Hydroclimate variability: comparing dendroclimatic records and future GCM scenarios

International Nuclear Information System (INIS)

Lapp, S.

2008-01-01

Drought events of the 20th Century in western North America have been linked to teleconnections that influence climate variability on inter-annual and decadal to multi-decadal time scales. These teleconnections represent the changes sea surface temperatures (SSTs) in the tropical and extra-tropical regions of the Pacific Ocean, ENSO (El-Nino Southern Oscillation) and PDO (Pacific Decadal Oscillation), respectively, and the Atlantic Ocean, AMO (Atlantic Multidecadal Oscillation), and also to atmospheric circulation patterns (PNA: Pacific-North American). A network of precipitation sensitive tree-ring chronologies from Montana, Alberta, Saskatchewan and NWT highly correlate to the climate moisture index (CMI) of precipitation potential evapotranspiration (P-PET), thus, capturing the long-term hydroclimatic variability of the region. Reconstructions of annual and seasonal CMI identify drought events in previous centuries that are more extreme in magnitude, frequency and duration than recorded during the instrumental period. Variability in the future climate will include these natural climate cycles as well as modulations of these cycles affected by human induced global warming. The proxy hydroclimate records derived from tree-rings present information on decadal and multi-decadal hydroclimatic variability for the past millennium; therefore, providing a unique opportunity to validate the climate variability simulated by GCMs (Global Climate Models) on longer time scales otherwise constrained by the shorter observation records. Developing scenarios of future variability depends: 1) on our understanding of the interaction of these teleconnection; and, 2) to identify climate models that are able to accurately simulate the hydroclimatic variability as detected in the instrumental and proxy records. (author)

Responses of runoff to historical and future climate variability over China

Science.gov (United States)

Wu, Chuanhao; Hu, Bill X.; Huang, Guoru; Wang, Peng; Xu, Kai

2018-03-01

China has suffered some of the effects of global warming, and one of the potential implications of climate warming is the alteration of the temporal-spatial patterns of water resources. Based on the long-term (1960-2008) water budget data and climate projections from 28 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5), this study investigated the responses of runoff (R) to historical and future climate variability in China at both grid and catchment scales using the Budyko-based elasticity method. Results show that there is a large spatial variation in precipitation (P) elasticity (from 1.1 to 3.2) and potential evaporation (PET) elasticity (from -2.2 to -0.1) across China. The P elasticity is larger in north-eastern and western China than in southern China, while the opposite occurs for PET elasticity. The catchment properties' elasticity of R appears to have a strong non-linear relationship with the mean annual aridity index and tends to be more significant in more arid regions. For the period 1960-2008, the climate contribution to R ranges from -2.4 to 3.6 % yr-1 across China, with the negative contribution in north-eastern China and the positive contribution in western China and some parts of the south-west. The results of climate projections indicate that although there is large uncertainty involved in the 28 GCMs, most project a consistent change in P (or PET) in China at the annual scale. For the period 2071-2100, the mean annual P is projected to increase in most parts of China, especially the western regions, while the mean annual PET is projected to increase in all of China, particularly the southern regions. Furthermore, greater increases are projected for higher emission scenarios. Overall, due to climate change, the arid regions and humid regions of China are projected to become wetter and drier in the period 2071-2100, respectively (relative to the baseline 1971-2000).

The climate: variabilities and future evolution. Press breakfast 8 november 2000

International Nuclear Information System (INIS)

Ciais, Ph.; Jouzel, J.; Le Treut, H.

2000-11-01

In the framework of CEA Press conference for the public information, this paper presents the CEA/CNRS laboratories working in the climatology domain. The main researches themes are the climate sciences, the biogeochemical cycles, the geo-markers and the climate simulation. For the simulation of the greenhouse gases effect on the climate, it is necessary to better know the past climate. One of the method is the analysis of ice samples. A presentation of the studies on the future climate simulation is proposed with information on the global climate warming and the consequences. (A.L.B.)

Assessment of climate change impacts on climate variables using probabilistic ensemble modeling and trend analysis

Science.gov (United States)

Safavi, Hamid R.; Sajjadi, Sayed Mahdi; Raghibi, Vahid

2017-10-01

Water resources in snow-dependent regions have undergone significant changes due to climate change. Snow measurements in these regions have revealed alarming declines in snowfall over the past few years. The Zayandeh-Rud River in central Iran chiefly depends on winter falls as snow for supplying water from wet regions in high Zagrous Mountains to the downstream, (semi-)arid, low-lying lands. In this study, the historical records (baseline: 1971-2000) of climate variables (temperature and precipitation) in the wet region were chosen to construct a probabilistic ensemble model using 15 GCMs in order to forecast future trends and changes while the Long Ashton Research Station Weather Generator (LARS-WG) was utilized to project climate variables under two A2 and B1 scenarios to a future period (2015-2044). Since future snow water equivalent (SWE) forecasts by GCMs were not available for the study area, an artificial neural network (ANN) was implemented to build a relationship between climate variables and snow water equivalent for the baseline period to estimate future snowfall amounts. As a last step, homogeneity and trend tests were performed to evaluate the robustness of the data series and changes were examined to detect past and future variations. Results indicate different characteristics of the climate variables at upstream stations. A shift is observed in the type of precipitation from snow to rain as well as in its quantities across the subregions. The key role in these shifts and the subsequent side effects such as water losses is played by temperature.

Effects of climate variability and climate change on crop production in southern Mali

NARCIS (Netherlands)

Traore, B.; Corbeels, M.; Wijk, van M.T.; Rufino, M.C.; Giller, K.E.

2013-01-01

In West Africa predictions of future changes in climate and especially rainfall are highly uncertain, and up to now no long-term analyses are available of the effects of climate on crop production. This study analyses long-term trends in climate variability at N'Tarla and Sikasso in southern Mali

Projected climate change futures for Southern Africa

CSIR Research Space (South Africa)

Tadross, M

2017-10-01

Full Text Available of the Council for Scientific and Industrial Research (CSIR) in South Africa. In these experiments, a variable-resolution atmospheric global circulation model, CCAM, was applied as a regional climate model (RCM) to simulate both present-day and future climate... climate projection Observed climate RCM Climate forcing Climate simulation Statistical downscaling Dynamical downscaling 22 | Second Edition There are four pathways – RCP2.6, RCP4.5, RCP6.0 and RCP8.5. RCP 2.6 describes a scenario of very low...

Human Responses to Climate Variability: The Case of South Africa

Science.gov (United States)

Oppenheimer, M.; Licker, R.; Mastrorillo, M.; Bohra-Mishra, P.; Estes, L. D.; Cai, R.

2014-12-01

Climate variability has been associated with a range of societal and individual outcomes including migration, violent conflict, changes in labor productivity, and health impacts. Some of these may be direct responses to changes in mean temperature or precipitation or extreme events, such as displacement of human populations by tropical cyclones. Others may be mediated by a variety of biological, social, or ecological factors such as migration in response to long-term changes in crops yields. Research is beginning to elucidate and distinguish the many channels through which climate variability may influence human behavior (ranging from the individual to the collective, societal level) in order to better understand how to improve resilience in the face of current variability as well as future climate change. Using a variety of data sets from South Africa, we show how climate variability has influenced internal (within country) migration in recent history. We focus on South Africa as it is a country with high levels of internal migration and dramatic temperature and precipitation changes projected for the 21st century. High poverty rates and significant levels of rain-fed, smallholder agriculture leave large portions of South Africa's population base vulnerable to future climate change. In this study, we utilize two complementary statistical models - one micro-level model, driven by individual and household level survey data, and one macro-level model, driven by national census statistics. In both models, we consider the effect of climate on migration both directly (with gridded climate reanalysis data) and indirectly (with agricultural production statistics). With our historical analyses of climate variability, we gain insights into how the migration decisions of South Africans may be influenced by future climate change. We also offer perspective on the utility of micro and macro level approaches in the study of climate change and human migration.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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...

Catchments' hedging strategy on evapotranspiration for climatic variability

Science.gov (United States)

Ding, W.; Zhang, C.; Li, Y.; Tang, Y.; Wang, D.; Xu, B.

2017-12-01

Hydrologic responses to climate variability and change are important for human society. Here we test the hypothesis that natural catchments utilize hedging strategies for evapotranspiration and water storage carryover with uncertain future precipitation. The hedging strategy for evapotranspiration in catchments under different levels of water availability is analytically derived from the economic perspective. It is found that there exists hedging between evapotranspiration for current and future only with a portion of water availability. Observation data sets of 160 catchments in the United States covering the period from 1983 to 2003 demonstrate the existence of hedging in catchment hydrology and validate the proposed hedging strategies. We also find that more water is allocated to carryover storage for hedging against the future evapotranspiration risk in the catchments with larger aridity indexes or with larger uncertainty in future precipitation, i.e., long-term climate and precipitation variability control the degree of hedging.

Response of switchgrass yield to future climate change

International Nuclear Information System (INIS)

Tulbure, Mirela G; Wimberly, Michael C; Owens, Vance N

2012-01-01

A climate envelope approach was used to model the response of switchgrass, a model bioenergy species in the United States, to future climate change. The model was built using general additive models (GAMs), and switchgrass yields collected at 45 field trial locations as the response variable. The model incorporated variables previously shown to be the main determinants of switchgrass yield, and utilized current and predicted 1 km climate data from WorldClim. The models were run with current WorldClim data and compared with results of predicted yield obtained using two climate change scenarios across three global change models for three time steps. Results did not predict an increase in maximum switchgrass yield but showed an overall shift in areas of high switchgrass productivity for both cytotypes. For upland cytotypes, the shift in high yields was concentrated in northern and north-eastern areas where there were increases in average growing season temperature, whereas for lowland cultivars the areas where yields were projected to increase were associated with increases in average early growing season precipitation. These results highlight the fact that the influences of climate change on switchgrass yield are spatially heterogeneous and vary depending on cytotype. Knowledge of spatial distribution of suitable areas for switchgrass production under climate change should be incorporated into planning of current and future biofuel production. Understanding how switchgrass yields will be affected by future changes in climate is important for achieving a sustainable biofuels economy. (letter)

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

Science.gov (United States)

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

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

Science.gov (United States)

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).

Response of the mean global vegetation distribution to interannual climate variability

Energy Technology Data Exchange (ETDEWEB)

Notaro, Michael [University of Wisconsin-Madison, Center for Climatic Research, Madison, WI (United States)

2008-06-15

The impact of interannual variability in temperature and precipitation on global terrestrial ecosystems is investigated using a dynamic global vegetation model driven by gridded climate observations for the twentieth century. Contrasting simulations are driven either by repeated mean climatology or raw climate data with interannual variability included. Interannual climate variability reduces net global vegetation cover, particularly over semi-arid regions, and favors the expansion of grass cover at the expense of tree cover, due to differences in growth rates, fire impacts, and interception. The area burnt by global fires is substantially enhanced by interannual precipitation variability. The current position of the central United States' ecotone, with forests to the east and grasslands to the west, is largely attributed to climate variability. Among woody vegetation, climate variability supports expanded deciduous forest growth and diminished evergreen forest growth, due to difference in bioclimatic limits, leaf longevity, interception rates, and rooting depth. These results offer insight into future ecosystem distributions since climate models generally predict an increase in climate variability and extremes. (orig.)

Coral Reef Habitat Suitability in Future Climate Scenarios from NCAR CESM1 considering a Suite of Biogeochemical Variables

Science.gov (United States)

Freeman, L. A.; Kleypas, J. A.; Miller, A. J.

2013-12-01

A maximum entropy species distribution model (Maxent) is used to describe coral reef habitat in current climate conditions and to predict changes to that habitat during the 21st century. Two climate change scenarios (RCP4.5 and RCP8.5) from the National Center for Atmospheric Research's Community Earth System Model version 1 (CESM1) were used with Maxent to determine environmental suitability for the family of corals Scleractina in 1° by 1° cells. Input environmental variables most suitable for representing coral habitat limitation are isolated using a principal component analysis and include cumulative thermal stress, salinity, light availability, current speed, phosphate levels and aragonite saturation state. Considering a suite of environmental variables allows for a more synergistic view of future habitat suitability, although individual variables are found to be limiting in certain areas- for example, aragonite saturation state is limiting at higher latitudes. Climate-driven coral reef habitat changes depend strongly on the oceanic region of interest and the region of corals used to train the niche model. Increased global coral habitat loss occurred in both RCP4.5 and RCP8.5 climate projections as time progressed through the 21th century. Maximum suitable habitat loss was 82% by 2100 for RCP8.5. When only Caribbean/Atlantic coral reef environmental data is applied globally, 88% of global habitat was lost by 2100 for RCP8.5. The global runs utilizing only Pacific Ocean reefs' ability to survive showed the most significant worldwide loss, 90% by 2100 for RCP8.5. When Maxent was trained with Indian Ocean reefs, an increase in suitable habitat worldwide was estimated. Habitat suitability was found to increase by 38% in RCP4.5 by 2100 and 28% in RCP8.5 by 2050. This suggests that shallow tropical sites in the Indian Ocean basin experience conditions today that are most similar to future worldwide climate projections. Indian Ocean reefs may be ideal candidate

Taking the pulse of mountains: Ecosystem responses to climatic variability

Science.gov (United States)

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

Human activity and climate variability project: annual report 2001

International Nuclear Information System (INIS)

Harle, K.J.; Heijnis, H.; Henderson-Sellers, A.; Sharmeen, S.; Zahorowski, W.

2002-01-01

Knowledge of the state of the Australian environment, including natural climate variability, prior to colonial settlement is vital if we are to define and understand the impact of over two hundred years of post-industrial human activity on our landscape. ANSTO, in conjunction with university partners, is leading a major research effort to provide natural archives of human activity and climate variability over the last 500 years in Australia, utilising a variety of techniques, including lead-210 and radiocarbon dating and analyses of proxy indicators (such as microfossils) as well as direct evidence (such as trace elements) of human activity and climate variability. The other major project objectives were to contribute to the understanding of the impact of human induced and natural aerosols in the East Asian region on climate through analysis and sourcing of fine particles and characterisation of air samples using radon concentrations and to contribute to the improvement of land surface parameterisation schemes and investigate the potential to use stable isotopes to improve global climate models and thus improve our understanding of future climate

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

Science.gov (United States)

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.

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

Science.gov (United States)

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 and sedimentation of a hydropower reservoir

International Nuclear Information System (INIS)

Riedel, M.

2008-01-01

As part of the relicensing of a large Hydroelectric Project in the central Appalachians, large scale watershed and reservoir sedimentation models were developed to forecast potential sedimentation scenarios. The GIS based watershed model was spatially explicit and calibrated to long term observed data. Potential socio/economic development scenarios were used to construct future watershed land cover scenarios. Climatic variability and potential change analysis were used to identify future climate regimes and shifts in precipitation and temperature patterns. Permutations of these development and climate changes were forecasted over 50 years and used to develop sediment yield regimes to the project reservoir. Extensive field work and reservoir survey, including current and wave instrumentation, were used to characterize the project watershed, rivers and reservoir hydrodynamics. A fully 3 dimensional hydrodynamic reservoir sedimentation model was developed for the project and calibrated to observed data. Hydrologic and sedimentation results from watershed forecasting provided boundary conditions for reservoir inputs. The calibrated reservoir model was then used to forecast changes in reservoir sedimentation and storage capacity under different future climate scenarios. Results indicated unique zones of advancing sediment deltas and temporary storage areas. Forecasted changes in reservoir bathymetry and sedimentation patterns were also developed for the various climate change scenarios. The warmer and wetter scenario produced sedimentation impacts similar to extensive development under no climate change. The results of these analyses are being used to develop collaborative watershed and soil conservation partnerships to reduce future soil losses and reservoir sedimentation from projected development. (author)

Climate of the future: the testimony of the past

International Nuclear Information System (INIS)

Jouzel, J.; Lorius, C.; Raynaud, D.

1994-01-01

Human activities are substantially increasing the atmospheric concentrations of greenhouse gases. Such increase may induce a significant warming over the next decades. Beyond complex predictive climate models, the archives of past climate contain information relevant to this future of our climate. It concerns, in particular, the link between climate and greenhouse gases in the past and the natural variability of the Earth's climate. Both are recorded in polar ice which thus provides records essential for better understanding of the behaviour of the climate system. This is examined from results recently obtained along deep ice cores from Greenland and Antarctica. (authors). 21 refs., 5 figs

Evaluation of the applicability in the future climate of a statistical downscaling method in France

Science.gov (United States)

Dayon, G.; Boé, J.; Martin, E.

2013-12-01

The uncertainties in climate projections during the next decades generally remain large, with an important contribution of internal climate variability. To quantify and capture the impact of those uncertainties in impact projections, multi-model and multi-member approaches are essential. Statistical downscaling (SD) methods are computationally inexpensive allowing for large ensemble approaches. The main weakness of SD is that it relies on a stationarity hypothesis, namely that the statistical relation established in the present climate remains valid in the climate change context. In this study, the evaluation of SD methods developed for a future study of hydrological changes during the next decades over France is presented, focusing on precipitation. The SD methods are all based on the analogs method which is quite simple to set up and permits to easily test different combinations of predictors, the only changing parameter in the methods discussed in this presentation. The basic idea of the analogs method is that for a same large scale climatic state, the state of local variables will be identical. In a climate change context, the statistical relation established on past climate is assumed to remain valid in the future climate. In practice, this stationarity assumption is impossible to verify until the future climate is effectively observed. It is possible to evaluate the ability of SD methods to reproduce the interannual variability in the present climate, but this approach does not guarantee their validity in the future climate as the mechanisms that play in the interannual and climate change contexts may not be identical. Another common approach is to test whether a SD method is able to reproduce observed, as they may be partly caused by climate changes. The observed trends in precipitation are compared to those obtained by downscaling 4 different atmospheric reanalyses with analogs methods. The uncertainties in downscaled trends due to renalyses are very large

Future climate warming increases Greenland ice sheet surface mass balance variability

NARCIS (Netherlands)

Fyke, J.G.; Vizcaino, M.; Lipscomb, W.; Price, S.

2014-01-01

The integrated surface mass balance (SMB) of the Greenland ice sheet (GrIS) has large interannual variability. Long-term future changes to this variability will affect GrIS dynamics, freshwater fluxes, regional oceanography, and detection of changes in ice volume trends. Here we analyze a simulated

Impacts of Present and Future Climate Variability On Agriculture and Forestry in the Humid and Sub-Humid Tropics

International Nuclear Information System (INIS)

Zhao, Y.; Wang, C.; Wang, S.; Tibig, Lourdes V.

2005-01-01

Although there are different results from different studies, most assessments indicate that climate variability would have negative effects on agriculture and forestry in the humid and sub-humid tropics. Cereal crop yields would decrease generally with even minimal increases in temperature. For commercial crops, extreme events such as cyclones, droughts and floods lead to larger damages than only changes of mean climate. Impacts of climate variability on livestock mainly include two aspects; impacts on animals such as increase of heat and disease stress-related death, and impacts on pasture. As to forestry, climate variability would have negative as well as some positive impacts on forests of humid and sub-humid tropics. However, in most tropical regions, the impacts of human activities such as deforestation will be more important than climate variability and climate change in determining natural forest cover

Multi-scale climate modelling over Southern Africa using a variable-resolution global model

CSIR Research Space (South Africa)

Engelbrecht, FA

2011-12-01

Full Text Available -mail: fengelbrecht@csir.co.za Multi-scale climate modelling over Southern Africa using a variable-resolution global model FA Engelbrecht1, 2*, WA Landman1, 3, CJ Engelbrecht4, S Landman5, MM Bopape1, B Roux6, JL McGregor7 and M Thatcher7 1 CSIR Natural... improvement. Keywords: multi-scale climate modelling, variable-resolution atmospheric model Introduction Dynamic climate models have become the primary tools for the projection of future climate change, at both the global and regional scales. Dynamic...

Impacts of climate change on the future of biodiversity.

Science.gov (United States)

Bellard, Céline; Bertelsmeier, Cleo; Leadley, Paul; Thuiller, Wilfried; Courchamp, Franck

2012-04-01

Many studies in recent years have investigated the effects of climate change on the future of biodiversity. In this review, we first examine the different possible effects of climate change that can operate at individual, population, species, community, ecosystem and biome scales, notably showing that species can respond to climate change challenges by shifting their climatic niche along three non-exclusive axes: time (e.g. phenology), space (e.g. range) and self (e.g. physiology). Then, we present the principal specificities and caveats of the most common approaches used to estimate future biodiversity at global and sub-continental scales and we synthesise their results. Finally, we highlight several challenges for future research both in theoretical and applied realms. Overall, our review shows that current estimates are very variable, depending on the method, taxonomic group, biodiversity loss metrics, spatial scales and time periods considered. Yet, the majority of models indicate alarming consequences for biodiversity, with the worst-case scenarios leading to extinction rates that would qualify as the sixth mass extinction in the history of the earth. © 2012 Blackwell Publishing Ltd/CNRS.

Impacts of climate change and variability on European agriculture

DEFF Research Database (Denmark)

Orlandini, Simone; Nejedlik, Pavol; Eitzinger, Josef

2008-01-01

susceptible to meteorological hazards. These hazards can modify environment-genotype interactions, which can affect the quality of production. The COST 734 Action (Impacts of Climate Change and Variability on European Agriculture), launched in 2006, is composed of 28 signature countries and is funded...... by the European Commission. The main objective of the Action is the evaluation of possible impacts arising from climate change and variability on agriculture and the assessment of critical thresholds for various European areas. The Action will concentrate on four different tasks: agroclimatic indices...... and simulation models, including review and assessment of tools used to relate climate and agricultural processes; evaluation of the current trends of agroclimatic indices and model outputs, including remote sensing; developing and assessing future regional and local scenarios of agroclimatic conditions...

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

Science.gov (United States)

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...

The essential interactions between understanding climate variability and climate change

Science.gov (United States)

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.

Projecting future precipitation and temperature at sites with diverse climate through multiple statistical downscaling schemes

Science.gov (United States)

Vallam, P.; Qin, X. S.

2017-10-01

Anthropogenic-driven climate change would affect the global ecosystem and is becoming a world-wide concern. Numerous studies have been undertaken to determine the future trends of meteorological variables at different scales. Despite these studies, there remains significant uncertainty in the prediction of future climates. To examine the uncertainty arising from using different schemes to downscale the meteorological variables for the future horizons, projections from different statistical downscaling schemes were examined. These schemes included statistical downscaling method (SDSM), change factor incorporated with LARS-WG, and bias corrected disaggregation (BCD) method. Global circulation models (GCMs) based on CMIP3 (HadCM3) and CMIP5 (CanESM2) were utilized to perturb the changes in the future climate. Five study sites (i.e., Alice Springs, Edmonton, Frankfurt, Miami, and Singapore) with diverse climatic conditions were chosen for examining the spatial variability of applying various statistical downscaling schemes. The study results indicated that the regions experiencing heavy precipitation intensities were most likely to demonstrate the divergence between the predictions from various statistical downscaling methods. Also, the variance computed in projecting the weather extremes indicated the uncertainty derived from selection of downscaling tools and climate models. This study could help gain an improved understanding about the features of different downscaling approaches and the overall downscaling uncertainty.

How will climate novelty influence ecological forecasts? Using the Quaternary to assess future reliability.

Science.gov (United States)

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

2018-03-23

Future climates are projected to be highly novel relative to recent climates. Climate novelty challenges models that correlate ecological patterns to climate variables and then use these relationships to forecast ecological responses to future climate change. Here, we quantify the magnitude and ecological significance of future climate novelty by comparing it to novel climates over the past 21,000 years in North America. We then use relationships between model performance and climate novelty derived from the fossil pollen record from eastern North America to estimate the expected decrease in predictive skill of ecological forecasting models as future climate novelty increases. We show that, in the high emissions scenario (RCP 8.5) and by late 21st century, future climate novelty is similar to or higher than peak levels of climate novelty over the last 21,000 years. The accuracy of ecological forecasting models is projected to decline steadily over the coming decades in response to increasing climate novelty, although models that incorporate co-occurrences among species may retain somewhat higher predictive skill. In addition to quantifying future climate novelty in the context of late Quaternary climate change, this work underscores the challenges of making reliable forecasts to an increasingly novel future, while highlighting the need to assess potential avenues for improvement, such as increased reliance on geological analogs for future novel climates and improving existing models by pooling data through time and incorporating assemblage-level information. © 2018 John Wiley & Sons Ltd.

Comparison of climate envelope models developed using expert-selected variables versus statistical selection

Science.gov (United States)

Brandt, Laura A.; Benscoter, Allison; Harvey, Rebecca G.; Speroterra, Carolina; Bucklin, David N.; Romañach, Stephanie; Watling, James I.; Mazzotti, Frank J.

2017-01-01

Climate envelope models are widely used to describe potential future distribution of species under different climate change scenarios. It is broadly recognized that there are both strengths and limitations to using climate envelope models and that outcomes are sensitive to initial assumptions, inputs, and modeling methods Selection of predictor variables, a central step in modeling, is one of the areas where different techniques can yield varying results. Selection of climate variables to use as predictors is often done using statistical approaches that develop correlations between occurrences and climate data. These approaches have received criticism in that they rely on the statistical properties of the data rather than directly incorporating biological information about species responses to temperature and precipitation. We evaluated and compared models and prediction maps for 15 threatened or endangered species in Florida based on two variable selection techniques: expert opinion and a statistical method. We compared model performance between these two approaches for contemporary predictions, and the spatial correlation, spatial overlap and area predicted for contemporary and future climate predictions. In general, experts identified more variables as being important than the statistical method and there was low overlap in the variable sets (0.9 for area under the curve (AUC) and >0.7 for true skill statistic (TSS). Spatial overlap, which compares the spatial configuration between maps constructed using the different variable selection techniques, was only moderate overall (about 60%), with a great deal of variability across species. Difference in spatial overlap was even greater under future climate projections, indicating additional divergence of model outputs from different variable selection techniques. Our work is in agreement with other studies which have found that for broad-scale species distribution modeling, using statistical methods of variable

Transient nature of late Pleistocene climate variability.

Science.gov (United States)

Crowley, Thomas J; Hyde, William T

2008-11-13

Climate in the early Pleistocene varied with a period of 41 kyr and was related to variations in Earth's obliquity. About 900 kyr ago, variability increased and oscillated primarily at a period of approximately 100 kyr, suggesting that the link was then with the eccentricity of Earth's orbit. This transition has often been attributed to a nonlinear response to small changes in external boundary conditions. Here we propose that increasing variablility within the past million years may indicate that the climate system was approaching a second climate bifurcation point, after which it would transition again to a new stable state characterized by permanent mid-latitude Northern Hemisphere glaciation. From this perspective the past million years can be viewed as a transient interval in the evolution of Earth's climate. We support our hypothesis using a coupled energy-balance/ice-sheet model, which furthermore predicts that the future transition would involve a large expansion of the Eurasian ice sheet. The process responsible for the abrupt change seems to be the albedo discontinuity at the snow-ice edge. The best-fit model run, which explains almost 60% of the variance in global ice volume during the past 400 kyr, predicts a rapid transition in the geologically near future to the proposed glacial state. Should it be attained, this state would be more 'symmetric' than the present climate, with comparable areas of ice/sea-ice cover in each hemisphere, and would represent the culmination of 50 million years of evolution from bipolar nonglacial climates to bipolar glacial climates.

Effects of climate variability on global scale flood risk

Science.gov (United States)

Ward, P.; Dettinger, M. D.; Kummu, M.; Jongman, B.; Sperna Weiland, F.; Winsemius, H.

2013-12-01

In this contribution we demonstrate the influence of climate variability on flood risk. Globally, flooding is one of the worst natural hazards in terms of economic damages; Munich Re estimates global losses in the last decade to be in excess of $240 billion. As a result, scientifically sound estimates of flood risk at the largest scales are increasingly needed by industry (including multinational companies and the insurance industry) and policy communities. Several assessments of global scale flood risk under current and conditions have recently become available, and this year has seen the first studies assessing how flood risk may change in the future due to global change. However, the influence of climate variability on flood risk has as yet hardly been studied, despite the fact that: (a) in other fields (drought, hurricane damage, food production) this variability is as important for policy and practice as long term change; and (b) climate variability has a strong influence in peak riverflows around the world. To address this issue, this contribution illustrates the influence of ENSO-driven climate variability on flood risk, at both the globally aggregated scale and the scale of countries and large river basins. Although it exerts significant and widespread influences on flood peak discharges in many parts of the world, we show that ENSO does not have a statistically significant influence on flood risk once aggregated to global totals. At the scale of individual countries, though, strong relationships exist over large parts of the Earth's surface. For example, we find particularly strong anomalies of flood risk in El Niño or La Niña years (compared to all years) in southern Africa, parts of western Africa, Australia, parts of Central Eurasia (especially for El Niño), the western USA (especially for La Niña), and parts of South America. These findings have large implications for both decadal climate-risk projections and long-term future climate change

Modelling climate impact on floods under future emission scenarios using an ensemble of climate model projections

Science.gov (United States)

Wetterhall, F.; Cloke, H. L.; He, Y.; Freer, J.; Pappenberger, F.

2012-04-01

Evidence provided by modelled assessments of climate change impact on flooding is fundamental to water resource and flood risk decision making. Impact models usually rely on climate projections from Global and Regional Climate Models, and there is no doubt that these provide a useful assessment of future climate change. However, cascading ensembles of climate projections into impact models is not straightforward because of problems of coarse resolution in Global and Regional Climate Models (GCM/RCM) and the deficiencies in modelling high-intensity precipitation events. Thus decisions must be made on how to appropriately pre-process the meteorological variables from GCM/RCMs, such as selection of downscaling methods and application of Model Output Statistics (MOS). In this paper a grand ensemble of projections from several GCM/RCM are used to drive a hydrological model and analyse the resulting future flood projections for the Upper Severn, UK. The impact and implications of applying MOS techniques to precipitation as well as hydrological model parameter uncertainty is taken into account. The resultant grand ensemble of future river discharge projections from the RCM/GCM-hydrological model chain is evaluated against a response surface technique combined with a perturbed physics experiment creating a probabilisic ensemble climate model outputs. The ensemble distribution of results show that future risk of flooding in the Upper Severn increases compared to present conditions, however, the study highlights that the uncertainties are large and that strong assumptions were made in using Model Output Statistics to produce the estimates of future discharge. The importance of analysing on a seasonal basis rather than just annual is highlighted. The inability of the RCMs (and GCMs) to produce realistic precipitation patterns, even in present conditions, is a major caveat of local climate impact studies on flooding, and this should be a focus for future development.

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

Science.gov (United States)

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...

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

International Nuclear Information System (INIS)

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

2014-01-01

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. - Highlights: �

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

Energy Technology Data Exchange (ETDEWEB)

Fatichi, S., E-mail: simone.fatichi@ifu.baug.ethz.ch; 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. - Highlights: �

A Framework for Benefit-Cost Analysis of Adaptation to Climate Change and Climate Variability

International Nuclear Information System (INIS)

Leary, N.A.

1999-01-01

The potential damages of climate change and climate variability are dependent upon the responses or adaptations that people make to their changing environment. By adapting the management of resources, the mix and methods of producing goods and services, choices of leisure activities, and other behavior, people can lessen the damages that would otherwise result. A framework for assessing the benefits and costs of adaptation to both climate change and climate variability is described in the paper. The framework is also suitable for evaluating the economic welfare effects of climate change, allowing for autonomous adaptation by private agents. The paper also briefly addresses complications introduced by uncertainty regarding the benefits of adaptation and irreversibility of investments in adaptation. When investment costs are irreversible and there is uncertainty about benefits, the usual net present value criterion for evaluating the investment gives the wrong decision. If delaying an adaptation project is possible, and if delay will permit learning about future benefits of adaptation, it may be preferable to delay the project even if the expected net present value is positive. Implications of this result for adaptation policy are discussed in the paper. 11 refs

Impacts of Present and Future Climate Variability and Change on Agriculture and Forestry in the Arid and Semi-Arid Tropics

Energy Technology Data Exchange (ETDEWEB)

Sivakumar, M.V.K. [World Meteorological Organization WMO, 7bis Avenue de la Paix, 1211 Geneva 2 (Switzerland); Das, H.P. [India Meteorological Department, Shivaji Nagar, Pune, 411005 (India); Brunini, O. [Center for Ecology and Biophysics, 13.020-430-Campinas, Sao Paulo (Brazil)

2005-05-01

The arid and semi-arid regions account for approximately 30% of the world total area and are inhabited by approximately 20% of the total world population. Issues of present and future climate variability and change on agriculture and forestry in the arid and semi-arid tropics of the world were examined and discussion under each of these issues had been presented separately for Asia, Africa and Latin America. Several countries in tropical Asia have reported increasing surface temperature trends in recent decades. Although, there is no definite trend discernible in the long-term mean for precipitation for the tropical Asian region, many countries have shown a decreasing trend in rainfall in the past three decades. African rainfall has changed substantially over the last 60 yr and a number of theoretical, modelling and empirical analyses have suggested that noticeable changes in the frequency and intensity of extreme events, including floods may occur when there are only small changes in climate. Climate in Latin America is affected by the El Nino-southern oscillation (ENSO) phases and there is a close relationship between the increase and decrease of rainfall depending upon the warm or cold phases of the phenomenon. Over land regions of Asia, the projected area-averaged annual mean warming is likely to be 1.6 {+-} 0.2C in the 2020s, 3.1 {+-} 0.3C in the 2050s, and 4.6 {+-} 0.4C in the 2080s and the models show high uncertainty in projections of future winter and summer precipitation. Future annual warming across Africa is projected to range from 0.2C per decade to more than 0.5C per decade, while future changes in mean seasonal rainfall in Africa are less well defined. In Latin America, projections indicate a slight increase in temperature and changes in precipitation. Impacts of climate variability and changes are discussed with suitable examples. Agricultural productivity in tropical Asia is sensitive not only to temperature increases, but also to changes in the

Impacts of Present and Future Climate Variability and Change on Agriculture and Forestry in the Arid and Semi-Arid Tropics

International Nuclear Information System (INIS)

Sivakumar, M.V.K.; Das, H.P.; Brunini, O.

2005-01-01

The arid and semi-arid regions account for approximately 30% of the world total area and are inhabited by approximately 20% of the total world population. Issues of present and future climate variability and change on agriculture and forestry in the arid and semi-arid tropics of the world were examined and discussion under each of these issues had been presented separately for Asia, Africa and Latin America. Several countries in tropical Asia have reported increasing surface temperature trends in recent decades. Although, there is no definite trend discernible in the long-term mean for precipitation for the tropical Asian region, many countries have shown a decreasing trend in rainfall in the past three decades. African rainfall has changed substantially over the last 60 yr and a number of theoretical, modelling and empirical analyses have suggested that noticeable changes in the frequency and intensity of extreme events, including floods may occur when there are only small changes in climate. Climate in Latin America is affected by the El Nino-southern oscillation (ENSO) phases and there is a close relationship between the increase and decrease of rainfall depending upon the warm or cold phases of the phenomenon. Over land regions of Asia, the projected area-averaged annual mean warming is likely to be 1.6 ± 0.2C in the 2020s, 3.1 ± 0.3C in the 2050s, and 4.6 ± 0.4C in the 2080s and the models show high uncertainty in projections of future winter and summer precipitation. Future annual warming across Africa is projected to range from 0.2C per decade to more than 0.5C per decade, while future changes in mean seasonal rainfall in Africa are less well defined. In Latin America, projections indicate a slight increase in temperature and changes in precipitation. Impacts of climate variability and changes are discussed with suitable examples. Agricultural productivity in tropical Asia is sensitive not only to temperature increases, but also to changes in the nature

Scale dependency of regional climate modeling of current and future climate extremes in Germany

Science.gov (United States)

Tölle, Merja H.; Schefczyk, Lukas; Gutjahr, Oliver

2017-11-01

A warmer climate is projected for mid-Europe, with less precipitation in summer, but with intensified extremes of precipitation and near-surface temperature. However, the extent and magnitude of such changes are associated with creditable uncertainty because of the limitations of model resolution and parameterizations. Here, we present the results of convection-permitting regional climate model simulations for Germany integrated with the COSMO-CLM using a horizontal grid spacing of 1.3 km, and additional 4.5- and 7-km simulations with convection parameterized. Of particular interest is how the temperature and precipitation fields and their extremes depend on the horizontal resolution for current and future climate conditions. The spatial variability of precipitation increases with resolution because of more realistic orography and physical parameterizations, but values are overestimated in summer and over mountain ridges in all simulations compared to observations. The spatial variability of temperature is improved at a resolution of 1.3 km, but the results are cold-biased, especially in summer. The increase in resolution from 7/4.5 km to 1.3 km is accompanied by less future warming in summer by 1 ∘C. Modeled future precipitation extremes will be more severe, and temperature extremes will not exclusively increase with higher resolution. Although the differences between the resolutions considered (7/4.5 km and 1.3 km) are small, we find that the differences in the changes in extremes are large. High-resolution simulations require further studies, with effective parameterizations and tunings for different topographic regions. Impact models and assessment studies may benefit from such high-resolution model results, but should account for the impact of model resolution on model processes and climate change.

Impacts of climate variability and change on crop yield in sub-Sahara Africa

Science.gov (United States)

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.

Future climate. Engineering solutions

Energy Technology Data Exchange (ETDEWEB)

Ferdinand, J.F.; Hagedorn-Rasmussen, P.; Fonnesbech, B.

2009-09-15

Future Climate Engineering Solutions - Joint Report is the common output and a documentation of more than 1 year's effort by 13 engineering associations - in 12 countries - to demonstrate how technologies can combat climate change. The report consists of three parts: Summaries of 10 national climate plans and technology prospects, 5 Key Common Findings, and a Climate Call from Engineers to create a new global climate treaty. The basic assumption of the project is recognition that GHG emissions, and their concentration in the atmosphere, must be reduced to a sustainable level. The project definition of a sustainable level is equivalent to the best-case stabilisation scenario which was presented in the 4th Assessment Report (AR4) by the UN Intergovernmental Panel on Climate Change (IPCC), whereby the global mean temperature is most likely to stabilise at 2.0-2.4 deg. C. The Future Climate website www.futureclimate.info holds more information about the project, including possibility to download project material, including the full national climate plans.

Solar Variability and Planetary Climates

CERN Document Server

Calisesi, Y; Gray, L; Langen, J; Lockwood, M

2007-01-01

Variations in solar activity, as revealed by variations in the number of sunspots, have been observed since ancient times. To what extent changes in the solar output may affect planetary climates, though, remains today more than ever a subject of controversy. In 2000, the SSSI volume on Solar Variability and Climate reviewed the to-date understanding of the physics of solar variability and of the associated climate response. The present volume on Solar Variability and Planetary Climates provides an overview of recent advances in this field, with particular focus at the Earth's middle and lower atmosphere. The book structure mirrors that of the ISSI workshop held in Bern in June 2005, the collection of invited workshop contributions and of complementary introductory papers synthesizing the current understanding in key research areas such as middle atmospheric processes, stratosphere-troposphere dynamical coupling, tropospheric aerosols chemistry, solar storm influences, solar variability physics, and terrestri...

Future vegetation ecosystem response to warming climate over the Tibetan Plateau

Science.gov (United States)

Bao, Y.; Gao, Y.; Wang, Y.

2017-12-01

The amplified vegetation response to climate variability has been found over the Tibetan Plateau (TP) in recent decades. In this study, the potential impacts of 21st century climate change on the vegetation ecosystem over the TP are assessed based on the dynamic vegetation outputs of models from Coupled Model Intercomparison Project Phase 5 (CMIP5), and the sensitivity of the TP vegetation in response to warming climate was investigated. Models project a continuous and accelerating greening in future, especially in the eastern TP, which closely associates with the plant type upgrade due to the pronouncing warming in growing season.Vegetation leaf area index (LAI) increase well follows the global warming, suggesting the warming climate instead of co2 fertilization controlls the future TP plant growth. The warming spring may advance the start of green-up day and extend the growing season length. More carbon accumulation in vegetation and soil will intensify the TP carbon cycle and will keep it as a carbon sink in future. Keywords: Leaf Area Index (LAI), Climate Change, Global Dynamic Vegetation Models (DGVMs), CMIP5, Tibetan Plateau (TP)

Climate - Our future?

