Disease and thermal acclimation in a more variable and unpredictable climate

NASA Astrophysics Data System (ADS)

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

2013-02-01

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

Climate Exposure of US National Parks in a New Era of Change

PubMed Central

Monahan, William B.; Fisichelli, Nicholas A.

2014-01-01

US national parks are challenged by climate and other forms of broad-scale environmental change that operate beyond administrative boundaries and in some instances are occurring at especially rapid rates. Here, we evaluate the climate change exposure of 289 natural resource parks administered by the US National Park Service (NPS), and ask which are presently (past 10 to 30 years) experiencing extreme (<5th percentile or >95th percentile) climates relative to their 1901–2012 historical range of variability (HRV). We consider parks in a landscape context (including surrounding 30 km) and evaluate both mean and inter-annual variation in 25 biologically relevant climate variables related to temperature, precipitation, frost and wet day frequencies, vapor pressure, cloud cover, and seasonality. We also consider sensitivity of findings to the moving time window of analysis (10, 20, and 30 year windows). Results show that parks are overwhelmingly at the extreme warm end of historical temperature distributions and this is true for several variables (e.g., annual mean temperature, minimum temperature of the coldest month, mean temperature of the warmest quarter). Precipitation and other moisture patterns are geographically more heterogeneous across parks and show greater variation among variables. Across climate variables, recent inter-annual variation is generally well within the range of variability observed since 1901. Moving window size has a measureable effect on these estimates, but parks with extreme climates also tend to exhibit low sensitivity to the time window of analysis. We highlight particular parks that illustrate different extremes and may facilitate understanding responses of park resources to ongoing climate change. We conclude with discussion of how results relate to anticipated future changes in climate, as well as how they can inform NPS and neighboring land management and planning in a new era of change. PMID:24988483

Climate exposure of US national parks in a new era of change.

PubMed

Monahan, William B; Fisichelli, Nicholas A

2014-01-01

US national parks are challenged by climate and other forms of broad-scale environmental change that operate beyond administrative boundaries and in some instances are occurring at especially rapid rates. Here, we evaluate the climate change exposure of 289 natural resource parks administered by the US National Park Service (NPS), and ask which are presently (past 10 to 30 years) experiencing extreme (<5th percentile or >95th percentile) climates relative to their 1901-2012 historical range of variability (HRV). We consider parks in a landscape context (including surrounding 30 km) and evaluate both mean and inter-annual variation in 25 biologically relevant climate variables related to temperature, precipitation, frost and wet day frequencies, vapor pressure, cloud cover, and seasonality. We also consider sensitivity of findings to the moving time window of analysis (10, 20, and 30 year windows). Results show that parks are overwhelmingly at the extreme warm end of historical temperature distributions and this is true for several variables (e.g., annual mean temperature, minimum temperature of the coldest month, mean temperature of the warmest quarter). Precipitation and other moisture patterns are geographically more heterogeneous across parks and show greater variation among variables. Across climate variables, recent inter-annual variation is generally well within the range of variability observed since 1901. Moving window size has a measureable effect on these estimates, but parks with extreme climates also tend to exhibit low sensitivity to the time window of analysis. We highlight particular parks that illustrate different extremes and may facilitate understanding responses of park resources to ongoing climate change. We conclude with discussion of how results relate to anticipated future changes in climate, as well as how they can inform NPS and neighboring land management and planning in a new era of change.

Short-Term Effects of Climatic Variables on Hand, Foot, and Mouth Disease in Mainland China, 2008–2013: A Multilevel Spatial Poisson Regression Model Accounting for Overdispersion

PubMed Central

Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying

2016-01-01

Background Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. Methods The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008–2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. Results The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse “V” shape and “V” shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. Conclusion We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic variables spatial heterogeneity distributed across provinces. Future research should explore the risk factors that cause spatial correlated structure or high variation of HFMD incidence which can be explained by temperature. When analyzing association between HFMD incidence and climatic variables, spatial heterogeneity among provinces should be evaluated. Moreover, the extra-Poisson multilevel model was capable of modeling the association between overdispersion of HFMD incidence and climatic variables. PMID:26808311

Short-Term Effects of Climatic Variables on Hand, Foot, and Mouth Disease in Mainland China, 2008-2013: A Multilevel Spatial Poisson Regression Model Accounting for Overdispersion.

PubMed

Liao, Jiaqiang; Yu, Shicheng; Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying

2016-01-01

Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008-2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse "V" shape and "V" shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic variables spatial heterogeneity distributed across provinces. Future research should explore the risk factors that cause spatial correlated structure or high variation of HFMD incidence which can be explained by temperature. When analyzing association between HFMD incidence and climatic variables, spatial heterogeneity among provinces should be evaluated. Moreover, the extra-Poisson multilevel model was capable of modeling the association between overdispersion of HFMD incidence and climatic variables.

Detection and Attribution of Temperature Trends in the Presence of Natural Variability

NASA Astrophysics Data System (ADS)

Wallace, J. M.

2014-12-01

The fingerprint of human-induced global warming stands out clearly above the noise In the time series of global-mean temperature, but not local temperature. At extratropical latitudes over land the standard error of 50-year linear temperature trends at a fixed point is as large as the cumulative rise in global-mean temperature over the past century. Much of the samping variability in local temperature trends is "dynamically-induced", i.e., attributable to the fact that the seasonally-varying mean circulation varies substantially from one year to the next and anomalous circulation patterns are generally accompanied by anomalous temperature patterns. In the presence of such large sampling variability it is virtually impossible to identify the spatial signature of greenhouse warming based on observational data or to partition observed local temperature trends into natural and human-induced components. It follows that previous IPCC assessments, which have focused on the deterministic signature of human-induced climate change, are inherently limited as to what they can tell us about the attribution of the past record of local temperature change or about how much the temperature at a particular place is likely to rise in the next few decades in response to global warming. To obtain more informative assessments of regional and local climate variability and change it will be necessary to take a probabilistic approach. Just as the use of the ensembles has contributed to more informative extended range weather predictions, large ensembles of climate model simulations can provide a statistical context for interpreting observed climate change and for framing projections of future climate. For some purposes, statistics relating to the interannual variability in the historical record can serve as a surrogate for statistics relating to the diversity of climate change scenarios in large ensembles.

Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada

DOE PAGES

Eum, Hyung-Il; Gachon, Philippe; Laprise, René

2016-01-01

This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affectedmore » by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. Finally, these results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.« less

Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada

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

Eum, Hyung-Il; Gachon, Philippe; Laprise, René

This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affectedmore » by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. Finally, these results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.« less

Evaluation of climatic changes in South-Asia

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-02-01

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

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

PubMed

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

2015-01-15

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

Relationship between climatic variables and the variation in bulk tank milk composition using canonical correlation analysis.

PubMed

Stürmer, Morgana; Busanello, Marcos; Velho, João Pedro; Heck, Vanessa Isabel; Haygert-Velho, Ione Maria Pereira

2018-06-04

A number of studies have addressed the relations between climatic variables and milk composition, but these works used univariate statistical approaches. In our study, we used a multivariate approach (canonical correlation) to study the impact of climatic variables on milk composition, price, and monthly milk production at a dairy farm using bulk tank milk data. Data on milk composition, price, and monthly milk production were obtained from a dairy company that purchased the milk from the farm, while climatic variable data were obtained from the National Institute of Meteorology (INMET). The data are from January 2014 to December 2016. Univariate correlation analysis and canonical correlation analysis were performed. Few correlations between the climatic variables and milk composition were found using a univariate approach. However, using canonical correlation analysis, we found a strong and significant correlation (r c  = 0.95, p value = 0.0029). Lactose, ambient temperature measures (mean, minimum, and maximum), and temperature-humidity index (THI) were found to be the most important variables for the canonical correlation. Our study indicated that 10.2% of the variation in milk composition, pricing, and monthly milk production can be explained by climatic variables. Ambient temperature variables, together with THI, seem to have the most influence on variation in milk composition.

Relationship between climatic variables and the variation in bulk tank milk composition using canonical correlation analysis

NASA Astrophysics Data System (ADS)

Stürmer, Morgana; Busanello, Marcos; Velho, João Pedro; Heck, Vanessa Isabel; Haygert-Velho, Ione Maria Pereira

2018-06-01

A number of studies have addressed the relations between climatic variables and milk composition, but these works used univariate statistical approaches. In our study, we used a multivariate approach (canonical correlation) to study the impact of climatic variables on milk composition, price, and monthly milk production at a dairy farm using bulk tank milk data. Data on milk composition, price, and monthly milk production were obtained from a dairy company that purchased the milk from the farm, while climatic variable data were obtained from the National Institute of Meteorology (INMET). The data are from January 2014 to December 2016. Univariate correlation analysis and canonical correlation analysis were performed. Few correlations between the climatic variables and milk composition were found using a univariate approach. However, using canonical correlation analysis, we found a strong and significant correlation (r c = 0.95, p value = 0.0029). Lactose, ambient temperature measures (mean, minimum, and maximum), and temperature-humidity index (THI) were found to be the most important variables for the canonical correlation. Our study indicated that 10.2% of the variation in milk composition, pricing, and monthly milk production can be explained by climatic variables. Ambient temperature variables, together with THI, seem to have the most influence on variation in milk composition.

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

PubMed

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

2012-09-01

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

How important is interannual variability in the climatic interpretation of moraine sequences?

NASA Astrophysics Data System (ADS)

Leonard, E. M.; Laabs, B. J. C.; Plummer, M. A.

2017-12-01

Mountain glaciers respond to both long-term climate and interannual forcing. Anderson et al. (2014) pointed out that kilometer-scale fluctuations in glacier length may result from interannual variability in temperature and precipitation given a "steady" climate with no long-term trends in mean or variability of temperature and precipitation. They cautioned that use of outermost moraines from the Last Glacial Maximum (LGM) as indicators of LGM climate will, because of the role of interannual forcing, result in overestimation of the magnitude of long-term temperature depression and/or precipitation enhancement. Here we assess the implications of these ideas, by examining the effect of interannual variability on glacier length and inferred magnitude of LGM climate change from present under both an assumed steady LGM climate and an LGM climate with low-magnitude, long-period variation in summer temperature and annual precipitation. We employ both the original 1-stage linear glacier model (Roe and O'Neal, 2009) used by Anderson et al. (2014) and a newer 3-stage linear model (Roe and Baker, 2014). We apply the models to two reconstructed LGM glaciers in the Colorado Sangre de Cristo Mountains. Three-stage-model results indicate that, absent long-term variations through a 7500-year-long LGM, interannual variability would result in overestimation of mean LGM temperature depression from the outermost moraine of 0.2-0.6°C. If small long-term cyclic variations of temperature (±0.5°C) and precipitation (±5%) are introduced, the overestimation of LGM temperature depression reduces to less than 0.4°C, and if slightly greater long-term variation (±1.0°C and ±10% precipitation) is introduced, the magnitude of overestimation is 0.3°C or less. Interannual variability may produce a moraine sequence that differs from the sequence that would be expected were glacier length forced only by long-term climate. With small amplitude (±0.5°C and ±5% precipitation) long-term variation, the moraine sequence expected if forced by a combination of interannual variability and long-term climate differs from that expected based on long-term climate forcing alone in 38% of model runs. With the larger amplitude long-term forcing (±1.0°C and ±10% precipitation) this difference occurs in 20% of model runs.

Spread in the magnitude of climate model interdecadal global temperature variability traced to disagreements over high-latitude oceans

NASA Astrophysics Data System (ADS)

Brown, Patrick T.; Li, Wenhong; Jiang, Jonathan H.; Su, Hui

2016-12-01

Unforced variability in global mean surface air temperature can obscure or exaggerate global warming on interdecadal time scales; thus, understanding both the magnitude and generating mechanisms of such variability is of critical importance for both attribution studies as well as decadal climate prediction. Coupled atmosphere-ocean general circulation models (climate models) simulate a wide range of magnitudes of unforced interdecadal variability in global mean surface air temperature (UITglobal), hampering efforts to quantify the influence of UITglobal on contemporary global temperature trends. Recently, a preliminary consensus has emerged that unforced interdecadal variability in local surface temperatures (UITlocal) over the tropical Pacific Ocean is particularly influential on UITglobal. Therefore, a reasonable hypothesis might be that the large spread in the magnitude of UITglobal across climate models can be explained by the spread in the magnitude of simulated tropical Pacific UITlocal. Here we show that this hypothesis is mostly false. Instead, the spread in the magnitude of UITglobal is linked much more strongly to the spread in the magnitude of UITlocal over high-latitude regions characterized by significant variability in oceanic convection, sea ice concentration, and energy flux at both the surface and the top of the atmosphere. Thus, efforts to constrain the climate model produced range of UITglobal magnitude would be best served by focusing on the simulation of air-sea interaction at high latitudes.

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

NASA Astrophysics Data System (ADS)

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 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.

Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

NASA Technical Reports Server (NTRS)

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.

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

NASA Astrophysics Data System (ADS)

Gaertner, B. A.; Zegre, N.

2015-12-01

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

Change in the magnitude and mechanisms of global temperature variability with warming.

PubMed

Brown, Patrick T; Ming, Yi; Li, Wenhong; Hill, Spencer A

2017-01-01

Natural unforced variability in global mean surface air temperature (GMST) can mask or exaggerate human-caused global warming, and thus a complete understanding of this variability is highly desirable. Significant progress has been made in elucidating the magnitude and physical origins of present-day unforced GMST variability, but it has remained unclear how such variability may change as the climate warms. Here we present modeling evidence that indicates that the magnitude of low-frequency GMST variability is likely to decline in a warmer climate and that its generating mechanisms may be fundamentally altered. In particular, a warmer climate results in lower albedo at high latitudes, which yields a weaker albedo feedback on unforced GMST variability. These results imply that unforced GMST variability is dependent on the background climatological conditions, and thus climate model control simulations run under perpetual preindustrial conditions may have only limited relevance for understanding the unforced GMST variability of the future.

Change in the Magnitude and Mechanisms of Global Temperature Variability with Warming

NASA Astrophysics Data System (ADS)

Brown, P. T.; Ming, Y.; Li, W.; Hill, S. A.

2017-12-01

Natural unforced variability in global mean surface air temperature (GMST) can mask or exaggerate human-caused global warming, and thus a complete understanding of this variability is highly desirable. Significant progress has been made in elucidating the magnitude and physical origins of present-day unforced GMST variability, but it has remained unclear how such variability may change as the climate warms. Here we present modeling evidence that indicates that the magnitude of low-frequency GMST variability is likely to decline in a warmer climate and that its generating mechanisms may be fundamentally altered. In particular, a warmer climate results in lower albedo at high latitudes, which yields a weaker albedo feedback on unforced GMST variability. These results imply that unforced GMST variability is dependent on the background climatological conditions, and thus climate model control simulations run under perpetual preindustrial conditions may have only limited relevance for understanding the unforced GMST variability of the future.

Modeling climate effects on hip fracture rate by the multivariate GARCH model in Montreal region, Canada.

PubMed

Modarres, Reza; Ouarda, Taha B M J; Vanasse, Alain; Orzanco, Maria Gabriela; Gosselin, Pierre

2014-07-01

Changes in extreme meteorological variables and the demographic shift towards an older population have made it important to investigate the association of climate variables and hip fracture by advanced methods in order to determine the climate variables that most affect hip fracture incidence. The nonlinear autoregressive moving average with exogenous variable-generalized autoregressive conditional heteroscedasticity (ARMAX-GARCH) and multivariate GARCH (MGARCH) time series approaches were applied to investigate the nonlinear association between hip fracture rate in female and male patients aged 40-74 and 75+ years and climate variables in the period of 1993-2004, in Montreal, Canada. The models describe 50-56% of daily variation in hip fracture rate and identify snow depth, air temperature, day length and air pressure as the influencing variables on the time-varying mean and variance of the hip fracture rate. The conditional covariance between climate variables and hip fracture rate is increasing exponentially, showing that the effect of climate variables on hip fracture rate is most acute when rates are high and climate conditions are at their worst. In Montreal, climate variables, particularly snow depth and air temperature, appear to be important predictors of hip fracture incidence. The association of climate variables and hip fracture does not seem to change linearly with time, but increases exponentially under harsh climate conditions. The results of this study can be used to provide an adaptive climate-related public health program and ti guide allocation of services for avoiding hip fracture risk.

Modeling climate effects on hip fracture rate by the multivariate GARCH model in Montreal region, Canada

NASA Astrophysics Data System (ADS)

Modarres, Reza; Ouarda, Taha B. M. J.; Vanasse, Alain; Orzanco, Maria Gabriela; Gosselin, Pierre

2014-07-01

Changes in extreme meteorological variables and the demographic shift towards an older population have made it important to investigate the association of climate variables and hip fracture by advanced methods in order to determine the climate variables that most affect hip fracture incidence. The nonlinear autoregressive moving average with exogenous variable-generalized autoregressive conditional heteroscedasticity (ARMA X-GARCH) and multivariate GARCH (MGARCH) time series approaches were applied to investigate the nonlinear association between hip fracture rate in female and male patients aged 40-74 and 75+ years and climate variables in the period of 1993-2004, in Montreal, Canada. The models describe 50-56 % of daily variation in hip fracture rate and identify snow depth, air temperature, day length and air pressure as the influencing variables on the time-varying mean and variance of the hip fracture rate. The conditional covariance between climate variables and hip fracture rate is increasing exponentially, showing that the effect of climate variables on hip fracture rate is most acute when rates are high and climate conditions are at their worst. In Montreal, climate variables, particularly snow depth and air temperature, appear to be important predictors of hip fracture incidence. The association of climate variables and hip fracture does not seem to change linearly with time, but increases exponentially under harsh climate conditions. The results of this study can be used to provide an adaptive climate-related public health program and ti guide allocation of services for avoiding hip fracture risk.

The seasonal response of the Held-Suarez climate model to prescribed ocean temperature anomalies. I - Results of decadal integrations

NASA Technical Reports Server (NTRS)

Phillips, T. J.; Semtner, A. J., Jr.

1984-01-01

Anomalies in ocean surface temperature have been identified as possible causes of variations in the climate of particular seasons or as a source of interannual climatic variability, and attempts have been made to forecast seasonal climate by using ocean temperatures as predictor variables. However, the seasonal atmospheric response to ocean temperature anomalies has not yet been systematically investigated with nonlinear models. The present investigation is concerned with ten-year integrations involving a model of intermediate complexity, the Held-Suarez climate model. The calculations have been performed to investigate the changes in seasonal climate which result from a fixed anomaly imposed on a seasonally varying, global ocean temperature field. Part I of the paper provides a report on the results of these decadal integrations. Attention is given to model properties, the experimental design, and the anomaly experiments.

Assessing performance and seasonal bias of pollen-based climate reconstructions in a perfect model world

NASA Astrophysics Data System (ADS)

Rehfeld, Kira; Trachsel, Mathias; Telford, Richard J.; Laepple, Thomas

2016-12-01

Reconstructions of summer, winter or annual mean temperatures based on the species composition of bio-indicators such as pollen, foraminifera or chironomids are routinely used in climate model-proxy data comparison studies. Most reconstruction algorithms exploit the joint distribution of modern spatial climate and species distribution for the development of the reconstructions. They rely on the space-for-time substitution and the specific assumption that environmental variables other than those reconstructed are not important or that their relationship with the reconstructed variable(s) should be the same in the past as in the modern spatial calibration dataset. Here we test the implications of this "correlative uniformitarianism" assumption on climate reconstructions in an ideal model world, in which climate and vegetation are known at all times. The alternate reality is a climate simulation of the last 6000 years with dynamic vegetation. Transient changes of plant functional types are considered as surrogate pollen counts and allow us to establish, apply and evaluate transfer functions in the modeled world. We find that in our model experiments the transfer function cross validation r2 is of limited use to identify reconstructible climate variables, as it only relies on the modern spatial climate-vegetation relationship. However, ordination approaches that assess the amount of fossil vegetation variance explained by the reconstructions are promising. We furthermore show that correlations between climate variables in the modern climate-vegetation relationship are systematically extended into the reconstructions. Summer temperatures, the most prominent driving variable for modeled vegetation change in the Northern Hemisphere, are accurately reconstructed. However, the amplitude of the model winter and mean annual temperature cooling between the mid-Holocene and present day is overestimated and similar to the summer trend in magnitude. This effect occurs because temporal changes of a dominant climate variable, such as summer temperatures in the model's Arctic, are imprinted on a less important variable, leading to reconstructions biased towards the dominant variable's trends. Our results, although based on a model vegetation that is inevitably simpler than reality, indicate that reconstructions of multiple climate variables based on modern spatial bio-indicator datasets should be treated with caution. Expert knowledge on the ecophysiological drivers of the proxies, as well as statistical methods that go beyond the cross validation on modern calibration datasets, are crucial to avoid misinterpretation.

An assessment of global climate model-simulated climate for the western cordillera of Canada (1961-90)

NASA Astrophysics Data System (ADS)

Bonsal, Barrie R.; Prowse, Terry D.; Pietroniro, Alain

2003-12-01

Climate change is projected to significantly affect future hydrologic processes over many regions of the world. This is of particular importance for alpine systems that provide critical water supplies to lower-elevation regions. The western cordillera of Canada is a prime example where changes to temperature and precipitation could have profound hydro-climatic impacts not only for the cordillera itself, but also for downstream river systems and the drought-prone Canadian Prairies. At present, impact researchers primarily rely on global climate models (GCMs) for future climate projections. The main objective of this study is to assess several GCMs in their ability to simulate the magnitude and spatial variability of current (1961-90) temperature and precipitation over the western cordillera of Canada. In addition, several gridded data sets of observed climate for the study region are evaluated.Results reveal a close correspondence among the four gridded data sets of observed climate, particularly for temperature. There is, however, considerable variability regarding the various GCM simulations of this observed climate. The British, Canadian, German, Australian, and US GFDL models are superior at simulating the magnitude and spatial variability of mean temperature. The Japanese GCM is of intermediate ability, and the US NCAR model is least representative of temperature in this region. Nearly all the models substantially overestimate the magnitude of total precipitation, both annually and on a seasonal basis. An exception involves the British (Hadley) model, which best represents the observed magnitude and spatial variability of precipitation. This study improves our understanding regarding the accuracy of GCM climate simulations over the western cordillera of Canada. The findings may assist in producing more reliable future scenarios of hydro-climatic conditions over various regions of the country. Copyright

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

NASA Astrophysics Data System (ADS)

Magee, Madeline R.; Wu, Chin H.

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

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

PubMed

Kukal, Meetpal S; Irmak, Suat

2018-02-22

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

Region-Specific Sensitivity of Anemophilous Pollen Deposition to Temperature and Precipitation

PubMed Central

Donders, Timme H.; Hagemans, Kimberley; Dekker, Stefan C.; de Weger, Letty A.; de Klerk, Pim; Wagner-Cremer, Friederike

2014-01-01

Understanding relations between climate and pollen production is important for several societal and ecological challenges, importantly pollen forecasting for pollinosis treatment, forensic studies, global change biology, and high-resolution palaeoecological studies of past vegetation and climate fluctuations. For these purposes, we investigate the role of climate variables on annual-scale variations in pollen influx, test the regional consistency of observed patterns, and evaluate the potential to reconstruct high-frequency signals from sediment archives. A 43-year pollen-trap record from the Netherlands is used to investigate relations between annual pollen influx, climate variables (monthly and seasonal temperature and precipitation values), and the North Atlantic Oscillation climate index. Spearman rank correlation analysis shows that specifically in Alnus, Betula, Corylus, Fraxinus, Quercus and Plantago both temperature in the year prior to (T-1), as well as in the growing season (T), are highly significant factors (TApril rs between 0.30 [P<0.05[ and 0.58 [P<0.0001]; TJuli-1 rs between 0.32 [P<0.05[ and 0.56 [P<0.0001]) in the annual pollen influx of wind-pollinated plants. Total annual pollen prediction models based on multiple climate variables yield R2 between 0.38 and 0.62 (P<0.0001). The effect of precipitation is minimal. A second trapping station in the SE Netherlands, shows consistent trends and annual variability, suggesting the climate factors are regionally relevant. Summer temperature is thought to influence the formation of reproductive structures, while temperature during the flowering season influences pollen release. This study provides a first predictive model for seasonal pollen forecasting, and also aides forensic studies. Furthermore, variations in pollen accumulation rates from a sub-fossil peat deposit are comparable with the pollen trap data. This suggests that high frequency variability pollen records from natural archives reflect annual past climate variability, and can be used in palaeoecological and -climatological studies to bridge between population- and species-scale responses to climate forcing. PMID:25133631

Characterizing Temperature Variability and Associated Large Scale Meteorological Patterns Across South America

NASA Astrophysics Data System (ADS)

Detzer, J.; Loikith, P. C.; Mechoso, C. R.; Barkhordarian, A.; Lee, H.

2017-12-01

South America's climate varies considerably owing to its large geographic range and diverse topographical features. Spanning the tropics to the mid-latitudes and from high peaks to tropical rainforest, the continent experiences an array of climate and weather patterns. Due to this considerable spatial extent, assessing temperature variability at the continent scale is particularly challenging. It is well documented in the literature that temperatures have been increasing across portions of South America in recent decades, and while there have been many studies that have focused on precipitation variability and change, temperature has received less scientific attention. Therefore, a more thorough understanding of the drivers of temperature variability is critical for interpreting future change. First, k-means cluster analysis is used to identify four primary modes of temperature variability across the continent, stratified by season. Next, composites of large scale meteorological patterns (LSMPs) are calculated for months assigned to each cluster. Initial results suggest that LSMPs, defined using meteorological variables such as sea level pressure (SLP), geopotential height, and wind, are able to identify synoptic scale mechanisms important for driving temperature variability at the monthly scale. Some LSMPs indicate a relationship with known recurrent modes of climate variability. For example, composites of geopotential height suggest that the Southern Annular Mode is an important, but not necessarily dominant, component of temperature variability over southern South America. This work will be extended to assess the drivers of temperature extremes across South America.

Analysis of rainfall and temperature time series to detect long-term climatic trends and variability over semi-arid Botswana

NASA Astrophysics Data System (ADS)

Byakatonda, Jimmy; Parida, B. P.; Kenabatho, Piet K.; Moalafhi, D. B.

2018-03-01

Arid and semi-arid environments have been identified with locations prone to impacts of climate variability and change. Investigating long-term trends is one way of tracing climate change impacts. This study investigates variability through annual and seasonal meteorological time series. Possible inhomogeneities and years of intervention are analysed using four absolute homogeneity tests. Trends in the climatic variables were determined using Mann-Kendall and Sen's Slope estimator statistics. Association of El Niño Southern Oscillation (ENSO) with local climate is also investigated through multivariate analysis. Results from the study show that rainfall time series are fully homogeneous with 78.6 and 50% of the stations for maximum and minimum temperature, respectively, showing homogeneity. Trends also indicate a general decrease of 5.8, 7.4 and 18.1% in annual, summer and winter rainfall, respectively. Warming trends are observed in annual and winter temperature at 0.3 and 1.5% for maximum temperature and 1.7 and 6.5% for minimum temperature, respectively. Rainfall reported a positive correlation with Southern Oscillation Index (SOI) and at the same time negative association with Sea Surface Temperatures (SSTs). Strong relationships between SSTs and maximum temperature are observed during the El Niño and La Niña years. These study findings could facilitate planning and management of agricultural and water resources in Botswana.

Statistical structure of intrinsic climate variability under global warming

NASA Astrophysics Data System (ADS)

Zhu, Xiuhua; Bye, John; Fraedrich, Klaus

2017-04-01

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

Disentangling Global Warming, Multidecadal Variability, and El Niño in Pacific Temperatures

NASA Astrophysics Data System (ADS)

Wills, Robert C.; Schneider, Tapio; Wallace, John M.; Battisti, David S.; Hartmann, Dennis L.

2018-03-01

A key challenge in climate science is to separate observed temperature changes into components due to internal variability and responses to external forcing. Extended integrations of forced and unforced climate models are often used for this purpose. Here we demonstrate a novel method to separate modes of internal variability from global warming based on differences in time scale and spatial pattern, without relying on climate models. We identify uncorrelated components of Pacific sea surface temperature variability due to global warming, the Pacific Decadal Oscillation (PDO), and the El Niño-Southern Oscillation (ENSO). Our results give statistical representations of PDO and ENSO that are consistent with their being separate processes, operating on different time scales, but are otherwise consistent with canonical definitions. We isolate the multidecadal variability of the PDO and find that it is confined to midlatitudes; tropical sea surface temperatures and their teleconnections mix in higher-frequency variability. This implies that midlatitude PDO anomalies are more persistent than previously thought.

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

PubMed

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

2013-06-01

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

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

PubMed

Molina, Oswaldo; Saldarriaga, Victor

2017-02-01

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

Germination responses to current and future temperatures of four seeder shrubs across a latitudinal gradient in western Iberia.

PubMed

Chamorro, Daniel; Luna, Belén; Moreno, José M

2017-01-01

Species differ in their temperature germination niche. Populations of a species may similarly differ across the distribution range of the species. Anticipating the impacts of climate variability and change requires understanding the differential sensitivity to germination temperature among and within species. Here we studied the germination responses of four hard-seeded Cistaceae seeders to a range of current and future temperatures. Seeds were collected at sites across the Iberian Peninsula and exposed or not exposed to a heat shock to break dormancy, then set to germinate under four temperature regimes. Temperatures were varied daily and seasonally, simulating the temperature range across the gradient, plus an increased temperature simulating future climate. Time to germination onset and cumulative germination at the end of each season were analyzed for the effects of temperature treatments, seasons, and local climate (temperature of the germination period, T gp ) at each site. T gp was a significant covariate of germination in all species but Cistus populifolius. Temperature treatments significantly affected Cistus ladanifer, C. salviifolius, and Halimium ocymoides. Germination occurred in simulated autumn conditions, with little germination occurring at later seasons, except in unheated seeds of H. ocymoides. Exposure to a heat shock changed the sensitivity to temperature treatments and the relationships with T gp . Germination responses to temperature differ not only among species but also within species across their latitudinal range. The responses were idiosyncratic and related to the local climate of the population. This germination variability complicates generalizing the impacts of climate variability and climate change. © 2017 Botanical Society of America.

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

PubMed

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

2017-03-01

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

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

NASA Astrophysics Data System (ADS)

Parsons, Luke Alexander

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

Amplification and dampening of soil respiration by changes in temperature variability

USGS Publications Warehouse

Sierra, C.A.; Harmon, M.E.; Thomann, E.; Perakis, S.S.; Loescher, H.W.

2011-01-01

Accelerated release of carbon from soils is one of the most important feed backs related to anthropogenically induced climate change. Studies addressing the mechanisms for soil carbon release through organic matter decomposition have focused on the effect of changes in the average temperature, with little attention to changes in temperature vari-ability. Anthropogenic activities are likely to modify both the average state and the variability of the climatic system; therefore, the effects of future warming on decomposition should not only focus on trends in the average temperature, but also variability expressed as a change of the probability distribution of temperature.Using analytical and numerical analyses we tested common relationships between temperature and respiration and found that the variability of temperature plays an important role determining respiration rates of soil organic matter. Changes in temperature variability, without changes in the average temperature, can affect the amount of carbon released through respiration over the long term. Furthermore, simultaneous changes in the average and variance of temperature can either amplify or dampen there release of carbon through soil respiration as climate regimes change. The effects depend on the degree of convexity of the relationship between temperature and respiration and the magnitude of the change in temperature variance. A potential consequence of this effect of variability would be higher respiration in regions where both the mean and variance of temperature are expected to increase, such as in some low latitude regions; and lower amounts of respiration where the average temperature is expected to increase and the variance to decrease, such as in northern high latitudes.

Frontiers in Decadal Climate Variability: Proceedings of a Workshop

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

Purcell, Amanda

A number of studies indicate an apparent slowdown in the overall rise in global average surface temperature between roughly 1998 and 2014. Most models did not predict such a slowdown--a fact that stimulated a lot of new research on variability of Earth's climate system. At a September 2015 workshop, leading scientists gathered to discuss current understanding of climate variability on decadal timescales (10 to 30 years) and whether and how prediction of it might be improved. Many researchers have focused their attention on the climate system itself, which is known to vary across seasons, decades, and other timescales. Several naturalmore » variables produce "ups and downs" in the climate system, which are superimposed on the long-term warming trend due to human influence. Understanding decadal climate variability is important not only for assessing global climate change but also for improving decision making related to infrastructure, water resources, agriculture, energy, and other realms. Like the well-studied El Nino and La Nina interannual variations, decadal climate variability is associated with specific regional patterns of temperature and precipitation, such as heat waves, cold spells, and droughts. Several participants shared research that assesses decadal predictive capability of current models.« less

Climate Factors as Important Determinants of Dengue Incidence in Curaçao.

PubMed

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

2016-03-01

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

Skilful multi-year predictions of tropical trans-basin climate variability

PubMed Central

Chikamoto, Yoshimitsu; Timmermann, Axel; Luo, Jing-Jia; Mochizuki, Takashi; Kimoto, Masahide; Watanabe, Masahiro; Ishii, Masayoshi; Xie, Shang-Ping; Jin, Fei-Fei

2015-01-01

Tropical Pacific sea surface temperature anomalies influence the atmospheric circulation, impacting climate far beyond the tropics. The predictability of the corresponding atmospheric signals is typically limited to less than 1 year lead time. Here we present observational and modelling evidence for multi-year predictability of coherent trans-basin climate variations that are characterized by a zonal seesaw in tropical sea surface temperature and sea-level pressure between the Pacific and the other two ocean basins. State-of-the-art climate model forecasts initialized from a realistic ocean state show that the low-frequency trans-basin climate variability, which explains part of the El Niño Southern Oscillation flavours, can be predicted up to 3 years ahead, thus exceeding the predictive skill of current tropical climate forecasts for natural variability. This low-frequency variability emerges from the synchronization of ocean anomalies in all basins via global reorganizations of the atmospheric Walker Circulation. PMID:25897996

Skilful multi-year predictions of tropical trans-basin climate variability.

PubMed

Chikamoto, Yoshimitsu; Timmermann, Axel; Luo, Jing-Jia; Mochizuki, Takashi; Kimoto, Masahide; Watanabe, Masahiro; Ishii, Masayoshi; Xie, Shang-Ping; Jin, Fei-Fei

2015-04-21

Tropical Pacific sea surface temperature anomalies influence the atmospheric circulation, impacting climate far beyond the tropics. The predictability of the corresponding atmospheric signals is typically limited to less than 1 year lead time. Here we present observational and modelling evidence for multi-year predictability of coherent trans-basin climate variations that are characterized by a zonal seesaw in tropical sea surface temperature and sea-level pressure between the Pacific and the other two ocean basins. State-of-the-art climate model forecasts initialized from a realistic ocean state show that the low-frequency trans-basin climate variability, which explains part of the El Niño Southern Oscillation flavours, can be predicted up to 3 years ahead, thus exceeding the predictive skill of current tropical climate forecasts for natural variability. This low-frequency variability emerges from the synchronization of ocean anomalies in all basins via global reorganizations of the atmospheric Walker Circulation.

Assessing performance and seasonal bias of pollen-based climate reconstructions in a perfect model world

NASA Astrophysics Data System (ADS)

Trachsel, M.; Rehfeld, K.; Telford, R.; Laepple, T.

2017-12-01

Reconstructions of summer, winter or annual mean temperatures based on the species composition of bio-indicators such as pollen are routinely used in climate model-proxy data comparison studies. Most reconstruction algorithms exploit the joint distribution of modern spatial climate and species distribution for the development of the reconstructions. They rely on the space-for-time substitution and the specific assumption that environmental variables other than those reconstructed are not important or that their relationship with the reconstructed variable(s) should be the same in the past as in the modern spatial calibration dataset. Here we test the implications of this "correlative uniformitarianism" assumption on climate reconstructions in an ideal model world, in which climate and vegetation are known at all times. The alternate reality is a climate simulation of the last 6000 years with dynamic vegetation. Transient changes of plant functional types are considered as surrogate pollen counts and allow us to establish, apply and evaluate transfer functions in the modeled world. We find that the transfer function cross validation r2 is of limited use to identify reconstructible climate variables, as it only relies on the modern spatial climate-vegetation relationship. However, ordination approaches that assess the amount of fossil vegetation variance explained by the reconstructions are promising. We show that correlations between climate variables in the modern climate-vegetation relationship are systematically extended into the reconstructions. Summer temperatures, the most prominent driving variable for modeled vegetation change in the Northern Hemisphere, are accurately reconstructed. However, the amplitude of the model winter and mean annual temperature cooling between the mid-Holocene and present day is overestimated and similar to the summer trend in magnitude. This effect occurs because temporal changes of a dominant climate variable are imprinted on a less important variable, leading to reconstructions biased towards the dominant variable's trends. Our results, although based on a model vegetation that is inevitably simpler than reality, indicate that reconstructions of multiple climate variables based on modern spatial bio-indicator datasets should be treated with caution.

Climate Change Impact Assessment in Pacific North West Using Copula based Coupling of Temperature and Precipitation variables

NASA Astrophysics Data System (ADS)

Qin, Y.; Rana, A.; Moradkhani, H.

2014-12-01

The multi downscaled-scenario products allow us to better assess the uncertainty of the changes/variations of precipitation and temperature in the current and future periods. Joint Probability distribution functions (PDFs), of both the climatic variables, might help better understand the interdependence of the two, and thus in-turn help in accessing the future with confidence. Using the joint distribution of temperature and precipitation is also of significant importance in hydrological applications and climate change studies. In the present study, we have used multi-modelled statistically downscaled-scenario ensemble of precipitation and temperature variables using 2 different statistically downscaled climate dataset. The datasets used are, 10 Global Climate Models (GCMs) downscaled products from CMIP5 daily dataset, namely, those from the Bias Correction and Spatial Downscaling (BCSD) technique generated at Portland State University and from the Multivariate Adaptive Constructed Analogs (MACA) technique, generated at University of Idaho, leading to 2 ensemble time series from 20 GCM products. Thereafter the ensemble PDFs of both precipitation and temperature is evaluated for summer, winter, and yearly periods for all the 10 sub-basins across Columbia River Basin (CRB). Eventually, Copula is applied to establish the joint distribution of two variables enabling users to model the joint behavior of the variables with any level of correlation and dependency. Moreover, the probabilistic distribution helps remove the limitations on marginal distributions of variables in question. The joint distribution is then used to estimate the change trends of the joint precipitation and temperature in the current and future, along with estimation of the probabilities of the given change. Results have indicated towards varied change trends of the joint distribution of, summer, winter, and yearly time scale, respectively in all 10 sub-basins. Probabilities of changes, as estimated by the joint precipitation and temperature, will provide useful information/insights for hydrological and climate change predictions.

Screening variability and change of soil moisture under wide-ranging climate conditions: Snow dynamics effects.

PubMed

Verrot, Lucile; Destouni, Georgia

2015-01-01

Soil moisture influences and is influenced by water, climate, and ecosystem conditions, affecting associated ecosystem services in the landscape. This paper couples snow storage-melting dynamics with an analytical modeling approach to screening basin-scale, long-term soil moisture variability and change in a changing climate. This coupling enables assessment of both spatial differences and temporal changes across a wide range of hydro-climatic conditions. Model application is exemplified for two major Swedish hydrological basins, Norrström and Piteälven. These are located along a steep temperature gradient and have experienced different hydro-climatic changes over the time period of study, 1950-2009. Spatially, average intra-annual variability of soil moisture differs considerably between the basins due to their temperature-related differences in snow dynamics. With regard to temporal change, the long-term average state and intra-annual variability of soil moisture have not changed much, while inter-annual variability has changed considerably in response to hydro-climatic changes experienced so far in each basin.

Analysis of vegetation dynamics and climatic variability impacts on greenness across Canada using remotely sensed data from 2000 to 2009

NASA Astrophysics Data System (ADS)

Fang, Xiuqin; Zhu, Qiuan; Chen, Huai; Ma, Zhihai; Wang, Weifeng; Song, Xinzhang; Zhao, Pengxiang; Peng, Changhui

2014-01-01

Using time series of moderate-resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data from 2000 to 2009, we assessed decadal vegetation dynamics across Canada and examined the relationship between NDVI and climatic variables (precipitation and temperature). The Palmer drought severity index and vapor pressure difference (VPD) were used to relate the vegetation changes to the climate, especially in cases of drought. Results indicated that MODIS NDVI measurements provided a dynamic picture of interannual variation in Canadian vegetation patterns. Greenness declined in 2000, 2002, and 2009 and increased in 2005, 2006, and 2008. Vegetation dynamics varied across regions during the period. Most forest land shows little change, while vegetation in the ecozone of Pacific Maritime, Prairies, and Taiga Shield shows more dynamics than in the others. Significant correlations were found between NDVI and the climatic variables. The variation of NDVI resulting from climatic variability was more highly correlated to temperature than to precipitation in most ecozones. Vegetation grows better with higher precipitation and temperature in almost all ecozones. However, vegetation grows worse under higher temperature in the Prairies ecozone. The annual changes in NDVI corresponded well with the change in VPD in most ecozones.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Change in the magnitude and mechanisms of global temperature variability with warming

PubMed Central

Brown, Patrick T.; Ming, Yi; Li, Wenhong; Hill, Spencer A.

2017-01-01

Natural unforced variability in global mean surface air temperature (GMST) can mask or exaggerate human-caused global warming, and thus a complete understanding of this variability is highly desirable. Significant progress has been made in elucidating the magnitude and physical origins of present-day unforced GMST variability, but it has remained unclear how such variability may change as the climate warms. Here we present modeling evidence that indicates that the magnitude of low-frequency GMST variability is likely to decline in a warmer climate and that its generating mechanisms may be fundamentally altered. In particular, a warmer climate results in lower albedo at high latitudes, which yields a weaker albedo feedback on unforced GMST variability. These results imply that unforced GMST variability is dependent on the background climatological conditions, and thus climate model control simulations run under perpetual preindustrial conditions may have only limited relevance for understanding the unforced GMST variability of the future. PMID:29391875

Global warming: it's not only size that matters

NASA Astrophysics Data System (ADS)

Hegerl, Gabriele C.

2011-09-01

Observed and model simulated warming is particularly large in high latitudes, and hence the Arctic is often seen as the posterchild of vulnerability to global warming. However, Mahlstein et al (2011) point out that the signal of climate change is emerging locally from that of climate variability earliest in regions of low climate variability, based on climate model data, and in agreement with observations. This is because high latitude regions are not only regions of strong feedbacks that enhance the global warming signal, but also regions of substantial climate variability, driven by strong dynamics and enhanced by feedbacks (Hall 2004). Hence the spatial pattern of both observed warming and simulated warming for the 20th century shows strong warming in high latitudes, but this warming occurs against a backdrop of strong variability. Thus, the ratio of the warming to internal variability is not necessarily highest in the regions that warm fastest—and Mahlstein et al illustrate that it is actually the low-variability regions where the signal of local warming emerges first from that of climate variability. Thus, regions with strongest warming are neither the most important to diagnose that forcing changes climate, nor are they the regions which will necessarily experience the strongest impact. The importance of the signal-to-noise ratio has been known to the detection and attribution community, but has been buried in technical 'optimal fingerprinting' literature (e.g., Hasselmann 1979, Allen and Tett 1999), where it was used for an earlier detection of climate change by emphasizing aspects of the fingerprint of global warming associated with low variability in estimates of the observed warming. What, however, was not discussed was that the local signal-to-noise ratio is of interest also for local climate change: where temperatures emerge from the range visited by internal climate variability, it is reasonable to assume that changes in climate will also cause more impacts than temperatures that have occurred frequently due to internal climate variability. Determining when exactly temperatures enter unusual ranges may be done in many different ways (and the paper shows several, and more could be imagined), but the main result of first local emergence in low latitudes remains robust. A worrying factor is that the regions where the signal is expected to emerge first, or is already emerging are largely regions in Africa, parts of South and Central America, and the Maritime Continent; regions that are vulnerable to climate change for a variety of regions (see IPCC 2007), and regions which contribute generally little to global greenhouse gas emissions. In contrast, strong emissions of greenhouse gases occur in regions of low warming-to-variability ratio. To get even closer to the relevance of this finding for impacts, it would be interesting to place the emergence of highly unusual summer temperatures in the context not of internal variability, but in the context of variability experienced by the climate system prior to the 20th century, as, e.g. documented in palaeoclimatic reconstructions and simulated in simulations of the last millennium (see Jansen et al 2007). External forcing has moved the temperature range around more strongly for some regions and in some seasons than others. For example, while reconstructions of summer temperatures in Europe appear to show small long-term variations, winter shows deep drops in temperature in the little Ice Age and a long-term increase since then (Luterbacher et al 2004), which was at least partly caused by external forcing (Hegerl et al 2011a) and therefore 'natural variability' may be different from internal variability. A further interesting question in attempts to provide a climate-based proxy for impacts of climate change is: to what extent does the rapidity of change matter, and how does it compare to trends due to natural variability? It is reasonable to assume that fast changes impact ecosystems and society more than slow, gradual ones. Also, is it really the mean seasonal temperature that counts, or should the focus change to extremes (see Hegerl et al 2011b)? Is seasonal mean exceedance of the prior temperature envelope a good and robust measure that also reflects these other, more complex diagnostics? Lots of food for thought and research! References Allen M R and Tett S F B 1999 Checking for model consistency in optimal finger printing Clim. Dyn. 15 419-34 Hall A 2004 The role of surface albedo feedback in climate J. Clim. 17 1550-68 Hasselmann K 1979 On the signal-to-noise problem in atmospheric response studies Meteorology of Tropical Oceans ed D B Shaw (Bracknell: Royal Meteorological Society) pp 251-9 Hegerl G C, Luterbacher J, Gonzalez-Ruoco F, Tett S F B and Xoplaki E 2011a Influence of human and natural forcing on European seasonal temperatures Nature Geoscience 4 99-103 Hegerl G, Hanlon H and Beierkuhnlein C 2011b Climate science: elusive extremes Nature Geoscience 4 142-3 IPCC 2007 Climate Change 2007: Impacts, Adaption and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change ed M L Parry, O F Canziani, J P Palutikof, P J van der Linden and C E Hanson (Cambridge: Cambridge University Press) Jansen E et al 2007 Palaeoclimate Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change ed S Solomon et al (Cambridge: Cambridge University Press) Luterbacher J et al 2004 European seasonal and annual temperature variability, trends, and extremes since 1500 Science 303 1499-503 Mahlstein I, Knutti R, Solomon S and Portmann R W 2011 Early onset of significant local warming in low latitude countries Environ. Res. Lett. 6 034009

Recent Climate Variability in Antarctica from Satellite-derived Temperature Data

NASA Technical Reports Server (NTRS)

Schneider, David P.; Steig, Eric J.; Comiso, Josefino C.

2004-01-01

Recent Antarctic climate variability on month-to-month to interannual time scales is assessed through joint analysis of surface temperatures from satellite thermal infrared observations (T(sub IR)) and passive microwave brightness temperatures (T(sub B)). Although Tw data are limited to clear-sky conditions and T(sub B) data are a product of the temperature and emissivity of the upper approx. 1m of snow, the two data sets share significant covariance. This covariance is largely explained by three empirical modes, which illustrate the spatial and temporal variability of Antarctic surface temperatures. T(sub B) variations are damped compared to TIR variations, as determined by the period of the temperature forcing and the microwave emission depth; however, microwave emissivity does not vary significantly in time. Comparison of the temperature modes with Southern Hemisphere (SH) 500-hPa geopotential height anomalies demonstrates that Antarctic temperature anomalies are predominantly controlled by the principal patterns of SH atmospheric circulation. The leading surface temperature mode strongly correlates with the Southern Annular Mode (SAM) in geopotential height. The second temperature mode reflects the combined influences of the zonal wavenumber-3 and Pacific South American (PSA) patterns in 500-hPa height on month-to-month timescales. ENSO variability projects onto this mode on interannual timescales, but is not by itself a good predictor of Antarctic temperature anomalies. The third temperature mode explains winter warming trends, which may be caused by blocking events, over a large region of the East Antarctic plateau. These results help to place recent climate changes in the context of Antarctica's background climate variability and will aid in the interpretation of ice core paleoclimate records.

Climate variation explains a third of global crop yield variability

PubMed Central

Ray, Deepak K.; Gerber, James S.; MacDonald, Graham K.; West, Paul C.

2015-01-01

Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for ~13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, >60% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (~32–39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability. PMID:25609225

Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability.

PubMed

Booth, Ben B B; Dunstone, Nick J; Halloran, Paul R; Andrews, Timothy; Bellouin, Nicolas

2012-04-04

Systematic climate shifts have been linked to multidecadal variability in observed sea surface temperatures in the North Atlantic Ocean. These links are extensive, influencing a range of climate processes such as hurricane activity and African Sahel and Amazonian droughts. The variability is distinct from historical global-mean temperature changes and is commonly attributed to natural ocean oscillations. A number of studies have provided evidence that aerosols can influence long-term changes in sea surface temperatures, but climate models have so far failed to reproduce these interactions and the role of aerosols in decadal variability remains unclear. Here we use a state-of-the-art Earth system climate model to show that aerosol emissions and periods of volcanic activity explain 76 per cent of the simulated multidecadal variance in detrended 1860-2005 North Atlantic sea surface temperatures. After 1950, simulated variability is within observational estimates; our estimates for 1910-1940 capture twice the warming of previous generation models but do not explain the entire observed trend. Other processes, such as ocean circulation, may also have contributed to variability in the early twentieth century. Mechanistically, we find that inclusion of aerosol-cloud microphysical effects, which were included in few previous multimodel ensembles, dominates the magnitude (80 per cent) and the spatial pattern of the total surface aerosol forcing in the North Atlantic. Our findings suggest that anthropogenic aerosol emissions influenced a range of societally important historical climate events such as peaks in hurricane activity and Sahel drought. Decadal-scale model predictions of regional Atlantic climate will probably be improved by incorporating aerosol-cloud microphysical interactions and estimates of future concentrations of aerosols, emissions of which are directly addressable by policy actions.

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

Treesearch

Marie Oliver; David W. Peterson; Becky Kerns

2016-01-01

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

The influence of climate variables on dengue in Singapore.

PubMed

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

2011-12-01

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

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

PubMed

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

2018-05-01

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

Sensitivity of summer stream temperatures to climate variability in the Pacific Northwest

Treesearch

Charles Luce; Brian Staab; Marc Kramer; Seth Wenger; Dan Isaak; Callie McConnell

2014-01-01

Estimating the thermal response of streams to a warming climate is important for prioritizing native fish conservation efforts. While there are plentiful estimates of air temperature responses to climate change, the sensitivity of streams, particularly small headwater streams, to warming temperatures is less well understood. A substantial body of literature correlates...

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

PubMed Central

2012-01-01

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

Crop responses to climatic variation

PubMed Central

Porter, John R; Semenov, Mikhail A

2005-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Measuring Skin Temperatures with the IASI Hyperspectral Mission

NASA Astrophysics Data System (ADS)

Safieddine, S.; George, M.; Clarisse, L.; Clerbaux, C.

2017-12-01

Although the role of satellites in observing the variability of the Earth system has increased in recent decades, remote-sensing observations are still underexploited to accurately assess climate change fingerprints, in particular temperature variations. The IASI - Flux and Temperature (IASI-FT) project aims at providing new benchmarks for temperature observations using the calibrated radiances measured twice a day at any location by the IASI thermal infrared instrument on the suite of MetOp satellites (2006-2025). The main challenge is to achieve the accuracy and stability needed for climate studies, particularly that required for climate trends. Time series for land and sea skin surface temperatures are derived and compared with in situ measurements and atmospheric reanalysis. The observed trends are analyzed at seasonal and regional scales in order to disentangle natural (weather/dynamical) variability and human-induced climate forcings.

Multiple stressors, nonlinear effects and the implications of climate change impacts on marine coastal ecosystems.

PubMed

Hewitt, Judi E; Ellis, Joanne I; Thrush, Simon F

2016-08-01

Global climate change will undoubtedly be a pressure on coastal marine ecosystems, affecting not only species distributions and physiology but also ecosystem functioning. In the coastal zone, the environmental variables that may drive ecological responses to climate change include temperature, wave energy, upwelling events and freshwater inputs, and all act and interact at a variety of spatial and temporal scales. To date, we have a poor understanding of how climate-related environmental changes may affect coastal marine ecosystems or which environmental variables are likely to produce priority effects. Here we use time series data (17 years) of coastal benthic macrofauna to investigate responses to a range of climate-influenced variables including sea-surface temperature, southern oscillation indices (SOI, Z4), wind-wave exposure, freshwater inputs and rainfall. We investigate responses from the abundances of individual species to abundances of functional traits and test whether species that are near the edge of their tolerance to another stressor (in this case sedimentation) may exhibit stronger responses. The responses we observed were all nonlinear and some exhibited thresholds. While temperature was most frequently an important predictor, wave exposure and ENSO-related variables were also frequently important and most ecological variables responded to interactions between environmental variables. There were also indications that species sensitive to another stressor responded more strongly to weaker climate-related environmental change at the stressed site than the unstressed site. The observed interactions between climate variables, effects on key species or functional traits, and synergistic effects of additional anthropogenic stressors have important implications for understanding and predicting the ecological consequences of climate change to coastal ecosystems. © 2015 John Wiley & Sons Ltd.

Cross-scale modeling of surface temperature and tree seedling establishment inmountain landscapes

USGS Publications Warehouse

Dingman, John; Sweet, Lynn C.; McCullough, Ian M.; Davis, Frank W.; Flint, Alan L.; Franklin, Janet; Flint, Lorraine E.

2013-01-01

Abstract: Introduction: Estimating surface temperature from above-ground field measurements is important for understanding the complex landscape patterns of plant seedling survival and establishment, processes which occur at heights of only several centimeters. Currently, future climate models predict temperature at 2 m above ground, leaving ground-surface microclimate not well characterized. Methods: Using a network of field temperature sensors and climate models, a ground-surface temperature method was used to estimate microclimate variability of minimum and maximum temperature. Temperature lapse rates were derived from field temperature sensors and distributed across the landscape capturing differences in solar radiation and cold air drainages modeled at a 30-m spatial resolution. Results: The surface temperature estimation method used for this analysis successfully estimated minimum surface temperatures on north-facing, south-facing, valley, and ridgeline topographic settings, and when compared to measured temperatures yielded an R2 of 0.88, 0.80, 0.88, and 0.80, respectively. Maximum surface temperatures generally had slightly more spatial variability than minimum surface temperatures, resulting in R2 values of 0.86, 0.77, 0.72, and 0.79 for north-facing, south-facing, valley, and ridgeline topographic settings. Quasi-Poisson regressions predicting recruitment of Quercus kelloggii (black oak) seedlings from temperature variables were significantly improved using these estimates of surface temperature compared to air temperature modeled at 2 m. Conclusion: Predicting minimum and maximum ground-surface temperatures using a downscaled climate model coupled with temperature lapse rates estimated from field measurements provides a method for modeling temperature effects on plant recruitment. Such methods could be applied to improve projections of species’ range shifts under climate change. Areas of complex topography can provide intricate microclimates that may allow species to redistribute locally as climate changes.

Variability in Temperature-Related Mortality Projections under Climate Change

PubMed Central

Benmarhnia, Tarik; Sottile, Marie-France; Plante, Céline; Brand, Allan; Casati, Barbara; Fournier, Michel

2014-01-01

Background: Most studies that have assessed impacts on mortality of future temperature increases have relied on a small number of simulations and have not addressed the variability and sources of uncertainty in their mortality projections. Objectives: We assessed the variability of temperature projections and dependent future mortality distributions, using a large panel of temperature simulations based on different climate models and emission scenarios. Methods: We used historical data from 1990 through 2007 for Montreal, Quebec, Canada, and Poisson regression models to estimate relative risks (RR) for daily nonaccidental mortality in association with three different daily temperature metrics (mean, minimum, and maximum temperature) during June through August. To estimate future numbers of deaths attributable to ambient temperatures and the uncertainty of the estimates, we used 32 different simulations of daily temperatures for June–August 2020–2037 derived from three global climate models (GCMs) and a Canadian regional climate model with three sets of RRs (one based on the observed historical data, and two on bootstrap samples that generated the 95% CI of the attributable number (AN) of deaths). We then used analysis of covariance to evaluate the influence of the simulation, the projected year, and the sets of RRs used to derive the attributable numbers of deaths. Results: We found that < 1% of the variability in the distributions of simulated temperature for June–August of 2020–2037 was explained by differences among the simulations. Estimated ANs for 2020–2037 ranged from 34 to 174 per summer (i.e., June–August). Most of the variability in mortality projections (38%) was related to the temperature–mortality RR used to estimate the ANs. Conclusions: The choice of the RR estimate for the association between temperature and mortality may be important to reduce uncertainty in mortality projections. Citation: Benmarhnia T, Sottile MF, Plante C, Brand A, Casati B, Fournier M, Smargiassi A. 2014. Variability in temperature-related mortality projections under climate change. Environ Health Perspect 122:1293–1298; http://dx.doi.org/10.1289/ehp.1306954 PMID:25036003

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

PubMed Central

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

2014-01-01

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

Impacts of temperature and its variability on mortality in New England

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

Climate Variability and Sugarcane Yield in Louisiana.

NASA Astrophysics Data System (ADS)

Greenland, David

2005-11-01

This paper seeks to understand the role that climate variability has on annual yield of sugarcane in Louisiana. Unique features of sugarcane growth in Louisiana and nonclimatic, yield-influencing factors make this goal an interesting and challenging one. Several methods of seeking and establishing the relations between yield and climate variables are employed. First, yield climate relations were investigated at a single research station where crop variety and growing conditions could be held constant and yield relations could be established between a predominant older crop variety and a newer one. Interviews with crop experts and a literature survey were used to identify potential climatic factors that control yield. A statistical analysis was performed using statewide yield data from the American Sugar Cane League from 1963 to 2002 and a climate database. Yield values for later years were adjusted downward to form an adjusted yield dataset. The climate database was principally constructed from daily and monthly values of maximum and minimum temperature and daily and monthly total precipitation for six cooperative weather-reporting stations representative of the area of sugarcane production. The influence of 74 different, though not independent, climate-related variables on sugarcane yield was investigated. The fact that a climate signal exists is demonstrated by comparing mean values of the climate variables corresponding to the upper and lower third of adjusted yield values. Most of these mean-value differences show an intuitively plausible difference between the high- and low-yield years. The difference between means of the climate variables for years corresponding to the upper and lower third of annual yield values for 13 of the variables is statistically significant at or above the 90% level. A correlation matrix was used to identify the variables that had the largest influence on annual yield. Four variables [called here critical climatic variables (CCV)], mean maximum August temperature, mean minimum February temperature, soil water surplus between April and September, and occurrence of autumn (fall) hurricanes, were built into a model to simulate adjusted yield values. The CCV model simulates the yield value with an rmse of 5.1 t ha-1. The mean of the adjusted yield data over the study period was 60.4 t ha-1, with values for the highest and lowest years being 73.1 and 50.6 t ha-1, respectively, and a standard deviation of 5.9 t ha-1. Presumably because of the almost constant high water table and soil water availability, higher precipitation totals, which are inversely related to radiation and temperature, tend to have a negative effect on the yields. Past trends in the values of critical climatic variables and general projections of future climate suggest that, with respect to the climatic environment and as long as land drainage is continued and maintained, future levels of sugarcane yield will rise in Louisiana.

Current Climate Variability & Change

NASA Astrophysics Data System (ADS)

Diem, J.; Criswell, B.; Elliott, W. C.

2013-12-01

Current Climate Variability & Change is the ninth among a suite of ten interconnected, sequential labs that address all 39 climate-literacy concepts in the U.S. Global Change Research Program's Climate Literacy: The Essential Principles of Climate Sciences. The labs are as follows: Solar Radiation & Seasons, Stratospheric Ozone, The Troposphere, The Carbon Cycle, Global Surface Temperature, Glacial-Interglacial Cycles, Temperature Changes over the Past Millennium, Climates & Ecosystems, Current Climate Variability & Change, and Future Climate Change. All are inquiry-based, on-line products designed in a way that enables students to construct their own knowledge of a topic. Questions representative of various levels of Webb's depth of knowledge are embedded in each lab. In addition to the embedded questions, each lab has three or four essential questions related to the driving questions for the lab suite. These essential questions are presented as statements at the beginning of the material to represent the lab objectives, and then are asked at the end as questions to function as a summative assessment. For example, the Current Climate Variability & Change is built around these essential questions: (1) What has happened to the global temperature at the Earth's surface, in the middle troposphere, and in the lower stratosphere over the past several decades?; (2) What is the most likely cause of the changes in global temperature over the past several decades and what evidence is there that this is the cause?; and (3) What have been some of the clearly defined effects of the change in global temperature on the atmosphere and other spheres of the Earth system? An introductory Prezi allows the instructor to assess students' prior knowledge in relation to these questions, while also providing 'hooks' to pique their interest related to the topic. The lab begins by presenting examples of and key differences between climate variability (e.g., Mt. Pinatubo eruption) and climate change. The next section guides students through the exploration of temporal changes in global temperature from the surface to the lower stratosphere. Students discover that there has been global warming over the past several decades, and the subsequent section allows them to consider solar radiation and greenhouse gases as possible causes of this warming. Students then zoom in on different latitudinal zones to examine changes in temperature for each zone and hypothesize about why one zone may have warmed more than others. The final section, prior to the answering of the essential questions, is an examination of the following effects of the current change in temperatures: loss of sea ice; rise of sea level; loss of permafrost loss; and moistening of the atmosphere. The lab addresses 14 climate-literacy concepts and all seven climate-literacy principles through data and images that are mainly NASA products. It focuses on the satellite era of climate data; therefore, 1979 is the typical starting year for most datasets used by students. Additionally, all time-series analysis end with the latest year with full-year data availability; thus, the climate variability and trends truly are 'current.'

On the origin of multi-decadal to centennial Greenland temperature anomalies over the past 800 yr

NASA Astrophysics Data System (ADS)

Kobashi, T.; Shindell, D. T.; Kodera, K.; Box, J. E.; Nakaegawa, T.; Kawamura, K.

2012-11-01

The surface temperature of the Greenland ice sheet is among the most important climate variables for assessing how climate change may impact human societies associated with accelerating sea level rise. However, the causes of multi-decadal-to-centennial temperature changes in Greenland are not well understood, largely owing to short observational records. To examine the causes of the Greenland temperature variability, we calculated the Greenland temperature anomalies (GTA(G-NH)) over the past 800 yr by subtracting the standardised NH temperature from the standardised Greenland temperature. It decomposes the Greenland temperature variation into background climate (NH); Polar amplification; and Regional variability (GTA(G-NH)). The Central Greenland polar amplification factor as expressed by the variance ratio = Greenland/NH is 2.6 over the past 161 yr, and 3.3-4.2 over the past 800 yr. The GTA explains 31-35% of the variation of Greenland temperature in the multi-decadal-to-centennial time scale over the past 800 yr. Another orthogonal component of the Greenland and NH temperatures, GTP(G+NH) (Greenland temperature plus = standardized Greenland temperature + standardized NH temperature) exhibited the multi-decadal variations that were likely induced by large volcanic eruptions, increasing greenhouse gasses, and internal variation of climate. We found that the GTA(G-NH) has been influenced by solar-induced changes in atmospheric circulation patterns such as those produced by North Atlantic Oscillation/Arctic Oscillation (NAO/AO). Climate modelling indicates that the anomaly is also likely linked to solar-paced changes in the Atlantic meridional overturning circulation (AMOC) and to associated changes in northward oceanic heat transport.

Impact of Subsurface Temperature Variability on Meteorological Variability: An AGCM Study

NASA Astrophysics Data System (ADS)

Mahanama, S. P.; Koster, R. D.; Liu, P.

2006-05-01

Anomalous atmospheric conditions can lead to surface temperature anomalies, which in turn can lead to temperature anomalies deep in the soil. The deep soil temperature (and the associated ground heat content) has significant memory -- the dissipation of a temperature anomaly may take weeks to months -- and thus deep soil temperature may contribute to the low frequency variability of energy and water variables elsewhere in the system. The memory may even provide some skill to subseasonal and seasonal forecasts. This study uses two long-term AGCM experiments to isolate the contribution of deep soil temperature variability to variability elsewhere in the climate system. The first experiment consists of a standard ensemble of AMIP-type simulations, simulations in which the deep soil temperature variable is allowed to interact with the rest of the system. In the second experiment, the coupling of the deep soil temperature to the rest of the climate system is disabled -- at each grid cell, the local climatological seasonal cycle of deep soil temperature (as determined from the first experiment) is prescribed. By comparing the variability of various atmospheric quantities as generated in the two experiments, we isolate the contribution of interactive deep soil temperature to that variability. The results show that interactive deep soil temperature contributes significantly to surface temperature variability. Interactive deep soil temperature, however, reduces the variability of the hydrological cycle (evaporation and precipitation), largely because it allows for a negative feedback between evaporation and temperature.

Climatically driven yield variability of major crops in Khakassia (South Siberia)

NASA Astrophysics Data System (ADS)

Babushkina, Elena A.; Belokopytova, Liliana V.; Zhirnova, Dina F.; Shah, Santosh K.; Kostyakova, Tatiana V.

2018-06-01

We investigated the variability of yield of the three main crop cultures in the Khakassia Republic: spring wheat, spring barley, and oats. In terms of yield values, variability characteristics, and climatic response, the agricultural territory of Khakassia can be divided into three zones: (1) the Northern Zone, where crops yield has a high positive response to the amount of precipitation, May-July, and a moderately negative one to the temperatures of the same period; (2) the Central Zone, where crops yield depends mainly on temperatures; and (3) the Southern Zone, where climate has the least expressed impact on yield. The dominant pattern in the crops yield is caused by water stress during periods of high temperatures and low moisture supply with heat stress as additional reason. Differences between zones are due to combinations of temperature latitudinal gradient, precipitation altitudinal gradient, and the presence of a well-developed hydrological network and the irrigational system as moisture sources in the Central Zone. More detailed analysis shows differences in the climatic sensitivity of crops during phases of their vegetative growth and grain development and, to a lesser extent, during harvesting period. Multifactor linear regression models were constructed to estimate climate- and autocorrelation-induced variability of the crops yield. These models allowed prediction of the possibility of yield decreasing by at least 2-11% in the next decade due to increasing of the regional summer temperatures.

Climatically driven yield variability of major crops in Khakassia (South Siberia)

NASA Astrophysics Data System (ADS)

Babushkina, Elena A.; Belokopytova, Liliana V.; Zhirnova, Dina F.; Shah, Santosh K.; Kostyakova, Tatiana V.

2017-12-01

We investigated the variability of yield of the three main crop cultures in the Khakassia Republic: spring wheat, spring barley, and oats. In terms of yield values, variability characteristics, and climatic response, the agricultural territory of Khakassia can be divided into three zones: (1) the Northern Zone, where crops yield has a high positive response to the amount of precipitation, May-July, and a moderately negative one to the temperatures of the same period; (2) the Central Zone, where crops yield depends mainly on temperatures; and (3) the Southern Zone, where climate has the least expressed impact on yield. The dominant pattern in the crops yield is caused by water stress during periods of high temperatures and low moisture supply with heat stress as additional reason. Differences between zones are due to combinations of temperature latitudinal gradient, precipitation altitudinal gradient, and the presence of a well-developed hydrological network and the irrigational system as moisture sources in the Central Zone. More detailed analysis shows differences in the climatic sensitivity of crops during phases of their vegetative growth and grain development and, to a lesser extent, during harvesting period. Multifactor linear regression models were constructed to estimate climate- and autocorrelation-induced variability of the crops yield. These models allowed prediction of the possibility of yield decreasing by at least 2-11% in the next decade due to increasing of the regional summer temperatures.

An assessment of precipitation and surface air temperature over China by regional climate models

NASA Astrophysics Data System (ADS)

Wang, Xueyuan; Tang, Jianping; Niu, Xiaorui; Wang, Shuyu

2016-12-01

An analysis of a 20-year summer time simulation of present-day climate (1989-2008) over China using four regional climate models coupled with different land surface models is carried out. The climatic means, interannual variability, linear trends, and extremes are examined, with focus on precipitation and near surface air temperature. The models are able to reproduce the basic features of the observed summer mean precipitation and temperature over China and the regional detail due to topographic forcing. Overall, the model performance is better for temperature than that of precipitation. The models reasonably grasp the major anomalies and standard deviations over China and the five subregions studied. The models generally reproduce the spatial pattern of high interannual variability over wet regions, and low variability over the dry regions. The models also capture well the variable temperature gradient increase to the north by latitude. Both the observed and simulated linear trend of precipitation shows a drying tendency over the Yangtze River Basin and wetting over South China. The models capture well the relatively small temperature trends in large areas of China. The models reasonably simulate the characteristics of extreme precipitation indices of heavy rain days and heavy precipitation fraction. Most of the models also performed well in capturing both the sign and magnitude of the daily maximum and minimum temperatures over China.

