration (6% by 2030-2060, 10% by 2070-2100) and groundwater recharge (26% and 30% increase by 2030-2060 and 2070-2100). Thus, despite increased precipitation in the cold season, soils may dry out earlier in the year, resulting in potentially longer drier summer conditions. If winter precipitation cannot offset drier summer conditions in the future, we expect big sagebrush regeneration and survival will be negatively impacted, potentially resulting in shifts in the relative abundance of big sagebrush plant functional groups. Our results also highlight the importance of assessing multiple GCMs to understand the range of climate change outcomes on ecohydrology, which was contingent on the GCM chosen.

Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada

DOE PAGES

Eum, Hyung-Il; Gachon, Philippe; Laprise, René

2016-01-01

This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affectedmore » by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. Finally, these results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.« less

Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eum, Hyung-Il; Gachon, Philippe; Laprise, René

This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affectedmore » by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. Finally, these results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.« less

Climate modulates internal wave activity in the Northern South China Sea

NASA Astrophysics Data System (ADS)

DeCarlo, Thomas M.; Karnauskas, Kristopher B.; Davis, Kristen A.; Wong, George T. F.

2015-02-01

Internal waves (IWs) generated in the Luzon Strait propagate into the Northern South China Sea (NSCS), enhancing biological productivity and affecting coral reefs by modulating nutrient concentrations and temperature. Here we use a state-of-the-art ocean data assimilation system to reconstruct water column stratification in the Luzon Strait as a proxy for IW activity in the NSCS and diagnose mechanisms for its variability. Interannual variability of stratification is driven by intrusions of the Kuroshio Current into the Luzon Strait and freshwater fluxes associated with the El Niño-Southern Oscillation. Warming in the upper 100 m of the ocean caused a trend of increasing IW activity since 1900, consistent with global climate model experiments that show stratification in the Luzon Strait increases in response to radiative forcing. IW activity is expected to increase in the NSCS through the 21st century, with implications for mitigating climate change impacts on coastal ecosystems.

Climate-mediated nitrogen and carbon dynamics in a tropical watershed

NASA Astrophysics Data System (ADS)

Ballantyne, A. P.; Baker, P. A.; Fritz, S. C.; Poulter, B.

2011-06-01

Climate variability affects the capacity of the biosphere to assimilate and store important elements, such as nitrogen and carbon. Here we present biogeochemical evidence from the sediments of tropical Lake Titicaca indicating that large hydrologic changes in response to global glacial cycles during the Quaternary were accompanied by major shifts in ecosystem state. During prolonged glacial intervals, lake level was high and the lake was in a stable nitrogen-limited state. In contrast, during warm dry interglacials lake level fell and rates of nitrogen concentrations increased by a factor of 4-12, resulting in a fivefold to 24-fold increase in organic carbon concentrations in the sediments due to increased primary productivity. Observed periods of increased primary productivity were also associated with an apparent increase in denitrification. However, the net accumulation of nitrogen during interglacial intervals indicates that increased nitrogen supply exceeded nitrogen losses due to denitrification, thereby causing increases in primary productivity. Although primary productivity in tropical ecosystems, especially freshwater ecosystems, tends to be nitrogen limited, our results indicate that climate variability may lead to changes in nitrogen availability and thus changes in primary productivity. Therefore some tropical ecosystems may shift between a stable state of nitrogen limitation and a stable state of nitrogen saturation in response to varying climatic conditions.

[Drivers of human-caused fire occurrence and its variation trend under climate change in the Great Xing'an Mountains, Northeast China].

PubMed

Li, Shun; Wu, Zhi Wei; Liang, Yu; He, Hong Shi

2017-01-01

The Great Xing'an Mountains are an important boreal forest region in China with high frequency of fire occurrences. With climate change, this region may have a substantial change in fire frequency. Building the relationship between spatial pattern of human-caused fire occurrence and its influencing factors, and predicting the spatial patterns of human-caused fires under climate change scenarios are important for fire management and carbon balance in boreal forests. We employed a spatial point pattern model to explore the relationship between the spatial pattern of human-caused fire occurrence and its influencing factors based on a database of historical fire records (1967-2006) in the Great Xing'an Mountains. The fire occurrence time was used as dependent variable. Nine abiotic (annual temperature and precipitation, elevation, aspect, and slope), biotic (vegetation type), and human factors (distance to the nearest road, road density, and distance to the nearest settlement) were selected as explanatory variables. We substituted the climate scenario data (RCP 2.6 and RCP 8.5) for the current climate data to predict the future spatial patterns of human-caused fire occurrence in 2050. Our results showed that the point pattern progress (PPP) model was an effective tool to predict the future relationship between fire occurrence and its spatial covariates. The climatic variables might significantly affect human-caused fire occurrence, while vegetation type, elevation and human variables were important predictors of human-caused fire occurrence. The human-caused fire occurrence probability was expected to increase in the south of the area, and the north and the area along the main roads would also become areas with high human-caused fire occurrence. The human-caused fire occurrence would increase by 72.2% under the RCP 2.6 scenario and by 166.7% under the RCP 8.5 scenario in 2050. Under climate change scenarios, the spatial patterns of human-caused fires were mainly influenced by the climate and human factors.

Climate change risk to forests in China associated with warming.

PubMed

Yin, Yunhe; Ma, Danyang; Wu, Shaohong

2018-01-11

Variations in forest net primary productivity (NPP) reflects the combined effects of key climate variables on ecosystem structure and function, especially on the carbon cycle. We performed risk analysis indicated by the magnitude of future negative anomalies in NPP in comparison with the natural interannual variability to investigate the impact of future climatic projections on forests in China. Results from the multi-model ensemble showed that climate change risk of decreases in forest NPP would be more significant in higher emission scenario in China. Under relatively low emission scenarios, the total area of risk was predicted to decline, while for RCP8.5, it was predicted to first decrease and then increase after the middle of 21st century. The rapid temperature increases predicted under the RCP8.5 scenario would be probably unfavorable for forest vegetation growth in the long term. High-level risk area was likely to increase except RCP2.6. The percentage area at high risk was predicted to increase from 5.39% (2021-2050) to 27.62% (2071-2099) under RCP8.5. Climate change risk to forests was mostly concentrated in southern subtropical and tropical regions, generally significant under high emission scenario of RCP8.5, which was mainly attributed to the intensified dryness in south China.

Forecasting climate change impacts to plant community composition in the Sonoran Desert region

USGS Publications Warehouse

Munson, Seth M.; Webb, Robert H.; Belnap, Jayne; Hubbard, J. Andrew; Swann, Don E.; Rutman, Sue

2012-01-01

Hotter and drier conditions projected for the southwestern United States can have a large impact on the abundance and composition of long-lived desert plant species. We used long-term vegetation monitoring results from 39 large plots across four protected sites in the Sonoran Desert region to determine how plant species have responded to past climate variability. This cross-site analysis identified the plant species and functional types susceptible to climate change, the magnitude of their responses, and potential climate thresholds. In the relatively mesic mesquite savanna communities, perennial grasses declined with a decrease in annual precipitation, cacti increased, and there was a reversal of the Prosopis velutina expansion experienced in the 20th century in response to increasing mean annual temperature (MAT). In the more xeric Arizona Upland communities, the dominant leguminous tree, Cercidium microphyllum, declined on hillslopes, and the shrub Fouquieria splendens decreased, especially on south- and west-facing slopes in response to increasing MAT. In the most xeric shrublands, the codominant species Larrea tridentata and its hemiparasite Krameria grayi decreased with a decrease in cool season precipitation and increased aridity, respectively. This regional-scale assessment of plant species response to recent climate variability is critical for forecasting future shifts in plant community composition, structure, and productivity.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vallis, Geoffrey K.

The project had two main components. The first concerns estimating the climate sensitivity in the presence of forcing uncertainty and natural variability. Climate sensitivity is the increase in the average surface temperature for a given increase in greenhouse gases, for example a doubling of carbon dioxide. We have provided new, probabilistic estimates of climate sensitivity using a simple climate model an the observed warming in the 20th century, in conjunction with ideas in data assimilation and parameter estimation developed in the engineering community. The estimates combine the uncertainty in the anthropogenic aerosols with the uncertainty arising because of natural variability.more » The second component concerns how the atmospheric circulation itself might change with anthropogenic global warming. We have shown that GCMs robustly predict an increase in the length scale of eddies, and we have also explored the dynamical mechanisms whereby there might be a shift in the latitude of the jet stream associated with anthropogenic warming. Such shifts in the jet might cause large changes in regional climate, potentially larger than the globally-averaged signal itself. We have also shown that the tropopause robustly increases in height with global warming, and that the Hadley Cell expands, and that the expansion of the Hadley Cell is correlated with the polewards movement of the mid-latitude jet.« less

Analysis of vegetation dynamics and climatic variability impacts on greenness across Canada using remotely sensed data from 2000 to 2009

NASA Astrophysics Data System (ADS)

Fang, Xiuqin; Zhu, Qiuan; Chen, Huai; Ma, Zhihai; Wang, Weifeng; Song, Xinzhang; Zhao, Pengxiang; Peng, Changhui

2014-01-01

Using time series of moderate-resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data from 2000 to 2009, we assessed decadal vegetation dynamics across Canada and examined the relationship between NDVI and climatic variables (precipitation and temperature). The Palmer drought severity index and vapor pressure difference (VPD) were used to relate the vegetation changes to the climate, especially in cases of drought. Results indicated that MODIS NDVI measurements provided a dynamic picture of interannual variation in Canadian vegetation patterns. Greenness declined in 2000, 2002, and 2009 and increased in 2005, 2006, and 2008. Vegetation dynamics varied across regions during the period. Most forest land shows little change, while vegetation in the ecozone of Pacific Maritime, Prairies, and Taiga Shield shows more dynamics than in the others. Significant correlations were found between NDVI and the climatic variables. The variation of NDVI resulting from climatic variability was more highly correlated to temperature than to precipitation in most ecozones. Vegetation grows better with higher precipitation and temperature in almost all ecozones. However, vegetation grows worse under higher temperature in the Prairies ecozone. The annual changes in NDVI corresponded well with the change in VPD in most ecozones.

Climate, weather, and hops

USDA-ARS?s Scientific Manuscript database

As climate and weather become more variable, hop growers face increased uncertainty in making decisions about their crop. Given the unprecedented nature of these changes, growers may no longer have enough information and intuitive understanding to adequately assess the situation and evaluate their m...

Effects of Changing Climate During the Snow Ablation Season on Seasonal Streamflow Forecasts

NASA Astrophysics Data System (ADS)

Gutzler, D. S.; Chavarria, S. B.

2017-12-01

Seasonal forecasts of total surface runoff (Q) in snowmelt-dominated watersheds derive most of their prediction skill from the historical relationship between late winter snowpack (SWE) and subsequent snowmelt runoff. Across the western US, however, the relationship between SWE and Q is weakening as temperatures rise. We describe the effects of climate variability and change during the springtime snow ablation season on water supply outlooks (forecasts of Q) for southwestern rivers. As snow melts earlier, the importance of post-snow rainfall increases: interannual variability of spring season precipitation accounts for an increasing fraction of the variability of Q in recent decades. The results indicate that improvements to the skill of S2S forecasts of spring season temperature and precipitation would contribute very significantly to water supply outlooks that are now based largely on observed SWE. We assess this hypothesis using historical data from several snowpack-dominated basins in the American Southwest (Rio Grande, Pecos, and Gila Rivers) which are undergoing rapid climate change.

Exploring adaptations to climate change with stakeholders: A participatory method to design grassland-based farming systems.

PubMed

Sautier, Marion; Piquet, Mathilde; Duru, Michel; Martin-Clouaire, Roger

2017-05-15

Research is expected to produce knowledge, methods and tools to enhance stakeholders' adaptive capacity by helping them to anticipate and cope with the effects of climate change at their own level. Farmers face substantial challenges from climate change, from changes in the average temperatures and the precipitation regime to an increased variability of weather conditions and the frequency of extreme events. Such changes can have dramatic consequences for many types of agricultural production systems such as grassland-based livestock systems for which climate change influences the seasonality and productivity of fodder production. We present a participatory design method called FARMORE (FARM-Oriented REdesign) that allows farmers to design and evaluate adaptations of livestock systems to future climatic conditions. It explicitly considers three climate features in the design and evaluation processes: climate change, climate variability and the limited predictability of weather. FARMORE consists of a sequence of three workshops for which a pre-existing game-like platform was adapted. Various year-round forage production and animal feeding requirements must be assembled by participants with a computerized support system. In workshop 1, farmers aim to produce a configuration that satisfies an average future weather scenario. They refine or revise the previous configuration by considering a sample of the between-year variability of weather in workshop 2. In workshop 3, they explicitly take the limited predictability of weather into account. We present the practical aspects of the method based on four case studies involving twelve farmers from Aveyron (France), and illustrate it through an in-depth description of one of these case studies with three dairy farmers. The case studies shows and discusses how workshop sequencing (1) supports a design process that progressively accommodates complexity of real management contexts by enlarging considerations of climate change to climate variability and low weather predictability, and (2) increases the credibility and salience of the design method. Further enhancements of the method are outlined, especially the selection of pertinent weather scenarios. Copyright © 2017 Elsevier Ltd. All rights reserved.

Anthropogenic nitrogen deposition alters growth responses of European beech (Fagus sylvativa L.) to climate change.

PubMed

Hess, Carsten; Niemeyer, Thomas; Fichtner, Andreas; Jansen, Kirstin; Kunz, Matthias; Maneke, Moritz; von Wehrden, Henrik; Quante, Markus; Walmsley, David; von Oheimb, Goddert; Härdtle, Werner

2018-02-01

Global change affects the functioning of forest ecosystems and the services they provide, but little is known about the interactive effects of co-occurring global change drivers on important functions such as tree growth and vitality. In the present study we quantified the interactive (i.e. synergistic or antagonistic) effects of atmospheric nitrogen (N) deposition and climatic variables (temperature, precipitation) on tree growth (in terms of tree-ring width, TRW), taking forest ecosystems with European beech (Fagus sylvatica L.) as an example. We hypothesised that (i) N deposition and climatic variables can evoke non-additive responses of the radial increment of beech trees, and (ii) N loads have the potential to strengthen the trees' sensitivity to climate change. In young stands, we found a synergistic positive effect of N deposition and annual mean temperature on TRW, possibly linked to the alleviation of an N shortage in young stands. In mature stands, however, high N deposition significantly increased the trees' sensitivity to increasing annual mean temperatures (antagonistic effect on TRW), possibly due to increased fine root dieback, decreasing mycorrhizal colonization or shifts in biomass allocation patterns (aboveground vs. belowground). Accordingly, N deposition and climatic variables caused both synergistic and antagonistic effects on the radial increment of beech trees, depending on tree age and stand characteristics. Hence, the nature of interactions could mediate the long-term effects of global change drivers (including N deposition) on forest carbon sequestration. In conclusion, our findings illustrate that interaction processes between climatic variables and N deposition are complex and have the potential to impair growth and performance of European beech. This in turn emphasises the importance of multiple-factor studies to foster an integrated understanding and models aiming at improved projections of tree growth responses to co-occurring drivers of global change. Copyright © 2017 Elsevier Ltd. All rights reserved.

On the brink of change: plant responses to climate on the Colorado Plateau

USGS Publications Warehouse

Munson, Seth M.; Belnap, Jayne; Schelz, Charles D.; Moran, Mary; Carolin, Tara W.

2011-01-01

The intensification of aridity due to anthropogenic climate change in the southwestern U.S. is likely to have a large impact on the growth and survival of plant species that may already be vulnerable to water stress. To make accurate predictions of plant responses to climate change, it is essential to determine the long-term dynamics of plant species associated with past climate conditions. Here we show how the plant species and functional types across a wide range of environmental conditions in Colorado Plateau national parks have changed with climate variability over the last twenty years. During this time, regional mean annual temperature increased by 0.18°C per year from 1989–1995, 0.06°C per year from 1995–2003, declined by 0.14°C from 2003–2008, and there was high interannual variability in precipitation. Non-metric multidimensional scaling of plant species at long-term monitoring sites indicated five distinct plant communities. In many of the communities, canopy cover of perennial plants was sensitive to mean annual temperature occurring in the previous year, whereas canopy cover of annual plants responded to cool season precipitation. In the perennial grasslands, there was an overall decline of C3 perennial grasses, no change of C4 perennial grasses, and an increase of shrubs with increasing temperature. In the shrublands, shrubs generally showed no change or slightly increased with increasing temperature. However, certain shrub species declined where soil and physical characteristics of a site limited water availability. In the higher elevation woodlands, Juniperus osteosperma and shrub canopy cover increased with increasing temperature, while Pinus edulis at the highest elevation sites was unresponsive to interannual temperature variability. These results from well-protected national parks highlight the importance of temperature to plant responses in a water-limited region and suggest that projected increases in aridity are likely to promote grass loss and shrub expansion on the Colorado Plateau.

Climate variability and the European agricultural production

NASA Astrophysics Data System (ADS)

Guimarães Nobre, Gabriela; Hunink, Johannes E.; Baruth, Bettina; Aerts, Jeroen C. J. H.; Ward, Philip J.

2017-04-01

By 2050, the global demand for maize, wheat and other major crops is expected to grow sharply. To meet this challenge, agricultural systems have to increase substantially their production. However, the expanding world population, coupled with a decline of arable land per person, and the variability in global climate, are obstacles to achieving the increasing demand. Creating a resilient agriculture system requires the incorporation of preparedness measures against weather-related events, which can trigger disruptive risks such as droughts. This study examines the influence of large-scale climate variability on agriculture production applying a robust decision-making tool named fast-and-frugal trees (FFT). We created FFTs using a dataset of crop production and indices of climate variability: the El Niño Southern Oscillation (SOI) and the North Atlantic Oscillation (NAO). Our main goal is to predict the occurrence of below-average crop production, using these two indices at different lead times. Initial results indicated that SOI and NAO have strong links with European low sugar beet production. For some areas, the FFTs were able to detect below-average productivity events six months before harvesting with hit rate and predictive positive value higher than 70%. We found that shorter lead times, such as three months before harvesting, have the highest predictive skill. Additionally, we observed that the responses of low production events to the phases of the NAO and SOI vary spatially and seasonally. Through the comprehension of the relationship between large scale climate variability and European drought related agricultural impact, this study reflects on how this information could potentially improve the management of the agricultural sector by coupling the findings with seasonal forecasting system of crop production.

Detrital events and hydroclimate variability in the Romanian Carpathians during the mid-to-late Holocene

NASA Astrophysics Data System (ADS)

Longman, Jack; Ersek, Vasile; Veres, Daniel; Salzmann, Ulrich

2017-07-01

The Romanian Carpathians are located at the confluence of three major atmospheric pressure fields: the North Atlantic, the Mediterranean and the Siberian. Despite its importance for understanding past human impact and climate change, high-resolution palaeoenvironmental reconstructions of Holocene hydroclimate variability, and in particular records of extreme precipitation events in the area, are rare. Here we present a 7500-year-long high-resolution record of past climatic change and human impact recorded in a peatbog from the Southern Carpathians, integrating palynological, geochemical and sedimentological proxies. Natural climate fluctuations appear to be dominant until 4500 years before present (yr BP), followed by increasing importance of human impact. Sedimentological and geochemical analyses document regular minerogenic deposition within the bog, linked to periods of high precipitation. Such minerogenic depositional events began 4000 yr BP, with increased depositional rates during the Medieval Warm Period (MWP), the Little Ice Age (LIA) and during periods of societal upheaval (e.g. the Roman conquest of Dacia). The timing of minerogenic events appears to indicate a teleconnection between major shifts in North Atlantic Oscillation (NAO) and hydroclimate variability in southeastern Europe, with increased minerogenic deposition correlating to low NAO index values. By linking the minerogenic deposition to precipitation variability, we state that this link persists throughout the mid-to-late Holocene.