International Nuclear Information System (INIS)

Schotterer, U.

1992-01-01

The aim of this picture-based book is to make climate change understandable to a wider public. Images tell the story, figure captions enhance the essentials. Text passages tie and highlight the story, rather than provide long explanations of complex scientific reasoning. Brief summaries at the end of each chapter review knowledge of which everybody should be aware. They are based on the scientific assessments of the 1990 Intergovernmental Panel on Climate Change Report. The climate story is explored from six different angles: the physical system, past changes, how climate affects cultures, how people affect climate, the importance of research and how to view the future

Terrestrial Biosphere Dynamics in the Climate System: Past and Future

Science.gov (United States)

Overpeck, J.; Whitlock, C.; Huntley, B.

2002-12-01

The paleoenvironmental record makes it clear that climate change as large as is likely to occur in the next two centuries will drive change in the terrestrial biosphere that is both large and difficult to predict, or plan for. Many species, communities and ecosystems could experience rates of climate change, and "destination climates" that are unprecedented in their time on earth. The paleorecord also makes it clear that a wide range of possible climate system behavior, such as decades-long droughts, increases in large storm and flood frequency, and rapid sea level rise, all occurred repeatedly in the past, and for poorly understood reasons. These types of events, if they were to reoccur in the future, could have especially devastating impacts on biodiversity, both because their timing and spatial extent cannot be anticipated, and because the biota's natural defenses have been compromised by land-use, reductions in genetic flexibility, pollution, excess water utilization, invasive species, and other human influences. Vegetation disturbance (e.g., by disease, pests and fire) will undoubtedly be exacerbated by climate change (stress), but could also speed the rate at which terrestrial biosphere change takes place in the future. The paleoenvironmental record makes it clear that major scientific challenges include an improved ability to model regional biospheric change, both past and future. This in turn will be a prerequisite to obtaining realistic estimates of future biogeochemical and biophysical feedbacks, and thus to obtaining better assessments of future climate change. These steps will help generate the improved understanding of climate variability that is needed to manage global biodiversity. However, the most troubling message from the paleoenvironmental record is that unchecked anthropogenic climate change could make the Earth's 6th major mass extinction unavoidable.

Impacts of Climate Trends and Variability on Livestock Production in Brazil

Science.gov (United States)

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.

Joint effects of climate variability and socioecological factors on dengue transmission: epidemiological evidence.

Science.gov (United States)

Akter, Rokeya; Hu, Wenbiao; Naish, Suchithra; Banu, Shahera; Tong, Shilu

2017-06-01

To assess the epidemiological evidence on the joint effects of climate variability and socioecological factors on dengue transmission. Following PRISMA guidelines, a detailed literature search was conducted in PubMed, Web of Science and Scopus. Peer-reviewed, freely available and full-text articles, considering both climate and socioecological factors in relation to dengue, published in English from January 1993 to October 2015 were included in this review. Twenty studies have met the inclusion criteria and assessed the impact of both climatic and socioecological factors on dengue dynamics. Among those, four studies have further investigated the relative importance of climate variability and socioecological factors on dengue transmission. A few studies also developed predictive models including both climatic and socioecological factors. Due to insufficient data, methodological issues and contextual variability of the studies, it is hard to draw conclusion on the joint effects of climate variability and socioecological factors on dengue transmission. Future research should take into account socioecological factors in combination with climate variables for a better understanding of the complex nature of dengue transmission as well as for improving the predictive capability of dengue forecasting models, to develop effective and reliable early warning systems. © 2017 John Wiley & Sons Ltd.

Assessment of CORDEX-South Asia experiments for monsoonal precipitation over Himalayan region for future climate

Science.gov (United States)

Choudhary, A.; Dimri, A. P.

2018-04-01

Precipitation is one of the important climatic indicators in the global climate system. Probable changes in monsoonal (June, July, August and September; hereafter JJAS) mean precipitation in the Himalayan region for three different greenhouse gas emission scenarios (i.e. representative concentration pathways or RCPs) and two future time slices (near and far) are estimated from a set of regional climate simulations performed under Coordinated Regional Climate Downscaling Experiment-South Asia (CORDEX-SA) project. For each of the CORDEX-SA simulations and their ensemble, projections of near future (2020-2049) and far future (2070-2099) precipitation climatology with respect to corresponding present climate (1970-2005) over Himalayan region are presented. The variability existing over each of the future time slices is compared with the present climate variability to determine the future changes in inter annual fluctuations of monsoonal mean precipitation. The long-term (1970-2099) trend (mm/day/year) of monsoonal mean precipitation spatially distributed as well as averaged over Himalayan region is analyzed to detect any change across twenty-first century as well as to assess model uncertainty in simulating the precipitation changes over this period. The altitudinal distribution of difference in trend of future precipitation from present climate existing over each of the time slices is also studied to understand any elevation dependency of change in precipitation pattern. Except for a part of the Hindu-Kush area in western Himalayan region which shows drier condition, the CORDEX-SA experiments project in general wetter/drier conditions in near future for western/eastern Himalayan region, a scenario which gets further intensified in far future. Although, a gradually increasing precipitation trend is seen throughout the twenty-first century in carbon intensive scenarios, the distribution of trend with elevation presents a very complex picture with lower elevations

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

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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

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

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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

Ecological and evolutionary impacts of changing climatic variability.

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Vázquez, Diego P; Gianoli, Ernesto; Morris, William F; Bozinovic, Francisco

2017-02-01

While average temperature is likely to increase in most locations on Earth, many places will simultaneously experience higher variability in temperature, precipitation, and other climate variables. Although ecologists and evolutionary biologists widely recognize the potential impacts of changes in average climatic conditions, relatively little attention has been paid to the potential impacts of changes in climatic variability and extremes. We review the evidence on the impacts of increased climatic variability and extremes on physiological, ecological and evolutionary processes at multiple levels of biological organization, from individuals to populations and communities. Our review indicates that climatic variability can have profound influences on biological processes at multiple scales of organization. Responses to increased climatic variability and extremes are likely to be complex and cannot always be generalized, although our conceptual and methodological toolboxes allow us to make informed predictions about the likely consequences of such climatic changes. We conclude that climatic variability represents an important component of climate that deserves further attention. © 2015 Cambridge Philosophical Society.

Connecting today's climates to future climate analogs to facilitate movement of species under climate change.

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Littlefield, Caitlin E; McRae, Brad H; Michalak, Julia L; Lawler, Joshua J; Carroll, Carlos

2017-12-01

Increasing connectivity is an important strategy for facilitating species range shifts and maintaining biodiversity in the face of climate change. To date, however, few researchers have included future climate projections in efforts to prioritize areas for increasing connectivity. We identified key areas likely to facilitate climate-induced species' movement across western North America. Using historical climate data sets and future climate projections, we mapped potential species' movement routes that link current climate conditions to analogous climate conditions in the future (i.e., future climate analogs) with a novel moving-window analysis based on electrical circuit theory. In addition to tracing shifting climates, the approach accounted for landscape permeability and empirically derived species' dispersal capabilities. We compared connectivity maps generated with our climate-change-informed approach with maps of connectivity based solely on the degree of human modification of the landscape. Including future climate projections in connectivity models substantially shifted and constrained priority areas for movement to a smaller proportion of the landscape than when climate projections were not considered. Potential movement, measured as current flow, decreased in all ecoregions when climate projections were included, particularly when dispersal was limited, which made climate analogs inaccessible. Many areas emerged as important for connectivity only when climate change was modeled in 2 time steps rather than in a single time step. Our results illustrate that movement routes needed to track changing climatic conditions may differ from those that connect present-day landscapes. Incorporating future climate projections into connectivity modeling is an important step toward facilitating successful species movement and population persistence in a changing climate. © 2017 Society for Conservation Biology.

Forests: the potential consequences of climate variability and change

Science.gov (United States)

USDA Forest Service

2001-01-01

This pamphlet reports the recent scientific assessment that analyzed how future climate variablity and change may affect forests in the United States. The assessment, sponsored by the USDA Forest Service, and supported, in part, by the U.S Department of Energy, and the National Atmospheric and Space Administration, describes the suite of potential impacts on forests....

Contributions of internal climate variability to mitigation of projected future regional sea level rise

Science.gov (United States)

Hu, A.; Bates, S. C.

2017-12-01

Observations indicate that the global mean surface temperature is rising, so does the global mean sea level. Sea level rise (SLR) can impose significant impacts on island and coastal communities, especially when SLR is compounded with storm surges. Here, via analyzing results from two sets of ensemble simulations from the Community Earth System Model version 1, we investigate how the potential SLR benefits through mitigating the future emission scenarios from business as usual to a mild-mitigation over the 21st Century would be affected by internal climate variability. Results show that there is almost no SLR benefit in the near term due to the large SLR variability due to the internal ocean dynamics. However, toward the end of the 21st century, the SLR benefit can be as much as a 26±1% reduction of the global mean SLR due to seawater thermal expansion. Regionally, the benefits from this mitigation for both near and long terms are heterogeneous. They vary from just a 11±5% SLR reduction in Melbourne, Australia to a 35±6% reduction in London. The processes contributing to these regional differences are the coupling of the wind-driven ocean circulation with the decadal scale sea surface temperature mode in the Pacific and Southern Oceans, and the changes of the thermohaline circulation and the mid-latitude air-sea coupling in the Atlantic.

Future Changes in Surface Runoff over Korea Projected by a Regional Climate Model under A1B Scenario

Directory of Open Access Journals (Sweden)

Ji-Woo Lee

2014-01-01

Full Text Available This study assesses future change of surface runoff due to climate change over Korea using a regional climate model (RCM, namely, the Global/Regional Integrated Model System (GRIMs, Regional Model Program (RMP. The RMP is forced by future climate scenario, namely, A1B of Intergovernmental Panel on Climate Change (IPCC Fourth Assessment Report (AR4. The RMP satisfactorily reproduces the observed seasonal mean and variation of surface runoff for the current climate simulation. The distribution of monsoonal precipitation-related runoff is adequately captured by the RMP. In the future (2040–2070 simulation, it is shown that the increasing trend of temperature has significant impacts on the intra-annual runoff variation. The variability of runoff is increased in summer; moreover, the strengthened possibility of extreme occurrence is detected in the future climate. This study indicates that future climate projection, including surface runoff and its variability over Korea, can be adequately addressed on the RMP testbed. Furthermore, this study reflects that global warming affects local hydrological cycle by changing major water budget components. This study adduces that the importance of runoff should not be overlooked in regional climate studies, and more elaborate presentation of fresh-water cycle is needed to close hydrological circulation in RCMs.

Interactions of Mean Climate Change and Climate Variability on Food Security Extremes

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Ruane, Alexander C.; McDermid, Sonali; Mavromatis, Theodoros; Hudson, Nicholas; Morales, Monica; Simmons, John; Prabodha, Agalawatte; Ahmad, Ashfaq; Ahmad, Shakeel; Ahuja, Laj R.

2015-01-01

Recognizing that climate change will affect agricultural systems both through mean changes and through shifts in climate variability and associated extreme events, we present preliminary analyses of climate impacts from a network of 1137 crop modeling sites contributed to the AgMIP Coordinated Climate-Crop Modeling Project (C3MP). At each site sensitivity tests were run according to a common protocol, which enables the fitting of crop model emulators across a range of carbon dioxide, temperature, and water (CTW) changes. C3MP can elucidate several aspects of these changes and quantify crop responses across a wide diversity of farming systems. Here we test the hypothesis that climate change and variability interact in three main ways. First, mean climate changes can affect yields across an entire time period. Second, extreme events (when they do occur) may be more sensitive to climate changes than a year with normal climate. Third, mean climate changes can alter the likelihood of climate extremes, leading to more frequent seasons with anomalies outside of the expected conditions for which management was designed. In this way, shifts in climate variability can result in an increase or reduction of mean yield, as extreme climate events tend to have lower yield than years with normal climate.C3MP maize simulations across 126 farms reveal a clear indication and quantification (as response functions) of mean climate impacts on mean yield and clearly show that mean climate changes will directly affect the variability of yield. Yield reductions from increased climate variability are not as clear as crop models tend to be less sensitive to dangers on the cool and wet extremes of climate variability, likely underestimating losses from water-logging, floods, and frosts.

The future demographic niche of a declining grassland bird fails to shift poleward in response to climate change

Science.gov (United States)

McCauley, Lisa A.; Ribic, Christine; Pomara, Lars Y.; Zuckerberg, Benjamin

2017-01-01

ContextTemperate grasslands and their dependent species are exposed to high variability in weather and climate due to the lack of natural buffers such as forests. Grassland birds are particularly vulnerable to this variability, yet have failed to shift poleward in response to recent climate change like other bird species in North America. However, there have been few studies examining the effect of weather on grassland bird demography and consequent influence of climate change on population persistence and distributional shifts.ObjectivesThe goal of this study was to estimate the vulnerability of Henslow’s Sparrow (Ammodramus henslowii), an obligate grassland bird that has been declining throughout much of its range, to past and future climatic variability.MethodsWe conducted a demographic meta-analysis from published studies and quantified the relationship between nest success rates and variability in breeding season climate. We projected the climate-demography relationships spatially, throughout the breeding range, and temporally, from 1981 to 2050. These projections were used to evaluate population dynamics by implementing a spatially explicit population model.ResultsWe uncovered a climate-demography linkage for Henslow’s Sparrow with summer precipitation, and to a lesser degree, temperature positively affecting nest success. We found that future climatic conditions—primarily changes in precipitation—will likely contribute to reduced population persistence and a southwestward range contraction.ConclusionsFuture distributional shifts in response to climate change may not always be poleward and assessing projected changes in precipitation is critical for grassland bird conservation and climate change adaptation.

Revealing, Reducing, and Representing Uncertainties in New Hydrologic Projections for Climate-changed Futures

Science.gov (United States)

Arnold, Jeffrey; Clark, Martyn; Gutmann, Ethan; Wood, Andy; Nijssen, Bart; Rasmussen, Roy

2016-04-01

The United States Army Corps of Engineers (USACE) has had primary responsibility for multi-purpose water resource operations on most of the major river systems in the U.S. for more than 200 years. In that time, the USACE projects and programs making up those operations have proved mostly robust against the range of natural climate variability encountered over their operating life spans. However, in some watersheds and for some variables, climate change now is known to be shifting the hydroclimatic baseline around which that natural variability occurs and changing the range of that variability as well. This makes historical stationarity an inappropriate basis for assessing continued project operations under climate-changed futures. That means new hydroclimatic projections are required at multiple scales to inform decisions about specific threats and impacts, and for possible adaptation responses to limit water-resource vulnerabilities and enhance operational resilience. However, projections of possible future hydroclimatologies have myriad complex uncertainties that require explicit guidance for interpreting and using them to inform those decisions about climate vulnerabilities and resilience. Moreover, many of these uncertainties overlap and interact. Recent work, for example, has shown the importance of assessing the uncertainties from multiple sources including: global model structure [Meehl et al., 2005; Knutti and Sedlacek, 2013]; internal climate variability [Deser et al., 2012; Kay et al., 2014]; climate downscaling methods [Gutmann et al., 2012; Mearns et al., 2013]; and hydrologic models [Addor et al., 2014; Vano et al., 2014; Mendoza et al., 2015]. Revealing, reducing, and representing these uncertainties is essential for defining the plausible quantitative climate change narratives required to inform water-resource decision-making. And to be useful, such quantitative narratives, or storylines, of climate change threats and hydrologic impacts must sample

The effects of global climate variability on water resources and agriculture

International Nuclear Information System (INIS)

Adibe, E.C.

1990-06-01

Widespread improvements in agricultural productivity have been achieved over the last century using a wide range of technological advances. Future improvements, however, are likely to be constrained by the decreasing quality of new lands brought into production, growing limitations on capital for crop expansion and mechanization, and increasing population pressures. On top of these constraints are new uncertainties about future climatic conditions and the effects of anthropogenic climatic changes on water availability. In order to better understand some of the impacts of climatic changes on food security, plausible changes in water supply are explored and the possible effects on food production investigated. The cases discussed here include increases and decreases in both the average and the variability of water resource availability. (author). 30 refs, 5 figs, 3 tabs

Ice_Sheets_CCI: Essential Climate Variables for the Greenland Ice Sheet

Science.gov (United States)

Forsberg, R.; Sørensen, L. S.; Khan, A.; Aas, C.; Evansberget, D.; Adalsteinsdottir, G.; Mottram, R.; Andersen, S. B.; Ahlstrøm, A.; Dall, J.; Kusk, A.; Merryman, J.; Hvidberg, C.; Khvorostovsky, K.; Nagler, T.; Rott, H.; Scharrer, M.; Shepard, A.; Ticconi, F.; Engdahl, M.

2012-04-01

As part of the ESA Climate Change Initiative (www.esa-cci.org) a long-term project "ice_sheets_cci" started January 1, 2012, in addition to the existing 11 projects already generating Essential Climate Variables (ECV) for the Global Climate Observing System (GCOS). The "ice_sheets_cci" goal is to generate a consistent, long-term and timely set of key climate parameters for the Greenland ice sheet, to maximize the impact of European satellite data on climate research, from missions such as ERS, Envisat and the future Sentinel satellites. The climate parameters to be provided, at first in a research context, and in the longer perspective by a routine production system, would be grids of Greenland ice sheet elevation changes from radar altimetry, ice velocity from repeat-pass SAR data, as well as time series of marine-terminating glacier calving front locations and grounding lines for floating-front glaciers. The ice_sheets_cci project will involve a broad interaction of the relevant cryosphere and climate communities, first through user consultations and specifications, and later in 2012 optional participation in "best" algorithm selection activities, where prototype climate parameter variables for selected regions and time frames will be produced and validated using an objective set of criteria ("Round-Robin intercomparison"). This comparative algorithm selection activity will be completely open, and we invite all interested scientific groups with relevant experience to participate. The results of the "Round Robin" exercise will form the algorithmic basis for the future ECV production system. First prototype results will be generated and validated by early 2014. The poster will show the planned outline of the project and some early prototype results.

Climate variability impacts on rice crop production in pakistan

International Nuclear Information System (INIS)

Shakoor, U.; Saboor, A.; Baig, I.

2015-01-01

The climate variability has affected the agriculture production all over the globe. This concern has motivated important changes in the field of research during the last decade. Climate changes are believed to have declining effects towards crop production in Pakistan. This study carries an empirical investigation of the effects of climate change on rice crop of Pakistan by employing Vector Auto Regression (VAR) model. Annual seasonal data of the climatic variables from 1980 to 2013 has been used. Results confirmed that rising mean maximum temperature would lead to reduction in rice production while increase in mean minimum temperature would be advantageous towards rice production. Variation in mean minimum temperature brought about seven percent increase in rice productivity as shown by Variance Decomposition. Mean precipitation and mean temperature would increase rice production but simulations scenarios for 2030 confirmed that much increase in rainfall and mean temperature in long run will negatively affect rice production in future. It is therefore important to follow adequate policy action to safeguard crop productions from disastrous effects. Development of varieties resistant to high temperatures as well as droughts will definitely enhance resilience of rice crop in Pakistan. (author)

Association of genetic and phenotypic variability with geography and climate in three southern California oaks.

Science.gov (United States)

Riordan, Erin C; Gugger, Paul F; Ortego, Joaquín; Smith, Carrie; Gaddis, Keith; Thompson, Pam; Sork, Victoria L

2016-01-01

Geography and climate shape the distribution of organisms, their genotypes, and their phenotypes. To understand historical and future evolutionary and ecological responses to climate, we compared the association of geography and climate of three oak species (Quercus engelmannii, Quercus berberidifolia, and Quercus cornelius-mulleri) in an environmentally heterogeneous region of southern California at three organizational levels: regional species distributions, genetic variation, and phenotypic variation. We identified climatic variables influencing regional distribution patterns using species distribution models (SDMs), and then tested whether those individual variables are important in shaping genetic (microsatellite) and phenotypic (leaf morphology) variation. We estimated the relative contributions of geography and climate using multivariate redundancy analyses (RDA) with variance partitioning. The modeled distribution of each species was influenced by climate differently. Our analysis of genetic variation using RDA identified small but significant associations between genetic variation with climate and geography in Q. engelmannii and Q. cornelius-mulleri, but not in Q. berberidifolia, and climate explained more of the variation. Our analysis of phenotypic variation in Q. engelmannii indicated that climate had more impact than geography, but not in Q. berberidifolia. Throughout our analyses, we did not find a consistent pattern in effects of individual climatic variables. Our comparative analysis illustrates that climate influences tree response at all organizational levels, but the important climate factors vary depending on the level and on the species. Because of these species-specific and level-specific responses, today's sympatric species are unlikely to have similar distributions in the future. © 2016 Botanical Society of America.

Post-Fire Recovery of Eco-Hydrologic Behavior Given Historic and Projected Climate Variability in California Mediterranean Type Environments

Science.gov (United States)

Seaby, L. P.; Tague, C. L.; Hope, A. S.

2006-12-01

The Mediterranean type environments (MTEs) of California are characterized by a distinct wet and dry season and high variability in inter-annual climate. Water limitation in MTEs makes eco-hydrological processes highly sensitive to both climate variability and frequent fire disturbance. This research modeled post-fire eco- hydrologic behavior under historical and moderate and extreme scenarios of future climate in a semi-arid chaparral dominated southern California MTE. We used a physically-based, spatially-distributed, eco- hydrological model (RHESSys - Regional Hydro-Ecologic Simulation System), to capture linkages between water and vegetation response to the combined effects of fire and historic and future climate variability. We found post-fire eco-hydrologic behavior to be strongly influenced by the episodic nature of MTE climate, which intensifies under projected climate change. Higher rates of post-fire net primary productivity were found under moderate climate change, while more extreme climate change produced water stressed conditions which were less favorable for vegetation productivity. Precipitation variability in the historic record follows the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO), and these inter-annual climate characteristics intensify under climate change. Inter-annual variation in streamflow follows these precipitation patterns. Post-fire streamflow and carbon cycling trajectories are strongly dependent on climate characteristics during the first 5 years following fire, and historic intra-climate variability during this period tends to overwhelm longer term trends and variation that might be attributable to climate change. Results have implications for water resource availability, vegetation type conversion from shrubs to grassland, and changes in ecosystem structure and function.

Influence of Climate Variability on US Regional Homicide Rates

Science.gov (United States)

Harp, R. D.; Karnauskas, K. B.

2017-12-01

Recent studies have found consistent evidence of a relationship between temperature and criminal behavior. However, despite agreement in the overall relationship, little progress has been made in distinguishing between two proposed explanatory theories. The General Affective Aggression Model (GAAM) suggests that high temperatures create periods of higher heat stress that enhance individual aggressiveness, whereas the Routine Activities Theory (RAT) theorizes that individuals are more likely to be outdoors interacting with others during periods of pleasant weather with a resulting increase in both interpersonal interactions and victim availability. Further, few studies have considered this relationship within the context of climate change in a quantitative manner. In an effort to distinguish between the two theories, and to examine the statistical relationships on a broader spatial scale than previously, we combined data from the Supplementary Homicide Report (SHR—compiled by the Federal Bureau of Investigation) and the North American Regional Reanalysis (NARR—compiled by the National Centers for Environmental Protection, a branch of the National Oceanic and Atmospheric Administration). US homicide data described by the SHR was compared with seven relevant observed climate variables (temperature, dew point, relative humidity, accumulated precipitation, accumulated snowfall, snow cover, and snow depth) provided by the NARR atmospheric reanalysis. Relationships between homicide rates and climate variables, as well as reveal regional spatial patterns will be presented and discussed, along with the implications due to future climate change. This research lays the groundwork for the refinement of estimates of an oft-overlooked climate change impact, which has previously been estimated to cause an additional 22,000 murders between 2010 and 2099, including providing important constraints for empirical models of future violent crime incidences in the face of global

Mediterranean climate modelling: variability and climate change scenarios

International Nuclear Information System (INIS)

Somot, S.

2005-12-01

Air-sea fluxes, open-sea deep convection and cyclo-genesis are studied in the Mediterranean with the development of a regional coupled model (AORCM). It accurately simulates these processes and their climate variabilities are quantified and studied. The regional coupling shows a significant impact on the number of winter intense cyclo-genesis as well as on associated air-sea fluxes and precipitation. A lower inter-annual variability than in non-coupled models is simulated for fluxes and deep convection. The feedbacks driving this variability are understood. The climate change response is then analysed for the 21. century with the non-coupled models: cyclo-genesis decreases, associated precipitation increases in spring and autumn and decreases in summer. Moreover, a warming and salting of the Mediterranean as well as a strong weakening of its thermohaline circulation occur. This study also concludes with the necessity of using AORCMs to assess climate change impacts on the Mediterranean. (author)

Quantifying Direct and Indirect Impact of Future Climate on Sub-Arctic Hydrology

Science.gov (United States)

Endalamaw, A. M.; Bolton, W. R.; Young-Robertson, J. M.; Morton, D.; Hinzman, L. D.

2016-12-01

Projected future climate will have a significant impact on the hydrology of interior Alaskan sub-arctic watersheds, directly though the changes in precipitation and temperature patterns, and indirectly through the cryospheric and ecological impacts. Although the latter is the dominant factor controlling the hydrological processes in the interior Alaska sub-arctic, it is often overlooked in many climate change impact studies. In this study, we aim to quantify and compare the direct and indirect impact of the projected future climate on the hydrology of the interior Alaskan sub-arctic watersheds. The Variable Infiltration Capacity (VIC) meso-scale hydrological model will be implemented to simulate the hydrological processes, including runoff, evapotranspiration, and soil moisture dynamics in the Chena River Basin (area = 5400km2), located in the interior Alaska sub-arctic region. Permafrost and vegetation distribution will be derived from the Geophysical Institute Permafrost Lab (GIPL) model and the Lund-Potsdam-Jena Dynamic Global Model (LPJ) model, respectively. All models will be calibrated and validated using historical data. The Scenario Network for Alaskan and Arctic Planning (SNAP) 5-model average projected climate data products will be used as forcing data for each of these models. The direct impact of climate change on hydrology is estimated using surface parameterization derived from the present day permafrost and vegetation distribution, and future climate forcing from SNAP projected climate data products. Along with the projected future climate, outputs of GIPL and LPJ will be incorporated into the VIC model to estimate the indirect and overall impact of future climate on the hydrology processes in the interior Alaskan sub-arctic watersheds. Finally, we will present the potential hydrological and ecological changes by the end of the 21st century.

The futures of climate engineering

Science.gov (United States)

Low, Sean

2017-01-01

This piece examines the need to interrogate the role of the conceptions of the future, as embedded in academic papers, policy documents, climate models, and other artifacts that serve as currencies of the science-society interface, in shaping scientific and policy agendas in climate engineering. Growing bodies of work on framings, metaphors, and models in the past decade serve as valuable starting points, but can benefit from integration with science and technology studies work on the sociology of expectations, imaginaries, and visions. Potentially valuable branches of work to come might be the anticipatory use of the future: the design of experimental spaces for exploring the future of an engineered climate in service of responsible research and innovation, and the integration of this work within the unfolding context of the Paris Agreement.

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

Science.gov (United States)

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.

Assessment of future extreme climate events over the Porto wine Region

Science.gov (United States)

Viceto, Carolina; Cardoso, Susana; Marta-Almeida, Martinho; Gorodetskaya, Irina; Rocha, Alfredo

2017-04-01

to be produced (Porto and Douro wine), while climate variability affects the annual productivity and quality of the grape harvest. Our study investigates changes in the extreme climate events in the future model runs, through a set of climate change indicators defined by the WRCP's Expert Team in Climate Change Detection and Indices, which uses variables such as daily maximum and minimum temperatures and precipitation amounts. Furthermore, we explore heat waves and their properties (duration, intensity and recovery factor). The analysis shows an increase of the mean temperature in the DDR higher than 2°C by the mid-21st century and 4.5°C by the end of the century, relatively to the reference period. Moreover, we found a major predisposition towards higher values of minimum and maximum daily temperatures and a decrease in the total precipitation during both future periods. These preliminary results indicate increased climatic stress on the DDR wine production and increased vulnerability of the wine varieties in this region.

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

Science.gov (United States)

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

Decadal to millennial time scale climate variability in the Central Mediterranean during the Holocene: a reconstruction based on geochemical proxies from high resolution sedimentary records

NARCIS (Netherlands)

Goudeau, M.S.

2014-01-01

To assess potential anthropogenic contributions to future climate change it is necessary to understand natural climate variability. This can be achieved by studying climate variability during the Holocene, when similar basic climate boundary conditions persisted as today. During this period climate

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

Science.gov (United States)

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

The Effects of Weather on Oilseed Rape (OSR Yield in China: Future Implications of Climate Change

Directory of Open Access Journals (Sweden)

Yaqin He

2017-03-01

Full Text Available Understanding the role of climatic factors on crop yields is essential in predicting the future impact of climate change. In order to understand the influence of climatic factors on OSR, detailed farm-level panel data from 2566 farms across 67 counties of the 6 major OSR production regions in China, from the surveys conducted by the national OSR industry project between 2008 and 2013, were used to examine the contribution of changes in selected climatic variables between 2008 and 2013 to yield variation. Spatial and temporal patterns of the relationships between OSR yield, climatic factors were estimated together with the effects of farmer adaptation and management practices on yield variability. The analysis revealed that yields in the low-latitude production regions were more sensitive to temperature increases and likely to decline. Precipitation iwas the most influential factor on yield at the first two growth stages; temperature and sunshine hours were most important at the third and fourth growth stages, respectively. Labour input was the most influential management factor affecting yields compared with fertilizer and other inputs. The study concludes that projection of future climate change impacts will need inter alia to incorporate more sophisticated and detailed measures of climatic variables than simple means of temperature and precipitation, incorporating timing in relation to plant growth and yield.

The Dependencies of Ecosystem Pattern, Structure, and Dynamics on Climate, Climate Variability, and Climate Change

Science.gov (United States)

Flanagan, S.; Hurtt, G. C.; Fisk, J. P.; Rourke, O.

2012-12-01

A robust understanding of the sensitivity of the pattern, structure, and dynamics of ecosystems to climate, climate variability, and climate change is needed to predict ecosystem responses to current and projected climate change. We present results of a study designed to first quantify the sensitivity of ecosystems to climate through the use of climate and ecosystem data, and then use the results to test the sensitivity of the climate data in a state-of the art ecosystem model. A database of available ecosystem characteristics such as mean canopy height, above ground biomass, and basal area was constructed from sources like the National Biomass and Carbon Dataset (NBCD). The ecosystem characteristics were then paired by latitude and longitude with the corresponding climate characteristics temperature, precipitation, photosynthetically active radiation (PAR) and dew point that were retrieved from the North American Regional Reanalysis (NARR). The average yearly and seasonal means of the climate data, and their associated maximum and minimum values, over the 1979-2010 time frame provided by NARR were constructed and paired with the ecosystem data. The compiled results provide natural patterns of vegetation structure and distribution with regard to climate data. An advanced ecosystem model, the Ecosystem Demography model (ED), was then modified to allow yearly alterations to its mechanistic climate lookup table and used to predict the sensitivities of ecosystem pattern, structure, and dynamics to climate data. The combined ecosystem structure and climate data results were compared to ED's output to check the validity of the model. After verification, climate change scenarios such as those used in the last IPCC were run and future forest structure changes due to climate sensitivities were identified. The results of this study can be used to both quantify and test key relationships for next generation models. The sensitivity of ecosystem characteristics to climate data

High Resolution Simulations of Future Climate in West Africa Using a Variable-Resolution Atmospheric Model

Science.gov (United States)

Adegoke, J. O.; Engelbrecht, F.; Vezhapparambu, S.

2013-12-01

In previous work demonstrated the application of a var¬iable-resolution global atmospheric model, the conformal-cubic atmospheric model (CCAM), across a wide range of spatial and time scales to investigate the ability of the model to provide realistic simulations of present-day climate and plausible projections of future climate change over sub-Saharan Africa. By applying the model in stretched-grid mode the versatility of the model dynamics, numerical formulation and physical parameterizations to function across a range of length scales over the region of interest, was also explored. We primarily used CCAM to illustrate the capability of the model to function as a flexible downscaling tool at the climate-change time scale. Here we report on additional long term climate projection studies performed by downscaling at much higher resolutions (8 Km) over an area that stretches from just south of Sahara desert to the southern coast of the Niger Delta and into the Gulf of Guinea. To perform these simulations, CCAM was provided with synoptic-scale forcing of atmospheric circulation from 2.5 deg resolution NCEP reanalysis at 6-hourly interval and SSTs from NCEP reanalysis data uses as lower boundary forcing. CCAM 60 Km resolution downscaled to 8 Km (Schmidt factor 24.75) then 8 Km resolution simulation downscaled to 1 Km (Schmidt factor 200) over an area approximately 50 Km x 50 Km in the southern Lake Chad Basin (LCB). Our intent in conducting these high resolution model runs was to obtain a deeper understanding of linkages between the projected future climate and the hydrological processes that control the surface water regime in this part of sub-Saharan Africa.

Establishing the common patterns of future tropospheric ozone under diverse climate change scenarios

Science.gov (United States)

Jimenez-Guerrero, Pedro; Gómez-Navarro, Juan J.; Jerez, Sonia; Lorente-Plazas, Raquel; Baro, Rocio; Montávez, Juan P.

2013-04-01

The impacts of climate change on air quality may affect long-term air quality planning. However, the policies aimed at improving air quality in the EU directives have not accounted for the variations in the climate. Climate change alone influences future air quality through modifications of gas-phase chemistry, transport, removal, and natural emissions. As such, the aim of this work is to check whether the projected changes in gas-phase air pollution over Europe depends on the scenario driving the regional simulation. For this purpose, two full-transient regional climate change-air quality projections for the first half of the XXI century (1991-2050) have been carried out with MM5+CHIMERE system, including A2 and B2 SRES scenarios. Experiments span the periods 1971-2000, as a reference, and 2071-2100, as future enhanced greenhouse gas and aerosol scenarios (SRES A2 and B2). The atmospheric simulations have a horizontal resolution of 25 km and 23 vertical layers up to 100 mb, and were driven by ECHO-G global climate model outputs. The analysis focuses on the connection between meteorological and air quality variables. Our simulations suggest that the modes of variability for tropospheric ozone and their main precursors hardly change under different SRES scenarios. The effect of changing scenarios has to be sought in the intensity of the changing signal, rather than in the spatial structure of the variation patterns, since the correlation between the spatial patterns of variability in A2 and B2 simulation is r > 0.75 for all gas-phase pollutants included in this study. In both cases, full-transient simulations indicate an enhanced enhanced chemical activity under future scenarios. The causes for tropospheric ozone variations have to be sought in a multiplicity of climate factors, such as increased temperature, different distribution of precipitation patterns across Europe, increased photolysis of primary and secondary pollutants due to lower cloudiness, etc

Possible Future Climate Change Impacts on the Hydrological Drought Events in the Weihe River Basin, China

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Fei Yuan

2016-01-01

Full Text Available Quantitative evaluation of future climate change impacts on hydrological drought characteristics is one of important measures for implementing sustainable water resources management and effective disaster mitigation in drought-prone regions under the changing environment. In this study, a modeling system for projecting the potential future climate change impacts on hydrological droughts in the Weihe River basin (WRB in North China is presented. This system consists of a large-scale hydrological model driven by climate outputs from three climate models (CMs for future streamflow projections, a probabilistic model for univariate drought assessment, and a copula-based bivariate model for joint drought frequency analysis under historical and future climates. With the observed historical climate data as the inputs, the Variable Infiltration Capacity hydrological model projects an overall runoff reduction in the WRB under the Intergovernmental Panel on Climate Change A1B scenario. The univariate drought assessment found that although fewer hydrological drought events would occur under A1B scenario, drought duration and severity tend to increase remarkably. Moreover, the bivariate drought assessment reveals that future droughts in the same return period as the baseline droughts would become more serious. With these trends in the future, the hydrological drought situation in the WRB would be further deteriorated.

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

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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

Climate Change or Climate Variability? History, Science and Politics in the Mesoamerican Climate

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Daniel Poleo

2016-08-01

Full Text Available Climate variations in Mesoamerica have influenced the development and decay of populations from the earliest human settlements. The present time is no exception; there is no evidence that global warming will impact rainfall in the region, but rather there are important studies showing a response of rainfall to climate variability in the American tropics. Since our tropical region is vulnerable to climate variability, public policies must be congruent to avoid the mistakes of previous generations and achieve, with the help of science, a real progress in the fight against global warming.

Anthropogenic radiative forcing of southern African and Southern Hemisphere climate variability and change

CSIR Research Space (South Africa)

Engelbrecht, FA

2014-10-01

Full Text Available of stratospheric ozone, greenhouse gasses, aerosols and sulphur dioxide, can improve the model's skill to simulate inter-annual variability over southern Africa. The paper secondly explores the role of different radiative forcings of future climate change over...

Thermal tolerance ranges and climate variability : A comparison between bivalves from differing climates

NARCIS (Netherlands)

Compton, Tanya J.; Rijkenberg, Micha J. A.; Drent, Jan; Piersma, Theunis

2007-01-01

The climate variability hypothesis proposes that in variable temperate climates poikilothermic animals have wide thermal tolerance windows, whereas in constant tropical climates they have small thermal tolerance windows. In this study we quantified and compared the upper and lower lethal thermal

The role of internal climate variability for interpreting climate change scenarios

Science.gov (United States)

Maraun, Douglas

2013-04-01

When communicating information on climate change, the use of multi-model ensembles has been advocated to sample uncertainties over a range as wide as possible. To meet the demand for easily accessible results, the ensemble is often summarised by its multi-model mean signal. In rare cases, additional uncertainty measures are given to avoid loosing all information on the ensemble spread, e.g., the highest and lowest projected values. Such approaches, however, disregard the fundamentally different nature of the different types of uncertainties and might cause wrong interpretations and subsequently wrong decisions for adaptation. Whereas scenario and climate model uncertainties are of epistemic nature, i.e., caused by an in principle reducible lack of knowledge, uncertainties due to internal climate variability are aleatory, i.e., inherently stochastic and irreducible. As wisely stated in the proverb "climate is what you expect, weather is what you get", a specific region will experience one stochastic realisation of the climate system, but never exactly the expected climate change signal as given by a multi model mean. Depending on the meteorological variable, region and lead time, the signal might be strong or weak compared to the stochastic component. In cases of a low signal-to-noise ratio, even if the climate change signal is a well defined trend, no trends or even opposite trends might be experienced. Here I propose to use the time of emergence (TOE) to quantify and communicate when climate change trends will exceed the internal variability. The TOE provides a useful measure for end users to assess the time horizon for implementing adaptation measures. Furthermore, internal variability is scale dependent - the more local the scale, the stronger the influence of internal climate variability. Thus investigating the TOE as a function of spatial scale could help to assess the required spatial scale for implementing adaptation measures. I exemplify this proposal with

Climate variability and change

International Nuclear Information System (INIS)

Manton, M.

2006-01-01

When Australia's climate should not be definite barrier to the population reaching 30 million by 2050, it is recognised that our climate has limited the development of the nation over the past 200 years. Indeed in 1911, based on a comparison of the climate and development between the US and Australia. Griffith Taylor predicted that Australia's population would be 19 million at the end of the 20th century, which is a pretty good 90-year forecast. The climate constraint is not only due to much of the country being semi-arid with an annual rainfall below 400 millimetres, but also due to the large year-to-year variability of rainfall across the country

Impacts of Present and Future Climate Variability on Agriculture and Forestry in the Temperate Regions. Europe

International Nuclear Information System (INIS)

Maracchi, G.; Sirotenko, O.; Bindi, M.

2005-01-01

Agriculture and forestry will be particularly sensitive to changes in mean climate and climate variability in the northern and southern regions of Europe. Agriculture may be positively affected by climate change in the northern areas through the introduction of new crop species and varieties, higher crop production and expansion of suitable areas for crop cultivation. The disadvantages may be determined by an increase in need for plant protection, risk of nutrient leaching and accelerated breakdown of soil organic matter. In the southern areas the benefits of the projected climate change will be limited, while the disadvantages will be predominant. The increased water use efficiency caused by increasing CO2 will compensate for some of the negative effects of increasing water limitation and extreme weather events, but lower harvestable yields, higher yield variability and reduction in suitable areas of traditional crops are expected for these areas. Forestry in the Mediterranean region may be mainly affected by increases in drought and forest fires. In northern Europe, the increased precipitation is expected to be large enough to compensate for the increased evapotranspiration. On the other hand, however, increased precipitation, cloudiness and rain days and the reduced duration of snow cover and soil frost may negatively affect forest work and timber logging determining lower profitability of forest production and a decrease in recreational possibilities. Adaptation management strategies should be introduced, as effective tools, to reduce the negative impacts of climate change on agricultural and forestry sectors

Costa Rica Rainfall in Future Climate Change Scenarios

Science.gov (United States)

Castillo Rodriguez, R. A., Sr.; Amador, J. A.; Duran-Quesada, A. M.