Understanding the science of climate change: Talking Points - Impacts to arid lands

Treesearch

Rachel Loehman

2010-01-01

Arid ecosystems are particularly sensitive to climate change and climate variability because organisms in these regions live near their physiological limits for water and temperature stress. Slight changes in temperature or precipitation regimes, or in magnitude and frequency of extreme climatic events, can significantly alter the composition, abundance, and...

Role of Internal Variability in Surface Temperature and Precipitation Change Uncertainties over India.

NASA Astrophysics Data System (ADS)

Achutarao, K. M.; Singh, R.

2017-12-01

There are various sources of uncertainty in model projections of future climate change. These include differences in the formulation of climate models, internal variability, and differences in scenarios. Internal variability in a climate system represents the unforced change due to the chaotic nature of the climate system and is considered irreducible (Deser et al., 2012). Internal variability becomes important at regional scales where it can dominate forced changes. Therefore it needs to be carefully assessed in future projections. In this study we segregate the role of internal variability in the future temperature and precipitation projections over the Indian region. We make use of the Coupled Model Inter-comparison Project - phase 5 (CMIP5; Taylor et al., 2012) database containing climate model simulations carried out by various modeling centers around the world. While the CMIP5 experimental protocol recommended producing numerous ensemble members, only a handful of the modeling groups provided multiple realizations. Having a small number of realizations is a limitation in producing a quantification of internal variability. We therefore exploit the Community Earth System Model Large Ensemble (CESM-LE; Kay et al., 2014) dataset which contains a 40 member ensemble of a single model- CESM1 (CAM5) to explore the role of internal variability in Future Projections. Surface air temperature and precipitation change projections over regional and sub-regional scale are analyzed under the IPCC emission scenario (RCP8.5) for different seasons and homogeneous climatic zones over India. We analyze the spread in projections due to internal variability in the CESM-LE and CMIP5 datasets over these regions.

Recent climate variability and its impacts on soybean yields in Southern Brazil

NASA Astrophysics Data System (ADS)

Ferreira, Danielle Barros; Rao, V. Brahmananda

2011-08-01

Recent climate variability in rainfall, temperatures (maximum and minimum), and the diurnal temperature range is studied with emphasis on its influence over soybean yields in southern Brazil, during 1969 to 2002. The results showed that the soybean ( Glycine max L. Merril) yields are more affected by changes in temperature during summer, while changes in rainfall are more important during the beginning of plantation and at its peak of development. Furthermore, soybean yields in Paraná are more sensitive to rainfall variations, while soybean yields in the Rio Grande do Sul are more sensitive to variations in temperature. Effects of interannual climatic variability on soybean yields are evaluated through three agro-meteorological models: additive Stewart, multiplicative Rao, and multiplicative Jensen. The Jensen model is able to reproduce the interannual behavior of soybean yield reasonably well.

Spatiotemporal Co-variability of Surface Climate for Renewable Energy across the Contiguous United States: Role of the North Atlantic Subtropical High

NASA Astrophysics Data System (ADS)

Doering, K.; Steinschneider, S.

2017-12-01

The variability of renewable energy supply and drivers of demand across space and time largely determines the energy balance within power systems with a high penetration of renewable technologies. This study examines the joint spatiotemporal variability of summertime climate linked to renewable energy production (precipitation, wind speeds, insolation) and energy demand (temperature) across the contiguous United States (CONUS) between 1948 and 2015. Canonical correlation analysis is used to identify the major modes of joint variability between summer wind speeds and precipitation and related patterns of insolation and temperature. Canonical variates are then related to circulation anomalies to identify common drivers of the joint modes of climate variability. Results show that the first two modes of joint variability between summer wind speeds and precipitation exhibit pan-US dipole patterns with centers of action located in the eastern and central CONUS. Temperature and insolation also exhibit related US-wide dipoles. The relationship between canonical variates and lower-tropospheric geopotential height indicates that these modes are related to variability in the North Atlantic subtropical high (NASH). This insight can inform optimal strategies for siting renewables in an interconnected electric grid, and has implications for the impacts of climate variability and change on renewable energy systems.

Notable shifting in the responses of vegetation activity to climate change in China

NASA Astrophysics Data System (ADS)

Chen, Aifang; He, Bin; Wang, Honglin; Huang, Ling; Zhu, Yunhua; Lv, Aifeng

The weakening relationship between inter-annual temperature variability and vegetation activity in the Northern Hemisphere over the last three decades has been reported by a recent study. However, how and to what extent vegetation activity responds to climate change in China is still unclear. We applied the Pearson correlation and partial correlation methods with a moving 15-y window to the GIMMS NDVI dataset from NOAA/AVHRR and observed climate data to examine the variation in the relationships between vegetation activity and climate variables. Results showed that there was an expanding negative response of vegetation growth to climate warming and a positive role of precipitation. The change patterns between NDVI and climate variables over vegetation types during the past three decades pointed an expending negative correlation between NDVI and temperature and a positive role of precipitation over most of the vegetation types (meadow, grassland, shrub, desert, cropland, and forest). Specifically, correlation between NDVI and temperature (PNDVI-T) have shifted from positive to negative in most of the station of temperature-limited areas with evergreen broadleaf forests, whereas precipitation-limited temperate grassland and desert were characterized by a positive PNDVI-P. This study contributes to ongoing investigations of the effects of climate change on vegetation activity. It is also of great importance for designing forest management strategies to cope with climate change.

A CLIMATOLOGY OF WATER BUDGET VARIABLE FOR THE NORTHEASTERN UNITED STATES

EPA Science Inventory

A Climatology of Water Budget Variables for the Northeast United States (Leathers and Robinson 1995). Climatic division precipitation and temperature data are used to calculate water budget variables based on the Thornthwaite/Mather climatic water budget methodology. Two water b...

Climate Impact of Solar Variability

NASA Technical Reports Server (NTRS)

Schatten, Kenneth H. (Editor); Arking, Albert (Editor)

1990-01-01

The conference on The Climate Impact of Solar Variability, was held at Goddard Space Flight Center from April 24 to 27, 1990. In recent years they developed a renewed interest in the potential effects of increasing greenhouse gases on climate. Carbon dioxide, methane, nitrous oxide, and the chlorofluorocarbons have been increasing at rates that could significantly change climate. There is considerable uncertainty over the magnitude of this anthropogenic change. The climate system is very complex, with feedback processes that are not fully understood. Moreover, there are two sources of natural climate variability (volcanic aerosols and solar variability) added to the anthropogenic changes which may confuse our interpretation of the observed temperature record. Thus, if we could understand the climatic impact of the natural variability, it would aid our interpretation and understanding of man-made climate changes.

External forcing as a metronome for Atlantic multidecadal variability

NASA Astrophysics Data System (ADS)

Otterå, Odd Helge; Bentsen, Mats; Drange, Helge; Suo, Lingling

2010-10-01

Instrumental records, proxy data and climate modelling show that multidecadal variability is a dominant feature of North Atlantic sea-surface temperature variations, with potential impacts on regional climate. To understand the observed variability and to gauge any potential for climate predictions it is essential to identify the physical mechanisms that lead to this variability, and to explore the spatial and temporal characteristics of multidecadal variability modes. Here we use a coupled ocean-atmosphere general circulation model to show that the phasing of the multidecadal fluctuations in the North Atlantic during the past 600 years is, to a large degree, governed by changes in the external solar and volcanic forcings. We find that volcanoes play a particularly important part in the phasing of the multidecadal variability through their direct influence on tropical sea-surface temperatures, on the leading mode of northern-hemisphere atmosphere circulation and on the Atlantic thermohaline circulation. We suggest that the implications of our findings for decadal climate prediction are twofold: because volcanic eruptions cannot be predicted a decade in advance, longer-term climate predictability may prove challenging, whereas the systematic post-eruption changes in ocean and atmosphere may hold promise for shorter-term climate prediction.

Pollen-based continental climate reconstructions at 6 and 21 ka: a global synthesis

USGS Publications Warehouse

Bartlein, P.J.; Harrison, S.P.; Brewer, Sandra; Connor, S.; Davis, B.A.S.; Gajewski, K.; Guiot, J.; Harrison-Prentice, T. I.; Henderson, A.; Peyron, O.; Prentice, I.C.; Scholze, M.; Seppa, H.; Shuman, B.; Sugita, S.; Thompson, R.S.; Viau, A.E.; Williams, J.; Wu, H.

2010-01-01

Subfossil pollen and plant macrofossil data derived from 14C-dated sediment profiles can provide quantitative information on glacial and interglacial climates. The data allow climate variables related to growing-season warmth, winter cold, and plant-available moisture to be reconstructed. Continental-scale reconstructions have been made for the mid-Holocene (MH, around 6 ka) and Last Glacial Maximum (LGM, around 21 ka), allowing comparison with palaeoclimate simulations currently being carried out as part of the fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change. The synthesis of the available MH and LGM climate reconstructions and their uncertainties, obtained using modern-analogue, regression and model-inversion techniques, is presented for four temperature variables and two moisture variables. Reconstructions of the same variables based on surface-pollen assemblages are shown to be accurate and unbiased. Reconstructed LGM and MH climate anomaly patterns are coherent, consistent between variables, and robust with respect to the choice of technique. They support a conceptual model of the controls of Late Quaternary climate change whereby the first-order effects of orbital variations and greenhouse forcing on the seasonal cycle of temperature are predictably modified by responses of the atmospheric circulation and surface energy balance.

Can temperature explain the latitudinal gradient of ulcerative colitis? Cohort of Norway

PubMed Central

2013-01-01

Background Incidence and prevalence of ulcerative colitis follow a north–south (latitudinal) gradient and increases northwards at the northern hemisphere or southwards at the southern hemisphere. The disease has increased during the last decades. The temporal trend has been explained by the hygiene hypothesis, but few parallel explanations exist for the spatial variability. Many factors are linked to latitude such as climate. Our purpose was to investigate the association between variables governing the climate and prospectively identified patients. Methods In this study, we used a subset of the population-based Cohort of Norway (n = 80412) where 370 prevalent cases of ulcerative colitis were identified through self-reported medication. The meteorological and climatic variables temperature, precipitation, and altitude were recorded from weather stations of the Norwegian Meteorological Institute. Summer temperature was used to capture environmental temperature. Results Summer temperature was significantly related to the prevalence of ulcerative colitis. For each one-degree increase in temperature the odds for ulcerative colitis decreased with about 9% (95% CI: 3%-15%). None of the other climatic factors were significantly associated to the risk of ulcerative colitis. Contextual variables did not change the association to the prevalence of ulcerative colitis. Conclusions The present results show that the prevalence of ulcerative colitis is associated to summer temperature. Our speculation is that summer temperature works as an instrumental variable for the effect of microbial species richness on the development of ulcerative colitis. Environmental temperature is one of the main forces governing microbial species richness and the microbial composition of the commensal gut flora is known to be an important part in the process leading to ulcerative colitis. PMID:23724802

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

PubMed

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

2018-01-01

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

A review of precipitation and temperature control on seedling emergence and establishment for ponderosa and lodgepole pine forest regeneration

USGS Publications Warehouse

Petrie, Matthew; Wildeman, A.M.; Bradford, John B.; Hubbard, R.M.; Lauenroth, W.K.

2016-01-01

The persistence of ponderosa pine and lodgepole pine forests in the 21st century depends to a large extent on how seedling emergence and establishment are influenced by driving climate and environmental variables, which largely govern forest regeneration. We surveyed the literature, and identified 96 publications that reported data on dependent variables of seedling emergence and/or establishment and one or more independent variables of air temperature, soil temperature, precipitation and moisture availability. Our review suggests that seedling emergence and establishment for both species is highest at intermediate temperatures (20 to 25 °C), and higher precipitation and higher moisture availability support a higher percentage of seedling emergence and establishment at daily, monthly and annual timescales. We found that ponderosa pine seedlings may be more sensitive to temperature fluctuations whereas lodgepole pine seedlings may be more sensitive to moisture fluctuations. In a changing climate, increasing temperatures and declining moisture availability may hinder forest persistence by limiting seedling processes. Yet, only 23 studies in our review investigated the effects of driving climate and environmental variables directly. Furthermore, 74 studies occurred in a laboratory or greenhouse, which do not often replicate the conditions experienced by tree seedlings in a field setting. It is therefore difficult to provide strong conclusions on how sensitive emergence and establishment in ponderosa and lodgepole pine are to these specific driving variables, or to investigate their potential aggregate effects. Thus, the effects of many driving variables on seedling processes remain largely inconclusive. Our review stresses the need for additional field and laboratory studies to better elucidate the effects of driving climate and environmental variables on seedling emergence and establishment for ponderosa and lodgepole pine.

Identification of weather variables sensitive to dysentery in disease-affected county of China.

PubMed

Liu, Jianing; Wu, Xiaoxu; Li, Chenlu; Xu, Bing; Hu, Luojia; Chen, Jin; Dai, Shuang

2017-01-01

Climate change mainly refers to long-term change in weather variables, and it has significant impact on sustainability and spread of infectious diseases. Among three leading infectious diseases in China, dysentery is exclusively sensitive to climate change. Previous researches on weather variables and dysentery mainly focus on determining correlation between dysentery incidence and weather variables. However, the contribution of each variable to dysentery incidence has been rarely clarified. Therefore, we chose a typical county in epidemic of dysentery as the study area. Based on data of dysentery incidence, weather variables (monthly mean temperature, precipitation, wind speed, relative humidity, absolute humidity, maximum temperature, and minimum temperature) and lagged analysis, we used principal component analysis (PCA) and classification and regression trees (CART) to examine the relationships between the incidence of dysentery and weather variables. Principal component analysis showed that temperature, precipitation, and humidity played a key role in determining transmission of dysentery. We further selected weather variables including minimum temperature, precipitation, and relative humidity based on results of PCA, and used CART to clarify contributions of these three weather variables to dysentery incidence. We found when minimum temperature was at a high level, the high incidence of dysentery occurred if relative humidity or precipitation was at a high level. We compared our results with other studies on dysentery incidence and meteorological factors in areas both in China and abroad, and good agreement has been achieved. Yet, some differences remain for three reasons: not identifying all key weather variables, climate condition difference caused by local factors, and human factors that also affect dysentery incidence. This study hopes to shed light on potential early warnings for dysentery transmission as climate change occurs, and provide a theoretical basis for the control and prevention of dysentery. Copyright © 2016 Elsevier B.V. All rights reserved.

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

PubMed

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

2017-05-25

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

Separating out the influence of climatic trend, fluctuations, and extreme events on crop yield: a case study in Hunan Province, China

NASA Astrophysics Data System (ADS)

Wang, Zhu; Shi, Peijun; Zhang, Zhao; Meng, Yongchang; Luan, Yibo; Wang, Jiwei

2017-09-01

Separating out the influence of climatic trend, fluctuations and extreme events on crop yield is of paramount importance to climate change adaptation, resilience, and mitigation. Previous studies lack systematic and explicit assessment of these three fundamental aspects of climate change on crop yield. This research attempts to separate out the impacts on rice yields of climatic trend (linear trend change related to mean value), fluctuations (variability surpassing the "fluctuation threshold" which defined as one standard deviation (1 SD) of the residual between the original data series and the linear trend value for each climatic variable), and extreme events (identified by absolute criterion for each kind of extreme events related to crop yield). The main idea of the research method was to construct climate scenarios combined with crop system simulation model. Comparable climate scenarios were designed to express the impact of each climate change component and, were input to the crop system model (CERES-Rice), which calculated the related simulated yield gap to quantify the percentage impacts of climatic trend, fluctuations, and extreme events. Six Agro-Meteorological Stations (AMS) in Hunan province were selected to study the quantitatively impact of climatic trend, fluctuations and extreme events involving climatic variables (air temperature, precipitation, and sunshine duration) on early rice yield during 1981-2012. The results showed that extreme events were found to have the greatest impact on early rice yield (-2.59 to -15.89%). Followed by climatic fluctuations with a range of -2.60 to -4.46%, and then the climatic trend (4.91-2.12%). Furthermore, the influence of climatic trend on early rice yield presented "trade-offs" among various climate variables and AMS. Climatic trend and extreme events associated with air temperature showed larger effects on early rice yield than other climatic variables, particularly for high-temperature events (-2.11 to -12.99%). Finally, the methodology use to separate out the influences of the climatic trend, fluctuations, and extreme events on crop yield was proved to be feasible and robust. Designing different climate scenarios and feeding them into a crop system model is a potential way to evaluate the quantitative impact of each climate variable.

Climate change but not unemployment explains the changing suicidality in Thessaloniki Greece (2000-2012).

PubMed

Fountoulakis, Konstantinos N; Savopoulos, Christos; Zannis, Prodromos; Apostolopoulou, Martha; Fountoukidis, Ilias; Kakaletsis, Nikolaos; Kanellos, Ilias; Dimellis, Dimos; Hyphantis, Thomas; Tsikerdekis, Athanasios; Pompili, Maurizio; Hatzitolios, Apostolos I

2016-03-15

Recently there was a debate concerning the etiology behind attempts and completed suicides. The aim of the current study was to search for possible correlations between the rates of attempted and completed suicide and climate variables and regional unemployment per year in the county of Thessaloniki, Macedonia, northern Greece, for the years 2000-12. The regional rates of suicide and attempted suicide as well as regional unemployment were available from previous publications of the authors. The climate variables were calculated from the daily E-OBS gridded dataset which is based on observational data Only the male suicide rates correlate significantly with high mean annual temperature but not with unemployment. The multiple linear regression analysis results suggest that temperature is the only variable that determines male suicides and explains 51% of their variance. Unemployment fails to contribute significantly to the model. There seems to be a seasonal distribution for attempts with mean rates being higher for the period from May to October and the rates clearly correlate with temperature. The highest mean rates were observed during May and August and the lowest during December and February. Multiple linear regression analysis suggests that temperature also determines the female attempts rate although the explained variable is significant but very low (3-5%) Climate variables and specifically high temperature correlate both with suicide and attempted suicide rates but with a different way between males and females. The climate effect was stronger than the effect of unemployment. Copyright © 2016 Elsevier B.V. All rights reserved.

Long-term climate patterns in Alaskan surface temperature and precipitation and their biological consequences

USGS Publications Warehouse

Simpson, James J.; Hufford, Gary L.; Fleming, Michael D.; Berg, Jared S.; Ashton, J.B.

2002-01-01

Mean monthly climate maps of Alaskan surface temperature and precipitation produced by the parameter-elevation regression on independent slopes model (PRISM) were analyzed. Alaska is divided into interior and coastal zones with consistent but different climatic variability separated by a transition region; it has maximum interannual variability but low long-term mean variability. Pacific decadal oscillation (PDO)- and El Nino Southern Oscillation (ENSO)-type events influence Alaska surface temperatures weakly (1-2/spl deg/C) statewide. PDO has a stronger influence than ENSO on precipitation but its influence is largely localized to coastal central Alaska. The strongest influence of Arctic oscillation (AO) occurs in northern and interior Alaskan precipitation. Four major ecosystems are defined. A major eco-transition zone occurs between the interior boreal forest and the coastal rainforest. Variability in insolation, surface temperature, precipitation, continentality, and seasonal changes in storm track direction explain the mapped ecosystems. Lack of westward expansion of the interior boreal forest into the western shrub tundra is influenced by the coastal marine boundary layer (enhanced cloud cover, reduced insolation, cooler surface and soil temperatures).

Spatiotemporal variability and predictability of Normalized Difference Vegetation Index (NDVI) in Alberta, Canada.

PubMed

Jiang, Rengui; Xie, Jiancang; He, Hailong; Kuo, Chun-Chao; Zhu, Jiwei; Yang, Mingxiang

2016-09-01

As one of the most popular vegetation indices to monitor terrestrial vegetation productivity, Normalized Difference Vegetation Index (NDVI) has been widely used to study the plant growth and vegetation productivity around the world, especially the dynamic response of vegetation to climate change in terms of precipitation and temperature. Alberta is the most important agricultural and forestry province and with the best climatic observation systems in Canada. However, few studies pertaining to climate change and vegetation productivity are found. The objectives of this paper therefore were to better understand impacts of climate change on vegetation productivity in Alberta using the NDVI and provide reference for policy makers and stakeholders. We investigated the following: (1) the variations of Alberta's smoothed NDVI (sNDVI, eliminated noise compared to NDVI) and two climatic variables (precipitation and temperature) using non-parametric Mann-Kendall monotonic test and Thiel-Sen's slope; (2) the relationships between sNDVI and climatic variables, and the potential predictability of sNDVI using climatic variables as predictors based on two predicted models; and (3) the use of a linear regression model and an artificial neural network calibrated by the genetic algorithm (ANN-GA) to estimate Alberta's sNDVI using precipitation and temperature as predictors. The results showed that (1) the monthly sNDVI has increased during the past 30 years and a lengthened growing season was detected; (2) vegetation productivity in northern Alberta was mainly temperature driven and the vegetation in southern Alberta was predominantly precipitation driven for the period of 1982-2011; and (3) better performances of the sNDVI-climate relationships were obtained by nonlinear model (ANN-GA) than using linear (regression) model. Similar results detected in both monthly and summer sNDVI prediction using climatic variables as predictors revealed the applicability of two models for different period of year ecologists might focus on.

Variation in the sensitivity of organismal body temperature to climate change over local and geographic scales.

PubMed

Gilman, Sarah E; Wethey, David S; Helmuth, Brian

2006-06-20

Global climate change is expected to have broad ecological consequences for species and communities. Attempts to forecast these consequences usually assume that changes in air or water temperature will translate into equivalent changes in a species' organismal body temperature. This simple change is unlikely because an organism's body temperature is determined by a complex series of interactions between the organism and its environment. Using a biophysical model, validated with 5 years of field observations, we examined the relationship between environmental temperature change and body temperature of the intertidal mussel Mytilus californianus over 1,600 km of its geographic distribution. We found that at all locations examined simulated changes in air or water temperature always produced less than equivalent changes in the daily maximum mussel body temperature. Moreover, the magnitude of body temperature change was highly variable, both within and among locations. A simulated 1 degrees C increase in air or water temperature raised the maximum monthly average of daily body temperature maxima by 0.07-0.92 degrees C, depending on the geographic location, vertical position, and temperature variable. We combined these sensitivities with predicted climate change for 2100 and calculated increases in monthly average maximum body temperature of 0.97-4.12 degrees C, depending on location and climate change scenario. Thus geographic variation in body temperature sensitivity can modulate species' experiences of climate change and must be considered when predicting the biological consequences of climate change.

Country-Specific Effects of Climate Variability on Human Migration.

PubMed

Gray, Clark; Wise, Erika

2016-04-01

Involuntary human migration is among the social outcomes of greatest concern in the current era of global climate change. Responding to this concern, a growing number of studies have investigated the consequences of short to medium-term climate variability for human migration using demographic and econometric approaches. These studies have provided important insights, but at the same time have been significantly limited by lack of expertise in the use of climate data, access to cross-national data on migration, and attention to model specification. To address these limitations, we link data on internal and international migration over a 6-year period from 9,812 origin households in Kenya, Uganda, Nigeria, Burkina Faso and Senegal to high-resolution gridded climate data from both station and satellite sources. Analyses of these data using several plausible specifications reveal that climate variability has country-specific effects on migration: Migration tends to increase with temperature anomalies in Uganda, tends to decrease with temperature anomalies in Kenya and Burkina Faso, and shows no consistent relationship with temperature in Nigeria and Senegal. Consistent with previous studies, precipitation shows weak and inconsistent relationships with migration across countries. These results challenge generalizing narratives that foresee a consistent migratory response to climate change across the globe.

Trends in seasonal warm anomalies across the contiguous United States: Contributions from natural climate variability

Treesearch

Lejiang Yu; Shiyuan Zhong; Warren E. Heilman; Xindi Bian

2018-01-01

Many studies have shown the importance of anthropogenic greenhouse gas emissions in contributing to observed upward trends in the occurrences of temperature extremes over the U.S. However, few studies have investigated the contributions of internal variability in the climate system to these observed trends. Here we use daily maximum temperature time series from the...

Growth responses of Scots pine to climatic factors on reclaimed oil shale mined land.

PubMed

Metslaid, Sandra; Stanturf, John A; Hordo, Maris; Korjus, Henn; Laarmann, Diana; Kiviste, Andres

2016-07-01

Afforestation on reclaimed mining areas has high ecological and economic importance. However, ecosystems established on post-mining substrate can become vulnerable due to climate variability. We used tree-ring data and dendrochronological techniques to study the relationship between climate variables and annual growth of Scots pine (Pinus sylvestris L.) growing on reclaimed open cast oil shale mining areas in Northeast Estonia. Chronologies for trees of different age classes (50, 40, 30) were developed. Pearson's correlation analysis between radial growth indices and monthly climate variables revealed that precipitation in June-July and higher mean temperatures in spring season enhanced radial growth of pine plantations, while higher than average temperatures in summer months inhibited wood production. Sensitivity of radial increment to climatic factors on post-mining soils was not homogenous among the studied populations. Older trees growing on more developed soils were more sensitive to precipitation deficit in summer, while growth indices of two other stand groups (young and middle-aged) were highly correlated to temperature. High mean temperatures in August were negatively related to annual wood production in all trees, while trees in the youngest stands benefited from warmer temperatures in January. As a response to thinning, mean annual basal area increment increased up to 50 %. By managing tree competition in the closed-canopy stands, through the thinning activities, tree sensitivity and response to climate could be manipulated.

A global perspective on Glacial- to Interglacial variability change

NASA Astrophysics Data System (ADS)

Rehfeld, Kira; Münch, Thomas; Ho, Sze Ling; Laepple, Thomas

2017-04-01

Changes in climate variability are more important for society than changes in the mean state alone. While we will be facing a large-scale shift of the mean climate in the future, its implications for climate variability are not well constrained. Here we quantify changes in temperature variability as climate shifted from the Last Glacial cold to the Holocene warm period. Greenland ice core oxygen isotope records provide evidence of this climatic shift, and are used as reference datasets in many palaeoclimate studies worldwide. A striking feature in these records is pronounced millennial variability in the Glacial, and a distinct reduction in variance in the Holocene. We present quantitative estimates of the change in variability on 500- to 1500-year timescales based on a global compilation of high-resolution proxy records for temperature which span both the Glacial and the Holocene. The estimates are derived based on power spectral analysis, and corrected using estimates of the proxy signal-to-noise ratios. We show that, on a global scale, variability at the Glacial maximum is five times higher than during the Holocene, with a possible range of 3-10 times. The spatial pattern of the variability change is latitude-dependent. While the tropics show no changes in variability, mid-latitude changes are higher. A slight overall reduction in variability in the centennial to millennial range is found in Antarctica. The variability decrease in the Greenland ice core oxygen isotope records is larger than in any other proxy dataset. These results therefore contradict the view of a globally quiescent Holocene following the instable Glacial, and imply that, in terms of centennial to millennial temperature variability, the two states may be more similar than previously thought.

Climate Variability and Yields of Major Staple Food Crops in Northern Ghana

NASA Astrophysics Data System (ADS)

Amikuzuno, J.

2012-12-01

Climate variability, the short-term fluctuations in average weather conditions, and agriculture affect each other. Climate variability affects the agroecological and growing conditions of crops and livestock, and is recently believed to be the greatest impediment to the realisation of the first Millennium Development Goal of reducing poverty and food insecurity in arid and semi-arid regions of developing countries. 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 provide some insight into the long run relationship between inter-annual variations in temperature and rainfall, and annual yields of the most important staple food crops in Northern Ghana. Applying pooled panel data of rainfall, temperature and yields of the selected crops from 1976 to 2010 to cointegration and Granger causality models, there is cogent evidence of cointegration between seasonal, total rainfall and crop yields; and causality from rainfall to crop yields in the Sudano-Guinea Savannah and Guinea Savannah zones of Northern Ghana. This suggests that inter-annual yields of the crops have been influenced by the total mounts of rainfall in the planting season. Temperature variability over the study period is however stationary, and is suspected to have minimal effect if any on crop yields. Overall, the results confirm the appropriateness of our attempt in modelling long-term relationships between the climate and crop yield variables.

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

Treesearch

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

2013-01-01

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

Impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling

NASA Astrophysics Data System (ADS)

Chen, Jie; Li, Chao; Brissette, François P.; Chen, Hua; Wang, Mingna; Essou, Gilles R. C.

2018-05-01

Bias correction is usually implemented prior to using climate model outputs for impact studies. However, bias correction methods that are commonly used treat climate variables independently and often ignore inter-variable dependencies. The effects of ignoring such dependencies on impact studies need to be investigated. This study aims to assess the impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling. To this end, a joint bias correction (JBC) method which corrects the joint distribution of two variables as a whole is compared with an independent bias correction (IBC) method; this is considered in terms of correcting simulations of precipitation and temperature from 26 climate models for hydrological modeling over 12 watersheds located in various climate regimes. The results show that the simulated precipitation and temperature are considerably biased not only in the individual distributions, but also in their correlations, which in turn result in biased hydrological simulations. In addition to reducing the biases of the individual characteristics of precipitation and temperature, the JBC method can also reduce the bias in precipitation-temperature (P-T) correlations. In terms of hydrological modeling, the JBC method performs significantly better than the IBC method for 11 out of the 12 watersheds over the calibration period. For the validation period, the advantages of the JBC method are greatly reduced as the performance becomes dependent on the watershed, GCM and hydrological metric considered. For arid/tropical and snowfall-rainfall-mixed watersheds, JBC performs better than IBC. For snowfall- or rainfall-dominated watersheds, however, the two methods behave similarly, with IBC performing somewhat better than JBC. Overall, the results emphasize the advantages of correcting the P-T correlation when using climate model-simulated precipitation and temperature to assess the impact of climate change on watershed hydrology. However, a thorough validation and a comparison with other methods are recommended before using the JBC method, since it may perform worse than the IBC method for some cases due to bias nonstationarity of climate model outputs.

The absence of an Atlantic imprint on the multidecadal variability of wintertime European temperature.

PubMed

Yamamoto, Ayako; Palter, Jaime B

2016-03-15

Northern Hemisphere climate responds sensitively to multidecadal variability in North Atlantic sea surface temperature (SST). It is therefore surprising that an imprint of such variability is conspicuously absent in wintertime western European temperature, despite that Europe's climate is strongly influenced by its neighbouring ocean, where multidecadal variability in basin-average SST persists in all seasons. Here we trace the cause of this missing imprint to a dynamic anomaly of the atmospheric circulation that masks its thermodynamic response to SST anomalies. Specifically, differences in the pathways Lagrangian particles take to Europe during anomalous SST winters suppress the expected fluctuations in air-sea heat exchange accumulated along those trajectories. Because decadal variability in North Atlantic-average SST may be driven partly by the Atlantic Meridional Overturning Circulation (AMOC), the atmosphere's dynamical adjustment to this mode of variability may have important implications for the European wintertime temperature response to a projected twenty-first century AMOC decline.

The paradox of cooling streams in a warming world: Regional climate trends do not parallel variable local trends in stream temperature in the Pacific continental United States

USGS Publications Warehouse

Arismendi, Ivan; Johnson, Sherri; Dunham, Jason B.; Haggerty, Roy; Hockman-Wert, David

2012-01-01

Temperature is a fundamentally important driver of ecosystem processes in streams. Recent warming of terrestrial climates around the globe has motivated concern about consequent increases in stream temperature. More specifically, observed trends of increasing air temperature and declining stream flow are widely believed to result in corresponding increases in stream temperature. Here, we examined the evidence for this using long-term stream temperature data from minimally and highly human-impacted sites located across the Pacific continental United States. Based on hypothesized climate impacts, we predicted that we should find warming trends in the maximum, mean and minimum temperatures, as well as increasing variability over time. These predictions were not fully realized. Warming trends were most prevalent in a small subset of locations with longer time series beginning in the 1950s. More recent series of observations (1987-2009) exhibited fewer warming trends and more cooling trends in both minimally and highly human-influenced systems. Trends in variability were much less evident, regardless of the length of time series. Based on these findings, we conclude that our perspective of climate impacts on stream temperatures is clouded considerably by a lack of long-termdata on minimally impacted streams, and biased spatio-temporal representation of existing time series. Overall our results highlight the need to develop more mechanistic, process-based understanding of linkages between climate change, other human impacts and stream temperature, and to deploy sensor networks that will provide better information on trends in stream temperatures in the future.

Projections of Future Summer Weather in Seoul and Their Impacts on Urban Agriculture

NASA Astrophysics Data System (ADS)

Kim, S. O.; Kim, J. H.; Yun, J. I.

2015-12-01

Climate departure from the past variability was projected to start in 2042 for Seoul. In order to understand the implication of climate departure in Seoul for urban agriculture, we evaluated the daily temperature for the June-September period from 2041 to 2070, which were projected by the RCP8.5 climate scenario. These data were analyzed with respect to climate extremes and their effects on growth of hot pepper (Capsicum annuum), one of the major crops in urban farming. The mean daily maximum and minimum temperatures in 2041-2070 approached to the 90th percentile in the past 30 years (1951- 1980). However, the frequency of extreme events such as heat waves and tropical nights appeared to exceed the past variability. While the departure of mean temperature might begin in or after 2040, the climate departure in the sense of extreme weather events seems already in progress. When the climate scenario data were applied to the growth and development of hot pepper, the departures of both planting date and harvest date are expected to follow those of temperature. However, the maximum duration for hot pepper cultivation, which is the number of days between the first planting and the last harvest, seems to have already deviated from the past variability.

Global land carbon sink response to temperature and precipitation varies with ENSO phase

DOE PAGES

Fang, Yuanyuan; Michalak, Anna M.; Schwalm, Christopher R.; ...

2017-06-01

Climate variability associated with the El Niño-Southern Oscillation (ENSO) and its consequent impacts on land carbon sink interannual variability have been used as a basis for investigating carbon cycle responses to climate variability more broadly, and to inform the sensitivity of the tropical carbon budget to climate change. Past studies have presented opposing views about whether temperature or precipitation is the primary factor driving the response of the land carbon sink to ENSO. We show that the dominant driver varies with ENSO phase. And whereas tropical temperature explains sink dynamics following El Niño conditions (r TG,P = 0.59, p

Global land carbon sink response to temperature and precipitation varies with ENSO phase

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

Fang, Yuanyuan; Michalak, Anna M.; Schwalm, Christopher R.

Climate variability associated with the El Niño-Southern Oscillation (ENSO) and its consequent impacts on land carbon sink interannual variability have been used as a basis for investigating carbon cycle responses to climate variability more broadly, and to inform the sensitivity of the tropical carbon budget to climate change. Past studies have presented opposing views about whether temperature or precipitation is the primary factor driving the response of the land carbon sink to ENSO. Here, we show that the dominant driver varies with ENSO phase. Whereas tropical temperature explains sink dynamics following El Niño conditions (r TG,P=0.59, p<0.01), the post Lamore » Niña sink is driven largely by tropical precipitation (r PG,T=-0.46, p=0.04). This finding points to an ENSO-phase-dependent interplay between water availability and temperature in controlling the carbon uptake response to climate variations in tropical ecosystems. We further find that none of a suite of ten contemporary terrestrial biosphere models captures these ENSO-phase-dependent responses, highlighting a key uncertainty in modeling climate impacts on the future of the global land carbon sink.« less

Global land carbon sink response to temperature and precipitation varies with ENSO phase

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

Fang, Yuanyuan; Michalak, Anna M.; Schwalm, Christopher R.

Climate variability associated with the El Niño-Southern Oscillation (ENSO) and its consequent impacts on land carbon sink interannual variability have been used as a basis for investigating carbon cycle responses to climate variability more broadly, and to inform the sensitivity of the tropical carbon budget to climate change. Past studies have presented opposing views about whether temperature or precipitation is the primary factor driving the response of the land carbon sink to ENSO. We show that the dominant driver varies with ENSO phase. And whereas tropical temperature explains sink dynamics following El Niño conditions (r TG,P = 0.59, p

Timing of climate variability and grassland productivity

PubMed Central

Craine, Joseph M.; Nippert, Jesse B.; Elmore, Andrew J.; Skibbe, Adam M.; Hutchinson, Stacy L.; Brunsell, Nathaniel A.

2012-01-01

Future climates are forecast to include greater precipitation variability and more frequent heat waves, but the degree to which the timing of climate variability impacts ecosystems is uncertain. In a temperate, humid grassland, we examined the seasonal impacts of climate variability on 27 y of grass productivity. Drought and high-intensity precipitation reduced grass productivity only during a 110-d period, whereas high temperatures reduced productivity only during 25 d in July. The effects of drought and heat waves declined over the season and had no detectable impact on grass productivity in August. If these patterns are general across ecosystems, predictions of ecosystem response to climate change will have to account not only for the magnitude of climate variability but also for its timing. PMID:22331914

Medieval Warm Period, Little Ice Age and 20th century temperature variability from Chesapeake Bay

USGS Publications Warehouse

Cronin, T. M.; Dwyer, G.S.; Kamiya, T.; Schwede, S.; Willard, D.A.

2003-01-01

We present paleoclimate evidence for rapid (< 100 years) shifts of ~2-4oC in Chesapeake Bay (CB) temperature ~2100, 1600, 950, 650, 400 and 150 years before present (years BP) reconstructed from magnesium/calcium (Mg/Ca) paleothermometry. These include large temperature excursions during the Little Ice Age (~1400-1900 AD) and the Medieval Warm Period (~800-1300 AD) possibly related to changes in the strength of North Atlantic thermohaline circulation (THC). Evidence is presented for a long period of sustained regional and North Atlantic-wide warmth with low-amplitude temperature variability between ~450 and 1000 AD. In addition to centennial-scale temperature shifts, the existence of numerous temperature maxima between 2200 and 250 years BP (average ~70 years) suggests that multi-decadal processes typical of the North Atlantic Oscillation (NAO) are an inherent feature of late Holocene climate. However, late 19th and 20th century temperature extremes in Chesapeake Bay associated with NAO climate variability exceeded those of the prior 2000 years, including the interval 450-1000 AD, by 2-3oC, suggesting anomalous recent behavior of the climate system.

The rise of the mediocre forest: why chronically stressed trees may better survive extreme episodic climate variability

Treesearch

Steven G. McNulty; Johnny L. Boggs; Ge Sun

2014-01-01

Anthropogenic climate change is a relatively new phenomenon, largely occurring over the past 150 years, and much of the discussion on climate change impacts to forests has focused on long-term shifts in temperature and precipitation. However, individual trees respond to the much shorter impacts of climate variability. Historically, fast growing, fully canopied, non-...

Climatic influences on fire regimes in montane forests of the southern Cascades, California, USA

Treesearch

A. H. Taylor; V. Trouet; C. N. Skinner

2008-01-01

he relationship between climate variability and fire extent was examined in montane and upper montane forests in the southern Cascades. Fire occurrence and extent were reconstructed for seven sites and related to measures of reconstructed climate for the period 1700 to 1900. The climate variables included the Palmer Drought Severity Index (PDSI), summer temperature (...

Central Tropical Pacific Variability And ENSO Response To Changing Climate Boundary Conditions: Evidence From Individual Line Island Foraminifera

NASA Astrophysics Data System (ADS)

Rustic, G. T.; Polissar, P. J.; Ravelo, A. C.; White, S. M.

2017-12-01

The El Niño Southern Oscillation (ENSO) plays a dominant role in Earth's climate variability. Paleoceanographic evidence suggests that ENSO has changed in the past, and these changes have been linked to large-scale climatic shifts. While a close relationship between ENSO evolution and climate boundary conditions has been predicted, testing these predictions remains challenging. These climate boundary conditions, including insolation, the mean surface temperature gradient of the tropical Pacific, global ice volume, and tropical thermocline depth, often co-vary and may work together to suppress or enhance the ocean-atmosphere feedbacks that drive ENSO variability. Furthermore, suitable paleo-archives spanning multiple climate states are sparse. We have aimed to test ENSO response to changing climate boundary conditions by generating new reconstructions of mixed-layer variability from sedimentary archives spanning the last three glacial-interglacial cycles from the Central Tropical Pacific Line Islands, where El Niño is strongly expressed. We analyzed Mg/Ca ratios from individual foraminifera to reconstruct mixed-layer variability at discrete time intervals representing combinations of climatic boundary conditions from the middle Holocene to Marine Isotope Stage (MIS) 8. We observe changes in the mixed-layer temperature variability during MIS 5 and during the previous interglacial (MIS 7) showing significant reductions in ENSO amplitude. Differences in variability during glacial and interglacial intervals are also observed. Additionally, we reconstructed mixed-layer and thermocline conditions using multi-species Mg/Ca and stable isotope measurements to more fully characterize the state of the Central Tropical Pacific during these intervals. These reconstructions provide us with a unique view of Central Tropical Pacific variability and water-column structure at discrete intervals under varying boundary climate conditions with which to assess factors that shape ENSO variability.

Impacts of Climate Trends and Variability on Livestock Production in Brazil

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Impact of Climate Change on Food Security in Kenya

NASA Astrophysics Data System (ADS)

Yator, J. J.

2016-12-01

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

A model for evaluating stream temperature response to climate change scenarios in Wisconsin

USGS Publications Warehouse

Westenbroek, Stephen M.; Stewart, Jana S.; Buchwald, Cheryl A.; Mitro, Matthew G.; Lyons, John D.; Greb, Steven

2010-01-01

Global climate change is expected to alter temperature and flow regimes for streams in Wisconsin over the coming decades. Stream temperature will be influenced not only by the predicted increases in average air temperature, but also by changes in baseflow due to changes in precipitation patterns and amounts. In order to evaluate future stream temperature and flow regimes in Wisconsin, we have integrated two existing models in order to generate a water temperature time series at a regional scale for thousands of stream reaches where site-specific temperature observations do not exist. The approach uses the US Geological Survey (USGS) Soil-Water-Balance (SWB) model, along with a recalibrated version of an existing artificial neural network (ANN) stream temperature model. The ANN model simulates stream temperatures on the basis of landscape variables such as land use and soil type, and also includes climate variables such as air temperature and precipitation amounts. The existing ANN model includes a landscape variable called DARCY designed to reflect the potential for groundwater recharge in the contributing area for a stream segment. SWB tracks soil-moisture and potential recharge at a daily time step, providing a way to link changing climate patterns and precipitation amounts over time to baseflow volumes, and presumably to stream temperatures. The recalibrated ANN incorporates SWB-derived estimates of potential recharge to supplement the static estimates of groundwater flow potential derived from a topographically based model (DARCY). SWB and the recalibrated ANN will be supplied with climate drivers from a suite of general circulation models and emissions scenarios, enabling resource managers to evaluate possible changes in stream temperature regimes for Wisconsin.

Multiproxy evidence of Holocene climate variability from estuarine sediments, eastern North America

USGS Publications Warehouse

Cronin, T. M.; Thunell, R.; Dwyer, G.S.; Saenger, C.; Mann, M.E.; Vann, C.; Seal, R.R.

2005-01-01

We reconstructed paleoclimate patterns from oxygen and carbon isotope records from the fossil estuarine benthic foraminifera Elphidium and Mg/ Ca ratios from the ostracode Loxoconcha from sediment cores from Chesapeake Bay to examine the Holocene evolution of North Atlantic Oscillation (NAO)-type climate variability. Precipitation-driven river discharge and regional temperature variability are the primary influences on Chesapeake Bay salinity and water temperature, respectively. We first calibrated modern ??18 Owater to salinity and applied this relationship to calculate trends in paleosalinity from the ??18 Oforam, correcting for changes in water temperature estimated from ostracode Mg /Ca ratios. The results indicate a much drier early Holocene in which mean paleosalinity was ???28 ppt in the northern bay, falling ???25% to ???20 ppt during the late Holocene. Early Holocene Mg/Ca-derived temperatures varied in a relatively narrow range of 13?? to 16??C with a mean temperature of 14.2??C and excursions above 16??C; the late Holocene was on average cooler (mean temperature of 12.8??C). In addition to the large contrast between early and late Holocene regional climate conditions, multidecadal (20-40 years) salinity and temperature variability is an inherent part of the region's climate during both the early and late Holocene, including the Medieval Warm Period and Little Ice Age. These patterns are similar to those observed during the twentieth century caused by NAO-related processes. Comparison of the midlatitude Chesapeake Bay salinity record with tropical climate records of Intertropical Convergence Zone fluctuations inferred from the Cariaco Basin titanium record suggests an anticorrelation between precipitation in the two regions at both millennial and centennial timescales. Copyright 2005 by the American Geophysical Union.

Temperature and rainfall strongly drive temporal growth variation in Asian tropical forest trees.

PubMed

Vlam, Mart; Baker, Patrick J; Bunyavejchewin, Sarayudh; Zuidema, Pieter A

2014-04-01

Climate change effects on growth rates of tropical trees may lead to alterations in carbon cycling of carbon-rich tropical forests. However, climate sensitivity of broad-leaved lowland tropical trees is poorly understood. Dendrochronology (tree-ring analysis) provides a powerful tool to study the relationship between tropical tree growth and annual climate variability. We aimed to establish climate-growth relationships for five annual-ring forming tree species, using ring-width data from 459 canopy and understory trees from a seasonal tropical forest in western Thailand. Based on 183/459 trees, chronologies with total lengths between 29 and 62 years were produced for four out of five species. Bootstrapped correlation analysis revealed that climate-growth responses were similar among these four species. Growth was significantly negatively correlated with current-year maximum and minimum temperatures, and positively correlated with dry-season precipitation levels. Negative correlations between growth and temperature may be attributed to a positive relationship between temperature and autotrophic respiration rates. The positive relationship between growth and dry-season precipitation levels likely reflects the strong water demand during leaf flush. Mixed-effect models yielded results that were consistent across species: a negative effect of current wet-season maximum temperatures on growth, but also additive positive effects of, for example, prior dry-season maximum temperatures. Our analyses showed that annual growth variability in tropical trees is determined by a combination of both temperature and precipitation variability. With rising temperature, the predominantly negative relationship between temperature and growth may imply decreasing growth rates of tropical trees as a result of global warming.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Sensitivity of the reference evapotranspiration to key climatic variables during the growing season in the Ejina oasis northwest China.

PubMed

Hou, Lan-Gong; Zou, Song-Bing; Xiao, Hong-Lang; Yang, Yong-Gang

2013-01-01

The standardized FAO56 Penman-Monteith model, which has been the most reasonable method in both humid and arid climatic conditions, provides reference evapotranspiration (ETo) estimates for planning and efficient use of agricultural water resources. And sensitivity analysis is important in understanding the relative importance of climatic variables to the variation of reference evapotranspiration. In this study, a non-dimensional relative sensitivity coefficient was employed to predict responses of ETo to perturbations of four climatic variables in the Ejina oasis northwest China. A 20-year historical dataset of daily air temperature, wind speed, relative humidity and daily sunshine duration in the Ejina oasis was used in the analysis. Results have shown that daily sensitivity coefficients exhibited large fluctuations during the growing season, and shortwave radiation was the most sensitive variable in general for the Ejina oasis, followed by air temperature, wind speed and relative humidity. According to this study, the response of ETo can be preferably predicted under perturbation of air temperature, wind speed, relative humidity and shortwave radiation by their sensitivity coefficients.

MISST: The Multi-Sensor Improved Sea Surface Temperature Project

DTIC Science & Technology

2009-06-01

climate change studies, fisheries management, and a wide range of other applications. Measurements are taken by several satellites carrying infrared and...TEMPERATURE PROJECT ABSTRACT. Sea surface temperature (SST) measurements are vital to global weather prediction, climate change studies, fisheries management...important variables related to the global ocean-atmosphere system. It is a key indicator of climate change , is widely applied to studies of upper

High-resolution spatial databases of monthly climate variables (1961-2010) over a complex terrain region in southwestern China

NASA Astrophysics Data System (ADS)

Wu, Wei; Xu, An-Ding; Liu, Hong-Bin

2015-01-01

Climate data in gridded format are critical for understanding climate change and its impact on eco-environment. The aim of the current study is to develop spatial databases for three climate variables (maximum, minimum temperatures, and relative humidity) over a large region with complex topography in southwestern China. Five widely used approaches including inverse distance weighting, ordinary kriging, universal kriging, co-kriging, and thin-plate smoothing spline were tested. Root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) showed that thin-plate smoothing spline with latitude, longitude, and elevation outperformed other models. Average RMSE, MAE, and MAPE of the best models were 1.16 °C, 0.74 °C, and 7.38 % for maximum temperature; 0.826 °C, 0.58 °C, and 6.41 % for minimum temperature; and 3.44, 2.28, and 3.21 % for relative humidity, respectively. Spatial datasets of annual and monthly climate variables with 1-km resolution covering the period 1961-2010 were then obtained using the best performance methods. Comparative study showed that the current outcomes were in well agreement with public datasets. Based on the gridded datasets, changes in temperature variables were investigated across the study area. Future study might be needed to capture the uncertainty induced by environmental conditions through remote sensing and knowledge-based methods.

Decadal Variability of Temperature and Salinity in the Northwest Atlantic Ocean

NASA Astrophysics Data System (ADS)

Mishonov, A. V.; Seidov, D.; Reagan, J. R.; Boyer, T.; Parsons, A. R.

2017-12-01

There are only a few regions in the World Ocean where the density of observations collected over the past 60 years is sufficient for reliable data mapping with spatial resolutions finer than one-degree. The Northwest Atlantic basin is one such regions where a spatial resolution of gridded temperature and salinity fields, comparable to those generated by eddy-resolving numerical models of ocean circulation, has recently becomes available. Using the new high-resolution Northwest Atlantic Regional Climatology, built on quarter-degree and one-tenth-degree resolution fields, we analyzed decadal variability and trends of temperature and salinity over 60 years in the Northwest Atlantic, and two 30-year ocean climates of 1955-1984 and 1985-2012 to evaluate the oceanic climate shift in this region. The 30-year climate shift is demonstrated using an innovative 3-D visualization of temperature and salinity. Spatial and temporal variability of heat accumulation found in previous research of the entire North Atlantic Ocean persists in the Northwest Atlantic Ocean. Salinity changes between two 30-year climates were also computed and are discussed.

Exploiting temporal variability to understand tree recruitment response to climate change

Treesearch

Ines Ibanez; James S. Clark; Shannon LaDeau; Janneke Hill Ris Lambers

2007-01-01

Predicting vegetation shifts under climate change is a challenging endeavor, given the complex interactions between biotic and abiotic variables that influence demographic rates. To determine how current trends and variation in climate change affect seedling establishment, we analyzed demographic responses to spatiotemporal variation to temperature and soil moisture in...

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

USDA-ARS?s Scientific Manuscript database

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

Analyzing climate variations at multiple timescales can guide Zika virus response measures.

PubMed

Muñoz, Ángel G; Thomson, Madeleine C; Goddard, Lisa; Aldighieri, Sylvain

2016-10-06

The emergence of Zika virus (ZIKV) in Latin America and the Caribbean in 2014-2016 occurred during a period of severe drought and unusually high temperatures, conditions that have been associated with the 2015-2016 El Niño event, and/or climate change; however, no quantitative assessment has been made to date. Analysis of related flaviviruses transmitted by the same vectors suggests that ZIKV dynamics are sensitive to climate seasonality and longer-term variability and trends. A better understanding of the climate conditions conducive to the 2014-2016 epidemic may permit the development of climate-informed short and long-term strategies for ZIKV prevention and control. Using a novel timescale-decomposition methodology, we demonstrate that the extreme climate anomalies observed in most parts of South America during the current epidemic are not caused exclusively by El Niño or climate change, but by a combination of climate signals acting at multiple timescales. In Brazil, the dry conditions present in 2013-2015 are primarily explained by year-to-year variability superimposed on decadal variability, but with little contribution of long-term trends. In contrast, the warm temperatures of 2014-2015 resulted from the compound effect of climate change, decadal and year-to-year climate variability. ZIKV response strategies made in Brazil during the drought concurrent with the 2015-2016 El Niño event, may require revision in light of the likely return of rainfall associated with the borderline La Niña event expected in 2016-2017. Temperatures are likely to remain warm given the importance of long term and decadal scale climate signals. The Author(s)

Climate change and water availability for vulnerable agriculture

NASA Astrophysics Data System (ADS)

Dalezios, Nicolas; Tarquis, Ana Maria

2017-04-01

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

IN11B-1621: Quantifying How Climate Affects Vegetation in the Amazon Rainforest

NASA Technical Reports Server (NTRS)

Das, Kamalika; Kodali, Anuradha; Szubert, Marcin; Ganguly, Sangram; Bongard, Joshua

2016-01-01

Amazon droughts in 2005 and 2010 have raised serious concern about the future of the rainforest. Amazon forests are crucial because of their role as the largest carbon sink in the world which would effect the global warming phenomena with decreased photosynthesis activity. Especially, after a decline in plant growth in 1.68 million km2 forest area during the once-in-a-century severe drought in 2010, it is of primary importance to understand the relationship between different climatic variables and vegetation. In an earlier study, we have shown that non-linear models are better at capturing the relation dynamics of vegetation and climate variables such as temperature and precipitation, compared to linear models. In this research, we learn precise models between vegetation and climatic variables (temperature, precipitation) for normal conditions in the Amazon region using genetic programming based symbolic regression. This is done by removing high elevation and drought affected areas and also considering the slope of the region as one of the important factors while building the model. The model learned reveals new and interesting ways historical and current climate variables affect the vegetation at any location. MAIAC data has been used as a vegetation surrogate in our study. For temperature and precipitation, we have used TRMM and MODIS Land Surface Temperature data sets while learning the non-linear regression model. However, to generalize the model to make it independent of the data source, we perform transfer learning where we regress a regularized least squares to learn the parameters of the non-linear model using other data sources such as the precipitation and temperature from the Climatic Research Center (CRU). This new model is very similar in structure and performance compared to the original learned model and verifies the same claims about the nature of dependency between these climate variables and the vegetation in the Amazon region. As a result of this study, we are able to learn, for the very first time how exactly different climate factors influence vegetation at any location in the Amazon rainforests, independent of the specific sources from which the data has been obtained.

Quantifying How Climate Affects Vegetation in the Amazon Rainforest

NASA Astrophysics Data System (ADS)

Das, K.; Kodali, A.; Szubert, M.; Ganguly, S.; Bongard, J.

2016-12-01

Amazon droughts in 2005 and 2010 have raised serious concern about the future of the rainforest. Amazon forests are crucial because of their role as the largest carbon sink in the world which would effect the global warming phenomena with decreased photosynthesis activity. Especially, after a decline in plant growth in 1.68 million km2 forest area during the once-in-a-century severe drought in 2010, it is of primary importance to understand the relationship between different climatic variables and vegetation. In an earlier study, we have shown that non-linear models are better at capturing the relation dynamics of vegetation and climate variables such as temperature and precipitation, compared to linear models. In this research, we learn precise models between vegetation and climatic variables (temperature, precipitation) for normal conditions in the Amazon region using genetic programming based symbolic regression. This is done by removing high elevation and drought affected areas and also considering the slope of the region as one of the important factors while building the model. The model learned reveals new and interesting ways historical and current climate variables affect the vegetation at any location. MAIAC data has been used as a vegetation surrogate in our study. For temperature and precipitation, we have used TRMM and MODIS Land Surface Temperature data sets while learning the non-linear regression model. However, to generalize the model to make it independent of the data source, we perform transfer learning where we regress a regularized least squares to learn the parameters of the non-linear model using other data sources such as the precipitation and temperature from the Climatic Research Center (CRU). This new model is very similar in structure and performance compared to the original learned model and verifies the same claims about the nature of dependency between these climate variables and the vegetation in the Amazon region. As a result of this study, we are able to learn, for the very first time how exactly different climate factors influence vegetation at any location in the Amazon rainforests, independent of the specific sources from which the data has been obtained.

Pollen-based continental climate reconstructions at 6 and 21 ka: A global synthesis

USGS Publications Warehouse

Bartlein, P.J.; Harrison, S.P.; Brewer, Sandra; Connor, S.; Davis, B.A.S.; Gajewski, K.; Guiot, J.; Harrison-Prentice, T. I.; Henderson, A.; Peyron, O.; Prentice, I.C.; Scholze, M.; Seppa, H.; Shuman, B.; Sugita, S.; Thompson, R.S.; Viau, A.E.; Williams, J.; Wu, H.

2011-01-01

Subfossil pollen and plant macrofossil data derived from 14C-dated sediment profiles can provide quantitative information on glacial and interglacial climates. The data allow climate variables related to growing-season warmth, winter cold, and plant-available moisture to be reconstructed. Continental-scale reconstructions have been made for the mid-Holocene (MH, around 6 ka) and Last Glacial Maximum (LGM, around 21 ka), allowing comparison with palaeoclimate simulations currently being carried out as part of the fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change. The synthesis of the available MH and LGM climate reconstructions and their uncertainties, obtained using modern-analogue, regression and model-inversion techniques, is presented for four temperature variables and two moisture variables. Reconstructions of the same variables based on surface-pollen assemblages are shown to be accurate and unbiased. Reconstructed LGM and MH climate anomaly patterns are coherent, consistent between variables, and robust with respect to the choice of technique. They support a conceptual model of the controls of Late Quaternary climate change whereby the first-order effects of orbital variations and greenhouse forcing on the seasonal cycle of temperature are predictably modified by responses of the atmospheric circulation and surface energy balance. ?? 2010 The Author(s).

Earth System Science Education Centered on Natural Climate Variability

NASA Astrophysics Data System (ADS)

Ramirez, P. C.; Ladochy, S.; Patzert, W. C.; Willis, J. K.

2009-12-01

Several new courses and many educational activities related to climate change are available to teachers and students of all grade levels. However, not all new discoveries in climate research have reached the science education community. In particular, effective learning tools explaining natural climate change are scarce. For example, the Pacific Decadal Oscillation (PDO) is a main cause of natural climate variability spanning decades. While most educators are familiar with the shorter-temporal events impacting climate, El Niño and La Niña, very little has trickled into the climate change curriculum on the PDO. We have developed two online educational modules, using an Earth system science approach, on the PDO and its role in climate change and variability. The first concentrates on the discovery of the PDO through records of salmon catch in the Pacific Northwest and Alaska. We present the connection between salmon abundance in the North Pacific to changing sea surface temperature patterns associated with the PDO. The connection between sea surface temperatures and salmon abundance led to the discovery of the PDO. Our activity also lets students explore the role of salmon in the economy and culture of the Pacific Northwest and Alaska and the environmental requirements for salmon survival. The second module is based on the climate of southern California and how changes in the Pacific Ocean , such as the PDO and ENSO (El Niño-Southern Oscillation), influence regional climate variability. PDO and ENSO signals are evident in the long-term temperature and precipitation record of southern California. Students are guided in the module to discover the relationships between Pacific Ocean conditions and southern California climate variability. The module also provides information establishing the relationship between climate change and variability and the state's water, energy, agriculture, wildfires and forestry, air quality and health issues. Both modules will be reviewed for inclusion on the ESSEA (Earth Systems Science Education Alliance) course module list. ESSEA is a NSF-funded organization dedicated to K-12 online Earth system science education.

Association between climate variability and malaria epidemics in the East African highlands.

PubMed

Zhou, Guofa; Minakawa, Noboru; Githeko, Andrew K; Yan, Guiyun

2004-02-24

The causes of the recent reemergence of Plasmodium falciparum epidemic malaria in the East African highlands are controversial. Regional climate changes have been invoked as a major factor; however, assessing the impact of climate in malaria resurgence is difficult due to high spatial and temporal climate variability and the lack of long-term data series on malaria cases from different sites. Climate variability, defined as short-term fluctuations around the mean climate state, may be epidemiologically more relevant than mean temperature change, but its effects on malaria epidemics have not been rigorously examined. Here we used nonlinear mixed-regression model to investigate the association between autoregression (number of malaria outpatients during the previous time period), seasonality and climate variability, and the number of monthly malaria outpatients of the past 10-20 years in seven highland sites in East Africa. The model explained 65-81% of the variance in the number of monthly malaria outpatients. Nonlinear and synergistic effects of temperature and rainfall on the number of malaria outpatients were found in all seven sites. The net variance in the number of monthly malaria outpatients caused by autoregression and seasonality varied among sites and ranged from 18 to 63% (mean=38.6%), whereas 12-63% (mean=36.1%) of variance is attributed to climate variability. Our results suggest that there was a high spatial variation in the sensitivity of malaria outpatient number to climate fluctuations in the highlands, and that climate variability played an important role in initiating malaria epidemics in the East African highlands.

Ecological principles: climate, physiography, soil, and vegetation

Treesearch

George R. Parker; George T. Weaver

1989-01-01

The central hardwood region is a land of transitions in climate, physiography, soils, plants, and animals. Winter temperature and drought are the two most important climatic variables operating on plants and animals. Occasional severe periods of low winter temperatures in the northern half of the region restrict the northern occurrence of many plant and animal species...

Climate Change and Conservation Planning in California: The San Francisco Bay Area Upland Habitat Goals Approach

NASA Astrophysics Data System (ADS)

Branciforte, R.; Weiss, S. B.; Schaefer, N.

2008-12-01

Climate change threatens California's vast and unique biodiversity. The Bay Area Upland Habitat Goals is a comprehensive regional biodiversity assessment of the 9 counties surrounding San Francisco Bay, and is designing conservation land networks that will serve to protect, manage, and restore that biodiversity. Conservation goals for vegetation, rare plants, mammals, birds, fish, amphibians, reptiles, and invertebrates are set, and those goals are met using the optimization algorithm MARXAN. Climate change issues are being considered in the assessment and network design in several ways. The high spatial variability at mesoclimatic and topoclimatic scales in California creates high local biodiversity, and provides some degree of local resiliency to macroclimatic change. Mesoclimatic variability from 800 m scale PRISM climatic norms is used to assess "mesoclimate spaces" in distinct mountain ranges, so that high mesoclimatic variability, especially local extremes that likely support range limits of species and potential climatic refugia, can be captured in the network. Quantitative measures of network resiliency to climate change include the spatial range of key temperature and precipitation variables within planning units. Topoclimatic variability provides a finer-grained spatial patterning. Downscaling to the topoclimatic scale (10-50 m scale) includes modeling solar radiation across DEMs for predicting maximum temperature differentials, and topographic position indices for modeling minimum temperature differentials. PRISM data are also used to differentiate grasslands into distinct warm and cool types. The overall conservation strategy includes local and regional connectivity so that range shifts can be accommodated.

The Great Plains low-level jet in 1.5C and 2C HAPPI simulations: Implications for changes in extreme climate events

NASA Astrophysics Data System (ADS)

Weaver, S. J.; Barcikowska, M. J.

2017-12-01

Global temperature targets have become the cornerstone for global climate policy discussions. Given the goal of the Paris Accord to limit the rise in global mean temperature to well below 2.0oC above pre-industrial levels, and pursue efforts toward the more ambitious 1.5oC goal, there is increasing focus in the climate science community on what the relative changes in regional climate extremes may be for these two scenarios. Despite the successes of major climate science modeling efforts, there is still a significant information gap regarding the regional and seasonal changes in some climate extremes over the U.S. as a function of these global mean temperature targets.During the spring and summer, large amounts of heat and moisture are transported northward into the central and eastern U.S. by the Great Plains Low-Level Jet (GPLLJ) - an atmospheric river which dominates the subcontinental scale climate variability during the warm half of the year. Accordingly, the GPLLJ and its vast spatiotemporal variability is highly influential over several types of extreme climate anomalies east of the Rocky Mountains, including, drought and pluvial events, tornadic activity, and the evolution of central U.S warming hole. Changes in the GPLLJ and its variability are probed from the perspective of several hundred climate realizations afforded by the availability of climate model experiments from the Half a degree additional warming, Prognosis, and Projected Impacts (HAPPI) effort - a suite of multi-model ensemble AMIP simulations forced by 1.5oC and 2oC levels of global warming. The multimodel analysis focuses on the variable magnitude of the seasonal changes in the mean GPLLJ and shifts in the extremes of the prominent modes of GPLLJ variability - both of which have implications for the future shifts in extreme climate events over the Great Plains, Midwest, and southeast regions of the U.S.

Evidence for lower plasticity in CTMAX at warmer developmental temperatures.

PubMed

Kellermann, Vanessa; Sgrò, Carla M

2018-06-07

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

Continental-scale temperature covariance in proxy reconstructions and climate models

NASA Astrophysics Data System (ADS)

Hartl-Meier, Claudia; Büntgen, Ulf; Smerdon, Jason; Zorita, Eduardo; Krusic, Paul; Ljungqvist, Fredrik; Schneider, Lea; Esper, Jan

2017-04-01

Inter-continental temperature variability over the past millennium has been reported to be more coherent in climate model simulations than in multi-proxy-based reconstructions, a finding that undermines the representation of spatial variability in either of these approaches. We assess the covariance of summer temperatures among Northern Hemisphere continents by comparing tree-ring based temperature reconstructions with state-of-the-art climate model simulations over the past millennium. We find inter-continental temperature covariance to be larger in tree-ring-only reconstructions compared to those derived from multi-proxy networks, thus enhancing the agreement between proxy- and model-based spatial representations. A detailed comparison of simulated temperatures, however, reveals substantial spread among the models. Over the past millennium, inter-continental temperature correlations are driven by the cooling after major volcanic eruptions in 1257, 1452, 1601, and 1815. The coherence of these synchronizing events appears to be elevated in several climate simulations relative to their own covariance baselines and the proxy reconstructions, suggesting these models overestimate the amplitude of cooling in response to volcanic forcing at large spatial scales.

Updating beliefs and combining evidence in adaptive forest management under climate change: a case study of Norway spruce (Picea abies L. Karst) in the Black Forest, Germany.

PubMed

Yousefpour, Rasoul; Temperli, Christian; Bugmann, Harald; Elkin, Che; Hanewinkel, Marc; Meilby, Henrik; Jacobsen, Jette Bredahl; Thorsen, Bo Jellesmark

2013-06-15

We study climate uncertainty and how managers' beliefs about climate change develop and influence their decisions. We develop an approach for updating knowledge and beliefs based on the observation of forest and climate variables and illustrate its application for the adaptive management of an even-aged Norway spruce (Picea abies L. Karst) forest in the Black Forest, Germany. We simulated forest development under a range of climate change scenarios and forest management alternatives. Our analysis used Bayesian updating and Dempster's rule of combination to simulate how observations of climate and forest variables may influence a decision maker's beliefs about climate development and thereby management decisions. While forest managers may be inclined to rely on observed forest variables to infer climate change and impacts, we found that observation of climate state, e.g. temperature or precipitation is superior for updating beliefs and supporting decision-making. However, with little conflict among information sources, the strongest evidence would be offered by a combination of at least two informative variables, e.g., temperature and precipitation. The success of adaptive forest management depends on when managers switch to forward-looking management schemes. Thus, robust climate adaptation policies may depend crucially on a better understanding of what factors influence managers' belief in climate change. Copyright © 2013 Elsevier Ltd. All rights reserved.

West African warming: Investigating Temperature Trends and their relation between Precipitation Trends over West African Sahel.

NASA Astrophysics Data System (ADS)

LY, M., Jr.

2014-12-01

It is now admitted that the West African region faces a lot of constraints due to the comprehensiveness of the high climate variability and potential climate change. This is mainly due to the lack of a large number of datasets and long-term records as summarized in the in the IPCC reports. This paper aims to provide improved knowledge and evidence on current and future climate conditions, for better manage climate variability over seasons and from year to year and strengthen the capacity to adapt to future climate change. In this regards, we analyse the evolution of some extreme temperature and precipitation indices over a large area of West Africa. Prior results show a general warming trend at individual stations throughout the region during the period from 1960 to 2010, namely negative trends in the number of cool nights, and positive trends in the number of warm days and length of warm spells. Trends in rainfall-related indices are not as uniform as the ones in temperatures, rather they display marked multi-decadal variability, as expected. To refine analyses of temperature variations and their relation to precipitation we investigated on cluster analysis aimed at distinguishing different sub-regions, such as continental and coastal, and relevant seasons, such as wet, dry/cold and dry warm. This will contribute to significantly lower uncertainties by developing better and more tailored temperature and precipitation trends to inform the user communities on climate related risks, as well as enhance their resilience to food insecurity and other climate related disasters.

Variability of Soil Temperature: A Spatial and Temporal Analysis.

ERIC Educational Resources Information Center

Walsh, Stephen J.; And Others

1991-01-01

Discusses an analysis of the relationship of soil temperatures at 3 depths to various climatic variables along a 200-kilometer transect in west-central Oklahoma. Reports that temperature readings increased from east to west. Concludes that temperature variations were explained by a combination of spatial, temporal, and biophysical factors. (SG)

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

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

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

NASA Astrophysics Data System (ADS)

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

2010-01-01

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

Climate risks on potato yield in Europe

NASA Astrophysics Data System (ADS)

Sun, Xun; Lall, Upmanu

2016-04-01

The yield of potatoes is affected by water and temperature during the growing season. We study the impact of a suite of climate variables on potato yield at country level. More than ten climate variables related to the growth of potato are considered, including the seasonal rainfall and temperature, but also extreme conditions at different averaging periods from daily to monthly. A Bayesian hierarchical model is developed to jointly consider the risk of heat stress, cold stress, wet and drought. Future climate risks are investigated through the projection of future climate data. This study contributes to assess the risks of present and future climate risks on potatoes yield, especially the risks of extreme events, which could be used to guide better sourcing strategy and ensure food security in the future.