Can temperature explain the latitudinal gradient of ulcerative colitis? Cohort of Norway

PubMed Central

2013-01-01

Background Incidence and prevalence of ulcerative colitis follow a north–south (latitudinal) gradient and increases northwards at the northern hemisphere or southwards at the southern hemisphere. The disease has increased during the last decades. The temporal trend has been explained by the hygiene hypothesis, but few parallel explanations exist for the spatial variability. Many factors are linked to latitude such as climate. Our purpose was to investigate the association between variables governing the climate and prospectively identified patients. Methods In this study, we used a subset of the population-based Cohort of Norway (n = 80412) where 370 prevalent cases of ulcerative colitis were identified through self-reported medication. The meteorological and climatic variables temperature, precipitation, and altitude were recorded from weather stations of the Norwegian Meteorological Institute. Summer temperature was used to capture environmental temperature. Results Summer temperature was significantly related to the prevalence of ulcerative colitis. For each one-degree increase in temperature the odds for ulcerative colitis decreased with about 9% (95% CI: 3%-15%). None of the other climatic factors were significantly associated to the risk of ulcerative colitis. Contextual variables did not change the association to the prevalence of ulcerative colitis. Conclusions The present results show that the prevalence of ulcerative colitis is associated to summer temperature. Our speculation is that summer temperature works as an instrumental variable for the effect of microbial species richness on the development of ulcerative colitis. Environmental temperature is one of the main forces governing microbial species richness and the microbial composition of the commensal gut flora is known to be an important part in the process leading to ulcerative colitis. PMID:23724802

Variability in winter climate and winter extremes reduces population growth of an alpine butterfly.

PubMed

Roland, Jens; Matter, Stephen F

2013-01-01

We examined the long-term, 15-year pattern of population change in a network of 21 Rocky Mountain populations of Parnassius smintheus butterflies in response to climatic variation. We found that winter values of the broadscale climate variable, the Pacific Decadal Oscillation (PDO) index, were a strong predictor of annual population growth, much more so than were endogenous biotic factors related to population density. The relationship between PDO and population growth was nonlinear. Populations declined in years with extreme winter PDO values, when there were either extremely warm or extremely cold sea surface temperatures in the eastern Pacific relative to that in the western Pacific. Results suggest that more variable winters, and more frequent extremely cold or warm winters, will result in more frequent decline of these populations, a pattern exacerbated by the trend for increasingly variable winters seen over the past century.

Contribution of geodiversity, climate and spatial variables for biodiversity across a gradient of human influence

NASA Astrophysics Data System (ADS)

Tukiainen, Helena; Alahuhta, Janne; Ala-Hulkko, Terhi; Field, Richard; Lampinen, Raino; Hjort, Jan

2016-04-01

Implementation of geodiversity may provide new perspectives for nature conservation. The relation between geodiversity and biodiversity has been established in recent studies but remains underexplored in environments with high human pressure. In this study, we explored the effect of geodiversity (i.e. geological, hydrological and geomorphological diversity), climate and spatial variables on biodiversity (vascular plant species richness) in environments with different human impact. The study area ranged trough the boreal vegetation zone in Finland and included altogether 1401 1-km2 grid cells from urban, rural and natural environments. The contribution of environmental variable groups for species diversity in different environments was statistically analyzed with variation partitioning method. According to the results, the contribution of geodiversity decreased and the contribution of climate and spatial variables increased as the land use became more human-induced. Hence, the connection between geodiversity and species richness was most pronounced in natural state environments.

Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model

USGS Publications Warehouse

Lee, Sangchul; Yeo, In-Young; Sadeghi, Ali M.; McCarty, Gregory W.; Hively, Wells; Lang, Megan W.; Sharifi, Amir

2018-01-01

Water quality problems in the Chesapeake Bay Watershed (CBW) are expected to be exacerbated by climate variability and change. However, climate impacts on agricultural lands and resultant nutrient loads into surface water resources are largely unknown. This study evaluated the impacts of climate variability and change on two adjacent watersheds in the Coastal Plain of the CBW, using the Soil and Water Assessment Tool (SWAT) model. We prepared six climate sensitivity scenarios to assess the individual impacts of variations in CO2concentration (590 and 850 ppm), precipitation increase (11 and 21 %), and temperature increase (2.9 and 5.0 °C), based on regional general circulation model (GCM) projections. Further, we considered the ensemble of five GCM projections (2085–2098) under the Representative Concentration Pathway (RCP) 8.5 scenario to evaluate simultaneous changes in CO2, precipitation, and temperature. Using SWAT model simulations from 2001 to 2014 as a baseline scenario, predicted hydrologic outputs (water and nitrate budgets) and crop growth were analyzed. Compared to the baseline scenario, a precipitation increase of 21 % and elevated CO2 concentration of 850 ppm significantly increased streamflow and nitrate loads by 50 and 52 %, respectively, while a temperature increase of 5.0 °C reduced streamflow and nitrate loads by 12 and 13 %, respectively. Crop biomass increased with elevated CO2 concentrations due to enhanced radiation- and water-use efficiency, while it decreased with precipitation and temperature increases. Over the GCM ensemble mean, annual streamflow and nitrate loads showed an increase of  ∼  70 % relative to the baseline scenario, due to elevated CO2 concentrations and precipitation increase. Different hydrological responses to climate change were observed from the two watersheds, due to contrasting land use and soil characteristics. The watershed with a larger percent of croplands demonstrated a greater increased rate of 5.2 kg N ha−1 in nitrate yield relative to the watershed with a lower percent of croplands as a result of increased export of nitrate derived from fertilizer. The watershed dominated by poorly drained soils showed increased nitrate removal due do enhanced denitrification compared to the watershed dominated by well-drained soils. Our findings suggest that increased implementation of conservation practices would be necessary for this region to mitigate increased nitrate loads associated with predicted changes in future climate.

Climatic and geographic predictors of life history variation in Eastern Massasauga (Sistrurus catenatus): A range-wide synthesis.

PubMed

Hileman, Eric T; King, Richard B; Adamski, John M; Anton, Thomas G; Bailey, Robyn L; Baker, Sarah J; Bieser, Nickolas D; Bell, Thomas A; Bissell, Kristin M; Bradke, Danielle R; Campa, Henry; Casper, Gary S; Cedar, Karen; Cross, Matthew D; DeGregorio, Brett A; Dreslik, Michael J; Faust, Lisa J; Harvey, Daniel S; Hay, Robert W; Jellen, Benjamin C; Johnson, Brent D; Johnson, Glenn; Kiel, Brooke D; Kingsbury, Bruce A; Kowalski, Matthew J; Lee, Yu Man; Lentini, Andrew M; Marshall, John C; Mauger, David; Moore, Jennifer A; Paloski, Rori A; Phillips, Christopher A; Pratt, Paul D; Preney, Thomas; Prior, Kent A; Promaine, Andrew; Redmer, Michael; Reinert, Howard K; Rouse, Jeremy D; Shoemaker, Kevin T; Sutton, Scott; VanDeWalle, Terry J; Weatherhead, Patrick J; Wynn, Doug; Yagi, Anne

2017-01-01

Elucidating how life history traits vary geographically is important to understanding variation in population dynamics. Because many aspects of ectotherm life history are climate-dependent, geographic variation in climate is expected to have a large impact on population dynamics through effects on annual survival, body size, growth rate, age at first reproduction, size-fecundity relationship, and reproductive frequency. The Eastern Massasauga (Sistrurus catenatus) is a small, imperiled North American rattlesnake with a distribution centered on the Great Lakes region, where lake effects strongly influence local conditions. To address Eastern Massasauga life history data gaps, we compiled data from 47 study sites representing 38 counties across the range. We used multimodel inference and general linear models with geographic coordinates and annual climate normals as explanatory variables to clarify patterns of variation in life history traits. We found strong evidence for geographic variation in six of nine life history variables. Adult female snout-vent length and neonate mass increased with increasing mean annual precipitation. Litter size decreased with increasing mean temperature, and the size-fecundity relationship and growth prior to first hibernation both increased with increasing latitude. The proportion of gravid females also increased with increasing latitude, but this relationship may be the result of geographically varying detection bias. Our results provide insights into ectotherm life history variation and fill critical data gaps, which will inform Eastern Massasauga conservation efforts by improving biological realism for models of population viability and climate change.

Climatic and geographic predictors of life history variation in Eastern Massasauga (Sistrurus catenatus): A range-wide synthesis

PubMed Central

King, Richard B.; Adamski, John M.; Anton, Thomas G.; Bailey, Robyn L.; Baker, Sarah J.; Bieser, Nickolas D.; Bell, Thomas A.; Bissell, Kristin M.; Bradke, Danielle R.; Campa, Henry; Casper, Gary S.; Cedar, Karen; Cross, Matthew D.; DeGregorio, Brett A.; Dreslik, Michael J.; Faust, Lisa J.; Harvey, Daniel S.; Hay, Robert W.; Jellen, Benjamin C.; Johnson, Brent D.; Johnson, Glenn; Kiel, Brooke D.; Kingsbury, Bruce A.; Kowalski, Matthew J.; Lee, Yu Man; Lentini, Andrew M.; Marshall, John C.; Mauger, David; Moore, Jennifer A.; Paloski, Rori A.; Phillips, Christopher A.; Pratt, Paul D.; Preney, Thomas; Prior, Kent A.; Promaine, Andrew; Redmer, Michael; Reinert, Howard K.; Rouse, Jeremy D.; Shoemaker, Kevin T.; Sutton, Scott; VanDeWalle, Terry J.; Weatherhead, Patrick J.; Wynn, Doug; Yagi, Anne

2017-01-01

Elucidating how life history traits vary geographically is important to understanding variation in population dynamics. Because many aspects of ectotherm life history are climate-dependent, geographic variation in climate is expected to have a large impact on population dynamics through effects on annual survival, body size, growth rate, age at first reproduction, size–fecundity relationship, and reproductive frequency. The Eastern Massasauga (Sistrurus catenatus) is a small, imperiled North American rattlesnake with a distribution centered on the Great Lakes region, where lake effects strongly influence local conditions. To address Eastern Massasauga life history data gaps, we compiled data from 47 study sites representing 38 counties across the range. We used multimodel inference and general linear models with geographic coordinates and annual climate normals as explanatory variables to clarify patterns of variation in life history traits. We found strong evidence for geographic variation in six of nine life history variables. Adult female snout-vent length and neonate mass increased with increasing mean annual precipitation. Litter size decreased with increasing mean temperature, and the size–fecundity relationship and growth prior to first hibernation both increased with increasing latitude. The proportion of gravid females also increased with increasing latitude, but this relationship may be the result of geographically varying detection bias. Our results provide insights into ectotherm life history variation and fill critical data gaps, which will inform Eastern Massasauga conservation efforts by improving biological realism for models of population viability and climate change. PMID:28196149

A plant’s perspective of extremes: Terrestrial plant responses to changing climatic variability

PubMed Central

Reyer, C.; Leuzinger, S.; Rammig, A.; Wolf, A.; Bartholomeus, R. P.; Bonfante, A.; de Lorenzi, F.; Dury, M.; Gloning, P.; Abou Jaoudé, R.; Klein, T.; Kuster, T. M.; Martins, M.; Niedrist, G.; Riccardi, M.; Wohlfahrt, G.; de Angelis, P.; de Dato, G.; François, L.; Menzel, A.; Pereira, M.

2013-01-01

We review observational, experimental and model results on how plants respond to extreme climatic conditions induced by changing climatic variability. Distinguishing between impacts of changing mean climatic conditions and changing climatic variability on terrestrial ecosystems is generally underrated in current studies. The goals of our review are thus (1) to identify plant processes that are vulnerable to changes in the variability of climatic variables rather than to changes in their mean, and (2) to depict/evaluate available study designs to quantify responses of plants to changing climatic variability. We find that phenology is largely affected by changing mean climate but also that impacts of climatic variability are much less studied but potentially damaging. We note that plant water relations seem to be very vulnerable to extremes driven by changes in temperature and precipitation and that heatwaves and flooding have stronger impacts on physiological processes than changing mean climate. Moreover, interacting phenological and physiological processes are likely to further complicate plant responses to changing climatic variability. Phenological and physiological processes and their interactions culminate in even more sophisticated responses to changing mean climate and climatic variability at the species and community level. Generally, observational studies are well suited to study plant responses to changing mean climate, but less suitable to gain a mechanistic understanding of plant responses to climatic variability. Experiments seem best suited to simulate extreme events. In models, temporal resolution and model structure are crucial to capture plant responses to changing climatic variability. We highlight that a combination of experimental, observational and /or modeling studies have the potential to overcome important caveats of the respective individual approaches. PMID:23504722

The role of ENSO in understanding changes in Colombia's annual malaria burden by region, 1960–2006

PubMed Central

Mantilla, Gilma; Oliveros, Hugo; Barnston, Anthony G

2009-01-01

Background Malaria remains a serious problem in Colombia. The number of malaria cases is governed by multiple climatic and non-climatic factors. Malaria control policies, and climate controls such as rainfall and temperature variations associated with the El Niño/Southern Oscillation (ENSO), have been associated with malaria case numbers. Using historical climate data and annual malaria case number data from 1960 to 2006, statistical models are developed to isolate the effects of climate in each of Colombia's five contrasting geographical regions. Methods Because year to year climate variability associated with ENSO causes interannual variability in malaria case numbers, while changes in population and institutional control policy result in more gradual trends, the chosen predictors in the models are annual indices of the ENSO state (sea surface temperature [SST] in the tropical Pacific Ocean) and time reference indices keyed to two major malaria trends during the study period. Two models were used: a Poisson and a Negative Binomial regression model. Two ENSO indices, two time reference indices, and one dummy variable are chosen as candidate predictors. The analysis was conducted using the five geographical regions to match the similar aggregation used by the National Institute of Health for its official reports. Results The Negative Binomial regression model is found better suited to the malaria cases in Colombia. Both the trend variables and the ENSO measures are significant predictors of malaria case numbers in Colombia as a whole, and in two of the five regions. A one degree Celsius change in SST (indicating a weak to moderate ENSO event) is seen to translate to an approximate 20% increase in malaria cases, holding other variables constant. Conclusion Regional differentiation in the role of ENSO in understanding changes in Colombia's annual malaria burden during 1960–2006 was found, constituting a new approach to use ENSO as a significant predictor of the malaria cases in Colombia. These results naturally point to additional needed work: (1) refining the regional and seasonal dependence of climate on the ENSO state, and of malaria on the climate variables; (2) incorporating ENSO-related climate variability into dynamic malaria models. PMID:19133152

Climate influence on dengue epidemics in Puerto Rico.

PubMed

Jury, Mark R

2008-10-01

The variability of the insect-borne disease dengue in Puerto Rico was studied in relation to climatic variables in the period 1979-2005. Annual and monthly reported dengue cases were compared with precipitation and temperature data. Results show that the incidence of dengue in Puerto Rico was relatively constant over time despite global warming, possibly due to the offsetting effects of declining rainfall, improving health care and little change in population. Seasonal fluctuations of dengue were driven by rainfall increases from May to November. Year-to-year variability in dengue cases was positively related to temperature, but only weakly associated with local rainfall and an index of El Nino Southern Oscillation (ENSO). Climatic conditions were mapped with respect to dengue cases and patterns in high and low years were compared. During epidemics, a low pressure system east of Florida draws warm humid air over the northwestern Caribbean. Long-term trends in past observed and future projected rainfall and temperatures were studied. Rainfall has declined slowly, but temperatures in the Caribbean are rising with the influence of global warming. Thus, dengue may increase in the future, and it will be necessary to anticipate dengue epidemics using climate forecasts, to reduce adverse health impacts.

Climatic variability leads to later seasonal flowering of Floridian plants.

PubMed

Von Holle, Betsy; Wei, Yun; Nickerson, David

2010-07-21

Understanding species responses to global change will help predict shifts in species distributions as well as aid in conservation. Changes in the timing of seasonal activities of organisms over time may be the most responsive and easily observable indicator of environmental changes associated with global climate change. It is unknown how global climate change will affect species distributions and developmental events in subtropical ecosystems or if climate change will differentially favor nonnative species. Contrary to previously observed trends for earlier flowering onset of plant species with increasing spring temperatures from mid and higher latitudes, we document a trend for delayed seasonal flowering among plants in Florida. Additionally, there were few differences in reproductive responses by native and nonnative species to climatic changes. We argue that plants in Florida have different reproductive cues than those from more northern climates. With global change, minimum temperatures have become more variable within the temperate-subtropical zone that occurs across the peninsula and this variation is strongly associated with delayed flowering among Florida plants. Our data suggest that climate change varies by region and season and is not a simple case of species responding to consistently increasing temperatures across the region. Research on climate change impacts need to be extended outside of the heavily studied higher latitudes to include subtropical and tropical systems in order to properly understand the complexity of regional and seasonal differences of climate change on species responses.

Results from the VALUE perfect predictor experiment: process-based evaluation

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Soares, Pedro; Hertig, Elke; Brands, Swen; Huth, Radan; Cardoso, Rita; Kotlarski, Sven; Casado, Maria; Pongracz, Rita; Bartholy, Judit

2016-04-01

Until recently, the evaluation of downscaled climate model simulations has typically been limited to surface climatologies, including long term means, spatial variability and extremes. But these aspects are often, at least partly, tuned in regional climate models to match observed climate. The tuning issue is of course particularly relevant for bias corrected regional climate models. In general, a good performance of a model for these aspects in present climate does therefore not imply a good performance in simulating climate change. It is now widely accepted that, to increase our condidence in climate change simulations, it is necessary to evaluate how climate models simulate relevant underlying processes. In other words, it is important to assess whether downscaling does the right for the right reason. Therefore, VALUE has carried out a broad process-based evaluation study based on its perfect predictor experiment simulations: the downscaling methods are driven by ERA-Interim data over the period 1979-2008, reference observations are given by a network of 85 meteorological stations covering all European climates. More than 30 methods participated in the evaluation. In order to compare statistical and dynamical methods, only variables provided by both types of approaches could be considered. This limited the analysis to conditioning local surface variables on variables from driving processes that are simulated by ERA-Interim. We considered the following types of processes: at the continental scale, we evaluated the performance of downscaling methods for positive and negative North Atlantic Oscillation, Atlantic ridge and blocking situations. At synoptic scales, we considered Lamb weather types for selected European regions such as Scandinavia, the United Kingdom, the Iberian Pensinsula or the Alps. At regional scales we considered phenomena such as the Mistral, the Bora or the Iberian coastal jet. Such process-based evaluation helps to attribute biases in surface variables to underlying processes and ultimately to improve climate models.

Getting even or moving on? Power, procedural justice, and types of offense as predictors of revenge, forgiveness, reconciliation, and avoidance in organizations.

PubMed

Aquino, Karl; Tripp, Thomas M; Bies, Robert J

2006-05-01

A field study and an experimental study examined relationships among organizational variables and various responses of victims to perceived wrongdoing. Both studies showed that procedural justice climate moderates the effect of organizational variables on the victim's revenge, forgiveness, reconciliation, or avoidance behaviors. In Study 1, a field study, absolute hierarchical status enhanced forgiveness and reconciliation, but only when perceptions of procedural justice climate were high; relative hierarchical status increased revenge, but only when perceptions of procedural justice climate were low. In Study 2, a laboratory experiment, victims were less likely to endorse vengeance or avoidance depending on the type of wrongdoing, but only when perceptions of procedural justice climate were high.

Climate-induced changes in forest disturbance and vegetation

NASA Technical Reports Server (NTRS)

Overpeck, Jonathan T.; Rind, David; Goldberg, Richard

1990-01-01

New and published climate-model results are discussed which indicate that global warming favors increased rates of forest disturbance as a result of weather more likely to cause forest fires, convective wind storms, coastal flooding, and hurricanes. New sensitivity tests carried out with a vegetation model indicate that climate-induced increases in disturbance could, in turn, significantly alter the total biomass and compositional response of forests to future warming. An increase in disturbance frequency is also likely to increase the rate at which natural vegetation responses to future climate change. The results reinforce the hypothesis that forests could be significantly altered by the first part of the next century. The modeling also confirms the potential utility of selected time series of fossil pollen data for investigating the poorly understood natural patterns of century-scale climate variability.