2017-12-01

Studies of intraseasonal and annual cycles of meteorological variables, using projections of climate change, are nowadays extremely important to improve regional socio-economic planning for countries. This is particularly true in Costa Rica, as Central America has been identified as a climate change hot spot. Today many of the economic activities in the region, especially those related to agriculture, tourism and hydroelectric power generation are linked to the seasonal cycle of precipitation. Changes in rainfall (mm/day) and in the diurnal temperature range (°C) for the periods 1950-2005 and 2006-2100 were investigated using the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) constructed using the CMIP5 (Coupled Model Intercomparison Project version 5) data. Differences between the multi-model ensembles of the two prospective scenarios (RCP 4.5 and RCP 8.5) and the retrospective baseline scenario were computed. This study highlights Costa Rica as an inflexion point of the climate change in the region and also suggests future drying conditions.

Quantifying uncertainty due to internal variability using high-resolution regional climate model simulations

Science.gov (United States)

Gutmann, E. D.; Ikeda, K.; Deser, C.; Rasmussen, R.; Clark, M. P.; Arnold, J. R.

2015-12-01

The uncertainty in future climate predictions is as large or larger than the mean climate change signal. As such, any predictions of future climate need to incorporate and quantify the sources of this uncertainty. One of the largest sources comes from the internal, chaotic, variability within the climate system itself. This variability has been approximated using the 30 ensemble members of the Community Earth System Model (CESM) large ensemble. Here we examine the wet and dry end members of this ensemble for cool-season precipitation in the Colorado Rocky Mountains with a set of high-resolution regional climate model simulations. We have used the Weather Research and Forecasting model (WRF) to simulate the periods 1990-2000, 2025-2035, and 2070-2080 on a 4km grid. These simulations show that the broad patterns of change depicted in CESM are inherited by the high-resolution simulations; however, the differences in the height and location of the mountains in the WRF simulation, relative to the CESM simulation, means that the location and magnitude of the precipitation changes are very different. We further show that high-resolution simulations with the Intermediate Complexity Atmospheric Research model (ICAR) predict a similar spatial pattern in the change signal as WRF for these ensemble members. We then use ICAR to examine the rest of the CESM Large Ensemble as well as the uncertainty in the regional climate model due to the choice of physics parameterizations.

Robust Performance of Marginal Pacific Coral Reef Habitats in Future Climate Scenarios.

Science.gov (United States)

Freeman, Lauren A

2015-01-01

Coral reef ecosystems are under dual threat from climate change. Increasing sea surface temperatures and thermal stress create environmental limits at low latitudes, and decreasing aragonite saturation state creates environmental limits at high latitudes. This study examines the response of unique coral reef habitats to climate change in the remote Pacific, using the National Center for Atmospheric Research Community Earth System Model version 1 alongside the species distribution algorithm Maxent. Narrow ranges of physico-chemical variables are used to define unique coral habitats and their performance is tested in future climate scenarios. General loss of coral reef habitat is expected in future climate scenarios and has been shown in previous studies. This study found exactly that for most of the predominant physico-chemical environments. However, certain coral reef habitats considered marginal today at high latitude, along the equator and in the eastern tropical Pacific were found to be quite robust in climate change scenarios. Furthermore, an environmental coral reef refuge previously identified in the central south Pacific near French Polynesia was further reinforced. Studying the response of specific habitats showed that the prevailing conditions of this refuge during the 20th century shift to a new set of conditions, more characteristic of higher latitude coral reefs in the 20th century, in future climate scenarios projected to 2100.

Robust Performance of Marginal Pacific Coral Reef Habitats in Future Climate Scenarios.

Directory of Open Access Journals (Sweden)

Lauren A Freeman

Full Text Available Coral reef ecosystems are under dual threat from climate change. Increasing sea surface temperatures and thermal stress create environmental limits at low latitudes, and decreasing aragonite saturation state creates environmental limits at high latitudes. This study examines the response of unique coral reef habitats to climate change in the remote Pacific, using the National Center for Atmospheric Research Community Earth System Model version 1 alongside the species distribution algorithm Maxent. Narrow ranges of physico-chemical variables are used to define unique coral habitats and their performance is tested in future climate scenarios. General loss of coral reef habitat is expected in future climate scenarios and has been shown in previous studies. This study found exactly that for most of the predominant physico-chemical environments. However, certain coral reef habitats considered marginal today at high latitude, along the equator and in the eastern tropical Pacific were found to be quite robust in climate change scenarios. Furthermore, an environmental coral reef refuge previously identified in the central south Pacific near French Polynesia was further reinforced. Studying the response of specific habitats showed that the prevailing conditions of this refuge during the 20th century shift to a new set of conditions, more characteristic of higher latitude coral reefs in the 20th century, in future climate scenarios projected to 2100.

Locally Downscaled and Spatially Customizable Climate Data for Historical and Future Periods for North America.

Science.gov (United States)

Wang, Tongli; Hamann, Andreas; Spittlehouse, Dave; Carroll, Carlos

2016-01-01

Large volumes of gridded climate data have become available in recent years including interpolated historical data from weather stations and future predictions from general circulation models. These datasets, however, are at various spatial resolutions that need to be converted to scales meaningful for applications such as climate change risk and impact assessments or sample-based ecological research. Extracting climate data for specific locations from large datasets is not a trivial task and typically requires advanced GIS and data management skills. In this study, we developed a software package, ClimateNA, that facilitates this task and provides a user-friendly interface suitable for resource managers and decision makers as well as scientists. The software locally downscales historical and future monthly climate data layers into scale-free point estimates of climate values for the entire North American continent. The software also calculates a large number of biologically relevant climate variables that are usually derived from daily weather data. ClimateNA covers 1) 104 years of historical data (1901-2014) in monthly, annual, decadal and 30-year time steps; 2) three paleoclimatic periods (Last Glacial Maximum, Mid Holocene and Last Millennium); 3) three future periods (2020s, 2050s and 2080s); and 4) annual time-series of model projections for 2011-2100. Multiple general circulation models (GCMs) were included for both paleo and future periods, and two representative concentration pathways (RCP4.5 and 8.5) were chosen for future climate data.

Complex response of white pines to past environmental variability increases understanding of future vulnerability.

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Virginia Iglesias

Full Text Available Ecological niche models predict plant responses to climate change by circumscribing species distributions within a multivariate environmental framework. Most projections based on modern bioclimatic correlations imply that high-elevation species are likely to be extirpated from their current ranges as a result of rising growing-season temperatures in the coming decades. Paleoecological data spanning the last 15,000 years from the Greater Yellowstone region describe the response of vegetation to past climate variability and suggest that white pines, a taxon of special concern in the region, have been surprisingly resilient to high summer temperature and fire activity in the past. Moreover, the fossil record suggests that winter conditions and biotic interactions have been critical limiting variables for high-elevation conifers in the past and will likely be so in the future. This long-term perspective offers insights on species responses to a broader range of climate and associated ecosystem changes than can be observed at present and should be part of resource management and conservation planning for the future.

Serious Simulation Role-Playing Games for Transformative Climate Change Education: "World Climate" and "Future Climate"

Science.gov (United States)

Rooney-Varga, J. N.; Sterman, J.; Sawin, E.; Jones, A.; Merhi, H.; Hunt, C.

2012-12-01

Climate change, its mitigation, and adaption to its impacts are among the greatest challenges of our times. Despite the importance of societal decisions in determining climate change outcomes, flawed mental models about climate change remain widespread, are often deeply entrenched, and present significant barriers to understanding and decision-making around climate change. Here, we describe two simulation role-playing games that combine active, affective, and analytical learning to enable shifts of deeply held conceptions about climate change. The games, World Climate and Future Climate, use a state-of-the-art decision support simulation, C-ROADS (Climate Rapid Overview and Decision Support) to provide users with immediate feedback on the outcomes of their mitigation strategies at the national level, including global greenhouse gas (GHG) emissions and concentrations, mean temperature changes, sea level rise, and ocean acidification. C-ROADS outcomes are consistent with the atmosphere-ocean general circulation models (AOGCMS), such as those used by the IPCC, but runs in less than one second on ordinary laptops, providing immediate feedback to participants on the consequences of their proposed policies. Both World Climate and Future Climate role-playing games provide immersive, situated learning experiences that motivate active engagement with climate science and policy. In World Climate, participants play the role of United Nations climate treaty negotiators. Participant emissions reductions proposals are continually assessed through interactive exploration of the best available science through C-ROADS. Future Climate focuses on time delays in the climate and energy systems. Participants play the roles of three generations: today's policymakers, today's youth, and 'just born.' The game unfolds in three rounds 25 simulated years apart. In the first round, only today's policymakers make decisions; In the next round, the young become the policymakers and inherit the

Prospects for future climate: A special US/USSR report on climate and climate change

International Nuclear Information System (INIS)

MacCracken, M.C.; Budyko, M.I.; Hecht, A.D.; Izrael, Y.A.

1990-01-01

Starting with the US-USSR Agreement on Protection of the Environment signed in 1972, the two nations have cooperated in joint research on atmospheric and environmental problems. The result of these efforts has been an innovative approach to projecting future climate change based on what has been learned about past warm periods and what can be learned from models. The chapters in this document explore the following: past changes in climate, both paleoclimatology and changes in the recent past; changes in atmospheric composition; estimates of greenhouse-induced change including the use of both empirical methods and climate models; impacts of climate change on water resources and agriculture in the two countries; and prospects for future climate changes

Orographic cirrus in a future climate

Directory of Open Access Journals (Sweden)

H. Joos

2009-10-01

Full Text Available A cloud resolving model (CRM is used to investigate the formation of orographic cirrus clouds in the current and future climate. The formation of cirrus clouds depends on a variety of dynamical and thermodynamical processes, which act on different scales. First, the capability of the CRM in realistically simulating orographic cirrus clouds has been tested by comparing the simulated results to aircraft measurements of an orographic cirrus cloud. The influence of a warmer climate on the microphysical and optical properties of cirrus clouds has been investigated by initializing the CRM with vertical profiles of horizontal wind, potential temperature and equivalent potential temperature, respectively. The vertical profiles are extracted from IPCC A1B simulations for the current climate and for the period 2090–2099 for two regions representative for North and South America. The influence of additional moisture in a future climate on the propagation of gravity waves and the formation of orographic cirrus could be estimated. In a future climate, the increase in moisture dampens the vertical propagation of gravity waves and the occurring vertical velocities in the moist simulations. Together with higher temperatures fewer ice crystals nucleate homogeneously. Assuming that the relative humidity does not change in a warmer climate the specific humidity in the model is increased. This increase in specific humidity in a warmer climate results in a higher ice water content. The net effect of a reduced ice crystal number concentration and a higher ice water content is an increased optical depth. However, in some moist simulations dynamical changes contribute to changes in the ice water content, ice crystal number concentration and optical depth. For the corresponding dry simulations dynamical changes are more pronounced leading to a decreased optical depth in a future climate in some cases.

Climate variability and vadose zone controls on damping of transient recharge

Science.gov (United States)

Corona, Claudia R.; Gurdak, Jason J.; Dickinson, Jesse; Ferré, T.P.A.; Maurer, Edwin P.

2017-01-01

Increasing demand on groundwater resources motivates understanding of the controls on recharge dynamics so model predictions under current and future climate may improve. Here we address questions about the nonlinear behavior of flux variability in the vadose zone that may explain previously reported teleconnections between global-scale climate variability and fluctuations in groundwater levels. We use hundreds of HYDRUS-1D simulations in a sensitivity analysis approach to evaluate the damping depth of transient recharge over a range of periodic boundary conditions and vadose zone geometries and hydraulic parameters that are representative of aquifer systems of the conterminous United States (U.S). Although the models were parameterized based on U.S. aquifers, findings from this study are applicable elsewhere that have mean recharge rates between 3.65 and 730 mm yr–1. We find that mean infiltration flux, period of time varying infiltration, and hydraulic conductivity are statistically significant predictors of damping depth. The resulting framework explains why some periodic infiltration fluxes associated with climate variability dampen with depth in the vadose zone, resulting in steady-state recharge, while other periodic surface fluxes do not dampen with depth, resulting in transient recharge. We find that transient recharge in response to the climate variability patterns could be detected at the depths of water levels in most U.S. aquifers. Our findings indicate that the damping behavior of transient infiltration fluxes is linear across soil layers for a range of texture combinations. The implications are that relatively simple, homogeneous models of the vadose zone may provide reasonable estimates of the damping depth of climate-varying transient recharge in some complex, layered vadose zone profiles.

Climate Change Impacts on Future Wave Climate around the UK

Directory of Open Access Journals (Sweden)

William G. Bennett

2016-11-01

Full Text Available Understanding the changes in future storm wave climate is crucial for coastal managers and planners to make informed decisions required for sustainable coastal management and for the renewable energy industry. To investigate potential future changes to storm climate around the UK, global wave model outputs of two time slice experiments were analysed with 1979–2009 representing present conditions and 2075–2100 representing the future climate. Three WaveNet buoy sites around the United Kingdom, which represent diverse site conditions and have long datasets, were chosen for this study. A storm event definition (Dissanayake et al., 2015 was used to separate meteorologically-independent storm events from wave data, which in turn allowed storm wave characteristics to be analysed. Model outputs were validated through a comparison of the modelled storm data with observed storm data for overlapping periods. Although no consistent trends across all future clusters were observed, there were no significant increases in storm wave height, storm count or storm power in the future, at least according to the global wave projection results provided by the chosen model.

The impacts of future climate and carbon dioxide changes on the average and variability of US maize yields under two emission scenarios

International Nuclear Information System (INIS)

Urban, Daniel W; Lobell, David B; Sheffield, Justin

2015-01-01

The United States is the largest producer of maize in the world, a crop for which demand continues to rise rapidly. Past studies have projected that climate change will negatively impact mean maize yields in this region, while at the same time increasing yield variability. However, some have questioned the accuracy of these projections because they are often based on indirect measures of soil moisture, have failed to explicitly capture the potential interactions between temperature and soil moisture availability, and often omit the beneficial effects of elevated carbon dioxide (CO 2 ) on transpiration efficiency. Here we use a new detailed dataset on field-level yields in Iowa, Indiana, and Illinois, along with fine-resolution daily weather data and moisture reconstructions, to evaluate the combined effects of moisture and heat on maize yields in the region. Projected climate change scenarios over this region from a suite of CMIP5 models are then used to assess future impacts and the differences between two contrasting emissions scenarios (RCP 4.5 and RCP 8.5). We show that (i) statistical models which explicitly account for interactions between heat and moisture, which have not been represented in previous empirical models, lead to significant model improvement and significantly higher projected yield variability under warming and drying trends than when accounting for each factor independently; (ii) inclusion of the benefits of elevated CO 2 significantly reduces impacts, particularly for yield variability; and (iii) net damages from climate change and CO 2 become larger for the higher emission scenario in the latter half of the 21st century, and significantly so by the end of century. (paper)

Impacts of Climate Change on Native Landcover: Seeking Future Climatic Refuges

Science.gov (United States)

Mangabeira Albernaz, Ana Luisa

2016-01-01

Climate change is a driver for diverse impacts on global biodiversity. We investigated its impacts on native landcover distribution in South America, seeking to predict its effect as a new force driving habitat loss and population isolation. Moreover, we mapped potential future climatic refuges, which are likely to be key areas for biodiversity conservation under climate change scenarios. Climatically similar native landcovers were aggregated using a decision tree, generating a reclassified landcover map, from which 25% of the map’s coverage was randomly selected to fuel distribution models. We selected the best geographical distribution models among twelve techniques, validating the predicted distribution for current climate with the landcover map and used the best technique to predict the future distribution. All landcover categories showed changes in area and displacement of the latitudinal/longitudinal centroid. Closed vegetation was the only landcover type predicted to expand its distributional range. The range contractions predicted for other categories were intense, even suggesting extirpation of the sparse vegetation category. The landcover refuges under future climate change represent a small proportion of the South American area and they are disproportionately represented and unevenly distributed, predominantly occupying five of 26 South American countries. The predicted changes, regardless of their direction and intensity, can put biodiversity at risk because they are expected to occur in the near future in terms of the temporal scales of ecological and evolutionary processes. Recognition of the threat of climate change allows more efficient conservation actions. PMID:27618445

Impacts of Climate Change on Native Landcover: Seeking Future Climatic Refuges.

Directory of Open Access Journals (Sweden)

Marina Zanin

Full Text Available Climate change is a driver for diverse impacts on global biodiversity. We investigated its impacts on native landcover distribution in South America, seeking to predict its effect as a new force driving habitat loss and population isolation. Moreover, we mapped potential future climatic refuges, which are likely to be key areas for biodiversity conservation under climate change scenarios. Climatically similar native landcovers were aggregated using a decision tree, generating a reclassified landcover map, from which 25% of the map's coverage was randomly selected to fuel distribution models. We selected the best geographical distribution models among twelve techniques, validating the predicted distribution for current climate with the landcover map and used the best technique to predict the future distribution. All landcover categories showed changes in area and displacement of the latitudinal/longitudinal centroid. Closed vegetation was the only landcover type predicted to expand its distributional range. The range contractions predicted for other categories were intense, even suggesting extirpation of the sparse vegetation category. The landcover refuges under future climate change represent a small proportion of the South American area and they are disproportionately represented and unevenly distributed, predominantly occupying five of 26 South American countries. The predicted changes, regardless of their direction and intensity, can put biodiversity at risk because they are expected to occur in the near future in terms of the temporal scales of ecological and evolutionary processes. Recognition of the threat of climate change allows more efficient conservation actions.

Impacts of Austrian Climate Variability on Honey Bee Mortality

Science.gov (United States)

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'.

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

Science.gov (United States)

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.

Science.gov (United States)

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.

Harvesting Atlantic Cod under Climate Variability

Science.gov (United States)

Oremus, K. L.

2016-12-01

Previous literature links the growth of a fishery to climate variability. This study uses an age-structured bioeconomic model to compare optimal harvest in the Gulf of Maine Atlantic cod fishery under a variable climate versus a static climate. The optimal harvest path depends on the relationship between fishery growth and the interest rate, with higher interest rates dictating greater harvests now at the cost of long-term stock sustainability. Given the time horizon of a single generation of fishermen under assumptions of a static climate, the model finds that the economically optimal management strategy is to harvest the entire stock in the short term and allow the fishery to collapse. However, if the biological growth of the fishery is assumed to vary with climate conditions, such as the North Atlantic Oscillation, there will always be pulses of high growth in the stock. During some of these high-growth years, the growth of the stock and its economic yield can exceed the growth rate of the economy even under high interest rates. This implies that it is not economically optimal to exhaust the New England cod fishery if NAO is included in the biological growth function. This finding may have theoretical implications for the management of other renewable yet exhaustible resources whose growth rates are subject to climate variability.

Impacts of Climate Change and Climate Variability on Cocoa ...

African Journals Online (AJOL)

Impacts of Climate Change and Climate Variability on Cocoa ( Theobroma Cacao ) Yields in Meme Division, South West Region of Cameroon. ... Farm selection was based on age, consistency of sizes and management practices in an attempt to keep the factors affecting cocoa yield constant. Data on cocoa yield, flowering, ...

Responses of Montane Forest to Climate Variability in the Central Himalayas of Nepal

Directory of Open Access Journals (Sweden)

Janardan Mainali

2015-02-01

Full Text Available Climate changes are having dramatic ecological impacts in mid- to high-latitude mountain ranges where growth conditions are limited by climatic variables such as duration of growing season, moisture, and ambient temperature. We document patterns of forest vegetative response for 5 major alpine forest communities to current climate variability in the central Himalayas of Nepal to provide a baseline for assessment of future changes, as well as offer some insight into the trajectory of these changes over time. We used mean monthly surface air temperature and rainfall and the monthly averaged normalized difference vegetation index (NDVI to compare relative vegetation productivity among forest types and in relation to both climatic variables. Because changes in temperature and precipitation are directly manifested as changes in phenology, we examined current vegetative responses to climate variability in an effort to determine which climate variable is most critical for different alpine forest types. Our results show that correlations differ according to vegetation type and confirm that both precipitation and temperature affect monthly NDVI values, though more significant correlations were found with temperature data. The temperature response was more consistent because at the maximum increased temperatures, there was still an ongoing increase in vegetative vigor. This indicates that temperature is still the major limiting factor for plant growth at higher-elevation sites. This part of the Himalayas has abundant moisture, and some forest types are already saturated in terms of growth in relation to precipitation. Clear increases in productivity are documented on the upper treeline ecotones, and these systems are likely to continue to have increasing growth rates.

US Climate Variability and Predictability Project

Energy Technology Data Exchange (ETDEWEB)

Patterson, Mike [University Corporation for Atmospheric Research (UCAR), Boulder, CO (United States)

2017-11-14

The US CLIVAR Project Office administers the US CLIVAR Program with its mission to advance understanding and prediction of climate variability and change across timescales with an emphasis on the role of the ocean and its interaction with other elements of the Earth system. The Project Office promotes and facilitates scientific collaboration within the US and international climate and Earth science communities, addressing priority topics from subseasonal to centennial climate variability and change; the global energy imbalance; the ocean’s role in climate, water, and carbon cycles; climate and weather extremes; and polar climate changes. This project provides essential one-year support of the Project Office, enabling the participation of US scientists in the meetings of the US CLIVAR bodies that guide scientific planning and implementation, including the scientific steering committee that establishes program goals and evaluates progress of activities to address them, the science team of funded investigators studying the ocean overturning circulation in the Atlantic, and two working groups tackling the priority research topics of Arctic change influence on midlatitude climate and weather extremes and the decadal-scale widening of the tropical belt.

Climate-induced interannual variability of marine primary and export production in three global coupled climate carbon cycle models

Directory of Open Access Journals (Sweden)

B. Schneider

2008-04-01

Full Text Available Fully coupled climate carbon cycle models are sophisticated tools that are used to predict future climate change and its impact on the land and ocean carbon cycles. These models should be able to adequately represent natural variability, requiring model validation by observations. The present study focuses on the ocean carbon cycle component, in particular the spatial and temporal variability in net primary productivity (PP and export production (EP of particulate organic carbon (POC. Results from three coupled climate carbon cycle models (IPSL, MPIM, NCAR are compared with observation-based estimates derived from satellite measurements of ocean colour and results from inverse modelling (data assimilation. Satellite observations of ocean colour have shown that temporal variability of PP on the global scale is largely dominated by the permanently stratified, low-latitude ocean (Behrenfeld et al., 2006 with stronger stratification (higher sea surface temperature; SST being associated with negative PP anomalies. Results from all three coupled models confirm the role of the low-latitude, permanently stratified ocean for anomalies in globally integrated PP, but only one model (IPSL also reproduces the inverse relationship between stratification (SST and PP. An adequate representation of iron and macronutrient co-limitation of phytoplankton growth in the tropical ocean has shown to be the crucial mechanism determining the capability of the models to reproduce observed interactions between climate and PP.

Climate related diseases. Current regional variability and projections to the year 2100

Directory of Open Access Journals (Sweden)

Błażejczyk Krzysztof

2018-03-01

Full Text Available The health of individuals and societies depends on different factors including atmospheric conditions which influence humans in direct and indirect ways. The paper presents regional variability of some climate related diseases (CRD in Poland: salmonellosis intoxications, Lyme boreliosis, skin cancers (morbidity and mortality, influenza, overcooling deaths, as well as respiratory and circulatory mortality. The research consisted of two stages: 1 statistical modelling basing on past data and 2 projections of CRD for three SRES scenarios of climate change (A1B, A2, B1 to the year 2100. Several simple and multiply regression models were found for the relationships between climate variables and CRD. The models were applied to project future levels of CRD. At the end of 21st century we must expect increase in: circulatory mortality, Lyme boreliosis infections and skin cancer morbidity and mortality. There is also projected decrease in: respiratory mortality, overcooling deaths and influenza infections.

Disease in a more variable and unpredictable climate

Science.gov (United States)

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.

The Effects of Weather on Oilseed Rape (OSR) Yield in China: Future Implications of Climate Change

OpenAIRE

Yaqin He; Brian J. Revell; Bofeng Leng; Zhongchao Feng

2017-01-01

Understanding the role of climatic factors on crop yields is essential in predicting the future impact of climate change. In order to understand the influence of climatic factors on OSR, detailed farm-level panel data from 2566 farms across 67 counties of the 6 major OSR production regions in China, from the surveys conducted by the national OSR industry project between 2008 and 2013, were used to examine the contribution of changes in selected climatic variables between 2008 and 2013 to yiel...

Cocoa farming households' vulnerability to climate variability in Ekiti ...

African Journals Online (AJOL)

BRO OKOJIE

Rural livelihoods in south western Nigeria are at risk to climate variability on the short run and climate change on .... to reduce their vulnerability to climate variability as well as longer-term climate change. Nigeria has lost her leading role in exportation of cocoa. This has been attributed .... sizes and type of farm ownership.

Adaptation to climatic variability and change. Report of the task force on climate adaptation

International Nuclear Information System (INIS)

Smit, B.

1994-01-01

A critique and interpretation is presented of what is known and available about adaptation to climate changes, not based on any particular climate scenario. It is assumed that variability is a fact of climate and that changes in climatic conditions are possible and are constantly occurring. Emphasis is on adaptation with regard to economic and social activities in Canada. A series of linked objectives are addressed, relating to demonstration of the significance of adaptation, consideration of case studies of adaptation (past and potential future) in Canada, clarification of the meaning of adaptation and the forms it takes, assessment of policy implications, and identification of research priorities. The basic facts on global climate change are reviewed, including long-term temperature variations, and adaptation is discussed as a public policy response. Examples of adaptation in Canada are given in the areas of Great Lakes property, power generation, and transportation; Atlantic Canada communities and fisheries; forestry; the construction industry; the energy industry; recreation and tourism; agriculture; urban areas; and national defense. Recommendations regarding adapation are made to governments, the private sector, and researchers. An inventory of adaptation strategies for agriculture, the Arctic, coastal areas, ecosystems and land use, energy supply, fisheries, forestry, urban infrastructure, and water resources is appended

Climate change projections: past and future mysteries of climate science

International Nuclear Information System (INIS)

Meehl, Gerald A.

2007-01-01

Full text: Full text: The history of climate change has been wrapped in mysteries. Some have been solved, and we await the outcome of others. The major mystery of 20th century climate was why did temperatures rise in the early part of the century, level off, and then rise rapidly again after the 1970s? It has only been in the past seven years that advances in climate modelling have allowed us to deconstruct 20th century climate to pull apart the separate influences of natural and human-caused factors. This has allowed us to understand the subtle interplay between these various influences that produced the temperature time evolution. Another mystery has involved extreme weather and climate events. Again, climate models have allowed us to quantify how the small changes in average climate translate into much larger changes of regional extremes. The biggest remaining mysteries in climate science involve the future, and how the climate will evolve over the coming century. Up until now, various scenarios postulating different possible outcomes for 21st century climate, assuming different types of human activities, have been run in the climate models to provide a wide range of possible futures. However, more recently the outlook for global warming is being framed as a combination of mitigation and adaptation. If policy actions are taken to mitigate part of the problem of global warming, then climate models must be relied on to quantify the time-evolving picture of how much regional climate change we must adapt to. Solving this mystery will be the biggest and most important challenge ever taken on by the climate modelling community

Climate change feedbacks on future oceanic acidification

International Nuclear Information System (INIS)

McNeil, Ben I.; Matear, Richard J.

2007-01-01

Oceanic anthropogenic CO 2 uptake will decrease both the pH and the aragonite saturation state (Oarag) of seawater leading to an oceanic acidification. However, the factors controlling future changes in pH and Oarag are independent and will respond differently to oceanic climate change feedbacks such as ocean warming, circulation and biological changes. We examine the sensitivity of these two CO 2 -related parameters to climate change feedbacks within a coupled atmosphere-ocean model. The ocean warming feedback was found to dominate the climate change responses in the surface ocean. Although surface pH is projected to decrease relatively uniformly by about 0.3 by the year 2100, we find pH to be insensitive to climate change feedbacks, whereas Oarag is buffered by ∼15%. Ocean carbonate chemistry creates a situation whereby the direct pH changes due to ocean warming are almost cancelled by the pH changes associated with dissolved inorganic carbon concentrations changes via a reduction in CO 2 solubility from ocean warming. We show that the small climate change feedback on future surface ocean pH is independent to the amount of ocean warming. Our analysis therefore implies that future projections of surface ocean acidification only need to consider future atmospheric CO 2 levels, not climate change induced modifications in the ocean

Inferring climate variability from skewed proxy records

Science.gov (United States)

Emile-Geay, J.; Tingley, M.

2013-12-01

Many paleoclimate analyses assume a linear relationship between the proxy and the target climate variable, and that both the climate quantity and the errors follow normal distributions. An ever-increasing number of proxy records, however, are better modeled using distributions that are heavy-tailed, skewed, or otherwise non-normal, on account of the proxies reflecting non-normally distributed climate variables, or having non-linear relationships with a normally distributed climate variable. The analysis of such proxies requires a different set of tools, and this work serves as a cautionary tale on the danger of making conclusions about the underlying climate from applications of classic statistical procedures to heavily skewed proxy records. Inspired by runoff proxies, we consider an idealized proxy characterized by a nonlinear, thresholded relationship with climate, and describe three approaches to using such a record to infer past climate: (i) applying standard methods commonly used in the paleoclimate literature, without considering the non-linearities inherent to the proxy record; (ii) applying a power transform prior to using these standard methods; (iii) constructing a Bayesian model to invert the mechanistic relationship between the climate and the proxy. We find that neglecting the skewness in the proxy leads to erroneous conclusions and often exaggerates changes in climate variability between different time intervals. In contrast, an explicit treatment of the skewness, using either power transforms or a Bayesian inversion of the mechanistic model for the proxy, yields significantly better estimates of past climate variations. We apply these insights in two paleoclimate settings: (1) a classical sedimentary record from Laguna Pallcacocha, Ecuador (Moy et al., 2002). Our results agree with the qualitative aspects of previous analyses of this record, but quantitative departures are evident and hold implications for how such records are interpreted, and

Arctic climate change and decadal variability

NARCIS (Netherlands)

Linden, van der Eveline C.

2016-01-01

High northern latitudes exhibit enhanced near-surface warming in a climate with increasing greenhouse gases compared to other parts of the globe, indicating an amplified climate response to external forcing. Decadal to multidecadal variability sometimes enhances and at other times reduces the

a New Framework for Characterising Simulated Droughts for Future Climates

Science.gov (United States)

Sharma, A.; Rashid, M.; Johnson, F.

2017-12-01

Significant attention has been focussed on metrics for quantifying drought. Lesser attention has been given to the unsuitability of current metrics in quantifying drought in a changing climate due to the clear non-stationarity in potential and actual evapotranspiration well into the future (Asadi-Zarch et al, 2015). This talk presents a new basis for simulating drought designed specifically for use with climate model simulations. Given the known uncertainty of climate model rainfall simulations, along with their inability to represent low-frequency variability attributes, the approach here adopts a predictive model for drought using selected atmospheric indicators. This model is based on a wavelet decomposition of relevant atmospheric predictors to filter out less relevant frequencies and formulate a better characterisation of the drought metric chosen as response. Once ascertained using observed precipication and associated atmospheric variables, these can be formulated from GCM simulations using a multivariate bias correction tool (Mehrotra and Sharma, 2016) that accounts for low-frequency variability, and a regression tool that accounts for nonlinear dependence (Sharma and Mehrotra, 2014). Use of only the relevant frequencies, as well as the corrected representation of cross-variable dependence, allows greater accuracy in characterising observed drought, from GCM simulations. Using simulations from a range of GCMs across Australia, we show here that this new method offers considerable advantages in representing drought compared to traditionally followed alternatives that rely on modelled rainfall instead. Reference:Asadi Zarch, M. A., B. Sivakumar, and A. Sharma (2015), Droughts in a warming climate: A global assessment of Standardized precipitation index (SPI) and Reconnaissance drought index (RDI), Journal of Hydrology, 526, 183-195. Mehrotra, R., and A. Sharma (2016), A Multivariate Quantile-Matching Bias Correction Approach with Auto- and Cross

Observations of Local Positive Low Cloud Feedback Patterns and Their Role in Internal Variability and Climate Sensitivity

Science.gov (United States)

Yuan, Tianle; Oreopoulos, Lazaros; Platnick, Steven E.; Meyer, Kerry

2018-05-01

Modeling studies have shown that cloud feedbacks are sensitive to the spatial pattern of sea surface temperature (SST) anomalies, while cloud feedbacks themselves strongly influence the magnitude of SST anomalies. Observational counterparts to such patterned interactions are still needed. Here we show that distinct large-scale patterns of SST and low-cloud cover (LCC) emerge naturally from objective analyses of observations and demonstrate their close coupling in a positive local SST-LCC feedback loop that may be important for both internal variability and climate change. The two patterns that explain the maximum amount of covariance between SST and LCC correspond to the Interdecadal Pacific Oscillation and the Atlantic Multidecadal Oscillation, leading modes of multidecadal internal variability. Spatial patterns and time series of SST and LCC anomalies associated with both modes point to a strong positive local SST-LCC feedback. In many current climate models, our analyses suggest that SST-LCC feedback strength is too weak compared to observations. Modeled local SST-LCC feedback strength affects simulated internal variability so that stronger feedback produces more intense and more realistic patterns of internal variability. To the extent that the physics of the local positive SST-LCC feedback inferred from observed climate variability applies to future greenhouse warming, we anticipate significant amount of delayed warming because of SST-LCC feedback when anthropogenic SST warming eventually overwhelm the effects of internal variability that may mute anthropogenic warming over parts of the ocean. We postulate that many climate models may be underestimating both future warming and the magnitude of modeled internal variability because of their weak SST-LCC feedback.

Climate variability and demand growth as drivers of water scarcity in the Turkwel river basin: a bottom-up risk assessment of a data-sparse basin in Kenya

Science.gov (United States)

Hirpa, F. A.; Dyer, E.; Hope, R.; Dadson, S. J.

2017-12-01

Sustainable water management and allocation are essential for maintaining human well-being, sustaining healthy ecosystems, and supporting steady economic growth. The Turkwel river basin, located in north-western Kenya, experiences a high level of water scarcity due to its arid climate, high rainfall variability, and rapidly growing water demand. However, due to sparse hydro-climatic data and limited literature, the water resources system of the basin has been poorly understood. Here we apply a bottom-up climate risk assessment method to estimate the resilience of the basin's water resources system to growing demand and climate stressors. First, using a water resource system model and historical climate data, we construct a climate risk map that depicts the way in which the system responds to climate change and variability. Then we develop a set of water demand scenarios to identify the conditions that potentially lead to the risk of unmet water demand and groundwater depletion. Finally, we investigate the impact of climate change and variability by stress testing these development scenarios against historically strong El Niño/Southern Oscillation (ENSO) years and future climate projections from multiple Global Circulation Models (GCMs). The results reveal that climate variability and increased water demand are the main drivers of water scarcity in the basin. Our findings show that increases in water demand due to expanded irrigation and population growth exert the strongest influence on the ability of the system to meet water resource supply requirements, and in all cases considered increase the impacts of droughts caused by future climate variability. Our analysis illustrates the importance of combining analysis of future climate risks with other development decisions that affect water resources planning. Policy and investment decisions which maximise water use efficiency in the present day are likely to impart resilience to climate change and variability under a

Effects of interannual climate variability on tropical tree cover

NARCIS (Netherlands)

Holmgren, M.; Hirota, M.; Nes, van E.H.; Scheffer, M.

2013-01-01

Climatic warming is substantially intensifying the global water cycle1 and is projected to increase rainfall variability2. Using satellite data, we show that higher climatic variability is associated with reduced tree cover in the wet tropics globally. In contrast, interannual variability in

Climate Variability and Phytoplankton in the Pacific Ocean

Science.gov (United States)

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 (pphytoplankton 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.

Modelling the impact of future socio-economic and climate change scenarios on river microbial water quality.

Science.gov (United States)

Islam, M M Majedul; Iqbal, Muhammad Shahid; Leemans, Rik; Hofstra, Nynke

2018-03-01

Microbial surface water quality is important, as it is related to health risk when the population is exposed through drinking, recreation or consumption of irrigated vegetables. The microbial surface water quality is expected to change with socio-economic development and climate change. This study explores the combined impacts of future socio-economic and climate change scenarios on microbial water quality using a coupled hydrodynamic and water quality model (MIKE21FM-ECOLab). The model was applied to simulate the baseline (2014-2015) and future (2040s and 2090s) faecal indicator bacteria (FIB: E. coli and enterococci) concentrations in the Betna river in Bangladesh. The scenarios comprise changes in socio-economic variables (e.g. population, urbanization, land use, sanitation and sewage treatment) and climate variables (temperature, precipitation and sea-level rise). Scenarios have been developed building on the most recent Shared Socio-economic Pathways: SSP1 and SSP3 and Representative Concentration Pathways: RCP4.5 and RCP8.5 in a matrix. An uncontrolled future results in a deterioration of the microbial water quality (+75% by the 2090s) due to socio-economic changes, such as higher population growth, and changes in rainfall patterns. However, microbial water quality improves under a sustainable scenario with improved sewage treatment (-98% by the 2090s). Contaminant loads were more influenced by changes in socio-economic factors than by climatic change. To our knowledge, this is the first study that combines climate change and socio-economic development scenarios to simulate the future microbial water quality of a river. This approach can also be used to assess future consequences for health risks. Copyright © 2017 The Authors. Published by Elsevier GmbH.. All rights reserved.

Comparing farmers' perception of climate change and variability with ...

African Journals Online (AJOL)

Perception of climate change and variability supported by local knowledge has helped to advance understanding of climate change and its impacts on agricultural land-use systems. This study compares farmers' perception of climate change and variability in four communities of the Upper East Region of Ghana. Using a ...

Future climate change over Southern Africa

CSIR Research Space (South Africa)

Davis, Claire L

2017-10-01

Full Text Available This chapter presents key messages drawn from recent subsets of future climate projections for the southern Africa region. Material in this chapter is drawn from Chapter 3 of Climate Risk and Vulnerability: A Handbook for Southern Africa (Davis 2011...

Effects of short-term variability of meteorological variables on soil temperature in permafrost regions

Science.gov (United States)

Beer, Christian; Porada, Philipp; Ekici, Altug; Brakebusch, Matthias

2018-03-01

Effects of the short-term temporal variability of meteorological variables on soil temperature in northern high-latitude regions have been investigated. For this, a process-oriented land surface model has been driven using an artificially manipulated climate dataset. Short-term climate variability mainly impacts snow depth, and the thermal diffusivity of lichens and bryophytes. These impacts of climate variability on insulating surface layers together substantially alter the heat exchange between atmosphere and soil. As a result, soil temperature is 0.1 to 0.8 °C higher when climate variability is reduced. Earth system models project warming of the Arctic region but also increasing variability of meteorological variables and more often extreme meteorological events. Therefore, our results show that projected future increases in permafrost temperature and active-layer thickness in response to climate change will be lower (i) when taking into account future changes in short-term variability of meteorological variables and (ii) when representing dynamic snow and lichen and bryophyte functions in land surface models.

Input variable selection for interpolating high-resolution climate ...

African Journals Online (AJOL)

Although the primary input data of climate interpolations are usually meteorological data, other related (independent) variables are frequently incorporated in the interpolation process. One such variable is elevation, which is known to have a strong influence on climate. This research investigates the potential of 4 additional ...

Empirical methods for estimating future climatic conditions

International Nuclear Information System (INIS)

Anon.