Country-Specific Effects of Climate Variability on Human Migration

PubMed Central

Gray, Clark; Wise, Erika

2016-01-01

Involuntary human migration is among the social outcomes of greatest concern in the current era of global climate change. Responding to this concern, a growing number of studies have investigated the consequences of short to medium-term climate variability for human migration using demographic and econometric approaches. These studies have provided important insights, but at the same time have been significantly limited by lack of expertise in the use of climate data, access to cross-national data on migration, and attention to model specification. To address these limitations, we link data on internal and international migration over a 6-year period from 9,812 origin households in Kenya, Uganda, Nigeria, Burkina Faso and Senegal to high-resolution gridded climate data from both station and satellite sources. Analyses of these data using several plausible specifications reveal that climate variability has country-specific effects on migration: Migration tends to increase with temperature anomalies in Uganda, tends to decrease with temperature anomalies in Kenya and Burkina Faso, and shows no consistent relationship with temperature in Nigeria and Senegal. Consistent with previous studies, precipitation shows weak and inconsistent relationships with migration across countries. These results challenge generalizing narratives that foresee a consistent migratory response to climate change across the globe. PMID:27092012

[Paleoclimate of La Guajira, Colombia; by the growth rings of Capparis odoratissima (Capparidaceae)].

PubMed

Ramírez, Jorge Andrés; Ignacio del Valle, Jorge

2011-09-01

There is great concern about the effect of climate change in arid and subarid areas of the tropics. Climate change combined with other anthropogenic activities such as deforestation, fires and over-grazing can accelerate their degradation and, consequently, the increases in losses of biological and economic productivity. Climate models, both local and global, predict that rainfall in the arid Peninsula of La Guajira in the Colombian Caribbean would be reduced and temperature would be increased as a result of climate change. However, as there are only suitable climate records since 1972, it is not possible to verify if, indeed, this is happening. To try to verify the hypothesis of reducing rainfall and rising temperatures we developed a growth ring chronology of Capparis odoratissima in the Middle Peninsula of La Guajira with 17 trees and 45 series which attain 48 years back. We use standard dendrochronological methods that showed statistically significant linear relationship with local climatic variables such as air temperature, sea surface temperature (SST), annual precipitation and wind speed; we also reach to successful relationship of the chronology with global climatic variables as the indices SOI and MEI of the ENSO phenomenon. The transfer functions estimated with the time series (1955 and 2003) do not showed statistically significant trends, indicating that during this period of time the annual precipitation or temperatures have not changed. The annual nature of C. odoratissima growth rings, the possibility of cross-dated among the samples of this species, and the high correlation with local and global climatic variables indicate a high potential of this species for dendrochronological studies in this part of the American continent.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Weaker soil carbon-climate feedbacks resulting from microbial and abiotic interactions

NASA Astrophysics Data System (ADS)

Tang, Jinyun; Riley, William J.

2015-01-01

The large uncertainty in soil carbon-climate feedback predictions has been attributed to the incorrect parameterization of decomposition temperature sensitivity (Q10; ref. ) and microbial carbon use efficiency. Empirical experiments have found that these parameters vary spatiotemporally, but such variability is not included in current ecosystem models. Here we use a thermodynamically based decomposition model to test the hypothesis that this observed variability arises from interactions between temperature, microbial biogeochemistry, and mineral surface sorptive reactions. We show that because mineral surfaces interact with substrates, enzymes and microbes, both Q10 and microbial carbon use efficiency are hysteretic (so that neither can be represented by a single static function) and the conventional labile and recalcitrant substrate characterization with static temperature sensitivity is flawed. In a 4-K temperature perturbation experiment, our fully dynamic model predicted more variable but weaker soil carbon-climate feedbacks than did the static Q10 and static carbon use efficiency model when forced with yearly, daily and hourly variable temperatures. These results imply that current Earth system models probably overestimate the response of soil carbon stocks to global warming. Future ecosystem models should therefore consider the dynamic interactions between sorptive mineral surfaces, substrates and microbial processes.

Rates of change in climatic niches in plant and animal populations are much slower than projected climate change

PubMed Central

Jezkova, Tereza

2016-01-01

Climate change may soon threaten much of global biodiversity. A critical question is: can species undergo niche shifts of sufficient speed and magnitude to persist within their current geographic ranges? Here, we analyse niche shifts among populations within 56 plant and animal species using time-calibrated trees from phylogeographic studies. Across 266 phylogeographic groups analysed, rates of niche change were much slower than rates of projected climate change (mean difference > 200 000-fold for temperature variables). Furthermore, the absolute niche divergence among populations was typically lower than the magnitude of projected climate change over the next approximately 55 years for relevant variables, suggesting the amount of change needed to persist may often be too great, even if these niche shifts were instantaneous. Rates were broadly similar between plants and animals, but especially rapid in some arthropods, birds and mammals. Rates for temperature variables were lower at lower latitudes, further suggesting that tropical species may be especially vulnerable to climate change. PMID:27881748

Rates of change in climatic niches in plant and animal populations are much slower than projected climate change.

PubMed

Jezkova, Tereza; Wiens, John J

2016-11-30

Climate change may soon threaten much of global biodiversity. A critical question is: can species undergo niche shifts of sufficient speed and magnitude to persist within their current geographic ranges? Here, we analyse niche shifts among populations within 56 plant and animal species using time-calibrated trees from phylogeographic studies. Across 266 phylogeographic groups analysed, rates of niche change were much slower than rates of projected climate change (mean difference > 200 000-fold for temperature variables). Furthermore, the absolute niche divergence among populations was typically lower than the magnitude of projected climate change over the next approximately 55 years for relevant variables, suggesting the amount of change needed to persist may often be too great, even if these niche shifts were instantaneous. Rates were broadly similar between plants and animals, but especially rapid in some arthropods, birds and mammals. Rates for temperature variables were lower at lower latitudes, further suggesting that tropical species may be especially vulnerable to climate change. © 2016 The Author(s).

Selection of climate change scenario data for impact modelling.

PubMed

Sloth Madsen, M; Maule, C Fox; MacKellar, N; Olesen, J E; Christensen, J Hesselbjerg

2012-01-01

Impact models investigating climate change effects on food safety often need detailed climate data. The aim of this study was to select climate change projection data for selected crop phenology and mycotoxin impact models. Using the ENSEMBLES database of climate model output, this study illustrates how the projected climate change signal of important variables as temperature, precipitation and relative humidity depends on the choice of the climate model. Using climate change projections from at least two different climate models is recommended to account for model uncertainty. To make the climate projections suitable for impact analysis at the local scale a weather generator approach was adopted. As the weather generator did not treat all the necessary variables, an ad-hoc statistical method was developed to synthesise realistic values of missing variables. The method is presented in this paper, applied to relative humidity, but it could be adopted to other variables if needed.

Spatial and seasonal characterization of net primary productivity and climate variables in southeastern China using MODIS data*

PubMed Central

Peng, Dai-liang; Huang, Jing-feng; Huete, Alfredo R.; Yang, Tai-ming; Gao, Ping; Chen, Yan-chun; Chen, Hui; Li, Jun; Liu, Zhan-yu

2010-01-01

We developed a sophisticated method to depict the spatial and seasonal characterization of net primary productivity (NPP) and climate variables. The role of climate variability in the seasonal variation of NPP exerts delayed and continuous effects. This study expands on this by mapping the seasonal characterization of NPP and climate variables from space using geographic information system (GIS) technology at the pixel level. Our approach was developed in southeastern China using moderate-resolution imaging spectroradiometer (MODIS) data. The results showed that air temperature, precipitation and sunshine percentage contributed significantly to seasonal variation of NPP. In the northern portion of the study area, a significant positive 32-d lagged correlation was observed between seasonal variation of NPP and climate (P<0.01), and the influences of changing climate on NPP lasted for 48 d or 64 d. In central southeastern China, NPP showed 16-d, 48-d, and 96-d lagged correlation with air temperature, precipitation, and sunshine percentage, respectively (P<0.01); the influences of air temperature and precipitation on NPP lasted for 48 d or 64 d, while sunshine influence on NPP only persisted for 16 d. Due to complex topography and vegetation distribution in the southern part of the study region, the spatial patterns of vegetation-climate relationship became complicated and diversiform, especially for precipitation influences on NPP. In the northern part of the study area, all vegetation NPP had an almost similar response to seasonal variation of air temperature except for broad crops. The impacts of seasonal variation of precipitation and sunshine on broad and cereal crop NPP were slightly different from other vegetation NPP. PMID:20349524

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

PubMed

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

2016-01-01

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

Spatial heterogeneity in ecologically important climate variables at coarse and fine scales in a high-snow mountain landscape.

PubMed

Ford, Kevin R; Ettinger, Ailene K; Lundquist, Jessica D; Raleigh, Mark S; Hille Ris Lambers, Janneke

2013-01-01

Climate plays an important role in determining the geographic ranges of species. With rapid climate change expected in the coming decades, ecologists have predicted that species ranges will shift large distances in elevation and latitude. However, most range shift assessments are based on coarse-scale climate models that ignore fine-scale heterogeneity and could fail to capture important range shift dynamics. Moreover, if climate varies dramatically over short distances, some populations of certain species may only need to migrate tens of meters between microhabitats to track their climate as opposed to hundreds of meters upward or hundreds of kilometers poleward. To address these issues, we measured climate variables that are likely important determinants of plant species distributions and abundances (snow disappearance date and soil temperature) at coarse and fine scales at Mount Rainier National Park in Washington State, USA. Coarse-scale differences across the landscape such as large changes in elevation had expected effects on climatic variables, with later snow disappearance dates and lower temperatures at higher elevations. However, locations separated by small distances (∼20 m), but differing by vegetation structure or topographic position, often experienced differences in snow disappearance date and soil temperature as great as locations separated by large distances (>1 km). Tree canopy gaps and topographic depressions experienced later snow disappearance dates than corresponding locations under intact canopy and on ridges. Additionally, locations under vegetation and on topographic ridges experienced lower maximum and higher minimum soil temperatures. The large differences in climate we observed over small distances will likely lead to complex range shift dynamics and could buffer species from the negative effects of climate change.

Spatial Heterogeneity in Ecologically Important Climate Variables at Coarse and Fine Scales in a High-Snow Mountain Landscape

PubMed Central

Ford, Kevin R.; Ettinger, Ailene K.; Lundquist, Jessica D.; Raleigh, Mark S.; Hille Ris Lambers, Janneke

2013-01-01

Climate plays an important role in determining the geographic ranges of species. With rapid climate change expected in the coming decades, ecologists have predicted that species ranges will shift large distances in elevation and latitude. However, most range shift assessments are based on coarse-scale climate models that ignore fine-scale heterogeneity and could fail to capture important range shift dynamics. Moreover, if climate varies dramatically over short distances, some populations of certain species may only need to migrate tens of meters between microhabitats to track their climate as opposed to hundreds of meters upward or hundreds of kilometers poleward. To address these issues, we measured climate variables that are likely important determinants of plant species distributions and abundances (snow disappearance date and soil temperature) at coarse and fine scales at Mount Rainier National Park in Washington State, USA. Coarse-scale differences across the landscape such as large changes in elevation had expected effects on climatic variables, with later snow disappearance dates and lower temperatures at higher elevations. However, locations separated by small distances (∼20 m), but differing by vegetation structure or topographic position, often experienced differences in snow disappearance date and soil temperature as great as locations separated by large distances (>1 km). Tree canopy gaps and topographic depressions experienced later snow disappearance dates than corresponding locations under intact canopy and on ridges. Additionally, locations under vegetation and on topographic ridges experienced lower maximum and higher minimum soil temperatures. The large differences in climate we observed over small distances will likely lead to complex range shift dynamics and could buffer species from the negative effects of climate change. PMID:23762277

Human Responses to Climate Variability: The Case of South Africa

NASA Astrophysics Data System (ADS)

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.

Assessing the Habitat of Coccidioides posadasii, the Valley Fever Pathogen: A Study of Environmental Variables and Human Incidence Data in Arizona

NASA Astrophysics Data System (ADS)

Mann, Sarina N.

Coccidioidomycosis, or Valley Fever, is an infectious disease caused by inhalation of soil-dwelling fungus Coccidioides posadasii spores in the Lower Sonoran Life Zone (LSLZ) in Arizona. In the context of climate change, the habitat of environmentally-mediated infectious diseases, such as Valley Fever, are expected to change. Connections have been drawn between climate and Valley Fever infection. The operational scale of the organism is still unknown. Here, we use climatic variables, including precipitation, soil moisture, and temperature. We use PRISM precipitation and temperature data, and Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) as a measure of soil moisture for the entire state of Arizona, divided into 126 primary care areas (PCA). These data are analyzed and regressed with Valley Fever incidence to determine the effects of climatic variability on disease distribution and timing. This study confirms that Valley Fever occurrence is clustered in the LSLZ. Seasonal Valley Fever outbreak was found to be variable year-to-year based on climatic variability. The inconclusive regression analyses indicate that the operational scale of Coccidioides is smaller than the PCA region. All variables are related to Valley Fever infection, but one variable was not found to hold more predictive power than others.

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

PubMed

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

2015-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Does the weather influence public opinion about climate change?

NASA Astrophysics Data System (ADS)

Donner, S. D.; McDaniel, J.

2010-12-01

Public opinion in North America about the science of anthropogenic climate change and the motivation for policy action has been variable over the past twenty years. The trends in public opinion over time have been attributed the general lack of pressing public concern about climate change to a range of political, economic and psychological factors. One driving force behind the variability in polling data from year to year may be the weather itself. The difference between what we “expect” - the climate - and what we “get” - the weather - can be a major source of confusion and obfuscation in the public discourse about climate change. For example, reaction to moderate global temperatures in 2007 and 2008 may have helped prompt the spread of a “global cooling” meme in the public and the news media. At the same time, a decrease in the belief in the science of climate change and the need for action has been noted in opinion polls. This study analyzes the relationship between public opinion about climate change and the weather in the U.S. since the mid-1980s using historical polling data from several major organizations (e.g. Gallup, Pew, Harris Interactive, ABC News), historical monthly air temperature (NCDC) and a survey of opinion articles from major U.S. newspapers (Washington Post, New York Times, Wall Street Journal, Houston Chronicle, USA Today). Seasonal and annual monthly temperature anomalies for the northeastern U.S and the continental U.S are compared with available national opinion data for three general categories of questions: i) Is the climate warming?, ii) Is the observed warming due to human activity?, and iii) Are you concerned about climate change? The variability in temperature and public opinion over time is also compared with the variability in the fraction of opinion articles in the newspapers (n ~ 7000) which express general agreement or disagreement with IPCC Summary for Policymakers consensus statements on climate change (“most of the observed increase in global average temperature is very likely to be due to the observed increase in anthropogenic greenhouse gas concentrations”). The results reveal a possible link between opinion leaders, particularly in the northeastern U.S, public confusion about the difference between weather and climate, and the evolution of U.S. public opinion about climate change.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

The absence of an Atlantic imprint on the multidecadal variability of wintertime European temperature

PubMed Central

Yamamoto, Ayako; Palter, Jaime B.

2016-01-01

Northern Hemisphere climate responds sensitively to multidecadal variability in North Atlantic sea surface temperature (SST). It is therefore surprising that an imprint of such variability is conspicuously absent in wintertime western European temperature, despite that Europe's climate is strongly influenced by its neighbouring ocean, where multidecadal variability in basin-average SST persists in all seasons. Here we trace the cause of this missing imprint to a dynamic anomaly of the atmospheric circulation that masks its thermodynamic response to SST anomalies. Specifically, differences in the pathways Lagrangian particles take to Europe during anomalous SST winters suppress the expected fluctuations in air–sea heat exchange accumulated along those trajectories. Because decadal variability in North Atlantic-average SST may be driven partly by the Atlantic Meridional Overturning Circulation (AMOC), the atmosphere's dynamical adjustment to this mode of variability may have important implications for the European wintertime temperature response to a projected twenty-first century AMOC decline. PMID:26975331

Climatological Modeling of Monthly Air Temperature and Precipitation in Egypt through GIS Techniques

NASA Astrophysics Data System (ADS)

El Kenawy, A.

2009-09-01

This paper describes a method for modeling and mapping four climatic variables (maximum temperature, minimum temperature, mean temperature and total precipitation) in Egypt using a multiple regression approach implemented in a GIS environment. In this model, a set of variables including latitude, longitude, elevation within a distance of 5, 10 and 15 km, slope, aspect, distance to the Mediterranean Sea, distance to the Red Sea, distance to the Nile, ratio between land and water masses within a radius of 5, 10, 15 km, the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Water Index (NDWI), the Normalized Difference Temperature Index (NDTI) and reflectance are included as independent variables. These variables were integrated as raster layers in MiraMon software at a spatial resolution of 1 km. Climatic variables were considered as dependent variables and averaged from quality controlled and homogenized 39 series distributing across the entire country during the period of (1957-2006). For each climatic variable, digital and objective maps were finally obtained using the multiple regression coefficients at monthly, seasonal and annual timescale. The accuracy of these maps were assessed through cross-validation between predicted and observed values using a set of statistics including coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), mean bias Error (MBE) and D Willmott statistic. These maps are valuable in the sense of spatial resolution as well as the number of observatories involved in the current analysis.

Climatic variability effects on summer cropping systems of the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Capa-Morocho, M.; Rodríguez-Fonseca, B.; Ruiz-Ramos, M.

2012-04-01

Climate variability and changes in the frequency of extremes events have a direct impact on crop yield and damages. Climate anomalies projections at monthly and yearly timescale allows us for adapting a cropping system (crops, varieties and management) to take advantage of favorable conditions or reduce the effect of adverse conditions. The objective of this work is to develop indices to evaluate the effect of climatic variability in summer cropping systems of Iberian Peninsula, in an attempt of relating yield variability to climate variability, extending the work of Rodríguez-Puebla (2004). This paper analyses the evolution of the yield anomalies of irrigated maize in several representative agricultural locations in Spain with contrasting temperature and precipitation regimes and compare it to the evolution of different patterns of climate variability, extending the methodology of Porter and Semenov (2005). To simulate maize yields observed daily data of radiation, maximum and minimum temperature and precipitation were used. These data were obtained from the State Meteorological Agency of Spain (AEMET). Time series of simulated maize yields were computed with CERES-maize model for periods ranging from 22 to 49 years, depending on the observed climate data available for each location. The computed standardized anomalies yields were projected on different oceanic and atmospheric anomalous fields and the resulting patterns were compared with a set of documented patterns from the National Oceanic and Atmospheric Administration (NOAA). The results can be useful also for climate change impact assessment, providing a scientific basis for selection of climate change scenarios where combined natural and forced variability represent a hazard for agricultural production. Interpretation of impact projections would also be enhanced.

Fine scale climatic and soil variability effects on plant species cover along the Front Range of Colorado, USA

NASA Astrophysics Data System (ADS)

Cumming, William Frank Preston

Fine scale studies are rarely performed to address landscape level responses to microclimatic variability. Is it the timing, distribution, and magnitude of soil temperature and moisture that affects what species emerge each season and, in turn, their resilience to fluctuations in microclimate. For this dissertation research, I evaluated the response of vegetation change to microclimatic variability within two communities over a three year period (2009-2012) utilizing 25 meter transects at two locations along the Front Range of Colorado near Boulder, CO and Golden, CO respectively. To assess microclimatic variability, spatial and temporal autocorrelation analyses were performed with soil temperature and moisture. Species cover was assessed along several line transects and correlated with microclimatic variability. Spatial and temporal autocorrelograms are useful tools in identifying the degree of dependency of soil temperature and moisture on the distance and time between pairs of measurements. With this analysis I found that a meter spatial resolution and two-hour measurements are sufficient to capture the fine scale variability in soil properties throughout the year. By comparing this to in situ measurements of soil properties and species percent cover I found that there are several plant functional types and/or species origin in particular that are more sensitive to variations in temperature and moisture than others. When all seasons, locations, correlations, and regional climate are looked at, it is the month of March that stands out in terms of significance. Additionally, of all of the vegetation types represented at these two sites C4, C3, native, non-native, and forb species seem to be the most sensitive to fluctuations in soil temperature, moisture, and regional climate in the spring season. The steady decline in percent species cover the study period and subsequent decrease in percent species cover and size at both locations may indicate that certain are unable to respond to continually higher temperatures and lower moisture availability that is inevitable with future climatic variability.

Winter and spring climatic conditions influence timing and synchrony of calving in reindeer.

PubMed

Paoli, Amélie; Weladji, Robert B; Holand, Øystein; Kumpula, Jouko

2018-01-01

In a context of climate change, a mismatch has been shown to occur between some species' reproductive phenology and their environment. So far, few studies have either documented temporal trends in calving phenology or assessed which climatic variables influence the calving phenology in ungulate species, yet the phenology of ungulates' births affects offspring survival and population's recruitment rate. Using a long-term dataset (45 years) of birth dates of a semi-domesticated reindeer population in Kaamanen, North Finland, we show that calving season has advanced by ~ 7 days between 1970 and 2016. Advanced birth dates were associated with lower precipitation and a reduced snow cover in April and warmer temperatures in April-May. Improved females' physical condition in late gestation due to warmer temperatures in April-May and reduced snow conditions in April probably accounted for such advance in calving date. On the other hand, a lengthening of the calving season was reported following a warmer temperature in January, a higher number of days when mean temperature exceeds 0°C in October-November and a decreasing snow cover from October to November. By affecting the inter-individual heterogeneity in the plastic response of females' calving date to better climatic conditions in fall and winter, climatic variability contributed to weaken the calving synchrony in this herd. Whether variability in climatic conditions form environmental cues for the adaptation of calving phenology by females to climate change is however uncertain, but it is likely. As such this study enhances our understanding on how reproductive phenology of ungulate species would be affected by climate change.

Winter and spring climatic conditions influence timing and synchrony of calving in reindeer

PubMed Central

Paoli, Amélie; Holand, Øystein; Kumpula, Jouko

2018-01-01

In a context of climate change, a mismatch has been shown to occur between some species’ reproductive phenology and their environment. So far, few studies have either documented temporal trends in calving phenology or assessed which climatic variables influence the calving phenology in ungulate species, yet the phenology of ungulates’ births affects offspring survival and population’s recruitment rate. Using a long-term dataset (45 years) of birth dates of a semi-domesticated reindeer population in Kaamanen, North Finland, we show that calving season has advanced by ~ 7 days between 1970 and 2016. Advanced birth dates were associated with lower precipitation and a reduced snow cover in April and warmer temperatures in April-May. Improved females’ physical condition in late gestation due to warmer temperatures in April-May and reduced snow conditions in April probably accounted for such advance in calving date. On the other hand, a lengthening of the calving season was reported following a warmer temperature in January, a higher number of days when mean temperature exceeds 0°C in October-November and a decreasing snow cover from October to November. By affecting the inter-individual heterogeneity in the plastic response of females’ calving date to better climatic conditions in fall and winter, climatic variability contributed to weaken the calving synchrony in this herd. Whether variability in climatic conditions form environmental cues for the adaptation of calving phenology by females to climate change is however uncertain, but it is likely. As such this study enhances our understanding on how reproductive phenology of ungulate species would be affected by climate change. PMID:29694410

Relationships between northern Adriatic Sea mucilage events and climate variability.

PubMed

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

2005-12-15

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

Review of Malaria Epidemics in Ethiopia using Enhanced Climate Services (ENACTS)

NASA Astrophysics Data System (ADS)

Muhammad, A.

2015-12-01

Malaria is a disease directly linked to temperature and rainfall. In Ethiopia, the influence of climate variables on malaria transmission and the subsequent role of ENSO in the rise of malaria incidence are becoming more recognized. Numerous publications attest to the extreme sensitivity of malaria to climate in Ethiopia. The majority of large-scale epidemics in the past were associated with climatic factors such as temperature and rainfall. However, there is limited information on climate variability and ENSO at the district level to aid in public health decision-making. Since 2008, the National Meteorogy Agency (NMA) and the International Research Institute for Climate and Society (IRI) have been collaborating on improving climate services in Ethiopia. This collaboration spurred the implementation of the Enhancing National Climate Services (ENACTS) initiative and the creation of the IRI Data Library (DL) NMA Ethiopia Maproom. ENACTS provides reliable and readily accessible climate data at high resolutions and the Maproom uses ENACTS to build a collection of maps and other figures that monitor climate and societal conditions at present and in the recent past (1981-2010). A recent analysis exploring the relationship of rainfall and temperature ENACTS products to malaria epidemics in proceeding rainy seasons within 12 woredas found above normal temperature anomalies to be more readily associated with epidemics when compared to above normal rainfall anomalies, regardless of the ENSO phase (Figure 1-2).

Modelling Spatial Dependence Structures Between Climate Variables by Combining Mixture Models with Copula Models

NASA Astrophysics Data System (ADS)

Khan, F.; Pilz, J.; Spöck, G.

2017-12-01

Spatio-temporal dependence structures play a pivotal role in understanding the meteorological characteristics of a basin or sub-basin. This further affects the hydrological conditions and consequently will provide misleading results if these structures are not taken into account properly. In this study we modeled the spatial dependence structure between climate variables including maximum, minimum temperature and precipitation in the Monsoon dominated region of Pakistan. For temperature, six, and for precipitation four meteorological stations have been considered. For modelling the dependence structure between temperature and precipitation at multiple sites, we utilized C-Vine, D-Vine and Student t-copula models. For temperature, multivariate mixture normal distributions and for precipitation gamma distributions have been used as marginals under the copula models. A comparison was made between C-Vine, D-Vine and Student t-copula by observational and simulated spatial dependence structure to choose an appropriate model for the climate data. The results show that all copula models performed well, however, there are subtle differences in their performances. The copula models captured the patterns of spatial dependence structures between climate variables at multiple meteorological sites, however, the t-copula showed poor performance in reproducing the dependence structure with respect to magnitude. It was observed that important statistics of observed data have been closely approximated except of maximum values for temperature and minimum values for minimum temperature. Probability density functions of simulated data closely follow the probability density functions of observational data for all variables. C and D-Vines are better tools when it comes to modelling the dependence between variables, however, Student t-copulas compete closely for precipitation. Keywords: Copula model, C-Vine, D-Vine, Spatial dependence structure, Monsoon dominated region of Pakistan, Mixture models, EM algorithm.

"Intelligent Ensemble" Projections of Precipitation and Surface Radiation in Support of Agricultural Climate Change Adaptation

NASA Technical Reports Server (NTRS)

Taylor, Patrick C.; Baker, Noel C.

2015-01-01

Earth's climate is changing and will continue to change into the foreseeable future. Expected changes in the climatological distribution of precipitation, surface temperature, and surface solar radiation will significantly impact agriculture. Adaptation strategies are, therefore, required to reduce the agricultural impacts of climate change. Climate change projections of precipitation, surface temperature, and surface solar radiation distributions are necessary input for adaption planning studies. These projections are conventionally constructed from an ensemble of climate model simulations (e.g., the Coupled Model Intercomparison Project 5 (CMIP5)) as an equal weighted average, one model one vote. Each climate model, however, represents the array of climate-relevant physical processes with varying degrees of fidelity influencing the projection of individual climate variables differently. Presented here is a new approach, termed the "Intelligent Ensemble, that constructs climate variable projections by weighting each model according to its ability to represent key physical processes, e.g., precipitation probability distribution. This approach provides added value over the equal weighted average method. Physical process metrics applied in the "Intelligent Ensemble" method are created using a combination of NASA and NOAA satellite and surface-based cloud, radiation, temperature, and precipitation data sets. The "Intelligent Ensemble" method is applied to the RCP4.5 and RCP8.5 anthropogenic climate forcing simulations within the CMIP5 archive to develop a set of climate change scenarios for precipitation, temperature, and surface solar radiation in each USDA Farm Resource Region for use in climate change adaptation studies.

Generalized Dissimilarity Modeling of Late-Quaternary Variations in Pollen-Based Compositional Dissimilarity

NASA Astrophysics Data System (ADS)

Williams, J. W.; Blois, J.; Ferrier, S.; Manion, G.; Fitzpatrick, M.; Veloz, S.; He, F.; Liu, Z.; Otto-Bliesner, B. L.

2011-12-01

In Quaternary paleoecology and paleoclimatology, compositionally dissimilar fossil assemblages usually indicate dissimilar environments; this relationship underpins assemblage-level techniques for paleoenvironmental reconstruction such as mutual climatic ranges or the modern analog technique. However, there has been relatively little investigation into the form of the relationship between compositional dissimilarity and climatic dissimilarity. Here we apply generalized dissimilarity modeling (GDM; Ferrier et al. 2007) as a tool for modeling the expected non-linear relationships between compositional and climatic dissimilarity. We use the CCSM3.0 transient paleoclimatic simulations from the SynTrace working group (Liu et al. 2009) and a new generation of fossil pollen maps from eastern North America (Blois et al. 2011) to 1) assess the spatial relationships between compositional dissimilarity and climatic dissimilarity and 2) whether these spatial relationships change over time. We used a taxonomic list of 106 genus-level pollen types, six climatic variables (winter precipitation and mean temperature, summer precipitation and temperature, seasonality of precipitation, and seasonality of temperature) that were chosen to minimize collinearity, and a cross-referenced pollen and climate dataset mapped for time slices spaced 1000 years apart. When GDM was trained for one time slice, the correlation between predicted and observed spatial patterns of community dissimilarity for other times ranged between 0.3 and 0.73. The selection of climatic predictor variables changed over time, as did the form of the relationship between compositional turnover and climatic predictors. Summer temperature was the only variable selected for all time periods. These results thus suggest that the relationship between compositional dissimilarity in pollen assemblages (and, by implication, beta diversity in plant communities) and climatic dissimilarity can change over time, for reasons to be further studied.

Rain, temperature, and child-adolescent height among Native Amazonians in Bolivia.

PubMed

Godoy, R; Goodman, E; Reyes-Garcia, V; Eisenberg, D T A; Leonard, W R; Huanca, T; McDade, T W; Tanner, S; Jha, N

2008-01-01

Global climate change and recent studies on early-life origins of well-being suggest that climate events early in life might affect health later in life. The study tested hypotheses about the association between the level and variability of rain and temperature early in life on the height of children and adolescents in a foraging-farming society of native Amazonians in Bolivia (Tsimane'). Measurements were taken for 525 children aged 2-12 and 218 adolescents aged 13-23 in 13 villages in 2005. Log of standing height was regressed on mean annual level and mean intra-annual monthly coefficient of variation (CV) of rain and mean annual level of temperature during gestation, birth year, and ages 2-4. Controls include age, quinquennium and season of birth, parent's attributes, and dummy variables for surveyors and villages. Climate variables were only related with the height of boys age 2-12. The level and CV of rain during birth year and the CV of rain and level of temperature during ages 2-4 were associated with taller stature. There were no secular changes in temperature (1973-2005) or rain (1943-2005). The height of young females and males is well protected from climate events, but protection works less well for boys ages 2-12.

Climatic Variables and Malaria Morbidity in Mutale Local Municipality, South Africa: A 19-Year Data Analysis.

PubMed

Adeola, Abiodun M; Botai, Joel O; Rautenbach, Hannes; Adisa, Omolola M; Ncongwane, Katlego P; Botai, Christina M; Adebayo-Ojo, Temitope C

2017-11-08

The north-eastern parts of South Africa, comprising the Limpopo Province, have recorded a sudden rise in the rate of malaria morbidity and mortality in the 2017 malaria season. The epidemiological profiles of malaria, as well as other vector-borne diseases, are strongly associated with climate and environmental conditions. A retrospective understanding of the relationship between climate and the occurrence of malaria may provide insight into the dynamics of the disease's transmission and its persistence in the north-eastern region. In this paper, the association between climatic variables and the occurrence of malaria was studied in the Mutale local municipality in South Africa over a period of 19-year. Time series analysis was conducted on monthly climatic variables and monthly malaria cases in the Mutale municipality for the period of 1998-2017. Spearman correlation analysis was performed and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model was developed. Microsoft Excel was used for data cleaning, and statistical software R was used to analyse the data and develop the model. Results show that both climatic variables' and malaria cases' time series exhibited seasonal patterns, showing a number of peaks and fluctuations. Spearman correlation analysis indicated that monthly total rainfall, mean minimum temperature, mean maximum temperature, mean average temperature, and mean relative humidity were significantly and positively correlated with monthly malaria cases in the study area. Regression analysis showed that monthly total rainfall and monthly mean minimum temperature ( R ² = 0.65), at a two-month lagged effect, are the most significant climatic predictors of malaria transmission in Mutale local municipality. A SARIMA (2,1,2) (1,1,1) model fitted with only malaria cases has a prediction performance of about 51%, and the SARIMAX (2,1,2) (1,1,1) model with climatic variables as exogenous factors has a prediction performance of about 72% in malaria cases. The model gives a close comparison between the predicted and observed number of malaria cases, hence indicating that the model provides an acceptable fit to predict the number of malaria cases in the municipality. To sum up, the association between the climatic variables and malaria cases provides clues to better understand the dynamics of malaria transmission. The lagged effect detected in this study can help in adequate planning for malaria intervention.

Climate influence on dengue epidemics in Puerto Rico.

PubMed

Jury, Mark R

2008-10-01

The variability of the insect-borne disease dengue in Puerto Rico was studied in relation to climatic variables in the period 1979-2005. Annual and monthly reported dengue cases were compared with precipitation and temperature data. Results show that the incidence of dengue in Puerto Rico was relatively constant over time despite global warming, possibly due to the offsetting effects of declining rainfall, improving health care and little change in population. Seasonal fluctuations of dengue were driven by rainfall increases from May to November. Year-to-year variability in dengue cases was positively related to temperature, but only weakly associated with local rainfall and an index of El Nino Southern Oscillation (ENSO). Climatic conditions were mapped with respect to dengue cases and patterns in high and low years were compared. During epidemics, a low pressure system east of Florida draws warm humid air over the northwestern Caribbean. Long-term trends in past observed and future projected rainfall and temperatures were studied. Rainfall has declined slowly, but temperatures in the Caribbean are rising with the influence of global warming. Thus, dengue may increase in the future, and it will be necessary to anticipate dengue epidemics using climate forecasts, to reduce adverse health impacts.

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

PubMed

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

2017-01-15

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

Connecting differential responses of native and invasive riparian plants to climate change and environmental alteration.

PubMed

Flanagan, Neal E; Richardson, Curtis J; Ho, Mengchi

2015-04-01

Climate change is predicted to impact river systems in the southeastern United States through alterations of temperature, patterns of precipitation and hydrology. Future climate scenarios for the southeastern United States predict (1) surface water temperatures will warm in concert with air temperature, (2) storm flows will increase and base flows will decrease, and (3) the annual pattern of synchronization between hydroperiod and water temperature will be altered. These alterations are expected to disturb floodplain plant communities, making them more vulnerable to establishment of invasive species. The primary objective of this study is to evaluate whether native and invasive riparian plant assemblages respond differently to alterations of climate and land use. To study the response of riparian wetlands to watershed and climate alterations, we utilized an existing natural experiment imbedded in gradients of temperature and hydrology-found among dammed and undammed rivers. We evaluated a suite of environmental variables related to water temperature, hydrology, watershed disturbance, and edaphic conditions to identify the strongest predictors of native and invasive species abundances. We found that native species abundance is strongly influenced by climate-driven variables such as temperature and hydrology, while invasive species abundance is more strongly influenced by site-specific factors such as land use and soil nutrient availability. The patterns of synchronization between plant phenology, annual hydrographs, and annual water temperature cycles may be key factors sustaining the viability of native riparian plant communities. Our results demonstrate the need to understand the interactions between climate, land use, and nutrient management in maintaining the species diversity of riparian plant communities. Future climate change is likely to result in diminished competitiveness of native plant species, while the competitiveness of invasive species will increase due to anthropogenic watershed disturbance and accelerated nutrient and sediment export.

A real-time Global Warming Index.

PubMed

Haustein, K; Allen, M R; Forster, P M; Otto, F E L; Mitchell, D M; Matthews, H D; Frame, D J

2017-11-13

We propose a simple real-time index of global human-induced warming and assess its robustness to uncertainties in climate forcing and short-term climate fluctuations. This index provides improved scientific context for temperature stabilisation targets and has the potential to decrease the volatility of climate policy. We quantify uncertainties arising from temperature observations, climate radiative forcings, internal variability and the model response. Our index and the associated rate of human-induced warming is compatible with a range of other more sophisticated methods to estimate the human contribution to observed global temperature change.

Climate and Physiography Predict Mercury Concentrations in Game Fish Species in Quebec Lakes Better than Anthropogenic Disturbances.

PubMed

Lucotte, Marc; Paquet, Serge; Moingt, Matthieu

2016-05-01

The fluctuations of mercury levels (Hg) in fish consumed by sport fishers in North-Eastern America depend upon a plethora of interrelated biological and abiological factors. To identify the dominant factors ultimately controlling fish Hg concentrations, we compiled mercury levels (Hg) during the 1976-2010 period in 90 large natural lakes in Quebec (Canada) for two major game species: northern pike (Esox lucius) and walleye (Sander vitreus). Our statistical analysis included 28 geographic information system variables and 15 climatic variables, including sulfate deposition. Higher winter temperatures explained 36% of the variability in higher walleye growth rates, in turn accounting for 54% of the variability in lower Hg concentrations. For northern pike, the dominance of a flat topography in the watershed explained 31% of the variability in lower Hg concentrations. Higher mean annual temperatures explained 27% of the variability in higher pike Hg concentrations. Pelagic versus littoral preferred habitats for walleye and pike respectively could explain the contrasted effect of temperature between the two species. Heavy logging could only explain 2% of the increase in walleye Hg concentrations. The influence of mining on fish Hg concentrations appeared to be masked by climatic effects.

A CLIMATOLOGY OF WATER BUDGET VARIABLES FOR THE NORTHEAST UNITED STATES

EPA Science Inventory

This dataset provided only by the Northeast Regional Climatic Center is the basis for A Climatology of Water Budget Variables for the Northeast United States (Leathers and Robinson 1995). Climatic division precipitation and temperature data are used to calculate water budget vari...

Effects of climate change on phenology in two French LTER (Alps and Brittany) for the period 1998-2009

NASA Astrophysics Data System (ADS)

Perrimond, B.; Bigot, S.; Quénol, H.; Spielgelberger, T.; Baudry, J.

2012-04-01

Climate and vegetation are linked all over the world. In this study, we work on a seasonal weather classification based on air temperature and precipitation to deduce a link with different phenological stage (greening up, senescence, ...) over a 12 year period (1998-2009) for two different domains in France (Alps and Brittany). In temperate land, the main climatic variable with a potential effect on vegetation is the mean temperature followed by the rainfall deficit. A better understanding in season and their climatic characteristic is need to establish link between climate and phenology; so a weather classification is proposed based on empirical orthogonal functions and ascending hierarchical classification on atmospheric variables. This classification allows us to exhibit the inter-annual and intra-seasonal climatic spatiotemporal variability for both experimental site. Relationships between climate and phenology consist in a comparison between advance and delay in phenological stage and weather type issue from the classification. Experiment field are two french Long Term Ecological Research (LTER). The first one (LTER 'Alps' ) have mountain characteristics about 1000 to 4780 m ASL, ~65% of forest occupation ; the second one (LTER Armorique) is an Atlantic coastal landscape, 0-360 m ASL, ~70% of agricultural field. Climatic data are SAFRAN-France reanalysis which are developed to run SVAT model and come from the French meteorological service 'Météo-France'. All atmospheric variable needed to run a hydrological model are available (air temperature, rainfall/snowfall, wind speed, relative humidity, incoming/outcoming radiation) at a 8-8 km2 space resolution and with a daily time resolution. The phenological data are extracted from SPOT-VGT product 1-1 km2 space resolution and 10 days time resolution) by time series analysis process. Such of study is particularly important to understand relationships between environmental and ecological variables and it will allow to better predict ecological reaction under climate change constraint.

A global assessment of climate-water quality relationships in large rivers: an elasticity perspective.

PubMed

Jiang, Jiping; Sharma, Ashish; Sivakumar, Bellie; Wang, Peng

2014-01-15

To uncover climate-water quality relationships in large rivers on a global scale, the present study investigates the climate elasticity of river water quality (CEWQ) using long-term monthly records observed at 14 large rivers. Temperature and precipitation elasticities of 12 water quality parameters, highlighted by N- and P-nutrients, are assessed. General observations on elasticity values show the usefulness of this approach to describe the magnitude of stream water quality responses to climate change, which improves that of simple statistical correlation. Sensitivity type, intensity and variability rank of CEWQ are reported and specific characteristics and mechanism of elasticity of nutrient parameters are also revealed. Among them, the performance of ammonia, total phosphorus-air temperature models, and nitrite, orthophosphorus-precipitation models are the best. Spatial and temporal assessment shows that precipitation elasticity is more variable in space than temperature elasticity and that seasonal variation is more evident for precipitation elasticity than for temperature elasticity. Moreover, both anthropogenic activities and environmental factors are found to impact CEWQ for select variables. The major relationships that can be inferred include: (1) human population has a strong linear correlation with temperature elasticity of turbidity and total phosphorus; and (2) latitude has a strong linear correlation with precipitation elasticity of turbidity and N nutrients. As this work improves our understanding of the relation between climate factors and surface water quality, it is potentially helpful for investigating the effect of climate change on water quality in large rivers, such as on the long-term change of nutrient concentrations. © 2013.

Application of solar max ACRIM data to analyze solar-driven climatic variability on Earth

NASA Technical Reports Server (NTRS)

Hoffert, M. I.

1986-01-01

Terrestrial climatic effects associated with solar variability have been proposed for at least a century, but could not be assessed quantitatively owing to observational uncertainities in solar flux variations. Measurements from 1980 to 1984 by the Active Cavity Radiometer Irradiance Monitor (ACRIM), capable of resolving fluctuations above the sensible atmosphere less than 0.1% of the solar constant, permit direct albeit preliminary assessments of solar forcing effects on global temperatures during this period. The global temperature response to ACRIM-measured fluctuations was computed from 1980 to 1985 using the NYU transient climate model including thermal inertia effects of the world ocean; and compared the results with observations of recent temperature trends. Monthly mean ACRIM-driven global surface temperature fluctuations computed with the climate model are an order of magnitude smaller, of order 0.01 C. In constrast, global mean surface temperature observations indicate an approx. 0.1 C increase during this period. Solar variability is therefore likely to have been a minor factor in global climate change during this period compared with variations in atmospheric albedo, greenhouse gases and internal self-inducedoscillations. It was not possible to extend the applicability of the measured flux variations to longer periods since a possible correlation of luminosity with solar annual activity is not supported by statistical analysis. The continuous monitoring of solar flux by satellite-based instruments over timescales of 20 years or more comparable to timescales for thermal relaxation of the oceans and of the solar cycle itself is needed to resolve the question of long-term solar variation effects on climate.

Long-Term Variability of Satellite Lake Surface Water Temperatures in the Great Lakes

NASA Astrophysics Data System (ADS)

Gierach, M. M.; Matsumoto, K.; Holt, B.; McKinney, P. J.; Tokos, K.

2014-12-01

The Great Lakes are the largest group of freshwater lakes on Earth that approximately 37 million people depend upon for fresh drinking water, food, flood and drought mitigation, and natural resources that support industry, jobs, shipping and tourism. Recent reports have stated (e.g., the National Climate Assessment) that climate change can impact and exacerbate a range of risks to the Great Lakes, including changes in the range and distribution of certain fish species, increased invasive species and harmful algal blooms, declining beach health, and lengthened commercial navigation season. In this study, we will examine the impact of climate change on the Laurentian Great Lakes through investigation of long-term lake surface water temperatures (LSWT). We will use the ATSR Reprocessing for Climate: Lake Surface Water Temperature & Ice Cover (ARC-Lake) product over the period 1995-2012 to investigate individual and interlake variability. Specifically, we will quantify the seasonal amplitude of LSWTs, the first and last appearances of the 4°C isotherm (i.e., an important identifier of the seasonal evolution of the lakes denoting winter and summer stratification), and interpret these quantities in the context of global interannual climate variability such as ENSO.

People as sensors: mass media and local temperature influence climate change discussion on Twitter

NASA Astrophysics Data System (ADS)

Kirilenko, A.; Molodtsova, T.; Stepchenkova, S.

2014-12-01

We examined whether people living under significant temperature anomalies connect their sensory experiences to climate change and the role that media plays in this process. We used Twitter messages containing words "climate change" and "global warming" as the indicator of attention that public pays to the issue. Specifically, the goals were: (1) to investigate whether people immediately notice significant local weather anomalies and connect them to climate change and (2) to examine the role of mass media in this process. Over 2 million tweets were collected for a two-year period (2012 - 2013) and were assigned to 157 urban areas in the continental USA (Figure 1). Geographical locations of the tweets were identified with a geolocation resolving algorithm based the profile of the users. Daily number of tweets (tweeting rate) was computed for 157 conterminous USA urban areas and adjusted for data acquisition errors. The USHCN daily minimum and maximum temperatures were obtained for the station locations closest to the centers of the urban areas and the 1981-2010 30-year temperature mean and standard deviation were used as the climate normals. For the analysis, we computed the following indices for each day of 2012 - 2013 period: standardized temperature anomaly, absolute standardized temperature anomaly, and extreme cold and hot temperature anomalies for each urban zone. The extreme cold and hot temperature anomalies were then transformed into country-level values that represent the number of people living in extreme temperature conditions. The rate of tweeting on climate change was regressed on the time variables, number of climate change publications in the mass media, and temperature. In the majority of regression models, the mass media and temperature variables were significant at the p<0.001 level. Additionally, we did not find convincing evidence that the media acts as a mediator in the relationship between local weather and climate change discourse intensity. Our analysis of Twitter data confirmed that the public is able to recognize extreme temperature anomalies and connects these anomalies to climate change. Finally, we demonstrated the utility of social network data for research on public climate change perception.

Plasticity in Dendroclimatic Response across the Distribution Range of Aleppo Pine (Pinus halepensis)

PubMed Central

de Luis, Martin; Čufar, Katarina; Di Filippo, Alfredo; Novak, Klemen; Papadopoulos, Andreas; Piovesan, Gianluca; Rathgeber, Cyrille B. K.; Raventós, José; Saz, Miguel Angel; Smith, Kevin T.

2013-01-01

We investigated the variability of the climate-growth relationship of Aleppo pine across its distribution range in the Mediterranean Basin. We constructed a network of tree-ring index chronologies from 63 sites across the region. Correlation function analysis identified the relationships of tree-ring index to climate factors for each site. We also estimated the dominant climatic gradients of the region using principal component analysis of monthly, seasonal, and annual mean temperature and total precipitation from 1,068 climatic gridpoints. Variation in ring width index was primarily related to precipitation and secondarily to temperature. However, we found that the dendroclimatic relationship depended on the position of the site along the climatic gradient. In the southern part of the distribution range, where temperature was generally higher and precipitation lower than the regional average, reduced growth was also associated with warm and dry conditions. In the northern part, where the average temperature was lower and the precipitation more abundant than the regional average, reduced growth was associated with cool conditions. Thus, our study highlights the substantial plasticity of Aleppo pine in response to different climatic conditions. These results do not resolve the source of response variability as being due to either genetic variation in provenance, to phenotypic plasticity, or a combination of factors. However, as current growth responses to inter-annual climate variability vary spatially across existing climate gradients, future climate-growth relationships will also likely be determined by differential adaptation and/or acclimation responses to spatial climatic variation. The contribution of local adaptation and/or phenotypic plasticity across populations to the persistence of species under global warming could be decisive for prediction of climate change impacts across populations. In this sense, a more complex forest dynamics modeling approach that includes the contribution of genetic variation and phenotypic plasticity can improve the reliability of the ecological inferences derived from the climate-growth relationships. PMID:24391786

Climate Change and ENSO Effects on Southeastern US Climate Patterns and Maize Yield.

PubMed

Mourtzinis, Spyridon; Ortiz, Brenda V; Damianidis, Damianos

2016-07-19

Climate change has a strong influence on weather patterns and significantly affects crop yields globally. El Niño Southern Oscillation (ENSO) has a strong influence on the U.S. climate and is related to agricultural production variability. ENSO effects are location-specific and in southeastern U.S. strongly connect with climate variability. When combined with climate change, the effects on growing season climate patterns and crop yields might be greater than expected. In our study, historical monthly precipitation and temperature data were coupled with non-irrigated maize yield data (33-43 years depending on the location) to show a potential yield suppression of ~15% for one °C increase in southeastern U.S. growing season maximum temperature. Yield suppression ranged between -25 and -2% among locations suppressing the southeastern U.S. average yield trend since 1981 by 17 kg ha(-1)year(-1) (~25%), mainly due to year-to-year June temperature anomalies. Yields varied among ENSO phases from 1971-2013, with greater yields observed during El Niño phase. During La Niña years, maximum June temperatures were higher than Neutral and El Niño, whereas June precipitation was lower than El Niño years. Our data highlight the importance of developing location-specific adaptation strategies quantifying both, climate change and ENSO effects on month-specific growing season climate conditions.

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

NASA Astrophysics Data System (ADS)

Los, S. O.

2015-06-01

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

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

PubMed

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

2012-02-01

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

Early Holocene hydroclimate of Baffin Bay: Understanding the interplay between abrupt climate change events and ice sheet fluctuations

NASA Astrophysics Data System (ADS)

Corcoran, M. C.; Thomas, E. K.; Castañeda, I. S.; Briner, J. P.

2017-12-01

Understanding the causes of ice sheet fluctuations resulting in sea level rise is essential in today's warming climate. In high-latitude ice-sheet-proximal environments such as Baffin Bay, studying both the cause and the rate of ice sheet variability during past abrupt climate change events aids in predictions. Past climate reconstructions are used to understand ice sheet responses to changes in temperature and precipitation. The 9,300 and 8,200 yr BP events are examples of abrupt climate change events in the Baffin Bay region during which there were multiple re-advances of the Greenland and Laurentide ice sheets. High-resolution (decadal-scale) hydroclimate variability near the ice sheet margins during these abrupt climate change events is still unknown. We will generate a decadal-scale record of early Holocene temperature and precipitation using leaf wax hydrogen isotopes, δ2Hwax, from a lake sediment archive on Baffin Island, western Baffin Bay, to better understand abrupt climate change in this region. Shifts in temperature and moisture source result in changes in environmental water δ2H, which in turn is reflected in δ2Hwax, allowing for past hydroclimate to be determined from these compound-specific isotopes. The combination of terrestrial and aquatic δ2Hwax is used to determine soil evaporation and is ultimately used to reconstruct moisture variability. We will compare our results with a previous analysis of δ2Hwax and branched glycerol dialkyl glycerol tetraethers, a temperature and pH proxy, in lake sediment from western Greenland, eastern Baffin Bay, which indicates that cool and dry climate occurred in response to freshwater forcing events in the Labrador Sea. Reconstructing and comparing records on both the western and eastern sides of Baffin Bay during the early Holocene will allow for a spatial understanding of temperature and moisture balance changes during abrupt climate events, aiding in ice sheet modeling and predictions of future sea level rise.

Use of a Weather Generator for analysis of projections of future daily temperature and its validation with climate change indices

NASA Astrophysics Data System (ADS)

Di Piazza, A.; Cordano, E.; Eccel, E.

2012-04-01

The issue of climate change detection is considered a major challenge. In particular, high temporal resolution climate change scenarios are required in the evaluation of the effects of climate change on agricultural management (crop suitability, yields, risk assessment, etc.) energy production and water management. In this work, a "Weather Generator" technique was used for downscaling climate change scenarios for temperature. An R package (RMAWGEN, Cordano and Eccel, 2011 - available on http://cran.r-project.org) was developed aiming to generate synthetic daily weather conditions by using the theory of vectorial auto-regressive models (VAR). The VAR model was chosen for its ability in maintaining the temporal and spatial correlations among variables. In particular, observed time series of daily maximum and minimum temperature are transformed into "new" normally-distributed variable time series which are used to calibrate the parameters of a VAR model by using ordinary least square methods. Therefore the implemented algorithm, applied to monthly mean climatic values downscaled by Global Climate Model predictions, can generate several stochastic daily scenarios where the statistical consistency among series is saved. Further details are present in RMAWGEN documentation. An application is presented here by using a dataset with daily temperature time series recorded in 41 different sites of Trentino region for the period 1958-2010. Temperature time series were pre-processed to fill missing values (by a site-specific calibrated Inverse Distance Weighting algorithm, corrected with elevation) and to remove inhomogeneities. Several climatic indices were taken into account, useful for several impact assessment applications, and their time trends within the time series were analyzed. The indices go from the more classical ones, as annual mean temperatures, seasonal mean temperatures and their anomalies (from the reference period 1961-1990) to the climate change indices selected from the list recommended by the World Meteorological Organization Commission for Climatology (WMO-CCL) and the Research Programme on Climate Variability and Predictability (CLIVAR) project's Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI). Each index was applied to both observed (and processed) data and to synthetic time series produced by the Weather Generator, over the thirty year reference period 1981-2010, in order to validate the procedure. Climate projections were statistically downscaled for a selection of sites for the two 30-year periods 2021-2050 and 2071-2099 of the European project "Ensembles" multi-model output (scenario A1B). The use of several climatic indices strengthens the trend analysis of both the generated synthetic series and future climate projections.

The forcing of southwestern Asia teleconnections by low-frequency sea surface temperature variability during boreal winter

USGS Publications Warehouse

Hoell, Andrew; Funk, Christopher C.; Mathew Barlow,

2015-01-01

Southwestern Asia, defined here as the domain bounded by 20°–40°N and 40°–70°E, which includes the nations of Iraq, Iran, Afghanistan, and Pakistan, is a water-stressed and semiarid region that receives roughly 75% of its annual rainfall during November–April. The November–April climate of southwestern Asia is strongly influenced by tropical Indo-Pacific variability on intraseasonal and interannual time scales, much of which can be attributed to sea surface temperature (SST) variations. The influences of lower-frequency SST variability on southwestern Asia climate during November–April Pacific decadal SST (PDSST) variability and the long-term trend in SST (LTSST) is examined. The U.S. Climate Variability and Predictability Program (CLIVAR) Drought Working Group forced global atmospheric climate models with PDSST and LTSST patterns, identified using empirical orthogonal functions, to show the steady atmospheric response to these modes of decadal to multidecadal SST variability. During November–April, LTSST forces an anticyclone over southwestern Asia, which results in reduced precipitation and increases in surface temperature. The precipitation and tropospheric circulation influences of LTSST are corroborated by independent observed precipitation and circulation datasets during 1901–2004. The decadal variations of southwestern Asia precipitation may be forced by PDSST variability, with two of the three models indicating that the cold phase of PDSST forces an anticyclone and precipitation reductions. However, there are intermodel circulation variations to PDSST that influence subregional precipitation patterns over the Middle East, southwestern Asia, and subtropical Asia. Changes in wintertime temperature and precipitation over southwestern Asia forced by LTSST and PDSST imply important changes to the land surface hydrology during the spring and summer.

Climatic change by cloudiness linked to the spatial variability of sea surface temperatures

NASA Technical Reports Server (NTRS)

Otterman, J.

1975-01-01

An active role in modifying the earth's climate is suggested for low cloudiness over the circumarctic oceans. Such cloudiness, linked to the spatial differences in ocean surface temperatures, was studied. The temporal variations from year to year of ocean temperature patterns can be pronounced and therefore, the low cloudiness over this region should also show strong temporal variations, affecting the albedo of the earth and therefore the climate. Photographs are included.

Tannat grape composition responses to spatial variability of temperature in an Uruguay's coastal wine region

NASA Astrophysics Data System (ADS)

Fourment, Mercedes; Ferrer, Milka; González-Neves, Gustavo; Barbeau, Gérard; Bonnardot, Valérie; Quénol, Hervé

2017-09-01

Spatial variability of temperature was studied in relation to the berry basic composition and secondary compounds of the Tannat cultivar at harvest from vineyards located in Canelones and Montevideo, the most important wine region of Uruguay. Monitoring of berries and recording of temperature were performed in 10 commercial vineyards of Tannat situated in the southern coastal wine region of the country for three vintages (2012, 2013, and 2014). Results from a multivariate correlation analysis between berry composition and temperature over the three vintages showed that (1) Tannat responses to spatial variability of temperature were different over the vintages, (2) correlations between secondary metabolites and temperature were higher than those between primary metabolites, and (3) correlation values between berry composition and climate variables increased when ripening occurred under dry conditions (below average rainfall). For a particular studied vintage (2013), temperatures explained 82.5% of the spatial variability of the berry composition. Daily thermal amplitude was found to be the most important spatial mode of variability with lower values recorded at plots nearest to the sea and more exposed to La Plata River. The highest levels in secondary compounds were found in berries issued from plots situated as far as 18.3 km from La Plata River. The increasing knowledge of temperature spatial variability and its impact on grape berry composition contributes to providing possible issues to adapt grapevine to climate change.

Twentieth century bipolar seesaw of the Arctic and Antarctic surface air temperatures

NASA Astrophysics Data System (ADS)

Chylek, Petr; Folland, Chris K.; Lesins, Glen; Dubey, Manvendra K.

2010-04-01

Understanding the phase relationship between climate changes in the Arctic and Antarctic regions is essential for our understanding of the dynamics of the Earth's climate system. In this paper we show that the 20th century de-trended Arctic and Antarctic temperatures vary in anti-phase seesaw pattern - when the Arctic warms the Antarctica cools and visa versa. This is the first time that a bi-polar seesaw pattern has been identified in the 20th century Arctic and Antarctic temperature records. The Arctic (Antarctic) de-trended temperatures are highly correlated (anti-correlated) with the Atlantic Multi-decadal Oscillation (AMO) index suggesting the Atlantic Ocean as a possible link between the climate variability of the Arctic and Antarctic regions. Recent accelerated warming of the Arctic results from a positive reinforcement of the linear warming trend (due to an increasing concentration of greenhouse gases and other possible forcings) by the warming phase of the multidecadal climate variability (due to fluctuations of the Atlantic Ocean circulation).

Understanding Climate Variability of Urban Ecosystems Through the Lens of Citizen Science

NASA Astrophysics Data System (ADS)

Ripplinger, J.; Jenerette, D.; Wang, J.; Chandler, M.; Ge, C.; Koutzoukis, S.

2017-12-01

The Los Angeles megacity is vulnerable to climate warming - a process that locally exacerbates the urban heat island effect as it intensifies with size and density of the built-up area. We know that large-scale drivers play a role, but in order to understand local-scale climate variation, more research is needed on the biophysical and sociocultural processes driving the urban climate system. In this study, we work with citizen scientists to deploy a high-density network of microsensors across a climate gradient to characterize geographic variation in neighborhood meso- and micro-climates. This research asks: How do urbanization, global climate, and vegetation interact across multiple scales to affect local-scale experiences of temperature? Additionally, citizen scientist-led efforts generated research questions focused on examining microclimatic differences among yard groundcover types (rock mulch vs. lawn vs. artificial turf) and also on variation in temperature related to tree cover. Combining sensor measurements with Weather Research and Forecasting (WRF) spatial models and satellite-based temperature, we estimate spatially-explicit maps of land surface temperature and air temperature to illustrate the substantial difference between surface and air urban heat island intensities and the variable degree of coupling between land surface and air temperature in urban areas. Our results show a strong coupling between air temperature variation and landcover for neighborhoods, with significant detectable signatures from tree cover and impervious surface. Temperature covaried most strongly with urbanization intensity at nighttime during peak summer season, when daily mean air temperature ranged from 12.8C to 30.4C across all groundcover types. The combined effects of neighborhood geography and vegetation determine where and how temperature and tree canopy vary within a city. This citizen science-enabled research shows how large-scale climate drivers and urbanization intensity jointly influence the nature and magnitude of coupling between air temperature and tree cover, and demonstrate how urban vegetation provides an important ecosystem service in cities by decreasing the intensity of local urban heat islands.

Correlation between asthma and climate in the European Community Respiratory Health Survey.

PubMed

Verlato, Giuseppe; Calabrese, Rolando; De Marco, Roberto

2002-01-01

The European Community Respiratory Health Survey, performed during 1991-1993, found a remarkable geographical variability in the prevalence of asthma and asthma-like symptoms in individuals aged 20-44 yr. The highest values occurred in the English-speaking centers. In the present investigation, the ecological relationship between climate and symptom prevalence was evaluated in the 48 centers of the European Community Respiratory Health Survey. Meteorological variables were derived from the Global Historical Climatology Network and were averaged over an 11-yr period (i.e., 1980-1990). Respiratory symptom prevalence was directly related to temperature in the coldest month and was related inversely to the temperature in the hottest month. Warm winters and cool summers are features of oceanic climate found in most English-speaking centers of the European Community Respiratory Health Survey (i.e., England, New Zealand, and Oregon). In conclusion, climate can account for significant geographic variability in respiratory symptom prevalence.

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

PubMed

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

2016-01-01

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

Forced Atlantic Multidecadal Variability Over the Past Millennium

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

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

NASA Astrophysics Data System (ADS)

Li, Zhi; Jin, Jiming

2017-11-01

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

The Plant Foliage Projective Coverage Change over the Northern Tibetan Plateau during 1957-2009

NASA Astrophysics Data System (ADS)

Cuo, L.

2015-12-01

Northern Tibetan Plateau is the headwater of the Yellow River, the Yangtze River and the Mekong River that support billions of the population. Vegetation change will affect the regional ecosystem and water balances through the changes in biomass and evapotranspiration. Dynamic vegetation growth is determined by physiological, morphological, bioclimatic and phenological properties. These properties are affected by climate variables such as air temperature, precipitation, soil temperature and concentration of CO2, etc. Due to climate change, some parts of the northern Tibetan Plateau are under the threat of desertification. Identifying the places of vegetation degradation and the dominant driven climatic factors will help mitigate the climate change impacts on ecosystem and water resources in this region. In this study, the changes of foliage projective coverages (FPCs) of various plant functional types (PFTs) existed in the northern Tibetan Plateau and the responses of FPCs to the four climate variables over 1957-2009 are examined. The dominant factors among the four climate variables are also identified. The Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM) is modified and used for the investigation. The modified LPJ-DGVM can better account for soil temperature in the top 0.4-m depth where vegetation root concentrates over the northern Tibetan Plateau. The modified model is evaluated by using monthly and annual soil temperature observed at stations across the region, and the eco-geographic maps that describe plant types and spatial distributions developed from field surveys and satellite images for this region.

Intercomparison of model response and internal variability across climate model ensembles

NASA Astrophysics Data System (ADS)

Kumar, Devashish; Ganguly, Auroop R.

2017-10-01

Characterization of climate uncertainty at regional scales over near-term planning horizons (0-30 years) is crucial for climate adaptation. Climate internal variability (CIV) dominates climate uncertainty over decadal prediction horizons at stakeholders' scales (regional to local). In the literature, CIV has been characterized indirectly using projections of climate change from multi-model ensembles (MME) instead of directly using projections from multiple initial condition ensembles (MICE), primarily because adequate number of initial condition (IC) runs were not available for any climate model. Nevertheless, the recent availability of significant number of IC runs from one climate model allows for the first time to characterize CIV directly from climate model projections and perform a sensitivity analysis to study the dominance of CIV compared to model response variability (MRV). Here, we measure relative agreement (a dimensionless number with values ranging between 0 and 1, inclusive; a high value indicates less variability and vice versa) among MME and MICE and find that CIV is lower than MRV for all projection time horizons and spatial resolutions for precipitation and temperature. However, CIV exhibits greater dominance over MRV for seasonal and annual mean precipitation at higher latitudes where signals of climate change are expected to emerge sooner. Furthermore, precipitation exhibits large uncertainties and a rapid decline in relative agreement from global to continental, regional, or local scales for MICE compared to MME. The fractional contribution of uncertainty due to CIV is invariant for precipitation and decreases for temperature as lead time progresses towards the end of the century.

Climate-change impact on the 20th-century relationship between the Southern Annular Mode and global mean temperature

PubMed Central

Wang, Guojian; Cai, Wenju

2013-01-01

The positive phase of the El Niño-Southern Oscillation (ENSO) increases global mean temperature, and contributes to a negative phase of the Southern Annular Mode (SAM), the dominant mode of climate variability in the Southern Hemisphere. This interannual relationship of a high global mean temperature associated with a negative SAM, however, is opposite to the relationship between their trends under greenhouse warming. We show that over much of the 20th century this relationship undergoes multidecadal fluctuations depending on the intensity of ENSO. During the period 1925–1955, subdued ENSO activities weakened the relationship. However, a similar weakening has occurred since the late 1970s despite the strong ENSO. We demonstrate that this recent weakening is induced by climate change in the Southern Hemisphere. Our result highlights a rare situation in which climate change signals emerge against an opposing property of interannual variability, underscoring the robustness of the recent climate change. PMID:23784087

Local-scale spatial modelling for interpolating climatic temperature variables to predict agricultural plant suitability

NASA Astrophysics Data System (ADS)

Webb, Mathew A.; Hall, Andrew; Kidd, Darren; Minansy, Budiman

2016-05-01

Assessment of local spatial climatic variability is important in the planning of planting locations for horticultural crops. This study investigated three regression-based calibration methods (i.e. traditional versus two optimized methods) to relate short-term 12-month data series from 170 temperature loggers and 4 weather station sites with data series from nearby long-term Australian Bureau of Meteorology climate stations. The techniques trialled to interpolate climatic temperature variables, such as frost risk, growing degree days (GDDs) and chill hours, were regression kriging (RK), regression trees (RTs) and random forests (RFs). All three calibration methods produced accurate results, with the RK-based calibration method delivering the most accurate validation measures: coefficients of determination ( R 2) of 0.92, 0.97 and 0.95 and root-mean-square errors of 1.30, 0.80 and 1.31 °C, for daily minimum, daily maximum and hourly temperatures, respectively. Compared with the traditional method of calibration using direct linear regression between short-term and long-term stations, the RK-based calibration method improved R 2 and reduced root-mean-square error (RMSE) by at least 5 % and 0.47 °C for daily minimum temperature, 1 % and 0.23 °C for daily maximum temperature and 3 % and 0.33 °C for hourly temperature. Spatial modelling indicated insignificant differences between the interpolation methods, with the RK technique tending to be the slightly better method due to the high degree of spatial autocorrelation between logger sites.

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

PubMed Central

Reyer, C.; Leuzinger, S.; Rammig, A.; Wolf, A.; Bartholomeus, R. P.; Bonfante, A.; de Lorenzi, F.; Dury, M.; Gloning, P.; Abou Jaoudé, R.; Klein, T.; Kuster, T. M.; Martins, M.; Niedrist, G.; Riccardi, M.; Wohlfahrt, G.; de Angelis, P.; de Dato, G.; François, L.; Menzel, A.; Pereira, M.

2013-01-01

We review observational, experimental and model results on how plants respond to extreme climatic conditions induced by changing climatic variability. Distinguishing between impacts of changing mean climatic conditions and changing climatic variability on terrestrial ecosystems is generally underrated in current studies. The goals of our review are thus (1) to identify plant processes that are vulnerable to changes in the variability of climatic variables rather than to changes in their mean, and (2) to depict/evaluate available study designs to quantify responses of plants to changing climatic variability. We find that phenology is largely affected by changing mean climate but also that impacts of climatic variability are much less studied but potentially damaging. We note that plant water relations seem to be very vulnerable to extremes driven by changes in temperature and precipitation and that heatwaves and flooding have stronger impacts on physiological processes than changing mean climate. Moreover, interacting phenological and physiological processes are likely to further complicate plant responses to changing climatic variability. Phenological and physiological processes and their interactions culminate in even more sophisticated responses to changing mean climate and climatic variability at the species and community level. Generally, observational studies are well suited to study plant responses to changing mean climate, but less suitable to gain a mechanistic understanding of plant responses to climatic variability. Experiments seem best suited to simulate extreme events. In models, temporal resolution and model structure are crucial to capture plant responses to changing climatic variability. We highlight that a combination of experimental, observational and /or modeling studies have the potential to overcome important caveats of the respective individual approaches. PMID:23504722

Tropical Pacific Mean State and ENSO Variability across Marine Isotope Stage 3

NASA Astrophysics Data System (ADS)

Hertzberg, J. E.; Schmidt, M. W.; Marcantonio, F.; Bianchi, T. S.