The paradox of cooling streams in a warming world: regional climate trends do not parallel variable local trends in stream temperature in the Pacific continental United States

Treesearch

Ivan Arismendi; Sherri L. Johnson; Jason B. Dunham; Roy Haggerty

2012-01-01

Temperature is a fundamentally important driver of ecosystem processes in streams. Recent warming of terrestrial climates around the globe has motivated concern about consequent increases in stream temperature. More specifically, observed trends of increasing air temperature and declining stream flow are widely believed to result in corresponding increases in stream...

Impacts of climate variability and change on crop yield in sub-Sahara Africa

NASA Astrophysics Data System (ADS)

Pan, S.; Zhang, J.; Yang, J.; Chen, G.; Xu, R.; Zhang, B.; Lou, Y.

2017-12-01

Much concern has been raised about the impacts of climate change and climate extremes on Africa's food security. The impact of climate change on Africa's agriculture is likely to be severe compared to other continents due to high rain-fed agricultural dependence, and limited ability to mitigate and adapt to climate change. In recent decades, warming in Africa is more pronounced and faster than the global average and this trend is likely to continue in the future. However, quantitative assessment on impacts of climate extremes and climate change on crop yield has not been well investigated yet. By using an improved agricultural module of the Dynamic Land Ecosystem Model (DLEM-AG2) driven by spatially-explicit information on land use, climate and other environmental changes, we have assessed impacts of historical climate variability and future climate change on food crop yield across the sub-Sahara Africa during1980-2016 and the rest of the 21st century (2017-2099). Our simulated results indicate that African crop yield in the past three decades shows an increasing trend primarily due to cropland expansion. However, crop yield shows substantially spatial and temporal variation due to inter-annual and inter-decadal climate variability and spatial heterogeneity of environmental drivers. Droughts have largely reduced crop yield in the most vulnerable regions of Sub-Sahara Africa. Future projections with DLEM-AG2 show that food crop production in Sub-Sahara Africa would be favored with limiting end-of-century warming to below 1.50 C.

Projected Impact of Climate Change on Hydrological Regimes in the Philippines

PubMed Central

Kanamaru, Hideki; Keesstra, Saskia; Maroulis, Jerry; David, Carlos Primo C.; Ritsema, Coen J.

2016-01-01

The Philippines is one of the most vulnerable countries in the world to the potential impacts of climate change. To fully understand these potential impacts, especially on future hydrological regimes and water resources (2010-2050), 24 river basins located in the major agricultural provinces throughout the Philippines were assessed. Calibrated using existing historical interpolated climate data, the STREAM model was used to assess future river flows derived from three global climate models (BCM2, CNCM3 and MPEH5) under two plausible scenarios (A1B and A2) and then compared with baseline scenarios (20th century). Results predict a general increase in water availability for most parts of the country. For the A1B scenario, CNCM3 and MPEH5 models predict an overall increase in river flows and river flow variability for most basins, with higher flow magnitudes and flow variability, while an increase in peak flow return periods is predicted for the middle and southern parts of the country during the wet season. However, in the north, the prognosis is for an increase in peak flow return periods for both wet and dry seasons. These findings suggest a general increase in water availability for agriculture, however, there is also the increased threat of flooding and enhanced soil erosion throughout the country. PMID:27749908

Identifying the fingerprints of the anthropogenic component of land use/land cover changes on regional climate of the USA high plains

NASA Astrophysics Data System (ADS)

Mutiibwa, D.; Irmak, S.

2011-12-01

The majority of recent climate change studies have largely focused on detection and attribution of anthropogenic forcings of greenhouse gases, aerosols, stratospheric and tropospheric ozone. However, there is growing evidence that land cover/land use (LULC) change can significantly impact atmospheric processes from local to regional weather and climate variability. Human activities such as conversion of natural ecosystem to croplands and urban-centers, deforestation and afforestation impact biophysical properties of the land surfaces including albedo, energy balance, moisture-holding capacity of soil, and surface roughness. Alterations in these properties affect the heat and moisture exchanges between the land surface and atmospheric boundary layer, and ultimately impact the climate system. The challenge is to demonstrate that LULC changes produce a signal that can be discerned from natural climate noise. In this study, we attempt to detect the signature of anthropogenic forcing of LULC change on climate on regional scale. The signal projector investigated for detecting the signature of LULC changes on regional climate of the High Plains of the USA is the Normalized Difference Vegetation Index (NDVI). NDVI is an indicator that captures short and long-term geographical distribution of vegetation surfaces. The study develops an enhanced signal processing procedure to maximize the signal to noise ratio by introducing a pre-filtering technique of ARMA processes on the investigated climate and signal variables, before applying the optimal fingerprinting technique to detect the signals of LULC changes on observed climate, temperature, in the High Plains. The intent is to filter out as much noise as possible while still retaining the essential features of the signal by making use of the known characteristics of the noise and the anticipated signal. The study discusses the approach of identifying and suppressing the autocorrelation in optimal fingerprint analysis by applying linear transformation of ARMA processes to the analysis variables. With the assumption that natural climate variability is a near stationary process, the pre-filters are developed to generate stationary residuals. The High Plains region although impacted by droughts over the last three decades has had an increase in agricultural lands, both irrigated and non-irrigated. The study shows that for the most part of the High Plains region there is significant influence of evaporative cooling on regional climate during the summer months. As the vegetation coverage increases coupled with increased in irrigation application, the regional daytime surface energy in summer is increasingly redistributed into latent heat flux which increases the effect of evaporative cooling on summer temperatures. We included the anthropogenic forcing of CO2 on regional climate with the main purpose of surpassing the radiative heating effect of greenhouse gases from natural climate noise, to enhance the LULC signal-to-noise ratio. The warming signal due to greenhouse gas forcing is observed to be weakest in the central part of the High Plains. The results showed that the CO2 signal in the region was weak or is being surpassed by the evaporative cooling effect.

The potential health impacts of climate variability and change for the United States: executive summary of the report of the health sector of the U.S. National Assessment.

PubMed Central

Patz, J A; McGeehin, M A; Bernard, S M; Ebi, K L; Epstein, P R; Grambsch, A; Gubler, D J; Reither, P; Romieu, I; Rose, J B; Samet, J M; Trtanj, J

2000-01-01

We examined the potential impacts of climate variability and change on human health as part of a congressionally mandated study of climate change in the United States. Our author team, comprising experts from academia, government, and the private sector, was selected by the federal interagency U.S. Global Change Research Program, and this report stems from our first 18 months of work. For this assessment we used a set of assumptions and/or projections of future climates developed for all participants in the National Assessment of the Potential Consequences of Climate Variability and Change. We identified five categories of health outcomes that are most likely to be affected by climate change because they are associated with weather and/or climate variables: temperature-related morbidity and mortality; health effects of extreme weather events (storms, tornadoes, hurricanes, and precipitation extremes); air-pollution-related health effects; water- and foodborne diseases; and vector- and rodent-borne diseases. We concluded that the levels of uncertainty preclude any definitive statement on the direction of potential future change for each of these health outcomes, although we developed some hypotheses. Although we mainly addressed adverse health outcomes, we identified some positive health outcomes, notably reduced cold-weather mortality, which has not been extensively examined. We found that at present most of the U.S. population is protected against adverse health outcomes associated with weather and/or climate, although certain demographic and geographic populations are at increased risk. We concluded that vigilance in the maintenance and improvement of public health systems and their responsiveness to changing climate conditions and to identified vulnerable subpopulations should help to protect the U.S. population from any adverse health outcomes of projected climate change. PMID:10753097

The potential health impacts of climate variability and change for the United States: executive summary of the report of the health sector of the U.S. National Assessment.

PubMed

Patz, J A; McGeehin, M A; Bernard, S M; Ebi, K L; Epstein, P R; Grambsch, A; Gubler, D J; Reither, P; Romieu, I; Rose, J B; Samet, J M; Trtanj, J

2000-04-01

We examined the potential impacts of climate variability and change on human health as part of a congressionally mandated study of climate change in the United States. Our author team, comprising experts from academia, government, and the private sector, was selected by the federal interagency U.S. Global Change Research Program, and this report stems from our first 18 months of work. For this assessment we used a set of assumptions and/or projections of future climates developed for all participants in the National Assessment of the Potential Consequences of Climate Variability and Change. We identified five categories of health outcomes that are most likely to be affected by climate change because they are associated with weather and/or climate variables: temperature-related morbidity and mortality; health effects of extreme weather events (storms, tornadoes, hurricanes, and precipitation extremes); air-pollution-related health effects; water- and foodborne diseases; and vector- and rodent-borne diseases. We concluded that the levels of uncertainty preclude any definitive statement on the direction of potential future change for each of these health outcomes, although we developed some hypotheses. Although we mainly addressed adverse health outcomes, we identified some positive health outcomes, notably reduced cold-weather mortality, which has not been extensively examined. We found that at present most of the U.S. population is protected against adverse health outcomes associated with weather and/or climate, although certain demographic and geographic populations are at increased risk. We concluded that vigilance in the maintenance and improvement of public health systems and their responsiveness to changing climate conditions and to identified vulnerable subpopulations should help to protect the U.S. population from any adverse health outcomes of projected climate change.

Assessing the Role of Climate Variability on Liver Fluke Risk in the UK Through Mechanistic Hydro-Epidemiological Modelling

NASA Astrophysics Data System (ADS)

Beltrame, L.; Dunne, T.; Rose, H.; Walker, J.; Morgan, E.; Vickerman, P.; Wagener, T.

2016-12-01

Liver fluke is a flatworm parasite infecting grazing animals worldwide. In the UK, it causes considerable production losses to cattle and sheep industries and costs farmers millions of pounds each year due to reduced growth rates and lower milk yields. Large part of the parasite life-cycle takes place outside of the host, with its survival and development strongly controlled by climatic and hydrologic conditions. Evidence of climate-driven changes in the distribution and seasonality of fluke disease already exists, as the infection is increasingly expanding to new areas and becoming a year-round problem. Therefore, it is crucial to assess current and potential future impacts of climate variability on the disease to guide interventions at the farm scale and mitigate risk. Climate-based fluke risk models have been available since the 1950s, however, they are based on empirical relationships derived between historical climate and incidence data, and thus are unlikely to be robust for simulating risk under changing conditions. Moreover, they are not dynamic, but estimate risk over large regions in the UK based on monthly average climate conditions, so they do not allow investigating the effects of climate variability for supporting farmers' decisions. In this study, we introduce a mechanistic model for fluke, which represents habitat suitability for disease development at 25m resolution with a daily time step, explicitly linking the parasite life-cycle to key hydro-climate conditions. The model is used on a case study in the UK and sensitivity analysis is performed to better understand the role of climate variability on the space-time dynamics of the disease, while explicitly accounting for uncertainties. Comparisons are presented with experts' knowledge and a widely used empirical model.

Influence of long-range atmospheric transport pathways and climate teleconnection patterns on the variability of surface 210Pb and 7Be concentrations in southwestern Europe.

PubMed

Grossi, C; Ballester, J; Serrano, I; Galmarini, S; Camacho, A; Curcoll, R; Morguí, J A; Rodò, X; Duch, M A

2016-12-01

The variability of the atmospheric concentration of the 7 Be and 210 Pb radionuclides is strongly linked to the origin of air masses, the strength of their sources and the processes of wet and dry deposition. It has been shown how these processes and their variability are strongly affected by climate change. Thus, a deeper knowledge of the relationship between the atmospheric radionuclides variability measured close to the ground and these atmospheric processes could help in the analysis of climate scenarios. In the present study, we analyze the atmospheric variability of a 14-year time series of 7 Be and 210 Pb in a Mediterranean coastal city using a synergy of different indicators and tools such as: the local meteorological conditions, global and regional climate indexes and a lagrangian atmospheric transport model. We particularly focus on the relationships between the main pathways of air masses and sun spots occurrence, the variability of the local relative humidity and temperature conditions, and the main modes of regional climate variability, such as the North Atlantic Oscillation (NAO) and the Western Mediterranean Oscillation (WeMO). The variability of the observed atmospheric concentrations of both 7 Be and 210 Pb radionuclides was found to be mainly positively associated to the local climate conditions of temperature and to the pathways of air masses arriving at the station. Measured radionuclide concentrations significantly increase when air masses travel at low tropospheric levels from central Europe and the western part of the Iberian Peninsula, while low concentrations are associated with westerly air masses. We found a significant negative correlation between the WeMO index and the atmospheric variability of both radionuclides and no significant association was observed for the NAO index. Copyright © 2016 Elsevier Ltd. All rights reserved.

CLIMATE VARIABILITY, ANTHROPOGENIC CHANGE, AND CONSEQUENCES IN THE MID-ATLANTIC

EPA Science Inventory

When compared to the preceding millennium, the rate of temperature change over the past century strongly suggests that we are in a period of rapid global climate change. Globally, continued anthropogenic increases in concentrations of atmospheric greenhouse gases probably will re...

Enhanced precipitation variability decreases grass- and increases shrub-productivity

PubMed Central

Gherardi, Laureano A.; Sala, Osvaldo E.

2015-01-01

Although projections of precipitation change indicate increases in variability, most studies of impacts of climate change on ecosystems focused on effects of changes in amount of precipitation, overlooking precipitation variability effects, especially at the interannual scale. Here, we present results from a 6-y field experiment, where we applied sequences of wet and dry years, increasing interannual precipitation coefficient of variation while maintaining a precipitation amount constant. Increased precipitation variability significantly reduced ecosystem primary production. Dominant plant-functional types showed opposite responses: perennial-grass productivity decreased by 81%, whereas shrub productivity increased by 67%. This pattern was explained by different nonlinear responses to precipitation. Grass productivity presented a saturating response to precipitation where dry years had a larger negative effect than the positive effects of wet years. In contrast, shrubs showed an increasing response to precipitation that resulted in an increase in average productivity with increasing precipitation variability. In addition, the effects of precipitation variation increased through time. We argue that the differential responses of grasses and shrubs to precipitation variability and the amplification of this phenomenon through time result from contrasting root distributions of grasses and shrubs and competitive interactions among plant types, confirmed by structural equation analysis. Under drought conditions, grasses reduce their abundance and their ability to absorb water that then is transferred to deep soil layers that are exclusively explored by shrubs. Our work addresses an understudied dimension of climate change that might lead to widespread shrub encroachment reducing the provisioning of ecosystem services to society. PMID:26417095

Roosevelt Island Climate Evolution Project (RICE): A 65 Kyr ice core record of black carbon aerosol deposition to the Ross Ice Shelf, West Antarctica.

NASA Astrophysics Data System (ADS)

Edwards, Ross; Bertler, Nancy; Tuohy, Andrea; Neff, Peter; Proemse, Bernedette; Feiteng, Wang; Goodwin, Ian; Hogan, Chad

2015-04-01

Emitted by fires, black carbon aerosols (rBC) perturb the atmosphere's physical and chemical properties and are climatically active. Sedimentary charcoal and other paleo-fire records suggest that rBC emissions have varied significantly in the past due to human activity and climate variability. However, few paleo rBC records exist to constrain reconstructions of the past rBC atmospheric distribution and its climate interaction. As part of the international Roosevelt Island Climate Evolution (RICE) project, we have developed an Antarctic rBC ice core record spanning the past ~65 Kyr. The RICE deep ice core was drilled from the Roosevelt Island ice dome in West Antarctica from 2011 to 2013. The high depth resolution (~ 1 cm) record was developed using a single particle intracavity laser-induced incandescence soot photometer (SP2) coupled to an ice core melter system. The rBC record displays sub-annual variability consistent with both austral dry-season and summer biomass burning. The record exhibits significant decadal to millennial-scale variability consistent with known changes in climate. Glacial rBC concentrations were much lower than Holocene concentrations with the exception of several periods of abrupt increases in rBC. The transition from glacial to interglacial rBC concentrations occurred over a much longer time relative to other ice core climate proxies such as water isotopes and suggests . The protracted increase in rBC during the transition may reflected Southern hemisphere ecosystem / fire regime changes in response to hydroclimate and human activity.

The climatic implications of the Holocene floods in the north-western Himalaya, India

NASA Astrophysics Data System (ADS)

Sharma, S.; Shukla, A. D.; Bartarya, S.; Marh, B.; Juyal, N.

2016-12-01

Understanding the growing trend of extreme hydrological events in response to climate variabilities is a major area of interest in the climate change science. More important so as the predictions suggest increased frequency and/or magnitude of floods in the Himalayan region due to more intense/frequent coupling between the Indian Summer Monsoon (ISM) and the mid-latitude westerlies. In view of this, studies pertaining to the geological evidence of extreme hydrological events (paleofloods) become important as these not only extend beyond the instrumental records but ensures better understanding of the pattern of river response to the extreme climate variability.The Satluj River in the north-western Himalaya is infamous for its history of recurrent and devastating floods for which there is no data beyond the historical record. The present study in the middle Satluj valley is a contribution towards expanding the cognizance of the climate and geomorphic processes responsible for the Holocene extreme events. Based on sedimentology and grain size variability a total of 24 flood events of increasing magnitude are identified. The geochemical data indicate that the flood sediments were mostly generated and transported from the Higher Himalayan Crystalline with some contribution from the Trans-Himalaya. The optical chronology allow us to identify four major flood clusters which are dated between 13-11 ka; 8-4 ka; 4-2 ka and < 2 ka respectively. Climatically, these correspond to the cooler/relatively drier climatic condition (weak monsoon) and broadly correlate with the phases of negative Arctic Oscillation (‒AO) and negative North Atlantic Oscillation (-NAO).

Climatic variability in the Gulf of California associated with the Medieval Warm Period and the Little Ice Age

NASA Astrophysics Data System (ADS)

Flores-Castillo, O. D. L. A.; Martínez-López, A.; Perez-Cruz, L. L.

2017-12-01

Marine ecosystems close to the coasts are highly susceptible to be affected both by the variability due to natural processes of the climate system as well as by anthropogenic activities. The Gulf of California, located near the tropical Pacific region, whose influence on the long-term global climate has already been demonstrated, represents a great opportunity to assess the regional response to these effects. This study reconstructs some of the oceanographic and climatic conditions that occurred simultaneously with the Medieval Warm Period (MWP) and the Little Ice Age (LIA) climatic periods in the southern region of the gulf. This reconstruction was based on the use of multiple indirect indicators or proxies of paleoproduction and geochemistry (determined by isotope-ratios mass spectrometer interfaced with an elemental analyzer and inductively coupled plasma mass spectrometry) preserved in a high-resolution laminated sedimentary sequence collected in the slope of southeastern coast of the Gulf of California (24.2822 ° N and 108.3037 ° W). The main effects of these periods were higher precipitation conditions that generated a greater fluvial contribution during the MWP besides a bigger oxygenation of the water mass near the bottom. These conditions were followed by an increase in exported production, decrease in the oxygen content of the water near the bottom and an increase in the denitrification during the transition to the LIA. The results confirm the existence of oceanographic and climatic variability on a secular scale in the Gulf of California associated with both global climatic periods.

Analysis of long-term climate change on per capita water demand in urban versus suburban areas in the Portland metropolitan area, USA

NASA Astrophysics Data System (ADS)

Parandvash, G. Hossein; Chang, Heejun

2016-07-01

We investigated the impacts of long-term climate variability and change on per capita water demand in urban and suburban service areas that have different degrees of development density in the Portland metropolitan area, USA. Together with historical daily weather and water production data, socioeconomic data such as population and unemployment rate were used to estimate daily per capita water demand in the two service areas. The structural time series regression model results show that the sensitivity of per capita water demand to both weather and unemployment rate variables is higher in suburban areas than in urban areas. This is associated with relatively higher proportional demand by the residential sector in the suburban area. The estimated coefficients of the historical demand model were used to project the mid-21st century (2035-2064) per capita water demand under three climate change scenarios that represent high (HadGEM2-ES), medium (MIROC5), and low (GFDL) climate changes. Without climate adaptation, compared to the historical period between 1983 and 2012, per capita water demand is projected to increase by 10.6% in the 2035-2064 period under the HadGEM2-ES in suburban areas, while per capita demand is projected to increase by 4.8% under the same scenario in urban areas. Our findings have implications for future urban water resource management and land use planning in the context of climate variability and change. A tight integration between water resource management and urban planning is needed for preparing for climate adaptation in municipal water planning and management.