1990-01-01

Applying the empirical approach permits the derivation of estimates of the future climate that are nearly independent of conclusions based on theoretical (model) estimates. This creates an opportunity to compare these results with those derived from the model simulations of the forthcoming changes in climate, thus increasing confidence in areas of agreement and focusing research attention on areas of disagreements. The premise underlying this approach for predicting anthropogenic climate change is based on associating the conditions of the climatic optimums of the Holocene, Eemian, and Pliocene with corresponding stages of the projected increase of mean global surface air temperature. Provided that certain assumptions are fulfilled in matching the value of the increased mean temperature for a certain epoch with the model-projected change in global mean temperature in the future, the empirical approach suggests that relationships leading to the regional variations in air temperature and other meteorological elements could be deduced and interpreted based on use of empirical data describing climatic conditions for past warm epochs. Considerable care must be taken, of course, in making use of these spatial relationships, especially in accounting for possible large-scale differences that might, in some cases, result from different factors contributing to past climate changes than future changes and, in other cases, might result from the possible influences of changes in orography and geography on regional climatic conditions over time

Ecoclimatic indicators to study crop suitability in present and future climatic conditions

Science.gov (United States)

Caubel, Julie; Garcia de Cortazar Atauri, Inaki; Huard, Frédéric; Launay, Marie; Ripoche, Dominique; Gouache, David; Bancal, Marie-Odile; Graux, Anne-Isabelle; De Noblet, Nathalie

2013-04-01

Climate change is expected to affect both regional and global food production through changes in overall agroclimatic conditions. It is therefore necessary to develop simple tools of crop suitability diagnosis in a given area so that stakeholders can envisage land use adaptations under climate change conditions. The most common way to investigate potential impacts of climate on the evolution of agrosystems is to make use of an array of agroclimatic indicators, which provide synthetic information derived from climatic variables and calculated within fixed periods (i.e. January first - 31th July). However, the information obtained during these periods does not enable to take account of the plant response to climate. In this work, we present some results of the research program ORACLE (Opportunities and Risks of Agrosystems & forests in response to CLimate, socio-economic and policy changEs in France (and Europe). We proposed a suite of relevant ecoclimatic indicators, based on temperature and rainfall, in order to evaluate crop suitability for both present and new climatic conditions. Ecoclimatic indicators are agroclimatic indicators (e.g., grain heat stress) calculated during specific phenological phases so as to take account of the plant response to climate (e.g., the grain filling period, flowering- harvest). These indicators are linked with the ecophysiological processes they characterize (for e.g., the grain filling). To represent this methodology, we studied the suitability of winter wheat in future climatic conditions through three distinct French sites, Toulouse, Dijon and Versailles. Indicators have been calculated using climatic data from 1950 to 2100 simulated by the global climate model ARPEGE forced by a greenhouse effect corresponding to the SRES A1B scenario. The Quantile-Quantile downscaling method was applied to obtain data for the three locations. Phenological stages (emergence, ear 1 cm, flowering, beginning of grain filling and harvest) have been

Effects of climatic variability and change on forest ecosystems: a comprehensive science synthesis for the U.S

Science.gov (United States)

James M. Vose; David L. Peterson; Toral Patel-Weynand

2012-01-01

This report is a scientific assessment of the current condition and likely future condition of forest resources in the United States relative to climatic variability and change. It serves as the U.S. Forest Service forest sector technical report for the National Climate Assessment and includes descriptions of key regional issues and examples of a risk-based framework...

The future of hydropower in Europe: Interconnecting climate, markets and policies

International Nuclear Information System (INIS)

Gaudard, Ludovic; Romerio, Franco

2014-01-01

Highlights: • Connecting the knowledges from various domains, in particular economics, engineering, policy and hydrology. • Giving the keys to assess the linking between hydropower, climate and electricity market. • Making an overall analysis. - Abstract: Hydropower is very important for electricity supply security in the European inter-connexion as well as for the economy of regions (primarily peripheral) that possess water resources. Its future may however be jeopardized by several factors: climate change, the development of new renewable energy, the creation of super and micro-grids, and progress in power storage technology. Energy and climate policy, as well as electricity market design and dynamics play a pivotal role. This article carries out a comprehensive analysis of all these factors and discusses the future of hydropower. This discussion follows an overview of the present situation and of future drivers. The technical, environmental, economic and political aspects of the problem are analyzed with an interdisciplinary approach. The stakes as well as the uncertainties are highlighted. The conclusion is that hydropower has a promising future, particularly in light of emerging sustainable energy policy, but that the risks should not be overlooked. Academics will find a comprehensive interdisciplinary analysis of hydropower in this article, whereas public bodies, communities and hydropower companies can identify the strategic variables that should be taken into consideration in the decision making process. The end of water concessions or authorizations is also evoked

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

Science.gov (United States)

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.

Regionalizing Africa: Patterns of Precipitation Variability in Observations and Global Climate Models

Science.gov (United States)

Badr, Hamada S.; Dezfuli, Amin K.; Zaitchik, Benjamin F.; Peters-Lidard, Christa D.

2016-01-01

Many studies have documented dramatic climatic and environmental changes that have affected Africa over different time scales. These studies often raise questions regarding the spatial extent and regional connectivity of changes inferred from observations and proxies and/or derived from climate models. Objective regionalization offers a tool for addressing these questions. To demonstrate this potential, applications of hierarchical climate regionalizations of Africa using observations and GCM historical simulations and future projections are presented. First, Africa is regionalized based on interannual precipitation variability using Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data for the period 19812014. A number of data processing techniques and clustering algorithms are tested to ensure a robust definition of climate regions. These regionalization results highlight the seasonal and even month-to-month specificity of regional climate associations across the continent, emphasizing the need to consider time of year as well as research question when defining a coherent region for climate analysis. CHIRPS regions are then compared to those of five GCMs for the historic period, with a focus on boreal summer. Results show that some GCMs capture the climatic coherence of the Sahel and associated teleconnections in a manner that is similar to observations, while other models break the Sahel into uncorrelated subregions or produce a Sahel-like region of variability that is spatially displaced from observations. Finally, shifts in climate regions under projected twenty-first-century climate change for different GCMs and emissions pathways are examined. A projected change is found in the coherence of the Sahel, in which the western and eastern Sahel become distinct regions with different teleconnections. This pattern is most pronounced in high-emissions scenarios.

Climate variability and sustainable food production: Insights from ...

African Journals Online (AJOL)

The past two decades have seen invigorated debates on the causal link between climate variability and food crop production. This study[1] extends the debate further by investigating how climate variability has affected the production of four specific food crops: maize, millet, rice, and groundnuts in north-eastern Ghana.

Economic perspectives on the impact of climate variability and change: A summary report

International Nuclear Information System (INIS)

Timmerman, P.; Grima, A.P.

1988-01-01

A summary is presented of a collection of papers on the economic methodologies applicable to studies of the impact of global climate variability and change. The research was sponsored by the Canadian Climate program and was conducted as part of a project investigating the potential impacts on various sectors of the Canadian economy of climate warming due to the greenhouse effect. Topics of the papers include microeconomic analysis, benefit/cost analysis, input-output analysis, policy options regarding water levels in the Great Lakes, the scenario approach to assessing socio-economic sensitivities to climate change in the agri-food sector, and analysis of weather impacts. Several analytical tools are seen to be readily applicable to economic analyses of the effects of climate change, and issues of future water supply and demand are seen as central to climate impact assessment, and of particular concern to Canada

Electricity consumption and climate, relationship with climatic variable

International Nuclear Information System (INIS)

Fonte Hernandez, Aramis; Rivero Jaspe, Zoltan

2004-01-01

Perhaps, since in the world people is more concerned about the possibility of climatic impact on the energy consumption, actually it is an attractive theme not only for undeveloped countries, but also for developed. In this work, a study on the electricity consumption of residential sector in the province of Camaguey, Cuba, during the last ten years of X X century, was done. In it, climatic variables like temperature, relative humidity, sunshine hours, and wind speed, were included. Specifically, in the case of temperature, it was used both in its primitive form, and like a derived variable in the form of degree-day. For this reason, firstly the appropriate value of base temperature for the area under study was determined, obtaining a value of 23.6 Celsius Degrade. After that, using nonlinear regression analysis, statistical models with acceptable predictive capacity, were obtained

Future projection of mean and variability of the Asian Summer Monsoon and Indian Ocean Climate systems

Energy Technology Data Exchange (ETDEWEB)

Annamalai, H. [Univ. of Hawaii, Honolulu, HI (United States)

2014-09-15

The overall goal of this project is to assess the ability of the CMIP3/5 models to simulate the Indian-Ocean monsoon systems. The PI along with post-docs investigated research issues ranging from synoptic systems to long-term trends over the Asian monsoon region. The PI applied diagnostic tools such as moist static energy (MSE) to isolate: the moist and radiative processes responsible for extended monsoon breaks over South Asia, precursors in the ENSO-monsoon association, reasons for the drying tendency over South Asia and the possible effect on tropical Indian Ocean climate anomalies influencing certain aspects of ENSO characteristics. By diagnosing various observations and coupled model simulations, we developed working hypothesis and tested them by carrying out sensitivity experiments with both linear and nonlinear models. Possible physical and dynamical reasons for model sensitivities were deduced. On the teleconnection front, the ability of CMIP5 models in representing the monsoon-desert mechanism was examined recently. Further more, we have applied a suite of diagnostics and have performed an in depth analysis on CMIP5 integrations to isolate the possible reasons for the ENSO-monsoon linkage or lack thereof. The PI has collaborated with Dr. K.R. Sperber of PCMDI and other CLIVAR Asian-Australian monsoon panel members in understanding the ability of CMIP3/5 models in capturing monsoon and its spectrum of variability. The objective and process-based diagnostics aided in selecting models that best represent the present-day monsoon and its variability that are then employed for future projections. Two major highlights were an invitation to write a review on present understanding monsoons in a changing climate in Nature Climate Change, and identification of an east-west shift in observed monsoon rainfall (more rainfall over tropical western Pacific and drying tendency over South Asia) in the last six decades and attributing that shift to SST rise over the tropical

Contrasted demographic responses facing future climate change in Southern Ocean seabirds.

Science.gov (United States)

Barbraud, Christophe; Rivalan, Philippe; Inchausti, Pablo; Nevoux, Marie; Rolland, Virginie; Weimerskirch, Henri

2011-01-01

1. Recent climate change has affected a wide range of species, but predicting population responses to projected climate change using population dynamics theory and models remains challenging, and very few attempts have been made. The Southern Ocean sea surface temperature and sea ice extent are projected to warm and shrink as concentrations of atmospheric greenhouse gases increase, and several top predator species are affected by fluctuations in these oceanographic variables. 2. We compared and projected the population responses of three seabird species living in sub-tropical, sub-Antarctic and Antarctic biomes to predicted climate change over the next 50 years. Using stochastic population models we combined long-term demographic datasets and projections of sea surface temperature and sea ice extent for three different IPCC emission scenarios (from most to least severe: A1B, A2, B1) from general circulation models of Earth's climate. 3. We found that climate mostly affected the probability to breed successfully, and in one case adult survival. Interestingly, frequent nonlinear relationships in demographic responses to climate were detected. Models forced by future predicted climatic change provided contrasted population responses depending on the species considered. The northernmost distributed species was predicted to be little affected by a future warming of the Southern Ocean, whereas steep declines were projected for the more southerly distributed species due to sea surface temperature warming and decrease in sea ice extent. For the most southerly distributed species, the A1B and B1 emission scenarios were respectively the most and less damaging. For the two other species, population responses were similar for all emission scenarios. 4. This is among the first attempts to study the demographic responses for several populations with contrasted environmental conditions, which illustrates that investigating the effects of climate change on core population dynamics

Temporal relationship between climate variability, Prosopis juliflora ...

African Journals Online (AJOL)

Kyuma

Key words: Climate, drylands, livestock, Prosopis juliflora, variability vegetation, trends, mesquite. ... climate change is costly and predictions are that both it and its cost will escalate ... Resilience Alliance, 2010; Tennigkeit and Wilkes, 2008;.

Climate Change and Variability in Ghana: Stocktaking

Directory of Open Access Journals (Sweden)

Felix A. Asante

2014-12-01

Full Text Available This paper provides a holistic literature review of climate change and variability in Ghana by examining the impact and projections of climate change and variability in various sectors (agricultural, health and energy and its implication on ecology, land use, poverty and welfare. The findings suggest that there is a projected high temperature and low rainfall in the years 2020, 2050 and 2080, and desertification is estimated to be proceeding at a rate of 20,000 hectares per annum. Sea-surface temperatures will increase in Ghana’s waters and this will have drastic effects on fishery. There will be a reduction in the suitability of weather within the current cocoa-growing areas in Ghana by 2050 and an increase evapotranspiration of the cocoa trees. Furthermore, rice and rooted crops (especially cassava production are expected to be low. Hydropower generation is also at risk and there will be an increase in the incidence rate of measles, diarrheal cases, guinea worm infestation, malaria, cholera, cerebro-spinal meningitis and other water related diseases due to the current climate projections and variability. These negative impacts of climate change and variability worsens the plight of the poor, who are mostly women and children.

THE EFFECTS OF CLIMATIC VARIABLES AND CROP AREA ON MAIZE YIELD AND VARIABILITY IN GHANA

Directory of Open Access Journals (Sweden)

Henry De-Graft Acquah

2012-10-01

Full Text Available Climate change tends to have negative effects on crop yield through its influence on crop production. Understanding the relationship between climatic variables and crop area on the mean and variance of crop yield will facilitate development of appropriate policies to cope with climate change. This paper examines the effects of climatic variables and crop area on the mean and variance of maize yield in Ghana. The Just and Pope stochastic production function using the Cobb-Douglas functional form was employed. The results show that average maize yield is positively related to crop area and negatively related to rainfall and temperature. Furthermore, increase in crop area and temperature will enlarge maize yield variability while rainfall increase will decrease the variability in maize yield.

Climate variability and impacts on east African livestock herders: the ...

African Journals Online (AJOL)

Climate variability and impacts on east African livestock herders: the Maasai of ... and vulnerability to climate variability and climate change is assessed, using data ... Model results suggest that the ecosystem is quite resilient and suggests that ...

The effect of future outdoor air pollution on human health and the contribution of climate change

Science.gov (United States)

Silva, R.; West, J. J.; Lamarque, J.; Shindell, D.; Collins, W.; Dalsoren, S. B.; Faluvegi, G. S.; Folberth, G.; Horowitz, L. W.; Nagashima, T.; Naik, V.; Rumbold, S.; Skeie, R.; Sudo, K.; Takemura, T.; Bergmann, D. J.; Cameron-Smith, P. J.; Cionni, I.; Doherty, R. M.; Eyring, V.; Josse, B.; MacKenzie, I. A.; Plummer, D.; Righi, M.; Stevenson, D. S.; Strode, S. A.; Szopa, S.; Zeng, G.

2013-12-01

At present, exposure to outdoor air pollution from ozone and fine particulate matter (PM2.5) causes over 2 million deaths per year, due to respiratory and cardiovascular diseases and lung cancer. Future ambient concentrations of ozone and PM2.5 will be affected by both air pollutant emissions and climate change. Here we estimate the potential impact of future outdoor air pollution on premature human mortality, and isolate the contribution of future climate change due to its effect on air quality. We use modeled present-day (2000) and future global ozone and PM2.5 concentrations from simulations with an ensemble of chemistry-climate models from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Future air pollution was modeled for global greenhouse gas and air pollutant emissions in the four IPCC AR5 Representative Concentration Pathway (RCP) scenarios, for 2030, 2050 and 2100. All model outputs are regridded to a common 0.5°x0.5° horizontal resolution. Future premature mortality is estimated for each RCP scenario and year based on changes in concentrations of ozone and PM2.5 relative to 2000. Using a health impact function, changes in concentrations for each RCP scenario are combined with future population and cause-specific baseline mortality rates as projected by a single independent scenario in which the global incidence of cardiopulmonary diseases is expected to increase. The effect of climate change is isolated by considering the difference between air pollutant concentrations from simulations with 2000 emissions and a future year climate and simulations with 2000 emissions and climate. Uncertainties in the results reflect the uncertainty in the concentration-response function and that associated with variability among models. Few previous studies have quantified the effects of future climate change on global human health via changes in air quality, and this is the first such study to use an ensemble of global models.

A plant's perspective of extremes: terrestrial plant responses to changing climatic variability.

Science.gov (United States)

Reyer, Christopher P O; Leuzinger, Sebastian; Rammig, Anja; Wolf, Annett; Bartholomeus, Ruud P; Bonfante, Antonello; de Lorenzi, Francesca; Dury, Marie; Gloning, Philipp; Abou Jaoudé, Renée; Klein, Tamir; Kuster, Thomas M; Martins, Monica; Niedrist, Georg; Riccardi, Maria; Wohlfahrt, Georg; de Angelis, Paolo; de Dato, Giovanbattista; François, Louis; Menzel, Annette; Pereira, Marízia

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, although potentially damaging. We note that plant water relations seem to be very vulnerable to extremes driven by changes in temperature and precipitation and that heat-waves 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. © 2012 Blackwell Publishing Ltd.

Impacts of Climate Change on Native Landcover: Seeking Future Climatic Refuges

OpenAIRE

Zanin, Marina; Mangabeira Albernaz, Ana Luisa

2016-01-01

Climate change is a driver for diverse impacts on global biodiversity. We investigated its impacts on native landcover distribution in South America, seeking to predict its effect as a new force driving habitat loss and population isolation. Moreover, we mapped potential future climatic refuges, which are likely to be key areas for biodiversity conservation under climate change scenarios. Climatically similar native landcovers were aggregated using a decision tree, generating a reclassified l...

Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

Science.gov (United States)

Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos

2016-01-01

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

Multi-wheat-model ensemble responses to interannual climatic variability

DEFF Research Database (Denmark)

Ruane, A C; Hudson, N I; Asseng, S

2016-01-01

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981–2010 grain yield, and ......-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.......We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981–2010 grain yield, and we...... evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal...

Climate and society: passed climates, man era, future climate: essential reference marks; Climat et societe: Climats passes, passage de l'homme, climat futur: reperes essentiels

Energy Technology Data Exchange (ETDEWEB)

Melieres, M.A.; Marechal, Ch.

2010-07-01

This teaching book takes stock of the climate change question which has moved beyond the simple scientific framework. Man will play a key role in the changes to come and the choices he is going to make will have a major impact on our environment and on our societies. The aim of this book is to draw out the essential marks from the multiple disciplines involved in the study of climate change in order to get a global overview of the question. Starting from simple mechanisms showing up the driving components of the climate equilibrium (like the greenhouse effect), the authors analyse the climates of the past, and describe the different causes of the actual climate change and its possible evolution in the future. The global nature of the climate warming in progress is demonstrated and some of its actual impacts on the environment are shown up. The importance of the anthropic influence in this change is underlined as well as the stakes of the mastery of our greenhouse gas emissions. (J.S.)

Pastoral suitability driven by future climate change along the Apennines

Directory of Open Access Journals (Sweden)

Camilla Dibari

2015-09-01

Full Text Available This work aims at evaluating the impacts of climate change on pastoral resources located along the Apennines chain. To this end, random forest machine learning model was first calibrated for the present period and then applied to future conditions, as projected by HadCM3 general circulation model, in order to simulate possible spatial variation/shift of pastoral areas in two time slices (centred on 2050 and 2080 under A2 and B2 SRES scenarios. Pre-existent spatial database, namely Corine land cover map and WorldClim, were integrated and harmonised in a GIS environment in order to extract climate variables (mean seasonal precipitation, mean maximum temperature of the warmest month and minimum temperature of the coldest month and response variables (presence/absence of pastures to be used as model predictors. Random forest model resulted robust and coherent to simulate pastureland suitability under current climatology (classification accuracy error=19%. Accordingly, results indicated that increases in temperatures coupled with decreases in precipitation, as simulated by HadCM3 in the future, would have impacts of great concern on potential pasture distribution. In the specific, an overall decline of pasturelands suitability is predicted by the middle of the century in both A2 (–46% and B2 (–41% along the entire chain. However, despite alarming reductions in pastures suitability along the northern (–69% and –71% under A2 and B2 scenarios, respectively and central Apennines (–90% under both scenarios by the end of the century, expansions are predicted along the southern areas of the chain (+96% and +105% under A2 and B2 scenarios, respectively. This may be probably due to expansions in pastures dominated by xeric and thermophiles species, which will likely benefit from warmer and drier future conditions predicted in the southern zone of the chain by the HadCM3. Hence, the expected climate, coupled with an increasing abandonment of the

Climatic Change--Past, Present & Future

Science.gov (United States)

Lindholm, Roy C.

1976-01-01

Presented is a review of studies investigating factors affecting climatic changes in the Earth's atmosphere--past, present, and future. Dating methods, particularly the Oxygen 18/16 method, are discussed. (SL)

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

Science.gov (United States)

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.

Future road salt use in Switzerland: an example of an effective climate service

Science.gov (United States)

Zubler, Elias M.; Fischer, Andreas M.; Schlegel, Thomas H.; Liniger, Mark A.

2015-04-01

The application of salt is the predominant measure taken to enhance road safety in Switzerland by clearing the roads from snow or preventing frozen surfaces during winter. The need for road salt exhibits a strong interannual variability, according to Schweizer Salinen AG - the Swiss monopolist for production and distribution of road salt. These fluctuations are to a large extent a direct consequence of the year-to-year variability in winter climate. In the course of the 21st century, Swiss climate is projected to depart significantly from present and past conditions. By the end of the century, winter temperatures over Switzerland are expected to rise by about 2-4°C relative to the mean over the period 1980-2009, while winter precipitation may either increase or decrease based on ENSEMBLES regional climate model projections under the SRES-scenario A1B. Faced with these changes, Schweizer Salinen AG asked for an estimate of the expected future road salt use for designing their long-term business strategy. The study is based on climate change projections from the CH2011 initiative and later extensions thereof as well as monthly sales data of road salt from Schweizer Salinen AG. For the period 1997-2013, a linear relationship was derived between the average number of days with snowfall and the road salt amount sold over "saltation years" defined from October 1st to September 30th in the 26 cantons (provinces) of Switzerland. The ad-hoc linear relationship was applied to the climate change projections to obtain future salt use information in three future periods for the greenhouse gas emission scenarios A1B, A2 and RCP3PD. We find that the expected future salt use is likely to be reduced by about 50% in 2045-2074 under the scenario A1B. Currently, the countrywide mean annual road salt use corresponds to about 220'000 tons. In a particularly snow-rich year, the company sells up to 400'000 tons. At the end of the century, following a pessimistic scenario such as A1B or A

Quantifying the Relative Contributions of Forest Change and Climatic Variability to Hydrology in Large Watersheds: A Critical Review of Research Methods

Directory of Open Access Journals (Sweden)

Xiaohua Wei

2013-06-01

Full Text Available Forest change and climatic variability are two major drivers for influencing change in watershed hydrology in forest–dominated watersheds. Quantifying their relative contributions is important to fully understand their individual effects. This review paper summarizes the progress on quantifying the relative contributions of forest or land cover change and climatic variability to hydrology in large watersheds using available case studies. It compared pros and cons of various research methods, identified research challenges and proposed future research priorities. Our synthesis shows that the relative hydrological effects of forest changes and climatic variability are largely dependent on their own change magnitudes and watershed characteristics. In some severely disturbed watersheds, impacts of forest changes or land use changes can be as important as those from climatic variability. This paper provides a brief review on eight selected research methods for this type of research. Because each method or technique has its own strengths and weaknesses, combining two or more methods is a more robust approach than using any single method alone. Future research priorities include conducting more case studies, refining research methods, and considering mechanism-based research using landscape ecology and geochemistry approaches.

Revisiting historical climatic signals to better explore the future: prospects of water cycle changes in Central Sahel

Science.gov (United States)

Leauthaud, C.; Demarty, J.; Cappelaere, B.; Grippa, M.; Kergoat, L.; Velluet, C.; Guichard, F.; Mougin, E.; Chelbi, S.; Sultan, B.

2015-06-01

Rainfall and climatic conditions are the main drivers of natural and cultivated vegetation productivity in the semiarid region of Central Sahel. In a context of decreasing cultivable area per capita, understanding and predicting changes in the water cycle are crucial. Yet, it remains challenging to project future climatic conditions in West Africa since there is no consensus on the sign of future precipitation changes in simulations coming from climate models. The Sahel region has experienced severe climatic changes in the past 60 years that can provide a first basis to understand the response of the water cycle to non-stationary conditions in this part of the world. The objective of this study was to better understand the response of the water cycle to highly variable climatic regimes in Central Sahel using historical climate records and the coupling of a land surface energy and water model with a vegetation model that, when combined, simulated the Sahelian water, energy and vegetation cycles. To do so, we relied on a reconstructed long-term climate series in Niamey, Republic of Niger, in which three precipitation regimes can be distinguished with a relative deficit exceeding 25% for the driest period compared to the wettest period. Two temperature scenarios (+2 and +4 °C) consistent with future warming scenarios were superimposed to this climatic signal to generate six virtual future 20-year climate time series. Simulations by the two coupled models forced by these virtual scenarios showed a strong response of the water budget and its components to temperature and precipitation changes, including decreases in transpiration, runoff and drainage for all scenarios but those with highest precipitation. Such climatic changes also strongly impacted soil temperature and moisture. This study illustrates the potential of using the strong climatic variations recorded in the past decades to better understand potential future climate variations.

Historical and future seasonal rainfall variability in Nusa Tenggara Barat Province, Indonesia: Implications for the agriculture and water sectors

Directory of Open Access Journals (Sweden)

Dewi G.C. Kirono

2016-01-01

Full Text Available Climate change impacts are most likely to be felt by resource-dependent communities, and consequently locally-relevant data are necessary to inform livelihood adaptation planning. This paper presents information for historical and future seasonal rainfall variability in Nusa Tenggara Barat (NTB Province, Indonesia, where rural livelihoods are highly vulnerable to current climate variability and future change. Historical rainfall variability is investigated using observational data from two stations located on the islands of Lombok and Sumbawa. Future rainfall is examined using an ensemble of six downscaled climate model simulations at a spatial resolution of 14 km for 1971–2100, applying the IPCC SRES-A2 ‘Business as Usual’ emissions scenario, and the six original global climate models (GCMs. Analyses of the observed seasonal rainfall data highlight cyclical variability and long-term declines. The observed periodicities are of about 2–4, 5, 8, 11, and 40–50 years. Furthermore, dry season rainfall is significantly correlated with the El Niño Southern Oscillation (ENSO, while wet season rainfall is weakly correlated with ENSO. The simulated rainfall data reproduce the observed seasonal cycle very well, but overestimate the magnitude of rainfall and underestimate inter-annual rainfall variability. The models also show that the observed rainfall periodicities will continue throughout the 21st century. The models project that rainfall will decline, although with wide ranges of uncertainty, depending on season and location. Crop water demand estimates show that the projected changes will potentially impact the first growing period for rice during November–March. Rainfall may also be insufficient to meet water demand for many crops in the second growing period of March–June, when high value commodities such as chillies and tobacco are produced. The results reinforce the importance to consider all uncertainties when utilizing climate

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

Science.gov (United States)

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

Sensitivity of Climate Change Detection and Attribution to the Characterization of Internal Climate Variability

KAUST Repository

Imbers, Jara; Lopez, Ana; Huntingford, Chris; Allen, Myles

2014-01-01

The Intergovernmental Panel on Climate Change's (IPCC) "very likely" statement that anthropogenic emissions are affecting climate is based on a statistical detection and attribution methodology that strongly depends on the characterization of internal climate variability. In this paper, the authors test the robustness of this statement in the case of global mean surface air temperature, under different representations of such variability. The contributions of the different natural and anthropogenic forcings to the global mean surface air temperature response are computed using a box diffusion model. Representations of internal climate variability are explored using simple stochastic models that nevertheless span a representative range of plausible temporal autocorrelation structures, including the short-memory first-order autoregressive [AR(1)] process and the long-memory fractionally differencing process. The authors find that, independently of the representation chosen, the greenhouse gas signal remains statistically significant under the detection model employed in this paper. The results support the robustness of the IPCC detection and attribution statement for global mean temperature change under different characterizations of internal variability, but they also suggest that a wider variety of robustness tests, other than simple comparisons of residual variance, should be performed when dealing with other climate variables and/or different spatial scales. © 2014 American Meteorological Society.

Sensitivity of Climate Change Detection and Attribution to the Characterization of Internal Climate Variability

KAUST Repository

Imbers, Jara

2014-05-01

The Intergovernmental Panel on Climate Change\\'s (IPCC) "very likely" statement that anthropogenic emissions are affecting climate is based on a statistical detection and attribution methodology that strongly depends on the characterization of internal climate variability. In this paper, the authors test the robustness of this statement in the case of global mean surface air temperature, under different representations of such variability. The contributions of the different natural and anthropogenic forcings to the global mean surface air temperature response are computed using a box diffusion model. Representations of internal climate variability are explored using simple stochastic models that nevertheless span a representative range of plausible temporal autocorrelation structures, including the short-memory first-order autoregressive [AR(1)] process and the long-memory fractionally differencing process. The authors find that, independently of the representation chosen, the greenhouse gas signal remains statistically significant under the detection model employed in this paper. The results support the robustness of the IPCC detection and attribution statement for global mean temperature change under different characterizations of internal variability, but they also suggest that a wider variety of robustness tests, other than simple comparisons of residual variance, should be performed when dealing with other climate variables and/or different spatial scales. © 2014 American Meteorological Society.

Future Flows Climate: an ensemble of 1-km climate change projections for hydrological application in Great Britain

Directory of Open Access Journals (Sweden)

C. Prudhomme

2012-11-01

Full Text Available The dataset Future Flows Climate was developed as part of the project ''Future Flows and Groundwater Levels'' to provide a consistent set of climate change projections for the whole of Great Britain at both space and time resolutions appropriate for hydrological applications, and to enable climate change uncertainty and climate variability to be accounted for in the assessment of their possible impacts on the environment.

Future Flows Climate is derived from the Hadley Centre's ensemble projection HadRM3-PPE that is part of the basis of UKCP09 and includes projections in available precipitation (water available to hydrological processes after snow and ice storages have been accounted for and potential evapotranspiration. It corresponds to an 11-member ensemble of transient projections from January 1950 to December 2098, each a single realisation from a different variant of HadRM3. Data are provided on a 1-km grid over the HadRM3 land areas at a daily (available precipitation and monthly (PE time step as netCDF files.

Because systematic biases in temperature and precipitation were found between HadRM3-PPE and gridded temperature and precipitation observations for the 1962–1991 period, a monthly bias correction procedure was undertaken, based on a linear correction for temperature and a quantile-mapping correction (using the gamma distribution for precipitation followed by a spatial downscaling. Available precipitation was derived from the bias-corrected precipitation and temperature time series using a simple elevation-dependant snow-melt model. Potential evapotranspiration time series were calculated for each month using the FAO-56 Penman-Monteith equations and bias-corrected temperature, cloud cover, relative humidity and wind speed from HadRM3-PPE along with latitude of the grid and the day of the year.

Future Flows Climate is freely available for non-commercial use under certain licensing conditions. It is the

Advances in Understanding Decadal Climate Variability

Science.gov (United States)

Busalacchi, Antonio J.

1999-01-01

Recently, a joint Brazil-France-U.S. program, known as PIRATA (Pilot Research moored Array in the Tropical Atlantic), was proposed to begin the deployment of moored measurement platforms in the tropical Atlantic in order to enhance the existing observational data base and subsequent understanding of the processes by which the ocean and atmosphere couple in key regions of the tropical Atlantic Ocean. Empirical studies have suggested that there are strong relationships between tropical Atlantic upper ocean variability, SST, ocean-atmosphere coupling and regional climate variability. During the early 1980's a coordinated set of surface wind, subsurface thermal structure, and subsurface current observations were obtained as part of the U.S.-France SEQUAL-FOCAL process experiment designed to observe the seasonal response of the tropical Atlantic Ocean to surface forcing. Since that time, however, the observational data base for the tropical Atlantic Ocean has disintegrated to a few ship-tracks measuring ocean temperatures and a small collection of tide gauge stations measuring sea level. A more comprehensive set of observations, modeling and empirical studies is now in order to make progress on understanding the regional climate variability. The proposed PIRATA program will use mooring platforms similar to the tropical Pacific Ocean TAO array to measure surface fluxes of momentum and heat and the corresponding changes in the upper ocean thermal structure. It is anticipated that the oceanic data from this monitoring array will also be used in a predictive mode for initialization studies of regional coupled climate models. Of particular interest are zonal and meridional modes of ocean-atmosphere variability within the tropical Atlantic basin that have significant impacts on the regional climate of the bordering continents.

Future climate

International Nuclear Information System (INIS)

La Croce, A.

1991-01-01

According to George Woodwell, founder of the Woods Hole Research Center, due the combustion of fossil fuels, deforestation and accelerated respiration, the net annual increase of carbon, in the form of carbon dioxide, to the 750 billion tonnes already present in the earth's atmosphere, is in the order of 3 to 5 billion tonnes. Around the world, scientists, investigating the probable effects of this increase on the earth's future climate, are now formulating coupled air and ocean current models which take account of water temperature and salinity dependent carbon dioxide exchange mechanisms acting between the atmosphere and deep layers of ocean waters

Impact of anthropogenic aerosols on present and future climate

International Nuclear Information System (INIS)

Deandreis, C.

2008-03-01

Aerosols influence the Earth radiative budget both through their direct effect (scattering and absorption of solar radiation) and their indirect effect (impacts on cloud microphysics). The role of anthropogenic aerosol in climate change has been recognized to be significant when compared to the one of greenhouse gases. Despite many studies on this topic, the assessments of both anthropogenic aerosol radiative forcing and their impacts on meteorological variables are still very uncertain. Major reasons for these uncertainties stem from the insufficient knowledge of the emissions sources and of the processes of formation, transformation and deposition. Models used to study climate are often inadequate to study aerosol processes because of coarse spatial and temporal scales. Uncertainties due to the parameterization of the aerosol are added to the uncertainties in the representation of large scale dynamics and physical processes such as transport, hydrological cycle and radiative budget. To predict, the role of the anthropogenic aerosol impact in the future climate change, I have addressed some of these key uncertainties. In this study, I simulate interactively aerosols processes in a climate model in order to improve the estimation of their direct and indirect effects. I estimate a modification of the top of the atmosphere net flux of 60% for the present period. I also show that, for future projection, the representation of the emissions source is an other important source of error. I assess that aerosols radiative forcing differ by 40% between simulations performed with 2 different emissions inventories. These inventories are representative for a high and a low limit in term of carbonaceous aerosols emissions for the 2050 horizon. (author)

Climate Change Effects on Heat Waves and Future Heat Wave-Associated IHD Mortality in Germany

Directory of Open Access Journals (Sweden)

Stefan Zacharias

2014-12-01

Full Text Available The influence of future climate change on the occurrence of heat waves and its implications for heat wave-related mortality due to ischemic heart diseases (IHD in Germany is studied. Simulations of 19 regional climate models with a spatial resolution of 0.25° × 0.25° forced by the moderate climate change scenario A1B are analyzed. Three model time periods of 30 years are evaluated, representing present climate (1971–2000, near future climate (2021–2050, and remote future climate (2069–2098. Heat waves are defined as periods of at least three consecutive days with daily mean air temperature above the 97.5th percentile of the all-season temperature distribution. Based on the model simulations, future heat waves in Germany will be significantly more frequent, longer lasting and more intense. By the end of the 21st century, the number of heat waves will be tripled compared to present climate. Additionally, the average duration of heat waves will increase by 25%, accompanied by an increase of the average temperature during heat waves by about 1 K. Regional analyses show that stronger than average climate change effects are observed particularly in the southern regions of Germany. Furthermore, we investigated climate change impacts on IHD mortality in Germany applying temperature projections from 19 regional climate models to heat wave mortality relationships identified in a previous study. Future IHD excess deaths were calculated both in the absence and presence of some acclimatization (i.e., that people are able to physiologically acclimatize to enhanced temperature levels in the future time periods by 0% and 50%, respectively. In addition to changes in heat wave frequency, we incorporated also changes in heat wave intensity and duration into the future mortality evaluations. The results indicate that by the end of the 21st century the annual number of IHD excess deaths in Germany attributable to heat waves is expected to rise by factor 2

Predicting Future Seed Sourcing of Platycladus orientalis (L. for Future Climates Using Climate Niche Models

Directory of Open Access Journals (Sweden)

Xian-Ge Hu

2017-12-01

Full Text Available Climate niche modeling has been widely used to assess the impact of climate change on forest trees at the species level. However, geographically divergent tree populations are expected to respond differently to climate change. Considering intraspecific local adaptation in modeling species responses to climate change will thus improve the credibility and usefulness of climate niche models, particularly for genetic resources management. In this study, we used five Platycladus orientalis (L. seed zones (Northwestern; Northern; Central; Southern; and Subtropical covering the entire species range in China. A climate niche model was developed and used to project the suitable climatic conditions for each of the five seed zones for current and various future climate scenarios (Representative Concentration Pathways: RCP2.6, RCP4.5, RCP6.0, and RCP8.5. Our results indicated that the Subtropical seed zone would show consistent reduction for all climate change scenarios. The remaining seed zones, however, would experience various degrees of expansion in suitable habitat relative to their current geographic distributions. Most of the seed zones would gain suitable habitats at their northern distribution margins and higher latitudes. Thus, we recommend adjusting the current forest management strategies to mitigate the negative impacts of climate change.

Use of variability modes to evaluate AR4 climate models over the Euro-Atlantic region

Energy Technology Data Exchange (ETDEWEB)

Casado, M.J.; Pastor, M.A. [Agencia Estatal de Meteorologia (AEMET), Madrid (Spain)

2012-01-15

This paper analyzes the ability of the multi-model simulations from the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) to simulate the main leading modes of variability over the Euro-Atlantic region in winter: the North-Atlantic Oscillation (NAO), the Scandinavian mode (SCAND), the East/Atlantic Oscillation (EA) and the East Atlantic/Western Russia mode (EA/WR). These modes of variability have been evaluated both spatially, by analyzing the intensity and location of their anomaly centres, as well as temporally, by focusing on the probability density functions and e-folding time scales. The choice of variability modes as a tool for climate model assessment can be justified by the fact that modes of variability determine local climatic conditions and their likely change may have important implications for future climate changes. It is found that all the models considered are able to simulate reasonably well these four variability modes, the SCAND being the mode which is best spatially simulated. From a temporal point of view the NAO and SCAND modes are the best simulated. UKMO-HadGEM1 and CGCM3.1(T63) are the models best at reproducing spatial characteristics, whereas CCSM3 and CGCM3.1(T63) are the best ones with regard to the temporal features. GISS-AOM is the model showing the worst performance, in terms of both spatial and temporal features. These results may bring new insight into the selection and use of specific models to simulate Euro-Atlantic climate, with some models being clearly more successful in simulating patterns of temporal and spatial variability than others. (orig.)

Uncertainty of climate change impacts and consequences on the prediction of future hydrological trends

International Nuclear Information System (INIS)

Minville, M.; Brissette, F.; Leconte, R.