2017-12-01

The El Niño/Southern Oscillation (ENSO) phenomenon is the largest natural interannual signal in the Earth's climate system and has widespread effects on global climate that impact millions of people worldwide. A series of recent research studies predict an increase in the frequency of extreme El Niño and La Niña events as Earth's climate continues to warm. In order for climate scientists to forecast how ENSO will evolve in response to global warming, it is necessary to have accurate, comprehensive records of how the system has naturally changed in the past, especially across past abrupt warming events. Nevertheless, there remains significant uncertainty about past changes in tropical Pacific climate and how ENSO variability relates to the millennial-scale warming events of the last ice age. This study aims to reconstruct changes in the tropical Pacific mean state and ENSO variability across Marine Isotope Stage 3 from a sediment core recovered from the Eastern Equatorial Pacific cold tongue (MV1014-02-17JC, 0°10.8' S, 85°52.0' W, 2846 m water depth). In this region, thermocline temperatures are significantly correlated to ENSO variability - thus, we analyzed Mg/Ca ratios in the thermocline dwelling foraminifera Neogloboquadrina dutertrei as a proxy for thermocline temperatures in the past. Bulk ( 50 tests/sample) foraminifera Mg/Ca temperatures are used to reconstruct long-term variability in the mean state, while single shell ( 1 test/sample, 60 samples) Mg/Ca analyses are used to assess thermocline temperature variance. Based on our refined age model, we find that thermocline temperature increases of up to 3.5°C occur in-step with interstadial warming events recorded in Greenland ice cores. Cooler thermocline temperatures prevail during stadial intervals and Heinrich Events. This suggests that interstadials were more El-Niño like, while stadials and Heinrich Events were more La-Niña like. These temperature changes are compared to new records of dust flux, export productivity, and bottom-water oxygenation measured in the same core. We will also present single shell Mg/Ca results for an interstadial, stadial, and Heinrich Event interval.

Emergent constraint on equilibrium climate sensitivity from global temperature variability.

PubMed

Cox, Peter M; Huntingford, Chris; Williamson, Mark S

2018-01-17

Equilibrium climate sensitivity (ECS) remains one of the most important unknowns in climate change science. ECS is defined as the global mean warming that would occur if the atmospheric carbon dioxide (CO 2 ) concentration were instantly doubled and the climate were then brought to equilibrium with that new level of CO 2 . Despite its rather idealized definition, ECS has continuing relevance for international climate change agreements, which are often framed in terms of stabilization of global warming relative to the pre-industrial climate. However, the 'likely' range of ECS as stated by the Intergovernmental Panel on Climate Change (IPCC) has remained at 1.5-4.5 degrees Celsius for more than 25 years. The possibility of a value of ECS towards the upper end of this range reduces the feasibility of avoiding 2 degrees Celsius of global warming, as required by the Paris Agreement. Here we present a new emergent constraint on ECS that yields a central estimate of 2.8 degrees Celsius with 66 per cent confidence limits (equivalent to the IPCC 'likely' range) of 2.2-3.4 degrees Celsius. Our approach is to focus on the variability of temperature about long-term historical warming, rather than on the warming trend itself. We use an ensemble of climate models to define an emergent relationship between ECS and a theoretically informed metric of global temperature variability. This metric of variability can also be calculated from observational records of global warming, which enables tighter constraints to be placed on ECS, reducing the probability of ECS being less than 1.5 degrees Celsius to less than 3 per cent, and the probability of ECS exceeding 4.5 degrees Celsius to less than 1 per cent.

Quantifying Tropical Glacier Mass Balance Sensitivity to Climate Change Through Regional-Scale Modeling and The Randolph Glacier Inventory

NASA Astrophysics Data System (ADS)

Malone, A.

2017-12-01

Quantifying mass balance sensitivity to climate change is essential for forecasting glacier evolution and deciphering climate signals embedded in archives of past glacier changes. Ideally, these quantifications result from decades of field measurement, remote sensing, and a hierarchy modeling approach, but in data-sparse regions, such as the Himalayas and tropical Andes, regional-scale modeling rooted in first principles provides a first-order picture. Previous regional-scaling modeling studies have applied a surface energy and mass balance approach in order to quantify equilibrium line altitude sensitivity to climate change. In this study, an expanded regional-scale surface energy and mass balance model is implemented to quantify glacier-wide mass balance sensitivity to climate change for tropical Andean glaciers. Data from the Randolph Glacier Inventory are incorporated, and additional physical processes are included, such as a dynamic albedo and cloud-dependent atmospheric emissivity. The model output agrees well with the limited mass balance records for tropical Andean glaciers. The dominant climate variables driving interannual mass balance variability differ depending on the climate setting. For wet tropical glaciers (annual precipitation >0.75 m y-1), temperature is the dominant climate variable. Different hypotheses for the processes linking wet tropical glacier mass balance variability to temperature are evaluated. The results support the hypothesis that glacier-wide mass balance on wet tropical glaciers is largely dominated by processes at the lowest elevation where temperature plays a leading role in energy exchanges. This research also highlights the transient nature of wet tropical glaciers - the vast majority of tropical glaciers and a vital regional water resource - in an anthropogenic warming world.

Emergent constraint on equilibrium climate sensitivity from global temperature variability

NASA Astrophysics Data System (ADS)

Cox, Peter M.; Huntingford, Chris; Williamson, Mark S.

2018-01-01

Equilibrium climate sensitivity (ECS) remains one of the most important unknowns in climate change science. ECS is defined as the global mean warming that would occur if the atmospheric carbon dioxide (CO2) concentration were instantly doubled and the climate were then brought to equilibrium with that new level of CO2. Despite its rather idealized definition, ECS has continuing relevance for international climate change agreements, which are often framed in terms of stabilization of global warming relative to the pre-industrial climate. However, the ‘likely’ range of ECS as stated by the Intergovernmental Panel on Climate Change (IPCC) has remained at 1.5-4.5 degrees Celsius for more than 25 years. The possibility of a value of ECS towards the upper end of this range reduces the feasibility of avoiding 2 degrees Celsius of global warming, as required by the Paris Agreement. Here we present a new emergent constraint on ECS that yields a central estimate of 2.8 degrees Celsius with 66 per cent confidence limits (equivalent to the IPCC ‘likely’ range) of 2.2-3.4 degrees Celsius. Our approach is to focus on the variability of temperature about long-term historical warming, rather than on the warming trend itself. We use an ensemble of climate models to define an emergent relationship between ECS and a theoretically informed metric of global temperature variability. This metric of variability can also be calculated from observational records of global warming, which enables tighter constraints to be placed on ECS, reducing the probability of ECS being less than 1.5 degrees Celsius to less than 3 per cent, and the probability of ECS exceeding 4.5 degrees Celsius to less than 1 per cent.

Quantitative Assessment of Antarctic Climate Variability and Change

NASA Astrophysics Data System (ADS)

Ordonez, A.; Schneider, D. P.

2013-12-01

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

Collaborative Research: Process-Resolving Decomposition of the Global Temperature Response to Modes of Low Frequency Variability in a Changing Climate

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

Deng, Yi

2014-11-24

DOE-GTRC-05596 11/24/2104 Collaborative Research: Process-Resolving Decomposition of the Global Temperature Response to Modes of Low Frequency Variability in a Changing Climate PI: Dr. Yi Deng (PI) School of Earth and Atmospheric Sciences Georgia Institute of Technology 404-385-1821, yi.deng@eas.gatech.edu El Niño-Southern Oscillation (ENSO) and Annular Modes (AMs) represent respectively the most important modes of low frequency variability in the tropical and extratropical circulations. The projection of future changes in the ENSO and AM variability, however, remains highly uncertain with the state-of-the-science climate models. This project conducted a process-resolving, quantitative evaluations of the ENSO and AM variability in the modern reanalysis observationsmore » and in climate model simulations. The goal is to identify and understand the sources of uncertainty and biases in models’ representation of ENSO and AM variability. Using a feedback analysis method originally formulated by one of the collaborative PIs, we partitioned the 3D atmospheric temperature anomalies and surface temperature anomalies associated with ENSO and AM variability into components linked to 1) radiation-related thermodynamic processes such as cloud and water vapor feedbacks, 2) local dynamical processes including convection and turbulent/diffusive energy transfer and 3) non-local dynamical processes such as the horizontal energy transport in the oceans and atmosphere. In the past 4 years, the research conducted at Georgia Tech under the support of this project has led to 15 peer-reviewed publications and 9 conference/workshop presentations. Two graduate students and one postdoctoral fellow also received research training through participating the project activities. This final technical report summarizes key scientific discoveries we made and provides also a list of all publications and conference presentations resulted from research activities at Georgia Tech. The main findings include: 1) the distinctly different roles played by atmospheric dynamical processes in establishing surface temperature response to ENSO at tropics and extratropics (i.e., atmospheric dynamics disperses energy out of tropics during ENSO warm events and modulate surface temperature at mid-, high-latitudes through controlling downward longwave radiation); 2) the representations of ENSO-related temperature response in climate models fail to converge at the process-level particularly over extratropics (i.e., models produce the right temperature responses to ENSO but with wrong reasons); 3) water vapor feedback contributes substantially to the temperature anomalies found over U.S. during different phases of the Northern Annular Mode (NAM), which adds new insight to the traditional picture that cold/warm advective processes are the main drivers of local temperature responses to the NAM; 4) the overall land surface temperature biases in the latest NCAR model (CESM1) are caused by biases in surface albedo while the surface temperature biases over ocean are related to multiple factors including biases in model albedo, cloud and oceanic dynamics, and the temperature biases over different ocean basins are also induced by different process biases. These results provide a detailed guidance for process-level model turning and improvement, and thus contribute directly to the overall goal of reducing model uncertainty in projecting future changes in the Earth’s climate system, especially in the ENSO and AM variability.« less

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

NASA Astrophysics Data System (ADS)

Williams, P.

2015-12-01

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

Can unforced radiative variability explain the "hiatus"?

NASA Astrophysics Data System (ADS)

Donohoe, A.

2016-02-01

The paradox of the "hiatus" is characterized as a decade long period over which global mean surface temperature remained relatively constant even though greenhouse forcing forcing is believed to have been positive and increasing. Explanations of the hiatus have focused on two primary lines of thought: 1. There was a net radiative imbalance at the top of atmosphere (TOA) but this energy input was stored in the ocean without increasing surface temperature or 2. There was no radiative imbalance at the TOA because the greenhouse forcing was offset by other climate forcings. Here, we explore a third hypothesis: that there was no TOA radiative imbalance over the decade due to unforced, natural modes of radiative variability that are unrelated to global mean temperature. Is it possible that the Earth could emit enough radiation to offset greenhouse forcing without increasing its temperature due to internal modes of climate variability? Global mean TOA energy imbalance is estimated to be 0.65 W m-2 as determined from the long term change in ocean heat content - where the majority of the energy imbalance is stored. Therefore, in order to offset this TOA energy imbalance natural modes of radiative variability with amplitudes of order 0.5 W m-2 at the decadal timescale are required. We demonstrate that unforced coupled climate models have global mean radiative variability of the required magnitude (2 standard deviations of 0.57 W m-2 in the inter-model mean) and that the vast majority (>90%) of this variability is unrelated to surface temperature radiative feedbacks. However, much of this variability is at shorter (monthly and annual) timescales and does not persist from year to year making the possibility of a decade long natural interruption of the energy accumulation in the climate system unlikely due to natural radiative variability alone given the magnitude of the greenhouse forcing on Earth. Comparison to observed satellite data suggest the models capture the magnitude (2 sigma = 0.61 W m-2) and mechanisms of internal radiative variability but we cannot exclude the possibility of low frequency modes of variability with significant magnitude given the limited length of the satellite record.

Interactions Between Mineral Surfaces, Substrates, Enzymes, and Microbes Result in Hysteretic Temperature Sensitivities and Microbial Carbon Use Efficiencies and Weaker Predicted Carbon-Climate Feedbacks

NASA Astrophysics Data System (ADS)

Riley, W. J.; Tang, J.

2014-12-01

We hypothesize that the large observed variability in decomposition temperature sensitivity and carbon use efficiency arises from interactions between temperature, microbial biogeochemistry, and mineral surface sorptive reactions. To test this hypothesis, we developed a numerical model that integrates the Dynamic Energy Budget concept for microbial physiology, microbial trait-based community structure and competition, process-specific thermodynamically ­­based temperature sensitivity, a non-linear mineral sorption isotherm, and enzyme dynamics. We show, because mineral surfaces interact with substrates, enzymes, and microbes, both temperature sensitivity and microbial carbon use efficiency are hysteretic and highly variable. Further, by mimicking the traditional approach to interpreting soil incubation observations, we demonstrate that the conventional labile and recalcitrant substrate characterization for temperature sensitivity is flawed. In a 4 K temperature perturbation experiment, our fully dynamic model predicted more variable but weaker carbon-climate feedbacks than did the static temperature sensitivity and carbon use efficiency model when forced with yearly, daily, and hourly variable temperatures. These results imply that current earth system models likely over-estimate the response of soil carbon stocks to global warming.

Hydrologic and temperature variability at Lake Titicaca over the past 50,000 years

NASA Astrophysics Data System (ADS)

Fornace, K.; Shanahan, T. M.; Sylva, S.; Ossolinski, J.; Baker, P. A.; Fritz, S. C.; Hughen, K. A.

2011-12-01

The Bolivian Altiplano has been the focus of many paleoclimate studies due to the important role it plays in the South American climate system. Although the timing of climate shifts in this region is relatively well known, the magnitudes of hydrologic versus temperature changes remain poorly quantified. Here we apply hydrogen isotope analysis (δD) of terrestrial leaf waxes and the TEX86 temperature proxy in sediments from Lake Titicaca to reconstruct hydrologic and temperature variability over the past 50,000 years. Our record reveals that the Altiplano underwent a major climate shift during the last deglaciation, reflected in a ~70-80% enrichment in leaf wax δD at the onset of the Holocene. Using the global isotope-temperature relationship for meteoric water, only 25-40% of this enrichment can be explained by the 4-5°C deglacial warming shown by the TEX86 proxy, indicating that precipitation was significantly reduced (and evaporation/evapotranspiration increased) during the Holocene. Further, the timing of these hydrologic and temperature changes was asynchronous during the transition from a cold and wet glacial state to a warm and dry Holocene. The major hydrologic shift recorded by leaf wax δD occurred around ~11-12 ka, consistent with Northern Hemisphere deglacial patterns, whereas TEX86 data indicate that rapid warming began much earlier, more typical of a Southern Hemisphere deglacial pattern. Within the late glacial and Holocene mean climate states, however, there is evidence of synchronous hydrologic and temperature variability on millennial timescales. This study demonstrates that climate on the Altiplano was controlled by the interaction of local and remote forcing on a range of timescales.

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

USGS Publications Warehouse

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

2015-01-01

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

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

PubMed

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

2015-09-01

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

Estimating the impact of internal climate variability on ice sheet model simulations

NASA Astrophysics Data System (ADS)

Tsai, C. Y.; Forest, C. E.; Pollard, D.

2016-12-01

Rising sea level threatens human societies and coastal habitats and melting ice sheets are a major contributor to sea level rise (SLR). Thus, understanding uncertainty of both forcing and variability within the climate system is essential for assessing long-term risk of SLR given their impact on ice sheet evolution. The predictability of polar climate is limited by uncertainties from the given forcing, the climate model response to this forcing, and the internal variability from feedbacks within the fully coupled climate system. Among those sources of uncertainty, the impact of internal climate variability on ice sheet changes has not yet been robustly assessed. Here we investigate how internal variability affects ice sheet projections using climate fields from two Community Earth System Model (CESM) large-ensemble (LE) experiments to force a three-dimensional ice sheet model. Each ensemble member in an LE experiment undergoes the same external forcings but with unique initial conditions. We find that for both LEs, 2m air temperature variability over Greenland ice sheet (GrIS) can lead to significantly different ice sheet responses. Our results show that the internal variability from two fully coupled CESM LEs can cause about 25 35 mm differences of GrIS's contribution to SLR in 2100 compared to present day (about 20% of the total change), and 100m differences of SLR in 2300. Moreover, only using ensemble-mean climate fields as the forcing in ice sheet model can significantly underestimate the melt of GrIS. As the Arctic region becomes warmer, the role of internal variability is critical given the complex nonlinear interactions between surface temperature and ice sheet. Our results demonstrate that internal variability from coupled atmosphere-ocean general circulation model can affect ice sheet simulations and the resulting sea-level projections. This study highlights an urgent need to reassess associated uncertainties of projecting ice sheet loss over the next few centuries to obtain robust estimates of the contribution of ice sheet melt to SLR.

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

PubMed

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

2013-01-01

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

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

PubMed Central

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

2013-01-01

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

Climate variability and changes in the agricultural cycle in the Czech Lands from the sixteenth century to the present

NASA Astrophysics Data System (ADS)

Brázdil, Rudolf; Možný, Martin; Klír, Tomáš; Řezníčková, Ladislava; Trnka, Miroslav; Dobrovolný, Petr; Kotyza, Oldřich

2018-05-01

This contribution analyses the influence of long-term climate variability on changes in the agricultural cycle in the Czech Lands over the course of the past five centuries. Series of crop- and grape-harvest (for wine) dates were compiled from rich documentary evidence for the periods of 1517-1542, 1561-1622, 1770-1815, 1871-1910 and 1971-2010. Two model areas were selected: the Louny region in north-west Bohemia and the Elbe region in central Bohemia. Fluctuations in selected agricultural series are compared with those expressed in temperature, precipitation and Standardised Precipitation Evapotranspiration Index (SPEI) series for various combinations of months. The basic statistics for the agricultural series are presented, and these are correlated with climatic variables. The earliest starts for harvests occurred in the recent 1971-2010 period and the 1517-1542 period. Harvest dates were comparatively delayed in the three remaining periods. Air temperature, also combined with the drought effect as expressed by SPEI, played a significant role in the agricultural cycle in all periods analysed except 1871-1910, in which temperatures were notably dominant as quite wet patterns prevailed. Summer precipitation played a significant role in the first three periods analysed. Correlation coefficients of agricultural series with temperatures indicate increasing weight for this factor over the course of the centuries. Possible effects of uncertainties in agricultural and climatic data in the results obtained are discussed, as well as the relationship of the agricultural cycle to climate variables and its broader context.

A Pathway-based Approach to Predicting Interactions between Chemical and Non-chemical Stressors: Applications to Global Climate Change

EPA Science Inventory

A variety of environmental variables influenced by global climate change (GCC) can directly or indirectly affect the health of organisms. These variables may include temperature, salinity, pH, and penetration of ultraviolet radiation (UVR) in aquatic environments, and water shor...

Evaluation of climate variability on drought occurrence in an agricultural watershed

USDA-ARS?s Scientific Manuscript database

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

Predicting drought in an agricultural watershed given climate variability

USDA-ARS?s Scientific Manuscript database

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

Volcanic influence on centennial to millennial Holocene Greenland temperature change.

PubMed

Kobashi, Takuro; Menviel, Laurie; Jeltsch-Thömmes, Aurich; Vinther, Bo M; Box, Jason E; Muscheler, Raimund; Nakaegawa, Toshiyuki; Pfister, Patrik L; Döring, Michael; Leuenberger, Markus; Wanner, Heinz; Ohmura, Atsumu

2017-05-03

Solar variability has been hypothesized to be a major driver of North Atlantic millennial-scale climate variations through the Holocene along with orbitally induced insolation change. However, another important climate driver, volcanic forcing has generally been underestimated prior to the past 2,500 years partly owing to the lack of proper proxy temperature records. Here, we reconstruct seasonally unbiased and physically constrained Greenland Summit temperatures over the Holocene using argon and nitrogen isotopes within trapped air in a Greenland ice core (GISP2). We show that a series of volcanic eruptions through the Holocene played an important role in driving centennial to millennial-scale temperature changes in Greenland. The reconstructed Greenland temperature exhibits significant millennial correlations with K + and Na + ions in the GISP2 ice core (proxies for atmospheric circulation patterns), and δ 18 O of Oman and Chinese Dongge cave stalagmites (proxies for monsoon activity), indicating that the reconstructed temperature contains hemispheric signals. Climate model simulations forced with the volcanic forcing further suggest that a series of large volcanic eruptions induced hemispheric-wide centennial to millennial-scale variability through ocean/sea-ice feedbacks. Therefore, we conclude that volcanic activity played a critical role in driving centennial to millennial-scale Holocene temperature variability in Greenland and likely beyond.

Malaria incidence trends and their association with climatic variables in rural Gwanda, Zimbabwe, 2005-2015.

PubMed

Gunda, Resign; Chimbari, Moses John; Shamu, Shepherd; Sartorius, Benn; Mukaratirwa, Samson

2017-09-30

Malaria is a public health problem in Zimbabwe. Although many studies have indicated that climate change may influence the distribution of malaria, there is paucity of information on its trends and association with climatic variables in Zimbabwe. To address this shortfall, the trends of malaria incidence and its interaction with climatic variables in rural Gwanda, Zimbabwe for the period January 2005 to April 2015 was assessed. Retrospective data analysis of reported cases of malaria in three selected Gwanda district rural wards (Buvuma, Ntalale and Selonga) was carried out. Data on malaria cases was collected from the district health information system and ward clinics while data on precipitation and temperature were obtained from the climate hazards group infrared precipitation with station data (CHIRPS) database and the moderate resolution imaging spectro-radiometer (MODIS) satellite data, respectively. Distributed lag non-linear models (DLNLM) were used to determine the temporal lagged association between monthly malaria incidence and monthly climatic variables. There were 246 confirmed malaria cases in the three wards with a mean incidence of 0.16/1000 population/month. The majority of malaria cases (95%) occurred in the > 5 years age category. The results showed no correlation between trends of clinical malaria (unconfirmed) and confirmed malaria cases in all the three study wards. There was a significant association between malaria incidence and the climatic variables in Buvuma and Selonga wards at specific lag periods. In Ntalale ward, only precipitation (1- and 3-month lag) and mean temperature (1- and 2-month lag) were significantly associated with incidence at specific lag periods (p < 0.05). DLNM results suggest a key risk period in current month, based on key climatic conditions in the 1-4 month period prior. As the period of high malaria risk is associated with precipitation and temperature at 1-4 month prior in a seasonal cycle, intensifying malaria control activities over this period will likely contribute to lowering the seasonal malaria incidence.

Marine assemblages respond rapidly to winter climate variability.

PubMed

Morley, James W; Batt, Ryan D; Pinsky, Malin L

2017-07-01

Even species within the same assemblage have varied responses to climate change, and there is a poor understanding for why some taxa are more sensitive to climate than others. In addition, multiple mechanisms can drive species' responses, and responses may be specific to certain life stages or times of year. To test how marine species respond to climate variability, we analyzed 73 diverse taxa off the southeast US coast in 26 years of scientific trawl survey data and determined how changes in distribution and biomass relate to temperature. We found that winter temperatures were particularly useful for explaining interannual variation in species' distribution and biomass, although the direction and magnitude of the response varied among species from strongly negative, to little response, to strongly positive. Across species, the response to winter temperature varied greatly, with much of this variation being explained by thermal preference. A separate analysis of annual commercial fishery landings revealed that winter temperatures may also impact several important fisheries in the southeast United States. Based on the life stages of the species surveyed, winter temperature appears to act through overwinter mortality of juveniles or as a cue for migration timing. We predict that this assemblage will be responsive to projected increases in temperature and that winter temperature may be broadly important for species relationships with climate on a global scale. © The Authors Global Change Biology Published by John Wiley & Sons Ltd.

Climate change and dead zones.

PubMed

Altieri, Andrew H; Gedan, Keryn B

2015-04-01

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

Enhancing seasonal climate prediction capacity for the Pacific countries

NASA Astrophysics Data System (ADS)

Kuleshov, Y.; Jones, D.; Hendon, H.; Charles, A.; Cottrill, A.; Lim, E.-P.; Langford, S.; de Wit, R.; Shelton, K.

2012-04-01

Seasonal and inter-annual climate variability is a major factor in determining the vulnerability of many Pacific Island Countries to climate change and there is need to improve weekly to seasonal range climate prediction capabilities beyond what is currently available from statistical models. In the seasonal climate prediction project under the Australian Government's Pacific Adaptation Strategy Assistance Program (PASAP), we describe a comprehensive project to strengthen the climate prediction capacities in National Meteorological Services in 14 Pacific Island Countries and East Timor. The intent is particularly to reduce the vulnerability of current services to a changing climate, and improve the overall level of information available assist with managing climate variability. Statistical models cannot account for aspects of climate variability and change that are not represented in the historical record. In contrast, dynamical physics-based models implicitly include the effects of a changing climate whatever its character or cause and can predict outcomes not seen previously. The transition from a statistical to a dynamical prediction system provides more valuable and applicable climate information to a wide range of climate sensitive sectors throughout the countries of the Pacific region. In this project, we have developed seasonal climate outlooks which are based upon the current dynamical model POAMA (Predictive Ocean-Atmosphere Model for Australia) seasonal forecast system. At present, meteorological services of the Pacific Island Countries largely employ statistical models for seasonal outlooks. Outcomes of the PASAP project enhanced capabilities of the Pacific Island Countries in seasonal prediction providing National Meteorological Services with an additional tool to analyse meteorological variables such as sea surface temperatures, air temperature, pressure and rainfall using POAMA outputs and prepare more accurate seasonal climate outlooks.

The paradox of cooling streams in a warming world: regional climate trends do not parallel variable local trends in stream temperature in the Pacific continental United States

Treesearch

Ivan Arismendi; Sherri L. Johnson; Jason B. Dunham; Roy Haggerty

2012-01-01

Temperature is a fundamentally important driver of ecosystem processes in streams. Recent warming of terrestrial climates around the globe has motivated concern about consequent increases in stream temperature. More specifically, observed trends of increasing air temperature and declining stream flow are widely believed to result in corresponding increases in stream...

Downscaling future climate projections to the watershed scale: A north San Francisco Bay estuary case study

USGS Publications Warehouse

Micheli, Elisabeth; Flint, Lorraine; Flint, Alan; Weiss, Stuart; Kennedy, Morgan

2012-01-01

We modeled the hydrology of basins draining into the northern portion of the San Francisco Bay Estuary (North San Pablo Bay) using a regional water balance model (Basin Characterization Model; BCM) to estimate potential effects of climate change at the watershed scale. The BCM calculates water balance components, including runoff, recharge, evapotranspiration, soil moisture, and stream flow, based on climate, topography, soils and underlying geology, and the solar-driven energy balance. We downscaled historical and projected precipitation and air temperature values derived from weather stations and global General Circulation Models (GCMs) to a spatial scale of 270 m. We then used the BCM to estimate hydrologic response to climate change for four scenarios spanning this century (2000–2100). Historical climate patterns show that Marin’s coastal regions are typically on the order of 2 °C cooler and receive five percent more precipitation compared to the inland valleys of Sonoma and Napa because of marine influences and local topography. By the last 30 years of this century, North Bay scenarios project average minimum temperatures to increase by 1.0 °C to 3.1 °C and average maximum temperatures to increase by 2.1 °C to 3.4 °C (in comparison to conditions experienced over the last 30 years, 1981–2010). Precipitation projections for the 21st century vary between GCMs (ranging from 2 to 15% wetter than the 20th-century average). Temperature forcing increases the variability of modeled runoff, recharge, and stream discharge, and shifts hydrologic cycle timing. For both high- and low-rainfall scenarios, by the close of this century warming is projected to amplify late-season climatic water deficit (a measure of drought stress on soils) by 8% to 21%. Hydrologic variability within a single river basin demonstrated at the scale of subwatersheds may prove an important consideration for water managers in the face of climate change. Our results suggest that in arid environments characterized by high topo-climatic variability, land and water managers need indicators of local watershed hydrology response to complement regional temperature and precipitation estimates. Our results also suggest that temperature forcing may generate greater drought stress affecting soils and stream flows than can be estimated by variability in precipitation alone.

Raised temperatures over the Kericho tea estates: revisiting the climate in the East African highlands malaria debate.

PubMed

Omumbo, Judith A; Lyon, Bradfield; Waweru, Samuel M; Connor, Stephen J; Thomson, Madeleine C

2011-01-17

Whether or not observed increases in malaria incidence in the Kenyan Highlands during the last thirty years are associated with co-varying changes in local temperature, possibly connected to global changes in climate, has been debated for over a decade. Studies, using differing data sets and methodologies, produced conflicting results regarding the occurrence of temperature trends and their likelihood of being responsible, at least in part, for the increases in malaria incidence in the highlands of western Kenya. A time series of quality controlled daily temperature and rainfall data from Kericho, in the Kenyan Highlands, may help resolve the controversy. If significant temperature trends over the last three decades have occurred then climate should be included (along with other factors such as land use change and drug resistance) as a potential driver of the observed increases in malaria in the region. Over 30 years (1 January 1979 to 31 December 2009) of quality controlled daily observations ( > 97% complete) of maximum, minimum and mean temperature were used in the analysis of trends at Kericho meteorological station, sited in a tea growing area of Kenya's western highlands. Inhomogeneities in all the time series were identified and corrected. Linear trends were identified via a least-squares regression analysis with statistical significance assessed using a two-tailed t-test. These 'gold standard' meteorological observations were compared with spatially interpolated temperature datasets that have been developed for regional or global applications. The relationship of local climate processes with larger climate variations, including tropical sea surface temperatures (SST), and El Niño-Southern Oscillation (ENSO) was also assessed. An upward trend of ≈0.2°C/decade was observed in all three temperature variables (P < 0.01). Mean temperature variations in Kericho were associated with large-scale climate variations including tropical SST (r = 0.50; p < 0.01). Local rainfall was found to have inverse effects on minimum and maximum temperature. Three versions of a spatially interpolated temperature data set showed markedly different trends when compared with each other and with the Kericho station observations. This study presents evidence of a warming trend in observed maximum, minimum and mean temperatures at Kericho during the period 1979 to 2009 using gold standard meteorological observations. Although local factors may be contributing to these trends, the findings are consistent with variability and trends that have occurred in correlated global climate processes. Climate should therefore not be dismissed as a potential driver of observed increases in malaria seen in the region during recent decades, however its relative importance compared to other factors needs further elaboration. Climate services, pertinent to the achievement of development targets such as the Millennium Development Goals and the analysis of infectious disease in the context of climate variability and change are being developed and should increase the availability of relevant quality controlled climate data for improving development decisions. The malaria community should seize this opportunity to make their needs heard.

Temporal and spatial variability in North Carolina piedmont stream temperature

Treesearch

J.L. Boggs; G. Sun; S.G. McNulty; W. Swartley; Treasure E.; W. Summer

2009-01-01

Understanding temporal and spatial patterns of in-stream temperature can provide useful information to managing future impacts of climate change on these systems. This study will compare temporal patterns and spatial variability of headwater in-stream temperature in six catchments in the piedmont of North Carolina in two different geological regions, Carolina slate...

Amplification and dampening of soil respiration by changes in temperature variability

Treesearch

C.A. Sierra; M.E. Harmon; E.A. Thomann; S.S. Perakis; H.W. Loescher

2011-01-01

Accelerated release of carbon from soils is one of the most important feedbacks related to anthropogenically induced climate change. Studies addressing the mechanisms for soil carbon release through organic matter decomposition have focused on the effect of changes in the average temperature, with little attention to changes in temperature variability. Anthropogenic...

Quantifying the Hydrologic Effect of Climate Variability in the Lower Colorado Basin

NASA Astrophysics Data System (ADS)

Switanek, M.; Troch, P. A.

2007-12-01

Regional climate patterns are driven in large part by ocean states and associated atmospheric circulations, but modified through feedbacks from land surface conditions. The latter defines the climate elasticity of a river basin. Many regions that lie between semi-arid and semi-humid zones with seasonal rainfall, for instance, experience prolonged periods of wet and dry spells. Understanding the triggers that bring a river basin from one state (e.g. wet period of late 90s in the Colorado basin) abruptly to another state (multi-year drought initiated in 2001 to present) is what motivates the present study. Our research methodology investigates the causes of regional climate variability and its effect on hydrologic response. By correlating, using different monthly time lags, sea surface temperatures (SST) and sea level pressures (SLP) with basin averaged precipitation and surface temperature, we determine the most influential regions of the Pacific Ocean on lower Colorado climate variability. Using the most correlated data for each month, we derive precipitation and temperature distributions under similar conditions to that of the El Niño Southern Oscillation (ENSO). We compare the distributions of the climatic data, given ENSO constraints on SST and SLP, to the distributions considering non-ENSO years. Finally, we use observed stream flows and climatic data to determine the basin's climate elasticity. This allows us to quantitatively translate the predicted regional climate effects of ENSO on hydrologic response. Our presentation will use data for the Little Colorado as an example to demonstrate the procedure and produce preliminary results.

Tolerance adaptation and precipitation changes complicate latitudinal patterns of climate change impacts.

PubMed

Bonebrake, Timothy C; Mastrandrea, Michael D

2010-07-13

Global patterns of biodiversity and comparisons between tropical and temperate ecosystems have pervaded ecology from its inception. However, the urgency in understanding these global patterns has been accentuated by the threat of rapid climate change. We apply an adaptive model of environmental tolerance evolution to global climate data and climate change model projections to examine the relative impacts of climate change on different regions of the globe. Our results project more adverse impacts of warming on tropical populations due to environmental tolerance adaptation to conditions of low interannual variability in temperature. When applied to present variability and future forecasts of precipitation data, the tolerance adaptation model found large reductions in fitness predicted for populations in high-latitude northern hemisphere regions, although some tropical regions had comparable reductions in fitness. We formulated an evolutionary regional climate change index (ERCCI) to additionally incorporate the predicted changes in the interannual variability of temperature and precipitation. Based on this index, we suggest that the magnitude of climate change impacts could be much more heterogeneous across latitude than previously thought. Specifically, tropical regions are likely to be just as affected as temperate regions and, in some regions under some circumstances, possibly more so.

Collaborative Research: Process-resolving Decomposition of the Global Temperature Response to Modes of Low Frequency Variability in a Changing Climate

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

Cai, Ming; Deng, Yi

2015-02-06

El Niño-Southern Oscillation (ENSO) and Annular Modes (AMs) represent respectively the most important modes of low frequency variability in the tropical and extratropical circulations. The future projection of the ENSO and AM variability, however, remains highly uncertain with the state-of-the-art coupled general circulation models. A comprehensive understanding of the factors responsible for the inter-model discrepancies in projecting future changes in the ENSO and AM variability, in terms of multiple feedback processes involved, has yet to be achieved. The proposed research aims to identify sources of such uncertainty and establish a set of process-resolving quantitative evaluations of the existing predictions ofmore » the future ENSO and AM variability. The proposed process-resolving evaluations are based on a feedback analysis method formulated in Lu and Cai (2009), which is capable of partitioning 3D temperature anomalies/perturbations into components linked to 1) radiation-related thermodynamic processes such as cloud and water vapor feedbacks, 2) local dynamical processes including convection and turbulent/diffusive energy transfer and 3) non-local dynamical processes such as the horizontal energy transport in the oceans and atmosphere. Taking advantage of the high-resolution, multi-model ensemble products from the Coupled Model Intercomparison Project Phase 5 (CMIP5) soon to be available at the Lawrence Livermore National Lab, we will conduct a process-resolving decomposition of the global three-dimensional (3D) temperature (including SST) response to the ENSO and AM variability in the preindustrial, historical and future climate simulated by these models. Specific research tasks include 1) identifying the model-observation discrepancies in the global temperature response to ENSO and AM variability and attributing such discrepancies to specific feedback processes, 2) delineating the influence of anthropogenic radiative forcing on the key feedback processes operating on ENSO and AM variability and quantifying their relative contributions to the changes in the temperature anomalies associated with different phases of ENSO and AMs, and 3) investigating the linkages between model feedback processes that lead to inter-model differences in time-mean temperature projection and model feedback processes that cause inter-model differences in the simulated ENSO and AM temperature response. Through a thorough model-observation and inter-model comparison of the multiple energetic processes associated with ENSO and AM variability, the proposed research serves to identify key uncertainties in model representation of ENSO and AM variability, and investigate how the model uncertainty in predicting time-mean response is related to the uncertainty in predicting response of the low-frequency modes. The proposal is thus a direct response to the first topical area of the solicitation: Interaction of Climate Change and Low Frequency Modes of Natural Climate Variability. It ultimately supports the accomplishment of the BER climate science activity Long Term Measure (LTM): "Deliver improved scientific data and models about the potential response of the Earth's climate and terrestrial biosphere to increased greenhouse gas levels for policy makers to determine safe levels of greenhouse gases in the atmosphere."« less

Signal to noise quantification of regional climate projections

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

European temperature records of the past five centuries based on documentary information compared to climate simulations

NASA Astrophysics Data System (ADS)

Zorita, E.

2009-09-01

Two European temperature records for the past half-millennium, January-to-April air temperature for Stockholm (Sweden) and seasonal temperature for a Central European region, both derived from the analysis of documentary sources combined with long instrumental records, are compared with the output of forced (solar, volcanic, greenhouse gases) climate simulations with the model ECHO-G. The analysis is complemented with the long (early)-instrumental record of Central England Temperature (CET). Both approaches to study past climates (simulations and reconstructions) are burdened with uncertainties. The main objective of this comparative analysis is to identify robust features and weaknesses that may help to improve models and reconstruction methods. The results indicate a general agreement between simulations and the reconstructed Stockholm and CET records regarding the long-term temperature trend over the recent centuries, suggesting a reasonable choice of the amplitude of the solar forcing in the simulations and sensitivity of the model to the external forcing. However, the Stockholm reconstruction and the CET record also show a long and clear multi-decadal warm episode peaking around 1730, which is absent in the simulations. The uncertainties associated with the reconstruction method or with the simulated internal climate variability cannot easily explain this difference. Regarding the interannual variability, the Stockholm series displays in some periods higher amplitudes than the simulations but these differences are within the statistical uncertainty and further decrease if output from a regional model driven by the global model is used. The long-term trends in the simulations and reconstructions of the Central European temperature agree less well. The reconstructed temperature displays, for all seasons, a smaller difference between the present climate and past centuries than the simulations. Possible reasons for these differences may be related to a limitation of the traditional technique for converting documentary evidence to temperature values to capture long-term climate changes, because the documents often reflect temperatures relative to the contemporary authors' own perception of what constituted 'normal' conditions. By contrast, the simulated and reconstructed inter-annual variability is in rather good agreement.

Climate variability in China during the last millennium based on reconstructions and simulations

NASA Astrophysics Data System (ADS)

García-Bustamante, E.; Luterbacher, J.; Xoplaki, E.; Werner, J. P.; Jungclaus, J.; Zorita, E.; González-Rouco, J. F.; Fernández-Donado, L.; Hegerl, G.; Ge, Q.; Hao, Z.; Wagner, S.

2012-04-01

Multi-decadal to centennial climate variability in China during the last millennium is analysed. We compare the low frequency temperature and precipitation variations from proxy-based reconstructions and palaeo-simulations from climate models. Focusing on the regional responses to the global climate evolution is of high relevance due to the complexity of the interactions between physical mechanisms at different spatio-temporal scales and the potential severity of the derived multiple socio-economic impacts. China stands out as a particularly interesting region, not only due to its complex climatic features, ranging from the semiarid northwestern Tibetan Plateau to the tropical monsoon southeastern climates, but also because of its wealth of proxy data. However, comprehensive assessments of proxy- and model-based information about palaeo-climatic variations in China are, to our knowledge, still lacking. In addition, existing studies depict a general lack of agreement between reconstructions and model simulations with respect to the amplitude and/or occurrence of warmer/colder and wetter/drier periods during the last millennium and the magnitude of the 20th century warming trend. Furthermore, these works are mainly focused on eastern China regions that show a denser proxy data coverage. We investigate how last millennium palaeo-runs compare to independent evidences from an unusual large number of proxy reconstructions over the study area by employing state-of-the-art palaeo-simulations with multi-member ensembles from the CMIP5/PMIP3 project. This shapes an ideal frame for the evaluation of the uncertainties associated to internal and intermodel model variability. Preliminary results indicate that despite the strong regional and seasonal dependencies, temperature reconstructions in China evidence coherent variations among all regions at centennial scale, especially during the last 500 years. The spatial consistency of low frequency temperature changes is an interesting aspect and of relevance for the assessment of forced climatic responses in China. The comparison between reconstructions and simulations from climate models show that, apart from the 20th century warming trend, the variance of the reconstructed mean China temperature lies in the envelope (uncertainty range) spanned by the temperature simulations. The uncertainty arises from the internal (multi-member ensembles) and the inter-model variability. Centennial variations tend to be broadly synchronous in the reconstructions and the simulations. However, the simulations show a delay of the warm period 1000-1300 AD. This warm medieval period both in the simulations and the reconstructions is followed by cooling till 1800 AD. Based on the simulations, the recent warming is not unprecedented and is comparable to the medieval warming. Further steps of this study will address the individual contribution of anthropogenic and natural forcings on climate variability and change during the last millennium in China. We will make use of of models that provide runs including single forcings (fingerprints) for the attribution of climate variations from decadal to multi-centennial time scales. With this aim, we will implement statistical techniques for the detection of optimal signal-to-noise-ratio between external forcings and internal variability of reconstructed temperatures and precipitation. To apply these approaches the uncertainties associated with both reconstructions and simulations will be estimated. The latter will shed some light into the mechanisms behind current climate evolution and will help to constrain uncertainties in the sensitivity of model simulations to increasing CO2 scenarios of future climate change. This work will also contribute to the overall aims of the PAGES 2k initiative in Asia (http://www.pages.unibe.ch/workinggroups/2k-network)

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Unlocking the climate riddle in forested ecosystems

Treesearch

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

2012-01-01

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

The Oceanic Contribution to Atlantic Multi-Decadal Variability

NASA Astrophysics Data System (ADS)

Wills, R. C.; Armour, K.; Battisti, D. S.; Hartmann, D. L.

2017-12-01

Atlantic multi-decadal variability (AMV) is typically associated with variability in ocean heat transport (OHT) by the Atlantic Meridional Overturning Circulation (AMOC). However, recent work has cast doubt on this connection by showing that slab-ocean climate models, in which OHT cannot vary, exhibit similar variability. Here, we apply low-frequency component analysis to isolate the variability of Atlantic sea-surface temperatures (SSTs) that occurs on decadal and longer time scales. In observations and in pre-industrial control simulations of comprehensive climate models, we find that AMV is confined to the extratropics, with the strongest temperature anomalies in the North Atlantic subpolar gyre. We show that warm subpolar temperatures are associated with a strengthened AMOC, increased poleward OHT, and local heat fluxes from the ocean into the atmosphere. In contrast, the traditional index of AMV based on the basin-averaged SST anomaly shows warm temperatures preceded by heat fluxes from the atmosphere into the ocean, consistent with the atmosphere driving this variability, and shows a weak relationship with AMOC. The autocorrelation time of the basin-averaged SST index is 1 year compared to an autocorrelation time of 5 years for the variability of subpolar temperatures. This shows that multi-decadal variability of Atlantic SSTs is sustained by OHT variability associated with AMOC, while atmosphere-driven SST variability, such as exists in slab-ocean models, contributes primarily on interannual time scales.

Impacts of climate change and variability on transportation systems and infrastructure : Gulf Coast study, phase I

DOT National Transportation Integrated Search

2008-03-01

Climate affects the design, construction, safety, operations, and maintenance of transportation : infrastructure and systems. The prospect of a changing climate raises critical questions : regarding how alterations in temperature, precipitation, stor...

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Substantial large-scale feedbacks between natural aerosols and climate

NASA Astrophysics Data System (ADS)

Scott, C. E.; Arnold, S. R.; Monks, S. A.; Asmi, A.; Paasonen, P.; Spracklen, D. V.

2018-01-01

The terrestrial biosphere is an important source of natural aerosol. Natural aerosol sources alter climate, but are also strongly controlled by climate, leading to the potential for natural aerosol-climate feedbacks. Here we use a global aerosol model to make an assessment of terrestrial natural aerosol-climate feedbacks, constrained by observations of aerosol number. We find that warmer-than-average temperatures are associated with higher-than-average number concentrations of large (>100 nm diameter) particles, particularly during the summer. This relationship is well reproduced by the model and is driven by both meteorological variability and variability in natural aerosol from biogenic and landscape fire sources. We find that the calculated extratropical annual mean aerosol radiative effect (both direct and indirect) is negatively related to the observed global temperature anomaly, and is driven by a positive relationship between temperature and the emission of natural aerosol. The extratropical aerosol-climate feedback is estimated to be -0.14 W m-2 K-1 for landscape fire aerosol, greater than the -0.03 W m-2 K-1 estimated for biogenic secondary organic aerosol. These feedbacks are comparable in magnitude to other biogeochemical feedbacks, highlighting the need for natural aerosol feedbacks to be included in climate simulations.

Tree- Rings Link Climate and Carbon Storage in a Northern Mixed Hardwood Forest

NASA Astrophysics Data System (ADS)

Chiriboga, A.

2007-12-01

The terrestrial biosphere is a variable sink for atmospheric carbon dioxide. It is important to understand how carbon storage in trees is affected by natural climate variability to better characterize the sink. Quantifying the sensitivity of forest carbon storage to climate will improve carbon budgets and have implications for forest management practices. Here we explore how climate variability affects the ability of a northern mixed hardwood forest in Michigan to sequester atmospheric carbon dioxide in woody tissues. This site is ideal for studies of carbon sequestration; The University of Michigan Biological Station is an Ameriflux site, and has detailed meteorological and biometric records, as well as CO2 flux data. We have produced an 82- year aspen (Populus grandidentata) tree-ring chronology for this site, and measured ring widths at several heights up the bole. These measurements were used to estimate annual wood volume, which represents carbon allocated to aboveground carbon stores. Standard dendroclimatological techniques are used to identify environmental factors (e.g. temperature or precipitation) that drive tree-ring increment variability in the past century, and therefore annual carbon storage in this forest. Preliminary results show that marker years within the tree- ring chronology correspond with years that have cold spring temperatures. This suggests that trees at this site are temperature sensitive.

Paleoclimate of the Neoglacial and Roman Warm Period Reconstructed from Oxygen Isotope Ratios of Limpet Shells (Patella vulgata), Northwest Scotland

NASA Astrophysics Data System (ADS)

Wang, T.; Surge, D. M.; Mithen, S.

2010-12-01

Paleoclimate reconstructions from different regions have reported abrupt climate change around 2800-2700 cal yr B.P. The timing of this abrupt climate change is close to the boundary between the Neoglacial (3300-2500 cal yr B.P.) and Roman Warm Period (2500-1600 cal yr B.P.). However, temporal and spatial variability observed in this climate change event raises controversies about the forcing factors driving it and why it has regional variability. Scotland lies in the North Atlantic Ocean, which responds sensitively to climate change. Therefore, even in the case of subtle climate change, the climate variability of Scotland should be able to capture such change. In this study, we expect that paleoclimate reconstructions of the Neoglacial and Roman Warm Period in Scotland will help improve our knowledge of abrupt climate change at 2800-2700 cal yr B.P. Archaeological shell deposits provide a rich source of climate proxy data preserved as oxygen isotope ratios in shell carbonate. Croig Cave on the Isle of Mull, Scotland, contains a nearly continuous accumulation of shells ranging from 800 BC-500 AD and possibly older. This range represents a broad chronology of human use from the late Bronze to Iron Ages and spans the Neoglacial through Roman Warm Period climate episodes. Here, we present seasonal temperature variability of the two climate episodes based on oxygen isotope ratios of ten limpet shells (Patella vulgata) from Croig Cave. Based on AMS dating (2 sigma calibration), the oldest shell was from 3480-3330 cal yr B.P. and the youngest shell was from 2060-1870 cal yr B.P. Our results indicated that estimated temperatures from the Neoglacial limpets average 6.44±0.56°C for coldest winters and 15.06±0.67°C for warmest summers. For the Roman Warm Period limpets, the average is 5.68±0.36°C for coldest winters and 14.14±0.81°C for warmest summers. We compared our estimated temperatures to the present sea surface temperature (SST) from 1961 to 1990 near our study area, which averages 7.40±0.35°C for coldest month and 14.12±0.54°C for warmest month. Our reconstructed temperatures from the Neoglacial limpets showed slightly (0-1°C) colder winters, similar or warmer (1-1.8°C) summers compared to present SST record. One shell captured a year without a summer likely resulting from an eruption of the Katla volcanic system in Iceland. The reconstructed temperatures from the Roman Warm Period limpets showed colder winters (up to 2°C) and similar summers compared with present SST record. Our findings represent the first insights of SST variability at seasonal time scales for these two climate episodes in northwest Scotland.

On the Origin of Multidecadal to Centennial Greenland Temperature Anomalies Over the Past 800 yr

NASA Technical Reports Server (NTRS)

Kobashi, T.; Shindell, D. T.; Kodera, K.; Box, J. E.; Nakaegawa, T.; Kawamura, K.

2013-01-01

The surface temperature of the Greenland ice sheet is among the most important climate variables for assessing how climate change may impact human societies due to its association with sea level rise. However, the causes of multidecadal-to-centennial temperature changes in Greenland temperatures are not well understood, largely owing to short observational records. To examine these, we calculated the Greenland temperature anomalies (GTA[G-NH]) over the past 800 yr by subtracting the standardized northern hemispheric (NH) temperature from the standardized Greenland temperature. This decomposes the Greenland temperature variation into background climate (NH); polar amplification; and regional variability (GTA[G-NH]). The central Greenland polar amplification factor as expressed by the variance ratio Greenland/NH is 2.6 over the past 161 yr, and 3.3-4.2 over the past 800 yr. The GTA[G-NH] explains 31-35%of the variation of Greenland temperature in the multidecadal-to-centennial time scale over the past 800 yr. We found that the GTA[G-NH] has been influenced by solar-induced changes in atmospheric circulation patterns such as those produced by the North Atlantic Oscillation/Arctic Oscillation (NAO/AO). Climate modeling and proxy temperature records indicate that the anomaly is also likely linked to solar-paced changes in the Atlantic meridional overturning circulation (AMOC) and associated changes in northward oceanic heat transport.

On the origin of multidecadal to centennial Greenland temperature anomalies over the past 800 yr

NASA Astrophysics Data System (ADS)

Kobashi, T.; Shindell, D. T.; Kodera, K.; Box, J. E.; Nakaegawa, T.; Kawamura, K.

2013-03-01

The surface temperature of the Greenland ice sheet is among the most important climate variables for assessing how climate change may impact human societies due to its association with sea level rise. However, the causes of multidecadal-to-centennial temperature changes in Greenland temperatures are not well understood, largely owing to short observational records. To examine these, we calculated the Greenland temperature anomalies (GTA[G-NH]) over the past 800 yr by subtracting the standardized northern hemispheric (NH) temperature from the standardized Greenland temperature. This decomposes the Greenland temperature variation into background climate (NH); polar amplification; and regional variability (GTA[G-NH]). The central Greenland polar amplification factor as expressed by the variance ratio Greenland/NH is 2.6 over the past 161 yr, and 3.3-4.2 over the past 800 yr. The GTA[G-NH] explains 31-35% of the variation of Greenland temperature in the multidecadal-to-centennial time scale over the past 800 yr. We found that the GTA[G-NH] has been influenced by solar-induced changes in atmospheric circulation patterns such as those produced by the North Atlantic Oscillation/Arctic Oscillation (NAO/AO). Climate modeling and proxy temperature records indicate that the anomaly is also likely linked to solar-paced changes in the Atlantic meridional overturning circulation (AMOC) and associated changes in northward oceanic heat transport.

An eco-hydrologic model of malaria outbreaks

NASA Astrophysics Data System (ADS)

Montosi, E.; Manzoni, S.; Porporato, A.; Montanari, A.

2012-03-01

Malaria is a geographically widespread infectious disease that is well known to be affected by climate variability at both seasonal and interannual timescales. In an effort to identify climatic factors that impact malaria dynamics, there has been considerable research focused on the development of appropriate disease models for malaria transmission and their consideration alongside climatic datasets. These analyses have focused largely on variation in temperature and rainfall as direct climatic drivers of malaria dynamics. Here, we further these efforts by considering additionally the role that soil water content may play in driving malaria incidence. Specifically, we hypothesize that hydro-climatic variability should be an important factor in controlling the availability of mosquito habitats, thereby governing mosquito growth rates. To test this hypothesis, we reduce a nonlinear eco-hydrologic model to a simple linear model through a series of consecutive assumptions and apply this model to malaria incidence data from three South African provinces. Despite the assumptions made in the reduction of the model, we show that soil water content can account for a significant portion of malaria's case variability beyond its seasonal patterns, whereas neither temperature nor rainfall alone can do so. Future work should therefore consider soil water content as a simple and computable variable for incorporation into climate-driven disease models of malaria and other vector-borne infectious diseases.

An ecohydrological model of malaria outbreaks

NASA Astrophysics Data System (ADS)

Montosi, E.; Manzoni, S.; Porporato, A.; Montanari, A.

2012-08-01

Malaria is a geographically widespread infectious disease that is well known to be affected by climate variability at both seasonal and interannual timescales. In an effort to identify climatic factors that impact malaria dynamics, there has been considerable research focused on the development of appropriate disease models for malaria transmission driven by climatic time series. These analyses have focused largely on variation in temperature and rainfall as direct climatic drivers of malaria dynamics. Here, we further these efforts by considering additionally the role that soil water content may play in driving malaria incidence. Specifically, we hypothesize that hydro-climatic variability should be an important factor in controlling the availability of mosquito habitats, thereby governing mosquito growth rates. To test this hypothesis, we reduce a nonlinear ecohydrological model to a simple linear model through a series of consecutive assumptions and apply this model to malaria incidence data from three South African provinces. Despite the assumptions made in the reduction of the model, we show that soil water content can account for a significant portion of malaria's case variability beyond its seasonal patterns, whereas neither temperature nor rainfall alone can do so. Future work should therefore consider soil water content as a simple and computable variable for incorporation into climate-driven disease models of malaria and other vector-borne infectious diseases.

Climatic Variables and Malaria Morbidity in Mutale Local Municipality, South Africa: A 19-Year Data Analysis

PubMed Central

Botai, Joel O.; Rautenbach, Hannes; Ncongwane, Katlego P.; Botai, Christina M.

2017-01-01

The north-eastern parts of South Africa, comprising the Limpopo Province, have recorded a sudden rise in the rate of malaria morbidity and mortality in the 2017 malaria season. The epidemiological profiles of malaria, as well as other vector-borne diseases, are strongly associated with climate and environmental conditions. A retrospective understanding of the relationship between climate and the occurrence of malaria may provide insight into the dynamics of the disease’s transmission and its persistence in the north-eastern region. In this paper, the association between climatic variables and the occurrence of malaria was studied in the Mutale local municipality in South Africa over a period of 19-year. Time series analysis was conducted on monthly climatic variables and monthly malaria cases in the Mutale municipality for the period of 1998–2017. Spearman correlation analysis was performed and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model was developed. Microsoft Excel was used for data cleaning, and statistical software R was used to analyse the data and develop the model. Results show that both climatic variables’ and malaria cases’ time series exhibited seasonal patterns, showing a number of peaks and fluctuations. Spearman correlation analysis indicated that monthly total rainfall, mean minimum temperature, mean maximum temperature, mean average temperature, and mean relative humidity were significantly and positively correlated with monthly malaria cases in the study area. Regression analysis showed that monthly total rainfall and monthly mean minimum temperature (R2 = 0.65), at a two-month lagged effect, are the most significant climatic predictors of malaria transmission in Mutale local municipality. A SARIMA (2,1,2) (1,1,1) model fitted with only malaria cases has a prediction performance of about 51%, and the SARIMAX (2,1,2) (1,1,1) model with climatic variables as exogenous factors has a prediction performance of about 72% in malaria cases. The model gives a close comparison between the predicted and observed number of malaria cases, hence indicating that the model provides an acceptable fit to predict the number of malaria cases in the municipality. To sum up, the association between the climatic variables and malaria cases provides clues to better understand the dynamics of malaria transmission. The lagged effect detected in this study can help in adequate planning for malaria intervention. PMID:29117114

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

NASA Astrophysics Data System (ADS)

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 is the most widely used heat stress index for working people and can be easily interpreted by means of ISO standards. Within the HEAT-SHIELD project, climate change projections of the WBGT will be used to assess the impact of climate change on workers' health and productivity.

Statistical downscaling of mean temperature, maximum temperature, and minimum temperature on the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Jiang, L.

2017-12-01

Climate change is considered to be one of the greatest environmental threats. Global climate models (GCMs) are the primary tool used for studying climate change. However, GCMs are limited because of their coarse spatial resolution and inability to resolve important sub-grid scale features such as terrain and clouds. Statistical downscaling methods can be used to downscale large-scale variables to local-scale. In this study, we assess the applicability of the Statistical Downscaling Model (SDSM) in downscaling the outputs from Beijing Normal University Earth System Model (BNU-ESM). The study focus on the the Loess Plateau, China, and the variables for downscaling include daily mean temperature (TMEAN), maximum temperature (TMAX) and minimum temperature (TMIN). The results show that SDSM performs well for these three climatic variables on the Loess Plateau. After downscaling, the root mean square errors for TMEAN, TMAX, TMIN for BNU-ESM were reduced by 70.9%, 75.1%, and 67.2%, respectively. All the rates of change in TMEAN, TMAX and TMIN during the 21st century decreased after SDSM downscaling. We also show that SDSM can effectively reduce uncertainty, compared with the raw model outputs. TMEAN uncertainty was reduced by 27.1%, 26.8%, and 16.3% for the future scenarios of RCP 2.6, RCP 4.5 and RCP 8.5, respectively. The corresponding reductions in uncertainty were 23.6%, 30.7%, and 18.7% for TMAX; 37.6%, 31.8%, and 23.2% for TMIN.

Interannual Variability of Regional Hadley Circulation Intensity Over Western Pacific During Boreal Winter and Its Climatic Impact Over Asia-Australia Region

NASA Astrophysics Data System (ADS)

Huang, Ruping; Chen, Shangfeng; Chen, Wen; Hu, Peng

2018-01-01

This study investigates interannual variability of boreal winter regional Hadley circulation over western Pacific (WPHC) and its climatic impacts. A WPHC intensity index (WPHCI) is defined as the vertical shear of the divergent meridional winds. It shows that WPHCI correlates well with the El Niño-Southern Oscillation (ENSO). To investigate roles of the ENSO-unrelated part of WPHCI (WPHCIres), variables that are linearly related to the Niño-3 index have been removed. It reveals that meridional sea surface temperature gradient over the western Pacific plays an essential role in modulating the WPHCIres. The climatic impacts of WPHCIres are further investigated. Below-normal (above-normal) precipitation appears over south China (North Australia) when WPHCIres is stronger. This is due to the marked convergence (divergence) anomalies at the upper troposphere, divergence (convergence) at the lower troposphere, and the accompanied downward (upward) motion over south China (North Australia), which suppresses (enhances) precipitation there. In addition, a pronounced increase in surface air temperature (SAT) appears over south and central China when WPHCIres is stronger. A temperature diagnostic analysis suggests that the increase in SAT tendency over central China is primarily due to the warm zonal temperature advection and subsidence-induced adiabatic heating. In addition, the increase in SAT tendency over south China is primarily contributed by the warm meridional temperature advection. Further analysis shows that the correlation of WPHCIres with the East Asian winter monsoon (EAWM) is weak. Thus, this study may provide additional sources besides EAWM and ENSO to improve understanding of the Asia-Australia climate variability.

Norwegian fjord sediments reveal NAO related winter temperature and precipitation changes of the past 2800 years

NASA Astrophysics Data System (ADS)

Faust, Johan C.; Fabian, Karl; Milzer, Gesa; Giraudeau, Jacques; Knies, Jochen

2016-02-01

The North Atlantic Oscillation (NAO) is the leading mode of atmospheric circulation variability in the North Atlantic region. Associated shifts of storm tracks, precipitation and temperature patterns affect energy supply and demand, fisheries and agricultural, as well as marine and terrestrial ecological dynamics. Long-term NAO records are crucial to better understand its response to climate forcing factors, and assess predictability and shifts associated with ongoing climate change. A recent study of instrumental time series revealed NAO as main factor for a strong relation between winter temperature, precipitation and river discharge in central Norway over the past 50 years. Here we compare geochemical measurements with instrumental data and show that primary productivity recorded in central Norwegian fjord sediments is sensitive to NAO variability. This observation is used to calibrate paleoproductivity changes to a 500-year reconstruction of winter NAO (Luterbacher et al., 2001). Conditioned on a stationary relation between our climate proxy and the NAO we establish a first high resolution NAO proxy record (NAOTFJ) from marine sediments covering the past 2800 years. The NAOTFJ shows distinct co-variability with climate changes over Greenland, solar activity and Northern Hemisphere glacier dynamics as well as climatically associated paleo-demographic trends. The here presented climate record shows that fjord sediments provide crucial information for an improved understanding of the linkages between atmospheric circulation, solar and oceanic forcing factors.

Mapping the changing pattern of local climate as an observed distribution

NASA Astrophysics Data System (ADS)

Chapman, Sandra; Stainforth, David; Watkins, Nicholas

2013-04-01

It is at local scales that the impacts of climate change will be felt directly and at which adaptation planning decisions must be made. This requires quantifying the geographical patterns in trends at specific quantiles in distributions of variables such as daily temperature or precipitation. Here we focus on these local changes and on the way observational data can be analysed to inform us about the pattern of local climate change. We present a method[1] for analysing local climatic timeseries data to assess which quantiles of the local climatic distribution show the greatest and most robust trends. We demonstrate this approach using E-OBS gridded data[2] timeseries of local daily temperature from specific locations across Europe over the last 60 years. Our method extracts the changing cumulative distribution function over time and uses a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. This deconstruction facilitates an assessment of the sensitivity of different quantiles of the distributions to changing climate. Geographical location and temperature are treated as independent variables, we thus obtain as outputs the pattern of variation in sensitivity with temperature (or occurrence likelihood), and with geographical location. We find as an output many regionally consistent patterns of response of potential value in adaptation planning. We discuss methods to quantify and map the robustness of these observed sensitivities and their statistical likelihood. This also quantifies the level of detail needed from climate models if they are to be used as tools to assess climate change impact. [1] S C Chapman, D A Stainforth, N W Watkins, 2013, On Estimating Local Long Term Climate Trends, Phil. Trans. R. Soc. A, in press [2] Haylock, M.R., N. Hofstra, A.M.G. Klein Tank, E.J. Klok, P.D. Jones and M. New. 2008: A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres), 113, D20119, doi:10.1029/2008JD10201

Temporal Variation of NDVI and the Drivers of Climate Variables in the Arctic Tundra Transition Zone

NASA Astrophysics Data System (ADS)

Lee, J.; Ryu, Y.; Lee, Y. K.

2016-12-01

The Arctic is a sensitive region to temperature, which is drastically increasing with climate change. Vegetation in transition zones of the sub-arctic tundra biome are most sensitive to the warming climate, as temperature in the Arctic ecosystem is one of important limiting factors of vegetation growth and decomposition. Previous research in the transition zone show that there is a difference of sensible heat flux (21 Wm-2), Leaf Area Index increase from 0.58 - 2.76 and canopy height from 0.1 - 6.1m across dwarf and tall shrubs to forest, however, we lack understanding of NDVI trend of this zone. To better understand the vegetation in transition zones of the arctic ecosystem, we analyze the long-term trend of NDVI (AVHRR 3g GIMMs data), temperature and precipitation (Climate Research Unit data) trend from 1982 - 2010 in Council, Alaska that is a region where arctic tundra is transitioning to boreal forest. We also analyze how the climatic factors, temperature or precipitation, affect NDVI. Annual precipitation had the highest interannual variability compared to temperature and NDVI. There was an overall decreasing trend of annual maximum NDVI (y = -0.0019x+4.7). During 1982 to 2003, NDVI and temperature had a similar pattern, but when temperature suddenly jumped to 13.2°C in 2004, NDVI and precipitation declined. This study highlights that temperature increase does not always lead to greening, but after a certain threshold they may cause damage to sub-arctic tundra vegetation.

Interannual variation of carbon fluxes from three contrasting evergreen forests: the role of forest dynamics and climate.

PubMed

Sierra, Carlos A; Loescher, Henry W; Harmon, Mark E; Richardson, Andrew D; Hollinger, David Y; Perakis, Steven S

2009-10-01

Interannual variation of carbon fluxes can be attributed to a number of biotic and abiotic controls that operate at different spatial and temporal scales. Type and frequency of disturbance, forest dynamics, and climate regimes are important sources of variability. Assessing the variability of carbon fluxes from these specific sources can enhance the interpretation of past and current observations. Being able to separate the variability caused by forest dynamics from that induced by climate will also give us the ability to determine if the current observed carbon fluxes are within an expected range or whether the ecosystem is undergoing unexpected change. Sources of interannual variation in ecosystem carbon fluxes from three evergreen ecosystems, a tropical, a temperate coniferous, and a boreal forest, were explored using the simulation model STANDCARB. We identified key processes that introduced variation in annual fluxes, but their relative importance differed among the ecosystems studied. In the tropical site, intrinsic forest dynamics contributed approximately 30% of the total variation in annual carbon fluxes. In the temperate and boreal sites, where many forest processes occur over longer temporal scales than those at the tropical site, climate controlled more of the variation among annual fluxes. These results suggest that climate-related variability affects the rates of carbon exchange differently among sites. Simulations in which temperature, precipitation, and radiation varied from year to year (based on historical records of climate variation) had less net carbon stores than simulations in which these variables were held constant (based on historical records of monthly average climate), a result caused by the functional relationship between temperature and respiration. This suggests that, under a more variable temperature regime, large respiratory pulses may become more frequent and high enough to cause a reduction in ecosystem carbon stores. Our results also show that the variation of annual carbon fluxes poses an important challenge in our ability to determine whether an ecosystem is a source, a sink, or is neutral in regard to CO2 at longer timescales. In simulations where climate change negatively affected ecosystem carbon stores, there was a 20% chance of committing Type II error, even with 20 years of sequential data.

Climate variability, weather and enteric disease incidence in New Zealand: time series analysis.

PubMed

Lal, Aparna; Ikeda, Takayoshi; French, Nigel; Baker, Michael G; Hales, Simon

2013-01-01

Evaluating the influence of climate variability on enteric disease incidence may improve our ability to predict how climate change may affect these diseases. To examine the associations between regional climate variability and enteric disease incidence in New Zealand. Associations between monthly climate and enteric diseases (campylobacteriosis, salmonellosis, cryptosporidiosis, giardiasis) were investigated using Seasonal Auto Regressive Integrated Moving Average (SARIMA) models. No climatic factors were significantly associated with campylobacteriosis and giardiasis, with similar predictive power for univariate and multivariate models. Cryptosporidiosis was positively associated with average temperature of the previous month (β =  0.130, SE =  0.060, p <0.01) and inversely related to the Southern Oscillation Index (SOI) two months previously (β =  -0.008, SE =  0.004, p <0.05). By contrast, salmonellosis was positively associated with temperature (β  = 0.110, SE = 0.020, p<0.001) of the current month and SOI of the current (β  = 0.005, SE = 0.002, p<0.050) and previous month (β  = 0.005, SE = 0.002, p<0.05). Forecasting accuracy of the multivariate models for cryptosporidiosis and salmonellosis were significantly higher. Although spatial heterogeneity in the observed patterns could not be assessed, these results suggest that temporally lagged relationships between climate variables and national communicable disease incidence data can contribute to disease prediction models and early warning systems.

Effects of ambient air temperature, humidity and rainfall on annual survival of adult little penguins Eudyptula minor in southeastern Australia

NASA Astrophysics Data System (ADS)

Ganendran, L. B.; Sidhu, L. A.; Catchpole, E. A.; Chambers, L. E.; Dann, P.

2016-08-01

Seabirds are subject to the influences of local climate variables during periods of land-based activities such as breeding and, for some species, moult; particularly if they undergo a catastrophic moult (complete simultaneous moult) as do penguins. We investigated potential relationships between adult penguin survival and land-based climate variables (ambient air temperature, humidity and rainfall) using 46 years of mark-recapture data of little penguins Eudyptula minor gathered at a breeding colony on Phillip Island in southeastern Australia. Our results showed that adult penguin survival had a stronger association with land-based climate variables during the moult period, when birds were unable to go to sea for up to 3 weeks, than during the breeding period, when birds could sacrifice breeding success in favour of survival. Annual adult survival probability was positively associated with humidity during moult and negatively associated with rainfall during moult. Prolonged heat during breeding and moult had a negative association with annual adult survival. Local climate projections suggest increasing days of high temperatures, fewer days of rainfall which will result in more droughts (and by implication, lower humidity) and more extreme rainfall events. All of these predicted climate changes are expected to have a negative impact on adult penguin survival.

Effects of ambient air temperature, humidity and rainfall on annual survival of adult little penguins Eudyptula minor in southeastern Australia.

PubMed

Ganendran, L B; Sidhu, L A; Catchpole, E A; Chambers, L E; Dann, P

2016-08-01

Seabirds are subject to the influences of local climate variables during periods of land-based activities such as breeding and, for some species, moult; particularly if they undergo a catastrophic moult (complete simultaneous moult) as do penguins. We investigated potential relationships between adult penguin survival and land-based climate variables (ambient air temperature, humidity and rainfall) using 46 years of mark-recapture data of little penguins Eudyptula minor gathered at a breeding colony on Phillip Island in southeastern Australia. Our results showed that adult penguin survival had a stronger association with land-based climate variables during the moult period, when birds were unable to go to sea for up to 3 weeks, than during the breeding period, when birds could sacrifice breeding success in favour of survival. Annual adult survival probability was positively associated with humidity during moult and negatively associated with rainfall during moult. Prolonged heat during breeding and moult had a negative association with annual adult survival. Local climate projections suggest increasing days of high temperatures, fewer days of rainfall which will result in more droughts (and by implication, lower humidity) and more extreme rainfall events. All of these predicted climate changes are expected to have a negative impact on adult penguin survival.