Does the weather influence public opinion about climate change?

NASA Astrophysics Data System (ADS)

Donner, S. D.; McDaniel, J.

2010-12-01

Public opinion in North America about the science of anthropogenic climate change and the motivation for policy action has been variable over the past twenty years. The trends in public opinion over time have been attributed the general lack of pressing public concern about climate change to a range of political, economic and psychological factors. One driving force behind the variability in polling data from year to year may be the weather itself. The difference between what we “expect” - the climate - and what we “get” - the weather - can be a major source of confusion and obfuscation in the public discourse about climate change. For example, reaction to moderate global temperatures in 2007 and 2008 may have helped prompt the spread of a “global cooling” meme in the public and the news media. At the same time, a decrease in the belief in the science of climate change and the need for action has been noted in opinion polls. This study analyzes the relationship between public opinion about climate change and the weather in the U.S. since the mid-1980s using historical polling data from several major organizations (e.g. Gallup, Pew, Harris Interactive, ABC News), historical monthly air temperature (NCDC) and a survey of opinion articles from major U.S. newspapers (Washington Post, New York Times, Wall Street Journal, Houston Chronicle, USA Today). Seasonal and annual monthly temperature anomalies for the northeastern U.S and the continental U.S are compared with available national opinion data for three general categories of questions: i) Is the climate warming?, ii) Is the observed warming due to human activity?, and iii) Are you concerned about climate change? The variability in temperature and public opinion over time is also compared with the variability in the fraction of opinion articles in the newspapers (n ~ 7000) which express general agreement or disagreement with IPCC Summary for Policymakers consensus statements on climate change (“most of the observed increase in global average temperature is very likely to be due to the observed increase in anthropogenic greenhouse gas concentrations”). The results reveal a possible link between opinion leaders, particularly in the northeastern U.S, public confusion about the difference between weather and climate, and the evolution of U.S. public opinion about climate change.

Climate forcing and desert malaria: the effect of irrigation.

PubMed

Baeza, Andres; Bouma, Menno J; Dobson, Andy P; Dhiman, Ramesh; Srivastava, Harish C; Pascual, Mercedes

2011-07-14

Rainfall variability and associated remote sensing indices for vegetation are central to the development of early warning systems for epidemic malaria in arid regions. The considerable change in land-use practices resulting from increasing irrigation in recent decades raises important questions on concomitant change in malaria dynamics and its coupling to climate forcing. Here, the consequences of irrigation level for malaria epidemics are addressed with extensive time series data for confirmed Plasmodium falciparum monthly cases, spanning over two decades for five districts in north-west India. The work specifically focuses on the response of malaria epidemics to rainfall forcing and how this response is affected by increasing irrigation. Remote sensing data for the Normalized Difference Vegetation Index (NDVI) are used as an integrated measure of rainfall to examine correlation maps within the districts and at regional scales. The analyses specifically address whether irrigation has decreased the coupling between malaria incidence and climate variability, and whether this reflects (1) a breakdown of NDVI as a useful indicator of risk, (2) a weakening of rainfall forcing and a concomitant decrease in epidemic risk, or (3) an increase in the control of malaria transmission. The predictive power of NDVI is compared against that of rainfall, using simple linear models and wavelet analysis to study the association of NDVI and malaria variability in the time and in the frequency domain respectively. The results show that irrigation dampens the influence of climate forcing on the magnitude and frequency of malaria epidemics and, therefore, reduces their predictability. At low irrigation levels, this decoupling reflects a breakdown of local but not regional NDVI as an indicator of rainfall forcing. At higher levels of irrigation, the weakened role of climate variability may be compounded by increased levels of control; nevertheless this leads to no significant decrease in the actual risk of disease. This implies that irrigation can lead to more endemic conditions for malaria, creating the potential for unexpectedly large epidemics in response to excess rainfall if these climatic events coincide with a relaxation of control over time. The implications of our findings for control policies of epidemic malaria in arid regions are discussed.

Improving Decision-Making Activities for Meningitis and Malaria

NASA Astrophysics Data System (ADS)

Ceccato, P.; Trzaska, S.; Perez, C.; Kalashnikova, O. V.; del Corral, J.; Cousin, R.; Blumenthal, M. B.; Connor, S.; Thomson, M. C.

2012-12-01

Public health professionals are increasingly concerned about the potential impact that climate variability and change can have on infectious disease. The International Research Institute for Climate and Society (IRI) is developing new products to increase the public health community's capacity to understand, use, and demand the appropriate climate data and climate information to mitigate the public health impacts of climate on infectious disease, in particular Meningitis and Malaria. In this paper we present the new and improved products that have been developed for monitoring dust, temperature, rainfall and vectorial capacity model for monitoring and forecasting risks of Meningitis and Malaria epidemics. We also present how the products have been integrated into a knowledge system (IRI Data Library Map room, SERVIR) to support the use of climate and environmental information in climate-sensitive health decision-making.

Sustainability or Collapse: Interplay Between Decadal Climate Variability and Human Activities Matters

NASA Astrophysics Data System (ADS)

Lu, Y.; Hu, H.; Tian, F.

2016-12-01

The Aral Sea Crisis and the deterioration of Tarim River Basin are representative cases of emergent water deficit problems in arid areas. Comparing cases of water deficit problems in different regions and considering the in the perspective of socio-hydrology is helpful to obtain guidance on integrated management of arid area basins. Analyzing the interplay between decadal climate variability and human activities in both basins, the important role of human activities is observed. Decadal climate variability tempts people to adapt fast to increasing water resources and slowly to decreasing water resources, while using unsustainable technical measures to offset water shortage. Due to this asymmetry the situation deteriorates with technically enhanced capabilities of societies to exploit water resources, and more integrated long-term management capacity is in high demand.

Assessment of Vulnerability to Coccidioidomycosis in Arizona and California.

PubMed

Shriber, Jennifer; Conlon, Kathryn C; Benedict, Kaitlin; McCotter, Orion Z; Bell, Jesse E

2017-06-23

Coccidioidomycosis is a fungal infection endemic to the southwestern United States, particularly Arizona and California. Its incidence has increased, potentially due in part to the effects of changing climatic variables on fungal growth and spore dissemination. This study aims to quantify the county-level vulnerability to coccidioidomycosis in Arizona and California and to assess the relationships between population vulnerability and climate variability. The variables representing exposure, sensitivity, and adaptive capacity were combined to calculate county level vulnerability indices. Three methods were used: (1) principal components analysis; (2) quartile weighting; and (3) percentile weighting. Two sets of indices, "unsupervised" and "supervised", were created. Each index was correlated with coccidioidomycosis incidence data from 2000-2014. The supervised percentile index had the highest correlation; it was then correlated with variability measures for temperature, precipitation, and drought. The supervised percentile index was significantly correlated ( p < 0.05) with coccidioidomycosis incidence in both states. Moderate, positive significant associations ( p < 0.05) were found between index scores and climate variability when both states were concurrently analyzed and when California was analyzed separately. This research adds to the body of knowledge that could be used to target interventions to vulnerable counties and provides support for the hypothesis that population vulnerability to coccidioidomycosis is associated with climate variability.

Assessment of Vulnerability to Coccidioidomycosis in Arizona and California

PubMed Central

Conlon, Kathryn C.; Benedict, Kaitlin; McCotter, Orion Z.; Bell, Jesse E.

2017-01-01

Coccidioidomycosis is a fungal infection endemic to the southwestern United States, particularly Arizona and California. Its incidence has increased, potentially due in part to the effects of changing climatic variables on fungal growth and spore dissemination. This study aims to quantify the county-level vulnerability to coccidioidomycosis in Arizona and California and to assess the relationships between population vulnerability and climate variability. The variables representing exposure, sensitivity, and adaptive capacity were combined to calculate county level vulnerability indices. Three methods were used: (1) principal components analysis; (2) quartile weighting; and (3) percentile weighting. Two sets of indices, “unsupervised” and “supervised”, were created. Each index was correlated with coccidioidomycosis incidence data from 2000–2014. The supervised percentile index had the highest correlation; it was then correlated with variability measures for temperature, precipitation, and drought. The supervised percentile index was significantly correlated (p < 0.05) with coccidioidomycosis incidence in both states. Moderate, positive significant associations (p < 0.05) were found between index scores and climate variability when both states were concurrently analyzed and when California was analyzed separately. This research adds to the body of knowledge that could be used to target interventions to vulnerable counties and provides support for the hypothesis that population vulnerability to coccidioidomycosis is associated with climate variability. PMID:28644403

Assessing the climate-scale variability of atmospheric rivers affecting western North America

NASA Astrophysics Data System (ADS)

Gershunov, Alexander; Shulgina, Tamara; Ralph, F. Martin; Lavers, David A.; Rutz, Jonathan J.

2017-08-01

A new method for automatic detection of atmospheric rivers (ARs) is developed and applied to an atmospheric reanalysis, yielding an extensive catalog of ARs land-falling along the west coast of North America during 1948-2017. This catalog provides a large array of variables that can be used to examine AR cases and their climate-scale variability in exceptional detail. The new record of AR activity, as presented, validated and examined here, provides a perspective on the seasonal cycle and the interannual-interdecadal variability of AR activity affecting the hydroclimate of western North America. Importantly, AR intensity does not exactly follow the climatological pattern of AR frequency. Strong links to hydroclimate are demonstrated using a high-resolution precipitation data set. We describe the seasonal progression of AR activity and diagnose linkages with climate variability expressed in Pacific sea surface temperatures, revealing links to Pacific decadal variability, recent regional anomalies, as well as a generally rising trend in land-falling AR activity. The latter trend is consistent with a long-term increase in vapor transport from the warming North Pacific onto the North American continent. The new catalog provides unprecedented opportunities to study the climate-scale behavior and predictability of ARs affecting western North America.

Assessing the sensitivity of avian species abundance to land cover and climate

USGS Publications Warehouse

LeBrun, Jaymi J.; Thogmartin, Wayne E.; Thompson, Frank R.; Dijak, William D.; Millspaugh, Joshua J.

2016-01-01

Climate projections for the Midwestern United States predict southerly climates to shift northward. These shifts in climate could alter distributions of species across North America through changes in climate (i.e., temperature and precipitation), or through climate-induced changes on land cover. Our objective was to determine the relative impacts of land cover and climate on the abundance of five bird species in the Central United States that have habitat requirements ranging from grassland and shrubland to forest. We substituted space for time to examine potential impacts of a changing climate by assessing climate and land cover relationships over a broad latitudinal gradient. We found positive and negative relationships of climate and land cover factors with avian abundances. Habitat variables drove patterns of abundance in migratory and resident species, although climate was also influential in predicting abundance for some species occupying more open habitat (i.e., prairie warbler, blue-winged warbler, and northern bobwhite). Abundance of northern bobwhite increased with winter temperature and was the species exhibiting the most significant effect of climate. Models for birds primarily occupying early successional habitats performed better with a combination of habitat and climate variables whereas models of species found in contiguous forest performed best with land cover alone. These varied species-specific responses present unique challenges to land managers trying to balance species conservation over a variety of land covers. Management activities focused on increasing forest cover may play a role in mitigating effects of future climate by providing habitat refugia to species vulnerable to projected changes. Conservation efforts would be best served focusing on areas with high species abundances and an array of habitats. Future work managing forests for resilience and resistance to climate change could benefit species already susceptible to climate impacts.

[Paleoclimate of La Guajira, Colombia; by the growth rings of Capparis odoratissima (Capparidaceae)].

PubMed

Ramírez, Jorge Andrés; Ignacio del Valle, Jorge

2011-09-01

There is great concern about the effect of climate change in arid and subarid areas of the tropics. Climate change combined with other anthropogenic activities such as deforestation, fires and over-grazing can accelerate their degradation and, consequently, the increases in losses of biological and economic productivity. Climate models, both local and global, predict that rainfall in the arid Peninsula of La Guajira in the Colombian Caribbean would be reduced and temperature would be increased as a result of climate change. However, as there are only suitable climate records since 1972, it is not possible to verify if, indeed, this is happening. To try to verify the hypothesis of reducing rainfall and rising temperatures we developed a growth ring chronology of Capparis odoratissima in the Middle Peninsula of La Guajira with 17 trees and 45 series which attain 48 years back. We use standard dendrochronological methods that showed statistically significant linear relationship with local climatic variables such as air temperature, sea surface temperature (SST), annual precipitation and wind speed; we also reach to successful relationship of the chronology with global climatic variables as the indices SOI and MEI of the ENSO phenomenon. The transfer functions estimated with the time series (1955 and 2003) do not showed statistically significant trends, indicating that during this period of time the annual precipitation or temperatures have not changed. The annual nature of C. odoratissima growth rings, the possibility of cross-dated among the samples of this species, and the high correlation with local and global climatic variables indicate a high potential of this species for dendrochronological studies in this part of the American continent.

Local Variability Mediates Vulnerability of Trout Populations to Land Use and Climate Change

PubMed Central

Penaluna, Brooke E.; Dunham, Jason B.; Railsback, Steve F.; Arismendi, Ivan; Johnson, Sherri L.; Bilby, Robert E.; Safeeq, Mohammad; Skaugset, Arne E.

2015-01-01

Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of Coastal Cutthroat Trout (Oncorhynchus clarkii clarkii) to scenarios simulating identical changes in temperature and stream flows linked to forest harvest, climate change, and their combined effects over six decades. We parameterized the model for four neighboring streams located in a forested headwater catchment in northwestern Oregon, USA with multi-year, daily measurements of stream temperature, flow, and turbidity (2007–2011), and field measurements of both instream habitat structure and three years of annual trout population estimates. Model simulations revealed that variability in habitat conditions among streams (depth, available habitat) mediated the effects of forest harvest and climate change. Net effects for most simulated trout responses were different from or less than the sum of their separate scenarios. In some cases, forest harvest countered the effects of climate change through increased summer flow. Climate change most strongly influenced trout (earlier fry emergence, reductions in biomass of older trout, increased biomass of young-of-year), but these changes did not consistently translate into reductions in biomass over time. Forest harvest, in contrast, produced fewer and less consistent responses in trout. Earlier fry emergence driven by climate change was the most consistent simulated response, whereas survival, growth, and biomass were inconsistent. Overall our findings indicate a host of local processes can strongly influence how populations respond to broad scale effects of land use and climate change. PMID:26295478

Local variability mediates vulnerability of trout populations to land use and climate change

USGS Publications Warehouse

Penaluna, Brooke E.; Dunham, Jason B.; Railsback, Steve F.; Arismendi, Ivan; Johnson, Sherri L.; Bilby, Robert E; Safeeq, Mohammad; Skaugset, Arne E.

2015-01-01

Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of Coastal Cutthroat Trout (Oncorhynchus clarkii clarkii) to scenarios simulating identical changes in temperature and stream flows linked to forest harvest, climate change, and their combined effects over six decades. We parameterized the model for four neighboring streams located in a forested headwater catchment in northwestern Oregon, USA with multi-year, daily measurements of stream temperature, flow, and turbidity (2007–2011), and field measurements of both instream habitat structure and three years of annual trout population estimates. Model simulations revealed that variability in habitat conditions among streams (depth, available habitat) mediated the effects of forest harvest and climate change. Net effects for most simulated trout responses were different from or less than the sum of their separate scenarios. In some cases, forest harvest countered the effects of climate change through increased summer flow. Climate change most strongly influenced trout (earlier fry emergence, reductions in biomass of older trout, increased biomass of young-of-year), but these changes did not consistently translate into reductions in biomass over time. Forest harvest, in contrast, produced fewer and less consistent responses in trout. Earlier fry emergence driven by climate change was the most consistent simulated response, whereas survival, growth, and biomass were inconsistent. Overall our findings indicate a host of local processes can strongly influence how populations respond to broad scale effects of land use and climate change.

Local Variability Mediates Vulnerability of Trout Populations to Land Use and Climate Change.

PubMed

Penaluna, Brooke E; Dunham, Jason B; Railsback, Steve F; Arismendi, Ivan; Johnson, Sherri L; Bilby, Robert E; Safeeq, Mohammad; Skaugset, Arne E

2015-01-01

Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of Coastal Cutthroat Trout (Oncorhynchus clarkii clarkii) to scenarios simulating identical changes in temperature and stream flows linked to forest harvest, climate change, and their combined effects over six decades. We parameterized the model for four neighboring streams located in a forested headwater catchment in northwestern Oregon, USA with multi-year, daily measurements of stream temperature, flow, and turbidity (2007-2011), and field measurements of both instream habitat structure and three years of annual trout population estimates. Model simulations revealed that variability in habitat conditions among streams (depth, available habitat) mediated the effects of forest harvest and climate change. Net effects for most simulated trout responses were different from or less than the sum of their separate scenarios. In some cases, forest harvest countered the effects of climate change through increased summer flow. Climate change most strongly influenced trout (earlier fry emergence, reductions in biomass of older trout, increased biomass of young-of-year), but these changes did not consistently translate into reductions in biomass over time. Forest harvest, in contrast, produced fewer and less consistent responses in trout. Earlier fry emergence driven by climate change was the most consistent simulated response, whereas survival, growth, and biomass were inconsistent. Overall our findings indicate a host of local processes can strongly influence how populations respond to broad scale effects of land use and climate change.

A top-down approach to projecting market impacts of climate change

NASA Astrophysics Data System (ADS)

Lemoine, Derek; Kapnick, Sarah

2016-01-01

To evaluate policies to reduce greenhouse-gas emissions, economic models require estimates of how future climate change will affect well-being. So far, nearly all estimates of the economic impacts of future warming have been developed by combining estimates of impacts in individual sectors of the economy. Recent work has used variation in warming over time and space to produce top-down estimates of how past climate and weather shocks have affected economic output. Here we propose a statistical framework for converting these top-down estimates of past economic costs of regional warming into projections of the economic cost of future global warming. Combining the latest physical climate models, socioeconomic projections, and economic estimates of past impacts, we find that future warming could raise the expected rate of economic growth in richer countries, reduce the expected rate of economic growth in poorer countries, and increase the variability of growth by increasing the climate's variability. This study suggests we should rethink the focus on global impacts and the use of deterministic frameworks for modelling impacts and policy.

The complexity of millennial-scale variability in southwestern Europe during MIS 11

NASA Astrophysics Data System (ADS)

Oliveira, Dulce; Desprat, Stéphanie; Rodrigues, Teresa; Naughton, Filipa; Hodell, David; Trigo, Ricardo; Rufino, Marta; Lopes, Cristina; Abrantes, Fátima; Sánchez Goñi, Maria Fernanda

2016-11-01

Climatic variability of Marine Isotope Stage (MIS) 11 is examined using a new high-resolution direct land-sea comparison from the SW Iberian margin Site U1385. This study, based on pollen and biomarker analyses, documents regional vegetation, terrestrial climate and sea surface temperature (SST) variability. Suborbital climate variability is revealed by a series of forest decline events suggesting repeated cooling and drying episodes in SW Iberia throughout MIS 11. Only the most severe events on land are coeval with SST decreases, under larger ice volume conditions. Our study shows that the diverse expression (magnitude, character and duration) of the millennial-scale cooling events in SW Europe relies on atmospheric and oceanic processes whose predominant role likely depends on baseline climate states. Repeated atmospheric shifts recalling the positive North Atlantic Oscillation mode, inducing dryness in SW Iberia without systematical SST changes, would prevail during low ice volume conditions. In contrast, disruption of the Atlantic meridional overturning circulation (AMOC), related to iceberg discharges, colder SST and increased hydrological regime, would be responsible for the coldest and driest episodes of prolonged duration in SW Europe.

Modelling seasonal effects of temperature and precipitation on honey bee winter mortality in a temperate climate.