2008-01-01

In the future, water is very likely to be the resource that will be most severely affected by climate change. It has been shown that small perturbations in precipitation frequency and/or quantity can result in significant impacts on the mean annual discharge. Moreover, modest changes in natural inflows result in larger changes in reservoir storage. There is however great uncertainty linked to changes in both the magnitude and direction of future hydrological trends. This presentation discusses the various sources of this uncertainty and their potential impact on the prediction of future hydrological trends. A companion paper will look at adaptation potential, taking into account some of the sources of uncertainty discussed in this presentation. Uncertainty is separated into two main components: climatic uncertainty and 'model and methods' uncertainty. Climatic uncertainty is linked to uncertainty in future greenhouse gas emission scenarios (GHGES) and to general circulation models (GCMs), whose representation of topography and climate processes is imperfect, in large part due to computational limitations. The uncertainty linked to natural variability (which may or may not increase) is also part of the climatic uncertainty. 'Model and methods' uncertainty regroups the uncertainty linked to the different approaches and models needed to transform climate data so that they can be used by hydrological models (such as downscaling methods) and the uncertainty of the models themselves and of their use in a changed climate. The impacts of the various sources of uncertainty on the hydrology of a watershed are demonstrated on the Peribonka River basin (Quebec, Canada). The results indicate that all sources of uncertainty can be important and outline the importance of taking these sources into account for any impact and adaptation studies. Recommendations are outlined for such studies. (author)

Refuge Lake Reclassification in 620 Minnesota Cisco Lakes under Future Climate Scenarios

Directory of Open Access Journals (Sweden)

Liping Jiang

2017-09-01

Full Text Available Cisco (Coregonus artedi is the most common coldwater stenothermal fish in Minnesota lakes. Water temperature (T and dissolved oxygen (DO in lakes are important controls of fish growth and reproduction and likely change with future climate warming. Built upon a previous study, this study uses a modified method to identify which of 620 cisco lakes in Minnesota can still support cisco populations under future climate and therefore be classified as cisco refuge lakes. The previous study used oxythermal stress parameter TDO3, the temperature at DO of 3 mg/L, simulated only from deep virtual lakes to classify 620 cisco lakes. Using four categories of virtual but representative cisco lakes in modified method, a one-dimensional water quality model MINLAKE2012 was used to simulate daily T and DO profiles in 82 virtual lakes under the past (1961–2008 and two future climate scenarios. A multiyear average of 31-day largest TDO3 over variable benchmark (VB periods, AvgATDO3VB, was calculated from simulated T and DO profiles using FishHabitat2013. Contour plots of AvgATDO3VB for four categories of virtual lakes were then developed to reclassify 620 cisco lakes into Tier 1 (AvgATDO3VB < 11 °C or Tier 2 refuge lakes, and Tier 3 non-refuge lakes (AvgATDO3VB > 17 °C. About 20% of 620 cisco lakes are projected to be refuge lakes under future climate scenarios, which is a more accurate projection (improving the prediction accuracy by ~6.5% from the previous study since AvgATDO3VB was found to vary by lake categories.

Future climate resources for tourism in Europe based on the daily Tourism Climatic Index

NARCIS (Netherlands)

Perch-Nielsen, S.; Amelung, B.; Knutti, R.

2010-01-01

Climate is an important resource for many types of tourism. One of several metrics for the suitability of climate for sightseeing is Mieczkowski’s “Tourism Climatic Index” (TCI), which summarizes and combines seven climate variables. By means of the TCI, we analyse the present climate resources for

Impacts of Present and Future Climate Change and Climate Variability on Agriculture in the Temperate Regions. North America

International Nuclear Information System (INIS)

Motha, Raymond P.; Baier, W.

2005-01-01

The potential impact of climate variability and climate change on agricultural production in the United States and Canada varies generally by latitude. Largest reductions are projected in southern crop areas due to increased temperatures and reduced water availability. A longer growing season and projected increases in CO2 may enhance crop yields in northern growing areas. Major factors in these scenarios analyzes are increased drought tendencies and more extreme weather events, both of which are detrimental to agriculture. Increasing competition for water between agriculture and non-agricultural users also focuses attention on water management issues. Agriculture also has impact on the greenhouse gas balance. Forests and soils are natural sinks for CO2. Removal of forests and changes in land use, associated with the conversion from rural to urban domains, alters these natural sinks. Agricultural livestock and rice cultivation are leading contributors to methane emission into the atmosphere. The application of fertilizers is also a significant contributor to nitrous oxide emission into the atmosphere. Thus, efficient management strategies in agriculture can play an important role in managing the sources and sinks of greenhouse gases. Forest and land management can be effective tools in mitigating the greenhouse effect

Climate Change: Past, Present, and Future

Science.gov (United States)

Chapman, David S.; Davis, Michael G.

2010-09-01

Questions about global warming concern climate scientists and the general public alike. Specifically, what are the reliable surface temperature reconstructions over the past few centuries? And what are the best predictions of global temperature change the Earth might expect for the next century? Recent publications [National Research Council (NRC), 2006; Intergovernmental Panel on Climate Change (IPCC), 2007] permit these questions to be answered in a single informative illustration by assembling temperature reconstructions of the past thousand years with predictions for the next century. The result, shown in Figure 1, illustrates present and future warming in the context of natural variations in the past [see also Oldfield and Alverson, 2003]. To quote a Chinese proverb, “A picture's meaning can express ten thousand words.” Because it succinctly captures past inferences and future projections of climate, the illustration should be of interest to scientists, educators, policy makers, and the public.

Projection of future climate changes

International Nuclear Information System (INIS)

Boucher, Olivier; Dufresne, Jean-Louis; Vial, Jessica; Brun, Eric; Cattiaux, Julien; Chauvin, Fabrice; Salas y Melia, David; Voldoire, Aurore; Bopp, Laurent; Braconnot, Pascale; Ciais, Philippe; Yiou, Pascal; Guilyardi, Eric; Mignot, Juliette; Guivarch, Celine

2015-01-01

Climate models provide the opportunity to anticipate how the climate system may change due to anthropogenic activities during the 21. century. Studies are based on numerical simulations that explore the evolution of the mean climate and its variability according to different socio-economic scenarios. We present a selection of results from phase 5 of the Climate model intercomparison project (CMIP5) with an illustrative focus on the two French models that participated to this exercise. We describe the effects of human perturbations upon surface temperature, precipitation, the cryo-sphere, but also extreme weather events and the carbon cycle. Results show a number of robust features, on the amplitude and geographical patterns of the expected changes and on the processes at play in these changes. They also show the limitations of such a prospective exercise and persistent uncertainties on some key aspects. (authors)

Understanding surface-water availability in the Central Valley as a means to projecting future groundwater storage with climate variability

Science.gov (United States)

Goodrich, J. P.; Cayan, D. R.

2017-12-01

California's Central Valley (CV) relies heavily on diverted surface water and groundwater pumping to supply irrigated agriculture. However, understanding the spatiotemporal character of water availability in the CV is difficult because of the number of individual farms and local, state, and federal agencies involved in using and managing water. Here we use the Central Valley Hydrologic Model (CVHM), developed by the USGS, to understand the relationships between climatic variability, surface water inputs, and resulting groundwater use over the historical period 1970-2013. We analyzed monthly surface water diversion data from >500 CV locations. Principle components analyses were applied to drivers constructed from meteorological data, surface reservoir storage, ET, land use cover, and upstream inflows, to feed multiple regressions and identify factors most important in predicting surface water diversions. Two thirds of the diversion locations ( 80% of total diverted water) can be predicted to within 15%. Along with monthly inputs, representations of cumulative precipitation over the previous 3 to 36 months can explain an additional 10% of variance, depending on location, compared to results that excluded this information. Diversions in the southern CV are highly sensitive to inter-annual variability in precipitation (R2 = 0.8), whereby more surface water is used during wet years. Until recently, this was not the case in the northern and mid-CV, where diversions were relatively constant annually, suggesting relative insensitivity to drought. In contrast, this has important implications for drought response in southern regions (eg. Tulare Basin) where extended dry conditions can severely limit surface water supplies and lead to excess groundwater pumping, storage loss, and subsidence. In addition to fueling our understanding of spatiotemporal variability in diversions, our ability to predict these water balance components allows us to update CVHM predictions before

Climate change projections of heat stress in Europe: From meteorological variables to impacts on productivity

Science.gov (United States)

Casanueva, Ana; Kotlarski, Sven; Liniger, Mark A.

2017-04-01

Future climate change is likely to have important impacts in many socio-economic sectors. In particular, higher summer temperatures or more prolonged heat waves may be responsible for health problems and productivity losses related to heat stress, especially affecting people exposed to such situations (e.g. working under outside settings or in non-acclimatized workplaces). Heat stress on the body under work load and consequently their productivity loss can be described through heat stress indices that are based on multiple meteorological parameters such as temperature, humidity, wind and radiation. Exploring the changes of these variables under a warmer climate is of prime importance for the Impacts, Adaptation and Vulnerability communities. In particular, the H2020 project HEAT-SHIELD aims at analyzing the impact of climate change on heat stress in strategic industries in Europe (manufacturing, construction, transportation, tourism and agriculture) within an inter-sectoral framework (climate scientists, biometeorologists, physiologists and stakeholders). In the present work we explore present and future heat stress over Europe using an ensemble of the state-of-the-art RCMs from the EURO-CORDEX initiative. Since RCMs cannot be directly used in impact studies due to their partly substantial biases, a standard bias correction method (empirical quantile mapping) is applied to correct the individual variables that are then used to derive heat stress indices. The objectives of this study are twofold, 1) to test the ability of the separately bias corrected variables to reproduce the main characteristics of heat stress indices in present climate conditions and 2) to explore climate change projections of heat stress indices. We use the wet bulb globe temperature (WBGT) as primary heat stress index, considering two different versions for indoor (or in the shade, based on temperature and humidity conditions) and outdoor settings (including also wind and radiation). The WBGT

A plant’s perspective of extremes: Terrestrial plant responses to changing climatic variability

Science.gov (United States)

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

Sensitivity of Water Scarcity Events to ENSO-Driven Climate Variability at the Global Scale

Science.gov (United States)

Veldkamp, T. I. E.; Eisner, S.; Wada, Y.; Aerts, J. C. J. H.; Ward, P. J.

2015-01-01

Globally, freshwater shortage is one of the most dangerous risks for society. Changing hydro-climatic and socioeconomic conditions have aggravated water scarcity over the past decades. A wide range of studies show that water scarcity will intensify in the future, as a result of both increased consumptive water use and, in some regions, climate change. Although it is well-known that El Niño- Southern Oscillation (ENSO) affects patterns of precipitation and drought at global and regional scales, little attention has yet been paid to the impacts of climate variability on water scarcity conditions, despite its importance for adaptation planning. Therefore, we present the first global-scale sensitivity assessment of water scarcity to ENSO, the most dominant signal of climate variability. We show that over the time period 1961-2010, both water availability and water scarcity conditions are significantly correlated with ENSO-driven climate variability over a large proportion of the global land area (> 28.1 %); an area inhabited by more than 31.4% of the global population. We also found, however, that climate variability alone is often not enough to trigger the actual incidence of water scarcity events. The sensitivity of a region to water scarcity events, expressed in terms of land area or population exposed, is determined by both hydro-climatic and socioeconomic conditions. Currently, the population actually impacted by water scarcity events consists of 39.6% (CTA: consumption-to-availability ratio) and 41.1% (WCI: water crowding index) of the global population, whilst only 11.4% (CTA) and 15.9% (WCI) of the global population is at the same time living in areas sensitive to ENSO-driven climate variability. These results are contrasted, however, by differences in growth rates found under changing socioeconomic conditions, which are relatively high in regions exposed to water scarcity events. Given the correlations found between ENSO and water availability and scarcity

Warm climates of the past--a lesson for the future?

Science.gov (United States)

Lunt, D J; Elderfield, H; Pancost, R; Ridgwell, A; Foster, G L; Haywood, A; Kiehl, J; Sagoo, N; Shields, C; Stone, E J; Valdes, P

2013-10-28

This Discussion Meeting Issue of the Philosophical Transactions A had its genesis in a Discussion Meeting of the Royal Society which took place on 10-11 October 2011. The Discussion Meeting, entitled 'Warm climates of the past: a lesson for the future?', brought together 16 eminent international speakers from the field of palaeoclimate, and was attended by over 280 scientists and members of the public. Many of the speakers have contributed to the papers compiled in this Discussion Meeting Issue. The papers summarize the talks at the meeting, and present further or related work. This Discussion Meeting Issue asks to what extent information gleaned from the study of past climates can aid our understanding of future climate change. Climate change is currently an issue at the forefront of environmental science, and also has important sociological and political implications. Most future predictions are carried out by complex numerical models; however, these models cannot be rigorously tested for scenarios outside of the modern, without making use of past climate data. Furthermore, past climate data can inform our understanding of how the Earth system operates, and can provide important contextual information related to environmental change. All past time periods can be useful in this context; here, we focus on past climates that were warmer than the modern climate, as these are likely to be the most similar to the future. This introductory paper is not meant as a comprehensive overview of all work in this field. Instead, it gives an introduction to the important issues therein, using the papers in this Discussion Meeting Issue, and other works from all the Discussion Meeting speakers, as exemplars of the various ways in which past climates can inform projections of future climate. Furthermore, we present new work that uses a palaeo constraint to quantitatively inform projections of future equilibrium ice sheet change.

Climate change and future fire regimes: Examples from California

Science.gov (United States)

Keeley, Jon E.; Syphard, Alexandra D.

2016-01-01

Climate and weather have long been noted as playing key roles in wildfire activity, and global warming is expected to exacerbate fire impacts on natural and urban ecosystems. Predicting future fire regimes requires an understanding of how temperature and precipitation interact to control fire activity. Inevitably this requires historical analyses that relate annual burning to climate variation. Fuel structure plays a critical role in determining which climatic parameters are most influential on fire activity, and here, by focusing on the diversity of ecosystems in California, we illustrate some principles that need to be recognized in predicting future fire regimes. Spatial scale of analysis is important in that large heterogeneous landscapes may not fully capture accurate relationships between climate and fires. Within climatically homogeneous subregions, montane forested landscapes show strong relationships between annual fluctuations in temperature and precipitation with area burned; however, this is strongly seasonal dependent; e.g., winter temperatures have very little or no effect but spring and summer temperatures are critical. Climate models that predict future seasonal temperature changes are needed to improve fire regime projections. Climate does not appear to be a major determinant of fire activity on all landscapes. Lower elevations and lower latitudes show little or no increase in fire activity with hotter and drier conditions. On these landscapes climate is not usually limiting to fires but these vegetation types are ignition-limited. Moreover, because they are closely juxtaposed with human habitations, fire regimes are more strongly controlled by other direct anthropogenic impacts. Predicting future fire regimes is not rocket science; it is far more complicated than that. Climate change is not relevant to some landscapes, but where climate is relevant, the relationship will change due to direct climate effects on vegetation trajectories, as well as

Climate Change and Future Fire Regimes: Examples from California

Directory of Open Access Journals (Sweden)

Jon E. Keeley

2016-08-01

Full Text Available Climate and weather have long been noted as playing key roles in wildfire activity, and global warming is expected to exacerbate fire impacts on natural and urban ecosystems. Predicting future fire regimes requires an understanding of how temperature and precipitation interact to control fire activity. Inevitably this requires historical analyses that relate annual burning to climate variation. Fuel structure plays a critical role in determining which climatic parameters are most influential on fire activity, and here, by focusing on the diversity of ecosystems in California, we illustrate some principles that need to be recognized in predicting future fire regimes. Spatial scale of analysis is important in that large heterogeneous landscapes may not fully capture accurate relationships between climate and fires. Within climatically homogeneous subregions, montane forested landscapes show strong relationships between annual fluctuations in temperature and precipitation with area burned; however, this is strongly seasonal dependent; e.g., winter temperatures have very little or no effect but spring and summer temperatures are critical. Climate models that predict future seasonal temperature changes are needed to improve fire regime projections. Climate does not appear to be a major determinant of fire activity on all landscapes. Lower elevations and lower latitudes show little or no increase in fire activity with hotter and drier conditions. On these landscapes climate is not usually limiting to fires but these vegetation types are ignition-limited. Moreover, because they are closely juxtaposed with human habitations, fire regimes are more strongly controlled by other direct anthropogenic impacts. Predicting future fire regimes is not rocket science; it is far more complicated than that. Climate change is not relevant to some landscapes, but where climate is relevant, the relationship will change due to direct climate effects on vegetation

Shift of biome patterns due to simulated climate variability and climate change

International Nuclear Information System (INIS)

Claussen, M.

1993-01-01

The variability of simulated equilibrium-response patterns of biomes caused by simulated climate variability and climate shift is analysed. This investigation is based on various realisations of simulated present-day climate and climate shift. It has been found that the difference between biomes computed from three 10-year climatologies and from the corresponding 30-year climatology, simulated by the Hamburg climate model at T21 resolution, amounts to approximately 6% of the total land area, Antarctica excluded. This difference is mainly due to differences in annual moisture availability and winter temperatures. When intercomparing biomes from the 10-year climatologies a 10% difference is seen, but there is no unique difference pattern. In contrast to the interdecadal variability, the shift of conditions favorable for biomes due to a shift in climate in the next 100 years, caused by an increase in sea-surface temperatures and atmospheric CO 2 , reveals a unique trend pattern. It turns out that the strongest and most significant signal is the north-east shift of conditions for boreal biomes. This signal is caused by an increase of annual temperature sums as well as mean temperatures of the coldest and warmest months. Trends in annual moisture availability are of secondary importance globally. Regionally, a decrease in water availability affects biomes in Central and East Europe and an increase of water availability leads to a potential increase in tropical rain forest. In total, all differences amount to roughly 30% of the total land surface, Antarctica excluded. (orig./KW)

Past and future effects of climate change on spatially heterogeneous vegetation activity in China

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Gao, Jiangbo; Jiao, Kewei; Wu, Shaohong; Ma, Danyang; Zhao, Dongsheng; Yin, Yunhe; Dai, Erfu

2017-07-01

Climate change is a major driver of vegetation activity but its complex ecological relationships impede research efforts. In this study, the spatial distribution and dynamic characteristics of climate change effects on vegetation activity in China from the 1980s to the 2010s and from 2021 to 2050 were investigated using a geographically weighted regression (GWR) model. The GWR model was based on combined datasets of satellite vegetation index, climate observation and projection, and future vegetation productivity simulation. Our results revealed that the significantly positive precipitation-vegetation relationship was and will be mostly distributed in North China. However, the regions with temperature-dominated distribution of vegetation activity were and will be mainly located in South China. Due to the varying climate features and vegetation cover, the spatial correlation between vegetation activity and climate change may be altered. There will be different dominant climatic factors for vegetation activity distribution in some regions such as Northwest China, and even opposite correlations in Northeast China. Additionally, the response of vegetation activity to precipitation will move southward in the next three decades. In contrast, although the high warming rate will restrain the vegetation activity, precipitation variability could modify hydrothermal conditions for vegetation activity. This observation is exemplified in the projected future enhancement of vegetation activity in the Tibetan Plateau and weakened vegetation activity in East and Middle China. Furthermore, the vegetation in most parts of North China may adapt to an arid environment, whereas in many southern areas, vegetation will be repressed by water shortage in the future.

Assessing the impact of future climate extremes on the US corn and soybean production

Science.gov (United States)

Jin, Z.

2015-12-01

Future climate changes will place big challenges to the US agricultural system, among which increasing heat stress and precipitation variability were the two major concerns. Reliable prediction of crop productions in response to the increasingly frequent and severe extreme climate is a prerequisite for developing adaptive strategies on agricultural risk management. However, the progress has been slow on quantifying the uncertainty of computational predictions at high spatial resolutions. Here we assessed the risks of future climate extremes on the US corn and soybean production using the Agricultural Production System sIMulator (APSIM) model under different climate scenarios. To quantify the uncertainty due to conceptual representations of heat, drought and flooding stress in crop models, we proposed a new strategy of algorithm ensemble in which different methods for simulating crop responses to those extreme climatic events were incorporated into the APSIM. This strategy allowed us to isolate irrelevant structure differences among existing crop models but only focus on the process of interest. Future climate inputs were derived from high-spatial-resolution (12km × 12km) Weather Research and Forecasting (WRF) simulations under Representative Concentration Pathways 4.5 (RCP 4.5) and 8.5 (RCP 8.5). Based on crop model simulations, we analyzed the magnitude and frequency of heat, drought and flooding stress for the 21st century. We also evaluated the water use efficiency and water deficit on regional scales if farmers were to boost their yield by applying more fertilizers. Finally we proposed spatially explicit adaptation strategies of irrigation and fertilizing for different management zones.

Accounting for multiple climate components when estimating climate change exposure and velocity

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Nadeau, Christopher P.; Fuller, Angela K.

2015-01-01

The effect of anthropogenic climate change on organisms will likely be related to climate change exposure and velocity at local and regional scales. However, common methods to estimate climate change exposure and velocity ignore important components of climate that are known to affect the ecology and evolution of organisms.We develop a novel index of climate change (climate overlap) that simultaneously estimates changes in the means, variation and correlation between multiple weather variables. Specifically, we estimate the overlap between multivariate normal probability distributions representing historical and current or projected future climates. We provide methods for estimating the statistical significance of climate overlap values and methods to estimate velocity using climate overlap.We show that climates have changed significantly across 80% of the continental United States in the last 32 years and that much of this change is due to changes in the variation and correlation between weather variables (two statistics that are rarely incorporated into climate change studies). We also show that projected future temperatures are predicted to be locally novel (using climate overlap compared to 1·4 km yr−1 when estimated using traditional methods.Our results suggest that accounting for changes in the means, variation and correlation between multiple weather variables can dramatically affect estimates of climate change exposure and velocity. These climate components are known to affect the ecology and evolution of organisms, but are ignored by most measures of climate change. We conclude with a set of future directions and recommend future work to determine which measures of climate change exposure and velocity are most related to biological responses to climate change.

Modeling key processes causing climate change and variability

Energy Technology Data Exchange (ETDEWEB)

Henriksson, S.

2013-09-01

Greenhouse gas warming, internal climate variability and aerosol climate effects are studied and the importance to understand these key processes and being able to separate their influence on the climate is discussed. Aerosol-climate model ECHAM5-HAM and the COSMOS millennium model consisting of atmospheric, ocean and carbon cycle and land-use models are applied and results compared to measurements. Topics at focus are climate sensitivity, quasiperiodic variability with a period of 50-80 years and variability at other timescales, climate effects due to aerosols over India and climate effects of northern hemisphere mid- and high-latitude volcanic eruptions. The main findings of this work are (1) pointing out the remaining challenges in reducing climate sensitivity uncertainty from observational evidence, (2) estimates for the amplitude of a 50-80 year quasiperiodic oscillation in global mean temperature ranging from 0.03 K to 0.17 K and for its phase progression as well as the synchronising effect of external forcing, (3) identifying a power law shape S(f) {proportional_to} f-{alpha} for the spectrum of global mean temperature with {alpha} {approx} 0.8 between multidecadal and El Nino timescales with a smaller exponent in modelled climate without external forcing, (4) separating aerosol properties and climate effects in India by season and location (5) the more efficient dispersion of secondary sulfate aerosols than primary carbonaceous aerosols in the simulations, (6) an increase in monsoon rainfall in northern India due to aerosol light absorption and a probably larger decrease due to aerosol dimming effects and (7) an estimate of mean maximum cooling of 0.19 K due to larger northern hemisphere mid- and high-latitude volcanic eruptions. The results could be applied or useful in better isolating the human-caused climate change signal, in studying the processes further and in more detail, in decadal climate prediction, in model evaluation and in emission policy

CLIMATE CHANGE, VARIABILITY AND SUSTAINABLE AGRICULTURE IN ZIMBABWE'S RURAL COMMUNITIES

Directory of Open Access Journals (Sweden)

Gukurume Simbarashe

2013-02-01

Full Text Available This article explores the impact of climate change and variability on agricultural productivity in the communal area of Bikita. The article further examines the adaptation and mitigation strategies devised by farmers to deal with the vagaries of climate change and variability. The sustainability of these is also interrogated in this article. This study juxtaposed qualitative and quantitative methodologies albeit with more bias on the former. A total of 40 farmers were sampled for unstructured interviews and focus group discussions. This article argues that the adverse impacts of climate change and variability are felt heavily by the poor communal farmers who are directly dependent on agriculture for livelihood. From the study, some of the widely reported signs of climate variability in Bikita included late and unpredictable rains, high temperatures (heat waves, successive drought, shortening rainfall seasons and seasonal changes in the timing of rainfall. The paper argues that climate change has compounded the vulnerability of peasant farmers in the drought - prone district of Bikita plunging them into food insecurity and abject poverty. It emerged in the study that some of effects of climate variability felt by communal farmers in Bikita included failure of crops, death of livestock and low crop yields, all of which have led to declining agricultural productivity. Findings in this study however established that communal farmers have not been passive victims of the vagaries of climate change and variability. They have rationally responded to it through various adaptation and mitigation strategies both individually and collectively.

Potential economic benefits of adapting agricultural production systems to future climate change

Science.gov (United States)

Fagre, Daniel B.; Pederson, Gregory; Bengtson, Lindsey E.; Prato, Tony; Qui, Zeyuan; Williams, Jimmie R.

2010-01-01

Potential economic impacts of future climate change on crop enterprise net returns and annual net farm income (NFI) are evaluated for small and large representative farms in Flathead Valley in Northwest Montana. Crop enterprise net returns and NFI in an historical climate period (1960–2005) and future climate period (2006–2050) are compared when agricultural production systems (APSs) are adapted to future climate change. Climate conditions in the future climate period are based on the A1B, B1, and A2 CO2 emission scenarios from the Intergovernmental Panel on Climate Change Fourth Assessment Report. Steps in the evaluation include: (1) specifying crop enterprises and APSs (i.e., combinations of crop enterprises) in consultation with locals producers; (2) simulating crop yields for two soils, crop prices, crop enterprises costs, and NFIs for APSs; (3) determining the dominant APS in the historical and future climate periods in terms of NFI; and (4) determining whether NFI for the dominant APS in the historical climate period is superior to NFI for the dominant APS in the future climate period. Crop yields are simulated using the Environmental/Policy Integrated Climate (EPIC) model and dominance comparisons for NFI are based on the stochastic efficiency with respect to a function (SERF) criterion. Probability distributions that best fit the EPIC-simulated crop yields are used to simulate 100 values for crop yields for the two soils in the historical and future climate periods. Best-fitting probability distributions for historical inflation-adjusted crop prices and specified triangular probability distributions for crop enterprise costs are used to simulate 100 values for crop prices and crop enterprise costs. Averaged over all crop enterprises, farm sizes, and soil types, simulated net return per ha averaged over all crop enterprises decreased 24% and simulated mean NFI for APSs decreased 57% between the historical and future climate periods. Although adapting

Potential Economic Benefits of Adapting Agricultural Production Systems to Future Climate Change

Science.gov (United States)

Prato, Tony; Zeyuan, Qiu; Pederson, Gregory; Fagre, Dan; Bengtson, Lindsey E.; Williams, Jimmy R.

2010-03-01

Potential economic impacts of future climate change on crop enterprise net returns and annual net farm income (NFI) are evaluated for small and large representative farms in Flathead Valley in Northwest Montana. Crop enterprise net returns and NFI in an historical climate period (1960-2005) and future climate period (2006-2050) are compared when agricultural production systems (APSs) are adapted to future climate change. Climate conditions in the future climate period are based on the A1B, B1, and A2 CO2 emission scenarios from the Intergovernmental Panel on Climate Change Fourth Assessment Report. Steps in the evaluation include: (1) specifying crop enterprises and APSs (i.e., combinations of crop enterprises) in consultation with locals producers; (2) simulating crop yields for two soils, crop prices, crop enterprises costs, and NFIs for APSs; (3) determining the dominant APS in the historical and future climate periods in terms of NFI; and (4) determining whether NFI for the dominant APS in the historical climate period is superior to NFI for the dominant APS in the future climate period. Crop yields are simulated using the Environmental/Policy Integrated Climate (EPIC) model and dominance comparisons for NFI are based on the stochastic efficiency with respect to a function (SERF) criterion. Probability distributions that best fit the EPIC-simulated crop yields are used to simulate 100 values for crop yields for the two soils in the historical and future climate periods. Best-fitting probability distributions for historical inflation-adjusted crop prices and specified triangular probability distributions for crop enterprise costs are used to simulate 100 values for crop prices and crop enterprise costs. Averaged over all crop enterprises, farm sizes, and soil types, simulated net return per ha averaged over all crop enterprises decreased 24% and simulated mean NFI for APSs decreased 57% between the historical and future climate periods. Although adapting APSs to

Potential economic benefits of adapting agricultural production systems to future climate change.

Science.gov (United States)

Prato, Tony; Zeyuan, Qiu; Pederson, Gregory; Fagre, Dan; Bengtson, Lindsey E; Williams, Jimmy R

2010-03-01

Potential economic impacts of future climate change on crop enterprise net returns and annual net farm income (NFI) are evaluated for small and large representative farms in Flathead Valley in Northwest Montana. Crop enterprise net returns and NFI in an historical climate period (1960-2005) and future climate period (2006-2050) are compared when agricultural production systems (APSs) are adapted to future climate change. Climate conditions in the future climate period are based on the A1B, B1, and A2 CO(2) emission scenarios from the Intergovernmental Panel on Climate Change Fourth Assessment Report. Steps in the evaluation include: (1) specifying crop enterprises and APSs (i.e., combinations of crop enterprises) in consultation with locals producers; (2) simulating crop yields for two soils, crop prices, crop enterprises costs, and NFIs for APSs; (3) determining the dominant APS in the historical and future climate periods in terms of NFI; and (4) determining whether NFI for the dominant APS in the historical climate period is superior to NFI for the dominant APS in the future climate period. Crop yields are simulated using the Environmental/Policy Integrated Climate (EPIC) model and dominance comparisons for NFI are based on the stochastic efficiency with respect to a function (SERF) criterion. Probability distributions that best fit the EPIC-simulated crop yields are used to simulate 100 values for crop yields for the two soils in the historical and future climate periods. Best-fitting probability distributions for historical inflation-adjusted crop prices and specified triangular probability distributions for crop enterprise costs are used to simulate 100 values for crop prices and crop enterprise costs. Averaged over all crop enterprises, farm sizes, and soil types, simulated net return per ha averaged over all crop enterprises decreased 24% and simulated mean NFI for APSs decreased 57% between the historical and future climate periods. Although adapting APSs

Estuarine fish communities respond to climate variability over both river and ocean basins.

Science.gov (United States)

Feyrer, Frederick; Cloern, James E; Brown, Larry R; Fish, Maxfield A; Hieb, Kathryn A; Baxter, Randall D

2015-10-01

Estuaries are dynamic environments at the land-sea interface that are strongly affected by interannual climate variability. Ocean-atmosphere processes propagate into estuaries from the sea, and atmospheric processes over land propagate into estuaries from watersheds. We examined the effects of these two separate climate-driven processes on pelagic and demersal fish community structure along the salinity gradient in the San Francisco Estuary, California, USA. A 33-year data set (1980-2012) on pelagic and demersal fishes spanning the freshwater to marine regions of the estuary suggested the existence of five estuarine salinity fish guilds: limnetic (salinity = 0-1), oligohaline (salinity = 1-12), mesohaline (salinity = 6-19), polyhaline (salinity = 19-28), and euhaline (salinity = 29-32). Climatic effects propagating from the adjacent Pacific Ocean, indexed by the North Pacific Gyre Oscillation (NPGO), affected demersal and pelagic fish community structure in the euhaline and polyhaline guilds. Climatic effects propagating over land, indexed as freshwater outflow from the watershed (OUT), affected demersal and pelagic fish community structure in the oligohaline, mesohaline, polyhaline, and euhaline guilds. The effects of OUT propagated further down the estuary salinity gradient than the effects of NPGO that propagated up the estuary salinity gradient, exemplifying the role of variable freshwater outflow as an important driver of biotic communities in river-dominated estuaries. These results illustrate how unique sources of climate variability interact to drive biotic communities and, therefore, that climate change is likely to be an important driver in shaping the future trajectory of biotic communities in estuaries and other transitional habitats. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Climate and society: passed climates, man era, future climate: essential reference marks

International Nuclear Information System (INIS)

Melieres, M.A.; Marechal, Ch.

2010-01-01

This teaching book takes stock of the climate change question which has moved beyond the simple scientific framework. Man will play a key role in the changes to come and the choices he is going to make will have a major impact on our environment and on our societies. The aim of this book is to draw out the essential marks from the multiple disciplines involved in the study of climate change in order to get a global overview of the question. Starting from simple mechanisms showing up the driving components of the climate equilibrium (like the greenhouse effect), the authors analyse the climates of the past, and describe the different causes of the actual climate change and its possible evolution in the future. The global nature of the climate warming in progress is demonstrated and some of its actual impacts on the environment are shown up. The importance of the anthropic influence in this change is underlined as well as the stakes of the mastery of our greenhouse gas emissions. (J.S.)

Research on climate change and variability at the Ab dus Salam International Centre for Theoretical Physics

International Nuclear Information System (INIS)

Giorgi, F.; Molteni, F.

2002-01-01

The Physics of Weather and Climate Section at the Abdus Salam International Centre for Theoretical Physics, established in 1998, is currently performing research on different aspects of climate variability, dealing with both natural and anthropogenic aspects of climate changes. In addition to performing diagnostic work on multi-decadal observational datasets and climate simulations carried out in major research centres, the PWC section has been developing its own climate modeling capability, which is focused on three main areas: a) modeling of regional climate change; b) seasonal forecasting at global and regional scale; c) development of simplified models of the general circulation. On topic a), research on different aspects of anthropogenic climate change is being carried out using the Regional Climate (RegCM) developed by Giorgi and collaborators at the National Centre for Atmospheric Research. Time-slice experiments with a high-resolution atmospheric GCM, comparing current climate conditions with future climate scenarios in selected decades, are also planned for the near future. On topic b), a strategy based on ensembles of high-resolution simulations with atmospheric GCM's, using sea surface temperature anomalies predicted by lower-resolution coupled models from other institutions, is currently under experimentation. A one-way nesting of RegCM into the GCM simulations will also be tested. On item c), a 5-layer atmospheric GCM with simplified physical parameterizations has been developed. This model has a very small computational cost compared with state-of-the-art GCMs, and is suitable for studies of natural climate variability on inter-decadal and intercentennial time scales. It is planned to couple this model to simplified ocean models of different complexity, from a simple, static mixed layer model, to simplified models of the tropical Pacific circulation suited to the simulation of the El Nino phenomenon. A joint project with the IAEA-MEL Laboratory in

Water and nitrogen management effects on semiarid sorghum production and soil trace gas flux under future climate.

Science.gov (United States)

Duval, Benjamin D; Ghimire, Rajan; Hartman, Melannie D; Marsalis, Mark A

2018-01-01

External inputs to agricultural systems can overcome latent soil and climate constraints on production, while contributing to greenhouse gas emissions from fertilizer and water management inefficiencies. Proper crop selection for a given region can lessen the need for irrigation and timing of N fertilizer application with crop N demand can potentially reduce N2O emissions and increase N use efficiency while reducing residual soil N and N leaching. However, increased variability in precipitation is an expectation of climate change and makes predicting biomass and gas flux responses to management more challenging. We used the DayCent model to test hypotheses about input intensity controls on sorghum (Sorghum bicolor (L.) Moench) productivity and greenhouse gas emissions in the southwestern United States under future climate. Sorghum had been previously parameterized for DayCent, but an inverse-modeling via parameter estimation method significantly improved model validation to field data. Aboveground production and N2O flux were more responsive to N additions than irrigation, but simulations with future climate produced lower values for sorghum than current climate. We found positive interactions between irrigation at increased N application for N2O and CO2 fluxes. Extremes in sorghum production under future climate were a function of biomass accumulation trajectories related to daily soil water and mineral N. Root C inputs correlated with soil organic C pools, but overall soil C declined at the decadal scale under current weather while modest gains were simulated under future weather. Scaling biomass and N2O fluxes by unit N and water input revealed that sorghum can be productive without irrigation, and the effect of irrigating crops is difficult to forecast when precipitation is variable within the growing season. These simulation results demonstrate the importance of understanding sorghum production and greenhouse gas emissions at daily scales when assessing annual

Quantifying the increasing sensitivity of power systems to climate variability

Science.gov (United States)

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.

Ecoclimatic indicators to study crop suitability in present and future climatic conditionsTIC CONDITIONS

Science.gov (United States)

Caubel, Julie; Garcia de Cortazar Atauri, Inaki; Huard, Frédéric; Launay, Marie; Ripoche, Dominique; Gouache, David; Bancal, Marie-Odile; Graux, Anne-Isabelle; De Noblet, Nathalie

2013-04-01

Climate change is expected to affect both regional and global food production through changes in overall agroclimatic conditions. It is therefore necessary to develop simple tools of crop suitability diagnosis in a given area so that stakeholders can envisage land use adaptations under climate change conditions. The most common way to investigate potential impacts of climate on the evolution of agrosystems is to make use of an array of agroclimatic indicators, which provide synthetic information derived from climatic variables and calculated within fixed periods (i.e. January first - 31th July). However, the information obtained during these periods does not enable to take account of the plant response to climate. In this work, we present some results of the research program ORACLE (Opportunities and Risks of Agrosystems & forests in response to CLimate, socio-economic and policy changEs in France (and Europe). We proposed a suite of relevant ecoclimatic indicators, based on temperature and rainfall, in order to evaluate crop suitability for both present and new climatic conditions. Ecoclimatic indicators are agroclimatic indicators (e.g., grain heat stress) calculated during specific phenological phases so as to take account of the plant response to climate (e.g., the grain filling period, flowering- harvest). These indicators are linked with the ecophysiological processes they characterize (for e.g., the grain filling). To represent this methodology, we studied the suitability of winter wheat in future climatic conditions through three distinct French sites, Toulouse, Dijon and Versailles. Indicators have been calculated using climatic data from 1950 to 2100 simulated by the global climate model ARPEGE forced by a greenhouse effect corresponding to the SRES A1B scenario. The Quantile-Quantile downscaling method was applied to obtain data for the three locations. Phenological stages (emergence, ear 1 cm, flowering, beginning of grain filling and harvest) have been

Future aridity under conditions of global climate change

Science.gov (United States)

Asadi Zarch, Mohammad Amin; Sivakumar, Bellie; Malekinezhad, Hossein; Sharma, Ashish

2017-11-01

Global climate change is anticipated to cause some major changes in hydroclimatic conditions around the world. As aridity is a reliable indicator of potential available water, assessment of its changes under future climatic conditions is important for proper management of water. This study employs the UNESCO aridity/humidity index, which is a derivative of precipitation (P) and potential evapotranspiration (PET), for assessment of aridity. Historical (1901-2005) simulations and future (2006-2100) projections of 22 global climate models (GCMs) from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) are studied. The Nested Bias Correction (NBC) approach is used to correct possible biases of precipitation (simulated directly by the GCMs) and PET (estimated by applying FAO56-Penman-Monteith model on simulated parameters of the GCMs). To detect future aridity changes, the areal extents of the aridity zones in the past and future periods as well as through four sub-periods (2006-2025, 2026-2050, 2051-2075, and 2076-2100) of the future are compared. The results indicate that changes in climate will alter the areal extents of aridity zones in the future. In general, from the first sub-period towards the last one, the area covered by hyper-arid, arid, semi-arid, and sub-humid zones will increase (by 7.46%, 7.01%, 5.80%, and 2.78%, respectively), while the area of the humid regions will decrease (by 4.76%), suggesting that there will be less water over the global land area in the future. To understand the cause of these changes, precipitation and PET are also separately assumed to be stationary throughout the four future sub-periods and the resulting aridity changes are then analyzed. The results reveal that the aridity changes are mostly caused by the positive PET trends, even though the slight precipitation increase lessens the magnitude of the changes.

Future-dependent Flow Policies with Prophetic Variables

DEFF Research Database (Denmark)

Li, Ximeng; Nielson, Flemming; Nielson, Hanne Riis

2016-01-01

future-dependent flow policies- policies that can depend on not only the current values of variables, but also their final values. The final values are referred to using what we call prophetic variables, just as the initial values can be referenced using logical variables in Hoare logic. We develop...... and enforce a notion of future-dependent security for open systems, in the spirit of "non-deducibility on strategies". We also illustrate our approach in scenarios where future-dependency has advantages over present-dependency and avoids mixtures of upgradings and downgradings....