Correlation dimensions of climate subsystems and their geographic variability

NASA Astrophysics Data System (ADS)

Gan, Thian Yew; Wang, Qiang; Seneka, Michael

2002-12-01

The correlation dimension D2 of precipitation (Canada and Africa), air temperature (Canada, New Zealand, and Southern Hemisphere), geo-potential height (Canada), and unregulated streamflow (Canada, USA, and Africa) were estimated using the Hill procedure of Mikosch and Wang [1995] and the bias correction of Wang and Gan [1998]. After bias correction, it seems that D2 is distinct between climate subsystems, such that for precipitation, it is between 8 and 9, for streamflow, it is between 7 and 9, for temperature, it is between 10 and 11, and for geo-potential heights, it is between 12 and 14. The results seem to suggest that climate might be viewed as a loosely coupled set of fairly high-dimensional subsystems and that different climate variables can yield different D2 values. Further, results also suggest that the D2 values of the climate subsystems studied, generally, have low geographic variability, as found between the precipitation data of Western Canada and Uganda, between the streamflow data of basins representing wide range climate and scales from Canada, USA, and Africa, and among the temperature data of Western Canada, New Zealand, and the southern hemisphere, and that the original D2 values analyzed from Canadian geo-potential heights are similar to that of Western Europe, eastern North America, and Germany. There is at most a weak relationship among basin physical characteristics, location, basin scale, and streamflow D2, while climatic influence is more obvious, as shown by drier basins having slightly higher D2 values than basins of wetter climate, basins from temperate climate having higher D2 values than those from cold or hot climates, and comparable D2 values between precipitation and streamflow data.

VEMAP Phase 2 bioclimatic database. I. Gridded historical (20th century) climate for modeling ecosystem dynamics across the conterminous USA

USGS Publications Warehouse

Kittel, T.G.F.; Rosenbloom, N.A.; Royle, J. Andrew; Daly, Christopher; Gibson, W.P.; Fisher, H.H.; Thornton, P.; Yates, D.N.; Aulenbach, S.; Kaufman, C.; McKeown, R.; Bachelet, D.; Schimel, D.S.; Neilson, R.; Lenihan, J.; Drapek, R.; Ojima, D.S.; Parton, W.J.; Melillo, J.M.; Kicklighter, D.W.; Tian, H.; McGuire, A.D.; Sykes, M.T.; Smith, B.; Cowling, S.; Hickler, T.; Prentice, I.C.; Running, S.; Hibbard, K.A.; Post, W.M.; King, A.W.; Smith, T.; Rizzo, B.; Woodward, F.I.

2004-01-01

Analysis and simulation of biospheric responses to historical forcing require surface climate data that capture those aspects of climate that control ecological processes, including key spatial gradients and modes of temporal variability. We developed a multivariate, gridded historical climate dataset for the conterminous USA as a common input database for the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP), a biogeochemical and dynamic vegetation model intercomparison. The dataset covers the period 1895-1993 on a 0.5?? latitude/longitude grid. Climate is represented at both monthly and daily timesteps. Variables are: precipitation, mininimum and maximum temperature, total incident solar radiation, daylight-period irradiance, vapor pressure, and daylight-period relative humidity. The dataset was derived from US Historical Climate Network (HCN), cooperative network, and snowpack telemetry (SNOTEL) monthly precipitation and mean minimum and maximum temperature station data. We employed techniques that rely on geostatistical and physical relationships to create the temporally and spatially complete dataset. We developed a local kriging prediction model to infill discontinuous and limited-length station records based on spatial autocorrelation structure of climate anomalies. A spatial interpolation model (PRISM) that accounts for physiographic controls was used to grid the infilled monthly station data. We implemented a stochastic weather generator (modified WGEN) to disaggregate the gridded monthly series to dailies. Radiation and humidity variables were estimated from the dailies using a physically-based empirical surface climate model (MTCLIM3). Derived datasets include a 100 yr model spin-up climate and a historical Palmer Drought Severity Index (PDSI) dataset. The VEMAP dataset exhibits statistically significant trends in temperature, precipitation, solar radiation, vapor pressure, and PDSI for US National Assessment regions. The historical climate and companion datasets are available online at data archive centers. ?? Inter-Research 2004.

Treeline dynamics in response to climate change in the Min Mountains, southwestern China.

PubMed

Zhao, Zhi-Jiang; Shen, Guo-Zhen; Tan, Liu-Yi; Kang, Dong-Wei; Wang, Meng-Jun; Kang, Wen; Guo, Wen-Xia; Zeppel, Melanie Jb; Yu, Qiang; Li, Jun-Qing

2013-12-01

Abies faxoniana is the dominant plant species of the forest ecosystem on the eastern edge of Qinghai-Tibet Plateau, where the treeline is strongly defined by climate. The tree-ring chronologies and age structure of Abies faxoniana were developed in the treeline ecotones on the northwestern and southeastern aspects of the Min Mountains in the Wanglang Nature Reserve to examine the treeline dynamics of recent decades in response to climate change. On the northwestern aspect, correlation analysis showed that the radial growth was significantly and positively correlated with precipitation in current January and monthly mean temperature in current April, but significantly and negatively correlated with monthly mean temperature in previous August. On the southeastern aspect, the radial growth was significantly negatively correlated with monthly mean temperature in previous July and August. The different responses of radial growth to climatic variability on both the aspects might be mainly due to the micro-environmental conditions. The recruitment benefited from the warm temperature in current April, July and September on the northwestern aspect. The responses of radial growth and recruitment to climatic variability were similar on the northwestern slope. Recruitment was greatly restricted by competition with dense bamboos on the southeastern aspect.

Evolutionary potential of upper thermal tolerance: biogeographic patterns and expectations under climate change.

PubMed

Diamond, Sarah E

2017-02-01

How will organisms respond to climate change? The rapid changes in global climate are expected to impose strong directional selection on fitness-related traits. A major open question then is the potential for adaptive evolutionary change under these shifting climates. At the most basic level, evolutionary change requires the presence of heritable variation and natural selection. Because organismal tolerances of high temperature place an upper bound on responding to temperature change, there has been a surge of research effort on the evolutionary potential of upper thermal tolerance traits. Here, I review the available evidence on heritable variation in upper thermal tolerance traits, adopting a biogeographic perspective to understand how heritability of tolerance varies across space. Specifically, I use meta-analytical models to explore the relationship between upper thermal tolerance heritability and environmental variability in temperature. I also explore how variation in the methods used to obtain these thermal tolerance heritabilities influences the estimation of heritable variation in tolerance. I conclude by discussing the implications of a positive relationship between thermal tolerance heritability and environmental variability in temperature and how this might influence responses to future changes in climate. © 2016 New York Academy of Sciences.

Accounting for downscaling and model uncertainty in fine-resolution seasonal climate projections over the Columbia River Basin

NASA Astrophysics Data System (ADS)

Ahmadalipour, Ali; Moradkhani, Hamid; Rana, Arun

2018-01-01

Climate change is expected to have severe impacts on natural systems as well as various socio-economic aspects of human life. This has urged scientific communities to improve the understanding of future climate and reduce the uncertainties associated with projections. In the present study, ten statistically downscaled CMIP5 GCMs at 1/16th deg. spatial resolution from two different downscaling procedures are utilized over the Columbia River Basin (CRB) to assess the changes in climate variables and characterize the associated uncertainties. Three climate variables, i.e. precipitation, maximum temperature, and minimum temperature, are studied for the historical period of 1970-2000 as well as future period of 2010-2099, simulated with representative concentration pathways of RCP4.5 and RCP8.5. Bayesian Model Averaging (BMA) is employed to reduce the model uncertainty and develop a probabilistic projection for each variable in each scenario. Historical comparison of long-term attributes of GCMs and observation suggests a more accurate representation for BMA than individual models. Furthermore, BMA projections are used to investigate future seasonal to annual changes of climate variables. Projections indicate significant increase in annual precipitation and temperature, with varied degree of change across different sub-basins of CRB. We then characterized uncertainty of future projections for each season over CRB. Results reveal that model uncertainty is the main source of uncertainty, among others. However, downscaling uncertainty considerably contributes to the total uncertainty of future projections, especially in summer. On the contrary, downscaling uncertainty appears to be higher than scenario uncertainty for precipitation.

Analysis of monthly, winter, and annual temperatures in Zagreb, Croatia, from 1864 to 2010: the 7.7-year cycle and the North Atlantic Oscillation

NASA Astrophysics Data System (ADS)

Sen, Asok K.; Ogrin, Darko

2016-02-01

Long instrumental records of meteorological variables such as temperature and precipitation are very useful for studying regional climate in the past, present, and future. They can also be useful for understanding the influence of large-scale atmospheric circulation processes on the regional climate. This paper investigates the monthly, winter, and annual temperature time series obtained from the instrumental records in Zagreb, Croatia, for the period 1864-2010. Using wavelet analysis, the dominant modes of variability in these temperature series are identified, and the time intervals over which these modes may persist are delineated. The results reveal that all three temperature records exhibit low-frequency variability with a dominant periodicity at around 7.7 years. The 7.7-year cycle has also been observed in the temperature data recorded at several other stations in Europe, especially in Northern and Western Europe, and may be linked to the North Atlantic Oscillation (NAO) and/or solar/geomagnetic activity.

Climate signals in a multispecies tree-ring network from central and southern Italy and reconstruction of the late summer temperatures since the early 1700s

NASA Astrophysics Data System (ADS)

Leonelli, Giovanni; Coppola, Anna; Salvatore, Maria Cristina; Baroni, Carlo; Battipaglia, Giovanna; Gentilesca, Tiziana; Ripullone, Francesco; Borghetti, Marco; Conte, Emanuele; Tognetti, Roberto; Marchetti, Marco; Lombardi, Fabio; Brunetti, Michele; Maugeri, Maurizio; Pelfini, Manuela; Cherubini, Paolo; Provenzale, Antonello; Maggi, Valter

2017-11-01

A first assessment of the main climatic drivers that modulate the tree-ring width (RW) and maximum latewood density (MXD) along the Italian Peninsula and northeastern Sicily was performed using 27 forest sites, which include conifers (RW and MXD) and broadleaves (only RW). Tree-ring data were compared using the correlation analysis of the monthly and seasonal variables of temperature, precipitation and standardized precipitation index (SPI, used to characterize meteorological droughts) against each species-specific site chronology and against the highly sensitive to climate (HSTC) chronologies (based on selected indexed individual series). We find that climate signals in conifer MXD are stronger and more stable over time than those in conifer and broadleaf RW. In particular, conifer MXD variability is directly influenced by the late summer (August, September) temperature and is inversely influenced by the summer precipitation and droughts (SPI at a timescale of 3 months). The MXD sensitivity to August-September (AS) temperature and to summer drought is mainly driven by the latitudinal gradient of summer precipitation amounts, with sites in the northern Apennines showing stronger climate signals than sites in the south. Conifer RW is influenced by the temperature and drought of the previous summer, whereas broadleaf RW is more influenced by summer precipitation and drought of the current growing season. The reconstruction of the late summer temperatures for the Italian Peninsula for the past 300 years, based on the HSTC chronology of conifer MXD, shows a stable model performance that underlines periods of climatic cooling (and likely also wetter conditions) in 1699, 1740, 1814, 1914 and 1938, and follows well the variability of the instrumental record and of other tree-ring-based reconstructions in the region. Considering a 20-year low-pass-filtered series, the reconstructed temperature record consistently deviates < 1 °C from the instrumental record. This divergence may also be due to the precipitation patterns and drought stresses that influence the tree-ring MXD at our study sites. The reconstructed late summer temperature variability is also linked to summer drought conditions and it is valid for the west-east oriented region including Sardinia, Sicily, the Italian Peninsula and the western Balkan area along the Adriatic coast.

Interaction of ice sheets and climate during the past 800 000 years

NASA Astrophysics Data System (ADS)

Stap, L. B.; van de Wal, R. S. W.; de Boer, B.; Bintanja, R.; Lourens, L. J.

2014-12-01

During the Cenozoic, land ice and climate interacted on many different timescales. On long timescales, the effect of land ice on global climate and sea level is mainly set by large ice sheets in North America, Eurasia, Greenland and Antarctica. The climatic forcing of these ice sheets is largely determined by the meridional temperature profile resulting from radiation and greenhouse gas (GHG) forcing. As a response, the ice sheets cause an increase in albedo and surface elevation, which operates as a feedback in the climate system. To quantify the importance of these climate-land ice processes, a zonally averaged energy balance climate model is coupled to five one-dimensional ice sheet models, representing the major ice sheets. In this study, we focus on the transient simulation of the past 800 000 years, where a high-confidence CO2 record from ice core samples is used as input in combination with Milankovitch radiation changes. We obtain simulations of atmospheric temperature, ice volume and sea level that are in good agreement with recent proxy-data reconstructions. We examine long-term climate-ice-sheet interactions by a comparison of simulations with uncoupled and coupled ice sheets. We show that these interactions amplify global temperature anomalies by up to a factor of 2.6, and that they increase polar amplification by 94%. We demonstrate that, on these long timescales, the ice-albedo feedback has a larger and more global influence on the meridional atmospheric temperature profile than the surface-height-temperature feedback. Furthermore, we assess the influence of CO2 and insolation by performing runs with one or both of these variables held constant. We find that atmospheric temperature is controlled by a complex interaction of CO2 and insolation, and both variables serve as thresholds for northern hemispheric glaciation.

Climate and atmosphere simulator for experiments on ecological systems in changing environments.

PubMed

Verdier, Bruno; Jouanneau, Isabelle; Simonnet, Benoit; Rabin, Christian; Van Dooren, Tom J M; Delpierre, Nicolas; Clobert, Jean; Abbadie, Luc; Ferrière, Régis; Le Galliard, Jean-François

2014-01-01

Grand challenges in global change research and environmental science raise the need for replicated experiments on ecosystems subjected to controlled changes in multiple environmental factors. We designed and developed the Ecolab as a variable climate and atmosphere simulator for multifactor experimentation on natural or artificial ecosystems. The Ecolab integrates atmosphere conditioning technology optimized for accuracy and reliability. The centerpiece is a highly contained, 13-m(3) chamber to host communities of aquatic and terrestrial species and control climate (temperature, humidity, rainfall, irradiance) and atmosphere conditions (O2 and CO2 concentrations). Temperature in the atmosphere and in the water or soil column can be controlled independently of each other. All climatic and atmospheric variables can be programmed to follow dynamical trajectories and simulate gradual as well as step changes. We demonstrate the Ecolab's capacity to simulate a broad range of atmospheric and climatic conditions, their diurnal and seasonal variations, and to support the growth of a model terrestrial plant in two contrasting climate scenarios. The adaptability of the Ecolab design makes it possible to study interactions between variable climate-atmosphere factors and biotic disturbances. Developed as an open-access, multichamber platform, this equipment is available to the international scientific community for exploring interactions and feedbacks between ecological and climate systems.

Statistical downscaling of mean temperature, maximum temperature, and minimum temperature on the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Lin, Jiang; Miao, Chiyuan

2017-04-01

Climate change is considered to be one of the greatest environmental threats. This has urged scientific communities to focus on the hot topic. Global climate models (GCMs) are the primary tool used for studying climate change. However, GCMs are limited because of their coarse spatial resolution and inability to resolve important sub-grid scale features such as terrain and clouds. Statistical downscaling methods can be used to downscale large-scale variables to local-scale. In this study, we assess the applicability of the widely used Statistical Downscaling Model (SDSM) for the Loess Plateau, China. The observed variables included daily mean temperature (TMEAN), maximum temperature (TMAX) and minimum temperature (TMIN) from 1961 to 2005. The and the daily atmospheric data were taken from reanalysis data from 1961 to 2005, and global climate model outputs from Beijing Normal University Earth System Model (BNU-ESM) from 1961 to 2099 and from observations . The results show that SDSM performs well for these three climatic variables on the Loess Plateau. After downscaling, the root mean square errors for TMEAN, TMAX, TMIN for BNU-ESM were reduced by 70.9%, 75.1%, and 67.2%, respectively. All the rates of change in TMEAN, TMAX and TMIN during the 21st century decreased after SDSM downscaling. We also show that SDSM can effectively reduce uncertainty, compared with the raw model outputs. TMEAN uncertainty was reduced by 27.1%, 26.8%, and 16.3% for the future scenarios of RCP 2.6, RCP 4.5 and RCP 8.5, respectively. The corresponding reductions in uncertainty were 23.6%, 30.7%, and 18.7% for TMAX, ; and 37.6%, 31.8%, and 23.2% for TMIN.

Impact of spectral nudging on regional climate simulation over CORDEX East Asia using WRF

NASA Astrophysics Data System (ADS)

Tang, Jianping; Wang, Shuyu; Niu, Xiaorui; Hui, Pinhong; Zong, Peishu; Wang, Xueyuan

2017-04-01

In this study, the impact of the spectral nudging method on regional climate simulation over the Coordinated Regional Climate Downscaling Experiment East Asia (CORDEX-EA) region is investigated using the Weather Research and Forecasting model (WRF). Driven by the ERA-Interim reanalysis, five continuous simulations covering 1989-2007 are conducted by the WRF model, in which four runs adopt the interior spectral nudging with different wavenumbers, nudging variables and nudging coefficients. Model validation shows that WRF has the ability to simulate spatial distributions and temporal variations of the surface climate (air temperature and precipitation) over CORDEX-EA domain. Comparably the spectral nudging technique is effective in improving the model's skill in the following aspects: (1), the simulated biases and root mean square errors of annual mean temperature and precipitation are obviously reduced. The SN3-UVT (spectral nudging with wavenumber 3 in both zonal and meridional directions applied to U, V and T) and SN6 (spectral nudging with wavenumber 6 in both zonal and meridional directions applied to U and V) experiments give the best simulations for temperature and precipitation respectively. The inter-annual and seasonal variances produced by the SN experiments are also closer to the ERA-Interim observation. (2), the application of spectral nudging in WRF is helpful for simulating the extreme temperature and precipitation, and the SN3-UVT simulation shows a clear advantage over the other simulations in depicting both the spatial distributions and inter-annual variances of temperature and precipitation extremes. With the spectral nudging, WRF is able to preserve the variability in the large scale climate information, and therefore adjust the temperature and precipitation variabilities toward the observation.

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

PubMed Central

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

2013-01-01

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

Spatio-temporal modelling of dengue fever incidence in Malaysia

NASA Astrophysics Data System (ADS)

Che-Him, Norziha; Ghazali Kamardan, M.; Saifullah Rusiman, Mohd; Sufahani, Suliadi; Mohamad, Mahathir; @ Kamariah Kamaruddin, Nafisah

2018-04-01

Previous studies reported significant relationship between dengue incidence rate (DIR) and both climatic and non-climatic factors. Therefore, this study proposes a generalised additive model (GAM) framework for dengue risk in Malaysia by using both climatic and non-climatic factors. The data used is monthly DIR for 12 states of Malaysia from 2001 to 2009. In this study, we considered an annual trend, seasonal effects, population, population density and lagged DIR, rainfall, temperature, number of rainy days and El Niño-Southern Oscillation (ENSO). The population density is found to be positively related to monthly DIR. There are generally weak relationships between monthly DIR and climate variables. A negative binomial GAM shows that there are statistically significant relationships between DIR with climatic and non-climatic factors. These include mean rainfall and temperature, the number of rainy days, sea surface temperature and the interaction between mean temperature (lag 1 month) and sea surface temperature (lag 6 months). These also apply to DIR (lag 3 months) and population density.

New insights into deglacial climate variability in tropical South America from molecular fossil and isotopic indicators in Lake Titicaca

NASA Astrophysics Data System (ADS)

Shanahan, T. M.; Hughen, K. A.; Fornace, K.; Baker, P. A.; Fritz, S. C.

2010-12-01

As one of the main centers of tropical convection, the South American Altiplano plays a crucial role in the long-term climate variability of South America. However, both the timing and the drivers of climate variability on orbital to millennial timescales remain poorly understood for this region. New data from molecular fossil (e.g., TEX86) and compound specific hydrogen isotope (D/H) analyses provide new insights into the climate evolution of this region over the last ~50 kyr. TEX86 temperature reconstructions suggest that the Altiplano warmed as early as 19- 21 kyr ago and proceeded rapidly, consistent with published evidence for an early retreat of LGM glaciers at this time at some locations. The early warming signal observed at Lake Titicaca also appears to be synchronous with continental temperature reconstructions at some sites in tropical Africa, but leads tropical SST changes by several thousands of years. Although the initiation of warming coincided with the peak in southern hemisphere summer insolation, subsequent temperature increases were accompanied by decreases in southern hemisphere insolation, suggesting a northern hemisphere driver for temperature changes in tropical South America. Preliminary D/H ratios from leaf waxes appear to support existing data suggesting that wet conditions prevailed until the late glacial/early Holocene and are broadly consistent with local southern hemisphere summer insolation forcing of the summer monsoon. These data suggest that temperature and precipitation changes during the last deglaciation were decoupled and that both local and extratropical drivers are important for controlling climate change in this region on orbital timescales.

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

PubMed

Kingsolver, Joel G; Buckley, Lauren B

2015-03-07

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

Relative importance of climate changes at different time scales on net primary productivity-a case study of the Karst area of northwest Guangxi, China.

PubMed

Liu, Huiyu; Zhang, Mingyang; Lin, Zhenshan

2017-10-05

Climate changes are considered to significantly impact net primary productivity (NPP). However, there are few studies on how climate changes at multiple time scales impact NPP. With MODIS NPP product and station-based observations of sunshine duration, annual average temperature and annual precipitation, impacts of climate changes at different time scales on annual NPP, have been studied with EEMD (ensemble empirical mode decomposition) method in the Karst area of northwest Guangxi, China, during 2000-2013. Moreover, with partial least squares regression (PLSR) model, the relative importance of climatic variables for annual NPP has been explored. The results show that (1) only at quasi 3-year time scale do sunshine duration and temperature have significantly positive relations with NPP. (2) Annual precipitation has no significant relation to NPP by direct comparison, but significantly positive relation at 5-year time scale, which is because 5-year time scale is not the dominant scale of precipitation; (3) the changes of NPP may be dominated by inter-annual variabilities. (4) Multiple time scales analysis will greatly improve the performance of PLSR model for estimating NPP. The variable importance in projection (VIP) scores of sunshine duration and temperature at quasi 3-year time scale, and precipitation at quasi 5-year time scale are greater than 0.8, indicating important for NPP during 2000-2013. However, sunshine duration and temperature at quasi 3-year time scale are much more important. Our results underscore the importance of multiple time scales analysis for revealing the relations of NPP to changing climate.

Selecting global climate models for regional climate change studies

PubMed Central

Pierce, David W.; Barnett, Tim P.; Santer, Benjamin D.; Gleckler, Peter J.

2009-01-01

Regional or local climate change modeling studies currently require starting with a global climate model, then downscaling to the region of interest. How should global models be chosen for such studies, and what effect do such choices have? This question is addressed in the context of a regional climate detection and attribution (D&A) study of January-February-March (JFM) temperature over the western U.S. Models are often selected for a regional D&A analysis based on the quality of the simulated regional climate. Accordingly, 42 performance metrics based on seasonal temperature and precipitation, the El Nino/Southern Oscillation (ENSO), and the Pacific Decadal Oscillation are constructed and applied to 21 global models. However, no strong relationship is found between the score of the models on the metrics and results of the D&A analysis. Instead, the importance of having ensembles of runs with enough realizations to reduce the effects of natural internal climate variability is emphasized. Also, the superiority of the multimodel ensemble average (MM) to any 1 individual model, already found in global studies examining the mean climate, is true in this regional study that includes measures of variability as well. Evidence is shown that this superiority is largely caused by the cancellation of offsetting errors in the individual global models. Results with both the MM and models picked randomly confirm the original D&A results of anthropogenically forced JFM temperature changes in the western U.S. Future projections of temperature do not depend on model performance until the 2080s, after which the better performing models show warmer temperatures. PMID:19439652

Drivers of River Water Temperature Space-time Variability in Northeast Greenland

NASA Astrophysics Data System (ADS)

Hannah, D. M.; Docherty, C.; Milner, A.

2015-12-01

Water temperature plays an important role in stream ecosystem functioning; however, water temperature dynamics in high Arctic environments have received relatively little attention. Given that global climate is predicted to change most at high latitudes, it is vital we broaden our knowledge of space-time variability in Arctic river temperature to understand controlling processes and potential consequences of climate change. To address this gap, our research aims: (1) to characterise seasonal and diel patterns of variability over three summer and two winter seasons with contrasting hydrometeorological conditions, (2) to unravel the key drivers influencing thermal regimes and (3) to place these results in the context of other snow/ glacier-melt dominated environments. Fieldwork was undertaken in July-September 2013, 2014 and 2015 close to the Zackenberg Research Station in Northeast Greenland - an area of continuous permafrost with a mean July air temperature of 6 °C. Five streams were chosen that drain different water source contributions (glacier melt, snow melt, groundwater). Data were collected at 30 minute intervals using micro-dataloggers. Air temperature data were collected within 7km by the Greenland Survey. Weather conditions were highly variable between field campaigns, with 2013 experiencing below average, and 2014 and 2015 above average, snowfall. Summer water temperatures appear to be high in comparison to some Arctic streams in Alaska and in Svalbard. Winter snowfall extent decreases stream water temperature; and water temperature increases with atmospheric exposure time (distance from source) - illustrating the intertwined controls of water and heat fluxes. These Greenland streams are most strongly influenced by snowmelt, but groundwater contributions could increase with a changing climate due to increased active layer thickness, which may result in increased river temperature with implications for aquatic biodiversity and ecosystem functioning.

Spatial variation in the climatic predictors of species compositional turnover and endemism.

PubMed

Di Virgilio, Giovanni; Laffan, Shawn W; Ebach, Malte C; Chapple, David G

2014-08-01

Previous research focusing on broad-scale or geographically invariant species-environment dependencies suggest that temperature-related variables explain more of the variation in reptile distributions than precipitation. However, species-environment relationships may exhibit considerable spatial variation contingent upon the geographic nuances that vary between locations. Broad-scale, geographically invariant analyses may mask this local variation and their findings may not generalize to different locations at local scales. We assess how reptile-climatic relationships change with varying spatial scale, location, and direction. Since the spatial distributions of diversity and endemism hotspots differ for other species groups, we also assess whether reptile species turnover and endemism hotspots are influenced differently by climatic predictors. Using New Zealand reptiles as an example, the variation in species turnover, endemism and turnover in climatic variables was measured using directional moving window analyses, rotated through 360°. Correlations between the species turnover, endemism and climatic turnover results generated by each rotation of the moving window were analysed using multivariate generalized linear models applied at national, regional, and local scales. At national-scale, temperature turnover consistently exhibited the greatest influence on species turnover and endemism, but model predictive capacity was low (typically r (2) = 0.05, P < 0.001). At regional scales the relative influence of temperature and precipitation turnover varied between regions, although model predictive capacity was also generally low. Climatic turnover was considerably more predictive of species turnover and endemism at local scales (e.g., r (2) = 0.65, P < 0.001). While temperature turnover had the greatest effect in one locale (the northern North Island), there was substantial variation in the relative influence of temperature and precipitation predictors in the remaining four locales. Species turnover and endemism hotspots often occurred in different locations. Climatic predictors had a smaller influence on endemism. Our results caution against assuming that variability in temperature will always be most predictive of reptile biodiversity across different spatial scales, locations and directions. The influence of climatic turnover on the species turnover and endemism of other taxa may exhibit similar patterns of spatial variation. Such intricate variation might be discerned more readily if studies at broad scales are complemented by geographically variant, local-scale analyses.

Planetary boundary layer as an essential component of the earth's climate system

NASA Astrophysics Data System (ADS)

Davy, Richard; Esau, Igor

2015-04-01

Following the traditional engineering approach proposed by Prandtl, the turbulent planetary boundary layers (PBLs) are considered in the climate science as complex, non-linear, essential but nevertheless subordinated components of the earth's climate system. Correspondingly, the temperature variations, dT - a popular and practically important measure of the climate variability, are seen as the system's response to the external heat forcing, Q, e.g. in the energy balance model of the type dT=Q/C (1). The moderation of this response by non-linear feedbacks embedded in the effective heat capacity, C, are to a large degree overlooked. The effective heat capacity is globally determined by the depth of the ocean mixed layer (on multi-decadal and longer time scales) but regionally, over the continents, C is much smaller and determined (on decadal time scales) by the depth, h, of the PBL. The present understanding of the climatological features of turbulent boundary layers is set by the works of Frankignoul & Hasselmann (1976) and Manabe & Stauffer (1980). The former explained how large-scale climate anomalies could be generated in the case of a large C (in the sea surface temperature) by the delta-correlated stochastic forcing (white noise). The latter demonstrated that the climate response to a given forcing is moderated by the depth, h, so that in the shallow PBL the signal should be significantly amplified. At present there are more than 3000 publications (ISI Web of Knowledge) which detail this understanding but the physical mechanisms, which control the boundary layer depth, and statistical relationships between the turbulent and climatological measures remain either unexplored or incorrectly attributed. In order to identify the climatic role of the PBL, the relationships between the PBL depth, h, - as the integral measure of the turbulent processes and micro-circulations due to the surface heterogeneity - and the climatic variability (variations and trends) of temperature have to be established. These relationships are necessary to complete the model (1) where the relationships between temperature variability, dT, and heat forcing, Q, are intensively studied. We demonstrate that the statistical dependences between dT and h becomes the primary factor in controlling the climate features of the earth's climate system when h is shallow (less than about 500 m). Such conditions are found in the cold (with negative surface heat balance on average) and dry (with large-scale air subsidence) climates. To get those climates and their variations correct, the climate models must be able to reproduce the shallow stably-stratified PBL. We show that the present-day CMIP-5 models are systematically and strongly biased towards producing deeper PBLs (between 20-50% deeper than observed) in this part of the parameter space which leads to large errors (around 15 K) and a damped variability of the surface temperatures under these conditions. More generally, this bias indicates that the models represent the earth's cooling processes incorrectly, which may be a part of the puzzle of the observed "hiatus" (or pause) in global warming. Frankignoul, C. & K. Hasselmann, 1977: Stochastic climate models. Part 2, Application to sea-surface temperature anomalies and thermocline variability, Tellus, 29, 289-305. Manabe, S. & R. Stouffer, 1980: Sensitivity of a Global Climate Model to an increase of CO2 concentration in the atmosphere, Journal of Geophysical Research, 85(C10): 5529-5554.

Trends in Extreme Rainfall Frequency in the Contiguous United States: Attribution to Climate Change and Climate Variability Modes

NASA Astrophysics Data System (ADS)

Armal, S.; Devineni, N.; Khanbilvardi, R.

2017-12-01

This study presents a systematic analysis for identifying and attributing trends in the annual frequency of extreme rainfall events across the contiguous United States to climate change and climate variability modes. A Bayesian multilevel model is developed for 1,244 stations simultaneously to test the null hypothesis of no trend and verify two alternate hypotheses: Trend can be attributed to changes in global surface temperature anomalies, or to a combination of cyclical climate modes with varying quasi-periodicities and global surface temperature anomalies. The Bayesian multilevel model provides the opportunity to pool information across stations and reduce the parameter estimation uncertainty, hence identifying the trends better. The choice of the best alternate hypotheses is made based on Watanabe-Akaike Information Criterion, a Bayesian pointwise predictive accuracy measure. Statistically significant time trends are observed in 742 of the 1,244 stations. Trends in 409 of these stations can be attributed to changes in global surface temperature anomalies. These stations are predominantly found in the Southeast and Northeast climate regions. The trends in 274 of these stations can be attributed to the El Nino Southern Oscillations, North Atlantic Oscillation, Pacific Decadal Oscillation and Atlantic Multi-Decadal Oscillation along with changes in global surface temperature anomalies. These stations are mainly found in the Northwest, West and Southwest climate regions.

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

USDA-ARS?s Scientific Manuscript database

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

North Atlantic sub-decadal variability in climate models

NASA Astrophysics Data System (ADS)

Reintges, Annika; Martin, Thomas; Latif, Mojib; Park, Wonsun

2017-04-01

The North Atlantic Oscillation (NAO) is the dominant variability mode for the winter climate of the North Atlantic sector. During a positive (negative) NAO phase, the sea level pressure (SLP) difference between the subtropical Azores high and the subpolar Icelandic low is anomalously strong (weak). This affects, for example, temperature, precipitation, wind, and surface heat flux over the North Atlantic, and over large parts of Europe. In observations we find enhanced sub-decadal variability of the NAO index that goes along with a dipolar sea surface temperature (SST) pattern. The corresponding SLP and SST patterns are reproduced in a control experiment of the Kiel Climate Model (KCM). Large-scale air-sea interaction is suggested to be essential for the North Atlantic sub-decadal variability in the KCM. The Atlantic Meridional Overturning Circulation (AMOC) plays a key role, setting the timescale of the variability by providing a delayed negative feedback to the NAO. The interplay of the NAO and the AMOC on the sub-decadal timescale is further investigated in the CMIP5 model ensemble. For example, the average CMIP5 model AMOC pattern associated with sub-decadal variability is characterized by a deep-reaching dipolar structure, similar to the KCM's sub-decadal AMOC variability pattern. The results suggest that dynamical air-sea interactions are crucial to generate enhanced sub-decadal variability in the North Atlantic climate.

Societal Impacts of Natural Decadal Climate Variability - The Pacemakers of Civilizations

NASA Astrophysics Data System (ADS)

Mehta, V. M.

2017-12-01

Natural decadal climate variability (DCV) is one of the oldest areas of climate research. Building on centuries-long literature, a substantial body of research has emerged in the last two to three decades, focused on understanding causes, mechanisms, and impacts of DCV. Several DCV phenomena - the Pacific Decadal Oscillation (PDO) or the Interdecadal Pacific Oscillation (IPO), tropical Atlantic sea-surface temperature gradient variability (TAG for brevity), West Pacific Warm Pool variability, and decadal variability of El Niño-La Niña events - have been identified in observational records; and are associated with variability of worldwide atmospheric circulations, water vapor transport, precipitation, and temperatures; and oceanic circulations, salinity, and temperatures. Tree-ring based drought index data going back more than 700 years show presence of decadal hydrologic cycles (DHCs) in North America, Europe, and South Asia. Some of these cycles were associated with the rise and fall of civilizations, large-scale famines which killed millions of people, and acted as catalysts for socio-political revolutions. Instrument-measured data confirm presence of such worldwide DHCs associated with DCV phenomena; and show these DCV phenomena's worldwide impacts on river flows, crop productions, inland water-borne transportation, hydro-electricity generation, and agricultural irrigation. Fish catch data also show multiyear to decadal catch variability associated with these DCV phenomena in all oceans. This talk, drawn from my recently-published book (Mehta, V.M., 2017: Natural Decadal Climate Variability: Societal Impacts. CRC Press, Boca Raton, Florida, 326 pp.), will give an overview of worldwide impacts of DCV phenomena, with specific examples of socio-economic-political impacts. This talk will also describe national and international security implications of such societal impacts, and worldwide food security implications. The talk will end with an outline of needed actions to adapt to these impacts.

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

PubMed

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

2017-10-01

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

Tropical cloud feedbacks and natural variability of climate

NASA Technical Reports Server (NTRS)

Miller, R. L.; Del Genio, A. D.

1994-01-01

Simulations of natural variability by two general circulation models (GCMs) are examined. One GCM is a sector model, allowing relatively rapid integration without simplification of the model physics, which would potentially exclude mechanisms of variability. Two mechanisms are found in which tropical surface temperature and sea surface temperature (SST) vary on interannual and longer timescales. Both are related to changes in cloud cover that modulate SST through the surface radiative flux. Over the equatorial ocean, SST and surface temperature vary on an interannual timescale, which is determined by the magnitude of the associated cloud cover anomalies. Over the subtropical ocean, variations in low cloud cover drive SST variations. In the sector model, the variability has no preferred timescale, but instead is characterized by a 'red' spectrum with increasing power at longer periods. In the terrestrial GCM, SST variability associated with low cloud anomalies has a decadal timescale and is the dominant form of global temperature variability. Both GCMs are coupled to a mixed layer ocean model, where dynamical heat transports are prescribed, thus filtering out El Nino-Southern Oscillation (ENSO) and thermohaline circulation variability. The occurrence of variability in the absence of dynamical ocean feedbacks suggests that climatic variability on long timescales can arise from atmospheric processes alone.

Pollen-based temperature and precipitation inferences for the montane forest of Mt. Kilimanjaro during the last Glacial and the Holocene

NASA Astrophysics Data System (ADS)

Schüler, L.; Hemp, A.; Behling, H.

2014-01-01

The relationship between modern pollen-rain taxa and measured climate variables was explored along the elevational gradient of the southern slope of Mt. Kilimanjaro, Tanzania. Pollen assemblages in 28 pollen traps positioned on 14 montane forest vegetation plots were identified and their relationship with climate variables was examined using multivariate statistical methods. Canonical correspondence analysis revealed that the mean annual temperature, mean annual precipitation and minimum temperature each account for significant fractions of the variation in pollen taxa. A training set of 107 modern pollen taxa was used to derive temperature and precipitation transfer functions based on pollen subsets using weighted-averaging-partial-least-squares (WA-PLS) techniques. The transfer functions were then applied to a fossil pollen record from the montane forest of Mt. Kilimanjaro and the climate parameter estimates for the Late Glacial and the Holocene on Mt. Kilimanjaro were inferred. Our results present the first quantitatively reconstructed temperature and precipitation estimates for Mt Kilimanjaro and give highly interesting insights into the past 45 000 yr of climate dynamics in tropical East Africa. The climate reconstructions are consistent with the interpretation of pollen data in terms of vegetation and climate history of afro-montane forest in East Africa. Minimum temperatures above the frostline as well as increased precipitation turn out to be crucial for the development and expansion of montane forest during the Holocene. In contrast, consistently low minimum temperatures as well as about 25% drier climate conditions prevailed during the pre LGM, which kept the montane vegetation composition in a stable state. In prospective studies, the quantitative climate reconstruction will be improved by additional modern pollen rain data, especially from lower elevations with submontane dry forests and colline savanna vegetation in order to extend the reference climate gradient.

Aroma types of flue-cured tobacco in China: spatial distribution and association with climatic factors

NASA Astrophysics Data System (ADS)

Yang, Chao; Wu, Wei; Wu, Shu-Cheng; Liu, Hong-Bin; Peng, Qing

2014-02-01

Aroma types of flue-cured tobacco (FCT) are classified into light, medium, and heavy in China. However, the spatial distribution of FCT aroma types and the relationships among aroma types, chemical parameters, and climatic variables were still unknown at national scale. In the current study, multi-year averaged chemical parameters (total sugars, reducing sugars, nicotine, total nitrogen, chloride, and K2O) of FCT samples with grade of C3F and climatic variables (mean, minimum and maximum temperatures, rainfall, relative humidity, and sunshine hours) during the growth periods were collected from main planting areas across China. Significant relationships were found between chemical parameters and climatic variables ( p < 0.05). A spatial distribution map of FCT aroma types were produced using support vector machine algorithms and chemical parameters. Significant differences in chemical parameters and climatic variables were observed among the three aroma types based on one-way analysis of variance ( p < 0.05). Areas with light aroma type had significantly lower values of mean, maximum, and minimum temperatures than regions with medium and heavy aroma types ( p < 0.05). Areas with heavy aroma type had significantly lower values of rainfall and relative humidity and higher values of sunshine hours than regions with light and medium aroma types ( p < 0.05). The output produced by classification and regression trees showed that sunshine hours, rainfall, and maximum temperature were the most important factors affecting FCT aroma types at national scale.

Evaluating within-population variability in behavior and demography for the adaptive potential of a dispersal-limited species to climate change

USGS Publications Warehouse

Muñoz, David J.; Miller Hesed, Kyle; Grant, Evan H. Campbell; Miller, David A.W.

2016-01-01

Multiple pathways exist for species to respond to changing climates. However, responses of dispersal-limited species will be more strongly tied to ability to adapt within existing populations as rates of environmental change will likely exceed movement rates. Here, we assess adaptive capacity in Plethodon cinereus, a dispersal-limited woodland salamander. We quantify plasticity in behavior and variation in demography to observed variation in environmental variables over a 5-year period. We found strong evidence that temperature and rainfall influence P. cinereus surface presence, indicating changes in climate are likely to affect seasonal activity patterns. We also found that warmer summer temperatures reduced individual growth rates into the autumn, which is likely to have negative demographic consequences. Reduced growth rates may delay reproductive maturity and lead to reductions in size-specific fecundity, potentially reducing population-level persistence. To better understand within-population variability in responses, we examined differences between two common color morphs. Previous evidence suggests that the color polymorphism may be linked to physiological differences in heat and moisture tolerance. We found only moderate support for morph-specific differences for the relationship between individual growth and temperature. Measuring environmental sensitivity to climatic variability is the first step in predicting species' responses to climate change. Our results suggest phenological shifts and changes in growth rates are likely responses under scenarios where further warming occurs, and we discuss possible adaptive strategies for resulting selective pressures.

Spatial and temporal variability in minimum temperature trends in the western U.S. sagebrush steppe

USDA-ARS?s Scientific Manuscript database

Climate is a major driver of ecosystem dynamics. In recent years there has been considerable interest in future climate change and potential impacts on ecosystems and management options. In this paper, we analyzed minimum monthly temperature (T min) for ten rural locations in the western sagebrush...

Optimal ranking regime analysis of intra- to multidecadal U.S. climate variability. Part I: Temperature

USDA-ARS?s Scientific Manuscript database

The Optimal Ranking Regime (ORR) method was used to identify intra- to multi-decadal (IMD) time windows containing significant ranking sequences in U.S. climate division temperature data. The simplicity of the ORR procedure’s output – a time series’ most significant non-overlapping periods of high o...

Last millennium Northern Hemisphere summer temperatures from tree rings: Part II, spatially resolved reconstructions

NASA Astrophysics Data System (ADS)

Anchukaitis, Kevin J.; Wilson, Rob; Briffa, Keith R.; Büntgen, Ulf; Cook, Edward R.; D'Arrigo, Rosanne; Davi, Nicole; Esper, Jan; Frank, David; Gunnarson, Björn E.; Hegerl, Gabi; Helama, Samuli; Klesse, Stefan; Krusic, Paul J.; Linderholm, Hans W.; Myglan, Vladimir; Osborn, Timothy J.; Zhang, Peng; Rydval, Milos; Schneider, Lea; Schurer, Andrew; Wiles, Greg; Zorita, Eduardo

2017-05-01

Climate field reconstructions from networks of tree-ring proxy data can be used to characterize regional-scale climate changes, reveal spatial anomaly patterns associated with atmospheric circulation changes, radiative forcing, and large-scale modes of ocean-atmosphere variability, and provide spatiotemporal targets for climate model comparison and evaluation. Here we use a multiproxy network of tree-ring chronologies to reconstruct spatially resolved warm season (May-August) mean temperatures across the extratropical Northern Hemisphere (40-90°N) using Point-by-Point Regression (PPR). The resulting annual maps of temperature anomalies (750-1988 CE) reveal a consistent imprint of volcanism, with 96% of reconstructed grid points experiencing colder conditions following eruptions. Solar influences are detected at the bicentennial (de Vries) frequency, although at other time scales the influence of insolation variability is weak. Approximately 90% of reconstructed grid points show warmer temperatures during the Medieval Climate Anomaly when compared to the Little Ice Age, although the magnitude varies spatially across the hemisphere. Estimates of field reconstruction skill through time and over space can guide future temporal extension and spatial expansion of the proxy network.

Winter temperature conditions (1670-2010) reconstructed from varved sediments, western Canadian High Arctic

NASA Astrophysics Data System (ADS)

Amann, Benjamin; Lamoureux, Scott F.; Boreux, Maxime P.

2017-09-01

Advances in paleoclimatology from the Arctic have provided insights into long-term climate conditions. However, while past annual and summer temperature have received considerable research attention, comparatively little is known about winter paleoclimate. Arctic winter is of special interest as it is the season with the highest sensitivity to climate change, and because it differs substantially from summer and annual measures. Therefore, information about past changes in winter climate is key to improve our knowledge of past forced climate variability and to reduce uncertainty in climate projections. In this context, Arctic lakes with snowmelt-fed catchments are excellent potential winter climate archives. They respond strongly to snowmelt-induced runoff, and indirectly to winter temperature and snowfall conditions. To date, only a few well-calibrated lake sediment records exist, which appear to reflect site-specific responses with differing reconstructions. This limits the possibility to resolve large-scale winter climate change prior the instrumental period. Here, we present a well-calibrated quantitative temperature and snowfall record for the extended winter season (November through March; NDJFM) from Chevalier Bay (Melville Island, NWT, Canadian Arctic) back to CE 1670. The coastal embayment has a large catchment influenced by nival terrestrial processes, which leads to high sedimentation rates and annual sedimentary structures (varves). Using detailed microstratigraphic analysis from two sediment cores and supported by μ-XRF data, we separated the nival sedimentary units (spring snowmelt) from the rainfall units (summer) and identified subaqueous slumps. Statistical correlation analysis between the proxy data and monthly climate variables reveals that the thickness of the nival units can be used to predict winter temperature (r = 0.71, pc < 0.01, 5-yr filter) and snowfall (r = 0.65, pc < 0.01, 5-yr filter) for the western Canadian High Arctic over the last ca. 400 years. Results reveal a strong variability in winter temperature back to CE 1670 with the coldest decades reconstructed for the period CE 1800-1880, while the warmest decades and major trends are reconstructed for the period CE 1880-1930 (0.26°C/decade) and CE 1970-2010 (0.37°C/decade). Although the first aim of this study was to increase the paleoclimate data coverage for the winter season, the record from Chevalier Bay also holds great potential for more applied climate research such as data-model comparisons and proxy-data assimilation in climate model simulations.

Constraints on Variability of Brightness and Surface Magnetism on Time Scales of Decades to Centuries in the Sun and Sun-Like Stars: A Source of Potential Terrestrial Climate Variability

NASA Technical Reports Server (NTRS)

Baliunas, Sallie L.; Sharber, James (Technical Monitor)

2001-01-01

These four points summarize our work to date. (1) Conciliation of solar and stellar photometric variability. Previous research by us and colleagues suggested that the Sun might at present be showing unusually low photometric variability compared to other sun-like stars. Those early results would question the suitability of the technique of using sun-like stars as proxies for solar irradiance change on time scales of decades to centuries. However, our results indicate the contrary: the Sun's observed short-term (seasonal) and longterm (year-to-year) brightness variations closely agree with observed brightness variations in stars of similar mass and age. (2) We have demonstrated an inverse correlation between the global temperature of the terrestrial lower troposphere, inferred from the NASA Microwave Sounding Unit (MSU) radiometers, and the total area of the Sun covered by coronal holes from January 1979 to present (up to May 2000). Variable fluxes of either solar charged particles or cosmic rays, or both, may influence the terrestrial tropospheric temperature. The geographical pattern of the correlation is consistent with our interpretation of an extra-terrestrial charged particle forcing. (3) Possible climate mechanism amplifying the impact of solar ultraviolet irradiance variations. The key points of our proposed climate hypersensitivity mechanism are: (a) The Sun is more variable in the UV (ultraviolet) than in the visible. However, the increased UV irradiance is mainly absorbed in the lower stratosphere/upper troposphere rather than at the surface. (b) Absorption in the stratosphere raises the temperature moderately around the vicinity of the tropopause, and tends to stabilize the atmosphere against vertical convective/diffusive transport, thus decreasing the flux of heat and moisture carried upward from surface. (c) The decrease in the upward convection of heat and moisture tends to raise the surface temperature because a drier upper atmosphere becomes less cloudy, which in turn allows more solar radiation to reach the Earth's surface. (4) Natural variability in an ocean-atmosphere climate model. We use a 14-region, 6-layer, global thermo-hydrodynamic ocean-atmosphere model to study natural climate variability. All the numerical experiments were performed with no change in the prescribed external boundary conditions (except for the seasonal cycle of the Sun's tilt angle). Therefore, the observed inter-annual variability is of an internal kind. The model results are helpful toward the understanding of the role of nonlinearity in climate change. We have demonstrated a range of possible climate behaviors using our newly developed ocean-atmosphere model. These include climate configurations with no interannual variability, with multi-year periodicities, with continuous chaos, or with chaotically occuring transitions between two discrete substrates. These possible modes of climate behavior are all possible for the real climate, as well as the model. We have shown that small temporary climate influences can trigger shifts both in the mean climate, and among these different types of behavior. Such shifts are not only theoretically plausible, as shown here and elsewhere; they are omnipresent in the climate record on time scales from several years to the age of the Earth. This has two apparently opposite implications for the possibility of anthropogenic global warming. First, any warming which might occur as a result of human influence would be only a fraction of the small-to-large unpredictable natural changes and changes which result from other external causes. On the other hand, small temporary influences such as human influence do have the potential of causing large permanent shifts in mean climate and interannual variability.

Climate variability and vulnerability to climate change: a review

PubMed Central

Thornton, Philip K; Ericksen, Polly J; Herrero, Mario; Challinor, Andrew J

2014-01-01

The focus of the great majority of climate change impact studies is on changes in mean climate. In terms of climate model output, these changes are more robust than changes in climate variability. By concentrating on changes in climate means, the full impacts of climate change on biological and human systems are probably being seriously underestimated. Here, we briefly review the possible impacts of changes in climate variability and the frequency of extreme events on biological and food systems, with a focus on the developing world. We present new analysis that tentatively links increases in climate variability with increasing food insecurity in the future. We consider the ways in which people deal with climate variability and extremes and how they may adapt in the future. Key knowledge and data gaps are highlighted. These include the timing and interactions of different climatic stresses on plant growth and development, particularly at higher temperatures, and the impacts on crops, livestock and farming systems of changes in climate variability and extreme events on pest-weed-disease complexes. We highlight the need to reframe research questions in such a way that they can provide decision makers throughout the food system with actionable answers, and the need for investment in climate and environmental monitoring. Improved understanding of the full range of impacts of climate change on biological and food systems is a critical step in being able to address effectively the effects of climate variability and extreme events on human vulnerability and food security, particularly in agriculturally based developing countries facing the challenge of having to feed rapidly growing populations in the coming decades. PMID:24668802

The rogue nature of hiatuses in a global warming climate

NASA Astrophysics Data System (ADS)

Sévellec, F.; Sinha, B.; Skliris, N.

2016-08-01

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

Skillful prediction of northern climate provided by the ocean

NASA Astrophysics Data System (ADS)

Årthun, Marius; Eldevik, Tor; Viste, Ellen; Drange, Helge; Furevik, Tore; Johnson, Helen L.; Keenlyside, Noel S.

2017-06-01

It is commonly understood that a potential for skillful climate prediction resides in the ocean. It nevertheless remains unresolved to what extent variable ocean heat is imprinted on the atmosphere to realize its predictive potential over land. Here we assess from observations whether anomalous heat in the Gulf Stream's northern extension provides predictability of northwestern European and Arctic climate. We show that variations in ocean temperature in the high latitude North Atlantic and Nordic Seas are reflected in the climate of northwestern Europe and in winter Arctic sea ice extent. Statistical regression models show that a significant part of northern climate variability thus can be skillfully predicted up to a decade in advance based on the state of the ocean. Particularly, we predict that Norwegian air temperature will decrease over the coming years, although staying above the long-term (1981-2010) average. Winter Arctic sea ice extent will remain low but with a general increase towards 2020.

Atmospheric QBO and ENSO indices with high vertical resolution from GNSS radio occultation temperature measurements

NASA Astrophysics Data System (ADS)

Wilhelmsen, Hallgeir; Ladstädter, Florian; Scherllin-Pirscher, Barbara; Steiner, Andrea K.

2018-03-01

We provide atmospheric temperature variability indices for the tropical troposphere and stratosphere based on global navigation satellite system (GNSS) radio occultation (RO) temperature measurements. By exploiting the high vertical resolution and the uniform distribution of the GNSS RO temperature soundings we introduce two approaches, both based on an empirical orthogonal function (EOF) analysis. The first method utilizes the whole vertical and horizontal RO temperature field from 30° S to 30° N and from 2 to 35 km altitude. The resulting indices, the leading principal components, resemble the well-known patterns of the Quasi-Biennial Oscillation (QBO) and the El Niño-Southern Oscillation (ENSO) in the tropics. They provide some information on the vertical structure; however, they are not vertically resolved. The second method applies the EOF analysis on each altitude level separately and the resulting indices contain information on the horizontal variability at each densely available altitude level. They capture more variability than the indices from the first method and present a mixture of all variability modes contributing at the respective altitude level, including the QBO and ENSO. Compared to commonly used variability indices from QBO winds or ENSO sea surface temperature, these new indices cover the vertical details of the atmospheric variability. Using them as proxies for temperature variability is also of advantage because there is no further need to account for response time lags. Atmospheric variability indices as novel products from RO are expected to be of great benefit for studies on atmospheric dynamics and variability, for climate trend analysis, as well as for climate model evaluation.

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

Response of wheat restricted-tillering and vigorous growth traits to variables of climate change.

PubMed

Dias de Oliveira, Eduardo A; Siddique, Kadambot H M; Bramley, Helen; Stefanova, Katia; Palta, Jairo A

2015-02-01

The response of wheat to the variables of climate change includes elevated CO2, high temperature, and drought which vary according to the levels of each variable and genotype. Independently, elevated CO2, high temperature, and terminal drought affect wheat biomass and grain yield, but the interactive effects of these three variables are not well known. The aim of this study was to determine the effects of elevated CO2 when combined with high temperature and terminal drought on the high-yielding traits of restricted-tillering and vigorous growth. It was hypothesized that elevated CO2 alone, rather than combined with high temperature, ameliorates the effects of terminal drought on wheat biomass and grain yield. It was also hypothesized that wheat genotypes with more sink capacity (e.g. high-tillering capacity and leaf area) have more grain yield under combined elevated CO2, high temperature, and terminal drought. Two pairs of sister lines with contrasting tillering and vigorous growth were grown in poly-tunnels in a four-factor completely randomized split-plot design with elevated CO2 (700 µL L(-1)), high day time temperature (3 °C above ambient), and drought (induced from anthesis) in all combinations to test whether elevated CO2 ameliorates the effects of high temperature and terminal drought on biomass accumulation and grain yield. For biomass and grain yield, only main effects for climate change variables were significant. Elevated CO2 significantly increased grain yield by 24-35% in all four lines and terminal drought significantly reduced grain yield by 16-17% in all four lines, while high temperature (3 °C above the ambient) had no significant effect. A trade-off between yield components limited grain yield in lines with greater sink capacity (free-tillering lines). This response suggests that any positive response to predicted changes in climate will not overcome the limitations imposed by the trade-off in yield components. © 2014 Commonwealth of Australia. Global Change Biology © 2014 John Wiley & Sons Ltd.

Recent variability of the tropical tropopause inversion layer

NASA Astrophysics Data System (ADS)

Wang, Wuke; Matthes, Katja; Schmidt, Torsten; Neef, Lisa

2013-12-01

The recent variability of the tropopause temperature and the tropopause inversion layer (TIL) are investigated with Global Positioning System Radio Occultation data and simulations with the National Center for Atmospheric Research's Whole Atmosphere Community Climate Model (WACCM). Over the past decade (2001-2011) the data show an increase of 0.8 K in the tropopause temperature and a decrease of 0.4 K in the strength of the tropopause inversion layer in the tropics, meaning that the vertical temperature gradient has declined, and therefore that the stability above the tropopause has weakened. WACCM simulations with finer vertical resolution show a more realistic TIL structure and variability. Model simulations show that the increased tropopause temperature and the weaker tropopause inversion layer are related to weakened upwelling in the tropics. Such changes in the thermal structure of the upper troposphere and lower stratosphere may have important implications for climate, such as a possible rise in water vapor in the lower stratosphere.

Without Warning: Worker Deaths From Heat 2014-2016.

PubMed

Roelofs, Cora

2018-01-01

Worker deaths from heat exposure are unlike heat deaths in the general population; workers tend to be outside in variable temperatures and younger than sixty-five years. Climate change will increase the frequency, duration, and variability of hot temperatures. Public health warning systems, such as the Heat Index of the National Weather Service, do not generally account for workers' greater likelihood of exposure to direct sunlight or exertion. Only 28% of the 79 worker heat-related fatalities during 2014-2016 occurred on days when the National Weather Service warning would have included the possibility of fatal heat stroke. Common heat illness prevention advice ignores workers' lack of control over their ability to rest and seek cooler temperatures. Additionally, acclimatization, or phased-in work in the heat, may be less useful given temperature variability under climate change. Workers' vulnerability and context of heat exposure should inform public health surveillance and response to prevent heat illness and death.

Variability in solar radiation and temperature explains observed patterns and trends in tree growth rates across four tropical forests.

PubMed

Dong, Shirley Xiaobi; Davies, Stuart J; Ashton, Peter S; Bunyavejchewin, Sarayudh; Supardi, M N Nur; Kassim, Abd Rahman; Tan, Sylvester; Moorcroft, Paul R

2012-10-07

The response of tropical forests to global climate variability and change remains poorly understood. Results from long-term studies of permanent forest plots have reported different, and in some cases opposing trends in tropical forest dynamics. In this study, we examined changes in tree growth rates at four long-term permanent tropical forest research plots in relation to variation in solar radiation, temperature and precipitation. Temporal variation in the stand-level growth rates measured at five-year intervals was found to be positively correlated with variation in incoming solar radiation and negatively related to temporal variation in night-time temperatures. Taken alone, neither solar radiation variability nor the effects of night-time temperatures can account for the observed temporal variation in tree growth rates across sites, but when considered together, these two climate variables account for most of the observed temporal variability in tree growth rates. Further analysis indicates that the stand-level response is primarily driven by the responses of smaller-sized trees (less than 20 cm in diameter). The combined temperature and radiation responses identified in this study provide a potential explanation for the conflicting patterns in tree growth rates found in previous studies.

Investigating the impact of diurnal cycle of SST on the intraseasonal and climate variability

NASA Astrophysics Data System (ADS)

Tseng, W. L.; Hsu, H. H.; Chang, C. W. J.; Keenlyside, N. S.; Lan, Y. Y.; Tsuang, B. J.; Tu, C. Y.

2016-12-01

The diurnal cycle is a prominent feature of our climate system and the most familiar example of externally forced variability. Despite this it remains poorly simulated in state-of-the-art climate models. A particular problem is the diurnal cycle in sea surface temperature (SST), which is a key variable in air-sea heat flux exchange. In most models the diurnal cycle in SST is not well resolved, due to insufficient vertical resolution in the upper ocean mixed-layer and insufficiently frequent ocean-atmosphere coupling. Here, we coupled a 1-dimensional ocean model (SIT) to two atmospheric general circulation model (ECHAM5 and CAM5). In particular, we focus on improving the representations of the diurnal cycle in SST in a climate model, and investigate the role of the diurnal cycle in climate and intraseasonal variability.

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

PubMed

Kerhoulas, Lucy P; Kane, Jeffrey M

2012-01-01

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

Climatic effects on mosquito abundance in Mediterranean wetlands

PubMed Central

2014-01-01

Background The impact of climate change on vector-borne diseases is highly controversial. One of the principal points of debate is whether or not climate influences mosquito abundance, a key factor in disease transmission. Methods To test this hypothesis, we analysed ten years of data (2003–2012) from biweekly surveys to assess inter-annual and seasonal relationships between the abundance of seven mosquito species known to be pathogen vectors (West Nile virus, Usutu virus, dirofilariasis and Plasmodium sp.) and several climatic variables in two wetlands in SW Spain. Results Within-season abundance patterns were related to climatic variables (i.e. temperature, rainfall, tide heights, relative humidity and photoperiod) that varied according to the mosquito species in question. Rainfall during winter months was positively related to Culex pipiens and Ochlerotatus detritus annual abundances. Annual maximum temperatures were non-linearly related to annual Cx. pipiens abundance, while annual mean temperatures were positively related to annual Ochlerotatus caspius abundance. Finally, we modelled shifts in mosquito abundances using the A2 and B2 temperature and rainfall climate change scenarios for the period 2011–2100. While Oc. caspius, an important anthropophilic species, may increase in abundance, no changes are expected for Cx. pipiens or the salt-marsh mosquito Oc. detritus. Conclusions Our results highlight that the effects of climate are species-specific, place-specific and non-linear and that linear approaches will therefore overestimate the effect of climate change on mosquito abundances at high temperatures. Climate warming does not necessarily lead to an increase in mosquito abundance in natural Mediterranean wetlands and will affect, above all, species such as Oc. caspius whose numbers are not closely linked to rainfall and are influenced, rather, by local tidal patterns and temperatures. The final impact of changes in vector abundance on disease frequency will depend on the direct and indirect effects of climate and other parameters related to pathogen amplification and spillover on humans and other vertebrates. PMID:25030527

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

NASA Technical Reports Server (NTRS)

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.

Climate change at upper treeline: How do trees on the edge react to increasing temperatures?

NASA Astrophysics Data System (ADS)

Jochner, Matthias; Bugmann, Harald; Nötzli, Magdalena; Bigler, Christof

2017-04-01

Treeline ecotones are thought to be particularly sensitive to climate warming, and an alteration of their growth conditions may have important implications for the ecosystem services they supply in mountain regions. We use a novel approach to quantify effects of a changing climate on tree growth, using case studies in the European Alps. We compiled tree-ring data from almost 600 trees of four species at treeline in three climate regions of Switzerland. Temperature loggers installed along transects provided data for a precise interpolation of temperatures experienced by the sampled trees. To assess the influence of temperature on annual growth, we used linear mixed-effects models, allowing us to quantify effect sizes and to account for between-tree growth variability. After removing biological growth trends, we isolated temporal trends of ring-width indices. Furthermore, we fitted non-linear regression models to radial growth rates of individual years with temperature and tree age as predicting covariates for a fine-scale investigation of the temperature dependency of tree growth. For all species, climate-growth linear mixed-effects models indicated strong positive responses of ring-width indices to temperature in early summer and previous year's autumn, featuring considerable between-tree variability. All species showed positive ring-width index trends at treeline but different interactions with elevation: Larix decidua exhibited a declining ring-width index trend with decreasing elevation, whereas Picea abies, Pinus cembra and Pinus mugo showed increasing and/or stable trends. Not only reflected our findings the effects of ameliorated growth conditions, they might have also revealed suspected negative and positive feedbacks of climate change on growth, and increased the knowledge about the functional form and parameterization of the temperature dependency of tree growth.

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

NASA Astrophysics Data System (ADS)

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.

Influence of Climate Oscillations on Extreme Precipitation in Texas

NASA Astrophysics Data System (ADS)

Bhatia, N.; Singh, V. P.; Srivastav, R. K.

2016-12-01

Much research in the field of hydroclimatology is focusing on the impact of climate variability on hydrologic extremes. Recent studies show that the unique geographical location and the enormous areal extent, coupled with extensive variations in climate oscillations, have intensified the regional hydrologic cycle of Texas. The state-wide extreme precipitation events can actually be attributed to sea-surface pressure and temperature anomalies, such as Bermuda High and Jet Streams, which are further triggered by such climate oscillations. This study aims to quantify the impact of five major Atlantic and Pacific Ocean related climate oscillations: (i) Atlantic Multidecadal Oscillation (AMO), (ii) North Atlantic Oscillation (NAO), (iii) Pacific Decadal Oscillation (PDO), (iv) Pacific North American Pattern (PNA), and (v) Southern Oscillation Index (SOI), on extreme precipitation in Texas. Their respective effects will be determined for both climate divisions delineated by the National Climatic Data Centre (NCDC) and climate regions defined by the Köppen Climate Classification System. This study will adopt a weighted correlation approach to attain the robust correlation coefficients while addressing the regionally variable data outliers for extreme precipitation. Further, the variation of robust correlation coefficients across Texas is found to be related to the station elevation, historical average temperature, and total precipitation in the months of extremes. The research will shed light on the relationship between precipitation extremes and climate variability, thus aiding regional water boards in planning, designing, and managing the respective systems as per the future climate change.

Raised temperatures over the Kericho tea estates: revisiting the climate in the East African highlands malaria debate

PubMed Central

2011-01-01

Background Whether or not observed increases in malaria incidence in the Kenyan Highlands during the last thirty years are associated with co-varying changes in local temperature, possibly connected to global changes in climate, has been debated for over a decade. Studies, using differing data sets and methodologies, produced conflicting results regarding the occurrence of temperature trends and their likelihood of being responsible, at least in part, for the increases in malaria incidence in the highlands of western Kenya. A time series of quality controlled daily temperature and rainfall data from Kericho, in the Kenyan Highlands, may help resolve the controversy. If significant temperature trends over the last three decades have occurred then climate should be included (along with other factors such as land use change and drug resistance) as a potential driver of the observed increases in malaria in the region. Methods Over 30 years (1 January 1979 to 31 December 2009) of quality controlled daily observations ( > 97% complete) of maximum, minimum and mean temperature were used in the analysis of trends at Kericho meteorological station, sited in a tea growing area of Kenya's western highlands. Inhomogeneities in all the time series were identified and corrected. Linear trends were identified via a least-squares regression analysis with statistical significance assessed using a two-tailed t-test. These 'gold standard' meteorological observations were compared with spatially interpolated temperature datasets that have been developed for regional or global applications. The relationship of local climate processes with larger climate variations, including tropical sea surface temperatures (SST), and El Niño-Southern Oscillation (ENSO) was also assessed. Results An upward trend of ≈0.2°C/decade was observed in all three temperature variables (P < 0.01). Mean temperature variations in Kericho were associated with large-scale climate variations including tropical SST (r = 0.50; p < 0.01). Local rainfall was found to have inverse effects on minimum and maximum temperature. Three versions of a spatially interpolated temperature data set showed markedly different trends when compared with each other and with the Kericho station observations. Conclusion This study presents evidence of a warming trend in observed maximum, minimum and mean temperatures at Kericho during the period 1979 to 2009 using gold standard meteorological observations. Although local factors may be contributing to these trends, the findings are consistent with variability and trends that have occurred in correlated global climate processes. Climate should therefore not be dismissed as a potential driver of observed increases in malaria seen in the region during recent decades, however its relative importance compared to other factors needs further elaboration. Climate services, pertinent to the achievement of development targets such as the Millennium Development Goals and the analysis of infectious disease in the context of climate variability and change are being developed and should increase the availability of relevant quality controlled climate data for improving development decisions. The malaria community should seize this opportunity to make their needs heard. PMID:21241505

ARIMA representation for daily solar irradiance and surface air temperature time series

NASA Astrophysics Data System (ADS)

Kärner, Olavi

2009-06-01

Autoregressive integrated moving average (ARIMA) models are used to compare long-range temporal variability of the total solar irradiance (TSI) at the top of the atmosphere (TOA) and surface air temperature series. The comparison shows that one and the same type of the model is applicable to represent the TSI and air temperature series. In terms of the model type surface air temperature imitates closely that for the TSI. This may mean that currently no other forcing to the climate system is capable to change the random walk type variability established by the varying activity of the rotating Sun. The result should inspire more detailed examination of the dependence of various climate series on short-range fluctuations of TSI.

Surprisingly robust projections of soil temperature and moisture for North American drylands in the 21st century

NASA Astrophysics Data System (ADS)

Bradford, J. B.; Schlaepfer, D.; Palmquist, K. A.; Lauenroth, W.

2017-12-01

Climate projections for western North America suggest temperature increases that are relatively consistent across climate models. However, precipitation projections are less consistent, especially in the Southwest, promoting uncertainty about the future of soil moisture and drought. We utilized a daily time-step ecosystem water balance model to characterize soil temperature and moisture patterns at a 10-km resolution across western North America for historical (1980-2010), mid-century (2020-2050), and late century (2070-2100). We simulated soil moisture and temperature under two representative concentration pathways and eleven climate models (selected strategically to represent the range of variability in projections among the full set of models in the CMIP5 database and perform well in hind-cast comparisons for the region), and we use the results to identify areas with robust projections, e.g. areas where the large majority of models agree in the direction of change in long-term average soil moisture or temperature. Rising air temperatures will increase average soil temperatures across western North America and expand the area of mesic and thermic soil temperature regimes while decreasing the area of cryic and frigid regimes. Future soil moisture conditions are relatively consistent across climate models for much of the region, including many areas with variable precipitation trajectories. Consistent projections for drier soils are expected in most of Arizona and New Mexico, similar to previous studies. Other regions with projections for declining soil moisture include the central and southern U.S. Great Plains and large parts of southern British Columbia. By contrast, areas with robust projections for increasing soil moisture include northeastern Montana, southern Alberta and Saskatchewan, and many areas in the intermountain west dominated by big sagebrush. In addition, seasonal moisture patterns in much of the western US drylands are expected to shift toward cool-season water availability, with potentially important consequences for ecosystem structure and function. These results provide a framework for coping with variability in climate projections and assessing climate change impacts on dryland ecosystems.