PubMed

Switanek, Matthew; Crailsheim, Karl; Truhetz, Heimo; Brodschneider, Robert

2017-02-01

Insect pollinators are essential to global food production. For this reason, it is alarming that honey bee (Apis mellifera) populations across the world have recently seen increased rates of mortality. These changes in colony mortality are often ascribed to one or more factors including parasites, diseases, pesticides, nutrition, habitat dynamics, weather and/or climate. However, the effect of climate on colony mortality has never been demonstrated. Therefore, in this study, we focus on longer-term weather conditions and/or climate's influence on honey bee winter mortality rates across Austria. Statistical correlations between monthly climate variables and winter mortality rates were investigated. Our results indicate that warmer and drier weather conditions in the preceding year were accompanied by increased winter mortality. We subsequently built a statistical model to predict colony mortality using temperature and precipitation data as predictors. Our model reduces the mean absolute error between predicted and observed colony mortalities by 9% and is statistically significant at the 99.9% confidence level. This is the first study to show clear evidence of a link between climate variability and honey bee winter mortality. Copyright © 2016 British Geological Survey, NERC. Published by Elsevier B.V. All rights reserved.

Evidence of recent climate change within the historic range of Rio Grande cutthroat trout: implications for management and future persistence

USGS Publications Warehouse

Zeigler, Matthew P.; Todd, Andrew S.; Caldwell, Colleen A.

2012-01-01

Evidence of anthropogenically influenced climate change has motivated natural resource managers to incorporate adaptive measures to minimize risks to sensitive and threatened species. Detecting trends in climate variables (i.e., air temperature and hydrology) can serve as a valuable management tool for protecting vulnerable species by increasing our understanding of localized conditions and trends. The Rio Grande cutthroat trout Oncorhynchus clarkii virginalis has suffered a severe decline in its historical distribution, with the majority of current populations persisting in isolated headwater streams. To evaluate recent climate change within the subspecies' historical range, we examined trends in average air temperatures, biologically important hydrological variables (timing of snowmelt and seasonal flows), and the April 1 snow water equivalent over the last 45 years (1963–2007). While rates of change in all three metrics were variable across sites, rangewide patterns were evident. Across the subspecies' historical range, average annual air temperatures increased (0.29°C per decade) and the timing of snowmelt shifted 10.6 d earlier in the year (2.3 d/decade). Flows increased during biologically important periods, including winter (January 1–March 31; 6.6% increase per decade), prespawning (April 1–May 14; 6.9% increase per decade), and spawning (May 15–June 15; 4.2% increase per decade) and decreased in summer (June 16–September 15; 1.9% decrease per decade). Evidence of decreasing April 1 snow water equivalent (5.3% per decade) was also observed. While the impacts of these changes at the population level are equivocal, it is likely that negative effects would influence the subspecies by altering its distribution, decreasing available habitat, and altering the timing of important life history components. Continued monitoring and proactive management will be required to increase the resiliency of remaining populations to ensure long-term persistence and protection in a changing climate.

Hydrological response to changing climate conditions: Spatial streamflow variability in the boreal region

NASA Astrophysics Data System (ADS)

Teutschbein, Claudia; Grabs, Thomas; Karlsen, Reinert H.; Laudon, Hjalmar; Bishop, Kevin

2016-04-01

It has long been recognized that streamflow-generating processes are not only dependent on climatic conditions, but also affected by physical catchment properties such as topography, geology, soils and land cover. We hypothesize that these landscape characteristics do not only lead to highly variable hydrologic behavior of rather similar catchments under the same stationary climate conditions (Karlsen et al., 2014), but that they also play a fundamental role for the sensitivity of a catchment to a changing climate (Teutschbein et al., 2015). A multi-model ensemble based on 15 regional climate models was combined with a multi-catchment approach to explore the hydrologic sensitivity of 14 partially nested and rather similar catchments in Northern Sweden to changing climate conditions and the importance of small-scale spatial variability. Current (1981-2010) and future (2061-2090) streamflow was simulated with the HBV model. As expected, projected increases in temperature and precipitation resulted in increased total available streamflow, with lower spring and summer flows, but substantially higher winter streamflow. Furthermore, significant changes in flow durations with lower chances of both high and low flows can be expected in boreal Sweden in the future. This overall trend in projected streamflow pattern changes was comparable among the analyzed catchments while the magnitude of change differed considerably. This suggests that catchments belonging to the same region can show distinctly different degrees of hydrological responses to the same external climate change signal. We reason that differences in spatially distributed physical catchment properties at smaller scales are not only of great importance for current streamflow behavior, but also play a major role as first-order control for the sensitivity of catchments to changing climate conditions. References Karlsen, R.H., T. Grabs, K. Bishop, H. Laudon, and J. Seibert (2014). Landscape controls on spatiotemporal variability of specific discharge in a boreal region, Abstract #H52B-07 presented at 2014 Fall Meeting, AGU, San Francisco, Calif., 15-19 Dec. [Available at http://adsabs.harvard.edu/abs/2014AGUFM.H52B..07K, last accessed 11 Jan 2016]. Teutschbein, C., T. Grabs, R.H. Karlsen, H. Laudon and K. Bishop (2015). Hydrological Response to Changing Climate Conditions: Spatial Streamflow Variability in the Boreal Region, Water Resour Res, doi: 10.1002/2015WR017337. [Available at http://onlinelibrary.wiley.com/doi/10.1002/2015WR017337/abstract, last accessed 11 Jan 2016].

Droughts and governance impacts on water scarcity: an~analysis in the Brazilian semi-arid

NASA Astrophysics Data System (ADS)

Silva, A. C. S.; Galvão, C. O.; Silva, G. N. S.

2015-06-01

Extreme events are part of climate variability. Dealing with variability is still a challenge that might be increased due to climate change. However, impacts of extreme events are not only dependent on their variability, but also on management and governance. In Brazil, its semi-arid region is vulnerable to extreme events, especially droughts, for centuries. Actually, other Brazilian regions that have been mostly concerned with floods are currently also experiencing droughts. This article evaluates how a combination between climate variability and water governance might affect water scarcity and increase the impacts of extreme events on some regions. For this evaluation, Ostrom's framework for analyzing social-ecological systems (SES) was applied. Ostrom's framework is useful for understanding interactions between resource systems, governance systems and resource users. This study focuses on social-ecological systems located in a drought-prone region of Brazil. Two extreme events were selected, one in 1997-2000, when Brazil's new water policy was very young, and the other one in 2012-2015. The analysis of SES considering Ostrom's principle "Clearly defined boundaries" showed that deficiencies in water management cause the intensification of drought's impacts for the water users. The reasons are more related to water management and governance problems than to drought event magnitude or climate change. This is a problem that holdup advances in dealing with extreme events.

Increasing importance of precipitation variability on global livestock grazing lands

NASA Astrophysics Data System (ADS)

Sloat, Lindsey L.; Gerber, James S.; Samberg, Leah H.; Smith, William K.; Herrero, Mario; Ferreira, Laerte G.; Godde, Cécile M.; West, Paul C.

2018-03-01

Pastures and rangelands underpin global meat and milk production and are a critical resource for millions of people dependent on livestock for food security1,2. Forage growth, which is highly climate dependent3,4, is potentially vulnerable to climate change, although precisely where and to what extent remains relatively unexplored. In this study, we assess climate-based threats to global pastures, with a specific focus on changes in within- and between-year precipitation variability (precipitation concentration index (PCI) and coefficient of variation of precipitation (CVP), respectively). Relating global satellite measures of vegetation greenness (such as the Normalized Difference Vegetation Index; NDVI) to key climatic factors reveals that CVP is a significant, yet often overlooked, constraint on vegetation productivity across global pastures. Using independent stocking data, we found that areas with high CVP support lower livestock densities than less-variable regions. Globally, pastures experience about a 25% greater year-to-year precipitation variation (CVP = 0.27) than the average global land surface area (0.21). Over the past century, CVP has generally increased across pasture areas, although both positive (49% of pasture area) and negative (31% of pasture area) trends exist. We identify regions in which livestock grazing is important for local food access and economies, and discuss the potential for pasture intensification in the context of long-term regional trends in precipitation variability.

Food Security Under Shifting Economic, Demographic, and Climatic Conditions (Invited)

NASA Astrophysics Data System (ADS)

Naylor, R. L.

2013-12-01

Global demand for food, feed, and fuel will continue to rise in a more populous and affluent world. Meeting this demand in the future will become increasingly challenging with global climate change; when production shocks stemming from climate variability are added to the new mean climate state, food markets could become more volatile. This talk will focus on the interacting market effects of demand and supply for major food commodities, with an eye on climate-related supply trends and shocks. Lessons from historical patterns of climate variability (e.g., ENSO and its global teleconnections) will be used to infer potential food security outcomes in the event of abrupt changes in the mean climate state. Domestic food and trade policy responses to crop output and price volatility in key producing and consuming nations, such as export bans and import tariffs, will be discussed as a potentially major destabilizing force, underscoring the important influence of uncertainty in achieving--or failing to achieve--food security.

Predicting Impacts of Lightning Strikes on Aviation under a Changing Climate Using Regression Kriging

NASA Astrophysics Data System (ADS)

Rakas, J.; Ding, C.; Murthi, A.; Lukovic, J.; Bajat, B.

2016-12-01

Lightning is a serious hazard that can cause significant impacts on human infrastructure. In the aviation industry, lightning strikes cause damage and outages to air traffic control equipment and facilities at airports that result in major disruptions in commercial air travel, compounding delays during storm events that lead to losses in the millions of dollars. To date poor attention has been given to how lightning might change with the increase of greenhouse gases and temperature. Under some climate change scenarios, the increase in the occurrence and severity of storms in the future with potential for increases in lightning activity has been studied. Recent findings suggest that lighting rates will increase 12 percent per every degree Celsius rise in global temperatures. That will results to a 50 percent increase by the end of the century. Accurate prediction of the intensity and frequency of lightning strikes is therefore required by the air traffic management and control sector in order to develop more robust adaptation and mitigation strategies under the threat of global climate change and increasing lightning rates. In this work, we use the regression kriging method to predict lightning strikes over several regions over the contiguous United Sates using two meteorological variables- namely convective available potential energy (CAPE) and total precipitation rate. These two variables are used as a measure of storm convection, since strong convections are related to more lightning. Specifically, CAPE multiplied by precipitation is used as a proxy for lightning strikes owing to a strong linear relationship between the two. These two meteorological variables are obtained from a subset of models used in phase 5 of the coupled model inter-comparison experiment pertaining to the "high emissions" climate change scenario corresponding to the representative concentration pathway (RCP) 8.5. Precipitation observations from the National Weather Cooperative Network (COOP) were incorporated as an additional dataset. This scenario indicates a doubling of CAPE and precipitation resulting in significant increases in CAPE×precipitation by the end of the century. Overall, this research highlights the use of global climate models and observations to assess climate change impacts on aviation.

Predicting population survival under future climate change: density dependence, drought and extraction in an insular bighorn sheep.

PubMed

Colchero, Fernando; Medellin, Rodrigo A; Clark, James S; Lee, Raymond; Katul, Gabriel G

2009-05-01

1. Our understanding of the interplay between density dependence, climatic perturbations, and conservation practices on the dynamics of small populations is still limited. This can result in uninformed strategies that put endangered populations at risk. Moreover, the data available for a large number of populations in such circumstances are sparse and mined with missing data. Under the current climate change scenarios, it is essential to develop appropriate inferential methods that can make use of such data sets. 2. We studied a population of desert bighorn sheep introduced to Tiburon Island, Mexico in 1975 and subjected to irregular extractions for the last 10 years. The unique attributes of this population are absence of predation and disease, thereby permitting us to explore the combined effect of density dependence, environmental variability and extraction in a 'controlled setting.' Using a combination of nonlinear discrete models with long-term field data, we constructed three basic Bayesian state space models with increasing density dependence (DD), and the same three models with the addition of summer drought effects. 3. We subsequently used Monte Carlo simulations to evaluate the combined effect of drought, DD, and increasing extractions on the probability of population survival under two climate change scenarios (based on the Intergovernmental Panel on Climate Change predictions): (i) increase in drought variability; and (ii) increase in mean drought severity. 4. The population grew from 16 individuals introduced in 1975 to close to 700 by 1993. Our results show that the population's growth was dominated by DD, with drought having a secondary but still relevant effect on its dynamics. 5. Our predictions suggest that under climate change scenario (i), extraction dominates the fate of the population, while for scenario (ii), an increase in mean drought affects the population's probability of survival in an equivalent magnitude as extractions. Thus, for the long-term survival of the population, our results stress that a more variable environment is less threatening than one in which the mean conditions become harsher. Current climate change scenarios and their underlying uncertainty make studies such as this one crucial for understanding the dynamics of ungulate populations and their conservation.

Coral bleaching pathways under the control of regional temperature variability

NASA Astrophysics Data System (ADS)

Langlais, C. E.; Lenton, A.; Heron, S. F.; Evenhuis, C.; Sen Gupta, A.; Brown, J. N.; Kuchinke, M.

2017-11-01

Increasing sea surface temperatures (SSTs) are predicted to adversely impact coral populations worldwide through increasing thermal bleaching events. Future bleaching is unlikely to be spatially uniform. Therefore, understanding what determines regional differences will be critical for adaptation management. Here, using a cumulative heat stress metric, we show that characteristics of regional SST determine the future bleaching risk patterns. Incorporating observed information on SST variability, in assessing future bleaching risk, provides novel options for management strategies. As a consequence, the known biases in climate model variability and the uncertainties in regional warming rate across climate models are less detrimental than previously thought. We also show that the thresholds used to indicate reef viability can strongly influence a decision on what constitutes a potential refugia. Observing and understanding the drivers of regional variability, and the viability limits of coral reefs, is therefore critical for making meaningful projections of coral bleaching risk.

Impacts of variability in cellulosic biomass yields on energy security.

PubMed

Mullins, Kimberley A; Matthews, H Scott; Griffin, W Michael; Anex, Robert

2014-07-01

The practice of modeling biomass yields on the basis of deterministic point values aggregated over space and time obscures important risks associated with large-scale biofuel use, particularly risks related to drought-induced yield reductions that may become increasingly frequent under a changing climate. Using switchgrass as a case study, this work quantifies the variability in expected yields over time and space through switchgrass growth modeling under historical and simulated future weather. The predicted switchgrass yields across the United States range from about 12 to 19 Mg/ha, and the 80% confidence intervals range from 20 to 60% of the mean. Average yields are predicted to decrease with increased temperatures and weather variability induced by climate change. Feedstock yield variability needs to be a central part of modeling to ensure that policy makers acknowledge risks to energy supplies and develop strategies or contingency plans that mitigate those risks.

The Use of Climate Projections in the Modelling of Bud Burst

NASA Astrophysics Data System (ADS)

O'Neill, Bridget F.; Caffara, Amelia; Gleeson, Emily; Semmler, Tido; McGrath, Ray; Donnelly, Alison

2010-05-01

Recent changes in global climate, such as increasing temperature, have had notable effects on the phenology (timing of biological events) of plants. The effects are variable across habitats and between species, but increasing temperatures have been shown to advance certain key phenophases of trees, such as bud burst (beginning of leaf unfolding). This project considered climate change impacts on phenology of plants at a local scale in Ireland. The output from the ENSEMBLES climate simulations were down-scaled to Ireland and utilised by a phenological model to project changes over the next 50-100 years. This project helps to showcase the potential use of climate simulations in phenological research.

Native temperature regime influences soil response to simulated warming

Treesearch

Timothy G. Whitby; Michael D. Madritch

2013-01-01

Anthropogenic climate change is expected to increase global temperatures and potentially increase soil carbon (C) mineralization, which could lead to a positive feedback between global warming and soil respiration. However the magnitude and spatial variability of belowground responses to warming are not yet fully understood. Some of the variability may depend...

Impacts of climate change on large forest wildfire of Washington and Oregon

NASA Astrophysics Data System (ADS)

Yang, Z.; Davis, R. J.; Yost, A.; Cohen, W. B.

2014-12-01

Climate changes in the 21st century were projected to have major impact on wildfire. The state of Washington and Oregon contains a tightly coupled forest ecosystem and fire regime. The objective of this study was to examine the impact of future climate changes for large wildfire in the two states. MAXENT algorithm was used to develop a large forest wildfire suitability model using historical fire for the 1971-2000 time period and validated for 1981-2010 time period . Input variables include climate (e.g. July-August temperature) and topographic variables (e.g. elevation). The model test AUC of 0.77±0.1. Using the predicted versus expected curve and methods described by Hirzel and others (Hirzel et al. 2006), we reclassified the model into four classes; low suitability (0-0.36), moderate suitability 0.36-0.5), high suitability (0.5-0.75), and very high suitability (0.75-1.0). To examine the future climate change impact, climate scenarios (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5) from 33 different climate models were used to predict the large wildfire suitability from 1971-2100 using the NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30) dataset. Results from ensembles of all the climate scenarios showed that the area with high and very high suitability for large wildfire increased under all 4 climate scenarios from 1971 to 2100. However, under RCP 2.6, the area start to decline from 2080 while the other three scenarios keep increasing. On the extreme case of RCP 8.5, very high suitable area increases from less than 1% during 1971-2000 to 14.9% during 2070-2100. Details about temporal patterns for the study area and changes by ecoregions will be presented.

Climate and landscape drivers of tree decline in a Mediterranean ecoregion

PubMed Central

Brouwers, Niels C; Mercer, Jack; Lyons, Tom; Poot, Pieter; Veneklaas, Erik; Hardy, Giles

2013-01-01

Climate change and anthropogenic land use are increasingly affecting the resilience of natural ecosystems. In Mediterranean ecoregions, forests and woodlands have shown progressive declines in health. This study focuses on the decline of an endemic woodland tree species, Eucalyptus wandoo (wandoo), occurring in the biodiversity hotspot of southwest Western Australia. We determined the change in health of wandoo stands between 2002 and 2008 across its geographic and climatic range, and associated this change in health with non-biotic variables focusing on: (1) fragment metrics; (2) topography; (3) soil characteristics; and (4) climate. Only fragment metrics and climate variables were found to be significantly related to the observed change in health. Stands that were small with high perimeter/area ratios were found to be most sensitive to health declines. Recent increases in autumn temperatures and decreases in annual rainfall were negatively affecting health of wandoo most prominently in the low rainfall zone of its climatic range. Together, these results suggest the onset of range contraction for this ecologically important species, which is likely to be exacerbated by projected future changes in climate. Our results emphasize the importance of establishing monitoring programs to identify changes in health and decline trends early to inform management strategies, particularly in the sensitive Mediterranean ecoregions. PMID:23403899

Sensitivity of water resources in the Delaware River basin to climate variability and change

USGS Publications Warehouse

Ayers, Mark A.; Wolock, David M.; McCabe, Gregory J.; Hay, Lauren E.; Tasker, Gary D.

1993-01-01

Because of the "greenhouse effect," projected increases in atmospheric carbon dioxide levels might cause global warming, which in turn could result in changes in precipitation patterns and evapotranspiration and in increases in sea level. This report describes the greenhouse effect; discusses the problems and uncertainties associated with the detection, prediction, and effects of climatic change, and presents the results of sensitivity-analysis studies of the potential effects of climate change on water resources in the Delaware River basin. On the basis of sensitivity analyses, potentially serious shortfalls of certain water resources in the basin could result if some climatic-change scenarios become true. The results of basin streamflow-model simulations in this study demonstrate the difficulty in distinguishing effects of climatic change on streamflow and water supply from effects of natural variability in current climate. The future direction of basin changes in most water resources, furthermore, cannot be determined precisely because of uncertainty in current projections of regional temperature and precipitation. This large uncertainty indicates that, for resource planning, information defining the sensitivities of water resources to a range of climate change is most relevant. The sensitivity analyses could be useful in developing contingency plans on how to evaluate and respond to changes, should they occur.

Identifying alternate pathways for climate change to impact inland recreational fishers

USGS Publications Warehouse

Hunt, Len M.; Fenichel, Eli P.; Fulton, David C.; Mendelsohn, Robert; Smith, Jordan W.; Tunney, Tyler D.; Lynch, Abigail J.; Paukert, Craig P.; Whitney, James E.

2016-01-01

Fisheries and human dimensions literature suggests that climate change influences inland recreational fishers in North America through three major pathways. The most widely recognized pathway suggests that climate change impacts habitat and fish populations (e.g., water temperature impacting fish survival) and cascades to impact fishers. Climate change also impacts recreational fishers by influencing environmental conditions that directly affect fishers (e.g., increased temperatures in northern climates resulting in extended open water fishing seasons and increased fishing effort). The final pathway occurs from climate change mitigation and adaptation efforts (e.g., refined energy policies result in higher fuel costs, making distant trips more expensive). To address limitations of past research (e.g., assessing climate change impacts for only one pathway at a time and not accounting for climate variability, extreme weather events, or heterogeneity among fishers), we encourage researchers to refocus their efforts to understand and document climate change impacts to inland fishers.