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

Science.gov (United States)

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

Eyewitness Accounts on Climate Variability and the Responses: Perspectives from Farmers

Directory of Open Access Journals (Sweden)

Jiban Mani Poudel

2012-06-01

Full Text Available People with different socio-cultural arrangements havedifferent experiences and responses to climatic variability. The place specific experiences and responses at community level still remain a little explored issue in the discourse of climate change research. This paper deals with local experiences of climatic variability which have been monitoring by locals in their lifetime, on the one hand, and, on the other, explore their responses or coping mechanisms which they have been practicing to mitigate with climatic risks. Moreover, farmers’ experiences were documented in term of observed climatic variability in their lifetime focusing on qualitative data. I have used eyewitness accounts and hearsays to document their experiences of climatic variability. Moreover, farmers have developed various coping mechanisms such as indigenous knowledge, utilize kinship based social network, environment friendly cropping practices, and use of alternative sources of water (water-tanker, well-water for irrigation, arrange rain-making ritual to cope with climatic uncertainty in their lifetime.DOI: http://dx.doi.org/10.3126/dsaj.v5i0.6362Dhaulagiri Journal of Sociology and Anthropology Vol. 5, 2011: 171-90

Nuclear energy - the future climate

International Nuclear Information System (INIS)

Ash, Eric Sir

2000-01-01

In June 1999, a report entitled Nuclear Energy-The Future Climate was published and was the result of a collaboration between the Royal Society and the Royal Academy of Engineering. The report was the work of a group of nine people, made up of scientists, engineers and an economist, whose purpose was to attempt a new and objective look at the total energy scene and specifically the future role of nuclear energy. This paper discusses the findings of that report. (author)

Simulation of climate variability and anthropogenic climate change

International Nuclear Information System (INIS)

Bengtsson, Lennart

1999-01-01

The climatic changes in the last century were discussed and focus was on the questions: 1) What are the causes of the rapid climate fluctuations and 2) Is the global warming, which is observed during the last century, caused by natural or anthropogenic effects. It is concluded that an understanding of climate based on the interpretation of observational data only is not feasible, unless supported by an adequate theoretical interpretation. The capabilities of climatic models were discussed and the importance of incorporating 1) calculations of the internal variability of the atmosphere when forced from an ocean with prescribed sea surface temperature as well as for a system consisting of an atmosphere and a mixed ocean of limited depth, 2) a fully coupled atmospheric and ocean model and finally, 3) a fully coupled system including transiently changing greenhouse gases and aerosols. A short summation of the results is presented. The pronounced warming during the last century is not reproduced under the assumption of constant forcing and pollution emissions have to be incorporated into the models in order to bring the simulated data in agreement with observations

Future Projection of Ocean Wave Climate: Analysis of SST Impacts on Wave Climate Changes in the Western North Pacific

OpenAIRE

Shimura, Tomoya; Mori, Nobuhito; Mase, Hajime

2015-01-01

Changes in ocean surface waves elicit a variety of impacts on coastal environments. To assess the future changes in the ocean surface wave climate, several future projections of global wave climate have been simulated in previous studies. However, previously there has been little discussion about the causes behind changes in the future wave climate and the differences between projections. The objective of this study is to estimate the future changes in mean wave climate and the sensitivity of...

Future directions in climate modeling: A climate impacts perspective

International Nuclear Information System (INIS)

Mearns, L.O.

1990-01-01

One of the most serious impediments to further progress on the determination of specific impacts of climate change on relevant earth systems is the lack of precise and accurate scenarios of regional change. Spatial resolution of models is generally coarse (5-10 degree, corresponding to 550-1,100 km), and the modeling of physical processes is quite crude. Three main areas in which improvements in the modeling of physical processes are being made are modeling of surface processes, modeling of oceans and coupling of oceans and atmospheric models, and modeling of clouds. Improvements are required in the modeling of surface hydrology and vegetative effects, which have significant impact on the albedo scheme used. Oceans are important in climate modeling for the following reasons: delay of warming due to oceanic heat absorption; effect of mean meridional circulation; control of regional patterns of sea surface temperatures and sea ice by wind driven currents; absorption of atmospheric carbon dioxide by the oceans; and determination of interannual climatic variability via variability in sea surface temperature. The effects of clouds on radiation balance is highly significant. Clouds both reflect shortwave radiation and trap longwave radiation. Most cloud properties are sub-grid scale and thus difficult to include explicitly in models. 25 refs., 1 tab

Modelling the future biogeography of North Atlantic zooplankton communities in response to climate change

KAUST Repository

Villarino, E; Chust, G; Licandro, P; Butenschö n, M; Ibaibarriaga, L; Larrañ aga, A; Irigoien, Xabier

2015-01-01

Advances in habitat and climate modelling allow us to reduce uncertainties of climate change impacts on species distribution. We evaluated the impacts of future climate change on community structure, diversity, distribution and phenology of 14 copepod species in the North Atlantic. We developed and validated habitat models for key zooplankton species using continuous plankton recorder (CPR) survey data collected at mid latitudes of the North Atlantic. Generalized additive models (GAMs) were applied to relate the occurrence of species to environmental variables. Models were projected to future (2080–2099) environmental conditions using coupled hydroclimatix–biogeochemical models under the Intergovernmental Panel on Climate Change (IPCC) A1B climate scenario, and compared to present (2001–2020) conditions. Our projections indicated that the copepod community is expected to respond substantially to climate change: a mean poleward latitudinal shift of 8.7 km per decade for the overall community with an important species range variation (–15 to 18 km per decade); the species seasonal peak is expected to occur 12–13 d earlier for Calanus finmarchicus and C. hyperboreus; and important changes in community structure are also expected (high species turnover of 43–79% south of the Oceanic Polar Front). The impacts of the change expected by the end of the century under IPCC global warming scenarios on copepods highlight poleward shifts, earlier seasonal peak and changes in biodiversity spatial patterns that might lead to alterations of the future North Atlantic pelagic ecosystem. Our model and projections are supported by a temporal validation undertaken using the North Atlantic climate regime shift that occurred in the 1980s: the habitat model built in the cold period (1970–1986) has been validated in the warm period (1987–2004).

Modelling the future biogeography of North Atlantic zooplankton communities in response to climate change

KAUST Repository

Villarino, E

2015-07-02

Advances in habitat and climate modelling allow us to reduce uncertainties of climate change impacts on species distribution. We evaluated the impacts of future climate change on community structure, diversity, distribution and phenology of 14 copepod species in the North Atlantic. We developed and validated habitat models for key zooplankton species using continuous plankton recorder (CPR) survey data collected at mid latitudes of the North Atlantic. Generalized additive models (GAMs) were applied to relate the occurrence of species to environmental variables. Models were projected to future (2080–2099) environmental conditions using coupled hydroclimatix–biogeochemical models under the Intergovernmental Panel on Climate Change (IPCC) A1B climate scenario, and compared to present (2001–2020) conditions. Our projections indicated that the copepod community is expected to respond substantially to climate change: a mean poleward latitudinal shift of 8.7 km per decade for the overall community with an important species range variation (–15 to 18 km per decade); the species seasonal peak is expected to occur 12–13 d earlier for Calanus finmarchicus and C. hyperboreus; and important changes in community structure are also expected (high species turnover of 43–79% south of the Oceanic Polar Front). The impacts of the change expected by the end of the century under IPCC global warming scenarios on copepods highlight poleward shifts, earlier seasonal peak and changes in biodiversity spatial patterns that might lead to alterations of the future North Atlantic pelagic ecosystem. Our model and projections are supported by a temporal validation undertaken using the North Atlantic climate regime shift that occurred in the 1980s: the habitat model built in the cold period (1970–1986) has been validated in the warm period (1987–2004).

Climate change and climate variability: personal motivation for adaptation and mitigation.

Science.gov (United States)

Semenza, Jan C; Ploubidis, George B; George, Linda A

2011-05-21

Global climate change impacts on human and natural systems are predicted to be severe, far reaching, and to affect the most physically and economically vulnerable disproportionately. Society can respond to these threats through two strategies: mitigation and adaptation. Industry, commerce, and government play indispensable roles in these actions but so do individuals, if they are receptive to behavior change. We explored whether the health frame can be used as a context to motivate behavioral reductions of greenhouse gas emissions and adaptation measures. In 2008, we conducted a cross-sectional survey in the United States using random digit dialing. Personal relevance of climate change from health threats was explored with the Health Belief Model (HBM) as a conceptual frame and analyzed through logistic regressions and path analysis. Of 771 individuals surveyed, 81% (n = 622) acknowledged that climate change was occurring, and were aware of the associated ecologic and human health risks. Respondents reported reduced energy consumption if they believed climate change could affect their way of life (perceived susceptibility), Odds Ratio (OR) = 2.4 (95% Confidence Interval (CI): 1.4-4.0), endanger their life (perceived severity), OR = 1.9 (95% CI: 1.1-3.1), or saw serious barriers to protecting themselves from climate change, OR = 2.1 (95% CI: 1.2-3.5). Perceived susceptibility had the strongest effect on reduced energy consumption, either directly or indirectly via perceived severity. Those that reported having the necessary information to prepare for climate change impacts were more likely to have an emergency kit OR = 2.1 (95% CI: 1.4-3.1) or plan, OR = 2.2 (95% CI: 1.5-3.2) for their household, but also saw serious barriers to protecting themselves from climate change or climate variability, either by having an emergency kit OR = 1.6 (95% CI: 1.1-2.4) or an emergency plan OR = 1.5 (95%CI: 1.0-2.2). Motivation for voluntary mitigation is mostly dependent on

Reservoir Performance Under Future Climate For Basins With Different Hydrologic Sensitivities

Science.gov (United States)

Mateus, M. C.; Tullos, D. D.

2013-12-01

In addition to long-standing uncertainties related to variable inflows and market price of power, reservoir operators face a number of new uncertainties related to hydrologic nonstationarity, changing environmental regulations, and rapidly growing water and energy demands. This study investigates the impact, sensitivity, and uncertainty of changing hydrology on hydrosystem performance across different hydrogeologic settings. We evaluate the performance of reservoirs in the Santiam River basin, including a case study in the North Santiam Basin, with high permeability and extensive groundwater storage, and the South Santiam Basin, with low permeability, little groundwater storage and rapid runoff response. The modeling objective is to address the following study questions: (1) for the two hydrologic regimes, how does the flood management, water supply, and environmental performance of current reservoir operations change under future 2.5, 50 and 97.5 percentile streamflow projections; and (2) how much change in inflow is required to initiate a failure to meet downstream minimum or maximum flows in the future. We couple global climate model results with a rainfall-runoff model and a formal Bayesian uncertainty analysis to simulate future inflow hydrographs as inputs to a reservoir operations model. To evaluate reservoir performance under a changing climate, we calculate reservoir refill reliability, changes in flood frequency, and reservoir time and volumetric reliability of meeting minimum spring and summer flow target. Reservoir performance under future hydrology appears to vary with hydrogeology. We find higher sensitivity to floods for the North Santiam Basin and higher sensitivity to minimum flow targets for the South Santiam Basin. Higher uncertainty is related with basins with a more complex hydrologeology. Results from model simulations contribute to understanding of the reliability and vulnerability of reservoirs to a changing climate.

THE EVOLUTION OF ANNUAL MEAN TEMPERATURE AND PRECIPITATION QUANTITY VARIABILITY BASED ON ESTIMATED CHANGES BY THE REGIONAL CLIMATIC MODELS

Directory of Open Access Journals (Sweden)

Paula Furtună

2013-03-01

Full Text Available Climatic changes are representing one of the major challenges of our century, these being forcasted according to climate scenarios and models, which represent plausible and concrete images of future climatic conditions. The results of climate models comparison regarding future water resources and temperature regime trend can become a useful instrument for decision makers in choosing the most effective decisions regarding economic, social and ecologic levels. The aim of this article is the analysis of temperature and pluviometric variability at the closest grid point to Cluj-Napoca, based on data provided by six different regional climate models (RCMs. Analysed on 30 year periods (2001-2030,2031-2060 and 2061-2090, the mean temperature has an ascending general trend, with great varability between periods. The precipitation expressed trough percentage deviation shows a descending general trend, which is more emphazied during 2031-2060 and 2061-2090.

Climatic changes and uplift patterns - past, present and future

International Nuclear Information System (INIS)

Bjoerck, S.; Svensson, N.O.

1992-11-01

Our knowledge about the Pleistocene (= last 2.5 million years) climatic changes and their global environmental effects on the Earth system, e.g. the glacial-interglacial cycles, the sea level changes, and the significant crustal movements in glaciated regions, has increased greatly during the last decades. This report outlines the historical background and the present state-of-the-arts on these matters. Because the driving mechanisms and feed-back effects behind these changes have been more and more discussed in earth-science literature, analysed, and probably also better and better understood, it has become possible to present theoretical models for future climates (not including mans influence on the earth system). The report presents and discusses one such climate model (short of predicting mans future behaviour and its consequent effect on climate) and its likely implications on future climatic and glacial conditions, and bedrock movements, with focus on the Stockholm region. Possibilities for quaternary geologists to establish and map post glacial fault zones, related to irregular bedrock movements, are also briefly outlined in the report. (222 refs.)

Thermal barriers constrain microbial elevational range size via climate variability.

Science.gov (United States)

Wang, Jianjun; Soininen, Janne

2017-08-01

Range size is invariably limited and understanding range size variation is an important objective in ecology. However, microbial range size across geographical gradients remains understudied, especially on mountainsides. Here, the patterns of range size of stream microbes (i.e., bacteria and diatoms) and macroorganisms (i.e., macroinvertebrates) along elevational gradients in Asia and Europe were examined. In bacteria, elevational range size showed non-significant phylogenetic signals. In all taxa, there was a positive relationship between niche breadth and species elevational range size, driven by local environmental and climatic variables. No taxa followed the elevational Rapoport's rule. Climate variability explained the most variation in microbial mean elevational range size, whereas local environmental variables were more important for macroinvertebrates. Seasonal and annual climate variation showed negative effects, while daily climate variation had positive effects on community mean elevational range size for all taxa. The negative correlation between range size and species richness suggests that understanding the drivers of range is key for revealing the processes underlying diversity. The results advance the understanding of microbial species thermal barriers by revealing the importance of seasonal and diurnal climate variation, and highlight that aquatic and terrestrial biota may differ in their response to short- and long-term climate variability. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

Climate change and forest diseases: using todays knowledge to address future challenges

Energy Technology Data Exchange (ETDEWEB)

Sturrock, R. N.

2012-11-01

The health of the earths forests and urban green spaces is increasingly challenged by the outcomes of human activities, including global climate change. As climate changes, the role and impact of diseases on trees in both forest ecosystems and in urban settings will also change. Knowledge of relationships between climate variables and diseases affecting forest and urban trees is reviewed, with specific emphasis on those affecting foliage, shoots, and stems. Evidence that forest diseases are already responding to the earths changing climate is examined (e.g., Dothistroma needle blight in northern British Columbia) as are predicted scenarios for future changes in impact on forests by other tree diseases. Outbreaks of tree diseases caused by native and alien pathogens are predicted to become more frequent and intense this and other general predictions about the effects of climate change on forest and tree diseases are discussed. Despite the uncertainty that accompanies such predictions it is imperative that researchers, forest and urban tree managers, and policy makers work together to develop and implement management strategies that enhance the resilience of the worlds forests and urbanized trees. Strategies discussed include monitoring, forecasting, planning, and mitigation. (Author) 60 refs.

Relative Contributions of Mean-State Shifts and ENSO-Driven Variability to Precipitation Changes in a Warming Climate*

Energy Technology Data Exchange (ETDEWEB)

Bonfils, Céline J. W.; Santer, Benjamin D.; Phillips, Thomas J.; Marvel, Kate; Leung, L. Ruby; Doutriaux, Charles; Capotondi, Antonietta

2015-12-01

The El Niño-Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. Most climate models project an increase in the frequency of extreme El Niño events under increased greenhouse-gas (GHG) forcing. However, it is unclear how other aspects of ENSO and ENSO-driven teleconnections will evolve in the future. Here, we identify in 20th century sea-surface temperature (SST) observations a time-invariant ENSO-like (ENSOL) pattern that is largely uncontaminated by GHG forcing. We use this pattern to investigate the future precipitation (P) response to ENSO-like SST anomalies. Models that better capture observed ENSOL characteristics produce P teleconnection patterns that are in better accord with observations and more stationary in the 21st century. We decompose the future P response to ENSOL into the sum of three terms: (1) the change in P mean state, (2) the historical P response to ENSOL, and (3) a future enhancement in the P response to ENSOL. In many regions, this last term can aggravate the P extremes associated with ENSO variability. This simple decomposition allows us to identify regions likely to experience ENSOL-induced P changes that are without precedent in the current climate.

Long-Term Variability of Surface Albedo and Its Correlation with Climatic Variables over Antarctica

Directory of Open Access Journals (Sweden)

Minji Seo

2016-11-01

Full Text Available The cryosphere is an essential part of the earth system for understanding climate change. Components of the cryosphere, such as ice sheets and sea ice, are generally decreasing over time. However, previous studies have indicated differing trends between the Antarctic and the Arctic. The South Pole also shows internal differences in trends. These phenomena indicate the importance of continuous observation of the Polar Regions. Albedo is a main indicator for analyzing Antarctic climate change and is an important variable with regard to the radiation budget because it can provide positive feedback on polar warming and is related to net radiation and atmospheric heating in the mainly snow- and ice-covered Antarctic. Therefore, in this study, we analyzed long-term temporal and spatial variability of albedo and investigated the interrelationships between albedo and climatic variables over Antarctica. We used broadband surface albedo data from the Satellite Application Facility on Climate Monitoring and data for several climatic variables such as temperature and Antarctic oscillation index (AAO during the period of 1983 to 2009. Time series analysis and correlation analysis were performed through linear regression using albedo and climatic variables. The results of this research indicated that albedo shows two trends, west trend and an east trend, over Antarctica. Most of the western side of Antarctica showed a negative trend of albedo (about −0.0007 to −0.0015 year−1, but the other side showed a positive trend (about 0.0006 year−1. In addition, albedo and surface temperature had a negative correlation, but this relationship was weaker in west Antarctica than in east Antarctica. The correlation between albedo and AAO revealed different relationships in the two regions; west Antarctica had a negative correlation and east Antarctica showed a positive correlation. In addition, the correlation between albedo and AAO was weaker in the west. This

Understanding the Association Between School Climate and Future Orientation.

Science.gov (United States)

Lindstrom Johnson, Sarah; Pas, Elise; Bradshaw, Catherine P

2016-08-01

Promoting students' future orientation is inherently a goal of the educational system. Recently, it has received more explicit attention given the increased focus on career readiness. This study aimed to examine the association between school climate and adolescents' report of future orientation using data from youth (N = 27,698; 49.4 % female) across 58 high schools. Three-level hierarchical linear models indicated that perceptions of available emotional and service supports, rules and consequences, and parent engagement were positively related to adolescents' future orientation. Additionally, the school-level average future orientation was significantly related to individuals' future orientation, indicating a potential influence of contextual effects on this construct. Taken together, these findings suggest that interventions targeting school climate may hold promise for promoting future orientation.

Temperature response to future urbanization and climate change

Science.gov (United States)

Argüeso, Daniel; Evans, Jason P.; Fita, Lluís; Bormann, Kathryn J.

2014-04-01

This study examines the impact of future urban expansion on local near-surface temperature for Sydney (Australia) using a future climate scenario (A2). The Weather Research and Forecasting model was used to simulate the present (1990-2009) and future (2040-2059) climates of the region at 2-km spatial resolution. The standard land use of the model was replaced with a more accurate dataset that covers the Sydney area. The future simulation incorporates the projected changes in the urban area of Sydney to account for the expected urban expansion. A comparison between areas with projected land use changes and their surroundings was conducted to evaluate how urbanization and global warming will act together and to ascertain their combined effect on the local climate. The analysis of the temperature changes revealed that future urbanization will strongly affect minimum temperature, whereas little impact was detected for maximum temperature. The minimum temperature changes will be noticeable throughout the year. However, during winter and spring these differences will be particularly large and the increases could be double the increase due to global warming alone at 2050. Results indicated that the changes were mostly due to increased heat capacity of urban structures and reduced evaporation in the city environment.

Some aspects of climate variability in the north east Ethiopian ...

African Journals Online (AJOL)

This paper presents a review of climate variability in the northeast Ethiopian Highlands, particularly Wollo and Tigray, during the last 10000 years (the Holocene) and an analysis of rainfall variability during the historical period. To date little work has been done on climate reconstruction in Tigray and Wollo, however, ...

Influence of climate variability on large rivers runoff

Directory of Open Access Journals (Sweden)

B. Nurtaev

2015-06-01

Full Text Available In accordance with IPCC Report the influence of climate change on the water cycle will increase hydrologic variability by means of changing of precipitation patterns, melting of ice and change of runoff. Precipitation has increased in high northern latitudes and decreased in southern latitudes. This study presents an analysis of river runoffs trends in different climatic zones of the world in condition of climate change.

From Resistance to Receptiveness: Farmer Willingness to Participate in Extension Discussions About Climate Variability and Climate Change

Directory of Open Access Journals (Sweden)

David C. Diehl

2016-10-01

Full Text Available Identifying what Extension professionals believe are the critical elements of a communication strategy that is most likely to encourage agricultural producers to participate in discussions of climate variability and climate change is pivotal to providing timely solutions to issues facing farmers. The current study involved interviews with 50 Extension professionals from four southeastern states (Alabama, Florida, Georgia, and South Carolina who were engaged in ongoing work related to climate and agriculture. Respondents were asked to assess how best to engage farmers in conversations related to climate variability and climate change. Qualitative analysis showed that Extension professionals recommended avoiding content related to politics, attribution of climate change to human causes, and telling farmers what to do. Respondents recommended emphasizing adaptation strategies, climate variability over climate change, evidence that climate change exists, and the financial benefits for farmers. In addition, Extension professionals proposed several delivery methods they thought would be most effective with farmers, including delivery tailored to the characteristics of the audience, a positive overall tone, and an understanding that engagement should be viewed as a long-term process based on building relationships with farmers. The findings suggest that farmers are a potentially receptive audience on climate issues when properly approached.

Cocoa farming households' vulnerability to climate variability in Ekiti ...

African Journals Online (AJOL)

BRO OKOJIE

and protocols that control climate variability and change. Keywords: ... internal processes within the climate system. (internal ... adverse effects on the agricultural sector of the ... information and technology, social capital, ... Not accounting for.

Climate variability, farmland value, and farmers’ perceptions of climate change

NARCIS (Netherlands)

Arshad, Muhammad; Kächele, Harald; Krupnik, Timothy J.; Amjath-Babu, T.S.; Aravindakshan, Sreejith; Abbas, Azhar; Mehmood, Yasir; Müller, Klaus

2017-01-01

Many studies have examined the impact of climatic variability on agricultural productivity, although an understanding of these effects on farmland values and their relationship to farmers’ decisions to adapt and modify their land-use practices remains nascent in developing nations. We estimated

A Robust Decision-Making Technique for Water Management under Decadal Scale Climate Variability

Science.gov (United States)

Callihan, L.; Zagona, E. A.; Rajagopalan, B.

2013-12-01

Robust decision making, a flexible and dynamic approach to managing water resources in light of deep uncertainties associated with climate variability at inter-annual to decadal time scales, is an analytical framework that detects when a system is in or approaching a vulnerable state. It provides decision makers the opportunity to implement strategies that both address the vulnerabilities and perform well over a wide range of plausible future scenarios. A strategy that performs acceptably over a wide range of possible future states is not likely to be optimal with respect to the actual future state. The degree of success--the ability to avoid vulnerable states and operate efficiently--thus depends on the skill in projecting future states and the ability to select the most efficient strategies to address vulnerabilities. This research develops a robust decision making framework that incorporates new methods of decadal scale projections with selection of efficient strategies. Previous approaches to water resources planning under inter-annual climate variability combining skillful seasonal flow forecasts with climatology for subsequent years are not skillful for medium term (i.e. decadal scale) projections as decision makers are not able to plan adequately to avoid vulnerabilities. We address this need by integrating skillful decadal scale streamflow projections into the robust decision making framework and making the probability distribution of this projection available to the decision making logic. The range of possible future hydrologic scenarios can be defined using a variety of nonparametric methods. Once defined, an ensemble projection of decadal flow scenarios are generated from a wavelet-based spectral K-nearest-neighbor resampling approach using historical and paleo-reconstructed data. This method has been shown to generate skillful medium term projections with a rich variety of natural variability. The current state of the system in combination with the

Rainfall variability, climate change and regionalization in the African monsoon region

International Nuclear Information System (INIS)

Fontaine, Bernard; Roucou, Pascal; Vigaud, Nicolas; Camara, Moctar; Konare, Abdourahamane; Sanda, Seidou Ibrah; Diedhiou, Arona; Janicot, Serge

2012-01-01

This summary recalls some results at the end of the AMMA international experiment (2003-2010) in terms of variability of the African monsoon at the intra-seasonal to multi-decadal scales and of climate prospective. The results confirmed the weight of surface temperatures and marine tele-connections for inter-annual and decadal fluctuations and stressed the importance of atmospheric variability. They also described the dominant modes of intra-seasonal variability as their interactions with the surface. Several hypotheses involving memory effects related to soil water and vegetation, particularly in boreal spring and autumn have also been made. Prospective analysis from model output suggests rainfall surplus around 2050 over the Eastern-central Sahel and relative deficit to the West. Phase 2 of AMMA (2010-2020) will focus more on aspects that have a high social impact in direct collaboration with meteorological services predictability, prediction scores, operational indicators, evaluation of the part of anthropogenic forcing in the current and future variations. (authors)

Climate change and climate variability: personal motivation for adaptation and mitigation

Directory of Open Access Journals (Sweden)

Ploubidis George B

2011-05-01

Full Text Available Abstract Background Global climate change impacts on human and natural systems are predicted to be severe, far reaching, and to affect the most physically and economically vulnerable disproportionately. Society can respond to these threats through two strategies: mitigation and adaptation. Industry, commerce, and government play indispensable roles in these actions but so do individuals, if they are receptive to behavior change. We explored whether the health frame can be used as a context to motivate behavioral reductions of greenhouse gas emissions and adaptation measures. Methods In 2008, we conducted a cross-sectional survey in the United States using random digit dialing. Personal relevance of climate change from health threats was explored with the Health Belief Model (HBM as a conceptual frame and analyzed through logistic regressions and path analysis. Results Of 771 individuals surveyed, 81% (n = 622 acknowledged that climate change was occurring, and were aware of the associated ecologic and human health risks. Respondents reported reduced energy consumption if they believed climate change could affect their way of life (perceived susceptibility, Odds Ratio (OR = 2.4 (95% Confidence Interval (CI: 1.4 - 4.0, endanger their life (perceived severity, OR = 1.9 (95% CI: 1.1 - 3.1, or saw serious barriers to protecting themselves from climate change, OR = 2.1 (95% CI: 1.2 - 3.5. Perceived susceptibility had the strongest effect on reduced energy consumption, either directly or indirectly via perceived severity. Those that reported having the necessary information to prepare for climate change impacts were more likely to have an emergency kit OR = 2.1 (95% CI: 1.4 - 3.1 or plan, OR = 2.2 (95% CI: 1.5 -3.2 for their household, but also saw serious barriers to protecting themselves from climate change or climate variability, either by having an emergency kit OR = 1.6 (95% CI: 1.1 - 2.4 or an emergency plan OR = 1.5 (95%CI: 1.0 - 2

Computing the distribution of return levels of extreme warm temperatures for future climate projections

Energy Technology Data Exchange (ETDEWEB)

Pausader, M.; Parey, S.; Nogaj, M. [EDF/R and D, Chatou Cedex (France); Bernie, D. [Met Office Hadley Centre, Exeter (United Kingdom)

2012-03-15

In order to take into account uncertainties in the future climate projections there is a growing demand for probabilistic projections of climate change. This paper presents a methodology for producing such a probabilistic analysis of future temperature extremes. The 20- and 100-years return levels are obtained from that of the normalized variable and the changes in mean and standard deviation given by climate models for the desired future periods. Uncertainty in future change of these extremes is quantified using a multi-model ensemble and a perturbed physics ensemble. The probability density functions of future return levels are computed at a representative location from the joint probability distribution of mean and standard deviation changes given by the two combined ensembles of models. For the studied location, the 100-years return level at the end of the century is lower than 41 C with an 80% confidence. Then, as the number of model simulations is low to compute a reliable distribution, two techniques proposed in the literature (local pattern scaling and ANOVA) have been used to infer the changes in mean and standard deviation for the combinations of RCM and GCM which have not been run. The ANOVA technique leads to better results for the reconstruction of the mean changes, whereas the two methods fail to correctly infer the changes in standard deviation. As standard deviation change has a major impact on return level change, there is a need to improve the models and the different techniques regarding the variance changes. (orig.)

Farmers' Perceptions of Climate Variability and Factors Influencing Adaptation: Evidence from Anhui and Jiangsu, China.

Science.gov (United States)

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.

Reprint of “The future of hydropower in Europe: Interconnecting climate, markets and policies”

International Nuclear Information System (INIS)

Gaudard, Ludovic; Romerio, Franco

2014-01-01

Highlights: • Connecting the knowledges from various domains, in particular economics, engineering, policy and hydrology. • Giving the keys to assess the linking between hydropower, climate and electricity market. • Making an overall analysis. - Abstract: Hydropower is very important for electricity supply security in the European inter-connexion as well as for the economy of regions (primarily peripheral) that possess water resources. Its future may however be jeopardized by several factors: climate change, the development of new renewable energy, the creation of super and micro-grids, and progress in power storage technology. Energy and climate policy, as well as electricity market design and dynamics play a pivotal role. This article carries out a comprehensive analysis of all these factors and discusses the future of hydropower. This discussion follows an overview of the present situation and of future drivers. The technical, environmental, economic and political aspects of the problem are analyzed with an interdisciplinary approach. The stakes as well as the uncertainties are highlighted. The conclusion is that hydropower has a promising future, particularly in light of emerging sustainable energy policy, but that the risks should not be overlooked. Academics will find a comprehensive interdisciplinary analysis of hydropower in this article, whereas public bodies, communities and hydropower companies can identify the strategic variables that should be taken into consideration in the decision making process. The end of water concessions or authorizations is also evoked

Conveying the Science of Climate Change: Explaining Natural Variability

Science.gov (United States)

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.

AMOC decadal variability in Earth system models: Mechanisms and climate impacts

Energy Technology Data Exchange (ETDEWEB)

Fedorov, Alexey [Yale Univ., New Haven, CT (United States)

2017-09-06

This is the final report for the project titled "AMOC decadal variability in Earth system models: Mechanisms and climate impacts". The central goal of this one-year research project was to understand the mechanisms of decadal and multi-decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) within a hierarchy of climate models ranging from realistic ocean GCMs to Earth system models. The AMOC is a key element of ocean circulation responsible for oceanic transport of heat from low to high latitudes and controlling, to a large extent, climate variations in the North Atlantic. The questions of the AMOC stability, variability and predictability, directly relevant to the questions of climate predictability, were at the center of the research work.

Methods for assessment of climate variability and climate changes in different time-space scales

International Nuclear Information System (INIS)

Lobanov, V.; Lobanova, H.

2004-01-01

Main problem of hydrology and design support for water projects connects with modern climate change and its impact on hydrological characteristics as observed as well as designed. There are three main stages of this problem: - how to extract a climate variability and climate change from complex hydrological records; - how to assess the contribution of climate change and its significance for the point and area; - how to use the detected climate change for computation of design hydrological characteristics. Design hydrological characteristic is the main generalized information, which is used for water management and design support. First step of a research is a choice of hydrological characteristic, which can be as a traditional one (annual runoff for assessment of water resources, maxima, minima runoff, etc) as well as a new one, which characterizes an intra-annual function or intra-annual runoff distribution. For this aim a linear model has been developed which has two coefficients connected with an amplitude and level (initial conditions) of seasonal function and one parameter, which characterizes an intensity of synoptic and macro-synoptic fluctuations inside a year. Effective statistical methods have been developed for a separation of climate variability and climate change and extraction of homogeneous components of three time scales from observed long-term time series: intra annual, decadal and centural. The first two are connected with climate variability and the last (centural) with climate change. Efficiency of new methods of decomposition and smoothing has been estimated by stochastic modeling and well as on the synthetic examples. For an assessment of contribution and statistical significance of modern climate change components statistical criteria and methods have been used. Next step has been connected with a generalization of the results of detected climate changes over the area and spatial modeling. For determination of homogeneous region with the same

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

Science.gov (United States)

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

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

Science.gov (United States)

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

Decadal analysis of impact of future climate on wheat production in dry Mediterranean environment: A case of Jordan.

Science.gov (United States)

Dixit, Prakash N; Telleria, Roberto; Al Khatib, Amal N; Allouzi, Siham F

2018-01-01

Different aspects of climate change, such as increased temperature, changed rainfall and higher atmospheric CO 2 concentration, all have different effects on crop yields. Process-based crop models are the most widely used tools for estimating future crop yield responses to climate change. We applied APSIM crop simulation model in a dry Mediterranean climate with Jordan as sentinel site to assess impact of climate change on wheat production at decadal level considering two climate change scenarios of representative concentration pathways (RCP) viz., RCP4.5 and RCP8.5. Impact of climatic variables alone was negative on grain yield but this adverse effect was negated when elevated atmospheric CO 2 concentrations were also considered in the simulations. Crop cycle of wheat was reduced by a fortnight for RCP4.5 scenario and by a month for RCP8.5 scenario at the approach of end of the century. On an average, a grain yield increase of 5 to 11% in near future i.e., 2010s-2030s decades, 12 to 16% in mid future i.e., 2040s-2060s decades and 9 to 16% in end of century period can be expected for moderate climate change scenario (RCP4.5) and 6 to 15% in near future, 13 to 19% in mid future and 7 to 20% increase in end of century period for a drastic climate change scenario (RCP8.5) based on different soils. Positive impact of elevated CO 2 is more pronounced in soils with lower water holding capacity with moderate increase in temperatures. Elevated CO 2 had greater positive effect on transpiration use efficiency (TUE) than negative effect of elevated mean temperatures. The change in TUE was in near perfect direct relationship with elevated CO 2 levels (R 2 >0.99) and every 100-ppm atmospheric CO 2 increase resulted in TUE increase by 2kgha -1 mm -1 . Thereby, in this environment yield gains are expected in future and farmers can benefit from growing wheat. Copyright © 2017 Elsevier B.V. All rights reserved.

Impacts of Climate Variability on Latin American Small-scale Fisheries

Directory of Open Access Journals (Sweden)

Omar Defeo

2013-12-01

Full Text Available Small-scale fisheries (SSFs are social-ecological systems that play a critical role in terms of food security and poverty alleviation in Latin America. These fisheries are increasingly threatened by anthropogenic and climatic drivers acting at multiple scales. We review the effects of climate variability on Latin American SSFs, and discuss the combined effects of two additional human drivers: globalization of markets and governance. We show drastic long-term and large-scale effects of climate variability, e.g., sea surface temperature anomalies, wind intensity, sea level, and climatic indices, on SSFs. These variables, acting in concert with economic drivers, have exacerbated stock depletion rates in Latin American SSFs. The impact of these drivers varied according to the life cycle and latitudinal distribution of the target species, the characteristics of the oceanographic systems, and the inherent features of the social systems. Our review highlights the urgent need to improve management and governance systems to promote resilience as a way to cope with the increasing uncertainty about the impacts of climate and globalization of markets on Latin American SSFs.

Climate Change Impact on Variability of Rainfall Intensity in Upper Blue Nile Basin, Ethiopia

Science.gov (United States)

Worku, L. Y.

2015-12-01

Extreme rainfall events are major problems in Ethiopia with the resulting floods that usually could cause significant damage to agriculture, ecology, infrastructure, disruption to human activities, loss of property, loss of lives and disease outbreak. The aim of this study was to explore the likely changes of precipitation extreme changes due to future climate change. The study specifically focuses to understand the future climate change impact on variability of rainfall intensity-duration-frequency in Upper Blue Nile basin. Precipitations data from two Global Climate Models (GCMs) have been used in the study are HadCM3 and CGCM3. Rainfall frequency analysis was carried out to estimate quantile with different return periods. Probability Weighted Method (PWM) selected estimation of parameter distribution and L-Moment Ratio Diagrams (LMRDs) used to find the best parent distribution for each station. Therefore, parent distributions for derived from frequency analysis are Generalized Logistic (GLOG), Generalized Extreme Value (GEV), and Gamma & Pearson III (P3) parent distribution. After analyzing estimated quantile simple disaggregation model was applied in order to find sub daily rainfall data. Finally the disaggregated rainfall is fitted to find IDF curve and the result shows in most parts of the basin rainfall intensity expected to increase in the future. As a result of the two GCM outputs, the study indicates there will be likely increase of precipitation extremes over the Blue Nile basin due to the changing climate. This study should be interpreted with caution as the GCM model outputs in this part of the world have huge uncertainty.

Adaptation to floods in future climate: a practical approach

Science.gov (United States)

Doroszkiewicz, Joanna; Romanowicz, Renata; Radon, Radoslaw; Hisdal, Hege

2016-04-01

In this study some aspects of the application of the 1D hydraulic model are discussed with a focus on its suitability for flood adaptation under future climate conditions. The Biała Tarnowska catchment is used as a case study. A 1D hydraulic model is developed for the evaluation of inundation extent and risk maps in future climatic conditions. We analyse the following flood indices: (i) extent of inundation area; (ii) depth of water on flooded land; (iii) the flood wave duration; (iv) the volume of a flood wave over the threshold value. In this study we derive a model cross-section geometry following the results of primary research based on a 500-year flood inundation extent. We compare two methods of localisation of cross-sections from the point of view of their suitability to the derivation of the most precise inundation outlines. The aim is to specify embankment heights along the river channel that would protect the river valley in the most vulnerable locations under future climatic conditions. We present an experimental design for scenario analysis studies and uncertainty reduction options for future climate projections obtained from the EUROCORDEX project. Acknowledgements: This work was supported by the project CHIHE (Climate Change Impact on Hydrological Extremes), carried out in the Institute of Geophysics Polish Academy of Sciences, funded by Norway Grants (contract No. Pol-Nor/196243/80/2013). The hydro-meteorological observations were provided by the Institute of Meteorology and Water Management (IMGW), Poland.

Climate variability and temporal trends of persistent organic pollutants in the arctic: a study of glaucous gulls.

Science.gov (United States)

Bustnes, Jan O; Gabrielsen, Geir W; Verreault, Jonathan

2010-04-15

The impact of climate variability on temporal trends (1997-2006) of persistent organic pollutants (POPs; polychlorinated biphenyls [PCB], hexachlorobenzene [HCB], and oxychlordane) was assessed in glaucous gulls (Larus hyperboreus) breeding in the Norwegian Arctic (n = 240). The Arctic Oscillation (AO: an index of sea-level pressure variability in the Northern Hemisphere above 20 degrees N) with different time lags was used as a climate proxy. The estimated concentrations of POPs in glaucous gull blood/plasma declined substantially (16-60%) over the time period. Multiple regression analyses showed that the rates of decline for POPs were correlated to climate variation when controlling for potential confounding variables (sex and body condition). More specifically AO in the current winter showed negative associations with POP concentrations, whereas the relationships with AO measurements from the year preceding POP measurements (AO preceding summer and AO preceding winter) were positive. Hence, gulls had relatively higher POP concentrations in breeding seasons following years with high air transport toward the Arctic. Furthermore, the impact of AO appeared to be stronger for HCB, a relatively volatile compound with high transport potential, compared to heavy chlorinated PCB congeners. This study thus suggests that predicted climate change should be considered in assessments of future temporal trends of POPs in Arctic wildlife.

Effects of climate variability and functional changes on the interannual variation of the carbon balance in a temperate deciduous forest

DEFF Research Database (Denmark)

Wu, Jian; van der Linden, Leon; Lasslop, G.

2012-01-01

scale, direct climatic variability and changes in ecosystem functional properties regulated the IAV of the carbon balance at this site. Correlation analysis showed that the sensitivity of carbon fluxes to climatic variability was significantly higher at shorter than at longer time scales and changed...... seasonally. Ecosystem response anomalies implied that changes in the distribution of climate anomalies during the vegetation period will have stronger impacts on future ecosystem carbon balances than changes in average climate. We improved a published modelling approach which distinguishes the direct....... At the annual time scale as much as 80% of the IAV in NEE was attributed to the variation in photosynthesis and respiration related model parameters. Our results suggest that the observed decadal NEE trend at the investigated site was dominated by changes in ecosystem functioning. In general this study showed...

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

Science.gov (United States)

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.

Potential impacts of agricultural drought on crop yield variability under a changing climate in Texas

Science.gov (United States)

Lee, K.; Leng, G.; Huang, M.; Sheffield, J.; Zhao, G.; Gao, H.