Climatic variability leads to later seasonal flowering of Floridian plants.

PubMed

Von Holle, Betsy; Wei, Yun; Nickerson, David

2010-07-21

Understanding species responses to global change will help predict shifts in species distributions as well as aid in conservation. Changes in the timing of seasonal activities of organisms over time may be the most responsive and easily observable indicator of environmental changes associated with global climate change. It is unknown how global climate change will affect species distributions and developmental events in subtropical ecosystems or if climate change will differentially favor nonnative species. Contrary to previously observed trends for earlier flowering onset of plant species with increasing spring temperatures from mid and higher latitudes, we document a trend for delayed seasonal flowering among plants in Florida. Additionally, there were few differences in reproductive responses by native and nonnative species to climatic changes. We argue that plants in Florida have different reproductive cues than those from more northern climates. With global change, minimum temperatures have become more variable within the temperate-subtropical zone that occurs across the peninsula and this variation is strongly associated with delayed flowering among Florida plants. Our data suggest that climate change varies by region and season and is not a simple case of species responding to consistently increasing temperatures across the region. Research on climate change impacts need to be extended outside of the heavily studied higher latitudes to include subtropical and tropical systems in order to properly understand the complexity of regional and seasonal differences of climate change on species responses.

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

Treesearch

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

2013-01-01

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

Seasonality of change: Summer warming rates do not fully represent effects of climate change on lake temperatures

USGS Publications Warehouse

Winslow, Luke; Read, Jordan S.; Hansen, Gretchen J. A.; Rose, Kevin C.; Robertson, Dale M.

2017-01-01

Responses in lake temperatures to climate warming have primarily been characterized using seasonal metrics of surface-water temperatures such as summertime or stratified period average temperatures. However, climate warming may not affect water temperatures equally across seasons or depths. We analyzed a long-term dataset (1981–2015) of biweekly water temperature data in six temperate lakes in Wisconsin, U.S.A. to understand (1) variability in monthly rates of surface- and deep-water warming, (2) how those rates compared to summertime average trends, and (3) if monthly heterogeneity in water temperature trends can be predicted by heterogeneity in air temperature trends. Monthly surface-water temperature warming rates varied across the open-water season, ranging from 0.013 in August to 0.073°C yr−1 in September (standard deviation [SD]: 0.025°C yr−1). Deep-water trends during summer varied less among months (SD: 0.006°C yr−1), but varied broadly among lakes (–0.056°C yr−1 to 0.035°C yr−1, SD: 0.034°C yr−1). Trends in monthly surface-water temperatures were well correlated with air temperature trends, suggesting monthly air temperature trends, for which data exist at broad scales, may be a proxy for seasonal patterns in surface-water temperature trends during the open water season in lakes similar to those studied here. Seasonally variable warming has broad implications for how ecological processes respond to climate change, because phenological events such as fish spawning and phytoplankton succession respond to specific, seasonal temperature cues.

Association between Climatic Variables and Malaria Incidence: A Study in Kokrajhar District of Assam, India

PubMed Central

Nath, Dilip C.; Mwchahary, Dimacha Dwibrang

2013-01-01

A favorable climatic condition for transmission of malaria prevails in Kokrajhar district throughout the year. A sizeable part of the district is covered by forest due to which dissimilar dynamics of malaria transmission emerge in forest and non-forest areas. Observed malaria incidence rates of forest area, non-forest area and the whole district over the period 2001-2010 were considered for analyzing temporal correlation between malaria incidence and climatic variables. Associations between the two were examined by Pearson correlation analysis. Cross-correlation tests were performed between pre-whitened series of climatic variable and malaria series. Linear regressions were used to obtain linear relationships between climatic factors and malaria incidence, while weighted least squares regression was used to construct models for explaining and estimating malaria incidence rates. Annual concentration of malaria incidence was analyzed by Markham technique by obtaining seasonal index. Forest area and non-forest area have distinguishable malaria seasons. Relative humidity was positively correlated with z malaria incidence, while temperature series were negatively correlated with non-forest malaria incidence. There was higher seasonality of concentration of malaria in the forest area than non-forest area. Significant correlation between annual changes in malaria cases in forest area and temperature was observed (coeff=0.689, p=0.040). Separate reliable models constructed for forecasting malaria incidence rates based on the combined influence of climatic variables on malaria incidence in different areas of the district were able to explain substantial percentage of observed variability in the incidence rates (R2adj=45.4%, 50.6%, 47.2%; p< .001 for all). There is an intricate association between climatic variables and malaria incidence of the district. Climatic variables influence malaria incidence in forest area and non-forest area in different ways. Rainfall plays a primary role in characterizing malaria incidences in the district. Malaria parasites in the district had adapted to a relative humidity condition higher than the normal range for transmission in India. Instead of individual influence of the climatic variables, their combined influence was utilizable for construction of models. PMID:23283041

Association between climatic variables and malaria incidence: a study in Kokrajhar district of Assam, India.

PubMed

Nath, Dilip C; Mwchahary, Dimacha Dwibrang

2012-11-11

A favorable climatic condition for transmission of malaria prevails in Kokrajhar district throughout the year. A sizeable part of the district is covered by forest due to which dissimilar dynamics of malaria transmission emerge in forest and non-forest areas. Observed malaria incidence rates of forest area, non-forest area and the whole district over the period 2001-2010 were considered for analyzing temporal correlation between malaria incidence and climatic variables. Associations between the two were examined by Pearson correlation analysis. Cross-correlation tests were performed between pre-whitened series of climatic variable and malaria series. Linear regressions were used to obtain linear relationships between climatic factors and malaria incidence, while weighted least squares regression was used to construct models for explaining and estimating malaria incidence rates. Annual concentration of malaria incidence was analyzed by Markham technique by obtaining seasonal index. Forest area and non-forest area have distinguishable malaria seasons. Relative humidity was positively correlated with forest malaria incidence, while temperature series were negatively correlated with non-forest malaria incidence. There was higher seasonality of concentration of malaria in the forest area than non-forest area. Significant correlation between annual changes in malaria cases in forest area and temperature was observed (coeff=0.689, p=0.040). Separate reliable models constructed for forecasting malaria incidence rates based on the combined influence of climatic variables on malaria incidence in different areas of the district were able to explain substantial percentage of observed variability in the incidence rates (R2adj=45.4%, 50.6%, 47.2%; p< .001 for all). There is an intricate association between climatic variables and malaria incidence of the district. Climatic variables influence malaria incidence in forest area and non-forest area in different ways. Rainfall plays a primary role in characterizing malaria incidences in the district. Malaria parasites in the district had adapted to a relative humidity condition higher than the normal range for transmission in India. Instead of individual influence of the climatic variables, their combined influence was utilizable for construction of models.

A modern pollen-climate dataset from the Darjeeling area, eastern Himalaya: Assessing its potential for past climate reconstruction

NASA Astrophysics Data System (ADS)

Ghosh, Ruby; Bruch, Angela A.; Portmann, Felix; Bera, Subir; Paruya, Dipak Kumar; Morthekai, P.; Ali, Sheikh Nawaz

2017-10-01

Relying on the ability of pollen assemblages to differentiate among elevationally stratified vegetation zones, we assess the potential of a modern pollen-climate dataset from the Darjeeling area, eastern Himalaya, in past climate reconstructions. The dataset includes 73 surface samples from 25 sites collected from a c. 130-3600 m a.s.l. elevation gradient along a horizontal distance of c. 150 km and 124 terrestrial pollen taxa, which are analysed with respect to various climatic and environmental variables such as mean annual temperature (MAT), mean annual precipitation (MAP), mean temperature of coldest quarter (MTCQ), mean temperature of warmest quarter (MTWQ), mean precipitation of driest quarter (MPDQ), mean precipitation of wettest quarter (MPWQ), AET (actual evapotranspiration) and MI (moisture index). To check the reliability of the modern pollen-climate relationships different ordination methods are employed and subsequently tested with Huisman-Olff-Fresco (HOF) models. A series of pollen-climate parameter transfer functions using weighted-averaging regression and calibration partial least squares (WA-PLS) models are developed to reconstruct past climate changes from modern pollen data, and have been cross-validated. Results indicate that three of the environmental variables i.e., MTCQ, MPDQ and MI have strong potential for past climate reconstruction based on the available surface pollen dataset. The potential of the present modern pollen-climate relationship for regional quantitative paleoclimate reconstruction is further tested on a Late Quaternary fossil pollen profile from the Darjeeling foothill region with previously reconstructed and quantified climate. The good agreement with existing data allows for new insights in the hydroclimatic conditions during the Last glacial maxima (LGM) with (winter) temperature being the dominant controlling factor for glacial changes during the LGM in the eastern Himalaya.

Quantitative Analysis of Relevant Soil, Land-use and Climate Characteristics on Landscape Degradation in Hungary

NASA Astrophysics Data System (ADS)

Kertesz, Adam; Mika, Janos; Jakab, Gergely; Palinkas, Melinda

2017-04-01

The objective of our research is to survey degradation processes acting in each micro-region of Hungary in connection with geographical and climatic characteristics. A survey of land degradation processes has been carried out at medium scale (1:50 000) to identify the affected areas of the region. Over 18,000 rectangles of Hungary have been digitally characterised for several types of land degradation. Water-flow type gully erosion and soil-loss (RUSLE, 2015: Esdac-data) are studied for dependent variables in this study. USDA textural classes, available water capacity, bulk density, clay content, coarse fragments, silt content, sand content, soil parent material, soil texture, land-use type (Corine, 2012) are used for non-climatic variables. Some of these characteristics are quantified in a non-scalable way, so the first step was to arrange these qualitative codes or pseudo-numbers into monotonous order for including them into the following multi-regression analyses. Data available from the CarpatClim Project (www.carpatclim-eu.org/pages/home) for 1961-2010 are also used in their 50 years averages is seasonal and annual resolution. The selected variables from this gridded data set are global radiation, daily mean temperature, maximum and minimum temperature, number of extreme cold days (< 20 C), precipitation, extreme wet days (>20 mm), days with utilizable precipitation (>1mm/d), potential evapotranspiration, Palmer Index (PDSI), Palfai Index (PAI), relative humidity and wind speed at 10 m height. The gully erosion processes strongly depend on the investigated non-climatic variables, mostly on parent material and slope. The group of further climatic factors is formed by winter relative humidity, wind speed and all-year round Palmer index. Besides leading role of the above non-climatic factors, additional effects of the significant climate variables are difficult to interpret. Nevertheless, the partial effects of these climate variables are combined with future climate scenarios available from GCM and RCM studies for Hungary. The real climate change effects may likely be stronger, than those obtained by this combination, due to inter-dependences between the non-climatic factors and climate variations. The study has been supported by the OTKA-K108755 project.

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

NASA Astrophysics Data System (ADS)

Murari, K. K.; Jayaraman, T.

2014-12-01

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

The effect of vaccination coverage and climate on Japanese encephalitis in Sarawak, Malaysia.

PubMed

Impoinvil, Daniel E; Ooi, Mong How; Diggle, Peter J; Caminade, Cyril; Cardosa, Mary Jane; Morse, Andrew P; Baylis, Matthew; Solomon, Tom

2013-01-01

Japanese encephalitis (JE) is the leading cause of viral encephalitis across Asia with approximately 70,000 cases a year and 10,000 to 15,000 deaths. Because JE incidence varies widely over time, partly due to inter-annual climate variability effects on mosquito vector abundance, it becomes more complex to assess the effects of a vaccination programme since more or less climatically favourable years could also contribute to a change in incidence post-vaccination. Therefore, the objective of this study was to quantify vaccination effect on confirmed Japanese encephalitis (JE) cases in Sarawak, Malaysia after controlling for climate variability to better understand temporal dynamics of JE virus transmission and control. Monthly data on serologically confirmed JE cases were acquired from Sibu Hospital in Sarawak from 1997 to 2006. JE vaccine coverage (non-vaccine years vs. vaccine years) and meteorological predictor variables, including temperature, rainfall and the Southern Oscillation index (SOI) were tested for their association with JE cases using Poisson time series analysis and controlling for seasonality and long-term trend. Over the 10-years surveillance period, 133 confirmed JE cases were identified. There was an estimated 61% reduction in JE risk after the introduction of vaccination, when no account is taken of the effects of climate. This reduction is only approximately 45% when the effects of inter-annual variability in climate are controlled for in the model. The Poisson model indicated that rainfall (lag 1-month), minimum temperature (lag 6-months) and SOI (lag 6-months) were positively associated with JE cases. This study provides the first improved estimate of JE reduction through vaccination by taking account of climate inter-annual variability. Our analysis confirms that vaccination has substantially reduced JE risk in Sarawak but this benefit may be overestimated if climate effects are ignored.

What Climate Sensitivity Index Is Most Useful for Projections?

NASA Astrophysics Data System (ADS)

Grose, Michael R.; Gregory, Jonathan; Colman, Robert; Andrews, Timothy

2018-02-01

Transient climate response (TCR), transient response at 140 years (T140), and equilibrium climate sensitivity (ECS) indices are intended as benchmarks for comparing the magnitude of climate response projected by climate models. It is generally assumed that TCR or T140 would explain more variability between models than ECS for temperature change over the 21st century, since this timescale is the realm of transient climate change. Here we find that TCR explains more variability across Coupled Model Intercomparison Project phase 5 than ECS for global temperature change since preindustrial, for 50 or 100 year global trends up to the present, and for projected change under representative concentration pathways in regions of delayed warming such as the Southern Ocean. However, unexpectedly, we find that ECS correlates higher than TCR for projected change from the present in the global mean and in most regions. This higher correlation does not relate to aerosol forcing, and the physical cause requires further investigation.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Regional Climate Change Hotspots over Africa

NASA Astrophysics Data System (ADS)

Anber, U.

2009-04-01

Regional Climate Change Index (RCCI), is developed based on regional mean precipitation change, mean surface air temperature change, and change in precipitation and temperature interannual variability. The RCCI is a comparative index designed to identify the most responsive regions to climate change, or Hot- Spots. The RCCI is calculated for Seven land regions over North Africa and Arabian region from the latest set of climate change projections by 14 global climates for the A1B, A2 and B1 IPCC emission scenarios. The concept of climate change can be approaches from the viewpoint of vulnerability or from that of climate response. In the former case a Hot-Spot can be defined as a region for which potential climate change impacts on the environment or different activity sectors can be particularly pronounced. In the other case, a Hot-Spot can be defined as a region whose climate is especially responsive to global change. In particular, the characterization of climate change response-based Hot-Spot can provide key information to identify and investigate climate change Hot-Spots based on results from multi-model ensemble of climate change simulations performed by modeling groups from around the world as contributions to the Assessment Report of Intergovernmental Panel on Climate Change (IPCC). A Regional Climate Change Index (RCCI) is defined based on four variables: change in regional mean surface air temperature relative to the global average temperature change ( or Regional Warming Amplification Factor, RWAF ), change in mean regional precipitation ( , of present day value ), change in regional surface air temperature interannual variability ( ,of present day value), change in regional precipitation interannual variability ( , of present day value ). In the definition of the RCCI it is important to include quantities other than mean change because often mean changes are not the only important factors for specific impacts. We thus also include inter annual variability, which is critical for many activity sectors, such as agriculture and water management. The RCCI is calculated for the above mentioned set of global climate change simulations and is inter compared across regions to identify climate change, Hot- Spots, that is regions with the largest values of RCCI. It is important to stress that, as will be seen, the RCCI is a comparative index, that is a small RCCI value does not imply a small absolute change, but only a small climate response compared to other regions. The models used are: CCMA-3-T47 CNRM-CM3 CSIRO-MK3 GFDL-CM2-0 GISS-ER INMCM3 IPSL-CM4 MIROC3-2M MIUB-ECHO-G MPI-ECHAM5 MRI-CGCM2 NCAR-CCSM3 NCAR-PCM1 UKMO-HADCM3 Note that the 3 IPCC emission scenarios, A1B, B1 and A2 almost encompass the entire IPCC scenario range, the A2 being close to the high end of the range, the B1 close to the low end and the A1B lying toward the middle of the range. The model data are obtained from the IPCC site and are interpolated onto a common 1 degree grid to facilitate intercomparison. The RCCI is here defined as in Giorgi (2006), except that the entire yea is devided into two six months periods, D J F M A M and J J A S O N. RCCI=[n(∆P)＋n(∆σP)+n(RWAF)+n(∆σT)]D...M + [n(∆P)＋n(∆σP)+n(RWAF)+n(∆σT)]J…N (1)

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Complex terrain alters temperature and moisture limitations of forest soil respiration across a semiarid to subalpine gradient

DOE PAGES

Berryman, E. M.; Barnard, H. R.; Adams, H. R.; ...

2015-02-10

Forest soil respiration is a major carbon (C) flux that is characterized by significant variability in space and time. In this paper, we quantified growing season soil respiration during both a drought year and a nondrought year across a complex landscape to identify how landscape and climate interact to control soil respiration. We asked the following questions: (1) How does soil respiration vary across the catchments due to terrain-induced variability in moisture availability and temperature? (2) Does the relative importance of moisture versus temperature limitation of respiration vary across space and time? And (3) what terrain elements are important formore » dictating the pattern of soil respiration and its controls? Moisture superseded temperature in explaining watershed respiration patterns, with wetter yet cooler areas higher up and on north facing slopes yielding greater soil respiration than lower and south facing areas. Wetter subalpine forests had reduced moisture limitation in favor of greater seasonal temperature limitation, and the reverse was true for low-elevation semiarid forests. Coincident climate poorly predicted soil respiration in the montane transition zone; however, antecedent precipitation from the prior 10 days provided additional explanatory power. A seasonal trend in respiration remained after accounting for microclimate effects, suggesting that local climate alone may not adequately predict seasonal variability in soil respiration in montane forests. Finally, soil respiration climate controls were more strongly related to topography during the drought year highlighting the importance of landscape complexity in ecosystem response to drought.« less

Complex terrain alters temperature and moisture limitations of forest soil respiration across a semiarid to subalpine gradient

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

Berryman, E. M.; Barnard, H. R.; Adams, H. R.

Forest soil respiration is a major carbon (C) flux that is characterized by significant variability in space and time. In this paper, we quantified growing season soil respiration during both a drought year and a nondrought year across a complex landscape to identify how landscape and climate interact to control soil respiration. We asked the following questions: (1) How does soil respiration vary across the catchments due to terrain-induced variability in moisture availability and temperature? (2) Does the relative importance of moisture versus temperature limitation of respiration vary across space and time? And (3) what terrain elements are important formore » dictating the pattern of soil respiration and its controls? Moisture superseded temperature in explaining watershed respiration patterns, with wetter yet cooler areas higher up and on north facing slopes yielding greater soil respiration than lower and south facing areas. Wetter subalpine forests had reduced moisture limitation in favor of greater seasonal temperature limitation, and the reverse was true for low-elevation semiarid forests. Coincident climate poorly predicted soil respiration in the montane transition zone; however, antecedent precipitation from the prior 10 days provided additional explanatory power. A seasonal trend in respiration remained after accounting for microclimate effects, suggesting that local climate alone may not adequately predict seasonal variability in soil respiration in montane forests. Finally, soil respiration climate controls were more strongly related to topography during the drought year highlighting the importance of landscape complexity in ecosystem response to drought.« less

Complex terrain alters temperature and moisture limitations of forest soil respiration across a semiarid to subalpine gradient

USGS Publications Warehouse

Berryman, Erin Michele; Barnard, H.R.; Adams, H.R.; Burns, M.A.; Gallo, E.; Brooks, P.D.

2015-01-01

Forest soil respiration is a major carbon (C) flux that is characterized by significant variability in space and time. We quantified growing season soil respiration during both a drought year and a nondrought year across a complex landscape to identify how landscape and climate interact to control soil respiration. We asked the following questions: (1) How does soil respiration vary across the catchments due to terrain-induced variability in moisture availability and temperature? (2) Does the relative importance of moisture versus temperature limitation of respiration vary across space and time? And (3) what terrain elements are important for dictating the pattern of soil respiration and its controls? Moisture superseded temperature in explaining watershed respiration patterns, with wetter yet cooler areas higher up and on north facing slopes yielding greater soil respiration than lower and south facing areas. Wetter subalpine forests had reduced moisture limitation in favor of greater seasonal temperature limitation, and the reverse was true for low-elevation semiarid forests. Coincident climate poorly predicted soil respiration in the montane transition zone; however, antecedent precipitation from the prior 10 days provided additional explanatory power. A seasonal trend in respiration remained after accounting for microclimate effects, suggesting that local climate alone may not adequately predict seasonal variability in soil respiration in montane forests. Soil respiration climate controls were more strongly related to topography during the drought year highlighting the importance of landscape complexity in ecosystem response to drought.

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

PubMed

Stillman, Jonathon H; Tagmount, Abderrahmane

2009-10-01

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

Implications of land use change in tropical West Africa under global warming

NASA Astrophysics Data System (ADS)

Brücher, Tim; Claussen, Martin

2015-04-01

Northern Africa, and the Sahel in particular, are highly vulnerable to climate change, due to strong exposure to increasing temperature, precipitation variability, and population growth. A major link between climate and humans in this region is land use and associated land cover change, mainly where subsistence farming prevails. But how strongly does climate change affect land use and how strongly does land use feeds back into climate change? To which extent may climate-induced water, food and wood shortages exacerbate conflict potential and lead changes in land use and to migration? Estimates of possible changes in African climate vary among the Earth System Models participating in the recent Coupled Model Intercomparison (CMIP5) exercise, except for the region adjacent to the Mediterranean Sea, where a significant decrease of precipitation emerges. While all models agree in a strong temperature increase, rainfall uncertainties for most parts of the Sahara, Sahel, and Sudan are higher. Here we present results of complementary experiments based on extreme and idealized land use change scenarios within a future climate.. We use the MPI-ESM forced with a strong green house gas scenario (RCP8.5) and apply an additional land use forcing by varying largely the intensity and kind of agricultural practice. By these transient experiments (until 2100) we elaborate the additional impact on climate due to strong land use forcing. However, the differences are mostly insignificant. The greenhouse gas caused temperature increase and the high variability in the West African Monsoon rainfall superposes the minor changes in climate due to land use. While simulated climate key variables like precipitation and temperature are not distinguishable from the CMIP5 RCP8.5 results, an additional greening is simulated, when crops are demanded. Crops have lower water usage than pastureland has. This benefits available soil water, which is taken up by the natural vegetation and makes it more productive. Given the limitations of an ESM, the findings of our study show that changes in the kind and intensity of land use have minor effects on the climate. Consequently, implications of extreme land use on e.g. human security, conflict or migration can be investigated in offline simulations.

Spatial patterns of simulated transpiration response to climate variability in a snow dominated mountain ecosystem

USGS Publications Warehouse

Christensen, L.; Tague, C.L.; Baron, Jill S.

2008-01-01

Transpiration is an important component of soil water storage and stream-flow and is linked with ecosystem productivity, species distribution, and ecosystem health. In mountain environments, complex topography creates heterogeneity in key controls on transpiration as well as logistical challenges for collecting representative measurements. In these settings, ecosystem models can be used to account for variation in space and time of the dominant controls on transpiration and provide estimates of transpiration patterns and their sensitivity to climate variability and change. The Regional Hydro-Ecological Simulation System (RHESSys) model was used to assess elevational differences in sensitivity of transpiration rates to the spatiotemporal variability of climate variables across the Upper Merced River watershed, Yosemite Valley, California, USA. At the basin scale, predicted annual transpiration was lowest in driest and wettest years, and greatest in moderate precipitation years (R2 = 0.32 and 0.29, based on polynomial regression of maximum snow depth and annual precipitation, respectively). At finer spatial scales, responsiveness of transpiration rates to climate differed along an elevational gradient. Low elevations (1200-1800 m) showed little interannual variation in transpiration due to topographically controlled high soil moistures along the river corridor. Annual conifer stand transpiration at intermediate elevations (1800-2150 m) responded more strongly to precipitation, resulting in a unimodal relationship between transpiration and precipitation where highest transpiration occurred during moderate precipitation levels, regardless of annual air temperatures. Higher elevations (2150-2600 m) maintained this trend, but air temperature sensitivities were greater. At these elevations, snowfall provides enough moisture for growth, and increased temperatures influenced transpiration. Transpiration at the highest elevations (2600-4000 m) showed strong sensitivity to air temperature, little sensitivity to precipitation. Model results suggest elevational differences in vegetation water use and sensitivity to climate were significant and will likely play a key role in controlling responses and vulnerability of Sierra Nevada ecosystems to climate change. Copyright ?? 2008 John Wiley & Sons, Ltd.

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

PubMed

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

2013-09-01

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

Trend Estimation and Regression Analysis in Climatological Time Series: An Application of Structural Time Series Models and the Kalman Filter.

NASA Astrophysics Data System (ADS)

Visser, H.; Molenaar, J.

1995-05-01

The detection of trends in climatological data has become central to the discussion on climate change due to the enhanced greenhouse effect. To prove detection, a method is needed (i) to make inferences on significant rises or declines in trends, (ii) to take into account natural variability in climate series, and (iii) to compare output from GCMs with the trends in observed climate data. To meet these requirements, flexible mathematical tools are needed. A structural time series model is proposed with which a stochastic trend, a deterministic trend, and regression coefficients can be estimated simultaneously. The stochastic trend component is described using the class of ARIMA models. The regression component is assumed to be linear. However, the regression coefficients corresponding with the explanatory variables may be time dependent to validate this assumption. The mathematical technique used to estimate this trend-regression model is the Kaiman filter. The main features of the filter are discussed.Examples of trend estimation are given using annual mean temperatures at a single station in the Netherlands (1706-1990) and annual mean temperatures at Northern Hemisphere land stations (1851-1990). The inclusion of explanatory variables is shown by regressing the latter temperature series on four variables: Southern Oscillation index (SOI), volcanic dust index (VDI), sunspot numbers (SSN), and a simulated temperature signal, induced by increasing greenhouse gases (GHG). In all analyses, the influence of SSN on global temperatures is found to be negligible. The correlations between temperatures and SOI and VDI appear to be negative. For SOI, this correlation is significant, but for VDI it is not, probably because of a lack of volcanic eruptions during the sample period. The relation between temperatures and GHG is positive, which is in agreement with the hypothesis of a warming climate because of increasing levels of greenhouse gases. The prediction performance of the model is rather poor, and possible explanations are discussed.

Quantitative estimates of Mid- to late Holocene Climate Variability in northeastern Siberia inferred from chironomids in lake sediments

NASA Astrophysics Data System (ADS)

Nazarova, Larisa; Diekmann, Bernhard; Pestrjakova, Ludmila; Herzschuh, Ulrike; Subetto, Dmitry

2010-05-01

Yakutia (Russia, northeastern part of Eurasia) represents one of Earths most extreme climatic settings in the world with deep-reaching frozen ground and a semiarid continental climate with highest seasonal temperature contrasts in the northern hemisphere. The amplitude of temperature variations around the year sometimes exceeds 100oC. There are few examples of quantitative palaeoecological studies in Siberia and these data have to be tested by quantitative studies from other sites in this region, inferred from different proxies and using regional calibration datasets and temperature models that are still lacking. Chironomid midges (Insecta, Diptera, Chironomidae) have been widely used to reconstruct past climate variability in many areas of Western Europe and North America. A chironomid-mean July air temperature inference model has been developed, based on a modern calibration set of 200 lakes sampled along a transect from 110° to 159° E and 61° to73° N in northern Russia. The inference model was applied to sediment cores from 2 lakes in the Central Yakutia in order to reconstruct past July air temperatures. The lacustrine records span mid- to late Holocene. The downcore variability in the chironomid assemblages and the composition of organic matter give evidence of climate-driven and interrelated changes in biological productivity, lacustrine trophic states, and lake-level fluctuations. Three phases of the climate development in Central Yakutia can be derived from the geochemical composition of the lake cores and according to the inferred from chironomid assemblages mean July air ToC. Content of organic matters reached maximal values in the period between 7000-4500 yBP. Sedimentation rate is especially high, numerous molluscs shells are found in sediments. All this along with the reconstructed air temperature confirmed that Mid Holocene optimum in Central Yakutia took place in this period with the maximal temperatures up to 4oC above present day ToC. Strong faunistic changes take place after 4500 yBP. Temperature reconstruction has shown that around 4500 ka BP air temperature went down up to 2oC below modern temperature. These observations confirm end of Holocene climate optimum at this time. The lake status record reveals a long-term trend towards lake-level lowering in the course of climate deterioration after 4.2 cal. ka BP and reduced evaporation as well as progressive sediment infill. This long-term trend is overprinted by short-term fluctuations at centennial time scales with high lake levels and decreased biological productivity during cool climate spells with reduced evaporation, as also observed in modern thermokarst lakes of Central Yakutia.

Complex interactions between climate change and toxicants: evidence that temperature variability increases sensitivity to cadmium.

PubMed

Kimberly, David A; Salice, Christopher J

2014-07-01

The Intergovernmental Panel on Climate Change projects that global climate change will have significant impacts on environmental conditions including potential effects on sensitivity of organisms to environmental contaminants. The objective of this study was to test the climate-induced toxicant sensitivity (CITS) hypothesis in which acclimation to altered climate parameters increases toxicant sensitivity. Adult Physa pomilia snails were acclimated to a near optimal 22 °C or a high-normal 28 °C for 28 days. After 28 days, snails from each temperature group were challenged with either low (150 μg/L) or high (300 μg/L) cadmium at each temperature (28 or 22 °C). In contrast to the CITS hypothesis, we found that acclimation temperature did not have a strong influence on cadmium sensitivity except at the high cadmium test concentration where snails acclimated to 28 °C were more cadmium tolerant. However, snails that experienced a switch in temperature for the cadmium challenge, regardless of the switch direction, were the most sensitive to cadmium. Within the snails that were switched between temperatures, snails acclimated at 28 °C and then exposed to high cadmium at 22 °C exhibited significantly greater mortality than those snails acclimated to 22 °C and then exposed to cadmium at 28 °C. Our results point to the importance of temperature variability in increasing toxicant sensitivity but also suggest a potentially complex cost of temperature acclimation. Broadly, the type of temporal stressor exposures we simulated may reduce overall plasticity in responses to stress ultimately rendering populations more vulnerable to adverse effects.

Testing for the Possible Influence of Unknown Climate Forcings upon Global Temperature Increases from 1950-2000

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

Anderson, Bruce T.; Knight, Jeff R.; Ringer, Mark A.

2012-10-15

Global-scale variations in the climate system over the last half of the twentieth century, including long-term increases in global-mean near-surface temperatures, are consistent with concurrent human-induced emissions of radiatively active gases and aerosols. However, such consistency does not preclude the possible influence of other forcing agents, including internal modes of climate variability or unaccounted for aerosol effects. To test whether other unknown forcing agents may have contributed to multidecadal increases in global-mean near-surface temperatures from 1950 to 2000, data pertaining to observed changes in global-scale sea surface temperatures and observed changes in radiatively active atmospheric constituents are incorporated into numericalmore » global climate models. Results indicate that the radiative forcing needed to produce the observed long-term trends in sea surface temperatures—and global-mean near-surface temperatures—is provided predominantly by known changes in greenhouse gases and aerosols. Further, results indicate that less than 10% of the long-term historical increase in global-mean near-surface temperatures over the last half of the twentieth century could have been the result of internal climate variability. In addition, they indicate that less than 25%of the total radiative forcing needed to produce the observed long-term trend in global-mean near-surface temperatures could have been provided by changes in net radiative forcing from unknown sources (either positive or negative). These results, which are derived from simple energy balance requirements, emphasize the important role humans have played in modifying the global climate over the last half of the twentieth century.« less

Detecting climate change oriented and human induced changes in stream temperature across the Southeastern U.S.

NASA Astrophysics Data System (ADS)

Zhang, X.; Voisin, N.; Cheng, Y.; Niemeyer, R. J.; Nijssen, B.; Yearsley, J. R.; Zhou, T.

2017-12-01

In many areas, climate change is expected to alter the flow regime and increase stream temperature, especially during summer low flow periods. During these low flow periods, water management increases flows in order to sustain human activities such as water for irrigation and hydroelectric power generation. Water extraction from rivers during warm season can increase stream temperature while reservoir regulation may cool downstream river temperatures by releasing cool water from deep layers. Thus, it is reasonable to hypothesize that water management changes the sensitivity of the stream temperature regime to climate change when compared to unmanaged resources. The time of emergence of change refers to the point in time when observations, or model simulations, show statistically significant changes from a given baseline period, i.e. above natural variability. Here we aim to address two questions by investigating the time of emergence of changes in stream temperature in the southeastern United States: what is the sensitivity of stream temperature under regulated flow conditions to climate change and what is the contribution of water management in increasing or decreasing stream temperature sensitivity to climate change. We simulate regulated flow by using runoff from the Variable Infiltration Capacity (VIC) macroscale hydrological model as input into a large scale river routing and reservoir model MOSART-WM. The River Basin Model (RBM), a distributed stream temperature model, includes a two-layer thermal stratification module to simulate stream temperature in regulated river systems. We evaluate the timing of emergence of changes in flow and stream temperature based on climate projections from two representative concentration pathways (RCPs; RCP4.5 and RCP8.5) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). We analyze the difference in emergence of change between natural and regulated streamflow. Insights will be provided toward applications for multiple sectors of activities including electrical resources adequacy studies over the southeastern U.S.

Upper-Level Mediterranean Oscillation index and seasonal variability of rainfall and temperature

NASA Astrophysics Data System (ADS)

Redolat, Dario; Monjo, Robert; Lopez-Bustins, Joan A.; Martin-Vide, Javier

2018-02-01

The need for early seasonal forecasts stimulates continuous research in climate teleconnections. The large variability of the Mediterranean climate presents a greater difficulty in predicting climate anomalies. This article reviews teleconnection indices commonly used for the Mediterranean basin and explores possible extensions of one of them, the Mediterranean Oscillation index (MOi). In particular, the anomalies of the geopotential height field at 500 hPa are analyzed using segmentation of the Mediterranean basin in seven spatial windows: three at eastern and four at western. That is, different versions of an Upper-Level Mediterranean Oscillation index (ULMOi) were calculated, and monthly and annual variability of precipitation and temperature were analyzed for 53 observatories from 1951 to 2015. Best versions were selected according to the Pearson correlation, its related p value, and two measures of standardized error. The combination of the Balearic Sea and Libya/Egypt windows was the best for precipitation and temperature, respectively. The ULMOi showed the highest predictive ability in combination with the Atlantic Multidecadal Oscillation index (AMOi) for the annual temperature throughout the Mediterranean basin. The best model built from the indices presented a final mean error between 15 and 25% in annual precipitation for most of the studied area.

Climatic effects on breeding grounds are more important drivers of breeding phenology in migrant birds than carry-over effects from wintering grounds.

PubMed

Ockendon, Nancy; Leech, Dave; Pearce-Higgins, James W

2013-01-01

Long-distance migrants may be particularly vulnerable to climate change on both wintering and breeding grounds. However, the relative importance of climatic variables at different stages of the annual cycle is poorly understood, even in well-studied Palaearctic migrant species. Using a national dataset spanning 46 years, we investigate the impact of wintering ground precipitation and breeding ground temperature on breeding phenology and clutch size of 19 UK migrants. Although both spring temperature and arid zone precipitation were significantly correlated with laying date, the former accounted for 3.5 times more inter-annual variation. Neither climate variable strongly affected clutch size. Thus, although carry-over effects had some impact, they were weaker drivers of reproductive traits than conditions on the breeding grounds.

Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble

NASA Astrophysics Data System (ADS)

Lorenz, Ruth; Argüeso, Daniel; Donat, Markus G.; Pitman, Andrew J.; van den Hurk, Bart; Berg, Alexis; Lawrence, David M.; Chéruy, Frédérique; Ducharne, Agnès.; Hagemann, Stefan; Meier, Arndt; Milly, P. C. D.; Seneviratne, Sonia I.

2016-01-01

We examine how soil moisture variability and trends affect the simulation of temperature and precipitation extremes in six global climate models using the experimental protocol of the Global Land-Atmosphere Coupling Experiment of the Coupled Model Intercomparison Project, Phase 5 (GLACE-CMIP5). This protocol enables separate examinations of the influences of soil moisture variability and trends on the intensity, frequency, and duration of climate extremes by the end of the 21st century under a business-as-usual (Representative Concentration Pathway 8.5) emission scenario. Removing soil moisture variability significantly reduces temperature extremes over most continental surfaces, while wet precipitation extremes are enhanced in the tropics. Projected drying trends in soil moisture lead to increases in intensity, frequency, and duration of temperature extremes by the end of the 21st century. Wet precipitation extremes are decreased in the tropics with soil moisture trends in the simulations, while dry extremes are enhanced in some regions, in particular the Mediterranean and Australia. However, the ensemble results mask considerable differences in the soil moisture trends simulated by the six climate models. We find that the large differences between the models in soil moisture trends, which are related to an unknown combination of differences in atmospheric forcing (precipitation, net radiation), flux partitioning at the land surface, and how soil moisture is parameterized, imply considerable uncertainty in future changes in climate extremes.

Norwegian fjord sediments reveal NAO related winter temperature and precipitation changes of the past 2800 years

NASA Astrophysics Data System (ADS)

Faust, Johan; Fabian, Karl; Giraudeau, Jacques; Knies, Jochen

2016-04-01

The North Atlantic Oscillation (NAO) is the leading mode of atmospheric circulation variability in the North Atlantic region. Associated shifts of storm tracks, precipitation and temperature patterns affect energy supply and demand, fisheries and agricultural, as well as marine and terrestrial ecological dynamics. Long-term NAO reconstructions are crucial to better understand NAO variability in its response to climate forcing factors, and assess predictability and possible shifts associated with ongoing climate change. Fjord deposits have a great potential for providing high-resolution sedimentary records that reflect local terrestrial and marine processes and, therefore, offer unique opportunities for the investigation of sedimentological and geochemical climatically induced processes. A recent study of instrumental time series revealed NAO as main factor for a strong relation between winter temperature, precipitation and river discharge in central Norway over the past 50 years. Here we use the gained knowledge to establish the first high resolution NAO proxy record from marine sediments. By comparing geochemical measurements from a short sediment core with instrumental data we show that marine primary productivity proxies are sensitive to NAO changes. Conditioned on a stationary relation between our climate proxy and the NAO we establish the first high resolution NAO proxy record (NAO-TFJ) from marine sediments covering the past 2,800 years. The NAO-TFJ shows distinct co-variability with climate changes over Greenland, solar activity and Northern Hemisphere glacier dynamics as well as climatically associated paleo-demographic trends.

Relating annual increments of the endangered Blanding's turtle plastron growth to climate

PubMed Central

Richard, Monik G; Laroque, Colin P; Herman, Thomas B

2014-01-01

This research is the first published study to report a relationship between climate variables and plastron growth increments of turtles, in this case the endangered Nova Scotia Blanding's turtle (Emydoidea blandingii). We used techniques and software common to the discipline of dendrochronology to successfully cross-date our growth increment data series, to detrend and average our series of 80 immature Blanding's turtles into one common chronology, and to seek correlations between the chronology and environmental temperature and precipitation variables. Our cross-dated chronology had a series intercorrelation of 0.441 (above 99% confidence interval), an average mean sensitivity of 0.293, and an average unfiltered autocorrelation of 0.377. Our master chronology represented increments from 1975 to 2007 (33 years), with index values ranging from a low of 0.688 in 2006 to a high of 1.303 in 1977. Univariate climate response function analysis on mean monthly air temperature and precipitation values revealed a positive correlation with the previous year's May temperature and current year's August temperature; a negative correlation with the previous year's October temperature; and no significant correlation with precipitation. These techniques for determining growth increment response to environmental variables should be applicable to other turtle species and merit further exploration. PMID:24963390

Relating annual increments of the endangered Blanding's turtle plastron growth to climate.

PubMed

Richard, Monik G; Laroque, Colin P; Herman, Thomas B

2014-05-01

This research is the first published study to report a relationship between climate variables and plastron growth increments of turtles, in this case the endangered Nova Scotia Blanding's turtle (Emydoidea blandingii). We used techniques and software common to the discipline of dendrochronology to successfully cross-date our growth increment data series, to detrend and average our series of 80 immature Blanding's turtles into one common chronology, and to seek correlations between the chronology and environmental temperature and precipitation variables. Our cross-dated chronology had a series intercorrelation of 0.441 (above 99% confidence interval), an average mean sensitivity of 0.293, and an average unfiltered autocorrelation of 0.377. Our master chronology represented increments from 1975 to 2007 (33 years), with index values ranging from a low of 0.688 in 2006 to a high of 1.303 in 1977. Univariate climate response function analysis on mean monthly air temperature and precipitation values revealed a positive correlation with the previous year's May temperature and current year's August temperature; a negative correlation with the previous year's October temperature; and no significant correlation with precipitation. These techniques for determining growth increment response to environmental variables should be applicable to other turtle species and merit further exploration.

Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation

USGS Publications Warehouse

Alvarez, Otto; Guo, Qinghua; Klinger, Robert C.; Li, Wenkai; Doherty, Paul

2013-01-01

Climate models may be limited in their inferential use if they cannot be locally validated or do not account for spatial uncertainty. Much of the focus has gone into determining which interpolation method is best suited for creating gridded climate surfaces, which often a covariate such as elevation (Digital Elevation Model, DEM) is used to improve the interpolation accuracy. One key area where little research has addressed is in determining which covariate best improves the accuracy in the interpolation. In this study, a comprehensive evaluation was carried out in determining which covariates were most suitable for interpolating climatic variables (e.g. precipitation, mean temperature, minimum temperature, and maximum temperature). We compiled data for each climate variable from 1950 to 1999 from approximately 500 weather stations across the Western United States (32° to 49° latitude and −124.7° to −112.9° longitude). In addition, we examined the uncertainty of the interpolated climate surface. Specifically, Thin Plate Spline (TPS) was used as the interpolation method since it is one of the most popular interpolation techniques to generate climate surfaces. We considered several covariates, including DEM, slope, distance to coast (Euclidean distance), aspect, solar potential, radar, and two Normalized Difference Vegetation Index (NDVI) products derived from Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS). A tenfold cross-validation was applied to determine the uncertainty of the interpolation based on each covariate. In general, the leading covariate for precipitation was radar, while DEM was the leading covariate for maximum, mean, and minimum temperatures. A comparison to other products such as PRISM and WorldClim showed strong agreement across large geographic areas but climate surfaces generated in this study (ClimSurf) had greater variability at high elevation regions, such as in the Sierra Nevada Mountains.

Characteristics of the East Asian Winter Climate Associated with the Westerly Jet Stream and ENSO

NASA Technical Reports Server (NTRS)

Yang, Song; Lau, K.-M.; Kim, K.-M.; Einaudi, Franco (Technical Monitor)

2000-01-01

In this study, the influences of the East Asian jet stream (EAJS) and El Nino/Southern Oscillation (ENSO) on the interannual variability of the East Asian winter climate are examined with a focus on the relative climate impacts of the two phenomena. Although the variations of the East Asian winter monsoon and the temperature and precipitation of China, Japan, and Korea are emphasized, the associated changes in the broad-scale atmospheric circulation patterns over Asia and the Pacific and in the extratropical North Pacific sea surface temperature (SST) are also investigated. It is demonstrated that there is no apparent relationship between ENSO and the interannual variability of EAJS core. The EAJS and ENSO are associated with distinctly different patterns of atmospheric circulation and SST in the Asian-Pacific regions. While ENSO causes major climate signals in the Tropics and over the North Pacific east of the dateline, the EAJS produces significant changes in the atmospheric circulation over East Asia and western Pacific. In particular, the EAJS explains larger variance of the interannual signals of the East Asian trough, the Asian continental high, the Aleutian low, and the East Asian winter monsoon. When the EAJS is strong, all these atmospheric systems intensify significantly. The response of surface temperature and precipitation to EAJS variability and ENSO is more complex. In general, the East Asian winter climate is cold (warm) and dry (wet) when the EAJS is strong (weak) and it is warm during El Nino years. However, different climate signals are found during different La Nina years. In terms of linear correlation, both the temperature and precipitation of northern China, Korea, and central Japan are more significantly associated with the EAJS than with ENSO.

Interactions between chemical and climate stressors: A role for mechanistic toxicology in assessing climate change risks

EPA Science Inventory

Incorporation of global climate change (GCC) effects into regulatory assessments of chemical risk and injury requires an integrated examination of both chemical and non-chemical stressors. Environmental variables altered by GCC, such as temperature, precipitation, salinity and pH...

On the brink of change: plant responses to climate on the Colorado Plateau

USGS Publications Warehouse

Munson, Seth M.; Belnap, Jayne; Schelz, Charles D.; Moran, Mary; Carolin, Tara W.

2011-01-01

The intensification of aridity due to anthropogenic climate change in the southwestern U.S. is likely to have a large impact on the growth and survival of plant species that may already be vulnerable to water stress. To make accurate predictions of plant responses to climate change, it is essential to determine the long-term dynamics of plant species associated with past climate conditions. Here we show how the plant species and functional types across a wide range of environmental conditions in Colorado Plateau national parks have changed with climate variability over the last twenty years. During this time, regional mean annual temperature increased by 0.18°C per year from 1989–1995, 0.06°C per year from 1995–2003, declined by 0.14°C from 2003–2008, and there was high interannual variability in precipitation. Non-metric multidimensional scaling of plant species at long-term monitoring sites indicated five distinct plant communities. In many of the communities, canopy cover of perennial plants was sensitive to mean annual temperature occurring in the previous year, whereas canopy cover of annual plants responded to cool season precipitation. In the perennial grasslands, there was an overall decline of C3 perennial grasses, no change of C4 perennial grasses, and an increase of shrubs with increasing temperature. In the shrublands, shrubs generally showed no change or slightly increased with increasing temperature. However, certain shrub species declined where soil and physical characteristics of a site limited water availability. In the higher elevation woodlands, Juniperus osteosperma and shrub canopy cover increased with increasing temperature, while Pinus edulis at the highest elevation sites was unresponsive to interannual temperature variability. These results from well-protected national parks highlight the importance of temperature to plant responses in a water-limited region and suggest that projected increases in aridity are likely to promote grass loss and shrub expansion on the Colorado Plateau.

Separate and combined effects of temperature and precipitation change on maize yields in sub-Saharan Africa for mid- to late-21st century

NASA Astrophysics Data System (ADS)

Waha, K.; Müller, C.; Rolinski, S.

2013-07-01

Maize (Zea mays L.) is one of the most important food crops and very common in all parts of sub-Saharan Africa. In 2010 53 million tons of maize were produced in sub-Saharan Africa on about one third of the total harvested cropland area (~ 33 million ha). Our aim is to identify the limiting agroclimatic variable for maize growth and development in sub-Saharan Africa by analyzing the separated and combined effects of temperature and precipitation. Under changing climate, both climate variables are projected to change severely, and their impacts on crop yields are frequently assessed using process-based crop models. However it is often unclear which agroclimatic variable will have the strongest influence on crop growth and development under climate change and previous studies disagree over this question.

Response of wheat yield in Spain to large-scale patterns

NASA Astrophysics Data System (ADS)

Hernandez-Barrera, Sara; Rodriguez-Puebla, Concepcion

2016-04-01

Crops are vulnerable to extreme climate conditions as drought, heat stress and frost risk. In previous study we have quantified the influence of these climate conditions for winter wheat in Spain (Hernandez-Barrera et al. 2015). The climate extremes respond to large-scale atmospheric and oceanic patterns. Therefore, a question emerges in our investigation: How large-scale patterns affect wheat yield? Obtaining and understanding these relationships require different approaches. In this study, we first obtained the leading mode of observed wheat yield variability to characterize the common variability over different provinces in Spain. Then, the wheat variability is related to different modes of mean sea level pressure, jet stream and sea surface temperature by using Partial Least-Squares, which captures the relevant climate drivers accounting for variations in wheat yield from sowing to harvesting. We used the ERA-Interim reanalysis data and the Extended Reconstructed Sea Surface Temperature (SST) (ERSST v3b). The derived model provides insight about the teleconnections between wheat yield and atmospheric and oceanic circulations, which is considered to project the wheat yield trend under global warming using outputs of twelve climate models corresponding to the Coupled Models Intercomparison Project phase 5 (CMIP5). Hernandez-Barrera S., C. Rodríguez-Puebla and A.J. Challinor. Effects of diurnal temperature range and drought on wheat yield in Spain. Theoretical and Applied Climatology (submitted)

Role of subsurface ocean in decadal climate predictability over the South Atlantic.

PubMed

Morioka, Yushi; Doi, Takeshi; Storto, Andrea; Masina, Simona; Behera, Swadhin K

2018-06-04

Decadal climate predictability in the South Atlantic is explored by performing reforecast experiments using a coupled general circulation model with two initialization schemes; one is assimilated with observed sea surface temperature (SST) only, and the other is additionally assimilated with observed subsurface ocean temperature and salinity. The South Atlantic is known to undergo decadal variability exhibiting a meridional dipole of SST anomalies through variations in the subtropical high and ocean heat transport. Decadal reforecast experiments in which only the model SST is initialized with the observation do not predict well the observed decadal SST variability in the South Atlantic, while the other experiments in which the model SST and subsurface ocean are initialized with the observation skillfully predict the observed decadal SST variability, particularly in the Southeast Atlantic. In-depth analysis of upper-ocean heat content reveals that a significant improvement of zonal heat transport in the Southeast Atlantic leads to skillful prediction of decadal SST variability there. These results demonstrate potential roles of subsurface ocean assimilation in the skillful prediction of decadal climate variability over the South Atlantic.

Reservoirs performances under climate variability: a case study

NASA Astrophysics Data System (ADS)

Longobardi, A.; Mautone, M.; de Luca, C.

2014-09-01

A case study, the Piano della Rocca dam (southern Italy) is discussed here in order to quantify the system performances under climate variability conditions. Different climate scenarios have been stochastically generated according to the tendencies in precipitation and air temperature observed during recent decades for the studied area. Climate variables have then been filtered through an ARMA model to generate, at the monthly scale, time series of reservoir inflow volumes. Controlled release has been computed considering the reservoir is operated following the standard linear operating policy (SLOP) and reservoir performances have been assessed through the calculation of reliability, resilience and vulnerability indices (Hashimoto et al. 1982), comparing current and future scenarios of climate variability. The proposed approach can be suggested as a valuable tool to mitigate the effects of moderate to severe and persistent droughts periods, through the allocation of new water resources or the planning of appropriate operational rules.

Local oceanographic variability influences the performance of juvenile abalone under climate change.

PubMed

Boch, C A; Micheli, F; AlNajjar, M; Monismith, S G; Beers, J M; Bonilla, J C; Espinoza, A M; Vazquez-Vera, L; Woodson, C B

2018-04-03

Climate change is causing warming, deoxygenation, and acidification of the global ocean. However, manifestation of climate change may vary at local scales due to oceanographic conditions. Variation in stressors, such as high temperature and low oxygen, at local scales may lead to variable biological responses and spatial refuges from climate impacts. We conducted outplant experiments at two locations separated by ~2.5 km and two sites at each location separated by ~200 m in the nearshore of Isla Natividad, Mexico to assess how local ocean conditions (warming and hypoxia) may affect juvenile abalone performance. Here, we show that abalone growth and mortality mapped to variability in stress exposure across sites and locations. These insights indicate that management decisions aimed at maintaining and recovering valuable marine species in the face of climate change need to be informed by local variability in environmental conditions.

Lateglacial climate reconstruction on the Bolivian Altiplano inferred from paleoglaciers and paleolakes

NASA Astrophysics Data System (ADS)

Martin, Léo; Blard, Pierre-Henri; Lavé, Jérôme; Prémaillon, Mélody; Jomelli, Vincent; Brunstein, Daniel; Lupker, Maarten; Charreau, Julien; Mariotti, Véronique; Condom, Thomas; Bourles, Didier

2016-04-01

Recent insights shed light on the global mechanisms involved in the abrupt oscillations of the Earth climate for the Late Glacial Maximum (LGM) to Holocene period (Zhang et al., 2014; Banderas et al., 2015). Yet the concomitant patterns of regional climate reorganization on continental areas are for now poorly documented. Particularly, few attempts have been made to propose temporal reconstructions of the regional climate variables in the High Tropical Andes, a region under the influence of multiple global climate forcings (Jomelli et al., 2014). We present new glacial chronologies from four sites of the Bolivian Altiplano: the Wara-Wara valley (17.3°S - 66.1°W), the Zongo valley (16.3°S - 68.1°W), the Cerro Tunupa (19.8°S - 67.6°W) and the Nevado Sajama (18.1°S 68.9°W). These chronologies are based on Cosmic Ray Exposure dating (CRE) from an exceptional suite of recessive moraines. These new data permitted to refine existing chronologies of Smith et al., 2005; Zech et al., 2010 and Blard et al., 2009. In both sites, glaciers recorded stillstand episodes synchronous with cold events such as the Henrich 1 event, the Younger Dryas and the Antarctic Cold Reversal. Since the nearby Altiplano basin registered lake level variations over the same period, we were able to apply a joint modelling of glaciers Equilibrium Line Altitude (ELA) and lake budget. This method permits to derive a temporal evolution of temperature and precipitation for the four sites. These new reconstructions show for all sites that glaciers of the Tropical Andes were influenced by the major climatic events of the Northern and Southern Hemispheres. Furthermore, the temperature variability observed at high latitudes results in these tropical latitudes in major precipitation variability whereas the lateglacial temperature patterns remain globally monotonic. This conversion of global temperature variability into regional precipitation variability support the idea that North Hemisphere cold events are coeval with an important southward deflexion of the Intertropical Convergence Zone (ITCZ) due to the inter-hemispheric temperature gradient (Schneider et al., 2014). Such a southward shift would lead to an increased moist supply of the subequatorial Amazonian basin (Montade et al., 2015) and thus an increased easterly driven moist transport over the Altiplano.

The 1430s: a cold period of extraordinary internal climate variability during the early Spörer Minimum with social and economic impacts in north-western and central Europe

NASA Astrophysics Data System (ADS)

Camenisch, Chantal; Keller, Kathrin M.; Salvisberg, Melanie; Amann, Benjamin; Bauch, Martin; Blumer, Sandro; Brázdil, Rudolf; Brönnimann, Stefan; Büntgen, Ulf; Campbell, Bruce M. S.; Fernández-Donado, Laura; Fleitmann, Dominik; Glaser, Rüdiger; González-Rouco, Fidel; Grosjean, Martin; Hoffmann, Richard C.; Huhtamaa, Heli; Joos, Fortunat; Kiss, Andrea; Kotyza, Oldřich; Lehner, Flavio; Luterbacher, Jürg; Maughan, Nicolas; Neukom, Raphael; Novy, Theresa; Pribyl, Kathleen; Raible, Christoph C.; Riemann, Dirk; Schuh, Maximilian; Slavin, Philip; Werner, Johannes P.; Wetter, Oliver

2016-12-01

Changes in climate affected human societies throughout the last millennium. While European cold periods in the 17th and 18th century have been assessed in detail, earlier cold periods received much less attention due to sparse information available. New evidence from proxy archives, historical documentary sources and climate model simulations permit us to provide an interdisciplinary, systematic assessment of an exceptionally cold period in the 15th century. Our assessment includes the role of internal, unforced climate variability and external forcing in shaping extreme climatic conditions and the impacts on and responses of the medieval society in north-western and central Europe.Climate reconstructions from a multitude of natural and anthropogenic archives indicate that the 1430s were the coldest decade in north-western and central Europe in the 15th century. This decade is characterised by cold winters and average to warm summers resulting in a strong seasonal cycle in temperature. Results from comprehensive climate models indicate consistently that these conditions occurred by chance due to the partly chaotic internal variability within the climate system. External forcing like volcanic eruptions tends to reduce simulated temperature seasonality and cannot explain the reconstructions. The strong seasonal cycle in temperature reduced food production and led to increasing food prices, a subsistence crisis and a famine in parts of Europe. Societies were not prepared to cope with failing markets and interrupted trade routes. In response to the crisis, authorities implemented numerous measures of supply policy and adaptation such as the installation of grain storage capacities to be prepared for future food production shortfalls.

Climate forcings and feedbacks

NASA Technical Reports Server (NTRS)

Hansen, James

1993-01-01

Global temperature has increased significantly during the past century. Understanding the causes of observed global temperature change is impossible in the absence of adequate monitoring of changes in global climate forcings and radiative feedbacks. Climate forcings are changes imposed on the planet's energy balance, such as change of incoming sunlight or a human-induced change of surface properties due to deforestation. Radiative feedbacks are radiative changes induced by climate change, such as alteration of cloud properties or the extent of sea ice. Monitoring of global climate forcings and feedbacks, if sufficiently precise and long-term, can provide a very strong constraint on interpretation of observed temperature change. Such monitoring is essential to eliminate uncertainties about the relative importance of various climate change mechanisms including tropospheric sulfate aerosols from burning of coal and oil smoke from slash and burn agriculture, changes of solar irradiance changes of several greenhouse gases, and many other mechanisms. The considerable variability of observed temperature, together with evidence that a substantial portion of this variability is unforced indicates that observations of climate forcings and feedbacks must be continued for decades. Since the climate system responds to the time integral of the forcing, a further requirement is that the observations be carried out continuously. However, precise observations of forcings and feedbacks will also be able to provide valuable conclusions on shorter time scales. For example, knowledge of the climate forcing by increasing CFC's relative to the forcing by changing ozone is important to policymakers, as is information on the forcing by CO2 relative to the forcing by sulfate aerosols. It will also be possible to obtain valuable tests of climate models on short time scales, if there is precise monitoring of all forcings and feedbacks during and after events such as a large volcanic eruption or an El Nino.

The mortality burden of hourly temperature variability in five capital cities, Australia: Time-series and meta-regression analysis.

PubMed

Cheng, Jian; Xu, Zhiwei; Bambrick, Hilary; Su, Hong; Tong, Shilu; Hu, Wenbiao

2017-12-01

Unstable weather, such as intra- and inter-day temperature variability, can impair the health and shorten the survival time of population around the world. Climate change will cause Earth's surface temperature rise, but has unclear effects on temperature variability, making it urgent to understand the characteristics of the burden of temperature variability on mortality, regionally and nationally. This paper aims to quantify the mortality risk of exposure to short-term temperature variability, estimate the resulting death toll and explore how the strength of temperature variability effects will vary as a function of city-level characteristics. Ten-year (2000-2009) time-series data on temperature and mortality were collected for five largest Australia's cities (Sydney, Melbourne, Brisbane, Perth and Adelaide), collectively registering 708,751 deaths in different climates. Short-term temperature variability was captured and represented as the hourly temperature standard deviation within two days. Three-stage analyses were used to assess the burden of temperature variability on mortality. First, we modelled temperature variability-mortality relation and estimated the relative risk of death for each city, using a time-series quasi-Poisson regression model. Second, we used meta-analysis to pool the city-specific estimates, and meta-regression to explore if some city-level factors will modify the population vulnerability to temperature variability. Finally, we calculated the city-specific deaths attributable to temperature variability, and applied such estimates to the whole of Australia as a reflection of the nation-wide death burden associated with temperature variability. We found evidence of significant associations between temperature variability and mortality in all cities assessed. Deaths associated with each 1°C rise in temperature variability elevated by 0.28% (95% confidence interval (CI): 0.05%, 0.52%) in Melbourne to 1.00% (95%CI: 0.52%, 1.48%) in Brisbane, with a pooled estimate of 0.51% (95%CI: 0.33%, 0.69%) for Australia. Subtropical and temperate regions showed no apparent difference in temperature variability impacts. Meta-regression analyses indicated that the mortality risk could be influenced by city-specific factors: latitude, mean temperature, population density and the prevalence of several chronic diseases. Taking account of contributions from the entire time-series, temperature variability was estimated to account for 0.99% to 3.24% of deaths across cities, with a nation-wide attributable fraction of 1.67% (9.59 deaths per 100, 000 population per year). Hourly temperature variability may be an important risk factor of weather-related deaths and led to a sizeable mortality burden. This study underscores the need for developing specific and effective interventions in Australia to lessen the health consequences of temperature variability. Copyright © 2017. Published by Elsevier Ltd.

Effects of climate change on Forest Service strategic goals

Treesearch

Forest Service U.S. Department of Agriculture

2010-01-01

Climate change affects forests and grasslands in many ways. Changes in temperature and precipitation affect plant productivity as well as some species' habitat. Changes in key climate variables affect the length of the fire season and the seasonality of National Forest hydrological regimes. Also, invasive species tend to adapt to climate change more easily and...

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

Treesearch

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

2008-01-01

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

Potential breeding distributions of U.S. birds predicted with both short-term variability and long-term average climate data

Treesearch

Brooke L. Bateman; Anna M. Pidgeon; Volker C. Radeloff; Curtis H. Flather; Jeremy VanDerWal; H. Resit Akcakaya; Wayne E. Thogmartin; Thomas P. Albright; Stephen J. Vavrus; Patricia J. Heglund

2016-01-01

Climate conditions, such as temperature or precipitation, averaged over several decades strongly affect species distributions, as evidenced by experimental results and a plethora of models demonstrating statistical relations between species occurrences and long-term climate averages. However, long-term averages can conceal climate changes that have occurred in...

Effects of climate on growth traits of river red gum are determined by respiration parameters

Treesearch

Richard S. Criddle; Thimmappa S. Anekonda; Sharon Tong; John N. Church; F. Thomas Ledig; Lee D. Hansen

2000-01-01

Temperature is the major uncontrollable climate variable in plantation forestry. Matching plants to climate is essential for optimizing growth. Matching is usually done with field trials because of the lack of a predictive relation between laboratory measurements of physiological responses and climatic factors affecting growth. This paper evaluates the potential of...

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

Boulton, Chris A; Lenton, Timothy M

2015-09-15

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

Reassessing regime shifts in the North Pacific: incremental climate change and commercial fishing are necessary for explaining decadal-scale biological variability.

PubMed

Litzow, Michael A; Mueter, Franz J; Hobday, Alistair J

2014-01-01

In areas of the North Pacific that are largely free of overfishing, climate regime shifts - abrupt changes in modes of low-frequency climate variability - are seen as the dominant drivers of decadal-scale ecological variability. We assessed the ability of leading modes of climate variability [Pacific Decadal Oscillation (PDO), North Pacific Gyre Oscillation (NPGO), Arctic Oscillation (AO), Pacific-North American Pattern (PNA), North Pacific Index (NPI), El Niño-Southern Oscillation (ENSO)] to explain decadal-scale (1965-2008) patterns of climatic and biological variability across two North Pacific ecosystems (Gulf of Alaska and Bering Sea). Our response variables were the first principle component (PC1) of four regional climate parameters [sea surface temperature (SST), sea level pressure (SLP), freshwater input, ice cover], and PCs 1-2 of 36 biological time series [production or abundance for populations of salmon (Oncorhynchus spp.), groundfish, herring (Clupea pallasii), shrimp, and jellyfish]. We found that the climate modes alone could not explain ecological variability in the study region. Both linear models (for climate PC1) and generalized additive models (for biology PC1-2) invoking only the climate modes produced residuals with significant temporal trends, indicating that the models failed to capture coherent patterns of ecological variability. However, when the residual climate trend and a time series of commercial fishery catches were used as additional candidate variables, resulting models of biology PC1-2 satisfied assumptions of independent residuals and out-performed models constructed from the climate modes alone in terms of predictive power. As measured by effect size and Akaike weights, the residual climate trend was the most important variable for explaining biology PC1 variability, and commercial catch the most important variable for biology PC2. Patterns of climate sensitivity and exploitation history for taxa strongly associated with biology PC1-2 suggest plausible mechanistic explanations for these modeling results. Our findings suggest that, even in the absence of overfishing and in areas strongly influenced by internal climate variability, climate regime shift effects can only be understood in the context of other ecosystem perturbations. © 2013 John Wiley & Sons Ltd.

Evaluating the robustness of conceptual rainfall-runoff models under climate variability in northern Tunisia

NASA Astrophysics Data System (ADS)

Dakhlaoui, H.; Ruelland, D.; Tramblay, Y.; Bargaoui, Z.

2017-07-01

To evaluate the impact of climate change on water resources at the catchment scale, not only future projections of climate are necessary but also robust rainfall-runoff models that must be fairly reliable under changing climate conditions. The aim of this study was thus to assess the robustness of three conceptual rainfall-runoff models (GR4j, HBV and IHACRES) on five basins in northern Tunisia under long-term climate variability, in the light of available future climate scenarios for this region. The robustness of the models was evaluated using a differential split sample test based on a climate classification of the observation period that simultaneously accounted for precipitation and temperature conditions. The study catchments include the main hydrographical basins in northern Tunisia, which produce most of the surface water resources in the country. A 30-year period (1970-2000) was used to capture a wide range of hydro-climatic conditions. The calibration was based on the Kling-Gupta Efficiency (KGE) criterion, while model transferability was evaluated based on the Nash-Sutcliffe efficiency criterion and volume error. The three hydrological models were shown to behave similarly under climate variability. The models simulated the runoff pattern better when transferred to wetter and colder conditions than to drier and warmer ones. It was shown that their robustness became unacceptable when climate conditions involved a decrease of more than 25% in annual precipitation and an increase of more than +1.75 °C in annual mean temperatures. The reduction in model robustness may be partly due to the climate dependence of some parameters. When compared to precipitation and temperature projections in the region, the limits of transferability obtained in this study are generally respected for short and middle term. For long term projections under the most pessimistic emission gas scenarios, the limits of transferability are generally not respected, which may hamper the use of conceptual models for hydrological projections in northern Tunisia.

Separating heat stress from moisture stress: analyzing yield response to high temperature in irrigated maize

NASA Astrophysics Data System (ADS)

Carter, Elizabeth K.; Melkonian, Jeff; Riha, Susan J.; Shaw, Stephen B.

2016-09-01

Several recent studies have indicated that high air temperatures are limiting maize (Zea mays L.) yields in the US Corn Belt and project significant yield losses with expected increases in growing season temperatures. Further work has suggested that high air temperatures are indicative of high evaporative demand, and that decreases in maize yields which correlate to high temperatures and vapor pressure deficits (VPD) likely reflect underlying soil moisture limitations. It remains unclear whether direct high temperature impacts on yields, independent of moisture stress, can be observed under current temperature regimes. Given that projected high temperature and moisture may not co-vary the same way as they have historically, quantitative analyzes of direct temperature impacts are critical for accurate yield projections and targeted mitigation strategies under shifting temperature regimes. To evaluate yield response to above optimum temperatures independent of soil moisture stress, we analyzed climate impacts on irrigated maize yields obtained from the National Corn Growers Association (NCGA) corn yield contests for Nebraska, Kansas and Missouri. In irrigated maize, we found no evidence of a direct negative impact on yield by daytime air temperature, calculated canopy temperature, or VPD when analyzed seasonally. Solar radiation was the primary yield-limiting climate variable. Our analyses suggested that elevated night temperature impacted yield by increasing rates of phenological development. High temperatures during grain-fill significantly interacted with yields, but this effect was often beneficial and included evidence of acquired thermo-tolerance. Furthermore, genetics and management—information uniquely available in the NCGA contest data—explained more yield variability than climate, and significantly modified crop response to climate. Thermo-acclimation, improved genetics and changes to management practices have the potential to partially or completely offset temperature-related yield losses in irrigated maize.

Spatial-temporal analysis of climate variations in mid-17th through 19th centuries in East China and the possible relationships with Monsoon climate

NASA Astrophysics Data System (ADS)

Lin, K. H. E.; Wang, P. K.; Liao, Y. C.; Lee, S. Y.; Tan, P.

2016-12-01

IPCC AR5 has revealed more frequent extreme climate events and higher climate variability in the near future. Regardless of all the improvements, East Asia monsoon climate is still less understood and/or poorly projected due partly to insufficient records. Most areas of the Asian region lack sufficient observational records to draw conclusions about trends in annual precipitation over the past century (i.e. WGIAR5 Chapter 2). Precipitation trends, including extremes, are characterized by strong variability, with both increasing and decreasing observed in different parts and seasons of Asia. Understanding the variations of the monsoon climate in historical time may bring significant insights to reveal its spatial and temporal patterns embedded in the atmospheric dynamics at different decadal or centennial scales. This study presents some preliminary research results of high resolution climate reconstruction, in both time and space coverage, in east China, by using RCEC historical climate dataset that is developed under interdisciplinary collaboration led by Research Center for Environmental Changes at Academia Sinica, Taiwan. The present research results are derived from chronological meteorological records in the RCEC dataset in Qing dynasty labeling mid-17th to 19th centuries. In total, the dataset comprises more than 1,300 cities/counties in China that has had more than sixty thousands meteorological records in the period. The analysis comprises three parts. Firstly, the frequency of extreme temperature, precipitation, drought, and flood in every recorded cities/counties were computed to depicting climate variabilities in northeast, central-east and southeast China. Secondly, the multivariate regression model was conducted to estimate the coefficients among the climatic index (temperature, precipitation, and drought). It is found that the temperature and wet-dry characteristics have great seasonal and yearly variations; northeast China compared with central-east or southeast tends to have higher variability. Thirdly, those data was used to conduct empirical orthogonal function (EOF) analysis to decompose possible mechanisms that might have cause changes in East Asia monsoon regime during the time period. The reconstructed data were also compared against paleoclimate simulation.