Role of Perturbing Ocean Initial Condition in Simulated Regional Sea Level Change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, Aixue; Meehl, Gerald; Stammer, Detlef

Multiple lines of observational evidence indicate that the global climate has been getting warmer since the early 20th century. This warmer climate has led to a global mean sea level rise of about 18 cm during the 20th century, and over 6 cm for the first 15 years of the 21st century. Regionally the sea level rise is not uniform due in large part to internal climate variability. To better serve the community, the uncertainties of predicting/projecting regional sea level changes associated with internal climate variability need to be quantified. Previous research on this topic has used single-model large ensemblesmore » with perturbed atmospheric initial conditions (ICs). Here we compare uncertainties associated with perturbing ICs in just the atmosphere and just the ocean using a state-of-the-art coupled climate model. We find that by perturbing the oceanic ICs, the uncertainties in regional sea level changes increase compared to those with perturbed atmospheric ICs. In order for us to better assess the full spectrum of the impacts of such internal climate variability on regional and global sea level rise, approaches that involve perturbing both atmospheric and oceanic initial conditions are thus necessary.« less

Climate, Birth Weight, and Agricultural Livelihoods in Kenya and Mali

PubMed Central

Grace, Kathryn; Nawrotzki, Raphael J.

2018-01-01

Objectives. To examine an association between climate variability and birth weight in Mali and Kenya in relation to the local agricultural specialization. Methods. We combined health and sociodemographic data from the Demographic Health Surveys for Kenya (2008 and 2014) and Mali (2006 and 2012) with detailed data on precipitation, temperature, and vegetation. We analyzed the association between climate variability and birth weight by using multilevel regression models for the most common agricultural specializations: food cropping, cash cropping, and pastoralism. Results. There are differences in sensitivity to climate among different agricultural communities. An additional 100 millimeters of rainfall during the 12-month period before birth was associated with a 47-gram (P = .001) and 89-gram (P = .10) increase in birth weight for food croppers in Kenya and Mali, respectively. Every additional hot month in food-cropping communities in Kenya was associated with a 71-gram decrease in birth weight (P = .030), likely because of food croppers’ limited use of modern agricultural techniques. Overall, cash croppers are least sensitive to climate variability in both countries. Conclusions. Effective climate change adaptation strategies are essential for protecting and improving health outcomes and should be tailored to local households’ livelihood strategies. PMID:29072943

Role of Perturbing Ocean Initial Condition in Simulated Regional Sea Level Change

DOE PAGES

Hu, Aixue; Meehl, Gerald; Stammer, Detlef; ...

2017-06-05

Multiple lines of observational evidence indicate that the global climate has been getting warmer since the early 20th century. This warmer climate has led to a global mean sea level rise of about 18 cm during the 20th century, and over 6 cm for the first 15 years of the 21st century. Regionally the sea level rise is not uniform due in large part to internal climate variability. To better serve the community, the uncertainties of predicting/projecting regional sea level changes associated with internal climate variability need to be quantified. Previous research on this topic has used single-model large ensemblesmore » with perturbed atmospheric initial conditions (ICs). Here we compare uncertainties associated with perturbing ICs in just the atmosphere and just the ocean using a state-of-the-art coupled climate model. We find that by perturbing the oceanic ICs, the uncertainties in regional sea level changes increase compared to those with perturbed atmospheric ICs. In order for us to better assess the full spectrum of the impacts of such internal climate variability on regional and global sea level rise, approaches that involve perturbing both atmospheric and oceanic initial conditions are thus necessary.« less

Simulating effects of fire disturbance and climate change on boreal forest productivity and evapotranspiration.

PubMed

Kang, Sinkyu; Kimball, John S; Running, Steven W

2006-06-01

We used a terrestrial ecosystem process model, BIOME-BGC, to investigate historical climate change and fire disturbance effects on regional carbon and water budgets within a 357,500 km(2) portion of the Canadian boreal forest. Historical patterns of increasing atmospheric CO2, climate change, and regional fire activity were used as model drivers to evaluate the relative effects of these impacts to spatial patterns and temporal trends in forest net primary production (NPP) and evapotranspiration (ET). Historical trends of increasing atmospheric CO2 resulted in overall 13% and 5% increases in annual NPP and ET from 1994 to 1996, respectively. NPP was found to be relatively sensitive to changes in air temperature (T(a)), while ET was more sensitive to precipitation (P) change within the ranges of observed climate variability (e.g., +/-2 degrees C for T(a) and +/-20% for P). In addition, the potential effect of climate change related warming on NPP is exacerbated or offset depending on whether these changes are accompanied by respective decreases or increases in precipitation. Historical fire activity generally resulted in reductions of both NPP and ET, which consumed an average of approximately 6% of annual NPP from 1959 to 1996. Areas currently occupied by dry conifer forests were found to be subject to more frequent fire activity, which consumed approximately 8% of annual NPP. The results of this study show that the North American boreal ecosystem is sensitive to historical patterns of increasing atmospheric CO2, climate change and regional fire activity. The relative impacts of these disturbances on NPP and ET interact in complex ways and are spatially variable depending on regional land cover and climate gradients.

Impacts of Austrian Climate Variability on Honey Bee Mortality

NASA Astrophysics Data System (ADS)

Switanek, Matt; Brodschneider, Robert; Crailsheim, Karl; Truhetz, Heimo

2015-04-01

Global food production, as it is today, is not possible without pollinators such as the honey bee. It is therefore alarming that honey bee populations across the world have seen increased mortality rates in the last few decades. The challenges facing the honey bee calls into question the future of our food supply. Beside various infectious diseases, Varroa destructor is one of the main culprits leading to increased rates of honey bee mortality. Varroa destructor is a parasitic mite which strongly depends on honey bee brood for reproduction and can wipe out entire colonies. However, climate variability may also importantly influence honey bee breeding cycles and bee mortality rates. Persistent weather events affects vegetation and hence foraging possibilities for honey bees. This study first defines critical statistical relationships between key climate indicators (e.g., precipitation and temperature) and bee mortality rates across Austria, using 6 consecutive years of data. Next, these leading indicators, as they vary in space and time, are used to build a statistical model to predict bee mortality rates and the respective number of colonies affected. Using leave-one-out cross validation, the model reduces the Root Mean Square Error (RMSE) by 21% with respect to predictions made with the mean mortality rate and the number of colonies. Furthermore, a Monte Carlo test is used to establish that the model's predictions are statistically significant at the 99.9% confidence level. These results highlight the influence of climate variables on honey bee populations, although variability in climate, by itself, cannot fully explain colony losses. This study was funded by the Austrian project 'Zukunft Biene'.

Interactions between rainfall, deforestation and fires during recent years in the Brazilian Amazonia.

PubMed

Aragão, Luiz Eduardo O C; Malhi, Yadvinder; Barbier, Nicolas; Lima, Andre; Shimabukuro, Yosio; Anderson, Liana; Saatchi, Sassan

2008-05-27

Understanding the interplay between climate and land-use dynamics is a fundamental concern for assessing the vulnerability of Amazonia to climate change. In this study, we analyse satellite-derived monthly and annual time series of rainfall, fires and deforestation to explicitly quantify the seasonal patterns and relationships between these three variables, with a particular focus on the Amazonian drought of 2005. Our results demonstrate a marked seasonality with one peak per year for all variables analysed, except deforestation. For the annual cycle, we found correlations above 90% with a time lag between variables. Deforestation and fires reach the highest values three and six months, respectively, after the peak of the rainy season. The cumulative number of hot pixels was linearly related to the size of the area deforested annually from 1998 to 2004 (r2=0.84, p=0.004). During the 2005 drought, the number of hot pixels increased 43% in relation to the expected value for a similar deforested area (approx. 19000km2). We demonstrated that anthropogenic forcing, such as land-use change, is decisive in determining the seasonality and annual patterns of fire occurrence. Moreover, droughts can significantly increase the number of fires in the region even with decreased deforestation rates. We may expect that the ongoing deforestation, currently based on slash and burn procedures, and the use of fires for land management in Amazonia will intensify the impact of droughts associated with natural climate variability or human-induced climate change and, therefore, a large area of forest edge will be under increased risk of fires.

Japanese and Taiwanese pelagic longline fleet dynamics and the impacts of climate change in the southern Indian Ocean

NASA Astrophysics Data System (ADS)

Michael, P. E.; Wilcox, C.; Tuck, G. N.; Hobday, A. J.; Strutton, P. G.

2017-06-01

Climate change is projected to continue shifting the distribution of marine species, leading to changes in local assemblages and different interactions with human activities. With regard to fisheries, understanding the relationship between fishing fleets, target species catch per unit effort (CPUE), and the environment enhances our ability to anticipate fisher response and is an essential step towards proactive management. Here, we explore the potential impact of climate change in the southern Indian Ocean by modelling Japanese and Taiwanese pelagic longline fleet dynamics. We quantify the mean and variability of target species CPUE and the relative value and cost of fishing in different areas. Using linear mixed models, we identify fleet-specific effort allocation strategies most related to observed effort and predict the future distribution of effort and tuna catch under climate change for 2063-2068. The Japanese fleet's strategy targets high-value species and minimizes the variability in CPUE of the primary target species. Conversely, the Taiwanese strategy indicated flexible targeting of a broad range of species, fishing in areas of high and low variability in catch, and minimizing costs. The projected future mean and variability in CPUE across species suggest a slight increase in CPUE in currently high CPUE areas for most species. The corresponding effort projections suggest a slight increase in Japanese effort in the western and eastern study area, and Taiwanese effort increasing east of Madagascar. This approach provides a useful method for managers to explore the impacts of different fishing and fleet management strategies for the future.

Interannual Variability of Regional Hadley Circulation Intensity Over Western Pacific During Boreal Winter and Its Climatic Impact Over Asia-Australia Region

NASA Astrophysics Data System (ADS)

Huang, Ruping; Chen, Shangfeng; Chen, Wen; Hu, Peng

2018-01-01

This study investigates interannual variability of boreal winter regional Hadley circulation over western Pacific (WPHC) and its climatic impacts. A WPHC intensity index (WPHCI) is defined as the vertical shear of the divergent meridional winds. It shows that WPHCI correlates well with the El Niño-Southern Oscillation (ENSO). To investigate roles of the ENSO-unrelated part of WPHCI (WPHCIres), variables that are linearly related to the Niño-3 index have been removed. It reveals that meridional sea surface temperature gradient over the western Pacific plays an essential role in modulating the WPHCIres. The climatic impacts of WPHCIres are further investigated. Below-normal (above-normal) precipitation appears over south China (North Australia) when WPHCIres is stronger. This is due to the marked convergence (divergence) anomalies at the upper troposphere, divergence (convergence) at the lower troposphere, and the accompanied downward (upward) motion over south China (North Australia), which suppresses (enhances) precipitation there. In addition, a pronounced increase in surface air temperature (SAT) appears over south and central China when WPHCIres is stronger. A temperature diagnostic analysis suggests that the increase in SAT tendency over central China is primarily due to the warm zonal temperature advection and subsidence-induced adiabatic heating. In addition, the increase in SAT tendency over south China is primarily contributed by the warm meridional temperature advection. Further analysis shows that the correlation of WPHCIres with the East Asian winter monsoon (EAWM) is weak. Thus, this study may provide additional sources besides EAWM and ENSO to improve understanding of the Asia-Australia climate variability.

Rainfall Variability, Adaptation through Irrigation, and Sustainable Management of Water Resources in India

NASA Astrophysics Data System (ADS)

Fishman, R.

2013-12-01

Most studies of the impact of climate change on agriculture account for shifts in temperature and total seasonal (or monthly) precipitation. However, climate change is also projected to increase intra-seasonal precipitation variability in many parts of the world. To provide first estimates of the potential impact, I paired daily rainfall and rice yield data during the period 1970-2004, from across India, where about a fifth of the world's rice is produced, and yields have always been highly dependent on the erratic monsoon rainfall. Multivariate regression models revealed that the number of rainless days during the wet season has a statistically robust negative impact on rice yields that exceeds that of total seasonal rainfall. Moreover, a simulation of climate change impacts found that the negative impact of the projected increase in the number of rainless days will trump the positive impact of the projected increase in total precipitation, and reverse the net precipitation effect on rice production from positive (+3%) to negative (-10%). The results also indicate that higher irrigation coverage is correlated with reduced sensitivity to rainfall variability, suggesting the expansion of irrigation can effectively adapt agriculture to these climate change impacts. However, taking into account limitations on water resource availability in India, I calculate that under current irrigation practices, sustainable use of water can mitigate less than a tenth of the impact.

Effects of watershed management on sources and fluxes of water, carbon, and nitrogen in streams: Climate implications

EPA Science Inventory

Background/Question/Methods Due to the interactive effects of urbanization and climate variability, managing impacts on watershed hydrology and biogeochemical processing has become increasingly important, particularly due to the enhanced potential for eutrophication and hypoxia i...

Tool for obtaining projected future climate inputs for the WEPP and SWAT models

USDA-ARS?s Scientific Manuscript database

Climate change is an increasingly important issue affecting natural resources. Rising temperatures, reductions in snow cover, and variability in precipitation depths and intensities are altering the accepted normal approaches for predicting runoff, soil erosion, and chemical losses from upland areas...

Using ensemble forecasting to examine how climate change promotes worldwide invasion of the golden apple snail (Pomacea canaliculata).

PubMed

Lei, Juncheng; Chen, Lian; Li, Hong

2017-08-01

The golden apple snail, Pomacea canaliculata, is one of the world's 100 most notorious invasive alien species. Knowledge about the critical climate variables that limit the global distribution range of the snail, as well as predictions of future species distributions under climate change, is very helpful for management of snail. In this study, the climatically suitable habitats for this kind of snail under current climate conditions were modeled by biomod2 and projected to eight future climate scenarios (2 time periods [2050s, 2080s] × 2 Representative Concentration Pathways [RCPs; RCP2.6, RCP8.5] × 2 atmospheric General Circulation Models [GCMs; Canadian Centre for Climate Modelling and Analysis (CCCMA), Commonwealth Scientific and Industrial Research Organisation (CSIRO)]). The results suggest that the lowest temperature of coldest month is the critical climate variable to restrict the global distribution range of P. canaliculata. It is predicted that the climatically suitable habitats for P. canaliculata will increase by an average of 3.3% in 2050s and 3.8% in 2080s for the RCP2.6 scenario, while they increase by an average of 8.7% in 2050s and 10.3% in 2080s for the RCP8.5 scenario. In general, climate change in the future may promote the global invasion of the invasive species. Therefore, it is necessary to take proactive measures to monitor and preclude the invasion of this species.

Seasonal and interannual variability of climate and vegetation indices across the Amazon

PubMed Central

Brando, Paulo M.; Goetz, Scott J.; Baccini, Alessandro; Nepstad, Daniel C.; Beck, Pieter S. A.; Christman, Mary C.

2010-01-01

Drought exerts a strong influence on tropical forest metabolism, carbon stocks, and ultimately the flux of carbon to the atmosphere. Satellite-based studies have suggested that Amazon forests green up during droughts because of increased sunlight, whereas field studies have reported increased tree mortality during severe droughts. In an effort to reconcile these apparently conflicting findings, we conducted an analysis of climate data, field measurements, and improved satellite-based measures of forest photosynthetic activity. Wet-season precipitation and plant-available water (PAW) decreased over the Amazon Basin from 1996−2005, and photosynthetically active radiation (PAR) and air dryness (expressed as vapor pressure deficit, VPD) increased from 2002–2005. Using improved enhanced vegetation index (EVI) measurements (2000–2008), we show that gross primary productivity (expressed as EVI) declined with VPD and PAW in regions of sparse canopy cover across a wide range of environments for each year of the study. In densely forested areas, no climatic variable adequately explained the Basin-wide interannual variability of EVI. Based on a site-specific study, we show that monthly EVI was relatively insensitive to leaf area index (LAI) but correlated positively with leaf flushing and PAR measured in the field. These findings suggest that production of new leaves, even when unaccompanied by associated changes in LAI, could play an important role in Basin-wide interannual EVI variability. Because EVI variability was greatest in regions of lower PAW, we hypothesize that drought could increase EVI by synchronizing leaf flushing via its effects on leaf bud development. PMID:20679201

Future changes in peak river flows across northern Eurasia as inferred from an ensemble of regional climate projections under the IPCC RCP8.5 scenario

NASA Astrophysics Data System (ADS)

Shkolnik, Igor; Pavlova, Tatiana; Efimov, Sergey; Zhuravlev, Sergey

2018-01-01

Climate change simulation based on 30-member ensemble of Voeikov Main Geophysical Observatory RCM (resolution 25 km) for northern Eurasia is used to drive hydrological model CaMa-Flood. Using this modeling framework, we evaluate the uncertainties in the future projection of the peak river discharge and flood hazard by 2050-2059 relative to 1990-1999 under IPCC RCP8.5 scenario. Large ensemble size, along with reasonably high modeling resolution, allows one to efficiently sample natural climate variability and increase our ability to predict future changes in the hydrological extremes. It has been shown that the annual maximum river discharge can almost double by the mid-XXI century in the outlets of major Siberian rivers. In the western regions, there is a weak signal in the river discharge and flood hazard, hardly discernible above climate variability. Annual maximum flood area is projected to increase across Siberia mostly by 2-5% relative to the baseline period. A contribution of natural climate variability at different temporal scales to the uncertainty of ensemble prediction is discussed. The analysis shows that there expected considerable changes in the extreme river discharge probability at locations of the key hydropower facilities. This suggests that the extensive impact studies are required to develop recommendations for maintaining regional energy security.

Forest management under changing climate conditions: Is timing a tool for Sustainable Forest Management? Relevant questions for research development

NASA Astrophysics Data System (ADS)

D'Aprile, Fabrizio; McShane, Paul; Tapper, Nigel

2013-04-01

Change of climate conditions influence energy fluxes applicable to forest ecosystems. These affect cycles of nutrients and materials, primary productivity of the ecosystem, biodiversity, ecological functionality and, consequently, carbon equilibria of the forest ecosystem. Temporal factors influence physical, biological, ecological, and climatic processes and functions. For example, seasonality, cycles, periodicity, and trends in climate variables; tree growth, forest growth, and forest metabolic activities (i.e., photosynthesis and respiration) are commonly known to be time-related. In tropical forests, the impacts of changing climate conditions may exceed temperature and/or precipitation thresholds critical to forest tree growth or health. Historically, forest management emphasises growth rates and financial returns as affected by species and site. Until recently, the influence of climate variability on growth dynamics has not been influential in forest planning and management. Under this system, especially in climatic and forest regions where most of species are stenoecious, periodical wood harvesting may occur in any phase of growth (increasing, decreasing, peak, and trough). This scenario presents four main situations: a) harvesting occurs when the rate of growth is decreasing: future productivity is damaged; the minimum biomass capital may be altered, and CO2 storage is negatively affected; b) harvesting occurs during a trough of the rate of growth: the minimum biomass capital necessary to preserve the resilience of the forest is damaged; the damage can be temporary (decades) or permanent; CO2 storage capacity is deficient - which may be read as an indirect emission of CO2 since the balance appears negative; c) harvesting occurs when the rate of growth is increasing: the planned wood mass can be used without compromising the resilience and recovery of the forest; CO2 storage remains increasing; d) harvesting occurs during a peak period of growth: the wood mass harvested can be even higher than planned, and the rate of CO2 storage can be above the average. A real risk for SFM under changing climatic conditions is that negative effects may be amplified; critical thresholds of temperature and/or rainfall for tree growth and stress may be exceeded with impacts on growth response, resilience, and CO2 balance that are not completely known. Furthermore, temporal changes in silvicultural and harvesting operations may lead to increased carbon emissions. Under this scenario and the consequent risks to SFM forestry operations should be planned or scheduled in periods when climate variables influencing tree growth and stress are within the relative thresholds. In this way, silvicultural operations and harvesting are going to be optimised to climate variability and forest growth responses, rather than just forest timber production.