2017-12-01

Texas has the largest farm area in the U.S, and its revenue from crop production ranks third overall. With the changing climate, hydrological extremes such as droughts are becoming more frequent and intensified, causing significant yield reduction in rainfed agricultural systems. The objective of this study is to investigate the potential impacts of agricultural drought on crop yields (corn, sorghum, and wheat) under a changing climate in Texas. The Variable Infiltration Capacity (VIC) model, which is calibrated and validated over 10 major Texas river basins during the historical period, is employed in this study.The model is forced by a set of statistically downscaled climate projections from Coupled Model Intercomparison Project Phase 5 (CMIP5) model ensembles at a spatial resolution of 1/8°. The CMIP5 projections contain four Representative Concentration Pathways (RCP) that represent different greenhouse gas concentration (4.5 and 8.5 w/m2 are selected in this study). To carry out the analysis, VIC simulations from 1950 to 2099 are first analyzed to investigate how the frequency and severity of agricultural droughts will be altered in Texas (under a changing climate). Second, future crop yields are projected using a statistical crop model. Third, the effects of agricultural drought on crop yields are quantitatively analyzed. The results are expected to contribute to future water resources planning, with a goal of mitigating the negative impacts of future droughts on agricultural production in Texas.

Analysis of the Relationship Between Climate and NDVI Variability at Global Scales

Science.gov (United States)

Zeng, Fan-Wei; Collatz, G. James; Pinzon, Jorge; Ivanoff, Alvaro

2011-01-01

interannual variability in modeled (CASA) C flux is in part caused by interannual variability in Normalized Difference Vegetation Index (NDVI) Fraction of Photosynthetically Active Radiation (FPAR). This study confirms a mechanism producing variability in modeled NPP: -- NDVI (FPAR) interannual variability is strongly driven by climate; -- The climate driven variability in NDVI (FPAR) can lead to much larger fluctuation in NPP vs. the NPP computed from FPAR climatology

Securing African forests for future drier climates: applying ...

African Journals Online (AJOL)

We argue that ecophysiological data will be crucial to future-proof tree improvement strategies in African commodity production landscapes, especially given future drier climates. Keywords: developing nations, drought tolerance, forest resilience, forest sustainability, plantation forestry, tree hydric strategy, wood anatomical ...

Internal variability of a dynamically downscaled climate over North America

Energy Technology Data Exchange (ETDEWEB)

Wang, Jiali; Bessac, Julie; Kotamarthi, Rao; Constantinescu, Emil; Drewniak, Beth

2017-09-08

This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 km and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late 21st century. However, the IV is larger than the projected changes in precipitation for the mid- and late 21st century.

Internal variability of a dynamically downscaled climate over North America

Energy Technology Data Exchange (ETDEWEB)

Wang, Jiali; Bessac, Julie; Kotamarthi, Rao; Constantinescu, Emil; Drewniak, Beth

2017-09-08

This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.

Internal variability of a dynamically downscaled climate over North America

Science.gov (United States)

Wang, Jiali; Bessac, Julie; Kotamarthi, Rao; Constantinescu, Emil; Drewniak, Beth

2017-09-01

This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.

Internal variability of a dynamically downscaled climate over North America

Science.gov (United States)

Wang, Jiali; Bessac, Julie; Kotamarthi, Rao; Constantinescu, Emil; Drewniak, Beth

2018-06-01

This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.

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

Science.gov (United States)

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.

International conference on past, present and future climate. Proceedings

Energy Technology Data Exchange (ETDEWEB)

Heikinheimo, P [ed.

1996-12-31

This publications contains the proceedings of the International Conference on Past, Present and Future Climate, held in Helsinki, Finland, on 22-25 August 1995. Conference was organized to serve at least two purposes. First, it was the fourth meeting in a series of Nordic climate conferences. Earlier Nordic meetings had been held in Copenhagen (1978), Stockholm (1983) and Tromsoe (1990). Secondly, the conference formed part of the integration activities of the Finnish Research Programme on Climate Change (SILMU). Four central themes were selected for the conference: (1) climatic changes since the last glaciation inferred from proxy data,(2) detection of climate change from the instrumental record,(3) changes in atmospheric composition, (4) predicting future climate. The Finnish Research Programme on Climate Change was in its sixth and final year at the time of the conference. One of the aims of the meeting was to foster the communication of SlLMU`s results to the scientific community at large. On the other hand, feedback from overseas colleagues was expected to be beneficial for the final reporting of the results of the research programme. Altogether 117 scientific contributions were submitted and more than 140 scientists attended the conference

International conference on past, present and future climate. Proceedings

Energy Technology Data Exchange (ETDEWEB)

Heikinheimo, P. [ed.

1995-12-31

This publications contains the proceedings of the International Conference on Past, Present and Future Climate, held in Helsinki, Finland, on 22-25 August 1995. Conference was organized to serve at least two purposes. First, it was the fourth meeting in a series of Nordic climate conferences. Earlier Nordic meetings had been held in Copenhagen (1978), Stockholm (1983) and Tromsoe (1990). Secondly, the conference formed part of the integration activities of the Finnish Research Programme on Climate Change (SILMU). Four central themes were selected for the conference: (1) climatic changes since the last glaciation inferred from proxy data,(2) detection of climate change from the instrumental record,(3) changes in atmospheric composition, (4) predicting future climate. The Finnish Research Programme on Climate Change was in its sixth and final year at the time of the conference. One of the aims of the meeting was to foster the communication of SlLMU`s results to the scientific community at large. On the other hand, feedback from overseas colleagues was expected to be beneficial for the final reporting of the results of the research programme. Altogether 117 scientific contributions were submitted and more than 140 scientists attended the conference

Rainfall variability over southern Africa: an overview of current research using satellite and climate model data

Science.gov (United States)

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

2009-04-01

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 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 is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. In this research, satellite-derived rainfall data are used as a basis for undertaking model experiments using a state-of-the-art climate model, run at both high and low spatial resolution. Once the model's ability to reproduce extremes has been assessed, idealised regions of sea surface temperature (SST) anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, a brief overview is given of the authors' research to date, pertaining to southern African rainfall. This covers (i) a description of present-day rainfall variability over southern Africa; (ii) a comparison of model simulated daily rainfall with the satellite-derived dataset; (iii) results from sensitivity testing of the model's domain size; and (iv) results from the idealised SST experiments.

Using ERA-Interim reanalysis for creating datasets of energy-relevant climate variables

Science.gov (United States)

Jones, Philip D.; Harpham, Colin; Troccoli, Alberto; Gschwind, Benoit; Ranchin, Thierry; Wald, Lucien; Goodess, Clare M.; Dorling, Stephen

2017-07-01

The construction of a bias-adjusted dataset of climate variables at the near surface using ERA-Interim reanalysis is presented. A number of different, variable-dependent, bias-adjustment approaches have been proposed. Here we modify the parameters of different distributions (depending on the variable), adjusting ERA-Interim based on gridded station or direct station observations. The variables are air temperature, dewpoint temperature, precipitation (daily only), solar radiation, wind speed, and relative humidity. These are available on either 3 or 6 h timescales over the period 1979-2016. The resulting bias-adjusted dataset is available through the Climate Data Store (CDS) of the Copernicus Climate Change Data Store (C3S) and can be accessed at present from climate.copernicus.eu" target="_blank">ftp://ecem.climate.copernicus.eu. The benefit of performing bias adjustment is demonstrated by comparing initial and bias-adjusted ERA-Interim data against gridded observational fields.

Future extreme events in European climate: An exploration of regional climate model projections

DEFF Research Database (Denmark)

Beniston, M.; Stephenson, D.B.; Christensen, O.B.

2007-01-01

-90) and future (2071-2 100) climate on the basis of regional climate model simulations produced by the PRUDENCE project. A summary of the main results follows. Heat waves - Regional surface warming causes the frequency, intensity and duration of heat waves to increase over Europe. By the end of the twenty first...

Development of a High-Resolution Climate Model for Future Climate Change Projection on the Earth Simulator

Science.gov (United States)

Kanzawa, H.; Emori, S.; Nishimura, T.; Suzuki, T.; Inoue, T.; Hasumi, H.; Saito, F.; Abe-Ouchi, A.; Kimoto, M.; Sumi, A.

2002-12-01

The fastest supercomputer of the world, the Earth Simulator (total peak performance 40TFLOPS) has recently been available for climate researches in Yokohama, Japan. We are planning to conduct a series of future climate change projection experiments on the Earth Simulator with a high-resolution coupled ocean-atmosphere climate model. The main scientific aims for the experiments are to investigate 1) the change in global ocean circulation with an eddy-permitting ocean model, 2) the regional details of the climate change including Asian monsoon rainfall pattern, tropical cyclones and so on, and 3) the change in natural climate variability with a high-resolution model of the coupled ocean-atmosphere system. To meet these aims, an atmospheric GCM, CCSR/NIES AGCM, with T106(~1.1o) horizontal resolution and 56 vertical layers is to be coupled with an oceanic GCM, COCO, with ~ 0.28ox 0.19o horizontal resolution and 48 vertical layers. This coupled ocean-atmosphere climate model, named MIROC, also includes a land-surface model, a dynamic-thermodynamic seaice model, and a river routing model. The poles of the oceanic model grid system are rotated from the geographic poles so that they are placed in Greenland and Antarctic land masses to avoild the singularity of the grid system. Each of the atmospheric and the oceanic parts of the model is parallelized with the Message Passing Interface (MPI) technique. The coupling of the two is to be done with a Multi Program Multi Data (MPMD) fashion. A 100-model-year integration will be possible in one actual month with 720 vector processors (which is only 14% of the full resources of the Earth Simulator).

Climate indices of Iran under climate change

OpenAIRE

alireza kochaki; mehdi nasiry; gholamali kamali

2009-01-01

Global warming will affect all climatic variables and particularly rainfall patterns. The purpose of present investigation was to predict climatic parameters of Iran under future climate change and to compare them with the present conditions. For this reason, UKMO General Circulation Model was used for the year 2025 and 2050. By running the model, minimum and maximum monthly temperature and also maximum monthly rainfall for the representative climate stations were calculated and finally the e...

Water planning in a changing climate: how do you plan for a future when the past no longer represents the future?

International Nuclear Information System (INIS)

Yuen, Emma

2007-01-01

Full text: Full text: By 2030, the catchments across south-west Western Australia can expect decreases in runoff ranging from 5% to 40% relative to 1990. This has ramifications, not only for consumptive and non-consumptive uses, but for the way decisions are made in an environment of uncertainty. Traditionally, water planning has assumed a static environment whereby statistically defensible climatic records have been used in decision-making. While climate modelling may provide projections of plausible climatic futures, this needs to be integrated with socio-political and economic futures when considering the environment in which regional water plans will apply. Where climate change is slow, enabling biophysical and social systems have time to adapt to long-term water resources planning needs that incorporate principles of intergenerational equity, the precautionary principle and resilience in management strategies. However where changes in climate are poorly recognised against the background of inherent climate variability or where step changes in rainfall occur or threshold assimilative levels of ecosystems are exceeded, conflict and uncertainty challenge the decisionmaking processes. Within the backdrop of climate change, the Department of Water is developing a Regional Water Plan for the southwest which will set the strategic direction on water resources for the next 25 years. In order to move forward with this process, the water sector must undergo a number of transformations: from linear science to complex dynamic systems thinking; from 'decide and defend'to increased community engagement when dealing with both complexity and uncertainty; from conservation of 'museum pieces' to innovation, partnerships and adaptive management. This paper will discuss the philosophy behind the decision-making framework based on experiences from business management and other sectors. It will also discuss an action research process that could be used in the South West Water Plan

A modelling methodology for assessing the impact of climate variability and climatic change on hydroelectric generation

International Nuclear Information System (INIS)

Munoz, J.R.; Sailor, D.J.

1998-01-01

A new methodology relating basic climatic variables to hydroelectric generation was developed. The methodology can be implemented in large or small basins with any number of hydro plants. The method was applied to the Sacramento, Eel and Russian river basins in northern California where more than 100 hydroelectric plants are located. The final model predicts the availability of hydroelectric generation for the entire basin provided present and near past climate conditions, with about 90% accuracy. The results can be used for water management purposes or for analyzing the effect of climate variability on hydrogeneration availability in the basin. A wide range of results can be obtained depending on the climate change scenario used. (Author)

Assessing potential changes of chestnut productivity in Europe under future climate conditions

Science.gov (United States)

Calheiros, T.; Pereira, M. G.; Pinto, J. G.; Caramelo, L.; Gomes-Laranjo, J.; Dacamara, C. C.

2012-04-01

The European chestnut is cultivated for its nuts and wood. Several studies point to the dependency of chestnut productivity on specific soil and climate characteristics. For instance, this species dislikes chalky and poorly drained soils, appreciates sedimentary, siliceous and acidic to neutral soils. Chestnut trees also seems to appreciate annual mean values of sunlight spanning between 2400 and 2600 h, rainfall ranging between 600 and 1500 mm, mean annual temperature between 9 and 13°C, 27°C being the mean of the maximum temperature (Heiniger and Conedera, 1992; Gomes-Laranjo et al.,2008). The amount of heat between May and October must range between 1800°D and 2400°D (Dinis et al., 2011) . In Poland, the growing season is defined as the period of time when the mean 24-h temperature is greater than 5°C (Wilczynski and Podalski, 2007). In Portugal, maximum photosynthetic activity occurs at 24-28°C for adult trees, but exhibits more than 50% of termoinhibition when the air temperature is above 32°C, which is frequent during summer (Gomes- Laranjo et al., 2006, 2008). Recently Pereira et al (2011) identified a set of meteorological variables/parameters with high impact on chestnut productivity. The main purpose of this work is to assess the potential impacts of future climate change on chestnut productivity in Portugal as well as on European chestnut orchards. First, observed data from the European Climate assessment (ECA) and simulations with the Regional Circulation Model (RCM) COSMO-CLM for recent climate conditions are used to assess the ability of the RCM to model the actual meteorological conditions. Then, ensemble projections from the ECHAM5/COSMO-CLM model chain for two climate scenarios (A1B and B1) are used to estimate the values of relevant meteorological variables and parameters und future climate conditions. Simulated values are then compared with those obtained for present climate. Results point to changes in the spatial and temporal

Climate variability and yields of major staple food crops in Northern ...

African Journals Online (AJOL)

Conversely, agriculture is a major contributor to climate variability and change by emitting greenhouse gases and reducing the agroecology's potential for carbon sequestration. What however, is the empirical evidence of this inter-dependence of climate variability and agriculture in Sub-Sahara Africa? In this paper, we ...

Atmospheric radiative feedbacks associated with transient climate change and climate variability

Energy Technology Data Exchange (ETDEWEB)

Colman, Robert A.; Power, Scott B. [Bureau of Meteorology, Centre for Australian Weather and Climate Research, GPO Box 1289, Melbourne, VIC (Australia)

2010-06-15

to mid-latitude response seen under secular climate change. Surface albedo feedback is, however, slightly stronger under interannual variability - partly due to regions of extremely weak, or even negative, feedback over Antarctic sea ice in the transient experiment. Both long and shortwave global cloud feedbacks are essentially zero on interannual timescales, with the shortwave term also being very weak under climate change, although cloud fraction and optical property components show correlation with global temperature both under interannual variability and transient climate change. The results of this modelling study, although for a single model only, suggest that the analogues provided by interannual variability may provide some useful pointers to some aspects of climate change feedback strength, particularly for water vapour and surface albedo, but that structural differences will need to be heeded in such an analysis. (orig.)

Climate Variability and Change in the Mediterranean Region

Science.gov (United States)

Lionello, Piero; Özsoy, Emin; Planton, Serge; Zanchetta, Giovanni

2017-04-01

This special issue collects new research results on the climate of the Mediterranean region. It covers traditional topics of the MedCLIVAR programme (www.medclivar.eu, Lionello et al. 2006, Lionello et al. 2012b) being devoted to papers addressing on-going and future climate changes in the Mediterranean region and their impacts on its environment.

Assessing the impact of future climate change on groundwater recharge in Galicia-Costa, Spain

Science.gov (United States)

Raposo, Juan Ramón; Dafonte, Jorge; Molinero, Jorge

2013-03-01

Climate change can impact the hydrological processes of a watershed and may result in problems with future water supply for large sections of the population. Results from the FP5 PRUDENCE project suggest significant changes in temperature and precipitation over Europe. In this study, the Soil and Water Assessment Tool (SWAT) model was used to assess the potential impacts of climate change on groundwater recharge in the hydrological district of Galicia-Costa, Spain. Climate projections from two general circulation models and eight different regional climate models were used for the assessment and two climate-change scenarios were evaluated. Calibration and validation of the model were performed using a daily time-step in four representative catchments in the district. The effects on modeled mean annual groundwater recharge are small, partly due to the greater stomatal efficiency of plants in response to increased CO2 concentration. However, climate change strongly influences the temporal variability of modeled groundwater recharge. Recharge may concentrate in the winter season and dramatically decrease in the summer-autumn season. As a result, the dry-season duration may be increased on average by almost 30 % for the A2 emission scenario, exacerbating the current problems in water supply.

The Future of Climate Science (Invited)

Science.gov (United States)

Bishop, R.

2010-12-01

High Performance Computing is currently deployed in several centers for climate research, but not at the levels needed to achieve substantial success on a global basis, given the complexity of the problem. A quantum leap in capabilities will be necessary to handle next-generation climate models that integrate newly emerging sciences, high-resolution grids, and voluminous observational data from satellites and sophisticated ground devices. Dr. Bishop will discuss efforts to build an International Centre for Earth Simulation (ICES) based in Switzerland that takes an holistic systems approach, and that has the competence and resources to achieve new insights in this new decade, and is capable to globally influence public policy with respect to weather, climate, environment, disaster risk reduction and socio-economic development. On this progressively crowded and fragile planet, such a capability will be invaluable, Bishop believes, if not imperative, for our long-term survival. ICES could serve as a test-bed for large scale public and private development planning. Decision makers could ask ‘what if’ questions for major construction projects (such as China’s Three Gorges Dam), and then interactively evaluate alternative scenarios. Likewise, ICES could help uncover the possible unintended consequences of climate remediation and adaptation strategies, geo-engineering ideas, CO2 sequestration, deep sea drilling, etc. ICES would be a resource for building more resilient societies in an era of rapid climate change and frequent natural disasters (such as flooding, extreme weather events and volcanic ash clouds), and therefore of great consequence to our future well-being. It would ultimately play a major role in the education and training of policy-makers, the public, and future Earth Scientists - in conjunction with the current national and regional centers.

Climate variability: Possible changes with climate change and impacts on crop yields

International Nuclear Information System (INIS)

Mearns, L.O.

1991-01-01

A pilot study was carried out of the sensitivity of the CERES wheat model, a deterministic crop-climate model, to changes in the interannual variability of temperature and precipitation. The study was designed to determine the effect of changed temperature variance on the mean and variance of the simulated yields, to compare the effect with the effect of mean temperature changes, and to determine the interacting effects of changes in mean and variance of temperature. The CERES model was applied to 29 cropping years (1952-1980), using three different soil types and two different management practices (fully irrigated and dryland). The coefficients of variation of the yields for irrigated and dryland conditions are plotted against variance change. It was found that in both management systems, the yield response is usually greater to increases rather than decreases in variance. The combined effect of mean and variance temperature changes are most striking under irrigated conditions, with a dramatic decrease in yield variability in the high mean climate change scenario with decreased temperature variance. This suggests that the variability decrease might mitigate the effect of a mean increase in temperature. This result is not found with the dryland case, where decreased temperature variability has little impact on yield variability. 12 refs., 4 figs

Nature Relation Between Climatic Variables and Cotton Production

Directory of Open Access Journals (Sweden)

Zakaria M. Sawan

2014-08-01

Full Text Available This study investigated the effect of climatic variables on flower and boll production and retention in cotton (Gossypium barbadense. Also, this study investigated the relationship between climatic factors and production of flowers and bolls obtained during the development periods of the flowering and boll stage, and to determine the most representative period corresponding to the overall crop pattern. Evaporation, sunshine duration, relative humidity, surface soil temperature at 1800 h, and maximum air temperature, are the important climatic factors that significantly affect flower and boll production. The least important variables were found to be surface soil temperature at 0600 h and minimum temperature. There was a negative correlation between flower and boll production and either evaporation or sunshine duration, while that correlation with minimum relative humidity was positive. Higher minimum relative humidity, short period of sunshine duration, and low temperatures enhanced flower and boll formation.

Rainwater catchment system design using simulated future climate data

Science.gov (United States)

Wallace, Corey D.; Bailey, Ryan T.; Arabi, Mazdak

2015-10-01

Rainwater harvesting techniques are used worldwide to augment potable water supply, provide water for small-scale irrigation practices, increase rainwater-use efficiency for sustained crop growth in arid and semi-arid regions, decrease urban stormwater flow volumes, and in general to relieve dependency on urban water resources cycles. A number of methods have been established in recent years to estimate reliability of rainwater catchment systems (RWCS) and thereby properly size the components (roof catchment area, storage tank size) of the system for a given climatic region. These methods typically use historical or stochastically-generated rainfall patterns to quantify system performance and optimally size the system, with the latter accounting for possible rainfall scenarios based on statistical relationships of historical rainfall patterns. To design RWCS systems that can sustainably meet water demand under future climate conditions, this paper introduces a method that employs climatic data from general circulation models (GCMs) to develop a suite of catchment area vs. storage size design curves that capture uncertainty in future climate scenarios. Monthly rainfall data for the 2010-2050 time period is statistically downscaled to daily values using a Markov chain algorithm, with results used only from GCMs that yield rainfall patterns that are statistically consistent with historical rainfall patterns. The process is demonstrated through application to two climatic regions of the Federated States of Micronesia (FSM) in the western Pacific, wherein the majority of the population relies on rainwater harvesting for potable water supply. Through the use of design curves, communities can provide household RWCS that achieve a certain degree of storage reliability. The method described herein can be applied generally to any geographic region. It can be used to first, assess the future performance of existing household systems; and second, to design or modify systems

Climate variability and environmental stress in the Sudan-Sahel zone of West Africa

DEFF Research Database (Denmark)

Mertz, Ole; D'haen, Sarah Ann Lise; Maiga, Abdou

2012-01-01

Environmental change in the Sudan-Sahel region of West Africa (SSWA) has been much debated since the droughts of the 1970s. In this article we assess climate variability and environmental stress in the region. Households in Senegal, Mali, Burkina Faso, Niger, and Nigeria were asked about climatic...... to household perceptions, observed rainfall patterns showed an increasing trend over the past 20 years. However, August rainfall declined, and could therefore potentially explain the contrasting negative household perceptions of rainfall trends. Most households reported degradation of soils, water resources......, vegetation, and fauna, but more so in the 500–900 mm zones. Adaptation measures to counter environmental degradation included use of manure, reforestation, soil and water conservation, and protection of fauna and vegetation. The results raise concerns for future environmental management in the region...

Global climate changes in the past and future

International Nuclear Information System (INIS)

Schoenwiese, C.D.

1993-01-01

Is man changing the climate of the Earth, and if so, is this at a global scale? This question with all its reunifications, usually referred to under the heading ''greenhouse effect'', deservedly stands in the focus of public attention. Besides fears and warnings reaching even to disaster scenarios there have recently also been sceptical voices pointing out the imponderabilities of filtering anthropogenic effects out of the climate data. This uncertainty is not surprising to the expert, as natural changes of climate always have, and will, superimpose anthropogenic influences. Therefore, it is not enough to peer into the future with the help of intricate climate models. Diagnostic analysis of the past climate is at least just as important. (orig.) [de

Potential impact of climate change to the future streamflow of Yellow River Basin based on CMIP5 data

Science.gov (United States)

Yang, Xiaoli; Zheng, Weifei; Ren, Liliang; Zhang, Mengru; Wang, Yuqian; Liu, Yi; Yuan, Fei; Jiang, Shanhu

2018-02-01

The Yellow River Basin (YRB) is the largest river basin in northern China, which has suffering water scarcity and drought hazard for many years. Therefore, assessments the potential impacts of climate change on the future streamflow in this basin is very important for local policy and planning on food security. In this study, based on the observations of 101 meteorological stations in YRB, equidistant CDF matching (EDCDFm) statistical downscaling approach was applied to eight climate models under two emissions scenarios (RCP4.5 and RCP8.5) from phase five of the Coupled Model Intercomparison Project (CMIP5). Variable infiltration capacity (VIC) model with 0.25° × 0.25° spatial resolution was developed based on downscaled fields for simulating streamflow in the future period over YRB. The results show that with the global warming trend, the annual streamflow will reduced about 10 % during the period of 2021-2050, compared to the base period of 1961-1990 in YRB. There should be suitable water resources planning to meet the demands of growing populations and future climate changing in this region.

Vulnerability and adaptation to climate variability and change in smallholder farming systems in Zimbabwe

NARCIS (Netherlands)

Rurinda, J.

2014-01-01

Keywords: Climate change; Increased climate variability; Vulnerability; Smallholder farmers; Adaptation

Climate change and increased climate variability are currently seen as the major constraints to the already stressed smallholder farming livelihood system in

Potential impacts of climate change and variability on groundwater ...

African Journals Online (AJOL)

Potential impacts of climate change and variability on groundwater resources in Nigeria. ... African Journal of Environmental Science and Technology ... of climate change induced groundwater impacts due to largely multi-scale local and regional heterogeneity, there is need to evaluate groundwater resources, quality and ...

Effects of adjusting cropping systems on utilization efficiency of climatic resources in Northeast China under future climate scenarios

Science.gov (United States)

Guo, Jianping; Zhao, Junfang; Xu, Yanhong; Chu, Zheng; Mu, Jia; Zhao, Qian

Quantitatively evaluating the effects of adjusting cropping systems on the utilization efficiency of climatic resources under climate change is an important task for assessing food security in China. To understand these effects, we used daily climate variables obtained from the regional climate model RegCM3 from 1981 to 2100 under the A1B scenario and crop observations from 53 agro-meteorological experimental stations from 1981 to 2010 in Northeast China. Three one-grade zones of cropping systems were divided by heat, water, topography and crop-type, including the semi-arid areas of the northeast and northwest (III), the one crop area of warm-cool plants in semi-humid plain or hilly regions of the northeast (IV), and the two crop area in irrigated farmland in the Huanghuaihai Plain (VI). An agro-ecological zone model was used to calculate climatic potential productivities. The effects of adjusting cropping systems on climate resource utilization in Northeast China under the A1B scenario were assessed. The results indicated that from 1981 to 2100 in the III, IV and VI areas, the planting boundaries of different cropping systems in Northeast China obviously shifted toward the north and the east based on comprehensively considering the heat and precipitation resources. However, due to high temperature stress, the climatic potential productivity of spring maize was reduced in the future. Therefore, adjusting the cropping system is an effective way to improve the climatic potential productivity and climate resource utilization. Replacing the one crop in one year model (spring maize) by the two crops in one year model (winter wheat and summer maize) significantly increased the total climatic potential productivity and average utilization efficiencies. During the periods of 2011-2040, 2041-2070 and 2071-2100, the average total climatic potential productivities of winter wheat and summer maize increased by 9.36%, 11.88% and 12.13% compared to that of spring maize

Zero discounting can compensate future generations for climate damage

NARCIS (Netherlands)

Davidson, M.D.

2014-01-01

In cost-benefit analysis of climate policy there are two main approaches to discounting, each with implications conflicting with our moral intuitions. Thus, discounted utilitarianism implies that we hardly need to protect future generations against climate change, while classical utilitarianism

Direct and indirect effects of climatic variations on the interannual variability in net ecosystem exchange across terrestrial ecosystems

Directory of Open Access Journals (Sweden)

Junjiong Shao

2016-08-01

Full Text Available Climatic variables not only directly affect the interannual variability (IAV in net ecosystem exchange of CO2 (NEE but also indirectly drive it by changing the physiological parameters. Identifying these direct and indirect paths can reveal the underlying mechanisms of carbon (C dynamics. In this study, we applied a path analysis using flux data from 65 sites to quantify the direct and indirect climatic effects on IAV in NEE and to evaluate the potential relationships among the climatic variables and physiological parameters that represent physiology and phenology of ecosystems. We found that the maximum photosynthetic rate was the most important factor for the IAV in gross primary productivity (GPP, which was mainly induced by the variation in vapour pressure deficit. For ecosystem respiration (RE, the most important drivers were GPP and the reference respiratory rate. The biome type regulated the direct and indirect paths, with distinctive differences between forests and non-forests, evergreen needleleaf forests and deciduous broadleaf forests, and between grasslands and croplands. Different paths were also found among wet, moist and dry ecosystems. However, the climatic variables can only partly explain the IAV in physiological parameters, suggesting that the latter may also result from other biotic and disturbance factors. In addition, the climatic variables related to NEE were not necessarily the same as those related to GPP and RE, indicating the emerging difficulty encountered when studying the IAV in NEE. Overall, our results highlight the contribution of certain physiological parameters to the IAV in C fluxes and the importance of biome type and multi-year water conditions, which should receive more attention in future experimental and modelling research.

Environmental forcing and Southern Ocean marine predator populations: effects of climate change and variability.

Science.gov (United States)

Trathan, P N; Forcada, J; Murphy, E J

2007-12-29

The Southern Ocean is a major component within the global ocean and climate system and potentially the location where the most rapid climate change is most likely to happen, particularly in the high-latitude polar regions. In these regions, even small temperature changes can potentially lead to major environmental perturbations. Climate change is likely to be regional and may be expressed in various ways, including alterations to climate and weather patterns across a variety of time-scales that include changes to the long interdecadal background signals such as the development of the El Niño-Southern Oscillation (ENSO). Oscillating climate signals such as ENSO potentially provide a unique opportunity to explore how biological communities respond to change. This approach is based on the premise that biological responses to shorter-term sub-decadal climate variability signals are potentially the best predictor of biological responses over longer time-scales. Around the Southern Ocean, marine predator populations show periodicity in breeding performance and productivity, with relationships with the environment driven by physical forcing from the ENSO region in the Pacific. Wherever examined, these relationships are congruent with mid-trophic-level processes that are also correlated with environmental variability. The short-term changes to ecosystem structure and function observed during ENSO events herald potential long-term changes that may ensue following regional climate change. For example, in the South Atlantic, failure of Antarctic krill recruitment will inevitably foreshadow recruitment failures in a range of higher trophic-level marine predators. Where predator species are not able to accommodate by switching to other prey species, population-level changes will follow. The Southern Ocean, though oceanographically interconnected, is not a single ecosystem and different areas are dominated by different food webs. Where species occupy different positions in

Projection of future runoff change using climate elasticity method derived from Budyko framework in major basins across China

Science.gov (United States)

Xing, Wanqiu; Wang, Weiguang; Zou, Shan; Deng, Chao

2018-03-01

This study established a climate elasticity method based on Budyko hypothesis and enhanced it by selecting the most effective Budyko-type formula to strengthen the runoff change prediction reliability. The spatiotemporal variations in hydrologic variables (i.e., runoff, precipitation and potential evaporation) during historical period were revealed first and the climate elasticities of runoff were investigated. The proposed climate elasticity method was also applied to project the spatiotemporal variations in future runoff and its key influencing factors in 35 watersheds across China. Wherein, the future climate series were retrieved by consulting the historical series, informed by four global climate models (GCMs) under representative concentration pathways from phase five of the Coupled Model Intercomparison Project. Wang-Tang equation was selected as the optimal Budyko-type equation for its best ability in reproducing the runoff change (with a coefficient of determination and mean absolute error of 0.998 and 1.36 mm, respectively). Observed runoff presents significant decreasing trends in the northern and increasing trends in the southern regions of China, and generally its change is identified to be more sensitive to climatic variables in Hai River Basin and lower Yellow River Basin. Compared to the runoff during the reference period, positive change rates in the north and negative change rates in the south of China in the mid-21st century can be practically generalized from the majority of GCMs projections. This maybe resulted from the increasing precipitation, especially in parts of northern basins. Meanwhile, GCMs project a consistently upward trend in potential evaporation although significant decreasing trends occur in the majority of catchments for the historical period. The results indicate that climate change will possibly bring some changes to the water resources over China in the mid-21st century and some countermeasures of water resources planning

Relationship between rice yield and climate variables in southwest Nigeria using multiple linear regression and support vector machine analysis

Science.gov (United States)

Oguntunde, Philip G.; Lischeid, Gunnar; Dietrich, Ottfried

2018-03-01

This study examines the variations of climate variables and rice yield and quantifies the relationships among them using multiple linear regression, principal component analysis, and support vector machine (SVM) analysis in southwest Nigeria. The climate and yield data used was for a period of 36 years between 1980 and 2015. Similar to the observed decrease ( P 1 and explained 83.1% of the total variance of predictor variables. The SVM regression function using the scores of the first principal component explained about 75% of the variance in rice yield data and linear regression about 64%. SVM regression between annual solar radiation values and yield explained 67% of the variance. Only the first component of the principal component analysis (PCA) exhibited a clear long-term trend and sometimes short-term variance similar to that of rice yield. Short-term fluctuations of the scores of the PC1 are closely coupled to those of rice yield during the 1986-1993 and the 2006-2013 periods thereby revealing the inter-annual sensitivity of rice production to climate variability. Solar radiation stands out as the climate variable of highest influence on rice yield, and the influence was especially strong during monsoon and post-monsoon periods, which correspond to the vegetative, booting, flowering, and grain filling stages in the study area. The outcome is expected to provide more in-depth regional-specific climate-rice linkage for screening of better cultivars that can positively respond to future climate fluctuations as well as providing information that may help optimized planting dates for improved radiation use efficiency in the study area.

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

Science.gov (United States)

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.

On climate prediction: how much can we expect from climate memory?

Science.gov (United States)

Yuan, Naiming; Huang, Yan; Duan, Jianping; Zhu, Congwen; Xoplaki, Elena; Luterbacher, Jürg

2018-03-01

Slowing variability in climate system is an important source of climate predictability. However, it is still challenging for current dynamical models to fully capture the variability as well as its impacts on future climate. In this study, instead of simulating the internal multi-scale oscillations in dynamical models, we discussed the effects of internal variability in terms of climate memory. By decomposing climate state x(t) at a certain time point t into memory part M(t) and non-memory part ɛ (t) , climate memory effects from the past 30 years on climate prediction are quantified. For variables with strong climate memory, high variance (over 20% ) in x(t) is explained by the memory part M(t), and the effects of climate memory are non-negligible for most climate variables, but the precipitation. Regarding of multi-steps climate prediction, a power law decay of the explained variance was found, indicating long-lasting climate memory effects. The explained variances by climate memory can remain to be higher than 10% for more than 10 time steps. Accordingly, past climate conditions can affect both short (monthly) and long-term (interannual, decadal, or even multidecadal) climate predictions. With the memory part M(t) precisely calculated from Fractional Integral Statistical Model, one only needs to focus on the non-memory part ɛ (t) , which is an important quantity that determines climate predictive skills.

Linking global climate and temperature variability to widespread amphibian declines putatively caused by disease.

Science.gov (United States)

Rohr, Jason R; Raffel, Thomas R

2010-05-04

The role of global climate change in the decline of biodiversity and the emergence of infectious diseases remains controversial, and the effect of climatic variability, in particular, has largely been ignored. For instance, it was recently revealed that the proposed link between climate change and widespread amphibian declines, putatively caused by the chytrid fungus Batrachochytrium dendrobatidis (Bd), was tenuous because it was based on a temporally confounded correlation. Here we provide temporally unconfounded evidence that global El Niño climatic events drive widespread amphibian losses in genus Atelopus via increased regional temperature variability, which can reduce amphibian defenses against pathogens. Of 26 climate variables tested, only factors associated with temperature variability could account for the spatiotemporal patterns of declines thought to be associated with Bd. Climatic predictors of declines became significant only after controlling for a pattern consistent with epidemic spread (by temporally detrending the data). This presumed spread accounted for 59% of the temporal variation in amphibian losses, whereas El Niño accounted for 59% of the remaining variation. Hence, we could account for 83% of the variation in declines with these two variables alone. Given that global climate change seems to increase temperature variability, extreme climatic events, and the strength of Central Pacific El Niño episodes, climate change might exacerbate worldwide enigmatic declines of amphibians, presumably by increasing susceptibility to disease. These results suggest that changes to temperature variability associated with climate change might be as significant to biodiversity losses and disease emergence as changes to mean temperature.

Climate change feedbacks on future oceanic acidification

OpenAIRE

McNeil, Ben I.; Matear, Richard J.

2011-01-01

Oceanic anthropogenic CO2 uptake will decrease both the pH and the aragonite saturation state (Ωarag) of seawater leading to an oceanic acidification. However, the factors controlling future changes in pH and Ωarag are independent and will respond differently to oceanic climate change feedbacks such as ocean warming, circulation and biological changes. We examine the sensitivity of these two CO2-related parameters to climate change feedbacks within a coupled atmosphere-ocean model. The ocean ...

Climate variability and change in the United States: potential impacts on water- and foodborne diseases caused by microbiologic agents.

Science.gov (United States)

Rose, J B; Epstein, P R; Lipp, E K; Sherman, B H; Bernard, S M; Patz, J A

2001-05-01

Exposure to waterborne and foodborne pathogens can occur via drinking water (associated with fecal contamination), seafood (due to natural microbial hazards, toxins, or wastewater disposal) or fresh produce (irrigated or processed with contaminated water). Weather influences the transport and dissemination of these microbial agents via rainfall and runoff and the survival and/or growth through such factors as temperature. Federal and state laws and regulatory programs protect much of the U.S. population from waterborne disease; however, if climate variability increases, current and future deficiencies in areas such as watershed protection, infrastructure, and storm drainage systems will probably increase the risk of contamination events. Knowledge about transport processes and the fate of microbial pollutants associated with rainfall and snowmelt is key to predicting risks from a change in weather variability. Although recent studies identified links between climate variability and occurrence of microbial agents in water, the relationships need further quantification in the context of other stresses. In the marine environment as well, there are few studies that adequately address the potential health effects of climate variability in combination with other stresses such as overfishing, introduced species, and rise in sea level. Advances in monitoring are necessary to enhance early-warning and prevention capabilities. Application of existing technologies, such as molecular fingerprinting to track contaminant sources or satellite remote sensing to detect coastal algal blooms, could be expanded. This assessment recommends incorporating a range of future scenarios of improvement plans for current deficiencies in the public health infrastructure to achieve more realistic risk assessments.

Climate Change and Future Pollen Allergy in Europe.

Science.gov (United States)

Lake, Iain R; Jones, Natalia R; Agnew, Maureen; Goodess, Clare M; Giorgi, Filippo; Hamaoui-Laguel, Lynda; Semenov, Mikhail A; Solomon, Fabien; Storkey, Jonathan; Vautard, Robert; Epstein, Michelle M

2017-03-01

Globally, pollen allergy is a major public health problem, but a fundamental unknown is the likely impact of climate change. To our knowledge, this is the first study to quantify the consequences of climate change upon pollen allergy in humans. We produced quantitative estimates of the potential impact of climate change upon pollen allergy in humans, focusing upon common ragweed ( Ambrosia artemisiifolia ) in Europe. A process-based model estimated the change in ragweed's range under climate change. A second model simulated current and future ragweed pollen levels. These findings were translated into health burdens using a dose-response curve generated from a systematic review and from current and future population data. Models considered two different suites of regional climate/pollen models, two greenhouse gas emissions scenarios [Representative Concentration Pathways (RCPs) 4.5 and 8.5], and three different plant invasion scenarios. Our primary estimates indicated that sensitization to ragweed will more than double in Europe, from 33 to 77 million people, by 2041-2060. According to our projections, sensitization will increase in countries with an existing ragweed problem (e.g., Hungary, the Balkans), but the greatest proportional increases will occur where sensitization is uncommon (e.g., Germany, Poland, France). Higher pollen concentrations and a longer pollen season may also increase the severity of symptoms. Our model projections were driven predominantly by changes in climate (66%) but were also influenced by current trends in the spread of this invasive plant species. Assumptions about the rate at which ragweed spreads throughout Europe had a large influence upon the results. Our quantitative estimates indicate that ragweed pollen allergy will become a common health problem across Europe, expanding into areas where it is currently uncommon. Control of ragweed spread may be an important adaptation strategy in response to climate change. Citation: Lake IR

Climate change and climate variability impacts on rainfed agricultural activities and possible adaptation measures. A Mexican case study

Energy Technology Data Exchange (ETDEWEB)

Conde, C.; Ferrer, R. [Centro de Ciencias de la Atmosfera, Universidad Nacional Autonoma de Mexico Circuito Exterior, Mexico, D.F. (Mexico)]. E-mail: e-mail: conde@servidor.unam.mx; Orozco, S. [Escuela de Agrobiologia, Universidad Autonoma de Tlaxcala, Tlaxcala (Mexico)

2006-07-15

Climate extreme events (such as those associated to strong El Nino events) highly affect Mexican agriculture, since more than sixty percent of it is rainfed. The basic crop cultivated is maize, which is still the main source of nutrients for a large portion of the rural population in the country. Within the project Capacity Building for Stage II Adaptation to Climate Change in Central America, Mexico and Cuba, we analyze the strategies developed by maize producers in the central region of the country to cope with climatic adverse events. Impact on rainfed maize due to climate variability and climate change conditions are studied using a crop simulation model. Several adaptation measures can be evaluated using that model. However, the effect of other stressors must be considered in an assessment of the adaptive capacity of small farmers to climate variability and change. Key stakeholders' involvement in the region helped us to decide which of the adaptive measures could be viable under the current conditions and under future climatic conditions. The construction of greenhouses, the use of compost, and dripping irrigation, were some of the techniques selected with the participation of the stakeholders. The enthusiastic responses to these measures allow us to consider that they can prevail in the future, under climate change conditions. However, the adaptation to climate change includes -besides the stated techniques- the generation of the capacities to cope with climatic adverse events, that is, to enhance the adaptive capacities to climate change among the key stakeholders. [Spanish] Los eventos climaticos extremos (como los asociados con eventos fuertes de El Nino) afectan de manera importante a la agricultura mexicana, ya que mas del sesenta por ciento de ella es de temporal, esto es, depende fundamentalmente de una buena temporada de lluvias para producir. El cultivo que se siembra es basicamente maiz, que todavia es la principal fuente de nutrientes para

Revealing Relationships among Relevant Climate Variables with Information Theory

Science.gov (United States)

Knuth, Kevin H.; Golera, Anthony; Curry, Charles T.; Huyser, Karen A.; Kevin R. Wheeler; Rossow, William B.