Future warming patterns linked to today’s climate variability

DOE PAGES

Dai, Aiguo

2016-01-11

The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models’ ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21 st century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today’s climate, with areas of larger variations duringmore » 1950–1979 having more GHG-induced warming in the 21 st century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950–2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21 st century in models and in the real world. Furthermore, they support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.« less

Topographical effects of climate dataset and their impacts on the estimation of regional net primary productivity

NASA Astrophysics Data System (ADS)

Sun, L. Qing; Feng, Feng X.

2014-11-01

In this study, we first built and compared two different climate datasets for Wuling mountainous area in 2010, one of which considered topographical effects during the ANUSPLIN interpolation was referred as terrain-based climate dataset, while the other one did not was called ordinary climate dataset. Then, we quantified the topographical effects of climatic inputs on NPP estimation by inputting two different climate datasets to the same ecosystem model, the Boreal Ecosystem Productivity Simulator (BEPS), to evaluate the importance of considering relief when estimating NPP. Finally, we found the primary contributing variables to the topographical effects through a series of experiments given an overall accuracy of the model output for NPP. The results showed that: (1) The terrain-based climate dataset presented more reliable topographic information and had closer agreements with the station dataset than the ordinary climate dataset at successive time series of 365 days in terms of the daily mean values. (2) On average, ordinary climate dataset underestimated NPP by 12.5% compared with terrain-based climate dataset over the whole study area. (3) The primary climate variables contributing to the topographical effects of climatic inputs for Wuling mountainous area were temperatures, which suggest that it is necessary to correct temperature differences for estimating NPP accurately in such a complex terrain.

Future warming patterns linked to today’s climate variability

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

Dai, Aiguo

The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models’ ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21 st century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today’s climate, with areas of larger variations duringmore » 1950–1979 having more GHG-induced warming in the 21 st century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950–2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21 st century in models and in the real world. Furthermore, they support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.« less

Detrending phenological time series improves climate-phenology analyses and reveals evidence of plasticity.

PubMed

Iler, Amy M; Inouye, David W; Schmidt, Niels M; Høye, Toke T

2017-03-01

Time series have played a critical role in documenting how phenology responds to climate change. However, regressing phenological responses against climatic predictors involves the risk of finding potentially spurious climate-phenology relationships simply because both variables also change across years. Detrending by year is a way to address this issue. Additionally, detrending isolates interannual variation in phenology and climate, so that detrended climate-phenology relationships can represent statistical evidence of phenotypic plasticity. Using two flowering phenology time series from Colorado, USA and Greenland, we detrend flowering date and two climate predictors known to be important in these ecosystems: temperature and snowmelt date. In Colorado, all climate-phenology relationships persist after detrending. In Greenland, 75% of the temperature-phenology relationships disappear after detrending (three of four species). At both sites, the relationships that persist after detrending suggest that plasticity is a major component of sensitivity of flowering phenology to climate. Finally, simulations that created different strengths of correlations among year, climate, and phenology provide broader support for our two empirical case studies. This study highlights the utility of detrending to determine whether phenology is related to a climate variable in observational data sets. Applying this as a best practice will increase our understanding of phenological responses to climatic variation and change. © 2016 by the Ecological Society of America.

Future Warming Patterns Linked to Today's Climate Variability.

PubMed

Dai, Aiguo

2016-01-11

The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models' ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21(st) century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today's climate, with areas of larger variations during 1950-1979 having more GHG-induced warming in the 21(st) century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950-2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21(st) century in models and in the real world. They support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.

Influence of long-range atmospheric transport pathways and climate teleconnection patterns on the variability of surface 210Pb and 7Be concentrations in southwestern Europe.

PubMed

Grossi, C; Ballester, J; Serrano, I; Galmarini, S; Camacho, A; Curcoll, R; Morguí, J A; Rodò, X; Duch, M A

2016-12-01

The variability of the atmospheric concentration of the 7 Be and 210 Pb radionuclides is strongly linked to the origin of air masses, the strength of their sources and the processes of wet and dry deposition. It has been shown how these processes and their variability are strongly affected by climate change. Thus, a deeper knowledge of the relationship between the atmospheric radionuclides variability measured close to the ground and these atmospheric processes could help in the analysis of climate scenarios. In the present study, we analyze the atmospheric variability of a 14-year time series of 7 Be and 210 Pb in a Mediterranean coastal city using a synergy of different indicators and tools such as: the local meteorological conditions, global and regional climate indexes and a lagrangian atmospheric transport model. We particularly focus on the relationships between the main pathways of air masses and sun spots occurrence, the variability of the local relative humidity and temperature conditions, and the main modes of regional climate variability, such as the North Atlantic Oscillation (NAO) and the Western Mediterranean Oscillation (WeMO). The variability of the observed atmospheric concentrations of both 7 Be and 210 Pb radionuclides was found to be mainly positively associated to the local climate conditions of temperature and to the pathways of air masses arriving at the station. Measured radionuclide concentrations significantly increase when air masses travel at low tropospheric levels from central Europe and the western part of the Iberian Peninsula, while low concentrations are associated with westerly air masses. We found a significant negative correlation between the WeMO index and the atmospheric variability of both radionuclides and no significant association was observed for the NAO index. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effects of climate on numbers of northern prairie wetlands

USGS Publications Warehouse

Larson, Diane L.

1995-01-01

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

Synoptic circulation and temperature pattern during severe wildland fires

Treesearch

Warren E. Heilman

1996-01-01

Large-scale changes in the atmosphere associated with a globally changed climate and changes in climatic variability may have important regional impacts on the frequency and severity of wildland fires in the future.

On nonstationarity and antipersistency in global temperature series

NASA Astrophysics Data System (ADS)

KäRner, O.

2002-10-01

Statistical analysis is carried out for satellite-based global daily tropospheric and stratospheric temperature anomaly and solar irradiance data sets. Behavior of the series appears to be nonstationary with stationary daily increments. Estimating long-range dependence between the increments reveals a remarkable difference between the two temperature series. Global average tropospheric temperature anomaly behaves similarly to the solar irradiance anomaly. Their daily increments show antipersistency for scales longer than 2 months. The property points at a cumulative negative feedback in the Earth climate system governing the tropospheric variability during the last 22 years. The result emphasizes a dominating role of the solar irradiance variability in variations of the tropospheric temperature and gives no support to the theory of anthropogenic climate change. The global average stratospheric temperature anomaly proceeds like a 1-dim random walk at least up to 11 years, allowing good presentation by means of the autoregressive integrated moving average (ARIMA) models for monthly series.

Global patterns in the poleward expansion of mangrove forests

NASA Astrophysics Data System (ADS)

Cavanaugh, K. C.; Feller, I. C.

2016-12-01

Understanding the processes that limit the geographic ranges of species is one of the central goals of ecology and biogeography. This issue is particularly relevant for coastal wetlands given that climate change is expected to lead to a `tropicalization' of temperate coastal and marine ecosystems. In coastal wetlands around the world, there have already been observations of mangroves expanding into salt marshes near the current poleward range limits of mangroves. However, there is still uncertainty regarding regional variability in the factors that control mangrove range limits. Here we used time series of Landsat satellite imagery to characterize patterns of mangrove abundance near their poleward range limits around the world. We tested the commonly held assumption that temporal variation in abundance should increase towards the edge of the range. We also compared variability in mangrove abundance to climate factors thought to set mangrove range limits (air temperature, water temperature, and aridity). In general, variability in mangrove abundance at range edges was high relative to range centers and this variability was correlated to one or more climate factors. However, the strength of these relationships varied among poleward range limits, suggesting that some mangrove range limits are control by processes other than climate, such as dispersal limitation.

Improving plot- and regional-scale crop models for simulating impacts of climate variability and extremes

NASA Astrophysics Data System (ADS)

Tao, F.; Rötter, R.

2013-12-01

Many studies on global climate report that climate variability is increasing with more frequent and intense extreme events1. There are quite large uncertainties from both the plot- and regional-scale models in simulating impacts of climate variability and extremes on crop development, growth and productivity2,3. One key to reducing the uncertainties is better exploitation of experimental data to eliminate crop model deficiencies and develop better algorithms that more adequately capture the impacts of extreme events, such as high temperature and drought, on crop performance4,5. In the present study, in a first step, the inter-annual variability in wheat yield and climate from 1971 to 2012 in Finland was investigated. Using statistical approaches the impacts of climate variability and extremes on wheat growth and productivity were quantified. In a second step, a plot-scale model, WOFOST6, and a regional-scale crop model, MCWLA7, were calibrated and validated, and applied to simulate wheat growth and yield variability from 1971-2012. Next, the estimated impacts of high temperature stress, cold damage, and drought stress on crop growth and productivity based on the statistical approaches, and on crop simulation models WOFOST and MCWLA were compared. Then, the impact mechanisms of climate extremes on crop growth and productivity in the WOFOST model and MCWLA model were identified, and subsequently, the various algorithm and impact functions were fitted against the long-term crop trial data. Finally, the impact mechanisms, algorithms and functions in WOFOST model and MCWLA model were improved to better simulate the impacts of climate variability and extremes, particularly high temperature stress, cold damage and drought stress for location-specific and large area climate impact assessments. Our studies provide a good example of how to improve, in parallel, the plot- and regional-scale models for simulating impacts of climate variability and extremes, as needed for better informed decision-making on adaptation strategies. References 1. Coumou, D. & Rahmstorf, S. A decade of extremes. Nature Clim. Change, 2, 491-496 (2012). 2. Rötter, R. P., Carter, T. R., Olesen, J. E. & Porter, J. R. Crop-climate models need an overhaul. Nature Clim. Change, 1, 175-177 (2011). 3. Asseng, S. et al., Uncertainty in simulating wheat yields under climate change. Nature Clim. Change. 10.1038/nclimate1916. (2013). 4. Porter, J.R., & Semenov, M., Crop responses to climatic variation . Trans. R. Soc. B., 360, 2021-2035 (2005). 5. Porter, J.R. & Christensen, S. Deconstructing crop processes and models via identities. Plant, Cell and Environment . doi: 10.1111/pce.12107 (2013). 6. Boogaard, H.L., van Diepen C.A., Rötter R.P., Cabrera J.M. & van Laar H.H. User's guide for the WOFOST 7.1 crop growth simulation model and Control Center 1.5, Alterra, Wageningen, The Netherlands. (1998) 7. Tao, F. & Zhang, Z. Climate change, wheat productivity and water use in the North China Plain: a new super-ensemble-based probabilistic projection. Agric. Forest Meteorol., 170, 146-165. (2013).

Thermal tolerance breadths among groundwater crustaceans living in a thermally constant environment.

PubMed

Mermillod-Blondin, F; Lefour, C; Lalouette, L; Renault, D; Malard, F; Simon, L; Douady, C J

2013-05-01

The climate variability hypothesis assumes that the thermal tolerance breadth of a species is primarily determined by temperature variations experienced in its environment. If so, aquatic invertebrates living in thermally buffered environments would be expected to exhibit narrow thermal tolerance breadths (stenothermy). We tested this prediction by studying the thermal physiology of three isopods (Asellidae, Proasellus) colonizing groundwater habitats characterized by an annual temperature amplitude of less than 1°C. The species responses to temperature variation were assessed in the laboratory using five physiological variables: survival, locomotor activity, aerobic respiration, immune defense and concentrations of total free amino acids and sugars. The three species exhibited contrasted thermal physiologies, although all variables were not equally informative. In accordance with the climate variability hypothesis, two species were extremely sensitive even to moderate changes in temperature (2°C) below and above their habitat temperature. In contrast, the third species exhibited a surprisingly high thermal tolerance breadth (11°C). Differences in response to temperature variation among Proasellus species indicated that their thermal physiology was not solely shaped by the current temperature seasonality in their natural habitats. More particularly, recent gene flow among populations living in thermally constant yet contrasted habitats might explain the occurrence of eurytherm species in thermally buffered environments.

Air temperature change in the northern and southern tropical Andes linked to North-Atlantic stadials and Greenland interstadials

NASA Astrophysics Data System (ADS)

Urrego, Dunia H.; Hooghiemstra, Henry

2016-04-01

We use eight pollen records reflecting climatic and environmental change from northern and southern sites in the tropical Andes. Our analysis focuses on the signature of millennial-scale climate variability during the last 30,000 years, in particular the Younger Dryas (YD), Heinrich stadials (HS) and Greenland interstadials (GI). We identify rapid responses of the vegetation to millennial-scale climate variability in the tropical Andes. The signature of HS and the YD are generally recorded as downslope migrations of the upper forest line (UFL), and are likely linked to air temperature cooling. The GI1 signal is overall comparable between northern and southern records and indicates upslope UFL migrations and warming in the tropical Andes. Our marker for lake level changes indicates a north to south difference that could be related to moisture availability. The direction of air temperature change recorded by the Andean vegetation is consistent with millennial-scale cryosphere and sea surface temperature records from the American tropics, but suggests a potential difference between the magnitude of temperature change in the ocean and the atmosphere.

An observationally centred method to quantify local climate change as a distribution

NASA Astrophysics Data System (ADS)

Stainforth, David; Chapman, Sandra; Watkins, Nicholas

2013-04-01

For planning and adaptation, guidance on trends in local climate is needed at the specific thresholds relevant to particular impact or policy endeavours. This requires quantifying trends at specific quantiles in distributions of variables such as daily temperature or precipitation. These non-normal distributions vary both geographically and in time. The trends in the relevant quantiles may not simply follow the trend in the distribution mean. We present a method[1] for analysing local climatic timeseries data to assess which quantiles of the local climatic distribution show the greatest and most robust trends. We demonstrate this approach using E-OBS gridded data[2] timeseries of local daily temperature from specific locations across Europe over the last 60 years. Our method extracts the changing cumulative distribution function over time and uses a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. This deconstruction facilitates an assessment of the sensitivity of different quantiles of the distributions to changing climate. Geographical location and temperature are treated as independent variables, we thus obtain as outputs how the trend or sensitivity varies with temperature (or occurrence likelihood), and with geographical location. These sensitivities are found to be geographically varying across Europe; as one would expect given the different influences on local climate between, say, Western Scotland and central Italy. We find as an output many regionally consistent patterns of response of potential value in adaptation planning. We discuss methods to quantify the robustness of these observed sensitivities and their statistical likelihood. This also quantifies the level of detail needed from climate models if they are to be used as tools to assess climate change impact. [1] S C Chapman, D A Stainforth, N W Watkins, 2013, On Estimating Local Long Term Climate Trends, Phil. Trans. R. Soc. A, in press [2] Haylock, M.R., N. Hofstra, A.M.G. Klein Tank, E.J. Klok, P.D. Jones and M. New. 2008: A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres), 113, D20119, doi:10.1029/2008JD10201

The role of ENSO in understanding changes in Colombia's annual malaria burden by region, 1960–2006

PubMed Central

Mantilla, Gilma; Oliveros, Hugo; Barnston, Anthony G

2009-01-01

Background Malaria remains a serious problem in Colombia. The number of malaria cases is governed by multiple climatic and non-climatic factors. Malaria control policies, and climate controls such as rainfall and temperature variations associated with the El Niño/Southern Oscillation (ENSO), have been associated with malaria case numbers. Using historical climate data and annual malaria case number data from 1960 to 2006, statistical models are developed to isolate the effects of climate in each of Colombia's five contrasting geographical regions. Methods Because year to year climate variability associated with ENSO causes interannual variability in malaria case numbers, while changes in population and institutional control policy result in more gradual trends, the chosen predictors in the models are annual indices of the ENSO state (sea surface temperature [SST] in the tropical Pacific Ocean) and time reference indices keyed to two major malaria trends during the study period. Two models were used: a Poisson and a Negative Binomial regression model. Two ENSO indices, two time reference indices, and one dummy variable are chosen as candidate predictors. The analysis was conducted using the five geographical regions to match the similar aggregation used by the National Institute of Health for its official reports. Results The Negative Binomial regression model is found better suited to the malaria cases in Colombia. Both the trend variables and the ENSO measures are significant predictors of malaria case numbers in Colombia as a whole, and in two of the five regions. A one degree Celsius change in SST (indicating a weak to moderate ENSO event) is seen to translate to an approximate 20% increase in malaria cases, holding other variables constant. Conclusion Regional differentiation in the role of ENSO in understanding changes in Colombia's annual malaria burden during 1960–2006 was found, constituting a new approach to use ENSO as a significant predictor of the malaria cases in Colombia. These results naturally point to additional needed work: (1) refining the regional and seasonal dependence of climate on the ENSO state, and of malaria on the climate variables; (2) incorporating ENSO-related climate variability into dynamic malaria models. PMID:19133152

Winter climate limits subantarctic low forest growth and establishment.

PubMed

Harsch, Melanie A; McGlone, Matt S; Wilmshurst, Janet M

2014-01-01

Campbell Island, an isolated island 600 km south of New Zealand mainland (52 °S, 169 °E) is oceanic (Conrad Index of Continentality  =  -5) with small differences between mean summer and winter temperatures. Previous work established the unexpected result that a mean annual climate warming of c. 0.6 °C since the 1940's has not led to upward movement of the forest limit. Here we explore the relative importance of summer and winter climatic conditions on growth and age-class structure of the treeline forming species, Dracophyllum longifolium and Dracophyllum scoparium over the second half of the 20th century. The relationship between climate and growth and establishment were evaluated using standard dendroecological methods and local climate data from a meteorological station on the island. Growth and establishment were correlated against climate variables and further evaluated within hierarchical regression models to take into account the effect of plot level variables. Winter climatic conditions exerted a greater effect on growth and establishment than summer climatic conditions. Establishment is maximized under warm (mean winter temperatures >7 °C), dry winters (total winter precipitation <400 mm). Growth, on the other hand, is adversely affected by wide winter temperature ranges and increased rainfall. The contrasting effect of winter warmth on growth and establishment suggests that winter temperature affects growth and establishment through differing mechanisms. We propose that milder winters enhance survival of seedlings and, therefore, recruitment, but increases metabolic stress on established plants, resulting in lower growth rates. Future winter warming may therefore have complex effects on plant growth and establishment globally.

Winter Climate Limits Subantarctic Low Forest Growth and Establishment

PubMed Central

Harsch, Melanie A.; McGlone, Matt S.; Wilmshurst, Janet M.

2014-01-01

Campbell Island, an isolated island 600 km south of New Zealand mainland (52°S, 169°E) is oceanic (Conrad Index of Continentality  = −5) with small differences between mean summer and winter temperatures. Previous work established the unexpected result that a mean annual climate warming of c. 0.6°C since the 1940's has not led to upward movement of the forest limit. Here we explore the relative importance of summer and winter climatic conditions on growth and age-class structure of the treeline forming species, Dracophyllum longifolium and Dracophyllum scoparium over the second half of the 20th century. The relationship between climate and growth and establishment were evaluated using standard dendroecological methods and local climate data from a meteorological station on the island. Growth and establishment were correlated against climate variables and further evaluated within hierarchical regression models to take into account the effect of plot level variables. Winter climatic conditions exerted a greater effect on growth and establishment than summer climatic conditions. Establishment is maximized under warm (mean winter temperatures >7 °C), dry winters (total winter precipitation <400 mm). Growth, on the other hand, is adversely affected by wide winter temperature ranges and increased rainfall. The contrasting effect of winter warmth on growth and establishment suggests that winter temperature affects growth and establishment through differing mechanisms. We propose that milder winters enhance survival of seedlings and, therefore, recruitment, but increases metabolic stress on established plants, resulting in lower growth rates. Future winter warming may therefore have complex effects on plant growth and establishment globally. PMID:24691026

Interannual variation of carbon fluxes from three contrasting evergreen forests: The role of forest dynamics and climate

USGS Publications Warehouse

Sierra, C.A.; Loescher, H.W.; Harmon, M.E.; Richardson, A.D.; Hollinger, D.Y.; Perakis, S.S.

2009-01-01

Interannual variation of carbon fluxes can be attributed to a number of biotic and abiotic controls that operate at different spatial and temporal scales. Type and frequency of disturbance, forest dynamics, and climate regimes are important sources of variability. Assessing the variability of carbon fluxes from these specific sources can enhance the interpretation of past and current observations. Being able to separate the variability caused by forest dynamics from that induced by climate will also give us the ability to determine if the current observed carbon fluxes are within an expected range or whether the ecosystem is undergoing unexpected change. Sources of interannual variation in ecosystem carbon fluxes from three evergreen ecosystems, a tropical, a temperate coniferous, and a boreal forest, were explored using the simulation model STANDCARB. We identified key processes that introduced variation in annual fluxes, but their relative importance differed among the ecosystems studied. In the tropical site, intrinsic forest dynamics contributed ?? 30% of the total variation in annual carbon fluxes. In the temperate and boreal sites, where many forest processes occur over longer temporal scales than those at the tropical site, climate controlled more of the variation among annual fluxes. These results suggest that climate-related variability affects the rates of carbon exchange differently among sites. Simulations in which temperature, precipitation, and radiation varied from year to year (based on historical records of climate variation) had less net carbon stores than simulations in which these variables were held constant (based on historical records of monthly average climate), a result caused by the functional relationship between temperature and respiration. This suggests that, under a more variable temperature regime, large respiratory pulses may become more frequent and high enough to cause a reduction in ecosystem carbon stores. Our results also show that the variation of annual carbon fluxes poses an important challenge in our ability to determine whether an ecosystem is a source, a sink, or is neutral in regard to CO2 at longer timescales. In simulations where climate change negatively affected ecosystem carbon stores, there was a 20% chance of committing Type II error, even with 20 years of sequential data. ?? 2009 by the Ecological Society of America.

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

PubMed

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

2015-04-01

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

Spatial patterns of recent Antarctic surface temperature trends and the importance of natural variability: lessons from multiple reconstructions and the CMIP5 models

NASA Astrophysics Data System (ADS)

Smith, Karen L.; Polvani, Lorenzo M.

2017-04-01

The recent annually averaged warming of the Antarctic Peninsula, and of West Antarctica, stands in stark contrast to very small trends over East Antarctica. This asymmetry arises primarily from a highly significant warming of West Antarctica in austral spring and a cooling of East Antarctica in austral autumn. Here we examine whether this East-West asymmetry is a response to anthropogenic climate forcings or a manifestation of natural climate variability. We compare the observed Antarctic surface air temperature trends over two distinct time periods (1960-2005 and 1979-2005), and with those simulated by 40 models participating in Phase 5 of the Coupled Model Intercomparison Project (CMIP5). We find that the observed East-West asymmetry differs substantially between the two periods and, furthermore, that it is completely absent from the forced response seen in the CMIP5 multi-model mean, from which all natural variability is eliminated by the averaging. We also examine the relationship between the Southern Annular mode (SAM) and Antarctic temperature trends, in both models and reanalyses, and again conclude that there is little evidence of anthropogenic SAM-induced driving of the recent temperature trends. These results offer new, compelling evidence pointing to natural climate variability as a key contributor to the recent warming of West Antarctica and of the Peninsula.

Downscaling GCM Output with Genetic Programming Model

NASA Astrophysics Data System (ADS)

Shi, X.; Dibike, Y. B.; Coulibaly, P.

2004-05-01

Climate change impact studies on watershed hydrology require reliable data at appropriate spatial and temporal resolution. However, the outputs of the current global climate models (GCMs) cannot be used directly because GCM do not provide hourly or daily precipitation and temperature reliable enough for hydrological modeling. Nevertheless, we can get more reliable data corresponding to future climate scenarios derived from GCM outputs using the so called 'downscaling techniques'. This study applies Genetic Programming (GP) based technique to downscale daily precipitation and temperature values at the Chute-du-Diable basin of the Saguenay watershed in Canada. In applying GP downscaling technique, the objective is to find a relationship between the large-scale predictor variables (NCEP data which provide daily information concerning the observed large-scale state of the atmosphere) and the predictand (meteorological data which describes conditions at the site scale). The selection of the most relevant predictor variables is achieved using the Pearson's coefficient of determination ( R2) (between the large-scale predictor variables and the daily meteorological data). In this case, the period (1961 - 2000) is identified to represent the current climate condition. For the forty years of data, the first 30 years (1961-1990) are considered for calibrating the models while the remaining ten years of data (1991-2000) are used to validate those models. In general, the R2 between the predictor variables and each predictand is very low in case of precipitation compared to that of maximum and minimum temperature. Moreover, the strength of individual predictors varies for every month and for each GP grammar. Therefore, the most appropriate combination of predictors has to be chosen by looking at the output analysis of all the twelve months and the different GP grammars. During the calibration of the GP model for precipitation downscaling, in addition to the mean daily precipitation and daily precipitation variability for each month, monthly average dry and wet-spell lengths are also considered as performance criteria. For the cases of Tmax and Tmin, means and variances of these variables corresponding to each month were considered as performance criteria. The GP downscaling results show satisfactory agreement between the observed daily temperature (Tmax and Tmin) and the simulated temperature. However, the downscaling results for the daily precipitation still require some improvement - suggesting further investigation of other grammars. KEY WORDS: Climate change; GP downscaling; GCM.

Oceanic influence on seasonal malaria outbreaks over Senegal and Sahel. Predictability using S4CAST model

NASA Astrophysics Data System (ADS)

Diouf, Ibrahima; Deme, Abdoulaye; Rodriguez-Fonseca, Belen; Suárez-Moreno, Roberto; Cisse, Moustapha; Ndione, Jacques-André; Thierno Gaye, Amadou

2014-05-01

Senegal and, in general, West African regions are affected by important outbreaks of diseases with destructive consequences for human population, livestock and country's economy. The vector-borne diseases such as mainly malaria, Rift Valley Fever and dengue are affected by the interanual to decadal variability of climate. Analysis of the spatial and temporal variability of climate parameters and associated oceanic patterns is important in order to assess the climate impact on malaria transmission. In this study, the approach developed to study the malaria-climate link is predefined by the QWeCI project (Quantifying Weather and Climate Impacts on Health in Developing Countries). Preliminary observations and simulations results over Senegal Ferlo region, confirm that the risk of malaria transmission is mainly linked to climate parameters such as rainfall, temperature and relative humidity; and a lag of one to two months between the maximum of malaria and the maximum of climate parameters as rainfall is observed. As climate variables are able to be predicted from oceanic SST variability in remote regions, this study explores seasonal predictability of malaria incidence outbreaks from previous sea surface temperatures conditions in different ocean basins. We have found causal or coincident relationship between El Niño and malaria parameters by coupling LMM UNILIV malaria model and S4CAST statistiscal model with the aim of predicting the malaria parameters with more than 6 months in advance. In particular, El Niño is linked to an important decrease of the number of mosquitoes and the malaria incidence. Results from this research, after assessing the seasonal malaria parameters, are expected to be useful for decision makers to better access to climate forecasts and application on health in the framework of rolling back malaria transmission.

Does climate directly influence NPP globally?

PubMed

Chu, Chengjin; Bartlett, Megan; Wang, Youshi; He, Fangliang; Weiner, Jacob; Chave, Jérôme; Sack, Lawren

2016-01-01

The need for rigorous analyses of climate impacts has never been more crucial. Current textbooks state that climate directly influences ecosystem annual net primary productivity (NPP), emphasizing the urgent need to monitor the impacts of climate change. A recent paper challenged this consensus, arguing, based on an analysis of NPP for 1247 woody plant communities across global climate gradients, that temperature and precipitation have negligible direct effects on NPP and only perhaps have indirect effects by constraining total stand biomass (Mtot ) and stand age (a). The authors of that study concluded that the length of the growing season (lgs ) might have a minor influence on NPP, an effect they considered not to be directly related to climate. In this article, we describe flaws that affected that study's conclusions and present novel analyses to disentangle the effects of stand variables and climate in determining NPP. We re-analyzed the same database to partition the direct and indirect effects of climate on NPP, using three approaches: maximum-likelihood model selection, independent-effects analysis, and structural equation modeling. These new analyses showed that about half of the global variation in NPP could be explained by Mtot combined with climate variables and supported strong and direct influences of climate independently of Mtot , both for NPP and for net biomass change averaged across the known lifetime of the stands (ABC = average biomass change). We show that lgs is an important climate variable, intrinsically correlated with, and contributing to mean annual temperature and precipitation (Tann and Pann ), all important climatic drivers of NPP. Our analyses provide guidance for statistical and mechanistic analyses of climate drivers of ecosystem processes for predictive modeling and provide novel evidence supporting the strong, direct role of climate in determining vegetation productivity at the global scale. © 2015 John Wiley & Sons Ltd.

Centennial-scale winter climate variability over the last two millennia in the northern Gulf of Mexico based on paired δ18O and Mg/Ca in Globorotalia truncatulinoides

NASA Astrophysics Data System (ADS)

Fortiz, V.; Thirumalai, K.; Richey, J. N.; Quinn, T. M.

2014-12-01

We present a replicated record of paired foraminiferal δ18O and Mg/Ca variations in multi-cores collected from the Garrison Basin (26º43'N, 93º55'W) in the northern Gulf of Mexico (GOM). Using δ18O (sea surface temperature, SST; sea surface salinity, SSS proxy) and Mg/Ca (SST proxy) variations in non-encrusted planktic foraminifer Globorotalia truncatulinoides we produce time series spanning the last two millennia that is characterized by centennial-scale climate variability. We interpret geochemical variations in G. truncatulinoides to reflect winter climate variability because data from a sediment trap, located ~350 km east of the core site, reveal that annual flux of G. truncatulinoides is heavily weighted towards winter (peak production in January-February; Spear et al., 2011). Similar centennial-scale variability is also observed in the foraminiferal geochemistry of Globigerinoides ruber in the same multi-cores, which likely reflect mean annual climate variations. Our replicated results and comparisons to other SST reconstructions from the region lend confidence that the northern GOM surface ocean underwent large, centennial-scale variability, most likely dominated by changes in winter climate. This variability occurred in a time period where climate forcing is small and background conditions are similar to pre-industrial times. References: Spear, J.W.; Poore, R.Z., and Quinn, T.M., 2011, Globorotalia truncatulinoides (dextral) Mg/Ca as a proxy for Gulf of Mexico winter mixed-layer temperature: Evidence from a sediment trap in the northern Gulf of Mexico. Marine Micropaleontology, 80, 53-61.

Native temperature regime influences soil response to simulated warming

Treesearch

Timothy G. Whitby; Michael D. Madritch

2013-01-01

Anthropogenic climate change is expected to increase global temperatures and potentially increase soil carbon (C) mineralization, which could lead to a positive feedback between global warming and soil respiration. However the magnitude and spatial variability of belowground responses to warming are not yet fully understood. Some of the variability may depend...

Climate and soil attributes determine plant species turnover in global drylands.

PubMed

Ulrich, Werner; Soliveres, Santiago; Maestre, Fernando T; Gotelli, Nicholas J; Quero, José L; Delgado-Baquerizo, Manuel; Bowker, Matthew A; Eldridge, David J; Ochoa, Victoria; Gozalo, Beatriz; Valencia, Enrique; Berdugo, Miguel; Escolar, Cristina; García-Gómez, Miguel; Escudero, Adrián; Prina, Aníbal; Alfonso, Graciela; Arredondo, Tulio; Bran, Donaldo; Cabrera, Omar; Cea, Alex; Chaieb, Mohamed; Contreras, Jorge; Derak, Mchich; Espinosa, Carlos I; Florentino, Adriana; Gaitán, Juan; Muro, Victoria García; Ghiloufi, Wahida; Gómez-González, Susana; Gutiérrez, Julio R; Hernández, Rosa M; Huber-Sannwald, Elisabeth; Jankju, Mohammad; Mau, Rebecca L; Hughes, Frederic Mendes; Miriti, Maria; Monerris, Jorge; Muchane, Muchai; Naseri, Kamal; Pucheta, Eduardo; Ramírez-Collantes, David A; Raveh, Eran; Romão, Roberto L; Torres-Díaz, Cristian; Val, James; Veiga, José Pablo; Wang, Deli; Yuan, Xia; Zaady, Eli

2014-12-01

Geographic, climatic, and soil factors are major drivers of plant beta diversity, but their importance for dryland plant communities is poorly known. This study aims to: i) characterize patterns of beta diversity in global drylands, ii) detect common environmental drivers of beta diversity, and iii) test for thresholds in environmental conditions driving potential shifts in plant species composition. 224 sites in diverse dryland plant communities from 22 geographical regions in six continents. Beta diversity was quantified with four complementary measures: the percentage of singletons (species occurring at only one site), Whittake's beta diversity (β(W)), a directional beta diversity metric based on the correlation in species occurrences among spatially contiguous sites (β(R 2 )), and a multivariate abundance-based metric (β(MV)). We used linear modelling to quantify the relationships between these metrics of beta diversity and geographic, climatic, and soil variables. Soil fertility and variability in temperature and rainfall, and to a lesser extent latitude, were the most important environmental predictors of beta diversity. Metrics related to species identity (percentage of singletons and β(W)) were most sensitive to soil fertility, whereas those metrics related to environmental gradients and abundance ((β(R 2 )) and β(MV)) were more associated with climate variability. Interactions among soil variables, climatic factors, and plant cover were not important determinants of beta diversity. Sites receiving less than 178 mm of annual rainfall differed sharply in species composition from more mesic sites (> 200 mm). Soil fertility and variability in temperature and rainfall are the most important environmental predictors of variation in plant beta diversity in global drylands. Our results suggest that those sites annually receiving ~ 178 mm of rainfall will be especially sensitive to future climate changes. These findings may help to define appropriate conservation strategies for mitigating effects of climate change on dryland vegetation.

Internal Variability-Generated Uncertainty in East Asian Climate Projections Estimated with 40 CCSM3 Ensembles.

PubMed

Yao, Shuai-Lei; Luo, Jing-Jia; Huang, Gang

2016-01-01

Regional climate projections are challenging because of large uncertainty particularly stemming from unpredictable, internal variability of the climate system. Here, we examine the internal variability-induced uncertainty in precipitation and surface air temperature (SAT) trends during 2005-2055 over East Asia based on 40 member ensemble projections of the Community Climate System Model Version 3 (CCSM3). The model ensembles are generated from a suite of different atmospheric initial conditions using the same SRES A1B greenhouse gas scenario. We find that projected precipitation trends are subject to considerably larger internal uncertainty and hence have lower confidence, compared to the projected SAT trends in both the boreal winter and summer. Projected SAT trends in winter have relatively higher uncertainty than those in summer. Besides, the lower-level atmospheric circulation has larger uncertainty than that in the mid-level. Based on k-means cluster analysis, we demonstrate that a substantial portion of internally-induced precipitation and SAT trends arises from internal large-scale atmospheric circulation variability. These results highlight the importance of internal climate variability in affecting regional climate projections on multi-decadal timescales.

Phenotypic Plasticity of Leaf Shape along a Temperature Gradient in Acer rubrum

PubMed Central

Royer, Dana L.; Meyerson, Laura A.; Robertson, Kevin M.; Adams, Jonathan M.

2009-01-01

Both phenotypic plasticity and genetic determination can be important for understanding how plants respond to environmental change. However, little is known about the plastic response of leaf teeth and leaf dissection to temperature. This gap is critical because these leaf traits are commonly used to reconstruct paleoclimate from fossils, and such studies tacitly assume that traits measured from fossils reflect the environment at the time of their deposition, even during periods of rapid climate change. We measured leaf size and shape in Acer rubrum derived from four seed sources with a broad temperature range and grown for two years in two gardens with contrasting climates (Rhode Island and Florida). Leaves in the Rhode Island garden have more teeth and are more highly dissected than leaves in Florida from the same seed source. Plasticity in these variables accounts for at least 6–19 % of the total variance, while genetic differences among ecotypes probably account for at most 69–87 %. This study highlights the role of phenotypic plasticity in leaf-climate relationships. We suggest that variables related to tooth count and leaf dissection in A. rubrum can respond quickly to climate change, which increases confidence in paleoclimate methods that use these variables. PMID:19893620

Does weather shape rodents? Climate related changes in morphology of two heteromyid species

NASA Astrophysics Data System (ADS)

Wolf, Mosheh; Friggens, Michael; Salazar-Bravo, Jorge

2009-01-01

Geographical variation in morphometric characters in heteromyid rodents has often correlated with climate gradients. Here, we used the long-term database of rodents trapped in the Sevilleta National Wildlife Refuge in New Mexico, USA to test whether significant annual changes in external morphometric characters are observed in a region with large variations in temperature and precipitation. We looked at the relationships between multiple temperature and precipitation variables and a number of morphological traits (body mass, body, tail, hind leg, and ear length) for two heteromyid rodents, Dipodomys merriami and Perognathus flavescens. Because these rodents can live multiple years in the wild, the climate variables for the year of the capture and the previous 2 years were included in the analyses. Using multiple linear regressions, we found that all of our morphometric traits, with the exception of tail length in D. merriami, had a significant relationship with one or more of the climate variables used. Our results demonstrate that effects of climate change on morphological traits occur over short periods, even in noninsular mammal populations. It is unclear, though, whether these changes are the result of morphological plasticity or natural selection.

Interactive influence of the Atlantic and Pacific climates and their contribution to the multidecadal variations of global temperature and precipitation.

NASA Astrophysics Data System (ADS)

Barcikowska, M. J.; Knutson, T. R.; Zhang, R.

2016-12-01

This study investigates mechanisms and global-scale climate impacts of multidecadal climate variability. Here we show, using observations and CSIRO-Mk3.6.0 model control run, that multidecadal variability of the Atlantic Meridional Overturning Circulation (AMOC) may have a profound impact on the thermal- and hydro-climatic changes over the Pacific region. In our model-based analysis we propose a mechanism, which comprises a coupled ocean-atmosphere teleconnection, established through the atmospheric overturning circulation cell between the tropical North Atlantic and tropical Pacific. For example, warming SSTs over the tropical North Atlantic intensify local convection and reinforce subsidence, low-level divergence in the eastern tropical Pacific. This is also accompanied with an intensification of trade winds, cooling and drying anomalies in the tropical central-east Pacific. The derived multidecadal changes, associated with the AMOC, contribute remarkably to the global temperature and precipitation variations. This highlights its potential predictive value. Shown here results suggest a possibility that: 1) recently observed slowdown in global warming may partly originate from internal variability, 2) climate system may be undergoing a transition to a cold AMO phase which could prolong the global slowdown.

Impacts of Climatic Variability on Vibrio parahaemolyticus Outbreaks in Taiwan

PubMed Central

Hsiao, Hsin-I; Jan, Man-Ser; Chi, Hui-Ju

2016-01-01

This study aimed to investigate and quantify the relationship between climate variation and incidence of Vibrio parahaemolyticus in Taiwan. Specifically, seasonal autoregressive integrated moving average (ARIMA) models (including autoregression, seasonality, and a lag-time effect) were employed to predict the role of climatic factors (including temperature, rainfall, relative humidity, ocean temperature and ocean salinity) on the incidence of V. parahaemolyticus in Taiwan between 2000 and 2011. The results indicated that average temperature (+), ocean temperature (+), ocean salinity of 6 months ago (+), maximum daily rainfall (current (−) and one month ago (−)), and average relative humidity (current and 9 months ago (−)) had significant impacts on the incidence of V. parahaemolyticus. Our findings offer a novel view of the quantitative relationship between climate change and food poisoning by V. parahaemolyticus in Taiwan. An early warning system based on climate change information for the disease control management is required in future. PMID:26848675

Impacts of Climatic Variability on Vibrio parahaemolyticus Outbreaks in Taiwan.

PubMed

Hsiao, Hsin-I; Jan, Man-Ser; Chi, Hui-Ju

2016-02-03

This study aimed to investigate and quantify the relationship between climate variation and incidence of Vibrio parahaemolyticus in Taiwan. Specifically, seasonal autoregressive integrated moving average (ARIMA) models (including autoregression, seasonality, and a lag-time effect) were employed to predict the role of climatic factors (including temperature, rainfall, relative humidity, ocean temperature and ocean salinity) on the incidence of V. parahaemolyticus in Taiwan between 2000 and 2011. The results indicated that average temperature (+), ocean temperature (+), ocean salinity of 6 months ago (+), maximum daily rainfall (current (-) and one month ago (-)), and average relative humidity (current and 9 months ago (-)) had significant impacts on the incidence of V. parahaemolyticus. Our findings offer a novel view of the quantitative relationship between climate change and food poisoning by V. parahaemolyticus in Taiwan. An early warning system based on climate change information for the disease control management is required in future.

Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise.

PubMed

Brown, Patrick T; Li, Wenhong; Cordero, Eugene C; Mauget, Steven A

2015-04-21

The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20(th) century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal.

Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise

PubMed Central

Brown, Patrick T.; Li, Wenhong; Cordero, Eugene C.; Mauget, Steven A.

2015-01-01

The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20th century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal. PMID:25898351

New climate change scenarios for the Netherlands.

PubMed

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

2007-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Improving the Representation of Land in Climate Models by Application of EOS Observations

NASA Technical Reports Server (NTRS)

2004-01-01

The PI's IDS current and previous investigation has focused on the applications of the land data toward the improvement of climate models. The previous IDS research identified the key factors limiting the accuracy of climate models to be the representation of albedos, land cover, fraction of landscape covered by vegetation, roughness lengths, surface skin temperature and canopy properties such as leaf area index (LAI) and average stomatal conductance. Therefore, we assembled a team uniquely situated to focus on these key variables and incorporate the remotely sensed measures of these variables into the next generation of climate models.

Spatial variation in the climatic predictors of species compositional turnover and endemism

PubMed Central

Di Virgilio, Giovanni; Laffan, Shawn W; Ebach, Malte C; Chapple, David G

2014-01-01

Previous research focusing on broad-scale or geographically invariant species-environment dependencies suggest that temperature-related variables explain more of the variation in reptile distributions than precipitation. However, species–environment relationships may exhibit considerable spatial variation contingent upon the geographic nuances that vary between locations. Broad-scale, geographically invariant analyses may mask this local variation and their findings may not generalize to different locations at local scales. We assess how reptile–climatic relationships change with varying spatial scale, location, and direction. Since the spatial distributions of diversity and endemism hotspots differ for other species groups, we also assess whether reptile species turnover and endemism hotspots are influenced differently by climatic predictors. Using New Zealand reptiles as an example, the variation in species turnover, endemism and turnover in climatic variables was measured using directional moving window analyses, rotated through 360°. Correlations between the species turnover, endemism and climatic turnover results generated by each rotation of the moving window were analysed using multivariate generalized linear models applied at national, regional, and local scales. At national-scale, temperature turnover consistently exhibited the greatest influence on species turnover and endemism, but model predictive capacity was low (typically r2 = 0.05, P < 0.001). At regional scales the relative influence of temperature and precipitation turnover varied between regions, although model predictive capacity was also generally low. Climatic turnover was considerably more predictive of species turnover and endemism at local scales (e.g., r2 = 0.65, P < 0.001). While temperature turnover had the greatest effect in one locale (the northern North Island), there was substantial variation in the relative influence of temperature and precipitation predictors in the remaining four locales. Species turnover and endemism hotspots often occurred in different locations. Climatic predictors had a smaller influence on endemism. Our results caution against assuming that variability in temperature will always be most predictive of reptile biodiversity across different spatial scales, locations and directions. The influence of climatic turnover on the species turnover and endemism of other taxa may exhibit similar patterns of spatial variation. Such intricate variation might be discerned more readily if studies at broad scales are complemented by geographically variant, local-scale analyses. PMID:25473479

Intra-Seasonal Variability of Climate and Peasant Perception of Climate Change in Massili Basin in Burkina Faso.

NASA Astrophysics Data System (ADS)

Kabore Bontogho, P. E.

2014-12-01

Knowledge of climate variability is relevant and challenging for farmers, decision makers and population in general. Ninety percent of Burkina Faso active population is engaged in agriculture and livestock, which accounts for 39% of gross domestic product. Located between the coordinates 1o15'-1o55' West and 12o17'- 12o50'North, Massili basin includes Ouagadougou the capital and has four dams, of which the most important dam, Loumbila is used for the capital water supply and irrigation. A change of climate may affect the water resources most likely limit the access to safe water. In order to characterize Massili basin climate variability, daily temperature and precipitation over 1960 to 2012 was analyzed using long-term records from the Ouagadougou synoptic station. By applying R-climdex and instat tools, indices were calculated by a consistent approach recommended by the World Meteorological Organization Expert Team on Climate Change Detection and Indices. The precipitation parameters computed were: the maximum 5-day precipitationamount; the number of days with precipitation amount ≥50 mm ; the maximum precipitation amount in consecutive wet days with RR≥ 1mm; the consecutives dry days;the extremely wet days ; the extreme precipitation in one day, the total precipitation in wet days; the temperature indices computed were : the maximum of the maximum daily temperature, the minimum of daily maximum temperature,the minimum of daily minimum temperature,the cold spell duration indices and the warm spell duration indicator. Results show a slight increase of the maximum 5-day precipitation, maximum precipitation amount in consecutive wet days with RR≥1mm, the onset delayed and the cessation is earlier meaning that the rainfall period is shortening. The total precipitationwas decreased in the basin but there is a slight increase in the occurrence of extremely wet days. CSDI is decreasing while warm spell duration indices are increasing. In parallel of the data analysis, a survey of 200 peasant spread within 20 villages was done to assess their perception on climate change. Farmers perception corroborate with the above results as their majority describes climate change as decrease of rainfall (79%) and increase of temperature (99%). In addition, all farmers agreed that more floods are occurring.

Quantifying Livestock Heat Stress Impacts in the Sahel

NASA Astrophysics Data System (ADS)

Broman, D.; Rajagopalan, B.; Hopson, T. M.

2014-12-01

Livestock heat stress, especially in regions of the developing world with limited adaptive capacity, has a largely unquantified impact on food supply. Though dominated by ambient air temperature, relative humidity, wind speed, and solar radiation all affect heat stress, which can decrease livestock growth, milk production, reproduction rates, and mortality. Indices like the thermal-humidity index (THI) are used to quantify the heat stress experienced from climate variables. Livestock experience differing impacts at different index critical thresholds that are empirically determined and specific to species and breed. This lack of understanding has been highlighted in several studies with a limited knowledge of the critical thresholds of heat stress in native livestock breeds, as well as the current and future impact of heat stress,. As adaptation and mitigation strategies to climate change depend on a solid quantitative foundation, this knowledge gap has limited such efforts. To address the lack of study, we have investigated heat stress impacts in the pastoral system of Sub-Saharan West Africa. We used a stochastic weather generator to quantify both the historic and future variability of heat stress. This approach models temperature, relative humidity, and precipitation, the climate variables controlling heat stress. Incorporating large-scale climate as covariates into this framework provides a better historical fit and allows us to include future CMIP5 GCM projections to examine the climate change impacts on heat stress. Health and production data allow us to examine the influence of this variability on livestock directly, and are considered in conjunction with the confounding impacts of fodder and water access. This understanding provides useful information to decision makers looking to mitigate the impacts of climate change and can provide useful seasonal forecasts of heat stress risk. A comparison of the current and future heat stress conditions based on climate variables for West Africa will be presented, An assessment of current and future risk was obtained by linking climatic heat stress to cattle health and production. Seasonal forecasts of heat stress are also provided by modeling the heat stress climate variables using persistent large-scale climate features.

Climatic Variability Leads to Later Seasonal Flowering of Floridian Plants

PubMed Central

Von Holle, Betsy; Wei, Yun; Nickerson, David

2010-01-01

Understanding species responses to global change will help predict shifts in species distributions as well as aid in conservation. Changes in the timing of seasonal activities of organisms over time may be the most responsive and easily observable indicator of environmental changes associated with global climate change. It is unknown how global climate change will affect species distributions and developmental events in subtropical ecosystems or if climate change will differentially favor nonnative species. Contrary to previously observed trends for earlier flowering onset of plant species with increasing spring temperatures from mid and higher latitudes, we document a trend for delayed seasonal flowering among plants in Florida. Additionally, there were few differences in reproductive responses by native and nonnative species to climatic changes. We argue that plants in Florida have different reproductive cues than those from more northern climates. With global change, minimum temperatures have become more variable within the temperate-subtropical zone that occurs across the peninsula and this variation is strongly associated with delayed flowering among Florida plants. Our data suggest that climate change varies by region and season and is not a simple case of species responding to consistently increasing temperatures across the region. Research on climate change impacts need to be extended outside of the heavily studied higher latitudes to include subtropical and tropical systems in order to properly understand the complexity of regional and seasonal differences of climate change on species responses. PMID:20657765

Modeling the impact of climate variability on diarrhea-associated diseases in Taiwan (1996-2007).

PubMed

Chou, Wei-Chun; Wu, Jiunn-Lin; Wang, Yu-Chun; Huang, Hsin; Sung, Fung-Chang; Chuang, Chun-Yu

2010-12-01

Diarrhea is an important public health problem in Taiwan. Climatic changes and an increase in extreme weather events (extreme heat, drought or rainfalls) have been strongly linked to the incidence of diarrhea-associated disease. This study investigated and quantified the relationship between climate variations and diarrhea-associated morbidity in subtropical Taiwan. Specifically, this study analyzed the local climatic variables and the number of diarrhea-associated infection cases from 1996 to 2007. This study applied a climate variation-guided Poisson regression model to predict the dynamics of diarrhea-associated morbidity. The proposed model allows for climate factors (relative humidity, maximum temperature and the numbers of extreme rainfall), autoregression, long-term trends and seasonality, and a lag-time effect. Results indicated that the maximum temperature and extreme rainfall days were strongly related to diarrhea-associated morbidity. The impact of maximum temperature on diarrhea-associated morbidity appeared primarily among children (0-14years) and older adults (40-64years), and had less of an effect on adults (15-39years). Otherwise, relative humidity and extreme rainfall days significantly contributed to the diarrhea-associated morbidity in adult. This suggested that children and older adults were the most susceptible to diarrhea-associated morbidity caused by climatic variation. Because climatic variation contributed to diarrhea morbidity in Taiwan, it is necessary to develop an early warning system based on the climatic variation information for disease control management. Copyright © 2010 Elsevier B.V. All rights reserved.

Tree ring imprints of long-term changes in climate in western Himalaya, India.

PubMed

Yadav, R R

2009-11-01

Tree-ring analyses from semi-arid to arid regions in western Himalaya show immense potential for developing millennia long climate records. Millennium and longer ring-width chronologies of Himalayan pencil juniper (Juniperus polycarpos), Himalayan pencil cedar (Cedrus deodara) and Chilgoza pine (Pinus gerardiana) have been developed from different sites in western Himalaya. Studies conducted so far on various conifer species indicate strong precipitation signatures in ring-width measurement series. The paucity of weather records from stations close to tree-ring sampling sites poses diffi culty in calibrating tree-ring data against climate data especially precipitation for its strong spatial variability in mountain regions. However, for the existence of strong coherence in temperature, even in data from distant stations, more robust temperature reconstructions representing regional and hemispheric signatures have been developed. Tree-ring records from the region indicate multi-century warm and cool anomalies consistent with the Medieval Warm Period and Little Ice Age anomalies. Signifi cant relationships noted between mean premonsoon temperature over the western Himalaya and ENSO features endorse utility of climate records from western Himalayan region in understanding long-term climate variability and attribution of anthropogenic impact.

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

PubMed

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

2018-04-15

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

A method for screening climate change-sensitive infectious diseases.

PubMed

Wang, Yunjing; Rao, Yuhan; Wu, Xiaoxu; Zhao, Hainan; Chen, Jin

2015-01-14

Climate change is a significant and emerging threat to human health, especially where infectious diseases are involved. Because of the complex interactions between climate variables and infectious disease components (i.e., pathogen, host and transmission environment), systematically and quantitatively screening for infectious diseases that are sensitive to climate change is still a challenge. To address this challenge, we propose a new statistical indicator, Relative Sensitivity, to identify the difference between the sensitivity of the infectious disease to climate variables for two different climate statuses (i.e., historical climate and present climate) in non-exposure and exposure groups. The case study in Anhui Province, China has demonstrated the effectiveness of this Relative Sensitivity indicator. The application results indicate significant sensitivity of many epidemic infectious diseases to climate change in the form of changing climatic variables, such as temperature, precipitation and absolute humidity. As novel evidence, this research shows that absolute humidity has a critical influence on many observed infectious diseases in Anhui Province, including dysentery, hand, foot and mouth disease, hepatitis A, hemorrhagic fever, typhoid fever, malaria, meningitis, influenza and schistosomiasis. Moreover, some infectious diseases are more sensitive to climate change in rural areas than in urban areas. This insight provides guidance for future health inputs that consider spatial variability in response to climate change.

A Method for Screening Climate Change-Sensitive Infectious Diseases

PubMed Central

Wang, Yunjing; Rao, Yuhan; Wu, Xiaoxu; Zhao, Hainan; Chen, Jin

2015-01-01

Climate change is a significant and emerging threat to human health, especially where infectious diseases are involved. Because of the complex interactions between climate variables and infectious disease components (i.e., pathogen, host and transmission environment), systematically and quantitatively screening for infectious diseases that are sensitive to climate change is still a challenge. To address this challenge, we propose a new statistical indicator, Relative Sensitivity, to identify the difference between the sensitivity of the infectious disease to climate variables for two different climate statuses (i.e., historical climate and present climate) in non-exposure and exposure groups. The case study in Anhui Province, China has demonstrated the effectiveness of this Relative Sensitivity indicator. The application results indicate significant sensitivity of many epidemic infectious diseases to climate change in the form of changing climatic variables, such as temperature, precipitation and absolute humidity. As novel evidence, this research shows that absolute humidity has a critical influence on many observed infectious diseases in Anhui Province, including dysentery, hand, foot and mouth disease, hepatitis A, hemorrhagic fever, typhoid fever, malaria, meningitis, influenza and schistosomiasis. Moreover, some infectious diseases are more sensitive to climate change in rural areas than in urban areas. This insight provides guidance for future health inputs that consider spatial variability in response to climate change. PMID:25594780

A Pilot Investigation of the Relationship between Climate Variability and Milk Compounds under the Bootstrap Technique

PubMed Central

Marami Milani, Mohammad Reza; Hense, Andreas; Rahmani, Elham; Ploeger, Angelika

2015-01-01

This study analyzes the linear relationship between climate variables and milk components in Iran by applying bootstrapping to include and assess the uncertainty. The climate parameters, Temperature Humidity Index (THI) and Equivalent Temperature Index (ETI) are computed from the NASA-Modern Era Retrospective-Analysis for Research and Applications (NASA-MERRA) reanalysis (2002–2010). Milk data for fat, protein (measured on fresh matter bases), and milk yield are taken from 936,227 milk records for the same period, using cows fed by natural pasture from April to September. Confidence intervals for the regression model are calculated using the bootstrap technique. This method is applied to the original times series, generating statistically equivalent surrogate samples. As a result, despite the short time data and the related uncertainties, an interesting behavior of the relationships between milk compound and the climate parameters is visible. During spring only, a weak dependency of milk yield and climate variations is obvious, while fat and protein concentrations show reasonable correlations. In summer, milk yield shows a similar level of relationship with ETI, but not with temperature and THI. We suggest this methodology for studies in the field of the impacts of climate change and agriculture, also environment and food with short-term data. PMID:28231215

Seasonal associations of climatic drivers and malaria in the highlands of Ethiopia.

PubMed

Midekisa, Alemayehu; Beyene, Belay; Mihretie, Abere; Bayabil, Estifanos; Wimberly, Michael C

2015-06-24

The impacts of interannual climate fluctuations on vector-borne diseases, especially malaria, have received considerable attention in the scientific literature. These effects can be significant in semi-arid and high-elevation areas such as the highlands of East Africa because cooler temperature and seasonally dry conditions limit malaria transmission. Many previous studies have examined short-term lagged effects of climate on malaria (weeks to months), but fewer have explored the possibility of longer-term seasonal effects. This study assessed the interannual variability of malaria occurrence from 2001 to 2009 in the Amhara region of Ethiopia. We tested for associations of climate variables summarized during the dry (January-April), early transition (May-June), and wet (July-September) seasons with malaria incidence in the early peak (May-July) and late peak (September-December) epidemic seasons using generalized linear models. Climate variables included land surface temperature (LST), rainfall, actual evapotranspiration (ET), and the enhanced vegetation index (EVI). We found that both early and late peak malaria incidence had the strongest associations with meteorological conditions in the preceding dry and early transition seasons. Temperature had the strongest influence in the wetter western districts, whereas moisture variables had the strongest influence in the drier eastern districts. We also found a significant correlation between malaria incidence in the early and the subsquent late peak malaria seasons, and the addition of early peak malaria incidence as a predictor substantially improved models of late peak season malaria in both of the study sub-regions. These findings suggest that climatic effects on malaria prior to the main rainy season can carry over through the rainy season and affect the probability of malaria epidemics during the late malaria peak. The results also emphasize the value of combining environmental monitoring with epidemiological surveillance to develop forecasts of malaria outbreaks, as well as the need for spatially stratified approaches that reflect the differential effects of climatic variations in the different sub-regions.

Simulation of climate change effects on streamflow, groundwater, and stream temperature using GSFLOW and SNTEMP in the Black Earth Creek Watershed, Wisconsin

USGS Publications Warehouse

Hunt, Randall J.; Westenbroek, Stephen M.; Walker, John F.; Selbig, William R.; Regan, R. Steven; Leaf, Andrew T.; Saad, David A.

2016-08-23

Potential future changes in air temperature drivers were consistently upward regardless of General Circulation Model and emission scenario selected; thus, simulated stream temperatures are forecast to increase appreciably with future climate. However, the amount of temperature increase was variable. Such uncertainty is reflected in temperature model results, along with uncertainty in the groundwater/surface-water interaction itself. The estimated increase in annual average temperature ranged from approximately 3 to 6 degrees Celsius by 2100 in the upper reaches of Black Earth Creek and 2 to 4 degrees Celsius in reaches farther downstream. As with all forecasts that rely on projections of an unknowable future, the results are best considered to approximate potential outcomes of climate change given the underlying uncertainty.

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

PubMed

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

2017-09-20

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

Skillful prediction of northern climate provided by the ocean

PubMed Central

Årthun, Marius; Eldevik, Tor; Viste, Ellen; Drange, Helge; Furevik, Tore; Johnson, Helen L.; Keenlyside, Noel S.

2017-01-01

It is commonly understood that a potential for skillful climate prediction resides in the ocean. It nevertheless remains unresolved to what extent variable ocean heat is imprinted on the atmosphere to realize its predictive potential over land. Here we assess from observations whether anomalous heat in the Gulf Stream's northern extension provides predictability of northwestern European and Arctic climate. We show that variations in ocean temperature in the high latitude North Atlantic and Nordic Seas are reflected in the climate of northwestern Europe and in winter Arctic sea ice extent. Statistical regression models show that a significant part of northern climate variability thus can be skillfully predicted up to a decade in advance based on the state of the ocean. Particularly, we predict that Norwegian air temperature will decrease over the coming years, although staying above the long-term (1981–2010) average. Winter Arctic sea ice extent will remain low but with a general increase towards 2020. PMID:28631732

Does climate variability influence the demography of wild primates? Evidence from long-term life-history data in seven species.

PubMed

Campos, Fernando A; Morris, William F; Alberts, Susan C; Altmann, Jeanne; Brockman, Diane K; Cords, Marina; Pusey, Anne; Stoinski, Tara S; Strier, Karen B; Fedigan, Linda M

2017-11-01

Earth's rapidly changing climate creates a growing need to understand how demographic processes in natural populations are affected by climate variability, particularly among organisms threatened by extinction. Long-term, large-scale, and cross-taxon studies of vital rate variation in relation to climate variability can be particularly valuable because they can reveal environmental drivers that affect multiple species over extensive regions. Few such data exist for animals with slow life histories, particularly in the tropics, where climate variation over large-scale space is asynchronous. As our closest relatives, nonhuman primates are especially valuable as a resource to understand the roles of climate variability and climate change in human evolutionary history. Here, we provide the first comprehensive investigation of vital rate variation in relation to climate variability among wild primates. We ask whether primates are sensitive to global changes that are universal (e.g., higher temperature, large-scale climate oscillations) or whether they are more sensitive to global change effects that are local (e.g., more rain in some places), which would complicate predictions of how primates in general will respond to climate change. To address these questions, we use a database of long-term life-history data for natural populations of seven primate species that have been studied for 29-52 years to investigate associations between vital rate variation, local climate variability, and global climate oscillations. Associations between vital rates and climate variability varied among species and depended on the time windows considered, highlighting the importance of temporal scale in detection of such effects. We found strong climate signals in the fertility rates of three species. However, survival, which has a greater impact on population growth, was little affected by climate variability. Thus, we found evidence for demographic buffering of life histories, but also evidence of mechanisms by which climate change could affect the fates of wild primates. © 2017 John Wiley & Sons Ltd.

Evaluation of CMIP5 Ability to Reproduce 20th Century Regional Trends in Surface Air Temperature and Precipitation over CONUS

NASA Astrophysics Data System (ADS)

Lee, J.; Waliser, D. E.; Lee, H.; Loikith, P. C.; Kunkel, K.

2017-12-01

Monitoring temporal changes in key climate variables, such as surface air temperature and precipitation, is an integral part of the ongoing efforts of the United States National Climate Assessment (NCA). Climate models participating in CMIP5 provide future trends for four different emissions scenarios. In order to have confidence in the future projections of surface air temperature and precipitation, it is crucial to evaluate the ability of CMIP5 models to reproduce observed trends for three different time periods (1895-1939, 1940-1979, and 1980-2005). Towards this goal, trends in surface air temperature and precipitation obtained from the NOAA nClimGrid 5 km gridded station observation-based product are compared during all three time periods to the 206 CMIP5 historical simulations from 48 unique GCMs and their multi-model ensemble (MME) for NCA-defined climate regions during summer (JJA) and winter (DJF). This evaluation quantitatively examines the biases of simulated trends of the spatially averaged temperature and precipitation in the NCA climate regions. The CMIP5 MME reproduces historical surface air temperature trends for JJA for all time period and all regions, except the Northern Great Plains from 1895-1939 and Southeast during 1980-2005. Likewise, for DJF, the MME reproduces historical surface air temperature trends across all time periods over all regions except the Southeast from 1895-1939 and the Midwest during 1940-1979. The Regional Climate Model Evaluation System (RCMES), an analysis tool which supports the NCA by providing access to data and tools for regional climate model validation, facilitates the comparisons between the models and observation. The RCMES Toolkit is designed to assist in the analysis of climate variables and the procedure of the evaluation of climate projection models to support the decision-making processes. This tool is used in conjunction with the above analysis and results will be presented to demonstrate its capability to access observation and model datasets, calculate evaluation metrics, and visualize the results. Several other examples of the RCMES capabilities can be found at https://rcmes.jpl.nasa.gov.

The Space-Time Variation of Global Crop Yields, Detecting Simultaneous Outliers and Identifying the Teleconnections with Climatic Patterns

NASA Astrophysics Data System (ADS)

Najafi, E.; Devineni, N.; Pal, I.; Khanbilvardi, R.

2017-12-01

An understanding of the climate factors that influence the space-time variability of crop yields is important for food security purposes and can help us predict global food availability. In this study, we address how the crop yield trends of countries globally were related to each other during the last several decades and the main climatic variables that triggered high/low crop yields simultaneously across the world. Robust Principal Component Analysis (rPCA) is used to identify the primary modes of variation in wheat, maize, sorghum, rice, soybeans, and barley yields. Relations between these modes of variability and important climatic variables, especially anomalous sea surface temperature (SSTa), are examined from 1964 to 2010. rPCA is also used to identify simultaneous outliers in each year, i.e. systematic high/low crop yields across the globe. The results demonstrated spatiotemporal patterns of these crop yields and the climate-related events that caused them as well as the connection of outliers with weather extremes. We find that among climatic variables, SST has had the most impact on creating simultaneous crop yields variability and yield outliers in many countries. An understanding of this phenomenon can benefit global crop trade networks.

Atlas of relations between climatic parameters and distributions of important trees and shrubs in North America: Revisions for all taxa from the United States and Canada and new taxa from the western United States

USGS Publications Warehouse

Thompson, Robert S.; Anderson, Katherine H.; Pelltier, Richard T.; Strickland, Laura E.; Shafer, Sarah L.; Bartlein, Patrick J.; McFadden, Andrew K.

2015-01-01

This volume of the atlas provides numerous changes, updates, and enhancements from previous volumes. Its geographic coverage is now restricted to Canada and the continental United States, and the source and time period of the climatic data have changed. New variables were added, including monthly values for temperature and precipitation, and measures of interannual variability. The distribution maps for all previously published species were redigitized, some distribution maps were revised, and 148 new species were added from the arid and semiarid western United States. The graphical displays were expanded to illustrate the new climatic variables, and the data tables were modified to provide more detail on the population distributions of plant taxa relative to climatic variables.

Climate Inferences From Geothermal Measurements in South America

NASA Astrophysics Data System (ADS)

Gurza Fausto, Edmundo; Harris, Robert; Montenegro, Alvaro; Tassara, Andrés; Beltrami, Hugo

2013-04-01

We present the data and analysis of 26 borehole temperature logs from South America. The dataset consists of a combination of 15 new borehole logs measured during 2012 distributed between three sites in Chile. These sites are located near Vallenar, Sierra Gorda and Sierra Limon Verde. Six temperature logs were measured during 1994 at sites near Michilla, Mansa Mina and the region of El Loa (Springer et al., Tectonophysics, 1998). Four logs were obtained from the NOAA Paleoclimatology Borehole Database located in Villa Staff, Toquepala and Talara in Peru. These data were analyzed for climate variability signals of the surface temperature and changes in the earth's surface energy balance. The analysis suggests regionalized temperature changes in ground surface temperatures with anomalies ranging from -0.1 to -0.3 K for Vallenar, -0.2 to -0.9 K in Sierra Gorda and 0.0 to 0.5 K for Sierra Limon Verde. We place the results within the context of surface air temperature yearly means obtained from existing meteorological and proxy paleoclimatic data between Peru and Northern Chile. The use of geothermal measurements for climate variability studies provides a further understanding of the climatic and energy cycles of the Southern Hemisphere, where meteorological data can be scarce to non-existent. Analysis of borehole temperature data have contributed significantly to estimating the last millennium surface temperature changes. Additionally, recent analysis have contributed to evaluate the Earth's energy balance by providing a quantitative value for the energy absorbed by the continents in the later part of the 20th century. Knowledge of the surface energy flux is important for understanding the solid Earth - atmosphere boundary condition, land cover changes, and their impact on regional and global climate models.

Characterizing Climate Controls on Vegetation Seasonality in the North American Southwest

NASA Astrophysics Data System (ADS)

Fish, M. A.; Cook, B.; Smerdon, J. E.; Seager, R.; Williams, P.

2014-12-01

The North American Southwest, which extends from Colorado to southern Mexico and California to eastern Texas, encompasses a diversity of climates, elevations, and ecosystems. This region is expected to experience significant climatic change, and associated impacts, in the coming decades. To better understand the spatiotemporal variability of vegetation in the Southwest and the expected climatic controls on timing and spatial extend of vegetation growth, we compared GIMMS normalized difference vegetation index (NDVI, 1981-2011) against temperature and precipitation data. Spatial variations in vegetation seasonality and the timing of peak NDVI are linked to spatial variability in the precipitation regimes across the Southwest. Regions with spring NDVI peaks are dominated by winter precipitation, while late summer and fall peaks are in regions with significant summer precipitation driven by the North American Monsoon. Inter-annual variability in peak NDVI is positively correlated with precipitation and negatively correlated with temperature, with the largest correlation coefficients at one-month lags. The only significant long-term trends in NDVI are for northern Mexico, where agricultural productivity has been increasing over the last 30 years.

Trends and Controls of inter-annual Variability in the Carbon Budget of Terrestrial Ecosystems

NASA Astrophysics Data System (ADS)

Cescatti, A.; Marcolla, B.

2014-12-01

The climate sensitivity of the terrestrial carbon budget will substantially affect the sign and strength of the land-climate feedbacks and the future climate trajectories. Current trends in the inter-annual variability of terrestrial carbon fluxes (IAV) may contribute to clarify the relative role of physical and biological controls of ecosystem responses to climate change. For this purpose we investigated how recent climate variability has impacted the carbon fluxes at long-term FLUXNET sites. Using a novel method, the IAV has been factored out in climate induced variability (physical control), variability due to changes in ecosystem functioning (biological control) and the interaction of the two terms. The relative control of the main climatic drivers (temperature, water availability) on the physical and biological sources of IAV has been investigated using both site level fluxes and global gridded products generated from the up-scaling of flux data. Results of this analysis highlight the fundamental role of precipitation trends on the pattern of IAV in the last 30 years. Our findings on the spatial/temporal trends of IAV have been finally confirmed using the signal derived from the global network of atmospheric CO2 concentrations measurements.

Tracking of climatic niche boundaries under recent climate change.