Variable effects of climate on forest growth in relation to climate extremes, disturbance, and forest dynamics.

PubMed

Itter, Malcolm S; Finley, Andrew O; D'Amato, Anthony W; Foster, Jane R; Bradford, John B

2017-06-01

Changes in the frequency, duration, and severity of climate extremes are forecast to occur under global climate change. The impacts of climate extremes on forest productivity and health remain difficult to predict due to potential interactions with disturbance events and forest dynamics-changes in forest stand composition, density, size and age structure over time. Such interactions may lead to non-linear forest growth responses to climate involving thresholds and lag effects. Understanding how forest dynamics influence growth responses to climate is particularly important given stand structure and composition can be modified through management to increase forest resistance and resilience to climate change. To inform such adaptive management, we develop a hierarchical Bayesian state space model in which climate effects on tree growth are allowed to vary over time and in relation to past climate extremes, disturbance events, and forest dynamics. The model is an important step toward integrating disturbance and forest dynamics into predictions of forest growth responses to climate extremes. We apply the model to a dendrochronology data set from forest stands of varying composition, structure, and development stage in northeastern Minnesota that have experienced extreme climate years and forest tent caterpillar defoliation events. Mean forest growth was most sensitive to water balance variables representing climatic water deficit. Forest growth responses to water deficit were partitioned into responses driven by climatic threshold exceedances and interactions with insect defoliation. Forest growth was both resistant and resilient to climate extremes with the majority of forest growth responses occurring after multiple climatic threshold exceedances across seasons and years. Interactions between climate and disturbance were observed in a subset of years with insect defoliation increasing forest growth sensitivity to water availability. Forest growth was particularly sensitive to climate extremes during periods of high stem density following major regeneration events when average inter-tree competition was high. Results suggest the resistance and resilience of forest growth to climate extremes can be increased through management steps such as thinning to reduce competition during early stages of stand development and small-group selection harvests to maintain forest structures characteristic of older, mature stands. © 2017 by the Ecological Society of America.

Variable effects of climate on forest growth in relation to climate extremes, disturbance, and forest dynamics

USGS Publications Warehouse

Itter, Malcolm S.; Finley, Andrew O.; D'Amato, Anthony W.; Foster, Jane R.; Bradford, John B.

2017-01-01

Changes in the frequency, duration, and severity of climate extremes are forecast to occur under global climate change. The impacts of climate extremes on forest productivity and health remain difficult to predict due to potential interactions with disturbance events and forest dynamics—changes in forest stand composition, density, size and age structure over time. Such interactions may lead to non-linear forest growth responses to climate involving thresholds and lag effects. Understanding how forest dynamics influence growth responses to climate is particularly important given stand structure and composition can be modified through management to increase forest resistance and resilience to climate change. To inform such adaptive management, we develop a hierarchical Bayesian state space model in which climate effects on tree growth are allowed to vary over time and in relation to past climate extremes, disturbance events, and forest dynamics. The model is an important step toward integrating disturbance and forest dynamics into predictions of forest growth responses to climate extremes. We apply the model to a dendrochronology data set from forest stands of varying composition, structure, and development stage in northeastern Minnesota that have experienced extreme climate years and forest tent caterpillar defoliation events. Mean forest growth was most sensitive to water balance variables representing climatic water deficit. Forest growth responses to water deficit were partitioned into responses driven by climatic threshold exceedances and interactions with insect defoliation. Forest growth was both resistant and resilient to climate extremes with the majority of forest growth responses occurring after multiple climatic threshold exceedances across seasons and years. Interactions between climate and disturbance were observed in a subset of years with insect defoliation increasing forest growth sensitivity to water availability. Forest growth was particularly sensitive to climate extremes during periods of high stem density following major regeneration events when average inter-tree competition was high. Results suggest the resistance and resilience of forest growth to climate extremes can be increased through management steps such as thinning to reduce competition during early stages of stand development and small-group selection harvests to maintain forest structures characteristic of older, mature stands.

Climate Change and Spatiotemporal Distributions of Vector-Borne Diseases in Nepal – A Systematic Synthesis of Literature

PubMed Central

Dhimal, Meghnath; Ahrens, Bodo; Kuch, Ulrich

2015-01-01

Background Despite its largely mountainous terrain for which this Himalayan country is a popular tourist destination, Nepal is now endemic for five major vector-borne diseases (VBDs), namely malaria, lymphatic filariasis, Japanese encephalitis, visceral leishmaniasis and dengue fever. There is increasing evidence about the impacts of climate change on VBDs especially in tropical highlands and temperate regions. Our aim is to explore whether the observed spatiotemporal distributions of VBDs in Nepal can be related to climate change. Methodology A systematic literature search was performed and summarized information on climate change and the spatiotemporal distribution of VBDs in Nepal from the published literature until December2014 following providing items for systematic review and meta-analysis (PRISMA) guidelines. Principal Findings We found 12 studies that analysed the trend of climatic data and are relevant for the study of VBDs, 38 studies that dealt with the spatial and temporal distribution of disease vectors and disease transmission. Among 38 studies, only eight studies assessed the association of VBDs with climatic variables. Our review highlights a pronounced warming in the mountains and an expansion of autochthonous cases of VBDs to non-endemic areas including mountain regions (i.e., at least 2,000 m above sea level). Furthermore, significant relationships between climatic variables and VBDs and their vectors are found in short-term studies. Conclusion Taking into account the weak health care systems and difficult geographic terrain of Nepal, increasing trade and movements of people, a lack of vector control interventions, observed relationships between climatic variables and VBDs and their vectors and the establishment of relevant disease vectors already at least 2,000 m above sea level, we conclude that climate change can intensify the risk of VBD epidemics in the mountain regions of Nepal if other non-climatic drivers of VBDs remain constant. PMID:26086887

Adaptation to Interannual and Interdecadal Climate Variability in Agricultural Production Systems of the Argentine Pampas

NASA Astrophysics Data System (ADS)

Podestá, G. P.; Bert, F.; Weber, E.; Laciana, C.; Rajagopalan, B.; Letson, D.

2007-05-01

Agricultural ecosystems play a central role in world food production and food security, and involve one of the most climate-sensitive sectors of society-agriculture. We focus on crop production in the Argentine Pampas, one of the world's major agricultural regions. Climate of the Pampas shows marked variability at both interannual and decadal time scales. We explored the scope for adaptive management in response to climate information on interannual scales. We show that different assumptions about what decision makers are trying to achieve (i.e., their objective functions) may change what actions are considered as "optimal" for a given climate context. Optimal actions also were used to estimate the economic value of forecasts of an ENSO phase. Decision constraints (e.g., crop rotations) have critical influence on value of the forecasting system. Gaps in knowledge or misconceptions about climate variability were identified in open-ended "mental model" interviews. Results were used to design educational interventions. A marked increase in precipitation since the 1970s, together with new production technologies, led to major changes in land use patterns in the Pampas. Continuous cropping has widely replaced agriculture-pasture rotations. Nevertheless, production systems that evolved partly in response to increased rainfall may not be viable if climate reverts to a drier epoch. We use historical data to define a range of plausible climate trajectories 20-30 years hence. Regional scenarios are downscaled using semi-parametric weather generators to produce multiple realizations of daily weather consistent with decadal scenarios. Finally, we use the synthetic climate, crop growth models, and realistic models of decision-making under risk to compute risk metrics (e.g., probability of yields or profits being below a threshold). Climatically optimal and marginal locations show differential responses: probabilities of negative economic results are much higher in currently marginal areas if precipitations decrease.

Demographic consequences of climate change and land cover help explain a history of extirpations and range contraction in a declining snake species.

PubMed

Pomara, Lars Y; LeDee, Olivia E; Martin, Karl J; Zuckerberg, Benjamin

2014-07-01

Developing conservation strategies for threatened species increasingly requires understanding vulnerabilities to climate change, in terms of both demographic sensitivities to climatic and other environmental factors, and exposure to variability in those factors over time and space. We conducted a range-wide, spatially explicit climate change vulnerability assessment for Eastern Massasauga (Sistrurus catenatus), a declining endemic species in a region showing strong environmental change. Using active season and winter adult survival estimates derived from 17 data sets throughout the species' range, we identified demographic sensitivities to winter drought, maximum precipitation during the summer, and the proportion of the surrounding landscape dominated by agricultural and urban land cover. Each of these factors was negatively associated with active season adult survival rates in binomial generalized linear models. We then used these relationships to back-cast adult survival with dynamic climate variables from 1950 to 2008 using spatially explicit demographic models. Demographic models for 189 population locations predicted known extant and extirpated populations well (AUC = 0.75), and models based on climate and land cover variables were superior to models incorporating either of those effects independently. These results suggest that increasing frequencies and severities of extreme events, including drought and flooding, have been important drivers of the long-term spatiotemporal variation in a demographic rate. We provide evidence that this variation reflects nonadaptive sensitivity to climatic stressors, which are contributing to long-term demographic decline and range contraction for a species of high-conservation concern. Range-wide demographic modeling facilitated an understanding of spatial shifts in climatic suitability and exposure, allowing the identification of important climate refugia for a dispersal-limited species. Climate change vulnerability assessment provides a framework for linking demographic and distributional dynamics to environmental change, and can thereby provide unique information for conservation planning and management. © 2013 John Wiley & Sons Ltd.

Country-Specific Effects of Climate Variability on Human Migration

PubMed Central

Gray, Clark; Wise, Erika

2016-01-01

Involuntary human migration is among the social outcomes of greatest concern in the current era of global climate change. Responding to this concern, a growing number of studies have investigated the consequences of short to medium-term climate variability for human migration using demographic and econometric approaches. These studies have provided important insights, but at the same time have been significantly limited by lack of expertise in the use of climate data, access to cross-national data on migration, and attention to model specification. To address these limitations, we link data on internal and international migration over a 6-year period from 9,812 origin households in Kenya, Uganda, Nigeria, Burkina Faso and Senegal to high-resolution gridded climate data from both station and satellite sources. Analyses of these data using several plausible specifications reveal that climate variability has country-specific effects on migration: Migration tends to increase with temperature anomalies in Uganda, tends to decrease with temperature anomalies in Kenya and Burkina Faso, and shows no consistent relationship with temperature in Nigeria and Senegal. Consistent with previous studies, precipitation shows weak and inconsistent relationships with migration across countries. These results challenge generalizing narratives that foresee a consistent migratory response to climate change across the globe. PMID:27092012

Ciguatera fish poisoning and climate change: analysis of National Poison Center Data in the United States, 2001-2011.

PubMed

Gingold, Daniel B; Strickland, Matthew J; Hess, Jeremy J

2014-06-01

Warm sea surface temperatures (SSTs) are positively related to incidence of ciguatera fish poisoning (CFP). Increased severe storm frequency may create more habitat for ciguatoxic organisms. Although climate change could expand the endemic range of CFP, the relationship between CFP incidence and specific environmental conditions is unknown. We estimated associations between monthly CFP incidence in the contiguous United States and SST and storm frequency in the Caribbean basin. We obtained information on 1,102 CFP-related calls to U.S. poison control centers during 2001-2011 from the National Poison Data System. We performed a time-series analysis using Poisson regression to relate monthly CFP call incidence to SST and tropical storms. We investigated associations across a range of plausible lag structures. Results showed associations between monthly CFP calls and both warmer SSTs and increased tropical storm frequency. The SST variable with the strongest association linked current monthly CFP calls to the peak August SST of the previous year. The lag period with the strongest association for storms was 18 months. If climate change increases SST in the Caribbean 2.5-3.5 °C over the coming century as projected, this model implies that CFP incidence in the United States is likely to increase 200-400%. Using CFP calls as a marker of CFP incidence, these results clarify associations between climate variability and CFP incidence and suggest that, all other things equal, climate change could increase the burden of CFP. These findings have implications for disease prediction, surveillance, and public health preparedness for climate change.

Assessing risks of climate variability and climate change for Indonesian rice agriculture.

PubMed

Naylor, Rosamond L; Battisti, David S; Vimont, Daniel J; Falcon, Walter P; Burke, Marshall B

2007-05-08

El Niño events typically lead to delayed rainfall and decreased rice planting in Indonesia's main rice-growing regions, thus prolonging the hungry season and increasing the risk of annual rice deficits. Here we use a risk assessment framework to examine the potential impact of El Niño events and natural variability on rice agriculture in 2050 under conditions of climate change, with a focus on two main rice-producing areas: Java and Bali. We select a 30-day delay in monsoon onset as a threshold beyond which significant impact on the country's rice economy is likely to occur. To project the future probability of monsoon delay and changes in the annual cycle of rainfall, we use output from the Intergovernmental Panel on Climate Change AR4 suite of climate models, forced by increasing greenhouse gases, and scale it to the regional level by using empirical downscaling models. Our results reveal a marked increase in the probability of a 30-day delay in monsoon onset in 2050, as a result of changes in the mean climate, from 9-18% today (depending on the region) to 30-40% at the upper tail of the distribution. Predictions of the annual cycle of precipitation suggest an increase in precipitation later in the crop year (April-June) of approximately 10% but a substantial decrease (up to 75% at the tail) in precipitation later in the dry season (July-September). These results indicate a need for adaptation strategies in Indonesian rice agriculture, including increased investments in water storage, drought-tolerant crops, crop diversification, and early warning systems.

Detecting the climatic effects of increasing carbon dioxide

DOE Office of Scientific and Technical Information (OSTI.GOV)

MacCracken, M C; Luther, F M

1985-12-01

This report documents what is known about detecting the CO2-induced changes in climate, and describes the uncertainties and unknowns associated with this monitoring and analysis effort. The various approaches for detecting CO2-induced climate changes are discussed first, followed by a review of applications of these strategies to the various climatic variables that are expected to be changing. Recommendations are presented for research and analysis activities. Separate abstracts have been prepared for the individual papers. (ACR)

Evaluation of terrestrial carbon cycle models with atmospheric CO2 measurements: Results from transient simulations considering increasing CO2, climate, and land-use effects

USGS Publications Warehouse

Dargaville, R.J.; Heimann, Martin; McGuire, A.D.; Prentice, I.C.; Kicklighter, D.W.; Joos, F.; Clein, Joy S.; Esser, G.; Foley, J.; Kaplan, J.; Meier, R.A.; Melillo, J.M.; Moore, B.; Ramankutty, N.; Reichenau, T.; Schloss, A.; Sitch, S.; Tian, H.; Williams, L.J.; Wittenberg, U.

2002-01-01

An atmospheric transport model and observations of atmospheric CO2 are used to evaluate the performance of four Terrestrial Carbon Models (TCMs) in simulating the seasonal dynamics and interannual variability of atmospheric CO2 between 1980 and 1991. The TCMs were forced with time varying atmospheric CO2 concentrations, climate, and land use to simulate the net exchange of carbon between the terrestrial biosphere and the atmosphere. The monthly surface CO2 fluxes from the TCMs were used to drive the Model of Atmospheric Transport and Chemistry and the simulated seasonal cycles and concentration anomalies are compared with observations from several stations in the CMDL network. The TCMs underestimate the amplitude of the seasonal cycle and tend to simulate too early an uptake of CO2 during the spring by approximately one to two months. The model fluxes show an increase in amplitude as a result of land-use change, but that pattern is not so evident in the simulated atmospheric amplitudes, and the different models suggest different causes for the amplitude increase (i.e., CO2 fertilization, climate variability or land use change). The comparison of the modeled concentration anomalies with the observed anomalies indicates that either the TCMs underestimate interannual variability in the exchange of CO2 between the terrestrial biosphere and the atmosphere, or that either the variability in the ocean fluxes or the atmospheric transport may be key factors in the atmospheric interannual variability.

A Vulnerability Assessment of Fish and Invertebrates to Climate Change on the Northeast U.S. Continental Shelf.

PubMed

Hare, Jonathan A; Morrison, Wendy E; Nelson, Mark W; Stachura, Megan M; Teeters, Eric J; Griffis, Roger B; Alexander, Michael A; Scott, James D; Alade, Larry; Bell, Richard J; Chute, Antonie S; Curti, Kiersten L; Curtis, Tobey H; Kircheis, Daniel; Kocik, John F; Lucey, Sean M; McCandless, Camilla T; Milke, Lisa M; Richardson, David E; Robillard, Eric; Walsh, Harvey J; McManus, M Conor; Marancik, Katrin E; Griswold, Carolyn A

2016-01-01

Climate change and decadal variability are impacting marine fish and invertebrate species worldwide and these impacts will continue for the foreseeable future. Quantitative approaches have been developed to examine climate impacts on productivity, abundance, and distribution of various marine fish and invertebrate species. However, it is difficult to apply these approaches to large numbers of species owing to the lack of mechanistic understanding sufficient for quantitative analyses, as well as the lack of scientific infrastructure to support these more detailed studies. Vulnerability assessments provide a framework for evaluating climate impacts over a broad range of species with existing information. These methods combine the exposure of a species to a stressor (climate change and decadal variability) and the sensitivity of species to the stressor. These two components are then combined to estimate an overall vulnerability. Quantitative data are used when available, but qualitative information and expert opinion are used when quantitative data is lacking. Here we conduct a climate vulnerability assessment on 82 fish and invertebrate species in the Northeast U.S. Shelf including exploited, forage, and protected species. We define climate vulnerability as the extent to which abundance or productivity of a species in the region could be impacted by climate change and decadal variability. We find that the overall climate vulnerability is high to very high for approximately half the species assessed; diadromous and benthic invertebrate species exhibit the greatest vulnerability. In addition, the majority of species included in the assessment have a high potential for a change in distribution in response to projected changes in climate. Negative effects of climate change are expected for approximately half of the species assessed, but some species are expected to be positively affected (e.g., increase in productivity or move into the region). These results will inform research and management activities related to understanding and adapting marine fisheries management and conservation to climate change and decadal variability.

A Vulnerability Assessment of Fish and Invertebrates to Climate Change on the Northeast U.S. Continental Shelf

PubMed Central

Hare, Jonathan A.; Morrison, Wendy E.; Nelson, Mark W.; Stachura, Megan M.; Teeters, Eric J.; Griffis, Roger B.; Alexander, Michael A.; Scott, James D.; Alade, Larry; Bell, Richard J.; Chute, Antonie S.; Curti, Kiersten L.; Curtis, Tobey H.; Kircheis, Daniel; Kocik, John F.; Lucey, Sean M.; McCandless, Camilla T.; Milke, Lisa M.; Richardson, David E.; Robillard, Eric; Walsh, Harvey J.; McManus, M. Conor; Marancik, Katrin E.; Griswold, Carolyn A.

2016-01-01

Climate change and decadal variability are impacting marine fish and invertebrate species worldwide and these impacts will continue for the foreseeable future. Quantitative approaches have been developed to examine climate impacts on productivity, abundance, and distribution of various marine fish and invertebrate species. However, it is difficult to apply these approaches to large numbers of species owing to the lack of mechanistic understanding sufficient for quantitative analyses, as well as the lack of scientific infrastructure to support these more detailed studies. Vulnerability assessments provide a framework for evaluating climate impacts over a broad range of species with existing information. These methods combine the exposure of a species to a stressor (climate change and decadal variability) and the sensitivity of species to the stressor. These two components are then combined to estimate an overall vulnerability. Quantitative data are used when available, but qualitative information and expert opinion are used when quantitative data is lacking. Here we conduct a climate vulnerability assessment on 82 fish and invertebrate species in the Northeast U.S. Shelf including exploited, forage, and protected species. We define climate vulnerability as the extent to which abundance or productivity of a species in the region could be impacted by climate change and decadal variability. We find that the overall climate vulnerability is high to very high for approximately half the species assessed; diadromous and benthic invertebrate species exhibit the greatest vulnerability. In addition, the majority of species included in the assessment have a high potential for a change in distribution in response to projected changes in climate. Negative effects of climate change are expected for approximately half of the species assessed, but some species are expected to be positively affected (e.g., increase in productivity or move into the region). These results will inform research and management activities related to understanding and adapting marine fisheries management and conservation to climate change and decadal variability. PMID:26839967

Reproductive success of a keystone herbivore is more variable and responsive to climate in habitats with lower resource diversity.