2005-01-01

The primary objective of the NASA Earth-Sun Exploration Technology Office is to understand the observed Earth climate variability, thus enabling the determination and prediction of the climate's response to both natural and human-induced forcing. We are currently developing a suite of computational tools that will allow researchers to calculate, from data, a variety of information-theoretic quantities such as mutual information, which can be used to identify relationships among climate variables, and transfer entropy, which indicates the possibility of causal interactions. Our tools estimate these quantities along with their associated error bars, the latter of which is critical for describing the degree of uncertainty in the estimates. This work is based upon optimal binning techniques that we have developed for piecewise-constant, histogram-style models of the underlying density functions. Two useful side benefits have already been discovered. The first allows a researcher to determine whether there exist sufficient data to estimate the underlying probability density. The second permits one to determine an acceptable degree of round-off when compressing data for efficient transfer and storage. We also demonstrate how mutual information and transfer entropy can be applied so as to allow researchers not only to identify relations among climate variables, but also to characterize and quantify their possible causal interactions.

US climate policy: evolution and future prospects

Energy Technology Data Exchange (ETDEWEB)

Agrawala, S.; Andresen, S.

2001-03-01

Climate change is a problem which US science has significantly helped to bring to the world's attention. It now requires initiatives in US domestic policy for even the first steps towards any realistic global resolution of this problem. This paper addresses three questions: (1) How has US climate policy evolved since climate change became an international political concern in the late 1980s?; (2) what is the relative significance of various factors, both domestic and international, in shaping this evolution?; and (3) what are some likely future scenarios for the climate regime and the role of the US under the new Bush (Jr.) administration? This analysis suggests that the US has generally played a cautious, even blocking role on the international arena, although the period between 1992 and 1997 witnessed a rather uneven march towards progressivism, culminating in the US agreeing to a 7 per cent cut in its greenhouse emissions by 2008-2012 under the Kyoto Protocol. US policy during the Bush (Sr.) and Clinton administrations was primarily shaped by powerful ideologues, while a second critical determinant was the constitutional separation of powers between the executive and legislature. Scientific assessments and international negotiations meanwhile have given climate change unusual stamina on the domestic agenda, while the preferred set of policy responses has been constrained by a national culture that gives primacy to the market over the state. Looking into the future, the recent one-two punch delivered by President George W. Bush in reversing his pledge to regulate carbon dioxide followed by a rejection of US commitments under the Kyoto Protocol renders any expectation of measures to reduce domestic emissions unrealistic, and is likely to cripple the treaty in its present form. The possibility of an alternative to the Kyoto Protocol also appears very remote at this time. However, while official action is unlikely, it is possible that the growth of US

Climate variability from isotope records in precipitation

International Nuclear Information System (INIS)

Grassl, H.; Latif, M.; Schotterer, U.; Gourcy, L.

2002-01-01

Selected time series from the Global Network for Isotopes in Precipitation (GNIP) revealed a close relationship to climate variability phenomena like El Nino - Southern Oscillation (ENSO) or the North Atlantic Oscillation (NAO) although the precipitation anomaly in the case studies of Manaus (Brazil) and Groningen (The Netherlands) is rather weak. For a sound understanding of this relationship especially in the case of Manaus, the data should include major events like the 1997/98 El Nino, however, the time series are interrupted frequently or important stations are even closed. Improvements are only possible if existing key stations and new ones (placed at 'hot spots' derived from model experiments) are supported continuously. A close link of GNIP to important scientific programmes like CLIVAR, the Climate Variability and Predictability Programme seems to be indispensable for a successful continuation. (author)

Coral based-ENSO/IOD related climate variability in Indonesia: a review

Science.gov (United States)

Yudawati Cahyarini, Sri; Henrizan, Marfasran

2018-02-01

Indonesia is located in the prominent site to study climate variability as it lies between Pacific and Indian Ocean. It has consequences to the regional climate in Indonesia that its climate variability is influenced by the climate events in the Pacific oceans (e.g. ENSO) and in the Indian ocean (e.g. IOD), and monsoon as well as Indonesian Throughflow (ITF). Northwestern monsoon causes rainfall in the region of Indonesia, while reversely Southwestern monsoon causes dry season around Indonesia. The ENSO warm phase called El Nino causes several droughts in Indonesian region, reversely the La Nina causes flooding in some regions in Indonesia. However, the impact of ENSO in Indonesia is different from one place to the others. Having better understanding on the climate phenomenon and its impact to the region requires long time series climate data. Paleoclimate study which provides climate data back into hundreds to thousands even to million years overcome this requirement. Coral Sr/Ca can provide information on past sea surface temperature (SST) and paired Sr/Ca and δ18O may be used to reconstruct variations in the precipitation balance (salinity) at monthly to annual interannual resolution. Several climate studies based on coral geochemical records in Indonesia show that coral Sr/Ca and δ18O from Indonesian records SST and salinity respectively. Coral Sr/Ca from inshore Seribu islands complex shows more air temperature rather than SST. Modern coral from Timor shows the impact of ENSO and IOD to the saliniy and SST is different at Timor sea. This result should be taken into account when interpreting Paleoclimate records over Indonesia. Timor coral also shows more pronounced low frequency SST variability compared to the SST reanalysis (model). The longer data of low frequency variability will improve the understanding of warming trend in this climatically important region.

Response of groundwater level and surface-water/groundwater interaction to climate variability: Clarence-Moreton Basin, Australia

Science.gov (United States)

Cui, Tao; Raiber, Matthias; Pagendam, Dan; Gilfedder, Mat; Rassam, David

2018-03-01

Understanding the response of groundwater levels in alluvial and sedimentary basin aquifers to climatic variability and human water-resource developments is a key step in many hydrogeological investigations. This study presents an analysis of groundwater response to climate variability from 2000 to 2012 in the Queensland part of the sedimentary Clarence-Moreton Basin, Australia. It contributes to the baseline hydrogeological understanding by identifying the primary groundwater flow pattern, water-level response to climate extremes, and the resulting dynamics of surface-water/groundwater interaction. Groundwater-level measurements from thousands of bores over several decades were analysed using Kriging and nonparametric trend analysis, together with a newly developed three-dimensional geological model. Groundwater-level contours suggest that groundwater flow in the shallow aquifers shows local variations in the close vicinity of streams, notwithstanding general conformance with topographic relief. The trend analysis reveals that climate variability can be quickly reflected in the shallow aquifers of the Clarence-Moreton Basin although the alluvial aquifers have a quicker rainfall response than the sedimentary bedrock formations. The Lockyer Valley alluvium represents the most sensitively responding alluvium in the area, with the highest declining (-0.7 m/year) and ascending (2.1 m/year) Sen's slope rates during and after the drought period, respectively. Different surface-water/groundwater interaction characteristics were observed in different catchments by studying groundwater-level fluctuations along hydrogeologic cross-sections. The findings of this study lay a foundation for future water-resource management in the study area.

Assessing Regional Scale Variability in Extreme Value Statistics Under Altered Climate Scenarios

Energy Technology Data Exchange (ETDEWEB)

Brunsell, Nathaniel [Univ. of Kansas, Lawrence, KS (United States); Mechem, David [Univ. of Kansas, Lawrence, KS (United States); Ma, Chunsheng [Wichita State Univ., KS (United States)

2015-02-20

validity of an innovative multi–resolution information theory approach, and the ability of the RCM modeling framework to represent the low-frequency modulation of extreme climate events. Once the skill of the modeling and analysis methodology has been established, we will apply the same approach for the AR5 (IPCC Fifth Assessment Report) climate change scenarios in order to assess how climate extremes and the the influence of lowfrequency variability on climate extremes might vary under changing climate. The research specifically addresses the DOE focus area 2. Simulation of climate extremes under a changing climate. Specific results will include (1) a better understanding of the spatial and temporal structure of extreme events, (2) a thorough quantification of how extreme values are impacted by low-frequency climate teleconnections, (3) increased knowledge of current regional climate models ability to ascertain these influences, and (4) a detailed examination of the how the distribution of extreme events are likely to change under different climate change scenarios. In addition, this research will assess the ability of the innovative wavelet information theory approach to characterize extreme events. Any and all of these results will greatly enhance society’s ability to understand and mitigate the regional ramifications of future global climate change.

Impacts of climate variability and change on beekeeping productivity ...

African Journals Online (AJOL)

This study investigated impacts of climate variability and change on Beekeeping productivity in Sunya, Kijungu and Olgira villages in Kiteto District in Manyara region in Tanzania. Specific objectives of the study were to identify the contribution of honey bees to community livelihoods, to identify climate related factors which ...

Country-Specific Effects of Climate Variability on Human Migration

Science.gov (United States)

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

Country-Specific Effects of Climate Variability on Human Migration.

Science.gov (United States)

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.

Are the Projections of Future Climate Change Reliable in the IPCC Reports?

Institute of Scientific and Technical Information of China (English)

Zongci Zhao

2011-01-01

@@ As we know,the projections of future climate change including impacts and strategies in the IPCC Assessment Reports were based on global climate models with scenarios on various human activities.Global climate model simulations provide key inputs for climate change assessments. In this study,the main objective is to analyze if the projections of fu-ture climate change by global climate models are reli-able.Several workshops have been held on this issue,such as the IPCC expert meeting on assessing and combining multi-model climate projections in January of 2010 (presided by the co-chairs of the IPCC WGI and WGII AR5),and the workshop of the combined global climate model group held by NCAR in June of 2010.

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

Science.gov (United States)

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

Assessing the Role of Climate Variability on Liver Fluke Risk in the UK Through Mechanistic Hydro-Epidemiological Modelling

Science.gov (United States)

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.

A method to encapsulate model structural uncertainty in ensemble projections of future climate: EPIC v1.0

Science.gov (United States)

Lewis, Jared; Bodeker, Greg E.; Kremser, Stefanie; Tait, Andrew

2017-12-01

A method, based on climate pattern scaling, has been developed to expand a small number of projections of fields of a selected climate variable (X) into an ensemble that encapsulates a wide range of indicative model structural uncertainties. The method described in this paper is referred to as the Ensemble Projections Incorporating Climate model uncertainty (EPIC) method. Each ensemble member is constructed by adding contributions from (1) a climatology derived from observations that represents the time-invariant part of the signal; (2) a contribution from forced changes in X, where those changes can be statistically related to changes in global mean surface temperature (Tglobal); and (3) a contribution from unforced variability that is generated by a stochastic weather generator. The patterns of unforced variability are also allowed to respond to changes in Tglobal. The statistical relationships between changes in X (and its patterns of variability) and Tglobal are obtained in a training phase. Then, in an implementation phase, 190 simulations of Tglobal are generated using a simple climate model tuned to emulate 19 different global climate models (GCMs) and 10 different carbon cycle models. Using the generated Tglobal time series and the correlation between the forced changes in X and Tglobal, obtained in the training phase, the forced change in the X field can be generated many times using Monte Carlo analysis. A stochastic weather generator is used to generate realistic representations of weather which include spatial coherence. Because GCMs and regional climate models (RCMs) are less likely to correctly represent unforced variability compared to observations, the stochastic weather generator takes as input measures of variability derived from observations, but also responds to forced changes in climate in a way that is consistent with the RCM projections. This approach to generating a large ensemble of projections is many orders of magnitude more

Cocoa farming households' vulnerability to climate variability in Ekiti ...

African Journals Online (AJOL)

Rural livelihoods in south western Nigeria are at risk to climate variability on the short run and climate change on the long run. This subjects agro ecological niches to high sensitivity and exposure thus reducing the adaptive capacity. Vulnerability results and the cocoa farming households, the major contributors to the ...

Perception of Climate Variability on Agriculture and Food Security by ...

African Journals Online (AJOL)

Dr Osondu

This paper focuses on how men and women farmers perceive climatic variability in Idanre ... Poor women and their ... Climate Change, Food Security and Poverty ..... 50. 8.3. Total. 180. 100. Marital status. Single. Married. Divorced. Widowed.

Impact of future climate change on wheat production in relation to plant-available water capacity in a semiaridenvironment

Science.gov (United States)

Yang, Yanmin; Liu, De Li; Anwar, Muhuddin Rajin; Zuo, Heping; Yang, Yonghui

2014-02-01

Conceptions encompassing climate change are irreversible rise of atmospheric carbon dioxide (CO2) concentration, increased temperature, and changes in rainfall both in spatial- and temporal-scales worldwide. This will have a major impact on wheat production, particularly if crops are frequently exposed to a sequence, frequency, and intensity of specific weather events like high temperature during growth period. However, the process of wheat response to climate change is complex and compounded by interactions among atmospheric CO2 concentration, climate variables, soil, nutrition, and agronomic management. In this study, we use the Agricultural Production Systems sIMulator (APSIM)-wheat model, driven by statistically downscaled climate projections of 18 global circulation models (GCMs) under the 2007 Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A2 CO2 emission scenario to examine impact on future wheat yields across key wheat growing regions considering different soil types in New South Wales (NSW) of Australia. The response of wheat yield, yield components, and phenology vary across sites and soil types, but yield is closely related to plant available water capacity (PAWC). Results show a decreasing yield trend during the period of 2021-2040 compared to the baseline period of 1961-1990. Across different wheat-growing regions in NSW, grain yield difference in the future period (2021-2040) over the baseline (1961-1990) varies from +3.4 to -14.7 %, and in most sites, grain number is decreased, while grain size is increased in future climate. Reduction of wheat yield is mainly due to shorter growth duration, where average flowering and maturing time are advanced by an average of 11 and 12 days, respectively. In general, larger negative impacts of climate change are exhibited in those sites with higher PAWC. Current wheat cultivars with shorter growing season properties are viable in the future climate, but breading for

The value of seasonal forecasting and crop mix adaptation to climate variability for agriculture under climate change

Science.gov (United States)

Choi, H. S.; Schneider, U.; Schmid, E.; Held, H.

2012-04-01

Changes to climate variability and frequency of extreme weather events are expected to impose damages to the agricultural sector. Seasonal forecasting and long range prediction skills have received attention as an option to adapt to climate change because seasonal climate and yield predictions could improve farmers' management decisions. The value of seasonal forecasting skill is assessed with a crop mix adaptation option in Spain where drought conditions are prevalent. Yield impacts of climate are simulated for six crops (wheat, barely, cotton, potato, corn and rice) with the EPIC (Environmental Policy Integrated Climate) model. Daily weather data over the period 1961 to 1990 are used and are generated by the regional climate model REMO as reference period for climate projection. Climate information and its consequent yield variability information are given to the stochastic agricultural sector model to calculate the value of climate information in the agricultural market. Expected consumers' market surplus and producers' revenue is compared with and without employing climate forecast information. We find that seasonal forecasting benefits not only consumers but also producers if the latter adopt a strategic crop mix. This mix differs from historical crop mixes by having higher shares of crops which fare relatively well under climate change. The corresponding value of information is highly sensitive to farmers' crop mix choices.

Modelling Bambara Groundnut Yield in Southern Africa: Towards a Climate-Resilient Future

Science.gov (United States)

Karunaratne, A. S.; Walker, S.; Ruane, A. C.

2015-01-01

Current agriculture depends on a few major species grown as monocultures that are supported by global research underpinning current productivity. However, many hundreds of alternative crops have the potential to meet real world challenges by sustaining humanity, diversifying agricultural systems for food and nutritional security, and especially responding to climate change through their resilience to certain climate conditions. Bambara groundnut (Vigna subterranea (L.) Verdc.), an underutilised African legume, is an exemplar crop for climate resilience. Predicted yield performances of Bambara groundnut by AquaCrop (a crop-water productivity model) were evaluated for baseline (1980-2009) and mid-century climates (2040-2069) under 20 downscaled Global Climate Models (CMIP5-RCP8.5), as well as for climate sensitivities (AgMIPC3MP) across 3 locations in Southern Africa (Botswana, South Africa, Namibia). Different land - races of Bambara groundnut originating from various semi-arid African locations showed diverse yield performances with diverse sensitivities to climate. S19 originating from hot-dry conditions in Namibia has greater future yield potential compared to the Swaziland landrace Uniswa Red-UN across study sites. South Africa has the lowest yield under the current climate, indicating positive future yield trends. Namibia reported the highest baseline yield at optimum current temperatures, indicating less yield potential in future climates. Bambara groundnut shows positive yield potential at temperatures of up to 31degC, with further warming pushing yields down. Thus, many regions in Southern Africa can utilize Bambara groundnut successfully in the coming decades. This modelling exercise supports decisions on genotypic suitability for present and future climates at specific locations.

Hydroclimate variability in Scandinavia over the last millennium - insights from a climate model-proxy data comparison

Science.gov (United States)

Seftigen, Kristina; Goosse, Hugues; Klein, Francois; Chen, Deliang

2017-12-01

The integration of climate proxy information with general circulation model (GCM) results offers considerable potential for deriving greater understanding of the mechanisms underlying climate variability, as well as unique opportunities for out-of-sample evaluations of model performance. In this study, we combine insights from a new tree-ring hydroclimate reconstruction from Scandinavia with projections from a suite of forced transient simulations of the last millennium and historical intervals from the CMIP5 and PMIP3 archives. Model simulations and proxy reconstruction data are found to broadly agree on the modes of atmospheric variability that produce droughts-pluvials in the region. Despite these dynamical similarities, large differences between simulated and reconstructed hydroclimate time series remain. We find that the GCM-simulated multi-decadal and/or longer hydroclimate variability is systematically smaller than the proxy-based estimates, whereas the dominance of GCM-simulated high-frequency components of variability is not reflected in the proxy record. Furthermore, the paleoclimate evidence indicates in-phase coherencies between regional hydroclimate and temperature on decadal timescales, i.e., sustained wet periods have often been concurrent with warm periods and vice versa. The CMIP5-PMIP3 archive suggests, however, out-of-phase coherencies between the two variables in the last millennium. The lack of adequate understanding of mechanisms linking temperature and moisture supply on longer timescales has serious implications for attribution and prediction of regional hydroclimate changes. Our findings stress the need for further paleoclimate data-model intercomparison efforts to expand our understanding of the dynamics of hydroclimate variability and change, to enhance our ability to evaluate climate models, and to provide a more comprehensive view of future drought and pluvial risks.

Future Climate Data from RCP 4.5 and Occurrence of Malaria in Korea

Directory of Open Access Journals (Sweden)

Jaewon Kwak

2014-10-01

Full Text Available Since its reappearance at the Military Demarcation Line in 1993, malaria has been occurring annually in Korea. Malaria is regarded as a third grade nationally notifiable disease susceptible to climate change. The objective of this study is to quantify the effect of climatic factors on the occurrence of malaria in Korea and construct a malaria occurrence model for predicting the future trend of malaria under the influence of climate change. Using data from 2001–2011, the effect of time lag between malaria occurrence and mean temperature, relative humidity and total precipitation was investigated using spectral analysis. Also, a principal component regression model was constructed, considering multicollinearity. Future climate data, generated from RCP 4.5 climate change scenario and CNCM3 climate model, was applied to the constructed regression model to simulate future malaria occurrence and analyze the trend of occurrence. Results show an increase in the occurrence of malaria and the shortening of annual time of occurrence in the future.

Future climate data from RCP 4.5 and occurrence of malaria in Korea.

Science.gov (United States)

Kwak, Jaewon; Noh, Huiseong; Kim, Soojun; Singh, Vijay P; Hong, Seung Jin; Kim, Duckgil; Lee, Keonhaeng; Kang, Narae; Kim, Hung Soo

2014-10-15

Since its reappearance at the Military Demarcation Line in 1993, malaria has been occurring annually in Korea. Malaria is regarded as a third grade nationally notifiable disease susceptible to climate change. The objective of this study is to quantify the effect of climatic factors on the occurrence of malaria in Korea and construct a malaria occurrence model for predicting the future trend of malaria under the influence of climate change. Using data from 2001-2011, the effect of time lag between malaria occurrence and mean temperature, relative humidity and total precipitation was investigated using spectral analysis. Also, a principal component regression model was constructed, considering multicollinearity. Future climate data, generated from RCP 4.5 climate change scenario and CNCM3 climate model, was applied to the constructed regression model to simulate future malaria occurrence and analyze the trend of occurrence. Results show an increase in the occurrence of malaria and the shortening of annual time of occurrence in the future.

Climate variability in the subarctic area for the last 2 millennia

Science.gov (United States)

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.

Mechanistic variables can enhance predictive models of endotherm distributions: The American pika under current, past, and future climates

Science.gov (United States)

Mathewson, Paul; Moyer-Horner, Lucas; Beever, Erik; Briscoe, Natalie; Kearney, Michael T.; Yahn, Jeremiah; Porter, Warren P.

2017-01-01

How climate constrains species’ distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8–19% less habitat loss in response to annual temperature increases of ~3–5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect

Mechanistic variables can enhance predictive models of endotherm distributions: the American pika under current, past, and future climates.

Science.gov (United States)

Mathewson, Paul D; Moyer-Horner, Lucas; Beever, Erik A; Briscoe, Natalie J; Kearney, Michael; Yahn, Jeremiah M; Porter, Warren P

2017-03-01

How climate constrains species' distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8-19% less habitat loss in response to annual temperature increases of ~3-5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect

Drought variability over Thessaly plain, Greece. Present and future changes

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Nastos, Panagiotis T.; Kapsomenakis, John; Dalezios, Nicolas R.; Kotsopoulos, Spyridon; Poulos, Serafim

2015-04-01

The diachronic variability of precipitation is of major scientific concern, because it is linked to water availability or deficiency on regional scale. The latter, resulted from a prolonged period of abnormally low precipitation or permanent absence of precipitation, is associated with dryness, having on one hand, a substantial impact on agricultural production and thus the society itself, and on the other hand, the redistribution of flora and fauna. In some cases, dryness drive climate refugees, and this is a great challenge - threat - that must be faced - mitigated - by stake holders in international organizations and fora. The Aridity Index (AI) measures the degree of dryness of the climate at a given region, and according to the United Nations Environmental Programme (UNEP) it is defined as the ratio of precipitation to the potential evapotranspiration. In this study, we investigate the climate change impacts on AI over Thessaly plain, Greece. Thessaly, the largest plain and granary of Greece, includes a total area of 14,036 km2, which represents almost 11% of the Greek territory. Regarding the geomorphology, the ground is 50% mountainous-hilly and 50% flat, irrigated by Peneus, the third largest river in the country, which flows through the axis east-west. The assessment of AI was conducted utilizing daily evapotranspiration losses, based on the modified FAO-56 Penman-Monteith formula, and daily precipitation totals from a number of Regional Climate Models (RCMs), within the ENSEMBLE European Project. Further, the projected changes of AI between the period 1961-1990 (reference period) and the periods 2021-2050 (near future) and 2071-2100 (far future) along with the inter-model standard deviations are presented, under SRES A1B. The findings of the analysis revealed significant spatiotemporal changes of AI over Thessaly plain, focusing on their societal aspects. Acknowlegdements. This work is supported by the project AGROCLIMA (11SYN_3_1913), which is funded by

Regulatory perspective on future climates at Yucca Mountain

International Nuclear Information System (INIS)

Coleman, N.M.; Eisenberg, N.A.; Brooks, D.J.

1996-01-01

Current regulations of the U.S. Nuclear Regulatory Commission (NRC) require that any performance assessment supporting the license application for a high-level waste (HLW) repository must consider the potential for changes in hydrologic conditions caused by reasonably foreseeable climatic conditions. The requirement is important because the earth's climate will almost certainly change significantly during the thousands of years that disposed nuclear wastes will remain hazardous. More importantly, climate controls the range of precipitation, which in turn controls the rates of infiltration, deep percolation, and groundwater flux through a geologic repository located in an unsaturated environment. Therefore, future changes in climate could significantly influence waste isolation in a repository at Yucca Mountain

Climate Change Impacts on the Congo Basin Region

NARCIS (Netherlands)

Ludwig, F.; Franssen, W.; Jans, W.W.P.; Kruijt, B.; Supit, I.

2012-01-01

This report presents analyses of climate change impacts in the Congo Basin on water for agriculture and hydropower, forest ecosystem functioning and carbon storage and impacts of climate variability and change on future economic development. To quantify the impacts of future climate we developed a

Future of endemic flora of biodiversity hotspots in India.

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Vishwas Sudhir Chitale

Full Text Available India is one of the 12 mega biodiversity countries of the world, which represents 11% of world's flora in about 2.4% of global land mass. Approximately 28% of the total Indian flora and 33% of angiosperms occurring in India are endemic. Higher human population density in biodiversity hotspots in India puts undue pressure on these sensitive eco-regions. In the present study, we predict the future distribution of 637 endemic plant species from three biodiversity hotspots in India; Himalaya, Western Ghats, Indo-Burma, based on A1B scenario for year 2050 and 2080. We develop individual variable based models as well as mixed models in MaxEnt by combining ten least co-related bioclimatic variables, two disturbance variables and one physiography variable as predictor variables. The projected changes suggest that the endemic flora will be adversely impacted, even under such a moderate climate scenario. The future distribution is predicted to shift in northern and north-eastern direction in Himalaya and Indo-Burma, while in southern and south-western direction in Western Ghats, due to cooler climatic conditions in these regions. In the future distribution of endemic plants, we observe a significant shift and reduction in the distribution range compared to the present distribution. The model predicts a 23.99% range reduction and a 7.70% range expansion in future distribution by 2050, while a 41.34% range reduction and a 24.10% range expansion by 2080. Integration of disturbance and physiography variables along with bioclimatic variables in the models improved the prediction accuracy. Mixed models provide most accurate results for most of the combinations of climatic and non-climatic variables as compared to individual variable based models. We conclude that a regions with cooler climates and higher moisture availability could serve as refugia for endemic plants in future climatic conditions; b mixed models provide more accurate results, compared to single

Future of endemic flora of biodiversity hotspots in India.

Science.gov (United States)

Chitale, Vishwas Sudhir; Behera, Mukund Dev; Roy, Partha Sarthi

2014-01-01

India is one of the 12 mega biodiversity countries of the world, which represents 11% of world's flora in about 2.4% of global land mass. Approximately 28% of the total Indian flora and 33% of angiosperms occurring in India are endemic. Higher human population density in biodiversity hotspots in India puts undue pressure on these sensitive eco-regions. In the present study, we predict the future distribution of 637 endemic plant species from three biodiversity hotspots in India; Himalaya, Western Ghats, Indo-Burma, based on A1B scenario for year 2050 and 2080. We develop individual variable based models as well as mixed models in MaxEnt by combining ten least co-related bioclimatic variables, two disturbance variables and one physiography variable as predictor variables. The projected changes suggest that the endemic flora will be adversely impacted, even under such a moderate climate scenario. The future distribution is predicted to shift in northern and north-eastern direction in Himalaya and Indo-Burma, while in southern and south-western direction in Western Ghats, due to cooler climatic conditions in these regions. In the future distribution of endemic plants, we observe a significant shift and reduction in the distribution range compared to the present distribution. The model predicts a 23.99% range reduction and a 7.70% range expansion in future distribution by 2050, while a 41.34% range reduction and a 24.10% range expansion by 2080. Integration of disturbance and physiography variables along with bioclimatic variables in the models improved the prediction accuracy. Mixed models provide most accurate results for most of the combinations of climatic and non-climatic variables as compared to individual variable based models. We conclude that a) regions with cooler climates and higher moisture availability could serve as refugia for endemic plants in future climatic conditions; b) mixed models provide more accurate results, compared to single variable based

Effects of future climate and land use scenarios on riverine source water quality.

Science.gov (United States)

Delpla, Ianis; Rodriguez, Manuel J

2014-09-15

Surface water quality is particularly sensitive to land use practices and climatic events that affect its catchment. The relative influence of a set of watershed characteristics (climate, land use, morphology and pedology) and climatic variables on two key water quality parameters (turbidity and fecal coliforms (FC)) was examined in 24 eastern Canadian catchments at various spatial scales (1 km, 5 km, 10 km and the entire catchment). A regression analysis revealed that the entire catchment was a better predictor of water quality. Based on this information, linear mixed effect models for predicting turbidity and FC levels were developed. A set of land use and climate scenarios was considered and applied within the water quality models. Four land use scenarios (no change, same rate of variation, optimistic and pessimistic) and three climate change scenarios (B1, A1B and A2) were tested and variations for the near future (2025) were assessed and compared to the reference period (2000). Climate change impacts on water quality remained low annually for this time horizon (turbidity: +1.5%, FC: +1.6%, A2 scenario). On the other hand, the influence of land use changes appeared to predominate. Significant benefits for both parameters could be expected following the optimistic scenario (turbidity: -16.4%, FC: -6.3%; p climate change impacts could become equivalent to those modeled for land use for this horizon. Copyright © 2014 Elsevier B.V. All rights reserved.

Updated analysis of flatfish recruitment response to climate variability and ocean conditions in the Eastern Bering Sea

Science.gov (United States)

Wilderbuer, Thomas; Stockhausen, William; Bond, Nicholas

2013-10-01

This study provides a retrospective analysis of the relationship between physical oceanography, biology and recruitment of three Eastern Bering Sea flatfish stocks: flathead sole (Hippoglossoides elassodon), northern rock sole (Lepidopsetta polyxystra), and arrowtooth flounder (Atheresthes stomias) during the period 1978-2005. Stock assessment model estimates of recruitment and spawning stock size indicate that temporal patterns in productivity are consistent with decadal scale (or shorter) patterns in climate variability, which may influence marine survival during the early life history phases. Density-dependence (through spawning stock size) was statistically significant in a Ricker stock-recruit model of flatfish recruitment that included environmental terms. Wind-driven advection of northern rock sole and flathead sole larvae to favorable nursery grounds was found to coincide with years of above-average recruitment. Ocean forcing of Bristol Bay surface waters during springtime was mostly on-shelf (eastward) during the 1980s and again in the early 2000s, but was off-shelf (westerly) during the 1990s, corresponding with periods of good and poor recruitment, respectively. Finally, the Arctic Oscillation was found to be an important indicator of arrowtooth flounder productivity. Model results were applied to IPCC (Intergovernmental Panel on Climate Change) future springtime wind scenarios to predict the future impact of climate on northern rock sole productivity and indicated that a moderate future increase in recruitment might be expected because the climate trends favor on-shelf transport but that density-dependence will dampen this effect such that northern rock sole abundance will not be substantially affected by climate change.

Decision-Support System for Urban Air Pollution under Future Climate Conditions

OpenAIRE

Jensen , Steen ,; Brandt , Jørgen; Hvidberg , Martin; Ketzel , Matthias; Hedegaard , Gitte ,; Christensen , Jens ,

2011-01-01

Part 6: Climate Services and Environmental Tools for Urban Planning and Climate Change Applications and Services; International audience; Climate change is expected to influence urban living conditions and challenge the ability of cities to adapt to and mitigate climate change. Urban climates will be faced with elevated temperatures and future climate conditions are expected to cause higher ozone concentrations, increased biogenic emissions from vegetation, changes in the chemistry of the atm...

Relationship between rice yield and climate variables in southwest Nigeria using multiple linear regression and support vector machine analysis.

Science.gov (United States)

Oguntunde, Philip G; Lischeid, Gunnar; Dietrich, Ottfried

2018-03-01

This study examines the variations of climate variables and rice yield and quantifies the relationships among them using multiple linear regression, principal component analysis, and support vector machine (SVM) analysis in southwest Nigeria. The climate and yield data used was for a period of 36 years between 1980 and 2015. Similar to the observed decrease (P  1 and explained 83.1% of the total variance of predictor variables. The SVM regression function using the scores of the first principal component explained about 75% of the variance in rice yield data and linear regression about 64%. SVM regression between annual solar radiation values and yield explained 67% of the variance. Only the first component of the principal component analysis (PCA) exhibited a clear long-term trend and sometimes short-term variance similar to that of rice yield. Short-term fluctuations of the scores of the PC1 are closely coupled to those of rice yield during the 1986-1993 and the 2006-2013 periods thereby revealing the inter-annual sensitivity of rice production to climate variability. Solar radiation stands out as the climate variable of highest influence on rice yield, and the influence was especially strong during monsoon and post-monsoon periods, which correspond to the vegetative, booting, flowering, and grain filling stages in the study area. The outcome is expected to provide more in-depth regional-specific climate-rice linkage for screening of better cultivars that can positively respond to future climate fluctuations as well as providing information that may help optimized planting dates for improved radiation use efficiency in the study area.

Women's role in adapting to climate change and variability

Science.gov (United States)

Carvajal-Escobar, Y.; Quintero-Angel, M.; García-Vargas, M.

2008-04-01

Given that women are engaged in more climate-related change activities than what is recognized and valued in the community, this article highlights their important role in the adaptation and search for safer communities, which leads them to understand better the causes and consequences of changes in climatic conditions. It is concluded that women have important knowledge and skills for orienting the adaptation processes, a product of their roles in society (productive, reproductive and community); and the importance of gender equity in these processes is recognized. The relationship among climate change, climate variability and the accomplishment of the Millennium Development Goals is considered.

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

Science.gov (United States)

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

Rainfall Downscaling Conditional on Upper-air Variables: Assessing Rainfall Statistics in a Changing Climate

Science.gov (United States)

Langousis, Andreas; Deidda, Roberto; Marrocu, Marino; Kaleris, Vassilios

2014-05-01

Due to its intermittent and highly variable character, and the modeling parameterizations used, precipitation is one of the least well reproduced hydrologic variables by both Global Climate Models (GCMs) and Regional Climate Models (RCMs). This is especially the case at a regional level (where hydrologic risks are assessed) and at small temporal scales (e.g. daily) used to run hydrologic models. In an effort to remedy those shortcomings and assess the effect of climate change on rainfall statistics at hydrologically relevant scales, Langousis and Kaleris (2013) developed a statistical framework for simulation of daily rainfall intensities conditional on upper air variables. The developed downscaling scheme was tested using atmospheric data from the ERA-Interim archive (http://www.ecmwf.int/research/era/do/get/index), and daily rainfall measurements from western Greece, and was proved capable of reproducing several statistical properties of actual rainfall records, at both annual and seasonal levels. This was done solely by conditioning rainfall simulation on a vector of atmospheric predictors, properly selected to reflect the relative influence of upper-air variables on ground-level rainfall statistics. In this study, we apply the developed framework for conditional rainfall simulation using atmospheric data from different GCM/RCM combinations. This is done using atmospheric data from the ENSEMBLES project (http://ensembleseu.metoffice.com), and daily rainfall measurements for an intermediate-sized catchment in Italy; i.e. the Flumendosa catchment. Since GCM/RCM products are suited to reproduce the local climatology in a statistical sense (i.e. in terms of relative frequencies), rather than ensuring a one-to-one temporal correspondence between observed and simulated fields (i.e. as is the case for ERA-interim reanalysis data), we proceed in three steps: a) we use statistical tools to establish a linkage between ERA-Interim upper-air atmospheric forecasts and

Irrigated agriculture and future climate change effects on groundwater recharge, northern High Plains aquifer, USA

Science.gov (United States)

Lauffenburger, Zachary H.; Gurdak, Jason J.; Hobza, Christopher M.; Woodward, Duane; Wolf, Cassandra

2018-01-01

Understanding the controls of agriculture and climate change on recharge rates is critically important to develop appropriate sustainable management plans for groundwater resources and coupled irrigated agricultural systems. In this study, several physical (total potential (ψT) time series) and chemical tracer and dating (3H, Cl−, Br−, CFCs, SF6, and 3H/3He) methods were used to quantify diffuse recharge rates beneath two rangeland sites and irrigation recharge rates beneath two irrigated corn sites along an east-west (wet-dry) transect of the northern High Plains aquifer, Platte River Basin, central Nebraska. The field-based recharge estimates and historical climate were used to calibrate site-specific Hydrus-1D models, and irrigation requirements were estimated using the Crops Simulation Model (CROPSIM). Future model simulations were driven by an ensemble of 16 global climate models and two global warming scenarios to project a 2050 climate relative to the historical baseline 1990 climate, and simulate changes in precipitation, irrigation, evapotranspiration, and diffuse and irrigation recharge rates. Although results indicate statistical differences between the historical variables at the eastern and western sites and rangeland and irrigated sites, the low warming scenario (+1.0 °C) simulations indicate no statistical differences between 2050 and 1990. However, the high warming scenarios (+2.4 °C) indicate a 25% and 15% increase in median annual evapotranspiration and irrigation demand, and decreases in future diffuse recharge by 53% and 98% and irrigation recharge by 47% and 29% at the eastern and western sites, respectively. These results indicate an important threshold between the low and high warming scenarios that if exceeded could trigger a significant bidirectional shift in 2050 hydroclimatology and recharge gradients. The bidirectional shift is that future northern High Plains temperatures will resemble present central High Plains

Projecting the Global Distribution of the Emerging Amphibian Fungal Pathogen, Batrachochytrium dendrobatidis, Based on IPCC Climate Futures.

Directory of Open Access Journals (Sweden)

Gisselle Yang Xie

Full Text Available Projected changes in climate conditions are emerging as significant risk factors to numerous species, affecting habitat conditions and community interactions. Projections suggest species range shifts in response to climate change modifying environmental suitability and is supported by observational evidence. Both pathogens and their hosts can shift ranges with climate change. We consider how climate change may influence the distribution of the emerging infectious amphibian chytrid fungus, Batrachochytrium dendrobatidis (Bd, a pathogen associated with worldwide amphibian population losses. Using an expanded global Bd database and a novel modeling approach, we examined a broad set of climate metrics to model the Bd-climate niche globally and regionally, then project how climate change may influence Bd distributions. Previous research showed that Bd distribution is dependent on climatic variables, in particular temperature. We trained a machine-learning model (random forest with the most comprehensive global compilation of Bd sampling records (~5,000 site-level records, mid-2014 summary, including 13 climatic variables. We projected future Bd environmental suitability under IPCC scenarios. The learning model was trained with combined worldwide data (non-region specific and also separately per region (region-specific. One goal of our study was to estimate of how Bd spatial risks may change under climate change based on the best available data. Our models supported differences in Bd-climate relationships among geographic regions. We projected that Bd ranges will shift into higher latitudes and altitudes due to increased environmental suitability in those regions under predicted climate change. Specifically, our model showed a broad expansion of areas environmentally suitable for establishment of Bd on amphibian hosts in the temperate zones of the Northern Hemisphere. Our projections are useful for the development of monitoring designs in these areas