PubMed

La Sorte, Frank A; Jetz, Walter

2012-07-01

1. Global climate has changed significantly during the past 30 years and especially in northern temperate regions which have experienced poleward shifts in temperature regimes. While there is evidence that some species have responded by moving their distributions to higher latitudes, the efficiency of this response in tracking species' climatic niche boundaries over time has yet to be addressed. 2. Here, we provide a continental assessment of the temporal structure of species responses to recent spatial shifts in climatic conditions. We examined geographic associations with minimum winter temperature for 59 species of winter avifauna at 476 Christmas Bird Count circles in North America from 1975 to 2009 under three sampling schemes that account for spatial and temporal sampling effects. 3. Minimum winter temperature associated with species occurrences showed an overall increase with a weakening trend after 1998. Species displayed highly variable responses that, on average and across sampling schemes, contained a strong lag effect that weakened in strength over time. In general, the conservation of minimum winter temperature was relevant when all species were considered together but only after an initial lag period (c. 35 years) was overcome. The delayed niche tracking observed at the combined species level was likely supported by the post1998 lull in the warming trend. 4. There are limited geographic and ecological explanations for the observed variability, suggesting that the efficiency of species' responses under climate change is likely to be highly idiosyncratic and difficult to predict. This outcome is likely to be even more pronounced and time lags more persistent for less vagile taxa, particularly during the periods of consistent or accelerating warming. Current modelling efforts and conservation strategies need to better appreciate the variation, strength and duration of lag effects and their association with climatic variability. Conservation strategies in particular will benefit through identifying and maintaining dispersal corridors that accommodate diverging dispersal strategies and timetables. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.

Effects of changes in climate variability and extremes on the exceedance of critical algal bloom thresholds

NASA Astrophysics Data System (ADS)

Hecht, J. S.; Zia, A.; Beckage, B.; Winter, J.; Schroth, A. W.; Bomblies, A.; Clemins, P. J.; Rizzo, D. M.

2017-12-01

Identifying critical thresholds associated with algal blooms in freshwater lakes is important for avoiding persistent eutrophic conditions and their undesirable ecological, recreational and drinking water impacts. Recent Integrated Assessment Model (IAM) and Bayesian network studies have demonstrated that future climatic changes could increase the duration and intensity of these blooms. Yet, few studies have systematically examined the sensitivity of algal blooms to projected changes in precipitation and temperature variability and extremes at storm-event to seasonal timescales. We employ an IAM, which couples downscaled Global Climate Model (GCM) output with hydrologic and water quality models, to examine the sensitivity of algal blooms in Lake Champlain's shallow Missisquoi Bay to potential future climate changes. We first identify a set of statistically downscaled GCMs from the Coupled Model Intercomparison Project Phase 5 (CMIP5) that reproduce recent historical daily temperature and precipitation observations well in the Lake Champlain basin. Then, we identify plausible covarying changes in the (i) mean and variance of seasonal precipitation and temperature distributions and (ii) frequency and magnitude of individual storm events. We assess the response of water quality indicators (e.g. chlorophyll a concentrations, Trophic State Index) and societal impacts to sequences of daily meteorological series generated from distributions that account for these covarying changes. We also discuss strategies for examining the sensitivity of bloom impacts to different weather sequences generated from a single set of precipitation and temperature distributions with a limited number of computationally intensive IAM simulations. We then evaluate the implications of modeling these changes in climate variability and extreme precipitation events for nutrient management. Finally, we consider the generalizability of our findings for water bodies with different physical and climatic characteristics and address the extent to which climate-driven alterations to terrestrial hydrologic processes, such as evapotranspiration and soil moisture storage, mediate changes to lake water quality.

Potential impacts of climate variability on respiratory morbidity in children, infants, and adults.

PubMed

Souza, Amaury de; Fernandes, Widinei Alves; Pavão, Hamilton Germano; Lastoria, Giancarlo; Albrez, Edilce do Amaral

2012-01-01

To determine whether climate variability influences the number of hospitalizations for respiratory diseases in infants, children, and adults in the city of Campo Grande, Brazil. We used daily data on admissions for respiratory diseases, precipitation, air temperature, humidity, and wind speed for the 2004-2008 period. We calculated the thermal comfort index, effective temperature, and effective temperature with wind speed (wind-chill or heat index) using the meteorological data obtained. Generalized linear models, with Poisson multiple regression, were used in order to predict hospitalizations for respiratory disease. The variables studied were (collectively) found to show relatively high correlation coefficients in relation to hospital admission for pneumonia in children (R² = 68.4%), infants (R² = 71.8%), and adults (R² = 81.8%). Our results indicate a quantitative risk for an increase in the number of hospitalizations of children, infants, and adults, according to the increase or decrease in temperature, humidity, precipitation, wind speed, and thermal comfort index in the city under study.

Association of Seasonal Climate Variability and Age-Specific Mortality in Northern Sweden before the Onset of Industrialization

PubMed Central

Rocklöv, Joacim; Edvinsson, Sören; Arnqvist, Per; de Luna, Sara Sjöstedt; Schumann, Barbara

2014-01-01

Background and aims: Little is known about health impacts of climate in pre-industrial societies. We used historical data to investigate the association of temperature and precipitation with total and age-specific mortality in Skellefteå, northern Sweden, between 1749 and 1859. Methods: We retrieved digitized aggregated population data of the Skellefteå parish, and monthly temperature and precipitation measures. A generalized linear model was established for year to year variability in deaths by annual and seasonal average temperature and cumulative precipitation using a negative binomial function, accounting for long-term trends in population size. The final full model included temperature and precipitation of all four seasons simultaneously. Relative risks (RR) with 95% confidence intervals (CI) were calculated for total, sex- and age-specific mortality. Results: In the full model, only autumn precipitation proved statistically significant (RR 1.02; CI 1.00–1.03, per 1cm increase of autumn precipitation), while winter temperature (RR 0.98; CI 0.95–1.00, per 1 °C increase in temperature) and spring precipitation (RR 0.98; CI 0.97–1.00 per 1 cm increase in precipitation) approached significance. Similar effects were observed for men and women. The impact of climate variability on mortality was strongest in children aged 3–9, and partly also in older children. Infants, on the other hand, appeared to be less affected by unfavourable climate conditions. Conclusions: In this pre-industrial rural region in northern Sweden, higher levels of rain during the autumn increased the annual number of deaths. Harvest quality might be one critical factor in the causal pathway, affecting nutritional status and susceptibility to infectious diseases. Autumn rain probably also contributed to the spread of air-borne diseases in crowded living conditions. Children beyond infancy appeared most vulnerable to climate impacts. PMID:25003551

Malaria transmission in two localities in north-western Argentina

PubMed Central

Dantur Juri, María J; Zaidenberg, Mario; Claps, Guillermo L; Santana, Mirta; Almirón, Walter R

2009-01-01

Background Malaria is one of the most important tropical diseases that affects people globally. The influence of environmental conditions in the patterns of temporal distribution of malaria vectors and the disease has been studied in different countries. In the present study, ecological aspects of the malaria vector Anopheles (Anopheles) pseudopunctipennis and their relationship with climatic variables, as well as the seasonality of malaria cases, were studied in two localities, El Oculto and Aguas Blancas, in north-western Argentina. Methods The fluctuation of An. pseudopunctipennis and the malaria cases distribution was analysed with Random Effect Poisson Regression. This analysis takes into account the effect of each climatic variable on the abundance of both vector and malaria cases, giving as results predicted values named Incidence Rate Radio. Results The number of specimens collected in El Oculto and Aguas Blancas was 4224 (88.07%) and 572 (11.93%), respectively. In El Oculto no marked seasonality was found, different from Aguas Blancas, where high abundance was detected at the end of spring and the beginning of summer. The maximum mean temperature affected the An. pseudopunctipennis fluctuation in El Oculto and Aguas Blancas. When considering the relationship between the number of malaria cases and the climatic variables in El Oculto, maximum mean temperature and accumulated rainfall were significant, in contrast with Aguas Blancas, where mean temperature and humidity showed a closer relationship to the fluctuation in the disease. Conclusion The temporal distribution patterns of An. pseudopunctipennis vary in both localities, but spring appears as the season with better conditions for mosquito development. Maximum mean temperature was the most important variable in both localities. Malaria cases were influenced by the maximum mean temperature in El Oculto, while the mean temperature and humidity were significant in Aguas Blancas. In Aguas Blancas peaks of mosquito abundance and three months later, peaks of malaria cases were observed. The study reported here will help to increase knowledge about not only vectors and malaria seasonality but also their relationships with the climatic variables that influence their appearances and abundances. PMID:19152707

Social vulnerability and climate variability in southern Brazil: a TerraPop case study

NASA Astrophysics Data System (ADS)

Adamo, S. B.; Fitch, C. A.; Kugler, T.; Doxsey-Whitfield, E.

2014-12-01

Climate variability is an inherent characteristic of the Earth's climate, including but not limited to climate change. It affects and impacts human society in different ways, depending on the underlying socioeconomic vulnerability of specific places, social groups, households and individuals. This differential vulnerability presents spatial and temporal variations, and is rooted in historical patterns of development and relations between human and ecological systems. This study aims to assess the impact of climate variability on livelihoods and well-being, as well as their changes over time and across space, and for rural and urban populations. The geographic focus is Southern Brazil-the states of Parana, Santa Catarina and Rio Grande do Sul-- and the objectives include (a) to identify and map critical areas or hotspots of exposure to climate variability (temperature and precipitation), and (b) to identify internal variation or differential vulnerability within these areas and its evolution over time (1980-2010), using newly available integrated data from the Terra Populus project. These data include geo-referenced climate and agricultural data, and data describing demographic and socioeconomic characteristics of individuals, households and places.

How will species respond to climate change? Examining the effects of temperature and population density on an herbivorous insect.

PubMed

Laws, Angela Nardoni; Belovsky, Gary E

2010-04-01

An important challenge facing ecologists is to understand how climate change may affect species performance and species interactions. However, predicting how changes in abiotic variables associated with climate change may affect species performance also depends on the biotic context, which can mediate species responses to climatic change. We conducted a 3-yr field experiment to determine how the herbivorous grasshopper Camnula pellucida (Scudder) responds to manipulations of temperature and population density. Grasshopper survival and fecundity decreased with density, indicating the importance of intraspecific competition. Female fecundity tended to increase with temperature, whereas grasshopper survival exhibited a unimodal response to temperature, with highest survival at intermediate temperatures. Grasshopper performance responses to temperature also depended on density. Peak survival in the low-density treatment occurred in warmer conditions than for the high-density treatment, indicating that the intensity of intraspecific competition varies with temperature. Our data show that changes to the temperature regimen can alter grasshopper performance and determine the intensity of intraspecific competition. However, the effects of temperature on grasshopper performance varied with density. Our data indicate the importance of the biotic context in mediating species responses to climatic factors associated with global change.

Regional cooling caused recent New Zealand glacier advances in a period of global warming.

PubMed

Mackintosh, Andrew N; Anderson, Brian M; Lorrey, Andrew M; Renwick, James A; Frei, Prisco; Dean, Sam M

2017-02-14

Glaciers experienced worldwide retreat during the twentieth and early twenty first centuries, and the negative trend in global glacier mass balance since the early 1990s is predominantly a response to anthropogenic climate warming. The exceptional terminus advance of some glaciers during recent global warming is thought to relate to locally specific climate conditions, such as increased precipitation. In New Zealand, at least 58 glaciers advanced between 1983 and 2008, and Franz Josef and Fox glaciers advanced nearly continuously during this time. Here we show that the glacier advance phase resulted predominantly from discrete periods of reduced air temperature, rather than increased precipitation. The lower temperatures were associated with anomalous southerly winds and low sea surface temperature in the Tasman Sea region. These conditions result from variability in the structure of the extratropical atmospheric circulation over the South Pacific. While this sequence of climate variability and its effect on New Zealand glaciers is unusual on a global scale, it remains consistent with a climate system that is being modified by humans.

Regional cooling caused recent New Zealand glacier advances in a period of global warming

NASA Astrophysics Data System (ADS)

Mackintosh, Andrew N.; Anderson, Brian M.; Lorrey, Andrew M.; Renwick, James A.; Frei, Prisco; Dean, Sam M.

2017-02-01

Glaciers experienced worldwide retreat during the twentieth and early twenty first centuries, and the negative trend in global glacier mass balance since the early 1990s is predominantly a response to anthropogenic climate warming. The exceptional terminus advance of some glaciers during recent global warming is thought to relate to locally specific climate conditions, such as increased precipitation. In New Zealand, at least 58 glaciers advanced between 1983 and 2008, and Franz Josef and Fox glaciers advanced nearly continuously during this time. Here we show that the glacier advance phase resulted predominantly from discrete periods of reduced air temperature, rather than increased precipitation. The lower temperatures were associated with anomalous southerly winds and low sea surface temperature in the Tasman Sea region. These conditions result from variability in the structure of the extratropical atmospheric circulation over the South Pacific. While this sequence of climate variability and its effect on New Zealand glaciers is unusual on a global scale, it remains consistent with a climate system that is being modified by humans.

Regional cooling caused recent New Zealand glacier advances in a period of global warming

PubMed Central

Mackintosh, Andrew N.; Anderson, Brian M.; Lorrey, Andrew M.; Renwick, James A.; Frei, Prisco; Dean, Sam M.

2017-01-01

Glaciers experienced worldwide retreat during the twentieth and early twenty first centuries, and the negative trend in global glacier mass balance since the early 1990s is predominantly a response to anthropogenic climate warming. The exceptional terminus advance of some glaciers during recent global warming is thought to relate to locally specific climate conditions, such as increased precipitation. In New Zealand, at least 58 glaciers advanced between 1983 and 2008, and Franz Josef and Fox glaciers advanced nearly continuously during this time. Here we show that the glacier advance phase resulted predominantly from discrete periods of reduced air temperature, rather than increased precipitation. The lower temperatures were associated with anomalous southerly winds and low sea surface temperature in the Tasman Sea region. These conditions result from variability in the structure of the extratropical atmospheric circulation over the South Pacific. While this sequence of climate variability and its effect on New Zealand glaciers is unusual on a global scale, it remains consistent with a climate system that is being modified by humans. PMID:28195582

Applying Multimodel Ensemble from Regional Climate Models for Improving Runoff Projections on Semiarid Regions of Spain

NASA Astrophysics Data System (ADS)

Garcia Galiano, S. G.; Olmos, P.; Giraldo Osorio, J. D.

2015-12-01

In the Mediterranean area, significant changes on temperature and precipitation are expected throughout the century. These trends could exacerbate the existing conditions in regions already vulnerable to climatic variability, reducing the water availability. Improving knowledge about plausible impacts of climate change on water cycle processes at basin scale, is an important step for building adaptive capacity to the impacts in this region, where severe water shortages are expected for the next decades. RCMs ensemble in combination with distributed hydrological models with few parameters, constitutes a valid and robust methodology to increase the reliability of climate and hydrological projections. For reaching this objective, a novel methodology for building Regional Climate Models (RCMs) ensembles of meteorological variables (rainfall an temperatures), was applied. RCMs ensembles are justified for increasing the reliability of climate and hydrological projections. The evaluation of RCMs goodness-of-fit to build the ensemble is based on empirical probability density functions (PDF) extracted from both RCMs dataset and a highly resolution gridded observational dataset, for the time period 1961-1990. The applied method is considering the seasonal and annual variability of the rainfall and temperatures. The RCMs ensembles constitute the input to a distributed hydrological model at basin scale, for assessing the runoff projections. The selected hydrological model is presenting few parameters in order to reduce the uncertainties involved. The study basin corresponds to a head basin of Segura River Basin, located in the South East of Spain. The impacts on runoff and its trend from observational dataset and climate projections, were assessed. Considering the control period 1961-1990, plausible significant decreases in runoff for the time period 2021-2050, were identified.

Climatic variability in Princess Elizabeth Land (East Antarctica) over the last 350 years

NASA Astrophysics Data System (ADS)

Ekaykin, Alexey A.; Vladimirova, Diana O.; Lipenkov, Vladimir Y.; Masson-Delmotte, Valérie

2017-01-01

We use isotopic composition (δD) data from six sites in Princess Elizabeth Land (PEL) in order to reconstruct air temperature variability in this sector of East Antarctica over the last 350 years. First, we use the present-day instrumental mean annual surface air temperature data to demonstrate that the studied region (between Russia's Progress, Vostok and Mirny research stations) is characterized by uniform temperature variability. We thus construct a stacked record of the temperature anomaly for the whole sector for the period of 1958-2015. A comparison of this series with the Southern Hemisphere climatic indices shows that the short-term inter-annual temperature variability is primarily governed by the Antarctic Oscillation (AAO) and Interdecadal Pacific Oscillation (IPO) modes of atmospheric variability. However, the low-frequency temperature variability (with period > 27 years) is mainly related to the anomalies of the Indian Ocean Dipole (IOD) mode. We then construct a stacked record of δD for the PEL for the period of 1654-2009 from individual normalized and filtered isotopic records obtained at six different sites (PEL2016 stacked record). We use a linear regression of this record and the stacked PEL temperature record (with an apparent slope of 9 ± 5.4 ‰ °C-1) to convert PEL2016 into a temperature scale. Analysis of PEL2016 shows a 1 ± 0.6 °C warming in this region over the last 3 centuries, with a particularly cold period from the mid-18th to the mid-19th century. A peak of cooling occurred in the 1840s - a feature previously observed in other Antarctic records. We reveal that PEL2016 correlates with a low-frequency component of IOD and suggest that the IOD mode influences the Antarctic climate by modulating the activity of cyclones that bring heat and moisture to Antarctica. We also compare PEL2016 with other Antarctic stacked isotopic records. This work is a contribution to the PAGES (Past Global Changes) and IPICS (International Partnerships in Ice Core Sciences) Antarctica 2k projects.

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

PubMed

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

2013-03-26

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

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

PubMed Central

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

2013-01-01

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

Decadal climate prediction with a refined anomaly initialisation approach

NASA Astrophysics Data System (ADS)

Volpi, Danila; Guemas, Virginie; Doblas-Reyes, Francisco J.; Hawkins, Ed; Nichols, Nancy K.

2017-03-01

In decadal prediction, the objective is to exploit both the sources of predictability from the external radiative forcings and from the internal variability to provide the best possible climate information for the next decade. Predicting the climate system internal variability relies on initialising the climate model from observational estimates. We present a refined method of anomaly initialisation (AI) applied to the ocean and sea ice components of the global climate forecast model EC-Earth, with the following key innovations: (1) the use of a weight applied to the observed anomalies, in order to avoid the risk of introducing anomalies recorded in the observed climate, whose amplitude does not fit in the range of the internal variability generated by the model; (2) the AI of the ocean density, instead of calculating it from the anomaly initialised state of temperature and salinity. An experiment initialised with this refined AI method has been compared with a full field and standard AI experiment. Results show that the use of such refinements enhances the surface temperature skill over part of the North and South Atlantic, part of the South Pacific and the Mediterranean Sea for the first forecast year. However, part of such improvement is lost in the following forecast years. For the tropical Pacific surface temperature, the full field initialised experiment performs the best. The prediction of the Arctic sea-ice volume is improved by the refined AI method for the first three forecast years and the skill of the Atlantic multidecadal oscillation is significantly increased compared to a non-initialised forecast, along the whole forecast time.

The role of environmental variables on Aedes albopictus biology and chikungunya epidemiology

PubMed Central

Waldock, Joanna; Chandra, Nastassya L; Lelieveld, Jos; Proestos, Yiannis; Michael, Edwin; Christophides, George; Parham, Paul E

2013-01-01

Aedes albopictus is a vector of dengue and chikungunya viruses in the field, along with around 24 additional arboviruses under laboratory conditions. As an invasive mosquito species, Ae. albopictus has been expanding in geographical range over the past 20 years, although the poleward extent of mosquito populations is limited by winter temperatures. Nonetheless, population densities depend on environmental conditions and since global climate change projections indicate increasing temperatures and altered patterns of rainfall, geographic distributions of previously tropical mosquito species may change. Although mathematical models can provide explanatory insight into observed patterns of disease prevalence in terms of epidemiological and entomological processes, understanding how environmental variables affect transmission is possible only with reliable model parameterisation, which, in turn, is obtained only through a thorough understanding of the relationship between mosquito biology and environmental variables. Thus, in order to assess the impact of climate change on mosquito population distribution and regions threatened by vector-borne disease, a detailed understanding (through a synthesis of current knowledge) of the relationship between climate, mosquito biology, and disease transmission is required, but this process has not yet been undertaken for Ae. albopictus. In this review, the impact of temperature, rainfall, and relative humidity on Ae. albopictus development and survival are considered. Existing Ae. albopictus populations across Europe are mapped with current climatic conditions, considering whether estimates of climatic cutoffs for Ae. albopictus are accurate, and suggesting that environmental thresholds must be calibrated according to the scale and resolution of climate model outputs and mosquito presence data. PMID:23916332

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

A Skilful Marine Sclerochronological Network Based Reconstruction of North Atlantic Subpolar Gyre Dynamics

NASA Astrophysics Data System (ADS)

Reynolds, D.; Hall, I. R.; Slater, S. M.; Scourse, J. D.; Wanamaker, A. D.; Halloran, P. R.; Garry, F. K.

2017-12-01

Spatial network analyses of precisely dated, and annually resolved, tree-ring proxy records have facilitated robust reconstructions of past atmospheric climate variability and the associated mechanisms and forcings that drive it. In contrast, a lack of similarly dated marine archives has constrained the use of such techniques in the marine realm, despite the potential for developing a more robust understanding of the role basin scale ocean dynamics play in the global climate system. Here we show that a spatial network of marine molluscan sclerochronological oxygen isotope (δ18Oshell) series spanning the North Atlantic region provides a skilful reconstruction of basin scale North Atlantic sea surface temperatures (SSTs). Our analyses demonstrate that the composite marine series (referred to as δ18Oproxy_PC1) is significantly sensitive to inter-annual variability in North Atlantic SSTs (R=-0.61 P<0.01) and surface air temperatures (SATs; R=-0.67, P<0.01) over the 20th century. Subpolar gyre (SPG) SSTs dominates variability in the δ18Oproxy_PC1 series at sub-centennial frequencies (R=-0.51, P<0.01). Comparison of the δ18Oproxy_PC1 series against variability in the strength of the European Slope Current and maximum North Atlantic meridional overturning circulation derived from numeric climate models (CMIP5), indicates that variability in the SPG region, associated with the strength of the surface currents of the North Atlantic, are playing a significant role in shaping the multi-decadal scale SST variability over the industrial era. These analyses demonstrate that spatial networks developed from sclerochronological archives can provide powerful baseline archives of past ocean variability that can facilitate the development of a quantitative understanding for the role the oceans play in the global climate systems and constraining uncertainties in numeric climate models.

Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble

USGS Publications Warehouse

Lorenz, Ruth; Argueso, Daniel; Donat, Markus G.; Pitman, Andrew J.; van den Hurk, Bart; Berg, Alexis; Lawrence, David M.; Cheruy, Frederique; Ducharne, Agnes; Hagemann, Stefan; Meier, Arndt; Milly, Paul C.D.; Seneviratne, Sonia I

2016-01-01

We examine how soil moisture variability and trends affect the simulation of temperature and precipitation extremes in six global climate models using the experimental protocol of the Global Land-Atmosphere Coupling Experiment of the Coupled Model Intercomparison Project, Phase 5 (GLACE-CMIP5). This protocol enables separate examinations of the influences of soil moisture variability and trends on the intensity, frequency, and duration of climate extremes by the end of the 21st century under a business-as-usual (Representative Concentration Pathway 8.5) emission scenario. Removing soil moisture variability significantly reduces temperature extremes over most continental surfaces, while wet precipitation extremes are enhanced in the tropics. Projected drying trends in soil moisture lead to increases in intensity, frequency, and duration of temperature extremes by the end of the 21st century. Wet precipitation extremes are decreased in the tropics with soil moisture trends in the simulations, while dry extremes are enhanced in some regions, in particular the Mediterranean and Australia. However, the ensemble results mask considerable differences in the soil moisture trends simulated by the six climate models. We find that the large differences between the models in soil moisture trends, which are related to an unknown combination of differences in atmospheric forcing (precipitation, net radiation), flux partitioning at the land surface, and how soil moisture is parameterized, imply considerable uncertainty in future changes in climate extremes.

Millennial-scale variability during the last glacial in vegetation records from North America

USGS Publications Warehouse

Jiménez-Moreno, Gonzalo; Anderson, R. Scott; Desprat, S.; Grigg, L.D.; Grimm, E.C.; Heusser, L.E.; Jacobs, Brian F.; Lopez-Martinez, C.; Whitlock, C.L.; Willard, D.A.

2010-01-01

High-resolution pollen records from North America show that terrestrial environments were affected by Dansgaard-Oeschger (D-O) and Heinrich climate variability during the last glacial. In the western, more mountainous regions, these climate changes are generally observed in the pollen records as altitudinal movements of climate-sensitive plant species, whereas in the southeast, they are recorded as latitudinal shifts in vegetation. Heinrich (HS) and Greenland (GS) stadials are generally correlated with cold and dry climate and Greenland interstadials (GI) with warm-wet phases. The pollen records from North America confirm that vegetation responds rapidly to millennial-scale climate variability, although the difficulties in establishing independent age models for the pollen records make determination of the absolute phasing of the records to surface temperatures in Greenland somewhat uncertain. ?? 2009 Elsevier Ltd.

A monthly global paleo-reanalysis of the atmosphere from 1600 to 2005 for studying past climatic variations

PubMed Central

Franke, Jörg; Brönnimann, Stefan; Bhend, Jonas; Brugnara, Yuri

2017-01-01

Climatic variations at decadal scales such as phases of accelerated warming or weak monsoons have profound effects on society and economy. Studying these variations requires insights from the past. However, most current reconstructions provide either time series or fields of regional surface climate, which limit our understanding of the underlying dynamics. Here, we present the first monthly paleo-reanalysis covering the period 1600 to 2005. Over land, instrumental temperature and surface pressure observations, temperature indices derived from historical documents and climate sensitive tree-ring measurements were assimilated into an atmospheric general circulation model ensemble using a Kalman filtering technique. This data set combines the advantage of traditional reconstruction methods of being as close as possible to observations with the advantage of climate models of being physically consistent and having 3-dimensional information about the state of the atmosphere for various variables and at all points in time. In contrast to most statistical reconstructions, centennial variability stems from the climate model and its forcings, no stationarity assumptions are made and error estimates are provided. PMID:28585926

Solar variability: Implications for global change

NASA Technical Reports Server (NTRS)

Lean, Judith; Rind, David

1994-01-01

Solar variability is examined in search of implications for global change. The topics covered include the following: solar variation modification of global surface temperature; the significance of solar variability with respect to future climate change; and methods of reducing the uncertainty of the potential amplitude of solar variability on longer time scales.

Climate controls on streamflow variability in the Missouri River Basin

NASA Astrophysics Data System (ADS)

Wise, E.; Woodhouse, C. A.; McCabe, G. J., Jr.; Pederson, G. T.; St-Jacques, J. M.

2017-12-01

The Missouri River's hydroclimatic variability presents a challenge for water managers, who must balance many competing demands on the system. Water resources in the Missouri River Basin (MRB) have increasingly been challenged by the droughts and floods that have occurred over the past several decades and the potential future exacerbation of these extremes by climate change. Here, we use observed and modeled hydroclimatic data and estimated natural flow records to describe the climatic controls on streamflow in the upper and lower portions of the MRB, examine atmospheric and oceanic patterns associated with high- and low-flow years, and investigate trends in climate and streamflow over the instrumental period. Results indicate that the two main source regions for total outflow, in the uppermost and lowermost parts of the basin, are under the influence of very different sets of climatic controls. Winter precipitation, impacted by changes in zonal versus meridional flow from the Pacific Ocean, as well as spring precipitation and temperature, play a key role in surface water supply variability in the upper basin. Lower basin flow is significantly correlated with precipitation in late spring and early summer, indicative of Atlantic-influenced circulation variability affecting the flow of moisture from the Gulf of Mexico. The upper basin, with decreasing snowpack and streamflow and warming spring temperatures, will be less likely to provide important flow supplements to the lower basin in the future.

Seasonality of Influenza and Respiratory Syncytial Viruses and the Effect of Climate Factors in Subtropical-Tropical Asia Using Influenza-Like Illness Surveillance Data, 2010 -2012.

PubMed

Kamigaki, Taro; Chaw, Liling; Tan, Alvin G; Tamaki, Raita; Alday, Portia P; Javier, Jenaline B; Olveda, Remigio M; Oshitani, Hitoshi; Tallo, Veronica L

2016-01-01

The seasonality of influenza and respiratory syncytial virus (RSV) is well known, and many analyses have been conducted in temperate countries; however, this is still not well understood in tropical countries. Previous studies suggest that climate factors are involved in the seasonality of these viruses. However, the extent of the effect of each climate variable is yet to be defined. We investigated the pattern of seasonality and the effect of climate variables on influenza and RSV at three sites of different latitudes: the Eastern Visayas region and Baguio City in the Philippines, and Okinawa Prefecture in Japan. Wavelet analysis and the dynamic linear regression model were applied. Climate variables used in the analysis included mean temperature, relative and specific humidity, precipitation, and number of rainy days. The Akaike Information Criterion estimated in each model was used to test the improvement of fit in comparison with the baseline model. At all three study sites, annual seasonal peaks were observed in influenza A and RSV; peaks were unclear for influenza B. Ranges of climate variables at the two Philippine sites were narrower and mean variables were significantly different among the three sites. Whereas all climate variables except the number of rainy days improved model fit to the local trend model, their contributions were modest. Mean temperature and specific humidity were positively associated with influenza and RSV at the Philippine sites and negatively associated with influenza A in Okinawa. Precipitation also improved model fit for influenza and RSV at both Philippine sites, except for the influenza A model in the Eastern Visayas. Annual seasonal peaks were observed for influenza A and RSV but were less clear for influenza B at all three study sites. Including additional data from subsequent more years would help to ascertain these findings. Annual amplitude and variation in climate variables are more important than their absolute values for determining their effect on the seasonality of influenza and RSV.

Analyzing the responses of species assemblages to climate change across the Great Basin, USA.

NASA Astrophysics Data System (ADS)

Henareh Khalyani, A.; Falkowski, M. J.; Crookston, N.; Yousef, F.

2016-12-01

The potential impacts of climate change on the future distribution of tree species in not well understood. Climate driven changes in tree species distribution could cause significant changes in realized species niches, potentially resulting in the loss of ecotonal species as well as the formation on novel assemblages of overlapping tree species. In an effort to gain a better understating of how the geographic distribution of tree species may respond to climate change, we model the potential future distribution of 50 different tree species across 70 million ha in the Great Basin, USA. This is achieved by leveraging a species realized niche model based on non-parametric analysis of species occurrences across climatic, topographic, and edaphic variables. Spatially explicit, high spatial resolution (30 m) climate variables (e.g., precipitation, and minimum, maximum, and mean temperature) and associated climate indices were generated on an annual basis between 1981-2010 by integrating climate station data with digital elevation data (Shuttle Radar Topographic Mission (SRTM) data) in a thin plate spline interpolation algorithm (ANUSPLIN). Bioclimate models of species niches in in the cotemporary period and three following 30 year periods were then generated by integrating the climate variables, soil data, and CMIP 5 general circulation model projections. Our results suggest that local scale contemporary variations in species realized niches across space are influenced by edaphic and topographic variables as well as climatic variables. The local variability in soil properties and topographic variability across space also affect the species responses to climate change through time and potential formation of species assemblages in future. The results presented here in will aid in the development of adaptive forest management techniques aimed at mitigating negative impacts of climate change on forest composition, structure, and function.

The Nature of Antarctic Temperature Change

NASA Astrophysics Data System (ADS)

Markle, B. R.; Steig, E. J.

2017-12-01

The Antarctic is an important component of global climate. While the Arctic has warmed significantly in the last century, the Antarctic as a whole has shown considerably less variability. There is, however, a pronounced spatial pattern to modern Antarctic temperature change. The high East Antarctic Ice Sheet shows little to no warming over recent decades while West Antarctica and the Peninsula shows some of the largest rates of warming on the globe. Examining past climate variability can help reveal the physical processes governing this spatial pattern of Antarctic temperature change. Modern Antarctic temperature variability is known from satellite and weather station observations. Understanding changes in the past, however, requires paleoclimate-proxies such as ice-core water-isotope records. Here we assess the spatial pattern of Antarctic temperature changes across a range of timescales, from modern decadal changes to millennial and orbital-scale variability. We reconstruct past changes in absolute temperatures from a suite of deep ice core records and an improved isotope-temperature reconstruction method. We use δ18O and deuterium excess records to reconstruct both evaporation source and condensation site temperatures. In contrast to previous studies we use a novel method that accounts for nonlinearities in the water-isotope distillation process. We quantify past temperature changes over the Southern Ocean and Antarctic Continent and the magnitude of polar amplification. We identify patterns of Antarctic temperature change that are common across a wide range of timescales and independent of the source of forcing. We examine the nature of these changes and their relationship to atmospheric thermodynamics.

Impacts of Soil-aquifer Heat and Water Fluxes on Simulated Global Climate

NASA Technical Reports Server (NTRS)

Krakauer, N.Y.; Puma, Michael J.; Cook, B. I.

2013-01-01

Climate models have traditionally only represented heat and water fluxes within relatively shallow soil layers, but there is increasing interest in the possible role of heat and water exchanges with the deeper subsurface. Here, we integrate an idealized 50m deep aquifer into the land surface module of the GISS ModelE general circulation model to test the influence of aquifer-soil moisture and heat exchanges on climate variables. We evaluate the impact on the modeled climate of aquifer-soil heat and water fluxes separately, as well as in combination. The addition of the aquifer to ModelE has limited impact on annual-mean climate, with little change in global mean land temperature, precipitation, or evaporation. The seasonal amplitude of deep soil temperature is strongly damped by the soil-aquifer heat flux. This not only improves the model representation of permafrost area but propagates to the surface, resulting in an increase in the seasonal amplitude of surface air temperature of >1K in the Arctic. The soil-aquifer water and heat fluxes both slightly decrease interannual variability in soil moisture and in landsurface temperature, and decrease the soil moisture memory of the land surface on seasonal to annual timescales. The results of this experiment suggest that deepening the modeled land surface, compared to modeling only a shallower soil column with a no-flux bottom boundary condition, has limited impact on mean climate but does affect seasonality and interannual persistence.

Socio-economic vulnerability to climate change in the central mountainous region of eastern Mexico.

PubMed

Esperón-Rodríguez, Manuel; Bonifacio-Bautista, Martín; Barradas, Víctor L

2016-03-01

Climate change effects are expected to be more severe for some segments of society than others. In Mexico, climate variability associated with climate change has important socio-economic and environmental impacts. From the central mountainous region of eastern Veracruz, Mexico, we analyzed data of total annual precipitation and mean annual temperature from 26 meteorological stations (1922-2008) and from General Circulation Models. We developed climate change scenarios based on the observed trends with projections to 2025, 2050, 2075, and 2100, finding considerable local climate changes with reductions in precipitation of over 700 mm and increases in temperature of ~9°C for the year 2100. Deforested areas located at windward were considered more vulnerable, representing potential risk for natural environments, local communities, and the main crops cultivated (sugarcane, coffee, and corn). Socio-economic vulnerability is exacerbated in areas where temperature increases and precipitation decreases.

Climatic factors affecting quantity and quality grade of in vivo derived embryos of cattle.

PubMed

Chinchilla-Vargas, Josué; Jahnke, Marianna M; Dohlman, Tyler M; Rothschild, Max F; Gunn, Patrick J

2018-05-01

The present study investigated the effects of climatic variables on the quality grade and quantity of in vivo derived cattle embryos in the Midwestern United States. Climatic information included greatest and least daily temperature, average daily wind speed and average temperature-humidity index for each of the 765 records. The response variables included the number of ovarian structures, viable embryos, quality grade 1 embryos, quality grade 2 embryos, quality grade 3 embryos, freezable embryos (sum of quality grade 1 and quality grade 2 embryos), transferable embryos (sum of quality grade 1-3 embryos), degenerate embryos and unfertilized ova. Measures for variables among the breeds of donors and sires grouped by geographical origin were compared. A negative effect of greater temperatures during the early embryonic development stage tended (P < 0.10) to be associated with a decrease in the quality of embryos recovered. Interestingly, the greater the Temperature-Humidity Index (THI) during the early ovarian antral follicular development stage 40-45 days prior to ovulation was associated with a tendency for greater numbers of total number of freezable and transferable embryos recovered per uterine flushing (P < 0.10). Increased wind speed at the early antral follicular phase 40-45 days prior to ovulation was associated with an increase in the percentage of quality grade 1 embryos recovered (P < 0.05). Wind speed during the estrous synchronization period was also associated with a lesser number of embryos recovered (P < 0.05). This retrospective study confirms that climatic variables have significant effects on the in vivo production of cattle embryos and that wind speed should be considered in future analyses of factors affecting embryo quality. Copyright © 2018 Elsevier B.V. All rights reserved.

Influence of North Atlantic modes on European climate extremes

NASA Astrophysics Data System (ADS)

Proemmel, K.; Cubasch, U.

2017-12-01

It is well known that the North Atlantic strongly influences European climate. Only few studies exist that focus on its impact on climate extremes. We are interested in these extremes and the processes and mechanisms behind it. For the analysis of the North Atlantic Oscillation (NAO) we use simulations performed with the Max Planck Institute for Meteorology Earth System Model (MPI-ESM). The NAO has a strong impact especially on European winter and the changes in minimum temperature are even larger than in maximum temperature. The impact of the Atlantic Multi-decadal Variability (AMV) on climate extremes is analyzed in ECHAM6 simulations forced with AMV warm and AMV cold sea surface temperature patterns. We analyze different extreme indices and try to understand the processes.

Variance decomposition shows the importance of human-climate feedbacks in the Earth system

NASA Astrophysics Data System (ADS)

Calvin, K. V.; Bond-Lamberty, B. P.; Jones, A. D.; Shi, X.; Di Vittorio, A. V.; Thornton, P. E.

2017-12-01

The human and Earth systems are intricately linked: climate influences agricultural production, renewable energy potential, and water availability, for example, while anthropogenic emissions from industry and land use change alter temperature and precipitation. Such feedbacks have the potential to significantly alter future climate change. Current climate change projections contain significant uncertainties, however, and because Earth System Models do not generally include dynamic human (demography, economy, energy, water, land use) components, little is known about how climate feedbacks contribute to that uncertainty. Here we use variance decomposition of a novel coupled human-earth system model to show that the influence of human-climate feedbacks can be as large as 17% of the total variance in the near term for global mean temperature rise, and 11% in the long term for cropland area. The near-term contribution of energy and land use feedbacks to the climate on global mean temperature rise is as large as that from model internal variability, a factor typically considered in modeling studies. Conversely, the contribution of climate feedbacks to cropland extent, while non-negligible, is less than that from socioeconomics, policy, or model. Previous assessments have largely excluded these feedbacks, with the climate community focusing on uncertainty due to internal variability, scenario, and model and the integrated assessment community focusing on uncertainty due to socioeconomics, technology, policy, and model. Our results set the stage for a new generation of models and hypothesis testing to determine when and how bidirectional feedbacks between human and Earth systems should be considered in future assessments of climate change.

Probabilistic Climate Scenario Information for Risk Assessment

NASA Astrophysics Data System (ADS)

Dairaku, K.; Ueno, G.; Takayabu, I.

2014-12-01

Climate information and services for Impacts, Adaptation and Vulnerability (IAV) Assessments are of great concern. In order to develop probabilistic regional climate information that represents the uncertainty in climate scenario experiments in Japan, we compared the physics ensemble experiments using the 60km global atmospheric model of the Meteorological Research Institute (MRI-AGCM) with multi-model ensemble experiments with global atmospheric-ocean coupled models (CMIP3) of SRES A1b scenario experiments. The MRI-AGCM shows relatively good skills particularly in tropics for temperature and geopotential height. Variability in surface air temperature of physical ensemble experiments with MRI-AGCM was within the range of one standard deviation of the CMIP3 model in the Asia region. On the other hand, the variability of precipitation was relatively well represented compared with the variation of the CMIP3 models. Models which show the similar reproducibility in the present climate shows different future climate change. We couldn't find clear relationships between present climate and future climate change in temperature and precipitation. We develop a new method to produce probabilistic information of climate change scenarios by weighting model ensemble experiments based on a regression model (Krishnamurti et al., Science, 1999). The method can be easily applicable to other regions and other physical quantities, and also to downscale to finer-scale dependent on availability of observation dataset. The prototype of probabilistic information in Japan represents the quantified structural uncertainties of multi-model ensemble experiments of climate change scenarios. Acknowledgments: This study was supported by the SOUSEI Program, funded by Ministry of Education, Culture, Sports, Science and Technology, Government of Japan.

Temperature Anomalies from the AIRS Product in Giovanni for the Climate Community

NASA Technical Reports Server (NTRS)

Ding, Feng; Hearty, Thomas J.; Wei, Jennifer; Theobald, Michael; Vollmer, Bruce; Seiler, Edward; Meyer, David

2018-01-01

The Atmospheric Infrared Sounder (AIRS) mission began with the launch of Aqua in 2002. Over 15 years of AIRS products have been used by the climate research and application communities. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), in collaboration with NASA Sounder Team at JPL, provides processing, archiving, and distribution services for NASA sounders: the present Aqua AIRS mission and the succeeding Suomi National Polar-Orbiting Partnership (SNPP) Cross-track Infrared Sounder (CrIS) mission. We generated a Multi-year Monthly Mean and Anomaly product using 14 years of AIRS standard monthly product. The product includes Air Temperature at the Surface and Surface Skin Temperature, both in Ascending/Daytime and Descending/Nighttime mode. The temperature variables and their anomalies are deployed to Giovanni, a Web-based application developed by the GES DISC. Giovanni provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data without having to download the data. It is also a powerful tool that stakeholders can use for decision support in planning and preparing for increased climate variability. In this presentation, we demonstrate the functions in Giovanni with use cases employing AIRS Multi-year Monthly Mean and Anomaly variables.

Qualitatively Assessing Randomness in SVD Results

NASA Astrophysics Data System (ADS)

Lamb, K. W.; Miller, W. P.; Kalra, A.; Anderson, S.; Rodriguez, A.

2012-12-01

Singular Value Decomposition (SVD) is a powerful tool for identifying regions of significant co-variability between two spatially distributed datasets. SVD has been widely used in atmospheric research to define relationships between sea surface temperatures, geopotential height, wind, precipitation and streamflow data for myriad regions across the globe. A typical application for SVD is to identify leading climate drivers (as observed in the wind or pressure data) for a particular hydrologic response variable such as precipitation, streamflow, or soil moisture. One can also investigate the lagged relationship between a climate variable and the hydrologic response variable using SVD. When performing these studies it is important to limit the spatial bounds of the climate variable to reduce the chance of random co-variance relationships being identified. On the other hand, a climate region that is too small may ignore climate signals which have more than a statistical relationship to a hydrologic response variable. The proposed research seeks to identify a qualitative method of identifying random co-variability relationships between two data sets. The research identifies the heterogeneous correlation maps from several past results and compares these results with correlation maps produced using purely random and quasi-random climate data. The comparison identifies a methodology to determine if a particular region on a correlation map may be explained by a physical mechanism or is simply statistical chance.

Stream temperature variability: why it matters to salmon

Treesearch

E. Ashley Steel; Brian Beckman; Marie Oliver

2014-01-01

Salmon evolved in natural river systems, where temperatures fluctuate daily, weekly, seasonally, and all along a stream’s path—from the mountains to the sea. Climate change and human activities alter this natural variability. Dams, for example, tend to reduce thermal fluctuations.Currently, scientists gauge habitat suitability for aquatic species by...

Beyond the mean: the role of variability in predicting ecological effects of stream temperature on salmon

Treesearch

E. Ashley Steel; Abby Tillotson; Donald A. Larson; Aimee H. Fullerton; Keith P. Denton; Brian R. Beckman

2012-01-01

Alterations in variance of riverine thermal regimes have been observed and are predicted with climate change and human development. We tested whether changes in daily or seasonal thermal variability, aside from changes in mean temperature, could have biological consequences by exposing Chinook salmon (Oncorhynchus tshawytscha) eggs to eight...

Model-based assessment of the role of human-induced climate change in the 2005 Caribbean coral bleaching event.

PubMed

Donner, Simon D; Knutson, Thomas R; Oppenheimer, Michael

2007-03-27

Episodes of mass coral bleaching around the world in recent decades have been attributed to periods of anomalously warm ocean temperatures. In 2005, the sea surface temperature (SST) anomaly in the tropical North Atlantic that may have contributed to the strong hurricane season caused widespread coral bleaching in the Eastern Caribbean. Here, we use two global climate models to evaluate the contribution of natural climate variability and anthropogenic forcing to the thermal stress that caused the 2005 coral bleaching event. Historical temperature data and simulations for the 1870-2000 period show that the observed warming in the region is unlikely to be due to unforced climate variability alone. Simulation of background climate variability suggests that anthropogenic warming may have increased the probability of occurrence of significant thermal stress events for corals in this region by an order of magnitude. Under scenarios of future greenhouse gas emissions, mass coral bleaching in the Eastern Caribbean may become a biannual event in 20-30 years. However, if corals and their symbionts can adapt by 1-1.5 degrees C, such mass bleaching events may not begin to recur at potentially harmful intervals until the latter half of the century. The delay could enable more time to alter the path of greenhouse gas emissions, although long-term "committed warming" even after stabilization of atmospheric CO(2) levels may still represent an additional long-term threat to corals.

The contribution of natural variability to GCM bias: Can we effectively bias-correct climate projections?

NASA Astrophysics Data System (ADS)

McAfee, S. A.; DeLaFrance, A.

2017-12-01

Investigating the impacts of climate change often entails using projections from inherently imperfect general circulation models (GCMs) to drive models that simulate biophysical or societal systems in great detail. Error or bias in the GCM output is often assessed in relation to observations, and the projections are adjusted so that the output from impacts models can be compared to historical or observed conditions. Uncertainty in the projections is typically accommodated by running more than one future climate trajectory to account for differing emissions scenarios, model simulations, and natural variability. The current methods for dealing with error and uncertainty treat them as separate problems. In places where observed and/or simulated natural variability is large, however, it may not be possible to identify a consistent degree of bias in mean climate, blurring the lines between model error and projection uncertainty. Here we demonstrate substantial instability in mean monthly temperature bias across a suite of GCMs used in CMIP5. This instability is greatest in the highest latitudes during the cool season, where shifts from average temperatures below to above freezing could have profound impacts. In models with the greatest degree of bias instability, the timing of regional shifts from below to above average normal temperatures in a single climate projection can vary by about three decades, depending solely on the degree of bias assessed. This suggests that current bias correction methods based on comparison to 20- or 30-year normals may be inappropriate, particularly in the polar regions.

New paleoclimatic database for the Iberian Peninsula since AD 1700 inferred from tree-ring records and documentary evidence: advances in temperature and drought variability reconstructions

NASA Astrophysics Data System (ADS)

Tejedor, Ernesto; Ángel Saz, Miguel; de Luis, Martín; Esper, Jan; Barriendos, Mariano; Serrano-Notivoli, Roberto; Novak, Klemen; Longares, Luis Alberto; Martínez-del Castillo, Edurne; María Cuadrat, José

2017-04-01

A substantial increase of surface air temperatures in the upcoming decades, particularly significant in the Mediterranean basin, has been reported by the IPCC (IPCC, 2013). It is therefore particularly important to study past climate extremes and variability in this region, which will in turn support the accuracy of future climate scenarios. Yet, our knowledge of past climate variability and trends is limited by the shortage of instrumental data prior to the twentieth century, which prompts to the need of discovering new sources with which to reconstruct past climate. We here present a new paleoclimatic database for the northeast of the Iberian Peninsula based on tree-ring records, documentary evidence and instrumental data. The network includes 774 tree-ring, earlywood and latewood width series from Pinus uncinata, Pinus sylvestris and Pinus nigra trees in the Pyrenees and Iberian Range reaching back to AD 1510. Three reconstructions are developed using these samples; an annual drought reconstruction since AD 1694, a summer drought reconstruction since AD 1734, and a maximum temperature reconstruction since AD 1604. Additionally, the documentary records from 16 locations in the Ebro Valley are examined focusing on climate-related 'rogations'. We differentiated three types of rogations, considering the importance of religious acts, to identify the severity of drought and pluvial events. Finally, an attempt to explore the links between documentary and tree-ring based reconstructions is presented.

Comment on: "Synchronizing biological cycles as key to survival under a scenario of global change: The Common quail (Coturnix coturnix) strategy" by Nadal, J., Ponz, C., Margalida, A.

PubMed

Rodríguez-Teijeiro, José Domingo; García-Galea, Eduardo; Sardà-Palomera, Francesc; Jiménez-Blasco, Irene; Puigcerver, Manel

2018-04-03

Nadal et al. (2018) recently reported on changes in the phenology of the Common quail (Coturnix coturnix) in seven cloudy regions of Spain in relation to climate change. The authors used a long-term ringing database (1961-2014) and calculated the mean date for three biological stages: arrival at the breeding areas, stay and autumn departure. They observed that some of these phenological variables were associated with the climate variables of temperature and rainfall (Figs. 4 and 6 of their article). They also analysed the yearly variation in temperature and rainfall over the last 86years, reporting an increase in temperature and a decrease in rainfall (Figs. 3 and 5 of their article). Based on these results, the authors suggested that the Common quail phenology has varied as a response to climate change in Spain, thus concluding that "quail movements and breeding attempts are eco-synchronized sequentially in cloudy regions. Our results suggest that quails attempt to overcome the negative impacts of climate change and agricultural intensification by searching for alternative high-quality habitats". We disagree with two methodological aspects of the article by Nadal et al. (2018): (1) the estimation of the mean date of arrival, stay and departure in the different regions studied; and (2) the analyses carried out to correlate the phenology of the species with the changes in climate variables. Copyright © 2018 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Kikoyo, Duncan A.; Nobert, Joel

2016-06-01

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

Nitrogen deposition outweighs climatic variability in driving annual growth rate of canopy beech trees: Evidence from long-term growth reconstruction across a geographic gradient.

PubMed

Gentilesca, Tiziana; Rita, Angelo; Brunetti, Michele; Giammarchi, Francesco; Leonardi, Stefano; Magnani, Federico; van Noije, Twan; Tonon, Giustino; Borghetti, Marco

2018-07-01

In this study, we investigated the role of climatic variability and atmospheric nitrogen deposition in driving long-term tree growth in canopy beech trees along a geographic gradient in the montane belt of the Italian peninsula, from the Alps to the southern Apennines. We sampled dominant trees at different developmental stages (from young to mature tree cohorts, with tree ages spanning from 35 to 160 years) and used stem analysis to infer historic reconstruction of tree volume and dominant height. Annual growth volume (G V ) and height (G H ) variability were related to annual variability in model simulated atmospheric nitrogen deposition and site-specific climatic variables, (i.e. mean annual temperature, total annual precipitation, mean growing period temperature, total growing period precipitation, and standard precipitation evapotranspiration index) and atmospheric CO 2 concentration, including tree cambial age among growth predictors. Generalized additive models (GAM), linear mixed-effects models (LMM), and Bayesian regression models (BRM) were independently employed to assess explanatory variables. The main results from our study were as follows: (i) tree age was the main explanatory variable for long-term growth variability; (ii) GAM, LMM, and BRM results consistently indicated climatic variables and CO 2 effects on G V and G H were weak, therefore evidence of recent climatic variability influence on beech annual growth rates was limited in the montane belt of the Italian peninsula; (iii) instead, significant positive nitrogen deposition (N dep ) effects were repeatedly observed in G V and G H ; the positive effects of N dep on canopy height growth rates, which tended to level off at N dep values greater than approximately 1.0 g m -2  y -1 , were interpreted as positive impacts on forest stand above-ground net productivity at the selected study sites. © 2018 John Wiley & Sons Ltd.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Development, malaria and adaptation to climate change: a case study from India.

PubMed

Garg, Amit; Dhiman, R C; Bhattacharya, Sumana; Shukla, P R

2009-05-01

India has reasons to be concerned about climate change. Over 650 million people depend on climate-sensitive sectors, such as rain-fed agriculture and forestry, for livelihood and over 973 million people are exposed to vector borne malarial parasites. Projection of climatic factors indicates a wider exposure to malaria for the Indian population in the future. If precautionary measures are not taken and development processes are not managed properly some developmental activities, such as hydro-electric dams and irrigation canal systems, may also exacerbate breeding grounds for malaria. This article integrates climate change and developmental variables in articulating a framework for integrated impact assessment and adaptation responses, with malaria incidence in India as a case study. The climate change variables include temperature, rainfall, humidity, extreme events, and other secondary variables. Development variables are income levels, institutional mechanisms to implement preventive measures, infrastructure development that could promote malarial breeding grounds, and other policies. The case study indicates that sustainable development variables may sometimes reduce the adverse impacts on the system due to climate change alone, while it may sometimes also exacerbate these impacts if the development variables are not managed well and therefore they produce a negative impact on the system. The study concludes that well crafted and well managed developmental policies could result in enhanced resilience of communities and systems, and lower health impacts due to climate change.

Development, Malaria and Adaptation to Climate Change: A Case Study from India

NASA Astrophysics Data System (ADS)

Garg, Amit; Dhiman, R. C.; Bhattacharya, Sumana; Shukla, P. R.

2009-05-01

India has reasons to be concerned about climate change. Over 650 million people depend on climate-sensitive sectors, such as rain-fed agriculture and forestry, for livelihood and over 973 million people are exposed to vector borne malarial parasites. Projection of climatic factors indicates a wider exposure to malaria for the Indian population in the future. If precautionary measures are not taken and development processes are not managed properly some developmental activities, such as hydro-electric dams and irrigation canal systems, may also exacerbate breeding grounds for malaria. This article integrates climate change and developmental variables in articulating a framework for integrated impact assessment and adaptation responses, with malaria incidence in India as a case study. The climate change variables include temperature, rainfall, humidity, extreme events, and other secondary variables. Development variables are income levels, institutional mechanisms to implement preventive measures, infrastructure development that could promote malarial breeding grounds, and other policies. The case study indicates that sustainable development variables may sometimes reduce the adverse impacts on the system due to climate change alone, while it may sometimes also exacerbate these impacts if the development variables are not managed well and therefore they produce a negative impact on the system. The study concludes that well crafted and well managed developmental policies could result in enhanced resilience of communities and systems, and lower health impacts due to climate change.

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

PubMed

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

2012-05-01

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

A two-fold increase of carbon cycle sensitivity to tropical temperature variations.

PubMed

Wang, Xuhui; Piao, Shilong; Ciais, Philippe; Friedlingstein, Pierre; Myneni, Ranga B; Cox, Peter; Heimann, Martin; Miller, John; Peng, Shushi; Wang, Tao; Yang, Hui; Chen, Anping

2014-02-13

Earth system models project that the tropical land carbon sink will decrease in size in response to an increase in warming and drought during this century, probably causing a positive climate feedback. But available data are too limited at present to test the predicted changes in the tropical carbon balance in response to climate change. Long-term atmospheric carbon dioxide data provide a global record that integrates the interannual variability of the global carbon balance. Multiple lines of evidence demonstrate that most of this variability originates in the terrestrial biosphere. In particular, the year-to-year variations in the atmospheric carbon dioxide growth rate (CGR) are thought to be the result of fluctuations in the carbon fluxes of tropical land areas. Recently, the response of CGR to tropical climate interannual variability was used to put a constraint on the sensitivity of tropical land carbon to climate change. Here we use the long-term CGR record from Mauna Loa and the South Pole to show that the sensitivity of CGR to tropical temperature interannual variability has increased by a factor of 1.9 ± 0.3 in the past five decades. We find that this sensitivity was greater when tropical land regions experienced drier conditions. This suggests that the sensitivity of CGR to interannual temperature variations is regulated by moisture conditions, even though the direct correlation between CGR and tropical precipitation is weak. We also find that present terrestrial carbon cycle models do not capture the observed enhancement in CGR sensitivity in the past five decades. More realistic model predictions of future carbon cycle and climate feedbacks require a better understanding of the processes driving the response of tropical ecosystems to drought and warming.

THE INFLUENCE OF VARIABLE TEMPERATURE AND HUMIDITY ON THE PREDATION EFFICIENCY OF P. PERSIMILIS, N. CALIFORNICUS AND N. FALLACIS.

PubMed

Audenaert, J; Vangansbeke, D; Verhoeven, R; De Clercq, P; Tirry, L; Gobin, B

2014-01-01

Predatory mites like Phytoseiulus persimilis Athias-Henriot, Neoseiulus californicus McGregor and N. fallacis (Garman) (Acari: Phytoseiidae) are essential in sustainable control strategies of the two-spotted spider mite Tetranychus urticae Koch (Acari: Tetranychidae) in warm greenhouse cultures to complement imited available pesticides and to tackle emerging resistance. However, in response to high energy prices, greenhouse plant breeders have recently changed their greenhouse steering strategies, allowing more variation in temperature and humidity. The impact of these variations on biological control agents is poorly understood. Therefore, we constructed functional response models to demonstrate the impact of realistic climate variations on predation efficiency. First, two temperature regimes were compared at constant humidity (70%) and photoperiod (16L:8D): DIF0 (constant temperature) and DIF15 (variable temperature with day-night difference of 15°C). At mean temperatures of 25°C, DIF15 had a negative influence on the predation efficiency of P. persimilis and N. californicus, as compared to DIF0. At low mean temperatures of 15°C, however, DIF15 showed a higher predation efficiency for P. persimilis and N. californicus. For N. fallacis no difference was observed at both 15°C and 25°C. Secondly, two humidity regimes were compared, at a mean temperature of 25°C (DIFO) and constant photoperiod (16L:8D): RHCTE (constant 70% humidity) and RHALT (alternating 40% L:70%D humidity). For P. persimilis and N. fallacis RHCTE resulted in a higher predation efficiency than RHALT, for N. californicus this effect was opposite. This shows that N. californicus is more adapted to dry climates as compared to the other predatory mites. We conclude that variable greenhouse climates clearly affect predation efficiency of P. persimilis, N. californicus and N. fallacis. To obtain optimal control efficiency, the choice of predatory mites (including dose and application frequency) should be adapted to the actual greenhouse climate.

Wind and rain are the primary climate factors driving changing phenology of an aerial insectivore.

PubMed

Irons, Rachel D; Harding Scurr, April; Rose, Alexandra P; Hagelin, Julie C; Blake, Tricia; Doak, Daniel F

2017-04-26

While the ecological effects of climate change have been widely observed, most efforts to document these impacts in terrestrial systems have concentrated on the impacts of temperature. We used tree swallow ( Tachycineta bicolor ) nest observations from two widely separated sites in central Alaska to examine the aspects of climate affecting breeding phenology at the northern extent of this species' range. We found that two measures of breeding phenology, annual lay and hatch dates, are more strongly predicted by windiness and precipitation than by temperature. At our longest-monitored site, breeding phenology has advanced at nearly twice the rate seen in more southern populations, and these changes correspond to long-term declines in windiness. Overall, adverse spring climate conditions known to negatively impact foraging success of swallows (wet, windy weather) appear to influence breeding phenology more than variation in temperature. Separate analyses show that short windy periods significantly delay initiation of individual clutches within years. While past reviews have emphasized that increasing variability in climate conditions may create physiological and ecological challenges for natural populations, we find that long-term reductions in inclement weather corresponded to earlier reproduction in one of our study populations. To better predict climate change impacts, ecologists need to more carefully test effects of multiple climate variables, including some, like windiness, that may be of paramount importance to some species, but have rarely been considered as strong drivers of ecological responses to climate alteration. © 2017 The Author(s).

Wind and rain are the primary climate factors driving changing phenology of an aerial insectivore

PubMed Central

Irons, Rachel D.; Harding Scurr, April; Rose, Alexandra P.; Hagelin, Julie C.; Blake, Tricia

2017-01-01

While the ecological effects of climate change have been widely observed, most efforts to document these impacts in terrestrial systems have concentrated on the impacts of temperature. We used tree swallow (Tachycineta bicolor) nest observations from two widely separated sites in central Alaska to examine the aspects of climate affecting breeding phenology at the northern extent of this species' range. We found that two measures of breeding phenology, annual lay and hatch dates, are more strongly predicted by windiness and precipitation than by temperature. At our longest-monitored site, breeding phenology has advanced at nearly twice the rate seen in more southern populations, and these changes correspond to long-term declines in windiness. Overall, adverse spring climate conditions known to negatively impact foraging success of swallows (wet, windy weather) appear to influence breeding phenology more than variation in temperature. Separate analyses show that short windy periods significantly delay initiation of individual clutches within years. While past reviews have emphasized that increasing variability in climate conditions may create physiological and ecological challenges for natural populations, we find that long-term reductions in inclement weather corresponded to earlier reproduction in one of our study populations. To better predict climate change impacts, ecologists need to more carefully test effects of multiple climate variables, including some, like windiness, that may be of paramount importance to some species, but have rarely been considered as strong drivers of ecological responses to climate alteration. PMID:28446701

Development of a Climate Prediction Market

NASA Astrophysics Data System (ADS)

Roulston, M. S.

2017-12-01

Winton, a global investment firm, is planning to establish a prediction market for climate. This prediction market will allow participants to place bets on global climate up to several decades in the future. Winton is pursuing this endeavour as part of its philanthropy that funds scientific research and the communication of scientific ideas. The Winton Climate Prediction Market will be based in the U.K. It will be structured as an online gambling site subject to the regulation of the Gambling Commission. Unlike existing betting sites, the Climate Prediction Market will be subsidized: a central market maker will inject money into the market. This is in contrast to traditional bookmakers or betting exchanges who set odds in their favour or charge commissions to make a profit. The philosophy of a subsidized prediction market is that the party seeking information should fund the market, rather than the participants who provide the information. The initial market will allow bets to be placed on the atmospheric concentration of carbon dioxide and the global mean temperature anomaly. It will thus produce implied forecasts of carbon dioxide concentration as well as global temperatures. If the initial market is successful, additional markets could be added which target other climate variables, such as regional temperatures or sea-level rise. These markets could be sponsored by organizations that are interested in predictions of the specific climate variables. An online platform for the Climate Prediction Market has been developed and has been tested internally at Winton.

Regional Climate Variability Under Model Simulations of Solar Geoengineering

NASA Astrophysics Data System (ADS)

Dagon, Katherine; Schrag, Daniel P.

2017-11-01

Solar geoengineering has been shown in modeling studies to successfully mitigate global mean surface temperature changes from greenhouse warming. Changes in land surface hydrology are complicated by the direct effect of carbon dioxide (CO2) on vegetation, which alters the flux of water from the land surface to the atmosphere. Here we investigate changes in boreal summer climate variability under solar geoengineering using multiple ensembles of model simulations. We find that spatially uniform solar geoengineering creates a strong meridional gradient in the Northern Hemisphere temperature response, with less consistent patterns in precipitation, evapotranspiration, and soil moisture. Using regional summertime temperature and precipitation results across 31-member ensembles, we show a decrease in the frequency of heat waves and consecutive dry days under solar geoengineering relative to a high-CO2 world. However in some regions solar geoengineering of this amount does not completely reduce summer heat extremes relative to present day climate. In western Russia and Siberia, an increase in heat waves is connected to a decrease in surface soil moisture that favors persistent high temperatures. Heat waves decrease in the central United States and the Sahel, while the hydrologic response increases terrestrial water storage. Regional changes in soil moisture exhibit trends over time as the model adjusts to solar geoengineering, particularly in Siberia and the Sahel, leading to robust shifts in climate variance. These results suggest potential benefits and complications of large-scale uniform climate intervention schemes.

Assessment of Air Temperature Trends in the Source Region of Yellow River and Its Sub-Basins, China

NASA Astrophysics Data System (ADS)

Iqbal, Mudassar; Wen, Jun; Wang, Xin; Lan, Yongchao; Tian, Hui; Anjum, Muhammad Naveed; Adnan, Muhammad

2018-02-01

Changes in climatic variables at the sub-basins scale (having different features of land cover) are crucial for planning, development and designing of water resources infrastructure in the context of climate change. Accordingly, to explore the features of climate changes in sub-basins of the Source Region of Yellow River (SRYR), absolute changes and trends of temperature variables, maximum temperature (Tmax), minimum temperature (Tmin), mean temperature (Tavg) and diurnal temperature range (DTR), were analyzed annually and seasonally by using daily observed air temperature dataset from 1965 to 2014. Results showed that annual Tmax, Tmin and Tavg for the SRYR were experiencing warming trends respectively at the rate of 0.28, 0.36 and 0.31°C (10 yr)-1. In comparison with the 1st period (1965-1989), more absolute changes and trends towards increasing were observed during the 2nd period (1990-2014). Apart from Tangnaihai (a low altitude sub-basin), these increasing trends and changes seemed more significant in other basins with highest magnitude during winter. Among sub-basins the increasing trends were more dominant in Huangheyan compared to other sub-basins. The largest increase magnitude of Tmin, 1.24 and 1.18°C (10 yr)-1, occurred in high altitude sub-basins Jimai and Huangheyan, respectively, while the smallest increase magnitude of 0.23°C (10 yr)-1 occurred in a low altitude sub-basin Tangnaihai. The high elevation difference in Tangnaihai probably was the main reason for the less increase in the magnitude of Tmin. In the last decade, smaller magnitude of trend for all temperature variables signified the signal of cooling in the region. Overall, changes of temperature variables had significant spatial and seasonal variations. It implies that seasonal variations of runoff might be greater or different for each sub-basin.

Drivers and uncertainties of forecasted range shifts for warm-water fishes under climate and land cover change

USGS Publications Warehouse

Bouska, Kristen; Whitledge, Gregory W.; Lant, Christopher; Schoof, Justin

2018-01-01

Land cover is an important determinant of aquatic habitat and is projected to shift with climate changes, yet climate-driven land cover changes are rarely factored into climate assessments. To quantify impacts and uncertainty of coupled climate and land cover change on warm-water fish species’ distributions, we used an ensemble model approach to project distributions of 14 species. For each species, current range projections were compared to 27 scenario-based projections and aggregated to visualize uncertainty. Multiple regression and model selection techniques were used to identify drivers of range change. Novel, or no-analogue, climates were assessed to evaluate transferability of models. Changes in total probability of occurrence ranged widely across species, from a 63% increase to a 65% decrease. Distributional gains and losses were largely driven by temperature and flow variables and underscore the importance of habitat heterogeneity and connectivity to facilitate adaptation to changing conditions. Finally, novel climate conditions were driven by mean annual maximum temperature, which stresses the importance of understanding the role of temperature on fish physiology and the role of temperature-mitigating management practices.

Estimation of Land Surface Temperature for the Quantitative Analysis of Land Cover of Lower Areas of Sindh to Assess the Impacts of Climate Variability

NASA Astrophysics Data System (ADS)

Qaisar, Maha

2016-07-01

Due to the present land use practices and climate variability, drastic shifts in regional climate and land covers are easily seen and their future reduction and gain are too well predicted. Therefore, there is an increasing need for data on land-cover changes at narrow and broad spatial scales. In this study, a remote sensing-based technique for land-cover-change analysis is applied to the lower Sindh areas for the last decade. Landsat satellite products were analyzed on an alternate yearly basis, from 1990 to 2016. Then Land-cover-change magnitudes were measured and mapped for alternate years. Land Surface Temperature (LST) is one of the critical elements in the natural phenomena of surface energy and water balance at local and global extent. However, LST was computed by using Landsat thermal bands via brightness temperature and a vegetation index. Normalized difference vegetation index (NDVI) was interpreted and maps were achieved. LST reflected NDVI patterns with complexity of vegetation patterns. Along with this, Object Based Image Analysis (OBIA) was done for classifying 5 major classes of water, vegetation, urban, marshy lands and barren lands with significant map layouts. Pakistan Meteorological Department provided the climate data in which rainfall, temperature and air temperature are included. Once the LST and OBIA are performed, overlay analysis was done to correlate the results of LST with OBIA and LST with meteorological data to ascertain the changes in land covers due to increasing centigrade of LST. However, satellite derived LST was also correlated with climate data for environmental analysis and to estimate Land Surface Temperature for assessing the inverse impacts of climate variability. This study's results demonstrate the land-cover changes in Lower Areas of Sindh including the Indus Delta mostly involve variations in land-cover conditions due to inter-annual climatic variability and temporary shifts in seasonality. However it is too concluded that transitory alteration of the biophysical characteristics of the surface driven by variations in rainfall is the prevailing progression. Moreover, future work will focus on finer-scale analysis and validations of patterns of changes due to rapid urbanization and population explosion in poverty stricken areas of Sindh which are posing an adverse impact on the land utilization and in turn increasing the land surface temperature and ultimately more stress on the low lying areas of Sindh i.e. Indus Delta will be losing its productivity and capacity to bear biodiversity whether the fauna or flora. Hence, this regional scale problem will become a global concern. Therefore, it is needed to stop the menace in its starting phase to mitigate the problem and to bring minds on this horrendous situation.