PubMed

Iles, David T; Rockwell, Robert F; Koons, David N

2018-07-01

The effects of climate on wild populations are often channelled through species interactions. Population responses to climate variation can therefore differ across habitats, owing to variation in the biotic community. Theory predicts that consumer demography should be less variable and less responsive to climate in habitats with greater resource diversity. We tested these predictions using a long-term study of breeding lesser snow geese along the western coast of Hudson Bay, Manitoba, Canada. Reproductive success was measured in 22 years from 114 locations, in either coastal or inland habitat types. We used Bayesian analysis to estimate the response of reproductive success to climate in each habitat type, along with residual variation not explained by climate. We then quantified gosling diet composition in each habitat type to test the prediction that reproductive success would be less variable and more responsive to climate in habitats with lower resource diversity. Reproductive success responded positively to seasonal warmness, but this response was much stronger in inland habitats than in coastal habitats. Site- and year-level random effects were also three to five times more variable in inland habitats. Simultaneously, land cover diversity and gosling diet diversity were lower in inland habitats. Our study illustrates that spatial variation in resource diversity (and thus, species interactions) can have important effects on consumer responses to climate. In this system, climate change is expected to disproportionately increase the reproductive success of snow geese in vast inland habitats, potentially counteracting management efforts to reduce the abundance of this keystone herbivore. © 2018 The Authors. Journal of Animal Ecology © 2018 British Ecological Society.

Quantifying streamflow change caused by forest disturbance at a large spatial scale: A single watershed study

NASA Astrophysics Data System (ADS)

Wei, Xiaohua; Zhang, Mingfang

2010-12-01

Climatic variability and forest disturbance are commonly recognized as two major drivers influencing streamflow change in large-scale forested watersheds. The greatest challenge in evaluating quantitative hydrological effects of forest disturbance is the removal of climatic effect on hydrology. In this paper, a method was designed to quantify respective contributions of large-scale forest disturbance and climatic variability on streamflow using the Willow River watershed (2860 km2) located in the central part of British Columbia, Canada. Long-term (>50 years) data on hydrology, climate, and timber harvesting history represented by equivalent clear-cutting area (ECA) were available to discern climatic and forestry influences on streamflow by three steps. First, effective precipitation, an integrated climatic index, was generated by subtracting evapotranspiration from precipitation. Second, modified double mass curves were developed by plotting accumulated annual streamflow against annual effective precipitation, which presented a much clearer picture of the cumulative effects of forest disturbance on streamflow following removal of climatic influence. The average annual streamflow changes that were attributed to forest disturbances and climatic variability were then estimated to be +58.7 and -72.4 mm, respectively. The positive (increasing) and negative (decreasing) values in streamflow change indicated opposite change directions, which suggest an offsetting effect between forest disturbance and climatic variability in the study watershed. Finally, a multivariate Autoregressive Integrated Moving Average (ARIMA) model was generated to establish quantitative relationships between accumulated annual streamflow deviation attributed to forest disturbances and annual ECA. The model was then used to project streamflow change under various timber harvesting scenarios. The methodology can be effectively applied to any large-scale single watershed where long-term data (>50 years) are available.

Climate variability in the subarctic area for the last 2 millennia

NASA Astrophysics Data System (ADS)

Nicolle, Marie; Debret, Maxime; Massei, Nicolas; Colin, Christophe; deVernal, Anne; Divine, Dmitry; Werner, Johannes P.; Hormes, Anne; Korhola, Atte; Linderholm, Hans W.

2018-01-01

To put recent climate change in perspective, it is necessary to extend the instrumental climate records with proxy data from paleoclimate archives. Arctic climate variability for the last 2 millennia has been investigated using statistical and signal analyses from three regionally averaged records from the North Atlantic, Siberia and Alaska based on many types of proxy data archived in the Arctic 2k database v1.1.1. In the North Atlantic and Alaska, the major climatic trend is characterized by long-term cooling interrupted by recent warming that started at the beginning of the 19th century. This cooling is visible in the Siberian region at two sites, warming at the others. The cooling of the Little Ice Age (LIA) was identified from the individual series, but it is characterized by wide-range spatial and temporal expression of climate variability, in contrary to the Medieval Climate Anomaly. The LIA started at the earliest by around AD 1200 and ended at the latest in the middle of the 20th century. The widespread temporal coverage of the LIA did not show regional consistency or particular spatial distribution and did not show a relationship with archive or proxy type either. A focus on the last 2 centuries shows a recent warming characterized by a well-marked warming trend parallel with increasing greenhouse gas emissions. It also shows a multidecadal variability likely due to natural processes acting on the internal climate system on a regional scale. A ˜ 16-30-year cycle is found in Alaska and seems to be linked to the Pacific Decadal Oscillation, whereas ˜ 20-30- and ˜ 50-90-year periodicities characterize the North Atlantic climate variability, likely in relation with the Atlantic Multidecadal Oscillation. These regional features are probably linked to the sea ice cover fluctuations through ice-temperature positive feedback.

Spatiotemporal variability and predictability of Normalized Difference Vegetation Index (NDVI) in Alberta, Canada.

PubMed

Jiang, Rengui; Xie, Jiancang; He, Hailong; Kuo, Chun-Chao; Zhu, Jiwei; Yang, Mingxiang

2016-09-01

As one of the most popular vegetation indices to monitor terrestrial vegetation productivity, Normalized Difference Vegetation Index (NDVI) has been widely used to study the plant growth and vegetation productivity around the world, especially the dynamic response of vegetation to climate change in terms of precipitation and temperature. Alberta is the most important agricultural and forestry province and with the best climatic observation systems in Canada. However, few studies pertaining to climate change and vegetation productivity are found. The objectives of this paper therefore were to better understand impacts of climate change on vegetation productivity in Alberta using the NDVI and provide reference for policy makers and stakeholders. We investigated the following: (1) the variations of Alberta's smoothed NDVI (sNDVI, eliminated noise compared to NDVI) and two climatic variables (precipitation and temperature) using non-parametric Mann-Kendall monotonic test and Thiel-Sen's slope; (2) the relationships between sNDVI and climatic variables, and the potential predictability of sNDVI using climatic variables as predictors based on two predicted models; and (3) the use of a linear regression model and an artificial neural network calibrated by the genetic algorithm (ANN-GA) to estimate Alberta's sNDVI using precipitation and temperature as predictors. The results showed that (1) the monthly sNDVI has increased during the past 30 years and a lengthened growing season was detected; (2) vegetation productivity in northern Alberta was mainly temperature driven and the vegetation in southern Alberta was predominantly precipitation driven for the period of 1982-2011; and (3) better performances of the sNDVI-climate relationships were obtained by nonlinear model (ANN-GA) than using linear (regression) model. Similar results detected in both monthly and summer sNDVI prediction using climatic variables as predictors revealed the applicability of two models for different period of year ecologists might focus on.

Large-scale assessment of present day and future groundwater recharge and its sensitivity to climate variability in Europe's karst regions

NASA Astrophysics Data System (ADS)

Hartmann, A. J.; Gleeson, T. P.; Wagener, T.; Wada, Y.

2016-12-01

Karst aquifers in Europe are an important source of fresh water contributing up to half of the total drinking water supply in some countries. Karstic groundwater recharge is one of the most important components of the water balance of karst systems as it feeds the karst aquifers. Presently available large-scale hydrological models do not consider karst heterogeneity adequately. Projections of current and potential future groundwater recharge of Europe's karst aquifers are therefore unclear. In this study we compare simulations of present (1991-2010) and future (2080-2099) recharge using two different models to simulate groundwater recharge processes. One model includes karst processes (subsurface heterogeneity, lateral flow and concentrated recharge), while the other is based on the conceptual understanding of common hydrological systems (homogeneous subsurface, saturation excess overland flow). Both models are driven by the bias-corrected 5 GCMs of the ISI-MIP project (RCP8.5). To further assess sensitivity of groundwater recharge to climate variability, we calculate the elasticity of recharge rates to annual precipitation, temperature and average intensity of rainfall events, which is the median change of recharge that corresponds to the median change of these climate variables within the present and future time period, respectively. Our model comparison shows that karst regions over Europe have enhanced recharge rates with greater inter-annual variability compared to those with more homogenous subsurface properties. Furthermore, the heterogeneous representation shows stronger elasticity concerning climate variability than the homogeneous subsurface representation. This difference tends to increase towards the future. Our results suggest that water management in regions with heterogeneous subsurface can expect a higher water availability than estimated by most of the current large-scale simulations, while measures should be taken to prepare for increasingly variable groundwater recharge rates.

Enhanced recharge rates and altered recharge sensitivity to climate variability through subsurface heterogeneity

NASA Astrophysics Data System (ADS)

Hartmann, Andreas; Gleeson, Tom; Wada, Yoshihide; Wagener, Thorsten

2017-04-01

Karst aquifers in Europe are an important source of fresh water contributing up to half of the total drinking water supply in some countries. Karstic groundwater recharge is one of the most important components of the water balance of karst systems as it feeds the karst aquifers. Presently available large-scale hydrological models do not consider karst heterogeneity adequately. Projections of current and potential future groundwater recharge of Europe's karst aquifers are therefore unclear. In this study we compare simulations of present (1991-2010) and future (2080-2099) recharge using two different models to simulate groundwater recharge processes. One model includes karst processes (subsurface heterogeneity, lateral flow and concentrated recharge), while the other is based on the conceptual understanding of common hydrological systems (homogeneous subsurface, saturation excess overland flow). Both models are driven by the bias-corrected 5 GCMs of the ISI-MIP project (RCP8.5). To further assess sensitivity of groundwater recharge to climate variability, we calculate the elasticity of recharge rates to annual precipitation, temperature and average intensity of rainfall events, which is the median change of recharge that corresponds to the median change of these climate variables within the present and future time period, respectively. Our model comparison shows that karst regions over Europe have enhanced recharge rates with greater inter-annual variability compared to those with more homogenous subsurface properties. Furthermore, the heterogeneous representation shows stronger elasticity concerning climate variability than the homogeneous subsurface representation. This difference tends to increase towards the future. Our results suggest that water management in regions with heterogeneous subsurface can expect a higher water availability than estimated by most of the current large-scale simulations, while measures should be taken to prepare for increasingly variable groundwater recharge rates.

Changing pattern of natural hazards due to extreme hydro-meteorological conditions (Apulia, southern Italy)

NASA Astrophysics Data System (ADS)

Polemio, Maurizio; Lonigro, Teresa

2013-04-01

Recent international researches have underlined the evidences of climate changes throughout the world. Among the consequences of climate change, there is the increase in the frequency and magnitude of natural disasters, such as droughts, windstorms, heat waves, landslides, floods and secondary floods (i.e. rapid accumulation or pounding of surface water with very low flow velocity). The Damaging Hydrogeological Events (DHEs) can be defined as the occurrence of one or more simultaneous aforementioned phenomena causing damages. They represent a serious problem, especially in DHE-prone areas with growing urbanisation. In these areas the increasing frequency of extreme hydrological events could be related to climate variations and/or urban development. The historical analysis of DHEs can support decision making and land-use planning, ultimately reducing natural risks. The paper proposes a methodology, based on both historical and time series approaches, used for describing the influence of climatic variability on the number of phenomena observed. The historical approach is finalised to collect phenomenon historical data. The historical flood and landslide data are important for the comprehension of the evolution of a study area and for the estimation of risk scenarios as a basis for civil protection purposes. Phenomenon historical data is useful for expanding the historical period of investigation in order to assess the occurrence trend of DHEs. The time series approach includes the collection and the statistical analysis of climatic and rainfall data (monthly rainfall, wet days, rainfall intensity, and temperature data together with the annual maximum of short-duration rainfall data, from 1 hour to 5 days), which are also used as a proxy for floods and landslides. The climatic and rainfall data are useful to characterise the climate variations and trends and to roughly assess the effects of these trends on river discharge and on the triggering of landslides. The time series approach is completed by tools to analyse simultaneously all data types. The methodology was tested considering a selected Italian region (Apulia, southern Italy). The data were collected in two databases: a damaging hydrogeological event database (1186 landslides and floods since 1918) and a climate database (from 1877; short-duration rainfall from 1921). A statistically significant decreasing trend of rainfall intensity and an increasing trend of temperature, landslides, and DHEs were observed. A generalised decreasing trend of short-duration rainfall was observed. If there is not an evident relationship between climate variability and the variability of DHE occurrences, the role of anthropogenic modifications (increasing use or misuse of flood- and landslide-prone areas) could be hypothesized to justify the increasing occurrences of floods and landslides.. This study identifies the advantages of a simplifying approach to reduce the intrinsic complexities of the spatial-temporal analysis of climate variability, permitting the simultaneous analysis of the modification of flood and landslide occurrences.

Do GCM's Predict the Climate.... Or the Low Frequency Weather?

NASA Astrophysics Data System (ADS)

Lovejoy, S.; Varon, D.; Schertzer, D. J.

2011-12-01

Over twenty-five years ago, a three-regime scaling model was proposed describing the statistical variability of the atmosphere over time scales ranging from weather scales out to ≈ 100 kyrs. Using modern in situ data reanalyses, monthly surface series (at 5ox5o), 8 "multiproxy" (yearly) series of the Northern hemisphere from 1500- 1980, and GRIP and Vostok paleotemperatures at 5.2 and ≈ 100 year resolutions (over the past 91-420 kyrs), we refine the model and show how it can be understood with the help of new developments in nonlinear dynamics, especially multifractals and cascades. In a scaling range, mean fluctuations in state variables such as temperature ΔT ≈ ΔtH the where Δt is the duration. At small (weather) scales the fluctuation exponents are generally H>0; they grow with scale. At longer scales Δt >τw (≈ 10 days) they change sign, the fluctuations decrease with scale; this is the low variability, "low frequency weather" regime the spectrum is a relatively flat "plateau", it's variability is that of the usual idea of "long term weather statistics". Finally for longer times, Δt>τc ≈ 10 - 100 years, again H>0, the variability again increases with scale. This is the true climate regime. These scaling regimes allow us to objectively define the weather as fluctuations over periods <τw, "climate states", as fluctuations at scale τc and "climate change" as the fluctuations at longer periods >τc). We show that the intermediate regime is the result of the weather regime undergoing a "dimensional transition": at temporal scales longer than the typical lifetime of planetary structures (τw), the spatial degrees of freedom are rapidly quenched, only the temporal degrees of freedom are important. This low frequency weather regime has statistical properties well reproduced not only by weather cascade models, but also by control runs (i.e. without climate forcing) of GCM's (including IPSL and ECHAM GCM's). In order for GCM's to go beyond simply predicting this low frequency weather so as to predict the climate, they need appropriate climate forcings and/ or new internal mechanisms of variability. We examine this using wavelet analyses of forced and unforced GCM outputs, including the ECHO-G simulation used in the Millenium project. For example, we find that climate scenarios with large CO2 increases do give rise to a climate regime but that Hc>1 i.e. much larger than that of natural variability which for temperatures has Hc≈0.4. In comparison, the (largely volcanic) forcing of the ECHO-G Millenium simulation is fairly realistic (Hc≈0.4), although it is not clear that this mechanism can explain the even lower frequency variability found in the paleotemperature series, nor is it clear that this is compatible with low frequency solar or orbital forcings.

Downscaling future climate projections to the watershed scale: A north San Francisco Bay estuary case study

USGS Publications Warehouse

Micheli, Elisabeth; Flint, Lorraine; Flint, Alan; Weiss, Stuart; Kennedy, Morgan

2012-01-01

We modeled the hydrology of basins draining into the northern portion of the San Francisco Bay Estuary (North San Pablo Bay) using a regional water balance model (Basin Characterization Model; BCM) to estimate potential effects of climate change at the watershed scale. The BCM calculates water balance components, including runoff, recharge, evapotranspiration, soil moisture, and stream flow, based on climate, topography, soils and underlying geology, and the solar-driven energy balance. We downscaled historical and projected precipitation and air temperature values derived from weather stations and global General Circulation Models (GCMs) to a spatial scale of 270 m. We then used the BCM to estimate hydrologic response to climate change for four scenarios spanning this century (2000–2100). Historical climate patterns show that Marin’s coastal regions are typically on the order of 2 °C cooler and receive five percent more precipitation compared to the inland valleys of Sonoma and Napa because of marine influences and local topography. By the last 30 years of this century, North Bay scenarios project average minimum temperatures to increase by 1.0 °C to 3.1 °C and average maximum temperatures to increase by 2.1 °C to 3.4 °C (in comparison to conditions experienced over the last 30 years, 1981–2010). Precipitation projections for the 21st century vary between GCMs (ranging from 2 to 15% wetter than the 20th-century average). Temperature forcing increases the variability of modeled runoff, recharge, and stream discharge, and shifts hydrologic cycle timing. For both high- and low-rainfall scenarios, by the close of this century warming is projected to amplify late-season climatic water deficit (a measure of drought stress on soils) by 8% to 21%. Hydrologic variability within a single river basin demonstrated at the scale of subwatersheds may prove an important consideration for water managers in the face of climate change. Our results suggest that in arid environments characterized by high topo-climatic variability, land and water managers need indicators of local watershed hydrology response to complement regional temperature and precipitation estimates. Our results also suggest that temperature forcing may generate greater drought stress affecting soils and stream flows than can be estimated by variability in precipitation alone.

Climate trends and projections for the Andean Altiplano and strategies for adaptation

NASA Astrophysics Data System (ADS)

Valdivia, C.; Thibeault, J.; Gilles, J. L.; García, M.; Seth, A.

2013-04-01

Climate variability and change impact production in rainfed agricultural systems of the Bolivian highlands. Maximum temperature trends are increasing for the Altiplano. Minimum temperature increases are significant in the northern region, and decreases are significant in the southern region. Producers' perceptions of climate hazards are high in the central region, while concerns with changing climate and unemployment are high in the north. Similar high-risk perceptions involve pests and diseases in both regions. Altiplano climate projections for end-of-century highlights include increases in temperature, extreme event frequency, change in the timing of rainfall, and reduction of soil humidity. Successful adaptation to these changes will require the development of links between the knowledge systems of producers and scientists. Two-way participatory approaches to develop capacity and information that involve decision makers and scientists are appropriate approaches in this context of increased risk, uncertainty and vulnerability.

Mind the wind: microclimate effects on incubation effort of an arctic seabird.

PubMed

Høyvik Hilde, Christoffer; Pélabon, Christophe; Guéry, Loreleï; Gabrielsen, Geir Wing; Descamps, Sébastien

2016-04-01

The energetic costs of reproduction in birds strongly depend on the climate experienced during incubation. Climate change and increasing frequency of extreme weather events may severely affect these costs, especially for species incubating in extreme environments. In this 3-year study, we used an experimental approach to investigate the effects of microclimate and nest shelter on the incubation effort of female common eiders (Somateria mollissima) in a wild Arctic population. We added artificial shelters to a random selection of nesting females, and compared incubation effort, measured as body mass loss during incubation, between females with and without shelter. Nonsheltered females had a higher incubation effort than females with artificial shelters. In nonsheltered females, higher wind speeds increased the incubation effort, while artificially sheltered females experienced no effect of wind. Although increasing ambient temperatures tended to decrease incubation effort, this effect was negligible in the absence of wind. Humidity had no marked effect on incubation effort. This study clearly displays the direct effect of a climatic variable on an important aspect of avian life-history. By showing that increasing wind speed counteracts the energetic benefits of a rising ambient temperature, we were able to demonstrate that a climatic variable other than temperature may also affect wild populations and need to be taken into account when predicting the effects of climate change.

Climate-driven changes in forest succession and the influence of management on forest carbon dynamics in the Puget Lowlands of Washington State, USA

Treesearch

Danelle M. Laflower; Matthew D. Hurteau; George W. Koch; Malcolm P. North; Bruce A. Hungate

2016-01-01

Projecting the response of forests to changing climate requires understanding how biotic and abiotic controls on tree growth will change over time. As temperature and interannual precipitation variability increase, the overall forest response is likely to be influenced by species-specific responses to changing climate. Management actions that alter composition...